http://wiki.metabolomicssociety.org/api.php?action=feedcontributions&user=EvelinaCharidemou&feedformat=atomMetabolomics Society Wiki - User contributions [en]2024-03-28T09:32:36ZUser contributionsMediaWiki 1.28.0http://wiki.metabolomicssociety.org/index.php?title=Michael_Witting&diff=1587Michael Witting2021-11-06T16:33:21Z<p>EvelinaCharidemou: /* Expert Opinion */</p>
<hr />
<div>[[Image: Michael Witting.jpg|thumb| Michael Witting ]]<br />
<br />
==Short Biography==<br />
<br />
''' Biography''' <br />
<br />
Dr. Michael Witting studied Applied Chemistry with a functional direction into biochemistry at the Georg-Simon-Ohm University of Applied Science, Nuremberg, Germany and obtained his PhD in 2013 from the Technical University of Munich. He is a current member of the Metabolomics Society Board of Directors and since 1st of January he is heading the metabolomics section of the Metabolomics and Proteomics Core at the Helmholtz Zentrum München. His main research interests are LC-MS based metabolomics method development and application, as well as metabolite identification improvement by retention time prediction.<br />
<br />
==Expert Opinion==<br />
===Question 1===<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations?'''<br />
<br />
I have started with metabolomics in 2009 when starting my PhD in the group of Philippe Schmitt-Kopplin at the Helmholtz Zentrum München. My first project funded by the ERA-Net project pathomics was to study host-pathogen interactions of the opportunistic human pathogen Pseudomonas aeruginosa. I applied direct infusion FT-ICR-MS as well as UPLC-UHR-ToF-MS based metabolomics and lipidomics to study the metabolic response of HeLa cells or Caenorhabditis elegans [1]. This was also the time, when my interest in this model organism started, realizing that C. elegans and metabolomics/lipidomics is a fruitful combination.<br />
<br />
===Question 2===<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
I have currently two main projects running. The first one is a French-German collaboration with the groups of Fabien Jourdan and Reza Salek in France as well as the group of Steffen Neumann in Germany. We are aiming to integrate different networks, such as mass-difference, correlation, spectral similarity networks with genome-scale metabolic reconstructions and other types of networks in a multilayer network to derive a better understanding of the data as well as helping to identify new metabolites and improve genome-scale metabolic models. Within this fantastic group my PhD student Liesa Salzer and I are working on C. elegans metabolomics and lipidomics data and the annotation of metabolites present in the nematode [2]. We are using different spectral libraries as well as in-silico tools to annotate the data as good as possible and feed it into our larger framework of the project. This is very interesting since it will enable us on the one side to define in more detail the metabolome and lipidome of C. elegans and on the other side requires to develop new scripts and pipelines for data handling. Furthermore, we hope to be able to identify several new metabolites and close some gaps on metabolic pathways. We are really looking forward to presenting our first results in the coming months.<br />
The second project is a collaborative project with the group of Sebastian Böcker aiming to develop reproducible and transferable retention time prediction. Chromatographic separation is important in metabolite identification since it allows the separation of isomers and represents an orthogonal information to MS and MS/MS giving hints about the polarity of a metabolite. However, it is often only used at a late stage of metabolite identification, typically when comparing against a reference standard. Retention time prediction enables to utilize this information in an early stage, potentially reducing the number of false positive annotations [3]. However, sharing of RTs is not as widespread as sharing of MS2 spectra. So, we first needed to identify good training data for our project. My PhD student Eva-Maria Harrieder did a great job identifying data sets and standardized them as well as curating chromatographic metadata. Throughout the project we realized that especially this metadata is crucial. In contrast to previous retention time prediction approaches, which predict RTs for single chromatographic systems, we aim to develop a transferable system embracing the power of machine and deep learning. The first results are looking very promising.<br />
Beside these two, many other projects are currently on my table. Since 1st of January 2021 I’m heading the metabolomics part of the newly fused Metabolomics and Proteomics Core facility. After this fusion we are working on new targeted assays and a major project is the measurement of a large epidemiological study with >4000 samples. Such large-scale experiments are really the future of metabolomics (not only in clinical or epidemiological settings, but also basic science) and further work towards standardization, QC, reporting and data integration are required, but the community is on a good way here.<br />
<br />
===Question 3===<br />
<br />
''' 3. How do you think the understanding of C. elegans and their metabolic interactions with beneficial microbes can be applied into health and disease?? '''<br />
<br />
C. elegans offers several advantages, not only to study the beneficial effects of microbes. The short generation cycle as well as the genetic tractability makes it possible to grow sufficient amounts of isogenic animals in a short time. Since the worm feeds on live bacteria, virtually all bacteria that can be grown under similar conditions can be used as food for C. elegans. However, in recent years there was shift from seeing bacteria only as food towards a real microbiome and host-microbe interactions. Escherichia coli is normally used as a food source for the nematode, since it is easy to cultivate and was readily available at the time of introduction of C. elegans as model organism by Sidney Brenner. However, this is not the natural food of C. elegans nor its natural microbiome. A group around Hinrich Schulenburg and Buck Samuel recently published the CeMBio resource, a collection of culturable microbes from the natural C. elegans microbiome [4]. With this we have now a reproducible system to study host-microbe interactions, also on a metabolic level. The group of Christoph Kaleta for example added genome-scale metabolic models for the bacteria to the toolset.<br />
Based on the available system we can now start to study interaction in more detail, also following genetic components on both sides as well as metabolic interactions etc. This system is still not comparable to e.g. the interaction of humans with their microbiome, but we can derive some basic, conserved principles. The fast growth also helps to perform several experiments in short time, potentially in future also in high-throughput screens (genetic or drug screens), which might include metabolomics as well. Results can be then transferred to e.g. mouse models as next step.<br />
<br />
===Question 4===<br />
<br />
''' 4. What are the main challenges when developing methods for metabolomic analysis from limited sample amount? '''<br />
<br />
The challenges are twofold. First, highly sensitive analytical approaches are required to enable the analysis of low amounts of material. In contrast to genomics and transcriptomics we are not able to amplify our molecules of interest. I think the MS field is rapidly developing in this direction and recent instrument releases or publications such as the SpaceM approach from Theodore Alexandrov’s group are great examples [5]. However, depending on the amount of material at your hands you might have to make sacrifices. While normally, one would combine e.g. RP and HILIC based methods to increase the coverage of metabolites, you might be restricted to a single method or even injection. The goal should be to maximize the information you can obtain, e.g. using for example data-independent acquisition to cover “all” detected metabolites with MS2 information. Likewise, optimizing methods further towards better metabolome coverage. We have developed a Tandem-LC method covering HILIC and RP from a single injection. The goal is to further miniaturize this to be compatible with a limited sample amount. Second, with a decreasing amount of sample, even going down to single cells, the demand on sample preparation increases. One might face very low volumes for pipetting, extraction and injection. I believe that novel automated liquid handling solutions can help a lot here. But also, with decreasing amount of sample might be also related to an increasing number of samples. C. elegans is a good example here. Typically, we process 500-5000 worms (each with ~1000 cells) for one biological replicate. The metabolic individuality of the worms is averaged out by extracting them all together. If you lower the amount of worms per sample the more the individuality comes into effect, theoretically going down to single worms. While it is interesting to study this level of detail in metabolism, one has to keep in mind that you would need a larger number of replicates to compensate for this to obtain meaningful data (a problem, which is well-known from studies with “free-living-humans”, e.g. epidemiological scale studies). One need to counter-balance these effects and perform vigorous study design and keep in mind that we are often still measuring in a sequential manner in contrast to genomics and transcriptomics, where a lot of measurements can be parallelized. In the end we are probably not talking about 5 cells of type A vs 5 cells of type B, but 5000 vs 5000 or even worse. That means a lot of measurement time and I even didn’t start on the data analysis and interpretation…<br />
<br />
===Question 5===<br />
<br />
''' 5. You are the deputy head of metabolomics and proteomics core of the Helmholtz Zentrum München. What do you think contributed significantly to your career path in becoming a deputy leader? '''<br />
<br />
There are many important things. I believe that good science will always find a way. The academic system is full of rejections and setbacks, but the key is to never give up and believe in the work you are doing. However, there are a few things that can turn the odds in your favor. I was lucky to participate in the Postdoctoral Fellowship Program of the HMGU, which gave me the chance to participate in many different courses on leadership, management, etc. as well as having a professional coaching. Especially the last one helped me a lot. During the process of coaching, it became clear to me that science has a lot of parallels to sales. Especially in the age of social media it makes a difference if you correctly “advertise” your work or not. The other important aspect is communication. Improving on my communication skills helped me a lot to better lead teams of scientist and to focus on common goals. I always try to remember myself that “the biggest misunderstanding in communication is that it happened”. Have an open ear, listen to others, ask questions and engage with people. Also think outside of the box, my personal coach never heard about metabolomics and that was great, because we never talked about science, but everything around it.<br />
From the scientific point of view, I was always happy and grateful that I had enough freedom to follow my own ideas. Even if you fail, you learn. And sometimes you learn more from your failures than your successes. And one last thing: All great minds, irrespective of the field, started as a beginner. Don’t be afraid to ask them, engage with them. You can learn a lot…<br />
<br />
<br />
===References===<br />
<br />
<br />
1. Witting, M., et al., DI-ICR-FT-MS-based high-throughput deep metabotyping: a case study of the Caenorhabditis elegans–Pseudomonas aeruginosa infection model. Analytical and Bioanalytical Chemistry, 2015. 407(4): p. 1059-1073.<br />
<br />
2. Salzer, L. and M. Witting, Quo Vadis Caenorhabditis elegans Metabolomics—A Review of Current Methods and Applications to Explore Metabolism in the Nematode. Metabolites, 2021. 11(5): p. 284.<br />
<br />
3. Witting, M. and S. Böcker, Current status of retention time prediction in metabolite identification. Journal of Separation Science, 2020. 43(9-10): p. 1746-1754.<br />
<br />
4. Dirksen, P., et al., CeMbio - The <em>Caenorhabditis elegans</em> Microbiome Resource. G3: Genes|Genomes|Genetics, 2020. 10(9): p. 3025-3039.<br />
<br />
5. Rappez, L., et al., SpaceM reveals metabolic states of single cells. Nature Methods, 2021. 18(7): p. 799-805.<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Michael_Witting&diff=1586Michael Witting2021-10-11T17:51:48Z<p>EvelinaCharidemou: </p>
<hr />
<div>[[Image: Michael Witting.jpg|thumb| Michael Witting ]]<br />
<br />
==Short Biography==<br />
<br />
''' Biography''' <br />
<br />
Dr. Michael Witting studied Applied Chemistry with a functional direction into biochemistry at the Georg-Simon-Ohm University of Applied Science, Nuremberg, Germany and obtained his PhD in 2013 from the Technical University of Munich. He is a current member of the Metabolomics Society Board of Directors and since 1st of January he is heading the metabolomics section of the Metabolomics and Proteomics Core at the Helmholtz Zentrum München. His main research interests are LC-MS based metabolomics method development and application, as well as metabolite identification improvement by retention time prediction.<br />
<br />
==Expert Opinion==<br />
===Question 1===<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations?'''<br />
<br />
I have started with metabolomics in 2009 when starting my PhD in the group of Philippe Schmitt-Kopplin at the Helmholtz Zentrum München. My first project funded by the ERA-Net project pathomics was to study host-pathogen interactions of the opportunistic human pathogen Pseudomonas aeruginosa. I applied direct infusion FT-ICR-MS as well as UPLC-UHR-ToF-MS based metabolomics and lipidomics to study the metabolic response of HeLa cells or Caenorhabditis elegans [1]. This was also the time, when my interest in this model organism started, realizing that C. elegans and metabolomics/lipidomics is a fruitful combination.<br />
<br />
===Question 2===<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
I have currently two main projects running. The first one is a French-German collaboration with the groups of Fabien Jourdan and Reza Salek in France as well as the group of Steffen Neumann in Germany. We are aiming to integrate different networks, such as mass-difference, correlation, spectral similarity networks with genome-scale metabolic reconstructions and other types of networks in a multilayer network to derive a better understanding of the data as well as helping to identify new metabolites and improve genome-scale metabolic models. Within this fantastic group my PhD student Liesa Salzer and I are working on C. elegans metabolomics and lipidomics data and the annotation of metabolites present in the nematode [2]. We are using different spectral libraries as well as in-silico tools to annotate the data as good as possible and feed it into our larger framework of the project. This is very interesting since it will enable us on the one side to define in more detail the metabolome and lipidome of C. elegans and on the other side requires to develop new scripts and pipelines for data handling. Furthermore, we hope to be able to identify several new metabolites and close some gaps on metabolic pathways. We are really looking forward to presenting our first results in the coming months.<br />
The second project is a collaborative project with the group of Sebastian Böcker aiming to develop reproducible and transferable retention time prediction. Chromatographic separation is important in metabolite identification since it allows the separation of isomers and represents an orthogonal information to MS and MS/MS giving hints about the polarity of a metabolite. However, it is often only used at a late stage of metabolite identification, typically when comparing against a reference standard. Retention time prediction enables to utilize this information in an early stage, potentially reducing the number of false positive annotations [3]. However, sharing of RTs is not as widespread as sharing of MS2 spectra. So, we first needed to identify good training data for our project. My PhD student Eva-Maria Harrieder did a great job identifying data sets and standardized them as well as curating chromatographic metadata. Throughout the project we realized that especially this metadata is crucial. In contrast to previous retention time prediction approaches, which predict RTs for single chromatographic systems, we aim to develop a transferable system embracing the power of machine and deep learning. The first results are looking very promising.<br />
Beside these two, many other projects are currently on my table. Since 1st of January 2021 I’m heading the metabolomics part of the newly fused Metabolomics and Proteomics Core facility. After this fusion we are working on new targeted assays and a major project is the measurement of a large epidemiological study with >4000 samples. Such large-scale experiments are really the future of metabolomics (not only in clinical or epidemiological settings, but also basic science) and further work towards standardization, QC, reporting and data integration are required, but the community is on a good way here.<br />
<br />
===Question 3===<br />
<br />
''' 3. How do you think the understanding of C. elegans and their metabolic interactions with beneficial microbes can be applied into health and disease?? '''<br />
<br />
C. elegans offers several advantages, not only to study the beneficial effects of microbes. The short generation cycle as well as the genetic tractability makes it possible to grow sufficient amounts of isogenic animals in a short time. Since the worm feeds on live bacteria, virtually all bacteria that can be grown under similar conditions can be used as food for C. elegans. However, in recent years there was shift from seeing bacteria only as food towards a real microbiome and host-microbe interactions. Escherichia coli is normally used as a food source for the nematode, since it is easy to cultivate and was readily available at the time of introduction of C. elegans as model organism by Sidney Brenner. However, this is not the natural food of C. elegans nor its natural microbiome. A group around Hinrich Schulenburg and Buck Samuel recently published the CeMBio resource, a collection of culturable microbes from the natural C. elegans microbiome [4]. With this we have now a reproducible system to study host-microbe interactions, also on a metabolic level. The group of Christoph Kaleta for example added genome-scale metabolic models for the bacteria to the toolset.<br />
Based on the available system we can now start to study interaction in more detail, also following genetic components on both sides as well as metabolic interactions etc. This system is still not comparable to e.g. the interaction of humans with their microbiome, but we can derive some basic, conserved principles. The fast growth also helps to perform several experiments in short time, potentially in future also in high-throughput screens (genetic or drug screens), which might include metabolomics as well. Results can be then transferred to e.g. mouse models as next step.<br />
<br />
===Question 4===<br />
<br />
''' 4. What are the main challenges when developing methods for metabolomic analysis from limited sample amount? '''<br />
<br />
The challenges are twofold. First, highly sensitive analytical approaches are required to enable the analysis of low amounts of material. In contrast to genomics and transcriptomics we are not able to amplify our molecules of interest. I think the MS field is rapidly developing in this direction and recent instrument releases or publications such as the SpaceM approach from Theodore Alexandrov’s group are great examples [5]. However, depending on the amount of material at your hands you might have to make sacrifices. While normally, one would combine e.g. RP and HILIC based methods to increase the coverage of metabolites, you might be restricted to a single method or even injection. The goal should be to maximize the information you can obtain, e.g. using for example data-independent acquisition to cover “all” detected metabolites with MS2 information. Likewise, optimizing methods further towards better metabolome coverage. We have developed a Tandem-LC method covering HILIC and RP from a single injection. The goal is to further miniaturize this to be compatible with a limited sample amount. Second, with a decreasing amount of sample, even going down to single cells, the demand on sample preparation increases. One might face very low volumes for pipetting, extraction and injection. I believe that novel automated liquid handling solutions can help a lot here. But also, with decreasing amount of sample might be also related to an increasing number of samples. C. elegans is a good example here. Typically, we process 500-5000 worms (each with ~1000 cells) for one biological replicate. The metabolic individuality of the worms is averaged out by extracting them all together. If you lower the amount of worms per sample the more the individuality comes into effect, theoretically going down to single worms. While it is interesting to study this level of detail in metabolism, one has to keep in mind that you would need a larger number of replicates to compensate for this to obtain meaningful data (a problem, which is well-known from studies with “free-living-humans”, e.g. epidemiological scale studies). One need to counter-balance these effects and perform vigorous study design and keep in mind that we are often still measuring in a sequential manner in contrast to genomics and transcriptomics, where a lot of measurements can be parallelized. In the end we are probably not talking about 5 cells of type A vs 5 cells of type B, but 5000 vs 5000 or even worse. That means a lot of measurement time and I even didn’t start on the data analysis and interpretation…<br />
<br />
===Question 5===<br />
<br />
''' 5. You are the deputy head of metabolomics and proteomics core of the Helmholtz Zentrum München. What do you think contributed significantly to your career path in becoming a deputy leader? '''<br />
<br />
system is full of rejections and setbacks, but the key is to never give up and believe in the work you are doing. However, there are a few things that can turn the odds in your favor. I was lucky to participate in the Postdoctoral Fellowship Program of the HMGU, which gave me the chance to participate in many different courses on leadership, management, etc. as well as having a professional coaching. Especially the last one helped me a lot. During the process of coaching, it became clear to me that science has a lot of parallels to sales. Especially in the age of social media it makes a difference if you correctly “advertise” your work or not. The other important aspect is communication. Improving on my communication skills helped me a lot to better lead teams of scientist and to focus on common goals. I always try to remember myself that “the biggest misunderstanding in communication is that it happened”. Have an open ear, listen to others, ask questions and engage with people. Also think outside of the box, my personal coach never heard about metabolomics and that was great, because we never talked about science, but everything around it.<br />
From the scientific point of view, I was always happy and grateful that I had enough freedom to follow my own ideas. Even if you fail, you learn. And sometimes you learn more from your failures than your successes. And one last thing: All great minds, irrespective of the field, started as a beginner. Don’t be afraid to ask them, engage with them. You can learn a lot…<br />
<br />
===References===<br />
<br />
<br />
1. Witting, M., et al., DI-ICR-FT-MS-based high-throughput deep metabotyping: a case study of the Caenorhabditis elegans–Pseudomonas aeruginosa infection model. Analytical and Bioanalytical Chemistry, 2015. 407(4): p. 1059-1073.<br />
<br />
2. Salzer, L. and M. Witting, Quo Vadis Caenorhabditis elegans Metabolomics—A Review of Current Methods and Applications to Explore Metabolism in the Nematode. Metabolites, 2021. 11(5): p. 284.<br />
<br />
3. Witting, M. and S. Böcker, Current status of retention time prediction in metabolite identification. Journal of Separation Science, 2020. 43(9-10): p. 1746-1754.<br />
<br />
4. Dirksen, P., et al., CeMbio - The <em>Caenorhabditis elegans</em> Microbiome Resource. G3: Genes|Genomes|Genetics, 2020. 10(9): p. 3025-3039.<br />
<br />
5. Rappez, L., et al., SpaceM reveals metabolic states of single cells. Nature Methods, 2021. 18(7): p. 799-805.<br />
<br />
<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Main_Page&diff=1585Main Page2021-10-11T17:50:47Z<p>EvelinaCharidemou: </p>
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Welcome to the '''Early-Career Members Network (EMN) Webpage''', a resource curated by [[Early-Career_Members_Network | Early-Career Members Network of the Metabolomics Society]]. This wiki-styled page is designed to be a focal point for educational resources and online tools related to all facets of metabolomics, aiming to reach mainly young researchers of the field.<br />
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<h3><br />
[[Image: Michael Witting.jpg|x140px|border|link= Michael Witting]]<br /><br /> <br />
This month Expert Opinion comes from Dr Michael Witting! Check it out [[Michael Witting| here!]]<br /><br /><br />
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|}</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Main_Page&diff=1584Main Page2021-10-11T17:50:18Z<p>EvelinaCharidemou: </p>
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<div>__NOTOC____NOEDITSECTION__{{notitle}}<div style="position: relative; top: -30px; z-index: 100; font-size:100%;"><br />
{|cellpadding="5" cellspacing="0"|<br />
<br />
|style="border: 1px solid #DDDDDD;font-size:120%"|<br />
Welcome to the '''Early-Career Members Network (EMN) Webpage''', a resource curated by [[Early-Career_Members_Network | Early-Career Members Network of the Metabolomics Society]]. This wiki-styled page is designed to be a focal point for educational resources and online tools related to all facets of metabolomics, aiming to reach mainly young researchers of the field.<br />
<br />
<!-- NOTES FOR THE CATEGORIES TABLE:<br />
<br />
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[[Image: Michael Witting.jpg|x140px|border|link= Michael Witting]]<br /><br /> <br />
This month Expert Opinion comes from Dr Michael Witting! Check it out [[Candice Ulmer| here!]]<br /><br /><br />
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[[Image:Dan_Fausto3.png|x150px|border|link=http://metabolomicssociety.org/site-map/articles/88-videos/306-2020-emn-webinars-public]]<br /><br /><br />
Check out our last EMN Webinar on new bio-statistical methods for metabolomics!<br /><br /><br />
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If you would like to suggest content, please contact the current EMN committee at ''info.emn@metabolomicssociety.org''<br />
|}</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Michael_Witting&diff=1583Michael Witting2021-10-11T17:47:45Z<p>EvelinaCharidemou: Created page with " Michael Witting ==Short Biography== ''' Biography''' Dr. Michael Witting studied Applied Chemistry with a functional direction into..."</p>
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<div>[[Image: Michael Witting.jpg|thumb| Michael Witting ]]<br />
<br />
==Short Biography==<br />
<br />
''' Biography''' <br />
<br />
Dr. Michael Witting studied Applied Chemistry with a functional direction into biochemistry at the Georg-Simon-Ohm University of Applied Science, Nuremberg, Germany and obtained his PhD in 2013 from the Technical University of Munich. He is a current member of the Metabolomics Society Board of Directors and since 1st of January he is heading the metabolomics section of the Metabolomics and Proteomics Core at the Helmholtz Zentrum München. His main research interests are LC-MS based metabolomics method development and application, as well as metabolite identification improvement by retention time prediction.<br />
<br />
==Expert Opinion==<br />
===Question 1===<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations?'''<br />
<br />
I have started with metabolomics in 2009 when starting my PhD in the group of Philippe Schmitt-Kopplin at the Helmholtz Zentrum München. My first project funded by the ERA-Net project pathomics was to study host-pathogen interactions of the opportunistic human pathogen Pseudomonas aeruginosa. I applied direct infusion FT-ICR-MS as well as UPLC-UHR-ToF-MS based metabolomics and lipidomics to study the metabolic response of HeLa cells or Caenorhabditis elegans [1]. This was also the time, when my interest in this model organism started, realizing that C. elegans and metabolomics/lipidomics is a fruitful combination.<br />
<br />
===Question 2===<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
I have currently two main projects running. The first one is a French-German collaboration with the groups of Fabien Jourdan and Reza Salek in France as well as the group of Steffen Neumann in Germany. We are aiming to integrate different networks, such as mass-difference, correlation, spectral similarity networks with genome-scale metabolic reconstructions and other types of networks in a multilayer network to derive a better understanding of the data as well as helping to identify new metabolites and improve genome-scale metabolic models. Within this fantastic group my PhD student Liesa Salzer and I are working on C. elegans metabolomics and lipidomics data and the annotation of metabolites present in the nematode [2]. We are using different spectral libraries as well as in-silico tools to annotate the data as good as possible and feed it into our larger framework of the project. This is very interesting since it will enable us on the one side to define in more detail the metabolome and lipidome of C. elegans and on the other side requires to develop new scripts and pipelines for data handling. Furthermore, we hope to be able to identify several new metabolites and close some gaps on metabolic pathways. We are really looking forward to presenting our first results in the coming months.<br />
The second project is a collaborative project with the group of Sebastian Böcker aiming to develop reproducible and transferable retention time prediction. Chromatographic separation is important in metabolite identification since it allows the separation of isomers and represents an orthogonal information to MS and MS/MS giving hints about the polarity of a metabolite. However, it is often only used at a late stage of metabolite identification, typically when comparing against a reference standard. Retention time prediction enables to utilize this information in an early stage, potentially reducing the number of false positive annotations [3]. However, sharing of RTs is not as widespread as sharing of MS2 spectra. So, we first needed to identify good training data for our project. My PhD student Eva-Maria Harrieder did a great job identifying data sets and standardized them as well as curating chromatographic metadata. Throughout the project we realized that especially this metadata is crucial. In contrast to previous retention time prediction approaches, which predict RTs for single chromatographic systems, we aim to develop a transferable system embracing the power of machine and deep learning. The first results are looking very promising.<br />
Beside these two, many other projects are currently on my table. Since 1st of January 2021 I’m heading the metabolomics part of the newly fused Metabolomics and Proteomics Core facility. After this fusion we are working on new targeted assays and a major project is the measurement of a large epidemiological study with >4000 samples. Such large-scale experiments are really the future of metabolomics (not only in clinical or epidemiological settings, but also basic science) and further work towards standardization, QC, reporting and data integration are required, but the community is on a good way here.<br />
<br />
===Question 3===<br />
<br />
''' 3. How do you think the understanding of C. elegans and their metabolic interactions with beneficial microbes can be applied into health and disease?? '''<br />
<br />
C. elegans offers several advantages, not only to study the beneficial effects of microbes. The short generation cycle as well as the genetic tractability makes it possible to grow sufficient amounts of isogenic animals in a short time. Since the worm feeds on live bacteria, virtually all bacteria that can be grown under similar conditions can be used as food for C. elegans. However, in recent years there was shift from seeing bacteria only as food towards a real microbiome and host-microbe interactions. Escherichia coli is normally used as a food source for the nematode, since it is easy to cultivate and was readily available at the time of introduction of C. elegans as model organism by Sidney Brenner. However, this is not the natural food of C. elegans nor its natural microbiome. A group around Hinrich Schulenburg and Buck Samuel recently published the CeMBio resource, a collection of culturable microbes from the natural C. elegans microbiome [4]. With this we have now a reproducible system to study host-microbe interactions, also on a metabolic level. The group of Christoph Kaleta for example added genome-scale metabolic models for the bacteria to the toolset.<br />
Based on the available system we can now start to study interaction in more detail, also following genetic components on both sides as well as metabolic interactions etc. This system is still not comparable to e.g. the interaction of humans with their microbiome, but we can derive some basic, conserved principles. The fast growth also helps to perform several experiments in short time, potentially in future also in high-throughput screens (genetic or drug screens), which might include metabolomics as well. Results can be then transferred to e.g. mouse models as next step.<br />
<br />
===Question 4===<br />
<br />
''' 4. What are the main challenges when developing methods for metabolomic analysis from limited sample amount? '''<br />
<br />
The challenges are twofold. First, highly sensitive analytical approaches are required to enable the analysis of low amounts of material. In contrast to genomics and transcriptomics we are not able to amplify our molecules of interest. I think the MS field is rapidly developing in this direction and recent instrument releases or publications such as the SpaceM approach from Theodore Alexandrov’s group are great examples [5]. However, depending on the amount of material at your hands you might have to make sacrifices. While normally, one would combine e.g. RP and HILIC based methods to increase the coverage of metabolites, you might be restricted to a single method or even injection. The goal should be to maximize the information you can obtain, e.g. using for example data-independent acquisition to cover “all” detected metabolites with MS2 information. Likewise, optimizing methods further towards better metabolome coverage. We have developed a Tandem-LC method covering HILIC and RP from a single injection. The goal is to further miniaturize this to be compatible with a limited sample amount. Second, with a decreasing amount of sample, even going down to single cells, the demand on sample preparation increases. One might face very low volumes for pipetting, extraction and injection. I believe that novel automated liquid handling solutions can help a lot here. But also, with decreasing amount of sample might be also related to an increasing number of samples. C. elegans is a good example here. Typically, we process 500-5000 worms (each with ~1000 cells) for one biological replicate. The metabolic individuality of the worms is averaged out by extracting them all together. If you lower the amount of worms per sample the more the individuality comes into effect, theoretically going down to single worms. While it is interesting to study this level of detail in metabolism, one has to keep in mind that you would need a larger number of replicates to compensate for this to obtain meaningful data (a problem, which is well-known from studies with “free-living-humans”, e.g. epidemiological scale studies). One need to counter-balance these effects and perform vigorous study design and keep in mind that we are often still measuring in a sequential manner in contrast to genomics and transcriptomics, where a lot of measurements can be parallelized. In the end we are probably not talking about 5 cells of type A vs 5 cells of type B, but 5000 vs 5000 or even worse. That means a lot of measurement time and I even didn’t start on the data analysis and interpretation…<br />
<br />
===Question 5===<br />
<br />
''' 5. You are the deputy head of metabolomics and proteomics core of the Helmholtz Zentrum München. What do you think contributed significantly to your career path in becoming a deputy leader? '''<br />
<br />
system is full of rejections and setbacks, but the key is to never give up and believe in the work you are doing. However, there are a few things that can turn the odds in your favor. I was lucky to participate in the Postdoctoral Fellowship Program of the HMGU, which gave me the chance to participate in many different courses on leadership, management, etc. as well as having a professional coaching. Especially the last one helped me a lot. During the process of coaching, it became clear to me that science has a lot of parallels to sales. Especially in the age of social media it makes a difference if you correctly “advertise” your work or not. The other important aspect is communication. Improving on my communication skills helped me a lot to better lead teams of scientist and to focus on common goals. I always try to remember myself that “the biggest misunderstanding in communication is that it happened”. Have an open ear, listen to others, ask questions and engage with people. Also think outside of the box, my personal coach never heard about metabolomics and that was great, because we never talked about science, but everything around it.<br />
From the scientific point of view, I was always happy and grateful that I had enough freedom to follow my own ideas. Even if you fail, you learn. And sometimes you learn more from your failures than your successes. And one last thing: All great minds, irrespective of the field, started as a beginner. Don’t be afraid to ask them, engage with them. You can learn a lot…<br />
<br />
===References===<br />
<br />
<br />
1. Witting, M., et al., DI-ICR-FT-MS-based high-throughput deep metabotyping: a case study of the Caenorhabditis elegans–Pseudomonas aeruginosa infection model. Analytical and Bioanalytical Chemistry, 2015. 407(4): p. 1059-1073.<br />
2. Salzer, L. and M. Witting, Quo Vadis Caenorhabditis elegans Metabolomics—A Review of Current Methods and Applications to Explore Metabolism in the Nematode. Metabolites, 2021. 11(5): p. 284.<br />
3. Witting, M. and S. Böcker, Current status of retention time prediction in metabolite identification. Journal of Separation Science, 2020. 43(9-10): p. 1746-1754.<br />
4. Dirksen, P., et al., CeMbio - The <em>Caenorhabditis elegans</em> Microbiome Resource. G3: Genes|Genomes|Genetics, 2020. 10(9): p. 3025-3039.<br />
5. Rappez, L., et al., SpaceM reveals metabolic states of single cells. Nature Methods, 2021. 18(7): p. 799-805.<br />
<br />
<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Expert_Opinion&diff=1582Expert Opinion2021-10-11T17:40:47Z<p>EvelinaCharidemou: </p>
<hr />
<div>The '''Expert Opinion''' is an initiative from the [[Early-Career Members Network|Early-Career Members Network (EMN) Committee]] that intends to publish career feedback from leading researchers in the metabolomics field. With that, early career researchers can get to know different specialists on the field and, more importantly, get insights and tips on how to build their on career.<br />
<br />
[[Image: Michael Witting.jpg|75px|link= Michael Witting]] [[Michael Witting| Dr. Michael Witting (October, 2021)]]<br />
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[[Image: Candice Ulmer.jpg|75px|link= Candice Ulmer]] [[Candice Ulmer| Dr. Candice Z. Ulmer (August, 2021)]]<br />
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[[Image: Kati_Hanhineva2.jpg|75px|link= Kati Hanhineva]] [[Kati Hanhineva| Dr. Kati Hanhineva (May, 2021)]]<br />
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[[Image: Justine_Bertrand-Michel.jpg|75px|link= Justine Bertrand-Michel]] [[Justine Bertrand-Michel|Dr. Justine Bertrand-Michel (April, 2021)]]<br />
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[[Image:Pieter_Dorrestein.jpg|75px|link= Pieter Dorrestein]] [[Pieter Dorrestein|Professor Pieter Dorrestein (March, 2021)]]<br />
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[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [[Roy Goodacre|Professor Roy Goodacre (February, 2021)]]<br />
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[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|Dr. Kazuki Saito (January, 2021)]]<br />
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[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|Dr. Augustin Scalbert (December, 2020)]]<br />
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[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|Associate Professor Jessica Lasky-Su (February, 2020)]]<br />
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[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|Dr Nichole Reisdorph (September, 2019)]]<br />
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[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|Professor Warwick (Rick) Dunn (July, 2019)]]<br />
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[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|Professor Mark Viant (April, 2019)]]<br />
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[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|Dr Stacey Reinke (March, 2019)]]<br />
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[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|Dr Carla Antonio (July, 2018)]]<br />
<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|Dr Justin J.J. van der Hooft (February, 2018)]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=File:Michael_Witting.jpg&diff=1581File:Michael Witting.jpg2021-10-11T17:39:01Z<p>EvelinaCharidemou: </p>
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<div></div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Main_Page&diff=1580Main Page2021-08-25T16:05:42Z<p>EvelinaCharidemou: </p>
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Welcome to the '''Early-Career Members Network (EMN) Webpage''', a resource curated by [[Early-Career_Members_Network | Early-Career Members Network of the Metabolomics Society]]. This wiki-styled page is designed to be a focal point for educational resources and online tools related to all facets of metabolomics, aiming to reach mainly young researchers of the field.<br />
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[[Image: Candice Ulmer.jpg|x140px|border|link= Candice Ulmer]]<br /><br /> <br />
This month Expert Opinion comes from Dr Candice Z. Ulmer! Check it out [[Candice Ulmer| here!]]<br /><br /><br />
</h3><br />
|style="width:25%; font-size:80%; vertical-align:center; text-align:center;"|<br />
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[[Image:Dan_Fausto3.png|x150px|border|link=http://metabolomicssociety.org/site-map/articles/88-videos/306-2020-emn-webinars-public]]<br /><br /><br />
Check out our last EMN Webinar on new bio-statistical methods for metabolomics!<br /><br /><br />
</h3><br />
|style="width:25%; font-size:80%; vertical-align:center; text-align:center;"|<br />
<h3><br />
[[Image:MetSocConf2021_2.png|x150px|border|link=Upcoming Events]]<br /><br /> <br />
Do not miss the upcoming events in our community (including MetSoc Conference 2021!) Check all [[Upcoming Events| here!]]<br /><br /><br />
|}<br />
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<br />
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!colspan=6 style="text-align:center; font-size:100%;"|'''Finding Metabolomics Communities'''<br />
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[[Image:128px-Blank Map-Africa.svg.png|link= Metabolomics Communities#Africa|x100px]]<br /><br /> <br />
[[Metabolomics_Communities#Africa|'''Africa''']] <br /><br /> <br />
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[[Metabolomics_Communities#Asia|'''Asia''']] <br /><br /> <br />
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[[Image:128px-America_Blank.svg.png|link=Metabolomics Communities#North and Central America|x100px]]<br /><br /> <br />
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[[Metabolomics_Communities#Oceania|'''Oceania''']] <br /><br /> <br />
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|}</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Candice_Ulmer&diff=1579Candice Ulmer2021-08-25T16:02:34Z<p>EvelinaCharidemou: Created page with " Candice Z. Ulmer ==Short Biography== ''' Biography''' Dr. Candice Z. Ulmer holds BS degrees in Chemistry and Biochemistry from the Col..."</p>
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<div>[[Image: Candice Ulmer.jpg|thumb| Candice Z. Ulmer ]]<br />
<br />
==Short Biography==<br />
<br />
''' Biography''' <br />
<br />
Dr. Candice Z. Ulmer holds BS degrees in Chemistry and Biochemistry from the College of Charleston. She obtained her Ph.D. in Chemistry at the University of Florida in 2016 under the direction of Dr. Richard Yost after only a 4-year tenure. Her multi-omics doctoral research focused on two main applications, T cell immune dysregulation in Type 1 Diabetes and biomarker discovery in melanoma skin cancer. After receiving her doctorate, Dr. Ulmer immediate pursued a NRC post-doctoral research fellowship at NIST under the direction of Dr. John Bowden, where her work focused on the standardization of lipid measurements in the first international lipidomics interlaboratory exercise. Dr. Candice Z. Ulmer is currently a Clinical Chemist at the Centers for Disease Control and Prevention in Atlanta, GA. As Project Lead and Acting Chief of the Clinical Reference Laboratory for Cancer, Kidney, and Bone Disease Biomarkers in the Clinical Chemistry Branch, Dr. Ulmer is involved with the planning and execution of programs to ensure the accurate measurement of chronic disease biomarkers (e.g., steroid and protein hormones) and the assessment of clinical analytical methods in patient care, both internationally and domestically. Dr. Ulmer was nominated by the American Association of Clinical Chemistry (AACC) to serve on the newly-formed International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Committee on Bone Metabolism. She is a co-chair of the American Society for Mass Spectrometry (ASMS) clinical chemistry interest group and publication committee. With over 30 publications and a pending patent as an early-career chemist, she serves as the ASMS clinical chemistry interest group co-chair and assumes appointed/elected memberships in six committees for other scientific organizations that include the International Metabolomics Society, the Metabolomics Quality Assurance and Quality Control Consortium, Metabolomics of North America, and the American Chemical Society.<br />
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==Expert Opinion==<br />
===Question 1===<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations?'''<br />
<br />
As a graduate student at the University of Florida under the direction of Dr. Richard Yost (2013 – 2016), I actively participated in metabolomics projects for the NIH-funded Southeast Center for Integrated Metabolomics (SECIM). In this role, I designed sample preparation protocols for multi-omics applications involving various matrices (e.g., suspension mammalian cells, plasma, and tissue). I thoroughly enjoyed applying UHPLC-HRMS techniques to profile the metabolome/lipidome of human cells and tissues to better understand the disease etiology of Type 1 Diabetes and melanoma skin cancer. I gained quite a bit of experience with various modes of ionization (e.g., MALDI, ESI, APCI, DESI, FlowProbe, and DART) while investigating my metabolomics projects, which was an amazing opportunity as a graduate student. I was also able to become well-versed with novel stable isotope labeling methodologies such as Isotopic Ratio Outlier Analysis (IROA) to aid in the identification of metabolites as compound identification is still considered a bottleneck in metabolomics studies. <br />
<br />
===Question 2===<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
After my NRC post-doctoral fellowship, I began working as a research chemist at the CDC in a clinical chemistry laboratory. My role in this position involves the planning and execution of programs for the harmonization and accurate reporting of chronic disease biomarkers. We study these markers to enhance the diagnosis and treatment of select endocrine diseases and advance CDC Standardization Programs – aimed at improving the accuracy and precision of clinical measurements in patient care. Currently, I am developing routine and reference measurement procedures for chronic disease biomarkers such as parathyroid hormone and its breakdown products. I’m also collaborating on projects such as the National Health and Nutrition Examination Survey (NHANES), which is a program of studies designed to assess the health of the US population, to provide measurements for various steroid and reproductive hormones. <br />
<br />
===Question 3===<br />
<br />
''' 3. You are currently working on identifying chronic disease biomarkers. What is the main challenge in discovering biomarkers? '''<br />
<br />
Challenges that I experience in discovering biomarkers generally stem from the lack of reference materials/methods, which are needed to accurately identify and measure these analytes of interest in various biological matrices. <br />
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===Question 4===<br />
<br />
''' 4. Do you think the discovery of chronic disease biomarkers can be applied successfully in drug discovery and development? '''<br />
<br />
As the appreciation for mass spectrometry continues to grow in the clinical space and as the technique continues to get incorporated in routine clinical testing, I do believe that chronic disease biomarkers will be successfully applied in drug discovery and development as surrogate endpoints for various clinical studies. A key element of this will be the transition from single analyte biomarker assays to quantitative panels able to measure multiple biomarkers and thus assess numerous disease states simultaneously. This will require these biomarkers to be reliable, validated, and qualified in the associated biological process/clinical endpoint. <br />
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===Question 5===<br />
<br />
''' 5. As a clinical chemist, what advice would you give to someone developing MS-based methods for lipidomics/metabolomics in biomarker discovery? '''<br />
<br />
My best advice would be to adhere to best practice guidelines outlined by stakeholder organizations (e.g., the International Lipidomics Society (ILS), the Metabolomics Society (MetSoc), the Metabolomics Quality Assurance & Quality Control Consortium (mQACC), LIPID MAPS, etc.) in the design of metabolomics/lipidomics biomarker discovery workflows. These organizations are actively working to develop harmonized principles for each component of the biomarker discovery workflow including bioanalysis (e.g., sample collection, sample preparation, data acquisition), data processing, compound identification, and biological interpretation. Implementation of these best practices will reduce the probability of sample bias, false positives, inaccurate data interpretation.<br />
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===Question 6===<br />
<br />
<br />
''' 6. You have achieved huge success in the initiation of the Coalition of Black Mass Spectrometrists. Could you briefly share the history behind this idea and the achievements and key aims of the organisation? '''<br />
<br />
Drs. Christina Jones, Michelle Reid, and I felt that it was necessary in 2019 to fulfill an initiative proposed by Dr. Rena Robinson, of creating a safe space for Blacks to engage and network amongst each other at conferences such as ASMS, because blacks face a unique set of challenges. Given the current climate of police brutality and racial injustice and the difficulty we ourselves witnessed/experienced in navigating through this in 2020, we decided to launch our first official event during ASMS and coined our organization Black People Meet @ ASMS. We established initiatives, such as Black People Meet @ ASMS, to call awareness to the need for initiatives and policies to ensure cultural diversity and the representation of Blacks in STEM. Honestly, our platform turned out to be larger than any of us could have imagined. We’ve touched the minds and ears of thousands of Blacks and allies with our voices, which has forced us to redesign our platform to touch a larger audience as the Coalition of Black Mass Spectrometrists (CBM). Since our reorganization, our redefined purpose is to create a platform for black mass spectrometrists to engage in discussion, cultivate a sense of community, and support each other. We’ve held socials for our members, established a social media presence, published an editorial piece in the Analytical Scientist, and presented on systemic racism for various scientific organizations (e.g., FeMS virtual happy hour, MUSC's Annual Inclusion to Innovation Summit, and the 68th ASMS Conference: ASMS 2020 Reboot). We now have a permanent page under the ASMS Member Center with highlighted resources on ways to be effective supporters/allies/advocates and to eradicate systemic racism. <br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Expert_Opinion&diff=1578Expert Opinion2021-08-25T15:56:39Z<p>EvelinaCharidemou: </p>
<hr />
<div>The '''Expert Opinion''' is an initiative from the [[Early-Career Members Network|Early-Career Members Network (EMN) Committee]] that intends to publish career feedback from leading researchers in the metabolomics field. With that, early career researchers can get to know different specialists on the field and, more importantly, get insights and tips on how to build their on career.<br />
<br />
[[Image: Candice Ulmer.jpg|75px|link= Candice Ulmer]] [[Candice Ulmer| Dr. Candice Z. Ulmer (August, 2021)]]<br />
<br />
[[Image: Kati_Hanhineva2.jpg|75px|link= Kati Hanhineva]] [[Kati Hanhineva| Dr. Kati Hanhineva (May, 2021)]]<br />
<br />
[[Image: Justine_Bertrand-Michel.jpg|75px|link= Justine Bertrand-Michel]] [[Justine Bertrand-Michel|Dr. Justine Bertrand-Michel (April, 2021)]]<br />
<br />
[[Image:Pieter_Dorrestein.jpg|75px|link= Pieter Dorrestein]] [[Pieter Dorrestein|Professor Pieter Dorrestein (March, 2021)]]<br />
<br />
[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [[Roy Goodacre|Professor Roy Goodacre (February, 2021)]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|Dr. Kazuki Saito (January, 2021)]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|Dr. Augustin Scalbert (December, 2020)]]<br />
<br />
[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|Associate Professor Jessica Lasky-Su (February, 2020)]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|Dr Nichole Reisdorph (September, 2019)]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|Professor Warwick (Rick) Dunn (July, 2019)]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|Professor Mark Viant (April, 2019)]]<br />
<br />
[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|Dr Stacey Reinke (March, 2019)]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|Dr Carla Antonio (July, 2018)]]<br />
<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|Dr Justin J.J. van der Hooft (February, 2018)]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=File:Candice_Ulmer.jpg&diff=1577File:Candice Ulmer.jpg2021-08-25T15:54:57Z<p>EvelinaCharidemou: </p>
<hr />
<div></div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Metabolomics_Society_Wiki:Privacy_policy&diff=1576Metabolomics Society Wiki:Privacy policy2021-07-26T13:17:24Z<p>EvelinaCharidemou: Blanked the page</p>
<hr />
<div></div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Metabolomics_Society_Wiki:Privacy_policy&diff=1575Metabolomics Society Wiki:Privacy policy2021-07-26T13:16:02Z<p>EvelinaCharidemou: </p>
<hr />
<div>The links provided below are to resources and tools on websites operated by organizations that are not affiliated with the Metabolomics Society. The Metabolomics Society does not control these websites and is not responsible for their contents, and our inclusion of the links does not imply any endorsement.</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Metabolomics_Society_Wiki:Privacy_policy&diff=1574Metabolomics Society Wiki:Privacy policy2021-07-26T13:15:17Z<p>EvelinaCharidemou: </p>
<hr />
<div>The links provided below are to resources and tools on websites operated by organizations that are not affiliated with the MetSoc. The MetSoc does not control these websites and is not responsible for their contents, and our inclusion of the links does not imply any endorsement.</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Metabolomics_Society_Wiki:Privacy_policy&diff=1573Metabolomics Society Wiki:Privacy policy2021-07-26T13:11:58Z<p>EvelinaCharidemou: Created page with "'''Links to Other Sites''' The Site contains links to websites operated by parties other than the Metabolomics Society. The Society does not control these websites and is not..."</p>
<hr />
<div>'''Links to Other Sites'''<br />
<br />
The Site contains links to websites operated by parties other than the Metabolomics Society. The Society does not control these websites and is not responsible for their contents or privacy practices. We encourage you to read these websites’ privacy policies. Our inclusion of links does not imply any endorsement of the content on the websites or any association with their operators.</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Kati_Hanhineva&diff=1351Kati Hanhineva2021-05-17T08:52:05Z<p>EvelinaCharidemou: Created page with " Dr. Kati Hanhineva ==Short Biography== ''' Biography''' I am professor in food development with special focus on Nordic foods and hea..."</p>
<hr />
<div>[[Image: Kati_Hanhineva.jpg|thumb| Dr. Kati Hanhineva ]]<br />
<br />
==Short Biography==<br />
<br />
''' Biography''' <br />
<br />
I am professor in food development with special focus on Nordic foods and health effects at the University of Turku, Department of Biochemistry, Food Chemistry and Food Development unit since beginning of 2020. Part of my research group is situated at the School of Public Health and Clinical Nutrition at the University of Eastern Finland. Since fall 2019 I am also affiliated as visiting scientist (Marie Curie MoRE2020 Fellow) at the Division of Food and Nutrition Science, Department of Biology and Biological Engineering at the Chalmers University of Technology, Gothenburg, Sweden. I have the docentship in nutrition and food metabolomics at the Faculty of Health Sciences, University of Eastern Finland.<br />
<br />
I completed PhD in biotechnology at the University of Kuopio 2008. During years 2008-2014 I conducted post-doctoral research at the Department of Public Health and Clinical Nutrition, at the University of Eastern Finland with several research visits to the Weizmann Institute of Science in Israel. Since 2014 I have been the principal investigator in food and nutritional metabolomics research group and led and participated in several national and EU-funded research projects including Academy Researcher fellowship 2014-2019.<br />
<br />
'''Research'''<br />
My main research focus is within the biochemistry of foods, especially phytochemical compounds and the effect of food processing such as fermentation on their composition. Likewise, molecular level understanding of the role of nutrition in maintaining good health, and food-microbiota interaction are within the core of my research. The key analytical technology at the different stages of research is the mass-spectrometry based metabolic profiling that I have developed and utilized for various food and nutrition related applications, in particular within projects related to the beneficial health effect of whole grain rich diets.<br />
<br />
List of publications can be found at https://www.utu.fi/en/people/kati-hanhineva<br />
<br />
==Expert Opinion==<br />
===Question 1===<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations?'''<br />
<br />
During my PhD studies. I generated transgenic strawberries and despite obvious differences in the phenotype could not find out any explanation based on traditional targeted chemical analysis. Then I contacted Prof Asaph Aharoni at Weizmann Institute, Israel, and was able to visit his lab several times to get accustomed to LC-MS based metabolic profiling. I eventually received the answer to my biggest question in the PhD project, and since then have always used this fascinating technology in all my research.<br />
<br />
===Question 2===<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
The most recent projects relate to my new position at University of Turku, Finland, where establishment of analytical platforms for various metabolomics approaches is currently ongoing. The research topics revolve around diets, mainly plant-based, and role of gut microbiota.<br />
<br />
===Question 3===<br />
<br />
''' 3. What was the most challenging aspect of developing analytical tools to study phytochemicals?? '''<br />
<br />
It is clearly the same issue that is a challenge for any metabolomics work, but especially relevant for phytochemicals – namely the identification of compounds. When analysing plant-based foods the plethora of various chemical signals is simply overwhelming since the plants are the most efficient chemical machineries on earth. On the other hand, this same aspect is also what makes the work with phytochemicals so interesting – what do all these potentially bioactive little creatures do when they arrive to our body and metabolism, and how do they interact with our gut flora?<br />
<br />
===Question 4===<br />
<br />
''' 4. How do you think your research on food-microbiota interaction can be applied today or in the future? '''<br />
<br />
Currently, the research in this area is still very much basic research to widen up our understanding on the mutual interaction between diet and gut flora in general, there is so much to learn still here! If we think about potential future applications, at least the monitoring of the function of gut flora by measuring the metabolites they produce in easily obtainable sample material such as plasma, urine, saliva, is regarded as very potential tool for the assessment of personalized nutrition schemes, for example.<br />
===Question 5===<br />
<br />
''' 5. One of the aims of your professorship is to collaborate with the food industry. What are the key elements for a successful collaboration between basic research laboratories and industries? '''<br />
<br />
Collaboration with industry is essential as no matter how healthy some plant or other food raw material is, it is meaningless unless someone produces a tasty food product from it that is well accepted by the consumers. In this sense, the active discussion on the health relevance of the different food materials and impact of food production methods on it is very important, ad requires intensive, multidisciplinary collaboration between various stakeholder groups – including academia and industry. <br />
<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Expert_Opinion&diff=1341Expert Opinion2021-05-17T08:46:59Z<p>EvelinaCharidemou: </p>
<hr />
<div>The '''Expert Opinion''' is an initiative from the [[Early-Career Members Network#EMN Committee|Early-Career Members Network (EMN) Committee]] that intends to publish career feedback from leading researchers in the metabolomics field. With that, early career researchers can get to know different specialists on the field and, more importantly, get insights and tips on how to build their on career.<br />
<br />
[[Image: Kati_Hanhineva.jpg|75px|link= Kati Hanhineva]] [[Kati Hanhineva|Dr. Kati Hanhineva (May, 2021)]]<br />
<br />
[[Image: Justine_Bertrand-Michel.jpg|75px|link= Justine Bertrand-Michel]] [[Justine Bertrand-Michel|Dr. Justine Bertrand-Michel (April, 2021)]]<br />
<br />
[[Image:Pieter_Dorrestein.jpg|75px|link= Pieter Dorrestein]] [[Pieter Dorrestein|Professor Pieter Dorrestein (March, 2021)]]<br />
<br />
[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [[Roy Goodacre|Professor Roy Goodacre (February, 2021)]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|Dr. Kazuki Saito (January, 2021)]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|Dr. Augustin Scalbert (December, 2020)]]<br />
<br />
[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|Associate Professor Jessica Lasky-Su (February, 2020)]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|Dr Nichole Reisdorph (September, 2019)]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|Professor Warwick (Rick) Dunn (July, 2019)]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|Professor Mark Viant (April, 2019)]]<br />
<br />
[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|Dr Stacey Reinke (March, 2019)]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|Dr Carla Antonio (July, 2018)]]<br />
<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|Dr Justin J.J. van der Hooft (February, 2018)]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=File:Kati_Hanhineva.jpg&diff=1337File:Kati Hanhineva.jpg2021-05-17T08:45:53Z<p>EvelinaCharidemou: </p>
<hr />
<div></div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Expert_Opinion&diff=1336Expert Opinion2021-05-17T08:45:26Z<p>EvelinaCharidemou: </p>
<hr />
<div>The '''Expert Opinion''' is an initiative from the [[Early-Career Members Network#EMN Committee|Early-Career Members Network (EMN) Committee]] that intends to publish career feedback from leading researchers in the metabolomics field. With that, early career researchers can get to know different specialists on the field and, more importantly, get insights and tips on how to build their on career.<br />
<br />
[[Image: Kati_Hanhineva.jpg|75px|link= Kati Hanhineva]] [Kati Hanhineva|Dr. Kati Hanhineva (May, 2021)]]<br />
<br />
[[Image: Justine_Bertrand-Michel.jpg|75px|link= Justine Bertrand-Michel]] [[Justine Bertrand-Michel|Dr. Justine Bertrand-Michel (April, 2021)]]<br />
<br />
[[Image:Pieter_Dorrestein.jpg|75px|link= Pieter Dorrestein]] [[Pieter Dorrestein|Professor Pieter Dorrestein (March, 2021)]]<br />
<br />
[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [[Roy Goodacre|Professor Roy Goodacre (February, 2021)]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|Dr. Kazuki Saito (January, 2021)]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|Dr. Augustin Scalbert (December, 2020)]]<br />
<br />
[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|Associate Professor Jessica Lasky-Su (February, 2020)]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|Dr Nichole Reisdorph (September, 2019)]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|Professor Warwick (Rick) Dunn (July, 2019)]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|Professor Mark Viant (April, 2019)]]<br />
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[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|Dr Stacey Reinke (March, 2019)]]<br />
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[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|Dr Carla Antonio (July, 2018)]]<br />
<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|Dr Justin J.J. van der Hooft (February, 2018)]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Metabolomics_Society_Forum&diff=1292Metabolomics Society Forum2021-05-17T08:13:31Z<p>EvelinaCharidemou: Created page with "The [http://www.metabolomics-forum.com/index.php?action=forum Metabolomics Society forum] is a space to engage in discussions, ask questions, and meet other scientists involve..."</p>
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<div>The [http://www.metabolomics-forum.com/index.php?action=forum Metabolomics Society forum] is a space to engage in discussions, ask questions, and meet other scientists involved in metabolomics.</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Databases&diff=1291Databases2021-05-17T08:12:45Z<p>EvelinaCharidemou: Created page with "This page lists open-access metabolomics-related databases. Databases are roughly categorized whether they are a repository for raw/processed metabolomics data, provide refere..."</p>
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<div>This page lists open-access metabolomics-related databases. Databases are roughly categorized whether they are a repository for raw/processed metabolomics data, provide reference spectra (experimentally or computationally derived) or principally provide curation/ontology of structures/pathways.<br />
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=Metabolomic repositories=<br />
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[[MassIVE]]<br />
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[[MetaboLights]]<br />
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[[MetabolomeExpress]]<br />
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=Reference databases=<br />
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[[Biological Magnetic Resonance Data Bank]]<br />
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[[Birmingham Metabolite Library]]<br />
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[[Glycan Mass Spectral Database]]<br />
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[[Golm Metabolome Database]]<br />
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[[Human Metabolome Database]]<br />
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[[Madison Metabolomics Consortium Database]]<br />
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[[MassBank]]<br />
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[[MassBank of North America]]<br />
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[[METLIN]]<br />
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[[MzCloud]]<br />
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[[NIST Standard Reference Database]]<br />
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[[Phenol-Explorer]]<br />
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[[Spectral Database for Organic Compounds]]<br />
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=Currated structures/pathways=<br />
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[[BiGG]]<br />
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[[BioModels]]<br />
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[[ChEBI]]<br />
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[[Chemspider]]<br />
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[[Human Metabolome Database]]<br />
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[[KEGG]]<br />
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[[LIPID MAPS Proteome Database]]<br />
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[[LIPID MAPS Structure Database]]<br />
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[[MetaCyc]]<br />
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[[OpenFoodTox]]<br />
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[[Phenol-Explorer]]<br />
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[[PhytoHub]]<br />
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[[PubChem]]<br />
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[[SwissLipids]]<br />
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[[WikiPathways]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Metabolomics_Society_Workshops&diff=1288Metabolomics Society Workshops2021-05-17T08:11:52Z<p>EvelinaCharidemou: Created page with "The Metabolomics Society holds workshops at the annual meeting each year. In addition, you may be interested in attending one of the external workshops that are available all..."</p>
<hr />
<div>The Metabolomics Society holds workshops at the annual meeting each year. In addition, you may be interested in attending one of the external workshops that are available all over the world and online. <br />
<br />
=Resources from previous Metabolomics Society Workshops=<br />
<br />
Resources from previous workshops can be found on the [http://metabolomicssociety.org/resources/multimedia society website].<br />
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===2014===<br />
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[[http://metabolomicssociety.org/site-map/articles/88-videos/177-2014-conference-workshop-videos-public Workshops from Metabolomics 2014 - Tsuroka, Japan]]<br />
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===2015===<br />
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[[http://metabolomicssociety.org/site-map/articles/88-videos/177-2014-conference-workshop-videos-public Workshops from Metabolomics 2015 - San Francisco, USA]]<br />
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===2017===<br />
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[[http://metabolomicssociety.org/site-map/articles/88-videos/177-2014-conference-workshop-videos-public Workshops from Metabolomics 2017 - Brisbane, Australia]]<br />
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===2018===<br />
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[[http://metabolomicssociety.org/site-map/articles/88-videos/177-2014-conference-workshop-videos-public Workshops from Metabolomics 2018 - Seattle, USA]]<br />
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===2019===<br />
<br />
[[http://metabolomicssociety.org/site-map/articles/88-videos/177-2014-conference-workshop-videos-public Workshops from Metabolomics 2019 - The Hague, The Netherlands]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Justine_Bertrand-Michel&diff=1202Justine Bertrand-Michel2021-04-15T16:11:52Z<p>EvelinaCharidemou: Created page with " Dr. Justine Bertrand-Michel ==Short Biography== ''' About my Career''' I got a PhD in chemistry of biomolecule at the Univer..."</p>
<hr />
<div>[[Image: Justine_Bertrand-Michel.jpg|thumb| Dr. Justine Bertrand-Michel ]]<br />
<br />
==Short Biography==<br />
<br />
''' About my Career''' <br />
<br />
I got a PhD in chemistry of biomolecule at the University of Bordeaux and join Inserm with Research Engineer position. I worked for 10 years in a laboratory interested in Nucleic Acid particularly in antisens and aptamer strategy. I then switched to the exciting world of lipids : I created the lipidomic facility in Toulouse in 2003 which is now a part of the MetaToul facility dedicated to Metabolomics, Fluxomic and Lipidomic to whom I am Co-director. In 2013, I created with 3 colleagues the Lipidomysts French network that include people who analyzed lipids in France. This include 80 people who meet every year for two days to discuss lipidomic technics and protocoles. <br />
<br />
''' About my Facility and my Work''' <br />
<br />
My facility is a located in the Institut of Cardiovascular and Metabolic Diseases, so our main projects are in the field of health. And is a part of MetaToul which brings together expertise (35 Engineer and students) and means (MS, NMR) in the field of global analysis of metabolism. I am in charge of a group of 7 full time persons dedicated to lipidomic with targeted (especially minor lipids such as oxylipine, oxysterols, new lipopeptids…) and global approaches (using SFC QTOF). My facility is a part of the French National Infrastructure (MetaboHUB) where I am in charge of the Lipidomic group and Services Work Package. I am involved in different scientific council (GERLI, Dijon, Montpellier and Chatenay Malabry Lipidomic Facilities), in Meeting organization : 2016 GERLI Meeting, 2017 European Lipidomic Meeting, 2020 Metabomeeting and in raviewing activity in J Chrom, Anal. Chem, EJON, ACA, Scientific Report, Food Chem, Metabolites, Metabolomic…<br />
<br />
Lipidomic is a huge and complex domain it is why I think it is essential to share discussions, results and workflows together so I am involved in the French Lipidomyst Network, in International Ring Tests (such as Ceramide organized by Singapore), in Standard Lipidomic Initiative and International Lipidomic Society.<br />
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<br />
==Expert Opinion==<br />
===Question 1===<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations?'''<br />
<br />
I am chemist and I wanted to be useful in biology, so when I change of lab 18years ago with this opportunity to create a new facility in lipidomic in Toulouse (South of France), I thought that would be a good chance to use my expertise in analytical chemistry for various project in health. The complexity and the variety of molecule studied in metabolomic (and even worse in lipidomic) immediately fascinated me.<br />
<br />
===Question 2===<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
Like usually we offer service on a lot of different project connected to cancer, inflammation diseases, microbiote, platelet and adipose tissues…But at the moment our main developments are focused on a global lipidomic profile by supercritical fluid chromatography which will to permit the relative quantification of around 550 species in plasma, on automation of sample preparation (which is a real bottler neck in lipidomic) and on the discovering of new lipopeptides in bacteria.<br />
<br />
===Question 3===<br />
<br />
''' 3. As the head of the MetaToul lipidomic facility, what are the most exciting aspects of studying lipids in biological systems? '''<br />
<br />
What I really like in my job is to work with different researcher in a lot of different domain. Each new project is a new challenge: it is a meeting with a researcher and a new scientific problematic. I have to be able to catch quickly what will be the best approaches, the best technic and the best lipids to study to bring the most important information and to be able to answer the questions asked in a specific experiment. I like to put our expertise at the disposal of a project and to organize the team (5 to 7 Engineers) to best respond to demand. <br />
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===Question 4===<br />
<br />
''' 4. What is the biggest challenge when developing new methods for lipidomics? '''<br />
<br />
I would see 4 main points : <br />
-Due to the complexity of this family of molecule, each new development or new organism to study is a new challenge for the analytical part but also for the sample preparation which shouldn’t be neglected. <br />
- There are quite few pure standards available for lipids (it is a huge family) so correct annotation is always a bit tricky and need to be conducted very carefully<br />
- Due to this lack of standard and to the mass spectrometry technology (which is not a good quantitative tool), absolute quantification of lipids is often impossible.<br />
- and finally, like for metabolomics, it is still really complicated to compare two series which have been analysed at different period which a real nightmare specially for very long series or for clinical data.<br />
<br />
===Question 5===<br />
<br />
''' 5. You have worked with both the academic and private sector. What are the main differences working in these environments? '''<br />
<br />
The difficulty to work with the private company is that very often we don’t really know what we are analysing, so for me it is less interesting than working with academic colleague where we can go deeper in the project so be more implicated in it.<br />
<br />
===Question 6===<br />
<br />
''' 6. What are your recommendations for people getting started in lipidomics? '''<br />
<br />
To be a good chemist ! <br />
We need to understand the biophysic properties of our molecule of interest to be able to extract and analyse them properly, so basic notions in organic chemistry are essential to understand and develop method in our field. Lipid can be analysed with different chromatographic system (gas, liquid,supercritical fluid, thin plate) coupled or not with mass spectrometry so the more technic you will know the best it will be !<br />
<br />
<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Category:Expert_Opinion&diff=1201Category:Expert Opinion2021-04-15T16:06:34Z<p>EvelinaCharidemou: </p>
<hr />
<div>== Archive ==<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|1. Dr Justin J.J. van der Hooft]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|2. Dr Carla Antonio]]<br />
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[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|3. Dr Stacey Reinke]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|4. Professor Mark Viant]]<br />
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[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|5. Professor Warwick (Rick) Dunn]]<br />
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[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|6. Dr Nichole Reisdorph]]<br />
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[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|7. Associate Professor Jessica Lasky-Su]]<br />
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[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|8. Dr. Augustin Scalbert]]<br />
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[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|9. Dr. Kazuki Saito]]<br />
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[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [[Roy Goodacre|10. Professor Roy Goodacre]]<br />
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[[Image:Pieter_Dorrestein.jpg|75px|link= Pieter Dorrestein]] [[Pieter Dorrestein|11. Professor Pieter Dorrestein]]<br />
<br />
[[Image:Justine_Bertrand-Michel.jpg|75px|link= Justine Bertrand-Michel]] [[Justine Bertrand-Michel|12. Dr. Justine Bertrand-Michel]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=File:Justine_Bertrand-Michel.jpg&diff=1200File:Justine Bertrand-Michel.jpg2021-04-15T16:04:55Z<p>EvelinaCharidemou: </p>
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<div></div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Category:Expert_Opinion&diff=1199Category:Expert Opinion2021-04-15T16:04:11Z<p>EvelinaCharidemou: </p>
<hr />
<div>== Archive ==<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|1. Dr Justin J.J. van der Hooft]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|2. Dr Carla Antonio]]<br />
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[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|3. Dr Stacey Reinke]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|4. Professor Mark Viant]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|5. Professor Warwick (Rick) Dunn]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|6. Dr Nichole Reisdorph]]<br />
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[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|7. Associate Professor Jessica Lasky-Su]]<br />
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[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|8. Dr. Augustin Scalbert]]<br />
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[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|9. Dr. Kazuki Saito]]<br />
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[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [[Roy Goodacre|10. Professor Roy Goodacre]]<br />
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[[Image:Pieter_Dorrestein.jpg|75px|link= Pieter Dorrestein]] [[Pieter Dorrestein|11. Professor Pieter Dorrestein]]<br />
<br />
[[Image:Justine_Bertrand-Michel.jpg|75px|link= Justine Bertrand-Michel]] [[Justine Bertrand-Michel|11. Dr. Justine Bertrand-Michel]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Pieter_Dorrestein&diff=1165Pieter Dorrestein2021-03-15T17:43:28Z<p>EvelinaCharidemou: Created page with " Professor Pieter Dorrestein ==Short Biography== Dorrestein is Professor at the University of California - San Diego. He is the Direct..."</p>
<hr />
<div>[[Image: Pieter_Dorrestein.jpg|thumb| Professor Pieter Dorrestein]]<br />
<br />
==Short Biography==<br />
<br />
Dorrestein is Professor at the University of California - San Diego. He is the Director of the Collaborative Mass Spectrometry Innovation Center and a Co-Director, Institute for Metabolomics Medicine in the Skaggs School of Pharmacy & Pharmaceutical Sciences, and Department of Pharmacology and Pediatrics. Although Born in Utrecht, the Netherlands, Dorrestein did his undergraduate in metalloorganic chemistry at Northern Arizona University under guidance of Prof MacDonald and his graduate work in mechanistic enzymology at Cornell University under guidance of Prof. Begley. He performed his post-doctoral work as an NIH through and NRSA fellowship in top-down proteomics in the lab of Prof. Kelleher. Since his arrival to UCSD in 2006, Prof. Dorrestein has been pioneering the development of mass spectrometry methods to study the chemical ecological crosstalk between microorganisms, including host interactions for agricultural, diagnostic and therapeutic applications. In his spare time Dorrestein likes to spend time with Kathleen, his better half (wife) and awesome daughter Tatiana. He also likes to and garden, rock climb, hike, kayak and mountain bike.<br />
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==Expert Opinion==<br />
===Question 1===<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations?'''<br />
<br />
As a graduate student, I was studying the mechanistic enzymology of how bacteria made vitamins. Initially, I did the synthesis of small molecules as mechanistic probes to understand the mechanisms by which the enzymes work but then pivoted to the analysis of the proteins by mass spectrometry. A large part of this work involved genome mining where we predicted the molecules that were made by gene clusters on bacterial genomes or the prediction of the roles and mechanisms by which small molecules were biosynthesized. This led to the discovery of a new biosynthetic pathway to make methionine in actinomycetes, a new strategy for bacteria to make vitamin B1 and many other examples. We were studying the intact proteins and their modifications they undergo during biosynthesis by top-down mass spectrometry that were involved in the biosynthesis. As a post-doc and as an assistant professor I expanded this work to study how small molecules are made by non-ribosomal peptide synthetases and polyketide synthetases using top and middle down proteomics methodologies as many of our therapeutic agents. (penicillin, vancomycin and lovastatin are made via those biosynthetic paradigms). <br />
<br />
But I was always very curious about the roles microbial small molecules played in their respective ecosystems (e.g. human, ocean, agriculture, environments, etc). questions such as "How do microbes use molecules to communicate with each other? or "How do microbes communicate with the host?" or "How do chemical milieu shape microbial communities?". In asking these questions and trying to solve them it became quickly evident that there were insufficient tools that could be widely employed. I realized this in my second year as an assistant professor and switched the entire lab, that was dedicated to doing top and middle down proteomics, to the study of small molecules within a two month period. I was strongly advised by senior co-workers not to make s dramatic switch as it would hurt my career. But decided that this is what I wanted to do scientifically and therefore proceeded.<br />
<br />
In this transition, we developed strategies such as microbial imaging mass spectrometry that allowed the investigation of the metabolic exchange of two or more microbes grown in Petri-dishes. This was so illuminating. However, while we got easy to interpret images in terms of metabolic exchange or communication, they were m/z signals. Translating the m/z signals to molecules turned out to be the most time-consuming and difficult part. In addition, it was not only one molecule but often panels or molecules that could be observed, each with different functions that could be detected. And then they were often only present in small quantities or unstable to isolation. One key limitation is that most microbial molecules are not covered in MS/MS-based reference libraries. This is because reference libraries are largely obtained from commercially available molecules. Thus new methods needed to be developed for the annotation and structural annotation or classification of the microbial molecules to allow the interpretation of the images. We therefore first leveraged our strength in genome mining and developed strategies to link mass spec signals to microbial genomic information. peptidogenomics, glycogenomics, leading to the tools such as NRPquest, RippQuest and Pep2Path and several others. Such work is still done in my lab through the many wonderful collaborations the lab still has in this area. However, they do not work for many classes of molecules.<br />
<br />
This led to another major shift in the lab, the shift from microbial imaging to the analysis of global data. This started with the introduction of molecular networking. From genome mining, we realized the importance of being able to compare two or more sequencing. From this one could infer modifications to the sequence. Around that time people just started to create networks of genes and infer function from them. By analogy, if we compare two MS/MS spectra and even though the parent mass are not the same but the overall MS/MS were (while taking in account the ions that differ by the same masses as the parent mass) then we could infer the structures were related. I gave my co-worker and collaborator Dr. Bandeira a DDA acquired data set of Bacillus subtilis and asked if he could give me a table with three columns. In the first two columns an MS/MS spectral ID of each spectrum to each spectrum and then in the third column and then I would look at it. But my jaw dropped when I looked and inspected the first molecular network. We had a very difficult time publishing the first paper on molecular networking with eight rejections. Only about 1 in 5 people understood the implications of molecular networking right away all others not until they tried with their own data. I got the paper published as I called an editor, the late Jerrold Meinwald, and told them this was the most impactful paper I have created in my scientific career to date and he was willing to listen and get it reviewed. I not only realized molecular networking is a key strategy to tackle the annotation problem but also that this is the key ingredient to start building the Google search engine equivalent of the world's MS/MS data. However, it meant that we also needed to get all that data and create an infrastructure that would capture the world's mass spectrometry data and knowledge associated with this data and make this freely accessible to the world. We are getting closer and closer to that goal.<br />
<br />
This set of the movement to building the global natural product social (GNPS) molecular networking analysis ecosystem that now has more than 300,000 accessions a month and has processed 3.2 million tasks through the submission of 200,000 jobs. The focus of the Bandeira lab had been to develop data storage called MassIVE for proteomics data, this was instrumental for the ability to develop GNPS. A student of his, in computer science, and now a postdoc in my lab, Mingxun Wang, led the development of the GNPS infrastructure but was originally only a small side project as a student. But the worldwide community saw the value of GNPS and it spawned so many wonderful collaborations. A key underappreciated aspect of GNPS is that this is provided for free to the community, and is made possible by hosting and maintaining 70 ft of server and compute hardware, an scientific engineering feat in its own right and is not documented in any publication. But as the community and the more users use the GNPS ecosystem and the more collaborations it initiates the more useful the analysis ecosystem becomes and are seeing an explosion of new tools, many of which build in the lab and in collaborations. For the first time, all publicly available reference spectra could be searched in one go, one could perform molecular networking to propagate annotations, introduce feature-based molecular networking and made it so that it functions together with many feature finding tools such as MZmine, OpenMS, XCMS, MS-DIAL, mzTab-M, and vendor feauture finding software. It also became possible that public data sets could be searched all without having to download data and converting the data to a format that the user could analyze as this was already done. We have introduced MS/MS searches called MASST across all public data so one can find all data files that contain the same MS/MS spectra of interest. This is useful as it allows one to ask simple questions such as is the discovery of this new molecule in an animal translational to people? or is this molecule found in people, host, diet or mycobiome derived? We have to build ReDU, a metadata-driven strategy, that allows searches of all data that contain specific annotation or allows for co-analysis of data that is filtered based on specific metadata. For example, filtering based on age and sex for clinical data or longitude /latitude for environmental data. Basically, these developments are early versions of the types of search engines we want to build. <br />
<br />
<br />
===Question 2===<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
I like to rephrase this in "What has the lab and world-wide collaborators been working on recently?" as this reflects the way the lab functions. We are working with a worldwide community to address some key and fundamentally important tools to allow us to understand all the information that is collected in untargeted mass spectrometry experiments. There are now 50 different tools available in GNPS. Some recent tools such as Passatuto (FDR estimator for spectral matching), Sirius, Zodiac (MF predictors), MS2LDA (substructure classification), Spec2Vec (a method that allows molecular networking when two or more modifications are present), CANOPUS (structural classification of MS/MS), Deprelicator, CSI:fingerID, NAP (In silico predictions), Qemistree (Visualization strategy of MS/MS similarity trees), Ion Identity networking (a molecular networking strategy that also networks based on peak shape analysis to find different ions of the same molecule), Native Spray based metal-small molecule discovery (Many molecules do not work without their metal counterpart and thus is a workflow that allows one to discover potential metal-small molecule pairs) are some of the key advances that are assisting in the deeper annotation of the untargeted metabolomics data.<br />
<br />
However, we are also interfacing GNPS with important third-party tools. For example, Cytoscape, developed by our co-worker Ideker. We now have a direct export into Cytoscape to visualize the results. We have linked GNPS to BIGscape, Natural Product atlas and iOMEGA to link gene clusters and microbial moelcules. We have direct connections to MONA via HASHtags so that public spectra can be searched. And to allow high-level statistical, multivariate analysis, ratio analysis, machine learning we export the result into a QIIME and QIITA format, that the Knight lab, another co-worker at UC-San Diego developed. While designed for the analysis of microbiome data from an ecological standpoint, they are one of the most advanced platforms for quantitative data analysis and visualization that is currently available in the scientific community. At the same time, GNPS is also compatible with more widely used tools such as Metabolanalyst, one of our favorite analysis programs we routinely use and Jupyter notebooks, which allows for improved reproducibility of custom scientific analysis and sharing of the code. Integration with other infrastructures has also been critical to developing new methods such as MMVec that learn microbe-metabolite relationships. <br />
<br />
There are also some additional new developments that are emerging that will become available through GNPS in the near future. 1) A new reference library of propagated annotations from the entire repository 2) A new Google doc equivalent for data analysis so that one can do data analysis with multiple people, share the content and then others can continue where the first person left off. 3)Tagging of molecules for ease of interpretation of the data. 4) Reference-based metabolomics that annotates not based on the structure but source. 5) we are developing new strategies to understand if molecules are microbial derived or not. 6) we are particularly excited to develop strategies that allow the understanding of diet to microbial community relationships and are developing a series of tools to address that need. 7) we are also excited to begin building connections to Metabolights, the European metabolomics repository. Ultimately we want all these results and knowledge gained from all the above-mentioned tools and others that were not mentioned be available from a single search and be distributed worldwide.<br />
<br />
===Question 3===<br />
<br />
''' 3. What are some challenges when characterizing the metabolic interactions between microbes? '''<br />
<br />
The small quantities and the many unique molecules they produce are not commercially available. There are now some 29,000 known microbial molecules but only a few hundred reference spectra are available of microbial metabolites. It means that even if the structures are known one still will not know. Thus it is critical to deposit reference spectra of any new structure that is determined so that the worldwide community does not spend time and a significant amount of money to solve a known structure. <br />
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===Question 4===<br />
<br />
''' 4. Do you envision your work on identifying small molecules involved in these dynamic interactions being translated into improved human health? '''<br />
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Yes, I strongly believe that many of these molecules are potential candidates to solve medical challenges. Companies license technologies directly from our university UC San Diego for this purpose. I am also on the scientific advisory boards of Sirenas, which explores the oceans for new molecules that benefit human health; Cybele Microbiome, and is developing a specific molecule to promote skin health; Galileo, which discovers human microbiome-derived molecules for human health and then, as approved by UC San Diego, I am also a co-founder Ometalabs that provides mass spectrometry analysis capabilities and infrastructure solutions for instances when companies, agencies or individuals cannot use public infrastructure or that do not want their data to be public for IP reasons and I am a co-founder of Enveda Biosciences, that is translating plant-derived molecules into medicine.<br />
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===Question 5===<br />
<br />
''' 5. As one of the creators of the Global Natural Products Social Molecular Networking (GNPS), what are the challenges when characterizing metabolites within complex mixtures or samples? '''<br />
<br />
I already mentioned some of the challenges due to the lack of available standards. But some of the other challenges are that GNPS is build for and by the community. We want to make the infrastructure fair for everyone and truly democratize metabolomics analysis. This means that a high school student will have the same compute capacity as a seasoned expert with 50 years of experience or that anyone with access to the internet can do large scale analysis and have access to the same knowledge as everyone else. We also wanted to reduce the barrier of entry by making sure all the data is already converted to a common data format (mzML, mzXML or MGF). Thus the limit then becomes how creative is the person doing the analysis. It has been amazing to see the solutions that the community has been developing using the GNPS infrastructure, oftentimes in very creative and unexpected ways. For example, the first hints of a molecule called colibactin, an E.coli derived molecule that causes cancer, was discovered using molecular networking and feeding studies but there are many such examples. But the real challenge is the lack of sharing data and annotations associated with the data. Imagine what the community can do if all the metabolomics data and annotations associated with it that everyone collects is available at your fingertips. This will transform our understanding of not only microbial metabolites but also relationships to health, xenobiotics, diet etc. This capacity will also transform the types of questions we can address and will ask. This is a transition that is happening and cannot wait to see how the next generation of metabolomics scientists leverage this information.<br />
<br />
===Question 6===<br />
<br />
''' 6. What are your recommendations for people getting started in microbial metabolomics? '''<br />
<br />
Currently, GNPS houses the most information on the metabolomics of microbial reference data thus GNPS is a good starting point. I would also familiarize myself with QIIME and QIITA. There are online tutorials and workshops available, attend them. Reach out to the authors, not only PIs, but the researchers that are listed first. They all get excited to help newcomers out with getting started. Also consult other infrastructures such as Metabolights, Metabolomics WBs, XCMSonline, NP atlas, there are lots of gems to be found. In addition, make your data available and early. For example, your data becomes searchable in MASST, ReDU but also becomes part of living data thus you can subscribe to your data and then if any new matches to your data become available from spectral libraries you will get an email and ensures that you do not miss any new annotations. More importantly, there are many microbial MS/MS spectra annotated in GNPS that are not yet published and then you can collaborate with the authors that deposited those spectra. In other words, become part of the community, if there is a tool you want to apply but don't know how to get started reach out directly to the authors or use forums. GNPS has it own forum linked in the GNPS banner for GNPS questions, as do the QIIME or Cytoscape analysis and data visualization tools but also the metabolomics society has a forum.<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Category:Expert_Opinion&diff=1164Category:Expert Opinion2021-03-15T17:37:28Z<p>EvelinaCharidemou: </p>
<hr />
<div>== Archive ==<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|1. Dr Justin J.J. van der Hooft]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|2. Dr Carla Antonio]]<br />
<br />
[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|3. Dr Stacey Reinke]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|4. Professor Mark Viant]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|5. Professor Warwick (Rick) Dunn]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|6. Dr Nichole Reisdorph]]<br />
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[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|7. Associate Professor Jessica Lasky-Su]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|8. Dr. Augustin Scalbert]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|9. Dr. Kazuki Saito]]<br />
<br />
[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [[Roy Goodacre|10. Professor Roy Goodacre]]<br />
<br />
[[Image:Pieter_Dorrestein.jpg|75px|link= Pieter Dorrestein]] [[Pieter Dorrestein|11. Professor Pieter Dorrestein]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=File:Pieter_Dorrestein.jpg&diff=1163File:Pieter Dorrestein.jpg2021-03-15T17:35:25Z<p>EvelinaCharidemou: </p>
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<div></div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Roy_Goodacre&diff=1149Roy Goodacre2021-02-15T13:14:07Z<p>EvelinaCharidemou: </p>
<hr />
<div>[[Image: Roy_Goodacre.png|thumb| Professor Roy Goodacre]]<br />
<br />
==Short Biography==<br />
<br />
Roy Goodacre is Professor of Biological Chemistry at the University of Liverpool. At Liverpool he is a director of the Centre for Metabolomics Research, Chair of the Institute of Systems, Molecular and Integrative Biology (ISMIB) research committee, and Deputy Head of the Department of Biochemistry and Systems Biology. <br />
<br />
Roy is the founder and current Editor-in-Chief of the peer-reviewed scientific journal Metabolomics. A Director of the Metabolomics Society (2005-2015 & 2020-) and since 2008 also a Director of the Metabolic Profiling Forum.<br />
<br />
Roy’s full biography can be found here [https://en.wikipedia.org/wiki/Roy_Goodacre]<br />
<br />
==Expert Opinion==<br />
===Question 1===<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations?'''<br />
<br />
That’s an interesting question, and one that actually has a rather long answer. This is because metabolomics as a discipline didn’t exist when I started conducting research.<br />
<br />
I started my PhD in the late 1980s where I was developing and applying pyrolysis-mass spectrometry (Py-MS, not to be confused with Pimm’s…) for the characterisation of bacteria. What I did was genetically modify bacteria by inserting plasmids (and curing some bacteria of these mobile elements), looking at gene knocking outs, as well as altering growth media to elicit specific phenotypic effects. These were then analysed using Py-MS. Pyrolysis was used to get non-volatile material (i.e., bacteria) into the gas phase for MS analysis. Back then MALDI and ESI were only just starting to be developed and applied, and of course people will remember that Koichi Tanaka and John Fenn shared the Nobel Prize in Chemistry in 2002 for developing MALDI and ESI for analysis of biological macromolecules. This was 14 years after my initial Py-MS experiments.<br />
<br />
These pyrolysis-mass spectra were complex (150 ion count values at amu from 51-200 m/z) and so I had to learn how to use multivariate analysis (chemometrics) within Genstat on a mainframe computer. That was quite scary – although not as scary as my PhD viva as I stupidly put all the equations for PCA, CVA and hierarchical clustering in my thesis. My internal examiner spent some considerable time asking me to derive these. I still get cold sweats when I think of this!<br />
<br />
After my PhD in Bristol, I did a post doc with Doug Kell in Aberystwyth where we developed Py-MS for quantitative analysis of bioprocesses using artificial neural networks (ANNs) and partial least squares regression (PLSR) for analysis of these spectra. During this time I went to many analytical pyrolysis conferences and met up with similar minded scientists. I met Rick Higashi from the University of Kentucky at these and he was using Py-GC-MS to understand soil chemistry. Rick as you know is a fellow ‘metabolomer’ and when we reconnected on the metabolomics conference circuit a decade or so later, we were both bemused and happy to see one another again.<br />
<br />
This history tells you that I was already using bioanalytical methods based on mass spectrometry to look at biological systems, and of course to analyse these data using chemometrics. This sounds a lot like metabolomics to me! I'm not the only person to have said this. Jan van der Greef from TNO and Leiden University, who was an early adopter of metabolomics for investigating health and disease, had come across the pioneering early work in Py-MS for bacterial analysis in The Netherlands by Henk Meuzelaar and Jaap Boon. Jan along with Age Smilde wrote about this scientific evolution of metabolomics with respect to chemometrics in 2005 where they mention pyrolysis-mass spectrometry being part of that journey [see J. Chemometrics 19, 376-386: https://doi.org/10.1002/cem.941].<br />
<br />
===Question 2===<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
Our research group is quite agnostic in terms of the sorts of biological systems that we analyse. These range from the analysis of human systems in health and disease, mammalian systems, as well as plants and microbial systems – in fact pretty much anything you can squirt into a mass spectrometer!<br />
<br />
That said, what currently drives us at the University of Liverpool is to try and understand bacterial responses to stress. We have worked in the past looking at bacterial adaptation when they encounter human drugs – this was initially from an environmental point of view, as many pharmaceuticals end up in the environment. Rivers are full of, amongst other things, anti-inflammatories like ibuprofen and diclofenac, as well as the beta-blocker propranolol, and these drugs may inadvertently alter metabolism within microbial communities. I also wonder what bacteria think of when they get a good glug of caffeine when we’ve excreted this after our morning fix! Do they get a similar buzz? I don’t know. <br />
<br />
An environment closer to home is the microflora within your gut. I think that it will be important to understand how this complex community responds to these stresses, especially as the human population is ageing and many people take drugs to stay fit and healthy. What is also becoming increasingly recognised is the link between bacteria and disease where there doesn’t seem to be any obvious microbiological link. The gut microbiome in humans has been implicated in many human diseases including amongst others Alzheimer's and Parkinson’s. A great table summarising these links is in this review by Etheresia Pretorius and Doug Kell [Table 3: FEMS Microbiol. Rev. 39, 567-591: https://doi.org/10.1093/femsre/fuv013].<br />
<br />
In addition to working in this area, we do have a particular focus on antimicrobial resistance (AMR). This urgently needs to be addressed and if you’ve read Jim O’Neill report on AMR [https://amr-review.org], he has stated that if left unaddressed AMR bacteria could kill 10 million people per year by 2050, this would surpass the current cancer mortality.<br />
<br />
===Question 3===<br />
<br />
''' 3. What are the main challenges for developing mass spectrometry-based metabolomics for long-term studies? '''<br />
<br />
I think there are several and most of them are not the analytics itself. The challenges are the wrapping at each end of the MS analyses and these are bound in computational analyses in terms of actually planning these experiments and what you do with the metabolomics data once they have been generated.<br />
<br />
During my career I’ve had the privilege of working with some outstanding scientists in this area. Most notably Dave Broadhurst and Rick Dunn, where we along with Doug Kell, Ian Wilson and many others established a series of protocols that allowed long-term collection of data over periods of 12 to 18 months. For those who haven’t seen our paper from 2011 it is here [Nature Protocols 6, 1060-1083: https://doi.org/10.1038/nprot.2011.335]. The key thing that we developed was the use of biological QCs that are analysed throughout the GC-MS and LC-MS runs. <br />
<br />
These QCs serve two purposes. The first is a rather basic one – if one uses an unsupervised learning method like PCA to analyse all the data (samples plus QCs) then in the PCA scores plots, if the QCs cluster together very close to the origin (they are of course the average sample) then one can have confidence in the reproducibility of the experiment. The second which really Dave pioneered, was to use the QCs to correct for local instrument drift throughout these analytical runs. I think the main challenge is to get this right. And, of course, how to do this when you don’t have the ideal QC at the start of the experiment. This is something we have tried to address in a recent review we published in Metabolomics in 2018 [14: 72: https://doi.org/10.1007/s11306-018-1367-3].<br />
<br />
===Question 4===<br />
<br />
''' 4. You have developed a variety of different Raman spectroscopy approaches for bioanalysis. What do you think is the future of Raman spectroscopy in metabolomics? '''<br />
<br />
I think Raman spectroscopy can be highly beneficial to metabolomics in several areas.<br />
<br />
Generally speaking, Raman is not chemically specific and gives an overall biochemical fingerprint of the sample. The provenance of the sample can then be assessed using chemometrics (the same multivariate analysis that people use in MS or NMR metabolomics). The advantage that this method has is that it can be delivered in a handheld portable format. Therefore, the spectrometer can go to the patient rather than the other way round. This could be readily employed in patient triage scenarios. Although not for clinical purposes, I used a handheld Raman instrument to measure Aboriginal Rock art in Kimberly, Australia in 2019 [https://rockartaustralia.org.au]. The aim was to use Raman spectroscopy to investigate the chemistry of pigments used in the rock art. It was very cool and exciting!<br />
<br />
Now whilst I said Raman was not chemically specific, one can make it so by coupling Raman spectroscopy with sensing devices based on gold or silver nanoparticles, that have nano-plasmonic properties. This is called surface-enhanced Raman spectroscopy (SERS). When SERS is done properly it can be used in a multiplexed fashion to sense many molecules simultaneously and can generate highly quantitative results. This is not metabolomics per se, as it is now a targeted biochemical assay. You can hopefully see within the metabolomics pipeline that Raman could be a game changer where the analysis of several small molecule biomarkers in population sizes of 10,000-100,000 patients is needed at point of care.<br />
<br />
The other area where Raman spectroscopy is exciting is the ability to couple this with microscopy and to image single cells with a pixel resolution of around 500 nm. Raman is not affected by water (unlike infrared spectroscopy) and this method is also non-destructive – two great assets for the analysis of delicate biological material.<br />
<br />
I hope that the metabolomics community hears a lot more about Raman spectroscopy in the future.<br />
<br />
===Question 5===<br />
<br />
''' 5. You are part of the UK Consortium for MetAbolic Phenotyping (MAP UK) project. What are the advantages and disadvantages for using metabolomics in large-population cohorts? '''<br />
<br />
I am indeed a small cog within MAP/UK (https://mapuk.org) where our aim is to create a unified platform that will make metabolic phenotyping robust, routine, and reproducible across the UK. I think the advantages are clear. If this MRC funded project is successful then this will be fantastic for the metabolomics community as scientists will be able to work together on common projects, share robust and validated protocols for untargeted metabolomics and targeted assays, and of course more readily share data. This is certainly needed for large-scale multi-centre studies. I actually don’t see any disadvantages in this. I do see the challenges. The most obvious one is to get everyone to agree on specific analytical approaches. For example, many of us use LC-MS for metabolomics, but how many of us use exactly the same stationary phase, and how many of us employ exactly the same gradient elution in the mobile phase. We need adoption of common protocols, or neat computational methods to account for retention time changes between different laboratories, so that metabolite identification is more robust which will lead to more accurate metabolite quantification.<br />
<br />
===Question 6===<br />
<br />
''' 6. You helped established the Centre for Metabolomics Research at the University of Liverpool. How has this shaped your career and what is your advice for early career researchers starting in metabolomics? '''<br />
<br />
It’s being an important part of my academic and research journey. I started off as a bacteriologist in a microbiology department in Bristol and during that time was exposed to analytical methods and data processing. When I moved to Aberystwyth, I got immersed in a group that was really doing exciting high-level computational biology – the first paper we published was on the application of neural networks to address olive oil adulteration. After that I moved to the chemistry department in UMIST in 2003 and I got more heavily involved in analytics and at that time metabolomics start to emerge as an exciting new science. UMIST and the Victoria University of Manchester merged shortly after I arrived in 2004. A couple of years later I moved into the Manchester Institute of Biotechnology where the focus was on interdisciplinary science and brought together scientists from very different disciplines. Although I enjoyed my time in a chemistry department it has been great to have moved in 2018 back into a biological department in the University of Liverpool where the focus is on biochemistry, systems, as well as molecular integrative biology. We have exciting opportunities within the Centre for Metabolomics Research (CMR) and this really drives me. There is great potential to fuse mass spectrometry-based metabolomics with a variety of Raman and infrared spectroscopies that we are developing. Watch this space .<br />
<br />
So, what advice would I give ECRs starting in metabolomics. That’s a great question and I think there are many different things I’d suggest anyone to consider. I think the first is to find a research area, perhaps a little bit niche, that one can be passionate about and committed to. Also, to consider that it takes years to establish something that you can feel proud of so patience and perseverance are essential. Developing a thick skin can also help as with every scientific area there will be failures that can be learnt from. Starting anything new will be challenging and so finding a good mentor is critical – I’ve been very lucky in my career to be supported by great mentors. Not only in terms shaping me as a scientist who can be independent, but also grounding me when I get a little too carried away. I think having the right mentor is the key thing. As well as being a great research scientist they should be inspirational and have good leadership qualities. At the same time being a good citizen who cares more about you, the research question, than promoting themselves.<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Roy_Goodacre&diff=1148Roy Goodacre2021-02-15T13:08:47Z<p>EvelinaCharidemou: Created page with " Professor Roy Goodacre ==Short Biography== Roy Goodacre is Professor of Biological Chemistry at the University of Liverpool. At Liverpool..."</p>
<hr />
<div>[[Image: Roy_Goodacre.png|thumb| Professor Roy Goodacre]]<br />
<br />
==Short Biography==<br />
<br />
Roy Goodacre is Professor of Biological Chemistry at the University of Liverpool. At Liverpool he is a director of the Centre for Metabolomics Research, Chair of the Institute of Systems, Molecular and Integrative Biology (ISMIB) research committee, and Deputy Head of the Department of Biochemistry and Systems Biology. <br />
<br />
Roy is the founder and current Editor-in-Chief of the peer-reviewed scientific journal Metabolomics. A Director of the Metabolomics Society (2005-2015 & 2020-) and since 2008 also a Director of the Metabolic Profiling Forum.<br />
<br />
Roy’s full biography can be found here [https://en.wikipedia.org/wiki/Roy_Goodacre]<br />
<br />
==Expert Opinion==<br />
===Question 1===<br />
<br />
"1. When and why did you start using metabolomics in your investigations?" <br />
<br />
That’s an interesting question, and one that actually has a rather long answer. This is because metabolomics as a discipline didn’t exist when I started conducting research.<br />
<br />
I started my PhD in the late 1980s where I was developing and applying pyrolysis-mass spectrometry (Py-MS, not to be confused with Pimm’s…) for the characterisation of bacteria. What I did was genetically modify bacteria by inserting plasmids (and curing some bacteria of these mobile elements), looking at gene knocking outs, as well as altering growth media to elicit specific phenotypic effects. These were then analysed using Py-MS. Pyrolysis was used to get non-volatile material (i.e., bacteria) into the gas phase for MS analysis. Back then MALDI and ESI were only just starting to be developed and applied, and of course people will remember that Koichi Tanaka and John Fenn shared the Nobel Prize in Chemistry in 2002 for developing MALDI and ESI for analysis of biological macromolecules. This was 14 years after my initial Py-MS experiments.<br />
<br />
These pyrolysis-mass spectra were complex (150 ion count values at amu from 51-200 m/z) and so I had to learn how to use multivariate analysis (chemometrics) within Genstat on a mainframe computer. That was quite scary – although not as scary as my PhD viva as I stupidly put all the equations for PCA, CVA and hierarchical clustering in my thesis. My internal examiner spent some considerable time asking me to derive these. I still get cold sweats when I think of this!<br />
<br />
After my PhD in Bristol, I did a post doc with Doug Kell in Aberystwyth where we developed Py-MS for quantitative analysis of bioprocesses using artificial neural networks (ANNs) and partial least squares regression (PLSR) for analysis of these spectra. During this time I went to many analytical pyrolysis conferences and met up with similar minded scientists. I met Rick Higashi from the University of Kentucky at these and he was using Py-GC-MS to understand soil chemistry. Rick as you know is a fellow ‘metabolomer’ and when we reconnected on the metabolomics conference circuit a decade or so later, we were both bemused and happy to see one another again.<br />
<br />
This history tells you that I was already using bioanalytical methods based on mass spectrometry to look at biological systems, and of course to analyse these data using chemometrics. This sounds a lot like metabolomics to me! I'm not the only person to have said this. Jan van der Greef from TNO and Leiden University, who was an early adopter of metabolomics for investigating health and disease, had come across the pioneering early work in Py-MS for bacterial analysis in The Netherlands by Henk Meuzelaar and Jaap Boon. Jan along with Age Smilde wrote about this scientific evolution of metabolomics with respect to chemometrics in 2005 where they mention pyrolysis-mass spectrometry being part of that journey [see J. Chemometrics 19, 376-386: https://doi.org/10.1002/cem.941].<br />
<br />
===Question 2===<br />
<br />
"2. What have you been working on recently?"<br />
<br />
Our research group is quite agnostic in terms of the sorts of biological systems that we analyse. These range from the analysis of human systems in health and disease, mammalian systems, as well as plants and microbial systems – in fact pretty much anything you can squirt into a mass spectrometer!<br />
<br />
That said, what currently drives us at the University of Liverpool is to try and understand bacterial responses to stress. We have worked in the past looking at bacterial adaptation when they encounter human drugs – this was initially from an environmental point of view, as many pharmaceuticals end up in the environment. Rivers are full of, amongst other things, anti-inflammatories like ibuprofen and diclofenac, as well as the beta-blocker propranolol, and these drugs may inadvertently alter metabolism within microbial communities. I also wonder what bacteria think of when they get a good glug of caffeine when we’ve excreted this after our morning fix! Do they get a similar buzz? I don’t know. <br />
<br />
An environment closer to home is the microflora within your gut. I think that it will be important to understand how this complex community responds to these stresses, especially as the human population is ageing and many people take drugs to stay fit and healthy. What is also becoming increasingly recognised is the link between bacteria and disease where there doesn’t seem to be any obvious microbiological link. The gut microbiome in humans has been implicated in many human diseases including amongst others Alzheimer's and Parkinson’s. A great table summarising these links is in this review by Etheresia Pretorius and Doug Kell [Table 3: FEMS Microbiol. Rev. 39, 567-591: https://doi.org/10.1093/femsre/fuv013].<br />
<br />
In addition to working in this area, we do have a particular focus on antimicrobial resistance (AMR). This urgently needs to be addressed and if you’ve read Jim O’Neill report on AMR [https://amr-review.org], he has stated that if left unaddressed AMR bacteria could kill 10 million people per year by 2050, this would surpass the current cancer mortality.<br />
<br />
===Question 3===<br />
<br />
"3. What are the main challenges for developing mass spectrometry-based metabolomics for long-term studies?"<br />
<br />
I think there are several and most of them are not the analytics itself. The challenges are the wrapping at each end of the MS analyses and these are bound in computational analyses in terms of actually planning these experiments and what you do with the metabolomics data once they have been generated.<br />
<br />
During my career I’ve had the privilege of working with some outstanding scientists in this area. Most notably Dave Broadhurst and Rick Dunn, where we along with Doug Kell, Ian Wilson and many others established a series of protocols that allowed long-term collection of data over periods of 12 to 18 months. For those who haven’t seen our paper from 2011 it is here [Nature Protocols 6, 1060-1083: https://doi.org/10.1038/nprot.2011.335]. The key thing that we developed was the use of biological QCs that are analysed throughout the GC-MS and LC-MS runs. <br />
<br />
These QCs serve two purposes. The first is a rather basic one – if one uses an unsupervised learning method like PCA to analyse all the data (samples plus QCs) then in the PCA scores plots, if the QCs cluster together very close to the origin (they are of course the average sample) then one can have confidence in the reproducibility of the experiment. The second which really Dave pioneered, was to use the QCs to correct for local instrument drift throughout these analytical runs. I think the main challenge is to get this right. And, of course, how to do this when you don’t have the ideal QC at the start of the experiment. This is something we have tried to address in a recent review we published in Metabolomics in 2018 [14: 72: https://doi.org/10.1007/s11306-018-1367-3].<br />
<br />
===Question 4===<br />
<br />
"4. You have developed a variety of different Raman spectroscopy approaches for bioanalysis. What do you think is the future of Raman spectroscopy in metabolomics?"<br />
<br />
I think Raman spectroscopy can be highly beneficial to metabolomics in several areas.<br />
<br />
Generally speaking, Raman is not chemically specific and gives an overall biochemical fingerprint of the sample. The provenance of the sample can then be assessed using chemometrics (the same multivariate analysis that people use in MS or NMR metabolomics). The advantage that this method has is that it can be delivered in a handheld portable format. Therefore, the spectrometer can go to the patient rather than the other way round. This could be readily employed in patient triage scenarios. Although not for clinical purposes, I used a handheld Raman instrument to measure Aboriginal Rock art in Kimberly, Australia in 2019 [https://rockartaustralia.org.au]. The aim was to use Raman spectroscopy to investigate the chemistry of pigments used in the rock art. It was very cool and exciting!<br />
<br />
Now whilst I said Raman was not chemically specific, one can make it so by coupling Raman spectroscopy with sensing devices based on gold or silver nanoparticles, that have nano-plasmonic properties. This is called surface-enhanced Raman spectroscopy (SERS). When SERS is done properly it can be used in a multiplexed fashion to sense many molecules simultaneously and can generate highly quantitative results. This is not metabolomics per se, as it is now a targeted biochemical assay. You can hopefully see within the metabolomics pipeline that Raman could be a game changer where the analysis of several small molecule biomarkers in population sizes of 10,000-100,000 patients is needed at point of care.<br />
<br />
The other area where Raman spectroscopy is exciting is the ability to couple this with microscopy and to image single cells with a pixel resolution of around 500 nm. Raman is not affected by water (unlike infrared spectroscopy) and this method is also non-destructive – two great assets for the analysis of delicate biological material.<br />
<br />
I hope that the metabolomics community hears a lot more about Raman spectroscopy in the future.<br />
<br />
===Question 5===<br />
<br />
"5. You are part of the UK Consortium for MetAbolic Phenotyping (MAP UK) project. What are the advantages and disadvantages for using metabolomics in large-population cohorts?"<br />
<br />
I am indeed a small cog within MAP/UK (https://mapuk.org) where our aim is to create a unified platform that will make metabolic phenotyping robust, routine, and reproducible across the UK. I think the advantages are clear. If this MRC funded project is successful then this will be fantastic for the metabolomics community as scientists will be able to work together on common projects, share robust and validated protocols for untargeted metabolomics and targeted assays, and of course more readily share data. This is certainly needed for large-scale multi-centre studies. I actually don’t see any disadvantages in this. I do see the challenges. The most obvious one is to get everyone to agree on specific analytical approaches. For example, many of us use LC-MS for metabolomics, but how many of us use exactly the same stationary phase, and how many of us employ exactly the same gradient elution in the mobile phase. We need adoption of common protocols, or neat computational methods to account for retention time changes between different laboratories, so that metabolite identification is more robust which will lead to more accurate metabolite quantification.<br />
<br />
===Question 6===<br />
<br />
"6. You helped established the Centre for Metabolomics Research at the University of Liverpool. How has this shaped your career and what is your advice for early career researchers starting in metabolomics?"<br />
<br />
It’s being an important part of my academic and research journey. I started off as a bacteriologist in a microbiology department in Bristol and during that time was exposed to analytical methods and data processing. When I moved to Aberystwyth, I got immersed in a group that was really doing exciting high-level computational biology – the first paper we published was on the application of neural networks to address olive oil adulteration. After that I moved to the chemistry department in UMIST in 2003 and I got more heavily involved in analytics and at that time metabolomics start to emerge as an exciting new science. UMIST and the Victoria University of Manchester merged shortly after I arrived in 2004. A couple of years later I moved into the Manchester Institute of Biotechnology where the focus was on interdisciplinary science and brought together scientists from very different disciplines. Although I enjoyed my time in a chemistry department it has been great to have moved in 2018 back into a biological department in the University of Liverpool where the focus is on biochemistry, systems, as well as molecular integrative biology. We have exciting opportunities within the Centre for Metabolomics Research (CMR) and this really drives me. There is great potential to fuse mass spectrometry-based metabolomics with a variety of Raman and infrared spectroscopies that we are developing. Watch this space .<br />
<br />
So, what advice would I give ECRs starting in metabolomics. That’s a great question and I think there are many different things I’d suggest anyone to consider. I think the first is to find a research area, perhaps a little bit niche, that one can be passionate about and committed to. Also, to consider that it takes years to establish something that you can feel proud of so patience and perseverance are essential. Developing a thick skin can also help as with every scientific area there will be failures that can be learnt from. Starting anything new will be challenging and so finding a good mentor is critical – I’ve been very lucky in my career to be supported by great mentors. Not only in terms shaping me as a scientist who can be independent, but also grounding me when I get a little too carried away. I think having the right mentor is the key thing. As well as being a great research scientist they should be inspirational and have good leadership qualities. At the same time being a good citizen who cares more about you, the research question, than promoting themselves.<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Category:Expert_Opinion&diff=1147Category:Expert Opinion2021-02-15T13:02:19Z<p>EvelinaCharidemou: </p>
<hr />
<div>== Archive ==<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|1. Dr Justin J.J. van der Hooft]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|2. Dr Carla Antonio]]<br />
<br />
[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|3. Dr Stacey Reinke]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|4. Professor Mark Viant]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|5. Professor Warwick (Rick) Dunn]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|6. Dr Nichole Reisdorph]]<br />
<br />
[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|7. Associate Professor Jessica Lasky-Su]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|8. Dr. Augustin Scalbert]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|9. Dr. Kazuki Saito]]<br />
<br />
[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [[Roy Goodacre|10. Professor Roy Goodacre]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Category:Expert_Opinion&diff=1146Category:Expert Opinion2021-02-15T13:01:13Z<p>EvelinaCharidemou: </p>
<hr />
<div>== Archive ==<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|1. Dr Justin J.J. van der Hooft]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|2. Dr Carla Antonio]]<br />
<br />
[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|3. Dr Stacey Reinke]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|4. Professor Mark Viant]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|5. Professor Warwick (Rick) Dunn]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|6. Dr Nichole Reisdorph]]<br />
<br />
[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|7. Associate Professor Jessica Lasky-Su]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|8. Dr. Augustin Scalbert]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|9. Dr. Kazuki Saito]]<br />
<br />
[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [[Roy Goodacre|10. Roy Goodacre]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Category:Expert_Opinion&diff=1145Category:Expert Opinion2021-02-15T13:00:46Z<p>EvelinaCharidemou: </p>
<hr />
<div>== Archive ==<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|1. Dr Justin J.J. van der Hooft]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|2. Dr Carla Antonio]]<br />
<br />
[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|3. Dr Stacey Reinke]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|4. Professor Mark Viant]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|5. Professor Warwick (Rick) Dunn]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|6. Dr Nichole Reisdorph]]<br />
<br />
[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|7. Associate Professor Jessica Lasky-Su]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|8. Dr. Augustin Scalbert]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|9. Dr. Kazuki Saito]]<br />
<br />
[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [Roy Goodacre|10. Roy Goodacre]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Category:Expert_Opinion&diff=1144Category:Expert Opinion2021-02-15T12:51:42Z<p>EvelinaCharidemou: </p>
<hr />
<div>== Archive ==<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|1. Dr Justin J.J. van der Hooft]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|2. Dr Carla Antonio]]<br />
<br />
[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|3. Dr Stacey Reinke]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|4. Professor Mark Viant]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|5. Professor Warwick (Rick) Dunn]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|6. Dr Nichole Reisdorph]]<br />
<br />
[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|7. Associate Professor Jessica Lasky-Su]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|8. Dr. Augustin Scalbert]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|9. Dr. Kazuki Saito]]<br />
<br />
[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [Roy Goodacre |10. Roy Goodacre]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Category:Expert_Opinion&diff=1143Category:Expert Opinion2021-02-15T12:51:13Z<p>EvelinaCharidemou: </p>
<hr />
<div>[[Image:Roy_Goodacre.png|75px|link= Roy Goodacre]] [Roy Goodacre |10. Roy Goodacre]]<br />
<br />
== Archive ==<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|1. Dr Justin J.J. van der Hooft]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|2. Dr Carla Antonio]]<br />
<br />
[[Image:StaceyReinke.jpg|75px|link= Stacey Reinke]] [[Stacey Reinke|3. Dr Stacey Reinke]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= Mark Viant]] [[Mark Viant|4. Professor Mark Viant]]<br />
<br />
[[Image:RickDunn.png|75px|link= Rick Dunn]] [[Rick Dunn|5. Professor Warwick (Rick) Dunn]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= Nichole Reisdorph]] [[Nichole Reisdorph|6. Dr Nichole Reisdorph]]<br />
<br />
[[Image: Jessica_LaskySu.jpg|75px|link= Jessica Lasky-Su]] [[Jessica Lasky-Su|7. Associate Professor Jessica Lasky-Su]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= Augustin Scalbert]] [[Augustin Scalbert|8. Dr. Augustin Scalbert]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= Kazuki Saito]] [[Kazuki Saito|9. Dr. Kazuki Saito]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=File:Roy_Goodacre.png&diff=1142File:Roy Goodacre.png2021-02-15T12:43:05Z<p>EvelinaCharidemou: </p>
<hr />
<div></div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Kazuki_Saito&diff=1106Kazuki Saito2021-01-18T15:03:48Z<p>EvelinaCharidemou: </p>
<hr />
<div>[[Image: Kazuki_Saito.png|thumb|Official Name Surname of the Expert]]<br />
<br />
==Short Biography==<br />
<br />
Professor Kazuki Saito graduated from the Faculty of Pharmaceutical Sciences, the University of Tokyo, Japan, in 1977, and then obtained his Ph.D. for bio-organic chemistry/biochemistry from the University of Tokyo in 1982. After staying at Keio University in Japan and Ghent University in Belgium (Prof. Marc Van Montagu’s laboratory), he became a faculty member at the Graduate School of Pharmaceutical Sciences, Chiba University, Japan. There he has been appointed as a full professor from 1995 until 2020. He is currently entitled as a Professor Emeritus at Chiba University and holds the part-time Director position at Plant Molecular Science Center. Since April 2005, he has been additionally appointed as a group director at RIKEN Plant Science Center, currently at RIKEN Center for Sustainable Resource Science (CSRS), to direct Metabolomics Research Group. Since April 2020, he also holds the post of Director of the RIKEN CSRS.<br />
He was awarded The Medal with Purple Ribbon by Japanese Government; The Prize for Science and Technology by the Minister of Education, Culture, Science and Technology, Japan; JSPP Award by the Japanese Society of Plant Physiologists; The Pharmaceutical Society of Japan Award; and Lifetime Honorary Fellowship of The Metabolomics Society. He has been selected one of ‘Highly Cited Researchers’ in the 'Plant & Animal Science' field for 2014-2020, and an ASPB Top Author.<br />
His research interests are metabolome-based functional genomics, biochemistry, molecular biology and biotechnology of primary and secondary metabolism in plants. In particular, he is engaging in the biosynthetic studies of sulfur compounds, flavonoids, terpenoids and alkaloids by means of metabolomics. He further pursues the establishment of a new field of 'Sustainable Resource Science'.<br />
<br />
==Expert Opinion==<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations? '''<br />
<br />
The initiation of my metabolomics research goes back to the late 1990s. That time was just the dawn of the coming genomic era. The draft assembly of the human genome was just going on from 1991, expecting the completion by the new millennium. In the plant science field, the international team was tackling the genome sequencing of a model plant species, Arabidopsis thaliana. We, plant scientists, were all very enthusiastic about completing the first revealed genome sequence of a plant species. As the consequence of the genome sequence, one can easily expect tremendous progress in holistic gene expression (transcriptomics) and protein accumulation (proteomics), since these pieces of downstream biological information can be deduced from the genome by the Central Dogma of molecular biology. However, the study on the entire accumulation of metabolites (metabolomics) is not necessarily straightforward as transcriptomics and proteomics even after decoding the genome sequence.<br />
From the early days of my scientific career, I have been so much fascinated with the chemical diversity of plants – why and how those diversified chemical compounds are synthesized in plants. To address these grand questions, before the completion of genome sequencing of A. thaliana in 2000, I was fully convinced that I should start plant metabolomics research, which looked like a promising new research area in the post-genome era worth challenging. I dreamed that we would connect each gene in the genome to each metabolite in a one-by-one manner in the genome-decoded A. thaliana.<br />
Fortunately, at the same time, in 2000, Japan Science Technology Agency (JST) called proposals for a large-amount grant (CREST) specifically for plant science. I have applied a multi-omics research proposal on model plants (Arabidopsis and rice) to this call together with several expert colleagues. Our proposal was luckily accepted, and we got started the metabolomics-based functional genomics project in 2000. In 2001, I organized the first international plant metabolomics symposium entitled 'Metabolomics Approach in Plant Functional Genomics in the Post-genome Eras' in Kisarazu, Chiba, Japan. Invited speakers included Lothar Willmitzer, Rick Dixon, Dirk Inze, Kirsi-Marja Oksman-Caldentey, Malcolm Hawkesford, and Dayan Goodenowe.<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
Our group has been dealing with functional genomics in A. thaliana through the integration of genomics, transcriptomics, and metabolomics. Omics-data have been acquired from Arabidopsis plants under a variety of conditions: ectopically expressed of regulatory and key metabolic genes, subjected to abiotic stresses (drought, heat, and nutrition depletion), or of natural variants. From those omics data, we can generate hypotheses regarding the relations of genes/transcripts to metabolites. These testable hypotheses can be validated by the reverse genetics approach in Arabidopsis, thanks to the availability of research resources such as a panel of knockout lines of almost all genes, the full-length cDNA collections, and bioinformatics tools. Two recent examples of such studies are published in the papers for the identification of a heat-mitigating gene (Higashi et al., 2018) and biosynthetic genes for seed-protective neolignane (Yonekura-Sakakibara et al, 2021).<br />
We are also exploring the metabolomics of major crops, e.g., rice, soybean, and tomato. These crop investigations aim to elucidate genes' function, metabolic physiology for crop performance, and evaluation of biotechnological modification. The metabolomic study of medicinal plants is another main subject of our research. What we are looking forward to is not only the identification of novel bioactive metabolites but functional identification of genes or genome regions for the production of medicinal compounds in given medicinal plants, as exemplified in the latest paper (Rai et al., 2021).<br />
Technology development of metabolomics is also one of the major topics of our research group. The combination of utilizing fully stable-isotope-labeled plant materials and cutting-edge chemoinformatics is a powerful strategy for reliable annotation of LC-MS-based plant metabolomics (Tsugawa et al., 2019). If imaging mass spectrometry is applied, new findings on metabolite accumulation and biosynthetic consideration can be obtained (Nakabayashi et al., 2020).<br />
<br />
• Yasuhiro Higashi, Yozo Okazaki, Kouji Takano, Fumiyoshi Myouga, Kazuo Shinozaki, Eva Knoch, Atsushi Fukushima, Kazuki Saito: HEAT INDUCIBLE LIPASE1 remodels chloroplastic monogalactosyldiacylglycerol by liberating α-linolenic acid in Arabidopsis leaves under heat stress. Plant Cell., 30, 1887-1905, doi: 10.1105/tpc.18.00347 (2018) <br />
• Keiko Yonekura-Sakakibara, Masaomi Yamamura, Fumio Matsuda, Eiichiro Ono, Ryo Nakabayashi, Satoko Sugawara, Tetsuya Mori, Yuki Tobimatsu, Toshiaki Umezawa, Kazuki Saito: Seed-coat protective neolignans are produced by the dirigent protein AtDP1 and the laccase AtLAC5 in Arabidopsis. Plant Cell, in press, https://doi.org/10.1093/plcell/koaa014 (2021) <br />
• Amit Rai, Hideki Hirakawa, Ryo Nakabayashi, Shinji Kikuchi, Koki Hayashi, Megha Rai, Hiroshi Tsugawa, Taiki Nakaya, Tetsuya Mori, Hideki Nagasaki, Runa Fukushi, Yoko Kusuya, Hiroki Takahashi, Hiroshi Uchiyama, Atsushi Toyoda, Shoko Hikosaka, Eiji Goto, Kazuki Saito, Mami Yamazaki: Chromosome-level genome assembly of Ophiorrhiza pumila reveals the evolution of camptothecin biosynthesis: Nature Commun., in press, https://doi.org/10.1038/s41467-020-20508-2 (2021)<br />
• Hiroshi Tsugawa, Ryo Nakabayashi, Tetsuya Mori, Yutaka Yamada, Mikiko Takahashi, Amit Rai, Ryosuke Sugiyama, Hiroyuki Yamamoto, Taiki Nakaya, Mami Yamazaki, Rik Kooke, Johanna A. Bac-Molenaar, Nihal Oztolan-Erol, Joost J.B. Keurentjes, Masanori Arita, Kazuki Saito: A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms. Nature Methods, 16, 295–298, https://doi.org/10.1038/s41592-019-0358-2 (2019) <br />
• Ryo Nakabayashi, Tetsuya Mori, Noriko Takeda, Kiminori Toyooka, Hiroshi Sudo, Hiroshi Tsugawa, Kazuki Saito: Metabolomics with 15N labeling for characterizing missing monoterpene indole alkaloids in plants. Anal. Chem., 92, 5670-5675 https://doi.org/10.1021/acs.analchem.9b03860 (2020)<br />
<br />
''' 3. As one of the pioneers in the field of plant metabolomics, what are the main challenges for developing high-throughput analytical techniques for plant metabolomics? '''<br />
<br />
As repeatedly mentioned in the scientific community, the biggest challenge in plant metabolomics is still metabolites' peak annotation. While a significant improvement in reliable peak annotation has been achieved by a magnificent effort of the community, mostly by the chemo/bioinformatic specialists working with experimental biologists, there is still room for advancements in the annotation of unknown metabolites, which is required prior to unequivocal identification of those peaks with synthetic or natural standard compounds. However, if you adopt the fully 13C-labelled plant materials, which are readily available for certain plant species by growing plants under a 13C-CO2 atmosphere or 13C-glucose as the sole carbon source, annotation reliability is dramatically improved. Collection of standard mass spectra of plant products in non-profit public databases, such as MassBank <http://www.massbank.jp/>, should be continued by a community effort for the better peak annotation without any obstacles. <br />
To maximize the coverage of chemical space by metabolomic analysis, metabolite analysis is often carried out by a combination of multiple mass-spec platforms in parallel, e.g., GC-MS, LC-MS (polar and non-polar), and CE-MS (positive and negative). Integration of metabolomics data from such multiple platforms is also challenging. Related to this point, absolute quantification of known metabolites is also highly required to obtain deeper insights into plant metabolic physiology under a given condition.<br />
<br />
''' 4. What are the main obstacles for integrating metabolomics and genomics? '''<br />
<br />
The speed, quality, and price of genome sequencing have been dramatically improved in the last few years, thanks to the development of new technology. We can expect a substantial number of diversified plant genomes are decoded in the coming years. Sequence diversification obtained by such studies is not only of a species-wide but natural-variant-wide with species- or variant-specific metabolite patterns. By integrating such diversified genome information with precise metabolomics, we will be able to find novel associations of genes to metabolites in a relatively easy manner. These associations provide excellent hints for the function of genes responsible for the production of specific metabolites.<br />
However, to verify the genes' function to produce specific metabolites, a reverse genetics approach with loss-of-function and gain-of-function experiments must be taken. While a great advancement has been seen in gene-editing technology represented by CRISPER/Cas9 system in the last several years, experimental protocols for each plant must still be established, in particular, in non-model plants (most of the medicinal plants and some local crops). These tissue-culture-based studies are a kind of tedious works with repeated trials and errors. <br />
From a physiological viewpoint, the accumulation of plant metabolites is highly cell-type specific, and the sites of storage are often different from those of biosynthesis. Therefore, a highly sophisticated transport mechanism is well organized for the efficient storage of plant metabolites. The insights on this transport/localization issue are not necessarily easily obtained from the genomics lying some gaps but not in a straightforward manner. We need to take biochemical and physiological approaches to tackle this issue.<br />
<br />
''' 5. How do you think the understanding of plant metabolism through genomic and post-genomic approaches can be applied into healthcare? '''<br />
<br />
To answer this question, we have to consider two different folds – direct application or indirect application into healthcare.<br />
Understanding of plant metabolism can be directly applied to human healthcare through medicines. In human history, humankind has received a tremendous benefit from novel plant products for curing and preventing diseases. One of the best representative examples is the finding of artemisinin from Artemisia annua as an anti-malaria agent, which was laureated as The Nobel Prize in Physiology and Medicine of 2015. In fact, Royal Botanical Garden Kew Report in 2016 <https://stateoftheworldsplants.org/2016/> says the largest number of plant species used in each category is for medicines over food, materials, and others. However, mankind has investigated only a small part of the huge chemical diversity of all plant species on earth. There are still hidden rich veins of gold of medicinal compounds in unexplored plant species. Genomics and metabolomics should be an excellent way to mine those hidden gold veins for our future healthcare.<br />
Indirectly, knowledge of plant metabolism can be applied to healthcare through nutritious and sustainable food, which is owed to the sustainable and resilient production of crops under environmental stresses. Besides food security, a decrease in the level of greenhouse gas, CO2, also depends on the metabolic activity of plants to some extent. These global issues, such as hunger and climate crisis connected to human healthcare, are all concerned with plant metabolism consequently. The study on plant metabolism thus takes a huge responsibility for keeping our planet sustainable and humanity improved.<br />
<br />
''' 6. What would your advice be for early career researchers working in the field of plant metabolomics? '''<br />
<br />
The field of plant metabolomics is really an open area – still, a lot of secrets await to be discovered. Without any doubt, you can be fully convinced that the study on plant metabolomics is worthwhile to be enthusiastic about. I hope you can join us to take an endeavor!<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Kazuki_Saito&diff=1105Kazuki Saito2021-01-18T15:03:09Z<p>EvelinaCharidemou: </p>
<hr />
<div>[[Image: Kazuki_Saito.png|thumb|Official Name Surname of the Expert]]<br />
<br />
==Short Biography==<br />
<br />
Professor Kazuki Saito graduated from the Faculty of Pharmaceutical Sciences, the University of Tokyo, Japan, in 1977, and then obtained his Ph.D. for bio-organic chemistry/biochemistry from the University of Tokyo in 1982. After staying at Keio University in Japan and Ghent University in Belgium (Prof. Marc Van Montagu’s laboratory), he became a faculty member at the Graduate School of Pharmaceutical Sciences, Chiba University, Japan. There he has been appointed as a full professor from 1995 until 2020. He is currently entitled as a Professor Emeritus at Chiba University and holds the part-time Director position at Plant Molecular Science Center. Since April 2005, he has been additionally appointed as a group director at RIKEN Plant Science Center, currently at RIKEN Center for Sustainable Resource Science (CSRS), to direct Metabolomics Research Group. Since April 2020, he also holds the post of Director of the RIKEN CSRS.<br />
He was awarded The Medal with Purple Ribbon by Japanese Government; The Prize for Science and Technology by the Minister of Education, Culture, Science and Technology, Japan; JSPP Award by the Japanese Society of Plant Physiologists; The Pharmaceutical Society of Japan Award; and Lifetime Honorary Fellowship of The Metabolomics Society. He has been selected one of ‘Highly Cited Researchers’ in the 'Plant & Animal Science' field for 2014-2020, and an ASPB Top Author.<br />
His research interests are metabolome-based functional genomics, biochemistry, molecular biology and biotechnology of primary and secondary metabolism in plants. In particular, he is engaging in the biosynthetic studies of sulfur compounds, flavonoids, terpenoids and alkaloids by means of metabolomics. He further pursues the establishment of a new field of 'Sustainable Resource Science'.<br />
<br />
==Expert Opinion==<br />
<br />
''' 1. When and why did you start using metabolomics in your investigations? '''<br />
<br />
The initiation of my metabolomics research goes back to the late 1990s. That time was just the dawn of the coming genomic era. The draft assembly of the human genome was just going on from 1991, expecting the completion by the new millennium. In the plant science field, the international team was tackling the genome sequencing of a model plant species, Arabidopsis thaliana. We, plant scientists, were all very enthusiastic about completing the first revealed genome sequence of a plant species. As the consequence of the genome sequence, one can easily expect tremendous progress in holistic gene expression (transcriptomics) and protein accumulation (proteomics), since these pieces of downstream biological information can be deduced from the genome by the Central Dogma of molecular biology. However, the study on the entire accumulation of metabolites (metabolomics) is not necessarily straightforward as transcriptomics and proteomics even after decoding the genome sequence.<br />
From the early days of my scientific career, I have been so much fascinated with the chemical diversity of plants – why and how those diversified chemical compounds are synthesized in plants. To address these grand questions, before the completion of genome sequencing of A. thaliana in 2000, I was fully convinced that I should start plant metabolomics research, which looked like a promising new research area in the post-genome era worth challenging. I dreamed that we would connect each gene in the genome to each metabolite in a one-by-one manner in the genome-decoded A. thaliana.<br />
Fortunately, at the same time, in 2000, Japan Science Technology Agency (JST) called proposals for a large-amount grant (CREST) specifically for plant science. I have applied a multi-omics research proposal on model plants (Arabidopsis and rice) to this call together with several expert colleagues. Our proposal was luckily accepted, and we got started the metabolomics-based functional genomics project in 2000. In 2001, I organized the first international plant metabolomics symposium entitled 'Metabolomics Approach in Plant Functional Genomics in the Post-genome Eras' in Kisarazu, Chiba, Japan. Invited speakers included Lothar Willmitzer, Rick Dixon, Dirk Inze, Kirsi-Marja Oksman-Caldentey, Malcolm Hawkesford, and Dayan Goodenowe.<br />
<br />
<br />
''' 2. What have you been working on recently? '''<br />
<br />
Our group has been dealing with functional genomics in A. thaliana through the integration of genomics, transcriptomics, and metabolomics. Omics-data have been acquired from Arabidopsis plants under a variety of conditions: ectopically expressed of regulatory and key metabolic genes, subjected to abiotic stresses (drought, heat, and nutrition depletion), or of natural variants. From those omics data, we can generate hypotheses regarding the relations of genes/transcripts to metabolites. These testable hypotheses can be validated by the reverse genetics approach in Arabidopsis, thanks to the availability of research resources such as a panel of knockout lines of almost all genes, the full-length cDNA collections, and bioinformatics tools. Two recent examples of such studies are published in the papers for the identification of a heat-mitigating gene (Higashi et al., 2018) and biosynthetic genes for seed-protective neolignane (Yonekura-Sakakibara et al, 2021).<br />
We are also exploring the metabolomics of major crops, e.g., rice, soybean, and tomato. These crop investigations aim to elucidate genes' function, metabolic physiology for crop performance, and evaluation of biotechnological modification. The metabolomic study of medicinal plants is another main subject of our research. What we are looking forward to is not only the identification of novel bioactive metabolites but functional identification of genes or genome regions for the production of medicinal compounds in given medicinal plants, as exemplified in the latest paper (Rai et al., 2021).<br />
Technology development of metabolomics is also one of the major topics of our research group. The combination of utilizing fully stable-isotope-labeled plant materials and cutting-edge chemoinformatics is a powerful strategy for reliable annotation of LC-MS-based plant metabolomics (Tsugawa et al., 2019). If imaging mass spectrometry is applied, new findings on metabolite accumulation and biosynthetic consideration can be obtained (Nakabayashi et al., 2020).<br />
<br />
• Yasuhiro Higashi, Yozo Okazaki, Kouji Takano, Fumiyoshi Myouga, Kazuo Shinozaki, Eva Knoch, Atsushi Fukushima, Kazuki Saito: HEAT INDUCIBLE LIPASE1 remodels chloroplastic monogalactosyldiacylglycerol by liberating α-linolenic acid in Arabidopsis leaves under heat stress. Plant Cell., 30, 1887-1905, doi: 10.1105/tpc.18.00347 (2018) <br />
• Keiko Yonekura-Sakakibara, Masaomi Yamamura, Fumio Matsuda, Eiichiro Ono, Ryo Nakabayashi, Satoko Sugawara, Tetsuya Mori, Yuki Tobimatsu, Toshiaki Umezawa, Kazuki Saito: Seed-coat protective neolignans are produced by the dirigent protein AtDP1 and the laccase AtLAC5 in Arabidopsis. Plant Cell, in press, https://doi.org/10.1093/plcell/koaa014 (2021) <br />
• Amit Rai, Hideki Hirakawa, Ryo Nakabayashi, Shinji Kikuchi, Koki Hayashi, Megha Rai, Hiroshi Tsugawa, Taiki Nakaya, Tetsuya Mori, Hideki Nagasaki, Runa Fukushi, Yoko Kusuya, Hiroki Takahashi, Hiroshi Uchiyama, Atsushi Toyoda, Shoko Hikosaka, Eiji Goto, Kazuki Saito, Mami Yamazaki: Chromosome-level genome assembly of Ophiorrhiza pumila reveals the evolution of camptothecin biosynthesis: Nature Commun., in press, https://doi.org/10.1038/s41467-020-20508-2 (2021)<br />
• Hiroshi Tsugawa, Ryo Nakabayashi, Tetsuya Mori, Yutaka Yamada, Mikiko Takahashi, Amit Rai, Ryosuke Sugiyama, Hiroyuki Yamamoto, Taiki Nakaya, Mami Yamazaki, Rik Kooke, Johanna A. Bac-Molenaar, Nihal Oztolan-Erol, Joost J.B. Keurentjes, Masanori Arita, Kazuki Saito: A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms. Nature Methods, 16, 295–298, https://doi.org/10.1038/s41592-019-0358-2 (2019) <br />
• Ryo Nakabayashi, Tetsuya Mori, Noriko Takeda, Kiminori Toyooka, Hiroshi Sudo, Hiroshi Tsugawa, Kazuki Saito: Metabolomics with 15N labeling for characterizing missing monoterpene indole alkaloids in plants. Anal. Chem., 92, 5670-5675 https://doi.org/10.1021/acs.analchem.9b03860 (2020)<br />
<br />
''' 3. As one of the pioneers in the field of plant metabolomics, what are the main challenges for developing high-throughput analytical techniques for plant metabolomics? '''<br />
<br />
As repeatedly mentioned in the scientific community, the biggest challenge in plant metabolomics is still metabolites' peak annotation. While a significant improvement in reliable peak annotation has been achieved by a magnificent effort of the community, mostly by the chemo/bioinformatic specialists working with experimental biologists, there is still room for advancements in the annotation of unknown metabolites, which is required prior to unequivocal identification of those peaks with synthetic or natural standard compounds. However, if you adopt the fully 13C-labelled plant materials, which are readily available for certain plant species by growing plants under a 13C-CO2 atmosphere or 13C-glucose as the sole carbon source, annotation reliability is dramatically improved. Collection of standard mass spectra of plant products in non-profit public databases, such as MassBank <http://www.massbank.jp/>, should be continued by a community effort for the better peak annotation without any obstacles. <br />
To maximize the coverage of chemical space by metabolomic analysis, metabolite analysis is often carried out by a combination of multiple mass-spec platforms in parallel, e.g., GC-MS, LC-MS (polar and non-polar), and CE-MS (positive and negative). Integration of metabolomics data from such multiple platforms is also challenging. Related to this point, absolute quantification of known metabolites is also highly required to obtain deeper insights into plant metabolic physiology under a given condition.<br />
<br />
''' 4. What are the main obstacles for integrating metabolomics and genomics? '''<br />
<br />
The speed, quality, and price of genome sequencing have been dramatically improved in the last few years, thanks to the development of new technology. We can expect a substantial number of diversified plant genomes are decoded in the coming years. Sequence diversification obtained by such studies is not only of a species-wide but natural-variant-wide with species- or variant-specific metabolite patterns. By integrating such diversified genome information with precise metabolomics, we will be able to find novel associations of genes to metabolites in a relatively easy manner. These associations provide excellent hints for the function of genes responsible for the production of specific metabolites.<br />
However, to verify the genes' function to produce specific metabolites, a reverse genetics approach with loss-of-function and gain-of-function experiments must be taken. While a great advancement has been seen in gene-editing technology represented by CRISPER/Cas9 system in the last several years, experimental protocols for each plant must still be established, in particular, in non-model plants (most of the medicinal plants and some local crops). These tissue-culture-based studies are a kind of tedious works with repeated trials and errors. <br />
From a physiological viewpoint, the accumulation of plant metabolites is highly cell-type specific, and the sites of storage are often different from those of biosynthesis. Therefore, a highly sophisticated transport mechanism is well organized for the efficient storage of plant metabolites. The insights on this transport/localization issue are not necessarily easily obtained from the genomics lying some gaps but not in a straightforward manner. We need to take biochemical and physiological approaches to tackle this issue.<br />
<br />
''' 5. How do you think the understanding of plant metabolism through genomic and post-genomic approaches can be applied into healthcare? '''<br />
<br />
To answer this question, we have to consider two different folds – direct application or indirect application into healthcare.<br />
Understanding of plant metabolism can be directly applied to human healthcare through medicines. In human history, humankind has received a tremendous benefit from novel plant products for curing and preventing diseases. One of the best representative examples is the finding of artemisinin from Artemisia annua as an anti-malaria agent, which was laureated as The Nobel Prize in Physiology and Medicine of 2015. In fact, Royal Botanical Garden Kew Report in 2016 <https://stateoftheworldsplants.org/2016/> says the largest number of plant species used in each category is for medicines over food, materials, and others. However, mankind has investigated only a small part of the huge chemical diversity of all plant species on earth. There are still hidden rich veins of gold of medicinal compounds in unexplored plant species. Genomics and metabolomics should be an excellent way to mine those hidden gold veins for our future healthcare.<br />
Indirectly, knowledge of plant metabolism can be applied to healthcare through nutritious and sustainable food, which is owed to the sustainable and resilient production of crops under environmental stresses. Besides food security, a decrease in the level of greenhouse gas, CO2, also depends on the metabolic activity of plants to some extent. These global issues, such as hunger and climate crisis connected to human healthcare, are all concerned with plant metabolism consequently. The study on plant metabolism thus takes a huge responsibility for keeping our planet sustainable and humanity improved.<br />
<br />
''' 6. What would your advice be for early career researchers working in the field of plant metabolomics? '''<br />
<br />
The field of plant metabolomics is really an open area – still, a lot of secrets await to be discovered. Without any doubt, you can be fully convinced that the study on plant metabolomics is worthwhile to be enthusiastic about. I hope you can join us to take an endeavor!<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Kazuki_Saito&diff=1104Kazuki Saito2021-01-18T15:00:13Z<p>EvelinaCharidemou: Created page with "Official Name Surname of the Expert ==Short Biography== Professor Kazuki Saito graduated from the Faculty of Pharmaceutical Sciences, the U..."</p>
<hr />
<div>[[Image: Kazuki_Saito.png|thumb|Official Name Surname of the Expert]]<br />
<br />
==Short Biography==<br />
<br />
Professor Kazuki Saito graduated from the Faculty of Pharmaceutical Sciences, the University of Tokyo, Japan, in 1977, and then obtained his Ph.D. for bio-organic chemistry/biochemistry from the University of Tokyo in 1982. After staying at Keio University in Japan and Ghent University in Belgium (Prof. Marc Van Montagu’s laboratory), he became a faculty member at the Graduate School of Pharmaceutical Sciences, Chiba University, Japan. There he has been appointed as a full professor from 1995 until 2020. He is currently entitled as a Professor Emeritus at Chiba University and holds the part-time Director position at Plant Molecular Science Center. Since April 2005, he has been additionally appointed as a group director at RIKEN Plant Science Center, currently at RIKEN Center for Sustainable Resource Science (CSRS), to direct Metabolomics Research Group. Since April 2020, he also holds the post of Director of the RIKEN CSRS.<br />
He was awarded The Medal with Purple Ribbon by Japanese Government; The Prize for Science and Technology by the Minister of Education, Culture, Science and Technology, Japan; JSPP Award by the Japanese Society of Plant Physiologists; The Pharmaceutical Society of Japan Award; and Lifetime Honorary Fellowship of The Metabolomics Society. He has been selected one of ‘Highly Cited Researchers’ in the 'Plant & Animal Science' field for 2014-2020, and an ASPB Top Author.<br />
His research interests are metabolome-based functional genomics, biochemistry, molecular biology and biotechnology of primary and secondary metabolism in plants. In particular, he is engaging in the biosynthetic studies of sulfur compounds, flavonoids, terpenoids and alkaloids by means of metabolomics. He further pursues the establishment of a new field of 'Sustainable Resource Science'.<br />
<br />
==Expert Opinion==<br />
<br />
1. When and why did you start using metabolomics in your investigations?<br />
<br />
The initiation of my metabolomics research goes back to the late 1990s. That time was just the dawn of the coming genomic era. The draft assembly of the human genome was just going on from 1991, expecting the completion by the new millennium. In the plant science field, the international team was tackling the genome sequencing of a model plant species, Arabidopsis thaliana. We, plant scientists, were all very enthusiastic about completing the first revealed genome sequence of a plant species. As the consequence of the genome sequence, one can easily expect tremendous progress in holistic gene expression (transcriptomics) and protein accumulation (proteomics), since these pieces of downstream biological information can be deduced from the genome by the Central Dogma of molecular biology. However, the study on the entire accumulation of metabolites (metabolomics) is not necessarily straightforward as transcriptomics and proteomics even after decoding the genome sequence.<br />
From the early days of my scientific career, I have been so much fascinated with the chemical diversity of plants – why and how those diversified chemical compounds are synthesized in plants. To address these grand questions, before the completion of genome sequencing of A. thaliana in 2000, I was fully convinced that I should start plant metabolomics research, which looked like a promising new research area in the post-genome era worth challenging. I dreamed that we would connect each gene in the genome to each metabolite in a one-by-one manner in the genome-decoded A. thaliana.<br />
Fortunately, at the same time, in 2000, Japan Science Technology Agency (JST) called proposals for a large-amount grant (CREST) specifically for plant science. I have applied a multi-omics research proposal on model plants (Arabidopsis and rice) to this call together with several expert colleagues. Our proposal was luckily accepted, and we got started the metabolomics-based functional genomics project in 2000. In 2001, I organized the first international plant metabolomics symposium entitled 'Metabolomics Approach in Plant Functional Genomics in the Post-genome Eras' in Kisarazu, Chiba, Japan. Invited speakers included Lothar Willmitzer, Rick Dixon, Dirk Inze, Kirsi-Marja Oksman-Caldentey, Malcolm Hawkesford, and Dayan Goodenowe.<br />
<br />
<br />
2. What have you been working on recently?<br />
<br />
Our group has been dealing with functional genomics in A. thaliana through the integration of genomics, transcriptomics, and metabolomics. Omics-data have been acquired from Arabidopsis plants under a variety of conditions: ectopically expressed of regulatory and key metabolic genes, subjected to abiotic stresses (drought, heat, and nutrition depletion), or of natural variants. From those omics data, we can generate hypotheses regarding the relations of genes/transcripts to metabolites. These testable hypotheses can be validated by the reverse genetics approach in Arabidopsis, thanks to the availability of research resources such as a panel of knockout lines of almost all genes, the full-length cDNA collections, and bioinformatics tools. Two recent examples of such studies are published in the papers for the identification of a heat-mitigating gene (Higashi et al., 2018) and biosynthetic genes for seed-protective neolignane (Yonekura-Sakakibara et al, 2021).<br />
We are also exploring the metabolomics of major crops, e.g., rice, soybean, and tomato. These crop investigations aim to elucidate genes' function, metabolic physiology for crop performance, and evaluation of biotechnological modification. The metabolomic study of medicinal plants is another main subject of our research. What we are looking forward to is not only the identification of novel bioactive metabolites but functional identification of genes or genome regions for the production of medicinal compounds in given medicinal plants, as exemplified in the latest paper (Rai et al., 2021).<br />
Technology development of metabolomics is also one of the major topics of our research group. The combination of utilizing fully stable-isotope-labeled plant materials and cutting-edge chemoinformatics is a powerful strategy for reliable annotation of LC-MS-based plant metabolomics (Tsugawa et al., 2019). If imaging mass spectrometry is applied, new findings on metabolite accumulation and biosynthetic consideration can be obtained (Nakabayashi et al., 2020).<br />
<br />
• Yasuhiro Higashi, Yozo Okazaki, Kouji Takano, Fumiyoshi Myouga, Kazuo Shinozaki, Eva Knoch, Atsushi Fukushima, Kazuki Saito: HEAT INDUCIBLE LIPASE1 remodels chloroplastic monogalactosyldiacylglycerol by liberating α-linolenic acid in Arabidopsis leaves under heat stress. Plant Cell., 30, 1887-1905, doi: 10.1105/tpc.18.00347 (2018) <br />
• Keiko Yonekura-Sakakibara, Masaomi Yamamura, Fumio Matsuda, Eiichiro Ono, Ryo Nakabayashi, Satoko Sugawara, Tetsuya Mori, Yuki Tobimatsu, Toshiaki Umezawa, Kazuki Saito: Seed-coat protective neolignans are produced by the dirigent protein AtDP1 and the laccase AtLAC5 in Arabidopsis. Plant Cell, in press, https://doi.org/10.1093/plcell/koaa014 (2021) <br />
• Amit Rai, Hideki Hirakawa, Ryo Nakabayashi, Shinji Kikuchi, Koki Hayashi, Megha Rai, Hiroshi Tsugawa, Taiki Nakaya, Tetsuya Mori, Hideki Nagasaki, Runa Fukushi, Yoko Kusuya, Hiroki Takahashi, Hiroshi Uchiyama, Atsushi Toyoda, Shoko Hikosaka, Eiji Goto, Kazuki Saito, Mami Yamazaki: Chromosome-level genome assembly of Ophiorrhiza pumila reveals the evolution of camptothecin biosynthesis: Nature Commun., in press, https://doi.org/10.1038/s41467-020-20508-2 (2021)<br />
• Hiroshi Tsugawa, Ryo Nakabayashi, Tetsuya Mori, Yutaka Yamada, Mikiko Takahashi, Amit Rai, Ryosuke Sugiyama, Hiroyuki Yamamoto, Taiki Nakaya, Mami Yamazaki, Rik Kooke, Johanna A. Bac-Molenaar, Nihal Oztolan-Erol, Joost J.B. Keurentjes, Masanori Arita, Kazuki Saito: A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms. Nature Methods, 16, 295–298, https://doi.org/10.1038/s41592-019-0358-2 (2019) <br />
• Ryo Nakabayashi, Tetsuya Mori, Noriko Takeda, Kiminori Toyooka, Hiroshi Sudo, Hiroshi Tsugawa, Kazuki Saito: Metabolomics with 15N labeling for characterizing missing monoterpene indole alkaloids in plants. Anal. Chem., 92, 5670-5675 https://doi.org/10.1021/acs.analchem.9b03860 (2020)<br />
<br />
3. As one of the pioneers in the field of plant metabolomics, what are the main challenges for developing high-throughput analytical techniques for plant metabolomics?<br />
<br />
As repeatedly mentioned in the scientific community, the biggest challenge in plant metabolomics is still metabolites' peak annotation. While a significant improvement in reliable peak annotation has been achieved by a magnificent effort of the community, mostly by the chemo/bioinformatic specialists working with experimental biologists, there is still room for advancements in the annotation of unknown metabolites, which is required prior to unequivocal identification of those peaks with synthetic or natural standard compounds. However, if you adopt the fully 13C-labelled plant materials, which are readily available for certain plant species by growing plants under a 13C-CO2 atmosphere or 13C-glucose as the sole carbon source, annotation reliability is dramatically improved. Collection of standard mass spectra of plant products in non-profit public databases, such as MassBank <http://www.massbank.jp/>, should be continued by a community effort for the better peak annotation without any obstacles. <br />
To maximize the coverage of chemical space by metabolomic analysis, metabolite analysis is often carried out by a combination of multiple mass-spec platforms in parallel, e.g., GC-MS, LC-MS (polar and non-polar), and CE-MS (positive and negative). Integration of metabolomics data from such multiple platforms is also challenging. Related to this point, absolute quantification of known metabolites is also highly required to obtain deeper insights into plant metabolic physiology under a given condition.<br />
<br />
4. What are the main obstacles for integrating metabolomics and genomics?<br />
<br />
The speed, quality, and price of genome sequencing have been dramatically improved in the last few years, thanks to the development of new technology. We can expect a substantial number of diversified plant genomes are decoded in the coming years. Sequence diversification obtained by such studies is not only of a species-wide but natural-variant-wide with species- or variant-specific metabolite patterns. By integrating such diversified genome information with precise metabolomics, we will be able to find novel associations of genes to metabolites in a relatively easy manner. These associations provide excellent hints for the function of genes responsible for the production of specific metabolites.<br />
However, to verify the genes' function to produce specific metabolites, a reverse genetics approach with loss-of-function and gain-of-function experiments must be taken. While a great advancement has been seen in gene-editing technology represented by CRISPER/Cas9 system in the last several years, experimental protocols for each plant must still be established, in particular, in non-model plants (most of the medicinal plants and some local crops). These tissue-culture-based studies are a kind of tedious works with repeated trials and errors. <br />
From a physiological viewpoint, the accumulation of plant metabolites is highly cell-type specific, and the sites of storage are often different from those of biosynthesis. Therefore, a highly sophisticated transport mechanism is well organized for the efficient storage of plant metabolites. The insights on this transport/localization issue are not necessarily easily obtained from the genomics lying some gaps but not in a straightforward manner. We need to take biochemical and physiological approaches to tackle this issue.<br />
<br />
5. How do you think the understanding of plant metabolism through genomic and post-genomic approaches can be applied into healthcare?<br />
<br />
To answer this question, we have to consider two different folds – direct application or indirect application into healthcare.<br />
Understanding of plant metabolism can be directly applied to human healthcare through medicines. In human history, humankind has received a tremendous benefit from novel plant products for curing and preventing diseases. One of the best representative examples is the finding of artemisinin from Artemisia annua as an anti-malaria agent, which was laureated as The Nobel Prize in Physiology and Medicine of 2015. In fact, Royal Botanical Garden Kew Report in 2016 <https://stateoftheworldsplants.org/2016/> says the largest number of plant species used in each category is for medicines over food, materials, and others. However, mankind has investigated only a small part of the huge chemical diversity of all plant species on earth. There are still hidden rich veins of gold of medicinal compounds in unexplored plant species. Genomics and metabolomics should be an excellent way to mine those hidden gold veins for our future healthcare.<br />
Indirectly, knowledge of plant metabolism can be applied to healthcare through nutritious and sustainable food, which is owed to the sustainable and resilient production of crops under environmental stresses. Besides food security, a decrease in the level of greenhouse gas, CO2, also depends on the metabolic activity of plants to some extent. These global issues, such as hunger and climate crisis connected to human healthcare, are all concerned with plant metabolism consequently. The study on plant metabolism thus takes a huge responsibility for keeping our planet sustainable and humanity improved.<br />
<br />
6. What would your advice be for early career researchers working in the field of plant metabolomics ?<br />
<br />
The field of plant metabolomics is really an open area – still, a lot of secrets await to be discovered. Without any doubt, you can be fully convinced that the study on plant metabolomics is worthwhile to be enthusiastic about. I hope you can join us to take an endeavor!<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Category:Expert_Opinion&diff=1103Category:Expert Opinion2021-01-18T14:53:44Z<p>EvelinaCharidemou: </p>
<hr />
<div>In this series, the EMN asks experts in the field of metabolomics about their research, career, goals and aspirations. These short interviews are featured on the [[Main Page]] and archived here.<br />
<br />
== Archive ==<br />
[[Image:Vanderhooft.jpg|75px|link= Justin van der Hooft]] [[Justin_van_der_Hooft|1. Dr Justin J.J. van der Hooft]]<br />
<br />
[[Image:Antonio.jpg|75px|link= Carla Antonio]] [[Carla_Antonio|2. Dr Carla Antonio]]<br />
<br />
[[Image:StaceyReinke.jpg|75px|link= StaceyReinke]] [[Stacey Reinke|3. Dr Stacey Reinke]]<br />
<br />
[[Image:Mark_R_Viant.png|75px|link= MarkViant]] [[Mark Viant|4. Professor Mark Viant]]<br />
<br />
[[Image:RickDunn.png|75px|link= RickDunn]] [[Rick Dunn|5. Professor Warwick (Rick) Dunn]]<br />
<br />
[[Image: Nichole_Reisdorph.png|75px|link= NicholeReisdorph]] [[Nichole Reisdorph|6. Dr Nichole Reisdorph]]<br />
<br />
[[Image: Jessica_LaskySu.jpg|75px|link= JessicaLaskySu]] [[Jessica Lasky-Su|7. Associate Professor Jessica Lasky-Su]]<br />
<br />
[[Image: Augustin_Scalbert.jpg|75px|link= AugustinScalbert]] [[Augustin Scalbert|8. Dr. Augustin Scalbert]]<br />
<br />
[[Image: Kazuki_Saito.jpg|75px|link= KazukiSaito]] [[Kazuki Saito|8. Dr. Kazuki Saito]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=File:Kazuki_Saito.jpg&diff=1102File:Kazuki Saito.jpg2021-01-18T14:48:42Z<p>EvelinaCharidemou: </p>
<hr />
<div></div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Augustin_Scalbert&diff=925Augustin Scalbert2020-12-17T17:31:12Z<p>EvelinaCharidemou: </p>
<hr />
<div>[[Image: SCALBERT_Augustin.png|thumb|Dr Augustin Scalbert]]<br />
==Short Biography==<br />
<br />
Augustin Scalbert is head of the Biomarkers Group at the International Agency for Research on Cancer (IARC) in Lyon, France (www.iarc.fr). His current research focusses on the development and implementation of metabolomic approaches in cancer epidemiology. Main objectives of his group are to discover novel biomarkers of exposure for dietary, environmental, and other lifestyle factors, and to identify risk factors for cancer and intermediate end-points through biomarker approaches. Robust methodologies developed in his lab for both targeted and untargeted metabolomic analyses have been applied in large multicentric epidemiological studies such as the European Prospective Investigation on Cancer and nutrition (EPIC) study and other EU-funded projects (EXPOsOMICS, TRANSCAN MetaboCCC). He developed the Exposome-Explorer database on biomarkers of exposure to disease risk factors (http://exposome-explorer.iarc.fr/). Before arriving at IARC in 2010, he conducted research at the National Institute of Agriculture Research (INRA) on the structure of lignins and tannins in lignocellulosic materials (INRA Grignon) and on the bioavailability and functions of dietary polyphenols in human nutrition (INRA Clermont-Ferrand). He has been identified as a Highly Cited Researcher (Clarivate Analytics).<br />
<br />
==Expert Opinion==<br />
<br />
'''1. When and why did you start using metabolomics in your investigations?<br />
'''<br />
I started using metabolomics about 15 years ago, when working on the health effects of dietary polyphenols. There were so many hypotheses on their biological effects and effects on human health and this made me feel that hypothesis-driven approaches were reaching some limits. This was particularly true in the field of nutrition research, with growing interest for many food bioactives like polyphenols, carotenoids, glucosinolates, phytates, etc. Many mechanisms of action had been proposed, largely based on in vitro studies, but few had been demonstrated in humans. Metabolomics offered a way to look at metabolic effects in a more comprehensive way in preclinical and dietary intervention studies. It became possible to compare the effects of food bioactive compounds on a large diversity of metabolic pathways, according to their magnitude, frequency or early onset, and to raise novel hypotheses on mechanisms of action. A second reason for my interest was the complexity of exposures to a huge number of compounds known in various foods. Here again, metabolomics revealed itself as a powerful approach to describe exposures to these natural compounds and to discover biomarkers of exposure for a large diversity of foods.<br />
<br />
<br />
'''2. What have you been working on recently?'''<br />
<br />
We are active in several research areas using metabolomics:<br />
- The identification of metabolic profiles associated with cancer outcomes in prospective epidemiological studies. We apply targeted and untargeted metabolomics approaches in case-control studies nested in large cohorts to identify metabolic features characterizing individuals who will later develop cancer. We can thus learn about mechanisms contributing to the risk of developing various cancers.<br />
- The discovery of novel biomarkers of dietary exposures suspected to play a role in the etiology of cancer and not easily assessed with dietary questionnaires commonly used in epidemiological studies. Recent work was focused on different types of coffee brews or on various processed meat products, respectively decreasing or increasing risk of some cancers.<br />
- The measurement of the internal exposome (all chemicals/metabolites that can be used as indicators of exposures to disease risk factors). We are partners in EXPANSE, a large European project, aiming at characterizing the urban exposome. As part of this project, we will analyze 10,000 blood samples from 15 different cohorts in Europe.<br />
<br />
<br />
'''3. Do you think the identification of dietary biomarkers can aid in the prevention of specific types of cancer?'''<br />
<br />
Many dietary biomarkers are now known, and some have been used in cancer epidemiology (http://exposome-explorer.iarc.fr/). Recent development of metabolomics has speed up discovery of novel dietary biomarkers. These biomarkers can be used to improve measurement of dietary exposures in epidemiological studies and strengthen the evidence on the role of dietary factors (food, nutrient or food constituent) in the etiology of different types of cancer. This evidence is regularly reviewed and constitutes the basis for cancer prevention.<br />
<br />
<br />
'''4. What are the current challenges for discovering dietary biomarkers for cancer risk in large epidemiological studies ?'''<br />
<br />
Two of the main challenges are the limited sensitivity of current methods and instruments to measure hundreds to thousands food compounds/metabolites in human blood or urine and the need for biological samples with high-quality metadata on dietary exposures and potential confounders. To address the first limitation, more sensitive targeted assays will be needed to measure large panels of dietary biomarkers. Dietary intervention studies are the gold standard to address the second limitation, but only a limited number of foods can be tested. Cross-sectional studies with high quality and highly detailed dietary data (e.g. from 24-hr dietary recalls) can also be used to cover a large diversity of foods.<br />
<br />
<br />
'''5. What would your advice be for people getting started in food metabolomics?'''<br />
<br />
I would say to have a good knowledge of food chemistry and metabolism, and secondly to have access to human samples from either dietary intervention studies or epidemiological studies. It is always possible to run your own intervention studies or to establish your own cohort study. This requires time and money. You can also collaborate with clinicians and epidemiologists, and bring knowledge and resources to run metabolomics analyses on human biospecimens they collected. This is what I did when developing this research first at the French National Institute of Agricultural Research (INRAe) and for the last ten years at the International Agency for Research on Cancer.<br />
<br />
<br />
'''6. You are the Biomarkers Group Leader at the International Agency for Research on Cancer. What do you think contributed significantly to your career path in becoming a group leader?'''<br />
<br />
Firstly, a desire for change and the wish to explore a new field of research, working with new people, in a new environment (about every 10 years in my own career, from wood chemistry to cancer epidemiology). Each of these changes was very demanding but also very rewarding. Secondly, the will of the Director of IARC at the time to start this new group to introduce metabolomics at IARC and develop its applications to cancer epidemiology, and lastly some experience in metabolomics, at a time when it was not as common as today.<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Augustin_Scalbert&diff=924Augustin Scalbert2020-12-17T17:30:06Z<p>EvelinaCharidemou: </p>
<hr />
<div>[[Image: SCALBERT_Augustin.png|thumb|Dr Augustin Scalbert]]<br />
==Short Biography==<br />
<br />
Augustin Scalbert is head of the Biomarkers Group at the International Agency for Research on Cancer (IARC) in Lyons, France (www.iarc.fr). His current research focusses on the development and implementation of metabolomic approaches in cancer epidemiology. Main objectives of his group are to discover novel biomarkers of exposure for dietary, environmental, and other lifestyle factors, and to identify risk factors for cancer and intermediate end-points through biomarker approaches. Robust methodologies developed in his lab for both targeted and untargeted metabolomic analyses have been applied in large multicentric epidemiological studies such as the European Prospective Investigation on Cancer and nutrition (EPIC) study and other EU-funded projects (EXPOsOMICS, TRANSCAN MetaboCCC). He developed the Exposome-Explorer database on biomarkers of exposure to disease risk factors (http://exposome-explorer.iarc.fr/). Before arriving at IARC in 2010, he conducted research at the National Institute of Agriculture Research (INRA) on the structure of lignins and tannins in lignocellulosic materials (INRA Grignon) and on the bioavailability and functions of dietary polyphenols in human nutrition (INRA Clermont-Ferrand). He has been identified as a Highly Cited Researcher (Clarivate Analytics).<br />
<br />
==Expert Opinion==<br />
<br />
'''1. When and why did you start using metabolomics in your investigations?<br />
'''<br />
I started using metabolomics about 15 years ago, when working on the health effects of dietary polyphenols. There were so many hypotheses on their biological effects and effects on human health and this made me feel that hypothesis-driven approaches were reaching some limits. This was particularly true in the field of nutrition research, with growing interest for many food bioactives like polyphenols, carotenoids, glucosinolates, phytates, etc. Many mechanisms of action had been proposed, largely based on in vitro studies, but few had been demonstrated in humans. Metabolomics offered a way to look at metabolic effects in a more comprehensive way in preclinical and dietary intervention studies. It became possible to compare the effects of food bioactive compounds on a large diversity of metabolic pathways, according to their magnitude, frequency or early onset, and to raise novel hypotheses on mechanisms of action. A second reason for my interest was the complexity of exposures to a huge number of compounds known in various foods. Here again, metabolomics revealed itself as a powerful approach to describe exposures to these natural compounds and to discover biomarkers of exposure for a large diversity of foods.<br />
<br />
<br />
'''2. What have you been working on recently?'''<br />
<br />
We are active in several research areas using metabolomics:<br />
- The identification of metabolic profiles associated with cancer outcomes in prospective epidemiological studies. We apply targeted and untargeted metabolomics approaches in case-control studies nested in large cohorts to identify metabolic features characterizing individuals who will later develop cancer. We can thus learn about mechanisms contributing to the risk of developing various cancers.<br />
- The discovery of novel biomarkers of dietary exposures suspected to play a role in the etiology of cancer and not easily assessed with dietary questionnaires commonly used in epidemiological studies. Recent work was focused on different types of coffee brews or on various processed meat products, respectively decreasing or increasing risk of some cancers.<br />
- The measurement of the internal exposome (all chemicals/metabolites that can be used as indicators of exposures to disease risk factors). We are partners in EXPANSE, a large European project, aiming at characterizing the urban exposome. As part of this project, we will analyze 10,000 blood samples from 15 different cohorts in Europe.<br />
<br />
<br />
'''3. Do you think the identification of dietary biomarkers can aid in the prevention of specific types of cancer?'''<br />
<br />
Many dietary biomarkers are now known, and some have been used in cancer epidemiology (http://exposome-explorer.iarc.fr/). Recent development of metabolomics has speed up discovery of novel dietary biomarkers. These biomarkers can be used to improve measurement of dietary exposures in epidemiological studies and strengthen the evidence on the role of dietary factors (food, nutrient or food constituent) in the etiology of different types of cancer. This evidence is regularly reviewed and constitutes the basis for cancer prevention.<br />
<br />
<br />
'''4. What are the current challenges for discovering dietary biomarkers for cancer risk in large epidemiological studies ?'''<br />
<br />
Two of the main challenges are the limited sensitivity of current methods and instruments to measure hundreds to thousands food compounds/metabolites in human blood or urine and the need for biological samples with high-quality metadata on dietary exposures and potential confounders. To address the first limitation, more sensitive targeted assays will be needed to measure large panels of dietary biomarkers. Dietary intervention studies are the gold standard to address the second limitation, but only a limited number of foods can be tested. Cross-sectional studies with high quality and highly detailed dietary data (e.g. from 24-hr dietary recalls) can also be used to cover a large diversity of foods.<br />
<br />
<br />
'''5. What would your advice be for people getting started in food metabolomics?'''<br />
<br />
I would say to have a good knowledge of food chemistry and metabolism, and secondly to have access to human samples from either dietary intervention studies or epidemiological studies. It is always possible to run your own intervention studies or to establish your own cohort study. This requires time and money. You can also collaborate with clinicians and epidemiologists, and bring knowledge and resources to run metabolomics analyses on human biospecimens they collected. This is what I did when developing this research first at the French National Institute of Agricultural Research (INRAe) and for the last ten years at the International Agency for Research on Cancer.<br />
<br />
<br />
'''6. You are the Biomarkers Group Leader at the International Agency for Research on Cancer. What do you think contributed significantly to your career path in becoming a group leader?'''<br />
<br />
Firstly, a desire for change and the wish to explore a new field of research, working with new people, in a new environment (about every 10 years in my own career, from wood chemistry to cancer epidemiology). Each of these changes was very demanding but also very rewarding. Secondly, the will of the Director of IARC at the time to start this new group to introduce metabolomics at IARC and develop its applications to cancer epidemiology, and lastly some experience in metabolomics, at a time when it was not as common as today.<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=File:SCALBERT_Augustin.png&diff=923File:SCALBERT Augustin.png2020-12-17T17:29:32Z<p>EvelinaCharidemou: </p>
<hr />
<div></div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Augustin_Scalbert&diff=920Augustin Scalbert2020-12-17T17:21:27Z<p>EvelinaCharidemou: </p>
<hr />
<div>[[Image: Augustin_Scalbert.jpg|thumb|Dr Augustin Scalbert]]<br />
==Short Biography==<br />
<br />
Augustin Scalbert is head of the Biomarkers Group at the International Agency for Research on Cancer (IARC) in Lyons, France (www.iarc.fr). His current research focusses on the development and implementation of metabolomic approaches in cancer epidemiology. Main objectives of his group are to discover novel biomarkers of exposure for dietary, environmental, and other lifestyle factors, and to identify risk factors for cancer and intermediate end-points through biomarker approaches. Robust methodologies developed in his lab for both targeted and untargeted metabolomic analyses have been applied in large multicentric epidemiological studies such as the European Prospective Investigation on Cancer and nutrition (EPIC) study and other EU-funded projects (EXPOsOMICS, TRANSCAN MetaboCCC). He developed the Exposome-Explorer database on biomarkers of exposure to disease risk factors (http://exposome-explorer.iarc.fr/). Before arriving at IARC in 2010, he conducted research at the National Institute of Agriculture Research (INRA) on the structure of lignins and tannins in lignocellulosic materials (INRA Grignon) and on the bioavailability and functions of dietary polyphenols in human nutrition (INRA Clermont-Ferrand). He has been identified as a Highly Cited Researcher (Clarivate Analytics).<br />
<br />
==Expert Opinion==<br />
<br />
'''1. When and why did you start using metabolomics in your investigations?<br />
'''<br />
I started using metabolomics about 15 years ago, when working on the health effects of dietary polyphenols. There were so many hypotheses on their biological effects and effects on human health and this made me feel that hypothesis-driven approaches were reaching some limits. This was particularly true in the field of nutrition research, with growing interest for many food bioactives like polyphenols, carotenoids, glucosinolates, phytates, etc. Many mechanisms of action had been proposed, largely based on in vitro studies, but few had been demonstrated in humans. Metabolomics offered a way to look at metabolic effects in a more comprehensive way in preclinical and dietary intervention studies. It became possible to compare the effects of food bioactive compounds on a large diversity of metabolic pathways, according to their magnitude, frequency or early onset, and to raise novel hypotheses on mechanisms of action. A second reason for my interest was the complexity of exposures to a huge number of compounds known in various foods. Here again, metabolomics revealed itself as a powerful approach to describe exposures to these natural compounds and to discover biomarkers of exposure for a large diversity of foods.<br />
<br />
<br />
'''2. What have you been working on recently?'''<br />
<br />
We are active in several research areas using metabolomics:<br />
- The identification of metabolic profiles associated with cancer outcomes in prospective epidemiological studies. We apply targeted and untargeted metabolomics approaches in case-control studies nested in large cohorts to identify metabolic features characterizing individuals who will later develop cancer. We can thus learn about mechanisms contributing to the risk of developing various cancers.<br />
- The discovery of novel biomarkers of dietary exposures suspected to play a role in the etiology of cancer and not easily assessed with dietary questionnaires commonly used in epidemiological studies. Recent work was focused on different types of coffee brews or on various processed meat products, respectively decreasing or increasing risk of some cancers.<br />
- The measurement of the internal exposome (all chemicals/metabolites that can be used as indicators of exposures to disease risk factors). We are partners in EXPANSE, a large European project, aiming at characterizing the urban exposome. As part of this project, we will analyze 10,000 blood samples from 15 different cohorts in Europe.<br />
<br />
<br />
'''3. Do you think the identification of dietary biomarkers can aid in the prevention of specific types of cancer?'''<br />
<br />
Many dietary biomarkers are now known, and some have been used in cancer epidemiology (http://exposome-explorer.iarc.fr/). Recent development of metabolomics has speed up discovery of novel dietary biomarkers. These biomarkers can be used to improve measurement of dietary exposures in epidemiological studies and strengthen the evidence on the role of dietary factors (food, nutrient or food constituent) in the etiology of different types of cancer. This evidence is regularly reviewed and constitutes the basis for cancer prevention.<br />
<br />
<br />
'''4. What are the current challenges for discovering dietary biomarkers for cancer risk in large epidemiological studies ?'''<br />
<br />
Two of the main challenges are the limited sensitivity of current methods and instruments to measure hundreds to thousands food compounds/metabolites in human blood or urine and the need for biological samples with high-quality metadata on dietary exposures and potential confounders. To address the first limitation, more sensitive targeted assays will be needed to measure large panels of dietary biomarkers. Dietary intervention studies are the gold standard to address the second limitation, but only a limited number of foods can be tested. Cross-sectional studies with high quality and highly detailed dietary data (e.g. from 24-hr dietary recalls) can also be used to cover a large diversity of foods.<br />
<br />
<br />
'''5. What would your advice be for people getting started in food metabolomics?'''<br />
<br />
I would say to have a good knowledge of food chemistry and metabolism, and secondly to have access to human samples from either dietary intervention studies or epidemiological studies. It is always possible to run your own intervention studies or to establish your own cohort study. This requires time and money. You can also collaborate with clinicians and epidemiologists, and bring knowledge and resources to run metabolomics analyses on human biospecimens they collected. This is what I did when developing this research first at the French National Institute of Agricultural Research (INRAe) and for the last ten years at the International Agency for Research on Cancer.<br />
<br />
<br />
'''6. You are the Biomarkers Group Leader at the International Agency for Research on Cancer. What do you think contributed significantly to your career path in becoming a group leader?'''<br />
<br />
Firstly, a desire for change and the wish to explore a new field of research, working with new people, in a new environment (about every 10 years in my own career, from wood chemistry to cancer epidemiology). Each of these changes was very demanding but also very rewarding. Secondly, the will of the Director of IARC at the time to start this new group to introduce metabolomics at IARC and develop its applications to cancer epidemiology, and lastly some experience in metabolomics, at a time when it was not as common as today.<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemouhttp://wiki.metabolomicssociety.org/index.php?title=Augustin_Scalbert&diff=919Augustin Scalbert2020-12-17T17:19:56Z<p>EvelinaCharidemou: </p>
<hr />
<div>[[Image: Augustin_Scalbert.jpg|thumb|Dr Augustin Scalbert]]<br />
==Short Biography==<br />
<br />
Augustin Scalbert is head of the Biomarkers Group at the International Agency for Research on Cancer (IARC) in Lyons, France (www.iarc.fr). His current research focusses on the development and implementation of metabolomic approaches in cancer epidemiology. Main objectives of his group are to discover novel biomarkers of exposure for dietary, environmental, and other lifestyle factors, and to identify risk factors for cancer and intermediate end-points through biomarker approaches. Robust methodologies developed in his lab for both targeted and untargeted metabolomic analyses have been applied in large multicentric epidemiological studies such as the European Prospective Investigation on Cancer and nutrition (EPIC) study and other EU-funded projects (EXPOsOMICS, TRANSCAN MetaboCCC). He developed the Exposome-Explorer database on biomarkers of exposure to disease risk factors (http://exposome-explorer.iarc.fr/). Before arriving at IARC in 2010, he conducted research at the National Institute of Agriculture Research (INRA) on the structure of lignins and tannins in lignocellulosic materials (INRA Grignon) and on the bioavailability and functions of dietary polyphenols in human nutrition (INRA Clermont-Ferrand). He has been identified as a Highly Cited Researcher (Clarivate Analytics).<br />
<br />
==Expert Opinion==<br />
===Q1?===<br />
<br />
1. When and why did you start using metabolomics in your investigations?<br />
<br />
I started using metabolomics about 15 years ago, when working on the health effects of dietary polyphenols. There were so many hypotheses on their biological effects and effects on human health and this made me feel that hypothesis-driven approaches were reaching some limits. This was particularly true in the field of nutrition research, with growing interest for many food bioactives like polyphenols, carotenoids, glucosinolates, phytates, etc. Many mechanisms of action had been proposed, largely based on in vitro studies, but few had been demonstrated in humans. Metabolomics offered a way to look at metabolic effects in a more comprehensive way in preclinical and dietary intervention studies. It became possible to compare the effects of food bioactive compounds on a large diversity of metabolic pathways, according to their magnitude, frequency or early onset, and to raise novel hypotheses on mechanisms of action. A second reason for my interest was the complexity of exposures to a huge number of compounds known in various foods. Here again, metabolomics revealed itself as a powerful approach to describe exposures to these natural compounds and to discover biomarkers of exposure for a large diversity of foods.<br />
<br />
===Q2===<br />
<br />
2. What have you been working on recently?<br />
<br />
We are active in several research areas using metabolomics:<br />
- The identification of metabolic profiles associated with cancer outcomes in prospective epidemiological studies. We apply targeted and untargeted metabolomics approaches in case-control studies nested in large cohorts to identify metabolic features characterizing individuals who will later develop cancer. We can thus learn about mechanisms contributing to the risk of developing various cancers.<br />
- The discovery of novel biomarkers of dietary exposures suspected to play a role in the etiology of cancer and not easily assessed with dietary questionnaires commonly used in epidemiological studies. Recent work was focused on different types of coffee brews or on various processed meat products, respectively decreasing or increasing risk of some cancers.<br />
- The measurement of the internal exposome (all chemicals/metabolites that can be used as indicators of exposures to disease risk factors). We are partners in EXPANSE, a large European project, aiming at characterizing the urban exposome. As part of this project, we will analyze 10,000 blood samples from 15 different cohorts in Europe.<br />
<br />
===Q3===<br />
<br />
3. Do you think the identification of dietary biomarkers can aid in the prevention of specific types of cancer?<br />
<br />
Many dietary biomarkers are now known, and some have been used in cancer epidemiology (http://exposome-explorer.iarc.fr/). Recent development of metabolomics has speed up discovery of novel dietary biomarkers. These biomarkers can be used to improve measurement of dietary exposures in epidemiological studies and strengthen the evidence on the role of dietary factors (food, nutrient or food constituent) in the etiology of different types of cancer. This evidence is regularly reviewed and constitutes the basis for cancer prevention.<br />
<br />
===Q4===<br />
<br />
4. What are the current challenges for discovering dietary biomarkers for cancer risk in large epidemiological studies ?<br />
<br />
Two of the main challenges are the limited sensitivity of current methods and instruments to measure hundreds to thousands food compounds/metabolites in human blood or urine and the need for biological samples with high-quality metadata on dietary exposures and potential confounders. To address the first limitation, more sensitive targeted assays will be needed to measure large panels of dietary biomarkers. Dietary intervention studies are the gold standard to address the second limitation, but only a limited number of foods can be tested. Cross-sectional studies with high quality and highly detailed dietary data (e.g. from 24-hr dietary recalls) can also be used to cover a large diversity of foods.<br />
<br />
===Q5===<br />
<br />
5. What would your advice be for people getting started in food metabolomics?<br />
<br />
I would say to have a good knowledge of food chemistry and metabolism, and secondly to have access to human samples from either dietary intervention studies or epidemiological studies. It is always possible to run your own intervention studies or to establish your own cohort study. This requires time and money. You can also collaborate with clinicians and epidemiologists, and bring knowledge and resources to run metabolomics analyses on human biospecimens they collected. This is what I did when developing this research first at the French National Institute of Agricultural Research (INRAe) and for the last ten years at the International Agency for Research on Cancer.<br />
<br />
===Q6===<br />
<br />
6. You are the Biomarkers Group Leader at the International Agency for Research on Cancer. What do you think contributed significantly to your career path in becoming a group leader?<br />
<br />
Firstly, a desire for change and the wish to explore a new field of research, working with new people, in a new environment (about every 10 years in my own career, from wood chemistry to cancer epidemiology). Each of these changes was very demanding but also very rewarding. Secondly, the will of the Director of IARC at the time to start this new group to introduce metabolomics at IARC and develop its applications to cancer epidemiology, and lastly some experience in metabolomics, at a time when it was not as common as today.<br />
<br />
==See also==<br />
<br />
[[Category:Expert Opinion]]</div>EvelinaCharidemou