<h4>Researchers will analyze materials from six disease study sites across US</h4>
Multi-omics is a research approach that leverages the power of several different “omics” data types at once to build a detailed picture of factors that contribute to human health and disease.
The National Institutes of Health (NIH) is channeling $50.3 million over the next five years into a new consortium dedicated to advancing the generation and analysis of multi-omics data for human health research. As part of this team, Washington University in St. Louis is establishing and will lead a central production center that functions as a hub for multi-omics analyses for materials from consortium members at each of six disease study sites identified by the NIH.
<a href="https://chemistry.wustl.edu/people/gary-patti?&amp;_ga=2.245277708.866671225.1710415924-433581621.1709556186">Gary Patti</a>, the Michael and Tana Powell Professor of Chemistry in Arts &amp; Sciences and a professor of medicine and of genetics at the School of Medicine, and <a href="https://genome.wustl.edu/people/ting-wang/?_ga=2.245277708.866671225.1710415924-433581621.1709556186">Ting Wang</a>, head of the Department of Genetics at the School of Medicine and the Sanford C. and Karen P. Loewentheil Distinguished Professor of Medicine, are principal investigators with the new consortium. Patti, who recently founded a multi-omics company called <a href="https://panomebio.com/">Panome Bio</a>, is an innovator in multi-omics research, and Wang is involved in multiple other NIH consortia, such as the <a href="https://medicine.wustl.edu/news/nih-funds-centers-to-improve-diversify-reference-human-genome/?_ga=2.20933809.866671225.1710415924-433581621.1709556186">Human Pangenome Reference Consortium</a>.
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Washington_University_in_St_Louis_Wash_U_leads_new_multi_omics_production_center_for_NIH_research_consortium_Patti_fa8e4a9e2a/Washington-University-in-St.-Louis-WashU-leads-new-multi-omics-production-center-for-NIH-research-consortium-Patti.jpg" alt="Washington University in St. Louis: WashU leads new multi-omics production center for NIH research consortium: Patti"/>
Collaborators will take advantage of cutting-edge resources at Washington University, such as the <a href="https://research.wustl.edu/core-facilities/center-for-metabolomics-and-isotope-tracing/?_ga=2.243156107.866671225.1710415924-433581621.1709556186">Center for Proteomics, Metabolomics, and Isotope Tracing</a> on the Danforth Campus. The university estimates the value of its portion of the new grant at $19.2 million.
“Most human diseases have complex origins that are influenced by a combination of genetic and environmental components such as diet, physical activity, exposure to pollutants and social determinants,” Patti said. “We are working to understand how disease develops in a person by studying the flow of molecular information at multiple levels of ‘omics’ in parallel.”
“*This consortium model eliminates one important barrier to progress by making it easier to collect multi-omics data from the same sets of samples and developing collaborative teams with the appropriate expertise to harmonize and integrate the results,*” he said.
<h4>A more holistic view</h4>
Multi-omics incorporates several “omics” data types, including genomics, epigenomics, transcriptomics, proteomics and metabolomics. Each of these data types reveals distinct information about different aspects of a biological system, and leveraging all these data types at once is becoming increasingly possible with advances in high-throughput technologies and data science.
The integration of multiple types of data from an individual participant’s biological sample can provide a more holistic view of the molecular factors and cellular processes involved in human health and disease, including untangling genetic and non-genetic factors in health and disease. This approach offers great promise in areas such as defining disease subtypes, identifying biomarkers and discovering drug targets.
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Washington_University_in_St_Louis_Wash_U_leads_new_multi_omics_production_center_for_NIH_research_consortium_Wang_017d37d6a5/Washington-University-in-St.-Louis-WashU-leads-new-multi-omics-production-center-for-NIH-research-consortium-Wang.jpg" alt="Washington University in St. Louis: WashU leads new multi-omics production center for NIH research consortium: Wang"/>
“*With each additional layer of omics information comes more clues about biology,” Wang said. “I’m really excited about the work we will do in this consortium to integrate genomics, proteomics and metabolomics data. This is the future of systems biology.*”
“*Beyond gaining insights into individual diseases, the primary goal of this consortium is to develop scalable and generalizable multi-omics research strategies as well as methods to analyze these large and complex datasets,” said Joannella Morales, a National Human Genome Research Institute (NHGRI) program director involved in leading the consortium. “We expect these strategies will ultimately be adopted by other research groups, ensuring the consortium’s work will have broad and long-lasting impacts for clinical research.*”
<a href="https://www.nih.gov/news-events/news-releases/nih-awards-503-million-multi-omics-research-human-health-disease">Funding for the consortium</a> will support work at six disease study sites, which will examine conditions such as fatty liver diseases, hepatocellular carcinoma, asthma, chronic kidney disease and preeclampsia, among others.
The sites will enroll research participants, at least 75% of whom will be from ancestral backgrounds underrepresented in genomics research. The sites also will collect data on participants’ environments and social determinants of health to be used in conjunction with the multi-omics data. Combining the multi-omic and environmental data can offer an even more comprehensive view of the factors that contribute to disease risk and outcomes.
Specimens provided by participants will be processed at the omics production center at Washington University, which will use high-throughput molecular assays to generate genomics, epigenomics, transcriptomics, proteomics and metabolomics data that will be analyzed to generate molecular profiles of disease and non-disease states.
A data analysis and coordination center will then incorporate all of these data into large, organized datasets that will be made available to the scientific community for further studies.
“*This is a rare opportunity to bring together a bunch of scientists with highly complementary expertise. I expect it to inspire breakthroughs in leveraging multi-omics approaches to understand disease,*” said <a href="https://chemistry.wustl.edu/people/leah-shriver?_ga=2.10043580.866671225.1710415924-433581621.1709556186">Leah Shriver</a>, a research associate professor of chemistry in Arts &amp; Sciences and a co-investigator on the research team.
“*Multi-omics studies are at the forefront of biomedical research and promise to advance our understanding of disease onset and progression,” said Erin Ramos, deputy director of NHGRI’s Division of Genomic Medicine. “All while potentially providing important clues for treatment design and drug-discovery efforts. This new consortium is an important step in making those advances a reality.*”
The award is funded jointly by NHGRI, the National Cancer Institute and the National Institute of Environmental Health Sciences.

WashU leads new multi-omics production center for NIH research consortium

Dear customers and business partners,
We are happy to announce our latest version of Clarity 9.1. This version introduces new control modules for Chromsystems, ECOM, and Welch. It also includes updated Advion, ECOM, Labio, NETEL, Sykam, YoungIn Chromass, and Agilent ICF control modules. A detailed list of changes is available in the What is new section on our web.
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DataApex Clarity 9.1 released

<h3>Tumors are composed of rapidly multiplying cancer cells. Understanding which biochemical processes fuel their relentless growth can provide hints at therapeutic targets.</h3>
Researchers from Washington University in St. Louis have developed a technology to study tumor growth in another dimension — literally. The scientists established a new method to watch what nutrients are used at which rates spatially throughout a tissue.
By using this multidimensional imaging approach, they identified pathways whose activities are uniquely elevated in brain cancer, offering clues for potential treatment strategies. The study was published May 19 in <a href="https://www.nature.com/articles/s41467-023-38403-x">Nature Communications</a>.
“*We figured out how to infer the rate of biochemical reactions directly from discrete regions of tissue,*” said <a href="https://chemistry.wustl.edu/people/gary-patti">Gary Patti</a>, the Michael and Tana Powell Professor of Chemistry in Arts &amp; Sciences and a professor of medicine at the School of Medicine. Patti, who is also a research member of the Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, is senior author of the new study.
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Washington_University_in_St_Louis_Wash_U_leads_new_multi_omics_production_center_for_NIH_research_consortium_Patti_fa8e4a9e2a/Washington-University-in-St.-Louis-WashU-leads-new-multi-omics-production-center-for-NIH-research-consortium-Patti.jpg" alt="Washington University in St. Louis: Patti"/>
Human biology is intrinsically 3D in nature. The emerging field of spatial biology aims to capture this geometry by imaging the locations of genes, proteins and metabolites. The approach reported by Patti and colleagues extends spatial profiling to fluxes, the rates at which molecules are transformed inside of cells.
<blockquote>
<h4>“Other technologies provide what is essentially a roadmap of biochemistry. Our goal was to add in a measurement of how fast traffic is flowing on the different roads.”</h4>
</blockquote>
<blockquote>
Gary J. Patti
</blockquote>
By Patti’s analogy, the new method is akin to the feature in Google Maps that uses green and red colors to indicate the density of cars on a given street.
Using a mouse model of glioblastoma, a deadly form of brain cancer in humans, the researchers created a high-resolution map of the “tumor ecosystem.” This allowed them to tell which molecules were located in what parts of the brain and how quickly those molecules were turning into other things.
The results shed light on how cancer cells in a brain tumor get lipids, a basic component of fat.
Lipids are required to make the outermost covering of a cell, known as a membrane. As cancer cells multiply, they need lipids to encase the new cells. Previous work from Patti had shown that cancer cells prefer to scavenge lipids from their local environments. But that was when cancer cells were cultured in isolation with lipids present in the media.
The new study showed that cancer cells in the brain tend to make, rather than siphon off, the lipids that they need to multiply.
“*The brain is a unique environment. The availability of lipids is more limited than in other tissues where tumors reside,*” Patti explained.
The speed at which some lipids were synthesized was as much as 8-fold higher in brain tumors compared with surrounding healthy tissue. Although the exact magnitude of the increase varied, the pattern was surprisingly consistent in cancer cells throughout the tumor.
“*A single tumor can span multiple different environments. The center might be hypoxic, while the outside is in contact with healthy tissue,” Patti said. “You might have predicted differences between these different regions, but we didn’t observe any patterns like that.*”
This finding is important because knowing that cancer cells within brain tumors rely on the same biochemical pathway to fuel their growth means that scientists could target it to slow or stop disease progression.
“*When a pathway is more active, its flux goes up. That makes it a good candidate for therapeutic intervention,” Patti said. “We are excited about testing whether impairment of fatty acid elongation will be effective in treating mouse models of disease.*”
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Washington_University_in_St_Louis_Spatial_metabolomics_images_of_a_brain_with_a_tumor_1c10f78195.jpg" alt="Washington University in St. Louis: Spatial metabolomics images of a brain with a tumor. Additional details available in Figure 8 from the technical article, “Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem.” (Image courtesy of Patti lab, Nature Communications)"/>
This study was funded in part by the McDonnell Center for Cellular and Molecular Neurobiology, as well as the National Institutes of Health grants R24 OD024624 and R35 ES2028365.

Cancer cells rev up synthesis, compared with neighbors

We are excited to introduce our Mnova Purification Suite, meticulously crafted to offer flexible, modular solutions that address the critical aspects of chromatographic purification. Our suite comprises three modules, each tailored to cater to distinct purification needs:
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Discover the optimal separation conditions for your compound through automated LC-MS data processing, method scoring, and report generation. This streamlines method development, allowing you to pinpoint the most suitable conditions for your compounds, thus minimizing trial-and-error iterations. <a href="http://www2.mestrelab.com/l/271522/2024-03-25/3nwskj">Learn more!</a>
<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Introducing_the_Mnova_Purification_Suite_your_solution_for_streamlined_chromatography_purifications_Optimizing_Separation_Conditions_with_Chrom_Best_Method_db29f3dcd9.jpg" alt="Mestrelab Research: Introducing the Mnova Purification Suite - Optimizing Separation Conditions with Chrom Best Method."/>
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<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Introducing_the_Mnova_Purification_Suite_your_solution_for_streamlined_chromatography_purifications_Fraction_Pooling_Decision_Support_with_Fraction_Analysis_ab756f1f64.jpg" alt="Mestrelab Research: Introducing the Mnova Purification Suite - Fraction Pooling Decision Support with Fraction Analysis."/>
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<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Mestrelab_Research_Introducing_the_Mnova_Purification_Suite_your_solution_for_streamlined_chromatography_purifications_Quality_Control_Checks_with_Chrom_QC_4c4f1079de.jpg" alt="Mestrelab Research: Introducing the Mnova Purification Suite - Quality Control Checks with Chrom QC."/>
Whether you choose to implement these modules individually or seamlessly integrate them into an enterprise solution is entirely your prerogative. Flexibility is at the core of our philosophy, and we strive to ensure that our solutions align with your evolving needs.
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If you&#39;re eager to explore our purification data workflows and automation solutions further, or if you have specific inquiries, please do not hesitate to <a href="https://www2.mestrelab.com/l/271522/2022-10-04/3836s2">reach out to us</a>! We are here to assist you every step of the way.

Introducing the Mnova Purification Suite: your solution for streamlined chromatography purifications!

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Introducing the Mnova Purification Suite: your solution for streamlined chromatography purifications!

Cancer cells rev up synthesis, compared with neighbors

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WashU leads new multi-omics production center for NIH research consortium

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