Global Untargeted Molecular Omics (Discovery) Archives - Center for Innovative Technology /cit Integrated ‘omics’ capabilities utilizing state-of-the-art multi-dimensional mass spectrometry and automated high content microscopy Mon, 08 Jun 2020 13:45:01 +0000 en-US hourly 1 https://wordpress.org/?v=5.8 https://cdn.vanderbilt.edu/vu-wp0/wp-content/uploads/sites/166/2019/02/27124736/WholeGear_Transparent-32x32.png Global Untargeted Molecular Omics (Discovery) Archives - Center for Innovative Technology /cit 32 32 A Guide to Metabolite Annotation: A Mini-Series (Part II) /cit/a-guide-to-metabolite-annotation-a-mini-series-part-ii/ Mon, 15 Jun 2020 07:37:09 +0000 /cit/?p=1509 The post A Guide to Metabolite Annotation: A Mini-Series (Part II) appeared first on Center for Innovative Technology.

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A Guide to Metabolite Annotation: A Mini-Series (Part II)


Collision Cross Section Data

Confident MS-based metabolite annotation requires experimental data that supports a specific molecule or class of compound. A high-resolution high-mass accuracy measurement is the first filter to determine metabolite candidates, and fragmentation (MS/MS) measurements are necessary to provide product ion knowledge that can help assign structural information.

For some isomeric small molecules, however, fragmentation data can be non-diagnostic. Retention time measurements obtained from liquid chromatography may resolve isomeric species, but in some cases, co-elution remains a concern. Ion mobility collision cross sections often provide additional confidence for isomeric, co-eluting species, by rendering orthogonal data to support annotations.

As such, members of the McLean Research Group and CIT have developed a collision cross section compendium to increase confidence in identifications and narrow the chemical search space for the small molecule omics community: 

Go to the publication

Collision Cross Section Data

Figure adapted from .



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Collision Cross Section Data
Metabolite Annotations
Katrina Leaptrot, Post Doc in the McLean Lab
Large Metabolomics Studies
High-Throughput Multi-Omic Analyses
qualitative amino acid panel

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A Guide to Metabolite Annotation: A Mini-Series /cit/a-guide-to-metabolite-annotation-a-mini-series/ Mon, 08 Jun 2020 07:33:40 +0000 /cit/?p=1505 The post A Guide to Metabolite Annotation: A Mini-Series appeared first on Center for Innovative Technology.

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A Guide to Metabolite Annotation: A Mini-Series (Part I)


Annotation can be a major hurdle for untargeted metabolomics workflows. In these types of analyses, the experimental mass for each compound of interest is compared against databases of known compound masses to generate a list of candidate matches. High-resolution high-mass accuracy instruments such as those housed in the CIT can minimize a list of candidates by applying a narrow mass tolerance window, thus minimizing false positive hits (as shown below). MS measurements alone are often only capable of determining molecular formula. In our next Molecular Omics update, you’ll see how additional orthogonal data (i.e., retention time, fragmentation data, and collision cross sections) can guide structure elucidation and increase metabolite annotation confidence.

Metabolite Annotations


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Small Molecule Omics and Cancer Biology /cit/small-molecule-omics-cancer-biology/ Tue, 14 Jan 2020 15:07:10 +0000 /cit/?p=1474 The post Small Molecule Omics and Cancer Biology appeared first on Center for Innovative Technology.

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Small Molecule Omics and Cancer Biology


“Oncometabolites” initiate or sustain cancer tumor growth and metastasis. The term oncometabolite was first used for 2- hydroxyglutarate, as it was found to activate hypoxiainduced, oncogenic pathways and affect DNA methylation, specifically in gliomas and acute myeloid leukemia.1 Understanding metabolic factors that enable cancer cell proliferation and finding reprogrammed metabolic pathways has led to several other oncometabolic targets (or metabolites) to be discovered.2-4 Of the metabolites involved in cancer biology, lipids have not only been shown to be involved in intracellular signaling of cancer cells, but de novo lipid synthesis has been found to be a key metabolic activity in cancer cell growth and survival and targeting lipid metabolic pathways has been shown to affect chemosensitivity.3,5 Previous data has also shown that branched-chain amino acid (BCAA) can serve as metabolic substrates in several types of cancer.6



The CIT has developed a conformational lipid atlas containing highly-accurate structural measurements in support of high-confidence lipidomic annotations. This lipid atlas is available in the CIT to help us and our collaborators better understand the role of lipids in cancer. Please contact us if you are interested in performing analyses to determine which lipids may be contributing to or reprogramming cancer cell proliferation in your specific biological system.

In addition, the CIT has also developed a qualitative amino acids MS-based assay that can be applied to diverse biological sample types (e.g. plasma, serum, urine, cells or tissue) without the need for tagging. These analyses are performed with high precision (≤ 5 ppm) and low variability (≤ 10% RSD).



References:

  1. Wishart DS, Emerging applications of metabolomics in drug discovery and precision medicine, Nat Rev Drug Discov 2016, 15, 473-484.
  2. Luengo A et al., Targeting Metabolism for Cancer Therapy, Cell Chem Biol 2017, 24, 1161-1180.
  3. Röhrig F et al., The multifaceted roles of fatty acid synthesis in cancer, Nat Rev Cancer 2016, 16, 732-749.
  4. Adams JL et al., Big opportunities for small molecules in immuno-oncology, Nat Rev Drug Discov 2015, 14, 603-622.
  5. Beloribi-Djefaflia S, Vasseur S, Guillaumond F, Lipid metabolic reprogramming in cancer cells, Oncogenesis 2016, 5, e189.
  6. Mayers JR, et al., Tissue of origin dictates branched-chain amino acid metabolism in mutant Kras-driven cancers, Science 2016, 353, 1161-1165.

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Quantity of Identified Metabolites in Untargeted Experiments /cit/quantity-identified-metabolites-untargeted-experiments/ Thu, 21 Feb 2019 14:01:19 +0000 /cit/?p=1058 The post Quantity of Identified Metabolites in Untargeted Experiments appeared first on Center for Innovative Technology.

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How Many Metabolites will be Identified in a Global, Untargeted Metabolomics Study?


This is a difficult question to answer!

The CIT typically observes between 500 and 10,000 compounds, depending on sample type. It is important to note that there is a range of annotation confidences assigned to each detected compound. The CIT uses a classification system to describe annotation confidence. Briefly, more experimental evidence (e.g., diagnostic fragmentation data, retention time, collision cross section, reference standard, etc.) enables a higher confidence metabolite identification assignment. While some compounds can be unambiguously identified (Level 1), others may be reported in groups (multiple candidate annotations; Level 3) owing to the fact that numerous metabolites are isomeric and metabolite databases are inherently incomplete. We search our extensive in-house library to reduce the number of candidates and/or increase the confidence of candidates when possible.

This classification scheme is widely adopted by the metabolomics community, see for more information.





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High-Throughput Multi-Omic Analyses /cit/high-throughput-multi-omics/ Mon, 21 Jan 2019 13:12:58 +0000 /cit/?p=996 The post High-Throughput Multi-Omic Analyses appeared first on Center for Innovative Technology.

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Multi-disciplinary collaboration across campus:

An Integrated, High-Throughput Strategy for Multi-Omic Analyses


In collaboration with the ý DARPA RTA Team (R. Caprioli, E. Skaar, J. Wikswo, J. McLean, B. Lacey, J. Norris), the CIT has contributed to developing an automated multi-omic sample preparation approach. The approach, sample preparation for multi-omics technologies (SPOT), provides equivalent performance to typical individual omic preparation methods but greatly enhances throughput and minimizes the resources required for multiomic experiments. In this manuscript, SPOT was used to understand the mechanism of action of Zn-treated HL-60 cells using transcriptomic, proteomic and metabolomic data generated from a common cell culture sample.

The details are available in the Journal of Proteome Research:



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Discovery-Based Metabolomics Reveals MBLAC1 Functionality /cit/discovery-based-metabolomics/ Tue, 08 Jan 2019 15:13:04 +0000 /cit/?p=991 The post Discovery-Based Metabolomics Reveals MBLAC1 Functionality appeared first on Center for Innovative Technology.

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Discovery-Based Metabolomics Lifts the Curtain on MBLAC1 Gene’s Functional Roles


A research project lead by Professor Blakely (Florida Atlantic University) in collaboration with the Center for Innovative Technology (CIT) at ý has been investigating the physiological role of the MBLAC1 gene via global, untargeted mass spectrometry analysis. In the serum metabolome the team was able to discover unique differences in primary bile acid biosynthesis and linoleate metabolism between MBLAC1 knock-out and age-matched wild-type mice. Future targeted metabolomics studies are expected to reveal the MBLAC1 substrate and its related neuroprotective effects.

The full, peer-reviewed publication can be found .



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