Director of Research, Colin Kay, PhD
Director of Operations, Renny Lan, PhD
The ACNC Metabolomics and Analytical Chemistry Core includes a full range of precision analytical instruments for detection, isolation, and purification of bioactive compounds and metabolites from plants, food matrices, and human/animal tissues. These systems contribute to the identification, and metabolomic fingerprinting, of fruits, vegetables, botanicals, and their metabolites.
- Thermo Q-Exactive system for untargeted lipidomics analysis and targeted metabolomics projects using the PRM method
- Thermo Orbitrap Exploris 480 MS for untargeted or semi-targeted metabolomics analysis, using AcquireX data acquisition to increase quantification of less-abundant metabolites and reduce background noise
- In our untargeted metabolomics workflow, an in-house spectral library contains more than 400 compounds (mainly microbial metabolites of dietary components) is built in our Q Exactive and Exlporis 480 system which aims to achieve level 1 data/compound identification on top of the cloud libraries (NIST and mzCloud) in metabolomics data processing
- A quantitative dietary phytochemical metabolite profiling workflow utilizing a SCIEX 7500+ enhanced high performance hybrid triple quadrupole MS, the Cores primary tool for targeted quantitative metabolite profiling and having MS(n) data capture, the system is capable of fragmentation profiling, isotope pattern verification, and targeted and untargeted scanning, affording the elucidation of both known and novel structures
- A Waters Select Series Cyclic Ion Mobility System (cIMS) separates ions based on their shapes, valuable for lipid analysis
- A Waters Xevo TQS micro Triple Quadrupole MS is used to build MRM methods for differential targeted assays including amino acids, bile acids, short chain fatty acids, acylcartines, tryptophan metabolism and many phytochemicals and is supported by a Waters PDa/QDa system to profile and complete quantitative analysis in food and botanical systems
- Analytical workflows are supported by two automated fluid handling platforms – Tecan Freedom Evo 150 fluid handling and automation system and Waters Andrews Alliance Pipetting Robot. The Tecan is comprised of a Span-8 and 96-well head capable of processing 96-well plates with high-throughput and unparalleled reproducibility. The fluid handling robot platforms can be modified for any application, including automated centrifugation, agitation, and positive-pressure manifold fluid extraction. Present workflows are configured to provide automated sample processing for 96-well solid-phase or liquid-liquid extraction (SPE or LLE). Plate relocation arm can move plates onto shakers, vortexes, vacuum manifolds for processing stages or can stack plates for higher throughput needs. Capable of processing over 5, 96-well plates per hour, the Tecan provides highly reproducible data which far exceeds human pipetting tolerance (CV<2%). Intelligent software is capable of regulatory compliance and validation tracking and can be equipped with a barcode reader for optimal chain-of-custody data reporting.
Also accessible through the Metabolomic and Analytical Core are advanced isothermal titration calorimeter (Microcal PEAQ-ITC, Malvern USA), Circular Dichroism (CD spectropolarimeter, J-1500 model, Jasco instruments, USA) and Oxytherm+ respirometer (Hansatech USA), ACTA Purification (GE USA) instruments for conducting biochemical and biophysical research in the fields of protein-ligand interactions and mitochondrial oxidative phosphorylation studies.
ACRI/NCSU Food Metabolome Database (P-MetDB) is a resource created in 2016 and is under continuous development and extends previous metabolite identifications provided by existing online food composition and metabolomic databases, including FooDB/HMDB, PhytoHub, PhenolExplorer, and USDA food composition databases. The current database was established by assessing what people eat using a) NHANES self-reported dietary intake data; b) and USDA consumer purchase records; and c) systematic reviews of the literature, capturing compounds reported in these phytochemical rich-dietary sources, and/or metabolites reported in biospecimens as derived from those foods; d) extracting chemical identifiers from online databases (i.e., Inchikey, chemical formula, accurate mass, PubChem ID); and e) MS(n) fragmentation voltages and profiles from the optimization of purchased reference standards for the captured compounds; ultimately creating a master dataset of compounds for library construction. In addition, the Kay-Lab modelled additional metabolites, using known routes of microbial, phase I (e.g., oxidation, reduction, or hydrolysis), and phase II conjugation (e.g., sulfate, glucuronides, or methyl conjugates). The Kay lab’s in-house phytochemical metabolome database will inform unique vs common metabolites predictive of diets rich in plant-products, and human and microbial metabolism.
ACRI/UNC/NCSU Metabolome of Food (MetaboFood®) knowledge DB (metabofood.org) is a novel database targeting personalized nutrition, which supports the lay public and researchers in nutrition, epidemiology, metabolomics, exposomics, microbiology, toxicology and medicine. MetaboFood-KDB is a food composition knowledgebase which captures chemical, analytical, spectral, and biological data; and having a data visualization interface provides users the ability to explore connections or relationships between food, diet, the human metabolome, biochemical pathway and disease pathology. This Cloud knowledgebase is a joint initiative developed by UNC and NCSU (and supported by the NC HHEAR Hub and IAFNS) to facilitate exploring complex interactions between diet, metabolism, biochemical pathways using graph database structure. MetaboFood® captures targets identified in USDA database and through systematic reviews of commonly consumed phytochemical-rich foods, and curation of compound synonyms matched to InChI Key, chemical (mass, formula etc.) and database identifiers (i.e., PubChem, HMDB, PhytoHub, KEGG etc.). MetaboFood® utilizes Flask, a micro web framework written in Python, with data visualization capabilities achieved using Self Organizing Maps (SOM), Node-link diagrams, bar charts, and Sankey diagrams.