Trevor Glaros

Primary human hepatocytes (PHHs) are widely used as in vitro models for liver function and drug metabolism studies, yet their metabolic stability post-thawing remains an open question. To better characterize early metabolic changes, we conducted a time-course experiment using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze metabolic shifts in PHHs cultured in suspension. Unexposed and exposed (acetaminophen-treated) samples were evaluated, and TITAN analysis was applied to determine the time point of maximal metabolic change at both individual metabolite and global metabolic profile levels. Our results indicate that the majority of metabolic shifts occur within the first five hours post-thawing. In the early culture time points, substantial metabolic overlap was observed between unexposed and exposed cells, suggesting a conserved biological response likely related to cellular recovery. However, at later time points, metabolite profiles diverged, with acetaminophen treatment-specific metabolic changes emerging, potentially reflecting differences in homeostatic restoration versus hepatotoxic responses. Our study highlights the importance of considering early post-thawing metabolic dynamics in experimental design and offers insights for optimizing hepatocyte culture protocols to better replicate in vivo physiological conditions.

Omics-based measurements enable the study of biomolecules in a high-throughput fashion, leading to the characterization and quantification of biological systems. Multi-omics methods aim to incorporate several omics measurements for a more holistic approach, which is crucial for advancing our understanding of the diversity and redundancy of biological systems. Current multi-omics sample preparation methods have achieved proteomics, lipidomics, and metabolomics from individual samples; however, the bioinformatic tools currently available for interpreting data generated from these omics are limited. Alternately, transcriptomics has a wide arsenal of available bioinformatic tools offering intensive sample characterization but has yet to be incorporated into a unified, multi-omics sample preparation technique. Herein we describe the modified bead-enabled accelerated monophasic multi-omics (mBAMM) method, which incorporates RNA extraction for transcriptomics analysis. mBAMM was shown to enable RNA-seq without compromising the isolation of biomolecules for proteomics, lipidomics, and metabolomics. This methodology greatly improves sample characterization and represents a major innovation toward cohesive insights into biological systems.

Although classical molecular biology assays can provide a measure of cellular response to chemical challenges, they rely on a single biological phenomenon to infer a broader measure of cellular metabolic response. These methods do not always afford the necessary sensitivity to answer questions of subcytotoxic effects, nor do they work for all cell types. Likewise, boutique assays such as cardiomyocyte beat rate may indirectly measure cellular metabolic response, but they too, are limited to measuring a specific biological phenomenon and are often limited to a single cell type. For these reasons, toxicological researchers need new approaches to determine metabolic changes across various doses in differing cell types, especially within the low-dose regime. The data collected herein demonstrate that LC-MS/MS-based untargeted metabolomics with a feature-agnostic view of the data, combined with a suite of statistical methods including an adapted environmental threshold analysis, provides a versatile, robust, and holistic approach to directly monitoring the overall cellular metabolomic response to pesticides. When employing this method in investigating two different cell types, human cardiomyocytes and neurons, this approach revealed separate subcytotoxic metabolomic responses at doses of 0.1 and 1 µM of chlorpyrifos and carbaryl. These findings suggest that this agnostic approach to untargeted metabolomics can provide a new tool for determining effective dose by metabolomics of chemical challenges, such as pesticides, in a direct measurement of metabolomic response that is not cell type-specific or observable using traditional assays.

A novel multidimensional scan technique combining MS ¹ and MS/MS scans greatly enhances bacterial differentiation from low resolution data for clinical and field-forward applications.

By characterizing physiological changes that occur in warfighters during simulated combat, we can start to unravel the key biomolecular components that are linked to physical and cognitive performance. Viable field-based sensors for the warfighter must be rapid and noninvasive. In an effort to facilitate this, we applied a multiomics pipeline to characterize the stress response in the saliva of warfighters to correlate biomolecular changes with overall performance and health. In this study, two different stress models were observed – one of chronic stress and one of acute stress. In both models, significant perturbations in the immune, metabolic, and protein manufacturing/processing systems were observed. However, when differentiating between stress models, specific metabolites associated with the “fight or flight” response and protein folding were seen to be discriminate of the acute stress model.

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has provided some of the most in-depth analyses of the phenotypes of human tumors ever constructed. Today, the majority of proteomic data analysis is still performed using software housed on desktop computers which limits the number of sequence variants and post-translational modifications that can be considered. The original CPTAC studies limited the search for PTMs to only samples that were chemically enriched for those modified peptides. Similarly, the only sequence variants considered were those with strong evidence at the exon or transcript level. In this multi-institutional collaborative reanalysis, we utilized unbiased protein databases containing millions of human sequence variants in conjunction with hundreds of common post-translational modifications. Using these tools, we identified tens of thousands of high-confidence PTMs and sequence variants. We identified 4132 phosphorylated peptides in nonenriched samples, 93% of which were confirmed in the samples which were chemically enriched for phosphopeptides. In addition, our results also cover 90% of the high-confidence variants reported by the original proteogenomics study, without the need for sample specific next-generation sequencing. Finally, we report fivefold more somatic and germline variants that have an independent evidence at the peptide level, including mutations in ERRB2 and BCAS1. In this reanalysis of CPTAC proteomic data with cloud computing, we present an openly available and searchable web resource of the highest-coverage proteomic profiling of human tumors described to date.

The U.S. Department of Energy's Office of Scientific and Technical Information

The inhibition of acetylcholinesterase is regarded as the primary toxic mechanism of action for chemical warfare agents. Recently, there have been numerous reports suggesting that metabolic processes could significantly contribute to toxicity. As such, we applied a multi-omics pipeline to generate a detailed cascade of molecular events temporally occurring in guinea pigs exposed to VX. Proteomic and metabolomic profiling resulted in the identification of several enzymes and metabolic precursors involved in glycolysis and the TCA cycle. All lines of experimental evidence indicated that there was a blockade of the TCA cycle at isocitrate dehydrogenase 2, which converts isocitrate to α-ketoglutarate. Using a primary beating cardiomyocyte cell model, we were able to determine that the supplementation of α-ketoglutarate subsequently rescued cells from the acute effects of VX poisoning. This study highlights the broad impacts that VX has and how understanding these mechanisms could result in new therapeutics such as α-ketoglutarate.

Microneedles have been demonstrated to be a minimally invasive technique for sampling dermal interstitial fluid (ISF). Shotgun quantitative proteomics has already identified hundreds of proteins in ISF and quantitatively compared the proteome to matching serum and plasma. Interstitial fluid was determined to be a viable minimally invasive alternative to blood-derived fluids. In this communication, we re-examined the proteomic data from previous work to determine the diversity of immunoglobulins present compared to serum and plasma. Similar to our previous findings regarding the proteomic content across fluid types, ISF had a similar composition of IgG, IgA, IgD, and IgE antibodies as plasma or serum. However, IgM was expressed in lower quantities, which could limit utility of this fluid type for certain diagnostic applications. The work offers a proof of principle result of the approach previously developed towards the potential of ISF to be used in diagnostic purposes. Data are available via ProteomeXchange with identifier PXD012658.