Biology subjects

Ellis, A. E.

Publications and source records attributed to Ellis, A. E..

12 recordsLinked to original sources

bioRxiv2026

Reducing background ion burden in tributylamine ion-pairing LC-MS improves signal intensity and feature coverage in metabolomics

Background chemical ions are a pervasive but often underappreciated limitation in LC-MS metabolomics, where they can suppress analyte signal, obscure endogenous metabolites, increase spectral complexity, and consume MS/MS acquisition events. Tributylamine (TBA) ion-pairing reversed-phase LC-MS provides stable retention and broad coverage of polar anionic metabolites, including central carbon intermediates, nucleotides, cofactors, and bile acids, but the back-ground burden introduced by the ion-pairing reagent itself has not been systematically addressed. Here, we identify commercial TBA as a major source of nonbiological contaminant ions and develop a practical strategy to reduce background burden while preserving metabolite coverage. Serial solid-phase extraction of TBA using orthogonal reversed-phase, strong anion-exchange, and strong cation-exchange sorbents removed chemically diverse contaminants, including isobaric background ions that interfered with endogenous hydroxybutyrate isomers. We further optimized the workflow by reducing medronic acid concentration, restricting medronic acid to the organic mobile phase, replacing phosphoric-acid column conditioning with metal-passivated column hardware, and adding EDTA to the sample reconstitution solvent to improve citrate detection. In mouse liver extracts, the optimized method increased signal intensity for most annotated metabolites and improved the fraction of full-scan ion current attributable to target analytes. Method optimization also altered compound-specific retention behavior, resolving some co-elution-based interferences while introducing new suppression relationships for selected analytes. Across mouse liver, human B lymphocytes, and NIST SRM 1950 plasma, the optimized workflow increased total feature detection by 45%, 72%, and 42%, respectively, and improved the number of low-variance features, precursors with data-dependent MS/MS spectra, and MS/MS library matches. These findings establish background-ion mitigation as a central design principle for LC-MS method development. More broadly, this work provides a generalizable framework for identifying, reducing, and validating reagent- and additive-derived background to improve targeted and untargeted LC-MS data quality.

biochemistry↗

bioRxiv2026

Complementary Single-Cell Microflow HILIC and Ion Pair LC-MS Reveal Bystander Metabolic Effects in a Macrophage Model of Tuberculosis

Single-cell metabolomics remains analytically challenging due to the low abundance and chemical diversity of metabolites in individual cells. We have developed complementary microflow HILIC and ion pair LC-MS methods to expand metabolite coverage in single macrophages. Ion pair LC-MS was applied to single cells for the first time, enabling retention of highly polar and ionic metabolites that elute early under conventional reversed-phase conditions. Across Mycobacterium bovis BCG infected, uninfected bystander, and control unexposed THP-1 macrophages, both microflow methods detected significantly more features than a previously reported analytical-flow HILIC method. The two microflow methods provided complementary chemical space, together yielding 633 unique named metabolites with MS2 spectra. This depth enabled pathway-level interpretation at single-cell resolution, revealing infection-associated changes in purine-, arginine-, glutathione-, and one-carbon folate-associated metabolism. Metabolite-level interrogation indicated shared purine and amino acid changes in both infected and neighbouring macrophages, while revealing a distinct bystander phenotype characterised by elevated glycine and heterogeneous ATP levels. Finally, we demonstrate sequential IP and HILIC analysis of the same single cell, establishing a route toward maximal coverage from individual cells. These results position microflow HILIC and IP LC-MS as powerful, orthogonal strategies for advancing single-cell metabolomics and unveiling heterogeneity within complex biological microenvironments. Table of Contents O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/733771v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@103ecfforg.highwire.dtl.DTLVardef@bc6734org.highwire.dtl.DTLVardef@11b96aforg.highwire.dtl.DTLVardef@41edfe_HPS_FORMAT_FIGEXP M_FIG Figure made in BioRender. C_FIG

microbiology↗

bioRxiv2026

Nanoflow ion-pairing LC-MS for ultra-low-input polar metabolomics and isotope tracing

Low-input and single-cell metabolomics remain constrained by the poor retention of polar metabolites in conventional reversed-phase nanoflow LC-MS workflows. Here, we establish nanoflow tributylamine (TBA) ion-pairing LC-MS as a platform for ultra-low-input polar metabolomics and stable isotope tracing. By adapting an analytical-flow TBA ion-pairing method to the nanoflow scale, this workflow extends the sensitivity and inline concentration advantages of nanoflow chromatography to charged metabolites involved in central carbon metabolism. Using mouse liver metabolite extracts, we show that the nanoflow method preserves chromatographic retention and separation of chemically diverse metabolite classes, including adenine nucleotides, nucleotide cofactors, TCA cycle intermediates, acyl-CoAs, and bile acid isomers. Despite loading 20-fold less tissue-equivalent material on column, nanoflow LC-MS produced higher signal intensity than the analytical-flow method for many metabolites. Across representative compounds, the nanoflow workflow reduced the biomass required for detection by approximately 20- to >600-fold, with pronounced gains for low-abundance metabolites such as NADPH and acetyl-CoA. TBA ion-pairing also enabled trap-and-elute nanoflow analysis of retained polar metabolites from single-cell-equivalent inputs. ATP was detected from one cell equivalent using both full-scan and targeted parallel reaction monitoring acquisition, with targeted acquisition further increasing signal over blank. Finally, we applied the workflow to stable isotope tracing in uniformly labeled 13C-glucose-treated cells. 13C-labeled ATP isotopologues were detectable from single-cell-equivalent input, and targeted acquisition improved isotopologue measurement near the detection limit. Together, these results demonstrate that nanoflow TBA ion-pairing LC-MS enables retained, high-sensitivity analysis of polar metabolites from ultra-low inputs and provides a foundation for extending central carbon metabolite analysis and isotope tracing toward single-cell-scale applications.

biochemistry↗

bioRxiv2026

Functional partitioning of lipoic acid decouples cellular abundance from mitochondrial utilization

-Lipoic acid (LA) is widely included in "mitochondrial cocktails" recommended to patients with primary mitochondrial disorders, yet its mechanism of action remains unclear. Here, we define the intracellular availability and functional utilization of LA in mammalian cells. We show that LA exists in two functionally distinct cellular pools: a low-abundance free pool and a protein-bound pool generated through mitochondrial fatty acid synthesis (mtFAS). Disruption of the mtFAS pathway abolishes protein lipoylation and impairs oxidative phosphorylation without altering free LA levels. Conversely, supplementation with exogenous LA markedly increases free intracellular LA without restoring protein lipoylation, mitochondrial respiration, or cell proliferation. Instead, the cellular effects of LA supplementation resemble those of the antioxidant N-acetylcysteine. These findings clarify the mechanism of action of a widely used mitochondrial supplement and identify a fundamental disconnect between cellular LA abundance and mitochondrial utilization, challenging the rationale for using LA supplementation to restore mitochondrial function.

biochemistry↗

bioRxiv2026

Cells Engage Endogenous Malonate Synthesis to Drive Mitochondrial Metabolism

Malonate is often described as an endogenous inhibitor of complex II of the electron transport chain. However, the cellular source of malonate is unclear, and current knowledge concerning its metabolism is limited to the action of a single enzyme, Acyl-CoA Synthetase Family Member 3 (ACSF3), which converts malonate to malonyl-CoA in the mitochondrial matrix. One potential route of malonate metabolism downstream of ACSF3 is its consumption by the mitochondrial fatty acid synthesis (mtFAS) pathway. However, studies examining the link between ACSF3 and mtFAS have yielded conflicting results. We developed a novel mass spectrometry approach to perform stable isotope tracing into products of mtFAS, and found that while malonate is in fact a carbon source for mtFAS, ACSF3 is not required for malonate incorporation into mtFAS products. Using this method to trace other nutrients into mtFAS, we also found evidence of acetyl-CoA carboxylase 1 (ACC1)-dependent malonate synthesis from glucose. We further show that ACC1 is required for optimal mtFAS activity, with downstream effects on oxidative phosphorylation. Together these findings establish the malonate as a regulated endogenous intermediate that supports mtFAS activity and mitochondrial oxidative function.

biochemistry↗

bioRxiv2024

Dietary Restriction Enhances CD8+ T Cell Ketolysis to Limit Exhaustion and Boost Anti-Tumor Immunity

Reducing calorie intake without malnutrition limits tumor progression but the underlying mechanisms are poorly understood. Here we show that dietary restriction (DR) suppresses tumor growth by enhancing CD8+ T cell-mediated anti-tumor immunity. DR reshapes CD8+ T cell differentiation within the tumor microenvironment (TME), promoting the development of effector T cell subsets while limiting the accumulation of exhausted T (Tex) cells, and synergizes with anti-PD1 immunotherapy to restrict tumor growth. Mechanistically, DR enhances CD8+ T cell metabolic fitness through increased ketone body oxidation (ketolysis), which boosts mitochondrial membrane potential and fuels tricarboxylic acid (TCA) cycle-dependent pathways essential for T cell function. T cells deficient for ketolysis exhibit reduced mitochondrial function, increased exhaustion, and fail to control tumor growth under DR conditions. Our findings reveal a critical role for the immune system in mediating the anti-tumor effects of DR, highlighting nutritional modulation of CD8+ T cell fate in the TME as a critical determinant of anti-tumor immunity.

immunology↗

bioRxiv2024

Glucose-dependent glycosphingolipid biosynthesis fuels CD8+ T cell function and tumor control

Glucose is essential for T cell proliferation and function, yet its specific metabolic roles in vivo remain poorly defined. Here, we identify glycosphingolipid (GSL) biosynthesis as a key pathway fueled by glucose that enables CD8+ T cell expansion and cytotoxic function in vivo. Using 13C-based stable isotope tracing, we demonstrate that CD8+ effector T cells use glucose to synthesize uridine diphosphate-glucose (UDP-Glc), a precursor for glycogen, glycan, and GSL biosynthesis. Inhibiting GSL production by targeting the enzymes UGP2 or UGCG impairs CD8+ T cell expansion and cytolytic activity without affecting glucose-dependent energy production. Mechanistically, we show that glucose-dependent GSL biosynthesis is required for plasma membrane lipid raft integrity and aggregation following TCR stimulation. Moreover, UGCG-deficient CD8+ T cells display reduced granzyme expression and tumor control in vivo. Together, our data establish GSL biosynthesis as a critical metabolic fate of glucose--independent of energy production--required for CD8+ T cell responses in vivo.

immunology↗

bioRxiv2024

NRF2-dependent regulation of the prostacyclin receptor PTGIR drives CD8 T cell exhaustion

The progressive decline of CD8 T cell effector function--also known as terminal exhaustion--is a major contributor to immune evasion in cancer. Yet, the molecular mechanisms that drive CD8 T cell dysfunction remain poorly understood. Here, we report that the Kelch-like ECH-associated protein 1 (KEAP1)-Nuclear factor erythroid 2-related factor 2 (NRF2) signaling axis, which mediates cellular adaptations to oxidative stress, directly regulates CD8 T cell exhaustion. Transcriptional profiling of dysfunctional CD8 T cells from chronic infection and cancer reveals enrichment of NRF2 activity in terminally exhausted (Texterm) CD8 T cells. Increasing NRF2 activity in CD8 T cells (via conditional deletion of KEAP1) promotes increased glutathione production and antioxidant defense yet accelerates the development of terminally exhausted (PD-1+TIM-3+) CD8 T cells in response to chronic infection or tumor challenge. Mechanistically, we identify PTGIR, a receptor for the circulating eicosanoid prostacyclin, as an NRF2-regulated protein that promotes CD8 T cell dysfunction. Silencing PTGIR expression restores the anti-tumor function of KEAP1-deficient T cells. Moreover, lowering PTGIR expression in CD8 T cells both reduces terminal exhaustion and enhances T cell effector responses (i.e. IFN-{gamma} and granzyme production) to chronic infection and cancer. Together, these results establish the KEAP1-NRF2 axis as a metabolic sensor linking oxidative stress to CD8 T cell dysfunction and identify the prostacyclin receptor PTGIR as an NRF2-regulated immune checkpoint that regulates CD8 T cell fate decisions between effector and exhausted states. One Sentence SummaryThe KEAP1-NRF2 pathway is hyperactivated in terminally exhausted CD8 T cells and drives T cell dysfunction via transcriptional regulation of the prostacyclin receptor, Ptgir.

immunology↗

bioRxiv2024

Lipid availability influences ferroptosis sensitivity in cancer cells by regulating polyunsaturated fatty acid trafficking

Ferroptosis is a form of cell death caused by lipid peroxidation that is emerging as a target for cancer therapy, highlighting the need to identify factors that govern ferroptosis susceptibility. Lipid peroxidation occurs primarily on phospholipids containing polyunsaturated fatty acids (PUFAs). Here, we show that even though extracellular lipid limitation reduces cellular PUFA levels, lipid-starved cancer cells are paradoxically more sensitive to ferroptosis. Using mass spectrometry-based lipidomics with stable isotope fatty acid labeling, we show that lipid limitation induces a fatty acid trafficking pathway in which PUFAs are liberated from triglycerides to synthesize highly unsaturated PUFAs such as arachidonic acid and adrenic acid. These PUFAs then accumulate in phospholipids, particularly ether phospholipids, to promote ferroptosis sensitivity. Therefore, PUFA levels within cancer cells do not necessarily correlate with ferroptosis susceptibility. Rather, how cancer cells respond to extracellular lipid levels by trafficking PUFAs into proper phospholipid pools dictates their sensitivity to ferroptosis.

cancer biology↗

bioRxiv2023

A diverse proteome is present and enzymatically active in metabolite extracts

Metabolomics, a foundational tool in metabolism research, relies on the accurate transmittal of biochemical profiles underlying biological phenotypes. Over the years, workflows used in metabolomics have been assumed to remove enzymes to preserve metabolite levels during processing. Here, we uncover a diverse landscape of over 1,000 proteins, strongly enriched for metabolic enzymes, within metabolite extracts generated using common extraction workflows. Moreover, by combining in-extract stable isotope additions and enzyme inhibitors, we demonstrate transaminase activity, which is preventable by protein removal by 3 kDa filtration. We extend these findings to untargeted metabolomics, revealing that both post-extraction formation of glutamate dipeptide and depletion of total glutathione can also be prevented by removing proteins. Finally, we present a simple yet novel workflow that integrates passive filtration for protein removal of crude metabolite extracts as a superior method for broad-coverage metabolomics. Our findings have broad-reaching experimental implications across all fields that use metabolomics and molecular metabolism, especially cancer, immunology, and diabetes research.

biochemistry↗

bioRxiv2023

NF1 deficiency drives metabolic reprogramming in ER+ breast cancer

ObjectiveNF1 is a tumor suppressor gene and its protein product, neurofibromin, is the key negative regulator of the RAS pathway. NF1 is one of the top driver mutations in sporadic breast cancer such that 27% of breast cancers exhibit damaging NF1 alterations. NF1 loss-of-function is a frequent event in the genomic evolution of estrogen receptor (ER)+ breast cancer metastasis and endocrine resistance. Individuals with Neurofibromatosis type 1 (NF) - a disorder caused by germline NF1 mutations - have an increased risk of dying from breast cancer [1-4]. NF-related breast cancers are associated with decreased overall survival compared to sporadic breast cancer. Despite numerous studies interrogating the role of RAS mutations in tumor metabolism, no study has comprehensively profiled the NF1-mutant breast cancer metabolome to define patterns of energetic and metabolic reprogramming. The goals of this investigation were (1) to define the role of NF1 deficiency in estrogen receptor-positive (ER+) breast cancer metabolic reprogramming and (2) to identify potential targeted pathway and metabolic inhibitor combination therapies for NF1-deficient ER+ breast cancer. MethodsWe employed two ER+ NF1-deficient breast cancer models: (1) an NF1-mutant MCF7 breast cancer cell line to model sporadic breast cancer, and (2) three distinct, Nf1-deficient rat models to model NF- related breast cancer [1]. IncuCyte proliferation analysis was used to measure the effect of NF1 deficiency on cell proliferation and drug response. Protein quantity was assessed by Western Blot analysis. We then used RNAseq to investigate the transcriptional effect of NF1 deficiency on global and metabolism-related transcription. We measured cellular energetics using Agilent Seahorse XF-96 Glyco Stress Test and Mito Stress Test assays. We performed stable isotope labeling and measured [U-13C]- glucose and [U-13C]-glutamine metabolite incorporation and measured total metabolite pools using mass spectrometry. Lastly, we used a Bliss synergy model to investigate NF1-driven changes in targeted and metabolic inhibitor synergy. ResultsOur results revealed that NF1 deficiency enhanced cell proliferation, altered neurofibromin expression, and increased RAS and PI3K/AKT pathway signaling while constraining oxidative ATP production and restricting energetic flexibility. Neurofibromin deficiency also increased glutamine influx into TCA intermediates and dramatically increased lipid pools, especially triglycerides (TG). Lastly, NF1 deficiency alters the synergy between metabolic inhibitors and traditional targeted inhibitors. This includes increased synergy with inhibitors targeting glycolysis, glutamine metabolism, mitochondrial fatty acid transport, and TG synthesis. ConclusionsNF1 deficiency drives metabolic reprogramming in ER+ breast cancer. This reprogramming is characterized by oxidative ATP constraints, glutamine TCA influx, and lipid pool expansion, and these metabolic changes introduce novel metabolic-to-targeted inhibitor synergies. HIGHLIGHTSO_LINF1 deficiency drives metabolic reprogramming in ER+ breast cancer. C_LIO_LINF1-driven metabolic reprogramming is characterized by oxidative ATP constraints, glutamine TCA influx, and lipid pool expansion. C_LIO_LINF1-deficient ER+ breast cancer cells have increased sensitivity to a combination of RAS and triglyceride synthesis inhibitors. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/568339v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1f4d135org.highwire.dtl.DTLVardef@1d3168forg.highwire.dtl.DTLVardef@16e083forg.highwire.dtl.DTLVardef@df6c1d_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Combined single-sample metabolomics and RNAseq reveals a hepatic pyrimidine metabolic response to acute viral infection

ObjectiveMetabolomics and RNA sequencing (RNAseq) each provide powerful readouts of phenotype, and integration of these data can provide information greater than the sum of their parts. The ability to conduct such analysis on a single sample has many practical advantages, especially when dealing with rare or difficult-to-obtain samples. While methods exist to isolate multiple biomolecular subclasses from the same sample, in-depth analysis of the suitability of these approaches for multi- omics readouts is lacking. MethodsMice were injected with lymphocytic choriomeningitis virus (LCMV) or vehicle (Veh) control and liver tissue was harvested 2.5-days later. RNA was isolated from aliquots of pulverized liver tissue either following metabolite extraction using 80% methanol (MetRNA) or directly from frozen tissue (RNA). RNA sequencing data was evaluated by differential expression analysis via edgeR and dispersion using Ginis mean differences. Differential metabolite abundance was assessed using LIMMA. Pathway enrichment analysis was conducted on metabolomics and RNAseq data using MetaboAnalysts joint-integration tools. ResultsPrior metabolite extraction had no deleterious effects on quality or quantity of isolated RNA. RNA and MetRNA generated from the same sample clustered together by principal component analysis, indicating that inter-individual differences were the largest source of variance. Of the 2,169 genes that were differentially expressed between LCMV and Veh, the vast majority (n=1,848) were shared between extraction method, with the remainder evenly divided between RNA (n=165) and MetRNA (n=156). These differentially expressed genes unique to extraction method were attributed to randomness around the false discovery rate (FDR) = 0.05 cutoff and stochastic changes in variance estimation. Gini analysis further revealed that extraction method had no effect on the dispersion of detected transcripts across the entire dataset. To demonstrate the power of multi-omics integration on interrogated metabolic phenotypes, we next performed integrated pathway enrichment analysis on RNAseq data and metabolomics data. Our analysis revealed pyrimidine metabolism as the most impacted pathway by LCMV infection. Plotting up- and down-regulated genes and metabolites on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pyrimidine pathway exposed a pattern enzymatic degradation of pyrimidine nucleotides to generate the nucleobase uracil. Further, uracil was among the most differentially abundant metabolite in serum of LCMV infected mice, suggesting a novel mechanism of hepatic uracil export in acute infection response. ConclusionsWe demonstrate that prior metabolite extraction does not have a deleterious effect on RNAseq quality, which enables investigators to confidently perform metabolomics and RNAseq on the same sample. Implementation of this approach revealed a novel involvement of the hepatic pyrimidine metabolism during acute viral infection.

molecular biology↗