Multiple sclerosis (MS) is a neurological condition characterized by recurrent inflammation, demyelination, axonal injury, and functional impairment. MS has a diverse array of clinical manifestations, with the progressiv...Multiple sclerosis (MS) is a neurological condition characterized by recurrent inflammation, demyelination, axonal injury, and functional impairment. MS has a diverse array of clinical manifestations, with the progressive variants leading to neurological impairment. Sensitive and accurate biomarkers are required to diagnose, predict disease progression, and guide MS management. Here, we utilized liquid chromatography-mass spectrometry-based proteomics (LC-MS/MS) to find biomarkers in serum from patients with MS. The study examined protein expression in healthy individuals (n = 20) and MS groups (n = 60), comprising 20 patients in each disease course (relapsing-remitting (RRMS), primary progressive (PPMS), and secondary progressive (SPMS)). An enzyme-linked immunosorbent assay (ELISA) was used to verify a candidate protein in serum samples from patients with MS (n = 18) and healthy controls (HC) (n = 15) (validation cohort). Our findings showed 12 differentially expressed proteins (DEPs). Among the discovered proteins, some have been previously documented in MS, while others constitute novel findings. We found two proteins, junction plakoglobin (JUP) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), that were downregulated and upregulated in patients with MS relative to HCs, respectively. ELISA validations were consistent with those from LC-MS/MS. Identification of these proteins may help elucidate pathogenic processes and support novel therapeutic methods for MS.
Both untargeted "discovery" and targeted lipid analyses were performed on liver extracts obtained from mice, following the intravenous administration (10 mg/kg) of the tyrosine kinase inhibitor gefitinib, to maximize cov...Both untargeted "discovery" and targeted lipid analyses were performed on liver extracts obtained from mice, following the intravenous administration (10 mg/kg) of the tyrosine kinase inhibitor gefitinib, to maximize coverage of the liver lipidome. Untargeted lipid analysis by RP-UHPLC-IM-MS in both +ve and -ve ESI showed time-related changes in lipid profiles, including reductions in the abundances of PCs and PEs and a concomitant rise in the LPCs. Targeted analysis by HILIC-UHPLC-MS using +ve ESI also showed time-related effects on the lipid profiles of gefitinib-dosed mice with PCs, SMs, TGs, and LPCs, particularly for the lipids PC(34:1), PC(32:1), SM(40:1), TG(48:1), and PC(32:0), and effects on a number of acyl carnitines were also noted. In addition, time-related effects were seen using -ve ESI on a range of lipids, including PGs, PCs, LPEs, PEs, and FFAs. The resulting data suggest widespread effects on fatty acid utilization and metabolism may occur in the liver of mice as a result of exposure to gefitinib.
Intrauterine growth restriction (IUGR) increases risk of developing respiratory diseases such as asthma later in life. This study aims to characterize the effects of maternal hypoxia-induced IUGR on the lung proteome and...Intrauterine growth restriction (IUGR) increases risk of developing respiratory diseases such as asthma later in life. This study aims to characterize the effects of maternal hypoxia-induced IUGR on the lung proteome and identify key altered pathways relevant to asthma development in male and female adult offspring. Pregnant mice were housed in hypoxic conditions (10.5% oxygen) from gestational day 11 to 17.5 and returned to normoxic conditions until term (gestational day ∼21). Control animals were housed in normoxic conditions throughout pregnancy. Offspring were weighed at birth. At 8 weeks, mice were weighed and right lung tissues collected for analysis. Proteomics profiling was performed using liquid chromatography tandem mass spectrometry to identify and quantify individual proteins. Mass spectrometry identified 1417 proteins with significant differences (Benjamini-Hochberg corrected < 0.05) between IUGR and control mice. IUGR mice showed reduced mitochondrial respiration complex proteins which may cause increased oxidative stress, compared to Controls. Many ribosomal subunit proteins were decreased, which may impact protein translation. Store-operated calcium entry proteins were increased in IUGR mice, indicating calcium homeostasis dysregulation. IUGR mediated protein expression changes in the lungs may alter key cellular processes. In-depth characterization of these changes can further elucidate disease pathways between IUGR and asthma.
Understanding human evolution relies on biomolecular data from ancient skeletal tissues, yet warm climates often cause complete collagen loss, excluding many regions from the study. This research investigates the surviva...Understanding human evolution relies on biomolecular data from ancient skeletal tissues, yet warm climates often cause complete collagen loss, excluding many regions from the study. This research investigates the survival of non-collagenous proteins (NCPs) and low-molecular-weight proteins in archaeological bones deemed collagen-free by traditional metrics. Using a multi-method approach, we employed sandwich enzyme-linked immunosorbent assays for osteocalcin quantification, Qubit fluorometry for total protein, and liquid chromatography tandem mass spectrometry (LC-MS/MS) for characterization, complemented by Fourier transform infrared spectroscopy to assess the diagenetic state. Samples included collagen-depleted bones from Neolithic Lebanon and Palaeolithic France, with well-preserved controls from Neolithic Serbia and Paleolithic Russia. Results indicate that bone-associated NCPs, including osteocalcin, survive only if the insoluble collagen is preserved. Methodologically, tangential flow filtration outperformed centrifugal devices for protein recovery. EDTA demineralization with FASP was most effective for maximizing collagen recovery, while HCl demineralized protein precipitation best detected unique NCPs. Collagen was identified in the soluble supernatants of most collagen-depleted bones. Abundant collagen peptides were identified in a sample with a 0% collagen yield and a very low amide-to-phosphate ratio. These findings demonstrate that bones unsuitable for traditional dating can still retain measurable collagen, broadening the range of biomolecular analyses possible in warm and humid climates.
Ultimately, most tandem mass spectrometry (MS/MS) proteomics experiments aim to not just detect but also quantify the proteins in a given complex sample. Here, we describe an extension to the Crux MS/MS analysis toolkit...Ultimately, most tandem mass spectrometry (MS/MS) proteomics experiments aim to not just detect but also quantify the proteins in a given complex sample. Here, we describe an extension to the Crux MS/MS analysis toolkit to enable label-free quantification of peptides. We demonstrate that Crux's new quantification command, which is modeled after the algorithms implemented in the widely used FlashLFQ software, is both efficient and accurate. In particular, we achieve a 1.9-fold speedup while reducing the memory usage by 26%. The new crux-lfq command is available in Crux v5.0.
Shellfish allergy is a major global health concern, with prawns representing the most common trigger. Black tiger prawn (, BTP) and white leg prawn (, WLP) dominate global consumption. Here, label-free shotgun proteomics...Shellfish allergy is a major global health concern, with prawns representing the most common trigger. Black tiger prawn (, BTP) and white leg prawn (, WLP) dominate global consumption. Here, label-free shotgun proteomics combined with in-silico allergenicity prediction was applied to identify and compare the allergen profiles of BTP and WLP. Raw prawn extracts were analyzed by LC-MS/MS, and allergens were identified and predicted using AllerCatPro. The relative abundance of allergens was assessed using iBAQ%, and the differential abundance was evaluated using LFQ intensity. Although allergens accounted for only ∼4% of identified proteins, they represented 34-38% of total protein abundance, highlighting their immunological relevance. Myosin light chain was the most abundant allergen, followed by arginine kinase, sarcoplasmic calcium-binding protein, and tropomyosin in both species. Four low-abundance proteins were identified as novel allergen candidates. Notable differences in allergen profiles between the two species were observed at the level of allergen orthologs, isoforms, and variants, with nine uniquely identified in BTP and seven in WLP. Together, these findings reveal species-specific variations with implications for improved diagnostic strategies, therapeutic approaches, and allergen detection methods for shellfish allergy.
The human genome contains approximately 20,000 protein-coding genes. However, millions of diverse protein variants, called proteoforms, exist. Despite originating from the same gene, proteoforms often have distinct biolo...The human genome contains approximately 20,000 protein-coding genes. However, millions of diverse protein variants, called proteoforms, exist. Despite originating from the same gene, proteoforms often have distinct biological roles. In bottom-up proteomics, the aggregation of peptide measurements into protein-level quantities often obscures this information. Existing methods for differential proteoform discovery are limited by their handling of missing data, which can introduce a significant bias. To address this, we developed ProteoForge, which builds on an imputation-aware statistical model to identify and group covarying peptides into quantitatively differential proteoforms (dPFs). Benchmarking against existing methods demonstrated that ProteoForge provides high accuracy and stability in data sets with high rates of missing values, complex experimental designs, or varying signal strengths. Application of ProteoForge to proteomics data from lung cancer cells under hypoxia revealed extensive proteoform-level regulation hidden by a standard protein-level analysis.
We developed a micro-immobilized metal affinity chromatography (m-IMAC) protein purification method coupled with label-free quantification (LFQ) to enable mapping of protein-protein interactions (PPIs). We applied this m...We developed a micro-immobilized metal affinity chromatography (m-IMAC) protein purification method coupled with label-free quantification (LFQ) to enable mapping of protein-protein interactions (PPIs). We applied this method to reveal the interactome of c-Myc/Max, a master transcriptional regulator that controls the expression of thousands of genes and plays a key role in tumorigenesis. The m-IMAC columns were fabricated from 2-hydroxyethyl methacrylate phosphate (HEMAP) and the cross-linker pentaerythritol triacrylate via photoinitiated polymerization inside pipet tips. The phosphate groups of the column bed were activated by chelating Ni ions, enabling immobilization of recombinant bait proteins through complexation with their His tag, thereby allowing efficient enrichment of c-Myc/Max-interacting proteins from cell lysate. Using data-independent acquisition (DIA)-based LFQ, we identified 574 c-Myc/Max-interacting proteins, the majority of which have not been reported previously. GO analysis of the c-Myc/Max interactome revealed significant enrichment in RNA processing, chromatin organization and chromatin remodeling, protein-DNA assembly, and ribosome biogenesis. Our work provided the most comprehensive and up-to-date view of PPIs involved in c-Myc/Max-mediated transcriptional regulation. The straightforward workflow, ease of operation, and robust performance of the m-IMAC purification make it a versatile and efficient strategy for high-throughput interactome analysis.
It is increasingly recognized that the 'omic analysis of whole blood has applications for precision medicine and disease phenotyping. Despite this realization, whole blood is generally viewed as a challenging analytical...It is increasingly recognized that the 'omic analysis of whole blood has applications for precision medicine and disease phenotyping. Despite this realization, whole blood is generally viewed as a challenging analytical matrix in comparison to plasma or serum. Moreover, proteomic analyses of whole blood have almost exclusively focused on (non)targeted analyses of protein abundances and much less on post-translational modifications (PTMs). Here, we developed a streamlined workflow for processing 20 microliters of venous blood collected by volumetric absorptive microsampling that incorporates serial trypsinization and -glycopeptide and phosphopeptide enrichment and avoids laborious sample dry-down or cleanup steps. As many as 10,000 analytes (reported as protein groups, glycopeptidoforms, and phosphosites) can be quantified by liquid chromatography-tandem mass spectrometry in under 2 h of MS acquisition time. Using these methods, we explored the stability of "dried" and "wet" blood proteomes, as well as the effects of ex vivo inflammatory stimulus or phosphatase inhibition. Multiomics factor analysis enabled facile identification of analytes that contributed to interindividual variability of the blood proteomes, including -glycopeptides that distinguish immunoglobulin heavy constant alpha 2 allotypes. Collectively, our results help to establish feasibility and best practices for the integrated MS-based quantification of proteins and PTMs from dried blood.
Type 2 diabetes mellitus (T2DM) imposes a significant global mortality and economic burden, with increasing prevalence among younger populations driven by unhealthy lifestyles. Definitive asymptomatic diagnosis is theref...Type 2 diabetes mellitus (T2DM) imposes a significant global mortality and economic burden, with increasing prevalence among younger populations driven by unhealthy lifestyles. Definitive asymptomatic diagnosis is therefore crucial for effective intervention. In this study, urine metabolomic profiles were elucidated using high-performance anion exchange chromatography (HPAEC), and differences in organic acids, anions, amino acids, and glucose between T2DM patients and healthy controls (HC) were quantified. Statistically significant alterations were identified in seven urinary metabolite such as glycolic acid, lactate, taurine, glycine, glutamate, chloride, and glucose. A multivariate biomarker panel comprising glycolate, lactate, and glycine demonstrated exceptional diagnostic performance for T2DM (AUC = 0.990; sensitivity = 95.8%, specificity = 95.8%) at a threshold > -0.863. Four metabolic pathways were significantly upregulated in T2DM patients including taurine and hypotaurine metabolism (impact score: 0.4286), starch and sucrose metabolism (impact score: 0.4207), glycine-serine-threonine metabolism, and glyoxylate-dicarboxylate metabolism. The first two pathways exhibited the highest perturbation, indicating profound metabolic dysregulation in T2DM. These findings expand urine metabolomic knowledge and highlight quantifiable combined metabolite biomarkers for differentiating T2DM.
Top-down proteomics of human serum is hindered by extreme dynamic range and cumbersome prefractionation. Here, we establish a fully solution-based protein precipitation-solid-phase extraction (PP-SPE) workflow for deep,...Top-down proteomics of human serum is hindered by extreme dynamic range and cumbersome prefractionation. Here, we establish a fully solution-based protein precipitation-solid-phase extraction (PP-SPE) workflow for deep, low-molecular-weight-biased proteoform profiling. Using systematically optimized combinations of five precipitants and three sorbents, the workflow enabled identification of 4470 proteoforms from 480 proteins with excellent reproducibility ( > 0.96). Compared with the gel-based PEPPI method, PP-SPE provided substantially greater depth, including >10-fold more <5 kDa proteoforms, while shortening the overall sample preparation workflow and offering a format that is readily adaptable to plate-based platforms, thus providing a robust front end for high-throughput serum top-down analyses.
Silica nanoparticles (SiNPs) are considered as one of the excellent alternative negative electrode materials for optimizing the storage performance of lithium-ion batteries. Therefore, with the global transition to new e...Silica nanoparticles (SiNPs) are considered as one of the excellent alternative negative electrode materials for optimizing the storage performance of lithium-ion batteries. Therefore, with the global transition to new energy, their production may rapidly increase, but there is still a lack of relevant research on occupational exposure risks, especially respiratory toxicity mechanisms and biomarkers, associated with lithium-ion battery-related SiNPs. This study investigated the mechanism of toxic effects and possible biomarkers of SiNPs on human bronchial epithelial cells (BEAS-2B) using integrative transcriptomic, proteomic, and metabolomic approaches. SiNPs used in this study were selected as the most relevant type of negative electrode material for lithium-ion batteries, and their physical and chemical properties were characterized in detail. It was found that SiNPs induced significant concentration- and time-dependent cytotoxicity on BEAS-2B cells. SiNPs could alter the multiomics phenotype of cells after treatment with 50 μg/mL for 24 h. Multiomic joint analysis found that SiNPs may have induced cytotoxicity through toxic pathways, including oxidative stress, inflammation, and fibrosis, screening possible biomarkers such as PTX3, SESN2, STC2, IL-6, CLDN1, and COL14A1. This study revealed the possible mechanisms and biomarkers of respiratory toxicity of lithium-ion battery-related SiNPs and also suggested that integrative omic analyses could be a useful approach for evaluating the toxicity of novel nanoparticles.
The response of lung cancer to chemoradiotherapy (CRT) is orchestrated by the dynamic interplay between immune microenvironment remodeling and metabolic reprogramming. However, robust biomarkers for predicting patient pr...The response of lung cancer to chemoradiotherapy (CRT) is orchestrated by the dynamic interplay between immune microenvironment remodeling and metabolic reprogramming. However, robust biomarkers for predicting patient prognosis remain elusive. In this study, we performed proteomics profiling of 22 pairs of lung cancer specimens and compared CRT-sensitive versus CRT-resistant subtypes. Functional analysis revealed distinct pathway enrichment between the two groups: the CRT-sensitive subtype was predominantly associated with fatty acid oxidation and energy metabolism, whereas the CRT-resistant subtype exhibited elevated immune activation, inflammatory responses, and stress-related signaling. Based on these findings, we developed a LASSO regression-based predictive model that pinpointed a protein signature encompassing IKBKB interacting protein (IKBIP) and citron rho-interacting serine/threonine kinase (CIT) as optimal predictors of CRT efficacy. Subsequent survival analysis further confirmed the prognostic relevance of these proteins. Collectively, our findings emphasize the critical role of the metabolic-immune axis in modulating CRT sensitivity and provide mechanistic insights into the molecular underpinnings of treatment response, thereby offering a clinically translatable tool for guiding precision therapeutic strategies in lung cancer.
A comprehensive global proteomic profiling of rat and hamster liver S9 fractions was conducted under basal conditions and following induction with Aroclor 1254 (Aroclor) or phenobarbital/β-naphthoflavone (PBNF). More tha...A comprehensive global proteomic profiling of rat and hamster liver S9 fractions was conducted under basal conditions and following induction with Aroclor 1254 (Aroclor) or phenobarbital/β-naphthoflavone (PBNF). More than 8500 proteins were quantified across conditions. Induction remodeled xenobiotic pathways with conserved increases in CYP1A and CYP2B, larger CYP3A responses in rats under Aroclor, and prominent CYP2F/CYP2G changes in hamsters, alongside a downshift in mitochondrial electron transport and activation of proteostasis networks (heat-shock chaperones). Complementary targeted analysis with stable isotope-labeled standards enabled absolute quantification of 15 cytochrome P450 enzymes, confirming significant inducer-dependent increases across species. This study integrates global proteomic analysis with absolute quantification of CYPs predominantly involved in drug and nitrosamine metabolism for representative enzymes spanning the CYP1A, CYP2A, CYP2C, CYP2D, CYP2E, and CYP3A families in induced and uninduced rat and hamster S9 fractions. The data set and assays serve as a practical reference for DMPK, toxicology, and nitrosamine activation studies and support selection of inducers to tune CYP-mediated oxidative capacity.
The glycosylation of monoclonal immunoglobulins (M-proteins) is implicated in the pathogenesis of multiple myeloma (MM), but a comprehensive, site-specific glycoproteomic characterization has been lacking. Here, we estab...The glycosylation of monoclonal immunoglobulins (M-proteins) is implicated in the pathogenesis of multiple myeloma (MM), but a comprehensive, site-specific glycoproteomic characterization has been lacking. Here, we established an integrated workflow that couples serum protein electrophoresis with ZenoTOF mass spectrometry for the in-depth quantitative profiling of intact -glycopeptides from purified serum M-proteins. This method was applied to a cohort including healthy controls (HCs) ( = 26), patients with IgG-MGUS (monoclonal gammopathy of undetermined significance) ( = 23), and IgG-MM patients ( = 32), with an independent validation set ( = 28). Longitudinal analysis was performed on samples (IgG-MM) from newly diagnosed MM (NDMM, = 14), very good partial response (VGPR, = 7), and complete response (CR, = 5) patients. We identified that sialylated glycopeptides were significantly upregulated in the MM. Notably, the site-specific glycoform IgG1H4N4F1S1 demonstrated superior diagnostic performance for distinguishing MM from HCs (AUC = 0.902). Crucially, longitudinal tracking revealed dynamic changes in IgG1H4N4F1S1 abundance, which decreased significantly as patients achieved deeper clinical responses (NDMM to CR), and its levels correlated with key clinical parameters. Our study provides a robust glycoproteomic strategy and unveils specific, dynamic glycosylation signatures on M-proteins that offer novel insights into MM biology and serve as potential biomarkers for monitoring the therapeutic efficacy.
Pancreatic ductal adenocarcinoma (PDAC) carries a poor prognosis largely due to lack of efficient diagnostic means. We applied mass spectrometry-based high-coverage plasma proteome analysis accompanying with machine lear...Pancreatic ductal adenocarcinoma (PDAC) carries a poor prognosis largely due to lack of efficient diagnostic means. We applied mass spectrometry-based high-coverage plasma proteome analysis accompanying with machine learning to develop a 5-protein diagnostic model: SNCA, GCLC, LBP, ALAD, and SORD. For differentiating PDAC from healthy controls (HCs), this model reached an area under the curve (AUC) of 0.973 with 100% sensitivity and 85% specificity in the discovery cohort, with nested cross-validation confirming robust performance (AUC = 0.958). Further validation centered on SNCA achieved an AUC of 0.835 in an independent validation cohort. SNCA also showed good diagnostic performance in PDAC patients with low CA19-9 level (AUC = 0.868), underscoring its potential value for this subgroup. Overall, these findings indicate SNCA as a promising candidate plasma diagnostic marker for PDAC.
is an opportunistic pathogen associated with severe cystic fibrosis (CF) lung infections, where macrophages serve as both a crucial reservoir and a key mediator of intense inflammation. Currently, there is a paucity of i...is an opportunistic pathogen associated with severe cystic fibrosis (CF) lung infections, where macrophages serve as both a crucial reservoir and a key mediator of intense inflammation. Currently, there is a paucity of insight into how infection impacts both the host and the proteomes. A key limitation for understanding the proteomic changes during intracellular replication of is its low infectivity, which results in in vitro infection models dominated by uninfected cells. Using antibody-mediated opsonization, we show that improving the efficiency and uniformity of internalization enhances dual proteomic analysis and changes in both the host and internalized , which can be assessed within a single experimental framework. Opsonization enhances the detection of protein changes, including proinflammatory signaling and macrophage activation markers. Using this dual proteomic approach, we assessed the impact of the type 6 secretion system (T6SS) and the T6SS effector TecA at 3 and 24 h postinfection, demonstrating that the presence/activity of the T6SS or TecA does not significantly alter the proinflammatory response of THP-1 cells. Thus, this work demonstrates a simple means for enhancing proteomic analysis of infections, enabling dual proteomic studies.
Macrophages are central players of innate immunity with diverse functions and involvement in numerous diseases, making it essential to understand their metabolic regulation. Here, we provide a comprehensive analysis of l...Macrophages are central players of innate immunity with diverse functions and involvement in numerous diseases, making it essential to understand their metabolic regulation. Here, we provide a comprehensive analysis of lipid metabolic dynamics during human monocyte-to-macrophage differentiation. Primary blood monocytes were differentiated for 5 days with either M-CSF or GM-CSF. Lipidomic profiling using the differential mobility spectrometry-shotgun lipidomics assistant (DMS-SLA) platform reliably quantified ∼400 lipids across 16 classes, while spectral flow cytometry was used to assess metabolic enzyme expression. Differentiation was marked by remodeling toward membrane lipids, accompanied by shorter acyl chains and reduced unsaturation in triglyceride (TG) and phosphatidylcholine (PC) species. PC species incorporated a more diverse range of pro- and anti-inflammatory precursors, whereas TG species mainly incorporated fatty acid FA 22:6. Metabolic enzyme expression showed dynamic, marker-specific changes over time, with G6PD and SDHA upregulation indicating enhanced pentose phosphate and oxidative phosphorylation pathways. M-CSF MDMs exhibited higher GLUT1 and CD36 expression and greater FA 22:6 incorporation within TGs. Together, these findings reveal extensive lipidome remodeling that underlies macrophage differentiation and distinct functional states.
Activating mutations are among the most frequent oncogenic drivers in breast cancer, with E545K and H1047R mutants representing the most prevalent hotspot variants. Despite the development of potent PI3K inhibitors, cli...Activating mutations are among the most frequent oncogenic drivers in breast cancer, with E545K and H1047R mutants representing the most prevalent hotspot variants. Despite the development of potent PI3K inhibitors, clinical efficacy remains limited in some cases. This underscores the need to understand how specific oncogenic mutations reshape signaling networks and therapeutic responses. Here, we compared the E545K and H1047R mutant breast epithelial cells to delineate mutation-specific signaling programs, growth phenotypes, and responses to PI3Kα inhibition in the presence and absence of insulin, using integrated growth assays and quantitative proteomic and phosphoproteomic profiling. These analyses uncovered mutation-specific signaling architectures and inhibitor sensitivities. Both mutants exhibited basal MAPK activation, but showed divergent MAPK phosphorylation dynamics in distinct mutations, suggesting a pivotal role for MAPK signaling. Upon PI3Kα inhibition with alpelisib, insulin engaged bypass signaling that partially counteracted downstream suppression. MEK inhibition alone suppressed the growth of mutant cells, and dual targeting of PI3K and MAPK signaling produced greater growth suppression than either single agent alone under insulin-stimulated conditions. Collectively, these findings reveal mutation-specific adaptive signaling and support combined PI3Kα and MAPK pathway inhibition as a strategy to improve therapeutic efficacy in mutant breast cancer.
Liquid chromatography-mass spectrometry is a potent and robust tool for studying metabolism. However, conventional workflows can suffer from poor peak shapes, limited pressure tolerance, coelution of polar metabolites, a...Liquid chromatography-mass spectrometry is a potent and robust tool for studying metabolism. However, conventional workflows can suffer from poor peak shapes, limited pressure tolerance, coelution of polar metabolites, and unstable retention times. Here, we describe the development of a more stable HILIC method for LC-MS metabolomics of human plasma and cell extracts, optimizing a zwitterionic HILIC (Z-HILIC) column for improved untargeted performance. We found that using high-pH ammonium bicarbonate with 90% acetonitrile in mobile phase B (ABC B) can greatly improve peak shapes of select metabolites when compared to 100% acetonitrile (ACN B), but at the cost of poor retention time stability. We therefore focused on optimizing chromatography for the ACN B method and observed that cooling the column to 5 °C substantially enhanced peak shape for the BEH-bound Z-HILIC and amide columns but had little effect on the polymeric ZIC-pHILIC column. The low-temperature method with the Z-HILIC column (LT-ZHILIC) enables high-resolution separation of 471 metabolite library standards and from both cellular extracts and human plasma and demonstrates robust stability over 100 consecutive injections and multiple days. Application of the untargeted LT-ZHILIC method to characterize the metabolic consequences of glutamine and pyruvate deficiency in human cells revealed a striking change in nucleotide phosphates─a perturbation that was not observed in the ZIC-pHILIC analysis of the same samples likely due to inadequate elution profiles. In sum, the LT-ZHILIC workflow offers a robust platform to advance untargeted metabolomics by improving metabolite coverage, resolution, and retention time stability, making it a promising technique for providing novel insights into cellular metabolic rewiring and the human plasma metabolome.