Biology subjects

Lewis, I. A.

Publications and source records attributed to Lewis, I. A..

14 recordsLinked to original sources

bioRxiv2026

LAMPrEY: a Python-based automated quality control tool for large-scale proteomics datasets

Over the past years, proteomics has moved increasingly towards the analysis of large cohorts of biological specimens. This has been made possible by significant improvements in mass spectrometry technology, chromatographic separation methods, and improved data acquisition strategies. These technological advances now routinely enable experiments that yield vast datasets that substantially outstrip the capacity of existing proteomics data analysis approaches. Processing such large datasets requires purpose-built, quality control tools designed to organize and analyze the data while recording all processing parameters for reproducibility. To address this need, we developed an open-source, Python-based software platform, Large-scale Automated Multi-level Proteomics Evaluation by Python (LAMPrEY), a comprehensive quality-control pipeline for quantitative proteomics analyses of large cohorts of samples. LAMPrEY features GUI-based file submission, automated processing with MaxQuant and RawTools, an interactive analytics dashboard, and an application programming interface (API) for programmatic usage that collectively enable rapid, reproducible analysis and interpretation of proteomics data. We demonstrate the longitudinal monitoring and analytical capabilities of LAMPrEY using TMT11 quantitative proteomics data generated from 910 Enterococcus faecium isolates collected from bloodstream infection patients. LAMPrEY is an open-source software that can be accessed at www.lewisresearchgroup.org/software.

bioinformatics↗

bioRxiv2026

Microbiome-derived hydroxyphenyl propanoates enhance antitumour immunity by potentiating gasdermin D activity in tumour-associated myeloid cells

The microbiome plays a critical role in immune health and response to immune-stimulating treatments, including cancer immunotherapy. However, the molecular mechanisms by which commensal microbes influence cancer immunology remain poorly understood. Here, we report a class of microbiome-derived metabolites called hydroxyphenyl propanoates (HPP) that enhance tumour immune surveillance and response to immune checkpoint blockade (ICB) therapy in mice. HPPs function as potentiators of innate immune signalling in tumour-associated myeloid cells by promoting cleavage of the pore-forming protein gasdermin D (GSDMD), a critical effector of inflammasome function. This enhances the secretion of proinflammatory cytokines, such as IL-1 family members, while simultaneously protecting against pyroptosis. Secreted IL-1 family cytokines in turn elicit autocrine and paracrine inflammatory signaling in tumour-infiltrating leukocytes. HPP supplementation increases anticancer T cell function, improves disease control and extends overall survival (OS) in tumour-bearing mice harboring complex microbiomes or those treated with broad-spectrum antibiotics. In humans, GSDMD activation is associated with a favourable response to PD-1 blockade therapy in patients with advanced stage melanoma. Our study uncovers a molecular mechanism of regulation over host antitumour immunity that is modifiable and can be harnessed for improved cancer immunotherapy in a broad spectrum of patients.

cancer biology↗

bioRxiv2025

Regulation of airway fumarate by host and pathogen promotes S. aureus pneumonia

Staphylococcus aureus is a leading cause of healthcare-associated pneumonia, contributing significantly to morbidity and mortality worldwide. As a ubiquitous colonizer of the upper respiratory tract, S. aureus must undergo substantial metabolic adaptation to achieve persistent infection in the distinctive microenvironment of the lung. We observed that fumC, which encodes the enzyme that converts fumarate to malate, is highly conserved with low mutation rates in S. aureus isolates from chronic lung infections. Fumarate, a pro-inflammatory metabolite produced by macrophages during infection, is regulated by the host fumarate hydratase (FH) to limit inflammation. Here, we demonstrate that fumarate, which accumulates in the chronically infected lung, is detrimental to S. aureus, blocking primary metabolic pathways such as glycolysis and oxidative phosphorylation (OXPHOS). This creates a metabolic bottleneck that drives staphylococcal FH (FumC) activity for airway adaptation. FumC not only degrades fumarate but also directs its utilization into critical pathways including the tricarboxylic acid (TCA) cycle, gluconeogenesis and hexosamine synthesis to maintain metabolic fitness and form a protective biofilm. Itaconate, another abundant immunometabolite in the infected airway enhances FumC activity, in synergy with fumarate. In a mouse model of pneumonia, a {Delta}fumC mutant displays significant attenuation compared to its parent and complemented strains, particularly in fumarate- and itaconate-replete conditions. Our findings underscore the pivotal role of immunometabolites in promoting S. aureus pulmonary adaptation.

microbiology↗

bioRxiv2024

DigestR an open-source software tool for visualizing LC-MS proteomics data resulting from natural protein catabolism

Protein catabolism is an essential biological function supported by every living organism. Although liquid chromatography mass spectrometry proteomics has advanced considerably over the past decade, protein catabolism in natural systems is still difficult to study. One reason for this is the lack of software tools designed specifically for decoding the complex mixtures of peptides that result from in vivo protein digestion. To address this, we developed DigestR, an open-source software tool designed specifically for the analysis of LC-MS proteomics data. DigestR allows users to visualize naturally occurring peptides and align them to a reference proteome at display them at either a proteome-wide and protein-specific level. These visualization tools allow users to track the patters of peptides occurring in natural systems and map naturally-occurring proteolytic cut sites. To demonstrate these functions, we used DigestR to analyze a mixture of peptides resulting from the in vitro digestion of human hemoglobin and bovine albumin with a cocktail of well characterized proteases. As expected, DigestR correctly identified both the proteins involved and the proteolytic cut sites produced by our protease cocktail. We then used DigestR to analyze the complex semi-ordered hemoglobin digestion pathway used by the malaria parasite Plasmodium falciparum. We show that DigestR successfully identified the proteolytic cut sites linked to the Plasmepsins, a protease known to be involved in hemoglobin digestion by the parasite. Collectively, these findings show that DigestR can be used to help visualize and interpret the complex mixtures of peptides occurring through in vivo protein catabolism. DigestR can be downloaded from www.lewisresearchgroup.org/software.

bioinformatics↗

bioRxiv2024

LC-MS system for automatically collecting time-resolved metabolomics data of cultured cells

Temporal metabolic dynamics are a critical, but difficult to study aspect of metabolism. To address this, we developed a liquid chromatography-mass spectrometry (LC-MS) system, temporal uptake and nutritional analysis (TUNA), to automatically collect time-resolved metabolomics data of cultured cells. TUNA enables sub-minute sequential sampling, has broad metabolite coverage, supports robust metabolite identification, can monitor over 72 conditions in parallel, and can be implemented in most LC-MS laboratories. We used TUNA to monitor temporal dynamics of uropathogens (Escherichia coli and Proteus mirabilis) and identify novel metabolic phenotypes that cannot be captured from a single time point.

microbiology↗

bioRxiv2024

Metabolomics survey of uropathogenic bacteria in human urine

Urinary tract infections (UTIs) are one of the most prevalent infections in North America and are caused by a diverse range of bacterial species. Although uropathogenesis has been studied extensively in the context of macromolecular interactions, the degree to which metabolism may contribute to infection is unclear. Currently, most of what is known about the metabolic capacity of uropathogens has been derived from genomics, genetic knockout studies or transcriptomic analyses. However, there are currently very little empirical data on the metabolic activity of uropathogens when grown in urine. To address this gap, we conducted a systematic survey of the metabolic activities of eight of the most common uropathogenic bacterial species that collectively represent 99% of uncomplicated UTIs. Liquid chromatography-mass spectrometry (LC-MS) analyses of human urine cultures revealed that uropathogens have four distinct metabolic clades. We generalized these clades as serine consumers (Escherichia coli, Klebsiella pneumoniae and Proteus mirabilis), glutamine consumers (Pseudomonas aeruginosa), amino acid abstainers (Enterococcus faecalis and Streptococcus agalactiae), and amino acid minimalists (Staphylococcus aureus and Staphylococcus saprophyticus). These metabolic classifications can be further subdivided on a species-to-species level. This survey provides a framework to understanding the metabolic activity of the diverse range of uropathogens and how these species use divergent metabolic strategies to occupy the same niche.

microbiology↗

bioRxiv2023

SCALiR: a web application for automating absolute quantification of mass spectrometry-based metabolomics data

Metabolomics is an important approach for studying complex biological systems. Quantitative liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is becoming a mainstream strategy but presents several technical challenges that limit its widespread use. Computing metabolite concentrations using standard curves generated from standard mixtures of known concentrations is a labor-intensive process which is often performed manually. Currently, there are few options for open-source software tools that can automatically calculate metabolite concentrations. Herein, we introduce SCALiR (Standard Curve Application for determining Linear Ranges), a new web-based software tool specifically built for this task, which allows users to automatically transform LC-MS signal data into absolute quantitative data (https://www.lewisresearchgroup.org/software). The algorithm used in SCALiR automatically finds the equation of the line of best fit for each standard curve and uses this equation to calculate compound concentrations from their LC-MS signal. Using a standard mix containing 77 metabolites, we found excellent correlation between the concentrations calculated by SCALiR and the expected concentrations of each compound (R2 = 0.99) and that SCALiR reproducibly calculated concentrations of mid-range standards across ten analytical batches (average coefficient of variation 0.091). SCALiR offers users several advantages, including that it (1) is open-source and vendor agnostic; (2) requires only 10 seconds of analysis time to compute concentrations of >75 compounds; (3) facilitates automation of quantitative workflows; and (4) performs deterministic evaluation of compound quantification limits. SCALiR provides the metabolomics community with a simple and rapid tool that enables rigorous and reproducible quantitative metabolomics studies.

biochemistry↗

bioRxiv2023

Metabolic Interactive Nodular Network for Omics (MINNO): Refining and investigating metabolic networks based on empirical metabolomics data

Metabolomics is a powerful tool for uncovering biochemical diversity in a wide range of organisms, and metabolic network modeling is commonly used to frame results in the context of a broader homeostatic system. However, network modeling of poorly characterized, non-model organisms remains challenging due to gene homology mismatches. To address this challenge, we developed Metabolic Interactive Nodular Network for Omics (MINNO), a web-based mapping tool that takes in empirical metabolomics data to refine metabolic networks for both model and unusual organisms. MINNO allows users to create and modify interactive metabolic pathway visualizations for thousands of organisms, in both individual and multi-species contexts. Herein, we demonstrate an important application of MINNO in elucidating the metabolic networks of understudied species, such as those of the Borrelia genus, which cause Lyme disease and relapsing fever. Using a hybrid genomics-metabolomics modeling approach, we constructed species-specific metabolic networks for three Borrelia species. Using these empirically refined networks, we were able to metabolically differentiate these genetically similar species via their nucleotide and nicotinate metabolic pathways that cannot be predicted from genomic networks. These examples illustrate the use of metabolomics for the empirical refining of genetically constructed networks and show how MINNO can be used to study non-model organisms. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/548964v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@8cdee6org.highwire.dtl.DTLVardef@7de3ddorg.highwire.dtl.DTLVardef@fac57forg.highwire.dtl.DTLVardef@1bc2efe_HPS_FORMAT_FIGEXP M_FIG MINNO tool facilitates refining of metabolic networks, multi omics integration and investigation of cross-species interactions. C_FIG

bioinformatics↗

bioRxiv2022

Method for quantifying the metabolic boundary fluxes of cell cultures in large cohorts by high resolution hydrophilic liquid chromatography mass spectrometry

Metabolomics is a mainstream approach for investigating the metabolic underpinnings of complex biological phenomena and is increasingly being applied to large scale studies involving hundreds or thousands of samples. Although metabolomics methods are robust in smaller scale studies, they can be challenging to apply in larger cohorts due to the inherent variability of liquid chromatography mass spectrometry (LC-MS). Much of this difficulty results from the time-dependent changes in the LC-MS system, which affects both the qualitative and quantitative performance of the instrument. Herein, we introduce an analytical strategy for addressing this problem in large-scale microbial studies. Our approach quantifies microbial boundary fluxes using two zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) columns that are plumbed to enable offline column equilibration. Using this strategy, we show that over 360 common metabolites can be resolved in 4.5 minutes per sample and that metabolites can be quantified with a median coefficient of variation of 0.127 across 1,100 technical replicates. We illustrate the utility of this strategy via an analysis of 960 strains of Staphylococcus aureus isolated from blood stream infections. These data capture the diversity of metabolic phenotypes observed in clinical isolates and provide an example of how large-scale investigations can leverage our novel analytical strategy.

biochemistry↗

bioRxiv2020

Altered glutamine metabolism of cultured fibroblasts predicts severity of cardiac dysfunction in the dilated cardiomyopathy with ataxia syndrome (DCMA), a mitochondrial cardiomyopathy

Dilated cardiomyopathy with ataxia (DCMA) syndrome is a rare mitochondrial disorder caused by mutations in the poorly understood DNAJC19 gene. The clinical presentation of DCMA is very diverse with symptoms ranging from mild cardiac dysfunction to intractable heart failure leading to death in early childhood. Although several lines of evidence indicate that DCMA symptoms are linked to mitochondrial function, the molecular underpinnings of this disease are unclear and there is no way to predict which patients are at risk for developing life-threatening symptoms. To address this we developed a metabolic flux assay for assessing the metabolic function of mitochondria in dermal fibroblasts derived from DCMA patients. Using this approach we discovered that fibroblasts from patients with DCMA showed elevated glutamine uptake, increased glutamate and ammonium secretion, and elevated lactate production when compared to controls. Moreover, the magnitude of these metabolic perturbations was closely correlated with patient cardiac dysfunction. This clinical/metabolic correlation was confirmed in a second blinded cohort of DCMA fibroblasts. Moreover, our metabolic flux diagnostic strategy correctly differentiated severe from mild DCMA cases with only one incorrect patient classification (positive predictive value 1.0 and negative predictive value 0.83). These findings suggest that glutamine catabolism is abnormal in DCMA and may serve as an early biomarker for predicting clinical progression. One Sentence SummaryAlterations in glutamine and lactate metabolism in patient-derived dermal fibroblasts are associated with the severity of cardiomyopathy in DCMA.

cell biology↗

bioRxiv2020

PelX is a UDP-N-acetylglucosamine C4-epimerase involved in Pel polysaccharide-dependent biofilm formation

Pel is an N-acetylgalactosamine rich polysaccharide that contributes to the structure and function of Pseudomonas aeruginosa biofilms. The pelABCDEFG operon is highly conserved among diverse bacterial species, and thus Pel may be a widespread biofilm determinant. Previous annotation of pel gene clusters led us to identify an additional gene, pelX, that is found adjacent to pelABCDEFG in over 100 different bacterial species. The pelX gene is predicted to encode a member of the short-chain dehydrogenase/reductase (SDR) superfamily of enzymes, but its potential role in Pel-dependent biofilm formation is unknown. Herein, we have used Pseudomonas protegens Pf-5 as a model to understand PelX function as P. aeruginosa lacks a pelX homologue in its pel gene cluster. We find that P. protegens forms Pel-dependent biofilms, however, despite expression of pelX under these conditions, biofilm formation was unaffected in a {Delta}pelX strain. This observation led to our identification of the pelX paralogue, PFL_5533, which we designate pgnE, that appears to be functionally redundant to pelX. In line with this, a {Delta}pelX {Delta}pgnE double mutant was substantially impaired in its ability to form Pel-dependent biofilms. To understand the molecular basis for this observation, we determined the structure of PelX to 2.1[A] resolution. The structure revealed that PelX resembles UDP-N-acetylglucosamine (UDP-GlcNAc) C4-epimerases and, using 1H NMR analysis, we show that PelX catalyzes the epimerization between UDP-GlcNAc and UDP-GalNAc. Taken together, our results demonstrate that Pel-dependent biofilm formation requires a UDP-GlcNAc C4-epimerase that generates the UDP-GalNAc precursors required by the Pel synthase machinery for polymer production.

microbiology↗

bioRxiv2020

Thermogenic hydrocarbons sustain diverse subseafloor microbial communities in deep sea cold seep sediments

At marine cold seeps, gaseous and liquid hydrocarbons migrate from deep subsurface origins to the sediment-water interface. Cold seep sediments are known to host taxonomically diverse microorganisms, but little is known about their metabolic potential and depth distribution in relation to hydrocarbon and electron acceptor availability. In this work, we combined geochemical, metagenomic and metabolomic measurements in distinct sediment redox regimes to profile microbial activities within the uppermost 350 cm of a newly discovered cold seep in the NW Atlantic deep sea (2.3 km water depth). Depth-resolved metagenomic profiling revealed compositional and functional differentiation between near-surface sediments (dominated by Proteobacteria) and deeper subsurface layers (dominated by Atribacteria, Chloroflexi, Euryarchaeota and Lokiarchaeota). Metabolic capabilities of community members were inferred from 376 metagenome-assembled genomes spanning 46 phyla (including five novel candidate phyla). In deeper sulfate-reducing and methanogenic sediments, various community members are capable of anaerobically oxidizing short-chain alkanes (alkyl-CoM reductase pathway), longer-chain alkanes (fumarate addition pathway), and aromatic hydrocarbons (fumarate addition and subsequent benzoyl-CoA pathways). Geochemical profiling demonstrated that hydrocarbon substrates are abundant in this location, thermogenic in origin, and subject to biodegradation. The detection of alkyl-/arylalkylsuccinate metabolites, together with carbon isotopic signatures of ethane, propane and carbon dioxide, support that microorganisms are actively degrading hydrocarbons in these sediments. Hydrocarbon oxidation pathways operate alongside other deep seabed metabolisms such as sulfide oxidation, hydrogen oxidation, carbon fixation, fermentation and reductive dehalogenation. Upward migrated thermogenic hydrocarbons thus sustain diverse microbial communities with activities that affect subseafloor biogeochemical processes across the redox spectrum in deep sea cold seeps.

microbiology↗

bioRxiv2019

Vancomycin Relieves Mycophenolate Mofetil-Induced Gastrointestinal Toxicity by Eliminating Gut Bacterial β-Glucuronidase Activity

Mycophenolate mofetil (MMF) is commonly prescribed after transplantation and has proven advantages over other immunosuppressive drugs but gastrointestinal (GI) side effects frequently limit its use. The pathways involved in the metabolism of the prodrug MMF and the bioactive derivative mycophenolic acid (MPA) are well characterized but the mechanism responsible for toxicity is unknown. Here we extend our previous observation that an intact gut microbiome is required for MMF-induced toxicity and demonstrate that gut bacterial metabolism is responsible for the GI inflammation and weight loss associated with MMF exposure. In mice consuming MMF, the introduction of vancomycin alone was sufficient to prevent or reverse MMF-induced weight loss and colonic inflammation. MMF induced the expansion of bacteria expressing {beta}-glucuronidase (GUS) in the cecum and proximal colon. GUS activity, which is responsible for the catabolism of glucuronidated MPA (MPAG) to free MPA, was increased in the presence of MMF and eliminated by vancomycin. Vancomycin eliminated multiple Bacteroides spp. that flourished in the presence of MMF and prevented the breakdown of MPAG without negatively affecting serum MPA levels. Human data suggests that increased stool GUS activity can be associated with MMF-related toxicity. Our work provides a mechanism for the GI toxicity associated with MMF and a future direction for the development of therapeutics.

microbiology↗

bioRxiv2018

Potential for microbial anaerobic hydrocarbon degradation in naturally occurring petroleum-associated deep-sea sediments

The lack of microbial genomes and isolates from the deep seabed means that very little is known about the ecology of this vast habitat. Here, we investigated energy and carbon acquisition strategies of microbial communities from three deep seabed petroleum seeps (3 km water depth) in the Eastern Gulf of Mexico. Shotgun metagenomic analysis revealed that each sediment harbored diverse communities of chemoheterotrophs and chemolithotrophs. We recovered 82 metagenome-assembled genomes affiliated with 21 different archaeal and bacterial phyla. Multiple genomes encoded enzymes for anaerobic oxidation of aliphatic and aromatic compounds, including those of candidate phyla Aerophobetes, Aminicenantes, TA06 and Bathyarchaeota. Microbial interactions are predicted to be driven by acetate and molecular hydrogen. These findings are supported by sediment geochemistry, metabolomics, and thermodynamic modelling. Overall, we infer that deep-sea sediments experiencing thermogenic hydrocarbon inputs harbor phylogenetically and functionally diverse communities potentially sustained through anaerobic hydrocarbon, acetate and hydrogen metabolism.

microbiology↗