Biology subjects

Mohanty, I.

Publications and source records attributed to Mohanty, I..

At least 19 recordsLinked to original sources

bioRxiv2026

The Evolving Bileome: A Pan-Repository Landscape of Expanded Bile Acid and Related Steroidal Signatures

Bile acids and related steroidal metabolites are among the most studied biomolecules, yet recent work has revealed far greater structural diversity than previously recognized, much of it shaped by the microbiome. We previously introduced a repository-scale bile acid MS/MS library built from queries targeting C24 bile acid fragmentation, limited to Orbitrap Q Exactive datasets within GNPS/MassIVE. Here we announce a major expansion of this library: a bile acid and steroidal MS/MS spectral library assembled across three major metabolomics repositories, now capturing C23, C24 (including alkamine), C26 (C-C bonded aceto derivatives), and C27 bile acids, as well as C28 bile alcohols. The expanded libraries comprise 640,141 unique MS/MS spectra, of which 120,293 (18.8%) match 2,529 reference spectra, leaving most of this steroidal chemical space structurally unassigned. Linked to harmonized pan-repository metadata, the library provides a starting point for classifying MS/MS spectra as likely bile acids or related steroids, with two example analyses illustrated here. This resource allows researchers to flag candidate bile acid and steroidal signatures in their own data for further characterization.

bioinformatics↗

bioRxiv2026

Serum metabolomics reveals signatures associated with physical resilience trajectories from middle to older age

Lifecourse physical resilience is defined by the ability to maintain abilities across multiple domains of physical performance. While the importance of physical resilience in functional independence and mobility disability is clear, studies investigating metabolomic signatures of physical resilience are lacking. Here, we performed untargeted metabolomics on serum samples from a community-based cohort of 237 individuals followed over 28 years, and applied spectral data mining tools to map identified metabolites to health phenotypes from public repositories. We identified metabolites across multiple chemical classes, including acylcarnitines, glutamine conjugates, and phosphocholines, that were differentially associated with physical resilience status. Notably, medium-chain acylcarnitines negatively associated with physical resilience were more frequently observed in disease phenotypes than in healthy individuals. Kynurenine, a tryptophan metabolite linked to age-related functional decline, increased more steeply with age in individuals with low physical resilience. We also found that metabolites of the antihypertensive drug verapamil were associated with physical resilience in a metabolism-dependent manner, differing between oxidative and glucuronidated forms. Together, these metabolic signatures offer a resource for identifying biochemical pathways and biomarkers relevant to physical resilience for healthy aging.

bioinformatics↗

bioRxiv2026

Alkamines reveal a hidden layer of steroid and drug metabolism

Biomedical research overlooks most genes in favor of a well-studied minority, yet whether analogous blind spots exist in metabolomics remains unknown. We show that reductive amination, forming secondary amines from aldehydes or ketones and amines, generates a previously hidden class of metabolites we term alkamines. Multiplexed synthesis of 8,475 alkamines combined with MS/MS searches across 1.7 billion spectra identified 1,626 candidates across multiple species and organs. Of these, 56 were confirmed in biological samples, including 27 steroid- and 12 drug-derived alkamines matching prescription patterns. Notably, 77% of synthesized alkamines are absent from PubChem. This combinatorial logic likely explains why alkamines have evaded detection and suggests drug metabolism frameworks substantially underestimate drug-derived metabolite diversity. Reductive amination is an overlooked route modifying steroids, bile acids, and xenobiotics.

biochemistry↗

bioRxiv2026

Serum metabolic signatures of cognitive resilience in a longitudinal aging cohort

Aging is typically accompanied by a progressive decline in cognitive function, yet some individuals maintain exceptional cognitive performance, even across the transition from middle to older age, defining exceptional cognitive resilience. While existing measures of resilience primarily rely on clinical assessments, its molecular determinants and early predictive markers remain poorly understood. Here, we performed untargeted LC-MS/MS profiling of longitudinal serum samples to identify metabolic signatures associated with cognitive resilience, which was established based on cognitive tests conducted over 28 years in a cohort of 237 participants. We observed associations across multiple chemical classes, including carnitines, glutamine conjugates, phosphocholines, as well as diet-and drug-derived metabolites. Chemical class-specific analyses revealed distinct metabolic profiles, including predominantly negative associations of medium-chain acylcarnitines with cognitive resilience, increased accumulation of glucuronide conjugates in individuals with low cognitive resilience, altered metabolism of the antihypertensive drug, metoprolol, and elevated levels of dietary compounds such as piperine and lutein in individuals with high cognitive resilience. By leveraging public metabolomics data, we further contextualized the metabolic signatures with respect to their organ specificity, microbial origin, and disease associations. Collectively, these metabolic features, including several previously underexplored compounds, represent promising candidates for functional characterization in mechanisms of aging biology and provide mechanistic insights into the molecular basis of cognitive resilience. HighlightsO_LISerum metabolite MS/MS features, including acyl carnitines, phosphocholines, and hippuric acid conjugates, are associated with cognitive resilience in 237 individuals transitioning from middle to older age. C_LIO_LIDiet-derived piperine is positively associated with cognitive resilience. C_LIO_LIDifferences in {beta}-blocker drug metabolism, rather than parent drug levels, are associated with cognitive resilience. C_LIO_LIRepository-scale searches for the resilience-associated metabolites reveal organ specificity, microbial contributions, and their presence across multiple disease contexts. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=166 SRC="FIGDIR/small/715122v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1038203org.highwire.dtl.DTLVardef@14ca5f1org.highwire.dtl.DTLVardef@12275fcorg.highwire.dtl.DTLVardef@16ff70c_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Farnesoid X receptor-dependent microbiome-bile acid signaling mediates obstructive sleep apnea-induced atherosclerosis

Intermittent hypoxia and hypercapnia (IHC), a hallmark of obstructive sleep apnea (OSA), accelerates atherosclerosis, yet the underlying mechanisms remain unclear. The gut microbiota and metabolites, specifically bile acids, change with IHC and thus the bile acid receptor farnesoid X receptor (FXR) might mediate IHC-induced atherosclerosis. In this study, ApoE-/- and ApoE-/- FXR-/- mice were exposed to IHC or room air and fed with a high-fat, high-cholesterol diet for 10 weeks. Markers of atherosclerosis, fecal microbiome, and metabolome were then examined via Sudan IV staining, absolute abundance shotgun metagenomics, and untargeted liquid chromatography tandem mass spectrometry (LC-MS/MS). IHC markedly increased aortic atherosclerosis in ApoE-/-mice, an increase that was abolished by FXR deficiency. In addition, IHC reshaped gut microbial composition, promoting enrichment of bile acid-modifying taxa and increasing levels of microbial hydroxysteroid dehydrogenase (hsdh). The bile acid pool was also remodeled and associated with aortic atherosclerosis via FXR-dependent metabolic signals in ApoE-/- mice. Knockout of FXR disrupted microbiome shift under IHC and uncoupled microbial bile acid metabolism from vascular lesion development, thereby protecting against aortic atherosclerosis. These findings show that FXR has a central role in linking IHC, microbial bile acid metabolism, and cardiovascular pathology.

microbiology↗

bioRxiv2026

Unlocking the Bile Acid Universe: Advanced Workflows and a Multidimensional Library of 280 Unique Species

Microbes and bile acids are tightly intertwined, especially in the gut. While the liver produces primary bile acids from cholesterol, gut bacteria transform these into diverse secondary forms which act as powerful signaling molecules, influencing host metabolism and immune function. Since bile acid changes are increasingly linked to health and disease, their accurate measurement in the gut and circulation is essential. Analytical evaluations, however, remain challenging as many bile acids co-elute in liquid chromatography (LC), share identical precursor masses in mass spectrometry (MS), and produce similar tandem mass spectrometry (MS/MS) spectra. As a result, conventional LC-MS/MS workflows struggle to differentiate bile acids, motivating the addition of orthogonal separations such as ion mobility spectrometry (IMS). Here, we assess optimal bile acid extraction parameters for stool, serum, and plasma; compare LC conditions; and assess electrospray ionization performance across polarities. Additionally, we created a multidimensional reference library containing LC retention times, IMS collision cross section values, and accurate precursor masses for 280 unique bile acids (264 endogenous and 16 deuterium-labeled species) including unconjugated, host-conjugated, and microbially conjugated bile acids. This multidimensional library empowers bile acid identification in complex samples and enables a more comprehensive exploration of their biological roles and disease associations.

microbiology↗

bioRxiv2026

Navigating the conjugated metabolome

Lifes chemical diversity far exceeds current biochemical maps. While metabolomics has catalogued tens of thousands of small molecules, conjugated metabolites, formed when two or more molecular entities are covalently fused through amidation, esterification, or related chemistries, remain underexplored. These molecules can act as microbial signals, detoxification intermediates, or endogenous regulators. Here, we mined 1.32 billion MS/MS spectra across public metabolomics repositories using reverse spectral searching coupled with delta-mass inference to map conjugation events. We generated structural hypotheses for 24,227,439 MS/MS clusters. From these, we inferred 217,291 substructure pairs with dual spectral support and 3,412,720 candidate conjugates with single-match support. Predictions span host-microbe co-metabolites, diet-derived conjugates, and drug-derived species, including drug-ethanolamine and creatinine conjugates with altered bioactivities. We also uncover a family of steroid-phosphoethanolamine conjugates. Fifty-five conjugates were matched by MS/MS of synthetic standards for this work, with 27 additionally supported by retention time matching in biological samples. Guidance on how to leverage this resource is also provided. Together, these results deliver a pan-repository map of potential conjugation chemistry, establish a resource for structural discovery and MS/MS annotation, and offer a scalable framework to explore the scope and diversity of the conjugated metabolome.

bioinformatics↗

bioRxiv2026

A searchable metadata network graph for microbiome metabolomics

Establishing the biological context of microbial metabolites remains a major challenge. We present microbiomeMASST, a metadata-driven network graph that maps metabolites across 467 available datasets with 144,424 mass spectrometry files from humans, animals, and microbial culture systems. MicrobiomeMASST integrates monocultures, synthetic communities, and host-associated samples across multiple body sites and plants. MS/MS spectra can be queried to trace occurrence across hosts, experimental conditions, and interventions, enabling cross-study integration. We demonstrate this framework by contextualizing microbial-conjugated bile acids and interrogating microbiome-mediated drug metabolism. Screening gut bacteria revealed deprolylation of the angiotensin-converting enzyme (ACE) inhibitor prodrug enalapril. Using microbiomeMASST, we traced this metabolite across human cohorts, microbial isolates, environmental samples, and in Gorilla gorilla. Structural modeling and enzymatic assays showed that microbial deprolylation abolishes ACE inhibition, thereby inactivating its therapeutic effect. Together, microbiomeMASST links MS/MS spectra to biological context, converting isolated observations into an interpretable microbiome map for cross-study analysis.

biochemistry↗

bioRxiv2025

Charting the Undiscovered Metabolome with Synthetic Multiplexing

Most molecular features detected in untargeted metabolomics remain uncharacterized due to the limited scope of existing spectral reference libraries. We synthesized >100,000 biologically inspired compounds using multiplexed reactions, of which 91% were absent from existing structural databases, and searched the resulting MS/MS library across >1.7 billion public spectra, increasing annotation rates by 17.4%. This approach revealed previously undescribed exposure-derived metabolites, including ibuprofen-carnitine. Because ibuprofen has been linked to rhabdomyolysis, reduced mitochondrial function, and impaired muscle recovery in carnitine-limited contexts, we investigated the functional relevance of this conjugate. Ibuprofen-carnitine reduced carnitine transport via the OCTN2 transporter, and in a postpartum mouse muscle injury model, ibuprofen delayed muscle repair that could be rescued by carnitine supplementation, with urinary ibuprofen-carnitine:carnitine ratios tracking this effect. These findings support a hypothesis whereby NSAID-carnitine conjugates compete for carnitine transport, impairing energy metabolism and muscle recovery in susceptible individuals. Synthetic multiplexing thus provides a scalable route to annotate the dark metabolome and generate experimentally testable biological hypotheses.

biochemistry↗

bioRxiv2025

Microbial lipid shifts in a multi-stage simulated gut

Food residues that bypass human digestion are further digested by gut microbes, leading to the production of diverse metabolites, including lipids. To investigate how lipids are affected during this transition, we used a colon simulator with four distinct vessels that mimics the proximal to distal part of the human colon. We observed dynamic shifts in a diverse array of microbially derived lipid molecules in the simulated intestinal chyme, including bile acids and N-acyl amides with short and odd-chain lipids. Histamine-linked N-acyl lipids increased from the proximal to the distal colon vessels (pH 5.5 - 7.0), whereas putrescine-linked, initially abundant in the media, decreased across the colon vessels. We uncovered dynamic associations between in vitro-derived short-chain N-acyl lipids and major lipid species such as cholesterol esters, phosphatidylethanolamines, ceramides, and sphingomyelins. To determine the broader relevance of these findings, we applied a reverse metabolomics approach and examined lipid profiles in human small intestine and fecal samples from public datasets. This validated the colon simulator as a model for studying diet-derived and microbially transformed metabolites with relevance to human and animal health and could perhaps be used as a strategy to discover microbial metabolites.

biochemistry↗

bioRxiv2025

Environmental and Maternal Imprints on Infant Gut Metabolic Programming

Early life is a critical period for immune and metabolic programming, but developmental patterns remain underexplored in populations from low- and middle-income countries. Here, we profiled the microbiome and metabolome of 55 Bangladeshi mother-infant dyads over the first six months of life. Importantly, we observed an increase in microbially-derived bile amidates and N-acyl lipids with age in conjunction with reads matching the bile salt hydrolase/transferase (bsh) gene. While microbial source tracking confirmed maternal fecal seeding, a substantial environmental contribution was also highlighted. Differences in infant fecal metabolic profiles were associated with delivery mode, maternal milk composition, household assets, and household-level water treatment. C-section delivery and untreated drinking water were linked to transient metabolic differences, including increases in bile amidates, N-acyl lipids, and other host-microbe co-metabolic products, including acylcarnitines. Multi-omics analysis revealed specific microbial-metabolite relationships, highlighting how early environmental and maternal living circumstances shape metabolic gut programming through the microbiome.

microbiology↗

bioRxiv2025

Influence of perinatal ampicillin exposure on maternal fecal microbial and metabolic profiles

Indirect exposure to antibiotics during early life, via maternal intrapartum antibiotic prophylaxis (IAP) or postpartum maternal antibiotic usage, is increasingly common and has been epidemiologically linked to altered growth and immune developmental trajectories in offspring. Nevertheless, the underlying mechanisms remain poorly understood. Here, we explored the effects of antepartum and postpartum maternal ampicillin administration on the dams fecal microbiome and metabolic profiles in vivo. Ampicillin caused a reproducible depletion of beneficial bacterial species belonging to the Muribaculaceae family, including Muribaculum intestinale and Duncaniella dubosii, and led to cohort-dependent enrichments of Enterococcus and Prevotella species. These microbial alterations were accompanied by substantial metabolic remodeling, characterized by elevated fecal acylcarnitines and dysregulation of the bile acids profile. Intriguingly, we identified two previously uncharacterized trihydroxylated bile acids conjugated to a hexose moiety, which appeared to be associated with antibiotic exposure across public metabolomics repositories. These alterations in the fecal maternal microbiome and metabolome coincided with increased weight gain in offspring, suggesting a possible role for maternal antibiotic exposure in shaping early developmental trajectories. Further studies are warranted to elucidate the long-term implications of these changes in infant health. IMPORTANCEPerinatal antibiotic administration is a critical intervention to reduce maternal and neonatal infections, including early-onset group B Streptococcus (GBS) disease, a major cause of neonatal mortality. Nevertheless, mounting evidence suggests that the use of broad-spectrum antibiotics during the perinatal period in mothers can affect infant gut microbiome development, with potential consequences for immune maturation and early development. Understanding how maternal antibiotic exposure affects the gut microbiome and metabolome is essential for uncovering the potential pathways by which maternal intervention may influence offspring outcomes and for guiding strategies that balance infection control with long-term infant health.

microbiology↗

bioRxiv2025

A Multi-Organ Murine Metabolomics Atlas Reveals Molecular Dysregulations in Alzheimer's Disease

The etiology of Alzheimers Disease (AD) remains largely unclear but is likely driven by gene-environment interactions. Here, we present a multi-organ untargeted metabolomics dataset (2,271 samples) generated from five tissue types in two genetic AD mouse models under colonized or germ-free conditions, complemented by shotgun metagenomics sequencing data (666 samples). Systems-level analyses of 3xTg and 5xFAD mice reveal clusters of dysregulated molecular classes across tissues including carnitines, bile acids, B vitamins, and neurotransmitters. This signature, coupled with microbiome profiles, suggests increased oxidative stress via mitochondrial dysfunction. Molecular feature tracking via tissueMASST, a mass spectrometry search tool we developed to bridge animal model findings with human data, identifies microbially-modulated phenylacetyl-carnitine as positively associated with aging and cognitive impairment across human AD studies. With hundreds of yet-to-be-characterized metabolites, this public resource and its associated tools will aid future research in the pathophysiology of AD.

microbiology↗

bioRxiv2025

Fecal Microbial and Metabolic Signatures in VEO-IBD: Implications for Unique Pathophysiology

Background and AimsVery early onset inflammatory bowel disease (VEO-IBD) is a clinically distinct form of IBD manifesting in children before the age of six years. Disease in these children is especially severe and often refractory to treatment. While previous studies have investigated changes in the fecal microbiome and metabolome in adult and pediatric IBD, insights in VEO-IBD remain limited. This multi-omics analysis reveals changes in the fecal microbiome and metabolome in VEO-IBD compared with healthy controls. MethodsFecal samples were collected from children diagnosed with VEO-IBD and age- and sex-matched healthy controls. Both the fecal metabolome and microbiome were profiled in each sample, using untargeted liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) and 16S rRNA gene amplicon sequencing. ResultsFecal microbial and metabolic profiles in VEO-IBD were significantly different from healthy controls. Untargeted metabolomics analysis identified a depletion of short-chain N-acyl lipids and an enrichment of dipeptides, tripeptides, and oxo bile acids in VEO-IBD patients. Differential abundance analysis of the gut microbiome showed lower abundance of beneficial bacteria such as Bifidobacterium and Blautia, and higher abundance of Lachnospira, Veillonella, and Bacteroides in VEO-IBD. The joint analysis suggested a clear association between the altered gut microbiome composition and metabolic dysregulation, specifically for the N-acyl lipids. ConclusionsThis study offers unique insight into fecal microbial and metabolic signatures in VEO-IBD, paving the way for a better understanding of disease patterns and thereby more effective treatment strategies.

microbiology↗

bioRxiv2025

MS/MS Mass Spectrometry Filtering Tree for Bile Acid Isomer Annotation.

Bile acids are essential steroids regulating immunity, nutrient absorption, insulin, appetite, and body temperature. Their structural diversity is vast, but due to spectral similarities, MS/MS spectral matching often fails to resolve isomers. This study introduces a proof-of-concept workflow using a mass spectrometry query language filtering tree that distinguishes isomeric bile acids in untargeted LC-MS/MS data. Its application revealed a deoxycholyl-2-aminophenol amidate linked to whole grain consumption.

bioinformatics↗

bioRxiv2025

Adaptive Example Selection: Prototype-Based Explainability for Interpretable Mitosis Detection

Understanding the decision-making process of black-box neural network classifiers is crucial for their adoption in medical applications, including histopathology and cancer diagnostics. An approach of increasing interest is to clarify how the decisions of neural networks compare to, and perform parallel to, those of highly-trained and knowledgeable clinicians and other medical professionals within their prototypical classes of interest. Motivated by this, we introduce Adaptive Example Selection (AES), a prototype-based explainable AI (XAI) framework that facilitates the interpretability of deep learning models for mitosis detection. AES works by selecting and presenting a small set of real-world mitotic images most informative to a given classification, allowing pathologists to visually assess and understand the neural networks decision by comparing test cases with similar previously annotated examples. AES achieves this by expanding the neural networks confidence/belief function and fitting it to a radial basis function (RBF) approximator, an approach we term Decision Boundary-based Analysis (DBA). This method makes the decision boundary more transparent, offering robust visual insights into the models decisions, and thereby equipping clinicians with the information needed to effectively utilize AI-driven diagnostics. Additionally, AES includes customizable user controls, allowing clinicians to tailor decision thresholds and select prototype examples to better align with their specific diagnostic needs. This flexibility empowers users to engage with the AI model more directly and meaningfully, increasing its practical relevance in clinical settings.

pathology↗

bioRxiv2024

The microbiome diversifies N-acyl lipid pools - including short-chain fatty acid-derived compounds

N-acyl lipids are important mediators of several biological processes including immune function and stress response. To enhance the detection of N-acyl lipids with untargeted mass spectrometry-based metabolomics, we created a reference spectral library retrieving N-acyl lipid patterns from 2,700 public datasets, identifying 851 N-acyl lipids that were detected 356,542 times. 777 are not documented in lipid structural databases, with 18% of these derived from short-chain fatty acids and found in the digestive tract and other organs. Their levels varied with diet, microbial colonization, and in people living with diabetes. We used the library to link microbial N-acyl lipids, including histamine and polyamine conjugates, to HIV status and cognitive impairment. This resource will enhance the annotation of these compounds in future studies to further the understanding of their roles in health and disease and highlight the value of large-scale untargeted metabolomics data for metabolite discovery.

bioinformatics↗

bioRxiv2024

Empirically establishing drug exposure records directly from untargeted metabolomics data

Despite extensive efforts, extracting information on medication exposure from clinical records remains challenging. To complement this approach, we developed the tandem mass spectrometry (MS/MS) based GNPS Drug Library. This resource integrates MS/MS data for drugs and their metabolites/analogs with controlled vocabularies on exposure sources, pharmacologic classes, therapeutic indications, and mechanisms of action. It enables direct analysis of drug exposure and metabolism from untargeted metabolomics data independent of clinical records. Our library facilitates stratification of individuals in clinical studies based on the empirically detected medications, exemplified by drug-dependent microbiota-derived N-acyl lipid changes in a cohort with human immunodeficiency virus. The GNPS Drug Library holds potential for broader applications in drug discovery and precision medicine.

bioinformatics↗