Biology subjects

Zemlin, J.

Publications and source records attributed to Zemlin, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Mapping bacterial bile amidation across the bile salt hydrolase family

Evaluating enzyme activity and specificity in complex microbiomes is challenging. The recent discovery that bacterial bile salt hydrolases (BSHs) also function as transaminases in the human gut microbiome highlights what remains to be disentangled, even within one of the most extensively studied microbiomes. BSHs as transaminases can conjugate bile acids with bioavailable amines to produce bacterial bile amidates (BBAs). The implications of BBAs for human health are rapidly evolving, but our understanding of which BSHs produce which specific BBAs remains limited. Here, we connect BSH sequence and function by evaluating the transaminase activities of 115 BSHs and reveal distinct amine specificities using molecular networking. Additionally, we identify enzymatically generated BBAs distributed across life-stage, tissue-, and disease-specific human samples by mining public metabolomics repositories, highlighting the previously unrecognized catalytic diversity of BSHs and their potential relevance to human health.

biochemistry↗

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

The Urogenital Lactobacillus Axis Across Menopause: Connections Between the Vagina, Bladder, and Urinary Metabolome

Alterations in the female urinary microbiome have been linked to several several common urinary conditions that increase in prevalence after menopause. Here we use sequencing and metabolomic data to compare the urinary bladder microenvironments between women who are premenopausal, postmenopausal, and postmenopausal using vaginal estrogen. While the urinary microbiome differs between pre- and postmenopausal women, at least 6 weeks of vaginal estrogen is associated with higher urinary lactobacilli and fewer opportunistic pathogens in the urinary postmenopausal microbiome, which closer approximates what is seen in the premenopausal context. Changes in urinary Lactobacillus species are correlated with vaginal pH and the same Lactobacillus species found in the vaginal microbiome tend to also be identified within the urinary bladder microbiome. Urinary metabolites differ by context (e.g., pre-, post-, and post-menopausal using vaginal estrogen), but the majority of metabolites that drive these differences are unannotated. Of the metabolites with shared associations among different Lactobacillus species, L. iners have consistently inverse relationships compared to L. crispatus, L. gasseri, or L. jensenii.

systems biology↗

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

Antibiotic Exposure Through Human Milk Influences the Infant Gut Microbiome

Infant antibiotic treatment is associated with increased risk of developing non-communicable diseases, potentially through disruption of the gut microbiome. However, the impact of indirect antibiotic exposure via human milk remains largely unexplored. Here, we investigate a cohort (n=80) of antibiotic-treated breastfeeding mother-infant dyads and untreated matching controls using integrative multi-omics analyses of fecal, milk, and skin samples (n=1,455). Maternal antibiotic treatment was associated with different infant fecal microbiome and metabolome profiles, including lower abundance of Bacteroides, Lactobacillus, and Bifidobacterium, and higher levels of antimicrobial resistance gene reads. Further, fecal metabolic alterations associated with indirect antibiotic exposure were exacerbated by formula milk supplementation. In a subset of infants (n=61), indirect exposure was associated with higher body mass index (BMI). These findings suggest that maternal antibiotic treatment during lactation may influence the early-life infant gut microbiome with potential long-term implications.

microbiology↗

bioRxiv2026

Pan-Metabolomics Repository Mapping of the Carnitine Landscape

Carnitines are a structurally diverse class of metabolites formed by conjugation of L-carnitine with fatty acids, amino acids, xenobiotics, and microbial metabolites. They play roles in transport, mitochondrial and peroxisomal metabolism, detoxification, and systemic signaling, yet their chemical diversity remains incompletely defined. We applied a pan-repository data mining strategy of LC-MS/MS data across GNPS/MassIVE, MetaboLights, and Metabolomics Workbench using MassQL diagnostic fragment ion filtering to systematically extract acylcarnitine spectra. This yielded a library of 34,222 unique MS/MS spectra representing 2,857 atomic compositions, corresponding to 3,872,050 detections. These datasets provide an MS/MS library for annotation, discovery, and contextualization of acylcarnitines, enabling identification of previously unknown carnitines, such as dihydroferulic acid conjugated carnitines and supporting future exploration of this metabolite class across host metabolism, diet, microbial activity, pharmacological exposures, and metabolic dysregulation.

bioinformatics↗

bioRxiv2026

Multi-omics Analyses of Facial Skin in Acne Identify Distinct Microbial and Metabolic Features at Lesional and Non-lesional Sites

The microbial and biochemical landscape of clinically normal-appearing skin in individuals with acne remains uncharacterized. Here, we performed longitudinal multi-omics profiling of facial skin from 10 individuals with moderate acne and 10 healthy controls, integrating 16S rRNA gene sequencing, shotgun metagenomics, and untargeted metabolomics across lesional and non-lesional sites. Compositional tensor factorization revealed that non-lesional acne skin occupies a distinct intermediate state between healthy and lesional skin in both the microbiome and the metabolome. Machine learning models distinguished healthy from non-lesional acne skin with 70% accuracy, demonstrating that molecular dysbiosis occurs in areas of the skin without visible lesions. Non-lesional sites exhibited reduced microbial diversity, strain-level shifts in Corynebacterium and Lawsonella correlating with disease severity, and metabolic alterations, including elevated lipids and perturbed amino acid and dipeptide profiles. Microbe-metabolite co-occurrence network analyses revealed that healthy skin is enriched for protective metabolites such as urocanic acid, while acne-associated skin shows distinct co-occurrence patterns. These findings establish that acne represents a field effect disorder, with molecular alterations extending beyond visible lesions to encompass the entire facial skin ecosystem. This molecular signature of pre-lesional skin provides potential biomarkers for early intervention and suggests that effective acne treatment may require holistic approaches targeting the broader skin environment rather than individual lesions alone.

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

Effect of Perinatal Ampicillin or Amoxicillin/Clavulanate Exposure on Maternal and Infant Gut Microbiome, Metabolome, and Infant Responses to the 20-valent Pneumococcal Conjugate Vaccine

Emerging studies suggest that antibiotics can disrupt the gut microbiome and alter vaccine-induced immune responses, but the specific consequences of early-life exposure on neonatal immune development remains poorly understood. Here, we examined how two antibiotics frequently used in perinatal care, broad-spectrum ampicillin (AMP) and the extended-spectrum combination amoxicillin/clavulanate (AMOX/CLAV), administered during gestation and lactation, influence neonatal gut microbiome composition, fecal metabolome profiles, and responses to the 20-valent pneumococcal conjugate vaccine (PCV20). Maternal treatment with AMOX/CLAV, but not AMP, significantly reduced PCV-specific IgG titers at 4-and 6-weeks post-prime immunization compared to untreated controls. Exclusive exposure to AMOX/CLAV also impaired neutrophil-mediated opsonophagocytic killing, indicating diminished antibody functionality. These effects were transient, with immune parameters normalizing by week 8 post-prime immunization. Metabolomic and microbiome profiling revealed that maternal AMP and AMOX/CLAV differentially perturbed specific metabolite classes including bile acids, N-acyl lipids, and indole-derivatives, as well as key commensal taxa including Bacteroidales and Coriobacteriales within the gut microbiota. Together, these findings reveal a previously underappreciated maternal-offspring route of antibiotic influence that transiently disrupts neonatal vaccine responsiveness through microbiome and metabolome alterations. These results highlight maternal antibiotic exposure as a modifiable factor shaping early-life immunity.

microbiology↗

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

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↗

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

Pathogenic Bacteroides fragilis strains can emerge from gut-resident commensals

Bacteroides fragilis is a prominent member of the human gut microbiota, playing crucial roles in maintaining gut homeostasis and host health. Although it primarily functions as a beneficial commensal, B. fragilis can become pathogenic. To determine the genetic basis of its duality, we conducted a comparative genomic analysis of 813 B. fragilis strains, representing both commensal and pathogenic origins. Our findings reveal that pathogenic strains emerge across diverse phylogenetic lineages, due in part to rapid gene exchange and the adaptability of the accessory genome. We identified 16 phylogenetic groups, differentiated by genes associated with capsule composition, interspecies competition, and host interactions. A microbial genome-wide association study identified 44 genes linked to extra-intestinal survival and pathogenicity. These findings reveal how genomic diversity within commensal species can lead to the emergence of pathogenic traits, broadening our understanding of microbial evolution in the gut.

microbiology↗

bioRxiv2023

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms role in ecology and human health.

microbiology↗