Biology subjects

Aksenov, A. A.

Publications and source records attributed to Aksenov, A. A..

17 recordsLinked to original sources

bioRxiv2026

A microbial metabolite reduces alcohol-induced inflammation via dual modulation of NF-κB and Interferon pathway

Background and aimsAlcohol-associated hepatitis (AH) is characterized by excessive inflammation and blunted antiviral interferon (IFN) responses. We hypothesized that specific gut microbiome-derived metabolites could selectively enhance interferon signaling while limiting NF-{kappa}B mediated inflammation, thereby restoring immune balance in AH. Our goal is to identify microbiome-derived metabolites that differentially regulate the NF-{kappa}B and IFN signaling pathways. Methods and resultsWe used human monocytic THP1-Dual cells, which secrete reporters for NF-{kappa}B and IFN signaling, to model innate immune responses and screened a library of 152 gut microbiome-derived metabolites. From the metabolite screen, 4-hydroxyphenylacetic acid (4-HPAA) emerged as a unique immunomodulator: in LPS-challenged cells, 4-HPAA selectively increased IFN signaling with minimal NF-{kappa}B activation. 4-HPAA was evaluated in vivo using a NIAAA-model, with 4-HPAA supplementation (0.4mg/ml) added to the diet. In the NIAAA-model, dietary 4-HPAA did not induce liver injury and was associated with enhanced interferon-stimulated gene expression. Simultaneously, 4-HPAA reduced pro-inflammatory markers such as Il1{beta}, Ly6g and F4/80 compared to the group exposed to ethanol alone. Metabolomic profiling of mouse cecal contents revealed 4-HPAA supplementation counteracted ethanols metabolic effects, selectively reducing triglyceride-associated lipids that had accumulated with ethanol feeding. Conclusions4-HPAA enhances interferon signaling and antiviral gene induction while dampening NF-{kappa}B-driven inflammation in the presence of LPS, both in vitro and in vivo. In an acute-on-chronic alcohol injury model, 4-HPAA attenuated hepatic inflammation, reduced immune cell recruitment, and activated antioxidant defenses, reflecting a shift toward a more hepatoprotective effect. 4-HPAA treatment was associated with reduced pro-inflammatory markers and modest attenuation of ethanol-induced liver injury. Additionally, 4-HPAA reversed ethanol-induced lipid-dysregulation, particularly triglyceride accumulation, highlighting its metabolic benefit in alcohol-fed mice. In conclusion, 4-HPAA rebalances immune and metabolic pathways by enhancing IFN signaling, suppressing NF-{kappa}B inflammation, and reversing alcohol-induced hepatic injury and lipid accumulation.

immunology↗

bioRxiv2026

HNSW-MS: Hierarchical Graph Indexing Enables Accurate Real-Time Mass Spectral Similarity Search at Repository Scale

Spectral similarity comparison is the basis of mass spectrometry-based metabolomics, underpinning library matching, molecular network construction, and repository searches such as MASST. Public repositories now exceed billion spectra, and exhaustive pairwise comparison is increasingly limiting. We introduce HNSW-MS, which implements Hierarchical Navigable Small World graph indexing natively for mass spectra. It operates directly on GC-MS and LC-MS/MS spectra without embedding, so scores are identical to those of exhaustive comparison and results are fully reproducible. On the benchmark dataset of 8.4 million LC-MS/MS spectra, HNSW-MS is up to 900-fold faster than linear search, recall@1 and recall@10 achieve over 90%, with the recall-speedup tradeoff tunable at query. Such rapid retrieval allows for any query spectrum to be near-instantaneously integrated into a global molecular network. We demonstrate specific examples of use of global networking for molecular discovery, including uncovering a new pathway of stenothricin biosynthesis and a new dipeptide conjugate bile acid.

bioinformatics↗

bioRxiv2025

Moving from Association to Causation: Instrumental factor models for causal inference in high-dimensional multi-omics data

Distinguishing true causal relationships from mere association is a core challenge in bioinformatics and science in general. Causal inference, in particular in "-omics" studies, is hindered by high dimensionality, correlated measurements, and pervasive endogeneity arising from unmeasured confounding and complex interventions. We introduce Factor IV, a supervised instrumental variable (IV) framework for identifying causal effects in high-dimensional biological systems. FactorIV constructs low-dimensional instrumental factors via a sparse low-rank decomposition of the instrument-exposure map, yielding an identifiable first stage even when either/both endogenous and instrumental variables are high-dimensional. Under standard IV assumptions, these factors remain orthogonal to outcome noise while capturing coordinated, perturbation-driven biological variation. The framework supports generalized first-stage models, including Gaussian, Bernoulli and negative binomial likelihoods. Simulation studies demonstrate accurate recovery of factor-level and feature-level causal effects under linear and generalized settings, with robustness to correlated errors and hidden confounding. To illustrate biological discovery, we applied FactorIV to a mouse hepatocellular carcinoma model and the DIABIMMUNE infant cohort. We demonstrate how FactorIV uncovers mechanistically interpretable causal structure beyond association-based analyses.

bioinformatics↗

bioRxiv2025

Variational Autoencoders for Metabolomics: Data Imputation, Deconfounding, and Correlation Discovery

This protocol describes a computational approach for constructing correlation-based molecular networks from untargeted metabolomics data using MetVAE, a variational autoencoder-based framework. Complementing spectral similarity networks, it captures functional relationships re-flected in cross-sample correlations. The workflow imports metabolomics features and sample metadata, adjusts for compositionality, missingness, confounding, and high-dimensionality, esti-mates sparse metabolite correlations, and exports GraphML files for network visualization. In a hepatocellular carcinoma mouse model, it links lipid classes in high-fat-diet animals, suggesting an endogenous "auto-brewery" route to lipotoxic metabolites.

bioinformatics↗

bioRxiv2025

S'Wipe: User-Friendly Stool Collection for High-Throughput Gut Metabolomics

Microbiome is increasingly recognized as a key factor in health. Intestinal microbiota modulates gut homeostasis via a range of diverse metabolites. For example, molecules such as short chain fatty acids (SCFAs), the microbial fermentation products of dietary fiber, have been established to be reflective of microbiome and/or dietary shifts and SCFAs alterations have been linked to multiple gastrointestinal disorders from cancer to colitis. Despite their potential as biomarkers, technical challenges in stool collection have limited clinical translation. Here we present Stool Wipe (SWipe), an ultra-low-cost fecal collection method using lint-free, mass spectrometry-compatible cellulose wipes as toilet paper. Specimens are preserved in ethanol without refrigeration and can be shipped via regular mail. Mass spectrometry analysis demonstrated that SWipe captures both volatile and non-volatile metabolites with reproducibility and stability validated for diagnostically relevant molecules. We show that SWipe performs equivalently to direct stool collection, enabling interchangeable use and comparison with existing studies. This methodology is ideally suited for large-scale population studies, longitudinal tracking, and personalized medicine applications. IMPORTANCEGut microbiome and intestinal metabolome present invaluable diagnostic and therapeutic targets. However, conventional stool testing has several barriers limiting bioassessment from populations. Routine, high temporal resolution monitoring of stool metabolome, including extensively validated and broadly informative biomarkers such as short chain fatty acids (SCFAs), is not implemented due to relatively high cost and inconvenience of sampling, possible need for clinical setting for sample collection, difficulty to collect samples reproducibly, especially due to potential for user errors, requirement for freezer storage and maintaining cold chain during shipment. We present a sampling strategy specifically designed to overcome these obstacles. We demonstrate how this method can enable capturing accurate molecular snapshots at massive scales, at ultra low cost. The approach collapses complex medical-grade collection into easy self-administration. Individuals can thereby self-monitor therapeutic responses through routine metabolome tracking, including the volatilome, otherwise hindered by infrastructure restrictions. Ultimately, this sampling approach is intended to enable participatory wellness transformation through practical high frequency self-sampling.

biochemistry↗

bioRxiv2024

Ordering molecular diversity in untargeted metabolomics via molecular community networking

Natures molecular diversity is not random but displays intricate organization stemming from biological necessity. Molecular networking connects metabolites with structural similarity, enabling molecular discoveries from mass spectrometry data using arbitrary similarity thresholds that can fracture natural metabolite families. We present molecular community networking (MCN), that optimizes connectivity for each metabolite, rescuing lost relationships and capturing otherwise "hidden" metabolite connections. Using MCN, we demonstrate the discovery of novel dipeptide-conjugated bile acids.

biochemistry↗

bioRxiv2024

Spatial chemistry of citrus reveals molecules bactericidal to Candidatus Liberibacter asiaticus

Huanglongbing (HLB), associated with the psyllid-vectored phloem-limited bacterium, Candidatus Liberibacter asiaticus (CLas), is a disease threat to all citrus production worldwide. Currently, there are no sustainable curative or prophylactic treatments available. In this study, we utilized mass spectrometry (MS)-based metabolomics in combination with 3D molecular mapping to visualize complex chemistries within plant tissues to explore how these chemistries change in vivo in HLB-impacted trees. We demonstrate how spatial information from molecular maps of branches and single leaves yields insight into the biology not accessible otherwise. In particular, we found evidence that flavonoid biosynthesis is disrupted in HLB-impacted trees, and an increase in the polyamine, feruloylputrescine, is highly correlated with an increase in disease severity. Based on mechanistic details revealed by these molecular maps, followed by metabolic modeling, we formulated and tested the hypothesis that CLas infection either directly or indirectly converts the precursor compound, ferulic acid, to feruloylputrescine to suppress the antimicrobial effects of ferulic acid and biosynthetically downstream flavonoids. Using in vitro bioassays, we demonstrated that ferulic acid and bioflavonoids are indeed highly bactericidal to CLas, with the activity on par with a reference antibiotic, oxytetracycline, recently approved for HLB management. We propose these compounds should be evaluated as therapeutics alternatives to the antibiotics for HLB treatment. Overall, the utilized 3D metabolic mapping approach provides a promising methodological framework to identify pathogen-specific inhibitory compounds in planta for potential prophylactic or therapeutic applications.

plant biology↗

bioRxiv2024

S-Wipe: stool sample collection for metabolomic gut health tracking

Microbiome is increasingly recognized as a key factor in health. Intestinal microbiota modulates gut homeostasis via a range of diverse metabolites. Molecules such as short chain fatty acids (SCFAs), the microbial fermentation products of dietary fiber, have been established to be reflective of microbiome and/or dietary shifts and have been linked to multiple gastrointestinal disorders from cancer to colitis, and thus present an excellent diagnostic target. Yet, technical bottlenecks preclude broad translation of such established biomarkers into routine medical practice. In particular, easily accessible, reproducible and robust sampling of stool remains challenging. Here we present Stool Wipe (S-Wipe), an ultra low cost, simplified fecal specimen collection approach designed to overcome key translational barriers without compromising analytical rigor. This sampling approach harnesses lint-free mass spectrometry-compatible cellulose wipes used as a regular toilet paper. The collected stool specimens are then preserved in ethanol solution, do not require refrigeration and can be shipped via regular mail. Using mass spectrometry, we have demonstrated a broad range of captured metabolites, both volatile and non-volatile. The reproducibility and stability of the method was validated for a panel of molecules of particular diagnostic interest, including SCFAs and p-cresol. We demonstrate sensitivity as well as stability and reproducibility of various metabolites collected with S-Wipe. We further demonstrate that S-Wipe is equivalent to the direct stool collection and thus could be used interchangeably and compared to other studies where stool is collected directly. This methodology is ideally suited and is scalable for broad population-based studies, longitudinal tracking such as therapeutic interventions and personalized medicine. IMPORTANCEGut microbiome and intestinal metabolome present invaluable diagnostic and therapeutic targets. However, conventional stool testing has several barriers limiting bioassessment from populations. Routine, high temporal resolution monitoring of stool metabolome, including validated biomarkers such as SCFAs, is not implemented due to relatively high cost and inconvenience of sampling, possible need for clinical setting for sample collection, difficulty to collect samples reproducibly, especially due to possible user errors, requirement for freezer storage and maintaining cold chain during shipment. We present a sampling strategy specifically designed to overcome these obstacles. This method can enable capturing accurate molecular snapshots at massive scales, at ultra low cost. The approach collapses complex medical-grade collection into easy self-administration. Individuals can thereby self-monitor therapeutic responses through routine metabolome tracking, including the volatilome, otherwise hindered by infrastructure restrictions. Ultimately, this sampling approach is intended to enable participatory wellness transformation through practical high frequency self-sampling.

biochemistry↗

bioRxiv2022

Open Access Repository-Scale Propagated Nearest Neighbor Suspect Spectral Library for Untargeted Metabolomics

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of public MS/MS spectra. Annotations were propagated based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimers brain phenotype. The nearest neighbor suspect spectral library is openly available through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

bioinformatics↗

bioRxiv2021

Multi-omics profiling of Earth's biomes reveals that microbial and metabolite composition are shaped by the environment

As our understanding of the structure and diversity of the microbial world grows, interpreting its function is of critical interest for understanding and managing the many systems microbes influence. Despite advances in sequencing, lack of standardization challenges comparisons among studies that could provide insight into the structure and function of microbial communities across multiple habitats on a planetary scale. Technical variation among distinct studies without proper standardization of approaches prevents robust meta-analysis. Here, we present a multi-omics, meta-analysis of a novel, diverse set of microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry), centering our description on relationships and co-occurrences of microbially-related metabolites and microbial taxa across environments. Standardized protocols and analytical methods for characterizing microbial communities, including assessment of molecular diversity using untargeted metabolomics, facilitate identification of shared microbial and metabolite features, permitting us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of a community resource that will become more valuable with time. To provide examples of applying this database, we outline important ecological questions that can be addressed, and test the hypotheses that every microbe and metabolite is everywhere, but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment. The relative abundances of microbially-related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner, and highlight the power of certain chemistry - in particular terpenoids - in distinguishing Earths environments.

ecology↗

bioRxiv2020

Ion Identity Molecular Networking in the GNPS Environment

Molecular networking connects tandem mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. To connect ion species of the same molecule, we developed Ion Identity Molecular Networking. These new relationships improve network connectivity, are shown to reveal novel ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral libraries.

bioinformatics↗

bioRxiv2019

Repository-scale Co- and Re-analysis of Tandem Mass Spectrometry Data

Metabolomics data are difficult to find and reuse, even in public repositories. We, therefore, developed the Reanalysis of Data User (ReDU) interface (https://redu.ucsd.edu/), a community- and data-driven approach that solves this problem at the repository scale. ReDU enables public data discovery and co- or re-analysis via uniformly formatted, publicly available MS/MS data and metadata in the Global Natural Product Social Molecular Networking Platform (GNPS), consistent with findable, accessible, interoperable, and reusable (FAIR) principles.1

bioinformatics↗

bioRxiv2019

Chemical Impacts of the Microbiome Across Scales Reveal Novel Conjugated Bile Acids

A mosaic of cross-phyla chemical interactions occurs between all metazoans and their microbiomes. In humans, the gut harbors the heaviest microbial load, but many organs, particularly those with a mucosal surface, associate with highly adapted and evolved microbial consortia1. The microbial residents within these organ systems are increasingly well characterized, yielding a good understanding of human microbiome composition, but we have yet to elucidate the full chemical impact the microbiome exerts on an animal and the breadth of the chemical diversity it contributes2. A number of molecular families are known to be shaped by the microbiome including short-chain fatty acids, indoles, aromatic amino acid metabolites, complex polysaccharides, and host lipids; such as sphingolipids and bile acids3-11. These metabolites profoundly affect host physiology and are being explored for their roles in both health and disease. Considering the diversity of the human microbiome, numbering over 40,000 operational taxonomic units12, a plethora of molecular diversity remains to be discovered. Here, we use unique mass spectrometry informatics approaches and data mapping onto a murine 3D-model13-15 to provide an untargeted assessment of the chemical diversity between germ-free (GF) and colonized mice (specific-pathogen free, SPF), and report the finding of novel bile acids produced by the microbiome in both mice and humans that have evaded characterization despite 170 years of research on bile acid chemistry16.

microbiology↗

bioRxiv2019

Cutibacterium acnes antibiotic production shapes niche competition in the human skin microbiome

The composition of the skin microbiome varies widely among individuals sampled at the same body site. A key question is which molecular factors determine strain-level variability within sub-ecosystems of the skin. We used a genomics-guided approach to identify an antibacterial biosynthetic gene cluster in Cutibacterium acnes (formerly Propionibacterium acnes) that is widely distributed across individuals and skin sites. Experimental characterization of this cluster enabled the identification of a new thiopeptide antibiotic, cutimycin. Analysis of individual human skin hair follicles showed that cutimycin is an important factor regulating colonization resistance against Staphylococcus species.\n\nOne Sentence SummaryCutimycin, a thiopeptide antibiotic produced by a widespread skin commensal, reduces Staphylococcus colonization of human follicles.

microbiology↗

bioRxiv2019

MASST: A Web-based Basic Mass Spectrometry Search Tool for Molecules to Search Public Data.

CorrespondenceWe introduce a web-enabled small-molecule mass spectrometry (MS) search engine. To date, no tool can query all the public small-molecule tandem MS data in metabolomics repositories, greatly limiting the utility of these resources in clinical, environmental and natural product applications. Therefore, we introduce a Mass Spectrometry Search Tool (MASST) (https://proteosafe-extensions.ucsd.edu/masst/), that enables the discovery of molecular relationships among accessible public metabolomics and natural product tandem mass spectrometry data (MS/MS).

bioinformatics↗

bioRxiv2018

Untargeted Mass Spectrometry-Based Metabolomics Tracks Molecular Changes in Raw and Processed Foods and Beverages

A major aspect of our daily lives is the need to acquire, store and prepare our food. Storage and preparation can have drastic effects on the compositional chemistry of our foods, but we have a limited understanding of the temporal nature of processes such as storage, spoilage, fermentation and brewing on the chemistry of the foods we eat. Here, we performed a temporal analysis of the chemical changes in foods during common household preparations using untargeted mass spectrometry and novel data analysis approaches. Common treatments of foods such as home fermentation of yogurt, brewing of tea, spoilage of meats and ripening of tomatoes altered the chemical makeup through time, through both chemical and biological processes. For example, brewing tea altered its composition by increasing the diversity of molecules, but this change was halted after 4 min of brewing. The results indicate that this is largely due to differential extraction of the material from the tea and not modification of the molecules during the brewing process. This is in contrast to the preparation of yogurt from milk, spoilage of meat and the ripening of tomatoes where biological transformations directly altered the foods molecular composition. Comprehensive assessment of chemical changes using multivariate statistics showed the varied impacts of the different food treatments, while analysis of individual chemical changes show specific alterations of chemical families in the different food types. The methods developed here represent novel approaches to studying the changes in food chemistry that can reveal global alterations in chemical profiles and specific transformations at the chemical level.\n\nO_LSTHighlightsC_LSTO_LIWe created a reference data set for tomato, milk to yogurt, tea, coffee, turkey and beef.\nC_LIO_LIWe show that normal preparation and handling affects the molecular make-up.\nC_LIO_LITea preparation is largely driven by differential extraction.\nC_LIO_LIFormation of yogurt involves chemical transformations.\nC_LIO_LIThe majority of meat molecules are not altered in 5 days at room temperature.\nC_LI

biochemistry↗

bioRxiv2018

American Gut: an Open Platform for Citizen-Science Microbiome Research

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the USA, UK, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes as compared to environmental samples, demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations, uncover new molecules and kinds of molecular communities in the human stool metabolome, and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness, and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education.\n\nImportanceWe show that a citizen-science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n=1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet which we confirm with untargeted metabolomics on hundreds of samples.

microbiology↗