Biology subjects

Melnik, A. V.

Publications and source records attributed to Melnik, A. V..

11 recordsLinked to original sources

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

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↗

bioRxiv2020

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS.

Gas chromatography-mass spectrometry (GC-MS) represents an analytical technique with significant practical societal impact. Spectral deconvolution is an essential step for interpreting GC-MS data. No public GC-MS repositories that also enable repository-scale analysis exist, in part because deconvolution requires significant user input. We therefore engineered a scalable machine learning workflow for the Global Natural Product Social Molecular Networking (GNPS) analysis platform to enable the mass spectrometry community to store, process, share, annotate, compare, and perform molecular networking of GC-MS data. The workflow performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization, using a Fast Fourier Transform-based strategy to overcome scalability limitations. We introduce a "balance score" that quantifies the reproducibility of fragmentation patterns across all samples. We demonstrate the utility of the platform with breathomics analysis applied to the early detection of oesophago-gastric cancer, and by creating the first molecular spatial map of the human volatilome.

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

The Molecular and Microbial Microenvironments in Chronically Diseased Lungs

To visualize the personalized distributions of pathogens, chemical environments including microbial metabolites, pharmaceuticals, and their metabolic products within and between human lungs afflicted with cystic fibrosis, we generated 3D microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments are variable between patients and within the lungs of each patient. Although the patients microbial ecosystems were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in lungs of the same individual sometimes exceeded inter-individual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate a complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.\n\nImportanceMicrobial infections are now recognized to be polymicrobial and personalized in nature. A comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remains limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we describe how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment, or vice versa. We highlight that three-dimensional organ mapping are hypothesis building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.

microbiology↗

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↗

bioRxiv2018

Identification of the bacterial biosynthetic gene clusters of the oral microbiome illuminates the unexplored social language of bacteria during health and disease

Small molecules are the primary communication media of the microbial world. Recent bioinformatics studies, exploring the biosynthetic gene clusters (BGCs) which produce many small molecules, have highlighted the incredible biochemical potential of the signaling molecules encoded by the human microbiome. Thus far, most research efforts have focused on understanding the social language of the gut microbiome, leaving crucial signaling molecules produced by oral bacteria, and their connection to health versus disease, in need of investigation. In this study, a total of 4,915 BGCs were identified across 461 genomes representing a broad taxonomic diversity of oral bacteria. Sequence similarity networking provided a putative product class for over 100 unclassified novel BGCs. The newly identified BGCs were cross-referenced against 254 metagenomes and metatranscriptomes derived from individuals with either good oral health, dental caries, or periodontitis. This analysis revealed 2,473 BGCs, which were differentially represented across the oral microbiomes associated with health versus disease. Co-abundance network analysis identified numerous inverse correlations between BGCs and specific oral taxa. These correlations were present in health, but greatly reduced in dental caries, which may suggest a defect in colonization resistance. Finally, corroborating mass spectrometry identified several compounds with homology to products of the predicted BGC classes. Together, these findings greatly expand the number of known biosynthetic pathways present in the oral microbiome and provide an atlas for experimental characterization of these abundant, yet poorly understood, molecules and socio-chemical relationships, which impact the development of caries and periodontitis, two of the worlds most common chronic diseases.\n\nIMPORTANCEThe healthy oral microbiome is symbiotic with the human host, importantly providing colonization resistance against potential pathogens. Dental caries and periodontitis are two of the worlds most common and costly chronic infectious diseases, and are caused by a localized dysbiosis of the oral microbiome. Bacterially produced small molecules, often encoded by BGCs, are the primary communication media of bacterial communities, and play a crucial, yet largely unknown, role in the transition from health to dysbiosis. This study provides a comprehensive mapping of the BGC repertoire of the human oral microbiome and identifies major differences in health compared to disease. Furthermore, BGC representation and expression is linked to the abundance of particular oral bacterial taxa in health versus dental caries and periodontitis. Overall, this study provides a significant insight into the chemical communication network of the healthy oral microbiome, and how it devolves in the case of two prominent diseases.

microbiology↗

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↗