Biology subjects

Dorrestein, P. C.

Publications and source records attributed to Dorrestein, P. C..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Early seed priming with closely related Bacillus strains induces divergent physiological and defense responses in melon

Early microbial seed priming is a promising strategy to improve crop resilience, yet it remains unclear whether plants can discriminate among closely related beneficial strains and integrate dose-dependent microbial cues. We primed melon (Cucumis melo) seeds with two phylogenetically similar Bacillus strains (B. subtilis NCIB3610 and B. velezensis FZB42) and combined transcriptomic, metabolomic and physiological analyses across development. Despite comparable colonization, the strains provoked contrasting host programs and distinct dose responses. B. subtilis promoted radicle elongation, chloroplastic starch storage and drought tolerance irrespective of inoculum level, together with L-tryptophan and palatinose accumulation. By contrast, B. velezensis displayed a clear dose effect: low inoculum sustained normal radicle growth, whereas high inoculum transiently repressed it, coinciding with retrotransposon activation, suppression of AOS and proteasome genes, and enrichment of flavonoids and glutathione in leaves. Chemical assays showed that radicle inhibition requires the combination of surfactin, produced by both strains, with bacillomycin D, an iturin-type lipopeptide unique to FZB42; neither molecule alone reproduced the effect. This synergy links the strain-specific lipopeptide repertoire to the dose-dependent growth response. Although their early trajectories diverged, both primings converged on improved above-ground performance. 3610-primed plants restricted Botrytis cinerea via caffeic- and rosmarinic-acid accumulation, whereas FZB42-primed plants curtailed jasmonate-sensitive Tetranychus urticae mites through early JA-pathway activation. Our results demonstrate that melon perceives inoculum dose and microbial identity, translating them into distinct metabolic and defense programs that converge on stress resilience. These mechanistic insights-linking lipopeptide fingerprints, sentinel metabolites and defense transcripts-provide a framework for precision seed treatments in horticultural crops.

plant biology↗

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↗

bioRxiv2024

Gut Microbiota and Derived Metabolites Mediate Obstructive Sleep Apnea Induced Atherosclerosis

BackgroundObstructive sleep apnea (OSA) is characterized by intermittent hypoxia/hypercapnia (IHC), affects predominantly obese individuals, and increases atherosclerosis risk. Since we and others have implicated gut microbiota and metabolites in atherogenesis, we dissected their contributions to OSA-induced atherosclerosis. ResultsAtherosclerotic lesions were compared between conventionally-reared specific pathogen free (SPF) and germ-free (GF) ApoE-/- mice following a high fat high cholesterol diet (HFHC), with and without IHC conditions. The fecal microbiota and metabolome were profiled using 16S rRNA gene amplicon sequencing and untargeted tandem mass spectrometry (LC-MS/MS) respectively. Phenotypic data showed that HFHC significantly increased atherosclerosis as compared to regular chow (RC) in both aorta and pulmonary artery (PA) of SPF mice. IHC exacerbated lesions in addition to HFHC. Differential abundance analysis of gut microbiota identified an enrichment of Akkermansiaceae and a depletion of Muribaculaceae (formerly S24-7) family members in the HFHC-IHC group. LC-MS/MS showed a dysregulation of bile acid profiles with taurocholic acid, taurodeoxycholic acid, and 12-ketodeoxycholic acid enriched in the HFHC-IHC group, long-chain N-acyl amides, and phosphatidylcholines. Interestingly, GF ApoE-/- mice markedly reduced atherosclerotic formation relative to SPF ApoE-/- mice in the aorta under HFHC/IHC conditions. In contrast, microbial colonization did not show a significant impact on the atherosclerotic progression in PA. ConclusionsIn summary, this research demonstrated that (1) IHC acts cooperatively with HFHC to induce atherosclerosis; (2) gut microbiota modulate atherogenesis, induced by HFHC/IHC, in the aorta not in PA; (3) different analytical methods suggest that a specific imbalance between Akkermansiaceae and Muribaculaceae bacterial families mediate OSA-induced atherosclerosis; and (4) derived bile acids, such as deoxycholic acid and lithocholic acid, regulate atherosclerosis in OSA. The knowledge obtained provides novel insights into the potential therapeutic approaches to prevent and treat OSA-induced atherosclerosis.

microbiology↗

bioRxiv2024

To impute or not to impute in untargeted metabolomics - that is the compositional question

Untargeted metabolomics often produce large datasets with missing values, arising from biological or technical factors, which can undermine statistical analyses and lead to biased biological interpretations. Imputation methods, such as k-Nearest Neighbors (kNN) and Random Forest (RF) regression are commonly used but their effects vary depending on the type of missing data e.g. Missing Completely At Random (MCAR) and Missing Not At Random (MNAR). Here, we determined the impacts of degree and type of missing data on the accuracy of kNN and RF imputation using two datasets: a targeted metabolomic dataset with spiked-in standards and an untargeted metabolomic dataset. We also assessed the effect of compositional data approaches (CoDA), such as the centered log-ratio (CLR) transform, on data interpretation, since these methods are increasingly being used in metabolomics. Overall, we found that kNN and RF performed more accurately when the proportion of missing data across samples for a metabolic feature was low. However, these imputations could not handle MNAR data and generated wildly inflated values or imputed values where none should exist. Furthermore, we show that the proportion of missing values had a strong impact on the accuracy of imputation which affected the interpretation of the results. Our results suggest extreme caution should be used with imputation even with modestly levels of missing data or when the type of missingness is unknown.

bioinformatics↗

bioRxiv2024

Annotating full-scan MS data using tandem MS libraries

Public liquid chromatography-mass spectrometry (LC-MS) and MS imaging metabolomics data repositories contain millions of files, with over 40% of them consisting solely of MS1 (full-scan) information, creating a significant gap in data reuse potential due to limited annotation capabilities. Here, we present ms1-id, an open-source Python package providing a unified solution for structural annotation of full-scan MS data applicable to both LC-MS and MS imaging analyses. Our approach leverages in-source fragments to generate pseudo MS/MS spectra through correlation analysis in either chromatographic or spatial domains. We introduce precursor-tolerant reverse spectral matching that accommodates multiple ion forms simultaneously and peak intensity scaling that enables matching of low-energy in-source fragments against existing reference MS/MS libraries. Applied to inflammatory bowel disease cohorts and diverse MS imaging samples, our method uncovers metabolites previously overlooked in traditional analyses. This strategy effectively addresses a critical need in metabolomics data reuse by enabling level 2/3 structural annotation of MS1-only data, facilitating new biological insights from existing repository data that was previously only annotated at the molecular formula level.

bioinformatics↗

bioRxiv2024

Metabolomic Profiling Reveals Potential of Fatty Acids as Regulators of Stem-like Exhausted CD8 T Cells During Chronic Viral Infection

Chronic infections drive a CD8 T cell program termed T cell exhaustion, characterized by reduced effector functions. While cell-intrinsic mechanisms underlying CD8 T cell exhaustion have been extensively studied, the impact of the metabolic environment in which exhausted CD8 T cells (Tex) operate remains less clear. Using untargeted metabolomics and the murine lymphocytic choriomeningitis virus infection model we investigated systemic metabolite changes early and late following acute versus chronic viral infections. We identified distinct short-term and persistent metabolite shifts, with the most significant differences occurring transiently during the acute phase of the sustained infection. This included nutrient changes that were independent of viral loads and partially associated with CD8 T cell-induced anorexia and lipolysis. One remarkable observation was the elevation of medium- and long-chain fatty acid (FA) and acylcarnitines during the early phase after chronic infection. During this time, virus-specific CD8 T cells from chronically infected mice exhibited increased lipid accumulation and uptake compared to their counterparts from acute infection, particularly stem-like Tex (TexSTEM), a subset that generates effector-like TexINT which directly limit viral replication. Notably, only TexSTEM increased oxidative metabolism and ATP production upon FA exposure. Consistently, short-term reintroduction of FA during late chronic infection exclusively improved TexSTEM mitochondrial fitness, percentages and numbers. This treatment, however, also reduced TexINT, resulting in compromised viral control. Our study offers a valuable resource for investigating the role of specific metabolites in regulating immune responses during acute and chronic viral infections and highlights the potential of long-chain FA to influence TexSTEM and viral control during a protracted infection. SignificanceThis study examines systemic metabolite changes during acute and chronic viral infections. Notably, we identified an early, transient nutrient shift in chronic infection, marked by an increase in medium- and long-chain fatty acid related species. Concomitantly, a virus-specific stem-like T cell population, essential for maintaining other T cells, displayed high lipid avidity and was capable of metabolizing exogenous fatty acids. Administering fatty acids late in chronic infection, when endogenous lipid levels had normalized, expanded this stem-like T cell population and enhanced their mitochondrial fitness. These findings highlight the potential role of fatty acids in regulating stem-like T cells in chronic settings and offer a valuable resource for studying other metabolic signatures in both acute and persistent infections.

immunology↗

bioRxiv2024

Human untargeted metabolomics in the gut microbiome era: ethanol vs methanol

Untargeted metabolomics is frequently performed on human fecal samples in conjunction with sequencing to unravel gut microbiome functionality. As sample collection efforts rapidly expand, with individuals often collecting specimens at home, metabolomics experiments should adapt to accommodate the safety and needs of bulk off-site collections. Here, we show that a 95% ethanol, safe to be shipped and handled, extraction pipeline recovers comparable amounts of metabolites as a validated 50% methanol extraction, preserving metabolic profiles differences between subjects. Additionally, the fecal metabolome remains relatively stable when stored in 95% ethanol for up to a week at room temperature. Finally, we suggest a metabolomics data analysis workflow using robust centered log ratio transformation, which removes variance introduced by different sample weights, allowing for reliable and integration-ready untargeted metabolomics experiments in gut microbiome studies.

biochemistry↗

bioRxiv2024

Untargeted and Semi-Targeted Metabolomics Approach for Profiling Small Intestinal and Fecal Metabolome Using High-Resolution Mass Spectrometry

The gut microbiome is a complex ecosystem varying along different gut sections, consisting of metabolites from food, host, and microbes. Microbially-derived metabolites like bile acids and short-chain fatty acids interact with host physiology. Current studies often use fecal samples, which dont fully represent the upper gut due to stratification. To sample the proximal gut microbiome, endoscopic methods or new non-invasive devices are used. We developed an approach combining untargeted and semi-targeted metabolomics using a Q-Exactive Plus Orbitrap mass spectrometer to profile gut metabolites. We initially selected 49 key metabolites based on specific criteria, validated them through repeatability tests, and created a compound database with TraceFinder software. Our workflow enables molecule annotation in untargeted studies while validating 37 metabolites in semitargeted analyses. This method, applied to clinical trial samples (NCT05477069), shows promise in discovering new gut metabolites. HighlightsO_LIInnovative Combined Metabolomics Workflow: The study introduces a combined approach that integrates semi-targeted and untargeted metabolomics analyses to characterized small intestinal and fecal metabolomes. This method allows for the relative quantification of carefully selected metabolites and the reanalysis of these metabolites using evolving curated databases, enhancing the understanding of the gut microbiome-health axis. C_LIO_LIUntargeted Metabolomics Strategy: The untargeted approach aims to determine the global metabolic profile of samples and discover new metabolites. This involves processing data through a detailed pipeline, statistical analysis, and feature annotation using tools like MZmine, MetaboAnalyst, and the GNPS platform. C_LIO_LIProof of Concept on Clinical Samples: The combined approach was tested on clinical samples from a participant in a clinical trial, revealing distinct metabolomes between small intestinal content and fecal samples. This proof of concept demonstrated the methods ability to identify and quantify metabolites, showing significant differences in metabolite abundance between the two sample types and highlighting the potential for discovering new bile acids through molecular networking. C_LI

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

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↗

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

Urinary Metabolomic Profile is Minimally Impacted by Common Storage Conditions and Additives

Metabolomics reflects the molecular communications within a biological system. Urine can be obtained non-invasively and is rich in metabolites that are potential biomarkers for human health and disease. The optimal urine storage conditions for metabolomic analysis are unknown. We measured the impact of common storage conditions and the presence of a DNA-stabilizer, AssayAssure(R) (Thermo Scientific), on metabolite content of voided human urine. Urinary metabolite composition was not altered across storage conditions. Although addition of AssayAssure(R) significantly alters metabolic profile by adduct addition, this does not preclude the identification of parent metabolites or overshadow biological differences. These data suggest biobanked urine stored in any of the tested conditions for metabolomic studies may be considered for metabolomic analysis.

molecular biology↗

bioRxiv2024

Perinatal ampicillin administration modulates murine bile acid metabolism in vivo - an observational study

Antibiotics are an indispensable tool of modern medicine, yet their impact extends beyond eliminating harmful bacteria to perturbing the commensal bacteria constituting the gut microbiome. This collateral damage is particularly significant in early life when the gut microbiome is still developing. In humans, antibiotic administration during infancy and childhood is associated with various long-term negative health outcomes. However, existing research has predominantly focused on the direct administration of antibiotics to infants, leaving uncertainties about whether indirect antibiotic exposure produces similar effects. Here, we use mouse models to investigate how three distinct routes of exposure to the commonly prescribed broad-spectrum antibiotic ampicillin influences parent and infant metabolism. These methods simulate major modes of both direct and indirect antibiotic exposure: intravenous antibiotic administration to the mother immediately before birth mimicking intrapartum antibiotic prophylaxis, antibiotic use by the mother during lactation, and direct administration to infants mimicking empiric antibiotic treatment for neonatal sepsis. Through untargeted metabolomics of fecal samples from mouse dams and infants, we identified one class of compounds, bile acids and related cholane steroids, as particularly sensitive to ampicillin treatment. Bile acids, produced by the host and extensively modified by the gut microbiome, serve as important mediators in the cross-talk between the microbiota and the host. Here, we detail the coordinated changes in bile acid metabolism in response to a commonly prescribed antibiotic, focusing on dams treated both pre- and postpartum. Additionally, we identify unique bile acids associated with weight gain in infant mice. ImportanceAntibiotics are widely used perinatally, administered to both parents and infants before, during, and after birth. While they can play a life-saving role, antibiotics also result in collateral damage to the beneficial microbes constituting the gut microbiome. These microbes have many important functions, particularly in the metabolism of small molecules in the body. One such group of molecules, bile acids, undergo extensive modifications by bacteria and may act as a "language" through which microbes communicate with the host. This observational study investigates the impact of the commonly prescribed antibiotic ampicillin on the metabolism of these molecules during childbirth. Our results indicate that ampicillin administration pre- or post-partum significantly alters the mothers bile acid metabolism, but has a minimal influence on infant bile acid levels. However, in all cases, ampicillin administration significantly increased infant weight, even when the antibiotic was solely administered to the mother.

pharmacology and toxicology↗

bioRxiv2023

High Resolution Biological and Physical Sampling Reveals Expression of Domoic Acid Biosynthetic Genes at Frontal Zones

Ocean microbes are the foundation of marine food webs, regulating carbon cycling and ecosystem dynamics. How they proliferate, die, move, and interact is regulated by physical, chemical, and biological factors that are dynamic and challenging to quantify in the natural environment. A significant limitation in many marine field studies is the inability to continuously sample the ever-changing ocean environment over space and time. In this study, we integrated spatiotemporal and multi-omic sample collection in an intensive sampling effort of phytoplankton ecology in Monterey Bay, California during the spring of 2021. Sampling methods coupled: (1) manual shipboard CTD sampling, (2) autonomous sampling using a Long-Range Autonomous Underwater Vehicle (LRAUV) equipped with an Environmental Sampling Processor (ESP), and (3) high-resolution physical measurements by an autonomous vertical profiler (Wirewalker). Sampling occurred as upwelling waned alongside declining domoic acid (DA) and low abundances of toxigenic Pseudo-nitzschia. Conditions needed to spark a widespread and toxic Pseudo-nitzschia bloom were absent, yet low-level DA was driven by similar mechanisms to those causing elevated DA. Three DA biosynthetic intermediate molecules were reported in the environment for the first time. Both shipboard and ESP sampling approaches identified DA biosynthetic gene expression at frontal zones. DA and expression of dabA, the gene encoding the first committed step of DA biosynthesis, were higher in association with recently upwelled water that supplied nutrients for growth and DA biosynthesis. Detection of subtle variations in dab gene expression in response to environmental variation provide a window into the ecological dynamics underpinning major toxic events. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/562961v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@1c1f554org.highwire.dtl.DTLVardef@d16b02org.highwire.dtl.DTLVardef@c856e1org.highwire.dtl.DTLVardef@bfd248_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2023

Comparative metabolomics and microbiome analysis of Ethanol vs. OMNImet/gene GUT fecal stabilization

Metabolites from feces provide important insights into the functionality of the gut microbiome. As immediate freezing is not always feasible in gut microbiome studies, there is a need for sampling protocols that provide stability of the fecal metabolome and microbiome at room temperature (RT). For this purpose, we investigated the stability of various metabolites and the microbiome (16S ribosomal RNA) in feces collected in 95% ethanol (EtOH) or OMNImet(R)*GUT/ OMNIgene(R)*GUT. To simulate in field-collection scenarios, the samples were stored at different temperatures at varying durations (24h +4{degrees}C, 24h RT, 36h RT, 48h RT, and 7 days RT), and compared to aliquots immediately frozen at -80{degrees}C. We applied several targeted and untargeted metabolomics platforms to measure lipids, polar untargeted metabolites, endocannabinoids, short chain fatty acids (SCFAs), and bile acids (BAs). We found that SCFAs in the non-stabilized samples increased over time, while a stable profile was recorded in sample aliquots stored in 95% EtOH and OMNImet(R)*GUT. When comparing the metabolite levels between fecal aliquots stored at room temperature and at +4{degrees}C, we detected several changes in microbial metabolites, including multiple BAs and SCFAs. Taken together, we found that storing fecal samples at room temperature and stabilizing them in 95% EtOH yielded metabolomic results comparable to flash freezing. We also found that overall composition of the gut microbiome did not vary significantly between different storage types. However, there were notable differences observed in alpha diversity. Taken together, the stability of the metabolome and microbiome in 95 % EtOH provided similar results as the validated commercial collection kits OMNImet(R)*GUT and OMNIgene(R)*GUT, respectively. IMPORTANCEThe analysis of the gut metabolome and microbiome requires the separate collection of fecal specimens using conventional methods or commercial kits. However, these approaches can potentially introduce sampling errors and biases. In addition, the logistical requirements of studying large human cohorts have driven the need for home collection and transport of human fecal specimens at room temperature. By adopting a unified sampling approach at room temperature, we can enhance sampling convenience and practicality, leading to a more precise and comprehensive understanding of gut microbial function. However, the development and applications of such unified sampling systems still face limitations. The results presented in this study aim to address this knowledge gap by investigating the stability of metabolites and the microbiome (16S ribosomal RNA) from fecal samples collected using 95% EtOH, in comparison to well-established commercial collection kits for fecal metabolome (OMNImet(R)*GUT) and microbiome (OMNIgene(R) *GUT) profiling. Additionally, we perform a comparative analysis of various platforms and metabolomic coverage using matrices containing ethanol, evaluating aspects of sensitivity, robustness, and throughput.

biochemistry↗