Biology subjects

Dorrestein, P.

Publications and source records attributed to Dorrestein, P..

At least 19 recordsLinked to original sources

bioRxiv2026

The caddisfly gut microbiome contributes to the consumption of riparian leaf litter within rivers

Ecosystem functions can be regulated by biodiversity ranging from broad to narrow scales, including variation within a species. For most multicellular life, intraspecific variation is determined not only by an organism's phenotype and genotype, but also variation imparted by their microbiome. Here, we investigate how leaf decomposition in rivers is affected by phenotypic variation in plant secondary metabolites (PSMs) and antibiotic-induced variation within the gut microbiomes of aquatic macroinvertebrate decomposers. We found that consumption by Dicosmoecus caddisflies was inhibited by the presence of dietary PSMs from riparian Alnus rubra trees, irrespective of the state of their gut microbiome. We further compared consumption of diets prepared from 20 different local and non-local A. rubra trees. We found that antibiotic-treated and control caddisflies consumed similar amounts of diets containing local A. rubra PSMs. However, compared to caddisflies with an intact gut microbiome, antibiotic-treated caddisflies consumed less of non-local A. rubra diets. Thus, decomposition by caddisflies could be regulated by both host adaptation to local resources and bacterial-mediated digestion of non-local resources. Overall, our study suggests that gut microbiomes can facilitate adjustment of macroinvertebrate decomposers to novel plant phenotypes, which may arise from shifting spatial distributions of plants in response to global change.

ecology↗

bioRxiv2026

Among-population variation in the threespine stickleback ( Gasterosteus aculeatus ) liver metabolome: effects of ancestry and environment

Untargeted metabolomics offers a powerful lens for quantifying high-dimensional phenotypic variation within and among species in nature, but has yet to be widely adopted in evolutionary ecology. Some important initial questions are whether metabolome composition differs among populations, and to what extent such variation is genetic or plastic. Here, we use untargeted liquid chromatography tandem mass spectrometry to characterize the relative abundance of 5,939 molecular features of the threespine stickleback (Gasterosteus aculeatus) liver metabolome. Native lake populations differ in metabolome composition, reflecting effects of sex, size, geography, and population ecotype (benthic versus limnetic). Stickleback from these lakes were translocated to found new populations in nine recently fishless lakes, permuting fish ecotypes across benthic and limnetic lake habitats. Several generations later, metabolomes in these experimental populations reflect effects both of their genetic ancestry (e.g., taurocholic acid, a cholane steroid bile acid, was elevated in limnetic-ancestries), as well as their present habitat (e.g., acylcarnitines). Additionally, ecotypes transplanted into a habitat to which they were maladapted exhibited a distinctive metabolomic profile. We conclude that stickleback exhibit both heritable and plastic among-population differences in liver metabolome, which could represent an important phenotypic basis of rapid evolution, population divergence, and perhaps local adaptation.

Molecular Biology↗

bioRxiv2026

TIMS-Bench: Towards community standards for benchmarking untargeted trapped ion mobility metabolomics tools and datasets

Untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics is an important technology for unbiased discovery of small molecules in biomedical (e.g., drug discovery to diagnostics), animal, plant, environmental, and microbial research. Over the past decade, ion mobility has added an additional dimension to the triplet of MS1, MS2, and retention time, helping resolve co-eluting or isomeric features in an LC-MS/MS that aid in compound identification. Here, we focused on evaluating the current trapped ion mobility spectrometry (TIMS)-amenable feature-finding tools (MZmine 4.9, MS-DIAL 5.5, and MetaboScape 2025 14.0.3) for pre-processing of metabolomics data generated using a popular ion mobility mass spectrometry (IM-MS) technique, TIMS. We leveraged ten public and three benchmark TIMS datasets to evaluate these tools for their strengths and weaknesses. Our results show that MZmine consistently identified the highest number of features and confidently annotated features; however, this performance was accompanied by an increased number of false positives, due to peak splitting, as well as reduced accuracy in collision cross section (CCS) measurements. In contrast, MetaboScape achieved the highest fraction of high-quality MS2 spectra, reflecting a more conservative feature detection strategy. MS-DIAL demonstrated balanced performance, identifying features that other tools missed. Finally, we publicly release the ground-truth datasets and code to support future developments in improving IMS data analysis.

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↗

bioRxiv2023

A multi-omics strategy for the study of microbial metabolism: application to the human skin's microbiome

Although metabolomics data acquisition and analysis technologies have become increasingly sophisticated over the past 5-10 years, deciphering a metabolites function from a description of its structure and its abundance in a given experimental setting is still a major scientific and intellectual challenge. To point out ways to address this data to knowledge challenge, we developed a functional metabolomics strategy that combines state-of-the-art data analysis tools and applied it to a human scalp metabolomics dataset: Skin swabs from healthy volunteers with normal or oily scalp (Sebumeter score 60-120, n = 33; Sebumeter score > 120, n = 41) were analyzed by LC-MS/MS, yielding four metabolomics datasets for RP18 or HILIC separation in ESI+ or ESI- ionization mode. Following our data analysis strategy, we were able to obtain increasingly comprehensive structural and functional annotations, by applying the GNPS (Wang et al., Nat. Biotechnol. 2016), SIRIUS (Duhrkop et al. Nat. Methods 2019), and MicrobeMASST (Zuffa et al., bioRxiv 2023) tools. We finally combined the metabolomics data with a corresponding metagenomic sequencing dataset using MMvec (Morton et al., Nat. Methods 2019), gaining insights into the metabolic niche of one of the most prominent microbes on the human skin, Staphylococcus epidermidis. IMPORTANCESystems biology research on host-associated microbiota focuses on two fundamental questions: Which microbes are present and how do they interact with each other, their host, and the broader host environment? Metagenomics provides us with a direct answer to the first part of the question: it unveils the microbial inhabitants, e.g., on our skin, and can provide insight into their functional potential. Yet, it falls short in revealing their active role. Metabolomics shows us the chemical composition of the environment in which microbes thrive and the transformation products they produce. In particular, untargeted metabolomics has the potential to observe a diverse set of metabolites and is thus an ideal complement to metagenomics. However, this potential often remains underexplored due to the low annotation rates in MS-based metabolomics and the necessity for multiple experimental chromatographic and mass spectrometric conditions. Beyond detection, prospecting metabolites functional role in the host/microbiome metabolome requires identifying the biological processes and entities involved in their production and biotransformations. In the present study of the human scalp, we developed a strategy to achieve comprehensive structural and functional annotation of the metabolites in the human scalp environment, thus diving one step deeper into the interpretation of omics data. Leveraging a collection of openly accessible software tools and integrating microbiome data as a source of functional metabolite annotations, we finally identified the specific metabolic niche of Staphylococcus epidermidis, one of the key players of the human skin microbiome.

systems biology↗

bioRxiv2022

Distinct bile salt hydrolase substrate preferences dictate C. difficile pathogenesis

Summary paragraphBile acids (BAs) mediate the crosstalk between human and microbial cells and influence intestinal diseases including Clostridioides difficile infection (CDI). While bile salt hydrolases (BSHs) shape the BA pool by deconjugating conjugated BAs, the basis for their substrate preferences and impact on C. difficile remain elusive. Here, we survey the diversity of Lactobacillus BSHs and unravel the structural basis of their substrate preference. We show that leveraging BSH activity and specificity is an effective strategy to prevent C. difficile growth in clinically relevant CDI models. A range of non-canonical conjugated BAs is also identified, comprising unique BSH substrates that also inhibit C. difficile spore germination. These findings establish BSHs as intestinal enzymes essential to BA homeostasis and colonization resistance against C. difficile. One sentence summaryBile salt hydrolase activity inhibits C. difficile by shaping the conventional and non-canonical conjugated bile acid pools

microbiology↗

bioRxiv2021

Mutualistic interactions between B. subtilis and seeds dictate plant development

A tightly coordinated developmental program controls precise genetic and metabolic reprogramming that dictates efficient transition of the seeds from dormancy to metabolically active seedlings. Beneficial microbes are known to stimulate the germination of the seeds or adaptation of the seedlings; however, investigations of exact mechanisms mediating these interactions and the resulting physiological responses of the plants are only beginning. Bacillus subtilis is commonly detected in the plant holobiont and belongs to the group of microbes that provide multifaceted contribution to the health of the plants. The present study demonstrated that B. subtilis triggered genetic and physiological responses in the seeds that determined subsequent metabolic and developmental status of adult plants. Chemically diverse extracellular matrix of Bacillus was demonstrated to structurally cooperate in bacterial colonization of the seed storage tissues. Additionally, an amyloid protein and fengycin, which are two components of the extracellular matrix, targeted the oil bodies of the seed endosperm, provoking changes in lipid metabolism or accumulation of glutathione-related molecules that stimulated two different plant growth programs: the development of seed radicles or overgrowth and immunization of adult plants. We propose this mutualistic interaction is conserved in Bacilli and plant seeds containing storage oil bodies.

microbiology↗

bioRxiv2021

Targeted Neuronal Activation of the Gastrointestinal Tract Shapes the Environment of the Gut in Mice

The gastrointestinal (GI) tract is extensively innervated by intrinsic neurons of the enteric nervous system (ENS) and extrinsic neurons of the central nervous system and peripheral ganglia, which together regulate gut physiology. The GI tract also harbors a diverse microbiome, but interactions between the ENS and the microbiome remain poorly understood. Herein, we activate choline acetyltransferase (ChAT)-expressing or tyrosine hydroxylase (TH)-expressing gut-associated neurons in mice to determine effects on intestinal microbial communities and their metabolites, as well as on host physiology. The resulting multi-omics datasets support broad roles for discrete peripheral neuronal subtypes in shaping microbiome structure, including modulating bile acid profiles and fungal colonization. Physiologically, activation of either ChAT+ or TH+ neurons increases fecal output, while only ChAT+ activation results in increased colonic migrating motor complexes and diarrhea-like fluid secretion. These findings suggest that specific subsets of peripherally-activated ENS neurons differentially regulate the gut microbiome and GI physiology in mice, without involvement of signals from the brain.

physiology↗

bioRxiv2021

Chemical interplay and complementary adaptative strategies toggle bacterial antagonism and co-existence

Bacterial communities are in a continuous adaptive and evolutionary race for survival. A myriad of molecules that kill, defend, or mediate communication between bacterial cells of different lineages shape the final structure of the microbial community. In this work we expand our knowledge on the chemical interplay and specific mutations that modulate the transition from antagonism to co-existence between two plant-beneficial bacteria, Pseudomonas chlororaphis PCL1606 and Bacillus amyloliquefaciens FZB42. We reveal that the bacteriostatic activity of bacillaene produced by Bacillus relies on an interaction with the protein elongation factor FusA and how mutations in this protein lead to tolerance to bacillaene and other protein translation inhibitors. Additionally, we describe how the unspecific tolerance to antimicrobials associated with mutations in the glycerol kinase GlpK is provoked mainly by a decrease of Bacillus cell membrane permeability among other pleiotropic cellular responses. We conclude that nutrient specialization and mutations in basic biological functions are bacterial evolutive and adaptive strategies that lead to the coexistence of two primary competitive bacterial species rather than their mutual eradication.

microbiology↗

bioRxiv2020

EMPress enables tree-guided, interactive, and exploratory analyses of multi-omic datasets

Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive tool for visualizing trees in the context of microbiome, metabolome, etc. community data scalable beyond modern large datasets like the Earth Microbiome Project. EMPress provides novel functionality--including ordination integration and animations--alongside many standard tree visualization features, and thus simplifies exploratory analyses of many forms of omic data.

bioinformatics↗

bioRxiv2020

Siderophore-mediated zinc acquisition enhances enterobacterial colonization of the inflamed gut.

Zinc is an essential cofactor for bacterial metabolism, and many Enterobacteriaceae express the zinc transporters ZnuABC and ZupT to acquire this metal in the host. Unexpectedly, the probiotic bacterium Escherichia coli Nissle 1917 exhibited appreciable growth in zinc-limited media even when these transporters were deleted. By utilizing in vitro and in vivo studies, as well as native spray metal infusion mass spectrometry and ion identity molecular networking, we discovered that Nissle utilizes yersiniabactin as a zincophore. Indeed, yersiniabactin enables Nissle to scavenge zinc in zinc-limited media, to resist calprotectin-mediated zinc sequestration, and to thrive in the inflamed gut. Moreover, we discovered that yersiniabactins affinity for iron or zinc changes in a pH-dependent manner, with higher affinity for zinc as the pH increased. Altogether, we demonstrate that siderophore metal affinity can be influenced by the local environment and reveal a mechanism of zinc acquisition available to many commensal and pathogenic Enterobacteriaceae.

microbiology↗

bioRxiv2020

Characterizing the response of Acinetobacter baumannii ATCC 17978 to azithromycin in multiple in vitro growth conditions

Multi-drug resistant (MDR) Acinetobacter baumannii is one of the most concerning pathogens in hospital infections. A. baumannii is categorized as an "Urgent Threat" by the U.S. Centers for Disease Control and the highest priority pathogen by the World Health Organization due to its propensity for broad antibiotic resistance and its associated high mortality rates. New treatment options are urgently needed for MDR A. baumannii infections. Our prior studies have demonstrated an unappreciated utility of the macrolide azithromycin (AZM) against MDR A. baumannii in tissue-culture medium. This finding is all the more surprising since AZM has no appreciable activity against A. baumannii in standard bacteriological media. The basis for this media-dependent activity of AZM against A. baumannii is not fully defined. In this study, we utilize a variety of techniques (growth dynamics, bacterial cytological profiling, RNA sequencing, and LC/MS) to profile the response of MDR A. baumannii to AZM in both standard bacteriological and more physiological relevant mammalian tissue-culture medium. [Table 1]

microbiology↗

bioRxiv2020

Identifying the effect of vancomycin on HA-MRSA strains using bacteriological and physiological media

Healthcare-associated methicillin-resistant Staphylococcus aureus (HA-MRSA) USA100 strains are of major concern due to their evolving antibiotic resistant. They are resistant to a broad class of antibiotics like macrolides, aminoglycosides, fluoroquinolones, and many more. The selection of appropriate antibiotic susceptibility examination media is very important. Thus, we use bacteriological (CA-MHB) as well as physiological (R10LB) media to determine the effect of vancomycin on USA100 strains. The study includes the profiling behaviour of HA-MRSA USA100 D592 and D712 strains in the presence of vancomycin through various high-throughput assays. The US100 D592 and D712 strains were characterized at sub-inhibitory concentrations through growth curves, RNA sequencing, bacterial cytological profiling, and exo-metabolomics high throughput experiments. The study reveals the vancomycin resistance behavior of USA100 strains in dual media conditions using wide-ranging experiments.

microbiology↗

bioRxiv2020

Profiling the effect of nafcillin on HA-MRSA D592 using bacteriological and physiological media

Staphylococcus aureus is a leading human pathogen associated with both hospital-acquired and community-acquired infections. The bacterium has steadily gained resistance to {beta}-lactams and other important first-line antibiotics culminating in its categorization as an urgent threat by the U.S. Centers for Disease Control and Prevention. Observations of a varying response to antimicrobial exposure as a function of media type has revealed that clinical susceptibility testing performed in standard bacteriological media might not adequately represent pharmacological responses in the patient. Such observations have encouraged research designed to identify media types that more closely mimic the in vivo environment. In this study, we examine the response of a hospital-acquired USA100 lineage methicillin-resistant, vancomycin-intermediate S. aureus (MRSA/VISA) strain (D592) to nafcillin in a bacteriological compared to a more physiological tissue culture-based medium. We performed multi-dimensional analysis including growth and bacterial cytological profiling, RNA sequencing, and exo-metabolomics measurements (both HPLC and LC/MS) to shed light on the media-dependent activity of the commonly prescribed {beta}-lactam antibiotic nafcillin. O_TBL View this table: org.highwire.dtl.DTLVardef@85b95borg.highwire.dtl.DTLVardef@14c1504org.highwire.dtl.DTLVardef@1f7e976org.highwire.dtl.DTLVardef@100598dorg.highwire.dtl.DTLVardef@1f770e9_HPS_FORMAT_FIGEXP M_TBL C_TBL

microbiology↗

bioRxiv2019

Revisiting microbe-metabolite interactions: doing better than random

I.Recently, Quinn and Erb et al [1] made the case that when used correctly, correlation and proportionality can outperform MMvec when identifying microbe-metabolite interactions. We revisit this comparison and show that the proposed correlation and proportionality are outperformed by MMvec on real data due to their inability to deal with sparsity commonly observed in microbiome and metabolome datasets.

bioinformatics↗

bioRxiv2019

ZODIAC: database-independent molecular formula annotation using Gibbs sampling reveals unknown small molecules

1The confident high-throughput identification of small molecules remains one of the most challenging tasks in mass spectrometry-based metabolomics. SIRIUS has become a powerful tool for the interpretation of tandem mass spectra, and shows outstanding performance for identifying the molecular formula of a query compound, being the first step of structure identification. Nevertheless, the identification of both molecular formulas for large compounds above 500 Daltons and novel molecular formulas remains highly challenging. Here, we present ZODIAC, a network-based algorithm for the de novo estimation of molecular formulas. ZODIAC reranks SIRIUS molecular formula candidates, combining fragmentation tree computation with Bayesian statistics using Gibbs sampling. Through careful algorithm engineering, ZODIACs Gibbs sampling is very swift in practice. ZODIAC decreases incorrect annotations 16.2-fold on a challenging plant extract dataset with most compounds above 700 Dalton; we then show improvements on four additional, diverse datasets. Our analysis led to the discovery of compounds with novel molecular formulas such as C24H47BrNO8P which, as of today, is not present in any publicly available molecular structure databases.

bioinformatics↗

bioRxiv2019

Implementations of the chemical structural and compositional similarity metric in R and Python

MotivationTandem mass spectrometry (MS/MS) has the potential to substantially improve metabolomics by acquiring spectra of fragmented ions. These fragmentation spectra can be represented as a molecular network, by measuring cosine distances between them, thus identifying signals from the same or similar molecules. Metrics that enable comparison between pairs of samples based on their metabolite profiles are in great need. Taking inspiration from the successful phylogeny-aware beta-diversity measures used in microbiome research, integrating chemical similarity information about the features in addition to their abundances could lead to better insights when comparing metabolite profiles. Chemical Structural and Compositional Similarity (CSCS) is a recently published similarity metric comparing the full set of signals and their chemical similarity between two samples. Efficient, scalable and easily accessible implementations of this algorithm is currently lacking. Here, we present an easily accessible and scalable implementation of CSCS in both python and R, including a version not weighted by intensity information. ResultsWe provide a new implementation of the CSCS algorithm that is over 300 times faster than the published implementation in R, making the algorithm suitable for large-scale metabolomics applications. We also show that adding chemical information enriches existing methods. Furthermore, the R implementation includes functions for exporting molecular networks directly from the mass spectral molecular networking platform GNPS for ease of use for downstream applications. Contactbrejnrod@sund.ku.dk Availabilitygithub.com/askerdb/rCSCS, github.com/askerdb/pyCSCS

bioinformatics↗

bioRxiv2018

Adaptation of Bacillus subtilis upon interaction with Setophoma terrestris results in loss of surfactin and plipastatin production

Environmental species of bacteria and fungi coexist and interact showing antagonistic and mutualistic behaviors, mediated by exchange of small diffusible metabolites, driving microbial adaptation to complex communal lifestyles1. Here we show that a wild Bacilus subtilis strain undergoes heritable phenotypic variation following interaction with the soil fungal pathogen Setophoma terrestris (ST) in co-culture. Metabolomics analysis revealed a differential profile in B. subtilis before (pre-ST) and after (post-ST) interacting with the fungus, which paradoxically involved the absence of lipopeptides surfactin and plipastatin and yet acquired antifungal activity in post-ST variants. Metabolic changes were also observed in the profile of volatile compounds, with 2-heptanone and 2-octanone being the most discriminating metabolites present at higher concentrations in post-ST during its interaction with the fungus. Most strikingly, both ketones showed strong antifungal activity against S. terrestris, which was lost with the addition of exogenous surfactin to the medium. Whole-genome analyses showed that mutations in the comA and comP genes of the ComQPXA quorum-sensing system, constituted the genetic bases of post-ST conversion, which allowed the concomitant production of ketones and elimination of surfactin. These findings suggest that mutations in ComQXPA stably rewired B. subtilis metabolism towards the depletion of surfactins and the production of antifungal compounds during its antagonistic interaction with S. terrestris.

microbiology↗