Biology subjects

Ducarmon, Q. R.

Publications and source records attributed to Ducarmon, Q. R..

11 recordsLinked to original sources

bioRxiv2024

Metagenomic global survey and in-depth genomic analyses of Ruminococcus gnavus reveal differences across host lifestyle and health status

Ruminococcus gnavus is a highly prevalent gut bacterium (present in >90% of healthy individuals), of which increased abundance is associated with chronic inflammatory diseases, most notably Crohns disease. Nevertheless, its global distribution has not been investigated and little is known about intraspecies genomic variation. Through a large-scale survey of 12,791 gut metagenomes, we recapitulated known associations with metabolic diseases and inflammatory bowel disease. We uncover a higher prevalence and abundance of R. gnavus in Westernized populations and observe relative abundances of up to 83% in newborns and infants. Next, we built a collection of existing and newly cultured R. gnavus isolates (N = 45) from both healthy individuals and Crohns disease patients and subjected these to PacBio circular consensus sequencing to greatly expand the number of complete R. gnavus genomes. Analysis of these genomes as well as publicly available high quality draft genomes (total > 300 genomes) revealed multiple clades which separated Crohns-derived isolates from healthy-derived isolates. Functional analyses of genes predicted to constitute R. gnavus virulence factors could not explain this separation. Bacterial GWAS revealed that Crohns-derived isolates were enriched in genes related to mobile elements and putative mucin foraging. Together, we present one of the largest complete genome collections of any commensal gut microbe and provide novel biological insights into the global distribution and genomic variation of R. gnavus.

microbiology↗

bioRxiv2024

Long-term fasting remodels gut microbial metabolism and host metabolism

Long-term fasting has become a promising research subject for its potential of treating and preventing metabolic diseases. However, little is known about its impact on the functional capacity of the gut microbiome and the combined effect on the serum metabolome. Here, we demonstrate extensive remodelling of the gut microbial ecosystem in humans (n=92) after an average of 9.8 days of fasting ([~]250 kcal / day). Fasting transiently affected the relative abundance of the majority of bacterial species (306 decreased and 210 increased out of 772). Species changes could largely be explained by their genomic repertoire of carbohydrate-active enzymes (CAZymes), which were investigated here for the first time. Fasting induced extensive abundance changes in CAZyme families, depleting families with dietary fibre substrates and increasing families with host-derived glycan substrates. Likewise, we observed extensive changes in the serum metabolome, with 382 out of 721 metabolites significantly affected (246 increased and 136 decreased). In-depth metagenome-metabolome co-variation analysis suggested Oscillibacter species to be key producers of indole-3-propionic acid, a crucial metabolite for cardiometabolic health. Together, our results provide an unprecedented view on the impact of long-term fasting on gut microbiome composition and function.

microbiology↗

bioRxiv2024

Large-scale computational analyses of gut microbial CAZyme repertoires enabled by Cayman

Carbohydrate-active enzymes (CAZymes) are crucial for digesting glycans, but bioinformatics tools for CAZyme profiling and interpretation of substrate preferences in microbial community data are lacking. To address this, we developed a CAZyme profiler (Cayman) and a hierarchical substrate annotation scheme. Leveraging these, we genomically survey CAZymes in human gut microbes (n=107,683 genomes), which suggests novel mucin-foraging species. In a subsequent meta-analysis of CAZyme repertoires in Western versus non-Western gut metagenomes (n=4,281) we find that non-Western metagenomes are richer in fibre-degrading CAZymes despite lower overall CAZyme richness. We additionally pinpoint the taxonomic drivers underlying these CAZyme community shifts. A second meta-analysis comparing colorectal cancer patients (CRC) to controls (n=1,998) shows that CRC metagenomes are deprived of dietary fibre-targeting, but enriched in glycosaminoglycan-targeting CAZymes. A genomic analysis of co-localizing CAZyme domains predicts novel substrates for CRC-enriched CAZymes. Cayman is broadly applicable across microbial communities and freely available from https://github.com/zellerlab/cayman.

microbiology↗

bioRxiv2023

Machine learning-based meta-analysis reveals gut microbiome alterations associated with Parkinson's disease

There is strong interest in exploring the potential of the gut microbiome for Parkinsons disease (PD) diagnosis and treatment. However, a consensus on the microbiome features associated with PD and a multi-study assessment of their diagnostic value is lacking. Here, we present a machine learning meta-analysis of PD microbiome studies of unprecedented scale (including 4,490 samples). Within most studies, microbiome-based machine learning models could accurately classify PD patients. However, models were study-specific and did not generalise well across other studies. By training models on multiple datasets, we could improve their general applicability and disease specificity as assessed against microbiomes from other neurodegenerative diseases. Meta-analysis of shotgun metagenomes moreover delineated PD-associated microbial pathways potentially contributing to the deterioration of gut health and favouring the translocation of pathogenic molecules along the gut-brain axis. Strikingly, diverse microbial pathways for the biotransformation of solvents and pesticides were enriched in PD. These results align with the epidemiological evidence that exposure to these molecules increases PD risk and raise the question of whether gut microbial metabolism modulates their toxicity. Taken together, we offer the most comprehensive overview to date about the PD gut microbiome and provide future reference for its diagnostic and functional potential.

microbiology↗

bioRxiv2022

Clostridioides difficile PCR ribotype 151 is polyphyletic and includes pathogenic isolates from cryptic clade C-II with mono-toxin pathogenicity loci that can escape routine diagnostics

We report a patient case with pseudomembranous colitis associated with a mono-toxin producing Clostridioides difficile belonging to the very rarely diagnosed PCR ribotype (RT) 151. The infection was difficult to diagnose, since the isolate and the feces sample tested negative for toxin-encoding genes using a routine commercial test. This prompted us to sequence n = 11 RT151s from various geographical regions to study their genomic characteristics and relatedness. By including whole genome sequence data from other sources, we could further place these isolates into the phylogenetic tree of C. difficile and assign them to their respective clades. These analyses revealed that 1) RT151s are polyphyletic with isolates falling into clades 1, and cryptic clades C-I and C-II 2) RT151 contains both non-toxigenic and toxigenic isolates and 3) RT151 C-II isolates contained mono-toxin pathogenicity loci (PaLoc). Additional analysis with PacBio circular consensus sequencing revealed that the isolate from our patient case report contains a novel PaLoc insertion site, lacked tcdA and a had significantly divergent tcdB sequence that might explain the failure of the diagnostic test. The study is noteworthy as 1) RT151 encompasses both typical and cryptic clades and 2) conclusive evidence for CDI due to clade C-II isolates was hitherto lacking.

microbiology↗

bioRxiv2022

Carriage of three plasmids in a single human clinical isolate of Clostridioides difficile

A subset of clinical isolates of Clostridioides difficile contains one or more plasmids and these plasmids can harbor virulence and antimicrobial resistance determinants. Despite their potential importance, C. difficile plasmids remain poorly characterized. Here, we describe a human clinical isolate that carries three plasmids from three different plasmid families that are therefore compatible. For two of these, we identify a region capable of sustaining plasmid replication in C. difficile. Together, our data advance our understanding of C. difficile plasmid biology. HighlightsThe complete circular genome sequence is provided for a C. difficile isolate harboring three plasmids These three plasmids (pJMR5-1, pJMR5-4 and pJRM5-W) are therefore compatible in a single strain Sequence analysis suggest a modular nature of plasmid families to which the pJMR-plasmids belong A functional replicon was cloned from pJMR5-1 (pCD-ECE1 family) and pJMR5-W (pCD-WTSI1 family) and plasmids carrying this replicon are compatible with plasmid pCD630

microbiology↗

bioRxiv2021

Impacts of dietary exposure to pesticides on faecal microbiome metabolism in adult twins

Concerns have been raised as to whether the consumption of foodstuffs contaminated with pesticides can contribute to the development of chronic human diseases by affecting microbial community function in the gut. We provide the first associations between urinary pesticide excretion and the composition and function of the faecal microbiome in 65 twin pairs in the UK. Biomonitoring of exposure to 186 common insecticide, herbicide, or fungicide residues showed the presence of pyrethroid and/or organophosphorus insecticide residues in all urine samples, while the herbicide glyphosate was found in 45% of individuals. Other pesticides such as DEET, imidacloprid or dithiocarbamate fungicides were less frequently detected. While the geographic location or the rural/urban environment had no influence on pesticide urinary excretion, food frequency questionnaires showed that DMTP levels, a metabolite of organophosphates, was higher with increased consumption of fruit and vegetables. Multivariable association between urinary pesticide excretion and faecal microbial composition and function were determined with shotgun metagenomics and metabolomics. A total of 34 associations between pesticide residues concentrations and faecal metabolite concentrations were detected. Glyphosate excretion was positively associated to an increased bacterial species richness, as well as to fatty acid metabolites and phosphate levels. The insecticide metabolite Br2CA, reflecting deltamethrin exposure, was positively associated with the mammalian phytoestrogens enterodiol and enterolactone, and negatively associated with some N-methyl amino acids. Urine metabolomics performed on a subset of samples did not reveal associations with the excretion of pesticide residues. Our results highlight the need for future interventional studies to understand effects of pesticide exposure on the gut microbiome and possible health consequences.

pharmacology and toxicology↗

bioRxiv2021

Asymptomatic gut colonization by extended-spectrum beta-lactamase-producing Escherichia coli is not associated with an altered gut microbiome or metabolome in Dutch adults

BackgroundGut colonization by antibiotic resistant E. coli strains, including extended-spectrum beta-lactamase (ESBL)-producing E. coli is a risk factor for developing overt infection. The gut microbiome can provide colonization resistance against enteropathogens, but it remains unclear whether it confers resistance against potentially pathogenic ESBL-producing E. coli. MaterialsFrom a Dutch cross-sectional population study (PIENTER-3), feces from 2751 individuals were used to culture ESBL-producing bacteria. Of these, we selected 49 samples which were positive for an ESBL-producing Escherichia coli (ESBL+), and negative for a variety of variables known to affect microbiome composition. These were matched in a 1:1 ratio to ESBL- samples based on age, sex, having been abroad in the past six months and ethnicity. Shotgun metagenomic sequencing was performed and taxonomic species composition and functional annotations (microbial metabolism and carbohydrate-active enzymes) were determined. Targeted quantitative metabolic profiling (1H NMR-spectroscopy) was performed to investigate metabolomic profiles. ResultsNo differences in alpha or beta diversity were observed, nor in relative abundance, between ESBL+ and ESBL- individuals based on bacterial species level composition. Machine learning approaches based on microbiota composition did not accurately predict ESBL status (area under the receiver operating characteristic curve (AUROC)=0.53), neither when based on functional profiles. The metabolome did also not convincingly differ between ESBL groups as assessed by a variety of approaches, including machine learning through random forest (AUROC=0.61). ConclusionUsing a combination of multi-omics and machine learning approaches, we conclude that asymptomatic gut carriage of ESBL-producing E. coli is not associated with an altered microbiome composition or function. This may suggest that microbiome-mediated colonization resistance against ESBL-producing E. coli is not as relevant as it is against other enteropathogens.

microbiology↗

bioRxiv2020

Multi-omics phenotyping of the gut-liver axis allows health risk predictability from in vivo subchronic toxicity tests of a low-dose pesticide mixture

Human health effects from chronic exposure to mixtures of pesticide residues are little investigated. We compared standard histopathology and serum biochemistry measures and multi-omics analyses in an in vivo subchronic toxicity test of a mixture of six pesticide active ingredients frequently detected in foodstuffs (azoxystrobin, boscalid, chlorpyrifos, glyphosate, imidacloprid and thiabendazole). Sprague-Dawley rats were administered with the pesticide mixture with each ingredient at its regulatory permitted acceptable daily intake. Analysis of water and feed consumption, body weight, histopathology and serum biochemistry showed little or no physiological effects from exposure to the pesticide mixture. In marked contrast, analysis of the host-gut microbiome axis using serum and caecum metabolomics revealed that nicotinamide and tryptophan metabolism were affected, which suggested the initiation of a cell danger response, including adaptation to oxidative stress. Only limited effects were detected on the caecum microbiota by shotgun metagenomics. Further analyses of in vitro bacterial cultures showed that growth of Lactobacillus rhamnosus and Escherichia coli strains was negatively impacted by the pesticide mixture at concentrations that were not inhibitory when exposure was to a single agent. Transcriptomics of the liver showed that 257 genes had their expression changed. Gene functions affected included those involved in the regulation of response to hormones and correlated with previously reported transcriptome changes following administration of nicotinamide. Genome-wide DNA methylation analysis of the same liver samples showed that 4255 CpG sites were differentially methylated (> 10% difference). Overall, we demonstrated that unlike standard blood biochemical and organ histological analysis, in-depth molecular profiling using a combination of high-throughput -omics methods in laboratory animals exposed to low concentrations of pesticides reveals metabolic effects on the gut-liver axis, which can potentially be used as biomarkers for the prediction of future negative health outcomes. Our data suggest that adoption of multi-omics as part of regulatory risk assessment procedures will result in more accurate outcome measures, with positive public health implications.

pharmacology and toxicology↗

bioRxiv2019

Shotgun metagenomics and metabolomics reveal glyphosate alters the gut microbiome of Sprague-Dawley rats by inhibiting the shikimate pathway

There is intense debate as to whether glyphosate can interfere with aromatic amino acid biosynthesis in microorganisms inhabiting the gastrointestinal tract, which could potentially lead to negative health outcomes. We have addressed this major gap in glyphosate toxicology by using a multi-omics strategy combining shotgun metagenomics and metabolomics. We tested whether glyphosate (0.5, 50, 175 mg/kg bw/day), or its representative EU commercial herbicide formulation MON 52276 at the same glyphosate equivalent doses, has an effect on the rat gut microbiome in a 90-day subchronic toxicity test. Clinical biochemistry measurements in blood and histopathological evaluations showed that MON 52276 but not glyphosate was associated with statistically significant increase in hepatic steatosis and necrosis. Similar lesions were also present in the liver of glyphosate-treated groups but not in the control group. Caecum metabolomics revealed that glyphosate inhibits the enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase in the shikimate pathway as evidenced by an accumulation of shikimic acid and 3-dehydroshikimic acid. Levels of caecal microbiome dipeptides involved in the regulation of redox balance ({gamma}-glutamylglutamine, cysteinylglycine, valylglycine) had their levels significantly increased. Shotgun metagenomics showed that glyphosate affected caecum microbial community structure and increased levels of Eggerthella spp. and Homeothermacea spp.. MON 52276, but not glyphosate, increased the relative abundance of Shinella zoogleoides. Since Shinella spp. are known to degrade alkaloids, its increased abundance may explain the decrease in solanidine levels measured with MON 52776 but not glyphosate. Other glyphosate formulations may have different effects since Roundup(R) GT Plus inhibited bacterial growth in vitro at concentrations at which MON 52276 did not present any visible effect. Our study highlights the power of a multiomics approach to investigate effects of pesticides on the gut microbiome. This revealed the first biomarker of glyphosate effects on rat gut microbiome. Although more studies will be needed to ascertain if there are health implications arising from glyphosate inhibition of the shikimate pathway in the gut microbiome, our findings can be used in environmental epidemiological studies to understand if glyphosate can have biological effects in human populations. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/870105v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@66578corg.highwire.dtl.DTLVardef@fddcd9org.highwire.dtl.DTLVardef@ae4ffforg.highwire.dtl.DTLVardef@5f7ed_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2019

Toward standards in clinical microbiome studies: comparison of three DNA extraction methods and two bioinformatic pipelines

When studying the microbiome using next generation sequencing, DNA extraction method, sequencing procedures and bioinformatic processing are crucial to obtain reliable data. Method choice has been demonstrated to strongly affect the final biological interpretation. We assessed the performance of three DNA extraction methods and two bioinformatic pipelines for bacterial microbiota profiling through 16S rRNA gene amplicon sequencing, using positive and negative controls for DNA extraction and sequencing, and eight different types of high- or low-biomass samples. Performance was evaluated based on quality control passing, DNA yield, richness, diversity and compositional profiles. All DNA extraction methods retrieved the theoretical relative bacterial abundance with maximum three-fold change, although differences were seen between methods, and library preparation and sequencing induced little variation. Bioinformatic pipelines showed different results for estimating richness, but diversity and compositional profiles were comparable. DNA extraction methods were successful for feces and oral swabs and variation induced by DNA extraction methods was lower than inter-subject (biological) variation. For low-biomass samples, a mixture of genera present in negative controls and sample-specific genera, possibly representing biological signal, were observed. We conclude that the tested bioinformatic pipelines perform equally with pipeline-specific advantages and disadvantages. Two out of three extraction methods performed equally well, while one method was less accurate regarding retrieval of compositional profiles. Lastly, we demonstrate the importance of including negative controls when analyzing low bacterial biomass samples.\n\nIMPORTANCEMethod choice throughout the workflow of a microbiome study, from sample collection to DNA extraction and sequencing procedures, can greatly affect results. This study evaluated three different DNA extraction methods and two bioinformatic pipelines by including positive and negative controls, and various biological specimens. By identifying an optimal combination of DNA extraction method and bioinformatic pipeline use, we hope to contribute to increased methodological consistency in microbiome studies. Our methods were not only applied to commonly studied samples for microbiota analysis, e.g. feces, but also for more rarely studied, low-biomass samples. Microbiota composition profiles of low-biomass samples (e.g. urine and tumor biopsies) were not always distinguishable from negative controls, or showed partial overlap, confirming the importance of including negative controls in microbiome studies, especially when low bacterial biomass is expected.

microbiology↗