Biology subjects

Willems, R. J. L.

Publications and source records attributed to Willems, R. J. L..

6 recordsLinked to original sources

bioRxiv2018

Bariatric surgery changes gut microbiota composition independent of operation type

BackgroundBariatric surgery in patients with morbid obesity, either through gastric sleeve gastrectomy or Roux-Y gastric bypass surgery, leads to sustainable weight loss, improvement of metabolic disorders and changes in the intestinal microbiota. Yet, the relationship between changes in gut microbiota, weight loss and the surgical procedure remains incompletely understood.\n\nSubjects/MethodsWe determined temporal changes in microbiota composition in 45 obese patients undergoing a crash diet followed by gastric sleeve gastrectomy (n= 22) or Roux-Y gastric bypass (n= 23). Intestinal microbiota composition was determined before intervention (baseline, S1), 2 weeks after a crash diet (S2), and 1 week (S3), 3 months (S4) and 6 months (S5) after surgery.\n\nResultsRelative to S1, the microbial diversity index declined at S2 and S3 (p< 0.05), and gradually returned to baseline levels at S5. The crash diet was associated with an increased abundance of Rikenellaceae and decreased abundances of Ruminococcaceae and Streptococcaceae (p< 0.05). After surgery, at S3, the relative abundance of Bifidobacteriaceae had decreased (compared to the moment directly after the crash diet), whereas those of Streptococcaceae and Enterobacteriaceae had increased (p< 0.05). Increased weight loss during the next 6 months was not associated without major changes in microbiota composition. Significant differences between both surgical procedures were not observed at any of the time points.\n\nConclusionsIn conclusion, undergoing a crash diet and bariatric surgery were associated with an immediate but temporary decline in the microbial diversity, with immediate and permanent changes in microbiota composition, with no differences between patients undergoing gastric sleeve gastrectomy or Roux-Y gastric bypass surgery.

microbiology↗

bioRxiv2018

mlplasmids: a user-friendly tool to predict plasmid- and chromosome-derived sequences for single species

Assembly of bacterial short-read whole genome sequencing (WGS) data frequently results in hundreds of contigs for which the origin, plasmid or chromosome, is unclear. Long-read sequencing has emerged as a solution to resolve plasmid structures and to obtain complete genomes for most bacterial species. This information can be used to generate and label datasets from short-read based contigs as plasmid- or chromosome-derived. We investigated the use of several popular machine learning methods to classify short-read contigs with known plasmid- or chromosome-origin from Enterococcus faecium, Klebsiella pneumoniae and Escherichia coli using pentamer frequencies. Based on resulting F1-scores we selected support-vector machine (SVM) models as best classifier for all three bacterial species (F1-score E. faecium = 0.94, F1-score K. pneumoniae = 0.90, F1-score E. coli = 0.76), which outperformed other existing plasmid tools using an independent set of isolates (precision E. faecium = 0.92, precision K. pneumoniae = 0.86, precision E. coli = 0.82). We demonstrated the scalability of our model by accurately predicting the plasmidome of a large collection of 1,644 E. faecium isolates with only short-read WGS available using a standard laptop with a single core. A low number of false positive predicted sequences suggests that the assignment of a particular gene of interest as plasmid- or chromosome-encoded by the models is plausible. The SVM classifiers are publicly available as a new R package called mlplasmids at https://gitlab.com/sirarredondo/mlplasmids under the GNU General Public License v3.0. We additionally developed a graphical-user interface using the Shiny package which can be accessed at https://sarredondo.shinyapps.io/mlplasmids/. Single genomes can easily be predicted by uploading genome assemblies. We anticipate that this tool may significantly facilitate research on the dissemination of plasmids encoding antibiotic resistance and/or contributing to host adaptation.

microbiology↗

bioRxiv2017

The microbiome and resistome of hospital sewage during passage through the community sewer system

Effluents from wastewater treatment plants (WWTPs) have been proposed to act as point sources of antibiotic-resistant bacteria (ARB) and antimicrobial resistance genes (ARGs) in the environment. Hospital sewage may contribute to the spread of ARB and ARGs as it contains the feces and urine of hospitalized patients, who are more frequently colonized with multi-drug resistant bacteria than the general population. However, whether hospital sewage noticeably contributes to the quantity and diversity of ARGs in the general sewerage system has not yet been determined.\n\nHere, we employed culture-independent techniques, namely 16S rRNA and nanolitre-scale quantitative PCRs, to describe the role of hospital effluent as a point source of ARGs in the sewer system, through comparing microbiota composition and levels of ARGs in hospital sewage with WWTP influent, WWTP effluent and the surface water in which the effluent is released.\n\nCompared to other sample sites, hospital sewage was richest in human-associated bacteria and contained the highest relative levels of ARGs. Yet, the abundance of ARGs was comparable in WWTPs with and without hospital wastewater, suggesting that hospitals do not contribute to the spread of ARGs in countries with a functioning sewerage system.

microbiology↗

bioRxiv2017

Prediction of the intestinal resistome by a novel 3D-based method

The intestinal microbiota is considered to be a major reservoir of antibiotic resistance determinants (ARDs) that could potentially be transferred to bacterial pathogens. Yet, this question remains hypothetical because of the difficulty to identify ARDs from intestinal bacteria. Here, we developed and validated a new annotation method (called pairwise comparative modelling, PCM) based on homology modelling in order to characterize the Human resistome. We were able to predict 6,095 ARDs in a 3.9 million protein catalogue from the Human intestinal microbiota. We found that predicted ARDs (pdARDs) were distantly related to known ARDs (mean amino-acid identity 29.8%). Among 3,651 pdARDs that were identified in metagenomic species, 3,489 (95.6%) were assumed to be located on the bacterial chromosome. Furthermore, genes associated with mobility were found in the neighbourhood of only 7.9% (482/6,095) of pdARDs. According to the composition of their resistome, we were able to cluster subjects from the MetaHIT cohort (n=663) into 6 \"resistotypes\". Eventually, we found that the relative abundance of pdARDs was positively associated with gene richness, but not when subjects were exposed to antibiotics. Altogether, our results support that most ARDs in the intestinal microbiota should be considered as intrinsic genes of commensal microbiota with a low risk of transfer to bacterial pathogens.

microbiology↗

bioRxiv2017

Gut microbiota and resistome dynamics in intensive care patients receiving selective digestive tract decontamination

BackgroundCritically ill patients hospitalized in an Intensive Care Unit (ICU) are at increased risk of acquiring potentially life-threatening infections with opportunistic pathogens. The gut microbiota of ICU patients forms an important reservoir for these infectious agents. To suppress gut colonization with opportunistic pathogens, a prophylactic antibiotic regimen, termed Selective decontamination of the digestive tract (SDD), may be used. SDD has previously been shown to improve clinical outcome in ICU patients, but the impact of ICU hospitalization and SDD on the gut microbiota remains largely unknown. Here, we characterize the composition of the gut microbiota and its antimicrobial resistance genes ( the resistome) of ICU patients during SDD.\n\nResultsDuring ICU-stay, 30 fecal samples of ten patients were collected. Additionally, feces were collected from five of these patients after transfer to a medium-care ward and cessation of SDD. As a control group, feces from ten healthy subjects were collected twice, with a one-year interval. Gut microbiota and resistome composition were determined using 16S rRNA phylogenetic profiling and nanolitre-scale quantitative PCRs.\n\nThe microbiota of the ICU patients differed from the microbiota of healthy subjects and was characterized by low microbial diversity, decreased levels of E. coli and of anaerobic Gram-positive, butyrate-producing bacteria of the Clostridium clusters IV and XIVa, and an increased abundance of Bacteroidetes and enterococci. Four resistance genes (aac(6')-Ii, ermC, qacA, tetQ), providing resistance to aminoglycosides, macrolides, disinfectants and tetracyclines respectively, were significantly more abundant among ICU patients than in healthy subjects, while a chloramphenicol resistance gene (catA) and a tetracycline resistance gene (tetW) were more abundant in healthy subjects.\n\nConclusionsThe microbiota and resistome of ICU patients and healthy subjects were noticeably different, but importantly, levels of E. coli remained low during ICU hospitalization, presumably due to SDD therapy. Selection for four antibiotic resistance genes was observed, but none of these are of particular concern as they do not contribute to clinically relevant resistance. Our data support the ecological safety of SDD, at least in settings with low levels of circulating antibiotic resistance.

microbiology↗

bioRxiv2017

Fitness determinants of vancomycin-resistant Enterococcus faecium during growth in human serum

Enterococcus faecium is a commensal of the human gastrointestinal tract and a frequent cause of bloodstream infections in hospitalized patients. Here, we identify genes that contribute to growth of E. faecium in human serum. We first sequenced the genome of E. faecium E745, a vancomycin-resistant clinical isolate, to completion and then compared its transcriptome during exponential growth in rich medium and in human serum by RNA-seq. This analysis revealed that 27.8% of genes on the E. faecium E745 genome were differentially expressed in these two conditions. A gene cluster with a role in purine biosynthesis was among the most upregulated genes in E. faecium E745 upon growth in serum. A high-throughput transposon sequencing (Tn-seq) approach was used to identify conditionally essential genes in E. faecium E745 during growth in serum. Genes involved in de novo nucleotide biosysnthesis (including pyrK_2, pyrF, purD, purH) and a gene encoding a phosphotransferase system subunit (manY_2) were thus identified to be contributing to E. faecium growth in human serum. Transposon mutants in pyrK_2, pyrF, purD, purH and manY_2 were isolated from the library and their impaired growth in human serum was confirmed. In addition, the pyrK_2 and manY_2 mutants also exhibited significantly attenuated virulence in an intravenous zebrafish infection model. We conclude that genes involved in carbohydrate and nucleotide metabolism of E. faecium are essential for growth in human serum and contribute to the pathogenesis of this organism.

microbiology↗