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Gut bacterial communities of diarrheic patients with indications of Clostridioides difficile infection.

ABSTRACT: We present bacterial 16S rRNA gene datasets derived from stool samples of 44 patients with diarrhea indicative of a Clostridioides difficile infection. For 20 of these patients, C. difficile infection was confirmed by clinical evidence. Stool samples from patients originating from Germany, Ghana, and Indonesia were taken and subjected to DNA isolation. DNA isolations of stool samples from 35 asymptomatic control individuals were performed. The bacterial community structure was assessed by 16S rRNA gene analysis (V3-V4 region). Metadata from patients and control individuals include gender, age, country, presence of diarrhea, concomitant diseases, and results of microbiological tests to diagnose C. difficile presence. We provide initial data analysis and a dataset overview. After processing of paired-end sequencing data, reads were merged, quality-filtered, primer sequences removed, reads truncated to 400?bp and dereplicated. Singletons were removed and sequences were sorted by cluster size, clustered at 97% sequence similarity and chimeric sequences were discarded. Taxonomy to each operational taxonomic unit was assigned by BLASTn searches against Silva database 123.1 and a table was constructed.

SUBMITTER: Schneider D

PROVIDER: S-EPMC5644368 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Gut bacterial communities of diarrheic patients with indications of Clostridioides difficile infection.

Schneider Dominik D Thürmer Andrea A Gollnow Kathleen K Lugert Raimond R Gunka Katrin K Groß Uwe U Daniel Rolf R

Scientific data 20171017

We present bacterial 16S rRNA gene datasets derived from stool samples of 44 patients with diarrhea indicative of a Clostridioides difficile infection. For 20 of these patients, C. difficile infection was confirmed by clinical evidence. Stool samples from patients originating from Germany, Ghana, and Indonesia were taken and subjected to DNA isolation. DNA isolations of stool samples from 35 asymptomatic control individuals were performed. The bacterial community structure was assessed by 16S rR ...[more]

PMID: 29039846

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Project description:Clostridioides difficile infection (CDI) is associated with high mortality rates among patients with chronic illnesses. We aimed to identify avoidable risk factors to reduce the mortality rate in CDI patients. A total of 306 patients with diarrhea and clinical suspicion of CDI were enrolled, and fecal samples were gathered from 145 patients. CDI was diagnosed by fecal positivity for the C. difficile tcdB gene. Risk factors associated with death within 180 days were identified using Cox regression analysis. The fecal microbiota was determined through bacterial 16S rRNA gene sequencing. Of the patients with diarrhea, 240 (mean age, 69.1 years) were positive for CDI, and 91 died within 180 days. Multivariate analysis revealed that male sex, high Charlson Comorbidity Index and McCabe scores, high serum C-reactive protein levels, low hematocrit levels, low absolute eosinophil counts, high neutrophil/lymphocyte ratios, and daily use of proton pump inhibitors (PPIs) were independent risk factors for overall mortality. Cumulative analyses confirmed the association of duration-dependent PPI use with a high mortality rate. Fecal microbiota analyses showed associations of decreased relative abundance of Ruminococcus gnavus (P = 0.001) and Prevotella copri (P = 0.025) and increased relative abundance of Parabacteroides merdae (P = 0.001) and Clostridioides difficile (P = 0.040) with higher mortality rates in patients with CDI. Moreover, these microbiota changes were correlated with the duration of PPI use. IMPORTANCE This article demonstrates that daily PPI use was the only avoidable risk factor for death. With more extended PPI use, the mortality rate was higher in patients with CDI. Decreases in Prevotella copri and Ruminococcus gnavus and increases in Parabacteroides merdae and Clostridioides difficile in line with daily PPI use duration were significantly associated with the death of CDI patients. Our findings provide in-depth insights into the cautious use of PPIs in chronically ill patients with CDI.

Project description:BackgroundClostridioides difficile infection (CDI) is the most common hospital acquired infection in the USA, with recurrence rates > 15%. Although primary CDI has been extensively linked to gut microbial dysbiosis, less is known about the factors that promote or mitigate recurrence. Moreover, previous studies have not shown that microbial abundances in the gut measured by 16S rRNA amplicon sequencing alone can accurately predict CDI recurrence.ResultsWe conducted a prospective, longitudinal study of 53 non-immunocompromised participants with primary CDI. Stool sample collection began pre-CDI antibiotic treatment at the time of diagnosis, and continued up to 8 weeks post-antibiotic treatment, with weekly or twice weekly collections. Samples were analyzed using (1) 16S rRNA amplicon sequencing, (2) liquid chromatography/mass-spectrometry metabolomics measuring 1387 annotated metabolites, and (3) short-chain fatty acid profiling. The amplicon sequencing data showed significantly delayed recovery of microbial diversity in recurrent participants, and depletion of key anaerobic taxa at multiple time-points, including Clostridium cluster XIVa and IV taxa. The metabolomic data also showed delayed recovery in recurrent participants, and moreover mapped to pathways suggesting distinct functional abnormalities in the microbiome or host, such as decreased microbial deconjugation activity, lowered levels of endocannabinoids, and elevated markers of host cell damage. Further, using predictive statistical/machine learning models, we demonstrated that the metabolomic data, but not the other data sources, can accurately predict future recurrence at 1 week (AUC 0.77 [0.71, 0.86; 95% interval]) and 2 weeks (AUC 0.77 [0.69, 0.85; 95% interval]) post-treatment for primary CDI.ConclusionsThe prospective, longitudinal, and multi-omic nature of our CDI recurrence study allowed us to uncover previously unrecognized dynamics in the microbiome and host presaging recurrence, and, in particular, to elucidate changes in the understudied gut metabolome. Moreover, we demonstrated that a small set of metabolites can accurately predict future recurrence. Our findings have implications for development of diagnostic tests and treatments that could ultimately short-circuit the cycle of CDI recurrence, by providing candidate metabolic biomarkers for diagnostics development, as well as offering insights into the complex microbial and metabolic alterations that are protective or permissive for recurrence. Video Abstract.

Project description:The gastrointestinal microbiome plays an important role in limiting susceptibility to infection with Clostridioides difficile To better understand the ecology of bacteria important for C. difficile colonization resistance, we developed an experimental platform to simplify complex communities of fecal bacteria through dilution and rapidly screen for their ability to resist C. difficile colonization after challenge, as measured by >100-fold reduction in levels of C. difficile in challenged communities. We screened 76 simplified communities diluted from cultures of six fecal donors and identified 24 simplified communities that inhibited C. difficile colonization in vitro Sequencing revealed that simplified communities were composed of 19 to 67 operational taxonomic units (OTUs) and could be partitioned into four distinct community types. One simplified community could be further simplified from 56 to 28 OTUs through dilution and retain the ability to inhibit C. difficile We tested the efficacy of seven simplified communities in a humanized microbiota mouse model. We found that four communities were able to significantly reduce the severity of the initial C. difficile infection and limit susceptibility to disease relapse. Analysis of fecal microbiomes from treated mice demonstrated that simplified communities accelerated recovery of indigenous bacteria and led to stable engraftment of 19 to 22 OTUs from simplified communities. Overall, the insights gained through the identification and characterization of these simplified communities increase our understanding of the microbial dynamics of C. difficile infection and recovery.IMPORTANCE Clostridioides difficile is the leading cause of antibiotic-associated diarrhea and a significant health care burden. Fecal microbiota transplantation is highly effective at treating recurrent C. difficile disease; however, uncertainties about the undefined composition of fecal material and potential long-term unintended health consequences remain. These concerns have motivated studies to identify new communities of microbes with a simpler composition that will be effective at treating disease. This work describes a platform for rapidly identifying and screening new simplified communities for efficacy in treating C. difficile infection. Four new simplified communities of microbes with potential for development of new therapies to treat C. difficile disease are identified. While this platform was developed and validated to model infection with C. difficile, the underlying principles described in the paper could be easily modified to develop therapeutics to treat other gastrointestinal diseases.

Dataset Information

Gut bacterial communities of diarrheic patients with indications of Clostridioides difficile infection.

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Gut bacterial communities of diarrheic patients with indications of Clostridioides difficile infection.

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