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      • Record: found
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      Is Open Access

      Gut microbiota signatures in cystic fibrosis: Loss of host CFTR function drives the microbiota enterophenotype

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          Abstract

          Background

          Cystic fibrosis (CF) is a disorder affecting the respiratory, digestive, reproductive systems and sweat glands. This lethal hereditary disease has known or suspected links to the dysbiosis gut microbiota. High-throughput meta-omics-based approaches may assist in unveiling this complex network of symbiosis modifications.

          Objectives

          The aim of this study was to provide a predictive and functional model of the gut microbiota enterophenotype of pediatric patients affected by CF under clinical stability.

          Methods

          Thirty-one fecal samples were collected from CF patients and healthy children (HC) (age range, 1–6 years) and analysed using targeted-metagenomics and metabolomics to characterize the ecology and metabolism of CF-linked gut microbiota. The multidimensional data were low fused and processed by chemometric classification analysis.

          Results

          The fused metagenomics and metabolomics based gut microbiota profile was characterized by a high abundance of Propionibacterium, Staphylococcus and Clostridiaceae, including Clostridium difficile, and a low abundance of Eggerthella, Eubacterium, Ruminococcus, Dorea, Faecalibacterium prausnitzii, and Lachnospiraceae, associated with overexpression of 4-aminobutyrate (GABA), choline, ethanol, propylbutyrate, and pyridine and low levels of sarcosine, 4-methylphenol, uracil, glucose, acetate, phenol, benzaldehyde, and methylacetate. The CF gut microbiota pattern revealed an enterophenotype intrinsically linked to disease, regardless of age, and with dysbiosis uninduced by reduced pancreatic function and only partially related to oral antibiotic administration or lung colonization/infection.

          Conclusions

          All together, the results obtained suggest that the gut microbiota enterophenotypes of CF, together with endogenous and bacterial CF biomarkers, are direct expression of functional alterations at the intestinal level. Hence, it’s possible to infer that CFTR impairment causes the gut ecosystem imbalance.This new understanding of CF host-gut microbiota interactions may be helpful to rationalize novel clinical interventions to improve the affected children’s nutritional status and intestinal function.

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          Most cited references 50

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          QIIME allows analysis of high-throughput community sequencing data.

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            Search and clustering orders of magnitude faster than BLAST.

             Robert Edgar (2010)
            Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
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              Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

              The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Methodology
                Role: Investigation
                Role: Investigation
                Role: InvestigationRole: Methodology
                Role: Investigation
                Role: Formal analysisRole: Methodology
                Role: Formal analysisRole: Methodology
                Role: Investigation
                Role: Investigation
                Role: Data curation
                Role: Investigation
                Role: Data curationRole: Validation
                Role: Investigation
                Role: Writing – review & editing
                Role: Investigation
                Role: Data curationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 December 2018
                2018
                : 13
                : 12
                Affiliations
                [1 ] Unit of Human Microbiome, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
                [2 ] Cystic Fibrosis Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
                [3 ] Diagnostics of Cystic Fibrosis, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
                [4 ] Department of Chemistry, Sapienza University of Rome, Rome, Italy
                [5 ] Department of Agricultural Sciences, Division of Microbiology, University of Naples Federico II, Portici, Napoli, Italy
                [6 ] Division of Metabolism, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
                [7 ] Department of Environmental Biology; Sapienza University of Rome, Rome, Italy
                [8 ] CNR-Institute for Systems Analysis and Computer Science (IASI), Rome, Italy
                [9 ] Scientific Directorate, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
                [10 ] Unit of Parasitology Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
                Institut Pasteur, FRANCE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                ‡ These authors are joint senior authors on this work.

                Article
                PONE-D-17-43072
                10.1371/journal.pone.0208171
                6283533
                30521551
                © 2018 Vernocchi et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Counts
                Figures: 4, Tables: 1, Pages: 23
                Product
                Funding
                Funded by: Ministry of Health, Ricerca Corrente
                Award ID: 201502P003534/201602P003702
                Award Recipient :
                This work was supported by the Ministry of Health, Ricerca Corrente 201502P003534 and 201602P003702 assigned to LP.
                Categories
                Research Article
                Medicine and Health Sciences
                Pharmacology
                Drugs
                Antimicrobials
                Antibiotics
                Biology and Life Sciences
                Microbiology
                Microbial Control
                Antimicrobials
                Antibiotics
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Medicine and Health Sciences
                Clinical Genetics
                Genetic Diseases
                Autosomal Recessive Diseases
                Cystic Fibrosis
                Biology and Life Sciences
                Developmental Biology
                Fibrosis
                Cystic Fibrosis
                Medicine and Health Sciences
                Pulmonology
                Cystic Fibrosis
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbiome
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Clostridium Difficile
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Bacterial Pathogens
                Clostridium
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Bacterial Pathogens
                Clostridium
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Clostridium
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Ruminococcus
                Biology and Life Sciences
                Organisms
                Bacteria
                Gut Bacteria
                Eubacterium
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. The 16S rRNA sequences were deposited in the sequence-read archive (SRA) of NCBI ( https://www.ncbi.nlm.nih.gov/).

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