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      Weight shapes the intestinal microbiome in preterm infants: results of a prospective observational study

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          Abstract

          Background

          The intestinal microbiome in preterm infants differs markedly from term infants. It is unclear whether the microbiome develops over time according to infant specific factors.

          Methods

          We analysed (clinical) metadata - to identify the main factors influencing the microbiome composition development - and the first meconium and faecal samples til the 4th week via 16 S rRNA amplican sequencing.

          Results

          We included 41 infants (gestational age 25–30 weeks; birth weight 430-990 g. Birth via Caesarean section (CS) was associated with placental insufficiency during pregnancy and lower BW. In meconium samples and in samples from weeks 2 and 3 the abundance of Escherichia and Bacteroides (maternal faecal representatives) were associated with vaginal delivery while Staphylococcus (skin microbiome representative) was associated with CS. Secondly, irrespective of the week of sampling or the mode of birth, a transition was observed as children children gradually increased in weight from a microbiome dominated by Staphylococcus (Bacilli) towards a microbiome dominated by Enterobacteriaceae (Gammaproteobacteria).

          Conclusions

          Our data show that the mode of delivery affects the meconium microbiome composition. They also suggest that the weight of the infant at the time of sampling is a better predictor for the stage of progression of the intestinal microbiome development/maturation than postconceptional age as it less confounded by various infant-specific factors.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12866-021-02279-y.

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          Most cited references 51

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          Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform.

          Rapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina's MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.
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            Quality control and preprocessing of metagenomic datasets

            Summary: Here, we present PRINSEQ for easy and rapid quality control and data preprocessing of genomic and metagenomic datasets. Summary statistics of FASTA (and QUAL) or FASTQ files are generated in tabular and graphical form and sequences can be filtered, reformatted and trimmed by a variety of options to improve downstream analysis. Availability and Implementation: This open-source application was implemented in Perl and can be used as a stand alone version or accessed online through a user-friendly web interface. The source code, user help and additional information are available at http://prinseq.sourceforge.net/. Contact: rschmied@sciences.sdsu.edu; redwards@cs.sdsu.edu
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              Calypso: a user-friendly web-server for mining and visualizing microbiome–environment interactions

              Abstract Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. Availability and Implementation: The web-interface is accessible via http://cgenome.net/calypso/. The software is programmed in Java, PERL and R and the source code is available from Zenodo (https://zenodo.org/record/50931). The software is freely available for non-commercial users. Contact: l.krause@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                f.h.heida@isala.nl
                Journal
                BMC Microbiol
                BMC Microbiol
                BMC Microbiology
                BioMed Central (London )
                1471-2180
                21 July 2021
                21 July 2021
                2021
                : 21
                Affiliations
                [1 ]GRID grid.452600.5, ISNI 0000 0001 0547 5927, Division of Obstetrics & Gynecology, , Isala Klinieken, University of Groningen, ; Zwolle, the Netherlands
                [2 ]GRID grid.4830.f, ISNI 0000 0004 0407 1981, Division of Pediatric Surgery Beatrix Children’s Hospital, University Medical Center Groningen, , University of Groningen, ; Groningen, the Netherlands
                [3 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Division of Neonatology Beatrix Children’s Hospital, , University of Groningen, University Medical Center Groningen, ; Groningen, the Netherlands
                [4 ]GRID grid.416153.4, ISNI 0000 0004 0624 1200, Victorian Infectious Diseases Reference Laboratory, Peter Doherty Institute for Infection and Immunity, , Royal Melbourne Hospital, ; Melbourne, Australia
                [5 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Division of Microbiology, , University of Groningen, University Medical Center Groningen, ; Groningen, the Netherlands
                [6 ]GRID grid.7177.6, ISNI 0000000084992262, Department of Vascular Medicine, Academic Medical Center, , University of Amsterdam, ; Amsterdam, the Netherlands
                [7 ]GRID grid.10306.34, ISNI 0000 0004 0606 5382, Parasites and Microboes, , Wellcome Sanger Institute, ; Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
                Article
                2279
                10.1186/s12866-021-02279-y
                8293572
                34289818
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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                Research
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                © The Author(s) 2021

                Microbiology & Virology

                intestinal microbiome, prematurity, mode of delivery, development, weight

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