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      Bacterial colonization reprograms the neonatal gut metabolome

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          Introductory Paragraph

          Initial microbial colonization and later succession in the gut of human infants are linked to health and disease later in life. The timing of the appearance of the first gut microbiome, and the consequences for the early life metabolome, are just starting to be defined. Here we evaluated the gut microbiome, proteome, and metabolome in 88 African American newborns using fecal samples collected in the first few days of life. Gut bacteria became detectable using molecular methods by 16 hours after birth. Detailed analysis of the three most common species, Escherichia coli, Enterococcus faecalis, and Bacteroides vulgatus, did not suggest a genomic signature for neonatal gut colonization. The appearance of bacteria was associated with reduced abundance of approximately 50 human proteins, decreased levels of free amino acids, and an increase in products of bacterial fermentation, including acetate and succinate. Using flux balance modeling and in vitro experiments, we provide evidence that fermentation of amino acids provides a mechanism for the initial growth of Escherichia coli, the most common early colonizer, under anaerobic conditions. These results provide a deep characterization of the first microbes in the human gut and show how the biochemical environment is altered by their appearance.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Is Open Access

            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              Fast and accurate short read alignment with Burrows–Wheeler transform

              Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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                Author and article information

                Journal
                101674869
                44774
                Nat Microbiol
                Nat Microbiol
                Nature microbiology
                2058-5276
                22 April 2020
                13 April 2020
                June 2020
                17 April 2021
                : 5
                : 6
                : 838-847
                Affiliations
                [1 ]Division of Gastroenterology, Hepatology, and Nutrition, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
                [2 ]Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [3 ]Division of Gastroenterology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [4 ]Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA 16802, USA
                [5 ]Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
                [6 ]Epigenetics Institute, Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [7 ]Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
                [8 ]Maternal and Child Health Research Center, Department of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                [9 ]Division of Endocrinology & Diabetes, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
                [10 ]Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.
                [11 ]Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
                Author notes

                Author Contributions

                BZ, GW, MAE and PD are responsible for the overall study design. EF, AK, and BZ performed clinical sampling. LM, DK, and CEH carried out DNA sequencing and qPCR experiments. CZ, KB, and MG carried out bioinformatics analysis. ASS, PL, and BG carried out proteomics experiments and performed data analysis. JC, YT, QL, and ADP carried out metabolomics experiments and performed data analysis. DS, JSHC, and CM carried out metabolomic flux modeling. JN and ESF carried out bacterial culture experiments and performed data analysis. KB, YL, CZ, and HL carried out statistical analysis. JSG, MAE, FDB, AK, and PD provided critical guidance in the analysis and interpretation of results. KB and GW wrote the manuscript. FDB, BZ, CZ, YL, AK, JSG, EF, JN, ESF, ADP, DS, CM, and LM revised the manuscript. BZ and GW managed the project.

                [* ]Corresponding authors: Kyle Bittinger, bittingerk@ 123456email.chop.edu , Babette Zemel, zemel@ 123456email.chop.edu , Gary D. Wu, gdwu@ 123456pennmedicine.upenn.edu
                Author information
                http://orcid.org/0000-0003-3472-5934
                http://orcid.org/0000-0002-6164-7348
                http://orcid.org/0000-0002-1829-8795
                Article
                NIHMS1563566
                10.1038/s41564-020-0694-0
                8052915
                32284564
                ca763db8-1252-4e27-8bf7-090522ce0254

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