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Metagenomics workflow for hybrid assembly, differential coverage binning, metatranscriptomics and pathway analysis (MUFFIN)

Van Damme, Renaud and Hoelzer, Martin and Viehweger, Adrian and Müller, Bettina and Bongcam-Rudloff, Erik and Brandt, Christian (2021). Metagenomics workflow for hybrid assembly, differential coverage binning, metatranscriptomics and pathway analysis (MUFFIN). PLoS Computational Biology. 17 , e1008716
[Research article]

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Abstract

Metagenomics has redefined many areas of microbiology. However, metagenome-assembled genomes (MAGs) are often fragmented, primarily when sequencing was performed with short reads. Recent long-read sequencing technologies promise to improve genome reconstruction. However, the integration of two different sequencing modalities makes downstream analyses complex. We, therefore, developed MUFFIN, a complete metagenomic workflow that uses short and long reads to produce high-quality bins and their annotations. The workflow is written by using Nextflow, a workflow orchestration software, to achieve high reproducibility and fast and straightforward use. This workflow also produces the taxonomic classification and KEGG pathways of the bins and can be further used for quantification and annotation by providing RNA-Seq data (optionally). We tested the workflow using twenty biogas reactor samples and assessed the capacity of MUFFIN to process and output relevant files needed to analyze the microbial community and their function. MUFFIN produces functional pathway predictions and, if provided de novo metatranscript annotations across the metagenomic sample and for each bin. MUFFIN is available on github under GNUv3 licence: .Author summaryDetermining the entire DNA of environmental samples (sequencing) is a fundamental approach to gain deep insights into complex bacterial communities and their functions. However, this approach produces enormous amounts of data, which makes analysis time intense and complicated. We developed the Software "MUFFIN," which effortlessly untangle the complex sequencing data to reconstruct individual bacterial species and determine their functions. Our software is performing multiple complicated steps in parallel, automatically allowing everyone with only basic informatics skills to analyze complex microbial communities.For this, we combine two sequencing technologies: "long-sequences" (nanopore, better reconstruction) and "short-sequences" (Illumina, higher accuracy). After the reconstruction, we group the fragments that belong together ("binning") via multiple approaches and refinement steps while also utilizing the information from other bacterial communities ("differential binning"). This process creates hundreds of "bins" whereas each represents a different bacterial species with a unique function. We automatically determine their species, assess each genome's completeness, and attribute their biological functions and activity ("transcriptomics and pathways"). Our Software is entirely freely available to everyone and runs on a good computer, compute cluster, or via cloud.

Authors/Creators:Van Damme, Renaud and Hoelzer, Martin and Viehweger, Adrian and Müller, Bettina and Bongcam-Rudloff, Erik and Brandt, Christian
Title:Metagenomics workflow for hybrid assembly, differential coverage binning, metatranscriptomics and pathway analysis (MUFFIN)
Series Name/Journal:PLoS Computational Biology
Year of publishing :2021
Volume:17
Article number:e1008716
Number of Pages:13
Publisher:PUBLIC LIBRARY SCIENCE
ISSN:1553-734X
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 1 Natural sciences > 102 Computer and Information Science > 10203 Bioinformatics (Computational Biology) (applications to be 10610)
URN:NBN:urn:nbn:se:slu:epsilon-p-111287
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-111287
Additional ID:
Type of IDID
DOI10.1371/journal.pcbi.1008716
Web of Science (WoS)000617535100004
ID Code:22955
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
VH - Faculty of Veterinary Medicine and Animal Science
Department:(NL, NJ) > Department of Molecular Sciences
(VH) > Dept. of Animal Breeding and Genetics
Deposited By: SLUpub Connector
Deposited On:07 Apr 2021 08:03
Metadata Last Modified:07 Apr 2021 08:11

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