Dataset Information

RANOMALY: AmplicoN wOrkflow for Microbial community AnaLYsis.

ABSTRACT: Bioinformatic tools for marker gene sequencing data analysis are continuously and rapidly evolving, thus integrating most recent techniques and tools is challenging. We present an R package for data analysis of 16S and ITS amplicons based sequencing. This workflow is based on several R functions and performs automatic treatments from fastq sequence files to diversity and differential analysis with statistical validation. The main purpose of this package is to automate bioinformatic analysis, ensure reproducibility between projects, and to be flexible enough to quickly integrate new bioinformatic tools or statistical methods. rANOMALY is an easy to install and customizable R package, that uses amplicon sequence variants (ASV) level for microbial community characterization. It integrates all assets of the latest bioinformatics methods, such as better sequence tracking, decontamination from control samples, use of multiple reference databases for taxonomic annotation, all main ecological analysis for which we propose advanced statistical tests, and a cross-validated differential analysis by four different methods. Our package produces ready to publish figures, and all of its outputs are made to be integrated in Rmarkdown code to produce automated reports.

SUBMITTER: Theil S

PROVIDER: S-EPMC7836088 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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rANOMALY: AmplicoN wOrkflow for Microbial community AnaLYsis.

Theil Sebastien S Rifa Etienne E

F1000Research 20210107

Bioinformatic tools for marker gene sequencing data analysis are continuously and rapidly evolving, thus integrating most recent techniques and tools is challenging. We present an R package for data analysis of 16S and ITS amplicons based sequencing. This workflow is based on several R functions and performs automatic treatments from fastq sequence files to diversity and differential analysis with statistical validation. The main purpose of this package is to automate bioinformatic analysis, ens ...[more]

PMID: 33537122

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Project description:BackgroundDandruff is a chronic, recurring, and common scalp problem that is caused by several etiopathogeneses with complex mechanisms. Management of this condition is typically achieved via antifungal therapies. However, the precise roles played by microbiota in the development of the condition have not been elucidated. Despite their omnipresence on human scalp little is known about the co-occurrence/co-exclusion network of cutaneous microbiota.ResultsWe characterized the scalp and hair surface bacterial and fungal communities of 95 dandruff-afflicted and healthy individuals residing in China. The degree distributions of co-occurrence/co-exclusion network in fungi-bacteria and bacteria-bacteria were higher in the healthy group (P < 0.0001), whereas the betweenness values are higher in the dandruff group (P < 0.01). Meanwhile, the co-occurrence/co-exclusion network among fungi-fungi and fungi-bacteria showed that compared to the healthy group, the dandruff group had more positive links (P < 0.0001). In addition, we observed that Malassezia slooffiae, Malassezia japonica and Malassezia furfur, were more abundant in the dandruff group than in the healthy group. These microbiota were co-exclusion by either multiple bacterial genera or Malassezia sp. in healthy group. The lactic acid bacteria on the scalp and hair surface, especially the genera Lactobacillus and Lactococcus, exhibit a negative correlation with multiple bacterial genera on the scalp and hair surface. Lactobacillus plantarum and Pediococcus lactis isolated on the healthy human scalp can inhibit the growth of Staphylococcus epidermidis in vitro.ConclusionsWe showed that microbial networks on scalp and hair surface with dandruff were less integrated than their healthy counterparts, with lower node degree and more positive and stronger links which were deemed to be unstable and may be more susceptible to environmental fluctuations. Lactobacillus bacteria have extensive interactions with other bacteria or fungi in the scalp and hair surface micro-ecological network and can be used as targets for improving scalp health.

Project description:BACKGROUND: Analyses of DNA sequences from cultivated microorganisms have revealed genome-wide, taxa-specific nucleotide compositional characteristics, referred to as genome signatures. These signatures have far-reaching implications for understanding genome evolution and potential application in classification of metagenomic sequence fragments. However, little is known regarding the distribution of genome signatures in natural microbial communities or the extent to which environmental factors shape them. RESULTS: We analyzed metagenomic sequence data from two acidophilic biofilm communities, including composite genomes reconstructed for nine archaea, three bacteria, and numerous associated viruses, as well as thousands of unassigned fragments from strain variants and low-abundance organisms. Genome signatures, in the form of tetranucleotide frequencies analyzed by emergent self-organizing maps, segregated sequences from all known populations sharing < 50 to 60% average amino acid identity and revealed previously unknown genomic clusters corresponding to low-abundance organisms and a putative plasmid. Signatures were pervasive genome-wide. Clusters were resolved because intra-genome differences resulting from translational selection or protein adaptation to the intracellular (pH approximately 5) versus extracellular (pH approximately 1) environment were small relative to inter-genome differences. We found that these genome signatures stem from multiple influences but are primarily manifested through codon composition, which we propose is the result of genome-specific mutational biases. CONCLUSIONS: An important conclusion is that shared environmental pressures and interactions among coevolving organisms do not obscure genome signatures in acid mine drainage communities. Thus, genome signatures can be used to assign sequence fragments to populations, an essential prerequisite if metagenomics is to provide ecological and biochemical insights into the functioning of microbial communities.

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RANOMALY: AmplicoN wOrkflow for Microbial community AnaLYsis.

Publications

rANOMALY: AmplicoN wOrkflow for Microbial community AnaLYsis.

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