Microdiversity can lead to different ecotypes within the same species. These are assumed to provide stability in time and space to those species. However, the role of microdiversity in the stability of whole microbial communities remains underexplored. Understanding the drivers of microbial community stability is necessary to predict community response to future disturbances. Here, we analyzed 16S rRNA gene amplicons from eight different temperate bog lakes at the 97% OTU and amplicon sequence variant (ASV) levels and found ecotypes within the same OTU with different distribution patterns in space and time. We observed that these ecotypes are adapted to different values of environmental factors such as water temperature and oxygen concentration. Our results showed that the existence of several ASVs within a OTU favored its persistence across changing environmental conditions. We propose that microdiversity aids the stability of microbial communities in the face of fluctuations in environmental factors.
Background: The dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities. Nowadays even small research groups can easily obtain raw sequencing data. After that, however, nonspecialists are faced with the double challenge of choosing among an everincreasing array of analysis methodologies, and navigating the vast amounts of results returned by these approaches. Results: Here we present a workflow that relies on the SqueezeMeta software for the automated processing of raw reads into annotated contigs and reconstructed genomes (bins). A set of custom scripts seamlessly integrates the output into the anvi'o analysis platform, allowing filtering and visual exploration of the results. Furthermore, we provide a software package with utility functions to expose the SqueezeMeta results to the R analysis environment. Conclusions: Altogether, our workflow allows non-expert users to go from raw sequencing reads to custom plots with only a few powerful, flexible and welldocumented commands.
Background: The dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities. Nowadays even small research groups can easily obtain raw sequencing data. After that, however, non-specialists are faced with the double challenge of choosing among an ever-increasing array of analysis methodologies, and navigating the vast amounts of results returned by these approaches.Results: Here we present a workflow that relies on the SqueezeMeta software for the automated processing of raw reads into annotated contigs and reconstructed genomes (bins). A set of custom scripts seamlessly integrates the output into the anvi'o analysis platform, allowing filtering and visual exploration of the results. Furthermore, we provide a software package with utility functions to expose the SqueezeMeta results to the R analysis environment.Conclusions: Altogether, our workflow allows non-expert users to go from raw sequencing reads to custom plots with only a few powerful, flexible and well-documented commands.
Intra-species diversity comprises different ecotypes within the same species. These are assumed to provide stability in time and space to those species. However, the role that microdiversity plays in the stability of whole microbial communities remains underexplored. Understanding the drivers of microbial community stability is necessary to predict community response to future disturbances. Here, we analyzed 16S rRNA gene amplicons from eight different temperate bog lakes at OTU-97% and amplicon sequence variant (ASV) levels, and we found ecotypes within the same species with different distribution patterns in space and time. We observed that these ecotypes are adapted to different values of environmental factors such as water temperature and oxygen concentration. Our results showed that the existence of several ASVs within a species favored its persistence across changing environmental conditions. We propose that microdiversity aids the stability of microbial communities in the face of fluctuations in environmental factors.2 15 20 After this step, we retained 26,128 ASVs from 1,108 samples. These ASV sequences are equivalent to OTUs (Operational Taxonomic Units) that differ in as little as one base out of 140 base pairs, therefore corresponding to more than 99.3% identity. The final result was a table containing the abundance of each ASV in each sample. The sequences were taxonomically classified against the FreshTrain database [45] using mothur v.1.39.1 [56]. More detailed information about the successive steps of the procedure can be found in Supplementary Table 1S.
Summary Advances in sequencing technologies have triggered the development of many bioinformatic tools aimed to analyze 16S rDNA sequencing data. As these tools need to be tested, it is important to simulate datasets that resemble samples from different environments. Here, we introduce M&Ms, a user-friendly open-source bioinformatic tool to produce different 16S rDNA datasets from reference sequences, based on pragmatic ecological parameters. It creates sequence libraries for ‘in silico’ microbial communities with user-controlled richness, evenness, microdiversity, and source environment. M&Ms allows the user to generate simple to complex read datasets based on real parameters that can be used in developing bioinformatic software or in benchmarking current tools. Availability The source code of M&Ms is freely available at https://github.com/ggnatalia/MMs (GPL-3.0 License). Supplementary information Supplementary data are available at Bioinformatics online.
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