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      Alternative approaches to identify core bacteria in Fucus distichus microbiome and assess their distribution and host-specificity

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          Abstract

          Background

          Identifying meaningful ecological associations between host and components of the microbiome is challenging. This is especially true for hosts such as marine macroalgae where the taxonomic composition of the microbiome is highly diverse and variable in space and time. Identifying core taxa is one way forward but there are many methods and thresholds in use. This study leverages a large dataset of microbial communities associated with the widespread brown macroalga, Fucus distichus, across sites and years on one island in British Columbia, Canada. We compare three different methodological approaches to identify core taxa at the amplicon sequence variant (ASV) level from this dataset: (1) frequency analysis of taxa on F. distichus performed over the whole dataset, (2) indicator species analysis (IndVal) over the whole dataset that identifies frequent taxa that are enriched on F. distichus in comparison to the local environment, and (3) a two-step IndVal method that identifies taxa that are consistently enriched on F. distichus across sites and time points. We then investigated a F. distichus time-series dataset to see if those core taxa are seasonally consistent on another remote island in British Columbia, Canada. We then evaluate host-specificity of the identified F. distichus core ASVs using comparative data from 32 other macroalgal species sampled at one of the sites.

          Results

          We show that a handful of core ASVs are consistently identified by both frequency analysis and IndVal approaches with alternative definitions, although no ASVs were always present on F. distichus and IndVal identified a diverse array of F. distichus indicator taxa across sites on Calvert Island in multiple years. Frequency analysis captured a broader suit of taxa, while IndVal was better at identifying host-specific microbes. Finally, two-step IndVal identified hundreds of indicator ASVs for particular sites/timepoints but only 12 that were indicators in a majority (> 6 out of 11) of sites/timepoints. Ten of these ASVs were also indicators on Quadra Island, 250 km away. Many F. distichus-core ASVs are generally found on multiple macroalgal species, while a few ASVs are highly specific to F. distichus.

          Conclusions

          Different methodological approaches with variable set thresholds influence core identification, but a handful of core taxa are apparently identifiable as they are widespread and temporally associated with F. distichus and enriched in comparison to the environment. Moreover, we show that many of these core ASVs of F. distichus are found on multiple macroalgal hosts, indicating that most occupy a macroalgal generalist niche rather than forming highly specialized associations with F. distichus. Further studies should test whether macroalgal generalists or specialists are more likely to engage in biologically important exchanges with host.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40793-022-00451-z.

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          Most cited references100

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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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              Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms

              DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600 Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.
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                Author and article information

                Contributors
                jungsoo.park@botany.ubc.ca
                kmdavis@zoology.ubc.ca
                genevieve.lajoie@umontreal.ca
                lwparfrey@botany.ubc.ca
                Journal
                Environ Microbiome
                Environ Microbiome
                Environmental Microbiome
                BioMed Central (London )
                2524-6372
                16 November 2022
                16 November 2022
                2022
                : 17
                : 55
                Affiliations
                [1 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, Department of Botany, Biodiversity Research Centre, , University of British Columbia, ; Vancouver, BC Canada
                [2 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, Department of Zoology, , University of British Columbia, ; Vancouver, BC Canada
                [3 ]GRID grid.14848.31, ISNI 0000 0001 2292 3357, Institut de Recherche en Biologie Végétale, Département de Sciences Biologiques, , Université de Montréal, ; Montréal, QC Canada
                Article
                451
                10.1186/s40793-022-00451-z
                9670562
                36384808
                a30109fa-ea71-4d3b-9def-502e58e47847
                © The Author(s) 2022

                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.

                History
                : 9 May 2022
                : 9 November 2022
                Funding
                Funded by: NSERC Discovery
                Award ID: 2021-03160
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                core microbiome,macroalgal microbiome,microbial ecology,symbiosis

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