Cholet, F., Lisik, A., Agogué, H., Ijaz, U. Z. , Pineau, P., Lachaussée, N. and Smith, C. J. (2022) Ecological observations based on functional gene sequencing are sensitive to the amplicon processing method. mSphere, 7(4), e0032422. (doi: 10.1128/msphere.00324-22) (PMID:35938727) (PMCID:PMC9429940)
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Abstract
Until recently, the de facto method for short-read-based amplicon reconstruction was a sequence similarity threshold approach (operational taxonomic units [OTUs]). This has changed with the amplicon sequence variant (ASV) method where distributions are fitted to abundance profiles of individual genes using a noise-error model. While OTU-based approaches are still useful for 16S rRNA/18S rRNA genes, where thresholds of 97% to 99% are used, their use for functional genes is still debatable as there is no consensus on clustering thresholds. Here, we compare OTU- and ASV-based reconstruction approaches and taxonomy assignment methods, the naive Bayesian classifier (NBC) and Bayesian lowest common ancestor (BLCA) algorithm, using a functional gene data set from the microbial nitrogen-cycling community in the Brouage mudflat (France). A range of OTU similarity thresholds and ASVs were used to compare amoA (ammonia-oxidizing archaea [AOA] and ammonia-oxidizing bacteria [AOB]), nxrB, nirS, nirK, and nrfA communities between differing sedimentary structures. Significant effects of the sedimentary structure on weighted UniFrac (WUniFrac) distances were observed for AOA amoA when using ASVs, an OTU at a threshold of 97% sequence identity (OTU-97%), and OTU-85%; AOB amoA when using OTU-85%; and nirS when using ASV, OTU-90%, and OTU-85%. For AOB amoA, significant effects of the sedimentary structures on UniFrac distances were observed when using OTU-97% but not ASVs, and the inverse was found for nrfA. Interestingly, conclusions drawn for nirK and nxrB were consistent between amplicon reconstruction methods. We also show that when the sequences in the reference database are related to the environment in question, the BLCA algorithm leads to more phylogenetically relevant classifications. However, when the reference database contains sequences more dissimilar to the ones retrieved, the NBC obtains more information.
| Item Type: | Articles |
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| Additional Information: | We acknowledge the following funders: Thomas Crawford Hayes NUIG (awarded to C.J.S. and A.L.), a Harry Smith vacation studentship (awarded to A.L.), a mobility grant from the French Embassy in Ireland (awarded to H.A. and C.J.S.), a research visit grant, a Microbiology Society and Research Student Mobility grant, the University of Glasgow (awarded to F.C.), La Rochelle University, and the Environmental Protection Agency STRIVE Doctoral Scholarship Scheme (2012-W-PhD-6) (awarded to C.J.S.). F.C. is supported by a University of Glasgow College of Science and Engineering doctoral scholarship, U.Z.I. was funded by NERC IRF NE/L011956/1, and C.J.S. is supported by a Royal Academy of EngineeringScottish Water Research Chair (RCSRF1718643) and EPSRC award EP/V030515/1. |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Cholet, Dr Fabien and Smith, Professor Cindy and Ijaz, Dr Umer |
| Authors: | Cholet, F., Lisik, A., Agogué, H., Ijaz, U. Z., Pineau, P., Lachaussée, N., and Smith, C. J. |
| College/School: | College of Science and Engineering > School of Engineering > Infrastructure and Environment |
| Journal Name: | mSphere |
| Publisher: | American Society for Microbiology |
| ISSN: | 2379-5042 |
| ISSN (Online): | 2379-5042 |
| Published Online: | 08 August 2022 |
| Copyright Holders: | Copyright © 2022 Cholet et al |
| First Published: | First published in mSphere 7(4): e0032422 |
| Publisher Policy: | Reproduced under a Creative Commons licence |
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