Literature DB >> 31639592

Community members in activated sludge as determined by molecular probe technology.

Weihong Xu1, Veronica R Brand2, Sundari Suresh3, Michael A Jensen3, Ronald W Davis4, Craig S Criddle2, Robert P St Onge5, Richard W Hyman6.   

Abstract

The use of molecular probe technology is demonstrated for routine identification and tracking of cultured and uncultured microorganisms in an activated sludge bioreactor treating domestic wastewater. A key advantage of molecular probe technology is that it can interrogate hundreds of microbial species of interest in a single measurement. In environmental niches where a single genus (such as Competibacteraceae) dominates, it can be difficult and expensive to identify microorganisms that are present at low relative abundance. With molecular probe technology, it is straightforward. Members of the Competibacteraceae family, none of which have been grown in pure culture, are abundant in an activated sludge system in the San Francisco Bay Area, California, USA. Molecular probe ensembles with and without Competibacteraceae probes were constructed. Whereas the probe ensemble with Competibacteraceae probes identified a total of ten bacteria, the molecular probe ensemble without Competibacteraceae probes identified 29 bacteria, including many at low relative abundance and including some species of public health significance.
Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Activated sludge; Bacteria; Molecular probes

Mesh:

Substances:

Year:  2019        PMID: 31639592      PMCID: PMC6873225          DOI: 10.1016/j.watres.2019.115104

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  38 in total

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Authors:  Ghalia Kaci; Denise Goudercourt; Véronique Dennin; Bruno Pot; Joël Doré; S Dusko Ehrlich; Pierre Renault; Hervé M Blottière; Catherine Daniel; Christine Delorme
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Journal:  Database (Oxford)       Date:  2015-06-27       Impact factor: 3.451

10.  Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences.

Authors:  Jai Ram Rideout; Yan He; Jose A Navas-Molina; William A Walters; Luke K Ursell; Sean M Gibbons; John Chase; Daniel McDonald; Antonio Gonzalez; Adam Robbins-Pianka; Jose C Clemente; Jack A Gilbert; Susan M Huse; Hong-Wei Zhou; Rob Knight; J Gregory Caporaso
Journal:  PeerJ       Date:  2014-08-21       Impact factor: 2.984

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