Literature DB >> 27160955

Flow cytometry community fingerprinting and amplicon sequencing for the assessment of landfill leachate cellulolytic bioaugmentation.

R Kinet1, P Dzaomuho1, J Baert1, B Taminiau2, G Daube2, C Nezer3, Y Brostaux4, F Nguyen5, G Dumont5, P Thonart6, F Delvigne7.   

Abstract

Flow cytometry (FCM) is a high throughput single cell technology that is actually becoming widely used for studying phenotypic and genotypic diversity among microbial communities. This technology is considered in this work for the assessment of a bioaugmentation treatment in order to enhance cellulolytic potential of landfill leachate. The experimental results reveal the relevant increase of leachate cellulolytic potential due to bioaugmentation. Cytometric monitoring of microbial dynamics along these assays is then realized. The flow FP package is used to establish microbial samples fingerprint from initial 2D cytometry histograms. This procedure allows highlighting microbial communities' variation along the assays. Cytometric and 16S rRNA gene sequencing fingerprinting methods are then compared. The two approaches give same evidence about microbial dynamics throughout digestion assay. There are however a lack of significant correlation between cytometric and amplicon sequencing fingerprint at genus or species level. Same phenotypical profiles of microbiota during assays matched to several 16S rRNA gene sequencing ones. Flow cytometry fingerprinting can thus be considered as a promising routine on-site method suitable for the detection of stability/variation/disturbance of complex microbial communities involved in bioprocesses.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Amplicon sequencing; Anaerobic digestion; Bioaugmentation; Cellulose; Flow cytometry; Landfill; Leachate

Mesh:

Substances:

Year:  2016        PMID: 27160955     DOI: 10.1016/j.biortech.2016.04.131

Source DB:  PubMed          Journal:  Bioresour Technol        ISSN: 0960-8524            Impact factor:   9.642


  6 in total

1.  Characterizing Microbiome Dynamics - Flow Cytometry Based Workflows from Pure Cultures to Natural Communities.

Authors:  Johannes Lambrecht; Florian Schattenberg; Hauke Harms; Susann Mueller
Journal:  J Vis Exp       Date:  2018-07-12       Impact factor: 1.355

2.  Initial evenness determines diversity and cell density dynamics in synthetic microbial ecosystems.

Authors:  Elham Ehsani; Emma Hernandez-Sanabria; Frederiek-Maarten Kerckhof; Ruben Props; Ramiro Vilchez-Vargas; Marius Vital; Dietmar H Pieper; Nico Boon
Journal:  Sci Rep       Date:  2018-01-10       Impact factor: 4.379

3.  Growth-dependent recombinant product formation kinetics can be reproduced through engineering of glucose transport and is prone to phenotypic heterogeneity.

Authors:  Juan Carlos Fragoso-Jiménez; Jonathan Baert; Thai Minh Nguyen; Wenzheng Liu; Hosni Sassi; Frédéric Goormaghtigh; Laurence Van Melderen; Paul Gaytán; Georgina Hernández-Chávez; Alfredo Martinez; Frank Delvigne; Guillermo Gosset
Journal:  Microb Cell Fact       Date:  2019-02-02       Impact factor: 5.328

Review 4.  Computational Analysis of Microbial Flow Cytometry Data.

Authors:  Peter Rubbens; Ruben Props
Journal:  mSystems       Date:  2021-01-19       Impact factor: 6.496

5.  Effect of micro-aerobic process on improvement of anaerobic digestion sewage sludge treatment: flow cytometry and ATP assessment.

Authors:  Reza Barati Rashvanlou; Abbas Rezaee; Mahdi Farzadkia; Mitra Gholami; Majid Kermani
Journal:  RSC Adv       Date:  2020-09-30       Impact factor: 4.036

6.  Machine learning analysis of microbial flow cytometry data from nanoparticles, antibiotics and carbon sources perturbed anaerobic microbiomes.

Authors:  Abhishek S Dhoble; Pratik Lahiri; Kaustubh D Bhalerao
Journal:  J Biol Eng       Date:  2018-09-12       Impact factor: 4.355

  6 in total

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