Literature DB >> 32948522

Genome-Centric Metagenomic Insights into the Impact of Alkaline/Acid and Thermal Sludge Pretreatment on the Microbiome in Digestion Sludge.

Zhiwei Liang1, Jiangjian Shi1, Chen Wang1, Junhui Li2, Dawei Liang3, Ee Ling Yong4, Zhili He1, Shanquan Wang5.   

Abstract

Pretreatment of waste-activated sludge (WAS) is an effective way to destabilize sludge floc structure and release organic matter for improving sludge digestion efficiency. Nonetheless, information on the impact of WAS pretreatment on digestion sludge microbiomes, as well as mechanistic insights into how sludge pretreatment improves digestion performance, remains elusive. In this study, a genome-centric metagenomic approach was employed to investigate the digestion sludge microbiome in four sludge digesters with different types of feeding sludge: WAS pretreated with 0.25 mol/liter alkaline/acid (APAD), WAS pretreated with 0.8 mol/liter alkaline/acid (HS-APAD), thermally pretreated WAS (thermal-AD), and fresh WAS (control-AD). We retrieved 254 metagenome-assembled genomes (MAGs) to identify the key functional populations involved in the methanogenic digestion process. These MAGs span 28 phyla, including 69 yet-to-be-cultivated lineages, and 30 novel lineages were characterized with metabolic potential associated with hydrolysis and fermentation. Interestingly, functional populations involving carbohydrate digestion were enriched in APAD and HS-APAD, while lineages related to protein and lipid fermentation were enriched in thermal-AD, corroborating the idea that different substrates are released from alkaline/acid and thermal pretreatments. Among the major functional populations (i.e., fermenters, syntrophic acetogens, and methanogens), significant correlations between genome sizes and abundance of the fermenters were observed, particularly in APAD and HS-APAD, which had improved digestion performance.IMPORTANCE Wastewater treatment generates large amounts of waste-activated sludge (WAS), which consists mainly of recalcitrant microbial cells and particulate organic matter. Though WAS pretreatment is an effective way to release sludge organic matter for subsequent digestion, detailed information on the impact of the sludge pretreatment on the digestion sludge microbiome remains scarce. Our study provides unprecedented genome-centric metagenomic insights into how WAS pretreatments change the digestion sludge microbiomes, as well as their metabolic networks. Moreover, digestion sludge microbiomes could be a unique source for exploring microbial dark matter. These results may inform future optimization of methanogenic sludge digestion and resource recovery.
Copyright © 2020 American Society for Microbiology.

Entities:  

Keywords:  APAD; digestion sludge microbiome; metagenome; sludge pretreatment

Mesh:

Substances:

Year:  2020        PMID: 32948522      PMCID: PMC7657636          DOI: 10.1128/AEM.01920-20

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  60 in total

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Authors:  Anton Bankevich; Sergey Nurk; Dmitry Antipov; Alexey A Gurevich; Mikhail Dvorkin; Alexander S Kulikov; Valery M Lesin; Sergey I Nikolenko; Son Pham; Andrey D Prjibelski; Alexey V Pyshkin; Alexander V Sirotkin; Nikolay Vyahhi; Glenn Tesler; Max A Alekseyev; Pavel A Pevzner
Journal:  J Comput Biol       Date:  2012-04-16       Impact factor: 1.479

2.  A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life.

Authors:  Donovan H Parks; Maria Chuvochina; David W Waite; Christian Rinke; Adam Skarshewski; Pierre-Alain Chaumeil; Philip Hugenholtz
Journal:  Nat Biotechnol       Date:  2018-08-27       Impact factor: 54.908

3.  Genome-centric resolution of microbial diversity, metabolism and interactions in anaerobic digestion.

Authors:  Inka Vanwonterghem; Paul D Jensen; Korneel Rabaey; Gene W Tyson
Journal:  Environ Microbiol       Date:  2016-07-22       Impact factor: 5.491

4.  Analytical and clinical validation of a microbial cell-free DNA sequencing test for infectious disease.

Authors:  Timothy A Blauwkamp; Simone Thair; Judith C Wilber; Samuel Yang; Michael J Rosen; Lily Blair; Martin S Lindner; Igor D Vilfan; Trupti Kawli; Fred C Christians; Shivkumar Venkatasubrahmanyam; Gregory D Wall; Anita Cheung; Zoë N Rogers; Galit Meshulam-Simon; Liza Huijse; Sanjeev Balakrishnan; James V Quinn; Desiree Hollemon; David K Hong; Marla Lay Vaughn; Mickey Kertesz; Sivan Bercovici
Journal:  Nat Microbiol       Date:  2019-02-11       Impact factor: 17.745

5.  MAFFT multiple sequence alignment software version 7: improvements in performance and usability.

Authors:  Kazutaka Katoh; Daron M Standley
Journal:  Mol Biol Evol       Date:  2013-01-16       Impact factor: 16.240

6.  Environmental genome shotgun sequencing of the Sargasso Sea.

Authors:  J Craig Venter; Karin Remington; John F Heidelberg; Aaron L Halpern; Doug Rusch; Jonathan A Eisen; Dongying Wu; Ian Paulsen; Karen E Nelson; William Nelson; Derrick E Fouts; Samuel Levy; Anthony H Knap; Michael W Lomas; Ken Nealson; Owen White; Jeremy Peterson; Jeff Hoffman; Rachel Parsons; Holly Baden-Tillson; Cynthia Pfannkoch; Yu-Hui Rogers; Hamilton O Smith
Journal:  Science       Date:  2004-03-04       Impact factor: 47.728

7.  Microwave and ultrasound pre-treatments influence microbial community structure and digester performance in anaerobic digestion of waste activated sludge.

Authors:  Maria Westerholm; Sam Crauwels; Maarten Van Geel; Raf Dewil; Bart Lievens; Lise Appels
Journal:  Appl Microbiol Biotechnol       Date:  2016-01-27       Impact factor: 4.813

8.  Binning metagenomic contigs by coverage and composition.

Authors:  Johannes Alneberg; Brynjar Smári Bjarnason; Ino de Bruijn; Melanie Schirmer; Joshua Quick; Umer Z Ijaz; Leo Lahti; Nicholas J Loman; Anders F Andersson; Christopher Quince
Journal:  Nat Methods       Date:  2014-09-14       Impact factor: 28.547

9.  IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies.

Authors:  Lam-Tung Nguyen; Heiko A Schmidt; Arndt von Haeseler; Bui Quang Minh
Journal:  Mol Biol Evol       Date:  2014-11-03       Impact factor: 16.240

10.  Twenty years of the MEROPS database of proteolytic enzymes, their substrates and inhibitors.

Authors:  Neil D Rawlings; Alan J Barrett; Robert Finn
Journal:  Nucleic Acids Res       Date:  2015-11-02       Impact factor: 16.971

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