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Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.

ABSTRACT: BACKGROUND:Microorganisms in activated sludge (AS) play key roles in the wastewater treatment processes. However, their ecological behaviors and differences from microorganisms in other environments have mainly been studied using the 16S rRNA gene that may not truly represent in situ functions. RESULTS:Here, we present 2045 archaeal and bacterial metagenome-assembled genomes (MAGs) recovered from 1.35?Tb of metagenomic data generated from 114 AS samples of 23 full-scale wastewater treatment plants (WWTPs). We found that the AS MAGs have obvious plant-specific features and that few proteins are shared by different WWTPs, especially for WWTPs located in geographically distant areas. Further, we developed a novel machine learning approach that can distinguish between AS MAGs and MAGs from other environments based on the clusters of orthologous groups of proteins with an accuracy of 96%. With the aid of machine learning, we also identified some functional features (e.g., functions related to aerobic metabolism, nutrient sensing/acquisition, and biofilm formation) that are likely vital for AS bacteria to adapt themselves in wastewater treatment bioreactors. CONCLUSIONS:Our work reveals that, although the bacterial species in different municipal WWTPs could be different, they may have similar deterministic functional features that allow them to adapt to the AS systems. Also, we provide valuable genome resources and a novel approach for future investigation and better understanding of the microbiome of AS and other ecosystems. Video Abtract.

SUBMITTER: Ye L

PROVIDER: S-EPMC7014675 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.

Ye Lin L Mei Ran R Liu Wen-Tso WT Ren Hongqiang H Zhang Xu-Xiang XX

Microbiome 20200211 1

<h4>Background</h4>Microorganisms in activated sludge (AS) play key roles in the wastewater treatment processes. However, their ecological behaviors and differences from microorganisms in other environments have mainly been studied using the 16S rRNA gene that may not truly represent in situ functions.<h4>Results</h4>Here, we present 2045 archaeal and bacterial metagenome-assembled genomes (MAGs) recovered from 1.35 Tb of metagenomic data generated from 114 AS samples of 23 full-scale wastewater ...[more]

PMID: 32046778

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Project description:A recent re-emerging bacterial canker disease incited by Pseudomonas syringae pv. actinidiae (Psa) is causing severe economic losses to Actinidia chinensis and A. deliciosa cultivations in southern Europe, New Zealand, Chile and South Korea. Little is known about the genetic features of this pathovar. We generated genome-wide Illumina sequence data from two Psa strains causing outbreaks of bacterial canker on the A. deliciosa cv. Hayward in Japan (J-Psa, type-strain of the pathovar) and in Italy (I-Psa) in 1984 and 1992, respectively as well as from a Psa strain (I2-Psa) isolated at the beginning of the recent epidemic on A. chinensis cv. Hort16A in Italy. All strains were isolated from typical leaf spot symptoms. The phylogenetic relationships revealed that Psa is more closely related to P. s. pv. theae than to P. avellanae within genomospecies 8. Comparative genomic analyses revealed both relevant intrapathovar variations and putative pathovar-specific genomic regions in Psa. The genomic sequences of J-Psa and I-Psa were very similar. Conversely, the I2-Psa genome encodes four additional effector protein genes, lacks a 50 kb plasmid and the phaseolotoxin gene cluster, argK-tox but has acquired a 160 kb plasmid and putative prophage sequences. Several lines of evidence from the analysis of the genome sequences support the hypothesis that this strain did not evolve from the Psa population that caused the epidemics in 1984-1992 in Japan and Italy but rather is the product of a recent independent evolution of the pathovar actinidiae for infecting Actinidia spp. All Psa strains share the genetic potential for copper resistance, antibiotic detoxification, high affinity iron acquisition and detoxification of nitric oxide of plant origin. Similar to other sequenced phytopathogenic pseudomonads associated with woody plant species, the Psa strains isolated from leaves also display a set of genes involved in the catabolism of plant-derived aromatic compounds.

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Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.

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Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.

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