The Microbial Dark Matter and "wanted List" in Worldwide Wastewater Treatment Plants

Overview

Journal Microbiome

Publisher Biomed Central

Specialties Genetics
Microbiology

Date 2023 Mar 27

PMID 36973807

Authors

Yulin Zhang

Yulin Wang

Mingxi Tang

Jizhong Zhou

Tong Zhang

Affiliations

Soon will be listed here.

Abstract

Background: Wastewater treatment plants (WWTPs) are one of the largest biotechnology applications in the world and are of critical importance to modern urban societies. An accurate evaluation of the microbial dark matter (MDM, microorganisms whose genomes remain uncharacterized) proportions in WWTPs is of great value, while there is no such research yet. This study conducted a global meta-analysis of MDM in WWTPs with 317,542 prokaryotic genomes from the Genome Taxonomy Database and proposed a "wanted list" for priority targets in further investigations of activated sludge.

Results: Compared with the Earth Microbiome Project data, WWTPs had relatively lower genome-sequenced proportions of prokaryotes than other ecosystems, such as the animal related environments. Analysis showed that the median proportions of the genome-sequenced cells and taxa (100% identity and 100% coverage in 16S rRNA gene region) in WWTPs reached 56.3% and 34.5% for activated sludge, 48.6% and 28.5% for aerobic biofilm, and 48.3% and 28.5% for anaerobic digestion sludge, respectively. This result meant MDM had high proportions in WWTPs. Besides, all of the samples were occupied by a few predominant taxa, and the majority of the sequenced genomes were from pure cultures. The global-scale "wanted list" for activated sludge contained four phyla that have few representatives and 71 operational taxonomic units with the majority of them having no genome or isolate yet. Finally, several genome mining methods were verified to successfully recover genomes from activated sludge such as hybrid assembly of the second- and third-generation sequencing.

Conclusions: This work elucidated the proportion of MDM in WWTPs, defined the "wanted list" of activated sludge for future investigations, and certified potential genome recovery methods. The proposed methodology of this study can be applied to other ecosystems and improve understanding of ecosystem structure across diverse habitats. Video Abstract.

Citing Articles

Exploring Microbial Dark Matter for the Discovery of Novel Natural Products: Characteristics, Abundance Challenges and Methods.

Alanzi A J Microbiol Biotechnol. 2024; 35:e2407064.

PMID: 39639495 PMC: 11813339. DOI: 10.4014/jmb.2407.07064.

Rhodobacteraceae are Prevalent and Ecologically Crucial Bacterial Members in Marine Biofloc Aquaculture.

Rajeev M, Cho J J Microbiol. 2024; 62(11):985-997.

PMID: 39546167 DOI: 10.1007/s12275-024-00187-0.

High-throughput single-cell sequencing of activated sludge microbiome.

Zhang Y, Xue B, Mao Y, Chen X, Yan W, Wang Y Environ Sci Ecotechnol. 2024; 23:100493.

PMID: 39430728 PMC: 11490935. DOI: 10.1016/j.ese.2024.100493.

Genome-centric metagenomics provides insights into the core microbial community and functional profiles of biofloc aquaculture.

Rajeev M, Jung I, Kang I, Cho J mSystems. 2024; 9(10):e0078224.

PMID: 39315779 PMC: 11494986. DOI: 10.1128/msystems.00782-24.

Synthetic Biology of Natural Products Engineering: Recent Advances Across the Discover-Design-Build-Test-Learn Cycle.

Foldi J, Connolly J, Takano E, Breitling R ACS Synth Biol. 2024; 13(9):2684-2692.

PMID: 39163395 PMC: 11421215. DOI: 10.1021/acssynbio.4c00391.

References

Thomas F, Corre E, Cebron A . Stable isotope probing and metagenomics highlight the effect of plants on uncultured phenanthrene-degrading bacterial consortium in polluted soil. ISME J. 2019; 13(7):1814-1830. PMC: 6775975. DOI: 10.1038/s41396-019-0394-z. View

Singleton C, Petriglieri F, Kristensen J, Kirkegaard R, Michaelsen T, Andersen M . Connecting structure to function with the recovery of over 1000 high-quality metagenome-assembled genomes from activated sludge using long-read sequencing. Nat Commun. 2021; 12(1):2009. PMC: 8012365. DOI: 10.1038/s41467-021-22203-2. View

Rinke C, Schwientek P, Sczyrba A, Ivanova N, Anderson I, Cheng J . Insights into the phylogeny and coding potential of microbial dark matter. Nature. 2013; 499(7459):431-7. DOI: 10.1038/nature12352. View

Parks D, Rinke C, Chuvochina M, Chaumeil P, Woodcroft B, Evans P . Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat Microbiol. 2017; 2(11):1533-1542. DOI: 10.1038/s41564-017-0012-7. View

Karst S, Dueholm M, McIlroy S, Kirkegaard R, Nielsen P, Albertsen M . Retrieval of a million high-quality, full-length microbial 16S and 18S rRNA gene sequences without primer bias. Nat Biotechnol. 2018; 36(2):190-195. DOI: 10.1038/nbt.4045. View

Mei R, Kim J, Wilson F, Bocher B, Liu W . Coupling growth kinetics modeling with machine learning reveals microbial immigration impacts and identifies key environmental parameters in a biological wastewater treatment process. Microbiome. 2019; 7(1):65. PMC: 6471889. DOI: 10.1186/s40168-019-0682-x. View

Amir A, McDonald D, Navas-Molina J, Kopylova E, Morton J, Xu Z . Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns. mSystems. 2017; 2(2). PMC: 5340863. DOI: 10.1128/mSystems.00191-16. View

Rodriguez-Perez H, Ciuffreda L, Flores C . NanoCLUST: a species-level analysis of 16S rRNA nanopore sequencing data. Bioinformatics. 2020; 37(11):1600-1601. DOI: 10.1093/bioinformatics/btaa900. View

Kivioja T, Vaharautio A, Karlsson K, Bonke M, Enge M, Linnarsson S . Counting absolute numbers of molecules using unique molecular identifiers. Nat Methods. 2011; 9(1):72-4. DOI: 10.1038/nmeth.1778. View

10.

Callahan B, Wong J, Heiner C, Oh S, Theriot C, Gulati A . High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution. Nucleic Acids Res. 2019; 47(18):e103. PMC: 6765137. DOI: 10.1093/nar/gkz569. View

11.

Price J, Ledford S, Ryan M, Toran L, Sales C . Wastewater treatment plant effluent introduces recoverable shifts in microbial community composition in receiving streams. Sci Total Environ. 2017; 613-614:1104-1116. DOI: 10.1016/j.scitotenv.2017.09.162. View

12.

Jousset A, Bienhold C, Chatzinotas A, Gallien L, Gobet A, Kurm V . Where less may be more: how the rare biosphere pulls ecosystems strings. ISME J. 2017; 11(4):853-862. PMC: 5364357. DOI: 10.1038/ismej.2016.174. View

13.

Schulz F, Eloe-Fadrosh E, Bowers R, Jarett J, Nielsen T, Ivanova N . Towards a balanced view of the bacterial tree of life. Microbiome. 2017; 5(1):140. PMC: 5644168. DOI: 10.1186/s40168-017-0360-9. View

14.

Lynch M, Neufeld J . Ecology and exploration of the rare biosphere. Nat Rev Microbiol. 2015; 13(4):217-29. DOI: 10.1038/nrmicro3400. View

15.

Chen Y, Wang Y, Paez-Espino D, Polz M, Zhang T . Prokaryotic viruses impact functional microorganisms in nutrient removal and carbon cycle in wastewater treatment plants. Nat Commun. 2021; 12(1):5398. PMC: 8438041. DOI: 10.1038/s41467-021-25678-1. View

16.

Olesen J, Bascompte J, Dupont Y, Jordano P . The modularity of pollination networks. Proc Natl Acad Sci U S A. 2007; 104(50):19891-6. PMC: 2148393. DOI: 10.1073/pnas.0706375104. View

17.

Gilbert J, Jansson J, Knight R . The Earth Microbiome project: successes and aspirations. BMC Biol. 2014; 12:69. PMC: 4141107. DOI: 10.1186/s12915-014-0069-1. View

18.

Zhang Z, Wang J, Wang J, Wang J, Li Y . Estimate of the sequenced proportion of the global prokaryotic genome. Microbiome. 2020; 8(1):134. PMC: 7496214. DOI: 10.1186/s40168-020-00903-z. View

19.

Lugli G, Milani C, Duranti S, Alessandri G, Turroni F, Mancabelli L . Isolation of novel gut bifidobacteria using a combination of metagenomic and cultivation approaches. Genome Biol. 2019; 20(1):96. PMC: 6524291. DOI: 10.1186/s13059-019-1711-6. View

20.

Thompson L, Sanders J, McDonald D, Amir A, Ladau J, Locey K . A communal catalogue reveals Earth's multiscale microbial diversity. Nature. 2017; 551(7681):457-463. PMC: 6192678. DOI: 10.1038/nature24621. View