Affiliations 

  • 1 Center for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, 200241, China
  • 2 Weill Cornell Medicine, USA; The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, USA
  • 3 Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India; Centre for Artificial Intelligence and Machine Learning, Indian Statistical Institute, Kolkata, India
  • 4 Universidad Andrés Bello, Center for Bioinformatics and Integrative Biology, Facultad de Ciencias de la Vida, Argentina
  • 5 Jagiellonian University, Faculty of Medicine, Department of Microbiology, Poland
  • 6 Department of Biological Sciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor, Malaysia
  • 7 University of Hawaii, John A. Burns School of Mecidine, USA
  • 8 Medical Genomics Group, A.C. Camargo Cancer Center and LIM-27 Faculdade de Medicina, USP, São Paulo, Brazil
  • 9 Institute of Molecular Biology and Genetics of National Academy of Science of Ukraine, Ukraine
  • 10 Department of Analytical, Environmental and Forensic Sciences, King's College London, UK
  • 11 Microbial Genomics Laboratory, Institut Pasteur de Montevideo, Uruguay; Center for Integrative Biology, Universidad Mayor, Santiago de Chile, Chile; Wellcome Sanger Institute, Hinxton, United Kingdom
  • 12 Institut Pasteur Korea, South Korea
  • 13 Małopolska Centre of Biotechnology, Jagiellonian University, Poland
  • 14 School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China
  • 15 University of Colorado at Boulder, Civil, Environmental and Architectural Department, Boulder, 80303, USA
  • 16 Applied Environmental Metagenomics and Infectious Diseases Research (AEMIDR), Department of Biological Sciences, Elizade University, Nigeria
  • 17 BCPL-CPERI, Centre for Research & Technology Hellas, Thessalonica, GR, 57001, Greece
  • 18 Department of Biology, Program on Disease Evolution, University of Louisville, Louisville, KY, 40292, USA
  • 19 Reckitt Health, Montvale, NJ, USA; Dept. of Biology, City University of New York, Brooklyn, 11210, NY, USA
  • 20 Aix-Marseille Université, IRD, AP-HM, IHU Méditerranée Infection, France
  • 21 University of Maryland School of Medicine, Institute for Genome Sciences, USA
  • 22 Robert Koch Institute Berlin, Germany
  • 23 Faculty of Environment and Information Studies, Keio University, Fujisawa, Kanagawa, Japan
  • 24 Millennium Initiative for Collaborative Research on Bacterial Resistance, Germany
  • 25 High Performance and Cloud Computing Group, Zentrum für Datenverarbeitung (ZDV), Eberhard Karls University of Tübingen, Wächterstraße 76, 72074, Tübingen, Germany
  • 26 Corporación Corpogen Research Center, Bogotá, Colombia
  • 27 Biological Targeting Diagnosis and Therapy Research Center, Guangxi Medical University, Nanning, 530021, China
  • 28 Center for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, 200241, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, 100083, China. Electronic address: tieliushi@yahoo.com
Environ Res, 2022 May 01;207:112183.
PMID: 34637759 DOI: 10.1016/j.envres.2021.112183

Abstract

In urban ecosystems, microbes play a key role in maintaining major ecological functions that directly support human health and city life. However, the knowledge about the species composition and functions involved in urban environments is still limited, which is largely due to the lack of reference genomes in metagenomic studies comprises more than half of unclassified reads. Here we uncovered 732 novel bacterial species from 4728 samples collected from various common surface with the matching materials in the mass transit system across 60 cities by the MetaSUB Consortium. The number of novel species is significantly and positively correlated with the city population, and more novel species can be identified in the skin-associated samples. The in-depth analysis of the new gene catalog showed that the functional terms have a significant geographical distinguishability. Moreover, we revealed that more biosynthetic gene clusters (BGCs) can be found in novel species. The co-occurrence relationship between BGCs and genera and the geographical specificity of BGCs can also provide us more information for the synthesis pathways of natural products. Expanded the known urban microbiome diversity and suggested additional mechanisms for taxonomic and functional characterization of the urban microbiome. Considering the great impact of urban microbiomes on human life, our study can also facilitate the microbial interaction analysis between human and urban environment.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.