Global airborne bacterial community—interactions with Earth’s microbiomes and anthropogenic activities

Significance Understanding the interactions of planetary microbiomes and their ecological and health consequences requires in-depth knowledge of bacterial communities in the atmosphere, which is the most untouched microbial habitat on the Earth. By establishing a comprehensive atlas of global airborne bacteria, we found that half of the airborne bacteria originate from surrounding environments and are mainly influenced by local meteorological and air quality conditions. One feature of the airborne bacteria in urban areas is that an increasing proportion consists of potential pathogens from human-related sources. The present study defines the aerial microbial world and its origins in a changing climate, and contributes to assessments of the health impact in atmospheric environments.

[1]  S. Grant,et al.  Limited Bacterial Removal in Full-Scale Stormwater Biofilters as Evidenced by Community Sequencing Analysis. , 2021, Environmental science & technology.

[2]  Persistent microbiome members in the common bean rhizosphere: an integrated analysis of space, time, and plant genotype , 2021, The ISME journal.

[3]  S. Wofsy,et al.  The Microbiome of Size-Fractionated Airborne Particles from the Sahara Region. , 2021, Environmental science & technology.

[4]  A. Arkin,et al.  A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming , 2020, Nature Communications.

[5]  Cesar Cardona,et al.  Earth microbial co-occurrence network reveals interconnection pattern across microbiomes , 2020, Microbiome.

[6]  T. Dunne,et al.  Surf zone microbiological water quality following emergency beach nourishment using sediments from a catastrophic debris flow. , 2020, Water research.

[7]  O. Magand,et al.  Global airborne microbial communities controlled by surrounding landscapes and wind conditions , 2019, Scientific Reports.

[8]  Jennifer Lu,et al.  Improved metagenomic analysis with Kraken 2 , 2019, Genome Biology.

[9]  Francesco Asnicar,et al.  Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2 , 2019, Nature Biotechnology.

[10]  Tianle Zhu,et al.  Culturability, metabolic activity and composition of ambient bacterial aerosols in a surrogate lung fluid. , 2019, The Science of the total environment.

[11]  Anthropogenic pressure explains variations in the biodiversity of pond communities along environmental gradients: a case study in south-eastern Serbia , 2019, Hydrobiologia.

[12]  A. Shade,et al.  Abundance-occupancy distributions to prioritize plant core microbiome membership. , 2019, Current opinion in microbiology.

[13]  Ling Jin,et al.  Air pollution: a global problem needs local fixes , 2019, Nature.

[14]  K. Pardesi,et al.  Emerging Strategies to Combat ESKAPE Pathogens in the Era of Antimicrobial Resistance: A Review , 2019, Front. Microbiol..

[15]  Yong Li,et al.  Global diversity and biogeography of bacterial communities in wastewater treatment plants , 2019, Nature Microbiology.

[16]  H. Kan,et al.  Profile of inhalable bacteria in PM2.5 at Mt. Tai, China: Abundance, community, and influence of air mass trajectories. , 2019, Ecotoxicology and environmental safety.

[17]  Pengxia Liu,et al.  Bacterial community structure in atmospheric particulate matters of different sizes during the haze days in Xi'an, China. , 2018, The Science of the total environment.

[18]  M. V. D. van der Heijden,et al.  Keystone taxa as drivers of microbiome structure and functioning , 2018, Nature Reviews Microbiology.

[19]  Falk Hildebrand,et al.  Structure and function of the global topsoil microbiome , 2018, Nature.

[20]  K. Finster,et al.  Aeolian dispersal of bacteria in southwest Greenland: their sources, abundance, diversity and physiological states , 2018, FEMS microbiology ecology.

[21]  Yu-Qin Zhang,et al.  Structural Variation in the Bacterial Community Associated with Airborne Particulate Matter in Beijing, China, during Hazy and Nonhazy Days , 2018, Applied and Environmental Microbiology.

[22]  Jia Gu,et al.  fastp: an ultra-fast all-in-one FASTQ preprocessor , 2018, bioRxiv.

[23]  Tingting Zhang,et al.  16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing , 2017, BMC Bioinformatics.

[24]  Z. Ouyang,et al.  Meteorological factors had more impact on airborne bacterial communities than air pollutants. , 2017, The Science of the total environment.

[25]  Rick L. Stevens,et al.  A communal catalogue reveals Earth’s multiscale microbial diversity , 2017, Nature.

[26]  R. Ambrosini,et al.  Influence of seasonality, air mass origin and particulate matter chemical composition on airborne bacterial community structure in the Po Valley, Italy. , 2017, The Science of the total environment.

[27]  Jia Zhang,et al.  Plant cultivars imprint the rhizosphere bacterial community composition and association networks , 2017 .

[28]  Y. Rudich,et al.  Origin-Dependent Variations in the Atmospheric Microbiome Community in Eastern Mediterranean Dust Storms. , 2017, Environmental science & technology.

[29]  U. Sommer,et al.  Variability of airborne bacteria in an urban Mediterranean area (Thessaloniki, Greece) , 2017 .

[30]  E. Graham,et al.  Deterministic influences exceed dispersal effects on hydrologically‐connected microbiomes , 2017, Environmental microbiology.

[31]  A. Mellouki,et al.  Bacterial characterization in ambient submicron particles during severe haze episodes at Ji'nan, China. , 2017, The Science of the total environment.

[32]  J. Raes,et al.  Combined use of network inference tools identifies ecologically meaningful bacterial associations in a paddy soil , 2017 .

[33]  Y. Tokue,et al.  Comparison of 16S ribosomal RNA gene sequence analysis and conventional culture in the environmental survey of a hospital , 2017, Journal of Pharmaceutical Health Care and Sciences.

[34]  Mehdi Layeghifard,et al.  Disentangling Interactions in the Microbiome: A Network Perspective , 2016, Trends in Microbiology.

[35]  Xiaoyan Fan,et al.  Airborne Bacterial Communities of PM2.5 in Beijing-Tianjin-Hebei Megalopolis, China as Revealed by Illumina MiSeq Sequencing: A Case Study , 2017 .

[36]  M. Andreae,et al.  Bioaerosols in the Earth system: Climate, health, and ecosystem interactions , 2016 .

[37]  Zhongbo Yu,et al.  Network analysis reveals seasonal variation of co-occurrence correlations between Cyanobacteria and other bacterioplankton. , 2016, The Science of the total environment.

[38]  P. Claus,et al.  Structure and function of methanogenic microbial communities in sediments of Amazonian lakes with different water types. , 2016, Environmental microbiology.

[39]  Ben Nichols,et al.  Distributed under Creative Commons Cc-by 4.0 Vsearch: a Versatile Open Source Tool for Metagenomics , 2022 .

[40]  L. Mur,et al.  Taxon interactions control the distributions of cryoconite bacteria colonizing a High Arctic ice cap , 2016, Molecular ecology.

[41]  T. Lane,et al.  Changes in the Structure of the Microbial Community Associated with Nannochloropsis salina following Treatments with Antibiotics and Bioactive Compounds , 2016, Front. Microbiol..

[42]  N. Ostle,et al.  Temporal and spatial influences incur reconfiguration of Arctic heathland soil bacterial community structure. , 2016, Environmental microbiology.

[43]  Steven Salzberg,et al.  Bracken: Estimating species abundance in metagenomics data , 2016, bioRxiv.

[44]  J. Lennon,et al.  Scaling laws predict global microbial diversity , 2016, Proceedings of the National Academy of Sciences.

[45]  L. Tedersoo,et al.  Stochastic distribution of small soil eukaryotes resulting from high dispersal and drift in a local environment , 2015, The ISME Journal.

[46]  W. Deng,et al.  Distribution of bacteria in inhalable particles and its implications for health risks in kindergarten children in Hong Kong , 2016 .

[47]  Yan He,et al.  Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China , 2016, The ISME Journal.

[48]  Detlef Weigel,et al.  Microbial Hub Taxa Link Host and Abiotic Factors to Plant Microbiome Variation , 2016, PLoS biology.

[49]  Aaron Marc Saunders,et al.  The activated sludge ecosystem contains a core community of abundant organisms , 2015, The ISME Journal.

[50]  A. Bertram,et al.  A marine biogenic source of atmospheric ice-nucleating particles , 2015, Nature.

[51]  C. Lovejoy,et al.  Co-occurrence patterns in aquatic bacterial communities across changing permafrost landscapes , 2015 .

[52]  Luis Pedro Coelho,et al.  Structure and function of the global ocean microbiome , 2015, Science.

[53]  K. Pollard,et al.  Continental-scale distributions of dust-associated bacteria and fungi , 2015, Proceedings of the National Academy of Sciences.

[54]  F. Baquero,et al.  Tackling antibiotic resistance: the environmental framework , 2015, Nature Reviews Microbiology.

[55]  T. Nakashima,et al.  Seasonal variations in airborne bacterial community structures at a suburban site of central Japan over a 1-year time period using PCR-DGGE method , 2015, Aerobiologia.

[56]  Shunsuke Takahashi,et al.  Development of a Prokaryotic Universal Primer for Simultaneous Analysis of Bacteria and Archaea Using Next-Generation Sequencing , 2014, PloS one.

[57]  Stefanie Widder,et al.  Deciphering microbial interactions and detecting keystone species with co-occurrence networks , 2014, Front. Microbiol..

[58]  L. Roesch,et al.  Network topology reveals high connectance levels and few key microbial genera within soils , 2014, Front. Environ. Sci..

[59]  Daizhou Zhang,et al.  Transport of bacterial cells toward the Pacific in Northern Hemisphere westerly winds , 2014 .

[60]  J. Priscu,et al.  Modular community structure suggests metabolic plasticity during the transition to polar night in ice-covered Antarctic lakes , 2013, The ISME Journal.

[61]  N. Yamaguchi,et al.  Long-range Transportation of Bacterial Cells by Asian Dust , 2014 .

[62]  S. Langenheder,et al.  The importance of species sorting differs between habitat generalists and specialists in bacterial communities. , 2014, FEMS microbiology ecology.

[63]  David J. Smith.  Microbes in the upper atmosphere and unique opportunities for astrobiology research. , 2013, Astrobiology.

[64]  Jun Yu Li,et al.  The use of levoglucosan and radiocarbon for source apportionment of PM(2.5) carbonaceous aerosols at a background site in East China. , 2013, Environmental science & technology.

[65]  B. Singh,et al.  Methane, microbes and models: fundamental understanding of the soil methane cycle for future predictions. , 2013, Environmental microbiology.

[66]  K. Konstantinidis,et al.  Microbiome of the upper troposphere: Species composition and prevalence, effects of tropical storms, and atmospheric implications , 2012, Proceedings of the National Academy of Sciences.

[67]  Giancarlo Rampazzo,et al.  Temporal variability and effect of environmental variables on airborne bacterial communities in an urban area of Northern Italy , 2013, Applied Microbiology and Biotechnology.

[68]  J. Vorholt.  Microbial life in the phyllosphere , 2012, Nature Reviews Microbiology.

[69]  R. Whittaker,et al.  The keystone species concept: a critical appraisal , 2012 .

[70]  David C. Smith,et al.  Global distribution of microbial abundance and biomass in subseafloor sediment , 2012, Proceedings of the National Academy of Sciences.

[71]  J. Raes,et al.  Microbial interactions: from networks to models , 2012, Nature Reviews Microbiology.

[72]  David S. Wishart,et al.  METAGENassist: a comprehensive web server for comparative metagenomics , 2012, Nucleic Acids Res..

[73]  Yves Rosseel,et al.  lavaan: An R Package for Structural Equation Modeling , 2012 .

[74]  William W. Nazaroff,et al.  Human Occupancy as a Source of Indoor Airborne Bacteria , 2012, PloS one.

[75]  N. Fierer,et al.  Seasonal variability in airborne bacterial communities at a high-elevation site , 2012 .

[76]  William A. Walters,et al.  Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms , 2012, The ISME Journal.

[77]  Peter Langfelder,et al.  Fast R Functions for Robust Correlations and Hierarchical Clustering. , 2012, Journal of statistical software.

[78]  Noah Fierer,et al.  Using network analysis to explore co-occurrence patterns in soil microbial communities , 2011, The ISME Journal.

[79]  Susan M. Huse,et al.  Defining seasonal marine microbial community dynamics , 2011, The ISME Journal.

[80]  W. Wade,et al.  Bergey’s Manual of Systematic Bacteriology , 2012 .

[81]  Michael Mitzenmacher,et al.  Detecting Novel Associations in Large Data Sets , 2011, Science.

[82]  Rob Knight,et al.  Bayesian community-wide culture-independent microbial source tracking , 2011, Nature Methods.

[83]  B. Cho,et al.  Prokaryotic abundance and 16S rRNA gene sequences detected in marine aerosols on the East Sea (Korea). , 2011, FEMS microbiology ecology.

[84]  Anders F. Andersson,et al.  Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea , 2011, The ISME Journal.

[85]  B. Bohannan,et al.  Biodiversity and biogeography of the atmosphere , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[86]  Campbell O. Webb,et al.  Picante: R tools for integrating phylogenies and ecology , 2010, Bioinform..

[87]  Seunghoon Lee,et al.  Identification of airborne bacterial and fungal community structures in an urban area by T-RFLP analysis and quantitative real-time PCR. , 2010, The Science of the total environment.

[88]  M. Lawrence,et al.  Bacteria in the global atmosphere – Part 2: Modeling of emissions and transport between different ecosystems , 2009 .

[89]  M. Lawrence,et al.  Bacteria in the global atmosphere – Part 1: Review and synthesis of literature data for different ecosystems , 2009 .

[90]  Mark V. Lomolino,et al.  The Reticulating Phylogeny of Island Biogeography Theory , 2009, The Quarterly Review of Biology.

[91]  Albert-László Barabási,et al.  Scale-Free Networks: A Decade and Beyond , 2009, Science.

[92]  Christine Wiedinmyer,et al.  Characterization of Airborne Microbial Communities at a High-Elevation Site and Their Potential To Act as Atmospheric Ice Nuclei , 2009, Applied and Environmental Microbiology.

[93]  Jianzhi Zhang,et al.  A Big World Inside Small-World Networks , 2009, PloS one.

[94]  K. Gurney,et al.  Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence , 2008, PloS one.

[95]  R. T. Carneiro,et al.  Culture-Independent Assessment of Rhizobiales-Related Alphaproteobacteria and the Diversity of Methylobacterium in the Rhizosphere and Rhizoplane of Transgenic Eucalyptus , 2008, Microbial Ecology.

[96]  W. Ludwig,et al.  SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB , 2007, Nucleic acids research.

[97]  T. McMahon,et al.  Updated world map of the Köppen-Geiger climate classification , 2007 .

[98]  Eoin L. Brodie,et al.  Urban aerosols harbor diverse and dynamic bacterial populations , 2007, Proceedings of the National Academy of Sciences.

[99]  P. Legendre,et al.  vegan : Community Ecology Package. R package version 1.8-5 , 2007 .

[100]  R. B. Jackson,et al.  The diversity and biogeography of soil bacterial communities. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[101]  Patrick C Phillips,et al.  Network thinking in ecology and evolution. , 2005, Trends in ecology & evolution.

[102]  Alan M. Jones,et al.  Climate factors influencing bacterial count in background air samples , 2005, International journal of biometeorology.

[103]  A. Palva,et al.  Development of an extensive set of 16S rDNA‐targeted primers for quantification of pathogenic and indigenous bacteria in faecal samples by real‐time PCR , 2004, Journal of applied microbiology.

[104]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[105]  Alan H. Strahler,et al.  Global land cover mapping from MODIS: algorithms and early results , 2002 .

[106]  Thomas P. Curtis,et al.  Estimating prokaryotic diversity and its limits , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[107]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[108]  W. Whitman,et al.  Prokaryotes: the unseen majority. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[109]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[110]  R. B. Jackson,et al.  A global budget for fine root biomass, surface area, and nutrient contents. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[111]  R. Paine.  Food Web Complexity and Species Diversity , 1966, The American Naturalist.