Applied Microbiology and Biotechnology

, Volume 99, Issue 11, pp 4867–4877 | Cite as

Spatio-temporal variability of airborne bacterial communities and their correlation with particulate matter chemical composition across two urban areas

  • I. Gandolfi
  • V. Bertolini
  • G. Bestetti
  • R. Ambrosini
  • E. Innocente
  • G. Rampazzo
  • M. Papacchini
  • A. Franzetti
Environmental biotechnology

Abstract

The study of spatio-temporal variability of airborne bacterial communities has recently gained importance due to the evidence that airborne bacteria are involved in atmospheric processes and can affect human health. In this work, we described the structure of airborne microbial communities in two urban areas (Milan and Venice, Northern Italy) through the sequencing, by the Illumina platform, of libraries containing the V5–V6 hypervariable regions of the 16S rRNA gene and estimated the abundance of airborne bacteria with quantitative PCR (qPCR). Airborne microbial communities were dominated by few taxa, particularly Burkholderiales and Actinomycetales, more abundant in colder seasons, and Chloroplasts, more abundant in warmer seasons. By partitioning the variation in bacterial community structure, we could assess that environmental and meteorological conditions, including variability between cities and seasons, were the major determinants of the observed variation in bacterial community structure, while chemical composition of atmospheric particulate matter (PM) had a minor contribution. Particularly, Ba, SO42− and Mg2+ concentrations were significantly correlated with microbial community structure, but it was not possible to assess whether they simply co-varied with seasonal shifts of bacterial inputs to the atmosphere, or their variation favoured specific taxa. Both local sources of bacteria and atmospheric dispersal were involved in the assembling of airborne microbial communities, as suggested, to the one side by the large abundance of bacteria typical of lagoon environments (Rhodobacterales) observed in spring air samples from Venice and to the other by the significant effect of wind speed in shaping airborne bacterial communities at all sites.

Keywords

Air pollution Bioaerosol Particulate matter NGS Milan Venice 

Notes

Acknowledgments

This work was supported by Grant PRIN 2010_2011 (2010WLNFY2_005) from the Italian Ministry of Research (MIUR). The high-volume samplers (ECHO HiVol, TCR TECORA, Milan, Italy) used for Venice-Mestre and Venice-Porto Marghera were kindly provided by the Regional Agency of Environmental Protection (ARPA-Veneto; www.arpa.veneto.it). Some bioinformatics analyses were performed on CINECA-HPC computer cluster PLX (Grant: IscraC_METEXTRA), Bologna (Italy).

Supplementary material

253_2014_6348_MOESM1_ESM.pdf (1.1 mb)
ESM 1(PDF 1081 kb)

References

  1. Benjamini Y, Yekutieli D (2001) The control of the false discovery rate in multiple testing under dependency. Ann Stat 29:1165–1188CrossRefGoogle Scholar
  2. Bertolini V, Gandolfi I, Ambrosini R, Bestetti G, Innocente E, Rampazzo G, Franzetti A (2013) Temporal variability and effect of environmental variables on airborne bacterial communities in an urban area of Northern Italy. Appl Microbiol Biotechnol 97:6561–6570. doi:10.1007/s00253-012-4450-0 CrossRefPubMedGoogle Scholar
  3. Borchard D, Gillet F, Legendre F (2011) Numerical ecology with R. Springer, New YorkCrossRefGoogle Scholar
  4. Bowers RM, Lauber CL, Wiedinmyer C, Hamady M, Hallar AG, Fall R, Knight R, Fierer N (2009) Characterization of airborne microbial communities at a high-elevation site and their potential to act as atmospheric ice nuclei. Appl Environ Microbiol 75:5121–5130. doi:10.1128/AEM. 00447-09 CrossRefPubMedCentralPubMedGoogle Scholar
  5. Bowers RM, McLetchie S, Knight R, Fierer N (2011a) Spatial variability in airborne bacterial communities across land-use types and their relationship to the bacterial communities of potential source environments. ISME J 5:601–612. doi:10.1038/ismej.2010.167 CrossRefPubMedCentralPubMedGoogle Scholar
  6. Bowers RM, Sullivan AP, Costello EK, Collett JL Jr, Knight R, Fierer N, Collett JL (2011b) Sources of bacteria in outdoor air across cities in the midwestern United States. Appl Environ Microbiol 77:6350–6356. doi:10.1128/AEM. 05498-11 CrossRefPubMedCentralPubMedGoogle Scholar
  7. Bowers RM, McCubbin IB, Hallar AG, Fierer N (2012) Seasonal variability in airborne bacterial communities at a high-elevation site. Atmos Environ 50:41–49. doi:10.1016/j.atmosenv.2012.01.005 CrossRefGoogle Scholar
  8. Bowers RM, Clements N, Emerson JB, Wiedinmyer C, Hannigan MP, Fierer N (2013) Seasonal variability in bacterial and fungal diversity of the near-surface atmosphere. Environ Sci Technol 47:12097–12106. doi:10.1021/es402970s CrossRefPubMedGoogle Scholar
  9. Brodie EL, DeSantis TZ, Parker JPM, Zubietta IX, Piceno YM, Andersen GL, Moberg Parker JP (2007) Urban aerosols harbor diverse and dynamic bacterial populations. Proc Natl Acad Sci U S A 104:299–304. doi:10.1073/pnas.0608255104 CrossRefPubMedCentralPubMedGoogle Scholar
  10. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6:1621–1624. doi:10.1038/ismej.2012.8 CrossRefPubMedCentralPubMedGoogle Scholar
  11. Claesson MJ, O’Sullivan O, Wang Q, Nikkila J, Marchesi JR, Smidt H, de Vos WM, Ross RP, O’Toole PW (2009) Comparative analysis of pyrosequencing and a phylogenetic microarray for exploring microbial community structures in the human distal intestine. PLoS One 4Google Scholar
  12. Córdova-Kreylos AL, Cao Y, Green PG, Hwang H-M, Kuivila KM, Lamontagne MG, Van De Werfhorst LC, Holden PA, Scow KM (2006) Diversity, composition, and geographical distribution of microbial communities in California salt marsh sediments. Appl Environ Microbiol 72:3357–3366. doi:10.1128/AEM. 72.5.3357-3366.2006 CrossRefPubMedCentralPubMedGoogle Scholar
  13. Dufrene M, Legendre P (2007) Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol Monogr 67:345–366Google Scholar
  14. European Environment Agency (2014) Air quality in EuropeGoogle Scholar
  15. Fang ZG, Ouyang ZY, Zheng H, Wang XK, Hu LF (2007) Culturable airborne bacteria in outdoor environments in Beijing, China. Microb Ecol 54:487–496. doi:10.1007/s00248-007-9216-3 CrossRefPubMedGoogle Scholar
  16. Fierer N, Liu ZZ, Rodriguez-Hernandez M, Knight R, Henn M, Hernandez MT (2008) Short-term temporal variability in airborne bacterial and fungal populations. Appl Environ Microbiol 74:200–207. doi:10.1128/aem. 01467-07 CrossRefPubMedCentralPubMedGoogle Scholar
  17. Franzetti A, Gandolfi I, Gaspari E, Ambrosini R, Bestetti G (2011) Seasonal variability of bacteria in fine and coarse urban air particulate matter. Appl Microbiol Biotechnol 90:745–753. doi:10.1007/s00253-010-3048-7 CrossRefPubMedGoogle Scholar
  18. Fu Y, Keats KF, Rivkin RB, Lang AS (2013) Water mass and depth determine the distribution and diversity of Rhodobacterales in an Arctic marine system. FEMS Microbiol Ecol 84:564–576. doi:10.1111/1574-6941.12085
  19. Gandolfi I, Bertolini V, Ambrosini R, Bestetti G, Franzetti A (2013) Unravelling the bacterial diversity in the atmosphere. Appl Microbiol Biotechnol 97:4727–4736. doi:10.1007/s00253-013-4901-2 CrossRefPubMedGoogle Scholar
  20. Gilbert JA, Steele JA, Caporaso JG, Steinbrück L, Reeder J, Temperton B, Huse S, McHardy AC, Knight R, Joint I, Somerfield P, Fuhrman JA, Field D (2012) Defining seasonal marine microbial community dynamics. ISME J 6:298–308. doi:10.1038/ismej.2011.107 CrossRefPubMedCentralPubMedGoogle Scholar
  21. Griffin DW (2007) Atmospheric movement of microorganisms in clouds of desert dust and implications for human health. Clin Microbiol Rev 20:459–77. doi:10.1128/CMR.00039-06, table of contentsCrossRefPubMedCentralPubMedGoogle Scholar
  22. Jarvis KE, Gray AL, Houk RS (2003) Handbook of inductively coupled plasma mass spectrometryGoogle Scholar
  23. Karthikeyan S, Joshi UM, Balasubramanian R (2006) Microwave assisted sample preparation for determining water-soluble fraction of trace elements in urban airborne particulate matter: evaluation of bioavailability. Anal Chim Acta 576:23–30. doi:10.1016/j.aca.2006.05.051 CrossRefPubMedGoogle Scholar
  24. Lee S-H, Lee HMH-J, Kim S-J, Kang H, Kim YP (2010) Identification of airborne bacterial and fungal community structures in an urban area by T-RFLP analysis and quantitative real-time PCR. Sci Total Environ 408:1349–1357. doi:10.1016/j.scitotenv.2009.10.061 CrossRefPubMedGoogle Scholar
  25. Legendre P, Legendre L (1998) Numerical ecology, 2nd English edition. Elsevier, AmstrerdamGoogle Scholar
  26. Mantecca P, Gualtieri M, Longhin E, Bestetti G, Palestini P, Bolzacchini E, Camatini M (2012) Adverse biological effects of Milan urban PM looking for suitable molecular markers of exposure. Chem Ind Chem Eng Q 18:635–641. doi:10.2298/CICEQ120206114M CrossRefGoogle Scholar
  27. Maron P-AA, Lejon DPHH, Carvalho E, Bizet K, Lemanceau P, Ranjard L, Mougel C (2005) Assessing genetic structure and diversity of airborne bacterial communities by DNA fingerprinting and 16S rDNA clone library. Atmos Environ 39:3687–3695. doi:10.1016/j.atosenv.2005.03.002 CrossRefGoogle Scholar
  28. Maron PA, Mougel C, Lejon DP H, Carvalho E, Bizet K, Marck G, Cubito N, Lemanceau P, Ranjard L, Lejon DPH (2006) Temporal variability of airborne bacterial community structure in an urban area. Atmos Environ 40:8074–8080. doi:10.1016/j.atmosenv.2006.08.047 CrossRefGoogle Scholar
  29. Nadkarni MA, Martin FE, Jacques NA, Hunter N (2002) Determination of bacterial load by real-time PCR using a broad-range (universal) probe and primers set. Microbiology 148:257–266PubMedGoogle Scholar
  30. O’Malley MA (2008) “Everything is everywhere: but the environment selects”: ubiquitous distribution and ecological determinism in microbial biogeography. Stud Hist Phil Biol Biomed Sci 39:314–325CrossRefGoogle Scholar
  31. Peccia J, Hernandez M (2006) Incorporating polymerase chain reaction-based identification, population characterization, and quantification of microorganisms into aerosol science: a review. Atmos Environ 40:3941–3961. doi:10.1016/j.atmosenv.2006.02.029 CrossRefGoogle Scholar
  32. Peres-Neto PR, Jackson DA, Somers KM (2005) How many principal components? stopping rules for determining the number of non-trivial axes revisited. Comput Stat Data Anal 49:974–997. doi:10.1016/j.csda.2004.06.015 CrossRefGoogle Scholar
  33. Polymenakou PN (2012) Atmosphere: a source of pathogenic or beneficial microbes? Atmosphere (Basel) 3:87–102. doi:10.3390/atmos3010087 CrossRefGoogle Scholar
  34. Rinsoz T, Duquenne P, Greff-Mirguet G, Oppliger A (2008) Application of real-time PCR for total airborne bacterial assessment: comparison with epifluorescence microscopy and culture-dependent methods. Atmos Environ 42:6767–6774. doi:10.1016/j.atmosenv.2008.05.018 CrossRefGoogle Scholar
  35. Sánchez de la Campa A, García-Salamanca A, Solano J, de la Rosa J, Ramos J-L (2013) Chemical and microbiological characterization of atmospheric particulate matter during an intense African dust event in Southern Spain. Environ Sci Technol 47:3630–3638. doi:10.1021/es3051235 CrossRefPubMedGoogle Scholar
  36. Scherer P, Sahm H (1981) Influence of sulphur-containing compounds on the growth of Methanosarcina barkeri in a defined medium. Eur J Appl Microbiol Biotechnol 12:28–35. doi:10.1007/BF00508115
  37. Schwartz J, Laden F, Zanobetti A (2002) The concentration-response relation between PM2.5 and daily deaths. Environ Health Perspect 110:1025–1029CrossRefPubMedCentralPubMedGoogle Scholar
  38. Smith DJ, Jaffe DA, Birmele MN, Griffin DW, Schuerger AC, Hee J, Roberts MS (2012) Free tropospheric transport of microorganisms from Asia to North America. Microb Ecol 64:973–985. doi:10.1007/s00248-012-0088-9 CrossRefPubMedGoogle Scholar
  39. Squizzato S, Masiol M, Innocente E, Pecorari E, Rampazzo G, Pavoni B (2012) A procedure to assess local and long-range transport contributions to PM2.5 and secondary inorganic aerosol. J Aerosol Sci 46:64–76. doi:10.1016/j.jaerosci.2011.12.001 CrossRefGoogle Scholar
  40. Team RDC (2008) R: A language and environment for statistical computingGoogle Scholar
  41. Vaïtilingom M, Attard E, Gaiani N, Sancelme M, Deguillaume L, Flossmann AI, Amato P, Delort A-M (2012) Long-term features of cloud microbiology at the puy de Dôme (France). Atmos Environ 56:88–100. doi:10.1016/j.atmosenv.2012.03.072 CrossRefGoogle Scholar
  42. Wainwright M (2003) Microorganisms cultured from stratospheric air samples obtained at 41 km. FEMS Microbiol Lett 218:161–165. doi:10.1016/S0378-1097(02)01138-2 CrossRefPubMedGoogle Scholar
  43. Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 5261–5267. doi:10.1128/AEM.00062-07Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • I. Gandolfi
    • 1
  • V. Bertolini
    • 1
  • G. Bestetti
    • 1
  • R. Ambrosini
    • 2
  • E. Innocente
    • 3
  • G. Rampazzo
    • 3
  • M. Papacchini
    • 4
  • A. Franzetti
    • 1
  1. 1.Department of Earth and Environmental SciencesUniversity of Milano-BicoccaMilanItaly
  2. 2.Department of Biotechnology and BiosciencesUniversity of Milano-BicoccaMilanItaly
  3. 3.Department of Environmental Sciences, Informatics and StatisticsUniversity of Ca’ FoscariVeniceItaly
  4. 4.INAIL Settore Ricerca, Certificazione e Verifica—DIPIARomaItaly

Personalised recommendations