Microbiological characterization of 3193 French dwellings of Elfe cohort children

Sci Total Environ. 2015 Feb 1;505:1026-35. doi: 10.1016/j.scitotenv.2014.10.086. Epub 2014 Nov 10.


Although exposure to indoor microorganisms in early life has already been associated with respiratory illness or allergy protection, only a few studies have performed standardized samplings and specific microbial analysis. Moreover, most do not target the different groups of microorganisms involved in respiratory diseases (fungi, bacteria, dust mites). In our study, ten specific qPCR targets (6 fungal species, 1 family and 2 genera of bacteria, 1 house dust mite) were used to analyze the microorganism composition of electrostatic dust fall collector (EDC) from 3193 dwellings of the Elfe French cohort study. Multivariate analyses allowed us to show that the microbial composition of dwellings, assessed with simultaneous analysis of 10 microorganisms, can be characterized by four entities: three bacteria, house dust mite Dermatophagoïdes pteronyssinus, fungi Alternaria alternata, and five other molds. Some dwellings' intrinsic characteristics (occupational ratio, type of dwelling and presence of pets) clearly influence microorganism distribution, and six different profiles of dwellings, characterized by their composition in microorganisms, have been described across France. The use of these clusters seems promising in the evaluation of allergic risk. Allergic respiratory diseases will develop in the near future in some children of the Elfe cohort and will indicate to what extent our approach can be predictive of respiratory disease.

Keywords: Dwelling qPCR profiles; Electrostatic dust fall collector (EDC); Elfe cohort; Microorganism geographical location; Respiratory disorders.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Microbiology*
  • Air Pollution, Indoor / statistics & numerical data
  • Child
  • Cohort Studies
  • Dust / analysis
  • Environmental Exposure / analysis*
  • Environmental Exposure / statistics & numerical data
  • France
  • Housing / statistics & numerical data*
  • Humans


  • Dust