
Phenotypic biomonitoring using multivariate flow cytometric analysis of multi‐stained microorganisms
Author(s) -
Wikström Per,
Johansson Thorsten,
Lundstedt Staffan,
Hägglund Lars,
Forsman Mats
Publication year - 2001
Publication title -
fems microbiology ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.377
H-Index - 155
eISSN - 1574-6941
pISSN - 0168-6496
DOI - 10.1111/j.1574-6941.2001.tb00769.x
Subject(s) - biology , microbial population biology , microorganism , microcosm , principal component analysis , partial least squares regression , multivariate statistics , ecology , bacteria , genetics , statistics , mathematics , artificial intelligence , computer science
A new method for monitoring phenotypic profiles of pure cultures and complex microbial communities was evaluated. The approach was to stain microorganisms with a battery of fluorescent dyes prior to flow cytometry analysis (FCM) and to analyse the data using multivariate methods, including principal component analysis and partial least squares. The FCM method was quantitatively evaluated using different mixtures of pure cultures as well as microbial communities. The results showed that the method could quantitatively and reproducibly resolve both populations and communities of microorganisms with 5% abundance in a diverse microbial background. The feasibility of monitoring complex microbial communities over time during the biodegradation of naphthalene using the FCM method was demonstrated. The biodegradation of naphthalene occurred to differing extents in microcosms representing three different types of aromatic‐contaminated groundwater and a sample of bio‐basin water. The FCM method distinguished each of these four microbial communities. The phenotypic profiles were compared with genotypic profiles generated by random‐amplified polymorphic DNA analysis. The genotypic profiles of the microbial communities described only the microbial composition, and not their functional change, whereas the phenotypic profiles seemed to contain information on both the composition and the functional change of the microorganisms. Furthermore, event analysis of the FCM data showed that microbial communities with initially differing compositions could converge towards a similar composition if they had a capacity for high levels of degradation, whereas microbial communities with similar initial compositions could diverge if they differed in biodegrading ability.