Details zur Publikation

Referenztyp Zeitschriften
DOI / URL Link
Titel (primär) CHIC—an automated approach for the detection of dynamic variations in complex microbial communities
Autor Koch, C.; Fetzer, I.; Harms, H.; Müller, S.;
Journal / Serie Cytometry Part A
Erscheinungsjahr 2013
Department UMB;
Band/Volume 83
Heft 6
Sprache englisch;
POF III (gesamt) R31;
Keywords automated pattern analysis; person-independent data evaluation; bacterial communities; microbial community dynamics; DNA pattern analysis; bioprocesses
UFZ Querschnittsthemen RU4;
Abstract Altering environmental conditions change structures of microbial communities. These effects have an impact on the single-cell level and can be sensitively detected using community flow cytometry. However, although highly accurate, microbial monitoring campaigns are still rarely performed applying this technique. One reason is the limited access to pattern analysis approaches for the evaluation of microbial cytometric data. In this article, a new analyzing tool, Cytometric Histogram Image Comparison (CHIC), is presented, which realizes trend interpretation of variations in microbial community structures (i) without any previous definition of gates, by working (ii) person independent, and (iii) with low computational demand. Various factors influencing a sensitive determination of changes in community structures were tested. The sensitivity of this technique was found to discriminate down to 0.5% internal variation. The final protocol was exemplarily applied to a complex microbial community dataset, and correlations to experimental variation were successfully shown.
ID 13551
dauerhafte UFZ-Verlinkung http://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=13551
Koch, C., Fetzer, I., Harms, H., Müller, S. (2013):
CHIC—an automated approach for the detection of dynamic variations in complex microbial communities
Cytom. Part A 83 (6), 561 - 567