INVESTIGADORES
DIONISI Hebe Monica
artículos
Título:
The bacterial community structure of hydrocarbon-polluted intertidal sediments as the basis for the definition of an ecological index of hydrocarbon exposure
Autor/es:
LOZADA, M.; MARCOS, M.S.; COMMENDATORE, M.; GIL, M.N.; DIONISI, H. M.
Revista:
MICROBES AND ENVIRONMENTS
Editorial:
JAPANESE SOC MICROBIAL ECOLOGY
Referencias:
Año: 2014 vol. 29 p. 269 - 276
ISSN:
1342-6311
Resumen:
Using amplicon pyrosequencing of 16S rRNA genes, we analyzed the bacterial community structure of intertidal sediments from two sites of the Patagonian coast with a different history of hydrocarbon exposure, using a global and a local perspective. Global-scale patterns in bacterial community structure seemed to be mostly associated with environmental factors such as sediment depth and distance from the coast, while the effect of hydrocarbon exposure was not noticeable. However, at a local scale, differences in community composition between samples with different hydrocarbon content could be detected at the class level, including higher abundances of Gammaproteobacteria and Alphaproteobacteria in polluted samples. These differences were more noticeable at the genus level, indicating that phylogenetic resolution is a factor to take into account when analyzing local differences in bacterial communities. Considering 63 bacterial genera selected based on being previously linked to hydrocarbon biodegradation, 40% of them showed higher abundances in at least one of the polluted samples with respect to the pristine sample. Using this information, an ecological indicator (ecological index of hydrocarbon exposure, EIHE) was defined and calculated for these samples, as well as for samples from a previous study. The EIHE index is directly related to the proportion of the bacterial community potentially capable of hydrocarbon biodegradation, and therefore can provide an estimation of hydrocarbon-degrading potential of the microbial community and of hydrocarbon exposure history. This index could be a valuable tool for bioremediation technologies, as a high number of samples can be processed and analyzed in a semi-automated manner.
