Microarray-based analysis of microbial functional diversity along an oil contamination gradient in oil field

Abstract

To understand better the in situ microbial functional diversity under oil contamination stress, soils were sampled along a contamination gradient at an oil field in north-east China. Microbial community functional structure was examined with a functional gene array, termed GeoChip. Multivariate statistical analysis and meta-analysis were conducted to study the functional gene responses to oil concentrations. The total functional gene abundance and diversity decreased along the gradient of increasing contamination. The overall abundance of soil bacteria, archaea and fungi decreased to 10%, 40% and 80% of those in the pristine soil. Several functional genes in the families pgl, rbcL, nifH and nor and those encoding cellulase, laccase, chitinase, urease and key enzymes in metabolizing organic compounds were significantly decreased with oil contamination, especially under high contamination stress. However, a few genes encoding key enzymes for catechol, protocatechuate, and biphenyl degradation and in the gene families of nir, rbcL and pgl showed a significant increase at a medium level of oil contamination. Oil content and soil available nitrogen were found to be important factors influencing the microbial community structure. The results provide an insight into microbial functional diversity in oil-contaminated soils, providing potential information for on-site management and remediation measures.

Functional gene diversity of soil microbial communities from five oil-contaminated fields in China

“…It is extremely difficult to detect microbial metabolic genes involved in contaminant degradation, as well as other important geochemical cycles, in a rapid and comprehensive way using conventional molecular ecology approaches. Microarray-based genomic technology provides a powerful tool for monitoring various microbial functional genes (Leigh et al, 2007;Yergeau et al, 2009;Liang et al, 2009a).…”

“…Oil contamination is particularly severe and has become a global issue, such as in Kuwait (Al-Sarawi and Massoud, 1998;Al-Hashem et al, 2007;Din et al, 2008), India (Gogoi et al, 2003), Libya (Hamid et al, 2008), China (Xiong et al, 1997;Liang et al, 2009a) and the United States (Lundegard and Johnson, 2006).…”

How sulphate-reducing microorganisms cope with stress: lessons from systems biology

“…SRM populations were found to be considerably larger in the oil-contaminated samples than in non-contaminated samples (Z. Lu and J.Z., unpublished observations), suggesting that these organisms contribute to natural bioremediation of oilcontaminated deep-sea ecosystems, as indicated by previous studies [117][118][119][120] . These and other applications of GeoChip 109,[121][122][123][124] demonstrate that this is a powerful tool for detecting and monitoring SRM populations and their associated microbial communities, as well as for assessing their metabolic potential and activity in response to different environmental stresses.…”

GeoChip 3.0 as a high-throughput tool for analyzing microbial community composition, structure and functional activity

“…Currently, this technology has become a powerful and high-throughput tool for analyzing microbial communities and monitoring environmental processes and ecosystem functions (c.f., Wu et al, 2001Wu et al, , 2006Wu et al, , 2008Loy et al, 2002;TaroncherOldenburg et al, 2003;Bodrossy and Sessitsch, 2004;Rhee et al, 2004;Steward et al, 2004;Tiquia et al, 2004;Dix et al, 2006;Rodriguez-Martinez et al, 2006;He et al, 2007;Leigh et al, 2007;Yergeau et al, 2007;Zhou et al, 2008;Liang et al, 2009;Mason et al, 2009;Tas et al, 2009;Van Nostrand et al, 2009;Waldron et al, 2009;Wang et al, 2009). Especially, one of our previous functional gene arrays (FGAs), GeoChip 2.0, containing more than 24 000 probes and covering more than 10 000 gene sequences from B150 gene categories involved in key microbially mediated biogeochemical processes has been widely used to analyze microbial communities from different resources, such as soils (Yergeau et al, 2007;Zhou et al, 2008), waters Leigh et al, 2007;Tas et al, 2009;Van Nostrand et al, 2009;Waldron et al, 2009), oil fields (Liang et al, 2009), marine sediments (Wu et al, 2008), extreme environments (Mason et al, 2009;Wang et al, 2009), bioreactor systems (Rodriguez-Martinez et al, 2006) and other habitats (Kimes et al, 2010), to address a variety of questions related to biogeochemical cycles, bioremediati...…”