To effectively monitor biodegrading populations, a comprehensive 50-mer-based oligonucleotide microarray was developed based on most of the 2,402 known genes and pathways involved in biodegradation and metal resistance. This array contained 1,662 unique and group-specific probes with <85% similarity to their nontarget sequences. Based on artificial probes, our results showed that under hybridization conditions of 50°C and 50% formamide, the 50-mer microarray hybridization can differentiate sequences having <88% similarity. Specificity tests with representative pure cultures indicated that the designed probes on the arrays appeared to be specific to their corresponding target genes. The detection limit was ϳ5 to 10 ng of genomic DNA in the absence of background DNA and 50 to 100 ng of pure-culture genomic DNA in the presence of background DNA or 1.3 ؋ 10 7 cells in the presence of background RNA. Strong linear relationships between the signal intensity and the target DNA and RNA were observed (r 2 ‫؍‬ 0.95 to 0.99). Application of this type of microarray to analyze naphthalene-amended enrichment and soil microcosms demonstrated that microflora changed differently depending on the incubation conditions. While the naphthalene-degrading genes from Rhodococcus-type microorganisms were dominant in naphthalene-degrading enrichments, the genes involved in naphthalene (and polyaromatic hydrocarbon and nitrotoluene) degradation from gram-negative microorganisms, such as Ralstonia, Comamonas, and Burkholderia, were most abundant in the soil microcosms. In contrast to general conceptions, naphthalene-degrading genes from Pseudomonas were not detected, although Pseudomonas is widely known as a model microorganism for studying naphthalene degradation. The real-time PCR analysis with four representative genes showed that the microarray-based quantification was very consistent with real-time PCR (r 2 ‫؍‬ 0.74). In addition, application of the arrays to both polyaromatic-hydrocarbon-and benzene-toluene-ethylbenzene-xylene-contaminated and uncontaminated soils indicated that the developed microarrays appeared to be useful for profiling differences in microbial community structures. Our results indicate that this technology has potential as a specific, sensitive, and quantitative tool in revealing a comprehensive picture of the compositions of biodegradation genes and the microbial community in contaminated environments, although more work is needed to improve detection sensitivity.The transformation of environmental contaminants is a complex process that is influenced by the nature and amount of the contaminant present, the structure and dynamics of the indigenous microbial community, and the interplay of geochemical and biological factors at contaminated sites (1,14,26,36). A better understanding of the processes inherent in natural bioremediation requires, in part, a better understanding of microbial ecology. However, conventional molecular methods (PCR-based technologies, such as gene cloning, terminal-restriction fragment len...

Microarray technology provides the opportunity to identify thousands of microbial genes or populations simultaneously, but low microbial biomass often prevents application of this technology to many natural microbial communities. We developed a whole-community genome amplification-assisted microarray detection approach based on multiple displacement amplification. The representativeness of amplification was evaluated using several types of microarrays and quantitative indexes. Representative detection of individual genes or genomes was obtained with 1 to 100 ng DNA from individual or mixed genomes, in equal or unequal abundance, and with 1 to 500 ng community DNAs from groundwater. Lower concentrations of DNA (as low as 10 fg) could be detected, but the lower template concentrations affected the representativeness of amplification. Robust quantitative detection was also observed by significant linear relationships between signal intensities and initial DNA concentrations ranging from (i) 0.04 to 125 ng (r 2 ‫؍‬ 0.65 to 0.99) for DNA from pure cultures as detected by whole-genome open reading frame arrays, (ii) 0.1 to 1,000 ng (r 2 ‫؍‬ 0.91) for genomic DNA using community genome arrays, and (iii) 0.01 to 250 ng (r 2 ‫؍‬ 0.96 to 0.98) for community DNAs from ethanol-amended groundwater using 50-mer functional gene arrays. This method allowed us to investigate the oligotrophic microbial communities in groundwater contaminated with uranium and other metals. The results indicated that microorganisms containing genes involved in contaminant degradation and immobilization are present in these communities, that their spatial distribution is heterogeneous, and that microbial diversity is greatly reduced in the highly contaminated environment.Microorganisms play integral and often unique roles in ecosystem functions, yet we often know little about dominant populations that presumably perform these functions, nor do we know much about how these populations differ with habitat.

Accurate climate projections require an understanding of the effects of warming on ecological communities and the underlying mechanisms that drive them 1-3 . However, little is known about the effects of climate warming on the succession of microbial communities 4,5 . Here we examined the temporal succession of soil microbes in a long-term climate change experiment at a tall-grass prairie ecosystem. Experimental warming was found to significantly alter the community structure of bacteria and fungi. By determining the time-decay relationships and the paired differences of microbial communities under warming and ambient conditions, experimental warming was shown to lead to increasingly divergent succession of the soil microbial communities, with possibly higher impacts on fungi than bacteria. Variation partition-and null model-based analyses indicate that stochastic processes played larger roles than deterministic ones in explaining microbial community taxonomic and phylogenetic compositions. However, in warmed soils, the relative importance of stochastic processes decreased over time, indicating a potential deterministic environmental filtering elicited by warming. Although successional trajectories of microbial communities are difficult to predict under future climate change scenarios, their composition and structure are projected to be less variable due to warming-driven selection.