Methylmercury is a potent neurotoxin produced in natural environments from inorganic mercury by anaerobic bacteria. However, until now the genes and proteins involved have remained unidentified. Here, we report a two-gene cluster, hgcA and hgcB, required for mercury methylation by Desulfovibrio desulfuricans ND132 and Geobacter sulfurreducens PCA. In either bacterium, deletion of hgcA, hgcB, or both genes abolishes mercury methylation. The genes encode a putative corrinoid protein, HgcA, and a 2[4Fe-4S] ferredoxin, HgcB, consistent with roles as a methyl carrier and an electron donor required for corrinoid cofactor reduction, respectively. Among bacteria and archaea with sequenced genomes, gene orthologs are present in confirmed methylators but absent in nonmethylators, suggesting a common mercury methylation pathway in all methylating bacteria and archaea sequenced to date.
Microbial mercury (Hg) methylation transforms a toxic trace metal into the highly bioaccumulated neurotoxin methylmercury (MeHg). The lack of a genetic marker for microbial MeHg production has prevented a clear understanding of Hg-methylating organism distribution in nature. Recently, a specific gene cluster (hgcAB) was linked to Hg methylation in two bacteria.1 Here we test if the presence of hgcAB orthologues is a reliable predictor of Hg methylation capability in microorganisms, a necessary confirmation for the development of molecular probes for Hg-methylation in nature. Although hgcAB orthologues are rare among all available microbial genomes, organisms are much more phylogenetically and environmentally diverse than previously thought. By directly measuring MeHg production in several bacterial and archaeal strains encoding hgcAB, we confirmed that possessing hgcAB predicts Hg methylation capability. For the first time, we demonstrated Hg methylation in a number of species other than sulfate- (SRB) and iron- (FeRB) reducing bacteria, including methanogens, and syntrophic, acetogenic, and fermentative Firmicutes. Several of these species occupy novel environmental niches for Hg methylation, including methanogenic habitats such as rice paddies, the animal gut, and extremes of pH and salinity. Identification of these organisms as Hg methylators now links methylation to discrete gene markers in microbial communities.
To determine the potential of DNA array technology for assessing functional gene diversity and distribution, a prototype microarray was constructed with genes involved in nitrogen cycling: nitrite reductase (nirS and nirK) genes, ammonia mono-oxygenase (amoA) genes, and methane mono-oxygenase (pmoA) genes from pure cultures and those cloned from marine sediments. In experiments using glass slide microarrays, genes possessing less than 80 to 85% sequence identity were differentiated under hybridization conditions of high stringency (65°C). The detection limit for nirS genes was approximately 1 ng of pure genomic DNA and 25 ng of soil community DNA using our optimized protocol. A linear quantitative relationship (r 2 ؍ 0.89 to 0.94) was observed between signal intensity and target DNA concentration over a range of 1 to 100 ng for genomic DNA (or genomic DNA equivalent) from both pure cultures and mixed communities. However, the quantitative capacity of microarrays for measuring the relative abundance of targeted genes in complex environmental samples is less clear due to divergent target sequences. Sequence divergence and probe length affected hybridization signal intensity within a certain range of sequence identity and size, respectively. This prototype functional gene array did reveal differences in the apparent distribution of nir and amoA and pmoA gene families in sediment and soil samples. Our results indicate that glass-based microarray hybridization has potential as a tool for revealing functional gene composition in natural microbial communities; however, more work is needed to improve sensitivity and quantitation and to understand the associated issue of specificity.
Recovery of mRNA from environmental samples for measurement of in situ metabolic activities is a significant challenge. A robust, simple, rapid, and effective method was developed for simultaneous recovery of both RNA and DNA from soils of diverse composition by adapting our previous grinding-based cell lysis method (Zhou et al., Appl. Environ. Microbiol. 62:316-322, 1996) for DNA extraction. One of the key differences is that the samples are ground in a denaturing solution at a temperature below 0°C to inactivate nuclease activity. Two different methods were evaluated for separating RNA from DNA. Among the methods examined for RNA purification, anion exchange resin gave the best results in terms of RNA integrity, yield, and purity. With the optimized protocol, intact RNA and high-molecular-weight DNA were simultaneously recovered from 19 soil and stream sediment samples of diverse composition. The RNA yield from these samples ranged from 1.4 to 56 g g of soil ؊1 dry weight), whereas the DNA yield ranged from 23 to 435 g g ؊1 . In addition, studies with the same soil sample showed that the DNA yield was, on average, 40% higher than that in our previous procedure and 68% higher than that in a commercial bead milling method. For the majority of the samples, the DNA and RNA recovered were of sufficient purity for nuclease digestion, microarray hybridization, and PCR or reverse transcription-PCR amplification.The application of culture-independent nucleic acid techniques has greatly advanced the detection and identification of microorganisms in natural environments (2,4,17,39,42,48). However, successful application of molecular techniques relies on effective recovery of nucleic acids from environmental samples. A variety of methods have been developed and used to directly recover nucleic acids from environmental samples (1,16,20,23,24,27,30,32,38,40,42,43,45,49), but most of the methods are not developed for recovering mRNA from environmental samples. Since RNA is not stable, recovery of intact mRNA from environmental samples is a great challenge.The RNA/DNA ratio is an important indicator of the metabolic status of bacterial (8,19,21,28,34) and microbial (10, 11) communities. Such a ratio can allow researchers to address questions concerning whether the response of a microbial community to environmental change is due to a population increase or activity increase. To obtain a reliable RNA/DNA ratio, both RNA and DNA should be recovered from environmental samples without bias. However, unbiased recovery of both DNA and RNA is a significant challenge due to microbial heterogeneity in natural environments, variations in experimental conditions, and differences in interactions of DNA and RNA molecules with environmental matrices. Although it is difficult to eliminate all sources of variation, variation originating from microbial heterogeneity and extraction conditions can be minimized if the RNA and DNA are simultaneously extracted from the same fraction of the sample. Also, in many cases (e.g., marine sediment samples,...
Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive.
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