Unraveling the drivers of community structure and succession in response to environmental change is a central goal in ecology. Although the mechanisms shaping community structure have been intensively examined, those controlling ecological succession remain elusive. To understand the relative importance of stochastic and deterministic processes in mediating microbial community succession, a unique framework composed of four different cases was developed for fluidic and nonfluidic ecosystems. The framework was then tested for one fluidic ecosystem: a groundwater system perturbed by adding emulsified vegetable oil (EVO) for uranium immobilization. Our results revealed that groundwater microbial community diverged substantially away from the initial community after EVO amendment and eventually converged to a new community state, which was closely clustered with its initial state. However, their composition and structure were significantly different from each other. Null model analysis indicated that both deterministic and stochastic processes played important roles in controlling the assembly and succession of the groundwater microbial community, but their relative importance was time dependent. Additionally, consistent with the proposed conceptual framework but contradictory to conventional wisdom, the community succession responding to EVO amendment was primarily controlled by stochastic rather than deterministic processes. During the middle phase of the succession, the roles of stochastic processes in controlling community composition increased substantially, ranging from 81.3% to 92.0%. Finally, there are limited successional studies available to support different cases in the conceptual framework, but further well-replicated explicit time-series experiments are needed to understand the relative importance of deterministic and stochastic processes in controlling community succession.community assembly | disturbances | metagenomics | GeoChip | remediation
Owing to their vast diversity and as-yet uncultivated status, detection, characterization and quantification of microorganisms in natural settings are very challenging, and linking microbial diversity to ecosystem processes and functions is even more difficult. Microarray-based genomic technology for detecting functional genes and processes has a great promise of overcoming such obstacles. Here, a novel comprehensive microarray, termed GeoChip, has been developed, containing 24 243 oligonucleotide (50 mer) probes and covering 410 000 genes in 4150 functional groups involved in nitrogen, carbon, sulfur and phosphorus cycling, metal reduction and resistance, and organic contaminant degradation. The developed GeoChip was successfully used for tracking the dynamics of metal-reducing bacteria and associated communities for an in situ bioremediation study. This is the first comprehensive microarray currently available for studying biogeochemical processes and functional activities of microbial communities important to human health, agriculture, energy, global climate change, ecosystem management, and environmental cleanup and restoration. It is particularly useful for providing direct linkages of microbial genes/populations to ecosystem processes and functions.
Deinococcus radiodurans R1 (DEIRA) is a bacterium best known for its extreme resistance to the lethal effects of ionizing radiation, but the molecular mechanisms underlying this phenotype remain poorly understood. To define the repertoire of DEIRA genes responding to acute irradiation (15 kGy), transcriptome dynamics were examined in cells representing early, middle, and late phases of recovery by using DNA microarrays covering Ϸ94% of its predicted genes. At least at one time point during DEIRA recovery, 832 genes (28% of the genome) were induced and 451 genes (15%) were repressed 2-fold or more. The expression patterns of the majority of the induced genes resemble the previously characterized expression profile of recA after irradiation. DEIRA recA, which is central to genomic restoration after irradiation, is substantially up-regulated on DNA damage (early phase) and down-regulated before the onset of exponential growth (late phase). Many other genes were expressed later in recovery, displaying a growth-related pattern of induction. Genes induced in the early phase of recovery included those involved in DNA replication, repair, and recombination, cell wall metabolism, cellular transport, and many encoding uncharacterized proteins. Collectively, the microarray data suggest that DEIRA cells efficiently coordinate their recovery by a complex network, within which both DNA repair and metabolic functions play critical roles. Components of this network include a predicted distinct ATP-dependent DNA ligase and metabolic pathway switching that could prevent additional genomic damage elicited by metabolism-induced free radicals.T he Gram-positive aerobic bacterium Deinococcus radiodurans R1 (DEIRA) has an extraordinary resistance to ␥-radiation and a wide range of other DNA-damaging conditions, including desiccation and oxidizing agents (1, 2). Ionizing radiation induces DNA double-stranded breaks (DSBs) that are the most lethal form of DNA damage (3). After acute exposures to 10 kGy, early stationary phase (ESP) DEIRA can reassemble its 3.285-Mbp genome, which consists of four haploid genomic copies per cell (4), from hundreds of DNA DSB fragments without lethality or induced mutagenesis (5, 6). Also remarkable is DEIRA's ability to grow at 60 Gy͞h without any discernable effect on its growth rate (7). Because most organisms, generally, can tolerate so few DSBs (8), radiationinduced DSBs and their repair have been difficult to study. In DEIRA, however, there are so many DSBs in fully viable irradiated cells after high-dose irradiation that the steps in DSB repair can be monitored directly in mass culture (5, 9-11). This characteristic has been exploited and used to examine the timing of DNA recombination (5, 10, 12) after high-dose irradiation and has revealed the sequential action of RecA-independent and -dependent pathways during repair (11).Comparative genomic and experimental analyses support the view that DEIRA's extreme radiation resistance phenotype is complex, likely determined collectively by an assortment o...
To begin defining the key determinants that drive microbial community structure in soil, we examined 29 soil samples from four geographically distinct locations taken from the surface, vadose zone, and saturated subsurface using a small-subunit rRNA-based cloning approach. While microbial communities in low-carbon, saturated, subsurface soils showed dominance, microbial communities in low-carbon surface soils showed remarkably uniform distributions, and all species were equally abundant. Two diversity indices, the reciprocal of Simpson's index (1/D) and the log series index, effectively distinguished between the dominant and uniform diversity patterns. For example, the uniform profiles characteristic of the surface communities had diversity index values that were 2 to 3 orders of magnitude greater than those for the high-dominance, saturated, subsurface communities. In a site richer in organic carbon, microbial communities consistently exhibited the uniform distribution pattern regardless of soil water content and depth. The uniform distribution implies that competition does not shape the structure of these microbial communities. Theoretical studies based on mathematical modeling suggested that spatial isolation could limit competition in surface soils, thereby supporting the high diversity and a uniform community structure. Carbon resource heterogeneity may explain the uniform diversity patterns observed in the high-carbon samples even in the saturated zone. Very high levels of chromium contamination (e.g., >20%) in the high-organic-matter soils did not greatly reduce the diversity. Understanding mechanisms that may control community structure, such as spatial isolation, has important implications for preservation of biodiversity, management of microbial communities for bioremediation, biocontrol of root diseases, and improved soil fertility.
Climate warming is increasingly leading to marked changes in plant and animal biodiversity, but it remains unclear how temperatures affect microbial biodiversity, particularly in terrestrial soils. Here we show that, in accordance with metabolic theory of ecology, taxonomic and phylogenetic diversity of soil bacteria, fungi and nitrogen fixers are all better predicted by variation in environmental temperature than pH. However, the rates of diversity turnover across the global temperature gradients are substantially lower than those recorded for trees and animals, suggesting that the diversity of plant, animal and soil microbial communities show differential responses to climate change. To the best of our knowledge, this is the first study demonstrating that the diversity of different microbial groups has significantly lower rates of turnover across temperature gradients than other major taxa, which has important implications for assessing the effects of human-caused changes in climate, land use and other factors.
Genetic heterogeneity of denitrifying bacteria in sediment samples from Puget Sound and two sites on the Washington continental margin was studied by PCR approaches amplifying nirK and nirS genes. These structurally different but functionally equivalent single-copy genes coding for nitrite reductases, a key enzyme of the denitrification process, were used as a molecular marker for denitrifying bacteria. nirS sequences could be amplified from samples of both sampling sites, whereas nirK sequences were detected only in samples from the Washington margin. To assess the underlying nir gene structure, PCR products of both genes were cloned and screened by restriction fragment length polymorphism (RFLP). Rarefraction analysis revealed a high level of diversity especially for nirS clones from Puget Sound and a slightly lower level of diversity for nirK and nirS clones from the Washington margin. One group dominated within nirK clones, but no dominance and only a few redundant clones were seen between sediment samples for nirS clones in both habitats. Hybridization and sequencing confirmed that all but one of the 228 putative nirS clones were nirS with levels of nucleotide identities as low as 45.3%. Phylogenetic analysis grouped nirS clones into three distinct subclusters within the nirS gene tree which corresponded to the two habitats from which they were obtained. These sequences had little relationship to any strain with known nirS sequences or to isolates (mostly close relatives of Pseudomonas stutzeri) from the Washington margin sediment samples. nirK clones were more closely related to each other than were the nirS clones, with 78.6% and higher nucleotide identities; clones showing only weak hybridization signals were not related to known nirK sequences. All nirK clones were also grouped into a distinct cluster which could not be placed with any strain with known nirK sequences. These findings show a very high diversity of nir sequences within small samples and that these novel nir clusters, some very divergent from known sequences, are not known in cultivated denitrifiers.Denitrification is a dissimilatory process where oxidized nitrogen compounds (NO 3 Ϫ and NO 2 Ϫ ) are used as alternative electron acceptors for energy production. Nitrogen oxides are reduced stepwise to gaseous end products (NO, N 2 O, and N 2 ) which are concomitantly released, leading to a loss of fixed nitrogen to the environment. In marine coastal sediments, 40 to 50% of external inputs of dissolved inorganic nitrogen are removed by denitrification (23), resulting in an unbalanced nitrogen budget in the ocean (5, 7). Accumulation of the intermediates NO and N 2 O contributes to global warming and the destruction of the ozone layer (6). Thus, the underlying communities of denitrifying bacteria and their responses to environmental conditions need to be understood. Commonly, 16S rDNA molecules are tools to investigate microbial communities which avoid limitations of culturability (9,11,16). Lately, several functional genes were shown to be us...
To determine the reproducibility and quantitation of the amplicon sequencing-based detection approach for analyzing microbial community structure, a total of 24 microbial communities from a long-term global change experimental site were examined. Genomic DNA obtained from each community was used to amplify 16S rRNA genes with two or three barcode tags as technical replicates in the presence of a small quantity (0.1% wt/wt) of genomic DNA from Shewanella oneidensis MR-1 as the control. The technical reproducibility of the amplicon sequencing-based detection approach is quite low, with an average operational taxonomic unit (OTU) overlap of 17.2% ± 2.3% between two technical replicates, and 8.2% ± 2.3% among three technical replicates, which is most likely due to problems associated with random sampling processes. Such variations in technical replicates could have substantial effects on estimating b-diversity but less on a-diversity. A high variation was also observed in the control across different samples (for example, 66.7-fold for the forward primer), suggesting that the amplicon sequencing-based detection approach could not be quantitative. In addition, various strategies were examined to improve the comparability of amplicon sequencing data, such as increasing biological replicates, and removing singleton sequences and less-representative OTUs across biological replicates. Finally, as expected, various statistical analyses with preprocessed experimental data revealed clear differences in the composition and structure of microbial communities between warming and non-warming, or between clipping and non-clipping. Taken together, these results suggest that amplicon sequencing-based detection is useful in analyzing microbial community structure even though it is not reproducible and quantitative. However, great caution should be taken in experimental design and data interpretation when the amplicon sequencing-based detection approach is used for quantitative analysis of the b-diversity of microbial communities.
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