Micro-organisms play critical roles in many important biogeochemical processes in the Earth's biosphere. However, understanding and characterizing the functional capacity of microbial communities are still difficult due to the extremely diverse and often uncultivable nature of most micro-organisms. In this study, we developed a new functional gene array, GeoChip 4, for analysing the functional diversity, composition, structure, metabolic potential/activity and dynamics of microbial communities. GeoChip 4 contained approximately 82 000 probes covering 141 995 coding sequences from 410 functional gene families related to microbial carbon (C), nitrogen (N), sulphur (S), and phosphorus (P) cycling, energy metabolism, antibiotic resistance, metal resistance/reduction, organic remediation, stress responses, bacteriophage and virulence. A total of 173 archaeal, 4138 bacterial, 404 eukaryotic and 252 viral strains were targeted, providing the ability to analyse targeted functional gene families of micro-organisms included in all four domains. Experimental assessment using different amounts of DNA suggested that as little as 500 ng environmental DNA was required for good hybridization, and the signal intensities detected were well correlated with the DNA amount used. GeoChip 4 was then applied to study the effect of long-term warming on soil microbial communities at a Central Oklahoma site, with results indicating that microbial communities respond to long-term warming by enriching carbon degradation, nutrient cycling (nitrogen and phosphorous) and stress response gene families. To the best of our knowledge, GeoChip 4 is the most comprehensive functional gene array for microbial community analysis.
Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore the potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C-cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations, whereas ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by Canonical correspondence analysis, Mantel tests and the similarity tests that soil pH, temperature, NH 4 þ -N and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. On the basis of these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N-cycling genes and consequently microbe-mediated soil N dynamics.
Microbes play key roles in various biogeochemical processes, including carbon (C) and nitrogen (N) cycling. However, changes of microbial community at the functional gene level by livestock grazing, which is a global land-use activity, remain unclear. Here we use a functional gene array, GeoChip 4.0, to examine the effects of free livestock grazing on the microbial community at an experimental site of Tibet, a region known to be very sensitive to anthropogenic perturbation and global warming. Our results showed that grazing changed microbial community functional structure, in addition to aboveground vegetation and soil geochemical properties. Further statistical tests showed that microbial community functional structures were closely correlated with environmental variables, and variations in microbial community functional structures were mainly controlled by aboveground vegetation, soil C/N ratio, and NH 4 + -N. In-depth examination of N cycling genes showed that abundances of N mineralization and nitrification genes were increased at grazed sites, but denitrification and N-reduction genes were decreased, suggesting that functional potentials of relevant bioprocesses were changed. Meanwhile, abundances of genes involved in methane cycling, C fixation, and degradation were decreased, which might be caused by vegetation removal and hence decrease in litter accumulation at grazed sites. In contrast, abundances of virulence, stress, and antibiotics resistance genes were increased because of the presence of livestock. In conclusion, these results indicated that soil microbial community functional structure was very sensitive to the impact of livestock grazing and revealed microbial functional potentials in regulating soil N and C cycling, supporting the necessity to include microbial components in evaluating the consequence of land-use and/or climate changes.
A microbial electrolysis cell (MEC) is a bioelectrochemical system that can produce hydrogen from acetate at high hydrogen recoveries, but the composition and structure of the microbial communities in this system have not been extensively studied. We used a high throughput metagenomics technology (GeoChip) to examine the microbial community functional structure in MECs initially operated under different conditions. We found that startup conditions had little or no effect on reactor performance in terms of Coulombic efficiencies (CEs) and COD removals, somewhat greater effects on CO(2) and CH(4) production, and very large effects on hydrogen production. Hydrogen yields were generally higher for reactors that were always operated as MECs than those initially operated as MFCs. Hydrogen yields were nine times larger for MEC reactors with an applied voltage of 0.7 V (64%∼80% efficiencies) than 0.3 V (<7-8%), independent of startup conditions. GeoChip analysis revealed that the functional and phylogenetic diversity of MEC microbial communities after 4 months was quite high despite the use of only a single substrate (acetate). MECs with the largest hydrogen yields had the highest microbial diversity. Multivariate analyses showed that communities that developed in the MECs were well separated from those present under startup conditions, indicating reactor operation altered microbial community composition. Community shifts based on a Mantel test were significantly related to CEs and COD removals in these reactors, suggesting that there were significant changes in microbial community composition as a result of conditions that affected MEC performance. Common well-known exoelectrogenic bacteria (e.g., Geobacter, Shewanella, Desulfovibrio, and Anaeromyxobacter) were found in these systems, but their importance in determining reactor functional performance was not supported with a high confidence in our statistical analysis.
Whether and how CO2 and nitrogen (N) availability interact to influence carbon (C) cycling processes such as soil respiration remains a question of considerable uncertainty in projecting future C–climate feedbacks, which are strongly influenced by multiple global change drivers, including elevated atmospheric CO2 concentrations (eCO2) and increased N deposition. However, because decades of research on the responses of ecosystems to eCO2 and N enrichment have been done largely independently, their interactive effects on soil respiratory CO2 efflux remain unresolved. Here, we show that in a multifactor free-air CO2 enrichment experiment, BioCON (Biodiversity, CO2, and N deposition) in Minnesota, the positive response of soil respiration to eCO2 gradually strengthened at ambient (low) N supply but not enriched (high) N supply for the 12-y experimental period from 1998 to 2009. In contrast to earlier years, eCO2 stimulated soil respiration twice as much at low than at high N supply from 2006 to 2009. In parallel, microbial C degradation genes were significantly boosted by eCO2 at low but not high N supply. Incorporating those functional genes into a coupled C–N ecosystem model reduced model parameter uncertainty and improved the projections of the effects of different CO2 and N levels on soil respiration. If our observed results generalize to other ecosystems, they imply widely positive effects of eCO2 on soil respiration even in infertile systems.
A novel Shigella strain (Shigella flexneri G3) showing high cellulolytic activity under mesophilic, anaerobic conditions was isolated and characterized. The bacterium is Gram negative, short rod shaped, and nonmotile and displays effective production of glucose, cellobiose, and other oligosaccharides from cellulose (Avicel PH-101) under optimal conditions (40°C and pH 6.5). Approximately 75% of the cellulose was hydrolyzed in modified ATCC 1191 medium containing 0.3% cellulose, and the oligosaccharide production yield and specific production rate reached 375 mg g Avicel ؊1 and 6.25 mg g Avicel ؊1 h ؊1 , respectively, after a 60-hour incubation. To our knowledge, this represents the highest oligosaccharide yield and specific rate from cellulose for mesophilic bacterial monocultures reported so far. The results demonstrate that S. flexneri G3 is capable of rapid conversion of cellulose to oligosaccharides, with potential biofuel applications under mesophilic conditions.Lignocellulosic biomass is abundant in nature, as well as in agricultural, forestry, and municipal wastes, and can be used as an excellent bioconversion feedstock. Biomass-derived saccharides, such as glucose, cellobiose, and other minor sugars, can be readily fermented by appropriate microbes into bioenergy products, such as hydrogen, ethanol, biodiesel, and other commodity chemicals. However, the high cost of converting biomass to sugars is the primary factor impeding establishment of a cellulosic-biofuels industry (24, 40). Lignocellulosic biofuels can be competitive on an industrial scale if efficient technologies can be developed (29,39). Currently, the most efficient process for utilization of cellulose as a feed stock is either a three-step process (separate hydrolysis and fermentation [SHF]) involving separate pretreatment, cellulose hydrolysis (i.e., saccharification), and hexose and pentose fermentation steps or a two-step process (simultaneous saccharification and fermentation [SSF]) involving separate pretreatment and simultaneous saccharification of hexose and pentose fermentation (48, 64). Combining hydrolysis of cellulose with simultaneous fermentation of hexose and pentose in a single process, i.e., direct microbial conversion (DMC), is an ideal strategy for converting cellulosic biomass to ethanol. However, no single microorganism/community can implement DMC with high efficiency (67). In any of these configurations, rapid and efficient saccharification is critical for developing competitive biotechnologies for cellulosic-biofuel production.In nature, cellulose is hydrolyzed to oligosaccharides by microorganisms, mainly fungi (e.g., brown-, white-, and soft-rot fungi) and bacteria (e.g., Clostridium and Cellulomonas), which produce either free cellulolytic enzymes or extracellular enzyme complexes known as cellulosomes (12). Many white-rot Basidiomycetes and some Actinomycetes have been employed for hydrolyzing lignocellulosic materials. For example, Trichoderma reesei has shown the highest cellulolytic activity currently known (27)....
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