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Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer-resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer-resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

The susceptibility of soil organic carbon (SOC) in tundra to microbial decomposition under warmer climate scenarios potentially threatens a massive positive feedback to climate change, but the underlying mechanisms of stable SOC decomposition remain elusive. Herein, Alaskan tundra soils from three depths (a fibric O horizon with litter and course roots, an O horizon with decomposing litter and roots, and a mineral-organic mix, laying just above the permafrost) were incubated. Resulting respiration data were assimilated into a 3-pool model to derive decomposition kinetic parameters for fast, slow, and passive SOC pools. Bacterial, archaeal, and fungal taxa and microbial functional genes were profiled throughout the 3-year incubation. Correlation analyses and a Random Forest approach revealed associations between model parameters and microbial community profiles, taxa, and traits. There were more associations between the microbial community data and the SOC decomposition parameters of slow and passive SOC pools than those of the fast SOC pool. Also, microbial community profiles were better predictors of model parameters in deeper soils, which had higher mineral contents and relatively greater quantities of old SOC than in surface soils. Overall, our analyses revealed the functional potential of microbial communities to decompose tundra SOC through a suite of specialized genes and taxa. These results portray divergent strategies by which microbial communities access SOC pools across varying depths, lending mechanistic insights into the vulnerability of what is considered stable SOC in tundra regions.

While functional gene arrays (FGAs) have greatly expanded our understanding of complex microbial systems, specificity, sensitivity, and quantitation challenges remain. We developed a new generation of FGA, GeoChip 5.0, using the Agilent platform. Two formats were created, a smaller format (GeoChip 5.0S), primarily covering carbon-, nitrogen-, sulfur-, and phosphorus-cycling genes and others providing ecological services, and a larger format (GeoChip 5.0M) containing the functional categories involved in biogeochemical cycling of C, N, S, and P and various metals, stress response, microbial defense, electron transport, plant growth promotion, virulence, gyrB, and fungus-, protozoan-, and virus-specific genes. GeoChip 5.0M contains 161,961 oligonucleotide probes covering >365,000 genes of 1,447 gene families from broad, functionally divergent taxonomic groups, including bacteria (2,721 genera), archaea (101 genera), fungi (297 genera), protists (219 genera), and viruses (167 genera), mainly phages. Computational and experimental evaluation indicated that designed probes were highly specific and could detect as little as 0.05 ng of pure culture DNAs within a background of 1 μg community DNA (equivalent to 0.005% of the population). Additionally, strong quantitative linear relationships were observed between signal intensity and amount of pure genomic (∼99% of probes detected; r > 0.9) or soil (∼97%; r > 0.9) DNAs. Application of the GeoChip to a contaminated groundwater microbial community indicated that environmental contaminants (primarily heavy metals) had significant impacts on the biodiversity of the communities. This is the most comprehensive FGA to date, capable of directly linking microbial genes/populations to ecosystem functions.IMPORTANCE The rapid development of metagenomic technologies, including microarrays, over the past decade has greatly expanded our understanding of complex microbial systems. However, because of the ever-expanding number of novel microbial sequences discovered each year, developing a microarray that is representative of real microbial communities, is specific and sensitive, and provides quantitative information remains a challenge. The newly developed GeoChip 5.0 is the most comprehensive microarray available to date for examining the functional capabilities of microbial communities important to biogeochemistry, ecology, environmental sciences, and human health. The GeoChip 5 is highly specific, sensitive, and quantitative based on both computational and experimental assays. Use of the array on a contaminated groundwater sample provided novel insights on the impacts of environmental contaminants on groundwater microbial communities.

Background: Tobacco (Nicotiana tabacum L.) is an important economic crop, and the use of plant growth-promoting bacteria (PGPB) to enhance its growth and suppress soil-borne diseases has garnered considerable research interest. However, the potential of yeast to augment the growth-promoting and disease-suppressing effects of PGPB on tobacco remains unclear. Methods: This study investigated the effects of Pichia sp. microbial fertilizer (J1), PGPB- Klebsiella oxytoca microbial fertilizer (ZS4), and their composite fertilizer (JZ) on tobacco growth indexes, soil properties, and soil microbial community through a pot experiment. Additionally, field experiments were conducted to further assess the efficacy of the composite microbial fertilizer on tobacco growth and the incidences of soil-borne diseases, including tobacco bacterial wilt (TBW) and tobacco black shank (TBS). Results and discussions: In the pot experiment, application of the microbial fertilizers significantly enhanced soil organic matter (OM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available phosphorus (AP), and available potassium (AK) levels. Compared to the control group (CK), J1, ZS4, and JZ microbial fertilizers significantly promoted tobacco growth, and the composite microbial fertilizers demonstrated superior to the individual microbial fertilizers. We found that the application of microbial fertilizer led to significant alterations in the structure and composition of the bacterial and fungal communities based on the high-throughput sequencing of 16S rRNA and internal transcribed spacer (ITS) regions. The bacterial and fungal diversity indexes showed a decreasing trend. Key microorganisms such as Sphingomonas , Kitasatospora , Nitrosospira , Mortierella , and Trichoderma were identified as influential in regulating soil physicochemical parameters to enhance tobacco growth. Functional prediction further demonstrated a significant increase in the relative abundances of certain enzymes, including Alkaline phosphatase, 1-aminocyclopropane-1-carboxylate deaminase (ACC deaminase), and Peroxidase, as well as antimicrobial substances like Tetracycline, Isoquinoline alkaloid, and Phenylpropanoids, following inoculation with the fertilizer. Besides, field experiments revealed that the JZ fertilizer significantly promoted tobacco growth and reduced the incidence of TBW and TBS, indicating its potential for further application in tobacco cultivation. [ABSTRACT FROM AUTHOR]

Temperature is an important correlate of global patterns of biodiversity, yet the mechanisms driving these relationships are not well understood. Taxa-area relationships (TARs) have been intensively examined, but the effects of temperature on TARs, particularly for microbial communities, are largely undocumented. Here we present a continental-scale description of temperature-dependent nested TARs of microbial communities (bacteria and archaea) from soils of six forest sites spanning a temperature gradient from subalpine Colorado to tropical Panama. Our results revealed that spatial scaling rates (z-values) of microbial communities varied with both taxonomic resolutions and phylogenetic groups. Additionally, microbial TAR z-values increased with temperature (r = 0.739, P < 0.05), but were not correlated with other environmental variables tested (P > 0.05), indicating that microbial spatial scaling rate is temperature-dependent. Understanding how temperature affects the spatial scaling of microbial biodiversity is of fundamental importance for preservation of soil biodiversity and management of ecosystems.

Land-cover change has long been recognized as having marked effect on the amount of soil organic carbon (SOC). However, the microbially mediated processes and mechanisms on SOC are still unclear. In this study, the soil samples in a degenerative succession from alpine meadow to alpine steppe meadow in the Qinghai-Tibetan Plateau were analysed using high-throughput technologies, including Illumina sequencing and geochip functional gene arrays. The soil microbial community structure and diversity were significantly (p