As the second-largest terrestrial carbon (C) flux, soil respiration (R_S) has been stimulated by climate warming. However, the magnitude and dynamics of such stimulations of soil respiration are highly uncertain at the global scale, undermining our confidence in future climate projections. Here, we present an analysis of global R_S observations from 1987-2016. R_S increased (P < 0.001) at a rate of 27.66 g C m^-2 yr^-2 (equivalent to 0.161 Pg C yr^-2) in 1987-1999 globally but became unchanged in 2000-2016, which were related to complex temporal variations of temperature anomalies and soil C stocks. However, global heterotrophic respiration (R_h) derived from microbial decomposition of soil C increased in 1987-2016 (P < 0.001), suggesting accumulated soil C losses. Given the warmest years on records after 2015, our modeling analysis shows a possible resuscitation of global R_S rise. This study of naturally occurring shifts in R_S over recent decades has provided invaluable insights for designing more effective policies addressing future climate challenges.

Soil carbon (C) and nitrogen (N) cycles and their complex responses to environmental changes have received increasing attention. However, large uncertainties in model predictions remain, partially due to the lack of explicit representation and parameterization of microbial processes. One great challenge is to effectively integrate rich microbial functional traits into ecosystem modeling for better predictions. Here, using soil enzymes as indicators of soil function, we developed a competitive dynamic enzyme allocation scheme and detailed enzyme-mediated soil inorganic N processes in the Microbial-ENzyme Decomposition (MEND) model. We conducted a rigorous calibration and validation of MEND with diverse soil C-N fluxes, microbial C:N ratios, and functional gene abundances from a 12-year CO₂  × N grassland experiment (BioCON) in Minnesota, USA. In addition to accurately simulating soil CO₂ fluxes and multiple N variables, the model correctly predicted microbial C:N ratios and their negative response to enriched N supply. Model validation further showed that, compared to the changes in simulated enzyme concentrations and decomposition rates, the changes in simulated activities of eight C-N-associated enzymes were better explained by the measured gene abundances in responses to elevated atmospheric CO₂ concentration. Our results demonstrated that using enzymes as indicators of soil function and validating model predictions with functional gene abundances in ecosystem modeling can provide a basis for testing hypotheses about microbially mediated biogeochemical processes in response to environmental changes. Further development and applications of the modeling framework presented here will enable microbial ecologists to address ecosystem-level questions beyond empirical observations, toward more predictive understanding, an ultimate goal of microbial ecology.

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.

Anaerobic digestion is one of the most successful waste management strategies worldwide, wherein microorganisms play an essential role in reducing organic pollutants and producing renewable energy. However, variations of microbial community in full-scale anaerobic digesters, particularly functional groups relevant to biogas production, remain elusive. Here, we examined microbial community in a year-long monthly time series of 3 full-scale anaerobic digesters. We observed substantial diversification in community composition, with only a few abundant OTUs (e.g. Clostridiales, Anaerolineaceae and Methanosaeta) persistently present across different samples. Similarly, there were high variations in relative abundance of methanogenic archaea and methanogenic genes, which were positively correlated (r² = 0.530, P < 0.001). Variations of methanogens explained 55.7% of biogas producing rates, much higher than the explanatory percentage of environmental parameters (16.4%). Hydrogenotrophic methanogens, especially abundant Methanomicrobiales taxa, were correlated with biogas production performance (r = 0.665, P < 0.001) and nearly all methanogenic genes (0.430 < r < 0.735, P < 0.012). Given that methanogenic archaea or genes are well established for methanogenesis, we conclude that high variations in methanogenic traits (e.g. taxa or genes) are responsible for biogas production variations in full-scale anaerobic digesters.

Introduction

Petroleum pollution resulting from spills and leakages in oil refinery areas has been a significant environmental concern for decades. Despite this, the effects of petroleum pollutants on soil microbial communities and their potential for pollutant biodegradation still required further investigation.

Methods

In this study, we collected 75 soil samples from 0 to 5 m depths of 15 soil profiles in an abandoned refinery to analyze the effect of petroleum pollution on soil microbial diversity, community structure, and network co-occurrence patterns.

Results

Our results suggested soil microbial a-diversity decreased under high C10-C40 levels, coupled with significant changes in the community structure of soil profiles. However, soil microbial network complexity increased with petroleum pollution levels, suggesting more complex microbial potential interactions. A module specific for methane and methyl oxidation was also found under high C10-C40 levels of the soil profile, indicating stronger methanotrophic and methylotrophic metabolic activities at the heavily polluted soil profile.

Discussion

The increased network complexity observed may be due to more metabolic pathways and processes, as well as increased microbial interactions during these processes. These findings highlight the importance of considering both microbial diversity and network complexity in assessing the effects of petroleum pollution on soil ecosystems.

Cancer stem cells (CSCs) are considered to be the cause of tumor initiation, metastasis and recurrence. Additionally, CSCs are responsible for the failure of chemotherapy and radiotherapy. The isolation and identification of CSCs is crucial for facilitating the monitoring, therapy or prevention of cancer. We aimed to identify esophageal squamous cell carcinoma (ESCC) stem-like cells, the epigenetic mechanism and identify novel biomarkers for targeting ESCC CSCs. Sixty-three paired ESCC tissues and adjacent non-cancerous tissues were included in this study. CD271, which was identified as the CSC marker for melanoma, was assessed using quantitative PCR (qPCR). Using flow cytometry, we isolated CD271+ cells comprising 7.5% of cancer cells from the KYSE70 cell line. Sphere formation and anchorage-independent growth were analyzed in CD271+ and CD271- cancer cells, respectively. qPCR was used to detect stem-related genes and CCK-8 was performed to analyze the sensitivity to chemotherapy in the two groups. Bisulfite genomic sequencing was used to analyze the methylation status. CD271 expression was significantly higher in ESCC tissues than in adjacent non-cancerous tissues. Compared with CD271- cancer cells, CD271+ cancer cells showed a higher ability of sphere and colony formation, a high level expression of stem-related gene, and resistance to chemotherapy. The expression of CD271 was induced by a demethylation agent. In conclusion, CD271+ ESCC cells possess stem-like properties. CD271 can potentially act as a prognostic marker for ESCC, whose expression is regulated epigenetically.

Nanoscale size-effects drastically alter the fundamental properties of semiconductors. Here, we investigate the dominant role of quantum confinement in the field-effect device properties of free-standing InAs nanomembranes with varied thicknesses of 5-50 nm. First, optical absorption studies are performed by transferring InAs "quantum membranes" (QMs) onto transparent substrates, from which the quantized sub-bands are directly visualized. These sub-bands determine the contact resistance of the system with the experimental values consistent with the expected number of quantum transport modes available for a given thickness. Finally, the effective electron mobility of InAs QMs is shown to exhibit anomalous field- and thickness-dependences that are in distinct contrast to the conventional MOSFET models, arising from the strong quantum confinement of carriers. The results provide an important advance towards establishing the fundamental device physics of 2-D semiconductors.

Soil types heavily influence ecological dynamics. It remains controversial to what extent soil types shape microbial responses to land management changes, largely due to lack of in-depth comparison across various soil types. Here, we collected samples from three major zonal soil types spanning from cold temperate to subtropical climate zones. We examined bacterial and fungal community structures, as well as microbial functional genes. Different soil types had distinct microbial biomass levels and community compositions. Five years of maize cropping (growing corn or maize) changed the bacterial community composition of the Ultisol soil type and the fungal composition of the Mollisol soil type but had little effect on the microbial composition of the Inceptisol soil type. Meanwhile, 5 years of fertilization resulted in soil acidification. Microbial compositions of the Mollisol and Ultisol, but not the Inceptisol, were changed and correlated (P < 0.05) with soil pH. These results demonstrated the critical role of soil type in determining microbial responses to land management changes. We also found that soil nitrification potentials correlated with the total abundance of nitrifiers and that soil heterotrophic respiration correlated with the total abundance of carbon degradation genes, suggesting that changes in microbial community structure had altered ecosystem processes. IMPORTANCE Microbial communities are essential drivers of soil functional processes such as nitrification and heterotrophic respiration. Although there is initial evidence revealing the importance of soil type in shaping microbial communities, there has been no in-depth, comprehensive survey to robustly establish it as a major determinant of microbial community composition, functional gene structure, or ecosystem functioning. We examined bacterial and fungal community structures using Illumina sequencing, microbial functional genes using GeoChip, microbial biomass using phospholipid fatty acid analysis, as well as functional processes of soil nitrification potential and CO₂ efflux. We demonstrated the critical role of soil type in determining microbial responses to land use changes at the continental level. Our findings underscore the inherent difficulty in generalizing ecosystem responses across landscapes and suggest that assessments of community feedback must take soil types into consideration. Author Video: An author video summary of this article is available.

Bacteria are one of the most abundant and diverse groups of micro‐organisms and mediate many critical terrestrial ecosystem processes. Despite the crucial ecological role of bacteria, our understanding of their large‐scale biogeography patterns across forests, and the processes that determine these patterns lags significantly behind that of macroorganisms. Here, we evaluated the geographic distributions of bacterial diversity and their driving factors across nine latitudinal forests along a 3,700‐km north–south transect in eastern China, using high‐throughput 16S rRNA gene sequencing. Four of 32 phyla detected were dominant: Acidobacteria, Actinobacteria, Alphaproteobacteria and Chloroflexi (relative abundance > 5%). Significant increases in bacterial richness and phylogenetic diversity were observed for temperate forests compared with subtropical or tropical forests. The soil organic matter (SOM) mineralisation rate (SOMₘᵢₙ, an index of SOM availability) explained the largest significant variations in bacterial richness. Variation partition analysis revealed that the bacterial community structure was closely correlated with environmental variables and geographic distance, which together explained 80.5% of community variation. Among all environmental factors, climatic features (MAT and MAP) were the best predictors of the bacterial community structure, whereas soil pH and SOMₘᵢₙ emerged as the most important edaphic drivers of the bacterial community structure. Plant functional traits (community weighted means of litter N content) and diversity resulted in weak but significant correlations with the bacterial community structure. Our findings provide new evidence of bacterial biogeography patterns from tropical to cold temperate forests. Additionally, the results indicated a close linkage among soil bacterial diversity, climate and SOM decomposition, which is critical for predicting continental‐scale responses under future climate change scenarios and promoting sustainable forest ecosystem services. A plain language summary is available for this article.

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.