Microbial resistance and resilience in response to environmental changes under the higher intensity of human activities than global average level

With the increasing intensity of global human activities, the ecosystem function, which is supported by the microbial community, will be dramatically changed and impaired. To investigate microbial resistance and resilience of microbial communities to human activities, we chose two typical types of human disturbances, urbanization, and reclamation under the higher intensity of human activities than the global average level. We examined microbial traits, including the abundance, diversity, phylogeny, and co‐occurrence interactions in soil microbial communities, together with the nitrification activities observed in the subtropical coastal ecosystem of the Pearl River Estuary and in soil microcosm experiments. Microbial communities were less resistant to the environmental changes caused by urbanization than to those caused by reclamation, which was significantly reflected in the nitrogen and/or carbon‐related patterns. However, most of the microbial traits could be recovered almost to the original level without significant differences in the microcosm after 40 days of incubation. The co‐occurrence interactions between nitrifiers and other microbial communities were dramatically changed and could not be completely recovered, but this change did not affect their nitrification activities for balancing the ammonium in the soil to the original level during the recovery stage, suggesting that the interactions between microbial communities might have fewer effects on their activities than previously thought. This study quantitatively demonstrated that microbial communities as a whole can recover to a status similar to the original state in a short time after the removal of stress at a large ecosystem scale even under the higher intensity of human activities than global average level in coastal ecosystems, which implied a strong recovery capacity of soil microbial community even after intense human disturbance.     

The role of competition versus cooperation in microbial community coalescence

New microbial communities often arise through the mixing of two or more separately assembled parent communities, a phenomenon that has been termed “community coalescence”. Understanding how the interaction structures of complex parent communities determine the outcomes of coalescence events is an important challenge. While recent work has begun to elucidate the role of competition in coalescence, that of cooperation, a key interaction type commonly seen in microbial communities, is still largely unknown. Here, using a general consumer-resource model, we study the combined effects of competitive and cooperative interactions on the outcomes of coalescence events. To do so, we simulate coalescence events between pairs of communities with different degrees of competition for shared carbon resources and cooperation through cross-feeding on leaked metabolic by-products (facilitation). We also study how structural and functional properties of post-coalescence communities evolve when they are subjected to repeated coalescence events. We find that in coalescence events, the less competitive and more cooperative parent communities contribute a higher proportion of species to the new community because of their superior ability to deplete resources and resist invasions. Consequently, when a community is subjected to repeated coalescence events, it gradually evolves towards being less competitive and more cooperative, as well as more speciose, robust and efficient in resource use. Encounters between microbial communities are becoming increasingly frequent as a result of anthropogenic environmental change, and there is great interest in how the coalescence of microbial communities affects environmental and human health. Our study provides new insights into the mechanisms behind microbial community coalescence, and a framework to predict outcomes based on the interaction structures of parent communities.     

From molecules to dynamic biological communities

Microbial ecology is flourishing, and in the process, is making contributions to how the ecology and biology of large organisms is understood. Ongoing advances in sequencing technology and computational methods have enabled the collection and analysis of vast amounts of molecular data from diverse biological communities. While early studies focused on cataloguing microbial biodiversity in environments ranging from simple marine ecosystems to complex soil ecologies, more recent research is concerned with community functions and their dynamics over time. Models and concepts from traditional ecology have been used to generate new insight into microbial communities, and novel system-level models developed to explain and predict microbial interactions. The process of moving from molecular inventories to functional understanding is complex and challenging, and never more so than when many thousands of dynamic interactions are the phenomena of interest. We outline the process of how epistemic transitions are made from producing catalogues of molecules to achieving functional and predictive insight, and show how those insights not only revolutionize what is known about biological systems but also about how to do biology itself. Examples will be drawn primarily from analyses of different human microbiota, which are the microbial consortia found in and on areas of the human body, and their associated microbiomes (the genes of those communities). Molecular knowledge of these microbiomes is transforming microbiological knowledge, as well as broader aspects of human biology, health and disease.     

长期不同施肥制度下几种土壤微生物学特征变化

 为阐明土壤微生物对土壤健康的生物指示功能, 以国家褐潮土肥力与肥料效益监测基地的长期肥料试验为平台, 应用BIOLOG ECO微平板培养法与常规分析法研究了长期施肥15年后不同施肥制度对土壤微生物生物量、活性、群落代谢功能多样性及土壤肥力的影响。研究结果表明, 与对照(CK)相比, 长期化肥与有机肥配施土壤中土壤有机质(SOM)、全氮(STN)、全磷(STP)含量升高, 土壤C/N与pH值降低, 土壤微生物量碳(Soil microbial biomass carbon, SMBC)、生物微生物量氮(Soil microbial biomass nitrogen, SMBN)、微生物商(qMB)及脲酶(Urease)活性升高, BIOLOG ECO微平板平均颜色变化率(Average well color development, AWCD)、土壤微生物代谢功能多样性指数变化不明显。和长期单施化肥处理(NPK)相比, 长期化肥与有机肥配施处理中上述几种微生物学特征(SMBC、SMBN、qMB、Urease及AWCD、代谢功能多样性指数)均呈极显著增加。NPK处理与CK相比虽然SOM、STN、STP含量稍有升高, 土壤C/N与pH值降低, SMBC、SMBN、qMB及Urease活性增高, 但是AWCD、土壤微生物代谢功能多样性指数却显著下降。过氧化氢酶活性(Catalase)在各处理土壤中的差异不显著。土壤微生物碳源利用的主成分分析表明, 长期不同施肥各处理在土壤微生物利用碳源的种类和能力上有差异。此试验说明, 土壤微生物受农业管理措施和多种环境因素的影响, 土壤微生物学特征可作为土壤质量的敏感指标, 为提高作物产量、增强肥力提供理论参考。     

Short pyrosequencing reads suffice for accurate microbial community analysis

Pyrosequencing technology allows us to characterize microbial communities using 16S ribosomal RNA (rRNA) sequences orders of magnitude faster and more cheaply than has previously been possible. However, results from different studies using pyrosequencing and traditional sequencing are often difficult to compare, because amplicons covering different regions of the rRNA might yield different conclusions. We used sequences from over 200 globally dispersed environments to test whether studies that used similar primers clustered together mistakenly, without regard to environment. We then tested whether primer choice affects sequence-based community analyses using UniFrac, our recently-developed method for comparing microbial communities. We performed three tests of primer effects. We tested whether different simulated amplicons generated the same UniFrac clustering results as near-full-length sequences for three recent large-scale studies of microbial communities in the mouse and human gut, and the Guerrero Negro microbial mat. We then repeated this analysis for short sequences (100-, 150-, 200- and 250-base reads) resembling those produced by pyrosequencing. The results show that sequencing effort is best focused on gathering more short sequences rather than fewer longer ones, provided that the primers are chosen wisely, and that community comparison methods such as UniFrac are surprisingly robust to variation in the region sequenced.     

Advanced computational algorithms for microbial community analysis using massive 16S rRNA sequence data

With the aid of next-generation sequencing technology, researchers can now obtain millions of microbial signature sequences for diverse applications ranging from human epidemiological studies to global ocean surveys. The development of advanced computational strategies to maximally extract pertinent information from massive nucleotide data has become a major focus of the bioinformatics community. Here, we describe a novel analytical strategy including discriminant and topology analyses that enables researchers to deeply investigate the hidden world of microbial communities, far beyond basic microbial diversity estimation. We demonstrate the utility of our approach through a computational study performed on a previously published massive human gut 16S rRNA data set. The application of discriminant and topology analyses enabled us to derive quantitative disease-associated microbial signatures and describe microbial community structure in far more detail than previously achievable. Our approach provides rigorous statistical tools for sequence-based studies aimed at elucidating associations between known or unknown organisms and a variety of physiological or environmental conditions.