林地覆盖对雷竹林土壤微生物特征及其与土壤养分制约性关系的影响

为了探讨林地覆盖雷竹林退化机理,给退化雷竹林恢复提供理论参考,对不同覆盖年限(CK、1、3 a 和6 a) 雷竹林土壤微生物区系组成和生物量碳(C_mic)、氮(N_mic)、磷(P_mic)等特征因子进行了测定,并分析了其与土壤养分的制约性关系。结果表明:(1) 雷竹林土壤微生物以细菌为主,真菌次之,放线菌最少,分别占土壤微生物总量的90.11%-98.03%、1.04%-9.22%和0.67%-1.37%。随覆盖年限增加,细菌、放线菌比率呈下降趋势,真菌比率呈上升趋势;土壤微生物总数、细菌和放线菌数量及C_mic、N_mic、P_mic均呈先升高后降低的变化趋势,试验雷竹林间差异极显著,真菌数量总体呈极显著升高趋势。(2)雷竹林土壤微生物特征因子与土壤有机质(SOM)、全氮(TN)、全磷(TP)、碱解氮(Available nitrogen, AN)和pH均呈显著或极显著相关,其中,CK和覆盖1 a、3 a雷竹林土壤微生物特征因子与土壤养分主要呈正相关,与pH呈负相关,而覆盖6 a雷竹林则相反。(3)不同覆盖年限雷竹林土壤养分与土壤微生物的制约性关系存在一定的差异,CK雷竹林土壤SOM、TN、AN、速效钾(AK)和pH主要影响土壤C_mic、N_mic和细菌,覆盖1 a雷竹林土壤SOM、TN、TP和AK主要影响土壤P_mic、放线菌和细菌,覆盖3 a雷竹林土壤SOM、TN、速效磷(AP)和AN主要影响土壤N_mic、放线菌和真菌,覆盖6 a雷竹林土壤SOM、TN和pH主要影响土壤N_mic、真菌。研究表明:长期覆盖雷竹林土壤细菌、放线菌数量与比例明显降低,真菌数量与比例明显提高,土壤养分与土壤微生物的制约性作用关系会发生较为明显变化,产生土壤障害,这是覆盖雷竹林退化的主要原因之一。     

Anoxic Conditions Promote Species-Specific Mutualism between Gut Microbes In Silico

The human gut is inhabited by thousands of microbial species, most of which are still uncharacterized. Gut microbes have adapted to each other''s presence as well as to the host and engage in complex cross feeding. Constraint-based modeling has been successfully applied to predicting microbe-microbe interactions, such as commensalism, mutualism, and competition. Here, we apply a constraint-based approach to model pairwise interactions between 11 representative gut microbes. Microbe-microbe interactions were computationally modeled in conjunction with human small intestinal enterocytes, and the microbe pairs were subjected to three diets with various levels of carbohydrate, fat, and protein in normoxic or anoxic environments. Each microbe engaged in species-specific commensal, parasitic, mutualistic, or competitive interactions. For instance, Streptococcus thermophilus efficiently outcompeted microbes with which it was paired, in agreement with the domination of streptococci in the small intestinal microbiota. Under anoxic conditions, the probiotic organism Lactobacillus plantarum displayed mutualistic behavior toward six other species, which, surprisingly, were almost entirely abolished under normoxic conditions. This finding suggests that the anoxic conditions in the large intestine drive mutualistic cross feeding, leading to the evolvement of an ecosystem more complex than that of the small intestinal microbiota. Moreover, we predict that the presence of the small intestinal enterocyte induces competition over host-derived nutrients. The presented framework can readily be expanded to a larger gut microbial community. This modeling approach will be of great value for subsequent studies aiming to predict conditions favoring desirable microbes or suppressing pathogens.     

Heterogeneity versus homogeneity: A conceptual and mathematical theory in terms of scale-invariant and scale-covariant distributions

Ecologists often use the words heterogeneity and homogeneity when they are describing the distribution of a variable, yet there has been no formal exploration into the relation of these two states to one another. This work formalizes their relationship within statistical theory with a conceptual framework that includes five parameters: L, K, S, D, and R. These parameters provide an increasing degree of specificity about a distribution as they are enumerated and accord with measurements of system extent, richness, evenness, variance, and scale-covariance. Moreover, a mathematical and physical basis for understanding heterogeneity and homogeneity is outlined in terms of Brownian motion, where the Hurst exponent H and the notion of variance are utilized to delimit these two states. Spatial and temporal patterns are quantified and classified according to the mathematical and physical basis at multiple scales, as well as within the conceptual framework that can be applied to other metrics. Concepts of scale-invariance and scale-covariance are discussed in terms of hierarchy theory. It is argued that in hierarchical distributions, we should expect more than simple scale-covariance; we should expect division by a transitional state that divides heterogeneity from homogeneity at some scale. By revisiting the underlying statistical theory behind these concepts, a more efficient approach to quantifying ecological distributions can result.     

How Many Parameters Does It Take to Describe Disease Tolerance?

The study of infectious disease has been aided by model organisms, which have helped to elucidate molecular mechanisms and contributed to the development of new treatments; however, the lack of a conceptual framework for unifying findings across models, combined with host variability, has impeded progress and translation. Here, we fill this gap with a simple graphical and mathematical framework to study disease tolerance, the dose response curve relating health to microbe load; this approach helped uncover parameters that were previously overlooked. Using a model experimental system in which we challenged Drosophila melanogaster with the pathogen Listeria monocytogenes, we tested this framework, finding that microbe growth, the immune response, and disease tolerance were all well represented by sigmoid models. As we altered the system by varying host or pathogen genetics, disease tolerance varied, as we would expect if it was indeed governed by parameters controlling the sensitivity of the system (the number of bacteria required to trigger a response) and maximal effect size according to a logistic equation. Though either the pathogen or host immune response or both together could theoretically be the proximal cause of pathology that killed the flies, we found that the pathogen, but not the immune response, drove damage in this model. With this new understanding of the circuitry controlling disease tolerance, we can now propose better ways of choosing, combining, and developing treatments.     

Compatible rhizosphere microbes mediated alleviation of biotic stress in chickpea through enhanced antioxidant and phenylpropanoid activities

The study was conducted to examine efficacy of a rhizospheric microbial consortium comprising of a fluorescent Pseudomonas (PHU094), Trichoderma (THU0816) and Rhizobium (RL091) strain on activation of physiological defense responses in chickpea against biotic stress caused by the collar rot pathogen Sclerotium rolfsii. Results of individual microbes were compared with dual and triple strain mixture treatments with reduced microbial load (1/2 and 1/3rd, respectively, of individual microbial load compared to single microbe application) in the mixtures. Periodical studies revealed maximum activities of phenylalanine ammonia lyase [E.C. 4.1.3.5] and polyphenol oxidase [E.C. 1.14.18.1] and accumulation of total phenol content in chickpea in the triple microbe consortium treated plants challenged with the pathogen compared to the single microbe and dual microbial consortia. Similarly, the expression of the antioxidant enzymes superoxide dismutase [E.C.1.15.1.1] and peroxidase [E.C.1.11.1.7] was also highest in the triple microbial consortium which was correlated with lesser lipid peroxidation in chickpea under the biotic stress. Histochemical staining clearly showed maximum and uniform lignification in vascular bundles of chickpea stem sections treated with the triple microbes. The physiological responses were directly correlated with the mortality rate as least plant mortality was recorded in the triple microbe consortium treated plants. The results thus suggest an augmented elicitation of stress response in chickpea under S. rolfsii stress by the triple microbial consortium in a synergistic manner under reduced microbial load.     

Detecting distant homologies of mosaic proteins. Analysis of the sequences of thrombomodulin, thrombospondin complement components C9, C8 alpha and C8 beta, vitronectin and plasma cell membrane glycoprotein PC-1

Recognition of homologies may give hints about the structure and function of proteins; therefore, we are developing strategies to aid sequence comparisons. Detecting homology of mosaic proteins is especially difficult since the modules constituting these proteins are usually distantly related and their homology is not readily recognized by conventional computer programs. In the present work we show that the rules of the evolution of mosaic proteins can guide the identification of modules of mosaic proteins and can delineate the group of sequences in which the presence of homologous sequences may be expected. By this approach we can concentrate the search for homology to a limited group of sequences; thus ensuring a more intense and more fruitful search. The power of this approach is illustrated by the fact that it could detect homologies not identified by earlier methods of sequence comparison. In this paper we show that thrombomodulin contains a domain homologous with animal lectins, that complement components C9, C8 alpha and C8 beta have modules homologous with one of the repeat units of thrombospondin and that the somatomedin B module of vitronectin is homologous with the internal repeats of plasma cell membrane glycoprotein PC-1.     

Natural variation in the contribution of microbial density to inducible immune dynamics

Immune responses evolve to balance the benefits of microbial killing against the costs of autoimmunity and energetic resource use. Models that explore the evolution of optimal immune responses generally include a term for constitutive immunity, or the level of immunological investment prior to microbial exposure, and for inducible immunity, or investment in immune function after microbial challenge. However, studies rarely consider the functional form of inducible immune responses with respect to microbial density, despite the theoretical dependence of immune system evolution on microbe‐ versus immune‐mediated damage to the host. In this study, we analyse antimicrobial peptide (AMP) gene expression from seven wild‐caught flour beetle populations (Tribolium spp.) during acute infection with the virulent bacteria Bacillus thuringiensis (Bt) and Photorhabdus luminescens (P.lum) to demonstrate that inducible immune responses mediated by the humoral IMD pathway exhibit natural variation in both microbe density‐dependent and independent temporal dynamics. Beetle populations that exhibited greater AMP expression sensitivity to Bt density were also more likely to die from infection, while populations that exhibited higher microbe density‐independent AMP expression were more likely to survive P. luminescens infection. Reduction in pathway signalling efficiency through RNAi‐mediated knockdown of the imd gene reduced the magnitude of both microbe‐independent and dependent responses and reduced host resistance to Bt growth, but had no net effect on host survival. This study provides a framework for understanding natural variation in the flexibility of investment in inducible immune responses and should inform theory on the contribution of nonequilibrium host‐microbe dynamics to immune system evolution.     

Inferring Stabilizing Mutations from Protein Phylogenies: Application to Influenza Hemagglutinin

One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution.     

Modelling the effect of birth and feeding modes on the development of human gut microbiota

The human gut microbiota is transmitted from mother to infant through vaginal birth and breastfeeding. Bifidobacterium, a genus that dominates the infants’ gut, is adapted to breast milk in its ability to metabolize human milk oligosaccharides; it is regarded as a mutualist owing to its involvement in the development of the immune system. The composition of microbiota, including the abundance of Bifidobacteria, is highly variable between individuals and some microbial profiles are associated with diseases. However, whether and how birth and feeding practices contribute to such variation remains unclear. To understand how early events affect the establishment of microbiota, we develop a mathematical model of two types of Bifidobacteria and a generic compartment of commensal competitors. We show how early events affect competition between mutualists and commensals and microbe-host-immune interactions to cause long-term alterations in gut microbial profiles. Bifidobacteria associated with breast milk can trigger immune responses with lasting effects on the microbial community structure. Our model shows that, in response to a change in birth environment, competition alone can produce two distinct microbial profiles post-weaning. Adding immune regulation to our competition model allows for variations in microbial profiles in response to different feeding practices. This analysis highlights the importance of microbe–microbe and microbe–host interactions in shaping the gut populations following different birth and feeding modes.     

Implementation of a Pan-Genomic Approach to Investigate Holobiont-Infecting Microbe Interaction: A Case Report of a Leukemic Patient with Invasive Mucormycosis

Disease can be conceptualized as the result of interactions between infecting microbe and holobiont, the combination of a host and its microbial communities. It is likely that genomic variation in the host, infecting microbe, and commensal microbiota are key determinants of infectious disease clinical outcomes. However, until recently, simultaneous, multiomic investigation of infecting microbe and holobiont components has rarely been explored. Herein, we characterized the infecting microbe, host, micro- and mycobiomes leading up to infection onset in a leukemia patient that developed invasive mucormycosis. We discovered that the patient was infected with a strain of the recently described Mucor velutinosus species which we determined was hypervirulent in a Drosophila challenge model and has a predisposition for skin dissemination. After completing the infecting M. velutinosus genome and genomes from four other Mucor species, comparative pathogenomics was performed and assisted in identifying 66 M. velutinosus-specific putatively secreted proteins, including multiple novel secreted aspartyl proteinases which may contribute to the unique clinical presentation of skin dissemination. Whole exome sequencing of the patient revealed multiple non-synonymous polymorphisms in genes critical to control of fungal proliferation, such as TLR6 and PTX3. Moreover, the patient had a non-synonymous polymorphism in the NOD2 gene and a missense mutation in FUT2, which have been linked to microbial dysbiosis and microbiome diversity maintenance during physiologic stress, respectively. In concert with host genetic polymorphism data, the micro- and mycobiome analyses revealed that the infection developed amid a dysbiotic microbiome with low α-diversity, dominated by staphylococci. Additionally, longitudinal mycobiome data showed that M. velutinosus DNA was detectable in oral samples preceding disease onset. Our genome-level study of the host-infecting microbe-commensal triad extends the concept of personalized genomic medicine to the holobiont-infecting microbe interface thereby offering novel opportunities for using synergistic genetic methods to increase understanding of infectious diseases pathogenesis and clinical outcomes.     

木论喀斯特自然保护区土壤微生物生物量的空间格局

土壤微生物是森林生态系统中的重要分解者,在森林生态系统物质循环和能量转换中占有特别重要的地位。以典型喀斯特峰丛洼地为试验对象,利用经典统计学和地统计方法分析了土壤微生物量的空间变异特征。结果表明:土壤微生物量的变异程度均很大,土壤微生物量碳(Cmic)、土壤微生物量氮(Nmic)、土壤微生物量磷(Pmic)的变化范围依次为:44.29—5209.63,20.91—1894.37,0.34—77.06 mg/kg。Cmic、Nmic呈极显著的相关关系,Cmic/Nmic为4.78,明显低于其它生态系统。半变异函数分析表明,Cmic和Nmic的最佳拟合模型为高斯模型,Pmic的最佳拟合模型为球状模型,Cmic/Nmic的最佳拟合模型为指数模型。土壤微生物量的块金值/基台值均介于25%—75%之间,表现为中等空间相关性,说明其受随机因素和结构因素的综合影响。Cmic、Nmic的自相关距离约为50 m,随着滞后距离的增大,自相关函数逐渐向负方向增长,达到显著的负相关。Pmic的Moran’s I在滞后距大于70 m后反而增大,表现为正相关。Cmic/Nmic的Moran’s I较小,在-0.2—0.2之间波动。Cmic、Nmic的空间分布具有很高的相似性,呈凸型片状分布,坡中含量高且向两边递减。Pmic表现为明显不同的分布格局,其在坡中上位和洼地含量较高。Cmic/Nmic呈相反的凹形零星斑块状分布。土壤微生物存在着一定的空间格局,受干扰后其含量急剧降低,因此应加强喀斯特原生生态系统的保护。     

Dynamics of a neural system with a multiscale architecture

The architecture of the brain is characterized by a modular organization repeated across a hierarchy of spatial scales-neurons, minicolumns, cortical columns, functional brain regions, and so on. It is important to consider that the processes governing neural dynamics at any given scale are not only determined by the behaviour of other neural structures at that scale, but also by the emergent behaviour of smaller scales, and the constraining influence of activity at larger scales. In this paper, we introduce a theoretical framework for neural systems in which the dynamics are nested within a multiscale architecture. In essence, the dynamics at each scale are determined by a coupled ensemble of nonlinear oscillators, which embody the principle scale-specific neurobiological processes. The dynamics at larger scales are 'slaved' to the emergent behaviour of smaller scales through a coupling function that depends on a multiscale wavelet decomposition. The approach is first explicated mathematically. Numerical examples are then given to illustrate phenomena such as between-scale bifurcations, and how synchronization in small-scale structures influences the dynamics in larger structures in an intuitive manner that cannot be captured by existing modelling approaches. A framework for relating the dynamical behaviour of the system to measured observables is presented and further extensions to capture wave phenomena and mode coupling are suggested.     

Resilience of the rhizosphere to anthropogenic disturbance

The rhizosphere is a dominant site of microbial metabolism in soiland whereas it can be shown that anthropogenic disturbances can influence this metabolism,the impact of these disturbances on biodiversity is rather difficult to determineat the species level. This is in part because no more than 10% of the microbial species are culturable, and in part because there is very poor precision inplate counting, usually requiring a change of 300–500% to be significant. We have therefore used a functional approach. The `ecophysiological index' is based onr or K strategy of the organisms being counted. Also, enzyme families, microbial biomass,microbe/microbe and microbe/fauna interactions have been determined,along with nutrient uptake measurements. The techniques have been applied to determinethe effects of disturbances created by the introduction of GM plants and microorganismsto soil, these effects being small compared with those caused by time-honoured practices such as crop rotation and ploughing. Toxicity from industrial influences(e.g. cyanide) can be remediated by rhizosphere microorganisms.     

New archaeal methyltransferases forming 1-methyladenosine or 1-methyladenosine and 1-methylguanosine at position 9 of tRNA

Two archaeal tRNA methyltransferases belonging to the SPOUT superfamily and displaying unexpected activities are identified. These enzymes are orthologous to the yeast Trm10p methyltransferase, which catalyses the formation of 1-methylguanosine at position 9 of tRNA. In contrast, the Trm10p orthologue from the crenarchaeon Sulfolobus acidocaldarius forms 1-methyladenosine at the same position. Even more surprisingly, the Trm10p orthologue from the euryarchaeon Thermococcus kodakaraensis methylates the N¹-atom of either adenosine or guanosine at position 9 in different tRNAs. This is to our knowledge the first example of a tRNA methyltransferase with a broadened nucleoside recognition capability. The evolution of tRNA methyltransferases methylating the N¹ atom of a purine residue is discussed.     

Primate microbial endocrinology: An uncharted frontier

Gut microbial communities communicate bidirectionally with the brain through endocrine, immune, and neural signaling, influencing the physiology and behavior of hosts. The emerging field of microbial endocrinology offers innovative perspectives and methods to analyze host‐microbe relationships with relevance to primate ecology, evolution, and conservation. Herein we briefly summarize key findings from microbial endocrinology and explore how applications of a similar framework could inform our understanding of primate stress and reproductive physiology and behavior. We conclude with three guiding hypotheses to further investigate endocrine signaling between gut microbes and the host: (a) host‐microbe communication systems promote microbe‐mediated stability, in which the microbes are using endocrine signaling from the host to maintain a functioning habitat for their own fitness, (b) host‐microbe communication systems promote host‐mediated stability, in which the host uses the endocrine system to monitor microbial communities and alter these communities to maintain stability, or (c) host‐microbe systems are simply the product of coincidental cross‐talk between the host and microbes due to similar molecules from shared ancestry. Utilizing theory and methodology for studying relationships between the microbiome, hormones, and behavior of wild primates is an uncharted frontier with many promising insights when applied to primatology.     

Moving forward with the primate microbiome: Introduction to a special issue of the American Journal of Primatology

Primate microbiome research is a quickly growing field with exciting potential for informing our understanding of primate biology, ecology, and evolution as well as host‐microbe interactions more broadly. This introductory essay to a special section of the American Journal of Primatology provides a cross‐sectional snapshot of current activity in these areas by briefly summarizing the diversity of contributed papers and their relationships to key themes in host‐associated microbiome research. It then uses this survey as a foundation for consolidating a set of key research questions to broadly guide future research. It also argues for the importance of methods standardization to facilitate comparative analyses and the identification of generalizable patterns and relationships. While primatology will benefit greatly from the integration of microbial datasets, it is uniquely positioned to address important questions regarding microbiology and macro‐ecology and evolution more generally. We are eager to see where the primate microbiome leads us.