Autotrophy as a predominant mode of carbon fixation in anaerobic methane-oxidizing microbial communities

The methane-rich, hydrothermally heated sediments of the Guaymas Basin are inhabited by thermophilic microorganisms, including anaerobic methane-oxidizing archaea (mainly ANME-1) and sulfate-reducing bacteria (e.g., HotSeep-1 cluster). We studied the microbial carbon flow in ANME-1/ HotSeep-1 enrichments in stable-isotope–probing experiments with and without methane. The relative incorporation of ¹³C from either dissolved inorganic carbon or methane into lipids revealed that methane-oxidizing archaea assimilated primarily inorganic carbon. This assimilation is strongly accelerated in the presence of methane. Experiments with simultaneous amendments of both ¹³C-labeled dissolved inorganic carbon and deuterated water provided further insights into production rates of individual lipids derived from members of the methane-oxidizing community as well as their carbon sources used for lipid biosynthesis. In the presence of methane, all prominent lipids carried a dual isotopic signal indicative of their origin from primarily autotrophic microbes. In the absence of methane, archaeal lipid production ceased and bacterial lipid production dropped by 90%; the lipids produced by the residual fraction of the metabolically active bacterial community predominantly carried a heterotrophic signal. Collectively our results strongly suggest that the studied ANME-1 archaea oxidize methane but assimilate inorganic carbon and should thus be classified as methane-oxidizing chemoorganoautotrophs.     

Carbonate-hosted microbial communities are prolific and pervasive methane oxidizers at geologically diverse marine methane seep sites

At marine methane seeps, vast quantities of methane move through the shallow subseafloor, where it is largely consumed by microbial communities. This process plays an important role in global methane dynamics, but we have yet to identify all of the methane sinks in the deep sea. Here, we conducted a continental-scale survey of seven geologically diverse seafloor seeps and found that carbonate rocks from all sites host methane-oxidizing microbial communities with substantial methanotrophic potential. In laboratory-based mesocosm incubations, chimney-like carbonates from the newly described Point Dume seep off the coast of Southern California exhibited the highest rates of anaerobic methane oxidation measured to date. After a thorough analysis of physicochemical, electrical, and biological factors, we attribute this substantial metabolic activity largely to higher cell density, mineral composition, kinetic parameters including an elevated V_max, and the presence of specific microbial lineages. Our data also suggest that other features, such as electrical conductance, rock particle size, and microbial community alpha diversity, may influence a sample’s methanotrophic potential, but these factors did not demonstrate clear patterns with respect to methane oxidation rates. Based on the apparent pervasiveness within seep carbonates of microbial communities capable of performing anaerobic oxidation of methane, as well as the frequent occurrence of carbonates at seeps, we suggest that rock-hosted methanotrophy may be an important contributor to marine methane consumption.

The anaerobic oxidation of methane (AOM) strongly modulates the emission of a potent greenhouse gas and represents a primary production pathway that mobilizes carbon, sulfur, and nitrogen on a global scale (1–3). AOM at marine methane seeps has been estimated to consume 80% of subsurface methane (2). However, the location and magnitude of methane oxidation within seep complexes are poorly constrained because the ways in which different substrate types (e.g., sediments or rocks) influence AOM have not been adequately studied.One overlooked habitat at methane seeps is carbonate rock, which can comprise a substantial proportion of methane-perfused volume at seeps (4–9). Biomarkers and geochemical signatures suggestive of methane-oxidizing lineages—such as archaeal lipids, 16S rRNA genes, and isotopically light carbon compositions—have been detected in seep-associated carbonates (4, 10–13), but the potential role of these substrates in contemporary methane cycling has been largely neglected. Carbonate-hosted (endolithic) AOM activity has been suggested by shifts in microbial community composition (14) and explicitly demonstrated through methane oxidation rate measurements and stable isotope probing at a single location [Hydrate Ridge (15)]. Given the importance of methane in climate regulation, the presence of authigenic carbonates at seeps, and the limited but encouraging indications of rock-hosted methanotrophy to date, the extent of endolithic methane-oxidizing activity at methane seeps warranted additional study.Here, we present a continental-scale survey of sediment and endolithic microbial communities and their AOM potential at a diverse set of marine methane seeps. Sampling locations included seven sites across four geological settings: 1) the northern Gulf of Mexico, where a sedimentary basin borders a carbonate platform (16); 2) two midcontinental slope submarine canyons on the US Atlantic passive margin (17); 3) two habitats in the Gulf of California’s Guaymas Basin, a heavily sedimented, organic rich hydrothermal site (18); and 4) two seep sites—including a newly discovered field of small carbonate “chimneys” near Point Dume, CA—along the Southern California coast’s active transpressional margin (19) (Fig. 1, Dataset S1, and SI Appendix, Figs. S1–S5). We quantified methane oxidation rates at methane-saturated conditions representative of many active seeps, compared our results to previously published data within a kinetic framework, and explored the likely determinants of rate differences, including microbial abundance, community composition, and mineralogical context. Our findings revealed extremely high potential rates of AOM within select carbonate structures, validating earlier research from a more limited set of samples (15) and demonstrating that endolithic methanotrophic communities are likely ubiquitous among the substantial carbonate deposits that occur within some areas of methane seepage. We posit that seep carbonates represent a habitat with attributes that can support elevated AOM rates and that carbonate-hosted AOM may play a role in greenhouse gas sequestration and the flow of methane-derived carbon into biogeochemical cycles.Open in a separate windowFig. 1.An overview of the seven sites across four distinct geological settings that were sampled in this study. All scale bars are ∼25 cm; additional geographical and ground cover context is provided for each site in SI Appendix, Figs. S1–S5.     

Syntrophic exchange in synthetic microbial communities

Metabolic crossfeeding is an important process that can broadly shape microbial communities. However, little is known about specific crossfeeding principles that drive the formation and maintenance of individuals within a mixed population. Here, we devised a series of synthetic syntrophic communities to probe the complex interactions underlying metabolic exchange of amino acids. We experimentally analyzed multimember, multidimensional communities of Escherichia coli of increasing sophistication to assess the outcomes of synergistic crossfeeding. We find that biosynthetically costly amino acids including methionine, lysine, isoleucine, arginine, and aromatics, tend to promote stronger cooperative interactions than amino acids that are cheaper to produce. Furthermore, cells that share common intermediates along branching pathways yielded more synergistic growth, but exhibited many instances of both positive and negative epistasis when these interactions scaled to higher dimensions. In more complex communities, we find certain members exhibiting keystone species-like behavior that drastically impact the community dynamics. Based on comparative genomic analysis of >6,000 sequenced bacteria from diverse environments, we present evidence suggesting that amino acid biosynthesis has been broadly optimized to reduce individual metabolic burden in favor of enhanced crossfeeding to support synergistic growth across the biosphere. These results improve our basic understanding of microbial syntrophy while also highlighting the utility and limitations of current modeling approaches to describe the dynamic complexities underlying microbial ecosystems. This work sets the foundation for future endeavors to resolve key questions in microbial ecology and evolution, and presents a platform to develop better and more robust engineered synthetic communities for industrial biotechnology.Microbes are abundantly found in almost every part of the world, living in communities that are diverse in many facets. Although it is clear that cooperation and competition within microbial communities is central to their stability, maintenance, and longevity, there is limited knowledge about the general principles guiding the formation of these intricate systems. Understanding the underlying governing principles that shape a microbial community is key for microbial ecology but is also crucial for engineering synthetic microbiomes for various biotechnological applications (1–3). Numerous such examples have been recently described including the bioconversion of unprocessed cellulolytic feedstocks into biofuel isobutanol using fungal–bacterial communities (4) and biofuel precursor methyl halides using yeast–bacterial cocultures (5). Other emerging applications in biosensing and bioremediation against environmental toxins such as arsenic (6) and pathogens such as Pseudomonas aeruginosa and Vibrio cholerae have been demonstrated using engineered quorum-sensing Escherichia coli (7, 8). These advances paint an exciting future for the development of sophisticated multispecies microbial communities to address pressing challenges and the crucial need to understand the basic principles that enables their design and engineering.An important process that governs the growth and composition of microbial ecosystems is the exchange of essential metabolites, known as metabolic crossfeeding. Entomological studies have elucidated on a case-by-case basis the importance of amino acids in natural interkingdom and interspecies exchange networks (9–11). Recent comparative analyses of microbial genomes suggest that a significant proportion of all bacteria lack essential pathways for amino acid biosynthesis (2). These auxotrophic microbes thus require extracellular sources of amino acids for survival. Understanding amino acid exchange therefore presents an opportunity to gain new insights into basic principles in metabolic crossfeeding. Recently, several studies have used model systems of Saccharomyces cerevisiae (12), Saccharomyces enterica (13), and E. coli (14–16) to study syntrophic growth of amino acid auxotrophs in coculture environments. Numerous quantitative models have also been developed to describe the behavior of these multispecies systems, including those that integrate dynamics (17, 18), metabolism (19–21), and spatial coordination (22). Although these efforts have led to an improved understanding of the dynamics of syntrophic pairs and the energetic and benefits of cooperativity in these simple systems (23), larger more complex syntrophic systems have yet to be explored.Here, we use engineered E. coli mutants to study syntrophic crossfeeding, scaling to higher-dimensional synthetic ecosystems of increasing sophistication. We first devised pairwise syntrophic communities that show essential and interesting dynamics that can be predicted by simple kinetic models. We then increased the complexity of the interaction in three-member synthetic consortia involving crossfeeding of multiple metabolites. To further increase the complexity of our system, we devised a 14-member community to understand key drivers of population dynamics over short and evolutionary timescales. Finally, we provide evidence for widespread trends of metabolic crossfeeding based on comparative genomic analysis of amino acid biosynthesis across thousands of sequenced genomes. Our large-scale and systematic efforts represent an important foray into forward and reverse engineering synthetic microbial communities to gain key governing principles of microbial ecology and systems microbiology.     

Niche and neutral models predict asymptotically equivalent species abundance distributions in high-diversity ecological communities

A fundamental challenge in ecology is to understand the mechanisms that govern patterns of relative species abundance. Previous numerical simulations have suggested that complex niche-structured models produce species abundance distributions (SADs) that are qualitatively similar to those of very simple neutral models that ignore differences between species. However, in the absence of an analytical treatment of niche models, one cannot tell whether the two classes of model produce the same patterns via similar or different mechanisms. We present an analytical proof that, in the limit as diversity becomes large, a strong niche model give rises to exactly the same asymptotic form of SAD as the neutral model, and we verify the analytical predictions for a Panamanian tropical forest data set. Our results strongly suggest that neutral processes drive patterns of relative species abundance in high-diversity ecological communities, even when strong niche structure exists. However, neutral theory cannot explain what generates high diversity in the first place, and it may not be valid in low-diversity communities. Our results also confirm that neutral theory cannot be used to infer an absence of niche structure or to explain ecosystem function.     

Evolutionary limits to cooperation in microbial communities

Microbes produce many compounds that are costly to a focal cell but promote the survival and reproduction of neighboring cells. This observation has led to the suggestion that microbial strains and species will commonly cooperate by exchanging compounds. Here, we examine this idea with an ecoevolutionary model where microbes make multiple secretions, which can be exchanged among genotypes. We show that cooperation between genotypes only evolves under specific demographic regimes characterized by intermediate genetic mixing. The key constraint on cooperative exchanges is a loss of autonomy: strains become reliant on complementary genotypes that may not be reliably encountered. Moreover, the form of cooperation that we observe arises through mutual exploitation that is related to cheating and “Black Queen” evolution for a single secretion. A major corollary is that the evolution of cooperative exchanges reduces community productivity relative to an autonomous strain that makes everything it needs. This prediction finds support in recent work from synthetic communities. Overall, our work suggests that natural selection will often limit cooperative exchanges in microbial communities and that, when exchanges do occur, they can be an inefficient solution to group living.

‘Benefit-of-the-species’ arguments … provide for the reader an escape from inner conflict, exacting nothing emotionally beyond what most of us learn to accept in childhood, that most forms of life exploit and prey on one another.

Hamilton, 1975 (1)

Microbes typically live in dense communities containing many strains and species. These genetically diverse societies are widespread and central to how microbes affect us, including examples such as the gut microbiome, polymicrobial infections, and communities vital to bioremediation and nutrient cycling (2, 3). In these collectives, ecological interactions are thought to be both common and strong given that cell density is typically high and that microbes possess many phenotypes that influence the reproduction and survival of surrounding cells (4, 5). Such social traits include many secretions, such as extracellular enzymes and scavenging molecules (4–6), and other beneficial “leaky” traits, such as detoxification agents (7) or amino acids (8, 9).A central explanation for cooperative phenotypes in microbes is that they function to help cells of the same genotype (10, 11), which is backed up by a growing body of theory and experiments (12–18). However, it is also clear that, in nature, microbes commonly interact with many different genotypes (both different strains and species) in complex ecological networks (19–21). Do these different microbial genotypes cooperate with one another? Understanding this question is central to building models of microbial communities and how they will respond to both environmental and anthropogenic perturbations (22).Studies involving genetically engineered (8, 9, 23, 24) and/or artificially selected communities (23, 25, 26) emphasize how easily cooperation between genotypes can be achieved in the laboratory. Additionally, there are a growing number of suggestions that cooperation should commonly evolve between microbial strains and species (27–30). This view contrasts with empirical surveys of natural bacterial communities, which suggest that competitive interactions predominate over cooperative interactions (31). However, it has also been suggested that cooperation between different genotypes may explain the unculturability of many species in the laboratory when in monoculture (32–34). If correct, studies with culturable species could underestimate cooperativity in microbial communities.The potential for cooperation between different microbial genotypes then remains unclear. Indeed, we even lack clear predictions of what to expect. There is a need for general theory on cooperation between microbial genotypes. One microbial interaction that has been explored theoretically is syntrophy, where one species produces a toxic waste product that another species consumes (35–38). Syntrophy is likely to be ecologically important and under some conditions (36), can benefit both species. However, syntrophic species need not pay energetic costs to interact: one species is producing waste, and the other species is feeding. Such byproduct cooperation can, therefore, readily evolve but is fundamentally different to the exchange of costly secretions (39, 40). Other models have analyzed when costly cooperation between species is expected in microbes and other organisms (35, 39, 41). However, these models assume that there is no opportunity for one partner to express the beneficial trait of the other. Although this constraint will sometimes occur, there is considerable functional overlap in the cooperative traits of microbial species (7). In addition, the potential for horizontal gene transfer in microbes means that there is a broad scope for a focal strain to pick up the phenotypes of co-occurring strains and species (42–44).Here, we examine the potential for microbial cooperation between different strains and species. We base our work on the well-established models of within-genotype microbial cooperation for a single public good (12, 18, 45–47) so that the relationship to previous work is clear (SI Materials and Methods). We add one key feature to these models: we allow cells to invest in multiple distinct cooperative secretions, such that there is the potential for different genotypes to exchange secretions with one another. Our analysis shows that the degree of genetic mixing defines the potential for cooperation both within and between genotypes. Low mixing favors genotypes that produce all secretions, whereas high mixing favors genotypes that do not produce any at all. Only for intermediate levels of genetic mixing do we find between-genotype cooperation, where strains produce a subset of secretions and rely on other genotypes for the complementary traits. Moreover, the form of cooperation that emerges is inefficient and results in a loss of productivity relative to one genotype making all secretions. Natural selection limits both the occurrence and effectiveness of cooperation within microbial communities.     

microRNAs在代谢综合征中的研究进展

近年来代谢综合征发病率持续攀升,造成了巨大的社会经济负担。传统的治疗方式主要包括生活方式干预和药物治疗,但都未能取得理想的治疗效果。microRNAs在诸如脂肪细胞分化、代谢整合、胰岛素抵抗和食欲调节等大多数生物过程均起到重要的调节作用。本文讨论了microRNAs在代谢综合征相关组份肥胖、糖代谢异常、血脂异常、高血压中的研究进展。microRNAs表达和代谢综合征相关组份的密切联系表明采用这些分子作为预测疾病进程的新的生物标记物以及治疗干预的靶点的可行性。     

Metabolic drift in the aging brain

Brain function is highly dependent upon controlled energy metabolism whose loss heralds cognitive impairments. This is particularly notable in the aged individuals and in age-related neurodegenerative diseases. However, how metabolic homeostasis is disrupted in the aging brain is still poorly understood. Here we performed global, metabolomic and proteomic analyses across different anatomical regions of mouse brain at different stages of its adult lifespan. Interestingly, while severe proteomic imbalance was absent, global-untargeted metabolomics revealed an energy metabolic drift or significant imbalance in core metabolite levels in aged mouse brains. Metabolic imbalance was characterized by compromised cellular energy status (NAD decline, increased AMP/ATP, purine/pyrimidine accumulation) and significantly altered oxidative phosphorylation and nucleotide biosynthesis and degradation. The central energy metabolic drift suggests a failure of the cellular machinery to restore metabostasis (metabolite homeostasis) in the aged brain and therefore an inability to respond properly to external stimuli, likely driving the alterations in signaling activity and thus in neuronal function and communication.     

Changing Metabolic and Energy Profiles in Fetal,Neonatal, and Adult Rat Brain

The regional energy status and the availability of metabolic substrates during brain development are important, since a variety of fetal metabolic insults have been increasingly implicated in the evolution of neonatal brain disorders. The response of the brain to a metabolic insult is determined, in large part, by the ability to utilize the various substrates for intermediary metabolism in order to maintain energy stores within the tissue. To ascertain if metabolic conditions of the fetal brain make it more or less vulnerable to a stress, the high-energy phosphates and glucose-related compounds were examined in five regions of the embryonic day 18 (E-18) fetal brain. Glucose and glycogen levels in the E-18 fetal brain were generally higher in the cerebellum and its neuroepithelium than in the hippocampus, cerebral cortex, and its neuroepithelium. Regional lactate and high-energy phosphate concentrations were essentially the same in the five regions. Subsequently, the metabolic profile was examined in the cerebral cortex and striatum from E-18, postpartum day 7 (P-7) and adult rats. At the various stages of development, there were only minimal differences in the high-energy phosphate levels in the striatum and cortex. Glucose levels, the primary substrate in the adult brain, were essentially unchanged throughout development. In contrast, lactate was significantly elevated by 6- and 2-fold over those in the adult brain in the E-18 and P-7 striatum and cortex, respectively. Another alternative substrate, -hydroxybutyrate, was also significantly elevated at E-18 and increased more than 2-fold at P-7, but was barely detectable in the adult cortex and striatum. Finally, glucose and lactate levels were examined in cerebrospinal fluid, blood, and brain from the E-18 brain to determine if a gradient among the compartments exists. The levels of both lactate and glucose exhibited a concentration gradient in the E-18 fetus: blood > cerebrospinal fluid > brain parenchyma. The results indicate that energy state in the fetal brain is comparable to that in the neonates and the adults, but that the availability of alternative substrates for intermediary metabolism change markedly with development. The age-dependent substrate specificity for intermediary metabolism could affect the response of the fetal brain to a metabolic insult.     

Effects of Myogenic and Metabolic Mechanisms on the Autoregulation of Blood Flow Through Muscle Tissue: A Mathematical Model Study

Mathematical modeling of mechanisms responsible for autoregulation have been thoroughly studied in the past. Less attention was, however, paid on the simultaneous action of different mechanisms, particularly during increased need for blood flow such as with increased metabolic activity or hypoxia. Here we present simultaneous effects of the myogenic and metabolic mechanisms of autoregulation. In the model the microvascular network was divided into three segments, each with the characteristic lumped resistance. The arterial resistance exhibited myogenic properties with the resistance linearly increasing as the transmural pressure departed from that in the resting conditions. The capillary resistance changed with the oxygen concentration in the venous blood. Finally, the venous and the arteriolar resistance both depended on the blood flow and were reduced with increased flow. The described network resistance led to a pressure flow relationship, which was used to fit the published experimental data of the perfused hind limb of a dog obtained in conditions of changed perfusion pressure, hypoxic conditions or during increased metabolic activity. By variation of the parameters we further studied their influence on the autoregulatory blood flow as well as on the venous blood O₂ concentration and the capillary pressure. We found that the metabolic component primarily changes the resistance of the network during increased metabolic activity or hypoxia. The myogenic component not only maintains blood flow despite changes in the perfusion pressure but also helps in facilitating blood flow either during the increased metabolic activity or hypoxic conditions.     

Functional equivalence and evolutionary convergence in complex communities of microbial sponge symbionts

Microorganisms often form symbiotic relationships with eukaryotes, and the complexity of these relationships can range from those with one single dominant symbiont to associations with hundreds of symbiont species. Microbial symbionts occupying equivalent niches in different eukaryotic hosts may share functional aspects, and convergent genome evolution has been reported for simple symbiont systems in insects. However, for complex symbiont communities, it is largely unknown how prevalent functional equivalence is and whether equivalent functions are conducted by evolutionarily convergent mechanisms. Sponges represent an evolutionarily divergent group of species with common physiological and ecological traits. They also host complex communities of microbial symbionts and thus are the ideal model to test whether functional equivalence and evolutionary convergence exist in complex symbiont communities across phylogenetically divergent hosts. Here we use a sampling design to determine the phylogenetic and functional profiles of microbial communities associated with six sponge species. We identify common functions in the six microbiomes, demonstrating the existence of functional equivalence. These core functions are consistent with our current understanding of the biological and ecological roles of sponge-associated microorganisms and also provide insight into symbiont functions. Importantly, core functions also are provided in each sponge species by analogous enzymes and biosynthetic pathways. Moreover, the abundance of elements involved in horizontal gene transfer suggests their key roles in the genomic evolution of symbionts. Our data thus demonstrate evolutionary convergence in complex symbiont communities and reveal the details and mechanisms that underpin the process.     

Metagenomic systems biology and metabolic modeling of the human microbiome: From species composition to community assembly rules

The human microbiome is a key contributor to health and development. Yet little is known about the ecological forces that are at play in defining the composition of such host-associated communities. Metagenomics-based studies have uncovered clear patterns of community structure but are often incapable of distinguishing alternative structuring paradigms. In a recent study, we integrated metagenomic analysis with a systems biology approach, using a reverse ecology framework to model numerous human microbiota species and to infer metabolic interactions between species. Comparing predicted interactions with species composition data revealed that the assembly of the human microbiome is dominated at the community level by habitat filtering. Furthermore, we demonstrated that this habitat filtering cannot be accounted for by known host phenotypes or by the metabolic versatility of the various species. Here we provide a summary of our findings and offer a brief perspective on related studies and on future approaches utilizing this metagenomic systems biology framework.     

Fluctuations in density of an outbreak species drive diversity cascades in food webs

Patterns in food-web structure have frequently been examined in static food webs, but few studies have attempted to delineate patterns that materialize in food webs under nonequilibrium conditions. Here, using one of nature's classical nonequilibrium systems as the food-web database, we test the major assumptions of recent advances in food-web theory. We show that a complex web of interactions between insect herbivores and their natural enemies displays significant architectural flexibility over a large fluctuation in the natural abundance of the major herbivore, the spruce budworm (Choristoneura fumiferana). Importantly, this flexibility operates precisely in the manner predicted by recent foraging-based food-web theories: higher-order mobile generalists respond rapidly in time and space by converging on areas of increasing prey abundance. This "birdfeeder effect" operates such that increasing budworm densities correspond to a cascade of increasing diversity and food-web complexity. Thus, by integrating foraging theory with food-web ecology and analyzing a long-term, natural data set coupled with manipulative field experiments, we are able to show that food-web structure varies in a predictable manner. Furthermore, both recent food-web theory and longstanding foraging theory suggest that this very same food-web flexibility ought to be a potent stabilizing mechanism. Interestingly, we find that this food-web flexibility tends to be greater in heterogeneous than in homogeneous forest plots. Because our results provide a plausible mechanism for boreal forest effects on populations of forest insect pests, they have implications for forest and pest management practices.     

More diverse plant communities have higher functioning over time due to turnover in complementary dominant species

More diverse communities have been shown to have higher and more temporally stable ecosystem functioning than less diverse ones, suggesting they should also have a consistently higher level of functioning over time. Diverse communities could maintain consistently high function because the species driving function change over time (functional turnover) or because they are more likely to contain key species with temporally stable functioning. Across 7 y in a large biodiversity experiment, we show that more diverse plant communities had consistently higher productivity, that is, a higher level of functioning over time. We identify the mechanism for this as turnover in the species driving biomass production; this was substantial, and species that were rare in some years became dominant and drove function in other years. Such high turnover allowed functionally more diverse communities to maintain high biomass over time and was associated with higher levels of complementarity effects in these communities. In contrast, turnover in communities composed of functionally similar species did not promote high biomass production over time. Thus, turnover in species promotes consistently high ecosystem function when it sustains functionally complementary interactions between species. Our results strongly reinforce the argument for conservation of high biodiversity.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Proteogenomic basis for ecological divergence of closely related bacteria in natural acidophilic microbial communities

Bacterial species concepts are controversial. More widely accepted is the need to understand how differences in gene content and sequence lead to ecological divergence. To address this relationship in ecosystem context, we investigated links between genotype and ecology of two genotypic groups of Leptospirillum group II bacteria in comprehensively characterized, natural acidophilic biofilm communities. These groups share 99.7% 16S rRNA gene sequence identity and 95% average amino acid identity between their orthologs. One genotypic group predominates during early colonization, and the other group typically proliferates in later successional stages, forming distinct patches tens to hundreds of micrometers in diameter. Among early colonizing populations, we observed dominance of five genotypes that differed from each other by the extent of recombination with the late colonizing type. Our analyses suggest that the specific recombinant variant within the early colonizing group is selected for by environmental parameters such as temperature, consistent with recombination as a mechanism for ecological fine tuning. Evolutionary signatures, and strain-resolved expression patterns measured via mass spectrometry–based proteomics, indicate increased cobalamin biosynthesis, (de)methylation, and glycine cleavage in the late colonizer. This may suggest environmental changes within the biofilm during development, accompanied by redirection of compatible solutes from osmoprotectants toward metabolism. Across 27 communities, comparative proteogenomic analyses show that differential regulation of shared genes and expression of a small subset of the ∼15% of genes unique to each genotype are involved in niche partitioning. In summary, the results show how subtle genetic variations can lead to distinct ecological strategies.     

Disentangling mechanisms that mediate the balance between stochastic and deterministic processes in microbial succession

Ecological succession and the balance between stochastic and deterministic processes are two major themes within microbial ecology, but these conceptual domains have mostly developed independent of each other. Here we provide a framework that integrates shifts in community assembly processes with microbial primary succession to better understand mechanisms governing the stochastic/deterministic balance. Synthesizing previous work, we devised a conceptual model that links ecosystem development to alternative hypotheses related to shifts in ecological assembly processes. Conceptual model hypotheses were tested by coupling spatiotemporal data on soil bacterial communities with environmental conditions in a salt marsh chronosequence spanning 105 years of succession. Analyses within successional stages showed community composition to be initially governed by stochasticity, but as succession proceeded, there was a progressive increase in deterministic selection correlated with increasing sodium concentration. Analyses of community turnover among successional stages—which provide a larger spatiotemporal scale relative to within stage analyses—revealed that changes in the concentration of soil organic matter were the main predictor of the type and relative influence of determinism. Taken together, these results suggest scale-dependency in the mechanisms underlying selection. To better understand mechanisms governing these patterns, we developed an ecological simulation model that revealed how changes in selective environments cause shifts in the stochastic/deterministic balance. Finally, we propose an extended—and experimentally testable—conceptual model integrating ecological assembly processes with primary and secondary succession. This framework provides a priori hypotheses for future experiments, thereby facilitating a systematic approach to understand assembly and succession in microbial communities across ecosystems.A major goal in microbial community ecology is to understand the processes that underlie observed patterns in species abundances across space and time (1–3). Two types of processes—deterministic and stochastic—influence the assembly of species into communities. Deterministic processes—in which abiotic and biotic factors determine the presence/absence and relative abundances of species—are associated with ecological selection [sensu Vellend (4)]. Stochastic processes include probabilistic dispersal and random changes in species relative abundances (ecological drift) that are not the consequence of environmentally determined fitness (5, 6).Historically, microbial community assembly has been studied from a deterministic perspective (7, 8), where empirical evidence shows that a variety of environmental factors—such as pH, salinity, and organic carbon—influence community establishment at different scales (9, 10). However, recent studies have provided increasing support for a predominant role of stochasticity in some microbial systems (e.g., ref. 11). As opposed to a dichotomous debate, in which one attempts to reject stochastic processes in favor of deterministic ones (or vice versa), a more comprehensive perspective should integrate both processes and work to understand how and why their relative influences vary across systems, time, and space (3, 6, 12–15).The study of ecological succession provides an ideal setting for understanding mechanisms that govern community assembly processes through time and space. Although ecological succession in microbial communities has been broadly investigated (16–21), little has been done to formally link this theme with the balance in stochastic/deterministic processes. Only two studies have directly related these conceptual domains, and both have focused on secondary succession (i.e., following disturbance) (2, 20). These studies show that disturbance promotes a time-dependent shift in the stochastic/deterministic balance. A full understanding of linkages among community succession, disturbance, and the assembly processes, however, requires a testable conceptual framework that enables systematic evaluation of the stochastic/deterministic interplay during succession in both pristine and disturbed ecosystems.Here we set up a framework that integrates the conceptual domains of microbial succession and the balance in stochastic/deterministic ecological processes. We first devised a conceptual model that links environmental heterogeneity to shifts in these assembly processes during microbial primary succession; for this, we purposefully followed the approach used in Ferrenberg et al. (20) to allow a direct linkage between our model and theirs. Alternative hypotheses within the conceptual model were tested by applying an ecological null modeling approach (3) to data from a soil chronosequence spanning 105 years of primary ecosystem succession (22). The analyses revealed scale dependency with respect to how environmental factors govern the interplay between stochastic and deterministic processes. To better understand the mechanisms underlying the observed patterns, we developed an ecological simulation model that revealed how changes in selective environments cause shifts in the processes underlying community assembly. Finally, to facilitate conceptual synthesis and to generate a priori hypotheses for future experiments, we merged our conceptual model—focused on primary succession—with an extended version of the Ferrenberg et al. (20) secondary succession model.     

Hallmarks of Metabolic Reprogramming and Their Role in Viral Pathogenesis

Metabolic reprogramming is a hallmark of cancer and has proven to be critical in viral infections. Metabolic reprogramming provides the cell with energy and biomass for large-scale biosynthesis. Based on studies of the cellular changes that contribute to metabolic reprogramming, seven main hallmarks can be identified: (1) increased glycolysis and lactic acid, (2) increased glutaminolysis, (3) increased pentose phosphate pathway, (4) mitochondrial changes, (5) increased lipid metabolism, (6) changes in amino acid metabolism, and (7) changes in other biosynthetic and bioenergetic pathways. Viruses depend on metabolic reprogramming to increase biomass to fuel viral genome replication and production of new virions. Viruses take advantage of the non-metabolic effects of metabolic reprogramming, creating an anti-apoptotic environment and evading the immune system. Other non-metabolic effects can negatively affect cellular function. Understanding the role metabolic reprogramming plays in viral pathogenesis may provide better therapeutic targets for antivirals.