Minimal Interspecies Interaction Adjustment (MIIA): Inference of Neighbor-Dependent Interactions in Microbial Communities.

An intriguing aspect in microbial communities is that pairwise interactions can be influenced by neighboring species. This creates context dependencies for microbial interactions that are based on the functional composition of the community. Context dependent interactions are ecologically important and clearly present in nature, yet firmly established theoretical methods are lacking from many modern computational investigations. Here, we propose a novel network inference method that enables predictions for interspecies interactions affected by shifts in community composition and species populations. Our approach first identifies interspecies interactions in binary communities, which is subsequently used as a basis to infer modulation in more complex multi-species communities based on the assumption that microbes minimize adjustments of pairwise interactions in response to neighbor species. We termed this rule-based inference minimal interspecies interaction adjustment (MIIA). Our critical assessment of MIIA has produced reliable predictions of shifting interspecies interactions that are dependent on the functional role of neighbor organisms. We also show how MIIA has been applied to a microbial community composed of competing soil bacteria to elucidate a new finding that - in many cases - adding fewer competitors could impose more significant impact on binary interactions. The ability to predict membership-dependent community behavior is expected to help deepen our understanding of how microbiomes are organized in nature and how they may be designed and/or controlled in the future.

Prediction of Neighbor-Dependent Microbial Interactions From Limited Population Data.

Modulation of interspecies interactions by the presence of neighbor species is a key ecological factor that governs dynamics and function of microbial communities, yet the development of theoretical frameworks explicit for understanding context-dependent interactions are still nascent. In a recent study, we proposed a novel rule-based inference method termed the Minimal Interspecies Interaction Adjustment (MIIA) that predicts the reorganization of interaction networks in response to the addition of new species such that the modulation in interaction coefficients caused by additional members is minimal. While the theoretical basis of MIIA was established through the previous work by assuming the full availability of species abundance data in axenic, binary, and complex communities, its extension to actual microbial ecology can be highly constrained in cases that species have not been cultured axenically (e.g., due to their inability to grow in the absence of specific partnerships) because binary interaction coefficients - basic parameters required for implementing the MIIA - are inestimable without axenic and binary population data. Thus, here we present an alternative formulation based on the following two central ideas. First, in the case where only data from axenic cultures are unavailable, we remove axenic populations from governing equations through appropriate scaling. This allows us to predict neighbor-dependent interactions in a relative sense (i.e., fractional change of interactions between with versus without neighbors). Second, in the case where both axenic and binary populations are missing, we parameterize binary interaction coefficients to determine their values through a sensitivity analysis. Through the case study of two microbial communities with distinct characteristics and complexity (i.e., a three-member community where all members can grow independently, and a four-member community that contains member species whose growth is dependent on other species), we demonstrated that despite data limitation, the proposed new formulation was able to successfully predict interspecies interactions that are consistent with experimentally derived results. Therefore, this technical advancement enhances our ability to predict context-dependent interspecies interactions in a broad range of microbial systems without being limited to specific growth conditions as a pre-requisite.

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process.

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community's traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.

Deterministic influences exceed dispersal effects on hydrologically-connected microbiomes.

Subsurface groundwater-surface water mixing zones (hyporheic zones) have enhanced biogeochemical activity, but assembly processes governing subsurface microbiomes remain a critical uncertainty in understanding hyporheic biogeochemistry. To address this obstacle, we investigated (a) biogeographical patterns in attached and waterborne microbiomes across three hydrologically-connected, physicochemically-distinct zones (inland hyporheic, nearshore hyporheic and river); (b) assembly processes that generated these patterns; (c) groups of organisms that corresponded to deterministic changes in the environment; and (d) correlations between these groups and hyporheic metabolism. All microbiomes remained dissimilar through time, but consistent presence of similar taxa suggested dispersal and/or common selective pressures among zones. Further, we demonstrated a pronounced impact of deterministic assembly in all microbiomes as well as seasonal shifts from heterotrophic to autotrophic microorganisms associated with increases in groundwater discharge. The abundance of one statistical cluster of organisms increased with active biomass and respiration, revealing organisms that may strongly influence hyporheic biogeochemistry. Based on our results, we propose a conceptualization of hyporheic zone metabolism in which increased organic carbon concentrations during surface water intrusion support heterotrophy, which succumbs to autotrophy under groundwater discharge. These results provide new opportunities to enhance microbially-explicit ecosystem models describing hyporheic zone biogeochemistry and its influence over riverine ecosystem function.

Indirect Interspecies Regulation: Transcriptional and Physiological Responses of a Cyanobacterium to Heterotrophic Partnership.

The mechanisms by which microbes interact in communities remain poorly understood. Here, we interrogated specific interactions between photoautotrophic and heterotrophic members of a model consortium to infer mechanisms that mediate metabolic coupling and acclimation to partnership. This binary consortium was composed of a cyanobacterium, Thermosynechococcus elongatus BP-1, which supported growth of an obligate aerobic heterotroph, Meiothermus ruber strain A, by providing organic carbon, O2, and reduced nitrogen. Species-resolved transcriptomic analyses were used in combination with growth and photosynthesis kinetics to infer interactions and the environmental context under which they occur. We found that the efficiency of biomass production and resistance to stress induced by high levels of dissolved O2 increased, beyond axenic performance, as a result of heterotrophic partnership. Coordinated transcriptional responses transcending both species were observed and used to infer specific interactions resulting from the synthesis and exchange of resources. The cyanobacterium responded to heterotrophic partnership by altering expression of core genes involved with photosynthesis, carbon uptake/fixation, vitamin synthesis, and scavenging of reactive oxygen species (ROS). IMPORTANCE This study elucidates how a cyanobacterial primary producer acclimates to heterotrophic partnership by modulating the expression levels of key metabolic genes. Heterotrophic bacteria can indirectly regulate the physiology of the photoautotrophic primary producers, resulting in physiological changes identified here, such as increased intracellular ROS. Some of the interactions inferred from this model system represent putative principles of metabolic coupling in phototrophic-heterotrophic partnerships.

Coupling among Microbial Communities, Biogeochemistry, and Mineralogy across Biogeochemical Facies.

Physical properties of sediments are commonly used to define subsurface lithofacies and these same physical properties influence subsurface microbial communities. This suggests an (unexploited) opportunity to use the spatial distribution of facies to predict spatial variation in biogeochemically relevant microbial attributes. Here, we characterize three biogeochemical facies-oxidized, reduced, and transition-within one lithofacies and elucidate relationships among facies features and microbial community biomass, richness, and composition. Consistent with previous observations of biogeochemical hotspots at environmental transition zones, we find elevated biomass within a biogeochemical facies that occurred at the transition between oxidized and reduced biogeochemical facies. Microbial richness-the number of microbial taxa-was lower within the reduced facies and was well-explained by a combination of pH and mineralogy. Null modeling revealed that microbial community composition was influenced by ecological selection imposed by redox state and mineralogy, possibly due to effects on nutrient availability or transport. As an illustrative case, we predict microbial biomass concentration across a three-dimensional spatial domain by coupling the spatial distribution of subsurface biogeochemical facies with biomass-facies relationships revealed here. We expect that merging such an approach with hydro-biogeochemical models will provide important constraints on simulated dynamics, thereby reducing uncertainty in model predictions.

Engineering microbial consortia for controllable outputs.

Much research has been invested into engineering microorganisms to perform desired biotransformations; nonetheless, these efforts frequently fall short of expected results due to the unforeseen effects of biofeedback regulation and functional incompatibility. In nature, metabolic function is compartmentalized into diverse organisms assembled into robust consortia, in which the division of labor is thought to lead to increased community efficiency and productivity. Here we consider whether and how consortia can be designed to perform bioprocesses of interest beyond the metabolic flexibility limitations of a single organism. Advances in post-genomic analysis of microbial consortia and application of high-resolution global measurements now offer the promise of systems-level understanding of how microbial consortia adapt to changes in environmental variables and inputs of carbon and energy. We argue that, when combined with appropriate modeling frameworks, systems-level knowledge can markedly improve our ability to predict the fate and functioning of consortia. Here we articulate our collective perspective on the current and future state of microbial community engineering and control while placing specific emphasis on ecological principles that promote control over community function and emergent properties.

Coupling Spatiotemporal Community Assembly Processes to Changes in Microbial Metabolism.

Community assembly processes generate shifts in species abundances that influence ecosystem cycling of carbon and nutrients, yet our understanding of assembly remains largely separate from ecosystem-level functioning. Here, we investigate relationships between assembly and changes in microbial metabolism across space and time in hyporheic microbial communities. We pair sampling of two habitat types (i.e., attached and planktonic) through seasonal and sub-hourly hydrologic fluctuation with null modeling and temporally explicit multivariate statistics. We demonstrate that multiple selective pressures-imposed by sediment and porewater physicochemistry-integrate to generate changes in microbial community composition at distinct timescales among habitat types. These changes in composition are reflective of contrasting associations of Betaproteobacteria and Thaumarchaeota with ecological selection and with seasonal changes in microbial metabolism. We present a conceptual model based on our results in which metabolism increases when oscillating selective pressures oppose temporally stable selective pressures. Our conceptual model is pertinent to both macrobial and microbial systems experiencing multiple selective pressures and presents an avenue for assimilating community assembly processes into predictions of ecosystem-level functioning.

Nitrate bioreduction in redox-variable low permeability sediments.

Lowpermeability zone (LPZ) can play an important role as a sink or secondary source in contaminant transport in groundwater system. This study investigated the rate and end product of nitrate bioreduction in LPZ sediments. The sedimentswere fromthe U.S. Department of Energy's Hanford Site,where nitrate is a groundwater contaminant as a by-product of radionuclide waste discharges. The LPZ at the Hanford site consists of two layerswith an oxidized layer on top and reduced layer below. The oxidized layer is directly in contact with the overlying contaminated aquifer, while the reduced layer is in contact with an uncontaminated aquifer below. The experimental results showed that nitrate bioreduction rate and end-product differed significantly in the sediments. The bioreduction rate in the oxidized sediment was significantly faster than that in the reduced one. A significant amount of N2O was accumulated in the reduced sediment; while in the oxidized sediment, N2O was further reduced to N2. RT-PCR analysis revealed that nosZ, the gene that codes for N2O reductase, was below detection limit in the reduced sediment. Batch experiments and kinetic modeling were performed to provide insights into the role of organic carbon bioavailability, biomass growth, and competition between nitrate and its reducing products for electrons fromelectron donors. The results revealed that it is important to consider sediment redox conditions and functional genes in understanding and modeling nitrate bioreduction in subsurface sediments. The results also implied that LPZ sediments can be important sink of nitrate and a potential secondary source of N2O as a nitrate bioreduction product in groundwater.

Integrating Ecological and Engineering Concepts of Resilience in Microbial Communities.

Many definitions of resilience have been proffered for natural and engineered ecosystems, but a conceptual consensus on resilience in microbial communities is still lacking. We argue that the disconnect largely results from the wide variance in microbial community complexity, which range from compositionally simple synthetic consortia to complex natural communities, and divergence between the typical practical outcomes emphasized by ecologists and engineers. Viewing microbial communities as elasto-plastic systems that undergo both recoverable and unrecoverable transitions, we argue that this gap between the engineering and ecological definitions of resilience stems from their respective emphases on elastic and plastic deformation, respectively. We propose that the two concepts may be fundamentally united around the resilience of function rather than state in microbial communities and the regularity in the relationship between environmental variation and a community's functional response. Furthermore, we posit that functional resilience is an intrinsic property of microbial communities and suggest that state changes in response to environmental variation may be a key mechanism driving functional resilience in microbial communities.

Redox Linked Flavin Sites in Extracellular Decaheme Proteins Involved in Microbe-Mineral Electron Transfer.

Extracellular microbe-mineral electron transfer is a major driving force for the oxidation of organic carbon in many subsurface environments. Extracellular multi-heme cytochromes of the Shewenella genus play a major role in this process but the mechanism of electron exchange at the interface between cytochrome and acceptor is widely debated. The 1.8 Å x-ray crystal structure of the decaheme MtrC revealed a highly conserved CX8C disulfide that, when substituted for AX8A, severely compromised the ability of S. oneidensis to grow under aerobic conditions. Reductive cleavage of the disulfide in the presence of flavin mononucleotide (FMN) resulted in the reversible formation of a stable flavocytochrome. Similar results were also observed with other decaheme cytochromes, OmcA, MtrF and UndA. The data suggest that these decaheme cytochromes can transition between highly reactive flavocytochromes or less reactive cytochromes, and that this transition is controlled by a redox active disulfide that responds to the presence of oxygen.

Estimating and mapping ecological processes influencing microbial community assembly.

Ecological community assembly is governed by a combination of (i) selection resulting from among-taxa differences in performance; (ii) dispersal resulting from organismal movement; and (iii) ecological drift resulting from stochastic changes in population sizes. The relative importance and nature of these processes can vary across environments. Selection can be homogeneous or variable, and while dispersal is a rate, we conceptualize extreme dispersal rates as two categories; dispersal limitation results from limited exchange of organisms among communities, and homogenizing dispersal results from high levels of organism exchange. To estimate the influence and spatial variation of each process we extend a recently developed statistical framework, use a simulation model to evaluate the accuracy of the extended framework, and use the framework to examine subsurface microbial communities over two geologic formations. For each subsurface community we estimate the degree to which it is influenced by homogeneous selection, variable selection, dispersal limitation, and homogenizing dispersal. Our analyses revealed that the relative influences of these ecological processes vary substantially across communities even within a geologic formation. We further identify environmental and spatial features associated with each ecological process, which allowed mapping of spatial variation in ecological-process-influences. The resulting maps provide a new lens through which ecological systems can be understood; in the subsurface system investigated here they revealed that the influence of variable selection was associated with the rate at which redox conditions change with subsurface depth.

Dynamics in microbial communities: unraveling mechanisms to identify principles.

Diversity begets higher-order properties such as functional stability and robustness in microbial communities, but principles that inform conceptual (and eventually predictive) models of community dynamics are lacking. Recent work has shown that selection as well as dispersal and drift shape communities, but the mechanistic bases for assembly of communities and the forces that maintain their function in the face of environmental perturbation are not well understood. Conceptually, some interactions among community members could generate endogenous dynamics in composition, even in the absence of environmental changes. These endogenous dynamics are further perturbed by exogenous forcing factors to produce a richer network of community interactions and it is this 'system' that is the basis for higher-order community properties. Elucidation of principles that follow from this conceptual model requires identifying the mechanisms that (a) optimize diversity within a community and (b) impart community stability. The network of interactions between organisms can be an important element by providing a buffer against disturbance beyond the effect of functional redundancy, as alternative pathways with different combinations of microbes can be recruited to fulfill specific functions.

Trends and future challenges in sampling the deep terrestrial biosphere.

Research in the deep terrestrial biosphere is driven by interest in novel biodiversity and metabolisms, biogeochemical cycling, and the impact of human activities on this ecosystem. As this interest continues to grow, it is important to ensure that when subsurface investigations are proposed, materials recovered from the subsurface are sampled and preserved in an appropriate manner to limit contamination and ensure preservation of accurate microbial, geochemical, and mineralogical signatures. On February 20th, 2014, a workshop on "Trends and Future Challenges in Sampling The Deep Subsurface" was coordinated in Columbus, Ohio by The Ohio State University and West Virginia University faculty, and sponsored by The Ohio State University and the Sloan Foundation's Deep Carbon Observatory. The workshop aims were to identify and develop best practices for the collection, preservation, and analysis of terrestrial deep rock samples. This document summarizes the information shared during this workshop.

Inference of interactions in cyanobacterial-heterotrophic co-cultures via transcriptome sequencing.

We used deep sequencing technology to identify transcriptional adaptation of the euryhaline unicellular cyanobacterium Synechococcus sp. PCC 7002 and the marine facultative aerobe Shewanella putrefaciens W3-18-1 to growth in a co-culture and infer the effect of carbon flux distributions on photoautotroph-heterotroph interactions. The overall transcriptome response of both organisms to co-cultivation was shaped by their respective physiologies and growth constraints. Carbon limitation resulted in the expansion of metabolic capacities, which was manifested through the transcriptional upregulation of transport and catabolic pathways. Although growth coupling occurred via lactate oxidation or secretion of photosynthetically fixed carbon, there was evidence of specific metabolic interactions between the two organisms. These hypothesized interactions were inferred from the excretion of specific amino acids (for example, alanine and methionine) by the cyanobacterium, which correlated with the downregulation of the corresponding biosynthetic machinery in Shewanella W3-18-1. In addition, the broad and consistent decrease of mRNA levels for many Fe-regulated Synechococcus 7002 genes during co-cultivation may indicate increased Fe availability as well as more facile and energy-efficient mechanisms for Fe acquisition by the cyanobacterium. Furthermore, evidence pointed at potentially novel interactions between oxygenic photoautotrophs and heterotrophs related to the oxidative stress response as transcriptional patterns suggested that Synechococcus 7002 rather than Shewanella W3-18-1 provided scavenging functions for reactive oxygen species under co-culture conditions. This study provides an initial insight into the complexity of photoautotrophic-heterotrophic interactions and brings new perspectives of their role in the robustness and stability of the association.

The X-ray crystal structure of Shewanella oneidensis OmcA reveals new insight at the microbe-mineral interface.

The X-ray crystal structure of Shewanella oneidensis OmcA, an extracellular decaheme cytochrome involved in mineral reduction, was solved to a resolution of 2.7 Å. The four OmcA molecules in the asymmetric unit are arranged so the minimum distance between heme 5 on adjacent OmcA monomers is 9 Å, indicative of a transient OmcA dimer capable of intermolecular electron transfer. A previously identified hematite binding motif was identified near heme 10, forming a hydroxylated surface that would bring a heme 10 electron egress site to ∼10 Å of a mineral surface.

Phototrophic biofilm assembly in microbial-mat-derived unicyanobacterial consortia: model systems for the study of autotroph-heterotroph interactions.

Microbial autotroph-heterotroph interactions influence biogeochemical cycles on a global scale, but the diversity and complexity of natural systems and their intractability to in situ manipulation make it challenging to elucidate the principles governing these interactions. The study of assembling phototrophic biofilm communities provides a robust means to identify such interactions and evaluate their contributions to the recruitment and maintenance of phylogenetic and functional diversity over time. To examine primary succession in phototrophic communities, we isolated two unicyanobacterial consortia from the microbial mat in Hot Lake, Washington, characterizing the membership and metabolic function of each consortium. We then analyzed the spatial structures and quantified the community compositions of their assembling biofilms. The consortia retained the same suite of heterotrophic species, identified as abundant members of the mat and assigned to Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes. Autotroph growth rates dominated early in assembly, yielding to increasing heterotroph growth rates late in succession. The two consortia exhibited similar assembly patterns, with increasing relative abundances of members from Bacteroidetes and Alphaproteobacteria concurrent with decreasing relative abundances of those from Gammaproteobacteria. Despite these similarities at higher taxonomic levels, the relative abundances of individual heterotrophic species were substantially different in the developing consortial biofilms. This suggests that, although similar niches are created by the cyanobacterial metabolisms, the resulting webs of autotroph-heterotroph and heterotroph-heterotroph interactions are specific to each primary producer. The relative simplicity and tractability of the Hot Lake unicyanobacterial consortia make them useful model systems for deciphering interspecies interactions and assembly principles relevant to natural microbial communities.

Genome Sequence of the Thermophilic Cyanobacterium Thermosynechococcus sp. Strain NK55a.

The genome of the unicellular cyanobacterium Thermosynechococcus sp. strain NK55a, isolated from the Nakabusa hot spring, Nagano Prefecture, Japan, comprises a single, circular, 2.5-Mb chromosome. The genome is predicted to contain 2,358 protein-encoding genes, including genes for all typical cyanobacterial photosynthetic and metabolic functions. No genes encoding hydrogenases or nitrogenase were identified.

Modeling biofilms with dual extracellular electron transfer mechanisms.

Electrochemically active biofilms have a unique form of respiration in which they utilize solid external materials as terminal electron acceptors for their metabolism. Currently, two primary mechanisms have been identified for long-range extracellular electron transfer (EET): a diffusion- and a conduction-based mechanism. Evidence in the literature suggests that some biofilms, particularly Shewanella oneidensis, produce the requisite components for both mechanisms. In this study, a generic model is presented that incorporates the diffusion- and the conduction-based mechanisms and allows electrochemically active biofilms to utilize both simultaneously. The model was applied to S. oneidensis and Geobacter sulfurreducens biofilms using experimentally generated data found in the literature. Our simulation results show that (1) biofilms having both mechanisms available, especially if they can interact, may have a metabolic advantage over biofilms that can use only a single mechanism; (2) the thickness of G. sulfurreducens biofilms is likely not limited by conductivity; (3) accurate intrabiofilm diffusion coefficient values are critical for current generation predictions; and (4) the local biofilm potential and redox potential are two distinct parameters and cannot be assumed to have identical values. Finally, we determined that simulated cyclic and squarewave voltammetry based on our model are currently not capable of determining the specific percentages of extracellular electron transfer mechanisms in a biofilm. The developed model will be a critical tool for designing experiments to explain EET mechanisms.