Accumulation and utilization of polysaccharide by hot-spring phototrophs during a light-dark transition

Diel metabolomics analysis of a hot spring chlorophototrophic microbial mat leads to new hypotheses of community member metabolisms

Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptive and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number of predominant taxa inhabit this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms, and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g., glycolate) and fermentation (e.g., acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gasses (e.g., H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: (1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; (2) photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; (3) glycolate and lactate are exchanged among Synechococcus and Roseiflexus spp.; and (4) fluctuations in many metabolite pools (e.g., wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences in their niches.

Comparison of Optimal Thermodynamic Models of the Tricarboxylic Acid Cycle from Heterotrophs, Cyanobacteria, and Green Sulfur Bacteria

We have applied a new stochastic simulation approach to predict the metabolite levels, material flux, and thermodynamic profiles of the oxidative TCA cycles found in E. coli and Synechococcus sp. PCC 7002, and in the reductive TCA cycle typical of chemolithoautotrophs and phototrophic green sulfur bacteria such as Chlorobaculum tepidum. The simulation approach is based on modeling states using statistical thermodynamics and employs an assumption similar to that used in transition state theory. The ability to evaluate the thermodynamics of metabolic pathways allows one to understand the relationship between coupling of energy and material gradients in the environment and the self-organization of stable biological systems, and it is shown that each cycle operates in the direction expected due to its environmental niche. The simulations predict changes in metabolite levels and flux in response to changes in cofactor concentrations that would be hard to predict without an elaborate model based on the law of mass action. In fact, we show that a thermodynamically unfavorable reaction can still have flux in the forward direction when it is part of a reaction network. The ability to predict metabolite levels, energy flow, and material flux should be significant for understanding the dynamics of natural systems and for understanding principles for engineering organisms for production of specialty chemicals.

OptCom: a multi-level optimization framework for the metabolic modeling and analysis of microbial communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models.

In silico approaches to study mass and energy flows in microbial consortia: a syntrophic case study

BACKGROUND

Three methods were developed for the application of stoichiometry-based network analysis approaches including elementary mode analysis to the study of mass and energy flows in microbial communities. Each has distinct advantages and disadvantages suitable for analyzing systems with different degrees of complexity and a priori knowledge. These approaches were tested and compared using data from the thermophilic, phototrophic mat communities from Octopus and Mushroom Springs in Yellowstone National Park (USA). The models were based on three distinct microbial guilds: oxygenic phototrophs, filamentous anoxygenic phototrophs, and sulfate-reducing bacteria. Two phases, day and night, were modeled to account for differences in the sources of mass and energy and the routes available for their exchange.

RESULTS

The in silico models were used to explore fundamental questions in ecology including the prediction of and explanation for measured relative abundances of primary producers in the mat, theoretical tradeoffs between overall productivity and the generation of toxic by-products, and the relative robustness of various guild interactions.

CONCLUSION

The three modeling approaches represent a flexible toolbox for creating cellular metabolic networks to study microbial communities on scales ranging from cells to ecosystems. A comparison of the three methods highlights considerations for selecting the one most appropriate for a given microbial system. For instance, communities represented only by metagenomic data can be modeled using the pooled method which analyzes a community's total metabolic potential without attempting to partition enzymes to different organisms. Systems with extensive a priori information on microbial guilds can be represented using the compartmentalized technique, employing distinct control volumes to separate guild-appropriate enzymes and metabolites. If the complexity of a compartmentalized network creates an unacceptable computational burden, the nested analysis approach permits greater scalability at the cost of more user intervention through multiple rounds of pathway analysis.

Population level functional diversity in a microbial community revealed by comparative genomic and metagenomic analyses

In microbial mat communities of Yellowstone hot springs, ribosomal RNA (rRNA) sequence diversity patterns indicate the presence of closely related bacterial populations along environmental gradients of temperature and light. To identify the functional bases for adaptation, we sequenced the genomes of two cyanobacterial (Synechococcus OS-A and OS-B') isolates representing ecologically distinct populations that dominate at different temperatures and are major primary producers in the mat. There was a marked lack of conserved large-scale gene order between the two Synechococcus genomes, indicative of extensive genomic rearrangements. Comparative genomic analyses showed that the isolates shared a large fraction of their gene content at high identity, yet, differences in phosphate and nitrogen utilization pathways indicated that they have adapted differentially to nutrient fluxes, possibly by the acquisition of genes by lateral gene transfer or their loss in certain populations. Comparisons of the Synechococcus genomes to metagenomic sequences derived from mats where these Synechococcus stains were originally isolated, revealed new facets of microbial diversity. First, Synechococcus populations at the lower temperature regions of the mat showed greater sequence diversity than those at high temperatures, consistent with a greater number of ecologically distinct populations at the lower temperature. Second, we found evidence of a specialized population that is apparently very closely related to Synechococcus OS-B', but contains genes that function in the uptake of reduced ferrous iron. In situ expression studies demonstrated that these genes are differentially expressed over the diel cycle, with highest expression when the mats are anoxic and iron may be in the reduced state. Genomic information from these mat-specific isolates and metagenomic information can be coupled to detect naturally occurring populations that are associated with different functionalities, not always represented by isolates, but which may nevertheless be important for niche partitioning and the establishment of microbial community structure.

Impact of carbon metabolism on 13C signatures of cyanobacteria and green non-sulfur-like bacteria inhabiting a microbial mat from an alkaline siliceous hot spring in Yellowstone National Park (USA)

Alkaline siliceous hot spring microbial mats in Yellowstone National Park are composed of two dominant phototropic groups, cyanobacteria and green non-sulfur-like bacteria (GNSLB). While cyanobacteria are thought to cross-feed low-molecular-weight organic compounds to support photoheterotrophic metabolism in GNSLB, it is unclear how this could lead to the heavier stable carbon isotopic signatures in GNSLB lipids compared with cyanobacterial lipids found in previous studies. The two groups of phototrophs were separated using percoll density gradient centrifugation and subsequent lipid and stable carbon isotopic analysis revealed that we obtained fractions with a approximately 60-fold enrichment in cyanobacterial and an approximately twofold enrichment in GNSLB biomass, respectively, compared with the mat itself. This technique was used to study the diel cycling and 13C content of the glucose pools in and the uptake of 13C-bicarbonate by the cyanobacteria and GNSLB, as well as the transfer of incorporated 13C from cyanobacteria to GNSLB. The results show that cyanobacteria have the highest bicarbonate uptake rates and accumulate glucose during the afternoon in full light conditions. In contrast, GNSLB have relatively higher bicarbonate uptake rates compared with cyanobacteria in the morning at low light levels. During the night GNSLB take up carbon that is likely derived through fermentation of cyanobacterial glucose enriched in 13C. The assimilation of 13C-enriched cyanobacterial carbon may thus lead to enriched 13C-contents of GNSLB cell components.

Diel variations in carbon metabolism by green nonsulfur-like bacteria in alkaline siliceous hot spring microbial mats from Yellowstone National Park

Green nonsulfur-like bacteria (GNSLB) in hot spring microbial mats are thought to be mainly photoheterotrophic, using cyanobacterial metabolites as carbon sources. However, the stable carbon isotopic composition of typical Chloroflexus and Roseiflexus lipids suggests photoautotrophic metabolism of GNSLB. One possible explanation for this apparent discrepancy might be that GNSLB fix inorganic carbon only during certain times of the day. In order to study temporal variability in carbon metabolism by GNSLB, labeling experiments with [13C]bicarbonate, [14C]bicarbonate, and [13C]acetate were performed during different times of the day. [14C]bicarbonate labeling indicated that during the morning, incorporation of label was light dependent and that both cyanobacteria and GNSLB were involved in bicarbonate uptake. 13C-labeling experiments indicated that during the morning, GNSLB incorporated labeled bicarbonate at least to the same degree as cyanobacteria. The incorporation of [13C]bicarbonate into specific lipids could be stimulated by the addition of sulfide or hydrogen, which both were present in the morning photic zone. The results suggest that GNSLB have the potential for photoautotrophic metabolism during low-light periods. In high-light periods, inorganic carbon was incorporated primarily into Cyanobacteria-specific lipids. The results of a pulse-labeling experiment were consistent with overnight transfer of label to GNSLB, which could be interrupted by the addition of unlabeled acetate and glycolate. In addition, we observed direct incorporation of [13C]acetate into GNSLB lipids in the morning. This suggests that GNSLB also have a potential for photoheterotrophy in situ.

Compound-specific isotopic fractionation patterns suggest different carbon metabolisms among Chloroflexus-like bacteria in hot-spring microbial mats

Stable carbon isotope fractionations between dissolved inorganic carbon and lipid biomarkers suggest photoautotrophy by Chloroflexus-like organisms in sulfidic and nonsulfidic Yellowstone hot springs. Where co-occurring, cyanobacteria appear to cross-feed Chloroflexus-like organisms supporting photoheterotrophy as well, although the relatively small 13C fractionation associated with cyanobacterial sugar biosynthesis may sometimes obscure this process.