Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections

Minimal Cut Sets (MCSs) identify sets of reactions which, when removed from a metabolic network, disable certain cellular functions. The traditional search for MCSs within genome-scale metabolic models (GSMMs) targets cellular growth, identifies reaction sets resulting in a lethal phenotype if disrupted, and retrieves a list of corresponding gene, mRNA, or enzyme targets. Using the dual link between MCSs and Elementary Flux Modes (EFMs), our logic programming-based tool aspefm was able to compute MCSs of any size from GSMMs in acceptable run times. The tool demonstrated better performance when computing large-sized MCSs than the mixed-integer linear programming methods. We applied the new MCSs methodology to a medically-relevant consortium model of two cross-feeding bacteria, Staphylococcus aureus and Pseudomonas aeruginosa. aspefm constraints were used to bias the computation of MCSs toward exchanged metabolites that could complement lethal phenotypes in individual species. We found that interspecies metabolite exchanges could play an essential role in rescuing single-species growth, for instance inosine could complement lethal reaction knock-outs in the purine synthesis, glycolysis, and pentose phosphate pathways of both bacteria. Finally, MCSs were used to derive a list of promising enzyme targets for consortium-level therapeutic applications that cannot be circumvented via interspecies metabolite exchange.

Simulating compatible solute biosynthesis using a metabolic flux model of the biomining acidophile, Acidithiobacillus ferrooxidans ATCC 23270

Halotolerant, acidophilic, bioleaching microorganisms are crucial to biomining operations that utilize saline water. Compatible solutes play an important role in the adaptation of these microorganisms to saline environments. Acidithiobacillus ferrooxidans ATCC 23270, an iron- and sulfur-oxidizing acidophilic bacterium, synthesizes trehalose as its native compatible solute but is still sensitive to salinity. Recently, halotolerant bioleaching bacteria were found to use ectoine as their key compatible solute. Previously, bioleaching bacteria were recalcitrant to genetic manipulation; however, recent advancements in genetic tools and techniques allow successful genetic modification of A. ferrooxidans ATCC 23270. Therefore, this study aimed to test, in silico, the effect of native and synthetic compatible solute biosynthesis by A. ferrooxidans ATCC 23270 on its growth and metabolism. Metabolic network flux modelling was used to provide a computational framework for the prediction of metabolic fluxes during production of native and synthetic compatible solutes by A. ferrooxidans ATCC 23270, in silico. Complete pathways for trehalose biosynthesis by the bacterium are proposed and captured in the updated metabolic model including a newly discovered UDP-dependent trehalose synthesis pathway. Finally, the effect of nitrogen sources on compatible solute production was simulated and showed that using nitrogen gas as the sole nitrogen source enables the ectoine-producing 'engineered' microbe to oxidize up to 20% more ferrous iron in comparison to the native microbe that only produces trehalose. Therefore, the predictive outcomes of the model have the potential to guide the design and optimization of a halotolerant strain of A. ferrooxidans ATCC 23270 for saline bioleaching operations.

Spatially resolved analysis of Pseudomonas aeruginosa biofilm proteomes measured by laser ablation sample transfer

Heterogeneity in the distribution of nutrients and oxygen gradients during biofilm growth gives rise to changes in phenotype. There has been long term interest in identifying spatial differences during biofilm development including clues that identify chemical heterogeneity. Laser ablation sample transfer (LAST) allows site-specific sampling combined with label free proteomics to distinguish radially and axially resolved proteomes for Pseudomonas aeruginosa biofilms. Specifically, differential protein abundances on oxic vs. anoxic regions of a biofilm were observed by combining LAST with bottom up proteomics. This study reveals a more active metabolism in the anoxic region of the biofilm with respect to the oxic region for this clinical strain of P. aeruginosa, despite this organism being considered an aerobe by nature. Protein abundance data related to cellular acclimations to chemical gradients include identification of glucose catabolizing proteins, high abundance of proteins from arginine and polyamine metabolism, and proteins that could also support virulence and environmental stress mediation in the anoxic region. Finally, the LAST methodology requires only a few mm2 of biofilm area to identify hundreds of proteins.

Limitation by a shared mutualist promotes coexistence of multiple competing partners

Although mutualisms are often studied as simple pairwise interactions, they typically involve complex networks of interacting species. How multiple mutualistic partners that provide the same service and compete for resources are maintained in mutualistic networks is an open question. We use a model bacterial community in which multiple 'partner strains' of Escherichia coli compete for a carbon source and exchange resources with a 'shared mutualist' strain of Salmonella enterica. In laboratory experiments, competing E. coli strains readily coexist in the presence of S. enterica, despite differences in their competitive abilities. We use ecological modeling to demonstrate that a shared mutualist can create temporary resource niche partitioning by limiting growth rates, even if yield is set by a resource external to a mutualism. This mechanism can extend to maintain multiple competing partner species. Our results improve our understanding of complex mutualistic communities and aid efforts to design stable microbial communities.

Pseudomonas aeruginosa reverse diauxie is a multidimensional, optimized, resource utilization strategy

Pseudomonas aeruginosa is a globally-distributed bacterium often found in medical infections. The opportunistic pathogen uses a different, carbon catabolite repression (CCR) strategy than many, model microorganisms. It does not utilize a classic diauxie phenotype, nor does it follow common systems biology assumptions including preferential consumption of glucose with an 'overflow' metabolism. Despite these contradictions, P. aeruginosa is competitive in many, disparate environments underscoring knowledge gaps in microbial ecology and systems biology. Physiological, omics, and in silico analyses were used to quantify the P. aeruginosa CCR strategy known as 'reverse diauxie'. An ecological basis of reverse diauxie was identified using a genome-scale, metabolic model interrogated with in vitro omics data. Reverse diauxie preference for lower energy, nonfermentable carbon sources, such as acetate or succinate over glucose, was predicted using a multidimensional strategy which minimized resource investment into central metabolism while completely oxidizing substrates. Application of a common, in silico optimization criterion, which maximizes growth rate, did not predict the reverse diauxie phenotypes. This study quantifies P. aeruginosa metabolic strategies foundational to its wide distribution and virulence including its potentially, mutualistic interactions with microorganisms found commonly in the environment and in medical infections.

Artificial consortium demonstrates emergent properties of enhanced cellulosic-sugar degradation and biofuel synthesis

Planktonic cultures, of a rationally designed consortium, demonstrated emergent properties that exceeded the sums of monoculture properties, including a >200% increase in cellobiose catabolism, a >100% increase in glycerol catabolism, a >800% increase in ethanol production, and a >120% increase in biomass productivity. The consortium was designed to have a primary and secondary-resource specialist that used crossfeeding with a positive feedback mechanism, division of labor, and nutrient and energy transfer via necromass catabolism. The primary resource specialist was Clostridium phytofermentans (a.k.a. Lachnoclostridium phytofermentans), a cellulolytic, obligate anaerobe. The secondary-resource specialist was Escherichia coli, a versatile, facultative anaerobe, which can ferment glycerol and byproducts of cellobiose catabolism. The consortium also demonstrated emergent properties of enhanced biomass accumulation when grown as biofilms, which created high cell density communities with gradients of species along the vertical axis. Consortium biofilms were robust to oxic perturbations with E. coli consuming O₂, creating an anoxic environment for C. phytofermentans. Anoxic/oxic cycling further enhanced biomass productivity of the biofilm consortium, increasing biomass accumulation ~250% over the sum of the monoculture biofilms. Consortium emergent properties were credited to several synergistic mechanisms. E. coli consumed inhibitory byproducts from cellobiose catabolism, driving higher C. phytofermentans growth and higher cellulolytic enzyme production, which in turn provided more substrate for E. coli. E. coli necromass enhanced C. phytofermentans growth while C. phytofermentans necromass aided E. coli growth via the release of peptides and amino acids, respectively. In aggregate, temporal cycling of necromass constituents increased flux of cellulose-derived resources through the consortium. The study establishes a consortia-based, bioprocessing strategy built on naturally occurring interactions for improved conversion of cellulose-derived sugars into bioproducts.

Interspecies interactions can enhance Pseudomonas aeruginosa tolerance to surfaces functionalized with silver nanoparticles

Development of anti-fouling surfaces is a major challenge in materials research. Microorganisms growing as biofilms have enhanced tolerance to antimicrobial strategies including antibiotics and antiseptics complicating the design of anti-fouling surfaces. Silver nanoparticles (AgNPs) are a promising antimicrobial technology with broad spectrum efficacy with a reduced likelihood of microorganisms developing resistance to the technology. This study tested the efficacy of new immobilized AgNP-modified surface technology against three common opportunistic pathogens grown either as monocultures or as cocultures. The presented study fills a gap in the literature by quantifying the efficacy of immobilized AgNP particles against multispecies biofilms. Polyethylene (PE) surfaces functionalized with the AgNPs were highly effective against Pseudomonas aeruginosa biofilms reducing viable cell counts by 99.8 % as compared to controls. However, the efficacy of the AgNP-modified PE surface was compromised when P. aeruginosa was cocultured with Candida albicans. Interspecies interactions can strongly influence the efficacy of anti-fouling AgNP coatings highlighting the need to test surfaces not only against biofilm phenotypes but under conditions representative of applications including the presence of multispecies consortia.

Pseudomonad reverse carbon catabolite repression, interspecies metabolite exchange, and consortial division of labor

Microorganisms acquire energy and nutrients from dynamic environments, where substrates vary in both type and abundance. The regulatory system responsible for prioritizing preferred substrates is known as carbon catabolite repression (CCR). Two broad classes of CCR have been documented in the literature. The best described CCR strategy, referred to here as classic CCR (cCCR), has been experimentally and theoretically studied using model organisms such as Escherichia coli. cCCR phenotypes are often used to generalize universal strategies for fitness, sometimes incorrectly. For instance, extremely competitive microorganisms, such as Pseudomonads, which arguably have broader global distributions than E. coli, have achieved their success using metabolic strategies that are nearly opposite of cCCR. These organisms utilize a CCR strategy termed 'reverse CCR' (rCCR), because the order of preferred substrates is nearly reverse that of cCCR. rCCR phenotypes prefer organic acids over glucose, may or may not select preferred substrates to optimize growth rates, and do not allocate intracellular resources in a manner that produces an overflow metabolism. cCCR and rCCR have traditionally been interpreted from the perspective of monocultures, even though most microorganisms live in consortia. Here, we review the basic tenets of the two CCR strategies and consider these phenotypes from the perspective of resource acquisition in consortia, a scenario that surely influenced the evolution of cCCR and rCCR. For instance, cCCR and rCCR metabolism are near mirror images of each other; when considered from a consortium basis, the complementary properties of the two strategies can mitigate direct competition for energy and nutrients and instead establish cooperative division of labor.

Integrated thermodynamic analysis of electron bifurcating [FeFe]-hydrogenase to inform anaerobic metabolism and H2 production

Electron bifurcating, [FeFe]-hydrogenases are recently described members of the hydrogenase family and catalyze a combination of exergonic and endergonic electron exchanges between three carriers (2 ferredoxin_red^- + NAD(P)H + 3 H⁺ = 2 ferredoxin_ox + NAD(P)⁺ + 2 H₂). A thermodynamic analysis of the bifurcating, [FeFe]-hydrogenase reaction, using electron path-independent variables, quantified potential biological roles of the reaction without requiring enzyme details. The bifurcating [FeFe]-hydrogenase reaction, like all bifurcating reactions, can be written as a sum of two non-bifurcating reactions. Therefore, the thermodynamic properties of the bifurcating reaction can never exceed the properties of the individual, non-bifurcating, reactions. The bifurcating [FeFe]-hydrogenase reaction has three competitive properties: 1) enabling NAD(P)H-driven proton reduction at pH₂ higher than the concurrent operation of the two, non-bifurcating reactions, 2) oxidation of NAD(P)H and ferredoxin simultaneously in a 1:1 ratio, both are produced during typical glucose fermentations, and 3) enhanced energy conservation (~10 kJ mol^-1 H₂) relative to concurrent operation of the two, non-bifurcating reactions. Our analysis demonstrated ferredoxin E°' largely determines the sensitivity of the bifurcating reaction to pH₂, modulation of the reduced/oxidized electron carrier ratios contributed less to equilibria shifts. Hydrogenase thermodynamics data were integrated with typical and non-typical glycolysis pathways to evaluate achieving the 'Thauer limit' (4 H₂ per glucose) as a function of temperature and pH₂. For instance, the bifurcating [FeFe]-hydrogenase reaction permits the Thauer limit at 60 °C if pH ₂ ≤ ~10 mbar. The results also predict Archaea, expressing a non-typical glycolysis pathway, would not benefit from a bifurcating [FeFe]-hydrogenase reaction; interestingly, no Archaea have been observed experimentally with a [FeFe]-hydrogenase enzyme.

Reverse diauxie phenotype in Pseudomonas aeruginosa biofilm revealed by exometabolomics and label-free proteomics

Microorganisms enhance fitness by prioritizing catabolism of available carbon sources using a process known as carbon catabolite repression (CCR). Planktonically grown Pseudomonas aeruginosa is known to prioritize the consumption of organic acids including lactic acid over catabolism of glucose using a CCR strategy termed "reverse diauxie." P. aeruginosa is an opportunistic pathogen with well-documented biofilm phenotypes that are distinct from its planktonic phenotypes. Reverse diauxie has been described in planktonic cultures, but it has not been documented explicitly in P. aeruginosa biofilms. Here a combination of exometabolomics and label-free proteomics was used to analyze planktonic and biofilm phenotypes for reverse diauxie. P. aeruginosa biofilm cultures preferentially consumed lactic acid over glucose, and in addition, the cultures catabolized the substrates completely and did not exhibit the acetate secreting "overflow" metabolism that is typical of many model microorganisms. The biofilm phenotype was enabled by changes in protein abundances, including lactate dehydrogenase, fumarate hydratase, GTP cyclohydrolase, L-ornithine N(5)-monooxygenase, and superoxide dismutase. These results are noteworthy because reverse diauxie-mediated catabolism of organic acids necessitates a terminal electron acceptor like O2, which is typically in low supply in biofilms due to diffusion limitation. Label-free proteomics identified dozens of proteins associated with biofilm formation including 16 that have not been previously reported, highlighting both the advantages of the methodology utilized here and the complexity of the proteomic adaptation for P. aeruginosa biofilms. Documenting the reverse diauxic phenotype in P. aeruginosa biofilms is foundational for understanding cellular nutrient and energy fluxes, which ultimately control growth and virulence.

In Silico Metabolic Design of Two-Strain Biofilm Systems Predicts Enhanced Biomass Production and Biochemical Synthesis

Engineered biofilm consortia have the potential to solve important biotechnological problems that have proved difficult for monoculture biofilms and planktonic consortia, such as conversion of lignocellulosic material to useful biochemicals. While considerable experimental progress has been reported for engineering and characterizing biofilm consortia, the field still lacks in silico tools for simulation, design, and optimization of stable, robust, and productive designed consortia. We developed biofilm consortia metabolic models for two coculture systems centered around the ecological design motif of a primary cell type that utilizes a supplied electron donor and secretes acetate as a byproduct and a secondary cell type that consumes the acetate, relieving byproduct inhibition on the primary cell type and enhancing overall system biomass. The models presented in this paper predict that distinct metabolic niches for the two cell types could be established by supplying electron donors and acceptors at opposite ends of the biofilm and that acetate consumption by the secondary cell type could increase total biomass accumulation and the synthesis of valuable biochemicals, such as isobutanol, by the primary cell type. System tunability is enhanced when each cell type is supplied with a unique terminal electron acceptor at opposite ends of the biofilm rather than competing for a common electron acceptor. Our model provides good qualitative agreement with data for a synthetic Escherichia coli coculture system, suggesting that the proposed design rules may have wide applicability to engineered biofilm consortia.

Role of resource allocation and transport in emergence of cross-feeding in microbial consortia

Microbial communities that implement mutual cross-feeding are commonly observed in nature and with synthetic constructs in laboratory experiments. A mathematical model of competition in a chemostat is developed to investigate the role that resource allocation and transport of metabolites play in cooperation. The model contains four cell types that differ by whether they produce two, one, or none of two essential metabolites. Producing cell types may export these resources into the environment, and those that do not produce both metabolites must import the missing resource. The contribution to the emergence of a collaborative consortium of single resource producers from the transport rate of these metabolites and the type of transport used by the cell (active vs. passive) is studied. Multiple instances of bi-stability and tri-stability are observed, and the effect of the initial concentration of a non-cooperative cheater cell type on the final outcome of the competition is examined. When the cost of producing metabolites is introduced into the model, significant changes to the outcome of the competition are observed, including coexistence of multiple cell types.

Multiscale analysis of autotroph-heterotroph interactions in a high-temperature microbial community

Interactions among microbial community members can lead to emergent properties, such as enhanced productivity, stability, and robustness. Iron-oxide mats in acidic (pH 2-4), high-temperature (> 65 °C) springs of Yellowstone National Park contain relatively simple microbial communities and are well-characterized geochemically. Consequently, these communities are excellent model systems for studying the metabolic activity of individual populations and key microbial interactions. The primary goals of the current study were to integrate data collected in situ with in silico calculations across process-scales encompassing enzymatic activity, cellular metabolism, community interactions, and ecosystem biogeochemistry, as well as to predict and quantify the functional limits of autotroph-heterotroph interactions. Metagenomic and transcriptomic data were used to reconstruct carbon and energy metabolisms of an important autotroph (Metallosphaera yellowstonensis) and heterotroph (Geoarchaeum sp. OSPB) from the studied Fe(III)-oxide mat communities. Standard and hybrid elementary flux mode and flux balance analyses of metabolic models predicted cellular- and community-level metabolic acclimations to simulated environmental stresses, respectively. In situ geochemical analyses, including oxygen depth-profiles, Fe(III)-oxide deposition rates, stable carbon isotopes and mat biomass concentrations, were combined with cellular models to explore autotroph-heterotroph interactions important to community structure-function. Integration of metabolic modeling with in situ measurements, including the relative population abundance of autotrophs to heterotrophs, demonstrated that Fe(III)-oxide mat communities operate at their maximum total community growth rate (i.e. sum of autotroph and heterotroph growth rates), as opposed to net community growth rate (i.e. total community growth rate subtracting autotroph consumed by heterotroph), as predicted from the maximum power principle. Integration of multiscale data with ecological theory provides a basis for predicting autotroph-heterotroph interactions and community-level cellular organization.

In a quest for engineering acidophiles for biomining applications: challenges and opportunities

Biomining with acidophilic microorganisms has been used at commercial scale for the extraction of metals from various sulfide ores. With metal demand and energy prices on the rise and the concurrent decline in quality and availability of mineral resources, there is an increasing interest in applying biomining technology, in particular for leaching metals from low grade minerals and wastes. However, bioprocessing is often hampered by the presence of inhibitory compounds that originate from complex ores. Synthetic biology could provide tools to improve the tolerance of biomining microbes to various stress factors that are present in biomining environments, which would ultimately increase bioleaching efficiency. This paper reviews the state-of-the-art tools to genetically modify acidophilic biomining microorganisms and the limitations of these tools. The first part of this review discusses resilience pathways that can be engineered in acidophiles to enhance their robustness and tolerance in harsh environments that prevail in bioleaching. The second part of the paper reviews the efforts that have been carried out towards engineering robust microorganisms and developing metabolic modelling tools. Novel synthetic biology tools have the potential to transform the biomining industry and facilitate the extraction of value from ores and wastes that cannot be processed with existing biomining microorganisms.

The Electron Bifurcating FixABCX Protein Complex from Azotobacter vinelandii: Generation of Low-Potential Reducing Equivalents for Nitrogenase Catalysis

The biological reduction of dinitrogen (N₂) to ammonia (NH₃) by nitrogenase is an energetically demanding reaction that requires low-potential electrons and ATP; however, pathways used to deliver the electrons from central metabolism to the reductants of nitrogenase, ferredoxin or flavodoxin, remain unknown for many diazotrophic microbes. The FixABCX protein complex has been proposed to reduce flavodoxin or ferredoxin using NADH as the electron donor in a process known as electron bifurcation. Herein, the FixABCX complex from Azotobacter vinelandii was purified and demonstrated to catalyze an electron bifurcation reaction: oxidation of NADH (E_m = -320 mV) coupled to reduction of flavodoxin semiquinone (E_m = -460 mV) and reduction of coenzyme Q (E_m = 10 mV). Knocking out fix genes rendered Δrnf A. vinelandii cells unable to fix dinitrogen, confirming that the FixABCX system provides another route for delivery of electrons to nitrogenase. Characterization of the purified FixABCX complex revealed the presence of flavin and iron-sulfur cofactors confirmed by native mass spectrometry, electron paramagnetic resonance spectroscopy, and transient absorption spectroscopy. Transient absorption spectroscopy further established the presence of a short-lived flavin semiquinone radical, suggesting that a thermodynamically unstable flavin semiquinone may participate as an intermediate in the transfer of an electron to flavodoxin. A structural model of FixABCX, generated using chemical cross-linking in conjunction with homology modeling, revealed plausible electron transfer pathways to both high- and low-potential acceptors. Overall, this study informs a mechanism for electron bifurcation, offering insight into a unique method for delivery of low-potential electrons required for energy-intensive biochemical conversions.

Combining Targeted Metabolomic Data with a Model of Glucose Metabolism: Toward Progress in Chondrocyte Mechanotransduction

Osteoarthritis is a debilitating disease likely involving altered metabolism of the chondrocytes in articular cartilage. Chondrocytes can respond metabolically to mechanical loads via cellular mechanotransduction, and metabolic changes are significant because they produce the precursors to the tissue matrix necessary for cartilage health. However, a comprehensive understanding of how energy metabolism changes with loading remains elusive. To improve our understanding of chondrocyte mechanotransduction, we developed a computational model to calculate the rate of reactions (i.e. flux) across multiple components of central energy metabolism based on experimental data. We calculated average reaction flux profiles of central metabolism for SW1353 human chondrocytes subjected to dynamic compression for 30 minutes. The profiles were obtained solving a bounded variable linear least squares problem, representing the stoichiometry of human central energy metabolism. Compression synchronized chondrocyte energy metabolism. These data are consistent with dynamic compression inducing early time changes in central energy metabolism geared towards more active protein synthesis. Furthermore, this analysis demonstrates the utility of combining targeted metabolomic data with a computational model to enable rapid analysis of cellular energy utilization.

Effects of Spatial Localization on Microbial Consortia Growth

Microbial consortia are commonly observed in natural and synthetic systems, and these consortia frequently result in higher biomass production relative to monocultures. The focus here is on the impact of initial spatial localization and substrate diffusivity on the growth of a model microbial consortium consisting of a producer strain that consumes glucose and produces acetate and a scavenger strain that consumes the acetate. The mathematical model is based on an individual cell model where growth is described by Monod kinetics, and substrate transport is described by a continuum-based, non-equilibrium reaction-diffusion model where convective transport is negligible (e.g., in a biofilm). The first set of results focus on a single producer cell at the center of the domain and surrounded by an initial population of scavenger cells. The impact of the initial population density and substrate diffusivity is examined. A transition is observed from the highest initial density resulting in the greatest cell growth to cell growth being independent of initial density. A high initial density minimizes diffusive transport time and is typically expected to result in the highest growth, but this expected behavior is not predicted in environments with lower diffusivity or larger length scales. When the producer cells are placed on the bottom of the domain with the scavenger cells above in a layered biofilm arrangement, a similar critical transition is observed. For the highest diffusivity values examined, a thin, dense initial scavenger layer is optimal for cell growth. However, for smaller diffusivity values, a thicker, less dense initial scavenger layer provides maximal growth. The overall conclusion is that high density clustering of members of a food chain is optimal under most common transport conditions, but under some slow transport conditions, high density clustering may not be optimal for microbial growth.

Stoichiometric modelling of assimilatory and dissimilatory biomass utilisation in a microbial community

Assimilatory and dissimilatory utilisation of autotroph biomass by heterotrophs is a fundamental mechanism for the transfer of nutrients and energy across trophic levels. Metagenome data from a tractable, thermoacidophilic microbial community in Yellowstone National Park was used to build an in silico model to study heterotrophic utilisation of autotroph biomass using elementary flux mode analysis and flux balance analysis. Assimilatory and dissimilatory biomass utilisation was investigated using 29 forms of biomass-derived dissolved organic carbon (DOC) including individual monomer pools, individual macromolecular pools and aggregate biomass. The simulations identified ecologically competitive strategies for utilizing DOC under conditions of varying electron donor, electron acceptor or enzyme limitation. The simulated growth environment affected which form of DOC was the most competitive use of nutrients; for instance, oxygen limitation favoured utilisation of less reduced and fermentable DOC while carbon-limited environments favoured more reduced DOC. Additionally, metabolism was studied considering two encompassing metabolic strategies: simultaneous versus sequential use of DOC. Results of this study bound the transfer of nutrients and energy through microbial food webs, providing a quantitative foundation relevant to most microbial ecosystems.

Metabolic modeling of a chronic wound biofilm consortium predicts spatial partitioning of bacterial species

Background

Chronic wounds are often colonized by consortia comprised of different bacterial species growing as biofilms on a complex mixture of wound exudate. Bacteria growing in biofilms exhibit phenotypes distinct from planktonic growth, often rendering the application of antibacterial compounds ineffective. Computational modeling represents a complementary tool to experimentation for generating fundamental knowledge and developing more effective treatment strategies for chronic wound biofilm consortia.

Results

We developed spatiotemporal models to investigate the multispecies metabolism of a biofilm consortium comprised of two common chronic wound isolates: the aerobe Pseudomonas aeruginosa and the facultative anaerobe Staphylococcus aureus. By combining genome-scale metabolic reconstructions with partial differential equations for metabolite diffusion, the models were able to provide both temporal and spatial predictions with genome-scale resolution. The models were used to analyze the metabolic differences between single species and two species biofilms and to demonstrate the tendency of the two bacteria to spatially partition in the multispecies biofilm as observed experimentally. Nutrient gradients imposed by supplying glucose at the bottom and oxygen at the top of the biofilm induced spatial partitioning of the two species, with S. aureus most concentrated in the anaerobic region and P. aeruginosa present only in the aerobic region. The two species system was predicted to support a maximum biofilm thickness much greater than P. aeruginosa alone but slightly less than S. aureus alone, suggesting an antagonistic metabolic effect of P. aeruginosa on S. aureus. When each species was allowed to enhance its growth through consumption of secreted metabolic byproducts assuming identical uptake kinetics, the competitiveness of P. aeruginosa was further reduced due primarily to the more efficient lactate metabolism of S. aureus. Lysis of S. aureus by a small molecule inhibitor secreted from P. aeruginosa and/or P. aeruginosa aerotaxis were predicted to substantially increase P. aeruginosa competitiveness in the aerobic region, consistent with in vitro experimental studies.

Conclusions

Our biofilm modeling approach allows the prediction of individual species metabolism and interspecies interactions in both time and space with genome-scale resolution. This study yielded new insights into the multispecies metabolism of a chronic wound biofilm, in particular metabolic factors that may lead to spatial partitioning of the two bacterial species. We believe that P. aeruginosa lysis of S. aureus combined with nutrient competition is a particularly relevant scenario for which model predictions could be tested experimentally.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0334-8) contains supplementary material, which is available to authorized users.

Integrated molecular, physiological and in silico characterization of two Halomonas isolates from industrial brine

Two haloalkaliphilic bacteria isolated from industrial brine solutions were characterized via molecular, physiological, and in silico metabolic pathway analyses. Genomes from the organisms, designated Halomonas BC1 and BC2, were sequenced; 16S ribosomal subunit-based phylogenetic analysis revealed a high level of similarity to each other and to Halomonas meridiana. Both strains were moderate halophiles with near optimal specific growth rates (≥60 % μ max) observed over <0.1-5 % (w/v) NaCl and pH ranging from 7.4 to 10.2. Isolate BC1 was further characterized by measuring uptake or synthesis of compatible solutes under different growth conditions; in complex medium, uptake and accumulation of external glycine betaine was observed while ectoine was synthesized de novo in salts medium. Transcriptome analysis of isolate BC1 grown on glucose or citrate medium measured differences in glycolysis- and gluconeogenesis-based metabolisms, respectively. The annotated BC1 genome was used to build an in silico, genome-scale stoichiometric metabolic model to study catabolic energy strategies and compatible solute synthesis under gradients of oxygen and nutrient availability. The theoretical analysis identified energy metabolism challenges associated with acclimation to high salinity and high pH. The study documents central metabolism data for the industrially and scientifically important haloalkaliphile genus Halomonas.

Physiological, biomass elemental composition and proteomic analyses of Escherichia coli ammonium-limited chemostat growth, and comparison with iron- and glucose-limited chemostat growth

Escherichia coli physiological, biomass elemental composition and proteome acclimations to ammonium-limited chemostat growth were measured at four levels of nutrient scarcity controlled via chemostat dilution rate. These data were compared with published iron- and glucose-limited growth data collected from the same strain and at the same dilution rates to quantify general and nutrient-specific responses. Severe nutrient scarcity resulted in an overflow metabolism with differing organic byproduct profiles based on limiting nutrient and dilution rate. Ammonium-limited cultures secreted up to 35% of the metabolized glucose carbon as organic byproducts with acetate representing the largest fraction; in comparison, iron-limited cultures secreted up to 70 % of the metabolized glucose carbon as lactate, and glucose-limited cultures secreted up to 4% of the metabolized glucose carbon as formate. Biomass elemental composition differed with nutrient limitation; biomass from ammonium-limited cultures had a lower nitrogen content than biomass from either iron- or glucose-limited cultures. Proteomic analysis of central metabolism enzymes revealed that ammonium- and iron-limited cultures had a lower abundance of key tricarboxylic acid (TCA) cycle enzymes and higher abundance of key glycolysis enzymes compared with glucose-limited cultures. The overall results are largely consistent with cellular economics concepts, including metabolic tradeoff theory where the limiting nutrient is invested into essential pathways such as glycolysis instead of higher ATP-yielding, but non-essential, pathways such as the TCA cycle. The data provide a detailed insight into ecologically competitive metabolic strategies selected by evolution, templates for controlling metabolism for bioprocesses and a comprehensive dataset for validating in silico representations of metabolism.

Differentiation of microbial species and strains in coculture biofilms by multivariate analysis of laser desorption postionization mass spectra

7.87 to 10.5 eV vacuum ultraviolet (VUV) photon energies were used in laser desorption postionization mass spectrometry (LDPI-MS) to analyze biofilms comprised of binary cultures of interacting microorganisms. The effect of photon energy was examined using both tunable synchrotron and laser sources of VUV radiation. Principal components analysis (PCA) was applied to the MS data to differentiate species in Escherichia coli-Saccharomyces cerevisiae coculture biofilms. PCA of LDPI-MS also differentiated individual E. coli strains in a biofilm comprised of two interacting gene deletion strains, even though these strains differed from the wild type K-12 strain by no more than four gene deletions each out of approximately 2000 genes. PCA treatment of 7.87 eV LDPI-MS data separated the E. coli strains into three distinct groups, two "pure" groups, and a mixed region. Furthermore, the "pure" regions of the E. coli cocultures showed greater variance by PCA at 7.87 eV photon energies compared to 10.5 eV radiation. This is consistent with the expectation that the 7.87 eV photoionization selects a subset of low ionization energy analytes while 10.5 eV is more inclusive, detecting a wider range of analytes. These two VUV photon energies therefore give different spreads via PCA and their respective use in LDPI-MS constitute an additional experimental parameter to differentiate strains and species.

Quantitative NMR metabolite profiling of methicillin-resistant and methicillin-susceptible Staphylococcus aureus discriminates between biofilm and planktonic phenotypes

Wound bioburden in the form of colonizing biofilms is a major contributor to nonhealing wounds. Staphylococcus aureus is a Gram-positive, facultative anaerobe commonly found in chronic wounds; however, much remains unknown about the basic physiology of this opportunistic pathogen, especially with regard to the biofilm phenotype. Transcriptomic and proteomic analysis of S. aureus biofilms have suggested that S. aureus biofilms exhibit an altered metabolic state relative to the planktonic phenotype. Herein, comparisons of extracellular and intracellular metabolite profiles detected by (1)H NMR were conducted for methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) S. aureus strains grown as biofilm and planktonic cultures. Principal component analysis distinguished the biofilm phenotype from the planktonic phenotype, and factor loadings analysis identified metabolites that contributed to the statistical separation of the biofilm from the planktonic phenotype, suggesting that key features distinguishing biofilm from planktonic growth include selective amino acid uptake, lipid catabolism, butanediol fermentation, and a shift in metabolism from energy production to assembly of cell-wall components and matrix deposition. These metabolite profiles provide a basis for the development of metabolite biomarkers that distinguish between biofilm and planktonic phenotypes in S. aureus and have the potential for improved diagnostic and therapeutic use in chronic wounds.

Direct measurement and characterization of active photosynthesis zones inside wastewater remediating and biofuel producing microalgal biofilms

Microalgal biofilm based technologies are of keen interest due to their high biomass concentrations and ability to utilize light and CO2. While photoautotrophic biofilms have long been used for wastewater remediation, biofuel production represents a relatively new and under-represented focus area. However, the direct measurement and characterization of fundamental parameters required for industrial control are challenging due to biofilm heterogeneity. This study evaluated oxygenic photosynthesis and respiration on two distinct microalgal biofilms cultured using a novel rotating algal biofilm reactor operated at field- and laboratory-scales. Clear differences in oxygenic photosynthesis and respiration were observed based on different culturing conditions, microalgal composition, light intensity and nitrogen availability. The cultures were also evaluated as potential biofuel synthesis strategies. Nitrogen depletion was not found to have the same effect on lipid accumulation compared to traditional planktonic microalgal studies. Physiological characterizations of these microalgal biofilms identify fundamental parameters needed to understand and control process optimization.

Complete enumeration of elementary flux modes through scalable demand-based subnetwork definition

MOTIVATION

Elementary flux mode analysis (EFMA) decomposes complex metabolic network models into tractable biochemical pathways, which have been used for rational design and analysis of metabolic and regulatory networks. However, application of EFMA has often been limited to targeted or simplified metabolic network representations due to computational demands of the method.

RESULTS

Division of biological networks into subnetworks enables the complete enumeration of elementary flux modes (EFMs) for metabolic models of a broad range of complexities, including genome-scale. Here, subnetworks are defined using serial dichotomous suppression and enforcement of flux through model reactions. Rules for selecting appropriate reactions to generate subnetworks are proposed and tested; three test cases, including both prokaryotic and eukaryotic network models, verify the efficacy of these rules and demonstrate completeness and reproducibility of EFM enumeration. Division of models into subnetworks is demand-based and automated; computationally intractable subnetworks are further divided until the entire solution space is enumerated. To demonstrate the strategy's scalability, the splitting algorithm was implemented using an EFMA software package (EFMTool) and Windows PowerShell on a 50 node Microsoft high performance computing cluster. Enumeration of the EFMs in a genome-scale metabolic model of a diatom, Phaeodactylum tricornutum, identified ∼2 billion EFMs. The output represents an order of magnitude increase in EFMs computed compared with other published algorithms and demonstrates a scalable framework for EFMA of most systems.

Design, construction, and characterization methodologies for synthetic microbial consortia

Engineered microbial consortia are of growing interest to a range of scientists including bioprocess engineers, systems biologists, and microbiologists because of their ability to simultaneously optimize multiple tasks, to test fundamental systems science, and to understand the microbial ecology of environments like chronic wounds. Metabolic engineering, synthetic biology, and microbial ecology provide a sound scientific basis for designing, building, and analyzing consortium-based microbial platforms.This chapter outlines strategies and protocols useful for (1) in silico network design, (2) experimental strain construction, (3) consortia culturing including biofilm growth methods, and (4) physiological characterization of consortia. The laboratory and computational methods given here may be adapted for synthesis and characterization of other engineered consortia designs.

Molecular imaging and depth profiling of biomaterials interfaces by femtosecond laser desorption postionization mass spectrometry

Mass spectrometry (MS) imaging is increasingly being applied to probe the interfaces of biomaterials with invasive microbial biofilms, human tissue, or other biological materials. Laser desorption vacuum ultraviolet postionization with ∼75 fs, 800 nm laser pulses (fs-LDPI-MS) was used to collect MS images of a yeast-Escherichia coli co-culture biofilm. The method was also used to depth profile a three-dimensionally structured, multispecies biofilm. Finally, fs-LDPI-MS analyses of yeast biofilms grown under different conditions were compared with LDPI-MS using ultraviolet, nanosecond pulse length laser desorption as well as with fs laser desorption ionization without postionization. Preliminary implications for the use of fs-LDPI-MS for the analysis of biomaterials interfaces are discussed and contrasted with established methods in MS imaging.

In situ analysis of oxygen consumption and diffusive transport in high-temperature acidic iron-oxide microbial mats

The role of dissolved oxygen as a principal electron acceptor for microbial metabolism was investigated within Fe(III)-oxide microbial mats that form in acidic geothermal springs of Yellowstone National Park (USA). Specific goals of the study were to measure and model dissolved oxygen profiles within high-temperature (65-75°C) acidic (pH = 2.7-3.8) Fe(III)-oxide microbial mats, and correlate the abundance of aerobic, iron-oxidizing Metallosphaera yellowstonensis organisms and mRNA gene expression levels to Fe(II)-oxidizing habitats shown to consume oxygen. In situ oxygen microprofiles were obtained perpendicular to the direction of convective flow across the aqueous phase/Fe(III)-oxide microbial mat interface using oxygen microsensors. Dissolved oxygen concentrations dropped from ∼ 50-60 μM in the bulk-fluid/mat surface to below detection (< 0.3 μM) at a depth of ∼ 700 μm (∼ 10% of the total mat depth). Net areal oxygen fluxes into the microbial mats were estimated to range from 1.4-1.6 × 10(-4)  μmol cm(-2)  s(-1) . Dimensionless parameters were used to model dissolved oxygen profiles and establish that mass transfer rates limit the oxygen consumption. A zone of higher dissolved oxygen at the mat surface promotes Fe(III)-oxide biomineralization, which was supported using molecular analysis of Metallosphaera yellowstonensis 16S rRNA gene copy numbers and mRNA expression of haem Cu oxidases (FoxA) associated with Fe(II)-oxidation.

Microbial Consortia Engineering for Cellular Factories: in vitro to in silico systems

This mini-review discusses the current state of experimental and computational microbial consortia engineering with a focus on cellular factories. A discussion of promising ecological theories central to community resource usage is presented to facilitate interpretation of consortial designs. Recent case studies exemplifying different resource usage motifs and consortial assembly templates are presented. The review also highlights in silico approaches to design and to analyze consortia with an emphasis on stoichiometric modeling methods. The discipline of microbial consortia engineering possesses a widely accepted potential to generate highly novel and effective bio-catalysts for applications from biofuels to specialty chemicals to enhanced mineral recovery.

Laser desorption VUV postionization MS imaging of a cocultured biofilm

Laser desorption postionization mass spectrometry (LDPI-MS) imaging is demonstrated with a 10.5 eV photon energy source for analysis and imaging of small endogenous molecules within intact biofilms. Biofilm consortia comprised of a synthetic Escherichia coli K12 coculture engineered for syntrophic metabolite exchange are grown on membranes and then used to test LDPI-MS analysis and imaging. Both E. coli strains displayed many similar peaks in LDPI-MS up to m/z 650, although some observed differences in peak intensities were consistent with the appearance of byproducts preferentially expressed by one strain. The relatively low mass resolution and accuracy of this specific LDPI-MS instrument prevented definitive assignment of species to peaks, but strategies are discussed to overcome this shortcoming. The results are also discussed in terms of desorption and ionization issues related to the use of 10.5 eV single-photon ionization, with control experiments providing additional mechanistic information. Finally, 10.5 eV LDPI-MS was able to collect ion images from intact, electrically insulating biofilms at ~100 μm spatial resolution. Spatial resolution of ~20 μm was possible, although a relatively long acquisition time resulted from the 10 Hz repetition rate of the single-photon ionization source.

Identification and imaging of peptides and proteins on Enterococcus faecalis biofilms by matrix assisted laser desorption ionization mass spectrometry

The heptapeptide ARHPHPH was identified from biofilms and planktonic cultures of two different strains of Enterococcus faecalis, V583 and ATCC 29212, using matrix assisted laser desorption ionization mass spectrometry (MALDI-MS). ARHPHPH was also imaged at the boundary of cocultured, adjacent E. faecalis and Escherichia coli (ATCC 25922) biofilms, appearing only on the E. faecalis side. ARHPHPH was proteolyzed from κ-casein, a component in the growth media, by E. faecalis microbes. Additionally, top down and bottom up proteomic approaches were combined to identify and spatially locate multiple proteins within intact E. faecalis V583 biofilms by MALDI-MS. The resultant tandem MS data were searched against the NCBInr E. faecalis V583 database to identify thirteen cytosolic and membrane proteins which have functional association with the cell surface. Two of these proteins, enolase and GAPDH, are glycolytic enzymes known to display multiple functions in bacterial virulence in related bacterial strains. This work illustrates a powerful approach for discovering and localizing multiple peptides and proteins within intact biofilms.

Potential role of multiple carbon fixation pathways during lipid accumulation in Phaeodactylum tricornutum

BACKGROUND

Phaeodactylum tricornutum is a unicellular diatom in the class Bacillariophyceae. The full genome has been sequenced (<30 Mb), and approximately 20 to 30% triacylglyceride (TAG) accumulation on a dry cell basis has been reported under different growth conditions. To elucidate P. tricornutum gene expression profiles during nutrient-deprivation and lipid-accumulation, cell cultures were grown with a nitrate to phosphate ratio of 20:1 (N:P) and whole-genome transcripts were monitored over time via RNA-sequence determination.

RESULTS

The specific Nile Red (NR) fluorescence (NR fluorescence per cell) increased over time; however, the increase in NR fluorescence was initiated before external nitrate was completely exhausted. Exogenous phosphate was depleted before nitrate, and these results indicated that the depletion of exogenous phosphate might be an early trigger for lipid accumulation that is magnified upon nitrate depletion. As expected, many of the genes associated with nitrate and phosphate utilization were up-expressed. The diatom-specific cyclins cyc7 and cyc10 were down-expressed during the nutrient-deplete state, and cyclin B1 was up-expressed during lipid-accumulation after growth cessation. While many of the genes associated with the C3 pathway for photosynthetic carbon reduction were not significantly altered, genes involved in a putative C4 pathway for photosynthetic carbon assimilation were up-expressed as the cells depleted nitrate, phosphate, and exogenous dissolved inorganic carbon (DIC) levels. P. tricornutum has multiple, putative carbonic anhydrases, but only two were significantly up-expressed (2-fold and 4-fold) at the last time point when exogenous DIC levels had increased after the cessation of growth. Alternative pathways that could utilize HCO3- were also suggested by the gene expression profiles (e.g., putative propionyl-CoA and methylmalonyl-CoA decarboxylases).

CONCLUSIONS

The results indicate that P. tricornutum continued carbon dioxide reduction when population growth was arrested and different carbon-concentrating mechanisms were used dependent upon exogenous DIC levels. Based upon overall low gene expression levels for fatty acid synthesis, the results also suggest that the build-up of precursors to the acetyl-CoA carboxylases may play a more significant role in TAG synthesis rather than the actual enzyme levels of acetyl-CoA carboxylases per se. The presented insights into the types and timing of cellular responses to inorganic carbon will help maximize photoautotrophic carbon flow to lipid accumulation.

Resolution of volatile fuel compound profiles from Ascocoryne sarcoides: a comparison by proton transfer reaction-mass spectrometry and solid phase microextraction gas chromatography-mass spectrometry

Volatile hydrocarbon production by Ascocoryne sacroides was studied over its growth cycle. Gas-phase compounds were measured continuously with a proton transfer reaction-mass spectrometry (PTR-MS) and at distinct time points with gas chromatography-mass spectrometry (GC-MS) using head space solid phase microextraction (SPME). The PTR-MS ion signal permitted temporal resolution of the volatile production while the SPME results revealed distinct compound identities. The quantitative PTR-MS results showed the volatile production was dominated by ethanol and acetaldehyde, while the concentration of the remainder of volatiles consistently reached 2,000 ppbv. The measurement of alcohols from the fungal culture by the two techniques correlated well. Notable compounds of fuel interest included nonanal, 1-octen-3-ol, 1-butanol, 3-methyl- and benzaldehyde. Abiotic comparison of the two techniques demonstrated SPME fiber bias toward higher molecular weight compounds, making quantitative efforts with SPME impractical. Together, PTR-MS and SPME GC-MS were shown as valuable tools for characterizing volatile fuel compound production from microbiological sources.

Systems analysis of microbial adaptations to simultaneous stresses

Microbes live in multi-factorial environments and have evolved under a variety of concurrent stresses including resource scarcity. Their metabolic organization is a reflection of their evolutionary histories and, in spite of decades of research, there is still a need for improved theoretical tools to explain fundamental aspects of microbial physiology. Using ecological and economic concepts, this chapter explores a resource-ratio based theory to elucidate microbial strategies for extracting and channeling mass and energy. The theory assumes cellular fitness is maximized by allocating scarce resources in appropriate proportions to multiple stress responses. Presented case studies deconstruct metabolic networks into a complete set of minimal biochemical pathways known as elementary flux modes. An economic analysis of the elementary flux modes tabulates enzyme atomic synthesis requirements from amino acid sequences and pathway operating costs from catabolic efficiencies, permitting characterization of inherent tradeoffs between resource investment and phenotype. A set of elementary flux modes with competitive tradeoffs properties can be mathematically projected onto experimental fluxomics datasets to decompose measured phenotypes into metabolic adaptations, interpreted as cellular responses proportional to the experienced culturing stresses. The resource-ratio based method describes the experimental phenotypes with greater accuracy than other contemporary approaches and further analysis suggests the results are both statistically and biologically significant. The insight into metabolic network design principles including tradeoffs associated with concurrent stress adaptation provides a foundation for interpreting physiology as well as for rational control and engineering of medically, environmentally, and industrially relevant microbes.

Synthetic Escherichia coli consortia engineered for syntrophy demonstrate enhanced biomass productivity

Synthetic Escherichia coli consortia engineered for syntrophy demonstrated enhanced biomass productivity relative to monocultures. Binary consortia were designed to mimic a ubiquitous, naturally occurring ecological template of primary productivity supported by secondary consumption. The synthetic consortia replicated this evolution-proven strategy by combining a glucose positive E. coli strain, which served as the system's primary producer, with a glucose negative E. coli strain which consumed metabolic byproducts from the primary producer. The engineered consortia utilized strategic division of labor to simultaneously optimize multiple tasks enhancing overall culture performance. Consortial interactions resulted in the emergent property of enhanced system biomass productivity which was demonstrated with three distinct culturing systems: batch, chemostat and biofilm growth. Glucose-based biomass productivity increased by ∼15, 20 and 50% compared to appropriate monoculture controls for these three culturing systems, respectively. Interestingly, the consortial interactions also produced biofilms with predictable, self-assembling, laminated microstructures. This study establishes a metabolic engineering paradigm which can be easily adapted to existing E. coli based bioprocesses to improve productivity based on a robust ecological theme.

Molecular-level tradeoffs and metabolic adaptation to simultaneous stressors

Life is a dynamic process driven by the complex interplay between physical constraints and selection pressures, ranging from nutrient limitation to inhibitory substances to predators. These stressors are not mutually exclusive; microbes have faced concurrent challenges for eons. Genome-enabled systems biology approaches are adapting economic and ecological concepts like tradeoff curves and strategic resource allocation theory to analyze metabolic adaptations to simultaneous stressors. These methodologies can accurately describe and predict metabolic adaptations to concurrent stresses by considering the tradeoff between investment of limiting resources into enzymatic machinery and the resulting cellular function. The approaches represent promising links between computational biology and well-established economic and ecological methodologies for analyzing the interplay between physical constraints and microbial fitness.

Robustness analysis of culturing perturbations on Escherichia coli colony biofilm beta-lactam and aminoglycoside antibiotic tolerance

Background

Biofilms are ubiquitous. For instance, the majority of medical infections are thought to involve biofilms. However even after decades of investigation, the in vivo efficacy of many antimicrobial strategies is still debated suggesting there is a need for better understanding of biofilm antimicrobial tolerances. The current study's goal is to characterize the robustness of biofilm antibiotic tolerance to medically and industrially relevant culturing perturbations. By definition, robust systems will return similar, predictable responses when perturbed while non-robust systems will return very different and potentially unpredictable responses. The predictability of an antibiotic tolerance response is essential to developing, testing, and employing antimicrobial strategies.

Results

The antibiotic tolerance of Escherichia coli colony biofilms was tested against beta-lactam and aminoglycoside class antibiotics. Control scenario tolerances were compared to tolerances under culturing perturbations including 1) different nutritional environments 2) different temperatures 3) interruption of cellular quorum sensing and 4) different biofilm culture ages. Here, antibiotic tolerance was defined in terms of culturable biofilm cells recovered after a twenty four hour antibiotic treatment.

Colony biofilm antibiotic tolerances were not robust to perturbations. Altering basic culturing parameters like nutritional environment or temperature resulted in very different, non-intuitive antibiotic tolerance responses. Some minor perturbations like increasing the glucose concentration from 0.1 to 1 g/L caused a ten million fold difference in culturable cells over a twenty four hour antibiotic treatment.

Conclusions

The current study presents a basis for robustness analysis of biofilm antibiotic tolerance. Biofilm antibiotic tolerance can vary in unpredictable manners based on modest changes in culturing conditions. Common antimicrobial testing methods, which only consider a single culturing condition, are not desirable since slight culturing variations can lead to very different outcomes. The presented data suggest it is essential to test antimicrobial strategies over a range of culturing perturbations relevant to the targeted application. In addition, the highly dynamic antibiotic tolerance responses observed here may explain why some current antimicrobial strategies occasionally fail.

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.

Decomposition of complex microbial behaviors into resource-based stress responses

MOTIVATION

Highly redundant metabolic networks and experimental data from cultures likely adapting simultaneously to multiple stresses can complicate the analysis of cellular behaviors. It is proposed that the explicit consideration of these factors is critical to understanding the competitive basis of microbial strategies.

RESULTS

Wide ranging, seemingly unrelated Escherichia coli physiological fluxes can be simply and accurately described as linear combinations of a few ecologically relevant stress adaptations. These strategies were identified by decomposing the central metabolism of E.coli into elementary modes (mathematically defined biochemical pathways) and assessing the resource investment cost-benefit properties for each pathway. The approach capitalizes on the inherent tradeoffs related to investing finite resources like nitrogen into different pathway enzymes when the pathways have varying metabolic efficiencies. The subset of ecologically competitive pathways represented 0.02% of the total permissible pathways. The biological relevance of the assembled strategies was tested against 10 000 randomly constructed pathway subsets. None of the randomly assembled collections were able to describe all of the considered experimental data as accurately as the cost-based subset. The results suggest these metabolic strategies are biologically significant. The current descriptions were compared with linear programming (LP)-based flux descriptions using the Euclidean distance metric. The current study's pathway subset described the experimental fluxes with better accuracy than the LP results without having to test multiple objective functions or constraints and while providing additional ecological insight into microbial behavior. The assembled pathways seem to represent a generalized set of strategies that can describe a wide range of microbial responses and hint at evolutionary processes where a handful of successful metabolic strategies are utilized simultaneously in different combinations to adapt to diverse conditions.

Anti-biofilm properties of chitosan-coated surfaces

Surfaces coated with the naturally-occurring polysaccharide chitosan (partially deacetylated poly N-acetyl glucosamine) resisted biofilm formation by bacteria and yeast. Reductions in biofilm viable cell numbers ranging from 95% to 99.9997% were demonstrated for Staphylococcus epidermidis, Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa and Candida albicans on chitosan-coated surfaces over a 54-h experiment in comparison to controls. For instance, chitosan-coated surfaces reduced S. epidermidis surface-associated growth more than 5.5 (10)log units (99.9997%) compared to a control surface. As a comparison, coatings containing a combination of the antibiotics minocycline and rifampin reduced S. epidermidis growth by 3.9 (10)log units (99.99%) and coatings containing the antiseptic chlorhexidine did not significantly reduce S. epidermidis surface associated growth as compared to controls. The chitosan effects were confirmed with microscopy. Using time-lapse fluorescence microscopy and fluorescent-dye-loaded S. epidermidis, the permeabilization of these cells was observed as they alighted on chitosan-coated surfaces. This suggests chitosan disrupts cell membranes as microbes settle on the surface. Chitosan offers a flexible, biocompatible platform for designing coatings to protect surfaces from infection.

Metabolic systems cost-benefit analysis for interpreting network structure and regulation

MOTIVATION

Interpretation of bioinformatics data in terms of cellular function is a major challenge facing systems biology. This question is complicated by robust metabolic networks filled with structural features like parallel pathways and isozymes. Under conditions of nutrient sufficiency, metabolic networks are well known to be regulated for thermodynamic efficiency however; efficient biochemical pathways are anabolically expensive to construct. While parameters like thermodynamic efficiency have been extensively studied, a systems-based analysis of anabolic proteome synthesis 'costs' and the cellular function implications of these costs has not been reported.

RESULTS

A cost-benefit analysis of an in silico Escherichia coli network revealed the relationship between metabolic pathway proteome synthesis requirements, DNA-coding sequence length, thermodynamic efficiency and substrate affinity. The results highlight basic metabolic network design principles. Pathway proteome synthesis requirements appear to have shaped biochemical network structure and regulation. Under conditions of nutrient scarcity and other general stresses, E. coli expresses pathways with relatively inexpensive proteome synthesis requirements instead of more efficient but also anabolically more expensive pathways. This evolutionary strategy provides a cellular function-based explanation for common network motifs like isozymes and parallel pathways and possibly explains 'overflow' metabolisms observed during nutrient scarcity.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A new spin on an old model: in vivo evaluation of disease progression by magnetic resonance imaging with respect to standard inflammatory parameters and histopathology in the adjuvant arthritic rat

OBJECTIVE

To noninvasively examine the pathogenesis of rat adjuvant-induced arthritis (AIA) by magnetic resonance imaging (MRI), and to correlate MRI indices of disease progression with classic inflammatory parameters and histologic evaluation.

METHODS

AIA was established in male Lewis rats following subcutaneous injection in the right hindpaw with 0.5 mg of heat-killed Mycobacterium butyricum suspended in light mineral oil. In vivo MRI evaluations of soft tissue and bony changes in AIA rats with matched histopathology were correlated with changes in left hindpaw volumes, circulating leukocytes, acute-phase reactants, and urinary collagen crosslinks throughout the disease process.

RESULTS

MRI of arthritic tibiotarsal joints of the uninjected left hindpaws from AIA rats demonstrated 2 distinct phases of disease activity. The first phase, apparent between days 10 and 18, was characterized by periarticular inflammation with marked synovitis, synovial fibroplasia, and distension of the joint capsule into the surrounding tissue. The secondary phase, occurring between days 18 and 30, was marked by continued soft tissue inflammation, periostitis with osteolysis, and periosteal new bone formation progressing to a state of near complete ankylosis by day 30. These 2 phases of disease activity observed by MRI paralleled biochemical, cellular, and histologic markers of disease progression.

CONCLUSION

MRI can be used to noninvasively detect, monitor, and quantify the chronic synovitis and progressive destruction of soft tissue and bone in live AIA rats, thereby improving the ability to evaluate disease progression in this preclinical animal model of rheumatoid arthritis.

A new spin on an old model: in vivo evaluation of disease progression by magnetic resonance imaging with respect to standard inflammatory parameters and histopathology in the adjuvant arthritic rat

OBJECTIVE

To noninvasively examine the pathogenesis of rat adjuvant-induced arthritis (AIA) by magnetic resonance imaging (MRI), and to correlate MRI indices of disease progression with classic inflammatory parameters and histologic evaluation.

METHODS

AIA was established in male Lewis rats following subcutaneous injection in the right hindpaw with 0.5 mg of heat-killed Mycobacterium butyricum suspended in light mineral oil. In vivo MRI evaluations of soft tissue and bony changes in AIA rats with matched histopathology were correlated with changes in left hindpaw volumes, circulating leukocytes, acute-phase reactants, and urinary collagen crosslinks throughout the disease process.

RESULTS

MRI of arthritic tibiotarsal joints of the uninjected left hindpaws from AIA rats demonstrated 2 distinct phases of disease activity. The first phase, apparent between days 10 and 18, was characterized by periarticular inflammation with marked synovitis, synovial fibroplasia, and distension of the joint capsule into the surrounding tissue. The secondary phase, occurring between days 18 and 30, was marked by continued soft tissue inflammation, periostitis with osteolysis, and periosteal new bone formation progressing to a state of near complete ankylosis by day 30. These 2 phases of disease activity observed by MRI paralleled biochemical, cellular, and histologic markers of disease progression.

CONCLUSION

MRI can be used to noninvasively detect, monitor, and quantify the chronic synovitis and progressive destruction of soft tissue and bone in live AIA rats, thereby improving the ability to evaluate disease progression in this preclinical animal model of rheumatoid arthritis.

Sirolimus (rapamycin, Rapamune) and combination therapy with cyclosporin A in the rat developing adjuvant arthritis model: correlation with blood levels and the effects of different oral formulations

OBJECTIVE AND DESIGN

To determine whole blood levels of sirolimus, a macrolide antibiotic in the rat developing adjuvant arthritis (AA) model after dosing orally with two different vehicles, and whether combinational doses of sirolimus and cyclosporin A (CsA) produced additive or synergistic inhibitory effects in this model.

MATERIAL

Male Lewis rats (150-180g).

TREATMENT

Arthritis was induced by the injection (0.5 mg/ rat) of heat-killed Mycobacterium butyricum suspended in light mineral oil. Drugs were administered orally either in fine suspension (0.5% Tween 80) or in emulsion (phosal 50 PG in 1% Tween 80) at doses of 0.1 to 5 mg/kg in a 7 day, MWF or daily regimen.

METHOD

Paw volumes (ml) were measured by automated mercury plethysmograph and sirolimus concentrations in whole blood were quantitated by liquid chromatography/ mass spectroscopy.

RESULTS

At 72h (7 days after adjuvant) after receiving the third oral dose (4.5 mg/kg p.o.), the phosal vehicle resulted in higher sirolimus blood levels (2.5 ng/ml) than in Tween 80 (1.6 ng/ml). After the rats received the last oral dose on day 14, (7 total doses of sirolimus at 4.5 mg/kg) the sirolimus blood levels (2h after the last dose) were about 2 times higher for the phosal dosed rats (9.8 ng/ml) compared to Tween 80 dosed rats (4.6ng/ml). Even 24h after the last dose, sirolimus blood levels were still elevated in the phosal dosed rats (0.8 ng/ml) relative to 0.5% Tween 80 dosed rats (0.5 ng/ml). At day 16 in the rat developing model, sirolimus, when given in phosal vehicle, produced an ED50 of 0.28 mg/ kg (i.e. inhibition of uninjected paw edema) that was about 5.5 times lower than using 0.5% Tween 80 as the suspending agent (ED50 = 1.6mg/kg). When combining sirolimus and CsA using precalculated doses for producing an additive effect in this adjuvant model, an additive inhibitory effect on uninjected paw edema was observed at equal combinational doses of 0.5 and 2 mg/kg, respectively.

CONCLUSIONS

The phosal vehicle used in administering sirolimus increases the absorption and whole blood levels in the rat and the elevated blood levels correlated positively with the therapeutic effect in the rat developing AA model. In addition, combination therapy using sirolimus and CsA produced an additive effect in rat developing AA.