Metabolic network architecture and carbon source determine metabolite production costs

Cytoplasmic Mg2+ supersedes carbon source preference to dictate Salmonella metabolism

Glucose is the preferred carbon source of most studied microorganisms. However, we now report that glucose loses preferred status when the intracellular pathogen Salmonella enterica serovar Typhimurium experiences cytoplasmic magnesium (Mg2+) starvation. We establish that this infection-relevant stress drastically reduces synthesis of cyclic adenosine monophosphate (cAMP), the allosteric activator of the cAMP receptor protein (CRP), master regulator of carbon utilization. The resulting reduction in cAMP concentration, which is independent of carbon source, decreases transcription of CRP-cAMP-activated carbon utilization genes, hinders carbon source uptake, and restricts metabolism, rendering wild-type bacteria phenotypically CRP-. A cAMP-independent allele of CRP overcame the transcriptional, uptake, and metabolic restrictions caused by cytoplasmic Mg2+ starvation and significantly increased transcription of the glucose uptake gene when S. Typhimurium was inside murine macrophages. The reduced preference for glucose exhibited by S. Typhimurium inside macrophages reflects that transcription of the glucose uptake gene requires higher amounts of active CRP-cAMP than transcription of uptake genes for preferred carbon sources, such as gluconate and glycerol. By reducing CRP-cAMP activity, low cytoplasmic Mg2+ alters carbon source preference, adjusting metabolism and growth.

Comparative analysis of amino acid auxotrophies and peptidase profiles in non-dysbiotic and dysbiotic small intestinal microbiomes

Small Intestinal Bacterial Overgrowth (SIBO) is linked to various diseases and has been associated with altered serum amino acid levels. However, the direct role of the gut microbiome in these changes remains unconfirmed. This study employs genome-scale metabolic modeling to predict amino acid auxotrophy and peptidase gene profiles in the small intestinal microbiomes of SIBO and non-SIBO subjects. Auxotrophy and peptidase gene profiles were further examined in the large intestinal microbiome under non-dysbiotic conditions to assess their similarity to the microbial SIBO profile. Our analysis revealed that the abundance of auxotrophic bacteria is higher in the microbiota of the small intestine than in the large intestine in non-dysbiotic controls. In patients with SIBO, the abundance of auxotrophies in the small intestine decreased compared to non-SIBO subjects. Peptidase gene profiles in non-dysbiotic individuals were distinct between small and large intestinal microbiomes, with fewer extracellular peptidase genes in small intestine microbiomes. In SIBO, extracellular peptidase genes increased compared to non-SIBO subjects. Further, there were more significant associations between the abundance of auxotrophies and peptidase genes in microbiomes of the small intestine compared to the large intestine. In conclusion, the auxotrophy and peptidase gene profiles of the small and large intestinal microbiomes were distinct. In SIBO, the small intestinal microbiome shifts towards a metabolic state resembling that of the large intestine, particularly in its increased abundance of extracellular peptidase genes. This highlights the potential of genome-scale metabolic modeling in identifying metabolic disruptions associated with SIBO, which could inform the development of targeted interventions.

A framework for understanding collective microbiome metabolism

Microbiome metabolism underlies numerous vital ecosystem functions. Individual microbiome members often perform partial catabolism of substrates or do not express all of the metabolic functions required for growth. Microbiome members can complement each other by exchanging metabolic intermediates and cellular building blocks to achieve a collective metabolism. We currently lack a mechanistic framework to explain why microbiome members adopt partial metabolism and how metabolic functions are distributed among them. Here we argue that natural selection for proteome efficiency-that is, performing essential metabolic fluxes at a minimal protein investment-explains partial metabolism of microbiome members, which underpins the collective metabolism of microbiomes. Using the carbon cycle as an example, we discuss motifs of collective metabolism, the conditions under which these motifs increase the proteome efficiency of individuals and the metabolic interactions they result in. In summary, we propose a mechanistic framework for how collective metabolic functions emerge from selection on individuals.

Carbon flow allocation patterns of CH4, CO2, and biomass production vary with sewage and sediment microbial and biochemical factors in the anaerobic sewer environment

Understanding the carbon (C) fate in municipal sewers is imperative for optimizing current sewer-C-degradation control and treatment efficiency, aligning with China's C-neutrality strategy in determining the exact C budget of the wastewater system. This study used laboratory batch tests mimicking the anaerobic sewer environment and sewage-sediment stratification to evaluate C flow allocation (CFA) patterns in response to biotic and abiotic variables. We quantified the C equivalent mass (CEM) and used absolute quantitative 16S rRNA gene amplicon sequencing to characterize the microbiome. The substantial methane production (CH4, 17.2%-18.8%) required both activated sediment and exogenous C, while biomass production (BP, 63.1%-74.9%) formed C sink predominated as the main CFA direction under the stratified state. This was supported by the high diversity, interspecific interactions, and metabolic capacity of the sediment microbiome. However, CH4 and BP patterns demonstrated non-synchronicity and opposite dynamic characteristics. Carbon dioxide (CO2, 64.0%-81.3%) production dominated the sewage CFA. The absolute abundance of the sediment microbiome, which was 5.6 times higher than that of the sewage, exhibited a strong increase in magnitude across the phases. It was primarily associated with biomass growth and N metabolism, whereas sewage showed differentiated and competing communities and appeared to act mainly as the exogenous C sources. We constructed a binary quadratic linear model revealing the non-linear relationship between ACK activity, DOC degradation rate, and CEMCH4 rate; the former maintained low CH4 production when the available substrate was insufficient. The influence of N and S factors on the CFA is complex and multi-faceted. These findings highlight the importance of further investigations into the process-based framework of the sewer C budget, focusing on the C source-emission-sink functions and mass balance.

Plant diversity drives positive microbial associations in the rhizosphere enhancing carbon use efficiency in agricultural soils

Expanding and intensifying agriculture has led to a loss of soil carbon. As agroecosystems cover over 40% of Earth's land surface, they must be part of the solution put in action to mitigate climate change. Development of efficient management practices to maximize soil carbon retention is currently limited, in part, by a poor understanding of how plants, which input carbon to soil, and microbes, which determine its fate there, interact. Here we implement a diversity gradient by intercropping undersown species with barley in a large field trial, ranging from one to eight undersown species. We find that increasing plant diversity strengthens positive associations within the rhizosphere soil microbial community in relation to negative associations. These associations, in turn, enhance community carbon use efficiency. Jointly, our results highlight how increasing plant diversity in agriculture can be used as a management strategy to enhance carbon retention potential in agricultural soils.

Serial adaptive laboratory evolution enhances mixed carbon metabolic capacity of Escherichia coli

Microbes have inherent capacities for utilizing various carbon sources, however they often exhibit sub-par fitness due to low metabolic efficiency. To test whether a bacterial strain can optimally utilize multiple carbon sources, Escherichia coli was serially evolved in L-lactate and glycerol. This yielded two end-point strains that evolved first in L-lactate then in glycerol, and vice versa. The end-point strains displayed a universal growth advantage on single and a mixture of adaptive carbon sources, enabled by a concerted action of carbon source-specialists and generalist mutants. The combination of just four variants of glpK, ppsA, ydcI, and rph-pyrE, accounted for more than 80% of end-point strain fitness. In addition, machine learning analysis revealed a coordinated activity of transcriptional regulators imparting condition-specific regulation of gene expression. The effectiveness of the serial adaptive laboratory evolution (ALE) scheme in bioproduction applications was assessed under single and mixed-carbon culture conditions, in which serial ALE strain exhibited superior productivity of acetoin compared to ancestral strains. Together, systems-level analysis elucidated the molecular basis of serial evolution, which hold potential utility in bioproduction applications.

Ecological dependencies and the illusion of cooperation in microbial communities

Ecological dependencies - where organisms rely on other organisms for survival - are a ubiquitous feature of life on earth. Multicellular hosts rely on symbionts to provide essential vitamins and amino acids. Legume plants similarly rely on nitrogen-fixing rhizobia to convert atmospheric nitrogen to ammonia. In some cases, dependencies can arise via loss-of-function mutations that allow one partner to benefit from the actions of another. It is common in microbiology to label ecological dependencies between species as cooperation - making it necessary to invoke cooperation-specific frameworks to explain the phenomenon. However, in many cases, such traits are not (at least initially) cooperative, because they are not selected for because of the benefits they confer on a partner species. In contrast, dependencies in microbial communities may originate from fitness benefits gained from genomic-streamlining (i.e. Black Queen Dynamics). Here, we outline how the Black Queen Hypothesis predicts the formation of metabolic dependencies via loss-of-function mutations in microbial communities, without needing to invoke any cooperation-specific explanations. Furthermore we outline how the Black Queen Hypothesis can act as a blueprint for true cooperation as well as discuss key outstanding questions in the field. The nature of interactions in microbial communities can predict the ability of natural communities to withstand and recover from disturbances. Hence, it is vital to gain a deeper understanding of the factors driving these dynamic interactions over evolutionary time.

Amino acid auxotrophies in human gut bacteria are linked to higher microbiome diversity and long-term stability

Amino acid auxotrophies are prevalent among bacteria. They can govern ecological dynamics in microbial communities and indicate metabolic cross-feeding interactions among coexisting genotypes. Despite the ecological importance of auxotrophies, their distribution and impact on the diversity and function of the human gut microbiome remain poorly understood. This study performed the first systematic analysis of the distribution of amino acid auxotrophies in the human gut microbiome using a combined metabolomic, metagenomic, and metabolic modeling approach. Results showed that amino acid auxotrophies are ubiquitous in the colon microbiome, with tryptophan auxotrophy being the most common. Auxotrophy frequencies were higher for those amino acids that are also essential to the human host. Moreover, a higher overall abundance of auxotrophies was associated with greater microbiome diversity and stability, and the distribution of auxotrophs was found to be related to the human host's metabolome, including trimethylamine oxide, small aromatic acids, and secondary bile acids. Thus, our results suggest that amino acid auxotrophies are important factors contributing to microbiome ecology and host-microbiome metabolic interactions.

The efficient solution to decline the greenhouses emission and enrich the bacterial community during pig manure composting: Regulating the particle size of cornstalk

In present study, four lengths of chopped cornstalks were amended with pig manure respectively for 100 days aerobic fermentation, which aimed to evaluate the impact of different length of agricultural solid wastes on gaseous emission and dominating bacterial community succession and connection. The result revealed that the maximum ammonia volatilization was observed in 5 cm of straw samples attributed to the prominent mineralization, which was opposite to the emission of CH4 and N2O. As for global warming potential, the minimum value was detected in 5 cm of straw samples, which decreased by 5.03-24.75% compared with other samples. Additionally, the strongest correlation and complexity of bacterial community could be detected in 5 cm of straw treatment, representing the most vigorous bacterial metabolic ability could be recorded by optimizing the microbial habitat. Therefore, in order to decline the greenhouse effect in livestock manure composting, the 5 cm of corn straw was recommended.

How Bacterial Pathogens Coordinate Appetite with Virulence

Cells adjust growth and metabolism to nutrient availability. Having access to a variety of carbon sources during infection of their animal hosts, facultative intracellular pathogens must efficiently prioritize carbon utilization. Here, we discuss how carbon source controls bacterial virulence, with an emphasis on Salmonella enterica serovar Typhimurium, which causes gastroenteritis in immunocompetent humans and a typhoid-like disease in mice, and propose that virulence factors can regulate carbon source prioritization by modifying cellular physiology. On the one hand, bacterial regulators of carbon metabolism control virulence programs, indicating that pathogenic traits appear in response to carbon source availability. On the other hand, signals controlling virulence regulators may impact carbon source utilization, suggesting that stimuli that bacterial pathogens experience within the host can directly impinge on carbon source prioritization. In addition, pathogen-triggered intestinal inflammation can disrupt the gut microbiota and thus the availability of carbon sources. By coordinating virulence factors with carbon utilization determinants, pathogens adopt metabolic pathways that may not be the most energy efficient because such pathways promote resistance to antimicrobial agents and also because host-imposed deprivation of specific nutrients may hinder the operation of certain pathways. We propose that metabolic prioritization by bacteria underlies the pathogenic outcome of an infection.

Effects of magnesite on nitrogen conversion and bacterial community during pig manure composting

The objective of this research was to elucidate the effect of varying proportions of magnesite (MS) addition - 0% (T1), 2.5% (T2), 5% (T3), 7.5% (T4), and 10% (T5) - on nitrogen transformation and bacterial community dynamics during pig manure composting. In comparison to T1 (control), MS treatments amplified the abundance of Firmicutes, Actinobacteriota, and Halanaerobiaeota, bolstered the metabolic functionality of associated microorganisms, and enhanced the nitrogenous substance metabolic pathway. A complementary effect in core bacillus species played a key role in nitrogen preservation. Compared to T1, 10% MS demonstrated the most substantial influence on composting because Total Kjeldahl Nitrogen increased by 58.31% and NH3 emission decreased by 41.52%. In conclusion, 10% MS appears to be optimal for pig manure composting, as it can augment microbial abundance and mitigate nitrogen loss. This study offers a more ecologically sound and economically viable method for curtailing nitrogen loss during composting.

The Architecture of Metabolic Networks Constrains the Evolution of Microbial Resource Hierarchies

Microbial strategies for resource use are an essential determinant of their fitness in complex habitats. When facing environments with multiple nutrients, microbes often use them sequentially according to a preference hierarchy, resulting in well-known patterns of diauxic growth. In theory, the evolutionary diversification of metabolic hierarchies could represent a mechanism supporting coexistence and biodiversity by enabling temporal segregation of niches. Despite this ecologically critical role, the extent to which substrate preference hierarchies can evolve and diversify remains largely unexplored. Here, we used genome-scale metabolic modeling to systematically explore the evolution of metabolic hierarchies across a vast space of metabolic network genotypes. We find that only a limited number of metabolic hierarchies can readily evolve, corresponding to the most commonly observed hierarchies in genome-derived models. We further show how the evolution of novel hierarchies is constrained by the architecture of central metabolism, which determines both the propensity to change ranks between pairs of substrates and the effect of specific reactions on hierarchy evolution. Our analysis sheds light on the genetic and mechanistic determinants of microbial metabolic hierarchies, opening new research avenues to understand their evolution, evolvability, and ecology.

Effects of adding corn steep liquor on bacterial community composition and carbon and nitrogen transformation during spent mushroom substrate composting

BACKGROUND

Carbon and nitrogen are essential energy and nutrient substances in the composting process. Corn steep liquor (CSL) is rich in soluble carbon and nitrogen nutrients and active substances and is widely used in the biological industry. Nonetheless, limited research has been done on the effect of CSL on composting. This work firstly reveals the effect of adding CSL to bacterial community composition and carbon and nitrogen conversion during composting. This study provides the choice of auxiliary materials for the spent mushroom substrate compost (SMS) and some novel knowledge about the effect of bacterial community on C and N cycling during composting of SMS and CSL. Two treatments were set up in the experiment: 100% spent mushroom substrate (SMS) as CK and SMS + 0.5% CSL (v/v) as CP.

RESULTS

The results showed that the addition of CSL enhanced the initial carbon and nitrogen content of the compost, altered the bacterial community structure, and increased the bacterial diversity and relative abundance, which might be beneficial to the conversion and retention of carbon and nitrogen in the composting process. In this paper, network analysis was used to screen the core bacteria involved in carbon and nitrogen conversion. In the CP network, the core bacteria were divided into two categories, synthesizing and degrading bacteria, and there were more synthesizing bacteria than degrading bacteria, so the degradation and synthesis of organic matter were carried out simultaneously, while only degrading bacteria were found in the CK network. Functional prediction by Faprotax identified 53 groups of functional bacteria, among which 20 (76.68% abundance) and 14 (13.15% abundance) groups of functional bacteria were related to carbon and nitrogen conversion, respectively. Adding CSL stimulated the compensatory effect of core and functional bacteria, enhanced the carbon and nitrogen transformation ability, stimulated the activity of low-abundance bacteria, and reduced the competitive relationship between the bacterial groups. This may be why the addition of CSL accelerated the organic matter degradation and increased carbon and nitrogen preservation.

CONCLUSIONS

These findings indicate that the addition of CSL promoted the cycling and preservation of carbon and nitrogen in the SMS composts, and the addition of CSL to the compost may be an effective way to dispose of agricultural waste.

Growth productivity as a determinant of the inoculum effect for bactericidal antibiotics

Understanding the mechanisms by which populations of bacteria resist antibiotics has implications in evolution, microbial ecology, and public health. The inoculum effect (IE), where antibiotic efficacy declines as the density of a bacterial population increases, has been observed for multiple bacterial species and antibiotics. Several mechanisms to account for IE have been proposed, but most lack experimental evidence or cannot explain IE for multiple antibiotics. We show that growth productivity, the combined effect of growth and metabolism, can account for IE for multiple bactericidal antibiotics and bacterial species. Guided by flux balance analysis and whole-genome modeling, we show that the carbon source supplied in the growth medium determines growth productivity. If growth productivity is sufficiently high, IE is eliminated. Our results may lead to approaches to reduce IE in the clinic, help standardize the analysis of antibiotics, and further our understanding of how bacteria evolve resistance.

Magnesite driven the complementary effects of core fungi by optimizing the physicochemical parameters in pig manure composting

The effects of magnesite (MS) on fungi communities and the core fungi complementarity during pig manure (PM) composting were explored. Different dosage of MS [0% (T1), 2.5% (T2), 5% (T3), 7.5% (T4) and 10% (T5)] as amendments mixed with PM for 42 days composting. The results showed the dominant of phyla were Ascomycota (78.87%), Neocallimastigomycota (41.40%), Basidiomycota (30.81%) and Aphelidiomycota (29.44%). From day 7 to 42, the abundance of Ascomycota and Aphelidiomycota were increased from 7.75% to 42.41% to 57.27%-78.87% and 0-0.70% to 11.73%-29.44% among all treatments. Nevertheless, the phyla abundance of Neocallimastigomycota and Basidiomycota decreased from day 7 to 42. The co-occurrence network indicated that the high additive amendment could enhance the core fungi complementarity effects capacity. The 10% MS addition was a promisable candidate to optimum fungal communities, and causing a better compost quality. This study illustrated the potential and fungi communities changing of MS as additives in composting.

Cooperation increases robustness to ecological disturbance in microbial cross-feeding networks

Microorganisms mainly exist within complex networks of ecological interactions. Given that the growth and survival of community members frequently depend on an obligate exchange of essential metabolites, it is generally unclear how such communities can persist despite the destabilising force of ecological disturbance. Here we address this issue using a population dynamics model. In contrast to previous work that suggests the potential for obligate interaction networks to emerge is limited, we find the opposite pattern: ecological disturbance favours both specific network topologies and cooperative cross-feeding among community members. These results establish environmental perturbations as a key driver shaping the architecture of microbial interaction networks.

Totoro: Identifying Active Reactions During the Transient State for Metabolic Perturbations

Motivation: The increasing availability of metabolomic data and their analysis are improving the understanding of cellular mechanisms and how biological systems respond to different perturbations. Currently, there is a need for novel computational methods that facilitate the analysis and integration of increasing volume of available data.

Results: In this paper, we present Totoro a new constraint-based approach that integrates quantitative non-targeted metabolomic data of two different metabolic states into genome-wide metabolic models and predicts reactions that were most likely active during the transient state. We applied Totoro to real data of three different growth experiments (pulses of glucose, pyruvate, succinate) from Escherichia coli and we were able to predict known active pathways and gather new insights on the different metabolisms related to each substrate. We used both the E. coli core and the iJO1366 models to demonstrate that our approach is applicable to both smaller and larger networks.

Availability:Totoro is an open source method (available at https://gitlab.inria.fr/erable/totoro) suitable for any organism with an available metabolic model. It is implemented in C++ and depends on IBM CPLEX which is freely available for academic purposes.

Identification of flux trade-offs in metabolic networks

Trade-offs are inherent to biochemical networks governing diverse cellular functions, from gene expression to metabolism. Yet, trade-offs between fluxes of biochemical reactions in a metabolic network have not been formally studied. Here, we introduce the concept of absolute flux trade-offs and devise a constraint-based approach, termed FluTO, to identify and enumerate flux trade-offs in a given genome-scale metabolic network. By employing the metabolic networks of Escherichia coli and Saccharomyces cerevisiae, we demonstrate that the flux trade-offs are specific to carbon sources provided but that reactions involved in the cofactor and prosthetic group biosynthesis are present in trade-offs across all carbon sources supporting growth. We also show that absolute flux trade-offs depend on the biomass reaction used to model the growth of Arabidopsis thaliana under different carbon and nitrogen conditions. The identified flux trade-offs reflect the tight coupling between nitrogen, carbon, and sulphur metabolisms in leaves of C₃ plants. Altogether, FluTO provides the means to explore the space of alternative metabolic routes reflecting the constraints imposed by inherent flux trade-offs in large-scale metabolic networks.

Adaptive laboratory evolution of Escherichia coli W enhances gamma-aminobutyric acid production using glycerol as the carbon source

The microbial conversion of glycerol into value-added commodity products has emerged as an attractive means to meet the demands of biosustainability. However, glycerol is a non-preferential carbon source for productive fermentation because of its low energy density. We employed evolutionary and metabolic engineering in tandem to construct an Escherichia coli strain with improved GABA production using glycerol as the feedstock carbon. Adaptive evolution of E. coli W under glycerol-limited conditions for 1300 generations harnessed an adapted strain with a metabolic system optimized for glycerol utilization. Mutation profiling, enzyme kinetic assays, and transcriptome analysis of the adapted strain allowed us to decipher the basis of glycerol adaptation at the molecular level. Importantly, increased substrate influx mediated by the mutant glpK and modulation of intracellular cAMP levels were the key drivers of improved fitness in the glycerol-limited condition. Leveraging the enhanced capability of glycerol utilization in the strain, we constructed a GABA-producing E. coli W-derivative with superior GABA production compared to the wild-type. Furthermore, rationally designed inactivation of the non-essential metabolic genes, including ackA, mgsA, and gabT, in the glycerol-adapted strain improved the final GABA titer and specific productivity by 3.9- and 4.3-fold, respectively, compared with the wild-type.

Variation of soil microbial carbon use efficiency (CUE) and its Influence mechanism in the context of global environmental change: a review

Soil microbial carbon utilization efficiency (CUE) is the efficiency with which microorganisms convert absorbed carbon (C) into their own biomass C, also referred to as microorganism growth efficiency. Soil microbial CUE is a critical physiological and ecological parameter in the ecosystem’s C cycle, influencing the processes of C retention, turnover, soil mineralization, and greenhouse gas emission. Understanding the variation of soil microbial CUE and its influence mechanism in the context of global environmental change is critical for a better understanding of the ecosystem’s C cycle process and its response to global changes. In this review, the definition of CUE and its measurement methods are reviewed, and the research progress of soil microbial CUE variation and influencing factors is primarily reviewed and analyzed. Soil microbial CUE is usually expressed as the ratio of microbial growth and absorption, which is divided into methods based on the microbial growth rate, microbial biomass, substrate absorption rate, and substrate concentration change, and varies from 0.2 to 0.8. Thermodynamics, ecological environmental factors, substrate nutrient quality and availability, stoichiometric balance, and microbial community composition all influence this variation. In the future, soil microbial CUE research should focus on quantitative analysis of trace metabolic components, analysis of the regulation mechanism of biological-environmental interactions, and optimization of the carbon cycle model of microorganisms’ dynamic physiological response process.

Evaluation of cornstalk as bulking agent on greenhouse gases emission and bacterial community during further composting

The aim of current work was to explore the impact of Cornstalk (CS) on greenhouse gaseous emission and maturation during further composting and analyzed its impact on bacterial diversity. Three kinds of immature fertilizers were collected from chicken, pig and dairy manure namely T1, T2 and T3 as control, T4, T5 and T6 were added CS into T1 to T3 and adjusted C/N to 25 namely treatment. The results illustrated that gases (N2O, CH4 and NH3) emission of CS added treatments decreased by 6.39%-24.68%, 10.60%-23.23% and 13.00%-19.58%, respectively. But the CS amendment increased CO2 emission by 15.53%-30.81%. The mineralization of carbon and nitrogen was mainly correlated to Firmicutes, Actinobacteria, Proteobacteria and Bacteroidota, CS amendment increased abundance by 22.28%, 17.79%, 1.48% and 35.90%, respectively. The strategy of employing CS would be the most feasible approach for recycling of immature manure, considering its compost quality and environmental from farm.

Metabolic dissimilarity determines the establishment of cross-feeding interactions in bacteria

The exchange of metabolites among different bacterial genotypes profoundly impacts the structure and function of microbial communities. However, the factors governing the establishment of these cross-feeding interactions remain poorly understood. While shared physiological features may facilitate interactions among more closely related individuals, a lower relatedness should reduce competition and thus increase the potential for synergistic interactions. Here, we investigate how the relationship between a metabolite donor and recipient affects the propensity of strains to engage in unidirectional cross-feeding interactions. For this, we performed pairwise cocultivation experiments between four auxotrophic recipients and 25 species of potential amino acid donors. Auxotrophic recipients grew in the vast majority of pairs tested (63%), suggesting metabolic cross-feeding interactions are readily established. Strikingly, both the phylogenetic distance between donor and recipient and the dissimilarity of their metabolic networks were positively associated with the growth of auxotrophic recipients. Analyzing the co-growth of species from a gut microbial community in silico also revealed that recipient genotypes benefitted more from interacting with metabolically dissimilar partners, thus corroborating the empirical results. Together, our work identifies the metabolic dissimilarity between bacterial genotypes as a key factor determining the establishment of metabolic cross-feeding interactions in microbial communities.

Assessment of Carbon Substrate Catabolism Pattern and Functional Metabolic Pathway for Microbiota of Limestone Caves

Carbon utilization of bacterial communities is a key factor of the biomineralization process in limestone-rich curst areas. An efficient carbon catabolism of the microbial community is associated with the availability of carbon sources in such an ecological niche. As cave environments promote oligotrophic (carbon source stress) situations, the present study investigated the variations of different carbon substrate utilization patterns of soil and rock microbial communities between outside and inside cave environments in limestone-rich crust topography by Biolog EcoPlate™ assay and categorized their taxonomical structure and predicted functional metabolic pathways based on 16S rRNA amplicon sequencing. Community level physiological profiling (CLPP) analysis by Biolog EcoPlate™ assay revealed that microbes from outside of the cave were metabolically active and had higher carbon source utilization rate than the microbial community inside the cave. 16S rRNA amplicon sequence analysis demonstrated, among eight predominant bacterial phylum Planctomycetes, Proteobacteria, Cyanobacteria, and Nitrospirae were predominantly associated with outside-cave samples, whereas Acidobacteria, Actinobacteria, Chloroflexi, and Gemmatimonadetes were associated with inside-cave samples. Functional prediction showed bacterial communities both inside and outside of the cave were functionally involved in the metabolism of carbohydrates, amino acids, lipids, xenobiotic compounds, energy metabolism, and environmental information processing. However, the amino acid and carbohydrate metabolic pathways were predominantly linked to the outside-cave samples, while xenobiotic compounds, lipids, other amino acids, and energy metabolism were associated with inside-cave samples. Overall, a positive correlation was observed between Biolog EcoPlate™ assay carbon utilization and the abundance of functional metabolic pathways in this study.

Manganese dioxide driven the carbon and nitrogen transformation by activating the complementary effects of core bacteria in composting

This study revealed core bacterial metabolic mechanisms involved in carbon (C) and nitrogen (N) in composting with adding MnO₂. Two tests (control group (CK), adding MnO₂ (M)) were performed. The results indicated that the MnO₂ accelerated the transformation of carbon and nitrogen in composting. Core bacteria involved in the C and N conversion were identified, the complementarity effects of core bacteria were stimulated in M composting. Additionally, the influence of core bacteria on the C and N conversion could be divided into two pathways in M composting. One was that core bacteria promoted C and N conversion by accelerating the flow of amino acids into the tricarboxylic acid cycle. Another was that the complementarity effects of core bacteria increased the overall bacterial diversity, which contributed to C and N conversion. These findings showed that the addition of MnO₂ to composting was a promising application to treat agricultural organic waste.

Conjugation dynamics depend on both the plasmid acquisition cost and the fitness cost

Plasmid conjugation is a major mechanism responsible for the spread of antibiotic resistance. Plasmid fitness costs are known to impact long-term growth dynamics of microbial populations by providing plasmid-carrying cells a relative (dis)advantage compared to plasmid-free counterparts. Separately, plasmid acquisition introduces an immediate, but transient, metabolic perturbation. However, the impact of these short-term effects on subsequent growth dynamics has not previously been established. Here, we observed that de novo transconjugants grew significantly slower and/or with overall prolonged lag times, compared to lineages that had been replicating for several generations, indicating the presence of a plasmid acquisition cost. These effects were general to diverse incompatibility groups, well-characterized and clinically captured plasmids, Gram-negative recipient strains and species, and experimental conditions. Modeling revealed that both fitness and acquisition costs modulate overall conjugation dynamics, validated with previously published data. These results suggest that the hours immediately following conjugation may play a critical role in both short- and long-term plasmid prevalence. This time frame is particularly relevant to microbiomes with high plasmid/strain diversity considered to be hot spots for conjugation.

Searching for New Beneficial Bacterial Isolates of Wild Raspberries for Biocontrol of Phytopathogens-Antagonistic Properties and Functional Characterization

The threat caused by plants fungal and fungal-like pathogens is a serious problem in the organic farming of soft fruits. The European Commission regulations prohibit some commercially available chemical plant protection products, and instead recommend the use of natural methods for improving the microbial soil status and thus increasing resistance to biotic stresses caused by phytopathogens. The solution to this problem may be biopreparations based on, e.g., bacteria, especially those isolated from native local environments. To select proper bacterial candidates for biopreparation, research was provided to preliminarily ensure that those isolates are able not only to inhibit the growth of pathogens, but also to be metabolically effective. In the presented research sixty-five isolates were acquired and identified. Potentially pathogenic isolates were excluded from further research, and beneficial bacterial isolates were tested against the following plant pathogens: Botrytis spp., Colletotrichum spp., Phytophthora spp., and Verticillium spp. The eight most effective antagonists belonging to Arthrobacter, Bacillus, Pseudomonas, and Rhodococcus genera were subjected to metabolic and enzymatic analyses and a resistance to chemical stress survey, indicating to their potential as components of biopreparations for agroecology.

Exoproduction and characterization of a detergent-stable alkaline keratinase from Arthrobacter sp. KFS-1

Arthrobacter sp. KFS-1 previously isolated from a dump site was used to produce keratinase in basal medium. The physico-chemical conditions were optimized to enhance the keratinase production, and biochemical properties of the enzyme were also evaluated. Arthrobacter sp. KFS-1 optimally produced keratinase in a basal medium that contained 1.0 g/L xylose, 2.5-5.0 g/L chicken feather; with initial pH, incubation temperature and agitation speed of 6.0, 30 °C and 200 rpm, respectively. Maximum keratinase activity of 1559.09 ± 29.57 U/mL was achieved at 96 h of fermentation; while optimal thiol concentration of 665.13 ± 38.73 μM was obtained at 144 h. Furthermore, the enzyme was optimally active at pH 8.0 and 60 °C. The enzyme activity was inhibited by ethylene diamine tetraacetic acid and 1,10-phenanthroline, but not affected by phenylmethylsulfonyl floride. In addition, the crude enzyme retained 55%, 63%, 80%, 81% and 90% of the original activity after respective pretreatment with some commercial detergents (Maq, Omo, Surf, Sunlight and Ariel). Moreso, the enzyme showed remarkable stability in the presence of reducing agents, surfactants, and organic solvents. Arthrobacter sp. KFS-1 significantly produced keratinase which exhibited excellent stability in presence of chemical agents and commercial laundry detergents; hence, suggesting its industrial application potentials especially in detergent formulation.

Gut Dysbiosis With Bacilli Dominance and Accumulation of Fermentation Products Precedes Late-onset Sepsis in Preterm Infants

BACKGROUND

Gut dysbiosis has been suggested as a major risk factor for the development of late-onset sepsis (LOS), a main cause of mortality and morbidity in preterm infants. We aimed to assess specific signatures of the gut microbiome, including metabolic profiles, in preterm infants <34 weeks of gestation preceding LOS.

METHODS

In a single-center cohort, fecal samples from preterm infants were prospectively collected during the period of highest vulnerability for LOS (days 7, 14, and 21 of life). Following 16S rRNA gene profiling, we assessed microbial community function using microbial metabolic network modeling. Data were adjusted for gestational age and use of probiotics.

RESULTS

We studied stool samples from 71 preterm infants with LOS and 164 unaffected controls (no LOS/necrotizing enterocolitis). In most cases, the bacteria isolated in diagnostic blood culture corresponded to the genera in the gut microbiome. LOS cases had a decelerated development of microbial diversity. Before onset of disease, LOS cases had specific gut microbiome signatures with higher abundance of Bacilli (specifically coagulase-negative Staphylococci) and a lack of anaerobic bacteria. In silico modeling of bacterial community metabolism suggested accumulation of the fermentation products ethanol and formic acid in LOS cases before the onset of disease.

CONCLUSIONS

Intestinal dysbiosis preceding LOS is characterized by an accumulation of Bacilli and their fermentation products and a paucity of anaerobic bacteria. Early microbiome and metabolic patterns may become a valuable biomarker to guide individualized prevention strategies of LOS in highly vulnerable populations.

Microbial diversity drives carbon use efficiency in a model soil

Empirical evidence for the response of soil carbon cycling to the combined effects of warming, drought and diversity loss is scarce. Microbial carbon use efficiency (CUE) plays a central role in regulating the flow of carbon through soil, yet how biotic and abiotic factors interact to drive it remains unclear. Here, we combine distinct community inocula (a biotic factor) with different temperature and moisture conditions (abiotic factors) to manipulate microbial diversity and community structure within a model soil. While community composition and diversity are the strongest predictors of CUE, abiotic factors modulated the relationship between diversity and CUE, with CUE being positively correlated with bacterial diversity only under high moisture. Altogether these results indicate that the diversity × ecosystem-function relationship can be impaired under non-favorable conditions in soils, and that to understand changes in soil C cycling we need to account for the multiple facets of global changes.

Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate

Growth rate and metabolic state of bacteria have been separately shown to affect antibiotic efficacy^1-3. However, the two are interrelated as bacterial growth inherently imposes a metabolic burden⁴; thus, determining individual contributions from each is challenging^5,6. Indeed, faster growth is often correlated with increased antibiotic efficacy^7,8; however, the concurrent role of metabolism in that relationship has not been well characterized. As a result, a clear understanding of the interdependence between growth and metabolism, and their implications for antibiotic efficacy, are lacking⁹. Here, we measured growth and metabolism in parallel across a broad range of coupled and uncoupled conditions to determine their relative contribution to antibiotic lethality. We show that when growth and metabolism are uncoupled, antibiotic lethality uniformly depends on the bacterial metabolic state at the time of treatment, rather than growth rate. We further reveal a critical metabolic threshold below which antibiotic lethality is negligible. These findings were general for a wide range of conditions, including nine representative bactericidal drugs and a diverse range of Gram-positive and Gram-negative species (Escherichia coli, Acinetobacter baumannii and Staphylococcus aureus). This study provides a cohesive metabolic-dependent basis for antibiotic-mediated cell death, with implications for current treatment strategies and future drug development.

An automated and parallelised DIY-dosing unit for individual and complex feeding profiles: Construction, validation and applications

Since biotechnological research becomes more and more important for industrial applications, there is an increasing need for scalable and controllable laboratory procedures. A widely used approach in biotechnological research to improve the performance of a process is to vary the growth rates in order to find the right balance between growth and the production. This can be achieved by the application of a suitable feeding strategy. During this initial bioprocess development, it is beneficial to have at hand cheap and easy setups that work in parallel (e.g. in shaking flasks). Unfortunately, there is a gap between these easy setups and defined and controllable processes, which are necessary for up-scaling to an industrial relevant volume. One prerequisite to test and evaluate different process strategies apart from batch-mode is the availability of pump systems that allow for defined feeding profiles in shaking flasks. To our knowledge, there is no suitable dosing device on the market which fulfils the requirements of being cheap, precise, programmable, and parallelizable. Commercially available dosing units are either already integrated in bioreactors and therefore inflexible, or not programmable, or expensive, or a combination of those. Here, we present a LEGO-MINDSTORMS-based syringe pump, which has the potential of being widely used in daily laboratory routine due to its low price, programmability, and parallelisability. The acquisition costs do not exceed 350 € for up to four dosing units, that are independently controllable with one EV3 block. The system covers flow rates ranging from 0.7 μL min-1 up to 210 mL min-1 with a reliable flux. One dosing unit can convey at maximum a volume of 20 mL (using all 4 units even up to 80 mL in total) over the whole process time. The design of the dosing unit enables the user to perform experiments with up to four different growth rates in parallel (each measured in triplicates) per EV3-block used. We estimate, that the LEGO-MINDSTORMS-based dosing unit with 12 syringes in parallel is reducing the costs up to 50-fold compared to a trivial version of a commercial pump system (~1500 €) which fits the same requirements. Using the pump, we set the growth rates of a E. coli HMS174/DE3 culture to values between 0.1 and 0.4 h-1 with a standard deviation of at best 0.35% and an average discrepancy of 13.2%. Additionally, we determined the energy demand of a culture for the maintenance of the pTRA-51hd plasmid by quantifying the changes in biomass yield with different growth rates set. Around 25% of total substrate taken up is used for plasmid maintenance. To present possible applications and show the flexibility of the system, we applied a constant feed to perform microencapsulation of Pseudomonas putida and an individual dosing profile for the purification of a his-tagged eGFP via IMAC. This smart and versatile dosing unit, which is ready-to-use without any prior knowledge in electronics and control, is affordable for everyone and due to its flexibility and broad application range a valuable addition to the laboratory routine.

iTRAQ-based quantitative proteomics reveals insights into metabolic and molecular responses of glucose-grown cells of Rubrivivax benzoatilyticus JA2

Anoxygenic photosynthetic bacteria thrive under diverse habitats utilising an extended range of inorganic/organic compounds under different growth modes. Although they display incredible metabolic flexibility, their responses and adaptations to changing carbon regimes is largely unexplored. In the present study, we employed iTRAQ-based global proteomic profiling and physiological studies to uncover the adaptive strategies of a phototrophic bacterium, Rubrivivax benzoatilyticus JA2 to glucose. Strain JA2 displayed altered growth rates, reduced cell size and progressive loss of pigmentation when grown on glucose compared to malate under photoheterotrophic condition. A ten-fold increase in the saturated to unsaturated fatty acid ratio of glucose-grown cells indicates a possible membrane adaptation. Proteomic profiling revealed extensive metabolic remodelling in the glucose-grown cells wherein signal-transduction, selective-transcription, DNA-repair, transport and protein quality control processes were up-regulated to cope with the changing milieu. Proteins involved in DNA replication, translation, electron-transport, photosynthetic machinery were down-regulated possibly to conserve the energy. Glycolysis/gluconeogenesis, TCA cycle and pigment biosynthesis were also down-regulated. The cell has activated alternative energy metabolic pathways viz., fatty acid β-oxidation, glyoxylate, acetate-switch and Entner-Doudoroff pathways. Overall, the present study deciphered the molecular/metabolic events associated with glucose-grown cells of strain JA2 and also unraveled how a carbon source modulates the metabolic phenotypes. SIGNIFICANCE: Anoxygenic photosynthetic bacteria (APB) exhibit incredible metabolic flexibility leading to diverse phenotypes. They thrive under diverse habitat using an array of inorganic/organic compounds as carbon sources, yet their metabolic adaptation to varying carbon regime is mostly unexplored. Present study uncovered the proteomic insights of the cellular responses of strain JA2 to changing carbon sources viz. malate and glucose under photoheterotrophic conditions. Our study suggests that carbon source can also determine the metabolic fate of the cells and reshape the energy dynamics of APB. Here, for the first time study highlighted the plausible carbon source (glucose) mediated regulation of photosynthesis in APB. The study sheds light on the plausible cellular events and adaptive metabolic strategies employed by strain JA2 in presence of non-preferred carbon source. It also revealed new insights into the metabolic plasticity of APB to the changing milieu.

Towards an Understanding of Energy Impairment in Huntington's Disease Brain

This review systematically examines the evidence for shifts in flux through energy generating biochemical pathways in Huntington’s disease (HD) brains from humans and model systems. Compromise of the electron transport chain (ETC) appears not to be the primary or earliest metabolic change in HD pathogenesis. Rather, compromise of glucose uptake facilitates glucose flux through glycolysis and may possibly decrease flux through the pentose phosphate pathway (PPP), limiting subsequent NADPH and GSH production needed for antioxidant protection. As a result, oxidative damage to key glycolytic and tricarboxylic acid (TCA) cycle enzymes further restricts energy production so that while basal needs may be met through oxidative phosphorylation, those of excessive stimulation cannot. Energy production may also be compromised by deficits in mitochondrial biogenesis, dynamics or trafficking. Restrictions on energy production may be compensated for by glutamate oxidation and/or stimulation of fatty acid oxidation. Transcriptional dysregulation generated by mutant huntingtin also contributes to energetic disruption at specific enzymatic steps. Many of the alterations in metabolic substrates and enzymes may derive from normal regulatory feedback mechanisms and appear oscillatory. Fine temporal sequencing of the shifts in metabolic flux and transcriptional and expression changes associated with mutant huntingtin expression remain largely unexplored and may be model dependent. Differences in disease progression among HD model systems at the time of experimentation and their varying states of metabolic compensation may explain conflicting reports in the literature. Progressive shifts in metabolic flux represent homeostatic compensatory mechanisms that maintain the model organism through presymptomatic and symptomatic stages.

Ecology and evolution of metabolic cross-feeding interactions in bacteria

Literature covered: early 2000s to late 2017Bacteria frequently exchange metabolites with other micro- and macro-organisms. In these often obligate cross-feeding interactions, primary metabolites such as vitamins, amino acids, nucleotides, or growth factors are exchanged. The widespread distribution of this type of metabolic interactions, however, is at odds with evolutionary theory: why should an organism invest costly resources to benefit other individuals rather than using these metabolites to maximize its own fitness? Recent empirical work has shown that bacterial genotypes can significantly benefit from trading metabolites with other bacteria relative to cells not engaging in such interactions. Here, we will provide a comprehensive overview over the ecological factors and evolutionary mechanisms that have been identified to explain the evolution and maintenance of metabolic mutualisms among microorganisms. Furthermore, we will highlight general principles that underlie the adaptive evolution of interconnected microbial metabolic networks as well as the evolutionary consequences that result for cells living in such communities.

The Exometabolome of Two Model Strains of the Roseobacter Group: A Marketplace of Microbial Metabolites

Recent studies applying Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) showed that the exometabolome of marine bacteria is composed of a surprisingly high molecular diversity. To shed more light on how this diversity is generated we examined the exometabolome of two model strains of the Roseobacter group, Phaeobacter inhibens and Dinoroseobacter shibae, grown on glutamate, glucose, acetate or succinate by FT-ICR-MS. We detected 2,767 and 3,354 molecular formulas in the exometabolome of each strain and 67 and 84 matched genome-predicted metabolites of P. inhibens and D. shibae, respectively. The annotated compounds include late precursors of biosynthetic pathways of vitamins B₁, B₂, B₅, B₆, B₇, B₁₂, amino acids, quorum sensing-related compounds, indole acetic acid and methyl-(indole-3-yl) acetic acid. Several formulas were also found in phytoplankton blooms. To shed more light on the effects of some of the precursors we supplemented two B₁ prototrophic diatoms with the detected precursor of vitamin B₁ HET (4-methyl-5-(β-hydroxyethyl)thiazole) and HMP (4-amino-5-hydroxymethyl-2-methylpyrimidine) and found that their growth was stimulated. Our findings indicate that both strains and other bacteria excreting a similar wealth of metabolites may function as important helpers to auxotrophic and prototrophic marine microbes by supplying growth factors and biosynthetic precursors.

Modelling microbial metabolic rewiring during growth in a complex medium

Background

In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now.

Results

We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs).

Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution.

Conclusions

Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3311-0) contains supplementary material, which is available to authorized users.

Experimental Evolution of Metabolic Dependency in Bacteria

Bacteria frequently lose biosynthetic genes, thus making them dependent on an environmental uptake of the corresponding metabolite. Despite the ubiquity of this ‘genome streamlining’, it is generally unclear whether the concomitant loss of biosynthetic functions is favored by natural selection or rather caused by random genetic drift. Here we demonstrate experimentally that a loss of metabolic functions is strongly selected for when the corresponding metabolites can be derived from the environment. Serially propagating replicate populations of the bacterium Escherichia coli in amino acid-containing environments revealed that auxotrophic genotypes rapidly evolved in less than 2,000 generations in almost all replicate populations. Moreover, auxotrophs also evolved in environments lacking amino acids–yet to a much lesser extent. Loss of these biosynthetic functions was due to mutations in both structural and regulatory genes. In competition experiments performed in the presence of amino acids, auxotrophic mutants gained a significant fitness advantage over the evolutionary ancestor, suggesting their emergence was selectively favored. Interestingly, auxotrophic mutants derived amino acids not only via an environmental uptake, but also by cross-feeding from coexisting strains. Our results show that adaptive fitness benefits can favor biosynthetic loss-of-function mutants and drive the establishment of intricate metabolic interactions within microbial communities.

Bacteria frequently lose seemingly essential genes from their genomes that are required to autonomously biosynthesize building block metabolites such as amino acids. It is generally unclear whether these losses are due to chance events in small populations or favored by selection, because loss-of-function mutants may save production cost when utilizing metabolites from the environment. We discovered that populations of Escherichia coli that evolved in amino acid-replete environments rapidly lost the ability to autonomously produce several amino acids, which was beneficial when amino acids were present in the environment. Interestingly, these mutants derived amino acids not just from the growth medium, but also from other, co-occurring strains. Our findings show that nutrient-containing environments drive the loss of biosynthetic genes from bacterial genomes and facilitate the establishment of metabolic cross-feeding interactions among bacteria.