Public goods and metabolic strategies

Fueling the protein transition: Can waste-derived ethanol enable efficient and high-quality microbial protein production?

Meeting the protein needs of a growing population will require significant resources. In this context, microbial protein (MP) offers a nutritious and versatile protein source from recovered resources. This meta-analysis of over 100 studies examines the efficiency and nutritional quality of MP production using ethanol. Ethanol, a feedstock derived from CO2 and biological waste, is used by various microorganisms, and has an established role in the food sector. Results show that ethanol-based MP production is technically feasible for food applications, reaching biomass concentrations of 14-230 g/L and productivities of 11-13 g/L/h. The protein content of MP correlates with productivity, and the nutritional quality of ethanol-grown MP matches common sources like pork and tofu. Lastly, operational choices affect the techno-economic feasibility of using waste-derived ethanol and other recovered resources. This meta-analysis highlights the potential of ethanol-grown MP, though further research is needed to close existing knowledge gaps.

Trait and plasticity evolution under competition and mutualism in evolving pairwise yeast communities

Although we have a good understanding of how phenotypic plasticity evolves in response to abiotic environments, we know comparatively less about responses to biotic interactions. We experimentally tested how competition and mutualism affected trait and plasticity evolution of pairwise communities of genetically modified brewer's yeast. We quantified evolutionary changes in growth rate, resource use efficiency (RUE), and their plasticity in strains evolving alone, with a competitor, and with a mutualist. Compared to their ancestors, strains evolving alone had lower RUE and RUE plasticity. There was also an evolutionary tradeoff between changes in growth rate and RUE in strains evolving alone, suggesting selection for increased growth rate at the cost of efficiency. Strains evolving with a competitive partner had higher growth rates, slightly lower RUE, and a stronger tradeoff between growth rate and efficiency. In contrast, mutualism had opposite effects on trait evolution. Strains evolving with a mutualist had slightly lower growth rates, higher RUE, and a weak evolutionary tradeoff between growth rate and RUE. Despite their different effects on trait evolution, competition and mutualism had little effect on plasticity evolution for either trait, suggesting that abiotic factors could be more important than biotic factors in generating selection for plasticity.

Synergistic vs. complementary synbiotics: the complexity of discriminating synbiotic concepts using a Lactiplantibacillus plantarum exemplary study

Synbiotics are defined as "a mixture comprising live microorganisms and substrate(s) selectively utilized by host microorganisms that confers a health benefit on the host". The definition discriminates between synergistic and complementary synbiotics. Synergistic synbiotics involve a direct interaction between the substrate and co-administered microbe(s), while complementary synbiotics act through independent mechanisms. Here, we evaluate the complexity of discrimination between these two synbiotic concepts using an exemplary study performed with a panel of Lactiplantibacillus plantarum (L. plantarum) strains to identify strain-specific synergistic synbiotics that eventually turned out to work via a complementary synbiotic mechanism. This study highlights that assessing the in situ selectivity of synergistic synbiotics in the intestinal tract is challenging due to the confounding effects of the substrate ingredient on the endogenous microbiome, thereby raising doubts about the added value of distinguishing between synergistic and complementary concepts in synbiotics.

No signs of microbial-influenced corrosion of cast iron and copper in bentonite microcosms after 400 days

High-level radioactive waste needs to be safely stored for a long time in a deep geological repository by using a multi-barrier system. In this system, suitable barrier materials are selected that ideally show long-term stability to prevent early radionuclide release into the biosphere. In this study, different container matals (copper and cast iron) and pore water compositions (Opalinus Clay pore water and saline cap rock solution) were combined with Bavarian bentonite in static batch experiments to investigate microbial-influenced corrosion. The increasing concentration of iron and copper in the solution as well as detected corrosion products on the metal surface are indicative of anaerobic corrosion of the respective metals during an incubation of 400 days at 37 °C. However, although the intrinsic microbial bentonite community was stimulated with either lactate or H2, an acceleration of cast iron- and copper corrosion did not occur. Furthermore, neither corrosive bacteria nor conventional bacterial corrosion products, such as metal sulfides, were detected in any of the analyzed samples. The analyses of geochemical parameters (e.g. ferrous iron-, iron-, copper- and potassium concentrations as well as redox potentials) showed significant changes in some cast iron- and copper-containing setups, but these changes did not correlate with the microbial community structure in the respective microcosms, as confirmed by statistical analyses. Hence, the analyzed Bavarian bentonite (type B25) showed no significant contribution to cast iron and copper corrosion under the applied conditions after 400 days of incubation. From this perspective, bentonite B25 could be a suitable candidate as a geotechnical barrier in future repositories.

On paradoxes between optimal growth, metabolic control analysis, and flux balance analysis

In Microbiology it is often assumed that growth rate is maximal. This may be taken to suggest that the dependence of the growth rate on every enzyme activity is at the top of an inverse-parabolic function, i.e. that all flux control coefficients should equal zero. This might seem to imply that the sum of these flux control coefficients equals zero. According to the summation law of Metabolic Control Analysis (MCA) the sum of flux control coefficients should equal 1 however. And in Flux Balance Analysis (FBA) catabolism is often limited by a hard bound, causing catabolism to fully control the fluxes, again in apparent contrast with a flux control coefficient of zero. Here we resolve these paradoxes (apparent contradictions) in an analysis that uses the 'Edinburgh pathway', the 'Amsterdam pathway', as well as a generic metabolic network providing the building blocks or Gibbs energy for microbial growth. We review and show that (i) optimization depends on so-called enzyme control coefficients rather than the 'catalytic control coefficients' of MCA's summation law, (ii) when optimization occurs at fixed total protein, the former differ from the latter to the extent that they may all become equal to zero in the optimum state, (iii) in more realistic scenarios of optimization where catalytically inert biomass is compensating or maintenance metabolism is taken into consideration, the optimum enzyme concentrations should not be expected to equal those that maximize the specific growth rate, (iv) optimization may be in terms of yield rather than specific growth rate, which resolves the paradox because the sum of catalytic control coefficients on yield equals 0, (v) FBA effectively maximizes growth yield, and for yield the summation law states 0 rather than 1, thereby removing the paradox, (vi) furthermore, FBA then comes more often to a 'hard optimum' defined by a maximum catabolic flux and a catabolic-enzyme control coefficient of 1. The trade-off between maintenance metabolism and growth is highlighted as worthy of further analysis.

Strengthening microbial cell factories for efficient production of bioactive molecules

High demand of bioactive molecules (food additives, antibiotics, plant growth enhancers, cosmetics, pigments and other commercial products) is the prime need for the betterment of human life where the applicability of the synthetic chemical product is on the saturation due to associated toxicity and ornamentations. It has been noticed that the discovery and productivity of such molecules in natural scenarios are limited due to low cellular yields as well as less optimized conventional methods. In this respect, microbial cell factories timely fulfilling the requirement of synthesizing bioactive molecules by improving production yield and screening more promising structural homologues of the native molecule. Where the robustness of the microbial host can be potentially achieved by taking advantage of cell engineering approaches such as tuning functional and adjustable factors, metabolic balancing, adapting cellular transcription machinery, applying high throughput OMICs tools, stability of genotype/phenotype, organelle optimizations, genome editing (CRISPER/Cas mediated system) and also by developing accurate model systems via machine-learning tools. In this article, we provide an overview from traditional to recent trends and the application of newly developed technologies, for strengthening the systemic approaches and providing future directions for enhancing the robustness of microbial cell factories to speed up the production of biomolecules for commercial purposes.

Biotic Interactions in Soil are Underestimated Drivers of Microbial Carbon Use Efficiency

Microbial carbon use efficiency (CUE)-the balance between microbial growth and respiration-strongly impacts microbial mediated soil carbon storage and is sensitive to many well-studied abiotic environmental factors. However, surprisingly, little work has examined how biotic interactions in soil may impact CUE. Here, we review the theoretical and empirical lines of evidence exploring how biotic interactions affect CUE through the lens of life history strategies. Fundamentally, the CUE of a microbial population is constrained by population density and carrying capacity, which, when reached, causes species to grow more quickly and less efficiently. When microbes engage in interspecific competition, they accelerate growth rates to acquire limited resources and release secondary chemicals toxic to competitors. Such processes are not anabolic and thus constrain CUE. In turn, antagonists may activate one of a number of stress responses that also do not involve biomass production, potentially further reducing CUE. In contrast, facilitation can increase CUE by expanding species realized niches, mitigating environmental stress and reducing production costs of extracellular enzymes. Microbial interactions at higher trophic levels also influence CUE. For instance, predation on microbes can positively or negatively impact CUE by changing microbial density and the outcomes of interspecific competition. Finally, we discuss how plants select for more or less efficient microbes under different contexts. In short, this review demonstrates the potential for biotic interactions to be a strong regulator of microbial CUE and additionally provides a blueprint for future research to address key knowledge gaps of ecological and applied importance for carbon sequestration.

A Game Theoretic Analysis of the Dual Function of Antibiotics

There are two major views toward the role of antibiotics in microbial social interactions. The classical view is that antibiotics serve as weapons, produced by a bacterial species, at a significant cost, to inhibit the growth of its competitors. This view is supported by observations that antibiotics are usually upregulated by stress responses that infer the intensity of ecological competition, such as nutrient limitation and cellular damage, which point out to a competitive role for antibiotics. The other ecological function frequently assigned to antibiotics is that they serve as signaling molecules which regulate the collective behavior of a microbial community. Here, we investigate the conditions at which a weapon can serve as a signal in the context of microbial competition. We propose that an antibiotic will serve as a signal whenever a potential alteration of the growth behavior of the signal receiver, in response to a subinhibitory concentration (SIC) of the antibiotic, reduces the competitive pressure on the signal producer. This in turn would lead to avoiding triggering the stress mechanisms of the signal producer responsible for further antibiotics production. We show using individual-based modeling that this reduction of competitive pressure on the signal producer can happen through two main classes of responses by the signal recipient: competition tolerance, where the recipient reduces its competitive impact on the signal producer by switching to a low growth rate/ high yield strategy, and niche segregation, where the recipient reduces the competitive pressure on the signal producer by reducing their niche overlap. Our hypothesis proposes that antibiotics serve as signals out of their original function as weapons in order to reduce the chances of engaging in fights that would be costly to both the antibiotic producer as well as to its competitors.

Energetic scaling in microbial growth

Microbial growth is a clear example of organization and structure arising in nonequilibrium conditions. Due to the complexity of the microbial metabolic network, elucidating the fundamental principles governing microbial growth remains a challenge. Here, we present a systematic analysis of microbial growth thermodynamics, leveraging an extensive dataset on energy-limited monoculture growth. A consistent thermodynamic framework based on reaction stoichiometry allows us to quantify how much of the available energy microbes can efficiently convert into new biomass while dissipating the remaining energy into the environment and producing entropy. We show that dissipation mechanisms can be linked to the electron donor uptake rate, a fact leading to the central result that the thermodynamic efficiency is related to the electron donor uptake rate by the scaling law [Formula: see text] and to the growth yield by [Formula: see text] These findings allow us to rederive the Pirt equation from a thermodynamic perspective, providing a means to compute its coefficients, as well as a deeper understanding of the relationship between growth rate and yield. Our results provide rather general insights into the relation between mass and energy conversion in microbial growth with potentially wide application, especially in ecology and biotechnology.

Commensal inter-bacterial interactions shaping the microbiota

The gut microbiota, a complex ecosystem of microorganisms of different kingdoms, impacts host physiology and disease. Within this ecosystem, inter-bacterial interactions and their impacts on microbiota community structure and the eukaryotic host remain insufficiently explored. Microbiota-related inter-bacterial interactions range from symbiotic interactions, involving exchange of nutrients, enzymes, and genetic material; competition for nutrients and space, mediated by biophysical alterations and secretion of toxins and anti-microbials; to predation of overpopulating bacteria. Collectively, these understudied interactions hold important clues as to forces shaping microbiota diversity, niche formation, and responses to signals perceived from the host, incoming pathogens and the environment. In this review, we highlight the roles and mechanisms of selected inter-bacterial interactions in the microbiota, and their potential impacts on the host and pathogenic infection. We discuss challenges in mechanistically decoding these complex interactions, and prospects of harnessing them as future targets for rational microbiota modification in a variety of diseases.

Serial propagation in water-in-oil emulsions selects for Saccharomyces cerevisiae strains with a reduced cell size or an increased biomass yield on glucose

In S. cerevisiae and many other micro-organisms an increase in metabolic efficiency (i.e. ATP yield on carbon) is accompanied by a decrease in growth rate. From a fundamental point of view, studying these yield-rate trade-offs provides insight in for example microbial evolution and cellular regulation. From a biotechnological point of view, increasing the ATP yield on carbon might increase the yield of anabolic products. We here aimed to select S. cerevisiae mutants with an increased biomass yield. Serial propagation of individual cells in water-in-oil emulsions previously enabled the selection of lactococci with increased biomass yields, and adapting this protocol for yeast allowed us to enrich an engineered Crabtree-negative S. cerevisiae strain with a high biomass yield on glucose. When we started the selection with an S. cerevisiae deletion collection, serial propagation in emulsion enriched hxk2Δ and reg1Δ strains with an increased biomass yield on glucose. Surprisingly, a tps1Δ strain was highly abundant in both emulsion- and suspension-propagated populations. In a separate experiment we propagated a chemically mutagenized S. cerevisiae population in emulsion, which resulted in mutants with a higher cell number yield on glucose, but no significantly changed biomass yield. Genome analyses indicate that genes involved in glucose repression and cell cycle processes play a role in the selected phenotypes. The repeated identification of mutations in genes involved in glucose-repression indicates that serial propagation in emulsion is a valuable tool to study metabolic efficiency in S. cerevisiae.

Positive linkage between bacterial social traits reveals that homogeneous rather than specialised behavioral repertoires prevail in natural Pseudomonas communities

Bacteria frequently cooperate by sharing secreted metabolites such as enzymes and siderophores. The expression of such 'public good' traits can be interdependent, and studies on laboratory systems have shown that trait linkage affects eco-evolutionary dynamics within bacterial communities. Here, we examine whether linkage among social traits occurs in natural habitats by examining investment levels and correlations between five public goods (biosurfactants, biofilm components, proteases, pyoverdines and toxic compounds) in 315 Pseudomonas isolates from soil and freshwater communities. Our phenotypic assays revealed that (i) social trait expression profiles varied dramatically; (ii) correlations between traits were frequent, exclusively positive and sometimes habitat-specific; and (iii) heterogeneous (specialised) trait repertoires were rarer than homogeneous (unspecialised) repertoires. Our results show that most isolates lie on a continuum between a 'social' type producing multiple public goods, and an 'asocial' type showing low investment into social traits. This segregation could reflect local adaptation to different microhabitats, or emerge from interactions between different social strategies. In the latter case, our findings suggest that the scope for competition among unspecialised isolates exceeds the scope for mutualistic exchange of different public goods between specialised isolates. Overall, our results indicate that complex interdependencies among social traits shape microbial lifestyles in nature.

Modeling microbial metabolic trade-offs in a chemostat

Microbes face intense competition in the natural world, and so need to wisely allocate their resources to multiple functions, in particular to metabolism. Understanding competition among metabolic strategies that are subject to trade-offs is therefore crucial for deeper insight into the competition, cooperation, and community assembly of microorganisms. In this work, we evaluate competing metabolic strategies within an ecological context by considering not only how the environment influences cell growth, but also how microbes shape their chemical environment. Utilizing chemostat-based resource-competition models, we exhibit a set of intuitive and general procedures for assessing metabolic strategies. Using this framework, we are able to relate and unify multiple metabolic models, and to demonstrate how the fitness landscape of strategies becomes intrinsically dynamic due to species-environment feedback. Such dynamic fitness landscapes produce rich behaviors, and prove to be crucial for ecological and evolutionarily stable coexistence in all the models we examined.

Adaptive Laboratory Evolution and Reverse Engineering of Single-Vitamin Prototrophies in Saccharomyces cerevisiae

Many strains of Saccharomyces cerevisiae, a popular platform organism in industrial biotechnology, carry the genetic information required for synthesis of biotin, thiamine, pyridoxine, para-aminobenzoic acid, pantothenic acid, nicotinic acid, and inositol. However, omission of these B vitamins typically leads to suboptimal growth. This study demonstrates that, for each individual B vitamin, it is possible to achieve fast vitamin-independent growth by adaptive laboratory evolution (ALE). Identification of mutations responsible for these fast-growing phenotypes by whole-genome sequencing and reverse engineering showed that, for each compound, a small number of mutations sufficed to achieve fast growth in its absence. These results form an important first step toward development of S. cerevisiae strains that exhibit fast growth on inexpensive, fully supplemented mineral media that only require complementation with a carbon source, thereby reducing costs, complexity, and contamination risks in industrial yeast fermentation processes.

Quantitative physiological studies on Saccharomyces cerevisiae commonly use synthetic media (SM) that contain a set of water-soluble growth factors that, based on their roles in human nutrition, are referred to as B vitamins. Previous work demonstrated that in S. cerevisiae CEN.PK113-7D, requirements for biotin were eliminated by laboratory evolution. In the present study, this laboratory strain was shown to exhibit suboptimal specific growth rates when either inositol, nicotinic acid, pyridoxine, pantothenic acid, para-aminobenzoic acid (pABA), or thiamine was omitted from SM. Subsequently, this strain was evolved in parallel serial-transfer experiments for fast aerobic growth on glucose in the absence of individual B vitamins. In all evolution lines, specific growth rates reached at least 90% of the growth rate observed in SM supplemented with a complete B vitamin mixture. Fast growth was already observed after a few transfers on SM without myo-inositol, nicotinic acid, or pABA. Reaching similar results in SM lacking thiamine, pyridoxine, or pantothenate required more than 300 generations of selective growth. The genomes of evolved single-colony isolates were resequenced, and for each B vitamin, a subset of non-synonymous mutations associated with fast vitamin-independent growth was selected. These mutations were introduced in a non-evolved reference strain using CRISPR/Cas9-based genome editing. For each B vitamin, the introduction of a small number of mutations sufficed to achieve a substantially increased specific growth rate in non-supplemented SM that represented at least 87% of the specific growth rate observed in fully supplemented complete SM.

IMPORTANCE Many strains of Saccharomyces cerevisiae, a popular platform organism in industrial biotechnology, carry the genetic information required for synthesis of biotin, thiamine, pyridoxine, para-aminobenzoic acid, pantothenic acid, nicotinic acid, and inositol. However, omission of these B vitamins typically leads to suboptimal growth. This study demonstrates that, for each individual B vitamin, it is possible to achieve fast vitamin-independent growth by adaptive laboratory evolution (ALE). Identification of mutations responsible for these fast-growing phenotypes by whole-genome sequencing and reverse engineering showed that, for each compound, a small number of mutations sufficed to achieve fast growth in its absence. These results form an important first step toward development of S. cerevisiae strains that exhibit fast growth on inexpensive, fully supplemented mineral media that only require complementation with a carbon source, thereby reducing costs, complexity, and contamination risks in industrial yeast fermentation processes.

Evolution of mutualistic behaviour between Chlorella sorokiniana and Saccharomyces cerevisiae within a synthetic environment

Yeast and microalgae are microorganisms with widely diverging physiological and biotechnological properties. Accordingly, their fields of applications diverge: yeasts are primarily applied in processes related to fermentation, while microalgae are used for the production of high-value metabolites and green technologies such as carbon capture. Heterotrophic-autotrophic systems and synthetic ecology approaches have been proposed as tools to achieve stable combinations of such evolutionarily unrelated species. We describe an entirely novel synthetic ecology-based approach to evolve co-operative behaviour between winery wastewater isolates of the yeast Saccharomyces cerevisiae and microalga Chlorella sorokiniana. The data show that biomass production and mutualistic growth improved when co-evolved yeast and microalgae strains were paired together. Combinations of co-evolved strains displayed a range of phenotypes, including differences in amino acid profiles. Taken together, the results demonstrate that biotic selection pressures can lead to improved mutualistic growth phenotypes over relatively short time periods.

Community biofilm-formation, stratification and productivity in serially-transferred microcosms

The establishment of O2 gradients in liquid columns by bacterial metabolic activity produces a spatially-structured environment. This produces a high-O2 region at the top that represents an un-occupied niche which could be colonised by biofilm-competent strains. We have used this to develop an experimental model system using soil-wash inocula and a serial-transfer approach to investigate changes in community-based biofilm-formation and productivity. This involved 10 transfers of mixed-community or biofilm-only samples over a total of 10-60 days incubation. In all final-transfer communities the ability to form biofilms was retained, though in longer incubations the build-up of toxic metabolites limited productivity. Measurements of microcosm productivity, biofilm-strength and attachment levels were used to assess community-aggregated traits which showed changes at both the community and individual-strain levels. Final-transfer communities were stratified with strains demonstrating a plastic phenotype when migrating between the high and low-O2 regions. The majority of community productivity came from the O2-depleted region rather than the top of the liquid column. This model system illustrates the complexity we expect to see in natural biofilm-forming communities. The connection between biofilms and the liquid column seen here has important implications for how these structures form and respond to selective pressure.

Simulations reveal challenges to artificial community selection and possible strategies for success

Multispecies microbial communities often display "community functions" arising from interactions of member species. Interactions are often difficult to decipher, making it challenging to design communities with desired functions. Alternatively, similar to artificial selection for individuals in agriculture and industry, one could repeatedly choose communities with the highest community functions to reproduce by randomly partitioning each into multiple "Newborn" communities for the next cycle. However, previous efforts in selecting complex communities have generated mixed outcomes that are difficult to interpret. To understand how to effectively enact community selection, we simulated community selection to improve a community function that requires 2 species and imposes a fitness cost on one or both species. Our simulations predict that improvement could be easily stalled unless various aspects of selection are carefully considered. These aspects include promoting species coexistence, suppressing noncontributors, choosing additional communities besides the highest functioning ones to reproduce, and reducing stochastic fluctuations in the biomass of each member species in Newborn communities. These considerations can be addressed experimentally. When executed effectively, community selection is predicted to improve costly community function, and may even force species to evolve slow growth to achieve species coexistence. Our conclusions hold under various alternative model assumptions and are therefore applicable to a variety of communities.

On the use of oxygenic photosynthesis for the sustainable production of commodity chemicals

A sustainable society will have to largely refrain from the use of fossil carbon deposits. In such a regime, renewable electricity can be harvested as a primary source of energy. However, as for the synthesis of carbon-based materials from bulk chemicals, an alternative is required. A sustainable approach towards this is the synthesis of commodity chemicals from CO₂ , water and sunlight. Multiple paths to achieve this have been designed and tested in the domains of chemistry and biology. In the latter, the use of both chemotrophic and phototrophic organisms has been advocated. 'Direct conversion' of CO₂ and H₂ O, catalyzed by an oxyphototroph, has excellent prospects to become the most economically competitive of these transformations, because of the relative ease of scale-up of this process. Significantly, for a wide range of energy and commodity products, a proof of principle via engineering of the corresponding production organism has been provided. In the optimization of a cyanobacterial production organism, a wide range of aspects has to be addressed. Of these, here we will put our focus on: (1) optimizing the (carbon) flux to the desired product; (2) increasing the genetic stability of the producing organism and (3) maximizing its energy conversion efficiency. Significant advances have been made on all these three aspects during the past 2 years and these will be discussed: (1) increasing the carbon partitioning to >50%; (2) aligning product formation with the growth of the cells and (3) expanding the photosynthetically active radiation region for oxygenic photosynthesis.

Model Microbial Consortia as Tools for Understanding Complex Microbial Communities

A major biological challenge in the postgenomic era has been untangling the composition and functions of microbes that inhabit complex communities or microbiomes. Multi-omics and modern bioinformatics have provided the tools to assay molecules across different cellular and community scales; however, mechanistic knowledge over microbial interactions often remains elusive. This is due to the immense diversity and the essentially undiminished volume of not-yet-cultured microbes. Simplified model communities hold some promise in enabling researchers to manage complexity so that they can mechanistically understand the emergent properties of microbial community interactions. In this review, we surveyed several approaches that have effectively used tractable model consortia to elucidate the complex behavior of microbial communities. We go further to provide some perspectives on the limitations and new opportunities with these approaches and highlight where these efforts are likely to lead as advances are made in molecular ecology and systems biology.

Constraint-based modeling in microbial food biotechnology

Genome-scale metabolic network reconstruction offers a means to leverage the value of the exponentially growing genomics data and integrate it with other biological knowledge in a structured format. Constraint-based modeling (CBM) enables both the qualitative and quantitative analyses of the reconstructed networks. The rapid advancements in these areas can benefit both the industrial production of microbial food cultures and their application in food processing. CBM provides several avenues for improving our mechanistic understanding of physiology and genotype–phenotype relationships. This is essential for the rational improvement of industrial strains, which can further be facilitated through various model-guided strain design approaches. CBM of microbial communities offers a valuable tool for the rational design of defined food cultures, where it can catalyze hypothesis generation and provide unintuitive rationales for the development of enhanced community phenotypes and, consequently, novel or improved food products. In the industrial-scale production of microorganisms for food cultures, CBM may enable a knowledge-driven bioprocess optimization by rationally identifying strategies for growth and stability improvement. Through these applications, we believe that CBM can become a powerful tool for guiding the areas of strain development, culture development and process optimization in the production of food cultures. Nevertheless, in order to make the correct choice of the modeling framework for a particular application and to interpret model predictions in a biologically meaningful manner, one should be aware of the current limitations of CBM.

The physical boundaries of public goods cooperation between surface-attached bacterial cells

Bacteria secrete a variety of compounds important for nutrient scavenging, competition mediation and infection establishment. While there is a general consensus that secreted compounds can be shared and therefore have social consequences for the bacterial collective, we know little about the physical limits of such bacterial social interactions. Here, we address this issue by studying the sharing of iron-scavenging siderophores between surface-attached microcolonies of the bacterium Pseudomonas aeruginosa Using single-cell fluorescence microscopy, we show that siderophores, secreted by producers, quickly reach non-producers within a range of 100 µm, and significantly boost their fitness. Producers in turn respond to variation in sharing efficiency by adjusting their pyoverdine investment levels. These social effects wane with larger cell-to-cell distances and on hard surfaces. Thus, our findings reveal the boundaries of compound sharing, and show that sharing is particularly relevant between nearby yet physically separated bacteria on soft surfaces, matching realistic natural conditions such as those encountered in soft tissue infections.

Bacterial social interactions and the emergence of community-intrinsic properties

Bacterial communities are dominated and shaped by social interactions, which facilitate the emergence of properties observed only in the community setting. Such community-intrinsic properties impact not only the phenotypes of cells in a community, but also community composition and function, and are thus likely to affect a potential host. Studying community-intrinsic properties is, therefore, important for furthering our understanding of clinical, applied and environmental microbiology. Here, we provide recent examples of research investigating community-intrinsic properties, focusing mainly on community composition and interactions in multispecies biofilms. We hereby wish to emphasize the importance of studying social interactions in settings where community-intrinsic properties are likely to emerge.

Constraint-based stoichiometric modelling from single organisms to microbial communities

Microbial communities are ubiquitously found in Nature and have direct implications for the environment, human health and biotechnology. The species composition and overall function of microbial communities are largely shaped by metabolic interactions such as competition for resources and cross-feeding. Although considerable scientific progress has been made towards mapping and modelling species-level metabolism, elucidating the metabolic exchanges between microorganisms and steering the community dynamics remain an enormous scientific challenge. In view of the complexity, computational models of microbial communities are essential to obtain systems-level understanding of ecosystem functioning. This review discusses the applications and limitations of constraint-based stoichiometric modelling tools, and in particular flux balance analysis (FBA). We explain this approach from first principles and identify the challenges one faces when extending it to communities, and discuss the approaches used in the field in view of these challenges. We distinguish between steady-state and dynamic FBA approaches extended to communities. We conclude that much progress has been made, but many of the challenges are still open.

Cell Surface Properties of Lactococcus lactis Reveal Milk Protein Binding Specifically Evolved in Dairy Isolates

Surface properties of bacteria are determined by the molecular composition of the cell wall and they are important for interactions of cells with their environment. Well-known examples of bacterial interactions with surfaces are biofilm formation and the fermentation of solid materials like food and feed. Lactococcus lactis is broadly used for the fermentation of cheese and buttermilk and it is primarily isolated from either plant material or the dairy environment. In this study, we characterized surface hydrophobicity, charge, emulsification properties, and the attachment to milk proteins of 55 L. lactis strains in stationary and exponential growth phases. The attachment to milk protein was assessed through a newly developed flow cytometry-based protocol. Besides finding a high degree of biodiversity, phenotype-genotype matching allowed the identification of candidate genes involved in the modification of the cell surface. Overexpression and gene deletion analysis allowed to verify the predictions for three identified proteins that altered surface hydrophobicity and attachment of milk proteins. The data also showed that lactococci isolated from a dairy environment bind higher amounts of milk proteins when compared to plant isolates. It remains to be determined whether the alteration of surface properties also has potential to alter starter culture functionalities.

Competition and niche separation of pelagic bacteria in freshwater habitats

Freshwater bacterioplankton assemblages are composed of sympatric populations that can be delineated, for example, by ribosomal RNA gene relatedness and that differ in key ecophysiological properties. They may be free-living or attached, specialized for particular concentrations or subsets of substrates, or invest a variable amount of their resources in defence traits against protistan predators and viruses. Some may be motile and tactic whereas others are not, with far-reaching implications for their respective life styles and niche partitioning. The co-occurrence of competitors with overlapping growth requirements has profound consequences for the stability of community functions; it can to some extent be explained by habitat factors such as the microscale complexity and spatiotemporal variability of the lacustrine environments. On the other hand, the composition and diversity of freshwater microbial assemblages also reflects non-equilibrium states, dispersal and the stochasticity of community assembly processes. This review synoptically discusses the competition and niche separation of heterotrophic bacterial populations (defined at various levels of phylogenetic resolution) in the pelagic zone of inland surface waters from a variety of angles, focusing on habitat heterogeneity and the resulting biogeographic distribution patterns, the ecophysiological adaptations to the substrate field and the interactions of prokaryotes with predators and viruses.

The fitness burden imposed by synthesising quorum sensing signals

It is now well established that bacterial populations utilize cell-to-cell signaling (quorum-sensing, QS) to control the production of public goods and other co-operative behaviours. Evolutionary theory predicts that both the cost of signal production and the response to signals should incur fitness costs for producing cells. Although costs imposed by the downstream consequences of QS have been shown, the cost of QS signal molecule (QSSM) production and its impact on fitness has not been examined. We measured the fitness cost to cells of synthesising QSSMs by quantifying metabolite levels in the presence of QSSM synthases. We found that: (i) bacteria making certain QSSMs have a growth defect that exerts an evolutionary cost, (ii) production of QSSMs negatively correlates with intracellular concentrations of QSSM precursors, (iii) the production of heterologous QSSMs negatively impacts the production of a native QSSM that shares common substrates, and (iv) supplementation with exogenously added metabolites partially rescued growth defects imposed by QSSM synthesis. These data identify the sources of the fitness costs incurred by QSSM producer cells, and indicate that there may be metabolic trade-offs associated with QS signaling that could exert selection on how signaling evolves.