Bacterial interspecies interactions modulate pH-mediated antibiotic tolerance

Multidimensional tolerance landscapes reveal antibiotic-environment interactions affecting population dynamics of wastewater bacteria

City sewers harbor diverse bacterial communities that are continuously exposed to a myriad of antibiotic residues resulting from human consumption and excretion. Despite their sub-inhibitory concentrations in sewage, these pharmaceutical residues affect the growth rate and the yield of susceptible wastewater-associated bacteria. Moreover, environmental conditions in sewers are complex, including variations in temperature and, in many coastal city sewers, salinity. These variables can modulate antibiotic tolerance and therefore affect the dynamics of microbial populations. To explore such interactions between antibiotics and abiotic environmental factors, we built continuous multivariate tolerance landscapes for three bacterial species commonly detected in sewage: Escherichia coli, the emerging pathogen Streptococcus suis, and a typical sewer dweller, Arcobacter cryaerophilus. We projected their intrinsic growth rate and carrying capacity onto a complex environment including temperature, salinity, and a range of concentrations of two antibiotics frequently measured in urban wastewater (ciprofloxacin and azithromycin). We revealed that antibiotic tolerance was maximal at salinities close to seawater for both E. coli and S. suis, and that the direction of the interaction between antibiotics and temperature is species dependent. In E. coli, we additionally observed a third-order interaction among salinity, temperature and antibiotics, highlighting the limits of predicting field dynamics of bacterial populations using standard laboratory measures. We projected these tolerance curves onto time series data of temperature and conductivity measured in the sewers of Barcelona. Our model highlights that low concentrations of antibiotics could exclude the most sensitive species, while interactions between antibiotics, temperature, and salinity substantially affected the dynamics of the more tolerant ones.

Assembly of stool-derived bacterial communities follows "early-bird" resource utilization dynamics

Diet can impact host health through changes to the gut microbiota, yet we lack mechanistic understanding linking nutrient availability and microbiota composition. Here, we use thousands of microbial communities cultured in vitro from human stool to develop a predictive model of community composition upon addition of single nutrients from central carbon metabolism to a complex medium. Among these communities, membership was largely determined by the donor stool, whereas relative abundances were determined by the supplemental carbon source. The absolute abundance of most taxa was independent of the supplementing nutrient due to the ability of a few organisms to quickly exhaust their niche in the complex medium and then exploit and monopolize the supplemental carbon source. Relative abundances of dominant taxa could be predicted from the nutritional preferences and growth dynamics of species in isolation, and exceptions were consistent with strain-level variation in growth capabilities. Our study reveals that assembly of this community of gut commensals can be explained by nutrient utilization dynamics that provide a predictive framework for manipulating community composition through nutritional perturbations.

Genome Analysis of 6222 Bacterial Isolates from Livestock and Food Environments in Spain to Decipher the Antibiotic Resistome

Background/Objectives: Antimicrobial resistance (AMR) poses a significant threat to global health and the economy, with projected costs ranging from $300 billion to $1 trillion annually and an estimated 10 million deaths per year by 2050. The food chain, from primary production to retail, represents a critical entry point for antimicrobial resistant bacteria into communities. This underscores the need for a coordinated "One Health" approach, integrating efforts in animal production, environmental health, and human healthcare to address this global concern. This study aimed to characterize the global resistome in Spanish primary production by sequencing 6222 bacterial genomes from animal origin. Methods and Results: Whole genome sequencing was performed on bacterial isolates collected from various farms and analyzed using a validated bioinformatic pipeline. The analysis revealed a diverse range of bacterial species, with Enterobacteriaceae being the most prevalent family. Escherichia coli was the most common species, followed by Salmonella enterica and Pseudomonas aeruginosa. This study identified 1072 antimicrobial resistance genes coding for 43 different classes of resistance, potentially conferring resistance to 81 antimicrobials. Additionally, 79 different plasmid types were detected, highlighting the potential for horizontal gene transfer. Conclusions: The resistome analysis revealed genes conferring resistance to various antibiotic classes, as well as antiseptics, disinfectants, and efflux pump-mediated resistance. This comprehensive characterization of AMR genes circulating in bacteria from primary production provides crucial insights into the ecology of AMR in Spanish livestock.

Commensal acidification of specific gut regions produces a protective priority effect against enteropathogenic bacterial infection

The commensal microbiome has been shown to protect against newly introduced enteric pathogens in multiple host species, a phenomenon known as a priority effect. Multiple mechanisms can contribute to this protective priority effect, including antimicrobial compounds, nutrient competition, and pH changes. In Drosophila melanogaster , Lactiplantibacillus plantarum has been shown to protect against enteric pathogens. However, the strains of L. plantarum studied were derived from laboratory flies or non-fly environments and have been found to be unstable colonizers of the fly gut that mainly reside on the food. To study the priority effect using a naturally occurring microbial relationship, we isolated a wild-fly derived strain of L. plantarum that stably colonizes the fly gut in conjunction with a common enteric pathogen, Serratia marcescens . Flies stably associated with the L. plantarum strain were more resilient to oral Serratia marcescens infection as seen by longer lifespan and lower S. marcescens load in the gut. Through in vitro experiments, we found that L. plantarum inhibits S. marcescens growth due to acidification. We used gut imaging with pH-indicator dyes to show that L. plantarum reduces the gut pH to levels that restrict S. marcescens growth in vivo . In flies colonized with L. plantarum prior to S. marcescens infection, L. plantarum and S. marcescens are spatially segregated in the gut and S. marcescens is less abundant where L. plantarum heavily colonizes, indicating that acidification of specific gut regions is a mechanism of a protective priority effect.

Pharmacodynamics of interspecies interactions in polymicrobial infections

The pharmacodynamic response of bacterial pathogens to antibiotics can be influenced by interactions with other bacterial species in polymicrobial infections (PMIs). Understanding the complex eco-evolutionary dynamics of PMIs and their impact on antimicrobial treatment response represents a step towards developing improved treatment strategies for PMIs. Here, we investigated how interspecies interactions in a multi-species bacterial community affect the pharmacodynamic response to antimicrobial treatment. To this end, we developed an in silico model which combined agent-based modeling with ordinary differential equations. Our analyses suggest that both interspecies interactions, modifying either drug sensitivity or bacterial growth rate, and drug-specific pharmacological properties drive the bacterial pharmacodynamic response. Furthermore, lifestyle of the bacterial population and the range of interactions can influence the impact of species interactions. In conclusion, this study provides a foundation for the design of antimicrobial treatment strategies for PMIs which leverage the effects of interspecies interactions.

Methods for studying microbial acid stress responses: from molecules to populations

The study of how micro-organisms detect and respond to different stresses has a long history of producing fundamental biological insights while being simultaneously of significance in many applied microbiological fields including infection, food and drink manufacture, and industrial and environmental biotechnology. This is well-illustrated by the large body of work on acid stress. Numerous different methods have been used to understand the impacts of low pH on growth and survival of micro-organisms, ranging from studies of single cells to large and heterogeneous populations, from the molecular or biophysical to the computational, and from well-understood model organisms to poorly defined and complex microbial consortia. Much is to be gained from an increased general awareness of these methods, and so the present review looks at examples of the different methods that have been used to study acid resistance, acid tolerance, and acid stress responses, and the insights they can lead to, as well as some of the problems involved in using them. We hope this will be of interest both within and well beyond the acid stress research community.

Disruption of bacterial interactions and community assembly in Babesia-infected Haemaphysalis longicornis following antibiotic treatment

BACKGROUND

A previous study highlighted the role of antibiotic-induced dysbiosis in the tick microbiota, facilitating the transstadial transmission of Babesia microti from nymph to adult in Haemaphysalis longicornis. This study builds on previous findings by analyzing sequence data from an earlier study to investigate bacterial interactions that could be linked to enhanced transstadial transmission of Babesia in ticks. The study employed antibiotic-treated (AT) and control-treated (CT) Haemaphysalis longicornis ticks to investigate shifts in microbial community assembly. Network analysis techniques were utilized to assess bacterial interactions, comparing network centrality measures between AT and CT groups, alongside studying network robustness and connectivity loss. Additionally, functional profiling was conducted to evaluate metabolic diversity in response to antibiotic treatment.

RESULTS

The analysis revealed notable changes in microbial community assembly in response to antibiotic treatment. Antibiotic-treated (AT) ticks displayed a greater number of connected nodes but fewer correlations compared to control-treated (CT) ticks, indicating a less interactive yet more connected microbial community. Network centrality measures such as degree, betweenness, closeness, and eigenvector centrality, differed significantly between AT and CT groups, suggesting alterations in local network dynamics due to antibiotic intervention. Coxiella and Acinetobacter exhibited disrupted connectivity and roles, with the former showing reduced interactions in AT group and the latter displaying a loss of connected nodes, emphasizing their crucial roles in microbial network stability. Robustness tests against node removal showed decreased stability in AT networks, particularly under directed attacks, confirming a susceptibility of the microbial community to disturbances. Functional profile analysis further indicated a higher diversity and richness in metabolic capabilities in the AT group, reflecting potential shifts in microbial metabolism as a consequence of antimicrobial treatment.

CONCLUSIONS

Our findings support that bacterial interaction traits boosting the transstadial transmission of Babesia could be associated with reduced colonization resistance. The disrupted microbial interactions and decreased network robustness in AT ticks suggest critical vulnerabilities that could be targeted for managing tick-borne diseases.

Deciphering the adaptation mechanism of anammox consortia under sulfamethoxazole stress: A model coupling resistance accumulation and interspecies-cooperation

Sulfamethoxazole (SMX) is frequently detected in wastewater where anammox applications are promising. While it has been demonstrated that anammox consortia can adapt to SMX stress, the underlying community adaptation strategy has not yet been fully addressed. Therefore, in this study, we initially ascertained anammox consortia's ability to co-metabolize SMX in batch tests. Then, a 200-day domestication process of anammox consortia under SMX stress was carried out with community variations and transcriptional activities monitored by metagenomic and metatranscriptomic sequencing techniques. Despite the initial drop to 41.88 %, the nitrogen removal efficiency of the anammox consortia rebounded to 84.64 % post-domestication under 5 mg/L SMX. Meanwhile, a 4.85-fold accumulation of antibiotic resistance genes (ARGs) under SMX stress was observed as compared to the control group. Interestingly, the anammox consortia may unlock the SMX-inhibited folate synthesis pathway through a novel interspecies cooperation triangle among Nitrospira (NAA), Desulfobacillus denitrificans (DSS1), and the core anammox population Candidatus Brocadia sinica (AMX1), in which the modified dihydropteroate synthase (encoded by sul1) of NAA reconnected the symbiotic cooperation between AMX1 and DSS1. Overall, this study provides a new model for the adaptation strategies of anammox consortia to SMX stress.

Deciphering the core microbiota in open environment solid-state fermentation of Beijing rice vinegar and its correlation with environmental factors

BACKGROUND

Rice vinegar is a popular cereal vinegar worldwide and is typically produced in an open environment, and the ecosystem of solid-state fermentation is complicated and robust. The present study aimed to reveal the shaping force of the establishment of the ecosystem of Beijing rice vinegar, the core function microbiota and their correlation with critical environmental factors. [Correction added after first online publication on 29 May 2024; the word "worldwide" has been removed from the first sentence under the section Background.] RESULTS: The experimental findings revealed the changes in environmental factors, major metabolites and microbial patterns during Beijing rice vinegar fermentation were obtained. The major metabolites accumulated at the middle and late acetic acid fermentation (AAF) periods. Principal coordinates and t-test analyses revealed the specific bacterial and fungal species at corresponding stages. Kosakonia, Methlobacterium, Sphingomonas, unidentified Rhizobiaceae, Pseudozyma and Saccharomycopsis dorminated during saccharification and alcohol fermentation and early AAF, whereas Lactococcus, Acetobacter, Rhodotorula and Kazachstania dominated the later AAF stages. Canonical correspondence analysis of environmental factors with core microbiota. Temperature and total acid were the most significant factors correlated with the SAF bacterial profile (Pediococcus, Weissella, Enterococcus and Kosakonia). Ethanol was the most significant factor between AAF1 and AAF3, and mainly affected Acetobacter and Lactobacillus. Conversely, ethanol was the most significant factor in the SAF, AAF1 and AAF3 fungi communities; typical microorganisms were Saccharomyces and Malassezia. Furthermore, the predicted phenotypes of bacteria and their response to environmental factors were evaluated.

CONCLUSION

In conclusion, the present study has provided insights into the process regulation of spontaneous fermentation and distinguished the key driving forces in the microbiota of Beijing rice vinegar fermentation. © 2024 Society of Chemical Industry.

Nutrient competition predicts gut microbiome restructuring under drug perturbations

Human gut commensal bacteria are routinely exposed to various stresses, including therapeutic drugs, and collateral effects are difficult to predict. To systematically interrogate community-level effects of drug perturbations, we screened stool-derived in vitro communities with 707 clinically relevant small molecules. Across ∼5,000 community-drug interaction conditions, compositional and metabolomic responses were predictably impacted by nutrient competition, with certain species exhibiting improved growth due to adverse impacts on competitors. Changes to community composition were generally reversed by reseeding with the original community, although occasionally species promotion was long-lasting, due to higher-order interactions, even when the competitor was reseeded. Despite strong selection pressures, emergence of resistance within communities was infrequent. Finally, while qualitative species responses to drug perturbations were conserved across community contexts, nutrient competition quantitatively affected their abundances, consistent with predictions of consumer-resource models. Our study reveals that quantitative understanding of the interaction landscape, particularly nutrient competition, can be used to anticipate and potentially mitigate side effects of drug treatment on the gut microbiota.

Microbiome and physical activity

Regular physical activity promotes health benefits and contributes to develop the individual biological potential. Chronical physical activity performed at moderate and high-intensity is the intensity more favorable to produce health development in athletes and improve the gut microbiota balance. The athletic microbiome is characterized by increased microbial diversity and abundance as well as greater phenotypic versatility. In addition, physical activity and microbiota composition have bidirectional effects, with regular physical activity improving microbial composition and microbial composition enhancing physical performance. The improvement of physical performance by a healthy microbiota is related to different phenotypes: i) efficient metabolic development, ii) improved regulation of intestinal permeability, iii) favourable modulation of local and systemic inflammatory and efficient immune responses, iv) efective regulation of systemic pH and, v) protection against acute stressful events such as environmental exposure to altitude or heat. The type of sport, both intensity or volume characteristics promote microbiota specialisation. Individual assessment of the state of the gut microbiota can be an effective biomarker for monitoring health in the medium to long term. The relationship between the microbiota and the rest of the body is bidirectional and symbiotic, with a full connection between the systemic functions of the nervous, musculoskeletal, endocrine, metabolic, acid-base and immune systems. In addition, circadian rhythms, including regular physical activity, directly influence the adaptive response of the microbiota. In conclusion, regular stimuli of moderate- and high-intensity physical activity promote greater diversity, abundance, resilience and versatility of the gut microbiota. This effect is highly beneficial for human health when healthy lifestyle habits including nutrition, hydration, rest, chronoregulation and physical activity.

Resource competition predicts assembly of gut bacterial communities in vitro

Microbial community dynamics arise through interspecies interactions, including resource competition, cross-feeding and pH modulation. The individual contributions of these mechanisms to community structure are challenging to untangle. Here we develop a framework to estimate multispecies niche overlaps by combining metabolomics data of individual species, growth measurements in spent media and mathematical models. We applied our framework to an in vitro model system comprising 15 human gut commensals in complex media and showed that a simple model of resource competition accounted for most pairwise interactions. Next, we built a coarse-grained consumer-resource model by grouping metabolomic features depleted by the same set of species and showed that this model predicted the composition of 2-member to 15-member communities with reasonable accuracy. Furthermore, we found that incorporation of cross-feeding and pH-mediated interactions improved model predictions of species coexistence. Our theoretical model and experimental framework can be applied to characterize interspecies interactions in bacterial communities in vitro.

Inter-species interactions between two bacterial flower commensals and a floral pathogen reduce disease incidence and alter pathogen activity

Flowers are colonized by a diverse community of microorganisms that can alter plant health and interact with floral pathogens. Erwinia amylovora is a flower-inhabiting bacterium and a pathogen that infects different plant species, including Malus × domestica (apple). Previously, we showed that the co-inoculation of two bacterial strains, members of the genera Pseudomonas and Pantoea, isolated from apple flowers, reduced disease incidence caused by this floral pathogen. Here, we decipher the ecological interactions between the two flower-associated bacteria and E. amylovora in field experimentation and in vitro co-cultures. The two flower commensal strains did not competitively exclude E. amylovora from the stigma habitat, as both bacteria and the pathogen co-existed on the stigma of apple flowers and in vitro. This suggests that plant protection might be mediated by other mechanisms than competitive niche exclusion. Using a synthetic stigma exudation medium, ternary co-culture of the bacterial strains led to a substantial alteration of gene expression in both the pathogen and the two microbiota members. Importantly, the gene expression profiles for the ternary co-culture were not just additive from binary co-cultures, suggesting that some functions only emerged in multipartite co-culture. Additionally, the ternary co-culture of the strains resulted in a stronger acidification of the growth milieu than mono- or binary co-cultures, pointing to another emergent property of co-inoculation. Our study emphasizes the critical role of emergent properties mediated by inter-species interactions within the plant holobiont and their potential impact on plant health and pathogen behavior.

IMPORTANCE

Fire blight, caused by Erwinia amylovora, is one of the most important plant diseases of pome fruits. Previous work largely suggested plant microbiota commensals suppressed disease by antagonizing pathogen growth. However, inter-species interactions of multiple flower commensals and their influence on pathogen activity and behavior have not been well studied. Here, we show that co-inoculating two bacterial strains that naturally colonize the apple flowers reduces disease incidence. We further demonstrate that the interactions between these two microbiota commensals and the floral pathogen led to the emergence of new gene expression patterns and a strong alteration of the external pH, factors that may modify the pathogen's behavior. Our findings emphasize the critical role of emergent properties mediated by inter-species interactions between plant microbiota and plant pathogens and their impact on plant health.

Active pH regulation facilitates Bacillus subtilis biofilm development in a minimally buffered environment

Biofilms provide individual bacteria with many advantages, yet dense cellular proliferation can also create intrinsic metabolic challenges including excessive acidification. Because such pH stress can be masked in buffered laboratory media-such as MSgg commonly used to study Bacillus subtilis biofilms-it is not always clear how such biofilms cope with minimally buffered natural environments. Here, we report how B. subtilis biofilms overcome this intrinsic metabolic challenge through an active pH regulation mechanism. Specifically, we find that these biofilms can modulate their extracellular pH to the preferred neutrophile range, even when starting from acidic and alkaline initial conditions, while planktonic cells cannot. We associate this behavior with dynamic interplay between acetate and acetoin biosynthesis and show that this mechanism is required to buffer against biofilm acidification. Furthermore, we find that buffering-deficient biofilms exhibit dysregulated biofilm development when grown in minimally buffered conditions. Our findings reveal an active pH regulation mechanism in B. subtilis biofilms that could lead to new targets to control unwanted biofilm growth.IMPORTANCEpH is known to influence microbial growth and community dynamics in multiple bacterial species and environmental contexts. Furthermore, in many bacterial species, rapid cellular proliferation demands the use of overflow metabolism, which can often result in excessive acidification. However, in the case of bacterial communities known as biofilms, these acidification challenges can be masked when buffered laboratory media are employed to stabilize the pH environment for optimal growth. Our study reveals that B. subtilis biofilms use an active pH regulation mechanism to mitigate both growth-associated acidification and external pH challenges. This discovery provides new opportunities for understanding microbial communities and could lead to new methods for controlling biofilm growth outside of buffered laboratory conditions.

Richness and density jointly determine context dependence in bacterial interactions

Pairwise interactions are often used to predict features of complex microbial communities due to the challenge of measuring multi-species interactions in high dimensional contexts. This assumes that interactions are unaffected by community context. Here, we used synthetic bacterial communities to investigate that assumption by observing how interactions varied across contexts. Interactions were most often weakly negative and showed a phylogenetic signal among genera. Community richness and total density emerged as strong predictors of interaction strength and contributed to an attenuation of interactions as richness increased. Population level and per-capita measures of interactions both displayed such attenuation, suggesting factors beyond systematic changes in population size were involved; namely, changes to the interactions themselves. Nevertheless, pairwise interactions retained some explanatory power across contexts, provided those contexts were not substantially divergent in richness. These results suggest that understanding the emergent properties of microbial interactions can improve our ability to predict the features of microbial communities.

Emergent antibiotic persistence in a spatially structured synthetic microbial mutualism

Antibiotic persistence (heterotolerance) allows a subpopulation of bacteria to survive antibiotic-induced killing and contributes to the evolution of antibiotic resistance. Although bacteria typically live in microbial communities with complex ecological interactions, little is known about how microbial ecology affects antibiotic persistence. Here, we demonstrated within a synthetic two-species microbial mutualism of Escherichia coli and Salmonella enterica that the combination of cross-feeding and community spatial structure can emergently cause high antibiotic persistence in bacteria by increasing the cell-to-cell heterogeneity. Tracking ampicillin-induced death for bacteria on agar surfaces, we found that E. coli forms up to 55 times more antibiotic persisters in the cross-feeding coculture than in monoculture. This high persistence could not be explained solely by the presence of S. enterica, the presence of cross-feeding, average nutrient starvation, or spontaneous resistant mutations. Time-series fluorescent microscopy revealed increased cell-to-cell variation in E. coli lag time in the mutualistic co-culture. Furthermore, we discovered that an E. coli cell can survive antibiotic killing if the nearby S. enterica cells on which it relies die first. In conclusion, we showed that the high antibiotic persistence phenotype can be an emergent phenomenon caused by a combination of cross-feeding and spatial structure. Our work highlights the importance of considering spatially structured interactions during antibiotic treatment and understanding microbial community resilience more broadly.

Antibiotic perturbations to the gut microbiome

Antibiotic-mediated perturbation of the gut microbiome is associated with numerous infectious and autoimmune diseases of the gastrointestinal tract. Yet, as the gut microbiome is a complex ecological network of microorganisms, the effects of antibiotics can be highly variable. With the advent of multi-omic approaches for systems-level profiling of microbial communities, we are beginning to identify microbiome-intrinsic and microbiome-extrinsic factors that affect microbiome dynamics during antibiotic exposure and subsequent recovery. In this Review, we discuss factors that influence restructuring of the gut microbiome on antibiotic exposure. We present an overview of the currently complex picture of treatment-induced changes to the microbial community and highlight essential considerations for future investigations of antibiotic-specific outcomes. Finally, we provide a synopsis of available strategies to minimize antibiotic-induced damage or to restore the pretreatment architectures of the gut microbial community.

Antibiotic resistance in bacterial communities

Bacteria are single-celled organisms, but the survival of microbial communities relies on complex dynamics at the molecular, cellular, and ecosystem scales. Antibiotic resistance, in particular, is not just a property of individual bacteria or even single-strain populations, but depends heavily on the community context. Collective community dynamics can lead to counterintuitive eco-evolutionary effects like survival of less resistant bacterial populations, slowing of resistance evolution, or population collapse, yet these surprising behaviors are often captured by simple mathematical models. In this review, we highlight recent progress - in many cases, advances driven by elegant combinations of quantitative experiments and theoretical models - in understanding how interactions between bacteria and with the environment affect antibiotic resistance, from single-species populations to multispecies communities embedded in an ecosystem.

Gut microbiota interspecies interactions shape the response of Clostridioides difficile to clinically relevant antibiotics

In the human gut, the growth of the pathogen Clostridioides difficile is impacted by a complex web of interspecies interactions with members of human gut microbiota. We investigate the contribution of interspecies interactions on the antibiotic response of C. difficile to clinically relevant antibiotics using bottom-up assembly of human gut communities. We identify 2 classes of microbial interactions that alter C. difficile's antibiotic susceptibility: interactions resulting in increased ability of C. difficile to grow at high antibiotic concentrations (rare) and interactions resulting in C. difficile growth enhancement at low antibiotic concentrations (common). Based on genome-wide transcriptional profiling data, we demonstrate that metal sequestration due to hydrogen sulfide production by the prevalent gut species Desulfovibrio piger increases the minimum inhibitory concentration (MIC) of metronidazole for C. difficile. Competition with species that display higher sensitivity to the antibiotic than C. difficile leads to enhanced growth of C. difficile at low antibiotic concentrations due to competitive release. A dynamic computational model identifies the ecological principles driving this effect. Our results provide a deeper understanding of ecological and molecular principles shaping C. difficile's response to antibiotics, which could inform therapeutic interventions.

Interspecies interaction reduces selection for antibiotic resistance in Escherichia coli

Evolution of microbial traits depends on the interaction of a species with its environment as well as with other coinhabiting species. However, our understanding of the evolution of specific microbial traits, such as antibiotic resistance in complex environments is limited. Here, we determine the role of interspecies interactions on the dynamics of nitrofurantoin (NIT) resistance selection among Escherichia coli. We created a synthetic two-species community comprised of two variants of E. coli (NIT susceptible and resistant) and Bacillus subtilis in minimal media with glucose as the sole carbon source. We show that the presence of B. subtilis significantly slows down the selection for the resistant E. coli mutant when NIT is present and that this slowdown is not due to competition for resources. Instead, the dampening of NIT resistance enrichment is largely mediated by extracellular compounds produced by B. subtilis with the peptide YydF playing a significant role. Our results not only demonstrate the impact of interspecies interactions on the evolution of microbial traits but also show the importance of using synthetic microbial systems in unravelling relevant interactions and mechanisms affecting the evolution of antibiotic resistance. This finding implies that interspecies interactions should be considered to better understand and predict resistance evolution in the clinic as well as in nature.

A symbiotic physical niche in Drosophila melanogaster regulates stable association of a multi-species gut microbiota

The gut is continuously invaded by diverse bacteria from the diet and the environment, yet microbiome composition is relatively stable over time for host species ranging from mammals to insects, suggesting host-specific factors may selectively maintain key species of bacteria. To investigate host specificity, we used gnotobiotic Drosophila, microbial pulse-chase protocols, and microscopy to investigate the stability of different strains of bacteria in the fly gut. We show that a host-constructed physical niche in the foregut selectively binds bacteria with strain-level specificity, stabilizing their colonization. Primary colonizers saturate the niche and exclude secondary colonizers of the same strain, but initial colonization by Lactobacillus species physically remodels the niche through production of a glycan-rich secretion to favor secondary colonization by unrelated commensals in the Acetobacter genus. Our results provide a mechanistic framework for understanding the establishment and stability of a multi-species intestinal microbiome.

Determinants of synergistic cell-cell interactions in bacteria

Bacteria are ubiquitous and colonize virtually every conceivable habitat on earth. To achieve this, bacteria require different metabolites and biochemical capabilities. Rather than trying to produce all of the needed materials by themselves, bacteria have evolved a range of synergistic interactions, in which they exchange different commodities with other members of their local community. While it is widely acknowledged that synergistic interactions are key to the ecology of both individual bacteria and entire microbial communities, the factors determining their establishment remain poorly understood. Here we provide a comprehensive overview over our current knowledge on the determinants of positive cell-cell interactions among bacteria. Taking a holistic approach, we review the literature on the molecular mechanisms bacteria use to transfer commodities between bacterial cells and discuss to which extent these mechanisms favour or constrain the successful establishment of synergistic cell-cell interactions. In addition, we analyse how these different processes affect the specificity among interaction partners. By drawing together evidence from different disciplines that study the focal question on different levels of organisation, this work not only summarizes the state of the art in this exciting field of research, but also identifies new avenues for future research.

Advances in linking single-cell bacterial stress response to population-level survival

Stress response mechanisms can allow bacteria to survive a myriad of challenges, including nutrient changes, antibiotic encounters, and antagonistic interactions with other microbes. Expression of these stress response pathways, in addition to other cell features such as growth rate and metabolic state, can be heterogeneous across cells and over time. Collectively, these single-cell-level phenotypes contribute to an overall population-level response to stress. These include diversifying actions, which can be used to enable bet-hedging, and coordinated actions, such as biofilm production, horizontal gene transfer, and cross-feeding. Here, we highlight recent results and emerging technologies focused on both single-cell and population-level responses to stressors, and we draw connections about the combined impact of these effects on survival of bacterial communities.

Community interactions drive the evolution of antibiotic tolerance in bacteria

The emergence of antibiotic tolerance (prolonged survival against exposure) in natural bacterial populations is a major concern. Since it has been studied primarily in isogenic populations, we do not yet understand how ecological interactions in a diverse community impact the evolution of tolerance. To address this, we studied the evolutionary dynamics of a synthetic bacterial community composed of two interacting strains. In this community, an antibiotic-resistant strain protected the other, susceptible strain by degrading the antibiotic ampicillin in the medium. Surprisingly, we found that in the presence of antibiotics, the susceptible strain evolved tolerance. Tolerance was typified by an increase in survival as well as an accompanying decrease in the growth rate, highlighting a trade-off between the two. A simple mathematical model explained that the observed decrease in the death rate, even when coupled with a decreased growth rate, is beneficial in a community with weak protective interactions. In the presence of strong interactions, the model predicted that the trade-off would instead be detrimental, and tolerance would not emerge, which we experimentally verified. By whole genome sequencing the evolved tolerant isolates, we identified two genetic hot spots which accumulated mutations in parallel lines, suggesting their association with tolerance. Our work highlights that ecological interactions can promote antibiotic tolerance in bacterial communities, which has remained understudied.

Assembly of gut-derived bacterial communities follows "early-bird" resource utilization dynamics

Diet can impact host health through changes to the gut microbiota, yet we lack mechanistic understanding linking nutrient availability and microbiota composition. Here, we use thousands of microbial communities cultured in vitro from human feces to uncover simple assembly rules and develop a predictive model of community composition upon addition of single nutrients from central carbon metabolism to a complex medium. Community membership was largely determined by the donor feces, whereas relative abundances were determined by the supplemental carbon source. The absolute abundance of most taxa was independent of the supplementing nutrient, due to the ability of fast-growing organisms to quickly exhaust their niche in the complex medium and then exploit and monopolize the supplemental carbon source. Relative abundances of dominant taxa could be predicted from the nutritional preferences and growth dynamics of species in isolation, and exceptions were consistent with strain-level variation in growth capabilities. Our study reveals that community assembly follows simple rules of nutrient utilization dynamics and provides a predictive framework for manipulating gut commensal communities through nutritional perturbations.

Classifying Interactions in a Synthetic Bacterial Community Is Hindered by Inhibitory Growth Medium

Predicting the fate of a microbial community and its member species relies on understanding the nature of their interactions. However, designing simple assays that distinguish between interaction types can be challenging. Here, we performed spent medium assays based on the predictions of a mathematical model to decipher the interactions among four bacterial species: Agrobacterium tumefaciens, Comamonas testosteroni, Microbacterium saperdae, and Ochrobactrum anthropi. While most experimental results matched model predictions, the behavior of C. testosteroni did not: its lag phase was reduced in the pure spent media of A. tumefaciens and M. saperdae but prolonged again when we replenished our growth medium. Further experiments showed that the growth medium actually delayed the growth of C. testosteroni, leading us to suspect that A. tumefaciens and M. saperdae could alleviate this inhibitory effect. There was, however, no evidence supporting such "cross-detoxification," and instead, we identified metabolites secreted by A. tumefaciens and M. saperdae that were then consumed or "cross-fed" by C. testosteroni, shortening its lag phase. Our results highlight that even simple, defined growth media can have inhibitory effects on some species and that such negative effects need to be included in our models. Based on this, we present new guidelines to correctly distinguish between different interaction types such as cross-detoxification and cross-feeding. IMPORTANCE Communities of microbes colonize virtually every place on earth. Ultimately, we strive to predict and control how these communities behave, for example, if they reside in our guts and make us sick. But precise control is impossible unless we can identify exactly how their member species interact with one another. To find a systematic way to measure interactions, we started very simply with a small community of four bacterial species and carefully designed experiments based on a mathematical model. This first attempt accurately mapped out interactions for all species except one. By digging deeper, we understood that our method failed for that species as it was suffering in the growth medium that we chose. A revised model that considered that growth media can be harmful could then make more accurate predictions. What we have learned with these four species can now be applied to decipher interactions in larger communities.

Reclaimed wastewater reuse in irrigation: Role of biofilms in the fate of antibiotics and spread of antimicrobial resistance

Reclaimed wastewater associated biofilms are made up from diverse class of microbial communities that are continuously exposed to antibiotic residues. The presence of antibiotic resistance bacteria (ARB) and their associated antibiotic resistance genes (ARGs) ensures also a continuous selection pressure on biofilms that could be seen as hotspots for antibiotic resistance dissemination but can also play a role in antibiotic degradation. In this study, the antibiotic degradation and the abundance of four ARGs (qnrS, sul1, blaTEM, ermB), and two mobile genetic elements (MGEs) including IS613 and intl1, were followed in reclaimed wastewater and biofilm samples collected at the beginning and after 2 weeks of six antibiotics exposure (10 µg L^-1). Antibiotics were partially degraded and remained above lowest minimum inhibitory concentration (MIC) for environmental samples described in the literature. The most abundant genes detected both in biofilms and reclaimed wastewater were sul1, ermB, and intl1. The relative abundance of these genes in biofilms increased during the 2 weeks of exposure but the highest values were found in control samples (without antibiotics pressure), suggesting that bacterial community composition and diversity are the driven forces for resistance selection and propagation in biofilms, rather than exposure to antibiotics. Planktonic and biofilm bacterial communities were characterized. Planktonic cells are classically defined "as free flowing bacteria in suspension" as opposed to the sessile state (the so-called biofilm): "a structured community of bacterial cells enclosed in a self-produced polymeric matrix and adherent to an inert or living. surface" as stated by Costerton et al. (1999). The abundance of some genera known to harbor ARG such as Streptococcus, Exiguobacterium, Acholeplasma, Methylophylaceae and Porphyromonadaceae increased in reclaimed wastewater containing antibiotics. The presence of biofilm lowered the level of these genera in wastewater but, at the opposite, could also serve as a reservoir of these bacteria to re-colonize low-diversity wastewater. It seems that maintaining a high diversity is important to limit the dissemination of antimicrobial resistance among planktonic bacteria. Antibiotics had no influence on the biofilm development monitored with optical coherence tomography (OCT). Further research is needed in order to clarify the role of inter-species communication in biofilm on antibiotic degradation and resistance development and spreading.

Modulating the evolutionary trajectory of tolerance using antibiotics with different metabolic dependencies

Antibiotic tolerance, or the ability of bacteria to survive antibiotic treatment in the absence of genetic resistance, has been linked to chronic and recurrent infections. Tolerant cells are often characterized by a low metabolic state, against which most clinically used antibiotics are ineffective. Here, we show that tolerance readily evolves against antibiotics that are strongly dependent on bacterial metabolism, but does not arise against antibiotics whose efficacy is only minimally affected by metabolic state. We identify a mechanism of tolerance evolution in E. coli involving deletion of the sodium-proton antiporter gene nhaA, which results in downregulated metabolism and upregulated stress responses. Additionally, we find that cycling of antibiotics with different metabolic dependencies interrupts evolution of tolerance in vitro, increasing the lifetime of treatment efficacy. Our work highlights the potential for limiting the occurrence and extent of tolerance by accounting for antibiotic dependencies on bacterial metabolism.

Microbiome-by-ethanol interactions impact Drosophila melanogaster fitness, physiology, and behavior

The gut microbiota can affect how animals respond to ingested toxins, such as ethanol, which is prevalent in the diets of diverse animals and often leads to negative health outcomes in humans. Ethanol is a complex dietary factor because it acts as a toxin, behavioral manipulator, and nutritional source, with both direct effects on the host as well as indirect ones through the microbiome. Here, we developed a model for chronic, non-intoxicating ethanol ingestion in the adult fruit fly, Drosophila melanogaster, and paired this with the tractability of the fly gut microbiota, which can be experimentally removed. We linked numerous physiological, behavioral, and transcriptional variables to fly fitness, including a combination of intestinal barrier integrity, stored triglyceride levels, feeding behavior, and the immunodeficiency pathway. Our results reveal a complex tradeoff between lifespan and fecundity that is microbiome-dependent and modulated by dietary ethanol and feeding behavior.

Fast growth can counteract antibiotic susceptibility in shaping microbial community resilience to antibiotics

SignificanceAntibiotic exposure stands among the most used interventions to drive microbial communities away from undesired states. How the ecology of microbial communities shapes their recovery-e.g., posttreatment shifts toward Clostridioides difficile infections in the gut-after antibiotic exposure is poorly understood. We study community response to antibiotics using a model community that can reach two alternative states. Guided by theory, our experiments show that microbial growth following antibiotic exposure can counteract antibiotic susceptibility in driving transitions between alternative community states. This makes it possible to reverse the outcome of antibiotic exposure through modifying growth dynamics, including cooperative growth, of community members. Our research highlights the relevance of simple ecological models to better understand the long-term effects of antibiotic treatment.

Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas

Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these macroecological patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical distribution. Our model parametrizes the consumer-resource properties of a community using only a small number of global parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We show that variation in these macroscopic parameters strongly affects the time series statistics generated by the model, and we identify specific sets of global parameters that can recapitulate macroecological patterns across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice, without needing to specify microscopic details of resource consumption. These findings suggest that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under a simple model, and provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.

The impact of carbon to nitrogen ratios and pH on the microbial prevalence and polyhydroxybutyrate production levels using a mixed microbial starter culture

Growth conditions have been frequently studied in optimizing polyhydroxybutyrate (PHB) production, while few studies were performed to unravel the dynamic mixed microbial consortia (MMCs) in the process. In this study, the relationship between growth conditions (C/N ratios and pH) and the corresponding key-microbes were identified and monitored during PHB accumulation. The highest PHB level (70 wt% of dry cell mass) was obtained at pH 9, C/N 40, and acetic acid 10 g/L. Linking the dominant genera with the highest point of PHB accumulation, Thauera was the most prevalent species in all MMCs of pH 9, except when a C/N ratio of 1 was applied. Notably, dominant bacteria shifted at pH 7 (C/N 10) from Thauera (0 h) to Paracoccus, and subsequently to Alcaligenes following the process of PHB accumulation and consumption. Further understanding of the relationship between the structure of the microbial community and the performance will be beneficial for regulating and obtaining high PHB accumulation within an MMC. Our study illustrates the impact of C/N ratios and pH on microbial prevalence and PHB production levels using a mixed microbial starter culture. This knowledge will broaden industrial perspectives for regulating high PHB production and timely harvesting.

The physiology and genetics of bacterial responses to antibiotic combinations

Several promising strategies based on combining or cycling different antibiotics have been proposed to increase efficacy and counteract resistance evolution, but we still lack a deep understanding of the physiological responses and genetic mechanisms that underlie antibiotic interactions and the clinical applicability of these strategies. In antibiotic-exposed bacteria, the combined effects of physiological stress responses and emerging resistance mutations (occurring at different time scales) generate complex and often unpredictable dynamics. In this Review, we present our current understanding of bacterial cell physiology and genetics of responses to antibiotics. We emphasize recently discovered mechanisms of synergistic and antagonistic drug interactions, hysteresis in temporal interactions between antibiotics that arise from microbial physiology and interactions between antibiotics and resistance mutations that can cause collateral sensitivity or cross-resistance. We discuss possible connections between the different phenomena and indicate relevant research directions. A better and more unified understanding of drug and genetic interactions is likely to advance antibiotic therapy.

Inter-species interactions alter antibiotic efficacy in bacterial communities

The efficacy of antibiotic treatments targeting polymicrobial communities is not well predicted by conventional in vitro susceptibility testing based on determining minimum inhibitory concentration (MIC) in monocultures. One reason for this is that inter-species interactions can alter the community members' susceptibility to antibiotics. Here we quantify, and identify mechanisms for, community-modulated changes of efficacy for clinically relevant antibiotics against the pathogen Pseudomonas aeruginosa in model cystic fibrosis (CF) lung communities derived from clinical samples. We demonstrate that multi-drug resistant Stenotrophomonas maltophilia can provide high levels of antibiotic protection to otherwise sensitive P. aeruginosa. Exposure protection to imipenem was provided by chromosomally encoded metallo-β-lactamase that detoxified the environment; protection was dependent upon S. maltophilia cell density and was provided by S. maltophilia strains isolated from CF sputum, increasing the MIC of P. aeruginosa by up to 16-fold. In contrast, the presence of S. maltophilia provided no protection against meropenem, another routinely used carbapenem. Mathematical ordinary differential equation modelling shows that the level of exposure protection provided against different carbapenems can be explained by differences in antibiotic efficacy and inactivation rate. Together, these findings reveal that exploitation of pre-occurring antimicrobial resistance, and inter-specific competition, can have large impacts on pathogen antibiotic susceptibility, highlighting the importance of microbial ecology for designing successful antibiotic treatments for multispecies communities.

Establishment and characterization of stable, diverse, fecal-derived in vitro microbial communities that model the intestinal microbiota

Efforts to probe the role of the gut microbiota in disease would benefit from a system in which patient-derived bacterial communities can be studied at scale. We addressed this by validating a strategy to propagate phylogenetically complex, diverse, stable, and highly reproducible stool-derived communities in vitro. We generated hundreds of in vitro communities cultured from diverse stool samples in various media; certain media generally preserved inoculum composition, and inocula from different subjects yielded source-specific community compositions. Upon colonization of germ-free mice, community composition was maintained, and the host proteome resembled the host from which the community was derived. Treatment with ciprofloxacin in vivo increased susceptibility to Salmonella invasion in vitro, and the in vitro response to ciprofloxacin was predictive of compositional changes observed in vivo, including the resilience and sensitivity of each Bacteroides species. These findings demonstrate that stool-derived in vitro communities can serve as a powerful system for microbiota research.

Putting microbial interactions back into community contexts

Microbial interactions are key aspects of the biology of microbiomes. Recently, there has been a shift in the field towards studying interactions in more representative contexts, whether using multispecies model microbial communities or by looking at interactions in situ. Across diverse microbial systems, these studies have begun to identify common interaction mechanisms. These mechanisms include interactions related to toxic molecules, nutrient competition and cross-feeding, access to metals, signaling pathways, pH changes, and interactions within biofilms. Leveraging technological innovations, many of these studies have used an interdisciplinary approach combining genetic, metabolomic, imaging, and/or microfluidic techniques to gain insight into mechanisms of microbial interactions and into the impact of these interactions on microbiomes.

Bugs on Drugs: A Drosophila melanogaster Gut Model to Study In Vivo Antibiotic Tolerance of E. coli

With an antibiotic crisis upon us, we need to boost antibiotic development and improve antibiotics’ efficacy. Crucial is knowing how to efficiently kill bacteria, especially in more complex in vivo conditions. Indeed, many bacteria harbor antibiotic-tolerant persisters, variants that survive exposure to our most potent antibiotics and catalyze resistance development. However, persistence is often only studied in vitro as we lack flexible in vivo models. Here, I explored the potential of using Drosophila melanogaster as a model for antimicrobial research, combining methods in Drosophila with microbiology techniques: assessing fly development and feeding, generating germ-free or bacteria-associated Drosophila and in situ microscopy. Adult flies tolerate antibiotics at high doses, although germ-free larvae show impaired development. Orally presented E. coli associates with Drosophila and mostly resides in the crop. E. coli shows an overall high antibiotic tolerance in vivo potentially resulting from heterogeneity in growth rates. The hipA7 high-persistence mutant displays an increased antibiotic survival while the expected low persistence of ΔrelAΔspoT and ΔrpoS mutants cannot be confirmed in vivo. In conclusion, a Drosophila model for in vivo antibiotic tolerance research shows high potential and offers a flexible system to test findings from in vitro assays in a broader, more complex condition.

Quantitative biology of survival under antibiotic treatments

The mathematical formulation for the dynamics of growth reduction and/or killing under antibiotic treatments has a long history. Even before the extensive use of antibiotics, attempts to model the killing dynamics of biocides were made [1]. Here, we review relatively simple quantitative formulations of the two main modes of survival under antibiotics, resistance and tolerance, as well as their heterogeneity in bacterial populations. We focus on the two main types of heterogeneity that have been described: heteroresistance and antibiotic persistence, each linked to the variation in a different parameter of the antibiotic response dynamics. Finally, we review the effects on survival of combining resistance and tolerance mutations as well as on the mode and tempo of evolution under antibiotic treatments.

Genetic mutations in adaptive evolution of growth-independent vancomycin-tolerant Staphylococcus aureus

BACKGROUND

Antibiotic tolerance allows bacteria to overcome antibiotic treatment transiently and potentially accelerates the emergence of resistance. However, our understanding of antibiotic tolerance at the genetic level during adaptive evolution of Staphylococcus aureus remains incomplete. We sought to identify the mutated genes and verify the role of these genes in the formation of vancomycin tolerance in S. aureus.

METHODS

Vancomycin-susceptible S. aureus strain Newman was used to induce vancomycin-tolerant isolates in vitro by cyclic exposure under a high concentration of vancomycin (20× MIC). WGS and Sanger sequencing were performed to identify the genetic mutations. The function of mutated genes in vancomycin-tolerant isolates were verified by gene complementation. Other phenotypes of vancomycin-tolerant isolates were also determined, including mutation frequency, autolysis, lysostaphin susceptibility, cell wall thickness and cross-tolerance.

RESULTS

A series of vancomycin-tolerant S. aureus (VTSA) strains were isolated and 18 mutated genes were identified by WGS. Among these genes, pbp4, htrA, stp1, pth and NWMN_1068 were confirmed to play roles in VTSA formation. Mutation of mutL promoted the emergence of VTSA. All VTSA showed no changes in growth phenotype. Instead, they exhibited reduced autolysis, decreased lysostaphin susceptibility and thickened cell walls. In addition, all VTSA strains were cross-tolerant to antibiotics targeting cell wall synthesis but not to quinolones and lipopeptides.

CONCLUSIONS

Our results demonstrate that genetic mutations are responsible for emergence of phenotypic tolerance and formation of vancomycin tolerance may lie in cell wall changes in S. aureus.

Host Immunity Alters Community Ecology and Stability of the Microbiome in a Caenorhabditis elegans Model

A growing body of data suggests that the microbiome of a species can vary considerably from individual to individual, but the reasons for this variation—and the consequences for the ecology of these communities—remain only partially explained. In mammals, the emerging picture is that the metabolic state and immune system status of the host affect the composition of the microbiome, but quantitative ecological microbiome studies are challenging to perform in higher organisms. Here, we show that these phenomena can be quantitatively analyzed in the tractable nematode host Caenorhabditis elegans. Mutants in innate immunity, in particular the DAF-2/insulin growth factor (IGF) pathway, are shown to contain a microbiome that differs from that of wild-type nematodes. We analyzed the underlying basis of these differences from the perspective of community ecology by comparing experimental observations to the predictions of a neutral sampling model and concluded that fundamental differences in microbiome ecology underlie the observed differences in microbiome composition. We tested this hypothesis by introducing a minor perturbation into the colonization conditions, allowing us to assess stability of communities in different host strains. Our results show that altering host immunity changes the importance of interspecies interactions within the microbiome, resulting in differences in community composition and stability that emerge from these differences in host-microbe ecology.

IMPORTANCE Here, we used a Caenorhabditis elegans microbiome model to demonstrate how genetic differences in innate immunity alter microbiome composition, diversity, and stability by changing the ecological processes that shape these communities. These results provide insight into the role of host genetics in controlling the ecology of the host-associated microbiota, resulting in differences in community composition, successional trajectories, and response to perturbation.

Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources.

Towards a mechanistic understanding of reciprocal drug-microbiome interactions

Broad-spectrum antibiotics target multiple gram-positive and gram-negative bacteria, and can collaterally damage the gut microbiota. Yet, our knowledge of the extent of damage, the antibiotic activity spectra, and the resistance mechanisms of gut microbes is sparse. This limits our ability to mitigate microbiome-facilitated spread of antibiotic resistance. In addition to antibiotics, non-antibiotic drugs affect the human microbiome, as shown by metagenomics as well as in vitro studies. Microbiome-drug interactions are bidirectional, as microbes can also modulate drugs. Chemical modifications of antibiotics mostly function as antimicrobial resistance mechanisms, while metabolism of non-antibiotics can also change the drugs' pharmacodynamic, pharmacokinetic, and toxic properties. Recent studies have started to unravel the extensive capacity of gut microbes to metabolize drugs, the mechanisms, and the relevance of such events for drug treatment. These findings raise the question whether and to which degree these reciprocal drug-microbiome interactions will differ across individuals, and how to take them into account in drug discovery and precision medicine. This review describes recent developments in the field and discusses future study areas that will benefit from systems biology approaches to better understand the mechanistic role of the human gut microbiota in drug actions.

Three-dimensional biofilm colony growth supports a mutualism involving matrix and nutrient sharing

Life in a three-dimensional biofilm is typical for many bacteria, yet little is known about how strains interact in this context. Here, we created essential gene CRISPR interference knockdown libraries in biofilm-forming Bacillus subtilis and measured competitive fitness during colony co-culture with wild type. Partial knockdown of some translation-related genes reduced growth rates and led to out-competition. Media composition led some knockdowns to compete differentially as biofilm versus non-biofilm colonies. Cells depleted for the alanine racemase AlrA died in monoculture but survived in a biofilm colony co-culture via nutrient sharing. Rescue was enhanced in biofilm colony co-culture with a matrix-deficient parent due to a mutualism involving nutrient and matrix sharing. We identified several examples of mutualism involving matrix sharing that occurred in three-dimensional biofilm colonies but not when cultured in two dimensions. Thus, growth in a three-dimensional colony can promote genetic diversity through sharing of secreted factors and may drive evolution of mutualistic behavior.

Ignoring social distancing: advances in understanding multi-species bacterial interactions

Almost every ecosystem on this planet is teeming with microbial communities made of diverse bacterial species. At a reductionist view, many of these bacteria form pairwise interactions, but, as the field of view expands, the neighboring organisms and the abiotic environment can play a crucial role in shaping the interactions between species. Over the years, a strong foundation of knowledge has been built on isolated pairwise interactions between bacteria, but now the field is advancing toward understanding how cohabitating bacteria and natural surroundings affect these interactions. Use of bottom-up approaches, piecing communities together, and top-down approaches that deconstruct communities are providing insight on how different species interact. In this review, we highlight how studies are incorporating more complex communities, mimicking the natural environment, and recurring findings such as the importance of cooperation for stability in harsh environments and the impact of bacteria-induced environmental pH shifts. Additionally, we will discuss how omics are being used as a top-down approach to identify previously unknown interspecies bacterial interactions and the challenges of these types of studies for microbial ecology.

Gut Microbiota and Host Thermoregulation in Response to Ambient Temperature Fluctuations

Ambient temperature (T_a ) is an important factor in shaping phenotypic plasticity. Plasticity is generally beneficial for animals in adapting to their environments. Gut microbiota are crucial in regulating host physiological and behavioral processes. However, whether the gut microbiota play a role in regulating host phenotypic plasticity under the conditions of repeated fluctuations in environmental factors has rarely been examined. We used intermittent T_a acclimations to test the hypothesis that the plasticity of gut microbiota confers on the host a metabolic adaptation to T_a fluctuations. Mongolian gerbils (Meriones unguiculatus) were acclimated to intermittent 5°C to 23°C, 37°C to 23°C or 23°C to 23°C conditions for 3 cycles (totally 3 months). Intermittent T_a acclimations induced variations in resting metabolic rate (RMR), serum thyroid hormones, and core body temperature (T_b ). We further identified that the β-diversity of the microbial community varied with T_a and showed diverse responses during the 3 cycles. Some specific bacteria were more sensitive to T_a and were associated with host dynamic metabolic plasticity during T_a acclimations. In addition, depletion of gut microbiota in antibiotic-treated gerbils impaired metabolic plasticity, particularly at low T_a , whereas supplementation with propionate as an energy resource improved the inhibited thermogenic capacity and increased the survival rate in the cold. These findings demonstrate that both gut microbiota and their host were more adaptive after repeated acclimations, and dynamic gut microbiota and their metabolites may confer host plasticity in thermoregulation in response to T_a fluctuations. It also implies that low T_a is a crucial cue in driving symbiosis between mammals and their gut microbiota during evolution.IMPORTANCE Whether gut microbiota play a role in regulating host phenotypic plasticity in small mammals living in seasonal environments has rarely been examined. The present study, through an intermittent temperature acclimation model, indicates that both gut microbiota and their host were more adaptive after repeated acclimations. It also demonstrates that dynamic gut microbiota confer host plasticity in thermoregulation in response to intermittent temperature fluctuations. Furthermore, low temperature seems to be a crucial cue in driving the symbiosis between mammals and their gut microbiota during evolution.

Weakest-Link Dynamics Predict Apparent Antibiotic Interactions in a Model Cross-Feeding Community

With the growing global threat of antimicrobial resistance, novel strategies are required for combatting resistant pathogens. Combination therapy, in which multiple drugs are used to treat an infection, has proven highly successful in the treatment of cancer and HIV. However, this practice has proven challenging for the treatment of bacterial infections due to difficulties in selecting the correct combinations and dosages. An additional challenge in infection treatment is the polymicrobial nature of many infections, which may respond to antibiotics differently than a monoculture pathogen.

With the growing global threat of antimicrobial resistance, novel strategies are required for combatting resistant pathogens. Combination therapy, in which multiple drugs are used to treat an infection, has proven highly successful in the treatment of cancer and HIV. However, this practice has proven challenging for the treatment of bacterial infections due to difficulties in selecting the correct combinations and dosages. An additional challenge in infection treatment is the polymicrobial nature of many infections, which may respond to antibiotics differently than a monoculture pathogen. This study tests whether patterns of antibiotic interactions (synergy, antagonism, or independence/additivity) in monoculture can be used to predict antibiotic interactions in an obligate cross-feeding coculture. Using our previously described weakest-link hypothesis, we hypothesized antibiotic interactions in coculture based on the interactions we observed in monoculture. We then compared our predictions to observed antibiotic interactions in coculture. We tested the interactions between 10 previously identified antibiotic combinations using checkerboard assays. Although our antibiotic combinations interacted differently than predicted in our monocultures, our monoculture results were generally sufficient to predict coculture patterns based solely on the weakest-link hypothesis. These results suggest that combination therapy for cross-feeding multispecies infections may be successfully designed based on antibiotic interaction patterns for their component species.

Environmental and Physiological Factors Affecting High-Throughput Measurements of Bacterial Growth

Bacterial growth under nutrient-rich and starvation conditions is intrinsically tied to the environmental history and physiological state of the population. While high-throughput technologies have enabled rapid analyses of mutant libraries, technical and biological challenges complicate data collection and interpretation. Here, we present a framework for the execution and analysis of growth measurements with improved accuracy over that of standard approaches. Using this framework, we demonstrate key biological insights that emerge from consideration of culturing conditions and history. We determined that quantification of the background absorbance in each well of a multiwell plate is critical for accurate measurements of maximal growth rate. Using mathematical modeling, we demonstrated that maximal growth rate is dependent on initial cell density, which distorts comparisons across strains with variable lag properties. We established a multiple-passage protocol that alleviates the substantial effects of glycerol on growth in carbon-poor media, and we tracked growth rate-mediated fitness increases observed during a long-term evolution of Escherichia coli in low glucose concentrations. Finally, we showed that growth of Bacillus subtilis in the presence of glycerol induces a long lag in the next passage due to inhibition of a large fraction of the population. Transposon mutagenesis linked this phenotype to the incorporation of glycerol into lipoteichoic acids, revealing a new role for these envelope components in resuming growth after starvation. Together, our investigations underscore the complex physiology of bacteria during bulk passaging and the importance of robust strategies to understand and quantify growth.IMPORTANCE How starved bacteria adapt and multiply under replete nutrient conditions is intimately linked to their history of previous growth, their physiological state, and the surrounding environment. While automated equipment has enabled high-throughput growth measurements, data interpretation and knowledge gaps regarding the determinants of growth kinetics complicate comparisons between strains. Here, we present a framework for growth measurements that improves accuracy and attenuates the effects of growth history. We determined that background absorbance quantification and multiple passaging cycles allow for accurate growth rate measurements even in carbon-poor media, which we used to reveal growth-rate increases during long-term laboratory evolution of Escherichia coli Using mathematical modeling, we showed that maximum growth rate depends on initial cell density. Finally, we demonstrated that growth of Bacillus subtilis with glycerol inhibits the future growth of most of the population, due to lipoteichoic acid synthesis. These studies highlight the challenges of accurate quantification of bacterial growth behaviors.

How gut microbiome interactions affect nutritional traits of Drosophila melanogaster

Most research on the impact of the gut microbiome on animal nutrition is designed to identify the effects of single microbial taxa and single metabolites of microbial origin, without considering the potentially complex network of interactions among co-occurring microorganisms. Here, we investigated how different microbial associations and their fermentation products affect host nutrition, using Drosophila melanogaster colonized with three gut microorganisms (the bacteria Acetobacter fabarum and Lactobacillus brevis, and the yeast Hanseniaspora uvarum) in all seven possible combinations. Some microbial effects on host traits could be attributed to single taxa (e.g. yeast-mediated reduction of insect development time), while other effects were sex specific and driven by among-microbe interactions (e.g. male lipid content determined by interactions between the yeast and both bacteria). Parallel analysis of nutritional indices of microbe-free flies administered different microbial fermentation products (acetic acid, acetoin, ethanol and lactic acid) revealed a single consistent effect: that the lipid content of both male and female flies is reduced by acetic acid. This effect was recapitulated in male flies colonized with both yeast and A. fabarum, but not for any microbial treatment in females or males with other microbial complements. These data suggest that the effect of microbial fermentation products on host nutritional status is strongly context dependent, with respect to both the combination of associated microorganisms and host sex. Taken together, our findings demonstrate that among-microbe interactions can play a critically important role in determining the physiological outcome of host-microbiome interactions in Drosophila and, likely, in other animal hosts.

Higher-Order Interactions Dampen Pairwise Competition in the Zebrafish Gut Microbiome

The microbial communities resident in animal intestines are composed of multiple species that together play important roles in host development, health, and disease. Due to the complexity of these communities and the difficulty of characterizing them in situ, the determinants of microbial composition remain largely unknown. Further, it is unclear for many multispecies consortia whether their species-level makeup can be predicted based on an understanding of pairwise species interactions or whether higher-order interactions are needed to explain emergent compositions. To address this, we examine commensal intestinal microbes in larval zebrafish, initially raised germfree, to allow the introduction of controlled combinations of bacterial species. Using a dissection and plating assay, we demonstrate the construction of communities of one to five bacterial species and show that the outcomes from the two-species competitions fail to predict species abundances in more complex communities. With multiple species present, interbacterial interactions become weaker, suggesting that higher-order interactions in the vertebrate gut stabilize complex communities.IMPORTANCE Understanding the rules governing the composition of the diverse microbial communities that reside in the vertebrate gut environment will enhance our ability to manipulate such communities for therapeutic ends. Synthetic microbial communities, assembled from specific combinations of microbial species in germfree animals, allow investigation of the fundamental question of whether multispecies community composition can be predicted solely based on the combined effects of interactions between pairs of species. If so, such predictability would enable the construction of communities with desired species from the bottom up. If not, the apparent higher-order interactions imply that emergent community-level characteristics are crucial. Our findings using up to five coexisting native bacterial species in larval zebrafish, a model vertebrate, provide experimental evidence for higher-order interactions and, moreover, show that these interactions promote the coexistence of microbial species in the gut.