Specialized acquisition behaviors maintain reliable environmental transmission in an insect-microbial mutualism.

Understanding how horizontally transmitted mutualisms are maintained is a major focus of symbiosis research.1,2,3,4 Unlike vertical transmission, hosts that rely on horizontal transmission produce symbiont-free offspring that must find and acquire their beneficial microbes from the environment. This transmission strategy is inherently risky since hosts may not obtain the right symbiont every generation. Despite these potential costs, horizontal transmission underlies stable mutualisms involving a large diversity of both plants and animals.5,6,7,8,9 One largely unexplored way horizontal transmission is maintained is for hosts to evolve sophisticated mechanisms to consistently find and acquire specific symbionts from the environment. Here, we examine this possibility in the squash bug Anasa tristis, an insect pest that requires bacterial symbionts in the genus Caballeronia10 for survival and development.11 We conduct a series of behavioral and transmission experiments that track strain-level transmission in vivo among individuals in real-time. We demonstrate that nymphs can accurately find feces from adult bugs in both the presence and absence of those adults. Once nymphs locate the feces, they deploy feeding behavior that results in nearly perfect symbiont acquisition success. We further demonstrate that nymphs can locate and feed on isolated, cultured symbionts in the absence of feces. Finally, we show this acquisition behavior is highly host specific. Taken together, our data describe not only the evolution of a reliable horizontal transmission strategy, but also a potential mechanism that drives patterns of species-specific microbial communities among closely related, sympatric host species.

Interspecies bacterial competition regulates community assembly in the C. elegans intestine.

From insects to mammals, a large variety of animals hold in their intestines complex bacterial communities that play an important role in health and disease. To further our understanding of how intestinal bacterial communities assemble and function, we study the C. elegans microbiota with a bottom-up approach by feeding this nematode with bacterial monocultures as well as mixtures of two to eight bacterial species. We find that bacteria colonizing well in monoculture do not always do well in co-cultures due to interspecies bacterial interactions. Moreover, as community diversity increases, the ability to colonize the worm gut in monoculture becomes less important than interspecies interactions for determining community assembly. To explore the role of host-microbe adaptation, we compare bacteria isolated from C. elegans intestines and non-native isolates, and we find that the success of colonization is determined more by a species' taxonomy than by the isolation source. Lastly, by comparing the assembled microbiotas in two C. elegans mutants, we find that innate immunity via the p38 MAPK pathway decreases bacterial abundances yet has little influence on microbiota composition. These results highlight that bacterial interspecies interactions, more so than host-microbe adaptation or gut environmental filtering, play a dominant role in the assembly of the C. elegans microbiota.

Experimental evolution reveals microbial traits for association with the host gut.

Understanding how microbes adapt to their host is an enduring problem in microbiome ecology, and understanding the microbial traits that allow colonization of the host and increase adaptation to the host environment is of particular interest. In this study, Robinson and colleagues use experimental evolution to demonstrate adaptation of a commensal bacterium to its zebrafish host and describe the changes in phenotype that emerge during this evolutionary process. These results provide insight into the evolutionary problem of host adaptation and demonstrate the utility of simple models for understanding host-microbiome dynamics.

Simple organizing principles in microbial communities.

There is a great deal of interest in discovering the principles that organize microbial communities, to better understand the structure and diversity of these communities in the natural world. Recent conceptual and technical advances have shown how simple organizing principles can give rise to surprising diversity and complex patterns in these consortia. Understanding competition, cooperation, and communication among microbes has provided novel insights into the structure and behavior of microbial collectives, and the use of simple animal models has advanced our understanding of microbial ecology in the host. These multidisciplinary efforts to understand and predict the properties of microbial communities will be critical in the development of microbial ecology as an applied science.

Stochastic assembly produces heterogeneous communities in the Caenorhabditis elegans intestine.

Host-associated bacterial communities vary extensively between individuals, but it can be very difficult to determine the sources of this heterogeneity. Here, we demonstrate that stochastic bacterial community assembly in the Caenorhabditis elegans intestine is sufficient to produce strong interworm heterogeneity in community composition. When worms are fed with two neutrally competing, fluorescently labeled bacterial strains, we observe stochastically driven bimodality in community composition, in which approximately half of the worms are dominated by each bacterial strain. A simple model incorporating stochastic colonization suggests that heterogeneity between worms is driven by the low rate at which bacteria successfully establish new intestinal colonies. We can increase this rate experimentally by feeding worms at high bacterial density; in these conditions, the bimodality disappears. These results demonstrate that demographic noise is a potentially important driver of diversity in bacterial community formation and suggest a role for C. elegans as a model system for ecology of host-associated communities.

Isolated cell behavior drives the evolution of antibiotic resistance.

Bacterial antibiotic resistance is typically quantified by the minimum inhibitory concentration (MIC), which is defined as the minimal concentration of antibiotic that inhibits bacterial growth starting from a standard cell density. However, when antibiotic resistance is mediated by degradation, the collective inactivation of antibiotic by the bacterial population can cause the measured MIC to depend strongly on the initial cell density. In cases where this inoculum effect is strong, the relationship between MIC and bacterial fitness in the antibiotic is not well defined. Here, we demonstrate that the resistance of a single, isolated cell-which we call the single-cell MIC (scMIC)-provides a superior metric for quantifying antibiotic resistance. Unlike the MIC, we find that the scMIC predicts the direction of selection and also specifies the antibiotic concentration at which selection begins to favor new mutants. Understanding the cooperative nature of bacterial growth in antibiotics is therefore essential in predicting the evolution of antibiotic resistance.

Collective antibiotic resistance: mechanisms and implications.

In collective resistance, microbial communities are able to survive antibiotic exposures that would be lethal to individual cells. In this review, we explore recent advances in understanding collective resistance in bacteria. The population dynamics of 'cheating' in a system with cooperative antibiotic inactivation have been described, providing insight into the demographic factors that determine resistance allele frequency in bacteria. Extensive work has elucidated mechanisms underlying collective resistance in biofilms and addressed questions about the role of cooperation in these structures. Additionally, recent investigations of 'bet-hedging' strategies in bacteria have explored the contributions of stochasticity and regulation to bacterial phenotypic heterogeneity and examined the effects of these strategies on community survival.

Salmonella typhimurium intercepts Escherichia coli signaling to enhance antibiotic tolerance.

Bacterial communication plays an important role in many population-based phenotypes and interspecies interactions, including those in host environments. These interspecies interactions may prove critical to some infectious diseases, and it follows that communication between pathogenic bacteria and commensal bacteria is a subject of growing interest. Recent studies have shown that Escherichia coli uses the signaling molecule indole to increase antibiotic tolerance throughout its population. Here, we show that the intestinal pathogen Salmonella typhimurium increases its antibiotic tolerance in response to indole, even though S. typhimurium does not natively produce indole. Increased antibiotic tolerance can be induced in S. typhimurium by both exogenous indole added to clonal S. typhimurium populations and indole produced by E. coli in mixed-microbial communities. Our data show that indole-induced tolerance in S. typhimurium is mediated primarily by the oxidative stress response and, to a lesser extent, by the phage shock response, which were previously shown to mediate indole-induced tolerance in E. coli. Further, we find that indole signaling by E. coli induces S. typhimurium antibiotic tolerance in a Caenorhabditis elegans model for gastrointestinal infection. These results suggest that the intestinal pathogen S. typhimurium can intercept indole signaling from the commensal bacterium E. coli to enhance its antibiotic tolerance in the host intestine.

Knowledge of and attitudes toward organ donation: a survey of medical students in Puerto Rico.

OBJECTIVE: The increasing demand for organ transplants exceeds the organ donation rate. Addressing this discrepancy is challenging for organ procurement agencies and health professionals involved in the care of patients in dire need of organs. Research suggests that health-care professionals' knowledge of, attitudes toward, and behavior in terms of organ donation and transplantation are deciding variables in promoting organ donation. In Puerto Rico, there is a lack of information regarding medical student's knowledge of and/or attitudes toward organ donation, a lack that our study was designed to address. METHODS: Two hundred thirty participants (98 first-year, 45 second-year, and 87 third-year medical students) completed a questionnaire consisting of 55 questions; 10 questions assessed knowledge and 20, attitudes about organ and tissue donation. The remaining questions inquired after demographic information, history of blood donation, and educational experience. RESULTS: In terms of their knowledge about organ donation, the participating students had a mean score of 6.29 on a 10-point scale-with 10 being the highest possible knowledge score-and 45.7% of them scored 7 or more. These data also showed that participants had a positive attitude toward organ donation (44.9; range 14 to 56), with approximately 72% having a favorable view. However, while 40% of the participating students stated their intentions to donate their organs, only 23% of them had donor cards. CONCLUSION: We determined that medical students have a positive attitude towards organ donation. However, a substantial lack of knowledge of organ donation among our subjects is a barrier to their taking the necessary measures to become active donors. Our data highlight the need to incorporate educational programs to increase knowledge and awareness regarding organ donation and the transplantation process.

Wisdom of crowds for robust gene network inference.

Reconstructing gene regulatory networks from high-throughput data is a long-standing challenge. Through the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we performed a comprehensive blind assessment of over 30 network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae and in silico microarray data. We characterize the performance, data requirements and inherent biases of different inference approaches, and we provide guidelines for algorithm application and development. We observed that no single inference method performs optimally across all data sets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse data sets. We thereby constructed high-confidence networks for E. coli and S. aureus, each comprising ~1,700 transcriptional interactions at a precision of ~50%. We experimentally tested 53 previously unobserved regulatory interactions in E. coli, of which 23 (43%) were supported. Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks.

Signaling-mediated bacterial persister formation.

Here we show that bacterial communication through indole signaling induces persistence, a phenomenon in which a subset of an isogenic bacterial population tolerates antibiotic treatment. We monitor indole-induced persister formation using microfluidics and identify the role of oxidative-stress and phage-shock pathways in this phenomenon. We propose a model in which indole signaling 'inoculates' a bacterial subpopulation against antibiotics by activating stress responses, leading to persister formation.