Mentoring practices that predict doctoral student outcomes in a biological sciences cohort.

Despite the importance of a diversity of backgrounds and perspectives in biological research, women, racial and ethnic minorities, and students from non-traditional academic backgrounds remain underrepresented in the composition of university faculty. Through a study on doctoral students at a research-intensive university, we pinpoint advising from faculty as a critical component of graduate student experiences and productivity. Graduate students from minority backgrounds reported lower levels of support from their advisors and research groups. However, working with an advisor from a similar demographic background substantially improved productivity and well-being of these students. Several other aspects of mentoring practices positively predicted student success and belonging, including frequent one-on-one meetings, empathetic and constructive feedback, and relationships with other peer or faculty mentors. Our study highlights the need to renovate graduate education with a focus on retention-not just recruitment-to best prepare students for success in scientific careers.

Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics.

While numerous health-beneficial interactions between host and microbiota have been identified, there is still a lack of targeted approaches for modulating these interactions. Thus, we here identify precision prebiotics that specifically modulate the abundance of a microbiome member species of interest. In the first step, we show that defining precision prebiotics by compounds that are only taken up by the target species but no other species in a community is usually not possible due to overlapping metabolic niches. Subsequently, we use metabolic modeling to identify precision prebiotics for a two-member Caenorhabditis elegans microbiome community comprising the immune-protective target species Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71. We experimentally confirm four of the predicted precision prebiotics, L-serine, L-threonine, D-mannitol, and γ-aminobutyric acid, to specifically increase the abundance of MYb11. L-serine was further assessed in vivo, leading to an increase in MYb11 abundance also in the worm host. Overall, our findings demonstrate that metabolic modeling is an effective tool for the design of precision prebiotics as an important cornerstone for future microbiome-targeted therapies.IMPORTANCEWhile various mechanisms through which the microbiome influences disease processes in the host have been identified, there are still only few approaches that allow for targeted manipulation of microbiome composition as a first step toward microbiome-based therapies. Here, we propose the concept of precision prebiotics that allow to boost the abundance of already resident health-beneficial microbial species in a microbiome. We present a constraint-based modeling pipeline to predict precision prebiotics for a minimal microbial community in the worm Caenorhabditis elegans comprising the host-beneficial Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71 with the aim to boost the growth of MYb11. Experimentally testing four of the predicted precision prebiotics, we confirm that they are specifically able to increase the abundance of MYb11 in vitro and in vivo. These results demonstrate that constraint-based modeling could be an important tool for the development of targeted microbiome-based therapies against human diseases.

Phyllosphere microbial associations improve plant reproductive success.

The above-ground (phyllosphere) plant microbiome is increasingly recognized as an important component of plant health. We hypothesized that phyllosphere bacterial recruitment may be disrupted in a greenhouse setting, and that adding a bacterial amendment would therefore benefit the health and growth of host plants. Using a newly developed synthetic phyllosphere bacterial microbiome for tomato (Solanum lycopersicum), we tested this hypothesis across multiple trials by manipulating microbial inoculation of leaves and measuring subsequent plant growth and reproductive success, comparing results from plants grown in both greenhouse and field settings. We confirmed that greenhouse-grown plants have a relatively depauperate phyllosphere bacterial microbiome, which both makes them an ideal system for testing the impact of phyllosphere communities on plant health and important targets for microbial amendments as we move towards increased agricultural sustainability. We find that the addition of the synthetic microbial community early in greenhouse growth leads to an increase in fruit production in this setting, implicating the phyllosphere microbiome as a key component of plant fitness and emphasizing the role that these bacterial microbiomes likely play in the ecology and evolution of plant communities.

Within-host adaptation alters priority effects within the tomato phyllosphere microbiome.

To predict the composition and function of ecological communities over time, it is essential to understand how in situ evolution alters priority effects between resident and invading species. Phyllosphere microbial communities are a useful model system to explore priority effects because the system is clearly spatially delineated and can be manipulated experimentally. We conducted an experimental evolution study with tomato plants and the early-colonizing bacterium species Pantoea dispersa, exploring priority effects when P. dispersa was introduced before, simultaneously with or after competitor species. P. dispersa rapidly evolved to invade a new niche within the plant tissue and altered its ecological interactions with other members of the plant microbiome and its effect on the host. Prevailing models have assumed that adaptation primarily improves the efficiency of resident species within their existing niches, yet in our study system, the resident species expanded its niche instead. This finding suggests potential limitations to the application of existing ecological theory to microbial communities.

Metabolic model predictions enable targeted microbiome manipulation through precision prebiotics.

The microbiome is increasingly receiving attention as an important modulator of host health and disease. However, while numerous mechanisms through which the microbiome influences its host have been identified, there is still a lack of approaches that allow to specifically modulate the abundance of individual microbes or microbial functions of interest. Moreover, current approaches for microbiome manipulation such as fecal transfers often entail a non-specific transfer of entire microbial communities with potentially unwanted side effects. To overcome this limitation, we here propose the concept of precision prebiotics that specifically modulate the abundance of a microbiome member species of interest. In a first step, we show that defining precision prebiotics by compounds that are only taken up by the target species but no other species in a community is usually not possible due to overlapping metabolic niches. Subsequently, we present a metabolic modeling network framework that allows us to define precision prebiotics for a two-member C. elegans microbiome model community comprising the immune-protective Pseudomonas lurida MYb11 and the persistent colonizer Ochrobactrum vermis MYb71. Thus, we predicted compounds that specifically boost the abundance of the host-beneficial MYb11, four of which were experimentally validated in vitro (L-serine, L-threonine, D-mannitol, and γ-aminobutyric acid). L-serine was further assessed in vivo, leading to an increase in MYb11 abundance also in the worm host. Overall, our findings demonstrate that constraint-based metabolic modeling is an effective tool for the design of precision prebiotics as an important cornerstone for future microbiome-targeted therapies.

Historical Contingency Drives Compensatory Evolution and Rare Reversal of Phage Resistance.

Bacteria and lytic viruses (phages) engage in highly dynamic coevolutionary interactions over time, yet we have little idea of how transient selection by phages might shape the future evolutionary trajectories of their host populations. To explore this question, we generated genetically diverse phage-resistant mutants of the bacterium Pseudomonas syringae. We subjected the panel of mutants to prolonged experimental evolution in the absence of phages. Some populations re-evolved phage sensitivity, whereas others acquired compensatory mutations that reduced the costs of resistance without altering resistance levels. To ask whether these outcomes were driven by the initial genetic mechanisms of resistance, we next evolved independent replicates of each individual mutant in the absence of phages. We found a strong signature of historical contingency: some mutations were highly reversible across replicate populations, whereas others were highly entrenched. Through whole-genome sequencing of bacteria over time, we also found that populations with the same resistance gene acquired more parallel sets of mutations than populations with different resistance genes, suggesting that compensatory adaptation is also contingent on how resistance initially evolved. Our study identifies an evolutionary ratchet in bacteria-phage coevolution and may explain previous observations that resistance persists over time in some bacterial populations but is lost in others. We add to a growing body of work describing the key role of phages in the ecological and evolutionary dynamics of their host communities. Beyond this specific trait, our study provides a new insight into the genetic architecture of historical contingency, a crucial component of interpreting and predicting evolution.

Mycophagous beetle females do not behave competitively during intrasexual interactions in presence of a fungal resource.

Intrasexual interactions can determine which individuals within a population have access to limited resources. Despite their potential importance on fitness generally and mating success especially, female-female interactions are not often measured in the same species where male-male interactions are well-defined. In this study, we characterized female-female interactions in Bolitotherus cornutus, a mycophagous beetle species native to Northeastern North America. We used dyadic, behavioral assays to determine whether females perform directly aggressive or indirectly exclusionary competitive behaviors. Polypore shelf fungus, an important food and egg-laying resource for B. cornutus females, is patchily distributed and of variable quality, so we tested for competition over fungus as a resource. Behavior of females was assessed in three sets of dyadic trials with randomly paired female partners. Overall, females did not behave aggressively toward their female partner or perform exclusionary behaviors over the fungal resource. None of the behaviors performed by females were individually repeatable. Two scenarios may explain our lack of observed competition: our trial context may not induce competition, or female B. cornutus simply may not behave competitively in the wild. We compare our results to a similar study on male-male interactions in the same species and propose future studies on female-female interactions under different competitive contexts to expand the understanding of female competition.

Water stress and disruption of mycorrhizas induce parallel shifts in phyllosphere microbiome composition.

Water and nutrient acquisition are key drivers of plant health and ecosystem function. These factors impact plant physiology directly as well as indirectly through soil- and root-associated microbial responses, but how they in turn affect aboveground plant-microbe interactions are not known. Through experimental manipulations in the field and growth chamber, we examine the interacting effects of water stress, soil fertility, and arbuscular mycorrhizal fungi on bacterial and fungal communities of the tomato (Solanum lycopersicum) phyllosphere. Both water stress and mycorrhizal disruption reduced leaf bacterial richness, homogenized bacterial community composition among plants, and reduced the relative abundance of dominant fungal taxa. We observed striking parallelism in the individual microbial taxa in the phyllosphere affected by irrigation and mycorrhizal associations. Our results show that soil conditions and belowground interactions can shape aboveground microbial communities, with important potential implications for plant health and sustainable agriculture.

Priority effects in microbiome assembly.

Advances in next-generation sequencing have enabled the widespread measurement of microbiome composition across systems and over the course of microbiome assembly. Despite substantial progress in understanding the deterministic drivers of community composition, the role of historical contingency remains poorly understood. The establishment of new species in a community can depend on the order and/or timing of their arrival, a phenomenon known as a priority effect. Here, we review the mechanisms of priority effects and evidence for their importance in microbial communities inhabiting a range of environments, including the mammalian gut, the plant phyllosphere and rhizosphere, soil, freshwaters and oceans. We describe approaches for the direct testing and prediction of priority effects in complex microbial communities and illustrate these with re-analysis of publicly available plant and animal microbiome datasets. Finally, we discuss the shared principles that emerge across study systems, focusing on eco-evolutionary dynamics and the importance of scale. Overall, we argue that predicting when and how current community state impacts the success of newly arriving microbial taxa is crucial for the management of microbiomes to sustain ecological function and host health. We conclude by discussing outstanding conceptual and practical challenges that are faced when measuring priority effects in microbiomes.

Social affiliation predicts mitochondrial DNA copy number in female rhesus macaques.

In many social mammals, social adversity predicts compromised health and reduced fitness. These effects are thought to be driven in part by chronic social stress, but their molecular underpinnings are not well understood. Recent work suggests that chronic stress can affect mitochondrial copy number, heteroplasmy rates and function. Here, we tested the first two possibilities for the first time in non-human primates. We manipulated dominance rank in captive female rhesus macaques ( n = 45), where low rank induces chronic social stress, and measured mitochondrial DNA (mtDNA) copy number and heteroplasmy in five peripheral blood mononuclear cell types from each study subject. We found no effect of dominance rank on either mtDNA copy number or heteroplasmy rates. However, grooming rate, a measure of affiliative social behaviour predicted by high social status, was positively associated with mtDNA copy number in B cells, cytotoxic T cells and monocytes. Our results suggest that social interactions can influence mtDNA regulation in immune cells. Further, they indicate the importance of considering both affiliative and competitive interactions in investigating this relationship.