Assessing the drivers of gut microbiome composition in wild redfronted lemurs via longitudinal metacommunity analysis

Temporal patterns of gut microbiota in lemurs (Eulemur rubriventer) living in intact and disturbed habitats in a novel sample type

The gut microbiome is a plastic phenotype; gut microbial composition is highly variable across an individual host's lifetime and between host social groups, and this variation has consequences for host health. However, we do not yet fully understand how longitudinal microbial dynamics and their social drivers may be influenced by ecological stressors, such as habitat degradation. Answering these questions is difficult in most wild animal systems, as it requires long-term collections of matched host, microbiome, and environmental trait data. To test if temporal and social influences on microbiome composition differ by the history of human disturbance, we leveraged banked, desiccated fecal samples collected over 5 months in 2004 from two ecologically distinct populations of wild, red-bellied lemurs (Eulemur rubriventer) that are part of a long-term study system. We found that social group explained more variation in microbiome composition than host population membership did, and that temporal variation in common microbial taxa was similar between populations, despite differences in history of human disturbance. Furthermore, we found that social group membership and collection month were both more important than individual lemur identity. Taken together, our results suggest that synchronized environments use can lead to synchronized microbial dynamics over time, even between habitats of varying quality, and that desiccated samples could become a viable approach for studying primate gut microbiota. Our work opens the door for other projects to utilize historic biological sample data sets to answer novel temporal microbiome questions in an ecological context.

Microbiome Dynamics: A Paradigm Shift in Combatting Infectious Diseases

Infectious diseases have long posed a significant threat to global health and require constant innovation in treatment approaches. However, recent groundbreaking research has shed light on a previously overlooked player in the pathogenesis of disease-the human microbiome. This review article addresses the intricate relationship between the microbiome and infectious diseases and unravels its role as a crucial mediator of host-pathogen interactions. We explore the remarkable potential of harnessing this dynamic ecosystem to develop innovative treatment strategies that could revolutionize the management of infectious diseases. By exploring the latest advances and emerging trends, this review aims to provide a new perspective on combating infectious diseases by targeting the microbiome.

Host-gut microbiota interactions during pregnancy

Mammalian pregnancy is characterized by a well-known suite of physiological changes that support fetal growth and development, thereby positively affecting both maternal and offspring fitness. However, mothers also experience trade-offs between current and future maternal reproductive success, and maternal responses to these trade-offs can result in mother-offspring fitness conflicts. Knowledge of the mechanisms through which these trade-offs operate, as well as the contexts in which they operate, is critical for understanding the evolution of reproduction. Historically, hormonal changes during pregnancy have been thought to play a pivotal role in these conflicts since they directly and indirectly influence maternal metabolism, immunity, fetal growth and other aspects of offspring development. However, recent research suggests that gut microbiota may also play an important role. Here, we create a foundation for exploring this role by constructing a mechanistic model linking changes in maternal hormones, immunity and metabolism during pregnancy to changes in the gut microbiota. We posit that marked changes in hormones alter maternal gut microbiome composition and function both directly and indirectly via impacts on the immune system. The gut microbiota then feeds back to influence maternal immunity and metabolism. We posit that these dynamics are likely to be involved in mediating maternal and offspring fitness as well as trade-offs in different aspects of maternal and offspring health and fitness during pregnancy. We also predict that the interactions we describe are likely to vary across populations in response to maternal environments. Moving forward, empirical studies that combine microbial functional data and maternal physiological data with health and fitness outcomes for both mothers and infants will allow us to test the evolutionary and fitness implications of the gestational microbiota, enriching our understanding of the ecology and evolution of reproductive physiology.

Best practice for wildlife gut microbiome research: A comprehensive review of methodology for 16S rRNA gene investigations

Extensive research in well-studied animal models underscores the importance of commensal gastrointestinal (gut) microbes to animal physiology. Gut microbes have been shown to impact dietary digestion, mediate infection, and even modify behavior and cognition. Given the large physiological and pathophysiological contribution microbes provide their host, it is reasonable to assume that the vertebrate gut microbiome may also impact the fitness, health and ecology of wildlife. In accordance with this expectation, an increasing number of investigations have considered the role of the gut microbiome in wildlife ecology, health, and conservation. To help promote the development of this nascent field, we need to dissolve the technical barriers prohibitive to performing wildlife microbiome research. The present review discusses the 16S rRNA gene microbiome research landscape, clarifying best practices in microbiome data generation and analysis, with particular emphasis on unique situations that arise during wildlife investigations. Special consideration is given to topics relevant for microbiome wildlife research from sample collection to molecular techniques for data generation, to data analysis strategies. Our hope is that this article not only calls for greater integration of microbiome analyses into wildlife ecology and health studies but provides researchers with the technical framework needed to successfully conduct such investigations.