Current gaps and future directions in microbiome ecology research
Given the above considerations, how do we move the field forward? Here we outline some applicable research directions that will generate significant impact, by helping to close some of the most pressing knowledge gaps in the near future.
1. Obtaining a better understanding of the ecological, evolutionary and mechanistic drivers of microbiome community assembly. A key research gap in microbiome ecology is the need for a comprehensive understanding of the drivers of community assembly. While significant progress has been made regarding microbiomes associated with humans and model organisms (e.g., Drosophila or Arabidopsis), further study on non-model animal and plant systems is required. Included within this goal is the investigation of phylosymbiosis – the topological congruence between host phylogenetic distance and the compositional similarity patterns of their associated microbiota (Brown et al., 2023); a pattern that can arise from both ecological and evolutionary processes. Mechanistic studies elucidating the specific processes that govern microbial transmission, colonization, competition and succession will help explain the presence or absence of phylosymbiosis signals across host species or populations, and are more broadly essential for a deeper understanding of microbiome assembly (Coyte et al., 2021). 2. Linking microbiome composition and host genetics. To gain insights into the ability of hosts to select specific microbes that may benefit their health or reproduction, future research should aim to link host-associated microbiome composition and diversity with genes and genomic regions of hosts. This hologenomic approach will enable the identification of host genetic factors, such as immune genes, that are key players in shaping the host microbiome and ultimately the resulting host phenotypes. By integrating both host genome and microbiome data, researchers can make progress at uncovering host-microbiome interactions (Sutherland et al., 2022; West et al., 2023). Incorporation of long-read sequencing and hybrid assembly approaches which utilize both short and long reads now offer exciting opportunities for advancing this research area. 3. Linking microbiomes to host traits and phenotypes. Understanding the connection between host-associated microbiomes and host phenotypes is a related and important research avenue. Investigating the influence of the microbiome on host development, behavior, metabolism, and life-history traits can therefore provide valuable insights (e.g., Bestion et al., 2017; Wood et al., 2022). For example, some nematode species are known to demonstrate extreme phenotypic plasticity in response to environmental cues (e.g. chemical or bacterial stimuli (Hauquier et al., 2017; Sommer et al., 2017), and one open question is whether microbioal taxa play an integral role in initiating such host developmental switch genes (which are themselves under epigenetic control in the case of Pristionchus spp. fig nematodes). By integrating microbiota data with detailed trait measurements of diverse hosts, researchers will be able to identify host phenotypes associated with certain microbiome compositions and start to unravel the underlying mechanisms of how certain microbes can influence the phenotypes of hosts, and vice versa. 4. Exploring microbial functions within host-associated microbiomes. While microbial community composition and diversity have been extensively studied in microbiome ecology, there is a significant need to explore the functional attributes of whole communities, localized populations, and individual microorganisms (genes and pangenomes) within a microbiome. Investigating microbial functions, such as metabolic pathways and molecular interactions between members of the microbiome and with the host, can provide important insights into the contributions of specific microbial taxa/consortia and their functional roles in host and ecosystem health (Béchade et al., 2023; e.g., Hicks et al., 2018; Karmacharya et al., 2019). Furthermore, isolation and culturing of microbial strains can provide complementary information not otherwise accessible through community -omics alone (e.g., physiological profiling of microbial growth rates and chemical/antibiotic sensitivity), while also paving the way for future experimental work using such host-associated microbial isolates. 5. Disentangle the role of the non-bacterial components of the microbiome. Although bacteria have been the primary focus of microbiome ecology research due to their overwhelming abundance, other components such as viruses, fungi, or protists play crucial roles in host-microbe interactions and ecosystem functioning (Jervis et al., 2021; Raghwani et al., 2023). Future investigations that include these non-bacterial components will allow us to more comprehensively understand the dynamics of the microbiome as a whole community, its interaction with hosts, and its role in the ecosystem. 6. Elucidate the role of host-associated microbiomes in wildlife disease and conservation ecology. Understanding the role of microbiomes in biological conservation, such as wildlife disease susceptibility and resistance, is an emerging and timely field of research within microbiome ecology. Investigating the interactions between host genetics, environmental factors and microbial communities can shed light on disease dynamics and the mechanisms through which microbiomes modulate host immune responses in wildlife populations (e.g., Bozzi et al., 2021; Gao et al., 2021; Jervis et al., 2021). Likewise, studies linking environmental microbiomes with land use, habitat fragmentation, and climate change can provide important information on how to address ecosystem challenges in a changing world. 7. Disentangling diet-microbiome associations. Diet is a well-known driver of microbiome composition in hosts, but the mechanisms by which components of the diet promote certain taxa and ultimately influences host health remain unclear. Therefore, the complexity of diet-microbiome associations requires further investigation (Kartzinel et al., 2019). Future research should aim to unravel the specific dietary components that shape microbial communities, how diet diversity is related to microbial diversity, and the mechanisms through which these interactions ultimately influence host health. Longitudinal studies and controlled dietary interventions can provide valuable insights into the specifics of diet-microbiome relationships (Couch et al., 2021). 8. Unravelling microbial interactions within the microbiome.Elucidating the nature of microbial interactions is crucial to understand the dynamics of microbial ecosystems. Patterns of co-occurrence are often used to evaluate microbial interactions (e.g., competition), yet doing so is problematic (see Blanchet et al. (2020)). Interactions are highly scale-dependent, which poses unique challenges for microbial communities with fine spatial structuring (Goberna & Verdú, 2022; Peng et al., 2023). Future experimental and observational studies at relevant scales, with large numbers of samples across time and including robust measures of abundance, will be able to better quantify microbial interactions (Blanchet et al., 2020). Statistical advances utilising generalized Lotka–Volterra models across time-series (Stein et al., 2013), or employing conditional probabilities to more directly capture how taxa relate to each other will also help infer interactions (Blanchet et al., 2020). 9. Determine microbial strain diversity and evolution within hosts. Microbial communities are often highly heterogeneous and different strains of a single microbial species can exhibit significant genetic and functional variability (Anderson & Bisanz, 2023; Goyal et al., 2022). Investigating microbial genetic diversity and the role of horizontal gene transfer are therefore crucial to better understand the adaptive processes and functional implications within a microbiome (Barreto & Gordo, 2023). For example, a shift in Escherichia coli clones was documented in the gut microbiome of ageing mice, and these were characterized by an increase in bacterial mutations targeting stress-response genes (Barreto et al., 2020). Integrating high-resolution genomic techniques with longitudinal and repeated sampling schemes can capture key patterns in temporal variation among microbial communities and significantly improve our understanding of how microbes evolve within individual hosts or specific environments.