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.