Understanding the evolution of interspecies interactions in microbial communities

Impacts of Millipedes on Acari and Collembola Communities-A Microcosm Experiment

Ecosystem engineers influence the structure and function of soil food webs through non-trophic interactions. The activity of large soil animals, such as earthworms, has a significant impact on the soil microarthropod community. However, the influence of millipedes on soil microarthropod communities remains largely unknown. In this microcosm experiment, we examined the effects of adding, removing, and restricting millipede activity on Acari and Collembola communities in litter and soil by conducting two destructive sampling sessions on days 10 and 30, respectively. At the time of the first sampling event (10 d), Acari and Collembola abundance was shown to increase and the alpha diversity went higher in the treatments with millipedes. At the time of the second sampling event (30 d), millipedes significantly reduced the Collembola abundance and alpha diversity. The results were even more pronounced as the millipedes moved through the soil, which caused the collembolans to be more inclined to inhabit the litter, which in turn resulted in the increase in the abundance and diversity of Acari in the soil. The rapid growth of Collembola in the absence of millipedes significantly inhibited the abundance of Acari. The presence of millipedes altered the community structure of Acari and Collembola, leading to a stronger correlation between the two communities. Changes in these communities were driven by the dominant taxa of Acari and Collembola. These findings suggest that millipedes, as key ecosystem engineers, have varying impacts on different soil microarthropods. This study enhances our understanding of biological interactions and offers a theoretical foundation for soil biodiversity conservation.

'Evolutionary poker': an agent-based model of interactome emergence and epistasis tested against Lenski's long-term E. coli experiments

A simple agent-based model is presented that produces results matching the experimental data found by Lenski's group for ≤50,000 generations of Escherichia coli bacteria under continuous selective pressure. Although various mathematical models have been devised previously to model the Lenski data, the present model has advantages in terms of overall simplicity and conceptual accessibility. The model also clearly illustrates a number of features of the evolutionary process that are otherwise not obvious, such as the roles of epistasis and historical contingency in adaptation and why evolution is time irreversible ('Dollo's law'). The reason for this irreversibility is that genomes become increasingly integrated or organized, and this organization becomes a novel selective factor itself, against which future generations must compete. Selection for integrated or synergistic networks, systems or sets of mutations or traits, not for individual mutations, confers the main adaptive advantage. The result is a punctuated form of evolution that follows a logarithmic occurrence probability, in which evolution proceeds very quickly when interactomes begin to form but which slows as interactomes become more robust and the difficulty of integrating new mutations increases. Sufficient parameters exist in the game to suggest not only how equilibrium or stasis is reached but also the conditions in which it will be punctuated, the factors governing the rate at which genomic organization occurs and novel traits appear, and how population size, genome size and gene variability affect these.

Parallel evolution of alternate morphotypes of Chryseobacterium gleum during experimental evolution with Caenorhabditis elegans

Microbial evolution within polymicrobial communities is a complex process. Here, we report within-species diversification within multispecies microbial communities during experimental evolution with the nematode Caenorhabditis elegans. We describe morphological diversity in the target species Chryseobacterium gleum, which developed a novel colony morphotype in a small number of replicate communities. Alternate morphotypes coexisted with original morphotypes in communities, as well as in single-species experiments using evolved isolates. We found that the original and alternate morphotypes differed in motility and in spatial expansion in the presence of C. elegans. This study provides insight into the emergence and maintenance of intraspecies diversity in the context of microbial communities.

Modeling Microbial Community Networks: Methods and Tools for Studying Microbial Interactions

Microbial interactions function as a fundamental unit in complex ecosystems. By characterizing the type of interaction (positive, negative, neutral) occurring in these dynamic systems, one can begin to unravel the role played by the microbial species. Towards this, various methods have been developed to decipher the function of the microbial communities. The current review focuses on the various qualitative and quantitative methods that currently exist to study microbial interactions. Qualitative methods such as co-culturing experiments are visualized using microscopy-based techniques and are combined with data obtained from multi-omics technologies (metagenomics, metabolomics, metatranscriptomics). Quantitative methods include the construction of networks and network inference, computational models, and development of synthetic microbial consortia. These methods provide a valuable clue on various roles played by interacting partners, as well as possible solutions to overcome pathogenic microbes that can cause life-threatening infections in susceptible hosts. Studying the microbial interactions will further our understanding of complex less-studied ecosystems and enable design of effective frameworks for treatment of infectious diseases.

Temporal assembly patterns of microbial communities in three parallel bioreactors treating low-concentration coking wastewater with differing carbon source concentrations

Carbon source is an important factor of biological treatment systems, the effects of which on their temporal community assembly patterns are not sufficiently understood currently. In this study, the temporal dynamics and driving mechanisms of the communities in three parallel bioreactors for low-concentration coking wastewater (CWW) treatment with differing carbon source concentrations (S0 with no glucose addition, S1 with 200 mg/L glucose addition and S2 with 400 mg/L glucose addition) were comprehensively studied. High-throughput sequencing and bioinformatics analyses including network analysis and Infer Community Assembly Mechanisms by Phylogenetic bin-based null model (iCAMP) were used. The communities of three systems showed turnover rates of 0.0029∼0.0034 every 15 days. Network analysis results showed that the S0 network showed higher positive correlation proportion (71.43%) and clustering coefficient (0.33), suggesting that carbon source shortage in S0 promoted interactions and cooperation of microbes. The neutral community model analysis showed that the immigration rate increased from 0.5247 in S0 to 0.6478 in S2. The iCAMP analysis results showed that drift (45.89%) and homogeneous selection (31.68%) dominated in driving the assembly of all the investigated microbial communities. The contribution of homogeneous selection increased with the increase of carbon source concentrations, from 27.92% in S0 to 36.08% in S2. The OTUs participating in aerobic respiration and tricarboxylic acid (TCA) cycle were abundant among the bins mainly affected by deterministic processes, while those related to the metabolism of refractory organic pollutants in CWW such as alkanes, benzenes and phenols were abundant in the bins dominated by stochastic processes.

Modeling interactions of Clostridium cadaveris and Clostridium sporogenes in anaerobic acidogenesis of glucose and peptone

This study focuses on developing a mathematical model to assess interaction among acidogenic bacteria during the anaerobic degradation of two substrates. Clostridium cadaveris and Clostridium sporogenes were cultured in various combinations with glucose and peptone. Parameter estimates are given for both conventional Monod parameters from single substrate-single species cultures and sum kinetics with interaction parameters obtained from dual substrate-single species cultures. The presence of multiple substrates led to both inhibitory and enhancing effects on biodegradation rates for dual substrates compared to single substrate cultures. A new model of interspecies interaction was developed within the framework of Lotka-Volterra incorporating substrate interaction parameters, with a focus on accuracy, realism, simplicity, and biological significance. The model demonstrated competitive interaction for resource sharing and the additional non-linearity parameter eliminated the constraint of the linear relationship between growth rate and population density.

The unique climate shapes distinct life-history traits of abundant bacteria in Tibetan Plateau grassland soil

The unique geographical patterns of the Qinghai-Tibet Plateau have shaped the different climatic characteristics of the Lhasa and Nyang River watersheds. However, our understanding of climate-dependent life history strategies in riparian grasslands is very limited. In this research, we have compared the causes and consequences of variations in the composition of soil abundant and rare bacterial taxa in the Nyang and Lhasa River watersheds. The results showed that the abundant bacteria, rather than the rare bacteria, exhibited distinct life history strategies between the Lhasa and Nyang watersheds that were a consequence of climate patterns. The wetter climate of the Nyang watershed led to a high ratio of r-strategists among the abundant bacteria (Abundant K:r = 0.323), while in the less favourable climate of the Lhasa watershed, K-strategists were more common among the soil abundant bacteria (Abundant K:r = 0.542). The assembly processes of abundant and rare bacteria in the Lhasa region under relatively harsh climatic conditions seemed to be more affected by variable selection than those in the Nyang region. Moreover, abundant bacteria in the Lhasa region developed stronger potentially cooperative relationships and exhibited a stronger metabolic capacity than those in the Nyang region. The 26 different functional genes identified in LS were highly associated with 38 abundant bacterial species. In contrast, the 16 identified functional genes in NY were highly correlated with 16 abundant bacterial species. These results provide new insights into climate-dependent life history strategies of soil bacterial communities with different abundances in riparian grasslands of the Tibetan Plateau. Contrasting the life history strategies of bacterial taxa with different abundances contributes to a better mechanistic knowledge of their impact on ecosystem functioning under current and future effects of global climate change.

The impact of interspecific competition on the genomic evolution of Phaeobacter inhibens and Pseudoalteromonas tunicata during biofilm growth

Interspecific interactions in biofilms have been shown to cause the emergence of community-level properties. To understand the impact of interspecific competition on evolution, we deep-sequenced the dispersal population of mono- and co-culture biofilms of two antagonistic marine bacteria (Phaeobacter inhibens 2.10 and Pseudoalteromononas tunicata D2). Enhanced phenotypic and genomic diversification was observed in the P. tunicata D2 populations under both mono- and co-culture biofilms in comparison to P. inhibens 2.10. The genetic variation was exclusively due to single nucleotide variants and small deletions, and showed high variability between replicates, indicating their random emergence. Interspecific competition exerted an apparent strong positive selection on a subset of P. inhibens 2.10 genes (e.g., luxR, cobC, argH, and sinR) that could facilitate competition, while the P. tunicata D2 population was genetically constrained under competition conditions. In the absence of interspecific competition, the P. tunicata D2 replicate populations displayed high levels of mutations affecting the same genes involved in cell motility and biofilm formation. Our results show that interspecific biofilm competition has a complex impact on genomic diversification, which likely depends on the nature of the competing strains and their ability to generate genetic variants due to their genomic constraints.

From microbiome composition to functional engineering, one step at a time

SUMMARYCommunities of microorganisms (microbiota) are present in all habitats on Earth and are relevant for agriculture, health, and climate. Deciphering the mechanisms that determine microbiota dynamics and functioning within the context of their respective environments or hosts (the microbiomes) is crucially important. However, the sheer taxonomic, metabolic, functional, and spatial complexity of most microbiomes poses substantial challenges to advancing our knowledge of these mechanisms. While nucleic acid sequencing technologies can chart microbiota composition with high precision, we mostly lack information about the functional roles and interactions of each strain present in a given microbiome. This limits our ability to predict microbiome function in natural habitats and, in the case of dysfunction or dysbiosis, to redirect microbiomes onto stable paths. Here, we will discuss a systematic approach (dubbed the N+1/N-1 concept) to enable step-by-step dissection of microbiome assembly and functioning, as well as intervention procedures to introduce or eliminate one particular microbial strain at a time. The N+1/N-1 concept is informed by natural invasion events and selects culturable, genetically accessible microbes with well-annotated genomes to chart their proliferation or decline within defined synthetic and/or complex natural microbiota. This approach enables harnessing classical microbiological and diversity approaches, as well as omics tools and mathematical modeling to decipher the mechanisms underlying N+1/N-1 microbiota outcomes. Application of this concept further provides stepping stones and benchmarks for microbiome structure and function analyses and more complex microbiome intervention strategies.

Soft rot pathogen Dickeya dadantii 3937 produces tailocins resembling the tails of Peduovirus P2

Tailocins are nanomolecular machines with bactericidal activity. They are produced by bacteria to contribute to fitness in mixed communities, and hence, they play a critical role in their ecology in a variety of habitats. Here, we characterized the new tailocin produced by Dickeya dadantii strain 3937, a well-characterized member of plant pathogenic Soft Rot Pectobacteriaceae (SRP). Tailocins induced in D. dadantii were ca. 166 nm long tubes surrounded by contractive sheaths with baseplates having tail fibers at one end. A 22-kb genomic cluster involved in their synthesis and having high homology to the cluster coding for the tail of the Peduovirus P2 was identified. The D. dadantii tailocins, termed dickeyocins P2D1 (phage P2-like dickeyocin 1), were resistant to inactivation by pH (3.5-12), temperature (4-50°C), and elevated osmolarity (NaCl concentration: 0.01-1 M). P2D1 could kill a variety of different Dickeya spp. but not any strain of Pectobacterium spp. tested and were not toxic to Caenorhabditis elegans.

Depth-Dependent Distribution of Prokaryotes in Sediments of the Manganese Crust on Nazimov Guyots of the Magellan Seamounts

Deep ocean polymetallic nodules, rich in cobalt, nickel, and titanium which are commonly used in high-technology and biotechnology applications, are being eyed for green energy transition through deep-sea mining operations. Prokaryotic communities underneath polymetallic nodules could participate in deep-sea biogeochemical cycling, however, are not fully described. To address this gap, we collected sediment cores from Nazimov guyots, where polymetallic nodules exist, to explore the diversity and vertical distribution of prokaryotic communities. Our 16S rRNA amplicon sequencing data, quantitative PCR results, and phylogenetic beta diversity indices showed that prokaryotic diversity in the surficial layers (0-8 cm) was > 4-fold higher compared to deeper horizons (8-26 cm), while heterotrophs dominated in all sediment horizons. Proteobacteria was the most abundant taxon (32-82%) across all sediment depths, followed by Thaumarchaeota (4-37%), Firmicutes (2-18%), and Planctomycetes (1-6%). Depth was the key factor controlling prokaryotic distribution, while heavy metals (e.g., iron, copper, nickel, cobalt, zinc) can also influence significantly the downcore distribution of prokaryotic communities. Analyses of phylogenetic diversity showed that deterministic processes governing prokaryotic assembly in surficial layers, contrasting with stochastic influences in deep layers. This was further supported from the detection of a more complex prokaryotic co-occurrence network in the surficial layer which suggested more diverse prokaryotic communities existed in the surface vs. deeper sediments. This study expands current knowledge on the vertical distribution of benthic prokaryotic diversity in deep sea settings underneath polymetallic nodules, and the results reported might set a baseline for future mining decisions.

Methyl halide transferase-based gas reporters for quantification of filamentous bacteria in microdroplet emulsions

The application of microfluidic techniques in experimental and environmental studies is a rapidly emerging field. Water-in-oil microdroplets can serve readily as controllable micro-vessels for studies that require spatial structure. In many applications, it is useful to monitor cell growth without breaking or disrupting the microdroplets. To this end, optical reporters based on color, fluorescence, or luminescence have been developed. However, optical reporters suffer from limitations when used in microdroplets such as inaccurate readings due to strong background interference or limited sensitivity during early growth stages. In addition, optical detection is typically not amenable to filamentous or biofilm-producing organisms that have significant nonlinear changes in opacity and light scattering during growth. To overcome such limitations, we show that volatile methyl halide gases produced by reporter cells expressing a methyl halide transferase (MHT) can serve as an alternative nonoptical detection approach suitable for microdroplets. In this study, an MHT-labeled Streptomyces venezuelae reporter strain was constructed and characterized. Protocols were established for the encapsulation and incubation of S. venezuelae in microdroplets. We observed the complete life cycle for S. venezuelae including the vegetative expansion of mycelia, mycelial fragmentation, and late-stage sporulation. Methyl bromide (MeBr) production was detected by gas chromatography-mass spectrometry (GC-MS) from S. venezuelae gas reporters incubated in either liquid suspension or microdroplets and used to quantitatively estimate bacterial density. Overall, using MeBr production as a means of quantifying bacterial growth provided a 100- to 1,000-fold increase in sensitivity over optical or fluorescence measurements of a comparable reporter strain expressing fluorescent proteins. IMPORTANCE Quantitative measurement of bacterial growth in microdroplets in situ is desirable but challenging. Current optical reporter systems suffer from limitations when applied to filamentous or biofilm-producing organisms. In this study, we demonstrate that volatile methyl halide gas production can serve as a quantitative nonoptical growth assay for filamentous bacteria encapsulated in microdroplets. We constructed an S. venezuelae gas reporter strain and observed a complete life cycle for encapsulated S. venezuelae in microdroplets, establishing microdroplets as an alternative growth environment for Streptomyces spp. that can provide spatial structure. We detected MeBr production from both liquid suspension and microdroplets with a 100- to 1,000-fold increase in signal-to-noise ratio compared to optical assays. Importantly, we could reliably detect bacteria with densities down to 106 CFU/mL. The combination of quantitative gas reporting and microdroplet systems provides a valuable approach to studying fastidious organisms that require spatial structure such as those found typically in soils.

Synthetic phylogenetically diverse communities promote denitrification and stability

Denitrification is an important process of the global nitrogen cycle as some of its intermediates are environmentally important or related to global warming. However, how the phylogenetic diversity of denitrifying communities affects their denitrification rates and temporal stability remains unclear. Here we selected denitrifiers based on their phylogenetic distance to construct two groups of synthetic denitrifying communities: one closely related (CR) group with all strains from the genus Shewanella and the other distantly related (DR) group with all constituents from different genera. All synthetic denitrifying communities (SDCs) were experimentally evolved for 200 generations. The results showed that high phylogenetic diversity followed by experimental evolution promoted the function and stability of synthetic denitrifying communities. Specifically, the productivity and denitrification rates were significantly (P < 0.05) higher with Paracocus denitrificans as the dominant species (since the 50th generation) in the DR community than those in the CR community. The DR community also showed significantly (t = 7.119, df = 10, P < 0.001) higher stability through overyielding and asynchrony of species fluctuations, and showed more complementarity than the CR group during the experimental evolution. This study has important implications for applying synthetic communities to remediate environmental problems and mitigate greenhouse gas emissions.

Regulated bacterial interaction networks: A mathematical framework to describe competitive growth under inclusion of metabolite cross-feeding

When bacterial species with the same resource preferences share the same growth environment, it is commonly believed that direct competition will arise. A large variety of competition and more general 'interaction' models have been formulated, but what is currently lacking are models that link monoculture growth kinetics and community growth under inclusion of emerging biological interactions, such as metabolite cross-feeding. In order to understand and mathematically describe the nature of potential cross-feeding interactions, we design experiments where two bacterial species Pseudomonas putida and Pseudomonas veronii grow in liquid medium either in mono- or as co-culture in a resource-limited environment. We measure population growth under single substrate competition or with double species-specific substrates (substrate 'indifference'), and starting from varying cell ratios of either species. Using experimental data as input, we first consider a mean-field model of resource-based competition, which captures well the empirically observed growth rates for monocultures, but fails to correctly predict growth rates in co-culture mixtures, in particular for skewed starting species ratios. Based on this, we extend the model by cross-feeding interactions where the consumption of substrate by one consumer produces metabolites that in turn are resources for the other consumer, thus leading to positive feedback in the species system. Two different cross-feeding options were considered, which either lead to constant metabolite cross-feeding, or to a regulated form, where metabolite utilization is activated with rates according to either a threshold or a Hill function, dependent on metabolite concentration. Both mathematical proof and experimental data indicate regulated cross-feeding to be the preferred model to constant metabolite utilization, with best co-culture growth predictions in case of high Hill coefficients, close to binary (on/off) activation states. This suggests that species use the appearing metabolite concentrations only when they are becoming high enough; possibly as a consequence of their lower energetic content than the primary substrate. Metabolite sharing was particularly relevant at unbalanced starting cell ratios, causing the minority partner to proliferate more than expected from the competitive substrate because of metabolite release from the majority partner. This effect thus likely quells immediate substrate competition and may be important in natural communities with typical very skewed relative taxa abundances and slower-growing taxa. In conclusion, the regulated bacterial interaction network correctly describes species substrate growth reactions in mixtures with few kinetic parameters that can be obtained from monoculture growth experiments.

Bioprospecting the Skin Microbiome: Advances in Therapeutics and Personal Care Products

Bioprospecting is the discovery and exploration of biological diversity found within organisms, genetic elements or produced compounds with prospective commercial or therapeutic applications. The human skin is an ecological niche which harbours a rich and compositional diversity microbiome stemming from the multifactorial interactions between the host and microbiota facilitated by exploitable effector compounds. Advances in the understanding of microbial colonisation mechanisms alongside species and strain interactions have revealed a novel chemical and biological understanding which displays applicative potential. Studies elucidating the organismal interfaces and concomitant understanding of the central processes of skin biology have begun to unravel a potential wealth of molecules which can exploited for their proposed functions. A variety of skin-microbiome-derived compounds display prospective therapeutic applications, ranging from antioncogenic agents relevant in skin cancer therapy to treatment strategies for antimicrobial-resistant bacterial and fungal infections. Considerable opportunities have emerged for the translation to personal care products, such as topical agents to mitigate various skin conditions such as acne and eczema. Adjacent compound developments have focused on cosmetic applications such as reducing skin ageing and its associated changes to skin properties and the microbiome. The skin microbiome contains a wealth of prospective compounds with therapeutic and commercial applications; however, considerable work is required for the translation of in vitro findings to relevant in vivo models to ensure translatability.

Metabolic evolution in response to interspecific competition in a eukaryote

Competition drives rapid evolution, which, in turn, alters the trajectory of ecological communities. These eco-evolutionary dynamics are increasingly well-appreciated, but we lack a mechanistic framework for identifying the types of traits that will evolve and their trajectories. Metabolic theory offers explicit predictions for how competition should shape the (co)evolution of metabolism and size, but these are untested, particularly in eukaryotes. We use experimental evolution of a eukaryotic microalga to examine how metabolism, size, and demography coevolve under inter- and intraspecific competition. We find that the focal species evolves in accordance with the predictions of metabolic theory, reducing metabolic costs and maximizing population carrying capacity via changes in cell size. The smaller-evolved cells initially had lower population growth rates, as expected from their hyper-allometric metabolic scaling, but longer-term evolution yielded important departures from theory: we observed improvements in both population growth rate and carrying capacity. The evasion of this trade-off arose due to the rapid evolution of metabolic plasticity. Lineages exposed to competition evolved more labile metabolisms that tracked resource availability more effectively than lineages that were competition-free. That metabolic evolution can occur is unsurprising, but our finding that metabolic plasticity also co-evolves rapidly is new. Metabolic theory provides a powerful theoretical basis for predicting the eco-evolutionary responses to changing resource regimes driven by global change. Metabolic theory needs also to be updated to incorporate the effects of metabolic plasticity on the link between metabolism and demography, as this likely plays an underappreciated role in mediating eco-evolutionary dynamics of competition.

Synthetic Denitrifying Communities Reveal a Positive and Dynamic Biodiversity-Ecosystem Functioning Relationship during Experimental Evolution

Biodiversity is vital for ecosystem functions and services, and many studies have reported positive, negative, or neutral biodiversity-ecosystem functioning (BEF) relationships in plant and animal systems. However, if the BEF relationship exists and how it evolves remains elusive in microbial systems. Here, we selected 12 Shewanella denitrifiers to construct synthetic denitrifying communities (SDCs) with a richness gradient spanning 1 to 12 species, which were subjected to approximately 180 days (with 60 transfers) of experimental evolution with generational changes in community functions continuously tracked. A significant positive correlation was observed between community richness and functions, represented by productivity (biomass) and denitrification rate, however, such a positive correlation was transient, only significant in earlier days (0 to 60) during the evolution experiment (180 days). Also, we found that community functions generally increased throughout the evolution experiment. Furthermore, microbial community functions with lower richness exhibited greater increases than those with higher richness. Biodiversity effect analysis revealed positive BEF relationships largely attributable to complementary effects, which were more pronounced in communities with lower richness than those with higher richness. This study is one of the first studies that advances our understanding of BEF relationships and their evolutionary mechanisms in microbial systems, highlighting the crucial role of evolution in predicting the BEF relationship in microbial systems. IMPORTANCE Despite the consensus that biodiversity supports ecosystem functioning, not all experimental models of macro-organisms support this notion with positive, negative, or neutral biodiversity-ecosystem functioning (BEF) relationships reported. The fast-growing, metabolically versatile, and easy manipulation nature of microbial communities allows us to explore well the BEF relationship and further interrogate if the BEF relationship remains constant during long-term community evolution. Here, we constructed multiple synthetic denitrifying communities (SDCs) by randomly selecting species from a candidate pool of 12 Shewanella denitrifiers. These SDCs differ in species richness, spanning 1 to 12 species, and were monitored continuously for community functional shifts during approximately 180-day parallel cultivation. We demonstrated that the BEF relationship was dynamic with initially (day 0 to 60) greater productivity and denitrification among SDCs of higher richness. However, such pattern was reversed thereafter with greater productivity and denitrification increments in lower-richness SDCs, likely due to a greater accumulation of beneficial mutations during the experimental evolution.

Evolutionary repeatability of emergent properties of ecological communities

Most species belong to ecological communities where their interactions give rise to emergent community-level properties, such as diversity and productivity. Understanding and predicting how these properties change over time has been a major goal in ecology, with important practical implications for sustainability and human health. Less attention has been paid to the fact that community-level properties can also change because member species evolve. Yet, our ability to predict long-term eco-evolutionary dynamics hinges on how repeatably community-level properties change as a result of species evolution. Here, we review studies of evolution of both natural and experimental communities and make the case that community-level properties at least sometimes evolve repeatably. We discuss challenges faced in investigations of evolutionary repeatability. In particular, only a handful of studies enable us to quantify repeatability. We argue that quantifying repeatability at the community level is critical for approaching what we see as three major open questions in the field: (i) Is the observed degree of repeatability surprising? (ii) How is evolutionary repeatability at the community level related to repeatability at the level of traits of member species? (iii) What factors affect repeatability? We outline some theoretical and empirical approaches to addressing these questions. Advances in these directions will not only enrich our basic understanding of evolution and ecology but will also help us predict eco-evolutionary dynamics. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Assessing the importance of interspecific interactions in the evolution of microbial communities

Interspecific interactions play an important role in the establishment of a community phenotype. Furthermore, the evolution of a community can both occur through an independent evolution of the species composing the community and the interactions among them. In this study, we investigated how important the evolution of interspecific interactions was in the evolutionary response of eight two‐bacterial species communities regarding productivity. We found evidence for an evolution of the interactions in half of the studied communities, which gave rise to a mean change of 15% in community productivity as compared to what was expected from the individual responses. Even when the interactions did not evolve themselves, they influenced the evolutionary responses of the bacterial strains within the communities, which further affected community response. We found that evolution within a community often promoted the adaptation of the bacterial strains to the abiotic environment, especially for the dominant strain in a community. Overall, this study suggested that the evolution of the interspecific interactions was frequent and that it could increase community response to evolution.

Phenomenology and dynamics of competitive ecosystems beyond the niche-neutral regimes

Structure, composition, and stability of ecological populations are shaped by the inter- and intraspecies interactions within their communities. It remains to be fully understood how the interplay of these interactions with other factors, such as immigration, controls the structure, the diversity, and the long-term stability of ecological systems in the presence of noise and fluctuations. We address this problem using a minimal model of interacting multispecies ecological communities that incorporates competition, immigration, and demographic noise. We find that a complete phase diagram exhibits rich behavior with multiple regimes that go beyond the classical "niche" and "neutral" regimes, extending and modifying the "rare biosphere" or "niche-like" dichotomy. In particular, we observe regimes that cannot be characterized as either niche or neutral where a multimodal species abundance distribution is observed. We characterize the transitions between the different regimes and show how these arise from the underlying kinetics of the species turnover, extinction, and invasion. Our model serves as a minimal null model of noisy competitive ecological systems, against which more complex models that include factors such as mutations and environmental noise can be compared.

Calibrating spatiotemporal models of microbial communities to microscopy data: A review

Spatiotemporal models that account for heterogeneity within microbial communities rely on single-cell data for calibration and validation. Such data, commonly collected via microscopy and flow cytometry, have been made more accessible by recent advances in microfluidics platforms and data processing pipelines. However, validating models against such data poses significant challenges. Validation practices vary widely between modelling studies; systematic and rigorous methods have not been widely adopted. Similar challenges are faced by the (macrobial) ecology community, in which systematic calibration approaches are often employed to improve quantitative predictions from computational models. Here, we review single-cell observation techniques that are being applied to study microbial communities and the calibration strategies that are being employed for accompanying spatiotemporal models. To facilitate future calibration efforts, we have compiled a list of summary statistics relevant for quantifying spatiotemporal patterns in microbial communities. Finally, we highlight some recently developed techniques that hold promise for improved model calibration, including algorithmic guidance of summary statistic selection and machine learning approaches for efficient model simulation.

The hiatus between organism and machine evolution: Contrasting mixed microbial communities with robots

Mixed microbial communities, usually composed of various bacterial and fungal species, are fundamental in a plethora of environments, from soil to human gut and skin. Their evolution is a paradigmatic example of intertwined dynamics, where not just the relations among species plays a role, but also the opportunities - and possible harms - that each species presents to the others. These opportunities are in fact affordances, which can be seized by heritable variations and selection. In this paper, starting from a systemic viewpoint of mixed microbial communities, we focus on the pivotal role of affordances in evolution and we contrast it to the artificial evolution of programs and robots. We maintain that the two realms are neatly separated, in that natural evolution proceeds by extending the space of its possibilities in a completely open way, while the latter is inherently limited by the algorithmic framework in which it is defined. This discrepancy characterizes also an envisioned setting in which robots evolve in the physical world. We present arguments supporting our claim and we propose an experimental setting for assessing our statements. Rather than just discussing the limitations of the artificial evolution of machines, the aim of this contribution is to emphasize the tremendous potential of the evolution of the biosphere, beautifully represented by the evolution of communities of microbes.

Ecological modelling approaches for predicting emergent properties in microbial communities

Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems of which they are a part. Emergent properties-patterns or functions that cannot be deduced linearly from the properties of the constituent parts-underlie important ecological characteristics such as resilience, niche expansion and spatial self-organization. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages and limitations of Lotka-Volterra, consumer-resource, trait-based, individual-based and genome-scale metabolic models. Future efforts in this research area would benefit from capitalizing on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems.

Species interactions constrain adaptation and preserve ecological stability in an experimental microbial community

Species loss within a microbial community can increase resource availability and spur adaptive evolution. Environmental shifts that cause species loss or fluctuations in community composition are expected to become more common, so it is important to understand the evolutionary forces that shape the stability and function of the emergent community. Here we study experimental cultures of a simple, ecologically stable community of Saccharomyces cerevisiae and Lactobacillus plantarum, in order to understand how the presence or absence of a species impacts coexistence over evolutionary timescales. We found that evolution in coculture led to drastically altered evolutionary outcomes for L. plantarum, but not S. cerevisiae. Both monoculture- and co-culture-evolved L. plantarum evolved dozens of mutations over 925 generations of evolution, but only L. plantarum that had evolved in isolation from S. cerevisiae lost the capacity to coexist with S. cerevisiae. We find that the evolutionary loss of ecological stability corresponds with fitness differences between monoculture-evolved L. plantarum and S. cerevisiae and genetic changes that repeatedly evolve across the replicate populations of L. plantarum. This work shows how coevolution within a community can prevent destabilising evolution in individual species, thereby preserving ecological diversity and stability, despite rapid adaptation.

Eutrophication dangers the ecological status of coastal wetlands: A quantitative assessment by composite microbial index of biotic integrity

The intertidal wetland ecosystem is vulnerable to environmental and anthropogenic stressors. Understanding how the ecological statuses of intertidal wetlands respond to influencing factors is crucial for the management and protection of intertidal wetland ecosystems. In this study, the community characteristics of bacteria, archaea and microeukaryote from Jiangsu coast areas (JCA), the longest muddy intertidal wetlands in the world, were detected to develop a composite microbial index of biotic integrity (CM-IBI) and to explore the influence mechanisms of stresses on the intertidal wetland ecological status. A total of 12 bacterial, archaea and microeukaryotic metrics were determined by range, responsiveness and redundancy tests for the development of ba-IBI, ar-IBI and eu-IBI. The CM-IBI was further developed via three sub-IBIs with weight coefficients 0.40, 0.33 and 0.27, respectively. The CM-IBI (R² = 0.58) exhibited the highest goodness of fit with the CEI, followed by ba-IBI (R² = 0.36), ar-IBI (R² = 0.25) and eu-IBI (R² = 0.21). Redundancy and random forest analyses revealed inorganic nitrogen (inorgN), total phosphorus (TP) and total organic carbon (TOC) to be key environmental variables influencing community compositions. A conditional reasoning tree model indicated the close associating between the ecological status and eutrophication conditions. The majority of sites with water inorgN<0.67 mg/L exhibited good statuses, while the poor ecological status was observed for inorgN>0.67 mg/L and TP > 0.11 mg/L. Microbial networks demonstrated the interactions of microbial taxonomic units among three kingdoms decreases with the ecological degradation, suggesting a reduced reliability and stability of microbial communities. Multi-level path analysis revealed fishery aquaculture and industrial development as the dominant anthropogenic activities effecting the eutrophication and ecological degradation of the JCA tidal wetlands. This study developed an efficient ecological assessment method of tidal wetlands based on microbial communities, and determined the influence of human activities and eutrophication on ecological status, providing guidance for management standards and coastal development.

Synthetic biology for the engineering of complex wine yeast communities

Wine fermentation is a representation of complex higher-order microbial interactions. Despite the beneficial properties that these communities bring to wine, their complexity poses challenges in predicting the nature and outcome of fermentation. Technological developments in synthetic biology enable the potential to engineer synthetic microbial communities for new purposes. Here we present the challenges and applications of engineered yeast communities in the context of a wine fermentation vessel, how this represents a model system to enable novel solutions for winemaking and introduce the concept of a 'synthetic' terroir. Furthermore, we introduce our vision for the application of control engineering.

Bacterial, archaeal, and fungal community structure and interrelationships of deep-sea shrimp intestine and the surrounding sediment

Invertebrate shrimp are one of the dominant benthic macrofaunae in the deep-sea environment. The microbiota of shrimp intestine can contribute to the adaptation of their host. The impact of surrounding sediment on intestinal microbiota has been observed in cultured shrimp species, but needs to be further investigated in deep-sea shrimp. The characterization of bacterial, archaeal, and fungal community structure and their interrelationships is also limited. In this study, wild-type deep-sea shrimp and the surrounding sediment were sampled. Shrimp individuals incubated in a sediment-absent environment were also used in this study. Microbial community structure of the shrimp intestine and sediment was investigated through amplicon sequencing targeting bacterial 16S rRNA genes, archaeal 16S rRNA genes, and fungal ITS genes. The results demonstrate distinct differences in community structure between shrimp intestine and the surrounding sediment and between surface and deep (5 mbsf) sediment. The composition of the intestinal microbiota in shrimp living without sediment was different from that of wild-type shrimp, indicating that the presence or absence of sediment could influence the shrimp intestinal microbiota. Carbohydrate metabolism, energy metabolism (carbon fixation, methane metabolism, nitrogen metabolism, and sulfur metabolism), amino acid metabolism, and xenobiotic biodegradation were the most commonly predicted microbial functionalities and they interacted closely with one another. Overall, this study provided comprehensive insights into bacterial, archaeal, and fungal community structure of deep-sea shrimp intestine as well as potential ecological interactions with the surrounding sediment. This study could update our understanding of the microbiota characteristics in shrimp and sediment in deep-sea ecosystems.

Understanding Interaction Patterns within Deep-Sea Microbial Communities and Their Potential Applications

Environmental microbes living in communities engage in complex interspecies interactions that are challenging to decipher. Nevertheless, the interactions provide the basis for shaping community structure and functioning, which is crucial for ecosystem service. In addition, microbial interactions facilitate specific adaptation and ecological evolution processes particularly essential for microbial communities dwelling in resource-limiting habitats, such as the deep oceans. Recent technological and knowledge advancements provide an opportunity for the study of interactions within complex microbial communities, such as those inhabiting deep-sea waters and sediments. The microbial interaction studies provide insights into developing new strategies for biotechnical applications. For example, cooperative microbial interactions drive the degradation of complex organic matter such as chitins and celluloses. Such microbiologically-driven biogeochemical processes stimulate creative designs in many applied sciences. Understanding the interaction processes and mechanisms provides the basis for the development of synthetic communities and consequently the achievement of specific community functions. Microbial community engineering has many application potentials, including the production of novel antibiotics, biofuels, and other valuable chemicals and biomaterials. It can also be developed into biotechniques for waste processing and environmental contaminant bioremediation. This review summarizes our current understanding of the microbial interaction mechanisms and emerging techniques for inferring interactions in deep-sea microbial communities, aiding in future biotechnological and therapeutic applications.

Nutrient supply controls the linkage between species abundance and ecological interactions in marine bacterial communities

Nutrient scarcity is pervasive for natural microbial communities, affecting species reproduction and co-existence. However, it remains unclear whether there are general rules of how microbial species abundances are shaped by biotic and abiotic factors. Here we show that the ribosomal RNA gene operon (rrn) copy number, a genomic trait related to bacterial growth rate and nutrient demand, decreases from the abundant to the rare biosphere in the nutrient-rich coastal sediment but exhibits the opposite pattern in the nutrient-scarce pelagic zone of the global ocean. Both patterns are underlain by positive correlations between community-level rrn copy number and nutrients. Furthermore, inter-species co-exclusion inferred by negative network associations is observed more in coastal sediment than in ocean water samples. Nutrient manipulation experiments yield effects of nutrient availability on rrn copy numbers and network associations that are consistent with our field observations. Based on these results, we propose a “hunger games” hypothesis to define microbial species abundance rules using the rrn copy number, ecological interaction, and nutrient availability.

Environmental and biotic factors control ecological communities. Here, the authors study community ribosomal rRNA gene copy number in coastal sediment and ocean bacterial communities, and in microcosm nutrient addition experiments, to propose a conceptual framework of how nutrient supply and ecological interactions shape the community.

Higher-order effects, continuous species interactions, and trait evolution shape microbial spatial dynamics

Persistently diverse microbial communities are one of biology’s great puzzles. Using a modeling framework that accommodates high mutation rates and a continuum of species traits, we studied microbial communities in which antagonistic interactions occur via the production of, inhibition of, and vulnerability to toxins (e.g., antibiotics). Mutation size and mobility enhanced microbial diversity and temporal persistence to extraordinarily high levels. These findings—including the discovery that the duration of the transient phase in community assembly provides a guide to equilibrial diversity—highlight the potentially critical role that antagonistic interactions play in promoting the diversity of bacterial systems. Such interactions, together with resource-driven interactions and spatial structure, may drive the enigmatic levels of biodiversity seen in microbial systems.

The assembly and maintenance of microbial diversity in natural communities, despite the abundance of toxin-based antagonistic interactions, presents major challenges for biological understanding. A common framework for investigating such antagonistic interactions involves cyclic dominance games with pairwise interactions. The incorporation of higher-order interactions in such models permits increased levels of microbial diversity, especially in communities in which antibiotic-producing, sensitive, and resistant strains coexist. However, most such models involve a small number of discrete species, assume a notion of pure cyclic dominance, and focus on low mutation rate regimes, none of which well represent the highly interlinked, quickly evolving, and continuous nature of microbial phenotypic space. Here, we present an alternative vision of spatial dynamics for microbial communities based on antagonistic interactions—one in which a large number of species interact in continuous phenotypic space, are capable of rapid mutation, and engage in both direct and higher-order interactions mediated by production of and resistance to antibiotics. Focusing on toxin production, vulnerability, and inhibition among species, we observe highly divergent patterns of diversity and spatial community dynamics. We find that species interaction constraints (rather than mobility) best predict spatiotemporal disturbance regimes, whereas community formation time, mobility, and mutation size best explain patterns of diversity. We also report an intriguing relationship among community formation time, spatial disturbance regimes, and diversity dynamics. This relationship, which suggests that both higher-order interactions and rapid evolution are critical for the origin and maintenance of microbial diversity, has broad-ranging links to the maintenance of diversity in other systems.

Transcriptome Profiling of 'Candidatus Liberibacter asiaticus' in Citrus and Psyllids

'Candidatus Liberibacter asiaticus' (Las) is an emergent bacterial pathogen that is associated with the devastating citrus huanglongbing (HLB). Vectored by the Asian citrus psyllid, Las colonizes the phloem tissue of citrus, causing severe damage to infected trees. So far, cultivating pure Las culture in axenic media has not been successful, and dual-transcriptome analyses aiming to profile gene expression in both Las and its hosts have a low coverage of the Las genome because of the low abundance of bacterial RNA in total RNA extracts from infected tissues. Therefore, a lack of understanding of the Las transcriptome remains a significant knowledge gap. Here, we used a bacterial cell enrichment procedure and confidently determined the expression profiles of approximately 84% of the Las genes. Genes that exhibited high expression in citrus include transporters, ferritin, outer membrane porins, specific pilins, and genes involved in phage-related functions, cell wall modification, and stress responses. We also found 106 genes to be differentially expressed in citrus versus Asian citrus psyllids. Genes related to transcription or translation and resilience to host defense response were upregulated in citrus, whereas genes involved in energy generation and the flagella system were expressed to higher levels in psyllids. Finally, we determined the relative expression levels of potential Sec-dependent effectors, which are considered as key virulence factors of Las. This work advances our understanding of HLB biology and offers novel insight into the interactions of Las with its plant host and insect vector.

Interactions among Escovopsis, Antagonistic Microfungi Associated with the Fungus-Growing Ant Symbiosis

Fungi in the genus Escovopsis (Ascomycota: Hypocreales) are prevalent associates of the complex symbiosis between fungus-growing ants (Tribe Attini), the ants' cultivated basidiomycete fungi and a consortium of both beneficial and harmful microbes found within the ants' garden communities. Some Escovopsis spp. have been shown to attack the ants' cultivated fungi, and co-infections by multiple Escovopsis spp. are common in gardens in nature. Yet, little is known about how Escovopsis strains impact each other. Since microbe-microbe interactions play a central role in microbial ecology and evolution, we conducted experiments to assay the types of interactions that govern Escovopsis-Escovopsis relationships. We isolated Escovopsis strains from the gardens of 10 attine ant genera representing basal (lower) and derived groups in the attine ant phylogeny. We conducted in vitro experiments to determine the outcome of both intraclonal and interclonal Escovopsis confrontations. When paired with self (intraclonal interactions), Escovopsis isolated from lower attine colonies exhibited antagonistic (inhibitory) responses, while strains isolated from derived attine colonies exhibited neutral or mutualistic interactions, leading to a clear phylogenetic pattern of interaction outcome. Interclonal interactions were more varied, exhibiting less phylogenetic signal. These results can serve as the basis for future studies on the costs and benefits of Escovopsis coinfection, and on the genetic and chemical mechanisms that regulate the compatibility and incompatibility observed here.

Combining Culture-Dependent and Independent Approaches for the Optimization of Epoxiconazole and Fludioxonil-Degrading Bacterial Consortia

Epoxiconazole (EPO) and fludioxonil (FLU) are two widely used fluorinated pesticides known to be highly persistent and with high ecotoxicological potential, turning them into pollutants of concern. This work aimed to optimize two degrading bacterial consortia, previously obtained from an agricultural soil through enrichment with EPO and FLU, by characterizing the contribution of their corresponding bacterial isolates to the biodegradation of these pesticides using both culture-dependent and independent methodologies. Results showed that a co-culture of the strains Hydrogenophaga eletricum 5AE and Methylobacillus sp. 8AE was the most efficient in biodegrading EPO, being able to defluorinate ca. 80% of this pesticide in 28 days. This catabolic performance is likely the result of a commensalistic cooperation, in which H. eletricum may be the defluorinating strain and Methylobacillus sp. may assume an accessory, yet pivotal, catabolic role. Furthermore, 16S rRNA metabarcoding analysis revealed that these strains represent a minority in their original consortium, showing that the biodegradation of EPO can be driven by less abundant phylotypes in the community. On the other hand, none of the tested combinations of bacterial strains showed potential to biodegrade FLU, indicating that the key degrading strains were not successfully isolated from the original enrichment culture. Overall, this work shows, for the first time, the direct involvement of two bacterial species, namely H. eletricum and Methylobacillus sp., in the biodegradation of EPO, while also offering insight on how they might cooperate to accomplish this process. Moreover, the importance of adequate culture-dependent approaches in the engineering of microbial consortia for bioremediation purposes is also emphasized.

Contribution of single-cell omics to microbial ecology

Micro-organisms play key roles in various ecosystems, but many of their functions and interactions remain undefined. To investigate the ecological relevance of microbial communities, new molecular tools are being developed. Among them, single-cell omics assessing genetic diversity at the population and community levels and linking each individual cell to its functions is gaining interest in microbial ecology. By giving access to a wider range of ecological scales (from individual to community) than culture-based approaches and meta-omics, single-cell omics can contribute not only to micro-organisms' genomic and functional identification but also to the testing of concepts in ecology. Here, we discuss the contribution of single-cell omics to possible breakthroughs in concepts and knowledge on microbial ecosystems and ecoevolutionary processes.

Leveraging Experimental Strategies to Capture Different Dimensions of Microbial Interactions

Microorganisms are a fundamental part of virtually every ecosystem on earth. Understanding how collectively they interact, assemble, and function as communities has become a prevalent topic both in fundamental and applied research. Owing to multiple advances in technology, answering questions at the microbial system or network level is now within our grasp. To map and characterize microbial interaction networks, numerous computational approaches have been developed; however, experimentally validating microbial interactions is no trivial task. Microbial interactions are context-dependent, and their complex nature can result in an array of outcomes, not only in terms of fitness or growth, but also in other relevant functions and phenotypes. Thus, approaches to experimentally capture microbial interactions involve a combination of culture methods and phenotypic or functional characterization methods. Here, through our perspective of food microbiologists, we highlight the breadth of innovative and promising experimental strategies for their potential to capture the different dimensions of microbial interactions and their high-throughput application to answer the question; are microbial interaction patterns or network architecture similar along different contextual scales? We further discuss the experimental approaches used to build various types of networks and study their architecture in the context of cell biology and how they translate at the level of microbial ecosystem.

Genetic variation is associated with differences in facilitative and competitive interactions in the Rhizobium leguminosarum species complex

Competitive and facilitative interactions influence bacterial community composition, diversity and functioning. However, the role of genetic diversity for determining interactions between coexisting strains of the same, or closely related, species remains poorly understood. Here, we investigated the type (facilitative/inhibitory) and potential underlying mechanisms of pairwise interactions between 24 genetically diverse bacterial strains belonging to three genospecies (gsA,C,E) of the Rhizobium leguminosarum species complex. Interactions were determined indirectly, based on secreted compounds in cell-free supernatants, and directly, as growth inhibition in cocultures. We found supernatants mediated both facilitative and inhibitory interactions that varied greatly between strains and genospecies. Overall, gsE strains indirectly suppressed growth of gsA strains, while their own growth was facilitated by other genospecies' supernatants. Similar genospecies-level patterns were observed in direct competition, where gsA showed the highest susceptibility and gsE the highest inhibition capacity. At the genetic level, increased gsA susceptibility was associated with a non-random distribution of quorum sensing and secondary metabolite genes across genospecies. Together, our results suggest that genetic variation is associated with facilitative and competitive interactions, which could be important ecological mechanisms explaining R. leguminosarum diversity.

Towards an ecosystem model of infectious disease

Increasingly intimate associations between human society and the natural environment are driving the emergence of novel pathogens, with devastating consequences for humans and animals alike. Prior to emergence, these pathogens exist within complex ecological systems that are characterized by trophic interactions between parasites, their hosts and the environment. Predicting how disturbance to these ecological systems places people and animals at risk from emerging pathogens-and the best ways to manage this-remains a significant challenge. Predictive systems ecology models are powerful tools for the reconstruction of ecosystem function but have yet to be considered for modelling infectious disease. Part of this stems from a mistaken tendency to forget about the role that pathogens play in structuring the abundance and interactions of the free-living species favoured by systems ecologists. Here, we explore how developing and applying these more complete systems ecology models at a landscape scale would greatly enhance our understanding of the reciprocal interactions between parasites, pathogens and the environment, placing zoonoses in an ecological context, while identifying key variables and simplifying assumptions that underly pathogen host switching and animal-to-human spillover risk. As well as transforming our understanding of disease ecology, this would also allow us to better direct resources in preparation for future pandemics.

Intraspecies heterogeneity in microbial interactions

Microbial interactions are increasingly recognized as an integral part of microbial physiology. Cell-cell communication mediated by quorum sensing and metabolite exchange is a formative element of microbial interactions. However, loss-of-function mutations in quorum-sensing components are common across diverse species. Furthermore, quorum sensing is modulated by small molecules and environmental conditions that may be altered in the presence of other microbial species. Recent evidence highlights how strain heterogeneity impacts microbial interactions. There is great potential for microbial interactions to act as selective pressures that influence the emergence of common mutations in quorum-sensing genes across the bacterial and fungal domains.

Community composition of microbial microcosms follows simple assembly rules at evolutionary timescales

Managing and engineering microbial communities relies on the ability to predict their composition. While progress has been made on predicting compositions on short, ecological timescales, there is still little work aimed at predicting compositions on evolutionary timescales. Therefore, it is still unknown for how long communities typically remain stable after reaching ecological equilibrium, and how repeatable and predictable are changes when they occur. Here, we address this knowledge gap by tracking the composition of 87 two- and three-species bacterial communities, with 3-18 replicates each, for ~400 generations. We find that community composition typically changed during evolution, but that the composition of replicate communities remained similar. Furthermore, these changes were predictable in a bottom-up approach-changes in the composition of trios were consistent with those that occurred in pairs during coevolution. Our results demonstrate that simple assembly rules can hold even on evolutionary timescales, suggesting it may be possible to forecast the evolution of microbial communities.

Vertical diversity and association pattern of total, abundant and rare microbial communities in deep-sea sediments

Microbial abundance and community composition in marine sediments have been widely explored. However, high‐resolution vertical changes of benthic microbial diversity and co‐occurrence patterns are poorly described. The ecological contributions of abundant and rare species in sediments also remain largely unknown. Here, by analysing microbial populations at 14 depth layers of 10 subseafloor sediment cores (water depth 1,250–3,530 m) obtained in the South China Sea, we provided the vertical profiles of microbial β‐diversity and co‐occurrence influenced by subcommunities of different abundance. These 134 sediment samples were clustered into four groups according to sediment depth (1–2, 6–10, 30–90 and 190–790 cm) with obvious shifts in microbial community compositions. The vertical succession of microorganisms was consistent with redox zonation and influenced by terrestrial inputs. Partitioning of vertical β‐diversity showed extremely high species replacement between deep layers and the surface layer, indicating selection‐induced loss of rare species and dispersal of dormant cells and spores. By contrast, for horizontal β‐diversity, richness of rare species became increasingly significant in deep sediments. Accompanying this β‐diversity profile were clear changes in the association pattern, with microorganisms being less connected in deeper sediment layers, probably reflecting reduced syntrophic interactions. Rare species accounted for an indispensable proportion in the co‐occurrence network, and tended to form complex “small worlds.” The rare subcommunity also responded differently to various environmental factors compared with the abundant subcommunity. Our findings expand current knowledge on vertical changes of marine benthic microbial diversity and their association patterns, emphasizing the potential roles of rare species.

Experimental Evolution in Plant-Microbe Systems: A Tool for Deciphering the Functioning and Evolution of Plant-Associated Microbial Communities

In natural environments, microbial communities must constantly adapt to stressful environmental conditions. The genetic and phenotypic mechanisms underlying the adaptive response of microbial communities to new (and often complex) environments can be tackled with a combination of experimental evolution and next generation sequencing. This combination allows to analyse the real-time evolution of microbial populations in response to imposed environmental factors or during the interaction with a host, by screening for phenotypic and genotypic changes over a multitude of identical experimental cycles. Experimental evolution (EE) coupled with comparative genomics has indeed facilitated the monitoring of bacterial genetic evolution and the understanding of adaptive evolution processes. Basically, EE studies had long been done on single strains, allowing to reveal the dynamics and genetic targets of natural selection and to uncover the correlation between genetic and phenotypic adaptive changes. However, species are always evolving in relation with other species and have to adapt not only to the environment itself but also to the biotic environment dynamically shaped by the other species. Nowadays, there is a growing interest to apply EE on microbial communities evolving under natural environments. In this paper, we provide a non-exhaustive review of microbial EE studies done with systems of increasing complexity (from single species, to synthetic communities and natural communities) and with a particular focus on studies between plants and plant-associated microorganisms. We highlight some of the mechanisms controlling the functioning of microbial species and their adaptive responses to environment changes and emphasize the importance of considering bacterial communities and complex environments in EE studies.

The ecology of wine fermentation: a model for the study of complex microbial ecosystems

The general interest in microbial ecology has skyrocketed over the past decade, driven by technical advances and by the rapidly increasing appreciation of the fundamental services that these ecosystems provide. In biotechnology, ecosystems have many more functionalities than single species, and, if properly understood and harnessed, will be able to deliver better outcomes for almost all imaginable applications. However, the complexity of microbial ecosystems and of the interactions between species has limited their applicability. In research, next generation sequencing allows accurate mapping of the microbiomes that characterise ecosystems of biotechnological and/or medical relevance. But the gap between mapping and understanding, to be filled by "functional microbiomics", requires the collection and integration of many different layers of complex data sets, from molecular multi-omics to spatial imaging technologies to online ecosystem monitoring tools. Holistically, studying the complexity of most microbial ecosystems, consisting of hundreds of species in specific spatial arrangements, is beyond our current technical capabilities, and simpler model systems with fewer species and reduced spatial complexity are required to establish the fundamental rules of ecosystem functioning. One such ecosystem, the ecosystem responsible for natural alcoholic fermentation, can provide an excellent tool to study evolutionarily relevant interactions between multiple species within a relatively easily controlled environment. This review will critically evaluate the approaches that are currently implemented to dissect the cellular and molecular networks that govern this ecosystem. KEY POINTS: • Evolutionarily isolated fermentation ecosystem can be used as an ecological model. • Experimental toolbox is gearing towards mechanistic understanding of this ecosystem. • Integration of multidisciplinary datasets is key to predictive understanding.

Ecology and evolution of antimicrobial resistance in bacterial communities

Accumulating evidence suggests that the response of bacteria to antibiotics is significantly affected by the presence of other interacting microbes. These interactions are not typically accounted for when determining pathogen sensitivity to antibiotics. In this perspective, we argue that resistance and evolutionary responses to antibiotic treatments should not be considered only a trait of an individual bacteria species but also an emergent property of the microbial community in which pathogens are embedded. We outline how interspecies interactions can affect the responses of individual species and communities to antibiotic treatment, and how these responses could affect the strength of selection, potentially changing the trajectory of resistance evolution. Finally, we identify key areas of future research which will allow for a more complete understanding of antibiotic resistance in bacterial communities. We emphasise that acknowledging the ecological context, i.e. the interactions that occur between pathogens and within communities, could help the development of more efficient and effective antibiotic treatments.

The Interconnected Health Initiative: A Smithsonian Framework to Extend One Health Research and Education

To better tackle diseases and sustain healthy ecosystems, One Health programs must efficiently bridge health in humans, domestic/livestock species, wild animals and plants, agriculture/aquaculture, and the environment. The Smithsonian Institution proposes to address this by considering ‘health' in a broad sense – the absence of undue pathogens and unnecessary stress for any organisms as well as access to good living conditions in functional environments. Considering the interconnectedness of all life forms, the Smithsonian plans to create a framework that will integrate cultural, social, and educational components into health research on humans, animals, plants, or ecosystems. The objectives of this perspective article are to (1) propose an innovative framework to support an interconnected/integrated approach to health and (2) provide examples fostering impactful collaborations on One Health research and education. Based on the core strengths of the Smithsonian (multidisciplinary research, outreach and education programs, libraries/archives, and collections) and central institutional support, this framework has the potential to extend existing health-related projects, address new needs and situations (e.g., response to pandemics), provide invaluable resources to inform policy and decision makers, and educate all audiences globally.

Rapid evolution destabilizes species interactions in a fluctuating environment

Positive species interactions underlie the functioning of ecosystems. Given their importance, it is crucial to understand the stability of positive interactions over evolutionary timescales, in both constant and fluctuating environments; e.g., environments interrupted with periods of competition. We addressed this question using a two-species microbial system in which we modulated interactions according to the nutrient provided. We evolved in parallel four experimental replicates of species growing in isolation or together in consortia for 200 generations in both a constant and fluctuating environment with daily changes between commensalism and competition. We sequenced full genomes of single clones isolated at different time points during the experiment. We found that the two species coexisted over 200 generations in the constant commensal environment. In contrast, in the fluctuating environment, coexistence broke down when one of the species went extinct in two out of four cases. We showed that extinction was highly deterministic: when we replayed the evolution experiment from an intermediate time point we repeatably reproduced species extinction. We further show that these dynamics were driven by adaptive mutations in a small set of genes. In conclusion, in a fluctuating environment, rapid evolution destabilizes the long-term stability of positive pairwise interactions.