Environmental fluctuations reshape an unexpected diversity-disturbance relationship in a microbial community

Enhancing nitrogen and phosphorus removal in plant-biochar-pyrite stormwater bioretention systems: Impact of temperature and high-frequency heavy rainfall

Global climate change and rapid urbanization have resulted in more frequent and intense rainfall events in urban areas, raising concerns about the effectiveness of stormwater bioretention systems. In this study, we optimized the design by constructing a multi-layer filler structure, including plant layer, biochar layer, and pyrite layer, and evaluated its performance in nitrogen (N) and phosphorus (P) removal under different temperatures (5-18 °C and 24-43 °C), rainfall intensity (47.06 mm rainfall depth), and frequency (1-5 days rainfall intervals) conditions. The findings indicate that over 775 days, the plant system consistently removed 62.3% of total nitrogen (TN) and 97.0% of total phosphorus (TP) from 103 intense rainfall events. Temperature fluctuations had minimal impact on nitrate nitrogen (NO3--N) and TP removal, with differences in removal rates of only 1.0% and 0.6%, respectively, among plant groups. Across the multi-layer structure, plant roots mitigated the impact of temperature differences on NO3--N removal, while high-frequency rainfall fluctuated the stability of NO3--N removal. Dense plant roots reinforced N and P removal by facilitating denitrification in the vadose zone (biochar) and strengthening denitrification processes. Biochar and pyrite contributed to stable microenvironments and diverse ecological functions, enhancing NO3--N and PO43- removal. In summary, the synergistic effects of the multi-layer filler structure improved and stabilized N and P removal, providing valuable insights for addressing runoff pollution in bioretention systems amidst rapid urbanization and climate change challenges.

Microbial Dormancy Supports Multi-Species Coexistence Under Resource Fluctuations

The ability for microbes to enter dormant states is adaptive under resource fluctuations and has been linked to the maintenance of diversity. Nevertheless, the mechanism by which microbial dormancy gives rise to the density-dependent feedbacks required for stable coexistence under resource fluctuations is not well understood. Via analysis of consumer-resource models, we show that the stable coexistence of dormancy and non-dormancy strategists is a consequence of the former benefiting more from resource fluctuations while simultaneously reducing overall resource variability, which sets up the requisite negative frequency dependence. Moreover, we find that dormants can coexist alongside gleaner and opportunist strategies in a competitive-exclusion-defying case of three species coexistence on a single resource. This multi-species coexistence is typically characterised by non-simple assembly rules that cannot be predicted from pairwise competition outcomes. The diversity maintained via this three-way trade-off represents a novel phenomenon that is ripe for further theoretical and empirical inquiry.

Overcoming toxicity: why boom-and-bust cycles are good for non-antagonistic microbes

Antagonistic interactions are critical determinants of microbial community stability and composition, offering host benefits such as pathogen protection and providing avenues for antimicrobial control. While the ability to eliminate competitors confers an advantage to antagonistic microbes, it often incurs a fitness cost. Consequently, many microbes only produce toxins or engage in antagonistic behavior in response to specific cues like population density or environmental stress. In laboratory settings, antagonistic microbes typically dominate over sensitive ones, raising the question of why both antagonistic and non-antagonistic microbes are found in natural environments and host microbiomes. Here, using both theoretical models and experiments with killer strains of Saccharomyces cerevisiae , we show that boom-and-bust dynamics caused by temporal environmental fluctuations can favor non-antagonistic microbes that do not incur the growth rate cost of toxin production. Additionally, using control theory, we derive bounds on the competitive performance and identify optimal regulatory toxin-production strategies in various boom-and-bust environments where population dilutions occur either deterministically or stochastically over time. Our findings offer a new perspective on how both antagonistic and non-antagonistic microbes can thrive under varying environmental conditions.

Biodiversity is enhanced by sequential resource utilization and environmental fluctuations via emergent temporal niches

How natural communities maintain their remarkable biodiversity and which species survive in complex communities are central questions in ecology. Resource competition models successfully explain many phenomena but typically predict only as many species as resources can coexist. Here, we demonstrate that sequential resource utilization, or diauxie, with periodic growth cycles can support many more species than resources. We explore how communities modify their own environments by sequentially depleting resources to form sequences of temporal niches, or intermediately depleted environments. Biodiversity is enhanced when community-driven or environmental fluctuations modulate the resource depletion order and produce different temporal niches on each growth cycle. Community-driven fluctuations under constant environmental conditions are rare, but exploring them illuminates the temporal niche structure that emerges from sequential resource utilization. With environmental fluctuations, we find most communities have more stably coexisting species than resources with survivors accurately predicted by the same temporal niche structure and each following a distinct optimal strategy. Our results thus present a new niche-based approach to understanding highly diverse fluctuating communities.

Microfluidic approaches in microbial ecology

Microbial life is at the heart of many diverse environments and regulates most natural processes, from the functioning of animal organs to the cycling of global carbon. Yet, the study of microbial ecology is often limited by challenges in visualizing microbial processes and replicating the environmental conditions under which they unfold. Microfluidics operates at the characteristic scale at which microorganisms live and perform their functions, thus allowing for the observation and quantification of behaviors such as growth, motility, and responses to external cues, often with greater detail than classical techniques. By enabling a high degree of control in space and time of environmental conditions such as nutrient gradients, pH levels, and fluid flow patterns, microfluidics further provides the opportunity to study microbial processes in conditions that mimic the natural settings harboring microbial life. In this review, we describe how recent applications of microfluidic systems to microbial ecology have enriched our understanding of microbial life and microbial communities. We highlight discoveries enabled by microfluidic approaches ranging from single-cell behaviors to the functioning of multi-cellular communities, and we indicate potential future opportunities to use microfluidics to further advance our understanding of microbial processes and their implications.

Disturbance-diversity relationships of microbial communities change based on growth substrate

Disturbance events can impact ecological community dynamics. Understanding how communities respond to disturbances and how those responses can vary is a challenge in microbial ecology. In this study, we grew a previously enriched specialized microbial community on either cellulose or glucose as a sole carbon source and subjected them to one of five different disturbance regimes of varying frequencies ranging from low to high. Using 16S rRNA gene amplicon sequencing, we show that the community structure is largely driven by substrate, but disturbance frequency affects community composition and successional dynamics. When grown on cellulose, bacteria in the genera Cellvibrio, Lacunisphaera, and Asticcacaulis are the most abundant microbes. However, Lacunisphaera is only abundant in the lower disturbance frequency treatments, while Asticcacaulis is more abundant in the highest disturbance frequency treatment. When grown on glucose, the most abundant microbes are two Pseudomonas sequence variants and a Cohnella sequence variant that is only abundant in the highest disturbance frequency treatment. Communities grown on cellulose exhibited a greater range of diversity (1.95-7.33 Hill 1 diversity) that peaks at the intermediate disturbance frequency treatment or one disturbance every 3 days. Communities grown on glucose, however, ranged from 1.63 to 5.19 Hill 1 diversity with peak diversity at the greatest disturbance frequency treatment. These results demonstrate that the dynamics of a microbial community can vary depending on substrate and the disturbance frequency and may potentially explain the variety of diversity-disturbance relationships observed in microbial systems.IMPORTANCEA generalizable diversity-disturbance relationship (DDR) of microbial communities remains a contentious topic. Various microbial systems have different DDRs. Rather than finding support or refuting specific DDRs, we investigated the underlying factors that lead to different DDRs. In this study, we measured a cellulose-enriched microbial community's response to a range of disturbance frequencies from high to low, across two different substrates: cellulose and glucose. We demonstrate that the community displays a unimodal DDR when grown on cellulose and a monotonically increasing DDR when grown on glucose. Our findings suggest that the same community can display different DDRs. These results suggest that the range of DDRs we observe across different microbial systems may be due to the nutritional resources microbial communities can access and the interactions between bacteria and their environment.

The optimization of microbial functions through rational environmental manipulations

Microorganisms play a central role in biotechnology and it is key that we develop strategies to engineer and optimize their functionality. To this end, most efforts have focused on introducing genetic manipulations in microorganisms which are then grown either in monoculture or in mixed-species consortia. An alternative strategy to optimize microbial processes is to rationally engineer the environment in which microbes grow. The microbial environment is multidimensional, including factors such as temperature, pH, salinity, nutrient composition, etc. These environmental factors all influence the growth and phenotypes of microorganisms and they generally "interact" with one another, combining their effects in complex, non-additive ways. In this piece, we overview the origins and consequences of these "interactions" between environmental factors and discuss how they have been built into statistical, bottom-up predictive models of microbial function to identify optimal environmental conditions for monocultures and microbial consortia. We also overview alternative "top-down" approaches, such as genetic algorithms, to finding optimal combinations of environmental factors. By providing a brief summary of the state of this field, we hope to stimulate further work on the rational manipulation and optimization of the microbial environment.

Searching for Principles of Microbial Ecology Across Levels of Biological Organization

Microbial communities play pivotal roles in ecosystems across different scales, from global elemental cycles to household food fermentations. These complex assemblies comprise hundreds or thousands of microbial species whose abundances vary over time and space. Unraveling the principles that guide their dynamics at different levels of biological organization, from individual species, their interactions, to complex microbial communities, is a major challenge. To what extent are these different levels of organization governed by separate principles, and how can we connect these levels to develop predictive models for the dynamics and function of microbial communities? Here, we will discuss recent advances that point towards principles of microbial communities, rooted in various disciplines from physics, biochemistry, and dynamical systems. By considering the marine carbon cycle as a concrete example, we demonstrate how the integration of levels of biological organization can offer deeper insights into the impact of increasing temperatures, such as those associated with climate change, on ecosystem-scale processes. We argue that by focusing on principles that transcend specific microbiomes, we can pave the way for a comprehensive understanding of microbial community dynamics and the development of predictive models for diverse ecosystems.

Synthesizing microbial biodiversity

The diversity of microbial ecosystems is linked to crucial ecological processes and functions. Despite its significance, the ecological mechanisms responsible for the initiation and maintenance of microbiome diversity are still not fully understood. The primary challenge lies in the difficulty of isolating, monitoring, and manipulating the complex and interrelated ecological processes that modulate the diversity of microbial communities in their natural habitats. Synthetic ecology experiments provide a suitable alternative for investigating the mechanisms behind microbial biodiversity in controlled laboratory settings, as the environment can be systematically and modularly manipulated by adding and removing components. This enables the testing of hypotheses and the advancement of predictive theories. In this review, we present an overview of recent progress toward achieving this goal.

Microbial interactions in theory and practice: when are measurements compatible with models?

Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other's growth and death. We review here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalised Lotka-Volterra (gLV) framework. Though widely used, we argue that the gLV model should be avoided for estimating interactions in batch culture - the most common, simplest and cheapest in vitro approach to culturing microbes. Fortunately, alternative approaches offer a way out of this conundrum. Firstly, on the experimental side, alternatives such as the serial-transfer and chemostat systems more closely match the theoretical assumptions of the gLV model. Secondly, on the theoretical side, explicit organism-environment interaction models can be used to study the dynamics of batch-culture systems. We hope that our recommendations will increase the tractability of microbial model systems for experimentalists and theoreticians alike.

Periodic temporal environmental variations induce coexistence in resource competition models

Natural ecosystems, in particular on the microbial scale, are inhabited by a large number of species. The population size of each species is affected by interactions of individuals with each other and by spatial and temporal changes in environmental conditions, such as resource abundance. Here, we use a generic population dynamics model to study how, and under what conditions, a periodic temporal environmental variation can alter an ecosystem's composition and biodiversity. We demonstrate that using timescale separation allows one to qualitatively predict the long-term population dynamics of interacting species in varying environments. We show that the notion of Tilman's R* rule, a well-known principle that applies for constant environments, can be extended to periodically varying environments if the timescale of environmental changes (e.g., seasonal variations) is much faster than the timescale of population growth (doubling time in bacteria). When these timescales are similar, our analysis shows that a varying environment deters the system from reaching a steady state, and stable coexistence between multiple species becomes possible. Our results posit that biodiversity can in part be attributed to natural environmental variations.

Disturbance-Diversity Relationships of Microbial Communities Change Based on Growth Substrate

Disturbance events can impact ecological community dynamics. Understanding how communities respond to disturbances, and how those responses can vary, is a challenge in microbial ecology. In this study, we grew a previously enriched specialized microbial community on either cellulose or glucose as a sole carbon source, and subjected them to one of five different disturbance regimes of varying frequencies ranging from low to high. Using 16S rRNA gene amplicon sequencing, we show that community structure is largely driven by substrate, but disturbance frequency affects community composition and successional dynamics. When grown on cellulose, bacteria in the genera Cellvibrio, Lacunisphaera, and Asticaccacaulis are the most abundant microbes. However, Lacunisphaera is only abundant in the lower disturbance frequency treatments, while Asticaccaulis is more abundant in the highest disturbance frequency treatment. When grown on glucose, the most abundant microbes are two Pseudomonas sequence variants, and a Cohnella sequence variant that is only abundant in the highest disturbance frequency treatment. Communities grown on cellulose exhibited a greater range of diversity (0.67-1.99 Shannon diversity and 1.38-5.25 Inverse Simpson diversity) that peak at the intermediate disturbance frequency treatment, or 1 disturbance every 3 days. Communities grown on glucose, however, ranged from 0.49-1.43 Shannon diversity and 1.37- 3.52 Inverse Simpson with peak diversity at the greatest disturbance frequency treatment. These results demonstrate that the dynamics of a microbial community can vary depending on substrate and the disturbance frequency, and may potentially explain the variety of diversity-disturbance relationships observed in microbial ecosystems.

Resolving metabolic interaction mechanisms in plant microbiomes

Metabolic interactions are fundamental to the assembly and functioning of microbiomes, including those of plants. However, disentangling the molecular basis of these interactions and their specific roles remains a major challenge. Here, we review recent applications of experimental and computational methods toward the elucidation of metabolic interactions in plant-associated microbiomes. We highlight studies that span various scales of taxonomic and environmental complexity, including those that test interaction outcomes in vitro and in planta by deconstructing microbial communities. We also discuss how the continued integration of multiple methods can further reveal the general ecological characteristics of plant microbiomes, as well as provide strategies for applications in areas such as improved plant protection, bioremediation, and sustainable agriculture.

Out of site, out of mind: Changes in feather moss phyllosphere microbiota in mine offsite boreal landscapes

Plant-microbe interactions play a crucial role in maintaining biodiversity and ecological services in boreal forest biomes. Mining for minerals, and especially the emission of heavy metal-enriched dust from mine sites, is a potential threat to biodiversity in offsite landscapes. Understanding the impacts of mining on surrounding phyllosphere microbiota is especially lacking. To investigate this, we characterized bacterial and fungal communities in the phyllosphere of feather moss Pleurozium schreberi (Brid). Mitt in boreal landscapes near six gold mine sites at different stages of the mine lifecycle. We found that (1) both mining stage and ecosystem type are drivers of the phyllosphere microbial community structure in mine offsite landscapes; (2) Bacterial alpha diversity is more sensitive than fungal alpha diversity to mining stage, while beta diversity of both groups is impacted; (3) mixed and deciduous forests have a higher alpha diversity and a distinct microbial community structure when compared to coniferous and open canopy ecosystems; (4) the strongest effects are detectable within 0.2 km from operating mines. These results confirmed the presence of offsite effects of mine sites on the phyllosphere microbiota in boreal forests, as well as identified mining stage and ecosystem type as drivers of these effects. Furthermore, the footprint was quantified at 0.2 km, providing a reference distance within which mining companies and policy makers should pay more attention during ecological assessment and for the development of mitigation strategies. Further studies are needed to assess how these offsite effects of mines affect the functioning of boreal ecosystems.

The community-function landscape of microbial consortia

Quantitatively linking the composition and function of microbial communities is a major aspiration of microbial ecology. Microbial community functions emerge from a complex web of molecular interactions between cells, which give rise to population-level interactions among strains and species. Incorporating this complexity into predictive models is highly challenging. Inspired by a similar problem in genetics of predicting quantitative phenotypes from genotypes, an ecological community-function (or structure-function) landscape could be defined that maps community composition and function. In this piece, we present an overview of our current understanding of these community landscapes, their uses, limitations, and open questions. We argue that exploiting the parallels between both landscapes could bring powerful predictive methodologies from evolution and genetics into ecology, providing a boost to our ability to engineer and optimize microbial consortia.

Resistance potential of soil bacterial communities along a biodiversity gradient in forest ecosystems

Higher biodiversity is often assumed to be a more desirable scenario for maintaining the functioning of ecosystems, but whether species-richer communities are also more disturbance-tolerant remains controversial. In this study, we investigated the bacterial communities based on 472 soil samples from 28 forests across China with associated edaphic and climatic properties. We developed two indexes (i.e., community mean tolerance breadth [CMTB] and community mean response asynchrony [CMRA]) to explore the relationship between diversity and community resistance potential. Moreover, we examined this resistance potential along the climatic and latitudinal gradients. We revealed that CMTB was significantly and negatively related to species richness, resulting from the changes in balance between relative abundances of putative specialists and generalists. In comparison, we found a unimodal relationship between CMRA and richness, suggesting that higher biodiversity might not always lead to higher community resistance. Moreover, our results showed differential local patterns along latitude. In particular, local patterns in the northern region mainly followed general relationships rather than those for the southern forests, which may be attributed to the differences in annual means and annual variations of climate conditions. Our findings highlight that the community resistance potential depends on the composition of diverse species with differential environmental tolerance and responses. This study provides a new, testable evaluation by considering tolerance breadth and response asynchrony at the community level, which will be helpful in assessing the influence of disturbance under rapid shifts in biodiversity and species composition as a result of global environmental change.

Controlling microbial co-culture based on substrate pulsing can lead to stability through differential fitness advantages

Microbial consortia are an exciting alternative for increasing the performances of bioprocesses for the production of complex metabolic products. However, the functional properties of microbial communities remain challenging to control, considering the complex interaction mechanisms occurring between co-cultured microbial species. Indeed, microbial communities are highly dynamic and can adapt to changing environmental conditions through complex mechanisms, such as phenotypic diversification. We focused on stabilizing a co-culture of Saccharomyces cerevisiae and Escherichia coli in continuous cultures. Our preliminary data pointed out that transient diauxic shifts could lead to stable co-culture by providing periodic fitness advantages to the yeast. Based on a computational toolbox called MONCKS (for MONod-type Co-culture Kinetic Simulation), we were able to predict the dynamics of diauxic shift for both species based on a cybernetic approach. This toolbox was further used to predict the frequency of diauxic shift to be applied to reach co-culture stability. These simulations were successfully reproduced experimentally in continuous bioreactors with glucose pulsing. Finally, based on a bet-hedging reporter, we observed that the yeast population exhibited an increased phenotypic diversification process in co-culture compared with mono-culture, suggesting that this mechanism could be the basis of the metabolic fitness of the yeast.

Being able to manipulate the dynamics of microbial co-cultures is a technical challenge that need to be addressed in order to get a deeper insight about how microbial communities are evolving in their ecological context, as well as for exploiting the potential offered by such communities in an applied context e.g., for setting up more robust bioprocesses relying on the use of several microbial species. In this study, we used continuous cultures of bacteria (E. coli) and yeast (S. cerevisiae) in order to demonstrate that a simple nutrient pulsing strategy can be used for adjusting the composition of the community with time. As expected, during growth on glucose, E. coli quickly outcompeted S. cerevisiae. However, when glucose is pulsed into the culture, increased metabolic fitness of the yeast was observed upon reconsumption of the main side metabolites i.e., acetate and ethanol, leading to a robust oscillating growth profile for both species. The optimal pulsing frequency was predicted based on a cybernetic version of a Monod growth model taking into account the main metabolic routes involved in the process. Considering the limited number of metabolic details needed, this cybernetic approach could be generalized to other communities.

Net effect of environmental fluctuations in multiple global-change drivers across the tree of life

Jensen's inequality predicts that the response of any given system to average constant conditions is different from its average response to varying ones. Environmental fluctuations in abiotic conditions are pervasive on Earth; yet until recently, most ecological research has addressed the effects of multiple environmental drivers by assuming constant conditions. One could thus expect to find significant deviations in the magnitude of their effects on ecosystems when environmental fluctuations are considered. Drawing on experimental studies published during the last 30 years reporting more than 950 response ratios (n = 5,700), we present a comprehensive analysis of the role that environmental fluctuations play across the tree of life. In contrast to the predominance of interactive effects of global-change drivers reported in the literature, our results show that their cumulative effects were additive (58%), synergistic (26%), and antagonistic (16%) when environmental fluctuations were present. However, the dominant type of interaction varied by trophic level (autotrophs: interactive; heterotrophs: additive) and phylogenetic group (additive in Animalia; additive and positive antagonism in Chromista; negative antagonism and synergism in Plantae). In addition, we identify the need to tackle how complex communities respond to fluctuating environments, widening the phylogenetic and biogeographic ranges considered, and to consider other drivers beyond warming and acidification as well as longer timescales. Environmental fluctuations must be taken into account in experimental and modeling studies as well as conservation plans to better predict the nature, magnitude, and direction of the impacts of global change on organisms and ecosystems.

Biogeographic patterns of benthic microbial communities in metal(loid)-contaminated semi-enclosed bay

Anthropogenic activities can adversely impact biogeochemical processes essential for maintaining ecosystem health in semi-enclosed bays. However, the influence of anthropogenic contaminants such as potentially toxic elements on microbial communities that regulate biogeochemical cycles in semi-enclosed bays is poorly understood. We determined the concentrations of four potentially toxic elements (Cu, Zn, Pb, and As) in sediments from a typical tropical semi-enclosed bay in Guangdong, China. Source apportionment using Pearson's correlation analysis revealed that aquaculture activities were probably the primary source of Cu, Zn, and Pb. Using high-throughput sediment DNA sequencing, we found that Proteobacteria was the dominant phylum in sediments. There was no evidence suggesting site-specific variation in microbial function even though sediments adjacent to aquaculture discharge points had higher microbial diversity. In contrast, pollutant-specific variations were observed; for example, Zn and Pd showed potential adverse effects on the environmental information processing function, while As showed a negative correlation with metabolic function. Based on different environmental characteristics, future research should consider the impact of multiple factors on the bacterial community in aquaculture systems.

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.

Microbiome assembly predictably shapes diversity across a range of disturbance frequencies in experimental microcosms

Diversity is often implied to have a positive effect on the functional stability of ecological communities. However, its relationship with stochastic and deterministic assembly mechanisms remains largely unknown, particularly under fluctuating disturbances. Here, we subjected complex bacterial communities in microcosms to different frequencies of alteration in substrate feeding scheme, tracking temporal dynamics in their assembly, structure and function. Activated sludge bioreactors were subjected to six different frequencies of double organic loading, either never (undisturbed), every 8, 6, 4, or 2 days (intermediately disturbed), or every day (press disturbed), and operated in daily cycles for 42 days. Null modeling revealed a stronger role of stochastic assembly at intermediate disturbance frequencies, with a peak in stochasticity that preceded the occurrence of a peak in α-diversity. Communities at extreme ends of the disturbance range had the lowest α-diversity and highest within-treatment similarity in terms of β-diversity, with stronger deterministic assembly. Increased carbon removal and microbial aggregate settleability (general functions) correlated with stronger deterministic processes. In contrast, higher stochasticity correlated with higher nitrogen removal (a specialized function) only during initial successional stages at intermediate disturbance frequencies. We show that changes in assembly processes predictably precede changes in diversity under a gradient of disturbance frequencies, advancing our understanding of the mechanisms behind disturbance-diversity-function relationships.

Methods for the directed evolution of biomolecular interactions

Noncovalent interactions between biomolecules such as proteins and nucleic acids coordinate all cellular processes through changes in proximity. Tools that perturb these interactions are and will continue to be highly valuable for basic and translational scientific endeavors. By taking cues from natural systems, such as the adaptive immune system, we can design directed evolution platforms that can generate proteins that bind to biomolecules of interest. In recent years, the platforms used to direct the evolution of biomolecular binders have greatly expanded the range of types of interactions one can evolve. Herein, we review recent advances in methods to evolve protein-protein, protein-RNA, and protein-DNA interactions.