Environment-to-phenotype mapping and adaptation strategies in varying environments

Response and acclimation of cyanobacteria to acidification: A comprehensive review

Cyanobacteria, as vital components of aquatic ecosystems, face increasing challenges due to acidification driven by various anthropogenic and natural factors. Understanding how cyanobacteria adapt and respond to acidification is crucial for predicting their ecological dynamics and potential impacts on ecosystem health. This comprehensive review synthesizes current knowledge on the acclimation mechanisms and responses of cyanobacteria to acidification stress. Detailly, ecological roles of cyanobacteria were firstly briefly concluded, followed by the effects of acidification on aquatic ecosystems and cyanobacteria. Then the review focuses on the physiological, biochemical, and molecular strategies employed by cyanobacteria to cope with acidification stress, highlighting key adaptive mechanisms and their ecological implications. Finally, a summary of strategies to enhance acid resistance in cyanobacteria and future directions was discussed. Utilizing omics data and machine learning technology to build a cyanobacterial acid regulatory network allows for predicting the impact of acidification on cyanobacteria and inferring its broader effects on ecosystems. Additionally, acquiring acid-tolerant chassis cells of cyanobacteria through innovative techniques facilitates the advancement of environmentally friendly production of acidic chemicals. By synthesizing empirical evidence and theoretical frameworks, this review aims to elucidate the complex interplay between cyanobacteria and acidification stressors, providing insights for future research directions and ecosystem management strategies.

Design principles of multi-map variation in biological systems

Complexity in biology is often described using a multi-map hierarchical architecture, where the genotype, representing the encoded information, is mapped to the functional level, known as the phenotype, which is then connected to a latent phenotype we refer to as fitness. This underlying architecture governs the processes driving evolution. Furthermore, natural selection, along with other neutral forces, can, in turn, modify these maps. At each level, variation is observed. Here, I propose the need to establish principles that can aid in understanding the transformation of variation within this multi-map architecture. Specifically, I will introduce three, related to the presence of modulators, constraints, and the modular channeling of variation. By comprehending these design principles in various biological systems, we can gain better insights into the mechanisms underlying these maps and how they ultimately contribute to evolutionary dynamics.

Perspectives on computational modeling of biological systems and the significance of the SysMod community

Motivation

In recent years, applying computational modeling to systems biology has caused a substantial surge in both discovery and practical applications and a significant shift in our understanding of the complexity inherent in biological systems.

Results

In this perspective article, we briefly overview computational modeling in biology, highlighting recent advancements such as multi-scale modeling due to the omics revolution, single-cell technology, and integration of artificial intelligence and machine learning approaches. We also discuss the primary challenges faced: integration, standardization, model complexity, scalability, and interdisciplinary collaboration. Lastly, we highlight the contribution made by the Computational Modeling of Biological Systems (SysMod) Community of Special Interest (COSI) associated with the International Society of Computational Biology (ISCB) in driving progress within this rapidly evolving field through community engagement (via both in person and virtual meetings, social media interactions), webinars, and conferences.

Availability and implementation

Additional information about SysMod is available at https://sysmod.info.

Adopting Mechanistic Molecular Biology Approaches in Exposome Research for Causal Understanding

Through investigating the combined impact of the environmental exposures experienced by an individual throughout their lifetime, exposome research provides opportunities to understand and mitigate negative health outcomes. While current exposome research is driven by epidemiological studies that identify associations between exposures and effects, new frameworks integrating more substantial population-level metadata, including electronic health and administrative records, will shed further light on characterizing environmental exposure risks. Molecular biology offers methods and concepts to study the biological and health impacts of exposomes in experimental and computational systems. Of particular importance is the growing use of omics readouts in epidemiological and clinical studies. This paper calls for the adoption of mechanistic molecular biology approaches in exposome research as an essential step in understanding the genotype and exposure interactions underlying human phenotypes. A series of recommendations are presented to make the necessary and appropriate steps to move from exposure association to causation, with a huge potential to inform precision medicine and population health. This includes establishing hypothesis-driven laboratory testing within the exposome field, supported by appropriate methods to read across from model systems research to human.

Individual variation in thermally induced plasticity of metabolic rates: ecological and evolutionary implications for a warming world

Energy metabolism is a fundamental property of life providing the energy for all processes and functions within an organism. As it is temperature-dependent, it mediates the effects of changing climate on ectotherm fitness and population dynamics. Though resting metabolic rate is a highly labile trait, part of its variation is individually consistent. Recent findings show that resting metabolic rate contains consistent variation not only in the elevations (intercepts) but also in the slopes of individual thermal dependence curves, challenging the thermal dependence assumption for this trait in several ectotherm taxa. I argue that among-individual variation in thermal metabolic curves represents a previously undetected component of ectotherm response to climate change, potentially affecting their adaptive capacity and population resilience under increasing stochasticity of thermal environment. Future studies need to examine not only the amount of among-individual variation in thermal metabolic curves across phylogenetic contexts but also other aspects concerning its mechanisms and adaptive significance to improve predictions about the impact of climate change on ectotherm population dynamics. This article is part of the theme issue 'The evolutionary significance of variation in metabolic rates'.

Heterogeneity in maternal mRNAs within clutches of eggs in response to thermal stress during the embryonic stage

BACKGROUND

The origin of variation is of central interest in evolutionary biology. Maternal mRNAs govern early embryogenesis in many animal species, and we investigated the possibility that heterogeneity in maternal mRNA provisioning of eggs can be modulated by environmental stimuli.

RESULTS

We employed two sibling species of the ascidian Ciona, called here types A and B, that are adapted to different temperature regimes and can be hybridized. Previous study showed that hybrids using type B eggs had higher susceptibility to thermal stress than hybrids using type A eggs. We conducted transcriptome analyses of multiple single eggs from crosses using eggs of the different species to compare the effects of maternal thermal stress on heterogeneity in egg provisioning, and followed the effects across generations. We found overall decreases of heterogeneity of egg maternal mRNAs associated with maternal thermal stress. When the eggs produced by the F1 AB generation were crossed with type B sperm and the progeny ('ABB' generation) reared unstressed until maturation, the overall heterogeneity of the eggs produced was greater in a clutch from an individual with a heat-stressed mother compared to one from a non-heat-stressed mother. By examining individual genes, we found no consistent overall effect of thermal stress on heterogeneity of expression in genes involved in developmental buffering. In contrast, heterogeneity of expression in signaling molecules was directly affected by thermal stress.

CONCLUSIONS

Due to the absence of batch replicates and variation in the number of reads obtained, our conclusions are very limited. However, contrary to the predictions of bet-hedging, the results suggest that maternal thermal stress at the embryo stage is associated with reduced heterogeneity of maternal mRNA provision in the eggs subsequently produced by the stressed individual, but there is then a large increase in heterogeneity in eggs of the next generation, although itself unstressed. Despite its limitations, our study presents a proof of concept, identifying a model system, experimental approach and analytical techniques capable of providing a significant advance in understanding the impact of maternal environment on developmental heterogeneity.

Unraveling the secrets of Eclipta alba (L.) Hassk.: a comprehensive study of morpho-anatomy and DNA barcoding

Safety regarding herbal products is very necessary; therefore, routine identification of raw materials should be performed to ensure that the raw materials used in pharmaceutical products are suitable for their intended use. In order for the identification-related data obtained to be accurate, the identification of various kinds of markers is also very necessary. The purpose of this study was to describe the characteristics of Eclipta alba (L.) Hassk. based on qualitative morpho-anatomical markers and quantitative DNA coding. The morphology of this plant has herbaceous habit with a taproot and a stem with branches that appear from the middle. Leaves are single type imperfectly arranged oppositely, lanceolatus, finely serrated on the edges, tapered at the base, pointed at the end, and have a pinnate and hairy leaf surface. The flowers consist of ray flowers and tube flowers with a cup shape. Meanwhile, in terms of anatomy, E. alba has aerenchyma, which are scattered in the cortex of the root and stem. In addition, there are anisocytic stomata, glandular trichomes, and non-glandural trichomes with an elongated shape accompanied by ornamentation found on the leaf epidermis. The results of sequence alignment and phylogenetic tree reconstruction show that the sample plants are closely related to species in the genus Eclipta.

Plasticity-led evolution as an intrinsic property of developmental gene regulatory networks

The modern evolutionary synthesis seemingly fails to explain how a population can survive a large environmental change: the pre-existence of heritable variants adapted to the novel environment is too opportunistic, whereas the search for new adaptive mutations after the environmental change is so slow that the population may go extinct. Plasticity-led evolution, the initial environmental induction of a novel adaptive phenotype followed by genetic accommodation, has been proposed to solve this problem. However, the mechanism enabling plasticity-led evolution remains unclear. Here, we present computational models that exhibit behaviors compatible with plasticity-led evolution by extending the Wagner model of gene regulatory networks. The models show adaptive plastic response and the uncovering of cryptic mutations under large environmental changes, followed by genetic accommodation. Moreover, these behaviors are consistently observed over distinct novel environments. We further show that environmental cues, developmental processes, and hierarchical regulation cooperatively amplify the above behaviors and accelerate evolution. These observations suggest plasticity-led evolution is a universal property of complex developmental systems independent of particular mutations.

Canalisation and plasticity on the developmental manifold of Caenorhabditis elegans

How do the same mechanisms that faithfully regenerate complex developmental programmes in spite of environmental and genetic perturbations also allow responsiveness to environmental signals, adaptation and genetic evolution? Using the nematode Caenorhabditis elegans as a model, we explore the phenotypic space of growth and development in various genetic and environmental contexts. Our data are growth curves and developmental parameters obtained by automated microscopy. Using these, we show that among the traits that make up the developmental space, correlations within a particular context are predictive of correlations among different contexts. Furthermore, we find that the developmental variability of this animal can be captured on a relatively low-dimensional phenotypic manifold and that on this manifold, genetic and environmental contributions to plasticity can be deconvolved independently. Our perspective offers a new way of understanding the relationship between robustness and flexibility in complex systems, suggesting that projection and concentration of dimension can naturally align these forces as complementary rather than competing.

Phylogenetic signal in gut microbial community rather than in rodent metabolic traits

Host phylogeny and environment have all been implicated in shaping the gut microbiota and host metabolic traits of mammals. However, few studies have evaluated phylogeny-associated microbial assembly and host metabolic plasticity concurrently, and their relationships on both short-term and evolutionary timescales. We report that the branching order of a gut microbial dendrogram was nearly congruent with phylogenetic relationships of seven rodent species, and this pattern of phylosymbiosis was intact after diverse laboratory manipulations. Laboratory rearing, diet or air temperature (Ta) acclimation induced alterations in gut microbial communities, but could not override host phylogeny in shaping microbial community assembly. A simulative heatwave reduced core microbiota diversity by 26% in these species, and led to an unmatched relationship between the microbiota and host metabolic phenotypes in desert species. Moreover, the similarity of metabolic traits across species at different Tas was not correlated with phylogenetic distance. These data demonstrated that the gut microbial assembly showed strong concordance with host phylogeny and may be shaped by environmental variables, whereas host metabolic traits did not seem to be linked with phylogeny.

Larval zebrafish as a model for studying individual variability in translational neuroscience research

The larval zebrafish is a popular model for translational research into neurological and psychiatric disorders due to its conserved vertebrate brain structures, ease of genetic and experimental manipulation and small size and scalability to large numbers. The possibility of obtaining in vivo whole-brain cellular resolution neural data is contributing important advances into our understanding of neural circuit function and their relation to behavior. Here we argue that the larval zebrafish is ideally poised to push our understanding of how neural circuit function relates to behavior to the next level by including considerations of individual differences. Understanding variability across individuals is particularly relevant for tackling the variable presentations that neuropsychiatric conditions frequently show, and it is equally elemental if we are to achieve personalized medicine in the future. We provide a blueprint for investigating variability by covering examples from humans and other model organisms as well as existing examples from larval zebrafish. We highlight recent studies where variability may be hiding in plain sight and suggest how future studies can take advantage of existing paradigms for further exploring individual variability. We conclude with an outlook on how the field can harness the unique strengths of the zebrafish model to advance this important impending translational question.

Development under predation risk increases serotonin-signaling, variability of turning behavior and survival in adult fruit flies Drosophila melanogaster

The development of high-throughput behavioral assays, where numerous individual animals can be analyzed in various experimental conditions, has facilitated the study of animal personality. Previous research showed that isogenic Drosophila melanogaster flies exhibit striking individual non-heritable locomotor handedness. The variability of this trait, i.e., the predictability of left-right turn biases, varies across genotypes and under the influence of neural activity in specific circuits. This suggests that the brain can dynamically regulate the extent of animal personality. It has been recently shown that predators can induce changes in prey phenotypes via lethal or non-lethal effects affecting the serotonergic signaling system. In this study, we tested whether fruit flies grown with predators exhibit higher variability/lower predictability in their turning behavior and higher survival than those grown with no predators in their environment. We confirmed these predictions and found that both effects were blocked when flies were fed an inhibitor (αMW) of serotonin synthesis. The results of this study demonstrate a negative association between the unpredictability of turning behavior of fruit flies and the hunting success of their predators. We also show that the neurotransmitter serotonin controls predator-induced changes in the turning variability of fruit flies, regulating the dynamic control of behavioral predictability.

Phenotypic variation in the molt characteristics of a seasonal coat color-changing species reveals limited resilience to climate change

The snowshoe hare (Lepus americanus) possesses a broad suite of adaptations to winter, including a seasonal coat color molt. Recently, climate change has been implicated in the range contraction of snowshoe hares along the southern range boundary. With shortening snow season duration, snowshoe hares are experiencing increased camouflage mismatch with their environment reducing survival. Phenological variation of hare molt at regional scales could facilitate local adaptation in the face of climate change, but the level of variation, especially along the southern range boundary, is unknown. Using a network of trail cameras and historical museum specimens, we (1) developed contemporary and historical molt phenology curves in the Upper Great Lakes region, USA, (2) calculated molt rate and variability in and among populations, and (3) quantified the relationship of molt characteristics to environmental conditions for snowshoe hares across North America. We found that snowshoe hares across the region exhibited similar fall and spring molt phenologies, rates and variation. Yet, an insular island population of hares on Isle Royale National Park, MI, completed their molt a week earlier in the fall and initiated molt almost 2 weeks later in the spring as well as exhibited slower rates of molting in the fall season compared to the mainland. Over the last 100 years, snowshoe hares across the region have not shifted in fall molt timing; though contemporary spring molt appears to have advanced by 17 days (~ 4 days per decade) compared to historical molt phenology. Our research indicates that some variation in molt phenology exists for snowshoe hares in the Upper Great Lakes region, but whether this variation is enough to offset the consequences of climate change remains to be seen.

Revealing the neurobiology underlying interpersonal neural synchronization with multimodal data fusion

Humans synchronize with one another to foster successful interactions. Here, we use a multimodal data fusion approach with the aim of elucidating the neurobiological mechanisms by which interpersonal neural synchronization (INS) occurs. Our meta-analysis of 22 functional magnetic resonance imaging and 69 near-infrared spectroscopy hyperscanning experiments (740 and 3721 subjects) revealed robust brain regional correlates of INS in the right temporoparietal junction and left ventral prefrontal cortex. Integrating this meta-analytic information with public databases, biobehavioral and brain-functional association analyses suggested that INS involves sensory-integrative hubs with functional connections to mentalizing and attention networks. On the molecular and genetic levels, we found INS to be associated with GABAergic neurotransmission and layer IV/V neuronal circuits, protracted developmental gene expression patterns, and disorders of neurodevelopment. Although limited by the indirect nature of phenotypic-molecular association analyses, our findings generate new testable hypotheses on the neurobiological basis of INS.

Safety Evaluation of Bacillus subtilis IDCC1101, Newly Isolated from Cheonggukjang, for Industrial Applications

The present study aimed to evaluate the safety of Bacillus subtilis (BS) IDCC1101, newly isolated from Cheonggukjang in Korea. Genome sequencing of BS IDCC1101 was performed to investigate the presence of secondary metabolites, virulence, antibiotic resistance, and mobile elements. Its phenotypic safety analyses included antibiotic susceptibility, enzyme activity, carbohydrate utilization, production of biogenic amines (BAs) and D-/L-lactate, hemolytic activity, and toxicities in HaCaT cells and rats. The genome of BS IDCC1101 consisted of 4,118,950 bp with 3077 functional genes. Among them, antimicrobial and antifungal secondary metabolites were found, such as fengycin, bacillibactin, and bacilysin. Antibiotic resistance and virulence genes did not exhibit transferability since they did not overlap with mobile elements in the genome. BS IDCC1101 was susceptible to almost all antibiotics suggested for assessment of BS's antibiotic susceptibility by EFSA guidelines, except for streptomycin. BS IDCC1101 showed the utilization of a wide range of 27 carbohydrates, as well as enzyme activities such as alkaline phosphatase, esterase, esterase lipase, naphthol-AS-BI-phosphohydrolase, α-galactosidase, β-galactosidase, α-glucosidase, and β-glucosidase activities. Additionally, BS IDCC1101 did not exhibit the production of D-/L-lactate and hemolytic activities. Its toxicity in HaCaT cells and rats was also not detected. Thus, these genotypic and phenotypic findings indicate that BS IDCC1101 can be safely used for industrial applications.

Microbial resistance to nanotechnologies: An important but understudied consideration using antimicrobial nanotechnologies in orthopaedic implants

Microbial resistance to current antibiotics therapies is a major cause of implant failure and adverse clinical outcomes in orthopaedic surgery. Recent developments in advanced antimicrobial nanotechnologies provide numerous opportunities to effective remove resistant bacteria and prevent resistance from occurring through unique mechanisms. With tunable physicochemical properties, nanomaterials can be designed to be bactericidal, antifouling, immunomodulating, and capable of delivering antibacterial compounds to the infection region with spatiotemporal accuracy. Despite its substantial advancement, an important, but under-explored area, is potential microbial resistance to nanomaterials and how this can impact the clinical use of antimicrobial nanotechnologies. This review aims to provide a better understanding of nanomaterial-associated microbial resistance to accelerate bench-to-bedside translations of emerging nanotechnologies for effective control of implant associated infections.

Collective behavior and nongenetic inheritance allow bacterial populations to adapt to changing environments

Collective behaviors require coordination among a group of individuals. As a result, individuals that are too phenotypically different from the rest of the group can be left out, reducing heterogeneity, but increasing coordination. If individuals also reproduce, the offspring can have different phenotypes from their parent(s). This raises the question of how these two opposing processes-loss of diversity by collective behaviors and generation of it through growth and inheritance-dynamically shape the phenotypic composition of an isogenic population. We examine this question theoretically using collective migration of chemotactic bacteria as a model system, where cells of different swimming phenotypes are better suited to navigate in different environments. We find that the differential loss of phenotypes caused by collective migration is environment-dependent. With cell growth, this differential loss enables migrating populations to dynamically adapt their phenotype compositions to the environment, enhancing migration through multiple environments. Which phenotypes are produced upon cell division depends on the level of nongenetic inheritance, and higher inheritance leads to larger composition adaptation and faster migration at steady state. However, this comes at the cost of slower responses to new environments. Due to this trade-off, there is an optimal level of inheritance that maximizes migration speed through changing environments, which enables a diverse population to outperform a nondiverse one. Growing populations might generally leverage the selection-like effects provided by collective behaviors to dynamically shape their own phenotype compositions, without mutations.

Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing Cognition in Diverse Embodiments

One of the most salient features of life is its capacity to handle novelty and namely to thrive and adapt to new circumstances and changes in both the environment and internal components. An understanding of this capacity is central to several fields: the evolution of form and function, the design of effective strategies for biomedicine, and the creation of novel life forms via chimeric and bioengineering technologies. Here, we review instructive examples of living organisms solving diverse problems and propose competent navigation in arbitrary spaces as an invariant for thinking about the scaling of cognition during evolution. We argue that our innate capacity to recognize agency and intelligence in unfamiliar guises lags far behind our ability to detect it in familiar behavioral contexts. The multi-scale competency of life is essential to adaptive function, potentiating evolution and providing strategies for top-down control (not micromanagement) to address complex disease and injury. We propose an observer-focused viewpoint that is agnostic about scale and implementation, illustrating how evolution pivoted similar strategies to explore and exploit metabolic, transcriptional, morphological, and finally 3D motion spaces. By generalizing the concept of behavior, we gain novel perspectives on evolution, strategies for system-level biomedical interventions, and the construction of bioengineered intelligences. This framework is a first step toward relating to intelligence in highly unfamiliar embodiments, which will be essential for progress in artificial intelligence and regenerative medicine and for thriving in a world increasingly populated by synthetic, bio-robotic, and hybrid beings.

Local ecological divergence of two closely related stag beetles based on genetic, morphological, and environmental analyses

The process of phenotypic adaptation to the environments is widely recognized. However, comprehensive studies integrating phylogenetic, phenotypic, and ecological approaches to assess this process are scarce. Our study aims to assess whether local adaptation may explain intraspecific differentiation by quantifying multidimensional differences among populations in closely related lucanid species, Platycerus delicatulus and Platycerus kawadai, which are endemic saproxylic beetles in Japan. First, we determined intraspecific analysis units based on nuclear and mitochondrial gene analyses of Platycerus delicatulus and Platycerus kawadai under sympatric and allopatric conditions. Then, we compared differences in morphology and environmental niche between populations (analysis units) within species. We examined the relationship between morphology and environmental niche via geographic distance. P. kawadai was subdivided into the “No introgression” and “Introgression” populations based on mitochondrial COI gene – nuclear ITS region discordance. P. delicatulus was subdivided into “Allopatric” and “Sympatric” populations. Body length differed significantly among the populations of each species. For P. delicatulus, character displacement was suggested. For P. kawadai, the morphological difference was likely caused by geographic distance or genetic divergence rather than environmental differences. The finding showed that the observed mitochondrial–nuclear discordance is likely due to historical mitochondrial introgression following a range of expansion. Our results show that morphological variation among populations of P. delicatulus and P. kawadai reflects an ecological adaptation process based on interspecific interactions, geographic distance, or genetic divergence. Our results will deepen understanding of ecological specialization processes across the distribution and adaptation of species in natural systems.

Evolutionary dynamics, evolutionary forces, and robustness: A nonequilibrium statistical mechanics perspective

Evolution through natural selection is an overwhelmingly complex process, and it is not surprising that theoretical approaches are strongly simplifying it. For instance, population genetics considers mainly dynamics of gene allele frequencies. Here, we develop a complementary approach to evolutionary dynamics based on three elements—organism reproduction, variations, and selection—that are essential for any evolutionary theory. By considering such general dynamics as a stochastic thermodynamic process, we clarify the nature and action of the evolutionary forces. We show that some of the forces cannot be described solely in terms of fitness landscapes. We also find that one force contribution can make organism reproduction insensitive (robust) to variations.

Any realistic evolutionary theory has to consider 1) the dynamics of organisms that reproduce and possess heritable traits, 2) the appearance of stochastic variations in these traits, and 3) the selection of those organisms that better survive and reproduce. These elements shape the “evolutionary forces” that characterize the evolutionary dynamics. Here, we introduce a general model of reproduction–variation–selection dynamics. By treating these dynamics as a nonequilibrium thermodynamic process, we make precise the notion of the forces that characterize evolution. One of these forces, in particular, can be associated with the robustness of reproduction to variations. Some of the detailed predictions of our model can be tested by quantitative laboratory experiments, similar to those performed in the past on evolving populations of proteins or viruses.

Merging the exposome into an integrated framework for “omics” sciences

The exposome concept encourages holistic consideration of the non-genetic factors (environmental exposures including lifestyle) that influence an individual’s health over their life course. However, disconnect between the concept and practical application has promoted divergent interpretations of the exposome across disciplines and reinforced separation of the environmental (emphasizing exposures) and biological (emphasizing responses) research communities. In particular, while knowledge of biological responses can help to distinguish actual (i.e. experienced) from potential exposures, the inclusion of endogenous processes has generated confusion about the position of the exposome in a multi-omics systems biology context. We propose a reattribution of “exposome” to exclusively represent the totality of contact with external factors that a biological entity experiences, and introduce the term “functional exposomics” to denote the systematic study of exposure-phenotype interaction. This reoriented definition of the exposome allows a more readily integrable dataset for multi-omics and systems biology research.

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Reattribution of exposome concept to exclusively represent environmental exposures

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Generalized the exposome concept for all levels of biological organization

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Functional exposome presented as the totality of exposure-phenotype interaction

Minimal informational requirements for fitness

The existing concept of the "fitness value of information" provides a theoretical upper bound on the fitness advantage of using information concerning a fluctuating environment. Using concepts from rate-distortion theory, we develop a theoretical framework to answer a different pair of questions: What is the minimal amount of information needed for a population to achieve a certain growth rate? What is the minimal amount of information gain needed for one subpopulation to achieve a certain average selection coefficient over another? We introduce a correspondence between fitness and distortion and solve for the rate-distortion functions of several systems using analytical and numerical methods. Because accurate information processing is energetically costly, our approach provides a theoretical basis for understanding evolutionary "design principles" underlying information-cost trade-offs.

Redundancy-selection trade-off in phenotype-structured populations

Realistic fitness landscapes generally display a redundancy-fitness trade-off: highly fit trait configurations are inevitably rare, while less fit trait configurations are expected to be more redundant. The resulting sub-optimal patterns in the fitness distribution are typically described by means of effective formulations, where redundancy provided by the presence of neutral contributions is modelled implicitly, e.g. with a bias of the mutation process. However, the extent to which effective formulations are compatible with explicitly redundant landscapes is yet to be understood, as well as the consequences of a potential miss-match. Here we investigate the effects of such trade-off on the evolution of phenotype-structured populations, characterised by continuous quantitative traits. We consider a typical replication-mutation dynamics, and we model redundancy by means of two dimensional landscapes displaying both selective and neutral traits. We show that asymmetries of the landscapes will generate neutral contributions to the marginalised fitness-level description, that cannot be described by effective formulations, nor disentangled by the full trait distribution. Rather, they appear as effective sources, whose magnitude depends on the geometry of the landscape. Our results highlight new important aspects on the nature of sub-optimality. We discuss practical implications for rapidly mutant populations such as pathogens and cancer cells, where the qualitative knowledge of their trait and fitness distributions can drive disease management and intervention policies.

Neuromodulation and Individuality

Within populations, individuals show a variety of behavioral preferences, even in the absence of genetic or environmental variability. Neuromodulators affect these idiosyncratic preferences in a wide range of systems, however, the mechanism(s) by which they do so is unclear. I review the evidence supporting three broad mechanisms by which neuromodulators might affect variability in idiosyncratic behavioral preference: by being a source of variability directly upstream of behavior, by affecting the behavioral output of a circuit in a way that masks or accentuates underlying variability in that circuit, and by driving plasticity in circuits leading to either homeostatic convergence toward a given behavior or divergence from a developmental setpoint. I find evidence for each of these mechanisms and propose future directions to further understand the complex interplay between individual variability and neuromodulators.

Evolution of phenotypic fluctuation under host-parasite interactions

Robustness and plasticity are essential features that allow biological systems to cope with complex and variable environments. In a constant environment, robustness, i.e., insensitivity of phenotypes, is expected to increase, whereas plasticity, i.e., the changeability of phenotypes, tends to diminish. Under a variable environment, existence of plasticity will be relevant. The robustness and plasticity, on the other hand, are related to phenotypic variances. As phenotypic variances decrease with the increase in robustness to perturbations, they are expected to decrease through the evolution. However, in nature, phenotypic fluctuation is preserved to a certain degree. One possible cause for this is environmental variation, where one of the most important “environmental” factors will be inter-species interactions. As a first step toward investigating phenotypic fluctuation in response to an inter-species interaction, we present the study of a simple two-species system that comprises hosts and parasites. Hosts are expected to evolve to achieve a phenotype that optimizes fitness. Then, the robustness of the corresponding phenotype will be increased by reducing phenotypic fluctuations. Conversely, plasticity tends to evolve to avoid certain phenotypes that are attacked by parasites. By using a dynamic model of gene expression for the host, we investigate the evolution of the genotype-phenotype map and of phenotypic variances. If the host–parasite interaction is weak, the fittest phenotype of the host evolves to reduce phenotypic variances. In contrast, if there exists a sufficient degree of interaction, the phenotypic variances of hosts increase to escape parasite attacks. For the latter case, we found two strategies: if the noise in the stochastic gene expression is below a certain threshold, the phenotypic variance increases via genetic diversification, whereas above this threshold, it is increased mediated by noise-induced phenotypic fluctuation. We examine how the increase in the phenotypic variances caused by parasite interactions influences the growth rate of a single host, and observed a trade-off between the two. Our results help elucidate the roles played by noise and genetic mutations in the evolution of phenotypic fluctuation and robustness in response to host–parasite interactions.

Plasticity and phenotypic variability induced by internal or external perturbations are common features of biological systems. However, under evolution for given environmental conditions, phenotypic variability is not advantageous, because it leads to the deviation from the fittest state. This has been demonstrated by previous laboratory and computer experiments. As a possible origin for the remnant phenotypic variance, we investigated the role of host–parasite interactions such as those between bacteria and phages. Different parasite-types attack hosts of certain phenotypes. Through numerical simulations of the evolution of the host genotype–phenotype mapping, we found that hosts increase phenotypic variation by increasing phenotypic fluctuations if the interaction is sufficiently strong. Depending on the degree of noise in gene expression dynamics, there are two distinct strategies for increasing phenotypic variances: stochasticity in gene expression or genetic variances. The former strategy, which can work over a faster time scale, leads to a decline in fitness, whereas the latter reduces the robustness of the fitted state. Our results provide insights into how phenotypic variances are preserved and how hosts can escape being attacked by parasites whose genes mutate to adapt to changes in parasites. These two host strategies, which depend on internal and external conditions, can be verified experimentally via the transcriptome analysis of microorganisms.

Identification of Potential Gene Regulatory Pathways Affecting the Ratio of Four-Seed Pod in Soybean

The number of four-seed pods is one of the most important agronomic traits affected by gene and environment that can potentially improve soybean (Glycine max) yield. However, the gene regulatory network that affects the ratio of four-seed pod (the ratio of the number of four-seed pods to the total number of pods in each individual plant) is yet unclear. Here, we performed bulked segregant RNA sequencing (BSR-seq) on a series of recombinant inbred lines (RILs) derived from hybrid progenies between Heinong 48 (HN48), a cultivar with a high ratio of four-seed pod, and Henong 64 (HN64), a cultivar with a low ratio of four-seed pod. Two tissues, flower bud and young pod, at two different growth stages, R1 and R3, were analyzed under the ratios of four-seed pod at less than 10% and greater than 30%, respectively. To identify the potential gene regulation pathways associated with the ratio of soybean four-seed pod, we performed differentially expressed analysis on the four bulked groups. A differentially expressed gene (DEG) encoding a photosystem II 5-kDa protein had the function of participating in the energy conversion of photosynthesis. In addition, 79 common DEGs were identified at different developmental stages and under different ratios of four-seed pod. Among them, four genes encoding calcium-binding proteins and a WRKY transcription factor were enriched in the plant-pathogen interaction pathway, and they showed a high level of expression in roots. Moreover, 10 DEGs were identified in the reported quantitative trait locus (QTL) interval of four-seed pod, and two of them were significantly enriched in the pentose and glucuronate interconversion pathway. These findings provide basic insights into the understanding of the underlying gene regulatory network affected by specific environment and lay the foundation for identifying the targets that affect the ratio of four-seed pod in soybean.

Ready, Steady, Go AI: A practical tutorial on fundamentals of artificial intelligence and its applications in phenomics image analysis

High-throughput image-based technologies are now widely used in the rapidly developing field of digital phenomics and are generating ever-increasing amounts and diversity of data. Artificial intelligence (AI) is becoming a game changer in turning the vast seas of data into valuable predictions and insights. However, this requires specialized programming skills and an in-depth understanding of machine learning, deep learning, and ensemble learning algorithms. Here, we attempt to methodically review the usage of different tools, technologies, and services available to the phenomics data community and show how they can be applied to selected problems in explainable AI-based image analysis. This tutorial provides practical and useful resources for novices and experts to harness the potential of the phenomic data in explainable AI-led breeding programs.

Non-Genetic Diversity in Chemosensing and Chemotactic Behavior

Non-genetic phenotypic diversity plays a significant role in the chemotactic behavior of bacteria, influencing how populations sense and respond to chemical stimuli. First, we review the molecular mechanisms that generate phenotypic diversity in bacterial chemotaxis. Next, we discuss the functional consequences of phenotypic diversity for the chemosensing and chemotactic performance of single cells and populations. Finally, we discuss mechanisms that modulate the amount of phenotypic diversity in chemosensory parameters in response to changes in the environment.

Individual reversible plasticity as a genotype-level bet-hedging strategy

Reversible plasticity in phenotypic traits allows organisms to cope with environmental variation within lifetimes, but costs of plasticity may limit just how well the phenotype matches the environmental optimum. An additional adaptive advantage of plasticity might be to reduce fitness variance, in other words: bet-hedging to maximize geometric (rather than simply arithmetic) mean fitness. Here, we model the evolution of plasticity in the form of reaction norm slopes, with increasing costs as the slope or degree of plasticity increases. We find that greater investment in plasticity (i.e. a steeper reaction norm slope) is favoured in scenarios promoting bet-hedging as a response to multiplicative fitness accumulation (i.e. coarser environmental grains and fewer time steps prior to reproduction), because plasticity lowers fitness variance across environmental conditions. In contrast, in scenarios with finer environmental grain and many time steps prior to reproduction, bet-hedging plays less of a role and individual-level optimization favours evolution of shallower reaction norm slopes. However, the opposite pattern holds if plasticity costs themselves result in increased fitness variation, as might be the case for production costs of plasticity that depend on how much change is made to the phenotype each time step. We discuss these contrasting predictions from this partitioning of adaptive plasticity into short-term individual benefits versus long-term genotypic (bet-hedging) benefits, and how this approach enhances our understanding of the evolution of optimum levels of plasticity in examples from thermal physiology to advances in avian lay dates.

Fitness value of information with delayed phenotype switching: Optimal performance with imperfect sensing

The ability of organisms to accurately sense their environment and respond accordingly is critical for evolutionary success. However, exactly how the sensory ability influences fitness is a topic of active research, while the necessity of a time delay between when unreliable environmental cues are sensed and when organisms can mount a response has yet to be explored at any length. Accounting for this delay in phenotype response in models of population growth, we find that a critical error probability can exist under certain environmental conditions: An organism with a sensory system with any error probability less than the critical value can achieve the same long-term growth rate as an organism with a perfect sensing system. We also observe a tradeoff between the evolutionary value of sensory information and robustness to error, mediated by the rate at which the phenotype distribution relaxes to steady state. The existence of the critical error probability could have several important evolutionary consequences, primarily that sensory systems operating at the nonzero critical error probability may be evolutionarily optimal.

Adaptive tuning of cell sensory diversity without changes in gene expression

In the face of uncertainty, cell populations tend to diversify to enhance survival and growth. Previous studies established that cells can optimize such bet hedging upon environmental change by modulating gene expression to adapt both the average and diversity of phenotypes. Here, we demonstrate that cells can tune phenotypic diversity also using posttranslational modifications. In the chemotaxis network of Escherichia coli, we find, for both major chemoreceptors Tar and Tsr, that cell-to-cell variation in response sensitivity is dynamically modulated depending on the presence or absence of their cognate chemoeffector ligands in the environment. Combining experiments with mathematical modeling, we show that this diversity tuning requires only the environment-dependent covalent modification of chemoreceptors and a standing cell-to-cell variation in their allosteric coupling. Thus, when environmental cues are unavailable, phenotypic diversity enhances the population's readiness for many signals. However, once a signal is perceived, the population focuses on tracking that signal.

Bioluminescence dynamics in single germinating bacterial spores reveal metabolic heterogeneity

Spore-forming bacteria modulate their metabolic rate by over five orders of magnitude as they transition between dormant spores and vegetative cells and thus represent an extreme case of phenotypic variation. During environmental changes in nutrient availability, clonal populations of spore-forming bacteria exhibit individual differences in cell fate, the timing of phenotypic transitions and gene expression. One potential source of this variability is metabolic heterogeneity, but this has not yet been measured, as existing single-cell methods are not easily applicable to spores due to their small size and strong autofluorescence. Here, we use the bacterial bioluminescence system and a highly sensitive microscope to measure metabolic dynamics in thousands of B. subtilis spores as they germinate. We observe and quantitate large variations in the bioluminescence dynamics across individual spores that can be decomposed into contributions from variability in germination timing, the amount of endogenously produced luminescence substrate and the intracellular reducing power. This work shows that quantitative measurement of spore metabolism is possible and thus it opens avenues for future study of the thermodynamic nature of dormant states.

A model for the interplay between plastic tradeoffs and evolution in changing environments

Performance tradeoffs are ubiquitous in both ecological and evolutionary modeling, yet they are usually postulated and built into fitness and ecological landscapes. However, tradeoffs depend on genetic background and evolutionary history and can themselves evolve. We present a simple model capable of capturing the key feedback loop: evolutionary history shapes tradeoff strength, which, in turn, shapes evolutionary future. One consequence of this feedback is that genomes with identical fitness can have different evolutionary properties shaped by prior environmental exposure. Another is that, generically, the best adaptations to one environment may evolve in another. Our simple framework bridges the gap between the phenotypic Fisher's Geometric Model and the genotypic properties, such as modularity and evolvability, and can serve as a rich playground for investigating evolution in multiple or changing environments.

Alternative responses to rare selection events are differentially vulnerable to changes in the frequency, scope, and intensity of environmental extremes

Extreme weather events are becoming more frequent, severe, and/or widespread as a consequence of anthropogenic climate change. While the economic and ecological implications of these changes have received considerable attention, the role of evolutionary processes in determining organismal responses to these critical challenges is currently unknown. Here we develop a novel theoretical framework that explores how alternative pathways for adaptation to rare selection events can influence population-level vulnerabilities to future changes in the frequency, scope, and intensity of environmental extremes. We begin by showing that different life histories and trait expression profiles can shift the balance between additive and multiplicative properties of fitness accumulation, favoring different evolutionary responses to identical environmental phenomena. We then demonstrate that these different adaptive outcomes lead to predictable differences in population-level vulnerabilities to rapid increases in the frequency, intensity, or scope of extreme weather events. Specifically, we show that when the primary mode of fitness accumulation is additive, evolution favors ignoring environmental extremes and lineages become highly vulnerable to extinction if the frequency or scope of extreme weather events suddenly increases. Conversely, when fitness accumulates primarily multiplicatively, evolution favors bet-hedging phenotypes that cope well with historical extremes and are instead vulnerable to sudden increases in extreme event intensity. Our findings address a critical gap in our understanding of the potential consequences of rare selection events and provide a relatively simple rubric for assessing the vulnerabilities of any population of interest to changes in a wide variety of extreme environmental phenomena.