Showing papers by "Chaitanya S. Gokhale published in 2020"

Eco-evolutionary agriculture: Host-pathogen dynamics in crop rotations.

Abstract: Since its origins, thousands of years ago, agriculture has been challenged by the presence of evolving plant pathogens. Temporal rotations of host and non-host crops have helped farmers to control epidemics among other utilities, but further efforts for strategy assessment are needed. Here, we present a methodology for developing crop rotation strategies optimal for control of pathogens informed by numerical simulations of eco-evolutionary dynamics in one field. This approach can integrate agronomic criteria used in crop rotations-soil quality and cash yield-and the analysis of pathogen evolution in systems where hosts are artificially selected. Our analysis shows which rotation patterns perform better in maximising crop yield when an unspecified infection occurs, with yield being dependent on both soil quality and the strength of the epidemic. Importantly, the use of non-host crops, which both improve soil quality and control the epidemic results in similar rational rotation strategies for diverse agronomic and infection conditions. We test the repeatability of the best rotation patterns over multiple decades, an essential end-user goal. Our results provide sustainable strategies for optimal resource investment for increased food production and lead to further insights into the minimisation of pesticide use in a society demanding ever more efficient agriculture.

Memory shapes microbial populations

Abstract: Correct decision making is fundamental for all living organisms to thrive under environmental changes. The patterns of environmental variation and the quality of available information define the most favourable strategy among multiple options, including sensing and reacting to environmental cues or randomly adopting a phenotypic state. Memory -- a phenomenon often associated with, but not restricted to, higher multicellular organisms -- can help when temporal correlations exist. How does memory manifest itself in unicellular organisms? Through a combination of deterministic modelling and stochastic simulations, we describe the population-wide fitness consequences of phenotypic memory in microbial populations. Moving beyond binary switching models, our work highlights the need to consider a broader range of switching behaviours when describing microbial adaptive strategies. We show that multiple cellular states capture the empirical observations of lag time distributions, overshoots, and ultimately the phenomenon of phenotypic heterogeneity. We emphasise the implications of our work in understanding antibiotic tolerance, and, in general, survival under fluctuating environments.

How sequence populations persist inside a genome

Abstract: Compared to their eukaryotic counterparts, bacterial genomes are small and contain extremely tightly packed genes Therefore, discovering a large number of short repetitive sequences in the genomes of Pseudomonads and Enterobacteria is unexpected These sequences can independently replicate in the host genome and form populations that persist for millions of years Here we model the interactions of intragenomic sequence populations with the bacterial host In a simple model, sequence populations either expand until they drive the host to extinction or the sequence population gets purged from the genome Including horizontal gene transfer does not change the qualitative outcome of the model and leads to the extinction of the sequence population However, a sequence population can be stably maintained, if each sequence provides a benefit that decreases with increasing sequence population size But concurrently, the replication of the sequence population needs to be costly to the host Surprisingly, in regimes where horizontal gene transfer plays a role, the benefit conferred by the sequence population does not have to exceed the damage it causes Together, our analyses provide a plausible scenario for the persistence of sequence populations in bacterial genomes More importantly, we hypothesize a limited biologically relevant parameter range, which can be tested in future experiments

Synthetic Symbiosis under Environmental Disturbances.

Abstract: By virtue of complex ecologies, the behavior of mutualisms is challenging to study and nearly impossible to predict. However, laboratory engineered mutualistic systems facilitate a better understanding of their bare essentials. On the basis of an abstract theoretical model and a modifiable experimental yeast system, we explore the environmental limits of self-organized cooperation based on the production and use of specific metabolites. We develop and test the assumptions and stability of the theoretical model by leveraging the simplicity of an artificial yeast system as a simple model of mutualism. We examine how one-off, recurring, and permanent changes to an ecological niche affect a cooperative interaction and change the population composition of an engineered mutualistic system. Moreover, we explore how the cellular burden of cooperating influences the stability of mutualism and how environmental changes shape this stability. Our results highlight the fragility of mutualisms and suggest interventions, including those that rely on the use of synthetic biology. IMPORTANCE The power of synthetic biology is immense. Will it, however, be able to withstand the environmental pressures once released in the wild. As new technologies aim to do precisely the same, we use a much simpler model to test mathematically the effect of a changing environment on a synthetic biological system. We assume that the system is successful if it maintains proportions close to what we observe in the laboratory. Extreme deviations from the expected equilibrium are possible as the environment changes. Our study provides the conditions and the designer specifications which may need to be incorporated in the synthetic systems if we want such “ecoblocs” to survive in the wild.

Consequences of combining life-history traits with sex-specific differences

Abstract: Males and females evolved distinct life-history strategies, reflected in diverse life-history traits, summarized as sexual dimorphism. Life-history traits are highly interlinked. The sex that allocates more resources towards offspring is expected to increase its life span, and this might require an efficient immune system. However, the other sex might allocate its resources towards ornamentation, and this might have immunosuppressive effects. Activity of immune response may not be specific to the sex that produces the eggs but could correlate with the amount of parental investment given. Informed by experimental data, we designed a theoretical framework that combines multiple life-history traits. We disentangled sex-biased life-history strategies from a particular sex to include species with reversed sex-roles, and male parental investment. We computed the lifetime reproductive success from the fitness components arising from diverse sex-biased life-history traits, and observed a strong bias in adult sex ratio depending on sex-specific resource allocation towards life-history traits. Overall, our work provides a generalized method to combine various life-history traits with sex-specific differences to calculate the lifetime reproductive success. This was used to explain certain empirical observations as a consequence of sexual dimorphism in life-history traits.

On the mechanistic roots of an ecological law: parasite aggregation

Abstract: Parasite aggregation, a recurring pattern in macroparasite infections, is considered one of the "laws" of parasite ecology. Few hosts have a large number of parasites while most hosts have a low number of parasites. Phenomenological models of host-parasite systems thus use the negative-binomial distribution. However, to infer the mechanisms of aggregation, a mechanistic model that does not make any a priori assumptions is essential. Here we formulate a mechanistic model of parasite aggregation in hosts without assuming a negative-binomial distribution. Our results show that a simple model of parasite accumulation still results in an aggregated pattern, as shown by the derived mean and variance of the parasite distribution. By incorporating the derived statistics in host-parasite interactions, we can predict how aggregation affects the population dynamics of the hosts and parasites through time. Thus, our results can directly be applied to observed data as well as can inform the designing of statistical sampling procedures. Overall, we have shown how a plausible mechanistic process can result in the often observed phenomenon of parasite aggregation occurring in numerous ecological scenarios, thus providing a basis for a ``law" of ecology.

A unifying approach to gene drive

Abstract: Synthetic gene drive technologies aim to spread transgenic constructs into wild populations even when they impose organismal fitness disadvantages. The properties of gene drive constructs are diverse and depend on their molecular construction, and differential selection pressure they impose in the varied ecological situations they encounter. The extraordinary diversity of conceivable drive mechanisms and the range of selective parameters they may encounter makes it very difficult to convey their relative predicted properties. The sheer number of published manuscripts in this field, experimental and theoretical, is a testament to the possibilities presented by this technology. We evaluate and condense the essential synthetic drive mechanisms from a variety of studies and present a unified mathematical paradigm (and a user-friendly tool DrMxR Drive Mixer) describing the properties of a wide variety of single construct gene drives (non-suppression). Within this common framework, we have been able to recapitulate key published results derived using bespoke modelling frameworks. Because a unified framework is employed, it is also possible to seamlessly explore the consequences of combining multiple drive approaches within a single construct. We provide a method for analytically assessing the measure of invasiveness of a drive construct. As opposed to typical studies of synthetic drives, we explore the resilience of such drives in a spatially explicit manner advancing the connection between realistic spatial dynamics and typical well-mixed populations. Besides a scientific advance, our results and the tools provided an intuitive and objective way for regulators, scientists and NGOs to evaluate the properties and robustness of proposed and future gene drive approaches.

Eco-evolutionary spatial dynamics of non-linear social dilemmas

Abstract: Spatial dynamics can promote the evolution of cooperation. While dispersal processes have been studied in simple evolutionary games, real-world social dilemmas are much more complicated. When the investment is low, for example, every additional unit of investment may substantially raise the public goods. However, the effect vanishes as the number of investments increases. Such nonlinear public goods are the norm in a variety of social as well as biological systems. Therefore, we investigate the effect of the nonlinearity on the evolution of cooperation. We show how the nonlinearity in payoffs, resulting in synergy or discounting of public goods, can alter the return on the cooperative investments compared to the linear game. The alteration affects the resulting spatial patterns, not just quantitatively, but in some cases, drastically changing the outcomes. Notably, in cases where a linear game would lead to extinction, synergy can support the coexistence of cooperators and defectors. The eco-evolutionary trajectory can thus be qualitatively different in cases on nonlinear social dilemmas.

Consequences of combining sex-specific life-history traits

Abstract: Males and females follow distinct life-history strategies that have co-evolved with several sex-specific traits Higher investment into parental investment demands an increased lifespan Thus, resource allocation towards an efficient immune system is mandatory In contrast, resources allocated towards secondary sexual signals (ornamentation) may negatively correlate with investment into immunity and ultimately result in a shorter lifespan Previous studies have addressed how resource allocation towards single sex-specific traits impacts lifetime reproductive success (LRS) However, the tradeoffs between diverse sex-specific characteristics and their impact on LRS remain largely unassessed impeding our understanding of life-history evolution We have designed a theoretical framework (informed by experimental data and evolutionary genetics) that explores the effects of multiple sex-specific traits and assessed how they influence LRS From the individual sex-specific traits, we inferred the consequences at the population level by evaluating adult sex ratios (ASR) Our theory implies that sex-specific resource allocation towards the assessed traits resulted in a biased ASR Our model focuses on the impact of parental investment, ornamentation and immunity as causal to biased ASR The framework developed herein can be employed to understand the combined impact of diverse sex-specific traits on the LRS and the eventual population dynamics of particular model systems

On the fitness of informative cues in complex environments

Abstract: To be able to deal with uncertainty is of primary importance to all organisms. When cues provide information about the state of the environment, organisms can use them to respond flexibly. Thus information can provide fitness advantages. Without environmental cues, an organism can reduce the risks of environmental uncertainty by hedging its bets across different scenarios. Risk mitigation is then possible by adopting a life-history of bet-hedging, either randomly switching between phenotypes (diversifying bet-hedging) or adopting intermediate phenotypes (conservative bet-hedging). Hence, understanding patterns of bet-hedging is necessary in order to quantify the fitness benefit of environmental cues, since it provides a baseline fitness in the absence of informative cues. Quantifying fitness benefits in terms of mutual information reveals deep connections between Darwinian evolution and information theory. However, physiological constraints or complex ecological scenarios often lead to the number of environmental states to exceed that of potential phenotypes, or a single intermediate phenotype is adopted, as in the case of conservative bet-hedging. Incorporating these biological complexities, we generalise the relationship between information theory and Darwinian fitness. Sophisticated bet-hedging strategies - combining diversifying and conservative bet-hedging - can then evolve. We show that, counterintuitively, environmental complexity can reduce, rather than increase, the number of phenotypes that an organism can adopt. In conclusion, we develop an information-theoretic extensible approach for investigating and quantifying fitness in ecological studies.