Biology subjects

Vibishan, B.

Publications and source records attributed to Vibishan, B..

6 recordsLinked to original sources

bioRxiv2025

Impacts of competition and phenotypic plasticity on the viability of adaptive therapy

Cancer is heterogeneous and variability in drug sensitivity is widely documented across cancer types. Adaptive therapy is an emerging modality of cancer treatment that leverages this drug resistance heterogeneity to improve therapeutic outcomes. Current standard treatments typically eliminate a large fraction of drug-sensitive cells, leading to drug-resistant relapse due to competitive release. Adaptive therapy aims to retain some drug-sensitive cells, thereby limiting resistant cell growth by ecological competition. While early clinical trials of such a strategy have shown promise, optimisation of adaptive therapy is a subject of active study. Current methods largely assume cell phenotypes to remain constant, even though cell-state transitions could permit drug-sensitive and -resistant phenotypes to interchange and thus escape therapy. We address this gap using a deterministic model of population growth, in which sensitive and resistant cells grow under competition and undergo cell-state transitions. Based on the models steady-state behaviour and temporal dynamics, we identify distinct balances of competition and phenotypic transitions that are suitable for effective adaptive versus constant dose therapy. Our data indicate that under adaptive therapy, models with cell-state transitions show a higher frequency of fluctuations than those without, suggesting that the balance between ecological competition and phenotypic transitions could determine population-level dynamical properties. Our analyses also identify key limitations of applying phenomenological models in clinical practice for therapy design and implementation, particularly when cell-state transitions are involved. These findings provide an overall perspective on the relevance of phenotypic plasticity for emerging cancer treatment strategies using population dynamics as an investigation framework. Significance StatementDrug-sensitive and -resistant cancer cells can compete with each other within the same tumour, and adaptive therapy exploits this competition to control overall tumour growth. The fact that sensitive and resistant cell types can switch phenotypes complicates the implementation of adaptive therapy. Our ODE-based theoretical ecology framework shows that asymmetric competition favouring sensitive cells generally benefits therapy outcomes, while phenotypic plasticity is usually detrimental. Our model also provides cell population-level indicators that can help predict the underlying balance between competition and plasticity. Phenomenological models are limited by whether their parameters can be reliably identified given scarce data, and our study illuminates the scope of such models in understanding cancer population dynamics and the need for mechanistic modelling.

systems biology↗

bioRxiv2024

Costs of dispersal evolution under larval malnutrition

Dispersal is a key eco-evolutionary process, and the causes and consequences of its evolution have been well-studied. However, although dispersal depends critically on the nutritional status of organisms, it is unclear how malnutrition affects the evolution of life history and the behavior of organisms under selection for increased dispersal. To address this issue, we used four replicate laboratory populations of Drosophila melanogaster previously selected for increased dispersal for 66-67 generations on a protein-poor larval diet. Compared to the unselected controls, the selected populations had lower female body weight, fecundity, male desiccation resistance and mating propensity, but greater male locomotor activity and mating latency. There were no significant differences in aggression. We also compared our results qualitatively with those from a previous study on dispersal selection under a standard larval diet. Barring desiccation resistance, locomotor activity, and rest duration, all other traits investigated responded differently to dispersal selection between the poor and the standard larval nutritional regimes. These results show that the evolution of traits associated with dispersal can differ markedly depending on the nutrition available for the dispersing populations.

evolutionary biology↗

bioRxiv2024

Experimental evolution of Drosophila without its microbiome

In single-generation experiments, microbiome removal often affects multiple host traits. However, relatively little is understood about the long-term implications of living in a microbe-free environment. To address this question, we evolved four replicate laboratory populations of Drosophila melanogaster without microbes and compared their traits with corresponding control populations that were reared with microbiota. This comparison was done under two assay environments: with-microbes and microbe-free. Prior single-generation experiments on our populations had revealed that microbiota removal significantly affects multiple traits, which suggested that the flies were under strong selection pressure to adapt to the absence of microbes. However, contrary to our expectations, the selected populations underwent very modest changes even after 54-57 generations of selection. Moreover, the magnitude of change in trait values across the with- and without- microbe environments was less for the selected populations than for the controls. RNA-Seq on one of the evolutionary replicates revealed that compared to the control, some anti-microbial peptides (AMPs) in the selected population were up-regulated, while several heat shock proteins (HSPs) were down-regulated. These results suggest that robust host-microbiome integrations on short timescales can nevertheless be labile on longer timescales. We situate these results in the context of the "evolutionary addiction hypothesis" and the "hygiene hypothesis".

evolutionary biology↗

bioRxiv2023

Selection for dispersal under larval malnutrition results in a non-monotonic kernel in Drosophila melanogaster

Dispersal is a key strategy for organisms to track favorable conditions and a shifting global climate has necessitated its closer investigation. While the distribution of dispersal distances (i.e. dispersal kernel) influences several aspects of population ecology, it remains unclear how kernel features are themselves affected by environmental factors. The current study addresses this question using laboratory populations of Drosophila melanogaster selected for greater dispersal under a protein-deficient larval diet. Our results reveal that dispersal-selected populations initiate dispersal more often and travel further on average than unselected controls. Although there is a significant change in the overall kernel shape, selection has not led to a greater tendency for long-distance dispersal (LDD). This is contrary to the results from a previous study on dispersal evolution under standard nutrition. We also find that dispersal evolution under larval malnutrition leads to a non-monotonic dispersal kernel, with the highest frequencies at intermediate distances. The evolved shape of the dispersal kernel and the limited LDD phenotype therefore point to significant qualitative shifts in the evolution of the dispersal kernel due to a change in larval nutrition. Our results thus provide a starting point for further investigation of such context dependence in dispersal evolution.

evolutionary biology↗

bioRxiv2023

A resource-based mechanistic framework for castration-resistant prostate cancer (CRPC)

Cancer therapy often leads to the selective elimination of drug-sensitive cells from the tumour. This can favour the growth of cells resistant to the therapeutic agent, ultimately causing a tumour relapse. Castration-resistant prostate cancer (CRPC) is a well-characterised instance of this phenomenon. In CRPC, after systemic androgen deprivation therapy (ADT), a subset of drug-resistant cancer cells autonomously produce testosterone, thus enabling tumour regrowth. A previous theoretical study has shown that such a tumour relapse can be delayed by inhibiting the growth of drug-resistant cells using biotic competition from drug-sensitive cells. In this context, the centrality of resource dynamics to intra-tumour competition in the CRPC system indicates clear scope for the construction of theoretical models that can explicitly incorporate the underlying mechanisms of tumour ecology. In the current study, we use a modified logistic framework to model cell-cell interactions in terms of the production and consumption of resources. Our results show that steady state composition of CRPC can be understood as a composite function of the availability and utilisation efficiency of two resources-oxygen and testosterone. In particular, we show that the effect of changing resource availability or use efficiency is conditioned by their general abundance regimes. Testosterone typically functions in trace amounts and thus affects steady state behaviour of the CRPC system differently from oxygen, which is usually available at higher levels. Our data thus indicate that explicit consideration of resource dynamics can produce novel and useful mechanistic understanding of CRPC. Furthermore, such a modelling approach also incorporates variables into the systems description that can be directly measured in a clinical context. This is therefore a promising avenue of research in cancer ecology that could lead to therapeutic approaches that are more clearly rooted in the biology of CRPC. HighlightsO_LICancer growth and progression can be driven by intra-tumour interactions. C_LIO_LIProstate cancer cells compete among each other for resources like testosterone and oxygen. C_LIO_LIWe model these interactions using a modified logistic model with resource dynamics. C_LIO_LIEquilibrium behaviour can be understood through resource supply and use efficiency. C_LIO_LIExplicitly ecological models could enable better strategies for cancer control. C_LI

cancer biology↗

bioRxiv2019

Context-dependent selection as the keystone in somatic evolution of cancer

Somatic evolution of cancer involves a series of mutations, and attendant changes, in one or more clones of cells. A \"bad luck\" type model assumes chance accumulation of mutations. The clonal expansion model assumes, on the other hand, that any mutation leading to partial loss of regulation of cell proliferation will give a selective advantage to the mutant. However, a number of experiments show that an intermediate pre-cancer mutant has only a conditional selective advantage. Given that tissue microenvironmental conditions differ across individual organisms, this selective advantage to a mutant could be widely distributed over the population of organisms. We evaluate three models, namely \"bad luck\", context-independent, and -dependent selection, in a comparative framework, on their ability to predict patterns in total incidence, age-specific incidence, and their ability to explain Peto's paradox. Results show that context dependence is necessary and sufficient to explain observed epidemiological patterns, and that cancer incidence is largely selection-limited, rather than mutation-limited. A wide range of physiological, genetic and behavioural factors influence the tissue micro-environment, and could therefore be the source of this context dependence in somatic evolution of cancer. The identification and targeting of these micro-environmental factors that influence the dynamics of selection offer new possibilities for cancer prevention.

cancer biology↗