Biology subjects

Baker, C. M.

Publications and source records attributed to Baker, C. M..

17 recordsLinked to original sources

bioRxiv2025

Estimating the impact of invasive pests and diseases on ecosystem services: modelling carbon sequestration loss due to myrtle rust (Austropuccinia psidii exotic strains) in Australia

The impacts of invasive pests and diseases are routinely estimated and measured in the context of agriculture, but less so in the context of biodiversity and ecosystem services. In this study, we estimate the potential reduction of carbon sequestration in Australia due to exotic strains of myrtle rust (Austropuccinia psidii, also known as Puccinia psidii, guava rust, or [o]hia rust). We model the contribution of susceptible plants to carbon sequestration and use previously known myrtle rust damage estimates to susceptible plant species and the valuation of carbon sequestration in Australia to estimate the potential monetary impact. This method can be systematically extended to other pests impacting plant growth as well as other ecosystem services. In the case of myrtle rust, we estimate that it could cause up to a 1.6% (95% CI: 1.3-2.0%) annual reduction in national carbon sequestration if it were to spread across all climatically suitable areas in Australia, resulting in an estimated value loss of over $340 million AUD (over $220 million USD) per year. Compared with contemporary syntheses of known cost estimates, our results show that the potential consequences of invasive species can be substantially larger than reported, and may be currently undervalued. Our work shows the need to systematically compile the potential impacts and costs to the environment and ecosystem services globally, to support both biosecurity decision-making and climate-change related initiatives such as net-zero emissions targets and reforestation efforts.

ecology↗

bioRxiv2025

Enhanced proconvulsant sensitivity, not spontaneous rapid swimming activity, is a robust correlate of scn1lab loss-of-function in stable mutant and F0 crispant hypopigmented zebrafish expressing GCaMP6s

Zebrafish models of genetic epilepsy benefit from the ability to assess disease-relevant knock-out alleles with numerous tools, including genetically encoded calcium indicators (GECIs) and hypopigmentation alleles to improve visualization. However, there may be unintended effects of these manipulations on the phenotypes under investigation. There is also debate regarding the use of stable loss-of-function (LoF) alleles in zebrafish, due to genetic compensation (GC). In the present study, we applied a method for combined movement and calcium fluorescence profiling to the study of a zebrafish model of SCN1A, the main gene associated with Dravet syndrome, which encodes the voltage-gated sodium channel alpha1 subunit (Nav1.1). We evaluated for spontaneous and proconvulsant-induced seizure-like activity associated with scn1lab LoF mutations in larval zebrafish expressing a neuronally-driven GECI (elavl3:GCaMP6s) and a nacre mutation causing a common pigmentation defect. In parallel studies of stable scn1labs552 mutants and F0 crispant larvae generated using a CRISPR/Cas9 multi-sgRNA approach, we find that neither stable nor acute F0 larvae recapitulate the previously reported seizure-like rapid swimming phenotype nor does either group show spontaneous calcium events meeting criteria for seizure-like activity based on a logistic classifier trained on movement and fluorescence features of proconvulsant-induced seizures. This constitutes two independent lines of evidence for a suppressive effect against the scn1lab phenotype, possibly due to the GCaMP6s-derived genetic background (AB) or nacre hypopigmentation. In response to the proconvulsant pentylenetetrazole (PTZ), we see evidence of a separate suppressive effect affecting all conspecific larvae derived from the stable scn1labs552 line, independent of genotype, possibly related to a maternal effect of scn1lab LoF in mutant parents or the residual TL background. Nonetheless, both stable and F0 crispant fish show enhanced sensitivity to PTZ relative to conspecific larvae, suggesting that proconvulsant sensitivity provides a more robust readout of scn1lab LoF under our experimental conditions. Our study underscores the unexpected challenges associated with the combination of common zebrafish tools with disease alleles in the phenotyping of zebrafish models of genetic epilepsy. Our work further highlights the advantages of using F0 crispants and the evaluation of proconvulsant sensitivity as complementary approaches that faithfully reflect the shared gene-specific pathophysiology underlying spontaneous seizures in stable mutant lines. Future work to understand the molecular mechanisms by which scn1lab-related seizures and PTZ-related hyperexcitability are suppressed under these conditions may shed light on factors contributing to variability in preclinical models of epilepsy more generally and may identify genetic modifiers relevant to Dravet syndrome.

neuroscience↗

bioRxiv2024

A real-time forecasting framework for emerging infectious diseases affecting animal populations

Infectious disease forecasting has become increasingly important in public health, as demonstrated during the COVID-19 pandemic. However, forecasting tools for emergency animal diseases, particularly those offering real-time decision support when parameters governing disease dynamics are unknown, remain limited. We introduce a generalised modelling framework for near-real-time forecasting of the temporal and spatial spread of infectious livestock diseases using data from the early stages of an outbreak. We applied the framework to the 2007 equine influenza outbreak in Australia, generating prediction targets at three timepoints across four regional clusters. Our targets included future daily case counts, outbreak size, peak timing and duration, and spatial distributions of future spread. We evaluated how well the forecasts predicted daily cases and the spatial distribution of case counts, using skill scores as a benchmark for future model improvements. Forecast accuracy, certainty, and skill improved significantly after the outbreaks peak, while early predictions were more variable, suggesting that pre-peak forecasts should be interpreted with caution. Spatial forecasts maintained positive skill throughout the outbreak, supporting their use in guiding response priorities. This framework provides a tool for real-time decision-making during livestock disease outbreaks and establishes a foundation for future refinements and applications to other animal diseases.

bioinformatics↗

bioRxiv2024

EEMtoolbox: A user-friendly R package for flexible ensemble ecosystem modeling

O_LIForecasting ecosystem changes due to disturbances or conservation interventions is essential to improve ecosystem management and anticipate unintended consequences of conservation decisions. Mathematical models allow practitioners to understand the potential effects and unintended consequences via simulation. However, calibrating these models is often challenging due to a paucity of appropriate ecological data. C_LIO_LIEnsemble ecosystem modelling (EEM) is a quantitative method used to parameterize models from theoretical ecosystem features rather than data. Two approaches have been considered to find parameter values satisfying those features: a standard accept-reject algorithm, appropriate for small ecosystem networks; and a sequential Monte Carlo (SMC) algorithm, that is more computationally efficient for larger networks. In practice, using SMC for EEM generation requires advanced statistical and mathematical knowledge, as well as strong programming skills, which might limit its uptake. In addition, current EEM approaches have been developed for only one model structure (generalized Lotka-Volterra). C_LIO_LITo facilitate the usage of EEM methods we introduce EEMtoolbox, an R package for calibrating quantitative ecosystem models. Our package allows the generation of parameter sets satisfying ecosystem features, by using either the standard accept-reject algorithm or the novel SMC procedure. Our package extends the existing EEM methodology, originally developed for the generalized Lotka-Volterra model, to two additional model structures (the multi-species Gompertz, and the Bimler-Baker model), and additionally allows users to define their own model structures. C_LIO_LIWe demonstrate the usage of EEMtoolbox by modelling the introduction of sihek (extinct-in-the-wild) on Palmyra Atoll in the Pacific Ocean. With its simple interface, our package facilitates straightforward generation of EEM parameter sets, thus unlocks advanced statistical methods supporting conservation decisions using ecosystem network models. C_LI

ecology↗

bioRxiv2024

A simple model of population dynamics with beneficial and harmful interaction networks for empirical applications.

O_LIPopulation dynamic models can forecast changes in the abundances of multiple interconnected species, which makes them potentially powerful tools for managing ecological communities, yet they remain largely under-utilised in applied settings. High data requirements and the ability to only model a narrow range of ecological interactions and/or trophic levels together limits their usefulness when faced with complex and data-poor systems, where beneficial (e.g. mutualism) and harmful (e.g. competition) interactions may operate simultaneously within and between species. C_LIO_LIWe present a model of population dynamics that can describe a wide range of ecological interaction outcomes with a simple, unified structure. Species growth rates are constrained by a maximum growth rate parameter which prevents the risk of population explosions even in the case of mutualism. Species interactions are defined by two, not mutually-exclusive interactions matrices that describe the effects of beneficial and harmful interactions respectively, together providing the potential for the net effect of interactions between one species and another to switch from beneficial to harmful as population density increases. C_LIO_LIThis model recreates classic dynamics in two-species mutualistic, competitive, and predator-prey scenarios, allowing us to model a wide range of trophic levels and interaction types together within the same equation. The maximum growth rate parameter, theoretically based in intrinsic constraints on reproduction, can be parameterised from a wide range of sources including natural history, historical data, and breeding programs. We illustrate the potential of this model with a data-poor case study of a threatened species and two interacting predators. C_LIO_LIThis new model is generaliseable to a wide range of natural ecological communities. Its model structure lowers data requirements whilst remaining intuitive and biologically realistic, making it an accessible option for predicting community-wide population changes in applied contexts where data is sparse and/or uncertain. C_LI

ecology↗

bioRxiv2024

Is testing the bee-all and end-all of varroa eradication?

Varroa destructor is a significant European honeybee pest, impacting agricultural industries globally. Since arriving in 2022, Australia faces the possibility that varroa will become established in European honeybee colonies nationally. Australia initially pursued a strategy of testing and subsequently eliminating hives infested with varroa. These management efforts raise interesting questions about the interplay between hive testing and elimination, and the spread of varroa between hives. This study uses mathematical modelling to investigate how combined hive testing and elimination strategies impact the spread of varroa through a network of European honeybee hives. We develop a model of both within-hive reproduction of varroa and hive testing, and between-hive movement of varroa on a network of hives. This model is used to assess the impact of various testing and hive elimination strategies on the total number of hives eliminated on the network of hives. Each model simulation starts with a single infested hive, and from this we observed one of two dynamics: either the infestation is caught before spreading, or varroa spreads extensively through the network before being caught by testing. Within our model we implement two common hive testing methods - sugar shake and alcohol testing. A shared limitation of these testing methods is that they can only detect mites in a specific stage of their lifecycle. As such, testing is not only dependent on how many varroa mites are in a hive, but what lifecycle stage the mites are in at the time of testing. By varying testing and movement parameters, we see that this testing limitation greatly impacts the number of hives eliminated in various scenarios. We find that there are largely two invasion possibilities: either there is only a small incursion, or that varroa achieves complete spread on the network. Furthermore, testing earlier, or testing more frequently, does not guarantee a smaller invasion. Our model results suggest irregular testing schedules, e.g. testing multiple times in close succession rather than just once in a given timeframe, may help overcome the limitations of common hive testing strategies.

ecology↗

bioRxiv2024

Zebrafish models of candidate human epilepsy-associated genes provide evidence of hyperexcitability

Hundreds of novel candidate human epilepsy-associated genes have been identified thanks to advancements in next-generation sequencing and large genome-wide association studies, but establishing genetic etiology requires functional validation. We generated a list of >2200 candidate epilepsy-associated genes, of which 81 were determined suitable for the generation of loss-of-function zebrafish models via CRISPR/Cas9 gene editing. Of those 81 crispants, 48 were successfully established as stable mutant lines and assessed for seizure-like swim patterns in a primary F2 screen. Evidence of seizure-like behavior was present in 5 (arfgef1, kcnd2, kcnv1, ubr5, wnt8b) of the 48 mutant lines assessed. Further characterization of those 5 lines provided evidence for epileptiform activity via electrophysiology in kcnd2 and wnt8b mutants. Additionally, arfgef1 and wnt8b mutants showed a decrease in the number of inhibitory interneurons in the optic tectum of larval animals. Furthermore, RNAseq revealed convergent transcriptional abnormalities between mutant lines, consistent with their developmental defects and hyperexcitable phenotypes. These zebrafish models provide strongest experimental evidence supporting the role of ARFGEF1, KCND2, and WNT8B in human epilepsy and further demonstrate the utility of this model system for evaluating candidate human epilepsy genes. HighlightsO_LIZebrafish models generated by CRISPR/Cas9 gene editing display seizure-like swim patterns in five candidate human epilepsy genes: arfgef1, kcnd2, kcnv1, ubr5, wnt8b. C_LIO_LILocal field potential abnormalities recorded from kcnd2 and wnt8b crispants provide additional evidence of hyperexcitability. C_LIO_LIArfgef1 and wnt8b mutant larvae have fewer inhibitory interneurons than wild type in the optic tectum. C_LIO_LICRISPR-generated mutants of epilepsy genes displayed convergent transcriptional dysregulation, consistent with developmental abnormalities and their hyperexcitability phenotype. C_LI

genetics↗

bioRxiv2023

Spatially resolved cell atlas of the teleost telencephalon and deep homology of the vertebrate forebrain

The telencephalon has undergone remarkable diversification and expansion throughout vertebrate evolution, exhibiting striking differences in structural and functional complexity. Nevertheless, fundamental features are shared across vertebrate taxa, such as the presence of distinct regions including the pallium, subpallium, and olfactory structures. Teleost fishes have a uniquely everted telencephalon, which has made it challenging to compare brain regions in fish to those in other vertebrates. Here we combine spatial transcriptomics and single-nucleus RNA-sequencing to generate a spatially-resolved transcriptional atlas of the cichlid fish telencephalon. We then compare cell-types and anatomical regions in the cichlid telencephalon with those in amphibians, reptiles, birds, and mammals. We uncover striking transcriptional similarities between cell populations in the fish telencephalon and subpallial, hippocampal, and cortical cell populations in tetrapods. Ultimately, our work lends new insights into the organization and evolution of conserved cell-types and regions in the vertebrate forebrain.

neuroscience↗

bioRxiv2023

A single neuron in C. elegans orchestrates multiple motor outputs through parallel modes of transmission

Animals generate a wide range of highly coordinated motor outputs, which allows them to execute purposeful behaviors. Individual neuron classes in the circuits that generate behavior have a remarkable capacity for flexibility, as they exhibit multiple axonal projections, transmitter systems, and modes of neural activity. How these multi-functional properties of neurons enable the generation of highly coordinated behaviors remains unknown. Here we show that the HSN neuron in C. elegans evokes multiple motor programs over different timescales to enable a suite of behavioral changes during egg-laying. Using HSN activity perturbations and in vivo calcium imaging, we show that HSN acutely increases egg-laying and locomotion while also biasing the animals towards low-speed dwelling behavior over longer timescales. The acute effects of HSN on egg-laying and high-speed locomotion are mediated by separate sets of HSN transmitters and different HSN axonal projections. The long-lasting effects on dwelling are mediated by HSN release of serotonin that is taken up and re-released by NSM, another serotonergic neuron class that directly evokes dwelling. Our results show how the multi-functional properties of a single neuron allow it to induce a coordinated suite of behaviors and also reveal for the first time that neurons can borrow serotonin from one another to control behavior.

neuroscience↗

bioRxiv2022

Multiscale modelling of invasive species control: the cane toad in Australia

O_LIThe cane toad (Bufo marinus) is an invasive species in Australia that has a negative impact on native species. Control methods such as trapping, fencing, and water exclusion have been devised to contain the spread of cane toads and reduce their ecological impact. However, implementing these interventions is expensive, and estimating the likely impact of a proposed intervention on spread at a large spatial scale, comprising one or more control methods, is challenging due to the lack of large-scale data and the computational cost of modelling a large number of toads. C_LIO_LITo address this challenge, we developed a multiscale model which uses individual-level data on cane toad behaviour to estimate the impact of trapping, fencing, and water exclusion when applied at scale in the Pilbara region in north-western Australia. Compared to previous work, our model allows us to explore more complex combinations and tradeoffs of control methods by utilising data sources at different scales. C_LIO_LIOur results suggest that exclusion of toads from water points is the most effective method for containing the spread of cane toads, and that trapping and fencing alone are unlikely to be sufficient. However, trapping and fencing are still useful supplementary measures in scenarios where exclusion cannot be broadly applied to a large number of water points. C_LIO_LISynthesis and applications. Our analyses highlight the importance of limiting access to sheltering and breeding sites in invasive species control. Furthermore, this study illustrates the value of multiscale computational models for exploring scenarios where parameters and calibration data are available at the scale of individuals and small groups, but management questions are framed at a much larger scale. C_LI

ecology↗

bioRxiv2022

The rediscovery of a relict unlocks the first global phylogeny of whip spiders (Amblypygi)

Asymmetrical rates of cladogenesis and extinction abound in the Tree of Life, resulting in numerous minute clades that are dwarfed by larger sister groups. Such taxa are commonly regarded as phylogenetic relicts or "living fossils" when they exhibit an ancient first appearance in the fossil record and prolonged external morphological stasis, particularly in comparison to their more diversified sister groups. Due to their special status, various phylogenetic relicts tend to be well-studied and prioritized for conservation. A notable exception to this trend is found within Amblypygi ("whip spiders"), a visually striking order of functionally hexapodous arachnids that are notable for their antenniform first walking leg pair (the eponymous "whips"). Paleoamblypygi, the putative sister group to the remaining Amblypygi, is known from Late Carboniferous and Eocene deposits, but is survived by a single living species, Paracharon caecus Hansen, 1921, that was last collected in 1899. Due to the absence of genomic sequence-grade tissue for this vital taxon, there is no global molecular phylogeny for Amblypygi to date, nor a fossil-calibrated estimation of divergences within the group. Here, we report several individuals of a previously unknown species of Paleoamblypygi from a cave site in Colombia. Capitalizing upon this discovery, we generated the first molecular phylogeny of Amblypygi, integrating ultraconserved element sequencing with legacy Sanger datasets and including described extant genera. To quantify the impact of sampling Paleoamblypygi on divergence time estimation, we performed in silico experiments with pruning of Paracharon. We demonstrate that the omission of relicts has a significant impact on the accuracy of node dating approaches that outweighs the impact of excluding ingroup fossils. Our results underscore the imperative for biodiversity discovery efforts in elucidating the phylogenetic relationships of "dark taxa", and especially phylogenetic relicts in tropical and subtropical habitats.

genomics↗

bioRxiv2021

Comprehensive species sampling and sophisticated algorithmic approaches refute the monophyly of Arachnida

Deciphering the evolutionary relationships of Chelicerata (arachnids, horseshoe crabs, and allied taxa) has proven notoriously difficult, due to their ancient rapid radiation and the incidence of elevated evolutionary rates in several lineages. While conflicting hypotheses prevail in morphological and molecular datasets alike, the monophyly of Arachnida is nearly universally accepted. Though a small number of phylotranscriptomic analyses have recovered arachnid monophyly, these did not sample all living chelicerate orders. We generated a dataset of 506 high-quality genomes and transcriptomes, sampling all living orders of Chelicerata with high occupancy and rigorous approaches to orthology inference. Our analyses consistently recovered the nested placement of horseshoe crabs within a paraphyletic Arachnida. This result was insensitive to variation in evolutionary rates of genes, complexity of the substitution models, and alternatives algorithmic approaches to species tree inference. Investigation of systematic bias showed that genes and sites that recover arachnid monophyly are enriched in noise and exhibit low information content. To test the effect of morphological data, we generated a 514-taxon morphological data matrix of extant and fossil Chelicerata, analyzed in tandem with the molecular matrix. Combined analyses recovered the clade Merostomata (the marine orders Xiphosura, Eurypterida, and Chasmataspidida), but nested within Arachnida. Our results suggest that morphological convergence resulting from adaptations to life in terrestrial habitats has driven the historical perception of arachnid monophyly, paralleling the history of numerous other invertebrate terrestrial groups.

evolutionary biology↗

bioRxiv2021

The genome of a daddy-long-legs (Opiliones) illuminates the evolution of arachnid appendages and chelicerate genome architecture

Chelicerates exhibit dynamic evolution of genome architecture, with multiple whole genome duplication events affecting groups like spiders, scorpions, and horseshoe crabs. Yet, genomes remain unavailable for several chelicerate orders, such as Opiliones (harvestmen), which has hindered comparative genomics and developmental genetics across arachnids. We assembled a draft genome of the daddy-long-legs Phalangium opilio, which revealed no signal of whole genome duplication. To test the hypothesis that single-copy Hox genes of the harvestman exhibit broader functions than subfunctionalized spider paralogs, we performed RNA interference against Deformed in P. opilio. Knockdown of Deformed incurred homeotic transformation of the two anterior pairs of walking legs into pedipalpal identity; by comparison, knockdown of the spatially restricted paralog Deformed-A in the spider affects only the first walking leg. To investigate the genetic basis for leg elongation and tarsomere patterning, we identified and interrogated the function of an Epidermal growth factor receptor (Egfr) homolog. Knockdown of Egfr incurred shortened appendages and the loss of distal leg structures. The overlapping phenotypic spectra of Egfr knockdown experiments in the harvestman and multiple insect models are striking because tarsomeres have evolved independently in these groups. Our results suggest a conserved role for Egfr in patterning distal leg structures across arthropods, as well as cooption of EGFR signaling in tarsomere patterning in both insects and arachnids. The establishment of genomic resources for P. opilio, together with functional investigations of appendage fate specification and distal patterning mechanisms, are key steps in understanding how daddy-long-legs make their long legs.

developmental biology↗

bioRxiv2020

Phylogenomics of scorpions reveal a co-diversification of scorpion mammalian predators and mammal-specific sodium channel toxins

Scorpions constitute a charismatic lineage of arthropods and comprise more than 2,500 described species. Found throughout various tropical and temperate habitats, these predatory arachnids have a long evolutionary history, with a fossil record that began in the Silurian. While all scorpions are venomous, the asymmetrically diverse family Buthidae harbors nearly half the diversity of extant scorpions, and all but one of the 58 species that are medically significant to humans. Many aspects of scorpion evolutionary history are unclear, such as the relationships of the most toxic genera and their constituent venom peptides. Furthermore, the diversification age of toxins that act specifically on mammalian ion channels have never been inferred. To redress these gaps, we assembled a large-scale phylogenomic dataset of 100 scorpion venom transcriptomes and/or genomes, emphasizing the sampling of highly toxic buthid genera. To infer divergence times of venom gene families, we applied a phylogenomic node dating approach for the species tree in tandem with phylostratigraphic bracketing to estimate minimum ages of mammal-specific toxins. Our analyses establish a robustly supported phylogeny of scorpions, particularly with regard to relationships between medically significant taxa. Analysis of venom gene families shows that mammal-specific sodium channel toxins have independently evolved in five lineages within Buthidae. The temporal windows of mammal-specific toxin origins are contiguous with the basal diversification of major scorpion mammal predators such as carnivores, shrews, bats and rodents. These results suggest an evolutionary arms race model comprised of co-diversification of mammalian predators and NaTx homologs in buthid venom.

evolutionary biology↗

bioRxiv2020

A neural circuit for flexible control of persistent behavioral states

To adapt to their environments, animals must generate behaviors that are closely aligned to a rapidly changing sensory world. However, behavioral states such as foraging or courtship typically persist over long time scales to ensure proper execution. It remains unclear how neural circuits generate persistent behavioral states while maintaining the flexibility to select among alternative states when the sensory context changes. Here, we elucidate the functional architecture of a neural circuit controlling the choice between roaming and dwelling states, which underlie exploration and exploitation during foraging in C. elegans. By imaging ensemble-level neural activity in freely-moving animals, we identify stable, circuit-wide activity patterns corresponding to each behavioral state. Combining circuit-wide imaging with genetic analysis, we find that mutual inhibition between two antagonistic neuromodulatory systems underlies the persistence and mutual exclusivity of the opposing network states. Through machine learning analysis and circuit perturbations, we identify a sensory processing neuron that can transmit information about food odors to both the roaming and dwelling circuits and bias the animal towards different states in different sensory contexts, giving rise to context-appropriate state transitions. Our findings reveal a potentially general circuit architecture that enables flexible, sensory-driven control of persistent behavioral states.

neuroscience↗

bioRxiv2019

Persistence is an optimal hedging strategy for bacteria in volatile environments

Bacteria invest in a slow-growing subpopulation, called persisters, to ensure survival in the face of uncertainty. This hedging strategy is remarkably similar to financial hedging, where diversifying an investment portfolio protects against economic uncertainty. We provide a new theoretical foundation for understanding cellular hedging by unifying the study of biological population dynamics and the mathematics of financial risk management through optimal control theory. Motivated by the widely accepted role of volatility in the emergence of persistence, we consider several novel models of environmental volatility described by continuous-time stochastic processes. This allows us to study an emergent cellular hedging strategy that maximizes the expected per-capita growth rate of the population. Analytical and simulation results probe the optimal persister strategy, revealing results that are consistent with experimental observations and suggest at new opportunities for experimental investigation and design. Overall, we provide a new way of conceptualising and modelling cellular decision-making in volatile environments by explicitly unifying theory from mathematical biology and finance.

systems biology↗

bioRxiv2019

Designing combination therapies using multiple optimal controls

Strategic management of populations of interacting biological species routinely requires interventions combining multiple treatments or therapies. This is important in key research areas such as ecology, epidemiology, wound healing and oncology. Despite the well developed theory and techniques for determining single optimal controls, there is limited practical guidance supporting implementation of combination therapies. In this work we use optimal control theory to calculate optimal strategies for applying combination therapies to a model of acute myeloid leukaemia. We consider various combinations of continuous and bang-bang (discrete) controls, and we investigate how the control dynamics interact and respond to changes in the weighting and form of the pay-off characterising optimality. We demonstrate that the optimal controls respond non-linearly to treatment strength and control parameters, due to the interactions between species. We discuss challenges in appropriately characterising optimality in a multiple control setting and provide practical guidance for applying multiple optimal controls. Code used in this work to implement multiple optimal controls is available on GitHub.

systems biology↗