Biology subjects

Jones, I. L.

Publications and source records attributed to Jones, I. L..

5 recordsLinked to original sources

bioRxiv2026

Adaptive immunity shapes baseline physiology of M. tuberculosis in high-dose versus low-dose infection BALB/c mouse drug treatment models

Preclinical tuberculosis (TB) drug evaluation relies heavily on mouse infection models. Drug efficacy varies depending on inoculum and the timing of treatment initiation. These differences reflect, in part, physiological adaptations of Mycobacterium tuberculosis (Mtb) to host immune pressure. We used novel molecular markers of pathogen health (RS ratio and SEARCH-TB) to contrast Mtb phenotypes in the BALB/c high dose aerosol (HDA) subacute TB and low dose aerosol (LDA) chronic TB infection models, focusing on the transition from innate to adaptive immunity. We found that the onset of adaptive immunity coincided with a rapid reprogramming of Mtb physiology, characterized by suppressed respiration, metabolism, and biosynthesis, together with induction of stress and nutrient acquisition pathways. Changes in key Mtb processes were concordant with changes in host expression of canonical features of adaptive immunity. Our results also explain key model-specific differences in drug efficacy: when used for drug evaluation, the HDA model begins treatment during the innate immune phase when Mtb are metabolically active, whereas the LDA model initiates therapy after host adaptive immunity has already activated and the bacterial population is immune-constrained. The HDA model is shown to be a mixed model, spanning immune phases with initial treatment acting on replicating bacteria and later treatment acting on immune-constrained populations. Together, the two models offer complementary perspectives on therapeutic activity across the spectrum of bacterial states and provide a framework for designing regimens that are effective against both active and immune-constrained Mtb.

genomics↗

bioRxiv2024

Spectinamide MBX-4888A exhibits favorable lesion and tissue distribution and promotes treatment shortening in advanced murine models of tuberculosis

The spectinamides are novel, narrow-spectrum semisynthetic analogs of spectinomycin, modified to avoid intrinsic efflux by Mycobacterium tuberculosis. Spectinamides, including lead MBX-4888A (Lee-1810), exhibit promising therapeutic profiles in mice, as single drugs and as partner agents with other anti-tuberculosis antibiotics including rifampin and/or pyrazinamide. To demonstrate that this translates to more effective cure, we first confirmed the role of rifampin, with or without pyrazinamide, as essential to achieve effective bactericidal responses and sterilizing cure in the current standard of care regimen in chronically infected C3HeB/FeJ mice compared to BALB/c mice. Thus, demonstrating added value in testing clinically relevant regimens in murine models of increasing pathologic complexity. Next we show that MBX-4888A, given by injection with the front-line standard of care regimen, is treatment shortening in multiple murine tuberculosis infection models. The positive treatment responses to MBX-4888A combination therapy in multiple mouse models including mice exhibiting advanced pulmonary disease can be attributed to favorable distribution in tissues and lesions, retention in caseum, along with favorable effects with rifampin and pyrazinamide under conditions achieved in necrotic lesions. This study also provides an additional data point regarding the safety and tolerability of spectinamide MBX-4888A in long-term murine efficacy studies.

microbiology↗

bioRxiv2023

The influence of diet on gut microbiome and body mass dynamics in a capital-breeding migratory bird

Gut-associated microbial communities are known to play a vital role in the health and fitness of their hosts. Though studies investigating the factors associated with among-individual variation in microbiome structure in wild animal species are increasing, knowledge of this variation at the individual level is scarce, despite the clear link between microbiome and nutritional status uncovered in humans and model organisms. Here, we combine detailed life history, foraging preference, and faecal microbiome data to investigate the relationship between diet, microbiome stability and rates of body mass gain in a migratory capital-breeding bird, the light-bellied Brent goose (Branta bernicla hrota). Our findings suggest that there is a significant relationship between foraging and the diversity, composition and stability of the faecal microbiome. We also suggest a link between foraging phenotype and the rates of mass gain during the spring staging of a capital breeder. This study offers rare insight into individual-level temporal dynamics of the gut microbiome of a wild host. Further work is needed to uncover the functional link between individual dietary choices, gut microbiome structure and stability, and the implications this has for the reproductive success of this capital breeder.

molecular biology↗

bioRxiv2021

Models as games: a novel approach for 'gamesourcing' parameter data and communicating complex models

1O_LIModels have become indispensable tools in conservation science in the face of increasingly rapid loss of biodiversity through anthropogenic habitat loss and natural resource exploitation. In addition to their ecological components, accurately representing human decision-making processes in such models is vital to maximise their utility. This can be problematic as modelling complexity increases, making them challenging to communicate and parameterise. C_LIO_LIGames have a long history of being used as science communication tools, but are less widely used as data collection tools, particularly in videogame form. We propose a novel approach to (1) aid communication of complex social-ecological models, and (2) "gamesource" human decision-making data, by explicitly casting an existing modelling framework as an interactive videogame. C_LIO_LIWe present players with a natural resource management game as a front-end to a social-ecological modelling framework (Generalised Management Strategy Evaluation, GMSE). Players actions replace a model algorithm making management decisions about a population of wild animals, which graze on crops and can thus lower agricultural yield. A number of non-player agents (farmers) respond through modelled algorithms to the players management, taking actions that may affect their crop yield as well as the animal population. Players are asked to set their own management goal (e.g. maintain the animal population at a certain level or improve yield) and make decisions accordingly. Trial players were also asked to provide any feedback on both gameplay and purpose. C_LIO_LIWe demonstrate the utility of this approach by collecting and analysing game play data from a sample of trial plays, in which we systematically vary two model parameters, and allowing trial players to interact with the model through the game interface. As an illustration, we show how variations in land ownership and the number of farmers in the system affects decision-making patterns as well as population trajectories (extinction probabilities). C_LIO_LIWe discuss the potential and limitations of this model-game approach in the light of trial player feedback received. In particular, we highlight how a common concern about the game framework (perceived lack of "realism" or relevance to a specific context) are actually criticisms of the underlying model, as opposed to the game itself. This further highlights both the parallels between games and models, as well as the utility of model-games to aid in communicating complex models. We conclude that videogames may be an effective tool for conservation and natural resource management, and that although they provide a promising means to collect data on human decision-making, it is vital to carefully consider both external validity and potential biases when doing so. C_LI

scientific communication and education↗

bioRxiv2017

GMSE: an R package for generalised management strategy evaluation

O_LIManagement strategy evaluation (MSE) is a powerful tool for simulating all key aspects of natural resource management under conditions of uncertainty.\nC_LIO_LIWe present the R package GMSE, which applies genetic algorithms to provide a generalised tool for simulating adaptive decision-making management scenarios between stakeholders with competing objectives under complex social-ecological interactions and uncertainty.\nC_LIO_LIGMSE models can be agent-based and spatially explicit, incorporating a high degree of realism through mechanistic modelling of links and feedbacks among stakeholders and with the ecosystem; additionally, user-defined sub-models can also be incorporated as functions into the broader GMSE framework.\nC_LIO_LIWe show how GMSE simulates a social-ecological system using the example of an adaptively managed waterfowl population on an agricultural landscape; simulated waterfowl exploit agricultural land, causing conflict between conservation interests and the interest of food producers maximising their crop yield.\nC_LIO_LIThe R package GMSE is open source under GNU Public License; source code and documents are freely available on GitHub.\nC_LI

ecology↗