Linking spatial drug heterogeneity to microbial growth dynamics in theory and experiment.

Diffusion and migration play pivotal roles in microbial communities - shaping, for example, colonization in new environments and the maintenance of spatial structures of biodiversity. While previous research has extensively studied free diffusion, such as range expansion, there remains a gap in understanding the effects of biologically or physically deleterious confined environments. In this study, we examine the interplay between migration and spatial drug heterogeneity within an experimental meta-community of .

Modeling spatial evolution of multi-drug resistance under drug environmental gradients.

Multi-drug combinations to treat bacterial populations are at the forefront of approaches for infection control and prevention of antibiotic resistance. Although the evolution of antibiotic resistance has been theoretically studied with mathematical population dynamics models, extensions to spatial dynamics remain rare in the literature, including in particular spatial evolution of multi-drug resistance. In this study, we propose a reaction-diffusion system that describes the multi-drug evolution of bacteria based on a drug-concentration rescaling approach.

Triggering Toll-Like Receptor 5 Signaling During Pneumococcal Superinfection Prevents the Selection of Antibiotic Resistance.

Toll-like receptor 5 (TLR5) signaling plays a key role in antibacterial defenses. We previously showed that respiratory administration of flagellin, a potent TLR5 agonist, in combination with amoxicillin (AMX) improves the treatment of primary pneumonia or superinfection caused by AMX-sensitive or AMX-resistant Streptococcus pneumoniae. Here, the impact of adjunct flagellin therapy on antibiotic dose/regimen and the selection of antibiotic-resistant S.

Pneumococcus and the stress-gradient hypothesis: A trade-off links R and susceptibility to co-colonization across countries.

Modern molecular technologies have revolutionized our understanding of bacterial epidemiology, but reported data across studies and different geographic endemic settings remain under-integrated in common theoretical frameworks. Pneumococcus serotype co-colonization, caused by the polymorphic bacteria Streptococcus pneumoniae, has been increasingly investigated and reported in recent years. While the global genomic diversity and serotype distribution of S.

Towards a mathematical understanding of invasion resistance in multispecies communities.

Multispecies community composition and dynamics are key to health and disease across biological systems, a prominent example being microbial ecosystems. Explaining the forces that govern diversity and resilience in the microbial consortia making up our body's defences remains a challenge. In this, theoretical models are crucial, to bridge the gap between species dynamics and underlying mechanisms and to develop analytic insight.

Modeling spatial evolution of multi-drug resistance under drug environmental gradients.

Multi-drug combinations to treat bacterial populations are at the forefront of approaches for infection control and prevention of antibiotic resistance. Although the evolution of antibiotic resistance has been theoretically studied with mathematical population dynamics models, extensions to spatial dynamics remain rare in the literature, including in particular spatial evolution of multi-drug resistance. In this study, we propose a reaction-diffusion system that describes the multi-drug evolution of bacteria, based on a rescaling approach (Gjini and Wood, 2021).

Quasi-neutral dynamics in a coinfection system with N strains and asymmetries along multiple traits.

Understanding the interplay of different traits in a co-infection system with multiple strains has many applications in ecology and epidemiology. Because of high dimensionality and complex feedback between traits manifested in infection and co-infection, the study of such systems remains a challenge. In the case where strains are similar (quasi-neutrality assumption), we can model trait variation as perturbations in parameters, which simplifies analysis.

Slow growing behavior in African trypanosomes during adipose tissue colonization.

When Trypanosoma brucei parasites, the causative agent of sleeping sickness, colonize the adipose tissue, they rewire gene expression. Whether this adaptation affects population behavior and disease treatment remained unknown. By using a mathematical model, we estimate that the population of adipose tissue forms (ATFs) proliferates slower than blood parasites.

Disentangling how multiple traits drive 2 strain frequencies in SIS dynamics with coinfection.

A general theory for competitive dynamics among many strains at the epidemiological level is required to understand polymorphisms in virulence, transmissibility, antibiotic resistance and other biological traits of infectious agents. Mathematical coinfection models have addressed specific systems, focusing on the criteria leading to stable coexistence or competitive exclusion, however, due to their complexity and nonlinearity, analytical solutions in coinfection models remain rare. Here we study a 2-strain Susceptible-Infected-Susceptible (SIS) compartmental model with co-infection/co-colonization, incorporating five strain fitness dimensions under the same framework: variation in transmissibility, duration of carriage, pairwise susceptibilities to coinfection, coinfection duration, and transmission priority effects from mixed coinfection.

Unsupervised learning approach for predicting sepsis onset in ICU patients.

Sepsis is a life-threatening condition caused by a deregulated host response to infection. If not diagnosed at an early stage, septic patients can go into a septic shock, associated with aggravated patient outcomes. Research has been mostly focused on predicting sepsis onset using supervised models that require big labeled datasets to train.

Price equation captures the role of drug interactions and collateral effects in the evolution of multidrug resistance.

Bacterial adaptation to antibiotic combinations depends on the joint inhibitory effects of the two drugs (drug interaction [DI]) and how resistance to one drug impacts resistance to the other (collateral effects [CE]). Here we model these evolutionary dynamics on two-dimensional phenotype spaces that leverage scaling relations between the drug-response surfaces of drug-sensitive (ancestral) and drug-resistant (mutant) populations. We show that evolved resistance to the component drugs - and in turn, the adaptation of growth rate - is governed by a Price equation whose covariance terms encode geometric features of both the two-drug-response surface (DI) in ancestral cells and the correlations between resistance levels to those drugs (CE).

The ratio of single to co-colonization is key to complexity in interacting systems with multiple strains.

The high number and diversity of microbial strains circulating in host populations have motivated extensive research on the mechanisms that maintain biodiversity. However, much of this work focuses on strain-specific and cross-immunity interactions. Another less explored mode of pairwise interaction is via altered susceptibilities to co-colonization in hosts already colonized by one strain.

Loss of α-gal during primate evolution enhanced antibody-effector function and resistance to bacterial sepsis.

Most mammals express a functional GGTA1 gene encoding the N-acetyllactosaminide α-1,3-galactosyltransferase enzyme, which synthesizes Gal-α1-3Gal-β1-4GlcNAc (α-gal) and are thus tolerant to this self-expressed glycan. Old World primates including humans, however, carry loss-of-function mutations in GGTA1 and lack α-gal. Presumably, fixation of such mutations was propelled by natural selection, favoring the emergence of α-gal-specific immunity, conferring resistance to α-gal-expressing pathogens.

Treatment timing shifts the benefits of short and long antibiotic treatment over infection.

Antibiotics are the major tool for treating bacterial infections. Rising antibiotic resistance, however, calls for a better use of antibiotics. While classical recommendations favor long and aggressive treatments, more recent clinical trials advocate for moderate regimens.

Predicting N-Strain Coexistence from Co-colonization Interactions: Epidemiology Meets Ecology and the Replicator Equation.

Multi-type infection processes are ubiquitous in ecology, epidemiology and social systems, but remain hard to analyze and to understand on a fundamental level. Here, we study a multi-strain susceptible-infected-susceptible model with coinfection. A host already colonized by one strain can become more or less vulnerable to co-colonization by a second strain, as a result of facilitating or competitive interactions between the two.

Modeling Competitive Mixtures With the Lotka-Volterra Framework for More Complex Fitness Assessment Between Strains.

With increasing resolution of microbial diversity at the genomic level, experimental and modeling frameworks that translate such diversity into phenotypes are highly needed. This is particularly important when comparing drug-resistant with drug-sensitive pathogen strains, when anticipating epidemiological implications of microbial diversity, and when designing control measures. Classical approaches quantify differences between microbial strains using the exponential growth model, and typically report a selection coefficient for the relative fitness differential between two strains.

Cell Competition, the Kinetics of Thymopoiesis, and Thymus Cellularity Are Regulated by Double-Negative 2 to 3 Early Thymocytes.

Cell competition in the thymus is a homeostatic process that drives turnover. If the process is impaired, thymopoiesis can be autonomously maintained for several weeks, but this causes leukemia. We aimed to understand the effect of cell competition on thymopoiesis, identify the cells involved, and determine how the process is regulated.

Renal control of disease tolerance to malaria.

Malaria, the disease caused by spp. infection, remains a major global cause of morbidity and mortality. Host protection from malaria relies on immune-driven resistance mechanisms that kill However, these mechanisms are not sufficient per se to avoid the development of severe forms of disease.

Transmission Fitness in Co-colonization and the Persistence of Bacterial Pathogens.

Humans are often colonized by polymorphic bacteria such as Streptococcus pneumoniae, Bordetella pertussis, Staphylococcus Aureus, and Haemophilus influenzae. Two co-colonizing pathogen clones may interact with each other upon host entry and during within-host dynamics, ranging from competition to facilitation. Here we examine the significance of these exploitation strategies for bacterial spread and persistence in host populations.

Geographic variation in pneumococcal vaccine efficacy estimated from dynamic modeling of epidemiological data post-PCV7.

Although mean efficacy of multivalent pneumococcus vaccines has been intensively studied, variance in vaccine efficacy (VE) has been overlooked. Different net individual protection across settings can be driven by environmental conditions, local serotype and clonal composition, as well as by socio-demographic and genetic host factors. Understanding efficacy variation has implications for population-level effectiveness and other eco-evolutionary feedbacks.

Integrating Antimicrobial Therapy with Host Immunity to Fight Drug-Resistant Infections: Classical vs. Adaptive Treatment.

Antimicrobial resistance of infectious agents is a growing problem worldwide. To prevent the continuing selection and spread of drug resistance, rational design of antibiotic treatment is needed, and the question of aggressive vs. moderate therapies is currently heatedly debated.

Expanding vaccine efficacy estimation with dynamic models fitted to cross-sectional prevalence data post-licensure.

The efficacy of vaccines is typically estimated prior to implementation, on the basis of randomized controlled trials. This does not preclude, however, subsequent assessment post-licensure, while mass-immunization and nonlinear transmission feedbacks are in place. In this paper we show how cross-sectional prevalence data post-vaccination can be interpreted in terms of pathogen transmission processes and vaccine parameters, using a dynamic epidemiological model.

A theoretical framework to identify invariant thresholds in infectious disease epidemiology.

Setting global strategies and targets for disease prevention and control often involves mathematical models. Model structure is typically subject to intense scrutiny, such as confrontation with empirical data and alternative formulations, while a less frequently challenged aspect is the widely adopted reduction of parameters to their average values. Focusing on endemic diseases, we use a general transmission model to explain how mean field approximations decrease the estimated R0 from prevalence data, while threshold phenomena - such as the epidemic and reinfection thresholds - remain invariant.

How direct competition shapes coexistence and vaccine effects in multi-strain pathogen systems.

We describe an integrated modeling framework for understanding strain coexistence in polymorphic pathogen systems. Previous studies have debated the utility of neutral formulations and focused on cross-immunity between strains as a major stabilizing mechanism. Here we convey that direct competition for colonization mediates stable coexistence only when competitive abilities amongst pathogen clones satisfy certain pairwise asymmetries.

Unveiling time in dose-response models to infer host susceptibility to pathogens.

The biological effects of interventions to control infectious diseases typically depend on the intensity of pathogen challenge. As much as the levels of natural pathogen circulation vary over time and geographical location, the development of invariant efficacy measures is of major importance, even if only indirectly inferrable. Here a method is introduced to assess host susceptibility to pathogens, and applied to a detailed dataset generated by challenging groups of insect hosts (Drosophila melanogaster) with a range of pathogen (Drosophila C Virus) doses and recording survival over time.