Can Immune Response Mechanisms Explain the Fecal Shedding Patterns of Cattle Infected with Mycobacterium avium Subspecies paratuberculosis?

Johne’s disease (JD) is a chronic disease in ruminants and is caused by infection with Mycobacterium avium subspecies paratuberculosis (MAP). At late stages of the disease, MAP bacilli are shed via feces excretion and in turn create the potential for oral-fecal transmission. The role of the host immune response in MAP bacteria shedding patterns at different stages of JD is still unclear. We employed mathematical modeling to predict if the variation in MAP shedding could be correlated to the immune response in infected animals. We used a novel inverse modeling approach that assumed biological interactions among the antigen-specific lymphocyte proliferation response (cell-mediated response), antibody/humoral immune responses, and MAP bacteria. The modeling framework was used to predict and test possible biological interactions between the measured variables and returns only the essential interactions that are relevant in explaining the observed cattle MAP experimental infection data. Through confronting the models with data, we predicted observed effects (enhancement or suppression) and extents of interactions among the three variables. This analysis enabled classification of the infected cattle into three different groups that correspond to the unique predicted immune responses that are essential to explain the data from cattle within these groups. Our analysis highlights the strong and weak points of the modeling approach, as well as the key immune mechanisms predicted to be expressed in all animals and those that were different between animals, hence giving insight into how animals exhibit different disease dynamics and bacteria shedding patterns

Predicting the Role of IL-10 in the Regulation of the Adaptive Immune Responses in Mycobacterium avium Subsp. paratuberculosis Infections Using Mathematical Models

Mycobacterium avium subsp. paratuberculosis (MAP) is an intracellular bacterial pathogen that causes Johne’s disease (JD) in cattle and other animals. The hallmark of MAP infection in the early stages is a strong protective cell-mediated immune response (Th1-type), characterized by antigen-specific γ-interferon (IFN-γ). The Th1 response wanes with disease progression and is supplanted by a non-protective humoral immune response (Th2-type). Interleukin-10 (IL-10) is believed to play a critical role in the regulation of host immune responses to MAP infection and potentially orchestrate the reversal of Th1/Th2 immune dominance during disease progression. However, how its role correlates with MAP infection remains to be completely deciphered. We developed mathematical models to explain probable mechanisms for IL-10 involvement in MAP infection. We tested our models with IL-4, IL-10, IFN-γ, and MAP fecal shedding data collected from calves that were experimentally infected and followed over a period of 360 days in the study of Stabel and Robbe-Austerman (2011). Our models predicted that IL-10 can have different roles during MAP infection, (i) it can suppress the Th1 expression, (ii) can enhance Th2 (IL-4) expression, and (iii) can suppress the Th1 expression in synergy with IL-4. In these predicted roles, suppression of Th1 responses was correlated with increased number of MAP. We also predicted that Th1-mediated responses (IFN-γ) can lead to high expression of IL-10 and that infection burden regulates Th2 suppression by the Th1 response. Our models highlight areas where more experimental data is required to refine our model assumptions, and further test and investigate the role of IL-10 in MAP infection

Inferring biomarkers for Mycobacterium avium subsp. paratuberculosis infection and disease progression in cattle using experimental data

Available diagnostic assays for Mycobacterium avium subsp. paratuberculosis (MAP) have poor sensitivities and cannot detect early stages of infection, therefore, there is need to find new diagnostic markers for early infection detection and disease stages. We analyzed longitudinal IFN-γ, ELISA-antibody and fecal shedding experimental sensitivity scores for MAP infection detection and disease progression. We used both statistical methods and dynamic mathematical models to (i) evaluate the empirical assays (ii) infer and explain biological mechanisms that affect the time evolution of the biomarkers, and (iii) predict disease stages of 57 animals that were naturally infected with MAP. This analysis confirms that the fecal test is the best marker for disease progression and illustrates that Th1/Th2 (IFN-γ/ELISA antibodies) assays are important for infection detection, but cannot reliably predict persistent infections. Our results show that the theoretical simulated macrophage-based assay is a potential good diagnostic marker for MAP persistent infections and predictor of disease specific stages. We therefore recommend specifically designed experiments to test the use of a based assay in the diagnosis of MAP infections

Examining the correlation between energy consumption and economic growth in selected SADC countries

Access to reliable energy that is especially modern and affordable, is a prerequisite for economic growth and improved quality of life. Accordingly, energy is an essential input for economic activity and human well-being. Estimates for technological advances in energy systems show that less than 30 percent of the population in sub Saharan Africa has access to affordable, reliable and modern forms of energy compared to 65 percent in South Asia and at least 90 percent in East Asia. Additionally, only 24.7 percent of the households in the southern most region of sub Saharan Africa have access to electricity, with biomass remaining the primary energy source. Focusing primarily on the Southern African region, this study used the time series analysis to investigate the causal relationship between energy consumption and economic growth in selected countries between 1980 and 2016. Regression analysis was used to establish the nature of the relationship between the variables. Lastly, the study predicted a 5-year energy consumption and economic growth using forecast models in Microsoft Excel. Variables were tested for statistical significance using granger causality tests. Results showed that there was a causality relationship between the two variables for Botswana and Zimbabwe. South Africa did not show any significance for analysis following the Granger causality test. Zimbabwe showed a very weak and negative linear relationship between energy consumption and economic growth. Overall, the results revealed that, in the short run, there was a bidirectional causality relationship between GDP per capita and electric power consumption per capita, and in the long run a unidirectional relationship running from GDP per capita to electric power consumption per capita. The overall findings of the study show that there is a corresponding relationship between energy consumption and economic growth. Therefore, improvements in energy generation are important for the economic development of SADC countries. Future studies may need to employ cointegration analyses to identify the degree to which variables are sensitive to the same average price over a specific period of time

Cellular and population plasticity of helper CD4(+) T cell responses

Vertebrates are constantly exposed to pathogens, and the adaptive immunity has most likely evolved to control and clear such infectious agents. CD4(+) T cells are the major players in the adaptive immune response to pathogens. Following recognition of pathogen-derived antigens naïve CD4(+) T cells differentiate into effectors which then control pathogen replication either directly by killing pathogen-infected cells or by assisting with generation of cytotoxic T lymphocytes (CTLs) or pathogen-specific antibodies. Pathogen-specific effector CD4(+) T cells are highly heterogeneous in terms of cytokines they produce. Three major subtypes of effector CD4(+) T cells have been identified: T-helper 1 (Th1) cells producing IFN-γ and TNF-α, Th2 cells producing IL-4 and IL-10, and Th17 cells producing IL-17. How this heterogeneity is maintained and what regulates changes in effector T cell composition during chronic infections remains poorly understood. In this review we discuss recent advances in our understanding of CD4(+) T cell differentiation in response to microbial infections. We propose that a change in the phenotype of pathogen-specific effector CD4(+) T cells during chronic infections, for example, from Th1 to Th2 response as observed in Mycobactrium avium ssp. paratuberculosis (MAP) infection of ruminants, can be achieved by conversion of T cells from one effector subset to another (cellular plasticity) or due to differences in kinetics (differentiation, proliferation, death) of different effector T cell subsets (population plasticity). We also shortly review mathematical models aimed at describing CD4(+) T cell differentiation and outline areas for future experimental and theoretical research. doi: 10.3389/fphys.2013.0020

Modelling within Host Parasite Dynamics of Schistosomiasis

Schistosomiasis infection is characterized by the presence of adult worms in the portal and mesenteric veins of humans as part of a complex migratory cycle initiated by cutaneous penetration of the cercariae shed by infected freshwater snails. The drug praziquantel is not always effective in the treatment against schistosomiasis at larvae stage. However, our simulations show that it is effective against mature worms and eggs. As a result, the study and understanding of immunological responses is key in understanding parasite dynamics. We therefore introduce quantitative interpretations of human immunological responses of the disease to formulate mathematical models for the within-host dynamics of schistosomiasis. We also use numerical simulations to demonstrate that it is the level of T cells that differentiates between either an effective immune response or some degree of infection. These cells are responsible for the differentiation and recruitment of eosinophils that are instrumental in clearing the parasite. From the model analysis, we conclude that control of infection is much attributed to the value of a function f, a measure of the average number of larvae penetrating a susceptible individual having hatched from an egg released by an infected individual. This agrees with evidence that there is a close association between the ecology, the distribution of infection and the disease

Ceftazidime-avibactam has potent sterilizing activity against highly drug-resistant tuberculosis.

There are currently many patients with multidrug-resistant and extensively drug-resistant tuberculosis. Ongoing transmission of the highly drug-resistant strains and high mortality despite treatment remain problematic. The current strategy of drug discovery and development takes up to a decade to bring a new drug to clinical use. We embarked on a strategy to screen all antibiotics in current use and examined them for use in tuberculosis. We found that ceftazidime-avibactam, which is already used in the clinic for multidrug-resistant Gram-negative bacillary infections, markedly killed rapidly growing, intracellular, and semidormant Mycobacterium tuberculosis in the hollow fiber system model. Moreover, multidrug-resistant and extensively drug-resistant clinical isolates demonstrated good ceftazidime-avibactam susceptibility profiles and were inhibited by clinically achievable concentrations. Resistance arose because of mutations in the transpeptidase domain of the penicillin-binding protein PonA1, suggesting that the drug kills M. tuberculosis bacilli via interference with cell wall remodeling. We identified concentrations (exposure targets) for optimal effect in tuberculosis, which we used with susceptibility results in computer-aided clinical trial simulations to identify doses for immediate clinical use as salvage therapy for adults and young children. Moreover, this work provides a roadmap for efficient and timely evaluation of antibiotics and optimization of clinically relevant dosing regimens

Can early host responses to mycobacterial infection predict eventual disease outcomes?

Diagnostic tests used for Johne’s disease in sheep either have poor sensitivity and specificity or only detect disease in later stages of infection. Predicting which of the infected sheep are likely to become infectious later in life is currently not feasible and continues to be a major hindrance in disease control. We conducted this longitudinal study to investigate if a suite of diagnostic tests conducted in Mycobacterium avium subspecies paratuberculosis (MAP) exposed lambs at 4 months post infection can accurately predict their clinical status at 12 months post infection. We tracked cellular and humoral responses and quantity of MAP shedding for up to 12 months post challenge in 20 controls and 37 exposed sheep. Infection was defined at necropsy by tissue culture and disease spectrum by lesion type. Data were analysed using univariable and multivariable logistic regression models and a subset of variables from the earliest period post inoculation (4 months) was selected for predicting disease outcomes later on (12 months). Sensitivity and specificity of tests and their combinations in series and parallel were determined. Early elevation in faecal MAP DNA quantity and a lower interferon gamma (IFNγ) response were significantly associated with sheep becoming infectious as well as progressing to severe disease. Conversely, early low faecal MAP DNA and higher interleukin-10 responses were significantly associated with an exposed animal developing protective immunity. Combination of early elevated faecal MAP DNA or lower IFNγ response had the highest sensitivity (75%) and specificity (81%) for identifying sheep that would become infectious. Collectively, these results highlight the potential for combined test interpretation to aid in the early prediction of sheep susceptibility to MAP infection. KEYWORDS: Paratuberculosis; diagnostic tests; Mycobacterium; faecal DNA; Johne’s disease; interferon gamma.This work was supported by Meat and Livestock Australia and by Cattle Council of Australia, Sheepmeat Council of Australia and WoolProducers Australia through Animal Health Australia

The specificity of phage testing for MAP — where might it fit into the diagnostic armoury?

The current individual tools available for the diagnosis of Johne's disease are far from suitable to tackle this endemic disease. Culture, polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) tests, when used together can be useful in managing the disease in the later stages of infection at a herd level. They are, however, ill-suited to detecting the causative agent Mycobacterium avium subsp. paratuberculosis (MAP) at the early stages of infection and at an individual level. Phage technology offers another tool in the attempt to better manage and control this disease. Phage-technology has been demonstrated to rapidly and sensitively detect and specifically identify viable MAP in the milk and blood of cattle. Although in relatively-early stages of development phage technology offers a strong addition to the armoury of tests used to detect MAP in blood and milk, and may go on to be part of ongoing control measures to reduce the burden of disease to farmers and veterinarians

Systems medicine and infection

By using a systems based approach, mathematical and computational techniques can be used to develop models that describe the important mechanisms involved in infectious diseases. An iterative approach to model development allows new discoveries to continually improve the model, and ultimately increase the accuracy of predictions. SIR models are used to describe epi demics, predicting the extent and spread of disease. Genome-wide genotyping and sequencing technologies can be used to identify the biological mechanisms behind diseases. These tools help to build strategies for disease prevention and treatment, an example being the recent outbreak of Ebola in West Africa where these techniques were deployed. HIV is a complex disease where much is still to be learnt about the virus and the best effective treatment. With basic mathematical modelling techniques, significant discoveries have been made over the last 20 years. With recent technological advances, the computation al resources now available and interdisciplinary cooperation, further breakthroughs are inevitable. In TB, modelling has traditionally been empirical in nature, with clinical data providing the fuel for this top-down approach. Recently, projects have begun to use data derived from laboratory experiments and clinical trials to create mathematical models that describe the mechanisms responsible for the disease. A systems medicine approach to infection modelling helps identify important biological questions that then direct future experiments , the results of which improve the model in an iterative cycle . This means that data from several model systems can be integrated and synthesised to explore complex biological systems .Postprin