Immune response to infection by Leishmania: A mathematical model

Treatment of leishmaniasis with chemotherapy and vaccine: a mathematical model

Leishmaniasis, an infectious disease, manifests itself mostly in two forms, cutaneous leishmaniasis (CL) and, a more severe and potentially deadly form, visceral leishmaniasis (VL). The current control strategy for leishmaniasis relies on chemotherapy drugs such as sodium antimony gluconate (SAG) and meglumine antimoniate (MA). However, all these chemotherapy compounds have poor efficacy, and they are associated with toxicity and other adverse effects, as well as drug resistance. While research in vaccine development for leishmaniasis is continuously progressing, no vaccine is currently available. However, some experimental vaccines such as LEISH-F1+MPL-SE (V) have demonstrated some efficacy when used as drugs for CL patients. In this paper we use a mathematical model to address the following question: To what extent vaccine shots can enhance the efficacy of standard chemotherapy treatment of leishmaniasis? Starting with standard MA treatment of leishmaniasis and combining it with three injections of V , we find, by Day 84, that efficacy increased from 29% to 65-91% depending on the amount of the vaccine. With two or just one injection of V , efficacy is still very high, but there is a definite resurgence of the disease by end-time.

Leishmania major Strain-Dependent Macrophage Activation Contributes to Pathogenicity in the Absence of Lymphocytes

Infection of C57BL/6 wild-type mice with Leishmania major 5-ASKH or Friedlin strains results in relatively similar pathogenicity with self-healing lesions within weeks. Parasite clearance depends on nitric oxide production by activated macrophages in response to cytokines produced mainly by CD4⁺ Th1 cells. In contrast, C57BL/6 Rag2 knockout mice, which lack T and B lymphocytes, show distinct pathologies during infection with these strains. Despite of the similar parasite number, the 5-ASKH infection induced severe inflammation rather than the Friedlin. To determine the immunological factors behind this phenomenon, we infected C57BL/6 Rag2 knockout mice with these two strains and compared immune cell kinetics and macrophage activation status. Compared with the Friedlin strain, the 5-ASKH strain elicited increased pathology associated with the accumulation of CD11b^high, Ly6G^high neutrophils by week four and increased the expression of macrophage activation markers. We then analyzed the differentially expressed transcripts in infected bone marrow-derived macrophages by RNA sequencing. It showed upregulation of multiple inflammatory transcripts, including Toll-like receptor 1/2 (TLR1/2), CD69, and CARD14, upon 5-ASKH infection. Our findings suggest that different L. major strains can trigger distinct macrophage activation, contributing to the disease outcome observed in the absence of lymphocytes but not in the presence of lymphocytes. IMPORTANCE Disease manifestations of cutaneous leishmaniasis (CL) range from self-healing cutaneous lesions to chronic forms of the disease, depending on the infecting Leishmania sp. and host immune protection. Previous works on mouse models of CL show the distinct pathogenicity of Leishmania major strains in the absence of lymphocytes. However, the mechanisms of this pathology remain uncovered. In the trial to understand the immunological process involved in lymphocyte-independent pathology, we have found a specific induction of macrophages by different L. major strains that affect their ability to mount innate responses leading to neutrophilic pathology when lymphocytes are ablated.

Computational Modeling of Macrophage Iron Sequestration during Host Defense against Aspergillus

Iron is essential to the virulence of Aspergillus species, and restricting iron availability is a critical mechanism of antimicrobial host defense. Macrophages recruited to the site of infection are at the crux of this process, employing multiple intersecting mechanisms to orchestrate iron sequestration from pathogens. To gain an integrated understanding of how this is achieved in aspergillosis, we generated a transcriptomic time series of the response of human monocyte-derived macrophages to Aspergillus and used this and the available literature to construct a mechanistic computational model of iron handling of macrophages during this infection. We found an overwhelming macrophage response beginning 2 to 4 h after exposure to the fungus, which included upregulated transcription of iron import proteins transferrin receptor-1, divalent metal transporter-1, and ZIP family transporters, and downregulated transcription of the iron exporter ferroportin. The computational model, based on a discrete dynamical systems framework, consisted of 21 3-state nodes, and was validated with additional experimental data that were not used in model generation. The model accurately captures the steady state and the trajectories of most of the quantitatively measured nodes. In the experimental data, we surprisingly found that transferrin receptor-1 upregulation preceded the induction of inflammatory cytokines, a feature that deviated from model predictions. Model simulations suggested that direct induction of transferrin receptor-1 (TfR1) after fungal recognition, independent of the iron regulatory protein-labile iron pool (IRP-LIP) system, explains this finding. We anticipate that this model will contribute to a quantitative understanding of iron regulation as a fundamental host defense mechanism during aspergillosis.

IMPORTANCE Invasive pulmonary aspergillosis is a major cause of death among immunosuppressed individuals despite the best available therapy. Depriving the pathogen of iron is an essential component of host defense in this infection, but the mechanisms by which the host achieves this are complex. To understand how recruited macrophages mediate iron deprivation during the infection, we developed and validated a mechanistic computational model that integrates the available information in the field. The insights provided by this approach can help in designing iron modulation therapies as anti-fungal treatments.

Mathematical modeling of the influence of cultural practices on cholera infections in Cameroon

The Far North Region of Cameroon, a high risk cholera endemic region, has been experiencing serious and recurrent cholera outbreaks in recent years. Cholera outbreaks in this region are associated with cultural practices (traditional and religious beliefs). In this paper, we introduce a mathematical model of the influence of cultural practices on the dynamics of cholera in the Far North Region. Our model is an SEIR type model with a pathogen class and multiple susceptible classes based on traditional and religious beliefs. Using daily reported cholera cases from three health districts (Kaélé, Kar Hay and Moutourwa) in the Far North Region from June 25, 2019 to August 16, 2019, we estimate parameter values of our model and use Akaike information criterion (AIC) to demonstrate that our model gives a good fit for our data on cholera cases. We use sensitivity analysis to study the impact of each model parameter on the threshold parameter (control reproduction number), R_c, and the number of model predicted cholera cases. Finally, we investigate the effect of cultural practices on the number of cholera cases in the region.

Mathematical Model of the Role of Asymptomatic Infection in Outbreaks of Some Emerging Pathogens

Preparation for outbreaks of emerging infectious diseases is often predicated on beliefs that we will be able to understand the epidemiological nature of an outbreak early into its inception. However, since many rare emerging diseases exhibit different epidemiological behaviors from outbreak to outbreak, early and accurate estimation of the epidemiological situation may not be straightforward in all cases. Previous studies have proposed considering the role of active asymptomatic infections co-emerging and co-circulating as part of the process of emergence of a novel pathogen. Thus far, consideration of the role of asymptomatic infections in emerging disease dynamics have usually avoided considering some important sets of influences. In this paper, we present and analyze a mathematical model to explore the hypothetical scenario that some (re)emerging diseases may actually be able to maintain stable, endemic circulation successfully in an entirely asymptomatic state. We argue that an understanding of this potential mechanism for diversity in observed epidemiological dynamics may be of considerable importance in understanding and preparing for outbreaks of novel and/or emerging diseases.

Leishmaniasis diagnosis: an update on the use of parasitological, immunological and molecular methods

Diagnosis of leishmaniasis has always been a major challenge as its clinical features resemble some other commonly occurring diseases such as tuberculosis, typhoid, and malaria. Reliable laboratory methods become important for differential diagnosis. Demonstration of the parasites in stained preparations of bone marrow and splenic aspirates being risky and invasive is still the gold standard for diagnosis. Serological tests utilizing rapid immunochromatographic formats or rK39 in enzyme linked immune sorbent assay, immunoblotting, direct agglutination test have complications related to high proportions of positive asymptomatic individuals and the inability to diagnose a relapse. Among the molecular techniques, polymerase chain reaction is the most commonly used technique that is successfully implied for diagnosis. This review provides updated information on the recent developments in the field of diagnosis in leishmaniasis, various methods utilized with their advantages and limitations.

Increase hemoglobin level in severe malarial anemia while controlling parasitemia: A mathematical model

Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine produced by immune cells; it can play a protective or deleterious role in response to pathogens. The intracellular malaria parasite secretes a similar protein, PMIF. The present paper is concerned with severe malarial anemia (SMA), where MIF suppresses the recruitment of red blood cells (RBCs) from the spleen and the bone marrow. This suppression results in a decrease of the hemoglobin (H_b) in the blood to a dangerous level. Indeed, SMA is responsible for the majority of death-related malaria cases. Artesunate is the first line of treatment of SMA; it accelerates the death of infected RBCs (iRBCs), thereby decreasing parasitemia. However, artesunate does not increase the level of H_b, and, in some cases, post-artesunate hemolytic anemia requires blood transfusion. In order to avoid this situation, we explore combining artesunate with another drug so that the H_b level is increased to healthy levels while parasitemia is still controlled. In this paper we show, by a mathematical model, that increasing the H_b levels while controlling parasitemia in malarial anemia can be done with the experimental drug Epoxyazadiradione (Epoxy) in combination with artesunate. Epoxy acts as MIF inhibitor and thus has the potential to increase the H_b level. Simulations of the model show that the two drugs compliment each other: while artesunate is primarily responsible for decreasing parasitemia, Epoxy is primarily responsible for increasing the hemoglobin level.

Spatial epidemiology of cutaneous leishmaniasis in Colombia: socioeconomic and demographic factors associated with a growing epidemic

BACKGROUND

Despite the identification of some environmental factors linked to the cutaneous leishmaniasis (CL) epidemic, little is known about the impact of environmental disturbances caused by human activities. We assessed the association between socioeconomic and demographic factors with the spatial structure of the CL epidemic in Colombia.

METHODS

Using data from more than 65 000 CL cases collected across the entire country from publicly available sources, we conducted a spatial clustering analysis to identify high burden areas (clusters) of CL. Associations between CL clusters and socioeconomic variables were investigated.

RESULTS

We identified seven statistically significant clusters of CL located across all Colombian biomes. Deforestation and livestock were statistically significantly associated with the spatial clustering of CL. Urbanization, time spent traveling to main cities and water bodies were other factors linked with the clustering of CL.

CONCLUSIONS

This study found that human activities such as deforestation linked to agriculture, livestock production and mining activities are key drivers of the spatial distribution of the CL epidemic. The intensity of these human activities, which are projected to increase because of social and economic transformations in progress in Colombia, will potentially exacerbate the already growing CL epidemic in the country.

Macrophage Polarization in Leishmaniasis: Broadening Horizons

Leishmaniasis is a vector-borne neglected tropical disease that affects more than 700,000 people annually. Leishmania parasites cause the disease, and different species trigger a distinct immune response and clinical manifestations. Macrophages are the final host cells for the proliferation of Leishmania parasites, and these cells are the key to a controlled or exacerbated response that culminates in clinical manifestations. M1 and M2 are the two main macrophage phenotypes. M1 is a pro-inflammatory subtype with microbicidal properties, and M2, or alternatively activated, is an anti-inflammatory/regulatory subtype that is related to inflammation resolution and tissue repair. The present review elucidates the roles of M1 and M2 polarization in leishmaniasis and highlights the role of the salivary components of the vector and the action of the parasite in the macrophage plasticity.

Dynamic balance of pro- and anti-inflammatory signals controls disease and limits pathology

Immune responses to pathogens are complex and not well understood in many diseases, and this is especially true for infections by persistent pathogens. One mechanism that allows for long-term control of infection while also preventing an over-zealous inflammatory response from causing extensive tissue damage is for the immune system to balance pro- and anti-inflammatory cells and signals. This balance is dynamic and the immune system responds to cues from both host and pathogen, maintaining a steady state across multiple scales through continuous feedback. Identifying the signals, cells, cytokines, and other immune response factors that mediate this balance over time has been difficult using traditional research strategies. Computational modeling studies based on data from traditional systems can identify how this balance contributes to immunity. Here we provide evidence from both experimental and mathematical/computational studies to support the concept of a dynamic balance operating during persistent and other infection scenarios. We focus mainly on tuberculosis, currently the leading cause of death due to infectious disease in the world, and also provide evidence for other infections. A better understanding of the dynamically balanced immune response can help shape treatment strategies that utilize both drugs and host-directed therapies.

Chronic hepatitis B virus and liver fibrosis: A mathematical model

Hepatitis B virus (HBV) infection is a liver disorder that can result in cirrhosis, liver failure and hepatocellular carcinoma. HBV infection remains a major global health problem, as it affects more 350 million people chronically and kills roughly 600,000 people annually. Drugs currently used against HBV include IFN-α that decreases viremia, inflammation and the growth of liver fibrosis, and adefovir that decreases the viral load. Each of these drugs can have severe side-effects. In the present paper, we consider the treatment of chronic HBV by a combination of IFN-α and adefovir, and raise the following question: What should be the optimal ratio between IFN-α and adefovir in order to achieve the best 'efficacy' under constraints on the total amount of the drugs; here the efficacy is measured by the reduction of the levels of inflammation and of fibrosis? We develop a mathematical model of HBV pathogenesis by a system of partial differential equations (PDEs) and use the model to simulate a 'synergy map' which addresses the above question.

Unbalanced inflammatory reaction could increase tissue destruction and worsen skin infectious diseases - a comparative study of leishmaniasis and sporotrichosis

The clinical presentations of skin diseases produced by different pathogens, as American tegumentary leishmaniasis (ATL) and sporotrichosis can be similar and possibly influenced by the skin immune system (SIS). The aim of the study was to understand the underlying mechanisms of skin inflammation produced by different pathogens. We used immunohistochemistry to analyze 96 patients: a- localized cutaneous leishmaniasis (LCL-ATL); b- sporotrichoid cutaneous leishmaniasis (SCL-ATL); c-lymphocutaneous (LC-SP); d- fixed (F-SP) sporotrichosis. LCL-ATL and SCL-ATL had a significantly higher percentage of CD8, FasL and NOS2 than sporotrichosis. In contrast, LC-SP had a substantially higher percentage of CD4, BCl2 and neutrophils than ATL lesions. These results indicated some differences in the profile of the in situ immune response suggesting that SIS is a complex, adaptable system capable of different responses to intracellular or extracellular pathogens. However, regardless of the etiological agents, the inflammatory reaction and clinical manifestations can be similar. SCL-ATL and LC-SP presented similarities in both clinical presentation and in situ inflammatory profile (CD3, CD22, neutrophils, macrophages). The clinical presentation of ATL and sporotrichosis could be explained by a combination of factors both of the host SIS and the etiological agent. The unbalanced host parasite relationship could result in atypical manifestations of skin disease.

Optimal control of vaccination rate in an epidemiological model of Clostridium difficile transmission

The spore-forming, gram-negative bacteria Clostridium difficile can cause severe intestinal illness. A striking increase in the number of cases of C. difficile infection (CDI) among hospitals has highlighted the need to better understand how to prevent the spread of CDI. In our paper, we modify and update a compartmental model of nosocomial C. difficile transmission to include vaccination. We then apply optimal control theory to determine the time-varying optimal vaccination rate that minimizes a combination of disease prevalence and spread in the hospital population as well as cost, in terms of time and money, associated with vaccination. Various hospital scenarios are considered, such as times of increased antibiotic prescription rate and times of outbreak, to see how such scenarios modify the optimal vaccination rate. By comparing the values of the objective functional with constant vaccination rates to those with time-varying optimal vaccination rates, we illustrate the benefits of time-varying controls.