Immune response dynamics in horses after vaccination against leptospirosis

Mapping the dynamics of immune cell populations over time or disease-course is key to understanding immunopathogenesis and devising putative interventions. We present TrackSOM, an algorithm which delineates cellular populations and tracks their development over a time- or disease-course of cytometry datasets. We demonstrate TrackSOM-enabled elucidation of the immune response to West Nile Virus infection in mice, uncovering heterogeneous sub-populations of immune cells and relating their functional evolution to disease severity. TrackSOM is easy to use, encompasses few parameters, is quick to execute, and enables an integrative and dynamic overview of the immune system kinetics that underlie disease progression and/or resolution.

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Regulation of Immune Response Dynamics

10.1201/9780429286070 ◽

2019 ◽

Keyword(s):

Immune Response ◽

Response Dynamics

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AN IMMUNO-EPIDEMIOLOGICAL VECTOR–HOST MODEL WITH WITHIN-VECTOR VIRAL KINETICS

Journal of Biological System ◽

10.1142/s0218339020400021 ◽

2020 ◽

Vol 28 (02) ◽

pp. 233-275 ◽

Cited By ~ 1

Author(s):

HAYRIYE GULBUDAK

Keyword(s):

Immune Response ◽

Disease Modeling ◽

Control Strategies ◽

Inoculum Size ◽

Disease Spread ◽

Positive Equilibrium ◽

Asymptotically Stable ◽

Response Dynamics ◽

Viral Kinetics ◽

Vector Borne Diseases

A current challenge for disease modeling and public health is understanding pathogen dynamics across scales since their ecology and evolution ultimately operate on several coupled scales. This is particularly true for vector-borne diseases, where within-vector, within-host, and between vector–host populations all play crucial roles in diversity and distribution of the pathogen. Despite recent modeling efforts to determine the effect of within-host virus-immune response dynamics on between-host transmission, the role of within-vector viral dynamics on disease spread is overlooked. Here, we formulate an age-since-infection-structured epidemic model coupled to nonlinear ordinary differential equations describing within-host immune-virus dynamics and within-vector viral kinetics, with feedbacks across these scales. We first define the within-host viral-immune response and within-vector viral kinetics-dependent basic reproduction number [Formula: see text] Then we prove that whenever [Formula: see text] the disease-free equilibrium is locally asymptotically stable, and under certain biologically interpretable conditions, globally asymptotically stable. Otherwise, if [Formula: see text] it is unstable and the system has a unique positive endemic equilibrium. In the special case of constant vector to host inoculum size, we show the positive equilibrium is locally asymptotically stable and the disease is weakly uniformly persistent. Furthermore, numerical results suggest that within-vector-viral kinetics and dynamic inoculum size may play a substantial role in epidemics. Finally, we address how the model can be utilized to better predict the success of control strategies such as vaccination and drug treatment.

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Immune response dynamics and Lutzomyia longipalpis exposure characterize a biosignature of visceral leishmaniasis susceptibility in a canine cohort

PLoS Neglected Tropical Diseases ◽

10.1371/journal.pntd.0009137 ◽

2021 ◽

Vol 15 (2) ◽

pp. e0009137

Author(s):

Manuela da Silva Solcà ◽

Maiara Reis Arruda ◽

Bruna Martins Macedo Leite ◽

Tiago Feitosa Mota ◽

Miriam Flores Rebouças ◽

...

Keyword(s):

Immune Response ◽

Visceral Leishmaniasis ◽

Clinical Manifestations ◽

Parasite Load ◽

Serum Levels ◽

Lutzomyia Longipalpis ◽

Response Dynamics ◽

Before And After ◽

One Year

Background Reports have shown correlations between the immune response to vector saliva and Leishmaniasis outcome. We followed dogs in an endemic area for two years characterizing resistance or susceptibility to canine visceral leishmaniasis (CVL) according to Leishmania infantum diagnosis and clinical development criteria. Then, we aimed to identify a biosignature based on parasite load, serum biological mediators’ interactions, and vector exposure intensity associated with CVL resistance and susceptibility. Methodology/Principal findings A prospective two-year study was conducted in an area endemic for CVL. Dogs were evaluated at 6-month intervals to determine infection, clinical manifestations, immune profile, and sandfly exposure. CVL resistance or susceptibility was determined upon the conclusion of the study. After two years, 78% of the dogs were infected with L. infantum (53% susceptible and 47% resistant to CVL). Susceptible dogs presented higher splenic parasite load as well as persistence of the parasite during the follow-up, compared to resistant ones. Susceptible dogs also displayed a higher number of correlations among the investigated biological mediators, before and after infection diagnosis. At baseline, anti-saliva antibodies, indicative of exposure to the vector, were detected in 62% of the dogs, reaching 100% in one year. Higher sandfly exposure increased the risk of susceptibility to CVL by 1.6 times (CI: 1.11–2.41). We identified a discriminatory biosignature between the resistant and susceptible dogs assessing splenic parasite load, interaction of biological mediators, PGE2 serum levels and intensity of exposure to sandfly. All these parameters were elevated in susceptible dogs compared to resistant animals. Conclusions/Significance The biosignature identified in our study reinforces the idea that CVL is a complex multifactorial disease that is affected by a set of factors which are correlated and, for a better understanding of CVL, should not be evaluated in an isolated way.

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Regulation of immune response dynamics

Mathematical Biosciences ◽

10.1016/0025-5564(84)90102-0 ◽

1984 ◽

Vol 70 (2) ◽

pp. 269-270

Author(s):

George Bell

Keyword(s):

Immune Response ◽

Response Dynamics

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Mechanistic Modeling of Mycobacterium tuberculosis Infection in Murine Models for Drug and Vaccine Efficacy Studies

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.01727-19 ◽

2020 ◽

Vol 64 (3) ◽

Author(s):

Nan Zhang ◽

Natasha Strydom ◽

Sandeep Tyagi ◽

Heena Soni ◽

Rokeya Tasneen ◽

...

Keyword(s):

Immune Response ◽

Mycobacterium Tuberculosis ◽

Vaccine Efficacy ◽

Vaccine Development ◽

Bacterial Load ◽

Mechanistic Modeling ◽

Response Dynamics ◽

Content Type ◽

Immune Effect ◽

Adaptive Immune

ABSTRACT Tuberculosis (TB) drug, regimen, and vaccine development rely heavily on preclinical animal experiments, and quantification of bacterial and immune response dynamics is essential for understanding drug and vaccine efficacy. A mechanism-based model was built to describe Mycobacterium tuberculosis H37Rv infection over time in BALB/c and athymic nude mice, which consisted of bacterial replication, bacterial death, and adaptive immune effects. The adaptive immune effect was best described by a sigmoidal function on both bacterial load and incubation time. Applications to demonstrate the utility of this baseline model showed (i) the important influence of the adaptive immune response on pyrazinamide (PZA) drug efficacy, (ii) a persistent adaptive immune effect in mice relapsing after chemotherapy cessation, and (iii) the protective effect of vaccines after M. tuberculosis challenge. These findings demonstrate the utility of our model for describing M. tuberculosis infection and corresponding adaptive immune dynamics for evaluating the efficacy of TB drugs, regimens, and vaccines.

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The Dynamics of Germinal Centre Selection as Measured by Graph-Theoretical Analysis of Mutational Lineage Trees

Developmental Immunology ◽

10.1080/10446670310001593541 ◽

2002 ◽

Vol 9 (4) ◽

pp. 233-243 ◽

Cited By ~ 40

Author(s):

Deborah K. Dunn-Walters ◽

Alex Belelovsky ◽

Hanna Edelman ◽

Monica Banerjee ◽

Ramit Mehr

Keyword(s):

Immune Response ◽

Theoretical Analysis ◽

Shape Analysis ◽

Humoral Immune Response ◽

Clonal Selection ◽

Selection Process ◽

Response Dynamics ◽

Humoral Immune ◽

Graph Theoretical Analysis ◽

Lineage Trees

We have developed a rigorous graph-theoretical algorithm for quantifying the shape properties of mutational lineage trees. We show that information about the dynamics of hypermutation and antigen-driven clonal selection during the humoral immune response is contained in the shape of mutational lineage trees deduced from the responding clones. Age and tissue related differences in the selection process can be studied using this method. Thus, tree shape analysis can be used as a means of elucidating humoral immune response dynamics in various situations.

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