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Pascucci E, Pugliese A. Modelling Immune Memory Development. Bull Math Biol 2021; 83:118. [PMID: 34687362 DOI: 10.1007/s11538-021-00949-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 09/27/2021] [Indexed: 12/01/2022]
Abstract
The cellular adaptive immune response to influenza has been analyzed through several recent mathematical models. In particular, Zarnitsyna et al. (Front Immunol 7:1-9, 2016) show how central memory CD8+ T cells reach a plateau after repeated infections, and analyze their role in the immune response to further challenges. In this paper, we further investigate the theoretical features of that model by extracting from the infection dynamics a discrete map that describes the build-up of memory cells. Furthermore, we show how the model by Zarnitsyna et al. (Front Immunol 7:1-9, 2016) can be viewed as a fast-scale approximation of a model allowing for recruitment of target epithelial cells. Finally, we analyze which components of the model are essential to understand the progressive build-up of immune memory. This is performed through the analysis of simplified versions of the model that include some components only of immune response. The analysis performed may also provide a theoretical framework for understanding the conditions under which two-dose vaccination strategies can be helpful.
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Affiliation(s)
- Eleonora Pascucci
- Dipartimento di Matematica, Università degli Studi di Trento, Via Sommarive 14, 38123, Povo, TN, Italy
| | - Andrea Pugliese
- Dipartimento di Matematica, Università degli Studi di Trento, Via Sommarive 14, 38123, Povo, TN, Italy.
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Gjini E, Paupério FFS, Ganusov VV. Treatment timing shifts the benefits of short and long antibiotic treatment over infection. Evol Med Public Health 2020; 2020:249-263. [PMID: 33376597 PMCID: PMC7750949 DOI: 10.1093/emph/eoaa033] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 08/19/2020] [Indexed: 12/13/2022] Open
Abstract
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. In this debate, two axes of 'aggression' have typically been conflated: treatment intensity (dose) and treatment duration. The third dimension of treatment timing along each individual's infection course has rarely been addressed. By using a generic mathematical model of bacterial infection controlled by immune response, we examine how the relative effectiveness of antibiotic treatment varies with its timing, duration and antibiotic kill rate. We show that short or long treatments may both be beneficial depending on treatment onset, the target criterion for success and on antibiotic efficacy. This results from the dynamic trade-off between immune response build-up and resistance risk in acute, self-limiting infections, and uncertainty relating symptoms to infection variables. We show that in our model early optimal treatments tend to be 'short and strong', while late optimal treatments tend to be 'mild and long'. This suggests a shift in the aggression axis depending on the timing of treatment. We find that any specific optimal treatment schedule may perform more poorly if evaluated by other criteria, or under different host-specific conditions. Our results suggest that major advances in antibiotic stewardship must come from a deeper empirical understanding of bacterial infection processes in individual hosts. To guide rational therapy, mathematical models need to be constrained by data, including a better quantification of personal disease trajectory in humans. Lay summary: Bacterial infections are becoming more difficult to treat worldwide because bacteria are becoming resistant to the antibiotics used. Addressing this problem requires a better understanding of how treatment along with other host factors impact antibiotic resistance. Until recently, most theoretical research has focused on the importance of antibiotic dosing on antibiotic resistance, however, duration and timing of treatment remain less explored. Here, we use a mathematical model of a generic bacterial infection to study three aspects of treatment: treatment dose/efficacy (defined by the antibiotic kill rate), duration, and timing, and their impact on several infection endpoints. We show that short and long treatment success strongly depends on when treatment begins (defined by the symptom threshold), the target criterion to optimize, and on antibiotic efficacy. We find that if administered early in an infection, "strong and short" therapy performs better, while if treatment begins at higher bacterial densities, a "mild and long" course of antibiotics is favored. In the model host immune defenses are key in preventing relapses, controlling antibiotic resistant bacteria and increasing the effectiveness of moderate intervention. In order to improve rational treatments of human infections, we call for a better quantification of individual disease trajectories in bacteria-immunity space.
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Affiliation(s)
- Erida Gjini
- Mathematical Modeling of Biological Processes Laboratory, Instituto Gulbenkian de Ciência, Rua da Quinta Grande, 6, Oeiras, 2780-156, Portugal
| | - Francisco F S Paupério
- Mathematical Modeling of Biological Processes Laboratory, Instituto Gulbenkian de Ciência, Rua da Quinta Grande, 6, Oeiras, 2780-156, Portugal
- Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Lisbon, 1749-016, Portugal
| | - Vitaly V Ganusov
- Department of Microbiology, University of Tennessee, Knoxville, TN 37996, USA
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Abstract
PURPOSE OF REVIEW Climate change, deforestation, urbanization, and increased population mobility have made the risk of large outbreaks of yellow fever more likely than ever. Yellow fever vaccine production barely meets demands. In this review, we address the causes of the recent yellow fever outbreaks, why fractional dose yellow fever vaccination works, the role of virus neutralizing antibodies in the protection against yellow fever, and the need for revaccination. RECENT FINDINGS Human activities have profoundly changed the epidemiology of yellow fever. The excess of infectious viral particles in routine yellow fever vaccine batches allows for off-label use of fractional dose yellow fever vaccination in response to emergency situations. Two studies have confirmed long-term protection after fractional dose yellow fever vaccination. The need for the presence of virus neutralizing antibodies (VNA) to protect an individual against yellow fever depends on the epidemiological setting. In case of sylvatic transmission, population immunity is irrelevant for individual protection, as mosquitoes are transmitting the virus from infected nonhuman primates to human. SUMMARY With the growing connectivity through air travel, countries with high densities of nonimmune populations and of the urban mosquito vector, Aedes aegypti, should ensure that their citizens are properly vaccinated against yellow fever before traveling to a yellow fever endemic country. In the situation of sylvatic transmission, the presence of protective levels of VNA will determine the outcome and may require revaccination at some point in time.
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Minervina AA, Pogorelyy MV, Komech EA, Karnaukhov VK, Bacher P, Rosati E, Franke A, Chudakov DM, Mamedov IZ, Lebedev YB, Mora T, Walczak AM. Primary and secondary anti-viral response captured by the dynamics and phenotype of individual T cell clones. eLife 2020; 9:53704. [PMID: 32081129 PMCID: PMC7060039 DOI: 10.7554/elife.53704] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 02/21/2020] [Indexed: 11/16/2022] Open
Abstract
The diverse repertoire of T-cell receptors (TCR) plays a key role in the adaptive immune response to infections. Using TCR alpha and beta repertoire sequencing for T-cell subsets, as well as single-cell RNAseq and TCRseq, we track the concentrations and phenotypes of individual T-cell clones in response to primary and secondary yellow fever immunization — the model for acute infection in humans — showing their large diversity. We confirm the secondary response is an order of magnitude weaker, albeit ∼10 days faster than the primary one. Estimating the fraction of the T-cell response directed against the single immunodominant epitope, we identify the sequence features of TCRs that define the high precursor frequency of the two major TCR motifs specific for this particular epitope. We also show the consistency of clonal expansion dynamics between bulk alpha and beta repertoires, using a new methodology to reconstruct alpha-beta pairings from clonal trajectories.
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Affiliation(s)
| | - Mikhail V Pogorelyy
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.,Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russian Federation
| | - Ekaterina A Komech
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.,Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russian Federation
| | | | - Petra Bacher
- Institute of Immunology, Kiel University, Kiel, Germany
| | - Elisa Rosati
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
| | - Dmitriy M Chudakov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.,Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russian Federation.,Center of Life Sciences, Skoltech, Moscow, Russian Federation.,Masaryk University, Central European Institute of Technology, Brno, Czech Republic
| | - Ilgar Z Mamedov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.,Masaryk University, Central European Institute of Technology, Brno, Czech Republic.,V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow, Russian Federation
| | - Yuri B Lebedev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.,Moscow State University, Moscow, Russian Federation
| | - Thierry Mora
- Laboratoire de physique de l'École normale supérieure, ENS, PSL, Sorbonne Université, Université de Paris, and CNRS, Paris, France
| | - Aleksandra M Walczak
- Laboratoire de physique de l'École normale supérieure, ENS, PSL, Sorbonne Université, Université de Paris, and CNRS, Paris, France
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