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Chen Y, Fan G, Yang B, Fan X, Chen H, Ma Z, Lou J, Xu J, Wang Y, Zhang S. The single-cell transcriptional landscape of lung cells from PCV2d-infected mice. Front Microbiol 2025; 16:1554961. [PMID: 40196036 PMCID: PMC11973356 DOI: 10.3389/fmicb.2025.1554961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2025] [Accepted: 02/18/2025] [Indexed: 04/09/2025] Open
Abstract
Introduction Porcine Circovirus (PCV2) infection is prevalent in pig farming and causes significant economic losses. In recent years, the PCV2d subtype has become the most prevalent genotype worldwide, exhibiting higher virulence, leading to more severe viremia and organ damage. Therefore, studying the biological characteristics of the PCV2d subtype is of great significance. Methods We established a PCV2d infection model using BALB/c mice and employed single-cell RNA sequencing (scRNA-seq) to systematically analyze the transcriptome of 10 cell types in the lung tissues of infected mice. We developed a comprehensive marker gene catalog for these cell types. Results Compared to uninfected mice, PCV2d infection induced extensive viral replication and immunosuppressive responses in most cell types. Monocyte macrophages with high levels of viral replication, pro-inflammatory cytokines, and various cell population interactions occurring through CD40-CD40L and CXCL14-CXCR4 were identified. These cells predominantly mediate antigen presentation and processing pathways in vivo, contributing to PCV2d-driven inflammatory lung injury. Discussion Our data uncovered a complex unique immune response scenario in the lung tissue of mice after PCV2d infection, deciphering the potential mechanisms underlying PCV2d-driven inflammatory responses in mice. Furthermore, this study provides a rich database for the molecular basis of different cell types' responses to PCV2d infection.
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Affiliation(s)
- Yunlong Chen
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
| | - Gang Fan
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
| | - Bin Yang
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
| | - Xinyi Fan
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
| | - Haiyan Chen
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
| | - Zhuoyuan Ma
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
| | - Jiao Lou
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
| | - Jingmei Xu
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
| | - Yan Wang
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
| | - Shiqiang Zhang
- College of Veterinary Medicine/Shaanxi Stem Cell Engineering Research Center, Northwest A&F University, Yangling, China
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, China
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Mulè MP, Martins AJ, Cheung F, Farmer R, Sellers BA, Quiel JA, Jain A, Kotliarov Y, Bansal N, Chen J, Schwartzberg PL, Tsang JS. Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint. Immunity 2024; 57:1160-1176.e7. [PMID: 38697118 DOI: 10.1016/j.immuni.2024.04.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 01/21/2024] [Accepted: 04/12/2024] [Indexed: 05/04/2024]
Abstract
Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.
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Affiliation(s)
- Matthew P Mulè
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA; NIH-Oxford-Cambridge Scholars Program, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Andrew J Martins
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Foo Cheung
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Rohit Farmer
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Brian A Sellers
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Juan A Quiel
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Arjun Jain
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Yuri Kotliarov
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Neha Bansal
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Jinguo Chen
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Pamela L Schwartzberg
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA; Cell Signaling and Immunity Section, NIAID, NIH, Bethesda, MD, USA
| | - John S Tsang
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA; NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA.
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Similuk M, Kuijpers T. Nature and nurture: understanding phenotypic variation in inborn errors of immunity. Front Cell Infect Microbiol 2023; 13:1183142. [PMID: 37780853 PMCID: PMC10538643 DOI: 10.3389/fcimb.2023.1183142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 08/17/2023] [Indexed: 10/03/2023] Open
Abstract
The overall disease burden of pediatric infection is high, with widely varying clinical outcomes including death. Among the most vulnerable children, those with inborn errors of immunity, reduced penetrance and variable expressivity are common but poorly understood. There are several genetic mechanisms that influence phenotypic variation in inborn errors of immunity, as well as a body of knowledge on environmental influences and specific pathogen triggers. Critically, recent advances are illuminating novel nuances for fundamental concepts on disease penetrance, as well as raising new areas of inquiry. The last few decades have seen the identification of almost 500 causes of inborn errors of immunity, as well as major advancements in our ability to characterize somatic events, the microbiome, and genotypes across large populations. The progress has not been linear, and yet, these developments have accumulated into an enhanced ability to diagnose and treat inborn errors of immunity, in some cases with precision therapy. Nonetheless, many questions remain regarding the genetic and environmental contributions to phenotypic variation both within and among families. The purpose of this review is to provide an updated summary of key concepts in genetic and environmental contributions to phenotypic variation within inborn errors of immunity, conceptualized as including dynamic, reciprocal interplay among factors unfolding across the key dimension of time. The associated findings, potential gaps, and implications for research are discussed in turn for each major influencing factor. The substantial challenge ahead will be to organize and integrate information in such a way that accommodates the heterogeneity within inborn errors of immunity to arrive at a more comprehensive and accurate understanding of how the immune system operates in health and disease. And, crucially, to translate this understanding into improved patient care for the millions at risk for serious infection and other immune-related morbidity.
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Affiliation(s)
- Morgan Similuk
- Centralized Sequencing Program, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Taco Kuijpers
- Department of Pediatric Immunology, Rheumatology and Infectious Diseases, Emma Children’s Hospital, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
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Forlin R, James A, Brodin P. Making human immune systems more interpretable through systems immunology. Trends Immunol 2023:S1471-4906(23)00113-8. [PMID: 37402600 DOI: 10.1016/j.it.2023.06.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/12/2023] [Accepted: 06/12/2023] [Indexed: 07/06/2023]
Abstract
The human immune system is a distributed system of specialized cell populations with unique functions that collectively give rise to immune responses to infections and during immune-mediated diseases. Cell composition, plasma proteins, and functional responses vary among individuals, making the system difficult to interpret, but this variation is nonrandom. With careful analyses using novel experimental and computational tools, human immune system composition and function carry interpretable information. Here, we propose that systems-level analyses offer an opportunity to make human immune responses more interpretable in the future, and we discuss herein important considerations and lessons learned to this end. Predictable human immunology holds implications for better diagnostic and curative precision in patients with infectious and immune-associated diseases.
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Affiliation(s)
- Rikard Forlin
- Unit for Clinical Pediatrics, Department of Women's and Children's Health, Karolinska Institutet, 17165, Solna, Sweden
| | - Anna James
- Unit for Clinical Pediatrics, Department of Women's and Children's Health, Karolinska Institutet, 17165, Solna, Sweden
| | - Petter Brodin
- Unit for Clinical Pediatrics, Department of Women's and Children's Health, Karolinska Institutet, 17165, Solna, Sweden; Department of Immunology and Inflammation, Imperial College London, London W12 0NN, UK; Medical Research Council London Institute of Medical Sciences (LMS), Imperial College Hammersmith Campus, London W12 0NN, UK.
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Mulè MP, Martins AJ, Cheung F, Farmer R, Sellers B, Quiel JA, Jain A, Kotliarov Y, Bansal N, Chen J, Schwartzberg PL, Tsang JS. Multiscale integration of human and single-cell variations reveals unadjuvanted vaccine high responders are naturally adjuvanted. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.20.23287474. [PMID: 37090674 PMCID: PMC10120791 DOI: 10.1101/2023.03.20.23287474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Advances in multimodal single cell analysis can empower high-resolution dissection of human vaccination responses. The resulting data capture multiple layers of biological variations, including molecular and cellular states, vaccine formulations, inter- and intra-subject differences, and responses unfolding over time. Transforming such data into biological insight remains a major challenge. Here we present a systematic framework applied to multimodal single cell data obtained before and after influenza vaccination without adjuvants or pandemic H5N1 vaccination with the AS03 adjuvant. Our approach pinpoints responses shared across or unique to specific cell types and identifies adjuvant specific signatures, including pro-survival transcriptional states in B lymphocytes that emerged one day after vaccination. We also reveal that high antibody responders to the unadjuvanted vaccine have a distinct baseline involving a rewired network of cell type specific transcriptional states. Remarkably, the status of certain innate immune cells in this network in high responders of the unadjuvanted vaccine appear "naturally adjuvanted": they resemble phenotypes induced early in the same cells only by vaccination with AS03. Furthermore, these cell subsets have elevated frequency in the blood at baseline and increased cell-intrinsic phospho-signaling responses after LPS stimulation ex vivo in high compared to low responders. Our findings identify how variation in the status of multiple immune cell types at baseline may drive robust differences in innate and adaptive responses to vaccination and thus open new avenues for vaccine development and immune response engineering in humans.
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Affiliation(s)
- Matthew P. Mulè
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program; Department of Medicine, University of Cambridge, Cambridge, UK
| | - Andrew J. Martins
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Foo Cheung
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Rohit Farmer
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Brian Sellers
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Juan A. Quiel
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Arjun Jain
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Yuri Kotliarov
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Neha Bansal
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Jinguo Chen
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
| | - Pamela L. Schwartzberg
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Cell Signaling and Immunity Section, NIAID, NIH, Bethesda, MD, USA
| | - John S. Tsang
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD, USA
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Hussain S, Yates C, Campbell MJ. Vitamin D and Systems Biology. Nutrients 2022; 14:5197. [PMID: 36558356 PMCID: PMC9782494 DOI: 10.3390/nu14245197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 11/28/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
The biological actions of the vitamin D receptor (VDR) have been investigated intensively for over 100 years and has led to the identification of significant insights into the repertoire of its biological actions. These were initially established to be centered on the regulation of calcium transport in the colon and deposition in bone. Beyond these well-known calcemic roles, other roles have emerged in the regulation of cell differentiation processes and have an impact on metabolism. The purpose of the current review is to consider where applying systems biology (SB) approaches may begin to generate a more precise understanding of where the VDR is, and is not, biologically impactful. Two SB approaches have been developed and begun to reveal insight into VDR biological functions. In a top-down SB approach genome-wide scale data are statistically analyzed, and from which a role for the VDR emerges in terms of being a hub in a biological network. Such approaches have confirmed significant roles, for example, in myeloid differentiation and the control of inflammation and innate immunity. In a bottom-up SB approach, current biological understanding is built into a kinetic model which is then applied to existing biological data to explain the function and identify unknown behavior. To date, this has not been applied to the VDR, but has to the related ERα and identified previously unknown mechanisms of control. One arena where applying top-down and bottom-up SB approaches may be informative is in the setting of prostate cancer health disparities.
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Affiliation(s)
- Shahid Hussain
- Division of Pharmaceutics and Pharmaceutical Chemistry, College of Pharmacy, The Ohio State University, Columbus, OH 43210, USA
| | - Clayton Yates
- Department of Biology and Center for Cancer Research, Tuskegee University, Tuskegee, AL 36088, USA
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- Department of Oncology Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Moray J. Campbell
- Division of Pharmaceutics and Pharmaceutical Chemistry, College of Pharmacy, The Ohio State University, Columbus, OH 43210, USA
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Tomazic ML, Marugan-Hernandez V, Rodriguez AE. Next-Generation Technologies and Systems Biology for the Design of Novel Vaccines Against Apicomplexan Parasites. Front Vet Sci 2022; 8:800361. [PMID: 35071390 PMCID: PMC8777213 DOI: 10.3389/fvets.2021.800361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
Parasites of the phylum Apicomplexa are the causative agents of important diseases such as malaria, toxoplasmosis or cryptosporidiosis in humans, and babesiosis and coccidiosis in animals. Whereas the first human recombinant vaccine against malaria has been approved and recently recommended for wide administration by the WHO, most other zoonotic parasitic diseases lack of appropriate immunoprophylaxis. Sequencing technologies, bioinformatics, and statistics, have opened the "omics" era into apicomplexan parasites, which has led to the development of systems biology, a recent field that can significantly contribute to more rational design for new vaccines. The discovery of novel antigens by classical approaches is slow and limited to very few antigens identified and analyzed by each study. High throughput approaches based on the expansion of the "omics", mainly genomics and transcriptomics have facilitated the functional annotation of the genome for many of these parasites, improving significantly the understanding of the parasite biology, interactions with the host, as well as virulence and host immune response. Developments in genetic manipulation in apicomplexan parasites have also contributed to the discovery of new potential vaccine targets. The present minireview does a comprehensive summary of advances in "omics", CRISPR/Cas9 technologies, and in systems biology approaches applied to apicomplexan parasites of economic and zoonotic importance, highlighting their potential of the holistic view in vaccine development.
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Affiliation(s)
- Mariela Luján Tomazic
- Instituto de Patobiología Veterinaria (IPVET), INTA-CONICET, Hurlingham, Argentina.,Universidad de Buenos Aires, Facultad de Farmacia y Bioquímica, Catedra de Biotecnología, Ciudad Autónoma de Buenos Aires, Argentina
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Van Tilbeurgh M, Lemdani K, Beignon AS, Chapon C, Tchitchek N, Cheraitia L, Marcos Lopez E, Pascal Q, Le Grand R, Maisonnasse P, Manet C. Predictive Markers of Immunogenicity and Efficacy for Human Vaccines. Vaccines (Basel) 2021; 9:579. [PMID: 34205932 PMCID: PMC8226531 DOI: 10.3390/vaccines9060579] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/22/2021] [Accepted: 05/24/2021] [Indexed: 02/07/2023] Open
Abstract
Vaccines represent one of the major advances of modern medicine. Despite the many successes of vaccination, continuous efforts to design new vaccines are needed to fight "old" pandemics, such as tuberculosis and malaria, as well as emerging pathogens, such as Zika virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Vaccination aims at reaching sterilizing immunity, however assessing vaccine efficacy is still challenging and underscores the need for a better understanding of immune protective responses. Identifying reliable predictive markers of immunogenicity can help to select and develop promising vaccine candidates during early preclinical studies and can lead to improved, personalized, vaccination strategies. A systems biology approach is increasingly being adopted to address these major challenges using multiple high-dimensional technologies combined with in silico models. Although the goal is to develop predictive models of vaccine efficacy in humans, applying this approach to animal models empowers basic and translational vaccine research. In this review, we provide an overview of vaccine immune signatures in preclinical models, as well as in target human populations. We also discuss high-throughput technologies used to probe vaccine-induced responses, along with data analysis and computational methodologies applied to the predictive modeling of vaccine efficacy.
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Affiliation(s)
- Matthieu Van Tilbeurgh
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
| | - Katia Lemdani
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
| | - Anne-Sophie Beignon
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
| | - Catherine Chapon
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
| | - Nicolas Tchitchek
- Unité de Recherche i3, Inserm UMR-S 959, Bâtiment CERVI, Hôpital de la Pitié-Salpêtrière, 75013 Paris, France;
| | - Lina Cheraitia
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
| | - Ernesto Marcos Lopez
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
| | - Quentin Pascal
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
| | - Roger Le Grand
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
| | - Pauline Maisonnasse
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
| | - Caroline Manet
- Immunology of Viral Infections and Autoimmune Diseases (IMVA), IDMIT Department, Institut de Biologie François-Jacob (IBJF), University Paris-Sud—INSERM U1184, CEA, 92265 Fontenay-Aux-Roses, France; (M.V.T.); (K.L.); (A.-S.B.); (C.C.); (L.C.); (E.M.L.); (Q.P.); (R.L.G.); (P.M.)
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Russo G, Reche P, Pennisi M, Pappalardo F. The combination of artificial intelligence and systems biology for intelligent vaccine design. Expert Opin Drug Discov 2020; 15:1267-1281. [PMID: 32662677 DOI: 10.1080/17460441.2020.1791076] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
INTRODUCTION A new body of evidence depicts the applications of artificial intelligence and systems biology in vaccine design and development. The combination of both approaches shall revolutionize healthcare, accelerating clinical trial processes and reducing the costs and time involved in drug research and development. AREAS COVERED This review explores the basics of artificial intelligence and systems biology approaches in the vaccine development pipeline. The topics include a detailed description of epitope prediction tools for designing epitope-based vaccines and agent-based models for immune system response prediction, along with a focus on their potentiality to facilitate clinical trial phases. EXPERT OPINION Artificial intelligence and systems biology offer the opportunity to avoid the inefficiencies and failures that arise in the classical vaccine development pipeline. One promising solution is the combination of both methodologies in a multiscale perspective through an accurate pipeline. We are entering an 'in silico era' in which scientific partnerships, including a more and more increasing creation of an 'ecosystem' of collaboration and multidisciplinary approach, are relevant for addressing the long and risky road of vaccine discovery and development. In this context, regulatory guidance should be developed to qualify the in silico trials as evidence for intelligent vaccine development.
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Affiliation(s)
- Giulia Russo
- Department of Drug Sciences, University of Catania , Catania, Italy
| | - Pedro Reche
- Department of Immunology, Universidad Complutense De Madrid, Ciudad Universitaria , Madrid, Spain
| | - Marzio Pennisi
- Computer Science Institute, DiSIT, University of Eastern Piedmont , Italy
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Abstract
Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.
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Affiliation(s)
| | - Edgar G Engleman
- Department of Pathology, Stanford University School of MedicineStanfordUnited States
- Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of MedicineStanfordUnited States
- Stanford Cancer Institute, Stanford UniversityStanfordUnited States
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Tran TM, Crompton PD. Decoding the complexities of human malaria through systems immunology. Immunol Rev 2019; 293:144-162. [PMID: 31680289 DOI: 10.1111/imr.12817] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 09/27/2019] [Accepted: 09/30/2019] [Indexed: 12/18/2022]
Abstract
The complexity of the Plasmodium parasite and its life cycle poses a challenge to our understanding of the host immune response against malaria. Studying human immune responses during natural and experimental Plasmodium infections can enhance our understanding of malaria-protective immunity and inform the design of disease-modifying adjunctive therapies and next-generation malaria vaccines. Systems immunology can complement conventional approaches to facilitate our understanding of the complex immune response to the highly dynamic malaria parasite. In this review, recent studies that used systems-based approaches to evaluate human immune responses during natural and experimental Plasmodium falciparum and Plasmodium vivax infections as well as during immunization with candidate malaria vaccines are summarized and related to each other. The potential for next-generation technologies to address the current limitations of systems-based studies of human malaria are discussed.
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Affiliation(s)
- Tuan M Tran
- Division of Infectious Diseases, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.,Ryan White Center for Pediatric Infectious Disease and Global Health, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Peter D Crompton
- Malaria Infection Biology and Immunity Section, Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, MD, USA
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12
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Grebennikov DS, Donets DO, Orlova OG, Argilaguet J, Meyerhans A, Bocharov GA. Mathematical Modeling of the Intracellular Regulation of Immune Processes. Mol Biol 2019. [DOI: 10.1134/s002689331905008x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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13
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Grebennikov D, Bouchnita A, Volpert V, Bessonov N, Meyerhans A, Bocharov G. Spatial Lymphocyte Dynamics in Lymph Nodes Predicts the Cytotoxic T Cell Frequency Needed for HIV Infection Control. Front Immunol 2019; 10:1213. [PMID: 31244829 PMCID: PMC6579925 DOI: 10.3389/fimmu.2019.01213] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 05/13/2019] [Indexed: 11/29/2022] Open
Abstract
The surveillance of host body tissues by immune cells is central for mediating their defense function. In vivo imaging technologies have been used to quantitatively characterize target cell scanning and migration of lymphocytes within lymph nodes (LNs). The translation of these quantitative insights into a predictive understanding of immune system functioning in response to various perturbations critically depends on computational tools linking the individual immune cell properties with the emergent behavior of the immune system. By choosing the Newtonian second law for the governing equations, we developed a broadly applicable mathematical model linking individual and coordinated T-cell behaviors. The spatial cell dynamics is described by a superposition of autonomous locomotion, intercellular interaction, and viscous damping processes. The model is calibrated using in vivo data on T-cell motility metrics in LNs such as the translational speeds, turning angle speeds, and meandering indices. The model is applied to predict the impact of T-cell motility on protection against HIV infection, i.e., to estimate the threshold frequency of HIV-specific cytotoxic T cells (CTLs) that is required to detect productively infected cells before the release of viral particles starts. With this, it provides guidance for HIV vaccine studies allowing for the migration of cells in fibrotic LNs.
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Affiliation(s)
- Dmitry Grebennikov
- Moscow Institute of Physics and Technology, National Research University, Dolgoprudny, Russia.,Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russia.,Peoples' Friendship University of Russia (RUDN University), Moscow, Russia
| | - Anass Bouchnita
- Division of Scientific Computing, Department of Information Technology, Uppsala University, Uppsala, Sweden
| | - Vitaly Volpert
- Peoples' Friendship University of Russia (RUDN University), Moscow, Russia.,Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, Villeurbanne, France.,INRIA Team Dracula, INRIA Lyon La Doua, Villeurbanne, France
| | - Nikolay Bessonov
- Institute of Problems of Mechanical Engineering, Russian Academy of Sciences, Saint Petersburg, Russia
| | - Andreas Meyerhans
- Infection Biology Laboratory, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Gennady Bocharov
- Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russia.,Sechenov First Moscow State Medical University, Moscow, Russia
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