1
|
Lee HJ, Seo Y, Park Y, Yi EC, Han D, Min H. Comprehensive immune cell spectral library for large-scale human primary T, B, and NK cell proteomics. Sci Data 2024; 11:871. [PMID: 39127789 PMCID: PMC11316730 DOI: 10.1038/s41597-024-03721-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 07/31/2024] [Indexed: 08/12/2024] Open
Abstract
Although proteomics is extensively used in immune research, there is currently no publicly accessible spectral assay library for the comprehensive proteome of immune cells. This study generated spectral assay libraries for five human immune cell lines and four primary immune cells: CD4 T, CD8 T, natural killer (NK) cells, and B cells. This was achieved by utilizing data-dependent acquisition (DDA) and employing fractionated samples from over 100 µg of proteins, which was applied to acquire the highest-quality MS/MS spectral data. In addition, Data-indedendent acquisition (DIA) was used to obtain sufficient data points for analyzing proteins from 10,000 primary CD4 T, CD8 T, NK, and B cells. The immune cell spectral assay library generated included 10,544 protein groups and 127,106 peptides. The proteomic profiles of 10,000 primary human immune cells obtained from 15 healthy volunteers analyzed using DIA revealed the highest heterogeneity of B cells among other immune cell types and the similarity between CD4 T and CD8 T cells. All data and spectral library are deposited in ProteomeXchange (PXD047742).
Collapse
Affiliation(s)
- Hyeon-Jeong Lee
- Doping Control Center, Korea Institute of Science and Technology (KIST), Seoul, 02792, Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 03080, Korea
| | - Yoondam Seo
- Doping Control Center, Korea Institute of Science and Technology (KIST), Seoul, 02792, Korea
| | - Yoon Park
- Chemical and Biological Integrative Research Center, Biomedical Research Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, Korea
| | - Eugene C Yi
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 03080, Korea
| | - Dohyun Han
- Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, 03080, Korea
| | - Hophil Min
- Doping Control Center, Korea Institute of Science and Technology (KIST), Seoul, 02792, Korea.
| |
Collapse
|
2
|
Purcell RA, Theisen RM, Arnold KB, Chung AW, Selva KJ. Polyfunctional antibodies: a path towards precision vaccines for vulnerable populations. Front Immunol 2023; 14:1183727. [PMID: 37600816 PMCID: PMC10433199 DOI: 10.3389/fimmu.2023.1183727] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 05/30/2023] [Indexed: 08/22/2023] Open
Abstract
Vaccine efficacy determined within the controlled environment of a clinical trial is usually substantially greater than real-world vaccine effectiveness. Typically, this results from reduced protection of immunologically vulnerable populations, such as children, elderly individuals and people with chronic comorbidities. Consequently, these high-risk groups are frequently recommended tailored immunisation schedules to boost responses. In addition, diverse groups of healthy adults may also be variably protected by the same vaccine regimen. Current population-based vaccination strategies that consider basic clinical parameters offer a glimpse into what may be achievable if more nuanced aspects of the immune response are considered in vaccine design. To date, vaccine development has been largely empirical. However, next-generation approaches require more rational strategies. We foresee a generation of precision vaccines that consider the mechanistic basis of vaccine response variations associated with both immunogenetic and baseline health differences. Recent efforts have highlighted the importance of balanced and diverse extra-neutralising antibody functions for vaccine-induced protection. However, in immunologically vulnerable populations, significant modulation of polyfunctional antibody responses that mediate both neutralisation and effector functions has been observed. Here, we review the current understanding of key genetic and inflammatory modulators of antibody polyfunctionality that affect vaccination outcomes and consider how this knowledge may be harnessed to tailor vaccine design for improved public health.
Collapse
Affiliation(s)
- Ruth A. Purcell
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia
| | - Robert M. Theisen
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
| | - Kelly B. Arnold
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
| | - Amy W. Chung
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia
| | - Kevin J. Selva
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, Australia
| |
Collapse
|
3
|
Stein CM. Genetic epidemiology of resistance to M. tuberculosis Infection: importance of study design and recent findings. Genes Immun 2023; 24:117-123. [PMID: 37085579 PMCID: PMC10121418 DOI: 10.1038/s41435-023-00204-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 04/03/2023] [Accepted: 04/14/2023] [Indexed: 04/23/2023]
Abstract
Resistance to M. tuberculosis, often referred to as "RSTR" in the literature, is being increasingly studied because of its potential relevance as a clinical outcome in vaccine studies. This review starts by addressing the importance of epidemiological characterization of this phenotype, and ongoing challenges in that characterization. Then, this review summarizes the extant genetic and genomic studies of this phenotype, including heritability studies, candidate gene studies, and genome-wide association studies, as well as whole transcriptome studies. Findings from recent studies that used longitudinal characterization of the RSTR phenotype are compared to those using a cross-sectional definition, and the challenges of using tuberculin skin test and interferon-gamma release assay are discussed. Finally, future directions are proposed. Since this is a rapidly evolving area of public health significance, this review will help frame future research questions and study designs.
Collapse
Affiliation(s)
- Catherine M Stein
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.
- Division of Infectious Diseases and HIV Medicine, Department of Medicine, Case Western Reserve University, Cleveland, OH, USA.
| |
Collapse
|
4
|
Qiu X, Wang H, Lan Y, Miao J, Pan C, Sun W, Li G, Wang Y, Zhao X, Zhu Z, Zhu S. Blood biomarkers of post-stroke depression after minor stroke at three months in males and females. BMC Psychiatry 2022; 22:162. [PMID: 35241021 PMCID: PMC8896360 DOI: 10.1186/s12888-022-03805-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 02/22/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. Studies on the underlying mechanisms and biological markers of sex differences in PSD are of great significance, but there are still few such studies. Therefore, the main objective of this study was to investigate the association of biomarkers with PSD at 3 months after minor stroke in men and women. METHODS This was a prospective multicenter cohort study that enrolled 530 patients with minor stroke (males, 415; females, 115). Demographic information and blood samples of patients were collected within 24 h of admission, and followed up at 3 months after stroke onset. PSD was defined as a depressive disorder due to another medical condition with depressive features, major depressive-like episode, or mixed-mood features according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-V). Univariate analysis was performed using the chi-square test, Mann-Whitney U test, or t-test. Partial least-squares discriminant analysis (PLS-DA) was used to distinguish between patients with and without PSD. Factors with variable importance for projection (VIP) > 1.0 were classified as the most important factors in the model segregation. RESULTS The PLS-DA model mainly included component 1 and component 2 for males and females. For males, the model could explain 13% and 16.9% of the variables, respectively, and 29.9% of the variables in total; the most meaningful predictors were exercise habit and fibrinogen level. For females, the model could explain 15.7% and 10.5% of the variables, respectively, and 26.2% of the variables in total; the most meaningful predictors in the model were brain-derived neurotrophic factor (BDNF), magnesium and free T3. Fibrinogen was positively correlated with the Hamilton Depression Scale-17 items (HAMD-17) score. BDNF, magnesium, and free T3 levels were negatively correlated with the HAMD-17 score. CONCLUSIONS This was a prospective cohort study. The most important markers found to be affecting PSD at 3 months were fibrinogen in males, and free T3, magnesium, and BDNF in females. TRIAL REGISTRATION ChiCTR-ROC-17013993 .
Collapse
Affiliation(s)
- Xiuli Qiu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - He Wang
- Department of Medical Affair, Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - Yan Lan
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - Jinfeng Miao
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - Chensheng Pan
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - Wenzhe Sun
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - Guo Li
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - Yanyan Wang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - Xin Zhao
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - Zhou Zhu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| | - Suiqiang Zhu
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030 Hubei China
| |
Collapse
|
5
|
Belkina AC, Starchenko A, Drake KA, Proctor EA, Pihl RMF, Olson A, Lauffenburger DA, Lin N, Snyder-Cappione JE. Multivariate Computational Analysis of Gamma Delta T Cell Inhibitory Receptor Signatures Reveals the Divergence of Healthy and ART-Suppressed HIV+ Aging. Front Immunol 2018; 9:2783. [PMID: 30568654 PMCID: PMC6290897 DOI: 10.3389/fimmu.2018.02783] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 11/12/2018] [Indexed: 12/15/2022] Open
Abstract
Even with effective viral control, HIV-infected individuals are at a higher risk for morbidities associated with older age than the general population, and these serious non-AIDS events (SNAEs) track with plasma inflammatory and coagulation markers. The cell subsets driving inflammation in aviremic HIV infection are not yet elucidated. Also, whether ART-suppressed HIV infection causes premature induction of the inflammatory events found in uninfected elderly or if a novel inflammatory network ensues when HIV and older age co-exist is unclear. In this study we measured combinational expression of five inhibitory receptors (IRs) on seven immune cell subsets and 16 plasma markers from peripheral blood mononuclear cells (PBMC) and plasma samples, respectively, from a HIV and Aging cohort comprised of ART-suppressed HIV-infected and uninfected controls stratified by age (≤35 or ≥50 years old). For data analysis, multiple multivariate computational algorithms [cluster identification, characterization, and regression (CITRUS), partial least squares regression (PLSR), and partial least squares-discriminant analysis (PLS-DA)] were used to determine if immune parameter disparities can distinguish the subject groups and to investigate if there is a cross-impact of aviremic HIV and age on immune signatures. IR expression on gamma delta (γδ) T cells exclusively separated HIV+ subjects from controls in CITRUS analyses and secretion of inflammatory cytokines and cytotoxic mediators from γδ T cells tracked with TIGIT expression among HIV+ subjects. Also, plasma markers predicted the percentages of TIGIT+ γδ T cells in subjects with and without HIV in PSLR models, and a PLS-DA model of γδ T cell IR signatures and plasma markers significantly stratified all four of the subject groups (uninfected younger, uninfected older, HIV+ younger, and HIV+ older). These data implicate γδ T cells as an inflammatory driver in ART-suppressed HIV infection and provide evidence of distinct “inflamm-aging” processes with and without ART-suppressed HIV infection.
Collapse
Affiliation(s)
- Anna C Belkina
- Flow Cytometry Core Facility, Boston University School of Medicine, Boston, MA, United States.,Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Alina Starchenko
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | | | - Elizabeth A Proctor
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Riley M F Pihl
- Flow Cytometry Core Facility, Boston University School of Medicine, Boston, MA, United States
| | - Alex Olson
- Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Douglas A Lauffenburger
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Nina Lin
- Department of Medicine, Boston University School of Medicine, Boston, MA, United States
| | - Jennifer E Snyder-Cappione
- Flow Cytometry Core Facility, Boston University School of Medicine, Boston, MA, United States.,Department of Microbiology, Boston University School of Medicine, Boston, MA, United States
| |
Collapse
|
6
|
Norman KC, Moore BB, Arnold KB, O’Dwyer DN. Proteomics: Clinical and research applications in respiratory diseases. Respirology 2018; 23:993-1003. [PMID: 30105802 PMCID: PMC6234509 DOI: 10.1111/resp.13383] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 07/05/2018] [Accepted: 07/19/2018] [Indexed: 12/27/2022]
Abstract
The proteome is the study of the protein content of a definable component of an organism in biology. However, the tissue-specific expression of proteins and the varied post-translational modifications, splice variants and protein-protein complexes that may form, make the study of protein a challenging yet vital tool in answering many of the unanswered questions in medicine and biology to date. Indeed, the spatial, temporal and functional composition of proteins in the human body has proven difficult to elucidate for many years. Given the effect of microRNA and epigenetic regulation on silencing and enhancing gene transcription, the study of protein arguably provides more accurate information on homeostasis and perturbation in health and disease. There have been significant advances in the field of proteomics in recent years, with new technologies and platforms available to the research community. In this review, we briefly discuss some of these new technologies and developments in the context of respiratory disease. We also discuss the types of data science approaches to analyses and interpretation of the large volumes of data generated in proteomic studies. We discuss the application of these technologies with regard to respiratory disease and highlight the potential for proteomics in generating major advances in the understanding of respiratory pathophysiology into the future.
Collapse
Affiliation(s)
- Katy C. Norman
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, USA
| | - Bethany B. Moore
- Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan Medical School, Ann Arbor, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, USA
| | - Kelly B. Arnold
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, USA
| | - David N. O’Dwyer
- Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Michigan Medical School, Ann Arbor, USA
| |
Collapse
|
7
|
Fong LE, Muñoz-Rojas AR, Miller-Jensen K. Advancing systems immunology through data-driven statistical analysis. Curr Opin Biotechnol 2018; 52:109-115. [PMID: 29656236 PMCID: PMC6294467 DOI: 10.1016/j.copbio.2018.03.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Revised: 03/21/2018] [Accepted: 03/22/2018] [Indexed: 12/14/2022]
Abstract
Systems biology provides an effective approach to decipher, predict, and ultimately manipulate the complex and inter-connected networks that regulate the immune system. Advances in high-throughput, multiplexed experimental techniques have increased the availability of proteomic and transcriptomic immunological datasets, and as a result, have also accelerated the development of new data-driven computational algorithms to extract biological insight from these data. This review highlights how data-driven statistical models have been used to characterize immune cell subsets and their functions, to map the signaling and intercellular networks that regulate immune responses, and to connect immune cell states to disease outcomes to generate hypotheses for novel therapeutic strategies. We focus on recent advances in evaluating immune cell responses following viral infection and in the tumor microenvironment, which hold promise for improving vaccines, antiviral and cancer immunotherapy.
Collapse
Affiliation(s)
- Linda E Fong
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | | | - Kathryn Miller-Jensen
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, CT, USA.
| |
Collapse
|
8
|
Arnold KB, Chung AW. Prospects from systems serology research. Immunology 2017; 153:279-289. [PMID: 29139548 PMCID: PMC5795183 DOI: 10.1111/imm.12861] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Revised: 11/02/2017] [Accepted: 11/04/2017] [Indexed: 12/28/2022] Open
Abstract
Antibodies are highly functional glycoproteins capable of providing immune protection through multiple mechanisms, including direct pathogen neutralization and the engagement of their Fc portions with surrounding effector immune cells that induce anti-pathogenic responses. Small modifications to multiple antibody biophysical features induced by vaccines can significantly alter functional immune outcomes, though it is difficult to predict which combinations confer protective immunity. In order to give insight into the highly complex and dynamic processes that drive an effective humoral immune response, here we discuss recent applications of 'Systems Serology', a new approach that uses data-driven (also called 'machine learning') computational analysis and high-throughput experimental data to infer networks of important antibody features associated with protective humoral immunity and/or Fc functional activity. This approach offers the ability to understand humoral immunity beyond single correlates of protection, assessing the relative importance of multiple biophysical modifications to antibody features with multivariate computational approaches. Systems Serology has the exciting potential to help identify novel correlates of protection from infection and may generate a more comprehensive understanding of the mechanisms behind protection, including key relationships between specific Fc functions and antibody biophysical features (e.g. antigen recognition, isotype, subclass and/or glycosylation events). Reviewed here are some of the experimental and computational technologies available for Systems Serology research and evidence that the application has broad relevance to multiple different infectious diseases including viruses, bacteria, fungi and parasites.
Collapse
Affiliation(s)
- Kelly B Arnold
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Amy W Chung
- Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Vic., Australia
| |
Collapse
|
9
|
Decker JT, Hobson EC, Zhang Y, Shin S, Thomas AL, Jeruss JS, Arnold KB, Shea LD. Systems analysis of dynamic transcription factor activity identifies targets for treatment in Olaparib resistant cancer cells. Biotechnol Bioeng 2017; 114:2085-2095. [PMID: 28322442 DOI: 10.1002/bit.26293] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2016] [Revised: 03/10/2017] [Accepted: 03/16/2017] [Indexed: 12/26/2022]
Abstract
The development of resistance to targeted therapeutics is a challenging issue for the treatment of cancer. Cancers that have mutations in BRCA, a DNA repair protein, have been treated with poly(ADP-ribose) polymerase (PARP) inhibitors, which target a second DNA repair mechanism with the aim of inducing synthetic lethality. While these inhibitors have shown promise clinically, the development of resistance can limit their effectiveness as a therapy. This study investigated mechanisms of resistance in BRCA-mutated cancer cells (HCC1937) to Olaparib (AZD2281) using TRACER, a technique for measuring dynamics of transcription factor (TF) activity in living cells. TF activity was monitored in the parental HCC1937 cell line and two distinct resistant cell lines, one with restored wild-type BRCA1 and one with acquired resistance independent of BRCA1 for 48 h during treatment with Olaparib. Partial least squares discriminant analysis (PLSDA) was used to categorize the three cell types based on TF activity, and network analysis was used to investigate the mechanism of early response to Olaparib in the study cells. NOTCH signaling was identified as a common pathway linked to resistance in both Olaparib-resistant cell types. Western blotting confirmed upregulation of NOTCH protein, and sensitivity to Olaparib was restored through co-treatment with a gamma secretase inhibitor. The identification of NOTCH signaling as a common pathway contributing to PARP inhibitor resistance by TRACER indicates the efficacy of transcription factor dynamics in identifying targets for intervention in treatment-resistant cancer and provides a new method for determining effective strategies for directed chemotherapy. Biotechnol. Bioeng. 2017;114: 2085-2095. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Joseph T Decker
- Department of Biomedical Engineering, University of Michigan, 2200 Bonisteel, 1119 Gerstacker, Ann Arbor 48109, Michigan
| | - Eric C Hobson
- Department of Biomedical Engineering, University of Michigan, 2200 Bonisteel, 1119 Gerstacker, Ann Arbor 48109, Michigan
| | - Yining Zhang
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Seungjin Shin
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois
| | | | | | - Kelly B Arnold
- Department of Biomedical Engineering, University of Michigan, 2200 Bonisteel, 1119 Gerstacker, Ann Arbor 48109, Michigan
| | - Lonnie D Shea
- Department of Biomedical Engineering, University of Michigan, 2200 Bonisteel, 1119 Gerstacker, Ann Arbor 48109, Michigan
| |
Collapse
|
10
|
Morel PA, Lee REC, Faeder JR. Demystifying the cytokine network: Mathematical models point the way. Cytokine 2016; 98:115-123. [PMID: 27919524 DOI: 10.1016/j.cyto.2016.11.013] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Accepted: 11/21/2016] [Indexed: 12/22/2022]
Abstract
Cytokines provide the means by which immune cells communicate with each other and with parenchymal cells. There are over one hundred cytokines and many exist in families that share receptor components and signal transduction pathways, creating complex networks. Reductionist approaches to understanding the role of specific cytokines, through the use of gene-targeted mice, have revealed further complexity in the form of redundancy and pleiotropy in cytokine function. Creating an understanding of the complex interactions between cytokines and their target cells is challenging experimentally. Mathematical and computational modeling provides a robust set of tools by which complex interactions between cytokines can be studied and analyzed, in the process creating novel insights that can be further tested experimentally. This review will discuss and provide examples of the different modeling approaches that have been used to increase our understanding of cytokine networks. This includes discussion of knowledge-based and data-driven modeling approaches and the recent advance in single-cell analysis. The use of modeling to optimize cytokine-based therapies will also be discussed.
Collapse
Affiliation(s)
- Penelope A Morel
- Department of Immunology, University of Pittsburgh, Pittsburgh, USA.
| | - Robin E C Lee
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, USA
| | - James R Faeder
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, USA
| |
Collapse
|
11
|
Gadkar K, Kirouac DC, Mager DE, van der Graaf PH, Ramanujan S. A Six-Stage Workflow for Robust Application of Systems Pharmacology. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2016; 5:235-49. [PMID: 27299936 PMCID: PMC4879472 DOI: 10.1002/psp4.12071] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2015] [Accepted: 02/18/2016] [Indexed: 12/30/2022]
Abstract
Quantitative and systems pharmacology (QSP) is increasingly being applied in pharmaceutical research and development. One factor critical to the ultimate success of QSP is the establishment of commonly accepted language, technical criteria, and workflows. We propose an integrated workflow that bridges conceptual objectives with underlying technical detail to support the execution, communication, and evaluation of QSP projects.
Collapse
Affiliation(s)
- K Gadkar
- Translational & Systems Pharmacology, PKPD, Genentech, South San Francisco, California, USA
| | - D C Kirouac
- Translational & Systems Pharmacology, PKPD, Genentech, South San Francisco, California, USA
| | - D E Mager
- Department of Pharmaceutical Sciences, University at Buffalo, SUNY, Buffalo, New York
| | - P H van der Graaf
- Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.,Certara QSP, Canterbury, UK
| | - S Ramanujan
- Translational & Systems Pharmacology, PKPD, Genentech, South San Francisco, California, USA
| |
Collapse
|
12
|
Arnold KB, Burgener A, Birse K, Romas L, Dunphy LJ, Shahabi K, Abou M, Westmacott GR, McCorrister S, Kwatampora J, Nyanga B, Kimani J, Masson L, Liebenberg LJ, Abdool Karim SS, Passmore JAS, Lauffenburger DA, Kaul R, McKinnon LR. Increased levels of inflammatory cytokines in the female reproductive tract are associated with altered expression of proteases, mucosal barrier proteins, and an influx of HIV-susceptible target cells. Mucosal Immunol 2016; 9:194-205. [PMID: 26104913 DOI: 10.1038/mi.2015.51] [Citation(s) in RCA: 175] [Impact Index Per Article: 21.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2015] [Accepted: 05/04/2015] [Indexed: 02/04/2023]
Abstract
Elevated inflammatory cytokines (EMCs) at mucosal surfaces have been associated with HIV susceptibility, but the underlying mechanisms remain unclear. We characterized the soluble mucosal proteome associated with elevated cytokine expression in the female reproductive tract. A scoring system was devised based on the elevation (upper quartile) of at least three of seven inflammatory cytokines in cervicovaginal lavage. Using this score, HIV-uninfected Kenyan women were classified as either having EMC (n=28) or not (n=68). Of 455 proteins quantified in proteomic analyses, 53 were associated with EMC (5% false discovery rate threshold). EMCs were associated with proteases, cell motility, and actin cytoskeletal pathways, whereas protease inhibitor, epidermal cell differentiation, and cornified envelope pathways were decreased. Multivariate analysis identified an optimal signature of 16 proteins that distinguished the EMC group with 88% accuracy. Three proteins in this signature were neutrophil-associated proteases that correlated with many cytokines, especially GM-CSF (granulocyte-macrophage colony-stimulating factor), IL-1β (interleukin-1β), MIP-3α (macrophage inflammatory protein-3α), IL-17, and IL-8. Gene set enrichment analyses implicated activated immune cells; we verified experimentally that EMC women had an increased frequency of endocervical CD4(+) T cells. These data reveal strong linkages between mucosal cytokines, barrier function, proteases, and immune cell movement, and propose these as potential mechanisms that increase risk of HIV acquisition.
Collapse
Affiliation(s)
- Kelly B Arnold
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Adam Burgener
- National HIV and Retrovirology Laboratory, JC Wilt Infectious Disease Research Centre, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Canada.,Department of Medical Microbiology, University of Manitoba, Winnipeg, Canada.,Unit of Infectious Diseases, Department of Medicine Solna, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Kenzie Birse
- National HIV and Retrovirology Laboratory, JC Wilt Infectious Disease Research Centre, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Canada.,Department of Medical Microbiology, University of Manitoba, Winnipeg, Canada
| | - Laura Romas
- National HIV and Retrovirology Laboratory, JC Wilt Infectious Disease Research Centre, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Canada.,Department of Medical Microbiology, University of Manitoba, Winnipeg, Canada
| | - Laura J Dunphy
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Max Abou
- National HIV and Retrovirology Laboratory, JC Wilt Infectious Disease Research Centre, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Canada
| | - Garrett R Westmacott
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Canada
| | - Stuart McCorrister
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Canada
| | - Jessie Kwatampora
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
| | - Billy Nyanga
- Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
| | - Joshua Kimani
- Department of Medical Microbiology, University of Manitoba, Winnipeg, Canada.,Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya
| | - Lindi Masson
- Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town, Cape Town, South Africa.,Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
| | - Lenine J Liebenberg
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
| | - Salim S Abdool Karim
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa.,Mailman School of Public Health, Department of Epidemiology, Columbia University, New York, USA
| | - Jo-Ann S Passmore
- Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town, Cape Town, South Africa.,Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa.,National Health Laboratory Service, South Africa
| | - Douglas A Lauffenburger
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Rupert Kaul
- Department of Medicine, University of Toronto, Toronto, Canada.,Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya.,University Health Network, University of Toronto, Toronto, Canada
| | - Lyle R McKinnon
- Department of Medicine, University of Toronto, Toronto, Canada.,Department of Medical Microbiology, University of Nairobi, Nairobi, Kenya.,Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
| |
Collapse
|
13
|
Birse K, Arnold KB, Novak RM, McCorrister S, Shaw S, Westmacott GR, Ball TB, Lauffenburger DA, Burgener A. Molecular Signatures of Immune Activation and Epithelial Barrier Remodeling Are Enhanced during the Luteal Phase of the Menstrual Cycle: Implications for HIV Susceptibility. J Virol 2015; 89:8793-805. [PMID: 26085144 PMCID: PMC4524071 DOI: 10.1128/jvi.00756-15] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2015] [Accepted: 06/03/2015] [Indexed: 12/15/2022] Open
Abstract
UNLABELLED The variable infectivity and transmissibility of HIV/SHIV has been recently associated with the menstrual cycle, with particular susceptibility observed during the luteal phase in nonhuman primate models and ex vivo human explant cultures, but the mechanism is poorly understood. Here, we performed an unbiased, mass spectrometry-based proteomic analysis to better understand the mucosal immunological processes underpinning this observed susceptibility to HIV infection. Cervicovaginal lavage samples (n = 19) were collected, characterized as follicular or luteal phase using days since last menstrual period, and analyzed by tandem mass spectrometry. Biological insights from these data were gained using a spectrum of computational methods, including hierarchical clustering, pathway analysis, gene set enrichment analysis, and partial least-squares discriminant analysis with LASSO feature selection. Of the 384 proteins identified, 43 were differentially abundant between phases (P < 0.05, ≥2-fold change). Cell-cell adhesion proteins and antiproteases were reduced, and leukocyte recruitment (interleukin-8 pathway, P = 1.41E-5) and extravasation proteins (P = 5.62E-4) were elevated during the luteal phase. LASSO/PLSDA identified a minimal profile of 18 proteins that best distinguished the luteal phase. This profile included cytoskeletal elements and proteases known to be involved in cellular movement. Gene set enrichment analysis associated CD4(+) T cell and neutrophil gene set signatures with the luteal phase (P < 0.05). Taken together, our findings indicate a strong association between proteins involved in tissue remodeling and leukocyte infiltration with the luteal phase, which may represent potential hormone-associated mechanisms of increased susceptibility to HIV. IMPORTANCE Recent studies have discovered an enhanced susceptibility to HIV infection during the progesterone-dominant luteal phase of the menstrual cycle. However, the mechanism responsible for this enhanced susceptibility has not yet been determined. Understanding the source of this vulnerability will be important for designing efficacious HIV prevention technologies for women. Furthermore, these findings may also be extrapolated to better understand the impact of exogenous hormone application, such as the use of hormonal contraceptives, on HIV acquisition risk. Hormonal contraceptives are the most widely used contraceptive method in sub-Saharan Africa, the most HIV-burdened area of the world. For this reason, research conducted to better understand how hormones impact host immunity and susceptibility factors important for HIV infection is a global health priority.
Collapse
Affiliation(s)
- Kenzie Birse
- National Lab for HIV Immunology, JC Wilt Infectious Disease Research Centre, Public Health Agency of Canada, Winnipeg, Manitoba, Canada Department of Medical Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Kelly B Arnold
- Department of Biological Engineering and Center for Gynepathology Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Richard M Novak
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Stuart McCorrister
- Mass Spectrometry Core Facility, National Microbiology Laboratory, Winnipeg, Manitoba, Canada
| | - Souradet Shaw
- Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Garrett R Westmacott
- Mass Spectrometry Core Facility, National Microbiology Laboratory, Winnipeg, Manitoba, Canada
| | - Terry B Ball
- National Lab for HIV Immunology, JC Wilt Infectious Disease Research Centre, Public Health Agency of Canada, Winnipeg, Manitoba, Canada Department of Medical Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada Department of Medical Microbiology, University of Nairobi, Department of Medical Microbiology, Nairobi, Kenya
| | - Douglas A Lauffenburger
- Department of Biological Engineering and Center for Gynepathology Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Adam Burgener
- National Lab for HIV Immunology, JC Wilt Infectious Disease Research Centre, Public Health Agency of Canada, Winnipeg, Manitoba, Canada Department of Medical Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada Unit of Infectious Diseases, Department of Medicine Solna, Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| |
Collapse
|