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Kumar R, Kolloli A, Singh P, Shi L, Kupz A, Subbian S. The innate memory response of macrophages to Mycobacterium tuberculosis is shaped by the nature of the antigenic stimuli. Microbiol Spectr 2024:e0047324. [PMID: 38980014 DOI: 10.1128/spectrum.00473-24] [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: 02/21/2024] [Accepted: 06/07/2024] [Indexed: 07/10/2024] Open
Abstract
Innate immune cells, such as macrophages, mount an immune response upon exposure to antigens and pathogens. Emerging evidence shows that macrophages exposed to an antigen can generate a "memory-like" response (a.k.a. trained immunity), which confers a non-specific and enhanced response upon subsequent stimulation with a second antigen/microbe. This trained immunity has been implicated in the enhanced response of macrophages against several invading pathogens. However, the association between the nature of the antigen and the corresponding immune correlate of elicited trained immunity is not fully understood. Similarly, the response of macrophages trained and restimulated with homologous stimulants to subsequent infection by pathogenic Mycobacterium tuberculosis (Mtb) remains unexplored. Here, we report the immune and metabolic profiles of trained immunity in human THP-1-derived macrophages after homologous training and restimulation with BCG, LPS, purified protein Derivative (PPD), heat-killed Mtb strains HN878 (hk-HN), and CDC1551 (hk-CDC). Furthermore, the impact of training on the autophagic and antimicrobial responses of macrophages with or without subsequent infection by clinical Mtb isolates HN878 and CDC1551 was evaluated. Results show that repeated stimulation of macrophages with different antigens displays distinct pro-inflammatory, metabolic, antimicrobial, and autophagy induction profiles. These macrophages also induce a differential antimicrobial response upon infection with clinical Mtb HN878 and CDC1551 isolates. A significantly reduced intracellular bacterial load was noted in the stimulated macrophages, which was augmented by the addition of rapamycin, an autophagy inducer. These observations suggest that the nature of the antigen and the mode of stimulation shape the magnitude and breadth of macrophage innate memory response, which impacts subsequent response to Mtb infection. IMPORTANCE Trained immunity (a.k.a. innate memory response) is a novel concept that has been rapidly emerging as a mechanism underpinning the non-specific immunity of innate immune cells, such as macrophages. However, the association between the nature of the stimuli and the corresponding immune correlate of trained immunity is not fully understood. Similarly, the kinetics of immunological and metabolic characteristics of macrophages upon "training" by the same antigen as primary and secondary stimuli (homologous stimulation) are not fully characterized. Furthermore, the ability of antigens such as purified protein derivative (PPD) and heat-killed-Mtb to induce trained immunity remains unknown. Similarly, the response of macrophages primed and trained by homologous stimulants to subsequent infection by pathogenic Mtb is yet to be reported. In this study, we evaluated the hypothesis that the nature of the stimuli impacts the depth and breadth of trained immunity in macrophages, which differentially affects their response to Mtb infection.
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Affiliation(s)
- Ranjeet Kumar
- Public Health Research Institute, Rutgers-New Jersey Medical School, Newark, New Jersey, USA
| | - Afsal Kolloli
- Public Health Research Institute, Rutgers-New Jersey Medical School, Newark, New Jersey, USA
| | - Pooja Singh
- Public Health Research Institute, Rutgers-New Jersey Medical School, Newark, New Jersey, USA
| | - Lanbo Shi
- Public Health Research Institute, Rutgers-New Jersey Medical School, Newark, New Jersey, USA
| | - Andreas Kupz
- Centre for Molecular Therapeutics, Australian Institute of Tropical Health and Medicine (AITHM), James Cook University, Cairns & Townsville, Queensland, Australia
| | - Selvakumar Subbian
- Public Health Research Institute, Rutgers-New Jersey Medical School, Newark, New Jersey, USA
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McLellan J, Croen LA, Iosif AM, Ashwood P, Yoshida C, Berger K, Van de Water J. Differences in mid-gestational and early postnatal neonatal cytokines and chemokines are associated with patterns of maternal autoantibodies in the context of autism. Cereb Cortex 2024; 34:50-62. [PMID: 38696596 PMCID: PMC11065110 DOI: 10.1093/cercor/bhae082] [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: 11/01/2023] [Revised: 01/25/2024] [Accepted: 01/06/2024] [Indexed: 05/04/2024] Open
Abstract
Associations between maternal immune dysregulation (including autoimmunity and skewed cytokine/chemokine profiles) and offspring neurodevelopmental disorders such as autism have been reported. In maternal autoantibody-related autism, specific maternally derived autoantibodies can access the fetal compartment to target eight proteins critical for neurodevelopment. We examined the relationship between maternal autoantibodies to the eight maternal autoantibody-related autism proteins and cytokine/chemokine profiles in the second trimester of pregnancy in mothers of children later diagnosed with autism and their neonates' cytokine/chemokine profiles. Using banked maternal serum samples from 15 to 19 weeks of gestation from the Early Markers for Autism Study and corresponding banked newborn bloodspots, we identified three maternal/offspring groups based on maternal autoantibody status: (1) mothers with autoantibodies to one or more of the eight maternal autoantibody-related autismassociated proteins but not a maternal autoantibody-related autism-specific pattern, (2) mothers with a known maternal autoantibody-related autism pattern, and (3) mothers without autoantibodies to any of the eight maternal autoantibody-related autism proteins. Using a multiplex platform, we measured maternal second trimester and neonatal cytokine/chemokine levels. This combined analysis aimed to determine potential associations between maternal autoantibodies and the maternal and neonatal cytokine/chemokine profiles, each of which has been shown to have implications on offspring neurodevelopment independently.
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Affiliation(s)
- Janna McLellan
- Department of Internal Medicine, Division of Rheumatology, Allergy, and Clinical Immunology, University of California Davis, 451 Health Sciences Drive, Suite 6505C, Davis, CA 95616, United States
| | - Lisa A Croen
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612, United States
| | - Ana-Maria Iosif
- Department of Public Health Sciences, Division of Biostatistics, University of California Davis, Medical Sciences 1C, Davis, CA, 95616, United States
| | - Paul Ashwood
- MIND Institute, University of California Davis, 2805 Wet Lab Building, Sacramento, CA 95817, United States
- Department of Medical Microbiology and Immunology, University of California Davis, 3146 One Shields Avenue, Tupper Hall, Davis, CA 95616, United States
| | - Cathleen Yoshida
- Division of Research, Kaiser Permanente Northern California, 2000 Broadway, Oakland, CA 94612, United States
| | - Kimberly Berger
- Sequoia Foundation, 741 Addison Suite B, Berkeley, CA 94710, United States
| | - Judy Van de Water
- Department of Internal Medicine, Division of Rheumatology, Allergy, and Clinical Immunology, University of California Davis, 451 Health Sciences Drive, Suite 6505C, Davis, CA 95616, United States
- MIND Institute, University of California Davis, 2805 Wet Lab Building, Sacramento, CA 95817, United States
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Lu Y, Sun Y, Xu K, Saaoud F, Shao Y, Drummer C, Wu S, Hu W, Yu J, Kunapuli SP, Bethea JR, Vazquez-Padron RI, Sun J, Jiang X, Wang H, Yang X. Aorta in Pathologies May Function as an Immune Organ by Upregulating Secretomes for Immune and Vascular Cell Activation, Differentiation and Trans-Differentiation-Early Secretomes may Serve as Drivers for Trained Immunity. Front Immunol 2022; 13:858256. [PMID: 35320939 PMCID: PMC8934864 DOI: 10.3389/fimmu.2022.858256] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 02/09/2022] [Indexed: 01/09/2023] Open
Abstract
To determine whether aorta becomes immune organ in pathologies, we performed transcriptomic analyses of six types of secretomic genes (SGs) in aorta and vascular cells and made the following findings: 1) 53.7% out of 21,306 human protein genes are classified into six secretomes, namely, canonical, caspase 1, caspase 4, exosome, Weibel-Palade body, and autophagy; 2) Atherosclerosis (AS), chronic kidney disease (CKD) and abdominal aortic aneurysm (AAA) modulate six secretomes in aortas; and Middle East Respiratory Syndrome Coronavirus (MERS-CoV, COVID-19 homologous) infected endothelial cells (ECs) and angiotensin-II (Ang-II) treated vascular smooth muscle cells (VSMCs) modulate six secretomes; 3) AS aortas upregulate T and B cell immune SGs; CKD aortas upregulate SGs for cardiac hypertrophy, and hepatic fibrosis; and AAA aorta upregulate SGs for neuromuscular signaling and protein catabolism; 4) Ang-II induced AAA, canonical, caspase 4, and exosome SGs have two expression peaks of high (day 7)-low (day 14)-high (day 28) patterns; 5) Elastase induced AAA aortas have more inflammatory/immune pathways than that of Ang-II induced AAA aortas; 6) Most disease-upregulated cytokines in aorta may be secreted via canonical and exosome secretomes; 7) Canonical and caspase 1 SGs play roles at early MERS-CoV infected ECs whereas caspase 4 and exosome SGs play roles in late/chronic phases; and the early upregulated canonical and caspase 1 SGs may function as drivers for trained immunity (innate immune memory); 8) Venous ECs from arteriovenous fistula (AVF) upregulate SGs in five secretomes; and 9) Increased some of 101 trained immunity genes and decreased trained tolerance regulator IRG1 participate in upregulations of SGs in atherosclerotic, Ang-II induced AAA and CKD aortas, and MERS-CoV infected ECs, but less in SGs upregulated in AVF ECs. IL-1 family cytokines, HIF1α, SET7 and mTOR, ROS regulators NRF2 and NOX2 partially regulate trained immunity genes; and NRF2 plays roles in downregulating SGs more than that of NOX2 in upregulating SGs. These results provide novel insights on the roles of aorta as immune organ in upregulating secretomes and driving immune and vascular cell differentiations in COVID-19, cardiovascular diseases, inflammations, transplantations, autoimmune diseases and cancers.
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Affiliation(s)
- Yifan Lu
- Cardiovascular Research Center, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Yu Sun
- Cardiovascular Research Center, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Keman Xu
- Cardiovascular Research Center, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Fatma Saaoud
- Cardiovascular Research Center, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Ying Shao
- Cardiovascular Research Center, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Charles Drummer
- Cardiovascular Research Center, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Sheng Wu
- Center for Metabolic Disease Research, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Wenhui Hu
- Center for Metabolic Disease Research, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Jun Yu
- Center for Metabolic Disease Research, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Satya P Kunapuli
- Sol Sherry Thrombosis Research, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - John R Bethea
- Department of Biology, College of Arts and Sciences, Drexel University, Philadelphia, PA, United States
| | - Roberto I Vazquez-Padron
- DeWitt Daughtry Family Department of Surgery, Leonard M. Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Jianxin Sun
- Department of Medicine, Center for Translational Medicine, Thomas Jefferson University, Philadelphia, PA, United States
| | - Xiaohua Jiang
- Cardiovascular Research Center, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States.,Center for Metabolic Disease Research, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Hong Wang
- Center for Metabolic Disease Research, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
| | - Xiaofeng Yang
- Cardiovascular Research Center, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States.,Center for Metabolic Disease Research, Departments of Cardiovascular Sciences and Biomedical Education and Data Sciences, Temple University Lewis Katz School of Medicine, Philadelphia, PA, United States
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