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Meade RK, Smith CM. Immunological roads diverged: mapping tuberculosis outcomes in mice. Trends Microbiol 2024:S0966-842X(24)00170-7. [PMID: 39034171 DOI: 10.1016/j.tim.2024.06.007] [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: 05/06/2024] [Revised: 06/24/2024] [Accepted: 06/25/2024] [Indexed: 07/23/2024]
Abstract
The journey from phenotypic observation to causal genetic mechanism is a long and challenging road. For pathogens like Mycobacterium tuberculosis (Mtb), which causes tuberculosis (TB), host-pathogen coevolution has spanned millennia, costing millions of human lives. Mammalian models can systematically recapitulate host genetic variation, producing a spectrum of disease outcomes. Leveraging genome sequences and deep phenotyping data from infected mouse genetic reference populations (GRPs), quantitative trait locus (QTL) mapping approaches have successfully identified host genomic regions associated with TB phenotypes. Here, we review the ongoing optimization of QTL mapping study design alongside advances in mouse GRPs. These next-generation resources and approaches have enabled identification of novel host-pathogen interactions governing one of the most prevalent infectious diseases in the world today.
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Affiliation(s)
- Rachel K Meade
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA; University Program in Genetics and Genomics, Duke University, Durham, NC, USA
| | - Clare M Smith
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA; University Program in Genetics and Genomics, Duke University, Durham, NC, USA.
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2
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Koyuncu D, Tavolara T, Gatti DM, Gower AC, Ginese ML, Kramnik I, Yener B, Sajjad U, Niazi MKK, Gurcan M, Alsharaydeh A, Beamer G. B cells in perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell signatures identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice. Infect Immun 2024; 92:e0026323. [PMID: 38899881 PMCID: PMC11238564 DOI: 10.1128/iai.00263-23] [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: 07/25/2023] [Accepted: 04/09/2024] [Indexed: 06/21/2024] Open
Abstract
Because most humans resist Mycobacterium tuberculosis infection, there is a paucity of lung samples to study. To address this gap, we infected Diversity Outbred mice with M. tuberculosis and studied the lungs of mice in different disease states. After a low-dose aerosol infection, progressors succumbed to acute, inflammatory lung disease within 60 days, while controllers maintained asymptomatic infection for at least 60 days, and then developed chronic pulmonary tuberculosis (TB) lasting months to more than 1 year. Here, we identified features of asymptomatic M. tuberculosis infection by applying computational and statistical approaches to multimodal data sets. Cytokines and anti-M. tuberculosis cell wall antibodies discriminated progressors vs controllers with chronic pulmonary TB but could not classify mice with asymptomatic infection. However, a novel deep-learning neural network trained on lung granuloma images was able to accurately classify asymptomatically infected lungs vs acute pulmonary TB in progressors vs chronic pulmonary TB in controllers, and discrimination was based on perivascular and peribronchiolar lymphocytes. Because the discriminatory lesion was rich in lymphocytes and CD4 T cell-mediated immunity is required for resistance, we expected CD4 T-cell genes would be elevated in asymptomatic infection. However, the significantly different, highly expressed genes were from B-cell pathways (e.g., Bank1, Cd19, Cd79, Fcmr, Ms4a1, Pax5, and H2-Ob), and CD20+ B cells were enriched in the perivascular and peribronchiolar regions of mice with asymptomatic M. tuberculosis infection. Together, these results indicate that genetically controlled B-cell responses are important for establishing asymptomatic M. tuberculosis lung infection.
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Affiliation(s)
- Deniz Koyuncu
- Rensselaer Polytechnic Institute, Troy, New York, USA
| | - Thomas Tavolara
- Wake Forest University, School of Medicine, Winston Salem, North Carolina, USA
| | | | - Adam C Gower
- Boston University Clinical and Translational Science Institute, Boston, Massachusetts, USA
| | - Melanie L Ginese
- Tufts University Cummings School of Veterinary Medicine, North Grafton, Massachusetts, USA
| | - Igor Kramnik
- NIEDL, Boston University, Boston, Massachusetts, USA
| | - Bülent Yener
- Rensselaer Polytechnic Institute, Troy, New York, USA
| | - Usama Sajjad
- Wake Forest University, School of Medicine, Winston Salem, North Carolina, USA
| | | | - Metin Gurcan
- Wake Forest University, School of Medicine, Winston Salem, North Carolina, USA
| | | | - Gillian Beamer
- Aiforia Inc., Cambridge, Massachusetts, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
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3
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Dartois V, Bonfield TL, Boyce JP, Daley CL, Dick T, Gonzalez-Juarrero M, Gupta S, Kramnik I, Lamichhane G, Laughon BE, Lorè NI, Malcolm KC, Olivier KN, Tuggle KL, Jackson M. Preclinical murine models for the testing of antimicrobials against Mycobacterium abscessus pulmonary infections: Current practices and recommendations. Tuberculosis (Edinb) 2024; 147:102503. [PMID: 38729070 PMCID: PMC11168888 DOI: 10.1016/j.tube.2024.102503] [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: 01/31/2024] [Revised: 03/08/2024] [Accepted: 03/17/2024] [Indexed: 05/12/2024]
Abstract
Mycobacterium abscessus, a rapidly growing nontuberculous mycobacterium, is increasingly recognized as an important pathogen of the human lung, disproportionally affecting people with cystic fibrosis (CF) and other susceptible individuals with non-CF bronchiectasis and compromised immune functions. M. abscessus infections are extremely difficult to treat due to intrinsic resistance to many antibiotics, including most anti-tuberculous drugs. Current standard-of-care chemotherapy is long, includes multiple oral and parenteral repurposed drugs, and is associated with significant toxicity. The development of more effective oral antibiotics to treat M. abscessus infections has thus emerged as a high priority. While murine models have proven instrumental in predicting the efficacy of therapeutic treatments for M. tuberculosis infections, the preclinical evaluation of drugs against M. abscessus infections has proven more challenging due to the difficulty of establishing a progressive, sustained, pulmonary infection with this pathogen in mice. To address this issue, a series of three workshops were hosted in 2023 by the Cystic Fibrosis Foundation (CFF) and the National Institute of Allergy and Infectious Diseases (NIAID) to review the current murine models of M. abscessus infections, discuss current challenges and identify priorities toward establishing validated and globally harmonized preclinical models. This paper summarizes the key points from these workshops. The hope is that the recommendations that emerged from this exercise will facilitate the implementation of informative murine models of therapeutic efficacy testing across laboratories, improve reproducibility from lab-to-lab and accelerate preclinical-to-clinical translation.
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Affiliation(s)
- Véronique Dartois
- Center for Discovery and Innovation & Department of Medical Sciences, Hackensack Meridian School of Medicine, Hackensack Meridian Health, Nutley, NJ, USA.
| | - Tracey L Bonfield
- Genetics and Genome Sciences and National Center for Regenerative Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Jim P Boyce
- Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Charles L Daley
- Department of Medicine, National Jewish Health, Denver, CO, USA; Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Thomas Dick
- Center for Discovery and Innovation & Department of Medical Sciences, Hackensack Meridian School of Medicine, Hackensack Meridian Health, Nutley, NJ, USA; Department of Microbiology and Immunology, Georgetown University, Washington, DC, USA
| | - Mercedes Gonzalez-Juarrero
- Mycobacteria Research Laboratories, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, 80523-1682, USA
| | - Shashank Gupta
- Laboratory of Chronic Airway Infection, Pulmonary Branch, National Heart, Lung, and Blood Institute, Bethesda, MD, USA; Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Igor Kramnik
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, 02215, USA; Department of Medicine, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Gyanu Lamichhane
- Division of Infectious Diseases, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Barbara E Laughon
- Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Nicola I Lorè
- Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Kenneth C Malcolm
- Department of Medicine, National Jewish Health, Denver, CO, USA; Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Kenneth N Olivier
- Department of Medicine, Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina, USA; Marsico Lung Institute, Chapel Hill, 27599-7248, NC, USA
| | | | - Mary Jackson
- Mycobacteria Research Laboratories, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, 80523-1682, USA.
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Painter H, Larsen SE, Williams BD, Abdelaal HFM, Baldwin SL, Fletcher HA, Fiore-Gartland A, Coler RN. Backtranslation of human RNA biosignatures of tuberculosis disease risk into the preclinical pipeline is condition dependent. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.21.600067. [PMID: 38948876 PMCID: PMC11212953 DOI: 10.1101/2024.06.21.600067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
It is not clear whether human progression to active tuberculosis disease (TB) risk signatures are viable endpoint criteria for evaluations of treatments in clinical or preclinical development. TB is the deadliest infectious disease globally and more efficacious vaccines are needed to reduce this mortality. However, the immune correlates of protection for either preventing infection with Mycobacterium tuberculosis or preventing TB disease have yet to be completely defined, making the advancement of candidate vaccines through the pipeline slow, costly, and fraught with risk. Human-derived correlate of risk (COR) gene signatures, which identify an individual's risk to progressing to active TB disease, provide an opportunity for evaluating new therapies for TB with clear and defined endpoints. Though prospective clinical trials with longitudinal sampling are prohibitively expensive, characterization of COR gene signatures is practical with preclinical models. Using a 3Rs (Replacement, Reduction and Refinement) approach we reanalyzed heterogeneous publicly available transcriptional datasets to determine whether a specific set of COR signatures are viable endpoints in the preclinical pipeline. We selected RISK6, Sweeney3 and BATF2 human-derived blood-based RNA biosignatures because they require relatively few genes to assign a score and have been carefully evaluated across several clinical cohorts. Excitingly, these data provide proof-of-concept that human COR signatures seem to have high fidelity across several tissue types in the preclinical TB model pipeline and show best performance when the model most closely reflected human infection or disease conditions. Human-derived COR signatures offer an opportunity for high-throughput preclinical endpoint criteria of vaccine and drug therapy evaluations. One Sentence Summary Human-derived biosignatures of tuberculosis disease progression were evaluated for their predictive fidelity across preclinical species and derived tissues using available public data sets.
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Gatti DM, Tyler AL, Mahoney JM, Churchill GA, Yener B, Koyuncu D, Gurcan MN, Niazi MKK, Tavolara T, Gower A, Dayao D, McGlone E, Ginese ML, Specht A, Alsharaydeh A, Tessier PA, Kurtz SL, Elkins KL, Kramnik I, Beamer G. Systems genetics uncover new loci containing functional gene candidates in Mycobacterium tuberculosis-infected Diversity Outbred mice. PLoS Pathog 2024; 20:e1011915. [PMID: 38861581 PMCID: PMC11195971 DOI: 10.1371/journal.ppat.1011915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 06/24/2024] [Accepted: 04/17/2024] [Indexed: 06/13/2024] Open
Abstract
Mycobacterium tuberculosis infects two billion people across the globe, and results in 8-9 million new tuberculosis (TB) cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. Here, we investigate the complex genetic basis of pulmonary TB by modelling human genetic diversity with the Diversity Outbred mouse population. When infected with M. tuberculosis, one-third develop early onset, rapidly progressive, necrotizing granulomas and succumb within 60 days. The remaining develop non-necrotizing granulomas and survive longer than 60 days. Genetic mapping using immune and inflammatory mediators; and clinical, microbiological, and granuloma correlates of disease identified five new loci on mouse chromosomes 1, 2, 4, 16; and three known loci on chromosomes 3 and 17. Further, multiple positively correlated traits shared loci on chromosomes 1, 16, and 17 and had similar patterns of allele effects, suggesting these loci contain critical genetic regulators of inflammatory responses to M. tuberculosis. To narrow the list of candidate genes, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks to generate scores representing functional relationships. The scores were used to rank candidates for each mapped trait, resulting in 11 candidate genes: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Although all candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling, and all contain single nucleotide polymorphisms (SNPs), SNPs in only four genes (S100a8, Itgb5, Fstl1, Zfp318) are predicted to have deleterious effects on protein functions. We performed methodological and candidate validations to (i) assess biological relevance of predicted allele effects by showing that Diversity Outbred mice carrying PWK/PhJ alleles at the H-2 locus on chromosome 17 QTL have shorter survival; (ii) confirm accuracy of predicted allele effects by quantifying S100A8 protein in inbred founder strains; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this body of work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and functionally relevant gene candidates that may be major regulators of complex host-pathogens interactions contributing to granuloma necrosis and acute inflammation in pulmonary TB.
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Affiliation(s)
- Daniel M. Gatti
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Anna L. Tyler
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | | | | | - Bulent Yener
- Rensselaer Polytechnic Institute, Troy, New York, United States of America
| | - Deniz Koyuncu
- Rensselaer Polytechnic Institute, Troy, New York, United States of America
| | - Metin N. Gurcan
- Wake Forest University School of Medicine, Winston Salem, North Carolina, United States of America
| | - MK Khalid Niazi
- Wake Forest University School of Medicine, Winston Salem, North Carolina, United States of America
| | - Thomas Tavolara
- Wake Forest University School of Medicine, Winston Salem, North Carolina, United States of America
| | - Adam Gower
- Clinical and Translational Science Institute, Boston University, Boston, Massachusetts, United States of America
| | - Denise Dayao
- Tufts University Cummings School of Veterinary Medicine, North Grafton, Massachusetts, United States of America
| | - Emily McGlone
- Tufts University Cummings School of Veterinary Medicine, North Grafton, Massachusetts, United States of America
| | - Melanie L. Ginese
- Tufts University Cummings School of Veterinary Medicine, North Grafton, Massachusetts, United States of America
| | - Aubrey Specht
- Tufts University Cummings School of Veterinary Medicine, North Grafton, Massachusetts, United States of America
| | - Anas Alsharaydeh
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
| | - Philipe A. Tessier
- Department of Microbiology and Immunology, Laval University School of Medicine, Quebec, Canada
| | - Sherry L. Kurtz
- Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, United States of America
| | - Karen L. Elkins
- Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, United States of America
| | - Igor Kramnik
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, Massachusetts, United States of America
| | - Gillian Beamer
- Texas Biomedical Research Institute, San Antonio, Texas, United States of America
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Bates TA, Trank-Greene M, Nguyenla X, Anastas A, Gurmessa SK, Merutka IR, Dixon SD, Shumate A, Groncki AR, Parson MAH, Ingram JR, Barklis E, Burke JE, Shinde U, Ploegh HL, Tafesse FG. ESAT-6 undergoes self-association at phagosomal pH and an ESAT-6-specific nanobody restricts M. tuberculosis growth in macrophages. eLife 2024; 12:RP91930. [PMID: 38805257 PMCID: PMC11132683 DOI: 10.7554/elife.91930] [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] [Indexed: 05/29/2024] Open
Abstract
Mycobacterium tuberculosis (Mtb) is known to survive within macrophages by compromising the integrity of the phagosomal compartment in which it resides. This activity primarily relies on the ESX-1 secretion system, predominantly involving the protein duo ESAT-6 and CFP-10. CFP-10 likely acts as a chaperone, while ESAT-6 likely disrupts phagosomal membrane stability via a largely unknown mechanism. we employ a series of biochemical analyses, protein modeling techniques, and a novel ESAT-6-specific nanobody to gain insight into the ESAT-6's mode of action. First, we measure the binding kinetics of the tight 1:1 complex formed by ESAT-6 and CFP-10 at neutral pH. Subsequently, we demonstrate a rapid self-association of ESAT-6 into large complexes under acidic conditions, leading to the identification of a stable tetrameric ESAT-6 species. Using molecular dynamics simulations, we pinpoint the most probable interaction interface. Furthermore, we show that cytoplasmic expression of an anti-ESAT-6 nanobody blocks Mtb replication, thereby underlining the pivotal role of ESAT-6 in intracellular survival. Together, these data suggest that ESAT-6 acts by a pH-dependent mechanism to establish two-way communication between the cytoplasm and the Mtb-containing phagosome.
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Affiliation(s)
- Timothy A Bates
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
| | - Mila Trank-Greene
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
| | - Xammy Nguyenla
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
| | - Aidan Anastas
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
| | - Sintayehu K Gurmessa
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
| | - Ilaria R Merutka
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
| | - Shandee D Dixon
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
| | - Anthony Shumate
- Department of Chemical Physiology and Biochemistry, Oregon Health & Science UniversityPortlandUnited States
| | - Abigail R Groncki
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
| | - Matthew AH Parson
- Department of Biochemistry and Microbiology, University of VictoriaVictoriaCanada
| | - Jessica R Ingram
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Harvard Medical SchoolBostonUnited States
| | - Eric Barklis
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
| | - John E Burke
- Department of Biochemistry and Microbiology, University of VictoriaVictoriaCanada
- Department of Biochemistry and Molecular Biology, The University of British ColumbiaVancouverCanada
| | - Ujwal Shinde
- Department of Chemical Physiology and Biochemistry, Oregon Health & Science UniversityPortlandUnited States
| | - Hidde L Ploegh
- Program in Cellular and Molecular Medicine, Boston Children's Hospital, Harvard Medical SchoolBostonUnited States
| | - Fikadu G Tafesse
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences UniversityPortlandUnited States
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7
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Bates TA, Trank-Greene M, Nguyenla X, Anastas A, Gurmessa SK, Merutka IR, Dixon SD, Shumate A, Groncki AR, Parson MAH, Ingram JR, Barklis E, Burke JE, Shinde U, Ploegh HL, Tafesse FG. ESAT-6 undergoes self-association at phagosomal pH and an ESAT-6 specific nanobody restricts M. tuberculosis growth in macrophages. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.16.553641. [PMID: 37645775 PMCID: PMC10462100 DOI: 10.1101/2023.08.16.553641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Mycobacterium tuberculosis (Mtb) is known to survive within macrophages by compromising the integrity of the phagosomal compartment in which it resides. This activity primarily relies on the ESX-1 secretion system, predominantly involving the protein duo ESAT-6 and CFP-10. CFP-10 likely acts as a chaperone, while ESAT-6 likely disrupts phagosomal membrane stability via a largely unknown mechanism. we employ a series of biochemical analyses, protein modeling techniques, and a novel ESAT-6-specific nanobody to gain insight into the ESAT-6's mode of action. First, we measure the binding kinetics of the tight 1:1 complex formed by ESAT-6 and CFP-10 at neutral pH. Subsequently, we demonstrate a rapid self-association of ESAT-6 into large complexes under acidic conditions, leading to the identification of a stable tetrameric ESAT-6 species. Using molecular dynamics simulations, we pinpoint the most probable interaction interface. Furthermore, we show that cytoplasmic expression of an anti-ESAT-6 nanobody blocks Mtb replication, thereby underlining the pivotal role of ESAT-6 in intracellular survival. Together, these data suggest that ESAT-6 acts by a pH dependent mechanism to establish two-way communication between the cytoplasm and the Mtb-containing phagosome.
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Affiliation(s)
- Timothy A Bates
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
| | - Mila Trank-Greene
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
| | - Xammy Nguyenla
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
| | - Aidan Anastas
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
| | - Sintayehu K Gurmessa
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
| | - Ilaria R Merutka
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
| | - Shandee D Dixon
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
| | - Anthony Shumate
- Department of Chemical Physiology and Biochemistry, Oregon Health & Science University, Portland, Oregon, United States
| | - Abigail R Groncki
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
| | - Matthew AH Parson
- Department of Biochemistry and Microbiology, University of Victoria, Victoria, Canada
| | - Jessica R Ingram
- Program in Cellular and Molecular Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Eric Barklis
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
| | - John E Burke
- Department of Biochemistry and Microbiology, University of Victoria, Victoria, Canada
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, Canada
| | - Ujwal Shinde
- Department of Chemical Physiology and Biochemistry, Oregon Health & Science University, Portland, Oregon, United States
| | - Hidde L Ploegh
- Program in Cellular and Molecular Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Fikadu G Tafesse
- Department of Molecular Microbiology and Immunology, Oregon Health & Sciences University, Portland, Oregon, United States
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Razbek J, Daken M, Chen Y, Ma L, Zhang Y, Xu W, Wen B, Wang J, Wang X, Cao M. Association Studies of Serum Levels of TNF- α, IL-10, IFN-γ and CXCL 5 with Latent Tuberculosis Infection in Close Contacts. Infect Drug Resist 2024; 17:899-910. [PMID: 38468847 PMCID: PMC10926862 DOI: 10.2147/idr.s442682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 02/22/2024] [Indexed: 03/13/2024] Open
Abstract
Purpose Early recognition and treatment of latent tuberculosis infection(LTBI) is key to tuberculosis(TB) prevention. However, the emergence of LTBI is influenced by a combination of factors, of which the role of individual immune cytokines remains controversial. The aim of this study is to explore the influencing factors of LTBI and their effects with cytokines on LTBI. Patients and Methods Close contacts of tuberculosis in Urumqi City from 2021 to 2022 were selected for the study to conduct a field survey. It used logistic regression model to analyse the influencing factors of LTBI, principal component analysis to extract a composite indicators of cytokines, and structural equation modelling to explore the direct and indirect effects of cytokines and influencing factors on LTBI. Results LTBI infection rate of 33.3% among 288 TB close contacts. A multifactorial Logistic model showed that factors influencing LTBI included education, daily contact hours, eating animal liver, and drinking coffee (P<0.05); After controlling for confounding factors and extracting composite indicators of cytokines using principal component analysis, CXCL5 and IFN-γ is a protective factor for LTBI(OR=0.572, P=0.047), IL-10 and TNF-α is a risk factor for LTBI(OR=2.119, P=0.010); Structural equation modelling shows drinking coffee, eating animal liver, daily contact hours, and IL-10 and TNF-α had direct effects on LTBI and educations had indirect effects on LTBI(P<0.05). Conclusion IL-10 and TNF-α are involved in the immune response and are directly related to LTBI. By monitoring the cytokine levels of TB close contacts and paying attention to their dietary habits and exposure, we can detect and intervene in LTBI at an early stage and control their progression to TB.
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Affiliation(s)
- Jaina Razbek
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Mayisha Daken
- Department of Epidemic Prevention, Karamay Centre for Disease Control and Prevention, Karamay, 834000, People’s Republic of China
| | - Yanggui Chen
- Department of Prevention and Control of Tuberculosis, Urumqi Centre for Disease Control and Prevention, Urumqi, 830011, People’s Republic of China
| | - Li Ma
- Department of Prevention and Control of Tuberculosis, Urumqi Centre for Disease Control and Prevention, Urumqi, 830011, People’s Republic of China
| | - Yan Zhang
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Wanting Xu
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Baofeng Wen
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Junan Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Xiaomin Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
| | - Mingqin Cao
- Department of Epidemiology and Health Statistics, College of Public Health, Xinjiang Medical University, Urumqi, 830011, People’s Republic of China
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9
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Acharya V, Choi D, Yener B, Beamer G. Prediction of Tuberculosis From Lung Tissue Images of Diversity Outbred Mice Using Jump Knowledge Based Cell Graph Neural Network. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2024; 12:17164-17194. [PMID: 38515959 PMCID: PMC10956573 DOI: 10.1109/access.2024.3359989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Tuberculosis (TB), primarily affecting the lungs, is caused by the bacterium Mycobacterium tuberculosis and poses a significant health risk. Detecting acid-fast bacilli (AFB) in stained samples is critical for TB diagnosis. Whole Slide (WS) Imaging allows for digitally examining these stained samples. However, current deep-learning approaches to analyzing large-sized whole slide images (WSIs) often employ patch-wise analysis, potentially missing the complex spatial patterns observed in the granuloma essential for accurate TB classification. To address this limitation, we propose an approach that models cell characteristics and interactions as a graph, capturing both cell-level information and the overall tissue micro-architecture. This method differs from the strategies in related cell graph-based works that rely on edge thresholds based on sparsity/density in cell graph construction, emphasizing a biologically informed threshold determination instead. We introduce a cell graph-based jumping knowledge neural network (CG-JKNN) that operates on the cell graphs where the edge thresholds are selected based on the length of the mycobacteria's cords and the activated macrophage nucleus's size to reflect the actual biological interactions observed in the tissue. The primary process involves training a Convolutional Neural Network (CNN) to segment AFBs and macrophage nuclei, followed by converting large (42831*41159 pixels) lung histology images into cell graphs where an activated macrophage nucleus/AFB represents each node within the graph and their interactions are denoted as edges. To enhance the interpretability of our model, we employ Integrated Gradients and Shapely Additive Explanations (SHAP). Our analysis incorporated a combination of 33 graph metrics and 20 cell morphology features. In terms of traditional machine learning models, Extreme Gradient Boosting (XGBoost) was the best performer, achieving an F1 score of 0.9813 and an Area under the Precision-Recall Curve (AUPRC) of 0.9848 on the test set. Among graph-based models, our CG-JKNN was the top performer, attaining an F1 score of 0.9549 and an AUPRC of 0.9846 on the held-out test set. The integration of graph-based and morphological features proved highly effective, with CG-JKNN and XGBoost showing promising results in classifying instances into AFB and activated macrophage nucleus. The features identified as significant by our models closely align with the criteria used by pathologists in practice, highlighting the clinical applicability of our approach. Future work will explore knowledge distillation techniques and graph-level classification into distinct TB progression categories.
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Affiliation(s)
| | - Diana Choi
- Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA 02155, USA
| | - BüLENT Yener
- Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Gillian Beamer
- Research Pathology, Aiforia Technologies, Cambridge, MA 02142, USA
- Texas Biomedical Research Institute, San Antonio, TX 78227, USA
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10
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Gatti DM, Tyler AL, Mahoney JM, Churchill GA, Yener B, Koyuncu D, Gurcan MN, Niazi M, Tavolara T, Gower AC, Dayao D, McGlone E, Ginese ML, Specht A, Alsharaydeh A, Tessier PA, Kurtz SL, Elkins K, Kramnik I, Beamer G. Systems genetics uncover new loci containing functional gene candidates in Mycobacterium tuberculosis-infected Diversity Outbred mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.21.572738. [PMID: 38187647 PMCID: PMC10769337 DOI: 10.1101/2023.12.21.572738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Mycobacterium tuberculosis, the bacillus that causes tuberculosis (TB), infects 2 billion people across the globe, and results in 8-9 million new TB cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. We investigated the complex genetic basis of pulmonary TB by modelling human genetic diversity with the Diversity Outbred mouse population. When infected with M. tuberculosis, one-third develop early onset, rapidly progressive, necrotizing granulomas and succumb within 60 days. The remaining develop non-necrotizing granulomas and survive longer than 60 days. Genetic mapping using clinical indicators of disease, granuloma histopathological features, and immune response traits identified five new loci on mouse chromosomes 1, 2, 4, 16 and three previously identified loci on chromosomes 3 and 17. Quantitative trait loci (QTLs) on chromosomes 1, 16, and 17, associated with multiple correlated traits and had similar patterns of allele effects, suggesting these QTLs contain important genetic regulators of responses to M. tuberculosis. To narrow the list of candidate genes in QTLs, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks, generating functional scores. The scores were then used to rank candidates for each mapped trait in each locus, resulting in 11 candidates: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Importantly, all 11 candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling. Further, all candidates contain single nucleotide polymorphisms (SNPs), and some but not all SNPs were predicted to have deleterious consequences on protein functions. Multiple methods were used for validation including (i) a statistical method that showed Diversity Outbred mice carrying PWH/PhJ alleles on chromosome 17 QTL have shorter survival; (ii) quantification of S100A8 protein levels, confirming predicted allele effects; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and new functionally relevant gene candidates that may be major regulators of granuloma necrosis and acute inflammation in pulmonary TB.
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Affiliation(s)
- D M Gatti
- The Jackson Laboratory, Bar Harbor, ME
| | - A L Tyler
- The Jackson Laboratory, Bar Harbor, ME
| | | | | | - B Yener
- Rensselaer Polytechnic Institute, Troy, NY
| | - D Koyuncu
- Rensselaer Polytechnic Institute, Troy, NY
| | - M N Gurcan
- Wake Forest University School of Medicine, Winston Salem, NC
| | - Mkk Niazi
- Wake Forest University School of Medicine, Winston Salem, NC
| | - T Tavolara
- Wake Forest University School of Medicine, Winston Salem, NC
| | - A C Gower
- Clinical and Translational Science Institute, Boston University, Boston, MA
| | - D Dayao
- Tufts University Cummings School of Veterinary Medicine, North Grafton, MA
| | - E McGlone
- Tufts University Cummings School of Veterinary Medicine, North Grafton, MA
| | - M L Ginese
- Tufts University Cummings School of Veterinary Medicine, North Grafton, MA
| | - A Specht
- Tufts University Cummings School of Veterinary Medicine, North Grafton, MA
| | - A Alsharaydeh
- Texas Biomedical Research Institute, San Antonio, TX
| | - P A Tessier
- Department of Microbiology and Immunology, Laval University School of Medicine, Quebec, Canada
| | - S L Kurtz
- Center for Biologics, Food and Drug Administration, Bethesda, MD
| | - K Elkins
- Center for Biologics, Food and Drug Administration, Bethesda, MD
| | - I Kramnik
- NIEDL, Boston University, Boston, MA
| | - G Beamer
- Texas Biomedical Research Institute, San Antonio, TX
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11
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Tjale MA, Ombinda-Lemboumba S, Maphanga C, Mthunzi-Kufa P. TB diagnostic insights, progress made on point of care diagnostics and bioinformatics as an additional tool for improvement. Indian J Tuberc 2023; 70:468-474. [PMID: 37968053 DOI: 10.1016/j.ijtb.2023.03.023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 08/19/2022] [Accepted: 03/31/2023] [Indexed: 11/17/2023]
Abstract
Despite major efforts made to control tuberculosis disease (TB), this disease continues to present a major global health challenge and drug resistance is continuously growing. TB is caused by Mycobacterium tuberculosis and spreads exclusively via human-to-human contact transmission. Therefore, early detection and diagnosis for proper treatment with active TB have a great impact on public health. Regardless, most people in developing countries with TB or TB-associated symptoms do not have access to an adequate initial diagnosis. Available bacteriologic-based techniques are either inefficient or may require a longer turnaround time from the laboratory. Contemporarily, non-bacteriologic based methods have both questionable sensitivity and specificity and while others cannot distinguish between active and latent TB. Thus, additional efforts have been made to find accurate diagnostic tests for TB. Herein, we review the available methods used for TB diagnosis, and in addition, we explore point of care (POC) diagnostics as an alternative way to develop TB diagnostic tests and further evaluate whether bioinformatics can be used as an additional screening tool for identification of possible TB biomarkers for the development of POC TB diagnostics, which is part of our research focus.
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Affiliation(s)
- Mabotse A Tjale
- Biophotonics, National Laser Centre, Council for Scientific and Industrial Research, P/O Box 395, Meiring Naudé Road Brummeria, Pretoria, South Africa.
| | - Saturnin Ombinda-Lemboumba
- Biophotonics, National Laser Centre, Council for Scientific and Industrial Research, P/O Box 395, Meiring Naudé Road Brummeria, Pretoria, South Africa
| | - Charles Maphanga
- Biophotonics, National Laser Centre, Council for Scientific and Industrial Research, P/O Box 395, Meiring Naudé Road Brummeria, Pretoria, South Africa; College of Agriculture, Engineering and Science, School of Chemistry and Physics, University of KwaZulu-Natal, Pietermaritzburg Campus, King Edward Avenue, Pietermaritzburg, South Africa
| | - Patience Mthunzi-Kufa
- Biophotonics, National Laser Centre, Council for Scientific and Industrial Research, P/O Box 395, Meiring Naudé Road Brummeria, Pretoria, South Africa; College of Agriculture, Engineering and Science, School of Chemistry and Physics, University of KwaZulu-Natal, Pietermaritzburg Campus, King Edward Avenue, Pietermaritzburg, South Africa
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12
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Corleis B, Bastian M, Hoffmann D, Beer M, Dorhoi A. Animal models for COVID-19 and tuberculosis. Front Immunol 2023; 14:1223260. [PMID: 37638020 PMCID: PMC10451089 DOI: 10.3389/fimmu.2023.1223260] [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: 05/15/2023] [Accepted: 07/21/2023] [Indexed: 08/29/2023] Open
Abstract
Respiratory infections cause tremendous morbidity and mortality worldwide. Amongst these diseases, tuberculosis (TB), a bacterial illness caused by Mycobacterium tuberculosis which often affects the lung, and coronavirus disease 2019 (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2), stand out as major drivers of epidemics of global concern. Despite their unrelated etiology and distinct pathology, these infections affect the same vital organ and share immunopathogenesis traits and an imperative demand to model the diseases at their various progression stages and localizations. Due to the clinical spectrum and heterogeneity of both diseases experimental infections were pursued in a variety of animal models. We summarize mammalian models employed in TB and COVID-19 experimental investigations, highlighting the diversity of rodent models and species peculiarities for each infection. We discuss the utility of non-human primates for translational research and emphasize on the benefits of non-conventional experimental models such as livestock. We epitomize advances facilitated by animal models with regard to understanding disease pathophysiology and immune responses. Finally, we highlight research areas necessitating optimized models and advocate that research of pulmonary infectious diseases could benefit from cross-fertilization between studies of apparently unrelated diseases, such as TB and COVID-19.
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Affiliation(s)
- Björn Corleis
- Institute of Immunology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Greifswald-Insel Riems, Germany
| | - Max Bastian
- Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Greifswald-Insel Riems, Germany
| | - Donata Hoffmann
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Greifswald-Insel Riems, Germany
| | - Martin Beer
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Greifswald-Insel Riems, Germany
| | - Anca Dorhoi
- Institute of Immunology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Greifswald-Insel Riems, Germany
- Faculty of Mathematics and Natural Sciences, University of Greifswald, Greifswald, Germany
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13
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Tyler AL, Spruce C, Kursawe R, Haber A, Ball RL, Pitman WA, Fine AD, Raghupathy N, Walker M, Philip VM, Baker CL, Mahoney JM, Churchill GA, Trowbridge JJ, Stitzel ML, Paigen K, Petkov PM, Carter GW. Variation in histone configurations correlates with gene expression across nine inbred strains of mice. Genome Res 2023; 33:857-871. [PMID: 37217254 PMCID: PMC10519406 DOI: 10.1101/gr.277467.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 05/19/2023] [Indexed: 05/24/2023]
Abstract
The Diversity Outbred (DO) mice and their inbred founders are widely used models of human disease. However, although the genetic diversity of these mice has been well documented, their epigenetic diversity has not. Epigenetic modifications, such as histone modifications and DNA methylation, are important regulators of gene expression and, as such, are a critical mechanistic link between genotype and phenotype. Therefore, creating a map of epigenetic modifications in the DO mice and their founders is an important step toward understanding mechanisms of gene regulation and the link to disease in this widely used resource. To this end, we performed a strain survey of epigenetic modifications in hepatocytes of the DO founders. We surveyed four histone modifications (H3K4me1, H3K4me3, H3K27me3, and H3K27ac), as well as DNA methylation. We used ChromHMM to identify 14 chromatin states, each of which represents a distinct combination of the four histone modifications. We found that the epigenetic landscape is highly variable across the DO founders and is associated with variation in gene expression across strains. We found that epigenetic state imputed into a population of DO mice recapitulated the association with gene expression seen in the founders, suggesting that both histone modifications and DNA methylation are highly heritable mechanisms of gene expression regulation. We illustrate how DO gene expression can be aligned with inbred epigenetic states to identify putative cis-regulatory regions. Finally, we provide a data resource that documents strain-specific variation in the chromatin state and DNA methylation in hepatocytes across nine widely used strains of laboratory mice.
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Affiliation(s)
- Anna L Tyler
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Catrina Spruce
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Romy Kursawe
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA
| | - Annat Haber
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA
| | - Robyn L Ball
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Wendy A Pitman
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Alexander D Fine
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | | | - Michael Walker
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Vivek M Philip
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | | | - J Matthew Mahoney
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Gary A Churchill
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | | | - Michael L Stitzel
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032, USA
| | - Kenneth Paigen
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
| | - Petko M Petkov
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA;
| | - Gregory W Carter
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine 04609, USA
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14
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Sampath P, Rajamanickam A, Thiruvengadam K, Natarajan AP, Hissar S, Dhanapal M, Thangavelu B, Jayabal L, Ramesh PM, Ranganathan UD, Babu S, Bethunaickan R. Plasma chemokines CXCL10 and CXCL9 as potential diagnostic markers of drug-sensitive and drug-resistant tuberculosis. Sci Rep 2023; 13:7404. [PMID: 37149713 PMCID: PMC10163852 DOI: 10.1038/s41598-023-34530-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/03/2023] [Indexed: 05/08/2023] Open
Abstract
Tuberculosis (TB) diagnosis still remains to be a challenge with the currently used immune based diagnostic methods particularly Interferon Gamma Release Assay due to the sensitivity issues and their inability in differentiating stages of TB infection. Immune markers are valuable sources for understanding disease biology and are easily accessible. Chemokines, the stimulant, and the shaper of host immune responses are the vital hub for disease mediated dysregulation and their varied levels in TB disease are considered as an important marker to define the disease status. Hence, we wanted to examine the levels of chemokines among the individuals with drug-resistant, drug-sensitive, and latent TB compared to healthy individuals. Our results demonstrated that the differential levels of chemokines between the study groups and revealed that CXCL10 and CXCL9 as potential markers of drug-resistant and drug-sensitive TB with better stage discriminating abilities.
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Affiliation(s)
- Pavithra Sampath
- Department of Immunology, ICMR-National Institute for Research in Tuberculosis (ICMR-NIRT), No.1. Mayor Sathyamoorthy Road, Chetpet, Chennai, 600 031, India
| | | | - Kannan Thiruvengadam
- Department of Statistics, ICMR-National Institute for Research in Tuberculosis (ICMR-NIRT), Chennai, India
| | | | - Syed Hissar
- Department of Clinical Research, ICMR-National Institute for Research in Tuberculosis (ICMR-NIRT), Chennai, India
| | - Madhavan Dhanapal
- Department of Immunology, ICMR-National Institute for Research in Tuberculosis (ICMR-NIRT), No.1. Mayor Sathyamoorthy Road, Chetpet, Chennai, 600 031, India
| | - Bharathiraja Thangavelu
- Department of Clinical Pharmacology, ICMR-National Institute for Research in Tuberculosis (ICMR-NIRT), Chennai, India
| | | | | | - Uma Devi Ranganathan
- Department of Immunology, ICMR-National Institute for Research in Tuberculosis (ICMR-NIRT), No.1. Mayor Sathyamoorthy Road, Chetpet, Chennai, 600 031, India
| | - Subash Babu
- ICMR-NIRT-NIH-International Center for Excellence in Research, Chennai, India
| | - Ramalingam Bethunaickan
- Department of Immunology, ICMR-National Institute for Research in Tuberculosis (ICMR-NIRT), No.1. Mayor Sathyamoorthy Road, Chetpet, Chennai, 600 031, India.
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15
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Balakrishnan V, Kehrabi Y, Ramanathan G, Paul SA, Tiong CK. Machine learning approaches in diagnosing tuberculosis through biomarkers - A systematic review. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 179:16-25. [PMID: 36931609 DOI: 10.1016/j.pbiomolbio.2023.03.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 02/25/2023] [Accepted: 03/09/2023] [Indexed: 03/17/2023]
Abstract
Biomarker-based tests may facilitate Tuberculosis (TB) diagnosis, accelerate treatment initiation, and thus improve outcomes. This review synthesizes the literature on biomarker-based detection for TB diagnosis using machine learning. The systematic review approach follows the PRISMA guideline. Articles were sought using relevant keywords from Web of Science, PubMed, and Scopus, resulting in 19 eligible studies after a meticulous screening. All the studies were found to have focused on the supervised learning approach, with Support Vector Machine (SVM) and Random Forest emerging as the top two algorithms, with the highest accuracy, sensitivity and specificity reported to be 97.0%, 99.2%, and 98.0%, respectively. Further, protein-based biomarkers were widely explored, followed by gene-based such as RNA sequence and, Spoligotypes. Publicly available datasets were observed to be popularly used by the studies reviewed whilst studies targeting specific cohorts such as HIV patients or children gathering their own data from healthcare facilities, leading to smaller datasets. Of these, most studies used the leave one out cross validation technique to mitigate overfitting. The review shows that machine learning is increasingly assessed in research to improve TB diagnosis through biomarkers, as promising results were shown in terms of model's detection performance. This provides insights on the possible application of machine learning approaches to diagnose TB using biomarkers as opposed to the traditional methods that can be time consuming. Low-middle income settings, where access to basic biomarkers could be provided as compared to sputum-based tests that are not always available, could be a major application of such models.
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Affiliation(s)
- Vimala Balakrishnan
- Faculty of Computer Science and Information Technology, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
| | - Yousra Kehrabi
- Department of Infectious Diseases, Hôpital Bichat-Claude Bernard, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Ghayathri Ramanathan
- Faculty of Computer Science and Information Technology, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Scott Arjay Paul
- School of Biosciences, Faculty of Health and Medical Sciences, Taylor's University, Subang Jaya, Malaysia
| | - Chiong Kian Tiong
- Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
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16
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Sarmah DT, Parveen R, Kundu J, Chatterjee S. Latent tuberculosis and computational biology: A less-talked affair. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 178:17-31. [PMID: 36781150 DOI: 10.1016/j.pbiomolbio.2023.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/13/2023]
Abstract
Tuberculosis (TB) is a pervasive and devastating air-borne disease caused by the organisms belonging to the Mycobacterium tuberculosis (Mtb) complex. Currently, it is the global leader in infectious disease-related death in adults. The proclivity of TB to enter the latent state has become a significant impediment to the global effort to eradicate TB. Despite decades of research, latent tuberculosis (LTB) mechanisms remain poorly understood, making it difficult to develop efficient treatment methods. In this review, we seek to shed light on the current understanding of the mechanism of LTB, with an accentuation on the insights gained through computational biology. We have outlined various well-established computational biology components, such as omics, network-based techniques, mathematical modelling, artificial intelligence, and molecular docking, to disclose the crucial facets of LTB. Additionally, we highlighted important tools and software that may be used to conduct a variety of systems biology assessments. Finally, we conclude the article by addressing the possible future directions in this field, which might help a better understanding of LTB progression.
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Affiliation(s)
- Dipanka Tanu Sarmah
- Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India
| | - Rubi Parveen
- Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India
| | - Jayendrajyoti Kundu
- Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India
| | - Samrat Chatterjee
- Complex Analysis Group, Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, 121001, India.
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17
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Jaffey JA, Shubitz LF, Johnson MDL, Bolch CA, da Cunha A, Murthy AK, Lopez BS, Monasky R, Carswell I, Spiker J, Neubert MJ, Menghani SV. Evaluation of Host Constitutive and Ex Vivo Coccidioidal Antigen-Stimulated Immune Response in Dogs with Naturally Acquired Coccidioidomycosis. J Fungi (Basel) 2023; 9:jof9020213. [PMID: 36836327 PMCID: PMC9959558 DOI: 10.3390/jof9020213] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/10/2023] [Accepted: 01/30/2023] [Indexed: 02/09/2023] Open
Abstract
The early innate immune response to coccidioidomycosis has proven to be pivotal in directing the adaptive immune response and disease outcome in mice and humans but is unexplored in dogs. The objectives of this study were to evaluate the innate immune profile of dogs with coccidioidomycosis and determine if differences exist based on the extent of infection (i.e., pulmonary or disseminated). A total of 28 dogs with coccidioidomycosis (pulmonary, n = 16; disseminated, n = 12) and 10 seronegative healthy controls were enrolled. Immunologic testing was performed immediately, without ex vivo incubation (i.e., constitutive), and after coccidioidal antigen stimulation of whole blood cultures. Whole blood cultures were incubated with a phosphate-buffered solution (PBS) (negative control) or a coccidioidal antigen (rCTS1 (105-310); 10 µg/mL) for 24 h. A validated canine-specific multiplex bead-based assay was used to measure 12 cytokines in plasma and cell culture supernatant. Serum C-reactive protein (CRP) was measured with an ELISA assay. Leukocyte expression of toll-like receptors (TLRs)2 and TLR4 was measured using flow cytometry. Dogs with coccidioidomycosis had higher constitutive plasma keratinocyte chemotactic (KC)-like concentrations (p = 0.02) and serum CRP concentrations compared to controls (p < 0.001). Moreover, dogs with pulmonary coccidioidomycosis had higher serum CRP concentrations than those with dissemination (p = 0.001). Peripheral blood leukocytes from dogs with coccidioidomycosis produced higher concentrations of tumor necrosis factor (TNF)-α (p = 0.0003), interleukin (IL)-6 (p = 0.04), interferon (IFN)-γ (p = 0.03), monocyte chemoattractant protein (MCP)-1 (p = 0.02), IL-10 (p = 0.02), and lower IL-8 (p = 0.003) in supernatants following coccidioidal antigen stimulation when compared to those from control dogs. There was no detectable difference between dogs with pulmonary and disseminated disease. No differences in constitutive or stimulated leukocyte TLR2 and TLR4 expression were found. These results provide information about the constitutive and coccidioidal antigen-specific stimulated immune profile in dogs with naturally acquired coccidioidomycosis.
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Affiliation(s)
- Jared A. Jaffey
- Department of Specialty Medicine, College of Veterinary Medicine, Midwestern University, Glendale, AZ 85308, USA
- Correspondence:
| | - Lisa F. Shubitz
- Valley Fever Center for Excellence, College of Medicine-Tucson, University of Arizona, Tucson, AZ 85724, USA
| | - Michael D. L. Johnson
- Department of Immunobiology, Valley Fever Center for Excellence, BIO5 Institute, Asthma and Airway Disease Research Center, University of Arizona, College of Medicine-Tucson, Tucson, AZ 85724, USA
| | - Charlotte A. Bolch
- Office of Research and Sponsored Programs, College of Graduate Studies, Midwestern University, Glendale, AZ 85308, USA
| | - Anderson da Cunha
- Department of Specialty Medicine, College of Veterinary Medicine, Midwestern University, Glendale, AZ 85308, USA
| | - Ashlesh K. Murthy
- Department of Pathology, College of Veterinary Medicine, Midwestern University, Glendale, AZ 85308, USA
| | - Brina S. Lopez
- Department of Pathology, College of Veterinary Medicine, Midwestern University, Glendale, AZ 85308, USA
| | - Ross Monasky
- Department of Pathology, College of Veterinary Medicine, Midwestern University, Glendale, AZ 85308, USA
| | - Imani Carswell
- Department of Specialty Medicine, College of Veterinary Medicine, Midwestern University, Glendale, AZ 85308, USA
| | - Justine Spiker
- Department of Specialty Medicine, College of Veterinary Medicine, Midwestern University, Glendale, AZ 85308, USA
| | - Miranda J. Neubert
- Department of Immunobiology, College of Medicine-Tucson, Tucson, AZ 85724, USA
| | - Sanjay V. Menghani
- Department of Immunobiology, Medical Scientist Training Program, College of Medicine-Tucson, Tucson, AZ 85724, USA
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18
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The Potential Importance of CXCL1 in the Physiological State and in Noncancer Diseases of the Cardiovascular System, Respiratory System and Skin. Int J Mol Sci 2022; 24:ijms24010205. [PMID: 36613652 PMCID: PMC9820720 DOI: 10.3390/ijms24010205] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 12/11/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Abstract
In this paper, we present a literature review of the role of CXC motif chemokine ligand 1 (CXCL1) in physiology, and in selected major non-cancer diseases of the cardiovascular system, respiratory system and skin. CXCL1, a cytokine belonging to the CXC sub-family of chemokines with CXC motif chemokine receptor 2 (CXCR2) as its main receptor, causes the migration and infiltration of neutrophils to the sites of high expression. This implicates CXCL1 in many adverse conditions associated with inflammation and the accumulation of neutrophils. The aim of this study was to describe the significance of CXCL1 in selected diseases of the cardiovascular system (atherosclerosis, atrial fibrillation, chronic ischemic heart disease, hypertension, sepsis including sepsis-associated encephalopathy and sepsis-associated acute kidney injury), the respiratory system (asthma, chronic obstructive pulmonary disease (COPD), chronic rhinosinusitis, coronavirus disease 2019 (COVID-19), influenza, lung transplantation and ischemic-reperfusion injury and tuberculosis) and the skin (wound healing, psoriasis, sunburn and xeroderma pigmentosum). Additionally, the significance of CXCL1 is described in vascular physiology, such as the effects of CXCL1 on angiogenesis and arteriogenesis.
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Olguín V, Durán A, Las Heras M, Rubilar JC, Cubillos FA, Olguín P, Klein AD. Genetic Background Matters: Population-Based Studies in Model Organisms for Translational Research. Int J Mol Sci 2022; 23:7570. [PMID: 35886916 PMCID: PMC9316598 DOI: 10.3390/ijms23147570] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/28/2022] [Accepted: 07/04/2022] [Indexed: 02/01/2023] Open
Abstract
We are all similar but a bit different. These differences are partially due to variations in our genomes and are related to the heterogeneity of symptoms and responses to treatments that patients exhibit. Most animal studies are performed in one single strain with one manipulation. However, due to the lack of variability, therapies are not always reproducible when treatments are translated to humans. Panels of already sequenced organisms are valuable tools for mimicking human phenotypic heterogeneities and gene mapping. This review summarizes the current knowledge of mouse, fly, and yeast panels with insightful applications for translational research.
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Affiliation(s)
- Valeria Olguín
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Anyelo Durán
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Macarena Las Heras
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Juan Carlos Rubilar
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Francisco A. Cubillos
- Departamento de Biología, Santiago, Facultad de Química y Biología, Universidad de Santiago de Chile, Santiago 9170022, Chile;
- Millennium Institute for Integrative Biology (iBio), Santiago 7500565, Chile
| | - Patricio Olguín
- Program in Human Genetics, Institute of Biomedical Sciences, Biomedical Neurosciences Institute, Department of Neuroscience, Facultad de Medicina, Universidad de Chile, Santiago 8380453, Chile;
| | - Andrés D. Klein
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
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Rosas Mejia O, Gloag ES, Li J, Ruane-Foster M, Claeys TA, Farkas D, Wang SH, Farkas L, Xin G, Robinson RT. Mice infected with Mycobacterium tuberculosis are resistant to acute disease caused by secondary infection with SARS-CoV-2. PLoS Pathog 2022; 18:e1010093. [PMID: 35325013 PMCID: PMC8946739 DOI: 10.1371/journal.ppat.1010093] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 02/23/2022] [Indexed: 12/22/2022] Open
Abstract
Mycobacterium tuberculosis (Mtb) and SARS-CoV-2 (CoV2) are the leading causes of death due to infectious disease. Although Mtb and CoV2 both cause serious and sometimes fatal respiratory infections, the effect of Mtb infection and its associated immune response on secondary infection with CoV2 is unknown. To address this question we applied two mouse models of COVID19, using mice which were chronically infected with Mtb. In both model systems, Mtb-infected mice were resistant to the pathological consequences of secondary CoV2 infection, and CoV2 infection did not affect Mtb burdens. Single cell RNA sequencing of coinfected and monoinfected lungs demonstrated the resistance of Mtb-infected mice is associated with expansion of T and B cell subsets upon viral challenge. Collectively, these data demonstrate that Mtb infection conditions the lung environment in a manner that is not conducive to CoV2 survival. Mycobacterium tuberculosis (Mtb) and SARS-CoV-2 (CoV2) are distinct organisms which both cause lung disease. We report the surprising observation that Mtb-infected mice are resistant to secondary infection with CoV2, with no impact on Mtb burden and resistance associating with lung T and B cell expansion.
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Affiliation(s)
| | | | | | | | | | - Daniela Farkas
- Department of Internal Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Davis Heart and Lung Research Institute
| | - Shu-Hua Wang
- Department of Infectious Disease, The Ohio State University, Columbus, Ohio, United States of America
| | - Laszlo Farkas
- Department of Internal Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Davis Heart and Lung Research Institute
| | - Gang Xin
- Department of Microbial Infection and Immunity
- Pelotonia Institute for Immuno-Oncology
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21
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Smith CM, Baker RE, Proulx MK, Mishra BB, Long JE, Park SW, Lee HN, Kiritsy MC, Bellerose MM, Olive AJ, Murphy KC, Papavinasasundaram K, Boehm FJ, Reames CJ, Meade RK, Hampton BK, Linnertz CL, Shaw GD, Hock P, Bell TA, Ehrt S, Schnappinger D, Pardo-Manuel de Villena F, Ferris MT, Ioerger TR, Sassetti CM. Host-pathogen genetic interactions underlie tuberculosis susceptibility in genetically diverse mice. eLife 2022; 11:74419. [PMID: 35112666 PMCID: PMC8846590 DOI: 10.7554/elife.74419] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/27/2022] [Indexed: 11/21/2022] Open
Abstract
The outcome of an encounter with Mycobacterium tuberculosis (Mtb) depends on the pathogen’s ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically diverse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to create a resource for associating bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb transposon mutant fitness (TnSeq) across the CC panel revealed that many virulence pathways are only required in specific host microenvironments, identifying a large fraction of the pathogen’s genome that has been maintained to ensure fitness in a diverse population. Both immunological and bacterial traits can be associated with genetic variants distributed across the mouse genome, making the CC a unique population for identifying specific host-pathogen genetic interactions that influence pathogenesis.
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Affiliation(s)
- Clare M Smith
- Department of Molecular Genetics and Microbiology, Duke University, Durham, United States
| | - Richard E Baker
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Megan K Proulx
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Bibhuti B Mishra
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Jarukit E Long
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Sae Woong Park
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Ha-Na Lee
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Michael C Kiritsy
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Michelle M Bellerose
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Andrew J Olive
- Microbiology and Molecular Genetics, Michigan State University, East Lansing, United States
| | - Kenan C Murphy
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Kadamba Papavinasasundaram
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Frederick J Boehm
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Charlotte J Reames
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Rachel K Meade
- Department of Molecular Genetics and Microbiology, Duke University, Durham, United States
| | - Brea K Hampton
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Colton L Linnertz
- Department of Genetics, University of North Carolina at Chapel Hill, Morrisville, United States
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Pablo Hock
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Timothy A Bell
- Department of Genetics,, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Sabine Ehrt
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Dirk Schnappinger
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | | | - Martin T Ferris
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Thomas R Ioerger
- Department of Computer Science and Engineering, Texas A&M University, College Station, United States
| | - Christopher M Sassetti
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
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22
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Iglesias-Carres L, Neilson AP. Utilizing preclinical models of genetic diversity to improve translation of phytochemical activities from rodents to humans and inform personalized nutrition. Food Funct 2021; 12:11077-11105. [PMID: 34672309 DOI: 10.1039/d1fo02782d] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Mouse models are an essential tool in different areas of research, including nutrition and phytochemical research. Traditional inbred mouse models have allowed the discovery of therapeutical targets and mechanisms of action and expanded our knowledge of health and disease. However, these models lack the genetic variability typically found in human populations, which hinders the translatability of the results found in mice to humans. The development of genetically diverse mouse models, such as the collaborative cross (CC) or the diversity outbred (DO) models, has been a useful tool to overcome this obstacle in many fields, such as cancer, immunology and toxicology. However, these tools have not yet been widely adopted in the field of phytochemical research. As demonstrated in other disciplines, use of CC and DO models has the potential to provide invaluable insights for translation of phytochemicals from rodents to humans, which are desperately needed given the challenges and numerous failed clinical trials in this field. These models may prove informative for personalized use of phytochemicals in humans, including: predicting interindividual variability in phytochemical bioavailability and efficacy, identifying genetic loci or genes governing response to phytochemicals, identifying phytochemical mechanisms of action and therapeutic targets, and understanding the impact of genetic variability on individual response to phytochemicals. Such insights would prove invaluable for personalized implementation of phytochemicals in humans. This review will focus on the current work performed with genetically diverse mouse populations, and the research opportunities and advantages that these models can offer to phytochemical research.
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Affiliation(s)
- Lisard Iglesias-Carres
- Plants for Human Health Institute, Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University, Kannapolis, NC, USA.
| | - Andrew P Neilson
- Plants for Human Health Institute, Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University, Kannapolis, NC, USA.
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