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McLoughlin KE, Correia CN, Browne JA, Magee DA, Nalpas NC, Rue-Albrecht K, Whelan AO, Villarreal-Ramos B, Vordermeier HM, Gormley E, Gordon SV, MacHugh DE. RNA-Seq Transcriptome Analysis of Peripheral Blood From Cattle Infected With Mycobacterium bovis Across an Experimental Time Course. Front Vet Sci 2021; 8:662002. [PMID: 34124223 PMCID: PMC8193354 DOI: 10.3389/fvets.2021.662002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 04/06/2021] [Indexed: 12/14/2022] Open
Abstract
Bovine tuberculosis, caused by infection with members of the Mycobacterium tuberculosis complex, particularly Mycobacterium bovis, is a major endemic disease affecting cattle populations worldwide, despite the implementation of stringent surveillance and control programs in many countries. The development of high-throughput functional genomics technologies, including RNA sequencing, has enabled detailed analysis of the host transcriptome to M. bovis infection, particularly at the macrophage and peripheral blood level. In the present study, we have analysed the transcriptome of bovine whole peripheral blood samples collected at −1 week pre-infection and +1, +2, +6, +10, and +12 weeks post-infection time points. Differentially expressed genes were catalogued and evaluated at each post-infection time point relative to the −1 week pre-infection time point and used for the identification of putative candidate host transcriptional biomarkers for M. bovis infection. Differentially expressed gene sets were also used for examination of cellular pathways associated with the host response to M. bovis infection, construction of de novo gene interaction networks enriched for host differentially expressed genes, and time-series analyses to identify functionally important groups of genes displaying similar patterns of expression across the infection time course. A notable outcome of these analyses was identification of a 19-gene transcriptional biosignature of infection consisting of genes increased in expression across the time course from +1 week to +12 weeks post-infection.
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Affiliation(s)
- Kirsten E McLoughlin
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Carolina N Correia
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - John A Browne
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - David A Magee
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Nicolas C Nalpas
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Kevin Rue-Albrecht
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Adam O Whelan
- TB Immunology and Vaccinology Team, Department of Bacteriology, Animal and Plant Health Agency, Weybridge, United Kingdom
| | - Bernardo Villarreal-Ramos
- TB Immunology and Vaccinology Team, Department of Bacteriology, Animal and Plant Health Agency, Weybridge, United Kingdom
| | - H Martin Vordermeier
- TB Immunology and Vaccinology Team, Department of Bacteriology, Animal and Plant Health Agency, Weybridge, United Kingdom
| | - Eamonn Gormley
- UCD School of Veterinary Medicine, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland
| | - Stephen V Gordon
- UCD School of Veterinary Medicine, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland.,UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
| | - David E MacHugh
- Animal Genomics Laboratory, UCD School of Agriculture and Food Science, UCD College of Health and Agricultural Sciences, University College Dublin, Dublin, Ireland.,UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
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Li Y, He D, Che Y, Zhao X. Monokine induced by gamma interferon for detecting pulmonary tuberculosis: A diagnostic meta-analysis. Medicine (Baltimore) 2020; 99:e23302. [PMID: 33217864 PMCID: PMC7676613 DOI: 10.1097/md.0000000000023302] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
BACKGROUNDS Pulmonary tuberculosis (PTB) is an oldest-known and most formidable disease. The standard microbiology culture is time-wasting. Monokine induced by gamma interferon (MIG) has been reported as a new biomarker to auxiliarily detect PTB. In our study, we used meta-analysis to assess the diagnostic value of MIG for PTB. METHODS PubMed, Embase, Web of Science, and Cochrane Library were searched for relative records up to April 2, 2020. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, area under the curve, and summary receiver operating characteristic curve were estimated. RESULTS Eight studies including 1487 participants were included. The pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of MIG for detecting PTB were 84%, 84%, 5.19, and 0.19, respectively. The diagnostic odds ratio and area under the curve were 27.88 and 0.90, respectively, indicating a good diagnostic ability of MIG. Meta-regression analysis showed that human immunodeficiency virus status might be a source of heterogeneity (P = .02). CONCLUSIONS Our results showed that MIG had a good diagnostic value for PTB.
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Araujo Z, Palacios A, Enciso-Moreno L, Lopez-Ramos JE, Wide A, Waard JHD, Rivas-Santiago B, Serrano CJ, Bastian-Hernandez Y, Castañeda-Delgado JE, Enciso-Moreno JA. Evaluation of the transcriptional immune biomarkers in peripheral blood from Warao indigenous associate with the infection by Mycobacterium tuberculosis. Rev Soc Bras Med Trop 2019; 52:e20180516. [PMID: 31141056 DOI: 10.1590/0037-8682-0516-2018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 03/22/2019] [Indexed: 02/08/2023] Open
Abstract
INTRODUCTION Biomarkers are critical tools for finding new approaches for controlling the spread of tuberculosis (TB), including for predicting the development of TB therapeutics, vaccines, and diagnostic tools. METHODS Expression of immune biomarkers was analyzed in peripheral blood cells stimulated and non-stimulated with M. tuberculosis antigens ESAT-6, CFP10 and TB7.7. in Warao indigenous individuals. These biomarkers may be able to differentiate TB states, such as active tuberculosis (ATB) cases and latent tuberculosis infection (LTBI) from non-infected controls (NIC). A real-time reverse transcription polymerase chain reaction (RT-qPCR) assay was performed on 100 blood samples under non-stimulation or direct ex vivo conditions (NS=50) and stimulation conditions (S=50). RESULTS The findings are shown as the median and interquartile range (IQR) of relative gene expression levels of IFN-γ, CD14, MMP9, CCR5, CCL11, CXCL9/MIG, and uPAR/PLAUR immune biomarkers. MMP9 levels were significantly higher in the LTBI-NS and LTBI-S groups compared with the NIC-NS and NIC-S groups. However, CCR5 levels were significantly lower in the LTBI-S group compared with both NIC-NS and NIC-S groups. CCL11 levels were significantly lower in the LTBI-S group compared with the NIC-NS group. CONCLUSIONS Preliminary findings showed that MMP9 immune biomarkers separated LTBI indigenous individuals from NIC indigenous individuals, while CCR5, CCL11, CD14, and IFN-γ did not differentiate TB states from NIC. MMP9 may be useful as a potential biomarker for LTBI and new infected case detection among Warao indigenous individuals at high risk of developing the disease. It may also be used to halt the epidemic, which will require further validation in larger studies.
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Affiliation(s)
- Zaida Araujo
- Laboratorio de Inmunología de Enfermedades Infecciosas, Instituto de Biomedicina "Dr. Jacinto Convit", Universidad Central de Venezuela, Caracas, Venezuela
| | - Andrea Palacios
- Laboratorio de Inmunología de Enfermedades Infecciosas, Instituto de Biomedicina "Dr. Jacinto Convit", Universidad Central de Venezuela, Caracas, Venezuela
| | - Leonor Enciso-Moreno
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Mexico
| | - Juan Ernesto Lopez-Ramos
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Mexico.,Universidad Autónoma de Aguascalientes, Aguascalientes, Mexico
| | - Albina Wide
- Laboratorio de Biotecnología, Instituto de Medicina Tropical, Universidad Central de Venezuela, Caracas, Venezuela
| | - Jacobus Henri de Waard
- Laboratorio de Tuberculosis, Instituto de Biomedicina "Dr. Jacinto Convit", Universidad Central de Venezuela, Caracas, Venezuela
| | - Bruno Rivas-Santiago
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Mexico
| | - Carmen Judith Serrano
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Mexico
| | - Yadira Bastian-Hernandez
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Mexico.,Cátedras CONACYT, Consejo Nacional de Ciencia y Tecnología, México
| | - Julio Enrique Castañeda-Delgado
- Unidad de Investigación Biomédica de Zacatecas, Instituto Mexicano del Seguro Social, Zacatecas, Mexico.,Cátedras CONACYT, Consejo Nacional de Ciencia y Tecnología, México
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