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Background: Tuberculosis (TB) is one of the world's most problematic infectious diseases. The pathogen Mycobacterium tuberculosis (Mtb) is contained by the immune system in people with latent TB infection (LTBI). No overt disease symptoms occur. The environmental and internal triggers leading to reactivation of TB are not well understood. Non-tuberculosis Mycobacteria (NTM) can also cause TB-like lung disease. Comparative analysis of blood plasma proteomes from subjects afflicted by these pathologies in an endemic setting may yield new differentiating biomarkers and insights into inflammatory and immunological responses to Mtb and NTM.
Methods: Blood samples from 40 human subjects in a pastoral region of Ethiopia were treated with the ESAT-6/CFP-10 antigen cocktail to stimulate anti-Mtb and anti-NTM immune responses. In addition to those of active TB, LTBI, and NTM cohorts, samples from matched healthy control (HC) subjects were available. Following the generation of sample pools, proteomes were analyzed via LC-MS/MS. These experiments were also performed without antigen stimulation steps. Statistically significant differences using the Z-score method were determined and interpreted in the context of the proteins' functions and their contributions to biological pathways.
Results: More than 200 proteins were identified from unstimulated and stimulated plasma samples (UPSs and SPSs, respectively). Thirty-four and 64 proteins were differentially abundant with statistical significance (P < 0.05; Benjamini-Hochberg correction with an FDR < 0.05) comparing UPS and SPS proteomic data of four groups, respectively. Bioinformatics analysis of such proteins via the Gene Ontology Resource was indicative of changes in cellular and metabolic processes, responses to stimuli, and biological regulations. The m7GpppN-mRNA hydrolase was increased in abundance in the LTBI group compared to HC subjects. Charged multivesicular body protein 4a and platelet factor-4 were increased in abundance in NTM as compared to HC and decreased in abundance in NTM as compared to active TB. C-reactive protein, α-1-acid glycoprotein 1, sialic acid-binding Ig-like lectin 16, and vitamin K-dependent protein S were also increased (P < 0.05; fold changes≥2) in SPSs and UPSs comparing active TB with LTBI and NTM cases. These three proteins, connected in a STRING functional network, contribute to the acute phase response and influence blood coagulation.
Conclusion: Plasma proteomes are different comparing LTBI, TB, NTM and HC cohorts. The changes are augmented following prior blood immune cell stimulation with the ESAT-6/CFP-10 antigen cocktail. The results encourage larger-cohort studies to identify specific biomarkers to diagnose NTM infection, LTBI, and to predict the risk of TB reactivation.
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http://dx.doi.org/10.1186/s12953-020-00165-5 | DOI Listing |
Protein Cell
August 2025
Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China.
Cardiovascular disease (CVD) research is hindered by limited comprehensive analyses of plasma proteome across disease subtypes. Here, we systematically investigated the associations between plasma proteins and cardiovascular outcomes in 53,026 UK Biobank participants over a 14-year follow-up. Association analyses identified 3,089 significant associations involving 892 unique protein analytes across 13 CVD outcomes.
View Article and Find Full Text PDFOpen Forum Infect Dis
September 2025
Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, California, USA.
Plasma samples obtained approximately 3 ( = 100) and 12 months ( = 78) after acute SARS-CoV-2 infection were tested for S1, spike, and N antigens. There were no significant differences in plasma proteins or single-cell protein expression levels on immune cells between those with and without plasma antigen detected.
View Article and Find Full Text PDFImmun Ageing
September 2025
Department of Biomedical Data Sciences, Molecular Epidemiology, LUMC, Leiden, The Netherlands.
The MetaboHealth score is an indicator of physiological frailty in middle aged and older individuals. The aim of the current study was to explore which molecular pathways co-vary with the MetaboHealth score. Using a Luminex cytokine assay and liquid chromatography-mass spectrometry-based proteomics we explored the plasma proteins associating with the difference in 100 extreme scoring individuals selected from two large population cohorts, the Leiden Longevity Study (LLS) and the Rotterdam Study (RS), and discordant monozygotic twin pairs from the Netherlands Twin Register (NTR).
View Article and Find Full Text PDFBiochim Biophys Acta Mol Cell Biol Lipids
September 2025
Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, British Columbia, V6T 1Z3, Canada; Department of Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia, V8W 2Y2, Canada; University of Victoria Genome BC Proteomics Centre, Vi
The class I phosphoinositide 3-kinase pathway (PI3K) is a master regulator of cellular growth, and plays essential roles in controlling immune cell function, metabolism, chemotaxis and proliferation. Activation of class I PI3Ks generates the signalling lipid PIP that activates multiple pro-growth signalling pathways. Class I PI3Ks can be activated by multiple plasma membrane stimuli, including G-protein coupled receptors, Ras superfamily GTPases, and receptor tyrosine kinases.
View Article and Find Full Text PDFJ Clin Invest
September 2025
The University of Texas at Austin, Austin, United States of America.
Background: Following SARS-CoV-2 infection, ~10-35% of COVID-19 patients experience long COVID (LC), in which debilitating symptoms persist for at least three months. Elucidating biologic underpinnings of LC could identify therapeutic opportunities.
Methods: We utilized machine learning methods on biologic analytes provided over 12-months after hospital discharge from >500 COVID-19 patients in the IMPACC cohort to identify a multi-omics "recovery factor", trained on patient-reported physical function survey scores.