Is targeting dysregulation in apoptosis splice variants in Mycobacterium tuberculosis (MTB) host interactions and splicing factors resulting in immune evasion by MTB strategies a possibility?

Dlamini, Zodwa; Alaouna, Mohammed; Cholo, Moloko C.; Hull, Rodney

doi:10.1016/j.tube.2020.101964

Cited by 4 publications

(3 citation statements)

References 48 publications

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“…The two clearly identified isoforms include one lacking exon 5 and one with truncated exon 2. Following MTB infection, exon 5-deficient isoforms compete with full-length protein and are downregulated . In Arabidopsis , disease-resistant protein RPS4 activates the defense system.…”

Section: Alternative Splicing In Plant–bacteria Interactions: Lessons...mentioning

confidence: 99%

“…Following MTB infection, exon 5-deficient isoforms compete with full-length protein and are downregulated. 54 In Arabidopsis, disease-resistant protein RPS4 activates the defense system. In RPS4, two common introns flanking exon 3 and a cryptic intron inside exon 3 produce multiple transcripts by AS.…”

Section: Function Of Alternative Splicing In Bacteria-caused Animal D...mentioning

confidence: 99%

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Alternative Splicing, An Overlooked Defense Frontier of Plants with Respect to Bacterial Infection

Xie,

Zhou,

Jia

et al. 2023

J. Agric. Food Chem.

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Disease represents a major problem in sustainable agricultural development. Plants interact closely with various microorganisms during their development and in response to the prevailing environment. In particular, pathogenic microorganisms can cause plant diseases, affecting the fertility, yield, and longevity of plants. During the long coevolution of plants and their pathogens, plants have evolved both molecular pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) signaling networks in order to regulate host cells in response to pathogen infestation. Additionally, in the postgenomic era, alternative splicing (AS) has become uncovered as one of the major drivers of proteome diversity, and abnormal RNA splicing is closely associated with bacterial infections. Currently, the complexity of host−bacteria interactions is a much studied area of research that has shown steady progress over the past decade. Although the development of high-throughput sequencing technologies and their application in transcriptomes have revolutionized our understanding of AS, many mechanisms related to host−bacteria interactions remain still unclear. To this end, this review summarizes the changes observed in AS during host−bacteria interactions and outlines potential therapeutics for bacterial diseases based on existing studies. In doing so, we hope to provide guidelines for plant disease management in agriculture.

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Section: Alternative Splicing In Plant–bacteria Interactions: Lessons...mentioning

confidence: 99%

Section: Function Of Alternative Splicing In Bacteria-caused Animal D...mentioning

confidence: 99%

Alternative Splicing, An Overlooked Defense Frontier of Plants with Respect to Bacterial Infection

Xie,

Zhou,

Jia

et al. 2023

J. Agric. Food Chem.

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“…Reduced activity of this response type may favour the persistence of infection in the body. M. tuberculosis can manipulate the host’s immune system, modulating the processing of antigens to enable its replication, propagation and persistence, causing an imbalance in effector immune responses, mainly related to the production of cytokines [ 20 , 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

Epidemiological and Cytokine Profile of Patients with Pulmonary and Extrapulmonary Tuberculosis in a Population of the Brazilian Amazon

Queiroz

Lima²,

Amoras³

et al. 2022

Microorganisms

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Several factors are associated with the development of different clinical forms of tuberculosis (TB). The present study evaluated epidemiological variables and cytokine levels in samples from 89 patients with TB (75 with pulmonary TB and 14 with extrapulmonary TB) and 45 controls. Cytokines were measured by flow cytometry (Human Th1/Th2/Th17 Cytometric Bead Array kit). The TB group had a higher frequency of individuals who were 39 years of age or older, married, with primary education or illiterate and had a lower family income (p < 0.05). All individuals with extrapulmonary TB reported that they were not working, and the main reasons were related to disease symptoms or treatment. The levels of IFN-γ (OR = 4.06) and IL-4 (OR = 2.62) were more likely to be elevated in the TB group (p = 0.05), and IFN-γ levels were lower in patients with extrapulmonary TB compared to those with pulmonary TB (OR = 0.11; p = 0.0050). The ROC curve was applied to investigate the diagnostic accuracy of IFN-γ levels between the different clinical forms of tuberculosis, resulting in high AUC (0.8661; p < 0.0001), sensitivity (93.85%) and specificity median (65.90%), suggesting that IFN-γ levels are useful to differentiate pulmonary TB from extrapulmonary TB. The dysregulation of pro- and anti-inflammatory cytokine levels represent a risk for the development of TB and contribute to the pathogenesis of the disease, especially variation in IFN-γ levels, which may determine protection or risk for extrapulmonary TB.

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RETRACTED ARTICLE: Structural modeling and phylogenetic analysis for infectious disease transmission pattern based on maximum likelihood tree approach

Mahmoud

Alamery

et al. 2021

J Ambient Intell Human Comput

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Is targeting dysregulation in apoptosis splice variants in Mycobacterium tuberculosis (MTB) host interactions and splicing factors resulting in immune evasion by MTB strategies a possibility?

Cited by 4 publications

References 48 publications

Alternative Splicing, An Overlooked Defense Frontier of Plants with Respect to Bacterial Infection

Alternative Splicing, An Overlooked Defense Frontier of Plants with Respect to Bacterial Infection

Epidemiological and Cytokine Profile of Patients with Pulmonary and Extrapulmonary Tuberculosis in a Population of the Brazilian Amazon

RETRACTED ARTICLE: Structural modeling and phylogenetic analysis for infectious disease transmission pattern based on maximum likelihood tree approach

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