Klf10 favors<i>Mycobacterium tuberculosis</i>survival by impairing IFN-γ production and preventing macrophages reprograming to macropinocytosis

Madrid-Paulino, Edgardo; Mata-Espinosa, Dulce; León-Contreras, Juan Carlos; Serrano‐Fujarte, Isela; León-Guerrero, Sol Díaz de; Villaseñor, Tomás; Ramón‐Luing, Lucero A.; Puente, José L.; Chávez‐Galán, Leslie; Hernández-Pando, Rogelio; Pérez-Martı́nez, Leonor; Pedraza‐Alva, Gustavo

doi:10.1002/jlb.4ma0422-288r

Cited by 2 publications

(4 citation statements)

References 58 publications

(119 reference statements)

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“…Due to the multiple evidence pointing that an excessive inflammation is highly detrimental to the organism 42 , 61 , a therapy focused on promoting phagocytosis could be safer than rising macrophage recruitment. Recent studies have demonstrated that silencing the transcriptional factor Klf10 in macrophages promotes bacterial clarification by augmenting IFN- levels which boosts phagocytosis and bacilli destruction 62 .…”

Section: Discussionmentioning

confidence: 99%

“…In the diagram, a synergistic effect was found when both parameters increased simultaneously, requiring almost half the recruitment needed to drive the system to bacterial clearance when is raised by two units, reducing the risk of excessive inflammation. An immunotherapy that increases IFN- 62 and blocks IL-4 and IL-10 cytokines 66 will increase and prevent from decreasing, resulting in an efficient nontoxic therapy. Phagocytosis and recruitment synergy also showed to work even in scenarios where rises.…”

Section: Discussionmentioning

confidence: 99%

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Bifurcation analysis of a tuberculosis progression model for drug target identification

Flores-Garza,

Hernández-Pando,

García-Zárate

et al. 2023

Sci Rep

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Tuberculosis (TB) is a major cause of morbidity and mortality worldwide. The emergence and rapid spread of drug-resistant M. tuberculosis strains urge us to develop novel treatments. Experimental trials are constrained by laboratory capacity, insufficient funds, low number of laboratory animals and obsolete technology. Systems-level approaches to quantitatively study TB can overcome these limitations. Previously, we proposed a mathematical model describing the key regulatory mechanisms underlying the pathological progression of TB. Here, we systematically explore the effect of parameter variations on disease outcome. We find five bifurcation parameters that steer the clinical outcome of TB: number of bacteria phagocytosed per macrophage, macrophages death, macrophage killing by bacteria, macrophage recruitment, and phagocytosis of bacteria. The corresponding bifurcation diagrams show all-or-nothing dose–response curves with parameter regions mapping onto bacterial clearance, persistent infection, or history-dependent clearance or infection. Importantly, the pathogenic stage strongly affects the sensitivity of the host to these parameter variations. We identify parameter values corresponding to a latent-infection model of TB, where disease progression occurs significantly slower than in progressive TB. Two-dimensional bifurcation analyses uncovered synergistic parameter pairs that could act as efficient compound therapeutic approaches. Through bifurcation analysis, we reveal how modulation of specific regulatory mechanisms could steer the clinical outcome of TB.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Bifurcation analysis of a tuberculosis progression model for drug target identification

Flores-Garza,

Hernández-Pando,

García-Zárate

et al. 2023

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recent studies have demonstrated that silencing the transcriptional factor Klf10 in macrophages promotes bacterial clarification by augmenting IFN-γ levels which boosts phagocytosis and bacilli destruction [43].…”

Section: Discussionmentioning

confidence: 99%

“…In the 𝐹 δ × 𝐹 α 1 diagram, a synergistic effect was found when both parameters rise simultaneously, taking almost half the recruitment needed to lead the system to bacterial clearance when 𝐹 𝛿 is raised by two units, lowering the risk of an excessive inflammation. An immunotherapy that rises IFN-γ [43] and block IL-4 and IL-10 cytokines [47] will rise 𝐹 𝛿 and keep 𝐹 α 1 from dropping which will result in an efficient nontoxic therapy. Phagocytosis and recruitment synergy also showed to work even in scenarios where 𝑃𝑇𝑓 rises.…”

Section: Discussionmentioning

confidence: 99%

Bifurcation analysis of a tuberculosis progression model for drug target identification

Flores-Garza,

Hernández-Pando,

García-Zárate

et al. 2023

Preprint

Self Cite

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Tuberculosis (TB) is a major cause of morbidity and mortality worldwide. The emergence and rapid spread of drug-resistant M. tuberculosis strains urge us to develop novel treatments. Experimental assays are restricted by lab capacity, insufficient funds, low numbers of laboratory animals and obsolete technology. Systems-level approaches to quantitatively study TB can overcome these limitations. Previously, we proposed a mathematical model describing the key regulatory mechanisms underlying the pathological progression of TB. Here, we systematically explore the effect of parameter variations on disease outcome. We find five bifurcation parameters that steer the clinical outcome of TB: number of bacteria phagocytized per macrophage, macrophages death, macrophage killing by bacteria, macrophage recruitment, and phagocytosis of bacteria. The corresponding bifurcation diagrams show all-or-nothing dose-response curves with parameter regions mapping onto bacterial clearance, persistent infection, or history-dependent clearance or infection. Importantly, pathogenic stage strongly affects the host’s sensitivity to these parameter variations. We identify parameter values corresponding to a latent-infection model of TB, where disease progression occurs significantly slower than in progressive TB. Two-dimensional bifurcation analyses uncovered synergistic parameter pairs which could act as efficient compound therapeutic approaches. Through bifurcation analysis, we reveal how modulating specific regulatory mechanisms could steer the clinical outcome of TB.

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Klf10 favorsMycobacterium tuberculosissurvival by impairing IFN-γ production and preventing macrophages reprograming to macropinocytosis

Abstract: By inducing Klf10 expression, Mycobacterium tuberculosis decreases IFN-γ production and impairs an IFN-γ-mediated autocrine loop that promotes macrophage macropinocytosis, thus favoring survival and infection.

Cited by 2 publications

References 58 publications

Bifurcation analysis of a tuberculosis progression model for drug target identification

Bifurcation analysis of a tuberculosis progression model for drug target identification

Bifurcation analysis of a tuberculosis progression model for drug target identification

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