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Prada Salcedo, J.

Publications and source records attributed to Prada Salcedo, J..

2 recordsLinked to original sources

Integrative phenotypic and transcriptomic validation of an alveolar-like macrophage model reveals early host-pathogen dynamics during Aspergillus fumigatus infection

Primary alveolar macrophages (pAMs) are essential for the rapid clearance of conidia and maintenance of pulmonary homeostasis. However, Aspergillus fumigatus remains the leading cause of invasive pulmonary aspergillosis in immunocompromised patients, and the mechanisms governing fungal clearance versus invasion remain poorly understood. Although, pAMs can be isolated from human donors, their broader application in in vitro infection studies is limited by their low availability and technical challenges with their maintenance in culture. In this study, we successfully adapted a previously established monocyte-derived alveolar-like macrophage (ALM) model to investigate early host-pathogen interactions upon A. fumigatus challenge. Given the requirement of GM-CSF for maintaining alveolar macrophage identity and function, we included GM-CSF differentiated macrophages (GM-M), as a widely employed reference model. Primary alveolar macrophages (pAM), isolated from human lung biopsies were utilized to validate the physiological relevance of the ALM model. Combined phenotypic, transcriptomic and functional analyses demonstrated that ALMs closely resemble pAMs under both steady-state and infection conditions across multiple time points and fungal burdens. Notably, fungal dual RNA-sequencing revealed a significant upregulation of fungal virulence-associated factors during interaction with ALM, which was not observed in our GM-M co-cultures. Collectively, these findings support the use of ALMs as a robust, experimentally accessible and physiologically relevant in vitro model for investigating early A. fumigatus infection, providing new insights into host-pathogen dynamics at the alveolar interface.

microbiology↗

Thrombo-inflammation analyzed in a validated seven-layer platelet decision model: cellular decisions are tough problems fast and heuristically solved

Decisions in biology happen fast and are driven by evolution to optimize survival chances. In platelets, this is achieved by organizing signaling cascades into rapid decision-funnels with modulatory crosstalk. We show that network decision processes underlying cellular decisions are tough to solve (equivalent to classical satisfiability problems, SAT). Hence, heuristics, modular decision-making, and decision funnels are required for efficient decisions. We establish this using a seven-layer platelet decision network that agrees well with all available genetic and functional experimental data. Platelet decision cascades are robust to perturbations: For example, receptors such as TRPM7 modulate platelet activity. However, knockouts of the receptors still leave platelets reactive overall. Dynamic control resolves relaying functions from kinases to cytoskeleton alterations. This allows fast execution of platelet shape change or aggregation. Stress conditions can shift platelet decision funnels towards constant activation of aggregation or immune signaling, causing thrombosis or thrombo-inflammation. Based on the network dynamics, we conclude that platelets pragmatically resolve the complex (non-polynomial (NP)) cellular decision problems by using a similar relaxation to those proposed in mathematics - many different configurations end up in similar states. Metamathematical considerations (no mathematical proof) suggest that NP problems are more complex then P problems. One sentence abstractWe show that cellular decision problems like the platelet signaling cascade may need unexpectedly long to solve but in general, they are efficiently solved using heuristics ("decision funnels"), implying fast decisions but the risk of chronic stress and inflammation.

bioinformatics↗