Structural insights and activating mutations in diverse pathologies define mechanisms of deregulation for phospholipase C gamma enzymes

BACKGROUND: PLCγ enzymes are key nodes in cellular signal transduction and their mutated and rare variants have been recently implicated in development of a range of diseases with unmet need including cancer, complex immune disorders, inflammation and neurodegenerative diseases. However, molecular nature of activation and the impact and dysregulation mechanisms by mutations, remain unclear; both are critically dependent on comprehensive characterization of the intact PLCγ enzymes. METHODS: For structural studies we applied cryo-EM, cross-linking mass spectrometry and hydrogen-deuterium exchange mass spectrometry. In parallel, we compiled mutations linked to main pathologies, established their distribution and assessed their impact in cells and in vitro. FINDINGS: We define structure of a complex containing an intact, autoinhibited PLCγ1 and the intracellular part of FGFR1 and show that the interaction is centred on the nSH2 domain of PLCγ1. We define the architecture of PLCγ1 where an autoinhibitory interface involves the cSH2, spPH, TIM-barrel and C2 domains; this relative orientation occludes PLCγ1 access to its substrate. Based on this framework and functional characterization, the mechanism leading to an increase in PLCγ1 activity for the largest group of mutations is consistent with the major, direct impact on the autoinhibitory interface. INTERPRETATION: We reveal features of PLCγ enzymes that are important for determining their activation status. Targeting such features, as an alternative to targeting the PLC active site that has so far not been achieved for any PLC, could provide new routes for clinical interventions related to various pathologies driven by PLCγ deregulation. FUND: CR UK, MRC and AstaZeneca

Retrospective Analysis of the SARS-CoV-2 Infection Profile in COVID-19 Positive Patients in Vitoria da Conquista, Northeast Brazil

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is responsible for causing Coronavirus Disease-2019 (COVID-19), a heterogeneous clinical condition that manifests varying symptom severity according to the demographic profile of the studied population. While many studies have focused on the spread of COVID-19 in large urban centers in Brazil, few have evaluated medium or small cities in the Northeast region. The aims of this study were: (i) to identify risk factors for mortality from SARS-CoV-2 infection, (ii) to evaluate the gene expression patterns of key immune response pathways using nasopharyngeal swabs of COVID-19 patients, and (iii) to identify the circulating SARS-CoV-2 variants in the residents of a medium-sized city in Northeast Brazil. A total of 783 patients infected with SARS-CoV-2 between May 2020 and August 2021 were included in this study. Clinical-epidemiological data from patients who died and those who survived were compared. Patients were also retrospectively divided into three groups based on disease severity: asymptomatic, mild, and moderate/severe. Samples were added to a qPCR array for analyses of 84 genes involved with immune response pathways and sequenced using the Oxford Nanopore MinION technology. Having pre-existing comorbidity; being male; having cardiovascular disease, diabetes, and/or chronic obstructive pulmonary disease; and PCR cycle threshold (Ct) values under 22 were identified as risk factors for mortality. Analysis of the expression profiles of inflammatory pathway genes showed that the greater the infection severity, the greater the activation of inflammatory pathways, triggering the cytokine storm and downregulating anti-inflammatory pathways. Viral genome analysis revealed the circulation of multiple lineages, such as B.1, B.1.1.28, Alpha, and Gamma, suggesting that multiple introduction events had occurred over time. This study’s findings help identify the specific strains and increase our understanding of the true state of local health. In addition, our data demonstrate that epidemiological and genomic surveillance together can help formulate public health strategies to guide governmental actions