Proteomic analysis of SARS-CoV-2 particles unveils a key role of G3BP proteins in viral assembly.

Considerable progress has been made in understanding the molecular host-virus battlefield during SARS-CoV-2 infection. Nevertheless, the assembly and egress of newly formed virions are less understood. To identify host proteins involved in viral morphogenesis, we characterize the proteome of SARS-CoV-2 virions produced from A549-ACE2 and Calu-3 cells, isolated via ultracentrifugation on sucrose cushion or by ACE-2 affinity capture. Bioinformatic analysis unveils 92 SARS-CoV-2 virion-associated host factors, providing a valuable resource to better understand the molecular environment of virion production. We reveal that G3BP1 and G3BP2 (G3BP1/2), two major stress granule nucleators, are embedded within virions and unexpectedly favor virion production. Furthermore, we show that G3BP1/2 participate in the formation of cytoplasmic membrane vesicles, that are likely virion assembly sites, consistent with a proviral role of G3BP1/2 in SARS-CoV-2 dissemination. Altogether, these findings provide new insights into host factors required for SARS-CoV-2 assembly with potential implications for future therapeutic targeting.

Inhibition of the lncRNA Coded within Transglutaminase 2 Gene Impacts Several Relevant Networks in MCF-7 Breast Cancer Cells.

Long non-coding RNAs are nucleotide molecules that regulate transcription in numerous cellular processes and are related to the occurrence of many diseases, including cancer. In this regard, we recently discovered a polyadenylated long non-coding RNA (named TG2-lncRNA) encoded within the first intron of the Transglutaminase type 2 gene (TGM2), which is related to tumour proliferation in human cancer cell lines. To better characterize this new biological player, we investigated the effects of its suppression in MCF-7 breast cancer cells, using siRNA treatment and RNA-sequencing. In this way, we found modifications in several networks associated to biological functions relevant for tumorigenesis (apoptosis, chronic inflammation, angiogenesis, immunomodulation, cell mobility, and epithelial-mesenchymal transition) that were originally attributed only to Transglutaminase type 2 protein but that could be regulated also by TG2-lncRNA. Moreover, our experiments strongly suggest the ability of TG2-lncRNA to directly interact with important transcription factors, such as RXRα and TP53, paving the way for several regulatory loops that can potentially influence the phenotypic behaviour of MCF-7 cells. These considerations imply the need to further investigate the relative relevance of the TG2 protein itself and/or other gene products as key regulators in the organization of breast cancer program.

Lack of association of S100ß and neuron-specific enolase with mortality in critically ill patients.

OBJECTIVE: To evaluate the relationship between brain damage biomarkers and mortality in the intensive care unit (ICU). METHODS: The sample comprised 70 patients admitted to an ICU. Blood samples were collected from all patients on ICU admission, and levels of S100ß and neuron-specific enolase (NSE) were determined by ELISA. RESULTS: Acute Physiologic and Chronic Health Evaluation (APACHE II) score was associated with mortality, but NSE and S100ß were not associated with this outcome. In contrast, S100ß levels were significantly higher in delirious and non-delirious patients who required mechanical ventilation during ICU stay. CONCLUSION: Levels of brain biomarkers at the time of ICU admission did not predict mortality in critically ill patients.

Lack of association of S100 and neuron-specific enolase with mortality in critically ill patients

Objective: To evaluate the relationship between brain damage biomarkers and mortality in the intensive care unit (ICU). Methods: The sample comprised 70 patients admitted to an ICU. Blood samples were collected from all patients on ICU admission, and levels of S100β and neuron-specific enolase (NSE) were determined by ELISA. Results: Acute Physiologic and Chronic Health Evaluation (APACHE II) score was associated with mortality, but NSE and S100β were not associated with this outcome. In contrast, S100β levels were significantly higher in delirious and non-delirious patients who required mechanical ventilation during ICU stay. Conclusion: Levels of brain biomarkers at the time of ICU admission did not predict mortality in critically ill patients. .

Comparison of CAM-ICU and ICDSC for the detection of delirium in critically ill patients focusing on relevant clinical outcomes.

PURPOSE: Delirium is a frequent and serious problem in the intensive care unit (ICU) that is associated with increased mortality, prolonged mechanical ventilation, and prolonged hospital length of stay (LOS). The main objective of the present study was to compare and assess the agreement between the diagnosis of delirium obtained by the Confusion Assessment Method for the ICU (CAM-ICU) and Intensive Care Delirium Screening Checklist (ICDSC) in patients admitted to the ICU and their association with outcomes. METHODS: Adult patients admitted to the ICU for more than 24 hours between May and November 2008 were included. Patients with a Richmond Agitation-Sedation Scale score of -4 to -5 for more than 3 days were excluded. Delirium was evaluated twice a day by the ICDSC and CAM-ICU. Patients were followed-up until ICU discharge or for a maximum of 28 days. RESULTS: During the study period, 383 patients were admitted to the ICU and 162 (42%) were evaluated; delirium was identified in 26.5% of patients by CAM-ICU and in 34.6% by ICDSC. There was agreement in diagnosing delirium diagnosis between the 2 methods in 42 (27.8%) patients and in excluding delirium in 105 (64.8%) patients. The ICDSC was positive in 14 (8.6%) patients in whom CAM-ICU was negative. Delirium, diagnosed either by ICDSC or CAM-ICU assessments, was associated with both significantly increased hospital LOS (14.8 ± 8.3 vs 9.8 ± 6.4, P < .001; 15.3 ± 8.7 vs 10.5 ± 7.1, P < .001, respectively), mortality in the ICU (11.1% vs 5.8%, P < .001; 12.5% vs 2.5%, P = .022), and in the hospital (10.7% vs 5.6%, P < .001; 23.2% vs 10.9%, P = .047). In addition, patients with positive ICDSC presenting with negative CAM-ICU had similar outcomes as compared with those without delirium. CONCLUSION: The findings of our study suggest that the CAM-ICU is better predictor of outcome when compared with ICDSC.

Brain-derived neurotrophic factor and neuron-specific enolase, but not S100ß, levels are associated to the occurrence of delirium in intensive care unit patients.

PURPOSE: The aim of this study was to determine the association between serum concentrations of brain-derived neurotrophic factor (BDNF), neuron-specific enolase (NSE), and S100ß and the occurrence of delirium in critically ill patients. MATERIAL AND METHODS: This case-control study included 30 patients with delirium and 30 matched controls in a 16-bed general intensive care unit (ICU). Serum BDNF, NSE, and S100 concentrations were determined by enzyme-linked immunosorbent assay assays at the time of ICU admission and on the day before delirium was diagnosed. Delirium was diagnosed by confusion assessment method for the ICU. RESULTS: At ICU admission, serum BDNF levels were significantly higher in delirious patients than in nondelirious controls (2.89 ± 1.48 vs 1.79 ± 0.89 ng/mL, respectively). When we compared serum S100 levels, there were no significant differences between the groups. Neuron-specific enolase values were significantly higher in the delirious patients than in the nondelirious controls (0.79 ± 0.03 ng/mL vs 0.59 ± 0.01 ng/mL, respectively). When patients who earlier developed delirium were separately analyzed, it was determined that serum NSE and BDNF levels at admission were significant higher only in this group. CONCLUSIONS: Our results suggest that admission serum BDNF and NSE levels are associated with the occurrence of delirium in ICU patients.