Chemistry and biology of ferritin.

Iron is an essential element required by cells and has been described as a key player in ferroptosis. Ferritin operates as a fundamental iron storage protein in cells forming multimeric assemblies with crystalline iron cores. We discuss the latest findings on ferritin structure and activity and its link to cell metabolism and ferroptosis. The chemistry of iron, including its oxidation states, is important for its biological functions, its reactivity, and the biology of ferritin. Ferritin can be localized in different cellular compartments and secreted by cells with a variety of functions depending on its spatial context. Here, we discuss how cellular ferritin localization is tightly linked to its function in a tissue-specific manner, and how impairment of iron homeostasis is implicated in diseases, including cancer and coronavirus disease 2019. Ferritin is a potential biomarker and we discuss latest research where it has been employed for imaging purposes and drug delivery.

Coupling immuno-magnetic capture with LC-MS/MS(MRM) as a sensitive, reliable, and specific assay for SARS-CoV-2 identification from clinical samples.

Recently, numerous diagnostic approaches from different disciplines have been developed for SARS-CoV-2 diagnosis to monitor and control the COVID-19 pandemic. These include MS-based assays, which provide analytical information on viral proteins. However, their sensitivity is limited, estimated to be 5 × 104 PFU/ml in clinical samples. Here, we present a reliable, specific, and rapid method for the identification of SARS-CoV-2 from nasopharyngeal (NP) specimens, which combines virus capture followed by LC-MS/MS(MRM) analysis of unique peptide markers. The capture of SARS-CoV-2 from the challenging matrix, prior to its tryptic digestion, was accomplished by magnetic beads coated with polyclonal IgG-α-SARS-CoV-2 antibodies, enabling sample concentration while significantly reducing background noise interrupting with LC-MS analysis. A sensitive and specific LC-MS/MS(MRM) analysis method was developed for the identification of selected tryptic peptide markers. The combined assay, which resulted in S/N ratio enhancement, achieved an improved sensitivity of more than 10-fold compared with previously described MS methods. The assay was validated in 29 naive NP specimens, 19 samples were spiked with SARS-CoV-2 and 10 were used as negative controls. Finally, the assay was successfully applied to clinical NP samples (n = 26) pre-determined as either positive or negative by RT-qPCR. This work describes for the first time a combined approach for immuno-magnetic viral isolation coupled with MS analysis. This method is highly reliable, specific, and sensitive; thus, it may potentially serve as a complementary assay to RT-qPCR, the gold standard test. This methodology can be applied to other viruses as well.

Exponential Amplification Using Photoredox Autocatalysis.

Exponential molecular amplification such as the polymerase chain reaction is a powerful tool that allows ultrasensitive biodetection. Here, we report a new exponential amplification strategy based on photoredox autocatalysis, where eosin Y, a photocatalyst, amplifies itself by activating a nonfluorescent eosin Y derivative (EYH3-) under green light. The deactivated photocatalyst is stable and rapidly activated under low-intensity light, making the eosin Y amplification suitable for resource-limited settings. Through steady-state kinetic studies and reaction modeling, we found that EYH3- is either oxidized to eosin Y via one-electron oxidation by triplet eosin Y and subsequent 1e-/H+ transfer, or activated by singlet oxygen with the risk of degradation. By reducing the rate of the EYH3- degradation, we successfully improved EYH3--to-eosin Y recovery, achieving efficient autocatalytic eosin Y amplification. Additionally, to demonstrate its flexibility in output signals, we coupled the eosin Y amplification with photoinduced chromogenic polymerization, enabling sensitive visual detection of analytes. Finally, we applied the exponential amplification methods in developing bioassays for detection of biomarkers including SARS-CoV-2 nucleocapsid protein, an antigen used in the diagnosis of COVID-19.

A multi-modal data harmonisation approach for discovery of COVID-19 drug targets.

Despite the volume of experiments performed and data available, the complex biology of coronavirus SARS-COV-2 is not yet fully understood. Existing molecular profiling studies have focused on analysing functional omics data of a single type, which captures changes in a small subset of the molecular perturbations caused by the virus. As the logical next step, results from multiple such omics analysis may be aggregated to comprehensively interpret the molecular mechanisms of SARS-CoV-2. An alternative approach is to integrate data simultaneously in a parallel fashion to highlight the inter-relationships of disease-driving biomolecules, in contrast to comparing processed information from each omics level separately. We demonstrate that valuable information may be masked by using the former fragmented views in analysis, and biomarkers resulting from such an approach cannot provide a systematic understanding of the disease aetiology. Hence, we present a generic, reproducible and flexible open-access data harmonisation framework that can be scaled out to future multi-omics analysis to study a phenotype in a holistic manner. The pipeline source code, detailed documentation and automated version as a R package are accessible. To demonstrate the effectiveness of our pipeline, we applied it to a drug screening task. We integrated multi-omics data to find the lowest level of statistical associations between data features in two case studies. Strongly correlated features within each of these two datasets were used for drug-target analysis, resulting in a list of 84 drug-target candidates. Further computational docking and toxicity analyses revealed seven high-confidence targets, amsacrine, bosutinib, ceritinib, crizotinib, nintedanib and sunitinib as potential starting points for drug therapy and development.

Circulating Von Willebrand factor and high molecular weight multimers as markers of endothelial injury predict COVID-19 in-hospital mortality.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a respiratory disease associated with endotheliitis and microthrombosis. OBJECTIVES: To correlate endothelial dysfunction to in-hospital mortality in a bi-centric cohort of COVID-19 adult patients. METHODS: Consecutive ambulatory and hospitalized patients with laboratory-confirmed COVID-19 were enrolled. A panel of endothelial biomarkers and von Willebrand factor (VWF) multimers were measured in each patient ≤ 48 h following admission. RESULTS: Study enrolled 208 COVID-19 patients of whom 23 were mild outpatients and 189 patients hospitalized after admission. Most of endothelial biomarkers tested were found increased in the 89 critical patients transferred to intensive care unit. However, only von Willebrand factor antigen (VWF:Ag) scaled according to clinical severity, with levels significantly higher in critical patients (median 507%, IQR 428-596) compared to non-critical patients (288%, 230-350, p < 0.0001) or COVID-19 outpatients (144%, 133-198, p = 0.007). Moreover, VWF high molecular weight multimers (HMWM) were significantly higher in critical patients (median ratio 1.18, IQR 0.86-1.09) compared to non-critical patients (0.96, 1.04-1.39, p < 0.001). Among all endothelial biomarkers measured, ROC curve analysis identified a VWF:Ag cut-off of 423% as the best predictor for in-hospital mortality. The accuracy of VWF:Ag was further confirmed in a Kaplan-Meier estimator analysis and a Cox proportional Hazard model adjusted on age, BMI, C-reactive protein and D-dimer levels. CONCLUSION: VWF:Ag is a relevant predictive factor for in-hospital mortality in COVID-19 patients. More than a biomarker, we hypothesize that VWF, including excess of HMWM forms, drives microthrombosis in COVID-19.