Background Critically ill 2019 coronavirus disease (COVID-19) patients under invasive mechanical ventilation (IMV) are 10 to 40 times more likely to die than the general population. Although progression from mild to severe COVID-19 has been associated with hypoxia, uncontrolled inflammation, and coagulopathy, the mechanisms involved in the progression to severity are poorly understood. Methods The virome of tracheal aspirates (TA) from 25 COVID-19 patients under IMV was assessed through unbiased RNA sequencing (RNA-seq), and correlation analyses were conducted using available clinical data. Unbiased sequences from nasopharyngeal swabs (NS) from mild cases and TA from non-COVID patients were included in our study for further comparisons. Results We found higher levels and differential expression of human endogenous retrovirus K (HERV-K) genes in TA from critically ill and deceased patients when comparing nasopharyngeal swabs from mild cases to TA from non-COVID patients. In critically ill patients, higher HERV-K levels were associated with early mortality (within 14 days of diagnosis) in the intensive care unit. Increased HERV-K expression in deceased patients was associated with IL-17-related inflammation, monocyte activation, and an increased consumption of clotting/fibrinolysis factors. Moreover, increased HERV-K expression was detected in human primary monocytes from healthy donors after experimental SARS-CoV-2 infection in vitro. Conclusion Our data implicate the levels of HERV-K transcripts in the physiopathology of COVID-19 in the respiratory tract of patients under invasive mechanical ventilation.

BackgroundExtracellular vesicles (EVs) are a valuable source of biomarkers and display the pathophysiological status of various diseases. In COVID-19, EVs have been explored in several studies for their ability to reflect molecular changes caused by SARS-CoV-2. Here we provide insights into the roles of EVs in pathological processes associated with the progression and severity of COVID-19.MethodsIn this study, we used a label-free shotgun proteomic approach to identify and quantify alterations in EV protein abundance in severe COVID-19 patients. We isolated plasma extracellular vesicles from healthy donors and patients with severe COVID-19 by size exclusion chromatography (SEC). Then, flow cytometry was performed to assess the origin of EVs and to investigate the presence of circulating procoagulant EVs in COVID-19 patients. A total protein extraction was performed, and samples were analyzed by nLC-MS/MS in a Q-Exactive HF-X. Finally, computational analysis was applied to signify biological processes related to disease pathogenesis.ResultsWe report significant changes in the proteome of EVs from patients with severe COVID-19. Flow cytometry experiments indicated an increase in total circulating EVs and with tissue factor (TF) dependent procoagulant activity. Differentially expressed proteins in the disease groups were associated with complement and coagulation cascades, platelet degranulation, and acute inflammatory response.ConclusionsThe proteomic data reinforce the changes in the proteome of extracellular vesicles from patients infected with SARS-CoV-2 and suggest a role for EVs in severe COVID-19.

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Leprosy is a worldwide health problem, which needs the development of new and innovative strategies to be controlled. Early diagnosis of leprosy is an important contribution to reducing the incidence of the disease; thus, the development of biotechnology platforms, which include the mapping of antigens with potential to be used in immunodiagnostic and molecular methods for the detection of Mycobacterium leprae, is an important tool to confirm the clinical diagnostic. Molecular biology and biotechnological methods have been used to assist in the diagnosis of this disease, each one with its advantages and drawbacks. Enzyme-linked immunosorbent assay (ELISA) is the used method for leprosy diagnosis, and it allows the detection of infection-related antigens. Alternatively, due to their versatility to perform the same functions as the protein and non-protein natural antigens, mimetic peptides are considered an important tool. On the other hand, lateral flow assay (LFA) and optical and electrochemical biosensors are rapid and portable methods, capable of performing diagnosis in the field without sample preparation.This chapter presents such techniques, their uses in the diagnosis and detection of M. leprae, as well as the potential for the development of new techniques and strategies that can help to control and understand mycobacteriosis.

IntroductionLeprosy reactions, the main cause of neural damage, can occur up to 7 years after starting multidrug therapy. We aimed to approach the prognostic factors that may influence the leprosy reactions over the follow-up time.MethodsRetrospective cohort study, encompassing 10 years of data collection, composed of 390 patients, divided into 201 affected by reactions and 189 reaction-free individuals. Epidemiological, clinical, and laboratory variables were approached as prognostic factors associated with leprosy reactions. The association among variables was analyzed by a binomial test and survival curves were compared by the Kaplan-Meier and Cox proportional-hazards regression.Results51.5% (201/390) of patients were affected by leprosy reactions. These immunological events were associated with lepromatous leprosy (16.2%; 63/390; p < 0.0001) and multibacillary group (43%; 169/390; p < 0.0001). This study showed that survival curves for the prognostic factor anti-PGL-I, comparing positive and negative cases at diagnosis, differed in relation to the follow-up time (Log Rank: p = 0.0760; Breslow: p = 0.0090; Tarone-Ware: p = 0.0110). The median survival times (time at which 50% of patients were affected by leprosy reactions) were 5 and 9 months for those reactional cases with negative (26/51) and positive serology (75/150), respectively. The time-dependent covariates in the cox proportional-hazards regression showed anti-PGL-I as the main prognostic factor to predict leprosy reactions (hazard ratio=1.91; p = 0.0110) throughout the follow-up time.ConclusionsFinally, these findings demonstrated that anti-PGL-I serology at diagnosis is the most important prognostic factor for leprosy reactions after starting multidrug therapy, thus enabling prediction of this immunological event.