RESUMEN
Studying specific subpopulations of cancer-derived extracellular vesicles (EVs) could help reveal their role in cancer progression. In cancer, an increase in reactive oxygen species (ROS) happens which results in lipid peroxidation with a major product of 4-hydroxynonenal (HNE). Adduction by HNE causes alteration to the structure of proteins, leading to loss of function. Blebbing of EVs carrying these HNE-adducted proteins as a cargo or carrying HNE-adducted on EV membrane are methods for clearing these molecules by the cells. We have referred to these EVs as Redox EVs. Here, we utilize a surface tension-mediated extraction process, termed exclusion-based sample preparation (ESP), for the rapid and efficient isolation of intact Redox EVs, from a mixed population of EVs derived from human glioblastoma cell line LN18. After optimizing different parameters, two populations of EVs were analyzed, those isolated from the sample (Redox EVs) and those remaining in the original sample (Remaining EVs). Electron microscopic imaging was used to confirm the presence of HNE adducts on the outer leaflet of Redox EVs. Moreover, the population of HNE-adducted Redox EVs shows significantly different characteristics to those of Remaining EVs including smaller size EVs and a more negative zeta potential EVs. We further treated glioblastoma cells (LN18), radiation-resistant glioblastoma cells (RR-LN18), and normal human astrocytes (NHA) with both Remaining and Redox EV populations. Our results indicate that Redox EVs promote the growth of glioblastoma cells, likely through the production of H2O2, and cause injury to normal astrocytes. In contrast, Remaining EVs have minimal impact on the viability of both glioblastoma cells and NHA cells. Thus, isolating a subpopulation of EVs employing ESP-based immunoaffinity could pave the way for a deeper mechanistic understanding of how subtypes of EVs, such as those containing HNE-adducted proteins, induce biological changes in the cells that take up these EVs.
RESUMEN
Persons living in long-term care facilities (LTCFs) were disproportionately affected by COVID-19. We used wastewater surveillance to detect SARS-CoV-2 infection in this setting by collecting and testing 24-hour composite wastewater samples 2-4 times weekly at 6 LTCFs in Kentucky, USA, during March 2021-February 2022. The LTCFs routinely tested staff and symptomatic and exposed residents for SARS-CoV-2 using rapid antigen tests. Of 780 wastewater samples analyzed, 22% (n = 173) had detectable SARS-CoV-2 RNA. The LTCFs reported 161 positive (of 16,905) SARS-CoV-2 clinical tests. The wastewater SARS-CoV-2 signal showed variable correlation with clinical test data; we observed the strongest correlations in the LTCFs with the most positive clinical tests (n = 45 and n = 58). Wastewater surveillance was 48% sensitive and 80% specific in identifying SARS-CoV-2 infections found on clinical testing, which was limited by frequency, coverage, and rapid antigen test performance.