Hamster organotypic kidney culture model of early-stage SARS-CoV-2 infection highlights a two-step renal susceptibility

Imaging 3D cell cultures with optical microscopy

Three-dimensional (3D) cell cultures have gained popularity in recent years due to their ability to represent complex tissues or organs more faithfully than conventional two-dimensional (2D) cell culture. This article reviews the application of both 2D and 3D microscopy approaches for monitoring and studying 3D cell cultures. We first summarize the most popular optical microscopy methods that have been used with 3D cell cultures. We then discuss the general advantages and disadvantages of various microscopy techniques for several broad categories of investigation involving 3D cell cultures. Finally, we provide perspectives on key areas of technical need in which there are clear opportunities for innovation. Our goal is to guide microscope engineers and biomedical end users toward optimal imaging methods for specific investigational scenarios and to identify use cases in which additional innovations in high-resolution imaging could be helpful.

Dengue Virus dependence on glucokinase activity and glycolysis Confers Sensitivity to NAD(H) biosynthesis inhibitors

Viruses have developed sophisticated strategies to control metabolic activity of infected cells in order to supply replication machinery with energy and metabolites. Dengue virus (DENV), a mosquito-borne flavivirus responsible for dengue fever, is no exception. Previous reports have documented DENV interactions with metabolic pathways and shown in particular that glycolysis is increased in DENV-infected cells. However, underlying molecular mechanisms are still poorly characterized and dependence of DENV on this pathway has not been investigated in details yet. Here, we identified an interaction between the non-structural protein 3 (NS3) of DENV and glucokinase regulator protein (GCKR), a host protein that inhibits the liver-specific hexokinase GCK. NS3 expression was found to increase glucose consumption and lactate secretion in hepatic cell line expressing GCK. Interestingly, we observed that GCKR interaction with GCK decreases DENV replication, indicating the dependence of DENV to GCK activity and supporting the role of NS3 as an inhibitor of GCKR function. Accordingly, in the same cells, DENV replication both induces and depends on glycolysis. By targeting NAD(H) biosynthesis with the antimetabolite 6-Amino-Nicotinamide (6-AN), we decreased cellular glycolytic activity and inhibited DENV replication in hepatic cells. Infection of primary organotypic liver cultures (OLiC) from hamsters was also inhibited by 6-AN. Altogether, our results show that DENV has evolved strategies to control glycolysis in the liver, which could account for hepatic dysfunctions associated to infection. Besides, our findings suggest that lowering intracellular availability of NAD(H) could be a valuable therapeutic strategy to control glycolysis and inhibit DENV replication in the liver.

In Silico Prediction of Hub Genes Involved in Diabetic Kidney and COVID-19 Related Disease by Differential Gene Expression and Interactome Analysis

Diabetic kidney disease (DKD) is a frequently chronic kidney pathology derived from diabetes comorbidity. This condition has irreversible damage and its risk factor increases with SARS-CoV-2 infection. The prognostic outcome for diabetic patients with COVID-19 is dismal, even with intensive medical treatment. However, there is still scarce information on critical genes involved in the pathophysiological impact of COVID-19 on DKD. Herein, we characterize differential expression gene (DEG) profiles and determine hub genes undergoing transcriptional reprogramming in both disease conditions. Out of 995 DEGs, we identified 42 shared with COVID-19 pathways. Enrichment analysis elucidated that they are significantly induced with implications for immune and inflammatory responses. By performing a protein-protein interaction (PPI) network and applying topological methods, we determine the following five hub genes: STAT1, IRF7, ISG15, MX1 and OAS1. Then, by network deconvolution, we determine their co-expressed gene modules. Moreover, we validate the conservancy of their upregulation using the Coronascape database (DB). Finally, tissue-specific regulation of the five predictive hub genes indicates that OAS1 and MX1 expression levels are lower in healthy kidney tissue. Altogether, our results suggest that these genes could play an essential role in developing severe outcomes of COVID-19 in DKD patients.