At present it is well-defined that autophagy is a fundamental process essential for cell life but its pro-viral and anti-viral role has been stated out with the COVID pandemic. However, viruses in turn have evolved diverse adaptive strategies to cope with autophagy driven host defense, either by blocking or hijacking the autophagy machinery for their own benefit. The mechanisms underlying autophagy modulation are presented in the current review which summarizes the accumulated knowledge on the crosstalk between autophagy and viral infections, with a particular emphasizes on SARS-CoV-2. The different types of autophagy related to infections and their molecular mechanisms are focused in the context of inflammation. In particular, SARS-CoV-2 entry, replication and disease pathogenesis are discussed. Models to study autophagy and to formulate novel treatment approaches and pharmacological modulation to fight COVID-19 are debated. The SARS-CoV-2—autophagy interplay is presented, revealing the complex dynamics and the molecular machinery of autophagy. The new molecular targets and strategies to treat COVID-19 effectively are envisaged. In conclusion, our finding underline the importance of development new treatment strategies and pharmacological modulation of autophagy to fight COVID-19.

Objective: Mitochondria drive cellular energy production and regulate key biological processes. High levels of heteroplasmic in mitochondrial DNA (mtDNA) variants can cause mitochondrial dysfunction and clinical symptoms. Third-generation sequencing overcomes the limitations of traditional mtDNA analysis methods, offering improved cost, throughput, and sensitivity. We developed an integrated approach for analyzing methylation patterns and genetic variations in mtDNA and ADME genes. Methods: We implemented Oxford Nanopore’s long-read sequencing with adaptive sampling (AS) to enrich enzymatically linearized mtDNA and absorption, distribution, metabolism, and excretion (ADME) genes without PCR amplification, enabling native sequencing in adipose-derived mesenchymal stem cells (AdMSC). Our custom algorithm preserved phase relationships between base modifications and sequence polymorphisms. Results: We identified differential methylation patterns in ADME genes correlating with specific genetic variants, suggesting epigenetic regulation of drug response. Adaptive sampling identifies a wider range of variant diversity, while whole genome sequencing (WGS) uncovers higher-frequency hotspots. Both methods offer complementary insights into mitochondrial heteroplasmy. In mtDNA, direct sequencing showed extensive hypomethylation, and low levels of non-CpG methylation were detected regardless of sequencing coverage depth. These sparse methylation patterns showed non-random distribution, correlating with functional regions and heteroplasmic sites. Conclusions: This study demonstrates the utility of adaptive sampling for the integrated analysis of mtDNA heteroplasmy and native base modifications, revealing widespread hypomethylation independent of coverage depth. The approach showcases the potential for combined pharmacoepigenomic and mitochondrial profiling in precision medicine, disease modeling, and therapeutic development.

Nanopore sequencing reads DNA base modifications from the ionic-current signal, but the R9.4.1 chemistry has no vendor model for N6-methyladenine (6mA), and third-party models are applied without an absolute error estimate. We measured the false-positive rate of two 6mA callers and of one all-context 5-methylcytosine (5mC) caller against a negative control that cannot carry either mark: PCR-amplified cDNA, in three independent controls from two cell lines. False-positive rates were resolved per 5-mer context and compared with the specificity that each modification’s prevalence demands. For CpG methylation, the measured false-positive rate remained approximately two orders of magnitude below the maximum rate permitted under the stated assumptions, and no context restriction was required. For 6mA, the pooled false-positive rate at the commonly used probability threshold of 0.7 was 23.2-fold higher than the maximum admissible rate. Most of the excess background was contributed by 30 of the 256 adenine-centred contexts, none of which carries a cytosine immediately 5′ of the called base; excluding them improves specificity 5.9-fold at threshold 0.95 and brings the caller inside the requirement there. The rank ordering of context-specific false-positive rates was correlated between cell lines (Spearman ρ = 0.862), although absolute rates were not identical. Under the tested Dorado/NEMO configuration, a second 6mA caller classified 0.63% of adenines as modified in amplified DNA even at threshold 0.99, corresponding to 277 times the admissible false-positive rate and insufficient specificity for rare 6mA detection. Genomic DNA prepared with the FFPE repair step omitted, so that 8-oxo-dG is preserved, inflates apparent 6mA 9- to 15-fold while leaving CpG calls unaffected.

The NLRP3 inflammasome is a key sensor of cellular stress and pathogen-associated signals in the innate immune system. Using confocal fluorescence microscopy in microvascular lung endothelial cells, we examined ASC speck formation following expression of the SARS-CoV-2 ORF3a protein. ORF3a engaged caspase-1 through dual architectural modes: alongside the canonical pyroptosome-like pathway, a novel distributed, multifocal inflammasome pathway emerged. Multiple ASC specks were observed at later time points, yet caspase-1 activation could occur in their absence, indicating that visible speck assembly is not strictly required for inflammasome signalling. These observations provide insight into the spatiotemporal dynamics of ASC during viral protein expression. The findings contribute to a better understanding of NLRP3 inflammasome regulation under conditions of viral replication.