Ganesh, V. | Search bioRxiv

bioRxiv2026

5-Iodotubercidin inhibits Epithelial to Mesenchymal Transition by inhibiting IKK/NFκB-dependent gene expression

Epithelial to mesenchymal transition (EMT) is a process of trans-differentiation important for development, inflammation and cancer. Transforming Growth Factor-{beta} (TGF{beta}) is a physiologically relevant inducer of EMT. We had recently characterized the adenosine analogue, adenosine kinase inhibitor 5-Iodotubercidin (5-ITu), as a compound which preferentially sensitizes MK2-deficient cells to TNF-induced, RIPK1-dependent cell death. Here we investigated the effect of 5-ITu on TGF{beta}-induced EMT. 5-ITu suppressed TGF{beta}-induced morphological changes and migration in A549 (lung cancer) and PANC1 (pancreatic cancer) cell lines. Consistent with these effects, there was significant suppression of EMT markers as indicated by qPCR, immunoblotting and immunofluorescence and confocal microscopy. Mechanistic investigations revealed that 5-ITu-mediated EMT suppression was independent of adenosine kinase inhibition and RIPK1 activation. 5-ITu suppressed NF{kappa}B activity in cells undergoing EMT and IKK inhibition phenocopied the effect of 5-ITu on EMT. Kinase assays revealed IKK{beta} as a potential direct target of 5-ITu. We identified a TGF{beta}-associated, NF{kappa}B-dependent gene signature consisting of 4 genes, which are differentially regulated upon 5-ITu treatment. Interestingly, this 4 gene signature could predict survival in lung and pancreatic cancer. The identification of this role for the multitarget kinase inhibitor 5-ITu in NF{kappa}B activity-dependent EMT, in addition to RIPK1-dependent necroptosis has potential implications in anticancer strategies.

cell biology↗

bioRxiv2020

Enhanced virus detection and metagenomic sequencing in patients with meningitis and encephalitis

Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific diagnostic tests, sometimes over days to weeks. Metagenomic next-generation sequencing (mNGS) is a high-throughput platform that profiles all nucleic acid in a sample. We prospectively enrolled 68 patients from New England with known or suspected CNS infection and performed mNGS from both RNA and DNA to identify potential pathogens. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects. This included some pathogens traditionally diagnosed by serology or not typically identified in CSF, including three transmitted by Ixodes scapularis ticks (Powassan virus, Borrelia burgdorferi, Anaplasma phagocytophilum). Among 24 subjects with no clinical diagnosis, we detected enterovirus in two subjects and Epstein Barr virus in one subject. We also evaluated two methods to enhance detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed detection of varicella zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with similar efficacy to pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis. ImportanceMeningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Despite intensive diagnostic efforts, 40-60% of people with meningitis or encephalitis have no clear cause of their CNS disease identified. As diagnostic uncertainty often leads to costly inappropriate therapies, the need for novel pathogen detection methods is paramount. Metagenomic next-generation sequencing (mNGS) offers the unique opportunity to circumvent these challenges using unbiased laboratory and computational methods. Here, we performed comprehensive mNGS from 68 patients with suspected CNS infection, and define enhanced methods to improve the detection of CNS pathogens, including those not traditionally identified in the CNS by nucleic acid detection. Overall, our work helps elucidate how mNGS can become a mainstay in the diagnostic toolkit for CNS infections.

neuroscience↗