Biology subjects

Puranik, A.

Publications and source records attributed to Puranik, A..

6 recordsLinked to original sources

bioRxiv2026

The RNA m6A reader YTHDF2 depletion phenocopies high glucose induced-cellular stress response in diabetic kidney disease

RNA modification, especially the m6A RNA methylation, has been increasingly associated with several physiological and pathophysiological processes. The proteins that help in establishment of the modification and its removal along with the reader proteins that facilitate the functional outcome, together play an important regulatory role in disease manifestation. Diabetic kidney disease (DKD) is one such example, which is categorized as a multifactorial disorder that involves complex metabolic, oxidative, inflammatory, and fibrotic alterations, mediated through genetic, epigenetic and signalling cascades. However, the contribution of m6A-associated RNA regulators in DKD manifestation is relatively less explored. In this study, using HFD+STZ-induced diabetic mice and high glucose-treated renal cell models, we identified the m6A reader protein, Ythdf2 as a consistently downregulated candidate. YTHDF2 depletion in the renal cell line altered cellular viability, proliferation and increased oxidative stress under high-glucose conditions. Click-IT EU labeling further revealed altered RNA processing effects following YTHDF2 depletion and glucose stress. In corroboration with the above observations in animal and cell line models, independent human DKD transcriptomic datasets demonstrated conserved inflammatory and fibrotic signatures as well as reduced YTHDF2 expression in DKD glomeruli. The YTHDF2 downregulation was found to be inversely correlated with several disease-associated inflammatory and fibrotic genes. Together, these findings identify YTHDF2 dysregulation as a potential post-transcriptional mechanism associated with cellular stress and disease-associated molecular programs in DKD.

physiology↗

bioRxiv2025

Infection of point-of-lay hens to assess the sequential events during H7N7 high-pathogenicity avian influenza emergence at a layer premises

H7N7 low-pathogenicity avian influenza virus (H7N7-LPAIV) incursions have preceded emergence of H7N7 high-pathogenicity (HP)AIV at several European layer hen outbreaks. Evidence from a UK layer H7N7-HPAIV (2008) outbreak informed in vivo modelling of sequential events, beginning with H7N7-LPAIV precursor incursion. Three groups of 17-week-old (point-of-lay) hens were inoculated with three precursor H7N7-LPAIV candidates which possessed: Group 1 - the classic LPAIV single-basic cleavage site (CS) (H7N7-SBCS); Group 2 - the dibasic CS (H7N7-DBCS) discovered at the outbreak (both represented direct H7N7-HPAIV (2008) precursors); Group 3 - a related European H7N7-LPAIV (2008) which possessed a DBCS within its haemagglutinin (HA) gene which was highly-conserved with the HA of the UK (2008) outbreak H7N7-HPAIV, but its other genetic segments differed. In Groups 1-3, initial H7N7-LPAIV exposure caused limited viral shedding, restricted H7-antibody responses and no deaths, by 14-days post-inoculation (dpi). H7N7-HPAIV challenge of all groups (n=8 per challenge group, including AIV-naive hens in Group 4) followed at 14 dpi. Prior H7N7-LPAIV inoculation protected against mortality due to H7N7-HPAIV challenge to varying degrees, with eight (100%), seven (87.5%), six (75%) and three (37.5%) survivors in Groups 1-4, respectively, by study-end (14-days post-challenge), when all 24 survivors had strongly seroconverted. Among challenge survivors belonging to Groups 1-3, 20/21 (95%) shed H7N7-HP, indicating that immunity acquired during initial H7N7-LPAIV exposure did not arrest H7N7-HPAIV replication. Despite prior H7N7-LPAIV incursion which elicited additional clinical protection against H7N7-HPAIV challenge, we showed how an emergent H7N7-HPAIV may represent a source for onward spread and further HPAIV outbreaks.

microbiology↗

bioRxiv2020

SARS-CoV-2 selectively mimics a cleavable peptide of human ENaC in a strategic hijack of host proteolytic machinery

Molecular mimicry of host proteins is an evolutionary strategy adopted by viruses to evade immune surveillance and exploit host cell systems. We report that SARS-CoV-2 has evolved a unique S1/S2 cleavage site (RRARSVAS), absent in any previous coronavirus sequenced, that results in mimicry of an identical FURIN-cleavable peptide on the human epithelial sodium channel -subunit (ENaC-). Genetic truncation at this ENaC- cleavage site causes aldosterone dysregulation in patients, highlighting the functional importance of the mimicked SARS-CoV-2 peptide. Single cell RNA-seq from 65 studies shows significant overlap between the expression of ENaC- and ACE2, the putative receptor for the virus, in cell types linked to the cardiovascular-renal-pulmonary pathophysiology of COVID-19. Triangulating this cellular fingerprint with amino acid cleavage signatures of 178 human proteases shows the potential for tissue-specific proteolytic degeneracy wired into the SARS-CoV-2 lifecycle. We extrapolate that the evolution of SARS-CoV-2 into a global coronavirus pandemic may be in part due to its targeted mimicry of human ENaC and hijack of the associated host proteolytic network.

bioinformatics↗

bioRxiv2020

Knowledge synthesis from 100 million biomedical documents augments the deep expression profiling of coronavirus receptors

The COVID-19 pandemic demands assimilation of all available biomedical knowledge to decode its mechanisms of pathogenicity and transmission. Despite the recent renaissance in unsupervised neural networks for decoding unstructured natural languages, a platform for the real-time synthesis of the exponentially growing biomedical literature and its comprehensive triangulation with deep omic insights is not available. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations extracted from unstructured biomedical text, and their triangulation with Single Cell RNA-sequencing based insights from over 25 tissues. Using this platform, we identify intersections between the pathologic manifestations of COVID-19 and the comprehensive expression profile of the SARS-CoV-2 receptor ACE2. We find that tongue keratinocytes, airway club cells, and ciliated cells are likely underappreciated targets of SARS-CoV-2 infection, in addition to type II pneumocytes and olfactory epithelial cells. We further identify mature small intestinal enterocytes as a possible hotspot of COVID-19 fecal-oral transmission, where an intriguing maturation-correlated transcriptional signature is shared between ACE2 and the other coronavirus receptors DPP4 (MERS-CoV) and ANPEP (-coronavirus). This study demonstrates how a holistic data science platform can leverage unprecedented quantities of structured and unstructured publicly available data to accelerate the generation of impactful biological insights and hypotheses. The nferX Platform Single-cell resource - https://academia.nferx.com/

genomics↗

bioRxiv2019

Recapitulation and Retrospective Prediction of Biomedical Associations Using Temporally-enabled Word Embeddings

The recent explosion of biomedical knowledge presents both a major opportunity and challenge for scientists tackling complex problems in healthcare. Here we present an approach for synthesizing biomedical knowledge based on a combination of word-embeddings and select cooccurrences. We evaluated our ability to recapitulate and retrospectively predict disease-gene associations from the Online Mendelian Inheritance in Man (OMIM) resource. Our metrics achieved an area under the curve (AUC) value of 0.981 at the recapitulation task for 2,400 disease-gene associations. At the most stringent cutoff, our metrics predicted 13.89% of these associations before their first cooccurrence in the literature, with a median time of 4 years between prediction and first cooccurrence. Finally, our literature metrics can be combined with human genetics data to retrospectively predict disease-gene associations, IL-6 and Giant Cell Arteritis provided as an example. We believe this framework can provide robust biomedical hypotheses at a much faster pace than current standard practices.

bioinformatics↗

bioRxiv2018

Avian influenza viruses in wild birds: virus evolution in a multi-host ecosystem

Wild ducks and gulls are the major reservoirs for avian influenza A viruses (AIVs). The mechanisms that drive AIV evolution are complex at sites where various duck and gull species from multiple flyways breed, winter or stage. The Republic of Georgia is located at the intersection of three migratory flyways: Central Asian Flyway, East Asian/East African Flyway and Black Sea/Mediterranean Flyway. For six consecutive years (2010-2016), we collected AIV samples from various duck and gull species that breed, migrate and overwinter in Georgia. We found substantial subtype diversity of viruses that varied in prevalence from year to year. Low pathogenic (LP)AIV subtypes included H1N1, H2N3, H2N5, H2N7, H3N8, H4N2, H6N2, H7N3, H7N7, H9N1, H9N3, H10N4, H10N7, H11N1, H13N2, H13N6, H13N8, H16N3, plus two H5N5 and H5N8 highly pathogenic (HP)AIVs belonging to clade 2.3.4.4. Whole genome phylogenetic trees showed significant host species lineage restriction for nearly all gene segments and significant differences for LPAIVs among different host species in observed reassortment rates, as defined by quantification of phylogenetic incongruence, and in nucleotide diversity. Hemagglutinin clade 2.3.4.4 H5N8 viruses, circulated in Eurasia during 2014-2015 did not reassort, but analysis after its subsequent dissemination during 2016-2017 revealed reassortment in all gene segments except NP and NS. Some virus lineages appeared to be unrelated to AIVs in wild bird populations in other regions with maintenance of local AIV viruses in Georgia, whereas other lineages showed considerable genetic inter-relationship with viruses circulating in other parts of Eurasia and Africa, despite relative under-sampling in the area.\n\nImportanceWaterbirds (e.g., gulls/ducks) are natural reservoirs of avian influenza viruses (AIVs) and have been shown to mediate dispersal of AIV at inter-continental scales during seasonal migration. The segmented genome of influenza viruses enables viral RNA from different lineages to mix or re-assort when two viruses infect the same host. Such reassortant viruses have been identified in most major human influenza pandemics and several poultry outbreaks. Despite their importance, we have only recently begun to understand AIV evolution and reassortment in their natural host reservoirs. This comprehensive study illustrates of AIV evolutionary dynamics within a multi-host ecosystem at a stop-over site where three major migratory flyways intersect. Our analysis of this ecosystem over a six-year period provides a snapshot of how these viruses are linked to global AIV populations. Understanding the evolution of AIVs in the natural host is imperative to both mitigating the risk of incursion into domestic poultry and potential risk to mammalian hosts including humans.

microbiology↗