Withania somnifera or Ashwagandha is a medicinal herb of Ayurveda. Though the extract and purified molecules, withanolides, from this plant have been shown to have different pharmacological activities, their effect on bone formation has not been studied. Here, we show that one of the withanolide, withaferin A (WFA) acts as a proteasomal inhibitor (PI) and binds to specific catalytic β subunit of the 20S proteasome. It exerts positive effect on osteoblast by increasing osteoblast proliferation and differentiation. WFA increased expression of osteoblast-specific transcription factor and mineralizing genes, promoted osteoblast survival and suppressed inflammatory cytokines. In osteoclast, WFA treatment decreased osteoclast number directly by decreasing expression of tartarate-resistant acid phosphatase and receptor activator of nuclear factor kappa-B (RANK) and indirectly by decreasing osteoprotegrin/RANK ligand ratio. Our data show that in vitro treatment of WFA to calvarial osteoblast cells decreased expression of E3 ubiquitin ligase, Smad ubiquitin regulatory factor 2 (Smurf2), preventing degradation of Runt-related transcription factor 2 (RunX2) and relevant Smad proteins, which are phosphorylated by bone morphogenetic protein 2. Increased Smurf2 expression due to exogenous treatment of tumor necrosis factor α (TNFα) to primary osteoblast cells was decreased by WFA treatment. This was corroborated by using small interfering RNA against Smurf2. Further, WFA also blocked nuclear factor kappa-B (NF-kB) signaling as assessed by tumor necrosis factor stimulated nuclear translocation of p65-subunit of NF-kB. Overall data show that in vitro proteasome inhibition by WFA simultaneously promoted osteoblastogenesis by stabilizing RunX2 and suppressed osteoclast differentiation, by inhibiting osteoclastogenesis. Oral administration of WFA to osteopenic ovariectomized mice increased osteoprogenitor cells in the bone marrow and increased expression of osteogenic genes. WFA supplementation improved trabecular micro-architecture of the long bones, increased biomechanical strength parameters of the vertebra and femur, decreased bone turnover markers (osteocalcin and TNFα) and expression of skeletal osteoclastogenic genes. It also increased new bone formation and expression of osteogenic genes in the femur bone as compared with vehicle groups (Sham) and ovariectomy (OVx), Bortezomib (known PI), injectible parathyroid hormone and alendronate (FDA approved drugs). WFA promoted the process of cortical bone regeneration at drill-holes site in the femur mid-diaphysis region and cortical gap was bridged with woven bone within 11 days of both estrogen sufficient and deficient (ovariectomized, Ovx) mice. Together our data suggest that WFA stimulates bone formation by abrogating proteasomal machinery and provides knowledge base for its clinical evaluation as a bone anabolic agent.

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The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the prognosis of COVID-19 severity. This in-depth study of plasma proteome alteration provides insights into the host physiological response towards the infection and also reveals the potential prognostic markers of the disease. Using label-free quantitative proteomics, we performed deep plasma proteome analysis in a cohort of 71 patients (20 COVID-19 negative, 18 COVID-19 non-severe, and 33 severe) to understand the disease dynamics. Of the 1200 proteins detected in the patient plasma, 38 proteins were identified to be differentially expressed between non-severe and severe groups. The altered plasma proteome revealed significant dysregulation in the pathways related to peptidase activity, regulated exocytosis, blood coagulation, complement activation, leukocyte activation involved in immune response, and response to glucocorticoid biological processes in severe cases of SARS-CoV-2 infection. Furthermore, we employed supervised machine learning (ML) approaches using a linear support vector machine model to identify the classifiers of patients with non-severe and severe COVID-19. The model used a selected panel of 20 proteins and classified the samples based on the severity with a classification accuracy of 0.84. Putative biomarkers such as angiotensinogen and SERPING1 and ML-derived classifiers including the apolipoprotein B, SERPINA3, and fibrinogen gamma chain were validated by targeted mass spectrometry-based multiple reaction monitoring (MRM) assays. We also employed an in silico screening approach against the identified target proteins for the therapeutic management of COVID-19. We shortlisted two FDA-approved drugs, namely, selinexor and ponatinib, which showed the potential of being repurposed for COVID-19 therapeutics. Overall, this is the first most comprehensive plasma proteome investigation of COVID-19 patients from the Indian population, and provides a set of potential biomarkers for the disease severity progression and targets for therapeutic interventions.

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