Integrated genetic and metabolic landscapes predict vulnerabilities of temozolomide resistant glioblastoma cells - Immanuel, Selva Rupa Christinal; Ghanate, Avinash D.; Parmar, Dharmeshkumar S.; Yadav, Ritu; Uthup, Riya; Panchagnula, Venkateswarlu; Raghunathan, Anu (npj Systems Biology and Applications, 2021)
Metabolic reprogramming and its molecular underpinnings are critical to unravel the duality of cancer cell function and chemo-resistance. Here, we use a constraints-based integrated approach to delineate the interplay between metabolism and epigenetics, hardwired in the genome, to shape temozolomide (TMZ) resistance. Differential metabolism was identified in response to TMZ at varying concentrations in both the resistant neurospheroidal (NSP) and the susceptible (U87MG) glioblastoma cell-lines. The genetic basis of this metabolic adaptation was characterized by whole exome sequencing that identified mutations in signaling pathway regulators of growth and energy metabolism. Remarkably, our integrated approach identified rewiring in glycolysis, TCA cycle, malate aspartate shunt, and oxidative phosphorylation pathways. The differential killing of TMZ resistant NSP by Rotenone at low concentrations with an IC50 value of 5 nM, three orders of magnitude lower than for U87MG that exhibited an IC50 value of 1.8 mM was thus identified using our integrated systems-based approach.

Tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India - Niveditha, Divya; Khan, Soumen; Khilari, Ajinkya; Nadkarni, Sanica; Bhalerao, Unnati; Kadam, Pradnya; Yadav, Ritu; Kanekar, Jugal B.; Shah, Nikita; Likhitkar, Bhagyashree; Sawant, Rutuja; Thakur, Shikha; et al. (Journal of Infection and Public Health, 2023)
Background: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data.Methods: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a ``band of five'' outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5).Results: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. Conclusions: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implica-tions for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.& COPY; 2023 Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: COVID-19; Delta; Omicron; SARS-CoV-2 genomic surveillance; Variant of concern; Whole Genome Sequencing (WGS)

Immunogenicity of SARS-CoV-2 vaccines BBV152 (COVAXIN®) and ChAdOx1 nCoV-19 (COVISHIELD™) in seronegative and seropositive individuals in India: a multicentre, nonrandomised observational study - Asokan, Mangaiarkarasi S.; Joan, Roshni Florina; Babji, Sudhir; Dayma, Girish; Nadukkandy, Prajitha; Subrahmanyam, Vinutha; Pandey, Archana; Malagi, Girish; Arya, Pooja; Mahajan, Vibhuti; Bhavikatti, Jayateerth; Pawar, Ketakee; et al. (Lancet Regional Health - Southeast Asia, 2024)
<p style="box-sizing: inherit; line-height: 1.5; margin: 1.2rem 0px; color: rgb(33, 33, 33); font-family: BlinkMacSystemFont, -apple-system, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Fira Sans", "Droid Sans", "Helvetica Neue", sans-serif; font-size: 16px;"> Background: There are limited global data on head-to-head comparisons of vaccine platforms assessing both humoral and cellular immune responses, stratified by pre-vaccination serostatus. The COVID-19 vaccination drive for the Indian population in the age group 18-45 years began in April 2021 when seropositivity rates in the general population were rising due to the delta wave of COVID-19 pandemic during April-May 2021. <p style="box-sizing: inherit; line-height: 1.5; margin: 1.2rem 0px; color: rgb(33, 33, 33); font-family: BlinkMacSystemFont, -apple-system, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Fira Sans", "Droid Sans", "Helvetica Neue", sans-serif; font-size: 16px;"> Methods: Between June 30, 2021, and Jan 28, 2022, we enrolled 691 participants in the age group 18-45 years across four clinical sites in India. In this non-randomised and laboratory blinded study, participants received either two doses of Covaxin® (4 weeks apart) or two doses of Covishield™ (12 weeks apart) as per the national vaccination policy. The primary outcome was the seroconversion rate and the geometric mean titre (GMT) of antibodies against the SARS-CoV-2 spike and nucleocapsid proteins post two doses. The secondary outcome was the frequency of cellular immune responses pre- and post-vaccination. <p style="box-sizing: inherit; line-height: 1.5; margin: 1.2rem 0px; color: rgb(33, 33, 33); font-family: BlinkMacSystemFont, -apple-system, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Fira Sans", "Droid Sans", "Helvetica Neue", sans-serif; font-size: 16px;"> Findings: When compared to pre-vaccination baseline, both vaccines elicited statistically significant seroconversion and binding antibody levels in both seronegative and seropositive individuals. In the per-protocol cohort, Covishield™ elicited higher antibody responses than Covaxin® as measured by seroconversion rate (98.3% vs 74.4%, p < 0.0001 in seronegative individuals; 91.7% vs 66.9%, p < 0.0001 in seropositive individuals) as well as by anti-spike antibody levels against the ancestral strain (GMT 1272.1 vs 75.4 binding antibody units/ml [BAU/ml], p < 0.0001 in seronegative individuals; 2089.07 vs 585.7 BAU/ml, p < 0.0001 in seropositive individuals). As participants at all clinical sites were not recruited at the same time, site-specific immunogenicity was impacted by the timing of vaccination relative to the delta and omicron waves. Surrogate neutralising antibody responses against variants-of-concern including delta and omicron was higher in Covishield™ recipients than in Covaxin® recipients; and in seropositive than in seronegative individuals after both vaccination and asymptomatic infection (omicron variant). T cell responses are reported from only one of the four site cohorts where the vaccination schedule preceded the omicron wave. In seronegative individuals, Covishield™ elicited both CD4+ and CD8+ spike-specific cytokine-producing T cells whereas Covaxin® elicited mainly CD4+ spike-specific T cells. Neither vaccine showed significant post-vaccination expansion of spike-specific T cells in seropositive individuals.

Integrated analysis of mitochondrial ETC inhibition reveals genotype-specific heterogeneity of drug response in glioblastoma - Belekar, Madhuri; Kavatalkar, Vijendra; Yadav, Ritu; Raghunathan, Anu (Biochemical and Biophysical Research Communications, 2025)
Glioblastoma (GBM) is among the most aggressive brain cancers, driven by genetic diversity and resistance to therapy. Mitochondrial metabolism-and in particular the electron transport chain (ETC)-has emerged as both a key weakness and a source of variable drug response. To investigate this, we integrated constraint-based metabolic modeling (CBM), high-resolution drug profiling, and genomic sequencing across three GBM cell models: LN229, U87MG, and neurospheres (NSP). Modeling predicted distinct ETC vulnerabilities, which were confirmed experimentally using inhibitors against Complexes I-V. Sensitivity to rotenone varied sharply: NSP cells were most vulnerable (IC50 = 0.007 mu M), LN229 showed intermediate sensitivity (0.021 mu M), and U87MG remained highly resistant (1.816 mu M). Across inhibitors, LN229 consistently showed steep dose-response slopes, U87MG maintained flat curves, and NSP displayed selective weaknesses. By incorporating slope (m) and Instantaneous Inhibitory Potential (IIP), median-effect analysis captured dynamic drug-response behaviour's that IC50 values alone overlooked. Genomic sequencing revealed striking differences in mutational burden: U87MG and NSP carried 354 and 307 single nucleotide polymorphisms (SNPs), respectively, compared with 141 in LN229. Several non-synonymous mutations were directly linked to altered drug sensitivity, including L194S, Y50 N, and L46V in LN229; S456L, A466T, and Y629F in U87MG; and the NSP-specific R159Q. Notably, mutations near catalytic sites correlated with changes in slope and IIP, providing mechanistic insight into therapeutic response. Together, these results show how genetic variation reshapes ETC function and drug sensitivity in GBM, offering a predictive framework for mutation-informed, personalized therapy.
Keywords: Drug dose response; Electron transport chain; Glioblastoma; IC50 value; Instantaneous inhibitory potential; Mitochondrial genome