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Biology subjects

Jha, R. M.

Publications and source records attributed to Jha, R. M..

3 recordsLinked to original sources

Protein Predictors of Worsening Cerebral Edema in Traumatic Brain Injury in Critically Ill Patients

Cerebral edema (CE) is a major determinant of poor outcomes after traumatic brain injury (TBI). CE affects approximately 60% of patients with mass lesions on head computed tomography (hCT) and confers a tenfold increase in mortality. Despite this burden, no validated biomarkers exist to identify patients at risk for early CE worsening or to elucidate the biological processes underlying divergent edema trajectories. We conducted high-throughput plasma proteomic profiling in a prospective moderate-severe TBI cohort with evidence of intracranial blood on the initial post-injury hCT scan (n=123 patients) to (1) identify a clinically feasible set of biomarkers plus a predictive model that could be used to assess CE risk at admission, and (2) conduct a mechanistic, hypothesis-generating analysis to identify the molecular networks involved in CE progression in the first hours post-injury. Plasma collected within 3 hours of injury was analyzed using the Olink Explore platform (5394 proteins), and patients underwent head CT imaging upon presentation and at 6 hours. Two complementary analytic pathways, reflecting the studys two goals, were pursued in parallel. First, logistic regression with false discovery rate (FDR) correction identified a conservative 12-protein set associated with baseline CE. When combined with targeted clinical variables (i.e., age, sex, admission GCS, pupil reactivity, admission glucose, admission alcohol), this panel supported high-performing supervised classifiers for predicting CE worsening by 6 hours post-baseline scan (best model: XGBoost, AUC = 0.78; recall = 0.83). Second, a broader 60-protein panel, selected via bootstrapped elastic-net regression, was used to interrogate the mechanistic architecture of CE worsening using random forest SHAP attribution and protein-protein interaction modeling. Proteomic signatures diverged sharply between patients whose CE did and did not worsen. The CE worsening group was characterized by a coherent neuronal-synaptic injury axis dominated by ELAVL4, CEND1, NEFL, NECAB2, GFAP, CHGB, RPH3A, HPCAL4, and HOMER1, proteins involved in neuronal structural integrity, vesicular trafficking, synaptic vesicle cycling, calcium signaling, and axonal degeneration. These reciprocal proteomic states suggest that early edema progression may be driven by coordinated disruption of neuronal and synaptic resilience programs. Together, these findings suggest (1) a hyperacute biomarker panel plus predictive model with potential for prospective validation and (2) mechanistic evidence for a distinct neuronal-synaptic injury network that associates with early edema worsening after TBI.

neuroscience↗

Lipid Droplets are active translation depots that respond to infection

Lipid droplets (LDs) are increasingly recognized as dynamic organelles with roles extending beyond lipid storage. While the core LD proteome across cells reveals minimal overlap, several proteins with "housekeeping" functions such as ribosomal proteins and translation factors have largely been ignored as contaminants. Here, we provide biochemical and microscopy-based evidence of ribosome components and the ribosome to be present in association with the LD. By developing a modified method based on puromycylation, we demonstrate that active ribosomes are localised in close-proximity of LDs, demonstrating that LDs serve as sites of active protein translation. By using Mycobacterium tuberculosis (Mtb) infection as a model, we show that LD-associated translation is regulated under infection conditions. Although the specific mRNAs translated on LDs remain to be identified, these findings reveal LDs as critical platforms for protein synthesis and provide insights into how the LD proteome is established. This work highlights the multifaceted role of LDs in cellular homeostasis and host-pathogen interactions. IMPORTANTO_LIManuscripts submitted to Review Commons are peer reviewed in a journal-agnostic way. C_LIO_LIUpon transfer of the peer reviewed preprint to a journal, the referee reports wil be available in ful to the handling editor. C_LIO_LIThe identity of the referees wil NOT be communicated to the authors unless the reviewers choose to sign their report. C_LIO_LIThe identity of the referee wil be confidentia ly disclosed to any a filiate journals to which the manuscript is transferred. C_LI GUIDELINESO_LIFor reviewers: https://www.reviewcommons.org/reviewers C_LIO_LIFor authors: https://www.reviewcommons.org/authors C_LI CONTACTThe Review Commons o fice can be contacted directly at: office@reviewcommons.org

cell biology↗

High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next generation sequencing

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance and for determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for detection of SARS-CoV-2, with an additional advantage of enabling genetic epidemiology of SARS-CoV-2.

genomics↗