Biology subjects

Mahajan, M.

Publications and source records attributed to Mahajan, M..

6 recordsLinked to original sources

bioRxiv2026

Stationary phase KCl levels trigger changes in Dps conformation to facilitate its partitioning between reversibly-aggregated deposits and Dps-DNA condensates

In E. coli populations subjected to starvation, the transition of cells into stationary-phase is characterized by reduced KCl levels, cytoplasmic acidification, and increased production of Dps, the DNA binding protein from starved cells. Here, we show that at KCl concentrations peculiar to the stationary-phase, Dps displays greater surface hydrophobicity, lower helical content, lower stability to denaturation, greater susceptibility to proteolysis, and an intriguing ability to undergo 'reversible' deposition into liquid-solid phase separated (LSPS) aggregates, when no DNA is present. Whereas we have already previously shown that, at growth-phase KCl concentrations, Dps either remains soluble or forms liquid-liquid phase separated (LLPS) condensates with DNA, when DNA is present, here we show that the coacervation of Dps with DNA is exacerbated by stationary-phase KCl concentrations. This leads us to suggest the following interesting possibilities: (i) newly-produced Dps is reversibly kinetically-partitioned between LSPS and LLPS states, at low KCl concentrations, depending on the availability of DNA; (ii) excess Dps that is not coacervated with DNA in the LSPS state, exists in the LSPS state at low KCl concentrations; and (iii) Dps in the LSPS state dissolves to become instantaneously available for the packaging of newly-produced DNA, once nutrition becomes available, growth resumes and cytoplasmic KCl concentrations rise, before there is any production of the growth-phase DNA-packaging protein, HU.

biophysics↗

bioRxiv2026

Resolving the immune response across clonal cancer evolution in situ with whole transcriptome profiling

Single-cell spatial transcriptomics is now central to studying tumors in their native tissue context. Here we present the first comprehensive, independent evaluation of Atera, a new spatial whole-transcriptome platform, compared with Xenium in human ductal carcinoma in situ (DCIS). We show that Atera enables granular cell-state annotation and resolves rare cell populations, experimentally validated by multiplex immunofluorescence (IF). We further show that its transcriptome-wide coverage enables inference of copy-number alterations at single-cell resolution, allowing us to reconstruct the clonal evolution of DCIS. We orthogonally confirm the inferred copy-number alterations by whole-genome sequencing of 16 microdissected tumor regions from consecutive tissue sections. Finally, by mapping the immune microenvironment onto this clonal architecture, we demonstrate the feasibility of tracking the changes in immune response along the clonal tumor evolution in situ. Together, our results establish Atera as a validated platform for tracking clonal evolution and immune adaptation in clinical samples.

bioinformatics↗

bioRxiv2024

A comprehensive multi-omics study reveals potential prognostic and diagnostic biomarkers for colorectal cancer

BackgroundColorectal cancer (CRC) is a complex disease with diverse genetic alterations and causes 10% of cancer-related deaths worldwide. Understanding its molecular mechanisms is essential for identifying potential biomarkers and therapeutic targets for its effective management. MethodWe integrated copy number alterations (CNA) and mutation data via their differentially expressed genes termed as candidate genes (CGs) computed using bioinformatics approaches. Then, using the CGs, we perform Weighted correlation network analysis (WGCNA) and utilise several hazard models such as Univariate Cox, Least Absolute Shrinkage and Selection Operator (LASSO) Cox and multivariate Cox to identify the key genes involved in CRC progression. We used different machine-learning models to demonstrate the discriminative power of selected hub genes among normal and CRC (early and late-stage) samples. ResultsThe integration of CNA with mRNA expression identified over 3000 CGs, including CRC-specific driver genes like MYC and APC. In addition, pathway analysis revealed that the CGs are mainly enriched in endocytosis, cell cycle, wnt signalling and mTOR signalling pathways. Hazard models identified four key genes, CASP2, HCN4, LRRC69 and SRD5A1, that were significantly associated with CRC progression and predicted the 1-year, 3-years, and 5-years survival times. WGCNA identified seven hub genes: DSCC1, ETV4, KIAA1549, NOP56, RRS1, TEAD4 and ANKRD13B, which exhibited strong predictive performance in distinguishing normal from CRC (early and late-stage) samples. ConclusionsIntegrating regulatory information with gene expression improved early versus latestage prediction. The identified potential prognostic and diagnostic biomarkers in this study may guide us in developing effective therapeutic strategies for CRC management.

bioinformatics↗

bioRxiv2020

A Library Of Induced Pluripotent Stem Cells From Clinically Well-Characterized, Diverse Healthy Human Individuals

A library of well-characterized human induced pluripotent stem cell (hiPSC) lines from clinically healthy human subjects could serve as a useful resource of normal controls for in vitro human development, disease modeling, genotype-phenotype association studies, and drug response evaluation. We report generation and extensive characterization of a gender-balanced, racially/ethnically diverse library of hiPSC lines from 40 clinically healthy human individuals who range in age from 22-61. The hiPSCs match the karyotype and short tandem repeat identity of their parental fibroblasts, and have a transcription profile characteristic of pluripotent stem cells. We provide whole genome sequencing data for one hiPSC clone from each individual, genomic ancestry determination, and analysis of Mendelian disease genes and risks. We document similar transcriptomic profiles, single-cell RNA-seq derived cell clusters and physiology of cardiomyocytes differentiated from multiple independent hiPSC lines. This extensive characterization makes this hiPSC library a valuable resource for many studies on human biology.

cell biology↗

bioRxiv2019

Exogenous application of KNO3 elevates the salinity tolerance of Stevia rebaudiana through ion homeostasis mechanism

Though relatively little is understood of adaptation, physiological and metabolic changes of Stevia rebaudiana under exposure to salinity stress, it is hypothesized that exogenous application of potassium (K+) could elevates the salinity tolerance through ions homeostasis. Thus, an experiment was conducted with twenty treatment combinations comprising four salinity levels (irrigation with normal water as control and three level of NaCl at 40, 80 and 120 mM) and five different concentrations of KNO3 (0.0, 2.5, 5.0, 7.5, and 10.0 g L-1). Dry leaf yield was not negatively affected with mild salinity (40 mM). However, the detrimental effects were observed at moderate and higher salinity levels (80 and 120 mM). The uptakes of K+, Ca2+, and N were significantly reduced at higher salinity level, whereas accumulations of Na+ and Cl- ions in plant tissues were substantially increased. Proline content in leaf was also increased significantly (P[≤]0.05) in response to salt stress. Among the foliar application, KNO3 at 5.0 gL-1 registered significantly (P[≤]0.05) higher dry leaf yield compared with control. Exogenous application of K+ under moderate salinity stress maintained ion balance in cytosol, particularly K: Na. Thus, the salinity tolerance of stevia can be elevated to some extent through exogenous application of K+.\n\nHighlightThe detrimental effects of moderate and higher salinity levels on growth and dry leaf yield of stevia were observed. However, tolerance level can be elevated through exogenous application of KNO3.

plant biology↗

bioRxiv2017

A Comparison of mRNA Sequencing with Random Primed and 3’-Directed Libraries

Deep mRNA sequencing (mRNAseq) is the state-of-the-art for whole transcriptome measurements. A key step is creating a library of cDNA sequencing fragments from RNA. This is generally done by random priming, creating multiple sequencing fragments along the length of each transcript. A 3 end-focused library approach cannot detect differential splicing, but has potentially higher throughput at lower cost (~10-fold lower), along with the ability to improve quantification by using transcript molecule counting with unique molecular identifiers (UMI) to correct for PCR bias. Here, we compare implementation of such a 3-digital gene expression (3-DGE) approach with \"conventional\" random primed mRNAseq, which has not yet been done. We find that while conventional mRNAseq detects ~15% more genes, the resulting lists of differentially expressed genes and therefore biological conclusions and gene signatures are highly concordant between the two techniques. We also find good quantitative agreement on the level of individual genes between the two techniques in terms of both read counts and fold change between two conditions. We conclude that for high-throughput applications, the potential cost savings associated with the 3-DGE approach are a very reasonable tradeoff for modest reduction in sensitivity and inability to observe alternative splicing, and should enable much larger scale studies focused on not only differential expression analysis, but also quantitative transcriptome profiling. The computational scripts and programs, along with experimental standard operating procedures used in our pipeline presented here, are freely available on our website (www.dtoxs.org).

genomics↗