Biology subjects

Saini, K.

Publications and source records attributed to Saini, K..

12 recordsLinked to original sources

bioRxiv2025

PIF4-mediated regulation of H2O2 homeostasis controls Arabidopsis seedling thermomorphogenesis

Thermomorphogenesis under high ambient temperature involves extensive developmental changes, including hypocotyl elongation at the seedling stage, in Arabidopsis. Reactive Oxygen Species (ROS), particularly hydrogen peroxide (H2O2), are important signaling molecules, playing crucial roles in plant development and stress responses. While ROS-homeostasis is shown to be crucial for maintaining cellular functions and mediating various developmental responses, the involvement of ROS-homeostasis in the regulation of thermomorphogenic responses and the underlying genetic basis remains poorly understood. In this study, comprehensive transcriptomic analyses revealed strong induction of ROS homeostasis and signaling genes in Arabidopsis seedlings under high ambient temperature. Pharmacological and genetic experiments showed that maintaining H2O2 homeostasis is crucial for seedling thermomorphogenesis. We identified PHYTOCHROME INTERACTING FACTOR 4 (PIF4) as a key regulator of H2O2 homeostasis via direct transcriptional activation of CAT2 and CAT3 genes, which are involved in the regulation of H2O2 levels, to modulate hypocotyl elongation under high temperature. Genetic and biochemical experiments confirmed that CATs act downstream to PIF4 in the same signaling pathway to regulate high-temperature-responsive hypocotyl elongation. Interestingly, elevated H2O2 levels reduced PIF4 protein abundance under high temperature. Together, our findings establish a PIF4-CAT-H2O2 regulatory module, functioning alongside the canonical PIF4-Auxin module, that integrates to auxin signaling to fine-tune hypocotyl elongation under high temperature by maintaining H2O2 homeostasis. HighlightsO_LIHigh ambient temperature significantly affects ROS homeostasis and signaling genes in Arabidopsis seedlings. C_LIO_LIH2O2 homeostasis is crucial for high-temperature-mediated hypocotyl elongation, a signature feature of Arabidopsis thermomorphogenesis. C_LIO_LIPHYTOCHROME INTERACTING FACTOR 4 (PIF4) regulates the expression of CATALASE genes in a temperature-dependent manner to maintain H2O2 levels for seedling thermomorphogenesis. C_LIO_LIElevated H2O2 level reduces PIF4 protein abundance, thus forming a PIF4-CAT-H2O2 regulatory module that integrates with auxin to fine-tune hypocotyl elongation under high temperature. C_LI

plant biology↗

bioRxiv2025

Deep learning-driven morphology analysis enables label-free classification of therapeutic agent- naive versus resistant cancer cells

Therapeutic drug treatments of solid tumors are often undermined by various resistance mechanisms. Identification of drug-resistance phenotypes at the single cell level is challenging because conventional molecular methods are cell-destructive, labor-intensive, and cost-prohibitive. To overcome these challenges, we developed an orthogonal approach to drug-resistance phenotyping, through the use of deep-learning-driven morphology analysis of single, high resolution cell images. Specifically, we trained deep learning-based drug resistance classifiers using cell images from 5 different cell lines that were rendered resistant to 5 different therapeutic agents, using a foundation model framework. With high accuracy, the classifier correctly predicted naive or resistance phenotypes across all cancer types and across all the therapeutic agent types (chemotherapeutic, targeted) tested. These results showed that morphology can capture complex phenotype information in the context of drug treatment. To demonstrate the potential clinical utility of the drug resistance classifier, it was applied to a dissociated tumor biopsy and the resulting phenotype predictions were in close concordance with scRNASeq analysis of the biopsy. Our study highlights the potential of deep-learning-driven morphology analysis to provide complex phenotype information, and ultimately shape oncology drug treatment strategies at the patient-level in a clinical context.

cancer biology↗

bioRxiv2024

Label-Free Melanoma Phenotype Classification Using Artificial Intelligence-Based Morphological Profiling

Melanomas are the deadliest skin cancers, in part due to cellular plasticity and heterogeneity. Intratumoral heterogeneity drives varied mutable phenotypes, specifically "melanocytic" and "mesenchymal" cell states, which result in differential functional properties and drug responses. Definitive and rigorous classification of these phenotypic states has been challenging with conventional biomarker-based methods, and high-parameter molecular methods are cell-destructive, labor-intensive, and time-consuming. To overcome these technical and practical limitations, we utilized label-free artificial intelligence-based morphological profiling to classify live melanoma cells into melanocytic and mesenchymal phenotypes based on high resolution imaging of single cells. To predict the phenotypes of single melanoma cells based on morphology alone, we developed the AI-based Melanoma Phenotype Classifier trained with 19 patient-derived cell lines with known melanocytic or mesenchymal transcriptional profiles. To link phenotypic state with high-dimensional morphological profiles, cells were subjected to genetic and chemical perturbations known to shift phenotypic states. The AI classifier successfully predicted phenotypic shifts which were confirmed by single-cell RNA-Seq (scRNA-Seq). These results demonstrate that correlations between melanoma cell phenotypes and morphological changes are detectable by AI. Additionally, the Melanoma Phenotype Classifier was applied to dissociated tumor biopsy samples and characterization of phenotypic heterogeneity was supported by scRNA-Seq transcriptional profiles. This work establishes a link between cell morphology and melanoma phenotypes, laying the groundwork for the use of a label-free morphology-based method for phenotyping live melanoma cells combined with additional analyses.

cancer biology↗

bioRxiv2023

Pan-tissue scaling of stiffness versus fibrillar collagen reflects contractility-driven strain that inhibits fibril degradation

Polymer network properties such as stiffness often exhibit characteristic power laws in polymer density and other parameters. However, it remains unclear whether diverse animal tissues, composed of many distinct polymers, exhibit such scaling. Here, we examined many diverse tissues from adult mouse and embryonic chick to determine if stiffness (Etissue) follows a power law in relation to the most abundant animal protein, Collagen-I, even with molecular perturbations. We quantified fibrillar collagen in intact tissue by second harmonic generation (SHG) imaging and from tissue extracts by mass spectrometry (MS), and collagenase-mediated decreases were also tracked. Pan-tissue power laws for tissue stiffness versus Collagen-I levels measured by SHG or MS exhibit sub-linear scaling that aligns with results from cellularized gels of Collagen-I but not acellular gels. Inhibition of cellular myosin-II based contraction fits the scaling, and combination with inhibitors of matrix metalloproteinases (MMPs) show collagenase activity is strain - not stress- suppressed in tissues, consistent with past studies of gels and fibrils. Beating embryonic hearts and tendons, which differ in both collagen levels and stiffness by >1000-fold, similarly suppressed collagenases at physiological strains of [~]5%, with fiber-orientation regulating degradation. Scaling of Etissue based on use-it-or-lose-it kinetics provides insight into scaling of organ size, microgravity effects, and regeneration processes while suggesting contractility-driven therapeutics.

molecular biology↗

bioRxiv2023

Artificial intelligence-driven morphology-based enrichment of malignant cells from body fluid

Cell morphology is a fundamental feature used to evaluate patient specimens in pathological analysis. However, traditional cytopathology analysis of patient effusion samples is limited by low tumor cell abundance coupled with high background of non-malignant cells, restricting the ability for downstream molecular and functional analyses to identify actionable therapeutic targets. We applied the Deepcell platform that combines microfluidic sorting, brightfield imaging, and real-time deep learning interpretations based on multi-dimensional morphology to enrich carcinoma cells from malignant effusions without cell staining or labels. Carcinoma cell enrichment was validated with whole genome sequencing and targeted mutation analysis, which showed higher sensitivity for detection of tumor fractions and critical somatic variant mutations that were initially at low-levels or undetectable in pre-sort patient samples. Combined, our study demonstrates the feasibility and added value of supplementing traditional morphology-based cytology with deep learning, multi-dimensional morphology analysis, and microfluidic sorting.

pathology↗

bioRxiv2022

Transcriptional profiles of functionally distinct HLADR+CD38+ CD8 T cells subsets from acute febrile dengue patients

Previous studies showed that a discrete population of the CD8 T cells with HLADR+CD38+ phenotype expand massively during the acute febrile phase of dengue natural infection. Although about a third of these massively expanding HLADR+CD38+ CD8 T cells were of CD69high phenotype, only a small fraction of them produced IFN{gamma} upon in vitro peptide stimulation. What other cytokines/ chemokines do these peptides stimulated HLADR+CD38+ CD8 T cells express, what transcriptional profiles distinguish the CD69+IFN{gamma}+, CD69+IFN{gamma}-, and CD69-IFN{gamma}- subsets, and whether the expansion of the total HLADR+CD38+ CD8 T cells or the IFN{gamma} producing CD8 T cells differ depending on disease severity remained unclear. This study addresses these knowledge gaps. We find that the CD69+IFN{gamma}+ subset uniquely expressed key genes involved in protein translation, cellular metabolism, proliferation and dendritic cell cross talk. Both the CD69+IFN{gamma}+ and CD69+IFN{gamma}- subsets had an antigen responsive gene signature with genes involved in cytotoxic effector functions, regulation of T cell receptor signaling, signaling by MAPK, chemotaxis and T cell trafficking to inflamed tissues with the expression being more robust in the IFN{gamma}+ CD69+ subset. On the other hand, the CD69- IFN{gamma}- subset was biased towards expression of genes that both augment and dampen T cell responses. Lastly, the expansion of total HLADR+ CD38+ CD8 T cells and also the IFN{gamma} producing HLADR+ CD38+ CD8 T cells was similar in patients with different grades of disease. Taken together, this study provides valuable insights into the inherent diversity of the effector CD8 T cell response during dengue.

immunology↗

bioRxiv2022

Realtime morphological characterization and sorting of unlabeled viable cells using deep learning

Phenotyping of single cells has dramatically lagged advances in molecular characterization and remains a manual, subjective, and destructive process. We introduce COSMOS, a platform for phenotyping and enrichment of cells based on deep learning interpretation of high-content morphology data in realtime. By training models on an atlas of >1.5 billion images, we demonstrate enrichment of unlabeled cells up to 33,000 fold. We apply COSMOS to multicellular tissue biopsy samples demonstrating that it can identify malignant cells with similar accuracy to molecular approaches while enriching viable cells for functional evaluation. We show high-dimensional embedding vectors of morphology generated by COSMOS without any need for complex sample pre-processing, gating, or bioinformatics capabilities, which enables discovery of cellular phenotypes, and integration of morphology into multi-dimensional analyses. One sentence summaryA novel platform capable of high-throughput imaging and gently sorting cells using deep morphological assessment.

cell biology↗

bioRxiv2022

High temperature limits leaf size via direct control of cell cycle by coordinated functions of PIF4 and TCP4

High ambient temperature suppresses Arabidopsis rosette leaf area, in contrast to elongation of stem and petiole. While the mechanism underlying temperature-induced elongation response is extensively studied, the genetic basis of temperature-regulation of leaf size is largely unknown. Here we show that warm temperature inhibits cell proliferation in the Arabidopsis leaves resulting in fewer cells compared to the control condition. Cellular phenotyping, genetic, and biochemical analyses established the key roles of PIF4 and TCP4 transcription factors in the suppression of Arabidopsis leaf area under high temperature by a reduction in cell number. We show that temperature-mediated suppression of cell proliferation requires PHYTOCHROME INTERACTING FACTOR 4 (PIF4). PIF4 interacts with TEOSINTE BRANCHED1/CYCLOIDEA/PCF4 (TCP4) and regulates the expression of cell cycle inhibitor, KIP-RELATED PROTEIN 1 (KRP1), to control the leaf size under high temperature. Warm temperature induces binding of both PIF4 and TCP4 to the KRP1 promoter. PIF4 binding to KRP1 under high temperature is TCP4 dependent as TCP4 regulates PIF4 levels under high temperature. We propose a model where a warm temperature-mediated accumulation of PIF4 in the leaf cells promotes its binding to the KRP1 promoter in a TCP4-dependent way to regulate cell production and leaf size. Our finding of high temperature-mediated transcriptional upregulation of KRP1 integrates a developmental signal with an environmental signal that converges on a basal cell regulatory process. One sentence summaryHigh ambient temperature suppresses Arabidopsis leaf area by reducing cell proliferation via PIF4- and TCP4-dependent transcription control of KRP1.

plant biology↗

bioRxiv2021

GA-mediated spatial control of cell division expounds the leaf size variation between cultivated and wild rice

O_LICellular and genetic understanding of rice leaf size regulation is limited, despite rice being the staple food of more than half of the global population. We investigated the mechanism controlling the rice leaf length using cultivated and wild rice accessions that remarkably differed for leaf size. C_LIO_LIComparative transcriptomics, Gibberellic Acid (GA) quantification, and leaf kinematics of the contrasting accessions suggested the involvement of GA, cell cycle, and Growth-Regulating Factors (GRFs) in the rice leaf size regulation. Zone-specific expression analysis and VIGS established the functions of specific GRFs in the process. C_LIO_LIThe leaf length of the selected accessions was strongly correlated with GA levels. Higher GA content in wild rice accessions with longer leaves and GA-induced increase in the leaf length via an increase in cell division confirmed a GA-mediated regulation of division zone in rice. Downstream to GA, OsGRF7 and OsGRF8 function for controlling cell division to determine the rice leaf length. C_LIO_LISpatial control of cell division to determine the division zone size mediated by GA and downstream OsGRF7 and OsGRF8 explains the leaf length differences between the cultivated and wild rice. This mechanism to control rice leaf length might have contributed to optimizing leaf size during domestication. C_LI

plant biology↗

bioRxiv2021

Immunophenotyping and transcriptional profiling of human plasmablasts in dengue.

Previous studies have shown that plasmablasts expand massively in dengue patients as compared to many other situations such as influenza infection or vaccination. However, a detailed understanding of the phenotypes and transcriptional features of these cells is lacking. Moreover, despite India having nearly a third of global dengue disease burden, there is virtually no information on plasmablasts responses in dengue patients from India. Here, we provide a detailed characterization of plasmablast responses from dengue confirmed febrile children in India. Immunophenotyping and RNA seq analysis showed that in addition to secreting dengue specific antibodies, these massively expanding cells expressed several adhesion molecules, chemokines and chemokine receptors that are involved in endothelial interactions, homing to skin or mucosal tissues including intestine. Surprisingly, we found that these cells also upregulated expression of several cytokine genes that are involved in angiogenesis, leukocyte extravasation and vascular permeability. These transcriptional features were qualitatively similar to plasmablasts from influenza vaccinees. Interestingly, the expansion of the plasmablasts in dengue patients was significantly lower in patients with primary dengue infection compared to those with secondary dengue. Moreover, within the primary dengue patients, their expansion was significantly lower in patients with mild dengue infection (DI) compared to patients with dengue with warning signs (DW) or severe dengue (SD). These results significantly improve our understanding of human plasmablast responses in dengue. Importance Dengue is a globally spreading with over 100 million clinical cases annually with symptoms ranging from mild self-limiting febrile illness to more severe and sometimes life-threatening dengue hemorrhagic fever or shock, especially among children. India contributes nearly a third of global dengue disease burden. The pathophysiology of dengue is complex and remains poorly understood despite many advances indicating a key role for antibody dependent enhancement of infection. While serum antibodies have been extensively studied, the characteristics of the cellular factories responsible for antibody production, i.e., plasmablasts, are only beginning to emerge. This study provides a comprehensive understanding of the magnitude, phenotype, functional and transcriptional profiles of human plasmablasts from dengue patients in India.

immunology↗

bioRxiv2021

Heterogeneous strains in tissue collagen show that high strains locally suppress degradation by collagenase

Collagen, the most abundant protein in mammals, contributes to the physical properties of different tissues during development, homeostasis, and disease. The adaptation of physical properties of tissues to mechanical stimuli is thus dependent on the control of tissue collagen levels by well-regulated synthesis and degradation of collagen. Importantly, how various molecular-level events within a tissue sustaining a range of mechanical strains contribute towards maintaining its collagen levels, remains unclear to date. Such molecular level processes in tissues are studied here in the case of isolated tendons consisting of collagen fibrils oriented along tissue loading-axis and beating embryonic hearts to gain understanding of mechanical load dependent tissue sculpting. Using a novel bioreactor design, starved mice tail tendon fascicles were used as a "cell-free" model and were subjected to heterogeneous and uniaxial deformation modes. Patterned photobleaching of fluorescent probes, a novel Aza-peptide or dye, on fascicles used to quantify tissue strains. Tissue microstructure was simultaneously imaged using second harmonic generation (SHG) signal to assess tissue collagen content while deformed fascicle samples were exposed to purified matrix metalloproteinase-1 (MMP-1) or bacterial collagenase (BC). A decrease in the degradation rate (relative to strain-free) was observed for physiological strain limits of tendon tissue (i.e. [~]5-8%) while at higher strains (i.e. pathological) the degradation rate was independent of strain magnitude changes. Interestingly, the strain dependence of degradation rate was independent of cleavage-site specificity of the collagenase molecules and the mode of tendon tissue deformation. Although spatially different within a tissue sample, the values of strain, degradation rate and collagen fiber organization with time during degradation of each tendon fascicle region were highly correlated. Tendon regions dominated by collagen fibers inclined to fascicle-axis were observed to follow non-affine deformation. The dependence of the degradation rate on mechanical strain is due to sequestration of collagen cleavage sites within fibrils. Permeation, tissue mass density and mobility of fluorescent collagenase and dextran are strain-independent for fascicle strains up to [~]5-8% while the degradation rate is positively correlated to unfolded triple-helical collagen content. Normal beating chick hearts subjected to [~]5% peak strain in a spatiotemporal coordinate contractile wave were observed to maintain their collagen mass until the beating strain is suppressed by inhibition of myosin-II. Based on the presence of exogeneous MMP inhibitors, endogenous MMPs within the non-beating hearts degrade the collagens immediately (in [~]30-60 mins). Both tissue systems under mechanical strains suggest degradative sculpting where mechanical strain-dependent collagen fibril architecture changes appear to play a key role in determining collagen lifetime within tissues. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=139 HEIGHT=200 SRC="FIGDIR/small/430141v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@17da11borg.highwire.dtl.DTLVardef@dbfb8forg.highwire.dtl.DTLVardef@6069b9org.highwire.dtl.DTLVardef@1bd273e_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2021

H3K27me3 mediated KRT14 upregulation promotes TNBC peritoneal metastasis

Triple Negative Breast Cancer (TNBC) is known to have poor prognosis and adverse clinical outcome among all breast cancer subtypes due to the absence of available targeted therapy for it. Emerging literature indicates that epigenetic reprogramming is now appreciated as a driving force for TNBC pathophysiology. High expression of epigenetic modulator EZH2 (Enhancer of zeste homolog 2) has been shown to correlate with TNBC poor prognosis but the contribution of EZH2 catalytic (H3K27me3) versus non-catalytic EZH2 (NC-EZH2) function in TNBC growth and progression remains elusive. In the process of dissecting the impact of H3K27me3 versus NC-EZH2 function in TNBC pathogenesis, we reveal that selective hyperactivation of H3K27me3 over NC-EZH2 not only promotes TNBC metastasis but also alters the metastatic landscape of TNBC. Using extensive in- vivo live animal imaging, we present conclusive evidence that peritoneal metastasis, particularly splenic metastasis of TNBC is governed by H3K27me3. Transcriptome analyses of hyperactive H3K27me3 cells lead us to discover Cytokeratin-14 (KRT14) as a new target of H3K27me3. Unlike classical H3K27me3 mediated suppression of gene expression, here; we observe that H3K27me3 enhances KRT14 transcription by attenuating the binding of transcriptional repressor Sp1 to its promoter. Further, loss of KRT14 significantly reduces TNBC migration, invasion and splenic metastasis. Finally, genetic ablation of EZH2 or pharmacological inhibition of EZH2 catalytic function by FDA approved drug tazemetostat (EPZ6438) robustly inhibits TNBC peritoneal metastasis. Altogether, our preclinical findings posit a rational insight for the clinical development of H3K27me3 inhibitor like tazemetostat as a targeted therapy against TNBC.

cancer biology↗