Biology subjects

Sandhu, J.

Publications and source records attributed to Sandhu, J..

12 recordsLinked to original sources

bioRxiv2026

MERFISH-based pooled genetic screening reveals cell non-autonomous phenotypes in intact tissue

Genetic perturbations can reshape both the state of a targeted cell and the behavior of neighboring cells. Measuring these effects systematically in intact tissues requires pooled screening methods that jointly identify perturbations, molecular phenotypes, and spatial context of individual cells. Here, we report an imaging-based pooled screening method that detects perturbation identities and endogenous RNAs without enzymatic amplification. Relative to our previous enzymatic-amplification-based workflow, amplification-free MERFISH detection with direct hybridization increased recovery of perturbation barcodes by ~10-fold and endogenous transcripts by 2.5-fold, improving perturbation assignment as well as molecular profiling of both perturbed and neighboring cells. Applying this method to a genetic mosaic mouse liver screen targeting ~200 genes in hepatocytes, we profiled 1.5 million cells in intact tissues and mapped both cell-autonomous responses of perturbed hepatocytes and cell non-autonomous changes in neighboring immune and vascular populations. These included localized accumulation of pDC-like cells near hepatocytes with impaired V-ATPase function and angiogenic responses in vascular cells near Vhl-perturbed hepatocytes with hypoxia activation. Our method provides a simplified, scalable approach to linking genetic perturbations with cell state, multicellular response, and tissue organization.

genomics↗

bioRxiv2025

A core genetic mechanism integrates growth hormone signals to control meristem fate and inflorescence architecture in setaria and maize

Inflorescence architecture in cereals is a major determinant of grain yield and harvestability. Architecture is determined by the number, arrangement and order of lateral branches, which are formed from clusters of stem cells called meristems. Variation in branching patterns arises from regulation of meristem determinacy, i.e., indeterminate meristems maintain meristematic activity allowing for higher order branching and determinate meristems form a terminal organ. The timing by which an indeterminate branch meristem acquires a determinate fate and transitions to a spikelet meristem (SM), ultimately forming the grain-bearing spikelet, defines architecture and grain yield potential. This study leverages the unique inflorescence morphology of model grass Setaria viridis (setaria) to identify factors controlling SM fate and determinacy and characterize their interactions. In setaria, axillary branches terminate either in a spikelet or sterile bristle, where the latter loses SM identity due to brassinosteroid (BR)-mediated disruption of organ boundary formation. A forward genetics screen identified two mutants with only bristles on their panicles; one defective in gibberellic acid (GA) signaling caused extreme elongation and disruption of spikelet development and the other homeotically converted spikelets to bristles. The latter named spikeletless (spkl) was mapped and validated as an ortholog of the maize determinacy factor ramosa1 (ra1). Genetic analyses showed that SvRa1 acts upstream of BR-mediated regulation of SM identity and determinacy. A model is proposed where SvRA1 maintains SM fate by modulating GA homeostasis, spatially restricting BR signaling and preserving boundary gene expression and determinacy. In bristle primordia, which are generally paired with spikelets, GA and BR act synergistically. Comparative analyses in maize highlight pathway conservation in inflorescence architecture with some specific variations.

plant biology↗

bioRxiv2025

High-resolution spatial mapping of cell state and lineage dynamics in vivo with PEtracer

Charting the spatiotemporal dynamics of cell fate determination in development and disease is a long-standing objective in biology. Here we present the design, development, and extensive validation of PEtracer, a prime editing-based, evolving lineage tracing technology compatible with both single-cell sequencing and multimodal imaging methodologies to jointly profile cell state and lineage in dissociated cells or while preserving cellular context in tissues with high spatial resolution. Using PEtracer coupled with MERFISH spatial transcriptomic profiling in a syngeneic mouse model of tumor metastasis, we reconstruct the growth of individually-seeded tumors in vivo and uncover distinct modules of cell-intrinsic and cell-extrinsic factors that coordinate tumor growth. More generally, PEtracer enables systematic characterization of cell state and lineage relationships in intact tissues over biologically-relevant temporal and spatial scales.

molecular biology↗

bioRxiv2024

A platform for multimodal in vivo pooled genetic screens reveals regulators of liver function

Organ function requires coordinated activities of thousands of genes in distinct, spatially organized cell types. Understanding the basis of emergent tissue function requires approaches to dissect the genetic control of diverse cellular and tissue phenotypes in vivo. Here, we develop paired imaging and sequencing methods to construct large-scale, multi-modal genotype-phenotypes maps in tissue with pooled genetic perturbations. Using imaging, we identify genetic perturbations in individual cells while simultaneously measuring their gene expression and subcellular morphology. Using single-cell sequencing, we measure transcriptomic responses to the same genetic perturbations. We apply this approach to study hundreds of genetic perturbations in the mouse liver. Our study reveals regulators of hepatocyte zonation and liver unfolded protein response, as well as distinct pathways that cause hepatocyte steatosis. Our approach enables new ways of interrogating the genetic basis of complex cellular and organismal physiology and provides crucial training data for emerging machine-learning models of cellular function.

genomics↗

bioRxiv2024

A brain-shuttled antibody targeting alpha synuclein aggregates for the treatment of synucleinopathies

Parkinsons disease and multiple system atrophy are members of a class of devastating neurodegenerative diseases called synucleinopathies, which are characterized by the presence of alpha-synuclein (-Syn) rich aggregates in the brains of patients. Passive immunotherapy targeting these aggregates is an attractive disease-modifying strategy. Such an approach must not only demonstrate target selectivity towards -Syn aggregates, but also achieve appropriate brain exposure to have the desired therapeutic effect. Here we present preclinical data for a next-generation antibody for the treatment of synucleinopathies. SAR446159 (ABL301) is a bispecific antibody composed of an -Syn-binding immunoglobulin (IgG) and an engineered insulin-like growth factor receptor 1 (IGF1R) binding single-chain variable fragment (scFv), acting as a shuttle to transport an antibody across the blood-brain barrier (BBB). SAR446159 binds tightly and preferentially to -Syn aggregates and prevents their seeding capacity in vitro and in vivo. Incubation with SAR446159 reduced -Syn preformed fibrils (PFFs) uptake in neurons and facilitated uptake and clearance by microglia. In wild type mice injected in the striatum with -Syn PFFs, treatment with SAR446159 reduced the spread of aSyn pathology as measured by phosphorylated -Syn staining and lessened the severity of motor phenotypes. Additionally, in 9-month-old transgenic mice overexpressing -Syn (mThy1--Syn, Line 61), repeated treatment with SAR446159 reduced markers of -Syn aggregation in the brain. SAR446159 had significantly higher brain and CSF penetration over a sustained period than its monospecific counterpart (1E4) in rats and monkeys. The binding properties of SAR446159 combined with its brain-shuttle technology make it a potent, next-generation immunotherapeutic for treating synucleinopathies.

neuroscience↗

bioRxiv2024

Spatial microenvironments tune immune response dynamics in the Drosophila larval fat body

Immune responses in tissues display complex spatial patterns of gene expression that are linked to disease outcomes. However, the mechanisms that generate these patterns--including the relative roles of noisy gene expression dynamics, microbial transport, and tissue anatomy-- are poorly understood. As a tractable model of spatial immune responses, we investigated heterogeneous expression of antimicrobial peptides in the larval fly fat body, an organ functionally analogous to the liver. Using live light sheet fluorescence microscopy, we discovered that individual fat body cells express antimicrobial peptides at approximately constant rates following infection, but that the average rate varies along the anterior-posterior axis of the fat body, with rapid expression in the anterior and posterior lobes. Overexpression of immune signaling components and analysis of spatial transcriptomes revealed that these tissue microenvironments are predefined independently of infection, with the rate-limiting step of antimicrobial peptide induction downstream of peptidoglycan sensing. The locations of these microevironments correlate with heartbeat-dependent fluid flow in a manner resembling the strategic positioning of immune cells in the liver, gut, and lymph nodes of mammals. We speculate that this spatial compartmentalization helps the fat body efficiently perform its diverse metabolic, enzymatic, and immunological functions. Author SummaryRecent sequencing and imaging technologies have revealed that immune responses in our organs are not spatially uniform, but occur in complex patterns in which clusters of nearby cells are strongly active. There is increasing evidence that these spatial interactions are important for controlling disease outcomes. However, little is known about the dynamics of how these spatial patterns form: are they created through randomness, are they shaped by external signals, such as pathogen localization, or are they predetermined, representing a fine-grained tissue anatomy? While it is practically infeasible to directly observe these types of cellular dynamics in humans or even mice, small, transparent organisms like fruit fly larvae offer a literal window into the inner workings of immune responses. We used a combined imaging and genetics approach to study heterogeneous spatial patterns of antimicrobial peptide production in the fruit fly equivalent of the liver. We discovered that these spatial patterns were in fact predetermined and represent previously unknown immune microenvironments within this important tissue that correlate with areas of fast blood flow. Since innate immune signaling in highly conserved, this spatial logic may be a general feature of immunological tissues that is relevant to other animals, including humans.

immunology↗

bioRxiv2023

Aster-dependent non-vesicular transport facilitates dietary cholesterol uptake

Intestinal cholesterol absorption is an important contributor to systemic cholesterol homeostasis. Niemann-Pick C1 Like 1 (NPC1L1), the target of the drug ezetimibe (EZ), assists in the initial step of dietary cholesterol uptake. However, how cholesterol moves downstream of NPC1L1 is unknown. Here we show that Aster-B and Aster-C are critical for non-vesicular cholesterol movement in enterocytes, bridging NPC1L1 at the plasma membrane (PM) and ACAT2 in the endoplasmic reticulum (ER). Loss of NPC1L1 diminishes accessible PM cholesterol in enterocytes and abolishes Aster recruitment to the intestinal brush border. Enterocytes lacking Asters accumulate cholesterol at the PM and display evidence of ER cholesterol depletion, including decreased cholesterol ester stores and activation of the SREBP-2 transcriptional pathway. Aster-deficient mice have impaired cholesterol absorption and are protected against diet-induced hypercholesterolemia. Finally, we show that the Aster pathway can be targeted with a small molecule inhibitor to manipulate dietary cholesterol uptake. These findings identify the Aster pathway as a physiologically important and pharmacologically tractable node in dietary lipid absorption. One-Sentence SummaryIdentification of a targetable pathway for regulation of dietary cholesterol absorption

physiology↗

bioRxiv2022

Evaluating metabolic and genomic data for predicting grain traits under high night temperature stress in rice

The asymmetric increase in average nighttime temperatures relative to increase in average daytime temperatures due to climate change is decreasing grain yield and quality in rice. Therefore, a better understanding of the impact of higher night temperature on single grain at whole genome level is essential for future development of more resilient rice. We investigated the utility of metabolites obtained from grains to classify high night temperature conditions of genotypes, and metabolites and single nucleotide polymorphisms to predict grain length, width, and perimeter phenotypes using a rice diversity panel. We found that the metabolic profiles of rice genotypes alone could be used to classify control and high night temperature conditions with high accuracy using random forest or extreme gradient boosting. The best linear unbiased prediction and BayesC showed greater metabolic prediction performance than machine learning models for grain-size phenotypes. Metabolic prediction was most effective for grain width, resulting in the highest prediction performance. Genomic prediction performed better than metabolic prediction. Integrating metabolites and genomics simultaneously in a prediction model slightly improved prediction performance. We did not observe a difference in prediction between the control and high night temperature conditions. Several metabolites were identified as auxiliary phenotypes that could be used to enhance the multi-trait genomic prediction of grain-size phenotypes. Our results showed that, in addition to single nucleotide polymorphisms, metabolites collected from grains offer rich information to perform predictive analyses, including classification modeling of high night temperature responses and regression modeling of grain size-related phenotypes in rice.

genetics↗

bioRxiv2020

A Uropathogenic E. coli UTI89 model of prostatic inflammation and collagen accumulation for use in studying aberrant collagen production in the prostate

Bacterial infection is one known etiology of prostatic inflammation. Prostatic inflammation is associated with prostatic collagen accumulation and both are linked to progressive lower urinary tract symptoms in men. We characterized a model of prostatic inflammation utilizing transurethral instillations of E. coli UTI89 in C57BL/6J male mice with the goal of determining the optimal instillation conditions, understanding the impact of instillation conditions on urinary physiology, and identifying ideal prostatic lobes and collagen 1a1 prostatic cell types for further analysis. The smallest instillation volume tested (50 {micro}L) distributes exclusively to bladder, 100 and 200 {micro}L volumes distributes to bladder and prostate, and a 500 {micro}L volume distributes to bladder, prostate and ureter. A threshold optical density (OD) of 0.4 E. coli UTI89 in the instillation fluid is necessary for significant (p < 0.05) prostate colonization. E. coli UTI89 infection results in a low frequency, high volume spontaneous voiding pattern. This phenotype is due to exposure to E. coli UTI89, not catheterization alone, and is minimally altered by a 50 {micro}L increase in instillation volume and doubling of E. coli concentration. Prostate inflammation is isolated to the dorsal prostate and is accompanied by increased collagen density. This is partnered with increased density of PTPRC+, ProCOL1A1+ co-positive cells and decreased density of ACTA2+, ProCOL1A1+ co-positive cells. Overall, we determined that this model is effective in altering urinary phenotype and producing prostatic inflammation and collagen accumulation in mice.

physiology↗

bioRxiv2020

SeedExtractor: an open-source GUI for seed image analysis

ABSTRACTAccurate measurement of seed size parameters is essential for both: breeding efforts□aimed at□enhancing yields and basic research□focused on discovering genetic components that regulate seed size. To address this need, we have developed an open-source graphical user interface (GUI) software, SeedExtractor that□determines seed size and shape (including area, perimeter, length, width, circularity, and centroid), and seed color with capability to process a large number of images in a time-efficient manner. In this context, our application takes ∼2 seconds for analyzing an image, i.e. significantly less compared to the other tools. As this software is open-source, it can be modified by users□to serve more specific needs. The adaptability of SeedExtractor was demonstrated by analyzing scanned seeds from multiple crops. We further validated the utility of this application by analyzing mature-rice seeds from 231 accessions in Rice Diversity Panel 1. The derived seed-size traits, such as seed length, width, were subjected to genome-wide association analysis. We identified well-known loci for regulating seed length (GS3) and width (qSW5/GW5) in rice, which demonstrated the accuracy of this application to extract seed phenotypes and accelerate trait discovery. In summary, we present a publicly available application that can be used to determine key yield-related traits in crops.HIGHLIGHT SeedExtractor is an open-source application designed to accurately measure seed size and seed color in a time-efficient manner for a wide variety of plant species.Competing Interest StatementThe authors have declared no competing interest.View Full Text

plant biology↗

bioRxiv2019

PI-Plat: A high-resolution image-based 3D reconstruction method to estimate growth dynamics of rice inflorescence traits

BackgroundRecent advances in image-based plant phenotyping have improved our capability to study vegetative stage growth dynamics. However, more complex agronomic traits such as inflorescence architecture (IA), which predominantly contributes to grain crop yield are more challenging to quantify and hence are relatively less explored. Previous efforts to estimate inflorescence-related traits using image-based phenotyping have been limited to destructive end-point measurements. Development of non-destructive inflorescence phenotyping platforms could accelerate the discovery of the phenotypic variation with respect to inflorescence dynamics and mapping of the underlying genes regulating critical yield components. ResultsThe major objective of this study is to evaluate post-fertilization development and growth dynamics of inflorescence at high spatial and temporal resolution in rice. For this, we developed the Panicle Imaging Platform (PI-Plat) to comprehend multi-dimensional features of IA in a non-destructive manner. We used 11 rice genotypes to capture multi-view images of primary panicle on weekly basis after the fertilization. These images were used to reconstruct a 3D point cloud of the panicle, which enabled us to extract digital traits such as voxel count and color intensity. We found that the voxel count of developing panicles is positively correlated with seed number and weight at maturity. The voxel count from developing panicles projected overall volumes that increased during the grain filling phase, wherein quantification of color intensity estimated the rate of panicle maturation. Our 3D based phenotyping solution showed superior performance compared to conventional 2D based approaches. ConclusionsFor harnessing the potential of the existing genetic resources, we need a comprehensive understanding of the genotype-to-phenotype relationship. Relatively low-cost sequencing platforms have facilitated high-throughput genotyping, while phenotyping, especially for complex traits, has posed major challenges for crop improvement. PI-Plat offers a low cost and high-resolution platform to phenotype inflorescence-related traits using 3D reconstruction-based approach. Further, the non-destructive nature of the platform facilitates analyses of the same panicle at multiple developmental time points, which can be utilized to explore the genetic variation for dynamic inflorescence traits in cereals.

plant biology↗

bioRxiv2017

Histamine signaling via the metabotropic receptor Trapped in endoderm 1 regulates courtship initiation in Drosophila melanogaster.

Understanding the role of genes in directing behavior is one of the primary goals of neuroscience. Mating behavior in Drosophila is controlled by male-specific splicing of the master regulatory gene fruitless (fru), and the male-specific splice form, fruM, is both necessary and sufficient for all aspects of the courtship ritual. We have previously described the role of Trapped in endoderm 1 (Tre1) in courtship behavior. Tre1 encodes an orphan G-protein-coupled receptor that is essential for normal courtship behavior in male flies. We previously found that feminizing Tre1-expressing cells in males via expression of the female-specific splicing factor Transformer (TraF) resulted in rapid courtship initiation. Here we confirm that Tre1 is required in neurons for normal courtship behavior, and present genetic evidence that Tre1 acts through the downregulation of the E-cadherin Shotgun, and that the neurotransmitter histamine is the likely Tre1 ligand. Our findings are the first evidence for metabotropic histamine receptors in Drosophila, and the first to demonstrate a role for histamine in courtship.

genetics↗