Biology subjects

Shah, S. I.

Publications and source records attributed to Shah, S. I..

10 recordsLinked to original sources

bioRxiv2025

Deep profiling of lupus nephritis kidneys reveals dynamic changes in myeloid cells associated with disease progression

ObjectivesLupus nephritis (LN) is a common, potentially fatal manifestation of systemic lupus erythematosus. We aim to gain new insights into the immune responses underlying LN and their relation to the histologic heterogeneity observed in this disease, focusing on myeloid cells. MethodsSingle-cell RNA-sequencing (scRNA-seq) was used to profile dissociated kidney samples from 156 LN patients and 30 healthy individuals. Spatial transcriptomics (ST), utilizing a gene panel designed to capture all myeloid subsets identified in the scRNA-seq data, was applied to kidney samples acquired from 6 LN patients and 2 healthy controls. ResultsWe generated a full catalog of the myeloid subsets found in LN kidneys. Our analyses indicated that an increase in irreversible tissue damage, as measured by the NIH chronicity index (CI), is associated with a gradual switch of the local immune response from one dominated by monocytes and macrophages to one featuring expanded CD4+ T, GZMK+CD8+ T, B and dendritic cells, with a parallel decrease in the interferon response. In proliferative/mixed LN only, the degree of active inflammation correlates with expansion of disease-specific macrophage (DMac) subsets, which later contract as the CI increases. Trajectory analysis of the scRNA-seq data suggested that DMacs arise from both infiltrating monocytes and tissue-resident macrophages; this was supported by the ST data, as well as cell cultures. DMacs are indicated to interact with parietal epithelial cells, promoting the development of glomerulosclerosis. ConclusionsWe suggest a detailed picture of the changes in the kidney immune mechanisms in LN as this disease progresses.

immunology↗

bioRxiv2025

Spatial Transcriptomics Identify T Cell-Driven Mechanisms of Kidney Damage in Immune Checkpoint Inhibitor-Associated Acute Interstitial Nephritis

IntroductionImmune checkpoint inhibitor-associated acute interstitial nephritis (ICI-AIN) is the most common finding on histopathology among patients with ICI-associated acute kidney injury (ICI-AKI). Patients with ICI-AIN often have T cell-dominant infiltration of the kidney and high tissue levels of CXCR3 ligands like CXCL9, 10, and 11; however, the mechanisms of inflammation in ICI-AIN are not well-understood. MethodsWe applied a sub-cellular spatial transcriptomics platform (Xenium Prime 5K) to compare the cellular composition of kidney biopsy tissue from patients with ICI-AIN with ICI-treated patients with acute tubular necrosis (ICI-ATN). ResultsAcross 8 kidney biopsy specimens (4 with ICI-AIN, 4 with ICI-ATN), we analyzed 332,000 cells, comprising kidney parenchymal cells and infiltrating immune cells. Using a spatially-aware cellular neighborhood-based classification, we identified cellular niches corresponding to each part of the nephron, in addition to unique fibrotic and inflammatory niches. Gene pathway analysis identified interferon-gamma (IFN-{gamma})/STAT1 signaling as strongly increased in ICI-AIN compared to ICI-ATN. While all inflammatory niches were overrepresented in ICI-AIN, CD8+ T cell infiltration and proinflammatory myeloid cells were the dominant immune niches. Spatial niche crosstalk analysis revealed that CD8+ T cell-derived IFN-{gamma} likely induced a proinflammatory program in myeloid cells, with increased production of CXCL9, 10, and 11. Furthermore, IFN-{gamma} signaling in ICI-AIN was associated with reduced oxidative phosphorylation in kidney tubular niches. ConclusionsSpatial transcriptomics reveal novel insights into key differences in the pathophysiology of ICI-AIN versus ICI-ATN. IFN-{gamma}-producing CD8+ T cells are likely key drivers of ICI-AIN and should be investigated as future therapeutic targets. Translational StatementSpatial transcriptomics may provide insight into differences in the cellular and spatial composition of immune checkpoint inhibitor-associated acute interstitial nephritis (ICI-AIN) and ICI-associated acute tubular necrosis (ICI-ATN). Using the novel Xenium 5K platform, we demonstrate that IFN-{gamma}-producing CD8+ T cells are central to the pathogenesis of ICI-AIN, and that CD8+ T cell-derived IFN-{gamma} likely induces a proinflammatory state in myeloid cells, with increased tissue production of CXCL9, 10, and 11. We then show that a reduction in oxidative phosphorylation and an IFN-{gamma}-driven influx of proinflammatory myeloid cells may further drive kidney damage in ICI-AIN. Many of these pathways represent potential druggable targets, and our findings may therefore inform future therapeutic approaches for ICI-AIN.

immunology↗

bioRxiv2024

A Deep Learning-Based Segmentation of Cells and Analysis (DL-SCAN)

With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to study cellular properties and signaling in living cells and tissues. Traditionally, microscopy image analysis heavily relies on manufacturer-supplied software, which often demands extensive training and lacks automation capabilities for handling diverse datasets. A critical challenge arises, if fluorophores employed exhibit low brightness and low Signal-to-Noise ratio (SNR). As a consequence, manual intervention may become a necessity, introducing variability in the analysis outcomes even for identical samples when analyzed by different users. This leads to the incorporation of blinded analysis which ensures that the outcome is free from user bias to a certain extent but is extremely time-consuming. To overcome these issues, we have developed a tool called DL-SCAN that automatically segments and analyzes fluorophore-stained regions of interest such as cell bodies in fluorescence microscopy images using a Deep Learning algorithm called Stardist. We demonstrate the programs ability to automate cell identification and study cellular ion dynamics using synthetic image stacks with varying SNR. This is followed by its application to experimental Na+ and Ca2+ imaging data from neurons and astrocytes in mouse brain tissue slices exposed to transient chemical ischemia. The results from DL-SCAN are consistent, reproducible, and free from user bias, allowing efficient and rapid analysis of experimental data in an objective manner. The open-source nature of the tool also provides room for modification and extension to analyze other forms of microscopy images specific to the dynamics of different ions in other cell types. Statement of SignificanceFluorescence microscopy is widely used to study the functional and morphological features of living cells. However, various factors, such as low SNR, background noise, drift in the signal, movement of the tissue, and the large size of the resulting imaging data, make the processing of fluorescence microscopy data prone to errors, user bias, and extremely time-consuming. These and other issues hinder the full utilization of these powerful experimental techniques. Our novel Deep Learning-based tool overcomes these issues by processing and analyzing fluorescence imaging data, e.g., enabling automated visualization of ion changes in living cells in brain slices. Yet the tool remains easy to use with a streamlined workflow.

neuroscience↗

bioRxiv2024

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimers disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions--middle temporal gyrus, superior frontal gyrus, and entorhinal cortex--we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, indicating that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, highlighting the differential impact of DEGs on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we note an overall downregulation of both astrocyte and microglia modules in AD across all brain regions, suggesting a prevailing trend of functional repression in glial cells across these regions. Notable genes, including those of the CALM and HSP90 family genes emerged as hub genes across neuronal modules in all brain regions, indicating conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems oriented approach combining pathway and network analysis for a comprehensive understanding of the cell-type-specific roles of genes in AD-related biological processes.

genomics↗

bioRxiv2023

Divergent patterns of healthy aging across human brain regions at single-cell resolution reveal links to neurodegenerative disease

Given that age is a significant risk factor for multiple neurodegenerative diseases, investigating normal brain aging may help identify molecular events that may contribute to increased disease risk over time. Single-nucleus RNA sequencing (snRNA-seq) enables analysis of gene expression changes within specific cell-types, potentially offering insights into the molecular mechanisms underlying aging. However, most brain snRNA-Seq datasets used age-matched controls from studies focused on pathological processes and have largely been limited to cortical regions. Therefore, there is a need to investigate the non-pathological aging process in brain regions that are vulnerable to age-related diseases. Here, we report a snRNA-seq study of 6 young (20-30 years) and 7 aged (60-85 years) encompassing four different brain regions: the entorhinal cortex, middle temporal gyrus, subventricular zone, and putamen. We captured over 150,000 nuclei that represented 10 broad cell-types. While we did not find statistically significant differences in cell-type proportions with age, region- and cell-type-specific differential expression analyses identified over 8,000 age-associated genes. Notably, within a given cell-type, most of these associations were region-specific. Functional enrichment analyses of the gene sets for each cell-type-region combination revealed diverse biological processes, including multiple hallmarks of aging, such as proteostasis, interactions with cytokines, vesicular trafficking, metabolism, inflammation, and metal ion homeostasis. Overall, our findings suggest that unique cell-types exhibit distinct transcriptional aging profiles both at the cell-type level and across different brain regions.

neuroscience↗

bioRxiv2022

Modeling the kinetics of amyloid beta pores and long-term evolution of their Ca2+ toxicity

The formation of cation-permeable pores due to amyloid beta (A{beta}) in the plasma membrane (PM) and membranes of intracellular organelles has been shown to cause disruption of Ca2+ homeostasis in Alzheimers disease, leading to neuronal malfunction and degeneration. However, detailed information about the formation, function, and time-evolution of A{beta} pores are still lacking. Here we present a comprehensive analysis to show that the Ca2+ toxicity of PM pores formed by A{beta}42 progressively increases over the duration of the experiments that last for more than an hour. This mainly results from a progressively increasing number of pores and activity of individual pores having higher open probability (Po) and Ca2+ conductance. To gain deeper insight into the function and evolution of A{beta}42 pores and establish their role in Ca2+ toxicity beyond experimental times scales, we developed a data-driven computational model that not only mimics the kinetics of these pores at a given time but also tracks their time-evolution over many hours. Our model suggests that the rising toxicity of A{beta}42 pores over time is a combined result of the large number of short-lived pores with low Ca2+ conductance and long-lived higher-conductance pores but fewer in number. Analysis and modeling of the voltage-dependent data show that A{beta}42 pores are most active when the cells membrane potential is near resting values, making the cell at rest especially more prone to Ca2+ disruptions.

cell biology↗

bioRxiv2022

Aβ42 and Aβ40 oligomers form transient and persistent pores with different time evolutions and toxicities

In Alzheimers disease (AD), formation of harmful self-gating pores formed by the insertion of amyloid beta oligomers (A{beta}Os) into the plasma membrane have been shown to cause disruption of Ca2+ homeostasis, leading to neuronal malfunctioning and degeneration. Among different isoforms, the most studied A{beta}40 and A{beta}42 are also believed to be the most toxic ones. Using single channel imaging, we show that both isoforms can form functionally distinct populations of Ca2+ permeable pores, we named transient and persistent pores. The transient pores could be seen only for a few tens of milliseconds, while persistent pores can be observed for more than an hour. However, while the Ca2+-toxicity of pores formed by A{beta}42Os tend to increase over time by displaying higher open probability and larger Ca2+ permeability, pores formed by A{beta}40Os show opposite time dependent behavior. We conclude that although both isoforms can form Ca2+ permeable pores in the cells plasma membrane, pores due to A{beta}42Os display worsening Ca2+ toxicity over time.

cell biology↗

bioRxiv2022

Upregulated Ca2+ release from the endoplasmic reticulum leads to impaired presynaptic function in Alzheimer's disease

Neurotransmitter release from presynaptic terminals is primarily regulated by rapid Ca2+ influx through membrane-resident voltage-gated Ca2+ channels (VGCCs). Also, accumulating evidence indicates that the endoplasmic reticulum (ER) is extensively present in axonal terminals of neurons and plays a modulatory role in synaptic transmission by regulating Ca2+ levels. Alzheimers disease (AD) is marked by enhanced Ca2+ release from the ER and downregulation of Ca2+ buffering proteins. However, the precise consequence of impaired Ca2+ signalling within the vicinity of VGCCs (active zone (AZ)) on exocytosis is poorly understood. Here, we perform in-silico experiments of intracellular Ca2+ signalling and exocytosis in a detailed biophysical model of hippocampal synapses to investigate the effect of aberrant Ca2+ signalling on neurotransmitter release in AD. Our model predicts that enhanced Ca2+ release from the ER increases the probability of neurotransmitter release in AD. Moreover, over very short timescales (30-60 msec), the model exhibits activity-dependent and enhanced short-term plasticity in AD, indicating neuronal hyperactivity--a hallmark of the disease. Similar to previous observations in AD animal models, our model reveals that during prolonged stimulation (~450 msec), pathological Ca2+ signalling increases depression and desynchronization with stimulus, causing affected synapses to operate unreliably. Overall, our work provides direct evidence in support of a crucial role played by altered Ca2+ homeostasis mediated by intracellular stores in AD.

neuroscience↗

bioRxiv2018

CellSpecks: A Software for Automated Detection and Analysis of Calcium Channels in Live Cells

To couple the fidelity of patch-clamp recording with a more high-throughput screening capability, we pioneered a novel approach to single channel recording that we named \"optical patch clamp\". By using highly-sensitive fluorescent Ca2+ indicator dyes in conjunction with total internal fluorescence microscopy techniques, we monitor Ca2+ flux through individual Ca2+-permeable channels. This approach provides information about channel gating analogous to patch-clamp recording at time resolution of ~ 2 ms, with the additional advantage of being massively parallel, providing simultaneous and independent recording from thousands of channels in native environment. However, manual analysis of the data generated by this technique presents severe challenges as a video recording can include many thousands of frames. To overcome this bottleneck, we developed an image processing and analysis framework called CellSpecks, capable of detecting and fully analyzing the kinetics of ion channels within a video sequence. By using a randomly generated synthetic data, we tested the ability of CellSpecks to rapidly and efficiently detect and analyze the activity of thousands of ion channels, including openings for a few milliseconds. Here, we report the use of CellSpecks for the analysis of experimental data acquired by imaging muscle nicotinic acetylcholine receptors and the Alzheimers disease-associated amyloid beta pores with multiconductance levels in the plasma membrane of Xenopus laevis oocytes. We show that CellSpecks can accurately and efficiently generate location maps, create raw and processed fluorescence time-traces, histograms of mean open times, mean close times, open probabilities, durations, and maximum amplitudes, and a channel chip showing the activity of all channels as a function of time. Although we specifically illustrate the application of CellSpecks for analyzing data from Ca2+ channels, it can be easily customized to analyze other spatially and temporally localized signals.

bioinformatics↗

bioRxiv2018

TraceSpecks: a software for automated idealization of noisy patch-clamp and imaging data

Experimental records of single molecules or ion channels from fluorescence microscopy and patch-clamp electrophysiology often include high-frequency noise and baseline fluctuations that are not generated by the system under investigation and have to be removed. More-over, multiple channels or conductance levels can be present at a time in the data that need to be quantified to accurately understand the behavior of the system. Manual procedures for removing these fluctuations and extracting conducting states or multiple channels are laborious, prone to subjective bias, and hinder the processing of often very large data-sets. We introduce a maximum likelihood formalism for separating signal from a noisy and drifting background such as fluorescence traces from imaging of elementary Ca2+ release events called puffs arising from clusters of channels and patch-clamp recordings of ion channels. Parameters such as the number of open channels or conducting states, noise level, and back-ground signal can all be optimized using the expectation-maximization (EM) algorithm. We implement our algorithm following the Baum-Welch approach to EM in the portable java language with a user-friendly graphical interface and test the algorithm on both synthetic and experimental data from patch-clamp electrophysiology of Ca2+ channels and fluorescence microscopy of a cluster of Ca2+ channels and Ca2+ channels with multiple conductance levels. The resulting software is accurate, fast, and provides detailed information usually not available through manual analysis. Options for visual inspection of the raw and processed data with key parameters, and exporting a range of statistics such as the mean open probabilities, mean open times, mean close times, and dwell time distributions for different number of channels open or conductance levels, amplitude distribution of all opening events, and number of transitions between different number of open channels or conducting levels in asci format with a single click are provided.

bioinformatics↗