Biology subjects

Ramalingam, N.

Publications and source records attributed to Ramalingam, N..

8 recordsLinked to original sources

bioRxiv2026

WDR44 drives de novo α-synuclein aggregation at the lysosomal membrane and promotes neuronal dysfunction in Parkinson's Disease

The aggregation of -synuclein (-SYN) into Lewy bodies (LBs) is a central event in the pathogenesis of Parkinsons disease (PD) and related synucleinopathies1,2. Despite significant advances in understanding -SYN self-assembly, the precise sequence of early aggregation steps has not been directly visualized in living neurons. Here, we use an optogenetic-induced protein aggregation system with a high temporal resolution to monitor the onset of -SYN assembly in neurons. We found that the initiation and accumulation of -SYN aggregates occur predominantly at the lysosomal membrane, an event driven by the -SYN N-terminus and modulated by the membrane-associated adaptor protein WD repeat-containing protein 44 (WDR44). Remarkably, we demonstrate that WDR44 knockdown markedly reduced de novo -SYN aggregation in both neuronal cultures and in vivo, whereas WDR44 overexpression enhances -SYN aggregation in PD patient-derived iPSC neurons. Consistent with its potential pathogenic involvement, WDR44 aberrantly accumulates in vivo and in the brains of PD patients, where it colocalizes with LB inclusions. Finally, we show that lysosome-associated -SYN aggregates compromised lysosomal structure and function, leading to neuronal impairment, a phenotype worsened by WDR44 overexpression, linking early aggregation events to downstream toxicity. Together, these findings reveal the earliest dynamic stages of -SYN oligomerization in living neurons and identify the WDR44--SYN interaction as a promising therapeutic target for reducing -SYN pathology and enabling early intervention in PD.

neuroscience↗

bioRxiv2025

Lipid droplets promote the aberrant liquid-liquid phase separation of alpha-synuclein leading to impaired energy homeostasis

Alpha-synuclein (Syn) inclusions, termed Lewy bodies, are the characteristic neuropathological feature of Parkinsons disease. Growing evidence points towards a role of aberrant liquid-liquid phase separation in the dysregulation of Syn and sequence of events that lead to the formation of Lewy bodies. However, the triggers leading to aberrant phase separation are unknown, as is the relevance of this phenomenon to the neurodegeneration process. In this study, we showed that Syn spontaneously phase separates into condensates in the presence of lipid droplets. These lipid droplet-rich condensates represent a toxic species of Syn that prevents the turnover of the entrapped lipid droplets; they are also toxic to neighbouring mitochondria which are depolarized and undergo increased mitophagy. These findings underscore the increasing importance of lipid droplets in the pathogenesis of neurodegenerative diseases, and Parkinsons disease in particular. The lipid droplets are significantly enriched within the neuromelanin in midbrain dopaminergic neurons in the substantia nigra and could therefore uniquely facilitate the early Syn-associated neurodegeneration of this region in PD. Our findings reveal a novel pathway implicated in the dysregulation of Syn that connects aberrant liquid-liquid phase separation, lipid droplets and mitochondrial toxicity.

neuroscience↗

bioRxiv2025

A Dual Assay to Compare Protein Levels and Toxicity of Alpha-Synuclein Variants: Acute Expression of Wild-Type versus S129A

Parkinsons disease (PD) affects over 12 million people worldwide and has the fastest-growing global impact. The pathological hallmark is the presence of Lewy bodies and Lewy neurites, which are intraneuronal lesions enriched in aggregated alpha-synuclein (S) that is typically hyper-phosphorylated at serine 129. Therefore, lowering phosphoserine 129 (pS129) may be a viable therapeutic strategy to treat PD. However, pS129 has also been proposed to regulate synaptic transmission and S degradation. In both cases, inhibiting pS129 could be detrimental. Here, we developed a sensitive assay in a human neuroblastoma model and utilized it to assess the relative expression levels and cytotoxicity of pS129 by comparing S wild-type (WT) vs. S129A (pS129-deficient). We show that the S129A mutant does not affect the acute expression levels or toxicity of S in a transient transfection paradigm. This provides new insight into the intricate interplay between S, phosphorylation, toxicity, and degradation. Our assay provides a versatile platform for understanding disease-relevant mechanisms and opens novel avenues for the design of future therapeutic interventions in PD and other -synucleinopathies.

cell biology↗

bioRxiv2022

Rapid iPSC inclusionopathy models shed light on formation, consequence and molecular subtype of alpha-synuclein inclusions

Intracellular inclusions accompanying neurodegeneration are histopathologically and ultrastructurally heterogeneous but the significance of this heterogeneity is unclear. iPSC models, while promising for disease modeling, do not form inclusions in a reasonable timeframe and suffer from limited tractability. Here, we developed an iPSC toolbox utilizing piggyBac-based or targeted transgenes to rapidly induce CNS cells with concomitant expression of aggregation-prone proteins. This system is amenable to screening and longitudinal tracking at single-cell and single-inclusion resolution. For proof-of-principle, cortical neuron -synuclein "inclusionopathy" models were engineered to form inclusions through exogenous seeding or -synuclein mutation. These models recapitulated known fibril- and lipid-rich inclusion subtypes, uncovering dynamic interactions between them, and refined the classification of inclusions in postmortem brain. Genetic-modifier and protein-interaction screens pinpointed proteins like RhoA whose sequestration into specific inclusion subtypes is likely to be toxic. This iPSC platform should enhance our understanding of proteinaceous pathologies in neurodegeneration and facilitate therapeutics development.

neuroscience↗

bioRxiv2021

Marker-free characterization of single live circulating tumor cell full-length transcriptomes

The identification and characterization of circulating tumor cells (CTCs) are important for gaining insights into the biology of metastatic cancers, monitoring disease progression, and medical management of the disease. The limiting factor that hinders enrichment of purified CTC populations is their sparse availability, heterogeneity, and altered phenotypic traits relative to the tumor of origin. Intensive research both at the technical and molecular fronts led to the development of assays that ease CTC detection and identification from the peripheral blood. Most CTC detection methods use a mix of size selection, immune marker based white blood cells (WBC) depletion, and positive enrichment antibodies targeting tumor-associated antigens. However, the majority of these methods either miss out on atypical CTCs or suffer from WBC contamination. Single-cell RNA sequencing (scRNA-Seq) of CTCs provides a wealth of information about their tumors of origin as well as their fate and is a potent method of enabling unbiased identification of CTCs. We present unCTC, an R package for unbiased identification and characterization of CTCs from single-cell transcriptomic data. unCTC features many standard and novel computational and statistical modules for various analysis tasks. These include a novel method of scRNA-Seq clustering, named Deep Dictionary Learning using K-means clustering cost (DDLK), expression based copy number variation (CNV) inference, and combinatorial, marker-based verification of the malignant phenotypes. DDLK enables robust segregation of CTCs and WBCs in the pathway space, as opposed to the gene expression space. We validated the utility of unCTC on scRNA-Seq profiles of breast CTCs from six patients, captured and profiled using an integrated ClearCell(R) FX and PolarisTM workflow that works by the principles of size-based separation of CTCs and marker based WBC depletion.

bioinformatics↗

bioRxiv2021

Microfluidic system-based time-course tracking of physical proximity between cells and its effect on gene expression for elucidating live single cancer-immune cell interactions

Cell-cell communication and physical interactions play a vital role in cancer initiation, homeostasis, progression, and immune response. Here, we report a system that combines live capture of different cell types, co-incubation, time-lapse imaging, and gene expression profiling of doublets using a microfluidic integrated fluidic circuit (IFC) that enables measurement of physical distances between cells and the associated transcriptional profiles due to cell-cell interactions. The temporal variations in natural killer (NK) - triple-negative breast cancer (TNBC) cell distances were tracked and compared with terminally profiled cellular transcriptomes. The results showed the time-bound activities of regulatory modules and alluded to the existence of transcriptional memory. Our experimental and bioinformatic approaches serve as a proof of concept for interrogating live cell interactions at doublet resolution, which can be applied across different cancers and cell types.

cancer biology↗

bioRxiv2019

Integrative analysis and machine learning based characterization of single circulating tumor cells

We collated publicly available single-cell expression profiles of circulating tumor cells (CTCs) and showed that CTCs across cancers lie on a near-perfect continuum of epithelial to mesenchymal (EMT) transition. Integrative analysis of CTC transcriptomes also highlighted the inverse gene expression pattern between PD-L1 and MHC, which is implicated in cancer immunotherapy. We used the CTCs expression profiles in tandem with publicly available peripheral blood mononuclear cell (PBMC) transcriptomes to train a classifier that accurately recognizes CTCs of diverse phenotype. Further, we used this classifier to validate circulating breast tumor cells captured using a newly developed microfluidic systems for label-free enrichment of CTCs.

genomics↗

bioRxiv2018

C1 CAGE detects transcription start sites and enhancer activity at single-cell resolution

Single-cell transcriptomic profiling is a powerful tool to explore cellular heterogeneity. However, most of these methods focus on the 3-end of polyadenylated transcripts and provide only a partial view of the transcriptome. We introduce C1 CAGE, a method for the detection of transcript 5-ends with an original sample multiplexing strategy in the C1 microfluidic system. We first quantified the performance of C1 CAGE and found it as accurate and sensitive as other methods in C1 system. We then used it to profile promoter and enhancer activities in the cellular response to TGF-{beta} of lung cancer cells and discovered subpopulations of cells differing in their response. We also describe enhancer RNA dynamics revealing transcriptional bursts in subsets of cells with transcripts arising from either strand within a single-cell in a mutually exclusive manner, which was validated using single molecule fluorescence in-situ hybridization.

genomics↗