Biology subjects

Chawla, S.

Publications and source records attributed to Chawla, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Determining organ size through growth rate dependent negative feedback without sensing size.

Drosophila imaginal discs are the favoured system to study organ size determination. The intrinsic mechanism of organ size determination remains elusive despite decades of research into the cellular nature, mechanics and genetics of growth in the wing imaginal discs. Here we propose a new model whose basis is growth rate dependent-negative feedback without size being sensed. We show that alterations in size before the growth period are not corrected for, but alterations in growth rate during the start of the growth period induce size-restoring feedback.

developmental biology↗

bioRxiv2026

scDiagnostics: systematic assessment of cell type annotation in single-cell transcriptomics data

Although cell type annotation has become an integral part of single-cell analysis workflows, the assessment of computational annotations remains challenging. Many annotation tools transfer labels from an annotated reference dataset to a new query dataset of interest, but blindly transferring labels from one dataset to another has its own set of challenges. Often enough there is no perfect alignment between datasets, especially when transferring annotations from a healthy reference atlas for the discovery of disease states. We present scDiagnostics, a new open-source software package that facilitates the detection of complex or ambiguous annotation cases that may otherwise go unnoticed, thus addressing a critical unmet need in current single-cell analysis workflows. scDiagnostics is equipped with novel diagnostic methods that are compatible with all major cell type annotation tools. We demonstrate that scDiagnostics reliably detects complex or conflicting annotations using both carefully designed simulated datasets and diverse real-world single-cell datasets. Our evaluation demonstrates that scDiagnostics reliably identifies misleading annotations that systematically distort downstream analysis and interpretation and that would otherwise remain undetected. The scDiagnostics R package is available from Bioconductor (https://bioconductor.org/packages/scDiagnostics).

bioinformatics↗

bioRxiv2025

Spatial profiling of central nervous system cellular markers in murine breast cancer to brain metastases

BackgroundBrain metastasis occurs in approximately 16% of metastatic breast cancer patients, and incidence is increasing. Patients with breast cancer brain metastases frequently develop neurological problems including cognitive impairments and seizures. We previously demonstrated accumulation of activated microglia around the tumour site in a breast cancer brain metastasis model, which co-localised with spontaneously occurring local field potential events that resembled interictal epileptic discharges. However, the mechanisms underlying these spatially restricted effects on neuronal excitability are poorly understood. MethodsTo better understand the underlying cellular changes and potential mechanisms, we used digital spatial profiling of brain cell subtype-specific markers to chart the spatial organisation of neurons, oligodendrocytes, astrocytes, and microglia in relation to metastatic lesion site. We developed a novel chordline-based approach to analyse these spatial changes in biomarker distribution. ResultsSeveral protein markers associated with proliferation (Ki67), astrocytes (GFAP) and microglia (CD11b, IBA1, CD45, MSR1) were upregulated in the tumour compared to healthy contralateral brain parenchyma. In contrast, some neuroglial markers (MAP2, Neurofilament light, NeuN, S100B and TMEM119) were lower in the lesion compared to normal tissue. ConclusionsOverall, the protein marker changes in the lesion are indicative of neuronal cell loss and changes in the immune microenvironment of the metastatic lesion involving activated microglia, astrocytes and recruitment of peripheral immune cells. Such cellular changes may contribute to the changes in electrical activity resulting from brain metastases observed in mice and patients.

neuroscience↗

bioRxiv2024

Cortical layer-specific and cell type-specific dendritic expression of Arc (Arg 3.1) in an in vitro model of slow-wave sleep

An abundance of evidence shows sleep homeostatically regulates synaptic plasticity and memory consolidation but the underlying molecular regulators of this important function of sleep have been difficult to directly elucidate. Arc is an immediate early gene that has a fundamental role in several aspects of synaptic plasticity including regulation and maintenance. Using a physiological brain slice model of slow-wave sleep, here we show that Arc protein has a characteristic spatial and cell-type specific distribution during persistent sleep-related delta oscillations in neocortical slices, which may correlate with aspects of sleep-dependent regulation of synaptic plasticity in cortical regions. In delta oscillating slices, Arc is highly expressed in layer 2/3 dendrites of the primary and secondary association cortex and this dendritic localisation is specific to intrinsically bursting cells (IB) whose cell bodies are in layer 5. Moreover, Arc immunopositive dendrites are clustered together arranged in a quasi hexagonal arrangement with a spacing of [~] 50 {micro}m between clusters. The cytoarchitectural distribution of Arc across the association cortex has implications for the mechanisms of sleep and for the synaptic homeostasis hypothesis regarding the function of sleep.

neuroscience↗

bioRxiv2024

The rhythmic transcriptional landscape in Caenorhabditis elegans: daily, circadian and novel 16-hour cycling gene expression revealed by RNA-sequencing

The nematode Caenorhabditis elegans is an unconventional model in chronobiology, reported to exhibit physiological and behavioural circadian rhythms while lacking a defined transcriptional oscillator. The extent and importance of circadian rhythms in C. elegans remain uncertain, given a probable lack of functional conservation of key circadian proteins, relatively non-robust reported rhythms and an ambiguous diel ecology. Here, we investigated the temporal coordination of gene expression in C. elegans post-development using RNA sequencing. Over a circadian time series, in which we synchronised nematodes to combined light and temperature cycles, we found clear evidence of daily oscillations in 343 genes using JTK_Cycle. However, rhythms were not well-sustained in constant conditions, with only 13 genes remaining significantly rhythmic. Reanalysis of previous transcriptomic data echoed this finding in identifying far fewer rhythmic genes in constant conditions, while also identifying a greater number of rhythmic genes overall. Weighted gene co-expression network analysis (WGCNA), a hierarchical clustering approach, further confirmed prevalent environmentally driven daily oscillations in the RNA-seq data. This analysis additionally revealed a novel co-expression trend in which over 1000 genes exhibited hitherto unreported 16-hour oscillations, highlighting a new facet of temporal gene expression coordination in C. elegans.

physiology↗

bioRxiv2023

Spatial and temporal profiling of the complement system uncovered novel functions of the alternative complement pathway in brain development

Mounting evidence implicated the classical complement pathway (CP) in normal brain development, and the pathogenesis of neuropsychiatric and neurodegenerative diseases. However the source and regulation of complement in the brain remain unclear. Using MERFISH, a spatial transcriptomic method with single-cell resolution, we established a developmental brain atlas of the complement system. We showed that the brain synthesizes essential building blocks of the complement system locally with remarkable cellular and spatial heterogeneity. We provided transcriptional evidence supporting the presence of the alternative pathway (AP), but lack of lectin pathway (LP) activity in postnatal brain development. Cell type, temporal and spatial expression patterns of genes involved indicate non-redundant functions of the CP and AP. In addition, deficiency in Masp3-driven AP resulted in developmental and cognitive defects, indicating essential functions of the AP, an observation that highlights the necessity to disentangle differential involvement of the three complement activation pathways in development and diseases.

neuroscience↗

bioRxiv2023

An Nav1.5-dependent feedback mechanism driving glycolytic acidification in breast cancer metastasis

Solid tumours have abnormally high intracellular [Na+]. The activity of various Na+ channels may underlie this Na+ accumulation. Voltage-gated Na+ channels (VGSCs) have been shown to be functionally active in cancer cell lines, where they promote invasion. However, the mechanisms involved, and clinical relevance, are incompletely understood. Here, we show that protein expression of the Nav1.5 VGSC subtype strongly correlates with increased metastasis and shortened cancer-specific survival in breast cancer patients. In addition, VGSCs are functionally active in patient-derived breast tumour cells, cell lines, and cancer-associated fibroblasts. Knock down of Nav1.5 in a mouse model of breast cancer suppresses expression of invasion-regulating genes. Nav1.5 activity increases glycolysis in breast cancer cells, likely by up-regulating activity of the Na+/K+ ATPase, thus promoting H+ production and extracellular acidification. The pH of murine xenograft tumours is lower at the periphery than in the core, in regions of higher proliferation and lower apoptosis. In turn, acidic extracellular pH elevates persistent Na+ influx through Nav1.5 into breast cancer cells. Together, these findings show positive feedback between extracellular acidification and movement of Na+ into cancer cells which can facilitate invasion. These results highlight the clinical significance of Nav1.5 activity as a potentiator of breast cancer metastasis and provide further evidence supporting the use of VGSC inhibitors in cancer treatment.

cancer biology↗

bioRxiv2023

Identification of GEFs and GAPS modulating phosphorylation and abundance of Rab10 by LRRK2-G2019S in neurons

The Parkinson s Disease associated kinase LRRK2 is proposed to act through phosphorylation of Rab proteins, most notably Rab10. All Rabs participate in a GTPase cycle, in which GEFs (Guanine nucleotide exchange factors) promote membrane binding, and GAPs (GTPase-activating proteins) promote release into the cytoplasm. LRRK2 is proposed to phosphorylate membrane bound Rab10. The hypothesis is that phosphoRab10 is less sensitive to GAP action and may remain membrane bound. To test how LRRK2 and Rab10 function in the GTPase cycle, we used an immunoblotting strategy in fly brains to show that a putative GEF Crag/DENND4C and three possible GAPs (pollux (plx), GAPcenA and Evi5, orthologs of AS160) interact with LRRK2 controlling the phosphorylation and abundance of Rab10. Crag behaves similarly to a Rab10 GEF and additionally modulates the level of panRab10. Only plx acts as a conventional GAP. GAPcenA seems to act as a GAP for phosphoRab10 more than panRab10. It is likely that Evi5 acts as a GAP for another Rab, possibly Rab11.

neuroscience↗

bioRxiv2023

Dynamic calcium-mediated stress response and recovery signatures in the fungal pathogen, Candida albicans

Calcium (Ca2+) is an important second messenger for activating stress response signalling and cell adaptation in eukaryotic cells yet intracellular Ca2+-dynamics in fungi is poorly understood due to lack of effective real-time Ca2+ reporters. We engineered the GCaMP6f construct for use in the fungal pathogen, Candida albicans, and used live-cell imaging to observe dynamic Ca2+ spiking as well as slower changes in ambient Ca2+-GCaMP levels elicited by stress or gene deletion. Short-term exposure to membrane, osmotic or oxidative stress generated immediate stress-specific responses and repeated exposure revealed differential recovery signatures. Osmotic stress caused yeast cell shrinkage and no adaptation response, where Ca2+-GCaMP spiking was inhibited by 1 M NaCl but not by 0.66 M CaCl2. Treatment with SDS caused a spike-burst, raised ambient Ca2+-GCaMP levels and significant cell death, but surviving cells adapted over subsequent exposures. Treatment with 5 mM H2O2 abolished spiking and caused transient autofluorescence but cells adapted such that spiking returned and autofluorescence diminished on repeated exposure. Adaptation to H2O2 was dependent on Cap1, extracellular Ca2+ and calcineurin, but not on its downstream target, Crz1. Ca2+-dynamics were not affected by H2O2 in the hog1{Delta} or yvc1{Delta} mutants, suggesting a pre-adapted, resistant state, possibly due to changes in membrane permeability. Live-cell imaging of Ca2+-GCaMP responses in individual cells has therefore revealed the dynamics of Ca2+-influx, signalling and homeostasis and their role in the temporal stress response signatures of C. albicans.

microbiology↗

bioRxiv2022

Latent representation of single-cell transcriptomes enables algebraic operations on cellular phenotypes

Single-cell RNA-sequencing (scRNA-seq) coupled with robust computational analysis facilitates the characterization of phenotypic heterogeneity within tumors. Current scRNA-seq analysis pipelines are capable of identifying a myriad of malignant and non-malignant cell subtypes from single-cell profiling of tumors. However, given the extent of intra-tumoral heterogeneity, it is challenging to assess the risk associated with individual cell subpopulations, primarily due to the complexity of the cancer phenotype space and the lack of clinical annotations associated with tumor scRNA-seq studies. To this end, we introduce SCellBOW, a scRNA-seq analysis framework inspired by document embedding techniques from the domain of Natural Language Processing (NLP). SCellBOW is a novel computational approach that facilitates effective identification and high-quality visualization of single-cell subpopulations. We compared SCellBOW with existing best practice methods for its ability to precisely represent phenotypically divergent cell types across multiple scRNA-seq datasets, including our in-house generated human splenocyte and matched peripheral blood mononuclear cell (PBMC) dataset. For tumor cells, SCellBOW estimates the relative risk associated with each cluster and stratifies them based on their aggressiveness. This is achieved by simulating how the presence or absence of a specific cell subpopulation influences disease prognosis. Using SCellBOW, we identified a hitherto unknown and pervasive AR-/NElow (androgen-receptor-negative, neuroendocrine-low) malignant subpopulation in metastatic prostate cancer with conspicuously high aggressiveness. Overall, the risk-stratification capabilities of SCellBOW hold promise for formulating tailored therapeutic interventions by identifying clinically relevant tumor subpopulations and their impact on prognosis.

bioinformatics↗

bioRxiv2022

Sodium regulates PLC and IP3R-mediated calcium signalling in invasive breast cancer cells

Intracellular Ca2+ signalling and Na+ homeostasis are inextricably linked via ion channels and co-transporters, with alterations in the concentration of one ion having profound effects on the other. Evidence indicates that intracellular Na+ concentration ([Na+]i) is elevated in breast tumours, and that aberrant Ca2+ signalling regulates numerous key cancer hallmark processes. The present study therefore aimed to determine the effects of Na+ depletion on intracellular Ca2+ handling in metastatic breast cancer cell lines. The relationship between Na+ and Ca2+ was probed using fura-2 and SBFI fluorescence imaging and replacement of extracellular Na+ with equimolar N-methyl-D-glucamine (0Na+/NMDG) or choline chloride (0Na+/ChoCl). In triple-negative MDA-MB-231 and MDA-MB-468 cells and Her2+ SKBR3 cells, but not ER+ MCF-7 cells, 0Na+/NMDG and 0Na+/ChoCl resulted in a slow, sustained depletion in [Na+]i that was accompanied by a rapid and sustained increase in intracellular Ca2+ concentration ([Ca2+]i). Application of La3+ in nominal Ca2+-free conditions had no effect on this response, ruling out reverse-mode NCX activity and Ca2+ entry channels. Moreover, the Na+-linked [Ca2+]i increase was independent of membrane potential hyperpolarisation (NS-1619), but was inhibited by pharmacological blockade of IP3 receptors (2-APB), phospholipase C (PLC, U73122) or following depletion of endoplasmic reticulum Ca2+ stores (cyclopiazonic acid). Thus, Na+ is linked to PLC/IP3-mediated activation of endoplasmic reticulum Ca2+ release in metastatic breast cancer cells and this may have an important role in breast tumours where [Na+]i is perturbed.

cancer biology↗

bioRxiv2022

A visual atlas of genes tissue-specific pathological roles

Dysregulation of a genes function, either due to mutations or impairments in regulatory networks, often triggers pathological states in the affected tissue. Comprehensive mapping of these apparent gene-pathology relationships is an ever daunting task, primarily due to genetic pleiotropy and lack of suitable computational approaches. With the advent of high throughput genomics platforms and community scale initiatives such as the Human Cell Landscape (HCL) project [1], researchers have been able to create gene expression portraits of healthy tissues resolved at the level of single cells. However, a similar wealth of knowledge is currently not at our finger-tip when it comes to diseases. This is because the genetic manifestation of a disease is often quite heterogeneous and is confounded by several clinical and demographic covariates. To circumvent this, we mined ~18 million PubMed abstracts published till May 2019 and selected ~6.1 million of them that describe the pathological role of genes in different diseases. Further, we employed a word embedding technique from the domain of Natural Language Processing (NLP) to learn vector representation of entities such as genes, diseases, tissues, etc., in a way such that their relationship is preserved in a vector space. Notably, Pathomap, by the virtue of its underpinning theory, also learns transitive relationships. Pathomap provided a vector representation of words indicating a possible association between DNMT3A/BCOR with CYLD cutaneous syndrome (CCS). The first manuscript reporting this finding was not part of our training data. Key pointsO_LIWe mined ~18 million PubMed abstracts to extract latent knowledge pertaining to tissue specific pathological roles of genes. C_LIO_LIWe found well-defined gene modules implicated in disease pathogenesis in anatomically proximal tissues. C_LIO_LIWe demonstrated an ahead of time discovery of the association between DNMT3A/BCOR with CYLD cutaneous syndrome (CCS), as a knowledge synthesis use-case. C_LI

bioinformatics↗

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

Gene expression based inference of drug resistance in cancer

Inter and intra-tumoral heterogeneity are major stumbling blocks in the treatment of cancer and are responsible for imparting differential drug responses in cancer patients. Recently, the availability of large-scale drug screening datasets has provided an opportunity for predicting appropriate patient-tailored therapies by employing machine learning approaches. In this study, we report a predictive modeling approach to infer treatment response in cancers using gene expression data. In particular, we demonstrate the benefits of considering integrated chemogenomics approach, utilizing the molecular drug descriptors and pathway activity information as opposed to gene expression levels. We performed extensive validation of our approach on tissue-derived single-cell and bulk expression data. Further, we constructed several prostate cancer cell lines and xenografts, exposed to differential treatment conditions to assess the predictability of the outcomes. Our approach was further assessed on pan-cancer RNA-sequencing data from The Cancer Genome Atlas (TCGA) archives, as well as an independent clinical trial study describing the treatment journey of three melanoma patients. To summarise, we benchmarked the proposed approach on cancer RNA-seq data, obtained from cell lines, xenografts, as well as humans. We concluded that pathway-activity patterns in cancer cells are reasonably indicative of drug resistance, and therefore can be leveraged in personalized treatment recommendations.

cancer biology↗

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↗

bioRxiv2021

A search-engine for single-cell epigenome profiles for multi-purpose applications

The true benefits of large datasets of the single-cell transcriptome and epigenome profiles can be availed only with their inclusion and search for annotating individual cells. Matching a single cell epigenome profile to a large pool of reference cells remains a major challenge. We developed a method (scEpiSearch) to resolve the challenges of searching and comparing single-cell open-chromatin profiles against large pools of single-cell expression and open chromatin datasets. scEpiSearch is more accurate than other methods when comparing single cell open-chromatin profiles to single-cell transcriptomes and epigenomes. scEpiSearch also provides a robust method for reference-supported co-embedding of single-cell open chromatin profiles. In performance benchmarks, scEpiSearch outperformed multiple methods for the low dimensional co-embedding of single-cell open-chromatin profiles irrespective of platforms and species. scEpiSearch works with both reference single-cell expression and epigenome profiles, enabling classification of single-cell open-chromatin profiles. Here we demonstrate the unconventional utilities of scEpiSearch by applying it on single-cell epigenome profiles of K562 cells and samples from patients with acute leukaemia to reveal different aspects of their heterogeneity, multipotent behaviour and de-differentiated states. Applying scEpiSearch on our single-cell open-chromatin profiles from embryonic stem cells(ESCs), we identified ESC subpopulations with more activity and poising for endoplasmic reticulum stress and unfolded protein response. Thus, scEpiSearch solves the non-trivial problem of amalgamating information from a large pool of single-cells to identify and study the regulatory states of cells using their single-cell epigenomes.The true benefits of large datasets of the single-cell transcriptome and epigenome profiles can be availed only with their inclusion and search for annotating individual cells.

systems biology↗

bioRxiv2021

Elevation of TRPV1 expression on T cells during experimental immunosuppression

An intracellular rise in calcium (Ca2+) is an essential requisite underlying T cell activation and its associated pro-inflammatory cytokine production. Transient receptor potential vanilloid channel (TRPV1) is a thermo-sensitive, polymodal gated and permeable to cations such as Ca2+. It has been reported that TRPV1 expression increases during T cell activation. However, the possible involvement of TRPV1 during immunosuppression of T cells has not been studied yet. Here, we investigated the possible role of TRPV1 in FK506 or B16F10-culture supernatant (B16F10-CS) driven experimental immunosuppression in T cells. Intriguingly, it was found that TRPV1 expression is further elevated during immunosuppression compared to ConA or TCR activated T cells. Similarly, in B16F10 tumor-bearing mice, the TRPV1 expression was upregulated in T cells as compared to control mice, in vivo. Moreover, we observed an immediate rise in intracellular Ca2+ levels in FK506 and B16F10-CS treated T cells as compared to ConA or TCR treated T cells. Likewise, in B16F10 tumor-bearing mice, the basal intracellular calcium level was upregulated in T cells as compared to control mice, in vivo. To further investigate the possible mechanism of such rise in intracellular Ca2+ levels, TRPV1 specific functional inhibitor, 5 -iodoresiniferatoxin (5 -IRTX) was used in calcium influx studies. It was observed that the total intracellular Ca2+ levels decreased significantly in presence of 5 -IRTX for either the FK506 or B16F10-CS as well as with ConA or TCR stimulated T cells, indicating the functional role of TRPV1 channels in FK506 or B16F10-CS mediated increase in intracellular Ca2+ levels. The current findings highlight an essential role of the TRPV1 channel in upregulating intracellular calcium levels during both immune-activation and immunosuppression. This study might also have broad implications in the context of other immune-suppressive diseases as well.

immunology↗

bioRxiv2020

Selective human tau protein expression in different clock circuits of the Drosophila brain disrupts different aspects of sleep and circadian rhythms

Circadian behavioural deficits, such as increased daytime naps and reduced night-time sleep, are common in Alzheimers disease and other tauopathies. But it has remained unclear whether these circadian abnormalities arise from tau pathology in either the master pacemaker or downstream neurons. Here we study this question by selectively expressing different human tau proteins in specific Drosophila brain circuits and monitoring locomotor activity under light-dark (LD) and in "free-running" dark-dark (DD) conditions. We show that expressing human tau proteins in the fly brain recapitulates faithfully several behavioural changes found in tauopathies. We identify discrete neuronal subpopulations within the clock network as the primary target of distinct circadian behavioural disturbances in different environmental conditions. Specifically, we show that the PDF-positive pacemaker neurons are the main site for night-activity gain and -sleep loss, whereas the non-PDF clock-neurons are the main site of reduced intrinsic behavioural rhythmicity. Bioluminescence measurements revealed that the molecular clock is intact despite the behavioural arrhythmia. Our results establish that dysfunction in both the central clock- and afferent clock-neurons jointly contribute to the circadian locomotor activity rhythm disruption in Drosophila expressing human tau. Significance StatementThis study directly links in vivo human tau protein expression in region-specific Drosophila clock-neurons with the resulting sleep and circadian rhythm deficits to extract new knowledge of how Alzheimers disease and other tauopathies perturb the balance of activity and sleep. We anticipate that this novel approach will provide a useful general template for other studies of neurodegeneration in model organisms, seeking to dissect the impact of neurodegenerative disease on circadian behaviour, and further deepening our understanding of how the clock-neuron network works.

neuroscience↗