Biology subjects

Lam, N.

Publications and source records attributed to Lam, N..

8 recordsLinked to original sources

bioRxiv2025

A CRISPR-CAS9 high throughput machine-learning platform for modulation of genes involved in Parkinson's disease-associated PINK1-mitophagy in iPSC-derived dopaminergic neurons

Parkinsons disease (PD) is a progressive neurodegenerative disorder characterised by the loss of dopaminergic neurons, driven by complex molecular mechanisms that are not fully understood. To address this issue, we have developed a novel high-content phenotypic screening platform using human induced pluripotent stem cell-derived dopaminergic neurons to investigate the PINK1-PARKIN mitophagy pathway, a critical process in PD pathogenesis. Utilising high throughput, 384 well arrayed CRISPR-CAS9 genetic manipulation and high-content immunofluorescence imaging complemented with machine learning analysis, we examined ubiquitin (Ub) pSer65 levels. Ub pSer65, a potential PD clinical biomarker, is a key marker of mitophagy initiation in dopaminergic neurons upon mitophagy initiation using exogenous stimuli to mimic the disease relevant environment. The CRISPR-CAS9 knockout (KO) screen revealed two distinct phenotypic classes: essential genes causing cell death upon deletion, and genes modulating Ub pSer65 levels. Notably, KO of PINK1, PARKIN, and TOM7 genes decreased Ub pSer65 upregulation during mitophagy activation, confirming their established roles in the pathway and validating the suitability of the platform for target identification. This innovative platform provides a precise tool to further interrogate PD-associated genes, offering insights into mitophagy-related pathogenic mechanisms and identification of potential therapeutic targets. By bridging functional genomics with disease-specific neuronal models, this approach presents a promising strategy for advancing PD research and developing targeted interventions. To our knowledge, this is the first reported use of a human, translationally relevant cell model to study genetic perturbation within a disease relevant phenotype.

neuroscience↗

bioRxiv2024

Sleep defined by arousal threshold reveals decreases in corticocortical functional correlations independently from the conventional sleep stages

Reports of sleep-specific brain activity patterns have been constrained by assessing brain function as it related to the conventional polysomnographic sleep stages. This limits the variety of sleep states and underlying activity patterns that one can discover. The current study used all-night functional MRI sleep data and defined sleep behaviorally with auditory arousal threshold (AAT) to characterize sleep depth better by searching for novel neural markers of sleep depth that are neuroanatomically localized and temporally unrelated to the conventional stages. Functional correlation values calculated in a four-min time window immediately before the determination of AAT were entered into a linear mixed effects model, allowing multiple arousals across the night per subject into the analysis, and compared to models with sleep stage to determine the unique relationships with AAT. These unique relationships were for thalamocerebellar correlations, the relationship between the right language network and the right "default-mode network dorsal medial prefrontal cortex subsystem," and the relationship between thalamus and ventral attention network. These novel neural markers of sleep depth would have remained undiscovered if the data were merely analyzed with the conventional sleep stages. Significance StatementThe original classification of sleep into distinct stages used behavioral characteristics. With the proliferation of new techniques, the first experiments might have been to perform correlations with arousal threshold. These experiments have never been performed, either with functional MRI or with any other modern technique. The amount of communication between brain regions as measured by all-night functional magnetic resonance imaging was correlated with arousal threshold. This revealed novel neural markers of sleep depth that would have remained undiscovered if the data were merely analyzed with the conventional stages. This expands our understanding of sleep and its functions beyond the constraints imposed by the conventional stages.

neuroscience↗

bioRxiv2021

Angiocrine IGFBP3 Spatially Coordinates IGF Signaling During Neonatal Cardiac Regeneration

To identify non-cell-autonomous effectors of cardiomyocyte mitosis, we analyzed a transcriptomic screen of regenerating and non-regenerating neonatal hearts for differentially-expressed secreted proteins - which we hypothesized could include candidate mitogens. We identified and validated IGFBP3, which has a Janus-like stabilizing and sequestering effect on IGF growth factors, as a neonatal injury-associated secreted protein. IGFBP3 is expressed by and secreted from vascular cells in the neonatal heart after cardiac injury, notably in the infarct border zone. We found that global deletion of IGFBP3 blunted neonatal regeneration, while gain-of-function experiments using recombinant IGFBP3 and a transgenic mouse model uncovered a pro-mitotic effect of IGFBP3 on cardiomyocytes in vitro and in the adult heart. We show that site-specific expression of an IGFBP3 protease (PAPP-A2) and its inhibitor (STC2) coordinate the spatial release of IGF2 in the infarct zone to regio-selectively activate the INSR-ERK-AKT cell growth pathways in cardiomyocytes. Collectively, our work highlights the spatiotemporal orchestration of endothelial-cardiomyocyte interactions that are required for neonatal cardiac regeneration.

cell biology↗

bioRxiv2021

Influence of age on functional memory T cell diversity

Memory T cells exhibit considerable diversity that determines their ability to be protective and their durability. Here, we examined whether changes in T cell heterogeneity contribute to the age-associated failure of immune memory. By screening for age-dependent T cell surface markers, we have identified CD4 and CD8 memory T cell subsets that are unrelated to previously defined subsets of central and effector memory cells. Memory T cells expressing the ecto-5-nucleotidase CD73 constitute a functionally distinct subset of memory T cells that declines with age. They exhibit many features favorable for immune protection, including longevity and polyfunctionality. They have a low turnover, but are poised to display effector functions and to develop into cells resembling tissue-resident memory T cells (TRM). Upstream regulators of differential chromatin accessibility and transcriptomes include transcription factors that are characteristic for conferring these superior memory features as well as facilitating CD73 expression. CD73 is not just a surrogate marker of these regulatory networks but is directly involved in T cell survival and TRM differentiation Interventions preventing the decline of this T cell subset or increasing CD73 expression have the potential to improve immune memory in older adults.

immunology↗

bioRxiv2020

Adducin Regulates Sarcomere Disassembly During Cardiomyocyte Mitosis

Recent interest in understanding cardiomyocyte cell-cycle has been driven by potential therapeutic applications in cardiomyopathy. However, despite recent advances, cardiomyocyte mitosis remains a poorly understood process. For example, it is unclear how sarcomeres are disassembled during mitosis to allow abscission of daughter cardiomyocytes. Here we identify adducin as a regulator of sarcomere disassembly during mammalian cardiomyocyte mitosis. /{gamma}-adducins are selectively expressed in neonatal mitotic cardiomyocytes, and their levels decline precipitously thereafter. Cardiomyocyte-specific overexpression of various splice isoforms and phosphoforms of -adducin in-vitro and in-vivo identified Thr445/Thr480 phosphorylation of a short isoform of adducin as a potent inducer of neonatal cardiomyocyte sarcomere disassembly. Concomitant overexpression of this -adducin variant along with {gamma}-adducin resulted in stabilization of the adducin complex and persistent sarcomere disassembly in adult mice, which is mediated by interaction with -actinin. These results highlight an important mechanism for coordination of cytoskeletal morphological changes during cardiomyocyte mitosis.

cell biology↗

bioRxiv2020

An autoimmune disease risk variant has a trans master regulatory effect mediated by IRF1 under immune stimulation

Functional mechanisms remain unknown for most genetic loci associated to complex human traits and diseases. In this study, we first mapped trans-eQTLs in a data set of primary monocytes stimulated with LPS, and discovered that a risk variant for autoimmune disease, rs17622517 in an intron of C5ORF56, affects the expression of the transcription factor IRF1 20 kb away. The cis-regulatory effect on IRF1 is active under early immune stimulus, with a large number of trans-eQTL effects across the genome under late LPS response. Using CRISPRi silencing, we showed that the SNP locus indeed functions as an IRF1 enhancer with widespread transcriptional effects. Genome editing by CRISPR further indicated that rs17622517 is indeed a causal variant in this locus, and recapitulated the LPS-specific trans-eQTL signal. Our results suggest that this common genetic variant affects inter-individual response to immune stimuli via regulation of IRF1. For this autoimmune GWAS locus, our work provides evidence of the causal variant, demonstrates a condition-specific enhancer effect, identifies IRF1 as the likely causal gene in cis, and indicates that overactivation of the downstream immune-related pathway may be the cellular mechanism increasing disease risk. This work not only provides rare experimental validation of a master-regulatory trans-eQTL, but also demonstrates the power of eQTL mapping to build mechanistic hypotheses amenable for experimental follow-up using the CRISPR toolkit.

genomics↗

bioRxiv2019

Supramodal sentence processing in the human brain: fMRI evidence for the influence of syntactic complexity in more than 200 participants

This study investigated two questions. One is to which degree sentence processing beyond single words is independent of the input modality (speech vs. reading). The second question is which parts of the network recruited by both modalities is sensitive to syntactic complexity. These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere fronto-temporoparietal network was found to be supramodal in nature, i.e. independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior middle temporal gyrus (LaMTG) showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior and posterior MTG and left inferior parietal lobe (LIPL) all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.

neuroscience↗

bioRxiv2017

Frequency-specific directed interactions in the human brain network for language

The brains remarkable capacity for language requires bidirectional interactions between functionally specialized brain regions. We used magnetoencephalography to investigate interregional interactions in the brain network for language, while 102 participants were reading sentences. Using Granger causality analysis, we identified inferior frontal cortex and anterior temporal regions to receive widespread input, and middle temporal regions to send widespread output. This fits well with the notion that these regions play a central role in language processing. Characterization of the functional topology of this network, using data-driven matrix factorization, which allowed for partitioning into a set of subnetworks, revealed directed connections at distinct frequencies of interaction. Connections originating from temporal regions peaked at alpha frequency, whereas connections originating from frontal and parietal regions peaked at beta frequency. These findings indicate that processing different types of linguistic information may depend on the contributions of distinct brain rhythms.\n\nOne Sentence SummaryCommunication between language relevant areas in the brain is supported by rhythmic synchronization, where different rhythms reflect the direction of information flow.

neuroscience↗