Biology subjects

Loh, Y. P.

Publications and source records attributed to Loh, Y. P..

5 recordsLinked to original sources

bioRxiv2026

Two orthogonal MAP3K-driven pathways of NLRP1 inflammasome activation revealed by poisonous beetles.

Environmental toxins that cause irritant dermatitis remain poorly understood as activators of innate immune pathways. Here, we identify rove beetle (Paederus) and blister beetle (Meloidae) toxins as previously unrecognized triggers of the human NLRP1 inflammasome in keratinocytes. Rove beetles, likely through the ribosome inhibitor pederin, activate NLRP1 via translational stalling and the ZAK-dependent ribotoxic stress response. In contrast, the phosphatase inhibitor cantharidin from blister beetles induces NLRP1 through TAK1-driven hyperphosphorylation of its linker region, independent of ZAK. In their hyperactivated states, ZAK and TAK1 share overlapping phosphosites on the NLRP1 disordered linker, including a common essential TZ motif. In addition, we show that TAK1 and ZAK are jointly responsible for NLRP1 linker phosphorylation and activation caused by dsRNA and CHIKV infection. These findings reveal medically relevant insect toxins as activators of NLRP1, and uncover parallel MAP3 kinase pathways as converging upstream activating signals for the human NLRP1 inflammasome. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=172 HEIGHT=200 SRC="FIGDIR/small/701189v1_ufig1.gif" ALT="Figure 1000"> View larger version (50K): org.highwire.dtl.DTLVardef@ee34b9org.highwire.dtl.DTLVardef@c79ec9org.highwire.dtl.DTLVardef@189c373org.highwire.dtl.DTLVardef@17ec853_HPS_FORMAT_FIGEXP M_FIG C_FIG KEY POINTSTwo dermatitis-causing beetle species induce NLRP1-driven pyroptosis of human keratinocytes Rove beetles, likely via pederin, activate NLRP1 via ribosome inhibition and ZAK[a]-driven RSR Cantharidin from blister beetles activates human via TAK1-, instead of ZAK[a]-driven hyperphosphorylation of the NLRP1 linker region Shared phosphosites by TAK1 and ZAK[a] on NLRP1 contribute to dsRNA-driven NLRP1 activation

immunology↗

bioRxiv2025

Neurotrophic Factor-α1/carboxypeptidase E regulates critical protein networks to rescue neurodegeneration, defective synaptogenesis and impaired autophagy in Alzheimer's Disease mice

BackgroundThe global aging population is increasingly inflicted with Alzheimers disease (AD), but a cure is still unavailable. Neurotrophic Factor-1/carboxypeptidase E (NF-1/CPE) gene therapy has been shown to prevent and reverse memory loss and pathology AD mouse models However, the mechanisms of action of NF-1/CPE are not fully understood. We investigated if a non-enzymatic form of NF-1/CPE-E342Q is efficient in reversing AD pathology and carried out a proteomic study to uncover the mechanisms of action of NF-1/CPE in AD mice. MethodsAAV-human NF-1/CPE and a non-enzymatic form, NF-1/CPE -E342Q were delivered into hippocampus of 3xTg-AD mice and effects on cognitive function, neurodegeneration, synaptogenesis and autophagy were investigated. A quantitative proteomic analysis of hippocampus of 3xTg-AD mice with and without AAV-NF-1/CPE treatment was carried out. ResultsHippocampal delivery of AAV-NF-1/CPE-E342Q prevented memory loss, neurodegeneration and increase in activated microglia in 3xTg-AD mice, indicating its action is independent of its enzymatic activity. Quantitative proteomic analysis of hippocampus of 3xTg-AD mice that underwent NF-1/CPE gene therapy revealed differential expression of >2000 proteins involving many metabolic pathways. Of these, two new proteins down-regulated by NF-1/CPE: Nexin4 (SNX4) and Trim28 which increase A{beta} production and tau levels, respectively were identified. Western blot analysis verified that they were reduced in AAV-NF-1/CPE treated 3xTg-AD mice compared to untreated mice. Our proteomic analysis indicated synaptic organization as top signaling pathway altered as a response to CPE expression. Synaptic markers PSD95 and Synapsin1 were decreased in 3xTg-AD mice and were restored with AAV-NF-1/CPE treatment. Proteomic analysis hypothesized involvement of autophagic signaling pathway. Indeed, multiple proteins known to be markers of autophagy were down-regulated in 3xTg-AD mice, accounting for impaired autophagy. Expression of these proteins were upregulated in 3xTg-AD mice with NF-1/CPE gene therapy, thereby reversing autophagic impairment. ConclusionsThis study uncovered vast actions of NF-1/CPE in restoring expression of networks of critical proteins including those necessary for maintaining neuronal survival, synaptogenesis and autophagy, while down-regulating many proteins that promote tau and A{beta} accumulation to reverse memory loss and AD pathology in 3xTg-AD mice. AAV-NF-1/CPE gene therapy uniquely targets many metabolic levels, offering a promising holistic approach for AD treatment. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/657876v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@10e468forg.highwire.dtl.DTLVardef@3a78adorg.highwire.dtl.DTLVardef@c8d62forg.highwire.dtl.DTLVardef@165d118_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

Chromatin Interaction Neural Network (ChINN): A machine learning-based method for predicting chromatin interactions from DNA sequences

Chromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is limited. Various computational methods have been developed to predict chromatin interactions. Most of these methods rely on large collections of ChIP-Seq/RNA-Seq/DNase-Seq datasets and predict only enhancer-promoter interactions. Some of the state-of-the-art methods have poor experimental designs, leading to over-exaggerated performances and misleading conclusions. Here we developed a computational method, Chromatin Interaction Neural Network (ChINN), to predict chromatin interactions between open chromatin regions by using only DNA sequences of the interacting open chromatin regions. ChINN is able to predict CTCF-, RNA polymerase II- and HiC-associated chromatin interactions between open chromatin regions. ChINN also shows good across-sample performances and captures various sequence features that are predictive of chromatin interactions. To apply our results to clinical patient data, we applied CHINN to predict chromatin interactions in 6 chronic lymphocytic leukemia (CLL) patient samples and a cohort of open chromatin data from 84 CLL samples that was previously published. Our results demonstrated extensive heterogeneity in chromatin interactions in patient samples, and one of the sources of this heterogeneity were the different subtypes of CLL.

bioinformatics↗

bioRxiv2019

Predicting chromatin interactions between open chromatin regions from DNA sequences

Chromatin interactions play important roles in regulating gene expression. However, the availability of genome-wide chromatin interaction data is very limited. Various computational methods have been developed to predict chromatin interactions. Most of these methods rely on large collections of ChIP-Seq/RNA-Seq/DNase-Seq datasets and predict only enhancer-promoter interactions. Some of the state-of-the-art methods have poor experimental designs, leading to over-exaggerated performances and misleading conclusions. Here we developed a computational method, Chromatin Interaction Neural Network (CHINN), to predict chromatin interactions between open chromatin regions by using only DNA sequences of the interacting open chromatin regions. CHINN is able to predict CTCF- and RNA polymerase II-associated chromatin interactions between open chromatin regions. CHINN also shows good across-sample performances and captures various sequence features that are predictive of chromatin interactions. We applied CHINN to 84 chronic lymphocytic leukemia (CLL) samples and detected systematic differences in the chromatin interactome between IGVH-mutated and IGVH-unmutated CLL samples.

bioinformatics↗

bioRxiv2019

H3K27me3-rich genomic regions can function as silencers to repress gene expression via chromatin interactions

Gene repression and silencers are poorly understood. We reasoned that H3K27me3-rich regions (MRRs) of the genome defined from clusters of H3K27me3 peaks may be used to identify silencers that can regulate gene expression via proximity or looping. MRRs were associated with chromatin interactions and interact preferentially with each other. MRR component removal at interaction anchors by CRISPR led to upregulation of interacting target genes, altered H3K27me3 and H3K27ac levels at interacting regions, and altered chromatin interactions. Chromatin interactions did not change at regions with high H3K27me3, but regions with low H3K27me3 and high H3K27ac levels showed changes in chromatin interactions. The MRR knockout cells also showed changes in phenotype associated with cell identity, and altered xenograft tumor growth. MRR-associated genes and long-range chromatin interactions were susceptible to H3K27me3 depletion. Our results characterized H3K27me3-rich regions and their mechanisms of functioning via looping.

genomics↗