Biology subjects

Ai, R.

Publications and source records attributed to Ai, R..

4 recordsLinked to original sources

bioRxiv2026

ATG-18 drives longevity in an HLH-30-dependent manner

Enhancing autophagy increases lifespan and healthspan in animal models, yet the precise molecular mechanisms underlying these effects are not fully understood. Here we show that overexpression of the essential autophagic gene atg-18 extends the lifespan of C. elegans. We describe a previously unknown, pleiotropic mechanism by which atg-18 impacts lysosomes and extends lifespan through the transcription factor hlh-30, the master regulator of lysosomal biogenesis. We show that, under stress conditions, HLH-30 requires atg-18 for nuclear translocation. Furthermore, atg-18 overexpression broadly improves health and stress resilience yet paradoxically increases early-life susceptibility to lethal heat stress. In contrast, enhances heat-stress survival a loss-of-function of function mutation in atg-18 enhances heat-stress survival, uncovering a temporal-specific effect of atg-18. These finding suggest an ATG-18--HLH-30 autophagy--lysosome pathway that plays a key role in lifespan and healthspan. Bulleted main discoveriesO_LIATG-18 overexpression increases C. elegans lifespan and plays an important role in resilience against starvation and heat stress. C_LIO_LIATG-18 is required for nuclear translocation of HLH-30 C_LIO_LIHLH-30 is required for ATG-18--mediated lifespan extension C_LIO_LIATG-18 positively regulates lysosomal biogenesis, suggesting a novel role as a molecular coordinator between autophagy and the lysosomal network. C_LI

molecular biology↗

bioRxiv2024

NAD+ - and EVA1-C-dependent reversal of neurological deficits is mediated by differential alternative RNA splicing in tauopathic animal models

Aberrant alternative splicing (ASEs) is an aging hallmark to Alzheimers Disease (AD). Although NAD+ and related metabolites can slow down AD, NAD+ on ASEs in AD remain unclear. Mouse transcriptomic data revealed NR-induced ASEs, focusing on the Eva1-C locus. AI-based algorithms predicted EVA1-C protein structures and protein-protein interactions. AD postmortem brain samples and tauopathy models including transgenic mice and worm was used for validation. NAD+ abundance/metabolic status modulates ASEs and the expression of EVA1-C isoforms, which in turn regulate the interaction with BAG-1 and HSP70 proteins. Importantly, EVA1-C is dramatically reduced in 20 Braak 5/6 AD patients compared to cognitive normal humans in different brain regions. NAD+ metabolism modulates abundance of specific mRNA isoforms, and that ASEs influence disease progression in model tauopathies and potentially AD. These results could facilitate future development of NAD+-based splice-switching therapeutics for AD. TeaserUnveiling the Link Between NAD+ Metabolism and Alzheimers Disease: Discovering the Role of Alternative RNA Splicing in Disease Progression and Potential Therapeutic Targets

neuroscience↗

bioRxiv2019

Identification of DNA motifs that regulate DNA methylation

DNA methylation is an important epigenetic mark but how its locus-specificity is decided in relation to DNA sequence is not fully understood. Here, we have analyzed 34 diverse whole-genome bisulfite sequencing datasets in human and identified 313 motifs, including 92 and 221 associated with methylation (methylation motifs, MMs) and unmethylation (unmethylation motifs, UMs), respectively. The functionality of these motifs is supported by multiple lines of evidences. First, the methylation levels at the MM and UM motifs are respectively higher and lower than the genomic background. Second, these motifs are enriched at the binding sites of methylation modifying enzymes including DNMT3A and TET1, indicating their possible roles of recruiting these enzymes. Third, these motifs significantly overlap with SNPs associated with gene expression and those with DNA methylation. Fourth, disruption of these motifs by SNPs is associated with significantly altered methylation level of the CpGs in the neighbor regions. Furthermore, these motifs together with somatic SNPs are predictive of cancer subtypes and patient survival. We revealed some of these motifs were also associated with histone modifications, suggesting possible interplay between the two types of epigenetic modifications. We also found some motifs form feed forward loops to contribute to DNA methylation dynamics.

bioinformatics↗

bioRxiv2018

Integrative analysis with expanded DNA methylation data reveals common key regulators and pathways in cancers

The integration of genomic and DNA methylation data has been demonstrated as a powerful strategy in understanding cancer mechanisms and identifying therapeutic targets. The TCGA consortium has mapped DNA methylation in thousands of cancer samples using Illumina Infinium Human Methylation 450K BeadChip (Illumina 450K array) that only covers about 1.5% of CpGs in the human genome. Therefore, increasing the coverage of the DNA methylome would significantly leverage the usage of the TCGA data. Here, we present a new model called EAGLING that can expand the Illumina 450K array data 18 times to cover about 30% of the CpGs in the human genome. We applied it to analyze 13 cancers in TCGA. By integrating the expanded methylation, gene expression and somatic mutation data, we identified the genes showing differential patterns in each of the 13 cancers. Many of the triple-evidenced genes identified in the majority of the cancers are biomarkers or potential biomarkers. Pan-cancer analysis also revealed the pathways in which the triple-evidenced genes are enriched, which include well known ones as well as new ones such as axonal guidance signaling pathway and pathways related to inflammatory processing or inflammation response. Triple-evidenced genes, particularly TNXB, RRM2, CELSR3, SLC16A3, FANCI, MMP9, MMP11, SIK1, TRIM59, showed superior predictive power in both tumor diagnosis and prognosis. These results have demonstrated that the integrative analysis using the expanded methylation data is powerful in identifying critical genes/pathways that may serve as new therapeutic targets.

bioinformatics↗