Biology subjects

LI, W.

Publications and source records attributed to LI, W..

6 recordsLinked to original sources

bioRxiv2025

Rewired m6A methylation of promoter antisense RNAs in Alzheimer disease regulates global gene transcription in the 3D nucleome

N6-methyladenosine (m6A) is the most prevalent internal RNA modification that can impact mRNA expression post-transcriptionally. Recent progress indicates that m6A also acts on nuclear or chromatin-associated RNAs to impact transcriptional and epigenetic processes. However, the landscapes and functional roles of m6A in human brains and neurodegenerative diseases, including Alzheimers disease (AD), have been under-explored. Here, we examined RNA m6A methylome using total RNA-seq and meRIP-seq in middle frontal cortex tissues of post-mortem human brains from individuals with AD and age-matched counterparts. Our results revealed AD-associated alteration of m6A methylation on both mRNAs and various noncoding RNAs. Notably, a series of promoter antisense RNAs (paRNAs) displayed cell-type-specific expression and changes in AD, including one produced adjacent to the MAPT locus that encodes the Tau protein. We found that MAPT-paRNA is enriched in neurons, and m6A positively controls its expression. In iPSC-derived human excitatory neurons, MAPT-paRNA promotes expression of hundreds of genes related to neuronal and synaptic functions, including a key AD resilience gene MEF2C, and plays a neuroprotective role against excitotoxicity. By examining RNA-DNA interactome in the three-dimensional (3D) nuclei of human brains, we demonstrated that brain paRNAs can interact with both cis- and trans-chromosomal target genes to impact their transcription. These data together reveal previously unexplored landscapes and functions of noncoding RNAs and m6A methylome in brain gene regulation, neuronal survival and AD pathogenesis.

molecular biology↗

bioRxiv2025

Unveiling the Evolution of Antimicrobial Peptides in Gut Microbes via Foundation Model-Powered Framework

Antimicrobial resistance poses a growing threat to public health, emphasizing the urgent need for novel therapeutic strategies. Antimicrobial peptides (AMPs), short peptide sequences with diverse mechanisms of action, offer a promising alternative due to their broad-spectrum activity against pathogens. Recent advances in protein language models (PLMs) have revolutionized protein structure prediction and functional annotation, highlighting their potential for AMP discovery and therapeutic development. In this context, we present AMP-SEMiner (Antimicrobial Peptide Structural Evolution Miner), an AI-driven framework designed to identify AMPs from metagenome-assembled genomes (MAGs). By integrating PLMs, structural clustering and evolutionary analysis into the framework, AMP-SEMiner can identify AMPs encoded by small open reading frames (smORFs) and encrypted peptides (EPs), significantly expanding the discovery space. Using this approach, we identified 1,670,600 AMP candidates from diverse habitats. Experimental validation of 29 candidates revealed antimicrobial activity in 18, with 13 surpassing antibiotics in effectiveness. Further analysis of AMPs from human gut microbiomes demonstrated both conserved and adaptive evolutionary strategies, ensuring their functional efficacy in the dynamic gut environment. These findings position AMP-SEMiner as a powerful tool for the discovery and characterization of novel AMPs, with significant potential to drive the development of new antimicrobial therapies.

microbiology↗

bioRxiv2024

Population comparisons reveal more social interactions are correlated with larger brains in the Lake Tanganyikan cichlid Neolamprologus brevis

The Social Brain Hypothesis (SBH) proposes that complex social environments drive the evolution of larger brains and specific neuroanatomical adaptations. This relationship can be difficult to study in the wild, because species that differ in social organization may also diverge in morphology, ecology, phylogeny, and other life history parameters. Here we use two populations of the shell-dwelling cichlid Neolamprologus brevis with contrasting social environments to test whether increased social complexity is associated with larger brain sizes or specific regional adaptations. Behavioral observations revealed similarly low feeding rates in both populations, but significantly more frequent social interaction frequencies in the population one of the populations. This population had larger total brain volumes relative to body size, with a disproportionately larger telencephalon and a smaller hypothalamus, suggesting region-specific adaptations to social demands. By integrating behavioral quantification and neuroanatomical analysis, our study highlights the importance of sociality as a driver of brain evolution and demonstrates the utility of cichlid fish as a model for testing the SBH in non-mammalian systems. These findings provide empirical support for the SBH and underscore the value of combining behavioral and morphological data in evolutionary neuroethology.

animal behavior and cognition↗

bioRxiv2024

Multiple within species comparisons show Tanganyikan cichlid fish have larger brains in less structurally complex habitats

Many studies have found a link between higher habitat structural complexity and increased relative brain size in vertebrates. Here we explore this relationship in a multi-species comparison, comparing ten species of wild cichlids that differ in their social and territorial behaviour, but which occur across four ecologically similar but structurally diverse rocky habitats. This design allows us to perform repeated intra-specific comparisons, avoiding confounds associated with comparisons across species boundaries. We sampled 147 fish, analysing brain size and architecture while controlling for body mass and species-specific variability and compared this with habitat complexity, quantified using underwater video and three-dimensional reconstructions. Our results challenge the Clever Foraging Hypothesis (CFH), which posits that greater habitat complexity correlates with larger brain sizes. Contrary to CFH, fish from the least complex habitat had significantly larger brains. Additionally, brain architecture analysis indicated a significant enlargement of the cerebellum in fish from less complex habitats, whereas the hypothalamus showed a non-significant negative trend. Taken together, these results indicate that lower habitat complexity may impose higher cognitive demands on spatial memory and navigation due to limited refuges and increased predation risk. This study highlights the need to reconsider the assumed linear positive relationship between environmental complexity and brain development, suggesting that simpler environments might also impose significant cognitive and ecological challenges that drive brain evolution. Our findings underscore the importance of considering intra-species variability and the specific ecological and cognitive demands of different habitats in studies of brain evolution.

evolutionary biology↗

bioRxiv2024

Discovering CRISPR-Cas system with self-processing pre-crRNA capability by foundation models

The discovery and functional annotation of CRISPR-Cas systems laid the groundwork for the development of novel CRISPR-based gene editing tools. Traditional similarity- search-based Cas discovery strategies, which rely heavily on local sequence alignment and reference Cas homologs, may overlook a significant number of remote homologs with limited sequence similarity; and it can not be applied directly for functional recognition. With the rapid development of protein large language models (LLMs), protein foundation models are expected to help model Cas systems with limited Cas homologs without extensive task-specific training data; however, the full potential of these models for Cas discovery and functional annotation has yet to be determined. To this end, we present a novel, effective and unified AI framework, CHOOSER (Cas HOmlog Observing and SElf-processing scReening), for alignment-free discovery of novel CRISPR-Cas systems with self-processing precursor CRISPR RNA (pre-crRNA) capability utilizing protein foundation models. CHOOSER successfully retrieved 11 novel homologs of Cas{lambda}, the majority of which are predicted to be able to self-process pre-crRNA, nearly doubling the current catalog. One of the candidates, EphcCas{lambda}, was subsequently experimentally validated for its ability to self-process pre-crRNA, target DNA cleavage, and trans-cleavage and was shown to be a promising candidate for use as a CRISPR-Cas-based pathogen detection system. Overall, our study provides an unprecedented perspective and methodology for discovering novel CRISPR-Cas systems with specific functions using foundation models, underscoring the potential for transforming newly identified Cas homologs into genetic editing tools.

bioinformatics↗

bioRxiv2020

SARS-CoV-2 neutralizing human antibodies protect against lower respiratory tract disease in a hamster model

Effective clinical intervention strategies for COVID-19 are urgently needed. Although several clinical trials have evaluated the use of convalescent plasma containing virus-neutralizing antibodies, the effectiveness has not been proven. We show that hamsters treated with a high dose of human convalescent plasma or a monoclonal antibody were protected against weight loss showing reduced pneumonia and pulmonary virus replication compared to control animals. However, a ten-fold lower dose of convalescent plasma showed no protective effect. Thus, variable and relatively low levels of virus neutralizing antibodies in convalescent plasma may limit their use for effective antiviral therapy, favouring concentrated, purified (monoclonal) antibodies.

microbiology↗