Biology subjects

Tan, J. W.

Publications and source records attributed to Tan, J. W..

7 recordsLinked to original sources

bioRxiv2026

Nailpolish: Reference-free UMI deduplication and consensus read generation

Long-read sequencing captures full-length transcripts but suffers elevated error rates, and PCR duplicates can distort quantification unless accounted for with UMIs. We present Nailpolish, a fast reference-free tool that error-corrects and deduplicates UMI-tagged long reads by generating consensus sequences via partial order alignment, while separating false duplicates arising from UMI collisions. Across eleven Oxford Nanopore Technologies and Pacific Biosciences datasets spanning bulk, single-cell, spatial, and targeted protocols, Nailpolish reduced per-read error rates and outperformed existing deduplication tools.

bioinformatics↗

bioRxiv2026

Compact adenine base editors to enable therapeutic rescue of Duchenne muscular dystrophy

Adenine base editors (ABEs) have emerged as a powerful gene-editing technology enabling precise and programmable adenine-to-guanine substitutions across the genome. However, their translation into in vivo therapeutics is limited by delivery challenges, as their size exceeds the packaging capacity of adeno-associated virus (AAV). Here, we report the discovery, structural characterization, and engineering of two compact, highly active ABEs built on novel deaminases and Cas9d nucleases, enabling all-in-one, single-vector AAV delivery. Applying these compact ABEs to Duchenne muscular dystrophy (DMD), we demonstrate efficient disruption of conserved splice-acceptor sites at dystrophin exons 45 and 51 in human skeletal muscle cells, enabling therapeutically relevant exon skipping. Together, these ABEs help expand the therapeutic reach of base editing towards diverse tissue types and disease targets.

bioengineering↗

bioRxiv2024

Transcriptome Analysis Reveals Long-Term Somatic Memory of Stress in The Woody Perennial Crop, Grapevine Vitis Vinifera cv. Cabernet Sauvignon

Plants can generate a molecular memory of stress resulting in primed plants that are more resilient to subsequent stresses occurring days to weeks after the priming event. Whether such a priming effect is maintained over longer periods, and after winter dormancy in perennial plants, is less studied. Here, we used whole transcriptome and methylome sequencing of grapevine plants over two growing seasons to characterize grapevines response to combined drought and heat stress in naive and primed plants. Our results showed changes in expression of genes associated with epigenetic modifications during stress and after stress removal, suggesting the establishment of epigenetic memory of stress. Primed plants had a small number of differentially expressed genes associated with stress response one year after the priming event even in the absence of second stress and presented a stronger transcriptional response than naive plants when re-exposed to stress. Methylome analysis revealed an increase in DNA methylation in primed vines under combined stress, and that methylation patterns were less variable among plants under stress than control plants. We did not observe any correlation between DNA methylation and gene transcription, suggesting that stress-induced expression changes were, at least partially, independent of DNA methylation, with posttranscriptional regulation and histone modifications more likely candidates in the establishment of epigenetic memory. Additionally, we characterized stress responsive genes based on their transcriptional profile and function and propose a new comprehensive and intuitive classification model for stress memory genes in perennials.

plant biology↗

bioRxiv2022

Insight parameter drug design for human beta-tryptase inhibition integrated molecular docking, QSAR, molecular dynamics simulation, and pharmacophore modelling studies of alpha-keto--oxadiazoles

Dengue hemorrhagic fever (DHF) is life-threatening severe dengue with a hallmark of vascular leakage. A mast cell protease, {beta}-tryptase, has been found to promote vascular leakage in DHF patients, which could be a potential target for the treatment of DHF. This study aims to develop a theoretical background for the design and selection of {beta}-tryptase inhibitors through these approaches: two-dimensional quantitative structure-activity relationships (2D-QSAR) study, molecular docking analysis, molecular dynamics (MD) simulation, and structure-based pharmacophore modelling (PM). A total of 34 a-keto-[1,2,3]-oxadiazoles scaffold-based compounds, obtained from a past study, were used to generate 2D-QSAR models by Genetic Function Approximation (GFA). The generated 2D-QSAR models were used to investigate the relationships between the molecular structure and the potency of {beta}-tryptase inhibition. Molecular docking explores the binding affinities and binding interactions of the a-keto-[1,2,3]-oxadiazoles scaffold-based compounds with {beta}-tryptase (PDB Code 4A6L) by the CDOCKER tool in Discovery Studio. In addition, MD simulation was performed using GROMACS on the docked complex of the reported most active compound, compound 11e, to study the binding mechanism of the compound towards {beta}-tryptase. Finally, a structure-based pharmacophore model was generated from the same docked complex to identify the important features that contribute positively to the inhibitory activity of the compound towards {beta}-tryptase. The best 2D-QSAR model has demonstrated statistically significant results through its r2, q2, and r2 (pred) values of 0.9077, 0.733, and 0.8104, respectively. The docking results of compound 11e showed lower CDOCKER energy than the 4A6L co-crystallised ligand, indicating good binding affinity. Furthermore, compound 11e has a similar binding pattern as the 4A6L co-crystallised ligand, which involves the binding of active residues such as Asp207, SER208, and GLY237. The MD simulation shows that the 4A6L-compound 11e complex has RMSD below 2[A] throughout the 100ns of simulation, indicating that the docked complex is stable. Besides, MD simulation showed that the inhibitory potency of compound 11e is contributed by hydrogen bonding with 4A6L active site residues, which are ASP207, SER208, and GLY237. The best pharmacophore model identified features that contribute to the inhibitory potency of a compound, which included hydrogen bond acceptor, ionic interaction, hydrophobic interaction, and aromatic ring. This study has fundamentally supplied valuable insight and knowledge for developing novel chemical compounds with improved inhibitory ability against human {beta}-tryptase. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/500327v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1e277c4org.highwire.dtl.DTLVardef@1250185org.highwire.dtl.DTLVardef@86fed8org.highwire.dtl.DTLVardef@c54035_HPS_FORMAT_FIGEXP M_FIG C_FIG DENV induces mast cell degranulation to release mediators, such as {beta}-tryptase. {beta}-Tryptase has been reported to promote plasma leakage, which is the hallmark of dengue hemorrhagic fever (DHF). Thus, {beta}-tryptase could be a promising target for the treatment of DHF. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=190 SRC="FIGDIR/small/500327v1_ufig2.gif" ALT="Figure 2"> View larger version (38K): org.highwire.dtl.DTLVardef@1fa7ff9org.highwire.dtl.DTLVardef@e7f1f8org.highwire.dtl.DTLVardef@1bf0175org.highwire.dtl.DTLVardef@f8d033_HPS_FORMAT_FIGEXP M_FIG C_FIG In this study, computer-aided drug design was used to examine the structure-activity relationship and binding mechanisms of {beta}-tryptase inhibitors reported in a past study. Finally, theoretical background for the design of {beta}-tryptase inhibitors was built.

biochemistry↗

bioRxiv2020

Prediction of novel components of bacterial ribosomes by crowd-sourced analysis of RNA sequencing data

Bacterial resistance to antibiotics is a growing problem that is projected to cause more deaths than cancer in 2050. Consequently, novel antibiotics are urgently needed. Since more than half of the available antibiotics target the bacterial ribosomes, proteins that are involved in protein synthesis are thus prime targets for the development of novel antibiotics. However, experimental identification of these potential antibiotic target proteins can be labor-intensive and challenging, as these proteins are likely to be poorly characterized and specific to few bacteria. In order to identify these novel proteins, we established a Large-Scale Transcriptomic Analysis Pipeline in Crowd (LSTrAP-Crowd), where 285 individuals processed 26 terabytes of RNA-sequencing data of the 17 most notorious bacterial pathogens. In total, the crowd processed 26,269 RNA-seq experiments and used the data to construct gene co-expression networks, which were used to identify more than a hundred uncharacterized genes that were transcriptionally associated with protein synthesis. We provide the identity of these genes together with the processed gene expression data. The data can be used to identify other vulnerabilities or bacteria, while our approach demonstrates how the processing of gene expression data can be easily crowdsourced.

bioinformatics↗

bioRxiv2020

Brucella suppress innate immunity by down-regulating STING expression in macrophages

Brucellosis, caused by Brucella bacteria species, remains the most prevalent zoonotic disease worldwide. Brucella establish chronic infections within host macrophages despite triggering cytosolic innate immune sensors, including Stimulator of Interferon Genes (STING), which potentially limit infection. In this study, STING was required for control of chronic Brucella infection in vivo. However, early during infection, Brucella down-regulated STING mRNA and protein. Down-regulation occurred post-transcriptionally, required live bacteria, the Brucella type IV secretion system, and was independent of host IRE1-RNase activity. Rather, Brucella induced a STING-targeting microRNA, miR-24-2. Furthermore, STING downregulation was inhibited by miR-24 anti-miRs and in mirn23a locus-deficient macrophages. Failure to suppress STING expression in mirn23a-/- macrophages correlated with diminished Brucella replication, and was rescued by exogenous miR-24. Anti-miR-24 potently suppressed replication in wild type, but much less in STING-/- macrophages, suggesting most of the impact of miR-24 induction on replication occurred via STING suppression. In summary, Brucella sabotages innate immunity by miR-24-dependent suppression of STING expression; post-STING activation "damage control" via targeted STING destruction may enable establishment of chronic infection. Author summaryCytosolic pattern recognition receptors, such as the nucleotide-activated STING molecule, play a critical role in the innate immune system by detecting the presence of intracellular invaders. Brucella bacterial species establish chronic infections in macrophages despite initially activating STING. STING does participate in the control of Brucella infection, as mice or cells lacking STING show a higher burden of Brucella infection. However, we have found that early following infection, Brucella upregulates a microRNA, miR-24, that targets the STING messenger RNA, resulting in lower STING levels. Dead bacteria or bacteria lacking a functional type IV secretion system were defective at upregulating miR-24 and STING suppression, suggesting an active bacteria-driven process. Failure to upregulate miR-24 and suppress STING greatly compromised the capacity for Brucella to replicate inside macrophages. Thus, although Brucella initially activate STING during infection, the ensuing STING downregulation serves as a "damage control" mechanism, enabling intracellular infection. Viruses have long been known to target immune sensors such as STING. Our results indicate that intracellular bacterial pathogens also directly target innate immune receptors to enhance their infectious success.

microbiology↗

bioRxiv2019

Rapid microbial interaction network inference in microfluidic droplets

Microbial interactions are major drivers of microbial community dynamics and functions. However, microbial interactions are challenging to decipher due to limitations in parallel culturing of sub-communities across many environments and accurate absolute abundance quantification of constituent members of the consortium. To this end, we developed Microbial Interaction Network Inference in microdroplets (MINI-Drop), a high-throughput method to rapidly infer microbial interactions in microbial consortia in microfluidic droplets. Fluorescence microscopy coupled to automated computational droplet and cell detection was used to rapidly determine the absolute abundance of each strain in hundreds to thousands of droplets per experiment. We show that MINI-Drop can accurately infer pairwise as well as higher-order interactions using a microbial interaction toolbox of defined microbial interactions mediated by distinct molecular mechanisms. MINI-Drop was used to investigate how the molecular composition of the environment alters the interaction network of a three-member consortium. To provide insight into the variation in community states across droplets, we developed a probabilistic model of cell growth modified by microbial interactions. In sum, we demonstrate a robust and generalizable method to probe cellular interaction networks by random encapsulation of sub-communities into microfluidic droplets.

systems biology↗