Biology subjects

Leung, A. W.-S.

Publications and source records attributed to Leung, A. W.-S..

8 recordsLinked to original sources

bioRxiv2025

Dual targeting of transferrin receptor and CD98hc enhances brain exposure of large molecules

Targeting proteins highly expressed at the blood-brain barrier, including transferrin receptor (TfR) and CD98hc, is a transformative approach enabling more effective brain delivery of biotherapeutics for treatment of neurological diseases. TfR-mediated delivery promotes rapid, high brain uptake, while CD98hc-mediated delivery is slower with more prolonged exposure. Here, we engineer a huIgG Fc domain to bind both TfR and CD98hc to create a dual transport vehicle (TV) platform that drives distinct brain delivery properties. Dual TVs achieve significantly higher brain concentrations than TVs targeting either TfR or CD98hc alone. Modulation of TfR and CD98hc affinities shifts dual TV brain exposure kinetics and biodistribution. Stronger TfR affinity drives faster brain uptake and clearance, while stronger CD98hc affinity yields higher, more sustained concentrations, likely due to CD98hc affinity-dependent reduction in TfR-mediated neuronal internalization. This dual targeting strategy leverages the complementary properties of TfR and CD98hc-mediated brain exposure to increase optionality for brain delivery of biotherapeutics.

neuroscience↗

bioRxiv2024

Engineering anti-amyloid antibodies with transferrin receptor targeting improves safety and brain biodistribution

Although the first generation of immunotherapies for Alzheimers disease (AD) are now clinically approved, amyloid-related imaging abnormalities (ARIA) remain a major safety problem for this class of drugs. Here, we report an antibody transport vehicle (ATV) targeting the transferrin receptor (TfR) for brain delivery of amyloid beta (A{beta}) antibodies that significantly reduced ARIA-like lesions and improved plaque target engagement in a mouse model of amyloid deposition. Asymmetrical Fc mutations (ATVcisLALA) allowed the molecule to selectively retain effector function only when bound to A{beta} while mitigating TfR-related hematology liabilities. Mice treated with ATVcisLALA:A{beta} exhibited broad brain parenchymal antibody distribution; in contrast, anti-A{beta} IgG was highly enriched at arterial perivascular spaces where vascular A{beta} localizes and likely plays a role in induction of ARIA. Importantly, ATVcisLALA: A{beta} almost completely eliminated ARIA-like lesions and vascular inflammation associated with anti-A{beta} treatment. Taken together, ATVcisLALA has the potential to significantly improve both safety and efficacy of A{beta} immunotherapy through enhanced biodistribution mediated by transport across the blood-brain barrier.

neuroscience↗

bioRxiv2022

Evaluation of Mycobacterium Tuberculosis enrichment in metagenomic samples using ONT adaptive sequencing and amplicon sequencing for identification and variant calling

Sensitive detection of Mycobacterium Tuberculosis (TB) in small percentages in metagenomic samples is essential for microbial classification and drug resistance prediction, and assisting in diagnosis and treatment planning. However, traditional methods, such as bacterial culture and microscopy, are time-consuming and sometimes have limited TB detection sensitivity. Oxford Nanopore Technologies MinION sequencing allows rapid and simple sample preparation for whole genome and amplicon sequencing. Its recently developed adaptive sequencing selects reads from targets, while allowing real-time base-calling during sequencing to achieve sequence enrichment or depletion. Another common enrichment method is PCR amplification of the target TB genes. In this study, we compared both methods with MinION sequencing for TB detection and variant calling in metagenomic samples using both simulation runs and those with synthetic and patient samples. We found that both methods effectively enrich TB reads from a high percentage of human and other microbial DNA. We provide a simple automatic analysis framework, including quality filtering, taxonomic classification, variant calling, and antimicrobial resistance prediction, to support these detection workflows for clinical use, openly available at https://github.com/HKU-BAL/ONT-TB-NF. Depending on the patients medical condition and sample type (commonly including bronchoalveolar lavage fluid, blood samples, sputum, and tissues), we discuss the findings and recommend that users optimize their workflow to improve the detection limit.

bioinformatics↗

bioRxiv2022

Duet: SNP-Assisted Structural Variant Calling and Phasing Using Oxford Nanopore Sequencing

BackgroundWhole genome sequencing (WGS) using the long-read Oxford Nanopore Technologies (ONT) MinION sequencer provides a cost-effective option for structural variant (SV) detection in clinical applications. Despite the advantage of using long reads, however, accurate SV calling and phasing are still challenging. ResultsWe introduce Duet, an SV detection tool optimized for SV calling and phasing using ONT data. The tool uses novel features integrated from both SV signatures and single-nucleotide polymorphism (SNP) signatures, which can accurately distinguish SV haplotype from a false signal. Duet was benchmarked against state-of-the-art tools on multiple ONT sequencing datasets of sequencing coverage ranging from 8X to 40X. At low sequencing coverage of 8X, Duet performs better than all other tools in SV calling, SV genotyping and SV phasing. When the sequencing coverage is higher (20X to 40X), the F1-score for SV phasing is further improved in comparison to the performance of other tools, while its performance of SV genotyping and SV calling remains comparable or higher than other tools. ConclusionDuet can perform accurate SV calling, SV genotyping and SV phasing using low-coverage ONT data, making it very useful for low-coverage genomes. It has great performance when scaled to high-coverage genomes, which is adaptable to various clinical applications. Duet is open source and is available at https://github.com/yekaizhou/duet.

bioinformatics↗

bioRxiv2021

Symphonizing pileup and full-alignment for deep learning-based long-read variant calling

Deep learning-based variant callers are becoming the standard and have achieved superior SNP calling performance using long reads. In this paper, we present Clair3, which leveraged the best of two major method categories: pile-up calling handles most variant candidates with speed, and full-alignment tackles complicated candidates to maximize precision and recall. Clair3 ran faster than any of the other state-of-the-art variant callers and performed the best, especially at lower coverage.

bioinformatics↗

bioRxiv2021

HKG: An open genetic variant database of 205 Hong Kong Cantonese exomes

HKG is the first fully accessible variant database for Hong Kong Cantonese, constructed from 205 novel whole-exome sequencing data. There has long been a research gap in the understanding of the genetic architecture of southern Chinese subgroups, including Hong Kong Cantonese. HKG detected 196,325 high-quality variants with 5.93% being novel, and 25,472 variants were found to be unique in HKG compared to other Chinese populations (CHN). PCA illustrates the uniqueness of HKG in CHN, and IBD analysis revealed that it is related mostly to southern Chinese with a similar effective population size. An admixture study estimated the ancestral composition of HKG and CHN, with a gradient change from north to south, consistent with their geological distribution. ClinVar, CIViC and PharmGKB annotated 599 clinically significant variants and 360 putative loss-of-function variants, substantiating our understanding of population characteristics for future medical development. Among the novel variants, 96.57% were singleton and 6.85% were of high impact. With a good representation of Hong Kong Cantonese, we demonstrated better variant imputation using reference with the addition of HKG data, thus successfully filling the data gap in southern Chinese to facilitate the regional and global development of population genetics.

bioinformatics↗

bioRxiv2021

DNA methylation affects pre-mRNA transcriptional initiation and processing in Arabidopsis

BackgroundDNA methylation may regulate pre-mRNA transcriptional initiation and processing, thus affecting gene expression. Unlike animal cells, plants, especially Arabidopsis thaliana, have relatively low DNA methylation levels, limiting our ability to observe any correlation between DNA methylation and pre-mRNA processing using typical short-read sequencing. However, with newly developed long-read sequencing technologies, such as Oxford Nanopore Technology Direct RNA sequencing (ONT DRS), combined with whole-genome bisulfite sequencing, we were able to precisely analyze the relationship between DNA methylation and pre-mRNA transcriptional initiation and processing using DNA methylation-related mutants. ResultsUsing ONT DRS, we generated more than 2 million high-quality full-length long reads of native mRNA for each of the wild type Col-0 and mutants defective in DNA methylation, identifying a total of 117,474 isoforms. We found that low DNA methylation levels around splicing sites tended to prevent splicing events from occurring. The lengths of the poly(A) tail of mRNAs were positively correlated with DNA methylation. DNA methylation before transcription start sites or around transcription termination sites tended to result in gene-silencing or read-through events. Furthermore, using ONT DRS, we identified novel transcripts that we could not have otherwise, since transcripts with intron retention and fusion transcripts containing the uncut intergenic sequence tend not to be exported to the cytoplasm. Using the met1-3 mutant with activated constitutive heterochromatin regions, we confirmed the effects of DNA methylation on pre-mRNA processing. ConclusionThe combination of ONT DRS with whole-genome bisulfite sequencing was a powerful tool for studying the effects of DNA methylation on splicing site selection and pre-mRNA processing, and therefore regulation of gene expression.

plant biology↗

bioRxiv2021

ECNano: A Cost-Effective Workflow for Target Enrichment Sequencing and Accurate Variant Calling on 4,800 Clinically Significant Genes Using a Single MinION Flowcell

BackgroundThe application of long-read sequencing using the Oxford Nanopore Technologies (ONT) MinION sequencer is getting more diverse in the medical field. Having a high sequencing error of ONT and limited throughput from a single MinION flowcell, however, limits its applicability for accurate variant detection. Medical exome sequencing (MES) targets clinically significant exon regions, allowing rapid and comprehensive screening of pathogenic variants. By applying MES with MinION sequencing, the technology can achieve a more uniform capture of the target regions, shorter turnaround time, and lower sequencing cost per sample. MethodWe introduced a cost-effective optimized workflow, ECNano, comprising a wet-lab protocol and bioinformatics analysis, for accurate variant detection at 4,800 clinically important genes and regions using a single MinION flowcell. The ECNano wet-lab protocol was optimized to perform long-read target enrichment and ONT library preparation to stably generate high-quality MES data with adequate coverage. The subsequent variant-calling workflow, Clair-ensemble, adopted a fast RNN-based variant caller, Clair, and was optimized for target enrichment data. To evaluate its performance and practicality, ECNano was tested on both reference DNA samples and patient samples. ResultsECNano achieved deep on-target depth of coverage (DoC) at average >100x and >98% uniformity using one MinION flowcell. For accurate ONT variant calling, the generated reads sufficiently covered 98.9% of pathogenic positions listed in ClinVar, with 98.96% having at least 30x DoC. ECNano obtained an average read length of 1,000 bp. The long reads of ECNano also covered the adjacent splice sites well, with 98.5% of positions having [≥] 30x DoC. Clair-ensemble achieved >99% recall and accuracy for SNV calling. The whole workflow from wet-lab protocol to variant detection was completed within three days. ConclusionWe presented ECNano, an out-of-the-box workflow comprising (1) a wet-lab protocol for ONT target enrichment sequencing and (2) a downstream variant detection workflow, Clair-ensemble. The workflow is cost-effective, with a short turnaround time for high accuracy variant calling in 4,800 clinically significant genes and regions using a single MinION flowcell. The long-read exon captured data has potential for further development, promoting the application of long-read sequencing in personalized disease treatment and risk prediction.

bioinformatics↗