Biology subjects

Wang, T.-H.

Publications and source records attributed to Wang, T.-H..

7 recordsLinked to original sources

bioRxiv2025

Mitochondrial genome reduction and accelerated evolution in planktonic foraminiferans

The evolution of mitochondria provides crucial insights into the diversification of eukaryotes, with complex events of gene losses revealed through comparative analyses of mitochondrial genomes (mitogenomes) across eukaryotic lineages. However, the mitogenomes of many microbial eukaryotes remain underexplored due to challenges in their isolation and cultivation. Particularly understudied are Foraminifera (Rhizaria, SAR), unicellular calcifyers that are widely distributed across global oceans and important paleoenvironmental proxies. Through single-cell genomic sequencing, here we report a 22-kb complete mitogenome of a planktonic foraminiferan from tropical seawater, which is the smallest known to date among all sequenced mitogenomes of Rhizaria, a major lineage of eukaryotes. It contains only six protein-coding genes and fragmented ribosomal RNA genes, and has lost most genes in oxidative phosphorylation and all genes in mitochondrial translation. Such genome reduction is associated with accelerated evolutionary rates and a lower GC content than that of benthic foraminiferan and other rhizarian mitogenomes. These findings highlight the unique trajectory of mitogenome reduction during rhizarian evolution and the use of single-cell approaches for recovering microbial eukaryotic genomes and expanding our understanding of mitochondrial evolution.

genomics↗

bioRxiv2025

Controlling Payload Heterogeneity in Lipid Nanoparticles for RNA-Based Therapeutics

Lipid nanoparticles (LNPs) are a leading platform for nucleic acid delivery, yet conventional assembly by mixing lipids with RNA yields particles with heterogeneous, bimodal payload distribution. Our transfection experiments demonstrate that heterogeneous siRNA distribution within LNPs significantly reduces gene knockdown efficiency. To systematically investigate the origin and extent of payload heterogeneity, we integrate coarse-grained molecular dynamics and kinetic Monte Carlo simulations with single-particle characterization via cylindrical illumination confocal spectroscopy and machine learning analysis. We find that the balance between RNA diffusion kinetics and lipid self-assembly dynamics is the dominant driver of payload heterogeneity. Leveraging this mechanistic insight, we show that (i) finely controlled turbulent mixing minimizes payload variance and increases the uniformity of RNA distribution without altering LNP size, and (ii) systematic adjustment of salt concentration and PEG-lipid content tunes RNA loading in a volume-dependent manner. Together, these results elucidate the self-assembly landscape of RNA-LNPs and provide actionable design principles for crafting more uniform, potent, and safer LNP-based nucleic acid therapies.

bioengineering↗

bioRxiv2024

An Interbacterial Cysteine Protease Toxin Inhibits Cell Growth by Targeting Type II DNA Topoisomerases GyrB and ParE

Bacteria deploy a diverse arsenal of toxic effectors to antagonize competitors, profoundly influencing the composition of microbial communities. Previous studies have identified an interbacterial toxin predicted to exhibit proteolytic activity that is broadly distributed among Gram-negative bacteria. However, the precise mechanism of intoxication remains unresolved. Here, we demonstrate that one such protease toxin from Escherichia coli, Cpe1, disrupts DNA replication and chromosome segregation by cleaving conserved sequences within the ATPase domain of type II DNA topoisomerases GyrB and ParE. This cleavage effectively inhibits topoisomerase-mediated relaxation of supercoiled DNA, resulting in impaired bacterial growth. Cpe1 belongs to the papain-like cysteine protease family and is associated with toxin delivery pathways, including the type VI secretion system and contact-dependent growth inhibition. The structure of Cpe1 in complex with its immunity protein reveals a neutralization mechanism involving competitive substrate binding rather than active site occlusion, distinguishing it from previously characterized effector-immunity pairs. Our findings unveil a unique mode of interbacterial intoxication and provide insights into how bacteria protect themselves from self-poisoning by protease toxins.

microbiology↗

bioRxiv2024

Haplotype-aware multiomics unveils the regulatory basis of haplodiplontic life-cycle differentiation in a cosmopolitan marine alga

Gephyrocapsa huxleyi (formerly Emiliania huxleyi), a key coccolithophore alga influencing the global carbon cycle through photosynthesis and calcification, undergoes a haplodiplontic sexual life cycle with a calcifying non-flagellate diploid and a non-calcifying biflagellate haploid stage. To reveal the molecular basis of their morpho-physiological distinctions, we generated chromosome-level genome assemblies and compared the transcriptomes, proteomes, and methylomes for a pair of isogenic haploid and diploid model strains and conducted haplotype-aware analyses of their multiomic features. In addition to calcification and flagella, transcriptomes and proteomes of haploid and diploid cells modulate their differentiation in photosynthesis, sulfatases, DMSP degradation, DNA replication, and endomembrane system and transport. Haploid-diploid differential gene expression can be partially attributable to allelic imbalance (allele-specific expression) in diploid cells. Gene transcript abundance is positively associated with both CG and CHG gene-body DNA methylation, which can be inheritable, allele-specific, and differentiated between life-cycle phases. This multiomic study unravels the regulatory basis of unicellular algal life-cycle differentiation and provides valuable resources for investigating the ecologically important coccolithophore algae.

genomics↗

bioRxiv2021

ATP and Substrate Binding Regulates Conformational Changes of Human Peroxisomal ABC Transporter ALDP

The malfunction of ABCD1 causes X-linked adrenoleukodystrophy (X-ALD), a rare neurodegenerative disease that affect all tissues in human. Residing in the peroxisome membrane, ABCD1 plays a role in the translocation of very long chain fatty acids (VLCFA) for their damage by {beta}-oxidation. Here, we present five Cryo-Electron microscopy structures of ABCD1 in four conformational states. Combined with functional analysis, we found that substrate and ATP trigger the closing of two nucleotide binding domains (NBDs) over a distance of 40 [A] and the rearrangement of the transmembrane domains. Each of the three inward-facing structure of ABCD1 has a vestibule opens to cytosol with variable size. Furthermore, the structure of ABCD1 in the outward-facing state supports that ATP molecules pull the two NBDs together and open the transmembrane domain to the peroxisomal lumen for substrate release. The five structures provide a snapshot of substrate transporting cycle and mechanistic implications for disease-causing mutations.

biochemistry↗

bioRxiv2020

A novel platform to accelerate antimicrobial susceptibility testing in Neisseria gonorrhoeae using RNA signatures

The rise of antimicrobial-resistant pathogens can be attributed to the lack of a rapid pathogen identification (ID) or antimicrobial susceptibility testing (AST), resulting in delayed therapeutic decisions at the point of care. Gonorrhea is usually empirically treated with no AST results available before treatment, thus contributing to the rapid rise in drug resistance. Herein we present a rapid AST platform using RNA signatures for Neisseria gonorrhoeae (NG). RNA-seq followed by bioinformatic tools were applied to explore potential markers in the transcriptome profile of NG upon minutes of azithromycin exposure. Validation of candidate markers using PCR showed that two markers (arsR (NGO1562) and rpsO) can deliver accurate AST results across 14 tested isolates. Further validation of our cutoff in comparison to MIC across 64 more isolates confirmed the reliability of our platform. Our RNA markers combined with emerging molecular point-of-care systems has the potential to greatly accelerate both ID and AST to inform treatment.

molecular biology↗

bioRxiv2019

A Methylation Density Binary Classifier for Predicting and Optimizing the Performance of Methylation Biomarkers in Clinical Samples

BackgroundVariation in intercellular methylation patterns can complicate the use of methylation biomarkers for clinical diagnostic applications such as blood-based cancer testing. Here, we describe development and validation of a methylation density binary classification method called EpiClass (available for download at https://github.com/Elnitskilab/EpiClass), that can be used to predict and optimize the performance of methylation biomarkers, particularly in challenging, heterogeneous samples such as liquid biopsies. This approach is based upon leveraging statistical differences in single-molecule sample methylation density distributions to identify ideal thresholds for sample classification. ResultsWe developed and tested the classifier using reduced representation bisulfite sequencing (RRBS) data derived from ovarian carcinoma tissue DNA and controls. We used these data to perform in silico simulations using methylation density profiles from individual epiallelic copies of ZNF154, a genomic locus known to be recurrently methylated in numerous cancer types. From these profiles, we predicted the performance of the classifier in liquid biopsies for the detection of epithelial ovarian carcinomas (EOC). In silico analysis indicated that EpiClass could be leveraged to better identify cancer-positive liquid biopsy samples by implementing precise thresholds with respect to methylation density profiles derived from circulating cell-free DNA (cfDNA) analysis. These predictions were confirmed experimentally using DREAMing to perform digital methylation density analysis on a cohort of low volume (1-mL) plasma samples obtained from 26 EOC-positive and 41 cancer-free women. EpiClass performance was then validated in an independent cohort of 24 plasma specimens, derived from a longitudinal study of 8 EOC-positive women, and 12 plasma specimens derived from 12 healthy women, respectively, attaining a sensitivity/specificity of 91.7%/100.0%. Direct comparison of CA-125 measurements with EpiClass demonstrated that EpiClass was able to better identify EOC-positive women than standard CA-125 assessment. Finally, we used independent whole genome bisulfite sequencing (WGBS) datasets to demonstrate that EpiClass can also identify other cancer types as well or better than alternative methylation-based classifiers. ConclusionsOur results indicate that assessment of intramolecular methylation density distributions calculated from cfDNA facilitate the use of methylation biomarkers for diagnostic applications. Furthermore, we demonstrated that EpiClass analysis of ZNF154 methylation was able to outperform CA-125 in the detection of etiologically-diverse ovarian carcinomas, indicating the broad utility of ZNF154 for use as a biomarker of ovarian cancer.

bioinformatics↗