Biology subjects

Tu, I.-P.

Publications and source records attributed to Tu, I.-P..

6 recordsLinked to original sources

bioRxiv2026

Structure-inspired design of Nsp8-based protein inhibitors to suppress SARS-CoV-2 replication

SARS-CoV-2 relies on a conserved RNA-dependent RNA polymerase (RdRp) complex composed of nsp12 and its cofactors nsp7 and nsp8 to replicate its RNA genome. Whereas most antiviral strategies target viral enzymes or surface proteins directly, an alternative approach is to disrupt the assembly or function of an essential viral molecular machine using a defective component derived from the pathogen itself. Here, guided by structural analyses of the nsp12-nsp7-nsp8 replication complex, we designed truncated nsp8 proteins that retain the ability to associate with nsp12 but are defective in engaging RNA. Using a purified nsp12-nsp7-nsp8 system capable of RNA primer extension, we show that selected truncated nsp8 variants inhibit polymerase activity when introduced into an otherwise functional complex. These results are consistent with a competitive mechanism in which the defective nsp8 variants associate with nsp12 and interfere with incorporation or function of wild-type nsp8, thereby compromising formation of a productive replication complex. To further explore this strategy, we used structure-guided in silico analysis of the nsp8-nsp12 interface to identify interaction hotspots and screened corresponding single-amino-acid substitutions. Several variants exhibited enhanced inhibitory activity in the reconstituted polymerase assay. Together, these findings establish a proof-of-concept strategy in which a structurally engineered, pathogen-derived protein can act as a dominant-negative inhibitor of an essential viral replication machinery. This approach provides a framework for developing protein- or peptide-based inhibitors that target conserved protein-protein interactions within viral replication complexes.

biochemistry↗

bioRxiv2025

A Hierarchical Robust Linear Model for Cryo-EM Map Analysis

Cryo-electron microscopy (cryo-EM) has become a central tool for determining the atomic structures of biological macromolecules, producing three-dimensional reconstruction maps that guide atomic model building. Current quantitative analyses of cryo-EM maps largely rely on simplified Gaussian signal models with fixed width parameters, limiting their ability to capture atom-specific signal characteristics directly from the maps. We propose a robust hierarchical linear (RHL) model for the statistical analysis of paired cryo-EM maps and atomic structures deposited in the EMDB and PDB. Within this framework, the logarithms of local voxel intensities surrounding each atom are modeled using a linearized Gaussian form, and atom-specific amplitude and width parameters are estimated through a hierarchical structure that pools information across atoms of the same type. The primary objective is to provide a statistically grounded framework for extracting quantitative atomic signal features from cryo-EM maps without imposing rigid physical assumptions on these parameters. To address contamination arising from overlapping atomic signals, spatially varying resolution, and experimental noise, we incorporate a data-adaptive weighting scheme based on minimum density power divergence estimation (MDPDE). This formulation preserves computational efficiency and ensures stable parameter estimation, while naturally facilitating the identification of deviated atomic profiles that may stem from model misspecification or local structural heterogeneity. Simulation studies demonstrate that the proposed method yields stable group-level parameter estimates even under substantial contamination. Applications to cryo-EM maps at multiple resolutions show that an atomic resolution (1.25 Angstrom) apoferritin map exhibits systematic atom-type differences in Gaussian amplitude and width, whereas a near-atomic-resolution map (2.20 Angstrom) shows closer agreement with conventional uniform-width assumptions. Beyondstructural biology, the proposed RHL framework provides a general statistical methodology for hierarchical data integration under heterogeneous noise, with potential applications in multi-center studies and federated learning.

bioinformatics↗

bioRxiv2024

Dynamic positioning of a TFIIE-related winged-helix domain in RNA polymerase elongation complex III underpins its multi-functionality

The tandem-winged-helix (tWH) domain of RNA polymerase III (Pol III) Rpc34 subunit is a multi-function hub in Pol III apparatus while the structure basis remains elusive. To probe tWH in Pol III elongation complex (EC), we engineered an azide-bearing unnatural amino acid into tWH and implemented a thiol-capping scheme to enable strain- promoted click reaction for selective dye labeling to suit single-molecule Forster resonance energy transfer (smFRET). Our discrete smFRET results and nano-positioning analysis reveal multiple docking sites of Rpc34 WH2 on Pol III EC with characteristic dwell-times, reflecting promiscuous and weak interactions underpinning tWHs multi-functionality. The docking sites include one overlapping with that during initiation and others on transcription bubble and downstream DNA, previously unreported. This work provides mechanistic insights into Pol III transcription re-initiation and elongation, with useful bio-orthogonal strategies for studying structural dynamics of large native protein complexes.

biophysics↗

bioRxiv2023

Use of phase plate cryo-EM reveals conformation diversity of therapeutic IgG with 50 kDa Fab fragment resolved below 6 angstrom

While cryogenic electron microscopy (cryo-EM) is fruitfully used for harvesting high-resolution structures of sizable macromolecules, its application to small or flexible proteins composed of domains like immunoglobulin (IgG) remain challenging. Here, we applied single particle cryo-EM to Rituximab, a therapeutic IgG mediating cancer cell toxicity, to explore its solution conformations. We found Rituximab molecules exhibited aggregates in cryo-EM specimens contrary to its solution behavior, and utilized a non-ionic detergent to successfully disperse them as isolated particles amenable to single particle analysis. As the detergent adversely reduced the protein-to-solvent contrast, we employed phase plate contrast to mitigate the impaired protein visibility. Assisted by phase plate imaging, we obtained a canonical three-arm IgG structure with other structures displaying variable arm densities co-existing in solution, affirming high flexibility of arm-connecting linkers. Furthermore, we showed phase plate imaging enables reliable structure determination of Fab to sub-nanometer resolution from ab initio, yielding a characteristic two-lobe structure that could be unambiguously docked with crystal structure. Our findings revealed conformation diversity of IgG and demonstrated phase plate was viable for cryo-EM analysis of small proteins without symmetry. This work helps extend cryo-EM boundaries, providing a valuable imaging and structural analysis framework for macromolecules with similar challenging features.

biochemistry↗

bioRxiv2023

Growth-dependent concentration gradient of the oscillating Min system in Escherichia coli

The Min system contributes to the spatiotemporal regulation of division sites in Escherichia coli. The MinD and MinE proteins of this system self-organize into oscillatory waves in the form of concentration gradients. How the intracellular Min protein concentration gradients are coordinated with cell growth to achieve spatiotemporal accuracy of cell division is unknown. Here, we report that the MinD concentration gradient becomes progressively steeper as cells elongate, suggesting that the division inhibitory activity at the midcell also decreases with cell growth. Interestingly, the oscillation period appears relatively stable across different cell lengths. Similar features were found in cells under carbon stress conditions, but the gradient was even steeper, likely favoring division at shorter cell lengths. The length-dependent variation of the concentration gradient was further examined in silico using a reaction-diffusion model, which not only supported the above features, but also revealed a decrease in the midcell concentration as the shape of the gradient becomes steeper in growing cells. This growth-dependent regulation of the midcell concentration of MinD may be coupled with the FtsZ ring formation through the MinD-interacting protein MinC. We found that the variable concentration gradients occur by coordinating the reaction rates of the recruitment of MinD and MinE to the membrane and the recharging of MinD with ATP in the cytoplasm. In conclusion, this work uncovers the plasticity of MinD concentration gradients during interpolar oscillations throughout cell growth, an intrinsic property integrated during cell division.

cell biology↗

bioRxiv2022

RE2DC: a robust and efficient 2D classifier with visualization for processing massive and heterogeneous cryo-EM data

Single-particle cryo-electron microscopy (cryo-EM) increasingly generates millions of particle images, yet two-dimensional (2D) classification remains a major bottleneck because existing approaches balance computational efficiency against robustness to noise, outliers and structural heterogeneity. We introduce RE2DC (Robust and Efficient 2D Classifier), an algorithmic framework that resolves this trade-off through dynamic linear-time clustering, dimension-reduction multi-reference alignment, and offers real-time interactive t-SNE visualization. Rather than relying primarily on hardware acceleration, RE2DC reduces the computational cost of robust clustering and employs de-noised images for alignment, enabling efficient execution on standard multi-core CPUs. Across diverse benchmark datasets, RE2DC achieves class homogeneity comparable to ISAC while processing datasets three- to ten-fold faster per classification round than RELION. Notably, RE2DC resolves rare, structurally coherent particle populations, enabling detection of transient conformational intermediates and supporting near real-time cryo-EM analysis. By addressing algorithmic complexity, RE2DC establishes a general framework for robust, scalable analysis of massive and heterogeneous image datasets.

bioinformatics↗