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Biomedical subjects

Huimin Zhao

Publications and source records attributed to Huimin Zhao.

5 recordsLinked to original sources
PubMed2026

Accelerating natural product discovery, characterization and engineering by biofoundries.

Covering: From early developments to the presentNatural product (NP) discovery is increasingly constrained by low-throughput screening, repeated rediscovery, and challenges in scaling genome mining-guided validation workflows. This highlight examines how automated biofoundries are accelerating NP discovery, characterization, and engineering through integrated design-build-test-learn (DBTL) cycles. We discuss recent advances in phenotype-first and genome-first discovery strategies enabled by robotics, high-throughput pathway reconstitution, and automated screening platforms. We further highlight emerging technologies, including cell-free biosynthesis, automated culturomics, programmable chassis engineering, and AI-assisted workflow orchestration, that may enable increasingly autonomous biofoundries for scalable exploration of NP chemical space and therapeutic discovery.

Journal Article↗
PubMed2026

Discovery and engineering of enzymes for new-to-nature photobiocatalysis.

Photobiocatalysis integrates enzymatic catalysis with photochemistry, enabling challenging radical transformations with high selectivity under mild conditions. Early developments in this field were largely driven by the discovery that enzyme-bound cofactors can form photoactive charge-transfer complexes with substrates, thereby initiating radical chemistry upon light irradiation. Recent advances, however, have substantially expanded the mechanistic landscape of photobiocatalysis through diverse mechanisms. This review summarizes major developments in photobiocatalysis reported since 2024. Rather than cataloging individual reactions, we focus on the fundamental mechanisms of radical generation and interception within enzyme active sites, and discuss how these mechanistic principles guide the discovery, engineering, and design of enzymes for new-to-nature photobiocatalysis.

Protein Engineering↗
PubMed2026

Acidic transcription factors position the genome at nuclear speckles through transcription-dependent and -independent mechanisms.

A small fraction of the genome reproducibly positions near nuclear speckles (NSs), increasing the expression and/or splicing efficiency of NS-associated genes. How specific genomic regions in mammalian cells are targeted to NSs remains unclear. Here, we demonstrate the establishment of genome-wide NS association without active transcription. We show that DNA sequences derived from NS-associated regions, when integrated as transgenes, are autonomously targeted to NSs. By systematically dissecting one such genomic locus, the COL1A1-SGCA locus, we identified redundant NS-targeting cis-regulatory elements, including an ∼600-bp fragment with 17 binding motifs for 8 transcription factors (TFs). Four NS-targeting TFs within this fragment contain acidic activation domains (AADs) that provide both chromatin-context and transcription-dependent NS targeting, properties that appear to be common among several other tested AADs. A subset of acidic activator TFs contains an additional, transcription-independent NS-targeting activity. Our findings establish diverse and partially redundant NS-targeting activities, which may facilitate dynamic gene positioning at the NS periphery for context-specific transcriptional responses.

Transcription, Genetic↗
PubMed2025

Synteny plot quality control with SyntenyQC.

SUMMARY: SyntenyQC is a data pre-processing tool for the construction of synteny plots. It supports genomic data collection, annotation and dereplication to facilitate (and in some cases fundamentally enable) the construction of informative synteny plots. AVAILABILITY AND IMPLEMENTATION: SyntenyQC is a command line app developed using Python version 3.10 and tested using pytest. SyntenyQC is available on PyPI (https://pypi.org/project/SyntenyQC) under the MIT License, along with a detailed user tutorial. Package tests can be viewed at https://github.com/Tim-Kirkwood/SyntenyQC.

Synteny↗