Biology subjects

Zhang, Y. J.

Publications and source records attributed to Zhang, Y. J..

4 recordsLinked to original sources

bioRxiv2024

Local delivery of cell surface-targeted immunocytokines programs systemic anti-tumor immunity

Cytokine therapies are potent immunotherapy agents but exhibit severe dose-limiting toxicities. One strategy to overcome this involves engineering cytokines for intratumoral retention following local delivery. Here, we develop a localized cytokine therapy that elicits profound anti-tumor immunity by engineered targeting to the ubiquitous leukocyte receptor CD45. We designed CD45-targeted immunocytokines (CD45-Cyt) that, upon injection, decorated the surface of leukocytes in the tumor and tumor-draining lymph node (TDLN) without systemic exposure. CD45-Cyt therapy eradicated both directly treated tumors and untreated distal lesions in multiple syngeneic mouse tumor models. Mechanistically, CD45-Cyt triggered prolonged pSTAT signaling and reprogrammed tumor-specific CD8+ T cells in the TDLN to exhibit an anti-viral transcriptional signature. CD45 anchoring represents a broad platform for protein retention by host immune cells for use in immunotherapy.

immunology↗

bioRxiv2024

Histone acetyltransferase HAF2 associates with PDC to control H3K14ac and H3K23ac in ethylene response

Ethylene plays its essential roles in plant development, growth, and defense responses by controlling the transcriptional reprogramming, in which EIN2-C-directed regulation of histone acetylation is the first key-step for chromatin to perceive ethylene signaling. However, the histone acetyltransferase in this process remains unknown. Here, we identified histone acetyltransferase HAF2, and mutations in HAF2 confer plants with ethylene insensitivity. Furthermore, we found that HAF2 interacts with EIN2-C in response to ethylene. Biochemical assays demonstrated that the bromodomain of HAF2 binds to H3K14ac and H3K23ac peptides with a distinct affinity for H3K14ac; the HAT domain possesses acetyltransferase catalytic activity for H3K14 and H3K23 acetylation, with a preference for H3K14. ChIP-seq results provide additional evidence supporting the role of HAF2 in regulating H3K14ac and H3K23ac levels in response to ethylene. Finally, our findings revealed that HAF2 co-functions with pyruvate dehydrogenase complex (PDC) to regulate H3K14ac and H3K23ac in response to ethylene in an EIN2 dependent manner. Overall, this research reveals that HAF2 as a histone acetyltransferase that forms a complex with EIN2-C and PDC, collectively governing histone acetylation of H3H14ac and H3K23ac, preferentially for H3K14 in response to ethylene.

plant biology↗

bioRxiv2022

LLPSWise - fast and accurate prediction of LLPS constituents

The recent discovery of different types of biological liquid-liquid phase separation (LLPS) systems presents enormous opportunities to uncover underlying biological mechanisms from a single-molecule level to mesoscopic scales and beyond. While progress has been made on the front of computational prediction of LLPS propensity of proteins, the constituent identification of LLPS systems continues to be a pertinent issue that has yet to be addressed. Compiled evidence indicates that the biological mechanism of LLPS involves the employment of different biomolecules into their liquid-liquid separation phase. Since constituent identification relies on experimental approaches, the process is arduous and inefficient. Here, we propose a sequence based LLPS propensity prediction method and scan the human proteome and biochemical pathways to establish a systematic biological view of LLPS. Additionally, we present a fast, accurate method for identifying the constituents of LLPS systems. The source code for our method is available via https://github.com/promethiume/LLPSWise

bioinformatics↗

bioRxiv2021

Deep learning redesign of PETase for practical PET degrading applications

Plastic waste poses an ecological challenge1. While current plastic waste management largely relies on unsustainable, energy-intensive, or even hazardous physicochemical and mechanical processes, enzymatic degradation offers a green and sustainable route for plastic waste recycling2. Poly(ethylene terephthalate) (PET) has been extensively used in packaging and for the manufacture of fabrics and single-used containers, accounting for 12% of global solid waste3. The practical application of PET hydrolases has been hampered by their lack of robustness and the requirement for high processing temperatures. Here, we use a structure-based, deep learning algorithm to engineer an extremely robust and highly active PET hydrolase. Our best resulting mutant (FAST-PETase: Functional, Active, Stable, and Tolerant PETase) exhibits superior PET-hydrolytic activity relative to both wild-type and engineered alternatives, (including a leaf-branch compost cutinase and its mutant4) and possesses enhanced thermostability and pH tolerance. We demonstrate that whole, untreated, post-consumer PET from 51 different plastic products can all be completely degraded by FAST-PETase within one week, and in as little as 24 hours at 50 {degrees}C. Finally, we demonstrate two paths for closed-loop PET recycling and valorization. First, we re-synthesize virgin PET from the monomers recovered after enzymatic depolymerization. Second, we enable in situ microbially-enabled valorization using a Pseudomonas strain together with FAST-PETase to degrade PET and utilize the evolved monomers as a carbon source for growth and polyhydroxyalkanoate production. Collectively, our results demonstrate the substantial improvements enabled by deep learning and a viable route for enzymatic plastic recycling at the industrial scale.

bioengineering↗