Biology subjects

YU, Z.

Publications and source records attributed to YU, Z..

2 recordsLinked to original sources

bioRxiv2026

art_modern: An Accelerated ART Simulator of Diverse Next-Generation Sequencing Reads

SummaryFast simulation of next-generation sequencing (NGS) data is vital for software development and benchmarking. Here we describe art_modern, an accelerated ART simulator that can simulate various NGS data. We accelerated ART using updated sampling algorithms, single-instruction multiple-data (SIMD) instruction-set extensions (ISEs), thread- and node-level parallelism, and an asynchronous output writer, while enabling simulation of transcriptome profiling data by supporting contig-specific coverage with strand information. The new implementation was benchmarked against popular performance-oriented NGS simulators, revealing a 75-77% reduction in CPU time and a 15-24 times acceleration in wall-clock time on a multi-core machine compared to the original implementation. With this simulator, the process of developing and benchmarking NGS sequence analysis algorithms can be largely accelerated. Availability and ImplementationThe software is implemented in C++17 with CMake as the building system. It can be built and executed on a modern GNU/Linux operating system with Boost, Zlib, and a C++17 compiler, with further acceleration available using Intel OneAPI C++/DPC++ compilers and Intel oneAPI MKL random generators. The software is available at https://github.com/YU-Zhejian/art_modern under the GNU General Public License v3. ContactZhejian Yu (yuzj25@seas.upenn.edu)

bioinformatics↗

bioRxiv2024

Bispecific antibody targeting of lipid nanoparticles

Lipid nanoparticles (LNP) are the most clinically advanced non-viral gene delivery system. While progress has been made for enhancing delivery, cell specific targeting remains a challenge. Targeting moieties such as antibodies can be chemically-conjugated to LNPs however, this approach is complex and has challenges for scaling up. Here, we developed an approach to generate antibody-conjugated LNPs that utilizes a bispecific antibody (bsAb) as the targeting bridge. As a docking site for the bsAb, we generated LNPs with a short epitope, derived from hemagglutinin antigen (HA), embedded in the PEG component of the particle (LNPHA). We generated bsAb in which one domain binds HA and the other binds different cell surface proteins, including PD-L1, CD4, CD5, and SunTag. Non-chemical conjugation of the bsAb and LNP resulted in a major increase in the efficiency and specificity of transfecting cells expressing the cognate target. LNP/bsAb mediated a 4-fold increase in in vivo transfection of PD-L1 expressing cancer cells, and a 26-fold increase in ex vivo transfection of quiescent primary human T cells. Additionally, we created a universal bsAb recognizing HA and anti-rat IgG2, enabling LNP tethering to off-the-shelf antibodies such as CD4, CD8, CD20, CD45, and CD3. By utilizing a molecular dock and bsAb technology, these studies demonstrate a simple and effective strategy to generate antibody-conjugated LNPs, enabling precise and efficient mRNA delivery.

bioengineering↗