Biology subjects

Yu, X.-H.

Publications and source records attributed to Yu, X.-H..

3 recordsLinked to original sources

bioRxiv2020

Rapid development of SARS-CoV-2 receptor binding domain-conjugated nanoparticle vaccine candidate

The ongoing of coronavirus disease 2019 (COVID-19) pandemic caused by novel SARS-CoV-2 coronavirus, resulting in economic losses and seriously threating the human health in worldwide, highlighting the urgent need of a stabilized, easily produced and effective preventive vaccine. The SARS-COV-2 spike protein receptor binding region (RBD) plays an important role in the process of viral binding receptor angiotensin-converting enzyme 2 (ACE2) and membrane fusion, making it an ideal target for vaccine development. In this study, we designed three different RBD-conjugated nanoparticles vaccine candidates, RBD-Ferritin (24-mer), RBD-mi3 (60-mer) and RBD-I53-50 (120-mer), with the application of covalent bond linking by SpyTag-SpyCatcher system. It was demonstrated that the neutralizing capability of sera from mice immunized with three RBD-conjugated nanoparticles adjuvanted with AddaVax or Sigma Systerm Adjuvant (SAS) after each immunization was ~8-to 120-fold greater than monomeric RBD group in SARS-CoV-2 pseudovirus and authentic virus neutralization assay. Most importantly, sera from RBD-conjugated NPs groups more efficiently blocked the binding of RBD to ACE2 or neutralizing antibody in vitro, a further proof of promising immunization effect. Besides, high physical stability and flexibility in assembly consolidated the benefit for rapid scale-up production of vaccine. These results supported that our designed SARS-CoV-2 RBD-conjugated nanoparticle was competitive vaccine candidate and the carrier nanoparticles could be adopted as universal platform for future vaccine development.

microbiology↗

bioRxiv2020

A consensus-based ensemble approach to improve de novo transcriptome assembly

BackgroundSystems-level analyses, such as differential gene expression analysis, co-expression analysis, and metabolic pathway reconstruction, depend on the accuracy of the transcriptome. Multiple tools exist to perform transcriptome assembly from RNAseq data. However, assembling high quality transcriptomes is still not a trivial problem. This is especially the case for non-model organisms where adequate reference genomes are often not available. Different methods produce different transcriptome models and there is no easy way to determine which are more accurate. Furthermore, having alternative-splicing events exacerbates such difficult assembly problems. While benchmarking transcriptome assemblies is critical, this is also not trivial due to the general lack of true reference transcriptomes. ResultsIn this study, we first provide a pipeline to generate a set of the benchmark transcriptome and corresponding RNAseq data. Using the simulated benchmarking datasets, we compared the performance of various transcriptome assembly approaches including both de novo and genome-guided methods. The results showed that the assembly performance deteriorates significantly when alternative transcripts (isoforms) exist or for genome-guided methods when the reference is not available from the same genome. To improve the transcriptome assembly performance, leveraging the overlapping predictions between different assemblies, we present a new consensus-based ensemble transcriptome assembly approach, ConSemble. ConclusionsWithout using a reference genome, ConSemble using four de novo assemblers achieved an accuracy up to twice as high as any de novo assemblers we compared. When a reference genome is available, ConSemble using four genome-guided assemblies removed many incorrectly assembled contigs with minimal impact on correctly assembled contigs, achieving higher precision and accuracy than individual genome-guided methods. Furthermore, ConSemble using de novo assemblers matched or exceeded the best performing genome-guided assemblers even when the transcriptomes included isoforms. We thus demonstrated that the ConSemble consensus strategy both for de novo and genome-guided assemblers can improve transcriptome assembly. The RNAseq simulation pipeline, the benchmark transcriptome datasets, and the script to perform the ConSemble assembly are all freely available from: http://bioinfolab.unl.edu/emlab/consemble/.

bioinformatics↗

bioRxiv2020

Structural Basis for Ca2+-Dependent Activation of a Plant Metacaspase

Plants metacaspases mediate programmed cell death in development 1,2, biotic and abiotic stresses 3, damage-induced immune response 4, and resistance to pathogen attack 5. Most metacaspases require Ca2+ for their activation and substrate processing 6-8. However, the Ca2+-dependent activation mechanism remains elusive 9-11. Here we report the crystal structure of Metacaspase 4 from Arabidopsis thaliana (AtMC4) that modulates Ca2+-dependent, damage-induced plant immune defense. The AtMC4 structure exhibits an inhibitory conformation in which a large linker domain blocks activation and substrate access. In addition, the side chain of Lys225 in the linker domain blocks the active site by sitting directly between two catalytic residues. We show that the activation of AtMC4 and cleavage of its physiological substrate involve multiple cleavages in the linker domain upon activation by Ca2+. Our analysis provides insight into the Ca2+-dependent activation of AtMC4 and lays the basis for tuning its activity in response to stresses that may help engineer more sustainable crops for production of food and biofuel.

biochemistry↗