Induction of Broadly Cross-Reactive Antibody Responses to SARS-CoV-2 Variants by S1 Nanoparticle Vaccines.

Despite the rapid deployment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines, the emergence of SARS-CoV-2 variants and reports of their immune evasion characteristics have led to an urgent need for novel vaccines that confer potent cross-protective immunity. In this study, we constructed three different SARS-CoV-2 spike S1-conjugated nanoparticle vaccine candidates that exhibited high structural homogeneity and stability. Notably, these vaccines elicited up to 50-times-higher neutralizing antibody titers than the S1 monomer in mice. Crucially, it was found that the S1-conjugated nanoparticle vaccine could elicit comparable levels of neutralizing antibodies against wild-type or emerging variant SARS-CoV-2, with cross-reactivity to SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV), the effect of which could be further enhanced using our designed nanoparticles. Our results indicate that the S1-conjugated nanoparticles are promising vaccine candidates with the potential to elicit potent and cross-reactive immunity against not only wild-type SARS-CoV-2, but also its variants of concern, variants of interest, and even other pathogenic betacoronaviruses. IMPORTANCE The emergence of SARS-CoV-2 variants led to an urgent demand for a broadly effective vaccine against the threat of variant infection. The spike protein S1-based nanoparticle designed in our study could elicit a comprehensive humoral response toward different SARS-CoV-2 variants of concern and variants of interest and will be helpful to combat COVID-19 globally.

Omics-guided bacterial engineering of Escherichia coli ER2566 for recombinant protein expression.

The goal of bacterial engineering is to rewire metabolic pathways to generate high-value molecules for various applications. However, the production of recombinant proteins is constrained by the complexity of the connections between cellular physiology and recombinant protein synthesis. Here, we used a rational and highly efficient approach to improve bacterial engineering. Based on the complete genome and annotation information of the Escherichia coli ER2566 strain, we compared the transcriptomic profiles of the strain under leaky expression and low temperature-induced stress. Combining the gene ontology (GO) enrichment terms and differentially expressed genes (DEGs) with higher expression, we selected and knocked out 36 genes to determine the potential impact of these genes on protein production. Deletion of bluF, cydA, mngR, and udp led to a significant decrease in soluble recombinant protein production. Moreover, at low-temperature induction, 4 DEGs (gntK, flgH, flgK, flgL) were associated with enhanced expression of the recombinant protein. Knocking out several motility-related DEGs (ER2666-ΔflgH-ΔflgL-ΔflgK) simultaneously improved the protein yield by 1.5-fold at 24 °C induction, and the recombinant strain had the potential to be applied in the expression studies of different exogenous proteins, aiming to improve the yields of soluble form to varying degrees in comparison to the ER2566 strain. Totally, this study focused on the anabolic and stress-responsive hub genes of the adaptation of E. coli to recombinant protein overexpression on the transcriptome level and constructs a series of engineering strains increasing the soluble protein yield of recombinant proteins which lays a solid foundation for the engineering of bacterial strains for recombinant technological advances. KEY POINTS: • Comparative transcriptome analysis shows host responses with altered induction stress. • Deletion of bluF, cydA, mngR, and udp genes was identified to significantly decrease the soluble recombinant protein productions. • Synchronal knockout of flagellar genes in E. coli can enhance recombinant protein yield up to ~ 1.5-fold at 24 °C induction. • Non-model bacterial strains can be re-engineered for recombinant protein expression.

A stepwise docking molecular dynamics approach for simulating antibody recognition with substantial conformational changes.

Conformational changes or rearrangements are common events during inter-biomolecular recognition. Tracking these changes are essential for exploring the allosteric mechanism and it is usually achieved by molecular dynamics simulation in silico. We previously identified a broad-neutralizing antibody against H5 influenza virus, 13D4, and solved the crystal structures of the free 13D4 Fab and its complex with hemagglutinin (HA). Structural comparison of the unbound and bound 13D4 Fabs showed that the heavy chain complementarity-determining region 3 (HCDR3) undergoes a substantial conformational rearrangement when it recognizes the receptor-binding site (RBS). Here, we used molecular dynamics (MD) to simulate the conformational changes that occur during antibody recognition. We showed that neither conventional MD nor steered MD could recapitulate the loop fitting of the RBS structure contour. Consequently, to simulate these challenging conformational changes, we engaged a stepwise docking MD method that allowed for the gradual docking of the ligand to receptor. This new method recapitulates the bound shape of the HCDR3 and provides the best approximation of the shape rendered by the co-crystal structure, with an RMSD of 0.926 Å. This strategy affords a flexible MD approach for simulating complicated conformational changes that occur during molecular recognition, and helps to provide an understanding of the involved allosteric mechanism.