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Abstract Background Thermostability is a fundamental property of proteins to maintain their biological functions. Predicting protein stability changes upon mutation is important for our understanding protein structure–function relationship, and is also of great interest in protein engineering and pharmaceutical design. Results Here we present mutDDG-SSM, a deep learning-based framework that uses the geometric representations encoded in protein structure to predict the mutation-induced protein stability changes. mutDDG-SSM consists of two parts: a graph attention network-based protein structural feature extractor that is trained with a self-supervised learning scheme using large-scale high-resolution protein structures, and an eXtreme Gradient Boosting model-based stability change predictor with an advantage of alleviating overfitting problem. The performance of mutDDG-SSM was tested on several widely-used independent datasets. Then, myoglobin and p53 were used as case studies to illustrate the effectiveness of the model in predicting protein stability changes upon mutations. Our results show that mutDDG-SSM achieved high performance in estimating the effects of mutations on protein stability. In addition, mutDDG-SSM exhibited good unbiasedness, where the prediction accuracy on the inverse mutations is as well as that on the direct mutations. Conclusion Meaningful features can be extracted from our pre-trained model to build downstream tasks and our model may serve as a valuable tool for protein engineering and drug design.

Abstract An ongoing randomized, double-blind, controlled phase 2 trial was conducted to evaluate the safety and immunogenicity of a mosaic-type recombinant vaccine candidate, named NVSI-06-09, as a booster dose in subjects aged 18 years and older from the United Arab Emirates (UAE), who had administered two or three doses of inactivated vaccine BBIBP-CorV at least 6 months prior to enrollment. The participants were randomly assigned with 1:1 to receive a booster dose of NVSI-06-09 or BBIBP-CorV. The primary outcomes were immunogenicity and safety against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant, and the exploratory outcome was cross-immunogenicity against other circulating strains. Between May 25 and 30, 2022, 516 adults received booster vaccination with 260 in NVSI-06-09 group and 256 in BBIBP-CorV group. Interim results showed a similar safety profile between two booster groups, with low incidence of adverse reactions of grade 1 or 2. For immunogenicity, by day 14 post-booster, the fold rises in neutralizing antibody geometric mean titers (GMTs) from baseline elicited by NVSI-06-09 were remarkably higher than those by BBIBP-CorV against the prototype strain (19.67 vs 4.47-fold), Omicron BA.1.1 (42.35 vs 3.78-fold), BA.2 (25.09 vs 2.91-fold), BA.4 (22.42 vs 2.69-fold), and BA.5 variants (27.06 vs 4.73-fold). Similarly, the neutralizing GMTs boosted by NVSI-06-09 against Beta and Delta variants were also 6.60-fold and 7.17-fold higher than those by BBIBP-CorV. Our findings indicated that a booster dose of NVSI-06-09 was well-tolerated and elicited broad-spectrum neutralizing responses against divergent SARS-CoV-2 variants, including Omicron and its sub-lineages.

Abstract The increased coronavirus disease 2019 (COVID-19) breakthrough cases pose the need of booster vaccination. We conducted a randomised, double-blinded, controlled, phase 2 trial to assess the immunogenicity and safety of the heterologous prime-boost vaccination with an inactivated COVID-19 vaccine (BBIBP-CorV) followed by a recombinant protein-based vaccine (NVSI-06-07), using homologous boost with BBIBP-CorV as control. Three groups of healthy adults (600 individuals per group) who had completed two-dose BBIBP-CorV vaccinations 1–3 months, 4–6 months and ≥6 months earlier, respectively, were randomly assigned in a 1:1 ratio to receive either NVSI-06-07 or BBIBP-CorV boost. Immunogenicity assays showed that in NVSI-06-07 groups, neutralizing antibody geometric mean titers (GMTs) against the prototype SARS-CoV-2 increased by 21.01–63.85 folds on day 28 after vaccination, whereas only 4.20–16.78 folds of increases were observed in control groups. For Omicron variant, the neutralizing antibody GMT elicited by homologous boost was 37.91 on day 14, however, a significantly higher neutralizing GMT of 292.53 was induced by heterologous booster. Similar results were obtained for other SARS-CoV-2 variants of concerns (VOCs), including Alpha, Beta and Delta. Both heterologous and homologous boosters have a good safety profile. Local and systemic adverse reactions were absent, mild or moderate in most participants, and the overall safety was quite similar between two booster schemes. Our findings indicated that NVSI-06-07 is safe and immunogenic as a heterologous booster in BBIBP-CorV recipients and was immunogenically superior to the homologous booster against not only SARS-CoV-2 prototype strain but also VOCs, including Omicron.

Large-scale populations in the world have been vaccinated with COVID-19 vaccines, however, breakthrough infections of SARS-CoV-2 are still growing rapidly due to the emergence of immune-evasive variants, especially Omicron. It is urgent to develop effective broad-spectrum vaccines to better control the pandemic of these variants. Here, we present a mosaic-type trimeric form of spike receptor-binding domain (mos-tri-RBD) as a broad-spectrum vaccine candidate, which carries the key mutations from Omicron and other circulating variants. Tests in rats showed that the designed mos-tri-RBD, whether used alone or as a booster shot, elicited potent cross-neutralizing antibodies against not only Omicron but also other immune-evasive variants. Neutralizing antibody ID50 titers induced by mos-tri-RBD were substantially higher than those elicited by homo-tri-RBD (containing homologous RBDs from prototype strain) or the BIBP inactivated COVID-19 vaccine (BBIBP-CorV). Our study indicates that mos-tri-RBD is highly immunogenic, which may serve as a broad-spectrum vaccine candidate in combating SARS-CoV-2 variants including Omicron.

Norovirus (NoV) is the major pathogen causing the outbreaks of the viral gastroenteritis across the world. Among the various genotypes of NoV, GII.4 is the most predominant over the past decades. GII.4 NoVs interact with the histo-blood group antigens (HBGAs) to invade the host cell, and it is believed that the receptor HBGAs may play important roles in selecting the predominate variants by the nature during the evolution of GII.4 NoVs. However, the evolution-induced changes in the HBGA-binding affinity for the GII.4 NoV variants and the mechanism behind the evolution of the NoV-HBGA interactions remain elusive. In the present work, the virus-like particles (VLPs) of the representative GII.4 NoV stains epidemic in the past decades were expressed by using the Hansenula polymorpha yeast expression platform constructed by our laboratory, and then the enzyme linked immunosorbent assay (ELISA)-based HBGA-binding assays as well as the molecular dynamics (MD) simulations combined with the molecular mechanics/generalized born surface area (MMGBSA) calculations were performed to investigate the interactions between various GII.4 strains and different types of HBGAs. The HBGA-binding assays show that for all the studied types of HBGAs, the evolution of GII.4 NoVs results in the increased NoV-HBGA binding affinities, where the early epidemic strains have the lower binding activity and the newly epidemic strains exhibit relative stronger binding intensity. Based on the MD simulation and MMGBSA calculation results, a physical mechanism that accounts for the increased HBGA-binding affinity was proposed. The evolution-involved residue mutations cause the conformational rearrangements of loop-2 (residues 390-396), which result in the narrowing of the receptor-binding pocket and thus tighten the binding of the receptor HBGAs. Our experimental and computational studies are helpful for better understanding the mechanism behind the evolution-induced increasing of HBGA-binding affinity, which may provide useful information for the drug and vaccine designs against GII.4 NoVs.

In this paper, a method for waste incineration slag is proposed. An incineration acidification alkalization modification was carried out based on the characteristics of the oxides (SiO2, CaO, Al2O3, Fe2O3, and MgO) of waste incineration slag. With modified slag as the carrier and NaHCO3 as the supporter, a slag-based composite powder explosion inhibitor was prepared with the solvent-crystallization wet coating (WCSC), ball milling dry coating (DCBM), and air impact dry coating (DCAI) methods. The advantages and disadvantages of the three methods were compared and analyzed. Explosion suppression experiments on oil shale dust were carried out, and the explosion suppression mechanism was described. The explosion suppression process of the modified slag–NaHCO3 composite powder explosion inhibitor for oil shale dust was found to involve a synergy of physical and chemical inhibition. This explosion suppression mechanism indicates three requirements for the preparation and application of industrial solid waste-based composite powder explosion inhibitors. The feasibility of preparing composite powder explosion inhibitors from waste incinerator slag was discussed from the experimental point of view and its explosion suppression performance on oil shale dust was studied with the intention of providing a new form of resource utilization for waste incinerator slag.

BackgroundThe UHRF1 gene is an epigenetic modification factor that mediates tumor suppressor gene silencing in a variety of cancers. Related studies have reported that UHRF1 can inhibit the expression of the KISS1 gene. However, the regulatory mechanism underlying UHRF1 expression in colorectal cancer (CRC) is still unclear. The aim of this study was to gain a better understanding of the regulation of UHRF1 expression in CRC and to determine whether it regulates the mechanism by which KISS1 promotes CRC metastasis.MethodsIn the present study, the levels of miR-506, UHRF1 and KISS1 expression in CRC tissues and in human CRC cell lines were studied using quantitative real-time PCR (qRT-PCR) and Western blotting. Cell proliferation, migration, and invasion assays are used to detect cell proliferation, migration, and invasion. A dual-luciferase reporter system was used to confirm the target gene of miR-506.ResultsThis study found that UHRF1 protein is highly expressed in CRC tissues and negatively correlated with KISS1 protein expression. UHRF1 overexpression activates the PI3K/NF-κB signaling pathway by inhibiting the mRNA expression levels of pathway mediators. Bioinformatics analysis and luciferase reporter gene assays confirmed that miR-506 targets UHRF1.ConclusionThis study identified the regulation of UHRF1 expression in CRC and the mechanism of CRC metastasis. UHRF1 may be a new potential target molecule for future CRC metastasis treatment.

Expression of inflammatory genes is determined in part by post-transcriptional regulation of mRNA metabolism but how stimulus- and transcript-dependent nuclear export influence is poorly understood. Here, we report a novel pathway in which LPS/TLR4 engagement promotes nuclear localization of IRAK2 to facilitate nuclear export of a specific subset of inflammation-related mRNAs for translation in murine macrophages. IRAK2 kinase activity is required for LPS-induced RanBP2-mediated IRAK2 sumoylation and subsequent nuclear translocation. Array analysis showed that an SRSF1-binding motif is enriched in mRNAs dependent on IRAK2 for nuclear export. Nuclear IRAK2 phosphorylates SRSF1 to reduce its binding to target mRNAs, which promotes the RNA binding of the nuclear export adaptor ALYREF and nuclear export receptor Nxf1 loading for the export of the mRNAs. In summary, LPS activates a nuclear function of IRAK2 that facilitates the assembly of nuclear export machinery to export selected inflammatory mRNAs to the cytoplasm for translation.

Abstract Background One of the essential processing events during pre-mRNA maturation is the post-transcriptional addition of a polyadenine [poly(A)] tail. The 3'-end poly(A) track protects mRNA from unregulated degradation, and indicates the integrity of mRNA through recognition by mRNA export and translation machinery. The position of a poly(A) site is predetermined by signals in the pre-mRNA sequence that are recognized by a complex of polyadenylation factors. These signals are generally tri-part sequence patterns around the cleavage site that serves as the future poly(A) site. In plants, there is little sequence conservation among these signal elements, which makes it difficult to develop an accurate algorithm to predict the poly(A) site of a given gene. We attempted to solve this problem. Results Based on our current working model and the profile of nucleotide sequence distribution of the poly(A) signals and around poly(A) sites in Arabidopsis, we have devised a Generalized Hidden Markov Model based algorithm to predict potential poly(A) sites. The high specificity and sensitivity of the algorithm were demonstrated by testing several datasets, and at the best combinations, both reach 97%. The accuracy of the program, called poly(A) site sleuth or PASS, has been demonstrated by the prediction of many validated poly(A) sites. PASS also predicted the changes of poly(A) site efficiency in poly(A) signal mutants that were constructed and characterized by traditional genetic experiments. The efficacy of PASS was demonstrated by predicting poly(A) sites within long genomic sequences. Conclusion Based on the features of plant poly(A) signals, a computational model was built to effectively predict the poly(A) sites in Arabidopsis genes. The algorithm will be useful in gene annotation because a poly(A) site signifies the end of the transcript. This algorithm can also be used to predict alternative poly(A) sites in known genes, and will be useful in the design of transgenes for crop genetic engineering by predicting and eliminating undesirable poly(A) sites.