In addition to causing cold and flu-like symptoms, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) can also cause chronic longer-term diseases. Antiviral drugs, especially used combinatorially, have the potential to reduce the severity of individual infections and prevent the development of chronic disease. One of the safest and most versatile reverse genetics systems for SARS-CoV-2 studies is a bacterial artificial chromosome (BAC)-based system harboring the WA1 strain full-length genome and attenuating deletions in the accessory open reading frame 3a and 7b proteins (ORF3a and ORF7b, respectively). Here, a scarless genome engineering technique called En Passant mutagenesis was used to change one amino acid in the viral main protease (Mpro P132) into the residue present in contemporary Omicron strains (H132), in order to more accurately study protease inhibitors and resistance mechanisms. This recombinant, attenuated viral system yields antiviral EC50 values for the active component of approved drugs including nirmatrelvir (Paxlovid) and ensitrelvir (Xocova) and, importantly, also enables a parallel assessment of drug efflux. For instance, the antiviral potency of nirmatrelvir improves 50-fold by inhibiting the P-Glycoprotein (P-Gp) transporter with ritonavir or tariquidar, whereas the potency of ensitrelvir is unaffected. This system also enables the safe isolation and characterization of viral variants with reduced sensitivity to drugs, as evidenced by Mpro M49L compromising the efficacy of ensitrelvir. Together, these systems combine to provide safe, reliable, and quantitative approaches for Mpro variant analysis and drug testing without the biosafety concerns of conducting these experiments using wildtype isolates. IMPORTANCE Safe genetic systems for studying coronavirus biology and developing next generation antivirals are important. One of the most versatile systems leverages a bacterial artificial chromosome to efficiently propagate and engineer a full-length SARS-CoV-2 genome. This system is also safe because it has crippling deletion mutations that limit virus replication to a small number of cell lines. Here, we use a genome engineering technology to change a single amino acid in the viruses’ main protease enzyme to match that of circulating Omicron isolates. The resulting attenuated virus was also used to demonstrate antiviral efficacy of approved drugs and uncover mutants with reduced drug sensitivity. The emergent mutants match those in a subset of circulating strains further demonstrating broad relevance.
This study constructed a pH-responsive P-TN/SF@Fe-Cur composite coating that demonstrated significant anti-infective, anti-inflammatory, antioxidant, pro-angiogenic, and pro-osteogenic effects in rat subcutaneous infection and femoral defect models.
The results show that alternative transcript diversity extensively enters translation-supported proteoform space and establish a systematic link between transcript variation and protein functional diversification.
Felicia T. Jiang, Dengwang Chen, Ziwei Wang et al.· bioRxiv· 1 citation
Protein therapeutic design and property prediction are frequently hampered by data scarcity. Here we propose a model, DyAb, that addresses these issues by leveraging a pair-wise representation to predict differences in binding affinity, rather than absolute values. DyAb is built on top of a pre-trained protein language model and achieves a Spearman rank correlation of up to 0.85 on binding affinity prediction across monoclonal antibodies targeting three different antigens (EGFR, IL-6, and an internal target), given as few as 100 training data. We employ DyAb in two design contexts: as a ranking model to score combinations of known mutations, and combined with a genetic algorithm to generate new sequences. Our method consistently generates antibody variants with high binding rates, including designs that improve on the binding affinity of the lead molecule by more than ten-fold. DyAb represents a powerful tool for optimizing antibody binding affinity in low data regimes common in early-stage drug development.
Joshua Yao-Yu Lin, Jennifer L. Hofmann, Andrew Leaver‐Fay et al.· mAbs· 1 citation
Due to its importance and wide adoption, wheat cultivation is promptly required to shift towards sustainable practices, reducing the dependency on chemical components. Among bio-based solutions aimed at securing the sustainability of wheat cultivation, biostimulants offer a versatile platform of eco-friendly tools assuring sustainability and profitability. Microalgae present a concrete example of a biostimulant source due to their richness in metabolites and high value products. Therefore, this study evaluated the biostimulant potential of eleven eco-extracts prepared from soil-isolated microalgae strains. Eco-extracts applied via soil drench at low dose (0.1 g/L) were investigated for their biostimulant effects on wheat growth, physiology, yield, and quality under controlled conditions. Results demonstrated significant ameliorations in treated plants as compared to the control, with no phytoinhibitory effects. Remarkable enhancements were notable in growth parameters such as shoot and root lengths (+40-70%), physiological traits such as total chlorophyll and stomatal conductance (+7-52%), yield components in the example of grain number per spike and thousand grain weight (+17-103%), and grain quality namely protein and polyphenol content (+2-fold to 4-fold). Similarly, phosphorus accumulation and uptake were significantly improved, while soil physicochemical status was ameliorated, indicating enhanced fertility. Multivariate analysis and composite index ranking marked Chlorella sp. GA18, Chlorella sp. GA65, Scenedesmus sp. GA69, and Chlorococcum sp. GA63 as eco-extracts with consistent performances across all plant traits. These findings highlighted the promising potential of integrating microalgae-based eco-friendly extracts in sustainable wheat cultivation.
Amer Chabili, Z. Hakkoum, F. Minaoui et al.· Plant Science· 1 citation
ProteinReasoner is developed, a multimodal generative protein foundation model that sequentially connects amino acid sequence, evolutionary constraints and three-dimensional structure within a shared autoregressive architecture and suggests a general route towards reasoning across interdependent representations in other scientific domains.
Chaozhong Liu, Linlin Chao, Shaomin Ji et al.· bioRxiv· 1 citation
HydroGym is introduced, a solver-independent reinforcement learning platform providing more than 60 validated, openly available flow control environments spanning from canonical laminar flows to complex turbulent flows, with systematic progression in the Reynolds number up to Re = 4 × 105, and Mach number variations in two and three dimensions.
Christian Lagemann, Sajeda Mokbel, Miro Gondrum et al.· Nature· 1 citation