Mitogenomes provide new insights of evolutionary history of Boreheptagyiini and Diamesini (Diptera: Chironomidae: Diamesinae)

Mitogenomes have been widely used for phylogenetic reconstruction of various Dipteran groups, but specifically for chironomid, they have not been carried out to resolve the relationships. Diamesinae (Diptera: Chironomidae) are important bioindicators for freshwater ecosystem monitoring, but its evolutionary history remains uncertain for lack of information. Here, coupled with one previously published and 30 new mitogenomes of Diamesinae, we carried out comparative mitogenomic analysis and phylogenetic analysis. Mitogenomes of Diamesinae were conserved in structure, and all genes arranged in the same order as the ancestral insect mitogenome. All protein‐coding genes in Diamesinae were under stronger purifying selection than those of other nonbiting midge species, which may exhibit signs of adaptation to life at cold living conditions. Phylogenetic analyses strongly supported the monophyly of Diamesinae, with Boreheptagyiini deeply nested within Diamesini. In addition, phylogenetic relationship of selected six genera was resolved, except Sympotthastia remained unstable. Our study revealed that the mitogenomes of Diamesinae are highly conserved, and they are practically useful for phylogenetic inference.     

Chromosome-level genome assembly and characterization of Sophora Japonica

Sophora japonica is a medium-size deciduous tree belonging to Leguminosae family and famous for its high ecological, economic and medicinal value. Here, we reveal a draft genome of S. japonica, which was ∼511.49 Mb long (contig N50 size of 17.34 Mb) based on Illumina, Nanopore and Hi-C data. We reliably assembled 110 contigs into 14 chromosomes, representing 91.62% of the total genome, with an improved N50 size of 31.32 Mb based on Hi-C data. Further investigation identified 271.76 Mb (53.13%) of repetitive sequences and 31,000 protein-coding genes, of which 30,721 (99.1%) were functionally annotated. Phylogenetic analysis indicates that S. japonica separated from Arabidopsis thaliana and Glycine max ∼107.53 and 61.24 million years ago, respectively. We detected evidence of species-specific and common-legume whole-genome duplication events in S. japonica. We further found that multiple TF families (e.g. BBX and PAL) have expanded in S. japonica, which might have led to its enhanced tolerance to abiotic stress. In addition, S. japonica harbours more genes involved in the lignin and cellulose biosynthesis pathways than the other two species. Finally, population genomic analyses revealed no obvious differentiation among geographical groups and the effective population size continuously declined since 2 Ma. Our genomic data provide a powerful comparative framework to study the adaptation, evolution and active ingredients biosynthesis in S. japonica. More importantly, our high-quality S. japonica genome is important for elucidating the biosynthesis of its main bioactive components, and improving its production and/or processing.     

DeepMHADTA: Prediction of Drug-Target Binding Affinity Using Multi-Head Self-Attention and Convolutional Neural Network

Drug-target interactions provide insight into the drug-side effects and drug repositioning. However, wet-lab biochemical experiments are time-consuming and labor-intensive, and are insufficient to meet the pressing demand for drug research and development. With the rapid advancement of deep learning, computational methods are increasingly applied to screen drug-target interactions. Many methods consider this problem as a binary classification task (binding or not), but ignore the quantitative binding affinity. In this paper, we propose a new end-to-end deep learning method called DeepMHADTA, which uses the multi-head self-attention mechanism in a deep residual network to predict drug-target binding affinity. On two benchmark datasets, our method outperformed several current state-of-the-art methods in terms of multiple performance measures, including mean square error (MSE), consistency index (CI), rm2, and PR curve area (AUPR). The results demonstrated that our method achieved better performance in predicting the drug–target binding affinity.     

AvrRps4 effector family processing and recognition in lettuce

During pathogenesis, effector proteins are secreted from the pathogen to the host plant to provide virulence activity for invasion of the host. However, once the host plant recognizes one of the delivered effectors, effector‐triggered immunity activates a robust immune and hypersensitive response (HR). In planta, the effector AvrRps4 is processed into the N‐terminus (AvrRps4^N) and the C‐terminus (AvrRps4^C). AvrRps4^C is sufficient to trigger HR in turnip and activate AtRRS1/AtRPS4‐mediated immunity in Arabidopsis; on the other hand, AvrRps4^N induces HR in lettuce. Furthermore, AvrRps4^N‐mediated HR requires a conserved arginine at position 112 (R112), which is also important for full‐length AvrRps4 (AvrRps4^F) processing. Here, we show that effector processing and effector recognition in lettuce are uncoupled for the AvrRps4 family. In addition, we compared effector recognition by lettuce of AvrRps4 and its homologues, HopK1 and XopO. Interestingly, unlike for AvrRps4 and HopK1, mutation of the conserved R111 in XopO by itself was insufficient to abolish recognition. The combination of amino acid substitutions arginine 111 to leucine with glutamate 114 to lysine abolished the XopO‐mediated HR, suggesting that AvrRps4 family members have distinct structural requirements for perception by lettuce. Together, our results provide an insight into the processing and recognition of AvrRps4 and its homologues.     

SARS-CoV-2 envelope protein causes acute respiratory distress syndrome (ARDS)-like pathological damages and constitutes an antiviral target

Cytokine storm and multi-organ failure are the main causes of SARS-CoV-2-related death. However, the origin of excessive damages caused by SARS-CoV-2 remains largely unknown. Here we show that the SARS-CoV-2 envelope (2-E) protein alone is able to cause acute respiratory distress syndrome (ARDS)-like damages in vitro and in vivo. 2-E proteins were found to form a type of pH-sensitive cation channels in bilayer lipid membranes. As observed in SARS-CoV-2-infected cells, heterologous expression of 2-E channels induced rapid cell death in various susceptible cell types and robust secretion of cytokines and chemokines in macrophages. Intravenous administration of purified 2-E protein into mice caused ARDS-like pathological damages in lung and spleen. A dominant negative mutation lowering 2-E channel activity attenuated cell death and SARS-CoV-2 production. Newly identified channel inhibitors exhibited potent anti-SARS-CoV-2 activity and excellent cell protective activity in vitro and these activities were positively correlated with inhibition of 2-E channel. Importantly, prophylactic and therapeutic administration of the channel inhibitor effectively reduced both the viral load and secretion of inflammation cytokines in lungs of SARS-CoV-2-infected transgenic mice expressing human angiotensin-converting enzyme 2 (hACE-2). Our study supports that 2-E is a promising drug target against SARS-CoV-2.Subject terms: Cell death, Molecular biology     

不同血清型肉毒毒素受体结合域研究进展

肉毒毒素(botulinum neurotoxin, BoNT)是人类已知毒性最强的蛋白质之一,可以引起肌肉松弛麻痹,严重时可导致死亡。肉毒毒素共分为7种血清型(BoNT/A-BoNT/G),根据氨基酸序列差异可进一步分为40多种亚型。肉毒毒素分子结构由3个基本结构域组成：重链羧基端细胞受体结合域、氨基端的易位域和轻链催化域。在运动神经元表面,受体结合域首先与聚唾液酸神经节苷脂结合,随后与突触囊泡蛋白2或突触囊泡结合蛋白结合形成双受体复合物。每种血清型的受体结合域都必须与其相应受体结合才能发挥作用。肉毒毒素的结构功能及其对宿主的作用一直都是研究热点。近年来,因受体结合域可以促进肉毒毒素与运动神经元膜特异性结合,而成为新的研究方向。本综述将概述不同血清型肉毒毒素与受体结合过程中受体结合域结构变化和结合位点差异。通过分析不同血清型及亚型的序列以及受体结合域结构特征,可以更好地了解细胞受体结合域的序列差异和功能,并为肉毒毒素的治疗策略提供新思路。     

生物启发的细菌表面人造矿物壳:通过仿生矿化保护活细胞

【目的】生物启发的细菌表面仿生矿化人造矿物壳被用于保护活细胞。【方法】将细菌限制在坚固而完整的矿物壳中,有限的物理空间和物质交换使其暂时进行休眠,降低长期保存期间的活力损失以及提高在各种极端环境中的生存能力,并且能够通过酸去除矿物壳而重新激活细菌。【结果】相较于未仿生矿化的细菌(EcN),矿化细菌(EcN@CaCO₃)在32 d的储存实验中活力最高提升262倍;在pH 2.5的强酸环境中存活率提高837倍;在pH 12.0的强碱环境中存活率提高171倍;在80 ℃的高温条件下存活率提高59.1倍;甚至在抗生素溶液中,EcN@CaCO₃中细菌的存活率是EcN的729.7倍。【结论】本研究利用仿生矿化提高了细菌的保存稳定性,使其能在酸刺激下去除涂层恢复活性,也能在极端环境下保留细菌的活力,为微生物在环境生态、食品制造和生物医药等领域的应用提供研究基础。