Cryo-electron microscopy reveals the membrane insertion mechanism of V. cholerae hemolysin

Vibrio cholerae hemolysin (HlyA) is a 65?kDa pore-forming toxin which causes lysis of target eukaryotic cells by forming heptameric channels in the plasma membrane. Deletion of the 15?kDa C-terminus β-prism carbohydrate-binding domain generates a 50?kDa truncated variant (HlyA50) with 1000-fold-reduced pore-forming activity. Previously, we showed by cryo-electron microscopy that the two toxin oligomers have central channels, but the 65?kDa toxin oligomer is a seven-fold symmetric structure with bowl-, ring-, and arm-like domains, whereas the 50?kDa oligomer is an asymmetric jar-like heptamer. In the present study, we determined three-dimensional(3D) structures of HlyA and HlyA50 in presence of erythrocyte stroma and observed that interaction of the 65?kDa toxin with the stroma induced a significant decrease in the height of the β-barrel oligomer with a change in conformation of the ring- and arm-like domains of HlyA. These features were absent in interaction of HlyA50 with stroma. We propose that this conformational transition is critical for membrane-insertion of the toxin.     

Linking behavioral states to landscape features for improved conservation management

1. A central theme for conservation is understanding how animals differentially use, and are affected by change in, the landscapes they inhabit. However, it has been challenging to develop conservation schemes for habitat‐specific behaviors.
2. Here we use behavioral change point analysis to identify behavioral states of golden eagles (Aquila chrysaetos) in the Sonoran and Mojave Deserts of the southwestern United States, and we identify, for each behavioral state, conservation‐relevant habitat associations.
3. We modeled behavior using 186,859 GPS points from 48 eagles and identified 2,851 distinct segments comprising four behavioral states. Altitude above ground level (AGL) best differentiated behavioral states, with two clusters of short‐distance movement behaviors characterized by low AGL (state 1 AGL = 14 m (median); state 2 AGL = 11 m) and two associated with longer‐distance movement behaviors and characterized by higher AGL (state 3 AGL = 108 m; state 4 AGL = 450 m).
4. Behaviors such as perching and low‐altitude hunting were associated with short‐distance movements in updraft‐poor environments, at higher elevations, and over steeper and more north‐facing terrain. In contrast, medium‐distance movements such as hunting and transiting were over gentle and south‐facing slopes. Long‐distance transiting occurred over the desert habitats that generate the best updraft.
5. This information can guide management of this species, and our approach provides a template for behavior‐specific habitat associations for other species of management concern.

     

“dendRoAnalyst”: A tool for processing and analysing dendrometer data

Dendrometers are vital tools for studying the response of trees to intra-annual environmental changes in different temporal resolutions, ranging from hourly, daily to weekly time resolution. Dendrometers are increasingly used in forest management and tree physiological studies. Besides the data analysis, data processing is also challenging, time-consuming and potentially error-prone due to the immense number of measurements generated by self-registering electronic dendrometers. We present the package ‘dendRoAnalyst’ based on R statistical software to process and analyse dendrometer data using various approaches. This package offers algorithms for handling and pre-cleaning of dendrometer data before the application of subsequent data analytical steps. This includes identifying and erasing artefacts in dendrometer datasets not related to actual stem circumference change, identifying data gaps within records, and the possibility of change(s) in temporal resolution. Furthermore, the package can calculate different daily statistics of dendrometer data, including the daily amplitude of tree growth. The package dendRoAnalyst is therefore intended to facilitate researchers with a collection of functions for handling and analysing dendrometer data.     

Adjusting for Nonignorable Missingness When Estimating Generalized Additive Models

Generalized additive models (GAMs) have been widely used for flexible modeling of various types of outcomes. When the outcome in a GAM is subject to missing, practical analyses often assume that missingness is missing at random (MAR). This assumption can be of suspicion when the missingness is not by design. Evaluating the potential effects of alternative nonignorable missing data mechanism on the MAR inference from a GAM can be important but often challenging due to the complicatedness of alternative nonignorable models. We apply the index approach to local sensitivity (Troxel, Ma, and Heitjan 2004 (2004). Statistica Sinica 14 , 1221–1237) to evaluate the potential changes of the GAM estimates in the neighborhood of the MAR model. The approach avoids fitting any complicated nonignorable GAM. Only MAR estimates are required to calculate the resulting sensitivity index and adjust the GAM estimates to account for nonignorable missingness. Thus the proposed approach is considerably simpler to conduct, as compared with the alternative methods. The simulation study shows that the index provides valid assessment of the local sensitivity of the GAM estimates to nonignorable missingness. We then illustrate the method using a rheumatoid arthritis clinical trial data set.     

Translating Cancer Molecular Variability into Personalized Information Using Bulk and Single Cell Approaches

Cancer research is striving toward new frontiers of assigning the correct personalized drug(s) to a given patient. However, extensive tumor heterogeneity poses a major obstacle. Tumors of the same type often respond differently to therapy, due to patient‐specific molecular aberrations and/or untargeted tumor subpopulations. It is frequently not possible to determine a priori which patients will respond to a certain therapy or how an efficient patient‐specific combined therapy should be designed. Large‐scale datasets have been growing at an accelerated pace and various technologies and analytical tools for single cell and bulk level analyses are being developed to extract significant individualized signals from such heterogeneous data. However, personalized therapies that dramatically alter the course of the disease remain scarce, and most tumors still respond poorly to medical care. In this review, the basic concepts of bulk and single cell approaches are discussed, as well as their emerging role in individualized designs of drug therapies, including the advantages and limitations of their applications in personalized medicine.     

PDMS Microwell Stencil Based Multiplexed Single‐Cell Secretion Analysis

Multiplexed single‐cell protein secretion analysis provides an in‐depth understanding of cellular heterogeneity in intercellular communications mediated by secreted proteins in both fundamental and clinical research. However, it has been challenging to increase the proteomic parameters co‐profiled from every single cell in a facile way. Herein, a simple method to improve the multiplexed proteomic parameters of PDMS microwell based single‐cell secretion analysis platform by sandwiching PDMS stencil in between two antibody‐coated glass slides is introduced. Two different antibody panels can be immobilized easily by static coating, without using sophisticated fluid handling or bulky equipment. 5‐plexed, 3‐fluorescence color single‐cell secretion assay is demonstrated with this platform to investigate human monocytic U937 cells in response to lipopolysaccharide and phorbol myristate acetate stimulation, which identified the existence of functional subsets dictated by different cytokine profiles. The technology introduced here is simple, easy to operate, which holds great potential to become a powerful tool for profiling multiplexed single‐cell cytokine secretion at high throughput to dissect cellular heterogeneity in secretome signatures.     

微生物燃料电池发展态势分析

随着世界经济的高速发展和人口的不断增长,能源短缺和环境污染问题日益成为制约发展的瓶颈。微生物燃料电池(microbial fuel cell,MFC)能将污染物中蕴含的化学能直接转化为电能,实现同步污水处理和电能回收,是一种极具前景的可持续污水处理技术。同时,MFC在污泥处理、生物修复、环境监测、海水淡化等方面也展示了诱人的前景。基于科睿唯安Web of Science数据库和德温特专利检索分析平台(Derwent Innovation, DI),对MFC领域1990~2018年的论文和专利数据进行统计分析,得出全球MFC领域的发展趋势、国际分布、研发热点和技术格局。在此基础上,对未来MFC领域的发展做出了展望,对中国MFC产业化发展提出了思考和建议。     

全球冠状病毒疫苗专利分析

冠状病毒是一类可感染人类和动物的RNA病毒,可引起严重急性呼吸综合征(SARS)和中东呼吸综合征(MERS)等严重疾病。新型冠状病毒是以前从未在人体中发现的冠状病毒新毒株,其人际传播迅速,引起了各国政府的高度重视并积极寻求疫苗防控对策。基于冠状病毒疫苗领域全景专利,在综合对比分析该领域的全部专利的发展趋势、主要国家和主要机构的专利产出的同时,重点揭示了其中的人用相关疫苗的发展与分布情况以及重点分析了人用疫苗产品的研发现状,以期为我国冠状病毒疫苗领域的科研工作者和管理决策者提供参考数据。