Proteomic Profile of Daphnia pulex using Data‐Independent Acquisition Mass Spectrometry and Ion Mobility Separation

Daphnia pulex is a keystone species for aquatic habitats and an ecological/evolution model organism. Although significant progress has been made on characterizing its genome, the D. pulex proteome remains largely uncharacterized partially due to abnormally high protein degradation during homogenization and emphasis on genomic analysis. In this study, various sample preparation and mass spectrometry acquisition methods are performed for the purpose of improving D. pulex proteome exploration. Benefits for employing both in‐gel and in‐solution methods of trypsin digestion are observed. Furthermore, acquisition methods employing ion mobility separation greatly increase peptide identification and more than doubled the proteome coverage. Bioinformatic analysis suggests that mitochondrial and hydrolytic activities are enriched in D. pulex compared to closely related invertebrates or Homo sapiens. Also, novel D. pulex proteins possessing putative genome modifying functional domains are identified. Data are available via ProteomeXchange with identifier PXD008455.     

Decreased E‐Cadherin in MCF7 Human Breast Cancer Cells Forming Multicellular Spheroids Exposed to Simulated Microgravity

MCF7 human breast cancer cells were cultured under normal gravity (1 g) and on a random positioning machine (RPM) preventing sedimentation. After 2 weeks, adherent 1 g‐control and adherent RPM cells (AD) as well as multicellular spheroids (MCS) were harvested. AD and MCS had been exposed to the RPM in the same culture flask. In a subsequent proteome analysis, the majority of the proteins detected showed similar label‐free quantification (LFQ) scores in each of the respective subpopulations, but in both AD or MCS cultures, proteins were also found whose LFQs deviated at least twofold from their counterparts in the 1 g‐control cells. They included the cell junction protein E‐cadherin, which was diminished in MCS cells, where proteins of the E‐cadherin autodegradation pathway were enhanced and c‐Src (proto‐oncogene tyrosine‐protein kinase c‐Src) was detected. Spheroid formation was prevented by inhibition of c‐Src but promoted by antibodies blocking E‐cadherin activity. An interaction analysis of the detected proteins that are involved in forming and regulating junctions or adhesion complexes and in E‐cadherin autodegradation indicated connections between the two protein groups. This suggests that the balance of proteins that up‐ or downregulate E‐cadherin mediates the tendency of MCF7 cells to form MCS during RPM exposure.     

大数据背景下北京市大型居住区通勤绿道选线研究

近年来,随着城市交通拥堵和环境污染等问题的日益凸显,自行车作为通勤出行方式的地位逐渐上升,通勤者对建立不受机动车干扰的、连续的、具备通勤功能的城市绿色道路的需求也在不断增加。绿色道路的线路建设不仅要保障空间可实施性和交通环境质量,还要与居民的通勤出行需求紧密结合,实现绿道使用的综合效益最大化。基于此,研究以北京市回龙观地区为对象,采用与居民出行行为有关的数据,识别郊区居民中短程通勤特征,划定主要通勤范围,探究基于居民真实出行的多源大数据的选线方法,通过基于通勤出行需求强度与吸引强度的绿道节点甄选与路段适宜性的评价分析。最后,通过GIS网络分析功能进行最优线路选择,并结合城市公园、绿地、河流等资源的分布情况进行修正,形成一条满足居民通勤需求的、完整互联的、安全的且具备较强实施性的绿色通道。最终达到降低居民通勤时耗、提升区域可达性、完善城市慢行系统网络的目的。     

GITAR: An Open Source Tool for Analysis and Visualization of Hi-C Data

Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources (GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains (TADs). GITAR is composed of two main modules: (1) HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and (2) processed data library, a large collection of human and mouse datasets processed using HiCtool. HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://genomegitar.org as an open-source software.     

A standard protocol for documenting modern and fossil ichnological data

The collection and dissemination of vertebrate ichnological data is struggling to keep up with techniques that are becoming commonplace in the wider palaeontological field. A standard protocol is required to ensure that data is recorded, presented and archived in a manner that will be useful both to contemporary researchers, and to future generations. Primarily, our aim is to make the 3D capture of ichnological data standard practice, and to provide guidance on how such 3D data can be communicated effectively (both via the literature and other means) and archived openly and in perpetuity. We recommend capture of 3D data, and the presentation of said data in the form of photographs, false‐colour images, and interpretive drawings. Raw data (3D models of traces) should always be provided in a form usable by other researchers (i.e. in an open format). If adopted by the field as a whole, the result will be a more robust and uniform literature, supplemented by unparalleled availability of datasets for future workers.     

Evolution of pollen morphology in Loranthaceae

Earlier studies indicate a strong correlation of pollen morphology and ultrastructure with taxonomy in Loranthaceae. Using high-resolution light microscopy and scanning electron microscopy imaging of the same pollen grains, we document pollen types of 35 genera including 15 studied for the first time. Using a molecular phylogenetic framework based on currently available sequence data with good genus-coverage, we reconstruct trends in the evolution of Loranthaceae pollen and pinpoint traits of high diagnostic value, partly confirming earlier intuitive hypotheses based on morphological observations. We find that pollen morphology in Loranthaceae is strongly linked to phylogenetic relationships. Some pollen types are diagnostic for discrete genera or evolutionary lineages, opening the avenue to recruit dispersed fossil pollen as age constraints for dated phylogenies and as independent data for testing biogeographic scenarios; so far based exclusively on modern-day data. Correspondences and discrepancies between palynological and molecular data and current taxonomic/systematic concepts are identified and suggestions made for future palynological and molecular investigations of Loranthaceae.     

Mapping the Polarity Interactome

Interactions between proteins are an essential part of biology, and the desire to identify these interactions has led to the development of numerous technologies to systematically map protein–protein interactions at a large scale. As in most cellular processes, protein interactions are central to the control of cell polarity, and a full understanding of polarity will require comprehensive knowledge of the protein interactions involved. At its core, cell polarity is established through carefully regulated mutually inhibitory interactions between several groups of cortical proteins. While several interactions have been identified, the dynamics and molecular mechanisms that control these interactions are not well understood. Cell polarity also needs to be integrated with cellular processes including junction formation, cytoskeletal organization, organelle positioning, protein trafficking, and functional specialization of membrane domains. Moreover, polarized cells need to respond to external cues that coordinate polarity at the tissue level. Identifying the protein–protein interactions responsible for integrating polarity with all of these processes remains a major challenge, in part because the mechanisms of polarity control vary in different contexts and with developmental times. Because of their unbiased nature, systematic large-scale protein–protein interaction mapping approaches can be particularly helpful to identify such mechanisms. Here, we discuss methods commonly used to generate proteome-wide interactome maps, with an emphasis on advances in our understanding of cell polarity that have been achieved through application of such methods.