Adaptive introgression of anticoagulant rodent poison resistance by hybridization between old world mice

Polymorphisms in the vitamin K 2,3-epoxide reductase subcomponent 1 (vkorc1) of house mice (Mus musculus domesticus) can cause resistance to anticoagulant rodenticides such as warfarin [1-3]. Here we show that resistant house mice can also originate from selection on vkorc1 polymorphisms acquired from the Algerian mouse (M. spretus) through introgressive hybridization. We report on a polymorphic introgressed genomic region in European M. m. domesticus that stems from M. spretus, spans >10 Mb on chromosome 7, and includes the molecular target of anticoagulants vkorc1 [1-4]. We show that in the laboratory, the homozygous complete vkorc1 allele of M. spretus confers resistance when introgressed into M. m. domesticus. Consistent with selection on the introgressed allele after the introduction of rodenticides in the 1950s, we found signatures of selection in patterns of variation in M. m. domesticus. Furthermore, we detected adaptive protein evolution of vkorc1 in M. spretus (Ka/Ks = 1.54-1.93) resulting in radical amino acid substitutions that apparently cause anticoagulant tolerance in M. spretus as a pleiotropic effect. Thus, positive selection produced an adaptive, divergent, and pleiotropic vkorc1 allele in the donor species, M. spretus, which crossed a species barrier and produced an adaptive polymorphic trait in the recipient species, M. m. domesticus.     

Metabolic capabilities and systems fluctuations in Haloarcula marismortui revealed by integrative genomics and proteomics analyses

The 1310 Haloarcula marismortui proteins identified from mid-log and late-log phase soluble and membrane proteomes were analyzed in metabolic and cellular process networks to predict the available systems and systems fluctuations upon environmental stresses. When the connected metabolic reactions with identified proteins were examined, the availability of a number of metabolic pathways and a highly connected amino acid metabolic network were revealed. Quantitative spectral count analyses suggested 300 or more proteins might have expression changes in late-log phase. Among these, integrative network analyses indicated approximately 106 were metabolic proteins that might have growth-phase dependent changes. Interestingly, a large proportion of proteins in affected biomodules had the same trend of changes in spectral counts. Disregard the magnitude of changes, we had successfully predicted and validated the expression changes of nine genes including the rimK, gltCP, rrnAC0132, and argC in lysine biosynthesis pathway which were downregulated in late-log phase. This study had not only revealed the expressed proteins but also the availability of biological systems in two growth phases, systems level changes in response to the stresses in late-log phase, cellular locations of identified proteins, and the likely regulated genes to facilitate further analyses in the postgenomic era.     

A HIF-1 target, ATIA, protects cells from apoptosis by modulating the mitochondrial thioredoxin, TRX2

The regulation of apoptosis is critical for controlling tissue homeostasis and preventing tumor formation and growth. Reactive oxygen species (ROS) generation plays a key role in such regulation. Here, we describe a HIF-1 target, Vasn/ATIA (anti-TNFα-induced apoptosis), which protects cells against TNFα- and hypoxia-induced apoptosis. Through the generation of ATIA knockout mice, we show that ATIA protects cells from apoptosis through regulating the function of the mitochondrial antioxidant, thioredoxin-2, and ROS generation. ATIA is highly expressed in human glioblastoma, and ATIA knockdown in glioblastoma cells renders them sensitive to hypoxia-induced apoptosis. Therefore, ATIA is not only a HIF-1 target that regulates mitochondrial redox pathways but also a potentially diagnostic marker and therapeutic target in human glioblastoma.     

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Visual analytics (VA) has emerged as a new way to analyze large dataset through interactive visual display. We demonstrated the utility and the flexibility of a VA approach in the analysis of biological datasets. Examples of these datasets in immunology include flow cytometry, Luminex data, and genotyping (e.g., single nucleotide polymorphism) data. Contrary to the traditional information visualization approach, VA restores the analysis power in the hands of analyst by allowing the analyst to engage in real-time data exploration process. We selected the VA software called Tableau after evaluating several VA tools. Two types of analysis tasks analysis within and between datasets were demonstrated in the video presentation using an approach called paired analysis. Paired analysis, as defined in VA, is an analysis approach in which a VA tool expert works side-by-side with a domain expert during the analysis. The domain expert is the one who understands the significance of the data, and asks the questions that the collected data might address. The tool expert then creates visualizations to help find patterns in the data that might answer these questions. The short lag-time between the hypothesis generation and the rapid visual display of the data is the main advantage of a VA approach.Download video file.^{(48M, mov)}     

Live-cell Imaging of Migrating Cells Expressing Fluorescently-tagged Proteins in a Three-dimensional Matrix

Traditionally, cell migration has been studied on two-dimensional, stiff plastic surfaces. However, during important biological processes such as wound healing, tissue regeneration, and cancer metastasis, cells must navigate through complex, three-dimensional extracellular tissue. To better understand the mechanisms behind these biological processes, it is important to examine the roles of the proteins responsible for driving cell migration. Here, we outline a protocol to study the mechanisms of cell migration using the epithelial cell line (MDCK), and a three-dimensional, fibrous, self-polymerizing matrix as a model system. This optically clear extracellular matrix is easily amenable to live-cell imaging studies and better mimics the physiological, soft tissue environment. This report demonstrates a technique for directly visualizing protein localization and dynamics, and deformation of the surrounding three-dimensional matrix. Examination of protein localization and dynamics during cellular processes provides key insight into protein functions. Genetically encoded fluorescent tags provide a unique method for observing protein localization and dynamics. Using this technique, we can analyze the subcellular accumulation of key, force-generating cytoskeletal components in real-time as the cell maneuvers through the matrix. In addition, using multiple fluorescent tags with different wavelengths, we can examine the localization of multiple proteins simultaneously, thus allowing us to test, for example, whether different proteins have similar or divergent roles. Furthermore, the dynamics of fluorescently tagged proteins can be quantified using Fluorescent Recovery After Photobleaching (FRAP) analysis. This measurement assays the protein mobility and how stably bound the proteins are to the cytoskeletal network.By combining live-cell imaging with the treatment of protein function inhibitors, we can examine in real-time the changes in the distribution of proteins and morphology of migrating cells. Furthermore, we also combine live-cell imaging with the use of fluorescent tracer particles embedded within the matrix to visualize the matrix deformation during cell migration. Thus, we can visualize how a migrating cell distributes force-generating proteins, and where the traction forces are exerted to the surrounding matrix. Through these techniques, we can gain valuable insight into the roles of specific proteins and their contributions to the mechanisms of cell migration.