Novel components of the Toxoplasma inner membrane complex revealed by BioID.

UNLABELLED:The inner membrane complex (IMC) of Toxoplasma gondii is a peripheral membrane system that is composed of flattened alveolar sacs that underlie the plasma membrane, coupled to a supporting cytoskeletal network. The IMC plays important roles in parasite replication, motility, and host cell invasion. Despite these central roles in the biology of the parasite, the proteins that constitute the IMC are largely unknown. In this study, we have adapted a technique named proximity-dependent biotin identification (BioID) for use in T. gondii to identify novel components of the IMC. Using IMC proteins in both the alveoli and the cytoskeletal network as bait, we have uncovered a total of 19 new IMC proteins in both of these suborganellar compartments, two of which we functionally evaluate by gene knockout. Importantly, labeling of IMC proteins using this approach has revealed a group of proteins that localize to the sutures of the alveolar sacs that have been seen in their entirety in Toxoplasma species only by freeze fracture electron microscopy. Collectively, our study greatly expands the repertoire of known proteins in the IMC and experimentally validates BioID as a strategy for discovering novel constituents of specific cellular compartments of T. gondii. IMPORTANCE:The identification of binding partners is critical for determining protein function within cellular compartments. However, discovery of protein-protein interactions within membrane or cytoskeletal compartments is challenging, particularly for transient or unstable interactions that are often disrupted by experimental manipulation of these compartments. To circumvent these problems, we adapted an in vivo biotinylation technique called BioID for Toxoplasma species to identify binding partners and proximal proteins within native cellular environments. We used BioID to identify 19 novel proteins in the parasite IMC, an organelle consisting of fused membrane sacs and an underlying cytoskeleton, whose protein composition is largely unknown. We also demonstrate the power of BioID for targeted discovery of proteins within specific compartments, such as the IMC cytoskeleton. In addition, we uncovered a new group of proteins localizing to the alveolar sutures of the IMC. BioID promises to reveal new insights on protein constituents and interactions within cellular compartments of Toxoplasma

MicroRNA-224 Targets SMAD Family Member 4 to Promote Cell Proliferation and Negatively Influence Patient Survival

10.1371/journal.pone.0068744PLoS ONE87-POLN

Optimized parameter search for large datasets of the regularization parameter and feature selection for ridge regression

In this paper we propose mathematical optimizations to select the optimal regularization parameter for ridge regression using cross-validation. The resulting algorithm is suited for large datasets and the computational cost does not depend on the size of the training set. We extend this algorithm to forward or backward feature selection in which the optimal regularization parameter is selected for each possible feature set. These feature selection algorithms yield solutions with a sparse weight matrix using a quadratic cost on the norm of the weights. A naive approach to optimizing the ridge regression parameter has a computational complexity of the order with the number of applied regularization parameters, the number of folds in the validation set, the number of input features and the number of data samples in the training set. Our implementation has a computational complexity of the order . This computational cost is smaller than that of regression without regularization for large datasets and is independent of the number of applied regularization parameters and the size of the training set. Combined with a feature selection algorithm the algorithm is of complexity and for forward and backward feature selection respectively, with the number of selected features and the number of removed features. This is an order faster than and for the naive implementation, with for large datasets. To show the performance and reduction in computational cost, we apply this technique to train recurrent neural networks using the reservoir computing approach, windowed ridge regression, least-squares support vector machines (LS-SVMs) in primal space using the fixed-size LS-SVM approximation and extreme learning machines

Plasma Protein and MicroRNA Biomarkers of Insulin Resistance: A Network-Based Integrative -Omics Analysis

Although insulin resistance (IR) is a key pathophysiologic condition underlying various metabolic disorders, impaired cellular glucose uptake is one of many manifestations of metabolic derangements in the human body. To study the systems-wide molecular changes associated with obesity-dependent IR, we integrated information on plasma proteins and microRNAs in eight obese insulin-resistant (OIR, HOMA-IR > 2.5) and nine lean insulin-sensitive (LIS, HOMA-IR < 1.0) normoglycemic males. Of 374 circulating miRNAs we profiled, 65 species increased and 73 species decreased in the OIR compared to the LIS subjects, suggesting that the overall balance of the miRNA secretome is shifted in the OIR subjects. We also observed that 40 plasma proteins increased and 4 plasma proteins decreased in the OIR subjects compared to the LIS subjects, and most proteins are involved in metabolic and endocytic functions. We used an integrative -omics analysis framework called iOmicsPASS to link differentially regulated miRNAs with their target genes on the TargetScan map and the human protein interactome. Combined with tissue of origin information, the integrative analysis allowed us to nominate obesity-dependent and obesity-independent protein markers, along with potential sites of post-transcriptional regulation by some of the miRNAs. We also observed the changes in each -omics platform that are not linked by the TargetScan map, suggesting that proteins and microRNAs provide orthogonal information for the progression of OIR. In summary, our integrative analysis provides a network of elevated plasma markers of OIR and a global shift of microRNA secretome composition in the blood plasma

Genome-wide signatures of convergent evolution in echolocating mammals

Evolution is typically thought to proceed through divergence of genes, proteins, and ultimately phenotypes(1-3). However, similar traits might also evolve convergently in unrelated taxa due to similar selection pressures(4,5). Adaptive phenotypic convergence is widespread in nature, and recent results from a handful of genes have suggested that this phenomenon is powerful enough to also drive recurrent evolution at the sequence level(6-9). Where homoplasious substitutions do occur these have long been considered the result of neutral processes. However, recent studies have demonstrated that adaptive convergent sequence evolution can be detected in vertebrates using statistical methods that model parallel evolution(9,10) although the extent to which sequence convergence between genera occurs across genomes is unknown. Here we analyse genomic sequence data in mammals that have independently evolved echolocation and show for the first time that convergence is not a rare process restricted to a handful of loci but is instead widespread, continuously distributed and commonly driven by natural selection acting on a small number of sites per locus. Systematic analyses of convergent sequence evolution in 805,053 amino acids within 2,326 orthologous coding gene sequences compared across 22 mammals (including four new bat genomes) revealed signatures consistent with convergence in nearly 200 loci. Strong and significant support for convergence among bats and the dolphin was seen in numerous genes linked to hearing or deafness, consistent with an involvement in echolocation. Surprisingly we also found convergence in many genes linked to vision: the convergent signal of many sensory genes was robustly correlated with the strength of natural selection. This first attempt to detect genome-wide convergent sequence evolution across divergent taxa reveals the phenomenon to be much more pervasive than previously recognised

Linifanib versus sorafenib in patients with advanced hepatocellular carcinoma: Results of a randomized phase III trial

Copyrigh

The HY5-PIF regulatory module coordinates light and temperature control of photosynthetic gene transcription

The ability to interpret daily and seasonal alterations in light and temperature signals is essential for plant survival. This is particularly important during seedling establishment when the phytochrome photoreceptors activate photosynthetic pigment production for photoautotrophic growth. Phytochromes accomplish this partly through the suppression of phytochrome interacting factors (PIFs), negative regulators of chlorophyll and carotenoid biosynthesis. While the bZIP transcription factor long hypocotyl 5 (HY5), a potent PIF antagonist, promotes photosynthetic pigment accumulation in response to light. Here we demonstrate that by directly targeting a common promoter cis-element (G-box), HY5 and PIFs form a dynamic activation-suppression transcriptional module responsive to light and temperature cues. This antagonistic regulatory module provides a simple, direct mechanism through which environmental change can redirect transcriptional control of genes required for photosynthesis and photoprotection. In the regulation of photopigment biosynthesis genes, HY5 and PIFs do not operate alone, but with the circadian clock. However, sudden changes in light or temperature conditions can trigger changes in HY5 and PIFs abundance that adjust the expression of common target genes to optimise photosynthetic performance and growth

A Role for Phosphatidic Acid in the Formation of “Supersized” Lipid Droplets

Lipid droplets (LDs) are important cellular organelles that govern the storage and turnover of lipids. Little is known about how the size of LDs is controlled, although LDs of diverse sizes have been observed in different tissues and under different (patho)physiological conditions. Recent studies have indicated that the size of LDs may influence adipogenesis, the rate of lipolysis and the oxidation of fatty acids. Here, a genome-wide screen identifies ten yeast mutants producing “supersized” LDs that are up to 50 times the volume of those in wild-type cells. The mutated genes include: FLD1, which encodes a homologue of mammalian seipin; five genes (CDS1, INO2, INO4, CHO2, and OPI3) that are known to regulate phospholipid metabolism; two genes (CKB1 and CKB2) encoding subunits of the casein kinase 2; and two genes (MRPS35 and RTC2) of unknown function. Biochemical and genetic analyses reveal that a common feature of these mutants is an increase in the level of cellular phosphatidic acid (PA). Results from in vivo and in vitro analyses indicate that PA may facilitate the coalescence of contacting LDs, resulting in the formation of “supersized” LDs. In summary, our results provide important insights into how the size of LDs is determined and identify novel gene products that regulate phospholipid metabolism

Atrial arrhythmogenicity in aged Scn5a+/∆KPQ mice modeling long QT type 3 syndrome and its relationship to Na+ channel expression and cardiac conduction

Recent studies have reported that human mutations in Nav1.5 predispose to early age onset atrial arrhythmia. The present experiments accordingly assess atrial arrhythmogenicity in aging Scn5a+/∆KPQ mice modeling long QT3 syndrome in relationship to cardiac Na+ channel, Nav1.5, expression. Atrial electrophysiological properties in isolated Langendorff-perfused hearts from 3- and 12-month-old wild type (WT), and Scn5a+/∆KPQ mice were assessed using programmed electrical stimulation and their Nav1.5 expression assessed by Western blot. Cardiac conduction properties were assessed electrocardiographically in intact anesthetized animals. Monophasic action potential recordings demonstrated increased atrial arrhythmogenicity specifically in aged Scn5a+/ΔKPQ hearts. These showed greater action potential duration/refractory period ratios but lower atrial Nav1.5 expression levels than aged WT mice. Atrial Nav1.5 levels were higher in young Scn5a+/ΔKPQ than young WT. These levels increased with age in WT but not Scn5a+/ΔKPQ. Both young and aged Scn5a+/ΔKPQ mice showed lower heart rates and longer PR intervals than their WT counterparts. Young Scn5a+/ΔKPQ mice showed longer QT and QTc intervals than young WT. Aged Scn5a+/ΔKPQ showed longer QRS durations than aged WT. PR intervals were prolonged and QT intervals were shortened in young relative to aged WT. In contrast, ECG parameters were similar between young and aged Scn5a+/ΔKPQ. Aged murine Scn5a+/ΔKPQ hearts thus exhibit an increased atrial arrhythmogenicity. The differing Nav1.5 expression and electrocardiographic indicators of slowed cardiac conduction between Scn5a+/ΔKPQ and WT, which show further variations associated with aging, may contribute toward atrial arrhythmia in aged Scn5a+/ΔKPQ hearts