IFITM3 inhibits influenza A virus infection by preventing cytosolic entry

To replicate, viruses must gain access to the host cell's resources. Interferon (IFN) regulates the actions of a large complement of interferon effector genes (IEGs) that prevent viral replication. The interferon inducible transmembrane protein family members, IFITM1, 2 and 3, are IEGs required for inhibition of influenza A virus, dengue virus, and West Nile virus replication in vitro. Here we report that IFN prevents emergence of viral genomes from the endosomal pathway, and that IFITM3 is both necessary and sufficient for this function. Notably, viral pseudoparticles were inhibited from transferring their contents into the host cell cytosol by IFN, and IFITM3 was required and sufficient for this action. We further demonstrate that IFN expands Rab7 and LAMP1-containing structures, and that IFITM3 overexpression is sufficient for this phenotype. Moreover, IFITM3 partially resides in late endosomal and lysosomal structures, placing it in the path of invading viruses. Collectively our data are consistent with the prediction that viruses that fuse in the late endosomes or lysosomes are vulnerable to IFITM3's actions, while viruses that enter at the cell surface or in the early endosomes may avoid inhibition. Multiple viruses enter host cells through the late endocytic pathway, and many of these invaders are attenuated by IFN. Therefore these findings are likely to have significance for the intrinsic immune system's neutralization of a diverse array of threats.     

Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia

Searching for genetic variants with unusual differentiation between subpopulations is an established approach for identifying signals of natural selection. However, existing methods generally require discrete subpopulations. We introduce a method that infers selection using principal components (PCs) by identifying variants whose differentiation along top PCs is significantly greater than the null distribution of genetic drift. To enable the application of this method to large datasets, we developed the FastPCA software, which employs recent advances in random matrix theory to accurately approximate top PCs while reducing time and memory cost from quadratic to linear in the number of individuals, a computational improvement of many orders of magnitude. We apply FastPCA to a cohort of 54,734 European Americans, identifying 5 distinct subpopulations spanning the top 4 PCs. Using the PC-based test for natural selection, we replicate previously known selected loci and identify three new genome-wide significant signals of selection, including selection in Europeans at ADH1B. The coding variant rs1229984^∗T has previously been associated to a decreased risk of alcoholism and shown to be under selection in East Asians; we show that it is a rare example of independent evolution on two continents. We also detect selection signals at IGFBP3 and IGH, which have also previously been associated to human disease.     

Sterol glycosyltransferases required for adaptation of Withania somnifera at high temperature

Heat is a major environmental stress factor that confines growth, productivity, and metabolism of plants. Plants respond to such unfavorable conditions through changes in their physiological, biochemical and developmental processes. Withania somnifera, an important medicinal plant, grows in hot and dry conditions, however, molecular mechanisms related to such adaptive properties are not known. Here, we elucidated that members of the sterol glycosyltransferases (SGT) gene family play important roles in the survival of W. somnifera under adverse conditions through maintaining the integrity of the membrane. SGTs are enzymes involved in sterol modifications and participate in metabolic flexibility during stress. Silencing of WsSGT members, for instance WsSGTL1, WsSGTL2 and WsSGTL4, was inimical for important physiological parameters, such as electron transport rate, photochemical quantum yield, acceptor side limitation, non‐photochemical quenching (NPQ), Fv/Fm and net photosynthetic rate, whereas stomatal conductance, transpiration rate and dark respiration rates (Rds) were increased. Decreased NPQ and increased Rds helped to generate significant amount of ROS in the Wsamisgt lines. After heat stress, H₂O₂, lipid peroxidation and nitric oxide production increased in the Wsamisgt lines due to high ROS generation. The expression of HSPs in Wsamisgt lines might be involved in regulation of physiological processes during stress. We have also observed increased proline accumulation which might be involved in restricting water loss in the Wsamisgt lines. Taken together, our observations revealed that SGTL enzyme activity is required to maintain the internal damages of the cell against high temperature by maintaining the sterol vs sterol glycosides ratio in the membranes of W. somnifera.     

Dynamic Redox Regulation of IL-4 Signaling

Quantifying the magnitude and dynamics of protein oxidation during cell signaling is technically challenging. Computational modeling provides tractable, quantitative methods to test hypotheses of redox mechanisms that may be simultaneously operative during signal transduction. The interleukin-4 (IL-4) pathway, which has previously been reported to induce reactive oxygen species and oxidation of PTP1B, may be controlled by several other putative mechanisms of redox regulation; widespread proteomic thiol oxidation observed via 2D redox differential gel electrophoresis upon IL-4 treatment suggests more than one redox-sensitive protein implicated in this pathway. Through computational modeling and a model selection strategy that relied on characteristic STAT6 phosphorylation dynamics of IL-4 signaling, we identified reversible protein tyrosine phosphatase (PTP) oxidation as the primary redox regulatory mechanism in the pathway. A systems-level model of IL-4 signaling was developed that integrates synchronous pan-PTP oxidation with ROS-independent mechanisms. The model quantitatively predicts the dynamics of IL-4 signaling over a broad range of new redox conditions, offers novel hypotheses about regulation of JAK/STAT signaling, and provides a framework for interrogating putative mechanisms involving receptor-initiated oxidation.     

Protein profiling underscores immunological functions of uterine cervical mucus plug in human pregnancy

The cervical mucus plug (CMP) differs from the cervical secretions of non-pregnant women, and is the ultimate sealant of the uterine cavity during pregnancy. Although several studies have analyzed biochemical properties of large glycoproteins in the CMP, comprehensive information about its protein composition is yet unavailable. We hypothesized that protein profiling of the CMP could provide key clues to its physiological functions in pregnancy. For this purpose, five CMPs obtained from women in labor at term were analyzed by LC-MS/MS. Out of 291 total proteins identified, 137 were detected in two or more samples, which included S100A8, S100A9, and complement proteins (C3, C4a, C4b, C6, and C8g). Several proteins, which have not been described in the cervical mucus of non-pregnant women or in cervicovaginal fluids, such as CD81 antigen and pregnancy zone protein, were also identified. Gene ontology analysis of identified proteins showed significant enrichment of 28 biological processes such as 'activation of plasma proteins involved in acute inflammatory response' and 'positive regulation of cholesterol esterification'. We report the proteome of CMPs from pregnant women at term for the first time, and the overall findings strongly suggest an important role for the CMP in the maintenance of pregnancy and parturition.     

Coupling dynamics and evolutionary information with structure to identify protein regulatory and functional binding sites

Binding sites in proteins can be either specifically functional binding sites (active sites) that bind specific substrates with high affinity or regulatory binding sites (allosteric sites), that modulate the activity of functional binding sites through effector molecules. Owing to their significance in determining protein function, the identification of protein functional and regulatory binding sites is widely acknowledged as an important biological problem. In this work, we present a novel binding site prediction method, Active and Regulatory site Prediction (AR-Pred), which supplements protein geometry, evolutionary, and physicochemical features with information about protein dynamics to predict putative active and allosteric site residues. As the intrinsic dynamics of globular proteins plays an essential role in controlling binding events, we find it to be an important feature for the identification of protein binding sites. We train and validate our predictive models on multiple balanced training and validation sets with random forest machine learning and obtain an ensemble of discrete models for each prediction type. Our models for active site prediction yield a median area under the curve (AUC) of 91% and Matthews correlation coefficient (MCC) of 0.68, whereas the less well-defined allosteric sites are predicted at a lower level with a median AUC of 80% and MCC of 0.48. When tested on an independent set of proteins, our models for active site prediction show comparable performance to two existing methods and gains compared to two others, while the allosteric site models show gains when tested against three existing prediction methods. AR-Pred is available as a free downloadable package at https://github.com/sambitmishra0628/AR-PRED_source .     

Protein model discrimination using mutational sensitivity derived from deep sequencing

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Highlights? Individual mutant phenotypes in a saturation library derived via deep sequencing ? Residue depth and active-site residue derivation from mutant phenotypes ? Mutant-phenotype-derived parameters used for protein model discrimination ? Derivation of sequence-structure-function relationships without protein isolation     

Phylogenetic analysis of polyomavirus BK sequences

Polyomavirus BK (BKV) has emerged as an important pathogen in kidney transplant patients. Existing taxonomic classifications of BKV come from conventional DNA sequence alignments based on limited data derived from the VP1 gene. We have used a phylogenetic whole-genome approach to examine the pattern of diversity and evolutionary relationships between 45 BKV strains isolated from multiple clinical settings. This analysis supports the classification of BKV into six genotypes, of which types V and VI have not been previously recognized. BKV strains hitherto classified as type I are, in fact, quite heterogeneous, and several cluster with our newly defined genotypes V and VI. The sequence information needed for assigning genotypes can be captured by VP1, VP2, VP3, or large T-gene sequencing. The most polymorphic coding region in the viral genome is VP1, but significant variation is also present in the large T-antigen gene, wherein polymorphisms are found in 11.39% of all nucleotide sites, 46.22% of which are cluster specific. Type-specific amino acid changes within the VP1 region are predicted to map to the BC and DE loops. The number of taxonomically informative amino acid changes in the large T antigen exceeds even that of the VP1 region. Viral strains isolated from healthy subjects and from patients with human immunodeficiency virus infection, Wiskott-Aldrich syndrome, and vasculopathy with capillary leak syndrome formed distinct subclusters. However, within the kidney transplant population, BKV strains derived from patients with asymptomatic viruria did not show complete separation from strains associated with allograft nephropathy.