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Fluorescence correlation spectroscopy and time-dependent fluorescence Stokes shift have been employed to elucidate dynamics in different time scales, ranging from picoseconds to nanoseconds, for human serum albumin, in its native and cationized forms as well as in the self-assembled complex of the cationized protein with the polymer surfactant (PS) glycolic acid ethoxylate lauryl ether. The effect of crowding in this complex, especially in the waterless condition, is of prime importance in this context. Excellent correlation of the dynamics with the structures, obtained by circular dichroism and Fourier transform infrared spectroscopy, has been observed. Slow solvation, associated classically with biological water, has been observed in these systems, even in the waterless condition. This apparently intriguing observation has been rationalized by the relaxation of segments of the protein and the PS in the microenvironment of the fluorescent probe.

Background: COVID-19 (Coronavirus Disease-19), a disease caused by the SARS-CoV-2 virus, has been declared as a pandemic by the World Health Organization on March 11, 2020. Over 15 million people have already been affected worldwide by COVID-19, resulting in more than 0.6 million deaths. Protein-protein interactions (PPIs) play a key role in the cellular process of SARS-CoV-2 virus infection in the human body. Recently a study has reported some SARS-CoV-2 proteins that interact with several human proteins while many potential interactions remain to be identified., Method: In this article, various machine learning models are built to predict the PPIs between the virus and human proteins that are further validated using biological experiments. The classification models are prepared based on different sequence-based features of human proteins like amino acid composition, pseudo amino acid composition, and conjoint triad., Result: We have built an ensemble voting classifier using SVM Radial , SVM Polynomial , and Random Forest technique that gives a greater accuracy, precision, specificity, recall, and F1 score compared to all other models used in the work. A total of 1326 potential human target proteins of SARS-CoV-2 have been predicted by the proposed ensemble model and validated using gene ontology and KEGG pathway enrichment analysis. Several repurposable drugs targeting the predicted interactions are also reported., Conclusion: This study may encourage the identification of potential targets for more effective anti-COVID drug discovery., Competing Interests: Conflicts of interest The authors declare that they have no conflict of interest., (Copyright © 2020 Chang Gung University. Published by Elsevier B.V. All rights reserved.)

Accuracy of protein-ligand binding free energy calculations utilizing implicit solvent models is critically affected by parameters of the underlying dielectric boundary, specifically, the atomic and water probe radii. Here, a global multidimensional optimization pipeline is developed to find optimal atomic radii specifically for protein-ligand binding calculations in implicit solvent. The computational pipeline has these three key components: (1) a massively parallel implementation of a deterministic global optimization algorithm (VTDIRECT95), (2) an accurate yet reasonably fast generalized Born implicit solvent model (GBNSR6), and (3) a novel robustness metric that helps distinguish between nearly degenerate local minima via a postprocessing step of the optimization. A graph-based " kT -connectivity" approach to explore and visualize the multidimensional energy landscape is proposed: local minima that can be reached from the global minimum without exceeding a given energy threshold ( kT ) are considered to be connected. As an illustration of the capabilities of the optimization pipeline, we apply it to find a global optimum in the space of just five radii: four atomic (O, H, N, and C) radii and water probe radius. The optimized radii, ρ W = 1.37 Å, ρ C = 1.40 Å, ρ H = 1.55 Å, ρ N = 2.35 Å, and ρ O = 1.28 Å, lead to a closer agreement of electrostatic binding free energies with the explicit solvent reference than two commonly used sets of radii previously optimized for small molecules. At the same time, the ability of the optimizer to find the global optimum reveals fundamental limits of the common two-dielectric implicit solvation model: the computed electrostatic binding free energies are still almost 4 kcal/mol away from the explicit solvent reference. The proposed computational approach opens the possibility to further improve the accuracy of practical computational protocols for binding free energy calculations.

This work presents an annotation tool that automatically locates mentions of particular amino-acid residues in published papers and identifies the protein concerned. These matches can be provided in context or in a searchable format in order for researchers to better use the existing and future literature.

Key Message: BjuWRR1, a CNL-type R gene, was identified from an east European gene pool line of Brassica juncea and validated for conferring resistance to white rust by genetic transformation. White rust caused by the oomycete pathogen Albugo candida is a significant disease of crucifer crops including Brassica juncea (mustard), a major oilseed crop of the Indian subcontinent. Earlier, a resistance-conferring locus named AcB1-A5.1 was mapped in an east European gene pool line of B. juncea-Donskaja-IV. This line was tested along with some other lines of B. juncea (AABB), B. rapa (AA) and B. nigra (BB) for resistance to six isolates of A. candida collected from different mustard growing regions of India. Donskaja-IV was found to be completely resistant to all the tested isolates. Sequencing of a BAC spanning the locus AcB1-A5.1 showed the presence of a single CC-NB-LRR protein encoding R gene. The genomic sequence of the putative R gene with its native promoter and terminator was used for the genetic transformation of a susceptible Indian gene pool line Varuna and was found to confer complete resistance to all the isolates. This is the first white rust resistance-conferring gene described from Brassica species and has been named BjuWRR1. Allelic variants of the gene in B. juncea germplasm and orthologues in the Brassicaceae genomes were studied to understand the evolutionary dynamics of the BjuWRR1 gene.

The Protein Data Bank in Europe (PDBe, pdbe.org) is actively engaged in the deposition, annotation, remediation, enrichment and dissemination of macromolecular structure data. This paper describes new developments and improvements at PDBe addressing three challenging areas: data enrichment, data dissemination and functional reusability. New features of the PDBe Web site are discussed, including a context dependent menu providing links to raw experimental data and improved presentation of structures solved by hybrid methods. The paper also summarizes the features of the LiteMol suite, which is a set of services enabling fast and interactive 3D visualization of structures, with associated experimental maps, annotations and quality assessment information. We introduce a library of Web components which can be easily reused to port data and functionality available at PDBe to other services. We also introduce updates to the SIFTS resource which maps PDB data to other bioinformatics resources, and the PDBe REST API., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

OneDep, a unified system for deposition, biocuration, and validation of experimentally determined structures of biological macromolecules to the PDB archive, has been developed as a global collaboration by the worldwide PDB (wwPDB) partners. This new system was designed to ensure that the wwPDB could meet the evolving archiving requirements of the scientific community over the coming decades. OneDep unifies deposition, biocuration, and validation pipelines across all wwPDB, EMDB, and BMRB deposition sites with improved focus on data quality and completeness in these archives, while supporting growth in the number of depositions and increases in their average size and complexity. In this paper, we describe the design, functional operation, and supporting infrastructure of the OneDep system, and provide initial performance assessments., (Published by Elsevier Ltd.)

The computational or in silico approaches for analysing the HIV-1-human protein-protein interaction (PPI) network, predicting different host cellular factors and PPIs and discovering several pathways are gaining popularity in the field of HIV research. Although there exist quite a few studies in this regard, no previous effort has been made to review these works in a comprehensive manner. Here we review the computational approaches that are devoted to the analysis and prediction of HIV-1-human PPIs. We have broadly categorized these studies into two fields: computational analysis of HIV-1-human PPI network and prediction of novel PPIs. We have also presented a comparative assessment of these studies and proposed some methodologies for discussing the implication of their results. We have also reviewed different computational techniques for predicting HIV-1-human PPIs and provided a comparative study of their applicability. We believe that our effort will provide helpful insights to the HIV research community., (© The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.)

In this article, the possible subcellular location of a protein is predicted using multiobjective particle swarm optimization-based feature selection technique. In general form of pseudo-amino acid composition, the protein sequences are used for constructing protein features. Here, the different amino acids compositions are used to construct the feature sets. Therefore, the data are presented as sample of protein versus amino acid compositions as features. The proposed algorithm tries to maximize the feature relevance and minimize the feature redundancy simultaneously. After proposed algorithm is executed on the multiclass dataset, some features are selected. On this resultant feature subset, tenfold cross-validation is applied and corresponding accuracy, F score, entropy, representation entropy and average correlation are calculated. The performance of the proposed method is compared with that of its single objective versions, sequential forward search, sequential backward search, minimum redundancy maximum relevance with two schemes, CFS, CBFS, [Formula: see text], Fisher discriminant and a Cluster-based technique.

Protein complexes play an important role in cellular mechanism. Identification of protein complexes in protein-protein interaction (PPI) networks is the first step in understanding the organization and dynamics of cell function. Several high-throughput experimental techniques produce a large amount of protein interactions, which can be used to predict protein complexes in a PPI network. We have developed an algorithm PROCOMOSS (Protein Complex Detection using Multi-objective Evolutionary Approach based on Semantic Similarity) for partitioning the whole PPI network into clusters, which serve as predicted protein complexes. We consider both graphical properties of a PPI network as well as biological properties based on GO semantic similarity measure as objective functions. Here three different semantic similarity measures are used for grouping functionally similar proteins in the same clusters. We have applied the PROCOMOSS algorithm on two different datasets of Saccharomyces cerevisiae to find and predict protein complexes. A real-life application of the PROCOMOSS is also shown here by applying it in the human PPI network consisting of differentially expressed genes affected by gastric cancer. Gene ontology and pathway based analyses are also performed to investigate the biological importance of the extracted gene modules.

Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1-human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1-human interaction network. Novel HIV-1-human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed.

13C-Based metabolic flux analysis provides valuable information about bacterial physiology. Though many biological processes rely on the synergistic functions of microbial communities, study of individual organisms in a mixed culture using existing flux analysis methods is difficult. Isotopomer-based flux analysis typically relies on hydrolyzed amino acids from a homogeneous biomass. Thus, metabolic flux analysis of a given organism in a mixed culture requires its separation from the mixed culture. Swift and efficient cell separation is difficult and a major hurdle for isotopomer-based flux analysis of mixed cultures. Here we demonstrate the use of a single highly expressed protein to analyze the isotopomer distribution of amino acids from one organism. Using the model organism Escherichia coli expressing a plasmid-borne, His-tagged green fluorescent protein (GFP), we show that induction of GFP does not affect E. coli growth kinetics or the isotopomer distribution in nine key metabolites. Further, the isotopomer labeling patterns of amino acids derived from purified GFP and total cell protein are indistinguishable, indicating that amino acids from a purified protein can be used to infer metabolic fluxes of targeted organisms in a mixed culture. This study provides the foundation to extend isotopomer-based flux analysis to study metabolism of individual strains in microbial communities.

The relaxin-like factor (RLF), which is the product of the INSL3 gene, is highly expressed in the fetal and adult-type Leydig cells of all species so far examined. In adult testes it is upregulated at puberty but appears subsequently to be expressed in a constitutive manner, independently of acute changes in the hypothalamic-pituitary-gonadal (HPG) axis. Functional hypogonadism with decreased testosterone is prevalent in the aging male. In order to test whether this is a property of the HPG axis, or of the Leydig cells themselves, RLF/INSL3 was used as an independent marker to assess rat Leydig cell differentiation status. Hybridization analysis showed that in the testes of old (2 years) rats, RLF/INSL3 mRNA expression was dramatically reduced, compared to young (3 months) animals. This was also evident at the protein level using immunohistochemistry. The results suggest that increasing functional hypogonadism in older male mammals is likely caused by a dedifferentiation of the Leydig cells themselves.

The glycosylation machinery in eukaryotic cells is available to all proteins that enter the secretory pathway. There is a growing interest in diseases caused by defective glycosylation, and in therapeutic glycoproteins produced through recombinant DNA technology route. The choice of a bioprocess for commercial production of recombinant glycoprotein is determined by a variety of factors, such as intrinsic biological properties of the protein being expressed and the purpose for which it is intended, and also the economic target. This review summarizes recent development and understanding related to synthesis of glycans, their functions, diseases, and various expression systems and characterization of glycans. The second section covers processing of N- and O-glycans and the factors that regulate protein glycosylation. The third section deals with in vivo functions of protein glycosylation, which includes protein folding and stability, receptor functioning, cell adhesion and signal transduction. Malfunctioning of glycosylation machinery and the resultant diseases are the subject of the fourth section. The next section covers the various expression systems exploited for the glycoproteins: it includes yeasts, mammalian cells, insect cells, plants and an amoeboid organism. Biopharmaceutical properties of therapeutic proteins are discussed in the sixth section. In vitro protein glycosylation and the characterization of glycan structures are the subject matters for the last two sections, respectively.

Expression of the relaxin-like factor (RLF) was studied at the messenger RNA (mRNA) and protein levels in the testes and ovaries of the mouse, as well as through testicular development and differentiation in the mouse testis. In situ hybridization or RT-PCR, and immunohistochemistry using a polyclonal antibody raised against a recombinant protein, provided mutually confirmatory results for a high expression of RLF in the Leydig cells of the adult testis and at a much lower level of expression in the luteal cells of the ovary through the cycle, pregnancy, and in lactation. Analysis of protein and mRNA expression, through postnatal testicular development, indicated moderate RLF expression also in the fetal population of Leydig cells, even in the hpg mutant mouse, lacking an active pituitary-gonadal axis. Prepubertal Leydig cells, however, exhibit only very low-level RLF gene expression, this phenotype persisting in the adult hpg mouse. In summary, fetal Leydig cells express RLF in an LH/human CG-independent fashion, whereas LH/human CG is essential to induce RLF expression in the adult-type Leydig cell. In cultured adult Leydig cells or in the mouse tumor MA-10 cell line, RLF mRNA is expressed in a constitutive fashion. RLF thus seems to be a useful marker of Leydig cell differentiation status.

Functional studies indicate that natriuretic peptides have direct effects on Leydig cells of the testis. In this report, we demonstrate local synthesis of one member of the natriuretic peptide family, C-type natriuretic peptide (CNP), in Leydig cells of human testes. Using RT-PCR assays, messenger RNA (mRNA) for the CNP precursor was detected in human testis and found to be prominently expressed in Leydig cells. Immunohistochemical analyses revealed CNP to be almost exclusively associated with Leydig cells. Distinct differences in the staining intensity-including cells without detectable staining-suggest a heterogeneity of CNP expression within the Leydig cells. Moreover, the presence of transcripts for the CNP receptor, a particulate guanylate cyclase, termed GC-B, was demonstrated by RT-PCR in human testis and in isolated Leydig cells. The expression of this receptor in human testis membranes could be confirmed by affinity labeling with 125I-labeled CNP. These findings demonstrate, for the first time, the production of a natriuretic peptide in human Leydig cells. The occurrence of CNP and its receptor in the human testis points to a local role of the peptide, presumably acting in an auto- or paracrine manner to modulate organ-specific functions.

We have maleylated proteins to target macrophage-specific scavenger receptors and have used this system to study changes in the epitopes and immunogenicity of such proteins. We show that maleylation of diphtheria toxoid (DT) induces targeting to macrophage scavenger receptors and enhances its immunogenicity. DT does not evoke detectable serum Ab responses upon injection as soluble protein. However, maleylated DT (mDT) does generate a significant Ab response. Furthermore, immunization with soluble mDT leads to a better T cell proliferative response in vitro than immunization with DT can generate, thereby demonstrating that maleylation leads to enhanced T cell immunogenicity in vivo. We also find that maleylation disrupts the native B cell epitopes of DT and creates new epitopes, because antisera to DT and mDT do not cross-react. At least some of the new epitopes generated are maleylation specific, because antisera against various maleylated proteins do cross-react. In contrast, maleylation does not significantly modify the repertoire of T cell epitopes generated from DT, because T cells generated by either DT or mDT immunization are cross-reactive, and both DT and mDT can stimulate T cells that are specific for single synthetic DT peptide. Maleylated proteins are better presented in vitro than are their native counterparts, and this enhancement of presentation is blocked by unrelated maleylated proteins. These results suggest that Ags targeted to scavenger receptors on macrophages by maleylation are better presented to T cells and are immunogenic in vivo without adjuvant.

In this report, we systematically characterize 32 response regulators (RRs) from a metal tolerant groundwater isolate, Pseudomonas stutzeri RCH2 to assess the impact of host-derived post-translational phosphorylation. As observed by distinct shifted bands in a phos-tag gel, 12 of the 24 detected RRs show homogenous mixtures of phosphorylated proteins or heterogenous mixtures of unphosphorylated and phosphorylated proteins. By evaluating the phosphorylation state of CzcR and CopR II under varying assay parameters, we found that changes to pH and exogenous addition of phospho-donors (e.g. acetyl phosphate) have little to no effect on phosphorylation state. By applying protein production conditions that decrease the pool of intracellular acetyl-phosphate in E. coli, we found a reduction in the phosphorylated population of CopR II when magnesium was added to the medium, but observed no change in phosphorylated population when CopR II is expressed in E. coli BL21 (DE3) ∆pta, a mutant with a metabolic disruption to the acetyl-phosphate pathway. Therefore, the specific mechanism of post-translational phosphorylation of RRs in E. coli remains obscure. These findings show the importance of characterizing the phosphorylation state of proteins when heterologously expressed, since their biochemical and physiological properties can be dependent on post-translational modification.

We review the status of protein-based molecular electronics. First, we define and discuss fundamental concepts of electron transfer and transport in and across proteins and proposed mechanisms for these processes. We then describe the immobilization of proteins to solid-state surfaces in both nanoscale and macroscopic approaches, and highlight how different methodologies can alter protein electronic properties. Because immobilizing proteins while retaining biological activity is crucial to the successful development of bioelectronic devices, we discuss this process at length. We briefly discuss computational predictions and their connection to experimental results. We then summarize how the biological activity of immobilized proteins is beneficial for bioelectronic devices, and how conductance measurements can shed light on protein properties. Finally, we consider how the research to date could influence the development of future bioelectronic devices.

MAGEA4 is a cancer-testis antigen primarily expressed in the testes but aberrantly overexpressed in several cancers. MAGEA4 interacts with the RING ubiquitin ligase RAD18 and activates trans-lesion DNA synthesis (TLS), potentially favouring tumour evolution. Here, we employed NMR and AlphaFold2 (AF) to elucidate the interaction mode between RAD18 and MAGEA4, and reveal that the RAD6-binding domain (R6BD) of RAD18 occupies a groove in the C-terminal winged-helix subdomain of MAGEA4. We found that MAGEA4 partially displaces RAD6 from the RAD18 R6BD and inhibits degradative RAD18 autoubiquitination, which could be countered by a competing peptide of the RAD18 R6BD. AlphaFold2 and cross-linking mass spectrometry (XL-MS) also revealed an evolutionary invariant intramolecular interaction between the catalytic RING and the DNA-binding SAP domains of RAD18, which is essential for PCNA mono-ubiquitination. Using interaction proteomics, we found that another Type-I MAGE, MAGE-C2, interacts with the RING ubiquitin ligase TRIM28 in a manner similar to the MAGEA4/RAD18 complex, suggesting that the MAGEA4 peptide-binding groove also serves as a ligase-binding cleft in other type-I MAGEs. Our data provide new insights into the mechanism and regulation of RAD18-mediated PCNA mono-ubiquitination. Synopsis: MAGE proteins bind RING ubiquitin ligases and often promote pro-oncogenic pathways. Through structural and biochemical approaches, this study gives insight into how MAGEA4 binds and regulates the RING E3 RAD18, which is crucial for DNA repair. MAGEA4 utilizes a C-terminal peptide binding groove (PBG) to bind and regulate RAD18. The PBG is important for RING ligase binding in other MAGE proteins. MAGEA4 protects RAD18 from degradative autoubiquitination. The RAD18 RING and SAP domains interact together to mediate monoubiquitination of the substrate PCNA. The interaction mode is conserved in another MAGE/RING pair, MAGE-C2 and TRIM28. MAGEA4 partly displaces RAD6 from the key DNA repair E3 RAD18, thereby protecting it from degradative autoubiquitination. [ABSTRACT FROM AUTHOR]

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

Context or Background: Pediatric renal tumours are the second most common solid tumours in children. The most common in this group is Wilms tumour with mesoblastic nephroma being the 2nd most common tumour in children, younger than 3 months.Aims and Objectives: The present study was conducted to study the epidemiological occurrence of pediatric renal tumours at a tertiary care hospital and to study the diagnostic efficacy of WT1 immunostaining in distinguishing Wilms tumour from other types of renal tumours.Materials and Methods: It was a single institution-based prospective and observational study conducted for 2 years (from October 2013 to September 2015) in the department of pathology in our hospital. A total of 50 cases were enrolled in this study all were below 15 years of age.Results: Nephroblastoma or Wilms tumour was found to be the most common type, occurring in 66% cases. Fourteen out of 33 cases of Wilms tumour showed triphasic components (blastemal, epithelial, and stromal) with Blastemal type Wilms being the second most common (11 cases). WT1 immunostaining was positive in 93.9% cases of nephroblastoma. The highest amount of nuclear positivity noted in blastemal cells followed by epithelial cells. Rhabdomyoblastic differentiation and regressive variant showed nonspecific cytoplasmic staining. Cystic partially differentiated nephroblastoma and diffuse anaplasia type Wilms tumour showed nuclear staining in blastemal cells.Conclusion: The expression of WT1 immunostain was found to be diagnostically significant in differentiating Wilms tumour from other renal tumours. [ABSTRACT FROM AUTHOR]

Dengue Virus (DENV) infection is one of the rapidly spreading mosquito-borne viral infections in humans. Every year, around 50 million people get affected by DENV infection, resulting in 20,000 deaths. Despite the recent experiments focusing on dengue infection to understand its functionality in the human body, several functionally important DENV-human protein-protein interactions (PPIs) have remained unrecognized. This article presents a model for predicting new DENV-human PPIs by combining different sequence-based features of human and dengue proteins like the amino acid composition, dipeptide composition, conjoint triad, pseudo amino acid composition, and pairwise sequence similarity between dengue and human proteins. A Learning vector quantization (LVQ)-based Compact Genetic Algorithm (CGA) model is proposed for feature subset selection. CGA is a probabilistic technique that simulates the behavior of a Genetic Algorithm (GA) with lesser memory and time requirements. Prediction of DENV-human PPIs is performed by the weighted Random Forest (RF) technique as it is found to perform better than other classifiers. We have predicted 1013 PPIs between 335 human proteins and 10 dengue proteins. All predicted interactions are validated by literature filtering, GO-based assessment, and KEGG Pathway enrichment analysis. This study will encourage the identification of potential targets for more effective anti-dengue drug discovery. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ydbio.2007.03.522 Byline: Sang-Chul Nam (a), Bibhash Mukhopadhyay (b), Kwang-Wook Choi (a)(b)(c) Keywords: Cell polarity; Photoreceptor; Rhabdomere; Bazooka; Par-1; PP2A Abstract: Establishment and maintenance of apical basal cell polarity are essential for epithelial morphogenesis and have been studied extensively using the Drosophila eye as a model system. Bazooka (Baz), a component of the Par-6 complex, plays important roles in cell polarity in diverse cell types including the photoreceptor cells. In ovarian follicle cells, localization of Baz at the apical region is regulated by Par-1 protein kinase. In contrast, Baz in photoreceptor cells is targeted to adherens junctions (AJs). To examine the regulatory pathways responsible for Baz localization in photoreceptor cells, we studied the effects of Par-1 on Baz localization in the pupal retina. Loss of Par-1 impairs the maintenance of AJ markers including Baz and apical polarity proteins of photoreceptor cells but not the establishment of cell polarity. In contrast, overexpression of Par-1 or Baz causes severe mislocalization of junctional and apical markers, resulting in abnormal cell polarity. However, flies with similar overexpression of kinase-inactive mutant Par-1 or unphosphorylatable mutant Baz protein show relatively normal photoreceptor development. These results suggest that dephosphorylation of Baz at the Par-1 phosphorylation sites is essential for proper Baz localization. We also show that the inhibition of protein phosphatase 2A (PP2A) mimics the polarity defects caused by Par-1 overexpression. Furthermore, Par-1 gain-of-function phenotypes are strongly enhanced by reduced PP2A function. Thus, we propose that antagonism between PP2A and Par-1 plays a key role in Baz localization at AJ in photoreceptor morphogenesis. Author Affiliation: (a) Department of Molecular and Cellular Biology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA (b) Program in Developmental Biology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA (c) Department of Ophthalmology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA Article History: Received 28 September 2006; Revised 27 March 2007; Accepted 28 March 2007