Recruitment of EB1, a master regulator of microtubule dynamics, to the surface of the Theileria annulata schizont

The apicomplexan parasite Theileria annulata transforms infected host cells, inducing uncontrolled proliferation and clonal expansion of the parasitized cell population. Shortly after sporozoite entry into the target cell, the surrounding host cell membrane is dissolved and an array of host cell microtubules (MTs) surrounds the parasite, which develops into the transforming schizont. The latter does not egress to invade and transform other cells. Instead, it remains tethered to host cell MTs and, during mitosis and cytokinesis, engages the cell's astral and central spindle MTs to secure its distribution between the two daughter cells. The molecular mechanism by which the schizont recruits and stabilizes host cell MTs is not known. MT minus ends are mostly anchored in the MT organizing center, while the plus ends explore the cellular space, switching constantly between phases of growth and shrinkage (called dynamic instability). Assuming the plus ends of growing MTs provide the first point of contact with the parasite, we focused on the complex protein machinery associated with these structures. We now report how the schizont recruits end-binding protein 1 (EB1), a central component of the MT plus end protein interaction network and key regulator of host cell MT dynamics. Using a range of in vitro experiments, we demonstrate that T. annulata p104, a polymorphic antigen expressed on the schizont surface, functions as a genuine EB1-binding protein and can recruit EB1 in the absence of any other parasite proteins. Binding strictly depends on a consensus SxIP motif located in a highly disordered C-terminal region of p104. We further show that parasite interaction with host cell EB1 is cell cycle regulated. This is the first description of a pathogen-encoded protein to interact with EB1 via a bona-fide SxIP motif. Our findings provide important new insight into the mode of interaction between Theileria and the host cell cytoskeleton

AntigenDB: an immunoinformatics database of pathogen antigens

The continuing threat of infectious disease and future pandemics, coupled to the continuous increase of drug-resistant pathogens, makes the discovery of new and better vaccines imperative. For effective vaccine development, antigen discovery and validation is a prerequisite. The compilation of information concerning pathogens, virulence factors and antigenic epitopes has resulted in many useful databases. However, most such immunological databases focus almost exclusively on antigens where epitopes are known and ignore those for which epitope information was unavailable. We have compiled more than 500 antigens into the AntigenDB database, making use of the literature and other immunological resources. These antigens come from 44 important pathogenic species. In AntigenDB, a database entry contains information regarding the sequence, structure, origin, etc. of an antigen with additional information such as B and T-cell epitopes, MHC binding, function, gene-expression and post translational modifications, where available. AntigenDB also provides links to major internal and external databases. We shall update AntigenDB on a rolling basis, regularly adding antigens from other organisms and extra data analysis tools. AntigenDB is available freely at http://www.imtech.res.in/raghava/antigendb and its mirror site http://www.bic.uams.edu/raghava/antigendb

Identification of NAD interacting residues in proteins

Background: Small molecular cofactors or ligands play a crucial role in the proper functioning of cells. Accurate annotation of their target proteins and binding sites is required for the complete understanding of reaction mechanisms. Nicotinamide adenine dinucleotide (NAD+ or NAD) is one of the most commonly used organic cofactors in living cells, which plays a critical role in cellular metabolism, storage and regulatory processes. In the past, several NAD binding proteins (NADBP) have been reported in the literature, which are responsible for a wide-range of activities in the cell. Attempts have been made to derive a rule for the binding of NAD+ to its target proteins. However, so far an efficient model could not be derived due to the time consuming process of structure determination, and limitations of similarity based approaches. Thus a sequence and non-similarity based method is needed to characterize the NAD binding sites to help in the annotation. In this study attempts have been made to predict NAD binding proteins and their interacting residues (NIRs) from amino acid sequence using bioinformatics tools. Results: We extracted 1556 proteins chains from 555 NAD binding proteins whose structure is available in Protein Data Bank. Then we removed all redundant protein chains and finally obtained 195 non-redundant NAD binding protein chains, where no two chains have more than 40% sequence identity. In this study all models were developed and evaluated using five-fold cross validation technique on the above dataset of 195 NAD binding proteins. While certain type of residues are preferred (e.g. Gly, Tyr, Thr, His) in NAD interaction, residues like Ala, Glu, Leu, Lys are not preferred. A support vector machine (SVM) based method has been developed using various window lengths of amino acid sequence for predicting NAD interacting residues and obtained maximum Matthew's correlation coefficient (MCC) 0.47 with accuracy 74.13% at window length 17. We also developed a SVM based method using evolutionary information in the form of position specific scoring matrix (PSSM) and obtained maximum MCC 0.75 with accuracy 87.25%. Conclusion: For the first time a sequence-based method has been developed for the prediction of NAD binding proteins and their interacting residues, in the absence of any prior structural information. The present model will aid in the understanding of NAD+ dependent mechanisms of action in the cell. To provide service to the scientific community, we have developed a user-friendly web server, which is available from URL http://www.imtech.res.in/raghava/nadbinder/

Genomic analysis of the causative agents of coccidiosis in domestic chickens

Global production of chickens has trebled in the past two decades and they are now the most important source of dietary animal protein worldwide. Chickens are subject to many infectious diseases that reduce their performance and productivity. Coccidiosis, caused by apicomplexan protozoa of the genus Eimeria, is one of the most important poultry diseases. Understanding the biology of Eimeria parasites underpins development of new drugs and vaccines needed to improve global food security. We have produced annotated genome sequences of all seven species of Eimeria that infect domestic chickens, which reveal the full extent of previously described repeat-rich and repeat-poor regions and show that these parasites possess the most repeat-rich proteomes ever described. Furthermore, while no other apicomplexan has been found to possess retrotransposons, Eimeria is home to a family of chromoviruses. Analysis of Eimeria genes involved in basic biology and host-parasite interaction highlights adaptations to a relatively simple developmental life cycle and a complex array of co-expressed surface proteins involved in host cell binding

Identification of SPP1 as a Prognostic Biomarker and Immune Cells Modulator in Urothelial Bladder Cancer: A Bioinformatics Analysis

Secreted phosphoprotein-1 (SPP1) expression is differentially altered in many malignancies and could serve as a potential prognostic biomarker. Recent findings indicated that SPP1 possesses a broader role in bladder cancer (BC) pathogenesis than previously envisioned; however, the underlying mechanisms governing its expression, cellular localization, prognostic value and immune-related role in bladder cancer remain poorly understood. The expression and the prognosis value of SPP1 were assessed using immunohistochemistry (IHC) staining on a tissue microarray. SPP1 expression was correlated with the clinicopathological parameters, and survival analysis was calculated using a Kaplan–Meier plotter. Bioinformatics analysis of TCGA data was queried using UALCAN, CIBERSORT and TIMER datasets to decipher the biological processes enrichment pattern, protein–protein interactions and characterize tumor-infiltrating immune cells, respectively. IHC revealed that SPP1 expression is significantly associated with tumor type, stage, grade and smoking status. The Kaplan–Meier survival curve showed that low SPP1 expression is an unfavorable prognostic indicator in bladder cancer patients (p = 0.02, log-rank). The significant increased expression of the SPP1 level is associated with evident hypomethylation of the gene promoter in cancer compared to normal tissues in the TCGA-bladder dataset. Missense mutation is the most frequent genetic alteration of the SPP1 gene. Protein–protein interactions demonstrated that SPP1 shares the same network with many important genes and is involved in many signaling pathways and biological processes. TIMER reported a significant correlation between SPP1 expression and multiple immune cells infiltration. Furthermore, the expression of SPP1 was found to be positively correlated with a number of immune checkpoint genes such as PD-1 and CTLA4. The current investigation indicates that the SPP1 protein could serve as a prognostic biomarker and merit further investigation to validate its clinical usefulness in patients with bladder cancer

Apigenin enhances sorafenib anti-tumour efficacy in hepatocellular carcinoma

Background: The “one drug-one target” paradigm has various limitations affecting drug efficacy, such as resistance profiles and adverse effects. Combinational therapies help reduce unexpected off-target effects and accelerate therapeutic efficacy. Sorafenib- an FDA-approved drug for liver cancer, has multiple limitations. Therefore, it is recommended to identify an agent that increases its effectiveness and reduces toxicity. In this regard, Apigenin, a plant flavone, would be an excellent option to explore. Methods: We used in silico, in vitro, and animal models to explore our hypothesis. For the in vitro study, HepG2 and Huh7 cells were exposed to Apigenin (12-96 μM) and Sorafenib (1-10 μM). For the in vivo study, Diethylnitrosamine (DEN) (25 mg/kg) induced tumor-bearing animals were given Apigenin (50 mg/kg) or Sorafenib (10 mg/kg) alone and combined. Apigenin's bioavailability was checked by UPLC. Tumor nodules were studied macroscopically and by Scanning Electron Microscopy (SEM). Biochemical analysis, histopathology, immunohistochemistry, and qRT-PCR were done. Results: The results revealed Apigenin's good bioavailability. In silico study showed binding affinity of both chemicals with p53, NANOG, ß-Catenin, c-MYC, and TLR4. We consistently observed a better therapeutic efficacy in combination than alone treatment. Combination treatment showed i) better cytotoxicity, apoptosis induction, and cell cycle arrest of tumor cells, ii) tumor growth reduction, iii) increased expression of p53 and decreased Cd10, Nanog, ß-Catenin, c-Myc, Afp, and Tlr4. Conclusions: In conclusion, Apigenin could enhance the therapeutic efficacy of Sorafenib against liver cancer and may be a promising therapeutic approach for treating HCC. However, further research is imperative to gain more in-depth mechanistic insights