The codon-optimization of cfaE gene and evaluating its high expression capacity and conserved immunogenicity in Escherichia coli

Enterotoxigenic Escherichia coli (ETEC) is the most common cause of children diarrhea in the world. Adhesion of ETEC to small intestine is an important virulence trait. One of the most prevalent colonization factors (CFs) in human is CFA/I fimbriae and CfaE which is the required binding factor for adhesion of ETEC to intestinal mucosa.We optimized cfaE gene codons according to codon bias of E. coli to achieve a high level of recombinant protein expression. The optimized gene was expressed in E. coli and rCFaE protein was used for mice immunization. Blocking activity of the obtained antibody was examined by microplate agglutination inhibition test. SDS-PAGE analysis indicated that the optimized sequence of cfaE produces a suitable amount of rCFaE in comparison with native gene sequence. This optimized rCFaE protein could induces strong humoral response in mice and the antibody obtained against rCFaE inhibited the adhesion of ETEC to human group A erythrocytes. It is concluded that codon optimization is a useful approach for obtaining large quantities of recombinant rCFaE protein. With regard to the results of hemagglutination inhibition test, codon optimization and increased production of recombinant protein expressed in E. coli did not affect the immunogenicity potential of CFaE.     

Protein-Protein Docking with F2Dock 2.0 and GB-Rerank

Motivation

Computational simulation of protein-protein docking can expedite the process of molecular modeling and drug discovery. This paper reports on our new F² Dock protocol which improves the state of the art in initial stage rigid body exhaustive docking search, scoring and ranking by introducing improvements in the shape-complementarity and electrostatics affinity functions, a new knowledge-based interface propensity term with FFT formulation, a set of novel knowledge-based filters and finally a solvation energy (GBSA) based reranking technique. Our algorithms are based on highly efficient data structures including the dynamic packing grids and octrees which significantly speed up the computations and also provide guaranteed bounds on approximation error.

Results

The improved affinity functions show superior performance compared to their traditional counterparts in finding correct docking poses at higher ranks. We found that the new filters and the GBSA based reranking individually and in combination significantly improve the accuracy of docking predictions with only minor increase in computation time. We compared F² Dock 2.0 with ZDock 3.0.2 and found improvements over it, specifically among 176 complexes in ZLab Benchmark 4.0, F² Dock 2.0 finds a near-native solution as the top prediction for 22 complexes; where ZDock 3.0.2 does so for 13 complexes. F² Dock 2.0 finds a near-native solution within the top 1000 predictions for 106 complexes as opposed to 104 complexes for ZDock 3.0.2. However, there are 17 and 15 complexes where F² Dock 2.0 finds a solution but ZDock 3.0.2 does not and vice versa; which indicates that the two docking protocols can also complement each other.

Availability

The docking protocol has been implemented as a server with a graphical client (TexMol) which allows the user to manage multiple docking jobs, and visualize the docked poses and interfaces. Both the server and client are available for download. Server: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dock.shtml. Client: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dockclient.shtml.     

Multigene delivery in mammalian cells: Recent advances and applications

Systems for multigene delivery in mammalian cells, particularly in the context of genome engineering, have gained a lot of attention in biomolecular research and medicine. Initially these methods were based on RNA polymerase II promoters and were used for the production of protein complexes and for applications in cell biology such as reprogramming of somatic cells to stem cells. Emerging technologies such as CRISPR/Cas9-based genome engineering, which enable any alteration at the genomic level of an organism, require additional elements including U6-driven expression cassettes for RNA expression and homology constructs for designed genome modifications. For these applications, systems with high DNA capacity, flexibility and transfer rates are needed. In this article, we briefly give an update on some of recent strategies that facilitate multigene assembly and delivery into mammalian cells. Also, we review applications in various fields of biology that rely on multigene delivery systems.     

A Precisely Designed Immunotoxin Against VCAM1 Consisting of a Humanized Antibody Variable Domain Fused to Granzyme: An In Silico Approach

International Journal of Peptide Research and Therapeutics - Atherosclerosis is a complex disease related to cardiovascular disorders and is one of the most considerable causes of mortality...     

Iterated local least squares microarray missing value imputation

Microarray gene expression data often contains multiple missing values due to various reasons. However, most of gene expression data analysis algorithms require complete expression data. Therefore, accurate estimation of the missing values is critical to further data analysis. In this paper, an Iterated Local Least Squares Imputation (ILLSimpute) method is proposed for estimating missing values. Two unique features of ILLSimpute method are: ILLSimpute method does not fix a common number of coherent genes for target genes for estimation purpose, but defines coherent genes as those within a distance threshold to the target genes. Secondly, in ILLSimpute method, estimated values in one iteration are used for missing value estimation in the next iteration and the method terminates after certain iterations or the imputed values converge. Experimental results on six real microarray datasets showed that ILLSimpute method performed at least as well as, and most of the time much better than, five most recent imputation methods.     

Anticancer Activity of Brevinin-2R Peptide and its Two Analogues Against Myelogenous Leukemia Cell Line as Natural Treatments: An In Vitro Study

Human chronic myelogenous leukemia (CML) is a stem cell driven hematological malignancy which shows resistance to existing therapeutics. This property of CML accentuates the necessity to develop alternative anti-CML therapeutic agents. Herein, we have evaluated the anticancer activity of a novel anticancer peptide, Brevinin-2R and its two analogues, Brevinin-2R-C and Brevinin-2R-D regarding their inhibitory activity against K562 cells. Various cell-based analyses have been conducted to analyze the effects of these peptides and their mechanism of action. Hematotoxicity assay was performed to determine their hemolytic activities. MTT and neutral red uptake assays were conducted to examine anti-proliferative effects, propidium iodide (PI) staining to monitor the DNA content in different phases of cell cycle and Annexin V/PI staining to detect the apoptosis induction for the peptides. Our findings indicated that these peptides are capable of diminishing the cell growth and inducing apoptosis and cell cycle arrest. Brevinin-2R and its two analogues inhibited cell proliferation through strong cell cycle arrest in G2/M phase leading to apoptosis induction. The cytotoxicity of Brevinin-2R was higher than that of its two derivatives. These observations have provided new insights into the therapeutic activity of Brevinin-2R and its two analogues and suggest that these peptides have the potential to act as anticancer agents in treatment of K562. Further in vivo investigations on the therapeutic potential of Brevinin-2R and its two analogues are required to get a better grasp of their mechanism of action.

     

Ensembled neural networks for brain death prediction for patients with severe head injury

The concept of organ donation has gradually been accepted by people in recent years so the judicial brain death determination process becomes very important. Clinically, patients with irreversible apnoeic coma (IAC) will be considered legally as brain death based on a judicial process, but this process can only be applied to people who had already signed the letter of consent to organ donation. The main idea behind the proposed model is to find out an easier way to diagnose the prognosis of patients with severe head injury, and offer the medical staffs more information to determine brain death. Therefore, the technique of ensembled neural networks (ENN) based on multi-layer perceptron (MLP) network has been applied to construct the prediction model of brain death index (BDI). Ten different signals were chosen to be the input data. Using these ten parameters, medical doctors depend on their experience to score the BDI hourly values. The BDI values from medical doctors become the training target of the ANN training process and the standard index of testing process. Moreover, in order to compare the differences between doctors’ and the network's rankings for the input data, the ranking of order of precedence of each input signal is analyzed via sensitivity analysis. The results show that the 4 layers network with validation has better performance than 3 layers. For sensitivity analysis, most of the input variables’ ranking from trained model were similar to the ranking of the medical doctors except RR/RR(Set) this parameter and 4 other parameters (PS-R, PR-R, PS-L, and PR-L) are difficult to rank, even medical doctors cannot decide the ranking accurately. Using the best topology structure of MLP 10-10-5-1, the ensemble neural network could effectively predict the BDI with small errors (i.e. training error = 0.219087; validation error = 0.370485; testing error = 0.280515). In conclusion, this model can provide medical staffs a reference index to evaluate the status of IAC and brain death patients. However, more clinical data are still needed, perhaps to refine the weights of EANN, and certainly to see how widely the model is applicable.     

Structure Based Screening for Inhibitory Therapeutics of CTLA-4 Unveiled New Insights About Biology of ACTH

Although the biology of adrenocorticotropic hormone (ACTH) protein has already been scrutinized, some functional aspects of its biology are yet to be elucidated in the context of immunological disorders. In this regard, virtual screening of a compound library was performed against the structure of Cytotoxic T-Lymphocyte Associated Protein-4 (CTLA-4) (assessed both spatially and energetically) to discover novel biological functions for ACTH. The results of virtual screening and the MD simulation demonstrated that DB01284 has high binding energy along with proper interaction orientation against CTLA-4 (FG loop) by a clamp like structure. The employed methodology was checked using confirmatory control analyses. Intriguingly, DB01284 belongs to Tetracosactide (already prescribed protein drug for clinical conditions) which is the N-terminal region of ACTH. This is the first study to reveal that ACTH protein binds to the same amino acids of CTLA-4 (FG-loop) as B7 and anti-CTLA-4 antibody binds. In light of this finding, the molecular mechanism of ACTH function in patients suffering from Cushing’s Syndrom and the immunological bases for ACTH therapy of multiple sclerosis (MS) patients could be further delineated. Moreover, this finding suggests that ACTH could also act to block CTLA-4 in the context of anticancer immune check point blockade.

     

Exosomes and microRNAs: New potential therapeutic candidates in Alzheimer disease therapy

Exosomes are biological nanocarriers which could be involved in a variety of basic physiological events. They exert their effects via targeting their cargos (i.e., DNAs, messenger RNAs, microRNAs [miRNAs], and proteins) to host cells, which led to change behaviors of recipient cells. One of the important aspects of exosomes is the roles of them in disease conditions. Increasing evidence indicated that exosomes are one of the main players in Alzheimer’s disease (AD) pathogenesis. Hence, it seems that these nanocarriers could be used as diagnostic and therapeutic biomarkers in AD treatment. Another important player in AD pathogenesis is miRNA. MiRNAs are short noncoding RNAs which exert their effects as epigenetic regulators. These molecules involved in different stages of AD. Therefore, miRNAs could be used as prognostic, diagnostic, and therapeutic biomarkers in AD. Here, we summarized various roles of exosomes and application of them in AD pathogenesis. Moreover, we highlighted the utilization of miRNAs as a therapeutic option in AD therapy.