Optimisation of protein extraction for in-depth profiling of the cereal grain proteome.

Cereal grain proteomics can provide valuable information regarding plant growth, nutritional status, adaptation to environmental stresses, and the role that grain proteins play in health disorders, such as coeliac disease. In this study liquid chromatography-mass spectrometry was used to compare the barley proteome after extraction using seven protocols, with and without defatting and protein precipitation steps that aimed to remove interfering secondary metabolites. Tris-HCl and urea buffers yielded 1405 and 1483 proteins (~79% overlap) from barley (cv Sloop). Inclusion of a pre-extraction defatting step yielded 1336 (Tris-HCl) and 1286 (urea) proteins (~74% overlap). Whilst post-extraction TCA/acetone protein precipitation negatively impacted protein recovery, yielding 673 (Tris-HCl) and 734 (urea) proteins. Alcohol-based extraction yielded a lower number of proteins (645), but notably this extraction method co-extracted and enriched the gluten and α-amylase trypsin inhibitors. Based on these preliminary results, proteins were extracted from two selected cultivars of wheat, rye, barley and oats using three extraction protocols. Bioinformatic analyses of the identified proteins provide evidence that the choice of extraction buffer enriches different protein functional classes. The selection of the protein extraction protocol directly influences the identified cereal grain proteome composition, thus affecting the downstream biological interpretation of data. SIGNIFICANCE: LC-MS/MS and bioinformatics analysis revealed that both Tris-HCl and urea-based extraction yielded a similar suite of proteins from cereal grains with remarkable (70-80%) overlap. Yet the peptides derived from the proteins differed, rendering these extraction buffers complementary, in particular resulting in improved protein sequence coverage. The inclusion of commonly incorporated practices, such as pre-extraction defatting or post-extraction precipitation steps offered no benefit. The extraction method selected was noted to impact the downstream functional annotation results and biological interpretation.

Whole-genome sequence of the bovine blood fluke Schistosoma bovis supports interspecific hybridization with S. haematobium.

Mesenteric infection by the parasitic blood fluke Schistosoma bovis is a common veterinary problem in Africa and the Middle East and occasionally in the Mediterranean Region. The species also has the ability to form interspecific hybrids with the human parasite S. haematobium with natural hybridisation observed in West Africa, presenting possible zoonotic transmission. Additionally, this exchange of alleles between species may dramatically influence disease dynamics and parasite evolution. We have generated a 374 Mb assembly of the S. bovis genome using Illumina and PacBio-based technologies. Despite infecting different hosts and organs, the genome sequences of S. bovis and S. haematobium appeared strikingly similar with 97% sequence identity. The two species share 98% of protein-coding genes, with an average sequence identity of 97.3% at the amino acid level. Genome comparison identified large continuous parts of the genome (up to several 100 kb) showing almost 100% sequence identity between S. bovis and S. haematobium. It is unlikely that this is a result of genome conservation and provides further evidence of natural interspecific hybridization between S. bovis and S. haematobium. Our results suggest that foreign DNA obtained by interspecific hybridization was maintained in the population through multiple meiosis cycles and that hybrids were sexually reproductive, producing viable offspring. The S. bovis genome assembly forms a highly valuable resource for studying schistosome evolution and exploring genetic regions that are associated with species-specific phenotypic traits.

Calypso: a user-friendly web-server for mining and visualizing microbiome-environment interactions.

Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. Availability and Implementation: The web-interface is accessible via http://cgenome.net/calypso/ . The software is programmed in Java, PERL and R and the source code is available from Zenodo ( https://zenodo.org/record/50931 ). The software is freely available for non-commercial users. Contact: l.krause@uq.edu.au. Supplementary information: Supplementary data are available at Bioinformatics online.

Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) Web-Server.

Genomics Data Miner (GMine) is a user-friendly online software that allows non-experts to mine, cluster and compare multidimensional biomolecular datasets. Various powerful visualization techniques are provided, generating high quality figures that can be directly incorporated into scientific publications. Robust and comprehensive analyses are provided via a broad range of data-mining techniques, including univariate and multivariate statistical analysis, supervised learning, correlation networks, clustering and multivariable regression. The software has a focus on multivariate techniques, which can attribute variance in the measurements to multiple explanatory variables and confounders. Various normalization methods are provided. Extensive help pages and a tutorial are available via a wiki server. Using GMine we reanalyzed proteome microarray data of host antibody response against Plasmodium falciparum. Our results support the hypothesis that immunity to malaria is a higher-order phenomenon related to a pattern of responses and not attributable to any single antigen. We also analyzed gene expression across resting and activated T cells, identifying many immune-related genes with differential expression. This highlights both the plasticity of T cells and the operation of a hardwired activation program. These application examples demonstrate that GMine facilitates an accurate and in-depth analysis of complex molecular datasets, including genomics, transcriptomics and proteomics data.

Less is more: extreme genome complexity reduction with ddRAD using Ion Torrent semiconductor technology.

Massively parallel sequencing a small proportion of the whole genome at high coverage enables answering a wide range of questions from molecular evolution and evolutionary biology to animal and plant breeding and forensics. In this study, we describe the development of restriction-site associated DNA (RAD) sequencing approach for Ion Torrent PGM platform. Our protocol results in extreme genome complexity reduction using two rare-cutting restriction enzymes and strict size selection of the library allowing sequencing of a relatively small number of genomic fragments with high sequencing depth. We applied this approach to a common freshwater fish species, the Eurasian perch (Perca fluviatilis L.), and generated over 2.2 MB of novel sequence data consisting of ~17,000 contigs, identified 1259 single nucleotide polymorphisms (SNPs). We also estimated genetic differentiation between the DNA pools from freshwater (Lake Peipus) and brackish water (the Baltic Sea) populations and identified SNPs with the strongest signal of differentiation that could be used for robust individual assignment in the future. This work represents an important step towards developing genomic resources and genetic tools for the Eurasian perch. We expect that our ddRAD sequencing protocol for semiconductor sequencing technology will be useful alternative for currently available RAD protocols.

Molecular docking studies on InhA, MabA and PanK enzymes from Mycobacterium tuberculosis of ellagic acid derivatives from Ludwigia adscendens and Trewia nudiflora.

PURPOSE: There is an urgent need to discover and develop new drugs to combat Mycobacterium tuberculosis, the causative agent of tuberculosis (TB) in humans. In recent years, there has been a renewed interest in the discovery of new anti-TB agents from natural sources. In the present investigation, molecular docking studies were carried out on two ellagic acid derivatives, namely pteleoellagic acid (1) isolated from Ludwigia adscendens, and 3,3'-di-O-methyl ellagic acid 4-O-α-rhamnopyranoside (2) isolated from Trewia nudiflora, to investigate their binding to two enzymes involved in M. tuberculosis cell wall biogenesis, namely 2-trans-enoyl-ACP reductase (InhA) and ß-ketoacyl-ACP reductase (MabA), and to pantothenate kinase (PanK type I) involved in the biosynthesis of coenzyme A, essential for the growth of M. tuberculosis. METHODS: Molecular docking experiments were performed using AutoDock Vina. The crystal structures of InhA, MabA and PanK were retrieved from the RCSB Protein Data Bank (PDB). Isonicotinic-acyl-NADH for InhA and MabA, and triazole inhibitory compound for PanK, were used as references. RESULTS: Pteleoellagic acid showed a high docking score, estimated binding free energy of -9.4 kcal/mol, for the MabA enzyme comparable to the reference compound isonicotinic-acyl-NADH. CONCLUSIONS: Knowledge on the molecular interactions of ellagic acid derivatives with essential M. tuberculosis targets could prove a useful tool for the design and development of future anti-TB drugs.

Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV.

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) belongs to the coronaviridae family. In spite of several outbreaks in the very recent years, no vaccine against this deadly virus is developed yet. In this study, the receptor binding domain (RBD) of Spike (S) glycoprotein of MERS-CoV was analyzed through Computational Immunology approach to identify the antigenic determinants (epitopes). In order to do so, the sequences of S glycoprotein that belong to different geographical regions were aligned to observe the conservancy of MERS-CoV RBD. The immune parameters of this region were determined using different in silico tools and Immune Epitope Database (IEDB). Molecular docking study was also employed to check the affinity of the potential epitope towards the binding cleft of the specific HLA allele. The N-terminus RBD (S367-S606) of S glycoprotein was found to be conserved among all the available strains of MERS-CoV. Based on the lower IC50 value, a total of eight potential T-cell epitopes and 19 major histocompatibility complex (MHC) class-I alleles were identified for this conserved region. A 9-mer epitope CYSSLILDY displayed interactions with the maximum number of MHC class-I molecules and projected the highest peak in the B-cell antigenicity plot which concludes that it could be a better choice for designing an epitope based peptide vaccine against MERSCoV considering that it must undergo further in vitro and in vivo experiments. Moreover, in molecular docking study, this epitope was found to have a significant binding affinity of -8.5 kcal/mol towards the binding cleft of the HLA-C*12:03 molecule.

CEPiNS: Conserved Exon Prediction in Novel Species.

Exon structure is relatively well conserved among orthologs in several large clades of species (e.g. Mammalia, Diptera, Lepidoptera) across evolutionary distances of up to 80 million years. Thus, it should be straightforward to predict the exon structures in novel species based upon the known exon structures of species that have had their genomes sequenced and well assembled. Being able to predict the exon boundaries in the genes of novel species is important given the quickly growing numbers of transcriptome sequencing projects. CEPiNS is a new pipeline for mining exon boundaries of predicted gene sets from model species and then using this information to identify the exon boundaries in a novel species through codon based alignment. The pipeline uses the freeware SPIDEY, an exon boundary prediction tool, and BLAST (BLASTN, BLASTP, TBLASTX), both of which are part of NCBI's toolkit. CEPiNS provides an important tool to analyze the transcriptome of novel species.

Inhibition of VEGF: a novel mechanism to control angiogenesis by Withania somnifera's key metabolite Withaferin A.

PURPOSE: Angiogenesis, or new blood vessel formation from existing one, plays both beneficial and detrimental roles in living organisms in different aspects. Vascular endothelial growth factor (VEGF), a signal protein, well established as key regulator of vasculogenesis and angiogenesis. VEGF ensures oxygen supply to the tissues when blood supply is not adequate, or tissue environment is in hypoxic condition. Limited expression of VEGF is necessary, but if it is over expressed, then it can lead to serious disease like cancer. Cancers that have ability to express VEGF are more efficient to grow and metastasize because solid cancers cannot grow larger than a limited size without adequate blood and oxygen supply. Anti-VEGF drugs are already available in the market to control angiogenesis, but they are often associated with severe side-effects like fetal bleeding and proteinuria in the large number of patients. To avoid such side-effects, new insight is required to find potential compounds as anti-VEGF from natural sources. In the present investigation, molecular docking studies were carried out to find the potentiality of Withaferin A, a key metabolite of Withania somnifera, as an inhibitor of VEGF. METHODS: Molecular Docking studies were performed in DockingServer and SwissDock. Bevacizumab, a commercial anti-VEGF drug, was used as reference to compare the activity of Withaferin A. X-ray crystallographic structure of VEGF, was retrieved from Protein Data Bank (PDB), and used as drug target protein. Structure of Withaferin A and Bevacizumab was obtained from PubChem and ZINC databases. Molecular visualization was performed using UCSF Chimera. RESULTS: Withaferin A showed favorable binding with VEGF with low binding energy in comparison to Bevacizumab. Molecular Docking studies also revealed potential protein-ligand interactions for both Withaferin A and Bevacizumab. CONCLUSIONS: Conclusively our results strongly suggest that Withaferin A is a potent anti-VEGF agent as ascertained by its potential interaction with VEGF. This scientific hypothesis might provide a better insight to control angiogenesis as well as to control solid cancer growth and metastasis.