Critical assessment of sequence-based protein-protein interaction prediction methods that do not require homologous protein sequences

Background  

Protein-protein interactions underlie many important biological processes. Computational prediction methods can nicely complement experimental approaches for identifying protein-protein interactions. Recently, a unique category of sequence-based prediction methods has been put forward - unique in the sense that it does not require homologous protein sequences. This enables it to be universally applicable to all protein sequences unlike many of previous sequence-based prediction methods. If effective as claimed, these new sequence-based, universally applicable prediction methods would have far-reaching utilities in many areas of biology research.     

RNA mutagenesis yields highly diverse mRNA libraries for <Emphasis Type="Italic">in vitro</Emphasis>protein evolution

Background  

In protein drug development, in vitro molecular optimization or protein maturation can be used to modify protein properties. One basic approach to protein maturation is the introduction of random DNA mutations into the target gene sequence to produce a library of variants that can be screened for the preferred protein properties. Unfortunately, the capability of this approach has been restricted by deficiencies in the methods currently available for random DNA mutagenesis and library generation. Current DNA based methodologies generally suffer from nucleotide substitution bias that preferentially mutate particular base pairs or show significant bias with respect to transitions or transversions. In this report, we describe a novel RNA-based random mutagenesis strategy that utilizes Qβ replicase to manufacture complex mRNA libraries with a mutational spectrum that is close to the ideal.     

Mutational spectrum of bleomycin in lacZ mouse kidney: a possible model for mutational spectrum of reactive oxygen species

The mutational spectrum of bleomycin was compared with the spontaneous mutational spectrum in lacZ mouse kidney. Mice were treated with four 20 mg/kg of doses of bleomycin over a two-week period, leading to a mutant fraction several times greater than that of controls. The major class of bleomycin-induced mutations consisted of small deletions, in particular -1 deletions at AT base pairs and hot spots for deletions at 5'-GTC-3' sequences. Smaller, but significant fractions of GC > AT followed by GC > TA substitutions were also observed. In untreated mice, the major class of mutations consisted of GC > AT substitutions followed by GC > TA mutations, and a much smaller fraction of deletions. Other than the specificity of bleomycin for AT base pairs and the 5'-GTC-3' hotspots, the mutational spectrum of bleomycin in mice is similar to that reported for ionizing radiation. However, bleomycin initially mediates the formation of oxidized DNA via reduction of molecular oxygen, as opposed to the radiolysis of water. In this respect mutagenesis induced by bleomycin may be more similar to that induced by endogenous reactive oxygen species (ROS) than mutagenesis induced by ionizing radiation. If bleomycin-induced mutagenesis is an appropriate model for mutagenesis induced by ROS, then, based on the difference between the mutational spectrum of bleomycin and spontaneous mutagenesis, the latter appears not to result predominantly from ROS, at least in mouse kidney.     

Prediction of the burial status of transmembrane residues of helical membrane proteins

Background  

Helical membrane proteins (HMPs) play a crucial role in diverse cellular processes, yet it still remains extremely difficult to determine their structures by experimental techniques. Given this situation, it is highly desirable to develop sequence-based computational methods for predicting structural characteristics of HMPs.     

Combining sequence-based prediction methods and circular dichroism and infrared spectroscopic data to improve protein secondary structure determinations

Background  

A number of sequence-based methods exist for protein secondary structure prediction. Protein secondary structures can also be determined experimentally from circular dichroism, and infrared spectroscopic data using empirical analysis methods. It has been proposed that comparable accuracy can be obtained from sequence-based predictions as from these biophysical measurements. Here we have examined the secondary structure determination accuracies of sequence prediction methods with the empirically determined values from the spectroscopic data on datasets of proteins for which both crystal structures and spectroscopic data are available.     

Convergent evolution in structural elements of proteins investigated using cross profile analysis

Background  

Evolutionary relations of similar segments shared by different protein folds remain controversial, even though many examples of such segments have been found. To date, several methods such as those based on the results of structure comparisons, sequence-based classifications, and sequence-based profile-profile comparisons have been applied to identify such protein segments that possess local similarities in both sequence and structure across protein folds. However, to capture more precise sequence-structure relations, no method reported to date combines structure-based profiles, and sequence-based profiles based on evolutionary information. The former are generally regarded as representing the amino acid preferences at each position of a specific conformation of protein segment. They might reflect the nature of ancient short peptide ancestors, using the results of structural classifications of protein segments.     

NClassG+: A classifier for non-classically secreted Gram-positive bacterial proteins

Background  

Most predictive methods currently available for the identification of protein secretion mechanisms have focused on classically secreted proteins. In fact, only two methods have been reported for predicting non-classically secreted proteins of Gram-positive bacteria. This study describes the implementation of a sequence-based classifier, denoted as NClassG+, for identifying non-classically secreted Gram-positive bacterial proteins.     

Development of a genome editing technique using the CRISPR/Cas9 system in the industrial filamentous fungus <Emphasis Type="Italic">Aspergillus oryzae</Emphasis>

Objectives

To develop a genome editing method using the CRISPR/Cas9 system in Aspergillus oryzae, the industrial filamentous fungus used in Japanese traditional fermentation and for the production of enzymes and heterologous proteins.

Results

To develop the CRISPR/Cas9 system as a genome editing technique for A. oryzae, we constructed plasmids expressing the gene encoding Cas9 nuclease and single guide RNAs for the mutagenesis of target genes. We introduced these into an A. oryzae strain and obtained transformants containing mutations within each target gene that exhibited expected phenotypes. The mutational rates ranged from 10 to 20 %, and 1 bp deletions or insertions were the most commonly induced mutations.

Conclusions

We developed a functional and versatile genome editing method using the CRISPR/Cas9 system in A. oryzae. This technique will contribute to the use of efficient targeted mutagenesis in many A. oryzae industrial strains.

     

Comparative mapping of sequence-based and structure-based protein domains

Background  

Protein domains have long been an ill-defined concept in biology. They are generally described as autonomous folding units with evolutionary and functional independence. Both structure-based and sequence-based domain definitions have been widely used. But whether these types of models alone can capture all essential features of domains is still an open question.     

Speeding disease gene discovery by sequence based candidate prioritization

Background  

Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning.     

Temporal and spatial control of transgene expression using laser induction of the hsp70 promoter

Background  

Precise temporal and spatial regulation of transgene expression is a critical tool to investigate gene function in developing organisms. The most commonly used technique to achieve tight control of transgene expression, however, requires the use of specific DNA enhancers that are difficult to characterize in non-model organisms. Here, we sought to eliminate the need for this type of sequence-based gene regulation and to open the field of functional genetics to a broader range of organisms.     

A new approach to 'megaprimer' polymerase chain reaction mutagenesis without an intermediate gel purification step

Background  

Site-directed mutagenesis is an efficient method to alter the structure and function of genes. Here we report a rapid and efficient megaprimer-based polymerase chain reaction (PCR) mutagenesis strategy that by-passes any intermediate purification of DNA between two rounds of PCR.     

Conditional gene expression in the mouse using a Sleeping Beauty gene-trap transposon

Background  

Insertional mutagenesis techniques with transposable elements have been popular among geneticists studying model organisms from E. coli to Drosophila and, more recently, the mouse. One such element is the Sleeping Beauty (SB) transposon that has been shown in several studies to be an effective insertional mutagen in the mouse germline. SB transposon vector studies have employed different functional elements and reporter molecules to disrupt and report the expression of endogenous mouse genes. We sought to generate a transposon system that would be capable of reporting the expression pattern of a mouse gene while allowing for conditional expression of a gene of interest in a tissue- or temporal-specific pattern.     

Whole genome profiling of spontaneous and chemically induced mutations in Toxoplasma gondii

Background

Next generation sequencing is helping to overcome limitations in organisms less accessible to classical or reverse genetic methods by facilitating whole genome mutational analysis studies. One traditionally intractable group, the Apicomplexa, contains several important pathogenic protozoan parasites, including the Plasmodium species that cause malaria.Here we apply whole genome analysis methods to the relatively accessible model apicomplexan, Toxoplasma gondii, to optimize forward genetic methods for chemical mutagenesis using N-ethyl-N-nitrosourea (ENU) and ethylmethane sulfonate (EMS) at varying dosages.

Results

By comparing three different lab-strains we show that spontaneously generated mutations reflect genome composition, without nucleotide bias. However, the single nucleotide variations (SNVs) are not distributed randomly over the genome; most of these mutations reside either in non-coding sequence or are silent with respect to protein coding. This is in contrast to the random genomic distribution of mutations induced by chemical mutagenesis. Additionally, we report a genome wide transition vs transversion ratio (ti/tv) of 0.91 for spontaneous mutations in Toxoplasma, with a slightly higher rate of 1.20 and 1.06 for variants induced by ENU and EMS respectively. We also show that in the Toxoplasma system, surprisingly, both ENU and EMS have a proclivity for inducing mutations at A/T base pairs (78.6% and 69.6%, respectively).

Conclusions

The number of SNVs between related laboratory strains is relatively low and managed by purifying selection away from changes to amino acid sequence. From an experimental mutagenesis point of view, both ENU (24.7%) and EMS (29.1%) are more likely to generate variation within exons than would naturally accumulate over time in culture (19.1%), demonstrating the utility of these approaches for yielding proportionally greater changes to the amino acid sequence. These results will not only direct the methods of future chemical mutagenesis in Toxoplasma, but also aid in designing forward genetic approaches in less accessible pathogenic protozoa as well.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-354) contains supplementary material, which is available to authorized users.     

Limited genetic diversity in <Emphasis Type="Italic">Salmonella enterica</Emphasis> Serovar Enteritidis PT13

Background  

Salmonella enterica serovar Enteritidis has emerged as a significant foodborne pathogen throughout the world and is commonly characterized by phage typing. In Canada phage types (PT) 4, 8 and 13 predominate and in 2005 a large foodborne PT13 outbreak occurred in the province of Ontario. The ability to link strains during this outbreak was difficult due to the apparent clonality of PT13 isolates in Canada, as there was a single dominant pulsed-field gel electrophoresis (PFGE) profile amongst epidemiologically linked human and food isolates as well as concurrent sporadic strains. The aim of this study was to perform comparative genomic hybridization (CGH), DNA sequence-based typing (SBT) genomic analyses, plasmid analyses, and automated repetitive sequence-based PCR (rep-PCR) to identify epidemiologically significant traits capable of subtyping S. Enteritidis PT13.     

Phenotypic error threshold; additivity and epistasis in RNA evolution

Background  

The error threshold puts a limit on the amount of information maintainable in Darwinian evolution. The error threshold was first formulated in terms of genotypes. However, if a genotype-phenotype map involves redundancy ("mutational neutrality"), the error threshold should be formulated in terms of phenotypes since there is no unique fittest genotype. A previous study formulated the error threshold in terms of phenotypes, and their results showed that a rather low degree of mutational neutrality can increase the error threshold unlimitedly.     

Using the nucleotide substitution rate matrix to detect horizontal gene transfer

Background  

Horizontal gene transfer (HGT) has allowed bacteria to evolve many new capabilities. Because transferred genes perform many medically important functions, such as conferring antibiotic resistance, improved detection of horizontally transferred genes from sequence data would be an important advance. Existing sequence-based methods for detecting HGT focus on changes in nucleotide composition or on differences between gene and genome phylogenies; these methods have high error rates.     

SNAD: sequence name annotation-based designer

Background  

A growing diversity of biological data is tagged with unique identifiers (UIDs) associated with polynucleotides and proteins to ensure efficient computer-mediated data storage, maintenance, and processing. These identifiers, which are not informative for most people, are often substituted by biologically meaningful names in various presentations to facilitate utilization and dissemination of sequence-based knowledge. This substitution is commonly done manually that may be a tedious exercise prone to mistakes and omissions.     

Improving consensus contact prediction via server correlation reduction

Background  

Protein inter-residue contacts play a crucial role in the determination and prediction of protein structures. Previous studies on contact prediction indicate that although template-based consensus methods outperform sequence-based methods on targets with typical templates, such consensus methods perform poorly on new fold targets. However, we find out that even for new fold targets, the models generated by threading programs can contain many true contacts. The challenge is how to identify them.