Quantitative Measure of Small-Subunit rRNA Gene Sequences of the Kingdom Korarchaeota

Comparative PCR amplification of small-subunit (SSU) rRNA gene (rDNA) sequences indicates substantial preferential PCR amplification of pJP27 sequences with korarchaeote-specific PCR primers. The coamplification of a modified SSU rDNA sequence can be used as an internal standard to determine the amount of a specific SSU rDNA sequence.     

Quantitative Immunofluorescence Assay to Measure the Variation in Protein Levels at Centrosomes

Centrosomes are small but important organelles that serve as the poles of mitotic spindle to maintain genomic integrity or assemble primary cilia to facilitate sensory functions in cells. The level of a protein may be regulated differently at centrosomes than at other .cellular locations, and the variation in the centrosomal level of several proteins at different points of the cell cycle appears to be crucial for the proper regulation of centriole assembly. We developed a quantitative fluorescence microscopy assay that measures relative changes in the level of a protein at centrosomes in fixed cells from different samples, such as at different phases of the cell cycle or after treatment with various reagents. The principle of this assay lies in measuring the background corrected fluorescent intensity corresponding to a protein at a small region, and normalize that measurement against the same for another protein that does not vary under the chosen experimental condition. Utilizing this assay in combination with BrdU pulse and chase strategy to study unperturbed cell cycles, we have quantitatively validated our recent observation that the centrosomal pool of VDAC3 is regulated at centrosomes during the cell cycle, likely by proteasome-mediated degradation specifically at centrosomes.     

Latent Periodicity of Protein Sequences

This article is in the area of protein sequence investigation. It studies protein sequence periodicity. The notion of latent periodicity is introduced. A mathematical method for searching for latent periodicity in protein sequences is developed. Implementation of the method developed for known cases of perfect and imperfect periodicity is demonstrated. Latent periodicity of many protein sequences from the SWISS-PROT data bank is revealed by the method and examples of latent periodicity of amino acid sequences are demonstrated for: the translation initiation factor EIF-2B (epsilon subunit) of Saccharomyces cerevisiae from the E2BE_YEAST sequence; the E.coli ferrienterochelin receptor from the FEPA_ECOLI sequence; the lysozyme of Bacteriophage SF6 from the LY_BPSF6 sequence; lipoamide dehydrogenase of Azotobacter vinelandii from the DLDH_AZOVI sequence. These protein sequences have latent periods equal to six, two, seven and 19 amino acids, respectively. We propose that a possible purpose of the amino acid sequence latent periodicity is to determine certain protein structures.     

Correlations in Protein Sequences and Property Codes

Correlation functions in large sets of non-homologous protein sequences are analysed. Finite size corrections are applied and fluctuations are estimated. As symbol sequences have to be mapped to sequences of numbers to calculate correlation functions, several property codes are tested as such mappings. We found hydrophobicity autocorrelation functions to be strongly oscillating. Another strong signal is the monotonously decaying α-helix propensity autocorrelation function. Furthermore, we detected signals corresponding to an alteration of positively and negatively charged residues at a distance of 3–4 amino acids.To look beyond the property codes gained by the methods of physical chemistry, mappings yielding a strong correlation signal are sought for using a Monte Carlo simulation. The mappings leading to strong signals are found to be related to hydrophobicity of α-helix propensity. A cluster analysis of the top scoring mappings leads to two novel property codes. These two property codes are gained from sequence data only. They turn out to be similar to known property codes for hydrophobicity or polarity.     

Resolving Power: A Quantitative Measure of Electrophoretic Resolution

Resolving power is a quantitative measure of the ability of an electrophoretic system to separate DNA (and other) molecules of similar size. It is a dimensionless quantity, and hence facilitates comparison of the performance of electrophoretic systems that operate very differently. Resolving power can be determined as a function of molecular length from experimental data consisting of a series of completely resolved bands on a gel or blot; closely spaced bands are not required. We discuss factors such as the mass of DNA in a particular band and the spatial resolution of the system used to image the distribution of DNA on a gel or blot that, while not an intrinsic part of the electrophoretic system, may influence the observed resolving power. We derive an empirical global dispersion function that applies both to images of gels obtained after a fixed time of electrophoresis of all the samples and to images obtained as each species reaches a detector located at a fixed distance from the starting well. We use this dispersion function to show that the improvement in resolving power produced by extending the time or distance of electrophoresis in a static, uniform electric field asymptotically approaches a limiting value that is a function of the length of the DNA. When plotted as a function of molecular length, this limiting value defines an envelope that characterizes the intrinsic limits of performance of a particular electrophoretic system (e.g., electric field strength, gel type and concentration, buffer, temperature). Comparing the resolving power of static field agarose gel electrophoresis as routinely practiced for separating DNA molecules from 10³ to 10⁵ bp long with other electrophoretic schemes suggests that significant improvements should be achievable.     

A Quantitative Measure of Field Illumination

In this paper, we describe a statistically based algorithm to quantify the uniformity of illumination in an optical light microscopy imaging system that outputs a single quality factor (QF) score. The importance of homogeneous field illumination in quantitative light microscopy is well understood and often checked. However, there is currently no standard automatic quantitative measure of the uniformity of the field illumination. Images from 89 different laser-scanning confocal microscopes (LSCMs), which were collected as part of an international study on microscope quality assessment, were used as a “training” set to build the algorithm. To validate the algorithm and verify its robustness, images from 33 additional microscopes, including LSCM and wide-field (WF) microscopes, were used. The statistical paradigm used for developing the quality scoring scale was a regression approach to supervised learning. Three intensity profiles across each image—2 corner-to-corner diagonals and a center horizontal—were used to generate pixel-intensity data. All of the lines passed through the center of the image. The intensity profile data then were converted into a single-field illumination QF score in the range of 0–100, with 0 having extreme variation, and therefore, essentially unusable, and 100 having no deviation, i.e., straight lines with a constant uniform intensity. Empirically, a QF ≥ 83 was determined to be the minimum acceptable value based on manufacturer acceptance tests and reasonably achievable values. This new QF is an invaluable metric to ascertain objectively and easily the uniformity of illumination quality, provide a traceable reference for monitoring field uniformity over time, and make a direct comparison among different microscopes. The QF can also be used as an indicator of system failure and the need for alignment or service of the instrument.     

蛋白质序列间进化距离的估计

本文考察了目前采用的估计同源蛋白质序列间进化距离的方法缺陷,并提出了几个新的计算公式,它们考虑了氨基酸位点间显然存在的替代速率的差异。另外,提出了一种考虑氨基酸间不同替代概率的最大似然估计方法。文中对这些公式进行了计算比较,并对它在实际中的运用提出了建议。     

On the Information Content of Protein Sequences

Abstract

TATA-box binding protein (TBP) in a monomelic form and the complexes it forms with DNA have been elucidated with molecular dynamics simulations. Large TBP domain motions (bend and twist) are detected in the monomer as well as in the DNA complexes; these motions can be important for TBP binding of DNA. TBP interacts with guanine bases flanking the TATA element in the simulations of the complex; these interactions may explain the preference for guanine observed at these DNA positions. Side chains of some TBP residues at the binding interface display significant dynamic flexibility that results in ‘flipflop’ contacts involving multiple base pairs of the DNA. We discuss the possible functional significance of these observations.     

Identifying and Quantifying Orphan Protein Sequences in Fungi

For large regions of many proteins, and even entire proteins, no homology to known domains or proteins can be detected. These sequences are often referred to as orphans. Surprisingly, it has been reported that the large number of orphans is sustained in spite of a rapid increase of available genomic sequences. However, it is believed that de novo creation of coding sequences is rare in comparison to mechanisms such as domain shuffling and gene duplication; hence, most sequences should have homologs in other genomes.To investigate this, the sequences of 19 complete fungi genomes were compared. By using the phylogenetic relationship between these genomes, we could identify potentially de novo created orphans in Saccharomyces cerevisiae. We found that only a small fraction, < 2%, of the S. cerevisiae proteome is orphan, which confirms that de novo creation of coding sequences is indeed rare. Furthermore, we found it necessary to compare the most closely related species to distinguish between de novo created sequences and rapidly evolving sequences where homologs are present but cannot be detected.Next, the orphan proteins (OPs) and orphan domains (ODs) were characterized. First, it was observed that both OPs and ODs are short. In addition, at least some of the OPs have been shown to be functional in experimental assays, showing that they are not pseudogenes. Furthermore, in contrast to what has been reported before and what is seen for older orphans, S. cerevisiae specific ODs and proteins are not more disordered than other proteins. This might indicate that many of the older, and earlier classified, orphans indeed are fast-evolving sequences. Finally, > 90% of the detected ODs are located at the protein termini, which suggests that these orphans could have been created by mutations that have affected the start or stop codons.     

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish

Zebrafish are a proven model for vision research, however many of the earlier methods generally focused on larval fish or demonstrated a simple response. More recently adult visual behavior in zebrafish has become of interest, but methods to measure specific responses are new coming. To address this gap, we set out to develop a methodology to repeatedly and accurately utilize the optokinetic response (OKR) to measure visual acuity in adult zebrafish. Here we show that the adult zebrafish''s visual acuity can be measured, including both binocular and monocular acuities. Because the fish is not harmed during the procedure, the visual acuity can be measured and compared over short or long periods of time. The visual acuity measurements described here can also be done quickly allowing for high throughput and for additional visual procedures if desired. This type of analysis is conducive to drug intervention studies or investigations of disease progression.     

Linguistic Measure of Taxonomic and Functional Relatedness of Nucleotide Sequences

Abstract

The frequencies of “words”, oligonucleotides within nucleotide sequences, reflect the genetic information contained in the sequence “texts”. Nucleotide sequences are characteristically represented by their contrast word vocabularies. Comparison of the sequences by correlating their contrast vocabularies is shown to reflect well the relatedness (unrelatedness) between the sequences. A single value, the linguistic similarity between the sequences, is suggested asa measure of sequence relatedness. Sequences as short as 1000 bases can be characterized and quantitatively related to other sequences by this technique. The linguistic sequence similarity value is used for analysis of taxonomically and functionally diverse nucleotide sequences. The similarity value is shown to be very sensitive to the relatedness of the source species, thus providing a convenient tool for taxonomic classification of species by their sequence vocabularies. Functionally diverse sequences appear distinct by their linguistic similarity values. This can be a basis for a quick screening technique for functional characterization of the sequences and for mapping functionally distinct regions in long sequences.     

A Score of the Ability of a Three-Dimensional Protein Model to Retrieve Its Own Sequence as a Quantitative Measure of Its Quality and Appropriateness

Background

Despite the remarkable progress of bioinformatics, how the primary structure of a protein leads to a three-dimensional fold, and in turn determines its function remains an elusive question. Alignments of sequences with known function can be used to identify proteins with the same or similar function with high success. However, identification of function-related and structure-related amino acid positions is only possible after a detailed study of every protein. Folding pattern diversity seems to be much narrower than sequence diversity, and the amino acid sequences of natural proteins have evolved under a selective pressure comprising structural and functional requirements acting in parallel.

Principal Findings

The approach described in this work begins by generating a large number of amino acid sequences using ROSETTA [Dantas G et al. (2003) J Mol Biol 332:449–460], a program with notable robustness in the assignment of amino acids to a known three-dimensional structure. The resulting sequence-sets showed no conservation of amino acids at active sites, or protein-protein interfaces. Hidden Markov models built from the resulting sequence sets were used to search sequence databases. Surprisingly, the models retrieved from the database sequences belonged to proteins with the same or a very similar function. Given an appropriate cutoff, the rate of false positives was zero. According to our results, this protocol, here referred to as Rd.HMM, detects fine structural details on the folding patterns, that seem to be tightly linked to the fitness of a structural framework for a specific biological function.

Conclusion

Because the sequence of the native protein used to create the Rd.HMM model was always amongst the top hits, the procedure is a reliable tool to score, very accurately, the quality and appropriateness of computer-modeled 3D-structures, without the need for spectroscopy data. However, Rd.HMM is very sensitive to the conformational features of the models'' backbone.     

蛋白质序列的特征周期研究

利用Fourier乘积谱(Fourier product spectrum,FPS)系统计算了76个蛋白质亚家族的疏水自由能(HΦ)序列、电子离子相互作用势(electron-ion interaction potential,EIIP)序列和结构拓扑指数(Balaban指数)序列的特征周期;讨论了特征周期的规律;并以时间周期谱(time periodicity spectrum,TPS)演示了如何定位特征周期在蛋白质序列上的热区.结果表明EIIP特征周期热区与蛋白质结合位点有较好的对应关系.     

On Graphical and Numerical Representation of Protein Sequences

Abstract

A new approach using a 3-D Cartesian coordinate system to represent protein sequences has been derived. By the 3-D Graphical representation we make a comparison of sequences belonging to nine different proteins.     

Prediction of S-Glutathionylation Sites Based on Protein Sequences

S-glutathionylation, the reversible formation of mixed disulfides between glutathione(GSH) and cysteine residues in proteins, is a specific form of post-translational modification that plays important roles in various biological processes, including signal transduction, redox homeostasis, and metabolism inside cells. Experimentally identifying S-glutathionylation sites is labor-intensive and time consuming, whereas bioinformatics methods provide an alternative way to this problem by predicting S-glutathionylation sites in silico. The bioinformatics approaches give not only candidate sites for further experimental verification but also bio-chemical insights into the mechanism of S-glutathionylation. In this paper, we firstly collect experimentally determined S-glutathionylated proteins and their corresponding modification sites from the literature, and then propose a new method for predicting S-glutathionylation sites by employing machine learning methods based on protein sequence data. Promising results are obtained by our method with an AUC (area under ROC curve) score of 0.879 in 5-fold cross-validation, which demonstrates the predictive power of our proposed method. The datasets used in this work are available at http://csb.shu.edu.cn/SGDB.     

Alignment of Helical Membrane Protein Sequences Using AlignMe

Few sequence alignment methods have been designed specifically for integral membrane proteins, even though these important proteins have distinct evolutionary and structural properties that might affect their alignments. Existing approaches typically consider membrane-related information either by using membrane-specific substitution matrices or by assigning distinct penalties for gap creation in transmembrane and non-transmembrane regions. Here, we ask whether favoring matching of predicted transmembrane segments within a standard dynamic programming algorithm can improve the accuracy of pairwise membrane protein sequence alignments. We tested various strategies using a specifically designed program called AlignMe. An updated set of homologous membrane protein structures, called HOMEP2, was used as a reference for optimizing the gap penalties. The best of the membrane-protein optimized approaches were then tested on an independent reference set of membrane protein sequence alignments from the BAliBASE collection. When secondary structure (S) matching was combined with evolutionary information (using a position-specific substitution matrix (P)), in an approach we called AlignMePS, the resultant pairwise alignments were typically among the most accurate over a broad range of sequence similarities when compared to available methods. Matching transmembrane predictions (T), in addition to evolutionary information, and secondary-structure predictions, in an approach called AlignMePST, generally reduces the accuracy of the alignments of closely-related proteins in the BAliBASE set relative to AlignMePS, but may be useful in cases of extremely distantly related proteins for which sequence information is less informative. The open source AlignMe code is available at https://sourceforge.net/projects/alignme/, and at http://www.forrestlab.org, along with an online server and the HOMEP2 data set.     

Rapid Evolution of Virus Sequences in Intrinsically Disordered Protein Regions

Nodamura Virus (NoV) is a nodavirus originally isolated from insects that can replicate in a wide variety of hosts, including mammals. Because of their simplicity and ability to replicate in many diverse hosts, NoV, and the Nodaviridae in general, provide a unique window into the evolution of viruses and host-virus interactions. Here we show that the C-terminus of the viral polymerase exhibits extreme structural and evolutionary flexibility. Indeed, fewer than 10 positively charged residues from the 110 amino acid-long C-terminal region of protein A are required to support RNA1 replication. Strikingly, this region can be replaced by completely unrelated protein sequences, yet still produce a functional replicase. Structure predictions, as well as evolutionary and mutational analyses, indicate that the C-terminal region is structurally disordered and evolves faster than the rest of the viral proteome. Thus, the function of an intrinsically unstructured protein region can be independent of most of its primary sequence, conferring both functional robustness and sequence plasticity on the protein. Our results provide an experimental explanation for rapid evolution of unstructured regions, which enables an effective exploration of the sequence space, and likely function space, available to the virus.     

CodHonEditor: Spreadsheets for Codon Optimization and Editing of Protein Coding Sequences

Gene synthesis is getting more important with the growing availability of low-cost commercial services. The coding sequences are often “optimized” as for the relative synonymous codon usage (RSCU) before synthesis, which is generally included in the commercial services. However, the codon optimization processes are different among different providers and are often hidden from the users. Here, the d'Hondt method, which is widely adopted as a method for determining the number of seats for each party in proportional-representation public elections, is applied to RSCU fitting. This allowed me to make a set of electronic spreadsheets for manual design of protein coding sequences for expression in Escherichia coli, with which users can see the process of codon optimization and can manually edit the codons after the automatic optimization. The spreadsheets may also be useful for molecular biology education