Protein Sequence Determination Research Articles

Paving the way to single-molecule protein sequencing.

Proteins are major building blocks of life. The protein content of a cell and an organism provides key information for the understanding of biological processes and disease. Despite the importance of protein analysis, only a handful of techniques are available to determine protein sequences, and these methods face limitations, for example, requiring a sizable amount of sample. Single-molecule techniques would revolutionize proteomics research, providing ultimate sensitivity for the detection of low-abundance proteins and the realization of single-cell proteomics. In recent years, novel single-molecule protein sequencing schemes that use fluorescence, tunnelling currents and nanopores have been proposed. Here, we present a review of these approaches, together with the first experimental efforts towards their realization. We discuss their advantages and drawbacks, and present our perspective on the development of single-molecule protein sequencing techniques.

Algorithm of Protein Sequence Determination by Combination of the Edman Degradation Method and Shotgun Mass Spectrometry

An algorithm combining advantages of the Edman degradation method and de novo mass-spectrometric sequencing was developed. The protein from the “Diaskintest” diagnostic test was used for analysis. The protein was digested with trypsin and 5 steps of Edman degradation were carried out sequentially for the mixture of peptides. At each stage, the resulting mixture was analyzed by shotgun mass spectrometry analysis. The results of mass-spectrometry were analyzed both by the well-known de novo sequencing programs Novor and PepNovo+, and by own program that clustered individual spectra with a C-terminal signature formed by Y-ions. This approach allows us to determine confidently the amino acid sequence of the N-terminal part of the peptides obtained after the protein hydrolysis by trypsin.

ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network.

With the development of next generation sequencing techniques, it is fast and cheap to determine protein sequences but relatively slow and expensive to extract useful information from protein sequences because of limitations of traditional biological experimental techniques. Protein function prediction has been a long standing challenge to fill the gap between the huge amount of protein sequences and the known function. In this paper, we propose a novel method to convert the protein function problem into a language translation problem by the new proposed protein sequence language “ProLan” to the protein function language “GOLan”, and build a neural machine translation model based on recurrent neural networks to translate “ProLan” language to “GOLan” language. We blindly tested our method by attending the latest third Critical Assessment of Function Annotation (CAFA 3) in 2016, and also evaluate the performance of our methods on selected proteins whose function was released after CAFA competition. The good performance on the training and testing datasets demonstrates that our new proposed method is a promising direction for protein function prediction. In summary, we first time propose a method which converts the protein function prediction problem to a language translation problem and applies a neural machine translation model for protein function prediction.

Single-Molecule Protein Fingerprinting with Nanopores

Proteins are the most abundant biomolecules in the human body. Proteomics is instrumental to understand and detect diseases. Despite the importance of protein analysis, only a handful of techniques are available to determine protein sequences and these face limitations, for example in the sizeable sample volume needed. During the last few decades, nanopore technology has emerged as one of the most promising techniques to sequence DNA. Sequencing proteins at the single-molecule level is a clear next step.

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

SFA-SPA: a suffix array based short peptide assembler for metagenomic data.

The determination of protein sequences from a metagenomic dataset enables the study of metabolism and functional roles of the organisms that are present in the sampled microbial community. We had previously introduced algorithm and software for the accurate reconstruction of protein sequences from short peptides identified on nucleotide reads in a metagenomic dataset. Here, we present significant computational improvements to the short peptide assembly algorithm that make it practical to reconstruct proteins from large metagenomic datasets containing several hundred million reads, while maintaining accuracy. The improved computational efficiency is achieved using a suffix array data structure that allows for fast querying during the assembly process, and a significant redesign of assembly steps that enables multi-threaded execution. The program is available under the GPLv3 license from sourceforge.net/projects/spa-assembler.

The use of native gels for the concomitant determination of protein sequences and modifications by mass spectrometry with subsequent conformational and functional analysis of native proteins following electro-elution

The protocol consists of running a native gel with in-gel digestion by proteases, subsequent mass spectrometrical determination of protein sequence and modifications, followed by electro-elution and conformational analysis using melting point and circular dichroism. Finally, the eluted protein is tested for preserved function. Herein, C1 esterase inhibitor is applied on a native gel; in-gel digestion by proteases is carried out and peptides are identified by nano-LC-ESI-CID/ETD-MS/MS using an ion trap for generation of peptide sequences and protein modifications. Protein from replicate bands from the same gel is electro-eluted and used for determination of the melting point and used for circular dichroism analysis. Additional bands from the native gel are either in-gel digested with asparaginase to generate deamidation or PNGase F for deglycosylation, followed by mass spectrometry, conformational and functional studies. Preserved conformation and function of the C1 esterase inhibitor was shown. This protocol can be completed in 1week.

Identification of amino acid sequences via X-ray crystallography: a mini review of case studies

ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Pietrzyk A, Bujacz A, Jaskolski M, Bujacz G. Identification of amino acid sequences via X-ray crystallography: a mini review of case studies. BioTechnologia. 2013;94(1):9-14. doi:10.5114/bta.2013.46427. APA Pietrzyk, A., Bujacz, A., Jaskolski, M., & Bujacz, G. (2013). Identification of amino acid sequences via X-ray crystallography: a mini review of case studies. BioTechnologia, 94(1), 9-14. https://doi.org/10.5114/bta.2013.46427 Chicago Pietrzyk, Agnieszka J., Anna Bujacz, Mariusz Jaskolski, and Grzegorz Bujacz. 2013. "Identification of amino acid sequences via X-ray crystallography: a mini review of case studies". BioTechnologia 94 (1): 9-14. doi:10.5114/bta.2013.46427. Harvard Pietrzyk, A., Bujacz, A., Jaskolski, M., and Bujacz, G. (2013). Identification of amino acid sequences via X-ray crystallography: a mini review of case studies. BioTechnologia, 94(1), pp.9-14. https://doi.org/10.5114/bta.2013.46427 MLA Pietrzyk, Agnieszka J. et al. "Identification of amino acid sequences via X-ray crystallography: a mini review of case studies." BioTechnologia, vol. 94, no. 1, 2013, pp. 9-14. doi:10.5114/bta.2013.46427. Vancouver Pietrzyk A, Bujacz A, Jaskolski M, Bujacz G. Identification of amino acid sequences via X-ray crystallography: a mini review of case studies. BioTechnologia. 2013;94(1):9-14. doi:10.5114/bta.2013.46427.

Characterization of Bean Necrotic Mosaic Virus: A Member of a Novel Evolutionary Lineage within the Genus Tospovirus

BackgroundTospoviruses (Genus Tospovirus, Family Bunyaviridae) are phytopathogens responsible for significant worldwide crop losses. They have a tripartite negative and ambisense RNA genome segments, termed S (Small), M (Medium) and L (Large) RNA. The vector-transmission is mediated by thrips in a circulative-propagative manner. For new tospovirus species acceptance, several analyses are needed, e.g., the determination of the viral protein sequences for enlightenment of their evolutionary history.Methodology/Principal FindingsBiological (host range and symptomatology), serological, and molecular (S and M RNA sequencing and evolutionary studies) experiments were performed to characterize and differentiate a new tospovirus species, Bean necrotic mosaic virus (BeNMV), which naturally infects common beans in Brazil. Based upon the results, BeNMV can be classified as a novel species and, together with Soybean vein necrosis-associated virus (SVNaV), they represent members of a new evolutionary lineage within the genus Tospovirus.Conclusion/SignificancesTaken together, these evidences suggest that two divergent lineages of tospoviruses are circulating in the American continent and, based on the main clades diversity (American and Eurasian lineages), new tospovirus species related to the BeNMV-SVNaV clade remain to be discovered. This possible greater diversity of tospoviruses may be reflected in a higher number of crops as natural hosts, increasing the economic impact on agriculture. This idea also is supported since BeNMV and SVNaV were discovered naturally infecting atypical hosts (common bean and soybean, respectively), indicating, in this case, a preference for leguminous species. Further studies, for instance a survey focusing on crops, specifically of leguminous plants, may reveal a greater tospovirus diversity not only in the Americas (where both viruses were reported), but throughout the world.

PSS-3D1D: an improved 3D1D profile method of protein fold recognition for the annotation of twilight zone sequences

Annotation of any newly determined protein sequence depends on the pairwise sequence identity with known sequences. However, for the twilight zone sequences which have only 15-25% identity, the pair-wise comparison methods are inadequate and the annotation becomes a challenging task. Such sequences can be annotated by using methods that recognize their fold. Bowie etal. described a 3D1D profile method in which the amino acid sequences that fold into a known 3D structure are identified by their compatibility to that known 3D structure. We have improved the above method by using the predicted secondary structure information and employ it for fold recognition from the twilight zone sequences. In our Protein Secondary Structure 3D1D (PSS-3D1D) method, a score (w) for the predicted secondary structure of the query sequence is included in finding the compatibility of the query sequence to the known fold 3D structures. In the benchmarks, the PSS-3D1D method shows a maximum of 21% improvement in predicting correctly the α + β class of folds from the sequences with twilight zone level of identity, when compared with the 3D1D profile method. Hence, the PSS-3D1D method could offer more clues than the 3D1D method for the annotation of twilight zone sequences. The web based PSS-3D1D method is freely available in the PredictFold server at http://bioinfo.bdu.ac.in/servers/ .

Specificity in Computational Protein Design

A long-standing goal of computational protein design is to create proteins similar to those found in Nature. One motivation is to harness the exquisite functional capabilities of proteins for our own purposes. The extent of similarity between designed and natural proteins also reports on how faithfully our models represent the selective pressures that determine protein sequences. As the field of protein design shifts emphasis from reproducing native-like protein structure to function, it has become important that these models treat the notion of specificity in molecular interactions. Although specificity may, in some cases, be achieved by optimization of a desired protein in isolation, methods have been developed to address directly the desire for proteins that exhibit specific functions and interactions.

Statistical Analysis of Peptide Electron Transfer Dissociation Fragmentation Mass Spectrometry

It is well established that protein sequence determination may be achieved by mass spectrometric analysis of protonated tryptic peptides subjected to collisional activation. When separated by nanoflow HPLC, a high percentage of peptides from complex mixtures of proteins can usually be identified. Recently, alternative, radical-driven fragmentation approaches of electron capture dissociation and the more common electron transfer dissociation (ETD) have been introduced and made widely available. In order to utilize these techniques in large scale proteomics studies, it is important to characterize the performance of these fragmentation processes on peptides formed by a range of enzymatic cleavages. In this study, we present a statistical analysis of the ion types that are observed from peptides produced by different enzymes and highlight the different characteristics of ETD spectra of doubly charged precursors in comparison to precursors of higher charge states.

Protein-specific glycosylation: signal patches and cis-controlling peptidic elements

The term 'protein-specific glycosylation' refers to important functional implications of a subset of glycosylation types that are under direct control of recognition determinants on the protein. Examples of the latter are found in the formation of the mannose-6-phosphate receptor ligand on lysosomal hydrolases, and in polysialylation of NCAM, which are regulated via conformational signal patches on the protein. Distinct from these examples, the beta4-GalNAc modification of N-linked glycans on a selected panel of proteins, such as carbonic anhydrase or glycodelin, was demonstrated recently to require specific protein (sequence) determinants proximal to the glycosylation site that function as cis-regulatory elements. Another example of such a cis-regulatory element was described for the control of mammalian O-mannosylation. In this case, the structural features of substrate sites within the mucin domain of alpha-dystroglycan are necessary, but not sufficient for determining the transfer of mannose to Ser/Thr. Evidence has been provided that an upstream-located peptide is also essential. Such cis-controlling elements provide a higher level of protein specificity, because a putative glycosylation site cannot result from a single point mutation. Here, we highlight recent work on protein-specific glycosylation with particular emphasis on the above-cited examples and we will try to link protein-specific glycosylation to function.

Impact of the Pneumococcal Conjugate Vaccine on Serotype Distribution and Antimicrobial Resistance of Invasive Streptococcus pneumoniae Isolates in Dallas, TX, Children From 1999 Through 2005

Because the heptavalent pneumococcal conjugate vaccine has reduced vaccine-type invasive pneumococcal disease (IPD) in children, a greater proportion of IPD is now caused by nonvaccine (NVT) serotypes. We analyzed the serotypes, antimicrobial resistance profiles and genetic relatedness of Streptococcus pneumoniae responsible for IPD at Children's Medical Center of Dallas. S. pneumoniae isolates were collected from January 1, 1999 through December 31, 2005. Incidence of IPD was calculated using inpatient and emergency center admissions to Children's Medical Center of Dallas as the denominator. Isolates were serotyped, and their penicillin and cefotaxime susceptibility determined. The 19A isolates were further characterized by pulsed-field gel electrophoresis, multilocus sequence typing and determination of penicillin-binding proteins and mef and erm genes. The incidence of IPD decreased from 93.6 cases/100,000 patients in 1999 to a nadir of 41 cases/100,000 patients in 2003 (P < 0.001). The number of IPD cases caused by serotype 19A increased, accounting for 40% of the cases of IPD in 2005. Penicillin and cefotaxime susceptibility of IPD isolates did not change from 1999 through 2005 (P = 0.687). There was a decrease in penicillin (P < 0.001) and cefotaxime (P = 0.034) susceptibility in NVT serotypes from 1999 to 2005. Molecular characterization of 19A isolates revealed a predominance of ST-199 (62%). Several highly penicillin-resistant and intermediately cefotaxime-resistant strains emerged in 2004 and 2005. In Dallas, heptavalent pneumococcal conjugate vaccine reduced the incidence of IPD from 1999 to 2005 by reducing the incidence of vaccine-type disease. NVT serotypes, particularly 19A, were prevalent and more resistant to antimicrobials in 2004 and 2005.

Identification of a novel panel of cerebrospinal fluid biomarkers for Alzheimer's disease

An early and accurate diagnosis of Alzheimer's disease (AD) is required to initiate symptomatic treatment with currently approved drugs and will be of even greater importance if disease modifying compounds in development display a clinical effect. Protein profiles of human cerebrospinal fluid samples from AD patients ( n = 95) and population-based healthy controls ( n = 72) were analyzed by SELDI-TOF-MS in order to discover and characterize novel candidate biomarker combinations that differentiate AD patients from normal aging in this explorative study. Thirty candidate biomarkers (ROC AUC > 0.7) were discovered that could differentiate patients with AD from healthy controls. Protein sequence determination and positive identification of 15 biomarkers revealed potential associations between the identified markers and AD pathogenesis. A multi-marker combination of five peaks could distinguish AD from healthy control individuals with high sensitivity (97%) and specificity (98%). The panel of five markers was tested on a blinded independent data set of 30 AD samples and 28 controls giving 100% sensitivity and 97% specificity. This novel panel of biomarkers could potentially be used to improve the accuracy of diagnosis of AD.

A Basic Molecular Analysis of the Diabetic Antigen GAD by Homology Modelling. Principles of the Method and Understanding of Antigenicity and Binding Sites

Abstract Functional specificity of a protein is linked to its structure. A growing section of bioinformatics deals with the prediction and visualization of protein 3D structures. In homology modelling, a protein sequence with an unknown structure is aligned with sequences of known protein structures. By exploiting structural information from the known configurations, the new structure can be predicted. In this introductory paper, we will present the principles of homology modelling and demonstrate the method used, by determining the structure of the enzyme glutamic decarboxylase (GAD 65). This protein is an autoantigen involved in several human autoimmune diseases. We will illustrate the different steps in structure prediction of GAD 65 by use of two experimentally determined structures of pig kidney DOPA decarboxylase (one structure in complex with the inhibitor carbidopa) as templates. The resulting model of GAD 65 provides detailed information about the active site of the protein and selected epitopes. By analysis of the interactions between the DOPA decarboxylase with the inhibitor carbidopa, the residues of the GAD 65 active site can be identified via the sequence alignment between DOPA and GAD 65. The locations of known epitopes in the molecule are visualized in special representations giving insights into mechanisms of antigenicity. Hydrophobicity analysis gives first hints for the adherence ability of GAD 65 to the cell membrane. Homology modelling is at present one of the most efficient techniques to provide accurate structural models of proteins. It is expected that in few years, for every new determined protein sequence, at least one member with a known structure of the same protein family will be available, which will steadily increase the importance and applicability of homology modelling.

Protein and DNA sequence determinants of thermophilic adaptation.

There have been considerable attempts in the past to relate phenotypic trait—habitat temperature of organisms—to their genotypes, most importantly compositions of their genomes and proteomes. However, despite accumulation of anecdotal evidence, an exact and conclusive relationship between the former and the latter has been elusive. We present an exhaustive study of the relationship between amino acid composition of proteomes, nucleotide composition of DNA, and optimal growth temperature (OGT) of prokaryotes. Based on 204 complete proteomes of archaea and bacteria spanning the temperature range from −10 °C to 110 °C, we performed an exhaustive enumeration of all possible sets of amino acids and found a set of amino acids whose total fraction in a proteome is correlated, to a remarkable extent, with the OGT. The universal set is Ile, Val, Tyr, Trp, Arg, Glu, Leu (IVYWREL), and the correlation coefficient is as high as 0.93. We also found that the G + C content in 204 complete genomes does not exhibit a significant correlation with OGT (R = −0.10). On the other hand, the fraction of A + G in coding DNA is correlated with temperature, to a considerable extent, due to codon patterns of IVYWREL amino acids. Further, we found strong and independent correlation between OGT and the frequency with which pairs of A and G nucleotides appear as nearest neighbors in genome sequences. This adaptation is achieved via codon bias. These findings present a direct link between principles of proteins structure and stability and evolutionary mechanisms of thermophylic adaptation. On the nucleotide level, the analysis provides an example of how nature utilizes codon bias for evolutionary adaptation to extreme conditions. Together these results provide a complete picture of how compositions of proteomes and genomes in prokaryotes adjust to the extreme conditions of the environment.

Molecular approaches for identification and construction of novel insecticidal genes for crop protection

The insecticidal cry (crystal) genes from Bacillus thuringiensis (Bt) have been used for insect control both as biopesticides and in transgenic plants. Discovery of new insecticidal genes is of importance for delaying the development of resistance in target insects. The diversity of Bt strains facilitates isolation of new types of cry and vip (vegetative insecticidal protein) genes. PCR is a useful technique for quick and simultaneous screening of Bt strains for classification and prediction of insecticidal activities. PCR together with other methods of analysis such as RFLP, gene sequence determination, electrophoretic, immunological and chromatographic analysis of Cry proteins and insect bioassays for evaluation of toxicity have been employed for identification of new insecticidal proteins. Some other new approaches have also been devised. Many Bt strains with novel insecticidal genes have been found. A desired combination of Cry proteins can be assembled via site-specific recombination vectors into a recipient Bt strain to create a genetically improved biopesticide. For better pest control, the cry genes have been transferred to plants. Stacking of more than one insecticidal gene is required for resistance management in transgenic crops. Modification of Cry proteins through protein engineering for increasing the toxicity and/or the insecticidal spectrum is also a promising approach, but requires detailed understanding of the structure and function of these proteins and analysis of toxin-receptor interactions. More research into this area will provide useful insights for the design of toxins for management of insect resistance. Insecticidal genes from other bacteria and plants are also being examined for their potential for deployment in transgenic crops. Stringent implementation of resistance management is needed for maintaining the efficacy of Bt transgenic crops and deriving maximum economic and environmental benefit.

Bacillolysin MA, a Novel Bacterial Metalloproteinase That Produces Angiostatin-like Fragments from Plasminogen and Activates Protease Zymogens in the Coagulation and Fibrinolysis Systems

We isolated a novel protease that converts plasminogen to angiostatin-like fragments (BL-angiostatins) from a culture of Bacillus megaterium A9542 through a single-step chromatography on CM-cellulose. The protease, designated bacillolysin MA (BL-MA), belongs to a family of neutral metalloproteinases based on the nucleotide sequence of its gene. At an enzyme:substrate ratio of 1:540, BL-MA cleaved human plasminogen mainly at Ser441-Val442 to form BL-angiostatin and miniplasminogen with a K(m) of 3.0 +/- 0.8 microM and a k(cat) of 0.70 +/- 0.09 s(-1). The resulting BL-angiostatins inhibited the proliferation, migration, and tube formation of vascular endothelial cells at concentrations of 1-10 microg/ml. Although BL-MA failed to activate plasminogen, it increased urokinase-catalyzed activation of plasminogen caused by production of miniplasminogen, which is highly susceptible to activation. In addition, BL-MA was active in converting prourokinase, prothrombin, coagulation factor X, and protein C to their active forms. BL-MA enhanced both the clotting of human plasma and clot dissolution in the presence of prourokinase. Thus, BL-MA affects blood coagulation and fibrinolysis systems and can be used to produce angiostatin-like plasminogen fragments and active serine proteases of human plasma.

Protein and DNA sequence determinants of thermophilic adaptation

Protein and DNA sequence determinants of thermophilic adaptation