Systematic assessment of the benefits and caveats in mining microbial post-translational modifications from shotgun proteomic data: the response of Shewanella oneidensis to chromate exposure

Microbes are known to regulate both gene expression and protein activity through the use of post-translational modifications (PTMs). Common PTMs involved in cellular signaling and gene control include methylations, acetylations, and phosphorylations, whereas oxidations have been implicated as an indicator of stress. Shewanella oneidensis MR-1 is a Gram-negative bacterium that demonstrates both respiratory versatility and the ability to sense and adapt to diverse environmental conditions. The data set used in this study consisted of tandem mass spectra derived from midlog phase aerobic cultures of S. oneidensis either native or shocked with 1 mM chromate [Cr(VI)]. In this study, three algorithms (DBDigger, Sequest, and InsPecT) were evaluated for their ability to scrutinize shotgun proteomic data for evidence of PTMs. The use of conservative scoring filters for peptides or proteins versus creating a subdatabase first from a nonmodification search was evaluated with DBDigger. The use of higher-scoring filters for peptide identifications was found to result in optimal identifications of PTM peptides with a 2% false discovery rate (FDR) for the total data set using the DBDigger algorithm. However, the FDR climbs to unacceptably high levels when only PTM peptides are considered. Sequest was evaluated as a method for confirming PTM peptides putatively identified using DBDigger; however, there was a low identification rate ( approximately 25%) for the searched spectra. InsPecT was found to have a much lower, and thus more acceptable, FDR than DBDigger for PTM peptides. Comparisons between InsPecT and DBDigger were made with respect to both the FDR and PTM peptide identifications. As a demonstration of this approach, a number of S. oneidensis chemotaxis proteins as well as low-abundance signal transduction proteins were identified as being post-translationally modified in response to chromate challenge.     

ModifiComb, a new proteomic tool for mapping substoichiometric post-translational modifications, finding novel types of modifications, and fingerprinting complex protein mixtures

A major challenge in proteomics is to fully identify and characterize the post-translational modification (PTM) patterns present at any given time in cells, tissues, and organisms. Here we present a fast and reliable method ("ModifiComb") for mapping hundreds types of PTMs at a time, including novel and unexpected PTMs. The high mass accuracy of Fourier transform mass spectrometry provides in many cases unique elemental composition of the PTM through the difference DeltaM between the molecular masses of the modified and unmodified peptides, whereas the retention time difference DeltaRT between their elution in reversed-phase liquid chromatography provides an additional dimension for PTM identification. Abundant sequence information obtained with complementary fragmentation techniques using ion-neutral collisions and electron capture often locates the modification to a single residue. The (DeltaM, DeltaRT) maps are representative of the proteome and its overall modification state and may be used for database-independent organism identification, comparative proteomic studies, and biomarker discovery. Examples of newly found modifications include +12.000 Da (+C atom) incorporation into proline residues of peptides from proline-rich proteins found in human saliva. This modification is hypothesized to increase the known activity of the peptide.     

VEMS 3.0: algorithms and computational tools for tandem mass spectrometry based identification of post-translational modifications in proteins

Protein and peptide mass analysis and amino acid sequencing by mass spectrometry is widely used for identification and annotation of post-translational modifications (PTMs) in proteins. Modification-specific mass increments, neutral losses or diagnostic fragment ions in peptide mass spectra provide direct evidence for the presence of post-translational modifications, such as phosphorylation, acetylation, methylation or glycosylation. However, the commonly used database search engines are not always practical for exhaustive searches for multiple modifications and concomitant missed proteolytic cleavage sites in large-scale proteomic datasets, since the search space is dramatically expanded. We present a formal definition of the problem of searching databases with tandem mass spectra of peptides that are partially (sub-stoichiometrically) modified. In addition, an improved search algorithm and peptide scoring scheme that includes modification specific ion information from MS/MS spectra was implemented and tested using the Virtual Expert Mass Spectrometrist (VEMS) software. A set of 2825 peptide MS/MS spectra were searched with 16 variable modifications and 6 missed cleavages. The scoring scheme returned a large set of post-translationally modified peptides including precise information on modification type and position. The scoring scheme was able to extract and distinguish the near-isobaric modifications of trimethylation and acetylation of lysine residues based on the presence and absence of diagnostic neutral losses and immonium ions. In addition, the VEMS software contains a range of new features for analysis of mass spectrometry data obtained in large-scale proteomic experiments. Windows binaries are available at http://www.yass.sdu.dk/.     

HGVbase: a human sequence variation database emphasizing data quality and a broad spectrum of data sources

HGVbase (Human Genome Variation database; http://hgvbase.cgb.ki.se, formerly known as HGBASE) is an academic effort to provide a high quality and non-redundant database of available genomic variation data of all types, mostly comprising single nucleotide polymorphisms (SNPs). Records include neutral polymorphisms as well as disease-related mutations. Online search tools facilitate data interrogation by sequence similarity and keyword queries, and searching by genome coordinates is now being implemented. Downloads are freely available in XML, Fasta, SRS, SQL and tagged-text file formats. Each entry is presented in the context of its surrounding sequence and many records are related to neighboring human genes and affected features therein. Population allele frequencies are included wherever available. Thorough semi-automated data checking ensures internal consistency and addresses common errors in the source information. To keep pace with recent growth in the field, we have developed tools for fully automated annotation. All variants have been uniquely mapped to the draft genome sequence and are referenced to positions in EMBL/GenBank files. Data utility is enhanced by provision of genotyping assays and functional predictions. Recent data structure extensions allow the capture of haplotype and genotype information, and a new initiative (along with BiSC and HUGO-MDI) aims to create a central repository for the broad collection of clinical mutations and associated disease phenotypes of interest.     

Different sequence patterns in signal peptides from mycoplasmas, other gram-positive bacteria, and Escherichia coli: a multivariate data analysis

Signal peptides are essential N-terminal extensions in export proteins, and have a positively charged N-terminus, a hydrophobic central core, and a C-terminal cleavage region. They interact in a consecutive manner with different accessory proteins during the secretion process. Potential patterns or periodicity in the amino acid (aa) sequence were searched, using multivariate techniques, for a large number of signal peptides from mollicutes (mycoplasmas), other Gram-positive bacteria, and Escherichia coli. Mollicutes signal peptides were significantly different from the E. coli and Gram-positive ones by their N-terminal charge, peptide length, and especially, unique periodicities of side chain hydrophobicity and volumes. Their lipoprotein signal peptides were longer than for any other bacteria. Significant differences were also recorded between the other bacterial peptide groups. Specific aa patterns were more related within the signal peptides from several groups of secreted bacillus enzymes, than for all signal peptides from one bacillus species. In E. coli, signal peptides from proteins routed for the various destinations revealed significant and compartment-specific sequence patterns not evident by other methods. This was substantiated from a large number of signal peptide secretion mutants for the E. coli periplasmic space. It is proposed that the differences in aa patterns and side-chain properties are related to the secondary structure sidedness and topology of the signal peptides, and important for specific interactions during the secretion process.     

Molecular identification and sequence analysis of Hillarin, a novel protein localized at the axon hillock.

The monoclonal antibody Lan3-15 identifies a novel protein, Hillarin, that is localized to the axon hillock of leech neurons. Using this antibody we have identified a full length cDNA coding for leech Hillarin and determined its sequence. The gene encodes a 1274 residue protein with a predicted molecular mass of 144013 Da. Data base searches revealed that leech Hillarin has potential orthologues in fly and nematode and that these proteins share two novel protein domains. The W180 domain is characterized by five conserved tryptophans whereas the H domains share 21 invariant residues. In contrast to the arrangement in fly and nematode the cassette containing the W180 and H domains is repeated twice in leech Hillarin. This suggests that the leech Hillarin sequence originated from a duplication event of an ancestral protein with single cassette structure.     

Robust hit identification by quality assurance and multivariate data analysis of a high-content, cell-based assay

Recent technological advances in high-content screening instrumentation have increased its ease of use and throughput, expanding the application of high-content screening to the early stages of drug discovery. However, high-content screens produce complex data sets, presenting a challenge for both extraction and interpretation of meaningful information. This shifts the high-content screening process bottleneck from the experimental to the analytical stage. In this article, the authors discuss different approaches of data analysis, using a phenotypic neurite outgrowth screen as an example. Distance measurements and hierarchical clustering methods lead to a profound understanding of different high-content screening readouts. In addition, the authors introduce a hit selection procedure based on machine learning methods and demonstrate that this method increases the hit verification rate significantly (up to a factor of 5), compared to conventional hit selection based on single readouts only.     

Non-canonical peroxisome targeting signals: identification of novel PTS1 tripeptides and characterization of enhancer elements by computational permutation analysis

ABSTRACT: BACKGROUND: High-accuracy prediction tools are essential in the post-genomic era to define organellar proteomes in their full complexity. We recently applied a discriminative machine learning approach to predict plant proteins carrying peroxisome targeting signals (PTS) type 1 from genome sequences. For Arabidopsis thaliana 392 gene models were predicted to be peroxisome-targeted. The predictions were extensively tested in vivo, resulting in a high experimental verification rate of Arabidopsis proteins previously not known to be peroxisomal. RESULTS: In this study, we experimentally validated the predictions in greater depth by focusing on the most challenging Arabidopsis proteins with unknown non-canonical PTS1 tripeptides and prediction scores close to the threshold. By in vivo subcellular targeting analysis, three novel PTS1 tripeptides (QRL>, SQM>, and SDL>) and two novel tripeptide residues (Q at position -3 and D at pos. -2) were identified. To understand why, among many Arabidopsis proteins carrying the same C-terminal tripeptides, these proteins were specifically predicted as peroxisomal, the residues upstream of the PTS1 tripeptide were computationally permuted and the changes in prediction scores were analyzed. The newly identified Arabidopsis proteins were found to contain four to five amino acid residues of high predicted targeting enhancing properties at position -4 to -12 in front of the non-canonical PTS1 tripeptide. The identity of the predicted targeting enhancing residues was unexpectedly diverse, comprising besides basic residues also proline, hydroxylated (Ser, Thr), hydrophobic (Ala, Val), and even acidic residues. CONCLUSIONS: Our computational and experimental analyses demonstrate that the plant PTS1 tripeptide motif is more diverse than previously thought, including an increasing number of non-canonical sequences and allowed residues. Specific targeting enhancing elements can be predicted for particular sequences of interest and are far more diverse in amino acid composition and positioning than previously assumed. Machine learning methods become indispensable to predict which specific proteins, among numerous candidate proteins carrying the same non-canonical PTS1 tripeptide, contain sufficient enhancer elements in terms of number, positioning and total strength to cause peroxisome targeting.     

Amplified fragment length polymorphisms and sequence data in the phylogenetic analysis of polyploids: multiple origins of Veronica cymbalaria (Plantaginaceae)

The origin of polyploid Veronica cymbalaria (Plantaginaceae) was investigated using DNA sequence data and amplified fragment length polymorphism (AFLP) fingerprints to reveal the parentage of this taxon. The use of AFLP fingerprints in phylogenetic analysis is problematic and various methods have therefore been compared. DNA sequence data (for the internal transcribed spacer (ITS) region and the plastid trnL-F region (trnL intron, 3'exon, and trnL-F spacer)) and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis of the ITS region suggested a reliable hypothesis for the evolution of the V. cymbalaria complex. This hypothesis allowed evaluation of the effect of different distance measures (Jaccard and Nei-Li) in phenetic, character-state weighted parsimony, and Bayesian analyses of AFLP markers. The study establishes that tetraploid V. cymbalaria originated at least twice in the eastern Mediterranean, with one parent differing in the two separate origins. Hexaploid V. cymbalaria originated even more often. The results illustrate that even subtle differences in the analyses of AFLP markers can lead to drastically different conclusions. The study reveals multiple origins of a Mediterranean polyploid species. Furthermore, it demonstrates that the analysis of a complex marker system such as AFLP fingerprints using only one type of analysis can easily be misleading.     

GENEVIEW and the DNACE data bus: computational tools for analysis, display and exchange of genetic information.

We describe an interactive computational tool, GENEVIEW, that allows the scientist to retrieve, analyze, display and exchange genetic information. The scientist may request a display of information from a GenBank locus, request that a restriction map be computed, stored and superimposed on GenBank information, and interactively view this information. GENEVIEW provides an interface between the GenBank data base and the programs of the Lilly DNA Computing Environment (DNACE). This interface stores genetic information in a simple, free format that has become the universal convention of DNACE; this format will serve as the convention for all future software development at Eli Lilly and Company, and could serve as a convention for genetic information exchange.     

Lividins: novel antimicrobial peptide homologs from the skin secretion of the Chinese Large Odorous frog, Rana (Odorrana) livida. Identification by "shotgun" cDNA cloning and sequence analysis

Odorous frogs of the sub-genus Odorrana are of oriental distribution, and are so called due to the foul smell of their defensive skin secretions released from specialized skin glands following stress or predator attack. Here we report the application of a "shotgun" skin secretion cDNA library cloning technique which can rapidly expedite identification of secretion bioactive peptides. From a library constructed from the skin secretion of the Large Chinese Odorous frog, Rana (Odorrana) livida, we have identified four novel peptides whose primary structures were deduced initially from cloned precursors. Subsequently, mature peptides were located in and structurally characterized from reverse phase HPLC fractions of skin secretion. Named lividins 1-4, these were found to be structural homologs of known antimicrobial peptide families from Rana frogs. Rapid identification of novel peptides can thus be rapidly achieved using this non-invasive, non-destructive technology and the extensive similarities revealed between antimicrobial peptide precursor organization and nucleic acid sequences would lend support to the hypothesis that they have a common ancestral origin.     

FlgM anti-sigma factors: identification of novel members of the family, evolutionary analysis, homology modeling, and analysis of sequence-structure-function relationships

FlgM proteins, also known as Anti-sigma-28 factor (sigma28), are negative regulators of flagellin synthesis. Recently, a three-dimensional structure of the Aquifex aeolicus sigma28/FlgM complex (PDB code: 1rp3) was determined by X-ray crystallography at 2.3 A resolution. Furthermore, experimental data on bacterial FlgM, including site-directed mutagenesis and structural characterization by NMR are also available. However, an interpretation of the sequence-structure-function relationships combining X-ray and NMR data with the evolutionary information extracted from the increasing number of FlgM-related sequences annotated in databases is not available. In the present study, we combined database sequence searches and sequence-analysis tools to update the multiple sequence alignment of a previously characterized cluster of orthologs (COG2747) and the PFAM classification of protein domains (PF04316) for the FlgM family. A phylogenetic analysis of 77 protein sequences revealed the presence of at least three major sequence clades within the FlgM family. Besides, we predicted functional residues using a SequenceSpace method. We also generated homology models for Bacillus subtilis and Salmonella typhimurium FlgM proteins, for which sequence-structure-function relationship data are available, and used the docking program ClusPro to hypothesize about the dimer association between FlgM proteins. In conclusion, the analysis presented in this work will be useful in designing new experiments to understand better protein-protein interactions between FglM, sigma factors, and putative molecules from the flagellar export apparatus. Electronic Supplementary Material is available in the online version of this article at http://link.springer.de/