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At least 19 recordsLinked to original sources
PubMed2004

SPIDER: software for protein identification from sequence tags with de novo sequencing error.

For the identification of novel proteins using MS/MS, de novo sequencing software computes one or several possible amino acid sequences (called sequence tags) for each MS/MS spectrum. Those tags are then used to match, accounting amino acid mutations, the sequences in a protein database. If the de novo sequencing gives correct tags, the homologs of the proteins can be identified by this approach and software such as MS-BLAST is available for the matching. However, de novo sequencing very often gives only partially correct tags. The most common error is that a segment of amino acids is replaced by another segment with approximately the same masses. We developed a new efficient algorithm to match sequence tags with errors to database sequences for the purpose of protein and peptide identification. A software package, SPIDER, was developed and made available on Internet for free public use. This paper describes the algorithms and features of the SPIDER software.

Algorithms↗
PubMed2005

SPIDER: software for protein identification from sequence tags with de novo sequencing error.

For the identification of novel proteins using MS/MS, de novo sequencing software computes one or several possible amino acid sequences (called sequence tags) for each MS/MS spectrum. Those tags are then used to match, accounting amino acid mutations, the sequences in a protein database. If the de novo sequencing gives correct tags, the homologs of the proteins can be identified by this approach and software such as MS-BLAST is available for the matching. However, de novo sequencing very often gives only partially correct tags. The most common error is that a segment of amino acids is replaced by another segment with approximately the same masses. We developed a new efficient algorithm to match sequence tags with errors to database sequences for the purpose of protein and peptide identification. A software package, SPIDER, was developed and made available on Internet for free public use. This paper describes the algorithms and features of the SPIDER software.

Algorithms↗
PubMed2001

Automated de novo sequencing of proteins using the differential scanning technique.

Despite the progress in genomic DNA sequencing de novo sequencing of peptides is still required in a biological research environment since many experiments are done in organisms whose genomes are not sequenced. A way to unambiguously retrieve a peptide sequence from a tandem mass spectrum is to assign the correct ion type to the fragments. Here we describe a method which improves the specificity in y-ion assignment throughout the spectrum. The differential scanning technique requires that the peptides are partially 18O labelled at their C-terminus and that two fragment spectra are acquired for each peptide, one selecting the 16O/18O isotopic cluster and a second fragmenting only the 18O labelled ions. When the spectra are acquired with a quadrupole time of flight mass spectrometer y-ions can be very specifically filtered from the spectrum using a computer algorithm. Partial or complete peptide sequences can be assigned automatically simply by finding the most abundant series of fragments spaced by amino acid residue masses. This method was used extensively in a project investigating vesicular transport in bovine brain cells. Human or mouse homologues to the bovine proteins were found in EST databases facilitating rapid cloning of the human homologues.

Algorithms↗
PubMed2005

NovoHMM: a hidden Markov model for de novo peptide sequencing.

De novo sequencing of peptides poses one of the most challenging tasks in data analysis for proteome research. In this paper, a generative hidden Markov model (HMM) of mass spectra for de novo peptide sequencing which constitutes a novel view on how to solve this problem in a Bayesian framework is proposed. Further extensions of the model structure to a graphical model and a factorial HMM to substantially improve the peptide identification results are demonstrated. Inference with the graphical model for de novo peptide sequencing estimates posterior probabilities for amino acids rather than scores for single symbols in the sequence. Our model outperforms state-of-the-art methods for de novo peptide sequencing on a large test set of spectra.

Amino Acid Sequence↗
PubMed2006

Performance evaluation of existing de novo sequencing algorithms.

Two methods have been developed for protein identification from tandem mass spectra: database searching and de novo sequencing. De novo sequencing identifies peptide directly from tandem mass spectra. Among many proposed algorithms, we evaluated the performance of the five de novo sequencing algorithms, AUDENS, Lutefisk, NovoHMM, PepNovo, and PEAKS. Our evaluation methods are based on calculation of relative sequence distance (RSD), algorithm sensitivity, and spectrum quality. We found that de novo sequencing algorithms have different performance in analyzing QSTAR and LCQ mass spectrometer data, but in general, perform better in analyzing QSTAR data than LCQ data. For the QSTAR data, the performance order of the five algorithms is PEAKS > Lutefisk, PepNovo > AUDENS, NovoHMM. The performance of PEAKS, Lutefisk, and PepNovo strongly depends on the spectrum quality and increases with an increase of spectrum quality. However, AUDENS and NovoHMM are not sensitive to the spectrum quality. Compared with other four algorithms, PEAKS has the best sensitivity and also has the best performance in the entire range of spectrum quality. For the LCQ data, the performance order is NovoHMM > PepNovo, PEAKS > Lutefisk > AUDENS. NovoHMM has the best sensitivity, and its performance is the best in the entire range of spectrum quality. But the overall performance of NovoHMM is not significantly different from the performance of PEAKS and PepNovo. AUDENS does not give a good performance in analyzing either QSTAR and LCQ data.

Algorithms↗
PubMed2004

High-throughput identification of proteins and unanticipated sequence modifications using a mass-based alignment algorithm for MS/MS de novo sequencing results.

With the increasing availability of de novo sequencing algorithms for interpreting high-mass accuracy tandem mass spectrometry (MS/MS) data, there is a growing need for programs that accurately identify proteins from de novo sequencing results. De novo sequences derived from tandem mass spectra of peptides often contain ambiguous regions where the exact amino acid order cannot be determined. One problem this poses for sequence alignment algorithms is the difficulty in distinguishing discrepancies due to de novo sequencing errors from actual genomic sequence variation and posttranslational modifications. We present a novel, mass-based approach to sequence alignment, implemented as a program called OpenSea, to resolve these problems. In this approach, de novo and database sequences are interpreted as masses of residues, and the masses, rather than the amino acid codes, are compared. To provide further flexibility, the masses can be aligned in groups, which can resolve many de novo sequencing errors. The performance of OpenSea was tested with three types of data: a mixture of known proteins, a mixture of unknown proteins that commonly contain sequence variations, and a mixture of posttranslationally modified known proteins. In all three cases, we demonstrate that OpenSea can identify more peptides and proteins than commonly used database-searching programs (SEQUEST and ProteinLynx) while accurately locating sequence variation sites and unanticipated posttranslational modifications in a high-throughput environment.

Algorithms↗
PubMed2024

NovoBoard: A Comprehensive Framework for Evaluating the False Discovery Rate and Accuracy of De Novo Peptide Sequencing.

De novo peptide sequencing is one of the most fundamental research areas in mass spectrometry-based proteomics. Many methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) of de novo peptide-spectrum matches. Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide-sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species) and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide-sequencing methods on target-decoy spectra and to estimate and validate their FDRs. Our FDR estimation provides valuable information to assess the reliability of new peptides identified by de novo sequencing tools, especially when no ground-truth information is available to evaluate their accuracy. The FDR estimation can also be used to evaluate the capability of de novo peptide sequencing tools to distinguish between de novo peptide-spectrum matches and random matches. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide-sequencing methods and how their performances depend on specific applications and the types of data.

Peptides↗
PubMed1999

Evaluation of charge derivatization of a proteolytic protein digest for improved mass spectrometric analysis: de novo sequencing by matrix-assisted laser desorption/ionization post-source decay mass spectrometry.

A simple mass spectrometric method to sequence a recombinant phosphoenolpyruvate carboxykinase of known structure and a novel variant of unknown structure isolated from Anaerobiospirillum succiniciproducens and Actinobacillus succinogenes 130Z, respectively, was evaluated. The proteolytic digests of the proteins were each chemically derivatized at the N-terminus by addition of a tris(trimethoxyphenyl)phosphoniumacetyl (TMPP(+)-Ac) group to produce peptides with a fixed positive charge. The derivatized digests were then partially separated by reversed-phase high-performance liquid chromatography. The fractions collected were subjected to matrix-assisted laser desorption/ionization post-source decay (MALDI/PSD) mass spectrometric analysis. The resulting spectra are sufficiently simple to allow the sequence to be read directly without extensive interpretation. This is in contrast to spectra of underivatized peptides obtained by MALDI/PSD or conventional tandem mass spectrometry, where full sequence interpretation can be challenging. Aided with a set of very simple established rules, it was shown that the sequence of TMPP(+)-Ac derivatives can be derived strictly from predictable fragment ion series. In most cases, this is sufficient to determine extensive, unambiguous, peptide sequences de novo. The partial sequence (35%) of the unknown phosphoenolpyruvate carboxykinase from Actinobacillus succinogenes 130Z was obtained entirely by the mass spectrometric method evaluated here, which provided the basis for evaluating homology and for the design of oligonucleotide probes for cloning the corresponding gene.

Amino Acid Sequence↗
PubMed2002

De novo sequencing of peptides using MALDI/TOF-TOF.

The recently developed MALDI TOF-TOF instrument yields relatively complex but interpretable fragmentation spectra. When coupled with a straightforward sequence extension algorithm, it is possible to develop complete peptide sequences de novo from the spectra. This approach has been applied to a set of peptides derived from typtic digestion of electrophoretically separated sea urchin egg membrane proteins. When directed to proteins that have been described previously, the results were in essential agreement with those obtained by conventional data base searching approaches, with certain important exceptions. The present method detected errors in published sequences and was able to develop sequences from peptides differing in mass by one dalton (Da). These results show both the power of the present approach and the need for using de novo methods more frequently than may be otherwise appreciated.

Algorithms↗
PubMed2002

"De novo" sequencing of peptides recovered from in-gel digested proteins by nanoelectrospray tandem mass spectrometry.

Proteins separated by one-dimensional or two-dimensional gel electrophoresis can be digested in-gel with trypsin and the recovered peptides can be sequenced de novo using triple quadrupole or hybrid quadrupole time-of-flight instruments equipped with a nanoelectrospray ion source. The peptide sequences determined provide useful information for identification of proteins by homology searching for cloning of the cognate genes by PCR based approaches.

Animals↗
PubMed2004

Sequencing from compomers: using mass spectrometry for DNA de novo sequencing of 200+ nt.

One of the main endeavors in today's life science remains the efficient sequencing of long DNA molecules. Today, most de novo sequencing of DNA is still performed using the electrophoresis-based Sanger concept of 1977, in spite of certain restrictions of this method. Methods using mass spectrometry to acquire the Sanger sequencing data are limited by short sequencing lengths of 15-25 nt. We propose a new method for DNA sequencing using base-specific cleavage and mass spectrometry that appears to be a promising alternative to classical DNA sequencing approaches. A single stranded DNA or RNA molecule is cleaved by a base-specific (bio-)chemical reaction using, for example, RNAses. The cleavage reaction is modified such that not all, but only a certain percentage of bases are cleaved. The resulting mixture of fragments is then analyzed using MALDI-TOF mass spectrometry, whereby we acquire the molecular masses of fragments. For every peak in the mass spectrum, we calculate those base compositions that will potentially create a peak of the observed mass and, repeating the cleavage reaction for all four bases, finally try to uniquely reconstruct the underlying sequence from these observed spectra. This leads us to the combinatorial problem of sequencing from compomers and, finally, to the graph-theoretical problem of finding a walk in a subgraph of the de Bruijn graph. Application of this method to simulated data indicates that it might be capable of sequencing DNA molecules with 200+ nt.

Algorithms↗
PubMed2001

Differential stable isotope labeling of peptides for quantitation and de novo sequence derivation.

We have demonstrated the use of per-methyl esterification of peptides for relative quantification of proteins between two mixtures of proteins and automated de novo sequence derivation on the same dataset. Protein mixtures for comparison were digested to peptides and resultant peptides methylated using either d0- or d3-methanol. Methyl esterification of peptides converted carboxylic acids, such as are present on the side chains of aspartic and glutamic acid as well as the carboxyl terminus, to their corresponding methyl esters. The separate d0- and d3-methylated peptide mixtures were combined and the mixture subjected to microcapillary high performance liquid chromatography/tandem mass spectrometry (HPLC/MS/MS). Parent proteins of methylated peptides were identified by correlative database searching of peptide tandem mass spectra. Ratios of proteins in the two original mixtures could be calculated by normalization of the area under the curve for identical charge states of d0- to d3-methylated peptides. An algorithm was developed that derived, without intervention, peptide sequence de novo by comparison of tandem mass spectra of d0- and d3-peptide methyl esters.

Algorithms↗
PubMedDate not supplied

AUDENS: a tool for automated peptide de novo sequencing.

We present AUDENS, a new platform-independent open source tool for automated de novo sequencing of peptides from MS/MS data. We implemented a dynamic programming algorithm and combined it with a flexible preprocessing module which is designed to distinguish between signal and other peaks. By applying a user-defined set of heuristics, AUDENS screens through the spectrum and assigns high relevance values to putative signal peaks. The algorithm constructs a sequence path through the MS/MS spectrum using the peak relevances to score each suggested sequence path, i.e., the corresponding amino acid sequence. At present, we consider AUDENS a prototype that unfolds its biggest potential if used in parallel with other de novo sequencing tools. AUDENS is available open source and can be downloaded with further documentation at http://www.ti.inf.ethz.ch/pw/software/audens/ .

Algorithms↗
PubMed2004

De novo sequencing, peptide composition analysis, and composition-based sequencing: a new strategy employing accurate mass determination by fourier transform ion cyclotron resonance mass spectrometry.

A new strategy is described for the determination of amino acid sequences of unknown peptides. Different from the well-known but often inefficient de novo sequencing approach, the new method is based on a two-step process. In the first step the amino acid composition of an unknown peptide is determined on the basis of accurate mass values of the peptide precursor ion and a small number of accurate fragment ion mass values, and, as in de novo sequencing, without employing protein database information or other pre-information. In the second step the sequence of the found amino acids of the peptide is determined by scoring the agreement between expected and observed fragment ion signals of the permuted sequences. It was found that the new approach is highly efficient if accurate mass values are available and that it easily outstrips common approaches of de novo sequencing being based on lower accuracies and detailed knowledge of fragmentation behavior. Simple permutation and calculation of all possible amino acid sequences, however, is only efficient if the composition is known or if possible compositions are at least reduced to a small list. The latter requires the highest possible instrumental mass accuracy, which is currently provided only by fourier transform ion cyclotron resonance mass spectrometry. The connection between mass accuracy and peptide composition variability is described and an example of peptide compositioning and composition-based sequencing is presented.

Amino Acid Sequence↗
PubMed2004

A case study of de novo sequence analysis of N-sulfonated peptides by MALDI TOF/TOF mass spectrometry.

The simplicity and sensitivity of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry have increased its application in recent years. The most common method of "peptide mass fingerprint" analysis often does not provide robust identification. Additional sequence information, obtained by post-source decay or collision induced dissociation, provides additional constraints for database searches. However, de novo sequencing by mass spectrometry is not yet common practice, most likely because of the difficulties associated with the interpretation of high and low energy CID spectra. Success with this type of sequencing requires full sequence coverage and demands better quality spectra than those typically used for data base searching. In this report we show that full-length de novo sequencing is possible using MALDI TOF/TOF analysis. The interpretation of MS/MS data is facilitated by N-terminal sulfonation after protection of lysine side chains (Keough et al., Proc. Natl. Acad. Sci. U.S.A. 1999, 96, 7131-7136). Reliable de novo sequence analysis has been obtained using sub-picomol quantities of peptides and peptide sequences of up to 16 amino acid residues in length have been determined. The simple, predictable fragmentation pattern allows routine de novo interpretation, either manually or using software. Characterization of the complete primary structure of a peptide is often hindered because of differences in fragmentation efficiencies and in specific fragmentation patterns for different peptides. These differences are controlled by various structural parameters including the nature of the residues present. The influence of the presence of internal Pro, acidic and basic residues on the TOF/TOF fragmentation pattern will be discussed, both for underivatized and guanidinated/sulfonated peptides.

Amino Acid Sequence↗
PubMed2000

Automated interpretation of low-energy collision-induced dissociation spectra by SeqMS, a software aid for de novo sequencing by tandem mass spectrometry.

SeqMS, a software aid for de novo sequencing by tandem mass spectrometry (MS/MS), which was initially developed for the automated interpretation of high-energy collision-induced dissociation (CID) MS/MS spectra of peptides, has been applied to the interpretation of low-energy CID and post-source decay (PSD) spectra of peptides. Based on peptide backbone fragmented ions and their related ions, which are the dominant ions observed in the latter two techniques, the types of ions and their propensities to be observed have been optimized for efficient interpretation of the spectra. In a typical example, the modified SeqMS allowed the complete sequencing of a 31-amino acid synthetic peptide, except for the isobaric amino acids (Leu or Ile, and Lys or Gln), based on only the low-energy CID-MS/MS spectrum.

Amino Acid Sequence↗
PubMed2000

Automated de novo sequencing of proteins by tandem high-resolution mass spectrometry.

A de novo sequencing program for proteins is described that uses tandem MS data from electron capture dissociation and collisionally activated dissociation of electrosprayed protein ions. Computer automation is used to convert the fragment ion mass values derived from these spectra into the most probable protein sequence, without distinguishing Leu/Ile. Minimum human input is necessary for the data reduction and interpretation. No extra chemistry is necessary to distinguish N- and C-terminal fragments in the mass spectra, as this is determined from the electron capture dissociation data. With parts-per-million mass accuracy (now available by using higher field Fourier transform MS instruments), the complete sequences of ubiquitin (8.6 kDa) and melittin (2.8 kDa) were predicted correctly by the program. The data available also provided 91% of the cytochrome c (12.4 kDa) sequence (essentially complete except for the tandem MS-resistant region K(13)-V(20) that contains the cyclic heme). Uncorrected mass values from a 6-T instrument still gave 86% of the sequence for ubiquitin, except for distinguishing Gln/Lys. Extensive sequencing of larger proteins should be possible by applying the algorithm to pieces of approximately 10-kDa size, such as products of limited proteolysis.

Amino Acid Sequence↗
PubMed2004

Automated de novo sequencing of nucleic acids by liquid chromatography-tandem mass spectrometry.

We present the first global computer-aided sequencing algorithm for the de novo determination of short nucleic acid sequences. The method compares the fragment ion spectra generated by collision-induced dissociation of multiply charged oligodeoxynucleotide-ions to the m/z values predicted employing established fragmentation pathways from a known reference sequence. The closeness of matching between the measured spectrum and the predicted set of fragment ions is characterized by the fitness, which takes into account the difference between measured and predicted m/z values, the intensity of the fragment ions, the number of fragments assigned, and the number of nucleotide positions not covered by fragment ions in the experimental spectrum. Smaller values for the fitness indicate a closer match between the measured spectrum and predicted m/z values. In order to find the sequence most closely matching the experimental spectrum, starting from a given nucleotide composition all possible oligonucleotide sequences are assembled followed by identification of the correct sequence by the lowest fitness value. Using this concept, sequences of 5- to 12-mer oligodeoxynucleotides were successfully de novo determined. High sequence coverage with fragment ions was essential for obtaining unequivocal sequencing results. Moreover, the collision energy was shown to have an impact on the interpretability of tandem mass spectra by the de novo sequencing algorithm. Experiments revealed that the optimal collision energy should be set to a value just sufficient for complete fragmentation of the precursor ion.

Algorithms↗