Candidate Biomarker Discovery for Angiogenesis by Automatic Integration of Orbitrap MS1 Spectral-and X!Tandem MS2 Sequencing Information

Candidate protein biomarker discovery by full automatic integration of Orbitrap full MS1 spectral peptide profiling and X!Tandem MS2 peptide sequencing is investigated by analyzing mass spectra from brain tumor samples using Peptrix. Potential protein candidate biomarkers found for angiogenesis are compared with those previously reported in the literature and obtained from previous Fourier transform ion cyclotron resonance (FT-ICR) peptide profiling. Lower mass accuracy of peptide masses measured by Orbitrap compared to those measured by FT-ICR is compensated by the larger number of detected masses separated by liquid chromatography (LC), which can be directly linked to protein identifications. The number of peptide sequences divided by the number of unique sequences is 9248/6911 ≈ 1.3. Peptide sequences appear 1.3 times redundant per up-regulated protein on average in the peptide profile matrix, and do not seem always up-regulated due to tailing in LC retention time (40%), modifications (40%) and mass determination errors (20%). Significantly up-regulated proteins found by integration of X!Tandem are described in the literature as tumor markers and some are linked to angiogenesis. New potential biomarkers are found, but need to be validated independently. Eventually more proteins could be found by actively involving MS2 sequence information in the creation of the MS1 peptide profile matrix.     

Predicting protein linkages in bacteria: Which method is best depends on task

Background

A Java? application is presented, which compares large numbers (n > 100) of raw FTICR mass spectra from patients and controls. Two peptide profile matrices can be produced simultaneously, one with occurrences of peptide masses in samples and another with the intensity of common peak masses in all the measured samples, using the peak- and background intensities of the raw data. In latter way, more significantly differentially expressed peptides are found between groups than just using the presence or absence in samples of common peak masses. The software application is tested by searching angiogenesis related proteins in glioma by comparing laser capture micro dissected- and enzymatic by trypsin digested tissue sections.

Results

By hierarchical clustering of the presence-absence matrix, it appears that proteins, such as hemoglobin alpha and delta subunit, fibrinogen beta and gamma chain precursor, tubulin specific chaperone A, epidermal fatty acid binding protein, neutrophil gelatinase-associated lipocalin precursor, peptidyl tRNA hydrolase 2 mitochondrial precursor, placenta specific growth hormone, and zinc finger CCHC domain containing protein 13 are significantly different expressed in glioma vessels. The up-regulated proteins in the glioma vessels with respect to the normal vessels determined by the Wilcoxon-Mann-Whitney test on the intensity matrix are vimentin, glial fibrillary acidic protein, serum albumin precursor, annexin A5, alpha cardiac and beta actin, type I cytoskeletal 10 keratin, calcium binding protein p22, and desmin. Peptide masses of calcium binding protein p22, Cdc42 effector protein 3, fibronectin precursor, and myosin-9 are exclusively present in glioma vessels. Some peptide fragments of non-muscular myosin-9 at the C-terminus are strongly up-regulated in the glioma vessels with respect to the normal vessels.

Conclusion

The less rigorous than in general used commercial propriety software de-isotope algorithm results in more mono-isotopic peptide masses and consequently more proteins. Centroiding of peptide masses takes place by taking the average over more spectra in the profile matrix. Cytoskeleton proteins and proteins involved in the calcium signaling pathway seem to be most up-regulated in glioma vessels. The finding that peptides at the C-terminus of myosin-9 are up-regulated could be ascribed to splicing or fragmentation by proteases.     

A well‐characterised peak identification list of MALDI MS profile peaks for human blood serum

MALDI MS profiling, using easily available body fluids such as blood serum, has attracted considerable interest for its potential in clinical applications. Despite the numerous reports on MALDI MS profiling of human serum, there is only scarce information on the identity of the species making up these profiles, particularly in the mass range of larger peptides. Here, we provide a list of more than 90 entries of MALDI MS profile peak identities up to 10 kDa obtained from human blood serum. Various modifications such as phosphorylation were detected among the peptide identifications. The overlap with the few other MALDI MS peak lists published so far was found to be limited and hence our list significantly extends the number of identified peaks commonly found in MALDI MS profiling of human blood serum.     

Characterization of a high field Orbitrap mass spectrometer for proteome analysis

The field of proteomics continues to be driven by improvements in analytical technology, notably in peptide separation, quantitative MS, and informatics. In this study, we have characterized a hybrid linear ion trap high field Orbitrap mass spectrometer (Orbitrap Elite) for proteomic applications. The very high resolution available on this instrument allows 95% of all peptide masses to be measured with sub‐ppm accuracy that in turn improves protein identification by database searching. We further confirm again that mass accuracy in tandem mass spectra is a valuable parameter for improving the success of protein identification. The new CID rapid scan type of the Orbitrap Elite achieves similar performance as higher energy collision induced dissociation fragmentation and both allow the identification of hundreds of proteins from as little as 0.1 ng of protein digest on column. The new instrument outperforms its predecessor the Orbitrap Velos by a considerable margin on each metric assessed that makes it a valuable and versatile tool for MS‐based proteomics.     

Corynebacterium ulcerans 0102 carries the gene encoding diphtheria toxin on a prophage different from the C. diphtheriae NCTC 13129 prophage

Background

Two important plant pathogenic bacteria Acidovorax oryzae and Acidovorax citrulli are closely related and often not easy to be differentiated from each other, which often resulted in a false identification between them based on traditional methods such as carbon source utilization profile, fatty acid methyl esters, and ELISA detection tests. MALDI-TOF MS and Fourier transform infrared (FTIR) spectra have recently been successfully applied in bacterial identification and classification, which provide an alternate method for differentiating the two species.

Results

Characterization and comparison of the 10 A. oryzae strains and 10 A. citrulli strains were performed based on traditional bacteriological methods, MALDI-TOF MS, and FTIR spectroscopy. Our results showed that the identity of the two closely related plant pathogenic bacteria A. oryzae and A. citrulli was able to be confirmed by both pathogenicity tests and species-specific PCR, but the two species were difficult to be differentiated based on Biolog and FAME profile as well as 16?S rRNA sequence analysis. However, there were significant differences in MALDI-TOF MS and FTIR spectra between the two species of Acidovorax. MALDI-TOF MS revealed that 22 and 18 peaks were specific to A. oryzae and A. citrulli, respectively, while FTIR spectra of the two species of Acidovorax have the specific peaks at 1738, 1311, 1128, 1078, 989?cm^-1 and at 1337, 968, 933, 916, 786?cm^-1, respectively.

Conclusions

This study indicated that MALDI-TOF MS and FTIR spectra may give a new strategy for rapid bacterial identification and differentiation of the two closely related species of Acidovorax.     

SELDI-TOF MS Proteomics in Breast Cancer

Background

Proteomic profiling is a rapidly developing technology that may enable early disease screening and diagnosis. Surface-enhanced laser desorption ionization–time of flight mass spectrometry (SELDI-TOF MS) has demonstrated promising results in screening and early detection of many diseases. In particular, it has emerged as a high-throughput tool for detection and differentiation of several cancer types. This review aims to appraise published data on the impact of SELDI-TOF MS in breast cancer.

Methods

A systematic literature search between 1965 and 2009 was conducted using the PubMed, EMBASE, and Cochrane Library databases. Studies covering different aspects of breast cancer proteomic profiling using SELDI-TOF MS technology were critically reviewed by researchers and specialists in the field.

Results

Fourteen key studies involving breast cancer biomarker discovery using SELDI-TOF MS proteomic profiling were identified. The studies differed in their inclusion and exclusion criteria, biologic samples, preparation protocols, arrays used, and analytical settings. Taken together, the numerous studies suggest that SELDI-TOF MS methodology may be used as a fast and robust approach to study the breast cancer proteome and enable the analysis of the correlations between proteomic expression patterns and breast cancer.

Conclusion

SELDI-TOF MS is a promising high-throughput technology with potential applications in breast cancer screening, detection, and prognostication. Further studies are needed to resolve current limitations and facilitate clinical utility.     

In-depth analysis of the chicken egg white proteome using an LTQ Orbitrap Velos

Background

Hen's egg white has been the subject of intensive chemical, biochemical and food technological research for many decades, because of its importance in human nutrition, its importance as a source of easily accessible model proteins, and its potential use in biotechnological processes. Recently the arsenal of tools used to study the protein components of egg white has been complemented by mass spectrometry-based proteomic technologies. Application of these fast and sensitive methods has already enabled the identification of a large number of new egg white proteins. Recent technological advances may be expected to further expand the egg white protein inventory.

Results

Using a dual pressure linear ion trap Orbitrap instrument, the LTQ Orbitrap Velos, in conjunction with data analysis in the MaxQuant software package, we identified 158 proteins in chicken egg white with two or more sequence unique peptides. This group of proteins identified with very high confidence included 79 proteins identified in egg white for the first time. In addition, 44 proteins were identified tentatively.

Conclusions

Our results, apart from identifying many new egg white components, indicate that current mass spectrometry technology is sufficiently advanced to permit direct identification of minor components of proteomes dominated by a few major proteins without resorting to indirect techniques, such as chromatographic depletion or peptide library binding, which change the composition of the proteome.     

Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data

Background

Genomic deletions and duplications are important in the pathogenesis of diseases, such as cancer and mental retardation, and have recently been shown to occur frequently in unaffected individuals as polymorphisms. Affymetrix GeneChip whole genome sampling analysis (WGSA) combined with 100 K single nucleotide polymorphism (SNP) genotyping arrays is one of several microarray-based approaches that are now being used to detect such structural genomic changes. The popularity of this technology and its associated open source data format have resulted in the development of an increasing number of software packages for the analysis of copy number changes using these SNP arrays.

Results

We evaluated four publicly available software packages for high throughput copy number analysis using synthetic and empirical 100 K SNP array data sets, the latter obtained from 107 mental retardation (MR) patients and their unaffected parents and siblings. We evaluated the software with regards to overall suitability for high-throughput 100 K SNP array data analysis, as well as effectiveness of normalization, scaling with various reference sets and feature extraction, as well as true and false positive rates of genomic copy number variant (CNV) detection.

Conclusion

We observed considerable variation among the numbers and types of candidate CNVs detected by different analysis approaches, and found that multiple programs were needed to find all real aberrations in our test set. The frequency of false positive deletions was substantial, but could be greatly reduced by using the SNP genotype information to confirm loss of heterozygosity.     

Method optimisation for peptide profiling of microdissected breast carcinoma tissue by matrix-assisted laser desorption/ionisation-time of flight and matrix-assisted laser desorption/ionisation-time of flight/time of flight-mass spectrometry

Appropriate methods for the analysis of microdissected solid tumour tissues by matrix-assisted laser desorption/ionisation-time of flight-mass spectrometry (MALDI-TOF MS) are not yet well established. Optimisation of sample preparation was performed first on undissected tissue slices, representing approximately 200 000 cells, which were solubilised either in urea containing buffer, trifluoroethanol/NH4HCO3, 0.1% sodium dodecyl sulphate (SDS) or in 0.1% RapiGest solution, then trypsin digested and analysed by MALDI-TOF MS. Solubilisation in 0.1% SDS resulted in detection of the highest number of sample specific peak signals. Interestingly, there was little overlap in detectable peaks using the different buffers, implying that they can be used complementarily to each other. Additionally, we fractionated tryptic digests on a monolithic high-performance liquid chromatography column. Fractionation of tryptic digest from whole tissue sections resulted in a four-fold increase in the total number of peaks detected. To prove this principle, we used 0.1% SDS to generate peptide patterns from 2000 microdissected tumour and stromal cells from five different breast carcinoma tumours. The tumour and stroma specific peaks could be detected upon comparison of the peptide profiles. Identification of differentially expressed peaks by MALDI-TOF/TOF MS was performed on fractionated tryptic digests derived from a whole tissue slice. In conclusion, we describe a method that is suitable for direct peptide profiling on small amounts of microdissected cells obtained from breast cancer tissues.     

A high confidence, manually validated human blood plasma protein reference set

Background

The immense diagnostic potential of human plasma has prompted great interest and effort in cataloging its contents, exemplified by the Human Proteome Organization (HUPO) Plasma Proteome Project (PPP) pilot project. Due to challenges in obtaining a reliable blood plasma protein list, HUPO later re-analysed their own original dataset with a more stringent statistical treatment that resulted in a much reduced list of high confidence (at least 95%) proteins compared with their original findings. In order to facilitate the discovery of novel biomarkers in the future and to realize the full diagnostic potential of blood plasma, we feel that there is still a need for an ultra-high confidence reference list (at least 99% confidence) of blood plasma proteins.

Methods

To address the complexity and dynamic protein concentration range of the plasma proteome, we employed a linear ion-trap-Fourier transform (LTQ-FT) and a linear ion trap-Orbitrap (LTQ-Orbitrap) for mass spectrometry (MS) analysis. Both instruments allow the measurement of peptide masses in the low ppm range. Furthermore, we employed a statistical score that allows database peptide identification searching using the products of two consecutive stages of tandem mass spectrometry (MS3). The combination of MS3 with very high mass accuracy in the parent peptide allows peptide identification with orders of magnitude more confidence than that typically achieved.

Results

Herein we established a high confidence set of 697 blood plasma proteins and achieved a high 'average sequence coverage' of more than 14 peptides per protein and a median of 6 peptides per protein. All proteins annotated as belonging to the immunoglobulin family as well as all hypothetical proteins whose peptides completely matched immunoglobulin sequences were excluded from this protein list. We also compared the results of using two high-end MS instruments as well as the use of various peptide and protein separation approaches. Furthermore, we characterized the plasma proteins using cellular localization information, as well as comparing our list of proteins to data from other sources, including the HUPO PPP dataset.

Conclusion

Superior instrumentation combined with rigorous validation criteria gave rise to a set of 697 plasma proteins in which we have very high confidence, demonstrated by an exceptionally low false peptide identification rate of 0.29%.     

Mass Spectrometric Amino Acid Sequencing of Short and Mid-Sized Peptides in a ESI-O-TOF System as an Alternative to MS/MS: I. Selective Fragmentation of Peptides with <Emphasis Type="Italic">y</Emphasis>-Ion Formation

The possibility of mass spectrometric sequencing of peptides without the need for the conventional MS/MS analysis has been demonstrated experimentally. The peptide hydrolysate was fractionated by reversephase chromatography on a microbore column. The eluate fraction was injected into the mass spectrometer via an electrospray ion source that directly coupled a liquid chromatography instrument to a time-of-flight mass spectrometer (HPLC-MS). Fragmentation of the peptides eluted from the column was performed in the mass spectrometer interface by varying the voltage difference between the mass spectrometer nozzle and skimmer. A restricted set of intensive peaks of y-ions, which corresponded to sequential cleavage of all amino acids from the peptide, was obtained. The ratios of the y-ion peak intensities to the background were (5?100)/1. The presence of Lys and Arg in the peptides provided for a substantial increase of informative peak intensity in the mass spectra. The mass spectra of short peptides (up to 10 residues) were processed manually, whereas the Proteos hardware and software system was used to process the fragmentation results for a long N-terminal peptide of the human hemoglobin α-chain.     

Reduced IgG anti-small nuclear ribonucleoprotein autoantibody production in systemic lupus erythematosus patients with positive IgM anti-cytomegalovirus antibodies

Introduction

In rheumatoid arthritis (RA), synovial fluid (SF) contains a large number of neutrophils that contribute to the inflammation and destruction of the joints. The SF also contains granulocyte-macrophage colony-stimulating factor (GM-CSF), which sustains viability of neutrophils and activates their functions. Using proteomic surveillance, we here tried to elucidate the effects of GM-CSF on neutrophils.

Methods

Neutrophils stimulated by GM-CSF were divided into four subcellular fractions: cytosol, membrane/organelle, nuclei, and cytoskeleton. Then, proteins were extracted from each fraction and digested by trypsin. The produced peptides were detected using matrix-assisted laser desorption ionisation-time-of-flight mass spectrometry (MALDI-TOF MS).

Results

We detected 33 peptide peaks whose expression was upregulated by more than 2.5-fold in GM-CSF stimulated neutrophils and identified 11 proteins out of the 33 peptides using MALDI-TOF/TOF MS analysis and protein database searches. One of the identified proteins was neutrophil gelatinase-associated lipocalin (NGAL). We confirmed that the level of NGAL in SF was significantly higher in patients with RA than in those with osteoarthritis. We next addressed possible roles of the increased NGAL in RA. We analysed proteome alteration of synoviocytes from patients with RA by treatment with NGAL in vitro. We found that, out of the detected protein spots (approximately 3,600 protein spots), the intensity of 21 protein spots increased by more than 1.5-fold and the intensity of 10 protein spots decreased by less than 1 to 1.5-fold as a result of the NGAL treatment. Among the 21 increased protein spots, we identified 9 proteins including transitional endoplasmic reticulum ATPase (TERA), cathepsin D, and transglutaminase 2 (TG2), which increased to 4.8-fold, 1.5-fold and 1.6-fold, respectively. Two-dimensional electrophoresis followed by western blot analysis confirmed the upregulation of TERA by the NGAL treatment and, moreover, the western blot analysis showed that the NGAL treatment changed the protein spots caused by post-translational modification of TERA. Furthermore, NGAL cancelled out the proliferative effects of fibroblast growth factor (FGF)-2 and epidermal growth factor (EGF) on chondrocytes from a patient with RA and proliferative effect of FGF-2 on chondrosarcoma cells.

Conclusions

Our results indicate that GM-CSF contributes to the pathogenesis of RA through upregulation of NGAL in neutrophils, followed by induction of TERA, cathepsin D and TG2 in synoviocytes. NGAL and the upregulated enzymes may therefore play an important role in RA.     

The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments

Background  

Isotope-coded affinity tags (ICAT) is a method for quantitative proteomics based on differential isotopic labeling, sample digestion and mass spectrometry (MS). The method allows the identification and relative quantification of proteins present in two samples and consists of the following phases. First, cysteine residues are either labeled using the ICAT Light or ICAT Heavy reagent (having identical chemical properties but different masses). Then, after whole sample digestion, the labeled peptides are captured selectively using the biotin tag contained in both ICAT reagents. Finally, the simplified peptide mixture is analyzed by nanoscale liquid chromatography-tandem mass spectrometry (LC-MS/MS). Nevertheless, the ICAT LC-MS/MS method still suffers from insufficient sample-to-sample reproducibility on peptide identification. In particular, the number and the type of peptides identified in different experiments can vary considerably and, thus, the statistical (comparative) analysis of sample sets is very challenging. Low information overlap at the peptide and, consequently, at the protein level, is very detrimental in situations where the number of samples to be analyzed is high.     

KniMet: a pipeline for the processing of chromatography–mass spectrometry metabolomics data

Introduction

Data processing is one of the biggest problems in metabolomics, given the high number of samples analyzed and the need of multiple software packages for each step of the processing workflow.

Objectives

Merge in the same platform the steps required for metabolomics data processing.

Methods

KniMet is a workflow for the processing of mass spectrometry-metabolomics data based on the KNIME Analytics platform.

Results

The approach includes key steps to follow in metabolomics data processing: feature filtering, missing value imputation, normalization, batch correction and annotation.

Conclusion

KniMet provides the user with a local, modular and customizable workflow for the processing of both GC–MS and LC–MS open profiling data.

     

Reproducibility of mass spectrometry based protein profiles for diagnosis of breast cancer across clinical studies: a systematic review

Serum protein profiling by mass spectrometry has achieved attention as a promising technology in oncoproteomics. We performed a systematic review of published reports on protein profiling as a diagnostic tool for breast cancer. The MEDLINE, EMBASE, and COCHRANE databases were searched for original studies reporting discriminatory protein peaks for breast cancer as either protein identity or as m/ z values in the period from January 1995 to October 2006. To address the important aspect of reproducibility of mass spectrometry data across different clinical studies, we compared the published lists of potential discriminatory peaks with those peaks detected in an original MALDI MS protein profiling study performed by our own research group. A total of 20 protein/peptide profiling studies were eligible for inclusion in the systematic review. Only 3 reports included information on protein identity. Although the studies revealed a considerable heterogeneity in relation to experimental design, biological variation, preanalytical conditions, methods of computational data analysis, and analytical reproducibility of profiles, we found that 45% of peaks previously reported to correlate with breast cancer were also detected in our experimental study. Furthermore, 25% of these redetected peaks also showed a significant difference between cases and controls in our study. Thus, despite known problems related to reproducibility, we were able to demonstrate overlap in peaks between clinical studies indicating some convergence toward a set of common discriminating, reproducible peaks for breast cancer. These peaks should be further characterized for identification of the protein identity and validated as biomarkers for breast cancer.     

Real-Time Search-Assisted Acquisition on a Tribrid Mass Spectrometer Improves Coverage in Multiplexed Single-Cell Proteomics

In the young field of single-cell proteomics (scMS), there is a great need for improved global proteome characterization, both in terms of proteins quantified per cell and quantitative performance thereof. The recently introduced real-time search (RTS) on the Orbitrap Eclipse Tribrid mass spectrometer in combination with SPS-MS3 acquisition has been shown to be beneficial for the measurement of samples that are multiplexed using isobaric tags. Multiplexed scMS requires high ion injection times and high-resolution spectra to quantify the single-cell signal; however, the carrier channel facilitates peptide identification and thus offers the opportunity for fast on-the-fly precursor filtering before committing to the time-intensive quantification scan. Here, we compared classical MS2 acquisition against RTS-SPS-MS3, both using the Orbitrap Eclipse Tribrid MS with the FAIMS Pro ion mobility interface and present a new acquisition strategy termed RETICLE (RTS enhanced quant of single cell spectra) that makes use of fast real-time searched linear ion trap scans to preselect MS1 peptide precursors for quantitative MS2 Orbitrap acquisition. We show that classical MS2 acquisition is outperformed by both RTS-SPS-MS3 through increased quantitative accuracy at similar proteome coverage, and RETICLE through higher proteome coverage, with the latter enabling the quantification of over 1000 proteins per cell at an MS2 injection time of 750 ms using a 2 h gradient.     

A simple peak detection and label-free quantitation algorithm for chromatography-mass spectrometry

Background

Label-free quantitation of mass spectrometric data is one of the simplest and least expensive methods for differential expression profiling of proteins and metabolites. The need for high accuracy and performance computational label-free quantitation methods is still high in the biomarker and drug discovery research field. However, recent most advanced types of LC-MS generate huge amounts of analytical data with high scan speed, high accuracy and resolution, which is often impossible to interpret manually. Moreover, there are still issues to be improved for recent label-free methods, such as how to reduce false positive/negatives of the candidate peaks, how to expand scalability and how to enhance and automate data processing. AB3D (A simple label-free quantitation algorithm for Biomarker Discovery in Diagnostics and Drug discovery using LC-MS) has addressed these issues and has the capability to perform label-free quantitation using MS1 for proteomics study.

Results

We developed an algorithm called AB3D, a label free peak detection and quantitative algorithm using MS1 spectral data. To test our algorithm, practical applications of AB3D for LC-MS data sets were evaluated using 3 datasets. Comparisons were then carried out between widely used software tools such as MZmine 2, MSight, SuperHirn, OpenMS and our algorithm AB3D, using the same LC-MS datasets. All quantitative results were confirmed manually, and we found that AB3D could properly identify and quantify known peptides with fewer false positives and false negatives compared to four other existing software tools using either the standard peptide mixture or the real complex biological samples of Bartonella quintana (strain JK31). Moreover, AB3D showed the best reliability by comparing the variability between two technical replicates using a complex peptide mixture of HeLa and BSA samples. For performance, the AB3D algorithm is about 1.2 - 15 times faster than the four other existing software tools.

Conclusions

AB3D is a simple and fast algorithm for label-free quantitation using MS1 mass spectrometry data for large scale LC-MS data analysis with higher true positive and reasonable false positive rates. Furthermore, AB3D demonstrated the best reproducibility and is about 1.2- 15 times faster than those of existing 4 software tools.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0376-0) contains supplementary material, which is available to authorized users.     

MS2‐Deisotoper: A Tool for Deisotoping High‐Resolution MS/MS Spectra in Normal and Heavy Isotope‐Labelled Samples

High‐resolution MS/MS spectra of peptides can be deisotoped to identify monoisotopic masses of peptide fragments. The use of such masses should improve protein identification rates. However, deisotoping is not universally used and its benefits have not been fully explored. Here, MS2‐Deisotoper, a tool for use prior to database search, is used to identify monoisotopic peaks in centroided MS/MS spectra. MS2‐Deisotoper works by comparing the mass and relative intensity of each peptide fragment peak to every other peak of greater mass, and by applying a set of rules concerning mass and intensity differences. After comprehensive parameter optimization, it is shown that MS2‐Deisotoper can improve the number of peptide spectrum matches (PSMs) identified by up to 8.2% and proteins by up to 2.8%. It is effective with SILAC and non‐SILAC MS/MS data. The identification of unique peptide sequences is also improved, increasing the number of human proteoforms by 3.7%. Detailed investigation of results shows that deisotoping increases Mascot ion scores, improves FDR estimation for PSMs, and leads to greater protein sequence coverage. At a peptide level, it is found that the efficacy of deisotoping is affected by peptide mass and charge. MS2‐Deisotoper can be used via a user interface or as a command‐line tool.