Optimizing the Parameters Governing the Fragmentation of Cross-Linked Peptides in a Tribrid Mass Spectrometer

Kolbowski, Lars; Mendes, Marta; Rappsilber, Juri

doi:10.1021/acs.analchem.6b04935

Cited by 60 publications

(92 citation statements)

References 24 publications

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“…Crosslinking mass spectrometry (CLMS) has become a standard tool for the topological analysis of multi‐protein complexes and has begun delivering high‐density information on protein structures, insights into structural changes and the wiring of interaction networks in situ (O'Reilly & Rappsilber, ). The technological development currently focuses on enrichment strategies for crosslinked peptides and mass spectrometric data acquisition (Leitner et al , ; Kolbowski et al , ; Liu et al , ), including newly designed crosslinkers (Kao et al , ). MS2‐cleavable crosslinkers, in particular, have celebrated recent successes for the analysis of protein complexes (Wang et al , ) or complex mixtures (Chavez et al , ; Liu & Heck, ).…”

Section: Introductionmentioning

confidence: 99%

An integrated workflow for crosslinking mass spectrometry

Mendes

Fischer

Chen

et al. 2019

Molecular Systems Biology

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We present a concise workflow to enhance the mass spectrometric detection of crosslinked peptides by introducing sequential digestion and the crosslink identification software xiSEARCH. Sequential digestion enhances peptide detection by selective shortening of long tryptic peptides. We demonstrate our simple 12‐fraction protocol for crosslinked multi‐protein complexes and cell lysates, quantitative analysis, and high‐density crosslinking, without requiring specific crosslinker features. This overall approach reveals dynamic protein–protein interaction sites, which are accessible, have fundamental functional relevance and are therefore ideally suited for the development of small molecule inhibitors.

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Section: Introductionmentioning

confidence: 99%

An integrated workflow for crosslinking mass spectrometry

Mendes

Fischer

Chen

et al. 2019

Molecular Systems Biology

Self Cite

135

142

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“…The three datasets were chosen to reflect a range of applications of cross-linking mass spectrometry and a range of data complexity: the first dataset is Human Serum Albumin (HSA) cross-linked with succinimidyl 4,4-azipentanoate (SDA) and fragmented using five different methods (PXD003737) 24 . The second dataset is a pooled pseudo-complex sample with seven separately cross-linked proteins with bis(sulfosuccinimidyl) suberate (BS3) (PXD006131) 6 . This dataset includes data from four different fragmentation methods.…”

Section: Methodsmentioning

confidence: 99%

“…enriching for crosslinked peptides [1][2][3] , using different proteases 1,4 or optimizing fragmentation methods 5,6 . In parallel with experimental developments, data analysis has also progressed.…”

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confidence: 99%

In-Search Assignment of Monoisotopic Peaks Improves the Identification of Cross-Linked Peptides

Lenz

Giese

Fischer

et al. 2018

Preprint

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Cross-linking/mass spectrometry (CLMS) has gone through a maturation process similar to standard proteomics by adapting key methods such as false discovery rate control and quantification. However, methods for preprocessing mass spectrometric data of cross-linked peptides are currently underexplored. Preprocessing only requires computational efforts and can significantly improve data quality and search engine results. Our analysis shows that monoisotopic peak selection is a major weakness of current data handling approaches. High precursor masses paired with low intensities, typical of cross-linked peptides, are the main causes of the frequent misassignment of their monoisotopic peaks. We address this by 'in-search selection of the monoisotopic peak' in Xi (Xi-MPS). We compare and evaluate the performance of MaxQuant-Xi, OpenMS-Xi and Xi-MPS on three publicly available datasets. Xi-MPS always delivered the highest number of identifications with ~2 to 4-fold increase of PSMs without compromising identification accuracy as determined by FDR estimation and comparison to crystallographic models.Several approaches have been utilized to increase the numbers of identified cross-links, e.g. enriching for crosslinked peptides 1-3 , using different proteases 1,4 or optimizing fragmentation methods 5,6 . In parallel with experimental developments, data analysis has also progressed. Search software has been designed for the identification of crosslinked peptides, for example Kojak 7 , xQuest 8 , pLink 9 , XlinkX 10 or Xi 11 . In addition, cross-linking workflows can make use of preprocessing methods to improve data quality and reduce file sizes, post-processing to filter out false identifications 7,12 and custom-tailored false discovery rate (FDR) estimation [13][14][15] .Preprocessing steps that improve the data quality for peptide identification can be split into those dealing with each of the two levels of acquisition: correction of the MS1 precursor ion m/z and simplifying MS2 fragment spectra. MS2 preprocessing, e.g. by deisotoping or removing less intense peaks, is search algorithm dependent due to distinct scoring methods on the fragment spectra 16 . Correction of the MS1 precursor ion can include correction of the charge state or m/z value. However, cross-linked peptides have characteristics that may make preprocessing methods used for linear peptide identification workflows nonoptimal: high-charge states, large masses, and low abundances.Several cross-link search engines include preprocessing steps in their pipeline: In pLink, spectral quality filtering and preprocessing of the MS2 spectra is implemented by removing noise peaks. The group also published a tool for correction of monoisotopic peaks 17 , and while it was not specifically designed for cross-link detection, it is implemented in their workflow 18 . The search engine Kojak averages precursor ion signals of neighboring scans to create a composite spectrum and infer the true monoisotopic mass of the precursor. Secondly, Kojak includes processing o...

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“…For further performance tests we used BSA, a protein which has emerged as a standard for testing crosslinking performance. [33][34][35] Crosslinking with 1 mM of PhoX and in-solution digesting the sample after crosslinking provided the input for our enrichment (see Fig. 1b; Supplementary Note 7).…”

Section: Synthesismentioning

confidence: 99%

PhoX – an IMAC-enrichable Crosslinking Reagent

Steigenberger

Pieters

Heck

et al. 2019

Preprint

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Chemical crosslinking mass spectrometry is rapidly emerging as a prominent technique to study protein structures. Structural information is obtained by covalently connecting peptides in close proximity by small reagents and identifying the resulting peptide pairs by mass spectrometry. However, sub-stoichiometric reaction efficiencies render routine detection of crosslinked peptides problematic. Here we present a new tri-functional crosslinking reagent, termed PhoX, which is decorated with a stable phosphonic acid handle. This makes the crosslinked peptides amenable to the well-established IMAC enrichment. The handle allows for 300x enrichment efficiency and 97% specificity, dramatically reducing measurement time and improving data quality. We exemplify the approach on various model proteins and protein complexes, e.g. resulting in a structural model of the LRP1/RAP complex. PhoX is also applicable to whole cell lysates. When focusing the database search on ribosomal proteins, our first attempt resulted in 355 crosslinks, out-performing current efforts in less measurement time.

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Optimizing the Parameters Governing the Fragmentation of Cross-Linked Peptides in a Tribrid Mass Spectrometer

Cited by 60 publications

References 24 publications

An integrated workflow for crosslinking mass spectrometry

An integrated workflow for crosslinking mass spectrometry

In-Search Assignment of Monoisotopic Peaks Improves the Identification of Cross-Linked Peptides

PhoX – an IMAC-enrichable Crosslinking Reagent

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