41 research outputs found

    Peptide Retention in Hydrophilic Strong Anion Exchange Chromatography Is Driven by Charged and Aromatic Residues

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    Hydrophilic strong anion exchange chromatography (hSAX) is becoming a popular method for the prefractionation of proteomic samples. However, the use and further development of this approach is affected by the limited understanding of its retention mechanism and the absence of elution time prediction. Using a set of 59 297 confidentially identified peptides, we performed an explorative analysis and built a predictive deep learning model. As expected, charged residues are the major contributors to the retention time through electrostatic interactions. Aspartic acid and glutamic acid have a strong retaining effect and lysine and arginine have a strong repulsion effect. In addition, we also find the involvement of aromatic amino acids. This suggests a substantial contribution of cation−π interactions to the retention mechanism. The deep learning approach was validated using 5-fold cross-validation (CV) yielding a mean prediction accuracy of 70% during CV and 68% on a hold-out validation set. The results of this study emphasize that not only electrostatic interactions but rather diverse types of interactions must be integrated to build a reliable hSAX retention time predictor

    Retention time prediction using neural networks increases identifications in crosslinking mass spectrometry

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    Crosslinking mass spectrometry has developed into a robust technique that is increasingly used to investigate the interactomes of organelles and cells. However, the incomplete and noisy information in the mass spectra of crosslinked peptides limits the numbers of protein–protein interactions that can be confidently identified. Here, we leverage chromatographic retention time information to aid the identification of crosslinked peptides from mass spectra. Our Siamese machine learning model xiRT achieves highly accurate retention time predictions of crosslinked peptides in a multi-dimensional separation of crosslinked E. coli lysate. Importantly, supplementing the search engine score with retention time features leads to a substantial increase in protein–protein interactions without affecting confidence. This approach is not limited to cell lysates and multi-dimensional separation but also improves considerably the analysis of crosslinked multiprotein complexes with a single chromatographic dimension. Retention times are a powerful complement to mass spectrometric information to increase the sensitivity of crosslinking mass spectrometry analyses

    Leveraging parameter dependencies in high-field asymmetric waveform ion-mobility spectrometry and size exclusion chromatography for proteome-wide cross-linking mass spectrometry

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    [Image: see text] Ion-mobility spectrometry shows great promise to tackle analytically challenging research questions by adding another separation dimension to liquid chromatography–mass spectrometry. The understanding of how analyte properties influence ion mobility has increased through recent studies, but no clear rationale for the design of customized experimental settings has emerged. Here, we leverage machine learning to deepen our understanding of field asymmetric waveform ion-mobility spectrometry for the analysis of cross-linked peptides. Knowing that predominantly m/z and then the size and charge state of an analyte influence the separation, we found ideal compensation voltages correlating with the size exclusion chromatography fraction number. The effect of this relationship on the analytical depth can be substantial as exploiting it allowed us to almost double unique residue pair detections in a proteome-wide cross-linking experiment. Other applications involving liquid- and gas-phase separation may also benefit from considering such parameter dependencies

    Optimized fragmentation regime for diazirine photo-cross-linked peptides

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    Cross-linking/mass spectrometry has evolved into a robust technology that reveals structural insights into proteins and protein complexes. We leverage a new tribrid instrument with improved fragmentation capacities in a systematic comparison to identify which fragmentation method would be best for the identification of cross-linked peptides. Specifically, we explored three fragmentation methods and two combinations: collision-induced dissociation (CID), beam-type CID (HCD), electron-transfer dissociation (ETD), ETciD, and EThcD. Trypsin-digested, SDA-cross-linked human serum albumin (HSA) served as a test sample, yielding over all methods and in triplicate analysis in total 2602 matched PSMs and 1390 linked residue pairs at 5% false discovery rate, as confirmed by the crystal structure. HCD wins in number of matched peptide-spectrum-matches (958 PSMs) and identified links (446). CID is most complementary, increasing the number of identified links by 13% (58 links). HCD wins together with EThcD in cross-link site calling precision, with approximately 62% of sites having adjacent backbone cleavages that unambiguously locate the link in both peptides, without assuming any cross-linker preference for amino acids. Overall quality of spectra, as judged by sequence coverage of both peptides, is best for EThcD for the majority of peptides. Sequence coverage might be of particular importance for complex samples, for which we propose a data dependent decision tree, else HCD is the method of choice. The mass spectrometric raw data has been deposited in PRIDE (PXD003737)

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

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    Cross-linking/mass spectrometry has undergone a maturation process akin to standard proteomics by adapting key methods such as false discovery rate control and quantification. A poorly evaluated search setting in proteomics is the consideration of multiple (lighter) alternative values for the monoisotopic precursor mass to compensate for possible misassignments of the monoisotopic peak. Here, we show that monoisotopic peak assignment is a major weakness of current data handling approaches in cross-linking. Cross-linked peptides often have high precursor masses, which reduces the presence of the monoisotopic peak in the isotope envelope. Paired with generally low peak intensity, this generates a challenge that may not be completely solvable by precursor mass assignment routines. We therefore took an alternative route by ‘”in-search assignment of the monoisotopic peak” in the cross-link database search tool Xi (Xi-MPA), which considers multiple precursor masses during database search. We compare and evaluate the performance of established preprocessing workflows that partly correct the monoisotopic peak and Xi-MPA on three publicly available data sets. Xi-MPA 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

    Distinct actin–tropomyosin cofilament populations drive the functional diversification of cytoskeletal myosin motor complexes

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    The effects of N-terminal acetylation of the high molecular weight tropomyosin isoforms Tpm1.6 and Tpm2.1 and the low molecular weight isoforms Tpm1.12, Tpm3.1 and Tpm4.2 on the actin affinity and the thermal stability of actin-tropomyosin cofilaments are described. Furthermore, we show how the exchange of cytoskeletal tropomyosin isoforms and their N-terminal acetylation affects the kinetic and chemomechanical properties of cytoskeletal actin-tropomyosin-myosin complexes. Our results reveal the extent to which the different actin-tropomyosin-myosin complexes differ in their kinetic and functional properties. The maximum sliding velocity of the actin filament as well as the optimal motor density for continuous unidirectional movement, parameters that were previously considered to be unique and invariant properties of each myosin isoform, are shown to be influenced by the exchange of the tropomyosin isoform and the N-terminal acetylation of tropomyosin

    First-line treatment of malignant glioma with carmustine implants followed by concomitant radiochemotherapy: a multicenter experience

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    Randomized phase III trials have shown significant improvement of survival 1, 2, and 3 years after implantation of 1,3-bis (2-chloroethyl)-1-nitrosourea (BCNU) wafers for patients with newly diagnosed malignant glioma. But these studies and subsequent non-phase III studies have also shown risks associated with local chemotherapy within the central nervous system. The introduction of concomitant radiochemotherapy with temozolomide (TMZ) has later demonstrated a survival benefit in a phase III trial and has become the current treatment standard for newly diagnosed malignant glioma patients. Lately, this has resulted in clinical protocols combining local chemotherapy with BCNU wafers and concomitant radiochemotherapy with TMZ although this may carry the risk of increased toxicity. We have compiled the treatment experience of seven neurosurgical centers using implantation of carmustine wafers at primary surgery followed by 6 weeks of radiation therapy (59–60 Gy) and 75 mg/m2/day TMZ in patients with newly diagnosed glioblastoma followed by TMZ monochemotherapy. We have retrospectively analyzed the postoperative clinical course, occurrence and severity of adverse events, progression-free interval, and overall survival in 44 patients with newly diagnosed glioblastoma multiforme. All patients received multimodal treatment including tumor resection, BCNU wafer implantation, and concomitant radiochemotherapy. Of 44 patients (mean age 59 ± 10.8 years) with glioblastoma who received Gliadel wafer at primary surgery, 28 patients (64%) had died, 16 patients (36%) were alive, and 15 patients showed no evidence of clinical or radiographic progression after a median follow-up of 15.6 months. At time of analysis of adverse events in this patient population, the median overall survival was 12.7 months and median progression-free survival was 7.0 months. Surgical, neurological, and medical adverse events were analyzed. Twenty-three patients (52%) experienced adverse events of any kind including complications that did not require treatment. Nineteen patients (43%) experienced grade 3 or grade 4 adverse events. Surgical complications included cerebral edema, healing abnormalities, cerebral spinal fluid leakage, meningitis, intracranial abscess, and hydrocephalus. Neurological adverse events included newly diagnosed seizures, alteration of mental status, and new neurological deficits. Medical complications were thromboembolic events (thrombosis, pulmonary embolism) and hematotoxicity. Combination of both treatment strategies, local chemotherapy with BCNU wafer and concomitant radiochemotherapy, appears attractive in aggressive multimodal treatment schedules and may utilize the sensitizing effect of TMZ and carmustine on MGMT and AGT on their respective drug resistance genes. Our data demonstrate that combination of local chemotherapy and concomitant radiochemotherapy carries a significant risk of toxicity that currently appears underestimated. Adverse events observed in this study appear similar to complication rates published in the phase III trials for BCNU wafer implantation followed by radiation therapy alone, but further add the toxicity of concomitant radiochemotherapy with systemic TMZ. Save use of a combined approach will require specific prevention strategies for multimodal treatments

    An integrated workflow for crosslinking mass spectrometry

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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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