Precise Alkoxyamine Design to Enable Automated Tandem Mass Spectrometry Sequencing of Digital Poly(phosphodiester)s.

A major step towards reliable reading of information coded in the sequence of long poly(phosphodiester)s was previously achieved by introducing an alkoxyamine spacer between information sub-segments. However, MS/MS decoding had to be performed manually to safely identify useful fragments of low abundance compared to side-products from the amide-based alkoxyamine used. Here, alternative alkoxyamines were designed to prevent side-reactions and enable automated MS/MS sequencing. Different styryl-TEMPO spacers were prepared to increase radical delocalization and stiffness of the structure. Their dissociation behavior was investigated by EPR and best results were obtained with spacers containing in-chain benzyl ring, with no side-reaction during synthesis or sequencing. Automated decoding of these polymers was performed using the MS-DECODER software, which interprets fragmentation data recorded for each sub-segment and re-align them in their original order based on location tags.

Optimal conditions for tandem mass spectrometric sequencing of information-containing nitrogen-substituted polyurethanes.

RATIONALE: To prevent solubility issues faced with sequence-defined polyurethanes, a new family of digital polyurethanes was conceived with the alkyl coding chain held by the carbamate nitrogen (N) atom and CH3 instead of OH as the ϖ termination. This led to different dissociation mechanisms that were explored prior to optimizing tandem mass spectrometric (MS/MS) sequencing. METHODS: N-Substituted polyurethanes (N-R PUs) were dissolved in methanol and subjected to collision-induced dissociation (CID) as deprotonated chains in the negative ion mode, and as ammonium and sodium adducts in the positive ion mode, using electrospray ionization (ESI) as the ionization technique. Their dissociation behavior was thoroughly investigated using a quadrupole time-of-flight (QTOF) instrument in order to provide accurate mass measurements to support proposed fragmentation mechanisms. RESULTS: While O-(CO) bonds were broken in N-H PUs, the CH2 -O linkage between repeating units was cleaved upon CID of N-R PUs. This main process occurred either from deprotonated molecules or from cationized chains but was followed by different rearrangements, producing up to four product ion series. Yet, MS/MS spectra could be drastically simplified for precursor ions having their acidic α group methylated, as was found to spontaneously occur upon storage in methanol. CONCLUSIONS: Using experimental conditions aimed at avoiding any reactive proton in precursor ions (no acidic end-groups and alkali adduction), full coverage sequence of N-R PUs was successfully achieved with the single ion series observed in MS/MS, opening a promising perspective for reading large amounts of information stored in these dyad-encoded polymers.

Proline: an efficient and user-friendly software suite for large-scale proteomics.

MOTIVATION: The proteomics field requires the production and publication of reliable mass spectrometry-based identification and quantification results. Although many tools or algorithms exist, very few consider the importance of combining, in a unique software environment, efficient processing algorithms and a data management system to process and curate hundreds of datasets associated with a single proteomics study. RESULTS: Here, we present Proline, a robust software suite for analysis of MS-based proteomics data, which collects, processes and allows visualization and publication of proteomics datasets. We illustrate its ease of use for various steps in the validation and quantification workflow, its data curation capabilities and its computational efficiency. The DDA label-free quantification workflow efficiency was assessed by comparing results obtained with Proline to those obtained with a widely used software using a spiked-in sample. This assessment demonstrated Proline's ability to provide high quantification accuracy in a user-friendly interface for datasets of any size. AVAILABILITY AND IMPLEMENTATION: Proline is available for Windows and Linux under CECILL open-source license. It can be deployed in client-server mode or in standalone mode at http://proline.profiproteomics.fr/#downloads. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cleavable Binary Dyads: Simplifying Data Extraction and Increasing Storage Density in Digital Polymers.

Digital polymers are uniform macromolecules that store monomer-based binary sequences. Molecularly stored information is usually extracted from the polymer by a tandem mass spectrometry (MS/MS) measurement, in which the coded chains are fragmented to reveal each bit (i.e. basic coded monomer unit) of the sequence. Here, we show that data-extraction can be greatly simplified by favoring the formation of MS/MS fragments containing two bits instead of one. In order to do so, digital poly(alkoxyamine phosphodiester)s, containing binary dyads in each repeat unit, were prepared by an orthogonal solid-phase approach involving successive phosphoramidite and radical-radical coupling steps. Three different sets of monomers were considered to build these polymers. In all cases, four coded building blocks-two hydroxy-nitroxides and two phosphoramidite monomers-were required to build the dyads. Among the three studied monomer sets, one combination allowed synthesis of uniform sequence-coded polymers. The resulting polymers led to clear dyad-containing fragments in MS/MS and could therefore be efficiently decoded. Additionally, an algorithm was created to detect specific dyad fragments, thus enabling automated sequencing.

Computational and Mass-Spectrometry-Based Workflow for the Discovery and Validation of Missing Human Proteins: Application to Chromosomes 2 and 14.

In the framework of the C-HPP, our Franco-Swiss consortium has adopted chromosomes 2 and 14, coding for a total of 382 missing proteins (proteins for which evidence is lacking at protein level). Over the last 4 years, the French proteomics infrastructure has collected high-quality data sets from 40 human samples, including a series of rarely studied cell lines, tissue types, and sample preparations. Here we described a step-by-step strategy based on the use of bioinformatics screening and subsequent mass spectrometry (MS)-based validation to identify what were up to now missing proteins in these data sets. Screening database search results (85,326 dat files) identified 58 of the missing proteins (36 on chromosome 2 and 22 on chromosome 14) by 83 unique peptides following the latest release of neXtProt (2014-09-19). PSMs corresponding to these peptides were thoroughly examined by applying two different MS-based criteria: peptide-level false discovery rate calculation and expert PSM quality assessment. Synthetic peptides were then produced and used to generate reference MS/MS spectra. A spectral similarity score was then calculated for each pair of reference-endogenous spectra and used as a third criterion for missing protein validation. Finally, LC-SRM assays were developed to target proteotypic peptides from four of the missing proteins detected in tissue/cell samples, which were still available and for which sample preparation could be reproduced. These LC-SRM assays unambiguously detected the endogenous unique peptide for three of the proteins. For two of these, identification was confirmed by additional proteotypic peptides. We concluded that of the initial set of 58 proteins detected by the bioinformatics screen, the consecutive MS-based validation criteria led to propose the identification of 13 of these proteins (8 on chromosome 2 and 5 on chromosome 14) that passed at least two of the three MS-based criteria. Thus, a rigorous step-by-step approach combining bioinformatics screening and MS-based validation assays is particularly suitable to obtain protein-level evidence for proteins previously considered as missing. All MS/MS data have been deposited in ProteomeXchange under identifier PXD002131.

MSDA, a proteomics software suite for in-depth Mass Spectrometry Data Analysis using grid computing.

One of the major bottlenecks in the proteomics field today resides in the computational interpretation of the massive data generated by the latest generation of high-throughput MS instruments. MS/MS datasets are constantly increasing in size and complexity and it becomes challenging to comprehensively process such huge datasets and afterwards deduce most relevant biological information. The Mass Spectrometry Data Analysis (MSDA, https://msda.unistra.fr) online software suite provides a series of modules for in-depth MS/MS data analysis. It includes a custom databases generation toolbox, modules for filtering and extracting high-quality spectra, for running high-performance database and de novo searches, and for extracting modified peptides spectra and functional annotations. Additionally, MSDA enables running the most computationally intensive steps, namely database and de novo searches, on a computer grid thus providing a net time gain of up to 99% for data processing.