MassUntangler: a novel alignment tool for label-free liquid chromatography-mass spectrometry proteomic data.

Liquid chromatography-mass spectrometry (LC-MS) has become an important analytical tool for quantitative proteomics and biomarker discovery. In the label-free differential LC-MS approach computational methods are required for an accurate alignment of peaks extrapolated from the experimental raw data accounting for retention time and m/z signals intensity, which are strongly affected by sample matrix and instrumental performance. A novel procedure "MassUntangler" for pairwise alignment has been developed, relying on a pattern-based matching algorithm integrated with filtering algorithms in a multi-step approach. The procedure has been optimized employing a two-step approach. Firstly, low-complexity LC-MS data derived from the enzymatic digestion of two standard proteins have been analyzed. Then, the algorithm's performance has been evaluated by comparing the results with other achieved using state-of-the-art alignment tools. In the second step, our algorithm has been used for the alignment of high-complexity LC-MS data consisting of peptides obtained by an Escherichia coli lysate available from a public repository previously used for the comparison of other alignment tools. MassUntangler gave excellent results in terms of precision scores (from 80% to 93%) and recall scores (from 68% to 89%), showing performances similar and even better than the previous developed tools. Considering the mass spectrometry sensitivity and accuracy, this approach allows the identification and quantification of peptides present in a biological sample at femtomole level with high confidence. The procedure's capability of aligning LC-MS data previously corrected for distortion in retention time has been studied through a hybrid approach, in which MassUntangler was interfaced with the OpenMS TOPP tool MapAligner. The hybrid aligner yielded better results, showing that an integration of different bioinformatic approaches for accurate label-free LC-MS data alignment should be used.

Ballardini R ，Benevento M ，Arrigoni G ，Pattini L ，Roda A ... -  《-》

A geometric approach for the alignment of liquid chromatography-mass spectrometry data.

Lange E ，Gröpl C ，Schulz-Trieglaff O ，Leinenbach A ，Huber C ，Reinert K ... -  《-》

Time alignment algorithms based on selected mass traces for complex LC-MS data.

Christin C ，Hoefsloot HC ，Smilde AK ，Suits F ，Bischoff R ，Horvatovich PL ... -  《-》

i-RUBY: a novel software for quantitative analysis of highly accurate shotgun-proteomics liquid chromatography/tandem mass spectrometry data obtained without stable-isotope labeling of proteins.

We developed a novel software named i-RUBY (identification-Related qUantification-Based strategY algorithm for liquid chromatography/tandem mass spectrometry (LC/MS/MS) data) that enables us to perform fully automatic ion current-based spectral feature analysis of highly accurate data obtained by LC/MS/MS. At the 1st step, this software utilizes accurate peptide/protein identification information for peak detection and peak matching among measurements. Then, at the 2nd step, it picks yet unidentified peaks and matches them to the peaks identified at the 1st step by a linear interpolation algorithm. The analysis of human plasma externally spiked with a known amount of yeast alcohol dehydrogenase 1 showed a good linear relationship between the amount of protein spiked and the quantitative values obtained by i-RUBY analysis. Experiment using human plasma digests spiked with a mixture of known amounts of synthetic peptides derived from two yeast proteins, alcohol dehydrogenase 1 and glucose-6-phospate isomerase, showed the expansion by the 2nd step of i-RUBY of the lower quantification limits to 1/10 to 1/1000 of those reached only by identified peaks at the 1st step. Good correlations between the i-RUBY results and the amount of proteins were confirmed by the analysis of real samples, i.e., sera of normal subjects and cancer patients, by comparing quantitative values of acute-phase proteins obtained by i-RUBY analysis of LC/MS/MS data with those obtained by an immunological method using Bio-Plex. These results taken together show that i-RUBY is a useful tool for obtaining dependable quantitative information from highly accurate shotgun-proteomics LC/MS/MS data.

Wada K ，Ogiwara A ，Nagasaka K ，Tanaka N ，Komatsu Y ... -  《-》

ProteinQuant Suite: a bundle of automated software tools for label-free quantitative proteomics.

Mann B ，Madera M ，Sheng Q ，Tang H ，Mechref Y ，Novotny MV ... -  《-》