De novo peptide sequencing has improved remarkably in the past decade as a result of better instruments and computational algorithms. However, de novo sequencing can correctly interpret only ∼30% of high-and medium-quality spectra generated by collision-induced dissociation (CID), which is much less than database search. This is mainly due to incomplete fragmentation and overlap of different ion series in CID spectra. In this study, we show that higher-energy collisional dissociation (HCD) is of great help to de novo sequencing because it produces high mass accuracy tandem mass spectrometry (MS/MS) spectra without the low-mass cutoff associated with CID in ion trap instruments. Besides, abundant internal and immonium ions in the HCD spectra can help differentiate similar peptide sequences. Taking advantage of these characteristics, we developed an algorithm called pNovo for efficient de novo sequencing of peptides from HCD spectra. pNovo gave correct identifications to 80% or more of the HCD spectra identified by database search. The number of correct full-length peptides sequenced by pNovo is comparable with that obtained by database search. A distinct advantage of de novo sequencing is that deamidated peptides and peptides with amino acid mutations can be identified efficiently without extra cost in computation. In summary, implementation of the HCD characteristics makes pNovo an excellent tool for de novo peptide sequencing from HCD spectra.
De novo peptide sequencing is the only tool for extracting peptide sequences directly from tandem mass spectrometry (MS) data without any protein database. However, neither the accuracy nor the efficiency of de novo sequencing has been satisfactory, mainly due to incomplete fragmentation information in experimental spectra. Recent advancement in MS technology has enabled acquisition of higher energy collisional dissociation (HCD) and electron transfer dissociation (ETD) spectra of the same precursor. These spectra contain complementary fragmentation information and can be collected with high resolution and high mass accuracy. Taking these advantages, we have developed a new algorithm called pNovo+, which greatly improves the accuracy and speed of de novo sequencing. On tryptic peptides, 86% of the topmost candidate sequences deduced by pNovo+ from HCD + ETD spectral pairs matched the database search results, and the success rate reached 95% if the top three candidates were included, which was much higher than using only HCD (87%) or only ETD spectra (57%). On Asp-N, Glu-C, or Elastase digested peptides, 69-87% of the HCD + ETD spectral pairs were correctly identified by pNovo+ among the topmost candidates, or 84-95% among the top three. On average, it takes pNovo+ only 0.018 s to extract the sequence from a spectrum or spectral pair on a common personal computer. This is more than three times as fast as other de novo sequencing programs. The increase of speed is mainly due to pDAG, a component algorithm of pNovo+. pDAG finds the k longest paths in a directed acyclic graph without the antisymmetry restriction. We have verified that the antisymmetry restriction is unnecessary for high resolution, high mass accuracy data. The extensive use of HCD and ETD spectral information and the pDAG algorithm make pNovo+ an excellent de novo sequencing tool.
In relative protein abundance determination from peptide intensities recorded in full mass scans, a major complication that affects quantitation accuracy is signal interference from coeluting ions of similar m/z values. Here, we present pQuant, a quantitation software tool that solves this problem. pQuant detects interference signals, identifies for each peptide a pair of least interfered isotopic chromatograms: one for the light and one for the heavy isotope-labeled peptide. On the basis of these isotopic pairs, pQuant calculates the relative heavy/light peptide ratios along with their 99.75% confidence intervals (CIs). From the peptides ratios and their CIs, pQuant estimates the protein ratios and associated CIs by kernel density estimation. We tested pQuant, Census and MaxQuant on data sets obtained from mixtures (at varying mixing ratios from 10:1 to 1:10) of light-and heavy-SILAC labeled HeLa cells or 14 N-and 15 N-labeled Escherichia coli cells. pQuant quantitated more peptides with better accuracy than Census and MaxQuant in all 14 data sets. On the SILAC data sets, the nonquantified "NaN" (not a number) ratios generated by Census, MaxQuant, and pQuant accounted for 2.5−10.7%, 1.8−2.7%, and 0.01−0.5% of all ratios, respectively. On the 14 N/ 15 N data sets, which cannot be quantified by MaxQuant, Census and pQuant produced 0.9−10.0% and 0.3−2.9% NaN ratios, respectively. Excluding these NaN results, the standard deviations of the numerical ratios calculated by Census or MaxQuant are 30−100% larger than those by pQuant. These results show that pQuant outperforms Census and MaxQuant in SILAC and 15 N-based quantitation.M uch progress has been made in mass spectrometry (MS)-based quantitative proteomics in recent years, as evidenced by numerous applications, such as biomarker discovery, 1 study of chromatin assembly and disassembly, 2 identification of insulin signaling targets, 3 and protein posttranslational modification (PTM). 4 Among the most commonly used quantitative strategies are full MS scan-based quantitation methods, such as SILAC (stable isotope labeling with amino acids in cell), 5 15 N-labeling, 6 and 18 O-labeling. 7 In these strategies, proteins are metabolically labeled with stable isotopes, digested into peptides, and then analyzed using liquid chromatography (LC)-MS/MS. Quantitation software tools are designed to extract the intensities of pairs of light (L, unlabeled) and heavy (H, labeled) peptides from full MS scans. The relative abundance ratio of a protein between two conditions is then calculated based on the ratios of its constituent peptides. 8 For high-complexity samples such as whole cell lysates, it is not uncommon that a peptide coelutes with another peptide or a nonpeptide contaminant of a similar m/z value. 9 The interference caused by coeluting ions of similar m/z values can seriously compromise the accuracy of quantitation. 10,11 We examined two leading quantitation software tools Census 12 and MaxQuant, 13 and found that a lot of the peptide quantitation results ...
For practical applications of high-performance supercapacitors as wearable energy storage devices attached to skin or clothes, the supercapacitors are recommended to have stable mechanical and electrochemical performances during dynamic deformations, including stretching, due to real-time movements of the human body. In this work, we demonstrate a skin-like, dynamically stretchable, planar supercapacitor (SPS). The SPS consists of buckled manganese/molybdenum (Mn/Mo) mixed oxide@multiwalled carbon nanotube (MWCNT) electrodes; organic gel polymer electrolyte of adiponitrile, succinonitrile, lithium bis(trifluoromethanesulfonyl)imide, and poly(methyl methacrylate); and a porous, elastomeric substrate. The addition of an Mn/Mo mixed oxide to the MWCNT film produces an 8-fold increase in the areal capacitance. The use of an organic solvent-based electrolyte enhances the operation cell voltage to 2 V and air stability to one month under ambient air conditions. The fabricated planar supercapacitors are biaxially stretchable up to 50% strain and maintain ∼90% of their initial capacitance after 1000 repetitive stretching/releasing cycles. Furthermore, the SPS exhibits stable electrochemical performance under dynamic stretching in real time regardless of the strain rate and performs reliably during repetitive bending/spreading motions of an index finger while attached to skin.
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