Exosomes are natural carriers of exogenous siRNA to human cells in vitro

© 2013 Shtam et al. Background: Exosomes are nano-sized vesicles of endocytic origin that are involved in cell-to-cell communication including shuttle RNA, mainly mRNA and microRNA. As exosomes naturally carry RNA between cells, these particles might be useful in gene cancer therapy to deliver therapeutic short interfering RNA (siRNA) to the target cells. Despite the promise of RNA interference (RNAi) for use in therapy, several technical obstacles must be overcome. Exogenous siRNA is prone to degradation, has a limited ability to cross cell membranes and may induce an immune response. Naturally occurring RNA carriers, such as exosomes, might provide an untapped source of effective delivery strategies. Results: This study demonstrates that exosomes can deliver siRNA to recipient cells in vitro. The different strategies were used to introduce siRNAs into human exosomes of various origins. The delivery of fluorescently labeled siRNA via exosomes to cells was confirmed using confocal microscopy and flow cytometry. Two different siRNAs against RAD51 and RAD52 were used to transfect into the exosomes for therapeutic delivery into target cells. The exosome-delivered siRNAs were effective at causing post-transcriptional gene silencing in recipient cells. Moreover, the exosome-delivered siRNA against RAD51 was functional and caused the massive reproductive cell death of recipient cancer cells. Conclusions: The results strongly suggest that exosomes effectively delivered the siRNA into the target cells. The therapeutic potential of exosome-mediated siRNA delivery was demonstrated in vitro by the strong knockdown of RAD51, a prospective therapeutic target for cancer cells. The results give an additional evidence of the ability to use human exosomes as vectors in cancer therapy, including RNAi-based gene therapy. © 2013 Shtam et al.; licensee BioMed Central Ltd.Russian Federal Program “Scientific and Scientific-Pedagogical Personnel of Innovative Russia”, contract 14.740.11.0754 and Fellowship from the Administration of Leningrad region to Shtam T

SuperQuant:a Data Processing Approach to Increase Quantitative Proteome Coverage

SuperQuant is a quantitative proteomics data processing approach that uses complementary fragment ions to identify multiple coisolated peptides in tandem mass spectra allowing for their quantification. This approach can be applied to any shotgun proteomics data set acquired with high mass accuracy for quantification at the MS¹ level. The SuperQuant approach was developed and implemented as a processing node within the Thermo Proteome Discoverer 2.x. The performance of the developed approach was tested using dimethyl-labeled HeLa lysate samples having a ratio between channels of 10­(heavy):4­(medium):1­(light). Peptides were fragmented with collision-induced dissociation using isolation windows of 1, 2, and 4 Th while recording data both with high-resolution and low-resolution. The results obtained using SuperQuant were compared to those using the conventional ion trap-based approach (low mass accuracy MS² spectra), which is known to achieve high identification performance. Compared to the common high-resolution approach, the SuperQuant approach identifies up to 70% more peptide–spectrum matches (PSMs), 40% more peptides, and 20% more proteins at the 0.01 FDR level. It identifies more PSMs and peptides than the ion trap-based approach. Improvements in identifications resulted in up to 10% more PSMs, 15% more peptides, and 10% more proteins quantified on the same raw data. The developed approach does not affect the accuracy of the quantification and observed coefficients of variation between replicates of the same proteins were close to the values typical for other precursor ion-based quantification methods. The raw data is deposited to ProteomeXchange (PXD001907). The developed node is available for testing at https://github.com/caetera/SuperQuantNode

Selective Maleylation-Directed Isobaric Peptide Termini Labeling for Accurate Proteome Quantification

Isobaric peptide termini labeling (IPTL) is an attractive protein quantification method because it provides more accurate and reliable quantification information than traditional isobaric labeling methods (e.g., TMT and iTRAQ) by making use of the entire fragment-ion series instead of only a single reporter ion. The multiplexing capacity of published IPTL implementations is, however, limited to three. Here, we present a selective maleylation-directed isobaric peptide termini labeling (SMD-IPTL) approach for quantitative proteomics of LysC protein digestion. SMD-IPTL extends the multiplexing capacity to 4-plex with the potential for higher levels of multiplexing using commercially available 13C/15N labeled amino acids. SMD-IPTL is achieved in a one-pot reaction in three consecutive steps: (1) selective maleylation at the N-terminus; (2) labeling at the ϵ-NH2 group of the C-terminal Lys with isotopically labeled acetyl-alanine; (3) thiol Michael addition of an isotopically labeled acetyl-cysteine at the maleylated N-terminus. The isobarically labeled peptides are fragmented into sets of b- and y-ion clusters upon LC-MS/MS, which convey not only sequence information but also quantitative information for every labeling channel and avoid the issue of ratio distortion observed with reporter-ion-based approaches. We demonstrate the SMD-IPTL approach with a 4-plex labeled sample of bovine serum albumin (BSA) and yeast lysates mixed at different ratios. With the use of SMD-IPTL for labeling and a narrow precursor isolation window of 0.8 Th with an offset of -0.2 Th, accurate ratios were measured across a 10-fold mixing range of BSA in a background of yeast proteome. With the yeast proteins mixed at ratios of 1:5:1:5, BSA was detected at ratios of 0.94:2.46:4.70:9.92 when spiked at 1:2:5:10 ratios with an average standard deviation of peptide ratios of 0.34

Cysteine-Directed Isobaric Labeling Combined with GeLC-FAIMS-MS for Quantitative Top-Down Proteomics

The quantification of proteoforms, i.e., all molecular forms in which proteins can be present, by top-down proteomics provides essential insights into biological processes at the molecular level. Isobaric labeling-based quantification strategies are suitable for multidimensional separation strategies and allow for multiplexing of the samples. Here, we investigated cysteine-directed isobaric labeling by iodoTMT in combination with a gel- and gas-phase fractionation (GeLC-FAIMS-MS) for in-depth quantitative proteoform analysis. We optimized the acquisition workflow (i.e., the FAIMS compensation voltages, isolation windows, acquisition strategy, and fragmentation method) using a two-proteome mix to increase the number of quantified proteoforms and reduce ratio compression. Additionally, we implemented a mass feature-based quantification strategy in the widely used deconvolution algorithm FLASHDeconv, which improves and facilitates data analysis. The optimized iodoTMT GeLC-FAIMS-MS workflow was applied to quantitatively analyze the proteome of Escherichia coli grown under glucose or acetate as the sole carbon source, resulting in the identification of 726 differentially abundant proteoforms

A Versatile Isobaric Tag Enables Proteome Quantification in Data-Dependent and Data-Independent Acquisition Modes

Quantifying proteins based on peptide-coupled reporter ions is a multiplexed quantitative strategy in proteomics that alleviates the problem of ratio distortion caused by peptide cofragmentation, as commonly observed in other reporter-ion-based approaches, such as TMT and iTRAQ. Data-independent acquisition (DIA) is an attractive alternative to data-dependent acquisition (DDA) due to its better reproducibility. While multiplexed labeling is widely used in DDA, it is rarely used in DIA, presumably because current approaches lead to more complex MS2 spectra, severe ratio distortion, or to a reduction in quantification accuracy and precision. Herein, we present a versatile acetyl-alanine-glycine (Ac-AG) tag that conceals quantitative information in isobarically labeled peptides and reveals it upon tandem MS in the form of peptide-coupled reporter ions. Since the peptide-coupled reporter ion is precursor-specific while fragment ions of the peptide backbone originating from different labeling channels are identical, the Ac-AG tag is compatible with both DDA and DIA. By isolating the monoisotopic peak of the precursor ion in DDA, intensities of the peptide-coupled reporter ions represent the relative ratios between constituent samples, whereas in DIA, the ratio can be inferred after deconvoluting the peptide-coupled reporter ion isotopes. The proteome quantification capability of the Ac-AG tag was demonstrated by triplex labeling of a yeast proteome spiked with bovine serum albumin (BSA) over a 10-fold dynamic range. Within this complex proteomics background, BSA spiked at 1:5:10 ratios was detected at ratios of 1.00:4.87:10.13 in DDA and 1.16:5.20:9.64 in DIA

Chemical approaches for quantitative proteomics

Xiaobo focuses on developing novel isotope labeling-based tags for quantitative proteomics along two lines of research: (1) In data-dependent acquisition (DDA) mode, eliminating the ratio distortion caused by peptide cofragmentation and increasing the multiplexing capacity. (2) In data-independent acquisition (DIA) mode, achieving multiplexed quantification with general DIA LC-MS settings. The representative work, Ac-IP tag that specifically suitable for the multiplexing in DIA mode, attracted much attention from peers

Proteomics using protease alternatives to trypsin benefits from sequential digestion with trypsin

Trypsin is the most used enzyme in proteomics. Nevertheless, proteases with complementary cleavage specificity have been applied in special circumstances. In this work, we analyzed the characteristics of five protease alternatives to trypsin for pro-tein identification and sequence coverage when applied to S. pombe whole cell lysates. The specificity of the protease heavily impacted on the number of proteins identified. Proteases with higher specificity let to the identification of more proteins than proteases with lower specificity. However, AspN, GluC, chymotrypsin and proteinase K largely benefited from being paired with trypsin in sequential digestion, as had been shown by us for elastase before. In the most extreme case, pre-digesting with trypsin improves the number of identified proteins for proteinase K by 731 %. Trypsin pre-digestion also improved the protein identifications of other proteases, AspN (+62 %), GluC (+80 %) and chymotrypsin (+21 %). Interestingly, the sequential digest with trypsin and AspN yielded even higher number of protein identifications than digesting with trypsin alone

MultiNotch MS3 Enables Accurate, Sensitive, and Multiplexed Detection of Differential Expression across Cancer Cell Line Proteomes

Multiplexed quantitation via isobaric chemical tags (e.g., tandem mass tags (TMT) and isobaric tags for relative and absolute quantitation (iTRAQ)) has the potential to revolutionize quantitative proteomics. However, until recently the utility of these tags was questionable due to reporter ion ratio distortion resulting from fragmentation of coisolated interfering species. These interfering signals can be negated through additional gas-phase manipulations (e.g., MS/MS/MS (MS3) and proton-transfer reactions (PTR)). These methods, however, have a significant sensitivity penalty. Using isolation waveforms with multiple frequency notches (i.e., synchronous precursor selection, SPS), we coisolated and cofragmented multiple MS2 fragment ions, thereby increasing the number of reporter ions in the MS3 spectrum 10-fold over the standard MS3 method (i.e., MultiNotch MS3). By increasing the reporter ion signals, this method improves the dynamic range of reporter ion quantitation, reduces reporter ion signal variance, and ultimately produces more high-quality quantitative measurements. To demonstrate utility, we analyzed biological triplicates of eight colon cancer cell lines using the MultiNotch MS3 method. Across all the replicates we quantified 8 378 proteins in union and 6 168 proteins in common. Taking into account that each of these quantified proteins contains eight distinct cell-line measurements, this data set encompasses 174 704 quantitative ratios each measured in triplicate across the biological replicates. Herein, we demonstrate that the MultiNotch MS3 method uniquely combines multiplexing capacity with quantitative sensitivity and accuracy, drastically increasing the informational value obtainable from proteomic experiments