Chengjian Tu

Depletion of Abundant Plasma Proteins and Limitations of Plasma Proteomics

Immunoaffinity depletion with antibodies to the top 7 or top 14 high-abundance plasma proteins is used to enhance detection of lower abundance proteins in both shotgun and targeted proteomic analyses. We evaluated the effects of top 7/top 14 immunodepletion on the shotgun proteomic analysis of human plasma. Our goal was to evaluate the impact of immunodepletion on detection of proteins across detectable ranges of abundance. The depletion columns afforded highly repeatable and efficient plasma protein fractionation. Relatively few nontargeted proteins were captured by the depletion columns. Analyses of unfractionated and immunodepleted plasma by peptide isoelectric focusing (IEF), followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), demonstrated enrichment of nontargeted plasma proteins by an average of 4-fold, as assessed by MS/MS spectral counting. Either top 7 or top 14 immunodepletion resulted in a 25% increase in identified proteins compared to unfractionated plasma. Although 23 low-abundance (<10 ng mL(-1)) plasma proteins were detected, they accounted for only 5-6% of total protein identifications in immunodepleted plasma. In both unfractionated and immunodepleted plasma, the 50 most abundant plasma proteins accounted for 90% of cumulative spectral counts and precursor ion intensities, leaving little capacity to sample lower abundance proteins. Untargeted proteomic analyses using current LC-MS/MS platforms-even with immunodepletion-cannot be expected to efficiently discover low-abundance, disease-specific biomarkers in plasma.

Combinatorial peptide ligand library treatment followed by a dual-enzyme, dual-activation approach on a nanoflow liquid chromatography/orbitrap/electron transfer dissociation system for comprehensive analysis of swine plasma proteome.

The plasma proteome holds enormous clinical potential, yet an in-depth analysis of the plasma proteome remains a daunting challenge due to its high complexity and the extremely wide dynamic range in protein concentrations. Furthermore, existing antibody-based approaches for depleting high-abundance proteins are not adaptable to the analysis of the animal plasma proteome, which is often essential for experimental pathology/pharmacology. Here we describe a highly comprehensive method for the investigation of the animal plasma proteome which employs an optimized combinatorial peptide ligand library (CPLL) treatment to reduce the protein concentration dynamic range and a dual-enzyme, dual-activation strategy to achieve high proteomic coverage. The CPLL treatment enriched the lower abundance proteins by >100-fold when the samples were loaded in moderately denaturing conditions with multiple loading-washing cycles. The native and the CPLL-treated plasma were digested in parallel by two enzymes (trypsin and GluC) carrying orthogonal specificities. By performing this differential proteolysis, the proteome coverage is improved where peptides produced by only one enzyme are poorly detectable. Digests were fractionated with high-resolution strong cation exchange chromatography and then resolved on a long, heated nano liquid chromatography column. MS analysis was performed on a linear triple quadrupole/orbitrap with two complementary activation methods (collisionally induced dissociation (CID) and electron transfer dissociation). We applied this optimized strategy to investigate the plasma proteome from swine, a prominent animal model for cardiovascular diseases (CVDs). This large-scale analysis results in identification of a total of 3421 unique proteins, spanning a concentration range of 9-10 orders of magnitude. The proteins were identified under a set of commonly accepted criteria, including a precursor mass error of <15 ppm, Xcorr cutoffs, and ≥2 unique peptides at a peptide probability of ≥95% and a protein probability of ≥99%, and the peptide false-positive rate of the data set was 1.8% as estimated by searching the reversed database. CPLL treatment resulted in 55% more identified proteins over those from native plasma; moreover, compared with using only trypsin and CID, the dual-enzyme/activation approach enabled the identification of 2.6-fold more proteins and substantially higher sequence coverage for most individual proteins. Further analysis revealed 657 proteins as significantly associated with CVDs (p < 0.05), which constitute five CVD-related pathways. This study represents the first in-depth investigation of a nonhuman plasma proteome, and the strategy developed here is adaptable to the comprehensive analysis of other highly complex proteomes.

Ion-current-based Proteomic Profiling of the Retina in a Rat Model of Smith-Lemli-Opitz Syndrome

Smith-Lemli-Opitz syndrome (SLOS) is one of the most common recessive human disorders and is characterized by multiple congenital malformations as well as neurosensory and cognitive abnormalities. A rat model of SLOS has been developed that exhibits progressive retinal degeneration and visual dysfunction; however, the molecular events underlying the degeneration and dysfunction remain poorly understood. Here, we employed a well-controlled, ion-current-based approach to compare retinas from the SLOS rat model to retinas from age- and sex-matched control rats (n = 5/group). Retinas were subjected to detergent extraction and subsequent precipitation and on-pellet-digestion procedures and then were analyzed on a long, heated column (75 cm, with small particles) with a 7-h gradient. The high analytical reproducibility of the overall proteomics procedure enabled reliable expression profiling. In total, 1,259 unique protein groups, ∼40% of which were membrane proteins, were quantified under highly stringent criteria, including a peptide false discovery rate of 0.4%, with high quality ion-current data (e.g. signal-to-noise ratio ≥ 10) obtained independently from at least two unique peptides for each protein. The ion-current-based strategy showed greater quantitative accuracy and reproducibility over a parallel spectral counting analysis. Statistically significant alterations of 101 proteins were observed; these proteins are implicated in a variety of biological processes, including lipid metabolism, oxidative stress, cell death, proteolysis, visual transduction, and vesicular/membrane transport, consistent with the features of the associated retinal degeneration in the SLOS model. Selected targets were further validated by Western blot analysis and correlative immunohistochemistry. Importantly, although photoreceptor cell death was validated by TUNEL analysis, Western blot and immunohistochemical analyses suggested a caspase-3-independent pathway. In total, these results provide compelling new evidence implicating molecular changes beyond the initial defect in cholesterol biosynthesis in this retinal degeneration model, and they might have broader implications with respect to the pathobiological mechanism underlying SLOS.

Systematic assessment of survey scan and MS2-based abundance strategies for label-free quantitative proteomics using high-resolution MS data.

Survey-scan-based label-free method have shown no compelling benefit over fragment ion (MS2)-based approaches when low-resolution mass spectrometry (MS) was used, the growing prevalence of high-resolution analyzers may have changed the game. This necessitates an updated, comparative investigation of these approaches for data acquired by high-resolution MS. Here, we compared survey scan-based (ion current, IC) and MS2-based abundance features including spectral-count (SpC) and MS2 total-ion-current (MS2-TIC), for quantitative analysis using various high-resolution LC/MS data sets. Key discoveries include: (i) study with seven different biological data sets revealed only IC achieved high reproducibility for lower-abundance proteins; (ii) evaluation with 5-replicate analyses of a yeast sample showed IC provided much higher quantitative precision and lower missing data; (iii) IC, SpC, and MS2-TIC all showed good quantitative linearity (R2 > 0.99) over a >1000-fold concentration range; (iv) both MS2-TIC and IC showed good linear response to various protein loading amounts but not SpC; (v) quantification using a well-characterized CPTAC data set showed that IC exhibited markedly higher quantitative accuracy, higher sensitivity, and lower false-positives/false-negatives than both SpC and MS2-TIC. Therefore, IC achieved an overall superior performance than the MS2-based strategies in terms of reproducibility, missing data, quantitative dynamic range, quantitative accuracy, and biomarker discovery.

Highly multiplexed and reproducible ion-current-based strategy for large-scale quantitative proteomics and the application to protein expression dynamics induced by methylprednisolone in 60 rats.

A proteome-level time-series study of drug effects (i.e., pharmacodynamics) is critical for understanding mechanisms of action and systems pharmacology, but is challenging, because of the requirement of a proteomics method for reliable quantification of many biological samples. Here, we describe a highly reproducible strategy, enabling a global, large-scale investigation of the expression dynamics of corticosteroid-regulated proteins in livers from adrenalectomized rats over 11 time points after drug dosing (0.5–66 h, N = 5/point). The analytical advances include (i) exhaustive tissue extraction with a Polytron/sonication procedure in a detergent cocktail buffer, and a cleanup/digestion procedure providing very consistent protein yields (relative standard deviation (RSD%) of 2.7%–6.4%) and peptide recoveries (4.1–9.0%) across the 60 animals; (ii) an ultrahigh-pressure nano-LC setup with substantially improved temperature stabilization, pump-noise suppression, and programmed interface cleaning, enabling excellent reproducibility for continuous analyses of numerous samples; (iii) separation on a 100-cm-long column (2-μm particles) with high reproducibility for days to enable both in-depth profiling and accurate peptide ion-current match; and (iv) well-controlled ion-current-based quantification. To obtain high-quality quantitative data necessary to describe the 11 time-points protein expression temporal profiles, strict criteria were used to define “quantifiable proteins”. A total of 323 drug-responsive proteins were revealed with confidence, and the time profiles of these proteins provided new insights into the diverse temporal changes of biological cascades associated with hepatic metabolism, response to hormone stimuli, gluconeogenesis, inflammatory responses, and protein translation processes. Most profile changes persisted well after the drug was eliminated. The developed strategy can also be broadly applied in preclinical and clinical research, where the analysis of numerous biological replicates is crucial.

ICan: an optimized ion-current-based quantification procedure with enhanced quantitative accuracy and sensitivity in biomarker discovery.

The rapidly expanding availability of high-resolution mass spectrometry has substantially enhanced the ion-current-based relative quantification techniques. Despite the increasing interest in ion-current-based methods, quantitative sensitivity, accuracy, and false discovery rate remain the major concerns; consequently, comprehensive evaluation and development in these regards are urgently needed. Here we describe an integrated, new procedure for data normalization and protein ratio estimation, termed ICan, for improved ion-current-based analysis of data generated by high-resolution mass spectrometry (MS). ICan achieved significantly better accuracy and precision, and lower false-positive rate for discovering altered proteins, over current popular pipelines. A spiked-in experiment was used to evaluate the performance of ICan to detect small changes. In this study E. coli extracts were spiked with moderate-abundance proteins from human plasma (MAP, enriched by IgY14-SuperMix procedure) at two different levels to set a small change of 1.5-fold. Forty-five (92%, with an average ratio of 1.71 ± 0.13) of 49 identified MAP protein (i.e., the true positives) and none of the reference proteins (1.0-fold) were determined as significantly altered proteins, with cutoff thresholds of ≥1.3-fold change and p ≤ 0.05. This is the first study to evaluate and prove competitive performance of the ion-current-based approach for assigning significance to proteins with small changes. By comparison, other methods showed remarkably inferior performance. ICan can be broadly applicable to reliable and sensitive proteomic survey of multiple biological samples with the use of high-resolution MS. Moreover, many key features evaluated and optimized here such as normalization, protein ratio determination, and statistical analyses are also valuable for data analysis by isotope-labeling methods.

Proteomic profiling of the retinas in a neonatal rat model of oxygen-induced retinopathy with a reproducible ion-current-based MS1 approach.

Investigation of the retina proteome during hypoxia-induced retinal neovascularization is valuable for understanding pathogenesis of retinopathy of prematurity (ROP). Here we employed a reproducible ion-current-based MS1 quantification approach (ICB) to explore the retinal proteomic changes in early stage of ROP in a rat model of oxygen-induced retinopathy (OIR). Retina proteins, which are rich in membrane proteins, were efficiently extracted by a detergent-cocktail and subjected to precipitation/on-pellet-digestion, followed by nano-LC-MS analysis on a 75-cm column with a 7-h gradient. The high reproducibility of sample preparation and chromatography separation enabled excellent peak alignment and contributed to the superior performance of ICB over parallel label-free approaches. In this study, sum-of-intensity with rejection was incorporated to determine the protein ratios. In total, 1325 unique protein groups were quantified from rat retinas (n = 4/group) with at least two distinct peptides at a protein FDR of 1%. Thirty-two significantly altered proteins were observed with confidence, and the elevated glial fibrillary acidic protein and decreased crystalline proteins in OIR retinas agree well with previous studies. Selected key alterations were further validated by Western blot analysis. Interestingly, Rab21/RhoA/ROCK2/moesin signaling pathway was found to be involved in retinal neovascularization of OIR. Moreover, highly elevated annexin A3, a potential angiogenic mediator, was observed in OIR retinas and may serve as a potential therapeutic target. In conclusion, reproducible ICB profiling enabled reliable discovery of many altered mediators and pathways in OIR retinas, thereby providing new insights into molecular mechanisms involved in pathogenesis of ROP.

An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts

In-depth and reproducible protein measurement in many biological samples is often critical for pharmaceutical/biomedical proteomics but remains challenging. MS1-based quantification using quadrupole/ultrahigh-field Orbitrap (Q/UHF-Orbitrap) holds great promise, but the critically important experimental approaches enabling reliable large-cohort analysis have long been overlooked. Here we described an IonStar experimental strategy achieving excellent quantitative quality of MS1 quantification. Key features include: (i) an optimized, surfactant-aided sample preparation approach provides highly efficient (>75% recovery) and reproducible (<15% CV) peptide recovery across large cell/tissue cohorts; (ii) a long column with modest gradient length (2.5 h) yields the optimal balance of depth/throughput on a Q/UHF-Orbitrap; (iii) a large-ID trap not only enables highly reproducible gradient delivery as for the first time observed via real-time conductivity monitoring, but also increases quantitative loading capacity by >8-fold and quantified >25% more proteins; (iv) an optimized HCD-OT markedly outperforms HCD-IT when analyzing large cohorts with high loading amounts; (v) selective removal of hydrophobic/hydrophilic matrix components using a novel selective trapping/delivery approach enables reproducible, robust LC-MS analysis of >100 biological samples in a single set, eliminating batch effect; (vi) MS1 acquired at higher resolution (fwhm = 120 k) provides enhanced S/N and quantitative accuracy/precision for low-abundance species. We examined this pipeline by analyzing a 5 group, 20 samples biological benchmark sample set, and quantified 6273 unique proteins (≥2 peptides/protein) under stringent cutoffs without fractionation, 6234 (>99.4%) without missing data in any of the 20 samples. The strategy achieved high quantitative accuracy (3-6% media error), low intragroup variation (6-9% media intragroup CV) and low false-positive biomarker discovery rates (3-8%) across the five groups, with quantified protein abundances spanning >6.5 orders of magnitude. Finally, this strategy is straightforward, robust, and broadly applicable in pharmaceutical/biomedical investigations.

Tandem Analysis of Transcriptome and Proteome Changes after a Single Dose of Corticosteroid: A Systems Approach to Liver Function in Pharmacogenomics

Corticosteroids (CS) such as methylprednisolone (MPL) affect almost all liver functions through multiple mechanisms of action, and long-term use results in dysregulation causing diverse side effects. The complexity of involved molecular mechanisms necessitates a systems approach. Integration of information from the transcriptomic and proteomic responses has potential to provide deeper insights into CS actions. The present report describes the tandem analysis of rich time-series transcriptomic and proteomic data in rat liver after a single dose of MPL. Hierarchical clustering of the common genes represented in both mRNA and protein datasets displayed two dominant patterns. One of these patterns exhibited complementary mRNA and protein expression profiles indicating that MPL affected the regulation of these genes at the transcriptional level. Some of the classic pharmacodynamic markers for CS actions, including tyrosine aminotransferase (TAT), were among this group, together with genes encoding urea cycle enzymes and ribosomal proteins. The other pattern was rather unexpected. For this group of genes, MPL had distinctly observable effects at the protein expression level, although a change in the reverse direction occurred at the transcriptional level. These genes were functionally associated with metabolic processes that might be essential to elucidate side effects of MPL on liver, most importantly including modulation of oxidative stress, fatty acid oxidation, and bile acid biosynthesis. Furthermore, profiling of gene and protein expression data was also done independently of one another by a two-way sequential approach. Prominent temporal shifts in expression and relevant cellular functions were described together with the assessment of changes in the complementary side.

Optimization of Search Engines and Postprocessing Approaches to Maximize Peptide and Protein Identification for High-Resolution Mass Data

The two key steps for analyzing proteomic data generated by high-resolution MS are database searching and postprocessing. While the two steps are interrelated, studies on their combinatory effects and the optimization of these procedures have not been adequately conducted. Here, we investigated the performance of three popular search engines (SEQUEST, Mascot, and MS Amanda) in conjunction with five filtering approaches, including respective score-based filtering, a group-based approach, local false discovery rate (LFDR), PeptideProphet, and Percolator. A total of eight data sets from various proteomes (e.g., E. coli, yeast, and human) produced by various instruments with high-accuracy survey scan (MS1) and high- or low-accuracy fragment ion scan (MS2) (LTQ-Orbitrap, Orbitrap-Velos, Orbitrap-Elite, Q-Exactive, Orbitrap-Fusion, and Q-TOF) were analyzed. It was found combinations involving Percolator achieved markedly more peptide and protein identifications at the same FDR level than the other 12 combinations for all data sets. Among these, combinations of SEQUEST-Percolator and MS Amanda-Percolator provided slightly better performances for data sets with low-accuracy MS2 (ion trap or IT) and high accuracy MS2 (Orbitrap or TOF), respectively, than did other methods. For approaches without Percolator, SEQUEST-group performs the best for data sets with MS2 produced by collision-induced dissociation (CID) and IT analysis; Mascot-LFDR gives more identifications for data sets generated by higher-energy collisional dissociation (HCD) and analyzed in Orbitrap (HCD-OT) and in Orbitrap Fusion (HCD-IT); MS Amanda-Group excels for the Q-TOF data set and the Orbitrap Velos HCD-OT data set. Therefore, if Percolator was not used, a specific combination should be applied for each type of data set. Moreover, a higher percentage of multiple-peptide proteins and lower variation of protein spectral counts were observed when analyzing technical replicates using Percolator-associated combinations; therefore, Percolator enhanced the reliability for both identification and quantification. The analyses were performed using the specific programs embedded in Proteome Discoverer, Scaffold, and an in-house algorithm (BuildSummary). These results provide valuable guidelines for the optimal interpretation of proteomic results and the development of fit-for-purpose protocols under different situations.