Shichen Shen

Qualitative and quantitative characterization of protein biotherapeutics with liquid chromatography mass spectrometry

In the last decade, the advancement of liquid chromatography mass spectrometry (LC/MS) techniques has enabled their broad application in protein characterization, both quantitatively and qualitatively. Owing to certain important merits of LC/MS techniques (e.g., high selectivity, flexibility, and rapid method development), LC/MS assays are often deemed as preferable alternatives to conventional methods (e.g., ligand-binding assays) for the analysis of protein biotherapeutics. At the discovery and development stages, LC/MS is generally employed for two purposes absolute quantification of protein biotherapeutics in biological samples and qualitative characterization of proteins. For absolute quantification of a target protein in bio-matrices, recent work has led to improvements in the efficiency of LC/MS method development, sample treatment, enrichment and digestion, and high-performance low-flow-LC separation. These advances have enhanced analytical sensitivity, specificity, and robustness. As to qualitative analysis, a range of techniques have been developed to characterize intramolecular disulfide bonds, glycosylation, charge variants, primary sequence heterogeneity, and the drug-to-antibody ratio of antibody drug conjugate (ADC), which has enabled a refined ability to assess product quality. In this review, we will focus on the discussion of technical challenges and strategies of LC/MS-based quantification and characterization of biotherapeutics, with the emphasis on the analysis of antibody-based biotherapeutics such as monoclonal antibodies (mAbs) and ADCs.

Global analysis of cellular protein flux quantifies the selectivity of basal autophagy

Graphical abstract In Brief Macroautophagy is a catabolic pathway for the degradation of proteins in eukaryotic cells. Zhang et al. quantified the relative contribution of macroautophagy to basal proteome turnover by comparing protein half-lives between wild-type and autophagy-deficient fibroblasts. The data provide a global map of the selectivity of macroautophagy in human cells.

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.

Performance Investigation of Proteomic Identification by HCD/CID Fragmentations in Combination with High/Low-Resolution Detectors on a Tribrid, High-Field Orbitrap Instrument

The recently-introduced Orbitrap Fusion mass spectrometry permits various types of MS2 acquisition methods. To date, these different MS2 strategies and the optimal data interpretation approach for each have not been adequately evaluated. This study comprehensively investigated the four MS2 strategies: HCD-OT (higher-energy-collisional-dissociation with Orbitrap detection), HCD-IT (HCD with ion trap, IT), CID-IT (collision-induced-dissociation with IT) and CID-OT on Orbitrap Fusion. To achieve extensive comparison and identify the optimal data interpretation method for each technique, several search engines (SEQUEST and Mascot) and post-processing methods (score-based, PeptideProphet, and Percolator) were assessed for all techniques for the analysis of a human cell proteome. It was found that divergent conclusions could be made from the same dataset when different data interpretation approaches were used and therefore requiring a relatively fair comparison among techniques. Percolator was chosen for comparison of techniques because it performs the best among all search engines and MS2 strategies. For the analysis of human cell proteome using individual MS2 strategies, the highest number of identifications was achieved by HCD-OT, followed by HCD-IT and CID-IT. Based on these results, we concluded that a relatively fair platform for data interpretation is necessary to avoid divergent conclusions from the same dataset, and HCD-OT and HCD-IT may be preferable for protein/peptide identification using Orbitrap Fusion.

Time-resolved Analysis of Proteome Dynamics by Tandem Mass Tags and Stable Isotope Labeling in Cell Culture (TMT-SILAC) Hyperplexing

Recent advances in mass spectrometry have enabled system-wide analyses of protein turnover. By globally quantifying the kinetics of protein clearance and synthesis, these methodologies can provide important insights into the regulation of the proteome under varying cellular and environmental conditions. To facilitate such analyses, we have employed a methodology that combines metabolic isotopic labeling (Stable Isotope Labeling in Cell Culture - SILAC) with isobaric tagging (Tandem Mass Tags - TMT) for analysis of multiplexed samples. The fractional labeling of multiple time-points can be measured in a single mass spectrometry run, providing temporally resolved measurements of protein turnover kinetics. To demonstrate the feasibility of the approach, we simultaneously measured the kinetics of protein clearance and accumulation for more than 3000 proteins in dividing and quiescent human fibroblasts and verified the accuracy of the measurements by comparison to established non-multiplexed approaches. The results indicate that upon reaching quiescence, fibroblasts compensate for lack of cellular growth by globally downregulating protein synthesis and upregulating protein degradation. The described methodology significantly reduces the cost and complexity of temporally-resolved dynamic proteomic experiments and improves the precision of proteome-wide turnover data.

Ion-Current-Based Temporal Proteomic Profiling of Influenza-A-Virus-Infected Mouse Lungs Revealed Underlying Mechanisms of Altered Integrity of the Lung Microvascular Barrier

Investigation of influenza-A-virus (IAV)-infected lung proteomes will greatly promote our understanding on the virus-host crosstalk. Using a detergent-cocktail extraction and digestion procedure and a reproducible ion-current-based method, we performed the first comprehensive temporal analysis of mouse IAV infection. Mouse lung tissues at three time points post-inoculation were compared with controls (n = 4/group), and >1600 proteins were quantified without missing value in any animal. Significantly changed proteins were identified at 4 days (n = 144), 7 days (n = 695), and 10 days (n = 396) after infection, with low false altered protein rates (1.73-8.39%). Functional annotation revealed several key biological processes involved in the systemic host responses. Intriguingly, decreased levels of several cell junction proteins as well as increased levels of tissue metalloproteinase MMP9 were observed, reflecting the IAV-induced structural breakdown of lung epithelial barrier. Supporting evidence of MMP9 activation came from immunoassays examining the abundance and phosphorylation states of all MAPKs and several relevant molecules. Importantly, IAV-induced MMP gelatinase expression was suggested to be specific to MMP9, and p38 MAPK may contribute predominantly to MMP9 elevation. These findings help to resolve the long-lasting debate regarding the signaling pathways of IAV-induced MMP9 expression and shed light on the molecular mechanisms underlying pulmonary capillary-alveolar leak syndrome that can occur during influenza infection.

Sensitive, High-Throughput, and Robust Trapping-Micro-LC-MS Strategy for the Quantification of Biomarkers and Antibody Biotherapeutics

For LC-MS-based targeted quantification of biotherapeutics and biomarkers in clinical and pharmaceutical environments, high sensitivity, high throughput, and excellent robustness are all essential but remain challenging. For example, though nano-LC-MS has been employed to enhance analytical sensitivity, it falls short because of its low loading capacity, poor throughput, and low operational robustness. Furthermore, high chemical noise in protein bioanalysis typically limits the sensitivity. Here we describe a novel trapping-micro-LC-MS (T-μLC-MS) strategy for targeted protein bioanalysis, which achieves high sensitivity with exceptional robustness and high throughput. A rapid, high-capacity trapping of biological samples is followed by μLC-MS analysis; dynamic sample trapping and cleanup are performed using pH, column chemistry, and fluid mechanics separate from the μLC-MS analysis, enabling orthogonality, which contributes to the reduction of chemical noise and thus results in improved sensitivity. Typically, the selective-trapping and -delivery approach strategically removes >85% of the matrix peptides and detrimental components, markedly enhancing sensitivity, throughput, and operational robustness, and narrow-window-isolation selected-reaction monitoring further improves the signal-to-noise ratio. In addition, unique LC-hardware setups and flow approaches eliminate gradient shock and achieve effective peak compression, enabling highly sensitive analyses of plasma or tissue samples without band broadening. In this study, the quantification of 10 biotherapeutics and biomarkers in plasma and tissues was employed for method development. As observed, a significant sensitivity gain (up to 25-fold) compared with that of conventional LC-MS was achieved, although the average run time was only 8 min/sample. No appreciable peak deterioration or loss of sensitivity was observed after >1500 injections of tissue and plasma samples. The developed method enabled, for the first time, ultrasensitive LC-MS quantification of low levels of a monoclonal antibody and antigen in a tumor and cardiac troponin I in plasma after brief cardiac ischemia. This strategy is valuable when highly sensitive protein quantification in large sample sets is required, as is often the case in typical biomarker validation and pharmaceutical investigations of antibody therapeutics.

Comparative Proteomic Analysis of the Mitochondria-associated ER Membrane (MAM) in a Long-term Type 2 Diabetic Rodent Model

The mitochondria-associated ER membrane (MAM) plays a critical role in cellular energetics and calcium homeostasis; however, how MAM is affected under diabetic condition remains elusive. This study presented a comprehensive proteome profiling of isolated brain MAM from long-term type 2 diabetic mice vs. non-diabetic controls. MAM protein was extracted efficiently by a surfactant-aided precipitation/on-pellet digestion (SOD) method, and MAM proteome was quantified by an ion-current-based MS1 method combined with nanoLC-MS/MS. A total of 1,313 non-redundant proteins of MAM were identified, among which 144 proteins were found significantly altered by diabetes. In-depth IPA analysis identified multiple disease-relevant signaling pathways associated with the MAM proteome changes in diabetes, most significantly the unfolded protein response (UPR), p53, hypoxia-related transcription factors, and methyl CpG binding protein 2. Using immunofluorescence labeling we confirmed the activation of three UPR branches and increased ERp29 and calreticulin in diabetic retinas. Moreover, we found GRP75, a key MAM tethering protein, was drastically reduced by long-term diabetes. In vitro, acute high glucose treatment reduces ER-mitochondrial contact in retinal endothelial cells. This study provides first insight into the significant alterations in MAM proteome associated with activation of the UPR in diabetes, which may serve as novel benchmarks for the future studies of diabetic complications.

Large-Scale, Ion-Current-Based Proteomic Investigation of the Rat Striatal Proteome in a Model of Short- and Long-Term Cocaine Withdrawal

Given the tremendous detriments of cocaine dependence, effective diagnosis and patient stratification are critical for successful intervention yet difficult to achieve due to the largely unknown molecular mechanisms involved. To obtain new insights into cocaine dependence and withdrawal, we employed a reproducible, reliable, and large-scale proteomics approach to investigate the striatal proteomes of rats (n = 40, 10 per group) subjected to chronic cocaine exposure, followed by either short- (WD1) or long- (WD22) term withdrawal. By implementing a surfactant-aided precipitation/on-pellet digestion procedure, a reproducible and sensitive nanoLC-Orbitrap MS analysis, and an optimized ion-current-based MS1 quantification pipeline, >2000 nonredundant proteins were quantified confidently without missing data in any replicate. Although cocaine was cleared from the body, 129/37 altered proteins were observed in WD1/WD22 that are implicated in several biological processes related closely to drug-induced neuroplasticity. Although many of these changes recapitulate the findings from independent studies reported over the last two decades, some novel insights were obtained and further validated by immunoassays. For example, significantly elevated striatal protein kinase C activity persisted over the 22 day cocaine withdrawal. Cofilin-1 activity was up-regulated in WD1 and down-regulated in WD22. These discoveries suggest potentially distinct structural plasticity after short- and long-term cocaine withdrawal. In addition, this study provides compelling evidence that blood vessel narrowing, a long-known effect of cocaine use, occurred after long-term but not short-term withdrawal. In summary, this work developed a well-optimized paradigm for ion-current-based quantitative proteomics in brain tissues and obtained novel insights into molecular alterations in the striatum following cocaine exposure and withdrawal.

Quantitative proteomic profiling of paired cancerous and normal colon epithelial cells isolated freshly from colorectal cancer patients

The heterogeneous structure in tumor tissues from colorectal cancer (CRC) patients excludes an informative comparison between tumors and adjacent normal tissues. Here, we develop and apply a strategy to compare paired cancerous (CEC) versus normal (NEC) epithelial cells enriched from patients and discover potential biomarkers and therapeutic targets for CRC.