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Capillary electrophoresis (CE) coupled with mass spectrometry (MS) is a promising alternative to conventional liquid chromatography (LC) MS in chemical and biological sample analysis due to its high resolving power and fast separation speed. Reproducibility and ruggedness problems, suffered to a certain degree by almost all the CE-MS interfaces, limit its broad applications. We present the development of a new sheathless CE-MS interface aiming at overcoming these problems and pushing CE-MS suitable to routine sample analysis with high sensitivity. A systematic evaluation of the new interface was performed using a hybrid capillary isotachophoresis (CITP) and capillary zone electrophoresis (CZE) separation coupled with electrospray ionization (ESI) MS for its achievable sensitivity and reproducibility in sample quantification.

Mass spectrometry (MS) based proteomics has increasingly been considered as a pivotal technology for biological and biomedical research. Verification studies using targeted proteomics are often required to provide high selectivity, accuracy, and sample throughput while maintaining high sensitivity. Selected reaction monitoring (SRM) has widely been used as a targeted MS technique with high sensitivity and selectivity. With recent advances in MS instrumentation especially the Orbitrap based hybrid mass spectrometers, two novel approaches, namely parallel reaction monitoring (PRM) and data independent acquisition (DIA), were also introduced for targeted proteomics analysis. Herein, we systematically assessed the analytical characteristics of SRM-, PRM-, and DIA-based targeted quantification and demonstrated the complementarity of these techniques for fit-for-purpose applications. Twenty peptides were selected for the initial evaluation of the 3 techniques. The heavy stable isotope-labeled peptides were synthesized and spiked into the samples as the internal standard. SRM was performed on the Thermo TSQ Vantage triple quadrupole instrument while PRM and DIA were carried out on the Thermo Q Exactive HF instrument with the same LC system and setup. Each transition and its corresponding collision energy were optimized for SRM while HCD of target precursor ions was acquired with an isolation window of 2 and 5 m/z for PRM and DIA, respectively. The performance of the 3 techniques was further evaluated using 133 and 110 peptides associated with EGFR pathway and prostate cancer, respectively. Data were analyzed using Skyline. The reverse response curve was created for the 20 peptides in HMEC cell digest to characterize the linear dynamic range and lower limit of quantification (LLOQ) of the 3 techniques. Overall, all 20 target peptides were quantified by SRM while 18 and 15 peptides were quantified by PRM and DIA, respectively; 6 peptides showed better LLOQ values by SRM over PRM and DIA while 3 peptides showed better LLOQ values by PRM over SRM and DIA. SRM also exhibited slightly better reproducibility. An averaged CV values were 8.3, 10.0, and 12.2 by SRM, PRM, and DIA, respectively. One of the challenges in SRM is potential interferences in complex samples due to the low mass resolution and accuracy achievable on the triple quadrupole instrument. PRM and DIA data acquired on high-resolution Q Exactive instrument are more flexible for minimizing interferences by requiring higher mass accuracy and post-acquisition transition refinement and peak integration, contributing to better selectivity and quantification accuracy for 8 of the target peptides. To further test the potential impact of multiplexing levels on the analytical performance, SRM and PRM were also performed for 110 peptides associated with prostate cancer. Two injection times (60 and 150 ms) were used for PRM. SRM and PRM quantified 44 and 48 peptides, respectively. Both ion injection time settings in PRM showed the same level of peptide detection and high correlation with SRM (R2>0.98); however the use of longer injection time resulted in better MS response and reproducibility. We are currently applying the 3 techniques to quantify 133 EGFR pathway peptides. Front-end enrichment techniques will also be tested for their impact on the sensitivity and selectivity of the 3 targeted quantification methods.

Mass spectrometry (MS) based proteomics has increasingly been considered as a pivotal technology for biological and biomedical research. Verification studies using targeted proteomics are often required to provide high selectivity, accuracy, and sample throughput while maintaining high sensitivity. Selected reaction monitoring (SRM) has widely been used as a targeted MS technique with high sensitivity and selectivity. With recent advances in MS instrumentation especially the Orbitrap based hybrid mass spectrometers, two novel approaches, namely parallel reaction monitoring (PRM) and data independent acquisition (DIA), were also introduced for targeted proteomics analysis. Herein, we systematically assessed the analytical characteristics of SRM-, PRM-, and DIA-based targeted quantification and demonstrated the complementarity of these techniques for fit-for-purpose applications. Twenty peptides were selected for the initial evaluation of the 3 techniques. The heavy stable isotope-labeled peptides were synthesized and spiked into the samples as the internal standard. SRM was performed on the Thermo TSQ Vantage triple quadrupole instrument while PRM and DIA were carried out on the Thermo Q Exactive HF instrument with the same LC system and setup. Each transition and its corresponding collision energy were optimized for SRM while HCD of target precursor ions was acquired with an isolation window of 2 and 5 m/z for PRM and DIA, respectively. The performance of the 3 techniques was further evaluated using 133 and 110 peptides associated with EGFR pathway and prostate cancer, respectively. Data were analyzed using Skyline. The reverse response curve was created for the 20 peptides in HMEC cell digest to characterize the linear dynamic range and lower limit of quantification (LLOQ) of the 3 techniques. Overall, all 20 target peptides were quantified by SRM while 18 and 15 peptides were quantified by PRM and DIA, respectively; 6 peptides showed better LLOQ values by SRM over PRM and DIA while 3 peptides showed better LLOQ values by PRM over SRM and DIA. SRM also exhibited slightly better reproducibility. An averaged CV values were 8.3, 10.0, and 12.2 by SRM, PRM, and DIA, respectively. One of the challenges in SRM is potential interferences in complex samples due to the low mass resolution and accuracy achievable on the triple quadrupole instrument. PRM and DIA data acquired on high-resolution Q Exactive instrument are more flexible for minimizing interferences by requiring higher mass accuracy and post-acquisition transition refinement and peak integration, contributing to better selectivity and quantification accuracy for 8 of the target peptides. To further test the potential impact of multiplexing levels on the analytical performance, SRM and PRM were also performed for 110 peptides associated with prostate cancer. Two injection times (60 and 150 ms) were used for PRM. SRM and PRM quantified 44 and 48 peptides, respectively. Both ion injection time settings in PRM showed the same level of peptide detection and high correlation with SRM (R2>0.98); however the use of longer injection time resulted in better MS response and reproducibility. We are currently applying the 3 techniques to quantify 133 EGFR pathway peptides. Front-end enrichment techniques will also be tested for their impact on the sensitivity and selectivity of the 3 targeted quantification methods.

Targeted MS-based proteomics such as selected reaction monitoring (SRM) provides an attractive alternatives to affinity reagent based methods (e.g., ELISA) for rapid, sensitive, specific, and multiplexed verification of genomics biomarker candidates at the protein level. In this study, 52 biomarker candidates for prostate cancer were selected from existing genomics data sets and validated cancer drivers, and analyzed in tumor and control tissue samples using the highly sensitive PRISM (high-pressure, high-resolution separations coupled with intelligent selection and multiplexing)-SRM approach to identify a panel of proteins with the potential to discriminate between aggressive and indolent forms of prostate cancer and predict prostate cancer progression. PRISM-SRM assays have been developed for the 52 prostate cancer biomarker candidates. Two sets of tissue samples were analyzed using PRISM-SRM: 1) 10 high Gleason-score (7-9) primary prostate tumors and 10 benign prostatic hyperplasia (BPH) tissues (OCT-embedded specimens); and 2) 10 primary tumors from patients showing metastatic progression, 10 primary tumors from patients who showed biochemical recurrence (BCR), and 10 primary tumors from patients with no BCR or metastatic progression after more than ten years of follow-up after radical prostatectomy (FFPE whole mount prostate specimens). After protein extraction, reduction, alkylation and tryptic digestion, peptide mixtures with spike-in heavy standards were analyzed. All SRM data were generated on ThermoScientific TSQ Vantage QQQ mass spectrometer and analyzed by Xcalibur and Skyline. PRISM-SRM analyses of all the patient tissue samples enabled the detection of 48 out of 52 biomarker candidates, suggesting extremely low level of expression of the remaining 4 genes in the prostate tissues (HXC6, OSTP, TWST1, and ERG8); in comparison regular LC-SRM can only detect 21 of these candidates at protein level. In the 10 high Gleason-scores tumors and 10 BPH controls, a total of 42 proteins were quantified and compared, among which 13 proteins were found differentially abundant in tumors versus controls, with P 0.7. The finding that these kinases and proteases were overexpressed in prostate cancer was consistent with previous genetic studies. Although PSA and ERG had p values slightly greater than 0.05, they also showed up-regulated protein expression levels in tumors (2.2- and 4-fold, respectively). PRISM-SRM analysis of the 30 FFPE tissue samples quantified a total of 42 proteins. The ERG status of the index tumor (which was dissected for protein extraction), determined by immunohistochemistry on the whole mounted prostate sections, correlated very well with the protein concentrations measured by PRISM-SRM, demonstrating the sensitivity and reliability of these PRISM-SRM assays. WE found 3 proteins discriminating between “metastatic progression” and “no progression” tumors, 1 protein discriminated between BCR and “no progression” tumors, and 4 proteins discriminated between metastatic progression and BCR tumors (P

Antibody-based flow cytometry and mass cytometry are predominant technologies for targeted proteomics analysis of single cells. However, they share common shortcomings with other antibody-based methods (e.g., low-multiplex, the need of high-quality antibodies, and unavailability of antibodies for new proteins). Furthermore, they lack quantitation accuracy to provide accurate protein concentrations. Mass spectrometry (MS)-based targeted proteomics has emerged as a promising alternative for antibody-free precise high-multiplex quantification of target proteins. However, it does not meet the merit for analysis of single cells due to insufficient sensitivity. To tackle this issue, we recently developed a new targeted MS approach that couples carrier-assisted sample preparation to a highly sensitive targeted MS platform for enabling proteomics analysis of single cells. In complex biological samples low abundant proteins can be reliably detected without loss because highly abundant proteins severe as an effective carrier to prevent their loss. With this observation, we recently developed a simple preparation method with using exogenous BSA protein as a carrier for lossless processing of single cells. A highly sensitive targeted MS platform PRISM-SRM/PRM (high-pressure, high-resolution separations with intelligent selection and multiplexing coupled to selected/parallel reaction monitoring) was then used for absolute quantification of key EGFR pathway proteins in 1-100 HMEC cells. The Waters nanoACQUITY UPLC system and the Thermo Scientific TSQ Vantage or Q Exactive MS instrument were used for LC separation and targeted quantification, respectively. The Skyline software was employed for analysis of SRM/PRM data.Recently PRISM-SRM was demonstrated for enabling highly sensitive quantification of target proteins at ≤100 copies per human cell when starting with only ~25 µg of cell lysate digests, which is equal to ~250,000 human cells. However, in the real clinical applications the available sample amount could be much smaller (e.g., 1-10 circulating tumor cells) and sample loss is almost inevitable for current targeted MS analysis. With the introduction of exogenous proteins as a carrier to prevent sample loss we refined our PRISM termed carrier-assisted PRISM (i.e., cPRISM) for enabling targeted quantification of proteins in single cells by coupling with SRM/PRM. In our proof-of-concept experiment BSA protein was selected as a carrier for assisting processing of a small number of cells. 1-100 isolated HMEC cells were collected into 50 µg of BSA carrier-containing tubes to prevent cell adhesion to the tube wall. When mixed with BSA carrier, the small number of cells were processed as easily as bulk cells with minimal sample loss. The constant ‘unbiased’ peptide recovery was observed across all the samples with confident detection of multiple endogenous peptides with different hydrophobicity at 1-5 HMEC cells as well as the linear response curves of target proteins from 1 to 100 cells. This result has shown the carrier-assisted method can be used to effectively process single cells for highly sensitive PRISM-SRM quantification. Furthermore, detection of SFADINLYR derived from NRAS in small numbers of HMEC cells (~80,000 NRAS molecules per HMEC cell from bulk cells) suggested that our current targeted MS platforms can provided ~100 zmol level of sensitivity. Currently we are working on further improving cPRISM-SRM performance in sensitivity, throughput and robustness. We envision that this new targeted MS approach will have broad utilities in biomedical research (e.g., single cells and clinical applications with extremely small sample amounts).