Native N-glycome profiling of single cells and ng-level blood isolates using label-free capillary electrophoresis-mass spectrometry

The development of reliable single-cell dispensers and substantial sensitivity improvement in mass spectrometry made proteomic profiling of individual cells achievable. Yet, there are no established methods for single-cell glycome analysis due to the inability to amplify glycans and sample losses associated with sample processing and glycan labeling. In this work, we present an integrated platform coupling online in-capillary sample processing with high-sensitivity label-free capillary electrophoresis-mass spectrometry for N-glycan profiling of single mammalian cells. Direct and unbiased quantitative characterization of single-cell surface N-glycomes are demonstrated for HeLa and U87 cells, with the detection of up to 100 N-glycans per single cell. Interestingly, N-glycome alterations are unequivocally detected at the single-cell level in HeLa and U87 cells stimulated with lipopolysaccharide. The developed workflow is also applied to the profiling of ng-level amounts (5-500 ng) of blood-derived protein, extracellular vesicle, and total plasma isolates, resulting in over 170, 220, and 370 quantitated N-glycans, respectively.

Improved Data Acquisition Settings on Q Exactive HF-X and Fusion Lumos Tribrid Orbitrap-Based Mass Spectrometers for Proteomic Analysis of Limited Samples

Deep proteomic profiling of complex biological and medical samples available at low nanogram and subnanogram levels is still challenging. Thorough optimization of settings, parameters, and conditions in nanoflow liquid chromatography-tandem mass spectrometry (MS)-based proteomic profiling is crucial for generating informative data using amount-limited samples. This study demonstrates that by adjusting selected instrument parameters, e.g., ion injection time, automated gain control, and minimally altering the conditions for resuspending or storing the sample in solvents of different compositions, up to 15-fold more thorough proteomic profiling can be achieved compared to conventionally used settings. More specifically, the analysis of 1 ng of the HeLa protein digest standard by Q Exactive HF-X Hybrid Quadrupole-Orbitrap and Orbitrap Fusion Lumos Tribrid mass spectrometers yielded an increase from 1758 to 5477 (3-fold) and 281 to 4276 (15-fold) peptides, respectively, demonstrating that higher protein identification results can be obtained using the optimized methods. While the instruments applied in this study do not belong to the latest generation of mass spectrometers, they are broadly used worldwide, which makes the guidelines for improving performance desirable to a wide range of proteomics practitioners.

Open-tubular trap columns: towards simple and robust liquid chromatography separations for single-cell proteomics

Nanoflow liquid chromatography-mass spectrometry is key to enabling in-depth proteome profiling of trace samples, including single cells, but these separations can lack robustness due to the use of narrow-bore columns that are susceptible to clogging. In the case of single-cell proteomics, offline cleanup steps are generally omitted to avoid losses to additional surfaces, and online solid-phase extraction/trap columns frequently provide the only opportunity to remove salts and insoluble debris before the sample is introduced to the analytical column. Trap columns are traditionally short, packed columns used to load and concentrate analytes at flow rates greater than those employed in analytical columns, and since these first encounter the uncleaned sample mixture, trap columns are also susceptible to clogging. We hypothesized that clogging could be avoided by using large-bore porous layer open tubular trap columns (PLOTrap). The low back pressure ensured that the PLOTraps could also serve as the sample loop, thus allowing sample cleanup and injection with a single 6-port valve. We found that PLOTraps could effectively remove debris to avoid column clogging. We also evaluated multiple stationary phases and PLOTrap diameters to optimize performance in terms of peak widths and sample loading capacities. Optimized PLOTraps were compared to conventional packed trap columns operated in forward and backflush modes, and were found to have similar chromatographic performance of backflushed traps while providing improved debris removal for robust analysis of trace samples.

Multimode chromatography-based techniques for high purity isolation of extracellular vesicles from human blood plasma

Extracellular vesicles (EVs) play a pivotal role in various biological pathways, such as immune responses and the progression of diseases, including cancer. However, it is challenging to isolate EVs at high purity from blood plasma and other biofluids due to their low abundance compared to more predominant biomolecular species such as lipoprotein particles and free protein complexes. Ultracentrifugation-based EV isolation, the current gold standard technique, cannot overcome this challenge due to the similar biophysical characteristics of such species. We developed several novel approaches to enrich EVs from plasma while depleting contaminating molecular species using multimode chromatography-based strategies. On average, we identified 716 ± 68 and 1054 ± 35 protein groups in EV isolates from 100 µL of plasma using multimode chromatography- and ultracentrifugation-based techniques, respectively. The developed methods resulted in similar EV isolates purity, providing significant advantages in simplicity, throughput, scalability, and applicability for various downstream analytical and potential clinical applications.

Native Capillary Electrophoresis-Mass Spectrometry of Near 1 MDa Non-Covalent GroEL/GroES/Substrate Protein Complexes

Protein complexes are essential for proteins' folding and biological function. Currently, native analysis of large multimeric protein complexes remains challenging. Structural biology techniques are time-consuming and often cannot monitor the proteins' dynamics in solution. Here, a capillary electrophoresis-mass spectrometry (CE-MS) method is reported to characterize, under near-physiological conditions, the conformational rearrangements of ∽1 MDa GroEL upon complexation with binding partners involved in a protein folding cycle. The developed CE-MS method is fast (30 min per run), highly sensitive (low-amol level), and requires ∽10 000-fold fewer samples compared to biochemical/biophysical techniques. The method successfully separates GroEL14 (∽800 kDa), GroEL7 (∽400 kDa), GroES7 (∽73 kDa), and NanA4 (∽130 kDa) oligomers. The non-covalent binding of natural substrate proteins with GroEL14 can be detected and quantified. The technique allows monitoring of GroEL14 conformational changes upon complexation with (ATPγS)4-14 and GroES7 (∽876 kDa). Native CE-pseudo-MS3 analyses of wild-type (WT) GroEL and two GroEL mutants result in up to 60% sequence coverage and highlight subtle structural differences between WT and mutated GroEL. The presented results demonstrate the superior CE-MS performance for multimeric complexes' characterization versus direct infusion ESI-MS. This study shows the CE-MS potential to provide information on binding stoichiometry and kinetics for various protein complexes.

Experimental and data analysis advances in thermal proteome profiling

Method development for mass spectrometry (MS)-based thermal shift proteomic assays have advanced to probe small molecules with known and unknown protein-ligand interaction mechanisms and specificity, which is predominantly used in characterization of drug-protein interactions. In the discovery of target and off-target protein-ligand interactions, a thorough investigation of method development and their impact on the sensitivity and accuracy of protein-small molecule and protein-protein interactions is warranted. In this review, we discuss areas of improvement at each stage of thermal proteome profiling data analysis that includes processing of MS-based data, method development, and their effect on the overall quality of thermal proteome profiles. We also overview the optimization of experimental strategies and prioritization of an increased number of independent biological replicates over the number of evaluated temperatures.

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly.

Characterization of charge variants, including post-translational modifications and proteoforms, of bispecific antigen-binding protein by cation-exchange chromatography coupled to native mass spectrometry

Charge variant characterization of biologics is critical to ensure that product meets the required quality and regulatory requirements to ensure safety and efficacy of the biotherapeutic. Charge variants arise from post-translation modifications (PTMs) during upstream processing and due to enzymatic and non-enzymatic chemical reactions that occur during downstream processing and storage. Some of these modifications may impact therapeutic potency, efficacy, or immunogenicity of a biotherapeutic. The traditional workflow for characterizing charge variants that involves fraction enrichment is time-consuming and labor-intensive. This approach can be especially challenging if the product is manufactured at low concentrations (e.g., ≤2 mg/mL). Recent advances in pH-based elution for ion-exchange chromatography utilizing volatile buffers have enabled rapid native mass-spectrometry-based identification of PTMs and proteoforms associated with protein therapeutics. In this study, we develop a novel workflow to rapidly and unambiguously characterize modifications associated with a new class of biotherapeutics known as bispecific antigen-binding protein (BsABP), including low-level modifications. A cation-exchange separation was optimized using volatile buffers to provide online hyphenation for native mass spectrometry to profile modifications and proteoforms present at the native level of a biotherapeutic, such as deamidation, O-glycosylation, amino acid substitution, N-linked glycosylation and oxidation. Furthermore, a limited proteolysis method was developed to specifically inform about modifications in the different domains of the bispecific antibody. Using this approach, we could efficiently identify PTMs in unstressed, thermally and photo-stressed samples, and provide information about the impact of downstream purification in clearing out modified BsABP species. Furthermore, peptide mapping was performed to identify and confirm modifications at the amino acid residue level. The developed workflow is less time-consumable and reduces sample processing- and analysis-related artifacts compared to traditional approaches.

Human red blood cells release microvesicles with distinct sizes and protein composition that alter neutrophil phagocytosis

Extracellular vesicles (EVs) are membrane-bound structures released by cells and tissues into biofluids, involved in cell-cell communication. In humans, circulating red blood cells (RBCs), represent the most common cell-type in the body, generating daily large numbers of microvesicles. In vitro, RBC vesiculation can be mimicked by stimulating RBCs with calcium ionophores, such as ionomycin and A23187. The fate of microvesicles released during in vivo aging of RBCs and their interactions with circulating cells is hitherto unknown. Using SEC plus DEG isolation methods, we have found that human RBCs generate microvesicles with two distinct sizes, densities, and protein composition, identified by flow cytometry, and MRPS, and further validated by immune TEM. Furthermore, proteomic analysis revealed that RBC-derived microvesicles (RBC-MVs) are enriched in proteins with important functions in ion channel regulation, calcium homeostasis, and vesicular transport, such as of sorcin, stomatin, annexin A7, and RAB proteins. Cryo-electron microscopy identified two separate pathways of RBC-MV-neutrophil interaction, direct fusion with the plasma membrane and internalization, respectively. Functionally, RBC-MVs decrease neutrophil ability to phagocytose E. coli but do not affect their survival at 24 hrs. This work brings new insights regarding the complexity of the RBC-MVs biogenesis, as well as their possible role in circulation.

Ultralow flow liquid chromatography and related approaches: A focus on recent bioanalytical applications

Ultralow flow LC employs ultra-narrow bore columns and mid-range pL/min to low nL/min flow rates (i.e., ≤20 nL/min). The separation columns that are used under these conditions are typically 2-30 μm in inner diameter. Ultralow flow LC systems allow for exceptionally high sensitivity and frequently high resolution. There has been an increasing interest in the analysis of scarce biological samples, for example, circulating tumor cells, extracellular vesicles, organelles, and single cells, and ultralow flow LC was efficiently applied to such samples. Hence, advances towards dedicated ultralow flow LC instrumentation, technical approaches, and higher throughput (e.g., tens-to-hundreds of single cells analyzed per day) were recently made. Here, we review the types of ultralow flow LC technology, followed by a discussion of selected representative ultralow flow LC applications, focusing on the progress made in bioanalysis of amount-limited samples during the last 10 years. We also discuss several recently reported high-sensitivity applications utilizing flow rates up to 100 nL/min, which are below commonly used nanoLC flow rates. Finally, we discuss the path forward for future developments of ultralow flow LC.

Statistical Detection of Differentially Abundant Proteins in Experiments with Repeated Measures Designs and Isobaric Labeling

Repeated measures experimental designs, which quantify proteins in biological subjects repeatedly over multiple experimental conditions or times, are commonly used in mass spectrometry-based proteomics. Such designs distinguish the biological variation within and between the subjects and increase the statistical power of detecting within-subject changes in protein abundance. Meanwhile, proteomics experiments increasingly incorporate tandem mass tag (TMT) labeling, a multiplexing strategy that gains both relative protein quantification accuracy and sample throughput. However, combining repeated measures and TMT multiplexing in a large-scale investigation presents statistical challenges due to unique interplays of between-mixture, within-mixture, between-subject, and within-subject variation. This manuscript proposes a family of linear mixed-effects models for differential analysis of proteomics experiments with repeated measures and TMT multiplexing. These models decompose the variation in the data into the contributions from its sources as appropriate for the specifics of each experiment, enable statistical inference of differential protein abundance, and recognize a difference in the uncertainty of between-subject versus within-subject comparisons. The proposed family of models is implemented in the R/Bioconductor package MSstatsTMT v2.2.0. Evaluations of four simulated datasets and four investigations answering diverse biological questions demonstrated the value of this approach as compared to the existing general-purpose approaches and implementations.

Single-cell omic molecular profiling using capillary electrophoresis-mass spectrometry

Tissues and other cell populations are highly heterogeneous at the cellular level, owing to differences in expression and modifications of proteins, polynucleotides, metabolites, and lipids. The ability to assess this heterogeneity is crucial in understanding numerous biological phenomena, including various pathologies. Traditional analyses apply bulk-cell sampling, which masks the potentially subtle differences between cells that can be important in understanding of biological processes. These limitations due to cell heterogeneity inspired significant efforts and interest toward the analysis of smaller sample sizes, down to the level of individual cells. Among the emerging techniques, the unique capabilities of capillary electrophoresis coupled with mass spectrometry (CE-MS) made it a prominent technique for proteomics and metabolomics analysis at the single-cell level. In this review, we focus on the application of CE-MS in the proteomic and metabolomic profiling of single cells and highlight the recent advances in sample preparation, separation, MS acquisition, and data analysis.

Experimental strategies to improve drug-target identification in mass spectrometry-based thermal stability assays

Mass spectrometry (MS)-based thermal stability assays have recently emerged as one of the most promising solutions for the identification of protein-ligand interactions. Here, we have investigated eight combinations of several recently introduced MS-based advancements, including the Phase-Constrained Spectral Deconvolution Method, Field Asymmetric Ion Mobility Spectrometry, and the implementation of a carrier sample as improved MS-based acquisition approaches for thermal stability assays (iMAATSA). We used intact Jurkat cells treated with a commercially available MEK inhibitor, followed by heat treatment, to prepare a set of unfractionated isobarically-labeled proof-of-concept samples to compare the performance of eight different iMAATSAs. Finally, the best-performing iMAATSA was compared to a conventional approach and evaluated in a fractionation experiment. Improvements of up to 82% and 86% were demonstrated in protein identifications and high-quality melting curves, respectively, over the conventional approach in the proof-of-concept study, while an approximately 12% improvement in melting curve comparisons was achieved in the fractionation experiment.

Highly-sensitive label-free deep profiling of N-glycans released from biomedically-relevant samples

Alterations of protein glycosylation can serve as sensitive and specific disease biomarkers. Labeling procedures for improved separation and detectability of oligosaccharides have several drawbacks, including incomplete derivatization, side-products, noticeable desialylation/defucosylation, sample loss, and interference with downstream analyses. Here, we develop a label-free workflow based on high sensitivity capillary zone electrophoresis-mass spectrometry (CZE-MS) for profiling of native underivatized released N-glycans. Our workflow provides a >45-fold increase in signal intensity compared to the conventional CZE-MS approaches used for N-glycan analysis. Qualitative and quantitative N-glycan profiling of purified human serum IgG, bovine serum fetuin, bovine pancreas ribonuclease B, blood-derived extracellular vesicle isolates, and total plasma results in the detection of >250, >400, >150, >310, and >520 N-glycans, respectively, using injected amounts equivalent to <25 ng of model protein and nL-levels of plasma-derived samples. Compared to reported results for biological samples of similar amounts and complexity, the number of identified N-glycans is increased up to ~15-fold, enabling highly sensitive analysis of sample amounts as low as sub-0.2 nL of plasma volume equivalents. Furthermore, highly sialylated N-glycans are identified and structurally characterized, and untreated sialic acid-linkage isomers are resolved in a single CZE-MS analysis.

Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments

Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at https://single-cell.net/guidelines .

Characterization of bispecific antigen-binding biotherapeutic fragmentation sites using microfluidic capillary electrophoresis coupled to mass spectrometry (mCZE-MS)

Fragmentation of therapeutic proteins is a potential critical quality attribute (CQA) that can occur in vivo or during manufacturing or storage due to enzymatic and non-enzymatic degradation pathways, such as hydrolysis, peroxide mediation, and acid/metal catalysis. Characterization of the fragmentation pattern of a therapeutic protein is traditionally accomplished using capillary gel electrophoresis with UV detection under both non-reducing and reducing conditions (nrCGE and rCGE). However, such methods are incompatible with direct coupling to mass spectrometry (MS) due to the use of anionic surfactants, e.g., sodium dodecyl sulfate (SDS). Here, we present a novel method to characterize size-based fragmentation variants of a new biotherapeutic kind using microfluidic ZipChip® capillary zone electrophoresis (mCZE) system interfaced with mass spectrometry (MS) to determine the molecular masses of fragments. A new modality of immuno-oncology therapy, bispecific antigen-binding biotherapeutic, was chosen to investigate its fragmentation pattern using mCZE-MS for the first time, according to our knowledge. Bispecific antigen-binding biotherapeutic samples from different stages of downstream column purification and forced degradation conditions were analyzed. The results were cross-validated with denaturing size-exclusion chromatography-mass spectrometry and conventional rSDS-CGE. In this study, we demonstrated that mCZE-MS could separate and characterize 12-40 kDa bispecific antigen-binding biotherapeutic fragments rapidly (within ≤12 minutes), with higher resolution and better sensitivity than traditional LC-MS methods.

On-capillary Cell Lysis Enables Top-down Proteomic Analysis of Single Mammalian Cells by CE-MS/MS

Proteomic analysis of limited samples and single cells requires specialized methods that prioritize high sensitivity and minimize sample loss. Consequently, sample preparation is one of the most important steps in limited sample analysis workflows to prevent sample loss. In this work, we have eliminated sample handling and transfer steps by processing intact cells directly in the separation capillary, online with capillary electrophoresis coupled to tandem mass spectrometry (CE-MS/MS) for top-down proteomic (TDP) analysis of low numbers of mammalian cancer cells (<10) and single cells. We assessed spray voltage injection of intact cells from a droplet of cell suspension (∼1000 cells) and demonstrated 0-9 intact cells injected with a dependency on the duration of spray voltage application. Spray voltage applied for 2 min injected an average of 7 ± 2 cells and resulted in 33-57 protein and 40-88 proteoform identifications (N = 4). To analyze single cells, manual cell loading by hydrodynamic pressure was used. Replicates of single HeLa cells (N = 4) lysed on the capillary and analyzed by CE-MS/MS demonstrated a range of 17-40 proteins and 23-50 proteoforms identified. An additional cell line, THP-1, was analyzed at the single-cell level, and proteoform abundances were compared to show the capabilities of single-cell TDP (SC-TDP) for assessing cellular heterogeneity. This study demonstrates the initial application of TDP in single-cell proteome-level profiling. These results represent the highest reported identifications from TDP analysis of a single HeLa cell and prove the tremendous potential for CE-MS/MS on-capillary sample processing for high sensitivity analysis of single cells and limited samples.

Coupling High-Field Asymmetric Ion Mobility Spectrometry with Capillary Electrophoresis-Electrospray Ionization-Tandem Mass Spectrometry Improves Protein Identifications in Bottom-Up Proteomic Analysis of Low Nanogram Samples

In this work, we pioneered the assessment of coupling high-field asymmetric waveform ion mobility spectrometry (FAIMS) with ultrasensitive capillary electrophoresis hyphenated with tandem mass spectrometry (CE-MS/MS) to achieve deeper proteome coverage of low nanogram amounts of digested cell lysates. An internal stepping strategy using three or four compensation voltages per analytical run with varied cycle times was tested to determine optimal FAIMS settings and MS parameters for the CE-FAIMS-MS/MS method. The optimized method applied to bottom-up proteomic analysis of 1 ng of HeLa protein digest standard identified 1314 ± 30 proteins, 4829 ± 200 peptide groups, and 7577 ± 163 peptide spectrum matches (PSMs) corresponding to a 16, 25, and 22% increase, respectively, over CE-MS/MS alone, without FAIMS. Furthermore, the percentage of acquired MS/MS spectra that resulted in PSMs increased nearly 2-fold with CE-FAIMS-MS/MS. Label-free quantitation of proteins and peptides was also assessed to determine the precision of replicate analyses from FAIMS methods with increased cycle times. Our results also identified from 1 ng of HeLa protein digest without any prior enrichment 76 ± 9 phosphopeptides, 18% of which were multiphosphorylated. These results represent a 46% increase in phosphopeptide identifications over the control experiments without FAIMS yielding 2.5-fold more multiphosphorylated peptides.

Development of Highly Sensitive LC–MS and CE–MS Methods for In-Depth Proteomic and Glycomic Profiling of Limited Biological Samples

nformative and deep proteomic and glycomic characterization of limited availability biological and medical samples has been a significant challenge. Here, we describe our current and recent efforts in advancing sample preparation as well as miniaturized electric field- and pressure-driven separation approaches interfaced with high-end mass spectrometry (MS) to enhance the sensitivity and depth of proteomic and glycomic profiling of several types of limited biological and clinically relevant samples.

MPAPASS software enables stitched multiplex, multidimensional EV repertoire analysis and a standard framework for reporting bead-based assays

Extracellular vesicles (EVs) of various types are released or shed from all cells. EVs carry proteins and contain additional protein and nucleic acid cargo that relates to their biogenesis and cell of origin. EV cargo in liquid biopsies is of widespread interest owing to its ability to provide a retrospective snapshot of cell state at the time of EV release. For the purposes of EV cargo analysis and repertoire profiling, multiplex assays are an essential tool in multiparametric analyte studies but are still being developed for high-parameter EV protein detection. Although bead-based EV multiplex analyses offer EV profiling capabilities with conventional flow cytometers, the utilization of EV multiplex assays has been limited by the lack of software analysis tools for such assays. To facilitate robust EV repertoire studies, we developed multiplex analysis post-acquisition analysis (MPAPASS) open-source software for stitched multiplex analysis, EV database-compatible reporting, and visualization of EV repertoires.

Capillary Electrophoresis Coupled to Electrospray Ionization Tandem Mass Spectrometry for Ultra-Sensitive Proteomic Analysis of Limited Samples

In this work, we developed an ultra-sensitive CE-MS/MS method for bottom-up proteomics analysis of limited samples, down to sub-nanogram levels of total protein. Analysis of 880 and 88 pg of the HeLa protein digest standard by CE-MS/MS yielded ∼1100 ± 46 and ∼160 ± 59 proteins, respectively, demonstrating higher protein and peptide identifications than the current state-of-the-art CE-MS/MS-based proteomic analyses with similar amounts of sample. To demonstrate potential applications of our ultra-sensitive CE-MS/MS method for the analysis of limited biological samples, we digested 500 and 1000 HeLa cells using a miniaturized in-solution digestion workflow. From 1-, 5-, and 10-cell equivalents injected from the resulted digests, we identified 744 ± 127, 1139 ± 24, and 1271 ± 6 proteins and 3353 ± 719, 5709 ± 513, and 8527 ± 114 peptide groups, respectively. Furthermore, we performed a comparative assessment of CE-MS/MS and two reversed-phased nano-liquid chromatography (RP-nLC-MS/MS) methods (monolithic and packed columns) for the analysis of a ∼10 ng HeLa protein digest standard. Our results demonstrate complementarity in the protein- and especially peptide-level identifications of the evaluated CE-MS- and RP-nLC-MS-based methods. The techniques were further assessed to detect post-translational modifications and highlight the strengths of the CE-MS/MS approach in identifying potentially important and biologically relevant modified peptides. With a migration window of ∼60 min, CE-MS/MS identified ∼2000 ± 53 proteins on average from a single injection of ∼8.8 ng of the HeLa protein digest standard. Additionally, an average of 232 ± 10 phosphopeptides and 377 ± 14 N-terminal acetylated peptides were identified in CE-MS/MS analyses at this sample amount, corresponding to 2- and 1.5-fold more identifications for each respective modification found by nLC-MS/MS methods.

Comparison of Microflow and Analytical Flow Liquid Chromatography Coupled to Mass Spectrometry Global Metabolomics Methods Using a Urea Cycle Disorder Mouse Model

Microscale-based separations are increasingly being applied in the field of metabolomics for the analysis of small-molecule metabolites. These methods have the potential to provide improved sensitivity, less solvent waste, and reduced sample-size requirements. Ion-pair free microflow-based global metabolomics methods, which we recently reported, were further compared to analytical flow ion-pairing reagent containing methods using a sample set from a urea cycle disorder (UCD) mouse model. Mouse urine and brain homogenate samples representing healthy, diseased, and disease-treated animals were analyzed by both methods. Data processing was performed using univariate and multivariate techniques followed by analyte trend analysis. The microflow methods performed comparably to the analytical flow ion-pairing methods with the ability to separate the three sample groups when analyzed by partial least-squares analysis. The number of detected metabolic features present after each data processing step was similar between the microflow-based methods and the ion-pairing methods in the negative ionization mode. The observed analyte trend and coverage of known UCD biomarkers were the same for both evaluated approaches. The 12.5-fold reduction in sample injection volume required for the microflow-based separations highlights the potential of this method to support studies with sample-size limitations.

High-throughput microfluidic 3D biomimetic model enabling quantitative description of the human breast tumor microenvironment

Cancer is driven by both genetic aberrations in the tumor cells and fundamental changes in the tumor microenvironment (TME). These changes offer potential targets for novel therapeutics, yet lack of in vitro 3D models recapitulating this complex microenvironment impedes such progress. Here, we generated several tumor-stroma scaffolds reflecting the dynamic in vivo breast TME, using a high throughput microfluidic system. Alginate (Alg) or alginate-alginate sulfate (Alg/Alg-S) hydrogels were used as ECM-mimics, enabling the encapsulation and culture of tumor cells, fibroblasts and immune cells (macrophages and T cells, of the innate and adaptive immune systems, respectively). Specifically, Alg/Alg-S was shown capable of capturing and presenting growth factors and cytokines with binding affinity that is comparable to heparin. Viability and cytotoxicity were shown to strongly correlate with the dynamics of cellular milieu, as well as hydrogel type. Using on-chip immunofluorescence, production of reactive oxygen species and apoptosis were imaged and quantitatively analyzed. We then show how macrophages in our microfluidic system were shifted from a proinflammatory to an immunosuppressive phenotype when encapsulated in Alg/Alg-S, reflecting in vivo TME dynamics. LC-MS proteomic profiling of tumor cells sorted from the TME scaffolds revealed upregulation of proteins involved in cell-cell interactions and immunomodulation in Alg/Alg-S scaffolds, correlating with in vivo findings and demonstrating the appropriateness of Alg/Alg-S as an ECM biomimetic. Finally, we show the formation of large tumor-derived vesicles, formed exclusively in Alg/Alg-S scaffolds. Altogether, our system offers a robust platform for quantitative description of the breast TME that successfully recapitulates in vivo patterns. STATEMENT OF SIGNIFICANCE: Cancer progression is driven by profound changes in both tumor cells and surrounding stroma. Here, we present a high throughput microfluidic system for the generation and analysis of dynamic tumor-stroma scaffolds, that mimic the complex in vivo TME cell proportions and compositions, constructing robust in vitro models for the study of the TME. Utilizing Alg/Alg-S as a bioinspired ECM, mimicking heparin's in vivo capabilities of capturing and presenting signaling molecules, we show how Alg/Alg-S induces complex in vivo-like responses in our models. Alg/Alg-S is shown here to promote dynamic protein expression patterns, that can serve as potential therapeutic targets for breast cancer treatment. Formation of large tumor-derived vesicles, observed exclusively in the Alg/Alg-S scaffolds suggests a mechanism for tumor survival.

Channeling macrophage polarization by rocaglates increases macrophage resistance to Mycobacterium tuberculosis

Macrophages contribute to host immunity and tissue homeostasis via alternative activation programs. M1-like macrophages control intracellular bacterial pathogens and tumor progression. In contrast, M2-like macrophages shape reparative microenvironments that can be conducive for pathogen survival or tumor growth. An imbalance of these macrophages phenotypes may perpetuate sites of chronic unresolved inflammation, such as infectious granulomas and solid tumors. We have found that plant-derived and synthetic rocaglates sensitize macrophages to low concentrations of the M1-inducing cytokine IFN-gamma and inhibit their responsiveness to IL-4, a prototypical activator of the M2-like phenotype. Treatment of primary macrophages with rocaglates enhanced phagosome-lysosome fusion and control of intracellular mycobacteria. Thus, rocaglates represent a novel class of immunomodulators that can direct macrophage polarization toward the M1-like phenotype in complex microenvironments associated with hypofunction of type 1 and/or hyperactivation of type 2 immunity, e.g., chronic bacterial infections, allergies, and, possibly, certain tumors.

Rapid Highly-Efficient Digestion and Peptide Mapping of Adeno-Associated Viruses

Adeno-associated viruses (AAVs) comprise an area of rapidly growing interest due to their ability to act as a gene delivery vehicle in novel gene therapy strategies and vaccine development. Peptide mapping is a common technique in the biopharmaceutical industry to confirm the correct sequence, product purity, post-translational modifications (PTMs), and stability. However, conventional peptide mapping is time-consuming and has proven difficult to reproduce with viral capsids because of their high structural stability and the suboptimal localization of trypsin cleavage sites in the AAV protein sequences. In this study, we present an optimized peptide mapping-based workflow that provides thorough characterization within 1 day. This workflow is also highly reproducible due to its simplicity having very few steps and is easy to perform proteolytic digestion utilizing thermally stable pepsin, which is active at 70 °C in acidic conditions. The acidic conditions of the peptic digestions drive viral capsid denaturation and improve cleavage site accessibility. We characterized the efficiency and ease of digestion through peptide mapping of the AAV2 viral capsid protein. Using nanoflow liquid chromatography coupled with tandem mass spectrometry, we achieved 100% sequence coverage of the low-abundance VP1 capsid protein with a digestion process taking only 10 min to prepare and 45 min to complete the digestion.

A systematic approach to development of analytical scale and microflow-based liquid chromatography coupled to mass spectrometry metabolomics methods to support drug discovery and development

As the reliance on metabolic biomarkers within drug discovery and development increases, there is also an increased demand for global metabolomics methods to provide broad metabolome coverage and sensitivity towards differences in metabolite expression and reproducibility. A systematic approach is necessary for the development, and evaluation, of metabolomics methods using either conventional techniques or when establishing new methods that allow for additional gains in sensitivity and a reduction in requirements for amounts of a biological sample, such as those seen with methods based on microseparations. We developed a novel standard mixture and used a systematic approach for the development and optimization of optimal, ion-pair free, liquid chromatography-mass spectrometry (LC-MS) global profiling methods. These methods were scaled-down to microflow-based LC separations and compared with analytical flow ion-pairing reagent containing methods. Average peak volume improvements of 7- and 22-fold were observed in the positive and negative ionization mode microflow methods as compared to the ion-pairing reagent analytical flow methods, respectively. The linear range of the newly developed microflow methods showed up to a 10-fold increase in the lower limit of detection in the negative ionization mode. The developed microflow LC-MS methods were further evaluated using wild-type mouse plasma where up to a 9-fold increase in peak volume was observed.

Simple and Efficient Microsolid-Phase Extraction Tip-Based Sample Preparation Workflow to Enable Sensitive Proteomic Profiling of Limited Samples (200 to 10,000 Cells)

In-depth LC-MS-based proteomic profiling of limited biological and clinical samples, such as rare cells or tissue sections from laser capture microdissection or microneedle biopsies, has been problematic due, in large, to the inefficiency of sample preparation and attendant sample losses. To address this issue, we developed on-microsolid-phase extraction tip (OmSET)-based sample preparation for limited biological samples. OmSET is simple, efficient, reproducible, and scalable and is a widely accessible method for processing ∼200 to 10,000 cells. The developed method benefits from minimal sample processing volumes (1-3 μL) and conducting all sample processing steps on-membrane within a single microreactor. We first assessed the feasibility of using micro-SPE tips for nanogram-level amounts of tryptic peptides, minimized the number of required sample handling steps, and reduced the hands-on time. We then evaluated the capability of OmSET for quantitative analysis of low numbers of human monocytes. Reliable and reproducible label-free quantitation results were obtained with excellent correlations between protein abundances and the amounts of starting material (R2 = 0.93) and pairwise correlations between sample processing replicates (R2 = 0.95) along with the identification of approximately 300, 1800, and 2000 protein groups from injected ∼10, 100, and 500 cell equivalents, resulting from processing approximately 200, 2000, and 10,000 cells, respectively.

A simple, high-throughput method of protein and label removal from extracellular vesicle samples

Evidence continues to increase of the clinical utility extracellular vesicles (EVs) as translational biomarkers. While a wide variety of EV isolation and purification methods have been implemented, few techniques are high-throughput and scalable for removing excess fluorescent reagents (e.g. dyes, antibodies). EVs are too small to be recovered from routine cell-processing procedures, such as filtration or centrifugation. The lack of suitable methods for removing unbound labels, especially in optical assays, is a major roadblock to accurate EV phenotyping and utilization of EV assays in a translational or clinical setting. Therefore, we developed a method for using a multi-modal resin, referred to as EV-Clean, to remove unbound labels from EV samples, and we demonstrate improvement in flow cytometric EV analysis with the use of this EV-Clean method.

Lipidome-based Targeting of STAT3-driven Breast Cancer Cells Using Poly-l-glutamic Acid-coated Layer-by-Layer Nanoparticles

The oncogenic transcription factor STAT3 is aberrantly activated in 70% of breast cancers, including nearly all triple-negative breast cancers (TNBCs). Because STAT3 is difficult to target directly, we considered whether metabolic changes driven by activated STAT3 could provide a therapeutic opportunity. We found that STAT3 prominently modulated several lipid classes, with most profound effects on N-acyl taurine and arachidonic acid, both of which are involved in plasma membrane remodeling. To exploit these metabolic changes therapeutically, we screened a library of layer-by-layer (LbL) nanoparticles (NPs) differing in the surface layer that modulates interactivity with the cell membrane. We found that poly-l-glutamic acid (PLE)-coated NPs bind to STAT3-transformed breast cancer cells with 50% greater efficiency than to nontransformed cells, and the heightened PLE-NP binding to TNBC cells was attenuated by STAT3 inhibition. This effect was also observed in densely packed three-dimensional breast cancer organoids. As STAT3-transformed cells show greater resistance to cytotoxic agents, we evaluated whether enhanced targeted delivery via PLE-NPs would provide a therapeutic advantage. We found that cisplatin-loaded PLE-NPs induced apoptosis of STAT3-driven cells at lower doses compared with both unencapsulated cisplatin and cisplatin-loaded nontargeted NPs. In addition, because radiation is commonly used in breast cancer treatment, and may alter cellular lipid distribution, we analyzed its effect on PLE-NP-cell binding. Irradiation of cells enhanced the STAT3-targeting properties of PLE-NPs in a dose-dependent manner, suggesting potential synergies between these therapeutic modalities. These findings suggest that cellular lipid changes driven by activated STAT3 may be exploited therapeutically using unique LbL NPs.

The integrated stress response mediates necrosis in murine Mycobacterium tuberculosis granulomas

The mechanism by which only some individuals infected with Mycobacterium tuberculosis develop necrotic granulomas with progressive disease while others form controlled granulomas that contain the infection remains poorly defined. Mice carrying the sst1-suscepible (sst1S) genotype develop necrotic inflammatory lung lesions, similar to human tuberculosis (TB) granulomas, which are linked to macrophage dysfunction, while their congenic counterpart (B6) mice do not. In this study we report that (a) sst1S macrophages developed aberrant, biphasic responses to TNF characterized by superinduction of stress and type I interferon pathways after prolonged TNF stimulation; (b) the late-stage TNF response was driven via a JNK/IFN-β/protein kinase R (PKR) circuit; and (c) induced the integrated stress response (ISR) via PKR-mediated eIF2α phosphorylation and the subsequent hyperinduction of ATF3 and ISR-target genes Chac1, Trib3, and Ddit4. The administration of ISRIB, a small-molecule inhibitor of the ISR, blocked the development of necrosis in lung granulomas of M. tuberculosis-infected sst1S mice and concomitantly reduced the bacterial burden. Hence, induction of the ISR and the locked-in state of escalating stress driven by the type I IFN pathway in sst1S macrophages play a causal role in the development of necrosis in TB granulomas. Interruption of the aberrant stress response with inhibitors such as ISRIB may offer novel host-directed therapy strategies.

High-Sensitivity Glycan Profiling of Blood-Derived Immunoglobulin G, Plasma, and Extracellular Vesicle Isolates with Capillary Zone Electrophoresis-Mass Spectrometry

We developed a highly sensitive method for profiling of N-glycans released from proteins based on capillary zone electrophoresis coupled to electrospray ionization mass spectrometry (CZE-ESI-MS) and applied the technique to glycan analysis of plasma and blood-derived isolates. The combination of dopant-enriched nitrogen (DEN)-gas introduced into the nanoelectrospray microenvironment with optimized ionization, desolvation, and CZE-MS conditions improved the detection sensitivity up to ∼100-fold, as directly compared to the conventional mode of instrument operation through peak intensity measurements. Analyses without supplemental pressure increased the resolution ∼7-fold in the separation of closely related and isobaric glycans. The developed method was evaluated for qualitative and quantitative glycan profiling of three types of blood isolates: plasma, total serum immunoglobulin G (IgG), and total plasma extracellular vesicles (EVs). The comparative glycan analysis of IgG and EV isolates and total plasma was conducted for the first time and resulted in detection of >200, >400, and >500 N-glycans for injected sample amounts equivalent to <500 nL of blood. Structural CZE-MS² analysis resulted in the identification of highly diverse glycans, assignment of α-2,6-linked sialic acids, and differentiation of positional isomers. Unmatched depth of N-glycan profiling was achieved compared to previously reported methods for the analysis of minute amounts of similar complexity blood isolates.

New mixture models for decoy-free false discovery rate estimation in mass spectrometry proteomics

MOTIVATION

Accurate estimation of false discovery rate (FDR) of spectral identification is a central problem in mass spectrometry-based proteomics. Over the past two decades, target-decoy approaches (TDAs) and decoy-free approaches (DFAs) have been widely used to estimate FDR. TDAs use a database of decoy species to faithfully model score distributions of incorrect peptide-spectrum matches (PSMs). DFAs, on the other hand, fit two-component mixture models to learn the parameters of correct and incorrect PSM score distributions. While conceptually straightforward, both approaches lead to problems in practice, particularly in experiments that push instrumentation to the limit and generate low fragmentation-efficiency and low signal-to-noise-ratio spectra.

RESULTS

We introduce a new decoy-free framework for FDR estimation that generalizes present DFAs while exploiting more search data in a manner similar to TDAs. Our approach relies on multi-component mixtures, in which score distributions corresponding to the correct PSMs, best incorrect PSMs and second-best incorrect PSMs are modeled by the skew normal family. We derive EM algorithms to estimate parameters of these distributions from the scores of best and second-best PSMs associated with each experimental spectrum. We evaluate our models on multiple proteomics datasets and a HeLa cell digest case study consisting of more than a million spectra in total. We provide evidence of improved performance over existing DFAs and improved stability and speed over TDAs without any performance degradation. We propose that the new strategy has the potential to extend beyond peptide identification and reduce the need for TDA on all analytical platforms.

AVAILABILITYAND IMPLEMENTATION

https://github.com/shawn-peng/FDR-estimation.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Improved Sensitivity of Ultralow Flow LC-MS-Based Proteomic Profiling of Limited Samples Using Monolithic Capillary Columns and FAIMS Technology

In this work, we pioneered a combination of ultralow flow (ULF) high-efficiency ultranarrow bore monolithic LC columns coupled to MS via a high-field asymmetric waveform ion mobility spectrometry (FAIMS) interface to evaluate the potential applicability for high sensitivity, robust, and reproducible proteomic profiling of low nanogram-level complex biological samples. As a result, ULF LC-FAIMS-MS brought unprecedented sensitivity levels and high reproducibility in bottom-up proteomic profiling. In addition, FAIMS improved the dynamic range, signal-to-noise ratios, and detection limits in ULF LC-MS-based measurements by significantly reducing chemical noise in comparison to the conventional nanoESI interface used with the same ULF LC-MS setup. Two, three, or four compensation voltages separated by at least 15 V were tested within a single LC-MS run using the FAIMS interface. The optimized ULF LC-ESI-FAIMS-MS/MS conditions resulted in identification of 2,348 ± 42 protein groups, 10,062 ± 285 peptide groups, and 15,734 ± 350 peptide-spectrum matches for 1 ng of a HeLa digest, using a 1 h gradient at the flow rate of 12 nL/min, which represents an increase by 38%, 91%, and 131% in respective identifications, as compared to the control experiment (without FAIMS). To evaluate the practical utility of the ULF LC-ESI-FAIMS-MS platform in proteomic profiling of limited samples, approximately 100, 1,000, and 10,000 U937 myeloid leukemia cells were processed, and a one-tenth of each sample was analyzed. Using the optimized conditions, we were able to reliably identify 251 ± 54, 1,135 ± 80, and 2,234 ± 25 protein groups from injected aliquots corresponding to ∼10, 100, and 1,000 processed cells.

Multi-Omics Reveals Impact of Cysteine Feed Concentration and Resulting Redox Imbalance on Cellular Energy Metabolism and Specific Productivity in CHO Cell Bioprocessing

Chinese hamster ovary (CHO) cells are currently the primary host cell lines used in biotherapeutic manufacturing of monoclonal antibodies (mAbs) and other biopharmaceuticals. Cellular energy metabolism and endoplasmic reticulum (ER) stress are known to greatly impact cell growth, viability, and specific productivity of a biotherapeutic; but the molecular mechanisms are not fully understood. The authors previously employed multi-omics profiling to investigate the impact of a reduction in cysteine (Cys) feed concentration in a fed-batch process and found that disruption of the redox balance led to a substantial decline in cell viability and titer. Here, the multi-omics findings are expanded, and the impact redox imbalance has on ER stress, mitochondrial homeostasis, and lipid metabolism is explored. The reduced Cys feed activates the amino acid response (AAR), increases mitochondrial stress, and initiates gluconeogenesis. Multi-omics analysis reveals that together, ER stress and AAR signaling shift the cellular energy metabolism to rely primarily on anaplerotic reactions, consuming amino acids and producing lactate, to maintain energy generation. Furthermore, the pathways are demonstrated in which this shift in metabolism leads to a substantial decline in specific productivity and altered mAb glycosylation. Through this work, meaningful bioprocess markers and targets for genetic engineering are identified.

Machine learning-aided quantification of antibody-based cancer immunotherapy by natural killer cells in microfluidic droplets

Natural killer (NK) cells have emerged as an effective alternative option to T cell-based immunotherapies, particularly against liquid (hematologic) tumors. However, the effectiveness of NK cell therapy has been less than optimal for solid tumors, partly due to the heterogeneity in target interaction leading to variable anti-tumor cytotoxicity. This paper describes a microfluidic droplet-based cytotoxicity assay for quantitative comparison of immunotherapeutic NK-92 cell interaction with various types of target cells. Machine learning algorithms were developed to assess the dynamics of individual effector-target cell pair conjugation and target death in droplets in a semi-automated manner. Our results showed that while short contacts were sufficient to induce potent killing of hematological cancer cells, long-lasting stable conjugation with NK-92 cells was unable to kill HER2+ solid tumor cells (SKOV3, SKBR3) significantly. NK-92 cells that were engineered to express FcγRIII (CD16) mediated antibody-dependent cellular cytotoxicity (ADCC) selectively against HER2+ cells upon addition of Herceptin (trastuzumab). The requirement of CD16, Herceptin and specific pre-incubation temperature served as three inputs to generate a molecular logic function with HER2+ cell death as the output. Mass proteomic analysis of the two effector cell lines suggested differential changes in adhesion, exocytosis, metabolism, transport and activation of upstream regulators and cytotoxicity mediators, which can be utilized to regulate specific functionalities of NK-92 cells in future. These results suggest that this semi-automated single cell assay can reveal the variability and functional potency of NK cells and may be used to optimize immunotherapeutic efficacy for preclinical analyses.

Technologies and Standardization in Research on Extracellular Vesicles

Extracellular vesicles (EVs) are phospholipid bilayer membrane-enclosed structures containing RNAs, proteins, lipids, metabolites, and other molecules, secreted by various cells into physiological fluids. EV-mediated transfer of biomolecules is a critical component of a variety of physiological and pathological processes. Potential applications of EVs in novel diagnostic and therapeutic strategies have brought increasing attention. However, EV research remains highly challenging due to the inherently complex biogenesis of EVs and their vast heterogeneity in size, composition, and origin. There is a need for the establishment of standardized methods that address EV heterogeneity and sources of pre-analytical and analytical variability in EV studies. Here, we review technologies developed for EV isolation and characterization and discuss paths toward standardization in EV research.

A nanoscale, multi-parametric flow cytometry-based platform to study mitochondrial heterogeneity and mitochondrial DNA dynamics

Mitochondria are well-characterized regarding their function in both energy production and regulation of cell death; however, the heterogeneity that exists within mitochondrial populations is poorly understood. Typically analyzed as pooled samples comprised of millions of individual mitochondria, there is little information regarding potentially different functionality across subpopulations of mitochondria. Herein we present a new methodology to analyze mitochondria as individual components of a complex and heterogeneous network, using a nanoscale and multi-parametric flow cytometry-based platform. We validate the platform using multiple downstream assays, including electron microscopy, ATP generation, quantitative mass-spectrometry proteomic profiling, and mtDNA analysis at the level of single organelles. These strategies allow robust analysis and isolation of mitochondrial subpopulations to more broadly elucidate the underlying complexities of mitochondria as these organelles function collectively within a cell.

Genetically Encoded Fluorescent Proteins Enable High-Throughput Assignment of Cell Cohorts Directly from MALDI-MS Images

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) provides a unique in situ chemical profile that can include drugs, nucleic acids, metabolites, lipids, and proteins. MSI of individual cells (of a known cell type) affords a unique insight into normal and disease-related processes and is a prerequisite for combining the results of MSI and other single-cell modalities (e.g. mass cytometry and next-generation sequencing). Technological barriers have prevented the high-throughput assignment of MSI spectra from solid tissue preparations to their cell type. These barriers include obtaining a suitable cell-identifying image (e.g. immunohistochemistry) and obtaining sufficiently accurate registration of the cell-identifying and MALDI-MS images. This study introduces a technique that overcame these barriers by assigning cell type directly from mass spectra. We hypothesized that, in MSI from mice with a defined fluorescent protein expression pattern, the fluorescent protein's molecular ion could be used to identify cell cohorts. A method was developed for the purification of enhanced yellow fluorescent protein (EYFP) from mice. To determine EYFP's molecular mass for MSI studies, we performed intact mass analysis and characterized the protein's primary structure and post-translational modifications through various techniques. MALDI-MSI methods were developed to enhance the detection of EYFP in situ, and by extraction of EYFP's molecular ion from MALDI-MS images, automated, whole-image assignment of cell cohorts was achieved. This method was validated using a well-characterized mouse line that expresses EYFP in motor and sensory neurons and should be applicable to hundreds of commercially available mice (and other animal) strains comprising a multitude of cell-specific fluorescent labels.

Multi-Omics Study on the Impact of Cysteine Feed Level on Cell Viability and mAb Production in a CHO Bioprocess

There is continual demand to maximize CHO cell culture productivity of a biotherapeutic while maintaining product quality. In this study, a comprehensive multi-omics analysis is performed to investigate the cellular response to the level of dosing of the amino acid cysteine (Cys) in the production of a monoclonal antibody (mAb). When Cys feed levels are insufficient, there is a significant decrease in protein titer. Multi-omics (metabolomics and proteomics, with support from RNAseq) is performed over the time course of the CHO bioprocess producing an IgG1 mAb in 5 L bioreactors. Pathway analysis reveals that insufficient levels of Cys in the feed lead to Cys depletion in the cell. This depletion negatively impacts antioxidant molecules, such as glutathione (GSH) and taurine, leading to oxidative stress with multiple deleterious cellular effects. In this paper, the resultant ER stress and subsequent apoptosis that affects cell viability and viable cell density has been considered. Key metabolic enzymes and metabolites are identified that can be potentially monitored as the process progresses and/or increased in the cell either by nutrient feeding or genetic engineering. This work reinforces the centrality of redox balance to cellular health and success of the bioprocess as well as the power of multi-omics to provide an in-depth understanding of the CHO cell biology during biopharmaceutical production.

Complementary middle-down and intact monoclonal antibody proteoform characterization by capillary zone electrophoresis - mass spectrometry

High-resolution capillary zone electrophoresis - mass spectrometry (CZE-MS) has been of increasing interest for the analysis of biopharmaceuticals. In this work, a combination of middle-down and intact CZE-MS analyses has been implemented for the characterization of a biotherapeutic monoclonal antibody (mAb) with a variety of post-translational modifications (PTMs) and glycosylation structures. Middle-down and intact CZE separations were performed in an acidified methanol-water background electrolyte on a capillary with a positively charged coating (M7C4I) coupled to an Orbitrap mass spectrometer using a commercial sheathless interface (CESI). Middle-down analysis of the IdeS-digested mAb provided characterization of PTMs of digestion fragments. High resolution CZE enabled separation of charge variants corresponding to 2X-deamidated, 1X-deamidated, and non-deamidated forms at baseline resolution. In the course of the middle-down CZE-MS analysis, separation of glycoforms of the F_C /2 fragment was accomplished due to hydrodynamic volume differences. Several identified PTMs were confirmed by CZE-MS² . Incorporation of TCEP-HCl reducing agent in the sample solvent resulted in successful analysis of reduced forms without the need for alkylation. CZE-MS studies on the intact mAb under denaturing conditions enabled baseline separation of the 2X-glycosylated, 1X-glycosylated, and aglycosylated populations as a result of hydrodynamic volume differences. The presence of a trace quantity of dissociated light chain was also detected in the intact protein analysis. Characterization of the mAb under native conditions verified identifications achieved via intact analysis and allowed for quantitative confirmation of proteoforms. Analysis of mAbs using CZE-MS represents a complementary approach to the more conventional liquid-chromatography - mass spectrometry-based approaches.

Analysis of Proteins, Protein Complexes, and Organellar Proteomes Using Sheathless Capillary Zone Electrophoresis - Native Mass Spectrometry

Native mass spectrometry (MS) is a rapidly advancing field in the analysis of proteins, protein complexes, and macromolecular species of various types. The majority of native MS experiments reported to-date has been conducted using direct infusion of purified analytes into a mass spectrometer. In this study, capillary zone electrophoresis (CZE) was coupled online to Orbitrap mass spectrometers using a commercial sheathless interface to enable high-performance separation, identification, and structural characterization of limited amounts of purified proteins and protein complexes, the latter with preserved non-covalent associations under native conditions. The performance of both bare-fused silica and polyacrylamide-coated capillaries was assessed using mixtures of protein standards known to form non-covalent protein-protein and protein-ligand complexes. High-efficiency separation of native complexes is demonstrated using both capillary types, while the polyacrylamide neutral-coated capillary showed better reproducibility and higher efficiency for more complex samples. The platform was then evaluated for the determination of monoclonal antibody aggregation and for analysis of proteomes of limited complexity using a ribosomal isolate from E. coli. Native CZE-MS, using accurate single stage and tandem-MS measurements, enabled identification of proteoforms and non-covalent complexes at femtomole levels. This study demonstrates that native CZE-MS can serve as an orthogonal and complementary technique to conventional native MS methodologies with the advantages of low sample consumption, minimal sample processing and losses, and high throughput and sensitivity. This study presents a novel platform for analysis of ribosomes and other macromolecular complexes and organelles, with the potential for discovery of novel structural features defining cellular phenotypes (e.g., specialized ribosomes). Graphical Abstract ᅟ.

Analysis of Proteins, Protein Complexes, and Organellar Proteomes Using Sheathless Capillary Zone Electrophoresis - Native Mass Spectrometry

Native mass spectrometry (MS) is a rapidly advancing field in the analysis of proteins, protein complexes, and macromolecular species of various types. The majority of native MS experiments reported to-date has been conducted using direct infusion of purified analytes into a mass spectrometer. In this study, capillary zone electrophoresis (CZE) was coupled online to Orbitrap mass spectrometers using a commercial sheathless interface to enable high-performance separation, identification, and structural characterization of limited amounts of purified proteins and protein complexes, the latter with preserved non-covalent associations under native conditions. The performance of both bare-fused silica and polyacrylamide-coated capillaries was assessed using mixtures of protein standards known to form non-covalent protein-protein and protein-ligand complexes. High-efficiency separation of native complexes is demonstrated using both capillary types, while the polyacrylamide neutral-coated capillary showed better reproducibility and higher efficiency for more complex samples. The platform was then evaluated for the determination of monoclonal antibody aggregation and for analysis of proteomes of limited complexity using a ribosomal isolate from E. coli. Native CZE-MS, using accurate single stage and tandem-MS measurements, enabled identification of proteoforms and non-covalent complexes at femtomole levels. This study demonstrates that native CZE-MS can serve as an orthogonal and complementary technique to conventional native MS methodologies with the advantages of low sample consumption, minimal sample processing and losses, and high throughput and sensitivity. This study presents a novel platform for analysis of ribosomes and other macromolecular complexes and organelles, with the potential for discovery of novel structural features defining cellular phenotypes (e.g., specialized ribosomes). Graphical Abstract ᅟ.

Binding Site Characterization of AM1336, a Novel Covalent Inverse Agonist at Human Cannabinoid 2 Receptor, Using Mass Spectrometric Analysis

Cannabinoid 2 receptor (CB2R), a Class-A G-protein coupled receptor (GPCR), is a promising drug target under a wide array of pathological conditions. Rational drug design has been hindered due to our poor understanding of the structural features involved in ligand binding. Binding of a high-affinity biarylpyrazole inverse agonist AM1336 to a library of the human CB2 receptor (hCB2R) cysteine-substituted mutants provided indirect evidence that two cysteines in transmembrane helix-7 (H7) were critical for the covalent attachment. We used proteomics analysis of the hCB2R with bound AM1336 to directly identify peptides with covalently attached ligand and applied in silico modeling for visualization of the ligand-receptor interactions. The hCB2R, with affinity tags (FlaghCB2His6), was produced in a baculovirus-insect cell expression system and purified as a functional receptor using immunoaffinity chromatography. Using mass spectrometry-based bottom-up proteomic analysis of the hCB2R-AM1336, we identified a peptide with AM1336 attached to the cysteine C284(7.38) in H7. The hCB2R homology model in lipid bilayer accommodated covalent attachment of AM1336 to C284(7.38), supporting both biochemical and mass spectrometric data. This work consolidates proteomics data and in silico modeling and integrates with our ligand-assisted protein structure (LAPS) experimental paradigm to assist in structure-based design of cannabinoid antagonist/inverse agonists.

Host Cell Protein Profiling by Targeted and Untargeted Analysis of Data Independent Acquisition Mass Spectrometry Data with Parallel Reaction Monitoring Verification

Host cell proteins (HCPs) are process-related impurities of biopharmaceuticals that remain at trace levels despite multiple stages of downstream purification. Currently, there is interest in implementing LC-MS in biopharmaceutical HCP profiling alongside conventional ELISA, because individual species can be identified and quantitated. Conventional data dependent LC-MS is hampered by the low concentration of HCP-derived peptides, which are 5-6 orders of magnitude less abundant than the biopharmaceutical-derived peptides. In this paper, we present a novel data independent acquisition (DIA)-MS workflow to identify HCP peptides using automatically combined targeted and untargeted data processing, followed by verification and quantitation using parallel reaction monitoring (PRM). Untargeted data processing with DIA-Umpire provided a means of identifying HCPs not represented in the assay library used for targeted, peptide-centric, data analysis. An IgG1 monoclonal antibody (mAb) purified by Protein A column elution, cation exchange chromatography, and ultrafiltration was analyzed using the workflow with 1D-LC. Five protein standards added at 0.5 to 100 ppm concentrations were detected in the background of the purified mAb, demonstrating sensitivity to low ppm levels. A calibration curve was constructed on the basis of the summed peak areas of the three highest intensity fragment ions from the highest intensity peptide of each protein standard. Sixteen HCPs were identified and quantitated on the basis of the calibration curve over the range of low ppm to over 100 ppm in the purified mAb sample. The developed approach achieves rapid HCP profiling using 1D-LC and specific identification exploiting the high mass accuracy and resolution of the mass spectrometer.

Rapid Isolation of Extracellular Vesicles from Blood Plasma with Size-Exclusion Chromatography Followed by Mass Spectrometry-Based Proteomic Profiling

The presented procedure allows rapid isolation of extracellular vesicles (EVs) from plasma using size-exclusion chromatography (SEC). Additionally, an approach for reducing the lipid and salt content of the EV isolate in preparation for mass spectrometry (MS)-based proteomic analysis is presented. An example setup for proteomic profiling of the processed samples by nanoflow liquid chromatography coupled to tandem mass spectrometry (nLC-MS/MS) is also presented. Approximately 1000 protein groups in blood plasma-derived EVs can be identified and quantitated following this procedure and using the described instrumentation.

Advanced Precursor Ion Selection Algorithms for Increased Depth of Bottom-Up Proteomic Profiling

Conventional TopN data-dependent acquisition (DDA) LC-MS/MS analysis identifies only a limited fraction of all detectable precursors because the ion-sampling rate of contemporary mass spectrometers is insufficient to target each precursor in a complex sample. TopN DDA preferentially targets high-abundance precursors with limited sampling of low-abundance precursors and repeated analyses only marginally improve sample coverage due to redundant precursor sampling. In this work, advanced precursor ion selection algorithms were developed and applied in the bottom-up analysis of HeLa cell lysate to overcome the above deficiencies. Precursors fragmented in previous runs were efficiently excluded using an automatically aligned exclusion list, which reduced overlap of identified peptides to ∼10% between replicates. Exclusion of previously fragmented high-abundance peptides allowed deeper probing of the HeLa proteome over replicate LC-MS runs, resulting in the identification of 29% more peptides beyond the saturation level achievable using conventional TopN DDA. The gain in peptide identifications using the developed approach translated to the identification of several hundred low-abundance protein groups, which were not detected by conventional TopN DDA. Exclusion of only identified peptides compared with the exclusion of all previously fragmented precursors resulted in an increase of 1000 (∼10%) additional peptide identifications over four runs, suggesting the potential for further improvement in the depth of proteomic profiling using advanced precursor ion selection algorithms.