Middle-Down Proteomic Analyses with Ion Mobility Separations of Endogenous Isomeric Proteoforms

Online, Bottom-up Characterization of Histone H4 4-17 Isomers

The "Histone Code" is comprised of specific types and positions of post-translational modifications (PTMs) which produce biological signals for gene regulation and have potential as biomarkers for medical diagnostics. Previous work has shown that electron-based fragmentation improves the sequence coverage and confidence of labile PTM position assignment. Here, we evaluated two derivatization methods (e.g., irreversible - propionylation and reversible-citraconylation) for bottom-up analysis of histone H4 4-17 proteoforms using online liquid chromatography (LC), trapped ion mobility spectrometry (TIMS), and electron-based dissociation (ExD) in tandem with mass spectrometry. Two platforms were utilized: a custom-built LC-TIMS-q-ExD-ToF MS/MS based on a Bruker Impact and a commercial μLC-EAD-ToF MS/MS SCIEX instrument. Complementary LC-TIMS preseparation of H4 4-17 0-4ac positional isomer standards showed that they can be resolved in their endogenous form, while positional isomers cannot be fully resolved in their propionylated form; online LC-ExD-MS/MS provided high sequence coverage (>90%) for all H4 4-17 (0-4ac) proteoforms in both instrumental platforms. When applied to model cancer cells treated with a histone deacetylase inhibitor (HeLa + HDACi), both derivatization methods and platforms detected and confirmed H4 4-17 (0-4ac) proteolytic peptides based on their fragmentation pattern. Moreover, a larger number of HeLa + HDACi H4 4-17 proteoforms were observed combining LC-TIMS and LC-q-ExD-ToF MS/MS due to the positional isomer preseparation in the LC-TIMS domain of citraconylated H4 4-17 (0-4ac) peptides.

Metal Polycation Adduction to Lipids Enables Superior Ion Mobility Separations with Ultrafast Ozone-Induced Dissociation

Specific lipid isomers are functionally critical, but their structural rigidity and usually minute geometry differences make separating them harder than other biomolecules. Such separations by ion mobility spectrometry (IMS) were recently enabled by new high-definition methods using dynamic electric fields, but major resolution gains are needed. Another problem of identifying many isomers with no unique fragments in ergodic collision-induced dissociation (CID) was partly addressed by the direct ozone-induced dissociation (OzID) that localizes the double bonds, but a low reaction efficiency has limited the sensitivity, dynamic range, throughput, and compatibility with other tools. Typically lipids are analyzed by MS as singly charged protonated, deprotonated, or ammoniated ions. Here, we explore the differential IMS (FAIMS) separations with OzID for exemplary lipids cationized by polyvalent metals. These multiply charged adducts have much greater FAIMS compensation voltages (UC) than the 1+ ions, with up to 10-fold resolution gain enabling baseline isomer separations even at a moderate resolving power of the SelexION stage. Concomitantly OzID speeds up by many orders of magnitude, producing a high yield of diagnostic fragments already in 1 ms. These capabilities can be ported to the superior high-definition FAIMS and high-pressure OzID systems to take lipidomic analyses to the next level.

Bottom-up Histone Post-translational Modification Analysis using Liquid Chromatography, Trapped Ion Mobility Spectrometry, and Tandem Mass Spectrometry

The amino acid position within a histone sequence and the chemical nature of post-translational modifications (PTMs) are essential for elucidating the "Histone Code". Previous work has shown that PTMs induce specific biological responses and are good candidates as biomarkers for diagnostics. Here, we evaluate the analytical advantages of trapped ion mobility (TIMS) with parallel accumulation-serial fragmentation (PASEF) and tandem mass spectrometry (MS/MS) for bottom-up proteomics of model cancer cells. The study also considered the use of nanoliquid chromatography (LC) and traditional methods: LC-TIMS-PASEF-ToF MS/MS vs nLC-TIMS-PASEF-ToF MS/MS vs nLC-MS/MS. The addition of TIMS and PASEF-MS/MS increased the number of detected peptides due to the added separation dimension. All three methods showed high reproducibility and low RSD in the MS domain (<5 ppm). While the LC, nLC and TIMS separations showed small RSD across samples, the accurate mobility (1/K0) measurements (<0.6% RSD) increased the confidence of peptide assignments. Trends were observed in the retention time and mobility concerning the number and type of PTMs (e.g., ac, me1-3) and their corresponding unmodified, propionylated peptide that aided in peptide assignment. Mobility separation permitted the annotation of coeluting structural and positional isomers and compared with nLC-MS/MS showed several advantages due to reduced chemical noise.

GeLC-FAIMS-MS workflow for in-depth middle-down proteomics

Middle-down proteomics (MDP) is an analytical approach in which protein samples are digested with proteases such as Glu-C to generate large peptides (>3 kDa) that are analyzed by mass spectrometry (MS). This method is useful for characterizing high-molecular-weight proteins that are difficult to detect by top-down proteomics (TDP), in which intact proteins are analyzed by MS. In this study, we applied GeLC-FAIMS-MS, a multidimensional separation workflow that combines gel-based prefractionation with LC-FAIMS MS, for deep MDP. Middle-down peptides generated by optimized limited Glu-C digestion conditions were first size-fractionated by polyacrylamide gel electrophoresis, followed by C4 reversed-phase liquid chromatography separation and additional ion mobility fractionation, resulting in a significant increase in peptide length detectable by MS. In addition to global analysis, the GeLC-FAIMS-MS concept can also be applied to targeted MDP, where only proteins in the desired molecular weight range are gel-fractionated and their Glu-C digestion products are analyzed, as demonstrated by targeted analysis of integrins in exosomes. In-depth MDP achieved by global and targeted GeLC-FAIMS-MS supports the exploration of proteoform information not covered by conventional TDP by increasing the number of detectable protein groups or post-translational modifications (PTMs) and improving the sequence coverage.

Top-down ion mobility/mass spectrometry reveals enzyme specificity: Separation and sequencing of isomeric proteoforms

Enzymatic catalysis is one of the fundamental processes that drives the dynamic landscape of post-translational modifications (PTMs), expanding the structural and functional diversity of proteins. Here, we assessed enzyme specificity using a top-down ion mobility spectrometry (IMS) and tandem mass spectrometry (MS/MS) workflow. We successfully applied trapped IMS (TIMS) to investigate site-specific N-ε-acetylation of lysine residues of full-length histone H4 catalyzed by histone lysine acetyltransferase KAT8. We demonstrate that KAT8 exhibits a preference for N-ε-acetylation of residue K16, while also adding acetyl groups on residues K5 and K8 as the first degree of acetylation. Achieving TIMS resolving power values of up to 300, we fully separated mono-acetylated regioisomers (H4K5ac, H4K8ac, and H4K16ac). Each of these separated regioisomers produce unique MS/MS fragment ions, enabling estimation of their individual mobility distributions and the exact localization of the N-ε-acetylation sites. This study highlights the potential of top-down TIMS-MS/MS for conducting enzymatic assays at the intact protein level and, more generally, for separation and identification of intact isomeric proteoforms and precise PTM localization.

Capillary zone electrophoresis-high field asymmetric ion mobility spectrometry-tandem mass spectrometry for top-down characterization of histone proteoforms

Characterization of histone proteoforms with various post-translational modifications (PTMs) is critical for a better understanding of functions of histone proteoforms in epigenetic control of gene expression. Mass spectrometry (MS)-based top-down proteomics (TDP) is a valuable approach for delineating histone proteoforms because it can provide us with a bird's-eye view of histone proteoforms carrying diverse combinations of PTMs. Here, we present the first example of coupling capillary zone electrophoresis (CZE), ion mobility spectrometry (IMS), and MS for online multi-dimensional separations of histone proteoforms. Our CZE-high-field asymmetric waveform IMS (FAIMS)-MS/MS platform identified 366 (ProSight PD) and 602 (TopPIC) histone proteoforms from a commercial calf histone sample using a low microgram amount of histone sample as the starting material. CZE-FAIMS-MS/MS improved the number of histone proteoform identifications by about 3 folds compared to CZE-MS/MS alone (without FAIMS). The results indicate that CZE-FAIMS-MS/MS could be a useful tool for comprehensive characterization of histone proteoforms with high sensitivity.

Top/Middle-Down Characterization of α-Synuclein Glycoforms

α-Synuclein is an intrinsically disordered protein that plays a critical role in the pathogenesis of neurodegenerative disorders, such as Parkinson's disease. Proteomics studies of human brain samples have associated the modification of the O-linked N-acetyl-glucosamine (O-GlcNAc) to several synucleinopathies; in particular, the position of the O-GlcNAc can regulate protein aggregation and subsequent cell toxicity. There is a need for site specific O-GlcNAc α-synuclein screening tools to direct better therapeutic strategies. In the present work, for the first time, the potential of fast, high-resolution trapped ion mobility spectrometry (TIMS) preseparation in tandem with mass spectrometry assisted by an electromagnetostatic (EMS) cell, capable of electron capture dissociation (ECD), and ultraviolet photodissociation (213 nm UVPD) is illustrated for the characterization of α-synuclein positional glycoforms: T72, T75, T81, and S87 modified with a single O-GlcNAc. Top-down 213 nm UVPD and ECD MS/MS experiments of the intact proteoforms showed specific product ions for each α-synuclein glycoforms associated with the O-GlcNAc position with a sequence coverage of ∼68 and ∼82%, respectively. TIMS-MS profiles of α-synuclein and the four glycoforms exhibited large structural heterogeneity and signature patterns across the 8+-15+ charge state distribution; however, while the α-synuclein positional glycoforms showed signature mobility profiles, they were only partially separated in the mobility domain. Moreover, a middle-down approach based on the Val40-Phe94 (55 residues) chymotrypsin proteolytic product using tandem TIMS-q-ECD-TOF MS/MS permitted the separation of the parent positional isomeric glycoforms. The ECD fragmentation of the ion mobility and m/z separated isomeric Val40-Phe94 proteolytic peptides with single O-GlcNAc in the T72, T75, T81, and S87 positions provided the O-GlcNAc confirmation and positional assignment with a sequence coverage of ∼80%. This method enables the high-throughput screening of positional glycoforms and further enhances the structural mass spectrometry toolbox with fast, high-resolution mobility separations and 213 nm UVPD and ECD fragmentation capabilities.

Top-Down Ion Mobility Separations of Isomeric Proteoforms

Continuing advances in proteomics highlight the ubiquity and biological importance of proteoforms─proteins with varied sequence, splicing, or distribution of post-translational modifications (PTMs). The preeminent example is histones, where the PTM pattern encodes the combinatorial language controlling the DNA transcription central to life. While the proteoforms with distinct PTM compositions are distinguishable by mass, the isomers with permuted PTMs commonly coexisting in cells generally require separation before mass-spectrometric (MS) analyses. That was accomplished on the bottom-up and middle-down levels using chromatography or ion mobility spectrometry (IMS), but proteolytic digestion obliterates the crucial PTM connectivity information. Here, we demonstrate baseline IMS resolution of intact isomeric proteoforms, specifically the acetylated H4 histones (11.3 kDa). The proteoforms with a single acetyl moiety on five alternative lysine residues (K5, K8, K12, K16, K20) known for distinct functionalities in vivo were constructed by two-step native chemical ligation and separated using trapped IMS at the resolving power up to 350 on the Bruker TIMS/ToF platform. Full resolution for several pairs was confirmed using binary mixtures and by unique fragments in tandem MS employing collision-induced dissociation. This novel capability for top-down proteoform characterization is poised to open major new avenues in proteomics and epigenetics.

Top-"Double-Down" Mass Spectrometry of Histone H4 Proteoforms: Tandem Ultraviolet-Photon and Mobility/Mass-Selected Electron Capture Dissociations

Post-translational modifications (PTMs) on intact histones play a major role in regulating chromatin dynamics and influence biological processes such as DNA transcription, replication, and repair. The nature and position of each histone PTM is crucial to decipher how this information is translated into biological response. In the present work, the potential of a novel tandem top-"double-down" approach─ultraviolet photodissociation followed by mobility and mass-selected electron capture dissociation and mass spectrometry (UVPD-TIMS-q-ECD-ToF MS/MS)─is illustrated for the characterization of HeLa derived intact histone H4 proteoforms. The comparison between q-ECD-ToF MS/MS spectra and traditional Fourier-transform-ion cyclotron resonance-ECD MS/MS spectra of a H4 standard showed a similar sequence coverage (∼75%) with significant faster data acquisition in the ToF MS/MS platform (∼3 vs ∼15 min). Multiple mass shifts (e.g., 14 and 42 Da) were observed for the HeLa derived H4 proteoforms for which the top-down UVPD and ECD fragmentation analysis were consistent in detecting the presence of acetylated PTMs at the N-terminus and Lys5, Lys8, Lys12, and Lys16 residues, as well as methylated, dimethylated, and trimethylated PTMs at the Lys20 residue with a high sequence coverage (∼90%). The presented top-down results are in good agreement with bottom-up TIMS ToF MS/MS experiments and allowed for additional description of PTMs at the N-terminus. The integration of a 213 nm UV laser in the present platform allowed for UVPD events prior to the ion mobility-mass precursor separation for collision-induced dissociation (CID)/ECD-ToF MS. Selected c305+ UVPD fragments, from different H4 proteoforms (e.g., Ac + Me2, 2Ac + Me2 and 3Ac + Me2), exhibited multiple IMS bands for which similar CID/ECD fragmentation patterns per IMS band pointed toward the presence of conformers, adopting the same PTM distribution, with a clear assignment of the PTM localization for each of the c305+ UVPD fragment H4 proteoforms. These results were consistent with the biological "zip" model, where acetylation proceeds in the Lys16 to Lys5 direction. This novel platform further enhances the structural toolbox with alternative fragmentation mechanisms (UVPD, CID, and ECD) in tandem with fast, high-resolution mobility separations and shows great promise for global proteoform analysis.

An experimental design to extract more information from MS-based histone studies

Histone-based chromatin organization paved the way for eukaryotic genome complexity. Because of their key role in information management, the histone posttranslational modifications (hPTM), which mediate their function, have evolved into an alphabet that has more letters than there are amino acids, together making up the "histone code". The resulting combinatorial complexity is manifold higher than what is usually encountered in proteomics. Consequently, a considerably bigger part of the acquired MSMS spectra remains unannotated to date. Adapted search parameters can dig deeper into the dark histone ion space, but the lack of false discovery rate (FDR) control and the high level of ambiguity when searching combinatorial PTMs makes it very hard to assess whether the newly assigned ions are informative. Therefore, we propose an easily adoptable time-lapse enzymatic deacetylation (HDAC1) of a commercial histone extract as a quantify-first strategy that allows isolating ion populations of interest, when studying e.g. acetylation on histones, that currently remain in the dark. By adapting search parameters to study potential issues in sample preparation, data acquisition and data analysis, we stepwise managed to double the portion of annotated precursors of interest from 10.5% to 21.6%. This strategy is intended to make up for the lack of validated FDR control and has led to several adaptations of our current workflow that will reduce the portion of the dark histone ion space in the future. Finally, this strategy can be applied with any enzyme targeting a modification of interest.

Chemical biology approaches to study histone interactors

Protein-protein interactions (PPIs) in the nucleus play key roles in transcriptional regulation and ensure genomic stability. Critical to this are histone-mediated PPI networks, which are further fine-tuned through dynamic post-translational modification. Perturbation to these networks leads to genomic instability and disease, presenting epigenetic proteins as key therapeutic targets. This mini-review will describe progress in mapping the combinatorial histone PTM landscape, and recent chemical biology approaches to map histone interactors. Recent advances in mapping direct interactors of histone PTMs as well as local chromatin interactomes will be highlighted, with a focus on mass-spectrometry based workflows that continue to illuminate histone-mediated PPIs in unprecedented detail.

Predicting differential ion mobility behaviour in silico using machine learning

Although there has been a surge in popularity of differential mobility spectrometry (DMS) within analytical workflows, determining separation conditions within the DMS parameter space still requires manual optimization. A means of accurately predicting differential ion mobility would benefit practitioners by significantly reducing the time associated with method development. Here, we report a machine learning (ML) approach that predicts dispersion curves in an N2 environment, which are the compensation voltages (CVs) required for optimal ion transmission across a range of separation voltages (SVs) between 1500 to 4000 V. After training a random-forest based model using the DMS information of 409 cationic analytes, dispersion curves were reproduced with a mean absolute error (MAE) of ≤ 2.4 V, approaching typical experimental peak FWHMs of ±1.5 V. The predictive ML model was trained using only m/z and ion-neutral collision cross section (CCS) as inputs, both of which can be obtained from experimental databases before being extensively validated. By updating the model via inclusion of two CV datapoints at lower SVs (1500 V and 2000 V) accuracy was further improved to MAE ≤ 1.2 V. This improvement stems from the ability of the "guided" ML routine to accurately capture Type A and B behaviour, which was exhibited by only 2% and 17% of ions, respectively, within the dataset. Dispersion curve predictions of the database's most common Type C ions (81%) using the unguided and guided approaches exhibited average errors of 0.6 V and 0.1 V, respectively.

Determining Collision Cross Sections from Differential Ion Mobility Spectrometry

The experimental determination of ion-neutral collision cross sections (CCSs) is generally confined to ion mobility spectrometry (IMS) technologies that operate under the so-called low-field limit or those that enable empirical calibration strategies (e.g., traveling wave IMS; TWIMS). Correlation of ion trajectories to CCS in other non-linear IMS techniques that employ dynamic electric fields, such as differential mobility spectrometry (DMS), has remained a challenge since its inception. Here, we describe how an ion's CCS can be measured from DMS experiments using a machine learning (ML)-based calibration. The differential mobility of 409 molecular cations (m/z: 86-683 Da and CCS 110-236 Å2) was measured in a N2 environment to train the ML framework. Several open-source ML routines were tested and trained using DMS-MS data in the form of the parent ion's m/z and the compensation voltage required for elution at specific separation voltages between 1500 and 4000 V. The best performing ML model, random forest regression, predicted CCSs with a mean absolute percent error of 2.6 ± 0.4% for analytes excluded from the training set (i.e., out-of-the-bag external validation). This accuracy approaches the inherent statistical error of ∼2.2% for the MobCal-MPI CCS calculations employed for training purposes and the <2% threshold for matching literature CCSs with those obtained on a TWIMS platform.

Combinatorial Histone H3 Modifications Are Dynamically Altered in Distinct Cell Cycle Phases

The cell cycle is a highly regulated and evolutionary conserved process that results in the duplication of cell content and the equal distribution of the duplicated chromosomes into a pair of daughter cells. Histones are fundamental structural components of chromatin in eukaryotic cells, and their post-translational modifications (PTMs) benchmark DNA readout and chromosome condensation. Aberrant regulation of the cell cycle associated with dysregulation of histone PTMs is the cause of critical diseases such as cancer. Monitoring changes of histone PTMs could pave the way to understanding the molecular mechanisms associated with epigenetic regulation of cell proliferation. Previously, our lab established a novel middle-down workflow using porous graphitic carbon (PGC) as a stationary phase to analyze histone PTMs, which utilizes the same reversed-phase chromatography for gradient separation as canonical proteomics coupled with online mass spectrometry (MS). Here, we applied this novel workflow for high-throughput analysis of histone modifications of H3.1 and H3.2 during the cell cycle. Collectively, we identified 1133 uniquely modified canonical histone H3 N-terminal tails. Consistent with previous findings, histone H3 phosphorylation increased significantly during the mitosis (M) phase. Histone H3 variant-specific and cell-cycle-dependent expressions of PTMs were observed, underlining the need to not combine H3.1 and H3.2 together as H3. We confirmed previously known H3 PTM crosstalk (e.g., K9me-S10ph) and revealed new information in this area as well. These findings imply that the combinatorial PTMs play a role in cell cycle control, and they may serve as markers for proliferation.

The Charge-State and Structural Stability of Peptides Conferred by Microsolvating Environments in Differential Mobility Spectrometry

The presence of solvent vapor in a differential mobility spectrometry (DMS) cell creates a microsolvating environment that can mitigate complications associated with field-induced heating. In the case of peptides, the microsolvation of protonation sites results in a stabilization of charge density through localized solvent clustering, sheltering the ion from collisional activation. Seeding the DMS carrier gas (N₂) with a solvent vapor prevented nearly all field-induced fragmentation of the protonated peptides GGG, AAA, and the Lys-rich Polybia-MP1 (IDWKKLLDAAKQIL-NH₂). Modeling the microsolvation propensity of protonated n-propylamine [PrNH₃]⁺, a mimic of the Lys side chain and N-terminus, with common gas-phase modifiers (H₂O, MeOH, EtOH, iPrOH, acetone, and MeCN) confirms that all solvent molecules form stable clusters at the site of protonation. Moreover, modeling populations of microsolvated clusters indicates that species containing protonated amine moieties exist as microsolvated species with one to six solvent ligands at all effective ion temperatures (T_eff) accessible during a DMS experiment (ca. 375-600 K). Calculated T_eff of protonated GGG, AAA, and Polybia-MPI using a modified two-temperature theory approach were up to 86 K cooler in DMS environments seeded with solvent vapor compared to pure N₂ environments. Stabilizing effects were largely driven by an increase in the ion's apparent collision cross section and by evaporative cooling processes induced by the dynamic evaporation/condensation cycles incurred in the presence of an oscillating electric separation field. When the microsolvating partner was a protic solvent, abstraction of a proton from [MP1 + 3H]³⁺ to yield [MP1 + 2H]²⁺ was observed. This result was attributed to the proclivity of protic solvents to form hydrogen-bond networks with enhanced gas-phase basicity. Collectively, microsolvation provides analytes with a solvent "air bag," whereby charge reduction and microsolvation-induced stabilization were shown to shelter peptides from the fragmentation induced by field heating and may play a role in preserving native-like ion configurations.

Misincorporation Proteomics Technologies: A Review

Proteinopathies are diseases caused by factors that affect proteoform conformation. As such, a prevalent hypothesis is that the misincorporation of noncanonical amino acids into a proteoform results in detrimental structures. However, this hypothesis is missing proteomic evidence, specifically the detection of a noncanonical amino acid in a peptide sequence. This review aims to outline the current state of technology that can be used to investigate mistranslations and misincorporations whilst framing the pursuit as Misincorporation Proteomics (MiP). The current availability of technologies explored herein is mass spectrometry, sample enrichment/preparation, data analysis techniques, and the hyphenation of approaches. While many of these technologies show potential, our review reveals a need for further development and refinement of approaches is still required.

Integrating ion mobility and imaging mass spectrometry for comprehensive analysis of biological tissues: A brief review and perspective

Imaging mass spectrometry (IMS) technologies are capable of mapping a wide array of biomolecules in diverse cellular and tissue environments. IMS has emerged as an essential tool for providing spatially targeted molecular information due to its high sensitivity, wide molecular coverage, and chemical specificity. One of the major challenges for mapping the complex cellular milieu is the presence of many isomers and isobars in these samples. This challenge is traditionally addressed using orthogonal liquid chromatography (LC)-based analysis, though, common approaches such as chromatography and electrophoresis are not able to be performed at timescales that are compatible with most imaging applications. Ion mobility offers rapid, gas-phase separations that are readily integrated with IMS workflows in order to provide additional data dimensionality that can improve signal-to-noise, dynamic range, and specificity. Here, we highlight recent examples of ion mobility coupled to IMS and highlight their importance to the field.

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.