Lombard-Banek C , Reddy S , Moody SA , Nemes P .

	Fig. 1. Flowchart for enabling label-free quantification (LFQ) on limited amounts of tissues and single embryonic cells in the 16-cell frog Xenopus laevis embryo. Check-points serve as feed-back mechanism to aid LFQ sensitivity. LFQ was performed to quantify protein expression between n = 3 midline dorsal-animal (D11) blastomeres, which reproducibly give rise to the nervous system (41). Scale bar = 100um.
	Fig. 2. Trace-level separation and quantification of peptides using CE-μESI-HRMS.A, Quantification was demonstrated across a 3 log-order dynamic range with a ∼75-amol estimated lower limit of detection for Met-Enk. B, The base-peak electropherogram for a 20 ng digest of a 16-cell Xenopus embryo demonstrated complex molecular composition. The extracted-ion currents monitor 9 different peptides (mers) with ± 50-mDa window that were identified from vitellogenin b1 (vtgb1), an abundant, native protein in the embryo (see peptide sequences in supplemental Table S1A. C, Peptide detection was quantitative also in this complex matrix, as exemplified for the vtgb110-mer2+, vtgb113-mer2+, and vtgb128-mer4+ signals. Error bars show S.E.M. in all panels. Parameters of linear regression (intercept/slope/R2): 4.52/1.07/0.99 for Met-Enk; 4.94/0.815/0.98 for vtgb110-mer2+; 5.07/0.730/0.99 for vtgb113-mer2+; and 4.33/0.861/0.96 for vtgb128-mer4+.
	Fig. 3. Sequencing trace-level peptides by CE-HRMS using Qq time-of-flight HRMS.A, Data-dependent tandem MS was tailored to closely migrating (top panel) and low-abundance peptide signals (bottom panel). Key: Δ, separation time difference between consecutively migrating peptides. B, Rate of fragmented molecular features (data in open circles) and identified peptides (data in filled circles) revealing compact separation and electrophoretic migration trends in the mass versus migration time versus charge state domain. Identified proteins are listed in supplemental Table S1B.
	Fig. 4. Identifying and quantifying protein groups in mass-limited specimens.A, Proteins were measured in progressively smaller amounts of digests from whole 16-cell Xenopus embryos using Qq-TOF-MS/MS (top panel). LFQ-based quantification was linear also at the level of proteins (bottom panel), as shown for Vtgb1 (R2 = 0.99), Ppia (R2 = 0.98), and Lipo 1 (R2 = 0.90). Using an orbitrap-quadrupole-linear ion trap (q-OT-LIT) instrument capable of ion trapping, higher-resolution analysis, and parallelization of MS1-MS/MS events, protein identification was enhanced fivefold. Quantified proteins are listed for the Qq-TOF in supplemental Table S1C and q-OT-LIT in supplemental Table S1D. Error bars show S.E.M. B, Gene ontology annotation of biological processes (top panel) and molecular functions (bottom panel) for proteins identified in the 16-cell embryo.
	Fig. 5. Correlation analysis for uncovering translational differences between three D11 blastomeres (D111, D112, D113) and the 16-cell embryo. Each data point represents a different protein group. A, LFQ intensities of proteins were reproducibly quantified between technical replicates (D112 shown, left panel), as indicated by high Pearson correlation coefficients (ρ) between the data sets. Prediction band with 95% confidence is shown in gray surrounding the linear fit. For any given protein (see mock protein in gray square), correlation was calculated as the Euclidean distance (d) from the linear fit. Based on the technical reproducibility, a d > 0.5 was considered to mark significant dysregulation in protein abundance (middle panel). LFQ intensities were repeatable with ∼20% relative standard deviation (RSD); therefore, a fold change of ≥1.5 was chosen to mark biological significance (right panel). B, Comparison of protein expression between the D11 cells and the whole 16-cell embryo revealing accumulation for 17 proteins in the cells and eight proteins in the average embryo (left panel). Using correlation distance and median-normalized fold change to query differentially expressed proteins (right panel). C, Correlation analysis also revealed graded translational differences between the D11 blastomeres (left panel). Categorization of protein expresion as stable and variable (see Table II) based on d values (right panel). Key: ρ = 0.72 for D111versus embryo, 0.76 for D112versus embryo, 0.61 for D112versus embryo, 0.61 for D111versus D112, 0.75 for D111versus D113, and 0.73 for D112versus D113. Vitellogenin proteins (LFQ intensity > ∼1 × 109) were excluded from the analysis and are not shown.
	Fig. 6. Protein interaction networks in single D11 blastomeres. Networks were predicted using STRING 10 based on proteins with (A) stable (d <= 0.5) and (B) variable (d > 0.5) abundance between the blastomeres. KEGG functions are labeled for proteins with associations. Among the differentially quantified proteins were many that are known to express in the neural plate, eye, head, nervous tissue, heart, or tail-bud of the embryo (see underlined proteins). An enlarged network is shown for stable proteins in supplemental Fig. S3. STRING parameters: actions view shown; disconnected nodes removed (Atic, Cirbp-p, and Vtga1 in panel B); k-means clustering = 3.

Abe, Xenopus laevis actin-depolymerizing factor/cofilin: a phosphorylation-regulated protein essential for development. 1996, Pubmed, Xenbase

Abe, Xenopus laevis actin-depolymerizing factor/cofilin: a phosphorylation-regulated protein essential for development. 1996, Pubmed , Xenbase
Aerts, Patch clamp electrophysiology and capillary electrophoresis-mass spectrometry metabolomics for single cell characterization. 2014, Pubmed
Altschuler, Cellular heterogeneity: do differences make a difference? 2010, Pubmed
Beck, The Impact II, a Very High-Resolution Quadrupole Time-of-Flight Instrument (QTOF) for Deep Shotgun Proteomics. 2015, Pubmed
Bendall, Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. 2011, Pubmed
Bonvin, Capillary electrophoresis-electrospray ionization-mass spectrometry interfaces: fundamental concepts and technical developments. 2012, Pubmed
Breadmore, Recent advances in enhancing the sensitivity of electrophoresis and electrochromatography in capillaries and microchips (2012-2014). 2015, Pubmed
Buchberger, Advances in Mass Spectrometric Tools for Probing Neuropeptides. 2015, Pubmed
Collart, High-resolution analysis of gene activity during the Xenopus mid-blastula transition. 2014, Pubmed , Xenbase
Cox, Andromeda: a peptide search engine integrated into the MaxQuant environment. 2011, Pubmed
Cox, MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. 2008, Pubmed
Cox, Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. 2014, Pubmed
De Domenico, Molecular asymmetry in the 8-cell stage Xenopus tropicalis embryo described by single blastomere transcript sequencing. 2015, Pubmed , Xenbase
Eisenberg, Human housekeeping genes are compact. 2003, Pubmed
Flachsova, Single blastomere expression profiling of Xenopus laevis embryos of 8 to 32-cells reveals developmental asymmetry. 2013, Pubmed , Xenbase
Giesen, Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry. 2014, Pubmed
Grant, Blastomere explants to test for cell fate commitment during embryonic development. 2013, Pubmed , Xenbase
Han, Sheathless capillary electrophoresis-tandem mass spectrometry for top-down characterization of Pyrococcus furiosus proteins on a proteome scale. 2014, Pubmed
Hebert, The one hour yeast proteome. 2014, Pubmed
Hofstadler, Analysis of single cells with capillary electrophoresis electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. 1996, Pubmed
Hofstadler, Capillary electrophoresis-electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry for direct analysis of cellular proteins. 1995, Pubmed
James-Zorn, Xenbase: Core features, data acquisition, and data processing. 2015, Pubmed , Xenbase
Jorgensen, The mechanism and pattern of yolk consumption provide insight into embryonic nutrition in Xenopus. 2009, Pubmed , Xenbase
Karpinka, Xenbase, the Xenopus model organism database; new virtualized system, data types and genomes. 2015, Pubmed , Xenbase
Kitagawa, Recent applications of on-line sample preconcentration techniques in capillary electrophoresis. 2014, Pubmed
Kler, Column-coupling strategies for multidimensional electrophoretic separation techniques. 2015, Pubmed
Lanni, Mass spectrometry imaging and profiling of single cells. 2012, Pubmed
Lombard-Banek, Single-Cell Mass Spectrometry for Discovery Proteomics: Quantifying Translational Cell Heterogeneity in the 16-Cell Frog (Xenopus) Embryo. 2016, Pubmed , Xenbase
Lomeli, New reagents for increasing ESI multiple charging of proteins and protein complexes. 2010, Pubmed
Ludwig, Over 2300 phosphorylated peptide identifications with single-shot capillary zone electrophoresis-tandem mass spectrometry in a 100 min separation. 2015, Pubmed
Macosko, Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets. 2015, Pubmed
McAlister, MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. 2014, Pubmed
Mellors, Integrated microfluidic device for automated single cell analysis using electrophoretic separation and electrospray ionization mass spectrometry. 2010, Pubmed
Moini, Simplifying CE-MS operation. 2. Interfacing low-flow separation techniques to mass spectrometry using a porous tip. 2007, Pubmed
Moody, Fates of the blastomeres of the 16-cell stage Xenopus embryo. 1987, Pubmed , Xenbase
Nagaraj, System-wide perturbation analysis with nearly complete coverage of the yeast proteome by single-shot ultra HPLC runs on a bench top Orbitrap. 2012, Pubmed
Nemes, Metabolic differentiation of neuronal phenotypes by single-cell capillary electrophoresis-electrospray ionization-mass spectrometry. 2011, Pubmed
Nemes, Spraying mode effect on droplet formation and ion chemistry in electrosprays. 2007, Pubmed
Nemes, Qualitative and quantitative metabolomic investigation of single neurons by capillary electrophoresis electrospray ionization mass spectrometry. 2013, Pubmed , Xenbase
Ong, Classification of Large Cellular Populations and Discovery of Rare Cells Using Single Cell Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry. 2015, Pubmed
Onjiko, Single-cell mass spectrometry reveals small molecules that affect cell fates in the 16-cell embryo. 2015, Pubmed , Xenbase
Onjiko, Single-cell mass spectrometry with multi-solvent extraction identifies metabolic differences between left and right blastomeres in the 8-cell frog (Xenopus) embryo. 2016, Pubmed , Xenbase
Pan, The single-probe: a miniaturized multifunctional device for single cell mass spectrometry analysis. 2014, Pubmed
Peshkin, On the Relationship of Protein and mRNA Dynamics in Vertebrate Embryonic Development. 2015, Pubmed , Xenbase
Picotti, A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis. 2013, Pubmed
Rubakhin, Profiling metabolites and peptides in single cells. 2011, Pubmed , Xenbase
Rubakhin, Progress toward single cell metabolomics. 2013, Pubmed
Singh, Patterns of basal signaling heterogeneity can distinguish cellular populations with different drug sensitivities. 2010, Pubmed
Sterling, Protein conformation and supercharging with DMSO from aqueous solution. 2011, Pubmed
Sun, Integrated capillary zone electrophoresis-electrospray ionization tandem mass spectrometry system with an immobilized trypsin microreactor for online digestion and analysis of picogram amounts of RAW 264.7 cell lysate. 2013, Pubmed
Sun, Capillary zone electrophoresis for bottom-up analysis of complex proteomes. 2016, Pubmed
Sun, Ultrasensitive and fast bottom-up analysis of femtogram amounts of complex proteome digests. 2013, Pubmed
Sun, Over 10,000 peptide identifications from the HeLa proteome by using single-shot capillary zone electrophoresis combined with tandem mass spectrometry. 2014, Pubmed
Sun, Quantitative proteomics of Xenopus laevis embryos: expression kinetics of nearly 4000 proteins during early development. 2014, Pubmed , Xenbase
Sun, Third-generation electrokinetically pumped sheath-flow nanospray interface with improved stability and sensitivity for automated capillary zone electrophoresis-mass spectrometry analysis of complex proteome digests. 2015, Pubmed , Xenbase
Svatoš, Single-cell metabolomics comes of age: new developments in mass spectrometry profiling and imaging. 2011, Pubmed
Szklarczyk, STRING v10: protein-protein interaction networks, integrated over the tree of life. 2015, Pubmed
UniProt Consortium, UniProt: a hub for protein information. 2015, Pubmed
Valaskovic, Attomole protein characterization by capillary electrophoresis-mass spectrometry. 1996, Pubmed
Virant-Klun, Identification of Maturation-Specific Proteins by Single-Cell Proteomics of Human Oocytes. 2016, Pubmed
Vizcaíno, The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013. 2013, Pubmed
Wang, Improving the comprehensiveness and sensitivity of sheathless capillary electrophoresis-tandem mass spectrometry for proteomic analysis. 2012, Pubmed
Whitt, Capillary electrophoresis to mass spectrometry interface using a porous junction. 2003, Pubmed
Wühr, The Nuclear Proteome of a Vertebrate. 2015, Pubmed , Xenbase
Wühr, Deep proteomics of the Xenopus laevis egg using an mRNA-derived reference database. 2014, Pubmed , Xenbase
Ye, Probing neuropeptide signaling at the organ and cellular domains via imaging mass spectrometry. 2012, Pubmed
Zenobi, Single-cell metabolomics: analytical and biological perspectives. 2013, Pubmed
Zhang, Nearly 1000 Protein Identifications from 50 ng of Xenopus laevis Zygote Homogenate Using Online Sample Preparation on a Strong Cation Exchange Monolith Based Microreactor Coupled with Capillary Zone Electrophoresis. 2016, Pubmed , Xenbase
Zhang, Protein analysis by shotgun/bottom-up proteomics. 2013, Pubmed