PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-12 (12)
 

Clipboard (0)
None

Select a Filter Below

Journals
Year of Publication
Document Types
1.  A platinum-based covalent viability reagent for single cell mass cytometry 
In fluorescence-based flow cytometry, cellular viability is determined with membrane-impermeable fluorescent reagents that specifically enter and label plasma membrane-compromised non-viable cells. A recent technological advance in flow cytometry uses antibodies conjugated to elemental metal isotopes, rather than to fluorophores, to allow signal detection by atomic mass spectrometry. Unhampered by the limitations of overlapping emission fluorescence, mass cytometry increases the number of parameters that can be measured in single cells. However, mass cytometry is unable to take advantage of current fluorescent viability dyes. An alternative methodology was therefore developed here in which the platinum-containing chemotherapy drug cisplatin was used to label cells for mass cytometry determinations of live/dead ratios. In a one-minute incubation step, cisplatin preferentially labeled non-viable cells, from both adherent and suspension cultures, resulting in a platinum signal quantifiable by mass cytometry. This protocol was compatible with established sample processing steps for cytometry. Furthermore, the live/dead ratios were comparable between mass and fluorescence based cytometry. Importantly, although cisplatin is a known DNA-damaging agent, a one-minute “pulse” of cisplatin did not induce observable DNA damage or apoptotic responses even within 6 hours post-exposure. Cisplatin can therefore be used as a viability reagent for a wide range of mass cytometry protocols.
doi:10.1002/cyto.a.22067
PMCID: PMC3808967  PMID: 22577098
Mass cytometry; cisplatin; viability reagent
2.  Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators 
Nature biotechnology  2012;30(9):858-867.
The ability to comprehensively explore the impact of bio-active molecules on human samples at the single-cell level can provide great insight for biomedical research. Mass cytometry enables quantitative single-cell analysis with deep dimensionality, but currently lacks high-throughput capability. Here we report a method termed mass-tag cellular barcoding (MCB) that increases mass cytometry throughput by sample multiplexing. 96-well format MCB was used to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics, cell-to-cell communication, the signaling variability between 8 donors, and to define the impact of 27 inhibitors on this system. For each compound, 14 phosphorylation sites were measured in 14 PBMC types, resulting in 18,816 quantified phosphorylation levels from each multiplexed sample. This high-dimensional systems-level inquiry allowed analysis across cell-type and signaling space, reclassified inhibitors, and revealed off-target effects. MCB enables high-content, high-throughput screening, with potential applications for drug discovery, pre-clinical testing, and mechanistic investigation of human disease.
doi:10.1038/nbt.2317
PMCID: PMC3627543  PMID: 22902532
3.  Phosphoproteomic Analysis Reveals Interconnected System-Wide Responses to Perturbations of Kinases and Phosphatases in Yeast 
Science signaling  2010;3(153):rs4.
The phosphorylation and dephosphorylation of proteins by kinases and phosphatases constitute an essential regulatory network in eukaryotic cells. This network supports the flow of information from sensors through signaling systems to effector molecules, and ultimately drives the phenotype and function of cells, tissues, and organisms. Dysregulation of this process has severe consequences and is one of the main factors in the emergence and progression of diseases, including cancer. Thus, major efforts have been invested in developing specific inhibitors that modulate the activity of individual kinases or phosphatases; however, it has been difficult to assess how such pharmacological interventions would affect the cellular signaling network as a whole. Here, we used label-free, quantitative phosphoproteomics in a systematically perturbed model organism (Saccharomyces cerevisiae) to determine the relationships between 97 kinases, 27 phosphatases, and more than 1000 phosphoproteins. We identified 8814 regulated phosphorylation events, describing the first system-wide protein phosphorylation network in vivo. Our results show that, at steady state, inactivation of most kinases and phosphatases affected large parts of the phosphorylation-modulated signal transduction machinery, and not only the immediate downstream targets. The observed cellular growth phenotype was often well maintained despite the perturbations, arguing for considerable robustness in the system. Our results serve to constrain future models of cellular signaling and reinforce the idea that simple linear representations of signaling pathways might be insufficient for drug development and for describing organismal homeostasis.
doi:10.1126/scisignal.2001182
PMCID: PMC3072779  PMID: 21177495
4.  Rewiring of Genetic Networks in Response to DNA Damage 
Science (New York, N.Y.)  2010;330(6009):1385-1389.
Although cellular behaviors are dynamic, the networks that govern these behaviors have been mapped primarily as static snapshots. Using an approach called differential epistasis mapping, we have discovered widespread changes in genetic interaction among yeast kinases, phosphatases, and transcription factors as the cell responds to DNA damage. Differential interactions uncover many gene functions that go undetected in static conditions. They are very effective at identifying DNA repair pathways, highlighting new damage-dependent roles for the Slt2 kinase, Pph3 phosphatase, and histone variant Htz1. The data also reveal that protein complexes are generally stable in response to perturbation, but the functional relations between these complexes are substantially reorganized. Differential networks chart a new type of genetic landscape that is invaluable for mapping cellular responses to stimuli.
doi:10.1126/science.1195618
PMCID: PMC3006187  PMID: 21127252
5.  Orm family proteins mediate sphingolipid homeostasis 
Nature  2010;463(7284):1048-1053.
Despite the essential roles of sphingolipids as both structural components of membranes and critical signalling molecules, we have a limited understanding of how cells sense and regulate their levels. Here we reveal the function in sphingolipid metabolism of the ORM/ORMDL genes, a conserved gene family that includes ORMDL3, which has recently been identified as a potential risk factor for childhood asthma. Starting from an unbiased functional genomic approach, we identify Orm proteins as negative regulators of sphingolipid synthesis that form a conserved complex with serine palmitoyltransferase, the first and rate-limiting enzyme in sphingolipid production. We also define a regulatory pathway in which phosphorylation of Orm proteins relieves their inhibitory activity when sphingolipid production is disrupted. Changes in ORM gene expression or mutations to their phosphorylation sites cause dysregulation of sphingolipid metabolism. Our work identifies the Orm proteins as critical mediators of sphingolipid homeostasis and raises the possibility that sphingolipid misregulation contributes to the development of childhood asthma.
doi:10.1038/nature08787
PMCID: PMC2877384  PMID: 20182505
6.  Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics 
Cell  2009;138(4):795-806.
Summary
The rise of systems biology implied a growing demand for highly sensitive techniques for the fast and consistent detection and quantification of target sets of proteins across multiple samples. This is only partly achieved by classical mass spectrometry or affinity-based methods. We applied a targeted proteomics approach based on selected reaction monitoring (SRM) to detect and quantify proteins expressed to a concentration below 50 copies/cell in total S. cerevisiae digests. The detection range can be extended to single-digit copies/cell and to proteins which were undetected by classical methods. We illustrate the power of the technique by the consistent and fast measurement of a network of proteins spanning the entire abundance range over a growth time-course of S. cerevisiae transiting through a series of metabolic phases. We therefore demonstrate the potential of SRM-based proteomics to provide assays for the measurement of any set of proteins of interest in yeast at high-throughput and quantitative accuracy.
doi:10.1016/j.cell.2009.05.051
PMCID: PMC2825542  PMID: 19664813
targeted proteomics; S. cerevisiae; selected / multiple reaction monitoring; MRM/SRM; dynamic range
7.  Comparison of MS2-only, MSA, and MS2/MS3 Methodologies for Phosphopeptide Identification 
Journal of proteome research  2009;8(2):887-899.
Current mass spectrometers provide a number of alternative methodologies for producing tandem mass spectra specifically for phosphopeptide analysis. In particular, generation of MS3 spectra in a data-dependent manner upon detection of the neutral loss of a phosphoric acid in MS2 spectra is a popular technique for circumventing the problem of poor phosphopeptide backbone fragmentation. The newer Multistage Activation method provides another option. Both these strategies require additional cycle time on the instrument and therefore reduce the number of spectra that can be measured in the same amount of time. Additional informatics is often required to make most efficient use of the additional information provided by these spectra as well. This work presents a comparison of several commonly used mass spectrometry methods for the study of phosphopeptide-enriched samples: an MS2-only method, a Multistage Activation method, and an MS2/MS3 data-dependent neutral loss method. Several strategies for dealing effectively with the resulting MS3 data in the latter approach are also presented and compared. The overall goal is to infer whether any one methodology performs significantly better than another for identifying phosphopeptides. On data presented here, the Multistage Activation methodology is demonstrated to perform optimally and does not result in significant loss of unique peptide identifications.
doi:10.1021/pr800535h
PMCID: PMC2734953  PMID: 19072539
Protein phosphorylation; mass spectrometry; MS3; Multistage Activation; phosphoproteomics; bioinformatics; peptide identification; database search
9.  Regulation of PKD by the MAPK p38δ in Insulin Secretion and Glucose Homeostasis 
Cell  2009;136(2):235-248.
Summary
Dysfunction and loss of insulin-producing pancreatic β cells represent hallmarks of diabetes mellitus. Here, we show that mice lacking the mitogen-activated protein kinase (MAPK) p38δ display improved glucose tolerance due to enhanced insulin secretion from pancreatic β cells. Deletion of p38δ results in pronounced activation of protein kinase D (PKD), the latter of which we have identified as a pivotal regulator of stimulated insulin exocytosis. p38δ catalyzes an inhibitory phosphorylation of PKD1, thereby attenuating stimulated insulin secretion. In addition, p38δ null mice are protected against high-fat-feeding-induced insulin resistance and oxidative stress-mediated β cell failure. Inhibition of PKD1 reverses enhanced insulin secretion from p38δ-deficient islets and glucose tolerance in p38δ null mice as well as their susceptibility to oxidative stress. In conclusion, the p38δ-PKD pathway integrates regulation of the insulin secretory capacity and survival of pancreatic β cells, pointing to a pivotal role for this pathway in the development of overt diabetes mellitus.
doi:10.1016/j.cell.2008.11.018
PMCID: PMC2638021  PMID: 19135240
SIGNALING; CELLBIO; HUMDISEASE
10.  Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics 
BMC Bioinformatics  2008;9:542.
Background
Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics.
Results
We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling.
Conclusion
The Corra computational framework leverages computational innovation to enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field.
doi:10.1186/1471-2105-9-542
PMCID: PMC2651178  PMID: 19087345
11.  Proteomics studies confirm the presence of alternative protein isoforms on a large scale 
Genome Biology  2008;9(11):R162.
Stably expressed alternatively-spliced protein isoforms are produced on a genome-wide scale in Drosophila.
Background
Alternative splicing of messenger RNA permits the formation of a wide range of mature RNA transcripts and has the potential to generate a diverse spectrum of functional proteins. Although there is extensive evidence for large scale alternative splicing at the transcript level, there have been no comparable studies demonstrating the existence of alternatively spliced protein isoforms.
Results
Recent advances in proteomics technology have allowed us to carry out a comprehensive identification of protein isoforms in Drosophila. The analysis of this proteomic data confirmed the presence of multiple alternative gene products for over a hundred Drosophila genes.
Conclusions
We demonstrate that proteomics techniques can detect the expression of stable alternative splice isoforms on a genome-wide scale. Many of these alternative isoforms are likely to have regions that are disordered in solution, and specific proteomics methodologies may be required to identify these peptides.
doi:10.1186/gb-2008-9-11-r162
PMCID: PMC2614494  PMID: 19017398
12.  PhosphoPep—a phosphoproteome resource for systems biology research in Drosophila Kc167 cells 
The ability to analyze and understand the mechanisms by which cells process information is a key question of systems biology research. Such mechanisms critically depend on reversible phosphorylation of cellular proteins, a process that is catalyzed by protein kinases and phosphatases. Here, we present PhosphoPep, a database containing more than 10 000 unique high-confidence phosphorylation sites mapping to nearly 3500 gene models and 4600 distinct phosphoproteins of the Drosophila melanogaster Kc167 cell line. This constitutes the most comprehensive phosphorylation map of any single source to date. To enhance the utility of PhosphoPep, we also provide an array of software tools that allow users to browse through phosphorylation sites on single proteins or pathways, to easily integrate the data with other, external data types such as protein–protein interactions and to search the database via spectral matching. Finally, all data can be readily exported, for example, for targeted proteomics approaches and the data thus generated can be again validated using PhosphoPep, supporting iterative cycles of experimentation and analysis that are typical for systems biology research.
doi:10.1038/msb4100182
PMCID: PMC2063582  PMID: 17940529
data integration; Drosophila; interactive database; phosphoproteomics; systems biology

Results 1-12 (12)