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1.  Quality Control of Danggui Buxue Tang, a Traditional Chinese Medicine Decoction, by 1H-NMR Metabolic Profiling 
Danggui Buxue Tang (DBT) is one of the simplest traditional Chinese medicine (TCM) decoctions, first described in China in 1247 AD. DBT is composed of 2 herbs, Astragali Radix (AR) and Angelica Sinensis Radix (ASR), boiled together in a 5 : 1 ratio. Clinically, DBT is prescribed to women as a remedy for menopausal symptoms. Here, H-NMR metabolic profiling was conducted for DBT and the water extracts of AR or ASR, to evaluate the potential of this chemical profiling method for quality control of the herbal decoction. Principal component analysis (PCA) showed that DBT could be readily distinguished from the water extracts of its constituent herbs by the metabolic profiles. More interestingly, the metabolic profile of DBT was not a simple sum of that of AR and ASR. Asparagine was found at significantly higher concentration in DBT than that in either AR or ASR extract, contributing mainly to the discrimination of DBT sample. In addition, we employed the same method to profile a commercial DBT powder, verifying its authenticity as compared to our prepared DBT. This study is the first to employ H-NMR metabolic profiling for the quality control of traditional Chinese medicine decoctions.
doi:10.1155/2014/567893
PMCID: PMC3980871  PMID: 24826194
2.  A complete mass spectrometric map for the analysis of the yeast proteome and its application to quantitative trait analysis 
Nature  2013;494(7436):266-270.
Complete reference maps or datasets, like the genomic map of an organism, are highly beneficial tools for biological and biomedical research. Attempts to generate such reference datasets for a proteome so far failed to reach complete proteome coverage, with saturation apparent at approximately two thirds of the proteomes tested, even for the most thoroughly characterized proteomes. Here, we used a strategy based on high-throughput peptide synthesis and mass spectrometry to generate a close to complete reference map (97% of the genome-predicted proteins) of the S. cerevisiae proteome. We generated two versions of this mass spectrometric map one supporting discovery- (shotgun) and the other hypothesis-driven (targeted) proteomic measurements. The two versions of the map, therefore, constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. The reference libraries can be browsed via a web-based repository and associated navigation tools. To demonstrate the utility of the reference libraries we applied them to a protein quantitative trait locus (pQTL) analysis, which requires measurement of the same peptides over a large number of samples with high precision. Protein measurements over a set of 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, impacting on the levels of related proteins. Our results suggest that selective pressure favors the acquisition of sets of polymorphisms that maintain the stoichiometry of protein complexes and pathways.
doi:10.1038/nature11835
PMCID: PMC3951219  PMID: 23334424
S. cerevisiae; selected reaction monitoring; SRM; MRM; spectral library; peptide library; mass spectrometric map; protein QTL
3.  Identifying sources of tick blood meals using unidentified tandem mass spectral libraries 
Nature communications  2013;4:1746.
Rapid and reliable identification of the vertebrate species on which a disease vector previously parasitized is imperative to study ecological factors that affect pathogen distribution and can aid the development of public health programs. Here we describe a proteome profiling technique designed to identify the source of blood meals of hematophagous arthropods. This method employs direct spectral matching and thus does not require a priori knowledge of any genetic or protein sequence information. Using this technology, we detect remnants of blood in blacklegged ticks (Ixodes scapularis) and correctly determine the vertebrate species from which the blood was derived even six months after the tick had fed. This biological fingerprinting methodology is sensitive, fast, cost-effective, and can potentially be adapted for other biological and medical applications when existing genome-based methods are impractical or ineffective.
doi:10.1038/ncomms2730
PMCID: PMC3635114  PMID: 23612287
4.  Chemical changes of Angelicae Sinensis Radix and Chuanxiong Rhizoma by wine treatment: chemical profiling and marker selection by gas chromatography coupled with triple quadrupole mass spectrometry 
Chinese Medicine  2013;8:12.
Background
Angelicae Sinensis Radix (ASR) and Chuanxiong Rhizoma (CR) can be treated with wine to promote their biological functions in Chinese medicine. Both ASR and CR contain similar volatile chemicals that could be altered after wine treatment. This study aims to identify the differential chemical profiles and to select marker chemicals of ASR and CR before and after wine treatment.
Methods
Chemical analyses were carried out by gas chromatography-triple quadrupole mass spectrometry (GC-QQQ-MS/MS) coupled with multivariate statistical analysis. Characterization of the compositions of essential oils was performed by automated matching to the MS library and comparisons of their mass spectra (NIST08 database). For ferulic acid, butylphthalide, Z-butylidenephthalide, senkyunolide A and Z-ligustilide, the mass spectrometer was operated in electron ionization mode, the selection reaction monitoring mode was used and an evaluation of the stability and sensitivity of the chromatographic system was performed for the tested extraction.
Results
Principal component analysis (PCA) simultaneously distinguished ASR and CR from different forms. Ferulic acid, Z-butylidenephthalide, Z-ligustilide, butylphthalide and senkyunolide A were screened by PCA loading plots and can be used as chemical markers for discrimination among different groups of samples.
Conclusion
Different chemical profiles of ASR and CR after wine treatment could be identified by GC-QQQ-MS/MS. The five marker chemicals selected by PCA, namely ferulic acid, butylphthalide, Z-butylidenephthalide, senkyunolide A and Z-ligustilide, were sufficient to distinguish between the crude and corresponding wine-treated forms of ASR and CR.
doi:10.1186/1749-8546-8-12
PMCID: PMC3693868  PMID: 23738580
5.  Statistical Platform to Discern Spatial and Temporal Coordination of Endothelial Sprouting 
Many biological processes, including angiogenesis, involve intercellular feedback and temporal coordination, but inference of these relations is often drowned in low sample sizes or noisy population data. To address this issue, a methodology was developed to statistically study spatial lateral inhibition and temporal synchronization in one specific biological process, endothelial sprouting mediated by Notch signaling. Notch plays an essential role in the development of organized vasculature, but the effects of Notch on the temporal characteristics of angiogenesis are not well understood. Results from this study showed that Notch lateral inhibition operates at distances less than 31μm. Furthermore, combining time lapse microscopy with an intraclass correlation model typically used to analyze family data showed intrinsic temporal synchronization among endothelial sprouts originating from the same microcarrier. Such synchronization was reduced with Notch inhibitors, but was enhanced with the addition of Notch ligands. These results indicate Notch plays a critical role in the temporal regulation of angiogenesis, as well as spatial control, and this method of analysis will be of significant utility in studies of a variety of other biological processes.
doi:10.1039/c2ib00057a
PMCID: PMC3654550  PMID: 22318325
6.  Metabonomic analysis of water extracts from Chinese and American ginsengs by 1H nuclear magnetic resonance: identification of chemical profile for quality control 
Chinese Medicine  2012;7:25.
Background
With the gaining popularity of commercially prepared decoctions of herbal medicines on the market, an objective and efficient way to reveal the authenticity of such products is urgently needed. Previous attempts to use chromatographic or spectroscopic methods to identify ginseng samples made use of components derived from methanol extracts of the herb. It was not established that these herbs can be distinguished solely from consumable components, which are responsible for the clinical efficacy of the herb.
In this study, metabonomics, or metabolic profiling, based on the application of 1H-Nuclear Magnetic Resonance (NMR), is applied to distinguish the water extracts of three closely related ginseng species: P. ginseng (from two different cultivated regions in China), P. notoginseng and P. quinquefolius.
Methods
A water extraction protocol that mimics how ginseng decoctions are made for consumption was used to prepare triplicate samples from each herb for analysis. High-resolution 1H NMR spectroscopy was used to acquire metabolic profiles of the four ginseng samples. The spectral data were subjected to multivariate and univariate analysis to identify metabolites that were able to distinguish different types of ginseng.
Results
H NMR metabolic profiling was performed to distinguish the water extracts of P. ginseng cultivated in Hebei and Jilin of China, both of which were distinguished from extracts of P. notoginseng and P. quinquefolius, by unsupervised principle component analysis based on the entire 1H NMR spectral fingerprint Statistically significant differences were found for several discriminating features traced to common metabolites and the ginsenosides Rg1 and Rd, in the 1H NMR spectra.
Conclusion
This study demonstrated that 1H NMR metabonomics can simultaneously distinguish different ginseng species and multiple samples of the same species that were cultivated in different regions. This technique is applicable to the authentication and quality control of ginseng products.
doi:10.1186/1749-8546-7-25
PMCID: PMC3507782  PMID: 23140520
7.  Fast parallel tandem mass spectral library searching using GPU hardware acceleration 
Journal of proteome research  2011;10(6):2882-2888.
Mass spectrometry-based proteomics is a maturing discipline of biologic research that is experiencing substantial growth. Instrumentation has steadily improved over time with the advent of faster and more sensitive instruments collecting ever larger data files. Consequently, the computational process of matching a peptide fragmentation pattern to its sequence, traditionally accomplished by sequence database searching and more recently also by spectral library searching, has become a bottleneck in many mass spectrometry experiments. In both of these methods, the main rate limiting step is the comparison of an acquired spectrum with all potential matches from a spectral library or sequence database. This is a highly parallelizable process because the core computational element can be represented as a simple but arithmetically intense multiplication of two vectors. In this paper we present a proof of concept project taking advantage of the massively parallel computing available on graphics processing units (GPUs) to distribute and accelerate the process of spectral assignment using spectral library searching. This program, which we have named FastPaSS (for Fast Parallelized Spectral Searching) is implemented in CUDA (Compute Unified Device Architecture) from NVIDIA which allows direct access to the processors in an NVIDIA GPU. Our efforts demonstrate the feasibility of GPU computing for spectral assignment, through implementation of the validated spectral searching algorithm SpectraST in the CUDA environment.
doi:10.1021/pr200074h
PMCID: PMC3107871  PMID: 21545112
CUDA; tandem mass spectrometry; spectral library searching; peptide identification
8.  Absolute quantification of microbial proteomes at different states by directed mass spectrometry 
The developed, directed mass spectrometry workflow allows to generate consistent and system-wide quantitative maps of microbial proteomes in a single analysis. Application to the human pathogen L. interrogans revealed mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense, and new insights about the regulation of absolute protein abundances within operons.
The developed, directed proteomic approach allowed consistent detection and absolute quantification of 1680 proteins of the human pathogen L. interrogans in a single LC–MS/MS experiment.The comparison of 25 extensive, consistent and quantitative proteome maps revealed new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans, and about the regulation of protein abundances within operons.The generated time-resolved data sets are compatible with pattern analysis algorithms developed for transcriptomics, including hierarchical clustering and functional enrichment analysis of the detected profile clusters.This is the first study that describes the absolute quantitative behavior of any proteome over multiple states and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
Over the last decade, mass spectrometry (MS)-based proteomics has evolved as the method of choice for system-wide proteome studies and now allows for the characterization of several thousands of proteins in a single sample. Despite these great advances, redundant monitoring of protein levels over large sample numbers in a high-throughput manner remains a challenging task. New directed MS strategies have shown to overcome some of the current limitations, thereby enabling the acquisition of consistent and system-wide data sets of proteomes with low-to-moderate complexity at high throughput.
In this study, we applied this integrated, two-stage MS strategy to investigate global proteome changes in the human pathogen L. interrogans. In the initial discovery phase, 1680 proteins (out of around 3600 gene products) could be identified (Schmidt et al, 2008) and, by focusing precious MS-sequencing time on the most dominant, specific peptides per protein, all proteins could be accurately and consistently monitored over 25 different samples within a few days of instrument time in the following scoring phase (Figure 1). Additionally, the co-analysis of heavy reference peptides enabled us to obtain absolute protein concentration estimates for all identified proteins in each perturbation (Malmström et al, 2009). The detected proteins did not show any biases against functional groups or protein classes, including membrane proteins, and span an abundance range of more than three orders of magnitude, a range that is expected to cover most of the L. interrogans proteome (Malmström et al, 2009).
To elucidate mechanistic proteome changes over time involved in pathogenic progression and antibiotic defense of L. interrogans, we generated time-resolved proteome maps of cells perturbed with serum and three different antibiotics at sublethal concentrations that are currently used to treat Leptospirosis. This yielded an information-rich proteomic data set that describes, for the first time, the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date. Using this unique property of the data set, we could quantify protein components of entire pathways across several time points and subject the data sets to cluster analysis, a tool that was previously limited to the transcript level due to incomplete sampling on protein level (Figure 4). Based on these analyses, we could demonstrate that Leptospira cells adjust the cellular abundance of a certain subset of proteins and pathways as a general response to stress while other parts of the proteome respond highly specific. The cells furthermore react to individual treatments by ‘fine tuning' the abundance of certain proteins and pathways in order to cope with the specific cause of stress. Intriguingly, the most specific and significant expression changes were observed for proteins involved in motility, tissue penetration and virulence after serum treatment where we tried to simulate the host environment. While many of the detected protein changes demonstrate good agreement with available transcriptomics data, most proteins showed a poor correlation. This includes potential virulence factors, like Loa22 or OmpL1, with confirmed expression in vivo that were significantly up-regulated on the protein level, but not on the mRNA level, strengthening the importance of proteomic studies. The high resolution and coverage of the proteome data set enabled us to further investigate protein abundance changes of co-regulated genes within operons. This suggests that although most proteins within an operon respond to regulation synchronously, bacterial cells seem to have subtle means to adjust the levels of individual proteins or protein groups outside of the general trend, a phenomena that was recently also observed on the transcript level of other bacteria (Güell et al, 2009).
The method can be implemented with standard high-resolution mass spectrometers and software tools that are readily available in the majority of proteomics laboratories. It is scalable to any proteome of low-to-medium complexity and can be extended to post-translational modifications or peptide-labeling strategies for quantification. We therefore expect the approach outlined here to become a cornerstone for microbial systems biology.
Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre-determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC–MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.
doi:10.1038/msb.2011.37
PMCID: PMC3159967  PMID: 21772258
absolute quantification; directed mass spectrometry; Leptospira interrogans; microbiology; proteomics
9.  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
10.  Trans-Proteomic Pipeline supports and improves analysis of electron transfer dissociation datasets 
Proteomics  2010;10(6):1190-1195.
Electron transfer dissociation (ETD) is an alternative fragmentation technique to collision induced dissociation (CID) that has recently become commercially available. ETD has several advantages over CID. It is less prone to fragmenting amino acid side chains, especially those that are modified, thus yielding fragment ion spectra with more uniform peak intensities. Further, precursor ions of longer peptides and higher charge states can be fragmented and identified. However, analysis of ETD spectra has a few important differences that require the optimization of the software packages used for the analysis of CID data, or the development of specialized tools. We have adapted the Trans-Proteomic Pipeline (TPP) to process ETD data. Specifically, we have added support for fragment ion spectra from high charge precursors, compatibility with charge-state estimation algorithms, provisions for the use of the Lys-C protease, capabilities for ETD spectrum library building, and updates to the data formats to differentiate CID and ETD spectra. We show the results of processing datasets from several different types of ETD instruments and demonstrate that application of the ETD-enhanced TPP can increase the number of spectrum identifications at a fixed false discovery rate by as much as 100% over native output from a single sequence search engine.
doi:10.1002/pmic.200900567
PMCID: PMC3018683  PMID: 20082347
shotgun proteomics; electron-transfer dissociation; bioinformatics
11.  A Guided Tour of the Trans-Proteomic Pipeline 
Proteomics  2010;10(6):1150-1159.
The Trans-Proteomic Pipeline (TPP) is a suite of software tools for the analysis of tandem mass spectrometry datasets. The tools encompass most of the steps in a proteomic data analysis workflow in a single, integrated software system. Specifically, the TPP supports all steps from spectrometer output file conversion to protein-level statistical validation, including quantification by stable isotope ratios. We describe here the full workflow of the TPP and the tools therein, along with an example on a sample dataset, demonstrating that the set up and use of the tools is straightforward and well supported and does not require specialized informatics resources or knowledge.
doi:10.1002/pmic.200900375
PMCID: PMC3017125  PMID: 20101611
12.  MaRiMba: A Software Application for Spectral Library-Based MRM Transition List Assembly 
Journal of proteome research  2009;8(10):4396-4405.
Multiple reaction monitoring mass spectrometry (MRM-MS) is a targeted analysis method that has been increasingly viewed as an avenue to explore proteomes with unprecedented sensitivity and throughput. We have developed a software tool, called MaRiMba, to automate the creation of explicitly defined MRM transition lists required to program triple quadrupole mass spectrometers in such analyses. MaRiMba creates MRM transition lists from downloaded or custom-built spectral libraries, restricts output to specified proteins or peptides, and filters based on precursor peptide and product ion properties. MaRiMba can also create MRM lists containing corresponding transitions for isotopically heavy peptides, for which the precursor and product ions are adjusted according to user specifications. This open-source application is operated through a graphical user interface incorporated into the Trans-Proteomic Pipeline, and it outputs the final MRM list to a text file for upload to MS instruments. To illustrate the use of MaRiMba, we used the tool to design and execute an MRM-MS experiment in which we targeted the proteins of a well-defined and previously published standard mixture.
doi:10.1021/pr900010h
PMCID: PMC2837355  PMID: 19603829
multiple reaction monitoring (MRM); selective reaction monitoring (SRM); MRM transition; transition list; spectral library; mass spectrometry; targeted proteomics
15.  Building Consensus Spectral Libraries for Peptide Identification in Proteomics 
Nature methods  2008;5(10):873-875.
Summary
Recently there has been an increasing interest in using spectral searching as an alternative to traditional database sequence searching methods for peptide identification from tandem mass spectrometry. In spectral searching, the query spectrum is compared to a carefully compiled library of previously observed and identified spectra; high spectral similarity signals positive identification. We have previously developed an open-source software toolkit, SpectraST, to enable proteomics researchers to integrate spectral searching into their data analysis pipeline. Here we report an additional module to SpectraST that provides the functionality of spectral library building, allowing users to build custom libraries when public spectral libraries do not adequately meet their needs. A consensus creation algorithm was developed to coalesce replicate spectra identified to the same peptide ion. Various quality filters were implemented to remove questionable and low-quality spectra from the library. To validate the methodology, we first compiled a spectral library from the 1.3 million SEQUEST-identified spectra (29,109 distinct peptide ions) among the publicly released datasets in the Human Plasma PeptideAtlas, a collection of 40 contributed, heterogeneous shotgun proteomics datasets, and verified the effectiveness of the library building algorithm to generate high-quality, representative consensus spectra and to remove questionable spectra. We then re-searched the same datasets by SpectraST against this spectral library filtered at different quality levels, and used the performance as a benchmark to evaluate our library building methods and to determine key parameters for high-quality library building. We demonstrated the importance of library quality on the performance of spectral searching. The ready-to-deploy software allows individual researchers to easily condense their raw data into specialized spectral libraries, summarizing useful information about their observed proteomes into a concise and retrievable format for future data analyses.
doi:10.1038/nmeth.1254
PMCID: PMC2637392  PMID: 18806791
16.  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

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