Improved LC-MS/MS spectral counting statistics by recovering low-scoring spectra matched to confidently identified peptide sequences

Proteomic Profiling of Venoms from Bungarus suzhenae and B. bungaroides: Enzymatic Activities and Toxicity Assessment

Kraits are venomous snakes of the genus Bungarus from the family Elapidae. Their venom typically demonstrates neurotoxicity; however, the toxicity is significantly influenced by the snake's species and geographical origin. Among the Bungarus species, Bungarus suzhenae and B. bungaroides have been poorly studied, with little to no information available regarding their venom composition. In this study, a proteomic approach was employed using LC-MS/MS to identify proteins from trypsin-digested peptides. The analysis revealed 102 venom-related proteins from 18 distinct functional protein families in the venom of B. suzhenae, with the primary components being three-finger toxins (3-FTx, 25.84%), phospholipase A2 (PLA2, 40.29%), L-amino acid oxidase (LAAO, 10.33%), Kunitz-type serine protease inhibitors (KUN, 9.48%), and snake venom metalloproteinases (SVMPs, 6.13%). In the venom of B. bungaroides, 99 proteins from 17 families were identified, with primary components being 3-FTx (33.87%), PLA2 (37.91%), LAAO (4.21%), and KUN (16.60%). Enzymatic activity assays confirmed the presence of key venom enzymes. Additionally, the LD50 values for B. suzhenae and B. bungaroides were 0.0133 μg/g and 0.752 μg/g, respectively, providing a reference for toxicity studies of these two species. This research elucidates the proteomic differences in the venoms of these two species, offering a foundation for developing antivenoms and clinical treatments for envenomation.

Effective Degradation of Brewer Spent Grains by a Novel Thermostable GH10 Xylanase

Brewer spent grains (BSGs) are one of the most abundant by-products in brewing industry. Due to microbiological instability and high perishability, the efficient degradation of BSGs is of environmental and economic importance. Streptomyces sp. F-3 could grow in the medium with BSGs as the only carbon and nitrogen source. Proteome mass spectrometry revealed that a GH10 xylanase SsXyn10A could be secreted in large quantities. SsXyn10A showed optimum activity at pH 7.0 and 60 °C. SsXyn10A exhibited excellent thermostability which retained approximately 100% and 58% after incubation for 5 h at 50 and 60 °C. SsXyn10A displayed high activity to beechwood xylan (BX) and wheat arabinoxylan (WAX). SsXyn10A is active against xylotetracose (X4), xylopentose (X5), and xylohexose (X6) to produce main products xylobiose (X2) and xylotriose (X3). Ssxyn10A showed synergistic effects with commercial cellulase on BSGs hydrolyzing into soluble sugar. In addition, the steam explosion pretreatment of BSGs as the substrate produced twice as much reducing sugar as the degradation of the original substrate. This study will contribute to efficient utilization of BSGs and provide a thermostable GH10 xylanase which has potential application in biomass hydrolysis.

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

The Extracellular Matrix: Its Composition, Function, Remodeling, and Role in Tumorigenesis

The extracellular matrix (ECM) is a ubiquitous member of the body and is key to the maintenance of tissue and organ integrity. Initially thought to be a bystander in many cellular processes, the extracellular matrix has been shown to have diverse components that regulate and activate many cellular processes and ultimately influence cell phenotype. Importantly, the ECM's composition, architecture, and stiffness/elasticity influence cellular phenotypes. Under normal conditions and during development, the synthesized ECM constantly undergoes degradation and remodeling processes via the action of matrix proteases that maintain tissue homeostasis. In many pathological conditions including fibrosis and cancer, ECM synthesis, remodeling, and degradation is dysregulated, causing its integrity to be altered. Both physical and chemical cues from the ECM are sensed via receptors including integrins and play key roles in driving cellular proliferation and differentiation and in the progression of various diseases such as cancers. Advances in 'omics' technologies have seen an increase in studies focusing on bidirectional cell-matrix interactions, and here, we highlight the emerging knowledge on the role played by the ECM during normal development and in pathological conditions. This review summarizes current ECM-targeted therapies that can modify ECM tumors to overcome drug resistance and better cancer treatment.

Tailoring the expression of Xyr1 leads to efficient production of lignocellulolytic enzymes in Trichoderma reesei for improved saccharification of corncob residues

BACKGROUND

The filamentous fungus Trichoderma reesei is extensively used for the industrial-scale cellulase production. It has been well known that the transcription factor Xyr1 plays an important role in the regulatory network controlling cellulase gene expression. However, the role of Xyr1 in the regulation of cellulase expression has not been comprehensively elucidated, which hinders further improvement of lignocellulolytic enzyme production.

RESULTS

Here, the expression dosage of xyr1 was tailored in T. reesei by differentially overexpressing the xyr1 gene under the control of three strong promoters (Pegl2, Pcbh1, and Pcdna1), and the transcript abundance of xyr1 was elevated 5.8-, 12.6-, and 47.2-fold, respectively. We found expression of cellulase genes was significantly increased in the Pegl2-driven xyr1 overexpression strain QE2X, whereas relatively low in the Pcbh1- and Pcdna1-driven overexpression strains. We also found that the Pegl2-driven overexpression of xyr1 caused a more significant opening of chromatin in the core promoter region of the prominent cellulase genes. Furthermore, the cellulase activity showed a 3.2-fold increase in the strain QE2X, while insignificant improvement in the Pcbh1- and Pcdna1-driven strains. Finally, the saccharification efficiency toward acid-pretreated corncob residues containing high-content lignin by the crude enzyme from QE2X was increased by 57.2% compared to that from the parental strain. Moreover, LC-MS/MS and RT-qPCR analysis revealed that expression of accessory proteins (Cip1, Cip2, Swo1, and LPMOs) was greatly improved in QE2X, which partly explained the promoting effect of the Pegl2-driven overexpression on enzymatic hydrolysis of lignocellulose biomass.

CONCLUSIONS

Our results underpin that the precise tailoring expression of xyr1 is essential for highly efficient cellulase synthesis, which provide new insights into the role of Xyr1 in regulating cellulase expression in T. reesei. Moreover, these results also provides a prospective strategy for strain improvement to enhance the lignocellulolytic enzyme production for use in biorefinery applications.

A highly efficient protein degradation system in Bacillus sp. CN2: a functional-degradomics study

A novel protease-producing Bacillus sp. CN2 isolated from chicken manure composts exhibited a relatively high proteolytic specific activity. The strain CN2 degradome consisted of at least 149 proteases and homolog candidates, which were distributed into 4 aspartic, 30 cysteine, 55 metallo, 56 serine, and 4 threonine proteases. Extracellular proteolytic activity was almost completely inhibited by PMSF (phenylmethylsulfonyl fluoride) rather than o-P, E-64, or pepstatin A, suggesting that strain CN2 primarily secreted serine protease. More importantly, analysis of the extracellular proteome of strain CN2 revealed the presence of a highly efficient protein degradation system. Three serine proteases of the S8 family with different active site architectures firstly fragmented protein substrates which were then degraded to smaller peptides by a M4 metalloendopeptidase that prefers to degrade hydrophobic peptides and by a S13 carboxypeptidase. Those enzymes acted synergistically to degrade intact substrate proteins outside the cell. Furthermore, highly expressed sequence-specific intracellular aminopeptidases from multiple families (M20, M29, and M42) accurately degraded peptides into oligopeptides or amino acids, thus realizing the rapid acquisition and utilization of nitrogen sources. In this paper, a systematic study of the functional-degradome provided a new perspective for understanding the complexity of the protease hydrolysis system of Bacillus, and laid a solid foundation for further studying the precise degradation of proteins with the cooperative action of different family proteases. KEY POINTS: • Bacillus sp. CN2 has relatively high proteolytic specific activity. • Bacillus sp. CN2 harbors a highly efficient protein degradation system. • The site-specific endopeptidases were secreted extracellular, while the sequence-specific aminopeptidases played a role in the cell.

Quantitative Mass Spectrometry-Based Proteomics: An Overview

In recent decades, mass spectrometry has moved more than ever before into the front line of protein-centered research. After being established at the qualitative level, the more challenging question of quantification of proteins and peptides using mass spectrometry has become a focus for further development. In this chapter, we discuss and review actual strategies and problems of the methods for the quantitative analysis of peptides, proteins, and finally proteomes by mass spectrometry. The common themes, the differences, and the potential pitfalls of the main approaches are presented in order to provide a survey of the emerging field of quantitative, mass spectrometry-based proteomics.

Novel Synergistic Mechanism for Lignocellulose Degradation by a Thermophilic Filamentous Fungus and a Thermophilic Actinobacterium Based on Functional Proteomics

Effective artificial microbial consortia containing microorganisms with desired biological functions have the potential to optimize the lignocellulose-based bioindustry. Thermobifida fusca was a dominant actinobacterium in high-temperature corn stalk composts, but it was unable to grow alone in corn stalk solid medium. Interestingly, T. fusca showed good growth and secreted enzymes when cocultured with Thermomyces lanuginosus. T. lanuginosus grew firstly during the initial stage, whereas T. fusca dominated the system subsequently during cocultivation. The secretome indicated that T. lanuginosus mainly degraded xylan by expressing a GH11 xylanase (g4601.t1, GenBank AAB94633.1; with relative secretion of 4.95 ± 0.65%). T. fusca was induced by xylan mainly to secrete a xylanase from GH11 family (W8GGR4, GenBank AHK22788.1; with relative secretion of 8.71 ± 3.83%) which could rapidly degrade xylan to xylo-oligosaccharide (XOS) and xylose within 2 min, while high concentrations (>0.5%, w/v) of XOS or xylose suppressed the growth of T. fusca; which may be the reason why T. fusca unable to grow alone in corn stalk solid medium. However, T. lanuginosus could utilize the XOS and xylose produced by xylanases secreted by T. fusca. During the synergistic degradation of lignocellulose by T. lanuginosus and T. fusca, xylan was rapidly consumed by T. lanuginosus, the residual cellulose could specifically induced T. fusca to express a GH10 xylanase with a CBM2 domain (Q47KR6, GenBank AAZ56956.1; with relative secretion of 5.03 ± 1.33%) and 6 cellulases (2 exocellulases and 4 endocellulases). Moreover, T. lanuginosus increased the secretion of cellulases from T. fusca by 19-25%. The order of T. lanuginosus and T. fusca was consistent with the multilayered structures of lignocellulose and could be regulated by different concentrations of XOS and xylose. The novel synergism of T. lanuginosus and T. fusca gave a new sight for revealing more synergetic relationships in natural environments and exploring efficient microbial inoculants and enzyme cocktails for lignocellulose degradation.

Insights into the cellulose degradation mechanism of the thermophilic fungus Chaetomium thermophilum based on integrated functional omics

BACKGROUND

Lignocellulose is the most abundant and renewable biomass resource on the planet. Lignocellulose can be converted into biofuels and high-value compounds; however, its recalcitrance makes its breakdown a challenge. Lytic polysaccharide monooxygenases (LPMOs) offer tremendous promise for the degradation of recalcitrant polysaccharides. Chaetomium thermophilum, having many LPMO-coding genes, is a dominant thermophilic fungus in cellulose-rich and self-heating habitats. This study explores the genome, secretomes and transcript levels of specific genes of C. thermophilum.

RESULTS

The genome of C. thermophilum encoded a comprehensive set of cellulose- and xylan-degrading enzymes, especially 18 AA9 LPMOs that belonged to different subfamilies. Extracellular secretomes showed that arabinose and microcrystalline cellulose (MCC) could specifically induce the secretion of carbohydrate-active enzymes (CAZymes), especially AA9 LPMOs, by C. thermophilum under different carbon sources. Temporal analyses of secretomes and transcripts revealed that arabinose induced the secretion of xylanases by C. thermophilum, which was obviously different from other common filamentous fungi. MCC could efficiently induce the specific secretion of LPMO2s, possibly because the insert in loop3 on the substrate-binding surface of LPMO2s strengthened its binding capacity to cellulose. LPMO2s, cellobio hydrolases (CBHs) and cellobiose dehydrogenases (CDHs) were cosecreted, forming an efficient cellulose degradation system of oxidases and hydrolases under thermophilic conditions.

CONCLUSIONS

The specific expression of LPMO2s and cosecretion of hydrolases and oxidases by the thermophilic fungus C. thermophilum play an important role in cellulose degradation. This insight increases our understanding of the cellulose degradation under thermophilic conditions and may inspire the design of the optimal enzyme cocktails for more efficient exploration of biomass resources in industrial applications.

Quantitative proteomic analysis of trypsin-treated extracellular vesicles to identify the real-vesicular proteins

Extracellular vesicles (EVs) are nano-sized vesicles surrounded by a lipid bilayer and released into the extracellular milieu by most of cells. Although various EV isolation methods have been established, most of the current methods isolate EVs with contaminated non-vesicular proteins. By applying the label-free quantitative proteomic analyses of human colon cancer cell SW480-derived EVs, we identified trypsin-sensitive and trypsin-resistant vesicular proteins. Further systems biology and protein-protein interaction network analyses based on their cellular localization, we classified the trypsin-sensitive and trypsin-resistant vesicular proteins into two subgroups: 363 candidate real-vesicular proteins and 151 contaminated non-vesicular proteins. Moreover, the protein interaction network analyses showed that candidate real-vesicular proteins are mainly derived from plasma membrane (46.8%), cytosol (36.6%), cytoskeleton (8.0%) and extracellular region (2.5%). On the other hand, most of the contaminated non-vesicular proteins derived from nucleus, Golgi apparatus, endoplasmic reticulum and mitochondria. In addition, ribosomal protein complexes and T-complex proteins were classified as the contaminated non-vesicular proteins. Taken together, our trypsin-digested proteomic approach on EVs is an important advance to identify the real-vesicular proteins that could help to understand EV biogenesis and protein cargo-sorting mechanism during EV release, to identify more reliable EV diagnostic marker proteins, and to decode pathophysiological roles of EVs.

Potential of proteomics to probe microbes

An organism exposed to a plethora of environmental perturbations undergoes proteomic changes which enable the characterization of total proteins in it. Much of the proteomic information is obtained from genomic data. Additional information on the proteome such as posttranslational modifications, protein-protein interactions, protein localization, metabolic pathways, and so on are deduced using proteomic tools which genomics and transcriptomics fail to offer. The proteomic analysis allows identification of precise changes in proteins, which in turn solve the complexity of microbial population providing insights into the microbial metabolism, cellular pathways, and behavior of microorganisms in new environments. Furthermore, they provide clues for the exploitation of their special features for biotechnological applications. Numerous techniques for the analysis of microbial proteome such as electrophoretic, chromatographic, mass spectrometric-based methods as well as quantitative proteomics are available which facilitate protein separation, expression, identification, and quantification of proteins. An understanding of the potential of each of the proteomic tools has created a significant impact on diverse microbiological aspects and the same has been discussed in this review.

A novel thermostable chitinolytic machinery of Streptomyces sp. F-3 consisting of chitinases with different action modes

BACKGROUND

The biodegradation of chitin is an important part of the carbon and nitrogen cycles in nature. Speeding up the biotransformation of chitin substrates can not only reduce pollution, but also produce high value-added products. However, this process is strictly regulated by the catalytic efficiency of the chitinolytic machinery. Therefore, it is necessary to study the mode of action and compound mechanisms of different chitin-degrading enzymes in depth to improve the catalytic efficiency of the chitinolytic machinery.

RESULTS

The thermophilic bacterium Streptomyces sp. F-3 showed comparatively high chitin degradation activities. To elucidate the mechanism underlying chitin hydrolysis, six chitin degradation-related enzymes were identified in the extracellular proteome of Streptomyces sp. F-3, including three chitinases (SsChi18A, SsChi18B, and SsChi18C) from the GH18 family, one GH19 chitinase (SsChi19A), one GH20 β-N-acetylhexosaminidase (SsGH20A), and one lytic polysaccharide monooxygenase (SsLPMO10A) from the AA10 family. All were upregulated by chitin. The heterologously expressed hydrolases could withstand temperatures up to 70 °C and were stable at pH values of 4 to 11. Biochemical analyses displayed that these chitin degradation-related enzymes had different functions and thus showed synergistic effects during chitin degradation. Furthermore, based on structural bioinformatics data, we speculated that the different action modes among the three GH18 chitinases may be caused by loop differences in their active site architectures. Among them, SsChi18A is probably processive and mainly acts on polysaccharides, while SsChi18B and SsChi18C are likely endo-non-processive and displayed higher activity on the degradation of chitin oligosaccharides. In addition, proteomic data and synergy experiments also indicated the importance of SsLPMO10A, which could promote the activities of the hydrolases and increase the monosaccharide content in the reaction system, respectively.

CONCLUSIONS

In this article, the chitinolytic machinery of a thermophilic Streptomyces species was studied to explore the structural basis for the synergistic actions of chitinases from different GH18 subfamilies. The elucidation of the degradation mechanisms of these thermophilic chitinases will lay a theoretical foundation for the efficient industrialized transformation of natural chitin.

Integrated Functional-Omics Analysis of Thermomyces lanuginosus Reveals its Potential for Simultaneous Production of Xylanase and Substituted Xylooligosaccharides

Thermophiles have several beneficial properties for the conversion of biomass at high temperatures. Thermomyces lanuginosus is a thermophilic filamentous fungus that was shown to secrete 40 glycoside hydrolases and 25 proteases when grown on different carbon sources. Among the 13 identified glycoside hydrolases with high expression levels, 9 were reduced sugar glycosidases (RSGs) belonging to seven GH families, and 7 of the 10 identified proteases were exopeptidases belonging to six different protease families. High expression of RSGs and exopeptidases may allow the fungus to efficiently degrade oligosaccharides and oligopeptides in saprophytic habitats. There were no xylan side chain-degrading enzymes predicted in the genome of T. lanuginosus, and only one thermophilic GH11 xylanase (g4601.t1) and one GH43 xylosidase (g3706.t1) were detected by liquid chromatography-mass spectrometry/mass spectrometry when T. lanuginosus grown on xylan, which led to the accumulation of substituted xylooligosaccharides (SXOS) during corncob xylan degradation where SXOS output made up more than 8% of the total xylan. The SXOS are beneficial prebiotics and important inducers for enzymes secretion of microorganisms. Thus, T. lanuginosus exhibits distinct advantages in utilizing cheap raw materials producing one thermostable xylanase and the high value-added SXOS as well as microbial inoculants to compost by batch fermentation.

Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics

Mass spectrometry-based quantitative proteomics is a powerful tool for gaining insights into function and dynamics of biological systems. However, peptides with different sequences have different ionization efficiencies, and their intensities in a mass spectrum are not correlated with their abundances. Therefore, various label-free or stable isotope label-based quantitation methods have emerged to assist mass spectrometry to perform comparative proteomic experiments, thus enabling nonbiased identification of thousands of proteins differentially expressed in healthy versus diseased cells. Here, we discuss the most widely used label-free and metabolic-, enzymatic-, and chemical labeling-based proteomic strategies for relative and absolute quantitation. We summarize the specific strengths and weaknesses of each technique in terms of quantification accuracy, proteome coverage, multiplexing capability, and robustness. Applications of each strategy for solving specific biological complexities are also presented.

Extracellular Enzyme Composition and Functional Characteristics of Aspergillus niger An-76 Induced by Food Processing Byproducts and Based on Integrated Functional Omics

Byproducts of food processing can be utilized for the production of high-value-added enzyme cocktails. In this study, we utilized integrated functional omics technology to analyze composition and functional characteristics of extracellular enzymes produced by Aspergillus niger grown on food processing byproducts. The results showed that oligosaccharides constituted by arabinose, xylose, and glucose in wheat bran were able to efficiently induce the production of extracellular enzymes of A. niger. Compared with other substrates, wheat bran was more effective at inducing the secretion of β-glucosidases from GH1 and GH3 families, as well as >50% of proteases from A1-family aspartic proteases. Compared with proteins induced by single wheat bran or soybean dregs, the protein yield induced by their mixture was doubled, and the time required to reach peak enzyme activity was shortened by 25%. This study provided a technical platform for the complex formulation of various substrates and functional analysis of extracellular enzymes.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we derived a quantification confidence score based on the quality of each peptide-spectrum match to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS data sets collected over a 7-month period. This study provides the first quality assessment on long-term stability and technical considerations for study design of a large-scale clinical proteomics project.

Secretome profiling reveals temperature-dependent growth of Aspergillus fumigatus

Aspergillus fumigatus is a ubiquitous opportunistic fungus. In this study, systematic analyses were carried out to study the temperature adaptability of A. fumigatus. A total of 241 glycoside hydrolases and 69 proteases in the secretome revealed the strong capability of A. fumigatus to degrade plant biomass and protein substrates. In total, 129 pathogenesis-related proteins detected in the secretome were strongly correlated with glycoside hydrolases and proteases. The variety and abundance of proteins remained at temperatures of 34°C-45°C. The percentage of endo-1,4-xylanase increased when the temperature was lowered to 20°C, while the percentage of cellobiohydrolase increased as temperature was increased, suggesting that the strain obtains carbon mainly by degrading xylan and cellulose, and the main types of proteases in the secretome were aminopeptidases and carboxypeptidases. Only half of the proteins were retained and their abundance declined to 9.7% at 55°C. The activities of the remaining β-glycosidases and proteases were merely 35% and 24%, respectively, when the secretome was treated at 60°C for 2 h. Therefore, temperatures >60°C restrict the growth of A. fumigatus.

A peptide-retrieval strategy enables significant improvement of quantitative performance without compromising confidence of identification

Reliable quantification of low-abundance proteins in complex proteomes is challenging largely owing to the limited number of spectra/peptides identified. In this study we developed a straightforward method to improve the quantitative accuracy and precision of proteins by strategically retrieving the less confident peptides that were previously filtered out using the standard target-decoy search strategy. The filtered-out MS/MS spectra matched to confidently-identified proteins were recovered, and the peptide-spectrum-match FDR were re-calculated and controlled at a confident level of FDR≤1%, while protein FDR maintained at ~1%. We evaluated the performance of this strategy in both spectral count- and ion current-based methods. >60% increase of total quantified spectra/peptides was respectively achieved for analyzing a spike-in sample set and a public dataset from CPTAC. Incorporating the peptide retrieval strategy significantly improved the quantitative accuracy and precision, especially for low-abundance proteins (e.g. one-hit proteins). Moreover, the capacity of confidently discovering significantly-altered proteins was also enhanced substantially, as demonstrated with two spike-in datasets. In summary, improved quantitative performance was achieved by this peptide recovery strategy without compromising confidence of protein identification, which can be readily implemented in a broad range of quantitative proteomics techniques including label-free or labeling approaches.

SIGNIFICANCE

We hypothesize that more quantifiable spectra and peptides in a protein, even including less confident peptides, could help reduce variations and improve protein quantification. Hence the peptide retrieval strategy was developed and evaluated in two spike-in sample sets with different LC-MS/MS variations using both MS1- and MS2-based quantitative approach. The list of confidently identified proteins using the standard target-decoy search strategy was fixed and more spectra/peptides with less confidence matched to confident proteins were retrieved. However, the total peptide-spectrum-match false discovery rate (PSM FDR) after retrieval analysis was still controlled at a confident level of FDR≤1%. As expected, the penalty for occasionally incorporating incorrect peptide identifications is negligible by comparison with the improvements in quantitative performance. More quantifiable peptides, lower missing value rate, better quantitative accuracy and precision were significantly achieved for the same protein identifications by this simple strategy. This strategy is theoretically applicable for any quantitative approaches in proteomics and thereby provides more quantitative information, especially on low-abundance proteins.

The genomic landscape of core-binding factor acute myeloid leukemias

Acute myeloid leukemia (AML) comprises a heterogeneous group of leukemias frequently defined by recurrent cytogenetic abnormalities, including rearrangements involving the core-binding factor (CBF) transcriptional complex. To better understand the genomic landscape of CBF-AMLs, we analyzed both pediatric (n = 87) and adult (n = 78) samples, including cases with RUNX1-RUNX1T1 (n = 85) or CBFB-MYH11 (n = 80) rearrangements, by whole-genome or whole-exome sequencing. In addition to known mutations in the Ras pathway, we identified recurrent stabilizing mutations in CCND2, suggesting a previously unappreciated cooperating pathway in CBF-AML. Outside of signaling alterations, RUNX1-RUNX1T1 and CBFB-MYH11 AMLs demonstrated remarkably different spectra of cooperating mutations, as RUNX1-RUNX1T1 cases harbored recurrent mutations in DHX15 and ZBTB7A, as well as an enrichment of mutations in epigenetic regulators, including ASXL2 and the cohesin complex. This detailed analysis provides insights into the pathogenesis and development of CBF-AML, while highlighting dramatic differences in the landscapes of cooperating mutations for these related AML subtypes.

Removal of SDS from biological protein digests for proteomic analysis by mass spectrometry

Background

Metal-organic frameworks (MOFs - MIL-101) are the most exciting, high profiled developments in nanotechnology in the last ten years, and it attracted considerable attention owing to their uniform nanoporosity, large surface area, outer-surface modification and in-pore functionality for tailoring the chemical properties of the material for anchoring specific guest moieties. MOF’s have been particularly highlighted for their excellent gas storage and separation properties. Recently biomolecules-based MOF’s were used as nanoencapsulators for antitumor and antiretroviral controlled drug delivery studies. However, usage of MOF material for removal of ionic detergent-SDS from biological samples has not been reported to date. Here, first time we demonstrate its novel applications in biological sample preparation for mass spectrometry analysis.

Methods

SDS removal using MIL-101 was assessed for proteomic analysis by mass spectrometry. We analysed removal of SDS from 0.5 % SDS solution alone, BSA mixture and HMEC cells lysate protein mixture. The removal of SDS by MIL-101 was confirmed by MALDI-TOF-MS and LC-MS techniques.

Results

In an initial demonstration, SDS has removed effectively from 0.5 % SDS solution by MIL-101via its binding attraction with SDS. Further, the experiment also confirmed that MIL-101 strongly removed the SDS from BSA and cell lysate mixtures.

Conclusions

These results suggest that SDS removal by the MIL-101 method is a practical, simple and broad applicable in proteomic sample processing for MALDI-TOF-MS and LC-MS analysis.

Quantitative Analysis of Human Pluripotency and Neural Specification by In-Depth (Phospho)Proteomic Profiling

Controlled differentiation of human embryonic stem cells (hESCs) can be utilized for precise analysis of cell type identities during early development. We established a highly efficient neural induction strategy and an improved analytical platform, and determined proteomic and phosphoproteomic profiles of hESCs and their specified multipotent neural stem cell derivatives (hNSCs). This quantitative dataset (nearly 13,000 proteins and 60,000 phosphorylation sites) provides unique molecular insights into pluripotency and neural lineage entry. Systems-level comparative analysis of proteins (e.g., transcription factors, epigenetic regulators, kinase families), phosphorylation sites, and numerous biological pathways allowed the identification of distinct signatures in pluripotent and multipotent cells. Furthermore, as predicted by the dataset, we functionally validated an autocrine/paracrine mechanism by demonstrating that the secreted protein midkine is a regulator of neural specification. This resource is freely available to the scientific community, including a searchable website, PluriProt.

Differential Potential of Pharmacological PARP Inhibitors for Inhibiting Cell Proliferation and Inducing Apoptosis in Human Breast Cancer Cells

BRCA1/2-mutant cells are hypersensitive to inactivation of poly(ADP-ribose) polymerase 1 (PARP-1). We recently showed that inhibition of PARP-1 by NU1025 is strongly cytotoxic for BRCA1-positive BT-20 cells, but not BRCA1-deficient SKBr-3 cells. These results raised the possibility that other PARP-1 inhibitors, particularly those tested in clinical trials, may be more efficacious against BRCA1-deficient SKBr-3 breast cancer cells than NU1025. Thus, in the presented study the cytotoxicity of four PARP inhibitors under clinical evaluation (olaparib, rucaparib, iniparib and AZD2461) was examined and compared to that of NU1025. The sensitivity of breast cancer cells to the PARP-1 inhibition strongly varied. Remarkably, BRCA-1-deficient SKBr-3 cells were almost completely insensitive to NU1025, olaparib and rucaparib, whereas BRCA1-expressing BT-20 cells were strongly affected by NU1025 even at low doses. In contrast, iniparib and AZD2461 were cytotoxic for both BT-20 and SKBr-3 cells. Of the four tested PARP-1 inhibitors only AZD2461 strongly affected cell cycle progression. Interestingly, the anti-proliferative and pro-apoptotic potential of the tested PARP-1 inhibitors clearly correlated with their capacity to damage DNA. Further analyses revealed that proteomic signatures of the two studied breast cancer cell lines strongly differ, and a set of 197 proteins was differentially expressed in NU1025-treated BT-20 cancer cells. These results indicate that BT-20 cells may harbor an unknown defect in DNA repair pathway(s) rendering them sensitive to PARP-1 inhibition. They also imply that therapeutic applicability of PARP-1 inhibitors is not limited to BRCA mutation carriers but can be extended to patients harboring deficiencies in other components of the pathway(s).

A multi-model statistical approach for proteomic spectral count quantitation

The rapid development of mass spectrometry (MS) technologies has solidified shotgun proteomics as the most powerful analytical platform for large-scale proteome interrogation. The ability to map and determine differential expression profiles of the entire proteome is the ultimate goal of shotgun proteomics. Label-free quantitation has proven to be a valid approach for discovery shotgun proteomics, especially when sample is limited. Label-free spectral count quantitation is an approach analogous to RNA sequencing whereby count data is used to determine differential expression. Here we show that statistical approaches developed to evaluate differential expression in RNA sequencing experiments can be applied to detect differential protein expression in label-free discovery proteomics. This approach, termed MultiSpec, utilizes open-source statistical platforms; namely edgeR, DESeq and baySeq, to statistically select protein candidates for further investigation. Furthermore, to remove bias associated with a single statistical approach a single ranked list of differentially expressed proteins is assembled by comparing edgeR and DESeq q-values directly with the false discovery rate (FDR) calculated by baySeq. This statistical approach is then extended when applied to spectral count data derived from multiple proteomic pipelines. The individual statistical results from multiple proteomic pipelines are integrated and cross-validated by means of collapsing protein groups.

BIOLOGICAL SIGNIFICANCE

Spectral count data from shotgun proteomics experiments is semi-quantitative and semi-random, yet a robust way to estimate protein concentration. Tag-count approaches are routinely used to analyze RNA sequencing data sets. This approach, termed MultiSpec, utilizes multiple tag-count based statistical tests to determine differential protein expression from spectral counts. The statistical results from these tag-count approaches are combined in order to reach a final MultiSpec q-value to re-rank protein candidates. This re-ranking procedure is completed to remove bias associated with a single approach in order to better understand the true proteomic differences driving the biology in question. The MultiSpec approach can be extended to multiple proteomic pipelines. In such an instance, MultiSpec statistical results are integrated by collapsing protein groups across proteomic pipelines to provide a single ranked list of differentially expressed proteins. This integration mechanism is seamlessly integrated with the statistical analysis and provides the means to cross-validate protein inferences from multiple proteomic pipelines.

Methods and applications of absolute protein quantification in microbial systems

In the last years the scientific community faced an increased need to provide high-quality data on the concentration of single proteins within a cell. Especially against the background of the fast evolving field of systems biology this does not only apply for a few proteins but preferably for the whole proteome of the organism. Therefore there has been a rapid development from pure identification of proteins via characterization of changes between different conditions by relative protein quantification towards determination of absolute protein amounts for hundreds of protein species in a cell. This review aims for discussion of different small-scale and large-scale approaches for absolute protein quantification in bacterial cells to picture biological processes and explore life in deeper detail. The presented advantages and limitations of various methods may provide interested researchers help to appraise available methods, select the most appropriate technique and avoid common pitfalls during determination of protein concentration in a complex sample.

SerpinB1 Promotes Pancreatic β Cell Proliferation

Although compensatory islet hyperplasia in response to insulin resistance is a recognized feature in diabetes, the factor(s) that promote β cell proliferation have been elusive. We previously reported that the liver is a source for such factors in the liver insulin receptor knockout (LIRKO) mouse, an insulin resistance model that manifests islet hyperplasia. Using proteomics we show that serpinB1, a protease inhibitor, which is abundant in the hepatocyte secretome and sera derived from LIRKO mice, is the liver-derived secretory protein that regulates β cell proliferation in humans, mice, and zebrafish. Small-molecule compounds, that partially mimic serpinB1 effects of inhibiting elastase activity, enhanced proliferation of β cells, and mice lacking serpinB1 exhibit attenuated β cell compensation in response to insulin resistance. Finally, SerpinB1 treatment of islets modulated proteins in growth/survival pathways. Together, these data implicate serpinB1 as an endogenous protein that can potentially be harnessed to enhance functional β cell mass in patients with diabetes.

Compensatory Islet Response to Insulin Resistance Revealed by Quantitative Proteomics

Compensatory islet response is a distinct feature of the prediabetic insulin-resistant state in humans and rodents. To identify alterations in the islet proteome that characterize the adaptive response, we analyzed islets from 5 month old male control, high-fat diet fed (HFD), or obese ob/ob mice by LC-MS/MS and quantified ~1100 islet proteins (at least two peptides) with a false discovery rate < 1%. Significant alterations in abundance were observed for ~350 proteins among groups. The majority of alterations were common to both models, and the changes of a subset of ~40 proteins and 12 proteins were verified by targeted quantification using selected reaction monitoring and western blots, respectively. The insulin-resistant islets in both groups exhibited reduced expression of proteins controlling energy metabolism, oxidative phosphorylation, hormone processing, and secretory pathways. Conversely, an increased expression of molecules involved in protein synthesis and folding suggested effects in endoplasmic reticulum stress response, cell survival, and proliferation in both insulin-resistant models. In summary, we report a unique comparison of the islet proteome that is focused on the compensatory response in two insulin-resistant rodent models that are not overtly diabetic. These data provide a valuable resource of candidate proteins to the scientific community to undertake further studies aimed at enhancing β-cell mass in patients with diabetes. The data are available via the MassIVE repository, under accession no. MSV000079093.

Highly multiplexed and reproducible ion-current-based strategy for large-scale quantitative proteomics and the application to protein expression dynamics induced by methylprednisolone in 60 rats

A proteome-level time-series study of drug effects (i.e., pharmacodynamics) is critical for understanding mechanisms of action and systems pharmacology, but is challenging, because of the requirement of a proteomics method for reliable quantification of many biological samples. Here, we describe a highly reproducible strategy, enabling a global, large-scale investigation of the expression dynamics of corticosteroid-regulated proteins in livers from adrenalectomized rats over 11 time points after drug dosing (0.5–66 h, N = 5/point). The analytical advances include (i) exhaustive tissue extraction with a Polytron/sonication procedure in a detergent cocktail buffer, and a cleanup/digestion procedure providing very consistent protein yields (relative standard deviation (RSD%) of 2.7%–6.4%) and peptide recoveries (4.1–9.0%) across the 60 animals; (ii) an ultrahigh-pressure nano-LC setup with substantially improved temperature stabilization, pump-noise suppression, and programmed interface cleaning, enabling excellent reproducibility for continuous analyses of numerous samples; (iii) separation on a 100-cm-long column (2-μm particles) with high reproducibility for days to enable both in-depth profiling and accurate peptide ion-current match; and (iv) well-controlled ion-current-based quantification. To obtain high-quality quantitative data necessary to describe the 11 time-points protein expression temporal profiles, strict criteria were used to define “quantifiable proteins”. A total of 323 drug-responsive proteins were revealed with confidence, and the time profiles of these proteins provided new insights into the diverse temporal changes of biological cascades associated with hepatic metabolism, response to hormone stimuli, gluconeogenesis, inflammatory responses, and protein translation processes. Most profile changes persisted well after the drug was eliminated. The developed strategy can also be broadly applied in preclinical and clinical research, where the analysis of numerous biological replicates is crucial.

Proteogenomic characterization of human colon and rectal cancer

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

Combined total proteomic and phosphoproteomic analysis of human pluripotent stem cells

Despite advances in understanding pluripotency through traditional cell biology and gene expression profiling, the signaling networks responsible for maintenance of pluripotency and lineage-specific differentiation are poorly defined. To aid in an improved understanding of these networks at the systems level, we present procedures for the combined analysis of the total proteome and total phosphoproteome (termed (phospho)proteome) from human embryonic stem cells (hESCs), human induced pluripotent stem cells (hiPSCs), and their differentiated derivatives. Because there has been considerable heterogeneity in the literature on the culture of pluripotent cells, we first briefly describe our feeder-free cell culture protocol. The focus, however, is on procedures necessary to generate large-scale (phospho)proteomic data from the cells. Human cells are described here, but the (phospho)proteomic procedures are broadly applicable. Detailed procedures are given for lysis of the cells, protein sample preparation and digestion, multidimensional liquid chromatography, analysis by tandem mass spectrometry, and database searches for peptide/protein identification (ID). We summarize additional data analysis procedures, the subject of ongoing efforts.

Standardization of data processing and statistical analysis in comparative plant proteomics experiment

Two-dimensional gel electrophoresis remains the most widely used technique for protein separation in plant proteomics experiments. Despite the continuous technical advances and improvements in current 2-DE protocols, an adequate and correct experimental design and statistical analysis of the data tend to be ignored or not properly documented in current literature. Both proper experimental design and appropriate statistical analysis are requested in order to confidently discuss our results and to conclude from experimental data.In this chapter, we describe a model procedure for a correct experimental design and a complete statistical analysis of proteomic dataset. Our model procedure covers all of the steps in data mining and processing, starting with the data preprocessing (transformation, missing value imputation, definition of outliers) and univariate statistics (parametric and nonparametric tests), and finishing with multivariate statistics (clustering, heat-mapping, PCA, ICA, PLS-DA).

Trauma-associated human neutrophil alterations revealed by comparative proteomics profiling

PURPOSE

Polymorphonuclear neutrophils (PMNs) play an important role in mediating the innate immune response after severe traumatic injury; however, the cellular proteome response to traumatic condition is still largely unknown.

EXPERIMENTAL DESIGN

We applied 2D-LC-MS/MS-based shotgun proteomics to perform comparative proteome profiling of human PMNs from severe trauma patients and healthy controls.

RESULTS

A total of 197 out of ~2500 proteins (being identified with at least two peptides) were observed with significant abundance changes following the injury. The proteomics data were further compared with transcriptomics data for the same genes obtained from an independent patient cohort. The comparison showed that the protein abundance changes for the majority of proteins were consistent with the mRNA abundance changes in terms of directions of changes. Moreover, increased protein secretion was suggested as one of the mechanisms contributing to the observed discrepancy between protein and mRNA abundance changes. Functional analyses of the altered proteins showed that many of these proteins were involved in immune response, protein biosynthesis, protein transport, NRF2-mediated oxidative stress response, the ubiquitin-proteasome system, and apoptosis pathways.

CONCLUSIONS AND CLINICAL RELEVANCE

Our data suggest increased neutrophil activation and inhibited neutrophil apoptosis in response to trauma. The study not only reveals an overall picture of functional neutrophil response to trauma at the proteome level, but also provides a rich proteomics data resource of trauma-associated changes in the neutrophil that will be valuable for further studies of the functions of individual proteins in PMNs.

A time course analysis of the extracellular proteome of Aspergillus nidulans growing on sorghum stover

BACKGROUND

Fungi are important players in the turnover of plant biomass because they produce a broad range of degradative enzymes. Aspergillus nidulans, a well-studied saprophyte and close homologue to industrially important species such as A. niger and A. oryzae, was selected for this study.

RESULTS

A. nidulans was grown on sorghum stover under solid-state culture conditions for 1, 2, 3, 5, 7 and 14 days. Based on analysis of chitin content, A. nidulans grew to be 4-5% of the total biomass in the culture after 2 days and then maintained a steady state of 4% of the total biomass for the next 12 days. A hyphal mat developed on the surface of the sorghum by day one and as seen by scanning electron microscopy the hyphae enmeshed the sorghum particles by day 5. After 14 days hyphae had penetrated the entire sorghum slurry. Analysis (1-D PAGE LC-MS/MS) of the secretome of A. nidulans, and analysis of the breakdown products from the sorghum stover showed a wide range of enzymes secreted. A total of 294 extracellular proteins were identified with hemicellulases, cellulases, polygalacturonases, chitinases, esterases and lipases predominating the secretome. Time course analysis revealed a total of 196, 166, 172 and 182 proteins on day 1, 3, 7 and 14 respectively. The fungus used 20% of the xylan and cellulose by day 7 and 30% by day 14. Cellobiose dehydrogenase, feruloyl esterases, and CAZy family 61 endoglucanases, all of which are thought to reduce the recalcitrance of biomass to hydrolysis, were found in high abundance.

CONCLUSIONS

Our results show that A. nidulans secretes a wide array of enzymes to degrade the major polysaccharides and lipids (but probably not lignin) by 1 day of growth on sorghum. The data suggests simultaneous breakdown of hemicellulose, cellulose and pectin. Despite secretion of most of the enzymes on day 1, changes in the relative abundances of enzymes over the time course indicates that the set of enzymes secreted is tailored to the specific substrates available. Our findings reveal that A. nidulans is capable of degrading the major polysaccharides in sorghum without any chemical pre-treatment.

System response of metabolic networks in Chlamydomonas reinhardtii to total available ammonium

Drastic alterations in macronutrients are known to cause large changes in biochemistry and gene expression in the photosynthetic alga Chlamydomonas reinhardtii. However, metabolomic and proteomic responses to subtle reductions in macronutrients have not yet been studied. When ammonium levels were reduced by 25-100% compared with control cultures, ammonium uptake and growth rates were not affected at 25% or 50% nitrogen-reduction for 28 h. However, primary metabolism and enzyme expression showed remarkable changes at acute conditions (4 h and 10 h after ammonium reduction) compared with chronic conditions (18 h and 28 h time points). Responses of 145 identified metabolites were quantified using gas chromatography-time of flight mass spectrometry; 495 proteins (including 187 enzymes) were monitored using liquid chromatography-ion trap mass spectrometry with label-free spectral counting. Stress response and carbon assimilation processes (Calvin cycle, acetate uptake and chlorophyll biosynthesis) were altered first, in addition to increase in enzyme contents for lipid biosynthesis and accumulation of short chain free fatty acids. Nitrogen/carbon balance metabolism was found changed only under chronic conditions, for example in the citric acid cycle and amino acid metabolism. Metabolism in Chlamydomonas readily responds to total available media nitrogen with temporal increases in short-chain free fatty acids and turnover of internal proteins, long before nitrogen resources are depleted.

Unraveling pancreatic islet biology by quantitative proteomics

The pancreatic islets of Langerhans play a critical role in maintaining blood glucose homeostasis by secreting insulin and several other important peptide hormones. Impaired insulin secretion due to islet dysfunction is linked to the pathogenesis underlying both Type 1 and Type 2 diabetes. Over the past 5 years, emerging proteomic technologies have been applied to dissect the signaling pathways that regulate islet functions and gain an understanding of the mechanisms of islet dysfunction relevant to diabetes. Herein, we briefly review some of the recent quantitative proteomic studies involving pancreatic islets geared towards gaining a better understanding of islet biology relevant to metabolic diseases.

Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present

Mass-spectrometry-based proteomics is continuing to make major contributions to the discovery of fundamental biological processes and, more recently, has also developed into an assay platform capable of measuring hundreds to thousands of proteins in any biological system. The field has progressed at an amazing rate over the past five years in terms of technology as well as the breadth and depth of applications in all areas of the life sciences. Some of the technical approaches that were at an experimental stage back then are considered the gold standard today, and the community is learning to come to grips with the volume and complexity of the data generated. The revolution in DNA/RNA sequencing technology extends the reach of proteomic research to practically any species, and the notion that mass spectrometry has the potential to eventually retire the western blot is no longer in the realm of science fiction. In this review, we focus on the major technical and conceptual developments since 2007 and illustrate these by important recent applications.

Simple sodium dodecyl sulfate-assisted sample preparation method for LC-MS-based proteomics applications

Sodium dodecyl sulfate (SDS) is one of the most popular laboratory reagents used for biological sample extraction; however, the presence of this reagent in samples challenges LC-MS-based proteomics analyses because it can interfere with reversed-phase LC separations and electrospray ionization. This study reports a simple SDS-assisted proteomics sample preparation method facilitated by a novel peptide-level SDS removal step. In an initial demonstration, SDS was effectively (>99.9%) removed from peptide samples through ion substitution-mediated DS(-) precipitation using potassium chloride (KCl), and excellent peptide recovery (>95%) was observed for <20 μg of peptides. Further experiments demonstrated the compatibility of this protocol with LC-MS/MS analyses. The resulting proteome coverage obtained for both mammalian tissues and bacterial samples was comparable to or better than that obtained for the same sample types prepared using standard proteomics preparation methods and analyzed using LC-MS/MS. These results suggest the SDS-assisted protocol is a practical, simple, and broadly applicable proteomics sample processing method, which can be particularly useful when dealing with samples difficult to solubilize by other methods.

Phosphoproteomic analysis: an emerging role in deciphering cellular signaling in human embryonic stem cells and their differentiated derivatives

Cellular signaling is largely controlled by protein phosphorylation. This post-translational modification (PTM) has been extensively analyzed when examining one or a few protein phosphorylation events that effect cell signaling. However, protein kinase-driven signaling networks, comprising total (phospho)proteomes, largely control cell fate. Therefore, large-scale analysis of differentially regulated protein phosphorylation is central to elucidating complex cellular events, including maintenance of pluripotency and differentiation of embryonic stem cells (ESCs). The current technology of choice for total phosphoproteome and combined total proteome plus total phosphoproteome (termed (phospho)proteome) analyses is multidimensional liquid chromatography-(MDLC) tandem mass spectrometry (MS/MS). Advances in the use of MDLC for separation of peptides comprising total (phospho)proteomes, phosphopeptide enrichment, separation of enriched fractions, and quantitative peptide identification by MS/MS have been rapid in recent years, as have improvements in the sensitivity, speed, and accuracy of mass spectrometers. Increasingly deep coverage of (phospho)proteomes is allowing an improved understanding of changes in protein phosphorylation networks as cells respond to stimuli and progress from one undifferentiated or differentiated state to another. Although MDLC-MS/MS studies are powerful, understanding the interpretation of the data is important, and targeted experimental pursuit of biological predictions provided by total (phospho)proteome analyses is needed. (Phospho)proteomic analyses of pluripotent stem cells are in their infancy at this time. However, such studies have already begun to contribute to an improved and accelerated understanding of basic pluripotent stem cell signaling and fate control, especially at the systems-biology level.

Liquid chromatography-mass spectrometry-based quantitative proteomics

LC-MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications due to growing capabilities for broad proteome coverage and good accuracy and precision in quantification. Herein, we review the current LC-MS-based quantification methods with respect to their advantages and limitations and highlight their potential applications.

A bayesian mixture model for comparative spectral count data in shotgun proteomics

Recent developments in mass-spectrometry-based shotgun proteomics, especially methods using spectral counting, have enabled large-scale identification and differential profiling of complex proteomes. Most such proteomic studies are interested in identifying proteins, the abundance of which is different under various conditions. Several quantitative methods have recently been proposed and implemented for this purpose. Building on some techniques that are now widely accepted in the microarray literature, we developed and implemented a new method using a Bayesian model to calculate posterior probabilities of differential abundance for thousands of proteins in a given experiment simultaneously. Our Bayesian model is shown to deliver uniformly superior performance when compared with several existing methods.