Isobaric protein and peptide quantification: perspectives and issues

An important challenge for proteomics is the ability to compare protein levels across biological samples. Since their introduction, isotopic and isobaric peptide labeling have played an important role in relative quantitative comparisons of proteomes. One important drawback of most of the isotopic-labeling techniques is an increase in sample complexity. This problem was successfully addressed with the construction of isobaric labeling strategies, such as isobaric tag for relative and absolute quantification (iTRAQ), tandem mass tagging, the cleavable isobaric affinity tag, dimethylated leucines and isobaric peptide termini labeling. Furthermore, numerous applications for multiplexing using iTRAQ and tandem mass tagging have been reported.     

Deep and quantitative top-down proteomics in clinical and translational research

It has long been understood that it is proteins, expressed and post-translationally modified, that are the primary regulators of both the fate and the function of cells. The ability to measure differences in the expression of the constellation of unique protein forms (proteoforms) with complete molecular specificity has the potential to sharply improve the return on investment for mass spectrometry-based proteomics in translational research and clinical diagnostics.     

Analysis of organelles within the nervous system: impact on brain and organelle functions

Currently, neuroproteomic approaches aimed at the profiling of total brain areas generally mirror the expression of the most abundant proteins, but fail to uncover less abundant proteins. By contrast, the focus on typical brain subproteomes, (e.g., synaptic vesicles, synaptic terminal membranes or the postsynaptic density), may give a more specific insight into brain function. Subproteomes are accessible via several strategies, including subcellular fractionation or affinity-based pull-down approaches. Combined with mass spectrometric quantification approaches, subcellular proteomics is expected to reveal differences in the protein constitution of related cellular organelles. Focusing on novel functions and mechanistic models, we review recent data on the analysis of brain-derived organelles and subproteomes, including presynaptic termini, synaptic vesicles, neuronal plasma membranes, postsynaptic density and neuromelanin granules, which were identified as novel lysosome-related organelles within the human brain.     

Epithelial cell adhesion molecule (EpCAM) is associated with prostate cancer metastasis and chemo/radioresistance via the PI3K/Akt/mTOR signaling pathway

Prostate cancer (CaP) is the second leading malignancy in men. The role of epithelial cell adhesion molecule (EpCAM), also known as CD326, in CaP progression and therapeutic resistance is still uncertain. Here, we aimed to investigate the roles of EpCAM in CaP metastasis and chemo/radioresistance. Expression of EpCAM in CaP cell lines and human CaP tissues was assessed using immunofluorescence and immunohistochemistry, respectively. EpCAM was knocked down (KD) in PC-3, DU145 and LNCaP-C4-2B cells using small interfering RNA (siRNA), and KD results were confirmed by confocal microscope, Western blotting and quantitative real time polymerase chain reaction (qRT-PCR). Cell growth was evaluated by proliferation and colony formation assays. The invasive potential was assessed using a matrigel chamber assay. Tumorigenesis potential was measured by a sphere formation assay. Chemo-/radiosensitivity were measured using a colony formation assay. Over-expression of EpCAM was found in primary CaP tissues and lymph node metastases including cancer cells and surrounding stromal cells. KD of EpCAM suppressed CaP proliferation and invasive ability, reduced sphere formation, enhanced chemo-/radiosensitivity, and down-regulated E-cadherin, p-Akt, p-mTOR, p-4EBP1 and p-S6K expression in CaP cells. Our findings suggest that EpCAM plays an important role in CaP proliferation, invasion, metastasis and chemo-/radioresistance associated with the activation of the PI3K/Akt/mTOR signaling pathway and is a novel therapeutic target to sensitize CaP cells to chemo-/radiotherapy.     

Differential label‐free quantitative proteomic analysis of avian eggshell matrix and uterine fluid proteins associated with eggshell mechanical property

Eggshell strength is a crucial economic trait for table egg production. During the process of eggshell formation, uncalcified eggs are bathed in uterine fluid that plays regulatory roles in eggshell calcification. In this study, a label‐free MS‐based protein quantification technology was used to detect differences in protein abundance between eggshell matrix from strong and weak eggs (shell matrix protein from strong eggshells and shell matrix protein from weak eggshells) and between the corresponding uterine fluids bathing strong and weak eggs (uterine fluid bathing strong eggs and uterine fluid bathing weak eggs) in a chicken population. Here, we reported the first global proteomic analysis of uterine fluid. A total of 577 and 466 proteins were identified in uterine fluid and eggshell matrix, respectively. Of 447 identified proteins in uterine fluid bathing strong eggs, up to 357 (80%) proteins were in common with proteins in uterine fluid bathing weak eggs. Similarly, up to 83% (328/396) of the proteins in shell matrix protein from strong eggshells were in common with the proteins in shell matrix protein from weak eggshells. The large amount of common proteins indicated that the difference in protein abundance should play essential roles in influencing eggshell strength. Ultimately, 15 proteins mainly relating to eggshell matrix specific proteins, calcium binding and transportation, protein folding and sorting, bone development or diseases, and thyroid hormone activity were considered to have closer association with the formation of strong eggshell.     

药用真菌猪苓溶血素基因克隆和序列分析

利用3'-RACE-PCR方法首次从药用真菌猪苓中克隆得到与真菌形态发育相关的溶血素基因。结果表明,猪苓溶血素基因的全长cDNA为744bp,其中编码区占447bp,共编码148个氨基酸,推测其分子量约为15.79kDa,理论等电点为4.89。推定的猪苓溶血素蛋白具有与杨树菇溶血素类蛋白家族相同的结构域和功能位点,两者同源性为60%。系统进化树结果显示猪苓溶血素隶属于担子菌类群。实时荧光定量PCR分析结果表明在菌核形成初期猪苓溶血素基因表达量较高,且显著高于菌丝体中猪苓溶血素基因的转录水平,说明溶血素基因参与了猪苓菌核的形态发育。     

Computational model for autophagic vesicle dynamics in single cells

Macroautophagy (autophagy) is a cellular recycling program essential for homeostasis and survival during cytotoxic stress. This process, which has an emerging role in disease etiology and treatment, is executed in four stages through the coordinated action of more than 30 proteins. An effective strategy for studying complicated cellular processes, such as autophagy, involves the construction and analysis of mathematical or computational models. When developed and refined from experimental knowledge, these models can be used to interrogate signaling pathways, formulate novel hypotheses about systems, and make predictions about cell signaling changes induced by specific interventions. Here, we present the development of a computational model describing autophagic vesicle dynamics in a mammalian system. We used time-resolved, live-cell microscopy to measure the synthesis and turnover of autophagic vesicles in single cells. The stochastically simulated model was consistent with data acquired during conditions of both basal and chemically-induced autophagy. The model was tested by genetic modulation of autophagic machinery and found to accurately predict vesicle dynamics observed experimentally. Furthermore, the model generated an unforeseen prediction about vesicle size that is consistent with both published findings and our experimental observations. Taken together, this model is accurate and useful and can serve as the foundation for future efforts aimed at quantitative characterization of autophagy.