代谢组学在肺癌中的应用

代谢组学是20世纪末逐渐发展起来的一门组学技术.它作为系统生物学的一部分,正广泛应用于包括肿瘤在内的各种疾病的诊断、治疗、预后等方面.肺癌是发病率和病死率最高的肿瘤,肺癌的早期和晚期发现在患者5年生存率上差异巨大,故肺癌的早期诊断意义重大.代谢组学除了应用于确定肺癌诊断的标志物,也可应用于确定肺癌的预后及治疗措施毒性或有效性的相关标志物.后者使得肺癌患者的治疗更加个体化成为可能.同时代谢组学研究也使得我们对肺癌的病理生理过程理解得更加深入.本文就代谢组学的定义和研究方法、代谢组学两大主要技术平台核磁共振和质谱的特点及其在肺癌中的应用作一综述.     

过氧化物酶体增殖物激活受体γ辅助激活因子-1α对不同浓度棕榈酸诱导下INS-1细胞生长及功能改变影响的研究

目的 观察不同浓度棕榈酸培养INS-1细胞时过氧化物酶体增殖物激活受体γ辅助激活因子-1α(PGC-1α)的表达变化及其与细胞增殖、凋亡和胰岛素分泌能力的关系. 方法 INS-1细胞在50、100、400 μmol/L棕榈酸培养4、8、12、24、48 h检测PGC-1α mRNA和蛋白表达、细胞增殖活力、Bcl-2蛋白、基础及葡萄糖刺激的胰岛素分泌. 结果 50 μmol/L棕榈酸培养时,INS-1细胞PGC-1α mRNA48 h有增多趋势,但差异无统计学意义;8、12 h细胞增殖活力降低,24、48 h与对照组比较差异无统计学意义;Bcl-2蛋白表达无变化;48 h基础及葡萄糖刺激胰岛素分泌量增加.100μmol/L棕榈酸培养时,INS-1细胞PGC-1α mRNA 24 h表达增加,48 h蛋白表达增加;8、12、24 h细胞增殖活力降低,48 h与对照组比较差异无统计学意义;Bcl-2蛋白表达无变化;基础及葡萄糖刺激胰岛素分泌量增加.400 μmol/L棕榈酸培养时,INS-1细胞PGC-1α mRNA 12 h表达增加,24 h后PGC-1α蛋白表达进行性增加;8h起细胞增殖活力降低;24 h起Bcl-2蛋白表达减少;48 h基础胰岛素分泌及葡萄糖刺激的胰岛素分泌降低. 结论 轻、中度高脂培养条件下INS-1细胞PGC-1α表达轻度增加,与细胞增殖活力改变和胰岛素分泌能力增加相关,重度高脂培养条件下INS-1细胞PGC-1α表达增加,与细胞增殖活力减低、抗凋亡减少和胰岛素分泌能力受损相关,提示PGC-1α可能参与棕榈酸对INS-1细胞增殖、凋亡及功能改变的影响.     

CD8+ T-cell recognition of a synthetic epitope formed by t-butyl modification

We set out to clone Bax-specific CD8⁺ T cells from peripheral blood samples of patients with primary chronic lymphocytic leukaemia. A number of clones were generated using a Bax peptide pool and their T-cell epitope was mapped to two peptides sharing a common 9-amino-acid sequence (LLSYFGTPT), restricted by HLA-A*0201. However, when these T-cell clones were tested against highly purified syntheses (> 95%) of the same peptide sequence, there was no functional response. Subsequent mass spectrometric analysis and HPLC fractionation suggested that the active component in the original crude peptide preparations (77% pure) was a peptide with a tert-butyl (tBu) modification of the tyrosine residue. This was confirmed by modification of the inactive wild-type sequence to generate functionally active peptides. Computer modelling of peptide:HLA-A*0201 structures predicted that the tBu modification would not affect interactions between peptide residues and the HLA binding site. However, these models did predict that the tBu modification of tyrosine would result in an extension of the side chain out of the peptide-binding groove up towards the T-cell receptor. This modified product formed < 1% of the original P603 crude peptide preparation and < 0·05% of the original 23-peptide mixture used for T-cell stimulation. The data presented here, illustrate the potential for chemical modifications to change the immunogenicity of synthetic peptides, and highlight the exquisite capacity of T-cell receptors to discriminate between structurally similar peptide sequences. Furthermore, this study highlights potential pitfalls associated with the use of synthetic peptides for the monitoring and modulating of human immune responses.     

Altered protein expression profile associated with phenotypic changes in lung fibroblasts co-cultured with gold nanoparticle-treated small airway epithelial cells

Despite the availability of toxicity studies on cellular exposure to gold nanoparticles (AuNPs), there is scarcity of information with regard to the bystander effects induced by AuNPs on neighboring cells not exposed to the NPs. In this study, we showed that exposure of small airway epithelial cells (SAECs) to AuNPs induced changes in protein expression associated with functional effects in neighboring MRC5 lung fibroblasts in a co-culture system. Uptake of 20 nm size AuNPs by SAECs was first verified by focused ion beam scanning electron microscopy. Subsequently, pretreated SAECs were co-cultured with unexposed MRC5 lung fibroblasts, which then underwent proteome profiling using a quantitative proteomic approach. Stable-isotope labeling by amino acids in cell culture (SILAC)–based mass spectrometry identified 109 proteins (which included 47 up-regulated and 62 down-regulated proteins) that were differentially expressed in the lung fibroblasts co-cultured with AuNP pretreated SAECs. There was altered expression of proteins such as Paxillin, breast cancer anti-estrogen resistance 1 and Caveolin-1, which are known to be involved in the cell adhesion process. Morphological studies revealed that there was a concomitant increase in cell adhesion and altered F-actin stress fiber arrangement involving vinculin in the lung fibroblasts. It is likely that phenotypic changes observed in the underlying lung fibroblasts were mediated by AuNP-induced downstream signals in the pretreated SAECs and cell–cell cross talk.     

A proteomic analysis on human sperm tail: comparison between normozoospermia and asthenozoospermia

Purpose

Asthenozoospermia is a common cause of human male infertility characterized by reduced sperm motility. The molecular mechanism that impairs sperm motility is not fully understood. This study proposed to identify novel biomarkers by focusing on sperm tail proteomic analysis of asthenozoospermic patients.

Methods

Sperm were isolated from normozoospermic and asthenozoospermic semen samples. Tail fractions were obtained by sonication followed by Percoll gradient. The proteins were extracted by solubilization and subjected to two-dimensional gel electrophoresis (2-DE); then, the spots were analyzed using Image Master 2D Platinum software. The significantly increased/decreased amounts of proteins in the two groups were exploited by matrix-assisted laser desorption-ionization time-of-flight/time-of-flight (MALDI-TOF-TOF) mass spectrometry.

Results

Three hundred ninety protein spots were detected in both groups. Twenty-one protein spots that had significantly altered amounts (p < 0.05) were excised and exploited using MALDI-TOF-TOF mass spectrometry. They led to the identification of the following 14 unique proteins: Tubulin beta 2B; glutathione S-transferase Mu 3; keratin, type II cytoskeletal 1; outer dense fiber protein 2; voltage-dependent anion-selective channel protein 2; A-kinase anchor protein 4; cytochrome c oxidase subunit 6B; sperm protein associated with the nucleus on the X chromosome B; phospholipid hydroperoxide glutathione peroxidase-mitochondrial; isoaspartyl peptidase/L-asparaginase; heat shock-related 70 kDa protein 2; stress-70 protein, mitochondrial; glyceraldehyde-3-phosphate dehydrogenase, testis-specific and clusterin.

Conclusion

Fourteen proteins present in different amounts in asthenozoospermic sperm tail samples were identified, four of which are reported here for the first time. These proteins might be used as markers for the better diagnosis of sperm dysfunctions, targets for male contraceptive development, and to predict embryo quality.     

From the Cover: Searching molecular structure databases with tandem mass spectra using CSI:FingerID

Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin.Metabolites, small molecules that are involved in cellular reactions, can provide detailed information about cellular state. Untargeted metabolomic studies may use NMR or MS technologies, but liquid chromatography followed by MS (LC/MS) can detect the highest number of metabolites from minimal amounts of sample (1, 2). Untargeted metabolomics comprehensively compares the mass spectral intensities of metabolite signals (peaks) between two or more samples (3, 4). Advances in MS instrumentation allow us to simultaneously detect thousands of metabolites in a biological sample. Identification of these compounds relies on tandem MS (MS/MS) data, produced by fragmenting the compound and recording the masses of the fragments. Structural elucidation remains a challenging problem, in particular for compounds that cannot be found in any spectral library (1): In total, all available spectral MS/MS libraries of pure chemical standards cover fewer than 20,000 compounds (5). Growth of spectral libraries is limited by the unavailability of pure reference standards for many compounds.In contrast, molecular structure databases such as PubChem (6) and ChemSpider (7) contain millions of compounds, with PubChem alone having surpassed 50 million entries. Searching in molecular structure databases using MS/MS data is therefore considered a powerful tool for assisting an expert in the elucidation of a compound. This problem is considerably harder than the fundamental analysis step in the shotgun proteomics workflow, namely, searching peptide MS/MS data in a peptide sequence database (8): Unlike proteins and peptides, metabolites show a large structural variability and, consequently, also large variations in MS/MS fragmentation. Computational approaches for interpreting and predicting MS/MS data of small molecules date back to the 1960s (9): Due to the unavailability of molecular structure databases at that time, structure libraries were combinatorially generated and then “searched” using the experimental MS/MS data. “Modern” methods for this question have been developed since mid-2000. Particular progress has been made for restricted metabolite classes such as lipids (5), but as with peptides, results cannot be generalized to other metabolite classes. For the general case, several strategies have been proposed during recent years, including simulation of mass spectra from molecular structure (10, 11), combinatorial fragmentation (12–17), and prediction of molecular fingerprints (18, 19).Searching in a molecular structure database is clearly limited to those compounds present in the database. Fragmentation trees have been introduced as a means of analyzing MS/MS data without the need of any (structural or spectral) database (20–22). In this paper, the term “fragmentation tree” is exclusively used to refer to the graph-theoretical concept introduced in ref. 20, not “spectral trees” that describe the dependencies of multiple MS measurements; see Vaniya and Fiehn (23) for a review. In more detail, our fragmentation trees are predicted from MS/MS data by an automated computational method such that peaks in the MS/MS spectrum are annotated with molecular formulas of the corresponding fragments, and fragments are connected via assumed losses. Clearly, there exist other approaches with the broad aim of identifying metabolites, such as network-based methods (24–26) and combined approaches (27); see Hufsky et al. (28) for a review of computational methods in MS-based metabolite identification.It is undisputed that MS/MS data alone are insufficient for full structural elucidation of metabolites. We argue that elucidation of stereochemistry is currently beyond the power of automated search engines, so we try to recover the correct constitution (bond structure) of the query molecule, that is, the identity and connectivity (with bond multiplicities) of the atoms, but no stereochemistry information. Throughout this paper, we refer to the constitution of the molecule as its structure. In practice, orthogonal information is usually available, both analytical (retention time, ion mobility drift time, infrared and UV spectroscopy, and NMR data) and on the experimental setup (extraction procedure and organism) (29, 30). We assume that this information is not presented to the search engines but rather used in a postprocessing step to manually select the best solution from the output list of the engine. This is comparable to the everyday use of search engines for the internet.Here, we present CSI (Compound Structure Identification):FingerID for searching a molecular structure database using MS/MS data. Our method combines computation and comparison of fragmentation trees with machine learning techniques for the prediction of molecular properties of the unknown compound (19). Our method shows significantly increased identification rates compared with all existing state-of-the-art methods for the problem. CSI:FingerID is available at www.csi-fingerid.org/. Our method can expedite the identification of metabolites in an untargeted workflow for the numerous cases where no reference measurements are available in spectral libraries.     

Microdroplet fusion mass spectrometry for fast reaction kinetics

We investigated the fusion of high-speed liquid droplets as a way to record the kinetics of liquid-phase chemical reactions on the order of microseconds. Two streams of micrometer-size droplets collide with one another. The droplets that fused (13 μm in diameter) at the intersection of the two streams entered the heated capillary inlet of a mass spectrometer. The mass spectrum was recorded as a function of the distance x between the mass spectrometer inlet and the droplet fusion center. Fused droplet trajectories were imaged with a high-speed camera, revealing that the droplet fusion occurred approximately within a 500-μm radius from the droplet fusion center and both the size and the speed of the fused droplets remained relatively constant as they traveled from the droplet fusion center to the mass spectrometer inlet. Evidence is presented that the reaction effectively stops upon entering the heated inlet of the mass spectrometer. Thus, the reaction time was proportional to x and could be measured and manipulated by controlling the distance x. Kinetic studies were carried out in fused water droplets for acid-induced unfolding of cytochrome c and hydrogen–deuterium exchange in bradykinin. The kinetics of the former revealed the slowing of the unfolding rates at the early stage of the reaction within 50 μs. The hydrogen–deuterium exchange revealed the existence of two distinct populations with fast and slow exchange rates. These studies demonstrated the power of this technique to detect reaction intermediates in fused liquid droplets with microsecond temporal resolution.Time-resolved measurements of reaction intermediates are crucial for understanding the fast kinetics of chemical reactions. Various approaches have been implemented to improve the temporal resolution of kinetic measurements in liquid reactions (1, 2), which are often limited by the mixing time. One approach for improving the mixing time involves the use of turbulent flow to increase the shear stress in fluid channels (3). Another approach is to stimulate the rapid initiation of a reaction by photo-triggered initiation (4), electron transfer (5), or temperature jump/rise (6). A small-size reactor was also used for rapid mixing so that the time required for diffusion-dependent mixing is minimized (7–10).Among various methods for detecting reaction intermediates, mass spectrometry has been a powerful tool for probing reaction products because it can discriminate similar species by their mass-to-charge ratio while simultaneously measuring multiple species. Time-resolved mass spectrometry (11) has been widely used for measuring the kinetics of protein–ligand complexation, organometallic compound formation, and enzyme-catalyzed processes. Despite these efforts for improving temporal resolution, time-resolved mass spectrometry has been limited to the millisecond timescale, with a recent achievement of 300 μs (12).A major obstacle for improving the timescale of kinetic measurements in the liquid phase involves the diffusion-limited mixing time of reactants in bulk solution. Carroll and Hidrovo (13) reported that a substantial improvement in mixing time could be achieved by colliding liquid droplets through inertial mixing. They used droplets ranging from 90 μm to 115 μm in diameter that were traveling at a speed of ∼0.5 m/s to achieve a mixing time of ∼600 μs. Because the mixing time under the inertial mixing is proportional to the system’s length scale and inversely proportional to the speed of colliding droplets (13), the mixing time can be further reduced to microseconds by decreasing droplet size and increasing collision speed. In this study, we generated micrometer-size liquid droplets of 13 ± 6 μm in diameter using pressurized nebulizing nitrogen gas. The propulsive force from the pressurized gas formed a stream of high-speed liquid droplets traveling in air at a speed of 84 ± 18 m/s. The collision of two high-speed streams of micrometer-size liquid droplets allowed for their rapid mixing, estimated to be less than a few microseconds. The resulting fused droplets were directed to a mass spectrometer that determined the masses of intermediates and final reaction products. Thus, the mixing time is expected to be essentially negligible in comparison with the travel time of the fused droplet to the inlet of the mass spectrometer.The reaction progressed as the fused droplet traveled in air to the inlet of the mass spectrometer. Once inside the heated inlet, the reaction was effectively complete. Although this might seem surprising, evidence for this behavior will be presented later, based on the observation of first-order kinetics of a known reaction. The fusion events and the distribution of droplet speeds were characterized by recording images with a camera running at 120,000 frames per second (fps). The fast mixing of micrometer-size liquid droplets traveling at a high speed enabled kinetic measurement with 3-μs temporal resolution and a dead time less than a few microseconds. We applied this technique to measure the kinetics on the microsecond timescale of the acid-induced unfolding of cytochrome c and the hydrogen–deuterium exchange (HDX) in the 9-aa peptide bradykinin.