Characterization of the human serum depletome by label-free shotgun proteomics

While it is known that immunoaffinity depletion of abundant proteins in serum removes additional proteins beyond those targeted, there has been little characterization of the co-depleted proteins in the high abundant fraction, which we refer to here as the "depletome". We present evidence of co-depletion of non-targeted proteins in human serum using a top-20 immunodepletion column, as shown by label-free liquid chromatography mass spectrometry (LC-MS(E)) profiling. This led to identification of 147 proteins which were specific for this fraction and comprised proteins with functions predominantly in binding and transport of nucleotides, metal ions, carbohydrates and lipids. These results suggest that further studies on this commonly ignored serum fraction may provide new insights into clinical proteomics.     

Screen-printed electrochemical sensors for label-free potentiometric and impedimetric detection of human serum albumin

Herein, two electrochemical methods based on potentiometric and impedimetric transductions were presented for albumin targeting, employing screen-printed platforms (SPEs) to make easy and cost-effective sensors with good detection merits. The SPEs incorporated ion-to-electron multi-walled carbon nanotubes (MWCNTs) transducer. Sensors were constructed using either tridodecyl methyl-ammonium chloride (TDMACl) (sensor I) or aliquate 336S (sensor II) in plasticized polymeric matrices of carboxylated poly (vinyl chloride) (PVC-COOH). Analytical performances of the sensors were evaluated using the above-mentioned electrochemical techniques. For potentiometric assay, constructed sensors responded to albumin with −81.7 ± 1.7 (r² = 0.9986) and −146.2 ± 2.3 mV/decade (r² = 0.9991) slopes over the linearity range 1.5 μM–1.5 mM with 0.8 and 1.0 μM detection limits for respective TDMAC- and aliquate-based sensors. Interference study showed apparent selectivity for both sensors. Impedimetric assays were performed at pH = 7.5 in 10 mM PBS buffer solution with a 0.02 M [Fe(CN)₆]^−3/−4 redox-active electrolyte. Sensors achieved detection limits of 4.3 × 10⁻⁸ and 1.8 × 10⁻⁷ M over the linear ranges of 5.2×10⁻⁸–1.0×10⁻⁴ M and 1.4×10⁻⁶–1.4×10⁻³ M, with 0.09 ± 0.004 and 0.168 ± 0.009 log Ω/decade slopes for sensors based on TDMAC and aliquate, respectively. These sensors are characterized with simple construction, high sensitivity and selectivity, fast response time, single-use, and cost-effectiveness. The methods were successfully applied to albumin assessment in different biological fluids.     

人血清内源性多肽无标记定量分析新策略

多肽组学(Pepti domics)以其在疾病标志物发现中所起的重要作用正受到越来越多的关注.然而,目前尚缺少针对多肽组学的高效定量方法.本文建立了一种基于纳升液相色谱与四极杆飞行时间质谱联用(μLC-Q-TOF-MS/MS)系统的色谱峰面积无标记多肽定量方法.该方法首先对两组样品中的多肽进行相对定量,然后选取相对量大于2或小于0.5的多肽,用纳升液相色谱与串联二级质谱(μLC-MS/MS)的选择性数据依赖模式(DDA)进行序列鉴定.将不同量标准样品牛血清白蛋白(BSA)酶解液加入到相同量的正常人血清样品中,然后用该方法进行定量分析,得到的定量结果平均相对偏差为6.42%.该方法分别被用于健康人血清与肝细胞癌(HCC)以及乳腺癌病人血清中内源性多肽的定量比较分析,并成功鉴定了血清中一些与HCC和乳腺癌相关的内源性多肽.由于Q-TOF-MS/MS的高分辨率和宽质量检测范围,价态高达+5和分子量超过4000的多肽也可被可靠地进行定性和定量分析.实验结果进一步表明在多肽组学分析中μLC-Q-TOF-MS/MS比传统的MALDI-TOF-MS具有更高的检测灵敏度.     

A strategy with label-free quantification of the targeted peptides for quantitative peptidome analysis of human serum

Peptidomics draws more and more attention in discovering useful biomarkers for early diagnosis of disease. However, there is lack of efficient quantification strategy in peptidome analysis. In this study, a strategy with label-free quantification of the targeted endogenous peptides based on peak intensity using μUPLC-Q-TOF-MS/MS was developed for quantitative peptidome analysis of human serum. Different amounts of standard BSA tryptic digesting peptides were added into the same serum extracts for evaluation...     

Data processing pipelines for comprehensive profiling of proteomics samples by label-free LC-MS for biomarker discovery

Label-free quantitative LC-MS profiling of complex body fluids has become an important analytical tool for biomarker and biological knowledge discovery in the past decade. Accurate processing, statistical analysis and validation of acquired data diversified by the different types of mass spectrometers, mass spectrometer parameter settings and applied sample preparation steps are essential to answer complex life science research questions and understand the molecular mechanism of disease onset and developments. This review provides insight into the main modules of label-free data processing pipelines with statistical analysis and validation and discusses recent developments. Special emphasis is devoted to quality control methods, performance assessment of complete workflows and algorithms of individual modules. Finally, the review discusses the current state and trends in high throughput data processing and analysis solutions for users with little bioinformatics knowledge.     

CSF biomarker discovery using label-free nano-LC-MS based proteomic profiling: technical aspects

Biomarker discovery in cerebrospinal fluid (CSF) can provide important information helping to diagnose and monitor disease progression in brain disorders. We present a label-free LC-MS strategy to investigate the proteomic profile of CSF. We provide a framework and protocol addressing quality control, sample replication steps and the adaptation of pattern recognition methods for the detection of experimental variation and (most importantly) putative biomarkers. This strategy was tested using a total of 20 CSF samples (ten samples from healthy volunteers and ten from schizophrenia patients). A clear difference was found between healthy volunteers and schizophrenia patients. With technical and biological variation controlled, we were able to detect 77 proteins with confidence in CSF, of which seven were newly identified, without prior depletion of abundant protein species. Our strategy provides a simple and controlled method for CSF biomarker discovery.     

Carbon dots as a fluorescent probe for label-free detection of physiological potassium level in human serum and red blood cells

A unique photoluminescence carbon dots (CDs) with larger size were prepared by microwave-assisted method. Complex functional groups on the surface of the CDs facilitate the nanoparticles to form affinity with some metal ions. Taking advantage of the effective fluorescence quenching effect of K⁺, a highly sensitive CD-based fluorescence analytical system for label-free detection of K⁺ with limit of detection (LOD) 1.0 × 10⁻¹² M was established. The concentrations of potassium ion in biological samples such as human serum are usually found at millimolar levels or even higher. The proposed method begins with a substantial dilution of the sample to place the K⁺ concentration in the dynamic range for quantification, which covers 3 orders of magnitude. This offers some advantages: the detection of K⁺ only needs very small quantities of biological samples, and the dilution of samples such as serum may effectively eliminate the potential interferences that often originate from the background matrix. The determined potassium levels were satisfactory and closely comparable with the results given by the hospital, indicating that this fluorescent probe is applicable to detection of physiological potassium level with high accuracy. Compared with other relative biosensors requiring modified design, bio-molecular modification or/and sophisticated instruments, this CD-based sensor is very simple, cost-effective and easy detection, suggesting great potential applications for successively monitoring physiological potassium level and the change in biological system.     

Automated quantum mechanical total line shape fitting model for quantitative NMR-based profiling of human serum metabolites

An automated quantum mechanical total line shape (QMTLS) fitting model was implemented for quantitative nuclear magnetic resonance (NMR)-based profiling of 42 metabolites in ultrafiltrated human serum samples. Each metabolite was described by a set of chemical shifts, J-couplings, and line widths. These parameters were optimized for each metabolite in each sample by iteratively minimizing the difference between the calculated and the experimental spectrum. In total, 92.0 to 98.1 % of the signal intensities in the experimental spectrum could be explained by the calculated spectrum. The model was validated by comparison to signal integration of metabolites with isolated signals and by means of standard additions. Metabolites present at average concentration higher than 50 μM were quantified with average absolute relative error less than 10 % when using different initial parameters for the fitting procedure. Furthermore, the biological applicability of the QMTLS model was demonstrated on 287 samples from an intervention study in 37 human volunteers undergoing an exercise challenge. Our automated QMTLS model was able to cope with the large dynamic range of metabolite concentrations in serum and proved to be suitable for high-throughput analysis.

Metabolic profiling reveals new serum biomarkers for differentiating diabetic nephropathy

Capillary electrophoresis coupled with time-of-flight mass spectrometry was used to explore new serum biomarkers with high sensitivity and specificity for diabetic nephropathy (DN) diagnosis, through comprehensive analysis of serum metabolites with 78 diabetic patients. Multivariate analyses were used for identification of marker candidates and development of discriminative models. Of the 289 profiled metabolites, orthogonal partial least-squares discriminant analysis identified 19 metabolites that could distinguish between DN with macroalbuminuria and diabetic patients without albuminuria. These identified metabolites included creatinine, aspartic acid, γ-butyrobetaine, citrulline, symmetric dimethylarginine (SDMA), kynurenine, azelaic acid, and galactaric acid. Significant correlations between all these metabolites and urinary albumin-to-creatinine ratios (p?<?0.009, Spearman’s rank test) were observed. When five metabolites (including γ-butyrobetaine, SDMA, azelaic acid and two unknowns) were selected from 19 metabolites and applied for multiple logistic regression model, AUC value for diagnosing DN was 0.927 using the whole dataset, and 0.880 in a cross-validation test. In addition, when four known metabolites (aspartic acid, SDMA, azelaic acid and galactaric acid) were applied, the resulting AUC was still high at 0.844 with the whole dataset and 0.792 with cross-validation. Combination of serum metabolomics with multivariate analyses enabled accurate discrimination of DN patients. The results suggest that capillary electrophoresis-mass spectrometry based metabolome analysis could be used for DN diagnosis.     

Secretome of the preimplantation human embryo by bottom-up label-free proteomics

A bottom-up label-free mass spectrometric proteomic strategy was used to analyse the protein profiles of the human embryonic secretome. Culture media samples used for embryonic culture of patients undergoing intracytoplasmic sperm injection cycles were selected as a test case for this exploratory proof-of-principle study. The media were stored after embryo transfer and then pooled into positive (n = 8) and negative (n = 8) implantation groups. The absolute quantitative bottom-up technique employed a multidimensional protein identification technology based on separation by nano-ultra-high pressure chromatography and identification via tandem nano-electrospray ionization mass spectrometry with data-independent scanning in a hydrid QqTOF mass spectrometer. By applying quantitative bottom-up proteomics, unique proteins were found exclusively in both the positive- and negative-implantation groups, which suggest that competent embryos express and secrete unique biomarker proteins into the surrounding culture medium. The selective monitoring of these possible secretome biomarkers could make viable procedures using single-embryo transfer.     

Metabolite profiling and beyond: approaches for the rapid processing and annotation of human blood serum mass spectrometry data

In this paper, we describe data processing and metabolite identification approaches which lead to a rapid and semi-automated interpretation of metabolomics experiments. Data from metabolite fingerprinting using LC-ESI-Q-TOF/MS were processed with several open-source software packages, including XCMS and CAMERA to detect features and group features into compound spectra. Next, we describe the automatic scheduling of tandem mass spectrometry (MS) acquisitions to acquire a large number of MS/MS spectra, and the subsequent processing and computer-assisted annotation towards identification using the R packages MetShot, Rdisop, and the MetFusion application. We also implement a simple retention time prediction model using predicted lipophilicity logD, which predicts retention times within 42 s (6 min gradient) for most compounds in our setup. We putatively identified 44 common metabolites including several amino acids and phospholipids at metabolomics standards initiative (MSI) levels two and three and confirmed the majority of them by comparison with authentic standards at MSI level one. To aid both data integration within and data sharing between laboratories, we integrated data from two labs and mapped retention times between the chromatographic systems. Despite the different MS instrumentation and different chromatographic gradient programs, the mapped retention times agree within 26 s (20 min gradient) for 90 % of the mapped features.

A new CZE method for profiling human serum albumin and its related forms to assess the quality of biopharmaceuticals

We present a new CZE method, which uses a polyethylene oxide-coated capillary to separate native HSA from more than five of its structural variants. These variants include oxidized, truncated, and cysteinylated forms of HSA which can all be found in biopharmaceutical products. Both CE and MS confirmed the high degree of heterogeneity of HSA preparations. Recovery studies demonstrated that adsorption of HSA on the capillary was significantly reduced under the conditions we developed, which led to a satisfactory repeatability (RSD for migration times and relative peak areas were less than 0.2 and 7.0%, respectively). Assignment of the main peaks was attempted using in vitro degraded/stressed HSA. We used our method to test batch-to-batch comparability and detected slight quantitative differences in the proportion of native HSA in batches produced from different fractionation methods.     

Multiplex suspension array for human anti-carbohydrate antibody profiling

Glycan-binding antibodies form a significant subpopulation of both natural and acquired antibodies and play an important role in various immune processes. They are for example involved in innate immune responses, cancer, autoimmune diseases, and neurological disorders. In the present study, a microsphere-based flow-cytometric immunoassay (suspension array) was applied for multiplexed detection of glycan-binding antibodies in human serum. Several approaches for immobilization of glycoconjugates onto commercially available fluorescent microspheres were compared, and as the result, the design based on coupling of end-biotinylated glycopolymers has been selected. This method requires only minute amounts of glycans, similar to a printed glycan microarray. The resulting glyco-microspheres were used for detection of IgM and IgG antibodies directed against ABO blood group antigens. The possibility of multiplexing this assay was demonstrated with mixtures of microspheres modified with six different ABO related glycans. Multiplexed detection of anti-glycan IgM and IgG correlated well with singleplex assays (Pearson's correlation coefficient r = 0.95-0.99 for sera of different blood groups). The suspension array in singleplex format for A/B trisaccharide, H(di) and Le(x) microspheres corresponded well to the standard ELISA (r > 0.94). Therefore, the described method is promising for rapid, sensitive, and reproducible detection of anti-glycan antibodies in a multiplexed format.     

Precision profiling and identification of human serum peptides using Fourier transform ion cyclotron resonance mass spectrometry

Many biomarker discovery studies are based on matrix-assisted laser desorption/ionisation (MALDI) peptide profiles. In this study, 96 human serum samples were analysed on a Bruker solariX(TM) MALDI Fourier transform ion cyclotron resonance (FTICR) system equipped with a 15 tesla magnet. Isotopically resolved peptides were observed in ultrahigh resolution FTICR profiles up to m/z 6500 with mass measurement errors (MMEs) of previously identified peptides at a sub-ppm level. For comparison with our previous platform for peptide profile mass analysis (i.e. Ultraflex II) the corresponding time-of-flight (TOF) spectra were obtained with isotopically resolved peptides up to m/z 3500. The FTICR and TOF systems performed rather similar with respect to the repeatability of the signal intensities. However, the mass measurement precision improved at least 10-fold in ultrahigh resolution data and thus simplified spectral alignment necessary for robust and quantitatively precise comparisons of profiles in large-scale clinical studies. From each single MALDI-FTICR spectrum an m/z-list was obtained with sub-ppm precision for all different species, which is beneficial for identification purposes and interlaboratory comparisons. Furthermore, the FTICR system allowed new peptide identifications from collision-induced dissociation (CID) spectra using direct infusion of reversed-phase (RP) C(18)-fractionated serum samples on an electrospray ionisation (ESI) source.     

Towards a proteome signature for invasive ductal breast carcinoma derived from label-free nanoscale LC-MS protein expression profiling of tumorous and glandular tissue

As more and more alternative treatments become available for breast carcinoma, there is a need to stratify patients and individual molecular information seems to be suitable for this purpose. In this study, we applied label-free protein quantitation by nanoscale LC-MS and investigated whether this approach could be used for defining a proteome signature for invasive ductal breast carcinoma. Tissue samples from healthy breast and tumor were collected from three patients. Protein identifications were based on LC-MS peptide fragmentation data which were obtained simultaneously to the quantitative information. Hereby, an invasive ductal breast carcinoma proteome signature was generated which contains 60 protein entries. The on-column concentrations for osteoinductive factor, vimentin, GAP-DH, and NDKA are provided as examples. These proteins represent distinctive gene ontology groups of differentially expressed proteins and are discussed as risk markers for primary tumor pathogenesis. The developed methodology has been found well applicable in a clinical environment in which standard operating procedures can be kept; a prerequisite for the definition of molecular parameter sets that shall be capable for stratification of patients.     

Hyphenation of ionic liquid albumin glassy carbon biosensor or protein label-free sensor with differential pulse stripping voltammetry for interaction studies of human serum albumin with fenoprofen enantiomers

A new biosensor or protein label-free sensor composed of 1-butyl-3-methylimidazolium hexafluorophosphates (BMIMPF₆)-human serum albumin (HSA) film on glassy carbon electrode (GCE) was produced. Unfortunately, the native proteins themselves are often unstable in physiological conditions. Here, we introduced conjugation with ionic liquid (IL) such as BMIMPF₆ which improved the stability and binding affinity of protein onto GCE. A rapid, simple and reliable method for the chiral discrimination and real time protein binding studies of fenoprofen enantiomers with HSA was developed by hyphenating ionic liquid albumin glassy carbon (ILAGC) biosensor with differential pulse cathodic stripping voltammetry under physiological conditions. The electrochemical behavior of chiral fenoprofen was monitored by cyclic voltammetry, from which large response was obtained from l-fenoprofen. The surface coverage of fenoprofen enantiomers was calculated by double potential-step chronocoulometry. The binding constants of chiral fenoprofen with HSA were estimated to be 3.2 × 10⁵ ± 0.3 L mol⁻¹ and 0.8 × 10⁴ ± 0.4 L mol⁻¹ for l- and d-fenoprofen, respectively giving acceptable precision (SD ≤ 0.4) and good agreement with the literature values. The competitive interactions of ibuprofen with fenoprofen enantiomers–HSA were studied giving a significant decreasing in the binding degrees of analytes to HSA. The reciprocal competitive experiments indicated that l-fenoprofen replaced d-fenoprofen from HSA. The proposed electrochemical biosensor holds great potential for chiral discrimination and real time binding studies of drugs with protein.     

A novel method for serum lipoprotein profiling using high performance capillary isotachophoresis

A new capillary isotachophoresis (cITP) method for lipoprotein profiling with superior lipoprotein coverage compared to previous methods has been developed, resolving twice as many lipoprotein species (18 peaks/fractions) in serum or plasma in less than 9.5 min. For this, a novel mixture of 24 spacers, including amino acids, dipeptides and sulfonic acids, was developed and fine-tuned, using predictive software (PeakMaster) and testing of spiked serum samples. Lipoprotein peaks were identified by serum-spiking with reference lipoproteins. Compatibility with common lipophilic stains for selective lipoprotein detection with either UV/Vis or laser-induced fluorescence was demonstrated. A special new capillary with a neutral coating (combining water-compatible OV1701-OH deactivation and methylation) was used for the first time for electrodriven separations, allowing very stable separations in a pH 8.8–9.4 gradient system, being functional for more than 100 injections. Excellent reproducibility was achieved, with coefficients of variation lower than 2.6% for absolute migration times. Comparison was performed with human plasma samples analyzed by NMR, leading to similar results with cITP after multivariate statistics, regarding group-clustering and lipoprotein species correlation. The new cITP method was applied to the analysis of serum samples from a LDL receptor knock-out mice model fed either a normal diet or a western-type diet. Differences in the lipoprotein levels and in the sublipoprotein types were detected, showing a shift to more atherogenic particles due to the high cholesterol diet. In summary, this novel method will allow more detailed and informative profiling of lipoprotein particle subtypes for cardiovascular disease research.