Liquid ultraviolet matrix-assisted laser desorption/ionization -- mass spectrometry for automated proteomic analysis

We have combined several key sample preparation steps for the use of a liquid matrix system to provide high analytical sensitivity in automated ultraviolet -- matrix-assisted laser desorption/ionisation -- mass spectrometry (UV-MALDI-MS). This new sample preparation protocol employs a matrix-mixture which is based on the glycerol matrix-mixture described by Sze et al. The low-femtomole sensitivity that is achievable with this new preparation protocol enables proteomic analysis of protein digests comparable to solid-state matrix systems. For automated data acquisition and analysis, the MALDI performance of this liquid matrix surpasses the conventional solid-state MALDI matrices. Besides the inherent general advantages of liquid samples for automated sample preparation and data acquisition the use of the presented liquid matrix significantly reduces the extent of unspecific ion signals in peptide mass fingerprints compared to typically used solid matrices, such as 2,5-dihydroxybenzoic acid (DHB) or alpha-cyano-hydroxycinnamic acid (CHCA). In particular, matrix and low-mass ion signals and ion signals resulting from cation adduct formation are dramatically reduced. Consequently, the confidence level of protein identification by peptide mass mapping of in-solution and in-gel digests is generally higher.     

A non-negative matrix factorization framework for identifying modular patterns in metagenomic profile data

Metagenomic studies sequence DNA directly from environmental samples to explore the structure and function of complex microbial and viral communities. Individual, short pieces of sequenced DNA (“reads”) are classified into (putative) taxonomic or metabolic groups which are analyzed for patterns across samples. Analysis of such read matrices is at the core of using metagenomic data to make inferences about ecosystem structure and function. Non-negative matrix factorization (NMF) is a numerical technique for approximating high-dimensional data points as positive linear combinations of positive components. It is thus well suited to interpretation of observed samples as combinations of different components. We develop, test and apply an NMF-based framework to analyze metagenomic read matrices. In particular, we introduce a method for choosing NMF degree in the presence of overlap, and apply spectral-reordering techniques to NMF-based similarity matrices to aid visualization. We show that our method can robustly identify the appropriate degree and disentangle overlapping contributions using synthetic data sets. We then examine and discuss the NMF decomposition of a metabolic profile matrix extracted from 39 publicly available metagenomic samples, and identify canonical sample types, including one associated with coral ecosystems, one associated with highly saline ecosystems and others. We also identify specific associations between pathways and canonical environments, and explore how alternative choices of decompositions facilitate analysis of read matrices at a finer scale.     

Confirmatory analysis of 17beta-boldenone, 17alpha-boldenone and androsta-1,4-diene-3,17-dione in bovine urine, faeces, feed and skin swab samples by liquid chromatography-electrospray ionisation tandem mass spectrometry

The origin, i.e. natural occurrence or illegal treatment, of findings of 17alpha-boldenone (alpha-Bol) and 17beta-boldenone (beta-Bol) in urine and faeces of cattle is under debate within the European Union. A liquid chromatographic positive ion electrospray tandem mass spectrometric method is presented for the confirmatory analysis of 17beta-boldenone, 17alpha-boldenone and an important metabolite/precursor androsta-1,4-diene-3,17-dione (ADD), using deuterium-labelled 17beta-boldenone (beta-Bol-d3) as internal standard. Detailed sample preparation procedures were developed for a variety of sample matrices such as bovine urine, faeces, feed and skin swab samples. The method was validated as a quantitative confirmatory method according to the latest EU guidelines and shows good precision, linearity and accuracy data, and CCalpha and CCbeta values of 0.1-0.3 and 0.4-1.0 ng/ml, respectively. Currently, the method has been successfully applied to suspect urine samples for more than a year, and occasionally to faeces, feed and swab samples as well. Results obtained from untreated and treated animals are given and their impact on the debate about the origin of residues of 17beta-boldenone is critically discussed. Finally, preliminary data about the degree of conjugation of boldenone residues are presented and a simple procedure for discrimination between residues from abuse versus natural origin is proposed.     

An automated mass spectrometry-based screening method for analysis of sulfated glycosaminoglycans

Glycosaminoglycans (GAGs) are linear polysaccharides, consisting of repeated disaccharide units, attached to core proteins in all multicellular organisms. Chondroitin sulfate (CS) and dermatan sulfate (DS) constitute a subgroup of sulfated GAGs for which the degree of sulfation varies between species and tissues. One major goal in GAG characterization is to correlate structure to function. A common approach is to exhaustively degrade the GAG chains and thereafter determine the amount of component disaccharide units. In large-scale studies, there is a need for high-throughput screening methods since existing methods are either very time- or samples consuming. Here, we present a new strategy applying MALDI-TOF MS in positive ion mode for semi-qualitative and quantitative analysis of CS/DS derived disaccharide units. Only a few picomoles of sample are required per analysis and 10 samples can be analyzed in 25 min, which makes this approach an attractive alternative to many established assay methods. The total CS/DS concentration in 19 samples derived from Caenorhabditis elegans and mammalian tissues and cells was determined. The obtained results were well in accordance with concentrations determined by a standard liquid chromatography-based method, demonstrating the applicability of the method for samples from various biological matrices containing CS/DS of different sulfation degrees.     

Flow infusion electrospray ionisation mass spectrometry for high throughput,non-targeted metabolite fingerprinting: a review

Producing a comprehensive overview of the chemical content of biologically-derived material is a major challenge. Apart from ensuring adequate metabolome coverage and issues of instrument dynamic range, mass resolution and sensitivity, there are major technical difficulties associated with data pre-processing and signal identification when attempting large scale, high-throughput experimentation. To address these factors direct infusion or flow infusion electrospray mass spectrometry has been finding utility as a high throughput metabolite fingerprinting tool. With little sample pre-treatment, no chromatography and instrument cycle times of less than 5 min it is feasible to analyse more than 1,000 samples per week. Data pre-processing is limited to aligning extracted mass spectra and mass-intensity matrices are generally ready in a working day for a month’s worth of data mining and hypothesis generation. ESI-MS fingerprinting has remained rather qualitative by nature and as such ion suppression does not generally compromise data information content as originally suggested when the methodology was first introduced. This review will describe how the quality of data has improved through use of nano-flow infusion and mass-windowing approaches, particularly when using high resolution instruments. The increasingly wider availability of robust high accurate mass instruments actually promotes ESI-MS from a merely fingerprinting tool to the ranks of metabolite profiling and combined with MS/MS capabilities of hybrid instruments improved structural information is available concurrently. We summarise current applications in a wide range of fields where ESI-MS fingerprinting has proved to be an excellent tool for “first pass” metabolome analysis of complex biological samples. The final part of the review describes a typical workflow with reference to recently published data to emphasise key aspects of overall experimental design.

     

On statistical methods for comparison of intrasample morphometric variability: Zalavár revisited

In studies of morphology, methods for comparing amounts of variability are often important. Three different ways of utilizing determinants of covariance matrices for testing for surplus variability in a hypothesis sample compared to a reference sample are presented: an F-test based on standardized generalized variances, a parametric bootstrap based on draws on Wishart matrices, and a nonparametric bootstrap. The F-test based on standardized generalized variances and the Wishart-based bootstrap are applicable when multivariate normality can be assumed. These methods can be applied with only summary data available. However, the nonparametric bootstrap can be applied with multivariate nonnormally distributed data as well as multivariate normally distributed data, and small sample sizes. Therefore, this method is preferable when raw data are available. Three craniometric samples are used to present the methods. A Hungarian Zalavár sample and an Austrian Berg sample are compared to a Norwegian Oslo sample, the latter employed as reference sample. In agreement with a previous study, it is shown that the Zalavár sample does not represent surplus variability, whereas the Berg sample does represent such a surplus variability.     

Minimal sample requirement for highly multiplexed protein quantification in cell lines and tissues by PCT‐SWATH mass spectrometry

The amount of sample available for clinical and biological proteomic research is often limited and thus significantly restricts clinical and translational research. Recently, we have integrated pressure cycling technology (PCT) assisted sample preparation and SWATH‐MS to perform reproducible proteomic quantification of biopsy‐level tissue samples. Here, we further evaluated the minimal sample requirement of the PCT‐SWATH method using various types of samples, including cultured cells (HeLa, K562, and U251, 500 000 to 50 000 cells) and tissue samples (mouse liver, heart, brain, and human kidney, 3–0.2 mg). The data show that as few as 50 000 human cells and 0.2–0.5 mg of wet mouse and human tissues produced peptide samples sufficient for multiple SWATH‐MS analyses at optimal sample load applied to the system. Generally, the reproducibility of the method increased with decreasing tissue sample amounts. The SWATH maps acquired from peptides derived from samples of varying sizes were essentially identical based on the number, type, and quantity of identified peptides. In conclusion, we determined the minimal sample required for optimal PCT‐SWATH analyses, and found smaller sample size achieved higher quantitative accuracy.     

A dynamic programming approach for the alignment of signal peaks in multiple gas chromatography-mass spectrometry experiments

Background  

Gas chromatography-mass spectrometry (GC-MS) is a robust platform for the profiling of certain classes of small molecules in biological samples. When multiple samples are profiled, including replicates of the same sample and/or different sample states, one needs to account for retention time drifts between experiments. This can be achieved either by the alignment of chromatographic profiles prior to peak detection, or by matching signal peaks after they have been extracted from chromatogram data matrices. Automated retention time correction is particularly important in non-targeted profiling studies.     

Nanostructure-initiator mass spectrometry: a protocol for preparing and applying NIMS surfaces for high-sensitivity mass analysis

Nanostructure-initiator mass spectrometry (NIMS) is a new surface-based MS technique that uses a nanostructured surface to trap liquid ('initiator') compounds. Analyte materials adsorbed onto this 'clathrate' surface are subsequently released by laser irradiation for mass analysis. In this protocol, we describe the preparation of NIMS surfaces capable of producing low background and high-sensitivity mass spectrometric measurement using the initiator compound BisF17. Examples of analytes that adsorb to this surface are small molecules, drugs, lipids, carbohydrates and peptides. Typically, NIMS is used to analyze samples ranging from simple analytical standards and proteolytic digests to more complex samples such as tissues, cells and biofluids. Critical experimental considerations of NIMS are described. Specifically, NIMS sensitivity is examined as a function of pre-etch cleaning treatment, etching current density, etching time, initiator composition, sample concentration, sample deposition method and laser fluence. Typically, NIMS surface preparation can be completed in less than 2 h. Subsequent sample preparation requires 1-5 min, depending on sample deposition method. Mass spectrometric data acquisition typically takes 1-30 s per sample.     

Integrative factorization of bidimensionally linked matrices

Advances in molecular “omics” technologies have motivated new methodologies for the integration of multiple sources of high-content biomedical data. However, most statistical methods for integrating multiple data matrices only consider data shared vertically (one cohort on multiple platforms) or horizontally (different cohorts on a single platform). This is limiting for data that take the form of bidimensionally linked matrices (eg, multiple cohorts measured on multiple platforms), which are increasingly common in large-scale biomedical studies. In this paper, we propose bidimensional integrative factorization (BIDIFAC) for integrative dimension reduction and signal approximation of bidimensionally linked data matrices. Our method factorizes data into (a) globally shared, (b) row-shared, (c) column-shared, and (d) single-matrix structural components, facilitating the investigation of shared and unique patterns of variability. For estimation, we use a penalized objective function that extends the nuclear norm penalization for a single matrix. As an alternative to the complicated rank selection problem, we use results from the random matrix theory to choose tuning parameters. We apply our method to integrate two genomics platforms (messenger RNA and microRNA expression) across two sample cohorts (tumor samples and normal tissue samples) using the breast cancer data from the Cancer Genome Atlas. We provide R code for fitting BIDIFAC, imputing missing values, and generating simulated data.     

Flow infusion electrospray ionisation mass spectrometry for high throughput,non-targeted metabolite fingerprinting: a review

Producing a comprehensive overview of the chemical content of biologically-derived material is a major challenge. Apart from ensuring adequate metabolome coverage and issues of instrument dynamic range, mass resolution and sensitivity, there are major technical difficulties associated with data pre-processing and signal identification when attempting large scale, high-throughput experimentation. To address these factors direct infusion or flow infusion electrospray mass spectrometry has been finding utility as a high throughput metabolite fingerprinting tool. With little sample pre-treatment, no chromatography and instrument cycle times of less than 5 min it is feasible to analyse more than 1,000 samples per week. Data pre-processing is limited to aligning extracted mass spectra and mass-intensity matrices are generally ready in a working day for a month’s worth of data mining and hypothesis generation. ESI-MS fingerprinting has remained rather qualitative by nature and as such ion suppression does not generally compromise data information content as originally suggested when the methodology was first introduced. This review will describe how the quality of data has improved through use of nano-flow infusion and mass-windowing approaches, particularly when using high resolution instruments. The increasingly wider availability of robust high accurate mass instruments actually promotes ESI-MS from a merely fingerprinting tool to the ranks of metabolite profiling and combined with MS/MS capabilities of hybrid instruments improved structural information is available concurrently. We summarise current applications in a wide range of fields where ESI-MS fingerprinting has proved to be an excellent tool for “first pass” metabolome analysis of complex biological samples. The final part of the review describes a typical workflow with reference to recently published data to emphasise key aspects of overall experimental design.     

Emerging technologies in mass spectrometry imaging

Mass spectrometry imaging (MSI) as an analytical tool for bio-molecular and bio-medical research targets accurate compound localization and identification. In terms of dedicated instrumentation, this translates into the demand for more detail in the image dimension (spatial resolution) and in the spectral dimension (mass resolution and accuracy), preferably combined in one instrument. At the same time, large area biological tissue samples require fast acquisition schemes, instrument automation and a robust data infrastructure. This review discusses the analytical capabilities of an "ideal" MSI instrument for bio-molecular and bio-medical molecular imaging. The analytical attributes of such an ideal system are contrasted with technological and methodological challenges in MSI. In particular, innovative instrumentation for high spatial resolution imaging in combination with high sample throughput is discussed. Detector technology that targets various shortcomings of conventional imaging detector systems is highlighted. The benefits of accurate mass analysis, high mass resolving power, additional separation strategies and multimodal three-dimensional data reconstruction algorithms are discussed to provide the reader with an insight in the current technological advances and the potential of MSI for bio-medical research.     

Full conjugate analysis of normal multiple traits with missing records using a generalized inverted Wishart distribution

A Markov chain Monte Carlo (MCMC) algorithm to sample an exchangeable covariance matrix, such as the one of the error terms (R₀) in a multiple trait animal model with missing records under normal-inverted Wishart priors is presented. The algorithm (FCG) is based on a conjugate form of the inverted Wishart density that avoids sampling the missing error terms. Normal prior densities are assumed for the ''fixed'' effects and breeding values, whereas the covariance matrices are assumed to follow inverted Wishart distributions. The inverted Wishart prior for the environmental covariance matrix is a product density of all patterns of missing data. The resulting MCMC scheme eliminates the correlation between the sampled missing residuals and the sampled R₀, which in turn has the effect of decreasing the total amount of samples needed to reach convergence. The use of the FCG algorithm in a multiple trait data set with an extreme pattern of missing records produced a dramatic reduction in the size of the autocorrelations among samples for all lags from 1 to 50, and this increased the effective sample size from 2.5 to 7 times and reduced the number of samples needed to attain convergence, when compared with the ''data augmentation'' algorithm.     

Sample size calculations for designing clinical proteomic profiling studies using mass spectrometry

In cancer clinical proteomics, MALDI and SELDI profiling are used to search for biomarkers of potentially curable early-stage disease. A given number of samples must be analysed in order to detect clinically relevant differences between cancers and controls, with adequate statistical power. From clinical proteomic profiling studies, expression data for each peak (protein or peptide) from two or more clinically defined groups of subjects are typically available. Typically, both exposure and confounder information on each subject are also available, and usually the samples are not from randomized subjects. Moreover, the data is usually available in replicate. At the design stage, however, covariates are not typically available and are often ignored in sample size calculations. This leads to the use of insufficient numbers of samples and reduced power when there are imbalances in the numbers of subjects between different phenotypic groups. A method is proposed for accommodating information on covariates, data imbalances and design-characteristics, such as the technical replication and the observational nature of these studies, in sample size calculations. It assumes knowledge of a joint distribution for the protein expression values and the covariates. When discretized covariates are considered, the effect of the covariates enters the calculations as a function of the proportions of subjects with specific attributes. This makes it relatively straightforward (even when pilot data on subject covariates is unavailable) to specify and to adjust for the effect of the expected heterogeneities. The new method suggests certain experimental designs which lead to the use of a smaller number of samples when planning a study. Analysis of data from the proteomic profiling of colorectal cancer reveals that fewer samples are needed when a study is balanced than when it is unbalanced, and when the IMAC30 chip-type is used. The method is implemented in the clippda package and is available in R at: http://www.bioconductor.org/help/bioc-views/release/bioc/html/clippda.html.     

An Evaluation of a Technical Holding Time for the Preparation and Analysis of Hexavalent Chromium in Soils/Sediments

Chromium (Cr) is routinely measured during environmental investigations involving soils and other solid matrix sampling. Regulatory-approved analytical methods are available to extract and quantify total Cr in various environmental media. However, due to significant toxicity differences between trivalent [Cr(III)] and hexavalent [Cr(VI)] valences, it is compelling that the two can be quantitatively distinguished. SW-846 Method 3060A is an effective extraction technique for soluble and insoluble Cr(VI). Several regulatory-approved methods exist for quantitating the Cr(VI) in extracts or aqueous samples. Although a 6-month holding time for total Cr is not encumbering, investigators are challenged by the typical 24-h holding time (sample collection through analysis) for Cr(VI) in aqueous samples and the 24- to 96-h holding time range for solid matrix samples typically set by regulators. This research report addresses quantitating Cr(VI) in solid matrices. Using SW-846 Methods 3060A/7196A, a scientifically defensible basis has been established for designating a 30-day holding time for Cr(VI) extraction from solid matrices and a 7-day holding time for Cr(VI) analysis once solubilized in the alkaline digestate. The study results indicate that a 30-day holding time, from sample collection to preparation, and a 7-day holding time, from digestion to analysis, are appropriate for Cr(VI) analysis.     

Variation in milk,serum, and blubber fatty acids in young,free‐ranging Steller sea lions

We determined the fatty acid signatures in milk, serum, and blubber samples collected from young free‐ranging Steller sea lions (Eumetopias jubatus) and investigated the partitioning of fatty acids among these matrices. We assessed the relationship of fatty acids in each matrix with region, age, season, sex, and body condition to gain information needed to determine the most appropriate type of samples to collect and analyze to address future research questions. The variability of fatty acid composition was almost entirely explained by sample type, highlighting the importance of selecting a matrix consistent with the study objectives. Regional differences in fatty acid composition were found in all sample types and these differences varied among matrices. The proportion of fatty acids in milk and serum were influenced by season of capture whereas blubber samples were more affected by age of the pup. The influence of season on the fatty acid signatures in milk and serum highlights the use of these samples over blubber in studies investigating seasonal changes in diet. Further, our findings suggest that the use of milk samples collected from the stomachs of pups may be a viable alternative to directly collecting milk from adult females.     

Biomarker discovery from body fluids using mass spectrometry

Systems analysis of body fluids by mass spectrometry (MS) is an upcoming field of biomarker research. This approach is extremely attractive because it does not require biomarker candidates and the sample preparation is simple. However, during the development of the technique strong critical comments were made on the poor reproducibility, the special characteristics of blood as a source of peptides and on the frequent non-adequate statistical analysis of the data. Here we discuss the efforts made in the last few years to develop suitable protocols, which could lead to biomarker discovery from body fluids by mass spectrometry. Our review focuses on the systems analysis of non-digested blood serum or plasma samples by MALDI-TOF and SELDI-TOF.     

Bioanalysis in clinical development of tasquinimod using liquid chromatography/tandem mass spectrometry

Tasquinimod (ABR-215050) is an oral drug in clinical development for treatment of patients with castrate resistant prostate cancer. This paper describes a method for the determination of tasquinimod in human plasma. The method is based on liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) using stable isotope labeled tasquinimod as internal standard (IS). The plasma samples were processed by protein precipitation using acidic acetonitrile containing the IS. The precipitated samples were centrifuged and the supernatant was injected directly into the LC-MS/MS system. Chromatographic separation was performed on a reversed phase column using fast gradient elution, with a total run cycle time of 4 min. The method was validated with respect to accuracy, precision, dynamic range, lower limit of quantification, selectivity and robustness. Furthermore, the stability of tasquinimod in spiked plasma, in processed extracts and in incurred samples was thoroughly studied. The method was validated in the range of 1.0-2400 nmol/L, defining the lower and upper limits of quantification. The repeatability, reproducibility and overall bias were 1.5-7.1%, 3.5-7.4%, and 1.3-4.7%, respectively, in the range of 1-2000 nmol/L. Excellent selectivity was demonstrated in the validation, as well as in study samples from both healthy volunteers and cancer patients. Robustness was demonstrated by the calculated carry-over as low as 0.06%, and by an incurred sample reproducibility (ISR) experiment where 97% of the reanalyzed samples fulfilled the acceptance criteria of 20% deviation from initial analysis result. Also, tasquinimod was found to be stable in all investigated matrices, including in incurred samples. In an incurred sample stability (ISS) investigation, tasquinimod was demonstrated to be stable for 24 months, and 97% of the reanalyzed samples were within 20% from the initial analysis result. In conclusion, the method was demonstrated to be accurate, precise, robust and reliable for the determination of tasquinimod. The method was successfully used in several clinical studies for the support of pharmacokinetic and pharmacodynamic evaluations.     

Ambient molecular imaging by desorption electrospray ionization mass spectrometry

Desorption electrospray ionization (DESI) allows the direct analysis of ordinary objects or pre-processed samples under ambient conditions. Among other applications, DESI is used to identify and record spatial distributions of lipids and drug molecules in biological tissue sections. This technique does not require sample preparation other than production of microtome tissue slices and does not involve the use of ionization matrices. This greatly simplifies the procedure and prevents the redistribution of analytes during matrix deposition. Images are obtained by continuously moving the sample relative to the DESI sprayer and the inlet of the mass spectrometer. The timing of the protocol depends on the size of the surface to be analyzed and on the desired resolution. Analysis of organ tissue slices at 250 microm resolution typically takes between 30 min and 2 h.     

Rapid detection of Salmonella enterica in primary production samples by eliminating DNA amplification inhibitors using an improved sample pre-treatment method

Sensitive detection of pathogens in livestock farms is an integral part of the One Health Action Plan of the European Union (EU). Ensuring this requires on-site testing devices that are compatible with complex matrices such as primary production samples. Among all, faeces are considered the most challenging matrix type that makes it difficult to identify pathogens because of complexity in sample preparation for molecular testing. We have developed a loop-mediated isothermal amplification (LAMP) based veterinary point-of-care (POC) device (VETPOD) and adapted it to detect Salmonella enterica in primary production samples. Three different sampling methods (semi-wet chicken faeces, boot socks collection and dust samples from poultry shed) were iteratively tested to assess their nature of complexity and possibility for adapting them as suitable sampling methods for on-site testing. During the study, the sample preparation method that included a two-step centrifugation combined with washing of the enriched Salmonella cells was found crucial in eliminating amplification inhibitors originating from the faecal matrices. A total of 90 samples were tested that included 60 samples for sensitivity study and 30 samples for relative level of detection (RLOD, a level of detection in comparison to ISO 6579:1 reference method). Overall, the VETPOD had a sensitivity of 90%, 84.62% and 81.82% for boot sock, faecal and dust samples, respectively. The RLOD was 2.23 CFU/25 g which was found to be 1.33 times higher than the ISO 6579:1. Performing with an excellent agreement with ISO 6579:1, the VETPOD proved as a promising alternative to detect Salmonella spp. in primary production and animal husbandry samples.