Optimization of MALDI-TOF MS detection for enhanced sensitivity of affinity-captured proteins spanning a 100 kDa mass range

Exploring structural features and potential lipid interactions of Pseudomonas aeruginosa type three secretion effector PemB by spectroscopic and calorimetric experiments

Type Three Secretion System (T3SS) is a sophisticated nano-scale weapon utilized by several gram negative bacteria under stringent spatio-temporal regulation to manipulate and evade host immune systems in order to cause infection. To the best of our knowledge, this present study is the first report where we embark upon characterizing inherent features of native type three secretion effector protein PemB through biophysical techniques. Herein, first, we demonstrate binding affinity of PemB for phosphoinositides through isothermal calorimetric titrations. Second, we shed light on its strong homo-oligomerization propensity in aqueous solution through multiple biophysical methods. Third, we also employ several spectroscopic techniques to delineate its disordered and helical conformation. Lastly, we perform a phylogenetic analysis of this new effector to elucidate evolutionary relationship with other organisms. Taken together, our results shall surely contribute to our existing knowledge of Pseudomonas aeruginosa secretome.

Protein profile of scorpion venom from Hottentotta rugiscutis and its immunogenic potential in inducing long term memory response

The scorpions of the Buthidae family exhibit diverse toxins with proven pharmacological activities and yet underexplored. The Hottentotta rugiscutis is a commonly found south-Indian buthid scorpion, whose venom proteomic profile is unknown. In this study, the venom was biochemically and immunologically characterized by SDS-PAGE, MALDI-TOF MS, Western blot and ELISA. The regional and seasonal variation in the venom composition from the same species was also assessed at the molecular mass level. The venom was further studied in albino mice to understand its impact on various blood parameters. The venom has varied MW proteins from 6 to 275 kDa, four of them were found to be major immunodominant proteins. The mass spectra have revealed that some proteins are predominantly present in the venom of 3-4.5 kDa or 6.5-8.0 kDa, which could be the K⁺ or Na⁺ channel blockers respectively whose ratio varied by season. The obtained venom-mass spectra could also be used as H. rugiscutis specific finger-print in identifying the region-specific species. The venom was found to elicit a stress-induced innate immune response in mice, giving rise to a strong Th2 mediated humoral immune response. Overall, this study has provided a glimpse of the venom composition and its immunogenicity.

Exploring the value of MALDI-TOF MS for the detection of clonal outbreaks of Burkholderia contaminans

BACKGROUND

Molecular genetics has risen in both output and affordability to become the gold standard in diagnosis, however it is not yet available for most routine clinical microbiology due to cost and the level of skill it requires. Matrix assisted laser desorption/ionisation - time of flight mass spectrometry (MALDI-TOF MS) approaches may be useful in bridging the gap between low-resolution phenotypic methods and bulky genotypic methods in the goal of epidemiological source-typing of microbes. Burkholderia has been shown to be identifiable at the subspecies level using MALDI-TOF MS. There have not yet been studies assessing the ability of MALDI-TOF MS to source-type Burkholderia contaminans isolates into epidemiologically relevant outbreak clusters.

METHODS

55 well-characterised B. contaminans isolates were used to create a panel for analysis of MALDI-TOF MS biomarker peaks and their relation to outbreak strains, location, source, patient, diagnosis and isolate genetics. Unsupervised clustering was performed and classification models were generated using biostatistical analysis software.

RESULTS

B. contaminans spectra derived from MALDI-TOF MS were of sufficiently high resolution to identify 100% of isolates. Unsupervised clustering methods showed poor evidence of spectra clustering by all characteristics measured. Classification algorithms were discriminatory, with Genetic Algorithm models showing 100% recognition capability for all outbreaks, the pulsed-field gel electrophoresis (PFGE) typeability model, and 96.63% recognition for the location model. A consistent peak at m/z of approximately 6943 was identified in all non-typeable strains but in none of the typeable strains.

CONCLUSIONS

MALDI-TOF MS successfully discriminates B. contaminans isolates into clonal, epidemiological clusters, and can recognise isolates non-typeable by PFGE. Further work should investigate this capability, and include peptide studies and genomic sequencing to identify individual proteins or genes responsible for this non-typeablity, particularly at the peak weight identified.

Challenges in biomarker discovery with MALDI-TOF MS

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

A Ti4+-immobilized phosphate polymer-patterned silicon substrate for on-plate selective enrichment and self-desalting of phosphopeptides

A circular hydrophobic–hydrophilic-Ti⁴⁺ immobilized phosphate polymer is patterned as the sample support for selective enrichment, wash-free self-desalting and mass spectroscopy (MS) analysis of phosphopeptides.

Comparative proteomic profiles indicating genetic factors may involve in hepatocellular carcinoma familial aggregation

Familial aggregation of hepatocellular carcinoma (HCC), the third leading cause of cancer death worldwide, has shown to be a common phenomenon. We investigated the association between the genetic background and HCC familial aggregation. Serum samples were collected from HCC family members and normal control family members for screening the differentially expressed protein peaks with the approach of surface-enhanced laser desorption ionization time-of-flight mass spectrometry. Potential genetically associated protein peaks were selected and further identified by matrix assisted laser desorption ionization-time of flight mass spectrometry. A panel of six protein peaks (m/z 6432.94, 8478.35, 9381.91, 17284.67, 17418.34, and 18111.04) were speculated to reflect the genetic susceptibility of HCC familial aggregation. Three of them (m/z 6432.94, 8478.35, and 9381.91) were selected to identify as the candidate proteins. Nine identified proteins, including mostly apolipoprotein family (ApoA1, ApoA2, ApoC3, ApoE) and serum amyloid A protein (SAA), were found overexpressed in the multiple HCC cases family members. The comparative proteomic profiles have suggested that genetic factors ought to be taken into account for familial aggregation of HCC.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Improved signal processing and normalization for biomarker protein detection in broad-mass-range TOF mass spectra from clinical samples

PURPOSE

To demonstrate robust detection of biomarkers in broad-mass-range TOF-MS data.

EXPERIMENTAL DESIGN

Spectra were obtained for two serum protein profiling studies: (i) 2-200 kDa for 132 patients, 67 healthy and 65 diagnosed as having adult T-cell leukemia and (ii) 2-100 kDa for 140 patients, 70 pairs, each with matched prostate-specific antigen (PSA) levels and biopsy-confirmed diagnoses of one benign and one prostate cancer. Signal processing was performed on raw spectra and peak data were normalized using four methods. Feature selection was performed using Bayesian Network Analysis and a classifier was tested on withheld data. Identification of candidate biomarkers was pursued.

RESULTS

Integrated peak intensities were resolved over full spectra. Normalization using local noise values was superior to global methods in reducing peak correlations, reducing replicate variability and improving feature selection stability. For the leukemia data set, potential disease biomarkers were detected and were found to be predictive for withheld data. Preliminary assignments of protein IDs were consistent with published results and LC-MS/MS identification. No prostate-specific-antigen-independent biomarkers were detected in the prostate cancer data set.

CONCLUSIONS AND CLINICAL RELEVANCE

Signal processing, local signal-to-noise (SNR) normalization and Bayesian Network Analysis feature selection facilitate robust detection and identification of biomarker proteins in broad-mass-range clinical TOF-MS data.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry combined with magnetic beads for detecting serum protein biomarkers in parkinson's disease

BACKGROUND

Biomarkers for neurodegenerative diseases are essential to facilitate disease diagnosis. Application of proteomics has greatly hastened the search for novel biomarkers. In this study, new potential biomarkers were discovered, and a diagnostic pattern was established for idiopathic Parkinson's disease (PD) by using proteomic technology.

METHODS

Serum proteins from PD patients and controls were captured by magnetic bead-based weak cation exchange. The molecular weight of the proteins in bead-binding fraction was detected by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Biomarker Wizard 3.1 and Biomarker Patterns Software were used for data analysis and constructing a model of biomarkers. A blinded testing set was used to validate the model.

RESULTS

A total of 17 discriminating m/z peaks related to PD were identified. The model based on the 5 biomarkers generated an excellent separation between PD and healthy controls with 98.36% for the sensitivity and 83.05% for the specificity. Blind test data demonstrated the model could recognize patients with PD with a sensitivity of 85.0% and a specificity of 70.0%.

CONCLUSIONS

The preliminary data suggested a potential application of MALDI-TOF-MS combined with magnetic beads. The model comprising 5 promising biomarkers can differentiate individuals with PD and the healthy subjects precisely.

Quadratic variance models for adaptively preprocessing SELDI-TOF mass spectrometry data

BACKGROUND

Surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI) is a proteomics tool for biomarker discovery and other high throughput applications. Previous studies have identified various areas for improvement in preprocessing algorithms used for protein peak detection. Bottom-up approaches to preprocessing that emphasize modeling SELDI data acquisition are promising avenues of research to find the needed improvements in reproducibility.

RESULTS

We studied the properties of the SELDI detector intensity response to matrix only runs. The intensity fluctuations and noise observed can be characterized by a natural exponential family with quadratic variance function (NEF-QVF) class of distributions. These include as special cases many common distributions arising in practice (e.g.- normal, Poisson). Taking this model into account, we present a modified Antoniadis-Sapatinas wavelet denoising algorithm as the core of our preprocessing program, implemented in MATLAB. The proposed preprocessing approach shows superior peak detection sensitivity compared to MassSpecWavelet for false discovery rate (FDR) values less than 25%.

CONCLUSIONS

The NEF-QVF detector model requires that certain parameters be measured from matrix only spectra, leaving implications for new experiment design at the trade-off of slightly increased cost. These additional measurements allow our preprocessing program to adapt to changing noise characteristics arising from intralaboratory and across-laboratory factors. With further development, this approach may lead to improved peak prediction reproducibility and nearly automated, high throughput preprocessing of SELDI data.

Automated assignment of ionization states in broad-mass matrix-assisted laser desorption/ionization spectra of protein mixtures

A computational technique is presented for the automated assignment of the multiple charge and multimer states (ionization states) in the time-of-flight (TOF) domain for matrix-assisted laser desorption/ionization (MALDI) spectra. Examples of the application of this technique include an improved, automatic calibration over the 2 to 70 kDa mass range and a reduced data redundancy after reconstruction of the molecular spectrum of only singly charged monomers. This method builds on our previously reported enhancement of broad-mass signal detection, and includes two steps: (1) an automated correction of the instrumental acquisition initial time delay, and (2) a recursive TOF detection of multiple charge states and singly charged multimers of molecular [MH](+) ions over the entire record range, based on MALDI methods. The technique is tested using calibration mixtures and pooled serum quality control samples acquired along with clinical study data. The described automated procedure improves the analysis and dimension reduction of MS data for comparative proteomics applications.

Optimal preparation methods for automated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry profiling of low molecular weight proteins and peptides

Mass spectrometry (MS) profiling of the proteome and peptidome for disease-associated patterns is a new concept in clinical diagnostics. The technique, however, is highly sensitive to external sources of variation leading to potentially unacceptable numbers of false positive and false negative results. Before MS profiling can be confidently implemented in a medical setting, standard experimental methods must be developed that minimize technical variance. Past studies of variance have focused largely on pre-analytical variation (i.e., sample collection, handling, etc.). Here, we examined how factors at the analytical stage including the matrix and solid-phase extraction influence MS profiling. Firstly, a standard peptide/protein sample was measured automatically by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS across five consecutive days using two different preparation methods, dried droplet and sample/matrix, of four types of matrix: alpha-cyano-4-hydroxycinnamic acid (HCCA), sinapinic acid (SA), 2,5-dihydroxybenzoic acid (DHB) and 2,5-dihydroxyacetophenone (DHAP). The results indicated that the matrix preparation greatly influenced a number of key parameters of the spectra including repeatability (within-day variability), reproducibility (inter-day variability), resolution, signal strength, background intensity and detectability. Secondly, an investigation into the variance associated with C8 magnetic bead extraction of the standard sample prior to automated MS profiling demonstrated that the process did not adversely affect these same parameters. In fact, the spectra were generally more robust following extraction. Thirdly, the best performing matrix preparations were evaluated using C8 magnetic bead extracted human plasma. We conclude that the DHAP prepared according to the dried-droplet method is the most appropriate matrix to use when performing automated MS profiling.

Precision enhancement of MALDI-TOF MS using high resolution peak detection and label-free alignment

We have developed an automated procedure for aligning peaks in multiple TOF spectra that eliminates common timing errors and small variations in spectrometer output. Our method incorporates high-resolution peak detection, re-binning, and robust linear data fitting in the time domain. This procedure aligns label-free (uncalibrated) peaks to minimize the variation in each peak's location from one spectrum to the next, while maintaining a high number of degrees of freedom. We apply our method to replicate pooled-serum spectra from multiple laboratories and increase peak precision (t/sigma(t)) to values limited only by small random errors (with sigma(t) less than one time count in 89 out of 91 instances, 13 peaks in seven datasets). The resulting high precision allowed for an order of magnitude improvement in peak m/z reproducibility. We show that the CV for m/z is 0.01% (100 ppm) for 12 out of the 13 peaks that were observed in all datasets between 2995 and 9297 Da.