Recent advancements in surface-enhanced laser desorption/ionization-time of flight-mass spectrometry

Text Mining and Computational Chemistry Reveal Trends in Applications of Laser Desorption/Ionization Techniques to Small Molecules

Continued development of laser desorption/ionization (LDI) since its inception in the 1960s has produced an explosion of soft ionization techniques, where ionization is assisted by the physical or chemical properties of a structure or matrix. While many of these techniques have primarily been used to ionize large biomolecules, including proteins, some have recently seen increasing applications to small molecules such as pharmaceuticals. Small molecules pose particular challenges for LDI techniques, including interference from the matrix or support in the low mass range. To investigate trends in the application of soft LDI techniques to small molecules, we combined text mining and computational chemistry, looking specifically at matrix substances, analyte properties, and the research domain. In addition to making visible the history of LDI techniques, the results may inform the choice of method and suggest new avenues of method development. All software and collected data are freely available on GitHub (https://github.com/ReinV/SCOPE), VOSviewer (https://www.vosviewer.com), and OSF (https://osf.io/zkmua/).

Titania Nanosheet as a Matrix for Surface-Assisted Laser Desorption/Ionization Mass Spectrometry Analysis and Imaging

Surface-assisted laser desorption/ionization (SALDI) acts as a soft desorption/ionization technique, which has been widely recognized in small-molecule analysis owing to eliminating the requirement of the organic matrix. Herein, titania nanosheets (TiO₂ NSs) were applied as novel substrates for simultaneous analysis and imaging of low-mass molecules and lipid species. A wide variety of representative analytes containing amino acids, bases, drugs, peptides, endogenous small molecules, and saccharide-spiked urine were examined by the TiO₂ NS-assisted LDI mass spectrometry (MS). Compared with conventional organic matrices and substrates [Ag nanoparticles (NPs), Au NPs, carbon nanotubes, carbon NPs, CeO₂ microparticles, and P25 TiO₂], the TiO₂ NS-assisted LDI MS method shows higher sensitivity and less spectral interference. Repeatability was evaluated with batch-to-batch relative standard deviations for 5-hydroxytryptophan, glucose-spiked urine, and glucose with addition of internal standard, which were 17.4, 14.9, and 2.8%, respectively. The TiO₂ NS-assisted LDI MS method also allows the determination of blood glucose levels in mouse serum with a linear range of 0.5-10 mM. Owing to the nanoscale size and uniform deposition of the TiO₂ NS matrix, spatial distributions of 16 endogenous small molecules and 16 lipid species from the horizontal section of the mouse brain tissue can be visualized at a 50 μm spatial resolution. These successful applications confirm that the TiO₂-assisted LDI MS method has promising prospects in the field of life science.

Proteomic analysis of pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a rare but fatal cardiovascular disorder with high morbidity and mortality. Diagnosis and treatment of this disease at an early stage would greatly improve outcomes. The molecular indicators of PAH are mostly nonspecific, and diagnostic and prognostic biomarkers are urgently needed. A more comprehensive understanding of the molecular mechanisms underlying this complex disease is crucial for the development of new and more effective therapeutics to improve patient outcomes. In this article, we review published literature on proteomic biomarkers and underlying molecular mechanisms in PAH and their value for disease management, aiming to deepen our understanding of the disease and, ultimately, pave the way for clinical application.

Astrochemical Pathways to Complex Organic and Prebiotic Molecules: Experimental Perspectives for In Situ Solid-State Studies

A deep understanding of the origin of life requires the physical, chemical, and biological study of prebiotic systems and the comprehension of the mechanisms underlying their evolutionary steps. In this context, great attention is paid to the class of interstellar molecules known as "Complex Organic Molecules" (COMs), considered as possible precursors of prebiotic species. Although COMs have already been detected in different astrophysical environments (such as interstellar clouds, protostars, and protoplanetary disks) and in comets, the physical-chemical mechanisms underlying their formation are not yet fully understood. In this framework, a unique contribution comes from laboratory experiments specifically designed to mimic the conditions found in space. We present a review of experimental studies on the formation and evolution of COMs in the solid state, i.e., within ices of astrophysical interest, devoting special attention to the in situ detection and analysis techniques commonly used in laboratory astrochemistry. We discuss their main strengths and weaknesses and provide a perspective view on novel techniques, which may help in overcoming the current experimental challenges.

A comprehensive overview of proteomics approach for COVID 19: new perspectives in target therapy strategies

World Health Organisation declared COVID-19 a pandemic on March 11, 2020. It was temporarily named as 2019-nCoV then subsequently named as COVID-19 virus. A coronavirus is a group of viruses, known to be zoonotic, causing illness ranging from acute to mild respiratory infections. These are spherical or pleomorphic enveloped particles containing positive sense RNA. The virus enters host cells, its uncoated genetic material transcribes, and translates. Since it has started spreading rapidly, protective measures have been taken all over the world. However, its transmission has been proved to be unstoppable and the absence of an effective drug makes the situation worse. The scientific community has gone all-out to discover and develop a possible vaccine or a competent antiviral drug. Other domains of biological sciences that promise effective results and target somewhat stable entities that are proteins, could be very useful in this time of crisis. Proteomics and metabolomics are the vast fields that are equipped with sufficient technologies to face this challenge. Various protein separation and identification techniques are available which facilitates the analysis of various types of interactions among proteins and their evolutionary lineages. The presented review aims at confronting the question: 'how proteomics can help in tackling SARS-CoV-2?' It deals with the role of upcoming proteome technology in these pandemic situations and discusses the proteomics approach towards the COVID-19 dilemma.

Deciphering plant-microbe crosstalk through proteomics studies

Proteomic approaches are being used to elucidate a better discretion of interactions occurring between host, pathogen, and/or beneficial microorganisms at the molecular level. Application of proteomic techniques, unravel pathogenicity, stress-related, and antioxidant proteins expressed amid plant-microbe interactions and good information have been generated. It is being perceived that a fine regulation of protein expression takes place for effective pathogen recognition, induction of resistance, and maintenance of host integrity. However, our knowledge of molecular plant-microbe interactions is still incomplete and inconsequential. This review aims to provide insight into numerous ways used for proteomic investigation including peptide/protein identification, separation, and quantification during host defense response. Here, we highlight the current progress in proteomics of defense responses elicited by bacterial, fungal, and viral pathogens in plants along with which the proteome level changes induced by beneficial microorganisms are also discussed.

Serum protein expression patterns in detecting a new viral protein in HBeAg-negative chronic hepatitis B

We analysed the changes in viral protein expression in HBeAg-negative chronic hepatitis B (CHB). In total, 160 samples were obtained from individuals infected by hepatitis B virus (HBV) and divided into four groups. Group A included 71 cases of hepatitis B e antigen (HBeAg)-negative CHB, Group B included 58 cases of inactive seroconverters and Group C included 31 cases of HBeAg-positive CHB. Group D included 22 normal healthy individuals as a control. All serum samples were examined using surface enhance laser desorption/ionization time of flight-mass spectrometry (SELDI-TOF-MS). The results indicated that a peak with 4140 m/z increased markedly in Group A at 1295.55 ± 745.87, which was significantly different from that in Group B at 896.99 ± 534.86 (P = 0.013). This peak indicated a close relationship with HBV DNA replication and may contribute to pathogenesis of HBeAg-negative chronic hepatitis.

Computational Convolution of SELDI Data for the Diagnosis of Alzheimer's Disease

Alzheimer’s disease is rapidly becoming an endemic for people over the age of 65. A vital path towards reversing this ominous trend is the building of reliable diagnostic devices for definite and early diagnoses in lieu of the longitudinal, usually inconclusive and non-generalize-able methods currently in use. In this article, we present a survey of methods for mining pools of mass spectrometer saliva data in relation to diagnosing Alzheimer’s disease. The computational methods provides new approaches for appropriately gleaning latent information from mass spectra data. They improve traditional machine learning algorithms and are most fit for handling matrix data points including solving problems beyond protein identifications and biomarker discovery.

The Molecular Basis of Thyroid Epithelial Tumorigenesis

Significant alterations in gene sequences, expression levels and protein structures have been associated with specific types of thyroid epithelial tumorigenesis. Recent revolutionary changes in molecular biology have spanned the disciplines of genomics and proteomics, which systematically generate and analyze the information about genomes, gene transcripts, proteins and their functions in a global, comprehensive manner. The application of these approaches will better discriminate between thyroid tumor subtypes that are not recognizable when traditional pathological criteria are used.

Identification of Novel Hemostatic Biomarkers of Adverse Clinical Events in Patients Implanted With a Continuous-Flow Left Ventricular Assist Device

Heart failure affects over 5 million people in the United States. Its rising prevalence and the limited supply of donor hearts is increasing the use of mechanical cardiac support with the implantation of continuous-flow ventricular assist devices (CF-VAD). Patients with CF-VAD implants are at risk of complications, specifically adverse hemostatic events such as nonsurgical bleeding and thrombosis. Development of a pump thrombus requires clinical intervention and/or surgical replacement significantly increasing the risk of patient morbidity and mortality. Identification of biomarkers for these events could improve current risk assessment models, subsequent treatment, and quality of life prognoses for VAD-implanted patients. The standard means for identifying thrombus in VAD patients is currently limited to monitoring levels of lactate dehydrogenase (>2× upper limit of normal), which is incapable of predicting a future event, but describes the risk of a present thrombus. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry is a technique used to identify biomarkers. In this study, 3 groups of unique peaks were identified in plasma from patients with left ventricular assist devices: 8.1-kDa, 11.7-kDa, and a 15.2-/16.1-kDa pair. Unique correlations were found for each peak, respectively, with microparticles (MPs) and MP procoagulant activity, C-reactive protein, and MP-tissue factor. Furthermore, the use of 8.1-kDa peaks may be able to differentiate thrombotic events from other hemostatic events.

Assessing the Statistical Significance of the Achieved Classification Error of Classifiers Constructed using Serum Peptide Profiles, and a Prescription for Random Sampling Repeated Studies for Massive High-Throughput Genomic and Proteomic Studies

Peptide profiles generated using SELDI/MALDI time of flight mass spectrometry provide a promising source of patient-specific information with high potential impact on the early detection and classification of cancer and other diseases. The new profiling technology comes, however, with numerous challenges and concerns. Particularly important are concerns of reproducibility of classification results and their significance. In this work we describe a computational validation framework, called PACE (Permutation-Achieved Classification Error), that lets us assess, for a given classification model, the significance of the Achieved Classification Error (ACE) on the profile data. The framework compares the performance statistic of the classifier on true data samples and checks if these are consistent with the behavior of the classifier on the same data with randomly reassigned class labels. A statistically significant ACE increases our belief that a discriminative signal was found in the data. The advantage of PACE analysis is that it can be easily combined with any classification model and is relatively easy to interpret. PACE analysis does not protect researchers against confounding in the experimental design, or other sources of systematic or random error. We use PACE analysis to assess significance of classification results we have achieved on a number of published data sets. The results show that many of these datasets indeed possess a signal that leads to a statistically significant ACE.

Understanding the Characteristics of Mass Spectrometry Data through the use of Simulation

Background

Mass spectrometry is actively being used to discover disease-related proteomic patterns in complex mixtures of proteins derived from tissue samples or from easily obtained biological fluids. The potential importance of these clinical applications has made the development of better methods for processing and analyzing the data an active area of research. It is, however, difficult to determine which methods are better without knowing the true biochemical composition of the samples used in the experiments.

Methods

We developed a mathematical model based on the physics of a simple MALDI-TOF mass spectrometer with time-lag focusing. Using this model, we implemented a statistical simulation of mass spectra. We used the simulation to explore some of the basic operating characteristics of MALDI or SELDI instruments.

Results

The simulation reproduced several characteristics of actual instruments. We found that the relative mass error is affected by the time discretization of the detector (about 0.01%) and the spread of initial velocities (about 0.1%). The accuracy of calibration based on external standards decays rapidly outside the range spanned by the calibrants. Natural isotope distributions play a major role in broadening peaks associated with individual proteins. The area of a peak is a more accurate measure of its size than the height.

Conclusions

The model described here is capable of simulating realistic mass spectra. The simulation should become a useful tool for generating spectra where the true inputs are known, allowing researchers to evaluate the performance of new methods for processing and analyzing mass spectra.

Availability

http://bioinformatics.mdanderson.org/cromwell.html

Optical measurements of paintings and the creation of an artwork database for authenticity

Paintings have high cultural and commercial value, so that needs to be preserved. Many techniques have been attempted to analyze properties of paintings, including X-ray analysis and optical coherence tomography (OCT) methods, and enable conservation of paintings from forgeries. In this paper, we suggest a simple and accurate optical analysis system to protect them from counterfeit which is comprised of fiber optics reflectance spectroscopy (FORS) and line laser-based topographic analysis. The system is designed to fully cover the whole area of paintings regardless of its size for the accurate analysis. For additional assessments, a line laser-based high resolved OCT was utilized. Some forgeries were created by the experts from the three different styles of genuine paintings for the experiments. After measuring surface properties of paintings, we could observe the results from the genuine works and the forgeries have the distinctive characteristics. The forgeries could be distinguished maximally 76.5% with obtained RGB spectra by FORS and 100% by topographic analysis. Through the several executions, the reliability of the system was confirmed. We could verify that the measurement system is worthwhile for the conservation of the valuable paintings. To store the surface information of the paintings in micron scale, we created a numerical database. Consequently, we secured the databases of three different famous Korean paintings for accurate authenticity.

The Use of Soluble, Salivary c-erbB-2 for the Detection and Post-operative Follow-up of Breast Cancer in Women: The Results of a Five-year Translational Research Study

A surge of new technological developments, coupled with the limitations of existing disease-detection methodologies, is propelling the field of medical diagnostics forward at unprecedented rates. Advancements in proteomics and nanotechnology are paving the way for diagnostic tests that will be capable of rapid multi-analyte detection in both laboratory and non-laboratory settings. Technological advancements have also benefited biomarker research to the point where saliva is now recognized as an excellent diagnostic medium that can be collected simply and non-invasively. Salivary biomarkers have been identified that may provide diagnostic information about a variety of cancers and other diseases. In particular, proof-of-principle has been demonstrated for salivary c-erbB-2, whose elevation has been shown to correlate strongly with breast malignancy in women. The purpose of this manuscript is to review the past literature and present the current research focused on the use of saliva as a diagnostic medium for the detection of malignancies that are remote from the oral cavity.

Ambient ionization MS for bioanalysis: recent developments and challenges

Ambient ionization MS has become very popular in analytical science and has now evolved as an effective analytical tool in metabolomics, biological tissue imaging, protein and small molecule drug analysis, where biological samples are probed in a rapid and direct fashion with minimal sample preparation at ambient conditions. However, certain inherent challenges continue to hinder the vibrant prospects of these methods for in situ analyses or to replace conventional methods in bioanalysis. This review provides an introduction to the field and its application in bioanalysis, with an emphasis on the most recent developments and applications. Furthermore, ongoing challenges or limitations related to quantitation, sensitivity, selectivity, instrumentation and mass range of these ambient methods will also be discussed.

Discrimination of normal and esophageal cancer plasma proteomes by MALDI-TOF mass spectrometry

BACKGROUND

Most patients presenting with symptoms of esophageal cancer (EC) have advanced disease. Even with resection, the cure rate is extremely low due to local recurrence and metastatic disease. Early detection and effective therapeutic intervention are essential to improve survival.

AIMS

This study tested the hypothesis that the presence of EC modulates concentrations of specific plasma proteins and peptides, potentially allowing discrimination between EC and controls based on mass spectrometric analysis of the respective plasma proteomes.

METHODS

Blood samples from 79 esophageal cancer patients and 40 age-matched normal subjects were processed to plasma, and protein/peptide sub-fractions were isolated using HIC8 or WAX-derivatized superparamagnetic beads. Triplicate matrix-assisted laser desorption time-of-flight mass spectra were acquired for specific plasma fractions from each subject.

RESULTS

HIC8 and WAX-derivatized plasma eluates yielded 79 and 77 candidate features, respectively, and a Random Forest algorithm identified a subset of features whose peak intensities allowed discrimination between cancer patients and controls. Areas under the curve in receiver operating characteristic curves for HIC8 spectra were 0.88 and 0.83 for WAX spectra. The combined feature set discriminated EC from control plasma with 79 % sensitivity and 79 % specificity, with positive and negative test likelihood ratios of >14 and 0.17, respectively.

CONCLUSIONS

These data lay the foundation for the development of a clinically useful test for esophageal cancer based on statistical analysis of proteomic spectra of patient plasma samples. This approach will be validated by analysis of larger patient cohorts, development of cancer-specific classifiers, and assessment of racial origin imbalances.

Mass spectrometric analysis of cerebrospinal fluid protein for glioma and its clinical application

Aim of the study

To establish and evaluate the fingerprint diagnostic models of cerebrospinal protein profile in glioma with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and bioinformatics analysis, in order to seek new tumor markers.

Material and methods

SELDI-TOF-MS was used to detect the cerebrospinal protein bond to ProteinChip H4. The cerebrospinal protein profiles were obtained and analyzed using the artificial neural network (ANN) method. Fingerprint diagnostic models of cerebrospinal protein profiles for distinguishing glioma from non-brain-tumor, and distinguishing glioma from benign brain tumor, were established. The support vector machine (SVM) algorithm was used for verification of established diagnostic models. The tumor markers were screened.

Results

In a fingerprint diagnostic model of cerebrospinal protein profiles for distinguishing glioma from non-brain tumor, the sensitivity and specificity of glioma diagnosis were 100% and 91.7%, respectively. Seven candidate tumor markers were obtained. In a fingerprint diagnostic model for distinguishing glioma from benign brain tumor, the sensitivity and specificity of glioma diagnosis were 88.9% and 100%, respectively, and 8 candidate tumor markers were gained.

Conclusions

The combination of SELDI-TOF-MS and bioinformatics tools is a very effective method for screening and identifying new markers of glioma. The established diagnostic models have provided a new way for clinical diagnosis of glioma, especially for qualitative diagnosis.

Chip-based nanoelectrospray mass spectrometry for protein characterization

In the last several years, significant progress has been made in the development of microfluidic-based analytical technologies for proteomic and drug discovery applications. Chip-based nanoelectrospray coupled to a mass spectrometer detector is one of the recently developed analytical microscale technologies. This technology offers unique advantages for automated nanoelectrospray including reduced sample consumption, improved detection sensitivity and enhanced data quality for proteomic studies. This review presents an overview and introduction of recent developments in chip devices coupled to electrospray mass spectrometers including the development of the automated nanoelectrospray ionization chip device for protein characterization. Applications using automated chip-based nanoelectrospray ionization technology in proteomic and bioanalytical studies are also extensively reviewed in the fields of high-throughput protein identification, protein post-translational modification studies, top-down proteomics, biomarker screening by pattern recognition, noncovalent protein-ligand binding for drug discovery and lipid analysis. Additionally, future trends in chip-based nanoelectrospray technology are discussed.

Role of proteomics in translational research in cervical cancer

Cervical cancer is one of the leading causes of cancer morbidity and mortality in women worldwide. More than 98% of cases are related to a human papillomavirus (HPV) infection. Infection with specific subtypes of HPV has been strongly implicated in cervical carcinogenesis. The identification and functional verification of host proteins associated with HPV E6 and E7 oncoproteins may provide useful information for understanding cervical carcinogenesis and the development of cervical cancer-specific markers. In addition, proteomic profiling of altered proteins by anticancer drugs on cervical cancer cells may contribute to providing the fundamental resources for investigation of disease-specific target proteins, elucidation of the novel mechanisms of action and development of new drugs. The advent of proteomics has provided the hope of discovering novel biological markers for use in the screening, early diagnosis and prediction of response to therapy. This review describes the studies where profiles of protein expression in cervical cancer have been generated.

Novel proteomic approaches for tissue analysis

Proteomics, the global study of protein expression and characteristics, has recently emerged as a key component in the field of molecular analysis. The dynamic nature of proteins, from ion channels to chaperones, presents a challenge, yet the understanding of these molecules provides a rich source of information. When applying proteomic analysis directly to human tissue samples, additional difficulties arise. The following article presents an overview of the current proteomic tools used in the analysis of tissues, beginning with conventional methods such as western blot analysis and 2D polyacrylamide gel electrophoresis. The most current high-throughput techniques being used today are also reviewed. These include protein arrays, reverse-phase protein lysate arrays, matrix-assisted laser desorption/ionization, surface-enhanced laser desorption/ionization and layered expression scanning. In addition, bioinformatics as well as issues regarding tissue preservation and microdissection to obtain pure cell populations are included. Finally, future directions of the tissue proteomics field are discussed.

Proteomics and NF-κB: an update

The transcription factor NF-κB was discovered in 1986 and since then has been extensively studied in relation to cancer research and inflammatory or autoimmune diseases due to its important roles in the regulation of apoptosis and inflammation as well as innate and adaptive immunity. Although much is known about NF-κB signaling, novel NF-κB functions in different diseases are still being uncovered, together with its target proteins, interaction partners and regulators of its activation cascade. Proteomic approaches are particularly suited to the discovery of new proteins involved in distinct signal transduction cascades. This review provides an update on and extension of a recent review that summarized a number of proteomic approaches to NF-κB signaling. The studies discussed here utilized innovative techniques and offer several new hypotheses on the role of NF-κB in physiological and pathophysiological processes, which open new avenues for research on NF-κB in the future.

Imaging mass spectrometry: from tissue sections to cell cultures

Imaging mass spectrometry (IMS) has been a useful tool for investigating protein, peptide, drug and metabolite distributions in human and animal tissue samples for almost 15years. The major advantages of this method include a broad mass range, the ability to detect multiple analytes in a single experiment without the use of labels and the preservation of biologically relevant spatial information. Currently the majority of IMS experiments are based on imaging animal tissue sections or small tumor biopsies. An alternative method currently being developed is the application of IMS to three-dimensional cell and tissue culture systems. With new advances in tissue culture and engineering, these model systems are able to provide increasingly accurate, high-throughput and cost-effective models that recapitulate important characteristics of cell and tissue growth in vivo. This review will describe the most recent advances in IMS technology and the bright future of applying IMS to the field of three-dimensional cell and tissue culture.

Matrix assisted ionization in vacuum, a sensitive and widely applicable ionization method for mass spectrometry

An astonishingly simple new method to produce gas-phase ions of small molecules as well as proteins from the solid state under cold vacuum conditions is described. This matrix assisted ionization vacuum (MAIV) mass spectrometry (MS) method produces multiply charged ions similar to those that typify electrospray ionization (ESI) and uses sample preparation methods that are nearly identical to matrix-assisted laser desorption/ionization (MALDI). Unlike these established methods, MAIV does not require a laser or voltage for ionization, and unlike the recently introduced matrix assisted ionization inlet method, does not require added heat. MAIV-MS requires only introduction of a crystalline mixture of the analyte incorporated with a suitable small molecule matrix compound such as 3-nitrobenzonitrile directly to the vacuum of the mass spectrometer. Vacuum intermediate pressure MALDI sources and modified ESI sources successfully produce ions for analysis by MS with this method. As in ESI-MS, ion formation is continuous and, without a laser, little chemical background is observed. MAIV, operating from a surface offers the possibility of significantly improved sensitivity relative to atmospheric pressure ionization because ions are produced in the vacuum region of the mass spectrometer eliminating losses associated with ion transfer from atmospheric pressure to vacuum. Mechanistic aspects and potential applications for this new ionization method are discussed.

Mass spectrometric profiling of low-molecular-weight proteins

Tracing potential biomarkers through proteomics has been further developed and is nearing realization. The whole sequence of human proteome is becoming better understood with the passage of time. However, it is a long way to go to pinpoint biomarker proteins out of complex biofluids and use them for clinical diagnosis, prognosis, and therapeutic applications. From that point of view, the high hopes put in proteomics have not been fulfilled yet. The key reasons for that is the complexity of the proteome and the limited technologies in terms of specificity and reproducibility. Thus, major focus is put on the development of novel innovative analytical techniques in the field of life science, using high-performance single- and multidimensional separation and enrichment methods, such as solid-phase extraction (SPE), liquid chromatography (HPLC), or capillary electrophoresis (CE) coupled to mass spectrometry (MS). A newly emerged technology, termed as material-enhanced laser desorption/ionization (MELDI) meets basic requirements and is applied to reduce the complexity of proteomic samples while liquid chromatography (LC) is used for separation and fractionation, followed by identification with MS/MS including database searching analysis. Different MELDI carriers are employed as support materials to specifically bind peptides and proteins from biofluids like serum or urine. The MELDI approach supports automated routine analysis by means of liquid handling robots for high-throughput applications leading to higher reproducibility, crucial for a successful identification of disease markers with MALDI-TOF MS. Such promising new methods and further technical developments will be necessary to answer the high-wrought expectations on the field of proteomics.

Sample handling and mass spectrometry for microbial metaproteomic analyses

Metaproteomic studies of whole microbial communities from environmental samples (e.g., soil, sediments, freshwater, seawater, etc.) have rapidly increased in recent years due to many technological advances in mass spectrometry (MS). A single 24-h liquid chromatograph-tandem mass spectrometry (LC-MS/MS) measurement can potentially detect and quantify thousands of proteins from many dominant and subdominant naturally occurring microbial populations. Importantly, amino acid sequences and relative abundance information for detected peptides are determined, which allows for the characterization of expressed protein functions within communities and specific matches to be made to microbial lineages, with potential subspecies resolution. Continued optimization of protein extraction and fractionation protocols, development of quantification methods, and advances in mass spectrometry instrumentation are enabling more accurate and comprehensive peptide detection within samples, leading to wider research applicability, greater ease of use, and overall accessibility. This chapter provides a brief overview of metaproteomics experimental options, including a general protocol for sample handling and LC-MS/MS measurement.

Discovery of putative salivary biomarkers for Sjögren's syndrome using high resolution mass spectrometry and bioinformatics

The purpose of the current study was to determine if saliva contains biomarkers that can be used as diagnostic tools for Sjögren's syndrome (SjS). Twenty seven SjS patients and 27 age-matched healthy controls were recruited for these studies. Unstimulated glandular saliva was collected from the Wharton's duct using a suction device. Two µl of salvia were processed for mass spectrometry analyses on a prOTOF 2000 matrix-assisted laser desorption/ionization orthogonal time of flight (MALDI O-TOF) mass spectrometer. Raw data were analyzed using bioinformatic tools to identify biomarkers. MALDI O-TOF MS analyses of saliva samples were highly reproducible and the mass spectra generated were very rich in peptides and peptide fragments in the 750-7,500 Da range. Data analysis using bioinformatic tools resulted in several classification models being built and several biomarkers identified. One model based on 7 putative biomarkers yielded a sensitivity of 97.5%, specificity of 97.8% and an accuracy of 97.6%. One biomarker was present only in SjS samples and was identified as a proteolytic peptide originating from human basic salivary proline-rich protein 3 precursor. We conclude that salivary biomarkers detected by high-resolution mass spectrometry coupled with powerful bioinformatic tools offer the potential to serve as diagnostic/prognostic tools for SjS.

Support vector machines coupled with proteomics approaches for detecting biomarkers predicting chemotherapy resistance in small cell lung cancer

The aim of this study was to identify serum protein fingerprints of small cell lung cancer (SCLC) and potential biomarkers related to chemotherapy resistance of SCLC with surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS). A total of 60 SCLC patients and 48 age- and sex-matched healthy individuals were enrolled. The chemotherapy regimen was cisplatin plus etoposide. All patients received two cycles of chemotherapy. Serum protein profiles were detected using SELDI-TOF MS and the spectra were analyzed with support vector machines (SVMs). Western blotting was performed to verify the results of SELDI-TOF MS. Three top scored peaks, at m/z of 6269, 9043 and 13124 Da, were finally selected as potential biomarkers for detection of SCLC. The SVM classifier separated the SCLC from the healthy samples in the blind test, with a sensitivity of 92.4% and a specificity of 92.5%. For the 56 eligible chemotherapy patients, 4 had a complete response (7.14%), 39 patients had a partial response (69.6%), 9 patients had a stable disease (16.1%) and 4 patients had a progressive disease (7.14%). The model constructed using two protein peaks with m/z of 8830 and 10468 Da separated the chemotherapy-resistant group from the chemotherapy-sensitive group with a sensitivity of 80.0% and a specificity of 80.0%. Initial protein database searching identified 10468 Da as S100-A9 which was confirmed by western blotting. The present results suggest that the combination of SELDI-TOF MS with SVM may provide a useful means in the search for serum biomarkers for predicting chemotherapy resistance in patients with SCLC.

Monitoring automotive oil degradation: analytical tools and onboard sensing technologies

Engine oil experiences a number of thermal and oxidative phases that yield acidic products in the matrix consequently leading to degradation of the base oil. Generally, oil oxidation is a complex process and difficult to elucidate; however, the degradation pathways can be defined for almost every type of oil because they mainly depend on the mechanical status and operating conditions. The exact time of oil change is nonetheless difficult to predict, but it is of great interest from an economic and ecological point of view. In order to make a quick and accurate decision about oil changes, onboard assessment of oil quality is highly desirable. For this purpose, a variety of physical and chemical sensors have been proposed along with spectroscopic strategies. We present a critical review of all these approaches and of recent developments to analyze the exact lifetime of automotive engine oil. Apart from their potential for degradation monitoring, their limitations and future perspectives have also been investigated.

Biological and methodical challenges of blood-based proteomics in the field of neurological research

Biomarker discovery is an application of major importance in today's proteomic research. There is an urgent need for suitable biomarkers to improve diagnostic tools and treatment in various neurological diseases, such as neurodegenerative disorders. Recent years have witnessed an enormous interest in proteomics, which is currently seen as an invaluable tool to shed more light on complex interacting signalling pathways and molecular networks involved in several neuropathological conditions. However, while first results of proteomic research studies have sparked much public attention, the momentum of further proteomic biomarker research in neurological disorders may suffer by its very complex methodology which is sensitive to various sources of artefacts. A major source of variability is proteome perturbation caused by sample handling/preservation (preanalytical phase) and processing/measurement (analytical phase). The aim of the present review is to summarize the current literature focusing on the crucial role played by preanalytical and analytical factors that affect the quality of samples and the reliability of the data produced in blood-based proteomic biomarker research in neurology, which may apply to Alzheimer's disease (AD) as well as other neurological disorders. Procedures for sample preparation and protocols for the analysis of serum and plasma samples will be delineated. Finally, the potential usefulness of bioinformatics--allowing for the assembly, store, and processing of data--as well as its contribution to the execution of proteomic studies will be critically discussed.

S100A10 protein expression is associated with oxaliplatin sensitivity in human colorectal cancer cells

Background

Individual responses to oxaliplatin (L-OHP)-based chemotherapy remain unpredictable. The objective of our study was to find candidate protein markers for tumor sensitivity to L-OHP from intracellular proteins of human colorectal cancer (CRC) cell lines. We performed expression difference mapping (EDM) analysis of whole cell lysates from 11 human CRC cell lines with different sensitivities to L-OHP by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS), and identified a candidate protein by liquid chromatography/mass spectrometry ion trap time-of-flight (LCMS-IT-TOF).

Results

Of the qualified mass peaks obtained by EDM analysis, 41 proteins were differentially expressed in 11 human colorectal cancer cell lines. Among these proteins, the peak intensity of 11.1 kDa protein was strongly correlated with the L-OHP sensitivity (50% inhibitory concentrations) (P < 0.001, R² = 0.80). We identified this protein as Protein S100-A10 (S100A10) by MS/MS ion search using LCMS-IT-TOF. We verified its differential expression and the correlation between S100A10 protein expression levels in drug-untreated CRC cells and their L-OHP sensitivities by Western blot analyses. In addition, S100A10 protein expression levels were not correlated with sensitivity to 5-fluorouracil, suggesting that S100A10 is more specific to L-OHP than to 5-fluorouracil in CRC cells. S100A10 was detected in cell culture supernatant, suggesting secretion out of cells.

Conclusions

By proteomic approaches including SELDI technology, we have demonstrated that intracellular S100A10 protein expression levels in drug-untreated CRC cells differ according to cell lines and are significantly correlated with sensitivity of CRC cells to L-OHP exposure. Our findings provide a new clue to searching predictive markers of the response to L-OHP, suggesting that S100A10 is expected to be one of the candidate protein markers.

Early diagnostic protein biomarkers for breast cancer: how far have we come?

Many studies have used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to search for blood-based proteins that are related to the presence of breast cancer. We review the biomarkers discovered or targeted measured by these methods and discuss the strengths and weaknesses of these studies. We highlight two proteins that were most often related to breast cancer: C3a des-arginine anaphylatoxin (C3adesArg) (molecular weight: 8,938 Da) and fragments of inter-alpha trypsin inhibitor heavy chain H4 (ITIH4). In addition, we elaborate on three important methodological aspects related to these studies: protein identification, specificity of the markers, and disease heterogeneity. Finally, we propose some points to be addressed in future studies. These include the use of other analytical measurement techniques, need of protein identification, the importance of identical sample handling protocols for cases and controls, and the stratification of the results according to molecular subtypes and stages of breast cancer. Ultimately this may lead to the discovery of new and valid breast cancer specific biomarkers.

Elucidating the role of metals in Alzheimer's disease through the use of Surface-Enhanced Laser Desorption/Ionisation time-of-flight mass spectrometry

Alzheimer's disease (AD) is a highly heterogeneous and progressive dementia which is characterised by a progressive decline in cognitive functioning, selective neuronal atrophy, and loss of cortical volume in areas involved in learning and memory. However, recent research has indicated that the AD-affected brain is also besieged by increases in oxidative stress as well as perturbations to the homeostasis of biometals, such as copper and iron. These metals are known to interact with the neuropathological hallmark of AD, the β-amyloid peptide (Aβ), in a manner which increases Aβ's neurotoxic effects. This knowledge has led to the development of therapeutic measures which act to restore biometal homeostasis within the AD brain. This chapter outlines how Surface-Enhanced Laser Desorption/Ionisation Time-of-Flight Mass Spectrometry can be used to monitor Aβ levels within biological systems as well as describing the use of immobilised metal affinity capture in the observation of synthetic Aβ peptides.

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.

Searching for early breast cancer biomarkers by serum protein profiling of pre-diagnostic serum; a nested case-control study

Background

Serum protein profiles have been investigated frequently to discover early biomarkers for breast cancer. So far, these studies used biological samples collected at or after diagnosis. This may limit these studies' value in the search for cancer biomarkers because of the often advanced tumor stage, and consequently risk of reverse causality. We present for the first time pre-diagnostic serum protein profiles in relation to breast cancer, using the Prospect-EPIC (European Prospective Investigation into Cancer and nutrition) cohort.

Methods

In a nested case-control design we compared 68 women diagnosed with breast cancer within three years after enrollment, with 68 matched controls for differences in serum protein profiles. All samples were analyzed with SELDI-TOF MS (surface enhanced laser desorption/ionization time-of-flight mass spectrometry). In a subset of 20 case-control pairs, the serum proteome was identified and relatively quantified using isobaric Tags for Relative and Absolute Quantification (iTRAQ) and online two-dimensional nano-liquid chromatography coupled with tandem MS (2D-nanoLC-MS/MS).

Results

Two SELDI-TOF MS peaks with m/z 3323 and 8939, which probably represent doubly charged apolipoprotein C-I and C3a des-arginine anaphylatoxin (C3a_desArg), were higher in pre-diagnostic breast cancer serum (p = 0.02 and p = 0.06, respectively). With 2D-nanoLC-MS/MS, afamin, apolipoprotein E and isoform 1 of inter-alpha trypsin inhibitor heavy chain H4 (ITIH4) were found to be higher in pre-diagnostic breast cancer (p < 0.05), while alpha-2-macroglobulin and ceruloplasmin were lower (p < 0.05). C3a_desArg and ITIH4 have previously been related to the presence of symptomatic and/or mammographically detectable breast cancer.

Conclusions

We show that serum protein profiles are already altered up to three years before breast cancer detection.

Novel Sample Preparation for Mass Spectral Analysis of Complex Biological Samples

The ability to combine a selective capture strategy with on chip MALDI-TOF analysis allows for rapid, sensitive analysis of a variety of different analytes. In this overview a series of applications of capture enhanced laser desorption ionization time of flight (CELDI-TOF) mass spectrometry are described. The key feature of the assay is an off-chip capture step that utilizes high affinity bacterial binding proteins to capture a selected ligand. This allows large volumes of sample to be used and provides for a concentration step prior to transfer to a gold chip for traditional mass spectral analysis. The approach can also be adapted to utilize specific antibody as the basis of the capture step. The direct and indirect CELDI-TOF assays are rapid, reproducible and can be a valuable proteomic tool for analysis of low abundance molecules present in complex mixtures like blood plasma.