Peptidomics technologies for human body fluids

Peptidomics technologies for human body fluids

Analysis of human bodily fluids on superabsorbent pads by ATR-FTIR

Deamidation of Amino Acids on the Surface of Adeno-Associated Virus Capsids Leads to Charge Heterogeneity and Altered Vector Function.

Amniotic fluid is a dynamic and complex mixture that reflects the physiological status of the developing fetus. In this study, the human amniotic fluid (AF) proteome of a 16-18-week normal pregnancy was profiled and analyzed to investigate the composition and functions of this fluid. Due to the complexity of AF, we utilized three different fractionation strategies to provide greater coverage. Two types of two-dimensional LC/MS/MS as well as an LC-SDS-PAGE-LC-MS/MS platform were used. A total of 16 AF samples between gestational ages of 16 and 18 weeks from women carrying chromosomally normal fetuses were analyzed by one of the three fractionation methods followed by a common reverse phase LC-MS/MS step. Mascot and The Global Proteome Machine engines were used to search the International Protein Index human database for peptide sequence identification. The list of proteins was generated by combining the results of both engines through the PeptideProphet of Scaffold software. All identified proteins were combined to generate the AF proteome comprising 1,026 unique gene matches or 842 non-redundant proteins. This list includes most of the currently used biomarkers for pregnancy-associated pathologic conditions such as preterm delivery, intra-amniotic infection, and chromosomal anomalies of the fetus. The subcellular localization, tissue expression, functions, and networks of the AF proteome were analyzed by various bioinformatic tools. These data will contribute to the better understanding of amniotic fluid function and to the discovery of novel biomarkers for prenatal diagnosis of fetal abnormalities.

Clinical proteomics involves the analysis of protein expression of disease proteomes, with the aim of solving a specific clinical problem. Discoveries made from proteomicbased studies contribute to the growing need for innovative medical diagnostics for disease detection. Taking into consideration the global health burden of cardiac disease, clinical proteomics is a valuable tool to improve risk stratification associated with this disease. In cardiovascular medicine, the identification of novel proteins, or biomarkers, that are differentially expressed in cardiac disease proteomes may enable early detection of the disease state, thereby preventing progression to disease end points. This review outlines various proteomic platforms and their technical advancements and relates these to the cardiovascular sciences. The entire protein complement of the cell, or proteome, is dynamic and changes in response to the disease state. 1 Proteomic-based experiments can be used to characterize such alterations in protein expression during disease progression. 2 With combined improvements in mass spectrometry (MS) technology as well as innovative molecular biology screening tools, there has been widespread growth in the characterization of cardiac disease proteomes. In fact, proteomic technology has been an important tool in the analysis of heart failure (HF), 3,4 cardiac hypertrophy, 5,6 and dilated cardiomyopathy.7 Several of the overarching aims of such studies include providing greater understanding of general biological mechanisms as well as identifying unique proteins that are clinically useful in the detection of cardiac disease in the early stages or potentially used as novel therapeutic targets. Clinical proteomics continues to benefit from advancements in technologies that allow for fast and consistent identification of proteins with corresponding increases in the dynamic range of proteins detectable in the disease proteome. MS-related technologies have improved in their ability to detect low-abundance proteins as well as membrane proteins and have benefited from sample preprocessing strategies that decrease the complexity of large-scale analyses. With the emergence of different methodologies for biomarker identification, the following 3 criteria must be taken into careful consideration to determine whether the protein is, in fact,

Extracellular vesicles (EVs) are cell-derived multicomponent messengers that participate in diverse intercellular communication processes regulating immune responses, cell survival and proliferation. However, EVs also play a role in disease processes like cancer. Since EVs contain biological information that reflects the status of the cell of origin, they might be used in liquid biopsies as disease biomarkers. The detection and characterization of EVs is a fundamental step towards EV-based biomarker profiling of pathological processes and is complicated due to their small size, heterogeneity and complex composition. Therefore, technological solutions that allow high throughput detection and analysis of single EVs are of utmost importance. Flow cytometry (FCM) is a promising technology for this purpose. However, traditional flow cytometers, designed for cells, lack the sensitivity for the detection of nano-sized EVs, whose signals are typically below or at the detection limit of conventional instruments. In my PhD thesis I explored the limits of flow cytometry of single EVs, provide guidance for reproducible and robust EV FCM and address the challenges of EV analysis in body fluids. First, we developed and characterized a reference material for EV research. Next, we focused on high-sensitivity FCM for the detection of EVs and I present a reporting framework developed by the ISEV-ISAC-ISTH EV Flow cytometry workgroup to increase reproducibility of results. Since fluorescence calibration of EV signals is of importance for inter-instrument and inter-lab comparisons, we provide insights into the utilization of current calibrators and show that intrinsic variations related to these calibrators compromise accurate calibration of EV signals. In addition to the fluorescence, light scatter signals also contain valuable information that it is often lost within the background noise. By using an open-architecture flow cytometer, we optimized the configuration by combining differently sized hardware components to improve light scatter-based EV detection by reducing optical background signals. Lastly, we applied these technological advancements in the field of high-sensitivity FCM to investigate interactions between biological particles, namely EVs and lipoprotein particles (LPPs), which are known to co-isolate. Liquid biopsy EV-based biomarker profiling is complicated because LPPs in blood outnumber EVs by orders of magnitude and have biophysical overlapping properties with EVs, including size and density. We here demonstrate by high-sensitivity FCM, in combination with orthogonal methods; i.e., Rayleigh and Raman scattering and cryo-electron microscopy, that EV-LPP complexes can be formed and can impact EV-analysis in blood. Overall, the findings presented in my thesis can contribute to the development of robust liquid biopsy EV biomarker profiling by FCM and shed light on the complexity of single EV analysis in body fluids, which will ultimately help to a successful clinical translation of EVs as disease biomarkers.

Investigation of Cu-, Zn- and Fe-containing human brain proteins using isotopic-enriched tracers by LA-ICP-MS and MALDI-FT-ICR-MS

Saliva plays many biological roles, from lubrication and digestion to regulating bacterial and leukocyte adhesion. To understand the functions of individual components and families of molecules, it is important to identify as many salivary proteins as possible. Toward this goal, we used a proteomic approach as the first step in a global analysis of this important body fluid. We collected parotid saliva as the ductal secretion from three human donors and separated the protein components by two-dimensional SDS-polyacrylamide gel electrophoresis (2D SDS-PAGE). Proteins in gel spots were identified by peptide mass fingerprinting, and the results were confirmed by tandem mass spectrometry of selected peptides. Complementing this approach we used ultrafiltration to prepare a low-molecular-weight fraction of parotid saliva, which was analyzed directly or after reversed phase high-performance liquid chromatography separation by using mass spectrometric approaches. MS analyses of 2D SDS-PAGE spots revealed known components of saliva, including cystatins, histatins, lysozyme, and isoforms and/or fragments of alpha-amylase, albumin, and proline-rich proteins. We also discovered novel proteins, such as several isoforms of Zn-alpha-2-glycoprotein and secretory actin-binding protein. MS analyses of the ultrafiltrate showed that the low-molecular-weight fraction of parotid saliva was peptide-rich, with novel fragments of proline-rich proteins and histatins in abundance. Experiments using Candida albicans as the test organism showed that at least one of the novel peptides had antifungal activity. Our results show that saliva is a rich source of proteins and peptides that are potential diagnostic and therapeutic targets.

In the last decade various analytical strategies have been established to enhance separation speed and efficiency in high performance liquid chromatography applications. Chromatographic supports based on monolithic material, small porous particles, and porous layer beads have been developed and commercialized to improve throughput and separation efficiency. This paper provides an overview of current developments in fast chromatography combined with mass spectrometry for the analysis of metabolites and proteins in clinical applications. Advances and limitations of fast chromatography for the combination with mass spectrometry are discussed. Practical aspects of, recent developments in, and the present status of high-throughput analysis of human body fluids for therapeutic drug monitoring, toxicology, clinical metabolomics, and proteomics are presented.

Characterisation of botulinum toxins type A and B, by matrix-assisted laser desorption ionisation and electrospray mass spectrometry

Quantitative proteomics is the workhorse of the modern proteomics initiative. The gel-based and MuDPIT approaches have facilitated vital advances in the measurement of protein expression alterations in normal and disease phenotypic states. The methodological advance in two-dimensional gel electrophoresis (2DGE) has been the multiplexing fluorescent two-dimensional fluorescence difference gel electrophoresis (2D-DIGE). 2D-DIGE is based on direct labeling of lysine groups on proteins with cyanine CyDye DIGE Fluor minimal dyes before isoelectric focusing, enabling the labeling of 2-3 samples with different dyes and electrophoresis of all the samples on the same 2D gel. This capability minimizes spot pattern variability and the number of gels in an experiment while providing simple, accurate and reproducible spot matching. This protocol can be completed in 3-5 weeks depending on the sample size of the experiment and the level of expertise of the investigator.

Isobaric tags for relative and absolute quantitation, an approach to concurrent, relative quantification of proteins present in four cell preparations, have recently been described. To validate this approach using complex mammalian cell samples that show subtle differences in protein levels, a model stem cell-like cell line (FDCP-mix) in the presence or absence of the leukemogenic oncogene TEL/PDGFRbeta has been studied. Cell lysates were proteolytically digested, and peptides within each sample were labeled with one of four isobaric, isotope-coded tags via their N-terminal and/or lysine side chains. The four labeled samples are mixed and peptides separated by two-dimensional liquid chromatography online to a mass spectrometer (LC-MS). Upon peptide fragmentation, each tag releases a distinct mass reporter ion; the ratio of the four reporters therefore gives relative abundances of the given peptide. Relative quantification of proteins is derived using summed data from a number of peptides. TEL/PDGFRbeta leukemic oncogene-mediated changes in protein levels were compared with those seen in microarray analysis of control and transfected FDCP-mix cells. Changes at the protein level in most cases reflected those seen at the transcriptome level. Nonetheless, novel differences in protein expression were found that indicate potential mechanisms for effects of this oncogene.

Integration of multi-omics approaches for understanding the Maize (Zea mays L.) foliar priming responses to Nano-urea plus (NUP) colloidal liquid fertilizer

Analytical identification of additional impurities in urinary-derived gonadotrophins

Human body fluids are considered as attractive sources for clinical markers. As for disease diagnosis and prognosis, advantages of body fluid testing include low invasiveness, low cost, and rapid sample collection and processing. Besides, altered protein expression profiles in body fluids reflect the change of physiological states and cellular networks of the diseased tissue/organ. Thus, analysis of human body fluid has become one of the most promising approaches to discover biomarkers or reveal pathophysiological mechanisms for human diseases. Human body fluid analysis is inherently challenging due to their unique characteristics such as protein complexity and the wide dynamic range of protein abundances. With the remarkable advances in the methods for sample preparation, proteomics technology, and quantitation, it is now possible to analyze body fluids with higher sensitivity and robust experimental design. As the recognition of the importance of “Translational Medicine” which is the process of turning appropriate biological discoveries into drugs and medical devices that can be used in the diagnosis and/or treatment of patients, a great quantity of researches were focusing on the human sample including human body fluids. Thus, it is conceivable that the new insight unveiled by human body fluid analysis will attract a wide audience abroad including researchers from the field of basic sciences, bioinformatics, analytical chemistry, molecular biology, and hospital. In the study of H. Y. Wu et al., authors performed the first differential proteomic profiling between peritoneal dialysates from chronic glomerulonephritis (CGN) patients at the early and middle stage of continuous ambulatory peritoneal dialysis (CAPD) treatment. The changed proteins provide clues to the PD-induced loss of proteins from the peritoneum and assist the identification of potential biomarkers for noninvasive monitoring of peritoneal damage. M. H. Yang et al. also characterized the peritoneal dialysate proteins from diabetes mellitus (DM) by proteomic tools. CGN peritoneal dialysate was used as control. Differentially expressed proteins in DM samples may indicate a situation for possible drug treatment and predictors of peritonitis for a validation study in the future. P. Badiee reviewed the evaluation of different human body fluids, pleural Effusion, bronchoalveolar lavage fluid, peritoneal fluid, urine, pericardial effusion, blood, cerebrospinal fluid (CSF), synovial fluid, and saliva, for diagnosing fungal infections. Routine laboratory tests for the diagnosis of FI include urinalysis and blood analysis while analyses of both CSF and serum can improve the accuracy of the diagnosis. K. Bořecka et al. studied the use of Coefficient of Energy Balance (CEB) values in a large CSF samples (n = 8183) to demonstrate that CEB enables more exact assessment of actual energy state in the CSF compartment than glucose and lactate alone. This study suggested that CEB combined with CSF cytology has a great importance for diagnosis, differential diagnosis, and early therapy of CNS diseases. H. C. Yen et al. discussed potential interferences on the analysis of F2-IsoPs and F4-NPs in CSF by GC/NICI-MS by present analytical methods. Proper TLC purification for obtaining reliable chromatograms for F2-IsoPs quantification in CSF is suggested as well as the necessity of adding additional holding of the column at 280°C for a period of time following data acquisition during F2-IsoPs and F4-NPs analysis to avoid potential interferences on subsequent F4-NPs quantification in CSF.