Review of software tools for design and analysis of large scale MRM proteomic datasets

Immunocapture LC-MS methods for pharmacokinetics of large molecule drugs

Implementation of immunocapture LC-MS methods to characterize the pharmacokinetic profile of large molecule drugs has become a widely used technique over the past decade. As the pharmaceutical industry strives for speediness into clinical development without jeopardizing quality, robust assays with generic application across the pipeline are becoming instrumental in bioanalysis, especially in early-stage development. This review highlights the capabilities and challenges involved in hybrid immunocapture LC-MS techniques and its continued applications in nonclinical and clinical pharmacokinetic assay design. This includes a comparison of LC-MS-based approaches to conventional ligand-binding assays and the driving demands in large molecule drug portfolios including growing sensitivity requirements and the unique challenges of new modalities requiring innovation in the bioanalytical laboratory.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Functional proteomics based on protein microarray technology for biomedical research

This chapter traces a route through Proteomics from its origins to the present day. The different proteomics applications are discussed with a focus on microarray technology. Analytical microarrays, functional microarrays and reverse phase microarrays and their different applications are discussed. Several studies are mentioned where the great versatility of this approach is shown. Finally, the advantages and future challenges of microarray technology are outlined.

Creation of a Plant Metabolite Spectral Library for Untargeted and Targeted Metabolomics

Large-scale high throughput metabolomic technologies are indispensable components of systems biology in terms of discovering and defining the metabolite parts of the system. However, the lack of a plant metabolite spectral library limits the metabolite identification of plant metabolomic studies. Here, we have created a plant metabolite spectral library using 544 authentic standards, which increased the efficiency of identification for untargeted metabolomic studies. The process of creating the spectral library was described, and the mzVault library was deposited in the public repository for free download. Furthermore, based on the spectral library, we describe a process of creating a pseudo-targeted method, which was applied to a proof-of-concept study of Arabidopsis leaf extracts. As authentic standards become available, more metabolite spectra can be easily incorporated into the spectral library to improve the mzVault package.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Paleoproteomics

Paleoproteomics, the study of ancient proteins, is a rapidly growing field at the intersection of molecular biology, paleontology, archaeology, paleoecology, and history. Paleoproteomics research leverages the longevity and diversity of proteins to explore fundamental questions about the past. While its origins predate the characterization of DNA, it was only with the advent of soft ionization mass spectrometry that the study of ancient proteins became truly feasible. Technological gains over the past 20 years have allowed increasing opportunities to better understand preservation, degradation, and recovery of the rich bioarchive of ancient proteins found in the archaeological and paleontological records. Growing from a handful of studies in the 1990s on individual highly abundant ancient proteins, paleoproteomics today is an expanding field with diverse applications ranging from the taxonomic identification of highly fragmented bones and shells and the phylogenetic resolution of extinct species to the exploration of past cuisines from dental calculus and pottery food crusts and the characterization of past diseases. More broadly, these studies have opened new doors in understanding past human-animal interactions, the reconstruction of past environments and environmental changes, the expansion of the hominin fossil record through large scale screening of nondiagnostic bone fragments, and the phylogenetic resolution of the vertebrate fossil record. Even with these advances, much of the ancient proteomic record still remains unexplored. Here we provide an overview of the history of the field, a summary of the major methods and applications currently in use, and a critical evaluation of current challenges. We conclude by looking to the future, for which innovative solutions and emerging technology will play an important role in enabling us to access the still unexplored "dark" proteome, allowing for a fuller understanding of the role ancient proteins can play in the interpretation of the past.

Targeted proteomics for cancer biomarker verification and validation

Targeted proteomics is a method that measures the amount of target proteins via liquid chromatography-tandem mass spectrometry and is used to verify and validate the candidate cancer biomarker proteins. Compared with antibody-based quantification methods such as ELISA, targeted proteomics enables rapid method development, simultaneous measurement of multiple proteins, and high-specificity detection of modifications. Moreover, by spiking the internal standard peptide, targeted proteomics detects the absolute amounts of marker proteins, which is essential for determining the cut-off values for diagnosis and thus for multi-institutional validation. With these unique features, targeted proteomics can seamlessly transfer cancer biomarker candidate proteins from the discovery phase to the verification and validation phases, thereby resulting in an accelerated cancer biomarker pipeline. Furthermore, understanding the basic principles, advantages, and disadvantages is necessary to effectively utilize targeted proteomics in cancer biomarker pipelines. This review aimed to introduce the technical principles of targeted proteomics for cancer biomarker verification and validation.

Recent advances in mass-spectrometry based proteomics software, tools and databases

The field of proteomics immensely depends on data generation and data analysis which are thoroughly supported by software and databases. There has been a massive advancement in mass spectrometry-based proteomics over the last 10 years which has compelled the scientific community to upgrade or develop algorithms, tools, and repository databases in the field of proteomics. Several standalone software, and comprehensive databases have aided the establishment of integrated omics pipeline and meta-analysis workflow which has contributed to understand the disease pathobiology, biomarker discovery and predicting new therapeutic modalities. For shotgun proteomics where Data Dependent Acquisition is performed, several user-friendly software are developed that can analyse the pre-processed data to provide mechanistic insights of the disease. Likewise, in Data Independent Acquisition, pipelines are emerged which can accomplish the task from building the spectral library to identify the therapeutic targets. Furthermore, in the age of big data analysis the implications of machine learning and cloud computing are appending robustness, rapidness and in-depth proteomics data analysis. The current review talks about the recent advancement, and development of software, tools, and database in the field of mass-spectrometry based proteomics.

Development and application of sequential window acquisition of all theoretical mass spectra data acquisition modes on ultra-high-performance liquid chromatography triple-quadrupole/time-of-flight mass spectrometry for metabolic profiling of amino acids in human plasma

Accumulating evidence suggests that amino acids are important indicators of nutritional and metabolic status. A high-resolution mass spectrometry method based on sequential window acquisition of all theoretical mass spectra acquisition was developed for the simultaneous determination of 16 amino acids in human plasma. Sample preparation by protein precipitation using a mixture of acetonitrile and formic acid was followed by a BEH Amide column. The superiority of this method was investigated by comparing it to time-of-flight scan and multiple reaction monitoring modes. The limit of detection in sequential window acquisition of all theoretical mass spectra mode for threonine, methionine, histidine, citrulline, and tryptophan is 0.1 ng on the column; for lysine and asparagine is 0.2 ng; for alanine, pyroglutamic acid, leucine, ornithine, and aspartate is 0.5 ng, for arginine is 1.0 ng; for glutamate and serine is 2.0 ng; for glutamine is 10.0 ng. This method was linear in the range 0.8-40 μg/mL for arginine, citrulline, glutamate, histidine, leucine, methionine, pyroglutamic acid, threonine, tryptophan; 2-100 μg/mL for asparagine, aspartate, lysine, ornithine, serine; and 4-200 μg/mL for alanine, glutamine with good accuracy and precision. Significantly different levels in 11 amino acids were observed between childhood and adulthood, representing the growth and development of individuals relating to the level of amino acids.

Forensic proteomics

Protein is a major component of all biological evidence, often the matrix that embeds other biomolecules such as polynucleotides, lipids, carbohydrates, and small molecules. The proteins in a sample reflect the transcriptional and translational program of the originating cell types. Because of this, proteins can be used to identify body fluids and tissues, as well as convey genetic information in the form of single amino acid polymorphisms, the result of non-synonymous SNPs. This review explores the application and potential of forensic proteomics. The historical role that protein analysis played in the development of forensic science is examined. This review details how innovations in proteomic mass spectrometry have addressed many of the historical limitations of forensic protein science, and how the application of forensic proteomics differs from proteomics in the life sciences. Two more developed applications of forensic proteomics are examined in detail: body fluid and tissue identification, and proteomic genotyping. The review then highlights developing areas of proteomics that have the potential to impact forensic science in the near future: fingermark analysis, species identification, peptide toxicology, proteomic sex estimation, and estimation of post-mortem intervals. Finally, the review highlights some of the newer innovations in proteomics that may drive further development of the field. In addition to potential impact, this review also attempts to evaluate the stage of each application in the development, validation and implementation process. This review is targeted at investigators who are interested in learning about proteomics in a forensic context and expanding the amount of information they can extract from biological evidence.

Leveraging proteomics in orphan disease research: pitfalls and potential

Introduction: The term 'orphan diseases' includes conditions meeting prevalence-based or commercial viability criteria: they affect a small number of individuals and are considered an unviable market for drug development. Proteomics is an important technology to study them, providing information on mechanisms and evolution, biomarkers, and effects of therapeutic interventions.Areas covered: Herein, we review how proteomics and bioinformatic tools could be applied to the study of rare diseases and discuss pitfalls and potential.Expert opinion: Research in the field of rare diseases has to face many challenges, and implementation plans should foresee highly specialized collaborative consortia to create multidisciplinary frameworks for data sharing, advancing research, supporting clinical studies, and accelerating drug development. The integration of different technologies will allow better knowledge of disease pathophysiology, and the inclusion of proteomics and other omics technologies in this context will be pivotal to this aim.Several aspects of rare diseases, often perceived as limiting factors, might actually be advantages for a precision medicine approach: the limited number of patients, the collaboration with patient societies, and the availability of curated clinical registries could allow the development of homogeneous clinical databases and ultimately a better control over the data to be analyzed.

Protein biomarker elucidation for the verification of biological agents in the taxonomic group of Gammaproteobacteria using tandem mass spectrometry

Some pathogenic microbes can be used for nefarious applications and instigate population-based fear. In a bio-threat scenario, rapid and accurate methods to detect biological agents in a wide range of complex environmental and clinical matrices, is of paramount importance for the implementation of mitigation protocols and medical countermeasures. This study describes targeted and shot-gun tandem MS based approaches for the verification of biological agents from the environmental samples. The marker proteins and peptides were elucidated by an exhaustive literature mining, in silico analysis of prioritized proteins, and MS/MS analysis of abundant proteins from selected bacterial species. For the shot-gun methodology, tandem MS analysis of abundant peptides was carried from spiked samples. The validation experiments employing a combination of shot-gun tandem MS analysis and a targeted search reported here is a proof of concept to show the applicability of the methodology for the unambiguous verification of biological agents at sub-species level, even with limited fractionation of crude protein extracts from environmental samples.

Emerging mass spectrometry-based proteomics methodologies for novel biomedical applications

Research into the basic biology of human health and disease, as well as translational human research and clinical applications, all benefit from the growing accessibility and versatility of mass spectrometry (MS)-based proteomics. Although once limited in throughput and sensitivity, proteomic studies have quickly grown in scope and scale over the last decade due to significant advances in instrumentation, computational approaches, and bio-sample preparation. Here, we review these latest developments in MS and highlight how these techniques are used to study the mechanisms, diagnosis, and treatment of human diseases. We first describe recent groundbreaking technological advancements for MS-based proteomics, including novel data acquisition techniques and protein quantification approaches. Next, we describe innovations that enable the unprecedented depth of coverage in protein signaling and spatiotemporal protein distributions, including studies of post-translational modifications, protein turnover, and single-cell proteomics. Finally, we explore new workflows to investigate protein complexes and structures, and we present new approaches for protein-protein interaction studies and intact protein or top-down MS. While these approaches are only recently incipient, we anticipate that their use in biomedical MS proteomics research will offer actionable discoveries for the improvement of human health.

Serum proteomics analysis of candidate predictive biomarker panel for the diagnosis of trastuzumab-based therapy resistant breast cancer

Human epidermal growth factor receptor 2 (HER2)-positive is a particularly aggressive type of the breast cancer. Trastuzumab-based therapy is a standard treatment for HER2-positive breast cancer, but some patients are resistant to the therapy. Serum proteins have been used to predict therapeutic benefit for various cancers, but whether serum proteins can serve as biomarkers for HER2-positive breast cancer remains unclear. Using an isobaric Tandem Mass Tag (TMT) label-based quantitative proteomic, we discovered 18 differentially expressed proteins in the serum of trastuzumab-based therapy resistant patients before therapy. Then, four proteins were selected and validated using an LC-MS/MS-based multiple reaction monitoring quantification method, and it was confirmed that three proteins (SRGN, LDHA and CST3) were correlated with trastuzumab-based therapy resistance. Finally, the trastuzumab-based therapy resistance diagnostic score was calculated and acquired by means of a logistic regression pattern based on the level of these three proteins. In summary, we develop a serum-based protein signature that potentially predicts the therapeutic effects of trastuzumab-based therapy for HER2-positive breast cancer patients.

The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics

Skyline is a freely available, open-source Windows client application for accelerating targeted proteomics experimentation, with an emphasis on the proteomics and mass spectrometry community as users and as contributors. This review covers the informatics encompassed by the Skyline ecosystem, from computationally assisted targeted mass spectrometry method development, to raw acquisition file data processing, and quantitative analysis and results sharing.

CalibraCurve: A Tool for Calibration of Targeted MS-Based Measurements

Targeted proteomics techniques allow accurate quantitative measurements of analytes in complex matrices with dynamic linear ranges that span up to 4-5 orders of magnitude. Hence, targeted methods are promising for the development of robust protein assays in several sensitive areas, for example, in health care. However, exploiting the full method potential requires reliable determination of the dynamic range along with related quantification limits for each analyte. Here, a software named CalibraCurve that enables an automated batch-mode determination of dynamic linear ranges and quantification limits for both targeted proteomics and similar assays is presented. The software uses a variety of measures to assess the accuracy of the calibration, namely precision and trueness. Two different kinds of customizable graphs are created (calibration curves and response factor plots). The accuracy measures and the graphs offer an intuitive, detailed, and reliable opportunity to assess the quality of the model fit. Thus, CalibraCurve is deemed a highly useful and flexible tool to facilitate the development and control of reliable SRM/MRM-MS-based proteomics assays.

Elucidation of protein biomarkers for verification of selected biological warfare agents using tandem mass spectrometry

Some pathogens and toxins have the potential to be used as weapons of mass destruction and instigate population-based fear. Efforts to mitigate biothreat require development of efficient countermeasures which in turn relies on fast and accurate methods to detect the biological agents in a range of complex matrices including environmental and clinical samples. We report here an mass spectrometry (MS) based methodology, employing both targeted and shot-gun approaches for the verification of biological agents from the environmental samples. Our shot-gun methodology relied on tandem MS analysis of abundant peptides from the spiked samples, whereas, the targeted method was based on an extensive elucidation of marker proteins and unique peptides resulting in the generation of an inclusion list of masses reflecting relevant peptides for the unambiguous identification of nine bacterial species [listed as priority agents of bioterrorism by Centre for Disease Control and Prevention (CDC)] belonging to phylogenetically diverse genera. The marker peptides were elucidated by extensive literature mining, in silico analysis, and tandem MS (MS/MS) analysis of abundant proteins of the cultivated bacterial species in our laboratory. A combination of shot-gun MS/MS analysis and the targeted search using a panel of unique peptides is likely to provide unambiguous verification of biological agents at sub-species level, even with limited fractionation of crude protein extracts from environmental samples. The comprehensive list of peptides reflected in the inclusion list, makes a valuable resource for the multiplex analysis of select biothreat agents and further development of targeted MS/MS assays.

Morphological, transcriptomics and phytohormone analysis shed light on the development of a novel dwarf mutant of cabbage (Brassica oleracea)

Plant dwarf mutants generally exhibit delayed growth, delayed development, short internodes, and abnormal leaves and flowers and are ideal materials to explore the molecular mechanism of plant growth and development. In the current study, we first discovered a spontaneous cabbage (Brassica oleracea) dwarf mutant 99-198dw, which exhibits a dwarf stature, wrinkled leaves, non-heading, and substantially reduced self-fertility compared with the wild-type 99-198; however, the underlying molecular mechanism of its dwarfism is unknown. Here, we performed comparative phenotype, transcriptome and phytohormone analyses between 99-198 and 99-198dw. Cytological analysis showed that an increase in cell size, a reduction in cell layers, chloroplast degradation and a reduction in mitochondria were observed in 99-198dw. RNA-Seq showed that a total of 3801 differentially expressed genes (DEGs) were identified, including 2203 upregulated and 1598 downregulated genes in the dwarf mutant. Key genes in stress-resistant pathways were mostly upregulated, including salicylic acid (SA), jasmonic acid (JA), abscisic acid (ABA), ethylene (ET), etc., while the DEGs reported to be related to plant height, such as those involved in the gibberellin (GA), brassinolide (BR), indole-3-acetic acid (IAA), and strigolactone (SL) pathways were mostly downregulated. In addition, the DEGs in the cell division pathway were all downregulated, which is consistent with the cytokinesis defects detected by cytological analysis. The changes in the GA4, JA, ET, SA and ABA contents measured by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) absolute quantification were consistent with the transcriptome analysis. Further hormone treatment tests showed that the exogenous application of GA, BR, 6BA, paclobutrazol (PC), etc. did not rescue the phenotype, implying that the change in phytohormones is due to but not the cause of the dwarf trait. It was speculated that mutation of certain DEG related to cell division or participating in signalling pathway of phytohormones like GA, BR, IAA, and SL were the cause of dwarf. These results are informative for the elucidation of the underlying regulatory network in 99-198dw and enrich our understanding of plant dwarf traits at the molecular level.

Precision Profiling of the Cardiovascular Post-Translationally Modified Proteome: Where There Is a Will, There Is a Way

There is an exponential increase in biological complexity as initial gene transcripts are spliced, translated into amino acid sequence, and post-translationally modified. Each protein can exist as multiple chemical or sequence-specific proteoforms, and each has the potential to be a critical mediator of a physiological or pathophysiological signaling cascade. Here, we provide an overview of how different proteoforms come about in biological systems and how they are most commonly measured using mass spectrometry-based proteomics and bioinformatics. Our goal is to present this information at a level accessible to every scientist interested in mass spectrometry and its application to proteome profiling. We will specifically discuss recent data linking various protein post-translational modifications to cardiovascular disease and conclude with a discussion for enablement and democratization of proteomics across the cardiovascular and scientific community. The aim is to inform and inspire the readership to explore a larger breadth of proteoform, particularity post-translational modifications, related to their particular areas of expertise in cardiovascular physiology.

Automation of mass spectrometric detection of analytes and related workflows: A review

The developments in mass spectrometry (MS) in the past few decades reveal the power and versatility of this technology. MS methods are utilized in routine analyses as well as research activities involving a broad range of analytes (elements and molecules) and countless matrices. However, manual MS analysis is gradually becoming a thing of the past. In this article, the available MS automation strategies are critically evaluated. Automation of analytical workflows culminating with MS detection encompasses involvement of automated operations in any of the steps related to sample handling/treatment before MS detection, sample introduction, MS data acquisition, and MS data processing. Automated MS workflows help to overcome the intrinsic limitations of MS methodology regarding reproducibility, throughput, and the expertise required to operate MS instruments. Such workflows often comprise automated off-line and on-line steps such as sampling, extraction, derivatization, and separation. The most common instrumental tools include autosamplers, multi-axis robots, flow injection systems, and lab-on-a-chip. Prototyping customized automated MS systems is a way to introduce non-standard automated features to MS workflows. The review highlights the enabling role of automated MS procedures in various sectors of academic research and industry. Examples include applications of automated MS workflows in bioscience, environmental studies, and exploration of the outer space.

Inferring Protein-Protein Interaction Networks From Mass Spectrometry-Based Proteomic Approaches: A Mini-Review

Studying protein-protein interaction networks provide key evidence for the underlying molecular mechanisms. Mass spectrometry-based proteomic approaches have been playing a pivotal role in deciphering these interaction networks, along with precise quantification for individual interactions. In this mini-review we discuss the available techniques and methods for qualitative and quantitative elucidation of protein-protein interaction networks. We then summarize the down-stream computational strategies for identification and quantification of interactions from those techniques. Finally, we highlight the challenges and limitations of current computational pipelines in eliminating false positive interactors, followed by a summary of the innovative algorithms to address these issues, along with the scope for future improvements.

Targeted Proteomics Comes to the Benchside and the Bedside: Is it Ready for Us?

While mass spectrometry (MS)-based quantification of small molecules has been successfully used for decades, targeted MS has only recently been used by the proteomics community to investigate clinical questions such as biomarker verification and validation. Targeted MS holds the promise of a paradigm shift in the quantitative determination of proteins. Nevertheless, targeted quantitative proteomics requires improvisation in making sample processing, instruments, and data analysis more accessible. In the backdrop of the genomic era reaching its zenith, certain questions arise: is the proteomic era about to come? If we are at the beginning of a new future for protein quantification, are we prepared to incorporate targeted proteomics at the benchside for basic research and at the bedside for the good of patients? Here, an overview of the knowledge required to perform targeted proteomics as well as its applications is provided. A special emphasis is placed on upcoming areas such as peptidomics, proteoform research, and mass spectrometry imaging, where the utilization of targeted proteomics is expected to bring forth new avenues. The limitations associated with the acceptance of this technique for mainstream usage are also highlighted. Also see the video abstract here https://youtu.be/mieB47B8gZw.

A Guide to Mass Spectrometry-Based Quantitative Proteomics

Proteomics has become an attractive science in the postgenomic era, given its capacity to identify up to thousands of molecules in a single, complex sample and quantify them in an absolute and/or relative manner. The use of these techniques enables understanding of cellular and molecular mechanisms of diseases and other biological conditions, as well as identification and screening of protein biomarkers. Here we provide a straightforward, up-to-date compilation and comparison of the main quantitation techniques used in comparative proteomics such as in vitro and in vivo stable isotope labeling and label-free techniques. Additionally, this chapter includes common methods for data acquisition in proteomics and some appropriate methods for data processing. This compilation can serve as a reference for scientists who are new to, or already familiar with, quantitative proteomics.

Maternal Apolipoprotein B100 Serum Levels are Diminished in Pregnancies with Intrauterine Growth Restriction and Differentiate from Controls

PURPOSE

Intrauterine growth restriction, a major cause of fetal morbidity and mortality, is defined as a condition in which the fetus does not reach its genetically given growth potential. Screening for intrauterine growth restriction biomarkers in the mother's blood would be of great help for optimal pregnancy management and timing of delivery as well as for identifying fetuses requiring further surveillance during their infancies.

EXPERIMENTAL DESIGN

A multiplexing serological assay based on liquid chromatography-multiple-reaction-monitoring mass spectrometry is applied for distinguishing serum samples of pregnant women.

RESULTS

Assessment of concentrations of apolipoproteins and of proteins that belong to the lipid transport system is performed with maternal serum samples, consuming only 10 μL of serum per multiplex assay from each patient. Of all investigated proteins the serum concentrations of apolipoprotein B100 shows the greatest power for discriminating intrauterine growth restriction from control samples, reaching areas under curves above 0.85 in receiver-operator-characteristics analyses.

CONCLUSIONS

These results indicate the potential of liquid chromatography-multiple-reaction-monitoring mass spectrometry to become of clinical importance in the future for intrauterine growth restriction risk assessment based on maternal apolipoprotein B100 serum levels.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Proteomics in the Diagnosis of Inborn Encephalopathies of Unknown Origin: A Myth or Reality

Synaptopathy underlies a great variety of neurological or neurodevelopmental disorders, including neurodegenerative diseases and the highly complex neuropsychiatric syndromes. Standard diagnostic assays in the majority of synaptopathies are insufficient to make an appropriate and fast diagnosis, which has spurred a search for more accurate diagnostic methods using recent technological advances. As synaptopathy phenotypes strictly depend on genetics and environmental factors, the best way to approach these diseases is the investigation of entire sets of protein characteristics. Thus, proteomics has emerged as a mainstay in the studies on synaptopathies, with mass spectrometry as a technology of choice. This review is an update on the proteomic methods and achievements in the understanding, diagnostics, and novel biomarkers of synaptopathies. The article also provides a critical point of view and future perspectives on the application of neuroproteomics in clinical practice.

Challenges and perspectives of metaproteomic data analysis

In nature microorganisms live in complex microbial communities. Comprehensive taxonomic and functional knowledge about microbial communities supports medical and technical application such as fecal diagnostics as well as operation of biogas plants or waste water treatment plants. Furthermore, microbial communities are crucial for the global carbon and nitrogen cycle in soil and in the ocean. Among the methods available for investigation of microbial communities, metaproteomics can approximate the activity of microorganisms by investigating the protein content of a sample. Although metaproteomics is a very powerful method, issues within the bioinformatic evaluation impede its success. In particular, construction of databases for protein identification, grouping of redundant proteins as well as taxonomic and functional annotation pose big challenges. Furthermore, growing amounts of data within a metaproteomics study require dedicated algorithms and software. This review summarizes recent metaproteomics software and addresses the introduced issues in detail.

Prediction of Hopeless Peptides Unlikely to be Selected for Targeted Proteome Analysis

In targeted proteomics using liquid chromatography-tandem triple quadrupole mass spectrometry (LC/MS/MS) in the selected reaction monitoring (SRM) mode, selecting the best observable or visible peptides is a key step in the development of SRM assay methods of target proteins. A direct comparison of signal intensities among all candidate peptides by brute-force LC/MS/MS analysis is a concrete approach for peptide selection. However, the analysis requires an SRM method with hundreds of transitions. This study reports on the development of a method for predicting and identifying hopeless peptides to reduce the number of candidate peptides needed for brute-force experiments. Hopeless peptides are proteotypic peptides that are unlikely to be selected for targets in SRM analysis owing to their poor ionization characteristics. Targeted proteomics data from Escherichia coli demonstrated that the relative ionization efficiency between two peptides could be predicted from sequences of two peptides, when a multivariate regression model is used. Validation of the method showed that >20% of the candidate peptides could be successfully eliminated as hopeless peptides with a false positive rate of less than 2%.

Host Cell Protein Profiling by Targeted and Untargeted Analysis of Data Independent Acquisition Mass Spectrometry Data with Parallel Reaction Monitoring Verification

Host cell proteins (HCPs) are process-related impurities of biopharmaceuticals that remain at trace levels despite multiple stages of downstream purification. Currently, there is interest in implementing LC-MS in biopharmaceutical HCP profiling alongside conventional ELISA, because individual species can be identified and quantitated. Conventional data dependent LC-MS is hampered by the low concentration of HCP-derived peptides, which are 5-6 orders of magnitude less abundant than the biopharmaceutical-derived peptides. In this paper, we present a novel data independent acquisition (DIA)-MS workflow to identify HCP peptides using automatically combined targeted and untargeted data processing, followed by verification and quantitation using parallel reaction monitoring (PRM). Untargeted data processing with DIA-Umpire provided a means of identifying HCPs not represented in the assay library used for targeted, peptide-centric, data analysis. An IgG1 monoclonal antibody (mAb) purified by Protein A column elution, cation exchange chromatography, and ultrafiltration was analyzed using the workflow with 1D-LC. Five protein standards added at 0.5 to 100 ppm concentrations were detected in the background of the purified mAb, demonstrating sensitivity to low ppm levels. A calibration curve was constructed on the basis of the summed peak areas of the three highest intensity fragment ions from the highest intensity peptide of each protein standard. Sixteen HCPs were identified and quantitated on the basis of the calibration curve over the range of low ppm to over 100 ppm in the purified mAb sample. The developed approach achieves rapid HCP profiling using 1D-LC and specific identification exploiting the high mass accuracy and resolution of the mass spectrometer.

Optimization by infusion of multiple reaction monitoring transitions for sensitive quantification of peptides by liquid chromatography/mass spectrometry

RATIONALE

In peptide quantification by liquid chromatography/mass spectrometry (LC/MS), the optimization of multiple reaction monitoring (MRM) parameters is essential for sensitive detection. We have compared different approaches to build MRM assays, based either on flow injection analysis (FIA) of isotopically labelled peptides, or on the knowledge and the prediction of the best settings for MRM transitions and collision energies (CE). In this context, we introduce MRMOptimizer, an open-source software tool that processes spectra and assists the user in selecting transitions in the FIA workflow.

METHODS

MS/MS spectral libraries with CE voltages from 10 to 70 V are automatically acquired in FIA mode for isotopically labelled peptides. Then MRMOptimizer determines the optimal MRM settings for each peptide. To assess the quantitative performance of our approach, 155 peptides, representing 84 proteins, were analysed by LC/MRM-MS and the peak areas were compared between: (A) the MRMOptimizer-based workflow, (B1) the SRMAtlas transitions set used 'as-is'; (B2) the same SRMAtlas set with CE parameters optimized by Skyline.

RESULTS

51% of the three most intense transitions per peptide were shown to be common to both A and B1/B2 methods, and displayed similar sensitivity and peak area distributions. The peak areas obtained with MRMOptimizer for transitions sharing either the precursor ion charge state or the fragment ions with the SRMAtlas set at unique transitions were increased 1.8- to 2.3-fold. The gain in sensitivity using MRMOptimizer for transitions with different precursor ion charge state and fragment ions (8% of the total), reaches a ~ 11-fold increase.

CONCLUSIONS

Isotopically labelled peptides can be used to optimize MRM transitions more efficiently in FIA than by searching databases. The MRMOptimizer software is MS independent and enables the post-acquisition selection of MRM parameters. Coefficients of variation for optimal CE values are lower than those obtained with the SRMAtlas approach (B2) and one additional peptide was detected. Copyright © 2017 John Wiley & Sons, Ltd.

Current trends in quantitative proteomics - an update

Proteins can provide insights into biological processes at the functional level, so they are very promising biomarker candidates. The quantification of proteins in biological samples has been routinely used for the diagnosis of diseases and monitoring the treatment. Although large-scale protein quantification in complex samples is still a challenging task, a great amount of effort has been made to advance the technologies that enable quantitative proteomics. Seven years ago, in 2009, we wrote an article about the current trends in quantitative proteomics. In writing this current paper, we realized that, today, we have an even wider selection of potential tools for quantitative proteomics. These tools include new derivatization reagents, novel sampling formats, new types of analyzers and scanning techniques, and recently developed software to assist in assay development and data analysis. In this review article, we will discuss these innovative methods, and their current and potential applications in proteomics. Copyright © 2017 John Wiley & Sons, Ltd.

Designing Successful Proteomics Experiments

Because proteomics experiments are so complex they can readily fail, and do so without clear cause. Using standard experimental design techniques and incorporating quality control can greatly increase the chances of success. This chapter introduces the relevant concepts and provides examples specific to proteomic workflows. Applying these notions to design successful proteomics experiments is straightforward. It can help identify failure causes and greatly increase the likelihood of inter-laboratory reproducibility.

Targeted Analysis of Phosphotyrosine Signaling by Multiple Reaction Monitoring Mass Spectrometry

Phosphoproteomics is an important tool for the unbiased investigation of signaling network activation and has particular application to unraveling aberrant signaling driving cancer progression. However, validating the behavior of specific phosphosites across multiple experimental conditions remains challenging, due to limitations inherent in discovery-based proteomic workflows and the limited availability of high-quality antibodies required for alternative, immunoaffinity-based methods. Targeted phosphoproteomics enables specific phosphosites to be quantified reproducibly across multiple experimental conditions. Importantly, targeted phosphoproteomic assays can be designed rapidly on the basis of data acquired in discovery proteomic experiments and circumvent the requirement of immunoaffinity techniques for reliable antibodies raised to specific, potentially poorly immunogenic phosphopeptides. In the following protocol, we present a method for the relative quantification of phosphosites across multiple experimental conditions and/or technical and biological replicates.

Quantification of short chain amines in aqueous matrices using liquid chromatography electrospray ionization tandem mass spectrometry

A new liquid chromatography-electrospray ionization-tandem Mass Spectrometry (LC-ESI-MS/MS) method was developed for the determination of more than 20 C₁-C₆ alkyl and alkanolamines in aqueous matrices. The method employs Hydrophilic Interaction Liquid Chromatography Multiple Reaction Monitoring (HILIC-MRM) with a ZIC-pHILIC column and four stable isotope labeled amines as internal standards for signal normalization and quantification of the amines. The method was validated using a refinery process water sample that was obtained from a cooling cycle of crude oil distillation. The averaged within run precision, between run precision and accuracy were generally within 2-10%, 1-9% and 80-120%, respectively, depending on the analyte and concentration level. Selected aqueous process samples were analyzed with the method.

Compartmentalized Metabolic Engineering for Artemisinin Biosynthesis and Effective Malaria Treatment by Oral Delivery of Plant Cells

Artemisinin is highly effective against drug-resistant malarial parasites, which affects nearly half of the global population and kills >500 000 people each year. The primary cost of artemisinin is the very expensive process used to extract and purify the drug from Artemisia annua. Elimination of this apparently unnecessary step will make this potent antimalarial drug affordable to the global population living in endemic regions. Here we reported the oral delivery of a non-protein drug artemisinin biosynthesized (∼0.8 mg/g dry weight) at clinically meaningful levels in tobacco by engineering two metabolic pathways targeted to three different cellular compartments (chloroplast, nucleus, and mitochondria). The doubly transgenic lines showed a three-fold enhancement of isopentenyl pyrophosphate, and targeting AACPR, DBR2, and CYP71AV1 to chloroplasts resulted in higher expression and an efficient photo-oxidation of dihydroartemisinic acid to artemisinin. Partially purified extracts from the leaves of transgenic tobacco plants inhibited in vitro growth progression of Plasmodium falciparum-infected red blood cells. Oral feeding of whole intact plant cells bioencapsulating the artemisinin reduced the parasitemia levels in challenged mice in comparison with commercial drug. Such novel synergistic approaches should facilitate low-cost production and delivery of artemisinin and other drugs through metabolic engineering of edible plants.

Fluid and ion transfer across the blood-brain and blood-cerebrospinal fluid barriers; a comparative account of mechanisms and roles

The two major interfaces separating brain and blood have different primary roles. The choroid plexuses secrete cerebrospinal fluid into the ventricles, accounting for most net fluid entry to the brain. Aquaporin, AQP1, allows water transfer across the apical surface of the choroid epithelium; another protein, perhaps GLUT1, is important on the basolateral surface. Fluid secretion is driven by apical Na+-pumps. K+ secretion occurs via net paracellular influx through relatively leaky tight junctions partially offset by transcellular efflux. The blood-brain barrier lining brain microvasculature, allows passage of O2, CO2, and glucose as required for brain cell metabolism. Because of high resistance tight junctions between microvascular endothelial cells transport of most polar solutes is greatly restricted. Because solute permeability is low, hydrostatic pressure differences cannot account for net fluid movement; however, water permeability is sufficient for fluid secretion with water following net solute transport. The endothelial cells have ion transporters that, if appropriately arranged, could support fluid secretion. Evidence favours a rate smaller than, but not much smaller than, that of the choroid plexuses. At the blood-brain barrier Na+ tracer influx into the brain substantially exceeds any possible net flux. The tracer flux may occur primarily by a paracellular route. The blood-brain barrier is the most important interface for maintaining interstitial fluid (ISF) K+ concentration within tight limits. This is most likely because Na+-pumps vary the rate at which K+ is transported out of ISF in response to small changes in K+ concentration. There is also evidence for functional regulation of K+ transporters with chronic changes in plasma concentration. The blood-brain barrier is also important in regulating HCO3- and pH in ISF: the principles of this regulation are reviewed. Whether the rate of blood-brain barrier HCO3- transport is slow or fast is discussed critically: a slow transport rate comparable to those of other ions is favoured. In metabolic acidosis and alkalosis variations in HCO3- concentration and pH are much smaller in ISF than in plasma whereas in respiratory acidosis variations in pHISF and pHplasma are similar. The key similarities and differences of the two interfaces are summarized.

Perturbational Profiling of Metabolites in Patient Fibroblasts Implicates α-Aminoadipate as a Potential Biomarker for Bipolar Disorder

Many studies suggest the presence of aberrations in cellular metabolism in bipolar disorder. We studied the metabolome in bipolar disorder to gain insight into cellular pathways that may be dysregulated in bipolar disorder and to discover evidence of novel biomarkers. We measured polar and nonpolar metabolites in fibroblasts from subjects with bipolar I disorder and matched healthy control subjects, under normal conditions and with two physiologic perturbations: low-glucose media and exposure to the stress-mediating hormone dexamethasone. Metabolites that were significantly different between bipolar and control subjects showed distinct separation by principal components analysis methods. The most statistically significant findings were observed in the perturbation experiments. The metabolite with the lowest p value in both the low-glucose and dexamethasone experiments was α-aminoadipate, whose intracellular level was consistently lower in bipolar subjects. Our study implicates α-aminoadipate as a possible biomarker in bipolar disorder that manifests under cellular stress. This is an intriguing finding given the known role of α-aminoadipate in the modulation of kynurenic acid in the brain, especially as abnormal kynurenic acid levels have been implicated in bipolar disorder.

Bacterial Electron Transfer Chains Primed by Proteomics

Electron transport phosphorylation is the central mechanism for most prokaryotic species to harvest energy released in the respiration of their substrates as ATP. Microorganisms have evolved incredible variations on this principle, most of these we perhaps do not know, considering that only a fraction of the microbial richness is known. Besides these variations, microbial species may show substantial versatility in using respiratory systems. In connection herewith, regulatory mechanisms control the expression of these respiratory enzyme systems and their assembly at the translational and posttranslational levels, to optimally accommodate changes in the supply of their energy substrates. Here, we present an overview of methods and techniques from the field of proteomics to explore bacterial electron transfer chains and their regulation at levels ranging from the whole organism down to the Ångstrom scales of protein structures. From the survey of the literature on this subject, it is concluded that proteomics, indeed, has substantially contributed to our comprehending of bacterial respiratory mechanisms, often in elegant combinations with genetic and biochemical approaches. However, we also note that advanced proteomics offers a wealth of opportunities, which have not been exploited at all, or at best underexploited in hypothesis-driving and hypothesis-driven research on bacterial bioenergetics. Examples obtained from the related area of mitochondrial oxidative phosphorylation research, where the application of advanced proteomics is more common, may illustrate these opportunities.

Urinary proteomics and metabolomics studies to monitor bladder health and urological diseases

Background

Assays of molecular biomarkers in urine are non-invasive compared to other body fluids and can be easily repeated. Based on the hypothesis that the secreted markers from the diseased organs may locally release into the body fluid in the vicinity of the injury, urine-based assays have been considered beneficial to monitoring bladder health and urological diseases. The urine proteome is much less complex than the serum and tissues, but nevertheless can contain biomarkers for diagnosis and prognosis of diseases. The urine metabolome has a much higher number and concentration of low-molecular metabolites than the serum or tissues, with a far lower lipid concentration, yet informs directly about dietary and microbial metabolism.

Discussion

We here discuss the use of mass spectrometry-based proteomics and metabolomics for urine biomarker assays, specifically with respect to the underlying mechanisms that trigger the pathological condition.

Conclusion

Molecular biomarker profiles, based on proteomics and metabolomics studies, reliably distinguish patients from healthy controls, stratify sub-populations with respect to treatment options, and predict therapeutic response of patients with urological disease.

Mass Spectrometry-Based Protein Quantification

Quantification of individual proteins and even entire proteomes is an important theme in proteomics research. Quantitative proteomics is an approach to obtain quantitative information about proteins in a sample. Compared to qualitative or semi-quantitative proteomics, this approach can provide more insight into the effects of a specific stimulus, such as a change in the expression level of a protein and its posttranslational modifications, or to a panel of proposed biomarkers in a given disease state. Proteomics methodologies, along with a variety of bioinformatics approaches, are a major tool in quantitative proteomics. As the theory and technological aspects underlying the proteomics methodologies will be extensively described in Chap. 20 , and protein identification as a prerequisite of quantification has been discussed in Chap. 17 , we will focus on the quantitative proteomics bioinformatics algorithms and software tools in this chapter. Our goal is to provide researchers and newcomers a rational framework to select suitable bioinformatics tools for data analysis, interpretation, and integration in protein quantification. Before doing so, a brief overview of quantitative proteomics is provided.

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.