Mass spectrometry. From genomics to proteomics

Spectroscopic methods for COVID-19 detection and early diagnosis

The coronavirus pandemic is a worldwide hazard that poses a threat to millions of individuals throughout the world. This pandemic is caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which was initially identified in Wuhan, China's Hubei provincial capital, and has since spread throughout the world. According to the World Health Organization's Weekly Epidemiological Update, there were more than 250 million documented cases of coronavirus infections globally, with five million fatalities. Early detection of coronavirus does not only reduce the spread of the virus, but it also increases the chance of curing the infection. Spectroscopic techniques have been widely used in the early detection and diagnosis of COVID-19 using Raman, Infrared, mass spectrometry and fluorescence spectroscopy. In this review, the reported spectroscopic methods for COVID-19 detection were discussed with emphasis on the practical aspects, limitations and applications.

OUP accepted manuscript

Background

COVID-19 is a highly contagious respiratory disease that can be transmitted through human exhaled breath. It has caused immense loss and has challenged the healthcare sector. It has affected the economy of countries and thereby affected numerous sectors. Analysis of human breath samples is an attractive strategy for rapid diagnosis of COVID-19 by monitoring breath biomarkers.

Content

Breath collection is a noninvasive process. Various technologies are employed for detection of breath biomarkers like mass spectrometry, biosensors, artificial learning, and machine learning. These tools have low turnaround time, robustness, and provide onsite results. Also, MS-based approaches are promising tools with high speed, specificity, sensitivity, reproducibility, and broader coverage, as well as its coupling with various chromatographic separation techniques providing better clinical and biochemical understanding of COVID-19 using breath samples.

Summary

Herein, we have tried to review the MS-based approaches as well as other techniques used for the analysis of breath samples for COVID-19 diagnosis. We have also highlighted the different breath analyzers being developed for COVID-19 detection.

Biopharmaceutical quality control with mass spectrometry

Mass spectrometry (MS) is a powerful technique for protein identification, quantification and characterization that is widely applied in biochemical studies, and which can provide data on the quantity, structural integrity and post-translational modifications of proteins. It is therefore a versatile and widely used analytic tool for quality control of biopharmaceuticals, especially in quantifying host-cell protein impurities, identifying post-translation modifications and structural characterization of biopharmaceutical proteins. Here, we summarize recent advances in MS-based analyses of these key quality attributes of the biopharmaceutical development and manufacturing processes.

Mass Spectrometry-Based Human Breath Analysis: Towards COVID-19 Diagnosis and Research

COVID-19 is a highly contagious respiratory disease that can be infected through human exhaled breath. Human breath analysis is an attractive strategy for rapid diagnosis of COVID-19 in a non-invasive way by monitoring breath biomarkers. Mass spectrometry (MS)-based approaches offer a promising analytical platform for human breath analysis due to their high speed, specificity, sensitivity, reproducibility, and broad coverage, as well as its versatile coupling methods with different chromatographic separation, and thus can lead to a better understanding of the clinical and biochemical processes of COVID-19. Herein, we try to review the developments and applications of MS-based approaches for multidimensional analysis of COVID-19 breath samples, including metabolites, proteins, microorganisms, and elements. New features of breath sampling and analysis are highlighted. Prospects and challenges on MS-based breath analysis related to COVID-19 diagnosis and study are discussed.

Recent advances in Schistosoma mekongi ecology, transcriptomics and proteomics of relevance to snail control

Mekong schistosomiasis caused by Schistosoma mekongi is a public health problem that occurs along the border between southern Laos and northern Cambodia. Given its restricted distribution and low prevalence, eventual eradication via an effective control program can be expected to be successful. To achieve this goal detailed knowledge of its basic biology, molecular biology, biochemistry, and pathology is urgently required. In this regard, recent studies on transcriptome analysis of adult male and female S. mekongi worms, and proteome analysis of developmental stages have been reported and are discussed here. The biology, habitat, and distribution of the snail intermediate host Neotricula aperta, which are factors in disease transmission, are discussed in this review. These have initiated renewed interest in S. mekongi research and contributed promising data that will be utilized in the generation of effective control and prevention strategies.

Proteome of fraction from Tityus serrulatus venom reveals new enzymes and toxins

Background

Tityus serrulatus venom (Ts venom) is a complex mixture of several compounds with biotechnological and therapeutical potentials, which highlights the importance of the identification and characterization of these components. Although a considerable number of studies have been dedicated to the characterization of this complex cocktail, there is still a limitation of knowledge concerning its venom composition. Most of Ts venom studies aim to isolate and characterize their neurotoxins, which are small, basic proteins and are eluted with high buffer concentrations on cation exchange chromatography. The first and largest fraction from carboxymethyl cellulose-52 (CMC-52) chromatography of Ts venom, named fraction I (Fr I), is a mixture of proteins of high and low molecular masses, which do not interact with the cation exchange resin, being therefore a probable source of components still unknown of this venom. Thus, the present study aimed to perform the proteome study of Fraction I from Ts venom, by high resolution mass spectrometry, and its biochemical characterization, by the determination of several enzymatic activities.

Methods

Fraction I was obtained by a cation exchange chromatography using 50 mg of crude venom. This fraction was subjected to a biochemical characterization, including determination of L-amino acid oxidase, phospholipase, hyaluronidase, proteases activities and inhibition of angiotensin converting enzyme (ACE) activity. Fraction I was submitted to reduction, alkylation and digestion processes, and the tryptic digested peptides obtained were analyzed in a Q-Exactive Orbitrap mass spectrometer. Data analysis was performed by PEAKS 8.5 software against NCBI database.

Results

Fraction I exhibits proteolytic activity and it was able to inhibit ACE activity. Its proteome analysis identified 8 different classes of venom components, among them: neurotoxins (48%), metalloproteinases (21%), hypotensive peptides (11%), cysteine-rich venom protein (9%), antimicrobial peptides (AMP), phospholipases and other enzymes (chymotrypsin and lysozymes) (3%) and phosphodiesterases (2%).

Conclusions

The combination of a proteomic and biochemical characterization strategies leads us to identify new components in the T. serrulatus scorpion venom. The proteome of venom´s fraction can provide valuable direction in the obtainment of components in their native forms in order to perform a preliminary characterization and, consequently, to promote advances in biological discoveries in toxinology.

Development and application of a recombination-based library versus library high- throughput yeast two-hybrid (RLL-Y2H) screening system

Protein-protein interaction (PPI) network maintains proper function of all organisms. Simple high-throughput technologies are desperately needed to delineate the landscape of PPI networks. While recent state-of-the-art yeast two-hybrid (Y2H) systems improved screening efficiency, either individual colony isolation, library preparation arrays, gene barcoding or massive sequencing are still required. Here, we developed a recombination-based 'library vs library' Y2H system (RLL-Y2H), by which multi-library screening can be accomplished in a single pool without any individual treatment. This system is based on the phiC31 integrase-mediated integration between bait and prey plasmids. The integrated fragments were digested by MmeI and subjected to deep sequencing to decode the interaction matrix. We applied this system to decipher the trans-kingdom interactome between Mycobacterium tuberculosis and host cells and further identified Rv2427c interfering with the phagosome-lysosome fusion. This concept can also be applied to other systems to screen protein-RNA and protein-DNA interactions and delineate signaling landscape in cells.

Multiplexed Isobaric Tagging Protocols for Quantitative Mass Spectrometry Approaches to Auditory Research

Modern biologists have at their disposal a large array of techniques used to assess the existence and relative or absolute quantity of any molecule of interest in a sample. However, implementing most of these procedures can be a daunting task for the first time, even in a lab with experienced researchers. Just choosing a protocol to follow can take weeks while all of the nuances are examined and it is determined whether a protocol will (a) give the desired results, (b) result in interpretable and unbiased data, and (c) be amenable to the sample of interest. We detail here a robust procedure for labeling proteins in a complex lysate for the ultimate differential quantification of protein abundance following experimental manipulations. Following a successful outcome of the labeling procedure, the sample is submitted for mass spectrometric analysis, resulting in peptide quantification and protein identification. While we will concentrate on cells in culture, we will point out procedures that can be used for labeling lysates generated from tissues, along with any minor modifications required for such samples. We will also outline, but not fully document, other strategies used in our lab to label proteins prior to mass spectrometric analysis, and describe under which conditions each procedure may be desirable. What is not covered in this chapter is anything but the most brief introduction to mass spectrometry (instrumentation, theory, etc.), nor do we attempt to cover much in the way of software used for post hoc analysis. These two topics are dependent upon one's resources, and where applicable, one's collaborators. We strongly encourage the reader to seek out expert advice on topics not covered here.

Toward Automated Interpretation of LC-MS Data for Quality Assurance of a Screening Collection

The AstraZeneca Compound Management group uses high-performance liquid chromatography-mass spectrometry for structure elucidation and purity determination of the AstraZeneca compound collection. These activities are conducted in a high-throughput environment where the rate-limiting step is the review and interpretation of analytical results, which is time-consuming and experience dependent. Despite the development of a semiautomated review system, manual interpretation of results remains a bottleneck. Data-mining techniques were applied to archived data to further automate the review process. Various classification models were evaluated using WEKA and Pipeline Pilot (Pipeline Pilot version 8.5.0.200, BIOVIA, San Diego, CA). Results were assessed using criteria including precision, recall, and receiver operating characteristic area. Each model was evaluated as a cost-insensitive classifier and again using MetaCost to apply cost sensitivity. Pruning and variable importance were also investigated. A 10-tree random forest generated with Pipeline Pilot reduced the number of analyses requiring manual review to 36.4% using a threshold of 90% confidence in predictions. This represents a 45% reduction in manual reviews compared with the previous system, delivering an annual savings of $45,000 or an increase in capacity from 25,000 analyses per month up to 45,000 with the same resource levels.

Predicting protein interface residues using easily accessible on-line resources

It has been more than a decade since the completion of the Human Genome Project that provided us with a complete list of human proteins. The next obvious task is to figure out how various parts interact with each other. On that account, we review 10 methods for protein interface prediction, which are freely available as web servers. In addition, we comparatively evaluate their performance on a common data set comprising different quality target structures. We find that using experimental structures and high-quality homology models, structure-based methods outperform those using only protein sequences, with global template-based approaches providing the best performance. For moderate-quality models, sequence-based methods often perform better than those structure-based techniques that rely on fine atomic details. We note that post-processing protocols implemented in several methods quantitatively improve the results only for experimental structures, suggesting that these procedures should be tuned up for computer-generated models. Finally, we anticipate that advanced meta-prediction protocols are likely to enhance interface residue prediction. Notwithstanding further improvements, easily accessible web servers already provide the scientific community with convenient resources for the identification of protein-protein interaction sites.

Understanding the rules of the road: proteomic approaches to interrogate the blood brain barrier

The blood brain barrier (BBB) is often regarded as a passive barrier that protects brain parenchyma from toxic substances, circulating leukocytes, while allowing the passage of selected molecules. Recently, a combination of molecular profiling techniques have characterized the constituents of the BBB based on in vitro models using isolated endothelial cells and ex vivo models analyzing isolated blood vessels. Characterization of gene expression profiles that are specific to the endothelium of brain blood vessels, and the identification of proteins, cells and multi-cellular structure that comprise the BBB have led to a emerging consensus that the BBB is not, in and of itself, a simple barrier of specialized endothelial cells. Instead, regulation of transcytosis, permeability, and drug translocation into the central nervous system is now viewed as a collection of neurovascular units (NVUs) that, together, give the BBB its unique biological properties. We will review recent technology advancing the understanding of the molecular basis of the BBB with a focus on proteomic approaches.

Real-time cellular exometabolome analysis with a microfluidic-mass spectrometry platform

To address the challenges of tracking the multitude of signaling molecules and metabolites that is the basis of biological complexity, we describe a strategy to expand the analytical techniques for dynamic systems biology. Using microfluidics, online desalting, and mass spectrometry technologies, we constructed and validated a platform well suited for sampling the cellular microenvironment with high temporal resolution. Our platform achieves success in: automated cellular stimulation and microenvironment control; reduced non-specific adsorption to polydimethylsiloxane due to surface passivation; real-time online sample collection; near real-time sample preparation for salt removal; and real-time online mass spectrometry. When compared against the benchmark of "in-culture" experiments combined with ultraperformance liquid chromatography-electrospray ionization-ion mobility-mass spectrometry (UPLC-ESI-IM-MS), our platform alleviates the volume challenge issues caused by dilution of autocrine and paracrine signaling and dramatically reduces sample preparation and data collection time, while reducing undesirable external influence from various manual methods of manipulating cells and media (e.g., cell centrifugation). To validate this system biologically, we focused on cellular responses of Jurkat T cells to microenvironmental stimuli. Application of these stimuli, in conjunction with the cell's metabolic processes, results in changes in consumption of nutrients and secretion of biomolecules (collectively, the exometabolome), which enable communication with other cells or tissues and elimination of waste. Naïve and experienced T-cell metabolism of cocaine is used as an exemplary system to confirm the platform's capability, highlight its potential for metabolite discovery applications, and explore immunological memory of T-cell drug exposure. Our platform proved capable of detecting metabolomic variations between naïve and experienced Jurkat T cells and highlights the dynamics of the exometabolome over time. Upregulation of the cocaine metabolite, benzoylecgonine, was noted in experienced T cells, indicating potential cellular memory of cocaine exposure. These metabolomics distinctions were absent from the analogous, traditional "in-culture" UPLC-ESI-IM-MS experiment, further demonstrating this platform's capabilities.

Use of generic LC–MS/MS assays to characterize atypical PK profile of a biotherapeutic monoclonal antibody

Background: The fully human monoclonal antibody mAb123, which binds to and neutralizes chemokine motif ligand-21 (CCL21) displays a faster clearance in cynomolgus monkey compared with typical IgG kinetics. A direct and an immunoaffinity LC–MS/MS assays were developed to compare with the previously established ligand-binding assays (LBAs). Results: A strong correlation of LC–MS/MS pharmacokinetic data with LBA data confirmed the rapid drug disposition of mAb123 is an intrinsic property of the molecule, rather than interference of anti-mAb123 antibodies in the LBA. Conclusion: The data illustrate that in cases of unexpected results from LBA, application of orthogonal bioanalytical techniques such as LC–MS/MS can help in in interpretation of pharmacokinetic as determined by LBAs.

Proteomic study of the microdissected aortic media in human thoracic aortic aneurysms

Aortic aneurysm is a complex multifactorial disease, and its molecular mechanism is not understood. In thoracic aortic aneurysm (TAA), the expansion of the aortic wall is lead by extracellular matrix (ECM) degeneration in the medial layer, which leads to weakening of the aortic wall. This dilatation may end in rupture and-if untreated-death. The aortic media is composed of vascular smooth muscle cells (VSMCs) and proteins involved in aortic elasticity and distensibility. Delineating their functional and quantitative decrease is critical in elucidating the disease causing mechanisms as well as the development of new preventive therapies. Laser microdissection (LMD) is an advanced technology that enables the isolation of the desired portion of tissue or cells for proteomics analysis, while preserving their integrity. In our study, the aortic media layers of 36 TAA patients and 8 controls were dissected using LMD technology. The proteins isolated from these tissue samples were subjected to comparative proteomic analysis by nano-LC-MS/MS, which enabled the identification of 352 proteins in aortic media. Among these, 41 proteins were differentially expressed in the TAA group with respect to control group, and all were downregulated in the patients. Of these medial proteins, 25 are novel, and their association with TAA is reported for the first time in our study. Subsequent analysis of the data by ingenuity pathway analysis (IPA) shows that the majority of differentially expressed proteins were found to be cytoskeletal-associated proteins and components of the ECM which are critical in maintaining aortic integrity. Our results indicate that the protein expression profile in the aortic media from TAA patients differs significantly from controls. Further analysis of the mechanism points to markers of pathological ECM remodeling, which, in turn, affect VSMC cytosolic structure and architecture. In the future, the detailed investigation of the differentially expressed proteins may provide insight into the elucidation of the pathological processes underlying aneurysms.

Characterization of a novel Conus bandanus conopeptide belonging to the M-superfamily containing bromotryptophan

A novel conotoxin (conopeptide) was biochemically characterized from the crude venom of the molluscivorous marine snail, Conus bandanus (Hwass in Bruguière, 1792), collected in the south-central coast of Vietnam. The peptide was identified by screening bromotryptophan from chromatographic fractions of the crude venom. Tandem mass spectrometry techniques were used to detect and localize different post-translational modifications (PTMs) present in the BnIIID conopeptide. The sequence was confirmed by Edman’s degradation and mass spectrometry revealing that the purified BnIIID conopeptide had 15 amino acid residues, with six cysteines at positions 1, 2, 7, 11, 13, and 14, and three PTMs: bromotryptophan, γ-carboxy glutamate, and amidated aspartic acid, at positions “4”, “5”, and “15”, respectively. The BnIIID peptide was synthesized for comparison with the native peptide. Homology comparison with conopeptides having the III-cysteine framework (–CCx₁x₂x₃x₄Cx₁x₂x₃Cx₁CC–) revealed that BnIIID belongs to the M-1 family of conotoxins. This is the first report of a member of the M-superfamily containing bromotryptophan as PTM.

Use of proteomics to define targets of T-cell immunity

The mammalian immune system has evolved to display peptides derived from microbial antigens to immune effector cells. Liberated from the intact antigens through distinct proteolytic mechanisms, these peptides are subsequently transported to the cell surface while bound to chaperone-like receptors known as major histocompatibility complex molecules. These complexes are then scrutinized by T-cells that express receptors with specificity for specific major histocompatibility complex-peptide complexes. In normal uninfected cells, this process of antigen processing and presentation occurs continuously, with the resultant array of self-antigen-derived peptides displayed on the surface of these cells. Changes in this cellular peptide array alert the immune system to changes in the intracellular environment that may be associated with infection, oncogenesis or other abnormal cellular processes, resulting in a cascade of events that result in the elimination of the abnormal cell. Since peptides play such an essential role in informing the immune system of infection with viral or microbial pathogens and the transformation of cells in malignancy, the tools of proteomics, in particular mass spectrometry, are ideally suited to study these immune responses at a molecular level. Recent advances in studies of immune responses that have utilized mass spectrometry and associated technologies are reviewed. The authors gaze into the future and look at current challenges and where proteomics will impact in immunology over the next 5 years.

Peptides in body fluids and tissues as markers of disease

The general awareness of the importance of peptides in physiology and pathophysiology has increased strongly over the last few years. With worldwide progress in the analysis of whole genomes, the knowledge base in gene sequence and expression data useful for protein and peptide analysis has drastically increased. The medical need for relevant biomarkers is enormous. This is particularly true for the many types of cancer, but other diseases such as Type 2 diabetes also lack useful and adequate diagnostic markers with high specificity and sensitivity. Despite advances in imaging technologies for early detection of diseases, proteomic and peptidomic multiplex techniques have evolved in recent years. This review focuses on the application of peptidomics technologies to peptides in health and disease. Peptidomics technologies provide new opportunities for the detection of low-molecular-weight proteome biomarkers (peptides) by mass spectrometry. Improvements in peptidomics research are based on separation of peptides and/or proteins by their physicochemical properties in combination with mass spectrometric detection, identification and sophisticated bioinformatics tools for data analysis. Therefore, peptidomics technologies offer an opportunity to discover novel biomarkers for diagnosis and management of disease (e.g., prognosis, treatment decision and monitoring response to therapy).

Identification of osteoarthritis biomarkers by proteomic analysis of synovial fluid

OBJECTIVE

To use proteomic analysis to identify novel candidate biomarker proteins in synovial fluid for the differential diagnosis of osteoarthritis and rheumatoid arthritis.

METHODS

Synovial fluid samples were analysed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Data were used to generate an artificial neural network (ANN). The identification of one protein peak was confirmed via Western blotting.

RESULTS

Fluid samples were analysed from 36 patients with osteoarthritis and 24 with rheumatoid arthritis. In total, three protein peaks (mass-to-charge ratio [m/z] 3893, 10,576 and 14,175 Da) were identified as potential biomarkers for osteoarthritis. The ANN differentiated between osteoarthritis and rheumatoid arthritis with a sensitivity of 89.4% and a specificity of 91.2%. The protein peak at m/z 10 576 was identified as S100 calcium binding protein A12 (S100A12).

CONCLUSIONS

A combination of SELDI-TOF-MS and ANN identified osteoarthritis biomarkers. SELDI-TOF-MS may be a useful tool in the screening of synovial fluid for osteoarthritis diagnosis.

Proteomics in uveal melanoma

Uveal melanoma is the most common primary intraocular malignancy in adults, with an incidence of 5-7 per million per year. It is associated with the development of metastasis in about 50% of cases, and 40% of patients with uveal melanoma die of metastatic disease despite successful treatment of the primary tumour. The survival rates at 5, 10 and 15 years are 65%, 50% and 45% respectively. Unlike progress made in many other areas of cancer, uveal melanoma is still poorly understood and survival rates have remained similar over the past 25 years. Recently, advances made in molecular genetics have improved our understanding of this disease and stratification of patients into low risk and high risk for developing metastasis. However, only a limited number of studies have been performed using proteomic methods. This review will give an overview of various proteomic technologies currently employed in life sciences research, and discuss proteomic studies of uveal melanoma.

Calorimetric analysis of the plasma proteome: identification of type 1 diabetes patients with early renal function decline

BACKGROUND

Microalbuminuria (MA) has been questioned as a predictor of progressive renal dysfunction in patients with type 1 diabetes (T1D). Consequently, new clinical end points are needed that identify or predict patients that are at risk for early renal function decline (ERFD). The potential clinical utility of differential scanning calorimetry (DSC) analysis of blood plasma and other biofluids has recently been reported. This method provides an alternate physical basis with which to study disease-associated changes in the bulk plasma proteome.

METHODS

DSC analysis of blood plasma was applied to identify unique signatures of ERFD in subjects enrolled in the 1st Joslin Study of the Natural History of Microalbuminuria in Type 1 Diabetes, a prospective cohort study of T1D patients. Recent data suggests that differences in the plasma peptidome of these patients correlate with longitudinal measures of renal function. Differences in DSC profile (thermogram) features were evaluated between T1D MA individuals exhibiting ERFD (n=15) and matched control subjects (n=14).

RESULTS

The average control group thermogram resembled a previously defined healthy thermogram. Differences were evident between ERFD and control individuals. Heat capacity values of the main two transitions were found to be significant discriminators of patient status.

CONCLUSIONS

Results from this pilot study suggest the potential utility of DSC proteome analysis to prognostic indicators of renal disease in T1D.

GENERAL SIGNIFICANCE

DSC shows sensitivity to changes in the bulk plasma proteome that correlate with clinical status in T1D providing additional support for the utility of DSC profiling in clinical diagnostics.

Performance evaluation of a dual linear ion trap-Fourier transform ion cyclotron resonance mass spectrometer for proteomics research

A novel dual cell linear ion trap Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS) and its performance characteristics are reported. A linear ion trap-Fourier transform ion cyclotron resonance mass spectrometer has been modified to incorporate a LTQ-Velos mass spectrometer. This modified instrument features efficient ion accumulation and fast MS/MS acquisition capabilities of dual cell linear RF ion trap instruments coupled to the high mass accuracy, resolution, and dynamic range of a FT-ICR for improved proteomic coverage. The ion accumulation efficiency is demonstrated to be an order of magnitude greater than that observed with LTQ-FT Ultra instrumentation. The proteome coverage with yeast was shown to increase over the previous instrument generation by 50% (100% increase on the peptide level). In addition, many lower abundance level yeast proteins were only detected with this modified instrument. This novel configuration also enables beam type CID fragmentation using a dual cell RF ion trap mass spectrometer. This technique involves accelerating ions between traps while applying an elevated DC offset to one of the traps to accelerate ions and induce fragmentation. This instrument design may serve as a useful option for labs currently considering purchasing new instrumentation or upgrading existing instruments.

BIOLOGICAL SIGNIFICANCE

A novel hybrid mass spectrometer that allows increased MS/MS acquisition rates with high mass measurement accuracy and new ion fragmentation methods greatly improves the number of proteins, posttranslational modifications and protein-protein interactions that can be identified from cells.

Combination of Edman degradation of peptides with liquid chromatography/mass spectrometry workflow for peptide identification in bottom-up proteomics

RATIONALE

High-throughput methods of proteomics are essential for identification of proteins in a cell or tissue under certain conditions. Most of these methods require tandem mass spectrometry (MS/MS). A multidimensional approach including predictive chromatography and partial chemical degradation could be a valuable alternative and/or addition to MS/MS.

METHODS

In the proposed strategy peptides are identified in a three-dimensional (3D) search space consisting of retention time (RT), mass, and reduced mass after one-step partial Edman degradation. The strategy was evaluated in silico for two databases: baker's yeast and human proteins. Rates of unambiguous identifications were estimated for mass accuracies from 0.001 to 0.05 Da and RT prediction accuracies from 0.1 to 5 min. Rates of Edman reactions were measured for test peptides.

RESULTS

A 3D description of proteolytic peptides allowing unambiguous identification without employing MS/MS of up to 95% and 80% of tryptic peptides from the yeast and human proteomes, respectively, was considered. Further extension of the search space to a four-dimensional one by incorporating the second N-terminal amino acid residue as the fourth dimension was also considered and was shown to result in up to 90% of human peptides being identified unambiguously.

CONCLUSIONS

The proposed 3D search space can be a useful alternative to MS/MS-based peptide identification approach. Experimental implementations of the proposed method within the on-line liquid chromatography/mass spectrometry (LC/MS) and off-line matrix-assisted laser desorption/ionization (MALDI) workflows are in progress.

Protein and peptide biomarkers in organ transplantation

Organ transplantation is the optimal treatment choice for end-stage organ failure in pediatric patients. The ideal maintenance of a transplanted organ requires efficient monitoring tools and an effective individualized post-transplant treatment plan. Currently available post-transplant monitoring options are not ideal because of their invasiveness or their lack of sensitivity and specificity when providing an accurate assessment of transplant injury. Current research on proteins and peptides, including mass spectrometry-based proteomics, can identify novel surrogate protein and peptide biomarkers that can assist in monitoring the graft in order to correctly assess the status of the transplanted organ. In this article, we have critically reviewed current relevant literature to highlight the importance of protein and peptide biomarkers in the field of pediatric organ transplantation, the status of research findings in the field of protein and peptide biomarkers in different organ transplantation and factors that impact and inhibit the progression of protein biomarker discovery in the field of solid-organ transplantation in pediatrics.

Observation of ion coalescence in Orbitrap Fourier transform mass spectrometry

RATIONALE

Similar to other mass spectrometric technologies based on ion trapping in a spatially restricted area, the performance of Orbitrap Fourier transform mass spectrometry (FTMS) is affected by the interaction between the trapped ion clouds. One of the effects associated with Coulombic interaction inside the ion trap is the ion cloud coupling, known in ion cyclotron resonance (ICR) FTMS as coalescence, or a phase-locking phenomenon. Nevertheless, the direct observation of ion coalescence has not been reported for Orbitrap FTMS yet.

METHODS

We have performed experiments on ion coalescence with a pair of isobaric peptides in the state-of-the-art hybrid linear ion trap high-field compact Orbitrap Elite FT mass spectrometer using both standard and advanced signal processing modes.

RESULTS

For the instrument configuration employed in this work we found that ion coalescence occurs when two singly charged peptides with the mass difference of 22 mDa and molecular weight of about 1060 Da have the total abundance of at least 7.5*10(4) charges.

CONCLUSIONS

We experimentally demonstrate the existence of the ion coalescence phenomenon in Orbitrap FTMS for peptides for a wide range of total trapped ion population. Using the applicable modeling of the phase-locking threshold we estimate the effect of ion coalescence on the performance of Orbitrap FTMS.

Yeast expressed foldable quadrivalent Aβ15 elicited strong immune response against Aβ without Aβ-specific T cell response in wild C57BL/6 mice

Active and passive immunizations with Aβ and Aβ antibodies successfully reduced AD pathology and improved cognitive functions in an AD mouse model. However, human clinical trials of vaccination with synthetic Aβ(AN1792), were halted due to brain inflammation, presumably induced by T cell-mediated immune response. In this study, we used Picha pastoris to produce a recombinant peptide vaccine, r4 × Aβ15(recombinant 4 × Aβ15), four tandem repeats of Aβ(1-15) interlinked by spacers . Wild-type mice were injected subcutaneously with CFA/IFA as adjuvant. r4 × Aβ15 vaccine elicited high titer anti-Aβ antibodies which bound to Aβ plaque in brain tissue from Tg2576 mouse. The antibody isotype was mainly IgG(1), indicating anti-inflammatory Th2 type. There was no splenocyte proliferation against Aβ peptide, which indicates that the r4 × Aβ15 vaccine does not induce Aβ-specific T cellular immune response. Thus, r4 × Aβ15 vaccine may be a safe and efficient vaccine for AD.

Review of current and "omics" methods for assessing the toxicity (genotoxicity, teratogenicity and nephrotoxicity) of herbal medicines and mushrooms

ETHNOPHARMACOLOGICAL RELEVANCE

The increasing use of traditional herbal medicines around the world requires more scientific evidence for their putative harmlessness. To this end, a plethora of methods exist, more or less satisfying. In this post-genome era, recent reviews are however scarce, not only on the use of new "omics" methods (transcriptomics, proteomics, metabonomics) for genotoxicity, teratogenicity, and nephrotoxicity assessment, but also on conventional ones.

METHODS

The present work aims (i) to review conventional methods used to assess genotoxicity, teratogenicity and nephrotoxicity of medicinal plants and mushrooms; (ii) to report recent progress in the use of "omics" technologies in this field; (iii) to underline advantages and limitations of promising methods; and lastly (iv) to suggest ways whereby the genotoxicity, teratogenicity, and nephrotoxicity assessment of traditional herbal medicines could be more predictive.

RESULTS

Literature and safety reports show that structural alerts, in silico and classical in vitro and in vivo predictive methods are often used. The current trend to develop "omics" technologies to assess genotoxicity, teratogenicity and nephrotoxicity is promising but most often relies on methods that are still not standardized and validated.

CONCLUSION

Hence, it is critical that toxicologists in industry, regulatory agencies and academic institutions develop a consensus, based on rigorous methods, about the reliability and interpretation of endpoints. It will also be important to regulate the integration of conventional methods for toxicity assessments with new "omics" technologies.

Proteomics/diagnosis of chorioamnionitis and of relationships with the fetal exposome

Proteomics, a relatively young science, originally emerged as a complement to genomics research. By definition, the goal of proteomics is to provide a snapshot of all the proteins within an organism, tissue or biological sample at a given moment. Proteomics has the ability to single out one or more proteins (biomarkers) that change consistently in affected subjects as compared to those disease-free. From a proteomics perspective, chorioamnionitis poses both challenges and opportunities. Challenges relate to the dynamic course of the inflammatory process, and compartmentalization of the gestational sac in relation to the maternal compartment. An inability to evaluate the amniotic fluid non-invasively and repeatedly for meaningful changes in its proteome, and lack of a true gold standard for diagnosis of inflammation and/or infection, represent additional challenges. On the other hand, the unbiased and holistic nature of proteomics offers a real opportunity to improve the current diagnostic and prognostic algorithms for chorioamnionitis. Even at this current stage there are reasons to believe that proteomic biomarkers will improve the understanding of how chorioamnionitis programs or affects the fetus in utero, thus defining its exposome (sum of interactions between genetic make-up of the fetus and the intrauterine environment) of pregnancies affected by infection and/or inflammation. This review summarizes the results of proteomics studies that have aimed or reached these goals.

Periodicity of monoisotopic mass isomers and isobars in proteomics

We report trends in the theoretically derived number of compositionally distinct peptides (i.e., peptides made up of different amino acid residues) up to a nominal mass of 1000. A total of 21 amino acid residues commonly found in proteomics studies are included in this study, 19 natural, nonisomeric amino acid residues as well as oxidated methione and acetamidated cysteine. The number of possibilities is found to increase in an exponential fashion with increasing nominal mass, and the data show a periodic oscillation that starts at mass ~200 and continues throughout to 1000. Note that similar effects are reported in the companion article on fragment ions from electron capture/transfer dissociation (ECD/ETD) (Mao et al. Anal. Chem.2011, DOI: 10.1021/ac201619t). The spacing of this oscillation is ~15 mass units at lower masses and ~14 mass units at higher nominal masses. This correlates with the most common mass differences between the amino acid building blocks. In other words, some mass differences are more common than others, thus determining the periodicity in this data. From an analytical point of view, nominal masses with a larger number of compositionally distinct peptides include a substantial number of isomers, which cannot be separated based on mass. Consequently, even ultrahigh mass accuracy (i.e., 0.5 ppm) does not lead to a substantially enhanced rate of identification. Conversely, for adjacent nominal masses with a lower number of isomers, moderately accurate mass (i.e., 10 ppm) gives a higher degree of certainty in identification. These effects are limited to the mass range between 200 and 500 Da. At higher masses, the percentage of uniquely identified peptides drops off to close to zero, independent of nominal mass, due the inherently high number of isomers. While the exact number of isobars/isomers at each nominal mass depends on the amino acid building blocks that are considered, the periodicity in the data is found to be remarkably robust; for instance, inclusion of phosphorylated residues barely affects the pattern at lower masses (i.e., <500 Da).

Green systems biology - From single genomes, proteomes and metabolomes to ecosystems research and biotechnology

Plants have shaped our human life form from the outset. With the emerging recognition of world population feeding, global climate change and limited energy resources with fossil fuels, the relevance of plant biology and biotechnology is becoming dramatically important. One key issue is to improve plant productivity and abiotic/biotic stress resistance in agriculture due to restricted land area and increasing environmental pressures. Another aspect is the development of CO(2)-neutral plant resources for fiber/biomass and biofuels: a transition from first generation plants like sugar cane, maize and other important nutritional crops to second and third generation energy crops such as Miscanthus and trees for lignocellulose and algae for biomass and feed, hydrogen and lipid production. At the same time we have to conserve and protect natural diversity and species richness as a foundation of our life on earth. Here, biodiversity banks are discussed as a foundation of current and future plant breeding research. Consequently, it can be anticipated that plant biology and ecology will have more indispensable future roles in all socio-economic aspects of our life than ever before. We therefore need an in-depth understanding of the physiology of single plant species for practical applications as well as the translation of this knowledge into complex natural as well as anthropogenic ecosystems. Latest developments in biological and bioanalytical research will lead into a paradigm shift towards trying to understand organisms at a systems level and in their ecosystemic context: (i) shotgun and next-generation genome sequencing, gene reconstruction and annotation, (ii) genome-scale molecular analysis using OMICS technologies and (iii) computer-assisted analysis, modeling and interpretation of biological data. Systems biology combines these molecular data, genetic evolution, environmental cues and species interaction with the understanding, modeling and prediction of active biochemical networks up to whole species populations. This process relies on the development of new technologies for the analysis of molecular data, especially genomics, metabolomics and proteomics data. The ambitious aim of these non-targeted 'omic' technologies is to extend our understanding beyond the analysis of separated parts of the system, in contrast to traditional reductionistic hypothesis-driven approaches. The consequent integration of genotyping, pheno/morphotyping and the analysis of the molecular phenotype using metabolomics, proteomics and transcriptomics will reveal a novel understanding of plant metabolism and its interaction with the environment. The analysis of single model systems - plants, fungi, animals and bacteria - will finally emerge in the analysis of populations of plants and other organisms and their adaptation to the ecological niche. In parallel, this novel understanding of ecophysiology will translate into knowledge-based approaches in crop plant biotechnology and marker- or genome-assisted breeding approaches. In this review the foundations of green systems biology are described and applications in ecosystems research are presented. Knowledge exchange of ecosystems research and green biotechnology merging into green systems biology is anticipated based on the principles of natural variation, biodiversity and the genotype-phenotype environment relationship as the fundamental drivers of ecology and evolution.

Identification and application of biomarkers in molecular and genomic epidemiologic research

Biomarkers are characteristic biological properties that can be detected and measured in a variety of biological matrices in the human body, including the blood and tissue, to give an indication of whether there is a threat of disease, if a disease already exists, or how such a disease may develop in an individual case. Along the continuum from exposure to clinical disease and progression, exposure, internal dose, biologically effective dose, early biological effect, altered structure and/or function, clinical disease, and disease progression can potentially be observed and quantified using biomarkers. While the traditional discovery of biomarkers has been a slow process, the advent of molecular and genomic medicine has resulted in explosive growth in the discovery of new biomarkers. In this review, issues in evaluating biomarkers will be discussed and the biomarkers of environmental exposure, early biologic effect, and susceptibility identified and validated in epidemiological studies will be summarized. The spectrum of genomic approaches currently used to identify and apply biomarkers and strategies to validate genomic biomarkers will also be discussed.

Calibration function for the Orbitrap FTMS accounting for the space charge effect

Ion storage in an electrostatic trap has been implemented with the introduction of the Orbitrap Fourier transform mass spectrometer (FTMS), which demonstrates performance similar to high-field ion cyclotron resonance MS. High mass spectral characteristics resulted in rapid acceptance of the Orbitrap FTMS for Life Sciences applications. The basics of Orbitrap operation are well documented; however, like in any ion trap MS technology, its performance is limited by interactions between the ion clouds. These interactions result in ion cloud couplings, systematic errors in measured masses, interference between ion clouds of different size yet with close m/z ratios, etc. In this work, we have characterized the space-charge effect on the measured frequency for the Orbitrap FTMS, looking for the possibility to achieve sub-ppm levels of mass measurement accuracy (MMA) for peptides in a wide range of total ion population. As a result of this characterization, we proposed an m/z calibration law for the Orbitrap FTMS that accounts for the total ion population present in the trap during a data acquisition event. Using this law, we were able to achieve a zero-space charge MMA limit of 80 ppb for the commercial Orbitrap FTMS system and sub-ppm level of MMA over a wide range of total ion populations with the automatic gain control values varying from 10 to 10(7).

Proteomics in detection and monitoring of asthma and smoking-related lung diseases

Asthma, chronic obstructive pulmonary disease (COPD) and lung cancer cause extensive mortality and morbidity worldwide. However, the current state-of-the-art diagnosis and management schemes of these diseases are suboptimal as the incidence of asthma has risen by 250% over the last two decades and the 5-year mortality rate of lung cancer remains at 88%. Proteomic analysis is at the frontier of medical research and demonstrates tremendous potential in the early detection, diagnosis and staging, as well as providing novel therapeutic targets for improved management of smoking-related lung diseases. Advances in analytical tools, such as 2D gel electrophoresis, mass spectrometry, protein arrays and improved bioinformatics, allow sensitive and specific biomarker/protein profile discoveries and the infusion of new knowledge towards the molecular basis of lung diseases and their progression. Significant hurdles still stand between these laboratory findings and their applications in clinical practice. One of the challenges is the difficulty in the selection of samples that provide scope into the specific disease entity. Induced sputum, bronchoalveolar lavage, exhaled breath and exhaled breath condensate are methods of sampling airway and lung fluids that can serve as a window to assess the microenvironment of the lungs. With better study design standardization and the implementation of novel technologies to reach the optimal research standard, there is enough reason be optimistic about the future of proteomic research and its clinical implications.

Enhanced protein detection using a trapping mode on a hybrid quadrupole linear ion trap (Q-Trap)

A novel method to improve the detection of protein ions using a linear ion trap mass spectrometer is presented. A scan function combining charge separation with segmented transmission of multiply charged ions was developed to enhance the sensitivity and resolution of the linear ion trap for the nanoLC-MS analysis of intact proteins. The analytical benefits of the present method are particularly apparent in protein analyses, where the increased proportion of multiply charged ions can exacerbate space-charge effects and compromise the dynamic range of the linear ion trap instrument. The enhanced ion storage and charge separation capabilities of our targeted and enhanced multiply charged scan mode provided a 4-fold increase in signal-to-noise and 5-fold increase in resolution, thus enabling the detection of closely related protein isoforms. The application of this method is demonstrated for low femtomole detection of protein standards and nuclear extracts enriched in histone proteins. The enhanced resolution of this scan mode also enabled us to monitor subtle changes in the methylation of a subpopulation of histone H3 that occurs in chicken DT40 cells lacking specific methyltransferase activity. The extent of the fold change and PTM site localization was performed using predictive software tools and targeted multiple reaction monitoring analysis of histone peptides. Monomethylation of Lys 79 in histone H3 (H3K79me1) was down regulated by 240-fold in methyltransferase deficient cells.

Differentiation of plant cells during symbiotic nitrogen fixation

Nitrogen-fixing symbioses between legumes and bacteria of the family Rhizobiaceae involve differentiation of both plant and bacterial cells. Differentiation of plant root cells is required to build an organ, the nodule, which can feed and accommodate a large population of bacteria under conditions conducive to nitrogen fixation. An efficient vascular system is built to connect the nodule to the root, which delivers sugars and other nutrients to the nodule and removes the products of nitrogen fixation for use in the rest of the plant. Cells in the outer cortex differentiate to form a barrier to oxygen diffusion into nodules, which helps to produce the micro-aerobic environment necessary for bacterial nitrogenase activity. Cells of the central, infected zone of nodules undergo multiple rounds of endoreduplication, which may be necessary for colonisation by rhizobia and may enable enlargement and greater metabolic activity of these cells. Infected cells of the nodule contain rhizobia within a unique plant membrane called the peribacteroid or symbiosome membrane, which separates the bacteria from the host cell cytoplasm and mediates nutrient and signal exchanges between the partners. Rhizobia also undergo differentiation during nodule development. Not surprisingly, perhaps, differentiation of each partner is dependent upon interactions with the other. High-throughput methods to assay gene transcripts, proteins, and metabolites are now being used to explore further the different aspects of plant and bacterial differentiation. In this review, we highlight recent advances in our understanding of plant cell differentiation during nodulation that have been made, at least in part, using high-throughput methods.

Biomarkers of chemotherapy resistance in breast cancer identified by proteomics: current status

This review describes and discusses the advantages and limitations of proteomic approaches in the identification of biomarkers associated with chemotherapy resistance. Both gel-based (two-dimensional polyacrylamide gel electrophoresis) and gel-free (shotgun and quantitative) mass spectrometry approaches are discussed. Non-mass spectrometry approaches including antibody microarray platforms are described as complementary proteomic strategies. Methods for technical confirmation and clinical validation of putative biomarkers are presented. Use of this proteomic toolbox in the quest for biomarkers of chemotherapy resistance in breast cancer is reviewed. Technical aspects of sample selection, acquisition, storage and analysis are discussed and putative biomarkers identified through proteomic approaches are presented.

Role for protein-protein interaction databases in human genetics

Proteomics and the study of protein-protein interactions are becoming increasingly important in our effort to understand human diseases on a system-wide level. Thanks to the development and curation of protein-interaction databases, up-to-date information on these interaction networks is accessible and publicly available to the scientific community. As our knowledge of protein-protein interactions increases, it is important to give thought to the different ways that these resources can impact biomedical research. In this article, we highlight the importance of protein-protein interactions in human genetics and genetic epidemiology. Since protein-protein interactions demonstrate one of the strongest functional relationships between genes, combining genomic data with available proteomic data may provide us with a more in-depth understanding of common human diseases. In this review, we will discuss some of the fundamentals of protein interactions, the databases that are publicly available and how information from these databases can be used to facilitate genome-wide genetic studies.

Characterization and expression of Ailuropoda melanoleuca leptin (ob gene)

Leptin, an adipocyte-derived hormone, plays important roles in metabolism and reproduction. In this article, we report the cloning, expression, and identification of the giant panda leptin (gLeptin) gene and its variants. The gLeptin cDNA was 504 bp long, encoding a precursor peptide of 167 amino acids including 21 residues of signal peptide. A short variant of gLeptin was 501 bp long, encoding a 166-aa peptide and also including a 21-aa signal peptide. Giant panda leptin was 99.4%, 94.6%, and 92.8% identical to that of black bear, dog, and cat, respectively, but was only 81.4% and 80.8% identical to that of human and rat. The cloned gLeptin gene was expressed in Escherichia coli, with expression confirmed by Western blotting and MALDI-TOF-TOF MS PMF. After purification, renaturation, and condensation, the gLeptin protein was injected into Kunming mice. The recombinant gLeptin significantly inhibited food intake by 41.8% and reduced body weight by 5.1% in the mice.

Detection of pathogenic Verticillium spp. using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Verticillium spp. have been listed by the European and Mediterranean Plant Protection Organization (EPPO) and China as plant quarantine pests. Although attempts have been made to develop a simple routine laboratory assay to detect these organisms, none are routinely used. We describe for the first time a robust assay for reliable identification of Verticillium spp. using protein fingerprinting data obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry(MALDI-TOF-MS). Several sample preparation methods and matrices were investigated to improve mass spectra for the routine identification of six species of Verticillium spp.(Verticillium dahiliae, V. alboatrum, V. fungicola, V. nigrescens, and V. lecanii) by MALDI-TOF-MS. Using the optimized experimental method, we constructed a protein fingerprint database for six species of Verticillium and established a analysis criteria of log(Score). This MALDI-TOF-MS protocol should prove useful as a rapid and reliable assay for distinguishing different Verticillium spp.

Analysis of time course 1H NMR metabolomics data by multivariate curve resolution

Modeling NMR-based metabolomics data often involves linear methods such as principal component analysis (PCA) and partial least squares (PLS). These methods have the objective of describing the main variance in the data and maximum covariance between the predictor variables and some response variable respectively. If the experiment is designed to investigate temporal biological fluctuations, however, the factors obtained become difficult to interpret in a biological context. Moreover, when these methods are applied to analyze data, an implicit assumption is made that the measurement errors exhibit an iid-normal distribution, often limiting the extent of the information recovered. A method for the linear decomposition of NMR-based metabolomics data by multivariate curve resolution (MCR), which has been used elsewhere for time course transcriptomics applications, is introduced and implemented via a weighted alternating least squares (ALS) approach. Measurement of error information is incorporated in the modeling process, allowing the least squares projections to be performed in a maximum likelihood fashion. As a result, noise heteroscedasticity resulting from pH-induced peak shifts can be modeled, eliminating the need for binning/bucketing. The utility of the method is demonstrated using two sets of temporal NMR metabolomics data, HgCl(2)-induced nephrotoxicity in rat, and fish (Japanese medaka, Oryzias latipes) embryogenesis. Profiles extracted for the nephrotoxicity data exhibit strong correlations with metabolites consistent with temporal fluctuations in glucosuria. The concentration of metabolites such as acetate, glucose, and alanine exhibit a steady increase, which peaks at Day 3 post dose and returns to basal levels at Day 8. Other metabolites including citrate and 2-oxoglutarate exhibit the opposite characteristics. Although the fish embryogenesis data are more complex, the profiles extracted by the algorithm display characteristics that depict temporal variation consistent with processes associated with embryogenesis.

Proteomics study of the hepatitis C virus replication complex

RNA replication of HCV occurs in the multiprotein complexes associated with the endoplasmic reticular (ER) membranes. The HCV NS3 to NS5B proteins are necessary and sufficient for HCV RNA replication in the cell, but cellular proteins in the HCV replication complex (RC) have not been determined. Several methods have been used to isolate the HCV RC, including crude cell extract preparation, subcellular fractionation, and affinity purification. The components of the HCV RC can be separated by two-dimensional electrophoresis and then determined by proteolytical digestion and mass spectrometry analysis in conjunction with peptide/protein database search and immunobiochemistry and functional genomic studies.