Isobaric protein and peptide quantification: perspectives and issues

An important challenge for proteomics is the ability to compare protein levels across biological samples. Since their introduction, isotopic and isobaric peptide labeling have played an important role in relative quantitative comparisons of proteomes. One important drawback of most of the isotopic-labeling techniques is an increase in sample complexity. This problem was successfully addressed with the construction of isobaric labeling strategies, such as isobaric tag for relative and absolute quantification (iTRAQ), tandem mass tagging, the cleavable isobaric affinity tag, dimethylated leucines and isobaric peptide termini labeling. Furthermore, numerous applications for multiplexing using iTRAQ and tandem mass tagging have been reported.     

Palaeomicrobiology: current issues and perspectives

Palaeomicrobiology is an emerging field that is devoted to the detection, identification and characterization of microorganisms in ancient remains. Data indicate that host-associated microbial DNA can survive for almost 20,000 years, and environmental bacterial DNA preserved in permafrost samples has been dated to 400,000-600,000 years. In addition to frozen and mummified soft tissues, bone and dental pulp can also be used to search for microbial pathogens. Various techniques, including microscopy and immunodetection, can be used in palaeomicrobiology, but most data have been obtained using PCR-based molecular techniques. Infections caused by bacteria, viruses and parasites have all been diagnosed using palaeomicrobiological techniques. Additionally, molecular typing of ancient pathogens could help to reconstruct the epidemiology of past epidemics and could feed into current models of emerging infections, therefore contributing to the development of appropriate preventative measures.     

Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification

Fourier transform-all reaction monitoring (FT-ARM) is a novel approach for the identification and quantification of peptides that relies upon the selectivity of high mass accuracy data and the specificity of peptide fragmentation patterns. An FT-ARM experiment involves continuous, data-independent, high mass accuracy MS/MS acquisition spanning a defined m/z range. Custom software was developed to search peptides against the multiplexed fragmentation spectra by comparing theoretical or empirical fragment ions against every fragmentation spectrum across the entire acquisition. A dot product score is calculated against each spectrum to generate a score chromatogram used for both identification and quantification. Chromatographic elution profile characteristics are not used to cluster precursor peptide signals to their respective fragment ions. FT-ARM identifications are demonstrated to be complementary to conventional data-dependent shotgun analysis, especially in cases where the data-dependent method fails because of fragmenting multiple overlapping precursors. The sensitivity, robustness, and specificity of FT-ARM quantification are shown to be analogous to selected reaction monitoring-based peptide quantification with the added benefit of minimal assay development. Thus, FT-ARM is demonstrated to be a novel and complementary data acquisition, identification, and quantification method for the large scale analysis of peptides.     

Mass spectrometry-based peptide quantification: applications and limitations

In various areas of research, proteomics and particularly the quantification of proteins and peptides renders a useful addition to biochemical experiments. The range of possible applications varies from supervision of concentration changes of relevant proteins during biogenesis to differential proteomics approaches, distinguishing, for instance, healthy and diseased states. Furthermore, mass spectrometry-based peptide quantification yields the possibility of using highly sensitive bottom-up approaches for determination of protein regulations as well as multiplexing capability. Thereby, changes in protein abundances may be linked to specific cellular states bearing the opportunity to reveal marker proteins for several diseases.     

Mass spectrometry-based peptide quantification: applications and limitations

In various areas of research, proteomics and particularly the quantification of proteins and peptides renders a useful addition to biochemical experiments. The range of possible applications varies from supervision of concentration changes of relevant proteins during biogenesis to differential proteomics approaches, distinguishing, for instance, healthy and diseased states. Furthermore, mass spectrometry-based peptide quantification yields the possibility of using highly sensitive bottom-up approaches for determination of protein regulations as well as multiplexing capability. Thereby, changes in protein abundances may be linked to specific cellular states bearing the opportunity to reveal marker proteins for several diseases.     

A computational approach toward label-free protein quantification using predicted peptide detectability

We propose here a new concept of peptide detectability which could be an important factor in explaining the relationship between a protein's quantity and the peptides identified from it in a high-throughput proteomics experiment. We define peptide detectability as the probability of observing a peptide in a standard sample analyzed by a standard proteomics routine and argue that it is an intrinsic property of the peptide sequence and neighboring regions in the parent protein. To test this hypothesis we first used publicly available data and data from our own synthetic samples in which quantities of model proteins were controlled. We then applied machine learning approaches to demonstrate that peptide detectability can be predicted from its sequence and the neighboring regions in the parent protein with satisfactory accuracy. The utility of this approach for protein quantification is demonstrated by peptides with higher detectability generally being identified at lower concentrations over those with lower detectability in the synthetic protein mixtures. These results establish a direct link between protein concentration and peptide detectability. We show that for each protein there exists a level of peptide detectability above which peptides are detected and below which peptides are not detected in an experiment. We call this level the minimum acceptable detectability for identified peptides (MDIP) which can be calibrated to predict protein concentration. Triplicate analysis of a biological sample showed that these MDIP values are consistent among the three data sets.     

Allatotropin-like peptide in Heliothis virescens: tissue localization and quantification

The mating-induced increase in juvenile hormone (JH) biosynthesis in Heliothis virescens females may be stimulated by production and/or release of stimulatory neuropeptides such as allatotropins (AT). Although there is evidence that H. virescens allatotropin may be structurally related to Manduca sexta allatotropin (Manse-AT), little is known of its occurrence and distribution in H. virescens. An enzyme-linked immunosorbent assay (ELISA) using a monoclonal antibody against Manse-AT was used to quantify concentrations of Manse-AT immunoreactivity in tissue extracts of H. virescens. In mated females, the highest concentrations of Manse-AT-like material occurred in the brain. The ventral nervous system and the accessory glands also contained considerable amounts of Manse-AT-like material, whereas concentrations were very low in ovaries, fat body, and flight muscle. The Manse-AT antibody was used for whole-mount immunocytochemistry to localize Manse-AT-immunoreactivity in the central nervous system. Several groups of Manse-AT-immunoreactive cells were discovered in the brain, subesophageal ganglion, and thoracic and abdominal ganglia of H. virescens females and males. Strong immunoreactivity was detected in axons going through the corpora cardiaca and branching out over the surface of the corpora allata. The presence of Manse-AT-like material in various locations in the central nervous system suggests that these peptides may have other as yet unknown functions. At the posterior margin of the terminal ganglion of males, a group of large immunoreactive cells was observed that was not present in females. Other than that, there were no obvious differences between virgin and mated females or males. The lack of differences in AT distribution in mated and virgin females suggests that mating-induced differences in female JH biosynthesis rates may be caused by changes in cellular response to AT at the level of the CA, rather than by changes in the amounts of AT acting on the CA.     

Sex-sorting sperm by flow cytometry in pigs: issues and perspectives

Several hundred thousand offspring of preselected sex of various species have been born since sperm sexing technology based on flow cytometric sorting of X- and Y-chromosome-bearing sperm and DNA was first demonstrated in 1989. The advantages derived from application of sexing technology to commercial dairy cattle production have been demonstrated worldwide. Utilizing sex-sorting technology for pig production systems offers many similar advantages. However, several factors currently limit implementation of sexing technology in pigs. Anatomical and physiological features inherent to the female pig, together with the relatively low sperm output of a flow sorter, are the main limitations to widespread use of this technology in pig production systems. This review analyzes the factors that limit the efficiency of sperm sorting technology for commercial swine production. In addition, this review discusses recent innovations in technical instrumentation and applied reproductive techniques that may help to overcome some of these limitations.     

冬虫夏草菌和蛹虫草菌的研究现状、问题及展望

冬虫夏草菌和蛹虫草菌是两种最著名的虫草菌。从分类学地位、分布、生活史及有性生殖类型、寄主范围、遗传多样性、分子遗传学和基因组学、生态学、人工栽培及产品开发等方面对冬虫夏草菌和蛹虫草菌的研究现状进行总结,指出了研究中存在的一些问题,并对研究前景进行展望。     

Differentially isotope-coded N-terminal protein sulphonation: combining protein identification and quantification

Most proteomic labelling technologies intend to improve protein quantification and/or facilitate (de novo) peptide sequencing. We present here a novel stable-isotope labelling method to simultaneously identify and quantify protein components in complex mixtures by specifically derivatizing the N-terminus of proteins with 4-sulphophenyl isothiocyanate (SPITC). Our approach combines protein identification with quantification through differential isotope-coded labelling at the protein N-terminus prior to digestion. The isotope spacing of 6 Da (unlabelled vs. six-fold 13C-labelled tag) between derivatized peptide pairs enables the detection on different MS platforms (MALDI and ESI). Optimisation of the reaction conditions using SPITC was performed on three model proteins. Improved detection of the N-terminally derivatized peptide compared to the native analogue was observed in negative-ion MALDI-MS. Simpler fragmentation patterns compared to native peptides facilitated protein identification. The 13C-labelled SPITC resulted in convenient peptide pair spacing without isotopic overlap and hence facilitated relative quantification by MALDI-TOF/TOF and LC-ESI-MS/MS. The combination of facilitated identification and quantification achieved by differentially isotope-coded N-terminal protein tagging with light/heavy SPITC represents, to our knowledge, a new approach to quantitative proteomics.     

Immunocontinuum: perspectives in antimicrobial peptide mechanisms of action and resistance

Antimicrobial peptides are present in organisms spanning virtually every kingdom, and employ sophisticated mechanisms to exert rapid microbicidal action consistent with their key roles in host defense. Offsetting these mechanisms, some microbial pathogens have evolved complex countermeasures to neutralize exposure to and subvert mechanisms of antimicrobial peptides. The following discussion highlights recent advances that offer greater understanding of the mechanisms of action and resistance of antimicrobial peptides.     

Artificial cultivation of true morels: current state,issues and perspectives

Morels (Morchella, Ascomycota), which are some of the most highly prized edible and medicinal mushrooms, are of great economic and scientific value. Morel cultivation has been a research focus worldwide for more than 100 years, and the outdoor cultivation of morels has succeeded and expanded to a large scale in China in recent years. In this study, we review the progress in recent research regarding the life cycle and reproductive systems in the genus Morchella and the current state of outdoor cultivation. Sclerotia formation and conidia production are two important phases during the life cycle. The morel species cultivated commercially in America is M. rufobrunnea based on molecular phylogenetic analysis. The species currently cultivated in China are black morels, including M. importuna, M. sextalata and M. eximia. The field cultivation of morels expanded in the majority of the provinces in China with a yield of fresh morels of 0–7620?kg per ha. The key techniques include spawn production, land preparation and spawning, the addition of exogenous nutrition, fruiting management and harvesting. The application of exogenous nutrition is the most important breakthrough in the field of morel cultivation, but the mechanism remains unclear. It was estimated that the total amount of field cultivated fresh morels was ～500 t in 2015–2016. We also discuss the potential issues remaining in the current literature and suggest directions for future studies.     

Histidine-rich peptide selection and quantification in targeted proteomics

Agarose based immobilized copper (II) affinity chromatography (Cu(II)-IMAC) in tandem with reversed-phase chromatography was applied to a yeast protein extract. Histidine-rich peptides were selected and, in the process, samples were substantially simplified prior to mass spectral analysis. Samples of proteins from the yeast extract at fermentation time periods of 2.5 and 10 h were compared quantitatively used the GIST protocol. Acylation of the N-terminus of tryptic peptides with N-acetoxysuccinamide was used to globally label and quantify relative protein concentration changes. Together with N-terminal acylation, an imidazole elution procedure allowed histidine-rich peptides to be preferentially selected by Cu(II)-IMAC. An inverse labeling strategy was applied to increase reliability in determinations of up- and down-regulation. It was found that the concentration of some histidine-rich proteins changed in excess of 4-fold during fermentation. These proteins covered a wide range of molecular weight and pI values.     

iTRAQ protein quantification: a quality-controlled workflow

Reporter ion-based methods are among the major techniques to quantify peptides and proteins. Two main labels, tandem mass tag (TMT) and iTRAQ, are widely used by the proteomics community. They are, however, often applied as out-of-the-box methods, without thorough quality control. Thus, due to undiscovered limitations of the technique, irrelevant results might be trusted. To address this issue, we here propose a step-by-step quality control of the iTRAQ workflow. From sample preparation to final ratio calculation we provide metrics and techniques assessing the actual effectiveness of iTRAQ quantification as well as a novel method for more reliable protein ratio estimation.     

Gene set analysis of genome-wide association studies: methodological issues and perspectives

Recent studies have demonstrated that gene set analysis, which tests disease association with genetic variants in a group of functionally related genes, is a promising approach for analyzing and interpreting genome-wide association studies (GWAS) data. These approaches aim to increase power by combining association signals from multiple genes in the same gene set. In addition, gene set analysis can also shed more light on the biological processes underlying complex diseases. However, current approaches for gene set analysis are still in an early stage of development in that analysis results are often prone to sources of bias, including gene set size and gene length, linkage disequilibrium patterns and the presence of overlapping genes. In this paper, we provide an in-depth review of the gene set analysis procedures, along with parameter choices and the particular methodology challenges at each stage. In addition to providing a survey of recently developed tools, we also classify the analysis methods into larger categories and discuss their strengths and limitations. In the last section, we outline several important areas for improving the analytical strategies in gene set analysis.     

Biased perspectives on formyl peptide receptors

The innate immune system is the first line of defense against pathogenic threats. For the early pathogen recognition and activation of cell protective mechanisms, germline-encoded pattern recognition receptors (PRRs) detect characteristic and evolutionary conserved pathogen-associated molecular patterns (PAMPs). PRRs are therefore key elements in the innate immune response; in addition, they sense danger-associated molecular patterns (DAMPs) that are released by host cell molecules under pathophysiological conditions. Formyl peptide receptors (FPRs) are G-protein-coupled PRRs that respond to a surprisingly broad range of ligands, derived from both pathogens and host cells. Here, we exemplary discuss ligands in order to illustrate the wide pathophysiological relevance of the FPR signaling axis in case of e.g., chronic inflammations and to underscore its potential therapeutic value in the light of “biased agonism”, a modern concept of GPCR (G-protein coupled receptors) activation. These novel insights into the GPCR receptor biochemistry will hopefully (re)stimulate FPR-related research and lead to novel strategies for the urgently needed development of drugs with pharmacologically advantageous characteristics.     

Synthetic peptide API manufacturing: A mini review of current perspectives for peptide manufacturing

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High-throughput peptide quantification using mTRAQ reagent triplex

Background

Continuing research into the global multiple sequence alignment problem has resulted in more sophisticated and principled alignment methods. Unfortunately these new algorithms often require large amounts of time and memory to run, making it nearly impossible to run these algorithms on large datasets. As a solution, we present two general methods, Crumble and Prune, for breaking a phylogenetic alignment problem into smaller, more tractable sub-problems. We call Crumble and Prune meta-alignment methods because they use existing alignment algorithms and can be used with many current alignment programs. Crumble breaks long alignment problems into shorter sub-problems. Prune divides the phylogenetic tree into a collection of smaller trees to reduce the number of sequences in each alignment problem. These methods are orthogonal: they can be applied together to provide better scaling in terms of sequence length and in sequence depth. Both methods partition the problem such that many of the sub-problems can be solved independently. The results are then combined to form a solution to the full alignment problem.

Results

Crumble and Prune each provide a significant performance improvement with little loss of accuracy. In some cases, a gain in accuracy was observed. Crumble and Prune were tested on real and simulated data. Furthermore, we have implemented a system called Job-tree that allows hierarchical sub-problems to be solved in parallel on a compute cluster, significantly shortening the run-time.

Conclusions

These methods enabled us to solve gigabase alignment problems. These methods could enable a new generation of biologically realistic alignment algorithms to be applied to real world, large scale alignment problems.