Search

Proteomics is the large-scale study and analysis of proteins, directed to analysing protein function in a cellular context. Since the vast majority of the processes occurring in a living cell rely on protein activity, proteomics offer a unique vantage point from which researchers can dissect, characterise, understand and manipulate biological systems. When developing a production strain, proteomics offers a versatile toolkit of analytical techniques. In this commentary, we highlight a number of recent developments in this field using three industrially relevant case studies: targeted proteomic analysis of heterologous pathways in Escherichia coli, biofuel production in Synechocystis PCC6803 and proteomic investigations of lignocellulose degradation. We conclude by discussing future developments in proteomics that will impact upon metabolic engineering and process monitoring of bio-producer strains., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

In recent years, much progress has been made in proteomic studies to unravel metabolic pathways and basic cellular processes. This is especially interesting for members of the Archaea, the third domain of life. Archaea exhibit extraordinary features and many of their cultivable representatives are adaptable to extreme environments. Archaea harbor many unique traits besides bacterial attributes, such as size, shape, and DNA structure and eukaryal characteristics like information processing. Sulfolobus solfataricus P2, a thermoacidophilic archaeal representative, is a well-established model organism adapted to low-pH environments (pH 2-3) and high temperatures (80°C). The genome has a size of 3 Mbp and its sequence has been deciphered. Approximately 3033 predicted open reading frames have been identified and the genome is characterized by a great number of diverse insertion sequence elements. In unraveling the organisms' metabolism and lifestyle, proteomic analyses have played a major role. Much effort has been directed at this organism and is reviewed here. With the help of proteomics, unique metabolic pathways were resolved in S. solfataricus, targets for regulatory protein phosphorylation identified, and cellular responses upon virus infection as well as oxidative stress analyzed., (© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Nitrogen starvation induced changes in carbohydrate and lipid content is described in several algal species. Although these phenotypic changes are desirable, such manipulations also significantly deteriorate culture health, ultimately halting growth. To optimize biofuel production from algae, it is desirable to induce lipid accumulation without compromising cell growth and survival. In this study, we utilized an 8-plex iTRAQ-based proteomic approach to assess the model alga Chlamydomonas reinhardtii CCAP 11/32CW15+ under nitrogen starvation. First-dimension fractionation was conducted using HILIC and SCX. A total of 587 proteins were identified (≥3 peptides) of which 71 and 311 were differentially expressed at significant levels (p<0.05), during nitrogen stress induced carbohydrate and lipid production, respectively. Forty-seven percent more changes with significance were observed with HILIC compared to SCX. Several trends were observed including increase in energy metabolism, decrease in translation machinery, increase in cell wall production and a change of balance between photosystems I and II. These findings point to a severely compromised system where lipid is accumulated at the expense of normal functioning of the organism, suggesting that a more informed and controlled method of lipid induction than gross nutrient manipulation would be needed for development of sustainable processes.

The iTRAQ (isobaric tags for relative and absolute quantification) technique is widely employed in proteomic workflows requiring relative quantification. Here, we review the iTRAQ literature; in particular, we focus on iTRAQ usage in relation to other commonly used quantitative techniques e.g. stable isotope labelling in culture (SILAC), label-free methods and selected reaction monitoring (SRM). As a result, we identify several issues arising with respect to iTRAQ. Perhaps frustratingly, iTRAQ's attractiveness has been undermined by a number of technical and analytical limitations: it may not be truly quantitative, as the changes in abundance reported will generally be underestimated. We discuss weaknesses and strengths of iTRAQ as a methodology for relative quantification in the light of this and other technical issues. We focus on technical developments targeted at iTRAQ accuracy and precision, use of 4-plex over 8-plex reagents and application of iTRAQ to post-translational modification (PTM) workflows. We also discuss iTRAQ in relation to label-free approaches, to which iTRAQ is losing ground.

Proteomics is very much a technology-driven field. The ambition is to identify, quantify and to assess the state of posttranslational modification and interaction partners for every protein in the cell. The proteome is in a state of flux and is thus extremely complex. Analysis of the proteome is exacerbated by the huge dynamic concentration range of proteins in the cellular environment. The impact that mass spectrometry-based proteomics has had on the field of biology has heavily depended on dramatic improvements in mass spectrometry that have been made in recent years. We examined 1541 reports indexed in PubMed relating to proteomics and reproduction to identify trends in the field and to make some broad observations for future work. To set the scene, in the first part of the report, we give a comprehensive overview of proteomics and associated techniques and technologies (such as separations and mass spectrometry). The second part examines the field in light of these techniques and suggests some opportunities for application of these tools in the area of reproduction., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Recently, the prospect of using Escherichia coli as a host for human glycoprotein production has increased due to detailed characterization of the prokaryotic N-glycosylation process and the ability to transfer the system into this bacterium. Although functionality of the native Campylobacter jejuni N-glycosylation system in E. coli has been demonstrated, the efficiency of the process using the well-characterized C. jejuni glycoprotein AcrA, was found to be low at 13.4±0.9% of total extracted protein. A combined approach using isobaric labeling of peptides and probability-based network analysis of metabolic changes was applied to forward engineer E. coli to improve glycosylation efficiency of AcrA. Enhancing flux through the glyoxylate cycle was identified as a potential metabolic manipulation to improve modification efficiency and was achieved by increasing the expression of isocitrate lyase. While the overall recombinant protein titre did not change significantly, the amount of glycosylated protein increased by approximately 300%., (Copyright © 2010 Wiley Periodicals, Inc.)

Tannerella forsythia is a Gram-negative anaerobe that is one of the most prominent inhabitants of the sub-gingival plaque biofilm, which is crucial for causing periodontitis. We have used iTRAQ proteomics to identify and quantify alterations in global protein expression of T. forsythia during growth in a biofilm. This is the first proteomic study concentrating on biofilm growth in this key periodontal pathogen, and this study has identified several changes in protein expression. Moreover, we introduce a rigorous statistical method utilising peptide-level intensities of iTRAQ reporters to determine which proteins are significantly regulated. In total, 348 proteins were identified and quantified with the expression of 44 proteins being significantly altered between biofilm and planktonic cells. We identified proteins from all cell compartments, and highlighted a marked upregulation in the relative abundances of predicted outer membrane proteins in biofilm cells. These included putative transport systems and the T. forsythia S-layer proteins. These data and our finding that the butyrate production pathway is markedly downregulated in biofilms indicate possible alterations in host interaction capability. We also identified upregulation of putative oxidative stress response proteins, and showed that biofilm cells are 10 to 20 fold more resistant to oxidative stress. This may represent an important adaptation of this organism to prolonged persistence and immune evasion in the oral cavity.

iTRAQ reagents allow the simultaneous multiplex identification and quantification of a large number of proteins. Success depends on effective peptide fragmentation in order to generate both peptide sequence ions (higher mass region, 150-2200 m/z) and reporter ions (low mass region, 113-121 m/z) for protein identification and relative quantification, respectively. After collision-induced dissociation, the key requirements to achieve a good balance between the high and low m/z ions are effective ion transmission and detection across the MS/MS mass range, since the ion transmission of the higher m/z range competes with that of the low m/z range. This study describes an analytical strategy for the implementation of iTRAQ on maXis UHR-Qq-ToF instruments, and discusses the impact of adjusting the MS/MS ion transmission parameters on the quality of the overall data sets. A technical discussion highlights a number of maXis-specific parameters, their impact of quantification and identification, and their cross-interactions.

The increasing popularity of iTRAQ for quantitative proteomics applications makes it necessary to evaluate its relevance, accuracy, and precision for biological interpretation. Here, we have assessed (a) the accuracy and precision of iTRAQ quantification in a controlled experimental setup, using low- and high-complexity protein mixtures; and (b) the potential pitfalls that hamper the applicability and attainable dynamic range of iTRAQ: isotopic contamination, background interference, and signal-to-noise ratio. Our data suggest greater dynamic crosstalk between interfering factors affecting underestimations, and that these interferences were largely scenario-specific, dependent on sample complexity. The good is the potential for iTRAQ to provide accurate quantification spanning 2 orders of magnitude. This potential is however limited by two factors. (1) The bad: the existence of isotopic impurities that can be corrected for; provided accurate isotopic factors are at one's disposal. (2) The ugly: we demonstrate here the interference of mixed MS/MS contribution occurring during precursor selection, an issue that is currently very difficult to minimize. In light of our results, we propose a list of advice for iTRAQ data analysis that could routinely ameliorate quantitative interpretation of proteomic data sets.

Nostoc punctiforme ATCC 29133 is a photoautotrophic cyanobacterium with the capacity to fix atmospheric N 2. Its ability to mediate this process is similar to that described for Nostoc sp. PCC 7120, where vegetative cells differentiate into heterocysts. Quantitative proteomic investigations at both the filament level and the heterocyst level are presented using isobaric tagging technology (iTRAQ), with 721 proteins at the 95% confidence interval quantified across both studies. Observations from both experiments yielded findings confirmatory of both transcriptional studies, and published Nostoc sp. PCC 7120 iTRAQ data. N. punctiforme exhibits similar metabolic trends, though changes in a number of metabolic pathways are less pronounced than in Nostoc sp. PCC 7120. Results also suggest a number of proteins that may benefit from future investigations. These include ATP dependent Zn-proteases, N-reserve degraders and also redox balance proteins. Complementary proteomic data sets from both organisms present key precursor knowledge that is important for future cyanobacterial biohydrogen research.

Technological developments in the life sciences have resulted in an ever-accelerating pace of data production. Systems Biology tries to shed light upon these data by building complex models describing the interactions between biological components. However, extracting information from this morass of data requires the use of sophisticated computational techniques. Here, we propose a method suitable to integrate data drawn from quantitative proteomics into a metabolic scaffold and identify the metabolic pathways which are collectively up-regulated or down-regulated. The availability of such a tool is highly desirable as the extracted information could then be taken as a starting point for in-depth analyses, in particular in fields like Synthetic Biology, where datasets need be characterized routinely.