Monitoring recombinant protein expression in bacteria by rapid evaporative ionisation mass spectrometry.

RATIONALE:There is increasing interest in methods of direct analysis mass spectrometry that bypass complex sample preparation steps. METHODS:One of the most interesting new ionisation methods is rapid evaporative ionisation mass spectrometry (REIMS) in which samples are vapourised and the combustion products are subsequently ionised and analysed by mass spectrometry (Synapt G2si). The only sample preparation required is the recovery of a cell pellet from a culture that can be analysed immediately. RESULTS:We demonstrate that REIMS can be used to monitor the expression of heterologous recombinant proteins in Escherichia coli. Clear segregation was achievable between bacteria harvesting plasmids that were strongly expressed and other cultures in which the plasmid did not result in the expression of large amounts of recombinant product. CONCLUSIONS:REIMS has considerable potential as a near-instantaneous monitoring tool for protein production in a biotechnology environment

Selection on Coding and Regulatory Variation Maintains Individuality in Major Urinary Protein Scent Marks in Wild Mice

Recognition of individuals by scent is widespread across animal taxa. Though animals can often discriminate chemical blends based on many compounds, recent work shows that specific protein pheromones are necessary and sufficient for individual recognition via scent marks in mice. The genetic nature of individuality in scent marks (e.g. coding versus regulatory variation) and the evolutionary processes that maintain diversity are poorly understood. The individual signatures in scent marks of house mice are the protein products of a group of highly similar paralogs in the major urinary protein (Mup) gene family. Using the offspring of wild-caught mice, we examine individuality in the major urinary protein (MUP) scent marks at the DNA, RNA and protein levels. We show that individuality arises through a combination of variation at amino acid coding sites and differential transcription of central Mup genes across individuals, and we identify eSNPs in promoters. There is no evidence of post-transcriptional processes influencing phenotypic diversity as transcripts accurately predict the relative abundance of proteins in urine samples. The match between transcripts and urine samples taken six months earlier also emphasizes that the proportional relationships across central MUP isoforms in urine is stable. Balancing selection maintains coding variants at moderate frequencies, though pheromone diversity appears limited by interactions with vomeronasal receptors. We find that differential transcription of the central Mup paralogs within and between individuals significantly increases the individuality of pheromone blends. Balancing selection on gene regulation allows for increased individuality via combinatorial diversity in a limited number of pheromones

Vanadium Complexes Are in vitro Inhibitors of Leishmania Secreted Acid Phosphatases

Leishmaniasis is a parasitic disease caused by the protozoa Leishmania. These organisms secrete acid phosphatases during their growth cycle as an important part of cell targeting to host macrophage cells thus allowing for a successful infection. Secreted acid phosphatases (SAP) are reported to play a significant role in the survival of Leishmania cells, thus evaluation of these enzymes is of interest. The inhibition of SAP can be the focus of a new drug therapy. We tested for SAP activity from Leishmania tarentolae following the addition of a series of vanadium complexes including decavanadate. Cell cultures at different stages in their growth curve were harvested by centrifugation and supernatant was collected. The SAP activity in the supernatant was assayed with the artificial substrate p-nitrophenylphosphate (pNPP). Incubation with orthovanadate resulted in a decrease in activity of 18% ± 1 relative to the control, in comparison to decavanadate, which resulted in a 35% ± 4 decrease in activity. Other vanadium complexes showed smaller inhibitory effects than orthovanadate. Some vanadium complexes appeared to have an effect on reducing cell clumping when compared to control cells. The SAP was partially isolated through anion exchange chromatography and results indicate that SAP isozyme forms are present in the supernatant from cells. Future work is focused on obtaining recombinant enzyme which can be more completely characterized for inhibition by vanadium complexes

Decoding the absolute stoichiometric composition and structural plasticity of α-carboxysomes

Carboxysomes are anabolic bacterial microcompartments that play an essential role in carbon fixation in cyanobacteria and some chemoautotrophs. This self-assembling organelle encapsulates the key CO 2 -fixing enzymes, Rubisco, and carbonic anhydrase using a polyhedral protein shell that is constructed by hundreds of shell protein paralogs. The α-carboxysome from the chemoautotroph Halothiobacillus neapolitanus serves as a model system in fundamental studies and synthetic engineering of carboxysomes. Here we adopt a QconCAT-based quantitative mass spectrometry to determine the absolute stoichiometric composition of native α-carboxysomes from H. neapolitanus . We further performed an in-depth comparison of the protein stoichiometry of native and recombinant α-carboxysomes heterologously generated in Escherichia coli to evaluate the structural variability and remodeling of α-carboxysomes. Our results provide insight into the molecular principles that mediate carboxysome assembly, which may aid in rational design and reprogramming of carboxysomes in new contexts for biotechnological applications

Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies. Reliable and accurate quantification of the proteins present in a cell or tissue remains a major challenge for post-genome scientists. Proteins are the primary functional molecules in biological systems and knowledge of their abundance and dynamics is an important prerequisite to a complete understanding of natural physiological processes, or dysfunction in disease. Accordingly, much effort has been spent in the development of reliable, accurate and sensitive techniques to quantify the cellular proteome, the complement of proteins expressed at a given time under defined conditions (1). Moreover, the ability to model a biological system and thus characterize it in kinetic terms, requires that protein concentrations be defined in absolute numbers (2, 3). Given the high demand for accurate quantitative proteome data sets, there has been a continual drive to develop methodology to accomplish this, typically using mass spectrometry (MS) as the analytical platform. Many recent studies have highlighted the capabilities of MS to provide good coverage of the proteome at high sensitivity often using yeast as a demonstrator system (4⇓⇓⇓⇓⇓–10), suggesting that quantitative proteomics has now “come of age” (1). However, given that MS is not inherently quantitative, most of the approaches produce relative quantitation and do not typically measure the absolute concentrations of individual molecular species by direct means. For the yeast proteome, epitope tagging studies using green fluorescent protein or tandem affinity purification tags provides an alternative to MS. Here, collections of modified strains are generated that incorporate a detectable, and therefore quantifiable, tag that supports immunoblotting or fluorescence techniques (11, 12). However, such strategies for copies per cell (cpc) quantification rely on genetic manipulation of the host organism and hence do not quantify endogenous, unmodified protein. Similarly, the tagging can alter protein levels - in some instances hindering protein expression completely (11). Even so, epitope tagging methods have been of value to the community, yielding high coverage quantitative data sets for the majority of the yeast proteome (11, 12). MS-based methods do not rely on such nonendogenous labels, and can reach genome-wide levels of coverage. Accurate estimation of absolute concentrations i.e. protein copy number per cell, also usually necessitates the use of (one or more) external or internal standards from which to derive absolute abundance (4). Examples include a comprehensive quantification of the Leptospira interrogans proteome that used a 19 protein subset quantified using selected reaction monitoring (SRM)1 to calibrate their label-free data (8, 13). It is worth noting that epitope tagging methods, although also absolute, rely on a very limited set of standards for the quantitative western blots and necessitate incorporation of a suitable immunogenic tag (11). Other recent, innovative approaches exploiting total ion signal and internal scaling to estimate protein cellular abundance (10, 14), avoid the use of internal standards, though they do rely on targeted proteomic data to validate their approach. The use of targeted SRM strategies to derive proteomic calibration standards highlights its advantages in comparison to label-free in terms of accuracy, precision, dynamic range and limit of detection and has gained currency for its reliability and sensitivity (3, 15⇓–17). Indeed, SRM is often referred to as the “gold standard proteomic quantification method,” being particularly well-suited when the proteins to be quantified are known, when appropriate surrogate peptides for protein quantification can be selected a priori, and matched with stable isotope-labeled (SIL) standards (18⇓–20). In combination with SIL peptide standards that can be generated through a variety of means (3, 15), SRM can be used to quantify low copy number proteins, reaching down to ∼50 cpc in yeast (5). However, although SRM methodology has been used extensively for S. cerevisiae protein quantification by us and others (19, 21, 22), it has not been used for large protein cohorts because of the requirement to generate the large numbers of attendant SIL peptide standards; the largest published data set is only for a few tens of proteins. It remains a challenge therefore to robustly quantify an entire eukaryotic proteome in absolute terms by direct means using targeted MS and this is the focus of our present study, the Census Of the Proteome of Yeast (CoPY). We present here direct and absolute quantification of nearly 2000 endogenous proteins from S. cerevisiae grown in steady state in a chemostat culture, using the SRM-based QconCAT approach. Although arguably not quantification of the entire proteome, this represents an accurate and rigorous collection of direct yeast protein quantifications, providing a gold-standard data set of endogenous protein levels for future reference and comparative studies. The highly reproducible SIL-SRM MS data, with robust CVs typically less than 20%, is compared with other extant data sets that were obtained via alternative analytical strategies. We also report a matched high quality transcriptome from the same cells using RNA-seq, which supports additional calculations including a refined estimate of the total protein content in yeast cells, and a simple linear model of translation explaining 70% of the variance between RNA and protein levels in yeast chemostat cultures. These analyses confirm the validity of our data and approach, which we believe represents a state-of-the-art absolute quantification compendium of a significant proportion of a model eukaryotic proteome

MEERCAT: Multiplexed Efficient Cell Free Expression of Recombinant QconCATs For Large Scale Absolute Proteome Quantification

A major challenge in proteomics is the absolute accurate quantification of large numbers of proteins. QconCATs, artificial proteins that are concatenations of multiple standard peptides, are well established as an efficient means to generate standards for proteome quantification. Previously, QconCATs have been expressed in bacteria, but we now describe QconCAT expression in a robust, cell-free system. The new expression approach rescues QconCATs that previously were unable to be expressed in bacteria and can reduce the incidence of proteolytic damage to QconCATs. Moreover, it is possible to cosynthesize QconCATs in a highly-multiplexed translation reaction, coexpressing tens or hundreds of QconCATs simultaneously. By obviating bacterial culture and through the gain of high level multiplexing, it is now possible to generate tens of thousands of standard peptides in a matter of weeks, rendering absolute quantification of a complex proteome highly achievable in a reproducible, broadly deployable system. One of the major challenges in proteomics is absolute quantification of individual proteins. The predominant technology in large scale protein quantification is MS of (usually tryptic) peptides derived from proteolysis of the proteome in vitro and it is well understood that although mass spectrometers can deliver linearity of response over many orders of magnitude, the response factor (signal intensity per mol of peptide) varies considerably among individual peptides (1, 2). One outcome is that commonly used “label-free” methods that sum the precursor ion intensities for the peptides derived from a single protein, are excellent for relative quantification, but are less satisfactory for absolute quantification. MS-based absolute quantification of proteins can be supported by external standards that are analyzed before and/or after the analyte or by stable-isotope labeled internal standards that are coanalyzed and which define the response factor for each peptide (3). These peptides can be individually synthesized and quantified (4) and there have been some remarkable large-scale studies. However, large numbers of accurately quantified peptides are costly. Further, a commercially produced, accurately quantified standard peptide is a finite resource and is hence best focused on low numbers of assays of a small number of target proteins. Intact protein standards (5⇓–7), or large fragments (8) provide multiple potential peptides for quantification of the targets. In 2005, a novel approach to the creation of standard peptides by biosynthesis was proposed in the form of QconCATs (9⇓⇓⇓–13). QconCATs are artificial proteins that are concatenations of standard peptides from multiple natural proteins, sometimes interspersed by short peptides to recapitulate the primary sequence context of the natural counterpart (14, 15). Peptides suitable for quantification are referred to as Q-peptides, and are not synonymous with proteotypic peptides, as the latter term refers to peptides, unique to one protein, that drive protein identification, not quantification. QconCATs genes are synthesized de novo and are routinely expressed in E. coli cultured in media supplemented with appropriate stable isotope labeled amino acids, such that peptides derived from QconCATs are discriminable from natural peptides within the mass spectrometer. The purified QconCATs are mixed with the biological analyte sample and coproteolyzed to generate a mixture of labeled (standard) and unlabeled (analyte) peptide pairs that can be analyzed by liquid chromatography coupled to MS to yield absolute quantification of the analyte proteins. QconCATs have the added advantage that with appropriate control of proteolysis (11) all standards are, by definition, in a 1:1 ratio, rendering independent quantification of each standard unnecessary; a single common peptide can function to quantify the QconCAT (13). However, successful expression of novel QconCATs in E. coli is not always guaranteed. In a large-scale quantification project that used over 100 independently designed and expressed QconCATs, we discovered that ∼1 in 10 of the concatamers would fail to express, even when a range of expression conditions were explored. Further, at a low frequency, some QconCATs were prone to proteolysis in the bacterial cell or during purification, rendering them of reduced value for quantification. Effective QconCAT deployment across large scale proteome quantification studies would require a high level of confidence in expression of every new construct. In addition, living-cell based synthesis systems are not ideal for high-throughput preparation of multiple QconCATs and many mass spectrometry laboratories are not equipped for the basic molecular biology that would be needed to subclone and express recombinant proteins. To enhance the potential of QconCAT technology for large-scale proteome quantification, we here focus on a wheat germ cell-free protein synthesis system (WGCFS)1 as a major enhancement to the workflow of high throughput QconCAT synthesis. WGCFS, which uses the powerful translation system for germination stored in wheat germ, realizes the highest yield of translation among commercially available eukaryotic derived cell-free systems (16⇓⇓⇓–20). Using WGCFS, we previously demonstrated the feasibility of synthesis of single, small QconCATs, typically 25 kDa (21). In the present study, we first assessed whether WGCFS could be used to express more typical QconCATs at approx. 60 kDa (for quantification of ∼25 proteins at two peptides per target protein), whether WGCFS would rescue “failed” QconCATs and whether this cell free system was able to reduce the risk of proteolytic degradation. Further, we established whether an additional step in efficiency could be derived from coexpression of multiple QconCATs in a single WGCFS reaction

Synthetic biology meets proteomics: Construction of a la carte QconCATs for absolute protein quantification

We report a new approach to the assembly and construction of QconCATs, quantitative concatamers for proteomic applications that yield stoichiometric quantities of sets of stable isotope-labelled internal standards. The new approach is based on synthetic biology precepts of biobricks, making use of loop assembly to construct larger entities from individual biobricks. It offers a major gain in flexibility of QconCAT implementation and enables rapid and efficient editability that permits, for example, substitution of one peptide for another. The basic building block (a Qbrick) is a segment of DNA that encodes two or more quantification peptides for a single protein, readily held in a repository as a library resource. These Qbricks are then assembled in a one tube ligation reaction that enforces the order of assembly, to yield short QconCATs that are useable for small quantification products. However, the DNA context of the short also allows a second cycle of assembly such that five different short QconCATs can be assembled into a longer QconCAT in a second, single tube ligation. From a library of Qbricks, a bespoke QconCAT can be assembled quickly and efficiently in a form suitable for expression and labelling in vivo or in vitro. We refer to this approach as the ALACAT strategy as it permits a la carte design of quantification standards

The relationship between lung disease severity and the sputum proteome in cystic fibrosis.

BackgroundProteomics can reveal molecular pathways of disease and provide translational perspectives to inform clinical decision making. Although several studies have previously reported the cystic fibrosis airway proteome, the relationship with severity of lung disease has not been characterised. The objectives of this observational study were to investigate differences in the CF sputum proteome associated with disease severity and identify potential markers of disease with translational potential.MethodsSputum samples from healthy volunteers and cystic fibrosis subjects (some prescribed modulator therapies) were analysed using liquid-chromatography tandem mass spectrometry. Severity of lung disease was based on baseline spirometry (percentage predicted forced expiratory volume in 1 s, FEV1%).ResultsMultiple sputum proteins (108 increased; 202 decreased) were differentially expressed in CF (n = 38) and healthy volunteers (n = 32). Using principal component analysis and hierarchical clustering, differences in sputum proteome were observed associated with progressive lung function impairment. In CF subjects, baseline FEV1% correlated with 87 proteins (positive correlation n = 20, negative n = 67); most were either neutrophil derived, or opposed neutrophil-driven oxidant and protease activity.ConclusionPredictable and quantifiable changes in the CF sputum proteome occurred associated with progressive lung function impairment, some of which might have value as markers of disease severity in CF sputum. Further work validating these markers in other patient cohorts and exploring their clinical utility is needed

Quantitative Proteomics of Enriched Esophageal and Gut Tissues from the Human Blood Fluke Schistosoma mansoni Pinpoints Secreted Proteins for Vaccine Development

Schistosomes are blood-dwelling helminth parasites that cause schistosomiasis, a debilitating disease resulting in inflammation and, in extreme cases, multiple organ damage. Major challenges to control the transmission persist, and the discovery of protective antigens remains of critical importance for vaccine development. Rhesus macaques can selfcure following schistosome infection, generating antibodies that target proteins from the tegument, gut, and esophagus, the last of which is the least investigated. We developed a dissection technique that permitted increased sensitivity in a comparative proteomics profiling of schistosome esophagus and gut. Proteome analysis of the male schistosome esophagus identified 13 proteins encoded by microexon genes (MEGs), 11 of which were uniquely located in the esophageal glands. Based on this and transcriptome information, a QconCAT was designed for the absolute quantification of selected targets. MEGs 12, 4.2, and 4.1 and venom allergen-like protein 7 were the most abundant, spanning over 245 million to 6 million copies per cell, while aspartyl protease, palmitoyl thioesterase, and galactosyl transferase were present at <1 million copies. Antigenic variation by alternative splicing of MEG proteins was confirmed together with a specialized machinery for protein glycosylation/secretion in the esophagus. Moreover, some gastrodermal secretions were highly enriched in the gut, while others were more uniformly distributed throughout the parasite, potentially indicating lysosomal activity. Collectively, our findings provide a more rational, better-oriented selection of schistosome vaccine candidates in the context of a proven model of protective immunity