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

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

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

Surface and Temporal Biosignatures

Recent discoveries of potentially habitable exoplanets have ignited the prospect of spectroscopic investigations of exoplanet surfaces and atmospheres for signs of life. This chapter provides an overview of potential surface and temporal exoplanet biosignatures, reviewing Earth analogues and proposed applications based on observations and models. The vegetation red-edge (VRE) remains the most well-studied surface biosignature. Extensions of the VRE, spectral "edges" produced in part by photosynthetic or nonphotosynthetic pigments, may likewise present potential evidence of life. Polarization signatures have the capacity to discriminate between biotic and abiotic "edge" features in the face of false positives from band-gap generating material. Temporal biosignatures -- modulations in measurable quantities such as gas abundances (e.g., CO2), surface features, or emission of light (e.g., fluorescence, bioluminescence) that can be directly linked to the actions of a biosphere -- are in general less well studied than surface or gaseous biosignatures. However, remote observations of Earth's biosphere nonetheless provide proofs of concept for these techniques and are reviewed here. Surface and temporal biosignatures provide complementary information to gaseous biosignatures, and while likely more challenging to observe, would contribute information inaccessible from study of the time-averaged atmospheric composition alone.Comment: 26 pages, 9 figures, review to appear in Handbook of Exoplanets. Fixed figure conversion error

PEPPI-MS: Polyacrylamide-Gel-Based Prefractionation for Analysis of Intact Proteoforms and Protein Complexes by Mass Spectrometry

Prefractionation of complex mixtures of proteins derived from biological samples is indispensable for proteome analysis via top-down mass spectrometry (MS). Polyacrylamide gel electrophoresis (PAGE), which enables high-resolution protein separation based on molecular size, is a widely used technique in biochemical experiments and has the potential to be useful in sample fractionation for top-down MS analysis. However, the lack of a means to efficiently recover the separated proteins in-gel has always been a barrier to its use in sample prefractionation. In this study, we present a novel experimental workflow, called Passively Eluting Proteins from Polyacrylamide gels as Intact species for MS ("PEPPI-MS"), which allows top-down MS of PAGE-separated proteins. The optimization of Coomassie brilliant blue staining followed by the passive extraction step in the PEPPI-MS workflow enabled the efficient recovery of proteins, separated on commercial precast gels, from a wide range of molecular weight regions in under 10 min. Two-dimensional separation combining offline PEPPI-MS with online reversed-phase liquid chromatographic separation resulted in identification of over 1000 proteoforms recovered from the target region of the gel (≤50 kDa). Given the widespread availability and relatively low cost of traditional sodium dodecyl sulfate (SDS)-PAGE equipment, the PEPPI-MS workflow will be a powerful prefractionation strategy for top-down proteomics

Exoplanet biosignatures : a review of remotely detectable signs of life

In the coming years and decades, advanced space- and ground-based observatories will allow an unprecedented opportunity to probe the atmospheres and surfaces of potentially habitable exoplanets for signatures of life. Life on Earth, through its gaseous products and reflectance and scattering properties, has left its fingerprint on the spectrum of our planet. Aided by the universality of the laws of physics and chemistry, we turn to Earth's biosphere, both in the present and through geologic time, for analog signatures that will aid in the search for life elsewhere. Considering the insights gained from modern and ancient Earth, and the broader array of hypothetical exoplanet possibilities, we have compiled a comprehensive overview of our current understanding of potential exoplanet biosignatures, including gaseous, surface, and temporal biosignatures. We additionally survey biogenic spectral features that are well known in the specialist literature but have not yet been robustly vetted in the context of exoplanet biosignatures. We briefly review advances in assessing biosignature plausibility, including novel methods for determining chemical disequilibrium from remotely obtainable data and assessment tools for determining the minimum biomass required to maintain short-lived biogenic gases as atmospheric signatures. We focus particularly on advances made since the seminal review by Des Marais et al. The purpose of this work is not to propose new biosignature strategies, a goal left to companion articles in this series, but to review the current literature, draw meaningful connections between seemingly disparate areas, and clear the way for a path forward.Publisher PDFPeer reviewe

Creative destruction in science

Drawing on the concept of a gale of creative destruction in a capitalistic economy, we argue that initiatives to assess the robustness of findings in the organizational literature should aim to simultaneously test competing ideas operating in the same theoretical space. In other words, replication efforts should seek not just to support or question the original findings, but also to replace them with revised, stronger theories with greater explanatory power. Achieving this will typically require adding new measures, conditions, and subject populations to research designs, in order to carry out conceptual tests of multiple theories in addition to directly replicating the original findings. To illustrate the value of the creative destruction approach for theory pruning in organizational scholarship, we describe recent replication initiatives re-examining culture and work morality, working parents\u2019 reasoning about day care options, and gender discrimination in hiring decisions. Significance statement It is becoming increasingly clear that many, if not most, published research findings across scientific fields are not readily replicable when the same method is repeated. Although extremely valuable, failed replications risk leaving a theoretical void\u2014 reducing confidence the original theoretical prediction is true, but not replacing it with positive evidence in favor of an alternative theory. We introduce the creative destruction approach to replication, which combines theory pruning methods from the field of management with emerging best practices from the open science movement, with the aim of making replications as generative as possible. In effect, we advocate for a Replication 2.0 movement in which the goal shifts from checking on the reliability of past findings to actively engaging in competitive theory testing and theory building. Scientific transparency statement The materials, code, and data for this article are posted publicly on the Open Science Framework, with links provided in the article