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

Conflict of Evidence:Resolving Discrepancies When Findings from Randomized Controlled Trials and Meta-analyses Disagree

Financial disclosures: Richard J. Sylvester certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: None. Funding/Support and role of the sponsor: None.Peer reviewedPostprin

Adopting a healthy lifestyle when pregnant and obese - an interview study three years after childbirth

Background: Obesity during pregnancy is increasing and is related to life-threatening and ill-health conditions in both mother and child. Initiating and maintaining a healthy lifestyle when pregnant with body mass index (BMI) ≥ 30 kg/m2 can improve health and decrease risks during pregnancy and of long-term illness for the mother and the child. To minimise gestational weight gain women with BMI ≥ 30 kg/m2 in early pregnancy were invited to a lifestyle intervention including advice and support on diet and physical activity in Gothenburg, Sweden. The aim of this study was to explore the experiences of women with BMI ≥ 30 kg/m2 regarding minimising their gestational weight gain, and to assess how health professionals' care approaches are reflected in the women's narratives. Methods: Semi-structured interviews were conducted with 17 women who had participated in a lifestyle intervention for women with BMI ≥ 30 kg/m2 during pregnancy 3 years earlier. The interviews were digitally recorded and transcribed in full. Thematic analysis was used. Results: The meaning of changing lifestyle for minimising weight gain and of the professional's care approaches is described in four themes: the child as the main motivation for making healthy changes; a need to be seen and supported on own terms to establish healthy routines; being able to manage healthy activities and own weight; and need for additional support to maintain a healthy lifestyle. Conclusions: To support women with BMI ≥ 30 kg/m2 to make healthy lifestyle changes and limit weight gain during pregnancy antenatal health care providers should 1) address women's weight in a non-judgmental way using BMI, and provide accurate and appropriate information about the benefits of limited gestational weight gain; 2) support the woman on her own terms in a collaborative relationship with the midwife; 3) work in partnership to give the woman the tools to self-manage healthy activities and 4) give continued personal support and monitoring to maintain healthy eating and regular physical activity habits after childbirth involving also the partner and family

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

Active manual control of object views facilitates visual recognition

AbstractActive exploration of large-scale environments leads to better learning of spatial layout than does passive observation [1–3]. But active exploration might also help us to remember the appearance of individual objects in a scene. In fact, when we encounter new objects, we often manipulate them so that they can be seen from a variety of perspectives. We present here the first evidence that active control of the visual input in this way facilitates later recognition of objects. Observers who actively rotated novel, three-dimensional objects on a computer screen later showed more efficient visual recognition than observers who passively viewed the exact same sequence of images of these virtual objects. During active exploration, the observers focused mainly on the ‘side’ or ‘front’ views of the objects (see also [4–6]). The results demonstrate that how an object is represented for later recognition is influenced by whether or not one controls the presentation of visual input during learning

Lysosome-targeted stress reveals increased stability of lipofuscin-containing lysosomes

Cellular ageing is associated with accumulation of undegradable intralysosomal material, called lipofuscin. In order to accelerate the lipofuscin accumulation, confluent, growth-arrested human fibroblasts were cultured under hyperoxic conditions. To provide a better insight into the effects of lipofuscin on cellular functions, we compared lysosomal stability in control and lipofuscin-loaded human fibroblasts under conditions of lysosome-targeted stress induced by exposure to either the lysosomotropic detergent MSDH or the redox-cycling quinone naphthazarin. We show that lysosomal damage, assessed by acridine-orange relocation, translocation of cathepsin D to the cytosol, and alkalinization of lysosomes, is more pronounced in control than in lipofuscin-loaded fibroblasts. Finding that lysosomal integrity was less affected or even preserved in case of lipofuscin-loaded cells enables us to suggest that lipofuscin exerts lysosome-stabilizing properties