Ole Vorm

Proteins from silver-stained gels can be digested enzymatically and the resulting peptide analyzed and sequenced by mass spectrometry. Standard proteins yield the same peptide maps when extracted from Coomassie- and silver-stained gels, as judged by electrospray and MALDI mass spectrometry. The low nanogram range can be reached by the protocols described here, and the method is robust. A silver-stained one-dimensional gel of a fraction from yeast proteins was analyzed by nano-electrospray tandem mass spectrometry. In the sequencing, more than 1000 amino acids were covered, resulting in no evidence of chemical modifications due to the silver staining procedure. Silver staining allows a substantial shortening of sample preparation time and may, therefore, be preferable over Coomassie staining. This work removes a major obstacle to the low-level sequence analysis of proteins separated on polyacrylamide gels.

The function of many of the uncharacterized open reading frames discovered by genomic sequencing can be determined at the level of expressed gene products, the proteome. However, identifying the cognate gene from minute amounts of protein has been one of the major problems in molecular biology. Using yeast as an example, we demonstrate here that mass spectrometric protein identification is a general solution to this problem given a completely sequenced genome. As a first screen, our strategy uses automated laser desorption ionization mass spectrometry of the peptide mixtures produced by in-gel tryptic digestion of a protein. Up to 90% of proteins are identified by searching sequence data bases by lists of peptide masses obtained with high accuracy. The remaining proteins are identified by partially sequencing several peptides of the unseparated mixture by nanoelectrospray tandem mass spectrometry followed by data base searching with multiple peptide sequence tags. In blind trials, the method led to unambiguous identification in all cases. In the largest individual protein identification project to date, a total of 150 gel spots-many of them at subpicomole amounts-were successfully analyzed, greatly enlarging a yeast two-dimensional gel data base. More than 32 proteins were novel and matched to previously uncharacterized open reading frames in the yeast genome. This study establishes that mass spectrometry provides the required throughput, the certainty of identification, and the general applicability to serve as the method of choice to connect genome and proteome.

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTImproved Resolution and Very High Sensitivity in MALDI TOF of Matrix Surfaces Made by Fast EvaporationOle. Vorm, Peter. Roepstorff, and Matthias. MannCite this: Anal. Chem. 1994, 66, 19, 3281–3287Publication Date (Print):October 1, 1994Publication History Published online1 May 2002Published inissue 1 October 1994https://pubs.acs.org/doi/10.1021/ac00091a044https://doi.org/10.1021/ac00091a044research-articleACS PublicationsRequest reuse permissionsArticle Views4054Altmetric-Citations595LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts

To further integrate mass spectrometry (MS)-based proteomics into biomedical research and especially into clinical settings, high throughput and robustness are essential requirements. They are largely met in high-flow rate chromatographic systems for small molecules but these are not sufficiently sensitive for proteomics applications. Here we describe a new concept that delivers on these requirements while maintaining the sensitivity of current nano-flow LC systems. Low-pressure pumps elute the sample from a disposable trap column, simultaneously forming a chromatographic gradient that is stored in a long storage loop. An auxiliary gradient creates an offset, ensuring the re-focusing of the peptides before the separation on the analytical column by a single high-pressure pump. This simplified design enables robust operation over thousands of sample injections. Furthermore, the steps between injections are performed in parallel, reducing overhead time to a few minutes and allowing analysis of more than 200 samples per day. From fractionated HeLa cell lysates, deep proteomes covering more than 130,000 sequence unique peptides and close to 10,000 proteins were rapidly acquired. Using this data as a library, we demonstrate quantitation of 5200 proteins in only 21 min. Thus, the new system - termed Evosep One - analyzes samples in an extremely robust and high throughput manner, without sacrificing in depth proteomics coverage. To further integrate mass spectrometry (MS)-based proteomics into biomedical research and especially into clinical settings, high throughput and robustness are essential requirements. They are largely met in high-flow rate chromatographic systems for small molecules but these are not sufficiently sensitive for proteomics applications. Here we describe a new concept that delivers on these requirements while maintaining the sensitivity of current nano-flow LC systems. Low-pressure pumps elute the sample from a disposable trap column, simultaneously forming a chromatographic gradient that is stored in a long storage loop. An auxiliary gradient creates an offset, ensuring the re-focusing of the peptides before the separation on the analytical column by a single high-pressure pump. This simplified design enables robust operation over thousands of sample injections. Furthermore, the steps between injections are performed in parallel, reducing overhead time to a few minutes and allowing analysis of more than 200 samples per day. From fractionated HeLa cell lysates, deep proteomes covering more than 130,000 sequence unique peptides and close to 10,000 proteins were rapidly acquired. Using this data as a library, we demonstrate quantitation of 5200 proteins in only 21 min. Thus, the new system - termed Evosep One - analyzes samples in an extremely robust and high throughput manner, without sacrificing in depth proteomics coverage. Bottom-up proteomics is a highly successful and generic technology, which now allows the analysis of complex samples ranging from bacteria through cell line systems and even human tissue samples (1Aebersold R. Mann M. Mass-spectrometric exploration of proteome structure and function.Nature. 2016; 537: 347-355Crossref PubMed Scopus (1105) Google Scholar). State-of-the-art workflows begin with a robust sample preparation to digest proteins and harvest purified peptides (2Kulak N.A. Pichler G. Paron I. Nagaraj N. Mann M. Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cells.Nat. Methods. 2014; 11: 319-324Crossref PubMed Scopus (991) Google Scholar), which are separated by a liquid chromatography (LC) 1The abbreviation used is:LCliquid chromatography. 1The abbreviation used is:LCliquid chromatography. system before they are analyzed by a mass spectrometer (MS). Established software solutions automatically interpret the acquired spectra, generating lists of thousands of quantified proteins (3Cox J. Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.Nat. Biotechnol. 2008; 26: 1367-1372Crossref PubMed Scopus (9154) Google Scholar, 4Bekker-Jensen D.B. Kelstrup C.D. Batth T.S. Larsen S.C. Haldrup C. Bramsen J.B. Sørensen K.D. Høyer S. Ørntoft T.F. Andersen C.L. Nielsen M.L. Olsen J.V. An optimized shotgun strategy for the rapid generation of comprehensive human proteomes.Cell Systems. 2017; 4: 587-599Abstract Full Text Full Text PDF PubMed Scopus (255) Google Scholar, 5Kelstrup C.D. Bekker-Jensen D.B. Arrey T.N. Hogrebe A. Harder A. Olsen J.V. Performance evaluation of the Q Exactive HF-X for shotgun proteomics.J Proteome Res,. 2018; 17: 727-738Crossref PubMed Scopus (159) Google Scholar, 6Kulak N.A. Geyer P.E. Mann M. Loss-less nano-fractionator for high sensitivity, high coverage proteomics.Mol. Cell. Proteomics. 2017; (Manuscript in Press, 2017)Abstract Full Text Full Text PDF PubMed Scopus (104) Google Scholar, 7Bruderer R. Bernhardt OM Gandhi T Xuan Y Sondermann J Schmidt M Gomez-Varela D Reiter L Optimization of experimental parameters in data-independent mass spectrometry significantly increases depth and reproducibility of results.Mol. Cell. Proteomics. 2017; 16: 2296-2309Abstract Full Text Full Text PDF PubMed Scopus (189) Google Scholar, 8Meier F. Geyer P.E. Virreira Winter S. Cox J. Mann M. BoxCar acquisition method enables single-shot proteomics at a depth of 10,000 proteins in 100 minutes.Nat. Methods. 2018; 10.1038/s41592-018-0003-5Crossref Scopus (218) Google Scholar). liquid chromatography. liquid chromatography. The current performance level is a result of improvements not only in the mass spectrometric components but also the chromatographic part of the LC-MS workflow. In the quest for ever increasing chromatographic separation power, columns have become longer and particle sizes smaller - now reaching the sub 2 μm range. This may require pump pressures more than 1000 bar, presenting great engineering challenges for both the pumps and the entire LC system, often limiting robustness in routine operation. Thus, chromatography remains a weak link in MS-based proteomics workflows, leading to calls for new approaches (9Riley N.M. Hebert A.S. Coon J.J. Proteomics Moves into the Fast Lane.Cell Syst,. 2016; 2: 142-143Abstract Full Text Full Text PDF PubMed Scopus (33) Google Scholar). Furthermore, irreproducibility of retention times within and between laboratories severely limits strategies that rely on the transfer of accurate retention times, especially targeted proteomics (10Picotti P. Aebersold R. Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions.Nat. Methods. 2012; 9: 555-566Crossref PubMed Scopus (991) Google Scholar), data independent acquisition (11Gillet L.C. Leitner A. Aebersold R. Mass spectrometry applied to bottom-up proteomics: entering the high-throughput era for hypothesis testing.Annu. Rev. Anal. Chem. 2016; 9: 449-472Crossref PubMed Scopus (207) Google Scholar) and “match between runs” at the MS level (12Cox J. Hein M.Y. Luber C.A. Paron I. Nagaraj N. Mann M. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ.Mol. Cell. Proteomics. 2014; 13: 2513-2526Abstract Full Text Full Text PDF PubMed Scopus (2688) Google Scholar, 13Geiger T. Wehner A Schaab C Cox J Mann M. Comparative proteomic analysis of eleven common cell lines reveals ubiquitous but varying expression of most proteins.Mol. Cell. Proteomics. 2012; 11M111.014050Abstract Full Text Full Text PDF PubMed Scopus (577) Google Scholar). There is great interest in applying the increasing power of MS-based proteomics to diagnostic and clinical questions (14Geyer P.E. Holdt L.M. Teupser D. Mann M. Revisiting biomarker discovery by plasma proteomics.Mol Syst Biol,. 2017; 13: 942Crossref PubMed Scopus (390) Google Scholar). “Clinical proteomics”, however, requires far more stability and reproducibility than that available even in the most advanced MS-based proteomics laboratories. Note that irreproducibility and robustness issues are not features of LC-MS per se, as the measurement of small molecules is firmly established in clinical laboratories around the world, which routinely of samples per day. The of these LC systems to the applied in proteomics are column and to and the to robustness in the of proteomics R. Aebersold R. Mass spectrometric protein for biomarker discovery and clinical Rev. 13: PubMed Scopus Google Scholar). the in is and reducing sensitivity at rates, which limits these approaches to a few from high throughput is the for MS-based is to routine clinical current proteomics workflows measurement long gradient In a plasma proteomics in more than a of the time to the system than the the column and steps between the of P.E. N.A. Pichler G. Holdt L.M. Teupser D. Mann M. proteome to human and 2016; 2: Full Text Full Text PDF PubMed Scopus Google Scholar, P.E. S. N. J. S. J.J. Mann M. Proteomics reveals the of on the human plasma 2016; PubMed Scopus Google Scholar). of the current a sample and for liquid for high sample throughput for clinical G. Larsen N. liquid chromatography to for and quantification of protein and Proteome 2014; 13: PubMed Scopus Google Scholar). The of the that are in proteomics for of peptides and J. Mann M. and with for and in Proteome PubMed Scopus Google Scholar, J. Mann M. and for and sample in Chem. PubMed Scopus Google Scholar, Mann M. for analysis of and clinical samples to a depth of PubMed Scopus Google Scholar). of into the of the system, a pump a gradient through the and the The system samples in only as as more than proteins from a HeLa cell in than G. Larsen N. liquid chromatography to for and quantification of protein and Proteome 2014; 13: PubMed Scopus Google Scholar). In with as on to of the in N.A. F. P. N. S. of proteomes and an Proteome PubMed Scopus Google Scholar). for protein the from and of only analytical columns chromatographic separation power of this In the we to the of the while also the features of this by through the to a workflow. In the Evosep One peptides are at and of of from a - termed the gradient with the are in a long loop. A single high-pressure pump the stored gradient to an analytical This in chromatographic separation performance while the to a gradient at high Thus, this the and robustness of high-flow systems with the sensitivity of column and of systems. further the of operation and of the Evosep in and and reproducibility in in MS-based The Evosep One single pumps and and high-pressure single pump they a and high-pressure pump is with a and to and the of the A at the of the pumps the for the system for The high-pressure pump a at for The only common is a storage which is to the high-pressure and is by a In this the high-pressure is to the analytical separation column but is the storage loop. In the is to but the storage loop. Thus, the storage the between the and high-pressure The steps are in the and in the the of an LC-MS the of a new LC-MS the of the Evosep One an disposable trap column with and with the at the In the pumps A and a gradient at the that through the disposable trap column, the of interest The of this gradient is to than to that only peptides of interest are the while as and highly to the disposable with from the Furthermore, the of this gradient is to few to and of the more This concept further in The C and D the at the to an to the gradient This the of the that the are on the analytical The gradient with the is into the storage before with the high-pressure pump. In to the the high-pressure pump is and the analytical column is the Evosep One the storage with the high-pressure pump and the gradient with the is the analytical column for high performance separation In to the LC-MS the Evosep One is for the sample by the disposable trap column, the and the the pumps and the of the pumps The to an LC and high in of the system, of the of an in the also in through the software the Evosep One before a sample HeLa were in high with and were an cell and stored at were in by at an of at a of in used to a that are to the of of human protein on for of human protein sample preparation we used the for proteomic samples (2Kulak N.A. Pichler G. Paron I. Nagaraj N. Mann M. Minimal, encapsulated proteomic-sample processing applied to copy-number estimation in eukaryotic cells.Nat. Methods. 2014; 11: 319-324Crossref PubMed Scopus (991) Google Scholar), with HeLa to the To and we and analyzed over times peptides of HeLa in this we used the of the Evosep One to a issues were and the system optimized the and in the the only for the of and software The HeLa samples were analyzed on a single column to in the system and the of the by a available and and for at to harvest from a with of the of the The plasma into a and with an sample preparation for Proteome as P.E. N.A. Pichler G. Holdt L.M. Teupser D. Mann M. proteome to human and 2016; 2: Full Text Full Text PDF PubMed Scopus Google Scholar). the as the and the peptides were analyzed with the 200 method with a 2 on a column μm particle for deep proteome analysis were fractionated a μm column on an high-pressure liquid chromatography system at A and were were separated by a gradient from to in by a to in min. In were without nano-flow the at per for the while from on an To the of as a of storage time in a storage we a to Evosep One operation as in A of pumps pump in in were to the This into a storage 100 a storage time a pump the of the at a rate of 2 a with a nano-flow cell to the at The storage and the pumps were to a to the a of a HeLa digest in with 100 of peptide and the on of the gradient were analyzed a Q Exactive to and targeted of the peptides in a used to between and reaction for of the peptides N. M. R. an for and targeted proteomics 26: PubMed Scopus Google Scholar). were from and for a were with 100 steps of in in by times in HeLa peptides were in in The optimized to for the to LC-MS of a Evosep One to an for the more than HeLa and the Evosep One to an Q Exactive HF-X for peptides were separated on the columns with μm and in the data were acquired with a data shotgun method and with a method for the Q Exactive HF-X the Q Exactive HF-X the for the MS in the with a time of and a of at of performed by with a of J.V. for peptide Methods. 4: PubMed Scopus Google Scholar). were performed at a of at 200 with an of and a time of to to of HeLa were at by with and 100 to the The cell by the and for an by for 2 with of on and at by and the with in an ratio of for by with to 2 and further with by with to a of and the peptide on with 2 of by 2 of The were and by and the peptide by at on a peptides were to MS analysis to the samples analyzed on the Evosep an μm column with μm while samples analyzed on the were separated in an μm column with the as The column at an column and with the mass MS were analyzed by the MaxQuant software (3Cox J. Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.Nat. Biotechnol. 2008; 26: 1367-1372Crossref PubMed Scopus (9154) Google Scholar) and lists were the human Proteome without with protein by the J. N. A. Olsen J.V. Mann M. a peptide into the MaxQuant Proteome Res,. PubMed Scopus Google Scholar) with as a and and as The for the 200 method analyzed with the from the of the discovery rate to at the peptide and protein and a of for as to and as and as and a of An mass to and a mass of were independent analysis were with A from the MaxQuant analysis of the analysis of the HeLa and were analyzed peptides and proteins by the software are available in and were with the software S. T. P. A. Hein M. T. Mann M. Cox J. The for comprehensive analysis of 2016; 13: PubMed Scopus Google Scholar) of the MaxQuant in as robust as high-flow LC to gradient from the high high-pressure separation on an analytical in established peptide the peptides are on of J. Mann M. and for and sample in Chem. PubMed Scopus Google of the peptides from the to the and in we elute from the into the loop. This is at pressures of only a few by pumps A and at of to Note that an entire gradient stored in a long - the peptides at the they elute from the a long of 100 μm a of for a analytical column separation of at at the gradient over time in the storage to liquid chromatography system for liquid Mass PubMed Scopus Google Scholar). the high ratio of column with in the this to in a storage in the system we not R. S. Cox J. D. Mann M. A chromatographic method allows of the Cell. Proteomics. 2008; Full Text Full Text PDF PubMed Scopus Google Scholar). To this we of and in the stored for and with a This not to that storage of in a is for established that an gradient and stored in a the to high chromatographic with the of an analytical A common in is peptides from the are not sufficiently on the analytical To this and to of the from the we a gradient the is with the system, a gradient from pumps A and the peptides from the the a gradient from pumps C and D the of the gradient and the the peptides from the are at the of the column and on the analytical column, this in the Note that to the and gradient the are on the column in a only a few of peptide is on the column at time with a of a of for a μm column which a of than generation of the the the storage with the high-pressure pump and the analytical column The high-pressure pump the and gradient with peptides over the analytical The that the is in the long of the and for at a of and To the Evosep One separation we a digest on an and in a 21 gradient from an analytical column μm μm This in and column injections that the are An of design is that the and steps that are between injections. the is also in the and than min. This the analysis time to close to gradient time that the allows a at the of the which further the time to of the peptides in the with this increases especially for while the and reproducibility issues of column F. N.A. Mann M. A liquid mass spectrometry system to per Cell. Proteomics. Full Text Full Text PDF PubMed Scopus Google Scholar). established the of we a that far as we leading as the and components were for throughput and robustness requirements in but for software we used the an and used with a to integrate with the MS To operation and we of a HeLa cell digest over times in a issues over time and the only to software In of the within the samples from sample to an of the and the In a we optimized the which in an of the between the and the of the as these issues were From issues to a new column to the concept in in injections. these samples the current the of the A few LC-MS were but this to to of the also the for the only a in that the column of and as further of the the of and were highly and in separation performance of the of were The Evosep One and for high throughput with a on clinical plasma is the most analyzed clinical with of samples is to plasma by of the of To demonstrate clinical of the system, we sample preparation - termed Proteome samples were and on the in a a The measurement time for the samples on the Evosep One than 2 to a throughput of samples per day. over sample and injections of the plasma of over clinical on the of is to from analysis to the we performed a with injections of plasma and The as as and of this to peptides on the and the from the robustness on the we the a of and column to ranging from high throughput of through comprehensive proteomics to the in depth single of complex The by the Evosep system used for complex samples and the longer for more complex Note that the design in the Evosep One also at in the current In common with in proteomics”, we to robustness and throughput over The of and columns with a of not sensitivity this by the sample through the in an optimized for to longer to the chromatographic performance of method a peptide into the complex of a HeLa reaction only the peptides a of proteomic From this data we and retention time for the peptides these data in for the optimized and column for the and sample to demonstrate the throughput on the and used the gradient with the 2 on the column In a single this in 200 data with protein coverage The proteins but of were this is this is not an of range. Furthermore, the proteins were quantified in of that the proteins were from the The high throughput for samples for single protein identification in for for analysis in protein expression in In also for more complex as from the of the system for samples in high we the rapid of high proteomics A is common in the analysis of cell line tissue but with the of a in time as the of on a strategy that high peptide in a without of the and D.B. Kelstrup C.D. Batth T.S. Larsen S.C. Haldrup C. Bramsen J.B. Sørensen K.D. Høyer S. Ørntoft T.F. Andersen C.L. Nielsen M.L. Olsen J.V. An optimized shotgun strategy for the rapid generation of comprehensive human proteomes.Cell Systems. 2017; 4: 587-599Abstract Full Text Full Text PDF PubMed Scopus (255) Google Scholar). to were analyzed in of allowing for high peptide and high and of the high acquisition of mass C.D. Batth T.S. Arrey T.N. A. M. Olsen J.V. and deep proteomes by on a mass Proteome 2014; 13: PubMed Scopus Google Scholar). This in a deep coverage of cell line and tissue on with D.B. Kelstrup C.D. Batth T.S. Larsen S.C. Haldrup C. Bramsen J.B. Sørensen K.D. Høyer S. Ørntoft T.F. Andersen C.L. Nielsen M.L. Olsen J.V. An optimized shotgun strategy for the rapid generation of comprehensive human proteomes.Cell Systems. 2017; 4: 587-599Abstract Full Text Full Text PDF PubMed Scopus (255) Google Scholar). A of the the of the mass to the and times of the which are with the Evosep To the for fractionated proteomes and to this to the used as a in laboratories as as in the we performed an analysis of HeLa on both systems. of the and on the and the Evosep One on the MS the time for and the of peptides and proteins The with optimized we used the 21 gradient of the method for the Evosep of the overhead time between the Evosep One significantly more in of of the mass A of the analysis time of on data acquisition In the the mass spectrometer for but only were This not at the of the of peptides and which with peptides and peptides for the Evosep One and the A of peptides in that they are This that the design of the Evosep One in measurement time in this at longer the time however, the high of mass they The that the Evosep is for the of proteomes the rapid analysis of the high that are used in we label-free quantitation the to also that an of proteins were in these There are proteomics strategies that as T. D. D. R. S. P. M. G. in by of the 2014; PubMed Scopus Google Scholar) proteomics S. Cox J. and of protein 2016; PubMed Scopus Google Scholar), and for strategies to rapidly and The far used data acquisition data independent acquisition is and R. Bernhardt OM Gandhi T Xuan Y Sondermann J Schmidt M Gomez-Varela D Reiter L Optimization of experimental parameters in data-independent mass spectrometry significantly increases depth and reproducibility of results.Mol. Cell. Proteomics. 2017; 16: 2296-2309Abstract Full Text Full Text PDF PubMed Scopus (189) Google Scholar). In we have to with on and high C.D. Bekker-Jensen D.B. Arrey T.N. Hogrebe A. Harder A. Olsen J.V. Performance evaluation of the Q Exactive HF-X for shotgun proteomics.J Proteome Res,. 2018; 17: 727-738Crossref PubMed Scopus (159) Google Scholar). The Evosep One with between to a to this strategy and we were to deep the proteome with a this we of the peptide in of the of HeLa the software with at both and protein in is a between the of peptide and the quantification of the time for a To we a and a method as in the 21 samples per the proteome coverage high for both with more than quantified proteins from more than This to unique proteins per gradient the the method in of with a of peptide and protein the and the the of proteins between and with and proteins in The method performed with to protein quantification with proteins with a than in the in the the of the proteome by data close to that the by the Evosep One with for high-throughput and acquisition of proteomic the great in high sensitivity nano-flow MS-based the robustness and throughput have weak even in of the MS-based proteomic This to a with a clinical at the of sensitivity M. I. C.L. proteomics sample preparation for mass Proteome 2018; 17: PubMed Scopus Google Scholar). we have an concept on the of at high-flow and This gradient the and is a column by a high-pressure pump. on these we a system that into a system - the Evosep established that of the by of the at the of the analytical column, chromatographic of the with the as a disposable sample the system is for sensitivity, and robustness - for clinical To we performed thousands of with cell as as complex clinical samples as that the of gradient with a system and the high-pressure peptide separation and operation without issues in chromatographic from the Evosep One to have and high of label-free quantitation injections.

Yeast remains an important model for systems biology and for evaluating proteomics strategies. In-depth shotgun proteomics studies have reached nearly comprehensive coverage, and rapid, targeted approaches have been developed for this organism. Recently, we demonstrated that single LC-MS/MS analysis using long columns and gradients coupled to a linear ion trap Orbitrap instrument had an unexpectedly large dynamic range of protein identification (Thakur, S. S., Geiger, T., Chatterjee, B., Bandilla, P., Frohlich, F., Cox, J., and Mann, M. (2011) Deep and highly sensitive proteome coverage by LC-MS/MS without prefractionation. Mol. Cell Proteomics 10, 10.1074/mcp.M110.003699). Here we couple an ultra high pressure liquid chromatography system to a novel bench top Orbitrap mass spectrometer (Q Exactive) with the goal of nearly complete, rapid, and robust analysis of the yeast proteome. Single runs of filter-aided sample preparation (FASP)-prepared and LysC-digested yeast cell lysates identified an average of 3923 proteins. Combined analysis of six single runs improved these values to more than 4000 identified proteins/run, close to the total number of proteins expressed under standard conditions, with median sequence coverage of 23%. Because of the absence of fractionation steps, only minuscule amounts of sample are required. Thus the yeast model proteome can now largely be covered within a few hours of measurement time and at high sensitivity. Median coverage of proteins in Kyoto Encyclopedia of Genes and Genomes pathways with at least 10 members was 88%, and pathways not covered were not expected to be active under the conditions used. To study perturbations of the yeast proteome, we developed an external, heavy lysine-labeled SILAC yeast standard representing different proteome states. This spike-in standard was employed to measure the heat shock response of the yeast proteome. Bioinformatic analysis of the heat shock response revealed that translation-related functions were down-regulated prominently, including nucleolar processes. Conversely, stress-related pathways were up-regulated. The proteomic technology described here is straightforward, rapid, and robust, potentially enabling widespread use in the yeast and other biological research communities. Yeast remains an important model for systems biology and for evaluating proteomics strategies. In-depth shotgun proteomics studies have reached nearly comprehensive coverage, and rapid, targeted approaches have been developed for this organism. Recently, we demonstrated that single LC-MS/MS analysis using long columns and gradients coupled to a linear ion trap Orbitrap instrument had an unexpectedly large dynamic range of protein identification (Thakur, S. S., Geiger, T., Chatterjee, B., Bandilla, P., Frohlich, F., Cox, J., and Mann, M. (2011) Deep and highly sensitive proteome coverage by LC-MS/MS without prefractionation. Mol. Cell Proteomics 10, 10.1074/mcp.M110.003699). Here we couple an ultra high pressure liquid chromatography system to a novel bench top Orbitrap mass spectrometer (Q Exactive) with the goal of nearly complete, rapid, and robust analysis of the yeast proteome. Single runs of filter-aided sample preparation (FASP)-prepared and LysC-digested yeast cell lysates identified an average of 3923 proteins. Combined analysis of six single runs improved these values to more than 4000 identified proteins/run, close to the total number of proteins expressed under standard conditions, with median sequence coverage of 23%. Because of the absence of fractionation steps, only minuscule amounts of sample are required. Thus the yeast model proteome can now largely be covered within a few hours of measurement time and at high sensitivity. Median coverage of proteins in Kyoto Encyclopedia of Genes and Genomes pathways with at least 10 members was 88%, and pathways not covered were not expected to be active under the conditions used. To study perturbations of the yeast proteome, we developed an external, heavy lysine-labeled SILAC yeast standard representing different proteome states. This spike-in standard was employed to measure the heat shock response of the yeast proteome. Bioinformatic analysis of the heat shock response revealed that translation-related functions were down-regulated prominently, including nucleolar processes. Conversely, stress-related pathways were up-regulated. The proteomic technology described here is straightforward, rapid, and robust, potentially enabling widespread use in the yeast and other biological research communities. Yeast is one of the most well established model systems in molecular biology. It is used to study a large range of conserved cellular processes, including the cell cycle, metabolism, and stress responses. Yeast was the first organism whose genome was sequenced completely (1Goffeau A. Barrell B.G. Bussey H. Davis R.W. Dujon B. Feldmann H. Galibert F. Hoheisel J.D. Jacq C. Johnston M. Louis E.J. Mewes H.W. Murakami Y. Philippsen P. Tettelin H. Oliver S.G. Life with 6000 genes.Science. 1996; 274 (546): 563-567Crossref Scopus (3282) Google Scholar), and many other systems-wide biology screens were first carried out in the yeast model (2Bader G.D. Heilbut A. Andrews B. Tyers M. Hughes T. Boone C. Functional genomics and proteomics: Charting a multidimensional map of the yeast cell.Trends Cell Biol. 2003; 13: 344-356Abstract Full Text Full Text PDF PubMed Scopus (95) Google Scholar, 3Jorgensen P. Breitkreutz B.J. Breitkreutz K. Stark C. Liu G. Cook M. Sharom J. Nishikawa J.L. Ketela T. 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S. spectrometry-based proteomics using a Orbitrap mass Full Text Full Text PDF PubMed Scopus Google the now The was in the with at a of at time to the top 10 most with from the were with an of and by J.V. B. O. A. S. Mann M. for peptide PubMed Scopus Google with of The ion times for the and the were and and the ion for were to of peptides was to a by dynamic of the sequenced peptides for The were using the proteomics J. Mann M. high peptide identification mass and protein Biotechnol. 2008; PubMed Scopus Google The were against the yeast of using the J. N. A. Olsen J.V. Mann M. into the Proteome Res. PubMed Scopus Google with the and mass to and and with to two of was as a and of and protein were as for Both peptide and protein were at discovery and were not on the peptide analysis was using the in the analysis and analysis of were with at a discovery of The are from the proteome with the to a shotgun proteomics with the possible number of and analysis and high Yeast were in the of and of protein The proteins were to peptides by using the J.R. A. N. Mann M. sample preparation for proteome 2009; PubMed Scopus Google Scholar), and the peptides were on J. Y. Mann M. and for and sample in 2003; PubMed Scopus Google Scholar). only and can be in hours and in for were then the of the system and in an by LC-MS/MS on the bench top Orbitrap mass spectrometer (Q Exactive) A. E. O. A. A. N. Cox J. Mann M. S. spectrometry-based proteomics using a Orbitrap mass Full Text Full Text PDF PubMed Scopus Google Scholar). The not use sample and The system is for and To of the proteome, we employed relatively long columns and This was by the a of at of the system is to at a and to columns more to a of the of a and gradients to be a for standard established the we six yeast cell an with and of peptide was the and with the analysis of the six LC-MS/MS in in an average of peptide with sequence for the single the runs on mass and retention time in to peptide single peptides were identified from this of total measurement peptides are on average than peptides and therefore more to the identification for runs were This is to the high mass by the high the proteins were identified the proteins were identified as and only of these had a single peptide and and and other the of the proteins identified with single the with an peptide of is high for a with the of the yeast proteome, and identified proteins. This that our not on study using a and the Orbitrap instrument identified under proteins in a T. B. P. F. Cox J. Mann M. Deep and highly sensitive proteome coverage by LC-MS/MS without Cell Full Text Full Text PDF PubMed Scopus Google Scholar). Here we to the complete expressed proteome a very and proteomic Median sequence coverage of identified proteins was with a median of peptide more peptides can be in MS plots than are sequenced and identified by tandem mass our the median of the was than that of the This that many more yeast peptides are present in the than are and not be to LC-MS/MS A. E. O. A. A. N. Cox J. Mann M. S. spectrometry-based proteomics using a Orbitrap mass Full Text Full Text PDF PubMed Scopus Google Scholar). key in shotgun proteomics is the to the absence of on proteins peptides in of the measurements of a and is by the of for in different of the we that a of the proteins were identified in six runs in and were identified in at least of the six This that for the of the is very the peptide is not as of the peptides are identified in at least of the six runs the single runs is a of the very high of the with the of peptides runs by To the of our we it against our in-depth study (14de Godoy L.M. Olsen J.V. Cox J. Nielsen M.L. Hubner N.C. Fröhlich F. Walther T.C. Mann M. Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast.Nature. 2008; 455: 1251-1254Crossref PubMed Scopus (744) Google Scholar). in the yeast versus different conditions and of the yeast genome in the of the here were in our the proteins not reported were identified in six of six runs in Yeast has that are as by the and these are not to a protein described (14de Godoy L.M. Olsen J.V. Cox J. Nielsen M.L. Hubner N.C. Fröhlich F. Walther T.C. Mann M. Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast.Nature. 2008; 455: 1251-1254Crossref PubMed Scopus (744) Google Scholar), this of a of identification The only identified two protein in on the of a we have expected in this of our coverage of the yeast one of the two was also in our study one of only in this that it not in be a that our is of and biological that are identified biological metabolic in a that the six runs identified of the as by the therefore at least this number is expressed as proteins in pathways and functions are not under conditions, and the proteins not be 88%, coverage of the proteins in the Kyoto Encyclopedia of Genes and Genomes was very high in the single yeast proteome, as was the coverage of the three and pathways of only a few we the analysis to pathways with 10 proteins coverage be without this the pathways with most proteins to and functions that are not expected to be active in haploid yeast in the number of identified we expected the proteome to have a large dynamic range of protein the peptide for the identified proteins of in the measurements multiple reaction monitoring study the of proteins to the range of the yeast protein expression from most to least protein (15Picotti P. Bodenmiller B. Mueller L.N. Domon B. Aebersold R. Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics.Cell. 2009; 138: 795-806Abstract Full Text Full Text PDF PubMed Scopus (649) Google Scholar). single proteome of these and the six proteins were in the of the proteins in the than were have been T. B. P. F. Cox J. Mann M. Deep and highly sensitive proteome coverage by LC-MS/MS without Cell Full Text Full Text PDF PubMed Scopus Google Scholar). these that our covered a large dynamic Bioinformatic analysis of in the most of the as the cell and functions the functions carried out by the most proteins. Cell functions are in and were in the SILAC has a standard and highly quantification in many the for metabolic from this in systems the for of on the are by a spike-in SILAC T. J.R. Cox J. S. M. Y. Mann M. of by in cell as a spike-in standard in PubMed Scopus Google Scholar). that a standard representing the proteome of is heavy lysine-labeled and as a across experiments can be as and the spike-in standard is in sample To a spike-in for yeast, we the in the was out by relatively of standard is for a large number of experiments It is to the standard so that it we also yeast under a different and a stress The spike-in was by three conditions in To quantification with the spike-in SILAC standard in conditions, we it into yeast under conditions in analyses identified yeast proteins This number is than in the experiments SILAC the of the peptide and the number of runs was these and were with two and three SILAC quantification in the The median number of was using a spike-in SILAC standard including conditions, the of the in these experiments was very with of the protein within a and analysis of the in values of at least of the in the now complete identification of the and cycle, and of as targeted in the multiple reaction monitoring study (15Picotti P. Bodenmiller B. Mueller L.N. Domon B. Aebersold R. Full dynamic range proteome analysis of S. cerevisiae by targeted proteomics.Cell. 2009; 138: 795-806Abstract Full Text Full Text PDF PubMed Scopus (649) Google Scholar). that the yeast spike-in SILAC the yeast proteome and that it well in quantification To the in a systems biology we to the heat shock This is a stress response in many studies O. G. D. Brown expression in the response of yeast to Biol. PubMed Scopus Google Scholar, B. E. Young of yeast genome expression in response to Biol. 2001; PubMed Scopus Google Scholar), in-depth proteomic study of this has been heat shock is an of experiments involving and it therefore be to heat shock the proteome. The heat shock was by the yeast from 24 to time at and after at The were with the spike-in standard and by single runs in analysis with the we identified proteins. The heat shock had an of proteins with the proteome in for proteins that had at least been at time and yeast proteins the of proteins with heat shock on a scale. these changes were as of by the of the to spike-in SILAC standard to heavy for and heat shock of the proteins with the to was shock protein is to be highly by heat shock as well as other stress a heat shock of of and PubMed Scopus Google Scholar). heat shock proteins were also including and and this group the changes the down-regulated we a group of proteins in and were down-regulated The changes of these proteins were and was by in we the global proteomics response using the that is of analysis of the at and and for multiple with a discovery of This proteins that were in expression than of these proteins were analysis of revealed the and as highly down-regulated the the to and were most The of the proteins for these are in and a we the in the is not heat not a heat of the down-regulated to the of proteins to metabolic are for and are down-regulated heat shock the and be expected to be and this is our analysis The is the for many of these and is to be a key of cellular stress S. B.J. S. The under 2010; Full Text Full Text PDF PubMed Scopus Google Scholar). analysis now proteins for this Here we have a proteomic only of preparation of yeast cell spike-in SILAC as the quantification single on a bench top mass spectrometer and analysis by the this technology very large coverage of the yeast proteome and analysis of a as stress