Nils A. Kulak

Circular RNAs (circRNAs) are broadly expressed in eukaryotic cells, but their molecular mechanism in human disease remains obscure. Here we show that circular antisense non-coding RNA in the INK4 locus (circANRIL), which is transcribed at a locus of atherosclerotic cardiovascular disease on chromosome 9p21, confers atheroprotection by controlling ribosomal RNA (rRNA) maturation and modulating pathways of atherogenesis. CircANRIL binds to pescadillo homologue 1 (PES1), an essential 60S-preribosomal assembly factor, thereby impairing exonuclease-mediated pre-rRNA processing and ribosome biogenesis in vascular smooth muscle cells and macrophages. As a consequence, circANRIL induces nucleolar stress and p53 activation, resulting in the induction of apoptosis and inhibition of proliferation, which are key cell functions in atherosclerosis. Collectively, these findings identify circANRIL as a prototype of a circRNA regulating ribosome biogenesis and conferring atheroprotection, thereby showing that circularization of long non-coding RNAs may alter RNA function and protect from human disease.

Proteins in the circulatory system mirror an individual's physiology. In daily clinical practice, protein levels are generally determined using single-protein immunoassays. High-throughput, quantitative analysis using mass-spectrometry-based proteomics of blood, plasma, and serum would be advantageous but is challenging because of the high dynamic range of protein abundances. Here, we introduce a rapid and robust "plasma proteome profiling" pipeline. This single-run shotgun proteomic workflow does not require protein depletion and enables quantitative analysis of hundreds of plasma proteomes from 1 μl single finger pricks with 20 min gradients. The apolipoprotein family, inflammatory markers such as C-reactive protein, gender-related proteins, and >40 FDA-approved biomarkers are reproducibly quantified (CV <20% with label-free quantification). Furthermore, we functionally interpret a 1,000-protein, quantitative plasma proteome obtained by simple peptide pre-fractionation. Plasma proteome profiling delivers an informative portrait of a person's health state, and we envision its large-scale use in biomedicine.

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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However, the expertise and analysis times associated with in-depth proteome measurements have so far precluded the widespread adoption of in-depth proteomics in the yeast research community. Targeted proteomics, in the form of multiple reaction monitoring, offers a possible solution to this problem and has recently been used to detect proteins throughout the dynamic range of the yeast proteome, as well as to quantify changes in key proteins after metabolic shift (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). However, targeted proteomics aims at the characterization of relatively few key proteins across many conditions, and it is therefore less well suited to the discovery of biological responses on a global scale. Both the multiple reaction monitoring experiments and analyses of the total features detectable in the MS retention time contour plots suggest that a very large number of peptides are present in LC-MS runs of total proteome digests (16Köcher T. Swart R. Mechtler K. Ultra-high-pressure RPLC hyphenated to an LTQ-Orbitrap Velos reveals a linear relation and number of identified PubMed Scopus Google Scholar, A. Cox J. Mann M. than detectable peptide in single shotgun proteomics runs the is to Proteome Res. PubMed Scopus Google Scholar). recently the dynamic range of single LC-MS/MS runs and that very proteins be in this 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). analysis without high only a few of peptides are to the to However, our study was with a and not be to for novel mass the a mass to the Orbitrap 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). this bench top are by the by J.V. B. O. A. S. Mann M. for peptide PubMed Scopus Google Scholar), and at high and mass in the Orbitrap times for a by to 10 are more than as as with of the Orbitrap Thus the offers the to many more peptides in a with very high to these with ultra used of in cell sample was not to in the of a developed system the we with relatively long columns and we this bench top and to the yeast proteome in high also in-depth ultra of in cell filter-aided sample preparation To quantify proteome in yeast, SILAC can be employed in the standard the and the conditions T.C. Olsen J.V. Mann M. Yeast expression proteomics by mass 2010; PubMed Scopus Google Scholar). To more systems analysis of perturbations of the yeast proteome, we to the SILAC metabolic from the experiments by using a 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). Here we developed a into proteome of then used this standard to quantify yeast proteome changes heat an important with and experiments B. Cell Cell Sci. 1999; PubMed Scopus Google Scholar, of yeast cell Cell Sci. 1999; PubMed Scopus Google Scholar). The yeast was in to phase and was by at 4000 for at The cell was in and The lysates were to for by using a for at the to complete The was at for to the protein The for heavy was by of the using the to C. N. C. S. H. A. G. E. E. M. for tagging of yeast more and 2004; PubMed Scopus Google Scholar). The were labeled only with heavy and not heavy to sample and to The spike-in standard was used to expression across different to phase in To biological conditions in the spike-in we also with as the as well as at for after at 24 three conditions were in to the spike-in This of be for thousands of spike-in experiments in measurements a few and hundreds of experiments with an fractionation J.R. A. Mann M. of and fractionation in-depth analysis of the proteome.J. Proteome Res. 2009; PubMed Scopus Google Scholar). Yeast was to phase to an of for at 24 in the and was to to and heat were at and after at to the proteome changes heat The were as described were using the J.R. A. N. Mann M. sample preparation for proteome 2009; PubMed Scopus Google Scholar). of protein was on the and was completely by two to three times with The proteins were then using and the was the The and proteins were using at the of with an to protein of by were using J. Y. Mann M. and for and sample in 2003; PubMed Scopus Google Scholar). The is a to at ultra high to The system two to gradients with to and pressure for are from the high pressure that can the The system is only two liquid by the the to the and a This and use is by a that to This with pressure of the use of long columns with linear of in the range of than the relatively high of to in our without ultra high pressure 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). were on a with with phase chromatography was using the with a system of and in The peptides were by a linear of to in for a with a of in the The was at a of by an with 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). The was coupled to a mass spectrometer 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 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