Nop9 is an RNA binding protein present in pre-40S ribosomes and required for 18S rRNA synthesis in yeast

Proteomic analyses in yeast have identified a large number of proteins that are associated with preribosomal particles. However, the product of the yeast ORF YJL010C, herein designated as Nop9, failed to be identified in any previous physical or genetic analysis of preribosomes. Here we report that Nop9 is a nucleolar protein, which is associated with 90S and 40S preribosomes. In cells depleted of Nop9p, early cleavages of the 35S pre-rRNA are inhibited, resulting in the nucleolar retention of accumulated precursors and a failure to synthesize 18S rRNA. Nop9 contains multiple pumilio-like putative RNA binding repeats and displays robust in vitro RNA binding activity. The identification of Nop9p as a novel, essential factor in the nuclear maturation of 90S and pre-40S ribosomal subunits shows that the complement of ribosome synthesis factors remains incomplete

Peptide Retention in Hydrophilic Strong Anion Exchange Chromatography Is Driven by Charged and Aromatic Residues

Hydrophilic strong anion exchange chromatography (hSAX) is becoming a popular method for the prefractionation of proteomic samples. However, the use and further development of this approach is affected by the limited understanding of its retention mechanism and the absence of elution time prediction. Using a set of 59 297 confidentially identified peptides, we performed an explorative analysis and built a predictive deep learning model. As expected, charged residues are the major contributors to the retention time through electrostatic interactions. Aspartic acid and glutamic acid have a strong retaining effect and lysine and arginine have a strong repulsion effect. In addition, we also find the involvement of aromatic amino acids. This suggests a substantial contribution of cation−π interactions to the retention mechanism. The deep learning approach was validated using 5-fold cross-validation (CV) yielding a mean prediction accuracy of 70% during CV and 68% on a hold-out validation set. The results of this study emphasize that not only electrostatic interactions but rather diverse types of interactions must be integrated to build a reliable hSAX retention time predictor

The Peptide MS/MS-Fragmentome: A Set of Predictable Fragment Ions with Highly Redundant Sequence Information

Upon low energy collision induced dissociation (CID), multiply protonated peptides generate a set of interdependent fragment ions detectable by MS/MS, the \u27[peptide]n+-fragmentome\u27. In particular dynamic fragmentation of [peptide]n+ ions in a collision cell generates information-rich MS/MS spectra. Currently, database-supported annotations of peptide MS/MS spectra are mainly based on a combination of peptide molecular weight and y type fragment ions, leaving a considerable number of good-quality peptide MS/MS spectra in proteomics studies unannotated. This situation may be improved by a more complete use of the structural information present in the [peptide]n+-fragmentome. The presentation provides an overview on the fragment ions of multiply protonated peptides and their connectivity, comprising a ions, b ions, y ions, and neutral loss reactions from the N-, and C-terminus, and internal b ions. In the low-mass region, the unique set of 19 y1 ions and of the 190 b2 ions carries a particular message, since these ions define the N-or C-terminal amino acid(s). Further, the b1 ions of the basic residues K, H, W, and R carry a specific N-terminal information, which is redundant to that contained in the corresponding b2 ions and in the N-terminal neutral loss peaks. Redundant information is also found in b and y ion series and in complementary b/y ion pairs. The latter are particularly abundant when generated by proline- or aspartate-induced backbone cleavages. From complementary b/y ion pairs the molecular weight of the precursor ion can be reconstructed to confirm or determine its molecular weight. This procedure is helpful in case a mixture of precursor ions is isolated or in case a precursor ion of very low abundance is isolated. Information about the precursor ion charge state is also delivered by precursor ion reconstruction using MS/MS data. In the analysis of covalently modified peptides, reporter ions are of particular importance. These ions can be used for mining of MS/MS data sets for the occurrence of selected modifications. Examples are presented for selected modifications, such as acetylation and phosphorylation. In phosphorylation analysis neutral loss reactions are highly important, and may also carry redundant information, when observed both from the molecular ion and from fragment ions. Search tools, which fully incorporate the current knowledge about the [peptide]n+-fragmentome will increase the scores of peptide/protein identifications by MS/MS and thus will increase the fraction of automatically assigned MS/MS spectra in proteomics studies

Rescuing error control in crosslinking mass spectrometry

Crosslinking mass spectrometry is a powerful tool to study protein-protein interactions under native or near-native conditions in complex mixtures. Through novel search controls, we show how biassing results towards likely correct proteins can subtly undermine error estimation of crosslinks, with significant consequences. Without adjustments to address this issue, we have misidentified an average of 260 interspecies protein-protein interactions across 16 analyses in which we synthetically mixed data of different species, misleadingly suggesting profound biological connections that do not exist. We also demonstrate how data analysis procedures can be tested and refined to restore the integrity of the decoy-false positive relationship, a crucial element for reliably identifying protein-protein interactions.</p

Proteomics of a fuzzy organelle: interphase chromatin

Chromatin proteins mediate replication, regulate expression and ensure integrity of the genome. So far, a comprehensive inventory of interphase chromatin has not been determined. This is largely due to its heterogeneous and dynamic composition, which makes conclusive biochemical purification difficult, if not impossible. As a fuzzy organelle it defies classical organellar proteomics and cannot be described by a single and ultimate list of protein components. Instead we propose a new approach that provides a quantitative assessment of a protein’s probability to function in chromatin. We integrate chromatin composition over a range of different biochemical and biological conditions. This resulted in interphase chromatin probabilities for 7635 human proteins, including 1840 previously uncharacterized proteins. We demonstrate the power of our large-scale data-driven annotation during the analysis of CDK regulation in chromatin. Quantitative protein ontologies may provide a general alternative to list-based investigations of organelles and complement Gene Ontology

Departmental seminar series and journal club with enhanced learning outcomes

Listening to scientific presentations and reading scientific literature are core activities of any scientist, and frequent components of students' curricula. When employing these activities in teaching, finding the right balance between student instruction and autonomous learning is important for best learning outcomes and teachers’ workload. We here present our course design for a coordinated lecture series and journal club, that finds this balance by leveraging modern learning concepts in a digital environment. Participating students were tasked to read a landmark scientific paper every week ahead of a lecture by a scientist with practical experience on the topic of that paper, often an author of that week’s paper. Students then had to hand in written answers to three questions probing their understanding of the topic and the paper. In a subsequent seminar, activating questions were discussed by the students in break-out rooms and then answered by randomly chosen students in class, followed by a broad discussion that included the homework questions. Students gave weekly feedback on their learning progress and experience, and the course was then dynamically adapted accordingly. This yielded a course with largely increased course capacity, reduced teachers’ workload, and substantially enhanced learning outcomes, qualitatively and quantitatively compared to previous implementations of the course