Addressing Statistical Biases in Nucleotide-Derived Protein Databases for Proteogenomic Search Strategies

Proteogenomics has the potential to advance genome annotation through high quality peptide identifications derived from mass spectrometry experiments, which demonstrate a given gene or isoform is expressed and translated at the protein level. This can advance our understanding of genome function, discovering novel genes and gene structure that have not yet been identified or validated. Because of the high-throughput shotgun nature of most proteomics experiments, it is essential to carefully control for false positives and prevent any potential misannotation. A number of statistical procedures to deal with this are in wide use in proteomics, calculating false discovery rate (FDR) and posterior error probability (PEP) values for groups and individual peptide spectrum matches (PSMs). These methods control for multiple testing and exploit decoy databases to estimate statistical significance. Here, we show that database choice has a major effect on these confidence estimates leading to significant differences in the number of PSMs reported. We note that standard target:decoy approaches using six-frame translations of nucleotide sequences, such as assembled transcriptome data, apparently underestimate the confidence assigned to the PSMs. The source of this error stems from the inflated and unusual nature of the six-frame database, where for every target sequence there exists five “incorrect” targets that are unlikely to code for protein. The attendant FDR and PEP estimates lead to fewer accepted PSMs at fixed thresholds, and we show that this effect is a product of the database and statistical modeling and not the search engine. A variety of approaches to limit database size and remove noncoding target sequences are examined and discussed in terms of the altered statistical estimates generated and PSMs reported. These results are of importance to groups carrying out proteogenomics, aiming to maximize the validation and discovery of gene structure in sequenced genomes, while still controlling for false positives

Analysis of Intrinsic Peptide Detectability via Integrated Label-Free and SRM-Based Absolute Quantitative Proteomics

Quantitative mass spectrometry-based proteomics of complex biological samples remains challenging in part due to the variability and charge competition arising during electrospray ionization (ESI) of peptides and the subsequent transfer and detection of ions. These issues preclude direct quantification from signal intensity alone in the absence of a standard. A deeper understanding of the governing principles of peptide ionization and exploitation of the inherent ionization and detection parameters of individual peptides is thus of great value. Here, using the yeast proteome as a model system, we establish the concept of peptide F-factor as a measure of detectability, closely related to ionization efficiency. F-factor is calculated by normalizing peptide precursor ion intensity by absolute abundance of the parent protein. We investigated F-factor characteristics in different shotgun proteomics experiments, including across multiple ESI-based LC–MS platforms. We show that F-factors mirror previously observed physicochemical predictors as peptide detectability but demonstrate a nonlinear relationship between hydrophobicity and peptide detectability. Similarly, we use F-factors to show how peptide ion coelution adversely affects detectability and ionization. We suggest that F-factors have great utility for understanding peptide detectability and gas-phase ion chemistry in complex peptide mixtures, selection of surrogate peptides in targeted MS studies, and for calibration of peptide ion signal in label-free workflows. Data are available via ProteomeXchange with identifier PXD003472

Slf1p associates with ribosomes independently of the La motif.

<p>(<b>A</b>) Western blotting of fractions isolated from polyribosome gradients are shown for strains expressing <i>SLF1</i>, ΔN+, ΔLaM and ΔM mutants. (<b>B</b>) As (A) but with RNAse I treated extracts.</p

Slf1p and Sro9p are required for growth under oxidative stress conditions.

<p>(<b>A</b>) Growth of the wild-type, <i>slf1Δ</i> and <i>sro9Δ</i> mutant strains on the indicated media for 3 days at 30°C. (<b>B</b>) Scatterplot comparing the mRNA targets identified by Slf1p-RIP Seq under control conditions (green) compared with 15 minutes of treatment with 0.4 mM Hydrogen peroxide (blue). ORFs identified under both conditions are indicated (red). The numbers of ORFs present in each group are shown (<b>C</b>) Functional categorisation of those mRNAs that are enriched in the Slf1p RIP Seq after peroxide treatment. Category classification is presented, as described in the legend to <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004903#pgen-1004903-g001" target="_blank">Fig. 1</a>. (D) 3′ UTR motifs of mRNAs bound by Slf1p in the presence and absence of hydrogen peroxide identified using the MEME Suite <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004903#pgen.1004903-Bailey1" target="_blank">[43]</a>.</p

Slf1p is associated with actively translating ribosomes during oxidative stress conditions.

<p>(<b>A</b>) Polyribosomal profiles of the <i>slf1</i>Δ and wild-type strains before or after hydrogen peroxide treatments for 15 min. (<b>B</b>) Quantification of the ratio of ribosomes in monosomes (80S) to Polysomes (M:P) over a 0–1 mM range of hydrogen peroxide concentrations. The polyribosomal profiles which were used to generate this data are shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004903#pgen.1004903.s006" target="_blank">S6 Fig</a>. (<b>C</b>) Ribosome-association of both Slf1p-TAP and Sro9p in fractions isolated from sucrose gradients of an Slf1p-TAP tagged strain. Cultures were treated with 0.4 mM hydrogen peroxide for 15 minutes or with EDTA as shown.</p

Slf1p is required for oxidative stress gene expression during oxidative stress conditions.

<p>(<b>A</b>) The fold-enrichment change is shown for those proteins identified as increasing or decreasing in the wild-type after peroxide treatment compared with the <i>slf1Δ</i> mutant. All proteins on the scatter plot were found to significantly alter in abundance (FDR<0.05) in the wild-type strain following oxidative stress (315 proteins; 249 up and 66 down). Proteins encoded by Slf1p target mRNAs are indicated as red and yellow dots. These include proteins which form part of the oxidative stress response according to MIPS (red dots) as well as proteins which are not directly involved in the oxidative stress response (yellow dots, for details see text). Proteins which form part of the oxidative stress response but are not direct Slf1p targets are shown as blue dots. The dotted line shows the trend-line that would be expected if there was no difference between the wild-type and <i>slf1Δ</i> mutant. (<b>B</b>) Diagrammatic representation of the oxidative stress response highlighting changes in the <i>slf1Δ</i> strain. Hydrogen peroxide (H₂O₂) is generated by the breakdown of superoxide (O₂^.-) catalysed by superoxide dismutases (SOD). Hydrogen peroxide can be reduced by iron (Fe2+) in the Fenton reaction to produce the highly reactive hydroxyl radical (^.OH). Various antioxidant enzymes are involved in the defence against hydrogen peroxide including peroxidases, peroxiredoxins (Prx), glutathione peroxidases (Gpx), glutathione transferases (GST), glutaredoxins (Grx), thioredoxins (Trx), glutathione reductase (Glr), thioredoxin reductase (Trr) and glutathione (GSH). mRNAs bound by Slf1p where protein induction is attenuated in the <i>slf1Δ</i> are in red (corresponding to red dots in Fig. 6A), mRNAs bound by Slf1p where the corresponding protein was not detected in the <i>slf1Δ</i> are in green and mRNAs which are not bound by Slf1p, but where protein induction is attenuated in the <i>slf1Δ</i> are in blue (corresponding to blue dots in Fig. 6A).</p

Comparison of Slf1p and Sro9p target mRNAs.

<p>(<b>A</b>) A scatterplot comparing the mRNA targets identified in the Slf1p (green), Sro9p (blue) or in both (red) Rip-Seq experiments. The number of ORFs identified as unique to Slf1p or Sro9p or in both are indicated. (<b>B</b>) MIPS Functional categorisation of Slf1p and Sro9p target mRNA enrichment. (<b>C</b>) Slf1p maintains steady state levels of its mRNA targets. Transcript abundance of the whole transcriptome and target mRNAs of Slf1p (Left) or Sro9p (Right) were analysed as described in the legend to <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004903#pgen-1004903-g001" target="_blank">Fig. 1A</a>. Slf1p and Sro9p targets were filtered (FDR<0.05). The x axis of the graph has been restricted to show only those data that are in bins between 3 and -3. (<b>D</b>) Translation efficiency <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004903#pgen.1004903-Subtelny1" target="_blank">[16]</a> of mRNAs bound in each IP and the total RNA. Outliers are shown (open circles) and samples with a P<2.2 -e16 (Wilcoxon rank) are indicated (asterisk).</p

Identification of 4E-BP associating proteins using TAP-tag IPs.

<p>A. Western blots of the TAP IPs, lanes 1–9 show input, flowthrough and eluates for the IP strains and lanes 10–13 show the eluates of the 4E-BPs with and without RNase I digestion. Blots were probed with the α Protein A peroxidase (PAP) antibody (detects the TAP-tag), αCaf20p, αeIF4E, αeIF4G and αRps3p to highlight IP efficiency and maintenance of previously published associations. B. Proportional Venn-style diagram depicting the overlaps between proteins associating with the 4E-BPs. C. Gene Ontology classes statistically overrepresented within 4E-BP associated proteins at indicated FDR significance. Only a representative selection of the significant functional categories is shown D. Western blots from reciprocal TAP IPs of a selection of RNA-binding proteins identified as interacting with the 4E-BPs probed with the indicated antibodies. E. Effect of RNase I digestion on protein interactions identified in D.</p

Models for 4E-DEP and 4E-IND Caf20p-mediated translational repression.

<p>A. Active translation. Short mRNA (blue line with grey ORF) shown with eIF4E (purple) bound to 5’cap (blue), eIF4G (blue oval) and Pab1p (green oval) facilitating mRNA circularisation and ribosome recruitment (cream ovals) that excludes Caf20p binding eIF4E. B. Caf20p mediated eIF4E-dependent translational repression. eIF4E/4G/Pab1p closed loop unstable on long mRNAs facilitating Caf20p binding (red). Caf20p binding to 80S ribosomes may contribute to its local recruitment. C. 4E-IND repression mechanisms. Caf20p 3’ UTR motif binding (may not be direct), either alone or in addition to 80S binding facilitates translational repression. eIF4E-Caf20p binding may contribute to repression on some of these mRNAs.</p

4E-BPs associate with translating ribosomes in an eIF4E-independent manner.

<p>A. Sucrose density gradient analysis of extracts from the Eap1-TAP strain. Fractions were collected and protein distribution across the gradients visualised with western blots. Blots were probed for the 4E-BPs, closed loop components and 40S/60S ribosomal subunits. B. Western blot analyses of fractions collected from sucrose density gradients of extracts from the Eap1-TAP strain. The 80S ribosomal complex was dissociated by removal of cycloheximide and MgCl₂ from the lysis buffer. Blots were probed for the 4E-BPs, closed loop components and 40S/60S ribosomal subunits. C. Western blot analysis of fractions collected from a sucrose density gradient of extract from the BY4741 <i>HIS3</i> strain GP6001. The lysate was pre-treated with RNase I. D. Western blot analysis of fractions collected from a sucrose density gradient of extracts from the BY4741 <i>HIS3</i> strain which had been grown in SCD-HIS and resuspended in SC-HIS for 10 min prior to cycloheximide treatment. E. Western blot analysis of FLAG immune-purification of whole cell extracts from <i>caf20Δ</i> strains harbouring an empty vector [pRS426], p[<i>CAF20-FLAG</i>] or p[<i>CAF20</i>^<i>m2</i>-<i>FLAG</i>]. F. Western blot analysis of fractions collected from sucrose density gradients of extracts from the p[<i>CAF20-FLAG</i>] and p[<i>CAF20</i>^<i>m2</i>-<i>FLAG</i>] strains.</p