Analysis of the Proteome of Saccharomyces cerevisiae for Methylarginine

Arginine methylation is a post-translational modification that has been implicated in a plethora of cellular processes. In the present manuscript, using two antimethylarginine antibodies and combinatorial deletion mutants of arginine methyltransferases, we found evidence of widespread arginine methylation in the Saccharomyces cerevisiae proteome. Immunoprecipitation was used for enrichment of methylarginine-containing proteins, which were identified via tandem mass spectrometry. From this, we identified a total of 90 proteins, of which 5 were previously known to be methylated. The proteins identified were involved in known methylarginine-associated biological functions such as RNA processing, nuclear transport, carbohydrate metabolic process, GMP biosynthetic process and protein folding. Through in vivo methylation by the incorporation of [³H]-methyl groups, we validated the methylation of 7 proteins (Ded1, Imd4, Lhp1, Nop1, Cdc11, Gus1, Pob3). By LC–MS/MS, we then confirmed a total of 15 novel methylarginine sites on 5 proteins (Ded1, Lhp1, Nop1, Pab1, and Ugp1). By examination of methylation on proteins from the triple knockout of methyltransferases Hmt1, Hsl7, Rmt2, we present evidence for the existence of additional unidentified arginine methyltransferases in the Saccharomyces cerevisiae proteome

MethylQuant: A Tool for Sensitive Validation of Enzyme-Mediated Protein Methylation Sites from Heavy-Methyl SILAC Data

The study of post-translational methylation is hampered by the fact that large-scale LC–MS/MS experiments produce high methylpeptide false discovery rates (FDRs). The use of heavy-methyl stable isotope labeling by amino acids in cell culture (heavy-methyl SILAC) can drastically reduce these FDRs; however, this approach is limited by a lack of heavy-methyl SILAC compatible software. To fill this gap, we recently developed MethylQuant. Here, using an updated version of MethylQuant, we demonstrate its methylpeptide validation and quantification capabilities and provide guidelines for its best use. Using reference heavy-methyl SILAC data sets, we show that MethylQuant predicts with statistical significance the true or false positive status of methylpeptides in samples of varying complexity, degree of methylpeptide enrichment, and heavy to light mixing ratios. We introduce methylpeptide confidence indicators, MethylQuant Confidence and MethylQuant Score, and demonstrate their strong performance in complex samples characterized by a lack of methylpeptide enrichment. For these challenging data sets, MethylQuant identifies 882 of 1165 true positive methylpeptide spectrum matches (i.e., >75% sensitivity) at high specificity (<2% FDR) and achieves near-perfect specificity at 41% sensitivity. We also demonstrate that MethylQuant produces high accuracy relative quantification data that are tolerant of interference from coeluting peptide ions. Together MethylQuant’s capabilities provide a path toward routine, accurate characterizations of the methylproteome using heavy-methyl SILAC

MicroRNA Regulatory Mechanisms Play Different Roles in <i>Arabidopsis</i>

Plant microRNAs (miRNAs) operate by guiding the cleavage or translational inhibition of mRNA targets. They act as key gene regulators for development and environmental adaptation, and Dicer-partnering proteins DRB1 and DRB2 govern which form of regulation plays the dominant role. Mutation of <i>Drb1</i> impairs transcript cleavage, whereas mutation of <i>Drb2</i> ablates translational inhibition. Regulation of gene expression by miRNA-guided cleavage has been extensively studied, but there is much less information about genes regulated through miRNA-mediated translation inhibition. Here, we compared the proteomes of <i>drb1</i> and <i>drb2</i> mutants to gain insight into the indirect effect of the different miRNA regulatory mechanisms in <i>Arabidopsis thaliana</i>. Our results show that miRNAs operating through transcript cleavage regulate a broad spectrum of processes, including catabolism and anabolism, and this was particularly obvious in the fatty acid degradation pathway. Enzymes catalyzing each step of this pathway were upregulated in <i>drb1</i>. In contrast, DRB2-associated translational inhibition appears to be less ubiquitous and specifically aimed toward responses against abiotic or biotic stimuli

Proteomic Validation of Transcript Isoforms, Including Those Assembled from RNA-Seq Data

Human proteome analysis now requires an understanding of protein isoforms. We recently published the PG Nexus pipeline, which facilitates high confidence validation of exons and splice junctions by integrating genomics and proteomics data. Here we comprehensively explore how RNA-seq transcriptomics data, and proteomic analysis of the same sample, can identify protein isoforms. RNA-seq data from human mesenchymal (hMSC) stem cells were analyzed with our new TranscriptCoder tool to generate a database of protein isoform sequences. MS/MS data from matching hMSC samples were then matched against the TranscriptCoder-derived database, along with Ensembl and the neXtProt database. Querying the TranscriptCoder-derived or Ensembl database could unambiguously identify ∼450 protein isoforms, with isoform-specific proteotypic peptides, including candidate hMSC-specific isoforms for the genes DPYSL2 and FXR1. Where isoform-specific peptides did not exist, groups of nonisoform-specific proteotypic peptides could specifically identify many isoforms. In both the above cases, isoforms will be detectable with targeted MS/MS assays. Unfortunately, our analysis also revealed that some isoforms will be difficult to identify unambiguously as they do not have peptides that are sufficiently distinguishing. We covisualize mRNA isoforms and peptides in a genome browser to illustrate the above situations. Mass spectrometry data is available via ProteomeXchange (PXD001449)

Proteogenomic Discovery of a Small, Novel Protein in Yeast Reveals a Strategy for the Detection of Unannotated Short Open Reading Frames

In recent years, proteomic data have contributed to genome annotation efforts, most notably in humans and mice, and spawned a field termed “proteogenomics”. Yeast, in contrast with higher eukaryotes, has a small genome, which has lent itself to simpler ORF prediction. Despite this, continual advances in mass spectrometry suggest that proteomics should be able to improve genome annotation even in this well-characterized species. Here we applied a proteogenomics workflow to yeast to identify novel protein-coding genes. Specific databases were generated, from intergenic regions of the genome, which were then queried with MS/MS data. This suggested the existence of several putative novel ORFs of <100 codons, one of which we chose to validate. Synthetic peptides, RNA-Seq analysis, and evidence of evolutionary conservation allowed for the unequivocal definition of a new protein of 78 amino acids encoded on chromosome X, which we dub YJR107C-A. It encodes a new type of domain, which ab initio modeling suggests as predominantly α-helical. We show that this gene is nonessential for growth; however, deletion increases sensitivity to osmotic stress. Finally, from the above discovery process, we discuss a generalizable strategy for the identification of short ORFs and small proteins, many of which are likely to be undiscovered

A new link between transcriptional initiation and pre-mRNA splicing: The RNA binding histone variant H2A.B

<div><p>The replacement of histone H2A with its variant forms is critical for regulating all aspects of genome organisation and function. The histone variant H2A.B appeared late in evolution and is most highly expressed in the testis followed by the brain in mammals. This raises the question of what new function(s) H2A.B might impart to chromatin in these important tissues. We have immunoprecipitated the mouse orthologue of H2A.B, H2A.B.3 (H2A.Lap1), from testis chromatin and found this variant to be associated with RNA processing factors and RNA Polymerase (Pol) II. Most interestingly, many of these interactions with H2A.B.3 (Sf3b155, Spt6, DDX39A and RNA Pol II) were inhibited by the presence of endogenous RNA. This histone variant can bind to RNA directly <i>in vitro</i> and <i>in vivo</i>, and associates with mRNA at intron—exon boundaries. This suggests that the ability of H2A.B to bind to RNA negatively regulates its capacity to bind to these factors (Sf3b155, Spt6, DDX39A and RNA Pol II). Unexpectedly, H2A.B.3 forms highly decompacted nuclear subdomains of active chromatin that co-localizes with splicing speckles in male germ cells. H2A.B.3 ChIP-Seq experiments revealed a unique chromatin organization at active genes being not only enriched at the transcription start site (TSS), but also at the beginning of the gene body (but being excluded from the +1 nucleosome) compared to the end of the gene. We also uncover a general histone variant replacement process whereby H2A.B.3 replaces H2A.Z at intron-exon boundaries in the testis and the brain, which positively correlates with expression and exon inclusion. Taken together, we propose that a special mechanism of splicing may occur in the testis and brain whereby H2A.B.3 recruits RNA processing factors from splicing speckles to active genes following its replacement of H2A.Z.</p></div

H2A.B.3 can bind RNA <i>in vitro</i> and <i>in vivo</i>.

<p>(a) Total cellular lysates were prepared from UV treated mouse testes and treated with RNase I or not. H2A.B.3 was then immunoprecipitated and the co-immunoprecipitated proteins were identified by western blotting with the indicated antibodies selected to detect proteins involved in different aspects of RNA synthesis, processing, and export. (b) Amino acid sequence alignment of the N-terminal region of histone H2A and the variants H2A.Z, H2A.B.3, and H2A.B. Compared to H2A, the N-terminus of H2A.B.3 and H2A.B are 6.3% and 23.5% identical, respectively. The red box demarcates the sequences corresponding to the N-terminal peptides used for the pulldown experiments in panel d, and corresponds to the unstructured region (dashed line) preceding the first alpha helix of H2A (α1; orange box). Arginine residues are highlighted in blue. (c) Histone dimer samples (0.6, 1.1, 2.3, 4.5 μM) were incubated with 20 ng <i>in vitro</i> transcribed RNA (222 nt and 152 nt, top and bottom panels, respectively) and analysed on 5% acrylamide 1X TB gels. The asterisk (*) denotes shifted bands corresponding to H2A.B—H2B-RNA complexes. (d) An RNA pulldown assay using biotinylated histone N-terminal peptides (n-H2A, n-H2A.Z, n-H2A.B and n-H2A.B; 130 pmol). Samples were run on 15% TBE-Urea gels, along with input RNA (5 pmol; 3% of total input) for comparison. (e) CLIP assays demonstrating that H2A.B.3 but not H2A.Z directly interacts with RNA in germ cells. Also show is the western blot analysis of the immunoprecipitated H2A.B.3 and H2A.Z. Following the RNA—IP procedure (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006633#sec011" target="_blank">Methods</a>), cells isolated from 28–30 day old testes were UV crosslinked, the chromatin sheared and following the immunopurification of H2A.B.3-containing chromatin fragments, the released RNA was sequenced to yield 100 base pair paired end reads. (f) H2A.B.3 RNA plot ranked according to expression aligned with all intron—exon boundaries. (g) A H2A.B.3 RNA plot ranked according to the level of exon inclusion (20 to 80%) aligned with the intron—exon boundary of alternatively spliced exons.</p

RNA-binding proteins that co-immunoprecipitate with anti-H2A.B.3 but not with ant- H2A.Z antibodies.

<p>RNA-binding proteins that co-immunoprecipitate with anti-H2A.B.3 but not with ant- H2A.Z antibodies.</p

The incorporation of H2A.B.3 at alternatively spliced exons is positively correlated with the level of inclusion.

<p>(a) Normalised testis H2A.B.3 ChIP-Seq reads aligned with the intron—exon boundary ranked according to the level of inclusion of alternatively spliced exons (very low, 20%; low, 40%; medium, 60%; and high, 80%). (b) Normalised hippocampus H2A.B.3 ChIP-Seq reads aligned with the intron—exon boundary ranked according to the level of inclusion of alternatively spliced exons. (c) Normalised testis input reads aligned with the intron—exon boundary ranked according to the level of inclusion of alternatively spliced exons. (d) Normalised hippocampus input reads aligned with the intron—exon boundary ranked according to the level of inclusion of alternatively spliced exons. (e) Normalised testis H2A.Z ChIP-Seq reads aligned with the intron—exon boundary ranked according to the level of inclusion of alternatively spliced exons. (f) Normalised hippocampus H2A.Z ChIP-Seq reads aligned with the intron—exon boundary ranked according to the level of inclusion of alternatively spliced exons.</p

H2A.B.3 replaces H2A.Z on the coding region of active genes.

<p>(a) Normalized testis H2A.Z ChIP-Seq reads ranked according to their expression level (repressed, low, medium and high) aligned with the intron—exon boundary. (b) Normalized hippocampus H2A.Z ChIP-Seq reads ranked according to their expression level aligned with the intron—exon boundary. (c) Normalised testis H2A.Z ChIP-Seq reads ranked according to the incorporation of histone H3 trimethyl K36 (very low, low, medium and high) aligned with the intron—exon boundary. (d) Quantitative H2A.B.3 and H2A.Z ChIP assays were performed in the testis at three exons for each of three individual genes (<i>Akap4</i>, <i>Il2rg</i> and <i>Akap14</i>) located on the X chromosome that are repressed at day 18 (the pachytene stage) but activated at day 30 (the late round spermatid stage). Standard deviation of three replicates is shown. (e) Quantitative H2A.B.3 and H2A.Z ChIP assays were performed in the hippocampus at an exon and its neighbouring intronic sequences for genes that are expressed more highly in the brain (<i>Ctnnd2</i>, <i>Mpped1</i> and <i>Ctnn1</i>) versus the testis (a brain to testis expression ratio of 27.1, 17.4 and 75.4, respectively). Standard deviation of three replicates is shown. (f) Quantitative H2A.B.3 and H2A.Z ChIP assays were performed in the testis at an exon and its neighbouring intronic sequences for genes that are expressed more highly in the testis (<i>Pkib</i>, <i>Tbata</i> and <i>Slain2</i>) versus the brain (a testis to brain expression ratio of 7.3, 23.4 and 22.2, respectively). Standard deviation of three replicates is shown.</p