Quantitative Analysis of Modified Proteins and Their Positional Isomers by Tandem Mass Spectrometry: Human Histone H4

Here we show that fragment ion abundances from dissociation of ions created from mixtures of multiply modified histone H4 (11 kDa) or of N-terminal synthetic peptides (2 kDa) correspond to their respective intact ion abundances measured by Fourier transform mass spectrometry. Isomeric mixtures of modified forms of the same protein are resolved and quantitated with a precision of ≤5% using the relative ratios of their fragment ions, with intact protein ions created by electrospray greatly easing many of the systematic biases that more strongly affect small peptides (e.g., differences in ionization efficiency and ion m/z values). The ion fragmentation methods validated here are directly extensible to intact human proteins to derive quantitative information on the highly related and often isomeric protein forms created by combinatorial arrays of posttranslational modifications

Tissue-Specific Expression and Post-Translational Modification of Histone H3 Variants

Analyses of histone H3 from 10 rat tissues using a Middle Down proteomics platform revealed tissue-specific differences in their expression and global PTM abundance. ESI/FTMS with electron capture dissociation showed that, in general, these proteins were hypomodified in heart, liver and testes. H3.3 was hypermodified compared to H3.2 in some, but not all tissues. In addition, a novel rat testes-specific H3 protein was identified with this approach

Precise Characterization of Human Histones in the H2A Gene Family by Top Down Mass Spectrometry

Top Down analysis revealed that at least fourteen genes encoding histone H2A are coexpressed in HeLa cells. Characterization of these species revealed that all except H2A.Z and H2A.F/Z were α-N-acetylated, H2A.O and H2A.C,D,I,N,P were the most abundant, and those exceeding ∼10% abundance lacked post-translational modifications. This unequivocal identification of H2A forms illustrates the advantages of Top Down Mass Spectrometry and provides a global perspective of H2A regulation through the cell cycle. Keywords: histone H2A • Fourier transform mass spectrometry (FTMS) • Top Down • post-translational modification (PTM) • SILAC • cell cycle • ubiquitination • electron capture dissociation (ECD) • histone code • chromati

Gene-Specific Characterization of Human Histone H2B by Electron Capture Dissociation

The basis set of protein forms expressed by human cells from the H2B gene family was determined by Top Down Mass Spectrometry. Using Electron Capture Dissociation for MS/MS of H2B isoforms, direct evidence for the expression of unmodified H2B.Q, H2B.A, H2B.K/T, H2B.J, H2B.E, H2B.B, H2B.F, and monoacetylated H2B.A was obtained from asynchronous HeLa cells. H2B.A was the most abundant form, with the overall expression profile not changing significantly in cells arrested in mitosis by colchicine or during mid-S, mid-G2, G2/M, and mid-G1 phases of the cell cycle. Modest hyperacetylation of H2B family members was observed after sodium butyrate treatment. Keywords: histone • chromatin • post-translational modifications • top down mass spectrometry • electron capture dissociatio

Interpreting Top-Down Mass Spectra Using Spectral Alignment

Recent advances in mass spectrometry instrumentation, such as FTICR and OrbiTrap, have made it possible to generate high-resolution spectra of entire proteins. While these methods offer new opportunities for performing “top-down” studies of proteins, the computational tools for analyzing top-down data are still scarce. In this paper we investigate the application of spectral alignment to the problem of identifying protein forms in top-down mass spectra (i.e., identifying the modifications, mutations, insertions, and deletions). We demonstrate how spectral alignment efficiently discovers protein forms even in the presence of numerous modifications and how the algorithm can be extended to discover positional isomers from spectra of mixtures of isobaric protein forms

The transcription factor <i>ultraspiracle (usp)</i> influences honey bee behavioral maturation.

<p>A) Knockdown of <i>usp</i> mRNA in the fat bodies of 3-day-old bees, 72 h after injection with dsUSP or control dsRNA (ds-pUC). qPCR; n = 10 bees; t-test: * P<0.05. B) <i>usp</i> RNAi does not knock down <i>usp</i> mRNA in the heads of these same bees. C) Knockdown of USP protein in the fat bodies 48, 72 and 96 h after injection was confirmed by immunoblotting with an antibody specific to honey bee USP (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596.s003" target="_blank">Figure S3</a>). D) <i>usp</i> RNAi delays the age at onset of foraging. Pooled results from 9 independent trials. Cox Proportional Hazards: P = 0.03. Numbers in legend indicate how many bees were measured for each group.</p

<i>cis</i>-regulatory sequences predict behaviorally-related responses of USP targets.

<p>A. The GRCACGCKVS motif enriched at USP binding sites (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen-1002596-g002" target="_blank">Figure 2C</a>) matches a Juvenile Hormone Response Element (JHRE) recognized by MET (and other bHLH TFs) <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Li1" target="_blank">[24]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Li2" target="_blank">[61]</a>. B. Predicted binding sites of USP and MET (the GGGGTCACS and GRCACGCKVS motifs, respectively) were consistently overlapping, with start positions located 3 bp apart. All adjacent pairs of Patser-predicted matches to these motifs in USP-binding loci (ChIP peaks) were considered; shown is the histogram of spacing between start positions of each pair, with negative numbers indicating that the MET site is on the left. Inset shows a zoomed-in view of the histogram for spacings in the range of 1–10 bp. C. Spacing constraints between sites of GGGGTCACS (USP) and potential cofactor motifs. Each of the 10 most significantly overrepresented motifs in USP-binding loci was tested for a constraint on spacing (< = 25 bp vs. >25 bp) between sites for USP and that motif. The Y-axis shows the −log10 of the p-value of this test, at five different statistical thresholds (X-axis) for defining motif matches.</p

Model for <i>usp</i> regulation of behavioral maturation.

<p>According to this model, USP mediates responses to JH as part of a complex of proteins – pre-assembled at the promoters of JH-responsive genes – that likely includes USP, MET, EcR, Chd64, and FKBP39; all of these TFs have been shown to physically interact with one another <i>in vitro </i><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Li1" target="_blank">[24]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Bitra1" target="_blank">[64]</a>. Low JH titers (nurse bees) lead to target gene repression. High JH titers (foragers) cause target gene activation. This might occur via ligand-dependent conformational changes in the protein complex and recruitment of general transcriptional machinery, both of which are known for USP in other contexts <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Mangelsdorf1" target="_blank">[53]</a> (not shown). JH most likely binds MET, the only TF in this complex known to have strong affinity for JH <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Miura1" target="_blank">[63]</a>. The model also suggests the presence of a feed-forward loop <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Davidson1" target="_blank">[10]</a> that stabilizes responses to JH; this role could be played by two components of the JH signaling complex – <i>usp</i> and <i>Chd64</i> – themselves USP targets. Other TFs among USP targets – including TFs previously implicated in JH signaling such as <i>E75</i> and <i>Hr46 </i><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Riddiford1" target="_blank">[25]</a> – are available to propagate these responses to indirect targets of USP and JH. This model can explain differential gene expression caused by both USP and JH despite the fact that USP was found to bind the same genomic locations in the fat bodies of nurses and foragers. It also is consistent with findings that these genomic locations are enriched for two very closely located (3 bp apart) <i>cis</i>-regulatory motifs, one recognized by USP and the other recognized by bHLH TFs, including MET.</p

Putative direct and indirect targets of USP in honey bee fat bodies.

<p>Putative targets of USP in the fat bodies were characterized both by <i>usp</i> RNAi—deep mRNA sequencing (in combination with juvenile hormone analog, JHA, treatments) as well as by USP ChIP-chip with fat body tissue samples from nurses and from foragers. A. Genomic regions surrounding two putative target genes, the transcription factors <i>SoxNeuro</i> and <i>Hr46</i>. Units for mRNA-seq are read counts, and for ChIP-chip the ratio of a-USP to control. B. Venn diagram shows that many USP target genes identified by <i>usp</i> RNAi and USP ChIP-chip are differentially expressed between nurses and foragers (“Maturation”). Fold enrichment of overlap and its significance (hypergeometric test) are indicated for each comparison. C. The 1360 genomic binding sites of USP are enriched for conserved <i>cis</i>-regulatory sequences, putatively recognized by the TFs shown at left. D. USP binds genomic locations near 67 transcription factors (TFs), including members of the nuclear hormone receptor family (diamonds) and other TF families (circles). Some of these TFs were differentially expressed between nurses and foragers (blue, higher in nurse; yellow, higher in forager), and predicted targets for several of these TFs based on transcriptional regulatory network analysis <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Chandrasekaran1" target="_blank">[20]</a> were enriched for genes that are differentially expressed in maturation-related contexts (thick outlines). Some of these TFs were also identified as USP targets in <i>D. melanogaster </i><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002596#pgen.1002596-Gauhar1" target="_blank">[55]</a> (red lines), and some binding sites contain the GGGGTCACS cis-regulatory sequence recognized by USP in <i>D. melanogaster</i> (solid lines).</p

Transcriptional co-expression analysis reveals that maturation involves overlapping, hormonally regulated gene modules in the fat bodies and brain.

<p>A. CoherentCluster revealed 85 maturation-related “coherent” gene modules that were preserved between the fat bodies and brain (colored circles). These modules were enriched for genes that were differentially expressed between nurses in foragers in either the fat bodies, the brain, or both, as indicated by Venn Diagram categories. The number within each circle indicates the number of genes in the module; a bold outline indicates that the module contains at least one TF; underlined numbers indicate modules containing at least one <i>usp</i>-related gene (identified empirically by either RNAi or ChIP-chip experiments). Circles are colored based on their enrichment (P<0.05) for genes that are differentially expressed in response to <i>usp</i> RNAi, <i>vg</i> RNAi, or JHA. One module (f-15-2-1) is selected for demonstration (inset). Nodes in this inset represent individual genes, and edges indicate co-expression. Yellow nodes indicate genes that were responsive to (all three of) <i>usp</i> RNAi, <i>vg</i> RNAi, and JHA in the fat bodies. In addition, we show enriched Gene Ontology processes for genes within this module. B. Hormones regulate the expression of genes within many coherent modules. Left: contingency table for the number of coherent modules that were enriched for maturationally-regulated genes and for hormonally-regulated genes (USP targets, JHA-responsive genes, and Vg RNAi–responsive genes). Right: Proportion of coherent modules and of fat body-specific modules that were enriched for JHA-responsive genes and Vg RNAi-responsive genes.</p