A Novel 3-Methylhistidine Modification of Yeast Ribosomal Protein Rpl3 Is Dependent upon the YIL110W Methyltransferase

We have shown that Rpl3, a protein of the large ribosomal subunit from baker''s yeast (Saccharomyces cerevisiae), is stoichiometrically monomethylated at position 243, producing a 3-methylhistidine residue. This conclusion is supported by top-down and bottom-up mass spectrometry of Rpl3, as well as by biochemical analysis of Rpl3 radiolabeled in vivo with S-adenosyl-l-[methyl-³H]methionine. The results show that a +14-Da modification occurs within the GTKKLPRKTHRGLRKVAC sequence of Rpl3. Using high-resolution cation-exchange chromatography and thin layer chromatography, we demonstrate that neither lysine nor arginine residues are methylated and that a 3-methylhistidine residue is present. Analysis of 37 deletion strains of known and putative methyltransferases revealed that only the deletion of the YIL110W gene, encoding a seven β-strand methyltransferase, results in the loss of the +14-Da modification of Rpl3. We suggest that YIL110W encodes a protein histidine methyltransferase responsible for the modification of Rpl3 and potentially other yeast proteins, and now designate it Hpm1 (Histidine protein methyltransferase 1). Deletion of the YIL110W/HPM1 gene results in numerous phenotypes including some that may result from abnormal interactions between Rpl3 and the 25 S ribosomal RNA. This is the first report of a methylated histidine residue in yeast cells, and the first example of a gene required for protein histidine methylation in nature.     

Detection of two distinct forms of apoC-I in great apes

ApoC-I, the smallest of the soluble apolipoproteins, associates with both TG-rich lipoproteins and HDL. Mass spectral analyses of human apoC-I previously had demonstrated that in the circulation there are two forms, either a 57 amino acid protein or a 55 amino acid protein, due to the loss of two amino acids from the N-terminus. In our analyses of the apolipoproteins of the other great apes by mass spectrometry, four forms of apoC-I were detected. Two of these showed a high degree of identity to the mature and truncated forms of human apoC-I. The other two were homologous to the virtual protein and its truncated form that are encoded by a human pseudogene. In humans, the genes for apoC-I and its pseudogene are located on chromosome 19, the pseudogene being 2.5 kb downstream from the apoC-I gene. Based on the similarity between the apoC-I gene and the pseudogene, it has been concluded that the latter arose from the former as a result of gene duplication approximately 35 Mya. Interestingly, the virtual protein encoded by the pseudogene is acidic, not basic like apoC-I. In the chimpanzee, there also are two genes for apoC-I, the one upstream encodes a basic protein and the downstream gene, rather than being a pseudogene, encodes an acidic protein (P86336). In addition to reporting on the molecular masses of great ape apoC-I, we were able to clearly demonstrate by “Top-down” sequencing that the acidic form arose from a separate gene. In our analyses, we have measured the molecular masses of apoC-I associated with the HDL of the following great apes: bonobo (Pan paniscus), chimpanzee (Pan troglodytes), and the Sumatran orangutan (Pongo abelii). Genomic variations in chromosome 19 among great apes, baboons and macaques as they relate to both genes for apoC-I and the pseudogene are compared and discussed.     

Deconvolution and Database Search of Complex Tandem Mass Spectra of Intact Proteins: A COMBINATORIAL APPROACH*

Top-down proteomics studies intact proteins, enabling new opportunities for analyzing post-translational modifications. Because tandem mass spectra of intact proteins are very complex, spectral deconvolution (grouping peaks into isotopomer envelopes) is a key initial stage for their interpretation. In such spectra, isotopomer envelopes of different protein fragments span overlapping regions on the m/z axis and even share spectral peaks. This raises both pattern recognition and combinatorial challenges for spectral deconvolution. We present MS-Deconv, a combinatorial algorithm for spectral deconvolution. The algorithm first generates a large set of candidate isotopomer envelopes for a spectrum, then represents the spectrum as a graph, and finally selects its highest scoring subset of envelopes as a heaviest path in the graph. In contrast with other approaches, the algorithm scores sets of envelopes rather than individual envelopes. We demonstrate that MS-Deconv improves on Thrash and Xtract in the number of correctly recovered monoisotopic masses and speed. We applied MS-Deconv to a large set of top-down spectra from Yersinia rohdei (with a still unsequenced genome) and further matched them against the protein database of related and sequenced bacterium Yersinia enterocolitica. MS-Deconv is available at http://proteomics.ucsd.edu/Software.html.Top-down proteomics is a mass spectrometry-based approach for identification of proteins and their post-translational modifications (PTMs)1 (1–14). Unlike the “bottom-up” approach where proteins are first digested into peptides and then a peptide mixture is analyzed by mass spectrometry, the top-down approach analyzes intact proteins. Thus, it has advantages in detecting and localizing PTMs as well as identifying multiple protein species (e.g. proteolytically processed protein species). Despite its advantages, top-down proteomics presents many challenges. These include requirement of high sample quantity, sophisticated instrumentation, protein separation, and robust computational analysis tools. For this reason, top-down proteomics has rarely been used for analyzing complex mixtures (12–18), and it is typically used to study single purified proteins. However, this situation is quickly changing with recent top-down studies of complex protein mixtures (14, 19).Because of the existence of natural isotopes, fragment ions of the same chemical formula and charge state are usually represented by a collection of spectral peaks in tandem mass spectra called an isotopomer envelope. The monoisotopic mass of a chemical formula is the sum of the masses of the atoms using the principal (most abundant) isotope for each element. Spectral deconvolution focuses on grouping spectral peaks into isotopomer envelopes. By doing so, the charge state and monoisotopic mass of each envelope are effectively determined. A complex multi-isotopic peak list in the m/z space is translated into a simple monoisotopic mass list that is easier to analyze.Given the monoisotopic mass and charge state of a fragment ion, its theoretical isotopic distribution can be predicted by assuming the fragment ion has an average elemental composition with respect to its mass (20) or using its precise elemental composition if the protein is known. Exploiting this, many deconvolution methods use theoretical isotopic distributions to detect and evaluate candidate isotopomer envelopes, which is the envelope detection problem (Fig. 1). To evaluate the fit of a candidate envelope to its theoretical isotopic distribution, many metrics have been proposed (20–32).Open in a separate windowFig. 1.Envelope detection. a, a theoretical isotopic distribution is predicted with the monoisotopic mass and charge state of a fragment ion. b, an observed envelope is detected by mapping peaks in the theoretical distribution to the spectrum. c, match between the theoretical isotopic distribution and the observed envelope. d, the theoretical isotopic distribution is scaled (the intensities of the peaks are multiplied by a constant) to have the best fit with the intensities of peaks in the observed envelope. Finally, a score for the observed envelope can be computed by comparing it with the intensity-scaled theoretical isotopic distribution.The candidate envelopes often overlap and share peaks, leading to a combinatorial problem of selecting the list of envelopes that best explains the spectrum (Fig. 2). In contrast to the well studied envelope detection problem, the envelope selection problem remains poorly explored. Most deconvolution algorithms follow a simple greedy approach to selecting the set of envelopes where the highest scoring envelopes are iteratively selected and removed from the spectrum. Although this approach often generates reasonable sets of envelopes for simple spectra, its performance deteriorates in cases of complex spectra.Open in a separate windowFig. 2.Envelope selection problem. Overlapping envelopes lead to a difficult combinatorial problem of selecting an optimal set of envelopes. We illustrate two cases where a deconvolution method that follows a greedy envelope selection outputs the envelope E₂, whereas the optimal solution consists of the envelopes E₁ and E₃. Example a illustrates the case where envelopes do not share peaks, and example b illustrates the case where envelopes share a spectral peak (E₁ and E₃).In particular, the greedy approach performs well when the envelopes are distributed sparsely along the m/z axis. Large proteins have many fragments that appear in multiple charge states. The high number of envelopes/peaks and the small m/z spread of the fragments with high charge states result in narrow m/z regions with high peak density. In these peak-dense regions, envelopes may overlap and share peaks, and the greedy approach and even manual interpretation often fail to find the optimal combination of envelopes (supplemental Fig. 1).Several methods have been proposed to explore the envelope selection problem. McIlwain et al. (33) presented a dynamic programming algorithm for selecting a set of envelopes such that the m/z ranges of the envelopes do not overlap. This non-overlapping condition becomes too restrictive for complex spectra of intact proteins. Samuelsson et al. (34) proposed a method that follows a non-negative sparse regression scheme. Du and Angeletti (35) and Renard et al. (36) addressed the envelope selection problem as a statistical problem of variable selection and used LASSO to solve it.Here, we present MS-Deconv, a combinatorial algorithm for spectral deconvolution. MS-Deconv (i) generates a large set of candidate envelopes, (ii) constructs an envelope graph encoding all envelopes and relationships between them, and (iii) finds a heaviest path in the envelope graph. Although the envelope graph of a complex spectrum is large (exceeding a million nodes in some cases), the heaviest path algorithm can efficiently find an optimal set of envelopes. MS-Deconv explicitly scores combinations of candidate envelopes rather than individual envelopes as in previous approaches.We tested MS-Deconv on a data set of top-down spectra from known proteins and evaluated the monoisotopic masses recovered by MS-Deconv. A mass was classified as a true positive if it was matched to the monoisotopic mass of a theoretical fragment ion of the protein within a specific parts per million (ppm) tolerance. We compared the performance of MS-Deconv with the widely used Thrash (20) and Xtract (37) and demonstrated that, with a few exceptions, MS-Deconv recovers more true positive masses. For example, for the collisionally activated dissociation (CAD) spectrum of bacteriorhodopsin (BR) with charge 10, the percentage of true positive masses among the top 150 masses is above 70% for MS-Deconv and less than 50% for Thrash. Additionally, MS-Deconv is ∼33 times faster than Thrash and 4 times faster than Xtract. Furthermore, MS-Deconv implements some user-friendly features: (i) outputs the set of peptide sequence tags, (ii) provides protein and spectral annotations, and (iii) allows one to inspect the recovered envelopes. We also tested MS-Deconv on a large LC-MS/MS data set from Yersinia rohdei (with a still unsequenced genome) (19). Y. rohdei is a non-pathogenic bacterium that is often used as a simulant for the potential bioterrorism agent Yersinia pestis, the causative agent of plague. We applied MS-Deconv to extract monoisotopic mass lists from top-down spectra and compared the mass lists with those reported by Thrash. We used ProSightPC (38) and the spectral alignment algorithm (39) to identify related proteins from a protein database of Yersinia enterocolitica (with a closely related and sequenced genome). The results demonstrated that MS-Deconv reported more matched fragments than Thrash for most proteins. Additionally, using spectral alignment, we identified eight proteins in Y. rohdei that were not reported in the ProSightPC-based searches (19) of the Y. enterocolitica protein database.     

Consequences of concurrent Ascaridia galli and Escherichia coli infections in chickens

   

Three experiments were carried out to examine the consequences of concurrent infections with Ascaridia galli and Escherichia coli in chickens raised for table egg production. Characteristic pathological lesions including airsacculitis, peritonitis and/or polyserositis were seen in all groups infected with E. coli. Furthermore, a trend for increased mortality rates was observed in groups infected with both organisms which, however, could not be confirmed statistically. The mean worm burden was significantly lower in combined infection groups compared to groups infected only with A. galli. It was also shown that combined infections of E. coli and A. galli had an added significant negative impact on weight gain.     

The evolutionary radiation of Arvicolinae rodents (voles and lemmings): relative contribution of nuclear and mitochondrial DNA phylogenies

Background  

Mitochondrial and nuclear genes have generally been employed for different purposes in molecular systematics, the former to resolve relationships within recently evolved groups and the latter to investigate phylogenies at a deeper level. In the case of rapid and recent evolutionary radiations, mitochondrial genes like cytochrome b (CYB) are often inefficient for resolving phylogenetic relationships. One of the best examples is illustrated by Arvicolinae rodents (Rodentia; Muridae), the most impressive mammalian radiation of the Northern Hemisphere which produced voles, lemmings and muskrats. Here, we compare the relative contribution of a nuclear marker – the exon 10 of the growth hormone receptor (GHR) gene – to the one of the mitochondrial CYB for inferring phylogenetic relationships among the major lineages of arvicoline rodents.     

ATM protein purified from vaccinia virus expression system: DNA binding requirements for kinase activation

The ataxia-telangiectasia mutated (ATM) gene product plays a role in responding to double stand DNA breaks. Some biochemical studies of ATM function have been hampered by lack of an efficient expression system and abundant purified ATM protein. We report the construction of a vaccinia virus expressing ATM, vWR-ATM, which was used to produce large amounts of functional FLAG-tagged ATM protein (FLAG-ATM) in HeLa cells. Kinase activity of the purified FLAG-ATM was dependent on manganese and inhibited with wortmannin. Using the FLAG-ATM recombinant protein, GST-p53 serine 15 phosphorylation increased in the presence of damaged DNA. PHAS-1 phosphorylation was found to be DNA independent. Purified FLAG-ATM was recovered in the autophosphorylated form, as demonstrated by phosphorylation of ATM serine 1981. As shown by atomic force microscopy, FLAG-ATM bound to linear DNA both at broken ends and in mid-strands. Vaccinia virus is the most efficient ATM expression system described to date.     

Transit peptide cleavage sites of integral thylakoid membrane proteins

A set of 58 nuclearly encoded thylakoid-integral membrane proteins from four plant species was identified, and their amino termini were assigned unequivocally based upon mass spectrometry of intact proteins and peptide fragments. The dataset was used to challenge the Web tools ChloroP, TargetP, SignalP, PSORT, Predotar, and MitoProt II for predicting organelle targeting and transit peptide proteolysis sites. ChloroP and TargetP reliably predicted chloroplast targeting but only reliably predicted transit peptide cleavage sites for soluble proteins targeted to the stroma. SignalP (eukaryote settings) accurately predicted the transit peptide cleavage site for soluble proteins targeted to the lumen. SignalP (Gram-negative bacteria settings) reliably predicted peptide cleavage of integral thylakoid proteins inserted into the membrane via the "spontaneous" pathway. The processing sites of more common thylakoid-integral proteins inserted by the signal recognition peptide-dependent pathway were not well predicted by any of the programs. The results suggest the presence of a second thylakoid processing protease that recognizes the transit peptide of integral proteins inserted via the spontaneous mechanism and that this mechanism may be related to the secretory mechanism of Gram-negative bacteria.