Deep proteogenomics; high throughput gene validation by multidimensional liquid chromatography and mass spectrometry of proteins from the fungal wheat pathogen Stagonospora nodorum

BACKGROUND: Stagonospora nodorum, a fungal ascomycete in the class dothideomycetes, is a damaging pathogen of wheat. It is a model for necrotrophic fungi that cause necrotic symptoms via the interaction of multiple effector proteins with cultivar-specific receptors. A draft genome sequence and annotation was published in 2007. A second-pass gene prediction using a training set of 795 fully EST-supported genes predicted a total of 10762 version 2 nuclear-encoded genes, with an additional 5354 less reliable version 1 genes also retained. RESULTS: In this study, we subjected soluble mycelial proteins to proteolysis followed by 2D LC MALDI-MS/MS. Comparison of the detected peptides with the gene models validated 2134 genes. 62% of these genes (1324) were not supported by prior EST evidence. Of the 2134 validated genes, all but 188 were version 2 annotations. Statistical analysis of the validated gene models revealed a preponderance of cytoplasmic and nuclear localised proteins, and proteins with intracellularassociated GO terms. These statistical associations are consistent with the source of the peptides used in the study. Comparison with a 6-frame translation of the S. nodorum genome assembly confirmed 905 existing gene annotations (including 119 not previously confirmed) and provided evidence supporting 144 genes with coding exon frameshift modifications, 604 genes with extensions of coding exons into annotated introns or untranslated regions (UTRs), 3 new gene annotations which were supported by tblastn to NR, and 44 potential new genes residing within un-assembled regions of the genome. CONCLUSION: We conclude that 2D LC MALDI-MS/MS is a powerful, rapid and economical tool to aid in the annotation of fungal genomic assemblies

Examination of the temporal variation of peptide content in decomposition fluid under controlled conditions using pigs as human substitutes

We report the preliminary observations of the peptide content of decomposition fluid produced under controlled laboratory conditions and in the absence of a soil matrix. Four domestic pig (Sus scrofa domesticus) cadavers were used to model human decomposition over a four-week trial period; physical characteristics were recorded and the peptide components of decomposition fluid was analysed using high performance liquid chromatography-time of flight mass spectrometry. Preliminary data analysis indicated that a range of peptides were consistently detected across the course of the trial period and 27 of these were common to all four cadavers; 22 originating from haemoglobin. The peptides associated with haemoglobin subunit alpha and beta displayed a breakdown pattern that remained consistent for all cadavers for the duration of the trial. Though identification of peptides during decomposition has potential for estimating the time since death, quantification of selected peptides is likely to be essential to identify time-dependent trends

ZnSe Heteroepitaxial Growth on Si (100) and GaAs (100)

The early stages of ZnSe heteroepitaxy on Si(100), Si(100):As and GaAs(100) are compared and contrasted, based on results of scanning tunneling microscopy and photoemission spectroscopy. High Se reactivity with the substrate constituents leads to bulk phase formation which is detrimental to heteroepitaxy. As-termination of Si(100) not only passivates the surface, but also provides an ideal buffer for ZnSe overgrowth. Lacking a similar buffer layer, stoichiometric control of the GaAs(100) surface is investigated to find a means for controlled heteroepitaxy

A new type of reconstruction on the InSb() surface determined by grazing incidence X-ray diffraction

The (3×3) reconstruction of the InSb( ) surface has been investigated by grazing incidence X-ray diffraction and scanning tunneling microscopy. The structure is characterized by 6-atom rings on top of a slightly buckled InSb top double layer. Two types of rings have been found, an elliptic ring consisting of 4 In and 2 Sb atoms and a trigonal ring with 3 In and 3 Sb atoms. The bond angles and lengths are consistent with the concept of rehybridization and depolarization which explains the reconstructions of the (111) and (110) surfaces

Deep proteogenomics; high throughput gene validation by multidimensional liquid chromatography and mass spectrometry of proteins from the fungal wheat pathogen Stagonospora nodorum

Background Stagonospora nodorum, a fungal ascomycete in the class dothideomycetes, is a damaging pathogen of wheat. It is a model for necrotrophic fungi that cause necrotic symptoms via the interaction of multiple effector proteins with cultivar-specific receptors. A draft genome sequence and annotation was published in 2007. A second-pass gene prediction using a training set of 795 fully EST-supported genes predicted a total of 10762 version 2 nuclear-encoded genes, with an additional 5354 less reliable version 1 genes also retained. Results In this study, we subjected soluble mycelial proteins to proteolysis followed by 2D LC MALDI-MS/MS. Comparison of the detected peptides with the gene models validated 2134 genes. 62% of these genes (1324) were not supported by prior EST evidence. Of the 2134 validated genes, all but 188 were version 2 annotations. Statistical analysis of the validated gene models revealed a preponderance of cytoplasmic and nuclear localised proteins, and proteins with intracellular-associated GO terms. These statistical associations are consistent with the source of the peptides used in the study. Comparison with a 6-frame translation of the S. nodorum genome assembly confirmed 905 existing gene annotations (including 119 not previously confirmed) and provided evidence supporting 144 genes with coding exon frameshift modifications, 604 genes with extensions of coding exons into annotated introns or untranslated regions (UTRs), 3 new gene annotations which were supported by tblastn to NR, and 44 potential new genes residing within un-assembled regions of the genome. Conclusion We conclude that 2D LC MALDI-MS/MS is a powerful, rapid and economical tool to aid in the annotation of fungal genomic assemblies

Epitaxial growth of topological insulator Bi2Se3 film on Si(111) with atomically sharp interface

Atomically sharp epitaxial growth of Bi2Se3 films is achieved on Si (111) substrate with MBE (Molecular Beam Epitaxy). Two-step growth process is found to be a key to achieve interfacial-layer-free epitaxial Bi2Se3 films on Si substrates. With a single-step high temperature growth, second phase clusters are formed at an early stage. On the other hand, with low temperature growth, the film tends to be disordered even in the absence of a second phase. With a low temperature initial growth followed by a high temperature growth, second-phase-free atomically sharp interface is obtained between Bi2Se3 and Si substrate, as verified by RHEED (Reflection High Energy Electron Diffraction), TEM (Transmission Electron Microscopy) and XRD (X-Ray Diffraction). The lattice constant of Bi2Se3 is observed to relax to its bulk value during the first quintuple layer according to RHEED analysis, implying the absence of strain from the substrate. TEM shows a fully epitaxial structure of Bi2Se3 film down to the first quintuple layer without any second phase or an amorphous layer.Comment: 20 pages, 7 figure

Gene validation and remodelling using proteogenomics of Phytophthora cinnamomi, the causal agent of Dieback

Phytophthora cinnamomi is a pathogenic oomycete that causes plant dieback disease across a range of natural ecosystems and in many agriculturally important crops on a global scale. An annotated draft genome sequence is publicly available (JGI Mycocosm) and suggests 26,131 gene models. In this study, soluble mycelial, extracellular (secretome), and zoospore proteins of P. cinnamomi were exploited to refine the genome by correcting gene annotations and discovering novel genes. By implementing the diverse set of sub-proteomes into a generated proteogenomics pipeline, we were able to improve the P. cinnamomi genome annotation. Liquid chromatography mass spectrometry was used to obtain high confidence peptides with spectral matching to both the annotated genome and a generated 6-frame translation. Two thousand seven hundred sixty-four annotations from the draft genome were confirmed by spectral matching. Using a proteogenomic pipeline, mass spectra were used to edit the P. cinnamomi genome and allowed identification of 23 new gene models and 60 edited gene features using high confidence peptides obtained by mass spectrometry, suggesting a rate of incorrect annotations of 3% of the detectable proteome. The novel features were further validated by total peptide support, alongside functional analysis including the use of Gene Ontology and functional domain identification. We demonstrated the use of spectral data in combination with our proteogenomics pipeline can be used to improve the genome annotation of important plant diseases and identify missed genes. This study presents the first use of spectral data to edit and manually annotate an oomycete pathogen

Resequencing and comparative genomics of stagonospora nodorum: Sectional gene absence and effector discovery

Stagonospora nodorum is an important wheat (Triticum aestivum) pathogen in many parts of the world, causing major yield losses. It was the first species in the large fungal Dothideomycete class to be genome sequenced. The reference genome sequence (SN15) has been instrumental in the discovery of genes encoding necrotrophic effectors that induce disease symptoms in specific host genotypes. Here we present the genome sequence of two further S. nodorum strains (Sn4 and Sn79) that differ in their effector repertoire from the reference. Sn79 is avirulent on wheat and produces no apparent effectors when infiltrated onto many cultivars and mapping population parents. Sn4 is pathogenic on wheat and has virulences not found in SN15. The new strains, sequenced with short-read Illumina chemistry, are compared with SN15 by a combination of mapping and de novo assembly approaches.Each of the genomes contains a large number of strain-specific genes, many of which have no meaningful similarity to any known gene. Large contiguous sections of the reference genome are absent in the two newly sequenced strains. We refer to these differences as “sectional gene absences.” The presence of genes in pathogenic strains and absence in Sn79 is added to computationally predicted properties of known proteins to produce a list of likely effector candidates. Transposon insertion was observed in the mitochondrial genomes of virulent strains where the avirulent strain retained the likely ancestral sequence. The study suggests that short-read enabled comparative genomics is an effective way to both identify new S. nodorum effector candidates and to illuminate evolutionary processes in this species

Evaluation of secretion prediction highlights differing approaches needed for oomycete and fungal effectors

© 2015 Sperschneider, Williams, Hane, Singh and Taylor. The steadily increasing number of sequenced fungal and oomycete genomes has enabled detailed studies of how these eukaryotic microbes infect plants and cause devastating losses in food crops. During infection, fungal and oomycete pathogens secrete effector molecules which manipulate host plant cell processes to the pathogen's advantage. Proteinaceous effectors are synthesized intracellularly and must be externalized to interact with host cells. Computational prediction of secreted proteins from genomic sequences is an important technique to narrow down the candidate effector repertoire for subsequent experimental validation. In this study, we benchmark secretion prediction tools on experimentally validated fungal and oomycete effectors. We observe that for a set of fungal SwissProt protein sequences, SignalP 4 and the neural network predictors of SignalP 3 (D-score) and SignalP 2 perform best. For effector prediction in particular, the use of a sensitive method can be desirable to obtain the most complete candidate effector set. We show that the neural network predictors of SignalP 2 and 3, as well as TargetP were the most sensitive tools for fungal effector secretion prediction, whereas the hidden Markov model predictors of SignalP 2 and 3 were the most sensitive tools for oomycete effectors. Thus, previous versions of SignalP retain value for oomycete effector prediction, as the current version, SignalP 4, was unable to reliably predict the signal peptide of the oomycete Crinkler effectors in the test set. Our assessment of subcellular localization predictors shows that cytoplasmic effectors are often predicted as not extracellular. This limits the reliability of secretion predictions that depend on these tools. We present our assessment with a view to informing future pathogenomics studies and suggest revised pipelines for secretion prediction to obtain optimal effector predictions in fungi and oomycetes