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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.

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.

© 2019 Asian Pacific Society of Respirology Background and objective: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic disease that has a poor 3-year median survival rate with unclear pathophysiology. Radiological features include bibasal, subpleural fibrosis and honeycombing while its pathology is characterized by fibroblastic foci and honeycombing. Proteomic analysis of circulating molecules in plasma may identify factors that characterize IPF and may assist in the diagnosis, prognostication and determination of pathogenic pathways in this condition. Methods: Two independent quantitative proteomic techniques were used, isobaric tags for relative and absolute quantitation (iTRAQ) and multiple reaction monitoring (MRM), to identify differentially expressed plasma proteins in a group of IPF patients in comparison to healthy controls with normal lung function matched for age and gender. Results: Five proteins were identified to be differentially expressed in IPF compared to healthy controls (upregulation of platelet basic protein and downregulation of actin, cytoplasmic 2, antithrombin-III, extracellular matrix protein-1 and fibronectin). Conclusion: This study further validates the combinational use of non-targeted discovery proteomics (iTRAQ) with targeted quantitation by mass spectrometry (MRM) of soluble biomarkers to identify potentially important molecules and pathways for pulmonary diseases such as IPF.

© 2019 Asian Pacific Society of Respirology Background and objective: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic disease that has a poor 3-year median survival rate with unclear pathophysiology. Radiological features include bibasal, subpleural fibrosis and honeycombing while its pathology is characterized by fibroblastic foci and honeycombing. Proteomic analysis of circulating molecules in plasma may identify factors that characterize IPF and may assist in the diagnosis, prognostication and determination of pathogenic pathways in this condition. Methods: Two independent quantitative proteomic techniques were used, isobaric tags for relative and absolute quantitation (iTRAQ) and multiple reaction monitoring (MRM), to identify differentially expressed plasma proteins in a group of IPF patients in comparison to healthy controls with normal lung function matched for age and gender. Results: Five proteins were identified to be differentially expressed in IPF compared to healthy controls (upregulation of platelet basic protein and downregulation of actin, cytoplasmic 2, antithrombin-III, extracellular matrix protein-1 and fibronectin). Conclusion: This study further validates the combinational use of non-targeted discovery proteomics (iTRAQ) with targeted quantitation by mass spectrometry (MRM) of soluble biomarkers to identify potentially important molecules and pathways for pulmonary diseases such as IPF.

© 2019 Asian Pacific Society of Respirology Background and objective: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic disease that has a poor 3-year median survival rate with unclear pathophysiology. Radiological features include bibasal, subpleural fibrosis and honeycombing while its pathology is characterized by fibroblastic foci and honeycombing. Proteomic analysis of circulating molecules in plasma may identify factors that characterize IPF and may assist in the diagnosis, prognostication and determination of pathogenic pathways in this condition. Methods: Two independent quantitative proteomic techniques were used, isobaric tags for relative and absolute quantitation (iTRAQ) and multiple reaction monitoring (MRM), to identify differentially expressed plasma proteins in a group of IPF patients in comparison to healthy controls with normal lung function matched for age and gender. Results: Five proteins were identified to be differentially expressed in IPF compared to healthy controls (upregulation of platelet basic protein and downregulation of actin, cytoplasmic 2, antithrombin-III, extracellular matrix protein-1 and fibronectin). Conclusion: This study further validates the combinational use of non-targeted discovery proteomics (iTRAQ) with targeted quantitation by mass spectrometry (MRM) of soluble biomarkers to identify potentially important molecules and pathways for pulmonary diseases such as IPF.

This study aimed to compare the depth and reproducibility of total proteome and differentially expressed protein coverage in technical duplicates and triplicates using iTRAQ 4-plex, iTRAQ 8-plex, and TMT 6-plex reagents. The analysis was undertaken because comprehensive comparisons of isobaric mass tag reproducibility have not been widely reported in the literature. The highest number of proteins was identified with 4-plex, followed by 8-plex and then 6-plex reagents. Quantitative analyses revealed that more differentially expressed proteins were identified with 4-plex reagents than 8-plex reagents and 6-plex reagents. Replicate reproducibility was determined to be =69% for technical duplicates and =57% for technical triplicates. The results indicate that running an 8-plex or 6-plex experiment instead of a 4-plex experiment resulted in 26 or 39% fewer protein identifications, respectively. When 4-plex spectra were searched with three software tools?ProteinPilot, Mascot, and Proteome Discoverer?the highest number of protein identifications were obtained with Mascot. The analysis of negative controls demonstrated the importance of running experiments as replicates. Overall, this study demonstrates the advantages of using iTRAQ 4-plex reagents over iTRAQ 8-plex and TMT 6-plex reagents, provides estimates of technical duplicate and triplicate reproducibility, and emphasizes the value of running replicate samples.

There is an increasing demand to develop cost-effective and accurate approaches to analyzing biological tissue samples. This is especially relevant in the fishing industry where closely related fish samples can be mislabeled, and the high market value of certain fish leads to the use of alternative species as substitutes, for example, Barramundi and Nile Perch (belonging to the same genus, Lates). There is a need to combine selective proteomic datasets with sophisticated computational analysis to devise a robust classification approach. This paper describes an integrated MS-based proteomics and bioinformatics approach to classifying a range of fish samples. A classifier is developed using training data that successfully discriminates between Barramundi and Nile Perch samples using a selected protein subset of the proteome. Additionally, the classifier is shown to successfully discriminate between test samples not used to develop the classifier, including samples that have been cooked, and to classify other fish species as neither Barramundi nor Nile Perch. This approach has applications to truth in labeling for fishmongers and restaurants, monitoring fish catches, and for scientific research into distances between species.

There is an increasing demand to develop cost-effective and accurate approaches to analyzing biological tissue samples. This is especially relevant in the fishing industry where closely related fish samples can be mislabeled, and the high market value of certain fish leads to the use of alternative species as substitutes, for example, Barramundi and Nile Perch (belonging to the same genus, Lates). There is a need to combine selective proteomic datasets with sophisticated computational analysis to devise a robust classification approach. This paper describes an integrated MS-based proteomics and bioinformatics approach to classifying a range of fish samples. A classifier is developed using training data that successfully discriminates between Barramundi and Nile Perch samples using a selected protein subset of the proteome. Additionally, the classifier is shown to successfully discriminate between test samples not used to develop the classifier, including samples that have been cooked, and to classify other fish species as neither Barramundi nor Nile Perch. This approach has applications to truth in labeling for fishmongers and restaurants, monitoring fish catches, and for scientific research into distances between species.

There is an increasing demand to develop cost-effective and accurate approaches to analyzing biological tissue samples. This is especially relevant in the fishing industry where closely related fish samples can be mislabeled, and the high market value of certain fish leads to the use of alternative species as substitutes, for example, Barramundi and Nile Perch (belonging to the same genus, Lates). There is a need to combine selective proteomic datasets with sophisticated computational analysis to devise a robust classification approach. This paper describes an integrated MS-based proteomics and bioinformatics approach to classifying a range of fish samples. A classifier is developed using training data that successfully discriminates between Barramundi and Nile Perch samples using a selected protein subset of the proteome. Additionally, the classifier is shown to successfully discriminate between test samples not used to develop the classifier, including samples that have been cooked, and to classify other fish species as neither Barramundi nor Nile Perch. This approach has applications to truth in labeling for fishmongers and restaurants, monitoring fish catches, and for scientific research into distances between species.

In this study, proteomics and metabolomics were used to study the wheat response to exposure to the SnToxA effector protein secreted by the fungal pathogen Stagonospora nodorum during infection. Ninety-one different acidic and basic proteins and 101 metabolites were differentially abundant when comparing SnToxA- and control-treated wheat leaves during a 72-h time course. Proteins involved in photosynthesis were observed to increase marginally initially after exposure, before decreasing rapidly and significantly. Proteins and metabolites associated with the detoxification of reactive oxygen species in the chloroplast were also differentially abundant during SnToxA exposure, implying that the disruption of photosynthesis causes the rapid accumulation of chloroplastic reactive oxygen species. Metabolite profiling revealed major metabolic perturbations in central carbon metabolism, evidenced by significant increases in tricarboxylic acid (TCA) cycle intermediates, suggestive of an attempt by the plant to generate ATP and reducing equivalents in response to the collapse of photosynthesis caused by SnToxA. This was supported by the observation that the TCA cycle enzyme malate dehydrogenase was up-regulated in response to SnToxA. The infiltration of SnToxA also resulted in a significant increase in abundance of many pathogenicity-related proteins, even in the absence of the pathogen or other pathogen-associated molecular patterns.This approach highlights the complementary nature of proteomics and metabolomics in studying effector–host interactions, and provides further support for the hypothesis that necrotrophic pathogens, such as S. nodorum, appear to exploit existing host cell death mechanisms to promote pathogen growth and cause disease.

The G protein α-subunit (Gna1) in the wheat pathogen Stagonospora nodorum has previously been shown to be a critical controlling element in disease ontogeny. In this study, iTRAQ and 2-D LC MALDI-MS/MS have been used to characterise protein expression changes in the S. nodorum gna1 strain versus the SN15 wild-type. A total of 1336 proteins were identified. The abundance of 49 proteins was significantly altered in the gna1 strain compared with the wildtype. Gna1 was identified as having a significant regulatory role on primary metabolic pathways, particularly those concerned with NADPH synthesis or consumption. Mannitol dehydrogenase was up-regulated in the gna1 strain while mannitol 1-phosphate dehydrogenase was down-regulated providing direct evidence of Gna1 regulation over this enigmatic pathway. Enzymatic analysis and growth assays confirmed this regulatory role. Several novel hypothetical proteins previously associated with stress and pathogen responses were identified as positively regulated by Gna1. A short-chain dehydrogenase (Sch3) was also significantly less abundant in the gna1 strains. Sch3 was further characterised by gene disruption in S. nodorum by homologous recombination. Functional characterisation of the sch3 strains revealed their inability to sporulate in planta providing a further link to Gna1 signalling and asexual reproduction. These data add significantly to the identification of the regulatory targets of Gna1 signalling in S. nodorum and have demonstrated the utility of iTRAQ in dissecting signal transduction pathways.

The G protein α-subunit (Gna1) in the wheat pathogen Stagonospora nodorum has previously been shown to be a critical controlling element in disease ontogeny. In this study, iTRAQ and 2-D LC MALDI-MS/MS have been used to characterise protein expression changes in the S. nodorum gna1 strain versus the SN15 wild-type. A total of 1336 proteins were identified. The abundance of 49 proteins was significantly altered in the gna1 strain compared with the wild-type. Gna1 was identified as having a significant regulatory role on primary metabolic pathways, particularly those concerned with NADPH synthesis or consumption. Mannitol dehydrogenase was up-regulated in the gna1 strain while mannitol 1-phosphate dehydrogenase was down-regulated providing direct evidence of Gna1 regulation over this enigmatic pathway. Enzymatic analysis and growth assays confirmed this regulatory role. Several novel hypothetical proteins previously associated with stress and pathogen responses were identified as positively regulated by Gna1. A short-chain dehydrogenase (Sch3) was also significantly less abundant in the gna1 strains. Sch3 was further characterised by gene disruption in S. nodorum by homologous recombination. Functional characterisation of the sch3 strains revealed their inability to sporulate in planta providing a further link to Gna1 signalling and asexual reproduction. These data add significantly to the identification of the regulatory targets of Gna1 signalling in S. nodorum and have demonstrated the utility of iTRAQ in dissecting signal transduction pathways.

The G protein a-subunit (Gna1) in the wheat pathogen Stagonospora nodorum has previouslybeen shown to be a critical controlling element in disease ontogeny. In this study, iTRAQ and2-D LC MALDI-MS/MS have been used to characterise protein expression changes in the S.nodorum gna1 strain versus the SN15 wild-type. A total of 1336 proteins were identified. Theabundance of 49 proteins was significantly altered in the gna1 strain compared with the wildtype.Gna1 was identified as having a significant regulatory role on primary metabolicpathways, particularly those concerned with NADPH synthesis or consumption. Mannitoldehydrogenase was up-regulated in the gna1 strain while mannitol 1-phosphate dehydrogenasewas down-regulated providing direct evidence of Gna1 regulation over this enigmaticpathway. Enzymatic analysis and growth assays confirmed this regulatory role. Severalnovel hypothetical proteins previously associated with stress and pathogen responses wereidentified as positively regulated by Gna1. A short-chain dehydrogenase (Sch3) was alsosignificantly less abundant in the gna1 strains. Sch3 was further characterised by genedisruption in S. nodorum by homologous recombination. Functional characterisation of thesch3 strains revealed their inability to sporulate in planta providing a further link to Gna1signalling and asexual reproduction. These data add significantly to the identification of theregulatory targets of Gna1 signalling in S. nodorum and have demonstrated the utility ofiTRAQ in dissecting signal transduction pathways.

We have shown previously that exposure of guinea pig ventricular myocytes to 30 μM hydrogen peroxide (H2O2) for 5 min followed by 10 U/ml catalase to degrade the H2O2 results in a persistent increase in superoxide production by the mitochondria. This leads to a 2-fold increase in protein synthesis measured as [3H] leucine incorporation. We characterised the effect of a transient exposure of cardiac myocytes to H2O2 on the proteome. Myocytes were exposed to 0 μM or 30 μM H2O2 for 5 min followed by 10U/ml catalase. Protein was extracted, labelled with iTRAQ reagents and the peptides were analysed by LC–MALDI-TOF/TOF mass spectrometry and identified against SwissProt and Ludwig NR databases. More than 900 proteins were identified. Transient exposure of the myocytes to H2O2 resulted in altered expression of 62 proteins. 40% of proteins identified with altered expression were mitochondrial. Consistent with our in vitro data, mitochondria complex I and complex III subunit expression was upregulated while downregulation of complex IV and ATP synthase subunits suggested compromised ATP production. We also detected an increase in sarcomere associated proteins including Troponin C, Tropomyosin I alpha isoform 6 and Myosin light chain 2 and 3. Prohibitin was downregulated and calcireticulin expression was upregulated, consistent with promotion of cellular growth. We are currently validating the findings with in vitro functional studies in the myocytes. These data suggest that transient exposure to cardiac myocytes is sufficient to significantly alter expression of proteins and provides insight into early mechanisms of development of cardiac hypertrophy.

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.

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.

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.