Application of Label-Free Shotgun nUPLC–MS^E and 2‑DE Approaches in the Study of <i>Botrytis cinerea</i> Mycelium

The phytopathogenic fungus <i>Botrytis cinerea</i> infects more than different 200 plant species and causes substantial losses in numerous crops. The B05.10 and T4 wild-type strain genomes have been recently sequenced, becoming a model system for necrotrophic pathogens, as well as opening up new alternatives in functional genomics, such as proteomics. We analyzed <i>B. cinerea</i> mycelium from these two wild-type strains, introducing label-free shotgun nUPLC–MS^E methodology to complement the 2-DE-MS-based approach. We assessed the label-free nUPLC–MS^E methodology for protein identification and quantification using five mycelium protein dilutions. A total of 225 and 170 protein species were identified by nUPLC–MS^E in the B05.10 and T4 strains, respectively. Moreover, 129 protein species were quantified in both strains. Significant differences in protein abundance were found in 15 more abundant and 16 less abundant protein species in the B05.10 strain compared to the T4 strain. Twenty-nine qualitative and 15 significant quantitative differences were found using 2-DE. The label-free nUPLC–MS^E was a reliable, reproducible and sensitive method for protein identification and quantification to study the <i>B. cinerea</i> mycelial proteome. Results obtained by gel-based and gel-free complementary approaches allow a deeper characterization of this fungus, as well as the identification of potential virulence factors

Application of Label-Free Shotgun nUPLC–MS^E and 2‑DE Approaches in the Study of <i>Botrytis cinerea</i> Mycelium

The phytopathogenic fungus <i>Botrytis cinerea</i> infects more than different 200 plant species and causes substantial losses in numerous crops. The B05.10 and T4 wild-type strain genomes have been recently sequenced, becoming a model system for necrotrophic pathogens, as well as opening up new alternatives in functional genomics, such as proteomics. We analyzed <i>B. cinerea</i> mycelium from these two wild-type strains, introducing label-free shotgun nUPLC–MS^E methodology to complement the 2-DE-MS-based approach. We assessed the label-free nUPLC–MS^E methodology for protein identification and quantification using five mycelium protein dilutions. A total of 225 and 170 protein species were identified by nUPLC–MS^E in the B05.10 and T4 strains, respectively. Moreover, 129 protein species were quantified in both strains. Significant differences in protein abundance were found in 15 more abundant and 16 less abundant protein species in the B05.10 strain compared to the T4 strain. Twenty-nine qualitative and 15 significant quantitative differences were found using 2-DE. The label-free nUPLC–MS^E was a reliable, reproducible and sensitive method for protein identification and quantification to study the <i>B. cinerea</i> mycelial proteome. Results obtained by gel-based and gel-free complementary approaches allow a deeper characterization of this fungus, as well as the identification of potential virulence factors

Application of Label-Free Shotgun nUPLC–MS^E and 2‑DE Approaches in the Study of <i>Botrytis cinerea</i> Mycelium

The phytopathogenic fungus <i>Botrytis cinerea</i> infects more than different 200 plant species and causes substantial losses in numerous crops. The B05.10 and T4 wild-type strain genomes have been recently sequenced, becoming a model system for necrotrophic pathogens, as well as opening up new alternatives in functional genomics, such as proteomics. We analyzed <i>B. cinerea</i> mycelium from these two wild-type strains, introducing label-free shotgun nUPLC–MS^E methodology to complement the 2-DE-MS-based approach. We assessed the label-free nUPLC–MS^E methodology for protein identification and quantification using five mycelium protein dilutions. A total of 225 and 170 protein species were identified by nUPLC–MS^E in the B05.10 and T4 strains, respectively. Moreover, 129 protein species were quantified in both strains. Significant differences in protein abundance were found in 15 more abundant and 16 less abundant protein species in the B05.10 strain compared to the T4 strain. Twenty-nine qualitative and 15 significant quantitative differences were found using 2-DE. The label-free nUPLC–MS^E was a reliable, reproducible and sensitive method for protein identification and quantification to study the <i>B. cinerea</i> mycelial proteome. Results obtained by gel-based and gel-free complementary approaches allow a deeper characterization of this fungus, as well as the identification of potential virulence factors

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study

Surfing Transcriptomic Landscapes. A Step beyond the Annotation of Chromosome 16 Proteome

The Spanish team of the Human Proteome Project (SpHPP) marked the annotation of Chr16 and data analysis as one of its priorities. Precise annotation of Chromosome 16 proteins according to C-HPP criteria is presented. Moreover, Human Body Map 2.0 RNA-Seq and Encyclopedia of DNA Elements (ENCODE) data sets were used to obtain further information relative to cell/tissue specific chromosome 16 coding gene expression patterns and to infer the presence of missing proteins. Twenty-four shotgun 2D-LC–MS/MS and gel/LC–MS/MS MIAPE compliant experiments, representing 41% coverage of chromosome 16 proteins, were performed. Furthermore, mapping of large-scale multicenter mass spectrometry data sets from CCD18, MCF7, Jurkat, and Ramos cell lines into RNA-Seq data allowed further insights relative to correlation of chromosome 16 transcripts and proteins. Detection and quantification of chromosome 16 proteins in biological matrices by SRM procedures are also primary goals of the SpHPP. Two strategies were undertaken: one focused on known proteins, taking advantage of MS data already available, and the second, aimed at the detection of the missing proteins, is based on the expression of recombinant proteins to gather MS information and optimize SRM methods that will be used in real biological samples. SRM methods for 49 known proteins and for recombinant forms of 24 missing proteins are reported in this study