Moving Away from the Reference Genome: Evaluating a Peptide Sequencing Tagging Approach for Single Amino Acid Polymorphism Identifications in the Genus <i>Populus</i>

The genetic diversity across natural populations of the model organism, Populus, is extensive, containing a single nucleotide polymorphism roughly every 200 base pairs. When deviations from the reference genome occur in coding regions, they can impact protein sequences. Rather than relying on a static reference database to profile protein expression, we employed a peptide sequence tagging (PST) approach capable of decoding the plasticity of the Populus proteome. Using shotgun proteomics data from two genotypes of P. trichocarpa, a tag-based approach enabled the detection of 6653 unexpected sequence variants. Through manual validation, our study investigated how the most abundant chemical modification (methionine oxidation) could masquerade as a sequence variant (Ala→Ser) when few site-determining ions existed. In fact, precise localization of an oxidation site for peptides with more than one potential placement was indeterminate for 70% of the MS/MS spectra. We demonstrate that additional fragment ions made available by high energy collisional dissociation enhances the robustness of the peptide sequence tagging approach (81% of oxidation events could be exclusively localized to a methionine). We are confident that augmenting fragmentation processes for a PST approach will further improve the identification of single amino acid polymorphism in Populus and potentially other species as well

Moving Away from the Reference Genome: Evaluating a Peptide Sequencing Tagging Approach for Single Amino Acid Polymorphism Identifications in the Genus <i>Populus</i>

The genetic diversity across natural populations of the model organism, <i>Populus</i>, is extensive, containing a single nucleotide polymorphism roughly every 200 base pairs. When deviations from the reference genome occur in coding regions, they can impact protein sequences. Rather than relying on a static reference database to profile protein expression, we employed a peptide sequence tagging (PST) approach capable of decoding the plasticity of the <i>Populus</i> proteome. Using shotgun proteomics data from two genotypes of <i>P. trichocarpa</i>, a tag-based approach enabled the detection of 6653 unexpected sequence variants. Through manual validation, our study investigated how the most abundant chemical modification (methionine oxidation) could masquerade as a sequence variant (Ala→Ser) when few site-determining ions existed. In fact, precise localization of an oxidation site for peptides with more than one potential placement was indeterminate for 70% of the MS/MS spectra. We demonstrate that additional fragment ions made available by high energy collisional dissociation enhances the robustness of the peptide sequence tagging approach (81% of oxidation events could be exclusively localized to a methionine). We are confident that augmenting fragmentation processes for a PST approach will further improve the identification of single amino acid polymorphism in <i>Populus</i> and potentially other species as well

Moving Away from the Reference Genome: Evaluating a Peptide Sequencing Tagging Approach for Single Amino Acid Polymorphism Identifications in the Genus <i>Populus</i>

The genetic diversity across natural populations of the model organism, <i>Populus</i>, is extensive, containing a single nucleotide polymorphism roughly every 200 base pairs. When deviations from the reference genome occur in coding regions, they can impact protein sequences. Rather than relying on a static reference database to profile protein expression, we employed a peptide sequence tagging (PST) approach capable of decoding the plasticity of the <i>Populus</i> proteome. Using shotgun proteomics data from two genotypes of <i>P. trichocarpa</i>, a tag-based approach enabled the detection of 6653 unexpected sequence variants. Through manual validation, our study investigated how the most abundant chemical modification (methionine oxidation) could masquerade as a sequence variant (Ala→Ser) when few site-determining ions existed. In fact, precise localization of an oxidation site for peptides with more than one potential placement was indeterminate for 70% of the MS/MS spectra. We demonstrate that additional fragment ions made available by high energy collisional dissociation enhances the robustness of the peptide sequence tagging approach (81% of oxidation events could be exclusively localized to a methionine). We are confident that augmenting fragmentation processes for a PST approach will further improve the identification of single amino acid polymorphism in <i>Populus</i> and potentially other species as well

Novel Insights into the Distribution of Reduced Sulfur Species in Prairie Pothole Wetland Pore Waters Provided by Bismuth Film Electrodes

Mercury/gold amalgam and bismuth film electrodes (BiFEs) were used to make the first centimeter-scale measurements of redox species in benthic pore waters of prairie pothole wetlands across a hydrologic gradient. Sulfide in pore waters increased across this system from negligible sulfide in hydrologically up-gradient recharge wetlands to thousands of micromolar in down-gradient discharge wetlands. Field measurements of sulfides using the BiFE were tested against an established colorimetric assay. Sulfide measured with the BiFE agreed well with colorimetric measurements but is not subject to analytical artifacts associated with methods needed to extract the pore waters. Use of Hg/Au and BiFE electrodes should allow for rapid in situ detection of redox active species, especially sulfide concentrations of >500 μM, in pore waters over seasonal to decadal time scales. Such measurements are needed to understand important biogeochemical and environmental processes such as carbon cycling and contaminant attenuation tied to sulfur dynamics in these important ecosystems

Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study

Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study

Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study

Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study