Characterization of Proteoform Post-Translational Modifications by Top-Down and Bottom-Up Mass Spectrometry in Conjunction with Annotations

Many proteoforms can be produced from a gene due to genetic mutations, alternative splicing, post-translational modifications (PTMs), and other variations. PTMs in proteoforms play critical roles in cell signaling, protein degradation, and other biological processes. Mass spectrometry (MS) is the primary technique for investigating PTMs in proteoforms, and two alternative MS approaches, top-down and bottom-up, have complementary strengths. The combination of the two approaches has the potential to increase the sensitivity and accuracy in PTM identification and characterization. In addition, protein and PTM knowledge bases, such as UniProt, provide valuable information for PTM characterization and verification. Here, we present a software pipeline PTM-TBA (PTM characterization by Top-down and Bottom-up MS and Annotations) for identifying and localizing PTMs in proteoforms by integrating top-down and bottom-up MS as well as PTM annotations. We assessed PTM-TBA using a technical triplicate of bottom-up and top-down MS data of SW480 cells. On average, database search of the top-down MS data identified 2000 mass shifts, 814.5 (40.7%) of which were matched to 11 common PTMs and 423 of which were localized. Of the mass shifts identified by top-down MS, PTM-TBA verified 435 mass shifts using the bottom-up MS data and UniProt annotations

Characterization of Proteoform Post-Translational Modifications by Top-Down and Bottom-Up Mass Spectrometry in Conjunction with Annotations

Many proteoforms can be produced from a gene due to genetic mutations, alternative splicing, post-translational modifications (PTMs), and other variations. PTMs in proteoforms play critical roles in cell signaling, protein degradation, and other biological processes. Mass spectrometry (MS) is the primary technique for investigating PTMs in proteoforms, and two alternative MS approaches, top-down and bottom-up, have complementary strengths. The combination of the two approaches has the potential to increase the sensitivity and accuracy in PTM identification and characterization. In addition, protein and PTM knowledge bases, such as UniProt, provide valuable information for PTM characterization and verification. Here, we present a software pipeline PTM-TBA (PTM characterization by Top-down and Bottom-up MS and Annotations) for identifying and localizing PTMs in proteoforms by integrating top-down and bottom-up MS as well as PTM annotations. We assessed PTM-TBA using a technical triplicate of bottom-up and top-down MS data of SW480 cells. On average, database search of the top-down MS data identified 2000 mass shifts, 814.5 (40.7%) of which were matched to 11 common PTMs and 423 of which were localized. Of the mass shifts identified by top-down MS, PTM-TBA verified 435 mass shifts using the bottom-up MS data and UniProt annotations

Characterization of Proteoform Post-Translational Modifications by Top-Down and Bottom-Up Mass Spectrometry in Conjunction with Annotations

Many proteoforms can be produced from a gene due to genetic mutations, alternative splicing, post-translational modifications (PTMs), and other variations. PTMs in proteoforms play critical roles in cell signaling, protein degradation, and other biological processes. Mass spectrometry (MS) is the primary technique for investigating PTMs in proteoforms, and two alternative MS approaches, top-down and bottom-up, have complementary strengths. The combination of the two approaches has the potential to increase the sensitivity and accuracy in PTM identification and characterization. In addition, protein and PTM knowledge bases, such as UniProt, provide valuable information for PTM characterization and verification. Here, we present a software pipeline PTM-TBA (PTM characterization by Top-down and Bottom-up MS and Annotations) for identifying and localizing PTMs in proteoforms by integrating top-down and bottom-up MS as well as PTM annotations. We assessed PTM-TBA using a technical triplicate of bottom-up and top-down MS data of SW480 cells. On average, database search of the top-down MS data identified 2000 mass shifts, 814.5 (40.7%) of which were matched to 11 common PTMs and 423 of which were localized. Of the mass shifts identified by top-down MS, PTM-TBA verified 435 mass shifts using the bottom-up MS data and UniProt annotations

Characterization of Proteoform Post-Translational Modifications by Top-Down and Bottom-Up Mass Spectrometry in Conjunction with Annotations

Many proteoforms can be produced from a gene due to genetic mutations, alternative splicing, post-translational modifications (PTMs), and other variations. PTMs in proteoforms play critical roles in cell signaling, protein degradation, and other biological processes. Mass spectrometry (MS) is the primary technique for investigating PTMs in proteoforms, and two alternative MS approaches, top-down and bottom-up, have complementary strengths. The combination of the two approaches has the potential to increase the sensitivity and accuracy in PTM identification and characterization. In addition, protein and PTM knowledge bases, such as UniProt, provide valuable information for PTM characterization and verification. Here, we present a software pipeline PTM-TBA (PTM characterization by Top-down and Bottom-up MS and Annotations) for identifying and localizing PTMs in proteoforms by integrating top-down and bottom-up MS as well as PTM annotations. We assessed PTM-TBA using a technical triplicate of bottom-up and top-down MS data of SW480 cells. On average, database search of the top-down MS data identified 2000 mass shifts, 814.5 (40.7%) of which were matched to 11 common PTMs and 423 of which were localized. Of the mass shifts identified by top-down MS, PTM-TBA verified 435 mass shifts using the bottom-up MS data and UniProt annotations

Characterization of Proteoform Post-Translational Modifications by Top-Down and Bottom-Up Mass Spectrometry in Conjunction with Annotations

Many proteoforms can be produced from a gene due to genetic mutations, alternative splicing, post-translational modifications (PTMs), and other variations. PTMs in proteoforms play critical roles in cell signaling, protein degradation, and other biological processes. Mass spectrometry (MS) is the primary technique for investigating PTMs in proteoforms, and two alternative MS approaches, top-down and bottom-up, have complementary strengths. The combination of the two approaches has the potential to increase the sensitivity and accuracy in PTM identification and characterization. In addition, protein and PTM knowledge bases, such as UniProt, provide valuable information for PTM characterization and verification. Here, we present a software pipeline PTM-TBA (PTM characterization by Top-down and Bottom-up MS and Annotations) for identifying and localizing PTMs in proteoforms by integrating top-down and bottom-up MS as well as PTM annotations. We assessed PTM-TBA using a technical triplicate of bottom-up and top-down MS data of SW480 cells. On average, database search of the top-down MS data identified 2000 mass shifts, 814.5 (40.7%) of which were matched to 11 common PTMs and 423 of which were localized. Of the mass shifts identified by top-down MS, PTM-TBA verified 435 mass shifts using the bottom-up MS data and UniProt annotations

Pilot Evaluation of the Long-Term Reproducibility of Capillary Zone Electrophoresis–Tandem Mass Spectrometry for Top-Down Proteomics of a Complex Proteome Sample

Mass spectrometry (MS)-based top-down proteomics (TDP) has revolutionized biological research by measuring intact proteoforms in cells, tissues, and biofluids. Capillary zone electrophoresis–tandem MS (CZE-MS/MS) is a valuable technique for TDP, offering a high peak capacity and sensitivity for proteoform separation and detection. However, the long-term reproducibility of CZE-MS/MS in TDP remains unstudied, which is a crucial aspect for large-scale studies. This work investigated the long-term qualitative and quantitative reproducibility of CZE-MS/MS for TDP for the first time, focusing on a yeast cell lysate. Over 1000 proteoforms were identified per run across 62 runs using one linear polyacrylamide (LPA)-coated separation capillary, highlighting the robustness of the CZE-MS/MS technique. However, substantial decreases in proteoform intensity and identification were observed after some initial runs due to proteoform adsorption onto the capillary inner wall. To address this issue, we developed an efficient capillary cleanup procedure using diluted ammonium hydroxide, achieving high qualitative and quantitative reproducibility for the yeast sample across at least 23 runs. The data underscore the capability of CZE-MS/MS for large-scale quantitative TDP of complex samples, signaling its readiness for deployment in broad biological applications. The MS RAW files were deposited in ProteomeXchange Consortium with the data set identifier of PXD046651

Pilot Evaluation of the Long-Term Reproducibility of Capillary Zone Electrophoresis–Tandem Mass Spectrometry for Top-Down Proteomics of a Complex Proteome Sample

Mass spectrometry (MS)-based top-down proteomics (TDP) has revolutionized biological research by measuring intact proteoforms in cells, tissues, and biofluids. Capillary zone electrophoresis–tandem MS (CZE-MS/MS) is a valuable technique for TDP, offering a high peak capacity and sensitivity for proteoform separation and detection. However, the long-term reproducibility of CZE-MS/MS in TDP remains unstudied, which is a crucial aspect for large-scale studies. This work investigated the long-term qualitative and quantitative reproducibility of CZE-MS/MS for TDP for the first time, focusing on a yeast cell lysate. Over 1000 proteoforms were identified per run across 62 runs using one linear polyacrylamide (LPA)-coated separation capillary, highlighting the robustness of the CZE-MS/MS technique. However, substantial decreases in proteoform intensity and identification were observed after some initial runs due to proteoform adsorption onto the capillary inner wall. To address this issue, we developed an efficient capillary cleanup procedure using diluted ammonium hydroxide, achieving high qualitative and quantitative reproducibility for the yeast sample across at least 23 runs. The data underscore the capability of CZE-MS/MS for large-scale quantitative TDP of complex samples, signaling its readiness for deployment in broad biological applications. The MS RAW files were deposited in ProteomeXchange Consortium with the data set identifier of PXD046651

µ-XRF elemental maps of rice grains after germination for 12 h.

<p>The green box on the lower magnification photo of the seed (upper, left) was rotated 90° clockwise to give the labeled, higher magnification image as well as the individual µ-XRF elemental maps and the color-merged image (lower left). Refer to the legend for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057360#pone-0057360-g004" target="_blank">Figure 4</a> for additional details.</p

µ-XRF elemental maps of early stage rice seedlings after seed germination for 48

<p> <b>h.</b> The orientation of the individual µ-XRF elemental maps and the color-merged image (upper right) is the same as that of the green rectangle around a portion of the labeled image of the germinating seed. Refer to the legend for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057360#pone-0057360-g004" target="_blank">Figure 4</a> for additional details.</p

Percentage distributions of Zn, Fe, K, Ca, and Mn in different fractions of rice grains.

<p>Data are the means of four replicates.</p