The composition of the large, single, mitochondrion of T. brucei was characterized by mass spectrometry (2D-LC-MS/MS and gel-LC-MS/MS) analyses. A total of 2,897 proteins representing a substantial proportion of procyclic form cellular proteome were identified, which confirmed the validity of the vast majority of gene predictions. The data also showed that the genes annotated as hypothetical (species specific) were over-predicted and that virtually all genes annotated as hypothetical, unlikely are not expressed. By comparing the mass spectrometry data with genome sequence, 40 genes were identified that were not previously predicted. The data are placed in a publicly available web-based database (www.TrypsProteome.org). The total mitochondrial proteome is estimated at 1,008 proteins, with 401, 196, and 283 assigned to the mitochondrion with high, moderate, and lower confidence, respectively. The remaining mitochondrial proteins were estimated by statistical methods although individual assignments could not be made. The identified proteins have predicted roles in macromolecular, metabolic, energy generating, and transport processes providing a comprehensive profile of the protein content and function of the T. brucei mitochondrion.
DUX4 is a transcription factor whose misexpression in skeletal muscle causes facioscapulohumeral muscular dystrophy (FSHD). DUX4’s transcriptional activity has been extensively characterized, but the DUX4-induced proteome remains undescribed. Here, we report concurrent measurement of RNA and protein levels in DUX4-expressing cells via RNA-seq and quantitative mass spectrometry. DUX4 transcriptional targets were robustly translated, confirming the likely clinical relevance of proposed FSHD biomarkers. However, a multitude of mRNAs and proteins exhibited discordant expression changes upon DUX4 expression. Our dataset revealed unexpected proteomic, but not transcriptomic, dysregulation of diverse molecular pathways, including Golgi apparatus fragmentation, as well as extensive post-transcriptional buffering of stress-response genes. Key components of RNA degradation machineries, including UPF1, UPF3B, and XRN1, exhibited suppressed protein, but not mRNA, levels, explaining the build-up of aberrant RNAs that characterizes DUX4-expressing cells. Our results provide a resource for the FSHD community and illustrate the importance of post-transcriptional processes in DUX4-induced pathology.
To identify diagnostic and prognostic markers of chronic graft-versus-host disease (cGVHD), the major cause of morbidity and mortality after allogeneic hematopoietic cell transplantation (HCT). Patients and MethodsUsing a quantitative proteomics approach, we compared pooled plasma samples obtained at matched time points after HCT (median, 103 days) from 35 patients with cGVHD and 18 without cGVHD (data are available via ProteomeXchange with identifier PXD002762). Of 105 proteins showing at least a 1.25-fold difference in expression, 22 were selected on the basis of involvement in relevant pathways and enzyme-linked immunosorbent assay availability. Chemokine (C-X-C motif) ligand 9 (CXCL9) and suppression of tumorigenicity 2 (ST2) also were measured on the basis of previously determined associations with GVHD. Concentrations of the four lead biomarkers were measured at or after diagnosis in plasma from two independent verification cohorts (n = 391) to determine their association with cGVHD. Their prognostic ability when measured at approximately day +100 after HCT was evaluated in plasma of a second verification cohort (n = 172). ResultsOf 24 proteins measured in the first verification cohort, nine proteins were associated with cGVHD, and only four (ST2, CXCL9, matrix metalloproteinase 3, and osteopontin) were necessary to compose a four-biomarker panel with an area under the receiver operating characteristic curve (AUC) of 0.89 and significant correlation with cGVHD diagnosis, cGVHD severity, and nonrelapse mortality. In a second verification cohort, this panel distinguished patients with cGVHD (AUC, 0.75), and finally, the panel measured at day +100 could predict cGVHD occurring within the next 3 months with an AUC of 0.67 and 0.79 without and with known clinical risk factors, respectively. ConclusionWe conclude that the biomarker panel measured at diagnosis or day +100 after HCT may allow patient stratification according to risk of cGVHD.
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