Dataset Information

LFQ proteomics analysis of M. smegmatis treated with BacPROTACs.

ABSTRACT: To monitor selective degradation of ClpC1 and ClpC2 using BacPROTAC compounds in M. smegmatis we performed a LFQ proteomics analysis treating the cells at bactericidal compound concentration. We detected degradation of both proteins and additional dysregulation of the mycobacterial PQC system.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Mycobacterium Smegmatis (strain Atcc 700084 / Mc(2)155)

SUBMITTER: David Hoi

LAB HEAD: Markus Hartl

PROVIDER: PXD037235 | Pride | 2023-06-07

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20220322_E2_RSLC2_Hoi_Clausen_IMP_24h_DMSO_1.raw	Raw
	20220322_E2_RSLC2_Hoi_Clausen_IMP_24h_DMSO_1_-45.mzxml	Mzxml
	20220322_E2_RSLC2_Hoi_Clausen_IMP_24h_DMSO_1_-60.mzxml	Mzxml
	20220322_E2_RSLC2_Hoi_Clausen_IMP_24h_DMSO_2.raw	Raw
	20220322_E2_RSLC2_Hoi_Clausen_IMP_24h_DMSO_2_-45.mzxml	Mzxml

Items per page:

1 - 5 of 91

Similar Datasets

Project description:Myocyte enhancer factor 2B (MEF2B) is a transcription factor with somatic mutation hotspots at K4, Y69 and D83 in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). The recurrence of these mutations indicates that they may drive lymphoma development. However, inferring the mechanisms by which they may drive lymphoma development was complicated by our limited understanding of MEF2B’s normal functions. To expand our understanding of the cellular activities of wildtype (WT) and mutant MEF2B, I developed and addressed two hypotheses: (1) identifying genes regulated by WT MEF2B will allow identification of cellular phenotypes affected by MEF2B activity and (2) contrasting the DNA binding sites, effects on gene expression and effects on cellular phenotypes of mutant and WT MEF2B will help refine hypotheses about how MEF2B mutations may contribute to lymphoma development. To address these hypotheses, I first identified genome-wide WT MEF2B binding sites and transcriptome-wide gene expression changes mediated by WT MEF2B. Using these data I identified and validated novel MEF2B target genes. I found that target genes of MEF2B included the cancer genes MYC, TGFB1, CARD11, NDRG1, RHOB, BCL2 and JUN. Identification of target genes led to findings that WT MEF2B promotes expression of mesenchymal markers, promotes HEK293A cell migration, and inhibits DLBCL cell chemotaxis. I then investigated how K4E, Y69H and D83V mutations change MEF2B’s activity. I found that K4E, Y69H and D83V mutations decreased MEF2B DNA binding and decreased MEF2B’s capacity to promote gene expression in both HEK293A and DLBCL cells. These mutations also reduced MEF2B’s capacity to alter HEK293A and DLBCL cell movement. From these data, I hypothesize that MEF2B mutations may promote DLBCL and FL development by reducing expression of MEF2B target genes that would otherwise function to help confine germinal centre B-cells to germinal centres. Overall, my research demonstrates how observations from genome-scale data can be used to identify cellular effects of candidate driver mutations. Moreover, my work provides a unique resource for exploring the role of MEF2B in cell biology: I map for the first time the MEF2B ‘regulome’, demonstrating connections between a relatively understudied transcription factor and genes significant to oncogenesis. ChIP-seq was performed using a V5 antibody on cells expressing V5 tagged WT and mutant MEF2B. Two biological replicates were performed on WT, K4E, Y69H and D83V MEF2B-V5 cells.

Project description:Myocyte enhancer factor 2B (MEF2B) is a transcription factor with somatic mutation hotspots at K4, Y69 and D83 in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). The recurrence of these mutations indicates that they may drive lymphoma development. However, inferring the mechanisms by which they may drive lymphoma development was complicated by our limited understanding of MEF2B’s normal functions. To expand our understanding of the cellular activities of wildtype (WT) and mutant MEF2B, I developed and addressed two hypotheses: (1) identifying genes regulated by WT MEF2B will allow identification of cellular phenotypes affected by MEF2B activity and (2) contrasting the DNA binding sites, effects on gene expression and effects on cellular phenotypes of mutant and WT MEF2B will help refine hypotheses about how MEF2B mutations may contribute to lymphoma development. To address these hypotheses, I first identified genome-wide WT MEF2B binding sites and transcriptome-wide gene expression changes mediated by WT MEF2B. Using these data I identified and validated novel MEF2B target genes. I found that target genes of MEF2B included the cancer genes MYC, TGFB1, CARD11, NDRG1, RHOB, BCL2 and JUN. Identification of target genes led to findings that WT MEF2B promotes expression of mesenchymal markers, promotes HEK293A cell migration, and inhibits DLBCL cell chemotaxis. I then investigated how K4E, Y69H and D83V mutations change MEF2B’s activity. I found that K4E, Y69H and D83V mutations decreased MEF2B DNA binding and decreased MEF2B’s capacity to promote gene expression in both HEK293A and DLBCL cells. These mutations also reduced MEF2B’s capacity to alter HEK293A and DLBCL cell movement. From these data, I hypothesize that MEF2B mutations may promote DLBCL and FL development by reducing expression of MEF2B target genes that would otherwise function to help confine germinal centre B-cells to germinal centres. Overall, my research demonstrates how observations from genome-scale data can be used to identify cellular effects of candidate driver mutations. Moreover, my work provides a unique resource for exploring the role of MEF2B in cell biology: I map for the first time the MEF2B ‘regulome’, demonstrating connections between a relatively understudied transcription factor and genes significant to oncogenesis. ChIP-seq was performed using H3K27ac and H3K4me3 antibodies on cells expressing V5 tagged WT MEF2B and on empty vector control cells. Two biological replicates were performed.

Dataset Information

LFQ proteomics analysis of M. smegmatis treated with BacPROTACs.

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets