CYRI-A limits invasive migration through macropinosome formation and integrin uptake regulation

Le, Anh Hoang; Yelland, T.; Paul, Nikki R.; Fort, Loïc; Nikolaou, Savvas; Ismail, Shehab; Machesky, Laura M.

doi:10.1083/jcb.202012114

Cited by 21 publications

(47 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CYRI-A is not part of the WAVE complex but it can disrupt the Rac1-WAVE regulatory complex. CYRI-A has been shown to indicate Rac1 activity by its localization (Le et al, 2021), which confirms the findings of our study. Pak1, Pak3, Pak4, PAR6A and TNK2 are kinases (Bishop and Hall, 2000;Garrard et al, 2003), N-WASP, WASp, IQGAP1, p67phox, BAIAP2, CDD42EPI and Bem1 are scaffold proteins (Bishop and Hall, 2000;Burbelo et al, 1999;Laan et al, 2015).…”

Section: Discussionsupporting

confidence: 92%

Cell-based optimisation and characterisation of genetically encoded, location-based biosensors for Cdc42 or Rac activity

Mahlandt

Kreider-Letterman²,

Chertkova

et al. 2022

Preprint

View full text Add to dashboard Cite

Rac and Cdc42 are Rho GTPases which regulate the formation of lamellipoda and filopodia and are therefore crucial in cellular processes such as cell migration. Both Rho GTPases are active at the leading edge of migrating cells. However, it is unclear how their signaling patterns differ from each other and what their specific roles are. To live image their signaling with high spatial and temporal resolution, location-based biosensors (relocating to the native location of the endogenous active Rho GTPase) are attractive probes. Until now, Rac and Cdc42 relocation sensors have not been characterized well, especially in terms of their specificity for the Rho GTPases. In this study, we identify a number of relocation sensor candidates for either Rac or Cdc42. We compared their (i) ability to bind the constitutively active Rho GTPases, (ii) specificity for Rac and Cdc42 and (iii) relocation efficiency in cell-based assays. Subsequently, the relocation efficiency was improved by a multi-domain approach. For Rac1 we found a sensor candidate with low relocation efficiency. For Cdc42 we found several sensors with sufficient relocation efficiency and specificity. These optimized sensors enable the wider application of Rho GTPase relocation sensors, which was showcased by the detection of local endogenous Cdc42 activity in a spreading endothelial cell and a multiplexing experiment with Rho and a Cdc42 relocation sensors. Moreover, we tested several fluorescent proteins and a HaloTag for their influence on the recruitment efficiency of the Rho location senor, to find optimal conditions for the multiplexing experiment. The characterization and optimization of relocation sensors will broaden their application and acceptance in the field of biosensors.

show abstract

Section: Discussionsupporting

confidence: 92%

Cell-based optimisation and characterisation of genetically encoded, location-based biosensors for Cdc42 or Rac activity

Mahlandt

Kreider-Letterman²,

Chertkova

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…At present, little is known about the role of FAM49A. It has been reported that CYRI-A, the post-translational product of FAM49A, is a dynamic regulator of large-scale pinocytosis, and it adjusts integrin together with CYPTI-B (the post-translational product of FAM49B, a family gene of FAM49A) (44). It has been reported that the mutation of MYO1F can increase the tumorigenicity of cells in vitro, which is characterized by accelerated growth and enhanced invasion.…”

Section: Discussionmentioning

confidence: 99%

Immune Score-based Molecular Subtypes and Signature Associated with Clinical Outcome in Hepatoblastoma

Huang

Yan²,

Liu

et al. 2021

Hepat Mon

View full text Add to dashboard Cite

Background: This study aimed to identify genes related to the immune score of hepatoblastoma, examine the characteristics of the immune microenvironment of hepatoblastoma, and construct a risk scoring system for predicting the prognosis of hepatoblastoma. Methods: Through using the gene chip data of patients with hepatoblastoma with survival data in the ArrayExpress and GEO databases, the immune score of hepatoblastoma was calculated by the ESITIMATE algorithm, and the prognostic value of immune score in patients with hepatoblastoma was studied by the survival analysis. Genes related to the immune score were identified by the WGCNA algorithm. According to these genes, patients with hepatoblastoma were clustered unsupervised. Finally, the risk scoring system was constructed according to the immune score-related genes. Results: The immune score calculated by the ESTIMATE algorithm had a good prognostic value in patients with hepatoblastoma. Patients with high immune scores had better OS than those with low immune scores (P < 0.001). A total of 146 immune score-related genes were identified by WGCNA analysis, and univariate COX regression analysis indicated that 59 of the genes had prognostic value. According to the unsupervised clustering results of the 146 immune score-related genes, patients with hepatoblastoma could be divided into two subtypes with different prognoses, namely molecular subtype 1 and subtype 2, with molecular subtype 1 having a better prognosis. The immunocyte infiltration analysis results showed that the difference between the two subtypes was mainly in activated CD4 T cells, activated dendritic cells, CD56 bright natural killer cells, the macrophage, and regulatory T cells. According to the immune score-related genes, a risk scoring system was constructed based on a five-gene signature. After the cut-off value was determined, patients with hepatoblastoma were divided into a high-risk group and a low-risk group. The prognosis of the two groups was different. Conclusions: The immune score has a good prognostic value in patients with hepatoblastoma. Based on the different expression patterns of immune score-related genes, hepatoblastoma can be divided into two different prognostic molecular subtypes, showing different immunocyte infiltration patterns. The established risk scoring system based on a five-gene signature has a good predictive value in patients with hepatoblastoma.

show abstract

“…All three members have been characterized by a highly conserved domain, DUF1394 (Domain of Unknown Function 1394) (PDB entry 3p8c) [ 1 ]. Only FAM49A and FAM49B exist in the human genome, while Fam49c has only been found in fish, amphibians, reptiles, birds and some lower mammals [ 2 , 3 , 4 ]. The 3D structure of FAM49B [ 5 , 6 ] has revealed the high similarity to a conserved domain of CYFIP proteins, the effectors of the small GTPase RAC1 [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Characterization and Functional Study of FAM49B Reveals Its Effect on Cell Proliferation in HEK293T Cells

Chen

Jiang

Lao

et al. 2022

Genes

View full text Add to dashboard Cite

FAM49B/Fam49b is a member of the Fam49 (Family with sequence similarity 49) gene family, which is characterized by the conserved domain, DUF1394 (Domain of Unknown Function 1394). It has also been named CYRI-B (CYFIP related RAC1 interactor B), implicating its important function of regulating RAC1-driven cytoskeleton remolding. In this study, to further investigate its functions and mechanisms affecting cell behaviors, HEK293T cells (where FAM49B is highly expressed) were used to establish a FAM49B knockout cell line by CRISPR/Cas9 genome editing technology. Our data have clearly revealed that there are triple alleles of FAM49B in the genome of HEK293T cells. Meanwhile, the proliferation deficiency of the FAM49B KO HEK293T cell line and the significantly changed cell proliferation related gene expression profiles, such as CCND1, have been uncovered. At the same time, the existence of isoform 3 has been confirmed in HEK293T cells. Our studies have suggested that FAM49B may also affect cell proliferation via Cyclins, besides its influence on the cytoskeleton.

show abstract

CYRI-A limits invasive migration through macropinosome formation and integrin uptake regulation

Cited by 21 publications

References 70 publications

Cell-based optimisation and characterisation of genetically encoded, location-based biosensors for Cdc42 or Rac activity

Cell-based optimisation and characterisation of genetically encoded, location-based biosensors for Cdc42 or Rac activity

Immune Score-based Molecular Subtypes and Signature Associated with Clinical Outcome in Hepatoblastoma

Characterization and Functional Study of FAM49B Reveals Its Effect on Cell Proliferation in HEK293T Cells

Contact Info

Product

Resources

About