A humanized β2 integrin knockin mouse reveals localized intra- and extravascular neutrophil integrin activation in vivo

Wen, Lai; Márki, Alex; Wang, Zhihao; Orecchioni, Marco; Makings, Jeffrey; Billitti, Monica; Wang, Erpei; Suthahar, Sujit Silas Armstrong; Kim, Kenneth S.; Kiosses, William B.; Mikulski, Zbigniew; Ley, Klaus

doi:10.1016/j.celrep.2022.110876

Cited by 7 publications

(9 citation statements)

References 63 publications

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“…Recent study further revealed that PTPRC downregulated significantly in patients with PD [ 34 ]. ITGB2, which encoded the β2 integrin subunit, is implicated in defective adhesion and the subsequent inflammatory reaction [ 35 ]. Bioinformatic analysis revealed that ITGB2 was robust in microglia and played a role in the pathological mechanism of AD [ 36 ].…”

Section: Discussionmentioning

confidence: 99%

Proteomic Analysis of Protective Effects of Dl-3-n-Butylphthalide against mpp + -Induced Toxicity via downregulating P53 pathway in N2A Cells

Zhao

Zhang

et al. 2023

Proteome Sci

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Background Dl-3-n-butylphthalide (NBP) is an important medial therapy for acute ischemic stroke in China. Recent studied have revealed that NBP not only rescued the loss of dopaminergic neurons in cellular and animal models of Parkinson's disease (PD), but also could improve motor symptoms in PD patients. However, the protective mechanism is not fully understood. P53 is a multifunctional protein implicated in numerous cellular processes, including apoptosis, DNA repair, mitochondrial functions, redox homeostasis, autophagy and protein aggregations. In PD, p53 integrated with various neurodegeneration-related signals inducing neuronal loss, indicating the suppression of P53 might be a promising target for PD treatment. Therefore, the purpose of the current study was to systemically screen new therapeutic targets of NBP in PD. Method In our study, we constructed mpp + induced N2A cells to investigate the benefit effect of NBP in PD. MTT assay was performed to evaluate the cell viability; TMT-based LC–MS/MS was applied to determine the different expressed proteins (DEPs) of NBP pretreatment; online bioinformatics databases such as DAVID, STRING, and KEGG was used to construe the proteomic data. After further analyzed and visualized the protein–protein interactions (PPI) by Cytoscape, DEPs were verified by western blot. Result A total of 5828 proteins were quantified in the comparative proteomics experiments and 417 proteins were considered as DEPs (fold change > 1.5 and p < 0.05). Among the 417 DEPs, 140 were upregulated and 277 were downregulated in mpp + -induced N2A cells with NBP pretreatment. KEGG pathway analysis indicated that lysosome, phagosome, apoptosis, endocytosis and ferroptosis are the mainly enriched pathways. By using MCL clustering in PPI analysis, 48 clusters were generated and the subsequent KEGG analysis of the top 3 clusters revealed that P53 signaling pathway was recognized as the dominant pathway for NBP treatment. Conclusion NBP significantly relived mpp + -induced cell toxicity. The neuroprotective role of NBP was implicated with P53 signaling pathway in some extent. These findings will reinforce the understanding of the mechanism of NBP in PD and identify novel therapeutic targets.

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Section: Discussionmentioning

confidence: 99%

Proteomic Analysis of Protective Effects of Dl-3-n-Butylphthalide against mpp + -Induced Toxicity via downregulating P53 pathway in N2A Cells

Zhao

Zhang

et al. 2023

Proteome Sci

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“…ITGB2 also complexes with other integrins like ITGAL, yet the contribution of each of these distinct receptors in Mab uptake remains unknown and will be examined in the future. While human and murine ITGB2 proteins are highly similar, it will be important to directly test the role of this integrin in Mab uptake in human macrophages ( 54 ). In addition, investigating how Mab uptake by distinct receptors alters intracellular trafficking and/or bacterial control will better define key host-pathogen interactions during Mab infections.…”

Section: Discussionmentioning

confidence: 99%

A Genome-Wide Screen in Macrophages Defines Host Genes Regulating the Uptake of Mycobacterium abscessus

Gilliland

Beckman

Olive

2023

mSphere

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“…The FCER2A − (ITGAM + ITGB2) signal between B cells and high-risk cells was activated. The MIF − (CD74 + CD44) signal between B cells and low-risk cells was activated (Bu et al 2020 ; Parvaneh et al 2010 ; Wen et al 2022 ; Tilstam et al 2021 ; Martin 2000 ). The SELPLG-SELL signal between DC cells and low-risk cells was activated (Bime et al 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Use of machine learning-based integration to develop a monocyte differentiation-related signature for improving prognosis in patients with sepsis

Ning

Sun

Wang

et al. 2023

Mol Med

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Background Although significant advances have been made in intensive care medicine and antibacterial treatment, sepsis is still a common disease with high mortality. The condition of sepsis patients changes rapidly, and each hour of delay in the administration of appropriate antibiotic treatment can lead to a 4–7% increase in fatality. Therefore, early diagnosis and intervention may help improve the prognosis of patients with sepsis. Methods We obtained single-cell sequencing data from 12 patients. This included 14,622 cells from four patients with bacterial infectious sepsis and eight patients with sepsis admitted to the ICU for other various reasons. Monocyte differentiation trajectories were analyzed using the “monocle” software, and differentiation-related genes were identified. Based on the expression of differentiation-related genes, 99 machine-learning combinations of prognostic signatures were obtained, and risk scores were calculated for all patients. The “scissor” software was used to associate high-risk and low-risk patients with individual cells. The “cellchat” software was used to demonstrate the regulatory relationships between high-risk and low-risk cells in a cellular communication network. The diagnostic value and prognostic predictive value of Enah/Vasp-like (EVL) were determined. Clinical validation of the results was performed with 40 samples. The “CBNplot” software based on Bayesian network inference was used to construct EVL regulatory networks. Results We systematically analyzed three cell states during monocyte differentiation. The differential analysis identified 166 monocyte differentiation-related genes. Among the 99 machine-learning combinations of prognostic signatures constructed, the Lasso + CoxBoost signature with 17 genes showed the best prognostic prediction performance. The highest percentage of high-risk cells was found in state one. Cell communication analysis demonstrated regulatory networks between high-risk and low-risk cell subpopulations and other immune cells. We then determined the diagnostic and prognostic value of EVL stabilization in multiple external datasets. Experiments with clinical samples demonstrated the accuracy of this analysis. Finally, Bayesian network inference revealed potential network mechanisms of EVL regulation. Conclusions Monocyte differentiation-related prognostic signatures based on the Lasso + CoxBoost combination were able to accurately predict the prognostic status of patients with sepsis. In addition, low EVL expression was associated with poor prognosis in sepsis.

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A humanized β2 integrin knockin mouse reveals localized intra- and extravascular neutrophil integrin activation in vivo

Cited by 7 publications

References 63 publications

Proteomic Analysis of Protective Effects of Dl-3-n-Butylphthalide against mpp + -Induced Toxicity via downregulating P53 pathway in N2A Cells

Proteomic Analysis of Protective Effects of Dl-3-n-Butylphthalide against mpp + -Induced Toxicity via downregulating P53 pathway in N2A Cells

A Genome-Wide Screen in Macrophages Defines Host Genes Regulating the Uptake of Mycobacterium abscessus

Use of machine learning-based integration to develop a monocyte differentiation-related signature for improving prognosis in patients with sepsis

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