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Defining the structure of the NF-ĸB pathway in human immune cells using quantitative proteomic data.

ABSTRACT: The NF-ĸB transcription factor is a critical regulator of immune homeostasis and inflammatory responses and is a critical factor in the pathogenesis of inflammatory disease. The pathways to NF-ĸB activation are paradigms for signal-induced ubiquitination and proteasomal degradation, control of transcription factor function by subcellular localisation, and the control of gene transcription and physiological processes by signal transduction mechanisms. Despite the importance of NF-ĸB in disease, the NF-ĸB pathway remains unexploited for the treatment of inflammatory disease. Our understanding of NF-ĸB comes mostly from studies of transgenic mice and cell lines where components of the pathway have been deleted or over expressed. Recent advances in quantitative proteomics offer new opportunities to understand the NF-ĸB pathway using the absolute abundance of individual pathway components. We have analysed available quantitative proteomic datasets to establish the structure of the NF-ĸB pathway in human immune cells under both steady state and activated conditions. This reveals a conserved NF-κB pathway structure across different immune cell lineages and identifies important differences to the current model of the NF-ĸB pathway. These include the findings that the IKK complex in most cells is likely to consist predominantly of IKKβ homodimers, that the relative abundancies of IκB proteins show strong cell type variation, and that the components of the non-canonical NF-ĸB pathway are significantly increased in activated immune cells. These findings challenge aspects of our current view of the NF-κB pathway and identify outstanding questions important for defining the role of key components in regulating inflammation and immunity.

SUBMITTER: Kok FO

PROVIDER: S-EPMC8573605 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice of using a competitive null as common approach; which fundamentally implies genes or proteins as independent units. The independent assumption ignores the associations among biomolecules with similar functions or cellular localization, as well as the interactions among them manifested as changes in expression ratios. Consequently, these methods often underestimate the associations among biomolecules and cause false positives in practice. Some studies incorporate the sample covariance matrix into the calculation to address this issue. However, sample covariance may not be a precise estimation if the sample size is very limited, which is usually the case for the data produced by mass spectrometry. In this study, we introduce a multivariate test under a self-contained null to perform pathway analysis for quantitative proteomic data. The covariance matrix used in the test statistic is constructed by the confidence scores retrieved from the STRING database or the HitPredict database. We also design an integrating procedure to retain pathways of sufficient evidence as a pathway group. The performance of the proposed T2-statistic is demonstrated using five published experimental datasets: the T-cell activation, the cAMP/PKA signaling, the myoblast differentiation, and the effect of dasatinib on the BCR-ABL pathway are proteomic datasets produced by mass spectrometry; and the protective effect of myocilin via the MAPK signaling pathway is a gene expression dataset of limited sample size. Compared with other popular statistics, the proposed T2-statistic yields more accurate descriptions in agreement with the discussion of the original publication. We implemented the T2-statistic into an R package T2GA, which is available at https://github.com/roqe/T2GA.

Project description:Brain induced extracellular vesicle (BDEV) elevates after traumatic brain injury (TBI) and contributes to secondary brain injury. However, the role of BDEV in TBI remains unclear. In this study, we determined the mechanisms of BDEV in brain injury and explored whether neuroprotective drug BKca channel opener NS1619 may attenuate BDEV-induced brain injury. We injected BDEV and lactadherin, respectively, to mimic the up and downregulation of BDEV after TBI and illustrated the role of BDEV in vivo. In vitro, the membrane potential and calcium concentration of HT-22, bEnd3, and BV-2 were measured by fluorescent staining. The effects of BDEV and NS1619 on HT-22 were evaluated by CCK-8, LDH release assay, Na+/k+-ATPase activity, JC-1 staining, DHE staining, and 4-HNE staining, respectively. The role of BDEV and NS1619 on the Nrf2/HO-1/p65 pathway was also evaluated in HT-22. Finally, we administrated TBI mice with NS1619 to clarify the role of NS1619 against BDEV in vivo. Our results suggested that BDEV aggravated and lactadherin mitigated TBI-induced EB leakage, brain edema, neuronal degeneration, apoptosis, ROS level, microgliosis, MMP-9 activity, and NF-κB activation. In vitro, BDEV-caused depolarized membrane potential and calcium overload were significantly attenuated by NS1619 in HT-22, bEnd3, and BV-2. BDEV markedly decreased cell viability, Na+/k+-ATPase activity, and caused mitochondrial dysregulation, oxidative stress, and NF-ĸB activation. NS1619 pretreatment alleviated above process and enhanced antioxidant system Nrf2/HO-1 in HT-22. Finally, NS1619 administration significantly inhibited neuroinflammation response and improved TBI outcome after TBI. NS1619 treatment also reduced 4-HNE content and NF-ĸB activation and enhanced Nrf2/HO-1 pathway. Our data showed that BDEV aggravated brain injury by perturbing cell membrane potential, calcium homeostasis, oxidative stress, and neuroinflammation. The BKca channel opener NS1619 attenuated BDEV-induced pathological process in vitro and in vivo by modulating the BKca channel and Nrf2/HO-1/NF-ĸB pathway.

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Defining the structure of the NF-ĸB pathway in human immune cells using quantitative proteomic data.

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