| 1. |
- N'Guessan, PD., et al.
(författare)
-
The UspA1 protein of Moraxella catarrhalis induces CEACAM-1-dependent apoptosis in alveolar epithelial cells.
- 2007
-
Ingår i: Journal of Infectious Diseases. - : Oxford University Press (OUP). - 1537-6613 .- 0022-1899. ; 195:11, s. 1651-1660
-
Tidskriftsartikel (refereegranskat)abstract
- Moraxella catarrhalis is a major cause of exacerbations of chronic obstructive pulmonary disease (COPD) and emphysema. M. catarrhalis–specific UspA1 and the epithelial carcinoembryonic antigen-related cell adhesion molecule (CEACAM1) were required to induce apoptosis. M. catarrhalis–induced apoptosis was significantly enhanced in HeLa cells stably transfected with CEACAM1, compared with HeLa cells not expressing CEACAM1. Infected cells showed increased activity of caspases 3, 6, and 9 but not of caspase 8. Reduced expression of Bcl-2, translocation of Bax into the mitochondria, and cytosolic increase of apoptosis-inducing factor in M. catarrhalis–infected cells implicated the involvement of mitochondrial death pathways. In conclusion, M. catarrhalis induced apoptosis in pulmonary epithelial cells—a process that was triggered by interaction between CEACAM1 and UspA1. Thus, M. catarrhalis–induced apoptosis of pulmonary epithelial cells may contribute to the development of COPD and emphysema.
|
|
| 2. |
- Demichev, Vadim, et al.
(författare)
-
A time-resolved proteomic and prognostic map of COVID-19
- 2021
-
Ingår i: Cell Systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 12:8, s. 780-794.e7
-
Tidskriftsartikel (refereegranskat)abstract
- COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.
|
|
| 3. |
- Messner, Christoph B., et al.
(författare)
-
Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection
- 2020
-
Ingår i: Cell Systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 11:1, s. 11-24.E4
-
Tidskriftsartikel (refereegranskat)abstract
- The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.
|
|
