Functional evaluation of TMEM176B and its predictive role for severe respiratory viral infection through integrated analysis of single-cell and bulk RNA-sequencing.

Functional evaluation of TMEM176B and its predictive role for severe respiratory viral infection through integrated analysis of single-cell and bulk RNA-sequencing.

Publication date: Oct 01, 2024

Transmembrane protein 176B (TMEM176B), localized mainly on the endosomal membrane, has been reported as an immune regulatory factor in malignant diseases. However, the biological function of this molecule remains undetermined during respiratory viral infections. To investigate the functions and prognostic value of this gene, six gene sets were selected from the Gene Expression Omnibus database for research. First, the function of TMEM176B and its co-expressed genes were evaluated at different levels (cell, peripheral blood, lung tissue). Afterwards, a machine learning algorithm was utilized to analyze the relationship between TMEM176B and its interacting genes with prognosis. After importance evaluation and variable screening, a prognostic model was established. Finally, the reliability of the model was further verified through external data sets. In vitro experiments were conducted to validate the function of TMEM176B. TMEM176B and its co-expressed genes are involved in multiple processes such as inflammasome activation, myeloid immune cell development, and immune cell infiltration. Machine learning further screened 27 interacting gene modules including TMEM176B as prognostic models for severe respiratory viral infections, with the area under the ROC curve (AUCs) of 0. 986 and 0. 905 in derivation and external validation sets, respectively. We further confirmed that viral load as well as NLRP3 activation and cell death were significantly enhanced in TMEM176B THP-1-differentiated macrophages via in vitro experiments. Our study revealed that TMEM176B is involved in a wide range of biological functions in respiratory viral infections and has potential prognostic value, which is expected to bring new insights into the clinical management of severe respiratory viral infection hosts.

Concepts Keywords
Models Gene Expression Profiling
Myeloid Humans
Research Machine Learning
Tmem176b Membrane Proteins
Viral Membrane Proteins
monocytes/macrophages
Prognosis
prognostic model
Respiratory Tract Infections
Sequence Analysis, RNA
Single-Cell Analysis
TMEM176B

Semantics

Type Source Name
disease IDO role
disease MESH viral infection
disease IDO cell
disease IDO blood
disease IDO algorithm
drug DRUGBANK Saquinavir
disease MESH viral load
disease MESH Respiratory Tract Infections
disease MESH influenza

Original Article

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