Introduction: Improved understanding of throat colonization in the presence of other co-existing microbes is important for mapping adaptation to the human throat, and recurrence of infection. Here, we explore the responses triggered by the encounter between two common throat bacteria, and , to identify genes in that are important for colonization in the presence of human tonsillar epithelial cells and , and further compare this transcriptome with the genes expressed in as only bacterium.
Methods: We performed an co-culture experiment followed by RNA sequencing to identify interaction-induced transcriptional alterations and differentially expressed genes (DEGs), followed by gene enrichment analysis.
Results And Discussion: A total of 332 and 279 significantly differentially expressed genes with p-value < 0.05 and log FoldChange (logFC) ≥ |2| were identified in after 1 h and 3 h co-culturing, respectively. Alterations in expression of various survival factors were observed when co-cultured with and tonsillar cells. The serine-aspartate repeat-containing protein D () involved in adhesion, was for example highly upregulated in during co-culturing with compared to grown in the absence of , especially at 3 h. Several virulence genes encoding secreted proteins were also highly upregulated only when was co-cultured with and tonsillar cells, and iron does not appear to be a limiting factor in this environment. These findings may be useful for the development of interventions against throat colonization and could be further investigated to decipher the roles of the identified genes in the host immune response in context of a throat commensal landscape.
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http://dx.doi.org/10.3389/fcimb.2024.1326730 | DOI Listing |
Theranostics
January 2025
Nano-Bio Regenerative Medical Institute, College of Medicine, Hallym University, Chuncheon 24252, Republic of Korea.
This study investigates a method for programming immune cells using a biomaterial-based system, providing an alternative to traditional cell manipulation techniques. It addresses the limitations of engineered adoptive T cell therapies, such as T cell exhaustion, by introducing a gelatin-hyaluronic acid (GH-GMA) hydrogel system. We characterized tonsil mesenchymal stem cells (TMSCs), lymphatic endothelial cells (T-LECs), stimulated T-CD8 T cells (STCs), and GH-GMA biomaterials.
View Article and Find Full Text PDFCells
December 2024
Department of Biochemistry, College of Medicine, Ewha Womans University, Seoul 07804, Republic of Korea.
In general, the nerve cells of the peripheral nervous system regenerate normally within a certain period after the physical damage of their axon. However, when peripheral nerves are transected by trauma or tissue extraction for cancer treatment, spontaneous nerve regeneration cannot occur. Therefore, it is necessary to perform microsurgery to connect the transected nerve directly or insert a nerve conduit to connect it.
View Article and Find Full Text PDFGenes (Basel)
December 2024
Department of Biochemistry and Molecular Biology, Kangwon National University School of Medicine, Chuncheon 24341, Republic of Korea.
Background/objectives: Tonsil-derived mesenchymal stem cells (TMSCs) are in the limelight in regenerative medicine due to their high proliferation and differentiation potential. It is important to conduct studies to determine the optimal conditions for achieving the maximum yield while maintaining the optimal differentiation capacity of TMSCs.
Methods: This study explores the impact of serial subculture on TMSCs by analyzing gene expression at passages 2, 4, 6, and 8.
Cancers (Basel)
December 2024
Multidisciplinary Institute for Investigation in Pediatric Pathologies (IMIPP), CONICET-GCBA, Pathology Division, Ricardo Gutiérrez Children's Hospital, Buenos Aires C1425EFD, Argentina.
: The Epstein-Barr virus (EBV) infects more than 90 percent of the human population. In pediatric patients, the innate immune response against EBV primary infection plays a key role. Monocytes and macrophages can have distinct functions depending on the microenvironment surrounding them.
View Article and Find Full Text PDFNat Commun
January 2025
Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Spatial protein expression technologies can map cellular content and organization by simultaneously quantifying the expression of >40 proteins at subcellular resolution within intact tissue sections and cell lines. However, necessary image segmentation to single cells is challenging and error prone, easily confounding the interpretation of cellular phenotypes and cell clusters. To address these limitations, we present STARLING, a probabilistic machine learning model designed to quantify cell populations from spatial protein expression data while accounting for segmentation errors.
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