Arce, M. | Search bioRxiv

bioRxiv2026

A decrease in specific health-associated commensals is linked to progressive periodontal tissue destruction independent of dysbiotic community profiles

Periodontitis is a chronic inflammatory disease associated with dysbiotic microbial communities that leads to destruction of the tooth-supporting tissues. The transition from host-microbial periodontal homeostasis to disease remains poorly understood. The murine ligature-induced periodontitis model was employed to characterize the temporal dynamics of the subgingival microbiome and host tissue features. Ligatures were placed in C57BL/6N mice, and collected on days 0, 1, 3, 5, and 7 post-induction. Bacterial load, alveolar bone loss, immune cells (CD45), cells with osteoclastogenic potential (TRAP) and collagen destruction were analyzed. Additionally, the V4 region of the 16S rRNA gene was sequenced for ecological analyses, including co-occurrence networks and functional prediction. Spatial distribution of the most abundant species was visualized using CLASI-FISH microscopy. Finally, association models were performed to link bacterial abundances with time and tissue parameters. The most substantial microbial shift occurred on day 1, and a dysbiotic community was established by day 3. CD45 cell infiltration increased as early as day 1, preceding the rise in TRAP cells on day 3 and the onset of tissue destruction on day 5. By day 7, predicted bacterial functions included protein export, lipid and galactose metabolism. Health-associated taxa were identified, and their abundance correlated positively with collagen integrity and negatively with immune cell infiltration and bacterial load, highlighting their role in homeostasis. These findings provide a high-resolution temporal map of microbiome-host interactions during experimental periodontitis establishment and identify specific microbial and cellular windows for potential therapeutic intervention.

microbiology↗

bioRxiv2025

In vivo genome-wide CRISPR screens in human T cells to enhance T cell therapy for solid tumors

Large-scale CRISPR screening in human T cells holds significant promise for identifying genetic modifications that can enhance cellular immunotherapy. However, many genetic regulators of T cell performance in solid tumors may not be readily revealed in vitro. In vivo screening in tumor-bearing mice offers greater physiological relevance, but has historically been limited by low intratumoral T cell recovery. Here, we developed a new model system that achieves significantly higher human T cell recovery from tumors, enabling genome-wide in vivo screens with small numbers of mice. Tumor-infiltrating T cells in this model exhibit hallmarks of dysfunction compared to matched splenic T cells, creating an ideal context for screening for genetic modifiers of T cell activity in the tumor microenvironment. Using this platform, we performed two genome-wide CRISPR knockout screens to identify genes regulating T cell intratumoral abundance and effector function (e.g., IFN-{gamma} production). The intratumoral abundance screen uncovered the P2RY8-G13 GPCR signaling pathway as a negative regulator of human T cell infiltration into tumors. The effector function screen identified GNAS (Gs), a central signaling mediator downstream of multiple GPCRs that sense different suppressive ligands, as a key regulator of T cell dysfunction in tumors. Targeted GNAS knockout rendered T cells resistant to multiple suppressive cues and significantly improved therapeutic performance across diverse solid tumor models. Moreover, combinatorial knockout of P2RY8 (trafficking) and GNAS (effector function) further enhanced overall tumor control, demonstrating that genetic modifications targeting distinct T cell phenotypes can be combined to improve therapeutic potency. This flexible and scalable in vivo screening platform can be adapted to diverse tumor models and pooled CRISPR libraries, enabling future discovery of genetic strategies that equip T cell therapies to overcome barriers imposed by solid tumors.

immunology↗