Anushka Yadav

Thetis cells (TCs) are a recently identified lineage of RORγt ⁺ antigen-presenting cells comprising four subsets, TC I to TC IV, including a tolerogenic subset (TC IV) that instructs tolerance to gut microbiota and food antigens ^1–6 . A developmental wave of TCs during early life creates a crucial window of opportunity for establishing intestinal tolerance ^1,5 . The ontogeny of TCs and the cues that shape their abundance and heterogeneity remain unknown, however, limiting efforts to harness their therapeutic potential. Here we identify a population of RORγt ⁺ progenitors, termed Thetis–lymphoid tissue inducer progenitors (TLPs), that give rise to the immediate TC progenitor (TCP) and the lymphoid tissue inducer (LTi) progenitor (LTiP), and identify PU.1 as the transcription factor that governs TC fate. Despite transcriptional similarity to myeloid-derived conventional dendritic cells, we show that TCs descend from the common lymphoid progenitor. Deletion of the plasmacytoid dendritic cell (pDC) lineage-determining transcription factor TCF4 expands TLPs and TCs, indicating a shared developmental branch with pDCs. TLPs are enriched in fetal liver, but, unlike LTi cells, TCs emerge postnatally, indicating that developmentally timed environmental cues promote TCP differentiation. We identify one such cue, RANKL provision by lymphoid tissue organizer cells, that is essential for TC I differentiation. Together, these findings define the ontogeny of TCs and the transcription factors that promote TC differentiation and heterogeneity, facilitating future investigations of these enigmatic cells and their therapeutic potential for tolerance induction in food allergy and autoimmunity.

Type 2 conventional dendritic cells (cDC2s) are functionally and phenotypically heterogenous. Previous work in mice and humans identified two cDC2 subsets (cDC2As and cDC2Bs) and a monocytic DC3 subset. However, the microenvironmental cues governing their distinct differentiation pathways remain unclear. Here, we delineate mouse cDC2 lineage relationships and the sequential signals required for cDC2A maintenance. We show that cDC2s, arising from the CLEC9A⁺ cDC progenitor, encompass T-BET-expressing cDC2As and two cDC2B subsets distinguished by MGL2 expression, with monocytic DC3s exhibiting transcriptional overlap with Mgl2⁻ cDC2Bs. Among these subsets, T-BET⁺ cDC2As dominate the spleen where they require cell-intrinsic retinoic acid signaling to sustain their differentiation via Notch signals. Lymphotoxin-β receptor signaling on splenic cDC2s limits F-actin content retaining cDC2s at sites of retinol delivery. In summary, these data establish the developmental and transcriptional relationships between diverse cDC2 subsets and identify signals that regulate their prevalence in specific lymphoid tissues.

Type II conventional dendritic cells (cDC2) are functionally and phenotypically heterogenous. Previous work in mice and humans identified two cDC2 subsets (cDC2A and cDC2B) and a monocytic DC3 subset. However, the microenvironmental cues governing their distinct differentiation pathways remain unclear. Here we delineate murine cDC2 lineage relationships and the sequential signals required for cDC2A maintenance. We show that cDC2s, arising from the CLEC9A+ cDC progenitor, encompass T-bet-expressing cDC2A and two cDC2B subsets distinguished by MGL2 expression, with monocytic DC3 exhibiting transcriptional overlap with Mgl2– cDC2B. Among these subsets, T-bet+ cDC2A dominate the spleen where they require cell-intrinsic retinoic acid (RA) signaling to sustain their differentiation via Notch signals. Lymphotoxin beta receptor signaling on splenic cDC2s limits F-actin content retaining cDC2 at sites of retinol delivery. In summary, these data establish the developmental and transcriptional relationships between diverse cDC2 subsets and identify signals that regulate their prevalence in specific lymphoid tissues.

Recent advances in high-throughput sequencing technologies have enabled the collection and sharing of a massive amount of omics data, along with its associated metadata—descriptive information that contextualizes the data, including phenotypic traits and experimental design. Enhancing metadata availability is critical to ensure data reusability and reproducibility and to facilitate novel biomedical discoveries through effective data reuse. Yet, incomplete metadata accompanying public omics data may hinder reproducibility and reusability and limit secondary analyses. Our study assesses the completeness of metadata in over 253 scientific studies, covering more than 164,000 samples from both human and non-human mammalian studies. We find that over 25% of critical metadata are omitted, with only 74.8% of relevant phenotypes available in publications or public repositories. Notably, public repositories alone contain 62% of the phenotypes, surpassing the textual content of publications by 3.5%. Only 11.5% of studies completely shared all phenotypes, while 37.9% shared less than 40% of the phenotypes. Additionally, studies with non-human samples are more likely to include complete metadata compared to human studies. Similar trends are observed in an extended dataset comprising 61,000 studies and 2.1 million samples from the Gene Expression Omnibus (GEO) data repository. These findings highlight significant gaps in metadata sharing, underscoring the need for standardized practices to improve metadata availability. Enhanced metadata reporting would foster data reusability, support better-informed decision-making, and promote reproducible research across the biomedical field.

Recent advances in high-throughput sequencing technologies have made it possible to collect and share a massive amount of omics data, along with its associated metadata. Enhancing metadata availability is critical to ensure data reusability and reproducibility and to facilitate novel biomedical discoveries through effective data reuse. Yet, incomplete metadata accompanying public omics data may hinder reproducibility and reusability by reducing sample interpretability and limiting secondary analyses. In this study, we performed a comprehensive assessment of metadata completeness shared in both scientific publications and/or public repositories by analyzing over 253 studies encompassing over 164 thousands samples, including both human and non-human mammalian studies. We observed that studies often omit over a quarter of important phenotypes, with an average of only 74.8% of them shared either in the text of publication or the corresponding repository. Notably, public repositories alone contained 62% of the metadata, surpassing the textual content of publications by 3.5%. Only 11.5% of studies completely shared all phenotypes, while 37.9% shared less than 40% of the phenotypes. Studies involving non-human samples were more likely to share metadata than studies involving human samples. We observed similar results on the extended dataset spanning 2.1 million samples across over 61,000 studies from the Gene Expression Omnibus repository. The limited availability of metadata reported in our study emphasizes the necessity for improved metadata sharing practices and standardized reporting. Finally, we discuss the numerous benefits of improving the availability and quality of metadata to the scientific community and beyond, supporting data-driven decision-making and policy development in the field of biomedical research. This work provides a scalable framework for evaluating metadata availability and may help guide future policy and infrastructure development.