Premature ovarian insufficiency (POI) affects approximately 1% of women. We aim to understand the ovarian microenvironment, including the extracellular matrix (ECM) and associated proteins (matrisome), and its role in controlling folliculogenesis. We mapped the composition of the matrisome of porcine ovaries through the cortical compartment, where quiescent follicles reside and the medullary compartment, where the larger follicles grow and mature. To do this we sliced the ovaries, uniformly in two anatomical planes, enriched for matrisome proteins and performed bottom-up shotgun proteomic analyses. We identified 42 matrisome proteins that were significantly differentially expressed across depths, and 11 matrisome proteins that have not been identified in previous ovarian protein analyses. We validated these data for nine proteins and confirmed compartmental differences with a second processing method. Here we describe a processing and proteomic analysis pipeline that revealed spatial differences and matrisome protein candidates that may influence folliculogenesis.

CD4 T cells help immune responses, but knowledge of how memory CD4 T cells are regulated and how they regulate adaptive immune responses and induce immunopathology is limited. Using adoptive transfer of virus-specific CD4 T cells, we show that naive CD4 T cells undergo substantial expansion following infection, but can induce lethal T helper type 1-driven inflammation. In contrast, memory CD4 T cells exhibit a biased proliferation of T follicular helper cell subsets and were able to improve adaptive immune responses in the context of minimal tissue damage. Our analyses revealed that type I interferon regulates the expansion of primary CD4 T cells, but does not seem to play a critical role in regulating the expansion of secondary CD4 T cells. Strikingly, blockade of type I interferon abrogated lethal inflammation by primary CD4 T cells following viral infection, despite that this treatment increased the numbers of primary CD4 T-cell responses. Altogether, these data demonstrate important aspects of how primary and secondary CD4 T cells are regulated in vivo, and how they contribute to immune protection and immunopathology. These findings are important for rational vaccine design and for improving adoptive T-cell therapies against persistent antigens.

The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research.HuBMAP was founded with the goal of establishing state-of-the-art frameworks for building spatial multiomic maps of non-diseased human organs at single-cell resolution 1 . During the first phase (2018)(2019)(2020)(2021)(2022), the priorities of the project included the validation and development of assay platforms; workflows for data processing, management, exploration and visualization; and the establishment of protocols, quality control standards and standard operating procedures. Extensive infrastructure was established through a coordinated effort among the various HuB-MAP integration, visualization and engagement teams, tissue-mapping centres, technology and tools development and rapid technology implementation teams and working groups 1 . Single-cell maps, predominantly consisting of two-dimensional (2D) spatial data as well as data from dissociated cells, were generated for several organs. The HuBMAP Data Portal (https://portal.hubmapconsortium.org) was established for open access to experimental tissue data and reference atlas data.The infrastructure was augmented with software tools for tissue data registration, processing, annotation, visualization, cell segmentation and automated annotation of cell types and cellular neighbourhoods from spatial data. Computational methods were developed for integrating multiple data types across scales and interpretation 2 . Standard reference terminology and a common coordinate framework spanning anatomical to biomolecular scales were established to ensure interoperability across organs, research groups and consortia 3 . Guidelines to capture high-quality multiplexed spatial data 4 were established including validated panels of cell-and structure-specific antibodies 5 . The first phase produced a large number of manuscripts (https://commonfund.nih.gov/ publications?pid=43) including spatially resolved single-cell maps [6][7][8][9][10][11] .The production phase of HuBMAP was launched in the autumn of 2022. The focus is on scaling data production spanning diverse biological variables (for example, age and ethnicity) and deployment and enhancement of analytical, visualization and navigational tools to generate high-resolution 3D accessible maps of major functional tissue units from more than 20 organs. This phase involves over 60 institutions and 400 researchers with opportunities for active intra-and inter-consortia collaborations and building a foundational resource for new biological insights and precision medicine. Below, ...

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