Spatial multiomics map of trophoblast development in early pregnancy

The relationship between the human placenta-the extraembryonic organ made by the fetus, and the decidua-the mucosal layer of the uterus, is essential to nurture and protect the fetus during pregnancy. Extravillous trophoblast cells (EVTs) derived from placental villi infiltrate the decidua, transforming the maternal arteries into high-conductance vessels1. Defects in trophoblast invasion and arterial transformation established during early pregnancy underlie common pregnancy disorders such as pre-eclampsia2. Here we have generated a spatially resolved multiomics single-cell atlas of the entire human maternal-fetal interface including the myometrium, which enables us to resolve the full trajectory of trophoblast differentiation. We have used this cellular map to infer the possible transcription factors mediating EVT invasion and show that they are preserved in in vitro models of EVT differentiation from primary trophoblast organoids3,4 and trophoblast stem cells5. We define the transcriptomes of the final cell states of trophoblast invasion: placental bed giant cells (fused multinucleated EVTs) and endovascular EVTs (which form plugs inside the maternal arteries). We predict the cell-cell communication events contributing to trophoblast invasion and placental bed giant cell formation, and model the dual role of interstitial EVTs and endovascular EVTs in mediating arterial transformation during early pregnancy. Together, our data provide a comprehensive analysis of postimplantation trophoblast differentiation that can be used to inform the design of experimental models of the human placenta in early pregnancy.

Production of human entorhinal stellate cell-like cells by forward programming shows an important role of Foxp1 in reprogramming

Stellate cells are principal neurons in the entorhinal cortex that contribute to spatial processing. They also play a role in the context of Alzheimer's disease as they accumulate Amyloid beta early in the disease. Producing human stellate cells from pluripotent stem cells would allow researchers to study early mechanisms of Alzheimer's disease, however, no protocols currently exist for producing such cells. In order to develop novel stem cell protocols, we characterize at high resolution the development of the porcine medial entorhinal cortex by tracing neuronal and glial subtypes from mid-gestation to the adult brain to identify the transcriptomic profile of progenitor and adult stellate cells. Importantly, we could confirm the robustness of our data by extracting developmental factors from the identified intermediate stellate cell cluster and implemented these factors to generate putative intermediate stellate cells from human induced pluripotent stem cells. Six transcription factors identified from the stellate cell cluster including RUNX1T1, SOX5, FOXP1, MEF2C, TCF4, EYA2 were overexpressed using a forward programming approach to produce neurons expressing a unique combination of RELN, SATB2, LEF1 and BCL11B observed in stellate cells. Further analyses of the individual transcription factors led to the discovery that FOXP1 is critical in the reprogramming process and omission of RUNX1T1 and EYA2 enhances neuron conversion. Our findings contribute not only to the profiling of cell types within the developing and adult brain's medial entorhinal cortex but also provides proof-of-concept for using scRNAseq data to produce entorhinal intermediate stellate cells from human pluripotent stem cells in-vitro.

Extracting and Integrating Protein Localization Changes from Multiple Image Screens of Yeast Cells

The evaluation of protein localization changes in cells under diverse chemical and genetic perturbations is now possible due to the increasing quantity of screens that systematically image thousands of proteins in an organism. Integrating information from different screens provides valuable contextual information about the protein function. For example, proteins that change localization in response to many different stressful environmental perturbations may have different roles than those that only change in response to a few. We developed, to our knowledge, the first protocol that permits the quantitative comparison and clustering of protein localization changes across multiple screens. Our analysis allows for the exploratory analysis of proteins according to their pattern of localization changes across many different perturbations, potentially discovering new roles by association.

Integrating images from multiple microscopy screens reveals diverse patterns of change in the subcellular localization of proteins

The evaluation of protein localization changes on a systematic level is a powerful tool for understanding how cells respond to environmental, chemical, or genetic perturbations. To date, work in understanding these proteomic responses through high-throughput imaging has catalogued localization changes independently for each perturbation. To distinguish changes that are targeted responses to the specific perturbation or more generalized programs, we developed a scalable approach to visualize the localization behavior of proteins across multiple experiments as a quantitative pattern. By applying this approach to 24 experimental screens consisting of nearly 400,000 images, we differentiated specific responses from more generalized ones, discovered nuance in the localization behavior of stress-responsive proteins, and formed hypotheses by clustering proteins that have similar patterns. Previous approaches aim to capture all localization changes for a single screen as accurately as possible, whereas our work aims to integrate large amounts of imaging data to find unexpected new cell biology.