Search

Elucidating the developmental process of an organism will require the complete cartography of cellular lineages in the spatial, temporal, and molecular domains. We present Zebrahub, a comprehensive dynamic atlas of zebrafish embryonic development that combines single-cell sequencing time course data with light-sheet microscopy-based lineage reconstructions. Zebrahub is a foundational resource to study developmental processes at both transcriptional and spatiotemporal levels. It is publicly accessible as a web-based resource, providing an open-access collection of datasets and tools. Using this resource we shed new light on the pluripotency of Neuro-Mesodermal Progenitors (NMPs). We find that NMPs are pluripotent only during early axis elongation before becoming exclusively mesodermal progenitors. We attribute this restriction in NMP cell fate to emerging morphodynamic features that compartmentalize tissue motion.

Metastasis is the leading cause of cancer-related deaths, but metastasis research is challenged by limited access to patient material and a lack of experimental models that appropriately recapitulate tumor heterogeneity. Here, we analyzed single-cell transcriptomes of matched primary tumor and metastasis from patient-derived xenograft models of breast cancer, demonstrating that primary tumor and metastatic cells show profound transcriptional differences across heterogeneous tumors. While primary tumor cells upregulated several metabolic genes, metastatic cells displayed a motility phenotype in micrometastatic lesions and increased stress response signaling during metastatic progression. Additionally, we identified gene signatures that are associated with the metastatic potential and correlated with patient outcomes. Poorly metastatic primary tumors showed increased immune-regulatory control that may prevent metastasis, whereas highly metastatic primary tumors upregulated markers of epithelial-mesenchymal transition (EMT). We found that intra-tumor heterogeneity is dominated by epithelial-mesenchymal plasticity (EMP) which presented as a dynamic continuum with intermediate cell states that were characterized by novel, specific markers. These intermediate EMP markers correlated with worse patient outcomes and could serve as potential new therapeutic targets to block metastatic development.

Spatial transcriptomics extends single cell RNA sequencing (scRNA-seq) by providing spatial context for cell type identification and analysis. Imaging-based spatial technologies such as Multiplexed Error-Robust Fluorescence In Situ Hybridization (MERFISH) can achieve single-cell resolution, directly mapping single cell identities to spatial positions. MERFISH produces an intrinsically different data type than scRNA-seq and a technical comparison between the two modalities is necessary to ascertain how to best integrate them. We performed MERFISH on mouse liver and kidney and compared the resulting bulk and single-cell RNA statistics with those from the Tabula Muris Senis cell atlas as well as from two Visium datasets. MERFISH quantitatively reproduced the bulk RNA-seq and scRNA-seq results with improvements in overall dropout rates and sensitivity. Finally, we found that MERFISH independently resolved distinct cell types and spatial structure in both liver and kidney. Computational integration with the Tabula Muris Senis atlas did not enhance these results. We conclude that compared to scRNA-seq, MERFISH provides a quantitatively comparable method for measuring single-cell gene expression and can robustly identify cell types without the need for computational integration with scRNA-seq reference atlases.

Github: (to be added) Laboratory testing for COVID-19 infection is an important part of both the individual patient care and public health responses to this emerging outbreak. Results are used to guide containment efforts, including isolation and contact tracing, and make clinical diagnosis for supportive management and experimental therapies (there is no known efficacious treatment available for COVID-19 infection as of March 2020). Real-time reverse transcriptase PCR (rRT-PCR) testing is a well-established method to detect viral RNA in clinical samples, and several labs around the world have designed and validated primers and probes for this purpose that are also used in this assay (4 and 5). This assay is intended to qualitatively detect COVID-19 viral RNA in patient samples to enable the diagnosis of COVID-19 disease. Testing should be performed for patients with signs and symptoms of potential COVID-19 infection. Positive results would generally indicate active infection but do not rule out co-infection with other viruses, bacteria or other pathogens. Negative test results do not absolutely rule out infection, and results should be interpreted in the clinical context. The oligonucleotide primers and probes for detection of SARS-CoV-2 were selected from regions of the Nucleoprotein (N gene)and the Envelope protein (E gene). An additional primer/probe set to detect the human RNase P gene (RP) in control samples and clinical specimens is also included in the panel. RNA isolated and purified from upper respiratory specimens is reverse transcribed to cDNA and subsequently amplified on the Bio-Rad CFX Real Time PCR Machine. In the process, the probes anneal to a specific target sequence located between the forward and reverse primers. During the extension phase of the PCR cycle, the 5’ nuclease activity of Taq polymerase degrades the probe, causing the reporter dye to separate from the quencher dye, generating a fluorescent signal. With each cycle, additional reporter dye molecules are cleaved from their respective probes, increasing the fluorescence intensity. Detection of viral RNA not only aids in the diagnosis of illness but also provides epidemiological and surveillance information.