Mycobacterium tuberculosis (MTB) ESX-1, a type VII secretion system, is a key virulence determinant contributing to MTB's survival within lung mononuclear phagocytes (MNPs), but its effect on MNP recruitment and differentiation remains unknown. Here, using multiple single-cell RNA sequencing techniques, we studied the role of ESX-1 in MNP heterogeneity and response in mice and murine bone marrow-derived macrophages (BMDM). We found that ESX-1 is required for MTB to recruit diverse MNP subsets with high MTB burden. Further, MTB induces a transcriptional signature of immune evasion in lung macrophages and BMDM in an ESX-1-dependent manner. Spatial transcriptomics revealed an up-regulation of permissive features within MTB lesions, where monocyte-derived macrophages concentrate near MTB-infected cells. Together, our findings suggest that MTB ESX-1 facilitates the recruitment and differentiation of MNPs, which MTB can infect and manipulate for survival. Our dataset across various models and methods could contribute to the broader understanding of recruited cell heterogeneity during MTB lung infection.

The mouse is a tractable model for human ovarian biology; however, its utility is limited by incomplete understanding of how transcription and signaling differ interspecifically and with age. We compared ovaries between species using three-dimensional imaging, single-cell transcriptomics, and functional studies. In mice, we mapped declining follicle numbers and oocyte competence during aging; in human ovaries, we identified cortical follicle pockets and decreases in density. Oocytes had species-specific gene expression patterns during growth that converged toward maturity. Age-related transcriptional changes were greater in oocytes than in granulosa cells across species, although mature oocytes change more in humans. We identified ovarian sympathetic nerves and glia; axon density increased in aged ovaries and, when ablated in mice, perturbed folliculogenesis. This comparative atlas defines shared and species-specific hallmarks of ovarian biology.

Elucidating organismal developmental processes requires a comprehensive understanding of cellular lineages in the spatial, temporal, and molecular domains. In this study, we introduce Zebrahub, a dynamic atlas of zebrafish embryonic development that integrates single-cell sequencing time course data with lineage reconstructions facilitated by light-sheet microscopy. This atlas offers high-resolution and in-depth molecular insights into zebrafish development, achieved through the sequencing of individual embryos across ten developmental stages, complemented by reconstructions of cellular trajectories. Zebrahub also incorporates an interactive tool to navigate the complex cellular flows and lineages derived from light-sheet microscopy data, enabling in silico fate-mapping experiments. To demonstrate the versatility of our multimodal resource, we utilize Zebrahub to provide fresh insights into the pluripotency of neuro-mesodermal progenitors (NMPs) and the origins of a joint kidney-hemangioblast progenitor population.

Mycobacterium tuberculosis (MTB) infects and replicates in lung mononuclear phagocytes (MNPs) with astounding ability to evade elimination. ESX-1, a type VII secretion system, acts as a virulence determinant that contributes to MTB's ability to survive within MNPs, but its effect on MNP recruitment and/or differentiation remains unknown. Here, using single-cell RNA sequencing, we studied the role of ESX-1 in MNP heterogeneity and response in mice and murine bone marrow-derived macrophages (BMDM). We found that ESX-1 is required for MTB to recruit diverse MNP subsets with high MTB burden. Further, MTB induces an anti-inflammatory signature in MNPs and BMDM in an ESX-1 dependent manner. Similarly, spatial transcriptomics revealed an upregulation of anti-inflammatory signals in MTB lesions, where monocyte-derived macrophages concentrate near MTB-infected cells. Together, our findings suggest that MTB ESX-1 mediates the recruitment and differentiation of anti-inflammatory MNPs, which MTB can infect and manipulate for survival.

Single-cell sequencing has revolutionized our understanding of cellular heterogeneity and cell state, enabling investigations across diverse fields such as developmental biology, immunology, and cancer biology. However, obtaining a high-quality single-cell suspension is still challenging, particularly when starting with limited materials like Zebrafish embryos, a powerful animal model for studying developmental processes and human diseases. Here, we present an optimized protocol for isolating single cells from individual zebrafish embryos, offering a valuable resource for researchers interested in working with limited starting material. The protocol facilitates unique investigations utilizing individual embryos, such as inter-individual genetic differences and embryo-specific lineage tracing analysis. Using a refined single-cell isolation protocol alongside zebrafish as a model organism, researchers can access a resource for exploring the emergence of all types and states of cells, advancing our understanding of cellular processes and disease mechanisms.

ABSTRACT Poxviruses are a large group of DNA viruses with exclusively cytoplasmic life cycles and complex gene expression programs. A number of systems-level studies have analyzed bulk transcriptome and proteome changes upon poxvirus infection, but the cell-to-cell heterogeneity of the transcriptomic response, and the subcellular resolution of proteomic changes have remained unexplored. Here, we measured single-cell transcriptomes of Vaccinia virus-infected populations of HeLa cells and immortalized human fibroblasts, resolving the cell-to-cell heterogeneity of infection dynamics and host responses within those cell populations. We further integrated our transcriptomic data with changes in the levels and subcellular localization of the host and viral proteome throughout the course of Vaccinia virus infection. Our findings from single-cell RNA sequencing indicate conserved transcriptome changes independent of the cellular context, including widespread host shutoff, heightened expression of cellular transcripts implicated in stress responses, the rapid accumulation of viral transcripts, and the robust activation of antiviral pathways in bystander cells. While most host factors were co-regulated at the RNA and protein level, we identified a subset of factors where transcript and protein levels were discordant in infected cells; predominantly factors involved in transcriptional and post-transcriptional mRNA regulation. In addition, we detected the relocalization of several host proteins such as TENT4A, NLRC5, and TRIM5, to different cellular compartments in infected cells. Collectively, our comprehensive data provide spatial and temporal resolution of the cellular and viral transcriptomes and proteomes and offer a robust foundation for in-depth exploration of virus-host interactions in poxvirus-infected cells.

Metastasis is the leading cause of cancer-related deaths. It is unclear how intratumor heterogeneity (ITH) contributes to metastasis and how metastatic cells adapt to distant tissue environments. The study of these adaptations is challenged by the limited access to patient material and a lack of experimental models that appropriately recapitulate ITH. To investigate metastatic cell adaptations and the contribution of ITH to metastasis, we analyzed single-cell transcriptomes of matched primary tumors and metastases from patient-derived xenograft models of breast cancer. We found profound transcriptional differences between the primary tumor and metastatic cells. Primary tumors upregulated several metabolic genes, whereas motility pathway genes were upregulated in micrometastases, and stress response signaling was upregulated during progression. Additionally, we identified primary tumor gene signatures that were associated with increased metastatic potential and correlated with patient outcomes. Immune-regulatory control pathways were enriched in poorly metastatic primary tumors, whereas genes involved in epithelial-mesenchymal transition were upregulated in highly metastatic tumors. We found that ITH was dominated by epithelial-mesenchymal plasticity (EMP), which presented as a dynamic continuum with intermediate EMP cell states characterized by specific genes such as CRYAB and S100A2. . Elevated expression of an intermediate EMP signature correlated with worse patient outcomes. Our findings identified inhibition of the intermediate EMP cell state as a potential therapeutic target to block metastasis.

During embryonic development, gene regulatory networks (GRNs) drive molecular differentiation of cell types. However, the temporal dynamics of these networks remain poorly understood. Here, we present Zebrahub-Multiome, a comprehensive, time-resolved atlas of zebrafish embryogenesis, integrating single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) from over 94,000 cells sampled across six key developmental stages (10 to 24 hours post-fertilization). Our analysis reveals early-stage GRNs shared across multiple lineages, followed by the emergence of lineage-specific regulatory programs during later stages. We also observe a shift in transcription factor (TF) influence from broad, multi-lineage roles in early development to more specialized, cell-type-specific functions as development progresses. Using in silico genetic perturbations, we highlight the dynamic role of TFs in driving cell fate decisions, emphasizing the gradual specialization of regulatory circuits. All data and analyses are made accessible through an interactive web portal, enabling users to explore zebrafish gene regulatory dynamics across time and cell types. This resource provides a foundation for hypothesis generation and deeper insights into vertebrate development. ### Competing Interest Statement The authors have declared no competing interest.

Glioblastoma (GBM) is an aggressive tumor with very bad prognosis. The urgent need to find new effective therapies is challenged by the unique characteristics of GBM, including high intra and intertumoral heterogeneity. Using single-nucleus transcriptomics (snRNA-seq), we characterized the panorama of a preclinical immunocompetent murine model based in the implantation of mouse glioblastoma stem cells (GL261-GSCs) into the brain parenchyma. Additionally, we performed Visium spatial transcriptomics in the in vivo model to confirm the location of annotated cells. To understand the technical bias of this approach, we performed two scRNA-seq methods in GBM cells. We thoroughly characterized the tumor microenvironment (TME) at early and late stages of tumor development and upon treatment with temozolomide (TMZ), the standard of care for patients with GBM, and with Tat-Cx43 266-283 , a promising experimental treatment. We identified prominent GBM targets that can be addressed using this preclinical model, such as Grik2 , Nlgn3 , Gap43 or Kcnn4 , which are involved in electrical and synaptic integration of GBM cells into neural circuits, as well as the expression of Nt5e , Cd274 or Irf8 , which indicates the development of immune evasive properties in these GBM cells. In agreement, snRNA-seq unveiled high expression of several immunosuppressive-associated molecules in immune cells, such as Csf1r, Arg1, Mrc1 and Tgfb1 , suggesting the development of an immunosuppressive microenvironment. We also show the landscape of cytokines, cytokine receptors, checkpoint ligands and receptors in tumor and TME cells, which are crucial data for a rational design of immunotherapy studies. Thus, Mrc1, PD-L1, TIM-3 or B7-H3 are among the immunotherapy targets that can be addressed in this model. Finally, the comparison of the preclinical GL261-GSC GBM model with human GBM subtypes unveiled important similarities with the recently identified TMEmed human GBM, indicating that preclinical data obtained in GL261-GSC GBM model might be applied to TMEmed human GBM, improving patient stratification in clinical trials. In conclusion, this work provides crucial information for future preclinical studies in GBM improving their clinical application.

Assigning cell identity to clusters of single cells is an essential step towards extracting biological insights from many genomics datasets. Although annotation workflows for datasets built with a single modality are well established, limitations exist in annotating cell types in datasets with multiple modalities due to the need for a framework to exploit them jointly. While, in principle, different modalities could convey complementary information about cell identity, it is unclear to what extent they can be combined to improve the accuracy and resolution of cell type annotations. Here, we present a conceptual framework to examine and jointly interrogate distinct modalities to identify cell types. We integrated our framework into a series of vignettes, using immune cells as a well-studied example, and demonstrate cell type annotation workflows ranging from using single-cell RNA-seq datasets alone, to using multiple modalities such as single-cell Multiome (RNA and chromatin accessibility), CITE-seq (RNA and surface proteins). In some cases, one or other single modality is superior to the other for identification of specific cell types, in others combining the two modalities improves resolution and the ability to identify finer subpopulations. Finally, we use interactive software from CZ CELLxGENE community tools to visualize and integrate histological and spatial transcriptomic data.

Spatial transcriptomics extends single cell RNA sequencing (scRNA-seq) technologies by providing spatial context for cell type identification and analysis. In particular, imaging-based spatial technologies such as Multiplexed Error-Robust Fluorescence In Situ Hybridization (MERFISH) can achieve single-cell resolution, allowing for the direct mapping of single cell identities to spatial positions. Nevertheless, because MERFISH produces an intrinsically different data type than scRNA-seq methods, a technical comparison between the two modalities is necessary to ascertain how best to integrate them. Here, we used the Vizgen MERSCOPE platform to perform MERFISH on mouse liver and kidney tissues and compared the resulting bulk and single-cell RNA statistics with those from the existing Tabula Muris Senis cell atlas. We found that MERFISH produced measurements that quantitatively reproduced the bulk RNA-seq and scRNA-seq results, with some minor differences in overall gene dropout rates and single-cell transcript count statistics. Finally, we explored the ability of MERFISH to identify cell types, and found that it could independently resolve distinct cell types and spatial structure in both liver and kidney. Computational integration with the Tabula Muris Senis atlas using scVI and scANVI did not noticeably enhance these results. We conclude that compared to scRNA-seq, MERFISH provides a quantitatively comparable method for measuring single-cell gene expression, and that efficient gene panel design allows for robust identification of cell types with intact spatial information without the need for computational integration with scRNA-seq reference atlases.

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.

The ability to slow or reverse biological ageing would have major implications for mitigating disease risk and maintaining vitality1. Although an increasing number of interventions show promise for rejuvenation2, their effectiveness on disparate cell types across the body and the molecular pathways susceptible to rejuvenation remain largely unexplored. Here we performed single-cell RNA sequencing on 20 organs to reveal cell-type-specific responses to young and aged blood in heterochronic parabiosis. Adipose mesenchymal stromal cells, haematopoietic stem cells and hepatocytes are among those cell types that are especially responsive. On the pathway level, young blood invokes new gene sets in addition to reversing established ageing patterns, with the global rescue of genes encoding electron transport chain subunits pinpointing a prominent role of mitochondrial function in parabiosis-mediated rejuvenation. We observed an almost universal loss of gene expression with age that is largely mimicked by parabiosis: aged blood reduces global gene expression, and young blood restores it in select cell types. Together, these data lay the groundwork for a systemic understanding of the interplay between blood-borne factors and cellular integrity.

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 a 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 the mouse liver and kidney and compared the resulting bulk and single-cell RNA statistics with those from the Tabula Muris Senis cell atlas and 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 the liver and kidney. Computational integration with the Tabula Muris Senis atlas did not enhance these results. We conclude that MERFISH provides a quantitatively comparable method for single-cell gene expression and can identify cell types without the need for computational integration with scRNA-seq atlases.

Author(s): Crawford, Emily D; Acosta, Irene; Ahyong, Vida; Anderson, Erika C; Arevalo, Shaun; Asarnow, Daniel; Axelrod, Shannon; Ayscue, Patrick; Azimi, Camillia S; Azumaya, Caleigh M; Bachl, Stefanie; Bachmutsky, Iris; Bhaduri, Aparna; Brown, Jeremy Bancroft; Batson, Joshua; Behnert, Astrid; Boileau, Ryan M; Bollam, Saumya R; Bonny, Alain R; Booth, David; Borja, Michael Jerico B; Brown, David; Buie, Bryan; Burnett, Cassandra E; Byrnes, Lauren E; Cabral, Katelyn A; Cabrera, Joana P; Caldera, Saharai; Canales, Gabriela; Castaneda, Gloria R; Chan, Agnes Protacio; Chang, Christopher R; Charles-Orszag, Arthur; Cheung, Carly; Chio, Unseng; Chow, Eric D; Citron, Y Rose; Cohen, Allison; Cohn, Lillian B; Chiu, Charles; Cole, Mitchel A; Conrad, Daniel N; Constantino, Angela; Cote, Andrew; Crayton-Hall, Tre'Jon; Darmanis, Spyros; Detweiler, Angela M; Dial, Rebekah L; Dong, Shen; Duarte, Elias M; Dynerman, David; Egger, Rebecca; Fanton, Alison; Frumm, Stacey M; Fu, Becky Xu Hua; Garcia, Valentina E; Garcia, Julie; Gladkova, Christina; Goldman, Miriam; Gomez-Sjoberg, Rafael; Gordon, M Grace; Grove, James CR; Gupta, Shweta; Haddjeri-Hopkins, Alexis; Hadley, Pierce; Haliburton, John; Hao, Samantha L; Hartoularos, George; Herrera, Nadia; Hilberg, Melissa; Ho, Kit Ying E; Hoppe, Nicholas; Hosseinzadeh, Shayan; Howard, Conor J; Hussmann, Jeffrey A; Hwang, Elizabeth; Ingebrigtsen, Danielle; Jackson, Julia R; Jowhar, Ziad M; Kain, Danielle; Kim, James YS; Kistler, Amy; Kreutzfeld, Oriana; Kulsuptrakul, Jessie; Kung, Andrew F

CLIAHUB How-To.pdf 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. EXTERNAL LINK https://doi.org/10.1371/journal.ppat.1008966 THIS PROTOCOL ACCOMPANIES THE FOLLOWING PUBLICATION Crawford ED, Acosta I, Ahyong V, Anderson EC, Arevalo S, Asarnow D, Axelrod S, Ayscue P, Azimi CS, Azumaya CM, Bachl S, Bachmutsky I, Bhaduri A, Brown JB, Batson J, Behnert A, Boileau RM, Bollam SR, Bonny AR, Booth D, Borja MJB, Brown D, Buie B, Burnett CE, Byrnes LE, Cabral KA, Cabrera JP, Caldera S, Canales G, Castañeda GR, Chan AP, Chang CR, Charles-Orszag A, Cheung C, Chio U, Chow ED, Citron YR, Cohen A, Cohn LB, Chiu C, Cole MA, Conrad DN, Constantino A, Cote A, Crayton-Hall T, Darmanis S, Detweiler AM, Dial RL, Dong S, Duarte EM, Dynerman D, Egger R, Fanton A, Frumm SM, Fu BXH, Garcia VE, Garcia J, Gladkova C, Goldman M, Gomez-Sjoberg R, Gordon MG, Grove JCR, Gupta S, HaddjeriHopkins A, Hadley P, Haliburton J, Hao SL, Hartoularos G, Herrera N, Hilberg M, Ho KYE, Hoppe N, Hosseinzadeh S, Howard CJ, Hussmann JA, Hwang E, Ingebrigtsen D, Jackson JR, Jowhar ZM, Kain D, Kim JYS, Kistler A, Kreutzfeld O, Kulsuptrakul J, Kung AF, Langelier C, Laurie MT, Lee L, Leng K, Leon KE, Leonetti MD, Levan SR, Li S, Li AW, Liu J, Lubin HS, Lyden A, Mann J, Mann S, Margulis G, Marquez DM, Marsh BP, Martyn C, McCarthy EE, McGeever A, Merriman AF, Meyer LK, Miller S, Moore MK, Mowery CT, Mukhtar T, Mwakibete LL, Narez N, Neff NF, Osso LA, Oviedo D, Peng S, Phelps M, Phong K, Picard P, Pieper LM, Pincha N, Pisco AO, Pogson A, Pourmal S, Puccinelli RR, Puschnik AS, Rackaityte E, Raghavan P, Raghavan M, Reese J, Replogle JM, Retallack H, Reyes H, Rose D, Rosenberg MF, Sanchez-Guerrero E, Sattler SM, Savy L, See SK, Sellers KK, Serpa PH, Sheehy M, Sheu J, Silas S, Streithorst JA, Strickland J, Stryke D, Sunshine S, Suslow P, Sutanto R, Tamura S, Tan M, Tan J, Tang A, Tato CM, Taylor JC, Tenvooren I, Thompson EM, Thornborrow EC, Tse E, Tung T, Turner ML, Turner VS, Turnham RE, Turocy MJ, Vaidyanathan TV, Vainchtein ID, Vanaerschot M, Vazquez SE, Wandler AM, Wapniarski A, Webber JT, Weinberg ZY, Westbrook A, Wong AW, Wong E, Worthington G, Xie F, Xu A, Yamamoto T, Yang Y, Yarza F, Zaltsman Y, Zheng T, DeRisi JL (2020) Rapid deployment of SARS-CoV-2 testing: The CLIAHUB. PLoS Pathog 16(10): e1008966. doi: 10.1371/journal.ppat.1008966 1 07/06/2020 Cita tion : Amy Lyden, Emily Crawford, Vida Ahyong, Manu Vanaerschot, Paula Hayakawa Serpa, Preethi Raghavan, Joana Cabrera, Michael Borja, Spyros Darmanis, Eric Chow, Joseph Derisi (07/06/2020). CLIAHUB Automated RNA Extraction & RT-PCR Protocol V2. https://dx.doi.org/10.17504/protocols.io.bfi2jkge This is an open access protocol distributed under the terms of the Crea tive Com m ons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited DOI dx.doi.org/10.17504/protocols.io.bfi2jkge EXTERNAL LINK https://doi.org/10.1371/journal.ppat.1008966 PROTOCOL CITATION Amy Lyden, Emily Crawford, Vida Ahyong, Manu Vanaerschot, Paula Hayakawa Serpa, Preethi Raghavan, Joana Cabrera, Michael Borja, Spyros Darmanis, Eric Chow, Joseph Derisi 2020. CLIAHUB Automated RNA Extraction & RT-PCR Protocol V2. protocols.io https://dx.doi.org/10.17504/protocols.io.bfi2jkge MANUSCRIPT CITATION please remember to cite the following publication along with this protocol Crawford ED, Acosta I, Ahyong V, Anderson EC, Arevalo S, Asarnow D, Axelrod S, Ayscue P, Azimi CS, Azumaya CM, Bachl S, Bachmutsky I, Bhaduri A, Brown JB, Batson J, Behnert A, Boileau RM, Bollam SR, Bonny AR, Booth D, Borja MJB, Brown D, Buie B, Burnett CE, Byrnes LE, Cabral KA, Cabrera JP, Caldera S, Canales G, Castañeda GR, Chan AP, Chang CR, Charles-Orszag A, Cheung C, Chio U, Chow ED, Citron YR, Cohen A, Cohn LB, Chiu C, Cole MA, Conrad DN, Constantino A, Cote A, Crayton-Hall T, Darmanis S, Detweiler AM, Dial RL, Dong S, Duarte EM, Dynerman D, Egger R, Fanton A, Frumm SM, Fu BXH, Garcia VE, Garcia J, Gladkova C, Goldman M, Gomez-Sjoberg R, Gordon MG, Grove JCR, Gupta S, HaddjeriHopkins A, Hadley P, Haliburton J, Hao SL, Hartoularos G, Herrera N, Hilberg M, Ho KYE, Hoppe N, Hosseinzadeh S, Howard CJ, Hussmann JA, Hwang E, Ingebrigtsen D, Jackson JR, Jowhar ZM, Kain D, Kim JYS, Kistler A, Kreutzfeld O, Kulsuptrakul J, Kung AF, Langelier C, Laurie MT, Lee L, Leng K, Leon KE, Leonetti MD, Levan SR, Li S, Li AW, Liu J, Lubin HS, Lyden A, Mann J, Mann S, Margulis G, Marquez DM, Marsh BP, Martyn C, McCarthy EE, McGeever A, Merriman AF, Meyer LK, Miller S, Moore MK, Mowery CT, Mukhtar T, Mwakibete LL, Narez N, Neff NF, Osso LA, Oviedo D, Peng S, Phelps M, Phong K, Picard P, Pieper LM, Pincha N, Pisco AO, Pogson A, Pourmal S, Puccinelli RR, Puschnik AS, Rackaityte E, Raghavan P, Raghavan M, Reese J, Replogle JM, Retallack H, Reyes H, Rose D, Rosenberg MF, Sanchez-Guerrero E, Sattler SM, Savy L, See SK, Sellers KK, Serpa PH, Sheehy M, Sheu J, Silas S, Streithorst JA, Strickland J, Stryke D, Sunshine S, Suslow P, Sutanto R, Tamura S, Tan M, Tan J, Tang A, Tato CM, Taylor JC, Tenvooren I, Thompson EM, Thornborrow EC, Tse E, Tung T, Turner ML, Turner VS, Turnham RE, Turocy MJ, Vaidyanathan TV, Vainchtein ID, Vanaerschot M, Vazquez SE, Wandler AM, Wapniarski A, Webber JT, Weinberg ZY, Westbrook A, Wong AW, Wong E, Worthington G, Xie F, Xu A, Yamamoto T, Yang Y, Yarza F, Zaltsman Y, Zheng T, DeRisi JL (2020) Rapid deployment of SARS-CoV-2 testing: The CLIAHUB. PLoS Pathog 16(10): e1008966. doi: 10.1371/journal.ppat.1008966 COLLECTIONS 2020 Featured Protocols LICENSE This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited CREATED Apr 24, 2020 LAST MODIFIED Jul 13, 2020 PROTOCOL INTEGER ID 36154 PARENT PROTOCOLS Part of collection 2020 Featured Protocols MATERIALS TEXT MATERIALS Quick-DNA/RNA Viral MagBead Zymo Research Catalog #R2140 / R2141 Biorad "F" Foil PCR Plate Microseal Contr ibuted by users Catalog # ​MSF1001 ​ N-gene E-gene and RNAse P primers and probes (see steps qPCR section for sequences) Contr ibuted by users 1mL Fisherbrand 96 deep well plates Contr ibuted by users Catalog #12-566-611 2mL Fisherbrand 96 deep well plates Contr ibuted by users Catalog #12-566-612 Sigma 100% Ethanol Contr ibuted by users Catalog #E7203 2 07/06/2020 Cita tion : Amy Lyden, Emily Crawford, Vida Ahyong, Manu Vanaerschot, Paula Hayakawa Serpa, Preethi Raghavan, Joana Cabrera, Michael Borja, Spyros Darmanis, Eric Chow, Joseph Derisi (07/06/2020). CLIAHUB Automated RNA Extraction & RT-PCR Protocol V2. https://dx.doi.org/10.17504/protocols.io.bfi2jkge This is an open access protocol distributed under the terms of the Crea tive Com m ons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Bio-rad Hard-shell thin-wall 384 well PCR plates Contr ibuted by users Catalog #HSP3905 Zymo 2x DNA/RNA Shield Contr ibuted by users Catalog #R1200-125 Zymo RNA Prep Buffer Contr ibuted by users Catalog #R1060-2-100 Bio-rad Hard-shell low-profile 96 well skirted PCR plates Contr ibuted by users Catalog #HSP9601 Zymo DNAse I Contr ibuted by users Catalog #E1011 Sigma Isopropanol Contr ibuted by users Catalog #190764-4L Beta-mercaptoethanol Contr ibuted by users Catalog #97622-10X1ML TTP Labtech Dragonfly Contr ibuted by users TTP Labtech Syringes Contr ibuted by users Catalog #4150-07200 TTP Labtech Reservoirs Contr ibuted by users Catalog #4150-07202 Thermo Multidrop Contr ibuted by users Catalog #5840300 Thermo Multidrop