Transcript-specific enrichment enables profiling rare cell states via scRNA-seq.

Single-cell genomics technologies have accelerated our understanding of cell-state heterogeneity in diverse contexts. Although single-cell RNA sequencing (scRNA-seq) identifies many rare populations of interest that express specific marker transcript combinations, traditional flow sorting limits our ability to enrich these populations for further profiling, including requiring cell surface markers with high-fidelity antibodies. Additionally, many single-cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. To address these limitations, we describe Programmable Enrichment via RNA Flow-FISH by sequencing (PERFF-seq), a scalable assay that enables scRNA-seq profiling of subpopulations from complex cellular mixtures defined by the presence or absence of specific RNA transcripts. Across immune populations (n = 141,227 cells) and fresh-frozen and formalin-fixed paraffin-embedded brain tissue (n = 29,522 nuclei), we demonstrate the sorting logic that can be used to enrich for cell populations via RNA-based cytometry followed by high-throughput scRNA-seq. Our approach provides a rational, programmable method for studying rare populations identified by one or more marker transcripts.

The covariance environment defines cellular niches for spatial inference.

A key challenge of analyzing data from high-resolution spatial profiling technologies is to suitably represent the features of cellular neighborhoods or niches. Here we introduce the covariance environment (COVET), a representation that leverages the gene-gene covariate structure across cells in the niche to capture the multivariate nature of cellular interactions within it. We define a principled optimal transport-based distance metric between COVET niches that scales to millions of cells. Using COVET to encode spatial context, we developed environmental variational inference (ENVI), a conditional variational autoencoder that jointly embeds spatial and single-cell RNA sequencing data into a latent space. ENVI includes two decoders: one to impute gene expression across the spatial modality and a second to project spatial information onto single-cell data. ENVI can confer spatial context to genomics data from single dissociated cells and outperforms alternatives for imputing gene expression on diverse spatial datasets.

Implementation of a pooled surveillance testing program for asymptomatic SARS-CoV-2 infections in K-12 schools and universities.

BACKGROUND: The negative impact of continued school closures during the height of the COVID-19 pandemic warrants the establishment of cost-effective strategies for surveillance and screening to safely reopen and monitor for potential in-school transmission. Here, we present a novel approach to increase the availability of repetitive and routine COVID-19 testing that may ultimately reduce the overall viral burden in the community. METHODS: We implemented a testing program using the SalivaClear࣪ pooled surveillance method that included students, faculty and staff from K-12 schools (student age range 5-18 years) and universities (student age range >18 years) across the country (Mirimus Clinical Labs, Brooklyn, NY). The data analysis was performed using descriptive statistics, kappa agreement, and outlier detection analysis. FINDINGS: From August 27, 2020 until January 13, 2021, 253,406 saliva specimens were self-collected from students, faculty and staff from 93 K-12 schools and 18 universities. Pool sizes of up to 24 samples were tested over a 20-week period. Pooled testing did not significantly alter the sensitivity of the molecular assay in terms of both qualitative (100% detection rate on both pooled and individual samples) and quantitative (comparable cycle threshold (Ct) values between pooled and individual samples) measures. The detection of SARS-CoV-2 in saliva was comparable to the nasopharyngeal swab. Pooling samples substantially reduced the costs associated with PCR testing and allowed schools to rapidly assess transmission and adjust prevention protocols as necessary. In one instance, in-school transmission of the virus was determined within the main office and led to review and revision of heating, ventilating and air-conditioning systems. INTERPRETATION: By establishing low-cost, weekly testing of students and faculty, pooled saliva analysis for the presence of SARS-CoV-2 enabled schools to determine whether transmission had occurred, make data-driven decisions, and adjust safety protocols. We provide strong evidence that pooled testing may be a fundamental component to the reopening of schools by minimizing the risk of in-school transmission among students and faculty. FUNDING: Skoll Foundation generously provided funding to Mobilizing Foundation and Mirimus for these studies.