Single-cell quantification of ribosome occupancy in early mouse development.

Translation regulation is critical for early mammalian embryonic development1. However, previous studies had been restricted to bulk measurements2, precluding precise determination of translation regulation including allele-specific analyses. Here, to address this challenge, we developed a novel microfluidic isotachophoresis (ITP) approach, named RIBOsome profiling via ITP (Ribo-ITP), and characterized translation in single oocytes and embryos during early mouse development. We identified differential translation efficiency as a key mechanism regulating genes involved in centrosome organization and N6-methyladenosine modification of RNAs. Our high-coverage measurements enabled, to our knowledge, the first analysis of allele-specific ribosome engagement in early development. These led to the discovery of stage-specific differential engagement of zygotic RNAs with ribosomes and reduced translation efficiency of transcripts exhibiting allele-biased expression. By integrating our measurements with proteomics data, we discovered that ribosome occupancy in germinal vesicle-stage oocytes is the predominant determinant of protein abundance in the zygote. The Ribo-ITP approach will enable numerous applications by providing high-coverage and high-resolution ribosome occupancy measurements from ultra-low input samples including single cells.

SARS-CoV-2 RNA in Wastewater Settled Solids Is Associated with COVID-19 Cases in a Large Urban Sewershed.

Wastewater-based epidemiology may be useful for informing public health response to viral diseases like COVID-19 caused by SARS-CoV-2. We quantified SARS-CoV-2 RNA in wastewater influent and primary settled solids in two wastewater treatment plants to inform the preanalytical and analytical approaches and to assess whether influent or solids harbored more viral targets. The primary settled solids samples resulted in higher SARS-CoV-2 detection frequencies than the corresponding influent samples. Likewise, SARS-CoV-2 RNA was more readily detected in solids using one-step digital droplet (dd)RT-PCR than with two-step RT-QPCR and two-step ddRT-PCR, likely owing to reduced inhibition with the one-step ddRT-PCR assay. We subsequently analyzed a longitudinal time series of 89 settled solids samples from a single plant for SARS-CoV-2 RNA as well as coronavirus recovery (bovine coronavirus) and fecal strength (pepper mild mottle virus) controls. SARS-CoV-2 RNA targets N1 and N2 concentrations correlated positively and significantly with COVID-19 clinically confirmed case counts in the sewershed. Together, the results demonstrate that measuring SARS-CoV-2 RNA concentrations in settled solids may be a more sensitive approach than measuring SARS-CoV-2 in influent.

Genome-wide reconstruction of complex structural variants using read clouds.

In read cloud approaches, microfluidic partitioning of long genomic DNA fragments and barcoding of shorter fragments derived from these fragments retains long-range information in short sequencing reads. This combination of short reads with long-range information represents a powerful alternative to single-molecule long-read sequencing. We develop Genome-wide Reconstruction of Complex Structural Variants (GROC-SVs) for SV detection and assembly from read cloud data and apply this method to Illumina-sequenced 10x Genomics sarcoma and breast cancer data sets. Compared with short-fragment sequencing, GROC-SVs substantially improves the specificity of breakpoint detection at comparable sensitivity. This approach also performs sequence assembly across multiple breakpoints simultaneously, enabling the reconstruction of events exhibiting remarkable complexity. We show that chromothriptic rearrangements occurred before copy number amplifications, and that rates of single-nucleotide variants and SVs are not correlated. Our results support the use of read cloud approaches to advance the characterization of large and complex structural variation.

Measurement of Oxidatively Induced DNA Damage in Caenorhabditis elegans with High-Salt DNA Extraction and Isotope-Dilution Mass Spectrometry.

Caenorhabditis elegans is used extensively as a medical and toxicological model organism. However, little is known about background levels of oxidatively induced DNA damage in the nematode or how culturing methods affect DNA damage levels. The tough C. elegans cuticle makes it challenging to extract genomic DNA without harsh procedures that can artifactually increase DNA damage. Therefore, a mild extraction protocol based on enzymatic digestion of the C. elegans cuticle with high-salt phase-separation of DNA has been developed and optimized. This method allows for efficient extraction of >50 µg DNA using a minimum of 250000 nematodes grown in liquid culture. The extracted DNA exhibited acceptable RNA levels (<10% contamination), functionality in polymerase chain reaction assays, and reproducible DNA fragmentation. Gas chromatography/tandem mass spectrometry (GC-MS/MS) with isotope-dilution measured lower lesion levels in high-salt extracts than in phenol extracts. Phenolic extraction produced a statistically significant increase in 8-hydroxyguanine, a known artifact, and additional artifactual increases in 2,6-diamino-4-hydroxy-5-formamidopyrimidine, 4,6-diamino-5-formamidopyrimidine, and 8-hydroxyadenine. The high-salt DNA extraction procedure utilizes green solvents and reagents and minimizes artifactual DNA damage, making it more suitable for molecular and toxicological studies in C. elegans. This is, to our knowledge, the first use of GC-MS/MS to measure multiple 8,5'-cyclopurine-2'-deoxynucleosides in a toxicologically important terrestrial organism.

SARS-CoV-2 RNA and N Antigen Quantification via Wastewater at the Campus Level, Building Cluster Level, and Individual-Building Level.

Monitoring wastewater for SARS-CoV-2 from populations smaller than those served by wastewater treatment plants may help identify small spatial areas (subsewersheds) where COVID-19 infections are present. We sampled wastewater from three nested locations with different sized populations within the same sewer network at a university campus and quantified SARS-CoV-2 RNA using reverse transcriptase droplet digital polymerase chain reaction (PCR). SARS-CoV-2 RNA concentrations and/or concentrations normalized by PMMoV were positively associated with laboratory-confirmed COVID-19 cases for both the sewershed level and the subsewershed level. We also used an antigen-based assay to detect the nucleocapsid (N) antigen from SARS-CoV-2 in wastewater samples at the sewershed level. The N antigen was regularly detected at the sewershed level, but the results were not associated with either laboratory-confirmed COVID-19 cases or SARS-CoV-2 RNA concentrations. The results of this study indicate that wastewater monitoring based on quantification of SARS-CoV-2 RNA using PCR-based methods is associated with COVID-19 cases at multiple geographic scales within the subsewershed level and can serve to aid the public health response.

Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917.

Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Material® 2917 (NIST SRM® 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study investigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 laboratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within- and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.

Scaling of SARS-CoV-2 RNA in Settled Solids from Multiple Wastewater Treatment Plants to Compare Incidence Rates of Laboratory-Confirmed COVID-19 in Their Sewersheds.

Published and unpublished reports show that SARS-CoV-2 RNA in publicly owned treatment work (POTW) wastewater influent and solids is associated with new COVID-19 cases or incidence in associated sewersheds, but methods for comparing data collected from diverse POTWs to infer information about the relative incidence of laboratory-confirmed COVID-19 cases, and scaling to allow such comparisons, have not been previously established. Here, we show that SARS-CoV-2 N1 and N2 concentrations in solids normalized by concentrations of PMMoV RNA in solids can be used to compare incidence of laboratory confirmed new COVID-19 cases across POTWs. Using data collected at seven POTWs along the United States West Coast, Midwest, and East Coast serving ∼3% of the U.S. population (9 million people), we show that a 1 log change in N gene/PMMoV is associated with a 0.24 (range 0.19 to 0.29) log10 change in incidence of laboratory confirmed COVID-19. Scaling of N1 and N2 by PMMoV is consistent, conceptually, with a mass balance model relating SARS-CoV-2 RNA to the number of infected individuals shedding virus in their stool. This information should support the application of wastewater-based epidemiology to inform the response to the COVID-19 pandemic and potentially future viral pandemics.

Simultaneous RNA purification and size selection using on-chip isotachophoresis with an ionic spacer.

We present an on-chip method for the extraction of RNA within a specific size range from low-abundance samples. We use isotachophoresis (ITP) with an ionic spacer and a sieving matrix to enable size-selection with a high yield of RNA in the target size range. The spacer zone separates two concentrated ITP peaks, the first containing unwanted single nucleotides and the second focusing RNA of the target size range (2-35 nt). Our ITP method excludes >90% of single nucleotides and >65% of longer RNAs (>35 nt). Compared to size selection using gel electrophoresis, ITP-based size-selection yields a 2.2-fold increase in the amount of extracted RNAs within the target size range. We also demonstrate compatibility of the ITP-based size-selection with downstream next generation sequencing. On-chip ITP-prepared samples reveal higher reproducibility of transcript-specific measurements compared to samples size-selected by gel electrophoresis. Our method offers an attractive alternative to conventional sample preparation for sequencing with shorter assay time, higher extraction efficiency and reproducibility. Potential applications of ITP-based size-selection include sequencing-based analyses of small RNAs from low-abundance samples such as rare cell types, samples from fluorescence activated cell sorting (FACS), or limited clinical samples.

Extensive sequencing of seven human genomes to characterize benchmark reference materials.

The Genome in a Bottle Consortium, hosted by the National Institute of Standards and Technology (NIST) is creating reference materials and data for human genome sequencing, as well as methods for genome comparison and benchmarking. Here, we describe a large, diverse set of sequencing data for seven human genomes; five are current or candidate NIST Reference Materials. The pilot genome, NA12878, has been released as NIST RM 8398. We also describe data from two Personal Genome Project trios, one of Ashkenazim Jewish ancestry and one of Chinese ancestry. The data come from 12 technologies: BioNano Genomics, Complete Genomics paired-end and LFR, Ion Proton exome, Oxford Nanopore, Pacific Biosciences, SOLiD, 10X Genomics GemCode WGS, and Illumina exome and WGS paired-end, mate-pair, and synthetic long reads. Cell lines, DNA, and data from these individuals are publicly available. Therefore, we expect these data to be useful for revealing novel information about the human genome and improving sequencing technologies, SNP, indel, and structural variant calling, and de novo assembly.