Emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States.

The highly transmissible B.1.1.7 variant of SARS-CoV-2, first identified in the United Kingdom, has gained a foothold across the world. Using S gene target failure (SGTF) and SARS-CoV-2 genomic sequencing, we investigated the prevalence and dynamics of this variant in the United States (US), tracking it back to its early emergence. We found that, while the fraction of B.1.1.7 varied by state, the variant increased at a logistic rate with a roughly weekly doubling rate and an increased transmission of 40%-50%. We revealed several independent introductions of B.1.1.7 into the US as early as late November 2020, with community transmission spreading it to most states within months. We show that the US is on a similar trajectory as other countries where B.1.1.7 became dominant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.

Emergence of an early SARS-CoV-2 epidemic in the United States.

The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.

A Small RNA-Catalytic Argonaute Pathway Tunes Germline Transcript Levels to Ensure Embryonic Divisions.

Multiple division cycles without growth are a characteristic feature of early embryogenesis. The female germline loads proteins and RNAs into oocytes to support these divisions, which lack many quality control mechanisms operating in somatic cells undergoing growth. Here, we describe a small RNA-Argonaute pathway that ensures early embryonic divisions in C. elegans by employing catalytic slicing activity to broadly tune, instead of silence, germline gene expression. Misregulation of one target, a kinesin-13 microtubule depolymerase, underlies a major phenotype associated with pathway loss. Tuning of target transcript levels is guided by the density of homologous small RNAs, whose generation must ultimately be related to target sequence. Thus, the tuning action of a small RNA-catalytic Argonaute pathway generates oocytes capable of supporting embryogenesis. We speculate that the specialized nature of germline chromatin led to the emergence of small RNA-catalytic Argonaute pathways in the female germline as a post-transcriptional control layer to optimize oocyte composition.

Pseudouridine synthases modify human pre-mRNA co-transcriptionally and affect pre-mRNA processing.

Pseudouridine is a modified nucleotide that is prevalent in human mRNAs and is dynamically regulated. Here, we investigate when in their life cycle mRNAs become pseudouridylated to illuminate the potential regulatory functions of endogenous mRNA pseudouridylation. Using single-nucleotide resolution pseudouridine profiling on chromatin-associated RNA from human cells, we identified pseudouridines in nascent pre-mRNA at locations associated with alternatively spliced regions, enriched near splice sites, and overlapping hundreds of binding sites for RNA-binding proteins. In vitro splicing assays establish a direct effect of individual endogenous pre-mRNA pseudouridines on splicing efficiency. We validate hundreds of pre-mRNA sites as direct targets of distinct pseudouridine synthases and show that PUS1, PUS7, and RPUSD4-three pre-mRNA-modifying pseudouridine synthases with tissue-specific expression-control widespread changes in alternative pre-mRNA splicing and 3' end processing. Our results establish a vast potential for cotranscriptional pre-mRNA pseudouridylation to regulate human gene expression via alternative pre-mRNA processing.

Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1-3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Context-dependent functional compensation between Ythdf m6A reader proteins.

The N6-methyladenosine (m6A) modification is the most prevalent post-transcriptional mRNA modification, regulating mRNA decay and splicing. It plays a major role during normal development, differentiation, and disease progression. The modification is regulated by a set of writer, eraser, and reader proteins. The YTH domain family of proteins consists of three homologous m6A-binding proteins, Ythdf1, Ythdf2, and Ythdf3, which were suggested to have different cellular functions. However, their sequence similarity and their tendency to bind the same targets suggest that they may have overlapping roles. We systematically knocked out (KO) the Mettl3 writer, each of the Ythdf readers, and the three readers together (triple-KO). We then estimated the effect in vivo in mouse gametogenesis, postnatal viability, and in vitro in mouse embryonic stem cells (mESCs). In gametogenesis, Mettl3-KO severity is increased as the deletion occurs earlier in the process, and Ythdf2 has a dominant role that cannot be compensated by Ythdf1 or Ythdf3, due to differences in readers' expression pattern across different cell types, both in quantity and in spatial location. Knocking out the three readers together and systematically testing viable offspring genotypes revealed a redundancy in the readers' role during early development that is Ythdf1/2/3 gene dosage-dependent. Finally, in mESCs there is compensation between the three Ythdf reader proteins, since the resistance to differentiate and the significant effect on mRNA decay occur only in the triple-KO cells and not in the single KOs. Thus, we suggest a new model for the Ythdf readers function, in which there is profound dosage-dependent redundancy when all three readers are equivalently coexpressed in the same cell types.

A Transcriptome-wide Translational Program Defined by LIN28B Expression Level.

LIN28 RNA binding proteins are dynamically expressed throughout mammalian development and during disease. However, it remains unclear how changes in LIN28 expression define patterns of post-transcriptional gene regulation. Here we show that LIN28 expression level is a key variable that sets the magnitude of protein translation. By systematically varying LIN28B protein levels in human cells, we discovered a dose-dependent divergence in transcriptome-wide ribosome occupancy that enabled the formation of two discrete translational subpopulations composed of nearly all expressed genes. This bifurcation in gene expression was mediated by a redistribution in Argonaute association, from let-7 to non-let-7 microRNA families, resulting in a global shift in cellular miRNA activity. Post-transcriptional effects were scaled across the physiological LIN28 expression range. Together, these data highlight the central importance of RBP expression level and its ability to encode regulation.

A large-scale binding and functional map of human RNA-binding proteins.

Many proteins regulate the expression of genes by binding to specific regions encoded in the genome1. Here we introduce a new data set of RNA elements in the human genome that are recognized by RNA-binding proteins (RBPs), generated as part of the Encyclopedia of DNA Elements (ENCODE) project phase III. This class of regulatory elements functions only when transcribed into RNA, as they serve as the binding sites for RBPs that control post-transcriptional processes such as splicing, cleavage and polyadenylation, and the editing, localization, stability and translation of mRNAs. We describe the mapping and characterization of RNA elements recognized by a large collection of human RBPs in K562 and HepG2 cells. Integrative analyses using five assays identify RBP binding sites on RNA and chromatin in vivo, the in vitro binding preferences of RBPs, the function of RBP binding sites and the subcellular localization of RBPs, producing 1,223 replicated data sets for 356 RBPs. We describe the spectrum of RBP binding throughout the transcriptome and the connections between these interactions and various aspects of RNA biology, including RNA stability, splicing regulation and RNA localization. These data expand the catalogue of functional elements encoded in the human genome by the addition of a large set of elements that function at the RNA level by interacting with RBPs.

Integrated Genomic and Social Network Analyses of SARS-CoV-2 Transmission in the Healthcare Setting.

BACKGROUND: Infection prevention (IP) measures are designed to mitigate the transmission of pathogens in healthcare. Using large-scale viral genomic and social network analyses, we determined if IP measures used during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were adequate in protecting healthcare workers (HCWs) and patients from acquiring SARS-CoV-2. METHODS: We performed retrospective cross-sectional analyses of viral genomics from all available SARS-CoV-2 viral samples collected at UC San Diego Health and social network analysis using the electronic medical record to derive temporospatial overlap of infections among related viromes and supplemented with contact tracing data. The outcome measure was any instance of healthcare transmission, defined as cases with closely related viral genomes and epidemiological connection within the healthcare setting during the infection window. Between November 2020 through January 2022, 12 933 viral genomes were obtained from 35 666 patients and HCWs. RESULTS: Among 5112 SARS-CoV-2 viral samples sequenced from the second and third waves of SARS-CoV-2 (pre-Omicron), 291 pairs were derived from persons with a plausible healthcare overlap. Of these, 34 pairs (12%) were phylogenetically linked: 19 attributable to household and 14 to healthcare transmission. During the Omicron wave, 2106 contact pairs among 7821 sequences resulted in 120 (6%) related pairs among 32 clusters, of which 10 were consistent with healthcare transmission. Transmission was more likely to occur in shared spaces in the older hospital compared with the newer hospital (2.54 vs 0.63 transmission events per 1000 admissions, P < .001). CONCLUSIONS: IP strategies were effective at identifying and preventing healthcare SARS-CoV-2 transmission.

Transcriptome-wide analysis of PGC-1α-binding RNAs identifies genes linked to glucagon metabolic action.

The peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) is a transcriptional coactivator that controls expression of metabolic/energetic genes, programming cellular responses to nutrient and environmental adaptations such as fasting, cold, or exercise. Unlike other coactivators, PGC-1α contains protein domains involved in RNA regulation such as serine/arginine (SR) and RNA recognition motifs (RRMs). However, the RNA targets of PGC-1α and how they pertain to metabolism are unknown. To address this, we performed enhanced ultraviolet (UV) cross-linking and immunoprecipitation followed by sequencing (eCLIP-seq) in primary hepatocytes induced with glucagon. A large fraction of RNAs bound to PGC-1α were intronic sequences of genes involved in transcriptional, signaling, or metabolic function linked to glucagon and fasting responses, but were not the canonical direct transcriptional PGC-1α targets such as OXPHOS or gluconeogenic genes. Among the top-scoring RNA sequences bound to PGC-1α were Foxo1, Camk1δ, Per1, Klf15, Pln4, Cluh, Trpc5, Gfra1, and Slc25a25 PGC-1α depletion decreased a fraction of these glucagon-induced messenger RNA (mRNA) transcript levels. Importantly, knockdown of several of these genes affected glucagon-dependent glucose production, a PGC-1α-regulated metabolic pathway. These studies show that PGC-1α binds to intronic RNA sequences, some of them controlling transcript levels associated with glucagon action.

Direct RNA sequencing enables m6A detection in endogenous transcript isoforms at base-specific resolution.

Direct RNA sequencing holds great promise for the de novo identification of RNA modifications at single-coordinate resolution; however, interpretation of raw sequencing output to discover modified bases remains a challenge. Using Oxford Nanopore's direct RNA sequencing technology, we developed a random forest classifier trained using experimentally detected N6-methyladenosine (m6A) sites within DRACH motifs. Our software MINES (m6A Identification using Nanopore Sequencing) assigned m6A methylation status to more than 13,000 previously unannotated DRACH sites in endogenous HEK293T transcripts and identified more than 40,000 sites with isoform-level resolution in a human mammary epithelial cell line. These sites displayed sensitivity to the m6A writer, METTL3, and eraser, ALKBH5, respectively. MINES (https://github.com/YeoLab/MINES.git) enables m6A annotation at single coordinate-level resolution from direct RNA nanopore sequencing.

The splicing factor RBM17 drives leukemic stem cell maintenance by evading nonsense-mediated decay of pro-leukemic factors.

Chemo-resistance in acute myeloid leukemia (AML) patients is driven by leukemic stem cells (LSCs) resulting in high rates of relapse and low overall survival. Here, we demonstrate that upregulation of the splicing factor, RBM17 preferentially marks and sustains LSCs and directly correlates with shorten patient survival. RBM17 knockdown in primary AML cells leads to myeloid differentiation and impaired colony formation and in vivo engraftment. Integrative multi-omics analyses show that RBM17 repression leads to inclusion of poison exons and production of nonsense-mediated decay (NMD)-sensitive transcripts for pro-leukemic factors and the translation initiation factor, EIF4A2. We show that EIF4A2 is enriched in LSCs and its inhibition impairs primary AML progenitor activity. Proteomic analysis of EIF4A2-depleted AML cells shows recapitulation of the RBM17 knockdown biological effects, including pronounced suppression of proteins involved in ribosome biogenesis. Overall, these results provide a rationale to target RBM17 and/or its downstream NMD-sensitive splicing substrates for AML treatment.

Sentinel Cards Provide Practical SARS-CoV-2 Monitoring in School Settings.

A promising approach to help students safely return to in person learning is through the application of sentinel cards for accurate high resolution environmental monitoring of SARS-CoV-2 traces indoors. Because SARS-CoV-2 RNA can persist for up to a week on several indoor surface materials, there is a need for increased temporal resolution to determine whether consecutive surface positives arise from new infection events or continue to report past events. Cleaning sentinel cards after sampling would provide the needed resolution but might interfere with assay performance. We tested the effect of three cleaning solutions (BZK wipes, Wet Wipes, RNase Away) at three different viral loads: "high" (4 × 104 GE/mL), "medium" (1 × 104 GE/mL), and "low" (2.5 × 103 GE/mL). RNase Away, chosen as a positive control, was the most effective cleaning solution on all three viral loads. Wet Wipes were found to be more effective than BZK wipes in the medium viral load condition. The low viral load condition was easily reset with all three cleaning solutions. These findings will enable temporal SARS-CoV-2 monitoring in indoor environments where transmission risk of the virus is high and the need to avoid individual-level sampling for privacy or compliance reasons exists. IMPORTANCE Because SARS-CoV-2, the virus that causes COVID-19, persists on surfaces, testing swabs taken from surfaces is useful as a monitoring tool. This approach is especially valuable in school settings, where there are cost and privacy concerns that are eliminated by taking a single sample from a classroom. However, the virus persists for days to weeks on surface samples, so it is impossible to tell whether positive detection events on consecutive days are a persistent signal or new infectious cases and therefore whether the positive individuals have been successfully removed from the classroom. We compare several methods for cleaning "sentinel cards" to show that this approach can be used to identify new SARS-CoV-2 signals day to day. The results are important for determining how to monitor classrooms and other indoor environments for SARS-CoV-2 virus.

Implementation of Practical Surface SARS-CoV-2 Surveillance in School Settings.

Surface sampling for SARS-CoV-2 RNA detection has shown considerable promise to detect exposure of built environments to infected individuals shedding virus who would not otherwise be detected. Here, we compare two popular sampling media (VTM and SDS) and two popular workflows (Thermo and PerkinElmer) for implementation of a surface sampling program suitable for environmental monitoring in public schools. We find that the SDS/Thermo pipeline shows superior sensitivity and specificity, but that the VTM/PerkinElmer pipeline is still sufficient to support surface surveillance in any indoor setting with stable cohorts of occupants (e.g., schools, prisons, group homes, etc.) and may be used to leverage existing investments in infrastructure. IMPORTANCE The ongoing COVID-19 pandemic has claimed the lives of over 5 million people worldwide. Due to high density occupancy of indoor spaces for prolonged periods of time, schools are often of concern for transmission, leading to widespread school closings to combat pandemic spread when cases rise. Since pediatric clinical testing is expensive and difficult from a consent perspective, we have deployed surface sampling in SASEA (Safer at School Early Alert), which allows for detection of SARS-CoV-2 from surfaces within a classroom. In this previous work, we developed a high-throughput method which requires robotic automation and specific reagents that are often not available for public health laboratories such as the San Diego County Public Health Laboratory (SDPHL). Therefore, we benchmarked our method (Thermo pipeline) against SDPHL's (PerkinElmer) more widely used method for the detection and prediction of SARS-CoV-2 exposure. While our method shows superior sensitivity (false-negative rate of 9% versus 27% for SDPHL), the SDPHL pipeline is sufficient to support surface surveillance in indoor settings. These findings are important since they show that existing investments in infrastructure can be leveraged to slow the spread of SARS-CoV-2 not in just the classroom but also in prisons, nursing homes, and other high-risk, indoor settings.

SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia sp.

Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions and to test whether our past observations linking SARS-CoV-2 abundance to Rothia sp. in hospitals also hold in a residential setting, we performed a detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences (to assess the bacterial community at each location), and to the Cq value of the contemporaneous clinical test. Our results showed that the highest SARS-CoV-2 load in this setting is on touched surfaces, such as light switches and faucets, but a detectable signal was present in many untouched surfaces (e.g., floors) that may be more relevant in settings, such as schools where mask-wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association. IMPORTANCE Surface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g., touching a light switch) or indirectly (e.g., by droplets or aerosols settling). We found the highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g., in schools, where students did not touch the light switches and also wore masks such that they had no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.

Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission.

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Non-microRNA binding competitively inhibits LIN28 regulation.

RNA binding protein (RBP) expression is finite. For RBPs that are vastly outnumbered by their potential target sites, a simple competition for binding can set the magnitude of post-transcriptional control. Here, we show that LIN28, best known for its direct regulation of let-7 miRNA biogenesis, is also indirectly regulated by its widespread binding of non-miRNA transcripts. Approximately 99% of LIN28 binding sites are found on non-miRNA transcripts, like protein coding and ribosomal RNAs. These sites are bound specifically and strongly, but they do not appear to mediate direct post-transcriptional regulation. Instead, non-miRNA sites act to sequester LIN28 protein and effectively change its functional availability, thus impeding the regulation of let-7 in cells. Together, these data show that the binding properties of the transcriptome broadly influence the ability of an RBP to mediate changes in RNA metabolism and gene expression.

Persistent mRNA localization defects and cell death in ALS neurons caused by transient cellular stress.

Persistent cytoplasmic aggregates containing RNA binding proteins (RBPs) are central to the pathogenesis of late-onset neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS). These aggregates share components, molecular mechanisms, and cellular protein quality control pathways with stress-induced RNA granules (SGs). Here, we assess the impact of stress on the global mRNA localization landscape of human pluripotent stem cell-derived motor neurons (PSC-MNs) using subcellular fractionation with RNA sequencing and proteomics. Transient stress disrupts subcellular RNA and protein distributions, alters the RNA binding profile of SG- and ALS-relevant RBPs and recapitulates disease-associated molecular changes such as aberrant splicing of STMN2. Although neurotypical PSC-MNs re-establish a normal subcellular localization landscape upon recovery from stress, cells harboring ALS-linked mutations are intransigent and display a delayed-onset increase in neuronal cell death. Our results highlight subcellular molecular distributions as predictive features and underscore the utility of cellular stress as a paradigm to study ALS-relevant mechanisms.

Gain-of-function cardiomyopathic mutations in RBM20 rewire splicing regulation and re-distribute ribonucleoprotein granules within processing bodies.

Mutations in the cardiac splicing factor RBM20 lead to malignant dilated cardiomyopathy (DCM). To understand the mechanism of RBM20-associated DCM, we engineered isogenic iPSCs with DCM-associated missense mutations in RBM20 as well as RBM20 knockout (KO) iPSCs. iPSC-derived engineered heart tissues made from these cell lines recapitulate contractile dysfunction of RBM20-associated DCM and reveal greater dysfunction with missense mutations than KO. Analysis of RBM20 RNA binding by eCLIP reveals a gain-of-function preference of mutant RBM20 for 3' UTR sequences that are shared with amyotrophic lateral sclerosis (ALS) and processing-body associated RNA binding proteins (FUS, DDX6). Deep RNA sequencing reveals that the RBM20 R636S mutant has unique gene, splicing, polyadenylation and circular RNA defects that differ from RBM20 KO. Super-resolution microscopy verifies that mutant RBM20 maintains very limited nuclear localization potential; rather, the mutant protein associates with cytoplasmic processing bodies (DDX6) under basal conditions, and with stress granules (G3BP1) following acute stress. Taken together, our results highlight a pathogenic mechanism in cardiac disease through splicing-dependent and -independent pathways.