Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics.

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

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.

Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation.

Poor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of 10 exRNA isolation methods across 5 biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNA-seq profiles. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle (EV)-, ribonucleoprotein (RNP)-, and high-density lipoprotein (HDL)-specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and reproducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

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.

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.

Extracellular Vesicle-Encapsulated microRNAs as Novel Biomarkers of Lung Health.

Rationale: Early detection of respiratory diseases is critical to facilitate delivery of disease-modifying interventions. Extracellular vesicle-enriched microRNAs (EV-miRNAs) may represent reliable markers of early lung injury. Objectives: Evaluate associations of plasma EV-miRNAs with lung function. Methods: The prospective NAS (Normative Aging Study) collected plasma EV-miRNA measurements from 1996-2015 and spirometry every 3-5 years through 2019. Associations of EV-miRNAs with baseline lung function were modeled using linear regression. To complement the individual miRNA approach, unsupervised machine learning was used to identify clusters of participants with distinct EV-miRNA profiles. Associations of EV-miRNA profiles with multivariate latent longitudinal lung function trajectories were modeled using log binomial regression. Biological functions of significant EV-miRNAs were explored using pathway analyses. Results were replicated in an independent sample of NAS participants and in the HEALS (Health Effects of Arsenic Longitudinal Study). Measurements and Main Results: In the main cohort of 656 participants, 51 plasma EV-miRNAs were associated with baseline lung function (false discovery rate-adjusted P value < 0.05), 28 of which were replicated in the independent NAS sample and/or in the HEALS cohort. A subset of participants with distinct EV-miRNA expression patterns had increased risk of declining lung function over time, which was replicated in the independent NAS sample. Significant EV-miRNAs were shown in pathway analyses to target biological pathways that regulate respiratory cellular immunity, the lung inflammatory response, and airway structural integrity. Conclusions: Plasma EV-miRNAs may represent a robust biomarker of subclinical lung injury and may facilitate early identification and treatment of patients at risk of developing overt lung disease.

Evolution of sexes from an ancestral mating-type specification pathway.

Male and female sexes have evolved repeatedly in eukaryotes but the origins of dimorphic sexes and their relationship to mating types in unicellular species are not understood. Volvocine algae include isogamous species such as Chlamydomonas reinhardtii, with two equal-sized mating types, and oogamous multicellular species such as Volvox carteri with sperm-producing males and egg-producing females. Theoretical work predicts genetic linkage of a gamete cell-size regulatory gene(s) to an ancestral mating-type locus as a possible step in the evolution of dimorphic gametes, but this idea has not been tested. Here we show that, contrary to predictions, a single conserved mating locus (MT) gene in volvocine algae-MID, which encodes a RWP-RK domain transcription factor-evolved from its ancestral role in C. reinhardtii as a mating-type specifier, to become a determinant of sperm and egg development in V. carteri. Transgenic female V. carteri expressing male MID produced functional sperm packets during sexual development. Transgenic male V. carteri with RNA interference (RNAi)-mediated knockdowns of VcMID produced functional eggs, or self-fertile hermaphrodites. Post-transcriptional controls were found to regulate cell-type-limited expression and nuclear localization of VcMid protein that restricted its activity to nuclei of developing male germ cells and sperm. Crosses with sex-reversed strains uncoupled sex determination from sex chromosome identity and revealed gender-specific roles for male and female mating locus genes in sexual development, gamete fitness and reproductive success. Our data show genetic continuity between the mating-type specification and sex determination pathways of volvocine algae, and reveal evidence for gender-specific adaptations in the male and female mating locus haplotypes of Volvox. These findings will enable a deeper understanding of how a master regulator of mating-type determination in an ancestral unicellular species was reprogrammed to control sexually dimorphic gamete development in a multicellular descendant.

Dynamic Changes in the Transcriptome and Methylome of Chlamydomonas reinhardtii throughout Its Life Cycle.

The green alga Chlamydomonas reinhardtii undergoes gametogenesis and mating upon nitrogen starvation. While the steps involved in its sexual reproductive cycle have been extensively characterized, the genome-wide transcriptional and epigenetic changes underlying different life cycle stages have yet to be fully described. Here, we performed transcriptome and methylome sequencing to quantify expression and DNA methylation from vegetative and gametic cells of each mating type and from zygotes. We identified 361 gametic genes with mating type-specific expression patterns and 627 genes that are specifically induced in zygotes; furthermore, these sex-related gene sets were enriched for secretory pathway and alga-specific genes. We also examined the C. reinhardtii nuclear methylation map with base-level resolution at different life cycle stages. Despite having low global levels of nuclear methylation, we detected 23 hypermethylated loci in gene-poor, repeat-rich regions. We observed mating type-specific differences in chloroplast DNA methylation levels in plus versus minus mating type gametes followed by chloroplast DNA hypermethylation in zygotes. Lastly, we examined the expression of candidate DNA methyltransferases and found three, DMT1a, DMT1b, and DMT4, that are differentially expressed during the life cycle and are candidate DNA methylases. The expression and methylation data we present provide insight into cell type-specific transcriptional and epigenetic programs during key stages of the C. reinhardtii life cycle.

Species and population level molecular profiling reveals cryptic recombination and emergent asymmetry in the dimorphic mating locus of C. reinhardtii.

Heteromorphic sex-determining regions or mating-type loci can contain large regions of non-recombining sequence where selection operates under different constraints than in freely recombining autosomal regions. Detailed studies of these non-recombining regions can provide insights into how genes are gained and lost, and how genetic isolation is maintained between mating haplotypes or sex chromosomes. The Chlamydomonas reinhardtii mating-type locus (MT) is a complex polygenic region characterized by sequence rearrangements and suppressed recombination between its two haplotypes, MT+ and MT-. We used new sequence information to redefine the genetic contents of MT and found repeated translocations from autosomes as well as sexually controlled expression patterns for several newly identified genes. We examined sequence diversity of MT genes from wild isolates of C. reinhardtii to investigate the impacts of recombination suppression. Our population data revealed two previously unreported types of genetic exchange in Chlamydomonas MT--gene conversion in the rearranged domains, and crossover exchanges in flanking domains--both of which contribute to maintenance of genetic homogeneity between haplotypes. To investigate the cause of blocked recombination in MT we assessed recombination rates in crosses where the parents were homozygous at MT. While normal recombination was restored in MT+ ×MT+ crosses, it was still suppressed in MT- ×MT- crosses. These data revealed an underlying asymmetry in the two MT haplotypes and suggest that sequence rearrangements are insufficient to fully account for recombination suppression. Together our findings reveal new evolutionary dynamics for mating loci and have implications for the evolution of heteromorphic sex chromosomes and other non-recombining genomic regions.

Extracellular Vesicle-Encapsulated microRNAs and Respiratory Health Among American Indian Participants in the Strong Heart Study.

BACKGROUND: American Indian populations have experienced marked disparities in respiratory disease burden. Extracellular vesicle-encapsulated microRNAs (EV-miRNAs) are a novel class of biomarkers that may improve recognition of lung damage in indigenous populations in the United States. RESEARCH QUESTION: Are plasma EV-miRNAs viable biomarkers of respiratory health in American Indian populations? STUDY DESIGN AND METHODS: The Strong Heart Study is a prospective cohort study that enrolled American Indian patients aged 45 to 74 years. EV-miRNA expression was measured in plasma (1993-1995). Respiratory health outcomes, including prebronchodilator FEV1, FVC, and respiratory symptom burden, were ascertained in the same study visit. Club cell secretory protein (CC-16), an antiinflammatory pneumoprotein implicated in COPD pathogenesis, was measured in serum. Linear and logistic regression were used for statistical analyses. Biological pathway analyses were used to elucidate gene targets of significant EV-miRNAs. RESULTS: Among 853 American Indian adults, three EV-miRNAs were associated with FEV1, four EV-miRNAs were associated with FVC, and one EV-miRNA was associated with FEV1/FVC (P < .05). Increased miR-1294 expression was associated with higher odds of airflow limitation (OR, 1.29; 95% CI, 1.07-1.55), whereas increased expression of miR-1294 (OR, 1.32; 95% CI, 1.07-1.63) and miR-532-5p (OR, 1.57; 95% CI, 1.02-2.40) was associated with higher odds of restriction. Increased miR-451a expression was associated with lower odds of exertional dyspnea (OR, 0.71; 95% CI, 0.59-0.85). Twenty-two EV-miRNAs were associated with serum CC-16 levels (q < 0.05), suggesting that EV-miRNAs may play a role in the pathway linking CC-16 to COPD pathogenesis. A pathway analysis showed key EV-miRNAs targeted biological pathways that modulate inflammation, immunity, and structural integrity in the lungs. INTERPRETATION: Circulating EV-miRNAs are novel mechanistic biomarkers of respiratory health and may facilitate the early detection and treatment of lung damage in American Indian populations that have been disproportionately affected by chronic lung diseases.

Humoral immune response to SARS-CoV-2 in pregnant and nonpregnant women following infection.

BACKGROUND: Immune changes that occur during pregnancy may place pregnant women at an increased risk for severe disease following viral infections like SARS-CoV-2. Whether these immunologic changes modify the immune response to SARS-CoV-2 infection during pregnancy is not well understood. OBJECTIVE: This study aimed to compare the humoral immune response to SARS-CoV-2 infection in pregnant and nonpregnant women. The immune response following vaccination for SARS-CoV-2 was also explored. STUDY DESIGN: In this cohort study, 24 serum samples from 20 patients infected with SARS-CoV-2 during pregnancy were matched by number of days after a positive test with 46 samples from 40 nonpregnant women of reproductive age. Samples from 9 patients who were vaccinated during pregnancy were also examined. Immunoglobulin G and immunoglobulin M levels were measured. Trends in the log antibody levels over time and mean antibody levels were assessed using generalized estimating equations. RESULTS: The median number of days from first positive test to sampling was 6.5 in the pregnant group (range, 3-97) and 6.0 among nonpregnant participants (range, 2-97). No significant differences in demographic or sampling characteristics were noted between the groups. No differences in immunoglobulin G or immunoglobulin M levels over time or mean antibody levels were noted among pregnant and nonpregnant participants following SARS-CoV-2 infection for any of the SARS-CoV-2 antigen targets examined (spike, spike receptor-binding domain, spike N-terminal domain, and nucleocapsid). Participants who were vaccinated during pregnancy had higher immunoglobulin G levels than pregnant patients who tested positive for all SARS-CoV-2 targets except nucleocapsid antibodies (all P<.001) and had lower immunoglobulin M spike (P<.05) and receptor-binding domain (P<.01) antibody levels. CONCLUSION: This study suggests that the humoral response following SARS-CoV-2 infection does not seem to differ between pregnant women and their nonpregnant counterparts. These findings should reassure patients and healthcare providers that pregnant patients seem to mount a nondifferential immune response to SARS-CoV-2.

Safer at school early alert: an observational study of wastewater and surface monitoring to detect COVID-19 in elementary schools.

Background: Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown. Methods: The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 to March 2021. Findings: In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88%-98%); 67% were associated with a positive wastewater sample (95% CI: 57%-77%), and 40% were associated with a positive surface sample (95% CI: 29%-52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples. Interpretation: Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy. Funding: County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

Wastewater and surface monitoring to detect COVID-19 in elementary school settings: The Safer at School Early Alert project.

Background: Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown. Methods: The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 - March 2021. Findings: In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88% - 98%); 67% were associated with a positive wastewater sample (95% CI: 57% - 77%), and 40% were associated with a positive surface sample (95% CI: 29% - 52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples. Interpretation: Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy. Funding: County of San Diego, Health and Human Services Agency, National Institutes of Health, National Science Foundation, Centers for Disease Control.

Extracellular microRNA and cognitive function in a prospective cohort of older men: The Veterans Affairs Normative Aging Study.

BACKGROUND: Aging-related cognitive decline is an early symptom of Alzheimer's disease and other dementias, and on its own can have substantial consequences on an individual's ability to perform important everyday functions. Despite increasing interest in the potential roles of extracellular microRNAs (miRNAs) in central nervous system (CNS) pathologies, there has been little research on extracellular miRNAs in early stages of cognitive decline. We leverage the longitudinal Normative Aging Study (NAS) cohort to investigate associations between plasma miRNAs and cognitive function among cognitively normal men. METHODS: This study includes data from up to 530 NAS participants (median age: 71.0 years) collected from 1996 to 2013, with a total of 1,331 person-visits (equal to 2,471 years of follow up). Global cognitive function was assessed using the Mini-Mental State Examination (MMSE). Plasma miRNAs were profiled using small RNA sequencing. Associations of expression of 381 miRNAs with current cognitive function and rate of change in cognitive function were assessed using linear regression (N = 457) and linear mixed models (N = 530), respectively. RESULTS: In adjusted models, levels of 2 plasma miRNAs were associated with higher MMSE scores (p < 0.05). Expression of 33 plasma miRNAs was associated with rate of change in MMSE scores over time (p < 0.05). Enriched KEGG pathways for miRNAs associated with concurrent MMSE and MMSE trajectory included Hippo signaling and extracellular matrix-receptor interactions. Gene targets of miRNAs associated with MMSE trajectory were additionally associated with prion diseases and fatty acid biosynthesis. CONCLUSIONS: Circulating miRNAs were associated with both cross-sectional cognitive function and rate of change in cognitive function among cognitively normal men. Further research is needed to elucidate the potential functions of these miRNAs in the CNS and investigate relationships with other neurological outcomes.

Severe acute respiratory coronavirus virus 2 (SARS-CoV-2) screening among symptom-free healthcare workers.

Transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is possible among symptom-free individuals. Patients are avoiding medically necessary healthcare visits for fear of becoming infected in the healthcare setting. We screened 489 symptom-free healthcare workers for SARS-CoV-2 and found no positive results, strongly suggesting that the prevalence of SARS-CoV-2 was <1%.

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.

Phase 2 of extracellular RNA communication consortium charts next-generation approaches for extracellular RNA research.

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

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.