A Bayesian framework for modeling COVID-19 case numbers through longitudinal monitoring of SARS-CoV-2 RNA in wastewater.

Wastewater-based surveillance has become an important tool for research groups and public health agencies investigating and monitoring the COVID-19 pandemic and other public health emergencies including other pathogens and drug abuse. While there is an emerging body of evidence exploring the possibility of predicting COVID-19 infections from wastewater signals, there remain significant challenges for statistical modeling. Longitudinal observations of viral copies in municipal wastewater can be influenced by noisy datasets and missing values with irregular and sparse samplings. We propose an integrative Bayesian framework to predict daily positive cases from weekly wastewater observations with missing values via functional data analysis techniques. In a unified procedure, the proposed analysis models severe acute respiratory syndrome coronavirus-2 RNA wastewater signals as a realization of a smooth process with error and combines the smooth process with COVID-19 cases to evaluate the prediction of positive cases. We demonstrate that the proposed framework can achieve these objectives with high predictive accuracies through simulated and observed real data.

Surveillance for SARS-CoV-2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks.

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with >2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to nonoutbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals.

Tracking Emergence and Spread of SARS-CoV-2 Omicron Variant in Large and Small Communities by Wastewater Monitoring in Alberta, Canada.

Wastewater monitoring of SARS-CoV-2 enables early detection and monitoring of the COVID-19 disease burden in communities and can track specific variants of concern. We determined proportions of the Omicron and Delta variants across 30 municipalities covering >75% of the province of Alberta (population 4.5 million), Canada, during November 2021-January 2022. Larger cities Calgary and Edmonton exhibited more rapid emergence of Omicron than did smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a medium-sized northern community that has many workers who fly in and out regularly. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden by late December, before the peak in newly diagnosed clinical cases throughout Alberta in mid-January. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of SARS-CoV-2 variants.

Surface resistance to SSVs and SIRVs in pilin deletions of Sulfolobus islandicus.

Characterizing the molecular interactions of viruses in natural microbial populations offers insights into virus-host dynamics in complex ecosystems. We identify the resistance of Sulfolobus islandicus to Sulfolobus spindle-shaped virus (SSV9) conferred by chromosomal deletions of pilin genes, pilA1 and pilA2 that are individually able to complement resistance. Mutants with deletions of both pilA1 and pilA2 or the prepilin peptidase, PibD, show the reduction in the number of pilins observed in TEM and reduced surface adherence but still adsorb SSV9. The proteinaceous outer S-layer proteins, SlaA and SlaB, are not required for adsorption nor infection demonstrating that the S-layer is not the primary receptor for SSV9 surface binding. Strains lacking both pilins are resistant to a broad panel of SSVs as well as a panel of unrelated S. islandicus rod-shaped viruses (SIRVs). Unlike SSV9, we show that pilA1 or pilA2 is required for SIRV8 adsorption. In sequenced Sulfolobus strains from around the globe, one copy of each pilA1 and pilA2 is maintained and show codon-level diversification, demonstrating their importance in nature. By characterizing the molecular interactions at the initiation of infection between S. islandicus and two different types of viruses we hope to increase the understanding of virus-host interactions in the archaeal domain.

Diesel and Crude Oil Biodegradation by Cold-Adapted Microbial Communities in the Labrador Sea.

Oil spills in the subarctic marine environment off the coast of Labrador, Canada, are increasingly likely due to potential oil production and increases in ship traffic in the region. To understand the microbiome response and how nutrient biostimulation promotes biodegradation of oil spills in this cold marine setting, marine sediment microcosms amended with diesel or crude oil were incubated at in situ temperature (4°C) for several weeks. Sequencing of 16S rRNA genes following these spill simulations revealed decreased microbial diversity and enrichment of putative hydrocarbonoclastic bacteria that differed depending on the petroleum product. Metagenomic sequencing revealed that the genus Paraperlucidibaca harbors previously unrecognized capabilities for alkane biodegradation, which were also observed in Cycloclasticus. Genomic and amplicon sequencing together suggest that Oleispira and Thalassolituus degraded alkanes from diesel, while Zhongshania and the novel PGZG01 lineage contributed to crude oil alkane biodegradation. Greater losses in PAHs from crude oil than from diesel were consistent with Marinobacter, Pseudomonas_D, and Amphritea genomes exhibiting aromatic hydrocarbon biodegradation potential. Biostimulation with nitrogen and phosphorus (4.67 mM NH4Cl and 1.47 mM KH2PO4) was effective at enhancing n-alkane and PAH degradation following low-concentration (0.1% [vol/vol]) diesel and crude oil amendments, while at higher concentrations (1% [vol/vol]) only n-alkanes in diesel were consumed, suggesting toxicity induced by compounds in unrefined crude oil. Biostimulation allowed for a more rapid shift in the microbial community in response to petroleum amendments, more than doubling the rates of CO2 increase during the first few weeks of incubation. IMPORTANCE Increases in transportation of diesel and crude oil in the Labrador Sea will pose a significant threat to remote benthic and shoreline environments, where coastal communities and wildlife are particularly vulnerable to oil spill contaminants. Whereas marine microbiology has not been incorporated into environmental assessments in the Labrador Sea, there is a growing demand for microbial biodiversity evaluations given the pronounced impact of climate change in this region. Benthic microbial communities are important to consider given that a fraction of spilled oil typically sinks such that its biodegradation occurs at the seafloor, where novel taxa with previously unrecognized potential to degrade hydrocarbons were discovered in this work. Understanding how cold-adapted microbiomes catalyze hydrocarbon degradation at low in situ temperature is crucial in the Labrador Sea, which remains relatively cold throughout the year.

A novel synthesis method of magnetic Janus particles for wastewater applications.

HYPOTHESIS: Magnetic particles are widely used in many adsorption and removal processes. Among the many types of magnetic colloids, magnetic Janus particles offer significant possibilities for the effective removal of several components from aqueous solutions. Nevertheless, the synthesis of structures integrating different types of materials requires scalable fabrication processes to overcome the limitations of the available methodologies. Herein, we hypothesized a fabrication process for dual-surface functionalized magnetic Janus particles. EXPERIMENTS: The primary silica particles with surface-attached amine groups are further asymmetrically modified by iron oxide nanoparticles, exploiting Pickering emulsion and electroless deposition techniques. The dual surface functionality of the particles is designed for its versatility and demonstrated in two wastewater-related applications. FINDINGS: We show that our design can simultaneously remove chromium (VI) and phenol from aqueous solution. The fabricated magnetic-responsive Janus particles are also an effective adsorbent for genomic Deoxyribonucleic acid (DNA) and show superior performance to commercial magnetic beads. Thus, this study provides a novel platform for designing magnetic Janus particles with multifunctional surfaces for wastewater treatment applications.

Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism.

Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community.

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites - regardless of several normalization strategies - with certain catchments consistently demonstrating values 1-2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.

The Frequency of V122I Transthyretin Mutation in a Cohort of African American Individuals With Bilateral Carpal Tunnel Syndrome.

Introduction: Hereditary transthyretin amyloidosis (hATTR) can cause multisystem organ disorders including polyneuropathy and cardiomyopathy. Amongst the many known pathologic mutations of the transthyretin (TTR) gene, the Val122Ile (V122I) mutation can be found in 3-4% of African Americans. Up to 47% of patients with the V122I hATTR cardiomyopathy had a history of carpal tunnel syndrome (CTS). This raises the question should we screen for this mutation in African Americans with bilateral CTS for the purpose of preventing advanced disease associated with hATTR. This is a prospective pilot study to determine the likelihood of African Americans with bilateral CTS having the V122I mutation and whether various clinical factors contribute to that probability. Methodology: Adult African American patients without prior history of amyloidosis diagnosed with bilateral CTS were recruited for the study. They received genetic testing to screen for a TTR mutation. They also completed questionnaires to screen for symptoms of cardiomyopathy and neuropathy, other risk factors for CTS, and family history of CTS and cardiomyopathy. Result: Two of the sixteen patients (12.5%) in this cohort were found to have the V122I mutation. The absence of polyneuropathy and cardiomyopathy symptoms, presence of other CTS risk factors, and absence of family history of CTS and cardiomyopathy did not decrease the likelihood of V122I mutation in this cohort. Conclusion: The frequency of V122I transthyretin mutation in African Americans with bilateral CTS may be higher than 3-4%. The presence of bilateral CTS alone may be a justification to screen for TTR mutation in this population.

Comparative study of different SES neighborhood clinics for health literacy and internet access.

Background: As healthcare services are increasingly dependent on patient utilization of technology to effectively deliver services, the digital divide has the potential to exacerbate health disparities if health literacy and internet access present formidable barriers to patient use of technology. Methods: We examined the differences in health literacy and internet access between lower and upper SES neighborhood primary-care clinics in Northeast Florida. The REALM-SF for health literacy was used to assess health literacy and census survey questions were used to assess internet and technology access, during the Fall, 2020. The clinics were affiliated with a safety-net hospital in a major city in Southeastern U.S. Results: Analysis of key demographic data confirmed that the responding patients from economically disadvantaged neighborhood clinics resided in economically disadvantaged zip codes (307 responding patients lived in lower SES neighborhoods) and did have lower education levels (3% of the patients from Upper SES clinics had 11 grade or lower education, compared to 21%-29% of patients from Lower SES clinics). Patient health literacy significantly differed between clinics located in economically disadvantaged neighborhoods and clinics located in more affluent neighborhoods, with Upper SES clinics being 2.4 times more likely to have 9th grade or higher reading level. Access to internet technology was also higher in the Upper SES clinics, with 59% of respondents from Upper SES clinics versus 32%-40% from Lower SES clinics owning a computer or an IPAD. Conclusion: Results of this study have important implications for patient-engaged use of digital technology for health. Healthcare and public health clinics should be aware of the difference in health literacy and internet access when implementing technology-based services, so that advances in medicine, including precision medicine and telehealth, can be disseminated and implemented with broad populations, including disadvantaged groups.

Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population.

Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.44 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December 2020) and the third-wave of the COVID-19 pandemic (mid-April to May 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06% (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals' primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1 & N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgary's three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.

CANT-HYD: A Curated Database of Phylogeny-Derived Hidden Markov Models for Annotation of Marker Genes Involved in Hydrocarbon Degradation.

Many pathways for hydrocarbon degradation have been discovered, yet there are no dedicated tools to identify and predict the hydrocarbon degradation potential of microbial genomes and metagenomes. Here we present the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), a database of 37 HMMs of marker genes involved in anaerobic and aerobic degradation pathways of aliphatic and aromatic hydrocarbons. Using this database, we identify understudied or overlooked hydrocarbon degradation potential in many phyla. We also demonstrate its application in analyzing high-throughput sequence data by predicting hydrocarbon utilization in large metagenomic datasets from diverse environments. CANT-HYD is available at https://github.com/dgittins/CANT-HYD-HydrocarbonBiodegradation.

A multicenter study investigating SARS-CoV-2 in tertiary-care hospital wastewater. viral burden correlates with increasing hospitalized cases as well as hospital-associated transmissions and outbreaks.

SARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals. Between August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling > 2100 dedicated inpatient beds) were collected. Hospital-1 and Hospital-2 could be captured with a single sampling point whereas Hospital-3 required three separate monitoring sites. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks. Of 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of the amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations at those sites with single monitoring points (Pearson's r = 0.679, P < 0.0001, Pearson's r = 0.799, P < 0.0001, respectively). Despite increasing hospitalizations through the study period, nosocomial-acquired cases of COVID-19 (Pearson's r = 0.389, P < 0.001) and unit-specific outbreaks were discernable with significant increases in detectable SARS-CoV-2 N1-RNA (median 112 copies/ml) versus outbreak-free periods (0 copies/ml; P < 0.0001). Wastewater-based monitoring of SARS-CoV-2 represents a promising tool for SARS-CoV-2 passive surveillance and case identification, containment, and mitigation in acute- care medical facilities.

Killer Archaea: Virus-Mediated Antagonism to CRISPR-Immune Populations Results in Emergent Virus-Host Mutualism.

Theory, simulation, and experimental evolution demonstrate that diversified CRISPR-Cas immunity to lytic viruses can lead to stochastic virus extinction due to a limited number of susceptible hosts available to each potential new protospacer escape mutation. Under such conditions, theory predicts that to evade extinction, viruses evolve toward decreased virulence and promote vertical transmission and persistence in infected hosts. To better understand the evolution of host-virus interactions in microbial populations with active CRISPR-Cas immunity, we studied the interaction between CRISPR-immune Sulfolobus islandicus cells and immune-deficient strains that are infected by the chronic virus SSV9. We demonstrate that Sulfolobus islandicus cells infected with SSV9, and with other related SSVs, kill uninfected, immune strains through an antagonistic mechanism that is a protein and is independent of infectious virus. Cells that are infected with SSV9 are protected from killing and persist in the population. We hypothesize that this infection acts as a form of mutualism between the host and the virus by removing competitors in the population and ensuring continued vertical transmission of the virus within populations with diversified CRISPR-Cas immunity.IMPORTANCE Multiple studies, especially those focusing on the role of lytic viruses in key model systems, have shown the importance of viruses in shaping microbial populations. However, it has become increasingly clear that viruses with a long host-virus interaction, such as those with a chronic lifestyle, can be important drivers of evolution and have large impacts on host ecology. In this work, we describe one such interaction with the acidic crenarchaeon Sulfolobus islandicus and its chronic virus Sulfolobus spindle-shaped virus 9. Our work expands the view in which this symbiosis between host and virus evolved, describing a killing phenotype which we hypothesize has evolved in part due to the high prevalence and diversity of CRISPR-Cas immunity seen in natural populations. We explore the implications of this phenotype in population dynamics and host ecology, as well as the implications of mutualism between this virus-host pair.

Diversified local CRISPR-Cas immunity to viruses of Sulfolobus islandicus.

The population diversity and structure of CRISPR-Cas immunity provides key insights into virus-host interactions. Here, we examined two geographically and genetically distinct natural populations of the thermophilic crenarchaeon Sulfolobus islandicus and their interactions with Sulfolobus spindle-shaped viruses (SSVs) and S. islandicus rod-shaped viruses (SIRVs). We found that both virus families can be targeted with high population distributed immunity, whereby most immune strains target a virus using unique unshared CRISPR spacers. In Kamchatka, Russia, we observed high immunity to chronic SSVs that increases over time. In this context, we found that some SSVs had shortened genomes lacking genes that are highly targeted by the S. islandicus population, indicating a potential mechanism of immune evasion. By contrast, in Yellowstone National Park, we found high inter- and intra-strain immune diversity targeting lytic SIRVs and low immunity to chronic SSVs. In this population, we observed evidence of SIRVs evolving immunity through mutations concentrated in the first five bases of protospacers. These results indicate that diversity and structure of antiviral CRISPR-Cas immunity for a single microbial species can differ by both the population and virus type, and suggest that different virus families use different mechanisms to evade CRISPR-Cas immunity. This article is part of a discussion meeting issue 'The ecology and evolution of prokaryotic CRISPR-Cas adaptive immune systems'.

Differentiation and Structure in Sulfolobus islandicus Rod-Shaped Virus Populations.

In the past decade, molecular surveys of viral diversity have revealed that viruses are the most diverse and abundant biological entities on Earth. In culture, however, most viral isolates that infect microbes are represented by a few variants isolated on type strains, limiting our ability to study how natural variation affects virus-host interactions in the laboratory. We screened a set of 137 hot spring samples for viruses that infect a geographically diverse panel of the hyperthemophilic crenarchaeon Sulfolobus islandicus. We isolated and characterized eight SIRVs (Sulfolobus islandicus rod-shaped viruses) from two different regions within Yellowstone National Park (USA). Comparative genomics revealed that all SIRV sequenced isolates share 30 core genes that represent 50-60% of the genome. The core genome phylogeny, as well as the distribution of variable genes (shared by some but not all SIRVs) and the signatures of host-virus interactions recorded on the CRISPR (clustered regularly interspaced short palindromic repeats) repeat-spacer arrays of S. islandicus hosts, identify different SIRV lineages, each associated with a different geographic location. Moreover, our studies reveal that SIRV core genes do not appear to be under diversifying selection and thus we predict that the abundant and diverse variable genes govern the coevolutionary arms race between SIRVs and their hosts.

Virus-induced dormancy in the archaeon Sulfolobus islandicus.

UNLABELLED: We investigated the interaction between Sulfolobus spindle-shaped virus (SSV9) and its native archaeal host Sulfolobus islandicus. We show that upon exposure to SSV9, S. islandicus strain RJW002 has a significant growth delay where the majority of cells are dormant (viable but not growing) for 24 to 48 hours postinfection (hpi) compared to the growth of controls without virus. We demonstrate that in this system, dormancy (i) is induced by both active and inactive virus particles at a low multiplicity of infection (MOI), (ii) is reversible in strains with active CRISPR-Cas immunity that prevents the establishment of productive infections, and (iii) results in dramatic and rapid host death if virus persists in the culture even at low levels. Our results add a new dimension to evolutionary models of virus-host interactions, showing that the mere presence of a virus induces host cell stasis and death independent of infection. This novel, highly sensitive, and risky bet-hedging antiviral response must be integrated into models of virus-host interactions in this system so that the true ecological impact of viruses can be predicted and understood. IMPORTANCE: Viruses of microbes play key roles in microbial ecology; however, our understanding of viral impact on host physiology is based on a few model bacteria that represent a small fraction of the life history strategies employed by hosts or viruses across the three domains that encompass the microbial world. We have demonstrated that rare and even inactive viruses induce dormancy in the model archaeon S. islandicus. Similar virus-induced dormancy strategies in other microbial systems may help to explain several confounding observations in other systems, including the surprising abundance of dormant cell types found in many microbial environments, the difficulty of culturing microorganisms in the laboratory, and the paradoxical virus-to-host abundances that do not match model predictions. A more accurate grasp of virus-host interactions will expand our understanding of the impact of viruses in microbial ecology.