Search

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continually evolving resulting in variants with increased transmissibility, more severe disease, reduced effectiveness of treatments or vaccines, or diagnostic detection failure. The SARS-CoV-2 Delta variant (B.1.617.2 and AY lineages) was the dominant circulating strain in the United States from July to mid-December 2021, followed by the Omicron variant (B.1.1.529 and BA lineages). Coronavirus disease 2019 (COVID-19) has been associated with neurological sequelae including loss of taste/smell, headache, encephalopathy, and stroke, yet little is known about the impact of viral strain on neuropathogenesis. Detailed postmortem brain evaluations were performed for 22 patients from Massachusetts, including 12 who died following infection with Delta variant and 5 with Omicron variant, compared to 5 patients who died earlier in the pandemic. Diffuse hypoxic injury, occasional microinfarcts and hemorrhage, perivascular fibrinogen, and rare lymphocytes were observed across the 3 groups. SARS-CoV-2 protein and RNA were not detected in any brain samples by immunohistochemistry, in situ hybridization, or real-time quantitative PCR. These results, although preliminary, demonstrate that, among a subset of severely ill patients, similar neuropathological features are present in Delta, Omicron, and non-Delta/non-Omicron variant patients, suggesting that SARS-CoV-2 variants are likely to affect the brain by common neuropathogenic mechanisms.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection is poorly understood, partly because few studies have systematically applied genomic analysis to distinguish reinfection from persistent RNA detection related to initial infection. We aimed to evaluate the characteristics of SARS-CoV-2 reinfection and persistent RNA detection using independent genomic, clinical, and laboratory assessments.MethodsAll individuals at a large academic medical center who underwent a SARS-CoV-2 nucleic acid amplification test (NAAT) ≥45 days after an initial positive test, with both tests between 14 March and 30 December 2020, were analyzed for potential reinfection. Inclusion criteria required having ≥2 positive NAATs collected ≥45 days apart with a cycle threshold (Ct) value ResultsAmong 1569 individuals with repeat SARS-CoV-2 testing ≥45 days after an initial positive NAAT, 65 (4%) met cohort inclusion criteria. Viral genomic analysis characterized mutations present and was successful for 14/65 (22%) subjects. Six subjects had genomically supported reinfection, and 8 subjects had genomically supported persistent RNA detection. Compared to viral genomic analysis, clinical and laboratory assessments correctly distinguished reinfection from persistent RNA detection in 12/14 (86%) subjects but missed 2/6 (33%) genomically supported reinfections.ConclusionsDespite good overall concordance with viral genomic analysis, clinical and Ct value-based assessments failed to identify 33% of genomically supported reinfections. Scaling-up genomic analysis for clinical use would improve detection of SARS-CoV-2 reinfections.

Background Neisseria gonorrhoeae is one of the most common bacterial sexually transmitted infections. The emergence of antimicrobial-resistant N. gonorrhoeae is an urgent public health threat. Currently, diagnosis of N. gonorrhoeae infection requires expensive laboratory infrastructure, while antimicrobial susceptibility determination requires bacterial culture, both of which are infeasible in low-resource areas where prevalence is highest. Recent advances in molecular diagnostics, such as Specific High-sensitivity Enzymatic Reporter unLOCKing (SHERLOCK) using CRISPR-Cas13a and isothermal amplification, have the potential to provide low-cost detection of pathogen and antimicrobial resistance. Methods and Results We designed and optimized RNA guides and primer-sets for SHERLOCK assays capable of detecting N. gonorrhoeae via the porA gene and of predicting ciprofloxacin susceptibility via a single mutation in the gyrase A (gyrA) gene. We evaluated their performance using both synthetic DNA and purified N. gonorrhoeae isolates. For porA, we created both a fluorescence-based assay and lateral flow assay using a biotinylated FAM reporter. Both methods demonstrated sensitive detection of 14 N. gonorrhoeae isolates and no cross-reactivity with 3 non-gonococcal Neisseria isolates. For gyrA, we created a fluorescence-based assay that correctly distinguished between 20 purified N. gonorrhoeae isolates with phenotypic ciprofloxacin resistance and 3 with phenotypic susceptibility. We confirmed the gyrA genotype predictions from the fluorescence-based assay with DNA sequencing, which showed 100% concordance for the isolates studied. Conclusion We report the development of Cas13a-based SHERLOCK assays that detect N. gonorrhoeae and differentiate ciprofloxacin-resistant isolates from ciprofloxacin-susceptible isolates.

Raw count matrices for the three datasets used in the study: - Multitissue short-read bulkRNA-sequencing data from Ebola virus-infected and not infectedRhesus Macaque (GSE192447, GSE115785) - Sigle-cell RNA-sequencing data from Rhesus MacaquePBMCs infected with Ebola virusin vivo(GSE158390) - Sigle-cell RNA-sequencing data from Rhesus MacaquePBMCs infected with Ebola virus exvivo(GSE158390)

Background The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly transmissible in vaccinated and unvaccinated populations. The dynamics that govern its establishment and propensity toward fixation (reaching 100% frequency in the SARS-CoV-2 population) in communities remain unknown. Here, we describe the dynamics of Omicron at 3 institutions of higher education (IHEs) in the greater Boston area. Methods We use diagnostic and variant-specifying molecular assays and epidemiological analytical approaches to describe the rapid dominance of Omicron following its introduction into 3 IHEs with asymptomatic surveillance programs. Results We show that the establishment of Omicron at IHEs precedes that of the state and region and that the time to fixation is shorter at IHEs (9.5–12.5 days) than in the state (14.8 days) or region. We show that the trajectory of Omicron fixation among university employees resembles that of students, with a 2- to 3-day delay. Finally, we compare cycle threshold values in Omicron vs Delta variant cases on college campuses and identify lower viral loads among college affiliates who harbor Omicron infections. Conclusions We document the rapid takeover of the Omicron variant at IHEs, reaching near-fixation within the span of 9.5–12.5 days despite lower viral loads, on average, than the previously dominant Delta variant. These findings highlight the transmissibility of Omicron, its propensity to rapidly dominate small populations, and the ability of robust asymptomatic surveillance programs to offer early insights into the dynamics of pathogen arrival and spread.

Synthetic biomarkers, bioengineered sensors that generate molecular reporters in diseased microenvironments, represent an emerging paradigm in precision diagnostics. Despite the utility of DNA barcodes as a multiplexing tool, their susceptibility to nucleases in vivo has limited their utility. Here we exploit chemically stabilized nucleic acids to multiplex synthetic biomarkers and produce diagnostic signals in biofluids that can be ‘read out’ via CRISPR nucleases. The strategy relies on microenvironmental endopeptidase to trigger the release of nucleic acid barcodes and polymerase-amplification-free, CRISPR-Cas-mediated barcode detection in unprocessed urine. Our data suggest that DNA-encoded nanosensors can non-invasively detect and differentiate disease states in transplanted and autochthonous murine cancer models. We also demonstrate that CRISPR-Cas amplification can be harnessed to convert the readout to a point-of-care paper diagnostic tool. Finally, we employ a microfluidic platform for densely multiplexed, CRISPR-mediated DNA barcode readout that can potentially evaluate complex human diseases rapidly and guide therapeutic decisions.

Lyme disease is the most common vector-borne disease in North America and Europe. The clinical manifestations of Lyme disease vary based on the genospecies of the infectingBorrelia burgdorferispirochete, but the microbial genetic elements underlying these associations are not known. Here, we report the whole genome sequence (WGS) and analysis of 299 patient-derivedB. burgdorferisensu stricto (Bbss) isolates from patients in the Eastern and Midwestern US and Central Europe. We develop a WGS-based classification ofBbssisolates, confirm and extend the findings of previous single- and multi-locus typing systems, define the plasmid profiles of human-infectiousBbssisolates, annotate the core and strain-variable surface lipoproteome, and identify loci associated with disseminated infection. A core genome consisting of ∼800 open reading frames and a core set of plasmids consisting of lp17, lp25, lp36, lp28-3, lp28-4, lp54, and cp26 are found in nearly all isolates. Strain-variable (accessory) plasmids and genes correlate strongly with phylogeny. Using genetic association study methods, we identify an accessory genome signature associated with dissemination and define the individual plasmids and genes that make up this signature. Strains within the RST1/WGS A subgroup, particularly a subset marked by the OspC type A genotype, are associated with increased rates of dissemination. OspC type A strains possess a unique constellation of strongly linked genetic changes including the presence of lp56 and lp28-1 plasmids and a cluster of genes that may contribute to their enhanced virulence compared to other genotypes. The patterns of OspC type A strains typify a broader paradigm acrossBbssisolates, in which genetic structure is defined by correlated groups of strain-variable genes located predominantly on plasmids, particularly for expression of surface-exposed lipoproteins. These clusters of genes are inherited in blocks through strain-specific patterns of plasmid occupancy and are associated with the probability of invasive infection.

Identifying the dissemination patterns and impacts of a virus of economic or health importance during a pandemic is crucial, as it informs the public on policies for containment in order to reduce the spread of the virus. In this study, we integrated genomic and travel data to investigate the emergence and spread of the SARS-CoV-2 B.1.1.318 and B.1.525 (Eta) variants of interest in Nigeria and the wider Africa region. By integrating travel data and phylogeographic reconstructions, we find that these two variants that arose during the second wave in Nigeria emerged from within Africa, with the B.1.525 from Nigeria, and then spread to other parts of the world. Data from this study show how regional connectivity of Nigeria drove the spread of these variants of interest to surrounding countries and those connected by air-traffic. Our findings demonstrate the power of genomic analysis when combined with mobility and epidemiological data to identify the drivers of transmission, as bidirectional transmission within and between African nations are grossly underestimated as seen in our import risk index estimates.

SARS-CoV-2 distribution and circulation dynamics are not well understood due to challenges in assessing genomic data from tissue samples. We develop experimental and computational workflows for high-depth viral sequencing and high-resolution genomic analyses from formalin-fixed, paraffin-embedded tissues and apply them to 120 specimens from six subjects with fatal COVID-19. To varying degrees, viral RNA is present in extrapulmonary tissues from all subjects. The majority of the 180 viral variants identified within subjects are unique to individual tissue samples. We find more high-frequency (>10%) minor variants in subjects with a longer disease course, with one subject harboring ten such variants, exclusively in extrapulmonary tissues. One tissue-specific high-frequency variant was a nonsynonymous mutation in the furin-cleavage site of the spike protein. Our findings suggest adaptation and/or compartmentalized infection, illuminating the basis of extrapulmonary COVID-19 symptoms and potential for viral reservoirs, and have broad utility for investigating human pathogens.

Design of nucleic acid-based viral diagnostics typically follows heuristic rules and, to contend with viral variation, focuses on a genome’s conserved regions. A design process could, instead, directly optimize diagnostic effectiveness using a learned model of sensitivity for targets and their variants. Toward that goal, we screen 19,209 diagnostic–target pairs, concentrated on CRISPR-based diagnostics, and train a deep neural network to accurately predict diagnostic readout. We join this model with combinatorial optimization to maximize sensitivity over the full spectrum of a virus’s genomic variation. We introduce Activity-informed Design with All-inclusive Patrolling of Targets (ADAPT), a system for automated design, and use it to design diagnostics for 1,933 vertebrate-infecting viral species within 2 hours for most species and within 24 hours for all but three. We experimentally show that ADAPT’s designs are sensitive and specific to the lineage level and permit lower limits of detection, across a virus’s variation, than the outputs of standard design techniques. Our strategy could facilitate a proactive resource of assays for detecting pathogens.

The coronavirus disease 2019 (COVID-19) pandemic has demonstrated a clear need for high-throughput, multiplexed and sensitive assays for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory viruses and their emerging variants. Here, we present a cost-effective virus and variant detection platform, called microfluidic Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (mCARMEN), which combines CRISPR-based diagnostics and microfluidics with a streamlined workflow for clinical use. We developed the mCARMEN respiratory virus panel to test for up to 21 viruses, including SARS-CoV-2, other coronaviruses and both influenza strains, and demonstrated its diagnostic-grade performance on 525 patient specimens in an academic setting and 166 specimens in a clinical setting. We further developed an mCARMEN panel to enable the identification of 6 SARS-CoV-2 variant lineages, including Delta and Omicron, and evaluated it on 2,088 patient specimens with near-perfect concordance to sequencing-based variant classification. Lastly, we implemented a combined Cas13 and Cas12 approach that enables quantitative measurement of SARS-CoV-2 and influenza A viral copies in samples. The mCARMEN platform enables high-throughput surveillance of multiple viruses and variants simultaneously, enabling rapid detection of SARS-CoV-2 variants.

The burden of ticks and the pathogens they carry is increasing worldwide. Powassan virus (POWV; Flaviviridae: Flavivirus), the only known North American tick-borne flavivirus, is of particular concern due to rising cases and the severe morbidity of POWV encephalitis. Here, we use a multifaceted approach to evaluate the emergence of the II POWV lineage, known as deer tick virus (DTV), in parts of North America where human cases occur. We detected DTV-positive ticks from eight of twenty locations in the Northeast USA with an average infection rate of 1.4 per cent. High-depth, whole-genome sequencing of eighty-four POWV and DTV samples allowed us to assess geographic and temporal phylodynamics. We observed both stable infection in the Northeast USA and patterns of geographic dispersal within and between regions. A Bayesian skyline analysis demonstrated DTV population expansion over the last 50 years. This is concordant with the documented expansion of Ixodes scapularis tick populations and suggests an increasing risk of human exposure as the vector spreads. Finally, we isolated sixteen novel viruses in cell culture and demonstrated limited genetic change after passage, a valuable resource for future studies investigating this emerging virus.

The global spread and continued evolution of SARS-CoV-2 has driven an unprecedented surge in viral genomic surveillance. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine laboratory processes and results. This challenge will increase with the expanding global production of sequences across a variety of laboratories for epidemiological and clinical interpretation, as well as for genomic surveillance of emerging diseases in future outbreaks. We present SDSI + AmpSeq, an approach that uses 96 synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination throughout the sequencing workflow. We apply SDSIs to the ARTIC Consortium's amplicon design, demonstrate their utility and efficiency in a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases and validate them across 6,676 diagnostic samples at multiple laboratories. We establish that SDSI + AmpSeq provides increased confidence in genomic data by detecting and correcting for relatively common, yet previously unobserved modes of error, including spillover and sample swaps, without impacting genome recovery.

While genome-wide association studies (GWAS) and selection scans identify genomic loci driving human phenotypic diversity, functional validation is required to discover the variant(s) responsible. We dissected theIVDlocus, implicated by selection statistics, multiple GWAS, and clinical genetics as important to function and fitness. We combined luciferase assays, CRISPR/Cas9 genome-editing, massively parallel reporter assays (MPRA), and bashing of regulatory loci. We identified three regulatory variants, including an indel, that may underpin GWAS signals for pulmonary fibrosis and testosterone, and that are linked on a positively selected haplotype in the Japanese population. These regulatory variants exhibit synergistic and opposing effects onIVDexpression experimentally. Alleles at these variants lie on a haplotype tagged by the variant most strongly associated withIVDexpression and metabolites, but with no functional evidence itself. This work demonstrates how comprehensive functional investigation and multiple technologies are needed to discover the true genetic drivers of phenotypic diversity.

Identifying the dissemination patterns and impacts of a virus of economic or health importance during a pandemic is crucial, as it informs the public on policies for containment in order to reduce the spread of the virus. In this study, we integrated genomic and travel data to investigate the emergence and spread of the B.1.1.318 and B.1.525 variants of interest in Nigeria and the wider Africa region. By integrating travel data and phylogeographic reconstructions, we find that these two variants that arose during the second wave emerged from within Africa, with the B.1.525 from Nigeria, and then spread to other parts of the world. Our results show how regional connectivity in downsampled regions like Africa can often influence virus transmissions between neighbouring countries. Our findings demonstrate the power of genomic analysis when combined with mobility and epidemiological data to identify the drivers of transmission in the region, generating actionable information for public health decision makers in the region.

Universities are vulnerable to infectious disease outbreaks, making them ideal environments to study transmission dynamics and evaluate mitigation and surveillance measures. Here, we analyze multimodal COVID-19-associated data collected during the 2020-2021 academic year at Colorado Mesa University and introduce a SARS-CoV-2 surveillance and response framework.We analyzed epidemiological and sociobehavioral data (demographics, contact tracing, and WiFi-based co-location data) alongside pathogen surveillance data (wastewater and diagnostic testing, and viral genomic sequencing of wastewater and clinical specimens) to characterize outbreak dynamics and inform policy. We applied relative risk, multiple linear regression, and social network assortativity to identify attributes or behaviors associated with contracting SARS-CoV-2. To characterize SARS-CoV-2 transmission, we used viral sequencing, phylogenomic tools, and functional assays.Athletes, particularly those on high-contact teams, had the highest risk of testing positive. On average, individuals who tested positive had more contacts and longer interaction durations than individuals who never tested positive. The distribution of contacts per individual was overdispersed, although not as overdispersed as the distribution of phylogenomic descendants. Corroboration via technical replicates was essential for identification of wastewater mutations.Based on our findings, we formulate a framework that combines tools into an integrated disease surveillance program that can be implemented in other congregate settings with limited resources.This work was supported by the National Science Foundation, the Hertz Foundation, the National Institutes of Health, the Centers for Disease Control and Prevention, the Massachusetts Consortium on Pathogen Readiness, the Howard Hughes Medical Institute, the Flu Lab, and the Audacious Project.

We measured viral kinetics of SARS-CoV-2 Omicron infection in 36 mRNA-vaccinated individuals, 11 of whom were treated with nirmatrelvir-ritonavir (NMV-r). We found that NMV-r was associated with greater incidence of viral rebound compared to no treatment. For those that did not rebound, NMV-r significantly reduced time to PCR conversion.

Effective interpretation of genome function and genetic variation requires a shift from epigenetic mapping of cis-regulatory elements (CREs) to characterization of endogenous function. We developed hybridization chain reaction fluorescence in situ hybridization coupled with flow cytometry (HCR-FlowFISH), a broadly applicable approach to characterize CRISPR-perturbed CREs via accurate quantification of native transcripts, alongside CRISPR activity screen analysis (CASA), a hierarchical Bayesian model to quantify CRE activity. Across >325,000 perturbations, we provide evidence that CREs can regulate multiple genes, skip over the nearest gene and display activating and/or silencing effects. At the cholesterol-level-associated FADS locus, we combine endogenous screens with reporter assays to exhaustively characterize multiple genome-wide association signals, functionally nominate causal variants and, importantly, identify their target genes.

Despite numerous viral outbreaks in the last decade, including a devastating global pandemic, diagnostic and therapeutic technologies remain severely lacking. CRISPR-Cas systems have the potential to address these critical needs in the response against infectious disease. Initially discovered as the bacterial adaptive immune system, these systems provide a unique opportunity to create programmable, sequence-specific technologies for detection of viral nucleic acids and inhibition of viral replication. This review summarizes how CRISPR-Cas systems—in particular the recently discovered DNA-targeting Cas12 and RNA-targeting Cas13, both possessing a unique trans-cleavage activity—are being harnessed for viral diagnostics and therapies. We further highlight the numerous technologies whose development has accelerated in response to the COVID-19 pandemic., In this review, Freije et al. describe the ways CRISPR-Cas systems have been harnessed for the detection and inhibition of mammalian viruses. They focus on Cas12- and Cas13-based detection technologies, including those developed in response to the COVID-19 pandemic and studies of Cas9 and Cas13’s antiviral activity.

Viral genomic surveillance has been integral in the global response to the SARS-CoV-2 pandemic. Surveillance efforts rely on the availability of representative clinical specimens from ongoing testing activities. However, testing practices have recently shifted due to the widespread availability and use of rapid antigen tests, which could lead to gaps in future monitoring efforts. As such, genomic surveillance strategies must adapt to include laboratory workflows that are robust to sample type. To that end, we compare the results of RT-qPCR and viral genome sequencing using samples from positive BinaxNOW™ COVID-19 Antigen Card swabs (N=555) to those obtained from previously collected nasopharyngeal (NP) swabs used for nucleic acid amplification testing (N=135). We show that swabs obtained from antigen cards are comparable in performance to clinical excess samples from NP swabs, providing a viable alternative. This validation permits the reliable expansion of viral genomic surveillance to cases identified in the clinic or home setting where rapid antigen tests are used.

The widespread transmission and evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) call for rapid nucleic acid diagnostics that are easy to use outside of centralized clinical laboratories. Here we report the development and performance benchmarking of Cas13-based nucleic acid assays leveraging lyophilised reagents and fast sample inactivation at ambient temperature. The assays, which we named SHINEv.2 (for ‘streamlined highlighting of infections to navigate epidemics, version 2’), simplify the previously reported RNA-extraction-free SHINEv.1 technology by eliminating heating steps and the need for cold storage of the reagents. SHINEv.2 detected SARS-CoV-2 in nasopharyngeal samples with 90.5% sensitivity and 100% specificity (benchmarked against the reverse transcription quantitative polymerase chain reaction) in less than 90 min, using lateral-flow technology and incubation in a heat block at 37 °C. SHINEv.2 also allows for the visual discrimination of the Alpha, Beta, Gamma, Delta and Omicron SARS-CoV-2 variants, and can be run without performance losses by using body heat. Accurate, easy-to-use and equipment-free nucleic acid assays could facilitate wider testing for SARS-CoV-2 and other pathogens in point-of-care and at-home settings.

Repeated emergence of SARS-CoV-2 variants with increased fitness necessitates rapid detection and characterization of new lineages. To address this need, we developed PyR0, a hierarchical Bayesian multinomial logistic regression model that infers relative prevalence of all viral lineages across geographic regions, detects lineages increasing in prevalence, and identifies mutations relevant to fitness. Applying PyR0to all publicly available SARS-CoV-2 genomes, we identify numerous substitutions that increase fitness, including previously identified spike mutations and many non-spike mutations within the nucleocapsid and nonstructural proteins. PyR0forecasts growth of new lineages from their mutational profile, identifies viral lineages of concern as they emerge, and prioritizes mutations of biological and public health concern for functional characterization.One Sentence summaryA Bayesian hierarchical model of all SARS-CoV-2 viral genomes predicts lineage fitness and identifies associated mutations.

A 56-year-old man receiving rituximab who had months of neurologic symptoms was found to have Jamestown Canyon virus in cerebrospinal fluid by clinical metagenomic sequencing. The patient died, and postmortem examination revealed extensive neuropathologic abnormalities. Deep sequencing enabled detailed characterization of viral genomes from the cerebrospinal fluid, cerebellum, and cerebral cortex.

SARS-CoV-2 reinfection is poorly understood, partly because few studies have systematically applied genomic analysis to distinguish reinfection from persistent RNA detection related to initial infection. We aimed to evaluate the characteristics of SARS-CoV-2 reinfection and persistent RNA detection using independent genomic, clinical, and laboratory assessments.All individuals at a large academic medical center who underwent a SARS-CoV-2 nucleic acid amplification test (NAAT) ≥ 45 days after an initial positive test, with both tests between March 14th and December 30th, 2020, were analyzed for potential reinfection. Inclusion criteria required having ≥2 positive NAATs collected ≥45 days apart with a cycle threshold (Ct) value35 at repeat testing. For each included subject, likelihood of reinfection was assessed by viral genomic analysis of all available specimens with a Ct value35, structured Ct trajectory criteria, and case-by-case review by infectious diseases physicians.Among 1,569 individuals with repeat SARS-CoV-2 testing ≥45 days after an initial positive NAAT, 65 (4%) met cohort inclusion criteria. Viral genomic analysis characterized mutations present, and was successful for 14/65 (22%) subjects. Six subjects had genomically-supported reinfection and eight subjects had genomically-supported persistent RNA detection. Compared to viral genomic analysis, clinical and laboratory assessments correctly distinguished reinfection from persistent RNA detection in 12/14 (86%) subjects but missed 2/6 (33%) genomically-supported reinfections.Despite good overall concordance with viral genomic analysis, clinical and Ct value-based assessments failed to identify 33% of genomically-supported reinfections. Scaling-up genomic analysis for clinical use would improve detection of SARS-CoV-2 reinfections.