Transmission from vaccinated individuals in a large SARS-CoV-2 Delta variant outbreak.

An outbreak of over 1,000 COVID-19 cases in Provincetown, Massachusetts (MA), in July 2021-the first large outbreak mostly in vaccinated individuals in the US-prompted a comprehensive public health response, motivating changes to national masking recommendations and raising questions about infection and transmission among vaccinated individuals. To address these questions, we combined viral genomic and epidemiological data from 467 individuals, including 40% of outbreak-associated cases. The Delta variant accounted for 99% of cases in this dataset; it was introduced from at least 40 sources, but 83% of cases derived from a single source, likely through transmission across multiple settings over a short time rather than a single event. Genomic and epidemiological data supported multiple transmissions of Delta from and between fully vaccinated individuals. However, despite its magnitude, the outbreak had limited onward impact in MA and the US overall, likely due to high vaccination rates and a robust public health response.

Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics.

Ebola virus (EBOV) causes epidemics with high mortality yet remains understudied due to the challenge of experimentation in high-containment and outbreak settings. Here, we used single-cell transcriptomics and CyTOF-based single-cell protein quantification to characterize peripheral immune cells during EBOV infection in rhesus monkeys. We obtained 100,000 transcriptomes and 15,000,000 protein profiles, finding that immature, proliferative monocyte-lineage cells with reduced antigen-presentation capacity replace conventional monocyte subsets, while lymphocytes upregulate apoptosis genes and decline in abundance. By quantifying intracellular viral RNA, we identify molecular determinants of tropism among circulating immune cells and examine temporal dynamics in viral and host gene expression. Within infected cells, EBOV downregulates STAT1 mRNA and interferon signaling, and it upregulates putative pro-viral genes (e.g., DYNLL1 and HSPA5), nominating pathways the virus manipulates for its replication. This study sheds light on EBOV tropism, replication dynamics, and elicited immune response and provides a framework for characterizing host-virus interactions under maximum containment.

Distinguishing Severe Acute Respiratory Syndrome Coronavirus 2 Persistence and Reinfection: A Retrospective Cohort Study.

BACKGROUND: Severe 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. METHODS: 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 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 <35 at repeat testing. For each included subject, likelihood of reinfection was assessed by viral genomic analysis of all available specimens with a Ct value <35, structured Ct trajectory criteria, and case-by-case review by infectious diseases physicians. RESULTS: Among 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. CONCLUSIONS: 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.

Rapid Detection of Powassan Virus in a Patient With Encephalitis by Metagenomic Sequencing.

We describe a patient with severe and progressive encephalitis of unknown etiology. We performed rapid metagenomic sequencing from cerebrospinal fluid and identified Powassan virus, an emerging tick-borne flavivirus that has been increasingly detected in the United States.

Clinical Performance of Cas13a-based Point-of-Care Lateral Flow Assay for Detecting Neisseria gonorrhoeae.

Background: Diagnosis of Neisseria (N.) gonorrhoeae is dependent on nucleic acid amplification testing (NAAT), which is not available in resource-limited settings where the prevalence of infection is highest. Recent advances in molecular diagnostics leveraging the high specificity of CRISPR enzymes can permit field-deployable, point-of-care lateral flow assays. We previously reported on the development and in vitro performance of a lateral flow assay for detecting N. gonorrhoeae. Here we aimed to pair that assay with point-of-care DNA extraction techniques and assess the performance on clinical urine specimens. Methods: We collected an additional urine specimen among individuals enrolling in an ongoing clinical trial at the Massachusetts General Hospital Sexual Health Clinic who presented with symptoms of urethritis or cervicitis (urethral or vaginal discharge, dysuria, or dyspareunia). We then assessed thermal, detergent, and combination DNA extraction conditions, varying the duration of heat at 95°C and concentration of Triton X. We assessed the efficacy of the various DNA extraction methods by quantitative polymerase chain reaction (qPCR). Once an extraction method was selected, we incubated samples for 90 minutes to permit isothermal recombinase polymerase amplification. We then assessed the performance of lateral flow Cas13a-based detection using our previously designed porA probe and primer system for N. gonorrhoeae detection, comparing lateral flow results with NAAT results from clinical care. Results: We assessed DNA extraction conditions on 3 clinical urine specimens. There was no consistent significant difference in copies per microliter of DNA obtained using more or less heat. On average, we noted that 0.02% triton combined with 5 minutes of heating to 95°C resulted in the highest DNA yield, however, 0.02% triton alone resulted in a quantity of DNA that was above the previously determined analytic sensitivity of the assay. Given that detergent-based extraction is more easily deployable, we selected that as our method for extraction. We treated 23 clinical specimens with 0.02% triton, which we added to the Cas13a detection system. We ran all lateral flow detections in duplicate. The Cas13a-based assay detected 8 of 8 (100%) positive specimens, and 0 of 15 negative specimens. Conclusion: Using point-of-care DNA extraction, isothermal amplification, and Cas13a-based detection, our point-of-care lateral flow N. gonorrhoeae assay correctly identified 23 clinical urine specimens as either positive or negative. Further evaluation of this assay among larger samples and more diverse sample types is warranted.

Babesia microti Variant With Multiple Resistance Mutations Detected in an Immunocompromised Patient Receiving Atovaquone Prophylaxis.

We report Babesia microti genomic sequences with multiple mutations in the atovaquone-target region of cytochrome b, including a newly identified Y272S mutation, plus 1 mutation of undetermined significance in the azithromycin-associated ribosomal protein L4. The parasite was sequenced from an immunocompromised patient on prophylactic atovaquone for Pneumocystis pneumonia before diagnosis of babesiosis.

Development of Cas13a-based assays for Neisseria gonorrhoeae detection and gyrase A determination.

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, the 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 the prevalence of infection 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. 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 fluorescein 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. We report the development of Cas13a-based SHERLOCK assays that detect N. gonorrhoeae and differentiate ciprofloxacin-resistant isolates from ciprofloxacin-susceptible isolates. IMPORTANCE Neisseria gonorrhoeae, the cause of gonorrhea, disproportionately affects resource-limited settings. Such areas, however, lack the technical capabilities for diagnosing the infection. The consequences of poor or absent diagnostics include increased disease morbidity, which, for gonorrhea, includes an increased risk for HIV infection, infertility, and neonatal blindness, as well as an overuse of antibiotics that contributes to the emergence of antibiotic resistance. We used a novel CRISPR-based technology to develop a rapid test that does not require laboratory infrastructure for both diagnosing gonorrhea and predicting whether ciprofloxacin can be used in its treatment, a one-time oral pill. With further development, that diagnostic test may be of use in low-resource settings.

Development of Cas13a-based Assays for Neisseria gonorrhoeae Detection and Gyrase A Determination.

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 por A gene and of predicting ciprofloxacin susceptibility via a single mutation in the gyrase A ( gyr A) gene. We evaluated their performance using both synthetic DNA and purified N. gonorrhoeae isolates. For por A, 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 gyr A, 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 gyr A 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.

Single-cell profiling of lncRNA expression during Ebola virus infection in rhesus macaques.

Long non-coding RNAs (lncRNAs) are involved in numerous biological processes and are pivotal mediators of the immune response, yet little is known about their properties at the single-cell level. Here, we generate a multi-tissue bulk RNAseq dataset from Ebola virus (EBOV) infected and not-infected rhesus macaques and identified 3979 novel lncRNAs. To profile lncRNA expression dynamics in immune circulating single-cells during EBOV infection, we design a metric, Upsilon, to estimate cell-type specificity. Our analysis reveals that lncRNAs are expressed in fewer cells than protein-coding genes, but they are not expressed at lower levels nor are they more cell-type specific when expressed in the same number of cells. In addition, we observe that lncRNAs exhibit similar changes in expression patterns to those of protein-coding genes during EBOV infection, and are often co-expressed with known immune regulators. A few lncRNAs change expression specifically upon EBOV entry in the cell. This study sheds light on the differential features of lncRNAs and protein-coding genes and paves the way for future single-cell lncRNA studies.

The 2022 RSV surge was driven by multiple viral lineages.

The US experienced an early and severe respiratory syncytial virus (RSV) surge in autumn 2022. Despite the pressure this has put on hospitals and care centers, the factors promoting the surge in cases are unknown. To investigate whether viral characteristics contributed to the extent or severity of the surge, we sequenced 105 RSV-positive specimens from symptomatic patients diagnosed with RSV who presented to the Massachusetts General Hospital (MGH) and its outpatient practices in the Greater Boston Area. Genomic analysis of the resulting 77 genomes (54 with >80% coverage, and 23 with >5% coverage) demonstrated that the surge was driven by multiple lineages of RSV-A (91%; 70/77) and RSV-B (9%; 7/77). Phylogenetic analysis of all US RSV-A revealed 12 clades, 4 of which contained Massachusetts and Washington genomes. These clades individually had times to most recent common ancestor (tMRCA) between 2014 and 2017, and together had a tMRCA of 2009, suggesting that they emerged well before the COVID-19 pandemic. Similarly, the RSV-B genomes had a tMRCA between 2016 and 2019. We found that the RSV-A and RSV-B genomes in our sample did not differ statistically from the estimated clock rate of the larger phylogenetic tree (10.6 and 12.4 substitutions per year, respectively). In summary, the polyphyletic nature of viral genomes sequenced in the US during the autumn 2022 surge is inconsistent with the emergence of a single, highly transmissible causal RSV lineage.

Natural history of Ebola virus disease in rhesus monkeys shows viral variant emergence dynamics and tissue-specific host responses.

Ebola virus (EBOV) causes Ebola virus disease (EVD), marked by severe hemorrhagic fever; however, the mechanisms underlying the disease remain unclear. To assess the molecular basis of EVD across time, we performed RNA sequencing on 17 tissues from a natural history study of 21 rhesus monkeys, developing new methods to characterize host-pathogen dynamics. We identified alterations in host gene expression with previously unknown tissue-specific changes, including downregulation of genes related to tissue connectivity. EBOV was widely disseminated throughout the body; using a new, broadly applicable deconvolution method, we found that viral load correlated with increased monocyte presence. Patterns of viral variation between tissues differentiated primary infections from compartmentalized infections, and several variants impacted viral fitness in a EBOV/Kikwit minigenome system, suggesting that functionally significant variants can emerge during early infection. This comprehensive portrait of host-pathogen dynamics in EVD illuminates new features of pathogenesis and establishes resources to study other emerging pathogens.

Synthetic DNA spike-ins (SDSIs) enable sample tracking and detection of inter-sample contamination in SARS-CoV-2 sequencing workflows.

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.

Comparative transmissibility of SARS-CoV-2 variants Delta and Alpha in New England, USA.

The SARS-CoV-2 Delta variant rose to dominance in mid-2021, likely propelled by an estimated 40%-80% increased transmissibility over Alpha. To investigate if this ostensible difference in transmissibility is uniform across populations, we partner with public health programs from all six states in New England in the United States. We compare logistic growth rates during each variant's respective emergence period, finding that Delta emerged 1.37-2.63 times faster than Alpha (range across states). We compute variant-specific effective reproductive numbers, estimating that Delta is 63%-167% more transmissible than Alpha (range across states). Finally, we estimate that Delta infections generate on average 6.2 (95% CI 3.1-10.9) times more viral RNA copies per milliliter than Alpha infections during their respective emergence. Overall, our evidence suggests that Delta's enhanced transmissibility can be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on underlying population attributes and sequencing data availability.

Multimodal surveillance of SARS-CoV-2 at a university enables development of a robust outbreak response framework.

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. CONCLUSIONS: 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. FUNDING: 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.

Enhanced Virus Detection and Metagenomic Sequencing in Patients with Meningitis and Encephalitis.

Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific tests, sometimes over days to weeks, whereas metagenomic next-generation sequencing (mNGS) profiles all nucleic acid in a sample. In this single-center, prospective study, 68 hospitalized patients with known (n = 44) or suspected (n = 24) CNS infections underwent mNGS from RNA and DNA to identify potential pathogens and also targeted sequencing of viruses using hybrid capture. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects, 3 of whom had no clinical diagnosis by routine workup. Among subjects diagnosed with infection by serology and/or peripheral samples, we demonstrated the utility of mNGS to detect pathogen nucleic acid in CSF, importantly for the Ixodes scapularis tick-borne pathogens Powassan virus, Borrelia burgdorferi, and Anaplasma phagocytophilum. We also evaluated two methods to enhance the detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed the detection of varicella-zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with efficacy similar to that of pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis. IMPORTANCE Meningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Despite intensive diagnostic efforts, 40 to 60% of people with meningitis or encephalitis have no clear cause of CNS disease identified. As diagnostic uncertainty often leads to costly inappropriate therapies, the need for novel pathogen detection methods is paramount. Metagenomic next-generation sequencing (mNGS) offers the unique opportunity to circumvent these challenges using unbiased laboratory and computational methods. Here, we performed comprehensive mNGS from 68 prospectively enrolled patients with known (n = 44) or suspected (n = 24) CNS viral infection from a single center in New England and evaluated enhanced methods to improve the detection of CNS pathogens, including those not traditionally identified in the CNS by nucleic acid detection. Overall, our work helps elucidate how mNGS can become integrated into the diagnostic toolkit for CNS infections.

Intrathecal inflammatory responses in the absence of SARS-CoV-2 nucleic acid in the CSF of COVID-19 hospitalized patients.

OBJECTIVE: Little is known about CSF profiles in patients with acute COVID-19 infection and neurological symptoms. Here, CSF was tested for SARS-CoV-2 RNA and inflammatory cytokines and chemokines and compared to controls and patients with known neurotropic pathogens. METHODS: CSF from twenty-seven consecutive patients with COVID-19 and neurological symptoms was assayed for SARS-CoV-2 RNA using quantitative reverse transcription PCR (RT-qPCR) and unbiased metagenomic sequencing. Assays for blood brain barrier (BBB) breakdown (CSF:serum albumin ratio (Q-Alb)), and proinflammatory cytokines and chemokines (IL-6, IL-8, IL-15, IL-16, monocyte chemoattractant protein -1 (MCP-1) and monocyte inhibitory protein - 1ß (MIP-1ß)) were performed in 23 patients and compared to CSF from patients with HIV-1 (16 virally suppressed, 5 unsuppressed), West Nile virus (WNV) (n = 4) and 16 healthy controls (HC). RESULTS: Median CSF cell count for COVID-19 patients was 1 white blood cell/µL; two patients were infected with a second pathogen (Neisseria, Cryptococcus neoformans). No CSF samples had detectable SARS-CoV-2 RNA by either detection method. In patients with COVID-19 only, CSF IL-6, IL-8, IL-15, and MIP-1ß levels were higher than HC and suppressed HIV (corrected-p < 0.05). MCP-1 and MIP-1ß levels were higher, while IL-6, IL-8, IL-15 were similar in COVID-19 compared to WNV patients. Q-Alb correlated with all proinflammatory markers, with IL-6, IL-8, and MIP-1ß (r ≥ 0.6, p < 0.01) demonstrating the strongest associations. CONCLUSIONS: Lack of SARS-CoV-2 RNA in CSF is consistent with pre-existing literature. Evidence of intrathecal proinflammatory markers in a subset of COVID-19 patients with BBB breakdown despite minimal CSF pleocytosis is atypical for neurotropic pathogens.

DNA spike-ins enable confident interpretation of SARS-CoV-2 genomic data from amplicon-based sequencing.

The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortium's amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.