Combining genomics and epidemiology to track mumps virus transmission in the United States.

Unusually large outbreaks of mumps across the United States in 2016 and 2017 raised questions about the extent of mumps circulation and the relationship between these and prior outbreaks. We paired epidemiological data from public health investigations with analysis of mumps virus whole genome sequences from 201 infected individuals, focusing on Massachusetts university communities. Our analysis suggests continuous, undetected circulation of mumps locally and nationally, including multiple independent introductions into Massachusetts and into individual communities. Despite the presence of these multiple mumps virus lineages, the genomic data show that one lineage has dominated in the US since at least 2006. Widespread transmission was surprising given high vaccination rates, but we found no genetic evidence that variants arising during this outbreak contributed to vaccine escape. Viral genomic data allowed us to reconstruct mumps transmission links not evident from epidemiological data or standard single-gene surveillance efforts and also revealed connections between apparently unrelated mumps outbreaks

Genomic epidemiology reveals multiple introductions of Zika virus into the United States

Zika virus (ZIKV) is causing an unprecedented epidemic linked to severe congenital abnormalities. In July 2016, mosquito-borne ZIKV transmission was reported in the continental United States; since then, hundreds of locally acquired infections have been reported in Florida. To gain insights into the timing, source, and likely route(s) of ZIKV introduction, we tracked the virus from its first detection in Florida by sequencing ZIKV genomes from infected patients and Aedes aegypti mosquitoes. We show that at least 4 introductions, but potentially as many as 40, contributed to the outbreak in Florida and that local transmission is likely to have started in the spring of 2016-several months before its initial detection. By analysing surveillance and genetic data, we show that ZIKV moved among transmission zones in Miami. Our analyses show that most introductions were linked to the Caribbean, a finding corroborated by the high incidence rates and traffic volumes from the region into the Miami area. Our study provides an understanding of how ZIKV initiates transmission in new regions

Capturing sequence diversity in metagenomes with comprehensive and scalable probe design.

Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of, and scale well with, known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic samples. We design, synthesize, and validate multiple probe sets, including one that targets the whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriches unique viral content on average 18-fold, allowing us to assemble genomes that could not be recovered without enrichment, and accurately preserves within-sample diversity. We also use these probe sets to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of uncharacterized viral infections in human and mosquito samples. The results demonstrate that CATCH enables more sensitive and cost-effective metagenomic sequencing

Genome sequencing reveals Zika virus diversity and spread in the Americas

Although the recent Zika virus (ZIKV) epidemic in the Americas and its link to birth defects have attracted a great deal of attention, much remains unknown about ZIKV disease epidemiology and ZIKV evolution, in part owing to a lack of genomic data. Here we address this gap in knowledge by using multiple sequencing approaches to generate 110 ZIKV genomes from clinical and mosquito samples from 10 countries and territories, greatly expanding the observed viral genetic diversity from this outbreak. We analysed the timing and patterns of introductions into distinct geographic regions; our phylogenetic evidence suggests rapid expansion of the outbreak in Brazil and multiple introductions of outbreak strains into Puerto Rico, Honduras, Colombia, other Caribbean islands, and the continental United States. We find that ZIKV circulated undetected in multiple regions for many months before the first locally transmitted cases were confirmed, highlighting the importance of surveillance of viral infections. We identify mutations with possible functional implications for ZIKV biology and pathogenesis, as well as those that might be relevant to the effectiveness of diagnostic tests

A high-resolution study of the chromatin environment around regulatory elements

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 111-114).Chemical modifications to histones, the proteins around which DNA wraps, are believed to play an important role in gene regulation. These modifications, along with others, make up a cell's "epigenome." It is known that the presence of a particular combination of these modifications at a region of a cell's genome determines, for that region, a state that carries functional significance. This work seeks to better understand the importance of not just presence, but also distribution of modifications within regulatory regions. One approach aimed at improving our understanding is to cluster regulatory regions based on information contained in signals that describe, at a high-resolution, the distribution of these modifications. In this thesis we develop a tool, called ChromSMS, to perform this clustering in a biologically meaningful and efficient way that is versatile in handling the underlying complexities of these signals. We apply the tool to data from the NIH's Roadmap Epigenomics Project to analyze ChromSMS and to better understand the mechanisms behind the patterns we observe. We find that ChromSMS produces meaningful clusters that are different from each other at a statistically significant level. Using ChromSMS to conduct analyses of epigenomic data, we discover strong relations between GC-content and the distribution of particular modifications. Furthermore, we uncover a small number of patterns that display high functional enrichment, and we begin to study the possible role and significance of motifs in driving these patterns. We conclude that ChromSMS can serve as a useful tool in examining regulatory regions at a high-resolution.by Hayden C. Metsky.M. Eng

Design methods for sensitive and comprehensive microbial surveillance

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2020Cataloged from student-submitted PDF of thesis.Includes bibliographical references (pages 169-203).We are surrounded by a vast and dynamic microbial world. Effective surveillance tools can benefit medicine and public health, including infectious disease diagnostics, proactive pathogen detection and characterization, and microbiome studies. New genomic technologies are transforming microbial surveillance, but face challenges stemming from low concentrations in collected samples and extensive, ever-changing diversity. In this thesis, we first demonstrate a need for stronger surveillance through mapping the spread of Zika virus during the 2015-16 epidemic. We generate 110 Zika virus genomes from across the Americas, forming the largest and most diverse Zika virus dataset at the time. We perform a Bayesian phylogenetic analysis of Zika's spread and discover that it circulated undetected in multiple regions for many months. Two reasons are that Zika virus is present in samples at ultra-low abundance and was, during its rapid spread, an obscure pathogen.Motivated by this, we develop computational approaches that enable sensitive, comprehensive surveillance. We present CATCH, an algorithm that enhances enrichment of highly diverse whole genomes for more sensitive sequencing. CATCH designs scalable capture probe sets that are comprehensive, to a well-defined extent, against known sequence diversity. We use CATCH to design probes targeting whole genomes of the 356 viral species known to infect humans, including their vast subspecies diversity. Applied to 30 patient and environmental samples, we show that these probes improve hypothesis-free detection of viral infections and considerably enhance genome assembly. Academic labs, research hospitals, and government public health institutes are using CATCH to help detect and characterize microbes. We also present ADAPT, a system for end-to-end sequence design of nucleic acid diagnostic assays.We develop algorithms to comprehensively consider known diversity and enforce high taxon-specificity, even under relaxed criteria arising with RNA binding. Focusing on CRISPR-Cas13 detection, we perform high-throughput screening of crRNA-target pairs and develop a model, applied to our dataset, that predicts detection activity; using this, ADAPT's designs have high predicted activity. Along with CATCH, ADAPT advances microbial surveillance by leveraging and progressing with the extensive, ever-changing landscape of microbial genome diversity.by Hayden C. Metsky.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc

Programmable Inhibition and Detection of RNA Viruses Using Cas13

© 2019 The Authors The CRISPR effector Cas13 could be an effective antiviral for single-stranded RNA (ssRNA) viruses because it programmably cleaves RNAs complementary to its CRISPR RNA (crRNA). Here, we computationally identify thousands of potential Cas13 crRNA target sites in hundreds of ssRNA viral species that can potentially infect humans. We experimentally demonstrate Cas13's potent activity against three distinct ssRNA viruses: lymphocytic choriomeningitis virus (LCMV); influenza A virus (IAV); and vesicular stomatitis virus (VSV). Combining this antiviral activity with Cas13-based diagnostics, we develop Cas13-assisted restriction of viral expression and readout (CARVER), an end-to-end platform that uses Cas13 to detect and destroy viral RNA. We further screen hundreds of crRNAs along the LCMV genome to evaluate how conservation and target RNA nucleotide content influence Cas13's antiviral activity. Our results demonstrate that Cas13 can be harnessed to target a wide range of ssRNA viruses and CARVER's potential broad utility for rapid diagnostic and antiviral drug development. Freije et al. demonstrate that Cas13 can be programmed to target and destroy the genomes of diverse mammalian single-stranded RNA viruses. They identify design principles for efficient Cas13 targeting of viral RNA and create companion Cas13-based diagnostics to rapidly measure the effects of Cas13 targeting

Massively multiplexed nucleic acid detection using Cas13

The overwhelming majority of globally circulating pathogens go undetected, undermining patient care and hindering outbreak preparedness and response. To enable routine surveillance and comprehensive diagnostic applications, there is a need for detection technologies that can scale to test many samples while simultaneously testing for many pathogens. Here, we develop Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN), a platform for scalable, multiplexed pathogen detection. In the CARMEN platform, nanoliter droplets containing CRISPR-based nucleic acid detection reagents self-organize in a microwell array to pair with droplets of amplified samples, testing each sample against each CRISPR RNA (crRNA) in replicate. The combination of CARMEN and Cas13 detection (CARMEN-Cas13) enables robust testing of >4,500 crRNA-target pairs on a single array. Using CARMEN-Cas13, we developed a multiplexed assay that simultaneously differentiates all 169 human-associated viruses with ≥10 published genome sequences and rapidly incorporated an additional crRNA to detect the causative agent of the 2020 COVID-19 pandemic. CARMEN-Cas13 further enables comprehensive subtyping of influenza A strains and multiplexed identification of dozens of HIV drug-resistance mutations. CARMEN’s intrinsic multiplexing and throughput capabilities make it practical to scale, as miniaturization decreases reagent cost per test >300-fold. Scalable, highly-multiplexed CRISPR-based nucleic acid detection shifts diagnostic and surveillance efforts from targeted testing of high-priority samples to comprehensive testing of large sample sets, greatly benefiting patients and public health. ©202

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

Abstract 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

Field-deployable viral diagnostics using CRISPR-Cas13

Mitigating global infectious disease requires diagnostic tools that are sensitive, specific, and rapidly field deployable. In this study, we demonstrate that the Cas13-based SHERLOCK (specific high-sensitivity enzymatic reporter unlocking) platform can detect Zika virus (ZIKV) and dengue virus (DENV) in patient samples at concentrations as low as 1 copy per microliter. We developed HUDSON (heating unextracted diagnostic samples to obliterate nucleases), a protocol that pairs with SHERLOCK for viral detection directly from bodily fluids, enabling instrument-free DENV detection directly from patient samples in <2 hours. We further demonstrate that SHERLOCK can distinguish the four DENV serotypes, as well as region-specific strains of ZIKV from the 2015–2016 pandemic. Finally, we report the rapid (<1 week) design and testing of instrument-free assays to detect clinically relevant viral single-nucleotide polymorphisms.NIH (Grants AI-100190, 1R01-HG009761, 1R01-MH110049, and 1DP1-HL141201