Design methods for sensitive and comprehensive microbial surveillance

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.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Metsky, Hayden C.

Advisor dc:contributor.advisor

• Pardis C. Sabeti.

• Electrical Engineering and Computer Science.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/128293

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/128293