A computational method helps scientists examine microbes at a larger, more comprehensive scale than previously possible.
Credit: Susanna M. Hamilton, Broad Communications
During the Zika virus outbreak of 2015-16,
public health officials scrambled to contain the epidemic and curb the
pathogen's devastating effects on pregnant women. At the same time,
scientists around the globe tried to understand the genetics of this
mysterious virus.
The problem was, there just aren't many Zika virus particles in the
blood of a sick patient. Looking for it in clinical samples can be like
fishing for a minnow in an ocean.
A new computational method developed by Broad Institute scientists
helps overcome this hurdle. Built in the lab of Broad Institute
researcher Pardis Sabeti, the "CATCH" method can be used to design
molecular "baits" for any virus known to infect humans and all their
known strains, including those that are present in low abundance in
clinical samples, such as Zika. The approach can help small sequencing
centers around the globe conduct disease surveillance more efficiently
and cost-effectively, which can provide crucial information for
controlling outbreaks.
The new study was led by MIT graduate student Hayden Metsky and postdoctoral researcher Katie Siddle, and it appears online in Nature Biotechnology.
"As genomic sequencing becomes a critical part of disease
surveillance, tools like CATCH will help us and others detect outbreaks
earlier and generate more data on pathogens that can be shared with the
wider scientific and medical research communities," said Christian
Matranga, a co-senior author of the new study who has joined a local
biotech startup.
Scientists have been able to detect some low-abundance viruses by
analyzing all the genetic material in a clinical sample, a technique
known as "metagenomic" sequencing, but the approach often misses viral
material that gets lost in the abundance of other microbes and the
patient's own DNA.
Another approach is to "enrich" clinical samples for a particular
virus. To do this, researchers use a kind of genetic "bait" to
immobilize the target virus's genetic material, so that other genetic
material can be washed away. Scientists in the Sabeti lab had
successfully used baits, which are molecular probes made of short
strands of RNA or DNA that pair with bits of viral DNA in the sample, to
analyze the Ebola and Lassa virus genomes. However, the probes were
always directed at a single microbe, meaning they had to know exactly
what they were looking for, and they were not designed in a rigorous,
efficient way.
What they needed was a computational method for designing probes that
could provide a comprehensive view of the diverse microbial content in
clinical samples, while enriching for low-abundance microbes like Zika.
"We wanted to rethink how we were actually designing the probes to do
capture," said Metsky. "We realized that we could capture viruses,
including their known diversity, with fewer probes than we'd used
before. To make this an effective tool for surveillance, we then decided
to try targeting about 20 viruses at a time, and we eventually scaled
up to the 356 viral species known to infect humans."
Short for "Compact Aggregation of Targets for Comprehensive
Hybridization," CATCH allows users to design custom sets of probes to
capture genetic material of any combination of microbial species,
including viruses or even all forms of all viruses known to infect
humans.
To run CATCH truly comprehensively, users can easily input genomes
from all forms of all human viruses that have been uploaded to the
National Center for Biotechnology Information's GenBank sequence
database. The program determines the best set of probes based on what
the user wants to recover, whether that's all viruses or only a subset.
The list of probe sequences can be sent to one of a few companies that
synthesize probes for research. Scientists and clinical researchers
looking to detect and study the microbes can then use the probes like
fishing hooks to catch desired microbial DNA for sequencing, thereby
enriching the samples for the microbe of interest.
Tests of probe sets designed with CATCH showed that after enrichment,
viral content made up 18 times more of the sequencing data than before
enrichment, allowing the team to assemble genomes that could not be
generated from un-enriched samples. They validated the method by
examining 30 samples with known content spanning eight viruses. The
researchers also showed that samples of Lassa virus from the 2018 Lassa
outbreak in Nigeria that proved difficult to sequence without enrichment
could be "rescued" by using a set of CATCH-designed probes against all
human viruses. In addition, the team was able to improve viral detection
in samples with unknown content from patients and mosquitos.
Using CATCH, Metsky and colleagues generated a subset of viral probes
directed at Zika and chikungunya, another mosquito-borne virus found in
the same geographic regions. Along with Zika genomes generated with
other methods, the data they generated using CATCH-designed probes
helped them discover that the Zika virus had been introduced in several
regions months before scientists were able to detect it, a finding that
can inform efforts to control future outbreaks.
To demonstrate other potential applications of CATCH, Siddle used
samples from a range of different viruses. Siddle and others have been
working with scientists in West Africa, where viral outbreaks and
hard-to-diagnose fevers are common, to establish laboratories and
workflows for analyzing pathogen genomes on-site. "We'd like our
partners in Nigeria to be able to efficiently perform metagenomic
sequencing from diverse samples, and CATCH helps them boost the
sensitivity for these pathogens," said Siddle.
The method is also a powerful way to investigate undiagnosed fevers
with a suspected viral cause. "We're excited about the potential to use
metagenomic sequencing to shed light on those cases and, in particular,
the possibility of doing so locally in affected countries," said Siddle.
One advantage of the CATCH method is its adaptability. As new
mutations are identified and new sequences are added to GenBank, users
can quickly redesign a set of probes with up-to-date information. In
addition, while most probe designs are proprietary, Metsky and Siddle
have made publicly available all of the ones they designed with CATCH.
Users have access to the actual probe sequences in CATCH, allowing
researchers to explore and customize the probe designs before they are
synthesized.
Sabeti and fellow researchers are excited about the potential for
CATCH to improve large-scale high-resolution studies of microbial
communities. They are also hopeful that the method could one day have
utility in diagnostic applications, in which results are returned to
patients to make clinical decisions. For now, they're encouraged by its
potential to improve genomic surveillance of viral outbreaks like Zika
and Lassa, and other applications requiring a comprehensive view of
low-level microbial content.
The CATCH software is publicly accessible on GitHub. Its development
and validation, supervised by Sabeti and Matranga, is described online
in Nature Biotechnology.
- Hayden C. Metsky, Katherine J. Siddle, Adrianne Gladden-Young, James Qu, David K. Yang, Patrick Brehio, Andrew Goldfarb, Anne Piantadosi, Shirlee Wohl, Amber Carter, Aaron E. Lin, Kayla G. Barnes, Damien C. Tully, Bjӧrn Corleis, Scott Hennigan, Giselle Barbosa-Lima, Yasmine R. Vieira, Lauren M. Paul, Amanda L. Tan, Kimberly F. Garcia, Leda A. Parham, Ikponmwosa Odia, Philomena Eromon, Onikepe A. Folarin, Augustine Goba, Etienne Simon-Lorière, Lisa Hensley, Angel Balmaseda, Eva Harris, Douglas S. Kwon, Todd M. Allen, Jonathan A. Runstadler, Sandra Smole, Fernando A. Bozza, Thiago M. L. Souza, Sharon Isern, Scott F. Michael, Ivette Lorenzana, Lee Gehrke, Irene Bosch, Gregory Ebel, Donald S. Grant, Christian T. Happi, Daniel J. Park, Andreas Gnirke, Pardis C. Sabeti, Christian B. Matranga. Capturing sequence diversity in metagenomes with comprehensive and scalable probe design. Nature Biotechnology, 2019; 37 (2): 160 DOI: 10.1038/s41587-018-0006-x
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