Jeffrey S. Buguliskis Ph.D. Technical Editor Genetic Engineering & Biotechnology News
Maximum Depth Sequencing Has the Potential to Be Applied To Human Cell Populations for Detecting Extremely Rare Mutations
As the precision medicine train continues to gather steam, building up speed to push itself down the clinical rails toward the prospect of actual individual therapies, genomics is the coal that fuels the mighty endeavor. Yet, fuel is only as good as the engine that converts the raw material into a usable form. For precision medicine, next-generation sequencing (NGS) is that finely tuned Formula 1 motor that rapidly and efficiently converts a genomic milieu into useable power for scientific research. This advanced sequencing technique has dramatically altered the field of genomic medicine in the past several years, allowing researchers to plumb the true depths of the human genome and rapidly apply the knowledge to drug discovery and disease treatment.
However, for all the power and speed NGS possesses, the technology is not without its limitations. To achieve high-throughput rates, NGS platforms break genomic sequences down into short read lengths (30 to 400 base pairs), which makes it difficult to reassemble the fragments in the proper order, given there is only a four-letter alphabet for the genetic code.
For instance, imagine if you had 100 copies of the Door’s 1967 debut album and, in a moment of temporary insanity, you decide to throw them all into a giant blender (will it blend?) and hit frappe. After the grinding stops, and you come out of your mad state, you realize there is a way to reassemble the tiny pieces and make the albums complete again, although you quickly surmise that if the pieces of the album were larger you would be able to play longer segments of the songs and tell which snippet went where. The smaller segments only allow you to hear a quick bit of instrument, a momentary blurb of vocals, or possibly only a single note—making the assembly profoundly more challenging and prone to errors.
The record shredding analogy underscores an inherent weaknesses of NGS technology, that scientists and platform manufacturers are continually seeking to improve in order to increase read lengths on their sequencers. However, another inborn problem of NGS lies within an integral portion of most advanced sequencing modalities: nucleotide amplification by PCR. High-fidelity polymerases that are most often used to construct NGS libraries introduce errors in roughly four bases out of a million. Though that may seem like an insignificant amount, when searching the genome for single nucleotide polymorphisms (SNPs)—a variant of one DNA base between sequences—the PCR-introduced errors can become extremely problematic.
Investigators like Evgeny Nudler, Ph.D., professor of biochemistry at New York University School of Medicine, whose laboratory focuses on bacterial evolution, adaptation, and development
of antibiotic resistance, are keenly aware of the difficulties studying de novo mutations in microbial species using high-throughput sequencing techniques. E. coli produce 1,000 fold fewer errors in their DNA (1 in 109 bases) than the DNA polymerases used for amplification. Combined with the fact that various NGS platforms can misread approximately 1 in 1,000 bases, Nudler, and his colleagues realized they needed to devise a new technique with enough accuracy if they hoped to reveal how bacteria use rapid evolution to defeat antibiotics.
“The initial motivation to develop (a new) technique was to measure the mutational rate directly in bacteria,” Dr. Nudler told Clinical OMICS. “We are a microbiology lab, and we wanted to understand the fundamental questions of the rate of mutation and the mechanism of bacterial mutations, but all of the traditional approaches to address these questions they required selection in order to see the mutations—like a marker.”
Nudler continued, saying “but these approaches ignore a large number of variants and only allow you to focus on one subset of mutations. Researchers have been searching for decades for an unbiased method to measure the mutation rate.”
Nudler and his team developed a method—dubbed Maximum Depth Sequencing (MDS)— that eliminates the error introduced by core methods behind current high-speed sequencing platforms, to catch genetic changes so rare that older methods could not tell them apart from machine error. The researchers published their findings recently in Nature through an article entitled “Rates and mechanisms of bacterial mutagenesis from maximum-depth sequencing.”
“We were able to measure directly, for the first time, both the standard change rate in DNA sequences across a bacterial genetic code, and the “hotspots” where bugs turn on genetic change many times faster than average to render antibiotics obsolete,” explained Nudler, who is the senior author on the current study. “Beyond antibiotic resistance, the technology may soon give us the ability to find extremely rare genetic changes in any cell population, including cells in the bloodstream poised to become cancerous, and long before they seed tumors.”
For a typical NGS run, DNA chains are broken into pieces so the fragments can be copied with DNA polymerase while subsequently adding in a genetic bar code—a tag that uniquely identifies each original DNA fragment. The sequencers then make a huge number of copies of each copy, until the fluorescent probes that identify each DNA base can be detected by the sequencer. Unfortunately for this method, any error that was introduced during the initial replication step would be amplified into all ensuing copies—providing no means to tell introduced errors apart from naturally occurring variants in an organism’s genomic background.
Nudler and his colleagues decided to take a different approach to amplifying the DNA for sequencing. The researchers added bar codes onto the ends of the initial DNA fragments and then made numerous, independent copies of those barcoded strands. This new process limits the amount of errors introduced by polymerases or sequencing to showing up in only a small number of the sequences generated and typically not all in the same place. Now, rather than sequence the entire genome, researchers can home in on specific regions of interest (ROIs) to search for extremely rare variants, sequencing each original fragment multiple times in a single run.
“The results we obtained from this method were quite interesting,” Nudler remarked to Clinical OMICs. “We see for the first time things people haven’t seen in bacteria,” referring to the continuous back and forth between continual damage done to DNA strands and the rapid, and in some cases unknown, mechanisms of DNA repair employed by the cells to maintain genomic fidelity.
Putting their new methodology to the test, the research team was able to identify enough mutations to accurately calculate—for the first time—the standard, ongoing mutation rate in E. coli. Empowered with this knowledge, the scientists were able to uncover that exposure to certain antibiotics led to a 10-fold increase above average in mutations for specific regions of the E. coli genome.
Specifically, Nudler and his team found that sublethal doses of ampicillin and norfloxacin downregulated the DNA mismatch repair—a post-replicative repair pathway common among most organisms that, when functioning normally, increases genomic integrity by 1,000-fold. The researchers surmised that increases in oxidative stress brought on by antibiotic exposure enabled bacteria to alter their genetic code more quickly—ultimately leading to the microbes evolving around treatments.
“We would never have seen these processes, but can now hope to harness them to take away a fundamental mechanism used by bacteria to acquire resistance,” stated Nudler.
It’s Good for What Ails Ya
Outside of understanding how bacterial evolution can direct some microbes down the path of antibiotic resistance, MDS has the potential to be applied to human cell populations for detecting extremely rare mutations, especially those involved in disease pathogenesis. Furthermore, Nudler told Clinical OMICs that his newly conceived methodology could be utilized to not only identify precancerous mutations long before problematic tumors form, he felt that MDS could be easily combined with simple blood tests to track patients’ progress during and after chemotherapy regimens—as is often done for new molecular diagnostic techniques like liquid biopsy.
Additionally, as other molecular techniques advance, they have the potential to be applied to MDS for improving the method. Molecular biologists have set the life sciences field ablaze with the multitude of uses—both research and clinical—they have found for genome editing tools. It would seem that MDS is no exception as Nudler noted “we already know how to improve the technology. Instead of using restriction enzymes to cut near the ROI [before PCR amplification] we can use CRISPR to 'cut' anywhere in the genome.” He believes this could be a rapid way to incorporate MDS clinically.
As next generation sequence platforms improve, via the work of research teams like the one headed by Nudler, and continue to transition from pure laboratory research tools to commonly employed clinical diagnostic methods, we can expect to see an array of novel approaches that attempt to tackle the challenging and outstanding questions surrounding the onset of disease.