Molecular probes designed to spot minute amounts of pathogens in biological samples may aid clinical laboratories’ speed-to-answer
Driven to find a better way to isolate minute samples of pathogens from among high-volumes of other biological organisms, researchers at Canada’s McMaster University in Hamilton, Ontario, have unveiled a bioinformatics algorithm which they claim shortens time-to-answer and speeds diagnosis of deadly diseases.
Two disease pathogens the researchers specifically targeted in their study are responsible for sepsis and SARS-CoV-2, the coronavirus causing COVID-19. Clinical laboratories would welcome a technology which both shortens time-to-answer and improves diagnostic accuracy, particularly for pathogens such as sepsis and SARS-CoV-2.
Their design of molecular probes that target the genomic sequences of specific pathogens can enable diagnosticians and clinical laboratories to spot extremely small amounts of viral and bacterial pathogens in patients’ biological samples, as well as in the environment and wildlife.
“There are thousands of bacterial pathogens and being able to determine which one is present in a patient’s blood sample could lead to the correct treatment faster when time is very important,” Zachery Dickson, a lead author of the study, told Brighter World. Dickson is a bioinformatics PhD candidate in the Department of Biology at McMaster University. “The probe makes identification much faster, meaning we could potentially save people who might otherwise die,” he added.
Sepsis is a life-threatening response to infection that leads to organ failure, tissue damage, and death in hospitals worldwide. According to Sepsis Alliance, about 30% of people diagnosed with severe sepsis will die without quick and proper treatment. Thus, a “shortcut” to identifying sepsis in its early stages may well save many lives, the McMaster researchers noted.
And COVID-19 has killed millions. Such a tool that identifies sepsis and SARS-CoV-2 in minute biological samples would be a boon to hospital medical laboratories worldwide.
“We currently need faster, cheaper, and more succinct ways to detect pathogens in human and environmental samples that democratize the hunt, and this pipeline does exactly that,” Hendrik Poinar, PhD (above), McMaster Professor of Anthropology and a lead author of the study, told Brighter World. Poinar is Director of the McMaster University Ancient DNA Center. Hospital medical laboratories could help save many lives if sepsis and COVID-19 could be detected earlier. (Graphic copyright: McMaster University.)
Is Bioinformatics ‘Shortcut’ Faster than PCR Testing?
The researchers say their probes enable a shortcut to detection—even in an infection’s early stages—by “targeting, isolating, and identifying the DNA sequences specifically and simultaneously.”
The probes’ design makes possible simultaneous targeted capture of diverse metagenomics targets, Biocompare explained.
But is it faster than PCR (polymerase chain reaction) testing?
The McMaster scientists were motivated by the “challenges of low signal, high background, and uncertain targets that plague many metagenomic sequencing efforts,” they noted in their paper.
They pointed to challenges posed by PCR testing, a popular technique used for detection of sepsis pathogens as well as, more recently, for SARS-CoV-2, the coronavirus causing COVID-19.
“The (PCR) technique relies on primers that bind to nucleic acid sequences specific to an organism or group of organisms. Although capable of sensitive, rapid detection and quantification of a particular target, PCR is limited when multiple loci are targeted by primers,” the researchers wrote in Cell Reports Methods.
According to LabMedica, “A wide array of metagenomic study efforts are hampered by the same challenge: low concentrations of targets of interest combined with overwhelming amounts of background signal. Although PCR or naive DNA capture can be used when there are a small number of organisms of interest, design challenges become untenable for large numbers of targets.”
Detecting Pathogens Faster, Cheaper, and More Accurately
As part of their study, researchers tested two probe sets:
one to target bacterial pathogens linked to sepsis, and
another to detect coronaviruses including SARS-CoV-2.
They were successful in using the probes to capture a variety of pathogens linked to sepsis and SARS-CoV-2.
“We validated HUBDesign by generating probe sets targeting the breadth of coronavirus diversity, as well as a suite of bacterial pathogens often underlying sepsis. In separate experiments demonstrating significant, simultaneous enrichment, we captured SARS-CoV-2 and HCoV-NL63 [Human coronavirus NL 63] in a human RNA background and seven bacterial strains in human blood. HUBDesign has broad applicability wherever there are multiple organisms of interest,” the researchers wrote in Cell Reports Methods.
The findings also have implications to the environment and wildlife, the researchers noted.
Of course, more research is needed to validate the tool’s usefulness in medical diagnostics. The McMaster University researchers intend to improve HUBDesign’s efficiency but note that probes cannot be designed for unknown targets.
Nevertheless, the advanced application of novel technologies to diagnose of sepsis, which causes 250,000 deaths in the US each year, according to the federal Centers for Disease Control and Prevention, is a positive development worth watching.
The McMaster scientists’ discoveries—confirmed by future research and clinical studies—could go a long way toward ending the dire effects of sepsis as well as COVID-19. That would be a welcome development, particularly for hospital-based laboratories.
Even more impressive is that the automated testing lab can reportedly process (with results in four hours) up to 3,000 patient samples daily for SARS-CoV-2, the coronavirus that causes the COVID-19 illness.
“All of our laboratories do PCR every day. But for this test we need to go above and beyond to ensure accurate detection,” said Jennifer Doudna, PhD, IGI Executive Director and UC Berkeley Professor of Molecular and Cell Biology, in an IGA news release.
“We put in place a robotic pipeline for doing thousands of tests per day,” she continued, “with a pipeline for managing the data and getting it back to clinicians. Imagine setting that up in a couple of weeks. It’s really extraordinary and something I’ve never seen in my career.”
Robert Sanders, UC Berkeley’s Manager Science Communications, told Dark Daily the COVID-19 lab performs about 180 tests per day and has tested 1,000 people so far—80% of the samples came from the campus community. About 1.5% to 4% of the tests were found to be positive for the SARS-CoV-2 coronavirus among the groups tested.
“We hope other academic institutions will set up testing labs too,” he said.
How Did Berkeley Set Up a COVID-19 Diagnostic Lab So Fast?
To get up and running quickly, university officials drew from the campus and surrounding business community to equip and operate the laboratory, as well as, train researchers to do clinical analysis of patient samples.
Though the methodology to test for the coronavirus—isolating RNA from a biological sample and amplifying it with PCR—is standard fare in most research labs worldwide, including at UC Berkeley, the campus’ research labs were shuttered due to the spread of the coronavirus.
IGI reached out to the idle labs for their high-throughput PCR systems to start-up the lab. Through its partnership with University Health Services and local and national companies, IGI created an automated sample intake and processing workflow.
Additionally, several research scientists who were under government-mandated stay-at-home orders made themselves available. “My own research is shut down—and there’s not very much I can do other than stay in my home … finally I’m useful,” said PhD candidate Holly Gildea in a Berkeleyside article which noted that about 30 people—mostly doctoral students and postdoctoral researchers—are being trained to oversee the process and monitor the automated equipment.
Postdoctoral fellows Jenny Hamilton (left) and Enrique Shao (right) with an automated liquid-handling robot (Hamilton Microlab STAR), which will be used to analyze swabs from patients to diagnose COVID-19. Hamilton and Shao volunteered to train to become CLIA certified so as to process patient samples. When analyzing real samples from patients, they would be wearing full personal protective equipment (PPE), including mask, face shield, gown and gloves. (Photo and caption copyright: Max and Jules Photography/UC Berkeley.)
Federal and State Authorities Remove Hurdles
In her article, “Blueprint for a Pop-up SARS-CoV-2 Testing Lab,” published on the medRxiv servers, Doudna summarized “three regulatory developments [that] allowed the IGI to rapidly transition its research laboratory space into a clinical testing facility.
“The second was California Governor Newsom’s Executive Order N-25-20, which modified the requirements for clinical laboratory personnel running diagnostic tests for SARS-CoV-2 in a certified laboratory.
“The third was increased flexibility and expediency at the state and federal levels for certification and licensure requirements for clinical laboratory facilities under the Clinical Laboratory Improvement Amendments (CLIA) program. Under these emergency conditions, the California Department of Public Health (CDPH) was willing to temporarily extend—once the appropriate regulatory requirements have been fulfilled—an existing CLIA certificate for high-complexity testing to a non-contiguous building on our university campus.”
“These developments,” wrote Doudna, “enabled us to develop and validate a laboratory-developed test (LDT) for SARS-CoV-2, extend the UC Berkeley Student Health Center’s clinical laboratory license to our laboratory space, and begin testing patient samples.”
Lessons Learned Implementing a Pop-Up COVID-19 Testing Laboratory
“Our procedures for implementing the technical, regulatory, and data management workstreams necessary for clinical sample processing provide a roadmap to others in setting up similar testing centers,” she wrote.
Learned strategies Doudna says could aid other academic research labs transform to a “SARS-CoV-2 Diagnostic Testing Laboratory include:
Leveraging licenses from existing CLIA-certified labs;
Following FDA authorized testing procedures;
Using online HIPAA training;
Managing supply chain “bottlenecks” by using donated equipment;
Adopting in-house sample barcoding;
Adapting materials, such as sampling tubes, to work with donated equipment;
Cost of equipment and supplies (not including staff) was $550,000, with a per test cost of $24, Doudna noted.
“As the COVID-19 pandemic continues, our intention is to provide both PCR-based diagnostic testing and to advance research on asymptomatic transmission, analyze virus sequence evolution, and provide benchmarking for new diagnostic technologies,” she added.
Medical laboratory leaders understand that the divide between clinical and research laboratories is not easy to surmount. Nevertheless, UC Berkley’s IGI pulled it off. The lab marshaled resources as it took on the novel coronavirus, quickly developed and validated a test workflow, and assembled and trained staff to analyze tests with fast TAT to providers, students, and area residents. There’s much that can be learned from UC Berkeley IGI’s accomplishments.
‘Prime editing’ is what researchers are calling the proof-of-concept research that promises improved diagnostics and more effective treatments for patients with genetic defects
Known as Prime Editing, the scientists developed this technique as a more accurate way to edit Deoxyribonucleic acid (DNA). In a paper published in Nature, the authors claim prime editing has the potential to correct up to 89% of disease-causing genetic variations. They also claim prime editing is more powerful, precise, and flexible than CRISPR.
The research paper describes prime editing as a “versatile and precise genome editing method that directly writes new genetic information into a specified DNA site using a catalytically impaired Cas9endonuclease fused to an engineered reverse transcriptase, programmed with a prime editing guide RNA (pegRNA) that both specifies the target site and encodes the desired edit.”
And a Harvard Gazette article states, “Prime editing differs from previous genome-editing systems in that it uses RNA to direct the insertion of new DNA sequences in human cells.”
Assuming further research and clinical studies confirm the
viability of this technology, clinical laboratories would have a new diagnostic
service line that could become a significant proportion of a lab’s specimen
volume and test mix.
In that e-briefing we wrote that Liu “has led a team of scientists in the development of a gene-editing protein delivery system that uses cationic lipids and works on animal and human cells. The new delivery method is as effective as protein delivery via DNA and has significantly higher specificity. If developed, this technology could open the door to routine use of genome analysis, worked up by the clinical laboratory, as one element in therapeutic decision-making.”
Now, Liu has taken that development even further.
“A major aspiration in the molecular life sciences is the ability to precisely make any change to the genome in any location. We think prime editing brings us closer to that goal,” David Liu, PhD (above), Director of the Merkin Institute of Transformative Technologies in Healthcare at the Broad Institute, told The Harvard Gazette. “We’re not aware of another editing technology in mammalian cells that offers this level of versatility and precision with so few byproducts.” (Photo copyright: Broad Institute.)
Cell Division Not Necessary
CRISPR stands for Clustered Regularly Interspaced Short Palindromic Repeats. It is considered the most advanced gene editing technology available. However, it has one drawback not found in Prime Editing—CRISPR relies on a cell’s ability to divide to generate desired alterations in DNA—prime editing does not.
This means prime editing could be used to repair genetic mutations in cells that do not always divide, such as cells in the human nervous system. Another advantage of prime editing is that it does not cut both strands of the DNA double helix. This lowers the risk of making unintended, potentially dangerous changes to a patient’s DNA.
The researchers claim prime editing can eradicate long lengths of disease-causing DNA and insert curative DNA to repair dangerous mutations. These feats, they say, can be accomplished without triggering genome responses introduced by other forms of CRISPR that may be potentially harmful.
“Prime editors are more like word processors capable of
searching for targeted DNA sequences and precisely replacing them with edited
DNA strands,” Liu told NPR.
The scientists involved in the study have used prime editing to perform over 175 edits in human cells. In the test lab, they have succeeded in repairing genetic mutations that cause both Sickle Cell Anemia (SCA) and Tay-Sachs disease, NPR reported.
“Prime editing is really a step—and potentially a significant step—towards this long-term aspiration of the field in which we are trying to be able to make just about any kind of DNA change that anyone wants at just about any site in the human genome,” Liu told News Medical.
Additional Research Required, but Results are Promising
Prime editing is very new and warrants further
investigation. The researchers plan to continue their work on the technology by
performing additional testing and exploring delivery mechanisms that could lead
to human therapeutic applications.
“Prime editing should be tested and optimized in as many cell types as researchers are interested in editing. Our initial study showed prime editing in four human cancer cell lines, as well as in post-mitotic primary mouse cortical neurons,” Liu told STAT. “The efficiency of prime editing varied quite a bit across these cell types, so illuminating the cell-type and cell-state determinants of prime editing outcomes is one focus of our current efforts.”
Although further research and clinical studies are needed to
confirm the viability of prime editing, clinical laboratories could benefit
from this technology. It’s worth watching.
Using animal blood, the researchers hope to improve the accuracy of AI driven diagnostic technology
What does a cheetah, a tortoise, and a Humboldt penguin have
in common? They are zoo animals helping scientists at Saarland University in
Saarbrücken, Germany, find biomarkers that can help computer-assisted diagnoses
of diseases in humans at early stages. And they are not the only animals
lending a paw or claw.
In their initial research, the scientists used blood samples
that had been collected during routine examinations of 21 zoo animals between
2016 and 2018, said a news
release. The team of bioinformatics
and human genetics experts
worked with German zoos Saarbrücken and Neunkircher for the study. The project
progresses, and thus far, they’ve studied the blood of 40 zoo animals, the
release states.
This research work may eventually add useful biomarkers and
assays that clinical
laboratories can use to support physicians as they diagnose patients,
select appropriate therapies, and monitor the progress of their patients. As medical
laboratory scientists know, for many decades, the animal kingdom has been
the source of useful insights and biological materials that have been
incorporated into laboratory assays.
“Measuring the molecular blood profiles of animals has never
been done before this way,” said Andreas
Keller, PhD, Saarland University Bioinformatics Professor and Chair for
Clinical Bioinformatics, in the news release. The Saarland researchers published
their findings in Nucleic Acids
Research, an Oxford
Academic journal.
“Studies on sncRNAs [small non-coding RNAs] are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500 pg of RNA from 21 animals at two German zoological gardens,” the article states.
Can Animals Improve the Accuracy of AI to Detect Disease
in Humans?
However, the researchers perceived an inability for AI and machine learning to
discern real biomarker patterns from those that just seemed to fit.
“The machine learning methods recognize the typical
patterns, for example for a lung tumor or Alzheimer’s disease. However, it is
difficult for artificial intelligence to learn which biomarker patterns are
real and which only seem to fit the respective clinical picture. This is where
the blood samples of the animals come into play,” Keller states in the news
release.
“If a biomarker is evolutionarily conserved, i.e. also
occurs in other species in similar form and function, it is much more likely
that it is a resilient biomarker,” Keller explained. “The new findings are now
being incorporated into our computer models and will help us to identify the
correct biomarkers even more precisely in the future.”
Andreas Keller, PhD (left), and zoo director Richard Francke (right), hold a pair of radiated tortoises that participated in the Saarland University study. (Photo copyright: Oliver Dietze/Saarland University.)
“Because blood can be obtained in a standardized manner and
miRNA expression patterns are technically very stable, it is easy to accurately
compare expression between different animal species. In particular, dried blood
spots or microsampling devices appear to be well suited as containers for
miRNAs,” the researchers wrote in Nucleic Acids Research.
Animal species that participated in the study include:
Additionally, human volunteers contributed blood specimens
for a total of 19 species studied. The scientists reported success in capturing
data from all of the species. They are integrating the information into their
computer models and have developed a public database of their
findings for future research.
“With our study, we provide a large collection of small RNA
NGS expression data of species that have not been analyzed before in great
detail. We created a comprehensive publicly available online resource for
researchers in the field to facilitate the assessment of evolutionarily
conserved small RNA sequences,” the researchers wrote in their paper.
Clinical Laboratory Research and Zoos: A Future
Partnership?
This novel involvement of zoo animals in research aimed at improving
the ability of AI driven diagnostics to isolate and identify human disease is
notable and worth watching. It is obviously pioneering work and needs much
additional research. At the same time, these findings give evidence that there
is useful information to be extracted from a wide range of unlikely sources—in
this case, zoo animals.
Also, the use of artificial intelligence to search for
useful patterns in the data is a notable part of what these researchers
discovered. It is also notable that this research is focused on sequencing DNA
and RNA of the animals involved with the goal of identifying sequences that are
common across several species, thus demonstrating the common, important
functions they serve.
In coming years, those clinical laboratories doing genetic
testing in support of patient care may be incorporating some of this research
group’s findings into their interpretation of certain gene sequences.
According to the researchers, the finding could reveal athletes who removed their blood, took out the red blood cells, and transfused the cells into their bodies before competition. When conducted by medical laboratory professionals, such autologous blood therapies can enhance oxygen intake and increase performance during sports. However, these “self-transfusions” have been difficult to detect using current methods and that highlights the importance of ensuring these procedures are carried out by authorized healthcare facilities.
The World Anti-Doping Agency (WADA), an international organization aimed at research and education for doping-free sport, funded the Duke University research. WADA currently uses the Athlete Biological Passport to assess, over time, competitors’ body chemistries.
As the Duke researchers explored nucleic acids in red blood cells, they found that the cells actually do have a nucleus, contrary to popular belief. From there, they honed in on RNA.
Short RNA pieces, called microRNA (miRNA), control production of proteins in a cell, according to the researchers.
“While once thought to lack nucleic acids, red blood cells actually contain diverse and abundant RNA species,” the scientists noted in their paper. “In addition, proteomic analyses of red blood cells have identified the presence of Argonaute 2 (AGO2), supporting the regulatory function of miRNAs.”
The methodology Duke researchers followed involved these steps, among others:
Three units of blood were drawn from volunteers;
The researchers removed the white blood cells and about 80% of the plasma;
The remaining red blood cells were pure, just as they would need to be by someone doing autologous transfusion;
The researchers analyzed cell RNA samples at specific daily intervals: 1, 3, 7, 10, 14, 28, 36, and, 42 days;
They then compared samples to day 1 and recorded changes in RNA due to storage.
The researchers found:
Two types of miRNA increased during storage and two declined; and,
miR-720 had the most dramatic and consistent changes.
They concluded that finding increased miR-720 in athletes’ blood could be used as a biomarker for detecting stored red blood cells, which could indicate blood doping had taken place.
“The difficulty has been that the tests [WADA] have couldn’t tell the difference between a young blood cell and an old one,” Jen-Tsan Ashley Chi, MD, PhD, lead researcher on the study and Duke’s Associate Professor in Molecular Genetics and Microbiology, noted in the news release. “This increase in miR-720 is significant enough and consistent enough that it could be used as a biomarker for detecting stored red blood cells.” Chi is affiliated with Duke’s Center for Genomic and Computational Biology. (Photo copyright: Duke University.)
Implications for Detecting Blood Doping
How does this help clinical laboratories detect blood doping in athletes?
The researchers explained that RNA changes were, indeed, tell-tale signs of old blood cells circulating with normal cells. Those old blood cells could identify an athlete who did a self-transfusion of their blood before a competition.
However, before the test is used in sports more research is needed. Activity by the enzyme angiogenin in stored cells also is worthy of more exploration, as is its role in breaking apart larger RNA, the researchers noted.
“While autologous blood transfusions in athletes is very difficult to identify using conventional tests, it may be detectable based on the presence of red blood cells with levels of miR-720 significantly higher than the normal circulating cells. Further investigations will be necessary to identify the signals during red blood cell storage that stimulate angiogenin activation,” the study paper concluded.
Clinical Laboratories Involved in Sports Testing
In its 2017 Anti-Doping Testing Figures Report, WADA reported 322,050 samples were analyzed, a 7.1% increase from 300,565 samples in 2016. WADA accredits medical laboratories worldwide for conducting such analyses according to the organization’s code. This presents opportunities in sports medicine for medical laboratories to increase revenue through a new line of diagnostic tests.
The Duke study exemplifies how clinical laboratories can extend their services beyond patient care and enter a new realm of leveling playing fields worldwide.
