Single genetic test can identify multiple pathogens and can be used by the UCSF clinical laboratory team to help physicians identify difficult to diagnose diseases
Continuing improvements in gene sequencing technologies and analytical software tools are enabling clinical laboratorians to diagnosis patients who have challenging symptoms. One such example is a new genomic test developed by researchers at University California, San Francisco (UCSF). The single test analyzes both RNA and DNA to detect almost any type of pathogen that may be the cause of specific illnesses.
The test uses a genomic sequencing technique known as metagenomics next-generation sequencing (mNGS). It works by sequencing genetic material found in blood, tissue, or body fluid samples and compares the sequenced data against a broad database of known pathogens to seek a match. Instead of looking for just one pathogen at a time, mNGS analyzes all of the nucleic acids, RNA, and DNA present in a sample simultaneously to detect nearly all pathogens, including viruses, bacteria, fungi, and parasites.
The mNGS test is not intended to replace existing clinical laboratory tests, but to help physicians diagnose an illness in cases where patients are experiencing severe symptoms, and where initial, commonplace tests are ineffective. In such cases, medical professionals require additional information to achieve a proper diagnosis.
“Our technology is deceptively simple,” said Charles Chiu, MD, PhD (above), professor of laboratory medicine and infectious diseases at UCSF and senior author of the studies in a news release. “By replacing multiple tests with a single test, we can take the lengthy guesswork out of diagnosing and treating infections.” The new technology may help physicians diagnose patients who have challenging symptoms and where current clinical laboratory testing is ineffective at identifying specific pathogens. (Photo copyright: University California San Francisco.)
Diagnostic Armamentarium for Physicians
According to an article published by the American Society for Microbiology (ASM) titled, “Metagenomic Next Generation Sequencing: How Does It Work and Is It Coming to Your Clinical Microbiology Lab?” mNGS is “running all nucleic acids in a sample, which may contain mixed populations of microorganisms, and assigning these to their reference genomes to understand which microbes are present and in what proportions. The ability to sequence and identify nucleic acids from multiple different taxa [plural for taxon] for metagenomic analysis makes this a powerful new platform that can simultaneously identify genetic material from entirely different kingdoms of organisms.”
The researchers developed the mNGS test years ago and it has produced promising results, including:
Diagnosing cases of encephalitis in transplant recipients to yellow fever in their organ donors.
Helping to identify the cause of a meningitis outbreak in Mexico among surgical patients.
Detecting a case of leptospirosis in a patient who was in a medically induced coma, which prompted doctors to prescribe penicillin and resulted in the full recovery of the patient.
Identifying the cause of neurological infections such as meningitis and encephalitis. The test successfully diagnosed 86% of neurological infections in more than 4,800 spinal fluid samples.
“Our mNGS test performs better than any other category of test for neurologic infections,” said Charles Chiu, MD, PhD, professor of laboratory medicine and infectious diseases at UCSF and senior author of the two studies, in a UCSF news release. “The results support its use as a critical part of the diagnostic armamentarium for physicians who are working up patients with infectious diseases.”
FDA Breakthrough Device Designation
The UCSF test has not yet been approved by the federal Food and Drug Administration (FDA), but it was granted a “breakthrough device” designation by the agency. This classification authorizes labs to use the test as a valid diagnosis method due to its potential ability to benefit patients.
Chiu told NBC News that the test costs about $3,000 per sample and fewer than 10 labs routinely use it due to several issues.
“Traditionally, it’s been used as a test of last resort, but that’s primarily because of issues involving, for instance, the cost of the test, the fact that it’s only available in specialized reference laboratories, and it also is quite laborious to run,” he said.
This type of lab testing is not feasible for most hospitals as it is costly and complicated, and because physicians may need assistance from clinical laboratory personnel who have the appropriate expertise to properly read test results.
“This just is not something that a clinical lab will be doing until somebody commercially puts it in a box with an easy button,” Susan Butler-Wu, PhD, associate professor of clinical pathology at the University of Southern California (USC), told NBC News. “It’s not a one-stop shop. It just can be helpful as an additional tool.”
Although the technology has some limitations, Chiu says the research performed by his team “raises the possibility that we perhaps should be considering running this test earlier” in symptomatic patients. He hopes the test will be used on a widespread basis in hospitals to diagnose various illnesses in the future.
“We need to get the cost down and we need to get the turnaround times down as well,” he told NBC.
Definitive Tool for Pathogen Detection
To increase access to the technology, Chiu and his colleagues founded Delve Bio, which is now the exclusive provider of the mNGS tool created at UCSF. In December, the company announced the commercial launch of Delve Detect, a metagenomic test for infectious diseases. According to its website, Delve Detect “offers genomic testing of cerebrospinal fluid (CSF) for more than 68,000 pathogens, with 48-hour turnaround time and metagenomics experts readily available to discuss results.”
“These findings support including mNGS as a core tool in the clinical workup for CNS [central nervous system] infections,” said Steve Miller, MD, PhD, UCSF volunteer clinical professor, laboratory medicine, and chief medical officer of Delve Bio in the UCSF news release. “mNGS offers the single most unbiased, complete and definitive tool for pathogen detection. Thanks to its ability to quickly diagnose an infection, mNGS helps guide management decisions and treatment for patients with meningitis and encephalitis, potentially reducing healthcare costs down the line.”
This mNGS test may prove to have the potential to greatly improve medical care for some infections and possibly expedite the detection of new viral threats. It is probable that clinical laboratories will soon be learning about and performing more tests of this nature in the future.
Although it is a non-specific procedure that does not identify specific health conditions, it could lead to new biomarkers that clinical laboratories could use for predictive healthcare
Researchers from the Mayo Clinic recently used artificial intelligence (AI) to develop a predictive computational tool that analyzes an individual’s gut microbiome to identify how a person may experience improvement or deterioration in health.
Dubbed the Gut Microbiome Wellness Index 2 (GMWI2), Mayo’s new tool does not identify the presence of specific health conditions but can detect even minor changes in overall gut health.
Built on an earlier prototype, GMWI2 “demonstrated at least 80% accuracy in differentiating healthy individuals from those with any disease,” according to a Mayo news release. “The researchers used bioinformatics and machine learning methods to analyze gut microbiome profiles in stool samples gathered from 54 published studies spanning 26 countries and six continents. This approach produced a diverse and comprehensive dataset.”
“Our tool is not intended to diagnose specific diseases but rather to serve as a proactive health indicator,” said senior study author Jaeyun Sung, PhD (above), a computational biologist at the Mayo Clinic Center for Individualized Medicine: Microbiomics Program in the news release ease. “By identifying adverse changes in gut health before serious symptoms arise, the tool could potentially inform dietary or lifestyle modifications to prevent mild issues from escalating into more severe health conditions, or prompt further diagnostic testing.” For microbiologists and clinical laboratory managers, this area of new knowledge about the human microbiome may lead to multiplex diagnostic assays. (Photo copyright: Mayo Clinic.)
Connecting Specific Diseases with Gut Microbiome
Gut bacteria that resides in the gastrointestinal tract consists of trillions of microbes that help regulate various bodily functions and may provide insights regarding the overall health of an individual. An imbalance in the gut microbiome is associated with an assortment of illnesses and chronic diseases, including cardiovascular issues, digestive problems, and some cancers and autoimmune diseases.
To develop GMWI2, the Mayo scientists provided the machine-learning algorithm with data on microbes found in stool samples from approximately 8,000 people collected from 54 published studies. They looked for the presence of 11 diseases, including colorectal cancer and inflammatory bowel disease (IBS). About 5,500 of the subjects had been previously diagnosed with one of the 11 diseases, and the remaining people did not have a diagnosis of the conditions.
The scientists then tested the efficacy of GMWI2 on an additional 1,140 stool samples from individuals who were diagnosed with conditions such as pancreatic cancer and Parkinson’s disease, compared with those who did not have those illnesses.
The algorithm gives subjects a score between -6 and +6. People with a higher GMWI2 score have a healthier microbiome that more closely resembles individuals who do not have certain diseases.
Likewise, a low GMWI2 score suggests the individual has a gut microbiome that is similar to those who have specific illnesses.
Highly Accurate Results
According to their study, the researchers determined that “GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence,” they wrote in Nature Communications.
Launched in 2020, the original GMWI (Gut Microbiome Wellness Index) was trained on a much smaller number of samples but still showed similar results.
The researchers tested the enhanced GMWI2 algorithm across various clinical schemes to determine if the results were similar. These scenarios included individuals who had previous fecal microbiota transplants and people who had made dietary changes or who had exposure to antibiotics. They found that their improved tool detected changes in gut health in those scenarios as well.
“By being able to answer whether a person’s gut is healthy or trending toward a diseased state, we ultimately aim to empower individuals to take proactive steps in managing their own health,” Sung said in the news release.
The Mayo Clinic team is developing the next version of their tool, which will be known as the Gut Microbiome Wellness Index 3. They plan to train it on at least 12,000 stool samples and use more sophisticated algorithms to decipher the data.
More research and studies are needed to determine the overall usefulness of Mayo’s Gut Microbiome Wellness Index and its marketability. Here is a world-class health institution disclosing a pathway/tool that analyzes the human microbiome to identify how an individual may be experiencing either an improvement in health or a deterioration in health.
The developers believe it will eventually help physicians determine how patients’ conditions are improving or worsening by comparing the patients’ microbiomes to the profiles of other healthy and unhealthy microbiomes. As this happens, it would create a new opportunity for clinical laboratories to perform the studies on the microbiomes of patients being assayed in this way by their physicians.
Study results from Switzerland come as clinical laboratory scientists seek new ways to tackle the problem of antimicrobial resistance in hospitals
Microbiologists and clinical laboratory scientists engaged in the fight against antibiotic-resistant (aka, antimicrobial resistant) bacteria will be interested in a recent study conducted at the University of Basel and University Hospital Basel in Switzerland. The epidemiologists involved in the study discovered that some of these so-called “superbugs” can remain in the body for as long as nine years continuing to infect the host and others.
The researchers wanted to see how two species of drug-resistant bacteria—K. pneumoniae and E. coli—changed over time in the body, according to a press release from the university. They analyzed samples of the bacteria collected from patients who were admitted to the hospital over a 10-year period, focusing on older individuals with pre-existing conditions. They found that K. pneumoniae persisted for up to 4.5 years (1,704 days) and E. coli persisted for up to nine years (3,376 days).
“These patients not only repeatedly become ill themselves, but they also act as a source of infection for other people—a reservoir for these pathogens,” said Lisandra Aguilar-Bultet, PhD, the study’s lead author, in the press release.
“This is crucial information for choosing a treatment,” explained Sarah Tschudin Sutter, MD, Head of the Division of Infectious Diseases and Hospital Epidemiology, and of the Division of Hospital Epidemiology, who specializes in hospital-acquired infections and drug-resistant pathogens. Sutter led the Basel University study.
“The issue is that when patients have infections with these drug-resistant bacteria, they can still carry that organism in or on their bodies even after treatment,” said epidemiologist Maroya Spalding Walters, MD (above), who leads the Antimicrobial Resistance Team in the Division of Healthcare Quality Promotion at the federal Centers for Disease Control and Prevention (CDC). “They don’t show any signs or symptoms of illness, but they can get infections again, and they can also transmit the bacteria to other people.” Clinical laboratories working with microbiologists on antibiotic resistance will want to follow the research conducted into these deadly pathogens. (Photo copyright: Centers for Disease Control and Prevention.)
COVID-19 Pandemic Increased Antibiotic Resistance
The Basel researchers looked at 76 K. pneumoniae isolates recovered from 19 patients and 284 E. coli isolates taken from 61 patients, all between 2008 and 2018. The study was limited to patients in which the bacterial strains were detected from at least two consecutive screenings on admission to the hospital.
“DNA analysis indicates that the bacteria initially adapt quite quickly to the conditions in the colonized parts of the body, but undergo few genetic changes thereafter,” the Basel University press release states.
The researchers also discovered that some of the samples, including those from different species, had identical mechanisms of drug resistance, suggesting that the bacteria transmitted mobile genetic elements such as plasmids to each other.
One limitation of the study, the authors acknowledged, was that they could not assess the patients’ exposure to antibiotics.
Meanwhile, recent data from the World Health Organization (WHO) suggests that the COVID-19 pandemic might have exacerbated the challenges of antibiotic resistance. Even though COVID-19 is a viral infection, WHO scientists found that high percentages of patients hospitalized with the disease between 2020 and 2023 received antibiotics.
“While only 8% of hospitalized patients with COVID-19 had bacterial co-infections requiring antibiotics, three out of four or some 75% of patients have been treated with antibiotics ‘just in case’ they help,” the WHO stated in a press release.
WHO uses an antibiotic categorization system known as AWaRe (Access, Watch, Reserve) to classify antibiotics based on risk of resistance. The most frequently prescribed antibiotics were in the “Watch” group, indicating that they are “more prone to be a target of antibiotic resistance and thus prioritized as targets of stewardship programs and monitoring.”
“When a patient requires antibiotics, the benefits often outweigh the risks associated with side effects or antibiotic resistance,” said Silvia Bertagnolio, MD, Unit Head in the Antimicrobial resistance (AMR) Division at the WHO in the press release. “However, when they are unnecessary, they offer no benefit while posing risks, and their use contributes to the emergence and spread of antimicrobial resistance.”
Citing research from the National Institutes of Health (NIH), NPR reported that in the US, hospital-acquired antibiotic-resistant infections increased 32% during the pandemic compared with data from just before the outbreak.
“While that number has dropped, it still hasn’t returned to pre-pandemic levels,” NPR noted.
The UPenn researchers have already developed an antimicrobial treatment derived from guava plants that has proved effective in mice, Vox reported. They’ve also trained an AI model to scan the proteomes of extinct organisms.
“The AI identified peptides from the woolly mammoth and the ancient sea cow, among other ancient animals, as promising candidates,” Vox noted. These, too, showed antimicrobial properties in tests on mice.
These findings can be used by clinical laboratories and microbiologists in their work with hospital infection control teams to better identify patients with antibiotic resistant strains of bacteria who, after discharge, may show up at the hospital months or years later.
Study findings could lead to new biomarker targets for clinical laboratories working to identify AMR bacteria
Reducing and managing antimicrobial resistance (AMR) is a major goal of researchers and health systems across the globe. And it is the job of microbiologists and clinical laboratories to identify microbes that are AMR and those which are not to guide physicians as to the most appropriate therapies for patients with bacterial infections.
“AMR is a silent pandemic of much greater risk to society than COVID-19. In addition to 10 million deaths per year by 2050, the WHO estimates AMR will cost the global economy $100 trillion if we can’t find a way to combat antibiotic failure,” Timothy Barnett, PhD (above), Deputy Director and head of the Strep A Pathogenesis and Diagnostics team at Wesfarmers Centre of Vaccines and Infectious Diseases, told News Medical. Additional research may provide new targets for clinical laboratories tasked with identifying antimicrobial resistant bacteria. (Photo copyright: University of Western Australia.)
Rendering an Antibiotic Ineffective
According to the University of Oxford, about 1.2 million people died worldwide in 2019 due to AMR, and antimicrobial-resistant infections played a role in as many as 4.95 million deaths that same year. The World Health Organization (WHO) declared AMR one of the top ten global public health threats facing humanity.
While investigating antibiotic sensitivity of Group A Streptococcus—a potentially deadly bacteria often detected on the skin and in the throat—the Australian researchers uncovered a mechanism that enabled bacteria to absorb nutrients from their human host and evade the antibiotic sulfamethoxazole, a commonly-prescribed treatment for Group A Strep.
“Bacteria need to make their own folates to grow and, in turn, cause disease. Some antibiotics work by blocking this folate production to stop bacteria growing and treat the infection,” Timothy Barnett, PhD, Deputy Director of the Wesfarmers Centre of Vaccines and Infectious Diseases and head of the Strep A Pathogenesis and Diagnostics team, told News Medical.
“When looking at an antibiotic commonly prescribed to treat Group A Strep skin infections, we found a mechanism of resistance where, for the first time ever, the bacteria demonstrated the ability to take folates directly from its human host when blocked from producing their own. This makes the antibiotic ineffective and the infection would likely worsen when the patient should be getting better,” he added.
According to their study, the researchers identified an energy-coupling (ECF) factor transporter S component gene that allows Group A Strep to acquire extracellular reduced folate compounds that likely “expands the substrate specificity of an endogenous ECF transporter to acquire reduced folate compounds directly from the host, thereby bypassing the inhibition of folate biosynthesis by sulfamethoxazole.”
The study indicates that this new form of antibiotic resistance is indistinguishable under traditional testing used in microbiology and clinical laboratories, which in turn makes it difficult for clinicians to prescribe effective antibiotics to fight an infection.
Understanding AMR before It Is Too Late
The research suggests that understanding AMR is more complicated and intricate than previously thought. Barnett and his team believe their discovery is just the “tip of the iceberg” and that it will prove to be a far-reaching issue across other bacterial pathogens in addition to Group A Strep.
“Without antibiotics, we face a world where there will be no way to stop deadly infections, cancer patients won’t be able to have chemotherapy and people won’t have access to have life-saving surgeries,” Barnett told News Medical. “In order to preserve the long-term efficacy of antibiotics, we need to further identify and understand new mechanisms of antibiotic resistance, which will aid in the discovery of new antibiotics and allow us to monitor AMR as it arises.”
More research and clinical studies are needed before this discovery can become technology that clinical laboratories can use to test if microbes are AMR. The scientists at Wesfarmers Centre of Vaccines and Infectious Diseases are now developing testing methods to detect the presence of the antibiotic resistant mechanism and determine the best treatment options.
“It is vital we stay one step ahead of the challenges of AMR and, as researchers, we should continue to explore how resistance develops in pathogens and design rapid accurate diagnostic methods and therapeutics,” Kalindu Rodrigo, a PhD student in the Barnett lab and one of the authors of the study told News Medical. “On the other hand, equal efforts should be taken at all levels of the society including patients, health professionals, and policymakers to help reduce the impacts of AMR.”
This innovative technology platform is newest effort to measure biomarkers without the need for the invasive specimen collection techniques used in medical laboratory testing
Pathologists and clinical laboratory managers interested in how new technologies are transforming certain well-established clinical practices will be interested to learn about the latest research breakthroughs in pulse oximetry, a common procedure used to measure the oxygen level (or oxygen saturation) in the blood.
Pulse oximetry is considered to be a noninvasive, painless, general indicator of oxygen delivery to the peripheral tissues (such as the finger, earlobe, or nose). For decades, PO has been ubiquitous in the hospital. Now, because of recent advance, this field is poised for a paradigm shift away from simple monitoring devices to advanced products capable of connecting patients to electronic systems that continuously gather data and notify caregivers when values become critical.
A group of bioengineering doctoral students at the University of California Berkeley (UC Berkeley) have invented an inexpensive Band-Aid-style oximeter that uses red and green light to non-invasively monitor pulse rate and oxygen level in blood. While this device could revolutionize pulse oximetry monitoring in healthcare settings, the technology might also be applied to measuring other useful biomarkers as one approach to eliminate invasive specimen collection. (more…)
