News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

Hosted by Robert Michel

News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

Hosted by Robert Michel
Sign In

McMaster University Uses AI Algorithm, Machine Learning to Find Antibiotic That Neutralizes Common Antimicrobial Resistant Superbug

Further development of this novel technology could result in new, more sensitive assays for clinical laboratories to use in the effort to improve antimicrobial stewardship in hospitals

Researchers at McMaster University in Ontario, Canada, have used artificial intelligence (AI) to identify a potential antibiotic that neutralizes the drug-resistant bacteria Acinetobacter baumannii, an antibiotic resistant pathogen commonly found in many hospitals. This will be of interest to clinical laboratory managers and microbiologists involved in identifying strains of bacteria to determine if they are antimicrobial-resistant (AMR) superbugs.

Using machine learning, the scientists screened thousands molecules to look for those that inhibited the growth of this specific pathogen. And they succeeded.

“We trained a neural network with this growth inhibition dataset and performed in silico predictions for structurally new molecules with activity against A. baumannii,” the researchers wrote in their published study.

They discovered that the molecule abaucin inhibited the growth of the antibiotic-resistant pathogen in vitro.

This shows how machine learning and AI technologies are giving biomedical researchers  tools to identify new therapeutic drugs that are effective against drug-resistant strains of bacteria. This same research can be expected to lead to new clinical laboratory assays that determine if superbugs can be attacked by specific therapeutic drugs.

The researchers published their findings in the journal Nature Chemical Biology titled, “Deep Learning-Guided Discovery of an Antibiotic Targeting Acinetobacter Baumannii.”

“When I think about AI in general, I think of these models as things that are just going to help us do the thing we’re going to do better,” Jonathan Stokes, PhD, Assistant Professor of Biomedicine and Biochemistry at McMaster University in Ontario, Canada, and lead author of the study, told USA Today. Clinical laboratory scientists and microbiologists will be encouraged by the McMaster University scientists’ findings. (Photo copyright: McMaster University.)

McMaster Study Details

Jonathan Stokes, PhD, head of the Stokes Laboratory at McMaster University, is Assistant Professor of Biomedicine/Biochemistry at McMaster and lead author of the study. Stokes’ team worked with researchers from the Broad Institute of MIT and Harvard to explore the effectiveness of AI in combating superbugs, USA Today reported.

“This work highlights the utility of machine learning in antibiotic discovery and describes a promising lead with targeted activity against a challenging Gram-negative pathogen,” the researchers wrote in Nature Chemical Biology.

Stokes Lab utilized the high-throughput drug screening technique, spending weeks growing and exposing Acinetobacter baumannii to more than 7,500 agents of drugs and active ingredients of drugs. When 480 compounds were uncovered that blocked the growth of bacteria, this information was then provided to a computer that was trained to run an AI algorithm, CNN reported.

“Once we had our [machine learning] model trained, what we could do then is start showing that model brand-new pictures of chemicals that it had never seen, right? And based on what it had learned during training, it would predict for us whether those molecules were antibacterial or not,” Stokes told CNN.

The model spent hours screening more than 6,000 molecules. It then narrowed the search to 240 chemicals, which were tested in the lab. The scientists pared down the results to the nine most effective inhibitors of bacteria. They then eliminated those that were either related to existing antibiotics or might be considered dangerous.

The researchers found one compound—RS102895 (abaucin)—which, according to Stokes, was likely created to treat diabetes, CNN reported. The scientists discovered that the compound prevented bacterial components from making their way from inside a cell to the cell’s surface.

“It’s a rather interesting mechanism and one that is not observed amongst clinical antibiotics so far as I know,” Stokes told CNN.

Because of the effectiveness of the antibiotic during testing on mice skin, the researchers believe this method may be useful for creating antibiotics custom made to battle additional drug resistant pathogens, CNN noted.

Defeating a ‘Professional Pathogen’

Acinetobacter baumannii (A. baumannii)—the focus of Stoke’s study—is often found on hospital counters and doorknobs and has a sneaky way of using other organisms’ DNA to resist antibiotic treatment, according to CNN

“It’s what we call in the laboratory a professional pathogen,” Stokes told CNN.

A. baumannii causes infections in the urinary tract, lungs, and blood and typically wreaks havoc to vulnerable patients on breathing machines, in intensive care units, or undergoing surgery, USA Today reported.

A. baumannii is resistant to carbapenem, a potent antibiotic. The Centers for Disease Control and Prevention (CDC) reported that in 2017 the bacteria infected 8,500 people in hospitals, 700 of those infections being fatal.

Further, in its 2019 “Antibiotic Resistance Threats in the United States” report, the CDC stated that one out of every four patients infected with the bacteria died within one month of their diagnosis. The federal agency deemed the bacteria “of greatest need” for new antibiotics.

Thus, finding a way to defeat this particularly nasty bacteria could save many lives.

Implications of Study Findings on Development of new Antibiotics

The Stokes Laboratory study findings show promise. If more antibiotics worked so precisely, it’s possible bacteria would not have a chance to become resistant in the first place, CNN reported.

Next steps in Stokes’ research include optimizing the chemical structure and testing in larger animals or humans, USA Today reported.

“It’s important to remember [that] when we’re trying to develop a drug, it doesn’t just have to kill the bacterium,” Stokes noted. “It also has to be well tolerated in humans and it has to get to the infection site and stay at the infection site long enough to elicit an effect,” USA Today reported.

Stokes’ study is a prime example of how AI can make a big impact in clinical laboratory diagnostics and treatment.

“We know broad-spectrum antibiotics are suboptimal and that pathogens have the ability to evolve and adjust to every trick we throw at them … AI methods afford us the opportunity to vastly increase the rate at which we discover new antibiotics, and we can do it at a reduced cost. This is an important avenue of exploration for new antibiotic drugs,” Stokes told CNN.

Clinical laboratory managers and microbiologists may want to keep an open-mind about the use of AI in drug development. More research is needed to give substance to the McMaster University study’s findings. But the positive results may lead to methods for fine tuning existing antibiotics to better combat antimicrobial-resistant bacteria, USA Today reported.

—Kristin Althea O’Connor

Related Information:

The Study: Deep Learning-Guided Discovery of an Antibiotic Targeting Acinetobacter Baumannii

Scientists Use AI to Discover Antibiotic to Fight Deadly Hospital Bug

A New Type of Antibiotic, Discovered with Artificial Intelligence, May Defeat a Dangerous Superbug

WHO Report: Bacteria for Which New Antibiotics are Urgently Needed

Abstract on Deaths of Those Infected with Acinetobacter

CDC: Antibiotic Resistance Threats in the United States

CDC: Acinetobacter in Healthcare Settings

Home Ice: Star Researcher Back at Mac to Pioneer Use of AI to Fight Antibiotic Resistance

Precision Healthcare Milestone Reached as Food and Drug Administration Clears New Multi-Marker Medical Laboratory Test to Detect Antibiotic-Resistant Bacteria

FDA issues press release following clearance of a clinical lab test to detect genetic markers that indicate the presence of Carbapenem-resistant Enterobacteriaceae

Clearance by the US Food and Drug Administration (FDA) of a new rapid, multi-marker genetic test designed to identify bacteria that are resistant to Carbapenem antibiotics was considered significant enough that the federal agency issued a press release announcing that the test was cleared and now available for use by physicians and clinical laboratories in the United States.

In the race to develop molecular assays and genetic tests for infectious disease that deliver improved sensitivity and specificity with a faster time-to-answer, this new test offers all three benefits. Results are available in just 48 minutes, for example.

It was on June 29, 2016, that the FDA cleared Cepheid’s Xpert Carba-R rapid-diagnostic test for marketing in the United States. This is the first clinical laboratory test cleared for market by the FDA that detects healthcare-associated infections (AKA, hospital-acquired infections or HAIs) through the use of genetic markers taken directly from clinical samples. The assay tests for genetic markers that indicate the presence of Carbapenem-resistant Enterobacteriaceae (CRE). (more…)

Researchers at Auburn University Collaborate with Clinical Laboratory Team at Keesler Air Force Base to Detect Antibiotic-resistant Bacteria in Just 10 Minutes

This technology could provide medical labs a quick, cost-effective way to diagnose methicillin-resistant Staphylococcus aureus

Even as in vitro diagnostics manufacturers are bringing rapid molecular tests to market that can identify infectious diseases within hours, a research collaboration involving a major university and a medical laboratory at an air force base has demonstrated the ability to identify antibiotic-resistant strains of Staphylococcus in just minutes.

This innovative research is being done by Auburn University’s College of Veterinary Medicine and clinical laboratory professionals at Keesler Air Force Base. Funding is by the U.S. Air Force. This research was of particular interest to the military because the risk for Staph infection increases when individuals are subjected to unhygienic conditions in close quarters. (more…)

Unexpected Discovery of Source of Lethal, Antibiotic-Resistant Strain of E. Coli Could Lead to New Medical Laboratory Tests and Preventative Treatment

Research breakthrough heralded as key insight that can lead to more accurate clinical laboratory tests and more effective antibiotics for treating E. Coli infections

Antibiotic-resistant strains of bacteria are one of healthcare’s biggest threats to patient safety and improved patient outcomes. Now advanced gene sequencing has given researchers a startling new understanding of how Escherichia coli (E. coli) has developed resistance to antibiotics.

This discovery may have a major impact on microbiology labs in hospitals, because they do so much of the medical laboratory testing to detect and identify infections. These new research findings also demonstrate to pathologists how quickly genome analysis can generate new knowledge about diseases and their causes. (more…)

New Tool for Fighting Antibiotic-Resistant Bacteria: Meet Bacteriophage

Microbiologists and hospital infection control teams are intensifying efforts to identify and control infections of antibiotic-resistant strains of bacteria. Now comes news of a new tool that can provide another way to control such infections.

Timothy Lu, a Harvard Medical School student and Massachusetts Institute of Technology Ph.D. recipient, has found a way to use bacteriophage-viruses that infect bacteria cells but not human ones-to boost the effectiveness of antibiotics. This development could prove instrumental to conquering the problem of antibiotic-resistant drugs, such as methacillin-resistant Staphylococus aureas, which causes 94,000 cases of life-threatening infections among hospital patients each year.

Lu has engineered bacteriophage to cut through biofilm-the slick, protective coating that covers bacteria-and to seek out the gene mutations that create antibiotic resistance. The bacteriophage then destroy the resistance mechanisms, enabling antibiotic drugs to perform better. The combination of engineered bacteriophage and antibiotics have the potential to eliminate nearly 30,000 times more bacteria than antibiotics alone.

Lu received the Lemelson-MIT Student Prize of $30,000 for inventing the bacteriophage platform. He is developing a secondary use of the platform that would allow bacteriophage to kill off deadly biofilms that attach themselves to food processing equipment and medical instruments.

The success of Lu’s invention could spell out a much better prognosis for patients who are discovered to have methacillin-resistant Staphylococus aureas (MRSA) based on confirmation by hospital-based laboratory tests. Laboratories always welcome medical advancements that make a positive result from a laboratory test less devastating/life-threatening to patients. Lu’s new technology may have applications in the treatment of numerous other superbugs and antibiotic-resistant bacteria strains.

Related Articles:

;