New technology could enable genetic scientists to identify antibiotic resistant genes and help physicians choose better treatments for genetic diseases
Genomic scientists at the Icahn School of Medicine at Mount Sinai Medical Center in New York City have developed what they call a “smart tweezer” that enables researchers to isolate a single bacterium from a patient’s microbiome in preparation for genetic sequencing. Though primarily intended for research purposes, the new technology could someday be used by clinical laboratories and microbiologists to help physicians diagnose chronic disease and choose appropriate genetic therapies.
The researchers designed their new technology—called mEnrich-seq—to improve the effectiveness of research into the complex communities of microorganisms that reside in the microbiomes within the human body. The discovery “ushers in a new era of precision in microbiome research,” according to a Mount Sinai Hospital press release.
“Imagine you’re a scientist who needs to study one particular type of bacteria in a complex environment. It’s like trying to find a needle in a large haystack,” said the study’s senior author Gang Fang, PhD (above), Professor of Genetics and Genomic Sciences at Icahn School of Medicine at Mount Sinai Medical Center, in a press release. “mEnrich-seq essentially gives researchers a ‘smart tweezer’ to pick up the needle they’re interested in,” he added. Might smart tweezers one day be used to help physicians and clinical laboratories diagnose and treat genetic diseases? (Photo copyright: Icahn School of Medicine.)
Addressing a Technology Gap in Genetic Research
Any imbalance or decrease in the variety of the body’s microorganisms can lead to an increased risk of illness and disease.
In researching the microbiome, many scientists “focus on studying specific types of bacteria within a sample, rather than looking at each type of bacteria present,” the press release states. The limitation of this method is that a specific bacterium is just one part of a complicated environment that includes other bacteria, viruses, fungi and host cells, each with their own unique DNA.
“mEnrich-seq effectively distinguishes bacteria of interest from the vast background by exploiting the ‘secret codes’ written on bacterial DNA that bacteria use naturally to differentiate among each other as part of their native immune systems,” the press release notes. “This new strategy addresses a critical technology gap, as previously researchers would need to isolate specific bacterial strains from a given sample using culture media that selectively grow the specific bacterium—a time-consuming process that works for some bacteria, but not others. mEnrich-seq, in contrast, can directly recover the genome(s) of bacteria of interest from the microbiome sample without culturing.”
Isolating Hard to Culture Bacteria
To conduct their study, the Icahn researchers used mEnrich-seq to analyze urine samples taken from three patients with urinary tract infections (UTIs) to reconstruct Escherichia coli (E. Coli) genomes. They discovered their “smart tweezer” covered more than 99.97% of the genomes across all samples. This facilitated a comprehensive examination of antibiotic-resistant genes in each genome. They found mEnrich-seq had better sensitivity than standard study methods of the urine microbiome.
They also used mEnrich-seq to selectively examine the genomes of Akkermansia muciniphila (A. muciniphila), a bacterium that colonizes the intestinal tract and has been shown to have benefits for obesity and Type 2 diabetes as well as a response to cancer immunotherapies.
“Akkermansia is very hard to culture,” Fang told GenomeWeb. “It would take weeks for you to culture it, and you need special equipment, special expertise. It’s very tedious.”
mEnrich-seq was able to quickly segregate it from more than 99.7% of A. muciniphila genomes in the samples.
Combatting Antibiotic Resistance Worldwide
According to the press release, mEnrich-seq could potentially be beneficial to future microbiome research due to:
Cost-Effectiveness: It offers a more economical approach to microbiome research, particularly beneficial in large-scale studies where resources may be limited.
Broad Applicability: The method can focus on a wide range of bacteria, making it a versatile tool for both research and clinical applications.
Medical Breakthroughs: By enabling more targeted research, mEnrich-seq could accelerate the development of new diagnostic tools and treatments.
“One of the most exciting aspects of mEnrich-seq is its potential to uncover previously missed details, like antibiotic resistance genes that traditional sequencing methods couldn’t detect due to a lack of sensitivity,” Fang said in the news release. “This could be a significant step forward in combating the global issue of antibiotic resistance.”
More research and clinical trials are needed before mEnrich-seq can be used in the medical field. The Icahn researchers plan to refine their novel genetic tool to improve its efficiency and broaden its range of applications. They also intend to collaborate with physicians and other healthcare professionals to validate how it could be used in clinical environments.
Should all this come to pass, hospital infection control teams, clinical laboratories, and microbiology labs would welcome a technology that would improve their ability to detect details—such as antibiotic resistant genes—that enable a faster and more accurate diagnosis of a patient’s infection. In turn, that could contribute to better patient outcomes.
Should the device prove effective, it could replace invasive point-of-care blood draws for clinical laboratory testing during patient drug therapy monitoring
What if it were possible to perform therapeutic drug monitoring (TDM) without invasive blood draws using breath alone? Patients fighting infections in hospitals certainly would benefit. Traditional TDM can be a painful process for patients, one that also brings risk of bloodline infections. Nevertheless, regular blood draws have been the only reliable method for obtaining viable samples for testing.
One area of critical TDM is in antibiotic therapy, also known as personalized antibiotherapy. However, for antibiotic therapy to be successful it typically requires close monitoring using point-of-care clinical laboratory testing.
Now, a team of engineers and biotechnologists from the University of Freiburg in Germany have developed a biosensor that can use breath samples to measure antibiotic concentrations present in blood, according to a University of Freiburg press release.
The team’s non-invasive collection method requires no needle sticks and can allow for frequent specimen collections to closely monitor the levels of an antibiotic prescribed for a patient. The biosensor also provides physicians the ability to tailor antibiotic regimens specific to individual patients, a core element of precision medicine.
“Until now researchers could only detect traces of antibiotics in the breath,” said Can Dincer, PhD (above), Junior Research Group Leader at the University of Freiburg, and one of the authors of the study, in the press release. “With our synthetic proteins on a microfluid chip, we can determine the smallest concentrations in the breath condensate and [how] they correlate with the blood values.” Should the breath biosensor prove effective in clinical settings, painful blood draws for clinical laboratory testing at the point of care could become obsolete. (Photo copyright: Conny Ehm/University of Freiburg.)
Can a Breath Biosensor Be as Accurate as Clinical Laboratory Testing?
The University of Freiburg’s biosensor is a multiplex, microfluid lab-on-a-chip based on synthetic proteins that react to antibiotics. It allows the simultaneous measurement of several breath samples and test substances to determine the levels of therapeutic antibiotics in the blood stream.
To perform their research, the University of Freiburg team tested their biosensor on blood, plasma, urine, saliva, and breath samples of pigs that had been given antibiotics. The results the researchers achieved with their device using breath samples were as accurate as standard clinical laboratory testing, according to the press release.
The microfluidic chip contains synthetic proteins affixed to a polymer film via dry film photoresist (DFR) technology. These proteins are similar to proteins used by drug-resistant bacteria to sense the presence of antibiotics in their environment. Each biosensor contains an immobilization area and an electrochemical cell which are separated by a hydrophobic stopping barrier. The antibiotic in a breath sample binds to the synthetic proteins which generates a change in an electrical current.
“You could say we are beating the bacteria at their own game,” said Wilfried Weber, PhD, Professor of Biology at the University of Freiburg and one of the authors of the research paper, in the press release.
Rapid Monitoring at Point-of-Care Using Breath Alone
The biosensor could prove to be a useful tool in keeping antibiotic levels stable in severely ill patients who are dealing with serious infections and facing the risk of sepsis, organ failure, or even death. Frequent monitoring of therapeutic antibiotics also could prevent bacteria from mutating and causing the body to become resistant to the medications.
“Rapid monitoring of antibiotic levels would be a huge advantage in hospital,” said H. Ceren Ates, PhD, scientific researcher at the University of Freiburg and one of the authors of the study in the press release. “It might be possible to fit the method into a conventional face mask.”
Along those lines, the researchers are also working on a project to create wearable paper sensors for the continuous measurement of biomarkers of diseases from exhaled breath. Although still in the development stages, this lightweight, small, inexpensive paper sensor can fit into conventional respiratory masks, according to a University of Freiburg press release.
Other Breath Analysis Devices Under Development
Devices that sample breath to detect biomarkers are not new. Dark Daily has regularly reported on similar developments worldwide.
Thus, University of Freiburg’s non-invasive lab-on-a-chip biosensor is worth watching. More research is needed to validate the effectiveness of the biosensor before it could be employed in hospital settings, however, monitoring and managing antibiotic levels in the body via breath samples could prove to be an effective, non-invasive method of providing personalized antibiotic therapy to patients.
Clinical trials on human breath samples are being planned by the University of Freiburg team. This type of precision medicine service may give medical professionals the ability to maintain proper medication levels within an optimal therapeutic window.
DeepMind hopes its unrivaled collection of data, enabled by artificial intelligence, may advance development of precision medicines, new medical laboratory tests, and therapeutic treatments
‘Tis the season for giving, and one United Kingdom-based artificial intelligence (AI) research laboratory is making a sizeable gift. After using AI and machine learning to create “the most comprehensive map of human proteins,” in existence, DeepMind, a subsidiary of Alphabet Inc. (NASDAQ:GOOGL), parent company of Google, plans to give away for free its database of millions of protein structure predictions to the global scientific community and to all of humanity, The Verge reported.
Pathologists and clinical laboratory scientists developing proteomic assays understand the significance of this gesture. They know how difficult and expensive it is to determine protein structures using sequencing of amino acids. That’s because the various types of amino acids in use cause the [DNA] string to “fold.” Thus, the availability of this data may accelerate the development of more diagnostic tests based on proteomics.
“For decades, scientists have been trying to find a method to reliably determine a protein’s structure just from its sequence of amino acids. Attraction and repulsion between the 20 different types of amino acids cause the string to fold in a feat of ‘spontaneous origami,’ forming the intricate curls, loops, and pleats of a protein’s 3D structure. This grand scientific challenge is known as the protein-folding problem,” a DeepMind statement noted.
Enter DeepMind’s AlphaFold AI platform to help iron things out. “Experimental techniques for determining structures are painstakingly laborious and time consuming (sometimes taking years and millions of dollars). Our latest version [of AlphaFold] can now predict the shape of a protein, at scale and in minutes, down to atomic accuracy. This is a significant breakthrough and highlights the impact AI can have on science,” DeepMind stated.
Release of Data Will Be ‘Transformative’
In July, DeepMind announced it would begin releasing data from its AlphaFold Protein Structure Database which contains “predictions for the structure of some 350,000 proteins across 20 different organisms,” The Verge reported, adding, “Most significantly, the release includes predictions for 98% of all human proteins, around 20,000 different structures, which are collectively known as the human proteome. By the end of the year, DeepMind hopes to release predictions for 100 million protein structures.”
According to Edith Heard, PhD, Director General of the European Molecular Biology Laboratory (EMBL), the open release of such a dataset will be “transformative for our understanding of how life works,” The Verge reported.
“I see this as the culmination of the entire 10-year-plus lifetime of DeepMind,” company CEO and co-founder Demis Hassabis (above), told The Verge. “From the beginning, this is what we set out to do: to make breakthroughs in AI, test that on games like Go and Atari, [and] apply that to real-world problems, to see if we can accelerate scientific breakthroughs and use those to benefit humanity.” The release of DeepMind’s entire protein prediction database will certainly do that. Clinical laboratory scientists worldwide will have free access to use it in developing new precision medicine treatments based on proteomics. (Photo copyright: BBC.)
Free Data about Proteins Will Accelerate Research on Diseases, Treatments
Research into how protein folds and, thereby, functions could have implications to fighting diseases and developing new medicines, according to DeepMind.
“This will be one of the most important datasets since the mapping of the human genome,” said Ewan Birney, PhD, Deputy Director General of the EMBL, in the DeepMind statement. EMBL worked with DeepMind on the dataset.
DeepMind protein prediction data are already being used by scientists in medical research. “Anyone can use it for anything. They just need to credit the people involved in the citation,” said Demis Hassabis, DeepMind CEO and Co-founder, in The Verge.
In a blog article, Hassabis listed several projects and organizations already using AlphaFold. They include:
“As researchers seek cures for diseases and pursue solutions to other big problems facing humankind—including antibiotic resistance, microplastic pollution, and climate change—they will benefit from fresh insights in the structure of proteins,” Hassabis wrote.
Because of the deep financial backing that Alphabet/Google can offer, it is reasonable to predict that DeepMind will make progress with its AI technology that regularly adds capabilities and accuracy, allowing AlphaFold to be effective for many uses.
This will be particularly true for the development of new diagnostic assays that will give clinical laboratories better tools for diagnosing disease earlier and more accurately.
In a separate study, HHS finds a 40% increase in sepsis cases, as more patients succumb to infections without effective antibiotics and antimicrobial drugs
Given the drastic steps being taken to slow the spread of the Coronavirus in America, it’s easy to forget that significant numbers of patients die each year due to antibiotic-resistant bacteria (ARB), other forms of antimicrobial resistance (AMR), and in thousands of cases the sepsis that follows the infections.
The CDC’s website states that “more than 2.8 million antibiotic-resistant infections occur in the US each year, and more than 35,000 people die as a result.” And a CDC news release states, “on average, someone in the United States gets an antibiotic-resistant infection every 11 seconds and every 15 minutes someone dies.”
Those are huge numbers.
Clinical laboratory leaders and microbiologists have learned to be vigilant as it relates to dangerously infectious antimicrobial-resistant agents that can result in severe patient harm and death. Therefore, new threats identified in the CDC’s Antibiotic Resistance Threats in the United States report will be of interest.
Drug-resistant Microbes That Pose Severe Risk
The CDC has added the fungus Candida auris (C. auris) and carbapenem-resistant Acinetobacter (a bacteria that can survive for a long time on surfaces) to its list of “urgent threats” to public health, CDC said in the news release. These drug-resistant microbes are among 18 bacteria and fungi posing a greater threat to patients’ health than CDC previously estimated, Live Science reported.
In 2013, the CDC estimated that about two million people each year acquired an antibiotic-resistant (AR) infection that killed as many as 23,000. However, in 2019, the CDC reported that those numbers were low and that the number of deaths due to AR infections in 2013 was about twice that amount. During a news conference following the CDC announcement, Michael Craig (above), a Senior Adviser for the CDC’s Antibiotic Resistance Coordination and Strategy Unit said, “We knew and said [in 2013] that our estimate was conservative … and we were right,” Live Science reported. In 2019, CDC reported 2.8 million antibiotic-resistant infections annually with more than 35,000 related deaths in the US alone. (Photo copyright: Centers for Disease Control and Prevention.)
The CDC considers five threats to be urgent. Including the
latest additions, they are:
Dark Daily has regularly covered the healthcare industry’s ongoing struggle with deadly fungus and bacteria that are responsible for hospital-acquired infections (HAI) and sepsis. This latest CDC report suggests healthcare providers continue to struggle with antimicrobial-resistant agents.
Acinetobacter Threat Increases and C. auris
a New Threat since 2013
Carbapenem-resistant Acinetobacter, a bacterium that
causes pneumonia and bloodstream and urinary tract infections, escalated from
serious to urgent in 2013. About 8,500 infections and 700 deaths were noted by the
CDC in 2017.
C. auris, however, was not addressed in the 2013
report at all. “It’s a pathogen that we didn’t even know about when we wrote
our last report in 2013, and since then it’s circumvented the globe,” said Michael
Craig, Senior Adviser for the CDC’s Antibiotic Resistance Coordination and
Strategy Unit, during a news conference following the CDC announcement, Live
Science reported.
Today, C. auris is better understood. The fungus
resists emerging drugs, can result in severe infections, and can be transmitted
between patients, CDC noted.
By year-end, CDC tracking showed 988 cases in the US.
More Patients Getting Sepsis as Antibiotics Fail: HHS
Study
In a separate study published in Critical Care Medicine, a journal of the Society of Critical Care Medicine (SCCM), the US Department of Health and Human Services (HHS) found that antibiotic-resistant bacteria and fungi are resulting in more people acquiring sepsis, a life-threatening condition, according to an HHS news release.
Sepsis increased by 40% among hospitalized Medicare patients
from 2012 through 2018, HHS reported.
“These (untreatable infections) are happening here and now in the United States in large numbers. This is isn’t some developing world thing. This isn’t a threat for 2050. It’s a threat for here and now,” Cornelius “Neil” Clancy, MD, Associate Chief of Veterans Affairs Pittsburg Health System (VAPHS) and Opportunistic Pathogens, told STAT.
It is troubling to see data about so many patient deaths
related to antibiotic-resistant infections and sepsis cases when the world is
transfixed by the Coronavirus. Nevertheless, it’s important that medical laboratory
leaders and microbiologists keep track of how the US healthcare system is or is
not responding to these new infectious agents. And, to contact infection
control and environmental services colleagues to enhance surveillance, ensure
safe healthcare environments and equipment, and adopt appropriate strategies to
prevent antibiotic-resistant infections.
Even as the nation’s hospitals embark on efforts to implement effective antimicrobial stewardship programs, researchers continue to seek solutions to the same problem. They are following several paths to combat the growing resistance certain pathogens have to antibiotics. In particular, two approaches are interesting for pathologists and medical laboratory personnel. One involves understanding the processes that lead to antibiotic resistance. The other is to identify useful biomarkers associated with specific strains of pathogens. (more…)
