Findings could lead to new therapies and clinical laboratory biomarkers for detecting and defeating antibiotic-resistant bacteria
Once again, new research shows that human gut bacteria (microbiota) may be useful in fighting antibiotic-resistant bacterial infections. The study findings could provide new therapeutics and clinical laboratory biomarkers for diagnosing and treating severe gastrointestinal disorders.
Antibiotic-resistant bacterial infections often appear in patients with chronic intestinal conditions and in those with long-term antibiotic use. Enterobacteriaceae is a large family of gram-negative bacteria that includes more than 30 genera and over 100 species.
“Despite two decades of microbiome research, we are just beginning to understand how to define health-promoting features of the gut microbiome,” said Marie-Madlen Pust, PhD, a computational postdoctoral researcher at the Broad Institute and co-first author of the paper, in the news release.
“Part of the challenge is that each person’s microbiome is unique. This collaborative effort allowed us to functionally characterize the different mechanisms of action these bacteria use to reduce pathogen load and gut inflammation,” she added.
The researchers identified a way to treat patients infected by antibiotic-resistant strains of bacteria that does not involve antibiotics. Should further research validate these early findings, this could be a viable approach to treating patients with this condition.
“Microbiome studies can often consist of analyzing collections of genetic sequences, without understanding what each gene does or why certain microbes are beneficial,” said Ramnik Xavier, MD (above), director of Broad Institute’s immunology program, co-director of the infectious disease and microbiome program, and co-senior author on the study, in a news release. “Trying to uncover that function is the next frontier, and this is a nice first step towards figuring out how microbial metabolites influence health and inflammation.” Clinical laboratories that test for intestinal conditions caused by antibiotic resistance will want to follow the Broad Institute’s research. (Photo copyright: Broad Institute.)
Suppressing Growth of Antibiotic-resistant Bacteria
To perform their research, the scientists isolated about 40 strains of bacteria from the stools of five healthy fecal donors. They then used those stool samples in fecal microbiota transplants to treat mice that had been infected with either Escherichia coli (E. coli) or Klebsiella, both forms of Enterobacteriaceae. The scientists tested different combinations of the 40 strains and identified 18 that suppressed the growth of Enterobacteriaceae.
“Antibiotic-resistant Enterobacteriaceae such as E. coli and Klebsiella bacteria are common in hospitals, where they can proliferate in the gut of patients and cause dangerous systemic infections that are difficult to treat. Some research suggests that Enterobacteriaceae also perpetuates inflammation in the intestine and infection by other microbes,” the Broad Institute news release notes.
The researchers discovered that Klebsiella changed the gene expression in carbohydrate uptake and metabolism in the Klebsiella-infected mice that were treated with the 18 beneficial strains. The gene expression included the downregulating of gluconate kinase and transporter genes, which revealed there is increased competition among gut bacteria for nutrients.
When combined, these 18 strains alleviated inflammation in the guts of the treated mice by depriving the harmful gut bacteria of carbohydrates. This non-antibiotic approach also prevented harmful bacteria from colonizing in the gut.
“In partnership with the Broad’s Metabolomics Platform, led by senior director and study co-author Clary Clish, PhD, they analyzed samples from pediatric patients with ulcerative colitis, looking for the presence of alternate gluconate pathway genes of gut microbes and fecal gluconate levels. They found higher levels of gluconate linked to more gluconate-consuming Enterobacteriaceae in samples from pediatric patients with ongoing inflammation, indicated by high levels of the protein calprotectin,” the study authors wrote in Nature.
“Together, the findings suggest that Enterobacteriaceae processes gluconate as a key nutrient and contributes to inflammation in patients. But when a gut microbiome includes the 18 helpful strains, they likely compete with Enterobacteriaceae for gluconate and other nutrient sources, limiting the proliferation of the harmful bacteria,” the scientists concluded.
Promising New Bacterial Therapies
This research could ultimately lead to the development of fecal microbiota transplants for individuals to eradicate antibiotic-resistant bacteria in a more objective and specific manner, with fewer side effects than current treatments.
“Harnessing these activities in the form of live bacterial therapies may represent a promising solution to combat the growing threat of proinflammatory, antimicrobial-resistant Enterobacteriaceae infection,” the scientists wrote in Nature.
According to the news release, they plan to continue research to “uncover the identity and function of unknown metabolites that contribute to gut health and inflammation.” The team hopes to discover how different bacteria compete with each other, and to develop microbial therapeutics that improve gut microbiome and curb bacterial infections.
More studies are needed to prove the efficacy of this type of fecal bacterial treatment. However, this research demonstrates how using nano processes enabled by new technologies to identify the actual work of proteins, RNA, and DNA in the body cheaply, faster, and with greater precision, will open doors to both therapeutic and diagnostic clinical laboratory biomarkers.
Researchers used CRISPR-based assays to develop new clinical laboratory point-of-care blood test which boasts accuracy, affordability, and accessibility
According to UPI, the test can “distinguish between influenza A and influenza B—the two main types of seasonal flu—as well as identifying more virulent strains like H1N1 and H3N2.”
Many research teams are working to develop paper-based diagnostic screening tests because of their lower cost to produce and usefulness in remote locations. Should this near-patient point-of-care test become clinically viable, it could mean shorter times to answer, enabling speedier diagnoses and earlier start of treatment.
It also means patient specimens do not have to be transported to a clinical laboratory for testing. And reduced cost per test makes it possible to test more people. This serves the public health aspect of monitoring outbreaks of influenza and other diseases and gives hope for improved treatment outcomes.
“Being able to tease apart what strain or subtype of influenza is infecting a patient has repercussions both for treating them and public health interventions, said Jon Arizti Sanz, PhD, co-lead study author and postdoctoral researcher at the Broad Institute of Harvard and MIT, in a Broad Institute news release.
“Ultimately, we hope these tests will be as simple as rapid antigen tests, and they’ll still have the specificity and performance of a nucleic acid test that would normally be done in a laboratory setting,” Cameron A. Myhrvold, PhD (above), Assistant Professor of Molecular Biology at Princeton University in New Jersey, told CIDRAP. Influenza tests that can be performed at the point of care and in remote locations may reduce the number of screening tests performed by clinical laboratories. (Photo copyright: Michael James Butts/Hertz Foundation.)
Her team developed their tests using Streamlined Highlighting of Infections to Navigate Epidemics (SHINE), “a clustered regularly interspaced short palindromic repeats (CRISPR)-based RNA detection platform,” the researchers wrote in their Journal of Molecular Diagnostics paper.
“SHINE has a runtime of 90 minutes, can be used at room temperature and only requires an inexpensive heat block to heat the reaction. The SHINE technology has previously been used to identify SARS-CoV-2 and later to distinguish between the Delta and Omicron variants,” Bioanalysis Zone reported.
“The test uses genetically engineered enzymes to identify specific sequences of viral RNA in samples,” the researchers told UPI. Originally designed to detect COVID-19, the team adapted the technology to detect influenza in 2022 “with the aim of creating a screening tool that could be used in the field or in clinics rather than hospitals or high-tech diagnostic labs,” they said.
Influenza A and B as well as H1N1 and H3N2 subtypes were the targets of the four SHINE assays. “When tested on clinical samples, these optimized assays achieved 100% concordance with quantitative RT-PCR. Duplex Cas12a/Cas13a SHINE assays were also developed to detect two targets simultaneously,” the researchers wrote in their paper.
The team used “20 nasal swabs from people with flu-like symptoms during the 2020-2021 flu season, nasal fluid from healthy people as the control, and 2016-2021 influenza sequences downloaded from the National Center for Biotechnology Information Influenza (NICB) database. They compared the results with those from quantitative reverse transcription-polymerase chain reaction (RT-PCR) tests,” CIDRAP reported.
The original 2020 test (shown above) takes 90 minutes to develop at room temperature. The test developers aim to drop this down to 15 minutes. In comparison, typical polymerase chain reaction (PCR) testing requires medical laboratories to have specialized equipment, trained staff, and prolonged processing times, the Broad Institute news release notes. (Photo copyright: Broad Institute.)
Implications of the New Tests
The ease of the new tests is an important development since approximately only 1% of individuals who come down with the flu see doctors for testing, according to the news release. And researchers had this in mind, looking at speed, accuracy, and affordability as a means to “improve outbreak response and infection care around the world,” UPI reported.
There are great benefits to strain differentiation that be achieved with the new test. Doctors are hopeful the test will help dial in the best treatment plans for patients since some strains are resistant to the antiviral medication oseltamivir (Tamiflu), UPI noted. This is significant since Tamiflu “is a common antiviral,” said Sanz in the Broad Institute news release.
“These assays have the potential to expand influenza detection outside of clinical laboratories for enhanced influenza diagnosis and surveillance,” the Journal of Molecular Diagnostics paper noted. This allows for more strategic treatment planning.
“Using a paper strip readout instead of expensive fluorescence machinery is a big advancement, not only in terms of clinical care but also for epidemiological surveillance purposes,” said Ben Zhang, an MD candidate in the Health Sciences and Technology at Harvard and co-first author of the study, in the Broad Institute news release.
Future Plans for Tests
“With further development, the test strip could be reprogrammed to distinguish between SARS-CoV-2 and flu and recognize swine flu and avian flu, including the H5N1 subtype currently causing an outbreak in US dairy cattle,” the study authors told CIDRAP.
The team is also looking at ways to help prevent H5N1 from crossing into human contamination, Sanz told UPI.
The new Princeton/MIT/Harvard tests echo the trend to bring in affordability and ease-of-use with accurate results as an end goal. Faster results mean the best treatments for each person can start sooner and may render the transport of specimens to a clinical laboratory as a second step unnecessary.
As research teams work to develop paper-based viral tests for their plethora of benefits, clinical laboratories will want to pay close attention to this development as it can have a big implication on assisting with future outbreaks.
Additional research is needed before these tests are going to be commonplace in homes worldwide, but this first step brings inspiration and hope of what’s to come.
In a follow-up story, investigative news team in Boston sends a reporter’s cheek swab sample to the same pet DNA testing lab: report states the reporter is part Malamute, Shar Pei, and Labrador Retriever
One pet DNA testing company returned results from human cheek swabs showing two different people were in fact part dog. The resulting local reporting calls into question the accuracy of DNA testing of our beloved furry friends and may impact the trust people have in clinical laboratory genetic testing as well.
Pet DNA analysis is nearly as popular as human DNA analysis. The market is expected to exceed $700 million by the end of the decade, according to Zion Market Research. But are customers getting their money’s worth? One CBS news station in Boston decided to find out.
Last year, the WBZ I-Team, the investigative part of a CBS News station in Boston, looked into the accuracy of pet DNA testing. They reported on a pet owner who questioned the DNA test results she received for her German Shepard. The report indicated that her dog had DNA from more than 10 breeds, besides German Shepard.
During their research, the WBZ investigative reporters learned that pet owners order these tests to reveal what one pet DNA testing company described as understanding “your dog’s unique appearance, behavior, and health.”
“So, the WBZ-TV I-Team came with more tests from different companies to compare. All came back with some German Shepherd, but the percentages ranged from 65% to just 29%. Aside from that, the three companies showed a puzzling hodgepodge of other breeds. One included Great Pyrenees, another came back with Siberian Husky, another listed Korean Jindo, and the list goes on,” WBZ News reported.
The owner of the German Shepard then sent two swab samples from her own cheeks to one of the pet DNA testing companies. The test results indicated that she was 40% Border Collie, 32% Cane Corso, and 28% Bulldog.
The company that performed that DNA testing—DNA My Dog—insisted to the WBZ I-Team that one of the pet owner’s cheek samples contained dog DNA, WBZ News reported.
“The second sample did in fact yield canine DNA. … The results provided would not be possible on a human sample,” Jessica Barnett, Director of Service Operations, DNA My Dog, told WBZ News.
This must have come as a shock to the pet owner, who is probably sure she is not part dog.
“I think that is a red flag for sure,” Lisa Moses, VMD (above), a veterinarian and bioethicist with Harvard Medical School, told WBZ News. “A company should know if they’ve in any basic way analyzed a dog’s DNA, that that is not a dog,” she said. One wonders what might happen if a dog’s DNA was secretly sent to a clinical laboratory performing human genetic testing. What might the results be? (Photo copyright: Harvard Medical School.)
Two Times is the Charm
To continue its investigation into this odd occurrence, the WBZ I-Team decided to repeat the test this year. They sent a cheek saliva sample from one of their own reporters to three different dog DNA testing companies.
According to the I-Team report, one company, Orivet, said the sample “failed to provide the data necessary to perform breed ID analysis. Another company, Wisdom Panel stated the sample “didn’t provide enough DNA to produce a reliable result.”
However, DNA My Dog once again reported that the human sample belonged to a canine. This time the company’s test reported that the DNA sample was 40% Alaskan Malamute, 35% Shar Pei, and 25% Labrador Retriever.
DNA My Dog did not respond to WBZ I-Team’s attempt to contact them for a comment, WBZ News reported.
Wild West of DNA Testing
“I personally do have concerns about the fact that, from a consumer standpoint, you don’t always know what you’re getting when you work with those companies,” said geneticist Elinor Karlsson, PhD, Director of the Vertebrate Genomics Group at the Broad Institute of MIT and Harvard, told WBZ News. “There’s not a lot of rules in this space.”
Karlsson is also founder and Chief Scientist at Darwin’s Ark, a nonprofit organization that combines dog genetics and behavior to advance the understanding of complex canine diseases. People participating in the initiative contribute data about their dogs to an open source database, which is then shared with researchers around the globe. To date, more than 44,000 dogs have been registered with the project.
She hopes that reports like the one from the WBZ I-Team will not dissuade interest in pet genetics, as the science does have significant value when performed correctly.
“We might be able to figure out which dogs are at risk of getting cancer, and screen them more often and be able to diagnose it earlier,” Karlsson said. “We might be able to develop new treatments for that cancer.”
“There isn’t necessarily a gold standard answer for what your dog is,” veterinarian and bioethicist Lisa Moses, VMD, co-director of the Capstone Program for the Master of Science in Bioethics Program at Harvard Medical School, told WBZ News. “A breed is something that we’ve decided, which is based upon essentially the way a dog looks. But that doesn’t necessarily mean that we’re going to know what their genes look like.”
DNA My Dog Awarded ‘Best Budget Dog DNA Test’
In February, US News and World Report published an article rating the best dog DNA tests of 2024. The magazine ranked the DNA My Dog Essential Breed ID Test as the “best budget dog DNA test on the market.” The test sells for $79.99. According to the company’s website, a simple cheek swab yields:
A complete breed breakdown,
Genetic health concerns,
Unique personality traits, and
Bonding tips for dogs and their owners.
“I worry about people making medical decisions … based on one of these tests,” Moses told WBZ News, which added that, “She and some of her colleagues have called on lawmakers to set standards and regulations for pet DNA labs, and to require them to share their databases with each other, for more consistent results.”
The investigation into pet DNA testing by the television news reporters in Boston is a reminder to clinical lab managers and pathologists that DNA testing can be problematic in many ways. Also, when consumers read news stories like this one about inaccurate canine DNA testing, it can cause them to question the accuracy of other types of DNA testing.
New gene-editing systems could provide markedly improved accuracy for DNA and RNA editing leading to new precision medicine tools and genetic therapies
In what may turn out to be a significant development in genetic engineering, researchers from three institutions have identified nearly 200 new systems that can be used for editing genes. It is believed that a number of these new systems can provide comparable or better accuracy when compared to CRISPER (Clustered Regularly Interspaced Short Palindromic Repeats), currently the most-used gene editing method.
CRISPR-Cas9 has been the standard tool for CRISPR gene editing and genetic engineering. However, publication of these new research findings are expected to give scientists better, more precise tools to edit genes. In turn, these developments could lead to new clinical laboratory tests and precision medicine therapies for patients with inherited genetic diseases.
“Best known as a powerful gene-editing tool, CRISPR actually comes from an inbuilt defense system found in bacteria and simple microbes called archaea. CRISPR systems include pairs of ‘molecular scissors’ called Cas enzymes, which allow microbes to cut up the DNA of viruses that attack them. CRISPR technology takes advantage of these scissors to cut genes out of DNA and paste new genes in,” according to Live Science.
In its article, New Atlas noted that the researchers looked to bacteria because “In nature, CRISPR is a self-defense tool used by bacteria.” They developed an algorithm—called FLSHclust—to conduct “a deep dive into three databases of bacteria, found in environments as diverse as Antarctic lakes, breweries, and dog saliva.”
In their paper, the researchers wrote, “We developed fast locality-sensitive hashing–based clustering (FLSHclust), a parallelized, deep clustering algorithm with linearithmic scaling based on locality-sensitive hashing. FLSHclust approaches MMseqs2, a gold-standard quadratic-scaling algorithm, in clustering performance. We applied FLSHclust in a sensitive CRISPR discovery pipeline and identified 188 previously unreported CRISPR-associated systems, including many rare systems.”
“In lab tests [the newfound CRISPR systems] demonstrated a range of functions, and fell into both known and brand new categories,” New Atlas reported.
“Some of these microbial systems were exclusively found in water from coal mines,” Soumya Kannan, PhD (above), a Graduate Fellow at MIT’s Zhang Lab and co-first author of the study, told New Atlas. “If someone hadn’t been interested in that, we may never have seen those systems.” These new gene-editing systems could lead to new clinical laboratory genetic tests and therapeutics for chronic diseases. (Photo copyright: MIT McGovern Institute.)
Deeper Look at Advancement
The CRISPR-Cas9 made a terrific impact when it was announced in 2012, earning a Nobel Prize in Chemistry.
Though CRISPR-Cas9 brought huge benefits to genetic research, the team noted in their Science paper that “existing methods for sequence mining lag behind the exponentially growing databases that now contain billions of proteins, which restricts the discovery of rare protein families and associations.
“We sought to comprehensively enumerate CRISPR-linked gene modules in all existing publicly available sequencing data,” the scientist continued. “Recently, several previously unknown biochemical activities have been linked to programmable nucleic acid recognition by CRISPR systems, including transposition and protease activity. We reasoned that many more diverse enzymatic activities may be associated with CRISPR systems, many of which could be of low abundance in existing [gene] sequence databases.”
Among the previously unknown gene-editing systems the researchers found were some belonging to the Type 1 CRISPR systems class. These “have longer guide RNA sequences than Cas9. They can be directed to their targets more precisely, reducing the risk of off-target edits—one of the main problems with CRISPR gene editing,” New Atlas reported.
“The authors also identified a CRISPR-Cas enzyme, Cas14, which cuts RNA precisely. These discoveries may help to further improve DNA- and RNA-editing technologies, with wide-ranging applications in medicine and biotechnology,” the Science paper noted.
Testing also showed these systems were able to edit human cells, meaning “their size should allow them to be delivered in the same packages currently used for CRISPR-Cas9,” New Atlas added.
Another newfound gene-editing system demonstrated “collateral activity, breaking down nucleic acids after binding to the target, New Atlas reported. SHERLOCK, a tool used to diagnose single samples of RNA or DNA to diagnose disease, previously utilized this system.
Additionally, New Atlas noted, “a type VII system was found to target RNA, which could unlock a range of new tools through RNA editing. Others could be adapted to record when certain genes are expressed, or as sensors for activity in cells.”
Looking Ahead
The strides in science from the CRISPR-Cas9 give a hint at what can come from the new discovery. “Not only does this study greatly expand the field of possible gene editing tools, but it shows that exploring microbial ecosystems in obscure environments could pay off with potential human benefits,” New Atlas noted.
“This study introduces FLSHclust as a tool to cluster millions of sequences quickly and efficiently, with broad applications in mining large sequence databases. The CRISPR-linked systems that we discovered represent an untapped trove of diverse biochemical activities linked to RNA-guided mechanisms, with great potential for development as biotechnologies,” the researchers wrote in Science.
How these newfound gene-editing tools and the new FLSHclust algorithm will eventually lead to new clinical laboratory tests and precision medicine diagnostics is not yet clear. But the discoveries will certainly improve DNA/RNA editing, and that may eventually lead to new clinical and biomedical applications.
Proof-of-concept study ‘highlights that using AI to integrate different types of clinically informed data to predict disease outcomes is feasible’ researchers say
Artificial intelligence (AI) and machine learning are—in stepwise fashion—making progress in demonstrating value in the world of pathology diagnostics. But human anatomic pathologists are generally required for a prognosis. Now, in a proof-of-concept study, researchers at Brigham and Women’s Hospital in Boston have developed a method that uses AI models to integrate multiple types of data from disparate sources to accurately predict patient outcomes for 14 different types of cancer.
The process also uncovered “the predictive bases of features used to predict patient risk—a property that could be used to uncover new biomarkers,” according to Genetic Engineering and Biotechnology News (GEN).
Should these research findings become clinically viable, anatomic pathologists may gain powerful new AI tools specifically designed to help them predict what type of outcome a cancer patient can expect.
“Experts analyze many pieces of evidence to predict how well a patient may do. These early examinations become the basis of making decisions about enrolling in a clinical trial or specific treatment regimens,” said Faisal Mahmood, PhD (above) in a Brigham press release. “But that means that this multimodal prediction happens at the level of the expert. We’re trying to address the problem computationally,” he added. Should they be proven clinically-viable through additional studies, these findings could lead to useful tools that help anatomic pathologists and clinical laboratory scientists more accurately predict what type of outcomes cancer patient may experience. (Photo copyright: Harvard.)
AI-based Prognostics in Pathology and Clinical Laboratory Medicine
The team at Brigham constructed their AI model using The Cancer Genome Atlas (TCGA), a publicly available resource which contains data on many types of cancer. They then created a deep learning-based algorithm that examines information from different data sources.
Pathologists traditionally depend on several distinct sources of data, such as pathology images, genomic sequencing, and patient history to diagnose various cancers and help develop prognoses.
For their research, Mahmood and his colleagues trained and validated their AI algorithm on 6,592 H/E (hematoxylin and eosin) whole slide images (WSIs) from 5,720 cancer patients. Molecular profile features, which included mutation status, copy-number variation, and RNA sequencing expression, were also inputted into the model to measure and explain relative risk of cancer death.
The scientists “evaluated the model’s efficacy by feeding it data sets from 14 cancer types as well as patient histology and genomic data. Results demonstrated that the models yielded more accurate patient outcome predictions than those incorporating only single sources of information,” states a Brigham press release.
“This work sets the stage for larger healthcare AI studies that combine data from multiple sources,” said Faisal Mahmood, PhD, Associate Professor, Division of Computational Pathology, Brigham and Women’s Hospital; and Associate Member, Cancer Program, Broad Institute of MIT and Harvard, in the press release. “In a broader sense, our findings emphasize a need for building computational pathology prognostic models with much larger datasets and downstream clinical trials to establish utility.”
Future Prognostics Based on Multiple Data Sources
The Brigham researchers also generated a research tool they dubbed the Pathology-omics Research Platform for Integrative Survival Estimation (PORPOISE). This tool serves as an interactive platform that can yield prognostic markers detected by the algorithm for thousands of patients across various cancer types.
The researchers believe their algorithm reveals another role for AI technology in medical care, but that more research is needed before their model can be implemented clinically. Larger data sets will have to be examined and the researchers plan to use more types of patient information, such as radiology scans, family histories, and electronic medical records in future tests of their AI technology.
“Future work will focus on developing more focused prognostic models by curating larger multimodal datasets for individual disease models, adapting models to large independent multimodal test cohorts, and using multimodal deep learning for predicting response and resistance to treatment,” the Cancer Cell paper states.
“As research advances in sequencing technologies, such as single-cell RNA-seq, mass cytometry, and spatial transcriptomics, these technologies continue to mature and gain clinical penetrance, in combination with whole-slide imaging, and our approach to understanding molecular biology will become increasingly spatially resolved and multimodal,” the researchers concluded.
Anatomic pathologists may find the Brigham and Women’s Hospital research team’s findings intriguing. An AI tool that integrates data from disparate sources, analyzes that information, and provides useful insights, could one day help them provide more accurate cancer prognoses and improve the care of their patients.
