Collected data could give healthcare providers and clinical laboratories a practical view of individuals’ oral microbiota and lead to new diagnostic assays
When people hear about microbiome research, they usually think of the study of gut bacteria which Dark Daily has covered extensively. However, this type of research is now expanding to include more microbiomes within the human body, including the oral microbiome—the microbiota living in the human mouth.
One example is coming from Genefitletics, a biotech company based in New Delhi, India. It recently launched ORAHYG, the first and only (they claim) at-home oral microbiome functional activity test available in Asia. The company is targeting the direct-to-consumer (DTC) testing market.
According to the Genefitletics website, the ORAHYG test can decode the root causes of:
“Using oral microbial gene expression sequencing technology and its [machine learning] model, [Genefitletics] recently debuted its oral microbiome gene expression solution, which bridges the gap between dentistry and systemic inflammation,” ETHealthworld reported.
“The molecular insights from this test would give an unprecedented view of functions of the oral microbiome, their interaction with gut microbiome and impact on metabolic, cardiovascular, cognitive, skin, and autoimmune health,” BioSpectrum noted.
“Microbes, the planet Earth’s original inhabitants, have coevolved with humanity, carry out vital biological tasks inside the body, and fundamentally alter how we think about nutrition, medicine, cleanliness, and the environment,” Sushant Kumar (above), founder and CEO of Genefitletics, told the Economic Times. “This has sparked additional research over the past few years into the impact of the trillions of microorganisms that inhabit the human body on our health and diverted tons of funding into the microbiome field.” Clinical laboratories may eventually see an interest and demand for testing of the oral microbiome. (Photo copyright: ETHealthworld.)
Imbalanced Oral Microbiome Can Trigger Disease
The term microbiome refers to the tiny microorganisms that reside on and inside our bodies. A high colonization of these microorganisms—including bacteria, fungi, yeast, viruses, and protozoa—live in our mouths.
“Mouth is the second largest and second most diverse colonized site for microbiome with 770 species comprising 100 billion microbes residing there,” said Sushant Kumar, founder and CEO of Genefitletics, BioSpectrum reported. “Each place inside the mouth right from tongue, throat, saliva, and upper surface of mouth have a distinctive and unique microbiome ecosystem. An imbalanced oral microbiome is said to trigger onset and progression of type 2 diabetes, arthritis, heart diseases, and even dementia.”
The direct-to-consumer ORAHYG test uses a saliva sample taken either by a healthcare professional or an individual at home. That sample is then sequenced through Genefitletics’ gene sequencing platform and the resulting biological data set added to an informatics algorithm.
Genefitletics’ machine-learning platform next converts that information into a pre-symptomatic molecular signature that can predict whether an individual will develop a certain disease. Genefitletics then provides that person with therapeutic and nutritional solutions that can suppress the molecules that are causing the disease.
“The current industrial healthcare system is really a symptom care [system] and adopts a pharmaceutical approach to just make the symptoms more bearable,” Kumar told the Economic Times. “The system cannot decode the root cause to determine what makes people develop diseases.”
Helping People Better Understand their Health
Founded in 2019, Genefitletics was created to pioneer breakthrough discoveries in microbial science to promote better health and increase longevity in humans. The company hopes to unravel the potential of the oral microbiome to help people fend off illness and gain insight into their health.
“Microorganisms … perform critical biological functions inside the body and transform our approach towards nutrition, medicine, hygiene and environment,” Kumar told CNBC. “It is important to understand that an individual does not develop a chronic disease overnight.
“It starts with chronic inflammation which triggers pro-inflammatory molecular indications. Unfortunately, these molecular signatures are completely invisible and cannot be measured using traditional clinical grade tests or diagnostic investigations,” he added. “These molecular signatures occur due to alteration in gene expression of gut, oral, or vaginal microbiome and/or human genome. We have developed algorithms that help us in understanding these alterations way before the clinical symptoms kick in.”
Genefitletics plans to utilize individuals’ collected oral microbiome data to determine their specific nutritional shortcomings, and to develop personalized supplements to help people avoid disease.
The company also produces DTC kits that analyze gut and vaginal microbiomes as well as a test that is used to evaluate an infant’s microbiome.
“The startup wants to develop comparable models to forecast conditions like autism, PCOS [polycystic ovarian syndrome], IBD [Inflammatory bowel disease], Parkinson’s, chronic renal [kidney] disease, anxiety, depression, and obesity,” the Economic Times reported.
Time will tell whether the oral microbiome tests offered by this company prove to be clinically useful. Certainly Genefitletics hopes its ORAHYG test can eventually provide healthcare providers—including clinical laboratory professionals—with a useful view of the oral microbiome. The collected data might also help individuals become aware of pre-symptomatic conditions that make it possible for them to seek confirmation of the disease and early treatment by medical professionals.
Research findings could lead to new biomarkers for genetic tests and give clinical laboratories new capabilities to diagnose different health conditions
New insights continue to emerge about “junk DNA” (aka, non-coding DNA). For pathologists and clinical laboratories, these discoveries may have value and eventually lead to new biomarkers for genetic testing.
One recent example comes from researchers at Stanford Medicine in California who recently learned how non-coding DNA—which makes up 98% of the human genome—affects gene expression, the function that leads to observable characteristics in an organism (phenotypes).
The research also could lead to a better understanding of how short tandem repeats (STRs)—the number of times a gene is copied into RNA for protein use—affect gene expression as well, according to Stanford.
“We’ve known for a while that short tandem repeats or STRs, aren’t junk because their presence or absence correlates with changes in gene expression. But we haven’t known how they exert these effects,” said study lead Polly Fordyce, PhD (above), Associate Professor of Bioengineering and Genetics at Stanford University, in a news release. The research could lead to new clinical laboratory biomarkers for genetic testing. (Photo copyright: Stanford University.)
To Bind or Not to Bind
In their Science paper, the Stanford researchers described an opportunity to explore a new angle to transcription factors binding to some sequences, also known as sequence motifs.
“Researchers have spent a lot of time characterizing these transcription factors and figuring out which sequences—called motifs—they like to bind to the most,” said the study lead Polly Fordyce, PhD, Associate Professor of Bioengineering and Genetics at Stanford University, in a Stanford Medicine news release.
“But current models don’t adequately explain where and when transcription factors bind to non-coding DNA to regulate gene expression. Sometimes, no transcription factor is attached to something that looks like a perfect motif. Other times, transcription factors bind to stretches of DNA that aren’t motifs,” the news release explains.
Transcription factors are “like light switches that can turn genes on or off depending on what cells need,” notes a King’s College LondonEDIT Labblog post.
But why do transcription factors target some places in the genome and not others?
“To solve the puzzle of why transcription factors go to some places in the genome and not to others, we needed to look beyond the highly preferred motifs,” Fordyce added. “In this study, we’re showing that the STR sequence around the motif can have a really big effect on transcription factor binding, providing clues as to what these repeated sequences might be doing.”
Such information could aid in understanding certain hereditary conditions and diseases.
“Variations in STR length have been associated with changes in gene expression and implicated in several complex phenotypes such as schizophrenia, cancer, autism, and Crohn’s disease. However, the mechanism by which STRs affect transcription remains unknown,” the researchers wrote in Science.
Special Assays Explore Binding
According to their paper, the research team turned to the Fordyce Lab’s previously developed microfluidic binding assays (MITOMI, k–MITOMI, and STAMMP) to analyze the impact of different DNA sequences on transcription factor binding.
“In the experiment we asked, ‘How do these changes impact the strength of transcription factor binding?’ We saw a surprisingly large effect. Varying the STR sequence around a motif can have a 70-fold impact on the binding,” Fordyce wrote.
In an accompanying Science article titled, “Repetitive DNA Regulates Gene Expression,” Thomas Kuhlman, PhD, Assistant Professor, Physics and Astronomy, University of California, Riverside, wrote that the study “demonstrates that STRs exert their effects by directly binding transcription factor proteins, thus explaining how STRs might influence gene expression in both normal and diseased states.”
“This research unveils, for the first time, the intricate connection between how variants in the non-coding genome affect genes that are associated with blood pressure and with hypertension. What we’ve created is a kind of functional map of the regulators of blood pressure genes, “said Philipp Maass, PhD, Lead Researcher and Assistant Professor Molecular Genetics, University of Toronto, in a news release.
The research team used massively parallel reporter assay (MPRA) technology to analyze 4,608 genetic variants associated with blood pressure.
The findings could aid precision medicine for cardiovascular health and may possibly be adopted to other conditions, according to The Hospital for Sick Children.
“The variants we have characterized in the non-coding genome could be used as genomic markers for hypertension, laying the groundwork for future genetic research and potential therapeutic targets for cardiovascular disease,” Maass noted.
Why All the ‘Junk’ DNA?
Clinical laboratory scientists may wonder why genetic research has primarily focused on 20,000 genes within the genome, leaving the “junk” DNA for later investigation. So did researchers at Harvard University.
“After the Human Genome Project, scientists found that there were around 20,000 genes within the genome, a number that some researchers had already predicted. Remarkably, these genes comprise only about 1-2% of the three billion base pairs of DNA. This means that anywhere from 98-99% of our entire genome must be doing something other than coding for proteins,” they wrote in a blog post.
“Imagine being given multiple volumes of encyclopedias that contained a coherent sentence in English every 100 pages, where the rest of the space contained a smattering of uninterpretable random letters and characters. You would probably start to wonder why all those random letters and characters were there in the first place, which is the exact problem that has plagued scientists for decades,” they added.
Not only is junk DNA an interesting study subject, but ongoing research may also produce useful new biomarkers for genetic diagnostics and other clinical laboratory testing. Thus, medical lab professionals may want to keep an eye on new developments involving non-coding DNA.
In addition to viruses, wastewater analysis can also be used to detect the presence of chemical substances such as opioids
Wastewater surveillance and analysis continues to be a useful tool for detecting the prevalence of viruses such as SARS-CoV-2, influenza, and respiratory syncytial virus (RSV) in a community. Perhaps more importantly, wastewater surveillance can fill in gaps where clinical laboratory testing data may be days or weeks behind the true spread of viral infections.
One sign of the value of testing wastewater for infectious diseases is the fact that government officials are financing a continuing program of wastewater testing. In September, the federal Centers for Disease Control and Prevention (CDC) awarded a contract to conduct wastewater surveillance/analysis worth millions of dollars to Verily Life Sciences, a Google company, rather than renewing its contract with Biobot Analytics, which had been doing the work since 2020. One interesting twist in the award of this contract is how an ensuing dispute pulled the plug on a significant portion of the wastewater analysis in this country.
In their September Morbidity and Mortality Weekly Report (MMWR), the CDC highlighted a CDC study during which wastewater samples were taken from 40 wastewater treatment plants located in Wisconsin’s three largest cities. The samples were collected weekly and tested for influenza and RSV. The findings were then compared with data regarding emergency department (ED) visits for those diseases.
The CDC found that higher detections of flu and RSV were associated with higher rates of ED visits for both illnesses. The study also suggests that wastewater might detect the spread of these viruses earlier than ED visit data alone.
“During the COVID-19 pandemic, wastewater surveillance for SARS-CoV-2 provided valuable insight into community incidence of COVID-19,” said Peter DeJonge, PhD (above), a CDC Career Epidemiology Field Officer, in an interview with Infectious Disease Special Edition. “[The CDC’s] report supports the idea that wastewater surveillance also has the potential to serve as a useful method with which to track community spread of influenza and RSV.” Local clinical laboratories are also involved in the CDC’s wastewater surveillance programs. (Photo copyright: CDC.)
Keeping Communities Informed about Spread of Viral Infections
The CDC’s study was conducted from August 2022 to March 2023. The wastewater samples from all three cities tested positive for the viruses in advance of increases in ED visits. After the ED visits for those viruses had subsided, the viral material remained in sewersheds for up to three months.
“Both influenza and RSV can cause substantial amounts of illness, hospitalization, and even death during annual epidemics, which often occur during winter months in the US,” Peter DeJonge, PhD, a CDC Career Epidemiology Field Officer assigned to the Chicago Department of Public Health, told Infectious Disease Special Edition (IDSE). “Clinical providers and public health officials benefit from surveillance data to understand when and where these diseases are spreading in a community each year. This type of data can help prepare clinics [and clinical laboratories] for anticipated cases, tailor public health messaging, and encourage timely vaccination.”
“The collective burden from these respiratory viruses is staggering. With these viruses circulating simultaneously and potentially shifting in seasonality and severity, communities must be able to understand the full impact of each of these illnesses to inform awareness and public health responses that can prevent infections, hospitalizations, and even deaths,” said Mariana Matus, PhD, CEO and cofounder of Biobot Analytics, in an August press release announcing the launch of a “Respiratory Illnesses Panel” that will monitor wastewater for Influenzas A and B (seasonal flu), Respiratory Syncytial Virus (RSV), and SARS-CoV-2 (COVID-19).
“Traditional testing methods for these illnesses do not provide a comprehensive picture of the number of people infected due to inaccurate reporting, as well as asymptomatic or misdiagnosed cases,” Matus continued. “By monitoring wastewater concurrently for influenza, RSV, and SARS-CoV-2, we can fill in these gaps and provide important information to communities.”
CDC Moves to Change Wastewater Surveillance Contractor Mid-stream
As new variants of SARS-CoV-2 emerge, a recent contract dispute may be the cause of a time delay in efforts to perform wastewater surveillance for the disease, as well as for other viral infections, according to Politico.
The CDC’s move to replace Biobot Analytics with Verily Life Sciences to do wastewater surveillance has led to Biobot filing a protest with the Government Accountability Office (GAO).
According to World Socialist Web Site (WSWS), “The scope of the [Biobot] contract [to provide extended data for the public health agency’s National Wastewater Surveillance System (NWSS)] included data from more than 400 locations from over 250 counties across the entire United States, covering 60 million people. On top of this, Biobot also conducted genomic sequencing to identify the latest variants in circulation.”
About one quarter of the wastewater testing sites in the country have been shut down due to Biobot’s contract being suspended in September. The remaining 1,200 sites that are not covered under the original contract will continue wastewater testing, Politico reported.
The GAO hopes to have a decision on the contract dispute in January. Verily says it is ready to proceed with testing in all locations and already has its infrastructure in place.
“We are committed to working with the CDC to advance the goals of the … testing program, initiate testing on the samples already delivered when allowed to resume work, and make wastewater data available as quickly as possible,” Bradley White, PhD, Principal Scientist/Director at Verily, told Politico.
Under the terms of Verily’s contract, the company will collect samples from wastewater treatment centers cross the county and analyze the samples for COVID-19 and the mpox (monkey pox) virus.
This contract marks the first agreement between the CDC and Verily.
The CDC has not disclosed why it decided to change contractors, but it is probable that cost may have been played a role in the decision. Verily’s contract is for $38 million over the course of five years and Biobot’s most recent contract was for around $31 million for a period of less than 18 months, Politico reported.
In a LinkedIn post, Matus reported that Biobot had already laid off 35% of its staff due to the contract decision by the CDC.
Competition in Wastewater Surveillance Market
When seeking viruses in wastewater, scientists use gene-based detection methods to locate and amplify genetic signs of pathogens. But public health officials are just beginning to tap into the potential opportunities that may exist in the analysis of data present in wastewater.
Wastewater surveillance is also being looked at as a way to combat America’s opioid epidemic.
“Wastewater surveillance is becoming more mature and more mainstream month after month, year over year,” Matus told Time.
Thus, regardless of which companies end up working with the CDC, it appears that wastewater surveillance and analysis, which requires a great deal of clinical laboratory testing, will continue to help fight the spread of deadly viral infections, as well as possibly the nation’s drug epidemic.
Doctors report difficulty differentiating COVID-19 from other viral infections, impacting clinical laboratory test orders
Because the SARS-CoV-2 coronavirus is in the same family of viruses that cause the common cold and influenza, virologists expected this virus—which caused the global COVID-19 pandemic—would evolve and mutate into a milder form of infection. Early evidence from this influenza season seems consistent with these expectations in ways that will influence how clinical laboratories offer tests for different respiratory viruses.
While new variants of the SARS-CoV-2 virus continue to appear, indications are that early in this flu season individuals infected with the more recent variants are experiencing milder symptoms when compared to the last few years. Doctors report they find it increasingly difficult to distinguish COVID-19 infections from allergies or the common cold because patients’ symptoms are less severe, according to NBC News.
This, of course, makes it challenging for doctors to know the most appropriate clinical laboratory tests to order to help them make accurate diagnoses.
“It isn’t the same typical symptoms that we were seeing before. It’s a lot of congestion, sometimes sneezing, usually a mild sore throat,” Erick Eiting, MD, Vice Chair of Operations for Emergency Medicine at Mount Sinai Hospital in New York City, told NBC News. “Just about everyone who I’ve seen has had really mild symptoms. The only way that we knew that it was COVID was because we happened to be testing them.” Knowing which tests for respiratory viruses that clinical laboratories need to perform may soon be the challenge for doctors. (Photo copyright: Mt. Sinai.)
Milder COVID-19 Symptoms Follow a Pattern
Previous hallmarks of a COVID-19 infection included:
Loss of taste,
loss of smell,
dry cough,
fever,
sore throat,
diarrhea,
body aches,
headaches.
However, physicians now observe milder symptoms of the infection that follow a distinct pattern and which are mostly concentrated in the upper respiratory tract.
Grace McComsey, MD, Vice President of Research and Associate Chief Scientific Officer at University Hospitals Health System (UH) in Cleveland, Ohio, told NBC News that some patients have described their throat pain as “a burning sensation like they never had, even with Strep in the past.”
“Then, as soon as the congestion happens, it seems like the throat gets better,” she added.
In addition to the congestion, some patients are experiencing:
headache,
fever,
chills,
fatigue,
muscle aches,
post-nasal drip.
McComsey noted that fatigue and muscle aches usually only last a couple of days, but that the congestion can sometimes last a few weeks. She also estimated that only around 10-20% of her newest COVID patients are losing their sense of smell or taste, whereas early in the pandemic that number was closer to 60-70% of her patients.
Doctors also noted that fewer patients are requiring hospitalization and that many recover without the use of antivirals or other treatments.
“Especially since July, when this recent mini-surge started, younger people that have upper respiratory symptoms—cough, runny nose, sore throat, fever and chills—99% of the time they go home with supportive care,” said Michael Daignault, MD, an emergency physician at Providence Saint Joseph Medical Center in Burbank, California.
Milder SARS-CoV-2 Variants Should Still be Taken Seriously
Doctors have varying opinions regarding why the current COVID-19 variants are milder. Some believe the recent variants simply aren’t as good at infecting the lungs as previous variants.
“Overall, the severity of COVID-19 is much lower than it was a year ago and two years ago,” Dan Barouch, MD, PhD, Director of the Center for Virology and Vaccine Research at Beth Israel Deaconess Medical Center, told NBC News. “That’s not because the variants are less robust. It’s because the immune responses are higher.”
McComsey added that she doesn’t think mild cases should be ignored as she is still seeing new cases of long COVID with rapid heart rate and exercise intolerance being among the most common lingering symptoms. Re-infections also add to the risks associated with long COVID.
“What we’re seeing in long COVID clinics is not just the older strains that continue to be symptomatic and not getting better—we’re adding to that number with the new strain as well,” McComsey said. “That’s why I’m not taking this new wave any less seriously.”
Clinical Laboratory COVID-19 Testing May Decrease
According to Andrew Read, PhD, Interim Senior Vice President for Research and Evan Pugh University Professor of Biology and Entomology at Pennsylvania State University, there is nothing unexpected or startling about the coronavirus acquiring new mutations.
“When a mutation confers an interesting new trick that’s got an advantage, it’s going to be popping up in many different places,” Read told the New York Times. “Everything we see is just consistent with how you imagine virus evolution proceeding in a situation where a new virus has jumped into a novel host population.”
Data from the Centers for Disease Control and Prevention’s COVID-19 Data Tracker—which reports weekly hospitalizations, deaths, emergency department (ED) visits, and COVID-19 test positivity results—shows infection trends fluctuating, but overall, they are decreasing.
For the week of October 21, 2023, there were 16,186 hospitalizations due to COVID-19 compared to the highest week recorded (January 15, 2022) with 150,674 hospitalizations nationwide.
The highest number of deaths reported in a single week were 25,974 for the week of January 8, 2021, while 637 patients perished from COVID-19 during the week of October 21, 2023.
In January of 2021, COVID accounted for 13.8% of all ED visits and in October 2023, COVID-19 was responsible for 1.3% of ED visits.
“What I think we’re seeing is the virus continuing to evolve, and then leading to waves of infection, hopefully mostly mild in severity,” Barouch told The New York Times.
As severity of COVID-19 infections continues to fall, so, presumably, will demand for COVID-19 testing which has been a source of revenue for clinical laboratories for several years.
Genetic engineers at the lab used the new tool to generate a catalog of 71 million possible missense variants, classifying 89% as either benign or pathogenic
Genetic engineers continue to use artificial intelligence (AI) and deep learning to develop research tools that have implications for clinical laboratories. The latest development involves Google’s DeepMind artificial intelligence lab which has created an AI tool that, they say, can predict whether a single-letter substitution in DNA—known as a missense variant (aka, missense mutation)—is likely to cause disease.
The Google engineers used their new model—dubbed AlphaMissense—to generate a catalog of 71 million possible missense variants. They were able to classify 89% as likely to be either benign or pathogenic mutations. That compares with just 0.1% that have been classified using conventional methods, according to the DeepMind engineers.
This is yet another example of how Google is investing to develop solutions for healthcare and medical care. In this case, DeepMind might find genetic sequences that are associated with disease or health conditions. In turn, these genetic sequences could eventually become biomarkers that clinical laboratories could use to help physicians make earlier, more accurate diagnoses and allow faster interventions that improve patient care.
“AI tools that can accurately predict the effect of variants have the power to accelerate research across fields from molecular biology to clinical and statistical genetics,” wrote Google DeepMind engineers Jun Cheng, PhD (left), and Žiga Avsec, PhD (right), in a blog post describing the new tool. Clinical laboratories benefit from the diagnostic biomarkers generated by this type of research. (Photo copyrights: LinkedIn.)
AI’s Effect on Genetic Research
Genetic experiments to identify which mutations cause disease are both costly and time-consuming, Google DeepMind engineers Jun Cheng, PhD, and Žiga Avsec, PhD, wrote in a blog post. However, artificial intelligence sped up that process considerably.
“By using AI predictions, researchers can get a preview of results for thousands of proteins at a time, which can help to prioritize resources and accelerate more complex studies,” they noted.
Of all possible 71 million variants, approximately 6%, or four million, have already been seen in humans, they wrote, noting that the average person carries more than 9,000. Most are benign, “but others are pathogenic and can severely disrupt protein function,” causing diseases such as cystic fibrosis, sickle-cell anemia, and cancer.
“A missense variant is a single letter substitution in DNA that results in a different amino acid within a protein,” Cheng and Avsec wrote in the blog post. “If you think of DNA as a language, switching one letter can change a word and alter the meaning of a sentence altogether. In this case, a substitution changes which amino acid is translated, which can affect the function of a protein.”
In the Google DeepMind study, AlphaMissense predicted that 57% of the 71 million variants are “likely benign,” 32% are “likely pathogenic,” and 11% are “uncertain.”
The AlphaMissense model is adapted from an earlier model called AlphaFold which uses amino acid genetic sequences to predict the structure of proteins.
“AlphaMissense was fed data on DNA from humans and closely related primates to learn which missense mutations are common, and therefore probably benign, and which are rare and potentially harmful,” The Guardian reported. “At the same time, the program familiarized itself with the ‘language’ of proteins by studying millions of protein sequences and learning what a ‘healthy’ protein looks like.”
The model assigned each variant a score between 0 and 1 to rate the likelihood of pathogenicity [the potential for a pathogen to cause disease]. “The continuous score allows users to choose a threshold for classifying variants as pathogenic or benign that matches their accuracy requirements,” Avsec and Cheng wrote in their blog post.
However, they also acknowledged that it doesn’t indicate exactly how the variation causes disease.
The engineers cautioned that the predictions in the catalog are not intended for clinical use. Instead, they “should be interpreted with other sources of evidence.” However, “this work has the potential to improve the diagnosis of rare genetic disorders, and help discover new disease-causing genes,” they noted.
Genomics England Sees a Helpful Tool
BBC noted that AlphaMissense has been tested by Genomics England, which works with the UK’s National Health Service. “The new tool is really bringing a new perspective to the data,” Ellen Thomas, PhD, Genomics England’s Deputy Chief Medical Officer, told the BBC. “It will help clinical scientists make sense of genetic data so that it is useful for patients and for their clinical teams.”
AlphaMissense is “a big step forward,” Ewan Birney, PhD, Deputy Director General of the European Molecular Biology Laboratory (EMBL) told the BBC. “It will help clinical researchers prioritize where to look to find areas that could cause disease.”
Other experts, however, who spoke with MIT Technology Review were less enthusiastic.
Heidi Rehm, PhD, co-director of the Program in Medical and Population Genetics at the Broad Institute, suggested that the DeepMind engineers overstated the certainty of the model’s predictions. She told the publication that she was “disappointed” that they labeled the variants as benign or pathogenic.
“The models are improving, but none are perfect, and they still don’t get you to pathogenic or not,” she said.
“Typically, experts don’t declare a mutation pathogenic until they have real-world data from patients, evidence of inheritance patterns in families, and lab tests—information that’s shared through public websites of variants such as ClinVar,” the MIT article noted.
Is AlphaMissense a Biosecurity Risk?
Although DeepMind has released its catalog of variations, MIT Technology Review notes that the lab isn’t releasing the entire AI model due to what it describes as a “biosecurity risk.”
The concern is that “bad actors” could try using it on non-human species, DeepMind said. But one anonymous expert described the restrictions “as a transparent effort to stop others from quickly deploying the model for their own uses,” the MIT article noted.
And so, genetics research takes a huge step forward thanks to Google DeepMind, artificial intelligence, and deep learning. Clinical laboratories and pathologists may soon have useful new tools that help healthcare provider diagnose diseases. Time will tell. But the developments are certain worth watching.
Cellular healthcare is an approach that goes beyond clinical laboratory testing to identify the location of specific cancer cells and aid in treatment decisions
Advances in synthetic biology and genetic engineering are leading to development of bacterial biosensors that could eventually aid pathologists and clinical laboratories in diagnosis of many types of cancers.
One recent example comes from researchers at the University of California San Diego (UCSD) who worked with colleagues in Australia to engineer bacteria that work as “capture agents” and bind to tumorous material.
The KRAS gene is associated with colorectal cancer. The researchers named their development the Cellular Assay for Targeted CRISPR-discriminated Horizontal gene transfer (CATCH).
CATCH successfully detected cancer in the colons of mice. The researchers believe it could be used to diagnose cancers, as well as infections and other diseases, in humans as well, according to a UCSD news release.
“If bacteria can take up DNA, and cancer is defined genetically by a change in its DNA, then, theoretically, bacteria could be engineered to detect cancer,” gastroenterologist Daniel Worthley, PhD, a cancer researcher at Colonoscopy Clinic in Brisbane, Australia, told MedicalResearch.com. This research could eventually provide clinical laboratories and anatomic pathologists with new tools to use in diagnosing certain types of cancer. (Photo copyright: Colonoscopy Clinic.)
Tapping Bacteria’s Natural Competence
In their Science paper, the researchers acknowledged other synthetic biology achievements in cellular biosensors aimed at human disease. But they noted that more can be done by leveraging the “natural competence” skill of bacteria.
“Biosensors have not yet been engineered to detect specific extracellular DNA sequences and mutations. Here, we engineered naturally competent Acinetobacter baylyi (A. baylyi) to detect donor DNA from the genomes of colorectal cancer cells, organoids, and tumors,” they wrote.
“Many bacteria can take up DNA from their environment, a skill known as natural competence,” said Rob Cooper, PhD, co-first author of the study and a scientist at US San Diego’s Synthetic Biology Institute, in the news release. A. baylyi is a type of bacteria renowned for success in doing just that, the NCI article pointed out.
This enabled them to explore “free-floating DNA sequences on a genomic level.”
Those sequences were compared to “known cancer DNA sequences.”
A. baylyi (genetically modified) was tested on its ability to detect “mutated and healthy KRAS DNA.”
Only bacteria that had “taken up mutated copies of KRAS … would survive treatment with a specific drug.”
“It was incredible when I saw the bacteria that had taken up the tumor DNA under the microscope. The mice with tumors grew green bacterial colonies that had acquired the ability to be grown on antibiotic plates,” said Josephine Wright, PhD, Senior Research Fellow, Gut Cancer Group, South Australian Health and Medical Research Institute (SAHMRI), in the news release.
Detecting DNA from Cancer Cells In Vitro and in Mice
Findings in vitro and in mice include the following:
The engineered bacteria enabled detection of DNA with KRAS G12D from colorectal cancer cells made in the lab, NCI reported.
When mice were injected with colorectal cancer cells, the researchers’ technology found tumor DNA, Engadget reported.
The study adds to existing knowledge of horizontal gene transfer from bacteria to bacteria, according to UCSD.
“We observed horizontal gene transfer from the tumor to the sensor bacteria in our mouse model of colorectal cancer. This cellular assay for targeted, CRISPR-discriminated horizontal gene transfer (CATCH) enables the biodetection of specific cell-free DNA,” the authors wrote in Science.
“Colorectal cancer seemed a logical proof of concept as the colorectal lumen is full of microbes and, in the setting of cancer, full of tumor DNA,” gastroenterologist Daniel Worthley, PhD, a cancer researcher at Colonoscopy Clinic in Brisbane, Australia, told MedicalResearch.com.
Finding More Cancers and Treatment
More research is needed before CATCH is used in clinical settings. The scientists are reportedly planning on adapting CATCH to multiple bacteria that can locate other cancers and infections.
“The most exciting aspect of cellular healthcare … is not in the mere detection of disease. A laboratory can do that,” wrote Worthley in The Conversation. “But what a laboratory cannot do is pair the detection of disease (a diagnosis) with the cells actually responding to the disease [and] with appropriate treatment.
“This means biosensors can be programmed so that a disease signal—in this case, a specific sequence of cell-free DNA—could trigger a specific biological therapy, directly at the spot where the disease is detected in real time,” he added.
Clinical laboratory scientists, pathologists, and microbiologists may want to stay abreast of how the team adapts CATCH, and how bacterial biosensors in general continue to develop to aid diagnosis of diseases and improve ways to target treatment.
