Though they are a mystery, once solved, Obelisks could lead to new biomarkers for clinical laboratory testing
Microbiologists and clinical laboratories know that human microbiota play many important roles in the body. Now, scientists from Stanford University have discovered an entirely new class of “viroid-like” lifeforms residing inside the human body. The researchers detected their presence in both the gut microbiome and saliva samples. Most interesting of all, the researchers are not sure what the lifeforms actually are.
The Stanford researchers, led by PhD student Ivan Zheludev, called the new discovery “Obelisks” due to their RNA structures, which are short and can fold into structures that resemble rods.
The scientists believe the Obelisks went undetected until now in the human microbiome due to their compact genetic elements, which are only around 1,000 characters or nucleotides in size. A typical human DNA structure consists of around three billion nucleotides.
In an article they published on the biology preprint server bioRxiv titled, “Viroid-like Colonists of Human Microbiomes,” the Stanford researchers wrote, “Here, we describe the ‘Obelisks,’ a previously unrecognized class of viroid-like elements that we first identified in human gut metatranscriptomic data. … Obelisks comprise a class of diverse RNAs that have colonized and gone unnoticed in human and global microbiomes.”
The researchers discovered that Obelisks “form their own distinct phylogenetic group with no detectable sequence or structural similarity to known biological agents.”
This is yet another example of how researchers are digging deeper into human biology and finding things never before identified or isolated.
“I am really impressed by the approach. The authors were really creative,” computational biologist Simon Roux, PhD (above) of the Department of Energy (DEO) Joint Genome Institute at Lawrence Berkeley National Laboratory told Science in response to the Stanford researcher’s published findings. “I think this [work] is one more clear indication that we are still exploring the frontiers of this viral universe. This is one of the most exciting parts of being in this field right now. We can see the picture of the long-term evolution of viruses on Earth start to slowly emerge.” How these findings might eventually spark new biomarkers for clinical laboratory testing remains to be seen. (Photo copyright: Berkeley Lab.)
Researchers Bewildered by Obelisks
In their study, “Zheludev and team searched 5.4 million datasets of published genetic sequences and identified almost 30,000 different Obelisks. They appeared in about 10% of the human microbiomes the team examined,” Science reported.
The Stanford researchers found that various types of Obelisks seem to inhabit different areas of the body. In one dataset, the Obelisks were found in half of the oral samples.
The function of Obelisks is unknown, but their discovery is bewildering experts.
Rod-like secondary structures encompassing the entire genome, and
Open reading frames coding for a novel protein superfamily, which the researchers dubbed “Oblins.”
At least half of the genetic material of the Obelisks was taken up by these Oblins. The researchers suspect those proteins may be involved in the replication process of the newly-discovered lifeforms.
The Oblins are also significantly larger than other genetic molecules that live inside cells and they do not have the genes to create protein shells that RNA viruses live within when they are outside of cells.
“Obelisks, therefore, need some kind of host. The researchers managed to identify one: A bacterium called Streptococcus sanguinis that lives mostly in dental plaque in our mouths. Exactly which other hosts obelisks inhabit is yet another mystery, as are what they do to their host and how they spread,” Vice reported.
“While we don’t know the ‘hosts’ of other Obelisks, it is reasonable to assume that at least a fraction may be present in bacteria,” the researchers noted in their bioRxiv paper.
Researchers are Stumped
The Stanford scientists were unable to identify any impact the Obelisks were having on their bacterial hosts—either negative or positive—or determine how they could spread between cells.
“These elements might not even be ‘viral’ in nature and might more closely resemble ‘RNA plasmids,’” they concluded in their paper.
The Stanford scientists are uncertain as to where or what the hosts of the Obelisks are, but they suspect that at least some of them are present in bacteria. However, Obelisks do not appear to be similar to any biological agents that could provide a link between genetic molecules and viruses.
And so, Obelisks are a true mystery—one the Stanford researchers may one day solve. If they do, new biomarkers for clinical laboratory testing may not be far behind.
Researchers intend their new AI image retrieval tool to help pathologists locate similar case images to reference for diagnostics, research, and education
Researchers at Stanford University turned to an unusual source—the X social media platform (formerly known as Twitter)—to train an artificial intelligence (AI) system that can look at clinical laboratory pathology images and then retrieve similar images from a database. This is an indication that pathologists are increasingly collecting and storing images of representative cases in their social media accounts. They then consult those libraries when working on new cases that have unusual or unfamiliar features.
The Stanford Medicine scientists trained their AI system—known as Pathology Language and Image Pretraining (PLIP)—on the OpenPath pathology dataset, which contains more than 200,000 images paired with natural language descriptions. The researchers collected most of the data by retrieving tweets in which pathologists posted images accompanied by comments.
“It might be surprising to some folks that there is actually a lot of high-quality medical knowledge that is shared on Twitter,” said researcher James Zou, PhD, Assistant Professor of Biomedical Data Science and senior author of the study, in a Stanford Medicine SCOPE blog post, which added that “the social media platform has become a popular forum for pathologists to share interesting images—so much so that the community has widely adopted a set of 32 hashtags to identify subspecialties.”
“It’s a very active community, which is why we were able to curate hundreds of thousands of these high-quality pathology discussions from Twitter,” Zou said.
“The main application is to help human pathologists look for similar cases to reference,” James Zou, PhD (above), Assistant Professor of Biomedical Data Science, senior author of the study, and his colleagues wrote in Nature Medicine. “Our approach demonstrates that publicly shared medical information is a tremendous resource that can be harnessed to develop medical artificial intelligence for enhancing diagnosis, knowledge sharing, and education.” Leveraging pathologists’ use of social media to store case images for future reference has worked out well for the Stanford Medicine study. (Photo copyright: Stanford University.)
Retrieving Pathology Images from Tweets
“The lack of annotated publicly-available medical images is a major barrier for innovations,” the researchers wrote in Nature Medicine. “At the same time, many de-identified images and much knowledge are shared by clinicians on public forums such as medical Twitter.”
In this case, the goal “is to train a model that can understand both the visual image and the text description,” Zou said in the SCOPE blog post.
“Pathology is perhaps even more suited to Twitter than many other medical fields because for most pathologists, the bulk of our daily work revolves around the interpretation of images for the diagnosis of human disease,” wrote Jerad M. Gardner, MD, a dermatopathologist and section head of bone/soft tissue pathology at Geisinger Medical Center in Danville, Pa., in a blog post about the Pathology Hashtag Ontology project. “Twitter allows us to easily share images of amazing cases with one another, and we can also discuss new controversies, share links to the most cutting edge literature, and interact with and promote the cause of our pathology professional organizations.”
The researchers used the 32 subspecialty hashtags to retrieve English-language tweets posted from 2006 to 2022. Images in the tweets were “typically high-resolution views of cells or tissues stained with dye,” according to the SCOPE blog post.
The researchers collected a total of 232,067 tweets and 243,375 image-text pairs across the 32 subspecialties, they reported. They augmented this with 88,250 replies that received the highest number of likes and had at least one keyword from the ICD-11 codebook. The SCOPE blog post noted that the rankings by “likes” enabled the researchers to screen for high-quality replies.
They then refined the dataset by removing duplicates, retweets, non-pathology images, and tweets marked by Twitter as being “sensitive.” They also removed tweets containing question marks, as this was an indicator that the practitioner was asking a question about an image rather than providing a description, the researchers wrote in Nature Medicine.
They cleaned the text by removing hashtags, Twitter handles, HTML tags, emojis, and links to websites, the researchers noted.
The final OpenPath dataset included:
116,504 image-text pairs from Twitter posts,
59,869 from replies, and
32,041 image-text pairs scraped from the internet or obtained from the LAION dataset.
The latter is an open-source database from Germany that can be used to train text-to-image AI software such as Stable Diffusion.
Training the PLIP AI Platform
Once they had the dataset, the next step was to train the PLIP AI model. This required a technique known as contrastive learning, the researchers wrote, in which the AI learns to associate features from the images with portions of the text.
As explained in Baeldung, an online technology publication, contrastive learning is based on the idea that “it is easier for someone with no prior knowledge, like a kid, to learn new things by contrasting between similar and dissimilar things instead of learning to recognize them one by one.”
“The power of such a model is that we don’t tell it specifically what features to look for. It’s learning the relevant features by itself,” Zou said in the SCOPE blog post.
The resulting AI PLIP tool will enable “a clinician to input a new image or text description to search for similar annotated images in the database—a sort of Google Image search customized for pathologists,” SCOPE explained.
“Maybe a pathologist is looking at something that’s a bit unusual or ambiguous,” Zou told SCOPE. “They could use PLIP to retrieve similar images, then reference those cases to help them make their diagnoses.”
The Stanford University researchers continue to collect pathology images from X. “The more data you have, the more it will improve,” Zou said.
Pathologists will want to keep an eye on the Stanford Medicine research team’s progress. The PLIP AI tool may be a boon to diagnostics and improve patient outcomes and care.
Immunotherapy device could also enable clinical laboratories to receive in vivo biomarker data wirelessly
Researchers from Rice University in Houston and seven other states in the US are working on a new oncotherapy sense-and-respond implant that could dramatically improve cancer outcomes. Called Targeted Hybrid Oncotherapeutic Regulation (THOR), the technology is intended primarily for the delivery of therapeutic drugs by monitoring specific cancer biomarkers in vivo.
Through a $45 million federal grant from the Advanced Research Projects Agency for Health (ARPA-H), the researchers set out to develop an immunotherapy implantable device that monitors a patient’s cancer and adjusts antibody treatment dosages in real time in response to the biomarkers it measures.
It’s not a far stretch to envision future versions of the THOR platform also being used diagnostically to measure biomarker data and transmit it wirelessly to clinical laboratories and anatomic pathologists.
ARPH-A is a federal funding agency that was established in 2022 to support the development of high-impact research to drive biomedical and health breakthroughs. THOR is the second program to receive funding under its inaugural Open Broad Agency Announcement solicitation for research proposals.
“By integrating a self-regulated circuit, the THOR technology can adjust the dose of immunotherapy reagents based on a patient’s responses,” said Weiyi Peng, MD, PhD (above), Assistant Professor of Biology and Biochemistry at the University of Houston and co-principal investigator on the research, in a UH press release. “With this new feature, THOR is expected to achieve better efficacy and minimize immune-related toxicity. We hope this personalized immunotherapy will revolutionize treatments for patients with peritoneal cancers that affect the liver, lungs, and other organs.” If anatomic pathologists and clinical laboratories could receive biometric data from the THOR device, that would be a boon to cancer diagnostics. (Photo copyright: University of Houston.)
Antibody Therapy on Demand
Omid Veiseh, PhD, Associate Professor of Bioengineering at Rice University and principal investigator on the project, described the THOR device as a “living drug factory” inside the body. The device is a rod-like gadget that contains onboard electronics and a wireless rechargeable battery. It is three inches long and has a miniaturized bioreactor that contains human epithelial cells that have been engineered to produce immune modulating therapies.
“Instead of tethering patients to hospital beds, IV bags, and external monitors, we’ll use a minimally invasive procedure to implant a small device that continuously monitors their cancer and adjusts their immunotherapy dose in real time,” said Veiseh in a Rice University press release. “This kind of ‘closed-loop therapy’ has been used for managing diabetes, where you have a glucose monitor that continuously talks to an insulin pump.
But for cancer immunotherapy, it’s revolutionary.”
The team believes the THOR device will have the ability to monitor biomarkers and produce an antibody on demand that will trigger the immune system to fight cancer locally. They hope the sensor within THOR will be able to monitor biomarkers of toxicity for the purpose of fine-tuning therapies to a patient immediately in response to signals from a tumor.
“Today, cancer is treated a bit like a static disease, which it’s not,” Veiseh said. “Clinicians administer a therapy and then wait four to six weeks to do radiological measurements to see if the therapy is working. You lose quite a lot of time if it’s not the right therapy. The tumor may have evolved into a more aggressive form.”
The THOR device lasts 60 days and can be removed after that time. It is designed to educate the immune system to recognize a cancer and prevent it from recurring. If the cancer is not fully eradicated after the first implantation, the patient can be implanted with THOR again.
Use of AI in THOR Therapy
The researchers plan to spend the next two and a half years building prototypes of the THOR device, testing them in rodents, and refining the list of biomarkers to be utilized in the device. Then, they intend to take an additional year to establish protocols for the US Food and Drug Administration’s (FDA) good manufacturing practices requirements, and to test the final prototype on large animals. The researchers estimate the first human clinical trials for the device will begin in about four years.
“The first clinical trial will focus on refractory recurrent ovarian cancer, and the benefit of that is that we have an ongoing trial for ovarian cancer with our encapsulated cytokine ‘drug factory’ technology,” said Veiseh in the UH press release.
The group is starting with ovarian cancer because research in this area is lacking and it will provide the opportunity for THOR to activate the immune system against ovarian cancer, which is typically challenging to fight with immunotherapy approaches. If successful in ovarian cancer, the researchers hope to test THOR in other cancers that metastasize within the abdomen, such as:
All control and decision-making will initially be performed by a healthcare provider based on signals transmitted by THOR using a computer or smartphone. However, Veiseh sees the device ultimately being powered by artificial intelligence (AI) algorithms that could independently make therapeutic decisions.
“As we treat more and more patients [with THOR], the devices are going to learn what type of biomarker readout better predicts efficacy and toxicity and make adjustments based on that,” he predicted. “Between the information you have from the first patient versus the millionth patient you treat, the algorithm is just going to get better and better.”
Moving Forward
In addition to UH and Rice University, scientists working on the project come from several institutions, including:
More research and clinical trials are needed before THOR can be used in the clinical treatment of cancer patients. If the device reaches the commercialization stage, Veiseh plans to either form a new company or license the technology to an existing company for further development.
“We know that the further we advance it in terms of getting that human data, the more likely it is that this could then be transferred to another entity,” he told Precision Medicine Online.
Pathologists and clinical laboratories will want to monitor the progress of the THOR technology’s ability to sense changes in cancer biomarkers and deliver controlled dosages of antibiotic treatments.
Study findings may lead to new clinical laboratory tests, as well as vaccines and immunotherapies for neurodegenerative diseases
Research into the human genome continues to produce useful new insights. This time, a study led by researchers at Stanford University identified a genetic variation that is believed to help “slow or even stall” progression of neurodegenerative diseases, including Alzheimer’s and Parkinson’s, according to a press release. Because these genetic variations are common, it is likely that diagnostic tests can be developed for use by clinical laboratories.
Researchers at Stanford Medicine led the study which discovered that approximately one in five individuals carry the gene variant, a protective allele identified as DR4 (aka, HLA-DR4). It’s one of a large number of alleles found in a gene known as DRB1.
DRB1 is part of a family of genes collectively known as the human lymphocyte antigen complex or HLA. The HLA-DRB1 gene plays a crucial role in the ability of the immune system to see a cell’s inner contents.
“In an earlier study, we’d found that carrying the DR4 allele seemed to protect against Parkinson’s disease,” said Emmanuel Mignot, MD, PhD (above), Director of the Stanford Center for Narcolepsy, in a Stanford press release. “Now, we’ve found a similar impact of DR4 on Alzheimer’s disease.” Clinical laboratories may soon have new vaccines for both neurodegenerative diseases. (Photo copyright: Stanford University.)
DR4 Found to Impact Both Parkinson’s and Alzheimer’s Diseases
To perform their research, the team examined a large collection of medical and genetic databases from 176,000 people who had either Alzheimer’s or Parkinson’s disease. The people involved in the study were from numerous countries located in East Asia, Europe, the Middle East and South America. Their genomes were then compared with people who did not have the diseases, focusing on the incidence and age of onset.
“In an earlier study we’d found that carrying the DR4 allele seemed to protect against Parkinson’s disease,” said Mignot in the Stanford press release. “Now, we’ve found a similar impact of DR4 on Alzheimer’s disease.”
The team found that about 20% to 30% of people carry DR4, and that they have around a 10% risk reduction for developing the two diseases.
“That this protective factor for Parkinson’s wound up having the same protective effect with respect to Alzheimer’s floored me,” said Emmanuel Mignot, MD, PhD, the Craig Reynolds Professor of Sleep Medicine in the Department of Psychiatry and Behavioral Sciences at Stanford University and the Director of the Stanford Center for Narcolepsy, in the Stanford Medicine press release. “The night after we found that out, I couldn’t sleep.”
The scientists also analyzed data from autopsied brains of more than 7,000 Alzheimer’s patients and discovered that individuals who carry DR4 had fewer neurofibrillary tangles and that those tangles are composed mainly of modified tau proteins, a common biomarker for Alzheimer’s.
The presence of these tangles corresponds with the severity of Alzheimer’s disease. They are not typically seen in Parkinson’s patients, but the Stanford team found that Parkinson’s patients who did carry DR4 experienced later onset of symptoms.
Mignot stated that tau, which is essential in Alzheimer’s, may also play a role in Parkinson’s, but that further research is required to prove its function.
Both diseases are characterized by the progressive loss of certain nerve cells or neurons in the brain and are linked to an accumulation of abnormal proteins. The Stanford researchers suggested that the DR4 gene variant may help protect individuals from Alzheimer’s and Parkinson’s by preventing the buildup of tau proteins.
“This is a very interesting study, providing additional evidence of the involvement of the immune system in the pathogenesis of Alzheimer’s and Parkinson’s,” neurologist Wassim Elyaman, PhD, Assistant Professor of Neurological Sciences in Neurology, the Taub Institute and the Institute for Genomic Medicine at Columbia University, told Live Science.
New Vaccines and Immunotherapies
According to the Alzheimer’s Association, more than six million Americans are currently living with Alzheimer’s disease and approximately one in three Americans die with Alzheimer’s or another dementia.
The Parkinson’s Foundation states that nearly one million Americans are currently living with Parkinson’s disease, and that number is expected to rise to 1.2 million by 2030. Parkinson’s is the second-most common neurodegenerative disease after Alzheimer’s disease.
Even though the genetic analysis of the Stanford research is strong, more immune cell and blood-based research is needed to definitively establish how tau is connected to the two diseases.
This research could have implications for clinical laboratories by giving them biomarkers for a useful new diagnostic test, particularly for diagnosing Alzheimer’s and Parkinson’s.
Further, Mignot suggested that an effective vaccine could delay the onset or slow the progression of both diseases. He hopes to test his hypothesis on genetically modified mice and eventually human subjects.
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.
