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.
Ten year collaboration between Google and Harvard may lead to a deeper understanding of the brain and new clinical laboratory diagnostics
With all our anatomic pathology and clinical laboratory science, we still do not know that much about the structure of the brain. But now, scientists at Harvard University and Google Research studying the emerging field of connectomics have published a highly detailed 3D reconstruction of human brain tissue that allows visualization of neurons and their connections at unprecedented nanoscale resolutions.
Further investigation of the nano-connections within the human brain could lead to novel insights about the role specific proteins and molecules play in the function of the brain. Though it will likely be years down the road, data derived from this study could be used to develop new clinical laboratory diagnostic tests.
The data to generate the model came from Google’s use of artificial intelligence (AI) algorithms to color-code Harvard’s electron microscope imaging of a cubic millimeter of neural tissue—equivalent to a half-grain of rice—that was surgically removed from an epilepsy patient.
“That tiny square contains 57,000 cells, 230 millimeters of blood vessels, and 150 million synapses, all amounting to 1,400 terabytes of data,” according to the Harvard Gazette, which described the project as “the largest-ever dataset of human neural connections.”
“A terabyte is, for most people, gigantic, yet a fragment of a human brain—just a minuscule, teeny-weeny little bit of human brain—is still thousands of terabytes,” said neuroscientist Jeff W. Lichtman, MD, PhD, Jeremy R. Knowles Professor of Molecular and Cellular Biology, whose Lichtman Lab at Harvard University collaborated on the project with researchers from Google. The two labs have been working together for nearly 10 years on this project, the Harvard Gazette reported.
Lichtman’s lab focuses on the emerging field of connectomics, defined “as understanding how individual neurons are connected to one another to form functional networks,” said neurobiologist Wei-Chung Allen Lee, PhD, Assistant Professor of Neurology, Harvard Medical School, in an interview with Harvard Medical News. “The goal is to create connectomes—or detailed structural maps of connectivity—where we can see every neuron and every connection.” Lee was not involved with the Harvard/Google Research study.
“The human brain uses no more power than a dim incandescent light bulb, yet it can accomplish feats still not possible with the largest artificial computing systems,” wrote Google Research scientist Viren Jain, PhD (above), in a blog post. “To understand how requires a level of understanding more profound than knowing what part of the brain is responsible for what function. The field of connectomics aims to achieve this by precisely mapping how each cell is connected to others.” Google’s 10-year collaboration with Harvard University may lead to new clinical laboratory diagnostics. (Photo copyright: Google Research.)
Study Data and Tools Freely Available
Along with the Science paper, the researchers publicly released the data along with analytic and visualization tools. The study noted that the dataset “is large and incompletely scrutinized,” so the scientists are inviting other researchers to assist in improving the model.
“The ability for other researchers to proofread and refine this human brain connectome is one of many ways that we see the release of this paper and the associated tools as not only the culmination of 10 years of work, but the beginning of something new,” wrote Google Research scientist Viren Jain, PhD, in a blog post that included links to the online resources.
One of those tools—Neuroglancer—allows any user with a web browser to view 3D models of neurons, axons, synapses, dendrites, blood vessels, and other objects. Users can rotate the models in xyz dimensions.
Users with the requisite knowledge and skills can proofread and correct the models by signing up for a CAVE (Connectome Annotation Versioning Engine) account.
Researchers Found Several Surprises
To perform their study, Lichtman’s team cut the neural tissue into 5,000 slices, each approximately 30 nanometers thick, Jain explained in the blog post. They then used a multibeam scanning electron microscope to capture high-resolution images, a process that took 326 days.
Jain’s team at Google used AI tools to build the model. They “stitched and aligned the image data, reconstructed the three dimensional structure of each cell, including its axons and dendrites, identified synaptic connections, and classified cell types,” he explained.
Jain pointed to “several surprises” that the reconstruction revealed. For example, he noted that “96.5% of contacts between axons and their target cells have just one synapse.” However, he added, “we found a class of rare but extremely powerful synaptic connections in which a pair of neurons may be connected by more than 50 individual synapses.”
In their Science paper, the researchers suggest that “these powerful connections are not the result of chance, but rather that these pairs had a reason to be more strongly connected than is typical,” Jain wrote in the blog post. “Further study of these connections could reveal their functional role in the brain.”
Mysterious Structures
Another anomaly was the presence of “axon whorls,” as Jain described them, “beautiful but mysterious structures in which an axon wraps itself into complicated knots.”
Because the sample came from an epilepsy patient, Jain noted that the whorls could be connected to the disease or therapies or could be found in all brains.
“Given the scale and complexity of the dataset, we expect that there are many other novel structures and characteristics yet to be discovered,” he wrote. “These findings are the tip of the iceberg of what we expect connectomics will tell us about human brains.”
The researchers have a larger goal to create a comprehensive high-resolution map of a mouse’s brain, Harvard Medical News noted. This would contain approximately 1,000 times the data found in the 1-cubic-millimeter human sample.
Dark Daily has been tracking the different fields of “omics” for years, as research teams announce new findings and coin new areas of science and medicine to which “omics” is appended. Connectomics fits that description.
Though the Harvard/Google research is not likely to lead to diagnostic assays or clinical laboratory tests any time soon, it is an example of how advances in technologies are enabling researchers to investigate smaller and smaller elements within the human body.
Best of all, the researchers say the test could provide an inexpensive means of early diagnosis. This assay could also be used to monitor how well patients respond to cancer therapy, according to a news release.
The protein had previously been identified as a promising biomarker and is readily detectable in tumor tissue, they wrote. However, it is found in extremely low concentrations in blood plasma and is “well below detection limits of conventional clinical laboratory methods,” they noted.
To overcome that obstacle, they employed an ultra-sensitive immunoassay known as a Simoa (Single-Molecule Array), an immunoassay platform for measuring fluid biomarkers.
“We were shocked by how well this test worked in detecting the biomarker’s expression across cancer types,” said lead study author gastroenterologist Martin Taylor, MD, PhD, Instructor in Pathology, Massachusetts General Hospital and Harvard Medical School, in the press release. “It’s created more questions for us to explore and sparked interest among collaborators across many institutions.”
“We’ve known since the 1980s that transposable elements were active in some cancers, and nearly 10 years ago we reported that ORF1p was a pervasive cancer biomarker, but, until now, we haven’t had the ability to detect it in blood tests,” said pathologist and study co-author Kathleen Burns, MD, PhD (above), Chair of the Department of Pathology at Dana-Farber Cancer Institute and a Professor of Pathology at Harvard Medical School, in a press release. “Having a technology capable of detecting ORF1p in blood opens so many possibilities for clinical applications.” Clinical laboratories may soon have a new blood test to detect multiple types of cancer. (Photo copyright: Dana-Farber Cancer Institute.)
Simoa’s Advantages
In their press release, the researchers described ORF1p as “a hallmark of many cancers, particularly p53-deficient epithelial cancers,” a category that includes lung, breast, prostate, uterine, pancreatic, and head and neck cancers in addition to the cancers noted above.
“Pervasive expression of ORF1p in carcinomas, and the lack of expression in normal tissues, makes ORF1p unlike other protein biomarkers which have normal expression levels,” Taylor said in the press release. “This unique biology makes it highly specific.”
Simoa was developed at the laboratory of study co-author David R. Walt, PhD, the Hansjörg Wyss Professor of Bioinspired Engineering at Harvard Medical School, and Professor of Pathology at Harvard Medical School and Brigham and Women’s Hospital.
The Simoa technology “enables 100- to 1,000-fold improvements in sensitivity over conventional enzyme-linked immunosorbent assay (ELISA) techniques, thus opening the window to measuring proteins at concentrations that have never been detected before in various biological fluids such as plasma or saliva,” according to the Walt Lab website.
Simoa assays take less than two hours to run and require less than $3 in consumables. They are “simple to perform, scalable, and have clinical-grade coefficients of variation,” the researchers wrote.
Study Results
Using the first generation of the ORF1p Simoa assay, the researchers tested blood samples of patients with a variety of cancers along with 406 individuals, regarded as healthy, who served as controls. The test proved to be most effective among patients with colorectal and ovarian cancer, finding detectable levels of ORF1p in 58% of former and 71% of the latter. Detectable levels were found in patients with advanced-stage as well as early-stage disease, the researchers wrote in Cancer Discovery.
Among the 406 healthy controls, the test found detectable levels of ORF1p in only five. However, the control with the highest detectable levels, regarded as healthy when donating blood, “was six months later found to have prostate cancer and 19 months later found to have lymphoma,” the researchers wrote.
They later reengineered the Simoa assay to increase its sensitivity, resulting in improved detection of the protein in blood samples from patients with colorectal, gastroesophageal, ovarian, uterine, and breast cancers.
The researchers also employed the test on samples from 19 patients with gastroesophageal cancer to gauge its utility for monitoring therapeutic response. Although this was a small sample, they found that among 13 patients who had responded to therapy, “circulating ORF1p dropped to undetectable levels at follow-up sampling.”
“More Work to Be Done”
The Simoa assay has limitations, the researchers acknowledged. It doesn’t identify the location of cancers, and it “isn’t successful in identifying all cancers and their subtypes,” the press release stated, adding that the test will likely be used in conjunction with other early-detection approaches. The researchers also said they want to gauge the test’s accuracy in larger cohorts.
“The test is very specific, but it doesn’t tell us enough information to be used in a vacuum,” Walt said in the news release. “It’s exciting to see the early success of this ultrasensitive assessment tool, but there is more work to be done.”
More studies will be needed to valid these findings. That this promising new multi-cancer immunoassay is based on a clinical laboratory blood sample means its less invasive and less painful for patients. It’s a good example of an assay that takes a proteomic approach looking for protein cancer biomarkers rather than the genetic approach looking for molecular DNA/RNA biomarkers of cancer.
Japanese scientists who developed the detection method hope to use it to create ‘easy testing kits that anyone can use’
What do ostriches and humans have in common during the current COVID-19 pandemic? The unexpected answer is that ostrich antibodies can be used to identify humans infected with COVID-19. If proven viable in healthcare settings, the possibility exists that new clinical laboratory tests could be developed based on wearable diagnostics technologies that pathologists would interpret for doctors and patients.
According to Study Finds, scientists at Kyoto Prefectural University in Japan have created a removable mask filter that, when sprayed with a fluorescent dye coated with antibodies extracted from ostrich eggs, will glow under UV light when COVID-19 is detected. The discovery by Yasuhiro Tsukamoto, PhD (above), President of Kyoto Prefectural University, and his researchers could lead to development of low-cost at home COVID-19 testing kits using the same ostrich-antibody-based technique. (Photo copyright: Kyoto Prefectural University/Reuters.)
The KPU scientists conducted a small study with 32 COVID-19 patients over a 10-day span. The surgical-style masks they wore later glowed around the nose and mouth areas but became dimmer over time as their viral load decreased.
“The ostrich antibody for corona placed on the mouth filter of the mask captures the coronavirus in coughing, sneezing, and water,” the researchers explained in Study Finds.
Tsukamoto himself learned he had contracted COVID-19 after wearing a prototype mask and noticing it glowed under UV light. A PCR test later confirmed his diagnosis, Kyodo News reported.
The KPU team “hopes to further develop the masks so they will glow automatically, without special lighting, if the [COVID-19] virus is detected.” Reuters noted in its coverage of the ostrich-antibody masks.
Making Medicine from Ostrich Antibodies
A profile in Audubon noted that Tsukamoto, who also serves as a veterinary medicine professor at Kyoto Prefectural University, made ostriches the focus of his research since the 1990s as he looked for ways to harness the dinosaur-like bird’s properties to fight human infections. He maintains a flock of 500 captive ostriches. Each female ostrich can produce 50 to 100 eggs/year over a 50-year life span.
Tsukamoto’s research focuses on customizing the antibodies in ostrich eggs by injecting females with inactive viruses, allergens, and bacteria, and then extracting the antibodies to develop medicines for humans. Antibodies form in the egg yolks in about six weeks and can be collected without harming the parent or young.
“The idea of using ostrich antibodies for therapeutics in general is a very interesting concept, particularly because of the advantages of producing the antibodies from eggs,” Ashley St. John, PhD, an Associate Professor in Immunology, at Duke-NUS Medical School in Singapore, told Audubon.
While more clinical studies will be needed before ostrich-antibody masks reach the commercial marketplace, Tsukamoto’s team is planning to expand their experiment to 150 participants with a goal of receiving Japanese government approval to begin selling the glowing COVID-detection masks as early as 2022. But they believe the ostrich-antibody technique ultimately may lead to development of an inexpensive COVID-19 testing kit.
“We can mass-produce antibodies from ostriches at a low cost. In the future, I want to make this into an easy testing kit that anyone can use,” Tsukamoto told Kyodo News.
Harvard, MIT Also Working on COVID-19 Detecting Facemask
According to Fast Company, the MIT/Harvard COVID-19-detecting masks use the same core technology as previous paper tests for Ebola and Zika that utilize proteins and nucleic acids embedded in paper that react to target molecules.
Fast Company explained that the mask wearer launches a test by pushing a button to release a small water reservoir embedded in the mask (above). Droplets from their breath are than analyzed by the sensors in the masks, which could be adapted to test for new COVID variants or other respiratory pathogens. In addition to eliminating the use of a nasal swab, the mask-based testing system may compete with clinical laboratory-based results. (Photo copyright: Felice Frankel/MIT.)
“They would especially be useful in situations where local variant outbreaks are occurring, allowing people to conveniently test themselves at home multiple times a day,” he told Fast Company.
“It’s on par specificity and sensitivity that you will get in a state-of-the-art [medical] laboratory, but with no one there,” Luis Ruben Soenksen, PhD, Venture Builder in Artificial Intelligence and Healthcare at MIT and one of the co-authors of the Nature Biotechnology study, told Fast Company.
As the definition of “wearable diagnostic technology” broadens, pathologists and clinical laboratory scientists may see their roles expand to include helping consumers interpret data collected by point-of-care testing technology as well as performing, evaluating, and interpreting laboratory test results that come from non-traditional sources.
By analyzing ancient poop, researchers have discovered how much the human microbiome has changed over the past millennium, what may have brought about the change, and how those changes formed today’s human microbiome
Two thousand year-old human poop has yielded new insights into the evolution of the microbial cells (microbiota) inhabiting today’s human gut—collectively known as the human microbiome—that could help pathologists and clinical laboratories better understand diseases that may be linked to gut bacteria.
A recent study conducted by an international team of scientists reveals that the gut bacteria of today’s humans may have been altered by the onset of modern processed foods, sanitation, and the use of antibiotics.
In “Reconstruction of Ancient Microbial Genomes from the Human Gut,” published in the journal Nature, the researchers wrote, “In this study, we establish that palaeofaeces [Paleofeces in the US] with well-preserved DNA are abundant sources of microbial genomes, including previously undescribed microbial species, that may elucidate the evolutionary histories of human microbiomes. Similar future studies tapping into the richness of palaeofaeces will not only expand our knowledge of the human microbiome but may also lead to the development of approaches to restore present-day gut microbiomes to their ancestral state.”
Ancient Poop Is a ‘Time Machine’ into the Human Microbiome
To perform the research for this study, scientists analyzed Deoxyribonucleic acid (DNA) from eight preserved, fossilized feces (coprolites) to gain insight into the gut bacteria of ancient communities. The samples used in the research were originally found in rock formations in Utah and Mexico and were preserved by dryness and stable temperatures. The coprolites were between 1,000 and 2,000 years old.
“These paleofeces are the equivalent of a time machine,” Justin Sonnenburg, PhD, Associate Professor, Microbiology and Immunology at Stanford University and co-author of the study, told Science. Tiny bits of food found in the coprolites indicated that the diet of the ancient people included:
The dried-out poop samples were first radiocarbon dated. Then, tiny fragments of the coprolites were rehydrated which allowed researchers to recover longer DNA strands than those found in previous, similar studies. This study compared the microbiome of the ancient populations to that of present-day individuals. The authors of the study suggest that during the past millennium, the human microbiome has lost dozens of bacterial species and has become less diverse.
Other research studies have linked lower diversity among gut bacteria to higher rates of modern diseases, such as diabetes, obesity, and allergies, Science noted.
“We really wanted to be able to go back in time and see when those changes [in the modern gut microbiome] came about, and what’s causing them,” Archeological Geneticist Christina Warinner, PhD, Assistant Professor of Anthropology at Harvard University and one of the authors of the study, told Science. “Is it food itself? Is it processing, is it antibiotics, is it sanitation?” Warinner is the Sally Starling Seaver Assistant Professor at the Radcliffe Institute, and a group leader in the Department of Archaeogenetics at the Max Planck Institute for Evolutionary Anthropology and affiliated with the faculty of biological sciences at the Friedrich Schiller University in Jena, Germany. (Photo copyright: The Game Changers.)
Ancient versus Modern Microbiome
The ancient microbiomes lacked markers for antibiotic resistance and included dozens of bacterial species that were previously unknown. According to the study, “a total of 181 of the 498 reconstructed microbial genomes were classified as gut derived and had extensive DNA damage, consistent with an ancient origin, and 39% of the ancient genomes offered evidence of being newly discovered species.”
The scientists also discovered that the gut bacteria of present-day people living in non-industrialized societies is more like that of the ancient people when compared to present-day humans living in industrialized societies. But there are still vast differences between the ancient and the modern microbiome.
For example, a bacteria known as Treponema is virtually unknown in the microbiome of current humans, even those living in non-industrialized societies. However, according to Kostic, “They’re present in every single one of the paleofeces, across all the geographic sites. That suggests it’s not purely diet that’s shaping things,” he told Science.
What Can Clinical Laboratories Learn from Ancient Poop?
The ancient poop study scientists hope that future research on coprolites from the past will reveal more information regarding when shifts in the microbiome occurred and what events or human activities prompted those changes.
Research on the human microbiome has been responsible for many discoveries that have greatly impacted clinical pathology and diagnostics development.
Microbiologists and other medical laboratory scientists may soon have more useful biomarkers that aid in earlier, more accurate detection of disease, as well as guiding physicians to select the most effective therapies for specific patients, a key component of Precision Medicine.
The findings of this study are another step forward in understanding the composition and functions of gut bacteria. The study of the microbiome could prove to be a growth area for clinical laboratories and microbiology labs as well. It is probable that soon, labs will be performing more microbiome testing to help with the diagnosis, and treatment selection and monitoring of patients.
