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.
According to the Centers for Disease Control and Prevention (CDC), the 1918 influenza (aka, the Spanish Flu) pandemic took place worldwide between 1918 and 1919. It was caused by the H1N1 virus (A/H1N1), a subtype of the Influenza A virus, and infected approximately 500 million people worldwide (a third of the human population at the time). Fifty million people died. Many were children or otherwise healthy individuals, but people from all age groups perished.
The CDC calls the Spanish Flu the “deadliest pandemic of the 20th century.” Past pandemics have generally concluded after 2.5 to 3.5 years. That’s how long it takes for new viruses to mutate and become endemic diseases, Healthline reported.
The COVID-19 pandemic has been around for about that long. It stands to reason the natural end of the COVID-19 pandemic may be just around the corner. But is it? And is the Omicron variant an indicator that the COVID-19 pandemic is winding down?
“Our analysis suggests that in the US, this combination of characteristics would lead to Omicron replacing Delta as the dominant variant in the next few months and to a higher peak burden of disease than the country saw in the second half of 2021 (but likely below the peak reached in the winter of 2020-21),” the report states.
McKinsey analysts also acknowledged the possible impact of new therapeutics, COVID-19 vaccine booster doses, and public health measures on Omicron spread. “In the short term, an accelerated rollout of booster doses of COVID-19 vaccines is likely to be one of the best protections against an Omicron-fueled wave of the disease,” the analysts wrote.
Does How the Spanish Flu Came to an End Mirror the COVID-19 Pandemic?
Virologists and infectious disease experts explained that the Spanish Flu virus did what viruses still do: mutate and become less dangerous. Herd immunity also helped end the 1918 pandemic.
“The 1918 influenza virus eventually mutated to the point of not having a high number of deaths—eventually over three years or so. We may very well be witnessing this process with ongoing variants of SARS-CoV-2,” virologist Rodney Rohde, PhD, Director of the Clinical Laboratory Science Program at Texas State University, told Healthline.
Today’s flu strains have “ancestral links” to the 1918 flu, and thus, the SARS-CoV-2 coronavirus will most likely also leave its mark, The Boston Herald reported. “The coronavirus will evolve and hopefully morph into a seasonal illness to which we pay little mind, but it’s still too early to tell,” Todd Ellerin, MD (above,) Director of Infectious Diseases, South Shore Health, South Weymouth, Mass., told The Boston Herald. (Photo copyright: Greg Derr/The Patriot Ledger.)
“If you think about the way viruses behave, biologically, their reason for living is to replicate and spread, and there’s really no advantage for the virus to kill the host,” infectious disease specialist Keith Armitage, MD, Professor of Medicine, Division of Infectious Diseases at Case Western Reserve University, told Healthline. “The hope is, that if the pandemic doesn’t go away, we will get new variants that are highly contagious but don’t produce much of a clinical illness,” he added.
In “2021’s Top 10 Lab Stories Confirm Important Trends,” Dark Daily’s sister publication, The Dark Report (TDR), posed a similar question in its number one story of 2021: “COVID-19: Will it Become Endemic and a Respiratory Virus that Shows Up Every Year like Influenza?”
“The question of whether SARS-CoV-2 is a pandemic that fades, as did SARS in 2003, or becomes endemic and a respiratory virus that shows up every season like influenza and the common cold, is of major concern to clinical lab administrators. That’s because clinical labs and pathology groups must continue to serve physicians and patients with the usual menu of routine, reference, and esoteric testing,” TDR noted.
Clinical Laboratories to Continue COVID Testing
It would be most helpful for medical laboratories and pathology groups to have some idea of when the pandemic will end. Unfortunately, such predictions would not be very useful.
“Since COVID-19 infections have a high number of asymptomatic transmitters, we may not fully understand how societal and environmental pressures—masks, distancing, remote working, etc.—on the virus will allow it to evolve,” Rohde told Healthline.
For now, clinical laboratories will need to continue to remain prepared as COVID-19 cases rise and people seek SARS-COV-2 tests, vaccinations, and treatments. COVID-19 testing is likely to be in demand throughout the coming year. The current surge in demand for COVID-19 tests is putting additional stress on the supply chain.
“We know pandemics end; it’s just a matter of time,” Sara Paton, PhD, Associate Professor of Epidemiology, Wright State University, told the Journal-News. “It could be in 2022, maybe later in the year, but I can’t say for sure. It could be 2023.”
DeepMind hopes its unrivaled collection of data, enabled by artificial intelligence, may advance development of precision medicines, new medical laboratory tests, and therapeutic treatments
‘Tis the season for giving, and one United Kingdom-based artificial intelligence (AI) research laboratory is making a sizeable gift. After using AI and machine learning to create “the most comprehensive map of human proteins,” in existence, DeepMind, a subsidiary of Alphabet Inc. (NASDAQ:GOOGL), parent company of Google, plans to give away for free its database of millions of protein structure predictions to the global scientific community and to all of humanity, The Verge reported.
Pathologists and clinical laboratory scientists developing proteomic assays understand the significance of this gesture. They know how difficult and expensive it is to determine protein structures using sequencing of amino acids. That’s because the various types of amino acids in use cause the [DNA] string to “fold.” Thus, the availability of this data may accelerate the development of more diagnostic tests based on proteomics.
“For decades, scientists have been trying to find a method to reliably determine a protein’s structure just from its sequence of amino acids. Attraction and repulsion between the 20 different types of amino acids cause the string to fold in a feat of ‘spontaneous origami,’ forming the intricate curls, loops, and pleats of a protein’s 3D structure. This grand scientific challenge is known as the protein-folding problem,” a DeepMind statement noted.
Enter DeepMind’s AlphaFold AI platform to help iron things out. “Experimental techniques for determining structures are painstakingly laborious and time consuming (sometimes taking years and millions of dollars). Our latest version [of AlphaFold] can now predict the shape of a protein, at scale and in minutes, down to atomic accuracy. This is a significant breakthrough and highlights the impact AI can have on science,” DeepMind stated.
Release of Data Will Be ‘Transformative’
In July, DeepMind announced it would begin releasing data from its AlphaFold Protein Structure Database which contains “predictions for the structure of some 350,000 proteins across 20 different organisms,” The Verge reported, adding, “Most significantly, the release includes predictions for 98% of all human proteins, around 20,000 different structures, which are collectively known as the human proteome. By the end of the year, DeepMind hopes to release predictions for 100 million protein structures.”
According to Edith Heard, PhD, Director General of the European Molecular Biology Laboratory (EMBL), the open release of such a dataset will be “transformative for our understanding of how life works,” The Verge reported.
“I see this as the culmination of the entire 10-year-plus lifetime of DeepMind,” company CEO and co-founder Demis Hassabis (above), told The Verge. “From the beginning, this is what we set out to do: to make breakthroughs in AI, test that on games like Go and Atari, [and] apply that to real-world problems, to see if we can accelerate scientific breakthroughs and use those to benefit humanity.” The release of DeepMind’s entire protein prediction database will certainly do that. Clinical laboratory scientists worldwide will have free access to use it in developing new precision medicine treatments based on proteomics. (Photo copyright: BBC.)
Free Data about Proteins Will Accelerate Research on Diseases, Treatments
Research into how protein folds and, thereby, functions could have implications to fighting diseases and developing new medicines, according to DeepMind.
“This will be one of the most important datasets since the mapping of the human genome,” said Ewan Birney, PhD, Deputy Director General of the EMBL, in the DeepMind statement. EMBL worked with DeepMind on the dataset.
DeepMind protein prediction data are already being used by scientists in medical research. “Anyone can use it for anything. They just need to credit the people involved in the citation,” said Demis Hassabis, DeepMind CEO and Co-founder, in The Verge.
In a blog article, Hassabis listed several projects and organizations already using AlphaFold. They include:
“As researchers seek cures for diseases and pursue solutions to other big problems facing humankind—including antibiotic resistance, microplastic pollution, and climate change—they will benefit from fresh insights in the structure of proteins,” Hassabis wrote.
Because of the deep financial backing that Alphabet/Google can offer, it is reasonable to predict that DeepMind will make progress with its AI technology that regularly adds capabilities and accuracy, allowing AlphaFold to be effective for many uses.
This will be particularly true for the development of new diagnostic assays that will give clinical laboratories better tools for diagnosing disease earlier and more accurately.
GISAID hosts a vast, open database of genomic sequences of SARS-CoV-2 coronavirus samples, and medical laboratory scientists in countries across the globe are contributing
Clinical laboratories around the world have been contributing to the global scientific community’s database of knowledge about SARS-CoV-2, the coronavirus that caused the COVID-19 pandemic, and its variants, through an ingenious and crucial network known as GISAID. This cooperative sharing of the coronavirus’ genetic data (now four million genomic sequences strong) has greatly contributed to understanding the spread of infections and progress obtained in developing effective treatments and vaccines.
Headquartered in Munich, Germany, GISAID, which stands for Global Initiative on Sharing Avian Influenza Data, was created in 2008 during the Avian Influenza (Bird Flu) pandemic. The GISAID initiative promotes “the rapid sharing of data from all influenza viruses and the coronavirus causing COVID-19. This includes genetic sequence and related clinical and epidemiological data associated with human viruses, and geographical as well as species-specific data associated with avian and other animal viruses, to help researchers understand how viruses evolve and spread during epidemics and pandemics,” according to the GISAID website.
Clinical pathologists are likely familiar with GISAID. The initiative has become an indispensable tool for researchers battling SARS-CoV-2. GISAID allows scientists and organizations worldwide to upload genetic sequences of COVID-19 samples. Those sequences can then be used in research for treatments, vaccines, and to track emerging variants. The information is invaluable, freely available, and represents the collaborative efforts of scientists around the world in the fight against COVID-19 and other infectious diseases.
An article published in The World, titled, “From Congo to Chile, Small Labs Are Playing a Growing Role in Global Understanding of COVID,” noted that more than four million genomic sequences have been submitted as of October 15, 2021. The more countries around the world that submit sequences to GISAID, the more understanding scientists have of how the virus is mutating. And, as the cost of performing genomic sequencing declines, the number of countries submitting genomes of SARS-CoV-2 to GISAID is rising.
How GISAID Ensures Contributors Receive Credit for Their Work
One of the reasons that GISAID has been so successful in gathering data is that it requires anyone who uses data downloaded from the massive database to give credit to the person or organization who uploaded it. In other words, if a scientist in the United Kingdom (UK) does breakthrough research using genomes that were originally uploaded to GISAID by a scientist in the Congo, the UK scientist must credit the work of the scientist from the Congo.
Other genomic databases do not have this requirement and genetic researchers are often hesitant to share information due to fear their work will be co-opted by others. According to The World, scientists in lower income countries are particularly vulnerable to having their work appropriated.
Even worse is having one’s work appropriated, used to create a product, and then not being given access to that product.
“Unfortunately, we’ve seen also the situation whereby people have leveraged that data and created the solution and refused to share the solution with those that shared the data,” virologist Christian Happi, PhD (above), who directs the African Center of Excellence for Genomics of Infectious Diseases (ACEGID) at Redeemer’s University in Nigeria, told The World. “And that is definitely going to roll back this whole open data sharing and access principle.” Happi is also a Visiting Scientist in the Department of Immunology and Infectious Diseases at Harvard’s T.H. Chan School of Public Health. (Photo copyright: Pius Utomi Ekpei/AFP/News 24.)
That is why GISAID’s policy of giving credit is so important, as molecular biologist Francine Ntoumi, PhD, told The World. “This means that we are going to participate in the game. We are able to say what is circulating. You are no more an observer and I think it makes a difference.” Ntoumi is Founder and Executive Director of the Congolese Foundation for Medical Research (CFMR) in the Republic of Congo, a lecturer in Immunology at Marien Ngouabi University, and Associate Professor and Head of a Research Group at the Institute of Tropical Medicine at the University of Tübingen, Germany.
The guarantee that credit will be given softens some of those fears and explains why the GISAID database is so vast, and increasingly contains sequences from scientists in Africa, South American, and other places where genomic sequencing was not widespread prior to the pandemic. Information from all over the world is crucial for scientists monitoring the mutations of the SARS-CoV-2 coronavirus.
Criticisms of GISAID
The fact that more countries are contributing to the GISAID database is certainly a positive, but the non-profit is not without its critics. There have been complaints about the lack of transparency, and some researchers claim to have had their access denied to the data without any explanation.
An article published in Science reported that “Scientists live in fear of losing access to the GISAID database.”
One scientist who requested anonymity told Science, “I am so tired of being scared all the time, of being terrified that if I take a step wrong, I will lose access to the data that I base my research on. [GISAID] has that sword hanging over any scientist that works on SARS-CoV-2.”
In response to these criticisms, GISAID said in a statement, “Any individual who registers with GISAID and agrees to the GISAID terms of use will be granted access credentials. … On rare occasions, GISAID has found it necessary to temporarily suspend access credentials to protect the GISAID sharing mechanism,” The World reported.
The strict sharing rules may be necessary to encourage researchers in lower income countries to contribute their genomic data on SARS-CoV-2. Charles Rotimi, PhD, a geneticist at the National Human Genome Research Institute (NHGRI), told Science, “To make scientists, especially from developing countries, more comfortable—making sure that they are recognized in the work that they are doing—sometimes you have to create an extra layer [of protection].”
GISAID has certainly accomplished much in its assembling four million SARS-CoV-2 genetic sequences. The initiative’s efforts have contributed to a substantial increase in the number of countries around the world that now have gene sequencing capabilities.
This is another illustration for clinical laboratory managers and pathologists of how continual technology advances in gene sequencing equipment and data analysis software make it significantly cheaper, faster, and more accurate to do genetic sequencing. This was not true, just a few years ago.
Molecular probes designed to spot minute amounts of pathogens in biological samples may aid clinical laboratories’ speed-to-answer
Driven to find a better way to isolate minute samples of pathogens from among high-volumes of other biological organisms, researchers at Canada’s McMaster University in Hamilton, Ontario, have unveiled a bioinformatics algorithm which they claim shortens time-to-answer and speeds diagnosis of deadly diseases.
Two disease pathogens the researchers specifically targeted in their study are responsible for sepsis and SARS-CoV-2, the coronavirus causing COVID-19. Clinical laboratories would welcome a technology which both shortens time-to-answer and improves diagnostic accuracy, particularly for pathogens such as sepsis and SARS-CoV-2.
Their design of molecular probes that target the genomic sequences of specific pathogens can enable diagnosticians and clinical laboratories to spot extremely small amounts of viral and bacterial pathogens in patients’ biological samples, as well as in the environment and wildlife.
“There are thousands of bacterial pathogens and being able to determine which one is present in a patient’s blood sample could lead to the correct treatment faster when time is very important,” Zachery Dickson, a lead author of the study, told Brighter World. Dickson is a bioinformatics PhD candidate in the Department of Biology at McMaster University. “The probe makes identification much faster, meaning we could potentially save people who might otherwise die,” he added.
Sepsis is a life-threatening response to infection that leads to organ failure, tissue damage, and death in hospitals worldwide. According to Sepsis Alliance, about 30% of people diagnosed with severe sepsis will die without quick and proper treatment. Thus, a “shortcut” to identifying sepsis in its early stages may well save many lives, the McMaster researchers noted.
And COVID-19 has killed millions. Such a tool that identifies sepsis and SARS-CoV-2 in minute biological samples would be a boon to hospital medical laboratories worldwide.
“We currently need faster, cheaper, and more succinct ways to detect pathogens in human and environmental samples that democratize the hunt, and this pipeline does exactly that,” Hendrik Poinar, PhD (above), McMaster Professor of Anthropology and a lead author of the study, told Brighter World. Poinar is Director of the McMaster University Ancient DNA Center. Hospital medical laboratories could help save many lives if sepsis and COVID-19 could be detected earlier. (Graphic copyright: McMaster University.)
Is Bioinformatics ‘Shortcut’ Faster than PCR Testing?
The researchers say their probes enable a shortcut to detection—even in an infection’s early stages—by “targeting, isolating, and identifying the DNA sequences specifically and simultaneously.”
The probes’ design makes possible simultaneous targeted capture of diverse metagenomics targets, Biocompare explained.
But is it faster than PCR (polymerase chain reaction) testing?
The McMaster scientists were motivated by the “challenges of low signal, high background, and uncertain targets that plague many metagenomic sequencing efforts,” they noted in their paper.
They pointed to challenges posed by PCR testing, a popular technique used for detection of sepsis pathogens as well as, more recently, for SARS-CoV-2, the coronavirus causing COVID-19.
“The (PCR) technique relies on primers that bind to nucleic acid sequences specific to an organism or group of organisms. Although capable of sensitive, rapid detection and quantification of a particular target, PCR is limited when multiple loci are targeted by primers,” the researchers wrote in Cell Reports Methods.
According to LabMedica, “A wide array of metagenomic study efforts are hampered by the same challenge: low concentrations of targets of interest combined with overwhelming amounts of background signal. Although PCR or naive DNA capture can be used when there are a small number of organisms of interest, design challenges become untenable for large numbers of targets.”
Detecting Pathogens Faster, Cheaper, and More Accurately
As part of their study, researchers tested two probe sets:
one to target bacterial pathogens linked to sepsis, and
another to detect coronaviruses including SARS-CoV-2.
They were successful in using the probes to capture a variety of pathogens linked to sepsis and SARS-CoV-2.
“We validated HUBDesign by generating probe sets targeting the breadth of coronavirus diversity, as well as a suite of bacterial pathogens often underlying sepsis. In separate experiments demonstrating significant, simultaneous enrichment, we captured SARS-CoV-2 and HCoV-NL63 [Human coronavirus NL 63] in a human RNA background and seven bacterial strains in human blood. HUBDesign has broad applicability wherever there are multiple organisms of interest,” the researchers wrote in Cell Reports Methods.
The findings also have implications to the environment and wildlife, the researchers noted.
Of course, more research is needed to validate the tool’s usefulness in medical diagnostics. The McMaster University researchers intend to improve HUBDesign’s efficiency but note that probes cannot be designed for unknown targets.
Nevertheless, the advanced application of novel technologies to diagnose of sepsis, which causes 250,000 deaths in the US each year, according to the federal Centers for Disease Control and Prevention, is a positive development worth watching.
The McMaster scientists’ discoveries—confirmed by future research and clinical studies—could go a long way toward ending the dire effects of sepsis as well as COVID-19. That would be a welcome development, particularly for hospital-based laboratories.
