The ASBMB story notes that nanopore technology depends on differences in charges on either side of the membrane to force DNA or RNA through the hole. This is one reason why proteins pose such a challenge.
“Think of a cell as a miniature city, with proteins as its inhabitants. Each protein-resident has a unique identity, its own characteristics, and function. If there was a database cataloging the fingerprints, job profiles, and talents of the city’s inhabitants, such a database would undoubtedly be invaluable!” said Behzad Mehrafrooz, PhD (above), Graduate Research Assistant at University of Illinois at Urbana-Champaign in an article he penned for the university website. This research should be of interest to the many clinical laboratories that do protein testing. (Photo copyright: University of Illinois.)
How the Maglia Process Works
In a Groningen University news story, Maglia said protein is “like cooked spaghetti. These long strands want to be disorganized. They do not want to be pushed through this tiny hole.”
His technique, developed in collaboration with researchers at the University of Rome Tor Vergata, uses electrically charged ions to drag the protein through the hole.
“We didn’t know whether the flow would be strong enough,” Maglia stated in the news story. “Furthermore, these ions want to move both ways, but by attaching a lot of charge on the nanopore itself, we were able to make it directional.”
The researchers tested the technology on what Maglia described as a “difficult protein” with many negative charges that would tend to make it resistant to flow.
“Previously, only easy-to-thread proteins were analyzed,” he said in the news story. “But we gave ourselves one of the most difficult proteins as a test. And it worked!”
Maglia now says that he intends to commercialize the technology through a new startup called Portal Biotech.
Detecting Post-Translational Modifications in the UK
In another recent study, researchers at the University of Oxford reported that they have adapted nanopore technology to detect post-translational modifications (PTMs) in protein chains. The term refers to changes made to proteins after they have been transcribed from DNA, explained an Oxford news story.
“The ability to pinpoint and identify post-translational modifications and other protein variations at the single-molecule level holds immense promise for advancing our understanding of cellular functions and molecular interactions,” said contributing author Hagan Bayley, PhD, Professor of Chemical Biology at University of Oxford, in the news story. “It may also open new avenues for personalized medicine, diagnostics, and therapeutic interventions.”
Bayley is the founder of Oxford Nanopore Technologies, a genetic sequencing company in the UK that develops and markets nanopore sequencing products.
The news story notes that the new technique could be integrated into existing nanopore sequencing devices. “This could facilitate point-of-care diagnostics, enabling the personalized detection of specific protein variants associated with diseases including cancer and neurodegenerative disorders,” the story states.
In another recent study, researchers at the University of Washington reported that they have developed their own method for protein sequencing with nanopore technology.
“This opens up the possibility for barcode sequencing at the protein level for highly multiplexed assays, PTM monitoring, and protein identification!” Motone wrote.
Single-cell proteomics, enabled by nanopore protein sequencing technology, “could provide higher sensitivity and wider throughput, digital quantification, and novel data modalities compared to the current gold standard of protein MS [mass spectrometry],” they wrote. “The accessibility of these tools to a broader range of researchers and clinicians is also expected to increase with simpler instrumentation, less expertise needed, and lower costs.”
There are approximately 20,000 human genes. However, there are many more proteins. Thus, there is strong interest in understanding the human proteome and the role it plays in health and disease.
Technology that makes protein testing faster, more accurate, and less costly—especially with a handheld analyzer—would be a boon to the study of proteomics. And it would give clinical laboratories new diagnostic tools and bring some of that testing to point-of-care settings like doctor’s offices.
Scientists believe useful new clinical laboratory assays could be developed by better understanding the huge number of ‘poorly researched’ genes and the proteins they build
Researchers have added a new “-ome” to the long list of -omes. The new -ome is the “unknome.” This is significant for clinical laboratory managers because it is part of an investigative effort to better understand the substantial number of genes, and the proteins they build, that have been understudied and of which little is known about their full function.
The Unknome Database includes “thousands of understudied proteins encoded by genes in the human genome, whose existence is known but whose functions are mostly not,” according to a news release.
The database, which is available to the public and which can be customized by the user, “ranks proteins based on how little is known about them,” the PLOS Biology paper notes.
It should be of interest to pathologists and clinical laboratory scientists. The fruit of this research may identify additional biomarkers useful in diagnosis and for guiding decisions on how to treat patients.
“These uncharacterized genes have not deserved their neglect,” said Sean Munro, PhD (above), MRC Laboratory of Molecular Biology in Cambridge, England, in a press release. “Our database provides a powerful, versatile and efficient platform to identify and select important genes of unknown function for analysis, thereby accelerating the closure of the gap in biological knowledge that the unknome represents.” Clinical laboratory scientists may find the Unknome Database intriguing and useful. (Photo copyright: Royal Society.)
Risk of Ignoring Understudied Proteins
Proteomics (the study of proteins) is a rapidly advancing area of clinical laboratory testing. As genetic scientists learn more about proteins and their functions, diagnostics companies use that information to develop new assays. But did you know that researchers tend to focus on only a small fraction of the total number of protein-coding DNA sequences contained in the human genome?
The study of proteomics is primarily interested in the part of the genome that “contains instructions for building proteins … [which] are essential for development, growth, and reproduction across the entire body,” according to Scientific American. These are all protein-coding genes.
Proteomics estimates that there are more than two million proteins in the human body, which are coded for 20,000 to 25,000 genes, according to All the Science.
To build their database, the MRC researchers ranked the “unknome” proteins by how little is known about their functions in cellular processes. When they tested the database, they found some of these less-researched proteins important to biological functions such as development and stress resistance.
“The role of thousands of human proteins remains unclear and yet research tends to focus on those that are already well understood,” said Sean Munro, PhD, MRC Laboratory of Molecular Biology in Cambridge, England, in the news release. “To help address this we created an Unknome database that ranks proteins based on how little is known about them, and then performed functional screens on a selection of these mystery proteins to demonstrate how ignorance can drive biological discovery.”
In the paper, they acknowledged the human genome encodes about 20,000 proteins, and that the application of transcriptomics and proteomics has “confirmed that most of these new proteins are expressed, and the function of many of them has been identified.
“However,” the authors added, “despite over 20 years of extensive effort, there are also many others that still have no known function.”
They also recognized limited resources for research and that a preference for “relative safety” and “well-established fields” are likely holding back discoveries.
The researchers note “significant” risks to continually ignoring unexplored proteins, which may have roles in cell processes, serve as targets for therapies, and be associated with diseases as well as being “eminently druggable,” Genetic Engineering News reported.
Setting up the Unknome Database
To develop the Unknome Database, the researchers first turned to what has already come to fruition. They gave each protein in the human genome a “knownness” score based on review of existing information about “function, conservation across species, subcellular localization, and other factors,” Interesting Engineering reported.
It turns out, 3,000 groups of proteins (805 with a human protein) scored zero, “showing there’s still much to learn within the human genome,” Science News stated, adding that the Unknome Database catalogues more than 13,000 protein groups and nearly two million proteins.
The researchers then tested the database by using it to determine what could be learned about 260 “mystery” genes in humans that are also present in Drosophila (small fruit flies).
“We used the Unknome Database to select 260 genes that appeared both highly conserved and particularly poorly understood, and then applied functional assays in whole animals that would be impractical at genome-wide scale,” the researchers wrote in PLOS Biology.
“We initially selected all genes that had a knownness score of ≤1.0 and are conserved in both humans and flies, as well as being present in at least 80% of available metazoan genome sequences. … After testing for viability, the nonessential genes were then screened with a panel of quantitative assays designed to reveal potential roles in a wide range of biological functions,” they added.
“Our screen in whole organisms reveals that, despite several decades of extensive genetic screens in Drosophila, there are many genes with essential roles that have eluded characterization,” the researchers conclude.
Clinical Laboratory Testing Using the Unknome Database
Future use of the Unknome Database may involve CRISPR technology to explore functions of unknown genes, according to the PLOS Biology paper.
Munro told Science News the research team may work with other research efforts aimed at understanding “mysterious proteins,” such as the Understudied Proteins Initiative.
The Unknome Database’s ability to be customized by others means researchers can create their own “knownness” scores as it applies to their studies. Thus, the database could be a resource in studies of treatments or medications to fight diseases, Chemistry World noted.
According to a statement prepared for Healthcare Dive by SomaLogic, a Boulder, Colorado-based protein biomarker company, diagnostic tests that measure proteins can be applied to diseases and conditions such as:
“The 27-protein model has potential as a ‘universal’ surrogate end point for cardiovascular risk,” the researchers wrote in Science Translational Medicine.
Proteomics definitely has its place in clinical laboratory testing. The development of MRC-LMB’s Unknome Database will help researchers’ increase their knowledge about the functions of more proteins which should in turn lead to new diagnostic assays for labs.
Spectroscopic technique was 91% accurate in identifying the notoriously difficult-to-diagnose disease suggesting a clinical diagnostic test for CFS may be possible
Most clinical pathologists know that, despite their best efforts, scientists have failed to come up with a reliable clinical laboratory blood test for diagnosing myalgic encephalomyelitis (ME), the condition commonly known as chronic fatigue syndrome (CFS)—at least not one that’s ready for clinical use.
But now an international team of researchers at the University of Oxford has developed an experimental non-invasive test for CFS using a simple blood draw, artificial intelligence (AI), and a spectroscopic technique known as Raman spectroscopy.
The approach uses a laser to identify unique cellular “fingerprints” associated with the disease, according to an Oxford news release.
“When Raman was added to a panel of potentially diagnostic outputs, we improved the ability of the model to identify the ME/CFS patients and controls,” Karl Morten, PhD, Director of Graduate Studies and Principal Investigator at Oxford University, told Advanced Science News. Morton led the research team along with Wei Huang, PhD, Professor of Biological Engineering at Oxford.
The researchers claim the test is 91% accurate in differentiating between healthy people, disease controls, and ME/CFS patients, and 84% accurate in differentiating between mild, moderate, and severe cases, the new release states.
“This could be a game changer as we are unsure what causes [ME/CFS] and diagnosis occurs perhaps 10 to 20 years after the condition has started to develop,” said Karl Morten, PhD, Director of Graduate Studies and Principal Investigator at Oxford University. “An early diagnosis might allow us to identify what is going wrong with the potential to fix it before the more long-term degenerative changes are observed.” Though this research may not lead to a simple clinical laboratory blood test for CFS, any non-invasive diagnostic test would enable doctors to help many people. (Photo copyright: Oxford University.)
Need for an ME/CFS Test
The federal Centers for Disease Control and Prevention (CDC) describes ME/CFS as “a serious, long-term illness that affects many body systems,” with symptoms that include severe fatigue and sleep difficulties. Citing an Institute of Medicine (IoM) report, the agency estimates that 836,000 to 2.5 million Americans suffer from the condition but notes that most cases have not been diagnosed.
“One of the difficulties is the complexity of the disease,” said Jonas Bergquist, MD, PhD, Director of the ME/CFS Research Center of Uppsala University in Sweden, told Advanced Science News. “Because it’s a multi-organ disorder, you get symptoms from many different regions of the body with different onsets, though it’s common with post viral syndrome to have different overlapping [symptoms] that disguise the diagnosis.” Bergquist was not involved with the Oxford study.
One key to the Oxford researchers’ technique is the use of multiple artificial intelligence models to analyze the spectral profiles. “These signatures are complex and by eye there are not necessarily clear features that separate ME/CFS patients from other groups,” Morten told Advanced Science News.
“The AI looks at this data and attempts to find features which can separate the groups,” he continued. “Different AI methods find different features in the data. Individually, each method is not that successful at assigning an unknown sample to the correct group. However, when we combine the different methods, we produce a model which can assign the subjects to the different groups very accurately.”
Without a reliable test, “diagnosis of the condition is difficult, with most patients relying on self-report, questionnaires, and subjective measures to receive a diagnosis,” the Oxford press release noted.
But developing such a test has been challenging, Advanced Science News noted.
How Oxford’s Raman Technique Works
Raman spectroscopy uses a laser to determine the “vibrational modes of molecules,” according to the Oxford press release.
“When a laser beam is directed at a cell, some of the scattered photons undergo frequency shifts due to energy exchanges with the cell’s molecular components,” the press release stated. “Raman micro-spectroscopy detects these shifted photons, providing a non-invasive method for single cell analysis. The resulting single cell Raman spectra serve as a unique fingerprint, revealing the intrinsic and biochemical properties and indicating the physiological and metabolic state of the cell.”
The researchers employed the technique on blood samples from 98 subjects, including 61 ME/CFS patients, 16 healthy controls, and 21 controls with multiple sclerosis (MS), Advanced Science reported.
The Oxford scientists focused their attention on peripheral blood mononuclear cells (PBMCs), as previous studies found that these cells showed “reduced energetic function” in ME/CFS patients. “With this evidence, the team proposed that single-cell analysis of PBMCs might reveal differences in the structure and morphology in ME/CFS patients compared to healthy controls and other disease groups such as multiple sclerosis,” the press release states.
Clinical Laboratory Blood Processing and the Oxford Raman Technique
Oxford’s Raman spectroscopic technique “only requires a small blood sample which could be developed as a point-of-care test perhaps from one drop of blood,” the researchers wrote. However, Advanced Science News pointed out that required laser microscopy equipment costs more than $250,000.
In their Advanced Science paper, the researchers note that the test could be made more widely available by transferring blood samples collected by local clinical laboratories to diagnostic centers that have the needed hardware.
“Alternatively, a compact system containing portable Raman instruments could be developed, which would be much cheaper than a standard Raman microscope, and [which] incorporated with microfluidic systems to stream cells through a Raman laser for detection, eliminating the need for lengthy blood sample processing,” the researchers wrote.
They noted that the technique could be adapted to test for other chronic conditions as well, such as MS, fibromyalgia, Lyme disease, and long COVID.
“Our paper is very much a starting point for future research,” Morten told Advanced Science News. “Larger cohorts need to be studied, and if Raman proves useful, we need to think carefully about how a test might be developed.”
Bergquist agreed, stating it’s “not necessarily something you would see in a doctor’s office. It requires a lot of advanced data analysis to use—I still see it as a research methodology. But in the long run, it could be developed into a tool that could be used in a more simplistic way.”
Though a useable diagnostic test may be far off, clinical laboratories should consider how they can aid in ME/CFS research.
Study findings could lead to new biomarker targets for clinical laboratories working to identify AMR bacteria
Reducing and managing antimicrobial resistance (AMR) is a major goal of researchers and health systems across the globe. And it is the job of microbiologists and clinical laboratories to identify microbes that are AMR and those which are not to guide physicians as to the most appropriate therapies for patients with bacterial infections.
“AMR is a silent pandemic of much greater risk to society than COVID-19. In addition to 10 million deaths per year by 2050, the WHO estimates AMR will cost the global economy $100 trillion if we can’t find a way to combat antibiotic failure,” Timothy Barnett, PhD (above), Deputy Director and head of the Strep A Pathogenesis and Diagnostics team at Wesfarmers Centre of Vaccines and Infectious Diseases, told News Medical. Additional research may provide new targets for clinical laboratories tasked with identifying antimicrobial resistant bacteria. (Photo copyright: University of Western Australia.)
Rendering an Antibiotic Ineffective
According to the University of Oxford, about 1.2 million people died worldwide in 2019 due to AMR, and antimicrobial-resistant infections played a role in as many as 4.95 million deaths that same year. The World Health Organization (WHO) declared AMR one of the top ten global public health threats facing humanity.
While investigating antibiotic sensitivity of Group A Streptococcus—a potentially deadly bacteria often detected on the skin and in the throat—the Australian researchers uncovered a mechanism that enabled bacteria to absorb nutrients from their human host and evade the antibiotic sulfamethoxazole, a commonly-prescribed treatment for Group A Strep.
“Bacteria need to make their own folates to grow and, in turn, cause disease. Some antibiotics work by blocking this folate production to stop bacteria growing and treat the infection,” Timothy Barnett, PhD, Deputy Director of the Wesfarmers Centre of Vaccines and Infectious Diseases and head of the Strep A Pathogenesis and Diagnostics team, told News Medical.
“When looking at an antibiotic commonly prescribed to treat Group A Strep skin infections, we found a mechanism of resistance where, for the first time ever, the bacteria demonstrated the ability to take folates directly from its human host when blocked from producing their own. This makes the antibiotic ineffective and the infection would likely worsen when the patient should be getting better,” he added.
According to their study, the researchers identified an energy-coupling (ECF) factor transporter S component gene that allows Group A Strep to acquire extracellular reduced folate compounds that likely “expands the substrate specificity of an endogenous ECF transporter to acquire reduced folate compounds directly from the host, thereby bypassing the inhibition of folate biosynthesis by sulfamethoxazole.”
The study indicates that this new form of antibiotic resistance is indistinguishable under traditional testing used in microbiology and clinical laboratories, which in turn makes it difficult for clinicians to prescribe effective antibiotics to fight an infection.
Understanding AMR before It Is Too Late
The research suggests that understanding AMR is more complicated and intricate than previously thought. Barnett and his team believe their discovery is just the “tip of the iceberg” and that it will prove to be a far-reaching issue across other bacterial pathogens in addition to Group A Strep.
“Without antibiotics, we face a world where there will be no way to stop deadly infections, cancer patients won’t be able to have chemotherapy and people won’t have access to have life-saving surgeries,” Barnett told News Medical. “In order to preserve the long-term efficacy of antibiotics, we need to further identify and understand new mechanisms of antibiotic resistance, which will aid in the discovery of new antibiotics and allow us to monitor AMR as it arises.”
More research and clinical studies are needed before this discovery can become technology that clinical laboratories can use to test if microbes are AMR. The scientists at Wesfarmers Centre of Vaccines and Infectious Diseases are now developing testing methods to detect the presence of the antibiotic resistant mechanism and determine the best treatment options.
“It is vital we stay one step ahead of the challenges of AMR and, as researchers, we should continue to explore how resistance develops in pathogens and design rapid accurate diagnostic methods and therapeutics,” Kalindu Rodrigo, a PhD student in the Barnett lab and one of the authors of the study told News Medical. “On the other hand, equal efforts should be taken at all levels of the society including patients, health professionals, and policymakers to help reduce the impacts of AMR.”
Researchers say their method can trace ancestry back 100,000 years and could lay groundwork for identifying new genetic markers for diseases that could be used in clinical laboratory tests
Cheaper, faster, and more accurate genomic sequencing technologies are deepening scientific knowledge of the human genome. Now, UK researchers at the University of Oxford have used this genomic data to create the largest-ever human family tree, enabling individuals to trace their ancestry back 100,000 years. And, they say, it could lead to new methods for predicting disease.
This new database also will enable genealogists and medical laboratory scientists to track when, where, and in what populations specific genetic mutations emerged that may be involved in different diseases and health conditions.
New Genetic Markers That Could Be Used for Clinical Laboratory Testing
As this happens, it may be possible to identify new diagnostic biomarkers and genetic indicators associated with specific health conditions that could be incorporated into clinical laboratory tests and precision medicine treatments for chronic diseases.
“We have basically built a huge family tree—a genealogy for all of humanity—that models as exactly as we can the history that generated all the genetic variation we find in humans today,” said Yan Wong, DPhil, an evolutionary geneticist at the Big Data Institute (BDI) at the University of Oxford, in a news release. “This genealogy allows us to see how every person’s genetic sequence relates to every other, along all the points of the genome.”
Researchers from University of Oxford’s BDI in London, in collaboration with scientists from the Broad Institute of MIT and Harvard; Harvard University, and University of Vienna, Austria, developed algorithms for combining different databases and scaling to accommodate millions of gene sequences from both ancient and modern genomes.
“Essentially, we are reconstructing the genomes of our ancestors and using them to form a series of linked evolutionary trees that we call a ‘tree sequence,’” said geneticist Anthony Wilder Wohns, PhD (above), in the Oxford news release. Wohns, a postdoctoral researcher in statistical and population genetics at the Broad Institute, led the study. “We can then estimate when and where these ancestors lived. The power of our approach is that it makes very few assumptions about the underlying data and can also include both modern and ancient DNA samples.” The study may result in new genetic biomarkers that lead to advances in clinical laboratory diagnostics for today’s diseases. (Photo copyright: Harvard School of Engineering and Applied Sciences.)
Tracking Genetic Markers of Disease
The BDI team overcame the major obstacle to tracing the origins of human genetic diversity when they developed algorithms to handle the massive amount of data created when combining genome sequences from many different databases. In total, they compiled the genomic sequences of 3,601 modern and eight high-coverage ancient people from 215 populations in eight datasets.
The ancient genomes included three Neanderthal genomes, a Denisovan genome, and a family of four people who lived in Siberia around 4,600 years ago.
The University of Oxford researchers noted in their news release that their method could be scaled to “accommodate millions of genome sequences.”
“This structure is a lossless and compact representation of 27 million ancestral haplotype fragments and 231 million ancestral lineages linking genomes from these datasets back in time. The tree sequence also benefits from the use of an additional 3,589 ancient samples compiled from more than 100 publications to constrain and date relationships,” the researchers wrote in their published study.
Wong believes his research team has laid the groundwork for the next generation of DNA sequencing.
“As the quality of genome sequences from modern and ancient DNA samples improves, the tree will become even more accurate and we will eventually be able to generate a single, unified map that explains the descent of all the human genetic variation we see today,” he said in the news release.
Developing New Clinical Laboratory Biomarkers for Modern Diagnostics
In a video illustrating the study’s findings, evolutionary geneticist Yan Wong, DPhil, a member of the BDI team, said, “If you wanted to know why some people have some sort of medical conditions, or are more predisposed to heart attacks or, for example, are more susceptible to coronavirus, then there’s a huge amount of that described by their ancestry because they’ve inherited their DNA from other people.”
Wohns agrees that the significance of their tree-recording methods extends beyond simply a better understanding of human evolution.
“[This study] could be particularly beneficial in medical genetics, in separating out true associations between genetic regions and diseases from spurious connections arising from our shared ancestral history,” he said.
The underlying methods developed by Wohns’ team could have widespread applications in medical research and lay the groundwork for identifying genetic predictors of disease risk, including future pandemics.
Clinical laboratory scientists will also note that those genetic indicators may become new biomarkers for clinical laboratory diagnostics for all sorts of diseases currently plaguing mankind.
