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.
UNC’s novel way to visualize the human proteome could lead to improved clinical laboratory tests along with the development of new therapies
Diagnostic testing based on proteomics is considered to be a field with immense potential in diagnostics and therapeutics. News of a research breakthrough into how scientists can visualize protein activity within cells will be of major interest to the pathologists, PhDs, and medical laboratory scientists who specialize in clinical laboratory testing involving proteins.
Proteins are essential to all life and to the growth, maintenance, and repair of the human body. So, a thorough understanding of how they function within living cells would be essential to informed medical decision-making as well. And yet, how proteins go about doing their work is not well understood.
That may soon change. Scientists at the University of North Carolina (UNC) School of Medicine have developed an imaging method that could provide new insights into how proteins alter their shapes within living cells. And those insights may lead to the development of new therapies and medical treatments.
Dubbed “binder-tag” by the UNC scientists, their new technique “allows researchers to pinpoint and track proteins that are in a desired shape or ‘conformation,’ and to do so in real time inside living cells,” according to a UNC Health news release.
Two labs in the UNC School of Medicine’s Department of Pharmacology collaborated to develop the binder-tag technique:
“No one has been able to develop a method that can do, in such a generalizable way, what this method does. So, I think it could have a very big impact,” said lead author of the UNC study Klaus Hahn PhD (above), in the news release. “With this method we can see, for example, how microenvironmental differences across a cell affect, often profoundly, what a protein is doing,” he added. This research may enlarge scientists’ understanding of how the human proteome works and could lead to new medical laboratory tests and therapeutic drugs. (Photo copyright: UNC School of Medicine.)
How Binder-Tag Works
During their study, the UNC scientists developed binder-tag “movies” that allow viewers to see how the binder-tag technique enables the tracking of active molecules in living cells.
The technique involves two parts: a fluorescent binder and a molecular tag that is attached to the proteins of interest.
When inactive, the tag is hidden inside the protein, but when the protein is ready for action it changes shape and exposes the tag.
The binder then joins with the exposed tag and fluoresces. This new fluorescence can easily be tracked within the cell.
Nothing else in the cell can bind to the binder or tag, so they only light up when in contact on the active protein.
This type of visualization will help researchers understand the dynamics of a protein in a cell.
“The method is compatible with a wide range of beacons, including much more efficient ones than the interacting beacon pairs required for ordinary FRET [fluorescence resonance energy transfer]. Binder-tag can even be used to build FRET sensors more easily. Moreover, the binder-tag molecules were chosen so that nothing in cells can react with them and interfere with their imaging role,” Hahn said in the news release.
“Only upon exposure can the peptide specifically interact with a reporter protein (the binder). Thus, simple fluorescence localization reflects protein conformation. Through direct excitation of bright dyes, the trajectory and conformation of individual proteins can be followed,” the UNC researchers wrote in Cell. “The simplicity of binder-tag can provide access to diverse proteins.”
The UNC researchers’ binder-tag technique is a way to overcome the dire challenge of seeing tiny and hard-working proteins, Cosmos noted. Typical light microscopy does not enable a view of molecules at work. This paves the way for the new binder-tag technique, UNC pointed out.
“With this method, we can see, for example, how microenvironmental differences across a cell affect—and often profoundly—what a protein is doing,” Hahn said. “For a lot of protein-related diseases, scientists haven’t been able to understand why proteins start to do the wrong thing. The tools for obtaining that understanding just haven’t been available.”
More Proteins to Study
More research is needed before the binder-tag method can be used in diagnostics. Meanwhile, the UNC scientists intend to show how binder-tag can be applied to other protein structures and functions.
“The human proteome has between 80,000 and 400,000 proteins, but not all at one time. They are expressed by 20,000 to 25,000 human genes. So, the human proteome has great promise for use in diagnostics, understanding disease, and developing therapies,” said Robert Michel, Editor-in-Chief of Dark Daily and its sister publication The Dark Report.
Medical scientists and diagnostics professionals will want to stay tuned to discover more about the tiny—though mighty—protein’s contributions to understanding diseases and patient treatment.
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.
The human proteome map provides a catalog of proteins expressed in nondiseased issues and organs to use as baseline in understanding changes that occur in disease
Given the growing importance of proteins in medical laboratory testing, pathologists will want to know about a major milestone recently achieved in this field. Researchers have announced that drafts of the complete human proteome have been released to the public.
Experts are comparing this to the first complete map of the human genome that was made public in 2000. Clinical laboratory managers and pathologists know how the availability of this information provided the foundation for rapid advances in understanding different aspects involving DNA and RNA. (more…)
Pathology groups and clinical laboratories are among the beneficiaries if the Accelerating Medicines Partnership achieves its goals
Power players in healthcare are about to invest nearly a quarter of a billion dollars to accelerate the time it takes for new medical discoveries to gain regulatory approval and enter clinical use. The emphasis will be on both therapeutic drugs and diagnostics, making this an important development for in vitro diagnostics companies and medical laboratories.
