In fact, the UB study suggests traditional anatomical methods for determining the evolutionary relationships between species may not be as accurate as once thought, an article in SciTechDaily reported.
Nevertheless, the UB’s research into convergent evolution is unlocking new insights into how genes evolve over time and this new knowledge may help researchers develop genetic tests that more accurately identify different diseases and health conditions.
Additionally, studies that bring a better understanding of how beneficial genetic mutations work their way into a species’ genome might also aid researchers in developing personalized clinical laboratory testing and therapies based on manipulating a patient’s genetic sequences in ways that would be beneficial.
Gene Sequencing More Accurate at Determining Evolutionary Relationships
The UB study suggests that existing evolutionary (phylogenetic) trees may need to be reconsidered. To put a finer point on the findings, a UB news release on the study states, “determining evolutionary trees of organisms by comparing anatomy rather than gene sequences is misleading.”
The UB scientists used genetic sequencing to quickly—and more cost effectively—determine evolutionary relationships as compared to traditional morphology (anatomy and structure), according to the news release.
They found genetic data that revealed surprising relationships about where the sequenced species originated, and which differed with prior conclusions that were drawn based on the species’ appearance. The findings suggest there may be need to “overturn centuries of scientific work in classifying relation of species by physical traits,” the UB scientists said.
“For over a hundred years, we’ve been classifying organisms according to how they look and are put together anatomically, but molecular data often tells us a rather different story,” said Matthew Wills, PhD (above), Professor of Evolutionary Paleobiology, Milner Center for Education at the University of Bath, in the news release. “Our study proves statistically that if you build an evolutionary tree of animals based on their molecular data, it often fits much better with their geographical distribution.” This new use of genetic sequencing could lead to improved precision medicine treatments and clinical laboratory testing. (Photo copyright: University of Bath.)
Molecular Data Leads to New Insights into Convergent Evolution
The UB study’s use of genetic sequencing led the researchers to a greater understanding of convergent evolution, defined by “a characteristic evolving separately in two genetically unrelated groups of organisms,” according to UB.
For example, wings are a widely developed characteristic. But they are not necessarily a sign of relatedness when it comes to birds, bats, and insects.
“Now with molecular data, we can see that convergent evolution happens all the time—things we thought were closely related often turn out to be far apart on the tree of life,” Wills said, adding, “Individuals within a family don’t always look similar; it’s the same with evolutionary trees, too.”
Family Trees: Morphology Versus Molecular
In their paper, the UB researchers acknowledged the importance of phylogenies (evolutionary history of species) in areas of biology, including medicine. They aimed to study a better way to produce accurate phylogenetic trees.
“Phylogenetic relationships are inferred principally from two classes of data: morphological and molecular,” they wrote, adding, “The superiority of molecular trees has rarely been assessed empirically.”
So, they set out to compare the two approaches to building evolutionary trees:
Traditional morphology analysis, and
Phylogenetic trees developed using molecular data.
Using 48 pairs of morphological and molecular trees, they mapped data geographically.
“We show that, on average, molecular trees provide a better fit to biogeographic data than their morphological counterparts, and that biogeographic congruence increases over research time,” the researchers wrote.
Biogeography a Better Gauge of Relatedness than Anatomy
The study also found animals on molecular trees lived geographically closer as compared to groups on morphological trees.
For example, molecular studies put aardvarks, elephants, golden moles, swimming manatees, and elephant shews in an Afrotheria group, named for Africa, which is where they came from. Therefore, the biogeography matches, however the appearances of these mammals clearly do not, the UB scientists point out.
“What’s most exciting is that we find strong statistical proof of molecular trees fitting better not just in groups like Afrotheria, but across the tree of life in birds, reptiles, insects, and plants,” said Jack Oyston PhD, UB Department of Biology and Biochemistry Research Associate and first author of the study, in the news release.
The researchers believe their findings support the accuracy of genetic-themed trees.
“It being such a widespread pattern makes it much more potentially useful as a general test of different evolutionary trees. But it also shows just how pervasive convergent evolution has been when it comes to misleading us,” Oyston added.
Advantages of Molecular Data
In their Nature Communications Biology paper, the UB scientists wrote that molecular data offer up these advantages over morphology:
Widely available in vast quantity.
Opportunity exists to “search, repurpose, and reanalyze sequenced data alongside novel sequences.”
Less subjectivity in researchers’ analysis.
Well-developed data at the ready and “still in their infancy.”
The University of Bath’s study of convergent evolution, phylogenetic trees, and comparison of molecular data versus morphology, has implications for medical laboratories. Should their research lead to new insights into how genes evolve over time, diagnostics professionals may have new information to identity diseases and work with others to precisely treat patients.
Genomic sequencing continues to benefit patients through precision medicine clinical laboratory treatments and pharmacogenomic therapies
EDITOR’S UPDATE—Jan. 26, 2022: Since publication of this news briefing, officials from Genomics England contacted us to explain the following:
The “five million genome sequences” was an aspirational goal mentioned by then Secretary of State for Health and Social Care Matt Hancock, MP, in an October 2, 2018, press release issued by Genomics England.
As of this date a spokesman for Genomics England confirmed to Dark Daily that, with the initial goal of 100,000 genomes now attained, the immediate goal is to sequence 500,000 genomes.
This goal was confirmed in a tweet posted by Chris Wigley, CEO at Genomics England.
In accordance with this updated input, we have revised the original headline and information in this news briefing that follows.
What better proof of progress in whole human genome screening than the announcement that the United Kingdom’s 100,000 Genome Project has not only achieved that milestone, but will now increase the goal to 500,000 whole human genomes? This should be welcome news to clinical laboratory managers, as it means their labs will be positioned as the first-line provider of genetic data in support of clinical care.
Many clinical pathologists here in the United States are aware of the 100,000 Genome Project, established by the National Health Service (NHS) in England (UK) in 2012. Genomics England’s new goal to sequence 500,000 whole human genomes is to pioneer a “lasting legacy for patients by introducing genomic sequencing into the wider healthcare system,” according to Technology Networks.
The importance of personalized medicine and of the power of precise, accurate diagnoses cannot be understated. This announcement by Genomics England will be of interest to diagnosticians worldwide, especially doctors who diagnose and treat patients with chronic and life-threatening diseases.
Building a Vast Genomics Infrastructure
Genetic sequencing launched the era of precision medicine in healthcare. Through genomics, drug therapies and personalized treatments were developed that improved outcomes for all patients, especially those suffering with cancer and other chronic diseases. And so far, the role of genomics in healthcare has only been expanding, as Dark Daily covered in numerous ebriefings.
Genomics England, which is wholly owned by the Department of Health and Social Care in the United Kingdom, was formed in 2012 with the goal of sequencing 100,000 whole genomes of patients enrolled in the UK National Health Service. That goal was met in 2018, and now the NHS aspires to sequence 500,000 genomes.
“The last 10 years have been really exciting, as we have seen genetic data transition from being something that is useful in a small number of contexts with highly targeted tests, towards being a central part of mainstream healthcare settings,” Richard Scott, MD, PhD (above), Chief Medical Officer at Genomics England told Technology Networks. Much of the progress has found its way into clinical laboratory testing and precision medicine diagnostics. (Photo copyright: Genomics England.)
Genomics England’s initial goals included:
To create an ethical program based on consent,
To set up a genomic medicine service within the NHS to benefit patients,
To make new discoveries and gain insights into the use of genomics, and
To begin the development of a UK genomics industry.
To gain the greatest benefit from whole genome sequencing (WGS), a substantial amount of data infrastructure must exist. “The amount of data generated by WGS is quite large and you really need a system that can process the data well to achieve that vision,” said Richard Scott, MD, PhD, Chief Medical Officer at Genomics England.
In early 2020, Weka, developer of the WekaFS, a fully parallel and distributed file system, announced that it would be working with Genomics England on managing the enormous amount of genomic data. When Genomics England reached 100,000 sequenced genomes, it had already gathered 21 petabytes of data. The organization expects to have 140 petabytes by 2023, notes a Weka case study.
Putting Genomics England’s WGS Project into Action
WGS has significantly impacted the diagnosis of rare diseases. For example, Genomics England has contributed to projects that look at tuberculosis genomes to understand why the disease is sometimes resistant to certain medications. Genomic sequencing also played an enormous role in fighting the COVID-19 pandemic.
Scott notes that COVID-19 provides an example of how sequencing can be used to deliver care. “We can see genomic influences on the risk of needing critical care in COVID-19 patients and in how their immune system is behaving. Looking at this data alongside other omics information, such as the expression of different protein levels, helps us to understand the disease process better,” he said.
What’s Next for Genomics Sequencing?
As the research continues and scientists begin to better understand the information revealed by sequencing, other areas of scientific study like proteomics and metabolomics are becoming more important.
“There is real potential for using multiple strands of data alongside each other, both for discovery—helping us to understand new things about diseases and how [they] affect the body—but also in terms of live healthcare,” Scott said.
Along with expanding the target of Genomics England to 500,000 genomes sequenced, the UK has published a National Genomic Strategy named Genome UK. This plan describes how the research into genomics will be used to benefit patients. “Our vision is to create the most advanced genomic healthcare ecosystem in the world, where government, the NHS, research and technology communities work together to embed the latest advances in patient care,” according to the Genome UK website.
Clinical laboratories professionals with an understanding of diagnostics will recognize WGS’ impact on the healthcare industry. By following genomic sequencing initiatives, such as those coming from Genomics England, pathologists can keep their labs ready to take advantage of new discoveries and insights that will improve outcomes for patients.
The new method employs a pH sensitive dye and AI algorithms to ‘distinguish between cells originating from normal and cancerous tissue, as well as among different types of cancer’ the researchers said
Might a pH-sensitive dye in tandem with an image analysis solution soon be used to identify cancerous cells within blood samples as well within tissue? Recent research indicates that could be a possibility. If further studies and clinical trials confirm this capability, then anatomic pathologists could gain another valuable tool to use in diagnosing cancers and other types of disease.
Currently, surgical pathologists use a variety of hematoxylin and eosin stains (H/E) to bring out useful features in cells and cell structures. So, staining tissue on glass slides is a common practice. Now, thanks to machine learning and artificial intelligence, anatomic pathologists may soon have a similar tool for spotting cancer cells within both tissue and blood samples.
Researchers at the National University of Singapore (NUS) have developed a method for identifying cancer that uses a pH sensitive dye called bromothymol blue. The dye reacts to various levels of acidity in cancer cells by turning colors. “The pH inside cancer cells tends to be higher than that of healthy cells. This phenomenon occurs at the very early phases of cancer development and becomes amplified as it progresses,” Labroots reported.
In “Machine Learning Based Approach to pH Imaging and Classification of Single Cancer Cells,” published in the journal APL Bioengineering, the NUS researchers wrote, “Here, we leverage a recently developed pH imaging modality and machine learning-based single-cell segmentation and classification to identify different cancer cell lines based on their characteristic intracellular pH. This simple method opens up the potential to perform rapid noninvasive identification of living cancer cells for early cancer diagnosis and further downstream analyses.”
According to an NUS news release, the bromothymol blue dye is “applied onto patients’ cells” being held ex vivo in cell culture dishes. The dye’s color changes depending on the acidity level of the cancer cells it encounters. Microscopic images of the now-visible cancers cells are taken, and a machine-learning algorithm analyzes the images before generating a report for the anatomic pathologist.
The NUS researchers claim the test can provide answers in about half an hour with 95% accuracy, Labroots reported.
“The ability to analyze single cells is one of the holy grails of health innovation for precision medicine or personalized therapy. Our proof-of-concept study demonstrates the potential of our technique to be used as a fast, inexpensive and accurate tool for cancer diagnosis,” said Lim Chwee Teck, PhD, NUS Society Professor and Director of NUS’ Institute for Health Innovation and Technology, in the NUS news release.
The novel technique for differentiating cancer cells from non-cancerous cells being developed at the National University of Singapore (NUS) could eventually become useful in detecting cancer cells in tissue samples, either obtained from tumor biopsies or blood samples. “As the number of cells in these samples can be in millions or even billions, the ability to detect the very few cancer cells among the others will be useful for clinicians,” NUS Society Professor and Director of NUS’ Institute for Health Innovation and Technology, Lim Chwee Teck, PhD (above) told The Straits Times. (Photo copyright: The Straits Times.)
AI Cell Analysis versus Laborious Medical Laboratory Steps
By developing an AI-driven method, Professor Lim and the NUS team sought to improve upon time-consuming techniques for identifying cells that traditionally involve using florescent probes, nanoparticles, and labeling steps, or for cells to be fixed or terminated.
“Unlike other cell analysis techniques, our approach uses simple, inexpensive equipment, and does not require lengthy preparation and sophisticated devices. Using AI, we are able to screen cells faster and accurately,” Professor Lim told Labroots. “Furthermore, we can monitor and analyze living cells without causing any toxicity to the cells or the need to kill them.”
The new technique may have implications for cancer detection in tumor tissue as well as in liquid biopsies.
“We are also exploring the possibility of performing the real-time analysis on circulating cancer cells suspended in blood,” Professor Lim said in the NUS news release. “One potential application for this would be in liquid biopsy where tumor cells that escaped from a primary tumor can be isolated in a minimally-invasive fashion from bodily fluids such as blood.”
Diagnosing Cancer in Real Time
The NUS’ method requires more research and clinical studies before it could become an actual tool for anatomic pathologists and other cancer diagnosticians. Additionally, the NUS researchers acknowledged that the focus on only four cell lines (normal cells, benign breast tumor cells, breast cancer cells, and pancreatic cancer cells) limited their study, as did lack of comparison with conventional florescent pH indicators.
Still, the NUS scientists are already planning more studies to advance their concept to different stages of cell malignancy. They envision a “real-time” version of the technique to enable recognition of cells and fast separation of those that need to be referred to clinical laboratories for molecular testing and/or genetic sequencing.
Medical laboratory leaders may want to follow the NUS study. An inexpensive AI-driven method that can accurately detect and classify cancer cells based on pH within the cells is provocative and may be eventually become integrated with other cancer diagnostics.
All-of-Us program is free to participants and provides data to more than 800 research studies for cancer, COVID-19, Alzheimer’s, and other diseases; findings will lead to new biomarkers for clinical laboratory tests
It is hard to say no to free. At least that is what the National Institutes of Health (NIH) is counting on to help increase the size and diversity of its database of genetic sequences. The NIH’s All-of-Us Research Program is offering free genetic testing for all participants in the program, as well as free wearable Fitbits for those selected to provide lifestyle and behavior data.
Many pathologists and clinical laboratory managers know that this group of researchers hope to build a database of more than one million genetic sequences to better understand “how certain genetic traits affect underrepresented communities, which could greatly affect the future of customized healthcare,” CBS affiliate 8 News Now reported.
“Customized healthcare” is a euphemism for precision medicine, and genetic sequencing is increasingly playing a key role in the development of personalized diagnostics and therapeutics for cancer and other deadly diseases.
In “VA’s ‘Million Veterans Program’ Research Study Receives Its 100,000th Human Genome Sequence,” Dark Daily described how the NIH’s All-of-Us program was launched in 2018 to aid research into health outcomes influenced by genetics, environments, and lifestyle. At that time, the program had biological samples from more than 270,000 people with a goal of one million participants.
Matthew Thombs, Senior Project Manager of Digital Health Technology at Scripps Research in La Jolla, Calif., joined the All-of-Us program after losing a family member “to a condition I believe could have been managed with changes to their lifestyle,” he told 8 News Now.
“What we are building will empower researchers with the information needed to make such conclusions (about possible need to change lifestyles) and forever alter how diseases are treated,” he added. “I hope that what we are doing here will help my son grow up in a world where healthcare is more of a priority, and many of the ailments we see today are things of the past.”
Such genetic testing could discover biomarkers for future personalized clinical laboratory diagnostics and drug therapies, a key aspect of precision medicine.
The photo above shows an All-of-Us participant being prepped to provide a biological sample for genetic testing. According to Matthew Thombs, Senior Project Manager of Digital Health Technology at Scripps Research, “participants can provide as much or as little information as they like, every single data point matters.” The collected data is shared anonymously with more than 800 research studies for COVID-19, Alzheimer’s, cancer, and other diseases, 8 News Now reported. (Photo copyright: KLAS-TV.)
Scripps Research Integrates Mobile Health Technology into All-of-Us Program
A critical aspect of the NIH’s research is determining how people’s behavior combined with their genetics may predispose them to certain diseases. Nonprofit research institution Scripps Research is working with the NIH’s All of Us Research Program to enroll and collect biological samples from one million US residents.
In addition, Scripps is fitting study participants with wearable mobile health devices to capture data on their habits and lifestyles.
“Until now, the treatment and prevention of disease has been based on a ‘one-size-fits-all’ approach, with most therapeutics tailored for the ‘average patient’. However, advances in genomic sequencing, mobile health technologies, and increasingly sophisticated informatics are ushering in a new era of precision medicine. This new approach takes into account differences in people’s genes, environment, and lifestyles giving medical professionals resources to design targeted treatments and prevention strategies for the individual,” Scripps states on its website.
Can wearable fitness devices and related data contribute to research on genetics and healthcare outcomes? Scripps aims to find out. It has fitted 10,000 people in the All-of-Us program with Fitbit devices (Fitbit Charge 4 tracker or Fitbit Versa 3 smartwatch) at no cost. Since February, Scripps has distributed 10,000 Fitbit wearable devices through the All-of-Us program.
“By sharing information about their health, habits, and environment, participants will help researchers understand why people get sick or stay healthy,” the Scripps website adds.
The Scripps researchers plan to analyze how the people use the wearable devices. They are also accumulating data about participants’ physical activity, heart rate, sleep, and other health metrics and outcomes “as part of the broader All of Us program,” a Scripps news release explained.
“This is the first time All of Us is distributing devices to participants. Our goal is to better understand how participants engage during research studies in order to continually improve user experience and participation. We also expect to learn more about how wearable data may inform the personalization of healthcare,” said Julia Moore Vogel, PhD, Director of The Participant Center at the All of Us Research Program at Scripps Research, in the news release.
All-of-Us Program Records ‘Significant Progress in Participant Diversity’
As of June, the NIH has enrolled 386,000 participants into the All-of-Us program, with 278,000 consenting to all of the program’s steps. Eighty percent of biological samples in the collection are from people in communities that have been under-represented in previous biomedical research an NIH new release noted. According to the NIH, that gives the All-of-Us research program “the most diverse dataset.”
What will all this research ultimately bring to clinical laboratories? Who knows? Nevertheless, if federal institutions like the NIH and non-profit research companies like Scripps believe precision medicine is worth investing in, then the All-of-Us program is worth watching.
A diverse database of a million genetic sequences combined with lifestyle and behavioral data may lead to new and improved personalized diagnostics and drug therapies.
Gene sequencing is enabling disease tracking in new ways that include retesting laboratory specimens from before the SARS-CoV-2 outbreak to determine when it arrived in the US
On February 26 of this year, nearly 200 executives and employees of neuroscience-biotechnology company Biogen gathered at the Boston Marriott Long Wharf hotel for their annual leadership conference. Unbeknownst to the attendees, by the end of the following day, dozens of them had been exposed to and become infected by SARS-CoV-2, the coronavirus that causes the COVID-19 illness.
Researchers now have hard evidence that attendees at this meeting returned to their communities and spread the infection. The findings of this study will be relevant to pathologists and clinical laboratory managers who are cooperating with health authorities in their communities to identify infected individuals and track the spread of the novel coronavirus.
This “superspreader” event has been closely investigated and has led to intriguing conclusions concerning the use of genetic sequencing to revealed vital information about the COVID-19 pandemic. Recent improvements in gene sequencing technology is giving scientists new ways to trace the spread of COVID-19 and other diseases, as well as a method for monitoring mutations and speeding research into various treatments and vaccines.
Genetic Sequencing Traces an Outbreak
“With genetic data, a record of our poor decisions is being captured in a whole new way,” Bronwyn MacInnis, PhD, Director of Pathogen Genomic Surveillance at the Broad Institute of MIT and Harvard, told The Washington Post (WaPo) during its analysis of the COVID-19 superspreading event. MacInnis is one of many Broad Institute, Harvard, MIT, and state of Massachusetts scientists who co-authored a study that detailed the coronavirus’ spread across Boston, including from the Biogen conference.
What they discovered is both surprising and enlightening. According to WaPo’s report, at least 35 new cases of the virus were linked directly to the Biogen conference, and the same strain was discovered in outbreaks in two homeless shelters in Boston, where 122 people were infected. The variant tracked by the Boston researchers was found in roughly 30% of the cases that have been sequenced in the state, as well as in Alaska, Senegal, and Luxembourg.
“The data reveal over 80 introductions into the Boston area, predominantly from elsewhere in the United States and Europe. We studied two superspreading events covered by the data, events that led to very different outcomes because of the timing and populations involved. One produced rapid spread in a vulnerable population but little onward transmission, while the other was a major contributor to sustained community transmission,” the researchers noted in their study abstract.
“The same two events differed significantly in the number of new mutations seen, raising the possibility that SARS-CoV-2 superspreading might encompass disparate transmission dynamics. Our results highlight the failure of measures to prevent importation into [Massachusetts] early in the outbreak, underscore the role of superspreading in amplifying an outbreak in a major urban area, and lay a foundation for contact tracing informed by genetic data,” they concluded.
The use of genetic sequencing to trace the virus could inform measures to control the spread in new ways, but currently, only about 0.33% of cases in the United States are being sequenced, MacInnis told WaPo, and that not sequencing samples is “throwing away the crown jewels of what you really want to know.”
Another role that genetic sequencing is playing in this pandemic is in tracking viral mutations. One of the ways that pandemics worsen is when viruses mutate to become deadlier or more easily spread. Scientists are using genetic sequencing to monitor SARS-CoV-2 for such mutations.
A group of scientists at Texas A&M University led by Yue Xing, PhD, published a paper titled, “MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences,” which explains that “Although most mutations are expected to be selectively neural, it is important to monitor if SARS-CoV-2 will eventually evolve to be a stronger or weaker infectious agent as time goes on. Therefore, it is vital to track mutations from newly sequenced SARS-CoV-2 genome.”
Korber’s findings are important because the mutation the scientists identified appears to have a fitness advantage. “Our data show that, over the course of one month, the variant carrying the D614G Spike mutation became the globally dominant form of SARS-CoV-2,” they wrote. Additionally, the study noted, people infected with the mutated variant appear to have a higher viral load in their upper respiratory tracts.
Genetic Sequencing, the Race for Treatments, Vaccines, and Managing Future Pandemics
If, as Fauci and Morens predict, future pandemics are likely, improvements in gene sequencing and analysis will become even more important for tracing, monitoring, and suppressing outbreaks. Clinical laboratory managers will want to watch this closely, as medical labs that process genetic sequencing will, no doubt, be part of that operation.
