Can fruit fly research help improve survival of cancer patients?

The experience of a fruit fly dying from cancer may seem worlds away from that of a human with a life-threatening tumor, yet University of California, Berkeley, researchers are finding commonalities between the two that could lead to ways to prolong the lives of cancer patients.

Fruit fly research is already pointing to a new anti-cancer strategy distinct from the conventional goal of destroying the tumor or cancerous cells. Instead, the research suggests, launching an attack against the destructive chemicals the cancer is throwing off could increase survival rates and improve patients' health.

"It's a really complementary way of thinking about therapy," said David Bilder, UC Berkeley professor of molecular and cell biology. "You're trying to help the host deal with the effects of the tumor, rather than killing the tumor itself."

Jung Kim, a postdoctoral fellow in Bilder's lab, recently discovered that tumors in fruit flies release a chemical that compromises the barrier between the bloodstream and the brain, letting the two environments mix -- a recipe for disaster in numerous diseases, including infection, trauma and even obesity. In collaboration with the labs of UC Berkeley professors David Raulet and Kaoru Saijo, Kim and Bilder subsequently demonstrated that tumors in mice that release the same chemical, a cytokine called interleukin-6 (IL-6), also make the blood-brain barrier leaky.

More importantly, they were able to extend the lifespan of both fruit flies and mice with malignant tumors by blocking the effect of the cytokine on the barrier.

"The IL-6 cytokine is known to cause inflammation. What's new here is that this tumor-induced inflammation is actually causing the blood-brain barrier to open. If we interfere with that opening process but leave the tumor alone, then the host can live significantly longer and healthier with the same tumor burden," Bilder said.

IL-6 plays other important roles in the body, so to benefit cancer patients, scientists would have to find a drug that blocks its action at the blood-brain barrier without altering its effects elsewhere. But such a drug could potentially extend the life span and health span of human cancer patients, he said.

Six years ago, Bilder's team found that tumors in fruit flies also release a substance that blocks the effects of insulin, providing a potential explanation for the tissue wasting called cachexia that kills one-fifth of all cancer patients. That work is now being explored by numerous labs around the world.

One advantage of helping the host fend off a tumor's effects on tissues far from the tumor site is that it could potentially reduce or even eliminate the need for toxic drugs typically used to subdue tumors. Such drugs also harm the patient, killing healthy cells as well as cancerous cells.

Beyond these side effects, targeting tumor cells "also selects for resistance in the tumor, because the tumor has genetic variability -- a drug-resistant clone arises that will then cause cancer recurrence," he said. "But if you could target the host cells, they have a stable genome and are not going to gain resistance to these drugs. That's our goal: to understand the ways that the tumor is affecting the host and attack the host side of the tumor-host dialogue."

Bilder and his colleagues published their work on IL-6 disruption of the blood-brain barrier last week in the journal Developmental Cell, and he authored a review of the impact that fruit fly research has had on understanding tumor-host interactions that was published last month in the journal Nature Reviews Cancer. Their cachexia work appeared in 2015 in Developmental Cell.

What actually kills cancer patients?

According to Bilder, scientists still are uncertain what causes death in many cancer patients. Cancer of the liver, for example, clearly destroys the function of an organ essential for life. However, other organs, like the skin or the ovaries, are less critical, yet people die from cancer in these sites, too, sometimes very quickly. And though cancers often metastasize to other organs -- multiple organ failure is one of the main causes of cancer death listed by doctors -- Bilder questions if that's the whole story.

"Many human cancers are metastatic, but that doesn't change the basic question: Why does the cancer kill?" he said. "If your tumor metastasized to the lung, are you dying because of lung failure or are you dying from something else?"

For that reason, he works with non-metastatic tumors implanted in fruit flies and mice and looks for systemic effects, not merely the effects on the tumor-containing organ itself.

One systemic effect of cancer is cachexia, the inability to maintain weight, which leads to wasting of muscle even when the patient is receiving intravenous nutrition. While Bilder discovered one possible reason for this -- cancers release a chemical that prevents insulin from storing energy in the body -- other scientists have found additional substances released by cancers that may also be responsible for tissue wasting.

Like cachexia, breaches in the blood-brain barrier may be another long-distance effect of tumors. In the new study, the researchers found that blocking the activity of IL-6 at the blood-brain barrier increased the lifespan of flies with cancer by 45%. Laboratory mice must be euthanized before they suffer and die from experimental cancer, but the team found that after 21 days, 75% of cancer-carrying mice treated with an IL-6 receptor blocker were alive, versus only 25% of untreated mice with cancer.

"It's not just the breakdown of the blood-brain barrier that's killing the animals," Bilder said. "Flies can live for three or four weeks with a leaky blood-brain barrier, whereas, if they have a tumor, they die almost immediately when the barrier is compromised. So, we think that the tumor is causing something else to happen. Maybe it's putting something in circulation that then gets through the broken barrier, though it could also be something going the other way, from the brain into the blood."

Bilder has found additional cancer-produced chemicals in flies that he's linked to edema -- bloating from excess fluid retention -- and excess blood clotting, which leads to blocked veins. Both conditions frequently accompany cancer. Other researchers have found tumor-produced fly chemicals linked to anorexia -- the loss of appetite -- and to immune disfunction, which also are symptoms of many cancers.

Bilder said that studying cancer in fruit flies offers several advantages over cancer models in other animals, such as mice and rats. For one thing, researchers can follow flies right up to the moment of death, in order to determine what actually causes mortality. Ethical concerns prevent researchers from allowing vertebrates to suffer, so research animals are euthanized before they die naturally, preventing a full understanding of the ultimate cause of death. For these animals, tumor size is used as a proxy to assess an animal's chance of survival.

"We're incredibly excited about the potential to look directly at survival and life span," he said. "We think that this is a real blind spot that hasn't allowed scientists to address questions about how the tumor is actually killing outside of its local growth. That's not to say that tumor size is misleading, but fruit flies give us a complementary way of looking at what cancer is doing."

And while most cancer studies in rodents involve just a few dozen animals, fruit fly experiments can involve many hundreds of individuals, which improves the statistical significance of the results. Fruit flies also reproduce quickly and have short natural life spans, allowing quicker studies.

Bilder acknowledges that fruit flies and humans are only distantly related, but in the past, these flies -- Drosophila melanogaster -- have played a key role in understanding tumor growth factors and oncogenes. Fruit flies now could also be key in understanding cancer's systemic effects.

"Not only can flies get tumors that resemble human tumors, which we described 20 years ago, but we're now seeing that the host response has remarkable similarities in cachexia, coagulopathies, immune response, cytokine production, all of these things," he said. "I think it (the tumor-host response in fruit flies) is a superrich area. Our hope is to bring attention to the field and attract other people to work in it, both from the fly perspective and from the cancer biology and clinician perspective."

Co-authors of the new paper include UC Berkeley postdoc Hsiu-Chun Chuang, graduate student Natalie Wolf and former doctoral student Christopher Nicolai.The work was supported by the National Institutes of Health (GM090150, GM130388, AI113041, HD092093).

Journal References:

1. Jung Kim, Hsiu-Chun Chuang, Natalie K. Wolf, Christopher J. Nicolai, David H. Raulet, Kaoru Saijo, David Bilder. Tumor-induced disruption of the blood-brain barrier promotes host death. Developmental Cell, 2021; DOI: 10.1016/j.devcel.2021.08.010
2. David Bilder, Katy Ong, Tsai-Ching Hsi, Kavya Adiga, Jung Kim. Tumour–host interactions through the lens of Drosophila. Nature Reviews Cancer, 2021; DOI: 10.1038/s41568-021-00387-5
3. Alejandra Figueroa-Clarevega, David Bilder. Malignant Drosophila Tumors Interrupt Insulin Signaling to Induce Cachexia-like Wasting. Developmental Cell, 2015; 33 (1): 47 DOI: 10.1016/j.devcel.2015.03.001 
   

 Courtesy:

University of California - Berkeley. "Can fruit fly research help improve survival of cancer patients? New anti-cancer strategy -- blocking chemicals produced by tumors -- could boost life span, health span." ScienceDaily. ScienceDaily, 16 September 2021. <www.sciencedaily.com/releases/2021/09/210916131326.htm>.

 

Scientists discover 14 genes that cause obesity

 Promising news in the effort to develop drugs to treat obesity: University of Virginia scientists have identified 14 genes that can cause and three that can prevent weight gain. The findings pave the way for treatments to combat a health problem that affects more than 40% of American adults.

"We know of hundreds of gene variants that are more likely to show up in individuals suffering obesity and other diseases. But 'more likely to show up' does not mean causing the disease. This uncertainty is a major barrier to exploit the power of population genomics to identify targets to treat or cure obesity. To overcome this barrier, we developed an automated pipeline to simultaneously test hundreds of genes for a causal role in obesity. Our first round of experiments uncovered more than a dozen genes that cause and three genes that prevent obesity," said Eyleen O'Rourke of UVA's College of Arts & Sciences, the School of Medicine's Department of Cell Biology and the Robert M. Berne Cardiovascular Research Center. "We anticipate that our approach and the new genes we uncovered will accelerate the development of treatments to reduce the burden of obesity."

OBESITY AND OUR GENES

O'Rourke's new research helps shed light on the complex intersections of obesity, diet and our DNA. Obesity has become an epidemic, driven in large part by high-calorie diets laden with sugar and high-fructose corn syrup. Increasingly sedentary lifestyles play a big part as well. But our genes play an important role too, regulating fat storage and affecting how well our bodies burn food as fuel. So if we can identify the genes that convert excessive food into fat, we could seek to inactivate them with drugs and uncouple excessive eating from obesity.

Genomicists have identified hundreds of genes associated with obesity -- meaning the genes are more or less prevalent in people who are obese than in people with healthy weight. The challenge is determining which genes play causal roles by directly promoting or helping prevent weight gain. To sort wheat from chaff, O'Rourke and her team turned to humble worms known as C. elegans. These tiny worms like to live in rotting vegetation and enjoy feasting on microbes. However, they share more than 70% of our genes, and, like people, they become obese if they are fed excessive amounts of sugar.

The worms have produced great benefits for science. They've been used to decipher how common drugs, including the antidepressant Prozac and the glucose-stabilizing metformin, work. Even more impressively, in the last 20 years three Nobel prizes were awarded for the discovery of cellular processes first observed in worms but then found to be critical to diseases such as cancer and neurodegeneration. They've also been fundamental to the development of therapeutics based on RNA technology.

In new work just published in the scientific journal PLOS Genetics, O'Rourke and her collaborators used the worms to screen 293 genes associated with obesity in people, with the goal of defining which of the genes were actually causing or preventing obesity. They did this by developing a worm model of obesity, feeding some a regular diet and some a high-fructose diet.

This obesity model, coupled to automation and supervised machine learning-assisted testing, allowed them to identify 14 genes that cause obesity and three that help prevent it. Enticingly, they found that blocking the action of the three genes that prevented the worms from becoming obese also led to them living longer and having better neuro-locomotory function. Those are exactly the type of benefits drug developers would hope to obtain from anti-obesity medicines.

More work needs to be done, of course. But the researchers say the indicators are encouraging. For example, blocking the effect of one of the genes in lab mice prevented weight gain, improved insulin sensitivity and lowered blood sugar levels. These results (plus the fact that the genes under study were chosen because they were associated with obesity in humans) bode well that the results will hold true in people as well, the researchers say.

"Anti-obesity therapies are urgently needed to reduce the burden of obesity in patients and the healthcare system," O'Rourke said. "Our combination of human genomics with causality tests in model animals promises yielding anti-obesity targets more likely to succeed in clinical trials because of their anticipated increased efficacy and reduced side effects."

Journal Reference:

1. Wenfan Ke, Jordan N. Reed, Chenyu Yang, Noel Higgason, Leila Rayyan, Carolina Wählby, Anne E. Carpenter, Mete Civelek, Eyleen J. O’Rourke. Genes in human obesity loci are causal obesity genes in C. elegans. PLOS Genetics, 2021; 17 (9): e1009736 DOI: 10.1371/journal.pgen.1009736 

Courtesy:

University of Virginia Health System. "Scientists discover 14 genes that cause obesity: Findings could decouple overeating from harmful health effects." ScienceDaily. ScienceDaily, 1 October 2021. <www.sciencedaily.com/releases/2021/10/211001100432.htm>.

 

 

Brain cell differences could be key to learning in humans and AI

 Imperial researchers have found that variability between brain cells might speed up learning and improve the performance of the brain and future artificial intelligence (AI).

The new study found that by tweaking the electrical properties of individual cells in simulations of brain networks, the networks learned faster than simulations with identical cells.

They also found that the networks needed fewer of the tweaked cells to get the same results, and that the method is less energy intensive than models with identical cells.

The authors say that their findings could teach us about why our brains are so good at learning, and might also help us to build better artificially intelligent systems, such as digital assistants that can recognise voices and faces, or self-driving car technology.

First author Nicolas Perez, a PhD student at Imperial College London's Department of Electrical and Electronic Engineering, said: "The brain needs to be energy efficient while still being able to excel at solving complex tasks. Our work suggests that having a diversity of neurons in both brains and AI systems fulfils both these requirements and could boost learning."

The research is published in Nature Communications.

Why is a neuron like a snowflake?

The brain is made up of billions of cells called neurons, which are connected by vast 'neural networks' that allow us to learn about the world. Neurons are like snowflakes: they look the same from a distance but on further inspection it's clear that no two are exactly alike.

By contrast, each cell in an artificial neural network -- the technology on which AI is based -- is identical, with only their connectivity varying. Despite the speed at which AI technology is advancing, their neural networks do not learn as accurately or quickly as the human brain -- and the researchers wondered if their lack of cell variability might be a culprit.

They set out to study whether emulating the brain by varying neural network cell properties could boost learning in AI. They found that the variability in the cells improved their learning and reduced energy consumption.

Lead author Dr Dan Goodman, of Imperial's Department of Electrical and Electronic Engineering, said: "Evolution has given us incredible brain functions -- most of which we are only just beginning to understand. Our research suggests that we can learn vital lessons from our own biology to make AI work better for us."

Tweaked timing

To carry out the study, the researchers focused on tweaking the "time constant" -- that is, how quickly each cell decides what it wants to do based on what the cells connected to it are doing. Some cells will decide very quickly, looking only at what the connected cells have just done. Other cells will be slower to react, basing their decision on what other cells have been doing for a while.

After varying the cells' time constants, they tasked the network with performing some benchmark machine learning tasks: to classify images of clothing and handwritten digits; to recognise human gestures; and to identify spoken digits and commands.

The results show that by allowing the network to combine slow and fast information, it was better able to solve tasks in more complicated, real-world settings.

When they changed the amount of variability in the simulated networks, they found that the ones that performed best matched the amount of variability seen in the brain, suggesting that the brain may have evolved to have just the right amount of variability for optimal learning.

Nicolas added: "We demonstrated that AI can be brought closer to how our brains work by emulating certain brain properties. However, current AI systems are far from achieving the level of energy efficiency that we find in biological systems.

"Next, we will look at how to reduce the energy consumption of these networks to get AI networks closer to performing as efficiently as the brain."

This research was funded by the Engineering and Physical Sciences Research Council and Imperial College President's PhD Scholarship

 Journal Reference:

1. Nicolas Perez-Nieves, Vincent C. H. Leung, Pier Luigi Dragotti, Dan F. M. Goodman. Neural heterogeneity promotes robust learning. Nature Communications, 2021; 12 (1) DOI: 10.1038/s41467-021-26022-3

 Courtesy: Imperial College London. "Brain cell differences could be key to learning in humans and AI." ScienceDaily. ScienceDaily, 6 October 2021. <www.sciencedaily.com/releases/2021/10/211006112626.htm>.

A multidimensional view of the coronavirus

 

What exactly happens when the corona virus SARS-CoV-2 infects a cell? In an article published in Nature, a team from the Technical University of Munich (TUM) and the Max Planck Institute of Biochemistry paints a comprehensive picture of the viral infection process. For the first time, the interaction between the coronavirus and a cell is documented at five distinct proteomics levels during viral infection. This knowledge will help to gain a better understanding of the virus and find potential starting points for therapies.

When a virus enters a cell, viral and cellular protein molecules begin to interact. Both the replication of the virus and the reaction of the cells are the result of complex protein signaling cascades. A team led by Andreas Pichlmair, Professor of Immunopathology of Viral Infections at the Institute of Virology at TUM, and Matthias Mann, Head of the Department of Proteomics and Signal Transduction at the Max Planck Institute of Biochemistry, has systematically recorded how human lung cells react to individual proteins of the covid-19 pathogen SARS-CoV-2 and the SARS coronavirus, the latter of which has been known for some time.

A detailed interaction map

To this end, more than 1200 samples were analyzed using the state-of-the-art mass spectrometry techniques and advanced bioinformatic methods. The result is a freely accessible dataset that provides information on which cellular proteins the viral proteins bind to and the effects of these interactions on the cell. In total, 1484 interactions between viral proteins and human cellular proteins were discovered. "Had we only looked at proteins, however, we would have missed out on important information," says Andreas Pichlmair. "A database that only includes the proteome would be like a map containing just the place names but no roads or rivers. If you knew about the connections between the points on that map, you could gain much more useful information."

According to Pichlmair, important counterparts to the network of traffic routes on a map are protein modifications called phosphorylation and ubiquitination. Both are processes in which other molecules are attached to proteins, thereby altering their functions. In a listing of proteins, these changes are not measured, so that there is no way of knowing whether proteins are active or inactive, for example. "Through our investigations, we systematically assign functions to the individual components of the pathogen, in addition to the cellular molecules that are switched off by the virus," explains Pichlmair. "There has been no comparable mapping for SARS-CoV-2 so far," adds Matthias Mann. "In a sense, we have taken a close look at five dimensions of the virus during an infection: its own active proteins and its effects on the host proteome, ubiquitinome, phosphoproteome and transcriptome."

Insights into how the virus works

Among other things, the database can also serve as a tool to find new drugs. By analyzing protein interactions and modifications, vulnerability hotspots of SARS-CoV-2 can be identified. These proteins bind to particularly important partners in cells and could serve as potential starting points for therapies. For example, the scientists concluded that certain compounds would inhibit the growth of SARS-CoV-2. Among them were some whose antiviral function is known, but also some compounds which have not yet been studied for efficacy against SARS-CoV-2. Further studies are needed to determine whether they show efficacy in clinical use against Covid-19.

"Currently, we are working on new anti Covid-19 drug candidates, that we have been able to identify through our analyses," says Andreas Pichlmair. "We are also developing a scoring system for automated identification of hotspots. I am convinced that detailed data sets and advanced analysis methods will enable us to develop effective drugs in a more targeted manner in the future and limit side effects in advance."

 

ournal Reference:

1. Alexey Stukalov, Virginie Girault, Vincent Grass, Ozge Karayel, Valter Bergant, Christian Urban, Darya A. Haas, Yiqi Huang, Lila Oubraham, Anqi Wang, M. Sabri Hamad, Antonio Piras, Fynn M. Hansen, Maria C. Tanzer, Igor Paron, Luca Zinzula, Thomas Enghleitner, Maria Reinecke, Teresa M. Lavacca, Rosina Ehmann, Roman Wölfel, Jörg Jores, Bernhard Kuster, Ulrike Protzer, Roland Rad, John Ziebuhr, Volker Thiel, Pietro Scaturro, Matthias Mann, Andreas Pichlmair. Multilevel proteomics reveals host perturbations by SARS-CoV-2 and SARS-CoV. Nature, 2021; DOI: 10.1038/s41586-021-03493-4 

Courtesy: ScienceDaily

Technical University of Munich (TUM). "A multidimensional view of the coronavirus: COVID-19: Analysis of protein interactions as a route to new drugs." ScienceDaily. ScienceDaily, 12 April 2021. <www.sciencedaily.com/releases/2021/04/210412142727.htm>.

 

How brain cells repair their DNA reveals 'hot spots' of aging and disease

Neurons lack the ability to replicate their DNA, so they're constantly working to repair damage to their genome. Now, a new study by Salk scientists finds that these repairs are not random, but instead focus on protecting certain genetic "hot spots" that appear to play a critical role in neural identity and function.

The findings, published in the April 2, 2021, issue of Science, give novel insights into the genetic structures involved in aging and neurodegeneration, and could point to the development of potential new therapies for diseases such Alzheimer's, Parkinson's and other age-related dementia disorders.

"This research shows for the first time that there are sections of genome that neurons prioritize when it comes to repair," says Professor and Salk President Rusty Gage, the paper's co-corresponding author. "We're excited about the potential of these findings to change the way we view many age-related diseases of the nervous system and potentially explore DNA repair as a therapeutic approach."

Unlike other cells, neurons generally don't replace themselves over time, making them among the longest-living cells in the human body. Their longevity makes it even more important that they repair lesions in their DNA as they age, in order to maintain their function over the decades of a human life span. As they get older, neurons' ability to make these genetic repairs declines, which could explain why people develop age-related neurodegenerative diseases like Alzheimer's and Parkinson's.

To investigate how neurons maintain genome health, the study authors developed a new technique they term Repair-seq. The team produced neurons from stem cells and fed them synthetic nucleosides -- molecules that serve as building blocks for DNA. These artificial nucleosides could be found via DNA sequencing and imaged, showing where the neurons used them to make repairs to DNA that was damaged by normal cellular processes. While the scientists expected to see some prioritization, they were surprised by just how focused the neurons were on protecting certain sections of the genome.

"What we saw was incredibly sharp, well-defined regions of repair; very focused areas that were substantially higher than background levels," says co-first and co-corresponding author Dylan Reid, a former Salk postdoctoral scholar and now a fellow at Vertex Pharmaceutics. "The proteins that sit on these 'hot spots' are implicated in neurodegenerative disease, and the sites are also linked to aging."

The authors found approximately 65,000 hot spots that covered around 2 percent of the neuronal genome. They then used proteomics approaches to detect what proteins were found at these hot spots, implicating many splicing-related proteins. (These are involved in the eventual production of other proteins.) Many of these sites appeared to be quite stable when the cells were treated with DNA-damaging agents, and the most stable DNA repair hot spots were found to be strongly associated with sites where chemical tags attach ("methylation") that are best at predicting neuronal age.

Previous research has focused on identifying the sections of DNA that suffer genetic damage, but this is the first time researchers have looked for where the genome is being heavily repaired.

"We flipped the paradigm from looking for damage to looking for repair, and that's why we were able to find these hot spots," Reid says. "This is really new biology that might eventually change how we understand neurons in the nervous system, and the more we understand that, the more we can look to develop therapies addressing age-related diseases."

Gage, who holds the Vi and John Adler Chair for Research on Age-Related Neurodegenerative Disease, adds, "Understanding which areas within the genome are vulnerable to damage is a very exciting topic for our lab. We think Repair-seq will be a powerful tool for research, and we continue to explore additional new methods to study genome integrity, particularly in relation to aging and disease."

 Journal Reference:

1. Dylan A. Reid, Patrick J. Reed, Johannes C. M. Schlachetzki, Ioana I. Nitulescu, Grace Chou, Enoch C. Tsui, Jeffrey R. Jones, Sahaana Chandran, Ake T. Lu, Claire A. McClain, Jean H. Ooi, Tzu-Wen Wang, Addison J. Lana, Sara B. Linker, Anthony S. Ricciardulli, Shong Lau, Simon T. Schafer, Steve Horvath, Jesse R. Dixon, Nasun Hah, Christopher K. Glass, Fred H. Gage. Incorporation of a nucleoside analog maps genome repair sites in postmitotic human neurons. Science, 2021; 372 (6537): 91 DOI: 10.1126/science.abb9032 

Courtesy: ScienceDaily

Salk Institute. "How brain cells repair their DNA reveals 'hot spots' of aging and disease." ScienceDaily. ScienceDaily, 1 April 2021. <www.sciencedaily.com/releases/2021/04/210401151248.htm>.

 

 

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Novel coronavirus circulated undetected months before first COVID-19 cases in Wuhan, China

Using molecular dating tools and epidemiological simulations, researchers at University of California San Diego School of Medicine, with colleagues at the University of Arizona and Illumina, Inc., estimate that the SARS-CoV-2 virus was likely circulating undetected for at most two months before the first human cases of COVID-19 were described in Wuhan, China in late-December 2019.

Writing in the March 18, 2021 online issue of Science, they also note that their simulations suggest that the mutating virus dies out naturally more than three-quarters of the time without causing an epidemic.

"Our study was designed to answer the question of how long could SARS-CoV-2 have circulated in China before it was discovered," said senior author Joel O. Wertheim, PhD, associate professor in the Division of Infectious Diseases and Global Public Health at UC San Diego School of Medicine.

"To answer this question, we combined three important pieces of information: a detailed understanding of how SARS-CoV-2 spread in Wuhan before the lockdown, the genetic diversity of the virus in China and reports of the earliest cases of COVID-19 in China. By combining these disparate lines of evidence, we were able to put an upper limit of mid-October 2019 for when SARS-CoV-2 started circulating in Hubei province."

Cases of COVID-19 were first reported in late-December 2019 in Wuhan, located in the Hubei province of central China. The virus quickly spread beyond Hubei. Chinese authorities cordoned off the region and implemented mitigation measures nationwide. By April 2020, local transmission of the virus was under control but, by then, COVID-19 was pandemic with more than 100 countries reporting cases.

SARS-CoV-2 is a zoonotic coronavirus, believed to have jumped from an unknown animal host to humans. Numerous efforts have been made to identify when the virus first began spreading among humans, based on investigations of early-diagnosed cases of COVID-19. The first cluster of cases -- and the earliest sequenced SARS-CoV-2 genomes -- were associated with the Huanan Seafood Wholesale Market, but study authors say the market cluster is unlikely to have marked the beginning of the pandemic because the earliest documented COVID-19 cases had no connection to the market.

Regional newspaper reports suggest COVID-19 diagnoses in Hubei date back to at least November 17, 2019, suggesting the virus was already actively circulating when Chinese authorities enacted public health measures.

In the new study, researchers used molecular clock evolutionary analyses to try to home in on when the first, or index, case of SARS-CoV-2 occurred. "Molecular clock" is a term for a technique that uses the mutation rate of genes to deduce when two or more life forms diverged -- in this case, when the common ancestor of all variants of SARS-CoV-2 existed, estimated in this study to as early as mid-November 2019.

Molecular dating of the most recent common ancestor is often taken to be synonymous with the index case of an emerging disease. However, said co-author Michael Worobey, PhD, professor of ecology and evolutionary biology at University of Arizona: "The index case can conceivably predate the common ancestor -- the actual first case of this outbreak may have occurred days, weeks or even many months before the estimated common ancestor. Determining the length of that 'phylogenetic fuse' was at the heart of our investigation."

Based on this work, the researchers estimate that the median number of persons infected with SARS-CoV-2 in China was less than one until November 4, 2019. Thirteen days later, it was four individuals, and just nine on December 1, 2019. The first hospitalizations in Wuhan with a condition later identified as COVID-19 occurred in mid-December.

Study authors used a variety of analytical tools to model how the SARS-CoV-2 virus may have behaved during the initial outbreak and early days of the pandemic when it was largely an unknown entity and the scope of the public health threat not yet fully realized.

These tools included epidemic simulations based on the virus's known biology, such as its transmissibility and other factors. In just 29.7 percent of these simulations was the virus able to create self-sustaining epidemics. In the other 70.3 percent, the virus infected relatively few persons before dying out. The average failed epidemic ended just eight days after the index case.

"Typically, scientists use the viral genetic diversity to get the timing of when a virus started to spread," said Wertheim. "Our study added a crucial layer on top of this approach by modeling how long the virus could have circulated before giving rise to the observed genetic diversity.

"Our approach yielded some surprising results. We saw that over two-thirds of the epidemics we attempted to simulate went extinct. That means that if we could go back in time and repeat 2019 one hundred times, two out of three times, COVID-19 would have fizzled out on its own without igniting a pandemic. This finding supports the notion that humans are constantly being bombarded with zoonotic pathogens."

Wertheim noted that even as SARS-CoV-2 was circulating in China in the fall of 2019, the researchers' model suggests it was doing so at low levels until at least December of that year.

"Given that, it's hard to reconcile these low levels of virus in China with claims of infections in Europe and the U.S. at the same time," Wertheim said. "I am quite skeptical of claims of COVID-19 outside China at that time."

The original strain of SARS-CoV-2 became epidemic, the authors write, because it was widely dispersed, which favors persistence, and because it thrived in urban areas where transmission was easier. In simulated epidemics involving less dense rural communities, epidemics went extinct 94.5 to 99.6 percent of the time.

The virus has since mutated multiple times, with a number of variants becoming more transmissible.

"Pandemic surveillance wasn't prepared for a virus like SARS-CoV-2," Wertheim said. "We were looking for the next SARS or MERS, something that killed people at a high rate, but in hindsight, we see how a highly transmissible virus with a modest mortality rate can also lay the world low."

Co-authors include: Jonathan Pekar and Niema Moshiri, UC San Diego; and Konrad Scheffler, Illumina, Inc.

Funding for this research came, in part, from the National Institutes of Health (grants AI135992, AI136056, T15LM011271), the Google Cloud COVID-19 Research Credits Program, the David and Lucile Packard Foundation, the University of Arizona and the National Science Foundation (grant 2028040).

Journal Reference:

1. Jonathan Pekar, Michael Worobey, Niema Moshiri, Konrad Scheffler, Joel O. Wertheim. Timing the SARS-CoV-2 index case in Hubei province. Science, 2021; eabf8003 DOI: 10.1126/science.abf8003 

Courtesy: ScienceDaily

University of California - San Diego. "Novel coronavirus circulated undetected months before first COVID-19 cases in Wuhan, China: Study dates emergence to as early as October 2019; Simulations suggest in most cases zoonotic viruses die out naturally before causing a pandemic." ScienceDaily. ScienceDaily, 18 March 2021. <www.sciencedaily.com/releases/2021/03/210318185328.htm>.