One of the main hurdles in CCM research has been identifying cell signalling pathways that can be targeted to treat patients. A team at The Hospital for Sick Children (SickKids), led by Dr. Brent Derry, Senior Scientist in the Developmental & Stem Cell Biology Program at SickKids is tackling this challenge.This research was published on April 17 in Nature Communications.
A new mechanism to inhibit Epstein-Barr virus infection; the virus responsible for kissing disease and several types of cancer
The largest study of its kind sheds light on how genes work together to keep cells healthy, paving the way for predicting a person’s risk of disease.
By: Jovana Drinjakovic
To understand how a cell works, biologists like to take it apart. By removing genes from cells in diverse combinations, researchers have now uncovered how different genes work together to keep cells alive. The research will help scientists understand how faults in multiple genes combine to drive common diseases such as cancer or heart disease.
Led by Charles Boone, a professor in the University of Toronto’s Donnelly Centre, Brenda Andrews, University Professor and director of the Donnelly Centre, and Professor Chad Myers, of the University of Minnesota-Twin Cities, MN, the research builds up on the teams’ previous work which showed how genes combine in pairs to underpin cell’s health. Taking it a step further, the new study examines for the first time how higher-order gene combinations—comprising three genes— help maintain normal cell physiology, as revealed today in Science.
Boone and Andrews are also professors in U of T’s Department of Molecular Genetics and Senior Fellows at the Canadian Institute for Advanced Research (CIFAR) and Myers is a Fellow at CIFAR.
“There’s a growing understanding that interactions between genes can drive inherited disease susceptibility, which is why we have to understand the general principles of these genetic interactions,” says Boone.
It’s very much like a giant game of Jenga, with thousands of gene blocks that can be removed. While most single blocks can be taken out without compromising the structure, when critical combinations of blocks are removed, the system collapses. Similarly, genes with different roles can combine to keep the cell alive. By unpicking such gene alliances, scientists hope to reveal clues about the foundations of personal health.
It’s now clear from genome sequencing studies that each person carries thousands of genetic variants – differences in genes’ DNA sequence — that could combine to impact our health. However, these studies do not have the statistical power to predict a person’s risk of disease from their unique combination of genetic variants. This poses a major obstacle for personalized medicine which seeks to use genome information to predict risk of disease and tailor treatment.
To uncover the rules of combinatorial gene function, the team previously investigated how genes work in pairs in yeast cells. The yeast is one of biologists’ favourite cell models due to its relatively small genome comprising 6,000 genes and an already existing wealth of data. Having previously removed from yeast all possible gene pairs—18 million of them— the team now went a step further to examine what happens when you remove a subset of 36 billion possible trigenic combinations.
They found that, similar to interactions between two genes, trigenic interactions also mainly occur between genes that are functionally related— they code for parts belonging to the same molecular machine or that exist in the same part of the cell, for example. But with trigenic interactions, the researchers also began to see more surprising partnerships between genes that have unrelated function and are involved in different bioprocesses in the cell.
“Studying genetic networks allows you to see how genes are connected, how biological processes talk to one another and how a cell deals with perturbations in multiple genes,” says Elena Kuzmin, a lead author on the paper and a previous graduate student in the Boone lab who is now a postdoctoral fellow at McGill University in Montreal. “You get a global view of the cell,” she says.
Furthermore, using mathematical modeling the researchers estimate that all genes in the cell have a role to play when trigenic interactions are taken into account. This could finally explain why only a tenth of yeast’s 6,000 genes are essential for cell survival, a rule that holds for other cell types including human cells.
Thanks to recent advances in gene editing, it is now possible to remove combinations of genes from human cells, which Boone and Andrews labs are currently doing in collaboration with Jason Moffat’s group in the Donnelly Centre to map relationships between disease genes.
“Our yeast work demonstrates how mutations in multiple genes combine to have unexpected effects and is providing a roadmap for understanding genetic interactions in much more complex cells and organisms, including humans.” says Andrews. “Identifying combinations of genes that work together to underpin robust biological systems is important for deciphering what goes wrong with its collapse into a disease state.”
The study was supported by research grants from the Canadian Institute for Health and Research (CIHR) and the National Institute of Health (NIH) in the US.
High-Density Proximity Mapping Reveals the Subcellular Organization of mRNA-Associated Granules and Bodies.
Ji-Young Youn et al. Molecular Cell 69:517 (2018)
Anne-Claude Gingras’ lab
Post-transcriptional regulation of mRNA is a complex process that occurs in distinct compartments within the cell. This compartmentalization can involve liquid-liquid phase separation (LLPS) into distinct RNA-associated bodies and granules. Cytosolic P-bodies and stress granules, which are respectively associated with mRNA degradation and storage, form by the coalescence of non-translating mRNA and associated proteins. Stress granules have recently become implicated in neurodegenerative disease as several ALS (amyotrophic lateral sclerosis) and FTD (Frontotemporal Dementia)-linked proteins localize to them. Mutations in these ALS/FTD-linked proteins have also been shown to promote stable LLPS events both in vivo and in vitro, simulating protein aggregates found in ALS/FTD patients. Despite the recent growing interest in these bodies and granules it has been technically challenging to systematically characterize them in vivo.
A new study from the Gingras lab (Youn et al., 2018), published in Molecular Cell, aimed to uncover the composition and the relative structural organization of P-bodies and stress granules. To accomplish this, Youn et al. employed a proteomics technique called BioID which detects proximal associations between proteins within a ~10nm radius in living human cells. By performing BioID on 119 different proteins associated with RNA-associated bodies and granules, Youn et al. were able to discover new components of stress granules and P-bodies and define the spatial organization of these structures. One surprising finding is that stress granules, which require stress induction to form visible structures through LLPS, already make proximal contacts in the absence of exogenous stress. These pre-existing contacts suggest that stress granule proteins already form densely connected networks in the absence of stress, thus allowing a rapid transition into microscopically visible granules upon stress. The findings in this paper offer new avenues for identifying the factors that induce the transition into microscopically visible stress granules and provide new opportunities for exploring the mechanisms that promote ALS/FTD pathologies.
The first author of the study, Dr. Ji-Young Youn, has been highlighted by Molecular Cell in the feature “Meet the Author”.
Author: Jovana Drinjakovic
Donnelly Centre researchers have developed a new technology for creating more durable disease-fighting molecules which could lead to drugs with longer-lasting effects.
When Alice stepped through the looking glass, she discovered a fantastical world. Unlike that dream world in Lewis Carrol’s novel, the world of mirror-image molecules is very much real and it could lead to better medicines.
Mirror-image versions of existing drugs last longer in the body because they are harder to digest. For patients, this would mean less frequent drug injections and more medicines could potentially be made available as pills.
Designing these drugs has been tricky, however.
Now a team of researchers led by Philip Kim, a professor of computer science and molecular genetics in the Donnelly Centre for Cellular and Biomolecular Research, has developed a new technology for making mirror-image peptides, which bind and activate receptors on the surface of cells. They created mirror-image versions of two blockbuster drugs, a diabetes medication called glucagon-like-peptide 1 (GLP1) and parathyroid hormone (PTH), a common treatment for osteoporosis. In studies, both mirror-image counterparts had longer effects on cells than the existing drugs.
The findings are described in a study published today in an early online edition of the Proceedings of the National Academy of Sciences.
“Mirror image peptides are not recognized and degraded by enzymes in the stomach or bloodstream and therefore have a long-lasting effect,” says Kim. The other advantage, he said, is that mirror-image peptides also get overlooked by the immune system, which often mistakes natural peptides for foreign invaders and thus limits drug efficacy.
Peptides are made from molecules called amino acids. For reasons that are not fully understood and which go back to the origin of life, almost all amino acids in the natural world occur in one geometric form. Their atoms are arranged in such a way that makes the entire amino acid molecule appear left-handed, or "L" for short, which means that natural peptides are also left-handed. Because peptides produced by microbes, plants and animals can be harmful, the human body has evolved efficient ways to purge them.
But if you inverse a peptide, by making a mirror-image of it, it can still bind correct receptors while sliding unnoticed past the body’s defense mechanisms. Mirror image peptides can be made in the lab from synthetic right-handed amino acids, which are also known as “D” for dextrorotary.
Unlike straight L peptides, which can be fairly easily converted to a D form, most biologically active peptides are twisted into helices, and so far there has been no good way to design their mirror-image counterparts on a large scale, said Kim.
Using a purely computational approach, Kim’s team was able to clear this obstacle. They started with the largest public database which contains structural information for three million helical peptides. They then created an algorithm to flip these peptides into their D versions. Finally, the team looked in this new virtual library of mirror-image peptides for those that best matched GLP1 and PTH.
Once they found the match, the researchers had the D-peptides synthesized and tested for their ability to activate their receptors on the cell’s surface. They found that both D-GLP1 and D-PTH elicited cellular responses similar to their natural counterparts but had a longer-lasting effect.
“We are now investigating whether the D-PTH could be orally delivered because it is avoiding breakdown in the stomach”, says Kim. “For frequently dosed medication, this is of great interest, as taking a pill is much easier than having an injection. This could lead to many more peptide drugs being taken as pills”.
Currently, patients who take GLP1, which was discovered at U of T by Professor Daniel Drucker, of the Department of Medicine, or PTH, must inject these drugs on a daily basis.
Kim is working with the U of T patent office to protect his technology as he explores opportunities to partner with the pharmaceutical industry to commercialize the research. He is also developing mirror-image versions of peptides that work against the Dengue and Zika viruses in order to make them more durable in the bloodstream.
“We are testing our approach on as many interesting peptides as we can,” Kim said.
The study was funded by research grants from the Canadian Institute of Health Research and the National Sciences and Engineering Research Council of Canada.
Tracing single brain cancer cells simplifies complexity of incurable brain cancers, suggesting new treatments, international study finds
TORONTO – Using an innovative barcode-like system that tracks the behaviour of individual brain cancer cells, an international research team has gained a new understanding of how glioblastoma brain cancers grow and has identified potential new ways of treating these incurable cancers.
This novel approach enables scientists to track how each marked cell contributes to tumour growth, generating important new findings about how these cancers evade conventional treatments and invade normal brain tissue. The research, led by The Hospital for Sick Children (SickKids) and the University of Cambridge, is published in the Aug. 30 online edition of Nature.
Glioblastoma is a type of brain cancer that affects about 1,500 adults and 150 children in Canada every year, and is notorious for its complex genetics and poor response to all treatments, leading to death within about 15 months. While research into this devastating cancer has progressed, many aspects of the disease remain poorly understood, including simply how these tumours grow over time.
A collaborative team, including Dr. Connie Eaves from the University of British Columbia, dissected the functional properties of individual marked or “barcoded” cancer cells and their progeny – termed clones – which together form the evolving cancer mass.
“The approach we took is like the difference between looking at the final score in a sports match when it is over, to watching the game unfold in real time,” says the study’s co-principal investigator, Dr. Peter Dirks, Staff Neurosurgeon and Senior Scientist at SickKids. “Sometimes the final score doesn’t really tell us how the match unfolded, and this approach is like analyzing the individual performance of each player during the game. By neutralizing the star players, we can win over glioblastoma.”
Using this cell-tracking strategy, the research team found that only a few of the marked cells could give rise to long-term tumour growth, suggesting that a large portion of patient tumours contain cells that cannot multiply to make tumours grow. This finding is consistent with the stem cell model of cancer, initially proposed by Dr. John Dick at the University of Toronto in 1994, and the Dirks’ group in brain cancer in 2004, but established now with improved methods.
They then followed the mosaic of these cancer subpopulations through the processes of tumour growth, response to treatment and brain invasion. They found that glioblastoma is made up of many different clones (mini-cancers) which on the face of it might seem like a challenge for cancer therapy. However, using biophysical approaches, Professor Benjamin Simons and his team at Cambridge, jointly based at the Wellcome Trust-CRUK Gurdon Institute, the Wellcome Trust-MRC Cambridge Stem Cell Institute and the Cavendish Laboratory, Department of Physics, were able to show that the diversity of growth behaviours reflected a simple program of cell fate decision-making.
“We observed that the vast majority of clones retained a stereotyped pattern of growth, reminiscent of a stem cell “hierarchy”, where only a minority of stem cells within a clone underpin the growth of the clone. We designated clones with this pattern of growth as Group A,” says Dirks, who also holds a Garron Family Research Chair in Childhood Cancer Research and is Professor in the Departments of Surgery, Molecular Genetics, and Laboratory Medicine and Pathobiology at the University of Toronto. The team also identified other, rarer, more aggressive clones – labelled as Group B – that were able to escape this more organized pattern of growth.
“These results were surprising because glioblastoma is known to be a highly aggressive disease, with different tumour clones bearing a cocktail of different genetic mutations,” says Dirks. “Yet, when we analyzed each tumour cell’s behaviour individually, we found that the behaviour is highly structured, despite genetic differences between cancer cells within the same tumour, and is reminiscent of how human neural stem cells grow and give rise to mature brain cell types during normal development; this part was the most surprising.” However, he notes that the existence of the highly aggressive Group B subtype was actually not as surprising, given the complex genomics of the disease. “These clones were found to exist before therapy, but could be selected by therapy and could be a reason these tumours ultimately escape treatments. With the ability to single out clone types, we can now target how these Group B clones arise and grow.”
Building on these findings, the research team also identified two existing drugs that can slow the growth of glioblastoma tumour cells: one that acts on Group A cells and another that acts on Group B. These drugs target epigenetic processes, how the DNA is packaged, which determines which part of the cell’s DNA blueprint is active at any point in time.
“Our study suggests that drugs that can affect the behaviour of the abnormal glioblastoma stem cells could be very effective in treating glioblastoma,” says (Xiaoyang) Kevin Lan, who was a PhD student at the University of Toronto and the first author of the study. “Without the small population of cells that continuously sustain the tumour, our model predicts that the tumour could collapse. We think a strategy that targets both Group A and B cells could be highly effective. It suggests that we might also be able to side-step the need to target different tumour mutations, as it seems that multiple mutant forms follow the same behaviour. We need to target the hierarchy, the stemness form of the tumour, and there may be some common programs here, particularly in the way the DNA is specially packaged in stem cells to direct cell behaviour.”
Next steps for this research include using the cellular hierarchy model to test additional types of glioblastoma tumours in an effort to expand the scope of these findings. The team also plans to further characterize the molecular difference between the Group A and B cells to better target both types of cells with other drug treatments.
Funders for this study include the Canadian Institutes of Health Research, the Ontario Institute for Cancer Research, Stand Up To Cancer (SU2C) Canada and SickKids Foundation; and in the United Kingdom, research was funded by the Wellcome Trust with additional core support
from Cancer Research UK and the Medical Research Council.
This paper is an example of how SickKids is contributing to making Ontario Healthier, Wealthier and Smarter. www.healthierwealthiersmarter.ca.
About The Hospital for Sick Children
The Hospital for Sick Children (SickKids) is recognized as one of the world’s foremost paediatric health-care institutions and is Canada’s leading centre dedicated to advancing children’s health through the integration of patient care, research and education. Founded in 1875 and affiliated with the University of Toronto, SickKids is one of Canada’s most research-intensive hospitals and has generated discoveries that have helped children globally. Its mission is to provide the best in complex and specialized child and family-centred care; pioneer scientific and clinical advancements; share expertise; foster an academic environment that nurtures health-care professionals; and champion an accessible, comprehensive and sustainable child health system. SickKids is proud of its vision for Healthier Children. A Better World. For more information, please visit www.sickkids.ca. Follow us on Twitter (@SickKidsNews) and Instagram (@SickKidsToronto).
The Hospital for Sick Children
416-813-7654, ext. 202059
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A team of Canadian, US and Japanese scientists turned to baker’s yeast in a hunt for better drugs.
One of the hardest parts in drug discovery is pinning down how a medicine actually works in the body. It took nearly 100 years to uncover the molecular target of aspirin, but even with cutting-edge technology, it can take years to untangle how drugs interfere with cells. And yet, to develop medicines that target disease effectively and are safe —with no side effects—these molecular insights are key.
Now a new method developed by U of T researchers and international collaborators has the potential to accelerate target discovery with help from yeast cells, which are a simpler version of human cells but far better known at the molecular level.
Teams led by Professors Charles Boone, a professor of molecular genetics in U of T’s Donnelly Centre, Chad Myers, of the University of Minnesota-Twin Cities, and Professors Minoru Yoshida and Hiroyuki Osada, from the RIKEN Centre for Sustainable Resource Science in Japan, developed a new chemical genetics approach to link a drug to a cellular process it acts on.
Boone and Myers are also fellows at the Canadian Institute for Advanced Research where Boone is a Senior Fellow and co-Director of the Genetics Networks program.
The study, published this week in the journal Nature Chemical Biology, tested how nearly 14,000 compounds, hundreds of which were previously unexplored, affect basic cellular processes, to alert drug makers towards chemicals that are most likely to target a particular disease. The data pointed to ~1000 chemicals, many of which are natural products derived from soil microbes as a rich source of potential medicines against a range of diseases, from infections, to Alzheimer’s and cancer.
Despite modern technology, drug discovery still largely rests on guesswork. To find a drug that, say, kills cancer cells, scientists sift through libraries containing thousands of chemical compounds, the majority of which will have no effect at all.
“There are many different types of libraries to choose from. A lot of the time you choose a library based on its availability or its cost, not any sort of functional information, and so it becomes a shot in the dark,” says Dr. Jeff Piotrowski, a lead author on the paper who was a postdoctoral fellow in both the Yoshida and Boone labs and now works at the Boston biotechnology company, Yumanity Therapeutics, which uses yeast cells to find drugs for neurodegenerative diseases.
With their chemical genetics platform, Piotrowski and colleagues were able to show which parts of the cell are targeted by thousands of compounds from seven different libraries, six of which have been extensively explored and includes collections from the National Cancer Institute (NCI), the National Institute of Health and the pharmaceutical company Glaxo-Smith-Kline. The seventh and largest collection, from RIKEN in Japan, harbors thousands of virtually unexplored natural products from soil microbes.
Yeasts are currently the only living organism in which scientists have a good handle on the basic cellular processes, such as DNA replication and repair, energy production, and transport of cargo molecules, allowing them to link a drug to a particular bioprocess.
“By annotating these libraries, we can tell which library targets which bioprocess in the cell. It gives us a head start on linking a compound to a target, which is perhaps the most challenging part of drug discovery,” says Piotrowski.
The data revealed, for example, that the RIKEN library contains compounds that act in many different ways: from microbe-fighting chemicals that could be used to treat infections, to drugs that target cellular trafficking that is implicated in Alzheimer’s and Parkinson’s diseases, to those that interfere with cell replication and might be used against cancer. In fact, the RIKEN library turned out to have many novel compounds with anticancer potential.
“It’s long been thought that natural products are more functionally diverse, that they can do more things than purely synthetized compounds and that certainly seems to be true from our data,” says Boone.
And because natural compounds were shaped by evolution to act on living organisms, they are better candidates for future medicines than synthetic compounds that often do not even get into the cells. Indeed, from aspirin to penicillin, to the blockbuster cancer drug taxol, some of our best medicines we have come from nature.
The data also revealed chemicals that influence more than one process in the cell. These compounds are more likely to cause side effects and are best avoided. “With our map, we can see these promiscuous compounds earlier and focus on the good ones,” says Piotrowski.
The study was possible thanks to an earlier work by Boone, Myers, and Donnelly Centre Director Brenda Andrews, that mapped out how thousands of genes interact with each other to drive fundamental processes in the cell. The basic premise here was that removing one gene might not do anything because there’s a backup system in place, but removing two genes leads to a profound effect. It’s a bit like playing pick-up sticks where removing one stick at a time has no effect, but removing two together brings the pile down, or makes it stronger.
Instead of looking at double mutants, the present study measured how single mutants combined with drugs to influence the cells’ well being. This then allowed researchers to identify which bioprocess is affected by a particular drug, thereby identifying the drug’s mode of action. The beauty of the system employed by this international, multidisciplinary research team was that it integrates all genes within the same assay to assess the behavior of the entire genome in response to a particular drug in one experiment.
The research was funded by the Canadian Institutes of Health Research and Canadian Institute for Advanced Research as well as with research grants from the National Institute of Health in the US and National Science Foundation in Japan.
Author: Jovana Drinjakovic
Donnelly Centre researchers have developed a deep learning algorithm that can track proteins, to help reveal what makes cells healthy and what goes wrong in disease.
Yeast cells (purple) with DNA-containing nuclei (pink) and a protein (green) that resides in the cell’s waste compartment or vacuole. “We can learn so much by looking at images of cells: how does the protein look under normal conditions and do they look different in cells that carry genetic mutations or when we expose cells to drugs or other chemical reagents? People have tried to manually assess what’s going on with their data but that takes a lot of time,” says Benjamin Grys, a graduate student in molecular genetics and a co-author on the study.
Dubbed DeepLoc, the algorithm can recognize patterns in the cell made by proteins better and much faster than the human eye or previous computer vision-based approaches. In the cover story of the latest issue of Molecular Systems Biology, teams led by Professors Brenda Andrews and Charles Boone of the Donnelly Centre and the Department of Molecular Genetics, also describe DeepLoc’s ability to process images from other labs, illustrating its potential for wider use.
From self-driving cars to computers that can diagnose cancer, artificial intelligence (AI) is shaping the world in ways that are hard to predict, but for cell biologists, the change could not come soon enough. Thanks to new and fully automated microscopes, scientists can collect reams of data faster than they can analyze it.
“Right now, it only takes days to weeks to acquire images of cells and months to years to analyze them. Deep learning will ultimately bring the timescale of this analysis down to the same timescale as the experiments,” says Oren Kraus, a lead co-author on the paper and a graduate student co-supervised by Andrews and Professor Brendan Frey of the Donnelly Centre and the Department of Electrical and Computer Engineering. Andrews, Boone and Frey are also Senior Fellows at the Canadian Institute for Advanced Research.
Similar to other types of AI, in which computers learn to recognize patterns in data, DeepLoc was trained to recognize diverse shapes made by glowing proteins—labeled a fluorescent tag that makes them visible—in cells. But unlike computer vision that requires detailed instructions, DeepLoc learns directly from image pixel data, making it more accurate and faster.
"Deep learning will ultimately bring the timescale of this analysis down to the same timescale as the experiments" - Oren Kraus
Grys and Kraus trained DeepLoc on the teams’ previously published data that shows an area in the cell occupied by more than 4,000 yeast proteins—three quarters of all proteins in yeast. This dataset remains the most complete map showing exact position for a vast majority of proteins in any cell. When it was first released in 2015, the analysis was done with a complex computer vision and machine learning pipeline that took months to complete. DeepLoc crunched the data in a matter of hours.
DeepLoc was able to spot subtle differences between similar images. The initial analysis identified 15 different classes of proteins, each representing distinct neighbourhoods in the cell; DeepLoc identified 22 classes. It was also able to sort cells whose shape changed due to a hormone treatment, a task that the previous pipeline couldn’t complete.
By Jovana Drinjakovic
Researchers partner with pharmaceutical industry to meet a global health challenge
Parasites nearly killed her grandmother, and now Samantha Del Borrello is striking back.
Del Borrello is a graduate student investigating new ways of attacking parasites. She says her “nonna’s” childhood in 1940s rural Italy was plagued by intestinal worms that ravaged her health to the point doctors thought she would die.
“It is crazy to think that I may not be here because of a parasite, and now I am working on preventing the parasites from hurting people. It’s kind of cool,” says Del Borrello, a PhD candidate in the University of Toronto’s Donnelly Centre and the Department of Molecular Genetics.
Internal parasites, which infect the gut, lungs and liver, may not be a major health concern in the developed world, but globally they affect two billion people.
Gut worms infect 880 million children, according to the World Health Organization. Parasitic infections are rampant in the poorest areas, caused by nematode worms like roundworms, whipworms and hookworms. Untreated, these infections typically cause anemia and lethargy, or even death. Children are most vulnerable.
“Drugs already exist for some parasite infections but resistance is always evolving — we need new ways to attack these complex creatures,” says Andrew Fraser, a professor in the Donnelly Centre, and Del Borrello’s PhD supervisor.
Growing drug resistance comes at a time when the pharmaceutical industry has little incentive to invest in solving health problems that affect poor people who cannot afford treatment.
One way forward is for academic labs to work with pharmaceutical companies to identify promising drugs. Fraser’s work with Janssen, a branch of the pharmaceutical giant Johnson & Johnson, is one example of this kind of collaboration.
Peter Roy, who is also a professor in the Donnelly Centre, says there is also potential for the agriculture industry to play a role in developing new treatments.
“Most of the meat we eat has been treated with anthelmintics, drugs that kill parasitic worms,” says Roy. “If novel anthelmintics are shown to be useful for cows and sheep, then they might become therapies for humans.”
Fraser and Roy, who are also both appointed to the Department of Molecular Genetics, lead research into identifying new anti-parasitic drugs. As their main tool, the researchers are relying on a harmless type of worm called C. elegans, which is also widely used in labs (see inset). Unlike parasites, which live inside a body, lab worms grow on a dish and are easy to work with.
Many parasites make their way to places in the body where there is little oxygen to breathe. In order to survive, they switch to a type of metabolism that’s not fueled by oxygen.
Normally, lab worms need oxygen to live. But Del Borrello and PhD candidate Margot Lautens found a way to trick the lab worm into behaving like a parasite, deep inside the gut. Using drugs, they turned off the worm’s ability to use oxygen, forcing the worm to use parasite-like metabolism. This allowed researchers to study quirky parasite biology in an animal right in front of them.
“The way worms survive in low oxygen is extremely unusual, humans don’t use this process at all. That’s the key. It means that if we can target this unusual metabolic pathway, we should be able to kill the worms without having any impact on the human host,” says Fraser.
Using a different strategy, Roy’s team has already uncovered a treasure trove of potential anti-parasitic compounds. Two years ago, postdoctoral fellow Andrew Burns was part of a team that uncovered 275 chemical compounds that killed C. elegans. These worm active compounds, dubbed wactives, were then tested on fish and human cells to identify which ones could potentially harm the host.
That team is now teasing apart how wactives work. A new study in PLOS Neglected Tropical Diseases describes how a compound called wact-86 works by blocking an important enzyme in the worm. The next step is to explore whether wactives can clear parasitic infections in larger animals.
Another potential avenue is to work with a pharmaceutical company from the start. To do this, Fraser is working with BIO Ventures for Global Health (BVGH), a Seattle-based non-profit that boosts research in neglected tropical diseases through partnerships between academic labs and the pharmaceutical industry. The organization, among other roles, helps academia and industry share reagents, says Ujwal Sheth, Associate Director at BVGH.
Last month, Fraser signed a deal with Janssen, granting his team rights to the company’s drug collection—a potential chemical gold mine with 80,000 diverse compounds. If they find a medicinally promising compound, Janssen could decide take it on, said Sheth. Or, the BVGH could help connect Fraser with other partners with capacity to develop new medicines, she added.
“The best anthelminthic drug today, ivermectin, was developed in the 1970s as a partnership between an academic lab and a major pharmaceutical company. It’s a great cooperative model to help solve these huge global health problems,” said Fraser.
Studies from the Cochrane Lab Outline the characterization of Small Molecule Inhibitors of HIV-1 or Adenovirus Replication that Function Through the Modulation of RNA Processing
A novel compound that blocks HIV-1 replication inhibits the splicing regulatory function of SRSF10.NAR This study outlines the identification of a novel inhibitor (designated 1C8) of HIV-1 replication that functions through modulation of host splicing factor function, specifically SRSF10. While addition of 1C8 is found to severely impact HIV-1 RNA accumulation, the compound has very limited effects on host RNA processing. The anti-HIV activity of this compound suggests its use as a novel therapeutic to treat this infection.
Identification of Small Molecule Modulators of HIV-1 Tat and Rev Protein Accumulation. Grosso et al describe the mechanism by which two cardiotonic steroids, digoxin and digitoxin, suppress replication of adenovirus. We demonstrate that these drugs do not affect virus entry or initiation of adenovirus gene expression, but alter the processing of viral RNA to negatively impact the production of other viral proteins and ultimately block virus DNA replication and assembly. The study is of note because it is a repurposing of a drug already approved for use in humans for an infection that currently has few treatment options.
Identification of Small Molecule Modulators of HIV-1 Tat and Rev Protein Accumulation. Retrovirology. Balachandran et al. identify three compounds (designated 791, 833, and 892) that suppress HIV-1 replication through effects on the expression of two essential viral regulatory factors, Tat and Rev. Data presented indicates that the compounds affect expression of these viral factors through changes in protein synthesis/stability. Despite the significant inhibition of HIV-1 replication/gene expression observed in the presence of these compounds, effects on host cell expression are limited. These observations highlight an alternative approach to the control of HIV-1.
CCM-3 Promotes C. elegans Germline Development by Regulating Vesicle Trafficking Cytokinesis and Polarity
Cerebral cavernous malformations (CCM) are disorders that cause biological tubes in the brain (i.e., veins and capillaries) to become deformed and leak blood, leading to symptoms that can range from mild headaches to hemorrhagic stroke. This rare disease can occur in people sporadically by unknown mechanisms or by inheritance of mutations in one of three genes (CCM1, CCM2 or CCM3). Patients with mutations in the CCM3 gene have the earliest disease onset (often in childhood) and suffer the greatest lesion burden compared with patients who inherit mutations in CCM1 or CCM2. The mechanism by which CCM3 maintains the integrity of biological tubes is not understood and there are currently no treatments for CCM patients, other than invasive neurosurgery. In this paper, Brent Derry's lab showed that CCM3 functions to maintain the integrity of the C. elegans germline by promoting endocytic recycling of cell surface receptors and membrane to the cytokinetic furrow of dividing cells. The also show that CCM-3, and its associated striatin interacting phosphatase and kinase (STRIPAK) complex, coordinates organization of anillin and non-muscle myosin to generate contractile forces necessary for cytokinesis and assembly of cells into biological tubes. By combining the powerful genetics and cell biology of C. elegans with proteomics methods in collaboration with Molecular Genetics professors Mike Moran and Anne-Claude Gingras they show that association of CCM-3 with its binding partners striatin and the germinal centre kinase GCK-1, dictates its subcellular localization as well as the proper positioning of polarity proteins in dividing embryonic cells and in the developing germline. This work provides new insights into the normal biological functions of CC3/STRIPAK during development that should uncover effective therapeutic targets for treating CCM patients. Towards this goal Derry is also collaborating with Peter Roy (CCBR) to identify small molecules that reverse the germline defects of ccm-3 mutants. This work was supported by grants from the CIHR and a donation from Angioma Alliance Canada.
Mar 15, 2017
Author: Jovana Drinjakovic
Study reveals a breadth of new drug targets for neurological conditions and opens the door to a greater understanding of the way in which common medications work.
Ever taken antihistamines? Or heartburn medication? Along with others used for a variety of conditions, from diabetes to high blood pressure to depression, these drugs work by targeting the same class of protein molecules on our cells. They’re the most common type of drug on the market—and in medicine cabinets at home. Yet the available medications are only the tip of the iceberg as a University of Toronto study reveals a large swath of new therapeutic opportunities, including one that could lead to a better treatment for Parkinson’s disease.
Despite representing about a half of prescribed medications worldwide, these compounds target only a sliver of one of the largest—and most elusive—classes of human proteins, called G protein coupled receptors (GPCRs). Tapping into this vast unexplored therapeutic potential has been difficult because available tools weren’t up to the task of surveying the GPCRs on large scale. Enter Professor Igor Stagljar of U of T’s Donnelly Centre.
“Our cells are made of proteins, which also do most of the work in them. But no protein acts alone and that’s why we have to look at interactions between proteins to understand what’s going on in the cell,” says Stagljar, who is also a professor in the departments of molecular genetics and biochemistry.
Stagljar’s new study, which earned the cover of the March issue of the journal Molecular Systems Biology, is based on a technology called MYTH. Previously developed in the lab, it allows detection of membrane protein interactions as they occur in their natural setting—on the surface of cells. Using MYTH, Stagljar’s team was able to capture almost 1,000 interactions between more than 600 proteins for almost 50 clinically important GPCRs. The largest survey of GPCRs to date, it revealed new associations among proteins involved in neurological disorders, such as motor neuron disease, schizophrenia, and neurodegenerative disorders, as potential targets for new drugs.
One association that stood out involved ADORA2A, a GPCR targeted by Parkinson’s disease drugs. By binding to ADORA2A, these drugs stimulate the release of dopamine, which helps communication between nerve cells to ultimately reduce tremor in patients with Parkinson’s. Stagljar’s team found that ADORA2A associates with another GPCR, called GPR37 or Parkinson’s disease associated receptor, in a way that affects movement in a mouse model of disease. This suggests that a combination of drugs targeting both receptors, may work better in patients.
The study featured on the journal cover The work on Parkinson’s was done in collaboration with Professor Francisco Ciruela’s team at the University of Barcelona in Spain, which will continue to investigate the clinical potential of the enhanced combination therapy involving ADORA2A and GPR37.
“High-throughput studies like ours are going to be major contributors in future drug development. You can look at the cell in the ways we could not do before. We can understand how proteins interconnect better to identify possible reasons why certain drug compounds might be causing side effects and also to predict which targets might potentially be valuable for treating disease,” says Jamie Snider, a senior research associate in the lab and a lead author of the study.
To appreciate just how pervasive the 800 or so human GPCRs are, you only need to take a deep breath and look around you. Nestled inside the eye, these proteins detect light and help us see; those in the nose detect scents, while the ones in taste buds let us taste chocolate and other sweet and bitter foods. But these proteins also detect glucose and hormones in the blood, neurotransmitters, or chemicals that help our brain cells communicate, as well as hold cells together ensuring that tissues don’t fall apart. It’s no surprise then, that when GPCRs go awry, this can lead to brain disorders, diabetes, cancer and a host of other diseases.
"Our previous limited knowledge of the GPCRs had already helped us to tremendously improve human health. Think of what we might be able to do if we mapped all these proteins and their interactions" - Professor Igor Stagljar
In the past, scientists would either focus on the GPCR parts that are easily accessible, such as those sticking out on either side of the cell. Or, to study the GPCRs in entirety, they would remove the surrounding membrane, which changes the proteins’ properties. Either way, researchers weren’t getting the full picture of how these proteins work. MYTH and MaMTH, another related technology developed in the lab, have revolutionized the study of membrane proteins, attracting interest from the pharmaceutical industry.
“Our previous limited knowledge of the GPCRs had already helped us to tremendously improve human health. Think of what we might be able to do if we mapped all these proteins and their interactions and then understand the biological importance of those – this would be a huge step forward for biomedicine,” says Stagljar.
By Jovana Drinjakovic
University of Toronto scientists have uncovered more than 300 drug targets in cancer, attracting interest from the pharmaceutical industry looking to develop more precise treatments. Led by Professor Igor Stagljar of U of T’s Donnelly Centre, the study maps interactions between receptor tyrosine kinases (RTKs) and protein tyrosine phosphatases (PTPs) in humans, which can lead to cancer when their functions are disrupted. The highly anticipated study will be featured on the cover of the journal Molecular Cell, available in print on January 19.
Most cancer patients are treated with punishing chemotherapy drugs that have serious side-effects. In the last 15 years, a new generation of "smart" cancer drugs has been developed such as Gleevec, which effectively cures some forms of leukemia. These drugs are designed to target cancer cells with needle-like precision to avoid harming tissue that’s healthy. They do this by blocking proteins called kinases, which include receptor tyrosine kinases (RTKs) that control cell growth. RTKs are often mutated in cancer. However, the existing drugs block only a fraction of RTKs because these proteins have features that have made them notoriously hard to study.
Senior research associate Dr. Zhong Yao was able to carry out the largest study of RTKs to date by mapping their physical interactions with PTPs using methods previously developed in Stagljar’s lab.
“We tested interactions between almost all 58 RTKs and 144 PTPs that exist in human cells. Our map reveals new and surprising ways in which these proteins work together. These insights will help us better understand what goes wrong in cancer in order to develop more effective treatments,” said Stagljar, who is also a professor in U of T’s molecular genetics and biochemistry departments.
Lodged inside the cell’s outer envelope, or membrane, RTKs receive signals from the outside world—a hormone, for example— telling the cell to grow and divide. Normally, their activity is controlled by PTPs, which bind the RTKs and shut them down. This prevents sustained cell division that could lead to cancer.
The RTK’s place in the cell membrane is critical for their function, but it is also what has made them such a tough nut to crack. Traditional methods haven’t been able to capture the often short-lived physical interactions between RTKs and PTPs because the surrounding membrane has to be dissolved, which changes the proteins’ behaviour. Stagljar bridged this gap by developing MYTH and MaMTH, technologies designed precisely for measuring such fleeting interactions between membrane proteins in their natural setting.
The resulting map charts out more than 300 interactions between RTKs and PTPs in human cells, each a potential way to fight cancer. The findings have attracted attention of major pharmaceutical companies, including the pharma giant Genentech, which could lead to future collaborations in drug development.
Stagljar worked with two leading experts in PTP biology: Professor Anne-Claude Gingras of the Lunenfeld-Tanenbaum Research Institute and U of T’s Department of Molecular Genetics, and Professor Benjamin Neel of New York University, who was formerly with U of T and the University Health Network’s Princess Margaret Cancer Center.
“We wanted to show that these two assays we developed in our lab – MYTH and MaMTH – are suitable for studying these two important classes of proteins on such a large scale. The resulting wealth of important data can be used to develop new therapies against various types of cancer,” said Stagljar. “Ultimately, we want to build a map of interactions with all 3,000 or so human membrane proteins, of which at least 500 have direct roles in the onset of many human diseases. This will keep us busy,” he added.
"CRISPR genome editing is quickly revolutionizing biomedical research, but the new technology is not yet exact. The technique can inadvertently make excessive or unwanted changes in the genome and create off-target mutations, limiting safety and efficacy." More
By Jovana Drinjakovic
The study could pave the way for more meaningful interpretation of personal genomes.
Toronto scientists have discovered that the largest group of human proteins, which work as genome gatekeepers to control gene activity, are even more diverse in their roles than previously thought. The finding expands our understanding of how proteins “read” the DNA and could lead to a more accurate interpretation of individual genomes.
Donnelly Centre teams, led by Professor Timothy Hughes and University Professor Jack Greenblatt, have shown that proteins called C2H2-zinc fingers (C2H2-ZF) can control gene activity in new and surprizing ways. Reporting in the December issue of Genome Research, the researchers also reveal DNA binding sites for more than a hundred C2H2-ZFs as part of an ongoing effort to decode genome sequences that do not code for genes.
Despite being the largest group of human proteins—counting 700 members—the C2H2-ZFs are poorly understood partly because their sheer abundance and diversity make them hard to study. Yet knowing how they work is important because they help orchestrate gene activity. Of 20,000 human genes, only a subset is active in the cell at any given time. This subset determines if the cell will, say, build blood, or the brain or go haywire to become cancer.
The C2H2-ZF proteins work by directly binding the DNA to control the genes nearby. Named after their finger-like structures that, aided by zinc ions, clasp the DNA, C2H2-ZFs have previously been thought to act by stifling a wide range of genes. In a previous study that included about 40 C2H2-ZFs, the team showed that each protein recognized a unique DNA snippet as its landing site in the genome, raising the possibility that the rest of the group could be just as diverse.
This was indeed confirmed in the present study in which the teams mapped DNA binding sites, most of which were unique, this time for 131 C2H2-ZF proteins. But they also uncovered a whole new way in which the C2H2-ZF proteins can be regulated to vastly expand their job repertoire in the cell.
In addition to binding the DNA, it turned out that each C2H2-ZF can partner with a motley of other proteins that could potentially tweak its ability to switch genes on and off in a unique way. The finding upended the previous thinking in which C2H2-ZF proteins were seen as limited in their ability to bind other proteins—half of them were thought to interact with a single protein that helps them gag target genes, while the rest lack the usual molecular features that help proteins contact one another.
“Our key finding is that there’s almost as much diversity in the protein-protein interactions as there is in the DNA binding sequences. It tells us that the way the C2H2-ZF proteins work is almost certainly more complicated than we would have expected,” said Hughes, who is also a professor in U of T’s department of molecular genetics and a fellow of the Canadian Institute for Advanced Research (CIFAR).
The kinds of proteins that C2H2-ZFs interact with suggest that their roles go beyond clamping down on genes and may even act to turn genes on or help package DNA inside the cell.
The study also shines light on how the C2H2-ZF evolved to become the largest and most diverse group of proteins we have. The DNA sequences that C2H2-ZF proteins recognize look a lot like they had come from viruses, some of which plagued our mammalian ancestors as long as 100 million years ago. This kind of viral DNA has been called “selfish DNA” because it spreads by inserting itself randomly in a host’s genome.
It is thought that the C2H2-ZF proteins evolved to shut down this selfish DNA, their legion expanding to keep up with new intruders. Once the viral DNA was squashed for good, the C2H2-ZF proteins were able to take on new roles in shutting down mammalian genes. And now, this new data suggest that the C2H2-ZF proteins branched out even more than previously thought to acquire wholly unexpected functions by binding to other proteins.
Knowing how C2H2-ZFs work will give scientists a better handle on predicting which genes they control and how this may relate to disease. So far, mass genome sequencing studies have fallen short from being able to tell one’s risk of common diseases, such as cancer or diabetes, because we still don’t know enough about the meaning of individual differences between genomes.
“Even today, 15 years after the human genome was sequenced, if you give any piece of DNA to a geneticist and ask them what this does, generally they are unable to tell you that. But the more we learn about how human proteins recognize the DNA and what they do, the better our ability will be to interpret genome sequences and say what the significance of the variants is,” said Hughes.