Even when injuries occur, the muscles activate an endogenous regeneration program: A reserve supply of muscle stem cells, known as satellite cells, reside around the muscle fibers and are essential for the repair of damaged muscle cells. These satellite cells produce new muscle fibers in a process which results in muscle regeneration. People maintain this ability well into old age. Researchers are particularly interested in these cells since they could provide targets for new therapeutic approaches for people with muscle diseases.

An overrated protein

Researchers previously assumed that a certain protein — the transcription factor PAX7 — plays a key role in muscle regeneration. “Cells from which new muscles arise have enormous potential for developing gene therapies to treat muscle atrophy. And PAX7 is actually considered a characteristic property of muscle-building satellite cells,” says Prof. Simone Spuler.

The scientist and physician is a research group leader at the Experimental and Clinical Research Center (ECRC), a joint institution of the Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) and Charité — Universitätsmedizin Berlin, and heads the Myology Group at the MDC. Her team has now reported in the journal Nature Communications that it’s possible for muscles to grow and regenerate without PAX7. The study characterized a previously unknown subtype of satellite cells that could play an important role in the future development of gene therapies from muscle stem cells.

“The findings will certainly surprise many researchers in the field,” says Dr. Andreas Marg, a senior scientist in Spuler’s lab and the lead author of the study. He himself was initially guided by the assumption that the transcription factor was crucial for muscle growth. “I previously focused my research on PAX7-positive cells. Our findings lead us down a new path.”

New muscles despite a mutation

The research team owes the discovery to a young girl: Lavin has suffered from a genetic form of muscular dystrophy since birth and is the protagonist in the study. Lavin has all the muscles of a healthy person, but each of her muscles is very small. The musculature along her spine is particularly affected by the disease. Lavin’s arms and legs are strong, but she suffers breathing problems and has difficulty bending forward and holding her head up.

Gene analysis shows that the gene for PAX7 is damaged in Lavin; her cells can’t produce this protein. The University Hospital Munich discovered this in 2017. Soon thereafter, Spuler and Marg learned of this extremely rare mutation — one that had not been described before. Lavin traveled with her parents to the Berlin-Buch campus, where the scientists took a sample of her muscle tissue. Marg used a new procedure to filter out Lavin’s satellite cells and then implanted them in mice. He observed that new muscle fibers grew in the mice from Lavin’s cells — despite the absence of PAX7.

Spuler presumes that PAX7 is not equally important for every cell. This would explain why Lavin can walk and climb relatively well, but has hardly any strength in her diaphragm, which causes the breathing problems. “We could perhaps develop a gene therapy for Lavin using the CRISPR-Cas9 gene-editing tool,” says Spuler. “However, to repair the defective gene, CRISPR-Cas9 would have to specifically target the cells of the axial musculature, and that is not yet possible.” But Spuler’s lab is working intensively to figure out how to repair defective genes in muscle cells. For Lavin and her family, this research offers a small glimmer of hope that a suitable therapy will be found.

A new subtype of muscle stem cells

Marg and Spuler collaborated on the study with many colleagues at the MDC and with scientists from institutions abroad. Prof. Nikolaus Rajewsky’s research group at the Berlin Institute for Medical Systems Biology (BIMSB) compared Lavin’s cells with those donated by healthy people. Single-cell analysis, which looks at the activity of each cell individually, revealed a previously unknown cell population. In around 20 percent of the donors, the majority of the activated satellite cells also don’t produce any PAX7, even though the genetic information is present in the cells. The team instead discovered something else in those cells in which the transcription factor was missing: CLEC14A, a protein that is found in many blood vessel cells. This very protein was highly expressed in Lavin’s muscle stem cells.

The new study describes a previously unknown subtype of satellite cells. First, the researchers identified these cells in the stem cell niche, which is where the satellite cells reside. Second, PAX7 is not present in these cells. Third, other characteristic proteins such as CLEC14A are present instead. And fourth, new muscle fibers can be derived from this cell population.

Up to now, only cells with PAX7 have been considered as targets for gene therapy research involving satellite cells. The new study shows that the subtype discovered should also play a role in therapeutic development.

The results, published today (20 December 2019) in Nature Communications, mean that the two datasets can be integrated to form the largest genetic screen of cancer cell lines to date, which will provide the basis for the Cancer Dependency Map in around 1,000 cancer models. The scale of this combined dataset will help to speed up the discovery and development of new cancer drugs.

The Cancer Dependency Map (Cancer DepMap) initiative aims to create a detailed rulebook of precision cancer treatments for patients. Two key elements of the Cancer DepMap are the mapping of the genes critical for the survival of cancer cells and analytics of the resulting datasets. Despite recent advances in cancer research, making precision medicine widely available to cancer patients requires many new drug targets.

To find these drug targets, Cancer DepMap researchers take tumour cells from patients to create cell lines that can be grown in the laboratory. They then use CRISPR-Cas9 technology to edit the genes in these cancer cells, turning them off one-by-one to measure how critical they are for the cancer to survive. The results of these experiments indicate which genes are the most likely to make viable drug targets.

In this new study, researchers analysed data from two recently published CRISPR-Cas9 genetic screens performed on cancer cell lines at the Broad and Sanger Institutes. Despite significant differences in experimental protocols, the team found that the screen results were consistent with one another. Crucially, the same genes essential to cancer survival — known as dependencies — were found in both datasets.

Dr Clare Pacini, a first author of the study from the Wellcome Sanger Institute and Open Targets, said: “The Sanger and Broad Institute CRISPR-Cas9 screens were created using slightly different protocols, such as cell growth duration and reagents used. To verify each Institute’s dataset, we have repeated CRISPR-Cas9 screens using the protocols originally employed at the other Institute. Importantly, we have found the same genetic dependencies in each, meaning the new drug targets originally identified are consistent.”

Aviad Tsherniak, of the Broad Institute of MIT and Harvard, said: “This is the first analysis of its kind and is really important for the whole cancer research community. Not only have we reproduced common and specific dependencies across the two datasets, but we have taken biomarkers of gene dependency found in one dataset and recovered them in the other. Our analysis has been unbiased, rigorous and proves the veracity of the approach and the drug targets identified.”

In 2013, results comparing two large pharmacogenomic datasets employing the cancer models used in this study raised concerns about the reproducibility of the experiments performed. Further independently-published analyses eventually proved the two resources to be reliable and consistent, restoring confidence in the robustness of large-scale drug screens, but the episode slowed the progress of cancer research.

This study validates the reproducibility of CRISPR-Cas9 functional genetic screens in order to remove any doubt about their efficacy. It sets rigorous standards for assessing these new types of dataset, facilitating the comparison and integration of large databases of cancer dependencies.

Dr Francesco Iorio, of the Wellcome Sanger Institute and Open Targets, said: “It is worth remembering that when these datasets were originally produced we were dealing with a new, unproven technology. This study is important because it demonstrates the validity of the experimental methods and the consistency of the data that they produce. It also means that two large cancer dependency datasets are compatible. By joining them together, we will have access to much greater statistical power to narrow down the list of targets for the next generation of cancer treatments.”

Story Source:

Materials provided by Wellcome Trust Sanger Institute. Note: Content may be edited for style and length.

In a new study published in Communications Biology, a group of scientists at Tokyo University of Science, led by Prof Sachihiro Matsunaga, wanted to find answers related to the origin of mitochondrial division. For their research, Prof Matsunaga and his team chose to study a type of red alga — the simplest form of a eukaryote, containing only one mitochondrion. Specifically, they wanted to observe whether the machinery involved in mitochondrial replication is conserved across different species and, if so, why. Talking about the motivation for this study, Prof Matsunaga says, “Mitochondria are important to cellular processes, as they supply energy for vital activities. It is established that cell division is accompanied by mitochondrial division; however, many points regarding its molecular mechanism are unclear.”

The scientists first focused on an enzyme called Aurora kinase, which is known to activate several proteins involved in cell division by “phosphorylating” them (a well-known process in which phosphate groups are added to proteins to regulate their functions). By using techniques such as immunoblotting and kinase assays, they showed that the Aurora kinase in red algae phosphorylates a protein called dynamin, which is involved in mitochondrial division. Excited about these findings, Prof Matsunaga and his team wanted to take their research to the next level by identifying the exact sites where Aurora kinase phosphorylates dynamin, and using mass spectrometric experiments, they succeeded in identifying four such sites. Prof Matsunaga says, “When we looked for proteins phosphorylated by Aurora kinase, we were surprised to find dynamin, a protein that constricts mitochondria and promotes mitochondrial division.”

Having gained a little more insight into how mitochondria divide in red algae, the scientists then wondered if the process could be similar in more evolved eukaryotes, such as humans. Prof Matsunaga and his team then used a human version of Aurora kinase to see if it phosphorylates human dynamin — and just as they predicted, it did. This led them to conclude that the process by which mitochondria replicate is very similar in different eukaryotic organisms. Prof Matsunaga elaborates on the findings by saying, “Using biochemical in vitro assays, we showed that Aurora kinase phosphorylates dynamin in human cells. In other words, it was found that the mechanism by which Aurora kinase phosphorylates dynamin in the mitochondrion is preserved from primitive algae to humans.”

Scientists have long pondered over the idea of mitochondrial division being conserved in eukaryotes. This study is the first to show not only the role of a new enzyme in mitochondrial replication but also that this process is similar in both algae and humans, hinting towards the fact that their common ancestry might have something to do with this. Prof Matsunaga concludes by talking about the potential implications of this study, “Since the mitochondrial fission system found in primitive algae may be preserved in all living organisms including humans, the development of this method can make it easier to manipulate cellular activities of various organisms, as and when required.”

As it turns out, we have much more in common with other species than we thought, and part of the evidence lies in our mitochondria!

Story Source:

Materials provided by Tokyo University of Science. Note: Content may be edited for style and length.

This structural information could become the basis for developing better diagnostics and drugs for life-threatening heart rhythm problems, according to the researchers from the University of Washington School of Medicine working in this area.

Their latest findings appear Dec. 19 in Cell in the paper, “Structure of the Cardiac Sodium Channel.” The senior authors are William Catterall and Ning Zheng, both UW School of Medicine professors of pharmacology. The first authors are Daohau Jiang and Hui Shi, UW postdoctoral fellows in pharmacology.

“The cardiac sodium channel not only initiates the heartbeat, mutations in it also cause deadly arrhythmias, and antiarrhythmic drugs act directly on it to control cardiac rhythms,” explained Catterall.

The heart is both a plumbing and electrical marvel. For each heartbeat, electrical waves travel across a healthy heart in a pattern that controls its filling and pumping in a tightly coordinated manner. The rate at which the impulse is propagated through the heart tissue relies on actions taking place at the molecular level in tiny protein pores present in cardiac cell membranes.

Sodium ions — a type of charged particles — pass through these protein passageways in the membrane boundary between the outside and inside of the cell.

Pufferfish harbor a toxin that acts on nerve and muscle, but not heart, sodium channels.

The activation and quick inactivation of these voltage-gated sodium channels are part of a series of electrical and physiological events that maintain a steady heartbeat.

“Sodium channels operate in concert with calcium channels and potassium channels to drive the heartbeat at a consistent frequency for our entire lives,” Zheng noted.

When sodium channels don’t work properly, the heart can be in trouble, even to the point of having dangerously fast and uncoordinated contractions that are life-threatening, the researchers explained.

Specifically, the NaV (Latin abbreviation for sodium, V for voltage) 1.5 channel has such an indispensable role that certain mutations in those channels can be fatal, because other sodium channels in the heart cannot compensate for their loss. These mutations can cause dangerous arrhythmias in adults and even sudden death in children and young athletes.

Fortunately, many heart rhythm disturbances can be treated with drugs that block cardiac sodium channels. For example, as UW Medicine physician Michael Lenaeus, a UW assistant professor of medicine, Division of General Internal Medicine, and a co-author of the study, noted, atrial fibrillation, or “A-fib,” is increasingly prevalent among older Americans.

This condition can often be treated effectively with the drug flecainide. In their recent study, the researchers sought to learn, among other things, how drugs like flecainide act within the predominant form of sodium channels found in cardiac cells.

To obtain a high-resolution, 3-D map of the channels, the scientists used advanced cryo-electron microscopy at the new Beckman Center for Cryo-EM at the UW. They wanted to explore important structural features of these sodium channels and relate their configuration to their actions in normal physiological function, dysfunction, disease mutations, toxin sensitivity and the pharmacology of antiarrhythmic drugs.

According to the scientists, their experiments provide a blueprint for understanding many various aspects of cardiac sodium channels.

Among the key findings from this work were:

• A description of some of the characteristics of the NaV1.5 channel that distinguish it from other sodium ion channels found in heart cells, as well as in nerve and muscle cells.
• Structural insights into the mode of action of various arrhythmia mutations. There are many parts of the sodium channel protein that can be disrupted by mutations. Some mutations interfere with the activation or inactivation of the sodium channel. Others cause altered function by creating a channel protein hole that leaks sodium continuously. Still other mutations, found in Brugada syndrome, can impair or block the conductance of sodium ions.
• Chemical insights into how the heart rhythm drug flecainide targets the inner pocket of the ion channel and plugs the central pore that conducts sodium ions.
• The structural determinants that distinguish tetrodotoxin sensitive and insensitive sodium channels. Tetrodotoxin, the infamous, deadly poison in pufferfish, is a sodium channel blocker that has a high affinity for sodium channels in nerves and muscles, but not for those in heart cells.
• A comparison of the conformation of an important component of the sodium ion channels that “senses” the voltage across the cell membrane and drives the channels from resting to activated states. After their rapid activation, cardiac sodium channels inactivate within 1 to 2 milliseconds, a timing that is essential to regular heart rhythm.

The researchers were able to determine how mutations can upset activation of the channel or even abolish its required rapid inactivation in a variety of ways.

In their conclusion, the researchers noted that, overall, the detailed, high-resolution structures they were able to obtain for the cardiac NaV1.5 channel allowed them to elucidate the molecular basis for several of its specific, distinctive, vital functions and to provide key chemical information for design and development of safer and more effective antiarrhythmic medications.

“Our high-resolution cryoEM structure of this iconic sodium channel gives new structure/function insights, reveals the molecular mechanisms of many inherited arrhythmias, and elucidates the exact binding site and blocking mode of the antiarrhythmic drug flecainide, which is used to treat atrial fibrillation, an increasingly prevalent problem in our aging population,” Catterall said in summarizing the results.

The research was funded by the National Institutes of Health (R01HL112808) and the Howard Hughes Medical Institute.

Purdue University drug discovery researchers have created a new framework for mining data for training machine learning models. The framework, called Lemon, helps drug researchers better mine the Protein Data Base (PDB) — a comprehensive resource with more than 140,000 biomolecular structures and with new ones being released every week. The work is published in the Oct. 15 edition of Bioinformatics.

“PDB is an essential tool for the drug discovery community,” said Gaurav Chopra, an assistant professor of analytical and physical chemistry in Purdue’s College of Science who works with other researchers in the Purdue Institute for Drug Discovery and led the team that created Lemon. “The problem is that it can take an enormous amount of time to sort through all the accumulated data. Machine learning can help, but you still need a strong framework from which the computer can quickly analyze data to help in the creation of safe and effective drugs.”

The Lemon software platform is a fast C++11 library with Python bindings that mines the PDB within minutes. Loading all traditional mmCIF files in the PDB takes about 290 minutes, but Lemon does this in about six minutes when applying a simple workflow on an 8-core machine. Lemon allows the user to write custom functions, include it as part of their software suite, and develop custom functions in a standard manner to generate unique benchmarking datasets for the entire scientific community.

“Experimental structures deposited in PDB have resulted in several advances for structural and computational biology scientific and education communities that help advance drug development and other areas,” said Jonathan Fine, a PhD student in chemistry who worked with Chopra to develop the platform. “We created Lemon as a one-stop-shop to quickly mine the entire data bank and pull out the useful biological information that is key for developing drugs.”

Lemon got its name as it was originally designed to create benchmarking sets for drug design software and identify the lemons, biomolecular interactions that cannot be modeled well, in the PDB.

The software development work is the latest project involving health innovations from Chopra and his team. Lemon is freely available on GitHub at https://github.com/chopralab/lemon. Detailed documentation is available at https://chopralab.github.io/lemon/latest/index.html.

Chopra also worked with the Purdue Research Foundation Office of Technology Commercialization to patent other innovations from his lab.

Story Source:

Materials provided by Purdue University. Original written by Chris Adam. Note: Content may be edited for style and length.

In the human gut, hundreds of species of microbes exchange nutrients in a complex food web. Large-scale food webs, such as those of tropical forests, typically follow a hierarchy in which energy flows from plants, to herbivores, to carnivores. Wang and colleagues wondered if the gut microbiome could be considered to follow a similar hierarchy, from microbes that consume nutrients in food eaten by the human host, to those that eat nutrients produced by the first microbes, and so on.

To address this question, the researchers developed a computational model that uses the known species of microbes in a person’s gut to predict microbial metabolites — the substances the microbes generate as part of their biological activities, and which may serve as nutrients for other gut microbes. The metabolite predictions generated by the model are in line with experimental data, providing support for its accuracy.

The new model indeed predicts a four-level hierarchy for the food web of the gut microbiome. This suggests that species composition systematically changes along the length of the gut. Near the entrance to the lower gut, one might find bacteria from the highest hierarchical level — those that consume nutrients in food eaten by the human. Near the end of the gut, one might find bacteria from the lowest level.

“There is a great premium on being able to predict metabolic profiles from species genomes, as our algorithm does,” Wang says. “Metabolites are better than species composition for predicting important aspects of gut function, but genome sequencing is faster and cheaper than measuring metabolic profiles.”

The researchers are now working to refine their model by using a machine-learning approach to infer important competitive relationships between gut microbes. Doing so could improve the model’s accuracy, potentially reducing the need for expensive measurements of metabolic profiles in research on gut function.

Story Source:

Materials provided by PLOS. Note: Content may be edited for style and length.