GN/ Cells: Longevity-promoting ‘recycling system’
Genetics biweekly vol.37, 7th September — 21st September
TL;DR
- Researchers described a pathway by which cells repair damaged lysosomes, structures that contribute to longevity by recycling cellular trash. The findings are an important step towards understanding and treating age-related diseases driven by leaky lysosomes.
- Scientists have harnessed the potential of bacteria to help build advanced synthetic cells which mimic real life functionality.
- Researchers have used data science and computational biology to show that the same ‘rules’ have shaped how mitochondria and chloroplasts have evolved throughout life’s history.
- Over the past two years, machine learning has revolutionized protein structure prediction. Now there’s a similar revolution in protein design. Biologists show that machine learning can be used to create protein molecules much more accurately and quickly than previously possible. By creating new, useful proteins not found in nature, they hope this advance will lead to many new vaccines, treatments, tools for carbon capture, and sustainable biomaterials.
- Scientists have solved the century-old mystery of a supergene that causes efficient cross-pollination in flowers.
- Crops bred to thrive in single-crop settings begin adapting to growing in multispecies environments over just two generations, shows a new study.
- Scientists solve the mystery of how Zika virus takes over key immune system cells. New findings shed light on how to stop the virus from spreading.
- Researchers have produced a high-resolution crystal structure of an enzyme essential to the survival of SARS-CoV-2, the virus that causes COVID-19. The discovery could lead to the design of critically needed new antivirals to combat current and future coronaviruses.
- ARHGAP11B — this complex name is given to a gene that is unique to humans and plays an essential role in the development of the neocortex. The neocortex is the part of the brain to which we owe our high mental abilities. A team of researchers has investigated the importance of ARHGAP11B in neocortex development during human evolution. To do this, the team introduced for the first time a gene that exists only in humans into laboratory-grown brain organoids from our closest living relatives, chimpanzees.
- Scientists have known that sex-determination in vertebrates happens in the germ cells, a body’s reproductive cells, and the somatic cells, the cells that are not reproductive cells. Yet they have not fully understood the mechanisms by which it happens. To better grasp the process of the germ cell’s sex determination, a research team has analyzed germ cells in chickens using RNA-sequencing to predict the mechanism that determines the sex. Their study provides insight into the mechanism of sex determination in birds.
- And more!
Overview
Genetic technology is defined as the term which includes a range of activities concerned with the understanding of gene expression, advantages of natural genetic variation, modifying genes and transferring genes to new hosts. Genes are found in all living organisms and are transferred from one generation to the next. Gene technology encompasses several techniques including marker-assisted breeding, RNAi and genetic modification. Only some gene technologies produce genetically modified organisms.
Modern genetic technologies like genome editing would not be possible without all the previous generations of genetic technologies that have enabled scientists to discover what genes are, what they do and how DNA can be modified to add, remove or replace genes. You can find major genetic technologies development milestones via the link.
Gene Technology Market
- The valuation of the genetic engineering market is projected to escalate to USD 6.90 MN by the end of 2027.
- Global Genetic Engineering Market is projected to grow at 12.48% CAGR during the assessment period (2017–2027).
- North America holds the largest share in the global genetic engineering market, followed by Europe and the Asia Pacific, respectively.
- Another research provider, MarketsandMarkets, forecasts the genome editing, genome engineering market to grow from USD 3.19 billion in 2017 to USD 6.28 billion by 2022, at a compounded annual growth rate (CAGR) of 14.5% during the forecast period. The key factors propelling market growth are rising government funding and growth in the number of genomics projects, high prevalence of infectious diseases (like COVID-19) and cancer, technological advancements, increasing production of genetically modified (GM) crops, and growing application areas of genomics.
Latest News & Research
A phosphoinositide signalling pathway mediates rapid lysosomal repair
by Jay Xiaojun Tan, Toren Finkel in Nature
University of Pittsburgh researchers describe for the first time a pathway by which cells repair damaged lysosomes, structures that contribute to longevity by recycling cellular trash. The findings are an important step towards understanding and treating age-related diseases driven by leaky lysosomes.
“Lysosome damage is a hallmark of aging and many diseases, particularly neurodegenerative disorders such as Alzheimer’s,” said lead author Jay Xiaojun Tan, Ph.D., assistant professor of cell biology at Pitt’s School of Medicine and member of the Aging Institute, a partnership between Pitt and UPMC. “Our study identifies a series of steps that we believe is a universal mechanism for lysosomal repair, which we named the PITT pathway as a nod to the University of Pittsburgh.”
As the cell’s recycling system, lysosomes contain potent digestive enzymes that degrade molecular waste. These contents are walled off from damaging other parts of the cell with a membrane that acts like a chain link fence around a hazardous waste facility. Although breaks can occur in this fence, a healthy cell quickly repairs the damage. To learn more about this repair process, Tan teamed up with senior author Toren Finkel, M.D., Ph.D., director of the Aging Institute and distinguished professor of medicine at Pitt’s School of Medicine.
First, Tan experimentally damaged lysosomes in lab-grown cells and then measured the proteins that arrived on the scene. He found that an enzyme called PI4K2A accumulated on damaged lysosomes within minutes and generated high levels of a signaling molecule called PtdIns4P.
“PtdIns4P is like a red flag. It tells the cell, ‘Hey, we have a problem here,’” said Tan. “This alert system then recruits another group of proteins called ORPs.”
ORP proteins work like tethers, Tan explained. One end of the protein binds to the PtdIns4P red flag on the lysosome, and the other end binds to the endoplasmic reticulum, the cellular structure involved in synthesis of proteins and lipids.
“The endoplasmic reticulum wraps around the lysosome like a blanket,” added Finkel. “Normally, the endoplasmic reticulum and lysosomes barely touch each other, but once the lysosome was damaged, we found that they were embracing.”
Through this embrace, cholesterol and a lipid called phosphatidylserine are shuttled to the lysosome and help patch up holes in the membrane fence. Phosphatidylserine also activates a protein called ATG2, which acts like a bridge to transfer other lipids to the lysosome, the final membrane repair step in the newly described PITT — or phosphoinositide-initiated membrane tethering and lipid transport — pathway.
“What’s beautiful about this system is that all of the components of the PITT pathway were known to exist, but they weren’t known to interact in this sequence or for the function of lysosome repair,” said Finkel. “I believe these findings are going to have many implications for normal aging and for age-related diseases.”
The researchers suspect that in healthy people, small breaks in the lysosome membrane are quickly repaired through the PITT pathway. But if the damage is too extensive or the repair pathway is compromised — due to age or disease — leaky lysosomes accumulate. In Alzheimer’s, leakage of tau fibrils from damaged lysosomes is a key step in progression of the disease.
When Tan deleted the gene encoding the first enzyme in the pathway, PI4K2A, he found that tau fibril spreading increased dramatically, suggesting that defects in the PITT pathway could contribute to Alzheimer’s disease progression. In future work, the researchers plan to develop mouse models to understand whether the PITT pathway can protect mice from developing Alzheimer’s disease.
Evolutionary inference across eukaryotes identifies universal features shaping organelle gene retention
by Konstantinos Giannakis, Samuel J. Arrowsmith, Luke Richards, Sara Gasparini, Joanna M. Chustecki, Ellen C. Røyrvik, Iain G. Johnston in Cell Systems
Mitochondria are compartments — so-called “organelles” — in our cells that provide the chemical energy supply we need to move, think, and live. Chloroplasts are organelles in plants and algae that capture sunlight and perform photosynthesis. At a first glance, they might look worlds apart. But an international team of researchers, led by the University of Bergen, have used data science and computational biology to show that the same “rules” have shaped how both organelles — and more — have evolved throughout life’s history.
Both types of organelle were once independent organisms, with their own full genomes. Billions of years ago, those organisms were captured and imprisoned by other cells — the ancestors of modern species. Since then, the organelles have lost most of their genomes, with only a handful of genes remaining in modern-day mitochondrial and chloroplast DNA. These remaining genes are essential for life and important in many devastating diseases, but why they stay in organelle DNA — when so many others have been lost — has been debated for decades.
For a fresh perspective on this question, the scientists took a data-driven approach. They gathered data on all the organelle DNA that has been sequenced across life. They then used modelling, biochemistry, and structural biology to represent a wide range of different hypotheses about gene retention as a set of numbers associated with each gene. Using tools from data science and statistics, they asked which ideas could best explain the patterns of retained genes in the data they had compiled — testing the results with unseen data to check their power.
“Some clear patterns emerged from the modelling,” explains Kostas Giannakis, a postdoctoral researcher at Bergen and joint first author on the paper. “Lots of these genes encode subunits of larger cellular machines, which are assembled like a jigsaw. Genes for the pieces in the middle of the jigsaw are most likely to stay in organelle DNA.”
The team believe that this is because keeping local control over the production of such central subunits help the organelle quickly respond to change — a version of the so-called “CoRR” model. They also found support for other existing, debated, and new ideas. For example, if a gene product is hydrophobic — and hard to import to the organelle from outside — the data shows that it is often retained there. Genes that are themselves encoded using stronger-binding chemical groups are also more often retained — perhaps because they are more robust in the harsh environment of the organelle.
“These different hypotheses have usually been thought of as competing in the past,” says Iain Johnston, a professor at Bergen and leader of the team. “But actually no single mechanism can explain all the observations — it takes a combination. A strength of this unbiased, data-driven approach is that it can show that lots of ideas are partly right, but none exclusively so — perhaps explaining the long debate on these topics.”
To their surprise, the team also found that their models trained to describe mitochondrial genes also predicted the retention of chloroplast genes, and vice versa. They also found that the same genetic features shaping mitochondrial and chloroplast DNA also appear to play a role in the evolution of other endosymbionts — organisms which have been more recently captured by other hosts, from algae to insects.
“That was a wow moment,” says Johnston. “We — and others — have had this idea that similar pressures might apply to the evolution of different organelles. But to see this universal, quantitative link — data from one organelle precisely predicting patterns in another, and in more recent endosymbionts — was really striking.”
Robust deep learning–based protein sequence design using ProteinMPNN
by J. Dauparas, I. Anishchenko, N. Bennett, H. Bai, R. J. Ragotte, et al in Science
Over the past two years, machine learning has revolutionized protein structure prediction. Now, three papers in describe a similar revolution in protein design.
In the new papers, biologists at the University of Washington School of Medicine show that machine learning can be used to create protein molecules much more accurately and quickly than previously possible. The scientists hope this advance will lead to many new vaccines, treatments, tools for carbon capture, and sustainable biomaterials.
“Proteins are fundamental across biology, but we know that all the proteins found in every plant, animal, and microbe make up far less than one percent of what is possible. With these new software tools, researchers should be able to find solutions to long-standing challenges in medicine, energy, and technology,” said senior author David Baker, professor of biochemistry at the University of Washington School of Medicine and recipient of a 2021 Breakthrough Prize in Life Sciences.
Proteins are often referred to as the “building blocks of life” because they are essential for the structure and function of all living things. They are involved in virtually every process that takes place inside cells, including growth, division, and repair. Proteins are made up of long chains of chemicals called amino acids. The sequence of amino acids in a protein determines its three-dimensional shape. This intricate shape is crucial for the protein to function.
Recently, powerful machine learning algorithms including AlphaFold and RoseTTAFold have been trained to predict the detailed shapes of natural proteins based solely on their amino acid sequences. Machine learning is a type of artificial intelligence that allows computers to learn from data without being explicitly programmed. Machine learning can be used to model complex scientific problems that are too difficult for humans to understand.
To go beyond the proteins found in nature, Baker’s team members broke down the challenge of protein design into three parts andused new software solutions for each. First, a new protein shape must be generated. In a paper published July 21 in the journal Science, the team showed that artificial intelligence can generate new protein shapes in two ways. The first, dubbed “hallucination,” is akin to DALL-E or other generative A.I. tools that produce output based on simple prompts. The second, dubbed “inpainting,” is analogous to the autocomplete feature found in modern search bars. Second, to speed up the process, the team devised a new algorithm for generating amino acid sequences. Described in the Sept.15 issue of Science, this software tool, called ProteinMPNN, runs in about one second. That’s more than 200 times faster than the previous best software. Its results are superior to prior tools, and the software requires no expert customization to run.
“Neural networks are easy to train if you have a ton of data, but with proteins, we don’t have as many examples as we would like. We had to go in and identify which features in these molecules are the most important. It was a bit of trial and error,” said project scientist Justas Dauparas, a postdoctoral fellow at the Institute for Protein Design
Third, the team used AlphaFold, a tool developed by Alphabet’s DeepMind, to independently assess whether the amino acid sequences they came up with were likely to fold into the intended shapes.
“Software for predicting protein structures is part of the solution but it cannot come up with anything new on its own,” explained Dauparas.
“ProteinMPNN is to protein design what AlphaFold was to protein structure prediction,” added Baker.
In another paper appearing in Science Sept. 15, a team from the Baker lab confirmed that the combination of new machine learning tools could reliably generate new proteins that functioned in the laboratory.
“We found that proteins made using ProteinMPNN were much more likely to fold up as intended, and we could create very complex protein assemblies using these methods” said project scientist Basile Wicky, a postdoctoral fellow at the Institute for Protein Design.
Among the new proteins made were nanoscale rings that the researchers believe could become parts for custom nanomachines. Electron microscopes were used to observe the rings, which have diameters roughly a billion times smaller than a poppy seed.
“This is the very beginning of machine learning in protein design. In the coming months, we will be working to improve these tools to create even more dynamic and functional proteins,” said Baker.
Human‐specific ARHGAP11B ensures human‐like basal progenitor levels in hominid cerebral organoids
by Jan Fischer, Eduardo Fernández Ortuño, Fabio Marsoner, Annasara Artioli, Jula Peters, Takashi Namba, Christina Eugster Oegema, Wieland B. Huttner, Julia Ladewig, Michael Heide in EMBO reports
ARHGAP11B — this complex name is given to a gene that is unique to humans and plays an essential role in the development of the neocortex. The neocortex is the part of the brain to which we owe our high mental abilities. A team of researchers from the German Primate Center (DPZ) — Leibniz Institute for Primate Research in Göttingen, the Max Planck Institute for Molecular Cell Biology and Genetics (MPI-CBG) in Dresden, and the Hector Institute for Translational Brain Research (HITBR) in Mannheim has investigated the importance of ARHGAP11B in neocortex development during human evolution.
To do this, the team introduced for the first time a gene that exists only in humans into laboratory-grown brain organoids from our closest living relatives, chimpanzees. In the chimpanzee brain organoid, the ARHGAP11B gene led to an increase in brain stem cells relevant to brain growth and an increase in those neurons that play a critical role in the extraordinary mental abilities of humans. If, on the other hand, the ARHGAP11B gene was switched off in human brain organoids, the quantity of these brain stem cells fell to the level of a chimpanzee. Thus, the research team was able to show that the ARGHAP11B gene played a crucial role in the evolution of the brain from our ancestors to modern humans.
Animal studies on great apes have long been banned in Europe for ethical reasons. For the question pursued here, so-called organoids, i.e. three-dimensional cell structures a few millimeters in size that are grown in the laboratory, are an alternative to animal experiments. These organoids can be produced from pluripotent stem cells, which then differentiate into specific cell types, such as nerve cells. In this way, the research team was able to produce both chimpanzee brain organoids and human brain organoids.
“These brain organoids allowed us to investigate a central question concerning ARHGAP11B,” says Wieland Huttner of the MPI-CBG, one of the three lead authors of the study.
“In a previous study we were able to show that ARHGAP11B can enlarge a primate brain. However, it was previously unclear whether ARHGAP11B had a major or minor role in the evolutionary enlargement of the human neocortex,” says Wieland Huttner.
To clarify this, the ARGHAP11B gene was first inserted into brain ventricle-like structures of chimpanzee organoids. Would the ARGHAP11B gene lead to the proliferation of those brain stem cells in the chimpanzee brain that are necessary for the enlargement of the neocortex?
“Our study shows that the gene in chimpanzee organoids causes an increase in relevant brain stem cells and an increase in those neurons that play a crucial role in the extraordinary mental abilities of humans,” said Michael Heide, the study’s lead author, who is head of the Junior Research Group Brain Development and Evolution at the DPZ and employee at the MPI-CBG.
When the ARGHAP11B gene was knocked out in human brain organoids or the function of the ARHGAP11B protein was inhibited, the amount of these brain stem cells decreased to the level of a chimpanzee. “We were thus able to show that ARHGAP11B plays a crucial role in neocortex development during human evolution,” says Michael Heide.
Rapid transgenerational adaptation in response to intercropping reduces competition
by Laura Stefan, Nadine Engbersen, Christian Schöb in eLife
The findings provide preliminary evidence about how quickly crops bred for single-species, or ‘monoculture’, settings can adapt to growing with other crop species.
Growing multiple food crops together is a more sustainable farming practice mimicking highly productive wild plant communities. This process, known as intercropping, takes advantage of complementary features of different types of crops to maximise production and minimise the need for fertilisers and other environmentally harmful practices. For example, indigenous people in North America have long grown corn, beans and squash together to maximise the yield of each plant and reduce the need for watering or fertiliser.
“Most commercial crops, however, have been bred for traits that make them highly productive in single-crop settings,” explains lead author Laura Stefan, a former PhD student at ETH Zurich and now a postdoctoral researcher at Agroscope, the Swiss Confederation’s Institute for Agricultural Research. “These crops may not be well suited for growing in multi-crop systems, which may reduce the benefits of intercropping.”
To learn more about different crops’ ability to adapt, the team grew wheat, oat, lentil, flax, camelina and coriander species in small plots. The plots included 13 combinations of two species, four mixtures of four different species, plants growing individually or in single-species parcels, in fertilised or unfertilised plots. The team repeated the experiments for three consecutive years, each year using seeds collected from the plots of the previous year to assess the generational effects of growing in different systems. In the third year, they measured the plants’ traits and productivity. They found that plants grown in the same multi-crop setting for two generations adapted to compete less and cooperate more with each other. However, the yield advantage of these multispecies crops compared to monoculture crops was only increased in fertilised plots. Over two generations, plants grown together in either monocultures or mixed-species plots grew taller. They also produced “cheaper,” or thinner leaves, indicating a growth strategy associated with rapid biomass production.
“Our study shows that annual crops rapidly adapt to be more cooperative over just two generations, but this doesn’t lead to increased yield advantages without fertiliser,” says co-author Nadine Engbersen, who worked on the study as a PhD student at the Institute of Agricultural Sciences at ETH Zurich, Switzerland. “Unexpectedly, the plants all grew to have more similar traits rather than specialising to fill a unique niche.”
The authors suggest that the short time frame of the study — over just three years — may explain why more differentiation did not occur. It is unlikely that many genetic changes happened during that time. However genetic selection of particular genotypes might have occurred for those species with existing genotypic variation. Furthermore, epigenetic modifications that turn genes on or off may explain some of the observed plant adaptations. Microbes or nutrient resources passed from one plant generation to the next via seeds may also explain some of these rapid adaptations. Longer-term studies may observe more adaptations caused by genetic mutations or genetic recombination, the rearrangement of plant DNA sequences. The current results suggest selective breeding could give rise to traits that optimise cooperation and yield in multispecies plots.
“Our findings have important implications for the shift to more diversified agriculture,” concludes senior author Christian Schöb, Head of the Agricultural Ecology Group, previously at ETH Zurich and now at the University Rey Juan Carlos. “They suggest breeding plants to grow in mixed-species plots may further improve yields and reduce the need for fertiliser and other harmful practices.”
Living material assembly of bacteriogenic protocells
by Can Xu, Nicolas Martin, Mei Li, Stephen Mann in Nature
Scientists have harnessed the potential of bacteria to help build advanced synthetic cells which mimic real life functionality.
The research, led by the University of Bristol, makes important progress in deploying synthetic cells, known as protocells, to more accurately represent the complex compositions, structure, and function of living cells. Establishing true-to-life functionality in protocells is a global grand challenge spanning multiple fields, ranging from bottom-up synthetic biology and bioengineering to origin of life research. Previous attempts to model protocells using microcapsules have fallen short, so the team of researchers turned to bacteria to build complex synthetic cells using a living material assembly process.
Professor Stephen Mann from the University of Bristol’s School of Chemistry, and the Max Planck Bristol Centre for Minimal Biologytogether with colleagues Drs Can Xu, Nicolas Martin (currently at the University of Bordeaux) and Mei Li in the Bristol Centre for Protolife Research have demonstrated an approach to the construction of highly complex protocells using viscous micro-droplets filled with living bacteria as a microscopic building site.
In the first step, the team exposed the empty droplets to two types of bacteria. One population spontaneously was captured within the droplets while the other was trapped at the droplet surface. Then, both types of bacteria were destroyed so that the released cellular components remained trapped inside or on the surface of the droplets to produce membrane-coated bacteriogenic protocells containing thousands of biological molecules, parts and machinery.
The researchers discovered that the protocells were able to produce energy-rich molecules (ATP) via glycolysis and synthesize RNA and proteins by in vitro gene expression, indicating that the inherited bacterial components remained active in the synthetic cells. Further testing the capacity of this technique, the team employed a series of chemical steps to remodel the bacteriogenic protocells structurally and morphologically. The released bacterial DNA was condensed into a single nucleus-like structure, and the droplet interior infiltrated with a cytoskeletal-like network of protein filaments and membrane-bounded water vacuoles.
As a step towards the construction of a synthetic/living cell entity, the researchers implanted living bacteria into the protocells to generate self-sustainable ATP production and long-term energization for glycolysis, gene expression and cytoskeletal assembly. Curiously, the protoliving constructs adopted an amoeba-like external morphology due to on-site bacterial metabolism and growth to produce a cellular bionic system with integrated life-like properties.
Corresponding author Professor Stephen Mann said: “Achieving high organisational and functional complexity in synthetic cells is difficult especially under close-to-equilibrium conditions. Hopefully, our current bacteriogenic approach will help to increase the complexity of current protocell models, facilitate the integration of myriad biological components and enable the development of energised cytomimetic systems.”
First author Dr Can Xu, Research Associate at the University of Bristol, added: “Our living-material assembly approach provides an opportunity for the bottom-up construction of symbiotic living/synthetic cell constructs. For example, using engineered bacteria it should be possible to fabricate complex modules for development in diagnostic and therapeutic areas of synthetic biology as well as in biomanufacturing and biotechnology in general.”
SREBP2-dependent lipid gene transcription enhances the infection of human dendritic cells by Zika virus
by Emilie Branche, Ying-Ting Wang, Karla M. Viramontes, et al in Nature Communications
Zika virus has a trick up its sleeve. Once inside the body, the virus likes to make a bee line for dendritic cells, the cells we rely on to launch an effective immune response.
“Dendritic cells are major cells of the innate immune system,” says LJI Professor Sujan Shresta, Ph.D., a member of the LJI Center for Infectious Disease and Vaccine Research. “How is this virus so clever that it’s able to establish infection in cells that would normally fight infections?”
Now Shresta and colleagues at LJI and the University of California, San Diego, have found that Zika virus actually forces dendritic cells to stop acting as immune cells. Using a new model of Zika virus infection, the LJI team showed that Zika virus instead makes dendritic cells churn out lipid molecules, which the virus uses to build copies of itself.
“Here are dendritic cells doing everything to help a virus,” says Shresta.
The is a major step forward in the Shresta Lab’s work to guide the design of new antiviral therapies against many members of the Flavivirus family, including Zika, dengue, and Japanese encephalitis virus (JEV).
“Understanding how viruses interact with human cells is critical for understanding how to treat or prevent infection in the future,” says UC San Diego Professor Aaron Carlin, M.D., Ph.D., a former trainee in the Shresta Lab and co-leader of the new study.
Emilie Branche, Ph.D., a former postdoctoral researcher at LJI, led the effort to develop a model to better understand how Zika virus and dengue virus target dendritic cells. She worked with human immune cells called monocytes, which she prompted to differentiate into dendritic cells. Branche analyzed how gene expression in these dendritic cells shifted during a Zika or dengue infection. She then compared the changes in gene expression with changes in cells she subjected to a “mock infection.” This comparison revealed precisely how Zika pulls off its cellular take-over. The researchers found that Zika virus manipulates the genes that control lipid metabolism in dendritic cells. The virus calls in a cellular protein called SREBP, which forces lipid, or fat molecule, production to go into overdrive. These lipids became the building blocks to assemble new copies of Zika virus — copies meant to spread through the body, further driving infection.
“We showed that Zika, but not dengue, modulates cellular metabolism in order to increase its replication,” says Branche.
The team then investigated whether Zika turns other cells into lipid factories. Although Zika is also known to target neuronal precursor cells, the researchers showed that Zika doesn’t manipulate the lipid metabolism genes in those cells. Shresta was surprised to see these changes only in dendritic cells, and she was surprised that Zika, not dengue, altered lipid production.
“These viruses are crazy,” says Shresta. “How these viruses manipulate host cell responses is very virus-specific and very cell-type specific.”
The next step is to develop antivirals that stop Zika from exploiting the genes for lipid metabolism. The new study shows that therapeutically silencing SREBP may hold promise. What to do about Zika’s cousin, dengue? Because these viruses are so closely related and overlap in so many places, Shresta imagines a SREBP inhibitor as just one ingredient in a “cocktail” of inhibitors to treat many different flavivirus infections.
“The more knowledge we can generate about these viruses, the closer we are to a ‘pan-flavivirus’ inhibitor,” she says.
Genomic analyses of the Linum distyly supergene reveal convergent evolution at the molecular level
by Juanita Gutiérrez-Valencia, Marco Fracassetti, Emma L. Berdan, Ignas Bunikis, et al in Current Biology
Scientists have solved the century-old mystery of a supergene that causes efficient cross-pollination in flowers. The results show that sequence length variation at the DNA level is important for the evolution of two forms of flowers that differ in the length of their sexual organs.
Gardeners and botanists have known since the 1500s that some plant species have two forms of flowers that differ reciprocally in the length of their male and female sexual organs. Darwin first proposed that such distylous flowers promoted efficient cross-pollination by insect pollinators. Early geneticists showed that the two forms of flowers were controlled by a single chromosomal region likely harboring a cluster of genes, a supergene. But until recently this supergene had never been sequenced.
Now, researchers at Stockholm University, together with partners at Uppsala University, Durham University, University of Granada, and University of Seville, have solved the mystery of the supergene. They studied a system where already Darwin described distyly, wild flaxseed species, Linum, and used modern DNA sequencing methods to identify the supergene. Surprisingly, they found that the supergene responsible for differing lengths of male and female sexual organs itself varied in length. Specifically, the dominant form of the supergene contained about 260 000 base pairs of DNA that were missing from the recessive form. The 260 000 base pair stretch of DNA harbored several genes likely to cause length variation in sexual organs.
“These results were really surprising to us, because a similar genetic makeup of the supergene that governs distyly has previously been identified in another system, primroses, where it evolved completely independently,” said Tanja Slotte, Professor in Ecological Genomics at Stockholm University and senior author of the study.
“Not only has evolution repeatedly led to similar variation in the flowers of primroses and flaxseed species, it has also relied on a similar genetic solution to achieve this feat,” said Juanita Gutiérrez-Valencia, PhD student at Stockholm University and first author of the study.
These findings provide new insights into the exceptional power of evolution to find convergent solutions to widespread adaptive challenges such as the need for flowering plants to be cross-pollinated.
“Distyly is ultimately a mechanism for efficient cross-pollination. Understanding pollination mechanisms is particularly important today given climate change and challenges faced by both plant and insect pollinator populations,” said Professor Tanja Slotte.
High-resolution structures of the SARS-CoV-2 N7-methyltransferase inform therapeutic development
by Jithesh Kottur, Olga Rechkoblit, Richard Quintana-Feliciano, Daniela Sciaky, Aneel K. Aggarwal in Nature Structural & Molecular Biology
A team of Mount Sinai researchers has produced a high-resolution crystal structure of an enzyme essential to the survival of SARS-CoV-2, the virus that causes COVID-19. The discovery could lead to the design of critically needed new antivirals to combat current and future coronaviruses.
The enzyme, known as nsp14, has a crucially important region known as the RNA methyltransferase domain, which has eluded previous attempts by the scientific community to characterize its three-dimensional crystal structure.
“Being able to visualize the shape of the methyltransferase domain of nsp14 at high resolution gives us insights into how to design small molecules that fit into its active site, and thus inhibit its essential chemistry,” says senior author Aneel Aggarwal, PhD, Professor of Pharmacological Sciences at the Icahn School of Medicine at Mount Sinai. “With this structural information, and in collaboration with medicinal chemists and virologists, we can now design small molecule inhibitors to add to the family of antivirals that go hand-in-hand with vaccines to combat SARS-CoV-2.”
Prescription antivirals that target key enzymes of SARS-CoV-2 include nirmatrelvir for the main protease (MPro) enzyme, and molnupiravir and remdesivir for the RNA polymerase (nsp12) enzyme. Research to develop new antivirals targeting different enzymatic activities has been accelerating in laboratories around the world, and Mount Sinai’s discovery has added significantly to that effort.
“Part of what drives our work,” says Dr. Aggarwal, “is the knowledge gained from treating HIV — that you typically need a cocktail of inhibitors for maximum impact against the virus.”
The Mount Sinai team actually developed three crystal structures of nsp14, each with different cofactors, from which they identified the best scaffold for the design of antivirals for inhibiting the RNA methyltransferase activity that the enzyme enables and the virus needs to survive. According to their scheme, the antiviral would take the place of the natural cofactor S-adenosylmethionine, thus preventing the methyltransferase chemistry from occurring. The crystal structures that the team has elucidated have been made available to the public and will now serve as guides for biochemists and virologists globally to engineer these compounds. Making the discovery possible was the ability of researchers to clear a hurdle that had prevented others in the past from creating three-dimensional crystals of the nsp14 methytransferase domain.
“We employed an approach known as fusion-assisted crystallization,” explains lead author Jithesh Kottur, PhD, a postdoctoral fellow at Icahn Mount Sinai, and a crystallographer and biochemist. “It involves fusing the enzyme with another small protein that helps it to crystalize.”
Dr. Aggarwal, an internationally recognized structural biologist, underscores the importance of ongoing investigative work by researchers in his field against a virus that has led to millions of deaths globally.
“The virus evolves so quickly that it can develop resistance to the antivirals now available, which is why we need to continue developing new ones,” he observes. “Because of the high sequence conservation of nsp14 across coronaviruses and their variants (meaning it does not mutate much), our study will aid in the design of broad-spectrum antivirals for both present and future coronavirus outbreaks.”
Prediction of sex-determination mechanisms in avian primordial germ cells using RNA-seq analysis
by Kennosuke Ichikawa, Yoshiaki Nakamura, Hidemasa Bono, Ryo Ezaki, Mei Matsuzaki, Hiroyuki Horiuchi in Scientific Reports
Scientists have known that sex-determination in vertebrates happens in the germ cells, a body’s reproductive cells, and the somatic cells, the cells that are not reproductive cells. Yet they have not fully understood the mechanisms by which it happens. To better grasp the process of the germ cell’s sex determination, a research team has analyzed germ cells in chickens using RNA-sequencing to predict the mechanism that determines the sex. Their study provides insight into the mechanism of sex determination in birds.
“While previous studies have demonstrated that chicken primordial germ cells possess a characteristic feature in sex determination, its mechanism remains unclear. To solve this challenge, we revealed gene expression profiles of male and female primordial germ cells derived from early chick embryos and then predicted the sex determination mechanism,” said Kennosuke Ichikawa, a postdoctoral researcher at the Genome Editing Innovation Center, Hiroshima University. This research is the first to predict the sex-determination mechanism by comparing the gene expression profiles of avian primordial germ cells at each embryonic stage, as well as by using a stimulation test.
Birds have unique mechanisms of sex determination, that are different from mammals. In mammals, which have an XX (female) — XY (male) sex chromosome system, their sex determination depends on the action of the Y-chromosome. In birds, which have a ZZ (male) — ZW (female) sex chromosome system, their sex depends on the action of the Z chromosome. Yet the molecular mechanism of sex determination remains unclear. The development of the reproductive glands called gonads, into either ovaries or testes, and the development of other sexual characteristics are at least partially cell autonomous. The researchers’ investigation of the sex-determination mechanism in birds provides them insight into the evolution of vertebrate sex-determining mechanisms.
To investigate the mechanisms underlying sex determination in avian germ cells, the team purified male and female primordial germ cells from the blood and the gonads, using fluorescence-activated cell sorting. With this process they achieved a purity of greater than 96 percent. They determined gene expression profiles of the primordial germ cells at each developmental stage for each sex using RNA-sequencing analysis, where next-generation sequencing is used to examine the quantity and sequences of RNA in a sample. Then, the researchers predicted the sex-determination mechanism of the primordial germ cells using bioinformatic analysis, where computer tools are used to understand biological data. To evaluate the prediction, they stimulated male primordial germ cells with retinoic acid in vitro, and examined the changes in gene expression.
Before settling in the gonads, the female circulating primordial germ cells obtained from blood displayed sex-biased expression. The primordial germ cells from the gonads also exhibited sex-biased expression, and the number of female-biased genes detected was higher than that of male-biased genes. The team realized that the female-biased genes in the primordial germ cells were enriched in some metabolic processes. To reveal the mechanisms underlying this process, the researchers performed stimulation tests.
The team used retinoic acid to stimulate the cultured primordial germ cells collected from male embryos. This stimulation resulted in the upregulation — the process where a cell’s components increase — of several female-biased genes. Overall, their results suggest that sex determination in avian primordial germ cells involves aspects of both cell-autonomous and somatic-cell regulation. Moreover, it appears that sex determination occurs earlier in females than in males.
“We successfully predicted female-specific potential processes and pathways in chicken primordial germ cells. We believe our data set can significantly contribute to elucidating the avian sex determination mechanism,” said Ichikawa.
Looking ahead to future work, the team plans to use the data set to identify the key molecules directly inducing the feminization of chicken primordial germ cells.
“The ultimate goal of this study is to elucidate the sex determination mechanism and then establish a sex selection method in chickens using genome editing targeting the key molecules,” said Ichikawa.
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