GN/ Targeting proteins inside cell membrane
Genetics biweekly vol.54, 21st March — 4th April
TL;DR
- Drug developers overcome membrane challenges with custom proteins targeting intramembrane sites, aiding drug delivery precision.
- Extremophiles’ survival strategies inform Earth life and extraterrestrial possibilities, offering valuable insights.
- Egg coat tightening post-fertilization prevents embryo damage, shedding light on infertility and contraception.
- Genome tuning of mushrooms and molds enhances nutritional value sustainably, promoting gourmet food production.
- Simple technique boosts accuracy in studying plant gene responses to external factors like temperature shifts.
- Novel protein design fights COVID-19 by recognizing and hindering viral infection, aiding diagnostics and prevention.
- Transgenic cow producing human insulin offers hope for affordable diabetes treatment, potentially revolutionizing insulin production.
- Gut bacteria and tryptophan-rich diets shield against pathogenic E. coli, paving the way for gastrointestinal illness prevention.
- Evolutionary divergence leads to different responses to “random DNA” in yeast and mammalian cells, despite a shared ancestry.
- Protein engineering method, combining cost-effective experiments and machine learning, predicts protein effectiveness efficiently for diverse applications.
- And more!
Overview
Genetic technology is defined as the term that 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 of the global genetic engineering market, followed by Europe and the Asia Pacific, respectively.
Latest News & Research
De novo-designed transmembrane proteins bind and regulate a cytokine receptor
by Marco Mravic, Li He, Huong T. Kratochvil, Hailin Hu, Sarah E. Nick, Weiya Bai, Anne Edwards, Hyunil Jo, Yibing Wu, Daniel DiMaio, William F. DeGrado in Nature Chemical Biology
Hitting targets embedded within the cell membrane has long been difficult for drug developers due to the membrane’s challenging biochemical properties. Now, Scripps Research chemists have demonstrated new custom-designed proteins that can efficiently reach these “intramembrane” targets.
In their study, the researchers used a unique computer-based approach to design novel proteins targeting the membrane-spanning region of the erythropoietin (EPO) receptor, which controls red blood cell production and can go awry in cancers. In addition to these new EPO-targeting molecules, the study yielded a general computational process, or “workflow,” for streamlining the flexible custom design of proteins aimed at intramembrane targets. The researchers are now using their approach to develop potential new intramembrane-targeting treatments across a wide range of diseases.
“This work opens up many new possibilities for the modulation of targets within the cell membrane, including for therapeutic applications and understanding signaling mechanisms across cell biology,” says study co-corresponding author Marco Mravic, PhD, an assistant professor in the Department of Integrative Structural and Computational Biology at Scripps Research.
The study’s other co-corresponding authors were Daniel DiMaio, MD, PhD, of the Yale School of Medicine; and William DeGrado, PhD, of the University of California, San Francisco School of Pharmacy, where Mravic was previously a PhD student.
“A major goal of synthetic biology is to design proteins with biological activity — here, we report the design and testing of a small protein that specifically perturbs the activity of a much larger protein receptor involved in blood cell growth and differentiation,” says DiMaio, who is a professor of Genetics and of Molecular Biophysics and Biochemistry, and deputy director of Yale Cancer Center. “We accomplished this by targeting the segment of the receptor that crosses the cell membrane. Because many cell proteins contain structurally conserved membrane-spanning segments, this general approach may be applicable to many other protein targets and provides a new tool to modulate the behavior of cells.”
Hitting intramembrane targets has long been an important goal in biomedicine since many proteins in cells — especially receptor proteins — have functionally important domains inside the membrane. Such proteins have prominent roles in almost every area of health and disease. Yet intramembrane targets are not ordinary targets. Cell membranes generally are made of two layers of tightly spaced, fat-related “lipid” molecules, which are water-repellent and have other unique and complex properties. This makes the intramembrane space a much harder target for drug designers, compared to the watery zones of cell surfaces or interiors.
“There have been very few successful examples of drugs that target this space inside the membrane,” Mravic says.
Those few successes, which include treatments for low-blood-platelet disorders and cystic fibrosis, have come from blind screenings of large compound libraries or from close mimicry of proteins known to interact with partner proteins within the cell membrane. By contrast, Mravic and colleagues set out to design completely novel proteins — small ones called peptides — to hit intramembrane protein targets in new and diverse ways. To do that, they had to extend the frontier of computational methods, combining “data mining” of known protein-to-protein interactions in membranes with traditional physics-based predictions of protein interactions.
Ultimately, Mravic and his colleagues designed the first proteins that bind the EPO receptor’s membrane-spanning portion in a new way — not seen in nature. The team showed that these proteins very specifically and potently block the receptor’s function, in contrast to prior approaches.
The results may be of most immediate interest to researchers seeking new ways to inhibit the EPO receptor, which is often abnormally activated by tumor cells to maintain their growth and survival. But for Mravic and his colleagues, the study above all represents a proof of principle of a new and more flexible approach to intramembrane targeting.
“We intend to use this approach to target membrane proteins across multiple biological processes and disease areas, including cancers, immune disorders, and pain,” Mravic says.
He also expects the computational workflow he designed for the project to be a general accelerator of membrane-targeting drug design.
“Before, the process basically involved two people in a dark room looking at a computer screen and saying, ‘Yeah, I think this looks better than that,’” Mravic says. “Now, we’ve automated a lot of that molecule design process and decision making in the computer. Being more modular, flexible and streamlined allows the method to be more accessible for a broader range of scientists.”
Exploring Andean High-Altitude Lake Extremophiles through Advanced Proteotyping
by Katharina Runzheimer, Clément Lozano, Diana Boy, Jens Boy, Roberto Godoy, Francisco J. Matus, Denise Engel, Bruno Pavletic, Stefan Leuko, Jean Armengaud, Ralf Moeller in Journal of Proteome Research
Perfectly adapted microorganisms live in extreme environments from deep-sea trenches to mountaintops. Learning more about how these extremophiles survive in hostile conditions could inform scientists about life on Earth and potential life on other planets. Researchers detail a method for more accurate extremophile identification based on protein fragments instead of genetic material. The study identified two new hardy bacteria from high-altitude lakes in Chile — an environment like early Mars.
Even though humans tend to avoid settling in extremely hot, cold or high-altitude areas, some microorganisms have adapted to live in such harsh locations. These extremophile microbes are of interest to astrobiologists who are searching for life on other planets. Researchers currently use individual gene sequencing to identify Earth-bound microbes, based on their DNA. However, current methods can’t distinguish closely related species of extremophiles. So, Ralf Moeller and colleagues investigated whether they could identify an extremophile by using its protein signature rather than a gene sequence.
The researchers started their demonstration with water samples from five high-altitude Andean lakes more than 2.3 miles above sea level in the Chilean Altiplano. (For reference, Denver is about one mile above sea level.) From the samples, the researchers cultivated 66 microbes and then determined which of two methods better identified the microorganisms:
- Traditional gene sequencing compared the nucleotides of the 16s rRNA gene (a typical gene for sequence-based microbe analysis) from each sample to a database for identification.
- The newer “proteotyping” technique analyzed protein fragments known as peptides to produce peptide signatures, which the team used to identify microorganisms from proteome databases.
With these methods, the researchers identified 63 of the 66 microorganisms that were cultivated from the high-altitude lake samples. For the three microorganisms that gene sequencing failed to identify because their genetic information wasn’t in the available database, proteotyping identified two potentially new types of extremophile bacteria. These results suggest proteotyping could be a more complete solution for identifying extremophile microorganisms from small biological samples. The team says protein profiling could someday help us search for and identify extraterrestrial life and better explore the biodiversity on our own planet.
ZP2 cleavage blocks polyspermy by modulating the architecture of the egg coat
by Shunsuke Nishio, Chihiro Emori, Benjamin Wiseman, et al in Cell
After the egg has been fertilized by a sperm, the surrounding egg coat tightens, mechanically preventing the entry of additional sperm and the ensuing death of the embryo. This is according to a new study led by researchers at Karolinska Institutet. The work also explains how mutations in egg coat proteins can cause female infertility and may eventually lead to new contraceptive methods.
Fertilization in mammals begins when a sperm attaches to the egg coat, a filamentous extracellular envelope that sperm must penetrate in order to fuse with the egg. Now an international team of researchers has mapped in detail the structure and function of the protein ZP2, an egg coat filament component that plays a key role in regulating how egg and sperm interact with each other at fertilization.
“It was known that ZP2 is cleaved after the first sperm has entered the egg, and we explain how this event makes the egg coat harder and impermeable to other sperm,” says Luca Jovine, Professor at the Department of Biosciences and Nutrition, Karolinska Institutet, who led the study. “This prevents polyspermy — the fusion of multiple sperm with a single egg — which is a fatal condition for the embryo.”
The changes in the egg coat after fertilization are also crucial to female fertility by ensuring the protection of the developing embryo until this implants in the uterus. The new knowledge may therefore have implications for the development of non-hormonal contraceptives that interfere with the formation of the egg coat. Moreover, the study explains egg coat-associated forms of female infertility.
“Mutations in the genes encoding egg coat proteins can cause female infertility, and more and more such mutations are being discovered,” explains Luca Jovine. “We hope that our study will contribute to the diagnosis of female infertility and, possibly, the prevention of unwanted pregnancies.”
Importantly, the study also shows that a part of ZP2 that was previously thought to act as a receptor for sperm is not necessary for sperm to attach to the egg. This raises the question of what is the true sperm receptor on the egg coat, which the researchers plan to investigate further.
The researchers combined X-ray crystallography and cryo-EM to study the 3D structure of egg coat proteins. The interaction between sperm and eggs carrying mutations in the ZP2 protein was functionally studied in mice, while the AI program AlphaFold was used to predict the structure of the egg coat in humans.
Edible mycelium bioengineered for enhanced nutritional value and sensory appeal using a modular synthetic biology toolkit
by Vayu Maini Rekdal, Casper R. B. van der Luijt, Yan Chen, Ramu Kakumanu, Edward E. K. Baidoo, Christopher J. Petzold, Pablo Cruz-Morales, Jay D. Keasling in Nature Communications
With animal-free dairy products and convincing vegetarian meat substitutes already on the market, it’s easy to see how biotechnology can change the food industry. Advances in genetic engineering are allowing us to harness microorganisms to produce cruelty-free products that are healthy for consumers and healthier for the environment.
One of the most promising sources of innovative foods is fungi — a diverse kingdom of organisms that naturally produce a huge range of tasty and nutritious proteins, fats, antioxidants, and flavor molecules. Chef-turned-bioengineer Vayu Hill-Maini, an affiliate in the Biosciences Area at Lawrence Berkeley National Laboratory (Berkeley Lab), is exploring the many possibilities for new flavors and textures that can be made from modifying the genes already present in fungi.
“I think it’s a fundamental aspect of synthetic biology that we’re benefiting from organisms that have evolved to be really good at certain things,” said Hill-Maini, who is a postdoctoral researcher at UC Berkeley in the lab of bioengineering expert Jay Keasling. “What we’re trying to do is to look at what is the fungus making and try to kind of unlock and enhance it. And I think that’s an important angle that we don’t need to introduce genes from wildly different species. We’re investigating how we can stitch things together and unlock what’s already there.”
In their recent paper, Hill-Maini and colleagues at UC Berkeley, the Joint BioEnergy Institute, and the Novo Nordisk Foundation Center for Biosustainability studied a multicellular fungus called Aspergillus oryzae, also known as koji mold, that has been used in East Asia to ferment starches into sake, soy sauce, and miso for centuries. First, the team used CRISPR-Cas9 to develop a gene editing system that can make consistent and reproducible changes to the koji mold genome. Once they had established a toolkit of edits, they applied their system to make modifications that elevate the mold as a food source. First, Hill-Maini focused on boosting the mold’s production of heme — an iron-based molecule which is found in many lifeforms butis most abundant in animal tissue, giving meat its color and distinctive flavor. (A synthetically produced plant-derived heme is also what gives the Impossible Burger its meat-duping properties.) Next, the team punched up production of ergothioneine, an antioxidant only found in fungi that is associated with cardiovascular health benefits.
After these changes, the once-white fungi grew red. With minimal preparation — removing excess water and grinding — the harvested fungi could be shaped into a patty, then fried into a tempting-looking burger. Hill-Maini’s next objective is to make the fungi even more appealing by tuning the genes that control the mold’s texture.
“We think that there’s a lot of room to explore texture by varying the fiber-like morphology of the cells. So, we might be able to program the structure of the lot fibers to be longer which would give a more meat-like experience. And then we can think about boosting lipid composition for mouth feel and further nutrition,” said Hill-Maini, who was a Fellow of the Miller Institute for Basic Research in Science at UC Berkeley during the study. “I’m really excited about how can we further look at the fungus and, you know, tinker with its structure and metabolism for food.”
Though this work is just the beginning of the journey to tap into fungal genomes to create new foods, it showcases the huge potential of these organisms to serve as easy-to-grow protein sources that avoid the complex ingredients lists of current meat substitutes and the cost barriers and technical difficulties hindering the launch of cultured meat. Additionally, the team’s gene editing toolkit is huge leap forward for the field of synthetic biology as a whole. Currently, a great variety of biomanufactured goods are made by engineered bacteria and yeast, the single-celled cousins of mushrooms and mold. Yet despite humanity’s long history of domesticating fungi to eat directly or to make staples like miso, multicellular fungi have not yet been harnessed as engineered cellular factories to the same extent because their genomes are far more complex, and have adaptations that make gene editing a challenge. The CRISPR-Cas9 toolkit developed in this paper lays the foundation to easily edit koji mold and its many relatives.
“These organisms have been used for centuries to produce food, and they are incredibly efficient at converting carbon into a wide variety of complex molecules, including many that would be almost impossible to produce using a classic host like brewer’s yeast or E. coli,” said Jay Keasling, who is a senior scientist at Berkeley Lab and a professor at UC Berkeley. “By unlocking koji mold through the development of these tools, we are unlocking the potential of a huge new group of hosts that we can use to make foods, valuable chemicals, energy-dense biofuels, and medicines. It’s a thrilling new avenue for biomanufacturing.”
Given his culinary background, Hill-Maini is keen to ensure that the next generation of fungi-based products are not only palatable, but truly desirable to customers, including those with sophisticated tastes. In a separate study, he and Keasling collaborated with chefs at Alchemist, a two-Michelin-starred restaurant in Copenhagen, to play with the culinary potential of another multicellular fungus, Neurospora intermedia. This fungus is traditionally used in Indonesia to produce a staple food called oncom by fermenting the waste products left over from making other foods, such as tofu. Intrigued by its ability to convert leftovers into a protein-rich food, the scientists and chefs studied the fungus in the Alchemist test kitchen. They discovered N. intermedia produces and excretes many enzymes as it grows. When grown on starchy rice, the fungi produces an enzyme that liquifies the rice and makes it intensely sweet.
“We developed a process with just three ingredients — rice, water, and fungus — to make a beautiful, striking orange-colored porridge,” said Hill-Maini. “That became a new dish on the tasting menu that utilizes fungal chemistry and color in a dessert. And I think that what it really shows is that there’s opportunity to bridge the laboratory and the kitchen.”
A normalization method that controls for total RNA abundance affects the identification of differentially expressed genes, revealing bias toward morning‐expressed responses
by Kanjana Laosuntisuk, Amaranatha Vennapusa, Impa M. Somayanda, Adam R. Leman, SV Krishna Jagadish, Colleen J. Doherty in The Plant Journal
Researchers have published a simple trick that improves the accuracy of techniques that help us understand how external variables — such as temperature — affect gene activity in plants.
“There are really two contributions here,” says Colleen Doherty, corresponding author of a paper on the work and an associate professor of molecular and structural biochemistry at North Carolina State University. “First, we’re raising the visibility of a problem that many of us in the plant research community were unfamiliar with, as well as highlighting the solution. Second, we’ve demonstrated that addressing this problem can make a significant difference in our understanding of gene activity in plants.”
At issue is a technique called RNA-seq analysis, which is used to measure changes in gene activity — i.e., when genes are actively transcribing to produce proteins.
“We use RNA-seq analysis to assess how plants respond to various stimuli, or changes in their environment,” Doherty says. “It’s used widely because it’s a relatively easy and inexpensive way to monitor plant responses.”
For example, researchers can use RNA-seq analysis to see which genes are turned on when a plant is experiencing drought conditions, which then informs the development of new plant varieties that are drought resistant. But there’s a specific challenge related to RNA-seq analysis, which Doherty and her collaborators ran into by accident.
“We were monitoring how plants respond to different temperatures at multiple times of day, and the results we got were wildly divergent,” Doherty says. “We initially thought we might be doing something wrong. But when we began looking into it, we learned that animals and yeasts are known to have global changes in transcription based on variables such as the time of day or nitrogen deprivation.”
In other words, researchers want to see how specific variables — such as increased temperature — affect transcription in specific genes. But there are some variables — like time of day — that can increase or decrease transcription in all the genes. This can throw off researchers’ ability to draw conclusions about the specific variables they want to study.
“Luckily, we found that this problem is sufficiently well-established among researchers who work on non-plant species that they have developed a method to account for it, called an artificial spike-in,” Doherty says. “These and similar techniques have been used in plant science in other contexts and when using older techniques and technologies. But for whatever reason, our field didn’t incorporate artificial spike-ins into our methodology when we adopted RNA-seq analysis.”
Artificial spike-ins make use of pieces of foreign RNA that are unlike anything in the plant’s genome, meaning that the foreign RNA will not be confused with anything the plant itself produces. Researchers introduce the foreign RNA into the analysis process at the beginning of the experiment. Because global changes in transcription will not affect the foreign RNA, it can be used as a fixed benchmark that allows researchers to determine the extent to which there is an overall increase or decrease in RNA that the plant itself is producing.
“When we used artificial spike-ins to account for global changes in transcription, we found that the differences in plants exposed to temperature changes at different times of day were actually even greater than we anticipated,” Doherty says.
The artificial spike-in gave us more accurate information and greater insight into how plants are behaving at night — since we found that global transcription was higher at night. Before we adopted the use of artificial spike-ins, we were missing a lot of what was happening at night.
“Artificial spike-ins are an elegant solution to a challenge many of us in the plant research community didn’t even know was there,” Doherty says. “We’re optimistic this technique will improve the accuracy of transcriptional analysis in the wide variety of conditions that can affect global transcription in plant species. And that, in turn, may help our research community garner new insights into the species we study.
“We didn’t develop this solution — artificial spike-ins — but we really hope it garners more widespread use in plant science.”
Dual coiled-coil protein domain mimic and drug delivery vehicle for SARS-CoV-2
by Dustin Britton, Chengliang Liu, Sihan Jia, Deven Paul, Jakub Legocki, Yingxin Xiao, Xunqing Jiang, Xiang-Peng Kong, Jin Kim Montclare in Biochemical Engineering Journal
In the wake of the COVID-19 pandemic, scientists have been racing to develop effective treatments and preventatives against the virus. A recent scientific breakthrough has emerged from the work of researchers aiming to combat SARS-CoV-2, the virus responsible for COVID-19.
Led by Jin Kim Montclare and her team, the study focuses on the design and development of a novel protein capable of binding to the spike proteins found on the surface of the coronavirus. The goal behind this innovative approach is twofold: first, to identify and recognize the virus for diagnostic purposes, and second, to hinder its ability to infect human cells.
The engineered protein, resembling a structure with five arms, exhibits a unique feature — a hydrophobic pore within its coiled-coil configuration. This feature enables the protein not only to bind to the virus but also to capture small molecules, such as the antiviral drug Ritonavir.
Ritonavir, already utilized in the treatment of SARS-CoV-2 infections, serves as a logical choice for integration into this protein-based therapeutic. By incorporating Ritonavir into the protein, the researchers aim to enhance the treatment’s efficacy while simultaneously targeting the virus directly.
The study marks a significant advancement in the fight against COVID-19, showcasing a multifaceted approach to combating the virus. Through a combination of protein engineering and computational design, the team has devised a promising strategy that may revolutionize current treatment modalities.
Although the research is still in its early stages, with no human or animal trials conducted as yet, the findings offer a proof of principle for the therapeutic potential of the designed protein. The team has demonstrated its ability to enhance the protein’s binding affinity to the virus spike protein, laying the groundwork for future investigations.
The potential applications of this protein-based therapeutic extend beyond COVID-19. Its versatility opens doors to combating a range of viral infections, offering a dual mode of action — preventing viral entry into human cells and neutralizing virus particles.
Furthermore, the success of this study underscores the importance of computational approaches in protein design. By leveraging computational tools such as Rosetta, the researchers have accelerated the process of protein engineering, enabling rapid iterations and optimization.
The development of this novel protein represents a significant step forward in the ongoing battle against COVID-19. As research progresses, the integration of computational design and protein engineering holds promise for the development of innovative therapeutics with broad-spectrum antiviral capabilities. While challenges remain, this study offers hope for a future where effective treatments against emerging viral threats are within reach.
Human proinsulin production in the milk of transgenic cattle
by Paulo S. Monzani, Juliano R. Sangalli, Rafael V. Sampaio, Samuel Guemra, Renato Zanin, Paulo R. Adona, Maria A. Berlingieri, Luiz F. C. Cunha‐Filho, Irma Y. Mora‐ Ocampo, Carlos P. Pirovani, Flávio V. Meirelles, Matthew B. Wheeler, Otavio M. Ohashi in Biotechnology Journal
An unassuming brown bovine from the south of Brazil has made history as the first transgenic cow capable of producing human insulin in her milk. The advancement, led by researchers from the University of Illinois Urbana-Champaign and the Universidade de São Paulo, could herald a new era in insulin production, one day eliminating drug scarcity and high costs for people living with diabetes.
“Mother Nature designed the mammary gland as a factory to make protein really, really efficiently. We can take advantage of that system to produce a protein that can help hundreds of millions of people worldwide,” said Matt Wheeler, professor in the Department of Animal Sciences, part of the College of Agricultural, Consumer and Environmental Sciences (ACES) at U. of I. He is also affiliated with the Carle Illinois College of Medicine, The Grainger College of Engineering, the College of Veterinary Medicine, the Beckman Institute, and the Carl R. Woese Institute for Genomic Biology.
Wheeler is lead author on a new study describing the development of the insulin-producing cow, a proof-of-concept achievement that could be scaled up after additional testing and FDA approval. Wheeler’s colleagues in Brazil inserted a segment of human DNA coding for proinsulin — the protein precursor of the active form of insulin — into cell nuclei of 10 cow embryos. These were implanted in the uteruses of normal cows in Brazil, and one transgenic calf was born. Thanks to updated genetic engineering technology, the human DNA was targeted for expression — the process whereby gene sequences are read and translated into protein products — in mammary tissue only.
“In the old days, we used to just slam DNA in and hope it got expressed where you wanted it to,” Wheeler said. “We can be much more strategic and targeted these days. Using a DNA construct specific to mammary tissue means there’s no human insulin circulating in the cow’s blood or other tissues. It also takes advantage of the mammary gland’s capabilities for producing large quantities of protein.”
When the cow reached maturity, the team unsuccessfully attempted to impregnate her using standard artificial insemination techniques. Instead, they stimulated her first lactation using hormones. The lactation yielded milk, but a smaller quantity than would occur after a successful pregnancy. Still, human proinsulin and, surprisingly, insulin were detectable in the milk.
“Our goal was to make proinsulin, purify it out to insulin, and go from there. But the cow basically processed it herself. She makes about three to one biologically active insulin to proinsulin,” Wheeler said. “The mammary gland is a magical thing.”
The insulin and proinsulin, which would need to be extracted and purified for use, were expressed at a few grams per liter in the milk. But because the lactation was induced hormonally and the milk volume was smaller than expected, the team can’t say exactly how much insulin would be made in a typical lactation.
Conservatively, Wheeler says if a cow could make 1 gram of insulin per liter and a typical Holstein makes 40 to 50 liters per day, that’s a lot of insulin. Especially since the typical unit of insulin equals 0.0347 milligrams.
“That means each gram is equivalent to 28,818 units of insulin,” Wheeler said. “And that’s just one liter; Holsteins can produce 50 liters per day. You can do the math.”
The team plans to re-clone the cow, and is optimistic they’ll achieve greater success with pregnancy and full lactation cycles in the next generation. Eventually, they hope to create transgenic bulls to mate with the females, creating transgenic offspring that can be used to establish a purpose-built herd. Wheeler says even a small herd could quickly outcompete existing methods — transgenic yeast and bacteria — for producing insulin, and could do so without having to create highly technical facilities or infrastructure.
“With regard to mass-producing insulin in milk, you’d need specialized, high-health-status facilities for the cattle, but it’s nothing too out of the ordinary for our well-established dairy industry,” Wheeler said. “We know what we’re doing with cows.”
An efficient system to collect and purify insulin products would be needed, as well as FDA approval, before transgenic cows could supply insulin for the world’s diabetics. But Wheeler is confident that day is coming.
Dopamine receptor D2 confers colonization resistance via microbial metabolites
by Samantha A. Scott, Jingjing Fu, Pamela V. Chang in Nature
Gut bacteria and a diet rich in the amino acid tryptophan can play a protective role against pathogenic E. coli, which can cause severe stomach upset, cramps, fever, intestinal bleeding and renal failure, according to a study.
The research reveals how dietary tryptophan — an amino acid found mostly in animal products, nuts, seeds, whole grains and legumes — can be broken down by gut bacteria into small molecules called metabolites. It turns out a few of these metabolites can bind to a receptor on gut epithelial (surface) cells, triggering a pathway that ultimately reduces the production of proteins that E. coli use to attach to the gut lining where they cause infection. When E. coli fail to attach and colonize the gut, the pathogen benignly moves through and passes out of the body.
The research describes a previously unknown role in the gut for a receptor, DRD2. DRD2 has otherwise been known as a dopamine (neurotransmitter) receptor in the central and peripheral nervous systems.
“It’s actually two completely different areas that this receptor could play a role in, which was not appreciated prior to our findings,” said Pamela Chang, associate professor of immunology in the College of Veterinary Medicine and of chemical biology in the College of Arts and Sciences. “We essentially think that DRD2 is moonlighting in the gut as a microbial metabolite sensor, and then its downstream effect is to help protect against infection.”
Samantha Scott, a postdoctoral researcher in Chang’s lab, is first author of the study. Now that Chang, Scott and colleagues have identified a specific pathway to help prevent E. coli infection, they may now begin studying the DRD2 receptor and components of its downstream pathway for therapeutic targets.
In the study, the researchers used mice infected with Citrobacter rodentium, a bacterium that closely resembles E. coli, since certain pathogenic E. coli don’t infect mice. Through experiments, the researchers identified that there was less pathogen and inflammation (a sign of an active immune system and infection) after mice were fed a tryptophan-supplemented diet. Then, to show that gut bacteria were having an effect, they gave the mice antibiotics to deplete microbes in the gut, and found that the mice were infected by C. rodentium in spite of eating a tryptophan diet, confirming that protection from tryptophan was dependent on the gut bacteria.
Then, using mass spectrometry, they ran a screen to find the chemical identities of tryptophan metabolites in a gut sample, and identified three such metabolites that were significantly increased when given a tryptophan diet. Again, based on pathogen levels and inflammation, when these three metabolites alone were fed to the mice, they had the same protective effect as giving the mice a full tryptophan diet.
Switching gears, the researchers used bioinformatics to find which proteins (and receptors) might bind to the tryptophan metabolites, and from a long list they identified three related receptors within the same family of dopamine receptors. Using a human intestinal cell line in the lab, they were able to isolate receptor DRD2 as the one that had the protective effect against infection in the presence of tryptophan metabolites.
Having identified the metabolites and the receptor, they analyzed the downstream pathway of DRD2 in human gut epithelial cells. Ultimately, they found that when the DRD2 pathway was activated, the host’s ability to produce an actin regulatory protein was compromised. C. rodentium (and E. coli) require actin to attach themselves to gut epithelial cells, where they colonize and inject virulence factors and toxins into the cells that cause symptoms. But without actin polymerization they can’t attach and the pathogen passes through and clears.
The experiments revealed a new role of dopamine receptor DRD2 in the gut that controls actin proteins and affects a previously unknown pathway for preventing a pathogenic bacteria’s ability to colonize the gut.
Synthetic reversed sequences reveal default genomic states
by Brendan R. Camellato, Ran Brosh, Hannah J. Ashe, Matthew T. Maurano, Jef D. Boeke in Nature
“Random DNA” is naturally active in the one-celled fungi yeast, while such DNA is turned off as its natural state in mammalian cells, despite their having a common ancestor a billion years ago and the same basic molecular machinery, a new study finds.
The new finding revolves around the process by which DNA genetic instructions are converted first into a related material called RNA and then into proteins that make up the body’s structures and signals. In yeast, mice, and humans, the first step in a gene’s expression, transcription, proceeds as DNA molecular “letters” (nucleobases) are read in one direction. While 80% of the human genome — the complete set of DNA in our cells — is actively decoded into RNA, less than 2% actually codes for genes that direct the building of proteins. A longstanding mystery in genomics then is what is all this non-gene-related transcription accomplishing. Is it just noise, a side effect of evolution, or does it have functions?
A research team at NYU Langone Health sought to answer the question by creating a large, synthetic gene, with its DNA code in reverse order from its natural parent. Then they put synthetic gene into yeast and mouse stem cells and watched transcription levels in each. The new study reveals that in yeast the genetic system is set so that nearly all genes are continually transcribed, while the same “default state” in the mammalian cells is that transcription is turned off.
Interestingly, say the study authors, the reverse order of the code meant that all of the mechanisms that evolved in yeast and mammalian cells to turn transcription on or off were absent because the reversed code was nonsense. Like a mirror image, however, the reversed code reflected some basic patterns seen in the natural code in terms of how often DNA letters were present, what they fell near, and how often they were repeated. With the reversed code being 100,000 molecular letters long, the team found that it randomly included many small stretches of previously unknown code that likely started transcription much more often yeast, and stopped it in mammalian cells.
“Understanding default transcription differences across species will help us to better understand what parts of the genetic code have functions, and which are accidents of evolution,” said corresponding author Jef Boeke, PhD, the Sol and Judith Bergstein Director of the Institute for Systems Genetics at NYU Langone Health. “This in turn promises to guide the engineering of yeast to make new medicines, or create new gene therapies, or even to help us find new genes buried in the vast code.”
The work lends weight to the theory that yeast’s very active transcriptional state is set so that foreign DNA, rarely injected into yeast for instance by a virus as it copies itself, is likely to get transcribed into RNA. If that RNA builds a protein with a helpful function, the code will be preserved by evolution as a new gene. Unlike a single-celled organism in yeast, which can afford risky new genes that drive faster evolution, mammalian cells, as part of bodies with millions of cooperating cells, are less free to incorporate new DNA every time a cell encounters a virus. Many regulatory mechanisms protect the delicately balanced code as it is.
The new study had to account for the size of DNA chains, with 3 billion “letters” included in the human genome, and some genes being 2 million letters long. While famous techniques enable changes to be made letter by letter, some engineering tasks are more efficient if researchers build DNA from scratch, with far-flung changes made in large swaths of pre-assembled code swapped into a cell in place of its natural counterpart. Because human genes are so complex, Boeke’s lab first developed its “genome writing” approach in yeast, but then recently adapted it to the mammalian genetic code. The study authors use yeast cells to assemble long DNA sequences in a single step, and then deliver the them into mouse embryonic stem cells.
For the current study, the research team addressed the question on how pervasive transcription is across evolution by introducing a synthetic 101 kilobase stretch of engineered DNA — the human gene hypoxanthine phosphoribosyl transferase 1 (HPRT1) in reverse coding order. They observed widespread activity of the gene in yeast despite the lack in the nonsense code of promoters, DNA snippets that evolved to signal for the start of transcription.
Further, the team identified small sequences in the reversed code, repeated stretches of adenosine and thymine building blocks, known to be recognized by transcription factors, proteins that bind to DNA to initiate transcription. Just 5 to 15 letters long, such sequences could easily occur randomly and may partly explain the very active yeast default state, the authors said.
To the contrary, the same reversed code, inserted into the genome of a mouse embryonic stem cells, did not cause widespread transcription. In this scenario, transcription was repressed even though evolved CpG dinucleotides, known to actively shut down (silence) genes, were not functional in the reversed code. The team surmises that other basic elements in the mammalian genome may restrict transcription much more so than in yeast, and perhaps by directly recruiting a protein group (the polycomb complex) known to silence genes.
“The closer we get to introducing a ‘genome’s worth’ of nonsense DNA into living cells, the better they can compare it to the actual, evolved genome,” said first author Brendan Camellato, a graduate student in Boeke’s lab. “This could lead us to a new frontier of engineered cell therapies, as the capacity to put in ever longer synthetic DNAs enables better understanding of what insertions genomes will tolerate, and perhaps the inclusion of one or more larger, complete, engineered genes.”
Machine learning to predict continuous protein properties from binary cell sorting data and map unseen sequence space
by Marshall Case, Matthew Smith, Jordan Vinh, Greg Thurber in Proceedings of the National Academy of Sciences
A protein engineering method using simple, cost-effective experiments and machine learning models can predict which proteins will be effective for a given purpose, according to a new study by University of Michigan researchers.
The method has far-reaching potential to assemble proteins and peptides for applications from industry tools to therapeutics. For instance, this technique can help speed up the development of stabilized peptides for treating diseases in ways that current medicines can’t, including improving how exclusively antibodies bind to their targets in immunotherapy.
“The rules that govern how proteins work, from sequence to structure to function, are so complicated. Contributing to the interpretability of protein engineering efforts is particularly exciting,” said Marshall Case, a doctoral graduate of chemical engineering at U-M and first author of the study.
Currently, most protein engineering experiments use complex, labor-intensive methods and expensive instruments to attain very precise data. The long process limits how much data can be acquired, and the complicated methods are challenging to learn and execute — a trade-off for precision.
“Our method has shown that for many applications, you can avoid these complicated methods,” said Case, now a computational biologist at Manifold Biotechnologies.
The updated method starts by sorting cells into two groups, known as binary sorting, based on whether they express a desired trait — like binding to fluorescent molecules — or not. Then, the cells are sequenced to get the underlying DNA codes for the proteins of interest. Machine learning algorithms then reduce the noise in the sequencing data to identify the best possible protein.
“Rather than selecting the ‘best book’ from the library, it’s like reading many books, then piecing together different pages from different stories to come up with the best book possible, even if it wasn’t in your original library,” said Greg Thurber, U-M associate professor of chemical engineering and corresponding author on the paper. “I was surprised to see the robustness of this technique using simple, binary sorting data.”
Further enhancing its accessibility, the method uses linear machine learning models, which are easier to interpret compared to models with dozens of parameters.
“Because we can learn physical rules about how the proteins are actually working, we can use linear equations to model nonlinear protein behavior and make better drugs that way,” Case said.
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