Breakthroughs in genetically altering cephalopods pave way for new studies of perception, brain evolution, and more
Category: genetics
Super Fungi Survive Extreme Mars-like Environments
People have long been intrigued by the possibility of life beyond Earth and how it might endure in extraterrestrial environments. There is no confirmed evidence of extraterrestrial life, not even on the planetary neighbor Mars. However, an international project led by KAUST’s Alexandre Rosado demonstrates how a particular type of black fungus, known to tolerate highly acidic conditions on Earth, could survive and even thrive in Mars-like environments [1].
“With the current advancement of space missions to Mars, both orbital and robotic, we are closer than ever to answering whether there was, or is, biological activity on the Red Planet,” says Alef Santos, who worked on the project as a visiting Ph.D. student in Rosado’s lab, together with Junia Schultz and co-workers. “Understanding the limits of life in extreme environments on Earth is a crucial step toward interpreting biosignatures beyond our planet. Extremophilic microorganisms that survive and thrive in hostile environments offer valuable natural models for how extraterrestrial life might adapt.”
The team chooses to study the black fungus Rhinocladiella similis based on genomic analyses and previous experimental evidence suggesting that the fungus possesses a robust genetic toolkit capable of withstanding multiple environmental stressors. They are particularly interested in how R. similis might survive in perchlorate salt brines, which are hypothesized to exist intermittently on Mars, along with other environmental factors, including intense UV-C radiation.
Researchers Uncover a Hidden Molecular Machine Parasites Need To Survive
Researchers have visualized two key stages of RNA processing in parasites that cause diseases such as sleeping sickness, Chagas’ disease, and leishmaniasis.
For nearly 40 years, scientists have known that trypanosomatid parasites depend on an unusual system for processing RNA. Now researchers have captured that machinery at near-atomic resolution, showing how its components assemble and operate during a reaction the parasites need to survive.
The study, conducted by researchers at the University of Liège and Rockefeller University, reconstructed the three-dimensional architecture of the trans-spliceosome, a massive molecular machine that prepares genetic messages for use inside trypanosomatid cells. The structures also identify features that differ from the RNA processing machinery found in humans, providing a potential starting point for developing drugs that interfere selectively with the parasites.
Cancer cells erase sections of Y chromosome to trigger tumor growth in men
A new study found that cancer cells selectively chip away gene-rich sections of the Y chromosome, triggering ripples that regulate tumor growth.
Co-led by University of Arizona Cancer Center physician-scientist Dr. Dan Theodorescu, the paper, “Recurrent deletions and regulatory disruption of the Y chromosome in cancer,” was published in the journal Communications Biology.
Each cell in men’s bodies usually contains one X and one Y chromosome. The Y chromosome has long been known to determine male sex, but researchers are learning its genes also play other roles in cells throughout the body. “Loss of Y” is a common genetic change in aging men, often found in blood cells. Y loss also occurs in cancer cells themselves, which is the focus of this study.
Autonomous Lipid Nanoparticle Engineering
Researchers at the Massachusetts Institute of Technology have developed an automated production system for lipid nanoparticles (LNPs) that offers unprecedented control over their size and shape, significantly accelerating the design of targeted RNA and DNA therapeutics. While LNPs serve as crucial delivery vehicles for mRNA vaccines and other nucleic acids, traditional manufacturing relies on time-consuming trial-and-error and cannot reliably control particle dimensions, which dictate their behavior and targeted organs in the body. Building on a previously developed two-step fluid mixing technique, the newly autonomous platform integrates real-time dynamic light scattering to continuously monitor particle formation and adjust parameters on the fly. By leveraging data gathered from this automated system, the team also trained a machine-learning model capable of predicting the exact manufacturing conditions required to engineer LNPs with specific sizes and non-spherical shapes. This streamlined, data-driven approach eliminates previous manufacturing guesswork, providing a powerful tool to rapidly engineer customized delivery vehicles for next-generation genetic therapies.
Lipid nanoparticles (LNPs) are the leading vehicles for encapsulating and delivering nucleic acid therapeutics. Yet, their process development remains labor-intensive and empirical, constrained by coupled quality attributes and limited mechanistic insight. We present an autonomous, pilot-scale platform for accelerating LNP process development by identifying critical process parameters (CPPs) that produce LNPs with target size attributes. The platform combines a size-control production method with inline dynamic light scattering (DLS) for real-time feedback, enabling closed-loop experimentation and accelerated optimization. With built-in automated design of experiments, dynamic parameter sweeps, and Bayesian optimization, the platform enables rapid, data-rich exploration of complex design spaces.
RNA-Based Gene Editing Tool Combats Diseases With Multiple Mutations
Investigators from Mass General Brigham and Beth Israel Deaconess Medical Center have developed STITCHR, a new gene editing tool that can insert therapeutic genes into specific locations without causing unwanted mutations. The system can be formulated completely as RNA, dramatically simplifying delivery logistics compared to traditional systems that use both RNA and DNA. By inserting an entire gene, the tool offers a one-and-done approach that overcomes hurdles from CRISPR gene editing technology—which is programmed to correct individual mutations—offering a promising step forward for gene therapy. Results are published in Nature.
“CRISPR has revolutionized how we think about gene editing, but it has limitations. CRISPR can’t target every location in the genome, and it can’t fix the thousands of mutations present in diseases like cystic fibrosis,” said co-senior author Omar Abudayyeh, PhD, an investigator at the Gene and Cell Therapy Institute (GCTI) at Mass General Brigham and Engineering in Medicine Division in the Department of Medicine at Brigham and Women’s Hospital (BWH). “When we started our lab, one of the big things we wanted to figure out was how to insert large pieces of genes, or even entire genes, to replace faulty ones. This would allow us to target every mutation for a disease with a single gene editing construct.”
STITCHR harnesses the power of enzymes from genetic elements called retrotransposons, which are found in all eukaryotic cells, including animals, fungi, and plants. They are often called “jumping genes” for their tendency to move around and insert themselves into the genome. The researchers recognized how the copy-and-paste mechanism they use to move could be repurposed to edit genes at specific locations.
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An RNA Language Model trained on sequence alone reveals the structural logic of Internal Ribosome Entry Sites
Teaching a computer to read rna’s hidden blueprint.
Every living thing relies on tiny molecular machines called ribosomes to build proteins — the workhorses of our cells. Normally, a ribosome latches onto a strand of RNA and starts reading it like a recipe. But some viruses, including the picornaviruses (the family behind the common cold and polio), have evolved a clever workaround. Instead of using the standard starting signal, they use special RNA structures called Internal Ribosome Entry Sites, or IRESes, to hijack our ribosomes and force them to produce viral proteins.
The problem is that these IRES structures are enormous, wildly varied between viruses, and notoriously difficult to map. Scientists have only been able to determine the detailed structures of a handful of them.
A new study tackles this challenge by training an RNA “language model” — a type of artificial intelligence similar to the models behind modern chatbots, but designed to read the genetic language of RNA. The model, named Albatross, learns only from RNA sequences, not structures, yet it can predict how these molecules fold into functional shapes with remarkable accuracy.
To test it, the team gathered real-world chemical probing data from 96 full-length IRESes taken from a diverse range of viruses. Albatross dramatically outperformed existing prediction tools, achieving 80% precision compared to 47%. The researchers then used Albatross to analyze a massive collection of 75,000 IRES structures, uncovering a previously unknown structural category (dubbed “Type II”) that they confirmed in the lab.
But what surprised the researchers most wasn’t the accuracy — it was what the model taught itself along the way. Albatross was never told anything about thermodynamics, the physical rules that govern how RNA folds. It was given only sequences. Yet it spontaneously learned to recognize alternative structures of riboswitches — RNA elements that change shape to control gene activity — and even critical loop-to-loop contacts that hold RNA molecules in precise three-dimensional arrangements.
“This is totally brain shattering,” said Dr. Silvi Rouskin, the study’s advising author (Harvard Medical School). “An LLM that was never told what thermodynamics is, was just given sequences, picks up alternative structures of riboswitches and critical tertiary loop-loop contacts.”
In other words, the model appears to have rediscovered the physics of RNA from raw data alone — much as a language model seems to pick up grammar without ever being taught linguistics. The team is now applying it to human biology, with early hints of previously unknown human riboswitches on the horizon.
