Now online! STING signaling modulation by COPII cargo recognition: Lyu et al. identify the STING-ER-exit motif and the mechanism of its recognition by the COPII vesicle cargo-binding protein SEC24C. This study reveals how STING achieves controlled rather than constitutive ER exit and how COPII cargo recognition of STING can be modulated to control STING signaling.
A new study from the Salk Institute maps how the aging brain changes at the epigenetic level — cell type by cell type.
The researchers created one of the most detailed single-cell atlases yet of the aging mouse brain, spanning 8 brain regions, 36 cell types, and hundreds of thousands of cells. They found major age-related changes in DNA methylation, chromatin structure, and gene activity, with some of the strongest changes appearing in non-neuronal cells.
This kind of work matters because it moves brain aging closer to mechanism — not just describing decline, but identifying the molecular regulatory shifts that may drive vulnerability to neurodegenerative disease.
Highlights Salk researchers create epigenetic atlas of cell type-specific changes in the aging mouse brain The atlas represents eight different brain regions and 36 different cell types, and shows clear epigenetic differences associated with different ages The new resource—available publicly on Amazon Web services—can be used to unravel age-related contributions to neurodegenerative diseases like Alzheimer’s, Parkinson’s, and ALS LA JOLLA—Neurodegenerative diseases affect more than 57 million people globally. The incidence of these diseases, from Alzheimer’s to Parkinson’s to ALS and beyond, is expected to double every 20 years. Though scientists know aging is a major risk factor for neurodegenerative diseases, the full mechanisms behind aging’s impact remain unclear.
Amebiasis is a parasitic disease caused by the microscopic protozoan Entamoeba histolytica. Infection occurs through the ingestion of cysts from contaminated water or food. Worldwide, approximately 50 million symptomatic cases are estimated annually, mainly in tropical and subtropical regions.
Fumagillin, a fungal natural product, has been studied for decades as a potential antiparasitic drug, but its more potent relative, ovalicin, was never developed. Now, a study published in the Journal of the American Chemical Society reveals why: although ovalicin is highly active against amebiasis, liver enzymes rapidly break it down in the body. Researchers used a chem-bio hybrid approach to turn that insight into metabolically stable drug candidates that worked in animal models of amebiasis, including liver infection with abscess formation.
The research team, led by scientists from the Graduate School of Bioagricultural Sciences at Nagoya University, identified the liver cytochrome P450 enzymes responsible for ovalicin breakdown, with CYP 2B1 and CYP 2C6 emerging as the main drivers. Blocking these enzymes with a chemical inhibitor significantly prolonged ovalicin survival, providing strong evidence that rapid liver metabolism limits its effectiveness.
“If it ain’t broke, don’t fix it,” goes the old adage, which Rice University professor James Chappell completely ignored in a recent Nature Communications publication. In the study, Chappell describes an innovation in plasmids, circular pieces of DNA that have been a workhorse of molecular biology research since the 1970s.
“For decades, we’ve been designing experiments around two major limitations of plasmids: fixed copy numbers and incompatibility,” said Chappell, the corresponding author on the study. “While functional, such workarounds are clunky. We created a synthetic version of a part of the plasmid called the origin of replication that allows us to modify the plasmid instead of modifying the experiment.”
Plasmids are typically put into bacterial cells, where they use the cell’s machinery to build proteins and create copies of themselves. Each plasmid generates tiny pieces of a stop signal, called a negative regulator, which binds to the origin of replication (ORI).
Quantum computing promises to transform our world in rapid, radical and revolutionary ways: solving in seconds problems that would take classical computers years, accelerating the discovery of new medicines, creating sustainable materials, optimizing complex systems, and strengthening cybersecurity. It does so using qubits, the quantum counterparts of classical bits, which can occupy multiple states simultaneously and enable a fundamentally new kind of computation.
For example, imagine 1,000 trucks need to arrive at 10,000 different locations, each, in different parts of the country. A traditional computation model would examine each of the 10 million possible routes one by one to evaluate their efficacy, but a quantum model would be able to evaluate all those millions of different routes instantaneously.
At the same time, quantum sensing is opening new frontiers in precision measurement, enabling technologies such as ultra-sensitive medical imaging and navigation systems that can detect minute changes in gravity or magnetic fields, capabilities that could allow doctors to identify diseases earlier or help vehicles navigate without GPS. UCF researchers believe the science of light, photonics, may hold the key to unlocking quantum computing’s true potential.
CRISPR is a powerful DNA-editing tool that has underpinned huge advancements in human health care in the last decade. It is a precision tool, but is not perfect, and misplaced DNA edits can compromise safety and efficacy, costing billions each year. Researchers at the MRC Laboratory of Medical Sciences (LMS), Imperial College London and the University of Sheffield have published research in Nature showing that the physical twisting of DNA plays an important role in these mistakes. Using a newly developed platform of tiny (nanometer-sized) DNA circles, called DNA minicircles, the team captured never-before-seen interactions between CRISPR and DNA, providing insights that could help eradicate errors altogether.
CRISPR-Cas9 has transformed biology by giving scientists a programmable way to cut and edit DNA. Its ever-growing impact includes groundbreaking therapies for genetic diseases such as sickle cell anemia and an increasing role in personalized cancer treatment and rapid diagnostics. But even carefully designed CRISPR systems can sometimes cut DNA sequences that were not the intended targets.
“It’s a tool that is not perfect and can introduce errors and make edits where it shouldn’t make them,” says Professor David Rueda, head of the Single Molecule Imaging group at the LMS and Chair in Molecular and Cellular Biophysics at Imperial College London. “And it’s an important problem for the industry. It’s been estimated to be $0.3 to $0.9 billions per year in industry costs, in profiling off-targets, redesigning guides and delays.”
ADAMTS7 has been repeatedly associated with coronary artery disease.
https://doi.org/10.1172/JCI187451 In this Research Article, Robert C. Bauer & team use the largest human atherosclerosis carotid artery scRNA-seq dataset and new mouse models to demonstrate that ADAMTS7 is expressed across multiple vascular cell types and contributes to atherosclerosis by promoting lipid accumulation in smooth muscle cells.
The image shows smooth muscle cells labeled with ZsGreen and counterstained with DAPI (blue) for nuclei—indicating increased foam cells from a diet-induced mouse model of atherosclerosis with Adamts7-overexpressing SMCs were from SMC origin.
1Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University, New York, New York, USA.
2Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Address correspondence to: Robert C. Bauer, Cardiometabolic Genomics Program, Division of Cardiology, Department of Medicine, Columbia University, 630 W. 168th Street, PS10-401, New York, New York 10,032, USA. Phone: 1.212.342.0952; Email: [email protected].
For decades, scientists studying brain disorders have focused almost exclusively on proteins and the genes encoding them. Now, research from Thomas Jefferson University’s Computational Medicine Center suggests that several classes of small regulatory molecules, fittingly known as small RNAs, may play a much larger role in schizophrenia and bipolar disorder, and in a healthy brain, than previously thought.
In a study recently published in Translational Psychiatry, a team led by Isidore Rigoutsos, Ph.D. took a comprehensive look at small RNAs in brain samples from people with schizophrenia, bipolar disorder and individuals without psychiatric illness. Their goal was to find out what kind of small RNAs are active in the brain, and whether their levels change in disease.
“Little attention had been paid to small RNAs in these disorders,” says Dr. Rigoutsos, “even though small RNAs help control numerous processes by modulating the abundance of genes.”
Consciousness, and the ways in which it can become impaired after certain brain injuries, are not well understood, making disorders of consciousness (DOC), like coma, vegetative states and minimally conscious states difficult to treat. But a new study, published in Nature Neuroscience, indicates that AI might be able to help researchers gain some traction with this problem. The research team involved in the new study has developed an adversarial AI framework to help them determine what exactly is going on in states of reduced consciousness and how to approach a solution.
To better understand the mechanisms behind impaired consciousness, the researchers developed two types of AI models and had them play a kind of game where one model determined different levels of consciousness based on EEGs simulated to look like those of real unconscious and conscious brains. The AI agents guessing consciousness levels, called deep convolutional neural networks (DCNNs), were first trained on 680,000 ten-second recordings of brain activity from conscious and unconscious humans, monkeys, bats and rats to detect which neural signals related to differing levels of consciousness. The AI showing EEG data was a biologically plausible simulation of the human brain.
“To decode consciousness from these signals, we trained three separate DCNNs, each specialized for a different brain region, to output a continuous score from 0 (unconscious) to 1 (fully conscious): a cortical consciousness detector (ctx-DCNN), a thalamic consciousness detector (th-DCNN) and a pallidal consciousness detector (pal-DCNN). The ctx-DCNN was trained on continuous consciousness levels derived from clinical scales (GCS and CRS-R), enabling it to recognize graded states of consciousness,” the study authors explain.
Researchers from Brown University and Mass General Brigham have developed an implantable brain-computer interface that allowed two people with paralysis — one with ALS and one with a spinal cord injury — to communicate through rapid, accurate typing. The system uses microelectrode sensors in the motor cortex, maps letters to attempted finger movements on a QWERTY keyboard, and decodes those neural signals into text.
In the study, one participant reached a top speed of 110 characters per minute (about 22 words per minute) with a 1.6% word error rate, and both participants were able to use the system from home after calibration with as few as 30 sentences. The results were published in Nature Neuroscience.
This is the kind of neurotechnology that starts to close the gap between thought and communication.
Implantable device research from the BrainGate clinical trial enables communication through rapid typing for a patient with ALS and a patient with a spinal cord injury.