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Category: bioengineering

Two-step approach creates more sustainable protein nanostructures for advanced sensing and therapeutics

Gas vesicles are among the largest known protein nanostructures produced and assembled inside microbial cells. These hollow, air-filled cylindrical nanostructures found in certain aquatic microbes have drawn increasing interest from scientists due to their potential for practical applications, including as part of novel diagnostic and therapeutic tools. However, producing gas vesicles is a difficult task for cells in the lab, hindering the development of applications.

In a study recently published in Nature Communications, a team of researchers led by Rice University bioengineer George Lu reports the development of a new genetic regulatory system to improve cell viability during the production of gas vesicles.

“In the past few years, studies have shown that gas vesicles’ ability to reflect sound makes them useful as unique and versatile acoustic reporter systems for biomedical research and clinical applications,” said Lu, an assistant professor in the Department of Bioengineering at Rice’s George R. Brown School of Engineering and Computing.

Epistasis study uncovers genetic interactions linked to heart disease

Euan Ashley’s lab explores the intricate interactions of gene variants. Tiny “typos,” or genetic mutations, can sneak into segments of DNA. Many of these are harmless, but some can cause health problems. Two or more genes can team up and change the outcome of a physical or molecular trait. This phenomenon, known as epistasis, occurs through complex interactions between genes that are functionally related—such as those that support protein creation.

Identifying these group dynamics provides crucial clues to how genetic diseases manifest and should be treated. But they’re not easily detected and often fly under the radar.

To help root out these connections, Ashley, MB ChB, DPhil, professor of genetics and of biomedical data science, and a team of scientists, including co-corresponding author Bin Yu, Ph.D., a professor of statistics and of electrical engineering and computer sciences at the University of California, Berkeley, have developed computational techniques to identify and understand the hidden ways epistasis influences inherited diseases.

The Successor to CRISPR May Be Even More World Changing

When Feng Zhang was in his early 30s, he used a set of genes found in bacteria called CRISPR to pioneer a new kind of gene editing tool in human cells. Today, the MIT biochemist is studying a different set of microbial genes called TIGR. And they may be the key to developing CRISPR’s successor. For this SciShow Field Trips video, we traveled to Zhang’s lab to learn about what may be the next generation of gene editing.

Higher Prevalence of Coronary Microvascular Dysfunction in Patients With HFpEF Without Obesity

Advanced psc-based strategies for leukodystrophy therapy👇

✅Pluripotent stem cell (PSC)–based technologies are opening new avenues for the treatment of leukodystrophies by combining cell replacement, gene correction, disease modeling, and drug discovery within a unified framework.

✅One major approach focuses on the development of off-the-shelf PSC-derived neural progenitor cells (NPCs). By precisely editing immune-related genes, PSCs can be engineered to evade immune rejection. Strategies include knocking out core components of HLA class I and II pathways while introducing protective molecules such as HLA-E, or selectively removing highly immunogenic HLA alleles. These modifications allow the generation of universal donor NPCs that are resistant to T cell– and NK cell–mediated killing.

✅Autologous induced pluripotent stem cell (iPSC) therapy represents a personalized treatment strategy. Patient-derived somatic cells are reprogrammed into iPSCs, followed by genetic correction of disease-causing mutations using viral vectors or CRISPR/Cas9-based editing. Corrected iPSCs are then differentiated into neural stem cells (NSCs), NPCs, or oligodendrocyte progenitor cells (OPCs) and transplanted back into the same patient, minimizing immune complications.

✅Beyond therapy, iPSC-based disease models provide powerful tools to study leukodystrophy pathogenesis. Disease-specific iPSCs recapitulate key cellular phenotypes such as impaired differentiation, lysosomal dysfunction, oxidative stress, and apoptosis. These models enable direct investigation of early developmental defects that are difficult to access in patients.

✅Corrected iPSCs restore normal cellular phenotypes, allowing direct comparison between diseased and healthy isogenic cells. This approach clarifies causal mechanisms and validates gene correction strategies at the cellular level, supporting precision medicine.

✅iPSC-derived neural systems also support advanced drug discovery platforms. By generating complex neural cultures or myelinating organoids (“myelinoids”), researchers can model neuron–glia interactions and myelination in vitro. Coupled with immunofluorescence, transcriptomics, and high-throughput screening, these systems enable systematic identification of small molecules that promote myelination or correct metabolic defects.

Continue reading “Higher Prevalence of Coronary Microvascular Dysfunction in Patients With HFpEF Without Obesity” | >

Immunoglobulin G’s overlooked hinge turns out to be a structural control hub

The lower hinge of immunoglobulin G (IgG), an overlooked part of the antibody, acts as a structural and functional control hub, according to a study by researchers at Science Tokyo. Deleting a single amino acid in this region transforms a full-length antibody into a stable half-IgG1 molecule with altered immune activity.

The findings provide a blueprint for engineering next-generation antibody therapies with precisely tailored immune effects for treating diseases such as cancer and autoimmune diseases.

Antibodies are Y-shaped proteins that help the immune system recognize and eliminate foreign threats such as bacteria and viruses. The dominant antibody in the bloodstream is immunoglobulin G (IgG), which accounts for about 75% of circulating antibodies. Its structure is divided into two main functional units connected by a flexible hinge that must work together seamlessly.

Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic mutation detection in cancer diagnostics and RNA-based genomic studies.

The pioneering research team, led by Professor Ruibang Luo from the School of Computing and Data Science, Faculty of Engineering, has unveiled two groundbreaking deep-learning algorithms—ClairS-TO and Clair3-RNA—set to revolutionize genetic analysis in both clinical and research settings.

Leveraging long-read sequencing technologies, these tools significantly improve the accuracy of detecting genetic mutations in complex samples, opening new horizons for precision medicine and genomic discovery. Both research articles have been published in Nature Communications.

A protein ‘tape recorder’ enables scientists to measure and decode cellular processes at scale and over time

Unraveling the mysteries of how biological organisms function begins with understanding the molecular interactions within and across large cell populations. A revolutionary new tool, developed at the University of Michigan, acts as a sort of tape recorder produced and maintained by the cell itself, enabling scientists to rewind back in time and view interactions on a large scale and over long periods of time.

Developed in the lab of Changyang Linghu, Ph.D., Assistant Professor of Cell and Developmental Biology and Biomedical Engineering and Principal Investigator in Michigan Neuroscience Institute, the so-called CytoTape is a flexible, thread-like intracellular protein fiber, designed with the help of AI to act as a tape recorder for large-scale measurement of cellular activities.

The research appears in the journal Nature.

Complement C5 Inhibitor Ameliorates a Case of Dysferlinopathy

Complement inhibition showed promising clinical improvement in this single case of dysferlinopathy.

Dysferlinopathy is a rare autosomal recessively inherited myopathy, presenting as several phenotypes, including a proximal weakness dominant limb-girdle muscular dystrophy R2 phenotype and a distal weakness dominant Miyoshi distal myopathy phenotype.1,2 Muscle weakness usually emerges in young adulthood, followed by a progressive motor decline over the first decade, which tends to be more rapid in individuals with earlier onset.3 Dysferlinopathy is caused by pathogenic variants of the DYSF gene that impair function of dysferlin, a protein that cooperates with others to repair membranes and restore skeletal muscle integrity after injury.4

To date, no effective treatment for dysferlinopathy has been clinically validated. Promising approaches, including exon skipping and gene editing targeting the DYSF gene, as well as myoblast transplantation, are still under investigation in preclinical models.5 Although dysferlinopathy often presents with inflammatory features on muscle pathology and is prone to misdiagnosis as myositis, it is characterized by the absence of focal MHC-I expression and complement C5b-9 deposition on nonnecrotic sarcolemma, which help distinguish it from other muscular dystrophies and inflammatory myopathies.6,7 Specially, complement C3 gene knockout in dysferlin-deficient mice has been demonstrated being able to reverse muscle pathology and improve motor function in the previous animal research.

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