Lifeboat Foundation

Pathogen encounter can result in epigenetic remodeling that shapes disease caused by heterologous pathogens.

The therapeutic potential of antigen-independent innate immune memory (IIM) is of particular relevance in the context of respiratory viruses with pandemic potential. Lercher et al. find that antiviral IIM in alveolar macrophages following SARS-CoV-2 infection ameliorates disease caused by a secondary unrelated pathogen, influenza A virus.

U.S. researchers developed CheekAge, a tool that reliably estimates mortality risk.

Researchers in the United States have created a next-generation tool named CheekAge, which uses methylation patterns found in easily obtainable cheek cells.

In a groundbreaking discovery, the team has demonstrated that CheekAge can reliably estimate mortality risk, even when epigenetic data from different tissues are utilized for analysis.

Continue reading “US scientist reveal mouth swab that can gauge your risk of death” »

A powerful new analytical tool offers a closer look at how tumor cells “shape-shift” to become more aggressive and untreatable, as shown in a study from researchers at Weill Cornell Medicine and the New York Genome Center.

A tumor cell shape-shifts by changing its cell type or state, thus altering its basic pattern of activity and perhaps even its appearance. This changeability or “plasticity” is a characteristic of cancer that leads to diverse tumor-cell populations and ultimately the emergence of cell types enabling treatment resistance and metastatic spread.

The new tool, described Sept. 24 in a paper in Nature Genetics, can be used to quantify this plasticity in samples of tumor cells. The researchers demonstrated it with analyses of tumor samples from animal models and human patients, identifying, for example, a key transitional cell state in glioblastoma, the most common form of brain cancer.

The FDA has approved a new targeted drug specifically for brain tumors called low-grade gliomas. The drug, vorasidenib, was shown in clinical trials to delay progression of low-grade gliomas that had mutations in the IDH1 or IDH2 genes.

“Although there have been other targeted therapies for the treatment of brain tumors with the IDH mutation, [this one] has been one of the most successful in survival prolongation of brain tumor patients,” said Darell Bigner, MD, PhD, the E. L. and Lucille F. Jones Cancer Distinguished Research Professor and founding director of the Preston Robert Tisch Brain Tumor Center at Duke.

In clinical trials, progression-free survival was estimated to be 27.7 months for people in the vorasidenib group versus 11.1 months for those in the placebo group.

Spider silk is one of the strongest materials on Earth, technically stronger than steel for a material of its size. However, it’s tough to obtain—spiders are too territorial (and cannibalistic) to breed them like silkworms, leading scientists to turn to artificial options.

Teaching microbes to produce the spider silk proteins through genetic engineering is one such option, but this has proved challenging because the proteins tend to stick together, reducing the silk’s yield. So, Bingbing Gao and colleagues wanted to modify the natural protein sequence to design an easily spinnable, yet still stable, spider silk using microbes.

The team first used these microbes to produce the silk proteins, adding extra peptides as well. The new peptides, following a pattern found in the protein sequence of amyloid polypeptides, helped the artificial silk proteins form an orderly structure when folded and prevented them from sticking together in solution, increasing their yield.

Koo and his team tested CREME on another AI-powered DNN genome analysis tool called Enformer. They wanted to know how Enformer’s algorithm makes predictions about the genome. Koo says questions like that are central to his work.

“We have these big, powerful models,” Koo said. “They’re quite compelling at taking DNA sequences and predicting gene expression. But we don’t really have any good ways of trying to understand what these models are learning. Presumably, they’re making accurate predictions because they’ve learned a lot of the rules about gene regulation, but we don’t actually know what their predictions are based off of.”

With CREME, Koo’s team uncovered a series of genetic rules that Enformer learned while analyzing the genome. That insight may one day prove invaluable for drug discovery. The investigators stated, “CREME provides a powerful toolkit for translating the predictions of genomic DNNs into mechanistic insights of gene regulation … Applying CREME to Enformer, a state-of-the-art DNN, we identify cis-regulatory elements that enhance or silence gene expression and characterize their complex interactions.” Koo added, “Understanding the rules of gene regulation gives you more options for tuning gene expression levels in precise and predictable ways.”

Summary: Researchers found that mutations in the Sox3 gene cause hypopituitarism, a condition where the pituitary gland produces insufficient hormones, leading to growth issues and infertility. In a study on mice, they discovered that Sox3 mutations affect brain cells called NG2 glia, which are essential for hormone production.

Treating the mice with aspirin or altering their gut microbiome restored NG2 glia levels and reversed hypopituitarism. These findings suggest that both aspirin and gut bacteria could be explored as potential treatments for people with Sox3 mutations or other hormone-related disorders.

Researchers have developed a groundbreaking system that uses bacteria to mimic the problem-solving capabilities of artificial neural networks.

Cell-based biocomputing is a novel technique that uses cellular processes to perform computations. Such micron-scale biocomputers could overcome many of the energy, cost and technological limitations of conventional microprocessor-based computers, but the technology is still very much in its infancy. One of the key challenges is the creation of cell-based systems that can solve complex computational problems.

Now a research team from the Saha Institute of Nuclear Physics in India has used genetically modified bacteria to create a cell-based biocomputer with problem-solving capabilities. The researchers created 14 engineered bacterial cells, each of which functioned as a modular and configurable system. They demonstrated that by mixing and matching appropriate modules, the resulting multicellular system could solve nine yes/no computational decision problems and one optimization problem.

Continue reading “Genetically engineered bacteria solve computational problems” »