Natural killer (NK) cells target infected and oncogenic cells, but are difficult to work with in vitro. Discover novel approaches to producing genetically modified NK cells for cell therapy.
Researchers at Trinity College Dublin have recovered remarkably preserved microbiomes from two teeth dating back 4,000 years, found in an Irish limestone cave. Genetic analyses of these microbiomes reveal major changes in the oral microenvironment from the Bronze Age to today. The teeth both belonged to the same male individual and also provided a snapshot of his oral health.
A new study has revealed that the size of human brains is getting larger, which means increased brain reserve and decreased chances of developing dementia. The researchers at UC Davis Health reached the conclusion by comparing the size of the brains of people born in the 1930s with those of people born in the 1970s. They noticed that the latter had 6.6 per cent larger brains. The study was published in JAMA Neurology.
“The decade someone is born appears to impact brain size and potentially long-term brain health,” said Charles DeCarli, first author of the study.
He further adds that genetics may also play a major role in determining the size of the brain. “Genetics plays a major role in determining brain size, but our findings indicate external influences — such as health, social, cultural and educational factors — may also play a role,” he said.
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In a recent study published in the journal Nature Aging, researchers assessed the added predictive value of integrating polygenic risk scores (PRSs) and gut microbiome scores with conventional risk factors for common diseases in a long-term cohort study.
Analysis: Integration of polygenic and gut metagenomic risk prediction for common diseases. Image Credit: remotevfx.com / Shutterstock.
To what extent are exceptional human achievements influenced by genetic factors? This question, dating back to the early days of human genetics, seems to be easier to address today as modern molecular methods make it possible to analyze DNA of individuals throughout history. But how reliable are the answers in this day and age?
PHILADELPHIA — Scientists at the University of Pennsylvania’s Perelman School of Medicine have developed a new method to create human artificial chromosomes (HACs) that could revolutionize gene therapy and other biotechnology applications. The study, published in Science, describes an approach that efficiently forms single-copy HACs, bypassing a common hurdle that has hindered progress in this field for decades.
Artificial chromosomes are lab-made structures designed to mimic the function of natural chromosomes, the packaged bundles of DNA found in the cells of humans and other organisms. These synthetic constructs have the potential to serve as vehicles for delivering therapeutic genes or as tools for studying chromosome biology. However, previous attempts to create HACs have been plagued by a major issue: the DNA segments used to build them often link together in unpredictable ways, forming long, tangled chains with rearranged sequences.
The Penn Medicine team, led by Dr. Ben Black, sought to overcome this challenge by completely overhauling the approach to HAC design and delivery. “The HAC we built is very attractive for eventual deployment in biotechnology applications, for instance, where large-scale genetic engineering of cells is desired,” Dr. Black explains in a media release. “A bonus is that they exist alongside natural chromosomes without having to alter the natural chromosomes in the cell.”
Ubiquitous Potential
While many gene-editing therapies are focused on fatal genetic diseases, epigenetic editing’s safety profile may enable the treatment of more common diseases. The fact that no underlying changes are made to the DNA sequence “offers some additional safety assurances for this approach compared to some others where the risk/benefit [ratio] needs to be maybe a little different before you would employ those technologies,” Kane told BioSpace.
Additionally, because most common diseases are not driven by genetic mutations, epigenetic editing may be a better fit. “Most of those diseases are driven from expression levels being at an unhealthy level,” Kane said. “That is something that a tool like epi[genetic] editing is uniquely well-suited to address.”
In support of a major collaborative project to store massive amounts of data in DNA molecules, a Los Alamos National Laboratory–led team has developed a key enabling technology that translates digital binary files into the four-letter genetic alphabet needed for molecular storage.
“Our software, the Adaptive DNA Storage Codec (ADS Codex), translates data files from what a computer understands into what biology understands,” said Latchesar Ionkov, a computer scientist at Los Alamos and principal investigator on the project. “It’s like translating from English to Chinese, only harder.”
DNA offers a compact way to store huge amounts of data cost-effectively. Los Alamos National Laboratory has developed ADS Codex to translate the 0s and 1s of digital computer files into the four-letter code of DNA.
Acute myeloid leukemia (AML) is a rare and aggressive hematologic malignancy. AML progresses rapidly and is indicated by an excess of immature white blood cells. It is caused by high mutational burden over the span of a person’s life. One signature mutated gene includes the tumor suppressor gene TP53. Normally, TP53 helps make protein to stop oncogenesis or the formation of tumors. However, mutated TP53 loses that function and commonly results in AML. Unfortunately, those that have a TP53 mutation have an extremely aggressive tumor that is resistant to conventional chemotherapy drugs and results in poor prognosis. Other standard treatments include stem-cells transplants, and sometimes targeted drugs such as intracellular pathway inhibitors. Although many treatments are routine and help the patient reduce symptoms, there is no cure. Extensive research is currently being done by researchers and physicians to identify new approaches for AML treatment.
One novel therapy used in other hematologic malignancies includes chimeric antigen receptor (CAR)-T cell therapy. This therapy takes immune T cells (responsible for lysing or kill infections) from the patient or a donor and engineers them to target the tumor. Normally, these T cells would not recognize tumor growth, therefore, the engineered CAR-T cells are programmed to elicit an immune response and recognize surface markers on the tumor to lyse it. This therapy has been successful in other leukemias such as B-cell acute leukemia, and researchers are working to overcome treatment resistant AML using the same approach.
A recent article in EMBO Molecular Medicine, by Drs. Markus Manz, Stephen Boettcher and others, demonstrate that TP53-mutated AML is resistant to CAR-T cell therapy as a single agent, but can be overcome through combination therapy. Manz and Boettcher are principal investigators from the University of Zurich and the Department of Medical Oncology and Hematology at the University Hospital Zurich (USZ) and focus on mechanisms surrounding hematological diseases. The Zurich team first reported why TP53-mutated AML is resistant to CAR-T cell therapy. Using various models, it was noted that the engineered T cells quickly become ‘exhausted’ or inactive due to overstimulation or surrounding stimuli. The team further studied the underlying mechanism in this disease by concluding that TP53-deficient cells caused resistance through several metabolic pathways. Moreover, these pathways including the mevalonate and Wnt pathways were identified to improve therapeutic efficacy.
Stanford and McMaster University researchers created an artificial intelligence (AI) model to design molecules that inhibit the growth of Acinetobacter baumannii, a common drug-resistant bacteria. They synthesized and validated six structurally novel molecules that demonstrated antibacterial activity against A. baumannii and other phylogenetically diverse bacterial pathogens. This study represents a significant step toward the practical application of generative AI approaches for antibiotic discovery and drug discovery in general.
The research article, “Generative AI for designing and validating easily synthesizable and structurally novel antibiotics,” was published in Nature Machine Intelligence.
Among the most critical issues in contemporary medicine is the worldwide spread of factors contributing to antibiotic resistance. In 2019, drug-resistant infections were responsible for an estimated 4.95 million deaths. As new antibiotics are being developed slower than the spread of antimicrobial resistance determinants, this figure is expected to reach 10 million annually by 2050.
