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Biochemistry

“Tailoring Gene Editing with Machine Learning: A Breakthrough in CRISPR-Cas9 Enzyme Engineering”

Genome editing has advanced at a rapid pace with promising results for treating genetic conditions — but there is always room for improvement. A new paper showcases the power of scalable protein engineering combined with machine learning to boost progress in the field of gene and cell therapy. In their study, authors developed a machine learning algorithm — known as PAMmla — that can predict the properties of about 64 million genome editing enzymes. The work could help reduce off-target effects and improve editing safety, enhance editing efficiency, and enable researchers to predict customized enzymes for new therapeutic targets.

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The article “Tailoring Gene Editing with Machine Learning: A Breakthrough in CRISPR-Cas9 Enzyme Engineering” discusses how researchers from Mass General Brigham have harnessed machine learning to revolutionize the field of genome editing. By developing a machine learning algorithm called PAMmla, they’ve predicted the properties of over 64 million genome editing enzymes, significantly expanding our repertoire of effective and safe CRISPR-Cas9 enzymes.

CRISPR-Cas9 enzymes are powerful tools for editing genes, but their traditional application can have off-target effects, modifying DNA at unintended sites in the genome. The researchers’ novel approach uses machine learning to better predict and tailor these enzymes, ensuring greater specificity and accuracy in gene editing. This scalable solution has the potential to transform our understanding of genetic conditions and unlock new therapeutic targets.

The study showcases the power of PAMmla by demonstrating its utility in precise editing disease-causing sequences in primary human cells and mice. The researchers have also made a web tool available for others to use this model, enabling the community to create customized enzymes tailored for specific research and therapeutic applications.

Ben Kleinstiver, PhD, and Rachel A. Silverstein, PhD candidate, are leading authors on this study, highlighting the potential of machine learning in expanding our capabilities in gene editing. This breakthrough has significant implications for the field, offering a new era of precision and safety in genome editing technology.

Biochemistry

Unveiling Molecular Motion: A Breakthrough in Synthetic Biology and Soft Matter Physics

Scientists have uncovered a previously unknown type of molecular motion inside DNA-based droplets: instead of spreading randomly, guest molecules advance in an organized wave. This surprising discovery opens the door to understanding how cells might organize internal processes without membranes. Using customizable DNA condensates as experimental models, the team showed how molecular waves emerge through precise DNA interactions. These insights could not only transform our grasp of cellular signaling but may even lay groundwork for treating neurodegenerative diseases by influencing how molecules behave inside aging cells.

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In a groundbreaking discovery, researchers from Johannes Gutenberg University Mainz, the Max Planck Institute for Polymer Research, and the University of Texas at Austin have uncovered a form of molecular motion that defies conventional understanding. When guest molecules penetrate droplets of DNA polymers, they don’t diffuse haphazardly; instead, they propagate through them in a clearly-defined frontal wave.

“This is an effect we didn’t expect at all,” says Weixiang Chen, a leading researcher from the Department of Chemistry at JGU. The findings have been published in Nature Nanotechnology, and the implications are significant.

In contrast to traditional diffusion models, where molecules spread out randomly, the observed behavior of guest molecules in DNA droplets is structured and controlled. This takes the form of a wave of molecules or a mobile boundary, as explained by Professor Andreas Walther from JGU’s Department of Chemistry, who led the research project.

The researchers used thousands of individual strands of DNA to create droplets, known as biomolecular condensates. These structures can be precisely determined and have counterparts in biological cells, which employ similar condensates to arrange complex biochemical processes without membranes.

“Our synthetic droplets represent an excellent model system for simulating natural processes and improving our understanding of them,” emphasizes Chen.

The intriguing motion of guest molecules is attributed to the way that added DNA and the DNA present in the droplets combine on the basis of the key-and-lock principle. This results in swollen, dynamic states developing locally, driven by chemical binding, material conversion, and programmable DNA interactions.

The findings are not only fundamental to our understanding of soft matter physics but also relevant to improving our knowledge of cellular processes. “This might be one of the missing pieces of the puzzle that, once assembled, will reveal to us how cells regulate signals and organize processes on the molecular level,” states Walther.

This new insight could contribute to the treatment of neurodegenerative disorders, where proteins migrate from cell nuclei into the cytoplasm, forming condensates. As these age, they transform from a dynamic to a more stable state and build problematic fibrils. “It is quite conceivable that we may be able to find a way of influencing these aging processes with the aid of our new insights,” concludes Walther.

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Biochemistry

A Game-Changing mRNA Vaccine that’s More Effective and Less Costly to Develop

A new type of mRNA vaccine is more scalable and adaptable to continuously evolving viruses such as SARS-CoV-2 and H5N1, according to a new study.

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A team of researchers from the University of Pittsburgh School of Public Health and Pennsylvania State University has made a groundbreaking discovery in the field of vaccine development. They have created a new type of mRNA vaccine that is not only more effective but also less costly to develop, making it a game-changer in the fight against infectious diseases.

The current mRNA vaccines, such as those used to prevent COVID-19, have two significant challenges: they require a high amount of mRNA to produce and are constantly evolving due to the changing nature of viruses like SARS-CoV-2 and H5N1. The researchers addressed these challenges by creating a proof-of-concept COVID-19 vaccine using what’s known as a “trans-amplifying” mRNA platform.

In this approach, the mRNA is separated into two fragments: the antigen sequence and the replicase sequence. The latter can be produced in advance, saving crucial time in the event of a new vaccine needing to be developed urgently and produced at scale. Additionally, the researchers analyzed the spike-protein sequences of all known variants of SARS-CoV-2 for commonalities, rendering what’s known as a “consensus spike protein” as the basis for the vaccine’s antigen.

The results are promising: in mice, the vaccine induced a robust immune response against many strains of SARS-CoV-2. This has the potential for more lasting immunity that would not require updating, because the vaccine has the potential to provide broad protection. Additionally, this format requires an mRNA dose 40 times less than conventional vaccines, so this new approach significantly reduces the overall cost of the vaccine.

The lessons learned from this study could inform more efficient vaccine development for other constantly evolving RNA viruses with pandemic potential, such as bird flu. The researchers hope to apply the principles of this lower-cost, broad-protection antigen design to pressing challenges like bird flu, making it a crucial step in preparing for future pandemics.

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Aerospace

Unveiling the Molecular Link Between Air Pollution and Pregnancy Risks: A Groundbreaking Study

A new study found exposure to specific tiny particles in air pollution during pregnancy are associated with increased risk of various negative birth outcomes.

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The air we breathe has long been a concern for public health, but a recent study by Emory University researchers sheds light on a specific and alarming link between air pollution and pregnancy risks. Published in Environmental Science & Technology, the research reveals that exposure to tiny particles in air pollution during pregnancy can disrupt maternal metabolism, leading to increased risk of various negative birth outcomes.

The study analyzed blood samples from 330 pregnant women in the Atlanta metropolitan area, providing a detailed insight into how ambient fine particulate matter (PM2.5) affects the metabolism of pregnant women and contributes to increased risks of preterm and early term births. This pioneering work marks the first time researchers have been able to investigate the specific fine particles responsible for these adverse outcomes.

“The link between air pollution and premature birth has been well established, but for the first time we were able to look at the detailed pathway and specific fine particles to identify how they are reflected in the increased risk of adverse birth outcomes,” says Donghai Liang, PhD, study lead author and associate professor of environmental health. “This is important because if we can figure out the ‘why’ and ‘how,’ then we can know better how to address it.”

Previous research has shown that pregnant women and fetuses are more vulnerable than other populations to exposure to PM2.5, which is emitted from combustion sources such as vehicle exhaust, industrial processes, and wildfires. This increased vulnerability is linked to a higher likelihood of preterm births, the leading cause of death globally among children under the age of five.

Preterm birth is associated with complications such as cerebral palsy, respiratory distress syndrome, and long-term noncommunicable disease risks. Early term births (37-39 weeks of gestation) are also linked to increased neonatal morbidity and developmental challenges. Approximately 10% of preterm births worldwide are attributable to PM2.5 exposure.

As an air pollution scientist, Liang emphasizes the importance of addressing this issue beyond simply asking people to move away from highly polluted areas. “From a clinical intervention standpoint, it’s critical to gain a better understanding on these pathways and molecules affected by pollution,” he says. “In the future, we may be able to target some of these molecules to develop effective strategies or clinical interventions that could help reduce these adverse health effects.”

This groundbreaking study highlights the urgent need for policymakers and healthcare providers to take action against air pollution, particularly in areas with high levels of PM2.5 exposure. By understanding the molecular link between air pollution and pregnancy risks, we can work towards developing targeted solutions to mitigate these negative outcomes and protect the health of future generations.

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