Tag: molecular biology

the rise of AI in neuro-oncology

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A new review article in npj Precision Oncology summarizes the current state of knowledge about the role of artificial intelligence (AI) in the diagnosis, treatment, and prognosis of brain tumors.

Study: Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment. Image Credit: metamorworks/Shutterstock.com

Background

Brain tumors, although uncommon, pose a significant health challenge globally, with approximately 250,000 new cases each year. In the United States alone, over 96,000 brain tumor cases were reported in 2022, with around 26,600 of these being cancerous.

Glioblastoma is the most frequently diagnosed type of brain tumor and has a particularly poor prognosis, with only a 7% survival rate five years after diagnosis.

This highlights the urgent need for improved methods of diagnosing, treating, and forecasting the progression of brain tumors.

Challenges in managing brain tumors

Diffuse midline glioma (DMG) in children and glioblastoma in adults are among the toughest brain tumors to treat and are often considered incurable with current medical approaches.

Tailored treatments stand the best chance of providing a cure with the least possible harm. However, the challenge is that information on diagnosing and treating brain tumors is scattered and hard to come by.

Only a select number of medical centers have access to the latest treatment techniques. Moreover, much of the available data on these treatments is sourced from just one or a few institutions, limiting the breadth of knowledge and accessibility for many.

Management approaches and diagnostic criteria based on such data are open to a lack of demographic data and may not be generalizable globally.

Socioeconomic inequity also contributes to late diagnosis, therapeutic challenges, and reduced survival by restricting access to some key tests and reducing the odds of combination therapies. This includes 06-Methylguanine-DNA-methyltransferase (MGMT) testing for glioblastoma.

The need for precise diagnosis, staging, and treatment monitoring is difficult to meet in many cases.

Taking into account the contribution of tumor genotype to the prognosis, limited accessibility for imaging and biopsy, intratumor heterogeneity, and poorly reliable biomarkers to monitor the progress of therapy, there are significant obstacles to the optimal care of these patients.

The brain tumor paradigm

In most cases, a suspected brain tumor is diagnosed, beginning with a physical examination and neuroimaging. A biopsy follows this. If possible, the tumor and other biomarkers are removed and subjected to histologic and molecular analysis.

The choice of therapy depends on available and recommended care practices, clinical trials that are currently going on, the patient’s medical status, and toxicity risks. Magnetic resonance imaging (MRI) is the follow-up modality of choice, sometimes supplemented with cerebrospinal fluid (CSF) or blood tests.

“Decisions regarding brain tumor treatment often involve multidisciplinary meetings between neuro-oncologists, neurosurgeons, neuroradiologists, molecular pathologists, and neuropathologists, underscoring the complexity of these decisions.”

The advantages of AI

AI includes machine learning (ML) and deep learning (DL) techniques, computer vision (CV), and the integration of these as Computational Biology. ML excels at pattern recognition and DL in extracting detailed features. CV improves visual interpretation of imaging data to provide medical data.

Computational biology uses all these methods to parse biological data, helping to understand tumor genetics and molecular biology.

This study aims to uncover AI-assisted tumor radiology, pathology, and genomics advancements. AI contributes synergistically to all these domains to improve their role as a combined dataset in brain tumor management.

AI may help clinicians navigate tumor management decisions by improving MRI imaging accuracy and enhancing the speed at which results are available.

It offers increased sensitivity to anomalies picked up on imaging, detailed image analysis, optimized workflows, comprehensive data analysis from multiple sources, and detecting patterns that could be missed by the human observer.

AI algorithms help localize tumors more efficiently, avoiding human error. The nnU-Net algorithm excels at tumor segmentation, reducing radiation or surgical harm.

This enables AI to help diagnose and grade the tumor, determine the prognosis, and plan treatment while setting up a monitoring framework.

AI may become part of new clinical trials, exploring the feasibility of personalized therapy by leveraging its ability to handle large volumes of data.

AI uses various data types, including imaging data from MRI and computerized tomography (CT), radiomics, histopathologic data, genomics, molecular biomarkers from tumor cells, and clinical data.

Neuroimaging often uses pre- and post-contrast T1-weighted, T2-weighted, fluid-attenuated inversion recovery (FLAIR), diffusion-weighted (DWI), and susceptibility-weighted imaging (SWI), as well as, in specialized centers, MR spectroscopy and perfusion imaging.

Molecular biomarkers include IDH mutations for astrocytomas and oligodendrogliomas, TERT promoter mutations for glioblastomas, EGFR amplification for glioblastomas, gain of chromosome 7 and loss of chromosome 10 for glioblastomas, and MGMT promoter methylation for glioblastomas.

Non-invasive circulating tumor DNA (ctDNA) analysis is a newer method for diagnosing such tumors.

AI platforms

3D U-Net, DeepMedic, and V-Net are AI architectures that help preprocess tumor images, making the analysis more robust and precise. Methylome profiling is useful in classifying brain tumors using AI/MI and systems like DeepGlioma. This uses stimulated Raman histology (SRH) to offer results on GMB molecular diagnosis within 90 seconds.

Other systems to predict IDH and other mutations based on radiomics data from MRI perfusion scans or 18F-FET PET/CT scans are being explored, such as a deep learning imaging signature (DLIS) and Terahertz spectroscopy.

‘Sturgeon’ is another DL method to classify brain tumors intraoperatively using nanopore-sequenced methylation array data. Its 40-minute turnaround time, with >70% accuracy, helps surgical decision-making.

Prognostic help is being provided from imaging data to predict overall survival and progression-free survival, two key clinical and research metrics.

Combined with histology and molecular biology, exceptional predictive performance has been demonstrated.

Integrated approaches

Multimodal data fusion approaches could help achieve a less invasive and more accurate understanding of brain tumors using multiple data sources. This will eventually help tailor management to the patient.

The challenge is to extend and diversify the data collection range to other populations and tumor types with standardized features to ensure reproducibility and generalizability.

The adoption of AI should not worsen healthcare and social inequities, emphasizing the need to remove biases, provide legal support, communicate the scope and benefits with transparency, define responsibilities and keep patients safe.

Conclusions

“AI has the potential to empower patients by providing personalized information and enabling shared decision-making. However, the equitable access and affordability of AI-driven healthcare need to be addressed to avoid exacerbating existing disparities.”

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April 2, 2024
Study reveals protein structure similarities in Alzheimer’s and Down syndrome

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More than 90% of people with Down syndrome, the most common chromosomal disorder in humans and the most frequent genetic cause of intellectual disability, are diagnosed with Alzheimer’s disease by ages 55-60. A new study recently published in Nature Structural and Molecular Biology uses leading-edge cryo-electron microscopy imaging technology to determine whether differences exist between the protein structures in those with Alzheimer’s disease and those with both Alzheimer’s disease and Down syndrome.

Just like in Alzheimer’s disease, the neuropathological phenotype in those with Down syndrome and Alzheimer’s disease is characterized by the presence of amyloid β (Aβ) and by abnormal accumulation of tau protein. The structures of Aβ and tau filaments in Down syndrome have not been previously investigated, and it is unknown whether they are different from those of Alzheimer’s disease.”

Ruben Vidal, PhD, the Luella McWhirter Martin Professor of Clinical Alzheimer’s Research at the Indiana University School of Medicine and lead investigator of the study

Researchers studied images of Aβ and tau filaments, which occurs in individuals with Down syndrome, and compared with those seen in the most common form of Alzheimer’s disease. They found that the protein structures of Aβ and tau filaments in people with both Down syndrome and Alzheimer’s disease have similarities to those found in Alzheimer’s disease.

Vidal said their findings may lead to better treatments for Alzheimer’s disease patients and individuals with Down syndrome.

“This study is the first comparison at the near atomic level of Aβ and tau filaments between individuals with both Down syndrome and Alzheimer’s disease and individuals with only Alzheimer’s disease,” Vidal said. “Importantly, the study found variations in the structure of Aβ, but no substantial variation in the structure of tau filaments between individuals with Alzheimer’s disease and both Down syndrome and Alzheimer’s disease. This supports the notion of common mechanisms operating in people with sporadic Alzheimer’s disease and in people with both Down syndrome and Alzheimer’s disease. This knowledge is crucial for understanding Alzheimer’s disease in people with Down syndrome and assessing whether adults with both conditions could be included in Alzheimer’s disease clinical trials. People with Down syndrome are living longer than ever, but almost all of them are dying of Alzheimer’s disease when they get older.”

Vidal, also an investigator in IU School of Medicine’s Stark Neurosciences Research Institute, said the research team used cryogenic electron microscopy to get a close-up, 3D view of the structure of Aβ and tau filaments in two individuals with both Down syndrome and Alzheimer’s disease. The study revealed two novel types of Aβ filaments in the vascular compartment with structures different from those previously reported in Alzheimer’s disease.

Vidal said the study’s findings show it is important to include people with both Down syndrome and Alzheimer’s disease in clinical trials targeting the Aβ or tau filaments. He said there are similarities between the mechanisms at play in amyloid aggregation, but more research is needed to determine whether the differences observed in vascular Aβ deposition are unique to those with Down syndrome.

“We are thrilled that our cryo-EM imaging and 3D modeling techniques have facilitated the determination of the atomic structures of amyloid beta and tau fibrils in individuals with Down syndrome, shedding light on the connection between Down syndrome and Alzheimer’s disease,” said Wen Jiang, PhD, professor of biology at Purdue University and co-corresponding author of the study. “We are fortunate to have the Purdue Cryo-EM Facility, which provides exceptional resources and services that have made this research possible. We are grateful to the patients who donated their brains to the research and thankful to the NIH for funding our work.”

Other study authors include co-corresponding author Bernardino Ghetti, Anllely Fernandez, Grace Hallinan, Kathy Newell and Holly Garringer, all from the IU School of Medicine; and Rejaul Hoq, Daoyi Li, Sakshibeedu Bharath, Frank Vago, Xiaoqi Zhang and Kadir Ozcan, all from Purdue University.

This research was funded by the National Institutes of Health and the IU School of Medicine Department of Pathology and Laboratory Medicine.

Source:

Indiana University School of Medicine

Journal reference:

Fernandez, A., et al. (2024). Cryo-EM structures of amyloid-β and tau filaments in Down syndrome. Nature Structural & Molecular Biology. doi.org/10.1038/s41594-024-01252-3.

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March 29, 2024
AI-powered method predicts protein dynamics to accelerate drug discovery

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Understanding the structure of proteins is critical for demystifying their functions and developing drugs that target them. To that end, a team of researchers at Brown University has developed a way of using machine learning to rapidly predict multiple protein configurations to advance understanding of protein dynamics and functions.

A study describing the approach was published in Nature Communications on Wednesday, March 27.

The authors say the technique is accurate, fast, cost-effective and has the potential to revolutionize drug discovery by uncovering many more targets for new treatments.

In targeted cancer therapy, for example, treatments are designed to zero in on proteins that control how cancer cells grow, divide and spread. One of the challenges for structural biologists has been understanding cell proteins thoroughly enough to identify targets, said study author Gabriel Monteiro da Silva, a Ph.D. candidate in molecular biology, cell biology and biochemistry at Brown.

Monteiro da Silva uses computational methods to model protein dynamics and looks for ways to improve methods or find new methods that work best for different situations. For this study, he partnered with Brenda Rubenstein, an associate professor of chemistry and physics, and other Brown researchers to experiment with an existing A.I.-powered computational method called AlphaFold 2.

While Monteiro da Silva said that the accuracy of AlphaFold 2 has revolutionized protein structure prediction, the method has limitations: It allows scientists to model proteins only in a static state at a specific point in time.

During most cellular processes, proteins will change shape dynamically. In order to match protein targets to drugs to treat cancer and other diseases, we need a more accurate understanding of these physiological changes. We need to go beyond 3D shapes to understanding 4D shapes, with the fourth dimension being time. That’s what we did with this approach.”

Gabriel Monteiro da Silva, Ph.D. candidate in molecular biology, cell biology and biochemistry at Brown University

Monteiro da Silva used the analogy of a horse to explain protein models. The arrangement of the horse’s muscles and limbs create different shapes depending on whether the horse is standing or galloping; protein molecules conform into different shapes due to the bonding arrangements of their constituent atoms. Imagine that the protein is a horse, Monteiro da Silva said. Previous methods were used to predict a model of a standing horse. It was accurate, but it didn’t tell much about how the horse behaved or how it looked when it wasn’t standing.

In this study, the researchers were able to manipulate the evolutionary signals from the protein to use AlphaFold 2 to rapidly predict multiple protein conformations, as well as how often those structures are populated. Using the horse analogy, the new method allows researchers to quickly predict multiple snapshots of a horse galloping, which means they can see how the muscular structure of the horse would change as it moved, and then compare those structural differences.

“If you understand the multiple snapshots that make up the dynamics of what’s going on with the protein, then you can find multiple different ways of targeting the proteins with drugs and treating diseases,” said Rubenstein, whose research focuses whose research focuses on electronic structure and biophysics.

Rubenstein explained that the protein on which the team focused in this study was one that had different drugs developed for it. Yet for many years, no one could understand why some of the drugs succeeded or failed, she said.

“It all came down to the fact that these specific proteins have multiple conformations, as well as to understanding how the drugs bind to the different conformations, instead of to the one static structure that these techniques previously predicted; knowing the set of conformations was incredibly important to understanding how these drugs actually functioned in the body,” Rubenstein said.

Accelerating discovery time

The researchers noted that existing computational methods are cost- and time-intensive.

“They’re expensive in terms of materials, in terms of infrastructure; they take a lot of time, and you can’t really do these computations in a high throughput kind of way -; I’m sure I was one of the top users of GPUs in Brown’s computer cluster,” Monteiro da Silva said. “On a larger scale, this is a problem because there’s a lot to explore in the protein world: how protein dynamics and structure are involved in poorly understood diseases, in drug resistance and in emerging pathogens.”

The researchers described how Monteiro da Silva previously spent three years using physics to understand protein dynamics and conformations. Using their new A.I.-powered approach, the discovery time decreased to mere hours.

“So you can imagine what a difference that would make in a person’s life: three years versus three hours,” Rubenstein said. “And that’s why it was very important that the method we developed should be high-throughput and highly efficient.”

As for next steps, the research team is refining their machine learning approach, making it more accurate as well as generalizable, and more useful for a range of applications.

The study was supported by the Blavatnik Family Foundation, which funds a graduate fellowship in biology and medicine at Brown University. Eight Blavatnik Family Fellows were selected in Fall 2023 based on outstanding academic achievement and demonstrated potential for producing research that advances scientific knowledge and understanding in the basic and clinical life sciences. Monteiro da Silva is one of the inaugural fellows, as is co-author Jennifer Cui, who is analyzing the structure and function of proteins involved in inflammation and cell signaling with fellow co-author George Lisi, a professor of molecular biology, cell biology and biochemistry.

Source:

Journal reference:

Monteiro da Silva, G., et al. (2024). High-throughput prediction of protein conformational distributions with subsampled AlphaFold2. Nature Communications. doi.org/10.1038/s41467-024-46715-9.

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March 27, 2024
Advanced sequencing reveals eye microbiome variances linked to dry eye

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Researchers have used advanced sequencing technology to determine how the mix of microbes present in patients with healthy eyes differs from the mix found in patients with dry eye. The new work could lead to improved treatments for various eye problems and for diseases affecting other parts of the body.

Microbial communities in and on our body -; collectively referred to as the human microbiota -; play an essential role in keeping us healthy. Although many studies have focused on microbial communities in our gut, understanding the microbiota present in other body sites is critical for advancing our knowledge of human health and developing targeted interventions for disease prevention and treatment.

Once we understand the eye microbiota properly, it will improve disease diagnosis at an early stage. This knowledge can also serve as a catalyst for developing innovative therapies aimed at preventing and treating ocular disease as well as those that affect the central microbiome site: the gut.”

Alexandra Van Kley, research team leader, professor at Stephen F. Austin State University in Nacogdoches, Texas

Pallavi Sharma, a graduate student in Van Kley’s lab, will present the research at Discover BMB, the annual meeting of the American Society for Biochemistry and Molecular Biology, which will be held March 23–26 in San Antonio.

“Human microbiome research suggests a strong connection between the gut microbiome and the brain and eyes,” said Sharma. “Any alteration in the gut microbiome affects other organs and can lead to disease. Therefore, we are trying to identify patterns of an imbalance between the types of microbes present in a person’s ocular microbiome for people with different health problems.”

For the study, the researchers collected eye samples from 30 volunteers using a swab and then performed 16S rRNA sequencing and bioinformatic analysis to determine the microbiome distribution for patients with healthy eyes and those with dry eyes.

The analysis showed that Streptococcus and Pedobacter bacteria species were the most prevalent microbes in healthy eyes while more Acinetobacter species were present in the eye microbiomes of people with dry eye. “We think the metabolites produced by these bacteria are responsible for dry eye conditions,” said Sharma. “We are performing further research to understand the metabolic pathways associated with the Acinetobacter to better understand the disease.”

Next, the researchers would like to explore the gut microbiome of the patients with dry eye to better understand how it related to the eye microbe differences they observed.

Source:

American Society for Biochemistry and Molecular Biology

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March 27, 2024
Feedback loop involving estrogen linked to women’s higher propensity to nicotine addiction

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A newly discovered feedback loop involving estrogen may explain why women might become dependent on nicotine more quickly and with less nicotine exposure than men. The research could lead to new treatments for women who are having trouble quitting nicotine-containing products such as cigarettes.

Sally Pauss is a doctoral student at the University of Kentucky College of Medicine in Lexington. She led the project.

“Studies show that women have a higher propensity to develop addiction to nicotine than men and are less successful at quitting,” said Pauss, who is working under the supervision of Terry D. Hinds Jr., an associate professor. “Our work aims to understand what makes women more susceptible to nicotine use disorder to reduce the gender disparity in treating nicotine addiction.”

The researchers found that the sex hormone estrogen induces the expression of olfactomedins, proteins that are suppressed by nicotine in key areas of the brain involved in reward and addiction. The findings suggest that estrogen–nicotine–olfactomedin interactions could be targeted with therapies to help control nicotine consumption.

Pauss will present the research at Discover BMB, the annual meeting of the American Society for Biochemistry and Molecular Biology, which will be held March 23–26 in San Antonio.

Our research has the potential to better the lives and health of women struggling with substance use. If we can confirm that estrogen drives nicotine seeking and consumption through olfactomedins, we can design drugs that might block that effect by targeting the altered pathways. These drugs would hopefully make it easier for women to quit nicotine.”

Sally Pauss, doctoral student, University of Kentucky College of Medicine

For the new study, the researchers used large sequencing datasets of estrogen-induced genes to identify genes that are expressed in the brain and exhibit a hormone function. They found just one class of genes that met these criteria: those coding for olfactomedins. They then performed a series of studies with human uterine cells and rats to better understand the interactions between olfactomedins, estrogen and nicotine. The results suggested that estrogen activation of olfactomedins -; which is suppressed when nicotine is present -; might serve as a feedback loop for driving nicotine addiction processes by activating areas of the brain’s reward circuitry such as the nucleus accumbens.

The researchers are now working to replicate their findings and definitively determine the role of estrogen. This knowledge could be useful for those taking estrogen in the form of oral contraceptives or hormone replacement therapy, which might increase the risk of developing a nicotine use disorder.

The investigators also want to determine the exact olfactomedin-regulated signaling pathways that drive nicotine consumption and plan to conduct behavioral animal studies to find out how manipulation of the feedback loop affects nicotine consumption.

Source:

American Society for Biochemistry and Molecular Biology

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March 26, 2024
Statins show promise in reducing gum disease inflammation

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Could taking statins benefit your mouth in addition to your arteries? A new study conducted in cell cultures showed that cholesterol-lowering drugs help to dampen the inflammation associated with periodontal disease by altering the behavior of macrophages, a type of immune cell.

Statins are the most common type of prescription medication in the United States today, taken by over 40 million Americans to lower cholesterol. The study suggests these drugs improve gum health and reduce the risk of heart disease.

Subramanya Pandruvada, an assistant professor in the College of Dental Medicine at the Medical University of South Carolina, oversaw the work.

During our study, we replicated specific conditions in periodontal disease and demonstrated that introducing statins to our in vitro model modifies macrophage response. This allowed us to explore how medication like statins can help us treat inflammatory conditions such as periodontal disease.”

Subramanya Pandruvada, Assistant Professor, College of Dental Medicine, Medical University of South Carolina

Pandruvada will present the new research at Discover BMB, the annual meeting of the American Society for Biochemistry and Molecular Biology, which is being held March 23–26 in San Antonio. The study’s lead authors are Waleed Alkakhan, a graduate dental resident in periodontology, and Nico Farrar, a dental student at the Medical University of South Carolina.

Periodontal disease occurs when the growth of bacteria in the gums causes the immune system to mount an inflammatory response, contributing to symptoms such as swelling, bleeding and bone degradation. Untreated, it can lead to tooth loss. Nearly half of adults over age 30 have some form of periodontal disease, according to the U.S. Centers for Disease Control and Prevention.

Current treatments for advanced periodontal disease include antibiotics, deep cleanings of tooth and root surfaces, and various surgical procedures. Researchers have sought new ways to calm gum disease through less invasive treatment strategies.

Some previous studies have shown that people taking statins tend to show fewer signs of periodontitis than people who do not take statins. The new study is the first to trace the biochemical pathways through which statins appear to reduce periodontal inflammation.

“Recent periodontal literature has shown the beneficial effects of statins when used with traditional periodontal therapy,” Pandruvada said. “However, our study highlights a novel approach in which statins affect macrophages specifically, which, through this mechanism, can help treat periodontal disease.”

Macrophages play an important role in helping the body fight infections; however, they can also worsen inflammation depending on the form they take at different phases of the immune response. The researchers grew macrophages and gum cells together for the study and exposed them to various conditions. They found that exposure to simvastatin, a common statin drug, suppressed the macrophage inflammatory response.

As a next step, the researchers plan to study the impacts of statins on periodontal disease in animal models, a step toward determining whether this strategy might be a safe and effective approach for future periodontal therapies.

The new findings build upon the group’s initial results, which were published last year in the journal Cells.

Source:

American Society for Biochemistry and Molecular Biology

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March 26, 2024
Study reveals neurological effects of reused frying oils

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A new study found higher levels of neurodegeneration in rats that consumed reused deep fried cooking oils and their offspring compared to rats on a normal diet. Deep frying, which involves completely submerging food in hot oil, is a common method of food preparation around the world.

Results from the study also suggest that the increased neurodegeneration is tied to the oil’s effects on the bidirectional communication network between the liver, gut and brain. The liver–gut–brain axis plays a crucial role in regulating various physiological functions, and its dysregulation has been associated with neurological disorders.

Kathiresan Shanmugam, an associate professor from Central University of Tamil Nadu in Thiruvarur, led the research team.

“Deep-frying at high temperatures has been linked with several metabolic disorders, but there have been no long-term investigations on the influence of deep-fried oil consumption and its detrimental effects on health,” said Shanmugam, formerly at Madurai Kamaraj University, Madurai. “To our knowledge we are first to report long-term deep-fried oil supplementation increases neurodegeneration in the first-generation offspring.”

Sugasini Dhavamani, a research collaborator from the University of Illinois at Chicago, will present the research at Discover BMB, the annual meeting of the American Society for Biochemistry and Molecular Biology, which will be held March 23–26 in San Antonio.

Deep frying food not only adds calories; reusing the same oil for frying, a common practice in both homes and restaurants, removes many of the oil’s natural antioxidants and health benefits. Oil that is reused also can contain harmful components such as acrylamide, trans fat, peroxides and polar compounds.

To explore the long-term effects of reused deep-fried frying oil, the researchers divided female rats into five groups that each received either standard chow alone or standard chow with 0.1 ml per day of unheated sesame oil, unheated sunflower oil, reheated sesame oil or reheated sunflower oil for 30 days. The reheated oils simulated reused frying oil.

Compared with the other groups, the rats that consumed reheated sesame or sunflower oil showed increased oxidative stress and inflammation in the liver. These rats also showed significant damage in the colon that brought on changes in endotoxins and lipopolysaccharides -; toxins released from certain bacteria. “As a result, liver lipid metabolism was significantly altered, and the transport of the important brain omega-3 fatty acid DHA was decreased. This, in turn, resulted in neurodegeneration, which was seen in the brain histology of the rats consuming the reheated oil as well as their offspring.”

Additional studies in which MSG was used to induce neurotoxicity in the offspring showed that the offspring that consumed the reheated oils were more likely to show neuronal damage than the control group receiving no oil or those that received unheated oil.

Although more studies are needed, the researchers say that supplementation with omega-3 fatty acids and nutraceuticals such as curcumin and oryzanol might be helpful in reducing liver inflammation and neurodegeneration. They added that clinical studies in humans are needed to evaluate the adverse effects of eating fried foods, especially those made with oil that is used repeatedly.

As a next step, the researchers would like to study the effects of deep-frying oil on neurodegenerative diseases such as Alzheimer’s and Parkinson’s as well as on anxiety, depression and neuroinflammation. They would also like to further explore the relationship between gut microbiota and the brain to identify potential new ways to prevent or treat neurodegeneration and neuroinflammation.

Source:

American Society for Biochemistry and Molecular Biology

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March 26, 2024
New glycan found to play a key role in nasal colonization of whooping cough bacteria

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Researchers have identified a new complex-carbohydrate biomolecule, or glycan, that plays a key role in the nasal colonization of the Bordetella bacteria responsible for whooping cough. The discovery could make it possible to create a new drug or vaccine that interferes with the glycan to greatly reduce or even stop ongoing Bordetella transmission.

Bordetella pertussis is the cause of the respiratory infection pertussis, which is widely known as whooping cough. Today’s pertussis vaccines keep people from getting severely sick, but they don’t eliminate the bacteria because it excels at colonizing, growing and persisting inside the nose. This means that despite more than 99% of people being vaccinated in the U.S., whooping cough continues to spread, leading to infections among vulnerable populations, particularly infants and elderly people.

Yang Su led the study at the University of Georgia in Athens.

Our newly discovered glycan is crucial for the bacteria to maintain its ability to efficiently colonize the nose and transmit to a new host. By understanding the biochemical and molecular function of genes and enzymes involved in its formation, we can now intervene in the production of this glycan.”

Yang Su, doctoral candidate, department of biochemistry and molecular biology, University of Georgia

Su will present the research at Discover BMB, the annual meeting of the American Society for Biochemistry and Molecular Biology, which will be held March 23–26 in San Antonio. He is co-advised by Maor Bar-Peled and Eric T. Harvill, both from the University of Georgia, and collaborates with Andrew Preston from the University of Bath in the UK and Thomas M. Krunkosky from the University of Georgia.

“My multidisciplinary approach integrates enzymology, glycan structural analyses, genetics, airway cell models and mouse infection models,” said Su. “To my knowledge, this is the first report of a glycan that is significant for the early colonization in the nose of its host.”

Glycans are biomolecules made of chains of carbohydrates such as polysaccharides. They are essential in various biological processes, including cell–cell recognition, signaling and immune response modulation.

In a previous study, the researchers discovered that a glycan known as transmission extracellular polysaccharide (tEPS) was required for Bordetella to spread among hosts. They then discovered that the production of tEPS glycan was related to another group of genes. The investigators suspected that this new group of genes likely produced another glycan, but nothing was known about its function or structure.

In the new work, the researchers eliminated the genes that expressed this unknown glycan from bacteria to see if they could uncover its function. The resulting Bordetella mutant showed a 70% reduction in its ability to colonize the nose of mice within six hours of inoculation. The mutant also showed a significantly reduced ability to transmit from the original host to a new host.

The researchers discovered that this new glycan, which they named bordetellea colonization oligosaccharide, or b-Cool, is found in multiple Bordetella species, including those infecting dogs and other animals, as well as in strains of Bordetella pertussis isolated from patients. This suggests that targeting b-Cool could lead to the development of vaccines and medications that would be effective against both animal and human infections.

The researchers are now working to understand how b-Cool mediates Bordetella colonization in the nose, information that will help develop therapeutics that interfere with colonization. They are also developing a vaccine that targets the b-Cool glycan, which they plan to test in various hosts.

Source:

American Society for Biochemistry and Molecular Biology

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March 26, 2024
New synthetic lung surfactant could revolutionize treatment for premature babies

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Scientists have developed a new lung surfactant that is produced synthetically rather than relying on the use of animal tissues. With further development, the formulation could provide a cheaper and more readily available alternative to Infasurf, a medication used to prevent and treat respiratory distress in premature babies.

Surfactants are substances that decrease surface tension where liquids interface with other liquids, gases or solids. In addition to their use in medicines, they are found in a wide range of products including detergents, cosmetics, motor oils and adhesives.

Suzanne Farver Lukjan, a lecturer in chemistry at Troy University in Alabama, led the work.

A synthetic surfactant could potentially have a longer shelf life, lower production costs, have less batch variability and pose less risk of an immune response compared to animal-derived lung surfactants. We hope our formulation will one day be used in hospitals.”

Suzanne Farver Lukjan, lecturer in chemistry, Troy University in Alabama

Lukjan will present the research at Discover BMB, the annual meeting of the American Society for Biochemistry and Molecular Biology, which is being held March 23–26 in San Antonio.

Lung surfactants help premature babies breathe while their lung cells finish developing. In addition to offering a potential alternative to replace Infasurf for babies, researchers say the new synthetic surfactant could be useful for treating adults with lung injuries as a result of diseases such as chronic obstructive pulmonary disorder, miner’s lung or emphysema.

Researchers have previously attempted to develop synthetic lung surfactants, but some have been removed from the market and others have not been able to lower surface tension as well as animal-derived formulations.

In the new work, Lukjan’s team created candidate surfactants from synthetic lipids (fats) and peptides (short chains of amino acids) and then tested their surface-tension-lowering capabilities. They aimed to mimic the composition, lipid phase behavior and biophysical function of Infasurf as closely as possible.

After tweaking a step in the sample preparation process, the researchers found a few formulations that showed particular promise. Although tests demonstrated that the chemical behavior of the synthetic surfactants was quite different from that of Infasurf, the new surfactants were able to mimic the drug’s functionality in terms of lowering surface tension and seem to achieve the optimal range in terms of peptide concentration.

As a next step, Lukjan said, the group plans to continue to refine and test their formulation to further optimize the combination of lipids and peptides. The surfactant would also need to undergo safety testing before it could be used clinically.

This work was partially funded by ONY Biotech Inc., maker of Infasurf.

Source:

American Society for Biochemistry and Molecular Biology

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March 26, 2024
New compound shows promise as a more effective treatment for schistosomiasis

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A newly developed compound is showing promise in animal studies as a more effective treatment for human schistosomiasis, an understudied tropical disease caused by parasitic worms. The spread of schistosomiasis, a disease responsible for nearly 12,000 deaths globally each year, has been documented in 78 nations.

Although schistosomiasis transmission tends to occur in tropical and subtropical areas, climate change could shift it into new areas such as southern Europe. There is currently no vaccine available for the disease, which comes with severe clinical symptoms. The drug praziquantel is used for treatment. However, resistant mutations are reducing praziquantel’s efficacy, and the drug doesn’t kill the larval-stage parasites.

Sevan N. Alwan, an assistant professor at The University of Texas Health Science Center at San Antonio, led the research team.

The infection can become reactivated when the larva develop into adult parasites, which comes with more severe symptoms and higher transmission rates. The compound we developed overcomes the limitations of praziquantel by being effective against the larval stage and resistant strains.”

Sevan N. Alwan, Assistant Professor, The University of Texas Health Science Center

Alwan will present the research at Discover BMB, the annual meeting of the American Society for Biochemistry and Molecular Biology, which will be held March 23–26 in San Antonio.

“In recent reports, the cure rates for praziquantel were 60% in Sub-Saharan Africa, where the disease is highly endemic,” said Alwan. “The drug limitations strongly warrant the need for new therapeutics with a distinctly different mechanism of action to reach a better cure rate.”

The new compound was developed as part of the research team’s effort to design, synthesize and test reengineered derivatives of oxamniquine, which was previously used to treat patients with parasite but is no longer used due to drug resistance and limited effectiveness.

The researchers developed and tested 350 compounds. Five of these killed human Schistosoma species as well as a praziquantel-resistant strain in animal models.

One of these compounds, called CIDD-0149830, also killed larval parasites in experiments with cultured cells and a mouse model of the disease. In experimental groups of five female mice each, the number of larval worms was reduced by 71.7% with CIDD-0149830, while praziquantel reduced them by only 21.1%. The study also showed that CIDD-0149830 reduced the number of eggs more effectively.

“In addition to being effective against the larval stage and resistant strains, CIDD-0149830 also overcomes the limitation of oxamniquine by being effective against two major species of the parasite in animal models and can effectively treat mixed infection by these two species,” Alwan said.

Although the new results are promising, the researchers caution that they must still determine dosing for humans and perform safety and toxicity studies to make sure the treatment is safe for human use. They also plan to conduct experiments with male and female mice to assess whether sex influences the outcome of worm burden and morbidity.

Source:

American Society for Biochemistry and Molecular Biology

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March 25, 2024