Publisher Health

Fathers exposed to chemicals in plastics can affect the metabolic health of their offspring for two generations, a University of California, Riverside, mouse study reports.
Plastics, which are now ubiquitous, contain endocrine disrupting chemicals, or EDCs, that have been linked to increased risk of many chronic diseases; parental exposure to EDCs, for example, has been shown to cause metabolic disorders, including obesity and diabetes, in the offspring.
Most studies have focused on the impact of maternal EDC exposure on the offspring’s health. The current study, published in the journal Environment International, focused on the effects of paternal EDC exposure.
Led by Changcheng Zhou, a professor of biomedical sciences in the School of Medicine, the researchers investigated the impact of paternal exposure to a phthalate called dicyclohexyl phthalate, or DCHP, on the metabolic health of first generation (F1) and second generation (F2) offspring in mice. Phthalates are chemicals used to make plastics more durable.
The researchers found that paternal DCHP exposure for four weeks led to high insulin resistance and impaired insulin signaling in F1 offspring. The same effect, but weaker, was seen in F2 offspring.
“We found paternal exposure to endocrine disrupting phthalates may have intergenerational and transgenerational adverse effects on the metabolic health of their offspring,” Zhou said. “To the best of our knowledge, our study is the first to demonstrate this.”
In the case of paternal exposure in the study, intergenerational effects are changes that occur due to direct exposure to a stressor, such as exposure to DCHP of fathers (F0 generation) and his developing sperm (F1 generation). Transgenerational effects are changes passed down to offspring that are not directly exposed to the stressor (for example, F2 generation).

Zhou’s team focused on sperm, specifically, its small-RNA molecules that are responsible for passing information down generations. The researchers used “PANDORA-seq method,” an innovative method that showed DCHP exposure can lead to small-RNA changes in sperm. These changes are undetected by traditional RNA-sequencing methods, which lack the comprehensive overview of the small-RNA profile that PANDORA-seq provides.
The study used only F1 males to breed with unexposed female mice to generate F2 offspring. The team found that paternal DCHP exposure induced metabolic disorders, such as impaired glucose tolerance, in both male and female F1 offspring, but these disorders were seen only in female F2 offspring. The study did not examine F3 offspring.
“This suggests that paternal DCHP exposure can lead to sex-specific transgenerational effects on the metabolic health of their progenies,” Zhou said. “At this time, we do not know why the disorders are not seen in male F2 offspring.”
Zhou stressed that the impact of exposure to DCHP on human health is not well understood, even though DCHP is widely used in a variety of plastic products and has been detected in food, water, and indoor particulate matter. DCHP has also been found in human urinary and blood samples. Indeed, the U.S. Environmental Protection Agency recently designated DCHP as one of 20 high-priority substances for risk evaluation.
“It’s best to minimize our use of plastic products,” Zhou said. “This can also help reduce plastic pollution, one of our most pressing environmental issues.”
Zhou, whose earlier mouse study showed exposure to DCHP leads to increased plasma cholesterol levels, was joined in the current study by Jingwei Liu, Junchao Shi, Rebecca Hernandez, Xiuchun Li, Pranav Konchadi, Yuma Miyake, and Qi Chen of UCR; and Tong Zhou of University of Nevada, Reno School of Medicine.
The study was partially supported by grants from the National Institutes of Health and American Heart Association. Hernandez was supported by a National Institutes of Health training grant and an American Heart Association predoctoral fellowship.

Scientists have created an AI system capable of generating artificial enzymes from scratch. In laboratory tests, some of these enzymes worked as well as those found in nature, even when their artificially generated amino acid sequences diverged significantly from any known natural protein.
The experiment demonstrates that natural language processing, although it was developed to read and write language text, can learn at least some of the underlying principles of biology. Salesforce Research developed the AI program, called ProGen, which uses next-token prediction to assemble amino acid sequences into artificial proteins.
Scientists said the new technology could become more powerful than directed evolution, the Nobel-prize winning protein design technology, and it will energize the 50-year-old field of protein engineering by speeding the development of new proteins that can be used for almost anything from therapeutics to degrading plastic.
“The artificial designs perform much better than designs that were inspired by the evolutionary process,” said James Fraser, PhD, professor of bioengineering and therapeutic sciences at the UCSF School of Pharmacy, and an author of the work, which was published Jan. 26, in Nature Biotechnology.
“The language model is learning aspects of evolution, but it’s different than the normal evolutionary process,” Fraser said. “We now have the ability to tune the generation of these properties for specific effects. For example, an enzyme that’s incredibly thermostable or likes acidic environments or won’t interact with other proteins.”
To create the model, scientists simply fed the amino acid sequences of 280 million different proteins of all kinds into the machine learning model and let it digest the information for a couple of weeks. Then, they fine-tuned the model by priming it with 56,000 sequences from five lysozyme families, along with some contextual information about these proteins.

The model quickly generated a million sequences, and the research team selected 100 to test, based on how closely they resembled the sequences of natural proteins, as well how naturalistic the AI proteins’ underlying amino acid “grammar” and “semantics” were.
Out of this first batch of a 100 proteins, which were screened in vitro by Tierra Biosciences, the team made five artificial proteins to test in cells and compared their activity to an enzyme found in the whites of chicken eggs, known as hen egg white lysozyme (HEWL). Similar lysozymes are found in human tears, saliva and milk, where they defend against bacteria and fungi.
Two of the artificial enzymes were able to break down the cell walls of bacteria with activity comparable to HEWL, yet their sequences were only about 18% identical to one another. The two sequences were about 90% and 70% identical to any known protein.
Just one mutation in a natural protein can make it stop working, but in a different round of screening, the team found that the AI-generated enzymes showed activity even when as little as 31.4% of their sequence resembled any known natural protein.
The AI was even able to learn how the enzymes should be shaped, simply from studying the raw sequence data. Measured with X-ray crystallography, the atomic structures of the artificial proteins looked just as they should, although the sequences were like nothing seen before.

Salesforce Research developed ProGen in 2020, based on a kind of natural language programming their researchers originally developed to generate English language text.
They knew from their previous work that the AI system could teach itself grammar and the meaning of words, along with other underlying rules that make writing well-composed.
“When you train sequence-based models with lots of data, they are really powerful in learning structure and rules,” said Nikhil Naik, PhD, Director of AI Research at Salesforce Research, and the senior author of the paper. “They learn what words can co-occur, and also compositionality.”
With proteins, the design choices were almost limitless. Lysozymes are small as proteins go, with up to about 300 amino acids. But with 20 possible amino acids, there are an enormous number (20300) of possible combinations. That’s greater than taking all the humans who lived throughout time, multiplied by the number of grains of sand on Earth, multiplied by the number of atoms in the universe.
Given the limitless possibilities, it’s remarkable that the model can so easily generate working enzymes.
“The capability to generate functional proteins from scratch out-of-the-box demonstrates we are entering into a new era of protein design,” said Ali Madani, PhD, founder of Profluent Bio, former research scientist at Salesforce Research, and the paper’s first author. “This is a versatile new tool available to protein engineers, and we’re looking forward to seeing the therapeutic applications.”
Further information: https://github.com/salesforce/progen

By using artificial human skin, a research group from the University of Copenhagen have managed to block invasive growth in a skin cancer model.
The study has been published in Science Signaling and looks at what actually happens when a cell turns into a cancer cell.
“We have been studying one of the cells’ signalling pathways, the so-called TGF beta pathway. This pathway plays a critical role in the cell’s communication with its surroundings, and it controls e.g. cell growth and cell division. If these mechanisms are damaged, the cell may turn into a cancer cell and invade the surrounding tissue,” explains Professor and Team Lead Hans Wandall from the Department of Cellular and Molecular Medicine at the University of Copenhagen.
Under normal circumstances, your skin cells will not just start to invade the hypodermis and wreak havoc. Instead, they will produce a new layer of skin. But when cancer cells emerge, the cells no longer respect the boundaries between skin layers, and they start to invade each other. This is called invasive growth.
Hans Wandall and his colleagues have been studying the TGF beta pathway and applied methods for blocking invasive growth and thus curbing the invasive growth in skin cancer.
“We already have various drugs that can block these signalling pathways and which may be used in tests. We have used some of them in this study,” explains Associate Professor and co-author of the study Sally Dabelsteen from the School of Dentistry.

Hans Wandall and Sally Dabelsteen have worked together with Dr. Zilu Ye and Professor Jesper V. Olsen from the Novo Nordisk Foundation Center for Protein Research at the Faculty of Health and Medical Sciences.
“Some of these drugs have already been tested on humans, and some are in the process of being tested in connection with other types of cancer. They could also be tested on skin cancer specifically,” she says.
Artificial skin is the closest we get to real human skin
The artificial skin used by the researchers in the new study consists of artificial, genetically manipulated human skin cells. Skin cells are produced on subcutaneous tissue made of collagen. This makes the cells grow in layers, just like real human skin.
Unlike mice models, the skin model, which is another word for artificial skin, allows researchers to introduce artificial genetic changes relatively quickly, which provide insight into the systems that support skin development and renewal.
This way they are also able to reproduce and follow the development of other skin disorders, not just skin cancer.
“By using artificial human skin we are past the potentially problematic obstacle of whether results from tests on mice models can be transferred to human tissue. Previously, we used mice models in most studies of this kind. Instead, we can now conclude that these substances probably are not harmful and could work in practice, because the artificial skin means that we are closer to human reality,” says Hans Wandall.
The artificial skin used by the researchers resembles the skin used to test cosmetics in the EU, which banned animal testing in 2004. However, artificial skin does not allow the researchers to test the effect of a drug on the entire organism, Hans Wandall points out. Skin models like the one used here have been used by cosmetics companies since the mid-1980s.
“We can study the effect focussing on the individual organ — the skin — and then we reap experiences with regard to how molecules work, while we seek to determine whether they damage the structure of the skin and the healthy skin cells,” he says.

People with early cardiovascular disease may be more likely to have memory and thinking problems and worse brain health in middle age, according to new research published in the January 25, 2023, online issue of Neurology®, the medical journal of the American Academy of Neurology.
“Cardiovascular diseases such as heart disease and stroke have been associated with an increased risk for cognitive impairment and dementia in older adults, but less is known about how having these diseases before age 60 impacts cognition and brain health over the course of life,” said study author Xiaqing Jiang, PhD, of the University of California, San Francisco. “Our study found that cardiovascular events earlier in life are associated with worse cognition, accelerated cognitive decline and poor brain health in middle age.”
The study looked at 3,146 people. Participants were 18 to 30 years old at the start of the study and were followed for up to 30 years. By the end of the study, they had an average age of 55.
Of the total participants, 147, or 5%, were diagnosed with early cardiovascular disease, which was defined as having coronary heart disease, stroke, congestive heart failure, carotid artery disease or peripheral artery disease before age 60. The average age for a first cardiovascular event was age 48.
After being followed for three decades, participants were given five cognitive tests. The tests measured thinking and memory skills including global cognition, processing speed, executive function, delayed verbal memory and verbal fluency.
Researchers found that people with early cardiovascular disease performed worse than those without on five out of five tests. In a test of recalling a list of words after 10 minutes where scores ranged from zero to 15, those with early cardiovascular disease compared to those without had an average score of 6.4 versus an average score of 8.5. In a test assessing global cognition where scores ranged from zero to 30, those with early cardiovascular disease had an average score of 21.4 compared to others without cardiovascular disease who had an average score of 23.9. A score of 26 or higher is considered typical, while people with mild cognitive impairment have an average score of 22.
Of the total participants, 656 people had brain scans to look at white matter hyperintensities and white matter integrity. White matter hyperintensities typically indicate vascular injury to the brain’s white matter. After adjusting for cardiovascular risk factors such as diabetes and high blood pressure, researchers found that early cardiovascular disease was associated with more white matter hyperintensities in the brain as well as higher white matter mean diffusivity, which indicates a decrease in brain tissue integrity.
For participants who had two sets of cognitive tests 25 and 30 years into the study, researchers found early cardiovascular disease was associated with three times greater likelihood of accelerated cognitive decline over five years, with 13% of people with early cardiovascular disease experiencing accelerated cognitive decline compared to 5% people who did not have the disease.
“Our research suggests that a person’s 20s and 30s are a crucial time to begin protecting brain health through cardiovascular disease prevention and intervention,” Jiang said. “Preventing these diseases may delay the onset of cognitive decline and promote a healthier brain throughout life.”
A limitation of the study is that cognitive tests were not given at the start of the study.
The study was supported by the National Institutes of Health, National Institute on Aging, National Heart, Lung, and Blood Institute, the University of Alabama at Birmingham, Northwestern University, the University of Minnesota, and Kaiser Foundation Research Institute.

Scientists from Rice University are using fluorescence lifetime to shed new light on a peptide associated with Alzheimer’s disease, which the Centers for Disease Control and Prevention estimates will affect nearly 14 million people in the U.S. by 2060.
Through a new approach using time-resolved spectroscopy and computational chemistry, Angel Martí and his team found experimental evidence of an alternative binding site on amyloid-beta aggregates, opening the door to the development of new therapies for Alzheimer’s and other diseases associated with amyloid deposits.
The study is published in Chemical Science.
Amyloid plaque deposits in the brain are a main feature of Alzheimer’s. “Amyloid-beta is a peptide that aggregates in the brains of people that suffer from Alzheimer’s disease, forming these supramolecular nanoscale fibers, or fibrils” said Martí, a professor of chemistry, bioengineering, and materials science and nanoengineering and faculty director of the Rice Emerging Scholars Program. “Once they grow sufficiently, these fibrils precipitate and form what we call amyloid plaques.
“Understanding how molecules in general bind to amyloid-beta is particularly important not only for developing drugs that will bind with better affinity to its aggregates, but also for figuring out who the other players are that contribute to cerebral tissue toxicity,” he added.
The Martí group had previously identified a first binding site for amyloid-beta deposits by figuring out how metallic dye molecules were able to bind to pockets formed by the fibrils. The molecules’ ability to fluoresce, or emit light when excited under a spectroscope, indicated the presence of the binding site.

Time-resolved spectroscopy, which the lab utilized in its latest discovery, “is an experimental technique that looks at the time that molecules spend in an excited state,” Martí said. “We excite the molecule with light, the molecule absorbs the energy from the light photons and gets to an excited state, a more energetic state.”
This energized state is responsible for the fluorescent glow. “We can measure the time that molecules spend in the excited state, which is called lifetime, and then we use that information to evaluate the binding equilibrium of small molecules to amyloid-beta,” Martí said.
In addition to the second binding site, the lab and collaborators from the University of Miami uncovered that multiple fluorescent dyes not expected to bind to amyloid deposits in fact did.
“These findings are allowing us to create a map of binding sites in amyloid-beta and a record of the amino acid compositions required for the formation of binding pockets in amyloid-beta fibrils,” Martí said.
The fact that time-resolved spectroscopy is sensitive to the environment around the dye molecule enabled Martí to infer the presence of the second binding site. “When the molecule is free in solution, its fluorescence has a particular lifetime that is due to this environment. However, when the molecule is bound to the amyloid fibers, the microenvironment is different and as a consequence so is the fluorescence lifetime,” he explained. “For the molecule bound to amyloid fibers, we observed two different fluorescence lifetimes.

“The molecule was not binding to a unique site in the amyloid-beta but to two different sites. And that was extremely interesting because our previous studies only indicated one binding site. That happened because we were not able to see all the components with the technologies we were using previously,” he added.
The discovery prompted more experimentation. “We decided to look into this further using not only the probe we designed, but also other molecules that have been used for decades in inorganic photochemistry,” he said. “The idea was to find a negative control, a molecule that would not bind to amyloid-beta. But what we discovered was that these molecules that we were not expecting would bind to amyloid-beta at all actually did bind to it with decent affinity.”
Martí said the findings will also impact the study of “many diseases associated with other kinds of amyloids: Parkinson’s, amyotrophic lateral sclerosis (ALS), Type 2 diabetes, systemic amyloidosis.”
Understanding the binding mechanisms of amyloid proteins is also useful for studying nonpathogenic amyloids and their potential applications in drug development and materials science.
“There are functional amyloids that our body and other organisms produce for different reasons that are not associated with diseases,” Martí said. “There are organisms that produce amyloids that have antibacterial effects. There are organisms that produce amyloids for structural purposes, to create barriers, and others that use amyloids for chemical storage. The study of nonpathogenic amyloids is an emerging area of science, so this is another path our findings can help develop.”
The National Science Foundation (2102563) and the family of the late Professor Donald DuPré, a Houston-born Rice alumnus and former professor of chemistry at the University of Louisville, supported the research.

When bacteria interact, they give off cellular signals that can trigger a response in their neighbors, causing them to behave in different ways or produce different substances. For example, they can communicate to coordinate movement away from danger or to emit light to ward off predators.
In new research published by Biophysical Reports, researchers from Florida State University and Cleveland State University lay out a mathematical model that explains how bacteria communicate within a larger ecosystem. By understanding how this process works, researchers can predict what actions might elicit certain environmental responses from a bacterial community.
“Typically, models of bacteria in synthetic environments have involved many, many equations describing many, many things, but they weren’t really flexible for different applications,” said co-author Bhargav Karamched, an assistant professor in FSU’s Department of Mathematics and the Institute of Molecular Biophysics. “What my collaborators and I have done is to create a flexible mathematical model that can be applied to a variety of experimental settings.”
Models like the one developed by Karamched’s team help to predict how those bacterial communities coordinate activity, allowing designers to adjust the parameters of a community, such as the population sizes of different types of bacteria or feedback loops, and tailor them for different purposes. For example, in a population of two kinds of bacteria, having more of one kind of bacteria can be dangerous for a host organism while having more of the other can be beneficial. Getting the right mix is crucial, and models help researchers design and analyze the bacterial communities they create.
“What’s lacking in synthetic biology right now are these general, flexible models that are ready off-the-shelf,” Karamched said. “This may not capture all the details in a bacteria community, but it still captures the general framework of what’s going on. Scientists and engineers can use that to compare against their experimental work and move forward.”
The researchers also tested their model against previously published research that examined how bacteria communicate across large spatial gaps. The previous research found that the bacteria only needed a positive feedback loop in order to signal to each other. But Karamched and his collaborators’ model predicts that the rate of production of signaling molecules must also be within a specific range for coordination to occur.
“This model lays the groundwork for a wide range of future experiments testing different strain interactions and geometries,” said co-author Shawn Ryan, an associate professor in the Department of Mathematics and Statistics and the co-director of the Center for Applied Data Analysis and Modeling at Cleveland State University.
Ryan Godin, a former Cleveland State University student and current Iowa State University doctoral student in chemical engineering, was the lead author on this paper.

Regularly eating a high fat/calorie diet could reduce the brain’s ability to regulate calorie intake. New research in rats published in The Journal of Physiology found that after short periods of being fed a high fat/high calorie diet, the brain adapts to react to what is being ingested and reduces the amount of food eaten to balance calorie intake. The researchers from Penn State College of Medicine, US, suggest that calorie intake is regulated in the short-term by cells called astrocytes (large star-shaped cells in the brain that regulate many different functions of neurons in the brain) that control the signalling pathway between the brain and the gut. Continuously eating a high fat/calorie diet seems to disrupt this signalling pathway.
Understanding the brain’s role and the complex mechanisms that lead to overeating, a behaviour that can lead to weight gain and obesity, could help develop therapies to treat it. Obesity is a global public-health concern because it is associated with increased risk of cardiovascular diseases and type 2 diabetes. In England, 63% of adults are considered above a healthy weight and around half of these are living with obesity. One in three children leaving primary school are overweight or obese1.
Dr Kirsteen Browning, Penn State College of Medicine, US, said,
“Calorie intake seems to be regulated in the short-term by astrocytes. We found that a brief exposure (three to five days) of high fat/calorie diet has the greatest effect on astrocytes, triggering the normal signalling pathway to control the stomach. Over time, astrocytes seem to desensitise to the high fat food. Around 10-14 days of eating high fat/calorie diet, astrocytes seem to fail to react and the brain’s ability to regulate calorie intake seems to be lost. This disrupts the signalling to the stomach and delays how it empties.”
Astrocytes initially react when high fat/calorie food is ingested. Their activation triggers the release of gliotransmitters, chemicals (including glutamate and ATP) that excite nerve cells and enable normal signalling pathways to stimulate neurons that control how the stomach works. This ensures the stomach contracts correctly to fill and empty in response to food passing through the digestive system. When astrocytes are inhibited, the cascade is disrupted. The decrease in signalling chemicals leads to a delay in digestion because the stomach doesn’t fill and empty appropriately.
The vigorous investigation used behavioural observation to monitor food intake in rats (N=205, 133 males, 72 females) which were fed a control or high fat/calorie diet for one, three, five or 14 days. This was combined with pharmacological and specialist genetic approaches (both in vivo and in vitro) to target distinct neural circuits. Enabling the researchers to specifically inhibit astrocytes in a particular region of the brainstem (the posterior part of the brain that connects the brain to the spinal cord), so they could assess how individual neurons behaved to studying rats’ behaviour when awake.
Human studies will need to be carried out to confirm if the same mechanism occurs in humans. If this is the case, further testing will be required to assess if the mechanism could be safely targeted without disrupting other neural pathways.
The researchers have plans to further explore the mechanism. Dr Kirsteen Browning said,
“We have yet to find out whether the loss of astrocyte activity and the signalling mechanism is the cause of overeating or that it occurs in response to the overeating. We are eager to find out whether it is possible to reactivate the brain’s apparent lost ability to regulate calorie intake. If this is the case, it could lead to interventions to help restore calorie regulation in humans.”

CTCF is a critical protein known to play various roles in key biological processes such as transcription. Scientists at St. Jude Children’s Research Hospital used a next-generation protein degradation technology to study CTCF. Their work revealed the superiority of the approach in addition to providing functional insights into how CTCF regulates transcription. The study, published today in Genome Biology,paves the way for more clear, nuanced studies of CTCF.
Transcription is an essential biological process where DNA is copied into RNA. The process is the first required step in a cell to take the instructions housed in DNA and ultimately translate that code into the amino acid or polypeptide building blocks that become active proteins. Dysregulated transcription plays a role in many types of pediatric cancer. Finding ways to modify or target aspects of the transcriptional machinery is a novel frontier in the search for vulnerabilities that can be exploited therapeutically.
While the biology of CTCF has been extensively studied, how the different domains (parts) of CTCF function in relation to transcription regulation remains unclear.
One of the most valuable ways to study a protein is to degrade, or remove, it from a model system. In the protein’s absence, researchers can study the functional changes that occur, providing insight into how the protein influences a cell. One system for degrading proteins is the auxin-inducible degron 1 (AID1) system. However, this system has limitations when investigating the function of CTCF, such as the high dosage dependency of auxin, which causes cellular toxicity that muddles results.
Scientists at St. Jude applied the second-generation system, auxin-inducible degron 2 (AID2) to CTCF (the system was developed by Masato Kanemaki, Ph.D., at the National Institute of Genetics). This system is superior for loss-of-function studies, overcoming the limitations of the AID1 system and eliminating the off-target effects seen with previous approaches.
“We’ve cracked open the understanding of the impact of CTCF using a degradation model, the AID2 system,” said co-corresponding author Chunliang Li, Ph.D., St. Jude Department of Tumor Cell Biology. “Using this system, we identified the rules that govern CTCF-dependent transcription regulation.”
“When the CTCF protein is gone, we and others have observed that very few genes transcriptionally change,” Li said. “We know when we remove most of the CTCF protein in cells, the impact on transcription is minimal. So, the disconnect between the depletion of protein and transcription must be following a mechanism. We identified part of the mechanism. The protein not only relies on binding to the DNA through the recognition of the CTCF DNA binding motif, but also relies on certain domains to bind to specific sequences flanking the motif. For a subset of genes, transcription is regulated only when CTCF binds to these specific sequences.”

“Swapping system” sheds light on the role of zinc finger domains
The researchers combined the AID2 system with leading-edge techniques such as SLAM-seq and sgRNA screening to study how the degradation of CTCF alters transcription.
“With degradation we can create a very clean background, and then introduce a mutant. This switch happens very fast, so we call it a fast-swapping system,” Li said. “This is the first time a clean and fast-swapping system has been used to study individual mutants of CTCF.”
Through their work the scientists identified the zinc finger (ZF) domain as the region within CTCF with the most functional relevance, including ZF1 and ZF10. Removing ZF1 and ZF10 from the model system revealed genomic regions that independently require these ZFs for binding DNA and regulating transcription.
“CTCF itself is a multifunctional protein,” said co-first author Judith Hyle, St. Jude Department of Tumor Cell Biology. “It has various roles in a cell from chromatin architecture maintenance to transcription regulation, either as an activator or repressor of transcription. Our interest is how CTCF is involved in transcriptional regulation, and with this new system we were able to degrade CTCF much more rapidly, and home in on the specific targets of CTCF. We were able to assign some function to these peripheral zinc fingers that have not been well understood, showing that certain regions within the genome required or were dependent upon these zinc finger bindings for transcriptional regulation. That was the first time that had been seen or confirmed in a cellular system.”
An open door for further research

The superior system allowed the researchers to introduce mutations that could be tracked through their model. Scientists then conducted functional studies to understand the consequences of such mutations regarding CTCF binding and transcriptional regulation.
Of the new approach, co-first author Mohamed Nadhir Djekidel, Ph.D., St. Jude Center for Applied Bioinformatics, said “because you can get clean data about the mutants when endogenous protein is degraded, you can actually infer the gene regulatory network, and that opens the door for different downstream analysis to understand how regulation works.”
The study demonstrates the superiority of the AID2 system for degrading proteins and showcases the importance of studying CTCF in a clear system. This is important verification for other researchers in the field of transcriptional regulation research. The work also revealed new avenues for research on this key protein.