<![CDATA[Newsroom University of ԰]]> /about/news/ en Wed, 15 Apr 2026 06:55:13 +0200 Mon, 13 Apr 2026 13:22:02 +0200 <![CDATA[Newsroom University of ԰]]> https://content.presspage.com/clients/150_1369.jpg /about/news/ 144 Lab-grown retina gives gene change clue to rare childhood eye condition /about/news/lab-grown-retina-gives--gene-change-clue-to-rare-childhood-eye-condition/ /about/news/lab-grown-retina-gives--gene-change-clue-to-rare-childhood-eye-condition/741829A led by University of ԰ scientists using tiny retinas grown in a lab has revealed how subtle changes in a key growth‑controlling protein can lead to a condition causing serious eye defects from birth.

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A led by University of ԰ scientists using tiny retinas grown in a lab has revealed how subtle changes in a key growth‑controlling protein can lead to a condition causing serious eye defects from birth.

The findings, published today in  journal BBA: Molecular Basis of Disease  shed new light on ocular coloboma, a rare congenital eye condition affecting around 1 in 5000 births and responsible for roughly 10% of childhood blindness.

Some of the researchers are also based at ԰ University NHS Foundation Trust  and the Greenwood Genetic Centre in the United States.

Coloboma arises when a structure in the developing eye, the optic fissure, fails to close properly and often co‑occurs with other tissue‑fusion problems such as cleft lip and/or palate.

The research focused on YAP1, a protein that helps guide how organs form and how tissues stay healthy.

YAP1 acts like a switch inside cells, helping them decide when to grow, change, or survive based on signals they receive.

Although changes in YAP1 have been linked to coloboma, it has been unclear why some people with these changes develop severe eye defects while others remain unaffected. To address that, they tested the different variants and compared their effects.

To understand the consequences of YAP1’s inactivity during eye development, the researchers studied human retinal organoids - lab-grown miniature versions of the developing human retina grown in the lab. When they reduced the activity of YAP1, they saw effects on how early retinal cells grow and develop.

Disrupting YAP1, they found,  reduced the activity of genes needed for early retinal cells to grow and maintain their identity.

 As a result, the cells developed more slowly, providing a potential explanation for how eye formation goes wrong.

The study also showed that not all YAP1 variants have the same effect. Using computer modelling alongside experimental data, the researchers found that the precise location of each genetic change determines how strongly it disrupts YAP1 function.

This helps explain why coloboma can vary so widely between individuals, even among those carrying changes in the same gene.

Coloboma has been linked to disease causing variants in more than 40 genes, but thanks to the study, YAP1 is now identified as  an important contributor.

“These findings give us a much clearer picture of how small genetic changes can have major effects during eye development,” said the lead author from The University of ԰.

“By pinpointing how each variant disrupts YAP1’s function, we can better interpret genetic results in patients and move closer to ways of supporting healthy eye formation.

“By combining stem‑cell models with detailed genetic testing, we’re finally beginning to understand how tiny changes in YAP1 can have such a big impact on how the eye forms.

“This work brings us a step closer to explaining why some children develop coloboma.

“Though retinal organoids cannot currently replace the use of animal models, this study shows how they can help us meet our ethical and legal obligations to replace, reduce and refine the use of animals in research wherever feasible.

“It also offers a new framework for understanding how likely YAP1 mutations are to cause disease in children with unexplained eye conditions.”

  • Domain-specific mechanisms of YAP1 variants in ocular coloboma revealed by in-vitro and organoid studies is available DOI:

  • Image: retinal organoid

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Kidney researcher wins University of ԰ 3Rs prize /about/news/kidney-researcher-wins-university-of-manchester-3rs-prize/ /about/news/kidney-researcher-wins-university-of-manchester-3rs-prize/677700A researcher from The University of ԰ has bagged a prize for developing a powerful way to minimize suffering in animals when studying kidney disease.

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A researcher from The University of ԰ has bagged a prize for developing a powerful way to minimize suffering in animals when studying kidney disease. 

The new tool -  now used across the world - was developed by research fellow Dr Richard Naylor who made it possible to use zebrafish larvae to easily and quickly screen new drugs for treating different kidney diseases. 

Replacement, reduction and refinement – known collectively as the 3Rs -  are an increasingly important area of biological research. 

By law scientists must demonstrate they have adhered to the principles of the 3Rs before their project license is granted by the Home Office. 

Dr Naylor will pick up his award today (14 November) at the second ever University of ԰  3Rs symposium, organised by the University’s animal unit, where  scientists will hear about the latest advances in 3Rs science. 

Using organisms that are not able to feed independently and are therefore considered to be minimally sentient - the judges recognised the tool as a novel alternative to mammals but also for its ability to reduce animal numbers and enhance the care they receive. 

Kidney disease is a major cause of illness and accounts for 10% of all deaths in humans. 

Protein in urine is produced when kidneys do not work properly and is easily tested in humans with a simple dipstick. 

Zebrafish- which have similar genetics to humans and possess 80% of human disease-causing genes - are a popular species used by research scientists because they produce large numbers of eggs (200 to 300 per week per female), which develop externally. 

In the past it was virtually impossible to test for protein in the urine of zebra fish larvae because the tiny amounts of urine produced are immediately diluted in the fish tank. 

However, a new genetically modified zebrafish larvae model, designed and generated by Dr Naylor and his team, contains a luminescent molecule called NL-D3 in its blood. 

When kidneys are damaged, NL-D3 leaks out of the kidneys and into the urine. NL-D3 can easily be detected in embryos using a luminometer which measures the light produced by urine in the water. 

As a result, scientists can now easily test for the level of protein in high numbers of the organisms which - at less than 5 days old - are not considered to be fully sentient under the law. 

The team tested the new tool by generating a zebrafish model of Alport syndrome, a kidney disease characterized by protein in the urine, publishing their results in the prestigious journal . 

In Alport zebrafish, levels of NL-D3 increased but could be subsequently reduced using captopril, a drug that lowers blood pressure, demonstrating the efficacy of the tool. 

Dr Naylor said: “Finding 3Rs solutions to animal research is incredibly important because as scientists we care about the welfare of the animals we are privileged to work with. 

“That is why it is so exciting we have demonstrated how is possible to conduct fundamental research on kidney disease without necessarily relying on mammalian models. 

“Testament to this, we have had seven research groups in the US and Europe request embryos be sent to them. 

“And even more excitingly, we are currently collaborating with a large pharmaceutical company to model acute kidney injury and screen drugs to treat it.” 

Dr Maria Kamper, Director of the animal unit at the University of ԰ said: “As Director of the Biological Services Facility, I am delighted to present our inaugural University of ԰ 3Rs prize to Dr Naylor and his team. 

“Their innovative work exemplifies our commitment to advancing scientific discovery while upholding the highest standards of animal welfare. The widespread adoption of this model by kidney disease researchers worldwide proves it is an outstanding achievement in the 3Rs space.” 

Replacing mouse models
Until now, protein in the urine as a marker of kidney dysfunction in disease and in response to drug treatments was mainly used in mouse models or from human patients. But with the new tool, the ability to use zebrafish to accurately monitor kidney dysfunction increases the appeal of pre-independent feeding stage zebrafish to model kidney disease for researchers worldwide. 

Fewer numbers needed
Previously, high numbers of embryos were needed due to high variability in methods used to test kidney dysfunction in zebrafish. The new tool, however, has reduced the number of procedures needed to be performed on zebrafish embryos to zero.  As the scientists now only need to analyse embryo medium, no animals are injected or are required to be anaesthetized. And fewer larvae are needed to achieve statistical significance. 

No need to anaesthetize the embryos
Before the paper was published, the only way to measure kidney dysfunction in zebrafish was to inject fluorescent dextran directly into the animals and observe how quickly the fluorescence was lost from the blood vasculature over the subsequent days. The approach meant having to anaesthetize zebrafish embryos repeatedly, which is now lo longer necessary.

  • The paper A novel nanoluciferase transgenic reporter measures proteinuria in zebrafish is published in
  • Images are of zebrafish larvae
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Planetary science could save thousands of lab mice /about/news/planetary-science-could-save-thousands-of-lab-mice/ /about/news/planetary-science-could-save-thousands-of-lab-mice/307233File 20181016 165905 17k44vb.jpg?ixlib=rb 1.1

 

, Research Associate, 

 

Experimenting on animals is a big part of biomedical research and also a big concern for those interested in animal welfare. Scientists are encouraged to use as few animals as possible in their research, but reducing animal numbers also reduces how precise a researcher can be about the results of a study. If a treatment only has a small effect, lots of animals are needed to see it.

However, a new machine-learning technique (a type of AI) could reduce the number of animals needed in certain studies and still give precise results.

The method, called linear Poisson modelling, developed at the University of ԰, was created to help planetary scientists automate the inspection of images of . It was used to learn the different textures of planetary terrain, then measure how much of those same textures appeared elsewhere on the same planet. The method also helped the citizen science project count craters on the moon.

Now back on Earth, it has found a new use as a tool for cancer researchers to inspect medical images of tumours implanted in lab mice. And compared with traditional statistical methods, early tests show that using this method up to 16 times fewer animals may be needed to detect the effects of treatments in cancer research.

From the moon to cancer tumours.

The machine learning method can describe the differences between groups of tumours that have been treated and those that have not. The medical images that were used in a we carried out used a type of scanning that measures the random motion of water molecules. This is useful because treated tumours become more watery as cell tissue breaks down.

Looking for these changes can be difficult because treatments take time to have an effect and tumours change over time whether they have been treated or not. Plus, there are lots of different ways that tumours can change and no two tumours are exactly alike. This complex behaviour can now be learnt using the machine learning method, allowing treatment effects to be precisely measured in individual tumours.

The more traditional approach, using what statisticians call a , often requires using a dozen or more animals before a precise result can be seen.

A more sensitive method

Cancer treatments can work better in certain combinations and can work better or worse depending upon the genetics of a tumour. Finding out which combinations of treatment work best for different tumours is an ongoing challenge.

The number of genetic differences between tumours and the number of treatment combinations that are possible leads to many thousands of experiments that need to be performed. This new method has the potential to significantly reduce the number of animals needed for large experiments. The sensitivity of the method may also allow shorter experiments to be performed, thereby reducing the discomfort and distress of the animals involved.

Our proof-of-concept study is the first step to fully realising the benefits of the new approach, but it must first be demonstrated that similar results can be repeated on other tumour images. We are optimistic that they will.The Conversation

This article is republished from under a Creative Commons license. Read the .

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