(Image caption: These are mature nerve cells generated from human cells using enhanced transcription factors. Credit: Fahad Ali)

Functional nerve cells from skin cells

A new method of generating mature nerve cells from skin cells could greatly enhance understanding of neurodegenerative diseases, and could accelerate the development of new drugs and stem cell-based regenerative medicine.

The nerve cells generated by this new method show the same functional characteristics as the mature cells found in the body, making them much better models for the study of age-related diseases such as Parkinson’s and Alzheimer’s, and for the testing of new drugs.

Eventually, the technique could also be used to generate mature nerve cells for transplantation into patients with a range of neurodegenerative diseases.

By studying how nerves form in developing tadpoles, researchers from the University of Cambridge were able to identify ways to speed up the cellular processes by which human nerve cells mature. The findings are reported in the May 27th edition of the journal Development.

Stem cells are our master cells, which can develop into almost any cell type within the body. Within a stem cell, there are mechanisms that tell it when to divide, and when to stop dividing and transform into another cell type, a process known as cell differentiation. Several years ago, researchers determined that a group of proteins known as transcription factors, which are found in many tissues throughout the body, regulate both mechanisms.

More recently, it was found that by adding these proteins to skin cells, they can be reprogrammed to form other cell types, including nerve cells. These cells are known as induced neurons, or iN cells. However, this method generates a low number of cells, and those that are produced are not fully functional, which is a requirement in order to be useful models of disease: for example, cortical neurons for stroke, or motor neurons for motor neuron disease.

In addition, for age-related diseases such as Parkinson’s and Alzheimer’s, both of which affect millions worldwide, mature nerve cells which show the same characteristics as those found in the body are crucial in order to enhance understanding of the disease and ultimately determine the best way to treat it.

"When you reprogramme cells, you’re essentially converting them from one form to another but often the cells you end up with look like they come from embryos rather than looking and acting like more mature adult cells," said Dr Anna Philpott of the Department of Oncology, who led the research. "In order to increase our understanding of diseases like Alzheimer’s, we need to be able to work with cells that look and behave like those you would see in older individuals who have developed the disease, so producing more ‘adult’ cells after reprogramming is really important."

By manipulating the signals which transcription factors send to the cells, Dr Philpott and her collaborators were able to promote cell differentiation and maturation, even in the presence of conflicting signals that were directing the cell to continue dividing.

When cells are dividing, transcription factors are modified by the addition of phosphate molecules, a process known as phosphorylation, but this can limit how well cells can convert to mature nerves. However, by engineering proteins which cannot be modified by phosphate and adding them to human cells, the researchers found they could produce nerve cells that were significantly more mature, and therefore more useful as models for disease such as Alzheimer’s.

Additionally, very similar protein control mechanisms are at work to mature important cells in other tissues such as pancreatic islets, the cell type that fails to function effectively in type 2 diabetes. As well as making more mature nerves, Dr Philpott’s lab is now using similar methods to improve the function of insulin-producing pancreas cells for future therapeutic applications.

"We’ve found that not only do you have to think about how you start the process of cell differentiation in stem cells, but you also have to think about what you need to do to make differentiation complete - we can learn a lot from how cells in developing embryos manage this," said Dr Philpott.

Brain cell find points to new therapies

Insights into how brain cells are produced could lead to treatments for brain cancer and other brain-related disorders.

Scientists have gained new understanding of the role played by a key molecule that controls how and when nerve and brain cells are formed - a process that allows the brain to develop and keeps it healthy.

Their findings could help explain what happens when cell production goes out of control, which is a fundamental characteristic of many diseases including cancer.

Regulatory systems

Researchers have focused on a RNA molecule, known as miR-9, which is linked to the development of brain cells, known as neurons and glial cells.

They have shown that a protein called Lin28a regulates the production of miR-9, which in turn controls the genes involved in brain cell development and function.

Scientists carried out lab studies of embryonic cells, which can develop into neurons, to determine how Lin28a controls the amount of miR-9 that is produced.

Complex pathways

They found that in embryonic cells, Lin28a prevents production of miR-9 by triggering the degradation of its precursor molecule.

In developed brain cells, Lin28a is no longer produced, which enables miR-9 to accumulate and function.

In cancer cells, Lin28a production is re-established, and as a result this natural process is disrupted.

Lab experiments

Researchers used a series of lab tests to unravel the complex processes that are directed by the Lin28a protein.

They say further studies could help explain fully the role of Lin28a and miR-9 in brain development, and pave the way to the development of novel therapies.

The study, published in Nature Communications, was supported by the Wellcome Trust and the Medical Research Council.

Understanding more of the complex science behind the fundamental processes of cell development will helps us learn more about what happens when this goes wrong – and what might be done to prevent it. -Dr Gracjan Michlewski (School of Biological Sciences)

(Image: iStock)

(Image caption: This image shows a PC12 cell growing onto a randomly textures surface. Note how the cell is spreading out in all directions.)

Surface Characteristics Influence Cellular Growth on Semiconductor Material

Changing the texture and surface characteristics of a semiconductor material at the nanoscale can influence the way that neural cells grow on the material.

The finding stems from a study performed by researchers at North Carolina State University, the University of North Carolina at Chapel Hill and Purdue University, and may have utility for developing future neural implants.

“We wanted to know how a material’s texture and structure can influence cell adhesion and differentiation,” says Lauren Bain, lead author of a paper describing the work and a Ph.D. student in the joint biomedical engineering program at NC State and UNC-Chapel Hill. “Basically, we wanted to know if changing the physical characteristics on the surface of a semiconductor could make it easier for an implant to be integrated into neural tissue – or soft tissue generally.”

The researchers worked with gallium nitride (GaN), because it is one of the most promising semiconductor materials for use in biomedical applications. They also worked with PC12 cells, which are model cells used to mimic the behavior of neurons in lab experiments.

In the study, the researchers grew PC12 cells on GaN squares with four different surface characteristics: some squares were smooth; some had parallel grooves (resembling an irregular corduroy pattern); some were randomly textured (resembling a nanoscale mountain range); and some were covered with nanowires (resembling a nanoscale bed of nails).

Very few PC12 cells adhered to the smooth surface. And those that did adhere grew normally, forming long, narrow extensions. More PC12 cells adhered to the squares with parallel grooves, and these cells also grew normally.

About the same number of PC12 cells adhered to the randomly textured squares as adhered to the parallel grooves. However, these cells did not grow normally. Instead of forming narrow extensions, the cells flattened and spread across the GaN surface in all directions.

More PC12 cells adhered to the nanowire squares than to any of the other surfaces, but only 50 percent of the cells grew normally. The other 50 percent spread in all directions, like the cells on the randomly textured surfaces.

“This tells us that the actual shape of the surface characteristics influences the behavior of the cells,” Bain says. “It’s a non-chemical way of influencing the interaction between the material and the body. That’s something we can explore as we continue working to develop new biomedical technologies.”

Comparing mouse and human immune systems

It is a familiar note struck when authors conclude their reports on experiments conducted in mouse models: They suggest caution when translating their findings from mouse to human. A variation of this refrain can be heard when a small molecule that works in mice fails in human clinical trials.

There may be myriad reasons why results differ, and some challenges to the relevance of mouse models to human disease and therapy may be more anecdotal than evidence-driven, scientists say. But the need for better understanding the differences and similarities between human and mouse is clear. Genomic tools and analysis have opened the door to making comprehensive comparisons at a basic level that can inform future research in both mice and humans.

Scientists studying cell differentiation and function in the immune system set out to chart how the mouse and human compare in this area. Tal Shay, a postdoctoral associate in Aviv Regev’s lab at the Broad Institute of Harvard and MIT, led a team from Harvard Medical School, the Broad and Stanford University who compared two large compendia containing transcriptional profiles—how genes are expressed—in human and mouse immune cell types.

The researchers found remarkable consistency between gene expression profiles in the mouse and human immune systems but also some instances of divergence. The majority of gene expression patterns—conservatively estimated at 80 percent—were the same in mouse and human. In addition, they suggest a role for transcriptional regulators that may guide some of the similarities.

Shay and her colleagues reported their findings in PNAS and also deposited their data and analysis in a web portal, which they hope will serve as a reference map for other investigators. Their work is part of the ImmGen Consortium, a collaboration of immunologists and computational biologists generating a complete compendium of gene expression and its regulation in the mouse immune system.

“We wanted to pinpoint where immune system genes and gene expression are different and where you should be very suspicious if something is found in mouse and likely to be translated to human,” said Shay, who is a lead author of the paper. “We thought we might be able to map those places where the comparison is less robust, but we had a very hard time pinpointing convincing differences.”

The researchers had to take extraordinary pains to make sure they were comparing only what was comparable—apples to apples. Not all mouse genes had a corresponding gene in the human data set, or they had more than one: There might be one gene in humans versus five in mice for smell receptors, for example. Sometimes differences were a matter of timing: Genes were activated earlier or later, depending on the species, said David Puyraimond-Zemmour, an HMS graduate student in immunology in the lab of Christophe Benoist and Diane Mathis and a co-author of the PNAS paper.

In all, they found several dozen genes in seven immune cell types that have different expression in 80 human and 137 mouse samples. Their conclusions are based on comparing data from the Differentiation Map—which measures gene expression in about 40 human cell types—and data from ImmGen, which does the same for about 200 mouse cell types. They did further analyses of gene expression when cells were activated in different states, such as responding to infection, based on a data set produced by Ei Wakamatsu and Ting Feng, postdoctoral fellows in the Benoist-Mathis lab. Shay also worked with the Differentiation Map data from the lab of Benjamin Ebert, HMS associate professor of medicine at Brigham and Women’s Hospital and Dana-Farber Cancer Institute and an associate member of the Broad Institute, as well as from the ImmGen Project.

“What we assume most people will be interested in knowing is, if they are working on gene X, whether gene X has the same expression pattern in human and mouse immune systems,” Shay said. “Most lineages have the same expression signature but some genes behave differently and we think it’s important for why some things work in mice but not humans and the other way around.”

Benoist, Morton Grove-Rasmussen Professor of Immunohematology at Harvard Medical School, said the continuing debate about the usefulness of mouse models in understanding humans “is often at the level of the emotional and not necessarily very informed.” Wildly different experimental conditions—hugely varying doses or duration in clinical trials—make comparisons suspect, he said.

Having clear data that scientists can freely access will be useful, said Benoist, who is also a co-author of the PNAS paper.

“The value here is putting up signposts, signaling when the function of a gene in mice may not be relevant to humans,” he said, referring to data and analysis from the work published in PNAS. “Because the differentiation and function of human and mouse lineages are highly related, there is the expectation of conservation, so it is important to know when inter-species inferences may be an issue. Mouse models are far too valuable to be jettisoned for pre-clinical exploration, but it is important to know when caution is needed.”