Secret Army: More Manoeuvres Revealed

 

I don’t know about you but I find it difficult to grasp the idea that there are more bugs in my body than there are ‘me’ cells. That is, microorganisms (mostly bacteria) outnumber the aggregate of liver, skin and what-have-you cells. They’re attracted, of course, to the warm, damp surfaces of the cavities in our bodies that are covered by a sticky, mucous membrane, e.g., the mouth, nose and especially the intestines (the gastrointestinal tract).

The story so far

Over the last few years it’s become clear that these co-residents — collectively called the microbiota — are not just free-loaders. They’re critical to our well-being in helping to fight infection by other microrganisms (as we noted in Our Inner Self), they influence our immune system and in the gut they extract the last scraps of nutrients from our diet. So maybe it makes them easier to live with if we keep in mind that we need them every bit as much as they depend on us.

We now know that there are about 2000 different species of bacteria in the human gut (yes, that really is 2,000 different types of bug) and, with all that diversity, it’s not surprising that the total number of genes they carry far exceeds our own complement (by several million to about 20,000). In it’s a small world we noted that obesity causes a switch in the proportions of two major sub-families of bacteria, resulting in a decrease in the number of bug genes. The flip side is that a more diverse bug population (microbiome) is associated with a healthy status. What’s more, shifts of this sort in the microbiota balance can influence cancer development. Even more remarkably, we saw in Hitchhiker Or Driver? That the microbiome may also play a role in the spread of tumours to secondary sites (metastasis).

Time for a deep breath

If all this is going on in the intestines you might well ask “What about the lungs?” — because, and if you didn’t know you might guess, their job of extracting oxygen from the air we inhale means that they are covered with the largest surface area of mucosal tissue in the body. They are literally an open invitation to passing microorganisms — as we all know from the ease with which we pick up infections.

In view of what we know about gut bugs a rather obvious question is “Could the bug community play a role in lung cancer?” It’s a particularly pressing question because not only is lung cancer the major global cause of cancer death but 70% lung cancer patients have bacterial infections and these markedly influence tumour development and patient survival. Tyler Jacks, Chengcheng Jin and colleagues at the Massachusetts Institute of Technology approached this using a mouse model for lung cancer (in which two mutated genes, Kras and P53 drive tumour formation).

In short they found that germ-free mice (or mice treated with antibiotics) were significantly protected from lung cancer in this model system.

How bacteria can drive lung cancer in mice. Left: scheme of a lung with low levels of bacteria and normal levels of immune system cells. Right: increased levels of bacteria accelerate tumour growth by stimulating the release of chemicals from blood cells that in turn activate cells of the immune system to release other effector molecules that promote tumour growth. The mice were genetically altered to promote lung tumour growth (by mutation of the Kras and P53 genes). In more detail the steps are that the bacteria cause macrophages to release interleukins (IL-1 & IL-23) that stick to a sub-set of T cells (γδ T cells): these in turn release factors that drive tumour cell proliferation, including IL-22. From Jin et al. 2019.

As lung tumours grow in this mouse model the total bacterial load increases. This abnormal regulation of the local bug community stimulates white blood cells (T cells present in the lung) to make and release small proteins (cytokines, in particular interleukin 17) that signal to neutrophils and tumour cells to promote growth.

This new finding reveals that cross-talk between the local microbiota and the immune system can drive lung tumour development. The extent of lung tumour growth correlated with the levels of bacteria in the airway but not with those in the intestinal tract — so this is an effect specific to the lung bugs.

Indeed, rather than the players prominent in the intestines (Bs & Fs) that we met in Hitchhiker Or Driver?, the most common members of the lung microbiome are Staphylococcus, Streptococcus and Lactobacillus.

In a final twist Jin & Co. took bacteria from late-stage tumours and inoculated them into the lungs of mice with early tumours that then grew faster.

These experiments have revealed a hitherto unknown role for bacteria in cancer and, of course, the molecular signals identified join the ever-expanding list of potential targets for drug intervention.

References

Jin, C. et al. (2019). Commensal Microbiota Promote Lung Cancer Development via γδ T Cells. Cell 176, 998-1013.e16.

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Sticky Cancer Genes

 

In the previous blog I talked about Breath Biopsy — a new method that aims to detect cancers from breath samples. I noted that it could end up complementing liquid biopsies — samples of tumour cell DNA pulled out of a teaspoon of blood — both being, as near as makes no difference, non-invasive tests. Just to show that there’s no limit to the ingenuity of scientists, yet another approach to the detection problem has just been published — this from Matt Trau and his wonderful team at The University of Queensland.

This new method, like the liquid biopsy, detects DNA but, rather than the sequence of bases, it identifies an epigenetic profile — that is, the pattern of chemical tags (methyl groups) attached to bases. As we noted in Cancer GPS? cancer cells often have abnormal DNA methylation patterns — excess methylation (hypermethylation) in some regions, reduced methylation in others. Methylation acts as a kind of ‘fine tuner’, regulating whether genes are switched on or off. In the methylation landscape of cancer cells there is an overall loss of methylation but there’s an increase in regions that regulate the expression of critical genes. This shows up as clusters of methylated cytosine bases.

Rather helpfully, a little while ago in Desperately SEEKing … we talked about epigenetics and included a scheme showing how differences in methylation clusters can identify normal cells and a variety of cancers and how these were analysed in the computer program CancerLocator.

The Trau paper has an even better scheme showing how the patterns of DNA decoration differ between normal and cancer cells and how this ‘methylscape’ (methylation landscape) affects the physical behaviour of DNA.

How epigenetic changes affect DNA. Scheme shows methylation (left: addition of a methyl group to a cytosine base in DNA) in the process of epigenetic reprogramming in cancer cells. This change in the methylation landscape affects the solubility of DNA and its adsorption by gold (from Sina et al. 2018).

Critically, normal and cancer epigenomes differ in stickiness — affinity — for metal surfaces, in particular for gold. In a clever ploy this work incorporated a colour change as indicator. We don’t need to bother with the details — and the result is easy to describe. DNA, extracted from a small blood sample, is added to water containing tiny gold nanoparticles. The colour indicator makes the water pink. If the DNA is from cancer cells the water retains its original colour. If it’s normal DNA from healthy cells the different binding properties turns the water blue.

By this test the Brisbane group have been able to identify DNA from breast, prostate and colorectal cancers as well as from lymphomas.

So effective is this method that it can detect circulating free DNA from tumour cells within 10 minutes of taking a blood sample.

The aim of the game — and the reason why so much effort is being expended — is to detect cancers much earlier than current methods (mammography, etc.) can manage. The idea is that if we can do this not weeks or months but perhaps years earlier, at that stage cancers may be much more susceptible to drug treatments. Trau’s paper notes that their test is sensitive enough to detect very low levels of cancer DNA — not the same thing as early detection but suggestive none the less.

So there are now at least three non-invasive tests for cancer: liquid biopsy, Breath Biopsy and the Queensland group’s Methylscape, and in the context of epigenetics we should also bear in mind the CancerLocator analysis programme.

Matt Trau acknowledges, speaking of Methylscape, that “We certainly don’t know yet whether it’s the holy grail for all cancer diagnostics, but it looks really interesting as an incredibly simple universal marker for cancer …” We know already that liquid biopsies can give useful information about patient response to treatment but it will be a while before we can determine how far back any of these methods can push the detection frontier. In the meantime it would be surprising if these tests were not being applied to age-grouped sets of normal individuals — because one would expect the frequency of cancer indication to be lower in younger people.

From a scientific point of view it would be exciting if a significant proportion of ‘positives’ was detected in, say, 20 to 30 year olds. Such a result would, however, raise some very tricky questions in terms of what, at the moment, should be done with those findings.

Reference

Abu Ali Ibn Sina, Laura G. Carrascosa, Ziyu Liang, Yadveer S. Grewal, Andri Wardiana, Muhammad J. A. Shiddiky, Robert A. Gardiner, Hemamali Samaratunga, Maher K. Gandhi, Rodney J. Scott, Darren Korbie & Matt Trau (2018). Epigenetically reprogrammed methylation landscape drives the DNA self-assembly and serves as a universal cancer biomarker. Nature Communications 9, Article number: 4915.

I Know What I Like

 

I guess most of us at some time or other will have stood gazing at a painting for a while before muttering ‘Wow, that’s awesome’ or words to that effect if we’re not into the modern argot. Some combination of subject, style and colour has turned our crank and left us thinking we wouldn’t mind having that on our kitchen wall.

Given the thousands of years of man’s daubing and the zillions of forms that have appeared from pre-historic cave paintings through Eastern painting, the Italian Renaissance, Impressionism, Dadaism and the rest to Pop Art, it’s amazing that everyone isn’t a fanatic for one sort or another. The sane might say the field’s given itself a bad name by passing off tins of baked beans, stuff thrown at a canvas and unmade beds as ‘art’ but, even so, it seems odd that it remains a minority obsession.

Can science help?

Science is wonderful, as we all know, but the notion that it might arouse the collective artistic lust seems fanciful. Nevertheless, unnoticed by practically everyone, our vast smorgasbord of smears has been surreptitiously joined over the last 30 years by a new form: an ever-expanding avalanche of pics created by biologists trying to pin down how animals work at the molecular level. The crucial technical development has been the application of fluorescence in the life sciences: flags that glow when you shine light on them and can be stuck on to molecules to track what goes on in cells and tissues. The pioneer of this field was Roger Tsien who died, aged 64, in 2016.

Because this has totally transformed cell biology we’ve run into lots of brilliant examples in these pages — recently in Shifting the Genetic Furniture, in Caveat Emptor and John Sulston: Biologist, Geneticist and Guardian of our Heritage and in the use of red and green tags for picking out individual types of proteins that mark mini-cells within cells in Lorenzo’s Oil for Nervous Breakdowns.

To mark the New Year this piece looks at science from a different angle by focussing not on the scientific story but on the beauty that has become a by-product of this pursuit of knowledge.

Step this way: entrance free

So let’s take a stroll through our science gallery and gaze at just a few, randomly selected works of art.

  1. Cells grown in culture:

This was one of the first experiments in my laboratory using fluorescently labelled antibodies, carried out by a student, Emily Hayes, so long ago that she now has a Ph.D., a husband and two children. The cells are endothelial cells (that line blood vessels). Blue: nuclei; green: F-actin; red: Von Willebrand factor, a protein marker for endothelium.

 

  1. Two very recent images taken by my colleague Roderik Kortlever of a senescent mouse fibroblast and of mouse breast tissue:

 

 

 

 

 

 

3. Waves of calcium in firing neurons:

One of my fondest memories is helping to do the first experiment that measured the level of calcium within a cell, carried out with my colleague the late Roger Tsien and two other friends. I only grew the cells: Roger had designed and made the molecule, quin2. We didn’t know it at the time but Roger’s wonder molecule was the first of many intracellular ‘reporters.’ Roger shared the 2008 Nobel Prize in Chemistry for his discovery and development of the green fluorescent protein with organic chemist Osamu Shimomura and neurobiologist Martin Chalfie.

This wonderful video of a descendant of quin2 in nerve cells was made in Dr. Sakaguchi’s lab at Iowa State University.

 

4. Calcium wave flooding a fertilized egg: Taro Kaneuchi and colleagues at the Tokyo Metropolitan University:

Click for a time-lapse movie of an egg cell that has been artificially stimulated to show the kind of calcium change that happens at fertilization. In this time-lapse movie the calcium level reaches a maximum signal intensity after about 30 min before gradually decreasing to the basal level.

 

5. The restless cell (1):

This movie shows how protein filaments in cells can continuously break down and reform – called treadmilling. Visualised in HeLa cells using a green fluorescent protein that sticks to microtubules (tubular polymers made up of the protein tubulin) by HAMAMATSU PHOTONICS.

 

6. The restless cell (2):

This movie shows how mitochondria (organelles within the cell) are continuously changing shape and moving within the cell’s interior (cytosol). Red marks the mitochondria; green DNA within the nucleus. HAMAMATSU PHOTONICS.

 

7. Cell division:

Pig kidney cells undergoing mitosis. Red marks DNA (nucleus); green is tubulin: HAMAMATSU PHOTONICS.

 

8. DNA portrait of Sir John Sulston by Marc Quinn commissioned by the National Portrait Gallery:This image looks a bit drab in the present context but in some ways it’s the most dramatic of all. John Sulston shared the 2002 Nobel Prize in Physiology or Medicine with Sydney Brenner and Robert Horvitz for working out the cell lineage of the roundworm Caenorhabditis elegans (i.e. how it develops from a single, fertilized egg to an adult). He went on to sequence the entire DNA of C. elegans. Published in 1998, it was the first complete genome sequence of an animal — an important proof-of-principle for the Human Genome Project that followed and for which Sulston directed the British contribution at the Sanger Centre in Cambridgeshire, England. The project was completed in 2003.

The portrait shows colonies of bacteria in a jelly that, together, carry all Sulston’s DNA. This represents DNA cloning in which DNA fragments, taken up by bacteria after insertion into a circular piece of DNA (a plasmid), are multiplied to give many identical copies for sequencing.

 

9. “Brainbow” mice by Tamily Weissman at Harvard University:

The science behind this astonishing image builds on the work of Roger Tsien. Mice are genetically engineered to carry three different fluorescent proteins corresponding to the primary colours red, yellow and blue. Within each cell recombination occurs randomly, giving rise to different colours. The principle of mixing primary colours is the same as used in colour televisions.  In this view individual neurons in the brain (specifically a layer of the hippocampus) project their dendrites into the outer layer. Other magnificent pictures can be seen in the Cell Picture Show.

It’s certainly science – but is it art?

A few years ago the Fitzwilliam Museum in Cambridge staged Vermeer’s Women, an exhibition of key works by Johannes Vermeer and over thirty other masterpieces from the Dutch ‘Golden Age’. I tried the experiment of standing in the middle of each room and picking out the one painting that, from a distance, most caught my amateur eye. Funny thing was: not one turned out to be by the eponymous star of the show! Wondrous though Vermeer’s paintings were, the ones that really took my fancy were by Pieter de Hooch, Samuel van Hoogstraten and Nicolaes Maes, guys I’d never heard of.

Which made the point that you don’t need to be a big cheese to make a splash and that in the new Dutch Republic of the 17th century, the most prosperous nation in Europe, there was enough money to keep a small army of splodgers in palettes and paint. Skillful and incredibly patient though these chaps were, they simply used the tools available to paint what they saw in the world before them — as for the most part have artists down the ages.

But hang on! Isn’t that what we’ve just been on about? Scientists applying enormous skill and patience in using the tools they’ve developed to visualize life — to image what Nature lays before them. So the only difference between the considerable army of biological scientists around the world making a new art form and the Old Masters is that the newcomers are unveiling life — as opposed to the immortalizing a rather dopy-looking aristocrat learning to play the virginal or some-such.

Controversial?

Not really. Let’s leave the last word to Roger Tsien. In our final picture there are eight bacterial colonies each expressing a different colour of fluorescent protein arranged to grow as a San Diego beach scene in a Petri dish. It became the logo of Roger’s laboratory.

Shifting the Genetic Furniture

 

Readers of these pages will know very well that cells are packets of magic. Of course, we often describe them in the simplest terms: ‘Sacs of gooey stuff with lots of molecules floating around.’ And it’s true that we know a lot about the protein pathways that capture energy from the food we eat and about the machinery that duplicates genetic material, makes new proteins and sustains life. Even so, although we’ve worked out much molecular detail, we have scarcely a clue about how ‘stuff’ in cells is organised. How do the tens of thousands of different types of proteins find their places in the seemingly chaotic jumble of a cell so that they can do their job? If that remains a mystery there’s an even more perplexing one in the form of the nucleus. That’s a smaller sac (i.e. a compartment surrounded by a membrane) that is home to most of our genetic material — i.e. DNA.

Sizing up the problem

It’s easy to see why evolution came up with the idea of a separate enclosure for DNA which only has to do two things: reproduce itself and enable regions of its four base code to be transcribed into molecules that can cross the nuclear membrane to be translated into proteins in the body of the cell. But here’s the puzzle. The nucleus is very small and there’s an awful lot of DNA — over 3,000 million bases in each of the two strands of human DNA (and, of course, two complete sets of chromosomes go to make up the human genome) — so 2 metres of it in every cell. A rather pointless exercise, unless you go in for pub quizzes, is to work out the length of all your DNA if you put it together in a single string. 1013 cells (i.e. 1 followed by 13 zeros) in your body: 2 metres per cell. Answer: your DNA would stretch to the sun and back 67 times.

Mmm. More relevantly, the nucleus of a cell is typically about 6 micrometres (µm) in diameter — that’s six millionths of a metre (6/1,000,000 metre), into which our 2 metres must squeeze.

Time for some serious packing to be done but it’s not just a matter of stuffing it in any old how and sitting on the lid. As we’ve just noted, every time cells divide all the DNA has to be replicated and regions (i.e. genes) are continually being “read” to make proteins. So the machinery in the nucleus has to be able to get at specific regions of DNA and disentangle them sufficiently for code reading. Part of evolution’s solution to these problems has been to add proteins called histones to DNA (the term chromosome refers to DNA together with histone packaging proteins and other proteins). To understand how this leads to “more being less”, consider DNA as a length of cotton. If you just scrunch the cotton up into a ball you get a tangled mess. But if you use cotton reels (aka histones — two or three hundred million per cell), you can reduce the great length to smaller, more organized blocks — which is just as well because they’re all that stands between life and a tangled mess.

Thinking of histones as cotton reels helps a bit in thinking about how the nucleus achieves the seemingly impossible but the fact of the matter is that we have no real idea about how DNA is unravelling is controlled so that the two strands can be unzipped and replicated, yet alone the way in which starting points for reading genes are found by proteins.

Undeterred by our profound ignorance Haifeng Wang and colleagues at Stanford University have just done something really amazing. They came up with a way of moving regions of DNA from the jumble of the nuclear interior to the membrane and they showed that this can change the activity of genes. They used CRISPR (that we described in Re-writing the Manual of Life) to insert a short piece of DNA next to a chosen gene. The insert was tagged with a protein designed to attach to a hormone that also binds to a protein (called emerin) that sits in the nuclear membrane. So the idea was that when the hormone is added to cells it can hook on to the DNA tag and, by attaching to emerin, can drag the chosen gene to the membrane. The coupling agent is a plant hormone (abscisic acid) although it also occurs in other species, including humans. Wang & Co christened their method CRISPR-GO for CRISPR-Genome Organizer.

Tagging a DNA insert with a protein so that a coupling molecule can pull a region of DNA to a protein in the membrane of the nucleus. From Wang et al., 2018.

Repositioning regions of DNA in the nucleus. DNA is labeled blue which defines the shape of the nucleus. Red dots are specific genes before (left) and after (right) adding the coupling agent. From Pennisi 2018.

How did CRISPR-GO go?

Astonishingly well. Not only could it shift tagged DNA from the interior to the membrane of the nucleus but the rearrangements could change the way cells behaved. Depending on which regions were moved and where to, cells grew more slowly or more rapidly.

So this is a really remarkable technical feat — but it’s not just molecular pyrotechnics for fun. It looks as though this approach may offer at long last a way of dissecting how cells go about getting a controlled response out of the mind-boggling complexity that is their genetic material.

References

Wang, H. et al. (2018). CRISPR-Mediated Programmable 3D Genome Positioning and Nuclear Organization. Cell 175, 1405-1417.

Pennisi, E. (2018). Moving DNA to a different part of the nucleus can change how it works. Science Oct. 11th.

Food Fix For Pharma Failure

 

If you held a global quiz, Question: “Which biological molecules can you name?” I guess, setting aside ‘DNA‘, the top two would be insulin and glucose. Why might that be? Well, the World Health Organization reckons diabetes is the seventh leading cause of death in the world. The number of people with diabetes has quadrupled in the last 30 years to over 420 million and, together with high levels of blood glucose (sugar), it kills nearly four million a year.

There are two forms of diabetes: in both the level of glucose in the blood is too high. That’s normally regulated by the hormone insulin, made in the pancreas. In Type 1 diabetes insulin isn’t made at all. In Type 2 insulin is made but doesn’t work properly.

When insulin is released into the bloodstream it can ‘talk’ to cells by binding to protein receptors that span cell membranes. Insulin sticks to the outside, the receptor changes shape and that switches on signalling pathways inside the cell. One of these causes transporter molecules to move into the cell membrane so that they can carry glucose from the blood into the cell. When insulin doesn’t work it is this circuit that’s disrupted.

Insulin signalling. Insulin binds to its receptor which transmits a signal across the cell membrane, leading to the activation of the enzyme PIK3. This leads indirectly to the movement of glucose transporter proteins to the cell membrane and influx of glucose.

So the key thing is that, under normal conditions, when the level of blood glucose rises (after eating) insulin is released from the pancreas. Its action (via insulin receptors on target tissues e.g., liver, muscle and fat) promotes glucose uptake and restores normal blood glucose levels. In diabetes, one way or another, this control is compromised.

Global expansion

Across most of the world the incidence of diabetes, obesity and cancer are rising in parallel. In the developed world most people are aware of the link between diabetes and weight: about 90% of adults with diabetes are overweight or obese. Over 2 billion adults (about one third of the world population) are overweight and nearly one third of these (31%) are obese — more than the number who are underweight. The cause and effect here is that obesity promotes long-term inflammation and insulin resistance — leading to Type 2 diabetes.

Including cancer

The first person who seems to have spotted a possible connection between diabetes and cancer was the 19th-century French surgeon Theodore Tuffier. He was a pioneer of lung and heart surgery and of spinal anaesthesia and he’s also a footnote in the history of art by virtue of having once owned A Young Girl Reading, one of the more famous oil paintings produced by the prolific 18th-century artist Jean-Honoré Fragonard (if you want to see it head for the National Gallery of Art in Washington DC). Tuffier noticed that having type 2 diabetes increased the chances of patients getting some forms of cancer and pondered whether there was a relationship between diabetes and cancer.

It was a good question then but it’s an even better one now when this duo have become dominant causes of morbidity and mortality worldwide.

We now know that being overweight increases the risk of a wide range of cancers including two of the most common types — breast and bowel cancers. Unsurprisingly, the evidence is also clear that diabetes (primarily type 2) is associated with increased risk for some cancers (liver, pancreas, endometrium, colon and rectum, breast, bladder).

With all this inter-connecting it’s perhaps not surprising that the pathway by which insulin regulates glucose also talks to signalling cascades involved in cell survival, growth and proliferation — in other words, potential cancer initiators. The central player in all this is a protein called PIK3 (it’s an enzyme that adds phosphate groups (so it’s a ‘kinase’) to a lipid called phosphatidylinositol bisphosphate, an oily, water-soluble component of the plasma membrane). It’s turned out that PIK3 is one of the most commonly mutated genes in human cancers — e.g., PIK3 mutations occur in 25–40% of all human breast cancers.

Signalling pathways switched on by mutant PIK3. A critical upshot is the activation of cell survival and growth that leads to cancer.

Accordingly, much effort has gone into producing drugs to block the action of PIK3 (or other steps in this signal pathway). The problem is that these have worked as cancer treatments either very variably or not at all.

The difficulty arises from the inter-connectivity of signalling that we’ve just described: a drug blocking insulin signalling causes the liver to release glucose and prevents muscle and fats cells from taking up glucose. Result: blood sugar levels rise (hyperglycaemia). This effect is usually transient as the pancreas makes more insulin that restores normal glucose levels.

Blockade of mutant PIK3 by an inhibitor. This blocks the route to cancer but glucose levels rise in the circulation (hyperglycaemia) promoting the release of insulin (top). Insulin can now signal through the normal pathway (bottom), overcoming the effect of the anti-cancer drug. Note that the cell has two copies of the PIK3 gene/protein, one of which is mutated, the other remaining normal.

Is our journey really necessary?

By now you might be wondering whether there is anything that makes grappling with insulin signaling worth the bother. Well, there is — and here it is. It’s a recent piece of work by Benjamin Hopkins, Lewis Cantley and colleagues at Weill Cornell Medicine, New York who looked at ways of getting round the insulin feedback response so that the effect of PIK3 inhibitors could be boosted.

Sketch showing the effect of diet on the potency of an anti-cancer drug in mice. The red line represents normal tumour growth. The black line shows the effect of PIK3 blockade when the mice are on a ketogenic diet: tumour growth is suppressed. On a normal diet the drug alone has only a slight effect on tumour growth. Similar results were obtained in a variety of model tumours (Hopkins et al., 2018).

They first showed that, in a range of model tumours in mice, insulin feedback caused by blockade of PIK3 was sufficient to switch on signalling even in the continued presence of anti-PIK3 drugs. The really brilliant result was that changing the diet of the mice could offset this effect. Switching the mice to a high-fat, adequate-protein, low-carbohydrate (sugar) diet essentially stopped the growth of tumours driven by mutant PIK3 treated with PIK3 blockers. This is a ketogenic (or keto) diet, the idea being to deplete the store of glucose in the liver and hence limit the rise in blood glucose following PIK3 blockade.

Giving the mice insulin after the drug drastically reduces the effect of the PIK3 inhibitor, supporting the idea that that a keto diet improves responses to PIK3 inhibitors by reducing blood insulin and hence its capacity to switch on signalling in tumour cells.

A few weeks prior to the publication of the PIK3 results another piece of work showed that adding the amino acid histidine to the diet of mice can increase the effectiveness of the drug methotrexate against leukemia. Methotrexate was one of the first anti-cancer agents to be made and has been in use for 70 years.

These are really remarkable results — as far as I know the first time diet has been shown to influence the efficacy of anti-cancer drugs. It doesn’t mean that all tumours with mutations in PIK3 have suddenly become curable or that the long-serving methotrexate is going to turn out to be a panacea after all — but it does suggest a way of improving the treatment of many types of tumour.

References

Hopkins, B.D. et al. (2018). Suppression of insulin feedback enhances the efficacy of PI3K inhibitors. Nature 560, 499-503.

Kanarek, N. et al. (2018). Histidine catabolism is a major determinant of methotrexate sensitivity. Nature 559, 632–636.

Taking Aim at Cancer’s Heart

 

Cancer is a unique paradox. At one level it’s as easy as can be to describe: damage to DNA (aka mutations) drives cells to behave abnormally — to make more of themselves when they shouldn’t.

But we all know that cancer’s fiendishly complicated — at least at the level of fine detail. Over the last decade or so the avalanche of sequenced DNA has revealed that every cell in a tumour is different: compare one cell to its neighbour and you’ll find variations in the individual units (the bases A, C, G & T) that make up the chains of DNA.

It’s a nightmare: every cancer is different so we need an infinite number of treatments to control or cure each one. Time to give up and retire to the pub.

Drivers and passengers

Not quite. DNA sequencing has also revealed that, amongst all the genetic mayhem, some mutations are more important than others. The movers and shakers have been dubbed ‘drivers’: those that come along for the ride are ‘passengers’. The hangers-on are heavily in the majority but, even so, several hundred drivers (i.e. mutated genes that give rise to abnormal proteins) have been identified. As it needs a group of drivers to work together to make a cancer we still have the problem that the number of critical combinations that can arise is essentially infinite.

One way of reducing the scale of the problem has been to look at what ‘driver’ proteins do in cells and to target those acting at key points to push cell proliferation beyond the normal.

Playing games

Just recently Giulio CaravagnaAndrea Sottoriva and colleagues at the Institute of Cancer Research, London and the University of Edinburgh have come up with a different approach. The idea goes back to the 1950s when a clever chap from Kansas by the name of Arthur Samuel came up with a program for IBM’s first commercial computer so that it could play draughts (checkers as our American friends call it) in its spare time. The program defined the patterns that could be formed by the pieces on the chequerboard so that, given enough of these, IBM 701 could indicate the optimal moves. Samuel called this machine learning, a precursor of the idea of artificial intelligence.

Perhaps the most famous moment in this saga came in 1997 when a later IBM computer, Deep Blue, beat the then world chess champion Garry Kasparov. Unsurprisingly, Kasparov was a bit miffed and accused IBM of cheating — to wit, getting a human to tell the machine what to do. Let’s hope that in the end he came to terms with the fact that Deep Blue could crank through 200 million positions per second and, however many games Grandmasters have in their heads, they can’t compete with that.

The cancer team realized that the mutations driving the evolution of cancer cells emerge as patterns in the sequence of DNA as a cell moves towards becoming independent of normal controls. Think of each cancer as a family tree of mutations, the key question being which branch leads to the most potent combination.

To pick out these patterns they applied a machine-learning approach known as transfer learning to the DNA sequences from a large number of cancers. They called this ‘repeated evolution in cancer’ — REVOLVER — aimed at picking out mutation patterns at the heart of cancer that foreshadow future genetic changes and can be used to predict how they will evolve.

Identifying patterns of mutation common to different tumours.

Samples are taken from different regions of a patient’s tumour (represented by the coloured dots). Their DNA sequences will have multiple variations that can mask underlying patterns of driver mutations present in some subgroups. The five trees show mutations picked up in those patients. REVOLVER uses transfer learning to screen the sequence data from many patients and pull out evolutionary trajectories shared by subgroups. The dotted red lines highlight common patterns that are represented in the lower strip. From Caravagna et al. 2018.

REVOLVER was applied to sequences from lung, breast, kidney and bowel cancers but there’s no reason it shouldn’t work with other tumours. The big attraction is that if these mini-sequence mutation patterns can be associated generally with how a given tumour develops they should help to inform treatment options and predict survival.

We have in the past referred to the ways cancers evolve as ‘genetic roulette’ — so perhaps it’s appropriate if game-playing computer programs turn out to be useful in teasing out behavioural clues.

Reference

Caravagna, G. et al. (2018). Detecting repeated cancer evolution from multi-region tumor sequencing data. Nature Methods 15, 707–714.

Now wash your hands!

 

You must have spent the last 20 years on a distant planet if you’re unaware that we’re heading for Antibiotic Armaggedon — the rise of “Superbugs”, i.e., bacteria resistant to once-successful medication. Microbes resistant to multiple antimicrobials are called multidrug resistant. It’s a desperate matter because it means trivial infections may become fatal and currently safe surgical procedures may become dangerous.

Time-line of the discovery of different antibiotic classes in clinical use. The key point is that the last antibiotic class to become a successful treatment was discovered in 1987.

What’s the problem?
It’s 30 years since we came up a new class of antibiotics. The golden age launched by Fleming’s celebrated discovery of penicillin is long gone and while the discovery curve has drifted ever downwards since 1960 the bugs have been busy.

Just how busy a bug can be was shown by a large-scale experiment carried out by Roy Kishony and friends. They built a “Mega-Plate” — a Petri Dish 2 ft by 4 ft filled with a jelly for the bacteria to grow in. The bugs were seeded into channels at either end so they would grow towards the middle. The only thing stopping them was four channels dosed with antibiotic at increasing concentrations — 10 times more in each successive channel.

The bugs grow until they hit a wall of antibiotic. There they pause for a think — and, after a bit, an intrepid little group start to make their way into the higher dose of drug. Gradually the number of groups expand until a tidal wave sweeps over that barrier. This is repeated at each new ‘wall’ — four times until the whole tray is a bug fest.

When they pause at each new ‘wall’ they’re not ‘thinking’ of course. They’re just picking up random mutations in their DNA until they are able to advance into the high drug environment. So this experiment is a fantastic visual display of bugs becoming drug-resistant. And it’s terrifying because it takes about 11 days for them to overcome four levels of drug. It’s even more scary in the speeded-up movie as that lasts less than two minutes.

Sound familiar?
It should do as this is a cancer column and readers will know that cancers arise by picking up mutations. To highlight the similarities the picture below is the left-hand half of the bug tray with new colonies shown as linked dots. You could perfectly well think of these as early stage cancer cells acquiring mutations in ‘driver’ genes that push them towards tumour formation.

So that’s pretty scary too and the only good news is that animal cells reproduce much more slowly than bacteria. The fastest they can manage is about 48 hours to grow and divide into two new cells and for many it’s much slower than that. Bugs, on the other hand, can do it in 20 minutes if you feed them enough of the right stuff.

Which is why we don’t all get zonked by cancer at an early age.

The evolution of bacteria on a “Mega-Plate” Petri Dish. The vertical red lines mark the boundaries of increasing antibiotic concentrations. You could equally think of each dot that represents a new bacterial colony being early stage cancer cells acquiring mutations in ‘driver’ genes (white arrows) that push them towards tumour formation. From Roy Kishony’s Laboratory at Harvard Medical School.

Enough of that!
But for once I don’t want to talk about cancer but about a really fascinating piece of work that caught my eye in the journal Cell Reports. It’s by Gianni Panagiotou, Kang Kang and colleagues from The University of Hong Kong and The Hans Knöll Institute, Jena, Germany and it’s all about their travels on the Hong Kong MTR (Mass Transit Railway). This is the network of over 200 km of railway lines with 159 stations that serves the urbanised areas of Hong Kong IslandKowloon, and the New Territories and has a cross- border connection to the neighboring city of Shenzhen in mainland China.

An MTR train on the Tung Chung line that links Lantau Island with Hong Kong Island.

Being scientists of course they weren’t just having a day out. They wanted to know the contents of the microbiome that they and their fellow travellers picked up on the palms of their hands when riding the rails. ‘Microbiome’ means all of the collection of microorganisms — though in practice this is almost entirely bacteria. So they swabbed the palms of volunteers and then threw the full power of modern DNA sequencing and genetic analysis at what they’d scraped off. Or, as they put it: “We conducted a metagenomic study of the Hong Kong MTR system.”

And if you’re thinking it might be possible to take a trip on the Hong Kong Metro without grabbing a handrail or otherwise engaging in what on the London Underground used to be called ‘strap-hanging’ you clearly haven’t tried it!

Hong Kong MTR.

 

The MTR System and Sampling Procedure. Left: The eight urban lines studied: the Airport Express line and Disneyland Resort branch were excluded. The Central-Hong Kong station and the cross-border rail stations connecting with the MTR and the Shenzhen metro system are labeled. Right: The sampling procedure included handwashing, handrail touching for 30 min and swabbing. From Kang et al. 2018.

Hold very tight please! 

It’s going to become a seriously bumpy ride. The major findings were:

  1. Four groups (phyla) of bacteria dominated: Actinobacteria [51%], Proteobacteria [27%], Firmicutes [11%] and Bacteroidetes [2%]. Followers of this blog will be delighted to spot the last two (B & F) as we’ve met them several times before (in Hitchhiker Or Driver?, Fast Food Fix Focuses on Fibre, Our Inner Self, The Best Laid Plans In Mice and Men, and, of course, in it’s a small world) — that’s how important they are in the context of cancer.
  2. The dominant organism (29% of the community) was P. acnes (one of the Actinobacteria — it’s the bug linked to the skin condition of acne).
  3. Some non-human-associated species (e.g., soil organisms) also popped up that varied enormously in amount from day to day — perhaps because of weather conditions (e.g., humidity).
  4. Variation in the make-up of the microbial communities picked up depended, more than anything else, on the time of day. There was a marked decrease in diversity in afternoon samples compared with those taken in the morning.
  5. Specific species of bacteria associated with individual metro lines. That is, sets of bug types are relatively abundant on a given line compared with all other lines, giving a kind of line-specific signature — though the distinction declines from morning to afternoon. The most physically isolated line, MOS (Ma On Shan), had a greater number of signature species. The MOS runs entirely above ground alongside the Shing Mun Channel, a polluted brackish river, and its ‘signature’ includes bacteria found in sewage.
  6. All of which brings us to bugs with antibiotic resistance genes (ARGs). Across the network 136 ARG families were detected including 24 that are clinically important. Strikingly, lines closer to Shenzhen (ER (East Rail) and MOS) tend to have higher ARG input during the day. Critically, the ER line a.m. signatures become p.m.-enriched in all MTR lines far from Shenzhen — that is, these ARG families spread over the network during the day.

Simplified map of the Hong Kong MTR indicating how antibiotic resistance genes spread during the day from the ER and MOS lines to the entire network. Tetracycline resistance genes: tetA, tetO, tetRRPP and tetMWOS; vancomycin resistance genes: vanC, vanX. From Kang et al. 2018.

These results clearly suggest that the ER line, the only cross-border line linked to mainland China, may be a source of clinically important ARGs, especially against tetracycline, a commonly used antibiotic in China’s swine feedlots. Antibiotics, including tetracycline, can be detected in the soil in the Pearl River Delta area where the cities of Hong Kong and Shenzhen are located.

It should be said that this is by no means the first survey of bugs on rails. Notable ones have looked at the New York and Boston metro systems and they too revealed the potential health risks of the bug communities found on trains and in the stations, including the presence of pathogens and antibiotic resistance. The Boston survey highlighted that different types of materials have surfaces that are preferred by different microbes with high variation in functional capacity and pathogenic potential.

One obvious suggestion from these studies is that world-wide we could do a lot to improve sanitation, e.g., by having hand sanitizer dispensers in all sensible places (at the exits of metro, railway and bike-sharing stations and airports and of course in hospitals). The Hong Kong data are seriously frightening and most people seem blissfully unaware that the invisible world they reveal carries the potential for the destruction of us all.

But, as ever, there’s two sides to the matter. We’ve evolved over millions of years to live with bugs and they with us. However you wash your hands you won’t get rid of every bug and anyway, as what’s-his-name almost says, “They’ll be back!” We all carry around micro-organisms that can be fatal if they get to the wrong place. But, if you’re reasonably fit, there’s a lot to be said for simply following sensible, basic hygiene rules with a philosophy of ‘live and let live.’

Have a nice day commuters, wherever you are!

References

Kang K., et al. (2018). The Environmental Exposures and Inner- and Intercity Traffic Flows of the Metro System May Contribute to the Skin Microbiome and Resistome. Cell Reports 24, 1190–1202.

Wu, N., Qiao, M., Zhang, B., Cheng, W.D., and Zhu, Y.G. (2010). Abundance and diversity of tetracycline resistance genes in soils adjacent to representative swine feedlots in China. Environ. Sci. Technol. 44, 6933–6939.

Li, Y.W., Wu, X.L., Mo, C.H., Tai, Y.P., Huang, X.P., and Xiang, L. (2011). Investigation of sulfonamide, tetracycline, and quinolone antibiotics in vegetable farmland soil in the Pearl River Delta area, southern China. J. Agric. Food Chem. 59, 7268–7276.

Leung, M.H., Wilkins, D., Li, E.K., Kong, F.K., and Lee, P.K. (2014). Indoor-air microbiome in an urban subway network: diversity and dynamics. Appl. Environ. Microbiol. 80, 6760–6770.

Robertson, C.E., Baumgartner, L.K., Harris, J.K., Peterson, K.L., Stevens, M.J., Frank, D.N., and Pace, N.R. (2013). Culture-independent analysis of aerosol microbiology in a metropolitan subway system. Appl. Environ. Microbiol. 79, 3485–3493.

Afshinnekoo, E., Meydan, C., Chowdhury, S., Jaroudi, D., Boyer, C., Bernstein, N., Maritz, J.M., Reeves, D., Gandara, J., Chhangawala, S., et al. (2015). Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics. Cell Syst 1, 72–87.

Hsu, T., Joice, R., Vallarino, J., Abu-Ali, G., Hartmann, E.M., Shafquat, A., Du- Long, C., Baranowski, C., Gevers, D., Green, J.L., et al. (2016). Urban Transit System Microbial Communities Differ by Surface Type and Interaction with Humans and the Environment. mSystems 1, e00018–e00016.

Caveat Emptor

 

It must be unprecedented for publication of a scientific research paper to make a big impact on a significant sector of the stock market. But, in these days of ‘spin-off’ companies and the promise of unimaginable riches from the application of molecular biology to every facet of medicine and biology, perhaps it was only a matter of time. Well, the time came with a bang this June when the journal Nature Medicine published two papers from different groups describing essentially the same findings. Result: three companies (CRISPR Therapeutics, Editas Medicine and Intellia) lost about 10% of their stock market value.

I should say that a former student of mine, Anthony Davies, who runs the Californian company Dark Horse Consulting Inc., mentioned these papers to me before I’d spotted them.

What on earth had they found that so scared the punters?

Well, they’d looked in some detail at CRISPR/Cas9, a method for specifically altering genes within organisms (that we described in Re-writing the Manual of Life).

Over the last five years it’s become the most widely used form of gene editing (see, e.g., Seeing a New World and Making Movies in DNA) and, as one of the hottest potatoes in science, the subject of fierce feuding over legal rights, who did what and who’s going to get a Nobel Prize. Yes, scientists do squabbling as well as anyone when the stakes are high.

Nifty though CRISPR/Cas9 is, it has not worked well in stem cells — these are the cells that can keep on making more of themselves and can turn themselves in other types of cell (i.e., differentiate — which is why they’re sometimes called pluripotent stem cells). And that’s a bit of a stumbling block because, if you want to correct a genetic disease by replacing a defective gene with one that’s OK, stem cells are a very attractive target.

Robert Ihry and colleagues at the Novartis Institutes for Biomedical Research got over this problem by modifying the Cas9 DNA construct so that it was incorporated into over 80% of stem cells and, moreover, they could switch it on by the addition of a drug. Turning on the enzyme Cas9 to make double-strand breaks in DNA in such a high proportion of cells revealed very clearly that this killed most of them.

When cells start dying the prime suspect is always P53, a so-called tumour suppressor gene, switched on in response to DNA damage. The p53 protein can activate a programme of cell suicide if the DNA cannot be adequately repaired, thereby preventing the propagation of mutations and the development of cancer. Sure enough, Ihry et al. showed that in stem cells a single cut is enough to turn on P53 — in other words, these cells are extremely sensitive to DNA damage.

Gene editing by Cas9 turns on P53 expression. Left: control cells with no activation of double strand DNA breaks; right: P53 expression (green fluorescence) several days after switching on expression of the Cas9 enzyme. Scale bar = 100 micrometers. From Ihry et al., 2018.

In a corresponding study Emma Haapaniemi and colleagues from the Karolinska Institute and the University of Cambridge, using a different type of cell (a mutated line that keeps on proliferating), showed that blocking P53 (hence preventing the damage response) improves the efficiency of genome editing. Good if you want precision genome editing by risky as it leaves the cell vulnerable to tumour-promoting mutations.

Time to buy?!

As ever, “Let the buyer beware” and this certainly isn’t a suggestion that you get on the line to your stockbroker. These results may have hit share prices but they really aren’t a surprise. What would you expect when you charge uninvited into a cell with a molecular bomb — albeit one as smart as CRISPR/Cas9. The cell responds to the DNA damage as it’s evolved to do — and we’ve known for a long time that P53 activation is exquisitely sensitive: one double-strand break in DNA is enough to turn it on. If the damage can’t be repaired P53’s job is to drive the cell to suicide — a perfect system to prevent mutations accumulating that might lead to cancer. The high sensitivity of stem cells may have evolved because they can develop into every type of cell — thus any fault could be very serious for the organism.

It’s nearly 40 years since P53 was discovered but for all the effort (over 45,000 research papers with P53 in the title) we’re still remarkably ignorant of how this “Guardian of the Genome” really works. By comparison gene editing, and CRISPR/Cas9 in particular, is in its infancy. It’s a wonderful technique and it may yet be possible to get round the problem of the DNA damage response. It may even turn out that DNA can be edited without making double strand breaks.

So maybe don’t rush to buy gene therapy shares — or to sell them. As the Harvard geneticist George Church put it “The stock market isn’t a reflection of the future.” Mind you, as a founder of Editas Medicine he’d certainly hope not.

References

Ihry, R.J. et al. (2018). p53 inhibits CRISPR–Cas9 engineering in human pluripotent stem cells. Nature Medicine, 1–8.

Haapaniemi, E. et al. (2018). CRISPR–Cas9 genome editing induces a p53-mediated DNA damage response. Nature Medicine (2018) 11 June 2018.

Fantastic Stuff

 

It certainly is for Judy Perkins, a lady from Florida, who is the subject of a research paper published last week in the journal Nature Medicine by Nikolaos Zacharakis, Steven Rosenberg and their colleagues at the National Cancer Institute in Bethesda, Maryland. Having reached a point where she was enduring pain and facing death from metastatic breast cancer, the paper notes that she has undergone “complete durable regression … now ongoing for over 22 months.”  Wow! Hard to even begin to imagine how she must feel — or, for that matter, the team that engineered this outcome.

How was it done?

Well, it’s a very good example of what I do tend to go on about in these pages — namely that science is almost never about ‘ground-breaking breakthroughs’ or ‘Eureka’ moments. It creeps along in tiny steps, sideways, backwards and sometimes even forwards.

You may recall that in Self Help – Part 2, talking about ‘personalized medicine’, we described how in one version of cancer immunotherapy a sample of a patient’s white blood cells (T lymphocytes) is grown in the lab. This is a way of either getting more immune cells that can target the patient’s tumour or of being able to modify the cells by genetic engineering. One approach is to engineer cells to make receptors on their surface that target them to the tumour cell surface. Put these cells back into the patient and, with luck, you get better tumour cell killing.

An extra step (Gosh! Wonderful GOSH) enabled novel genes to be engineered into the white cells.

The Shape of Things to Come? took a further small step when DNA sequencing was used to identify mutations that gave rise to new proteins in tumour cells (called tumour-associated antigens or ‘neoantigens’ — molecular flags on the cell surface that can provoke an immune response – i.e., the host makes antibody proteins that react with (stick to) the antigens). Charlie Swanton and his colleagues from University College London and Cancer Research UK used this method for two samples of lung cancer, growing them in the lab to expand the population and testing how good these tumour-infiltrating cells were at recognizing the abnormal proteins (neo-antigens) on cancer cells.

Now Zacharakis & Friends followed this lead: they sequenced DNA from the tumour tissue to pinpoint the main mutations and screened the immune cells they’d grown in the lab to find which sub-populations were best at attacking the tumour cells. Expand those cells, infuse into the patient and keep your fingers crossed.

Adoptive cell transfer. This is the scheme from Self Help – Part 2 with the extra step (A) of sequencing the breast tumour. Four mutant proteins were found and tumour-infiltrating lymphocytes reactive against these mutant versions were identified, expanded in culture and infused into the patient.

 

What’s next?

The last step with the fingers was important because there’s almost always an element of luck in these things. For example, a patient may not make enough T lymphocytes to obtain an effective inoculum. But, regardless of the limitations, it’s what scientists call ‘proof-of-principle’. If it works once it’ll work again. It’s just a matter of slogging away at the fine details.

For Judy Perkins, of course, it’s about getting on with a life she’d prepared to leave — and perhaps, once in while, glancing in awe at a Nature Medicine paper that does not mention her by name but secures her own little niche in the history of cancer therapy.

References

McGranahan et al. (2016). Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 10.1126/science.aaf490 (2016).

Zacharakis, N. et al. (2018). Immune recognition of somatic mutations leading to complete durable regression in metastatic breast cancer. Nature Medicine 04 June 2018.

Now You See It

 

In the pages of this blog we’ve often highlighted the power of fluorescent tags to track molecules and see what they’re up to. It’s a method largely pioneered by the late Roger Tsien and it has revolutionized cell biology over the last 20 years.

In parallel with molecular tagging has come genetic engineering that permits novel genes, usually carried by viruses, to be introduced to cells and animals. As we saw in Gosh! Wonderful GOSH and Blowing Up Cancer, various ‘virotherapy’ approaches have been used with some success to treat leukemias and skin cancers and a trial is underway in China treating metastatic non-small cell lung cancer.

A major aim of genetic engineering is to be able to control the expression of novel genes (i.e. protein production from the encoding DNA sequence) that have been introduced into an animal — in the jargon, to ‘switch’ on or off at will. That can be done but only by administering a drug or some other regulator, either in drinking water, by injection or squirting directly into the lungs. An ideal would be something that’s more controlled and less invasive. How about shining a light on the relevant spot?!

Wacky or what?

That may sound as though we’re veering towards science fiction but reflect for a moment that every animal with vision, however rudimentary, sees by transforming light entering the eyes into electrical signals that the brain turns into a picture of the world around them. This relies on photoreceptor proteins that span the membranes of retinal cells.

How vision works. Light passes through the lens and falls on the retina at the back of the eye. The photoreceptor cells it activates are rod cells (that respond to low light levels — there’s about 100 million of them) and cone cells (stimulated by bright light). Sitting across the membranes of these cells are photoreceptor proteins — rhodopsin in rods and photopsin in cones. Photoreceptor proteins change shape when light falls on them — the driver for this being a small chemical attached to the proteins called retinal, one of the many forms of vitamin A. This shape change allows the proteins to ‘talk’ to the inside of the cell, i.e. to interact with other proteins to switch on enzymes and change the level of ions (sodium and calcium). The upshot is that the signal is passed through neural cells in the optic nerve to the brain where the incoming light signals are processed into the images that we perceive. © Arizona Board of Regents / ASU Ask A Biologist.

The seemingly far-fetched notion of controlling genes by light was floated by Francis Crick in 1999. The field was launched in 2002 by Boris Zemelman and Gero Miesenböck who engineered neurons to express one form of rhodopsin. This gave birth to the subject of optogenetics — using light to control cells in living tissues that have been genetically modified to express light-sensitive ion channels such as rhodopsin. By 2010 optogenetics had advanced to being the ‘Method of the Year’ according to the research journal Nature Methods.

Dropping like flies

One of the most dramatic demonstrations of the power of optogenetics has come from Robert Kittel and colleagues in Würzburg and Göttingen who made a mutant form of a protein called channelrhodopsin-1 (found in green algae) and expressed it in fruit flies (Drosophila melanogaster). The mutant protein (ChR2-XXL) carries very large photocurrents of ions (critically sodium and calcium) with the result that photostimulation can drastically change the behaviour of freely moving flies.

Light-induced stimulation of motor neurons in adult flies expressing a mutant form of rhodopsin ChR2-XXL. Click to run movie.

Left hand tube: Activation of ChR2-XXL in motor neurons with white light LEDs caused reversible immobilization of adult flies. In contrast (right hand tube) flies expressing normal (wild-type) channelrhodopsin-2 showed no response. From Dawydow et al., 2014.

Other optogenetic experiments on flies can be viewed on You Tube, e.g., the TED talk of Gero Miesenböck and the Manchester Fly Facility video of fly maggots, engineered to have a channel protein (channelrhodopsin) in their neurons, responding to blue light.

Of flies … and mice … and men

This is stunning science and it’s opened a new vista in neurobiology. But what about the things we’re concerned with in these pages — treating diseases like diabetes and cancer?

Scheme showing how genetic engineering can make the release of insulin from cells controllable by light. Normally cells of the pancreas (beta cells) take up glucose when its level in the circulation rises (via a glucose transporter protein). The rise in glucose triggers ATP production in the cell. This in turn causes potassium channels in the membrane to close (called depolarization) and this opens calcium channels. The increase in calcium in the cell drives insulin secretion. From Kushibiki et al., 2015.

The left-hand scheme above shows how glucose triggers the pancreas to produce the hormone insulin. Diabetes occurs when either the pancreas doesn’t make enough insulin or when cells of the body don’t respond properly to insulin by taking up glucose.

As a first step to see whether optogenetic regulation of calcium levels in pancreatic cells could trigger insulin release, Toshihiro Kushibiki and colleagues at the National Defense Medical College in Saitama, Japan engineered the channelrhodopsin-1 protein into mouse cells and hit them with laser light of the appropriate frequency. An hour after a short burst of light (a few seconds) the insulin levels had doubled.

The photo below shows a clump of these cells: the nuclei are blue and the channel protein (yellow) can be seen sitting across the cell membranes.

 

Cells expressing a fluorescently tagged channelrhodopsin protein (yellow). Nuclei are blue. From Kushibiki et al., 2015.

 

 

To show that this could work in animals they suspended the engineered cells in a gel and inoculated blobs of the goo under the skin of diabetic mice. Laser burst again: blood glucose levels fell and they showed this was due to the irradiated, implanted cells producing insulin.

Fast forward three years

Those brilliant results highlighted the potential of optogenetic technology as a completely novel approach to a disease that afflicts over 300 million people worldwide.

Scheme showing a Smartphone can be used to regulate the release of insulin from engineered cells implanted in a mouse with diabetes. The key events in the cell are that the light-activated receptor turns on an enzyme (BphS) that in turn controls a transcription regulator (FRTA) that binds to a DNA construct to switch on the Gene Of Interest (GOI) — in this case encoding insulin. (shGLP1, short human glucagon-like peptide 1, is a hormone that has the opposite effect to insulin). From Shao et al., 2017.

In a remarkable confluence of technologies Jiawei Shao and colleagues from a number of institutes in Shanghai, including the Shanghai Academy of Spaceflight Technology, and from ETH Zürich have recently published work that takes the application of optogenetics well and truly into the twenty-first century.

They figured that, as these days nearly everyone lives with their smartphone, the world could use a diabetes app. Essentially they designed a home server SmartController to process wireless signals so that a smartphone could control insulin production by cells in gel capsules implanted in mice. There are differences in the genetic engineering of these cells from those used by Kushibiki’s group but the critical point is unchanged: laser light stimulates insulin release. The capsules carry wirelessly powered LEDs.

The only other thing needed is to know glucose levels. Because mice are only little and they’ve already got their gel capsule, rather than implanting a monitor they took a drop of blood from the tail and used a glucometer. However, looking ahead to human applications, continuous glucose monitors are now available that, placed under the skin, can transmit a radio signal to the controller and, ultimately, it will be possible for the gel capsules to have a built-in battery plus glucose sensor and the whole thing could work automatically.

Any chance of illuminating cancer?

This science is so breathtaking it seems cheeky to ask but, well, I’d say ‘yes but not just yet.’ So long as the ‘drug’ you wish to use can be made biologically (i.e. from DNA by the machinery of the cell), rather than by chemical synthesis, Shao’s Smartphone set-up can readily be adapted to deliver anti-cancer drugs. This might be hugely preferable to the procedures currently in use and would offer an additional advantage by administering drugs in short bursts of lower concentration — a regimen that in some mouse cancer models at least is more effective.

References

Dawydow, A., Kittel, R.J. et al., 2014. Channelrhodopsin-2–XXL, a powerful optogenetic tool for low-light applications. PNAS 111, 13972-13977.

Kushibiki et al., (2015). Optogenetic control of insulin secretion by pancreatic beta-cells in vitro and in vivo. Gene Therapy 22, 553-559.

Shao, J. et al., 2017. Smartphone-controlled optogenetically engineered cells enable semiautomatic glucose homeostasis in diabetic mice. Science Translational Medicine 9, Issue 387, eaal2298.