Making Movies in DNA

Last time we reminded ourselves of one of the ways in which cancer is odd but, of course, underpinning not just cancers but all the peculiarities of life is DNA. The enduring wonder is how something so basically simple – just four slightly different chemical groups (OK, they are bases!) – can form the genetic material (the instruction book, if you like) for all life on earth. The answer, as almost everyone knows these days, is that there’s an awful lot of it in every cell – meaning that the four bases (A, C, G & T) have an essentially infinite coding capacity.

That doesn’t make it any the less wonderful but it does carry a huge implication: if something you can squeeze into a single cell can carry limitless information it must be the most powerful of all storage systems.

A picture’s worth a thousand words

We looked at the storage power of DNA a few months ago (in “How Does DNA Do It?”) and noted that its storage density is 1000 times that of flash memories, that it’s fairly easy to scan text and transform the pixels into genetic code and that, as an example, someone has already put Shakespeare’s sonnets into DNA form.

Now Seth Shipman, George Church and colleagues at Harvard have taken the field several steps forward by capturing black and white images and a short movie in DNA. Moreover they’ve managed to get these ‘DNA recordings’ taken up by living cells from which they could subsequently recover the images.

Crumbs! How did they do it?

First they used essentially the text method to encode images of a human hand: assign the four bases (A, C, G & T) to four pixel colours (this gives a grayscale image: colours can be acquired by using groups of bases for each pixel). These DNA sequences were then introduced into bacteria (specifically E. coli) by electroporation (an electrical pulse briefly opens pores in the cell membrane).

The cells treat this foreign DNA as though it was from an invading virus and switch on their CRISPR system (summarized in “Re-writing the Manual of Life”). This takes short pieces of viral DNA and inserts them into the cell’s own genome in the form of ‘spacers’ (the point being that the stored sequences confer ‘adaptive immunity’: the cell has an immunological memory so it is primed to respond effectively if it’s infected again by that viral pathogen).

In this case, however, the cells have been fooled: the ‘spacers’ generated carry encoded pictures, rather than viral signatures.

Because spacers are short it’s obvious that you’ll need lots of them to carry the information in a photo. To keep track when it comes to reassembling the picture, each DNA fragment was tagged with a barcode (and fortunately we explained cellular barcoding in “A Word From The Nerds”).

Once incorporated in the bugs the information was maintained over many bacterial generations (48 in fact) and is recoverable by high-throughput sequencing and reconstruction of the patterns using the barcodes.

And the movie bit?

Simple. In principle they used the same methods to encode sequential frames.

Pictures in DNA.

Top: Using triplets of bases to encode 21 pixel colours. Images of a human hand (top) and a horse (bottom) were captured. For the movie they used freeze frames taken in 1872 by the English photographer Eadweard Muybridge. These showed that, for a fraction of a second, a galloping horse lifts all four hooves off the ground. Seemingly this won a return for the sometime California governor, Leland Stanford (he of university-founding fame) who had put a wager on geegees doing just that. From Shipman et al., 2017. You can see the movie here.

Getting the picture clear

To recap, in case you’re wondering if this is some scientific April Fools’ prank. What Church & Co. did is scan pictures and transform pixel density into the genetic code (i.e. sequences of the four bases A, C, G & T). They then made DNA carrying these sequences, persuaded bacteria to take up the DNA and incorporate it into their own genomes and, after growing many generations of the bugs, extracted their DNA, sequenced it and reconstructed the original images. By scanning sequential frames this can be extended to movies.

It’s not science fiction – but it is pretty amazing. With a droll turn of phrase Seth Shipman said “We want to turn cells into historians” and the work does have significant implications in showing something of the scope of biological memory systems.

Won’t be long before the trendy, instead of birthday presents of electronic family photo albums, are giving small tubes of bugs!


Shipman, S.L., Nivala, J., Macklis, J.D. & Church, G.M. (2017). CRISPR–Cas encoding of a digital movie into the genomes of a population of living bacteria. Nature 547, 345–349.

A Word From The Nerds

I went (a long time ago it has to be admitted) to what people call an ‘old-fashioned’ grammar school. It wasn’t really old-fashioned – we didn’t wear wigs and frock coats – it just put great emphasis in getting its kids into good universities. To this end we were, at an early stage, split into scientists and the rest (aka arts students). It was a bit more severe even than that because the ‘scientists’ were sub-divided: those considered bright did Maths, Chemistry and Physics whilst the rest did Biology instead of Maths (or anything instead of Maths). All of which was consistent with the view that biologists – and that includes medics – could get by without being able to add up. That was a long time ago, of course, but to some extent the myth lives on. In tutorials with first year medical students I found an ace way of inducing nervous breakdowns was to ask them to do a sum in their heads (“Put that calculator away Biggs minor”).

But times do change and when I asked a doctor the other day which branches of medical science required maths, he paused for moment and then said “All of them.” By that he meant that pretty well every area of current research relies on the application of mathematics. We hear much about DNA sequencing, genomics and its various offshoots but all of these need ‘bioinformaticists’ (whizzos at sums) to extract the useful grains form the vast mass of data generated. Much the same may be said of research in what are called imaging techniques – developing methods of detecting tumours – and there is now a vast subject in itself of ‘systems biology’ in which mathematical modeling is applied to complex biological events (e.g., signalling within cells) with the aim of being able to reconstruct what goes on – what folk like to call a holistic approach. A variation on this theme is studying how large populations of cells behave – for example, tumour cells when exposed to an anti-cancer drug. And that’s an important matter: if your drug kills off every cancer cell bar one but that one happens to be very good at reproducing itself, before long you’ll be back to square one. The way to avoid going round in circles is to detect and interrogate individual survivor cells to find out why they are such good escape artists.

Girls will be girls

All of which brings us to Franziska Michor. Born in Vienna of a michor2-d5f528c0eec02b1797c3028e48c17598.pngmathematician father who, she has recounted, told her and her sister that they had either to study maths or marry a mathematician. Sounds a frightening version of tradition to me – and it had perhaps the intended effect on the girls: frantic sprints to the nearest Department of Mathematics. That’s a bit unfair. As they say, some of my best friends are mathematicians – so they’re not at all the stereotypical distrait, inarticulate, socially inept weirdos. Although most of them are.

But Fräulein Michor was clearly one of the exceptions. She’s now a professor at the Dana-Farber Cancer Institute and Harvard School of Public Health in Boston and, with colleagues, she’s had a go at an important question: when cancer cells become resistant to a drug, is it because they acquire new mutations in their DNA or is it that some cells are already resistant and they are the ones that survive and grow. Their results suggest the simple answer is ‘the latter’ – resistant clones are present before treatment and they’re the survivors. So the upshot is clear but the route to it was very clever – not least because the maths involved in teasing out the answer is positively frightening. Fortunately (medics breathe a sigh of relief!) we can ignore the horrors of ‘Stochastic mathematical modeling using a nonhomogeneous continuous-time multitype birth–death process’ – yes, really – and just look at the biology, which was ingenious enough. To get at the answer they developed a tagging system that tracked the individual fates of over one million barcoded cancer cells under drug treatment.

Nerd picBarcoding cells. Strings of DNA 30 base pairs in length and of random sequence are artificially synthesized (coloured bars). These fragments are inserted in the genomes of viruses. The viruses infect cancer cells in culture and, after drug treatment, cells that survive (drug resistant) are harvested, their DNA is extracted and barcode DNA is detected (redrawn from Bhang et al. 2015).

Check this out!

Barcodes were pioneered by two young Americans, Bernard Silver and Norman Woodland, for automatically reading product information at checkouts and nowadays they’re used to mark everything from bananas to railway wagons and plane tickets. Their most familiar form is essentially a one-dimensional array that Woodland said he came up with by drawing Morse code in sand and just extending the dots and dashes to make narrow and wide lines.

120px-UPC-A-036000291452128px-PhotoTAN_mit_Orientierungsmarkierungen.svgbarcode n





Cellular barcoding uses the same idea but the ‘label’ is an artificial DNA sequence. Such is the power of the genetic code that a random string made up of 30 of its four distinct units (A, C, G & T) can essentially make an infinite number of different tags. Just like those on supermarket labels, two different codes look the same at first glance:



The tags are made in an oligonucleotide synthesizer (a machine that sticks the units together) and then incorporated into virus backbones, just as we described for immunotherapy. The viruses (+ barcodes) then infect cells in culture, these are treated with a drug and the survivors present after a few weeks have their barcode DNAs sequenced. The deal here is that the number of different barcodes detected reflects the proportion of the original cell population that survived – and it indeed turned out that it’s very rare, pre-existing clones that are drug resistant. For one of the cell lines (derived from a human lung cancer) about one in 2,000 of the starting cell population showed resistance to the drug erlotinib.


The obvious question then is ‘What’s special about those few cells that they can thumb their noses at drugs that kill off most of their pals?’ To begin to get answers Bhang, Michor and colleagues noted that, for the lung cancer line, resistance to erlotinib occurs in cells that have multiple copies of a gene called MET – which makes a signalling protein. Exposing the cells to erlotinib and a MET inhibitor (crizotinib) greatly reduced the size of the resistant population (to one in 200,000).

This still leaves the question of the genetic alterations in that 0.0005% – and of course, finding drugs to target them. A further point is that this was a study of cells grown in the lab and it’s not possible to use this system in patients – but it could be used in mice to follow the development of implanted human tumours. If the causes of resistance can be tracked down it would open the way to using combinations of drugs that target both the bulk of tumour cells and the small sub-populations in which resistance lurks. That upshot would bring us to clinicians at the bedside (non-mathematicians!) – but not before running up a big debt to the maths geeks and in this case to a Viennese Dad who really did know best (offspring of the world please note!).


Bhang, H.C. et al. (2015). Studying clonal dynamics in response to cancer therapy using high-complexity barcoding. Nature Medicine 21, 440-448.