How does a cell swim fowards?

“Why are they swimming backwards?” This is one of the most common questions I get asked whenever I show a video of Leishmania parasites swimming.

Swimming Leishmania at 200 frames per second (8× slower than actual speed)

If you look at Leishmana with a high speed video it's easy to see they tend to swim 'tail-first', with the flagellum sticking forward into the direction of travel. Sperm, probably the best-known swimming cells, do the opposite, and swim 'head-first'.

Sperm on the left, Leishmania on the right

Of course, if you could ask the Leishmania, they'd say that they're swimming forwards and it's the sperm which are swimming backwards. This raises the question of how does a swimming cell decide which direction it should swim? Which direction is forwards?

The direction a cell swims depends on the waves which travel down the flagellum. If they start at the base and go towards the tip then the cell will swim head-first. If they start at the tip and go towards the base then the cell will swim tail tail first. So how do they choose where the waves start?

We answered this question taking advantage of a useful behaviour of Leishmania. If you look closely at the video above you can see one cell is swimming forwards (the cell on the left) and the other is turning on the spot (the cell on the right). And if you look very closely you'll see that the waves in the cell on the left start at the flagellum tip, and the waves in the cell on the right start at the base of the flagellum.

Tip-to-base on the left and base-to-tip on the right.

This let us use genetic tools to try to break one direction of flagellum wave without affecting the other and tease apart how the flagellum movement might be chosen by the cell. To cut a long story short, we found differences in the motor proteins between the base and tip which seem responsible. Interestingly, similar differences turn up in many organisms, including human sperm, suggesting it might be a general pmechanism. You can read all about this in our recent paper: At the PNAS website or as a PDF.

https://doi:10.1073/pnas.1805827115

How to be a parasite

For an organism to become a parasite it has to adapt to live in a host. This might mean it needs to grow faster, invade cells or tissues, or avoid being killed by the immune system. It can also 'forget' how to live outside a host. It can forget how to search for food, how to survive the cold, and how to avoid drying out.

We can learn how parasites adapt to infect hosts by looking at the nearest free living relatives. What had the parasite lost relative to the free living cousin, because it just doesn't need it to survive in a host? Or vice versa, what has it kept because it's useful for infecting a host?

I've looked at this question for trypanosomatid parasites. They are protozoan (single cell) parasites, like the malaria parasite, and cause several deadly tropical diseases.

A few hundreds of millions of years ago, they weren't parasites at all. The ancestors of these parasites were free living, probably swimming in ponds, lakes and seas. Then, at some point, some evolved the ability to infect insects.

Millions of years passed. Then, several tens of millions of years ago, some managed to get transmitted from their host insect into a vertebrate host. And, most importantly, they survived and could get transmited back to the fly.

This adaptation to infect animals probably happened on three separate occasions. Those parasites kept evolving and adapting, and are now the three human trypanosomatid-caused diseases: Sleeping sickness, Chagas disease and leishmaniasis.

My most recent paper is all about this. Julius Lukeš has discovered a species of trypanosomatid that only infects insects, and looks like it hasn't changed much from the first ancestor ever to infect insects.

With Tomáš and Eva, we looked at what this species tells us about how these parasites adapted to infect flies: How does the cell grow, adapts its shape, and stick to surfaces? How does its internal organisation adjust to allow these changes? How does its metabolism change for different energy sources? And, how has the genome, which encodes the proteins that drive these functions, changed to achieve this?

Using this information, we could then get insights into what is important for human infective parasites. What aspects of shape, structure and metabolism adaptations have they 'forgotten'? And which have they kept? The ones they have kept are the ones important for infecting, and killing, people.

Want to read more? You can get a copy of the paper from my website: richardwheeler.net

Skalický T*, Dobáková E*,1, Wheeler RJ*, Tesařová M, Flegontova P, Jirsová D, Votýpkaa J, Yurchenkoa V, Ayalag FJ, Lukeš J (2017) "Extensive flagellar remodeling during the complex life cycle of Paratrypanosoma, an early-branching trypanosomatid" PNAS doi:10.1073/pnas.1712311114

Moving in a straight line - sounds simple, right?

One hundred years ago Asa Schaeffer blindfolded his friend and challenged him to walk in a straight line. He did three loops of a spiral, before tripping over a tree stump. This wasn't a cruel prank, it was an experiment, and all people are surprisingly bad at this simple challenge.

More modern experiments showed it is lack of external reference points that trips people up. Blindfolded in a desert? You walk in circles. Not blindfolded in a desert? Straight lines. Forest on a sunny day? Straight lines. Forest on an overcast day? Circles. Current Biology, DOI: 10.1016/j.cub.2009.07.053

People need some external reference point, a distant hill, the sun, or even the direction of shadows, to manage a straight line. Why they drift into circles without a reference isn't clear. Is it asymmetric leg strength? A handedness bias? Or some psychological miss-correction? What is clear is that it is a universal problem.

Navigation without reference points is always difficult. This is why spin stabilisation is widely used to stop flying objects, from bullets to rugby balls, curving off course in the air. Even advanced tools like inertial navigation systems, which use dead reckoning from measuring acceleration, always drift off course. 

So how about swimming cells? Many swimming cells and microorganisms have the ability to swim in a straight line. Most have no ability to look at a reference point, they can only perceive the liquid they are in immediate contact with. They are also typically top small to be affected by gravity, so have no way of using up or down for reference. They are essentially blind.

The trick for straight line swimming in cells seems to be some kind of spin stabilisation. Way back in 1901, H.S. Jennings noted that many microorganisms spin as they swim, and thought this could be a spin stabilisation somewhat like a spinning bullet. The problem is it can't be. Rugby balls, bullets and spacecraft use spin stabilisation which depends on rotational inertia to keep them spinning and stable, similar to a spinning top. If you made a top that was the size of a cell, and span it in water, it would stop spinning immediately; there is too much friction. The American Naturalist, 35(413):369-379

It turns out the mechanism is just geometry. A person walking is a back-forward/left-right, a 2D, situation. If you curve the walking path it makes it into a looping circle. For a cell swimming there is another direction to think about; in 3D there are two ways to curve the swimming path. The first which curls the path into a circle, and a second which twists the circle to elongate it into a helix-shaped path. Elongate the helix far enough and it turns into a straight line, with the cell rotating as it swims.

The interesting property of the helical swimming paths is their stability. If a cell deliberately twists its swimming path into a helix then small asymmetries (the cellular equivalent of having one leg stronger than the other) won't bend the swimming path into a circle. Instead it just slightly alters the shape of the helix. It can ensure the cell swims in a dead straight line.

My latest paper is all about how cells manage straight line swimming, looking at trypanosome and Leishmania human parasites. Each aspect of swimming has been looked at before, but I believe has never previously been put together as a full story: from mutants with altered cell shape (to add more or less twist), measuring the effect on swimming, and matching this to simulation of how cells achieve their straight line swimming. PLOS Computational Biology, DOI: 10.1371/journal.pcbi.1005353

There are still big unanswered questions though: Why do parasites need to swim in a straight line? And what are they swimming towards? This is an area of active research, with several major trypanosome research groups (especially Kent Hill and Markus Engstler) interested in addressing these questions.

Looking at the structure inside cells

How complex and structured is the inside of a cell? It's hard to imagine, but the internal organisation of cells is typically precisely controlled by molecular skeletons and scaffolds, giving cells the shape they need to function.

We can discover the 3D organisation of the inside of cells using electron tomography; a process where you capture a series of images with an electron microscope, with the sample tilted at a slightly different angle for each image. This can then be used to calculate the 3D shape of the sample, using the same maths as for an X-ray CT scan.

Leishmania parasites are exquisitely structured. While they are only 2 micrometres wide (100 would fit across a human hair) they have a precise internal organisation which they faithfully replicate each time they divide. One of the distinctive parts of this organisation is the flagellar pocket, where the cell membrane folds in on itself at the base of the whip-like flagellum that the cell uses to swim.

In my latest paper, "Flagellar pocket restructuring through the Leishmania life cycle involves a discrete flagellum attachment zone", I used electron tomography to reconstruct the three-dimensional organisation of the Leishmania flagellar pocket. The structure in this area of the cell is incredible, and the journal picked a rendering of it for the cover image.

Volume covered in this 3D reconstruction is only 3 by 2 by 1 micrometres, about the size of a typical bacterial cell, but has enormous complexity. I have shown the microtubules (which make up most of the cytoskeleton) in red and membranes in blue. Each microtubule is only about 5 molecules wide, and is about 10,000 times narrower than a human hair! Some other specialised parts of the cytoskeleton are in green.

You can download the paper for free here to take a look at the structures in this area of the cell in more detail.

Software used:
IMod: Electron tomography structure
Blender: Tidying and rendering of the 3D structure

Ergodic Analysis

My review paper about ergodic analysis came out on Thursday. Does ergodic analysis sound terrifying? It's actually quite a simple concept and it is a powerful method for extracting information about the dynamics of a cell division cycle from a single snapshot of cells at random stages of the cell cycle.

Ergodic analysis is particularly useful if a time-lapse video is impossible, for example if the cells swim or you want to do an analysis that kills the cells.

Does this sound interesting for your research? Drop me a message: @Zephyris.

Software used:
Autodesk Sketchbook Pro: Drawing the cells.
Inkscape: Page layout.

Book Scanning

I have an old book which I am mining data from... The problem is paper is a pain; there is no Ctrl+F function and unless the index includes the terms you are after (which, in this case, it doesn't) then searching turns into a real pain.

The solution? Scan it.
The problem? How to scan it.

Unlike printed, typed or even many handwritten documents it's not easy to pull apart a book and scan the pages with an automatic machine, especially when the book is old, out of print and quite valuable. Most book scanners (including Google's) use cameras instead. This is my setup:

A very high-tech setup.

It's all very simple; a camera, a tripod to hold the camera still, remote shutter button to snap the pictures, lots of lamps for even illumination and a data connection to the computer so I didn't fill up the memory card too fast.

It was a pretty chunky book (801 pages) and it took a total of 489 shots (including reshoots of slightly out-of-focus pages) to capture all of it. That took nearly 1.5 hours, or about 10 seconds per photo. So what does a whole book look like?

With some magic semi-automated processing these images are all that is needed for a perfect scan. Using ImageJ I converted them to black and white, subtracted the background and cropped/rotated the pages. These are some samples:

These processed images can simply be fed into Adobe Acrobat or other similar optical character recognition (OCR) software to translate the image of the text into machine-understandable, fully-searchable text. Exactly what I need!

Software used:

ImageJ: Automated image processing

Adobe Acrobat: OCR

Paper Autofluorescence

Microscopes are fun... Small things are cool! This is paper in all its fibrous glory; illuminated in ultraviolet paper autofluoresces at blue wavelengths and looks amazing! This was created from a 3x3 array of images, see the links below for higher resolutions:
6400x4800 at Wikipedia
Single screen wallpapers at Deviantart
Dual screen wallpapers at Deviantart

Software used:
The GIMP