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.

The website for one of my new major research projects is now live!

TrypTag.org

TrypTag is a project to tag every gene in the trypanosome genome with a fluorescent marker to see where it goes in the cell.

Do you have no idea what I'm talking about? Read on to see what all that jargon means!

Trypanosomes are one of the parasites my research involves. They are single cell parasites that live in the blood, and they cause the diseases sleeping sickness in humans and nagana in livestock across Africa. All in all, not very nice.

Like all cells, trypanosomes are made up of protein machinery. Each protein is encoded by a gene in genome. A first step in finding a protein's function is finding where it goes in the cell. If you can map it to a particular structure then you have a good idea it's going to function there too.

To find where a protein goes in a cell we genetically modify the cell, sticking a fluorescent marker to the protein so we can see where it goes using a microscope. This is the process of tagging.

We are going to tag every protein gene in the genome, around 8000 genes, and build a complete map of the protein composition of the cell.

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.

Trypanosome Lego

Trypanosomes and Leishmania are the two tropical parasites that I do most of my research on. These cells seem to have a lot of modularity in controlling their shape, and have quite a lot of flexibility in reshuffling where particular structures (made up of many organelles) sit within the cell.

The base of the flagellum, the whip-like tail which the cell uses to swim, is also the site where the cell takes up material from its environment (essentially its mouth) and is linked with the Golgi apparatus (an important organelle in protein processing) and the mitochondrion (the powerhouse of the cell) and links to the mitochondrial DNA. It turns out reducing the level of just one protein in the cell can cause this entire complex structure to shift its position.

Cells are not quite as flexible as Lego, but it is still impressive that a single protein can have such a large effect on the organisation of a cell.

This one goes out to the cilia biologists...

Have no idea what this is about? Try reading about cilia and hedgehogs...

Need to teach PCR?

Need some high quality diagrams to explain polymerase chain reaction (PCR), designing primers, or some combo of both? You have come to the right place! There seemed to be a complete lack of high quality diagrams of primer sequences and the PCR cycle, so I drew some.


The primers. http://en.wikipedia.org/wiki/File:Primers_RevComp.svg



 Melting the template DNA. http://en.wikipedia.org/wiki/File:Primers_RevComp_Melted2.svg

Annealing of the primers. http://en.wikipedia.org/wiki/File:Primers_RevComp_Annealed2.svg

Elongation by DNA polymerase from the primers. http://en.wikipedia.org/wiki/File:Primers_RevComp_Elongation2.svg

These diagrams are all in scalable vector graphics (SVG) format and free for others to use and edit. Inkscape is a great, free, SVG editor, feel free to grab it and modify these images to your heart's content!

Software used:
Inkscape: Vector graphics

Cilia

Each term I make a research comic for the Oxford University Biochemical Society magazine called Phenotype. This term's topic; cilia! These organelles can be found on a huge number of eukaryotic cells, ranging from nearly every cell in your body, to free living single cell microorganisms and protozoan parasites. The most famous function of cilia is swimming or moving a cell's surroundings, like the sperm flagellum (flagellum and cilium are different names for the same structure) or the cells in your lungs which help keep them clear of mucous.

Cilia are famous for their movement, but cilia are one of our the most multifunctional cell structures and have extremely important sensory and development functions. Can you guess which four if the five classic senses (touch, taste, smell, hearing, sight) need flagella to work?

This term's research comic feature in OUBS Phenotype is all about the diverse functions of cilia/flagella. Check out the comic here, or download the whole issue for free here.

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

This one goes out to the immunologists...

If you are totally confused start reading here, and here. Oh, and it's not called a FACS plot by the way.
Search engine optimisation: CD25 FOXP3 CD4 Tcell T cell T rex Tyrannosaurus

Valentine's Day Electron Microscopy

Electron microscopes are pretty impressive machines. By firing electrons at a sample they can generate images thousands, or even millions, times sharper than you can make with light. With the right sample you can spot individual protein molecules in a cell, and even individual atoms within a molecule. When using these microscopes to look at the structures within biological samples like cells there are two big problems though:

1. Proteins, sugars, fats, DNA, water, plastic, etc. all block electrons by about the same amount. 
2. Electrons can only travel very short distances through materials.

These two issues make looking at a cell tricky: firstly the cell is too thick for most electrons to travel through it. You can up the power of the electron beam, but then you just vaporise the cell. To solve this the cell has to be sliced up into very thin layers called 'sections'. The next problem is therefore how to slice up a cell, which is basically a bag of proteins dissolved in water. The answer is to replace the water with plastic, making a solidified version of the cell which can be sliced up into thin sections. Finally, to actually tell the difference between protein, fat and DNA in the sample, you need to stain them to make them stand out from the plastic in the background. This is done by using heavy metals, like osmium and lead. The huge positively charged nuclei in these atoms scatter electrons away from the the detector; this makes regions where heavy metals have bound to proteins, fats, etc. look darker.

A block of plasticated cells stained with heavy metals (the black bit) in an epoxy resin plastic (the amber bit) in a metal holder (the silver bit).

So how thin does one of these sections need to be? In short, very. Even travelling through air an electron may only go a couple of centimetres before an atom captures it or deflects it from its path. In a solid material like plastic the distance is far shorter, about 1 million times shorter, with electrons travelling less than 1 millionth of a metre before being scattered or captured. The sections a sample is currently in into must be very thin, about one ten millionth of a metre (100 nanometres) is common.

Cutting a sample into slices one ten millionth of a metre thick is a challenge. It is like cutting a human hair into 1000 slices, each section is about 2000 times thinner than normal office paper. A lab machine called an ultramicrotome is designed to do this, and can cut slices as thin as 30nm. This is a tiny distance, about the width of 15 DNA double helices. The next problem is; how do you know you have cut a slice of the correct thickness? The sections are far too thin to be able to pick them up and measure them by any normal method. Luckily a physical phenomenon called thin film interference gives an easy way to do this.

When light hits a thin film, like a thin layer of oil in water or a soap bubble, some light bounces off the front of the film and some off the back. If the film is a similar thickness to the wavelength of light (around 500 nm) then interference between the two paths the light takes will occur. The interference can be constructive (boosting the light intensity) or destructive (reducing the light intensity). Because different colours of light have different wavelengths, different colours will experience constructive or destructive interference, for example if blue and green wavelengths destructively interfere, but red does not, then only red light will be reflected. The film will look red, even if the material it is made of is totally transparent.

Thin film interference in a soap bubble. CC-BY-SA by link.

Sections of cells embedded in plastic for electron microscopy act just like an oil or soap film, and have distinctive colours based on their thickness. We use these colours to check that the sections we have cut are the correct thickness, without having to directly measure them. It really is very quick and easy!

Lots of electron microscopy sections of different thickness. From bottom to top: 30nm (grey), 50nm (white), 70nm (white), 100nm (gold), 150nm (purple), 200nm (blue), 250nm (yellow), 300nm (pink/red), 400nm (green), 500nm (purple).

So what does this have to do with Valentine's day?

As far as I can work out the sectioning process you use for electron microscopy is a great way to make the smallest possible valentines heart which is still has a vivid pink/red colour. 'All' you need is:

• An ultramicrotome
• A block of plastic 
• A razor blade 
• Steady hands
• About 10 minutes

Step 1:
Trim the plastic block to a flat face, then cut a heart shape into that face. This is the bit the steady hands and razor blade are needed for, the heart needs to be about 0.3 to 0.5 mm (250 to 500 um) wide! It also needs to have tidy flat edges so sections can be cut without damaging the knife blade.

The trimmed, heart-shaped, block of plastic.

Step 2:
Use the ultramicrotome to cut a section 300 nm (3 ten millionths of a metre) thick off the block, and catch it on the surface of a pool of water next to the knife edge. From the colour scale of thin film interference we expect a 300 nm section to be a vivid red/pink colour (even though the plastic itself is a transparent amber colour).

A 300nm thick sliver of the block, the tiniest Valentine's heart ever.

Step 3:
Bask in the glory of having made the smallest, and geekiest, valentines heart ever. It is so thin that even if you scaled it up to the size of an A4/letter sheet of paper it would still be 4 times thinner than cling film/saran wrap and 40 times thinner than paper. This tiny thickness gives it a tiny volume: it has a volume of about 3×10^-14 metres cubed, and a mass of about 3×10^-11 grams. That is similar to the mass of a single, average, human cell.

Software used:
ImageJ: Focus stacking.
Photomatix: HDR image processing.

Cell Picture Show

One of my scanning electron microscope images from my research into the division of Leishmania parasites is currently featured in the Cell journal picture show on parasites and vectors. You can check it out (image number 11) here.

A montage of seven scanning electron micrographs of L. mexicana.

"Leishmania mexicana promastigotes, which normally inhabit the gut of the sand fly vector, are shown at different stages of the cell cycle. Cells are arranged by cell-cycle progression, increasing in a clockwise direction. L. mexicana mainly causes a mild form of cutaneous leishmaniasis, forming ulcers at the bite site of an infected sand fly."

Software used:

ImageJ: Micrograph processing

Scientific Icons

If you have ever searched for scientific icons (unlikely but possible) you will have found it is nearly impossible to find decent ones...

I thought it was time to change this; download my new set of 22 scientific icons here: SciIcons

Software used:
Inkscape

Trendy and Elemental

You can explore the properties of the periodic table interactively here, and you each one of the periodic table images links to an interactive version showing the same data.

The periodic table is an amazingly elegant arrangement of the elements based on the electron configuration of the atoms... Its power lies in its predictive abilities; clusters of elements in the periodic table have similar properties and there are distinctive trends across the table. This inspired me to make a website where you can explore these trends interactively.

Some of the classic trends are:
Atomic radius (darker colours indicate smaller atoms)
Thermal conductivity (darker colours more conductive, this reflects metallic character)Ionisation energy (darker colours indicate less energy is required to remove an electron)These are just the boring "classic" trends though... You can look at lots of other properties of the elements. The stability of the nucleus (linked with radioactivity) also gives some interesting patterns:
Radioactive decay half life (darker colours indicate more unstable elements, greyed out elements are not radioactive)
There is a clear pattern, only elements with a large number of protons are radioactive, with two exceptions; Tc (Technetium) and Pm (Promethium) which fall out of this sequence... What causes this? We can work it out by looking at the number of stable isotopes for each element, i.e. the number configurations of neutron number for an element which are not radioactive.

Number of stable isotopes (darker colours indicate less stable isotopes, light colours indicate more stable isotopes)The number of stable isotopes shows a distincive striped pattern where alternating columns have either few or many stable isotopes... Notably Tc (Technetium) and Pm (Promethium) fall in columns where the elements have few stable isotopes. These patterns show how an even numbers of protons makes the nucleus more stable, and odd numbers make it less stable. The effect of this can be extreme; Sn (Tin) with 50 protons (an even number) has 10 stable isotopes with 62, 64, 65, 66, 67, 68, 69, 70, 72 or 74 neutrons. Tc (Technetium) with 43 protons (an odd number) has no stable isotopes.

In turn the stability of the nucleus influences how abundant an element is in the universe...
Abundance in the universe (darker colours indicate more rare, light colours indicate more common)Only non-radioactive elements are common in the universe, radioactive heavy elements quickly decay after they are produced (by nucleosynthesis). There is also an obvious general trend that elements with smaller nuclei are more common.

If you look closely at the abundance of columns of elements you can, however, see trends which mirror the number of stable isotopes; elements like Cu (Copper, 29 protons), Ag (Silver, 47 protons) and Au (Gold, 79 protons) are more rare than elements like Ni (Nickel, 28 protons), Pd (Palladium, 26 protons) and Pt (Platinum, 78 protons)... Elements with more stable nuclei are more likely to be formed in supernovae.

There are always exeptions to the rule though, Li (Lithium), Be (Beryllium) and B (Boron) are much less abundant than you might expect from the "smaller nuclei are more common" trend... Turns out these are not produced in large quantities by stars, unlike carbon, oxygen and nitrogen, and were instead produced by cosmic ray spallation, but that's another story...

If you have enjoyed exploring the properties of the periodic table you can carry on, interactively, here. This is an example screenshot showing the heat capacity of the elements (in the colour hue), atomic radius (in colour saturation) and melting point (in colour brightness):
Software used:
HTML5 (canvas) & Javascript