Tuesday, 25 May 2021

Trypanosomatid cell structures

These are my oft-requested diagrams of trypanosomatid parasites. They're heavily inspired by the amazing illustrations of trypanosomatids by Keith Vickerman, like this classic, though with a more modern twist.

Both aim to be fully accurate diagrams, targeting a specialist text book or review paper level. They're drawn based on on lots of papers, both by others and by me, plus many hours on electron microscopes looking at them! They are slightly 'cartoony' though, exaggerating the size of some of the organelles/structures for clarity.


Trypanosoma brucei procyclic trypomastigote form - as found in the tsetse fly midgut. This diagram is featured in my annual review with Keith Gull and Jack Sunter: Coordination of the Cell Cycle in Trypanosomes

Leishmania mexicana procyclic promastigote form - as found in the sandfly midgut. Drawn in the same style as T. brucei, but not published.

Trypanosomatid parasites are wonderfully structured and intrinsically beautiful cells. They've been the subject of many of my illustrations over the years, you'll find them around, and give a track record of my illustration skill... for better or for worse.

Please ask before using these - they represent a big investment of time - but they are made to be used and belong in lecture slides! Drop me a message if you need really high resolution versions, vector versions (pdf/svg), etc.

Tuesday, 15 October 2019

Tryp/Leish Stickers!


It's been a busy year starting my lab... But in more important news, T. brucei, T. cruzi and Leishmania stickers!

Tuesday, 18 September 2018

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.

Friday, 14 September 2018

How happy are your HeLa cells?

Figure 1. HeLa cell nucleus happiness scale. HeLa cells expressing FUS eGFP were asked how they felt. The morphology of the nucleus and nucleolus, visible via FUS eGFP localisation, was used to infer happiness. The response was ranked by two independent experts, and used to build a HeLa happiness scale.

Monday, 30 October 2017

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

Thursday, 2 February 2017

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.

Saturday, 28 January 2017

Molecular Cell Biology of Protozoan Parasites - Ghana 2017

Things change fast in Ghana! Three years ago, I helped teach a course for young African scientists in the University of Ghana in Accra. This January I got the chance to do the same again, and it has been fantastic. The University of Ghana is becoming a centre of great science in West Africa, with huge contributions by Gordon Awandare and his West African Centre for Cell Biology of Infectious Pathogens (WACCBIP) course, funded by the World Bank.


This time around, our teaching course was made possible by our TrypTag project, funded by the Wellcome Trust. We applied for extra funds so we could transfer the genetic engineering technologies we developed for TrypTag into the hands of African researchers; to get the research techniques to the parts of the world that really suffer from parasitic diseases.

Our course focused on tools for analysing parasites and what makes them tick, particularly using genetic tools. We mostly looked at Plasmodium (malaria), Trypanosoma (sleeping sickness) and Leishmania (leishmaniasis). To teach the malaria side of the course we had the excellent Kirk Deitsch (Cornell University, New York) and Oliver Billker (Sanger Institute, Cambridge). On the trypanosome and Leishmania side we had Keith Gull (University of Oxford) and Sue Vaughan (Oxford Brookes University), along with the TrypTag team: Jack Sunter, Sam Dean and me!

So what was the course all about?

We focused on the tools to help young African scientists (starting their Master's or PhDs) take control of their research - from learning about free genome data and bioinformatics experiments, to computational and genetic tools to make discoveries about parasite biology.

A major part of the course was tools for handling DNA: PCR for detecting genes in a sample, amplifying DNA to clone it into a plasmid, and working with software (ApE) to design cloning strategies for gene tagging, deletion and RNA interference/siRNA knockdown. Teaching how to design a PCR or cloning experiment, rather than just teaching how to do the experimental technique, was very popular.



We also taught how to use the sequence resources you need for working with DNA: How to get the most from genome databases, like PlasmoDB for malaria and TriTrypDB for trypanosomes and Leishmania. The course also covered bioinformatics experiments, thinking how to test a biological hypothesis using existing data from genome data. The students quickly recognised the power of this approach, particularly given genome sequence resources are free! Many were immediately applying these ideas to their areas of research.



We made sure there was a big push towards critical thinking. The student's loved critical reading of articles in the journal clubs, and thinking about how to apply this critical assessment to their own experiments to make them as good as possible.


We also tried, for the first time ever, using the TrypTag.org website as the start point for a bioinformatics experiment. The students were challenged to start with a protein localisation patterns to identify protiens likely involved in particular aspects of parasite energy metabolism, then test whether any of these were unique to trypanosomes making them a potential drug target.



This was the perfect stress test for the new TrypTag.org website and server. It coped with up to a page view per second, and downloads of 10 images per second, with no problems. All over a slightly unreliable internet connection in Ghana! Many thanks to the scientific computing at the Sir William Dunn School of Pathology in Oxford for helping make this happen.


Overall the course was a great success, with very positive feedback from the students and local research staff. The students were smart, engaged and hard-working. It will be exciting to see what these young people can achieve over the next few years.

Monday, 5 September 2016

TrypTag.org

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.

Tuesday, 16 February 2016

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

Sunday, 8 November 2015

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.

Monday, 1 June 2015

Pebbling in colour

The Pebble Time is finally out! This fantastically simple, yet massively functional, little smartwatch is now shipping to the Kickstarter backers who pledged their renewed support to the company that produced the original Pebble.



I've been lucky enough to be beta testing a developer preview model of the Pebble Time, and have had it on my wrist for the last few weeks. I used this time to put together some animated watchfaces which make the most of the colour screen, and learn some C programming along the way!





An elegant animated watchface, with each digit built from curving paths. Animated minute transitions, and tap-triggered animation to improve readability under low light. Animations, line widths and colours can be customised.

Inspired by the watchface shown on the red Pebble Time Steel advertising images:







A fun, animated, easy to read watchface. Every minute the bubbles in the background pop, and a set of new ones appear (by default) in a new colour. Alternatively you can customsise the colour of the bubbles. Tapping or shaking the watch also triggers the animation.

Inspired by the watchface shown on the red Pebble Time advertising images:






A colourful interpretation of the classic arc watchface design, with a Pebble Time-style loading animation and dynamic colour schemes. Colour schemes and whether or not to show the second hand can be customised.





A colourful interpretation of the classic pixel array digital watchface design, with loading animations, animated minute transitions and dynamic colour schemes. Colour schemes, pixel styles and animations can be customised.



Software used:
CloudPebble: Watchface programming. CloudPebble is an online IDE for Pebble watchfaces and apps.
Notepad++: Server side HTML/Javascript for the watchface settings.

Friday, 17 April 2015

Light-Years of DNA

Light-year, and DNA. Not two scientific terms you expect to see on the same page, but over your lifetime your body will produce around one light-year of DNA! That is about one trillion kilometres. Don't believe me? Let's do some maths:

Every cell in your body has two copies of your genome, held in 23 pairs of chromosomes. The human genome is approximately three billion (3×109) base pairs of DNA.

The famous double helix of DNA has about 10 base pairs per twist, and each twist is 3.4 nanometers long (3.4×10-9 metres, the same as roughly 20 carbon-carbon bonds).

This means that the total length of DNA contained in every cell of your body is approximately 2 meters (3×109 base pairs multiplied by 0.34×10-9 metres per base pair, doubled because of the two copies).

Your body has about ten trillion (1×1013) cells (excluding red blood cells), and this remains roughly constant through your life. There is a huge turnover of these cells though, as your body replaces cells to maintain itself.

Every time a cell is replaced its 2 metres of DNA must be produced. In most tissues the cells are replaced in a couple of months, and in many they are replaced in just a couple of days. Even cells in bones are replaced every few years.

The average lifetime of a cell is probably one or two months, so if you live to 80 then your cells are replaced about 500 times throughout the course of your life.

This means that the total length of DNA your body produces in your lifetime is approximately 1×1016 metres (2 metres multiplied by 1×1013 cells, multiplied by 500 replacements). 1×1016 metres (ten thousand trillion metres) is about one light-year (0.946×1016 metres)! Most amazingly it would not be a light-year of random DNA sequence, but ten thousand trillion identical copies of your DNA, faithfully replicated by your cells.

References:
An estimation of the number of cells in the human body
How quickly do different cells in the body replace themselves?
Thanks to Rob Phillips for making me think about this!

Sunday, 22 March 2015

Wednesday, 28 January 2015

Smooth Videos - AKA Correcting NASA

What makes a video look smooth? Your eye is extremely sensitive to problems with videos, and for any video to look smooth it has to have:

  • A high frame rate
  • A steady camera
  • Roughly even brightness each frame

Normally these are easy to get. Any modern camera will give a decent frame rate, and the exposure time for each shot will be accurate, giving an even brightness of images each frame. Camera steadiness is more difficult, but a basic tripod will solve that.

This is a lot harder in space! For a NASA space probe floating through deep space, keeping a steady orientation is a challenge. Spacecraft can do this well quite well, using thrusters and reaction wheels. They still make some small mistakes though. Getting an even exposure time for each frame of a video is also harder in deep space, especially as it might take minutes or hours for radio commands to reach the space probe so you have to trust its autoexposure. Luckily, given ok starting material, correcting camera shake and frame brightness problems by image processing is quite easy.

NASA's Dawn space probe is currently approaching Ceres, getting sharper pictures of this dwarf planet than ever before. A series of these pictures even shows this tiny world rotating. Unfortunately, they didn't correct the shake or brightness problems in the video released to the press:


A quick fix in ImageJ to remove the shake and even out the frame brightness makes a (dwarf) world of difference:


As the probe gets closer and closer to Ceres its shots are getting more and more spectacular, but the videos still need shake and brightness correction.


Interested in improving some NASA videos? I did the corrections using the free scientific image editing software ImageJ, and these are two handy macro scripts for video corrections in ImageJ:

Image stabilisation
//Stabilise based on signal intensity centroid (centre of gravity)
//Stabilises using translation only, using frame 1 as the reference location
//This method is suitable for stabilising videos of bright objects on a dark background
for (z=0; z<nSlices(); z++) {
 //For each slice
 setSlice(z+1);
 //Do a weighted sum of signal for centroid determination
 sxv=0;
 syv=0;
 s=0;
 for (x=0; x<getWidth(); x++) {
  for (y=0; y<getHeight(); y++) {
   v=getPixel(x, y);
   sxv+=v*x;
   syv+=v*y;
   s+=v;
  }
 }
 //Calculate the centroid location
 cx=sxv/s;
 cy=syv/s;
 if (z==0) {
  //If the first slice, record as the reference location
  rcx=cx;
  rcy=cy;
  print(rcx, rcy);
 } else {
  //Otherwise calculate the image shift and correct
  dx=cx-rcx;
  dy=cy-rcy;
  print(dx, dy);
  makeRectangle(0, 0, getWidth(), getHeight());
  run("Copy");
  makeRectangle(-dx, -dy, getWidth(), getHeight());
  run("Paste");
 }
}
Brightness normalisation
//Normalise image brightness to reduce video flicker
//Scales intensity based on the mean and standard deviation, using frame 1 as the reference frame
//This method is suitable for reducing flicker in most videos
for (z=0; z<nSlices(); z++) {
 //For each slice
 setSlice(z+1);
 //Find the signal mean and standard deviation
 run("Select All");
 getRawStatistics(area, mean, min, max, stdev);
 if (z==0) {
  //If the first slice, record as the reference signal mean and stdev
  rmean=mean;
  rstdev=stdev;
  print(rmean, rstdev);
 } else {
  //Otherwise calculate the brightness and scaling correction
  run("Macro...", "code=v="+rmean+"+"+rstdev+"*(v-"+mean+")/"+stdev);
  print(mean, stdev);
 }
}

Software used:
ImageJ: Image corrections
GIMP: Animated gif file size optimisation

Thursday, 22 January 2015

Tengwar - Transliterating Font

This blog post is about a Tengwar font I designed. It automatically converts text as you type into accurate Elvish script. You can download it for free here.  Just make sure you enable ligatures, contextual alternates and kerning for best results!






While writing his Middle Earth books, JRR Tolkein invented an entire alphabet for the elves called Tengwar. His attention to detail was incredible, Tengwar is a fully functioning writing system. This is the famous Elvish writing seen all through Lord of The Rings and the Hobbit.

Tengwar is an alphabet, not a language, and can be used to write many languages. This is like, for example, Latin and Greek alphabets; the word English word “ring” is normally written in the Latin alphabet but could also be written in the Greek alphabet as “ρινγ”. The two sound the same, it is just a different way of writing the sounds of the word “ring”. The process of transferring a word between two different alphabets is called transliteration.

In Middle Earth, Tengwar is one of the major ways of writing. Many languages were written in Tengwar: two Elvish languages called Sindarin and Quenya, the Black Speech of Mordor (on the One Ring), and the language of men (English). Tolkein gave detailed notes on how to write English in the Tengwar alphabet. In Tengwar “ring” is written:


Writing in Tengwar follows simple rules but quickly gets complicated, so I designed a font that does it automatically! You can download it for free here.  As far as I know this font is unique, all other Tengwar fonts are just collections of symbols you have to manually mix and match.

To use this font you just need to download and install it. Once it is installed, just select it as the font and start typing as normal. The font will automatically transliterate the text you type into accurate Tengwar, based on Tolkein’s rules about writing English in Tengwar.

To make sure the font is working accurately you need to make sure three settings are enabled: kerning, contextual alternates and ligatures. For example, in Microsoft Word you can do this through the advanced font settings:


So how does it work? Basic Tengwar is similar to the Latin alphabet, with two classes of symbols representing the sounds of different consonants and different vowels. At the simplest level, to write the word “ring” the font just selects the four symbols for “r”, “i”, “n” and “g”:


Unlike the Latin alphabet, there are special rules for how vowels are written. Instead of always being a separate letter, if a vowel comes immediately before a consonant it is written as an accent on that consonant. In “ring” the “i” comes immediately before the “n” so the font writes it as an accent on the “n”:


There are some special rules to use for some consonants, depending on where they are in a word. “r” is one of these letters. If it is followed by a vowel then it should have a different symbol, which the font automatically selects:


Finally, some common combinations of consonants that have a single sound (like “th” as in “the”, “ch” as in “church” and “gh” as in “ghost”) have their own single symbol. “ng” is one of these pairs and, again, the font automatically makes this substitution:


And that is how the font automatically writes “ring” in Tengwar. These are not the only rules though, there are also other ones built into the font that involve double vowels, double consonants, the letter “n” preceding another consonant, whether a “y” is used as a vowel or a consonant, whether an “e” is voiced in a word or is silent at the end of a word, etc.

The key feature of my font is that it takes all of these rules into account automatically and lets you simply type away as normal and get an accurate, readable result in Tengwar. You can also just select an existing chunk of text and apply the font to it to transliterate it to Tengwar, but make sure the text is all lower case for best effect. It does make a few very small mistakes, but Tolkein would understand it!

Tengwar is a beautiful and concise alphabet. The way vowels, double letters and letter pairs combine make many words very short and elegant:


The overall flow of a paragraph is also excellent, with the letters falling into self-symmetric curves and alignments.

(This is the first paragraph of Lord of The Rings, converted to Tengwar by just changing the font to my Tengwar Transliteral font.)

If you are interested in playing with Tengwar text for any kind of design please consider downloading the italic and script versions of the font here. These cost a few pounds/dollars/euros.

If you are interested in reading Tengwar, or manually translating it, then the excellent “Tengwar Textbook” Chris McKay is available online for free: Tengwar Textbook.

There are also excellent simple guides on writing in Tengwar (like this one), but why do that when you could just download my font and type your name?

Software used:
Inkscape: Glyph design
Fontforge: Font design