Making molecules crystal clear

A crystal image of a breakdown pathway of atrazine

A crystal image of a breakdown pathway of atrazine

The International Year of Crystallography is drawing to a close, and we’re not going to let it finish without showing you something about what crystallographers do. Which is not what most people would assume when they hear the word: there are crystals involved, but it’s not exactly the study of crystals as we generally think of them. It’s the study of how matter is organised, using crystals as a tool.

Now, naturally we want to know how matter is arranged. Apart from being very, very interesting to find out about, it also helps in many different fields, from drug delivery to materials science. In fact, it was crystallography that provided – controversially – the key to understanding the structure of DNA.

So assume you want to look at something in the greatest possible detail, seeing its smallest possible components. Obviously, you’d use a microscope. But there’s a limit to the smallness of things you can see that way: the wavelength of the light human eyes see. Visible light has a frequency of between roughly 400 and 700 nanometres, and can’t detect atoms, which are separated by 0.1 nanometres. This is the perfect frequency for X-rays.

We can’t make appropriate X-ray lenses to make x-ray microscopes to study molecules: we have to do it in a roundabout way. We beam X-rays onto crystals, scattering the rays, in just the same way that light reflects when it hits an object. Then we use a computer to reassemble the rays —the diffraction pattern —into an image. The diffraction of a single molecule would be so weak that we couldn’t get any meaningful information from it, so we use crystals, which have many molecules in an ordered array, to amplify the signal so we can see it. Crystals are highly ordered structures, made up of 1012 or more molecules, makes the x-ray diffraction patterns — the main tool of crystallography —possible to analyse.

Crystallographers were among the first scientists to use computers, and used them to do the advanced calculations needed to reassemble diffraction patterns into coherent images. That’s why it seemed fitting to name our supercomputer after the founders of crystallography – Lawrence and Henry Bragg. Lawrence was the first person to solve a molecular structure using x-ray diffraction.

Today we can not only view molecules in 3D, but also study the way they operate. Improvements in x-ray machines have also led to synchrotron facilities, which can produce far more efficient and precise beams.

And speaking of synchrotrons …

One of our crystallographers, Tom Peat, has deposited more than 120 structures in the Protein Data Bank using data collected at the Australian Synchrotron. They were all derived from crystals developed in CSIRO’s Collaborative Crystallisation Centre.

This is one of our favourite structures.

AtzF structure (the Australia crystal)

AtzF structure (the Australia crystal)

It’s the structure of AtzF. This enzyme forms part of the breakdown pathway for atrazine, a commonly used herbicide. We’re trying to understand enzymes better and use them for bioremediation – cleaning up environmental detritus such as pesticides and herbicides – and we’ve now solved the structures of four of the six enzymes involved in the atrazine breakdown pathway. We also look at protein engineering, to see if we can make these enzymes even more effective at cleaning up the environment.

Before we get to the crystal image, there are other steps on the way. First, someone has to grow the crystals (clone the protein, express it, purify it and crystallise it). Then it’s off to the Synchrotron to get a data set (many diffraction images in sequence). Here you can see an actual protein crystal.

An actual protein crystal

An actual protein crystal

The picture on the right is the diffraction image.

Diffraction image

Diffraction image

The crystallographers measure the intensity of the reflections (the dark dots). They combine that with the geometry and use some complicated maths (a Fourier Transform) to produce an electron density map. They then use that map to build a model.

Not all our crystallography work is in the same area. We also work on some pharmaceutical applications. One of our projects, with hugely important implications for human health, is on the design of desperately needed new antibiotics.  We’ve been collaborating with Monash University, looking at the pathway that sulpha drugs (such as sulfamethoxazole)– the ones we used to treat bacterial infections prior to the discovery of penicillin – take to treat Golden Staph infections in humans. The aim is to design new antibiotics that target the same pathway. You can read a paper that describes our recent findings in the Journal of Medicinal Chemistry, and here’s a picture of what we’ve been doing.

Golden Staph treatment pathway

Golden Staph treatment pathway

We think this deserves its own Year. And we hope it’s clear just how important it is. Crystal clear.


Making STEM deadly

Picture of Tayla Macdonald

Tayla Macdonald

Before she went on a science and maths camp, 19-year-old Tayla Macdonald says, she didn’t have a huge interest in science. She wanted to be a journalist.

But the camp made science significant and meaningful to her, and to her family’s Aboriginal roots. Tailored for Indigenous students, the camp blended science with Aboriginal culture, involving fieldwork and activities at culturally significant sites.

‘The camp gave me the belief that a science degree could be possible and that perhaps it wouldn’t be as difficult as I thought it was. I felt like it opened up new possibilities and choices I hadn’t considered before,’ says Tayla.

Three years later and Tayla is studying medical science, hoping to specialise in paediatrics and work either in regional communities or in humanitarian aid.

Initiatives like this are important, because Aboriginal and Torres Strait Islander students’ participation in science, technology, engineering and mathematics subjects at university and in related professions is significantly lower than the Australian average.

Alarmingly, an international survey showed that, overall, Aboriginal and Torres Strait Islander students are around two-and-a-half years behind their peers in scientific and mathematical literacy, and this gap has remained the same over ten years.

The reasons for this are complex, but our research shows that tailored learning programs can make a real difference.

That’s why we’ve partnered with BHP Billiton Foundation to deliver a new education project for Aboriginal and Torres Strait Islander students that aims to increase their participation and achievement in science, technology, engineering and mathematics (also known as STEM).

The five-year project is expected to involve Aboriginal students from all states and territories, from primary school through to tertiary education. It will cater to the diversity of learners – from those in remote communities through to high-achieving students attending mainstream schools.

Our research shows that community engagement, learning on-country and long-term investment and collaboration are vital for improving Indigenous education outcomes in science and maths subjects.

We’ve designed the project incorporating these elements, along with hands-on, inquiry-based learning approaches. There’s an awards program to recognise and reward high-achieving students.

This tailored approach will provide students with the learning setting and support they need for their best chance to achieve.

We hope students who participate in the program will consider taking up a career in science, just like Tayla.

Read more about our education program for Aboriginal and Torres Strait Islanders.


The spice is right: how curry and the cloud may improve Alzheimer’s testing

By Carrie Bengston, James Davidson and Olivier Salvado

Mmm . . . lovely! A hot Indian curry is simmering away on the stove on a wintry night. The smell of spices fills the kitchen. One of the spices is turmeric, from the ginger family. Its vibrant yellow colour comes from the compound curcumin which is finding a use in clinical tests for Alzheimers disease (AD).

Who knew? Soon everyone will! We’re presenting our research this week at a major conference in Copenhagen, AAIC2014.

Indian curry in a dish

Curry night! The golden yellow spice turmeric contains curcumin – a key ingredient of a new eye test for Alzheimer’s

A clinical trial of the spice-infused eye test is being led by our own Dr Shaun Frost and team, with WA’s Edith Cowan University, US company NeuroVision Imaging, and the McCusker Alzheimer’s Research Foundation in Perth. Several hundred volunteers have taken part. They include healthy people, mildly cognitively impaired people and patients with AD. It’s all part of the Australian Imaging Biomarkers and Lifestyle study of Aging (AIBL)

The trial asks volunteers to come along to two visits for retinal fluorescence imaging, ie an eye scan. This is quick and painless. Patients sit in front of a specialised camera and a photo is taken of the retina at the back of their eye.

Patient having eye scanned by researcher

Dr Shaun Frost takes a photo of the back of a patient’s eyes, not for Instagram but for a clinical trial

Between visits, volunteers eat some curcumin which binds to beta-amyloid plaques, the sticky proteins that indicate Alzheimers, and fluoresces. The plaques (if there are any) show up in the eye scans as bright spots which can be counted and measured. The data is then used to calculate a special number for each patient, a retinal amyloid index (RAI), and compared between healthy, mildly cognitively impaired and AD patients.

Bright spots showing Alzheimer's plaques in retinal scan

Amyloid plaques, a sign of Alzheimer’s, show up in retinal scan as fluorescent spots as curcumin binds to them

Encouragingly, as we announced this week, early results show the amount of plaque in the retina closely mirrors the amount in the brain. If confirmed, retinal imaging may be the beginnings of an easy, non-invasive test for early detection of AD. Combined with results of cognitive tests and other markers it could help doctors diagnose AD more confidently.

Eye scans like this also find plaques when they’re smaller than the ones in brain scans, potentially finding signs of AD earlier – maybe up to 20 years before cognitive symptoms appear. If diagnosed, AD patients could start treatment sooner and have regular eye scans to see which treatments work best for them.

Brain imaging on the cloud

From curry to the cloud. More research presented this week is about more accurately interpreting brain images sometimes used to diagnose AD.

To get a brain scan, a patient lies on a bed in a large machine like a Magnetic Resonance Imaging (MRI) or Positron Emission tomography (PET) scanner. These machines record a series of images through the brain, which are then visually checked by a radiologist who compiles a report for the patient’s doctor.

This visual inspection can be subjective, tedious and time consuming. But recent advances in scientific computing and machine learning allows systems to accurately measure features of the 3D scan, such as brain size or concentration of a tracer molecule, that support a diagnosis.

Using these techniques, a new trend is emerging for improving radiologists’ productivity. Scanners and specialised medical software can report quantitative values and compare them to the values expected for normal, healthy patients – just like blood test results from a pathology lab do.

Our researchers, led by health imaging specialist Associate Prof Olivier Salvado, have just released a new cloud computing application, MILXCloud, that automatically delivers standardised radiology reports.

brain surface showing the concentration of a radioactive dye imaged by PET scan

Our new software, MILXCloud, automates brain scan analysis and reporting on the Cloud

Users will be able to upload a PET scan and within 15 minutes be emailed a one page quantitative report showing a diagram of the brain with colour coded values compared with what’s normal. This data will help support diagnosis by the radiologist and enhance delivery of eHealth services.

Whether it’s curry or the Cloud, the future of Alzheimer’s detection sure looks bright.

Media: Andreas Kahl  |  0407 751 330  |  andreas.kahl@csiro.au


Baking bread by the numbers

Whether it’s sourdough, seeded rye, gluten-free or plain old white, there’s nothing like tucking into a fresh slice of bread. And it’s little wonder this age-old staple tastes so good – experts have been perfecting the art of bread making for thousands of years.

If we had to name who’s involved in bread making, most of us would probably identify the baker, the farmer who grows the wheat and maybe even the miller who grinds the wheat into flour. But how many people would think of the humble statistician? Dr Emma Huang would – and she’s eager to prove their worth in the process.

Statistical genius (er, geneticist) Emma Huang (second from left) is crunching the numbers for a better loaf of bread.

Statistical genius Emma Huang (second from left) is crunching the numbers for a better loaf of bread.

Emma is a statistical geneticist working with our Computational Informatics and Food Futures teams. She spends her days searching through thousands of genes for the few that affect yield and disease resistance in wheat.

By understanding the complex genetics of cultivated plants like wheat, Emma is helping farmers select the best crop varieties needed to produce the perfect loaf of bread.

“The impact of statistics in bread making starts well before preheating the oven. Statisticians are crucial in implementing efficient experimental design to compare different varieties of wheat for desirable characteristics,” says Emma.

After completing a Bachelor of Science in Mathematics at Caltech and a Doctor of Philosophy in Biostatistics at the University of North Carolina, Emma left the States to join our team in Brisbane.

Here she is using her mathematical expertise to detect regions of the wheat plants genome – or its inheritable traits – that are directly related to enhanced crop performance. This allows breeders to selectively breed specific genes, reducing the amount of time it takes to improve our food supply.

Her goal is to eventually be able to model the entire process of bread making, incorporating the effects of environment and genetics all the way from growing plants in the field, to milling the flour and baking the bread.

Performing some personal culinary research at the world famous El Celler de Can Roca restaurant in Spain.

Performing some personal culinary research at the infamous El Celler de Can Roca restaurant in Spain.

When she’s not crunching numbers in the name of food, Emma does her own private research into the best cuisine the world has to offer, indulging at world class restaurants like Spain’s El Celler de Can Roca. But fitness freaks don’t fret, she works off the extra calories playing water polo and going for ocean swims.

“Sometimes I think I was destined to be a statistical geneticist. Both my mother and aunt are qualified statisticians, my siblings all studied mathematics at university, and even my fiancé is a statistician!”

Who better to investigate the impact of genetics on our everyday life?

For more information on careers at CSIRO, follow us on LinkedIn.


The maths behind a zombie apocalypse

Could maths help us prepare for a zombie apocalypse? Image: Pedro Vezini.

Could maths help us prepare for a zombie apocalypse? Image: Pedro Vezini.

By Carrie Bengston

What would happen if zombies invaded the planet? World War Z tells the story with Brad Pitt and a much bigger film budget than we have.

But it will hearten you to know that a team in Canada has actually crunched the numbers for a zombie apocalypse. They created a mathematical model for zombie infection, suggesting that only quick, aggressive attacks can stave off the doomsday scenario.

The take home message from the maths? Hit ‘em hard and hit ‘em often.

Maths can help us explore all kinds of real and hypothetical scenarios. You might not think it, but maths is vital in understanding the complex and dynamic planet we call home.

This was made clear last week at Mathematics of Planet Earth Year: The Conference, where over 200 people gathered to hear what maths is telling us about our precious planet.

Phenomics_animated

Maths helps us accurately measure organism characteristics through 3D phenotyping.

For our young graduate fellows who are test driving a maths research career, the conference was a chance to see the limitless applications of their chosen field. These include an amazing variety of natural and human-organised aspects of planet Earth discussed during the conference.

From understanding climate and weather patterns to identifying pests that threaten our biosecurity using 3D insect imaging, it was evident how important maths is in understanding the many challenges facing Earth today.

Mathematical modelling has even been used to protect people in earthquake-prone areas, promote sustainable dairy farming and watch a virus spread within a plant.

Maths adds a lot of value to our own research too. For instance, our mathematical scientists have contributed to important discoveries about Alzheimer’s disease. Take a look:

***

2013 is the International year of Mathematics of Planet Earth. Learn more about how maths and stats are helping us understand the challenges of our world.


Going nuts with the Canberra distance

By Arwen Cross

Love it or hate it, Canberra is our capital city. But it isn’t the only thing named Canberra. Hamish Boland-Rudder has found five other things with the same name, which he described in an article in the Canberra Times last week. It looks like most of them post-date our 100 year old capital, and were named after it.

Canberra is an indigenous placename, but sadly we don’t know what it means or exactly what location the name originally referred to. Some popular suggestions about the meaning of Canberra are ‘meeting place’ or, more racily, ‘the space between a woman’s breasts’, referring to the shapes of Mt Ainslie and Black Mountain. Linguist Harold Koch’s research shows that neither of these explanations is very believable (see page 153, Chapter 5 of Naming and re-naming the Australian landscape). But it’s a rare honour for an Australian capital city to have an indigenous name.

The Canberra distance

One of the things that’s named after the city of Canberra is the Canberra distance, a mathematical function used to sort things according to their similarity.

The Canberra distance was invented by CSIRO scientists Bill Williams and Godfrey Lance in the 1960s. They developed it based on the Manhattan distance, which may have inspired them to name it after their own city, Canberra.

road sign showing distance to Canberra

The Canberra distance isn’t an everyday distance between places. Photo adapted from: jczart on Flickr.

The Canberra distance isn’t a distance in the everyday sense like how far away ANU is from the nearest pub. Mathematicians recognise lots of different types of distances, for example:

  • Euclidian distance – the straight line distance between two points. This is similar to our everyday idea of distance.
  • Levenshtein distance – the distance between two words measured by how many single-character edits are needed to change one into the other.
  • Canberra distance – a measure of similarity and dissimilarity between groups.

So what can you use the Canberra distance for?

It’s often used to sort plants and animals into groups that are more closely or distantly related to each other. Although it can be used outside biology too.

Two sheep and a goat

The Canberra distance can be used to group individuals according to how similar and dissimilar they are. Photo: A. Cross

Let’s say you want to separate the sheep from the goats in your large herd. You might need to consider several criteria to make your decision:

  • Binary data – has a beard/doesn’t have a beard
  • Ordered categorical data – hair very woolly/ hair moderately woolly/ hair not woolly
  • Quantitative data – a measurement like weight in kilograms or height in centimetres

The Canberra distance is a way to use all these criteria together to separate individuals according to how similar or dissimilar they are. In our case, we’ll separate the herd according to how sheepy or goaty they are.

If you’ve got a large herd, you’d start by measuring all the criteria for each animal. Then you’d need some statistics, including the Canberra distance, to cluster the data into groups of animals that were similar across several characteristics.

You might find that your herd was made up of three groups of animals: a large cluster of animals with sheepy characteristics, a small cluster with goaty characteristics, and another cluster of animals that is part sheep and part goat.

Going nuts with peanut research

An actual example of the use of the Canberra distance in biological research comes from peanut breeding. Our chief mathematical scientist Bronwyn Harch worked on this project for her PhD. Instead of separating sheep from goats, she was organising peanut plants into groups.

Peanut plants are an important agricultural crop, and plant breeders are always working on new varieties that will grow better in particular climates, be more resistant to disease, or produce a better quality peanut.

To do this they keep collections of seeds from many different peanut varieties. Some wild peanuts might be very resistant to disease but have a poor yield of nuts, while commercial varieties might be disease sensitive but high yielding. Peanut breeders cross varieties to generate new ones and select the offspring with desirable characteristics.

a peanut plant showing leaves and peanuts on roots

There are lots of varieties of peanut plants. Photo: Wikimedia Commons.

Bronwyn looked at the characteristics of peanuts in the Australian peanut collection and in the world peanut collection in India. Her analysis helped her advise Australian peanut breeders about what characteristics were missing in their collection that they could find in the world collection. Her work also informed scientists going into the Amazon rainforest to collect new peanut plants from the wild about what characteristics to look out for.

The Canberra distance is a useful mathematical tool. But now I’m going to put my feet up and enjoy some of Hamish Boland-Rudder’s other Canberra discoveries – perhaps a glass of Canberra ale.

I would like to thank David Nash and Bob Anderssen for their advice on this article.


A little drop of π for pi day

By Carrie Bengston and Arwen Cross

Every time you sneeze, droplets of snot shoot out of your nose and mouth (that’s why you should cover your mouth when you sneeze). But did you know droplets are roughly spherical and you need π to describe their shape?

Today is pi day because the date is written 3.14 in some parts of the world. So we’re bringing you an example of how our researchers use π.

a man sneezing with pale droplets visible against the dark background

When you sneeze, small droplets come out of your nose and mouth. They’re roughly spherical. Photo by Public Health Image Library.

Our mathematicians are interested in droplets. But Benny Kuan and Peter Witt aren’t studying snot, they’re studying droplets of hot magnesium. Their work will help perfect a new way of producing magnesium called MagSonic.

MagSonic works by blasting hot magnesium gas out of a nozzle at four times the speed of sound (over a kilometre per second) and allowing it to cool in a vacuum at a rate of more than a million degrees Celsius per second. The magnesium gas condenses to form liquid droplets before solidifying into powder.

MagSonic purifies magnesium more efficiently than existing methods, so the MagSonic team leader Leon Prentice and his team won the 2013 Vittorio de Nora prize for Environmental Improvements in Metallurgical Industries.

Producing magnesium efficiently is important because we use the metal for many purposes. These include alloys of magnesium and aluminium for lightweight applications like building aircraft and rockets, in certain batteries and as an additive in steel.

Diagram showing a long tube with a nozzle at one end and a wide chamber at the other

Cut away diagram of the MagSonic™ Rig showing the nozzle and chiller chamber.

π is a key character in the MagSonic story, because when you’re making magnesium using MagSonic you have to be careful that the reactor doesn’t get blocked with metal. This depends on how quickly the magnesium gas condenses and solidifies as it comes out of the Laval nozzle. π comes in because the calculations about condensing droplets assume they’re spherical (although in practice they’re often ellipsoidal shaped).

Our mathematicians Benny and Peter are using mathematical modelling to optimise the shape of the Laval nozzle and the MagSonic reactor. How fast the droplets condense, and whether they do that in the nozzle or after they’re sprayed out, depends on lots of things including the shape of the Laval nozzle.

In the MagSonic process hot gas moves at supersonic speed through the nozzle and then condenses and solidifies. The shape of the nozzle determines the rate at which the gas accelerates to and beyond the speed of sound. The speed of the gas is one of the factors that affects how fast it condenses.

π appears frequently when you calculate parameters like the speed of the droplets and the rate of nucleation and condensation. That’s because the spherical droplet’s surface area, volume and cross-sectional area are needed to calculate several things. These include the drag on droplets, how heat is transferred between the droplets and the gas, and whether the droplets grow in size as they condense.

Any high school student can tell you that you calculate the volume of a sphere by cubing its radius and multiplying by π and by four thirds (volume = 4/3 π r3). You can apply similar equations to the magnesium droplets condensing from gas.

Benny and Peter used these equations in their computer models to design nozzles for MagSonic. Then Leon and their other colleagues in the lab tested the new nozzle designs.

Now they’ve got a MagSonic reactor that doesn’t get blocked – thanks to π, computer modelling, and experimentation.

Man standing at a whiteboard covered in mathematical equations

Benny Kuan demonstrating some of the equations he used for the MagSonic project.

Benny says he never thought the strange, irrational number he learnt at school would be so useful in his job doing maths for light metals research – but it is !

Thank you π!

A few facts about π

  • π is irrational, so if you try to calculate it precisely, the decimal places never stop or repeat.
  • People memorise it for fun – the record is currently 67 890 memorised digits.
  • π was known in ancient Egypt and Babylon, but the Greek scholar Archimedes developed the first rigorous approach for calculating π (using polygons).
  • The Greek letter π has only been used to represent π since the mid-18th century.

Read more

Check out the pi day activities on the Helix Blog and read more about π fun via the Maths of Planet Earth site.


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