Overview

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Speaker: My research is interested in understanding how bacteria coordinate their activities as large populations of individual entities. And the reason we want to do that is because bacteria tend to live as communities, not individually. And by understanding how they do what they do, we will hopefully come up with better ways of preventing and treating infection. The most exciting that our research has revealed is that the rules that bacteria use to coordinate their own multi-cellular behaviours are very similar to the rules that higher organisms use to coordinate group behaviours. For example, how termites build their nests, and how ants are able to forage after food, and even how humans control traffic and how we follow pedestrian paths and hiking trails that other people have built for us. These are the same rules that bacteria are using to coordinate their behaviours to create these amazingly complex, self-organised communities. It’s important that we know that, because many bacteria use this behaviour to be able to migrate across surfaces to actually spread infections. If we can understand how the bacteria are coordinating their behaviours, maybe we can actually then impose our own will on the bacteria so that we can then stop that behaviour. This is really important in this day and age because we’re entering a global crisis of antibiotic resistance, and it’s really imperative that we understand how bacteria cause infection, and by understanding the basics of how they do that, we may be able to come up with new and novel ideas as to how to prevent and treat infections, either by creating new antibiotics, or preferably even by using non-antibiotic approaches.

 

Speaker: The Data Arena has helped with our research in that it’s been able to provide us with a real powerful visual tool to be able to to interact with our data in a way that we haven’t currently been able to do so. So what we’re currently doing is developing a pipeline to convert our visual data, the movies that I’ve been making in the lab, segment and outline each individual cell to get the coordinates for each cell across a given time period, and we can then bring in those data into the Data Arena and recreate the movie using that data. And from that, we can then start looking at, in a lot more detail, the quantitative behaviour of the cells in a way that we haven’t been able to do so before. So for us, it’s really powerful in giving us a better understanding of how the bacteria can coordinate together and act as a cohesive entity.

 

Speaker: My role at UTS is to actually run a very high-end microscope, what’s called a super resolution microscope, within the microbial imaging facility within the Faculty of Science here. My role with the Data Arena has been to try and make a simple pipeline for people who want to use the microscope to be able to bring their data across to the Data Arena in a simple way. So with the Data Arena, we can actually zoom into an image but we can still see the whole image, whereas if you work with a normal small computer screen, if you zoom in to see a detail, you lose the rest of the image and you can only see that one small spot. The most exciting thing that I think we’ve done so far is we’ve put up some images of what are very small bacteria or parasites. Because they’re three-dimensional you can actually spin the around, and you actually find yourself ducking to get out of the road of this thing that you know is smaller than the width of your hair, but it looks the size of, you know, a couple of human beings. So on the screen you can see a pig lung cell, and this pig lung cell has been infected with a very small bacteria. We can actually see the topography of the pig cell itself, so it looks like hills and valleys, and we can see where the bacteria are sort of preferring to interact with that cell. With tools like the Data Arena being a very powerful visual tool, because we always say seeing is believing, we can take this knowledge that we get and visually present it to the public, and I think it’s very important part of being a scientist is to use these tools to communicate our knowledge to the public so that they become more scientifically literate, and to understand the great stuff that’s being done within Australian universities and here at UTS.

 

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Speaker: The project that I’m working on, it deals with pipes, basically, the large type of pipes that you and I drink water from. These are the ones that are in the main avenues of cities such as Parramatta or right outside UTS. And the idea is that we want to analyse the data that is being used to inspect those pipes with various techniques, so that we can catch them before they break. One of the key aspects of this projects is to go and actually exhume pipes; we actually take them out of the ground, and then we inspect them with very high definition 3D lasers that give you point clouds, so the idea is that when you dig them up and actually scan them, you have loads and loads of points – we’re talking about millions of points. Dealing with that data is obviously a challenge, so the idea here is that we are able to manipulate and represent that data in a manner that we can easily find the crevices and the holes that we’re looking for. This pipe, the colours that you see in this particular pipe tells you what is the remaining wall thickness – how thick is the wall? So red colours means that there is less remaining wall thickness, yellow colours means there is more remaining wall thickness. Less remaining wall thickness equates to holes, cracks and eventually the pipe will not actually be able to withstand the water that’s inside it; it just breaks. I believe the potential of the Data Arena for industry and for research in general is the ability to visualise structures, as a matter of fact. You know, a pipe allows you to see large volumes of data and gives it a physical meaning, so think of molecules, think of buildings, think of large networks, rail tracks or whatever – things that actually allow you to [inaudible] manipulate that data. I think that brings a lot of value. But also it’s been very useful from the point of view of the partners themselves, because they’ve never seen their own assets this way; they always see an asset as just a number on their big spread sheets and you know, their asset management so when we’ve had them over here, which have come and have a look at the data, they’ve been quite in awe at seeing ‘Ah! So this is what my asset number x and x and x looks like.’ One of the most exciting things is probably coming to the realisation that this is a project that spans all of the world. Everybody has got pipes; in developed countries everybody needs drinking water. So it’s nice to be able to have a project that has such a widespread impact and that is why they’ve actually come on board in the first instance and given us money to do this research.

 

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Speaker: The project itself was to map in very high detail an abandoned marble quarry at Wombeyan Caves for the National Parks and Wildlife Service. And so we contacted CSIRO that had this amazing device called a Zebedee, which is a handheld device – you just hold it in your hand – and as you walk along, it wobbles, and there’s a laser which scans back and forward 40,000 times a second, and as it wobbles about, it basically, effectively looks around the cave and takes thousands and thousands of measurements, and so after you just wander around the tracks and the cave for a few hours, you’ve scanned the entire cave. The reason why we like to scan caves and find this information out is on the scientific side, there’s still a lot of research going into how caves actually form, and so looking at the cave structure – it’s called the geomorphology of the cave – and looking at the shape of the cave, we can get a bit of a clue as to how the cave might be formed. We’ve discovered quite a few things by looking at the data in the data arena. When we look at Wombeyan Cave data, we can look at the roof and the sides of the cave, and you can see stream channels in the roof, which means it was formed by water moving through that cave system. And also, looking at the cave in 3D and considering the geology, we can look at the cave and think ‘Now, where else are there going to be undiscovered passages? Where would this cave continue on?’ The reason why the Data Arena is so special is that it’s got that ability to show you visually really, really complex datasets and sometimes when a dataset’s in tabular form or just data or in spread sheets, you can’t really see what’s going on. If you can visualise the data, the brain is one of the most fantastic computer devices we have, but it’s very visually orientated. And if you can then see a little pattern visually, then you can go back to a high performance computer and say ‘This is the pattern I’m looking for; find other patterns like that.’