I got really excited about this research and just had to share it. I might be biased because it’s in my field of interest and uses some sexy maths, but I hope you enjoy it too. Many important compounds we use, like drugs and fragrances, are complex molecules. They’re often found in nature and produced by organisms like plants or marine life. Problem is, if we want a large amount of compound it can be hard to obtain. A good example is the cancer drug taxol (paclitaxel) that originally required killing up to four pacific yew trees to obtain one course of treatment. Thankfully, scientists have found a more efficient way to make the drug, but like many drugs and fragrances it still involves extraction from a natural source, which is expensive and wasteful. For some compounds, like the anti-malarial artemisinin, it also means the price of the product can fluctuate wildly depending on agricultural factors, demand and supply. Sometimes it is possible to make the product synthetically in a lab instead, but this depends on how complicated the product is and the availability of suitable starting materials. Clearly there is a need to develop better ways of making these important compounds.
Enter microbial biosynthesis. Microbial biosynthesis basically involves using a microbial organism, like yeast, bacteria, algae or fungi, to synthesise a useful product. This can be achieved from simple feedstocks (like corn syrup or plant by-products) through a fermentation process. The metabolic pathways of the organism are genetically manipulated to maximise production of the compound of interest, which could be anything from drugs and nutraceuticals, to fragrances and cosmetics, or even biofuels. Usually microbial biosynthesis is achieved using a single strain – that is one type of yeast or bacteria etc. This can be more efficient because it means intermediates don’t have to be transported across cell membranes but it has several downsides for complicated pathways. Firstly, the more complicated a pathway is, the more potential for metabolic ‘cross talk’ where the production of one intermediate unintentionally influences another metabolic pathway. Secondly, if an intermediate is toxic to the organism it will gradually cause mutations or death of high-producing populations leading to an overall lower yield of product. Thirdly, the burden of having to produce large amounts of compound in a single cell can slow down other metabolic processes meaning lower cell growth and ultimately less product. To get around this, an alternative is to use multiple cell types, such as combining two different types of bacteria, or a bacterial strain and a yeast strain, to share the load (Division of Labour). The idea is that one organism will produce an intermediate which is then used by the second organism to make the product. While this can reduce overall complexity by dividing tasks between the organisms, it can be limited by how well the intermediates are transported in and out of the cells. While division of labour has been used for individual cases, there’s no blanket rule or easy way to tell if it’s better to use one cell strain or multiple for any given project. Think about it like a team working on a project: sometimes it’s more efficient to just do all the work yourself rather than try and chase up people and pass documents around, but sometimes working as a team can lead to a better outcome. But how can you decide which way would be better? A team of researchers at Duke University have developed a model to understand the factors that influence productivity in a microbial system. They took into account things like enzyme production, rate of transport into and out of cells, rate of intermediate and product synthesis, and cell volume and growth to determine when it is more beneficial to use division of labour over a single strain. Effectively it boils down to two things: how fast the cells are growing and how well the intermediate is transported between the cells. From this, the researchers have come up with a general criterion to assess the efficiency of division of labour. Ideally, a scientist would be able to test these factors experimentally and use the model to decide which scenario is most appropriate for their project. Microbial biosynthesis is still relatively in its infancy in terms of industrial applications, but as technology improves, with the help of modelling systems like this one, more efficient syntheses can be achieved for the cheaper and more environmentally friendly production of important molecules.
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How many times have you watched a murder mystery show where the detective strolls into the murder scene and inspects the victim’s body for just a few moments before confidently declaring the time of death? This may not come as a surprise, but in real life it’s not that simple. In the first few hours, time of death is usually estimated by taking into account physiological factors, like body temperature, rigor mortis and skin discolouration. However, these methods are still largely unreliable and inaccurate, as they can be influenced by a number of factors including the ambient conditions, cause of death, body structure, body location, and drug consumption. Researchers have been searching for ways to make estimating time of death more accurate, and one of these new methods involves looking not just at the body as a whole, but analysing what is inside cells at the molecular level.
Our genetic information is stored in cells as DNA. In order for that information to actually do something, in needs to be read. When DNA is read it is transcribed into RNA, which is then translated into proteins that undertake some action in the cell. When a tissue dies, the cells in that tissue undergo changes in gene expression. A team of researchers in Portugal and Spain has looked at how gene expression changes after death by analysing RNA levels in pre-mortem and post-mortem samples. They found that each tissue exhibits specific changes in gene expression that is not consistent with random RNA degradation but actually a result of active and ongoing gene regulation, even after the organism dies. These changes are speculated to be caused by low oxygen as the blood supply to the tissue is lost. Each tissue type has its own unique pattern of changes in gene expression over time since death. From this, the researchers built a model that can be used to estimate time of death by looking at RNA levels in tissues that are likely to be found in a forensics scenario, including fat, lung, skin and thyroid tissue. They also found no impact of cause of death on their estimates. This technique could not only improve time-of-death estimates in forensic pathology, but also assist researchers working with post-mortem tissue samples and have implications for organ preservation and transplantations. Also, if you’re curious as to how forensic scientists determine time of death after days, or even weeks and months, check out this article on forensic entomology. The world population is predicted to reach 9.8 billion by 2050. In order to feed this number of people, we need to dramatically increase cereal yields, above what is already being achieved by plant breeders. Wheat is one of the oldest and most important cereal crops. Without it we wouldn’t have tasty food like bread, pasta, cake, and pizza. (I get hungry just thinking about wheat. So delicious). Some of the factors that can be selected for to improve wheat yield include nitrogen uptake, leaf mass and photosynthetic efficiency. However, in order to select the best plants for breeding, all of these factors need to be measured. Traditionally these measurements are time consuming, destructive, and require special facilities, which is not practical on the large scale required for plant breeding. Ideally, researchers want to be able to tease out genetic markers they can look for that will tell them if a plant, or its offspring, will be high-yielding. However, considering the wheat genome has 6 times more base pairs than humans, this is no easy task!
Recently a group of researchers at the ARC Centre for Excellence for Translational Photosynthesis sought to speed up the wheat-analysis process. They wanted to see if hyperspectral reflectance– that is reflecting light in colours beyond the visible spectrum, like UV and infrared – could be linked to photosynthetic- and biomass-related traits. To test this they grew a lot of wheat plants in a greenhouse and took measurements of traits like carbon dioxide conversion, leaf mass, nitrogen content and chlorophyll content, as well as the leaf reflectance over a full range of wavelengths (350 – 2500 nm, or UV-Vis-Infrared). They then put these measurements together to construct a statistical model of how well hyperspectral reflectance can be linked to the measured traits. Their model is able to provide robust estimates for 6 traits that are linked to wheat yield, biomass and photosynthetic ability. The importance of this technique is that it is very fast compared to traditional methods. It used to take researchers 20 minutes per leaf to obtain this kind of information, but using hyperspectral reflectance approximately 100 plants can be analysed within an hour. Higher-throughput will make it easier to screen large populations for breeding and to identify genetic markers that will increase wheat yield. The researchers hope to expand their model by adding more leaf properties to measure, and the technique is starting to be used for other crops including corn, rice and sorghum. Down the track, using hyperspectral reflectance will hopefully lead to higher grain and cereal yields to meet the demands of a growing population. Whether you say ‘lay-go’, ‘leg-oh’, or ‘lee-go’, we can all agree that LEGO is pretty awesome. Personally, my childhood was filled with LEGO houses and castles, tower building competitions, and shredded fingernails from trying to prise apart small plates (did you know they have a tool for that now?). One of the best things about LEGO is that you can create almost anything, from giant sculptures to a working mechanical keyboard. But who knew LEGO could be so versatile that it could be used to build a tiny, modular, microfluidics lab? Microfluidics is basically the manipulation of fluids on a really small scale. Fluids are moved, mixed, separated or otherwise processed through tiny capillaries on the sub-millimetre scale. This can be used for things like enzymatic analysis, DNA sequencing, continuous testing for pathogens or toxins, and many other biological, optical and chemical applications. Microfluidic devices usually take the form of a ‘lab on a chip’ – a tiny, flat surface etched with channels and ports to manipulate the flow, mixing, and separating of the fluid. However, the problem with this is that so far there’s no universally accepted way to construct this device, meaning each one needs to be custom synthesised for its purpose, and it’s hard to mix and match devices. On top of that, they’re not exactly easy to make either as 3D printing is not yet precise enough for this purpose so construction usually requires expensive facilities, materials and labour. An alternative method is to use a modular system, that is, each module performs a single function. And scientists at MIT have found a novel platform: LEGO bricks. In their recent paper, published in Lab on a Chip (cool journal name btw), Crystal Owens and John Hart explored the use of LEGO bricks to build a microfluidic platform. They went out to the shop and bought an off-the-shelf LEGO set, and used a micromilling technique to precisely etch tiny channels into the bricks. To seal the faces, the bricks were covered in a thin plastic film, and brick modules were joined via an O-ring. Because LEGO bricks are so consistent in size and fit together easily, the O-rings formed reliable and reversible seals that allow the microfluidic device to be literally ‘clicked’ together. While this system is cheap to build and extremely reliable, it isn’t perfect yet. Firstly, the micromilled channels are relatively large and not suitable for many applications. They’re also made of plastic so they wouldn’t be suitable to use with some organic solvents. Future work will look at different types of materials and different ways of constructing the bricks so they can be used for a wider range of applications. But for now, a LEGO ‘lab on a brick’ could be the future of prototyping these tiny microfluidic devices. |
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Emi Schutz Archives
March 2018
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