A new development in cell analytics uses sound waves to sort cells. This researchers say will lead to the development of miniaturised medical diagnostic devices.
This new device utilises a set of acoustic tweezers. These are generated from the projection of two sound waves across a silicone membrane. These tweezers can be used to sort a continuous flow of cells into 5 or more channels. This sorting can be altered through adjusting the frequency of the acoustic waves.
Cell sorting devices are in a serious need of a revamp. Currently they are bulky, expensive and have the potential to damage cells. The technology is also limited because it can only sort cells into two channels over one step. This new method will change all this, creating efficient and miniaturised cell sorting devices. The aim is to produce a cell sorter that is the same size as a mobile phone; this could be used for blood or genetic tests.
The acoustic cell-sorting device uses a layer of silicone (polydimethylsiloxane) with two parallel transducers placed either side of the chip. These transducers convert alternating current into acoustic waves. These waves interfere with each other and by doing so form pressure nodes (channels) on the chip. Cells are then channelled towards these pressure nodes. The important point is that these transducers are tuneable. This allows different frequencies to be produced across the chip, allowing for different channels to be created.
To test the device a stream of fluorescent polystyrene beads were sorted into three channels. Before switching on the transducer the particles were not filtered. However as soon as it was the beads were separated into 3 distinct channels. The device was then used to sort human white blood cells, which were affected by Leukaemia, into five channels. A possible of 10 channels has been suggested as possible by the researchers.
This provides researchers with a serious advance in their ability to sort cells. Utilising a novel method to sort cells will enable researchers to work with greater flexibility. It is also more convenient, efficient and safer. Are there any other new technological advances that are exciting you?
Great new research is now allowing scientists to watch and manipulate stem cells regenerating tissue in real time. This can all happen without injuring the animal. In order to do this researcher have developed a new sophisticated imaging technique. This new technique has allowed a greater insight into how the tissue regeneration process works.
This study focused on stem cell behaviour within the hair follicles of mice. Due to the accessibility of these stem cells, the researchers were able to view the process in real time. The study used a 2-photon intravital microscopy. This new techniques works by using transgenic mice and near infrared light, to allow deeper penetration with less damage to the tissue.
Using this technique the study was able to observe the interactions between stem cells and their progeny. It showed that different stem cells were creating different cell types within the tissue. Further the interaction between these cells and their immediate environment determines how they will divide, where they will migrate too and in what way they will specialise. I hear you saying we already knew this. I agree, but the ability to visualise this in a uninjured animal, in real time, really bring the whole process to life and after all that’s what biology is about; real life.
The real ‘discovery’ in this project was in terms of mouse hair follicles. The study found that hair growth would not occur in the absence of the connective tissue mesenchyme, which appears early on in embryonic development. Stem cells are very important and as our understanding grows, they are only going to get more important. This is due to their ability to regenerate many other types of tissue in mammals. This study really highlights the importance of the microenvironment in determining stem cell behaviour. Armed with this knowledge we can uncover the mechanisms that go wrong in the cases of cancer and other diseases. This same technique has the potential to shed light on multiple different areas: what stimuli is required to trigger repairs in a variety of organs and how stem cells interact with other cells.
In recent times businesses have succeed or failed based on the power of their algorithms. The field of Genetics’ has also harnessed the power of the algorithms. Algorithms are being used to decode, sequence and compare various genomes. Genome searching has become a staple research practise and it is even starting to emerge into more clinical areas. However its major draw back is that it takes a long time, around 2 weeks, to carry out.
Scientists at MIT and Harvard universities recently have developed a new algorithm. This will significantly reduced the time required to search through a genome. This new algorithm improves efficiency in two key areas:
First a major issue when sequencing a genome is that you need to store the masses of data that is produced. There is so much data that you need to compress it. The draw back occurs when you return to look at this data you have to decompress it and this takes a lot of time. The new system works by using compressed data, therefore removing the laborious decompressing step and consequently saving time while maintaining the accuracy of analysis.
The second step utilises the extensive genetic overlap between closely related species. The team developed a system to mathematically represent different species. This mathematical modelling allows researchers to only store overlapping genomic data once. Therefore searches can now focus on the differences between species rather than wasting time on the areas of similarities.
Currently the most common genome-searching tool is BLAST, the basic local alignment search tool, this finds regions of local similarities between sequences. The team compared their algorithm to BLAST, in the analysis of 36 yeast genomes. The results showed that the new algorithm was twice as fast in comparing 10 of the genomes and 4 times as fast in comparing all 36.
The most interesting development, with this algorithm, is that it utilises the work you have already done. It always takes a set amount of time to analyse a genome. Due to certain properties of the genome there is overlap between samples, therefore this property can be used to speed up sequencing time.
This new technique has many potential applications such as: identification of new microbes, determining the cause of infection and even study physical evidence from a crime scene. What do you think? Are scientific algorithms as important as people make out?
Personalised medicine is all about you, who you are, what you have experienced and what you are made up of. In the year 2000, after 10 years of hard work, a working draft of the human genome was announced. This draft consisted of the identification and mapping of around 20,000 -25,000 genes. The identification and “decoding” of the human genome opened the door to a new breed of medical practise; personalised medicine. Continue reading