In a nutshell:
Fully automated single molecule measurements allow scientists to probe complex biological networks in living cells.
Technique holds promise for understanding of disease and drug discovery.
A new approach for studying the behaviour of proteins in living cells has been developed by an interdisciplinary team of biologists and physicists in the Cell Biology and Biophysics Unit, the Ellenberg group and the Advanced Light Microscopy Facility at the European Molecular Biology Laboratory in Heidelberg.
Described in a new study, published today in Nature Biotechnology, the approach allows scientists for the first time to follow the protein networks that drive a biological process in real time.
Which proteins interact with each other and where they meet within cells is of huge interest to scientists because it reveals the state and activity of the molecular machinery that drives the most fundamental functions of life such as the ability of cells to divide. The new technique will also be useful for scientists to investigate the mechanisms of disease and for pharmaceutical companies to explore new drug targets.
At the heart of this technology is a method called fluorescence correlation spectroscopy (FCS). Originally developed in the 1970s, FCS enables scientists to track individual proteins inside living cells once they have been fused to a fluorescent marker. FCS can measure where proteins move and when they meet, in a similar way to how Google can track people in traffic jams with their smartphone GPS signals.
Each green image shows a cell expressing a green-labelled protein of interest. Each red image shows the chromatin/DNA distribution in the cell. The opposing graphs show representative FCS measurements recorded in the cells. Image: Petra Riedinger.
Although such data would be tremendously valuable to have for all the proteins within a cell, until now FCS microscopes have been very cumbersome to use and the data difficult to interpret. The new development at EMBL automates the whole process of measuring protein behaviour and analysing the very large amounts of single molecule data.
“Our approach enables huge time savings” explains Malte Wachsmuth, of EMBL, who co-authored the study. “Whereas previously a scientist might spend a day observing one protein in a few cells, we can now acquire data from tens of proteins in thousands of cells fully automatically.”
“Because we have made FCS into a high throughput method, we can acquire data from many different proteins, which is key to studying biological networks that typically consist of tens to hundreds of components” says Jan Ellenberg.
The research was jointly funded by EMBL and the European Union. The team plans to exploit the method now to build up a “Google map” of the proteins in a living cell.
Wachsmuth M. et al. High-throughput fluorescence correlation spectroscopy enables analysis of proteome dynamics in living cells. Advanced online publication in Nature Biotechnology on the 16 March, 2015. DOI: 10.1038/NBT.3146
To understand the function of cellular protein networks, spatial and temporal context is essential. Fluorescence correlation spectroscopy (FCS) is a single-molecule method to study the abundance, mobility and interactions of fluorescence-labeled biomolecules in living cells. However, manual acquisition and analysis procedures have restricted live-cell FCS to short-term experiments of a few proteins. Here, we present high-throughput (HT)-FCS, which automates screening and time-lapse acquisition of FCS data at specific subcellular locations and subsequent data analysis1,2. We demonstrate its utility by studying the dynamics of 53 nuclear proteins3,4. We made 60,000 measurements in 10,000 living human cells, to obtain biophysical parameters that allowed us to classify proteins according to their chromatin binding and complex formation. We also analyzed the cell-cycle-dependent dynamics of the mitotic kinase complex Aurora B/INCENP5 and showed how a rise in Aurora concentration triggers two-step complex formation. We expect that throughput and robustness will make HT-FCS a broadly applicable technology for characterizing protein network dynamics in cells.
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