A Bayesian approach to tracking in single molecule fluorescence microscopy

Using fluorescence microscopy with single molecule sensitivity it is now possible to follow the movement of individual fluorophore tagged molecules such as proteins and lipids in the cell membrane with nanometer precision. These experiments are important as they allow many key biological processes on the cell membrane and in the cell, such as transcription, translation and DNA replication, to be studied at new levels of detail. Computerized microscopes generate sequences of images (in the order of tens to hundreds) of the molecules diffusing and one of the challenges is to track these molecules to obtain reliable statistics such as speed distributions, diffusion patterns, intracellular positioning, etc. The data set is challenging because the molecules are tagged with a single or small number of fluorophores, which makes it difficult to distinguish them from the background, the fluorophore bleaches irreversibly over time, the number of tagged molecules are unknown and there is occasional loss of signal from the tagged molecules. All these factors make accurate tracking over long trajectories difficult. Also the experiments are technically difficulty to conduct and thus there is a pressing need to develop better algorithms to extract the maximum information from the data. For this purpose we propose a Bayesian approach and apply our technique to synthetic and a real experimental data set.

Probing small molecule binding to amyloid fibrils.

Much effort has focussed in recent years on probing the interactions of small molecules with amyloid fibrils and other protein aggregates. Understanding and control of such interactions are important for the development of diagnostic and therapeutic strategies in situations where protein aggregation is associated with disease. In this perspective article we give an overview over the toolbox of biophysical methods for the study of such amyloid-small molecule interactions. We discuss in detail two recently developed techniques within this framework: linear dichroism, a promising extension of the more traditional spectroscopic techniques, and biosensing methods, where surface-bound amyloid fibrils are exposed to solutions of small molecules. Both techniques rely on the measurement of physical properties that are very directly linked to the binding of small molecules to amyloid aggregates and therefore provide an attractive route to probe these important interactions.

A simple bioconjugate attachment protocol for use in single molecule force spectroscopy experiments based on mixed self-assembled monolayers.

Single molecule force spectroscopy is a technique that can be used to probe the interaction force between individual biomolecular species. We focus our attention on the tip and sample coupling chemistry, which is crucial to these experiments. We utilised a novel approach of mixed self-assembled monolayers of alkanethiols in conjunction with a heterobifunctional crosslinker. The effectiveness of the protocol is demonstrated by probing the biotin-avidin interaction. We measured unbinding forces comparable to previously reported values measured at similar loading rates. Specificity tests also demonstrated a significant decrease in recognition after blocking with free avidin.

Kinetic modelling of growth and storage molecule production in microalgae under mixotrophic and autotrophic conditions.

In order to improve algal biofuel production on a commercial-scale, an understanding of algal growth and fuel molecule accumulation is essential. A mathematical model is presented that describes biomass growth and storage molecule (TAG lipid and starch) accumulation in the freshwater microalga Chlorella vulgaris, under mixotrophic and autotrophic conditions. Biomass growth was formulated based on the Droop model, while the storage molecule production was calculated based on the carbon balance within the algal cells incorporating carbon fixation via photosynthesis, organic carbon uptake and functional biomass growth. The model was validated with experimental growth data of C. vulgaris and was found to fit the data well. Sensitivity analysis showed that the model performance was highly sensitive to variations in parameters associated with nutrient factors, photosynthesis and light intensity. The maximum productivity and biomass concentration were achieved under mixotrophic nitrogen sufficient conditions, while the maximum storage content was obtained under mixotrophic nitrogen deficient conditions.

Biofunctionalization of PET/SiO2 surfaces for single molecule experiments and medical applications

PET/SiO2 layers were chemically modified to maintain immobilization of functional single molecules. GFP molecules provide an ideal system due to their stability and intrinsic fluorescence. GFP in vivo biotinylated within its NH2-terminal region and attached on the substrate via the biotinstreptavidin bond was further investigated with confocal microscopy, atomic force microscopy (AFM) and spectroscopic ellipsometry (SE). AFM revealed monolayered donut-like structures representing assemblies of biotinstreptavidinbiotinGFP immobilized onto PET/SiO2 surfaces via mPEG. In particular, regions with an approximate height of 12 nm, which approaches the molecular dimensions of the above complex given by molecular modeling, could be detected. The dimensions of the donut-like structures suggest a close-to-each-other positioning of the GFP molecules - which, however, retain their functionality, as evidenced by confocal microscopy. © 2011 World Scientific Publishing Company.

Kinetic modelling of growth and storage molecule production in microalgae under mixotrophic and autotrophic conditions

In order to improve algal biofuel production on a commercial-scale, an understanding of algal growth and fuel molecule accumulation is essential. A mathematical model is presented that describes biomass growth and storage molecule (TAG lipid and starch) accumulation in the freshwater microalga Chlorella vulgaris, under mixotrophic and autotrophic conditions. Biomass growth was formulated based on the Droop model, while the storage molecule production was calculated based on the carbon balance within the algal cells incorporating carbon fixation via photosynthesis, organic carbon uptake and functional biomass growth. The model was validated with experimental growth data of C. vulgaris and was found to fit the data well. Sensitivity analysis showed that the model performance was highly sensitive to variations in parameters associated with nutrient factors, photosynthesis and light intensity. The maximum productivity and biomass concentration were achieved under mixotrophic nitrogen sufficient conditions, while the maximum storage content was obtained under mixotrophic nitrogen deficient conditions. © 2014 Elsevier Ltd.