Software tools to aid in organisation of samples and stocks
Managing chemical stocks and samples in any laboratory is an arduous task; in a crystallization laboratory this is particularly burdensome, given the need for many stocks to facilitate optimization of crystal hits obtained from screening experiments. Although inventory management is widespread in retail and other arenas, most small academic laboratories do not adopt formal stock management
systems. Without an overarching system for handling stocks and samples, problems such as stock duplication, inappropriate stock storage and insufficient labelling are rife. Two applications have been developed in the Collaborative Crystallization Centre, the first of which manages the hundreds of stocks used for crystallization, and a second which manages protein (and other) samples stored in the 193 K freezer. Both applications are built around a simple database, with a Python front end that allows samples or stocks to be scanned in or out. Information from a decade of crystallization stock usage allows a good estimation of what chemicals are used (and in what quantities) in a crystallization laboratory.
Download Article: Gu, A., Marshall, B., Rosa, N., Ristic, M. & Newman, J. Organizing a crystallization laboratory. J Appl Cryst, J Appl Crystallogr 51, 47–54 (2018). doi:10.1107/S1600576717016727
A Tool to Help in the Interpretation of Thermal Melt Curves Acquired by Differential Scanning Fluorimetry
The output of a differential scanning fluorimetry (DSF) assay is a series of melt curves, which need to be interpreted to get value from the assay. An application that translates raw thermal melt curve data into more easily assimilated knowledge is described. This program, called “Meltdown,” conducts four main activities—control checks, curve normalization, outlier rejection, and melt temperature (Tm) estimation—and performs optimally in the presence of triplicate (or higher) sample data. The final output is a report that summarizes the results of a DSF experiment. The goal of Meltdown is not to replace human analysis of the raw fluorescence data but to provide a meaningful and comprehensive interpretation of the data to make this useful experimental technique accessible to inexperienced users, as well as providing a starting point for detailed analyses by more experienced users.
Download Article: Rosa, N., Ristic, M., Seabrook, S.A., Lovell, D., Lucent, D., Newman, J., 2015. Meltdown: A Tool to Help in the Interpretation of Thermal Melt Curves Acquired by Differential Scanning Fluorimetry. J Biomol Screen 20, 898–905. doi:10.1177/1087057115584059
Formulation screening by differential scanning fluorimetry: how often does it work?
There is strong evidence to suggest that a protein sample needs to be well folded and uniform in order to form protein crystals, and it is accepted knowledge that the formulation can have profound effects on the behaviour of the protein sample. Automated analysis of the DSF results suggest that in over 35% of cases buffer screening significantly increases the stability of the protein sample.
Download Article: Ristic, M., Rosa, N., Seabrook, S.A., Newman, J., 2015. Formulation screening by differential scanning fluorimetry: how often does it work? Acta Cryst F, Acta Cryst Sect F, Acta Crystallogr F, Acta Crystallogr Sect F, Acta Cryst F Struct Biol Cryst Commun, Acta Cryst Sect F Struct Biol Cryst Commun, Acta Crystallogr Sect F Struct Biol Cryst Commun 71, 1359–1364. doi:10.1107/S2053230X15012662
How to name your chemicals – consistency matters
Sharing information between labs can be made (unintentionally) difficult due to our tendency to use colloquial abbreviations for chemicals. Structural biology projects typical involve biologists, chemists and physicists who each have their own naming preference – this paper demonstrates how we can improve the naming situation for protein crystallisation, and remove ambiguity about what is in an experiment.
Download Article: Newman J, Peat TS, Savage GP. What’s in a Name? Moving Towards a Limited Vocabulary for Macromolecular Crystallisation. Australian Journal of Chemistry 2014. DOI: 10.1071/CH14199
Obtaining a stable construct for crystallisation – this is how we do it
We use Differential Scanning Fluorimetry (DSF) to help find an experimental formulation to enhance protein stability for down-stream biophysical assays. Why? Your protein is the most important factor in any experiment, and making it stable (and thus consistent) can help speed up the biophysics workflow. This paper outlines how our fee-for-service thermofluor assay operates, and provides enough information for you to mimic it in your own HTP lab.
Download Article: Seabrook SA, Newman J. High-throughput thermal scanning for protein stability: Making a good technique more robust. ACS Combinatorial Science 2013. DOI: 10.1021/co400013v
Conformational flexibility of insect hormones investigated
The ecdysone receptor (EcR) represents an interesting class of insect hormones that can help us to develop more efficient insecticides. Here, we’ve looked at how the structure of Bovicola ovis EcR behaves in the presence of a ectysteroid partner and a synthetic insecticide, using both structural and thermodynamic tools.
Download article: Ren B. Peat, TS. et al. Unprecedented conformational flexibility revealed in the ligand-binding domains of the Bovicola ovis ecdysone receptor (EcR) and ultraspiracle (USP) subunits. Acta Crystallographica Section D 2014, 70 (7), 1954-1964.
Is that really a protein crystal? The pros & cons of UV imaging are discussed
High-throughput UV imaging of protein crystallisation screening experiments can enable crystallographers to differentiate between protein and salt crystals. But, buyer beware! UV imaging is based on fluorescence, an energy exchange event that is easily influenced by its chemical surroundings. In this publication we attempt to lay out some guidelines when using UV imaging in a structural biology lab.
Download article: Desbois S, Seabrook SA, Newman J: Some practical guidelines for UV imaging in the protein crystallization laboratory. Acta Crystallographica Section F 2013; 69