The intracellular Ig fold: a robust protein scaffold for the engineering of molecular recognition

Protein scaffolds that support molecular recognition have multiple applications in biotechnology. Thus, protein frames with robust structural cores but adaptable surface loops are in continued demand. Recently, notable progress has been made in the characterization of Ig domains of intracellular origin--in particular, modular components of the titin myofilament. These Ig belong to the I(intermediate)-type, are remarkably stable, highly soluble and undemanding to produce in the cytoplasm of Escherichia coli. Using the Z1 domain from titin as representative, we show that the I-Ig fold tolerates the drastic diversification of its CD loop, constituting an effective peptide display system. We examine the stability of CD-loop-grafted Z1-peptide chimeras using differential scanning fluorimetry, Fourier transform infrared spectroscopy and nuclear magnetic resonance and demonstrate that the introduction of bioreactive affinity binders in this position does not compromise the structural integrity of the domain. Further, the binding efficiency of the exogenous peptide sequences in Z1 is analyzed using pull-down assays and isothermal titration calorimetry. We show that an internally grafted, affinity FLAG tag is functional within the context of the fold, interacting with the anti-FLAG M2 antibody in solution and in affinity gel. Together, these data reveal the potential of the intracellular Ig scaffold for targeted functionalization.

How reliable and robust are current biomarkers for copper status?

Cu is an essential nutrient for man, but can be toxic if intakes are too high. In sensitive populations, marginal over- or under-exposure can have detrimental effects. Malnourished children, the elderly, and pregnant or lactating females may be susceptible for Cu deficiency. Cu status and exposure in the population can currently not be easily measured, as neither plasma Cu nor plasma cuproenzymes reflect Cu status precisely. Some blood markers (such as ceruloplasmin) indicate severe Cu depletion, but do not inversely respond to Cu excess, and are not suitable to indicate marginal states. A biomarker of Cu is needed that is sensitive to small changes in Cu status, and that responds to Cu excess as well as deficiency. Such a marker will aid in monitoring Cu status in large populations, and will help to avoid chronic health effects (for example, liver damage in chronic toxicity, osteoporosis, loss of collagen stability, or increased susceptibility to infections in deficiency). The advent of high-throughput technologies has enabled us to screen for potential biomarkers in the whole proteome of a cell, not excluding markers that have no direct link to Cu. Further, this screening allows us to search for a whole group of proteins that, in combination, reflect Cu status. The present review emphasises the need to find sensitive biomarkers for Cu, examines potential markers of Cu status already available, and discusses methods to identify a novel suite of biomarkers.

Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.