Interspecies exchange mutagenesis of the first epidermal growth factor-like domain of human factor VII

Characterization of canine coagulation factor VII and its complex formation with tissue factor: canine-human cross-species compatibility

BACKGROUND

Canine models have been good predictors of efficacy of hemophilia treatments, including recombinant human coagulation factor (F)VIIa (hFVIIa). However, canine FVIIa and tissue factor (TF) have remained incompletely characterized.

OBJECTIVE

 To explore canine-human cross-species FVIIa-TF compatibility in order to strengthen the predictive value of canine models in research on FVIIa and TF.

METHODS

Canine FVIIa (cFVIIa) and canine TF((1-217)) [cTF((1-217))] were produced by recombinant techniques, and canine-human cross-species FVIIa-TF interactions were characterized in vitro.

RESULTS

 Recombinant cFVIIa and soluble cTF((1-217)) were produced and purified to homogeneity. hFVIIa and cFVIIa bound with comparably high affinities to cTF((1-217)) (K(D)=6.0±0.7 nm and K(D)=6.0±0.3 nm, respectively) and to cell surface-expressed cTF (K(D)=8.4±0.4 nm and K(D)=7.2±1.2 nm, for (125) I-labeled hFVIIa and cFVII, respectively). In contrast, cFVIIa bound to human TF (hTF) with decreased affinity, both in solution and on cell surfaces. The decreased binding resulted in reduced activity of cFVIIa in functional assays with hTF((1-209)) . In direct comparison, cFVIIa was more active than hFVIIa, both in the absence and the presence of cognate TF.

CONCLUSION

The present finding that hFVIIa binds to cTF essentially as it does to hTF substantiates the hypothesis that human FVIIa-TF biology can be reliably recapitulated in canine models on administration of hFVIIa to dogs.

Survey of the year 2005 commercial optical biosensor literature

We identified 1113 articles (103 reviews, 1010 primary research articles) published in 2005 that describe experiments performed using commercially available optical biosensors. While this number of publications is impressive, we find that the quality of the biosensor work in these articles is often pretty poor. It is a little disappointing that there appears to be only a small set of researchers who know how to properly perform, analyze, and present biosensor data. To help focus the field, we spotlight work published by 10 research groups that exemplify the quality of data one should expect to see from a biosensor experiment. Also, in an effort to raise awareness of the common problems in the biosensor field, we provide side-by-side examples of good and bad data sets from the 2005 literature.