ALBERT

Description: Recent advance in FTIR spectroscopy has shown the usefulness of13C uniform isotope labeling in proteins to study protein–protein interactions.13C uniform isotope labeling can significantly resolve the spectral overlap in the amide I/I′ region in the spectra of protein–protein complexes, and therefore allows more accurate determination of secondary structures of individual protein component in the complex than does the conventional FTIR spectroscopy. Only a limited number of biophysical techniques can be used effectively to obtain structural information of large protein–protein complex in solution. Though X‒ray crystallography and NMR have been used to provide structural information of proteins at atomic resolution, they are limited either by the ability of protein to crystallize or the large molecular weight of protein. Vibrational spectroscopy, including FTIR and Raman spectroscopies, has been extensively employed to investigate secondary structures and conformational dynamics of protein–protein complexes. However, significant spectral overlap in the amide I/Iʹ region in the spectra of protein–protein complexes often hinders the utilization of vibrational spectroscopy in the study of protein–protein complex. In this review, we shall discuss our recent work involving the application of isotope labeled FTIR to the investigation of protein–protein complexes such as cytokine–receptor complexes. One of the examples involves G‒CSF/receptor complex. To determine unambiguously the conformations of G‒CSF and the receptor in the complex, we have prepared uniformly13C/15N isotope labeled G‒CSF to resolve its amide Iʹ band from that of its receptor in the IR spectrum of the complex. Conformational changes and structural stability of individual protein subunit in G‒CSF/receptor complex have then been investigated by using FTIR spectroscopy (Li et al.,Biochemistry29 (1997), 8849–8859). Another example involves BDNF/trkB complex in which13C/15N uniformly labeled BDNF is complexed with its receptor trkB (Li et al.,Biopolymers67(1) (2002), 10–19). Interactions of13C/15N uniformly labeled brain‒derived neurotrophic factor (BDNF) with the extracellular domain of its receptor, trkB, have been investigated by employing FTIR spectroscopy. Conformational changes and structural stability and dynamics of BDNF/trkB complex have been determined unambiguously by FTIR spectroscopy, since amide I/Iʹ bands of13C/15N labeled BDNF are resolved from those of the receptor. Together, those studies have shown that isotope edited FTIR spectroscopy can be successfully applied to the determination of protein secondary structures of protein complexes containing either the same or different types of secondary structures. It was observed that13C/15N uniform labeling also affects significantly the frequency of amide IIʹ band, which may permit the determination of hydrogen–deuterium exchange in individual subunit of protein–protein complexes.

Description: Actual evapotranspiration (Ea) plays a key role in the global water and energy cycles. The accurate quantification of the impacts of different factors on Ea change can help us better understand the driving mechanisms of Ea in a changing environment. Climate change and vegetation variations are well known as two main factors that have significant impacts on Ea change. Our study used three differential Budyko-type equations to quantify the contributions of climate change and vegetation variations to Ea change. First, in order to establish the relationship between the parameter n, which usually presents the land surface characteristics in the Budyko-type equations, with basic climatic variables and the Normalized Difference Vegetation Index (NDVI), the stepwise linear regression method has been used. Then, elasticity and contribution analyses were performed to quantify the contributions of different numbers of climatic factors and NDVI to Ea change. The North and South Panjiang basin in China was selected to investigate the efficiency of the modified Budyko-type equations and quantify the impacts of climate change and vegetation variations on Ea change. The empirical formal of the parameter n established in this study can be used to simulate the parameter n and Ea for the study area. The results of the elasticity and contribution analyses suggest that climate change contributed (whose average contribution is 149.6%) more to Ea change than vegetation variation (whose average contribution is −49.4%). Precipitation, NDVI and the maximum temperature are the major drivers of Ea change, while the minimum temperature and wind speed contribute the least to Ea change.