Amino-acid Type Identification in 15N-HSQC Spectra by Combinatorial Selective 15N-labelling

Abstract

The efficiency of cell-free protein synthesis combined with combinatorial selective 15N-labelling provides a method for the rapid assignment of 15N-HSQC cross-peaks to the 19 different non-proline amino-acid types from five 15N-HSQC spectra. This strategy was explored with two different constructs of the C-terminal domain V of the tau subunit of the Escherichia coli DNA polymerase III holoenzyme, tauC16 and tauC14. Since each of the five 15N-HSQC spectra contained only about one third of the cross-peaks present in uniformly labelled samples, spectral overlap was much reduced. All 15N-HSQC cross-peaks of the backbone amides could be assigned to the correct amino-acid type. Availability of the residue-type information greatly assisted the evaluation of the changes in chemical shifts observed for corresponding residues in tauC16 vs. those in tauC14, and the analysis of the structure and mobility of the C-terminal residues present in tauC16 but not in tauC14.

Membrane domain structures of three classes of histidine kinase receptors by cell-free expression and rapid NMR analysis

“…Several approaches were built upon this method to perform site-selective screening (24) and to accelerate the resonance assignment by using dual combinatorial labeling (25)(26)(27). Simplified approach utilizing combinatorial selective 15 N labeling was proposed for determination of the amino acid types for 1 H N , 15 N H resonances (28). Combinatorial selective labeling approaches (reviewed in refs.…”

Stable isotope labeling strategy based on coding theory

“…Signal overlapping usually impede amino acid discrimination especially in CSL, therefore, the number of labeled aminoacids is reduced according to its occurrence in some CSL (Trbovic et al 2005;Wu et al 2006;Sobhanifar et al 2010;Löhr et al 2012). In the present study, we labeled all of the non-proline 19 amino acids, however, quantitative peak fitting used for decoding information in SiCode solved the signal overlapping issue as demonstrated.…”

“…As described above, conventional CSL schemes generally uses two SI-labeling levels, enabling that 1 bit information is contained in each labeled sample (Parker et al 2004;Shi et al 2004;Trbovic et al 2005;Staunton et al 2006;Wu et al 2006;Maslennikov et al 2010;Sobhanifar et al 2010;Hefke et al 2011;Krishnarjuna et al 2011;Jaipuria et al 2012; Maslennikov and Choe 2013). In the previously mentioned triple selective CSL approach (Löhr et al 2012), three SIlabeling types can be discriminated for both residues i and i -1: unlabeled, 15 N-labeled, or 2-13 C/ 15 N-labeled for the residue i and unlabeled, 1-13 C-labeled, or 1,2-13 C-labeled for the residue i -1, respectively, being considered that 1 trit (ternary digit) information is contained in each sample.…”

“…However, for the discrimination of all amino-acids, these simple AASIL schemes require a large number of samples, which are typically the same as the number of amino acids (19 for nitrogen or 20 for carbon). For this reason, various combinatorial selective labeling (CSL) schemes (Parker et al 2004;Shi et al 2004;Trbovic et al 2005;Staunton et al 2006;Wu et al 2006;Maslennikov et al 2010;Sobhanifar et al 2010;Hefke et al 2011;Krishnarjuna et al 2011;Jaipuria et al 2012;Löhr et al 2012; Maslennikov and Choe 2013) were developed to reduce required number of samples, by representing amino acids as combination of SI labeled samples rather than simply assigning one amino acid to one SI labeled sample. For example, a CSL scheme developed by Parker et al (2004), which is based on the dual selective approach, can discriminate 16 amino-acids with one uniformly 13 C and 15 N-labeled reference and four selectively (100 or 0 % for 13 C and 100 or 50 % for 15 N, respectively) labeled samples.…”

“…The use of labeling ratio of 100 or 50 % for 15 N, rather than that of 100 or 0 %, ensures obtaining 13 C labeling information from HN(CO) spectrum, irrespective of 15 N labeling ratio. Otting and colleagues reported simpler CSL scheme using five samples (Wu et al 2006), based on the single selective 15 N-labeling approach, in which spectral overlaps were diminished by labeling one amino acid with high occurrence and at most three ones with low occurrence in each sample. Dötche and colleagues developed focused CSL (Trbovic et al 2005;Sobhanifar et al 2010), in which 6 or 7 amino acids frequently appearing in transmembrane regions of membrane proteins were labeled with 15 N or 1-13 C. They further improved the CSL to discriminate up to 20 amino-acids with a number of samples labeled with 15 N and/or 13 C by using dual selective approach (Hefke et al 2011), or to discriminate 12 amino-acids with only three samples by introducing triple selective approach (Löhr et al 2012), in which the samples were labeled with the combination of 15 N, 1-13 C, and 13 C/ 15 N. Choe and colleagues also improved membrane protein-focused CSL (Maslennikov et al 2010;Maslennikov and Choe 2013) to discriminate up to 19 amino-acids except for glutamate with six samples simply labeled with 13 C and/or 15 N. A couple of computational methods for designing labeling patterns for CSL were employed (Maslennikov et al 2010;Hefke et al 2011;Maslennikov and Choe 2013) in order to maximize assignable residues by using dual selective approaches.…”