Residues in the human corticosteroid-binding globulin reactive center loop that influence steroid binding before and after elastase cleavage
Authors: Hai-Yan Lin
Yves A Muller
Bernd R Gardill
Geoffrey L Hammond
Caroline Underhill
Journal: Journal of Biological Chemistry (2009)
Discipline: BIOLOGY & BIOCHEMISTRY
Keywords: Corticosteroid-binding globulin; serpin; proteolytic cleavage; reactive center loop; steroid binding
Affiliations: Child and Family Research Institute, University of British Columbia, Vancouver, British Columbia V5Z 4H4, Canada.

Abstract:  Corticosteroid-binding globulin (CBG) is a non-inhibitory serine proteinase inhibitor (serpin) that transports cortisol and progesterone in blood. Crystal structures of rat CBG and a thrombin-cleaved human CBG:anti-trypsin (Pittsburgh) chimera show how structural transitions after proteolytic cleavage of the CBG reactive center loop (RCL) could disrupt steroid binding. This ligand release mechanism is assumed to involve insertion of the cleaved RCL into the beta-sheet A of the serpin structure. We have, therefore, examined how amino acid substitutions in the human CBG RCL influence steroid binding before and after its cleavage by neutrophil elastase. Elastase-cleaved wild-type CBG or variants with substitutions at P15 and/or P16 (E334G/G335N or E334A) lost steroid binding completely, whereas deletion of Glu-334 resulted in no loss of steroid binding after RCL cleavage, presumably because this prevents its insertion into beta-sheet A. Similarly, the steroid binding properties of CBG variants with substitutions at P15 (G335P), P14 (V336R), or P12 (T338P) in the RCL hinge were largely unaffected after elastase cleavage, most likely because the re-orientation and/or insertion of the cleaved RCL was blocked. Substitutions at P10 (G340P, G340S) or P8 (T342P, T342N) resulted in a partial loss of steroid binding after proteolysis which we attribute to incomplete insertion of the cleaved RCL. Remarkably, several substitutions (E334A, V336R, G340S, and T342P) increased the steroid binding affinities of human CBG even before elastase cleavage, consistent with the concept that CBG normally toggles between a high affinity ligand binding state where the RCL is fully exposed and a lower affinity state in which the RCL is partly inserted into beta-sheet A. 

Retracted: No

PubPeer comments:
 In Ext. Fig5, there were image duplications. ![file] , 
 Dear Apotomus Rufithoraxuff1a Thanks for your kind remind of the figure issues in our paper. These duplications were not made on purpose. When we looked back to our raw data, we realized that we pasted the wrong pictures during Figure assembly. However, due to the publication police, we uploaded the source data to Nature cell biology when we finalized our paper at the same time. You can see that the correct Ext. Figure 5f was as we shown below, and you can also download it from Nature cell biology website. Please understand that the schedule was tight during revision and the final version was not fully reviewed by other authors. We sincerely apologize for the mistake again. ![file] Sincerely , 
 **Another issue, involved in Extended Data Figure 6d**: DNA gel electrophoresis of RT-PCR for EGFR in GSC17-WT, 17-KO, NSC-WT, and NSC-KO cells. ![file] **As like as two peas, the two red boxes of DNA electrophoresis were exactly the same actually. The authors just made the appearance of inconsistency by adjusting the brightness based on the same image. When the brightness of the image on the right is increased by about 70%, it could be clearly found that the two images were from the same DNA electrophoresis result**. ![file] Please observe the details of the gel plots carefully, thank you. , 
 **Extended Data Figure 2g** was confusing, the authors stated in the figure legends that , **Two-sided, Log-rank analysis of GBM patients (nu2009=u200945) biologically independent samples) from cohort 3 correlated with C-E-Cad levels (left); CGGA database with C-E-Cad levels (middle) and E-Cad levels (right)** ![file] CGGA database with C-E-Cad levels in the middle panel, **the number of patients was 45? Please be noted that 45 was the number for cohort 3**. , 
 Also, one more question, why the numbers in cohort 3, between the C-E-Cad high group and C-E-Cad low group, were inconsistent between the left and right survival plots, as follows: ![file] **25 vs 20? or 30 vs 15?** , 
 Figure 2E ![file] ![file] The authors tried to use their own samples to testify that E-Cad (CDH1) is high expressed in the normal tissue. However, this result is completely opposite to the TCGA database ![file] ![file] **The author then used TCGA database to verify the survival analysis of E-cad in GBM in the subsequent Fig. 2F, but the author deliberately avoided the comparison results of E-cad expression between GBM and normal tissues by the TCGA database, only used their own samples for comparison**. **In TCGA database, E-cad was slightly up-regulated in tumor tissues, but it did decrease very significantly in the author s own specimens, just to highlight the effect of C-E-Cad? which was newly reported by the authors in this paper** The authors are expected to rely for it, thank you. , 
 #5 #3: Dear Litoria modicauff1a I am xinya gao, the first author of this paper. Thanks for point out this issue. We checked our raw data and verified this was indeed a mistake. When we were taking the gel images, high exposure and low exposure pictures for GSC17 and NSC were saved in the same folder. We pasted it wrongly during the Figure assembly in both source data and Ext.Fig.6d. We sincerely apologize for our carelessness. However, please note that the IB and Sanger sequencing result were also provided for NSC K.O. cells, thus the data integrity and conclusion were not affected. We will post an erratum to NCB later. #4 and #5 Thanks for your question. Please note that cohort 3 and CGGA samples were independent cohorts, from each we randomly selected 45 samples. Sincerely , 
 #6 Dear Pandanus basedowii: Thanks for your question. Please note that TCGA did not contain circular RNA-seq data. As you mentioned, E-cad RNA was only slightly upregulated in TCGA GBM (not significant), but in our samples E-Cad protein (by IHC) was downregulated. There may some other mechanisms induced this downregulation. Sincerely , 
 #7 Thanks for your relpy. I have noticed that cohort 3 and CGGA samples were independent cohorts. Then, the CGGA database marked in red included the middle and the right panels? ![file] Wrong figure annotation? , 
 #7 As for your analysis based on the CGGA data, I have also accessed to the database, however, I could not repeat your results, whether for the primary or the recurrent, or in different stages. Kindly upload your analysis processuff1f ![file] ![file] ![file] , 
 #7 Could the authors specify which data you used for analysis, in **CGGA database**? ![file] link for CGGA database: http: www.cgga.org.cn index.jsp Of note was the observation that in your paper, the Extended Figure 2G, The patient number of E-Cad high group was 54, E-Cad low group was 53. 54+53=97 **The problem is the number of 97, which is the corresponding dataset in CGGA database**? , 
 ![file] Of note was the observation that in your paper, the Extended Figure 2G, The patient number of E-Cad high group was 54, E-Cad low group was 53. 54+53=107 **The problem is the number of 107, which is the corresponding dataset in CGGA database**? , 
 #7 Finally, I have found that the authors used the mRNA_array_301 dataset, the WHO IV glioma, to demonstrated the Extended Figure 2G, as follows: ![file] ![file] Still, why not use the result from mRNAseq_325? Please be noted that in mRNAseq_325 dataset there was a significantly better survival result in E-Cad high group as compared with low group, P = 0.05. ![file] ![file] **The authors should explain the difference between the results from mRMA micro-array and mRNA sequence, based on the CGGA database for E-Cad expression, in GBM, i.e., in WHO IV Grade Glioma**. , 
 Dear PuBPeer editors, Thank you for your REPEATED EMAILS for the comments and the authors responses posted at this website. I am now aware of these comments on the data associated with this joint publication. I carefully looked through the responses from the first author and the last senior author s responses to the comments posted. I trust that these responses satisfactorily addressed each of the comments and the one who posted the comments or editors at your office should post your response either you accept these responses or you have additional comments to make. Moreover, please, please do not send the multiple emails such as FIVE emails in one minute to me. This is not professional behavior! ON the other hand, all the experiments and bioinformatics analyses were performed at the laboratory of Dr. Zhang in Guangzhou, China. As a co-senior author, I helped to re-organized, re-analyzed the majority of data and figures presented in this study, did multiple runs of revisions and editing, reviewed and discussed all the results and data with Dr. Zhang during the entire submission process. Therefore, please direct your comments questions regarding to the figures and data in this paper to the first author and Dr. Zhang if you have additional comments or concerns. Your professional behavior is much appreciated. Best regards, Shi-Yuan Cheng , 
 #2 Thank you very much for your timely reply. In addition to the problem of WB bands duplication, the molecular weight of your PDGFRA is also wrong, which should be 190kDa. See: https: www.cellsignal.com ![file] ![file] What s more, when I looked at the annotation of Extended Data Fig. 5, I found that there was even no annotation of the panel **F**. ![file] , 
 #2 The authors have mentioned the source data in the website of Nature cell biology. Unfortunately, Also in **Extended Data Fig. 5D, the WB bands were inconsistent with the uploaded source data**. ![file] In the uploaded original source data (right), **the WB bands for PARP have turned into Caspase3 in the Extended Figure 5D, the WB bands for Caspase3 have turned into PARP**. When enlarged: ![file] ![file] ,