Biochemical and computational analyses of two phenotypically related GALT mutations (S222N and S135L) that lead to atypical galactosemia

Benjamin Cocanougher; Umut Aypar; Amber McDonald; Linda Hasadsri; Michael J Bennett; W Edward Highsmith; Kristin D׳Aco

doi:10.1016/j.dib.2015.01.001

Biochemical and computational analyses of two phenotypically related GALT mutations (S222N and S135L) that lead to atypical galactosemia

Data Brief. 2015 Feb 7:3:34-9. doi: 10.1016/j.dib.2015.01.001. eCollection 2015 Jun.

Authors

Benjamin Cocanougher¹, Umut Aypar², Amber McDonald², Linda Hasadsri², Michael J Bennett³, W Edward Highsmith², Kristin D׳Aco¹

Affiliations

¹ University of Rochester School of Medicine and Dentistry, Department of Pediatrics, Division of Genetics, Rochester, NY, USA.
² Molecular Genetics Laboratory, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
³ Metabolic Disease Laboratory, Children׳s Hospital of Philadelphia, USA ; Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.

Abstract

Galactosemia is a metabolic disorder caused by mutations in the GALT gene [1,2]. We encountered a patient heterozygous for a known pathogenic H132Q mutation and a novel S222N variant of unknown significance [3]. Reminiscent of patients with the S135L mutation, our patient had loss of GALT enzyme activity in erythrocytes but a very mild clinical phenotype [3-8]. We performed splicing experiments and computational structural analyses to investigate the role of the novel S222N variant. Alamut software data predicted loss of splicing enhancers for the S222N and S135L mutations [9,10]. A cDNA library was generated from our patient׳s RNA to investigate for splicing errors, but no change in transcript length was seen [3]. In silico structural analysis was performed to investigate enzyme stability and attempt to understand the mechanism of the atypical galactosemia phenotype. Stability results are publicly available in the GALT Protein Database 2.0 [11-14]. Animations were created to give the reader a dynamic view of the enzyme structure and mutation locations. Protein database files and python scripts are included for further investigation.