An empirical analysis of enzyme function reporting for experimental reproducibility: Missing/incomplete information in published papers

Peter Halling; Paul F Fitzpatrick; Frank M Raushel; Johann Rohwer; Santiago Schnell; Ulrike Wittig; Roland Wohlgemuth; Carsten Kettner

doi:10.1016/j.bpc.2018.08.004

An empirical analysis of enzyme function reporting for experimental reproducibility: Missing/incomplete information in published papers

Biophys Chem. 2018 Nov:242:22-27. doi: 10.1016/j.bpc.2018.08.004. Epub 2018 Aug 24.

Authors

Peter Halling¹, Paul F Fitzpatrick², Frank M Raushel³, Johann Rohwer⁴, Santiago Schnell⁵, Ulrike Wittig⁶, Roland Wohlgemuth⁷, Carsten Kettner⁸

Affiliations

¹ WestCHEM, Department of P & A Chemistry, University of Strathclyde, Glasgow G1 1XL, United Kingdom. Electronic address: [email protected].
² The University of Texas Health Science Center, San Antonio, TX, USA.
³ Department of Chemistry, Texas A&M University, College Station, TX, USA.
⁴ Department of Biochemistry, University of Stellenbosch, Stellenbosch, South Africa.
⁵ Department of Molecular & Integrative Physiology, Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
⁶ Heidelberg Institute for Theoretical Studies (HITS gGmbH), Heidelberg, Germany.
⁷ Sigma-Aldrich, Member of Merck Group, Industriestrasse 25, Buchs CH-9470, Switzerland.
⁸ Beilstein-Institut, Frankfurt am Main, Germany.

Abstract

A key component of enzyme function experiments is reporting of considerable metadata, to allow other researchers to replicate, interpret properly or use fully the results. This paper evaluates the completeness of enzyme function data reporting for reproducibility. We present a detailed examination of 11 recent papers (and their supplementary material) from two leading journals. We found that in every paper we were not able to collect some critical information necessary to reproduce the enzyme function findings. Study of 100 papers used by the SABIO-RK database confirmed some of the most common omissions: concentration of enzyme or its substrates, identity of counter-ions in buffers. A computer system should be better at preventing such omissions, helping secure the scientific record. Many of the omissions found would be trapped by the currently available version of STRENDA DB.

Keywords: Data quality; Enzyme function; Metadata; Reproducibility; Standardization; Transparency.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Databases, Factual
Enzyme Assays / standards
Enzymes / metabolism*
Publishing*
Reproducibility of Results

Substances

Enzymes

Grants and funding

R25 DK088752/DK/NIDDK NIH HHS/United States