A new quality management perspective for biodiversity conservation and research: Investigating Biospecimen Reporting for Improved Study Quality (BRISQ) and the Standard PRE-analytical Code (SPREC) using Natural History Museum and culture collections as case studies

posted on 26.07.2016 by Erica E. Benson, Keith Harding, Jacqueline Mackenzie-dodds

The aims of this paper are to debate and raise awareness about the use of systematic, interconnected approaches for biodiversity collection curation by exploring the multi-disciplinary relevance of quality management tools developed by clinical biobanks. An appraisal of their best practices indicated the need for improved sample and process chain annotation as a significant number of historical collections used in medical research were of inadequate quality. This stimulated the creation of a new discipline, biospecimen science to develop quality management tools for clinical biobanks, two of which, Biospecimen Reporting for Improved Study Quality (BRISQ) and the Standard PRE-analytical Code (SPREC) report critical information about samples and process chain variables. Unprecedented advances in molecular-genetic and in silico technologies applied across the tree of life require international conservation networks to generate and share knowledge. This is used in biodiversity and systematics research, and to address the accelerating loss of species, including the sustainable use of bioresources. This review investigates the application of BRISQ and SPREC for biodiversity research and conservation using natural history, museum and living culture collections as case studies. The distinction between preservation and conservation is discussed with regard to process and storage treatments and how they impact on the usability of biospecimens and cultures. We conclude: (i) more rigorous approaches are needed for the quality management of biospecimens, bioresources and their associated sample and processing data to assure their fitness-for-purpose; and (ii) biospecimen science tools developed by clinical biobanks can be adapted to future-proof the quality of biodiversity collections and the reliability of molecular data generated from their use.