Effects of Sample Storage and Successive Freeze-thaw Cycles on Serum Fructosamine

ABSTRACT Metabolomics has great potential for uncovering biomarkers of the disease state in CF and many other contexts. However, sample storage timing and temperature may alter the abundance of clinically relevant metabolites. To assess whether existing samples are stable and to direct future study design, we conducted untargeted GC-MS metabolomic analysis of CF sputum samples after one or two freeze-thaw cycles and storage at 4°C and −20°C for 4 to 8 weeks. Overall, storage at −20°C and freeze-thaw cycles had little impact on metabolite profiles; however, storage at 4°C shifted metabolite abundances significantly. GC-MS profiling will aid in our understanding of the CF lung, but care should be taken in studies using sputum samples to ensure that samples are properly stored. Metabolites of human or microbial origin have the potential to be important biomarkers of the disease state in cystic fibrosis (CF). Clinical sample collection and storage conditions may impact metabolite abundances with clinical relevance. We measured the change in metabolite composition based on untargeted gas chromatography-mass spectrometry (GC-MS) when CF sputum samples were stored at 4°C, −20°C, or −80°C with one or two freeze-thaw cycles. Daily measurements were taken for 1 week and then weekly for 4 weeks (4°C) and 8 weeks (−20°C). The metabolites in samples stored at −20°C maintained abundances similar to those found at−80°C over the course of 8 weeks (average change in Bray-Curtis distance, 0.06 ± 0.04) and were also stable after one or two freeze-thaw cycles. However, the metabolite profiles of samples stored at 4°C shifted after 1 day and continued to change over the course of 4 weeks (average change in Bray-Curtis distance, 0.31 ± 0.12). The abundances of several amino acids and other metabolites increased with time of storage at 4°C but remained constant at −20°C. Storage temperature was a significant factor driving the metabolite composition (permutational multivariate analysis of variance: r 2 = 0.32 to 0.49, P < 0.001). CF sputum samples stored at −20°C at the time of sampling maintain a relatively stable untargeted GC-MS profile. Samples should be frozen on the day of collection, as more than 1 day at 4°C impacts the global composition of the metabolites in the sample. IMPORTANCE Metabolomics has great potential for uncovering biomarkers of the disease state in CF and many other contexts. However, sample storage timing and temperature may alter the abundance of clinically relevant metabolites. To assess whether existing samples are stable and to direct future study design, we conducted untargeted GC-MS metabolomic analysis of CF sputum samples after one or two freeze-thaw cycles and storage at 4°C and −20°C for 4 to 8 weeks. Overall, storage at −20°C and freeze-thaw cycles had little impact on metabolite profiles; however, storage at 4°C shifted metabolite abundances significantly. GC-MS profiling will aid in our understanding of the CF lung, but care should be taken in studies using sputum samples to ensure that samples are properly stored.

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Standard Sample Storage Conditions Impact on Inferred Microbiome Composition and Antimicrobial Resistance Patterns

10.1101/2021.05.24.445395 ◽

2021 ◽

Author(s):

Casper S. Poulsen ◽

Rolf Sommer Kaas ◽

Frank M. Aarestrup ◽

Sünje Johanna Pamp

Keyword(s):

Antimicrobial Resistance ◽

Dna Sequencing ◽

Storage Conditions ◽

Systematic Effect ◽

Sample Storage ◽

Sequencing Data ◽

Freezing And Thawing ◽

Microbiome Composition ◽

Freeze Thaw ◽

Eukaryotic Microorganisms

Storage of biological specimens is crucial in the life and medical sciences. The storage conditions for samples can be different for a number of reasons, and it is unclear which effect this can have on the inferred microbiome composition in metagenomics analyses. Here, we assess the effect of common storage temperatures (deep freezer: -80°C, freezer: -20°C, fridge: 5°C, room temperature: 22°C) and storage times, (immediate sample processing: 0h, next day: 16h, over weekend: 64h, and longer term: 4, 8, 12 months), as well as repeated sample freezing and thawing (2-4 freeze-thaw cycles). We examine two different pig feces and sewage samples, unspiked and spiked with a mock community, and in triplicates, respectively, amounting to a total of 438 samples (777 Gbp; 5.1 billion reads). Storage conditions had a significant and systematic effect on the taxonomic and functional composition of microbiomes. Distinct microbial taxa and antimicrobial resistance classes were in some situations similarly effected across samples, while others were not, suggesting an impact of individual inherent sample characteristics. With an increasing number of freeze-thaw cycles, an increasing abundance of Firmicutes, Actinobacteria, and eukaryotic microorganisms was observed. We include recommendations for sample storage, and strongly suggest including more detailed information in the metadata together with the DNA sequencing data in public repositories to better facilitate meta-analyses and reproducibility of findings. IMPORTANCE: Previous research has reported effects of DNA isolation, library preparation, and sequencing technology on metagenomics-based microbiome composition; however, the effect of biospecimen storage conditions has not been thoroughly assessed. We examined the effect of common sample storage conditions on metagenomics-based microbiome composition and find significant and, in part, systematic effects. Repeated freeze-thaw cycles could be used to improve the detection of microorganisms with more rigid cell walls, including parasites. We provide a dataset that could also be used for benchmarking algorithms to identify and correct for batch effects. Overall, the findings suggest that all samples of a microbiome study should be stored in the same way. Furthermore, there is a need to mandate more detailed information about sample storage and processing published together with the DNA sequencing data at INSDC (ENA/EBI, NCBI, DDBJ) or other repositories.

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