Utilising liquid nitrogen for snap-freezing samples is widely regarded as the benchmark method for extracting pristine DNA from an unmodified microbial community. Nevertheless, the feasibility of promptly freezing samples while maintaining an unbroken cold chain isn’t always achievable, especially during field sampling missions. Consequently, dependable substitutes become imperative. This necessity has spurred the creation of various preservatives, enabling samples to be preserved at room temperature over prolonged durations. Nonetheless, research has unveiled that these preservatives can impart significant biases during the generation of diverse omic layers . Therefore, maintaining uniformity in the selection of preservatives is of paramount importance to ensure consistency across analyses.
Numerous preservatives necessitate removal before extraction, such as ethanol, NAP buffer, and RNAlater. However, this removal process can inadvertently eliminate non-pelleting entities, including bacteriophages and other viruses. Conversely, certain preservatives also serve as lysis buffers, exemplified by Zymo’s DNA/RNA Shield. Notably advantageous, these buffers directly participate in DNA extraction. Although these preservatives do not stabilise DNA within cells, they initiate cellular degradation while stabilising DNA in the matrix. Maintaining the recommended material-to-buffer ratio is imperative across all these buffers to ensure optimal outcomes. Overloading with biological material can negate the beneficial effects of the buffers.
Avoiding freeze-thaw cycles is ideal, as they are recognised sources of DNA degradation and variations in microbial community composition, especially when samples are repetitively thawed . Opting for small aliquots tailored to the extraction protocol during sample collection, rather than bulk collection, facilitates thawing only the sample intended for processing. This practice sidesteps detrimental thaw-freeze cycles and diminishes the risk of cross-contamination from other samples.
Furthermore, the biological and chemical characteristics of molecules (e.g., DNA, RNA, proteins, metabolites) used in omic data generation must be acknowledged. Host DNA’s abundance and stability render HG less sensitive. Conversely, MG warrants more cautious handling due to potential microbial community fluctuations post-sampling, unless biochemical reactions are halted. HT and MT demand even swifter preservation to capture representative gene expression patterns. Lastly, metabolites exhibit diverse chemical properties, ranging from stable steroids to highly volatile short-chain fatty acids. Thus, judicious selection of appropriate preservatives becomes paramount when generating multiple omic layers. This decision involves determining whether omic data will be sourced from a single biological sample, necessitating a universal preservative, or multiple samples, each potentially requiring a distinct preservative.
Importantly, the diverse physicochemical properties of samples mandate that collection and storage methods validated for one sample type cannot be universally assumed optimal for others. Therefore, preliminary optimisation tests are prudent, and methodological consistency emerges as a prerequisite for the production of dependable omic data.