۱- Introduction

۲- Materials and methods

۳- Results

۴- Discussion

۵- Conclusions

References

Abstract

High-resolution melting (HRM) analysis followed by sequencing was applied for determination of bacteria grown on plates isolated from farmed mussels (Mytilus galloprovincialis) during their storage at 4 °C. The V3–V4 region of the 16S rRNA gene from the isolates was amplified using 16S universal primers. Melting curves (peaks) and high resolution melting curves (shape) of the amplicons and sequencing analysis were used for differentiation and identification of the isolated bacteria, respectively. The majority of the isolates (a sum of 101 colonies, from five time intervals: day 0, 2, 4, 6 and 8) from non-selective solid medium plates were classified in four bacterial groups based on the melting curves (peaks) and HRM curves (shape) of the amplicons, while three isolates presented distinct HRM curve profiles (single). Afterwards, sequencing analysis showed that the isolates with a) the same melting peak temperature and b) HRM curves that were >95% similar grouped into the same bacterial species. Therefore, based on this methodology, the cultivable microbial population of chill-stored mussels was initially dominated by Psychrobacter alimentarius against others, such as Psychrobacter pulmonis, Psychrobacter celer and Klebsiella pneumoniae. P. alimentarius was also the dominant microorganism at the time of the sensory rejection (day 8). Concluding, HRM analysis could be used as a useful tool for the rapid differentiation of the bacteria isolated from mussels during storage, at species level, and then identification is feasible by the sequencing of one only representative of each bacterial species, thus reducing the cost of required sequencing.

Introduction

The determination of seafood quality from their harvest to consumer table is of high importance for the aquaculture sectors, fishery trade associations, food industry and food authorities. The enumeration of Aerobic Plate Counts (APC) or alternatively Specific Spoilage Organisms (SSOs) is a common way to evaluate freshness of stored seafood. SSOs constitute a small fraction of the initial total microbiota which grows faster than the rest microorganisms during storage reaching higher population densities and produces metabolites that cause the organoleptic rejection of the product (Boziaris and Parlapani, 2016; Gram and Huss, 1996). In this context, the monitoring of the diversity and dynamic of SSOs lets us know which microorganisms prevail against others under the specific storage conditions, e.g., temperature (Parlapani et al., 2015b). Using plate-based against culture-independent approach, we have the advantage to isolate microorganisms for further studies regarding their spoilage potential and activity which can lead to the characterization of them as key players of seafood spoilage (Parlapani et al., 2017). Culture-dependent identification of seafood microbiota has been traditionally studied by phenotypic and biochemical tests, however these are laborious and usually lack discriminatory power giving failed results (Nisiotou et al., 2014). For these reasons, other, alternative, rapid, accurate and reliable methodologies have been developed. The 16S rRNA gene sequence analysis has been conducted by analyzing (amplification and sequencing) numerous isolates e.g., 50% or more of the total colonies grown on plates (Parlapani and Boziaris, 2016; Parlapani et al., 2015a, 2015b).