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Abstract Background Aerobic anoxygenic phototrophs are metabolically highly active, diverse and widespread polyphyletic members of bacterioplankton whose photoheterotrophic capabilities shifted the paradigm about simplicity of the microbial food chain. Despite their considerable contribution to the transformation of organic matter in marine environments, relatively little is still known about their community structure and ecology at fine-scale taxonomic resolution. Up to date, there is no comprehensive (i.e. qualitative and quantitative) analysis of their community composition in the Adriatic Sea. Results Analysis was based on pufM gene metabarcoding and quantitative FISH-IR approach with the use of artificial neural network. Significant seasonality was observed with regards to absolute abundances (maximum average abundances in spring 2.136 ± 0.081 × 104 cells mL−1, minimum in summer 0.86 × 104 cells mL−1), FISH-IR groups (Roseobacter clade prevalent in autumn, other Alpha- and Gammaproteobacteria in summer) and pufM sequencing data agglomerated at genus-level. FISH-IR results revealed heterogeneity with the highest average relative contribution of AAPs assigned to Roseobacter clade (37.66%), followed by Gammaproteobacteria (35.25%) and general Alphaproteobacteria (31.15%). Community composition obtained via pufM sequencing was dominated by Gammaproteobacteria clade NOR5/OM60, specifically genus Luminiphilus, with numerous rare genera present in relative abundances below 1%. The use of artificial neural network connected this community to biotic (heterotrophic bacteria, HNA and LNA bacteria, Synechococcus, Prochlorococcus, picoeukaryotes, heterotrophic nanoflagellates, bacterial production) and abiotic environmental factors (temperature, salinity, chlorophyll a and nitrate, nitrite, ammonia, total nitrogen, silicate, and orthophosphate concentration). A type of neural network, neural gas analysis at order-, genus- and ASV-level, resulted in five distinct best matching units (representing particular environments) and revealed that high diversity was generally independent of temperature, salinity, and trophic status of the environment, indicating a potentially dissimilar behaviour of aerobic anoxygenic phototrophs compared to the general bacterioplankton. Conclusion This research represents the first comprehensive analysis of aerobic anoxygenic phototrophs in the Adriatic Sea on a trophic gradient during a year-round period. This study is also one of the first reports of their genus-level ecology linked to biotic and abiotic environmental factors revealed by unsupervised neural network algorithm, paving the way for further research of substantial contribution of this important bacterial functional group to marine ecosystems.

Abstract By combining qualitative 16S metabarcoding and quantitative CARD-FISH methods with neural gas analysis, different patterns of the picoplankton community were revealed at finer taxonomic levels in response to changing environmental conditions in the Adriatic Sea. We present the results of a one-year study carried out in an oligotrophic environment where increased salinity was recently observed. We have shown that the initial state of community structure changes according to environmental conditions and is expressed as qualitative and quantitative changes. A general pattern of increasing diversity under harsh environmental conditions, particularly under the influence of increasing salinity at the expense of community abundance was observed. Considering the trend of changing seawater characteristics due to climate change, this study helps in understanding a possible structural change in the microbial community of the Adriatic Sea that could affect higher levels of the marine food web.

Recent advances in new molecular biology methods and next-generation sequencing (NGS) technologies have revolutionized metabarcoding studies investigating complex microbial communities from various environments. The inevitable first step in sample preparation is DNA extraction which introduces its own set of biases and considerations. In this study, we assessed the influence of five DNA extraction methods [B1: phenol/chloroform/isoamyl extraction, B2 and B3: isopropanol and ethanol precipitations, respectively—both modifications of B1, K1: DNeasy PowerWater Kit (QIAGEN), K2: modified DNeasy PowerWater Kit (QIAGEN) and direct PCR approach (P) that completely circumvents this step on community composition and DNA yield of mock and marine sample communities from the Adriatic Sea]. B1–B3 methods generally produced higher DNA yields and more similar microbial communities, but with higher interindividual variability. Each method demonstrated significant differences in a specific community structure, where rare taxa seem to play a crucial role. There was not one superior method closest to the theoretically expected mock community composition, they all demonstrated skewed ratios, but in a similar way which might be attributed to other factors, such as primer bias or 16S rRNA gene count for specific taxa. Direct PCR represents an interesting approach when high throughput in sample processing is required. We emphasize the importance of making a cautious decision about the choice of the extraction method or direct PCR approach, but even more importantly its consistent application throughout the study.