Picoplankton diversity in an oligotrophic and high salinity environment in the central Adriatic Sea

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.

Distinct communities of Bacteria and unicellular eukaryotes in the different water masses of Cretan Passage water column (Eastern Mediterranean Sea)

“…Moreover, Pseudohongiella , another γ-proteobacterium, preferred colder waters and positively interacted with Prochlorococcus and Cyanobium . Furthermore, the major Bacteroidota, NS4 and NS5 marine groups , were more abundant in Koufonisi (summer) following the picoplankton bloom in winter, confirming their association with the degradation of high molecular weight organic matter (OM) [43]. Marine mycobiome diversity and ecology is generally understudied however they seem to be involved in OM decomposition, nutrient metabolism and parasitism on picoeukaryotic algae [44].…”

Ecology of aerobic anoxygenic phototrophs on a fine-scale taxonomic resolution in Adriatic Sea unravelled by unsupervised neural network

“…Quantitative estimates of specific bacterial groups resulting from fluorescence in situ hybridisation combined with catalysed reporter deposition (CARD-FISH) have been widely reported in numerous ecological studies for years [ 14 , 27 , 59 – 61 ]. Nevertheless, quantitative estimates of AAPs taxonomically assigned to specific clades or groups are rare [ 21 , 29 ], especially for environmental samples.…”

“…Seasons were determined according to the criteria of a comprehensive historical hydrographic dataset of the Adriatic Sea, with the months January to April being considered winter, May and June spring, July to October summer and November and December autumn [ 26 ]. Temperature, salinity, nutrients concentrations and chlorophyll a (Chl a ) were measured as described in a previous study [ 27 ] and values are shown in Fig. 2 .…”

“…2 . Abundances of picoplankton community members, namely Synechococcus and Prochlorococcus , picoeukaryotes (PE), heterotrophic bacteria, high and low nucleic acid bacteria (HNA and LNA bacteria, respectively) and heterotrophic nanoflagellates (HNF), were measured by flow cytometry as previously described [ 27 ]. Bacterial production was estimated by the 3H-thymidine incorporation method as previously described [ 28 ].…”

“…An artificial neural network/unsupervised topology learning algorithm, neural gas (NG), was applied to a CLR-transformed puf M dataset to estimate characteristic AAP patterns associated with specific biotic/abiotic environmental factors [ 53 ]. NG has been successfully used for this type of data in previous studies due to its suitability for modelling anomalies and the mean distribution of microbiological parameters [ 25 , 27 , 54 ]. In our study, separate NG models were created on agglomerated and CLR-transformed datasets on puf M sequencing data, carried out at the order-, genus- and ASV-levels.…”