16S rRNA Gene Metabarcoding Indicates Species-Characteristic Microbiomes in Deep-Sea Benthic Foraminifera.

Panagiota-Myrsini Chronopoulou,Iines S Salonen,Hidetaka Nomaki,Karoliina A Koho,Dewi Langlet,Masashi Tsuchiya

doi:10.3389/fmicb.2021.694406

Abstract

Foraminifera are unicellular eukaryotes that are an integral part of benthic fauna in many marine ecosystems, including the deep sea, with direct impacts on benthic biogeochemical cycles. In these systems, different foraminiferal species are known to have a distinct vertical distribution, i.e., microhabitat preference, which is tightly linked to the physico-chemical zonation of the sediment. Hence, foraminifera are well-adapted to thrive in various conditions, even under anoxia. However, despite the ecological and biogeochemical significance of foraminifera, their ecology remains poorly understood. This is especially true in terms of the composition and diversity of their microbiome, although foraminifera are known to harbor diverse endobionts, which may have a significant meaning to each species’ survival strategy. In this study, we used 16S rRNA gene metabarcoding to investigate the microbiomes of five different deep-sea benthic foraminiferal species representing differing microhabitat preferences. The microbiomes of these species were compared intra- and inter-specifically, as well as with the surrounding sediment bacterial community. Our analysis indicated that each species was characterized with a distinct, statistically different microbiome that also differed from the surrounding sediment community in terms of diversity and dominant bacterial groups. We were also able to distinguish specific bacterial groups that seemed to be strongly associated with particular foraminiferal species, such as the family Marinilabiliaceae for Chilostomella ovoidea and the family Hyphomicrobiaceae for Bulimina subornata and Bulimina striata. The presence of bacterial groups that are tightly associated to a certain foraminiferal species implies that there may exist unique, potentially symbiotic relationships between foraminifera and bacteria that have been previously overlooked. Furthermore, the foraminifera contained chloroplast reads originating from different sources, likely reflecting trophic preferences and ecological characteristics of the different species. This study demonstrates the potential of 16S rRNA gene metabarcoding in resolving the microbiome composition and diversity of eukaryotic unicellular organisms, providing unique in situ insights into enigmatic deep-sea ecosystems.

Highlights

Benthic foraminifera are single-celled eukaryotes, widespread in global oceans and abundant in deep-sea sediments, accounting for up to 50% or more of the total eukaryotic biomass in places (Snider et al, 1984; Gooday et al, 1992)
The bacterial composition of the foraminiferal microbiome is likely reflecting the ecological characteristics of the given foraminiferal species, and the overall aim of the study was to gain insights into individual ecological strategies of the studied foraminiferal species and identify bacteriaforaminifera interactions that may be endobiotic in nature
Based on measurements from 2019 (Table 1), a NO3− reduction zone was present in the sediment down to approximately 1.5 cm depth (Figure 2), which is consistent with the Mn reduction taking place at similar sediment depths

Summary

Introduction

Benthic foraminifera are single-celled eukaryotes, widespread in global oceans and abundant in deep-sea sediments, accounting for up to 50% or more of the total eukaryotic biomass in places (Snider et al, 1984; Gooday et al, 1992). They are important consumers of phytodetritus (Gooday, 1988; Ohga and Kitazato, 1997; Moodley et al, 2002), experimentally shown to consume carbon faster than metazoans (Nomaki et al, 2005). Some studies indicate that the prokaryotic composition of the microbiome may be flexible and display a considerable amount of local variation (Prazeres et al, 2017) whereas evidence of speciesspecific microbiomes have been observed in shallow intertidal areas with no indication of spatial variability (Salonen et al, 2019)

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