Reduced methane oxidizing activity by sediment methanotrophs in shallow coastal zones with high methane emissions

Background Coastal zones are transitional areas between land and sea where large amounts of organic and inorganic carbon compounds are recycled by microbes. Especially shallow zones near land have been shown to be the main source for oceanic methane (CH4) emissions. Water depth has been predicted as the best explanatory variable, which is related to CH4 ebullition, but exactly how sediment methanotrophic bacteria mediates these emissions along water depth is unknown. Here, we investigated the activity of methanotrophs in the sediment of shallow coastal zones with high CH4 emissions within a depth gradient from 10–45 m. Field sampling consisted of collecting sediment slices from eight stations along a coastal gradient (0–4 km from land) in the coastal Baltic Sea. We combined real-time measurements of surface water CH4 concentrations, acoustic detection of CH4 seeps in the bottom water, and sediment DNA plus RNA sequencing. Results The relative abundance and CH4 oxidizing activity (pMMO; particulate methane monooxygenase) of the dominant methanotroph Methylococcales was significantly higher in deeper costal offshore areas (36–45 m water depth) compared to adjacent shallow zones (10–28 m). This was in accordance with the shallow zones having CH4 concentrations in the surface water, as well as more CH4 seeps from the sediment. Furthermore, our findings indicate that the low prevalence of Methylococcales and their activity was restrained to the euphotic zone (indicated by PAR data, photosynthesis proteins, and 18S rRNA data of benthic diatoms). This was also indicated by a positive relationship between water depth and the relative abundance of Methylococcales and pMMO. Conclusions We detected a low relative abundance of methanotrophs and CH4

oxidizing activity in shallow coastal areas, this can partly explain the difference in CH4 emissions between shallow and deep coastal areas (and the relationship between CH4 emission and water depth). Potentially a reduced activity of methanotrophs also facilities the build-up of CH4 bubbles in the sediment. CH4 emissions from the study area has previously been calculated to be comparable to that of subarctic lakes, and it is suggested that shallow coastal waters, similarly to inland waters, are hotspots for CH4 emissions.

Background
Coastal zones are transitional areas between land and sea where microbes in the water and sediment cycle large amounts of organic and inorganic carbon compounds [1]. Such zones have recently been shown to be the main source for oceanic methane (CH 4 ) emissions [2]. CH 4 is a potent greenhouse gas that has increased ~2.5 times in the atmosphere since the industrial revolution [3], and is today at ~1.85 ppm [4], and contributes to approximately 20% of tropospheric radiative forcing [5]. Furthermore, the annual atmospheric CH 4 concentration measured during 2014-2017 was record high since 1980 [4]. The majority of CH 4 emissions are derived from human activities (~60%) such as livestock [6], rice paddies [7,8], hydropower dams [9], and waste management [10]. However, natural aquatic systems such as inland waters are reported to contribute a significant portion to CH 4 emissions (30 % or more) [10][11][12]. In marine ecosystems, coastal zones have the highest contribution to global CH 4 emissions [2,13], with shallow inshore waters closer to land being estimated to have an annual CH 4

emission 370
times higher compared to that in the open ocean [12,14,15]. Globally, shallow water depths in coastal zones are linked to higher CH 4 emissions [2], but environmental predictors have been unable to explain this relationship [2]. It is therefore possible that biological mechanisms are partly able to explain the discrepancy between coastal shallow and deeper areas. However, this has not been fully investigated and would help to increase the understanding of the controls of CH 4 cycling in coastal areas.
The cycling of CH 4 in natural aquatic ecosystems is driven by microbial consumption and oxidative processes [16]. In brief, the majority of CH 4 is produced in anoxic zones in sediments as a result of the reduction of e.g. CO 2 , acetate, or methanol by anaerobic methanogenic archaea [17]. Large parts of the produced CH 4 diffuses upwards in the sediment and is oxidized to CO 2 by anaerobic methanotrophic archaea (ANME) [18], anaerobic methanotrophic bacteria [19], and eventually by aerobic methanotrophic bacteria in the oxic sediment surface or the water column [20]. These aerobic methanotrophic bacteria thrive on produced CH 4 , and have traditionally been divided into two types: Type I belonging to the Gammaproteobacteria family Methylococcales; and Type II belonging to the Alphaproteobacteria family Methylocystaceae and Beijerinckiaceae [21]. Both types use the enzyme methane monooxygenase (MMO) to oxidize CH 4 , and are able to utilize either the particulate form (pMMO, i.e. bound to the intracellular membrane) and/or the soluble form (sMMO, i.e. enzyme complex in the cytoplasma) [21]. The importance of methanotrophic bacteria to limit CH 4 Table 2).
Alpha and beta diversity. In the 0-2 cm sediment surface prokaryotic alpha diversity ranged between 7.0-7.9 (Shannon's H, 16S rRNA 2018 data) and only station 13 was slightly lower compared to stations 7 and 11 (7.2 ± 0.3 compared 7.5 ± 0.3 and 7.5 ± 0.1, respectively; One-Way ANOVA, Data S1. Methanotrophic bacteria in inshore and offshore sediments. Gammaproteobacteria had the highest relative abundance of the prokaryotic community in the 0-2 cm sediment surface when comparing phyla and Proteobacteria classes between stations ( Fig. 2A). In the RNA-seq 16 rRNA data the relative abundance of Gammaproteobacteria ranged between 8-29 % ( Fig. 2A), while in the metagenome 16S rRNA gene the relative abundance was between 14 and 24 % for all stations  Because light has been indicated to inhibit CH 4 oxidation we also analysed the amount of RNA transcripts attributed to proteins in the Gene Ontology (GO) category Photosynthesis (Table 2  18S rRNA data of diatoms with a higher relative abundance of benthic genera such as Amphora and Nitzschia in the inshore stations provides further indication that these stations were euphotic (Additional File 1: Fig. S4). This in accordance with the PAR data that indicated the inshore areas to be illuminated while offshore bottom zones were in darkness.
Our results clearly show that Methylococcales were the major methanotroph active in our sediments, while other methanotrophic bacteria were absent or present in low relative abundances in the dataset. The Type II methanotrophic family Methylocystaceae (belonging to Alphaproteobacteria) was not present in the dataset, while the Type II family Beijerinckiaceae had less than 0.06 % relative abundance in each sample (Additional File 2: Data S1). Similarly, the Verrucomicrobia family Methylacidiphilaceae had less than 0.06% relative abundance in each sample (Additional File 2: Data S1). Finally, the NC10 phylum known to contain anaerobic methanotrophic bacteria had less than 0.02% relative abundance in each sample (Additional File 2: Data S1).
However, in the DNA and RNA dataset ammonia oxidizing bacteria/archaea and anaerobic ammonium oxidation (anammox) Planctomycetes together contributed to less than 2.5% of the whole microbial community (Additional File 1: Fig. S5).
Furthermore, AMO sequences showed no differences in CPM values between the offshore and inshore stations (196 ± 90 CPM, Kruskal-Wallis test, H = 0.4, P = 0.83; Fig. 4), suggesting that pore water NH 4 + concentrations did not explain the difference in methanotrophic activity between inshore and offshore areas.
Methanotrophic and methanogenic archaea in the sediment. Archaea had a low relative abundance in the 0-2 cm sediment (1-5 %; Fig. 2), and methanotrophic archaea (ANME) had a less than 0.06 % relative abundance (Additional File 2: Data S1). Methanogenic archaea represented < 15 % of all archaea and did not show a difference in relative abundance among inshore and offshore stations (based on RNA-seq extracted 16S rRNA data, One-Way ANOVA post hoc Tukey tests for each station; Additional File 1: Fig. S6). However, the 16S rRNA relative abundance of methanogenic archaea was indicated to be associated with sites close to the coast by correlating positively with the measured CH 4 concentrations in the water surface (2018 RNA data, Spearman's rank correlations, rho = 0.672, P = 0.0008, n = 21), and negatively with water depth (rho = -0.707, P = 0.0003). RNA transcripts and genes attributed to proteins affiliated with the GO category methanogenesis were found at all stations with low CPM values (< 800 CPM; Table 1). This finding suggests that higher CH 4 concentrations in the surface water in the study area was Methane escape from the sediment. Acoustic data of the seafloor and bottom water was collected in the study area during 2018, and CH 4 seeps were defined as either trains of bubbles or bubble plumes (Fig. 5). The results showed that the prevalence of CH 4 seeps in sediment surface was greater in shallow areas compared to deeper areas ( Fig. 6A), further suggesting that CH 4 availability did not explain the lower relative abundance of methanotrophs in the inshore stations. Moreover, the amount of CH 4 seeps km -1 was negatively correlated with water depth (Pearson correlation, r = -0.83, P < 0.000001, n = 52; Fig. 6B).

Discussion
Shallow coastal zones are known to have high CH 4 concentrations in the water column compared to deeper waters [12,14,15]. This was also indicated by our acoustic data of CH 4 seeps and the real-time measurements of CH 4 in the surface oxygenated at all studied stations and was therefore unlikely to be a limiting factor for methanotrophs in the study area. In addition, the real-time measurements and acoustic data of CH 4 also showed more CH 4 availability in the inshore areas (compared to offshore), and it is therefore unlikely CH 4 was a limiting factor inhibiting growth and activity of methanotrophs. The 0-2 cm sediment surface was sliced and the data showed a very low relative abundance of methanogens and their activity at all studied stations. Considering that methanogenesis occurs in anoxic sediment [17] these findings indicate that the sediment surface was oxygenated by the bottom water in the study area.
We measured higher pore water NH 4 + concentrations in the offshore stations, and most of the measured NH 4 + likely derived from organic matter mineralization in the Considering that the geochemistry data (CH 4 water concentrations and CH 4 seabed seeps) and biology data (relative abundance of methanotrophic bacteria and RNA transcripts attributed to pMMO) both showed a positive relationship with water depth and that the main environmental factor changing along this gradient was light intensity, we suggest that illumination might influence sediment microbial communities. That the inshore stations were euphotic was indicated by 1) the CTD profiles showed that PAR light reached 28 m in the study area; 2) photosynthesis mRNA data (Fig. 7) that showed a decrease with water depth; and 3) benthic diatoms such as Amphora and Nitzschia [ 43] in the inshore stations based on 18S rRNA data (Additional File 1: Fig. S4). Previous studies conducted in a reservoir and water concentrations increased when the snow cover was removed and illumination increased in the water column. Additionally, the activity of NH 4 + oxidizing bacteria are known to be inhibited by light availability [45], and this can further explain why light might have an effect on methanotrophs as the enzymes ammonia monooxygenase (AMO) and MMO are highly similar and evolutionary related [46].
However, light has also been observed to stimulate methanotrophic activity in wetland sediments (Florida, USA) [47], and polar lake water (north-west Russia)

Conclusions
On a global scale CH 4 emissions from coastal zones are higher at shallower water depths [2], and we also detected this relationship between water depth and CH 4 seeps and CH 4  reported in this study). This is within the range of CH 4 emissions reported from subarctic lakes [49], and it is suggested that shallow coastal waters, similarly to inland waters, are hotspots for CH 4 emission. Moreover, limited methanotrophic activity could also explain why shallow coastal waters in rapidly changing ecosystems like the East Siberian artic shelf have higher CH 4 emissions compared to the deeper offshore water [50,51]. Significant CH 4 emissions from the artic subsea might therefore only occur in the shallowest parts due to a limited activity of methanotrophs. Our results imply that methanotrophs, rather than solely methanogens, play a key role in shallow coastal zones regulating CH 4 emissions.
Globally, low methanotrophic activity in the sediment could partly explain the substantial amount of CH 4 emissions from shallow inland water bodies and reservoirs [52]. Furthermore, the results suggest that low CH 4 oxidizing activity by methanotrophs might explain why shallow parts of the costal rim has higher CH 4 emissions. This is an overlooked mechanism that can potentially contribute to explain the dynamics of greenhouse emissions from marine ecosystems. . In brief, circulation pumps equipped to a seawater inlet transfer seawater into an equilibrator with showerhead. The gas is transferred through a gas handling system, and is analysed for CH 4 concentrations by a cavity ring-down spectrometer gas analyser (Picarro G2131-i). This system also tracked temperature and salinity as long as Electra was cruising.

Methods
Acoustic data of methane seeps from the sediment. Acoustic data were collected  Fig. S7. This is because the beam footprint increases with depth. While this should provide a more accurate picture in theory, there might be issues with overlapping seeps (multiple seeps being counted as one), and the actual seep distribution might be somewhere in between.
Taxonomic annotation. SSU rRNA sequences were extracted from the DNA and RNA sequence data with SortMeRNA 2.1b [59] followed by annotation using Kraken2 2.0.7 [60]. After ribosomal depletion RNA sequencing still yielded on average 89% rRNA sequences per sample (range 86-92%). We therefore decided to also taxonomically classify 16S rRNA sequences. Kraken2 was run with a paired-end The python package biom-format 2.1.7 [62] was then used to convert the biom-  [69]. In more detail, the perl script "run_DE_analysis.pl" supplied with Trinity 2.8.2 [70] was used to run the analysis.
The script inputs raw read data, and normalize read counts, and analyze differential

Declarations
Ethics approval and consent to participate Not applicable.

Consent for publication
Not applicable.

Availability of data and materials
The raw sequencing data supporting the conclusions of this article is available in the NCBI BioProject repositories, PRJNA541421 (DNA data) and PRJNA541422 (RNA data    Figure 1 The map shows the Baltic Sea and the location of the study area in the Western Gulf of Finla The stacked bars show relative abundance (x-axis %) of A) prokaryotic phyla and Proteobacte Sequences annotated to the InterPro AMO/pMMO family was classified against the UniProtKB Figure 5 Onboard the research vessel acoustic data (EK80 wide band transceiver) was collected from