Lake mixing regime selects methane-oxidation kinetics of the 1 methanotroph assemblage 2

In freshwater lakes, large amounts of methane are produced in anoxic sediments. Methane-oxidizing bacteria 11 effectively convert this potent greenhouse gas into biomass and carbon dioxide. These bacteria are present throughout the 12 water column where methane concentrations can range from nanomolar to millimolar concentrations. In this study, we tested 13 the hypothesis that methanotroph assemblages in seasonally stratified lakes are adapted to the contrasting methane 14 concentrations in the epiand hypolimnion. We further hypothesized that lake overturn would change the methane oxidation 15 kinetics as more methane becomes available in the epilimnion. Together with the change of methane oxidation kinetics, we 16 investigated changes in the transcription of genes encoding methane monooxygenase, the enzyme responsible for the first step 17 of methane oxidation, with metatranscriptomics. We show that the half-saturation constant (Km) for methane, obtained from 18 laboratory experiments with the natural microbial community, differed by two orders of magnitude between epiand 19 hypolimnion during stable stratification. During lake overturn, however, the kinetic constants in the epiand hypolimnion 20 converged along with a change of the transcriptionally active methanotroph assemblage. Conventional particulate methane 21 monooxygenase appeared to be responsible for methane oxidation under different methane concentrations. Our results suggest 22 that methane availability is important for creating niches for methanotroph assemblages with well-adapted methane-oxidation 23 kinetics. This rapid selection and succession of adapted lacustrine methanotroph assemblages allows high methane removal 24 efficiency of more than 90 % to be maintained even under rapidly changing conditions during lake overturn. Consequently, 25 only a small fraction of methane stored in the anoxic hypolimnion is emitted to the atmosphere. 26 https://doi.org/10.5194/bg-2019-482 Preprint. Discussion started: 27 January 2020 c © Author(s) 2020. CC BY 4.0 License.


Introduction 27
Lakes are an important source of greenhouse gases with methane emissions contributing a major fraction to the climate impact 28 of lacustrine systems (DelSontro et al., 2018). The oxidation of the strong greenhouse gas methane in freshwater lakes is 29 mainly achieved by methane-oxidizing bacteria (MOB), which have the unique ability to use methane as their sole carbon and 30 energy source (Hanson and Hanson, 1996). In anoxic habitats of seasonally stratified lakes, large amounts of methane, which 31 is produced as a final product of anaerobic organic matter degradation, can accumulate in the oxygen-depleted hypolimnion 32 (Conrad, 2009;Steinsberger et al., 2017). Under stratified conditions, aerobic and sometimes anaerobic MOB oxidize this 33 methane in the water column, thereby preventing diffusive outgassing (Bastviken et  kinetic traits in rapidly changing lake environments has so far not been studied systematically. Here, we hypothesized that 47 kinetic parameters of methane oxidation vary between epi-and hypolimnion and that kinetic parameters vary seasonally 48 together with the MOB assemblage, which would show that methane availability is a driver of methane oxidation kinetics of 49 the MOB assemblage. Further, the methane affinity of lacustrine MOB especially in the epilimnion has implications for the 50 amount of methane outgassing during both, stable stratification and lake overturn. 51 The first step of methane oxidation is mediated by the methane monooxygenase. Most MOB possess the copper-dependent 52 particulate form of the methane monooxygenase (pMMO). Known isozymes of pMMO have been shown to exhibit different 53 methane oxidation kinetics, including high affinity variants that are able to oxidize methane even at atmospheric concentrations 54 (Baani and Liesack, 2008;Dam et al., 2012). A subset of MOB encode the soluble MMO (sMMO) that has a lower methane 55 affinity than pMMO and has been hypothesized to be used by MOB under high methane concentration, because MOB biomass 56 is assumed to be higher under such conditions leading to copper limitation and a switch to copper-free sMMO (Semrau et al., 57 2018). The abundance of the sMMO gene has been found to be low in a Lake Rotsee (Guggenheim et al., 2019), but relative 58 transcription between epi-and hypolimnion has not been investigated so far. 59 In this study we conducted a combined kinetic and metatranscriptomic analysis to test our hypothesis that MOB assemblages 60 show distinct methane oxidation kinetics in the methane-rich hypolimnion compared to the epilimnion with low methane 61 sequenced separately serving as replicates indicated with Jan (r). RNA yields from the October sampling were deemed 143 insufficient for sequencing as no typical RNA bands were visible during quality control and therefore these samples were 144 omitted from metatransciptome analysis. Metagenomic and metatranscriptomic 150bp paired-end sequencing was done on a 145 NovaSeq 6000 sequencer (Illumina) at Novogene (HK) company limited (Hong Kong, China). Ribosomal RNA was depleted 146 with Ribo-Zero Magnetic Kit (Illumina) prior to sequencing. The co-assembly of metagenomic sequences alone yielded less 147 pmoA as well as pmoB and pmoC sequences than expected, likely due to low coverage. Therefore, we combined predicted 148 genes from both the metagenomic and the metatranscriptomic de-novo assembly as described below. Due to low coverage of 149 pmoA, pmoB and pmoC in the metagenome, we used the metagenome only in the assembly process. All further analyses relied 150 on the metatranscriptome.

Environmental conditions during the autumn overturn 175
From October 2017 to January 2018 the epilimnion depth in Lake Rotsee gradually increased from 5.5 to 13.7 m ( Fig. 1a-d). 176 This process of vertical mixing continuously transferred methane that was stored below the oxycline into the epilimnion above. 177 The gradual progression of the autumn overturn stimulates the growth of a distinct MOB assemblage in the epilimnion above 178 the oxycline in response to an influx of methane from the hypolimnion as shown in previous work of Lake Rotsee (Mayr et

Succession of kinetically different microbial communities 196
Along with the differences in the physical and chemical properties of the two water bodies, we observed a significant difference 197 in the methane oxidation kinetics of the MOB assemblages. From the methane oxidation rates shown in Fig. 1e-h we derived 198 the parameters of Monod kinetics (Fig. 2). These kinetic parameters allowed us to characterize the MOB assemblages above 199 and below the oxycline physiologically and to relate these results to the biogeochemical conditions. The curves describing the 200 methane oxidation kinetics of the MOB assemblages above and below the oxycline did not intersect (except at the origin) in 201 https://doi.org/10.5194/bg-2019-482 Preprint. Discussion started: 27 January 2020 c Author(s) 2020. CC BY 4.0 License.
October and November ( Fig. 1e-g). This means that the MOB assemblage in the epilimnion showed both a higher affinity for 202 methane (Fig. 2a) and a higher cell-specific maximum methane oxidation rate (Fig. 2b) than the assemblage below the oxycline. 203 The higher methane affinity is in line with the methane-deficient conditions in the epilimnion. But the fact that both affinity 204 and maximum rate are higher suggests that there were likely additional mechanisms or traits, like adaptation to oxygen 205 concentration or temperature (Hernandez et al., 2015;Trotsenko and Khmelenina, 2005), that prevent the epilimnetic MOB 206 assemblage from invading the assemblage in the hypolimnion. At the end of the overturn period (Fig. 1h) both MOB 207 assemblages showed very similar methane oxidation kinetics. 208 The pronounced difference in Km of the two assemblages in October, when the lake was still stratified, gradually converged 209 during lake overturn from November to January (Fig. 2a). From October to January, the half-saturation constant for methane 210 decreased from 15 to 2.7 µM for the hypolimnetic assemblage, but increased from 0.7 to 1.2 µM in the epilimnion, with higher 211 Km values in November and December (Fig. 2a). A table summarizing the measured methane oxidation kinetics can be found 212 in Supplementary Table 1 In contrast to the substrate affinity, the maximum cell-specific methane oxidation rate started at similar levels in the stratified 225 lake (Fig. 2b). As methane entered the epilimnion in November, the cell-specific Vmax of the MOB assemblage in this layer 226 was almost 15 times faster than the hypolimnion assemblage, which ensured a fast methane oxidation rate in the epilimnion 227 close to the surface during this critical phase. As a consequence, methane concentrations and emissions remain low 228 (Zimmermann et al., 2019). Towards the end of the lake overturn, when the thermocline had moved to 15 m depth and the two 229 MOB assemblages were most likely homogenized, methane oxidation rates decreased again. By contrast, the cell-specific 230 methane oxidation rate in the hypolimnion remained rather constant throughout the overturn from November to December.  h -1 cell -1 , of the MOB assemblage in the hypolimnion were well in the range of these reported values. However, the MOB 242 assemblage in the epilimnion showed much higher specific affinities suggesting that these assemblages were well adapted to 243 the very methane limited conditions in the epilimnion. 244 Methanotroph cell counts suggest that both the MOB assemblage above and below the oxycline were actively growing over 245 the course of the overturn. In the epilimnion the abundance of MOB increased from 0.1x10 5 to 2x10 5 cells mL -1 from October 246 to December, below the oxycline the abundance increased from 0.8x10 5 to 1.2x10 5 cells mL -1 . The in-situ methane oxidation 247 rates (Supplementary Table 1 rates were 93 % (median) of the maximum methane oxidation rate. This suggests that the growth of the MOB assemblage in 250 the epilimnion was generally methane limited, despite their higher methane affinity. 251

Dynamics of the MOB assemblage and variants of pMMO 252
Methane oxidation during lake overturn was performed by diverse assemblages of MOB as determined by metatranscriptomic 253 analysis (Fig. 3a1-c1). Thus, the reported kinetics reflect aggregate properties of the respective assemblage.   , (b1) pmoB, (c1) pmoC based on transcripts per million (TPM), mapped at 99% identity. pmoCAB variants were assembled from metagenomes and metatranscriptomes samples originating from the same depths and dates as shown in Fig. 1. Different color schemes were chosen for pmoA, pmoB and pmoC variants. (a2) pmoA, (b2) pmoB, (c2) pmoC shown as summed TPM of all variants for epi-and hypolimnion (orange and cyan, respectively). Epi = epilimnion, Hypo = hypolimnion.
In November, and to a lesser degree in December, the composition of transcribed pmoCAB gene variants differed between epi-266 and hypolimnion, with some variants (e.g. pmoA_8 and 10, pmoB_7, 9 and 16, pmoC_9, 16, 22) being confined to the 267 hypolimnion ( Fig. 3a1-c1). The difference in gene transcription reflects changes in the MOB assemblage (see detrended 268 correspondence analysis in Supplementary Fig. 2), which may explain the observed differences in methane-affinity (Fig. 2). 269 Notably however, a prominent proportion of the pmoCAB gene variants transcribed in the epilimnion were also present in high 270 abundance in the hypolimnion, which likely reflects the increasing influence of the highly transcriptionally active epilimnion 271 assemblage (Fig. 3a2-c2)  The composition of transcribed pmoCAB variants showed a distinct change over time (Fig. 3a1-c1 and Supplementary Fig. 2). 276 The relative abundance of the pmoCAB variants that were specific to the hypolimnion decreased until January (Fig. 3a1-c1) 277 and the two MOB assemblages became increasingly similar in terms of their kinetical properties (Fig. 2). From December to 278 January another strong shift in the MOB assemblage towards dominance of pmoA_1, pmoB_3 and pmoC_3 occurred. This 279 did however not change the methane affinity much (Fig. 2), suggesting that different MOB assemblages can have similar 280 methane affinities. The shift of the MOB assemblage was accompanied by a drop in temperature and rise in oxygen, which are 281 probable drivers of MOB succession in addition to methane availability (Hernandez et al., 2015;Oshkin et al., 2015;Trotsenko 282 and Khmelenina, 2005). With this shift, we also observed a decrease in Vmax per cell (Fig. 2B). We attribute this to a shift from 283 growth-oriented MOB dominating the bloom phase to a late-successional MOB assemblage adapted to cold temperatures as 284 observed the year before (Mayr et al., 2019b). Further, the metatranscriptomic analysis supports the interpretation that the 285 observed differences in methane oxidation kinetic parameters between water layers and over time have a basis in compositional 286 differences of the transcriptionally active MOB assemblages. 287

Conclusions 288
In Lake Rotsee, as in many other stratified lakes, the high methane availability in the hypolimnion contrasts with low methane 289 availability in the epilimnion. Therefore, we hypothesized that the resident MOB assemblages are adapted to the respective 290 conditions. Our field study revealed a high level of adaptation of the MOB assemblage: the Km differed by two orders of 291 magnitude between epi-and hypolimnion during stable stratification. Transcribed methane oxidation genes differed as well, 292 indicating that methane affinity is an important trait structuring MOB assemblages in this system. The MOB assemblage and 293 its kinetic traits adapted rapidly to changing conditions in the epilimnion. In October, the low epilimnion Km suggested an 294 adaptation to oligotrophic conditions with low methane concentrations. During the autumn overturn, affinity decreased slightly 295 but remained below hypolimnion values, reflecting persistently low methane concentrations that suggest methane-limited 296 growth despite higher methane input. We observed increased Vmax in the epilimnion during November and December. In this 297 period, continuous transport of methane into the epilimnion provided an advantage of fast-growing MOB over slower 298 competitors. By contrast, in the hypolimnion methane concentrations during overturn exceeded the Km several-fold suggesting 299 that MOB growth was not limited by methane concentrations. 300 Our transcriptomic analysis revealed that the variations in methane affinity were entirely linked to pmoCAB variants and 301 pMMO appeared to be the dominant methane monooxygenase throughout. We found no evidence for shifts between sMMO 302 and pMMO transcription as hypothesized previously (Semrau et al., 2018) nor could we observe previously described high-303 affinity pMMO variants, which suggests considerable, so far unappreciated variability in pMMO kinetics. Further research 304 will be needed to obtain kinetic data on individual pMMO variants. However, the provided kinetic parameters for lake MOB 305 assemblages will inform future trait or process-based models of the MOB assemblage and methane emissions. In summary, 306 our work demonstrates that differential methane availability governed by lake mixing regimes creates niches for MOB 307 assemblages with well-adapted methane-oxidation kinetics.

319
The January hypolimnion sample was measured twice and the replicate is labelled as Jan (r). Relative abundance of gene variants of (a1) 320 pmoA, (b1) pmoB, (c1) pmoC based on transcripts per million (TPM), mapped at 99% identity. pmoCAB variants were assembled from 321 metagenomes and metatranscriptomes samples originating from the same depths and dates as shown in Fig. 1

Competing interests 334
The authors declare that they have no conflict of interest. 335

Acknowledgements 336
This research was funded by the Swiss National Science Foundation (grant CR23I3_156759), by ETH Zurich and Eawag. We 337 are grateful to Andreas Brand for his support and advice in the early stages of the project, to Carsten Schubert, Serge Robert 338 and Daniel Steiner for the possibility and the support to use the equipment for radioisotope and methane measurement. We are 339 also grateful to Lea Steinle for sharing her expertise on how to handle the radiolabeled methane. We would like to thank Karin 340 Beck and Patrick Kathriner for technical assistance during field work and laboratory analysis. We thank Feng Ju and Robert 341 Niederdorfer for advice on the bioinformatics analysis. Sequencing data were analyzed in collaboration with the Genetic 342 Diversity Centre (GDC) of ETH Zurich.