Grazing Pressure-Induced Shift in Planktonic Bacterial Communities with The

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Grazing pressure-induced shift in planktonic bacterial communities with the

dominance of acIII-A1 actinobacterial lineage in soda pans

Attila Szabó1, Kristóf Korponai1, Boglárka Somogyi2, Balázs Vajna1, Lajos Vörös2, Zsófia Horváth2, Emil

Boros3, Nóra Szabó-Tugyi2, Károly Márialigeti1, Tamás Felföldi1

1 1 Department of Microbiology, ELTE Eötvös Loránd University, Pázmány Péter stny. 1/C., 1117 Budapest,

2 Hungary.

3 2 Balaton Limnological Institute, Centre for Ecological Research, Klebelsberg Kunó u. 3., 8237 Tihany, Hungary.

4 3 Danube Research Institute, Centre for Ecological Research, Karolina út 29., 1113 Budapest, Hungary.

7 Astatic soda pans of the Pannonian Steppe are unique environments with respect to their multiple extreme physical

8 and chemical characteristics (high daily water temperature fluctuation, high turbidity, alkaline pH, salinity,

9 polyhumic organic carbon concentration, hypertrophic state and special ionic composition). However, little is

10 known about the seasonal dynamics of the bacterial communities inhabiting these lakes and the role of

11 environmental factors that have the main impact on their structure. Therefore, two soda pans were sampled

12 monthly between April 2013 and July 2014 to reveal changes in the planktonic community. By late spring in both

13 years, a sudden shift in the community structure was observed, the previous algae-associated bacterial

14 communities had collapsed, resulting the highest ratio of actinobacteria within the bacterioplankton (89%, with

15 the dominance of acIII-A1 lineage) ever reported in the literature. Before these peaks, an extremely high

16 abundance (>10,000 individuum l-1) of microcrustaceans (Moina and Arctodiaptomus) was observed. OTU-based

17 statistical approaches showed that in addition to algal blooms and water-level fluctuations, zooplankton densities

18 had the strongest effect on the composition of bacterial communities. In these extreme environments, this implies

19 a surprisingly strong, community-shaping top-down role of microcrustacean grazers.

21 The Pannonian Steppe is a part of the Eurasian steppe; it is situated within the Carpathian Basin, surrounded by

22 the Carpathian Mountains. Soda lakes or smaller pans, as in elsewhere in the steppe, are integral parts of the

23 landscape. They are particularly numerous within the Carpathian Basin, which is their most western occurrence

24 in Eurasia (Boros and Kolpakova, 2018). Soda pans in this region represent multiple extreme environments with

25 respect to their special ion composition, alkaline pH, salinity, high turbidity, humic material and nutrient content,

26 and special underwater light-limited conditions (Boros et al., 2014, 2017, 2020). The lakes can be divided into

27 two ecologically distinct types: some of them are ‘turbid’ because of the immense number of inorganic suspended

28 particles, and others are ‘colored’ due to the high concentration of dissolved humic matter (Boros et al., 2014).

29 Planktonic algal blooms occur frequently in these lakes, since the high nutrient content (inorganic nitrogen and

30 phosphorus) is present throughout the year, mainly due to the guano of migratory birds and decaying plant

31 material originating from the shoreline vegetation (Somogyi et al., 2009; Boros et al., 2016). During summer

32 months, filamentous cyanobacteria bloom in the shallow waters, while at temperatures under 15°C, pico-sized

33 green algae become abundant and may form visible algal blooms (Somogyi et al., 2009; Pálffy et al., 2014). Fish

34 are absent from these pans due to their intermittent character, and partly because of this microcrustaceans,

35 especially the natronophilic Arctodiaptomus spinosus (Copepoda: Calanoida) and Moina brachiata (Cladocera)

36 can be abundant by late spring (Horváth et al., 2014; Tóth et al., 2014). Due to the complexity of aquatic food

37 webs and bottom-up effects, only a few reports were published on how zooplankton regulate natural aquatic

38 microbial communities (e.g., Eckert et al., 2013). Since the microbial communities of these pans are not limited

39 by nutrients, these environments pose as natural field models to study the grazing effect of zooplankton (rotifers

40 and microcrustaceans) on bacterioplankton composition.

41 Prokaryotic communities of many alkaline lakes were investigated in detail (e.g., Antony et al., 2013; Lanzén et

42 al., 2013; Vavourakis et al., 2016; Andreote et al., 2018; Edwardson and Hollibaugh, 2018, Zorz et al., 2019),

43 but no comprehensive study focusing on the seasonal dynamics and biological relationships of soda lake

44 planktonic microbial communities has been performed so far. Nevertheless, soda lakes can be found on almost

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 45 every continent, and these extreme environments represent a significant fraction of continental saline aquatic

46 habitats and an important source of unexplored microbial biodiversity (Hammer 1986, Grant 2004, Sorokin et al.

47 2014).

48 The relatively easily accessible pans of the Pannonian Steppe provide a unique opportunity to reveal temporal

49 patterns in the microbial community structure, as was reported previously in the case of freshwater and marine

50 communities (see, e.g., Eiler et al., 2012; Fuhrman et al., 2015). Therefore, monthly sampling was carried out for

51 more than a year in two ex lege protected soda pans representing different types, the colored Sós-ér pan and the

52 turbid Zab-szék pan situated in the Kiskunság region (Hungary). In order to put these findings into a broader

53 ecological context, microscopic and zoological investigations were carried out in parallel.

54 Results

55 Environmental conditions

56 The water depth of the pans changed remarkably throughout the study period (in the turbid Zab-szék pan: 2-45

57 cm, in the colored Sós-ér pan: 0-50 cm). The water level in the turbid pan was under 12 cm from February to July

58 2014 and under 3 cm from April to June 2014. Salinity values also varied greatly, from subsaline (1.5 - 2.4 g l-1,

59 associated with high water level during the spring of 2013) to almost mesosaline (18.9 g l-1, close to desiccation).

60 The pH was alkaline throughout the study period (turbid pan: 9.1 - 10.2; colored pan: 8.3 - 10.0) and was the

61 lowest in the colored pan during the spring of 2013. The water temperature remained below 16°C from September

62 to March, with the lowest value measured in December 2013. During the summer months, the water temperature

63 varied between 25°C and 31°C. The total organic carbon content was generally higher in the colored pan [the

64 highest values (855, 1223 mg l-1) were observed before desiccation]. In the colored pan, organic carbon was

65 generally present in dissolved form, while in the turbid pan, it was composed of both particulate and dissolved

66 matter. The inorganic suspended solids (ISS) content was much higher on average in the turbid pan than in the

67 colored pan. Prokaryotic cell numbers varied between 1.42 × 107 and 4.74 × 108 cells ml-1. The environmental

68 parameters measured are given in Supplementary Table S1. 4

70 Based on their chlorophyll a content, pans were hypertrophic; a winter/spring algal bloom was observed from

71 November 2013 to April 2014. During the algal bloom, nanoplanktonic and picoeukaryotic algae dominated in

72 the colored pan, while in the turbid pan an exclusive picoeukaryotic dominance was found (Supplementary Table

73 S1 and S3). Moreover, in the turbid pan, the phytoplankton was dominated by picoalgae through the entire study

74 period. In August 2013, picocyanobacteria (genus Synechococcus, Supplementary Fig. S2) proliferated

75 massively, then in October the pico-sized green algae (Chloroparva, Choricystis and other trebouxiophyceaen

76 green algae, Supplementary Fig. S3) became dominant; their abundance peaked in February 2014 (with 3 × 105

77 µg l-1 biomass). Picoalgal cell numbers were higher by one order of magnitude there than in the colored pan.

78 Nanoplanktonic algae were detected only on three sampling dates: Nitzschia palea and Chlamydomonas sp. in

79 August 2013, Nitzschia palea in December 2013 and Cryptomonas sp. in March 2014, the latter with a high

80 biomass (3,450 µg l-1).

81 Contrary to in the turbid pan, larger nanoplanktonic algae dominated in the colored pan. During the spring and

82 early summer of 2013, algal cells were scarce and mostly nanoflagellates (Cryptomonas, Rhodomonas,

83 Chlamydomonas) were present (chlorophyll a concentration 0.5-3.6 µg l-1). In July, only diatoms were detected

84 (Nitzschia, Cocconeis and Cymbella species). Before the desiccation of the pan, cyanobacteria (Anabaenopsis

85 sp.), pico-sized green algae, euglenoids and green flagellated algae (Chlamydomonas sp.) were abundant in the

86 water (the chlorophyll a concentration was 460 µg l-1 in August 2013). After refilling in November 2013, the

87 chlorophyll a concentration values were high (between 350 and 380 µg l-1) until February 2014, and pico-sized

88 green algae, euglenoids (Euglena and Phacus) and green flagellated algae (Carteria and Chlamydomonas species)

89 dominated. Before the desiccation in July 2014, Navicula sp. was also present. In December 2013, the filamentous

90 cyanobacterium Oscillatoria was also detected.

91 Zooplankton

92 In the turbid pan, cladocerans and copepods peaked in May 2014, with a surprisingly high abundance of 14,160

93 and 17,760 individuum l-1 (Supplementary Table S1). These groups were present throughout the year, with an

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 94 average abundance of 143 and 636 individuum l-1, respectively. The average abundance of rotifers in this pan was

95 637 individuum l-1, and they peaked in September 2013, with 5148 individuum l-1. In the colored pan, the

96 abundance of small crustaceans was an order of magnitude lower, with maximum values in July 2013 and in

97 March 2014. Rotifer numbers were high in May 2013, between July and August 2013, before the desiccation of

98 the pan.

99 Diversity and composition of the prokaryotic community

100 Based on the qPCR results, Archaea represented only a minor fraction (13% on average) of the prokaryotic

101 community (Supplementary Fig. S4); however, they were detected in most of the samples. Their average

102 proportion of the community was higher in the turbid pan (19%), and their highest relative abundance (47%) was

103 also detected in the turbid pan in the sample taken in June 2014.

104 The number of bacterial OTUs, the estimated richness and the diversity indices varied across the sampling period

105 (Supplementary Fig. S5). Richness and diversity values were generally higher in the turbid pan. In this pan, the

106 lowest values were detected in July 2013 and June 2014, during the actinobacterial relative abundance peaks. The

107 highest richness values from this pan were obtained from September to October 2013. In the colored pan samples,

108 the lowest richness was detected in the April 2013 sample, while the highest richness was estimated in the March

109 2014 sample. Diversity estimators in the turbid pan were lowest in June 2014 and highest in May and December

110 2013, and in March 2014. In the colored pan, the lowest values were recorded in April 2013 and the highest in

111 June 2014. Based on the two-way PERMANOVA test, the bacterial communities of the pans and seasons were

112 significantly different (p < 0.001) in the study period. From the 3127 OTUs obtained, 532 were shared between

113 both pans, 1858 were detected only from the turbid pan and 737 only from the colored pan. However, the vast

114 majority of the sequences (81%) belonged to the shared OTUs, and thus the dominant OTUs were the same in

115 both pans. Based on the Bray-Curtis similarity index, the communities showed similar seasonal dynamics

116 (Supplementary Fig. S6). Changes in the taxonomic compositions of the pans had the same tendency from April

117 to May 2013, and the same pattern was observed between February and May 2014 in the turbid pan and between

118 March and June in the colored pan. This common phenomenon was the result of remarkable changes in the relative 6

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 119 abundance of actinobacteria (Fig. 1). Similarities in the bacterial community structures were visualized by NMDS

120 ordination based on a Bray-Curtis distance matrix (Fig. 2). The following environmental variables were fitted

121 significantly (p ≤ 0.05) onto the NMDS ordination: depth, pH, salinity, concentration of chlorophyll a, dissolved

122 organic carbon (DOC), particulate organic carbon (POC), ISS, picocyanobacterial and picoeukaryotic algal

123 biomass, copepod and cladoceran abundance. Based on the SIMPER test, the following OTUs were responsible

124 for the at least 40% differences among the samples: OTU1 (acIII-A1), OTU15 (Cyclobacteriaceae), OTU10

125 (Flavobacterium), OTU9 (Flavobacterium), OTU3 (Nitriliruptor), OTU2 (Synechococcus), OTU6 (bacII), OTU7

126 (Rhodobaca), OTU8 (Hydrogenphaga), OTU4 (Ilumatobacter), OTU5 (acTH1), OTU14 (Actinobacteria),

127 OTU13 (Luteolibacter), OTU11 (acSTL), OTU31 (Algoriphagus), OTU29 (Limnohabitans), OTU16 (alfVI) and

128 OTU27 (alfVI) (OTU serial numbers correspond to their abundance in the whole dataset; lower numbers with a

129 higher constitution). Most of the taxa were related to higher algal densities, while betaproteobacteria were related

130 to the high water level and low salinity period of the pans (during the spring of 2013). These samples (especially

131 from the colored pan) were the most distinct from the others. An inverse relationship was observed between

132 prokaryotic cell numbers and depth. Samples from the low water-level period were fitted with pH, salinity, the

133 concentration of DOC, POC and ISS, because of the evaporation and concentration of lake water. Chlorophyll a

134 concentration, nanoplankton biomass and an Euglena chloroplast OTU (colored pan), picoeukaryotic algal

135 biomass (turbid pan) fitted with samples from the winter algal bloom period. Picocyanobacterial biomass fitted

136 with the summer samples of the turbid pan. The abundance of microcrustaceans fitted with the samples having

137 high relative abundance of actinobacteria, except the June 2014 sample from the turbid pan. Based on the

138 significantly fitted environmental parameters and the NMDS ordination, water regime (depth and salinity),

139 phytoplankton (algal biomass and composition) and microcrustaceans (their abundance) shaped the planktonic

140 bacterial community structure.

141 Changes in the prokaryotic community composition

142 In April 2013, Betaproteobacteria, especially the genus Hydrogenophaga, was the most abundant bacterial

143 community member in the turbid pan (Fig. 1). Other groups with a high relative abundance (≥ 5%) were 7

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 144 Luteolibacter, an uncultivated Planctomycetaceae genus, bacII and the acIII-A1 actinobacterial lineage. After

145 continuous increase, the relative abundance of planktonic actinobacteria peaked in July (51%), with acIV, acTH1,

146 acIII-A1 and Nitriliruptor as the most significant groups. Besides Actinobacteria, genus Blastocatella

147 (Acidobacteria) was also abundant. In August and September 2013, in accordance with the microscopic

148 observations, picocyanobacteria became abundant within the bacterial community, while the relative abundance

149 of actinobacteria slowly decreased. From September 2013, the relative abundance of bacterial groups dominant

150 during the winter/spring phytoplankton bloom started to increase. These taxa (i.e. Rhodobaca and another

151 unidentified member of the alfVI lineage, Luteolibacter, various unidentified lineages from Cyclomorphaceae,

152 Cryomorphaceae, Flavobacteriaceae and Saprospiraceae, genera Flavobacterium and Aquiflexum from

153 Bacteroidetes, cyanobacteria, Ilumatobacter, acIII-A1, acSTL, and an unidentified group of Actinobacteria) with

154 varying relative abundances dominated the planktonic microbial community until May 2014. From May, the

155 relative abundance of planktonic actinobacteria increased suddenly, peaked in June with 89% within the bacterial

156 community, and then started to decrease again by July. The acIII-A1 lineage was the most dominant group (54%

157 of total bacteria) in June besides Ilumatobacter, acTH1, acSTL and Nitriliruptor.

158 The colored pan was dominated by Flavobacteria and Betaproteobacteria in the spring of 2013 (Fig. 1). In April,

159 the genus Flavobacterium was the most plenteous (69%) in the water, and in the following months, other

160 Bacteroidetes taxa (Fluviicola, Algoriphagus, unidentified Sphingobacteriales) were also abundant. From

161 Betaproteobacteria, the genera Hydrogenophaga and Limnohabitans had high relative abundance. By the summer,

162 Actinobacteria, especially the acIII-A1 lineage became the most significant constituent in the bacterial

163 community. After refilling, an unidentified Cyclobacteriaceae group was the most abundant, with other taxa

164 dominant during the winter/spring phytoplankton bloom (Indibacter, Flavobacterium, Rhodobaca, and other

165 bacII and alfVI group representatives, and members of Verrucomicrobia and Actinobacteria). In December 2013

166 and January 2014, an unidentified Oligoflexaceae group was also abundant. Hydrogenophaga became abundant

167 again within the community during the early months of 2014. Between April and June 2014, the relative

168 abundance of the acIII-A1 actinobacterial lineage peaked again. In addition to this lineage, Nitriliruptor, an

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 169 unidentified Actinobacteria, a Cryomorphaceae group, Flavobacterium, a Sphingobacteriales group, alf-B, alfVI

170 and Comamonadaceae lineages were present with a high relative abundance.

171 Effects of algae and zooplankton abundance on the planktonic bacterial community

172 In both pans, during the winter/spring algal blooms, members of the Cytophagia, Flavobacteriia and

173 Rhodobacterales taxa dominated in the planktonic bacterial community. Later, in parallel with the increasing

174 zooplankton abundance, algal blooms collapsed, and actinobacterial relative abundance peaks occurred (Fig. 3).

175 Based on these observations we highlighted two groups within the microbial community: the algae-associated

176 Cytophaga-Flavobacteriia-Rhodobacterales (CFR) group and planktonic actinobacteria. Changes in the relative

177 abundance of the CFR group and actinobacteria in parallel with algal biomass and zooplankton abundance are

178 presented in Fig. 3. The CFR group had a high relative abundance in the periods with high algal biomass, and

179 further during the spring of 2013, when Flavobacterium was dominant within the community. The relative

180 abundance of actinobacteria peaked during and after the peaks of microcrustacean abundance. It was especially

181 striking in the turbid pan in May 2014, when both cladoceran and copepod microcrustaceans had an exceptionally

182 high abundance with more than 104 individuum per liter, and the relative abundance of planktonic actinobacteria

183 (60%) also became surprisingly high. After the ‘microcrustacean peaks’, the abundance of rotifers increased in

184 parallel with decreasing actinobacterial relative abundance.

185 Co-occurrence network analysis

186 To reveal causal relations and correlations within the microbial community of the pans and between the

187 bacterioplankton and environmental factors, co-occurrence networks were created based on time-shifted and local

188 correlations. This resulted in a single interconnected network in the case of both pans (Fig. 4).

189 In the turbid pan, from the 7,260 correlations tested, 385 (LS) and 1,246 (SPCC) were significant. The number of

190 shared edges among these correlations was 237. The resulting network contained 120 nodes. The density of the

191 network was 0.2, and the centralization was 0.152. The following nodes had the highest number of edges:

192 chlorophyll a (41), OTU50 (Actinobacteria) (39), OTU7 (Rhodobaca) (38) and OTU78 (TK10-Chloroflexi) (38).

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 193 The average number of neighbors of the nodes was 23.2. Chlorophyll a (0.045), OTU7 (Rhodobaca) (0.039),

194 OTU1 (acIII-A1) (0.031), OTU34 (Seohaeicola) (0.030), OTU11 (acSTL) (0.026) and OTU26 (Synechococcus)

195 (0.026) had the highest betweenness centrality values.

196 Within the colored pan samples, from the 4,656 correlations tested, 97 (LS) and 859 (SPCC) were significant,

197 and 63 correlations were shared between the two approaches. The network contained 95 nodes, the network

198 density was 0.2, with a centralization of 0.154. The highest significant correlations were detected with nodes

199 OTU151 (Aliidiomarina) (33), OTU69 (Loktanella) (33), POC and salinity (31-31). Node’s average number of

200 neighbors was 18.8. The highest betweenness centrality values were obtained with OTU69 (Loktanella) (0.029),

201 OTU3 (Nitriliruptor) (0.021) and OTU10 (Flavobacterium) (0.016).

202 On the resulting edge-weighted arrangement of the networks, the temperature was separated from other nodes.

203 On the co-occurrence network of the turbid pan, two major group of nodes were separated from each other, with

204 many negative correlations: (1) OTUs presented during higher water levels, mostly from the spring of 2013 (these

205 were, for example, beta- and gammaproteobacteria, freshwater actinobacteria, Blastocatella), and (2) an algae-

206 associated microbial group containing picoeukaryotic algae and cyanobacteria, the previously mentioned CFR-

207 group and Verrucomicrobia. With the second group, OTU1 (acIII-A1) was associated with a number of directed

208 correlations; chloroplast and CFR OTUs effected OTU1 negatively. On the other hand, cladoceran (SPCC: 0.92)

209 and copepod abundance (SPCC: 0.89), and from the more abundant OTUs, OTU17 (Nitriliruptor) (SPCC: 0.91),

210 and OTU45 (Spartobacteria) (SPCC: 0.95) had positive effects. OTU1 had a strong positive correlation with

211 chloroplast OTU5 (Euglena sp.) (SPCC: 0.90), DOC (SPCC: 0.86), salinity (SPCC: 0.76), OTU4 (Ilumatobacter)

212 (SPCC: 0.82) and OTU11 (acSTL) (SPCC: 0.67), and had a positive effect on OTU5 (acTH1) (SPCC: 0.85) and

213 OTU3 (Nitriliruptor) (SPCC: 0.72). OTU11 and OTU81 (both acSTL) had the same relationship with the

214 environmental parameters, while OTU51 (acSTL) had a positive effect on OTU5 (acTH1) and was associated

215 with cladocerans and copepods, indicating that it was abundant prior to the other two acSTL OTUs. Between the

216 two major groups of the turbid pan network, OTU2 (Synechococcus), chloroplast OTU8 (Bacillariophyta) and

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 217 OTU9 (Nitzschia) were situated and had a positive effect on the rotifers. These groups dominated in the water

218 during the summer period. The Nitriliruptor OTU3 also had a positive effect on these groups.

219 The colored pan co-occurrence network contained fewer negative associations, and it was more integrated than

220 the turbid one. Most of the environmental parameters were situated in a central position. The CFR group and

221 certain chloroplast OTUs were associated with each other, while the dominant OTUs during the high water level

222 (mostly flavobacteria and betaproteobacteria) were separated loosely from other groups. OTUs belonging to the

223 same genus were associated with different environmental factors in some cases, for example OTU9

224 (Flavobacterium) was associated with other bacterial groups abundant in the samples collected at high water

225 levels in spring, while OTU71 (Flavobacterium) was connected with algae-associated groups, and OTU10

226 (Flavobacterium) was associated with both groups. In the colored pan, copepods (SPCC: 0.78), chloroplast

227 OTU15 (Phacus sp.) (SPCC 0.82) and chloroplast OTU8 (Bacillariophyta) (SPCC: 0.83) had a positive effect on

228 OTU1 (acIII-A1), which was also connected with chloroplast OTU18 (Euglena sp.) (SPCC: 0.82) and the

229 prokaryotic cell number (SPCC: 0.80). Rotifers in the colored pan had an effect on the phytoplankton, while

230 Cladocera and Copepoda had a strong positive correlation with each other, both in the turbid (SPCC: 0.99) and

231 in the colored pan (SPCC: 0.93).

232 Discussion

233 The environmental variables measured reflected multiple extreme conditions and were similar to those that had

234 previously been reported in soda pans of the Carpathian Basin (Boros et al., 2014, 2017); i.e. the turbid Zab-szék

235 pan had a higher average concentration of ISS (1436 mg l-1) than the colored Sós-ér pan (86 mg l-1), while DOC

236 values where higher in the latter (75 mg l-1 vs. 490 mg l-1, respectively), pH was alkaline (~9-10) and the salinity

237 ranged between 1.5 to 18.9 g l-1 (subsaline to hyposaline, according to Hammer, 1986). Prokaryotic cell numbers

238 were in the same magnitude as had been measured previously in the soda pans of the region studied (106-108 cells

239 ml-1) (Vörös et al., 2008), but higher than in five soda pans from the Seewinkel region (Austria) (106 cells ml-1)

240 (Eiler et al., 2003). Interestingly, the number of cells did not increase linearly with depth, proving the dynamic

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 241 nature of the prokaryotic community and the ecosystem. Previous studies have shown that picoeukaryotic algae

242 have a competitive advantage at low temperature and low light intensity values, and, therefore, winter blooms of

243 these small algae have frequently been observed in soda pans before (Somogyi et al., 2009; Pálffy et al., 2014).

244 Despite the fact that the pans studied represented different ecotypes (of ‘turbid’ and ‘colored’ character), the same

245 prokaryotic groups were present in both pans. Moreover, similar seasonal patterns were observed in the microbial

246 community structure. Certain groups of planktonic actinobacteria were characteristic in both of the pans studied:

247 the acIII-A1, acSTL, acTH1 groups and genera Nitriliruptor and Ilumatobacter. The classes Cytophagia,

248 Flavobacteria and the order Rhodobacterales (CFR group) were also abundant, mostly during algal blooms.

249 Betaproteobacteria, which is a well-known and abundant group in various freshwater ecosystems (Newton et al.,

250 2011), were frequent at higher water levels and lower salinity. Picocyanobacteria (represented by the genus

251 Synechococcus) occurred frequently in the lakes, which also corresponded with literature data and with previous

252 studies on the soda pans within this region (Felföldi et al., 2009, 2011; Somogyi et al., 2009); however, sometimes

253 filamentous groups (e.g., Anabaenopsis) were also detected. Several uncultured/unclassified taxa were abundant

254 in the pans and were important constituents of the community.

255 Compared to other alkaline lakes (e.g., Vavourakis et al., 2016), the presence of Archaea was not significant

256 (13%) within the prokaryotic community.

257 Planktonic actinobacteria were one of the most significant bacterial groups in the pans studied, reaching even

258 89% relative abundance within the bacterial community, which was the highest value compared to any literature

259 data from aquatic habitats. Especially abundant (up to 54%) was the currently poorly characterized acIII-A1

260 lineage, which was first described based on clone sequences from the hypersaline Mono Lake soda lake

261 (California, USA) and the meromictic Lake Sælenvannet estuary (Norway) (Warnecke et al., 2004). Later, Ghai

262 and colleagues (2012) also identified this lineage in coastal lagoons. We suspect that the main reason behind the

263 lack of reports on this group is that they could be only distinguished by the FreshTrain dataset, although other

264 methodological problems (e.g., the widely used 1492R primer fails to amplify some groups of Actinobacteria;

265 Farris and Olson, 2007) could also have contributed to this phenomenon. Using ARB-SILVA, the taxonomic

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 266 assignment for these reads results in an ‘unclassified’ rank within the family Microbacteriaceae. To test our

267 hypothesis, we reanalyzed some previously published datasets from the epilimnion of saline-alkaline lakes (SRA:

268 SRS950620 – Baatar et al., 2016, SRA: SRP044627 –454 FLX Titanium runs, Sinclair et al., 2015, SRA:

269 SRR10674068, Szabó A, Márton Zs, Boros E, Felföldi T, unpublished results) downloaded from the NCBI SRA,

270 applying the same sequence analysis pipeline as for our samples (data not shown). As a result, the acIII-A1 group

271 was detected with high relative abundance in three soda lakes in the Seewinkel region, Austria (Silber Lacke:

272 21%, Unterer Stinker: 6%, Zicklacke: 7%), from Lake Teniz in North-Kazakhstan (11%) and from the surface

273 water of Lake Oigon (5%), which is another saline steppe lake with high pH in Mongolia.

274 Based on our findings, the high grazing pressure of microcrustaceans coincided with the unusually high relative

275 abundance of acIII-A1 and other planktonic actinobacterial groups during the spring/summer transition in both

276 pans. Due to their small cell size (< 0.1 µm3) and the presence of S-layer in their cell wall, planktonic

277 actinobacteria are more resistant to grazing compared to other freshwater bacteria (Tarao et al., 2009; Newton et

278 al., 2011). Pernthaler et al. (2001) proved experimentally that due to the presence of a size-selective predator

279 (Ochromonas nanoflagellate), the relative abundance of the acI planktonic actinobacterial lineage, which are

280 among the most abundant bacteria in temperate lakes (Newton et al., 2011), increased suddenly and even reached

281 60% in the model freshwater community. Hahn et al. (2003) obtained similar results with the Luna actinobacterial

282 clades. In another study, Šimek et al. (2018) compared the population growth of heterotrophic nanoflagellates

283 (HNF) on different freshwater betaproteobacterial and acIII-A1-related Luna2 actinobacterial strains. According

284 to their findings, a rapid HNF population growth occurred on all bacterial strains tested, except for the Luna2

285 actinobacterium. Tarao and colleagues (2009) proved that the destruction of the actinobacterial cell wall’s surface

286 layer results increased predation on Luna2 strains. In certain circumstances, especially following a phytoplankton

287 spring bloom, metazoan grazing could have a greater impact on bacterial diversity than the predation by HNFs

288 (Hahn and Höfle, 2001; Langenheder and Jürgens, 2001). Studies have shown that microcrustaceans and rotifers

289 also like to feed on bacterioplankton, not just on algae (Sanders et al., 1989; Turner and Tester, 1992; Roff et al.,

290 1995; Kirchman, 2002;, Agasild and Nõges, 2005; Berga et al., 2015). Daphnia magna, an abundant

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 291 microcrustacean in these soda pans (Tóth et al., 2014), usually feeds on larger bacterial cells but also consumes

292 HNFs, ciliates and algae (Jürgens, 1994; Berga et al., 2015). During an experiment using aquatic

293 metacommunities (Berga et al., 2015), in the presence of Daphnia magna, the relative abundance of

294 Actinobacteria and Sphingobacteria increased. In our study, during the period investigated, Daphnia was also

295 present in the pans, but the most abundant cladoceran species (especially during late spring and early summer)

296 was Moina brachiata, which is a characteristic species of soda pans of the Carpathian Basin (Tóth et al., 2014).

297 We did not find any data in the literature on the relationship of Moina brachiata and bacterioplankton; however,

298 a closely-related cladoceran, Moina macrocopa, was the most efficient predator of bacteria in an experiment

299 where Vibrio cholerae cells were used (Ramirez et al., 2012). The other abundant microcrustacean species was

300 Arctodiaptomus spinosus, a characteristic copepod in soda lakes (Tóth et al., 2014). It mostly feeds on algae,

301 protists and rotifers; however, in the nauplius stage, copepods could also be bacterivorous (Turner and Tester,

302 1992; Roff et al., 1995). It can be hypothesized that due to the large number of copepods, the abundance of the

303 non-size selective bacterivorous ciliates (if they are present at all in remarkable number in the plankton) also

304 decreases, thus favoring the growth of planktonic actinobacteria. Members of the acI clade, another small cell-

305 sized planktonic actinobacteria, are capable of utilizing N-acetylglucosamine (monomeric unit of chitin and

306 component of the bacterial murein cell-wall) (Beier and Bertilsson, 2011; Eckert et al., 2013; Garcia et al., 2013),

307 which can also contribute to the increase of their relative abundance with zooplankton numbers. In previous works

308 on soda pans of the Seewinkel region (Eiler et al., 2003; Krammer et al., 2008), the authors stated that the observed

309 high abundance of cladocerans (2 × 103 specimen l-1) and protists must be an important regulatory factor on the

310 bacterial population. In conclusion, intensive grazing by zooplankton could favor planktonic actinobacteria by

311 the elimination of their larger, fast-growing bacterial competitors and also by their ability to degrade chitin, which

312 could present in high amounts in the water by the end of the zooplankton ‘bloom’.

313 During or after the actinobacterial relative abundance peaks, the abundance of rotifers also increased in our study;

314 however significant relationship between these groups was not proved statistically. Besides the small cell size,

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 315 increasing the size is also a good strategy for a microbe to avoid predation (Hahn and Höfle, 2001). Probably this

316 also contributes to the summer blooms of filamentous cyanobacteria in these pans (Boros et al., 2013).

317 In addition to actinobacteria, the other abundant taxon was the Cytophaga-Flavobacteria group in the pans studied.

318 In aquatic environments, the CF group usually participates in the degradation of dissolved and particulate organic

319 matter; it is capable of utilizing biopolymers that have a high molecular weight, which are frequently associated

320 with algal blooms (Kirchman, 2002; Newton et al., 2011; Teeling et al., 2012; Williams et al., 2013; Buchan et

321 al., 2014). Flavobacteria were also abundant in the colored pan at higher water levels. These microorganisms are

322 not just capable of utilizing algae-derived compounds, but also macrophyte-derived organic matter, which could

323 originate from the allochthonous terrestrial and autochthonous marshland vegetation of the pan (Boros et al,

324 2020). In a preliminary metagenomic study (Szabó et al., 2017), genes of the TonB receptor system were the most

325 abundant genes within the planktonic community, which highlights the importance of the CF group and algae-

326 derived organic compounds in nutrient cycling. Members of Rhodobacterales (alfVI) were also abundant during

327 the winter-spring algal bloom in the pans. These microbes are related to phytoplankton-derived organic matter

328 but rather utilize algal exudates instead of larger compounds (Teeling et al., 2012; Williams et al., 2013; Buchan

329 et al., 2014). In the co-occurrence network of the turbid pan, the chlorophyll a content had the highest number of

330 connections and betweenness centrality values (the second highest was a Rhodobaca-related OTU, which was

331 also correlated with algal biomass). These correlations were distorted in the colored pan, because of the

332 contribution of macrophyton-derived organic matter to the total carbon budget.

333 During the spring of 2013, the high water level reduced the pH and salinity of the pans. At this stage, the colored

334 pan rather resembled an alkalic ‘freshwater’ marsh, and this was also reflected in the composition of the bacterial

335 community. During this phase, mostly alkalitolerant heterotrophic groups were abundant (Flavobacteriia,

336 Novosphingobium), instead of the aforementioned typical soda lake bacterial groups, which were otherwise

337 present in the pans. The former taxa are capable of utilizing plant-derived matter, and they had high growth rates

338 in natural aquatic habitats. Therefore, they are able to become dominant quickly in the community, decreasing

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 339 the overall bacterial diversity. Thus, besides zooplankton grazing and algal blooms, the water depth also has a

340 remarkable impact on the structure of the planktonic microbial community in the soda pans studied.

341

342 In conclusion, even if the prokaryotic communities of the colored Sós-ér and the turbid Zab-szék pans differed

343 significantly, the same core-taxa were dominant in both pans. These groups are characteristic for other saline-

344 alkaline environments worldwide, especially for soda lakes; however, the importance of acIII-A1 actinobacteria

345 in the bacterioplankton of lakes was revealed for the first time in this study. Seasonal abiotic and biotic effects

346 (predation, algal blooms and water depth) have a great impact on the microbial composition, and our study

347 highlights the dynamic nature of the prokaryotic community in soda lakes and the importance of frequent

348 sampling to reveal ecological processes. Since most soda lakes are situated in remote places of the world, soda

349 pans of the Carpathian Basin are ideal sites to study these environments in detail. Furthermore, these moderately

350 saline, hypertrophic habitats with rapidly changing environmental conditions and a simple food web structure

351 may be regarded as model systems of the current and predicted processes associated with global climate change

352 and the growing human population (introduction of salt water to freshwater, weather changes, a loss of biological

353 diversity and pollution of inland waters). Moreover, further studies are needed to reveal the metabolic potential

354 and geographic distribution of acIII-A1 actinobacteria, the composition of protists and the controlling role of

355 viruses on the planktonic microbial community in soda lakes and pans.

356 Experimental procedures

357 Sample collection

358 A detailed description of the pans studied (the turbid Zab-szék pan and the colored Sós-ér pan; Supplementary

359 Fig. S1) can be found in Boros et al. (2016) and in Szabó et al. (2017). Samples were collected monthly from 17

360 April 2013 to 29 July 2014. The Sós-ér pan was completely desiccated on 24 September, 17 October 2013 and

361 after 18 June 2014, and, therefore sampling on these dates was not possible. Based on our investigation on spatial

362 heterogeneity, using three replicate samples from these sites, there were no remarkable differences in the bacterial 16

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 363 community composition (Bedics et al., 2019), presumably due to the constant mixture of the shallow water by

364 the wind (Boros et al., 2017). Nevertheless, to represent the total bacterial community of the pans, composite

365 samples were taken from at least ten different points each time in the vicinity of the deepest parts of the open

366 water bodies. To avoid diel differences in community composition and environmental parameters as referred to

367 by Kirschner and colleagues (2002), samplings were performed approximately the same time on every occasion.

368 Further information about sample collection dates is given in Supplementary Table S1. The determination of

369 physicochemical parameters, prokaryotic cell count, composition and biomass of algae was performed as

370 described in Mentes et al. (2018). Salinity values were calculated from electric conductivity based on the equation

371 published by Boros et al. (2014). To determine mesozooplankton abundance, a 10 l water sample was randomly

372 collected from the open water of each pan and filtered through a 30 µm mesh plankton net, then preserved in 70%

373 ethanol (zooplankton was not enumerated in the case of samples collected on 18 June 2013 and on 9 Dec 2013

374 due to technical problems).

375 Community DNA isolation, amplification, sequencing

376 DNA extraction, 16S rRNA gene amplification and amplicon sequencing were performed as described in Szabó

377 et al. (2017), while qPCR measurements to determine the ratio of archaea to bacteria were carried out as described

378 in Korponai et al. (2019).

379 Bioinformatic and statistical analyses

380 Sequence processing, taxonomic assignments and OTU-picking (defined at a 97% similarity level) were carried

381 out using mothur v1.35 (Schloss et al., 2009), as described in Szabó et al. (2017) (scripts are also available in the

382 Supplementary Material of this paper). For abundant unassigned OTUs, the FreshTrain reference dataset (18 Aug

383 2016 release, Newton et al., 2011) was used as a taxonomic reference. Cyanobacterial and chloroplast sequences

384 were also analyzed separately from bacterial reads; the OTU’s taxonomic identification was carried out based on

385 phylogenetic analysis with 16S rRNA gene sequences obtained from GenBank and from reference strains (using

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 386 the methods described in Felföldi et al. (2011) and Borsodi et al. (2017); see additional details in Supplementary

387 Table S2).

388 Subsampling the reads to the smallest data set (n = 1896), calculation of richness (sobs - number of OTUs at a

389 97% similarity threshold, Chao1 - Chao 1 index and ACE - Abundance-based Coverage Estimator), and diversity

390 estimators (Simpson’s inverse and Shannon indices), along with the Bray-Curtis similarity index, were also

391 performed using mothur. For the determination of significant differences in community composition between

392 pans and among seasons, a two-way PERMANOVA test was applied based on Bray-Curtis similarity with 9999

393 permutations using the PAST3 program (Hammer et al., 2001). PAST3 was also used to perform a SIMPER test,

394 which determined the OTUs responsible for the dissimilarity among all of the samples. Non-metric

395 multidimensional scaling (NMDS) ordinations and ‘envfit’ analyses were carried out with R (R Core Team, 2017)

396 using the vegan (Oksanen et al., 2017) and ggplot2 (Wickham 2009) packages. All variables were log10-

397 transformed before the ‘envfit’ analysis to reduce the effect of outliers and to obtain normal distribution of the

398 data. Shapiro-Wilk tests were used to check normality.

399 Co-occurrence networks were created using the eLSA program (Xia et al., 2011, 2013) to reveal local and time-

400 shifted correlations among abundant (with at least 1% relative abundance in one sample) bacterial and chloroplast

401 OTUs and environmental parameters within each pan. Data were normalized using the percentileZ function, and

402 p-values were estimated based on 1000 permutations. Strongly significant (q < 0.01, p < 0.01) local similarity

403 score (LS) and delay-shifted Pearson's correlation coefficient (SPCC) parameters were used as edges of the

404 networks. Cytoscape v3.4.0 was used for network visualization and analysis (Shannon et al., 2003). To indicate

405 relationships between nodes, networks were generated using the edge-weighted spring-embedded layout.

406 Topological metrics were calculated using the network analysis plug-in (Assenov et al., 2008).

408 Raw sequence data were submitted to NCBI under BioProject ID PRJNA272672.

409 Acknowledgements

410 The authors are thankful to Balázs Németh and Tamás Sápi for their assistance during sampling, to Csaba Ferenc

411 Vad, Vera Senánszky, Adrienn Tóth and Katalin Zsuga for zooplankton data, to Zsuzsanna Márton and Anikó

412 Mentes for their help in the qPCR measurements and the sequencing of algal strains, respectively, and further, to

413 Susann Pihl for proofreading the manuscript.

414 Funding 415 This work was financially supported by the National Research, Development and Innovation Office (grant no.

416 K116275 and PD105407). Purchase of equipment was financed by the National Development Agency (grant no.

417 KMOP-4.2.1/B-10-2011-0002 and TÁMOP-4.2.2/B-10/1-2010-0030).

418 Contributions 419

420 A.Sz. and T.F. wrote the paper. B.S. and E.B. carried out the sampling and determined physicochemical 421 parameters. B.S. and L.V. determined algal cell counts and biomass. N.Sz-T. determined prokaryotic cell counts. 422 Zs.H. supervised the determination of zooplankton abundance and identification of taxa. A.Sz. and K.K. 423 performed DNA isolation, amplification and sequencing. A.Sz. carried out qPCR measurements, bioinformatic 424 analyses and the statistical analyses with B.V. T.F and K.M. advised on the interpretation of the results. All 425 authors read, commented and validated the final version of the manuscript.

426 Additional Information

427 Competing interests 428 The authors declare no competing interests.

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588 Fig. 1. Seasonal changes in the bacterial OTU composition of the turbid and colored pan between April 2013 and

589 July 2014. ‘Other’ represented taxa has less than 5% relative abundance. Letters on the x-axis are the

590 abbreviations for months. Abbreviation: uc_Bacteria (unclassified Bacteria).

591 Fig. 2. NMDS ordination of soda pan samples collected between April 2013 and July 2014 based on the Bray-

592 Curtis distance of the bacterial OTUs (stress: 0.15). Based on SIMPER analysis, OTUs responsible for 40%

593 dissimilarity among samples are shown in gray. Significantly fitted (p < 0.05) environmental variables are shown

594 with gray vectors. Abbreviations: Actino (unclassified Actinobacteria), Chl-a (chlorophyll a), CyP

595 (cyanobacterial plankton), DOC (dissolved organic carbon), EuAPP (eukaryotic autrotrophic picoplankton, i.e.

596 pico-sized green algae), Euglena sp. (chlp5), ISS (inorganic suspended solids), POC (particulate organic carbon),

597 Prok. cell number (prokaryotic cell number); for sample codes, see Supplementary Table S1.

598 Fig. 3. Relative abundance changes of Actinobacteria and the Cytophaga-Flavobacteria-Rhodobacterales (CFR)

599 group, comparing to the biomass of planktonic algae and zooplankton abundance in the turbid and colored pan

600 between April 2013 and July 2014. For visualization, algal biomass and zooplankton abundance values were

601 transformed to a log10-scale. Letters on the x-axis are the abbreviations for months. Abbreviations: CyP

602 (cyanobacterial plankton), EuAPP (eukaryotic autrotrophic picoplankton).

603 Fig. 4. Co-occurrence networks of bacterial OTUs and environmental variables in the turbid and colored pans

604 based on significant (p < 0.01, q < 0.01) time-shifted (blue edges) and local (red edges) correlations. Directed

605 effects are shown with arrows, continuous lines represent positive correlations, and dashed lines depict negative

606 correlations. Environmental parameters are shown in gray, identified algae chloroplast OTUs are shown with

607 green squares. Names of the other hubs represent the closest assigned taxa to bacterial OTUs, and the size of the

608 nodes correlates with the absolute abundance of the OTU in the sample set. The color of the nodes represents

609 class-level phylogenetic relationships. Abbreviations: Actino (Actinobacteria), Alii (Aliidiomarina), Algori

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 610 (Algoriphagus), Alpini (Alpinimonas), Aqui (Aquiflexum), Belli (Belliella), Blasto (Blastopirellula), Cece

611 (Cecembia), Chl-a (chlorophyll a), Coma (Comamonadaceae), Cryo (Cryomorphaceae), Cyano (Cyanobacteria),

612 CyP (cyanobacterial plankton), Cyclo (Cyclobacteriaceae), DOC (dissolved organic carbon), Ecto

613 (Ectothiorhodospira), EuAPP (eukaryotic autrotrophic picoplankton), Flavo (Flavobacterium), Fibro

614 (Fibrobacteraceae), Fluvi (Fluviicola), Gamma (TX1A55 Acidithiobacillales), Gamma2 (K189A clade

615 Gammaproteobacteria), Halo (Haloferula), Hydro (Hydrogenophaga), Idio (Idiomarina), Illumato

616 (Ilumatobacter), Indi (Indibacter), ISS (inorganic suspended solids), Limno (Limnohabitans), Lokta (Loktanella),

617 Luteoli (Luteolibacter), Nitrili (Nitriliruptor), Novo (Novosphingobium), Oligo (Oligoflexaceae), Para

618 (Paracoccus), Pisci (Piscirickettsiaceae), POC (particulate organic carbon), Porphyro (Porphyrobacter), Prca

619 (Proteocatella), Prok. cell number (prokaryotic cell number), Pseudo (Pseudomonas), Pseudosp

620 (Pseudospirillum), Roseim (Roseimaritima), Roseo (Roseococcus), Rhodo (Rhodobaca), Seo (Seohaeicola),

621 Sparto (Spartobacteria), Synecho (Synechococcus), Verruco (Verrucomicrobia).

623 624

626 627

628 Figure 3

629

630

631 Figure 4

632 633

634

turbid colored (Zab-szék) (Sós-ér)

635 636 Supplementary Fig. S1. View of sampling sites and the color of their water.

637

638 639 Supplementary Fig. S2. Phylogenetic position of cyanobacterial 16S rRNA gene amplicon reads from the soda pan samples 640 collected between April 2013 and July 2014.

641 The tree was constructed using the maximum likelihood method and is based on 365 nucleotide positions. Each OTU is 642 represented with the most abundant read. Read numbers are given in brackets (only OTUs having at least 20 reads in the 643 whole dataset are shown). Bootstrap values higher than 70 are shown at the nodes. OTUs detected in the colored and turbid 644 pan are marked with brown and gray squares, respectively. mpc – marine picophytoplankton clade.

645

646

647 648 Supplementary Fig. S3. Phylogenetic position of chloroplast 16S rRNA gene amplicon reads from the soda pan samples 649 collected between April 2013 and July 2014.

650 The tree was constructed using the maximum likelihood method and is based on 439 nucleotide positions. Each OTU is 651 represented with the most abundant read. Read numbers are given in brackets (only OTUs having at least 20 reads in the 652 whole dataset are shown). Bootstrap values higher than 70 are shown at the nodes. OTUs detected in the colored and turbid 653 pan are marked with brown and gray squares, respectively.

654

655

656 Supplementary Fig. S4. Relative abundance of Archaea and Bacteria in the colored pan (Sós-ér) and turbid pan (Zab-szék 657 pan) between April 2013 and July 2014. Letters on the x-axis are the abbreviations for months. 658

659 660 661

662

663 Supplementary Fig. S5. Changes in OTU richness and diversity in the studied pans between April 2013 and July 2014. 664 Letters on the x-axis are the abbreviations for months. Abbreviations: H (Shannon diversity index), 1/λ (inverse Simpson 665 diversity index). 666

667

668 Supplementary Fig. S6. Monthly changes in Bray-Curtis similarity within bacterial communities of the pans studied 669

bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made Supplementary Table S1. Physicochemicalavailable characteristics under aCC-BY-NC-ND and selected 4.0 International biological license variables. of the water samples studied

Prokaryotic CyP2 EuAPP3 Nanoplanktonic Depth Temperature Conductivity Chlorophyll a Salinity DOC POC1 ISS1 Rotatoria Cladocera Copepoda cell number - Sample code Sampling date pH -1 -1 -1 -1 -1 -1 biomass biomass algal biomass µg l -1 -1 -1 cm °C µS cm µg l g l mg l mg l mg l -1 individuum l individuum l individuum l cells ml µg l-1 µg l-1 1 SO02 17 April 2013 50 17 8.3 1880 1.5 1.5 84 1 3 2,39E+07 0 0 14 52 95 99 SO03 30 May 2013 45 17 8.5 2980 3.6 2.4 144 4 24 1,42E+07 0 0 152 1352 80 133 SO04 18 June 2013 35 30 8.7 3800 0.5 3.0 174 0 6 1,76E+07 0 0 4 n.d. n.d. n.d. SO05 24 July 2013 18 25 9.1 7850 1.8 6.3 350 5 7 2,27E+08 0 0 35 837 339 10 SO06 16 August 2013 10 27 9.6 23600 463.0 18.9 1164 59 232 1,03E+08 3515 64 32150 1603 0 1 SO09 19 November 2013 4 8 10.0 11400 348.9 9.1 626 46 173 7,24E+07 0 3077 5960 0 0 5 SO10 09 December 2013 9 4 9.9 7790 340.0 6.2 533 13 92 3,14E+07 70 2681 2918 n.d. n.d. n.d. SO11 10 January 2014 9 5 9.9 9500 379.0 7.6 595 19 221 4,67E+07 0 2376 11670 0 0 12 SO12 26 February 2014 18 7 9.1 4500 148.5 3.6 276 18 88 3,13E+07 0 494 8160 0 2 2 SO13 26 March 2014 13 11 9.2 6800 64.9 5.4 449 10 19 4,74E+08 0 8 11840 8 234 272 SO14 23 April 2014 8 21 9.3 10700 49.4 8.6 682 15 139 n.d. 0 114 75 4 46 68 SO15 22 May 2014 13 25 9.3 7700 2.2 6.2 466 10 0 n.d. 0 3 0 209 93 14 SO16 18 June 2014 7 24 9.6 15000 92.0 12.0 830 25 115 1,30,E+08 9 186 2710 451 1 1 ZA02 17 April 2013 45 24 9.1 2430 6.8 1.9 31 6 1499 1,81,E+07 0 159 0 0 7 50 ZA03 30 May 2013 31 17 9.3 3020 11.7 2.4 33 5 791 3,87,E+07 0 207 0 283 8 152 ZA04 18 June 2013 32 26 9.2 3300 1.7 2.6 32 8 649 2,11,E+07 8 152 0 n.d. n.d. n.d. ZA05 24 July 2013 20 31 9.5 5500 3.8 4.4 50 4 372 2,96,E+07 16 159 0 115 149 256 ZA06 16 August 2013 13 30 9.8 9410 44.1 7.5 75 9 447 1,02,E+08 4216 1594 39 2 61 393 ZA07 24 September 2013 13 16 10.0 12300 153.2 9.8 92 36 2228 1,60,E+08 3516 14934 0 5148 150 2394 ZA08 17 October 2013 6 17 10.1 8000 259.8 6.4 60 41 2031 6,88,E+07 542 14455 0 2304 296 361 ZA09 19 November 2013 4 11 10.2 9400 430.2 7.5 74 41 1679 1,08,E+08 1053 126661 0 882 324 666 ZA10 09 December 2013 6 4 10.2 6400 455.7 5.1 59 37 1115 6,57,E+07 549 114084 40 n.d. n.d. n.d. ZA11 10 January 2014 4 6 10.2 8000 1043.7 6.4 64 74 456 1,70,E+08 206 183349 0 0 20 742 ZA12 26 February 2014 12 10 9.6 4800 1499.4 3.8 41 86 4438 5,34,E+07 1511 313554 0 0 21 1563 ZA13 26 March 2014 7 14 9.7 6400 2555.5 5.1 53 127 1809 3,84,E+08 494 180479 3450 3 96 988 ZA14 23 April 2014 3 25 9.7 9000 822.0 7.2 74 147 1527 n.d. 69 129407 0 8 428 710 ZA15 22 May 2014 3 28 9.4 8300 59.6 6.6 97 55 3215 1,92E+08 824 20726 0 43 14160 17760 ZA16 18 June 2014 2 28 9.9 21200 199.0 17.0 217 22 133 9,07E+07 3 404 0 99 0 1 ZA17 29 July 2014 7 31 9.7 12600 6.8 10.1 142 8 502 6,20E+07 144 62 0 26 397 419

n.d. - no data 1POC = TOC - DOC; ISS = TSS - POC 2CyP - cyanobacterial plankton 3EuAPP - eukaryotic autrotrophic picoplankton (= pico-sized eukaryotic algae) bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made Supplementary Table S2. Referenceavailable underchloroplast aCC-BY-NC-ND 16S rRNA 4.0 International gene sequences license. generated in this study Method applied for 16S Taxonomic 16S rRNA gene Primer Strain code Type strain Taxonomic identity Isolation source rRNA gene sequence Applied primers reference GenBank Acc. No.* reference determination ACT 0622 no Chloroparva sp. Böddi-szék soda pan, Hungary 1, 2 MK397007 cloning and sequencing OXY107F-OXY1313R 5 ACT 0605 no Choricystis sp. Böddi-szék soda pan, Hungary 3 MK397008 direct sequencing OXY107F-OXY1313R 5 ACT 0607 no Choricystis sp. Böddi-szék soda pan, Hungary 3 MK397009 direct sequencing OXY107F-OXY1313R 5 ACT 1006 no Mychonastes sp. Ruster Poschen soda pan (Seewinkel region), Austria 4 MK397011 direct sequencing OXY107F-OXY1313R 5 ACT 1015 no Nannochloris bacillaris Lake Balaton, Hungary 4 MK397010 direct sequencing CYA106F-CYA781R 6 SAG 55.87 yes Pseudochloris wilhelmii seawater aquarium, Germany 2 MK397012 direct sequencing OXY107F-OXY1313R 5 *sequences with bold letters were determined in this study

References: (1) Somogyi B, Felföldi T, Solymosi K, Makk J, Homonnay ZG, Horváth G, Turcsi E, Böddi B, Márialigeti K, Vörös L. 2011. Chloroparva pannonica gen. et sp. nov. Trebouxiophyceae, Chlorophyta) – a new picoplanktonic green alga from a turbid, shallow soda pan. Phycologia 50: 1-10. (2) Somogyi, B., Felföldi, T., Solymosi, K., Flieger, K., Márialigeti, K., Böddi, B., Vörös, L. 2013. One step closer to eliminating nomenclatural problems of minute coccoid green algae: Pseudochloris wilhelmii gen. et sp. nov. (Trebouxiophyceae, Chlorophyta). European Journal of Phycology 48: 427-436. (3) Boglárka Somogyi and Tamás Felföldi, unpublished results (4) Somogyi B, Felföldi T, V.-Balogh K, Boros E, Pálffy K, Vörös L. 2016. The role and composition of winter picoeukaryotic assemblages in shallow Central European great lakes. Journal of Great Lakes Research 42: (5) Fuller NJ, Marie D, Partensky F, Vaulot D, Post AF, Scanlan DJ. 2003. Clade-specific 16S ribosomal DNA oligonucleotides reveal the predominance of a single marine Synechococcus clade throughout a stratified water column in the Red Sea. Applied and Environmental Microbiology 69: 2430-2443. (6) Nübel U, Garcia-Pichel F, Muyzer G. 1997. PCR primers to amplify 16S rRNA genes from Cyanobacteria. Applied and Environmental Microbiology 63: 3327-3332. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made Supplementary Table S3. Eukaryoticavailable under nanoplanktonic aCC-BY-NC-ND algae4.0 International detected license in the. pans and their estimated biomass turbid pan (Zab-szék) Sampling date 17 April 2013 30 May 2013 18 June 2013 24 July 2013 16 August 2013 24 September 2013 17 October 2013 19 November 2013 Cryptomonas sp. (µg l-1) 0 0 0 0 0 0 0 0 Chlamydomonas sp. (µg l-1) 0 0 0 0 27 0 0 0 Nitzschia palea (µg l-1) 0 0 0 0 12 0 0 0 Sum of the biomass of eukaryotic nanoplanktonic algae (µg l-1) 0 0 0 0 39 0 0 0 colored pan (Sós-ér) Sampling date 17 April 2013 30 May 2013 18 June 2013 24 July 2013 16 August 2013 24 September 2013 17 October 2013 19 November 2013 Euglena sp. (µg l-1) 0 0 0 0 4000 n.a. n.a. 520 Phacus sp. (µg l-1) 0 0 0 0 0 n.a. n.a. 0 Cryptomonas sp. (µg l-1) 6 0 0 0 0 n.a. n.a. 0 Rhodomonas sp. (µg l-1) 3 0 4 0 0 n.a. n.a. 0 Tribonema sp. (µg l-1) 0 150 0 0 0 n.a. n.a. 0 Carteria sp. (µg l-1) 0 0 0 0 0 n.a. n.a. 2040 Chlamydomonas sp. (µg l-1) 5 0 0 0 28150 n.a. n.a. 3400 Nitzschia sp. (µg l-1) 0 2 0 10 0 n.a. n.a. 0 Navicula sp. (µg l-1) 0 0 0 0 0 n.a. n.a. 0 Cocconeis sp. (µg l-1) 0 0 0 12 0 n.a. n.a. 0 Cymbella sp. (µg l-1) 0 0 0 13 0 n.a. n.a. 0 Sum of the biomass of eukaryotic nanoplanktonic algae (µg l-1) 14 152 4 35 32150 n.a. n.a. 5960 n.a. - not applicable bioRxiv preprint doi: https://doi.org/10.1101/2020.06.04.133827; this version posted June 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

09 December 2013 10 January 2014 26 February 2014 26 March 2014 23 April 2014 22 May 2014 18 June 2014 29 July 2014 0 0 0 3450 0 0 0 0 0 0 0 0 0 0 0 0 40 0 0 0 0 0 0 0 40 0 0 3450 0 0 0 0

09 December 2013 10 January 2014 26 February 2014 26 March 2014 23 April 2014 22 May 2014 18 June 2014 29 July 2014 2340 8250 3960 9600 0 0 1200 n.a. 0 0 0 2240 0 0 500 n.a. 0 0 0 0 0 0 0 n.a. 0 0 0 0 0 0 0 n.a. 0 0 0 0 0 0 0 n.a. 600 0 0 0 0 0 0 n.a. 40 3420 4200 0 75 0 30 n.a. 8 0 0 0 0 0 0 n.a. 0 0 0 0 0 0 980 n.a. 0 0 0 0 0 0 0 n.a. 0 0 0 0 0 0 0 n.a. 2988 11670 8160 11840 75 0 2710 n.a.