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    Exploring the upper pH limits of nitrite oxidation: diversity, ecophysiology, and adaptive traits of haloalkalitolerant Nitrospira

    Community composition of Nitrospira in the saline-alkaline lakes
    Members of the genus Nitrospira are the most diverse and widespread known NOB. However, reports of Nitrospira occurrence in alkaline habitats are scarce [23, 30], and a systematic assessment of their presence and activity in such extreme environments is missing. In this study, we discovered and investigated unusually alkalitolerant Nitrospira in saline-alkaline lakes of the national park “Neusiedler See-Seewinkel”, Burgenland, Austria using targeted amplicon profiling of the 16S rRNA gene and nxrB, of which the latter encodes the beta-subunit of nitrite oxidoreductase (the key enzyme for nitrite oxidation). In sediment samples from nine lakes, we detected phylogenetically diverse Nitrospira phylotypes which were affiliated with Nitrospira lineages I, II and IV (Fig. 2) [1].
    Fig. 2: Phylogenetic maximum likelihood analysis based on the 16S rRNA gene sequences of selected representatives from the genus Nitrospira and of the Nitrospira members detected in sediments from nine saline-alkaline lakes.

    Sequences obtained in this study are printed in bold. “Ca. N. alkalitolerans” is the Nitrospira species cultured and further analyzed in this study. The tree was constructed using full length sequences and a 50% conservation filter resulting in 1310 valid alignment positions. Shorter sequences from this study, generated through amplicon and Sanger sequencing were added to the tree using the Evolutionary Placement Algorithm (EPA) without changing the overall tree topology. Numbers in brackets behind these sequences firstly denote the likelihood score of the exact placement and secondly the cumulative likelihood score of the placement within the cluster. Filled, gray, and open circles denote branches with ≥90%, ≥70% and ≥50% bootstrap support, respectively. Leptospirillum ferrooxidans (AJ237903), Ca. Magnetobacterium bavaricum (FP929063), Thermodesulfovibrio yellowstonii DSM 11347 (CP001147), and Ca. Methylomirabilis oxyfera (FP565575) were used as outgroup. The scale bar indicates 6% estimated sequence divergence.

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    The genomes of sequenced Nitrospira possess one to six paralogous copies of nxrB, and the nxrB copy numbers per genome remain unknown for the majority of uncultured Nitrospira [42]. This large variability likely affects relative abundance estimations of Nitrospira OTUs based on nxrB amplicon data. In contrast, all sequenced Nitrospira genomes contain only one ribosomal RNA (rrn) operon. Therefore, our further assessment of the Nitrospira community structures relies on the 16S rRNA gene amplicon datasets.
    The estimated alpha-diversity of Nitrospira 16S rRNA gene phylotypes was compared across the nine examined lakes (Fig. S1). The inverse Simpson’s index of the Nitrospira communities was negatively correlated with pH and the nitrite concentration (p = 0.00004, Tau-b = −0.53 for pH and p = 0.03, Tau-b = −0.36 for nitrite). The decrease of Nitrospira diversity with increasing pH may indicate that only specific Nitrospira phylotypes tolerate highly alkaline conditions.
    The Nitrospira communities clustered into two distinct major groups (Fig. 3). Group 1 mainly comprised the communities from those lakes, which are located closely to the shore of the much larger Lake Neusiedl, whereas group 2 contained the communities from the remaining lakes that are farther away from Lake Neusiedl (Fig. 1). The average pH and salinity in the water of lakes from the group 1 cluster were 9.97 ± 0.24. and 6.1 ± 4.1 g/l, respectively. These values were significantly higher (Welch’s t-test; p = 0.00001 for pH and p = 0.017 for salinity) than the mean pH of 9.37 ± 0.26 and salinity of 2.74 ± 0.88 g/l in the group 2 lakes (Table 1). None of the other determined lake properties at time of sampling differed significantly between the two groups. The Nitrospira phylotypes with the highest relative abundance in the sediments from group 1 were OTU1 and OTU20, both affiliated with Nitrospira lineage IV, whereas these OTUs were nearly absent from the sediments of the lakes in group 2 (Fig. 3). In contrast, the predominant phylotypes in the group 2 lake sediments were affiliated with Nitrospira lineage II (Fig. 3). Consistent with these results, a principal coordinate analysis showed a clear separation of the Nitrospira communities with the same two groups separated on the first axis of the ordination (Fig. S2). These results indicate a strong influence of pH and salinity on the composition of the Nitrospira communities. Members of Nitrospira lineage IV are adapted to saline conditions and are commonly found in marine ecosystems [15, 43,44,45,46,47]. However, to date no Nitrospira species have been described to tolerate elevated pH conditions. Our results show that a substantial diversity of Nitrospira is able to colonize alkaline environments. The data also indicate a niche differentiation between lineages IV and II in saline-alkaline lakes, which likely includes a higher tolerance of the detected lineage IV organisms toward an elevated pH and salinity.
    Fig. 3: Normalized abundances of Nitrospira 16S rRNA gene phylotypes detected in triplicate sediment samples from nine saline-alkaline lakes.

    Nitrospira communities are grouped by hierarchical clustering on the y-axis, and OTUs are grouped by phylogenetic affiliation on the x-axis. Lake names are abbreviated as in  Fig. 1. Lin. IV, Nitrospira lineage IV ; Lin. II, Nitrospira lineage II; I, Nitrospira lineage I; Freq normalized frequency counts; Grp.1, group 1 lakes; Grp.2, group 2 lakes (see also Fig. 1).

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    Metagenome sequencing and physiology of alkalitolerant Nitrospira enrichments
    Following the inoculation of mineral nitrite medium flasks with sediment and/or water samples from four saline-alkaline lakes (LL, WW, KS and OEW; abbreviations see Table 1), we initially obtained 17 enrichment cultures that oxidized nitrite to nitrate. Based on FISH analyses with Nitrospira-specific 16S rRNA gene-targeted probes and Sanger sequencing of cloned 16S rRNA genes, several of these preliminary enrichment cultures contained co-existing phylotypes from Nitrospira lineages I, II, and IV as well as from the genus Nitrobacter (data not shown). Members of the genera Nitrotoga and Nitrospina were screened for by FISH or PCR, but were not detected.
    We used three of the enrichments which contained only Nitrospira NOB and originated from different lakes (referred to as EN_A from lake OEW, EN_B from lake LL, and EN_C from lake WW comprising ~35% Nitrospira in relation to the total microbial community based on FISH analysis) to determine the pH range for activity of the enriched Nitrospira members. Enrichment cultures EN_A and EN_C contained phylotypes from Nitrospira lineages I and II, while EN_B contained phylotypes from lineages I, II, and IV as determined by 16 rRNA gene amplicon cloning and Sanger sequencing (Fig. 2). The continued presence of these Nitrospira phylotypes for more than 2 years, despite several serial dilution transfers, demonstrates their tolerance to the alkaline incubation conditions and suggests that they were native to the saline-alkaline environment which they were sampled from. Hence, we conclude that at least the highly similar uncultured Nitrospira OTUs detected by amplicon sequencing (Fig. 2) were most likely also native inhabitants of the saline-alkaline lakes. Aliquots of each enrichment culture were incubated with nitrite as the sole added energy source for six weeks at pH 7.61–7.86 and 9–9.04, respectively. During this period, pH had no significant effect on nitrite utilization (Pearson correlation coefficient ≥0.96 with, p ≤ 0.01 for all three enrichments) and nitrate production (Pearson correlation coefficient ≥0.98 with, p ≤ 0.01 for all three enrichments) over time for any of the three enrichments (Fig. S3). Subsequently, the enrichment culture aliquots that had been incubated at pH 9–9.04 were sequentially incubated at pH 9.97–10, 10.24–10.52, and 10.72–11.02 for eight to nine days at each pH (Table S1). For all three enrichments, the observed nitrate production tended to be slower at pH 9.97–10 and 10.24–10.52 than at pH 9–9.04 (Fig. S3 and S4). At pH 10.72–11.02, no nitrite consumption was detected (Fig. S4). The trends observed at pH 10.24–10.52 and above were in stark contrast to the persistently high nitrite-oxidizing activity of the enrichments when routinely cultured at pH 9–10 for several weeks. While it was not possible to determine based on our data whether all Nitrospira phylotypes present in the three enrichments responded equally to the tested pH conditions, we can conclude that the activity of at least some Nitrospira remained unaffected up to pH 9 and had an upper limit between pH 10.5 and 10.7. This is remarkable, because previously enriched or isolated Nitrospira strains were not cultivated above pH 8.0 except for two Nitrospira cultures from geothermal springs, which showed activity up to pH 8.8 [4] or pH 9.0 [7]. To our knowledge, this is the first report of nitrite oxidation by Nitrospira at pH values above 9 and as high as 10.5.
    Further analyses focused on one additional enrichment, which had been inoculated with sediment from lake Krautingsee, belonging to the group 2 of the analyzed lakes (KS, Table 1). In contrast to the other enrichment cultures, this enrichment contained only lineage IV Nitrospira based on FISH analysis (Fig. 4a). Nitrospira-specific, 16S rRNA gene and nxrB-targeted PCR and phylogeny detected one phylotype from Nitrospira lineage IV that was related to other phylotypes detected from the lakes, specifically OTU 5 and EN_B_1 (16S rRNA gene, 100% and 98% nucleotide sequence identity, respectively; Fig. 2) and OTU 2 (nxrB, 98.5% nucleotide sequence identity; Fig. S5). Both these OTU phylotypes occurred in most of the analyzed lakes (Fig. 3). Thus, the closely related enrichment from lake KS may represent Nitrospira that could adapt to a relatively broad range of conditions, while some of the other OTUs were more abundant in specific lakes only (Fig. 3). The enriched Nitrospira reached a high relative abundance in the enrichment culture of ~60% of all bacteria based on metagenomic read abundance (see below) and observation by FISH.
    Fig. 4: Visualization and metagenomic analysis of the “Ca. N. alkalitolerans” enrichment.

    a FISH image showing dense cell clusters of “Ca. N. alkalitolerans” in the enrichment culture. The “Ca. N. alkalitolerans” cells appear in red (labeled by probe Ntspa1151 which has 1 mismatch at the 3’ end to the 16S rRNA gene sequence of “Ca. N. alkalitolerans”; the absence of lineage II Nitrospira in the enrichment culture was confirmed by the application of the competitor oligonucleotides c1Ntspa1151 and c2Ntspa1151 as indicated in the Supplementary text). Other organisms were stained by DAPI and are shown in light gray. Scale bar, 25 µm. b Phylogenetic affiliation of the metagenome scaffolds from the “Ca. N. alkalitolerans” enrichment, clustered based on sequence coverage and the GC content of DNA. Closed circles represent scaffolds, scaled by the square root of their length. Clusters of similarly colored circles represent potential genome bins.

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    High-throughput metagenome sequencing, scaffold assembly, and binning revealed that the enrichment contained three Nitrospira strains that could be separated into three genome bins based on sequence coverage data (Table S2, Fig. S6). No other NOB were identified in the metagenome, and the three Nitrospira bins represented the most abundant organisms in the enrichment culture (Fig. 4b). Since the genome-wide average nucleotide identity (gANI) values were above the current species threshold of 95% [48] (Table S2), the three bins likely represented very closely related strains of the same Nitrospira lineage IV species with unique genetic components. From the predominant (based on coverage data) Nitrospira sequence bin, an almost complete metagenome-assembled genome (MAG) was reconstructed, which met the criteria for a “high-quality draft” genome [49] (Table S2), and used for comparative genomic analysis. Genome-wide, pairwise comparison of the gANI and average amino acid (gAAI) identity between this MAG and Nitrospira marina as the only other genome-sequenced and cultured Nitrospira lineage IV representative resulted in values of 80.1 and 77.3, respectively. The 16S rRNA gene, which had been retrieved from the MAG, was 97.90% identical to the 16S rRNA gene of N. marina, 97.87% identical to “N. strain Ecomares 2.1”, 94.92% to “Ca. N. salsa”, and 94.51% to “Nitrospira strain Aa01”, which are the other cultured members of Nitrospira lineage IV [15, 43, 46, 47]. These values are below the current species threshold of 98.7–99% for 16S rRNA genes [50]. Based on the low gANI and 16S rRNA gene sequence identities to described Nitrospira species, and additionally considering the distinct haloalkalitolerant phenotype (see also below), we conclude that the enriched Nitrospira represent a new species and propose “Ca. Nitrospira alkalitolerans” as the tentative name.
    The enrichment culture was maintained at a pH of 9–10 and a salt concentration of 2 g/l, resembling the natural conditions in the saline-alkaline lakes based on available data from 5 years. “Ca. N. alkalitolerans” grew in dense flocks (Fig. 4a), thereby possibly relieving the pH stress [51]. Its nitrite-oxidizing activity was not affected when the pH in the cultivation medium decreased below 8. However, no nitrite oxidation was observed when the enrichment culture was transferred into medium with 4× to 8× higher salt concentrations, the latter resembling marine conditions. Thus, “Ca. N. alkalitolerans” is best described as a facultatively haloalkalitolerant organism that oxidizes nitrite as an energy source over a wide range of pH and under hyposaline conditions. This phenotype is certainly advantageous in the investigated saline-alkaline lakes, as these lakes are prone to evaporation in summer, which causes a temporarily elevated salinity and alkalinity in the remaining water body and the sediment [35].
    The enrichment culture of “Ca. N. alkalitolerans” oxidized nitrite over a broad range of initial nitrite concentrations tested, although an extended lag phase of 10–15 days occurred at the higher concentrations of 0.7 and 1 mM nitrite (Fig. S7). Similarly, a lag phase at elevated nitrite concentrations was also observed for the Nitrospira lineage II member Nitrospira lenta [52]. A preference for low nitrite levels is consistent with the presumed ecological role of nitrite-oxidizing Nitrospira as slow-growing K-strategists, which are adapted to low nitrite concentrations [50, 52, 53].
    Genomic adaptations to the saline-alkaline environment
    As described below, comparative genomic analysis of “Ca. N. alkalitolerans” revealed several features that distinguish this organism from other known NOB and likely form the basis of its tolerance toward elevated alkalinity and salinity (Fig. 5).
    Fig. 5: Cell metabolic cartoon constructed from the genome annotation of “Ca. N. alkalitolerans”.

    Features putatively involved in the adaptation to high alkalinity and salinity, and selected core metabolic pathways of chemolithoautotrophic nitrite-oxidizing Nitrospira, are shown. Note that the transport stoichiometry of the ion transporters in “Ca. N. alkalitolerans” remains unknown. Colors of text labels indicate whether adaptive features are present (i.e., have homologs) in the genomes of other NOB (red, feature is not present in any other characterized NOB; blue, feature is present only in the marine Nitrospina gracilis; purple, feature is present in several other characterized NOB).

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    Cytoplasmic pH and ion homeostasis
    At high pH, alkaliphilic and alkalitolerant microbes maintain a higher transmembrane electrical potential (ΔΨ) component of the proton motive force (PMF) than usually found in neutrophiles. The high ΔΨ is required to maintain PMF, because the ΔpH component of the PMF is reversed when the extracellular pH is higher than the intracellular pH [54]. Like in neutrophiles, the ΔΨ of alkaliphiles is negative inside the cell relative to the outside [54]. Furthermore, the intracellular pH must be kept below the (extremely) alkaline extracellular pH. At elevated salinity, resistance against high salt concentrations is an additional, fundamental necessity for survival. All this requires a tightly regulated pH and ion homeostasis, in which cation transmembrane transporters play key roles [54,55,56]. The “Ca. N. alkalitolerans” genome codes for various Na+-dependent transporters (Fig. 5, Table S3) including secondary Na+/H+ antiporters that are involved in pH homeostasis in other organisms: two copies of a group 3 Mrp-type Na+/H+ antiporter [57, 58] encoded by the seven genes mrpA-G, and monovalent cation-proton antiporters of the types NhaA and NhaB, each of which is encoded by a single gene [59]. The Mrp antiporter is crucial for growth at high pH and elevated salinity in alkaliphilic Halomonas spp. and Bacillus spp., where it exports Na+ and imports H+, thus contributing to the maintenance of a lower intracellular pH compared to the environment (e.g., cytoplasmic pH 8.3 at external pH ~ 10.5) [[60] and references cited therein, [55]]. The Mrp proteins may form a large surface at the outside of the cytoplasmic membrane that could support proton capture under alkaline conditions [54, 57]. Nha-type antiporters are widely distributed among non-extremophilic and extremophilic organisms [55]. Being involved in the homeostasis of Na+ and H+, they are important for survival under saline and/or alkaline conditions [56]. In E. coli, NhaA is regulated by the cytoplasmic pH and it catalyzes the import of 2H+ with the concurrent export of one Na+. This electrogenic activity is driven by ΔΨ and maintains pH homeostasis at elevated external pH [[52] and references cited therein]. The simultaneous presence of the two antiporters NhaA and NhaB has been associated with halophilic or haloalkaliphilic phenotypes in other organisms [55, 59]. Although the regulation and cation transport stoichiometry of the homologs in “Ca. N. alkalitolerans” remain unknown, the Mrp- and Nha-family antiporters most likely exhibit important physiological roles in this organism and support its survival under haloalkaline conditions. Possibly, “Ca. N. alkalitolerans” can even combine its growth in dense flocks with the extrusion of protons by its numerous proton transporters thereby lowering the pH inside the flock [51].
    One of the two nhaB genes present in the “Ca. N. alkalitolerans” genome is located in an interesting genomic region that also contains all genes encoding the group 3 Mrp-type Na+/H+ antiporter (Fig. S8). The two genes downstream from mrpD display sequence similarity to the NADH dehydrogenase (complex I) subunits NuoM and NuoL. However, based on the genomic context they are more likely additional mrpA- and/or mrpD-like genes, as these Na+/H+ antiporter subunits are evolutionary related to NuoM and NuoL [61]. Multiple copies of subunits NuoM and NuoL of the NADH dehydrogenase are encoded elsewhere in the genome, partially in larger nuo operons (see Table S3). Moreover, the locus contains one gene coding for the low-affinity, high flux Na+/HCO3− uptake symporter BicA [62] and gene motB encoding a H+-translocating flagellar motor component (Fig. S8). In the haloalkalitolerant cyanobacterium Aphanothece halophytica, a similar clustering of bicA with genes coding for Na+/H+ antiporters has been described. The authors proposed a model of cooperation between these transporters, where Na+ extruded by the Na+/H+ antiporters could drive the uptake of HCO3− by BicA under alkaline conditions when CO2 becomes limiting [63]. Sodium-driven import of HCO3− could be an essential feature for “Ca. N. alkalitolerans”, because bicarbonate is the main source of inorganic carbon for autotrophic organisms, but becomes less accessible at high pH >10 [55]. A carbonic anhydrase, which is also present in the genome (Fig. 5, Table S3), can convert the imported HCO3− to CO2 for carbon fixation via the reductive tricarboxylic acid cycle (Fig. 5).
    Since cytoplasmic K+ accumulation may compensate for Na+ toxicity at elevated intracellular pH [64], many alkaliphiles retain an inward directed K+ gradient [55]. The potassium uptake transporters of the Trk family contribute to pH and K+ homeostasis of halo- and/or alkaliphiles [55]. TrkAH catalyzes the NAD+-regulated uptake of K+ possibly coupled with H+ import [65]. Moreover, kinetic experiments revealed that TrkAH of the gammaproteobacterium Alkalimonas amylolytica is salt-tolerant and functions optimally at pH > 8.5 [66]. “Ca. N. alkalitolerans” encodes a TrkAH complex (Fig. 5, Table S3), which may be a specific adaptation to its haloalkaline environment as no homologous K+ transporter has been identified yet in any other NOB genome. Under more neutral pH conditions, Kef-type K+ efflux pumps, which are present in two copies in the “Ca. N. alkalitolerans” genome, could excrete excess K+ (Fig. 5, Table S3).
    Adaptations of the energy metabolism
    Aside from the different cation transporters (see above), “Ca. N. alkalitolerans” also encodes several mechanisms for cation homeostasis that are linked to membrane-bound electron transport and energy conservation. Like in other aerobic alkaliphiles [56], ATP synthesis is likely catalyzed by a canonical, H+-translocating F1FO-ATPase (Fig. 5, Table S3). In addition, the genome contains all genes of a predicted Na+-translocating N-ATPase [67] (Fig. 5, Fig. S9, Table S3). N-ATPases form a separate subfamily of F-type ATPases and have been suggested to be ATP-driven ion pumps that extrude Na+ cations [67] or H+ [68]. The c subunit of the N-ATPase in the genome of “Ca. N. alkalitolerans” contains the typical amino acid motifs for Na+ binding and transport [67] (Fig. S10). Subunits a and c of the N-ATPase, which are involved in ion transport, are most similar to homologs from the halotolerant, sulfate-reducing Desulfomicrobium baculatum (81.5% AA identity) and the haloalkalitolerant, sulfur-oxidizing Sulfuricella denitrificans (88.2% AA identity), respectively. Hence, in “Ca. N. alkalitolerans”, the N-ATPase may contribute to the maintenance of ΔΨ, the generation of a sodium motive force (SMF), and salt resistance (Fig. 5).
    The genome of “Ca. N. alkalitolerans” encodes two different types of NADH:quinone oxidoreductase (complex I of the electron transport chain) (Fig. 5, Table S3). Firstly, the organism possesses all 14 genes of type I NADH dehydrogenase (nuoA to nuoN). They are present in one to three copies each. The nuo genes are mostly clustered at several genomic loci (Table S3) and are most similar to either of the two nuo operons present in Nitrospira defluvii [39], with AA identities between 41% and 90%. As mentioned above, nuoL/M-like genes at loci without other nuo genes might represent subunits of cation antiporters.
    The genome furthermore contains a locus encoding all six subunits of a Na+-dependent NADH:quinone oxidoreductase (Nqr or type III NAD dehydrogenase) (Fig. 5, Table S3). The locus is situated on a single contig in the vicinity of transposase genes, indicating that “Ca. N. alkalitolerans” might have received this type of complex I by lateral gene transfer. The gene of subunit E, which takes part in Na+ translocation [69], is most similar to a homolog in the ammonia-oxidizing bacterium Nitrosomonas nitrosa (86% AA identity).
    The metabolic model for N. defluvii [39] assumes that two different versions of the H+-dependent complex I (Nuo) are used for forward or reverse electron transport, respectively. Nitrospira possess a canonical Nuo that is likely used for PMF generation during the forward flow of low-potential electrons from the degradation of intracellular glycogen or from hydrogen as an alternative substrate (see also below). In addition, reverse electron transport is essential in NOB to generate reducing power for CO2 fixation. In Nitrospira, a second (modified) form of Nuo with duplicated proton-translocating NuoM subunits might use PMF to lift electrons from quinol to ferredoxin [70]. The reduced ferredoxin is required for CO2 fixation via the rTCA cycle. As expected, “Ca. N. alkalitolerans” possesses these two Nuo forms that are conserved in other characterized Nitrospira members. In addition, the Na+-dependent Nqr complex might function in two directions in “Ca. N. alkalitolerans” as well. During forward electron flow, Nqr would contribute to SMF generation (Fig. 5). Reverse operation of the Nqr could generate NADH while importing Na+, thus utilizing SMF for the reduction of NAD+ with electrons derived from quinol (Fig. 5). Hence, the two types of complex I are likely involved in essential electron transport and the fine-tuning of PMF and SMF. They probably cooperate with the Na+- and the H+-translocating ATPases and the various cation transporters (see above) to adjust the cytoplasmic ion concentrations and the membrane potential in response to the environmental salinity and pH.
    In addition to a novel “bd-like” cytochrome c oxidase, which is commonly found in Nitrospira genomes [16, 39], the genome of “Ca. N. alkalitolerans” contains a locus with fused genes for a cbb3-type cytochrome c oxidase (Fig. 5, Table S3) similar to the one present in the marine nitrite oxidizer Nitrospina gracilis [41]. The cbb3-type terminal oxidases usually exhibit high affinities for O2 [71] and may allow “Ca. N. alkalitolerans” to sustain respiration at low oxygen levels.
    Interestingly, “Ca. N. alkalitolerans” encodes two different hydrogenases and the accessory proteins for hydrogenase maturation (Fig. 5, Table S3). First, it possesses a group 2a uptake hydrogenase that is also found in N. moscoviensis, which can grow autotrophically on H2 as the sole energy source [16]. Second, “Ca. N. alkalitolerans” codes for a putative bidirectional group 3b (sulf)hydrogenase that also occurs in other NOB and in comammox Nitrospira [18, 41] but has not been functionally characterized in these organisms. Experimental confirmation of H2 utilization as an alternative energy source and electron donor by “Ca. N. alkalitolerans” is pending. However, we assume that this capability would confer ecophysiological flexibility, especially if nitrite concentrations fluctuate and H2 is available at oxic-anoxic boundaries in biofilms or upper sediment layers. While electrons from the group 2a hydrogenase are probably transferred to quinone [16], the group 3b hydrogenase might reduce NAD+ [41] and fuel forward electron transport through the Nuo and Nqr complexes (see above).
    Osmoadaptation
    The intracellular accumulation of compatible solutes is an important mechanism allowing microorganisms to withstand the high osmotic pressure in saline habitats [55]. “Ca. N. alkalitolerans” has the genetic capacity to synthesize or import the compatible solutes trehalose, glycine betaine, and glutamate (Fig. 5). For trehalose synthesis the gene treS of trehalose synthase (Table S3), which enables trehalose synthesis from maltose, is present. The genes opuD and opuCB for glycine betaine import (Table S3) have been identified in the marine Nitrospina gracilis [41], but not yet in any Nitrospira species. For glutamate synthesis, the genes gltB and gltD were identified (Table S3). They code for the alpha and beta subunits of glutamate synthase, which catalyzes L-glutamate synthesis from L-glutamine and 2-oxoglutarate with NADPH as cofactor. In addition, we identified adaptations of “Ca. N. alkalitolerans” to the low availability of iron and the presence of toxic arsenite in saline-alkaline systems (Supplementary text). More

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    Climate and atmospheric deposition effects on forest water-use efficiency and nitrogen availability across Britain

    Site and sampling
    We selected twelve monoculture tree stands of the most common tree species in Britain, Scots pine (Pinus sylvestris L.), Sitka spruce (Picea sitchensis Bong. Carr.), pedunculate oak (Quercus robur L.) and common beech (Fagus sylvatica L.). The majority of the stands were experimental sites within the Level II- ICP intensive forest monitoring network (http://icp-forests.net/), with the exception of Covert Wood, Shobdon and Goyt. The Goyt site was added as a high Ndep site as a contrast to the low Ndep Sitka spruce site in Scotland (Fig. 1, Table 1, Supplementary Table 1). For each species, forests were selected with similar soil type and age, but with contrasting Ndep, Sdep and climate, particularly rainfall and temperature, as described in Fig. 1, Table 1 and Supplementary Table 1. Stand information (mean tree height, mean diameter at the breast height and basal area) as measured for target years and for some of the forest stands are shown in Fig. S4.
    At each ICP forest site, a plot of 0.25 ha was established in 1995 to carry out monitoring30 and a similar protocol was followed at the Goyt and Shobdon sites. Within each plot, 10 trees were selected for the collection of 3 wood cores per tree by using a 5 mm diameter increment borer, which were placed in paper straws for transport. Sampling was carried out between November 2010 and March 2011. Once in the laboratory, samples were dried at 70 °C for 48 h. Of the three wood cores sampled, one was kept for dendrochronology, with the other two used for stable isotope analyses.
    Climate and atmospheric deposition data
    Climate data (Temperature, T, Vapour Pressure Deficit, VPD, Precipitation, P) were obtained from automated weather stations at the sites and/or the nearest local meteorological stations (data were provided by the British Atmospheric Data Centre). Annual mean (Ta) and mean maximum (Tamax) values for temperature were calculated from monthly mean and maximum air temperature, T, respectively, and annual precipitation (Pa) was calculated as the sum of total monthly precipitations. Annual VPD was calculated from averaging monthly values obtained from mean monthly maximum temperature and minimum monthly relative humidity. For all the parameters, mean values were also calculated over the growing season, i.e., from May to September. We also considered the standardised precipitation-evapo-transpiration index, SPEI, relative to August, with 1 (SPEI8_1), 2 (SPEI8_2) and 3 (SPEI8_3) months time-scale and SPEI relative to December, with 1 and 12 months time-scale, the latter providing year-cumulated soil moisture conditions. SPEI values were obtained from the global database with 0.5 degrees spatial resolution available online at: https://sac.csic.es/spei/.
    Yearly wet nitrogen (Ndep) and sulphur deposition (Sdep) were obtained from measured bulk precipitation and throughfall water volumes at the sites and measured elemental concentrations (NO3−, NH4+ and SO2–4) as previously described30. For the spatial analyses, we considered mean of annual deposition (sNdep and sSdep), obtained as the sum of total (NH4-N + NO3-N for Ndep) wet and dry deposition. The latter were estimated as difference between throughfall and bulk precipitation N fluxes30. For Rogate only 1 year (2010) of monitoring was available. For Goyt site, atmospheric deposition data collected at Ladybower were considered, as the two sites are 30 km apart. For two sites (i.e., Shobdon and Covert Wood), which were not part of the regular ICP forest sites, the wet deposition obtained from the UK 5 × 5 km grid Ndep and Sdep dataset was used4. The estimate included wet and dry NHx-N (NH4, NH3), NOy-N (NO2, NO3, HNO3) and S (SOx = SO2 and SO4) deposition, modelled using FRAME with 2005 emissions data4. However, only the total wet deposition was included in the analyses here, as we previously reported a good agreement between modelled and measured wet Ndep50.
    For the temporal analyses, only wet deposition (as calculated from NO3−, NH4+ and SO2–4 concentrations in bulk precipitation) was considered (indicated as aNdep and aSdep), given the uncertainties associated with the quantification of the dry deposition. For instance, when differences between throughfall and bulk precipitation are  More

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    Elevational is the main factor controlling the soil microbial community structure in alpine tundra of the Changbai Mountain

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    Author Correction: Efficient production of male Wolbachia-infected Aedes aegypti mosquitoes enables large-scale suppression of wild populations

    Verily Life Sciences, South San Francisco, CA, USA
    Jacob E. Crawford, David W. Clarke, Victor Criswell, Mark Desnoyer, Kyle Gong, Kaycie C. Hopkins, Paul Howell, Justin S. Hyde, Josh Livni, Charlie Behling, Renzo Benza, Willa Chen, Craig Eldershaw, Daniel Greeley, Yi Han, Bridgette Hughes, Evdoxia Kakani, Joe Karbowski, Angus Kitchell, Erika Lee, Teresa Lin, Jianyi Liu, Martin Lozano, Warren MacDonald, Matty Metlitz, Sara N. Mitchell, David Moore, Johanna R. Ohm, Kathleen Parkes, Alexandra Porshnikoff, Chris Robuck, Martin Sheridan, Robert Sobecki, Peter Smith, Jessica Stevenson, Jordan Sullivan, Brian Wasson, Allison M. Weakley, Mark Wilhelm, Joshua Won, Ari Yasunaga, William C. Chan, Nigel Snoad, Linus Upson, Tiantian Zha, Peter Massaro & Bradley J. White

    Consolidated Mosquito Abatement District, Parlier, CA, USA
    Devon Cornel, Brittany Deegan, Jodi Holeman & F. Steven Mulligan

    MosquitoMate Inc., Lexington, KY, USA
    Karen L. Dobson, James W. Mains & Stephen L. Dobson

    Department of Entomology, University of Kentucky, Lexington, KY, USA
    Stephen L. Dobson More

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    Biases in estimation of insect herbivory from herbarium specimens

    Effect of sampling protocol on leaf area lost to insects
    We analysed 248 samples collected from 17 species of woody plants native to the study region. Among these, 85 samples were collected using the protocol developed for ecological research, and 163 samples were collected as herbarium specimens. Each herbarium specimen, on average, contained four-fold fewer leaves than a sample collected by ecological methods (13.5 and 50.3 leaves, respectively).
    Measurements of leaf area lost to insects were performed by M.V.K., who was aware of research hypothesis and sample origin, and by J. Rikus, who was blinded to these factors. The measurements by both persons yielded the same results (average difference ± SE: 0.52 ± 0.48%; P  > 0.38), indicating that the results by M.V.K. used in subsequent analyses were not affected by confirmation bias.
    The average losses of woody plant foliage (Supplementary Data S1) were significantly lower for herbarium specimens (4.87%) than for ecological samples (7.96%), although the differences between these two types of samples varied with the plant species (Table 1, Fig. 1). Collectors generally prefer branches with low levels of herbivory, and when insect damage increases in nature, the difference between herbarium specimens and ecological samples becomes greater (see e.g. Sorbus aucuparia and Tilia cordata on Fig. 1). Individual collectors significantly differed in their attitudes to leaf damage by insects (F14, 79 = 1.93, P = 0.04; Fig. 2) while collecting herbarium specimens, with their choices ranging from careful selection of branches with nearly undamaged leaves to taking almost no account of the extent of insect herbivory. As a result, the actual levels of herbivory and the damage in herbarium specimens varied independently from each other (regression analysis: F1, 15 = 0.07, P = 0.80; Fig. 3). Additional analysis showed that exclusion of Sorbus aucuparia, the species with the extreme differences between the levels of herbivory measured from two types of samples, did not change our main result: the correlation between the levels of herbivory in ecological samples and in herbarium specimens remained not significant (data not shown).
    Table 1 Sources of variation in losses of woody plant foliage to insects: results of field experiment (SAS GLIMMIX procedure).
    Full size table

    Figure 1

    Leaf area loss (estimated marginal means + SE) measured from ecological samples (black bars) and from herbarium specimens (white bars) collected at the same time from the same localities (sample sizes are shown within bars). An asterisk indicates a significant (P  More

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    Contribution of plant-induced pressurized flow to CH4 emission from a Phragmites fen

    Study site
    The study was conducted in the Federseemoor (48.092°N, 9.636°E), a peatland of 30 km2 located in the region Upper Swabia in southwest Germany. This peatland has developed via natural terrestrialization from a proglacial lake after the last ice age. As a result, the surface area of the lake declined from 30 to 12 km2. Between 1787 and 1808, the lake was further reduced to a size of 1.4 km2 by drainage activities. The newly gained land of 11 km2 was used as pasture but turned out to be unprofitable due to the recurring high water table. Nowadays it is a nature conservation area, mainly consisting of fen (see van den Berg et al.21 for a vegetation map). The lake Federsee is completely surrounded by reed vegetation (P. australis), with a total area of 2.2 km2 and a density of around 70 living shoots and 75 dead stems per m2. During the measurement period (7–10 June) the Phragmites plants were 1.2 m high. This is half their maximum height, which is reached at the end of July. The high density of Phragmites and lack of other species in the reed belt result from high nutrient concentrations due to wastewater input to the lake since 1951. After 1982, the input of untreated sewage water was stopped, which reduced the nutrient concentrations. Only since 2006 has there been a significant improvement in water quality, and after 2008 the lake water became clear again. The field experiment was installed in the middle of the reed area at around 70 m distance from an eddy covariance (EC) tower, which has been running since March 201321. In a radius of at least 200 m around the EC tower, the vegetation is dominated by Phragmites (see van den Berg et al.21), meaning only reed dominated the measured EC footprint.
    Field experiment
    Nine plots of 2 m × 2 m were prepared for three treatments with three replicates: (1) clipped reed (CR), to exclude the pressurized flow in the plants; (2) clipped and sealed reed (CSR), to exclude any exchange via plant stems; and (3) control where reed was not manipulated. In the CR and CSR treatments, living and dead reed stems were clipped to about 10 cm above the water table. In the CSR treatment the clipped reed stems was sealed with an acrylic sealant. Since rhizomes connect plants over longer distances, plots were isolated by cutting rhizomes from the reed plants around each plot to a depth of 50 cm, to avoid gas exchange with the surrounding area. The period between preparation of the plots and measurements was minimized (1–2 days) to reduce possible side effects, such as change in substrate availability for methanogens. One day before the first measurement, the water table rose about 20 cm in the whole field, flooding the prepared sealed stems of one plot already prepared for the CSR treatment. Nevertheless, since no gas exchange is expected from the sealed stems, this plot was still included in the experiment. CH4 and CO2 diffusive fluxes from the soil and plant-mediated fluxes were measured with transparent flow through chambers. Pore water was extracted to analyze the effect of the reduced/excluded gas exchange by the plants on soil chemistry. In each plot ebullition was measured as well (see below).
    Diffusive and plant mediated CH4 flux
    On 7, 9 and 10 June 2016 between 07:00 and 18:00, the gas fluxes of each treatment were alternately measured. Per day, only one of the triplicates per treatment was measured. CH4 fluxes were measured in the middle of the plots with transparent chambers with a diameter of 50 cm. One chamber was 2 m high and was on the control plots. Two chambers were 1 m high and used on the CR and CSR plots. The 1-m chambers were equipped with a small fan of 8 cm × 8 cm that had a flow capacity of 850 l min−1; two fans were installed in the 2-m chamber. Each day one replicate of every treatment was measured, to be able to capture the diurnal cycle for each plot and to minimize disturbance by translocating the chambers. The chambers were connected with 8 m tubing to a multiport inlet unit attached to a fast greenhouse gas analyzer (GGA) with off-axis integrated cavity output spectroscopy (GGA-24EP, Los Gatos Research, USA) measuring the concentration of CH4 and CO2 every second. Every 5 min, the multiport switched between the three chambers, allowing air from each chamber to be alternately pumped through the GGA with a pumping rate of 300 ml min−1 and resulting in four flux measurements per plot per hour (~ 35 measurements per plot per day). The withdrawn air from the chamber was replaced with ambient air through an opening in the chamber. After 1–2 h of continuous measurements, the chambers were ventilated by lifting the chambers to fully replace inside air with ambient air. After 15 min, the chamber was put back and measurements continued. Since it takes a long time before the chamber CH4 gets to equilibrium with the water column, 1–2 h of increasing CH4 concentration in the chamber will have little effect on the measurement accuracy of the CH4 flux (in contrary to the CO2 flux)22. Nevertheless, we used only data from the first 30 min after ventilating to calculate the diffusive flux (five measurements per plot per day), since this is the period where temperature and humidity inside the chamber resemble outside conditions most closely. Only for the comparison between eddy covariance fluxes and chamber fluxes on the control plots we did use data from the whole measurement period.
    The concentration for every measurement point was corrected for the change in concentration caused by the inflow of ambient air with known CO2 and CH4 concentrations (measured by the EC station) and outflow of chamber air (both with a flow rate of the pump speed of the Los Gatos). The slope of the corrected chamber concentrations over a 4 min period within the 5 min measurement was used to calculate the flux and was checked for non-linear fluctuations due to e.g. ebullition. Fluxes corresponding to an average chamber concentration of  > 100 ppm CH4 were discarded, because of the GGA’s detection limit. In total 11% of the fluxes were discarded.
    Ebullition
    In each plot ebullition was measured by catching bubbles from a fixed surface with an ebullition trap10, composed of a 20 cm diameter funnel, to which a glass bottle of 300 ml was attached. The bottles were filled with water from the site and the ebullition trap was installed under the water table on 8 June and carefully anchored between reed stems (no open endings of stems were below the trap) on the soil surface around 0.55 m below the water surface. Bubbles were captured in the glass bottle for 18 days, after which the bottles were removed and gas samples were taken in the field. The total volume of ebullition gas was determined and the concentration of CH4, CO2 and N2O were measured by gas chromatography (7890B GC, Agilent Technologies, USA) in the lab.
    Environmental variables
    In each chamber, temperature and radiation were measured with a temperature/light sensor (HOBO Pendant data logger, Onset Computer Corporation, USA) logging at an interval of 30 s. Every minute soil temperature was measured in each plot in the upper 0–0.05 m with a Soil Water Content Reflectometer (CS655, Campbell Scientific Inc., USA) around 0.56 m below the water table. Air temperature, air relative humidity (HMP155, Vaisala Inc., Finland) and incoming and outgoing shortwave and longwave radiation (CNR4, Kipp & Zonen Inc., The Netherlands) were measured at a height of 6 m close to or at the EC station. Groundwater table was continuously measured with a water level pressure sensor (Mini-Diver datalogger, Eijkelkamp Agrisearch Equipment Inc., The Netherlands) placed at 1.45 m depth in a 2-m long filter pipe that was placed 1.60 m into the soil. Data were recorded at a 30 min interval.
    Pore water sampling and analysis
    To see if the treatments had any effect on the methane production, pore water samples were analyzed. At two locations in each plot, pore water was extracted anaerobically with ceramic cups (Eijkelkamp Agrisearch Equipment Inc., The Netherlands). Pore water from 10, 20, 30 and 50 cm depth was collected by vacuum suction in syringes and transported to the lab. In the lab, pore water was diluted with a ratio of 1:3. Dissolved organic carbon (DOC) concentration was measured with a Dimatoc 100 DOC/TN-analyzer (Dimatec, Germany). A second pore water sample was taken in vacuumed 13 ml exetainers with 3 g of NaCl. The concentration of CH4 in the headspace of these exetainers, representing the CH4 concentration in pore water, was determined on a HP gas chromatograph (Hewlett Packard, USA). A third pore water sample was fixed with 0.2% 2.2-bipyridin in 10% CH3COOH buffer in the field to determine Fe(II) measuring photometrical absorption at 546 nm in the lab.
    Eddy covariance
    The EC tower was located at a distance of around 70 m from the prepared plots. The tower was 6 m high and consisted of a LI-7700 open path CH4 gas analyser (LI-COR Inc., USA), a LI-7200 enclosed path CO2/H2O gas analyser (LI-COR Inc., USA) and a WindMaster Pro sonic anemometer (GILL Instruments Limited Inc., UK). Molar mixing ratio/mass density of the gases and wind speed in three directions were measured at a frequency of 10 Hz. Fluxes were calculated for an averaging interval of 15 min with the software EddyPro version 6.1.0. For more detailed information about the set up and calculations of the fluxes, see van den Berg et al.21.
    δ13C measurements
    CH4 oxidation and transport lead to isotopic fractionation of δ13C of CH423. The difference between δ13C of the CH4 present in the soil and the CH4 emitted to the atmosphere may therefore reveal the importance of both methane oxidation and the different emission pathways.
    The δ13C of CH4 tends to be much lower than the natural abundance in organic compounds, because methanotrophic prokaryotes prefer the lighter 12CH4 to 13CH4 thereby increasing the δ13C of CH4. Diffusion rates for 12CH4 are higher than for 13CH414 decreasing the δ13C of the emitted CH423. Although 13C enrichment (compared to produced CH4) has been found in internal spaces of plants due to CH4 oxidation14, the fractionation at the plant-atmosphere surface reduces the δ13C by about 12–18‰ due to the faster transport rate of 12CH4, which makes that emitted CH4 can have a lower fraction of δ13C than the produced CH4. Differences in δ13C between sediment and overall emission are larger for plants with diffusive internal gas transport than for plants with convective gas transport23.
    Since fractionation of CH4 emitted through ebullition in shallow waters is negligible, these gas bubbles can be used to know the isotopic composition of CH4 produced in sediment23. We therefore compared the δ13CH4 signature of ebullition gas with the signatures of CH4 from the chambers. Gas samples from the chamber were taken when the CH4 concentration was at least 10 times the ambient concentration, from each plot in the afternoon. The δ13CH4 signature was measured with an isotope-ratio mass spectrometer Delta plus XP (Thermo Finnigan, Germany).
    Statistics
    Chamber fluxes were measured at different times of the day, which means that environmental variables like temperature and radiation were varying. To be able to compare the different treatments without the variation resulting from environmental conditions, an analysis of covariance (ANCOVA) was conducted with the environmental variables as covariables. For the analysis, the data of the different measurement days were pooled together per treatment. The residuals of the model were normally distributed. With the parameters of the ANCOVA model, average fluxes were calculated with average environmental variables for the period ebullition was measured (8–27 June), to be able to compare the chamber fluxes with ebullition.
    To test if the means of the ebullition measurements or pore water concentrations were different between the treatments, an analysis of variance (ANOVA) test was performed with Fishers’s Least Significant Difference (LSD) post hoc test to find the specific differences between the treatments. More