Ecology

Volatile contents of S. caucasica shoots during the stages of oviposition by G. pecorum
Overall, 60 volatile compounds were identified in S. caucasica shoots during the preoviposition (I), oviposition (II), and postoviposition (III) stages of G. pecorum. These comprised 16 aldehydes, 14 ketones, 12 esters, 9 alcohols, 3 alkanes, 3 aromatic hydrocarbons, 1 acid, 1 ether, and 1 other. Among them, 35 volatiles were identified in I-L, 36 in II-L, and 37 in III-L. In addition, 18 volatiles were common to I-L, II-L, and III-L; 5 to I-L and II-L; 5 to II-L and III-L; and 2 to I-L and III-L. Ten volatiles were unique to I-L, 8 to II-L, and 12 to III-L (Table 1). The main chemical classes of I-L, II-L, and III-L were alcohols, esters, and others; alcohols and others; and alcohols and esters, respectively (Fig. 1).
Table 1 Volatiles detected from shoots of Stipa caucasica during preoviposition, oviposition, and postoviposition of Gasterophilus pecorum.
Full size table

Figure 1

Volatiles classes from shoots of Stipa caucasica during preoviposition, oviposition, and postoviposition of Gasterophilus pecorum. I-L, II-L, and III-L represent Stipa caucasica shoots during the preoviposition, oviposition, and postoviposition stages of Gasterophilus pecorum. (A) alcohols, (B) esters, (C) aldehydes, (D) ketones, (E) others, (F) acids, (G) alkanes, (H) aromatic hydrocarbons, and (I) ethers. Data are mean (n = 3) ± SE. Different letters indicate significant differences at p  0.05) (Fig. 1A). Of the alcohols, 3-hexen-1-ol,(Z)- had the highest relative contents, 25.68%, 55.65%, and 32.35% in I-L, II-L, and III-L, respectively, with no significant differences among these three (P  > 0.05). The relative content of 1-hexanol was higher in II-L (1.52%) than in III-L (1.01%) (P = 0.002) or I-L (0.89%) (P = 0.001), whereas III-L and I-L showed no significant difference (P  > 0.05). The relative contents of the other volatile alcohols were less than 0.8% (Table 1).
Twelve esters were identified from the three stages of S. caucasica. Among them, three, i.e., acetic acid hexyl ester, ethyl acetate, and acetic acid phenylmethyl ester, were common to all three stages; and four, i.e., 3-cyclohexen-1-ol,acetate, 2(3H)-furanone,5-ethyldihydro-, 3-hexen-1-ol,formate,(Z)-, and acetic acid pentyl ester, were common to two of the three stages. The relative contents of esters were lower in II-L (3.16%) than in III-L (40.61%) or I-L (27.81%) (P = 0.000; P = 0.000), whereas there was no significant difference between III-L and I-L (P  > 0.05) (Fig. 1B). The relative contents of acetic acid hexyl ester in II-L (1.47%) and III-L (1.14%) were not significantly different (P  > 0.05), but were higher in both than in I-L (0.52%) (P = 0.001 and 0.005, respectively). The relative contents of 3-hexen-1-ol,acetate,(Z)- (24.8%), a specific volatile of I-L, and 3-hexen-1-ol,acetate(E)- (38.7%), which was specific to III-L, were highest in esters in stages specifically containing them. The relative content of propanoic acid,2-methyl-,3-hydroxy-2,4,4-trimethylpentyl ester, which was detected only in I-L, was 1.12%, whereas those of the other volatiles in esters were lower than 0.8% (Table 1).
Sixteen aldehydes were identified from the three stages of S. caucasica. Among them, seven, i.e., hexanal, nonanal, decanal, heptanal, undecanal, 2-octenal, (E)-, and 2-heptenal,(Z)-, were common to all three stages; and two, i.e., 3-hexenal and 2,4-hexadienal, (E,E)-, were common to two of the three stages. The relative contents of aldehydes in I-L, II-L, and III-L were 10.83%, 6.84%, and 9.9%, and those of hexanal were 0.62%, 2.38%, and 1.16%, respectively; none of these differences was significant (P  > 0.05) (Fig. 1C). The relative contents of nonanal in I-L (1.45%) and II-L (1.9%) did not differ significantly (P  > 0.05), and both were higher than that in III-L (0.96%) (P  > 0.05 and P = 0.018, respectively). The relative content of decanal was higher in II-L (1.20%) than in I-L (0.78%) (P = 0.043) or III-L (0.65%) (P = 0.016), but those in I-L and III-L did not differ significantly (P  > 0.05). The following two volatiles were present in two of the three stages: 3-hexenal, with higher content in I-L (7.10%) than in III-L (5.03%) (P  > 0.05); and 2,4-hexadienal,(E,E)-, with content higher in II-L (0.3%) than in III-L (0.22%) (P = 0.00). Benzaldehyde was specific to III-L (0.99%), with the relative contents of other volatile aldehydes  0.05), with no significant difference between II-L and III-L (P  > 0.05) (Fig. 1D). The content of 2(5H)-Furanone,5-ethyl- was specific to II-L (2.38%), and the relative contents of the other ketones were  0.05), and both were higher than those for III-L (12.9%) (P = 0.017 and P  > 0.05, respectively) (Fig. 1E). The relative content of acetic acid, the only volatile in the class of acids, was lower in III-L (0.61%) than in II-L (3.36%) or I-L (2.14%) (P = 0.022 and P  > 0.05, respectively); there was no significant difference between the latter two (P  > 0.05). The relative contents of alkanes, aromatic hydrocarbons, and ethers were less than 0.22% (Fig. 1G–I). These included three alkanes, one in I-L and two each in II-L and III-L; three aromatic hydrocarbons, one of them specific to each stage; and one ether, which was not found in III-L (Table 1).
The five volatile compounds with the highest relative contents, in order, during the three stages of S. caucasica were as follows: I-L, caprolactam (30.66%)  > 3-hexen-1-ol,(Z)- (25.68%)  > 3-hexen-1-ol,acetate,(Z)- (24.8%)  > 3-hexenal (7.1%)  > acetic acid (2.14%); II-L, 3-hexen-1-ol,(Z)- (55.65%)  > caprolactam (22.68%)  > acetic acid (3.36%)  > hexanal (2.38%) = 2(5H)-furanone,5-ethyl- (2.38%); III-L, 3-hexen-1-ol,acetate,(E)- (38.7%)  > 3-hexen-1-ol,(Z)- (32.35%)  > caprolactam (12.9%)  > 3-hexenal (5.03%)  > hexanal (1.16%) (Table 1). A total of eight volatiles were detected: two (i.e., 3-hexen-1-ol,(Z)- and caprolactam) were common to the three stages, and three (i.e., acetic acid, 3-hexenal, and hexanal) to two of the three stages. Finally, 2(5H)-furanone,5-ethyl- was in the top 5 volatile compounds of only II-L.
Relative contents of volatiles in three plant species during the oviposition stage of G. pecorum
During the oviposition stage of G. pecorum, a total of 60 volatiles were identified in S. orientalis (II-D), S. caucasica (II-L), and C. latens (II-T). These comprised 18 esters, 13 aldehydes, 11 alcohols, 10 ketones, 2 alkanes, 2 aromatic hydrocarbons, 1 acid, 1 alkene, 1 ether, and 1 other. Of these, 35 were identified in II-D, 36 in II-L, and 27 in II-T. In addition, 11 were common to II-D, II-L, and II-T, 14 to II-D and II-L, and 2 to II-L and II-T; 10 were unique to II-D, 9 to II-L, and 14 to II-T (Table 2). The main chemical classes of II-D and II-L were alcohols and others, and those of II-T were alcohols, esters, and others (Fig. 2).
Table 2 Volatiles detected from shoots of three plant species during oviposition of Gasterophilus pecorum.
Full size table

Figure 2

Volatiles classes from shoots of three plant species during oviposition of Gasterophilus pecorum. II-D, II-L, and II-T represent shoots of Stipa orientalis, Stipa caucasica, and Ceratoides latens during the oviposition stage of Gasterophilus pecorum. (A) alcohols, (B) esters, (C) aldehydes, (D) ketones, (E) others, (F) acids, (G) alkanes, (H) aromatic hydrocarbons, (I) ethers, and (J) alkenes. Data are mean (n = 3) ± SE. Different letters indicate significant differences at p  0.05) (Fig. 2A). The relative content of 3-hexen-1-ol,(Z)- was lower in II-T (14.28%) than in II-L (55.65%) or II-D (44.64%) (P = 0.002 and 0.008), but there was not significant difference between II-L and II-D (P  > 0.05). The relative contents of 1-hexanol and 2-hexen-1-ol,(E)- in II-D, II-L, and II-T were 1.67%, 1.52%, 2.79%, and 0.72%, and 0.59% and 2.66%, respectively; these differences were not significant (P  > 0.05). Finally, 3-hexen-1-ol was specific to II-D (1.57%), and the relative contents of other alcohols were  0.05) (Fig. 2B). The relative content of acetic acid hexyl ester in II-D, II-L, and II-T was 0.4%, 1.47%, and 4.25%, respectively; these differences were not significant (P  > 0.05). The relative content of 2(3H)-furanone, 5-ethyldihydro- was higher in II-T (0.71%) than in II-D (0.27%) or II-L (0.26%) (P = 0.000; P = 0.000), but II-D and II-L were not significantly different (P  > 0.05). Both 3-hexen-1-ol,acetate,(Z)- (13.13%) and propanoic acid,2-methyl-,3-hydroxy-2,4,4-trimethylpentyl ester (1.07%) were unique to II-D, and benzoic acid methyl ester (1.88%), methyl salicylate (2.52%), and cis-3-hexenyl isovalerate (8.45%) were all unique to II-T. The relative contents of other esters were  0.05) (Fig. 2C). The relative contents of hexanal, nonanal, decanal, and heptanal were 0.25–2.38% and were higher in II-L than in II-D or II-T, although the differences were not significant (P  > 0.05). Finally, 3-hexenal (6.57%) was unique to II-D, and benzaldehyde (0.94%) to II-T. The relative contents of other aldehydes were  0.05) (Fig. 2D). Five ketones, i.e., 5-hepten-2-one,6-methyl-, 2(3H)-furanone,dihydro-5-methyl-, 2-hexanone,4-methyl-, 2-undecanone,6,10-dimethyl-, and acetophenone, were common to II-D and II-L, and 2(5H)-furanone,5-ethyl- (2.38%) was unique to II-L. The relative contents of other ketones were  0.05) (Fig. 2E). Acetic acid was the only substance in the class ‘acids,’ and its relative content was lower in II-D (1.44%) than in II-T (3.62%) (P = 0.046) or II-L (3.36%) (P  > 0.05); contents in II-T and II-L did not differ significantly (P  > 0.05). The only alkene, 1,3,6-Octatriene,3,7-dimethyl-, was unique to II-T (12.67%). The relative contents of other alkanes and ethers were  caprolactam (21.76%)  > 3-hexen-1-ol,acetate,(Z)- (13.13%)  > 3-hexenal (6.57%)  > 1-hexanol (1.67%); II-L, 3-hexen-1-ol,(Z)- (55.65%)  > caprolactam (22.68%)  > acetic acid (3.36%)  > hexanal (2.38%) = 2(5H)-furanone,5-ethyl- (2.38%); II-T, caprolactam (34.2%)  > 3-hexen-1-ol,(Z)- (14.28%)  > 1,3,6-octatriene,3,7-dimethyl- (12.67%)  > cis-3-hexenyl isovalerate (8.45%)  > acetic acid hexyl ester (4.25%) (Table 2). Eleven volatiles were included: two (3-hexen-1-ol,(Z)- and caprolactam) were common to all three plant species; the other nine were in the top five of only one species.
Relative contents of volatiles from S. caucasica in different growth periods
From S. caucasica at the early, flourishing, and late growth periods (GP1, GP2, and GP3, respectively), a total of 69 volatile compounds were identified. These comprised 17 ketones, 13 aldehydes, 11 esters, 10 alcohols, 4 alkanes, 4 aromatic hydrocarbons, 2 acids, 2 alkenes, 1 ether, and 5 others. Of these, 35 were found in GP1, 36 in GP2, and 40 in GP3. In addition, 11 were common to all three stages, 10 to both GP2 and GP3, 6 to both GP1 and GP2, and 4 to both GP1 and GP3; 14 were unique to GP1, 9 to GP2, and 15 to GP3 (Table 3). The main chemical classes of GP1 and GP2 were alcohols and others, and those of GP3 were esters and others (Fig. 3).
Table 3 Volatiles detected from shoots of Stipa caucasica during its different growth periods.
Full size table

Figure 3

Volatiles classes from shoots of Stipa caucasica during its different growth periods. GP1, GP2, and GP3 represent Stipa caucasica shoots during the early, flourishing, and late growth periods, respectively. Note that GP2 was actually the same sample as II-L in Figs. 1 and 2. Thus, the three groups had a total of seven rather than nine samples. (A) alcohols, (B) esters, (C) aldehydes, (D) ketones, (E) others, (F) acids, (G) alkanes, (H) aromatic hydrocarbons, (I) ethers, and (J) alkenes. Data are mean (n = 3) ± SE. Different letters indicate significant differences at p  0.05). The 3-hexen-1-ol,(Z)- content, which was the highest among all alcohols, was lower in GP3 (15.42%) than in GP1 (49.5%) or GP2 (55.65%) (P = 0.005 and 0.002, respectively); the latter two did not differ significantly (P  > 0.05). The relative content of 1-hexanol was lower in GP3 (0.59%) than in GP1 (1.98%) or GP2 (1.52%) (P = 0.001 and 0.007, respectively); the latter two were not significantly different (P  > 0.05). The relative contents of other alcohols were  0.05) (Fig. 3B). The relative content of acetic acid hexyl ester was higher in GP2 (1.47%) than in GP1 (0.52%) (P = 0.022) or GP3 (0.98%) (P  > 0.05), with no significant difference between GP1 and GP3 (P  > 0.05). Propanoic acid,2-methyl-,3-hydroxy-2,4,4-trimethylpentyl ester (1.48%) was unique to GP1, and 3-hexen-1-ol,acetate,(Z)- (28.42%) to GP3. The relative contents of other esters were  0.05) (Fig. 3E). The relative contents of the remaining four ‘others’ were  0.05) (Fig. 3C). The relative contents of hexanal and decanal decreased with growth period from 4.77% and 1.38% to 1.51% and 1.06%, respectively; but there were no significant differences between periods (P  > 0.05). Six volatiles were common to two of the three periods. There were no significant differences between the relative contents of 3-hexenal in GP3 (6.13%) and in GP1 (5.50%) (P  > 0.05) or between those of nonanal in GP2 (1.90%) and GP3 (1.43%) (P  > 0.05). Finally, 2-hexenal (4.51%) was unique to GP3, and the relative contents of other aldehydes were  0.05) (Fig. 3D). The relative content of 5-hepten-2-one, 6-methyl- was higher in GP1 (0.7%) than in GP3 (0.33%) (P = 0.020), with no significant difference between that in GP2 (0.45%) and that in GP1 or GP3 (both P  > 0.05). The relative content of 2-undecanone,6,10-dimethyl- was higher in GP1 (3.12%) than in GP2 (0.14%) (P = 0.05). Finally, 2(5H)-furanone,5-ethyl- (2.38%) was specific to GP2, and the relative contents of other ketones were  0.05) (Fig. 3F). The relative content of acetic acid, which was common to all three periods, was higher in GP2 (3.36%) than in GP3 (0.97%) (P = 0.035), but there was no significant difference between GP1 (1.87%) and GP2 or GP3 (both P  > 0.05). The other acid, propanoic acid,2-methyl-,2,2-dimethyl-1- (1%), was specific to GP3 (Table 3).
Four alkanes were identified, and the relative contents of individual alkanes ranged from 0.06% to 0.89%. The relative contents of all alkanes were higher in GP1 (1.56%) than in GP3 (0.15%) (P = 0.022), with no significant difference between GP2 (0.22%) and GP1 or GP3 (both P  > 0.05) (Fig. 3G). Two alkenes were found only in GP3; they had a total relative content of 4.76% (Fig. 3J); one, 1,3,6-octatrine,3,7-dimethyl-, accounted for 4.70% of this total. The relative aromatic hydrocarbon and ether contents were  caprolactam (19.78%)  > 3-hexenal (5.5%)  > hexanal (4.77%)  > 2-undecanone,6,10-dimethyl- (3.12%); GP2, 3-hexen-1-ol,(Z)- (55.65%)  > caprolactam (22.68%)  > acetic acid (3.36%)  > hexanal (2.38%) = 2(5H)-furanone,5-ethyl-(2.38%); GP3, caprolactam (28.8%)  > 3-hexen-1-ol,acetate,(Z)- (28.42%)  > 3-hexen-1-ol,(Z)- (15.42%)  > 3-hexenal (6.13%)  > 1,3,6-octatriene,3,7-dimethyl- (4.70%) (Table 3). Overall, nine volatiles were detected: two (3-hexen-1-ol,(Z)- and caprolactam) were in the top five in all three growth periods, two (3-hexenal and hexanal) in two growth periods, and the other five were in the top five of in only one of the three growth periods. More

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Estimation of a generalized wastewater treatment plant microbial community
In order to perform a deep taxonomic survey of microbial communities associated to wastewater treatment, we initially surveyed the EBI MGnify database11, collecting abundance profiles obtained by 16S amplicon based surveys of wastewater treatment communities.
We were able to roughly identify 1465 prokaryotic genera in 3433 samples from 49 studies (see Supplementary Data S1.1), with members of the archaea kingdom in about 22.5% of samples. When we restricted the analysis on sludges the number of studies was reduced to 33 with 1363 samples, however we identified 1379 genera and the number of samples showing archaea was about 40% (see supplementary data S1.2). Such observation underlined the relevance of archaea in wastewater environments. Interestingly, in the wastewater biome we found 128 samples (about 3.7%) from 24 studies (about 50%) showing evidence of anammox species, a percent that grew to about 5% in sludge samples from 10 studies (30%). This result manifests the need of properly taking into account anammox communities when estimating microbial abundance profiles in such environments.
Evaluation of existing primers
We then sought to verify whether existing primer pairs with established high performances and good coverage over the widest range of microbial species were able to appropriately cover wastewater associated communities, especially for the anammox components, using the most updated 16S RDP collection.
All Takahashi et al.10 and Albertsen et al.11 primers pairs were tested in silico using RDP ProbeMatch against updated 16S rRNA sequences from all genera available in the current RDP database. As shown in Fig. 1, we found that all Albertsen et al. primer pairs targeting the V1-V3 and V3-V4 and V4 only 16S region showed good performances for bacteria, but had relatively poor performances for archaeal species, that we have shown above to be relevant for wastewater associated communities12. On the contrary, Takahashi Pro pair (Pro341F and Pro805R) effectively showed high coverage for both bacteria and archaea, despite a surprisingly low performance for microbes highly relevant for the denitrification cycle, namely anammox bacteria especially of the Brocadiaceae family, Candidatus brocadia genus. Accordingly, our further efforts were focused on improving the Takahashi et al. primer pair.
Figure 1

Comparison of the overall theoretical performance in coverage (percent of members of the given rank mapped) of the different primer pairs used in this study.

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Predicted improvement of coverage on RDP database
When specifically matched against Brocadiales sequences, we found the possibility of improving the coverage of the Takahashi PRO primer pair by introducing a purine degeneration in the forward primer Pro341F, so that most member of our community of interest was matched. To design this, we extracted from the RDP global dataset all high quality ( > 1200 bp) 16S classified as Brocadiaceae at the family rank. On this dataset we simulated amplicons formation with RDP probeMatch, systematically imposing degenerations that could accommodate members of this family in the most complete as well as parsimonious way. We ended up with a modified primer, Pro341FB, that was paired with the original reverse primer Pro805R and tested in silico using a mismatch 0 approach and considering the taxonomic coverage as a selection metric. As shown in Fig. 1, the primer pair Pro341FB + Pro805R (TAKB_v3v4) proved a very modest 0.007% coverage increase for archaea with respect to primer Pro341F + Pro805R (TAK_v3v4), while we found a noticeable 1% coverage increase for bacteria. Primer Pro341FB was theoretically able to amplify a total of 59% of the approximately 3.2 million sequences present in the bacteria data bank. In particular, primer Pro341FB was found to target phyla that were completely ignored by the primer Pro341F. As shown in Fig. 2, phyla which received an increase in coverage of more than 25% were found to be Chlamydiae (41%), Lentisphaerae (76%), Omnitrophica (63%), Parcubacteria (44%), candidate division WPS-1 (46%) and, importantly for this study, Planctomycetes (46%). Descending the taxonomic tree from phylum Planctomycetes to genera involved in anaerobic ammonium oxidation (anammox) we systematically observed an increase in coverage (class Planctomycetia 45%, order Candidatus Brocadiales 28%, family Candidatus Brocadiaceae 28%, genus Candidatus Brocadia 75%). As shown in Fig. 3, all anammox bacteria (genera Candidatus Brocadia, Candidatus Kuenenia, Candidatus Anammoxoglobus, Candidatus Jettenia and Candidatus Scalindua), that were almost neglected by the original Pro341F primer (red bars, secondary y-axis), resulted, as expected, markedly more covered when the Pro341FB primer was used. Major numerical details on the results of this comparison are available in supplementary materials (Supplementary data S2).
Figure 2

Improvement of taxonomic coverage by the newly optimized primer Pro341FB. The coverage percent value refers to the proportion between the total RDP database sequences annotated with the specific taxonomic rank and those that proved to generate an amplicon using the currently optimized Pro341FB primer and the original Pro341F (white bars), paired with the common reverse primer Pro805R. Only taxonomies with a difference in coverage higher than 25% are shown. The suffixes P, C, O, F and G refers to the ranks phylum, class, order, family and genus, respectively. Black columns mark taxonomic ranks associated with anammox bacteria.

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Figure 3

Comparison of the theoretical coverage performance between the new Pro341FB (black, left axis) and the original Pro341F (red, right axis). The Brocadiaceae family consists of 5 genera, 4 of which are represented in the figure. A further genus named Candidatus jettenia is not present since no high-quality sequence (i.e.  > 1200 bp) was present in RDP database.

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Testing primer variations by NGS on selected communities
In order to verify the increase in performances for anammox communities by our modified forward primer Pro341FB, we collected the microbial community samples from 5 different origins, namely activated sludges from a domestic WWTP plant (SCS), activated sludges from a tannery WWTP (CDS), aerobic granular sludge (AGS), and partial nitrification anammox granular sludge (PNA) from pilot scale reactors fed with domestic wastewater. For the two former plants, samples from their anaerobic digestion reactors were also collected (SCD and CDD, respectively). The samples were collected from bioreactors operated in widely different conditions (suspended vs biofilm and aerobic/anoxic vs anaerobic) and fed with various substrates, in order to allow the validation of the protocol in most of the selective conditions typical for microbial communities in wastewater treatment. The total DNA of all communities was extracted and amplicons were generated using the primer pairs Pro341F + Pro805R or Pro341FB + Pro805R. As shown in Fig. 4, NGS revealed that the percentage of identified phyla was almost the same in all samples but in the PNA, where anammox communities were largely underestimated by Pro341F with respect to Pro341FB. As a confirmation it has been recently reported that anammox species largely dominate the granule population1, underlining the underestimation by the original Pro341F primer.
Figure 4

NGS verification of the improvement of coverage percent for members of the Brocadiaceae family coverage by the optimized Pro341FB primer. The tested samples (CDS, CDD, SCS, SCD, AGS, PNA, see text for a description) were amplified with Pro341F (suffix 1) or Pro341FB (suffix 2). Samples marked with the suffix 2 are systematically higher in Brocadia associated ranks.

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Physicochemical properties
In all sampled environments, Typha angustifolia was the main emergent macrophyte and formed almost monospecific communities covering large surface areas. Moreover, sampled environments were located in a relatively small geographical area, thus minimizing weather effects (temperature, average rain, and solar radiation). Nevertheless, physicochemical conditions of the chosen environments were essentially different in terms of nutrient concentrations, salinity and redox potential. Unfortunately, nutrient concentrations in water were not recorded at the moment of sampling. Nitrate and ammonia concentrations in the two studied systems are relatively variable (ranging from undetectable to above 10 mg/L for NO3− and NH4+, NO2− is not detected above 0.2 mg/L) and highly influenced by the performance of the WWTP in the Empuriabrava area, or nutrient discharges due to agricultural activities in the Baix Ter area10, 35, 36. Water temperatures were around 26 °C, being slightly lower in Bassa de les Tortugues and higher in the Daró river mouth (Table 1). When samples were grouped according to the location (i.e. FWS-CW and Baix Ter), no significant differences of temperature were observed (U Mann–Whitney test, p  > 0.05). Sampled environments spanned along a salinity gradient, ranging from slightly saline (conductivity values of 11.95 mS/cm2, estimated salinity 6.84 ppt), such as Bassa de les Tortugues, to low salinity fresh water, such as Rec Coll (0.823 mS/cm2, salinity 0.40 ppt). Water in the Empuriabrava FWS-CW showed typical conductivity values for the system in summer37.
Table 1 Main water physicochemical parameters in the studied sites.
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Water oxygen concentration, pH and Redox values were significantly different between the two geographical locations (U Mann–Whitney test, p  More

Data collection
We hypothesized that the evolution of underground species affected protein networks in a unique manner in which various types of protein domains served as building blocks of protein evolution. To study the evolution of protein networks, we collected genomic, proteomic, and protein domain classification data, namely, fully sequenced genomes with coding sequences and annotated proteomes, together with protein ortholog assignments, from 32 species living in three broad ecological niches, namely subterranean, fossorial, and aboveground (Table 1, and listed in Materials and Methods). We first sought overall statistics regarding the number of proteins and the number of corresponding orthologous protein families. Overall PPI statistics were calculated, including those predicting PPIs in organisms for which experimentally verified PPI data are missing. We used the KEGG orthologs (KO) group of orthologous proteins in KEGG (Kyoto Encyclopaedia of Genes and Genomes)17 to reproduce gain and loss of protein domains in orthologous proteins. We collected 1,350,898 proteins from the studied organisms that belong to 624,787 KO groups (10,314 are unique ortholog groups). The matching number of interactors and networks for every organism were exhaustively calculated for all these proteins (Fig. 1). We found that 361,615 of the 1,350,898 proteins are distributed among 5,879,879 (predicted and real) PPIs. The mean number of interactors per protein within each habitat, namely, aboveground (A), fossorial (F), and subterranean (S) were 32.07, 32.48, and 32.67, respectively (see details in the supplementary results and in Tables S1–S3). This shows that the number of interactors per protein is similar for organisms from different ecologies.
Table 1 All organisms included in the PASTORAL database, with a complete number of proteins in the corresponding proteome.
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Figure 1

The study overview. Fully sequenced genomes with coding sequences and annotated proteomes were collected from 32 species living in three broad ecological niches: subterranean, fossorial, and aboveground. For collected proteins (1,350,898), protein domains, protein disordered regions, and KEGG orthologous annotation (624,787) were predicted using the Pfam search tool53 along with HMMER60 , IUPred2A44, and the KEGG database17, respectively. Next, 5,879,879 PPIs were evaluated using our previously developed ChiPPI tool15. Briefly, ChiPPI uses a domain-domain co-occurrence table. When a certain domain is missing, ChiPPI evaluates the corresponding missing interactors in the PPI network15, based on real PPI data (363,816) as obtained from BioGrid (release 3.4.163)16. Finally, PPI data are organized in PASTORAL, a dedicated database.

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Additional analysis of PPI features for orthologous proteins (516 KOs) common to all organisms were similar across ecologies. These features included the number of interactors, the number of PPIs, and global/individual clustering coefficients (supplementary results, Figures S1, S2, Table S4). Thus, we studied PPI properties of genes encoding products related to stresses that differ across the ecologies considered, such as hypoxia. Our findings confirm our hypothesis that the design principles of the evolution of underground species involve various types of protein domains serving as building blocks of protein evolution.
Analysis of the PPIs of stress-response proteins cluster organisms according to habitat
To examine how organisms might have adapted to the various stresses in each habitat, we analyzed mutations and changes in the PPIs encoded by stress response genes. Heat-shock, hypoxia, and circadian stresses differ considerably between aboveground and underground environments, and are likely to drive evolutionary selection of proteins that provide optimal function in each niche1,9. We assumed that organisms subject to a shared ecological experience would face similar environmental stresses. PPI networks of stress-related proteins would thus be expected to differ substantially according to ecology.
To test our hypothesis, we performed clustering analysis of all the organisms included in our study, based on mutations and PPI network features, and compared the results for each classification. Such analysis included all orthologous stress-response, hypoxia, heat-shock, and circadian stress proteins (Table 1). In total, 85,173 PPIs related to stress-response proteins were found to be distributed among 1,103 proteins. These comprised of 730 heat shock proteins in 71,940 PPIs, 254 hypoxia-related proteins in 10,256 PPIs, and 119 circadian proteins in 2,977 PPIs (Table 1, Tables S1–S7). All orthologous stress-response genes (KO groups) were obtained by querying the KEGG database with the terms “heat-shock”, “hypoxia”, and “circadian” terms. The results are listed in Table 2, while the corresponding lists of proteins are found in Tables S5, S6 and S7, respectively.
Table 2 KEGG Orthologs: Heat-shock (upper), hypoxia-related (middle) and circadian (bottom) proteins.
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Next, we performed clustering analysis based on sequence mutations and PPI features for the full set of heat-shock, hypoxia, and circadian stress proteins (Table 2). Remarkably, proteins related to hypoxia, heat-shock, and circadian stresses in the 32 organisms studied did not all cluster according to shared ecology based on sequence mutations (Fig. 2A) but significantly did so on the basis of “PPI network clustering coefficient” (Fig. 2B–D; p value (AU)  More

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