Surface water samples were collected at three stations in the Gulf of Mexico along a transect, i.e., one nearshore (NS), one offshore (OS), and one open ocean (OO) station (Fig. 1). The measured in situ environmental variables varied among NS, OS, and OO (Lu et al. 2020; Supplementary Table S1). From the NS site that is distant from the shore (OS and OO), the salinity increased, while nitrate (NO3-), nitrite (NO2-), dissolved organic carbon (DOC), dissolved nitrogen (DN), and water temperature (Temp) decreased (one-way ANOVA, P < 0.05). Opposite from the other nutrients, concentrations of ammonium (NH4+) increased and had the highest values at OS (one-way ANOVA, P < 0.05). HPLC was used to detect putrescine (PUT), spermidine (SPD), and spermine (SPM) (Lu et al. 2014; Fig. 2A). SPD (3.9–5.6 nmol/L) and SPM (4.4–5.5 nmol/L) were measured at all three sites with no significant spatial difference (one-way ANOVA, P > 0.05; Fig. 2A). PUT was not detected at any site in the present study. The individual and total concentrations of PAs here were similar to previously reported values from marine environments (Lu et al. 2014; Nishibori et al. 2001, 2003) but appeared to be less diverse.
Figure 1. The sampling sites of NS, OS, and OO in the Gulf of Mexico in May, 2013. The depth of water column at each site is listed in the parentheses
Figure 2. A The concentrations of individual PA compounds in situ environment, and B the degradation rate of individual PA compounds in microcosm experiment. The error bar represents standard error
Duplicate microcosms were set up on the deck of the sampling cruise ship using NS, OS, and OO samples and amended with 200 nmol/L (final concentration) of PUT, SPD, SPM, or an equal volume of diH2O (serving as controls, CTL). After 48 h of incubation at ambient temperature and light, residual PAs in each of the microcosms were measured and used to calculate PA degradation rates (Fig. 2B). Significant PA degradation (50–100%) was observed in all microcosms. Comparable rates of PA degradation by marine bacteria have been observed in the Atlantic Ocean (Höfle 1984; Lu et al. 2015). No significant difference of PA degradation rate was observed among microcosms of different sites and PA amendments (Fig. 2B).
Metagenomes of samples from each of the incubated microcosms (48 h) were sequenced, which yielded a total of 6, 700, 391 Illumina Mi-Seq sequences with an average length of 363 bp (Table 1). Samples for PUT metagenomes in the OO sites were lost during transportation and were not included in the analysis. Ribosomal RNA (rRNA) sequences accounted for 0.7–1.5% of the metagenomic sequences, which is typical for metagenomes (Mou et al. 2008). A total of 6, 564, 670 sequences were identified as putative protein-coding sequences, 62.0% of them further received annotations to the gene level. The gene sequences were then functionally classified into 1742–2289 unique clusters of orthologous groups (COGs, 26.8–50.8%), and 150–184 unique Kyoto encyclopedia of genes and genomes (KEGG) pathways (19.2–33.6%).
Sample Treatment No. of total reads Ave. read length (bp) No. (%) of rRNA genes No. of functional genes Number (%) of functional genes categorized COG KEGG SEED RefSeq NS CTR 667, 229 352 5782 (0.9) 651, 430 195, 916 (30.1) 151, 370 (23.2) 278, 781 (42.8) 336, 018 (51.6) PUT 690, 505 368 5172 (0.7) 675, 272 187, 977 (27.8) 144, 906 (21.5) 266, 353 (39.4) 326, 610 (48.4) SPD 572, 549 364 8652 (1.5) 562, 633 158, 693 (28.2) 122, 385 (21.8) 229, 394 (40.8) 272, 623 (48.5) SPM 730, 564 363 7220 (1.0) 717, 015 175, 105 (24.4) 142, 492 (19.9) 265, 289 (37.0) 331, 892 (46.3) OS CTR 627, 823 375 6185 (1.0) 618, 570 281, 642 (45.5) 200, 375 (32.4) 400, 261 (64.7) 450, 690 (72.9) PUT 541, 964 364 7153 (1.3) 533, 190 235, 835 (44.2) 164, 547 (30.9) 366, 391 (68.7) 401, 489 (75.3) SPD 417, 359 356 4926 (1.2) 408, 875 109, 554 (26.8) 786, 44 (19.2) 178, 124 (43.6) 202, 107 (49.4) SPM 619, 496 369 5071 (0.8) 610, 849 269, 610 (44.1) 201, 170 (32.9) 347, 919 (57.0) 412, 019 (67.5) OO CTR 446, 460 371 3716 (0.8) 433, 953 198, 682 (45.8) 136, 013 (31.3) 270, 245 (62.3) 298, 374 (68.8) SPD 771, 798 347 8988 (1.2) 749, 701 344, 920 (46.0) 238, 692 (31.8) 511, 034 (68.2) 550, 155 (73.4) SPM 614, 644 368 9001 (1.5) 603, 182 306, 355 (50.8) 202, 863 (33.6) 462, 950 (76.8) 482, 365 (80.0)
Table 1. Statistics of experimental metagenomes
NMDS and ANOSIM analyses were performed based on the relative abundances of major (≥97%) COGs among PUT, SPD, and SPM metagenomes. They consistently showed that metagenomes of NS, OS, and OO bacterioplankton were well separated (rANOSIM=0.65, P < 0.05; Fig. 3). The distinct COG contents between NS and OS/OO sites suggest that there may be a variety of metabolic strategies among sites with different environmental conditions (Lu et al. 2020).
Figure 3. The non-metric multidimensional scaling (NMDS) plot based on the relative abundance of major COGs in metagenomes of nearshore (NS; triangle), offshore (OS; square), and open ocean (OO; circle) in the Gulf of Mexico
Xipe-TOTEC analysis identified 129–197 COGs that were significantly enriched in the PUT metagenomic libraries relative to the CTR libraries in the NS site. The number of COGs increased to 249–296 in OS and then to 289–357 in the OO site. A total of 12 of the COGs have been shown to be involved in polyamine transformation steps, such as PA synthesis (3 COGs), transport (6 COGs), and degradation (3 COGs) (Fig. 4; Supplementary Table S3). The distribution of these PA-related COGs was site- and PA compound-specific. Specifically, the OS site had the highest number (up to 10 in total) of PA-related COGs among the three sites. In line with overall COG data, this again indicates that PA compounds may be metabolized via different pathways (Chou et al. 2008; Dasu et al. 2006; Mou et al. 2010) by marine bacterioplankton in a given location. In addition, most of the PA-related COGs were found in SPM (7 COGs) metagenomes (Fig. 4), indicating the importance and universal distribution of SPM along the studied transect.
The taxonomic affiliations of all enriched COGs, i.e., PA-responsive COGs, in metagenomic libraries, were significantly different among sampling sites and PA compounds (i.e., PUT, SPM, and SPD) at the family level, as revealed by NMDS (data not shown) and ANOSIM (rANOSIM=0.87, P < 0.05) analyses. In the NS metagenomes, Rhodobacteraceae (Alphaproteobacteria) was generally dominating in PUT (14.4% in average), SPD (15.0%), and SPM (21.6%) libraries (Fig. 5). Rhodobacteraceae-affiliated roseobacters are known for their high abundance and strong ability in processing plankton-derived DOC compounds (González et al. 2000; Hahnke et al. 2013). These results are consistent with a previous metatranscriptomic study, suggesting the importance of roseobacters in PA transformations in nearshore marine environments (Lu et al. 2020).
Figure 5. Taxonomic binning of the protein-encoding sequences in significantly enriched COGs at bacterial family level in the PA amended metagenomes (PUT, SPD, and SPM). Rows were organized using the hclust method in R
In the OS metagenomes, PA-responsive COGs were most affiliated with three Gammaproteobacteria families, i.e., Alteromonadaceae (14.6%), Pseudomonadaceae (13.6%, ), and Alcanivoracaceae (13.2%) in the PUT library (Fig. 5). In the SPD library, unclassified Chroococcales (12.4%; Cyanobacteria) and Planctomycetaceae (7.6%; Planctomycetes) were the most abundant PA-responsive families (Fig. 5). In SPM, Prochlorococcaceae (13.0%; Cyanobacteria), Rhodobacteraceae (9.2%, Alphaproteobacteria), and Comamonadaceae (9.0%; Betaproteobacteria) were predominant (Fig. 5).
In the OO metagenomes, PA-responsive COGs were again mostly affiliated with Gammaproteobacteria but with different families from those in the OS metagenomes; these included Idiomarinaceae (13.7%, ) and Shewanellaceae (13.0%) in the SPD library, and Pseudoalteromonadaceae (55.4%, ) in the SPM library (Fig. 5). The importance of various Gammaproteobacteria in transforming PAs in non-coastal sites has also been suggested in a study performed at the South Atlantic Bight (Lu et al. 2015, 2020). No PA-responsive COGs were found to be affiliated with SAR11, although this taxon dominates open ocean environments and has been suggested to be involved in PA transformations in a metaproteomic study (Sowell et al. 2008).
Variations in the relative abundance of responsive bacterioplankton to different PA compounds (ANOVA, P < 0.05) were observed in this study; this agrees with the findings of a previous study, which identified different PA-responding bacterial families between PUT and SPD transformation (Lu et al. 2015). However, a metatranscriptomic study performed at the same Gulf of Mexico sites indicates that PUT, SPM, and SPD may share similar taxa for their transformation (Lu et al. 2020). The metatranscriptomic study also identified that PA-responsive taxa varied between the OS and OO sites, which is also identified in the present study. This discrepancy may partly be explained by method differences, such as length of incubation time (days for the metagenomic study vs. hours for the metatranscriptomic study). More importantly, the two studies sequenced different nucleic acids, i.e., community DNAs for the metagenomic study and community mRNA for the metatranscriptomic study (Aguiar-Pulido et al. 2016; Shakya et al. 2019). Response of mRNA synthesis to external stimuli can be observed in seconds to minutes, while changes of DNA require a much longer time (days) (Aguiar-Pulido et al. 2016). However, mRNA is far less stable than DNA and some mRNA can be degraded before sample collection (Shakya et al. 2019). Moreover, different bacteria may have different sensitivity to PA compounds, some can respond in seconds, and others may take longer times.
Genes that are known to participate in processing PAs, including transporter genes (potABCDEFGH), γ-glutamylation genes (puuABCDE), transamination genes (spuC, kauB, and GabT), and SPD cleavage genes (spdH and gltA) were identified, and their relative abundance was calculated for each metagenomes (Supplementary Table S3). Among PA uptake- and degradation-related genes, the ones that were significantly enriched in PA metagenomes relative to the corresponding CTRs were designated as PA-responsive.
Responsive PA transporter genes were only identified in SPM libraries of OS and OO (OR > 1, P < 0.02; Fig. 6A). The taxonomic affiliations of these transporter genes were primarily assigned to Rhodobacteraceae (26.9% of the total assigned putative PA genes) and Alteromonadaceae (66.7%), respectively (Fig. 6B).
Figure 6. A The enriched PA degradation pathways; B the relative abundance of diagnostic PA uptake/degradation genes and their taxonomic affiliations in CTR, PUT, SPD, and SPM
Responsive PA degradation genes, however, were identified in all three PA metagenomes (PUT, SPD, and SPM) of all three sites (OR > 1, P < 0.02). At the NS site, putative γ-glutamylation genes were enriched in SPD metagenomes (OR > 1, P < 0.02; Fig. 6B), and were mostly affiliated with Rhodobacteraceae (6.0%) (Fig. 6B). In contrast, putative SPD cleavage genes were enriched in the PUT and SPM metagenomes of NS (OR > 1, P < 0.02; Fig. 6B), and the taxonomic binnings of these genes were primarily assigned to Methylophilaceae (2.8%; Betaproteobacteria) and SAR11 clade (3.3%; Alphaproteobacteria), respectively (Fig. 6B).
At the OS, putative γ-glutamylation genes were enriched in PUT and SPD metagenomes (OR > 1, P < 0.02; Fig. 6B), and were primarily binned to Alteromonadaceae (1.0%) and Plantomycetaceae (1.6%), respectively (Fig. 6B). Putative SPD cleavage genes also showed enrichment in SPD metagenomes (OR > 1, P < 0.02; Fig. 6B) and they were mainly assigned to Planctomycetaceae (1.8%) and Alteromonadaceae (1.4%) (Fig. 6B).
At the OO, putative γ-glutamylation genes were enriched in SPD metagenomes (OR > 1, P < 0.02; Fig. 6B) and the majority of the sequences were affiliated with OMG group (2.0%) (Fig. 6B). Putative SPD cleavage genes were enriched in SPM metagenomes of OO (OR > 1, P < 0.02; Fig. 6B) and were taxonomically binned to Rhizobiaceae (1.8%) and Shewanellaceae (1.8%) (Fig. 6B). Putative transamination genes were enriched also in SPD metagenomes (OR > 1, P < 0.02; Fig. 6B) and were mostly affiliated with Alteromonadaceae (3.2%) (Fig. 6B). No genes of the PA transamination pathway were identified as PA-responsive in either NS site or OS site.
Results of PA-responsive gene analysis largely agree with the COG gene results on the diversity of bacterial taxa that are potentially involved in PA transformation (Fig. 5), including families of Proteobacteria (alpha, beta, and gamma-lineages), Planctomycetes and Cyanobacteria. At the family level, Rhodobacteraceae of Alphaproteobacteria consistently appeared to be the most important in PA transformation at all sites and for all tested PA compounds. In addition, these two sets of results both indicate that PA-responsive bacterioplankton taxa of individual PA compounds can be site-specific. The PA-responsive gene analysis, recovered genes of SAR11 (Alphaproteobacteria) from most PA metagenomes and these genes were mostly affiliated with transporter genes. The indicated importance of SAR11 in PA transformation is consistent with the previous studies (Lu et al. 2020; Sowell et al. 2008).
The absence and relatively low abundance of PA transamination genes in the PA-responsive gene groups at the NS and OS sites suggests a minor importance of this pathway in PA transformation in the coastal regions of the Gulf of Mexico. This result contrasts with the finding of a previous metatranscriptomic study of coastal PA-transforming bacterioplankton in the South Atlantic Bight, in which transamination dominated the PUT and SPD degradation (Mou et al. 2011). This reveals large-scale spatial differences in PA transformation.
Similar to the COG-gene-based analysis, results of PA-responsive gene analysis of metagenomes had some different findings from the previous metatranscriptomic study (Lu et al. 2020). For example, in this study, PA transporter genes were responsive to the PA addition in the OS and OO sites; however, they were only responsive in the NS site in the metatranscriptomic study. In addition, in the NS site, this study found that γ-glutamylation was most important in transforming PAs. However, the metatranscriptomic study identified the transamination pathway as the most important at the same site. We again attributed these different results mostly to method differences described in the above section. Nonetheless, most results of this metagenomic and previous metatranscriptomic studies were consistent (Lu et al. 2020) and allow a better understanding of PA transformations of individual compounds at coastal and open ocean environments.