Nature Communications volume 14, numero articolo: 2033 (2023) Citare questo articolo
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L’ossidazione del tiosolfato da parte dei microbi ha un impatto importante sul ciclo globale dello zolfo. Qui forniamo la prova che i batteri all’interno di vari lignaggi Roseobacter sono importanti per l’ossidazione del tiosolfato nei biofilm marini. Isoliamo e sequenziamo i genomi di 54 ceppi di Roseobacter associati al biofilm, trovando cluster di geni sox conservati per l'ossidazione del tiosolfato e plasmidi, indicando uno stile di vita specifico di nicchia. L’analisi dei dati metagenomici dell’oceano globale suggerisce che i ceppi di Roseobacter sono abbondanti nei biofilm e nei tappetini su vari substrati, tra cui pietre, superfici artificiali, radici di piante e camini di sfiato idrotermali. L'analisi metatrascrittomica indica che la maggior parte dei geni sox attivi nei biofilm appartengono a ceppi di Roseobacter. Inoltre, dimostriamo che i ceppi di Roseobacter possono crescere e ossidare il tiosolfato in solfato sia in condizioni aerobiche che anaerobiche. Le analisi trascrittomiche e proteomiche di membrana dei biofilm formati da un ceppo rappresentativo indicano che il tiosolfato induce l'espressione del gene sox e alterazioni nella composizione proteica della membrana cellulare e promuove la formazione di biofilm e la respirazione anaerobica. Proponiamo che i batteri del gruppo Roseobacter siano i principali ossidanti del tiosolfato nei biofilm marini, dove è preferito il metabolismo anaerobico del tiosolfato.
Il ciclo dei composti inorganici dello zolfo da parte dei microbi rappresenta un importante progresso biogeochimico. La trasformazione dello zolfo coinvolge il tiosolfato come intermedio, che è abbondante negli ambienti marini1,2. È noto che i batteri ossidanti lo zolfo includono diversi batteri autotrofi di vari gruppi, come SUP05, SAR324, BS-GSO2 e Chlorobi3. Questi batteri utilizzano la via multienzimatica sox per l'ossidazione del tiosolfato4,5 e possono crescere autotroficamente utilizzando il tiosolfato come donatore di elettroni per la produzione di energia6. I prodotti finali dell'ossidazione del tiosolfato differiscono tra i diversi batteri, poiché alcuni batteri organotrofi obbligati (ad esempio, Pseudomonas stutzeri e Catenocossus thiosyclus) ossidano il tiosolfato in modo incompleto a tetrationato, mentre altri eterotrofi (ad esempio, Bosea thiooxidans e Limnobacter thiooxidans) ossidano il tiosolfato a solfato, il forma di zolfo più ossidata, in un percorso simile comune tra i batteri autotrofi ossidanti lo zolfo7. Trovato per la prima volta nei batteri litoautotrofi Paracoccus pantotrophus5,8, il sistema enzimatico ossidante dello zolfo (SOX), un tipico sistema multienzimatico periplasmatico, è il mediatore più noto dell'ossidazione del tiosolfato. Per quanto riguarda l'utilizzo degli accettori di elettroni e la distribuzione di nicchia, gli ossidanti aerobici del tiosolfato sono stati isolati dal massimo profondo della clorofilla9, dall'acqua di mare costiera10 e dai sedimenti marini costieri11, mentre gli ossidanti anaerobici del tiosolfato sono stati recentemente segnalati nei bacini marini anossici12, nelle zone oceaniche con minimo di ossigeno13 e nelle sorgenti idrotermali14. Inoltre, le condizioni ambientali influenzano i principali prodotti della produzione di tiosolfato. Ad esempio, nei sedimenti marini costieri, il tiosolfato viene ossidato in proporzioni variabili di tetrationato e solfato, nonché di zolfo elementare, a seconda delle condizioni solfidriche e ossigenate11.
Essendo una nicchia importante per molti microbi, i biofilm costituiscono il 40% della biomassa microbica oceanica15. Molti microbi formano biofilm quando iniziano ad attaccarsi a qualsiasi superficie immersa nell'acqua, come materiali artificiali, superfici rocciose, pelli di animali e neve marina15,16. Una comunità di biofilm marino può essere composta da centinaia di specie microbiche e strutturalmente il biofilm è caratterizzato da eterogeneità in termini di concentrazione di ossigeno stratificato, nutrienti e molecole di segnalazione17. I nostri studi recenti18,19 hanno suggerito che i biofilm marini costituiscono una banca di taxa e funzioni sconosciute, contenente oltre 7000 specie batteriche non altrimenti presenti nel microbiota dell’acqua di mare. Inoltre, si ritiene che i biofilm marini siano coinvolti in importanti processi biogeochimici, come la conversione della materia organica disciolta, la rimineralizzazione delle particelle e il passaggio dei nutrienti dalle acque superficiali agli oceani profondi20. Tuttavia, probabilmente a causa delle complesse strutture della comunità fisica e delle composizioni tassonomiche, l’ossidazione del tiosolfato nei biofilm marini rimane in gran parte sconosciuta, in particolare in relazione ai contributi dei diversi taxa e alle loro caratteristiche metaboliche rilevanti. Domande specifiche riguardano quali batteri contribuiscono maggiormente all’ossidazione del tiosolfato nei biofilm marini e come conducono questo processo.
89% identity in the 16 S rRNA gene, are heterotrophs found worldwide in marine ecosystems. The so far discovered Roseobacter group comprises 327 species and 128 genera21, represented by Ruegeria (e.g, Ruegeria pomeroyi DSS-322, a model strain), Phaeobacter (well-known strains for the production of tropodithietic acid23), Sulfitobacter (widely-distributed strains in the global ocean24), and Loktanella (adapted to the polar regions25). Certain Roseobacter strains are reported to be associated with biofilms on surfaces of marine algae, invertebrates, and particles, although most of the isolated Roseobacter strains are free-living. For instance, analyses of the Tara ocean data suggested that Ruegeria mobilis strains occur in 40 and 6% of samples of the particle-associated fraction and the free-living fraction, respectively26, implying their preference for a biofilm-associated lifestyle. Physiologically, Roseobacter strains are often known for their metabolic versatility, mainly involving carbon monoxide oxidation, aromatic compound degradation, secondary metabolic production, and oxidation of sulfur compounds27,28,29. The genomes of several isolated Roseobacter strains contain sox genes, although their ability to oxidize thiosulfate has not been experimentally demonstrated. Moreover, as thiosulfate oxidation is affected by the availability of electron acceptors, it is possible that the oxygen gradient in biofilms may promote the development of novel thiosulfate-oxidizing bacteria./p>0.1 mM) in the cultures was observed for the six strains (M382, M583, M619, S051, S190, and S2214) possessing the sox genes by barium precipitation after removing bacterial cells from the cultures, and sulfate production was detected (Supplementary Fig. 19). In particular, the sulfate production rate of Rhodobacteraceae sp. M382 is shown (Fig. 4a). This strain was selected as a model for the following analyses and experiments, because it probably represents a new genus and its genetic manipulation can be achieved. In both conditions, the sulfate concentration in M382 cultures increased along with the bacterial growth (Fig. 4a, b). In contrast, the sulfate concentrations in the cultures of two mutant strains of M382, M382-ΔsoxX, and M382-ΔsoxA, showed a slight decrease (Fig. 4a, b), confirming the role of sox genes in thiosulfate oxidation and sulfate production. The slight decrease in sulfate concentration may be due to assimilatory consumption of sulfate originally present in seawater. To confirm the production of barium sulfate, the pellet of a tested sample was examined by scanning electron microscopy (SEM) (Fig. 4c), and the dominant spectra of barium, sulfur, and oxygen were observed (Fig. 4d). These results suggested that the biofilm Roseobacter strains use sox genes for thiosulfate oxidation under both aerobic and anaerobic conditions. These results also showed that when grown planktonically, mutation of the soxX or soxA genes did not affect the growth of M382 (Fig. 4a, b), and motivated us to examine the growth of wild-type M382, M382-ΔsoxX, and M382-ΔsoxA in the biofilm state. After culture under aerobic or anaerobic conditions in artificial seawater media with 10 mM thiosulfate in biofilms, the wild-type strain displayed a significantly higher cell density than the two mutants (Supplementary Fig. 20), suggesting that thiosulfate oxidation may affect the bacterial growth when they have formed biofilms rather than grown planktonically./p>2 and P value <0.05 by Student’s t test) up-regulated by thiosulfate, 58 KEGG genes were down-regulated, while 4607 KEGG genes remained unchanged (Supplementary Fig. 21). Notably, the transcription of all sox genes was induced by thiosulfate (Fig. 5a). For example, there was over 14-fold induction of soxC transcription (Fig. 5a). Moreover, several genes related to anaerobic respiration were also induced by thiosulfate, including the ferredoxin-type protein-encoding gene napH (K02574), D-lactate dehydrogenase dld (K03777), the cytochrome c biogenetic gene ccdA (K06196), and anaerobic dimethyl sulfoxide reductase dmsC (K07308) (Fig. 5b). In addition, two ORFs encoding PorD (K11069), the substrate-binding protein of the spermidine/putrescine transport system, were up-regulated by thiosulfate, as well as an ORF encoding the outer membrane protein OmpW (K07275) (Fig. 5c), which has been reported to play a role in biofilm formation44,45. As examples, PotD is a spermidine/putrescine-binding periplasmic protein, and its overexpression strongly promotes biofilm formation in Escherichia coli44, and the mutant strain ΔompW of Acinetobacter baumannii showed reduced biofilm formation45. The full list of the genes with significantly higher transcription levels in the thiosulfate culture are shown in Supplementary Fig. 22, while the down-regulated genes are shown in Supplementary Fig. 23. It is worth mentioning that transcription of the sat gene (K00958) and three cys genes (K00381 and two K00390 genes) were down-regulated by thiosulfate (Supplementary Fig. 23), suggesting the inhibitory effect of thiosulfate on sulfate reduction./p>2 and P value <0.05 (*P value <0.05; **P value <0.01; ***P value <0.001). Exact P values in a: 0.0002, 0.0005, 1.7E-05, 0.0136, 0.0031, 0.0013, 0.0225; b: 0.0011, 0.0032, 7.5E-07, 1.5E-06, 7.8E-08, 3.8E-06, 0.0001; c: 0.0067, 0.0032, 0.0039, 0.0251; d: 4.5E-05, 0.0014, 0.0173, 0.0015, 0.0006, 0.0008, 0.0183, 0.0120; e: 0.0469, 0.0353, 0.0255; f: 0.0006, 0.0001, 0.0013, 0.0002, 0.0053, 0.0075, 0.0004, 0.0048, 0.0023, 0.0112. Source data are provided as a Source data file./p>9000 bp), and Illumina sequencing was performed on the NovaSeq 6000 system to generate 2 Gb of data (read length = 150 bp). Preliminary assembly and correction were performed with SMRT Link v5.0.1 (CCS = 3, minimum accuracy >0.99), and then corrected by the Illumina data using Minimap2 (Minimap2: pairwise alignment for nucleotide sequences). In detail, the PacBio-derived contigs were mapped with the Illumina reads, and the locations without alignment were corrected according to the contigs assembled from Illumina reads. The chromosome and plasmid sequences were distinguished based on the reads coverage and screened by BLASTn to form a complete genome. Genome annotation was performed on a local Linux platform. Ribosomal RNA genes (rRNA) and transfer RNA genes (tRNA) were predicted using the software Barrnap (https://github.com/tseemann/barrnap) and Aragorn64, respectively. ORFs were predicted using Prodigal (version 2.60)65 in a single-genome analysis model with close-end ORF prediction. For phylogenetic analysis, 31 essential marker genes (dnaG, frr, infC, nusA, pgk, pyrG, rplA, rplB, rplC, rplD, rplE, rplF, rplK, rplL, rplM, rplN, rplP, rplS, rplT, rpmA, rpoB, rpsB, rpsC, rpsE, rpsI, rpsJ, rpsK, rpsM, rpsS, smpB, and tsf) were extracted from the genomes using AMPHORA266. The protein sequences of these marker genes were aligned using MEGA (version 6.05)67 to construct a maximum-likelihood tree under the Jones–Taylor–Thornton mode. The marker genes were aligned individually and then concatenated to generate alignments for tree construction. The tree was built in MEGA67 and bootstrap values were calculated with 500 replicates. ANI was calculated using the software fastANI68 installed in a local Linux system. Two different species show <95% ANI69, and two different strains have <99% ANI70. For functional gene annotation, the protein sequences of a given genome searched with BLASTp (E-value <1e-7) against the KEGG database (2022 version). Metabolic pathways were reconstructed using the online server KEGG Mapper (https://www.genome.jp/kegg/mapper.html)./p> 1 were used as the thresholds of significance. Differentially expressed genes were illustrated using volcano plots drawn in MS Excel and heatmaps drawn with Cluster 3.0 (hierarchical clustering with average linkage79) and Java TreeView80./p>2 and P value <0.05./p>
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