Insights into ecological roles and potential evolution of Mlr-dependent microcystin-degrading bacteria

Science of the Total Environment 710 (2020) 136401

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Insights into ecological roles and potential evolution of Mlr-dependent microcystin-degrading bacteria Xian Zhang a,⁎, Fei Yang a,b, Lv Chen a, Hai Feng a, Shiqian Yin c, Mengshi Chen d a

Department of Occupational and Environmental Health, Xiangya School of Public Health, Central South University, Changsha, China Key Laboratory of Hunan Province for Water Environment and Agriculture Product Safety, Central South University, Changsha, China School of Environmental Science and Engineering, Qilu University of Technology, Jinan, China d Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China b c

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• 16S rRNA-based phylogeny reevaluating the taxonomy of MCdegrading bacteria • Genome-wide study strongly suggesting the genetic differences as to gene repertoire • Study on metabolic profiles revealing the presence of phenylacetate-related genes • Evolutionary analysis indicating the potential recruitment of functional genes • Schematic model for ecological roles of Mlr-dependent MC-degrading bacteria

a r t i c l e

i n f o

Article history: Received 11 October 2019 Received in revised form 12 December 2019 Accepted 27 December 2019 Available online 03 January 2020 Editor: Fang Wang Keywords: Microcystins Bacterial biodegradation Phylogeny Genome-wide comparison Metabolic potential

⁎ Corresponding author. E-mail address: [email protected] (X. Zhang).

https://doi.org/10.1016/j.scitotenv.2019.136401 0048-9697/© 2018 Elsevier B.V. All rights reserved.

a b s t r a c t Over decades many studies have focused on the biodegradation of microcystins (MCs), and some Mlr-dependent MC-degrading bacteria were recorded, but the ecological functions, metabolic traits, and potential evolution of these organisms remain poorly understood. In this study, 16S rRNA-based phylogeny unraveled a wide range of genetic diversity across bacterial lineage, accompanied by re-evaluation of taxonomic placement of some MC-degrading species. Genome-wide comparison showed that considerable genes unique in individual organisms were identified, suggesting genetic differentiation among these Mlr-dependent MC-degrading bacteria. Notably, analyses of metabolic profiles first revealed the presence of functional genes involved in phenylacetate biodegradation in the specialized genomic regions, and mlr gene cluster was located around the neighborhood. The identification of transposable elements further indicated that these genomic regions might undergo horizontal gene transfer events to recruit novel functionalities, suggesting an adaptive force driving genome evolution of these organisms. In short, phylogenetic and genetic content analyses of Mlr-dependent MC-degraders shed light on their metabolic potential, ecological roles, and bacterial evolution, and expand the understanding of ecological status of MCs biodegradation. © 2018 Elsevier B.V. All rights reserved.

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X. Zhang et al. / Science of the Total Environment 710 (2020) 136401

1. Introduction Toxic products (such as cyanotoxins) produced by harmful cyanobacterial blooms have been frequently found in eutrophic aquatic environments. Especially, bloom-forming genera including Planktothrix (Christiansen et al., 2003; Zhang et al., 2019) and Microcystis (Yan et al., 2004) have the potential to intracellularly synthesize microcystins (MCs). It has been commonly recognized that MCs are the most toxic and ubiquitous cyanotoxins that are known for carcinogenicity to hepatocytes. These toxic and widespread MCs poison the drinking water for human and animals, and thus challenge the ecological safe and global public health. Among over 240 variants (Janssen, 2019), MC-Leu(L) Arg(R) was acutely toxic and the most potent hepatotoxin, followed by MC-Arg(R)Arg(R) and MC-Tyr(Y)Arg(R) (Sivonen and Jones, 1999; Merel et al., 2013). A chemically stable structure of monocyclic heptapeptide, cyclo-(D-Ala(1)-R(12)-D-iso-MeAsp(3)-R(24)-Adda(5)-D-isoGlu(6)-Mdha(7)-), enables MCs to resist many natural factors, such as high temperature, extreme pH, and non-specific enzymes (Rastogi et al., 2014). In the common eutrophic water reservoirs, noteworthy, many indigenous organisms that can gradually degrade the MCs have been recorded, including prokaryotes (e.g., bacteria) and eukaryotes (Cousins et al., 1996; Chen et al., 2010; Christoffersen et al., 2002). Various bacterioplankton, especially these heterotrophic bacteria with MCdegradation capability, inhabit the ‘cyanosphere’ (Alvarenga et al., 2017), a region surrounding cyanobacteria, and play a critical role in turnover of the organic matter in aquatic ecosystems (Lezcano et al., 2017). In an updated review, Li et al. (2017) have summarized a vast number of MC-degrading bacteria across diverse taxonomic groups, such as α-Proteobacteria, β-Proteobacteria, and γ-Proteobacteria. These bacteria, especially members of genera Sphingomonas and Sphingopyxis, were successively identified in diverse ecosystems worldwide, dating back to 1994 (Jones et al., 1994). Previous surveys unraveled that almost all bacterial biodegradation for MCs were observed under aerobic conditions, although a few anaerobic biodegradations were also reported in certain natural sediments (Holst et al., 2003; Chen et al., 2010). Studies on genetic mechanisms for both aerobic and anaerobic MCbiodegradation have advanced our understanding of biological attenuation for MCs in nature. Evidences revealed that cyclic MC-LR was aerobically degraded by Sphingomonas sp. ACM-3962, which employed a four-gene cluster consisting of mlrA, mlrB, mlrC, and mlrD (Bourne et al., 1996, 2001). It was recognized that mlrA-C encode potential hydrolyses, while mlrD was presumed to encode an underappreciated protein (Li et al., 2017) rather than a transporter protein for uptake of MCs or MC-degrading products. Mlr-dependent biodegradation of cyclic MCs involves in step-by-step cleavages of peptide bonds, which yields Adda as a product. Furthermore, mlr gene-guided phylogeny may expand our knowledge on the origin and evolution of Mlr-dependent MC-degraders (Li et al., 2017; Zhu et al., 2016). However, not all MC-degradations are Mlr-dependent. For instance, non-mlr pathways for aerobic MCdegradation were reported in many previous studies (Su et al., 2017; Dziga et al., 2017; Manage et al., 2009; Lawton et al., 2011). In addition, a few anaerobic MC-degrading bacteria, such as ALA-1 strain (Bao and Wu, 2016), were also investigated in previous studies. Since no mlr genes were detected in both Mlr-independent aerobic biodegradation (Manage et al., 2009) and anaerobic MC-degradation (Chen et al., 2010; Bao and Wu, 2016), genetic and enzymatic mechanisms for

1

D-Ala: D-alanine. R1: highly variable L-amino acid. 3 D-iso-MeAsp: D-erythro-β-methyl-aspartic acid. 4 R2: highly variable L-amino acid. 5 Adda: (2S, 3S, 8S, 9S)-3-amino-9-methoxy-2, 6, 8-trimethyl-10-phenyldeca-4(E), 6 (E)-dienoic acid. 6 D-iso-Glu: D-glutamic acid. 7 Mdha: N-methyl-dehydroalanine. 2

these two pathways are likely to be significantly distinct from that for aerobic Mlr-dependent MC-degradation. Environmental genomics has extended their investigation far beyond the general studies of certain functional genes, allowing the characterization of the whole gene pool for any given organism. Using mlr genes as the characteristic indicator, we initially determined how many Mlr-dependent MC-degrading bacteria with sequenced genomes exist in the public database. As of August 2018, three isolates from different genera have been genomically sequenced and released (Table 1). Genome-wide analysis as an effective way improves the resolution of genetic identification, and comparative genomics provides a coherent picture of intra- and inter-species difference with respect to gene repertoire. Based on the limited genome sequences, we conducted a systematic study to first investigate their metabolic profiles, ecological roles, and underlying bacterial evolution of these Mlr-dependent MCdegraders. 2. Materials and methods 2.1. Phylogeny based on 16S rRNA genes In an earlier review (Li et al., 2017), many MC-degrading bacteria belonging to various taxonomic groups have been summarized, with some unclassified isolates and/or sequence clones. Among them, a total of 53 16S rRNA gene sequences were obtained from GenBank database. More details for these sequences were shown in Table S1. To recognize the taxonomic assignments of MC-degrading bacteria used in this study, their evolutionary relationships were re-evaluated using the phylogenetic reconstruction strategy. We first performed the similarity-based search in a quality-controlled database of 16S rRNA sequences using an online platform EzBioCloud (Yoon et al., 2017) to provide a glimpse of provisional recognition. Herein, five 16S rRNA gene sequences with relatively shorter length were excluded for phylogenetic construction. For each sequence, the top ten results with nonrepetition were selected for subsequent analysis. Using a broader dataset of 245 available sequences (Table S2), online platform MAFFT version 7 (Katoh et al., 2017) with an automatic strategy was applied for multiple sequence alignment. Maximum-likelihood (ML) phylogenetic tree was constructed using the PhyML 3.0 (Guindon et al., 2010). More details for the parameters were listed in Table S3. A constructed ML tree was finally visualized using software FigTree v1.4.3. 2.2. Whole-genome-based studies for Mlr-dependent MC-degrading bacteria Using mlr genes as the indicator, we retrieved the public databases to confirm how many sequenced genomes from Mlr-dependent MCdegrading bacteria were deposited. As a result, three complete/draft genomes available in the GenBank database were acquired (Table 1), including Novosphingobium sp. MD-1, Sphingosinicella sp. B9, and Sphingopyxis sp. C-1 (Okano et al., 2015). In order to assess the evolutionary relationships among these three MC-degraders and their closely related species, JSpeciesWS (Richter et al., 2016) with default parameters was employed to calculate the values of average nucleotide identity (ANI) (Goris et al., 2007) based on BLAST (ANIb) and MUMmer (ANIm) (Kurtz et al., 2004), and tetranucleotide frequencies (TETRA) (Teeling et al., 2004) between pairs of sequenced genomes. Furthermore, whole-genome comparison based on BLASTN algorithm was performed and visualized using software CirCos (Krzywinski et al., 2009) with the built-in parameters. Each genome was used as reference in turn, and the others were then compared to reference genome. In addition, online platforms tRNAscan-SE 2.0 (Lowe and Chan, 2016) and RNAmmer 1.2 Server (Lagesen et al., 2007) were applied for the prediction of tRNA and rRNA genes, respectively.

X. Zhang et al. / Science of the Total Environment 710 (2020) 136401

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Table 1 General features of Mlr-dependent MC-degrading bacteria with sequenced genomes.

Isolation source Accession number Genome status No. of contigs Genome size (Mbp) GC content (%) CDSs Hypothetical protein KO assignment tRNA 5S rRNA 16S rRNA 23S rRNA Transposable element Reference

Novosphingobium sp. MD-1

Sphingosinicella sp. B9

Sphingopyxis sp. C-1

Biofilm of WTF, Lake Kasumigaura, Japan BBXA00000000 Draft 34 4.62 65.82 4179 1328 (31.78%) 1894 (45.32%) 56 3 3 3 76 Unpublished

Water, Lake Tsukui, Japan AP018711 Complete 1 4.04 63.92 3810 1396 (36.64%) 1757 (46.16%) 48 1 1 1 71 Unpublished

Water, Lake Hongfeng, China BBRO00000000 Draft 2 4.58 63.73 4200 875 (20.83%) 1858 (44.24%) 46 1 1 1 48 (Okano et al., 2015)

Using in-house Perl scripts, predicted protein-coding sequences (CDSs) were extracted from bacterial genomes with GenBank formats. KEGG Automatic Annotation Server (KAAS) (Moriya et al., 2007) with default settings was applied to assign the KEGG Orthology (KO) and predict the KEGG pathways. To identify the homologous and nonhomologous genes among these three strains, sequence alignment was performed using a program PanOCT v3.18 (Fouts et al., 2012). More details for the parameters were listed in Table S3. Herein, predicted mobile genetic elements were excluded prior to the identification of homologous sequences. These common genes shared by all three genomes were then used for functional assignments via aligning against the specialized databases, i.e., the extended COG (Franceschini et al., 2013) and KEGG. Visualization for metabolic pathways common in all three strains was performed using a web-based tool Interactive Pathways Explorer (iPath) v3 (Yamada et al., 2011). Putative alien genes and their donors were predicted using the Colombo v4.0 with Sigi-HMM method (Waack et al., 2006). Furthermore, possible transposable elements as the signatures of horizontal gene transfer (HGT) were predicted using the online server ISFinder (Siguier et al., 2006) with E-value cut-off of 1e−5 and sequence identity cut-off of 35%. Finally, all alignment results were manually checked. Multiple genome sequences of genera Novosphingobium and Sphingopyxis were downloaded from GenBank database, and orthogroups (herein referred as gene families) within each genus were then identified using the program OrthoFinder v2.3.1 (Emms and Kelly, 2015) with Markov cluster algorithm. Due to the limited number of genomes available in public database, genus Sphingosinicella was excluded for the analysis of gene families. Subsequently, the program BadiRate v1.35 (Librado et al., 2012) with a ‘GD-FR-CWP’ model was applied to calculate the rates of gene gain and loss by counting gain/loss events from the minimum number of members of gene families in the phylogenetic nodes, as described in a previous study (Zhang et al., 2019). In this model, each branch has its own turnover rate. Moreover, topology of whole-genome-based phylogeny generated by CVTree3 (Zuo and Hao, 2015) was used as the reference tree, with Sphingomonas wittichii RW1 as the outgroup. 2.3. Comparative analyses for genomic regions of interest Whole-genome-scale analyses provided insights into the orthologous and non-orthologous genes, as well as common and individual genomic regions among these Mlr-dependent MC-degrading bacteria. Notably, both CirCos diagram and KAAS annotation revealed the presence of phenylacetate-associated genes, which were located at the neighborhood of mlr gene cluster. In our study, EasyFig (Sullivan et al., 2011) running BLAST+ version 2.2.31 was applied to visualize these genomic regions of interest, which comprise the potential mlr gene cluster and phenylacetate-related genes. To determine whether

homologous genes existed in other members of common genus, all mlr and phenylacetate-associated genes in Novosphingobium sp. MD-1 and Sphingopyxis sp. C-1 were used for sequence alignment. Additionally, ChemDraw was applied to visualize the structural formulae of metabolites of interest. For mlr gene cluster, each gene was used as the query sequence for BLAST search, and a total of 100 alignment results (Table S4) were retained for subsequent analyses. These orthologous proteins were aligned using online MAFFT as described above, and ML phylogenetic tree was then constructed using PhyML. More details for the parameters were listed in Table S3. Visualization for ML tree was conducted using the FigTree. Notably, several phenylacetate-related genes in all genomes were predicted to encode the acid-thiol ligases (EC: 6.2.1.-). Thus, it is of interest to investigate their potential evolutionary lineages. These selected proteins were used as query sequences in turn to be aligned against the public database. Apart from repetitive sequences, the remaining sequences (Table S5) were used for the construction of ML tree. Furthermore, sequences of these predicted acid-thiol ligases were aligned against the Protein Data Bank database. Then, sequences with identity ≥ 40% in these search results (Table S6) were implemented homology modelling using the web server SWISS-MODEL (Waterhouse et al., 2018). Multiple sequence alignment was performed using DNAMAN version 7 with default built-in parameters, and threedimensional structures of homology models were visualized using the Discovery Studio v2.5 (Accelrys Inc., San Diego, USA). 3. Results 3.1. Phylogeny and taxonomy of MC-degrading bacteria Many MC-degrading bacteria across diverse taxa have been summarized (Li et al., 2017). However, some of these isolates remain unclassified and certain conflicting taxonomy confounds the understanding of evolutionary lineage of MC-degraders. In this study, phylogenetic relationships among all strains used were re-evaluated based on their own 16S rRNA genes (Tables S1–2). As depicted in Fig. 1, sequence reassignments may provide novel insights into bacterial taxonomy. For instance, Sphingomonas strains ACM-3962 (Jones et al., 1994) and MD-1 (Saitou et al., 2003) were phylogenetically affiliated with genus Novosphingobium, and Sphingomonas strains Y2 (Park et al., 2001), 7CY (Ishii et al., 2004), and B9 (Harada et al., 2004; Imanishi et al., 2005) were reassigned into genus Sphingosinicella. Notably, Arthrobacter strains R4, F7, R6, and R9 (Manage et al., 2009) were reclassified to genus Glutamicibacter, while some other strains, e.g., Arthrobacter sp. C6, were more likely to be the members of novel and non-designated genera (Fig. 1). Interestingly, genera of γProteobacteria, i.e., Stenotrophomonas, Aeromonas, and Acinetobacter,

X. Zhang et al. / Science of the Total Environment 710 (2020) 136401

were obviously separated by members of β-Proteobacteria. More specifically, strains of Stenotrophomonas were all far away from that of Aeromonas and Acinetobacter, but close to genera of β-Proteobacteria. Using the limited number of genomes, global comparison provided a higher resolution to infer the evolutionary relationships among these Mlr-dependent MC-degrading bacteria and their closely related species. Values of ANI and TETRA below the thresholds of species delineation (96% and 0.99, respectively; Table 2) strongly indicated that the three bacterial strains were significantly distinct from those validated microbial species, although value of TETRA (0.99433) between Sphingopyxis sp. C-1 and Sphingopyxis fribergensis Kp5.2T outnumbered the threshold value. Nevertheless, we could not determine whether these three MC-degrading bacteria belong to novel species, since type strains of many other closely related species have not yet been genomically sequenced.

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Using the complete/draft genomes of Mlr-dependent MC-degraders, comparative analyses were performed to explore their genetic nature and functional diversity. As shown in Fig. S1, whole-genome-based comparison demonstrated the differences among these three strains with respect to genome architecture. Numerous strain-specific genomic regions were observed, despite of many collinear blocks. As listed in Table 1, numerically, CDSs were extracted from GenBank files and counted. KAAS results showed that more than one-half CDSs were failed to be assigned into KEGG orthologs, indicating that most of them had unclear functional roles. Notably, transposable elements in Novosphingobium sp. MD-1 and Sphingosinicella sp. B9 outnumbered that in Sphingopyxis sp. C-1, suggesting that HGT events might frequently occur in the former two organisms.

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Fig. 1. Maximum likelihood phylogeny based on 16S rRNA gene sequences of MC-degrading bacteria and their closely related species. Detailed characteristics of MC-degrading bacteria were summarized in Table S1. Pentacle and pentagon represent known MC-degrading bacteria and possibly questionable species, respectively. The latter's taxonomy was revised according to phylogenetic tree. These three Mlr-dependent MC-degrading strains used for subsequent genome-based analysis were highlighted in red color. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Table 2 Calculation for whole-genome-based comparison of these three Mlr-dependent MC-degrading bacteria to their closely related species with sequenced genomes. Query organism

Reference organism (type strain)

Novosphingobium sp. MD-1 Novosphingobium nitrogenifigens DSM 19370T Novosphingobium subterraneum DSM 12447T Novosphingobium aromaticivorans DSM 12444T Novosphingobium fuchskuhlense NE08-7T Novosphingobium stygium ATCC 700280T Sphingosinicella sp. B9 Sphingosinicella vermicomposti KCTC 22446T Sphingopyxis sp. C-1 Sphingopyxis bauzanensis DSM 22271T Sphingopyxis fribergensis Kp5.2T Sphingopyxis witflariensis DSM 14551T Sphingopyxis alaskensis RB2256T Sphingopyxis macrogoltabida 203T Sphingopyxis granuli NBRC 100800T Sphingopyxis flava R11HT Sphingopyxis indica DS15T Sphingopyxis terrae subsp. ummariensis UI2T a

Accession ID

ANIb (%)a

ANIm (%)a

TETRAa

BBXA00000000 AQWK00000000 JRVC00000000 NC_007794 LLZS00000000 FMVR01000000 AP018711 PXYJ00000000 BBRO00000000 NISK00000000 NZ_CP009122 NISJ00000000 NC_008048 NZ_CP009429 BCUA00000000 FUYP00000000 FZPA00000000 FXWL00000000

− 74.12 75.44 77.03 75.43 76.40 − 69.74 − 81.30 84.46 80.37 82.45 82.01 79.87 78.19 79.71 79.99

− 84.40 85.42 85.35 84.18 85.27 − 83.18 − 85.12 87.10 85.06 85.43 86.28 84.80 84.00 84.74 84.84

− 0.81869 0.92421 0.93821 0.91886 0.93836 − 0.86505 − 0.97665 0.99433 0.98428 0.97849 0.98486 0.96148 0.96464 0.97285 0.98444

Values below the thresholds of ≤95% (ANI) and ≤0.99 (TETR A) suggested that strains used for pairwise comparison belonged to the different species.

Pan-genome analysis unraveled that core genome comprised a total of 1209 genes, while dispensable genome dominated the gene pool, as evidenced by the presence of numerous species-specific genes (Fig. 2A). Functional classification based on COG annotation revealed that the most abundant CDSs with known functions in core genome were grouped into COG category [J] (Translation, ribosomal structure and biogenesis; 20.84%), followed by COG categories [E] (Amino acid transport and metabolism; 19.85%), [C] (Energy production and conversion; 16.05%), and [I] (Lipid transport and metabolism; 12.57%; Fig. 2A and Table S7). The findings pointed out that it was necessary for basic lifestyle of MC-degrading bacteria via efficient uptake of nutrients from different ecosystems. Furthermore, our results showed that most genes unique in Novosphingobium sp. MD-1, Sphingosinicella sp. B9, and Sphingopyxis sp. C-1 were assigned to COG categories [C], [E], and [T] (Signal transduction mechanisms), respectively. 3.3. Comparison of inferred metabolic potential To explore the metabolic traits common in all three bacteria, metabolic pathways were predicted using the KAAS (Table S8) and visualized using the iPath (Fig. 2B). Of these CDSs, most were involved in amino acid metabolism (195), followed by carbohydrate metabolism (177), energy metabolism (110), and metabolism of cofactors and vitamins (99; Table S8). The findings, together with COG classification, extend our understanding of functional attributes of Mlr-dependent MCdegrading bacteria at the level of metabolism. As the important parts of central metabolism, nitrogen and sulfur metabolisms were investigated in this section. As demonstrated in Fig. S2A, there were differences in nitrogen metabolism, characterized by the utilization of nitrogen source. KAAS results revealed that Sphingosinicella sp. B9 and Sphingopyxis sp. C-1 were predicted to utilize nitrate, nitrite, and ammonia to support their growth, while ammonia was used as the source of external nitrogen in Novosphingobium sp. MD-1. Study on sulfur metabolism unraveled that a potential assimilatory sulfate reduction was identified in all strains (Fig. S2B), suggesting an allotrophic lifestyle of sulfur assimilation. Notably, a genomic region unique in Novosphingobium sp. MD-1 was predicted to be involved in biological transformation of urea (Fig. S3). Further analysis showed that this genomic region comprised a suite of genes that encoded potential urea carboxylase (UCA)-related ABC transporters (i.e., periplasmic substrate-binding protein, permease protein, and ATPase protein), nickel responsive regulator nikR, two copies of UCA-related aminomethyltransferase, UCA, and allophanate hydrolase. Similar to urea amidolyase that mediates two independent enzymatic reactions (Kanamori et al., 2004),

UCA was likely to be responsible for ATP-dependent carboxylation of urea to generate allophanate as an intermediate, and allophanate hydrolase might catalyze the hydrolysis of allophanate to NH3 and CO2. Thus, Novosphingobium sp. MD-1 might assimilate the urea as alternative nitrogen source via an UCA-allophanate hydrolasedependent pathway. Interestingly, all three strains were predicted to harbor a full suite of genes involved in phenylacetate biodegradation, except for gene encoding AMP-forming phenylacetyl-CoA ligase (PA-CoA ligase; EC: 6.2.1.30) in Sphingopyxis sp. C-1 (Fig. 2C). PA-CoA ligase, the initial enzyme of phenylacetate degradation, was responsible for the conversion of phenylacetic acid (PAA) to PA-CoA (Martínez-Blanco et al., 1990). It's worth mentioning that our results suggested the presence of several long-chain fatty acyl-CoA synthetases (LCFACSs) in the specialized genomic regions of all strains including Sphingopyxis sp. C-1 (Fig. 3A and Table S9), and both PA-CoA ligase and FACSs belong to acid-thiol ligases (EC: 6.2.1.-). Further analysis revealed that phenylacetate-associated genes in Novosphingobium sp. MD-1 and Sphingopyxis sp. C-1 were located at the genomic neighborhoods of mlr gene cluster, while these homologous genes in Sphingosinicella sp. B9 were divided into two distinct genomic regions. Of them, one region (893,011–907,778) contained genes encoding both LC-FACSs and PA-CoA ligases. Accordingly, it was of interest to further infer the possible phylogenetic relationships among these family members of acid-thiol ligases, including PACoA ligases and FACSs in all sequenced genomes. 3.4. Potential evolutionary lineage of acid-thiol ligases Numerous sequences of acid-thiol ligases across diverse taxa were collected, and functional sequence-based phylogeny clearly divided them into several distinct clades (Fig. 3B). Of these AMP-dependent synthetases/ligases, notably, PA-CoA ligases from Novosphingobium sp. MD-1 and Sphingosinicella sp. B9 were phylogenetically distinct from each other, suggesting an evolutionarily distant relationship between these two bacteria. Our results further showed that PA-CoA ligase in Sphingosinicella sp. B9 had a close genetic relationship with a cluster of LC-FACSs or acyl-CoA synthetases. Apart from annotated PA-CoA ligases, other selected sequences from these three Mlr-dependent MCdegrading bacteria were phylogenetically clustered but distinctively different from these PA-CoA ligases. To further infer the potential functional attributes of acid-thiol ligases in all three MC-degraders, homology modelling based on SWISS-MODEL was performed. In this procedure, three query sequences having relatively high identity (≥ 40%) with template

6

X. Zhang et al. / Science of the Total Environment 710 (2020) 136401

Novosphingobium sp. MD-1

Sphingosinicella sp. B9 Sphingosinicella sp. B9 specific

Novosphingobium sp. MD-1 specific

151

2309

2157

1209 284

495 Core

Sphingopyxis sp. C-1 specific

2201

Sphingopyxis sp. C-1

J K L D V T M N U O C G E F H I P Q R S No hits

Phenylacetate degradation

Ascorbate and aldarate metabolism [B] Endocrine Disrupting Compounds Caffeine metabolism

Xenobiotics Biodegradation and metabolism

DDT degradation

Phenylacetate

Inositol phosphate metabolism

Enther-Douoroff pathway

Reductive pentose phosphate cycle (Clavin-Benson cycle) Ethylbenzene degradation

C4-dicarboxylic acid cycle Pentose phosphate pathway

Purine metabolism

CAM

?

EC: 6.2.1.30

Fructose and mannose metabolism Carbon fixation in photosynthetic organisms

Steroid degradation

Phenylacetyl-CoA

Naphthalene degradation

EC: 1.14.13.149

Xylene degradation Glycolysis / Gluconeogenesis Dioxin degradation

2-(1,2-Epoxy-1,2-dihydrophenyl)acetyl-CoA Methane metabolism Phosphonate and phosphinate metabolism

Toluene degradation

Energy metabolism

Styrene degradation

EC: 5.3.3.18

2-Oxepin-2(3H)-ylideneacetyl-CoA

Benzoate degradation Atrazine degradation

EC: 3.3.2.12 Aminobenzoate degradation Polycyclic aromatic hydrocarbon degradation

Pyruvate metabolism

Bisphenol degradation Carbon fixation pathways in prokaryotes

3-Oxo-5,6-dehydrosuberyl-CoA semialdehyde EC: 1.2.1.91

Sulfur metabolism Chloroalkane and chloroalkene degradation Nitrogen metabolism Ectoine biosynthesis

Citrate cycle (TCA cycle)

Glyoxylate and dicarboxylate metabolism

Caprolactam degradation

Phenylalanine metabolism Chlorocyclohexane and chlorobenzene degradation

Tyrosine metabolism Lysine biosynthesis

Fluorobenzoate degradation

Nitrotoluene degradation

Glycine, serine and threonine metabolism

Vitamine B6 metabolism

Lysine degradation Nicotinate and nicotinamide metabolism

3-Oxo-5,6-didehydrosuberoyl-CoA EC: 2.3.1.223

Acetyl-CoA

Furfural degradation

Fig. 2. Genome-oriented analyses highlighting the metabolic profile of the three Mlr-dependent MC-degrading bacteria. (A) Venn diagram showing the orthologous and non-orthologous genes among these species. COG classifications of common genes and species-specific genes were shown in bar diagram. Abbreviations: J, translation, ribosomal structure, and biogenesis; K, transcription; L, replication, recombination, and repair; D, cell cycle control, cell division, chromosome partitioning; V, defense mechanisms; T, signal transduction mechanisms; M, cell wall/membrane/envelope biogenesis; N, cell motility; U, intracellular trafficking, secretion, and vesicular transport; O, posttranslational modification, protein turnover, chaperones; C, energy production and conversion; G, carbohydrate transport and metabolism; E, amino acid transport and metabolism; F, nucleotide transport and metabolism; H, coenzyme transport and metabolism; I, lipid transport and metabolism; P, inorganic ion transport and metabolism; Q, secondary metabolites biosynthesis, transport and catabolism; R, general function prediction only; S, function unknown. (B) The common metabolic potential of these three bacteria. A potential route involved in phenylacetate biodegradation was highlighted in oval. (C) Schematic diagram depicting the pathway for phenylacetate degradation according to KEGG annotation. However, gene encoding potential PA-CoA ligase (EC: 6.2.1.30) was absent in Sphingopyxis sp. C-1.

sequences (Table S6) were used for multiple sequence alignment and model visualization. Of these sequences, one from Sphingosinicella sp. B9 (897104–898729) was matched with LCFACS of Thermus thermophilus ATCC 27634 (1UlT) (Hisanaga et al., 2004), and two others from Sphingosinicella sp. B9 (893011–894306 and 256762–258000, respectively) were significantly similar (≥71.08%) to PA-CoA ligase of Burkholderia cenocepacia ATCC BAA-245 (bcPaaK1; 2Y27) (Law and Boulanger, 2011). In LCFACS-like proteins, two conserved motifs, including linker (L) and gate (G) motifs, as well as the P-loop were identified. As depicted in Fig. 3B, L motif (Asp431-Arg-Ala-Lys-Asp-Val 436 ) contained the peptide that linked N- with C-terminal domains, G motif (Ser 226 Ser-Phe-Tyr-His-Ala-Thr-Gly-Trp 234 ) contained the gate residue Trp 234 , and P-loop (Thr184-Ser-Gly-Thr-Thr-Gly-Tyr-Pro-Lys192 ) was the phosphate-binding site (Black and DiRusso, 2003; Black et al., 2000; Saraste et al., 1990; Weimar et al., 2002). However,

adenine motif (Gly-Tyr-Gly-Lue-Thr-Glu-Thr) containing the adenine-binding residue Tyr (Hisanaga et al., 2004) was absent in all observed sequences, probably suggesting a functional divergence. Similar to bcPaaK1 (Law and Boulanger, 2011), two copies of PA-CoA ligases-like in Sphingosinicella sp. B9 were predicted to harbor the Ploop (Ser93-Ser-Gly-Thr-Thr-Gly-Lys-Ala-Thr101 and Ser73-Ser-GlyThr-Thr-Gly-Lys-Ala-Thr81, respectively) and aryl substrate binding pocket (Val-X n -Tyr136 -X n -Phe-Xn -Gly-X n -Ala 147 -X n -Met-X n -GlyAla-X n -Ile-Tyr-Gly-Xn-Gly-Pro and Val-Xn -Tyr116-Xn -Phe-X n -GlyX n -Ala 127 -X n -Met-X n -Gly-Ala-X n -Ile-Tyr-Gly-X n -Gly-Pro, respectively). P-loop in adenylate forming enzyme superfamily had a key bifunctional role (Law and Boulanger, 2011), and aryl binding pocket acted as the active site that accommodated the phenyl group of phenylacetate intermediate. In short, visualization for topology exhibited the spatial positions of these ligand complexes in LC-FACSlike and PA-CoA ligase-like of Sphingosinicella sp. B9. As for other

X. Zhang et al. / Science of the Total Environment 710 (2020) 136401

A

Sphingosinicella sp. B9

PaaZ

PaaA PaaC

PaaG

PaaE

7

PaaK

1

Contig1: 893,011

Contig1: 907,778 PaaB PaaD

PaaI

100%

64%

Mircoystin degrading enzyme

2

Phenylacetate degrading enzyme Fatty-acyl-CoA synthase Potential transposase Other functional protein

Novosphingobium sp. MD-1

MlrF

3

MlrE

MlrB

MlrD

MlrA

MlrC

4

PaaZ

PaaG

PaaA PaaC

PaaE

Contig30: 457,337

Contig30: 404,297 PaaB PaaD

Sphingopyxis sp. C-1

5

6

Contig2: 1,370,399

Contig2: 1,330,562

Sphingosinicella sp. B9

7

8

9

10

Contig1: 108,625

Contig1: 148,719

B

P

G

C

L

A

sLC-FACS ttLC-FACS SCX99101 WP_039606663 RCI87145 WP_045162067 WP_102851456 WP_102846221 WP_031310757 EQM79500 WP_029404598 SEH89152 WP_102835490 WP_056364083 SKC08491 WP_079650772 WP_047167161 WP_011951614 WP_030092338 WP_029994686

11

MlrA

Val436

L

Asp431

192

P Lys

Thr184

G Trp234 Ser226

0.6

0.3

0.4

8 MlrC 1

MlrB

10 6 4 136

Tyr 147 Ala

B

7

0.5

Ser93

P

0.2

101

Thr

0.3

MlrF

P

Thr81 73 Ser

3 5

127

Ala Tyr116

B

9 0.7

2 12

MlrD

MlrE

Fig. 3. Genomic regions probably involved in MCs degradation and phenylacetate degradation in these three Mlr-dependent MC-degrading bacteria. (A) Pairwise comparisons showing the gene content, order, and orientation of genomic regions. Different kinds of functional genes were indicated in distinct colors. More details for these sequences were shown in Table S9. (B) Phylogeny based on sequences of acid-thiol ligases from different bacterial species. Nine clades are shown in different colors. All acid-thiol ligases from these three Mlr-dependent MCdegrading bacteria were extracted and labeled. Number for each sequence corresponds to that in A. Of these sequences, two potential PA-CoA ligases from Novosphingobium sp. MD-1 (11) and Sphingosinicella sp. B9 (12) respectively were included. More details for these sequences used were shown in Table S5. In addition, sequences having relatively high similarities (≥40%) with their template sequences were used for multiple sequence alignment and homology modelling. Abbreviations: P, P-loop; G, gate motif; A, adenine motif; L, linker motif; B, aryl binding pocket. (C) Phylogenetic analyses of core Mlr proteins MlrA, -B, -C, -D, -E, and -F. More details for these sequences were shown in Table S4.

acid-thiol ligases, exact binding mechanisms were unclear due to the lack of their three-dimensional structures. 3.5. Analyses of mlr gene clusters Mlr-dependent MC-biodegradation as an efficient pathway involves a series of intracellular enzymes that were responsible for the conversion of MCs to produce Adda. Furthermore, two additional adjacent genes designated as mlrE and mlrF were also proposed to be involved in MC-biodegradation (Okano et al., 2015). Genomic neighborhoods of mlr gene clusters in these three strains were compared and visualized using the EasyFig. As depicted in Fig. 3A, these clusters were similar with each other as to their gene content, order, and orientation. Functionalities of enzymes MlrA, -B, and -C have been elaborated (Bourne et al., 1996, 2001), but that of the others remains unclear. MlrE and MlrF were annotated as peptide-modifying dipeptidase and D-aminoacylase, respectively. However, more evidences should be provided to determine the catalytic activities of these protein compounds. To explore the potential evolutionary history of MC-degrading bacteria, amino acid sequences of core Mlr protein complex, MlrA, -B, -C, -D, -E, and -F, were used for phylogenetic analyses. As shown in Fig. 3C, each phylogeny suggested a wide range of genetic diversity. Notably, it appears that mlr gene cluster both in Novosphingobium sp. MD-1 and Sphingosinicella sp. B9 was integrated into the specialized genomic region that might undergo HGT events, since transposable elements were identified in the surroundings (Fig. 3A).

3.6. Evolutionary analysis of Mlr-dependent MC-degrading bacteria To investigate the potential evolutionary pattern, gene turnover rates of Novosphingobium and Sphingopyxis genomes were evaluated. Gene families in these two organisms were classified as orthogroups and listed in Table S10. Ancestral gene set was evaluated at all nodes of phylogenomic tree to provide an overview of evolutionary dynamics of gene families (Fig. 4A and B). Starting from the common ancestor, diverse gain/loss events frequently occurred, as evidenced by variation among genomes in terms of the total gene numbers. Especially, a dramatic gene increase at branches leading to Novosphingobium sp. MD-1 and Sphingopyxis sp. C-1 was observed in the evolutionary process. Sigi-HMM prediction (Fig. S4) further showed that most of putative alien genes in Novosphingobium sp. MD-1 were presumably originated from αProteobacteria (66%), while that in Sphingosinicella sp. B9 and Sphingopyxis sp. C-1 were derived from Chlorobia (31% and 25%, respectively). Collectively, the findings indicated that frequent gene turnover might contribute to the observed divergent evolution and genome diversification. To infer how metabolisms of MCs and PAA evolve in Mlrdependent MC-degrading bacteria, metabolism-associated genes in these strains were used as the reference to determine whether other organisms in the common genus have the potential to metabolize these compounds. As depicted in Fig. 4A and B, no other members had a suite of gene homologs related to MCs and PAA

8

X. Zhang et al. / Science of the Total Environment 710 (2020) 136401

A

1 2 3 4 5 6 7 8 9 101112131415 +103; -393 +1156; -208 +170; -85 +1235; -107 +891; -109

+735; -326 +177; -178

+717; -300 +874; -74 +475; -109

+232; -233

3359

+585; -84

3381

+149; -127

+337; -188 +581; -88 +610; -180

+47; -744

2816 +131; -156

+785; -299 +652; -335

2777

+106; -193

+145; -95

+89; -299

2983

+326; -162

3020

4147 +117; -466

+248; -10 +278; -207

3107

+61; -16 +627; -186

+396; -52 +107; -56

3049

+25; -12 +481; -347

3451

+3; -20 +482; -39

3894

+7; -4

4210

+791; -152 +555; -218 +133; -110

2708

+450; -151

3267 +905; -279

+239; -120

2968 +2; -0

+392; -132

+0; -8

4311

+0; -2

3228 +5; -0 +123; -44

4316

3841 +0; -0

+637; -103

+2; -2

4316

+0; -1 +0; -0 +163; -42

3762

+554; -313 +1215; -137 +629; -275 +333; -129 +695; -60

+239; -142

3316

+847; -284 +381; -209

+146; -254

3208 +602; -438

+163; -252 +522; -98

3119 +818; -277 +408; -43

3252 +519; -138

3500

4517 +457; -282 +831; -167

+176; -349

3219

+706; -54

4152

+275; -171

3647

Novosphingobium sp. B 225 Novosphingobium sp. PASSN1

3380

Novosphingobium fuchskuhlense FNE08-7

4059

Novosphingobium sp. NDB2Meth1

3707

Novosphingobium sp. AAP93

3966

Novosphingobium sp. MD-1

3959

Novosphingobium sp. SCN 66-18

3300

Novosphingobium sp. 17-62-19

2937

Novosphingobium sp. 12-62-10 Novosphingobium sp. 17-62-9

3687

Novosphingobium sp. 28-62-57

3091

Novosphingobium sp. SYSU G00007

3937

Novosphingobium stygium ATCC 700280

3905

Novosphingobium aromaticivorans DSM 12444

4028

Novosphingobium sp. B1

4313

Novosphingobium subterraneum NBRC 16086

4333

Novosphingobium subterraneum DSM 12447

4256 +585; -492

+601; -83

+123; -45

+635; -312

3392 +209; -194

+483; -159

3234 +216; -74

+738; -92

3880

+258; -15

3642

2897

4849

Novosphingobium sp. CCH12-A3

3409

Novosphingobium sp. 32-60-15

3592

Novosphingobium sp. AAP83

3565

Novosphingobium nitrogenifigens DSM 19370

4012

Novosphingobium sp. FSW06-99

3742

Novosphingobium sp. Fuku2-ISO-50

+38; -248

+531; -124

3834

Novosphingobium sp. B3058 49

4313

Novosphingobium sp. GV061

Sphingopyxis sp. A083 Sphingopyxis sp. MC1 Sphingopyxis sp. SCN 67-31

4097

Sphingopyxis granuli TFA

3680

Sphingopyxis granuli NBRC 100800

+6; -310

2932

Sphingopyxis granuli ku-sg

3236

3674

3100 +864; -61 4201

3398 +650; -331 +363; -65 3758 3439 +276; -235 4079 +237; -68

+807; -167 +573; -287

2819

3171

+813; -167 3847 +258; -55

3853

+895; -243 +2; -13 4103 +7; -4 +2; -9 +3; -9 +873; -207 +99; -33

2885

4111 +1; -3 4110

4308

Novosphingobium sp. GV027

4314

Novosphingobium sp. GV079

4315

Novosphingobium sp. GV055

4316

Novosphingobium sp. GV064

3962

Novosphingobium sp. AAP1

4113 +3; -3 3445 +3; -2

+3; -0

+4; -3 +2; -9 +781; -213

+264; -34

+517; -183

3324

Novosphingobium sp. B-7

3069

Novosphingobium barchaimii NS277

4330

Novosphingobium sp. PC22D

4509

Novosphingobium pentaromativorans S2_005_002_R2_33

4327

Novosphingobium lindaniclasticum LE124

4510

Novosphingobium sp. ST904

3771

Novosphingobium sp. Rr 2-17

4168

2998 +1222; -72 +300; -49

Sphingopyxis sp. MG Sphingopyxis indica DS15 Sphingopyxis sp. GW247-27LB Sphingopyxis flava R11H Sphingopyxis sp. 113P3 Sphingopyxis macrogoltabida S2_005_003_R2_47 Sphingopyxis witflariensis DSM 14551 Sphingopyxis sp. WS5A3p Sphingopyxis sp. H107

4107

Sphingopyxis sp. H100

4104

Sphingopyxis sp. H081

4112

Sphingopyxis sp. H071

4116

Sphingopyxis sp. H073

4117

Sphingopyxis sp. H067

4105

Sphingopyxis sp. H057

4013

Sphingopyxis sp. H050

4502

Sphingopyxis macrogoltabida EY-1

+112; -1

5429

Sphingopyxis macrogoltabida 203N

5284

Sphingopyxis macrogoltabida 203

4394

Sphingopyxis sp. RIFCSPHIGHO2_01_FULL_65_24

4303

Sphingopyxis sp. Root1497

5318

+8; -42 +471; -133

3575 +378; -84 4056 +175; -115

3762 +350; -103 3909

+378; -231 3702 +42; -21

+281; -154 +817; -170 +164; -86

3883

+1; -2

4112 +5; -2 4116

+195; -74

+158; -45

+256; -32

Sphingopyxis sp. HXXIV

4424

Sphingopyxis sp. HIX

+14; -17

+368; -337

3345

3895

Sphingopyxis sp. QXT-31

4074

Sphingopyxis sp. H115

3411

Sphingopyxis sp. RIFCSPHIGHO2_12_FULL_65_19

+525; -242 3690 +74; -85

3094

+139; -104

+521; -169 +1101; -113

3418

3759

Sphingopyxis sp. LC363

4551

Sphingopyxis fribergensis Kp5.2

+464; -268 3845 +118; -108

3649

3291

Novosphingobium sp. Leaf2

3664

Novosphingobium sp. HII-3

+168; -23

Sphingopyxis sp. UC10

3407

3380 +135; -39

Sphingopyxis sp. KK2

4448

4427

3780

+321; -206 +800; -71

+200; -162

4080

3563

+553; -122 +2; -10 4320 +654; -96

Sphingopyxis sp. YR583 Sphingopyxis sp. C-1 Sphingopyxis sp. Root214

4328

5058

Novosphingobium guangzhouense SA925

5356

Novosphingobium resinovorum KF1

5873

Novosphingobium resinovorum SA1

4717

Novosphingobium sp. AP12

4547

Novosphingobium barchaimii LL02

+240; -164

+3; -1 +5; -25

3639

+83; -45

+7; -14

3121

+205; -74

Novosphingobium sp. CPC302

3552

Novosphingobium sp. CF614

4346

Novosphingobium mathurense SM117

4429

Novosphingobium sp. KN65.2

4731

Novosphingobium pentaromativorans US6-1

4636

Novosphingobium sp. PP1Y

4097

Novosphingobium sp. MBES04

+1; -8

+12; -4

+811; -93

4633

+12; -3

+1; -4

4643

+10; -12

4641 +4; -5

+1; -1

Novosphingobium malaysiense MUSC 273

3484

+6; -5

4626 4634

3770

Novosphingobium sp. P6W

3083 +88; -99

+267; -122

3915

4330

Sphingopyxis sp. Root154

4606

Sphingopyxis sp. H080

4635

Sphingopyxis sp. H077

4636

Sphingopyxis sp. H012

4638

Sphingopyxis sp. H038

4640

Sphingopyxis sp. H053

4636

Sphingopyxis sp. H005

4641

+1; -6 +10; -25 4713 +96; -1

Sphingopyxis sp. H093

4728

+10; -9 +322; -282

4729

Sphingopyxis sp. H085

3955

Sphingopyxis sp. LC81

+354; -233 3145 +88; -185

Sphingopyxis alaskensis RB2256

3024

4123 +659; -146 +1028; -323

3432

Sphingopyxis terrae subsp. terrae NBRC 15098

Sphingopyxis terrae subsp. ummariensis DSM 24316

4482

+2; -198 3680 +458; -14 +731; -157

+695; -102

4022 +1092; -484

+297; -49

+284; -143

3402

+333; -193

+546; -91

3501

Sphingopyxis sp. 65-8

Sphingopyxis terrae subsp. ummariensis UI2

4114

+365; -167 5456 +1130; -128 +935; -198 4139 +397; -224

3229 +764; -682

3360

3354 3360 +9; -3 3161 +266; -59 3353 2983 3146 +116; -131 3380

2650

4454

+207; -212

2698 3609

3201

5181 +834; -142 +719; -258

Sphingopyxis sp. MWB1

+49; -68

+259; -56

3100

Sphingopyxis sp. NORP11

2728

+8; -2

+275; -41 +1057; -76

+5; -1002

3365

+186; -24

+156; -70

4155

3951 +722; -550 +1026; -467

+204; -84

+298; -105

4316

+374; -253

2828

3193 4159

+498; -69

3018 3180

3386 +613; -257 +807; -201

+661; -191

Novosphingobium kunmingense CGMCC 1.12274

+155; -475 +185; -150

3072 +689; -169 +501; -203

+296; -156

3185

+338; -218 4330

+420; -104

+248; -356

Novosphingobium sp. GV010

3892

2828 +184; -178

Novosphingobium sp. SCN 63-17

1 2 3 4 5 6 7 8 9 101112131415 +204; -486 +330; -252

3449

+310; -8

3043 +104; -46

Novosphingobium sp. 63-713

4592

3473

2993

+110; -147

4797 5066

B

3558

+344; -167

+243; -78

Novosphingobium tardaugens NBRC 16725

2776

3513

2802

Novosphingobium sp. Chol11

3764

4712

3584 +497; -143 +1227; -219

+245; -151

3223

3462

+581; -143 +882; -215 3761 +107; -96

Sphingopyxis sp. FD7 Sphingopyxis bauzanensis DSM 22271

3094

+581; -178

3497

Sphingopyxis sp. EG6

Fig. 4. Evolutionary analysis of Novosphingobium (A) and Sphingopyxis (B) strains. Topology of phylogenomic tree generated by CVTree3 was used as reference, and Sphingomonas wittichii RW1 as an outgroup. Gene turnover rates were calculated using BadiRate with the GD-FR-CWP model. Number at each node indicates the number of possible ancestral genes as retrieved. Numbers on and at the end of the branches mean the number of gain (+) and loss (−) genes, and the extant counts of genes, respectively. MC-degrading bacteria are highlighted in pink color. The filled and outlined rectangles suggest that metabolic enzymes are present and absent in the targeted organisms, respectively. Protein enzymes involved in MCs biodegradation (MlrA, MlrB, MlrC, MlrD, MlrE, MlrF; numbers 1–6) were shown in green color, while PAA metabolism-associated proteins (PaaZ, PaaG, PaaA, PaaB, PaaC, PaaD, PaaE; numbers 8–14) were indicated in blue color. In addition, acid-thiol ligases including FACSs (Number 7; purple color) and PaaK (Number 15; red color) were also shown. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

biodegradation, despite certain phenylacetate-associated genes in a couple of strains. 4. Discussion In our study, 16S rRNA-oriented phylogeny re-evaluated the taxonomic placement of MC-degrading bacteria (Fig. 1). Of these named organisms in distinct clades, some were taxonomically revised, such as Novosphingobium (formerly Sphingomonas) sp. MD-1 and Sphingosinicella (formerly Sphingomonas) sp. B9. And in fact, family Sphingomonadaceae has been previously proposed to be subdivided into five validated genera, i.e., Sphingomonas, Sphingobium, Novosphingobium, Sphingopyxis (Takeuchi et al., 2001), and Sphingosinicella (Maruyama et al., 2006). However, species delineation merely based on 16S rRNA genes has its limitation. For instance, some Arthrobacter spp. used in this study were reassigned into genus Glutamicibacter and/or other novel genera. A possible explication for this reason was that the limited number of reference sequences deposited at public database, at that time, has limited the taxonomic assignment, since homology search as a basic means was widely used for taxonomy. As for these questionable strains, genome-wide phylogeny could improve the phylogenetic resolution and better define the species boundaries. As of August 2018, genomes of three Mlr-dependent MC-degrading bacteria have been sequenced and released into the public database. Analysis based on the existing

genomes further determined the taxonomy of the three bacteria, suggesting that they were phylogenetically divergent from those known species. Furthermore, inter-taxon divergence was observed in γ-Proteobacteria (Fig. 1), probably suggesting that members of genus Stenotrophomonas might belong to a novel class. Our phylogeny based on 16S rRNA gene sequences advanced the current knowledge of taxonomy of MC-degrading bacteria. However, a metagenomic identification suggested that Methylophilales and Burkholderiales of β-Proteobacteria were more important in MCs degradation than Sphingomonadales of α-Proteobacteria (Mou et al., 2013), which was commonly regarded as the major MC-degrading bacteria. Therefore, it is of interest to acquire more detailed genetic information to investigate the evolutionary lineage of MCdegrading bacterial communities. To further investigate the ecological roles and potential evolution, existing genomes of Mlr-dependent MC-degraders were used for comparative analyses. Significant differences among these three genomes were identified with respect to gene repertoire, as evidenced by considerable species-specific genes (Fig. 2A). Given that varied events of gene gain, loss, and/or rearrangement result in genome differentiation across bacterial lineages, genome evolution might be reflected by metabolic differences. For example, nitrate, nitrite, and ammonia were utilized by Sphingosinicella sp. B9 and Sphingopyxis sp. C-1, while Novosphingobium sp. MD-1 was predicted to assimilate the ammonia. Moreover, Novosphingobium sp. MD-1 had the potential to transform

X. Zhang et al. / Science of the Total Environment 710 (2020) 136401

the urea via UCA-allophanate hydrolase-dependent pathway to support its growth. Apart from species-specific genes, a larger number of CDSs were common in these MC-degrading bacteria. Functional assignment of core genome revealed that abundant CDSs were involved in biotrophic life strategy. The findings were similar with some other genome-based studies (Ji et al., 2014; Zhang et al., 2018a; Zhang et al., 2018b). Analysis of metabolic profile further revealed that the majority of core genes were related to amino acid, carbohydrate, and energy metabolism. In bacterial genomes, necessary components probably encode functions that are related to basic biology and phenotypes. Notably, a suite of genes involved in potential phenylacetate biodegradation were identified in Mlr-dependent MC-degrading bacteria, although gene encoding PA-CoA ligase was absent in Sphingopyxis sp. C1 (Fig. 3A). In general, the widespread occurrence of aromatic contaminants (pervasive hydrophobic organic compounds) has become the health-related issues of high concern due to their potential toxicity and carcinogenicity (Nguyen et al., 2014; Dean, 1985; Hu et al., 2014; Yoshikawa et al., 1985), and biodegradation for hazardous pollutants has been an efficient approach to diminish their environmentallyrelated adverse impacts (Bilal et al., 2019). A previous study has highlighted the potential role of genes for xenobiotic metabolism in MCs biodegradation, as they were overrepresented in MC-amended microcosms (Mou et al., 2013). Furthermore, comparative analysis based on a total of 26 Sphingomonas and Sphingobium strains showed that these organisms had a huge aromatic biodegradation potential (Zhao et al., 2017). In our study, the presence of predicted PAA pathway in these MC-degrading bacteria might provide an exciting avenue for pollutant biodegradation. PAA was predicted to be a potential natural substrate of MC-degraders in this work, however, it is of necessity to experimentally determine whether PAA would be degraded by these bacteria in the future study. Phylogenetic tree based on sequenced acid-thiol ligases presented that these sequences were clustered into several distinct clades. As for homology modelling, attempt to simulate the stereo-chemical configuration of some acid-thiol ligases was failed due to the relatively lower similarities with template sequences. Thus, determination of what these protein enzymes are responsible for and whether other gene homologs encoding PA-CoA ligases-like exist in Sphingopyxis sp. C-1 are

9

important goals for further work. Furthermore, transposable elements were identified at the genomic neighborhoods of mlr gene clusters and PAA-associated genes in Novosphingobium sp. MD-1 and Sphingosinicella sp. B9, which suggested that the transposon genes flanking MCs and PAA metabolizing genes might make them mobile through HGT. In other words, these genomic regions might undergo several HGT events to recruit novel functionalities. Further analysis (Fig. 4) indicated that a genomic basis to support the degradation of PAA analogs was established much earlier than when ancestral mlr genes were introduced from the allochthonous species. Ecosystems deluged with MCs enrichment were stochastically colonized by the common ancestor, and the feedback of eco-environments potentially promoted the selection of inhabitants that might obtain the necessary set of genes via HGT events. The recruitment of MC-degrading capacity might enrich their metabolic traits, and enhance their environmental adaptation. For these biodegrading bacteria, MCs could not be considered as reliable nutrients and would rather be utilized opportunistically by MC-degrading bacteria, with enzyme pathways that are not core to any other basic and conserved life strategy that might be associated with a narrow taxonomic representation. Nonetheless, previous study shown that natural MCs was able to both directly and indirectly drive the changes in structure of microbial communities, and presented a relation between MCs exposure and degradation rate of such toxins (Giaramida et al., 2013). We thus proposed a complementary model for a consortium of co-existing bloom-forming cyanobacteria, such as Planktothrix and Microcystis, and MC-degrading bacteria (Fig. 5). Eutrophication of water bodies causes excessive growth of cyanobacteria, and the resulting harmful cyanobacterial blooms generate plentiful cyanotoxins such as MCs. MCs, to some extent, are efficiently utilized by MC-degrading bacteria as alternative carbon, nitrogen, and energy sources to support their growth. Metabolic differences as to nutrients utilization presented a possible scenario whereby individual-level partitions of metabolic functions strengthen the relation of microbial members, according to a community-dependent Black Queen Hypothesis (Morris et al., 2012). The exploration of targeted genomics has provided a better understanding of the ecological functions, metabolic diversity, and potential evolution of Mlr-dependent MC-degraders. However, the limited

N, P

O2 Novosphingobium sp. MD-1 Sphingosinicella sp. B9 Sphingopyxis sp. C-1

MCs Cyanobacteria

iso-Glu COOH

Urea

OCH3

NH4+

MCs

Mlr protein complex

CH3

Adda

NO3NO2

NH

N

CH3

Adda

NH O

O

(e.g., Planktothrix and Microcystis)

Mdha

CH3

O

MlrC

MlrA

CH3 NH2

NH

-

CH2 CH3

NH

O

NH

NH

O

Ala

MlrB

CH3

CH3

NH

NH

O

Arg

HOOC

O

Leu

CH3

iso-MeAsp

MC-LR

TCA

P

Acetyl-CoA Phenylacetate degradation

PAA

OCH3

NH2

DOC

?

O OH

O OH

CH3

CH3

CH3

Adda

Mlr-dependent MC-degrading bacteria

Fig. 5. Schematic for proposed ecological role of Mlr-dependent MC-degrading bacteria in aquatic ecosystems. Various organic carbon and nitrogen compounds as the available nutrients support the growth of MC-degrading bacteria. These organisms were responsible for biodegradation of MCs (such as MC-LR), which were produced by some bloom-forming cyanobacteria, e.g., Planktothrix and Microcystis, after the emergence of eutrophication. In these Mlr-dependent MC-degraders, Mlr complex has been recognized to be key important in the biotransformation of such toxins. Notably, these three strains were predicted to harbor the potential of PAA biodegradation, which enriched their ecological functions in aquatic ecosystems. However, whether PA-CoA ligase or its homolog exists in Sphingopyxis sp. C-1 remains unclear. Abbreviations: MCs, microcystins; Adda: (2S, 3S, 8S, 9S)-3-amino-9-methoxy-2, 6, 8-trimethyl-10phenyldeca-4(E), 6(E)-dienoic acid; DOC, dissolved organic carbon; PAA, phenylacetic acid.

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X. Zhang et al. / Science of the Total Environment 710 (2020) 136401

number of genomes, to some extent, hinders the process of adequate understanding of molecular mechanisms for MCs degradation, especially those Mlr-independent MC-biodegradations. Metagenomic analysis deduced that alternative genes and/or pathways pertaining the MCs degradation might be employed by Lake Erie bacterioplankton, as homologs to mlr genes were not overrepresented in metagenome data (Mou et al., 2013). Another study showed that bacterial taxa without mlr genes increased their relative abundance in microbial communities during the maximum cyanobacterial biomass and cell lysis, and further suggested that these bacteria with biodegradation ability for xenobiotic and other complex organic compounds might be involved in the removal of MCs in aquatic ecosystems (Lezcano et al., 2017). To date, Mlr-dependent MC-biodegradation has been well studied, but little is known about the molecular mechanisms for Mlr-independent pathways of MC-degradation in many other organisms such as Arthrobacter, Brevibacterium, and Rhodococcus. Thus, more whole-genome-based analyses in the further work may contribute to elaborating the novel genetic and enzymatic pathways for MCs biodegradations. Declaration of competing interest • The manuscript represents original and valid work and that neither this manuscript nor one with substantially similar content under the same authorship has been published or is being considered for publication elsewhere. • Every author has agreed to allow the corresponding author to serve as the primary correspondent with the editorial office, and to review the edited typescript and proof. • Each author has given final approval of the submitted manuscript and order of authors. Any subsequent change to authorship will be approved by all authors. • Each author has participated sufficiently in the work to take public responsibility for all the content.

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