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Genome sequence of the entomopathogenic Serratia entomophila isolate 626 and characterisation of the species specific itaconate degradation pathway

BMC Genomics volume 23, Article number: 728 (2022) Cite this article

Abstract

Background

Isolates of Serratia entomophila and S. proteamaculans (Yersiniaceae) cause disease specific to the endemic New Zealand pasture pest, Costelytra giveni (Coleoptera: Scarabaeidae). Previous genomic profiling has shown that S. entomophila isolates appear to have conserved genomes and, where present, conserved plasmids. In the absence of C. giveni larvae, S. entomophila prevalence reduces in the soil over time, suggesting that S. entomophila has formed a host-specific relationship with C. giveni. To help define potential genetic mechanisms driving retention of the chronic disease of S. entomophila, the genome of the isolate 626 was sequenced, enabling the identification of unique chromosomal properties, and defining the gain/loss of accessory virulence factors relevant to pathogenicity to C. giveni larvae.

Results

We report the complete sequence of S. entomophila isolate 626, a causal agent of amber disease in C. giveni larvae. The genome of S. entomophila 626 is 5,046,461 bp, with 59.1% G + C content and encoding 4,695 predicted CDS. Comparative analysis with five previously sequenced Serratia species, S. proteamaculans 336X, S. marcescens Db11, S. nematodiphila DH-S01, S. grimesii BXF1, and S. ficaria NBRC 102596, revealed a core of 1,165 genes shared. Further comparisons between S. entomophila 626 and S. proteamaculans 336X revealed fewer predicted phage-like regions and genomic islands in 626, suggesting less horizontally acquired genetic material.

Genomic analyses revealed the presence of a four-gene itaconate operon, sharing a similar gene order as the Yersinia pestis ripABC complex. Assessment of a constructed 626::RipC mutant revealed that the operon confer a possible metabolic advantage to S. entomophila in the initial stages of C. giveni infection.

Conclusions

Evidence is presented where, relative to S. proteamaculans 336X, S. entomophila 626 encodes fewer genomic islands and phages, alluding to limited horizontal gene transfer in S. entomophila.

Bioassay assessments of a S. entomophila-mutant with a targeted mutation of the itaconate degradation region unique to this species, found the mutant to have a reduced capacity to replicate post challenge of the C. giveni larval host, implicating the itaconate operon in establishment within the host.

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Background

The genus Serratia comprises ubiquitous species of obligate symbionts and opportunistic pathogens. Their success is, in part, due to their production of a wide range of proteases, lipases, and chitinases, as demonstrated in S. marcescens [1, 2], which have been implicated in the degradation of the insect exoskeletons and gut epithelial tissue [3, 4].

Serratia entomophila is the causal agent of amber disease and is used as a biopesticide in exotic grass pastures for control larvae of the endemic pest, Costelytra giveni (Coleoptera, Scarabaeidae) [5]. The main insect virulence determinants of S. entomophila are encoded on the amber disease-associated plasmid pADAP [6] which encodes two virulence factors, the Sep Toxin complex [7], and the Anti feeding prophage (Afp) (Hurst 2004). pADAP-bearing isolates of S. entomophila and some plasmid-bearing isolates of Serratia proteamaculans are implicated in a host-specific chronic infection C. giveni larvae that can take 2–3 months after ingestion of bacteria before larval death. Due to the weakening of the host intestine over time, the bacteria eventually gain entry to the haemocoel causing death by septicemia [8]. Recently, a highly virulent isolate (AGR96X) of S. proteamaculans with bioactivity towards both C. giveni and New Zealand manuka beetle Pyronota spp., has been identified that causes the death of larvae within 5–12 days of ingestion [9].

To date, only single isolations of S. entomophila from outside New Zealand, in France, Mexico, and India, have been reported [10,11,12]. Restriction enzyme profile assessment of the chromosomes and plasmids of C. giveni active strains revealed isolates of S. entomophila appeared to be genetically conserved while those of S. proteamaculans were more varied [13,14,15].

Unique to S. entomophila is its ability to utilize itaconate, which can be used to differentiate S. entomophila from other Serratia species [11, 16]. Recent research has highlighted the importance of itaconate as a eukaryote-derived antibacterial metabolite [17]. Yersinia pestis and Pseudomonas aeruginosa encode an itaconate degradation pathway enabling the bacteria to convert host-derived itaconate (methylenesuccinate) into pyruvate and acetyl-CoA, allowing the pathogen to survive [18]. The utilization of itaconate by Y. pestis enables the bacterium to survive in host macrophages [18]. The cleavage of isocitrate into succinate in the glyoxylate cycle in the itaconate degradation pathway has been implicated in fungal and bacterial pathogen persistence [19].

Through use of itaconate selective medium as a basis to isolate S. entomophila from soil Jackson et al. [20] found that, in the presence of C. giveni larvae, the number of S. entomophila cells in soil increased from an average of 5 × 104 CFU/g soil to as high as 107 CFU/g soil with increasing larval density. This was followed by a rapid decline of C. giveni larvae and a subsequent decline in S. entomophila in soil samples to the point where the bacterium was no longer able to be isolated on selective media. This, combined with the host-specific nature of S. entomophila towards C. giveni and the chronic nature of amber disease, suggests that S. entomophila may be co-evolving with its host in a predator–prey relationship [20].

In this study, we describe the first reported genome sequence of S. entomophila, of isolate 626, the active agent of the commercial biopesticide BioShield® [21]. The ability of S. entomophila to degrade itaconate was also characterised. Through in silico analysis, we sought to define unique genetic adaptations of S. entomophila required for long term interaction in C. giveni, and its limited ability to survive long term in the soil.

Results

Annotation and overview of the Serratia entomophila 626 genome

The S. entomophila 626 genome sequence comprises one complete chromosomal contig and a single plasmid contig, the latter previously annotated by Sitter et al. [15]. The S. entomophila isolate 626 chromosome comprised of 5,046,461 bp, of a comparable size to S. grimesii (5,072,299 bp) but smaller than S. proteamaculans (5,593,263 bp, Table 1). The G + C content of S. entomophila (59.1%) is similar to S. nematodiphila, S. marcescens, and S. ficaria, but ~ 5% higher than S. proteamaculans and S. grimesii. The chromosome of S. entomophila encodes 22 rRNA genes compared to 12 S. grimesii rRNA genes, but similar number to the 22–24 rRNA genes noted in the other assessed Serratia species (Table 1).

Table 1 Genome statistics of individual Serratia spp. isolates assessed in the study
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Based on 16S rDNA phylogeny, S. entomophila shares the highest similarity to S. vespertilionis and S. ficaria (Fig. 1A). Functional genome distribution (FGD) analysis of the selected Serratia species assessed in this study found S. entomophila was most similar to S. ficaria (Fig. 1B) which was corroborated by nonrecombinant core genome phylogeny. wherein the S. entomophila A1 type strain is included (Fig. 1C). The S. entomophila type strain A1 and isolate 626 share 99.4% nucleotide identity as determined by LastZ chromosomal alignment in Geneious version 10.2.6 [22, 23]. Core phylogeny was built on a concatenated alignment of 630 nonrecombinant single copy gene groups, resulting in strong support of tree nodes and correlating with the 16S and FGD analysis.

Fig. 1
figure 1

Inferred phylogeny of Serratia entomophila within the Serratia genus. A 16S rDNA Maximum likelihood tree of 18 sequenced Serratia spp. Percentage of trees shown in which the associated taxa cluster together is shown next to the branches. Branch lengths measured in the number of substitutions per site. This analysis assessed 17 members of the Serratia genus with Yersinia pestis used as an outgroup. Accession numbers for each 16S sequenced used is shown in square brackets. Serratia entomophila 626 is indicated in bold. B Functional genome distribution (FGD) analysis of representative complete Serratia genomes. The predicted ORFeomes of all 6 genomes were subjected to an FGD analysis [24], and the resulting distance matrix was imported into MEGA11 [25]. The functional distribution was visualized using the UPGMA method [26]. C Nonrecombinant core phylogeny of S. entomophila 626 and 12 representatives of the Serratia genus including the S. entomophila A1 type strain

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To further define the relatedness of S. entomophila to the selected Serratia species, the genomes of the strains were assessed by ANI. S. entomophila isolate 626 shared highest ANI of 91.2% with S. ficaria followed by S. marcescens and S. nematodiphila at 86% with S. proteamaculans 336X only sharing 84.6% nucleotide identity (Fig. 2). S. vespertilionis is now considered a heterotypic synonym of S. ficaria, with 99.5% sequence similarity between the type strains [27].

Fig. 2
figure 2

ANI values of all the comparative Serratia isolates used in this study displayed in a heat map derived from the comparative matrix. Green denotes nucleotide > 95% percentage similarity, red to yellow reflects lower nucleotide similarity values. Serratia entomophila 626 shown in bold

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Alignment and BlastP vs BlastP analysis of the S. entomophila genome against the selected Serratia species, identified eleven large S. entomophila unique regions (Fig. 3). Two of these regions coincided with phage elements. Unique region 6 encoded genes associated with itaconate degradation, a property specific to this species.

Fig. 3
figure 3

Genome atlas for Serratia entomophila 626. The genome atlas outermost circle shows BlastP similarities against the five Serratia isolates assessed in the study. Regions in blue represent unique proteins whereas red indicates high levels of conservation. Inner circle 2 shows GC content deviation, where dips below the average GC content are shown in green, and high spikes in orange. Circle 3 shows annotations of rRNA (Green) and tRNAs (Red) encoded on the forward and reverse strand. Circle 4 shows ORF orientation either in sense (+, Red) or antisense (-, Blue) orientation. Circle 5 shows the prediction of Signal peptide domains. Outer circle 6 shows assigned COG classification assigned into categories 1–5, 1) Information storage processing 2) cellular processes and signalling 3) metabolism 4) poor characterisation 5) uncharacterised or no assignment. The final innermost circle shows GC skew. Unique regions and phages are highlighted and numbered. Phage_1 denotes the DinI encoding phage. Unique_6 denotes position of the Itaconate degradation operon

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Reflecting chromosome size, S. entomophila 626 encodes fewer predicted proteins (n = 5,289) than S. proteamaculans 336X (n = 5,935) (Table 1). Figure 4 presents the clusters of orthologous groups (COGs) of the assessed Serratia (detailed in Additional File 1). Irrespective of genome size the percentage genome allocation to these COG clusters reveals key differences. S. entomophila 626 features a noticeable reduction in proteins assigned to energy production and conversion when compared to other Serratia isolates (Category C). Relative to S. proteamaculans isolate 336X, 626 encodes fewer phage-associated proteins and replication (Category X), while 626 encodes more COGs assigned to translation, ribosomal structure, and biogenesis (Category J). Across the assessed Serratia species, there were no noted differences in either the cell defence (Category V) or secondary metabolites biosynthesis, transport, and catabolism (Category Q). The S. ficaria isolate NBRC 102596 encodes more energy-producing (+ 0.52%) and carbohydrate metabolism (+ 1.55%) genes than S. entomophila 626 (Category C, 4.48% and Category G, 7.45% respectively). Relative to S. ficaria, S. entomophila 626 encodes for 0.3% more phage-derived proteins (Category X) in addition to 0.14% more allocation to cell defence mechanisms (Category V).

Fig. 4
figure 4

Distribution of COG functional categories for Serratia spp. Percentage COG distributions of annotated genes and their functions in the complete chromosomes of species belonging to the Serratia genus. The cumulative stacked count shown for each species representative. Full COG breakdowns listed in Additional File 1

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Determination of core genes in the Serratia genus was assessed by Roary through translated BlastP (95% cutoff) (Figs. 5 and 6). The average core genome (n = 6) was found to comprise 1,165 genes. The average gene count per isolate (n = 6) was 4,758 of which the average core genome comprised 1,165 genes approximating 24% of each genome. S. nematodiphila and S. marcescens encoded the fewest unique genes of the assessed Serratia species. Reflecting the smaller genome size, S. entomophila had the smallest count of total encoded genes relative to the other Serratia species assessed in this study (Fig. 5, Table 1). The total number of unique genes (< 95% translated amino acid similarity) identified by Roary in S. entomophila, S. ficaria and S. grimesii (~ 2000) was greater than in other species of Serratia assessed.

Fig. 5
figure 5

Total and unique genes for each Serratia isolate assessed. Minimum percentage of isolates a gene must reside to be defined as ‘core’ was set at the default of 95% amino acid similarity. Serratia entomophila 626 highlighted in bold

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Fig. 6
figure 6

Roary alignments of Serratia entomophila 626 and closest related Serratia species. Peach denotes the presence and yellow the absence of a gene (95% cut off). S. entomophila 626 highlighted in bold

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Roary analysis showed chromosomal similarities to S. entomophila were largely shared with S. ficaria, with a smaller region conserved across S. entomophila, S. proteamaculans, S. grimesii, and S. ficaria (Fig. 6). The genomes of S. marcescens and S. nematodiphila showed greater differentiation to S. entomophila 626 but were largely similar to each other. Clustering phylogeny generated by Roary supports earlier 16S phylogeny/ FGD analysis (Fig. 1A and B) and ANI (Fig. 2) revealing similarities between S. entomophila and S. ficaria.

To determine the extent of the pangenome for assessed Serratia, analysis was undertaken to calculate the maximum number of genes within the clade. Analysis of the pangenome of the Serratia spp. described a Chao statistic of 11,758, and an alpha value of Heaps Law as 0.7496, defining the Serratia pangenome as open.

Comparative genomic analysis

MAUVE was used to compare large colinear blocks shared between S. entomophila 626 and other species of Serratia. Many of these clusters are putative genomic islands (listed in Table 2), or chromosomal deletions where absence of a block in an otherwise colinear section of more than two chromosomes. Large genomic rearrangements can be seen between S. entomophila and S. proteamaculans isolate 336X, with one large, inverted region in Serratia entomophila 626 as opposed to S. proteamaculans (Fig. 7). Excluding S. ficaria, the other assessed Serratia species shared large regions of uniformity over collinear blocks, with areas of low homogeneity within these areas (Fig. 7). Though sharing a large degree of orthologous gene clusters relative to S. entomophila, S. ficaria and S. grimesii share large collinear blocks in the opposing orientation to S. entomophila (Fig. 7), indicative of chromosomal rearrangements.

Table 2 IslandViewer4 hits predicted in Serratia entomophila isolate 626 with putative function assigned
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Fig. 7
figure 7

Genomic alignments of six Serratia spp. using MAUVE multiple genome alignment software. Blocks indicate orthologous regions- with colour maps showing the percentage nucleotide identity between each orthologous block. Blocks lying above the centre line are in the forward orientation. Blocks below the centre line are on the opposite strand and represent chromosomal rearrangements. 1) Genome location of the itaconate degradation operon in S. entomophila 626. 2) Location of the unique SeDIN. 3) Location of region encoding extracellular phospholipase A1. Parentheses denote inverted region in S. proteamaculans 336X relative to S. entomophila 626

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Assessments of genomic islands of the selected Serratia genomes by IslandViewer revealed S. entomophila 626 has 25 predicted chromosomally encoded islands (Table 2) compared to the 40 predicted islands in S. proteamaculans 336X and of the other assessed Serratia isolates (Fig. 8). These include phage remnants, toxin-antitoxin systems, anti-bacterial defensive genes, and secretion systems (Table 2). The prediction of these islands corresponds to the identification of unique regions and phages in S. entomophila 626 identified by BlastP against other species of the Serratia genus (Fig. 3). Five of the predicted islands in S. entomophila 626 encoded proteins with COG function attributed to defense, where one was a predicted phage. Region 3 (Fig. 8A) encoded an HRH endonuclease with no further similarity BlastP hits within the Serratia genus. Region 10 encoded two defense mechanism associated proteins alongside additional fimbriae proteins. One of the two defense associated proteins was a predicted hypothetical. BlastP analysis showed 84.5% identity to an addiction module antitoxin (accession: 0A240BVB2) from S. ficaria, whereas the second was a putative efflux pump protein. Through this analysis, the latter described 626 itaconate degradation operon (Fig. 7 labelled ‘1’; Fig. 8, Island 12), which is absent in the other assessed Serratia genomes, based on % G + C content IslandViewer predictions and absence within the genus is predicted as a genomic island.

Fig. 8
figure 8

Predicted genomic island using IslandViewer4 for Serratia entomophila chromosome and of the genomes of the selected Serratia isolates. A Putative genomic islands for S. entomophila 626. Numbers correspond to genomic island with predicted COG function presented in Table 2. B Putative islands for S. proteamaculans 336X. Red indicates where a genomic island has been predicted by one of the identification tools utilised by IslandViewer (IslandPath-DIMOB, SIGI-HMM, IslandPick, Islander) where blue, orange and green represent alternate prediction tool. Pink dots show the location of homologs of antimicrobial resistance genes identified in the chromosomes of S. proteamaculans 336X, S. marcescens Db11, and S. nematodiphila DH-S01, where prior described island results were available in the database. The S. entomophila 626 itaconate degradation encoding genomic island is identified by point 12

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Comparison of the GC skew revealed greater variability in S. proteamaculans 336X than in S. entomophila 626 (Fig. 8A and B). Based on IslandViewer, S. entomophila 626, S. proteamaculans 336X and S. ficaria encode a greater number of predicted genomic islands than S. marcescens, S. grimesii and S. nematodiphila, with S. grimesii encoding the least (Fig. 8).

Assessments of the selected species for phage-like elements using the Phaster phage search tool revealed that the S. entomophila isolate 626 encoded two predicted intact (18.9 Kb and 40.4 Kb) and two incomplete phage regions (7.9 Kb and 33.3 Kb). IslandViewer predictions revealed PHAGE_Escher_500465_1_NC_049342 region in S. entomophila 626 comprised two smaller islands (annotated as 19 and 20 in Fig. 8) with a combined length of ~ 17 Kb. These two smaller islands encode mostly hypothetical proteins, and the Phaster predictions include adjacent fimbriae encoded genes. Across the genus, homogeneous regions span between 9.3 Kb and 14.9 Kb with minimum 67.9% pairwise DNA sequence identity to other Serratia isolates (Fig. 7, label 3). Nucleotide alignments of the shared region sequence identity of Escherichia phage 500465.1 ranged from 84.0% in S. grimesii to 92.9% in S. ficaria. This region encodes a DUF2974 domain-containing protein (KFQ06_18140), where Blast analysis revealed sequence homology to the extracellular phospholipase A1. Comparison of the extracellular phospholipase A1 amino acid sequences showed homology relationships to S. entomophila similar to that of the phylogenetic and ANI analyses, where S. ficaria showed the highest amino acid similarity (Fig. 9). Unique region phage 2 (Fig. 3; Table 2, Island 24) on investigation shows most in common with phage PSP3 of Salmonella enterica. This region however is mostly unique, where only 15 of the S. entomophila phage proteins shared synteny with genes from phage PSP3.

Fig. 9
figure 9

Amino acid alignment of predicted phospholipase A1 from across the Serratia genus. S. entomophila 626 (CP074347), S. ficaria NBRC 102596 (NZ_BCTS00000000.1), S. nematodiphila DH-S01 (NZ_CP038662.1), S. marcescens Db11 (NZ_HG326223.1), S. proteamaculans 336X (NZ_CP045913.1), S. grimesii BXF1 (LT883155). GenBank protein accessions shown in brackets

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Aside from the Escherichia phage 500465.1 region, 10 predicted prophage regions were identified in S. proteamaculans 336X (between 12 Kb and 63.9 Kb in length), with three intact, four incomplete and three questionable phages. Both S. grimesii and S. marcescens encoded the least predicted phages, with one intact and one incomplete phage (Table 3).

Table 3 Annotation of SeDIN and its flanking tRNA regions in S. entomophila 626
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Unique to S. entomophila and not predicted by IslandViewer is an 18.9 Kb region located between 3.35 Mb-3.37 Mb of the 626 chromosome. Flanked by tRNA-Pro and tRNA-Thr, this phage-like structure is devoid of DNA packing apparatus, 5’ of which is a gene encoding a DinI protein (Fig. 3 Phage_1, Table 2 Island 18, Fig. 7 ‘2’, Fig. 8, Table 3). The predicted phage-like Din Island designated SeDIN (Island 18, Fig. 8) has a lower G + C content (55.3%) relative to the chromosome to S. entomophila 626 (59.1%).

To define potential genomic regions that may limit HGT, chromosomal searches were undertaken to locate CRISPR-Cas and restriction-modification (R-M) systems. Neither S. proteamaculans 336X nor S. grimesii DXF1 encoded R-M systems, whereas type 1 R-M systems were ubiquitous across other isolates. S. marcescens Db11 (Type 3 R-M) and S. nematodiphila DH-S01 (Type 2) were unique in the additional R-M system types present on the chromosome. Three of the six assessed Serratia encoded putative CRISPR-Cas systems, with a greater number in S. grimesii DXF1 (Table 4). CRISPR arrays in S. ficaria and S. proteamaculans 336X had short candidate arrays of 1–3 spacers that may be recent or relic arrays that may not be functional CRISPR systems, as predicted through CRISPR-CASFinder. S. grimesii had one array with low evidence (< 4 spacers present) and two active CRISPR-Cas systems (Table 4). S. entomophila 626, like S. marcescens, contains no CRISPR-Cas systems, but similar to the other assessed Serratia species does encode a type I R-M system (Table 4).

Table 4 Predicted phage, CRISPR-Cas systems and R-M systems within the assembled chromosome of Serratia entomophila 626 and the selected Serratia spp
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In agreement with the ability of S. entomophila to produce DNase, S. entomophila isolate 626 encoded a single non-specific endonuclease, the translated products of which have high amino acid identity with nucA orthologues from S. marcescens and S. ficaria (Table 5). A second endonuclease, endA was identified, the translated product of which shares 95.2% amino acid identity to EndA in S. ficaria and shares 75.3% amino acid identity with Dickeya dadantii NucM (Table 5).

Table 5 Identification of secreted nuclease from S. entomophila isolate 626, and its closest % similarity from BlastP
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Chromosomally encoded hydrolases and metabolites

To help define the plasmid-independent virulence of S. entomophila relative to the other assessed Serratia spp. the chromosomes were independently interrogated by using hmmsearch searching for chitinase and lipase motifs. The 626 chromosome was found to encode single copies of four chitin and one chitin-binding protein (Table 6). Most lipases identified from Pfam HMM motif searches were identified in isolate 626, which shared high amino acid similarity to the S. ficaria lipases (A0A240AUF3). Isolate 626 also encodes an extracellular phospholipase (KFQ06_18140) sharing 90% amino acid identity to the S. liquefaciens extracellular lipase A1 (A0A240CAJ3) and co-located to the Escherichia phage 500465.1 found across the genus. Other Lipases were consistently present across the genus (Table 6).

Table 6 Presence or absence of lipase, chitin binding and chitinases encoding genes of the assessed Serratia spp
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Of relevance to potential entomopathogenic properties, four chitinases (Chitinase A, A1, B and an orthologue of ChiD) were present in S. entomophila 626, each harbouring a glycoside hydrolase family 18 domain (Table 7). Chitin-binding protein GbpA was only found in S. entomophila 626 and S. proteamaculans 336X. Excluding chitinase A1, which was absent in S. ficaria and ChiD, two additional encoded chitinases were present across the assessed Serratia. The loci KFQ06_20145 encoding a protein with a hydrolase family 18 domain shares low amino acid similarity with a predicted lipoprotein (Table 7).

Table 7 Chitin-associated genes and their respective functions determined through UniProt
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Analysis of potential secondary metabolites produced by S. entomophila 626 via antiSMASH revealed seven predicted secondary metabolite clusters (Table 8). Each was able to be assigned a candidate gene cluster type and only one (cluster 7) matched with high similarity to a known cluster, with a cluster hit of 77% (aerobactin). Three non-ribosomal peptide synthase (NRPS) regions were detected with one at 3.8 Kb sharing 30% cluster similarity to turnerbactin synthases. The remaining three clusters identified were identified as a putative hserlactone cluster, betalactone, and a thiopeptide synthase (Table 8).

Table 8 Summary of AntiSMASH analysis for predicted secondary metabolite cluster in Serratia entomophila 626
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Serratia entomophila encoded itaconate degradation cluster

Based on the ability of S. entomophila to utilize itaconate as a sole carbon source and the predicted itaconate degradation operon residing as a predicted genomic island 12 (Fig. 3 unique region 6; Fig. 4, Fig. 8) absent from the other assessed Serratia species, the S. entomophila itaconate operon was assessed for its potential role in virulence. As listed in Table 9, the itaconate region comprises four genes: i) coenzyme A (CoA) transferase, ii) ripC encoding l-malyl-CoA lyase, iii) ripB the translated product of which encodes a mesaconyl-CoA hydratase, and iv), a putative transporter protein. Based on gene synteny the S. entomophila itaconate degradation region is most like the Y. pestis ripABC operon identified as ripC, ripB, and CoA transferase (Fig. 10B) and shares varying levels of amino acid similarity to the translated components of the Y. pestis rip operon (Table 9). RipC is more diverged, sharing only 57% amino acid similarity with the Y. pestis RipC ortholog. RipC phylogeny of BlastP closest relative proteins showed that the S. entomophila 626 RipC protein is closely related to that from the nitrogen-fixing soil bacterium Beikerinckia indica (Fig. 10A). Phyre.2 analysis of the translated product of the KFQ06_09545 located 3’ of ripC revealed 90% structural identity to a family member of the NADC transporter protein (Table 9). Located in the opposing orientation 3’ of the S. entomophila itaconate operon is a predicted LysR regulator (KFQ06_09525). Five prime (DNA polymerase III subunit theta, KFQ06_09550) and 3’ (pip, KFQ06_09520) genes flanking the S. entomophila itaconate region are co-located in the non-itaconate encoding S. proteamaculans 336X genome (Fig. 10C). No IS or repeat elements were detected at the periphery of either the S. entomophila 626 or the Y. pestis ripABC predicted itaconate operons. Relative to 626 itaconate encoding region with a % G + C of 59.1%, the Y. pestis KIM10 + itaconate clusters % G + C was lower (51.2%), supporting the hypothesis of its acquisition by HGT.

Table 9 Results of the BlastP analysis of the Serratia entomophila and Yersinia pestis itaconate degradation encoding operon, showing closest related ortholog and origin species
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Fig. 10
figure 10

Gene synteny of the itaconate degradation pathway operon. A Maximum likelihood tree of RipC amino acid sequence from Serratia entomophila (bold) alongside seven other gene homologues found through BlastP. Scale bar represents 20% genetic variation. Bootstrap values above 50% are shown. B ripABC synteny and gene arrangement with the depicted itaconate operons- the three gene Yersinia pestis and six gene Pseudomonas aeruginosa operons. Colours indicate genes with the same functional prediction as S. entomophila, refer Table 8 for annotations. Red arrow under ripC denotes the mutated gene. C S. proteamaculans co-location of pip and DNA polymerase III subunit theta, where in S. entomophila 626 the itaconate degradation region is positioned. GenBank protein accessions shown in brackets

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Characterization of the S. entomophila itaconate region

Based on the role of the itaconate degradation operon in the utilisation of itaconate as a carbon source [28], it is plausible that this region may be advantageous to S. entomophila in a specific niche. As expected, the 626::RipC mutant was unable to grow on ITA agar plates (Fig. 11A) validating the role of the ripC gene in itaconate utilization. This loss of ITA utilization was able to be restored through the trans complementation by pACRipC with 626::RipC, where similar growth to that of the 626 strain was observed on ITA agar media (Fig. 11A).

Fig. 11
figure 11

Growth of WT 626, 626::RipC and complemented ripC gene in optimal and stress conditions. 48 h growth curves in triplicate with standard error shown. A) growth of wildtype 626, the 626::RipC mutant and its trans-complemented derivative 626::RipC pACRipC on itaconate agar.B) in LB broth and C) M9 minimal (glucose) broth

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To determine any metabolic benefit the itaconate degradation operon may confer to the growth of S. entomophila, the growth kinetics of S. entomophila 626 and 626::RipC were independently assessed over a 48 h duration in LB and then M9 (glucose) broth. Assessments of the resultant growth curves found no difference in the growth of S. entomophila 626 and 626::RipC in LB broth (Fig. 11B). In M9 minimal broth (glucose), the rate of growth of 626::RipC was reduced in the lag and exponential growth phase. The CFUs of 626::RipC and 626::RipC + pACRipC plateaued by the 48 h time points with 2.19 × 109 and 1.98 × 109 CFU/ mL respectively, where wildtype S. entomophila 626 achieved higher cell numbers of 2.39 × 109 CFU/ mL (Fig. 11).

Larval co-infection assays

To determine if 626::RipC may impair the infectivity to challenged C. giveni larvae, the lethal concentration (LC50) and lethal time (LT50) of disease were determined for 626::RipC and S. entomophila 626 (Table 10). Initial bioassay assessments of C. giveni larvae separately challenged with isolates 626 or 626::RipC defined LC50 of 626 to be approximately tenfold lower than that observed with 626::RipC (Table 10). Assessment of the LT50 where larvae were dosed with ~ 7 × 107 CFU revealed an LT50 of 3 days in WT S. entomophila 626 and 4 days in the 626::RipC mutant.

Table 10 Bioassay LC50 and LT50 data with standard error on the mean for mutant 626::RipC and Serratia entomophila 626 controls. Results were determined from day 12 observations. P values (Fisher’s exact), with statistical significance to the negative control, are highlighted in bold
Full size table

To determine any in vivo potential competitive advantage of S. entomophila 626 over 626::RipC a co-infection assay of C. giveni larvae with both strains was carried out and relative cell numbers 12 days post-challenge assessed (Fig. 12). Although inoculation CFU for WT 626 (6.2 × 109 /mL) was slightly lower than for the itaconate mutant (9.6 × 109 /mL), CFU of S. entomophila 626 re-isolated from in vivo macerate samples remained (~ 1 × 106 CFU) higher than for the mutant strain. At 3 days post-challenge, the cell numbers for both strains significantly differed (P = 0.013), where WT 626 showed an advantage in the establishment of the larvae post-challenge over the mutant (Fig. 12). Unlike the 626::RipC mutant, WT 626 remained at a relatively stable cell density (~ 106 CFU per larvae) over the duration of the 12-day competition assay. From day 6 until day 12, the 626::RipC cell number declined by 95%, dropping to ~ 5 × 104 CFU per larvae by day 12. While the endpoint difference did not significantly differ (P = 0.057), WT 626 (104 CFU per larvae) was trending towards a growth advantage against the 626::RipC mutant with a log fold difference in cell numbers between days 3 to 12 of the bioassay.

Fig. 12
figure 12

In vivo competitive growth experiment. In vivo growth curve of a 12 day of 50:50 inoculants of WT 626 and its itaconate mutant derivative 626::RipC in challenged C. giveni larvae, represented on a log10 scale. CFU log10 results for each isolate recorded in triplicate for three-day intervals

Full size image

Discussion

The complete genome of the S. entomophila BioShield® isolate 626, used for the control of C. giveni larvae in New Zealand, was sequenced and described in this study.

As determined through Roary, the core genome of Serratia genomes assessed in this study (n = 1165) is 24% of the overall chromosome size. The inclusion of additional and more varied Serratia spp. would likely decrease the core genome of Serratia spp., as suggested by the value of alpha in Heap’s law describing an open pangenome. Chao’s statistic [29] however, defines the upper bounds of the pangenome as 11,758 genes. Close relationship predictions of the assessed Serratia by ANI (> 62%) are within the genus boundary suggested by Kim et al. [30] and a large core genome suggests that adaptive evolution to host and environment in the Serratia genus is mediated by acquisition of DNA through HGT and chromosomal rearrangements within the genus. Of these relationships, S. entomophila shares the highest ANI with S. ficaria (91.1%). This was further supported by 16S and core genome phylogenies, showing S. ficaria is the closest related Serratia species identified to S. entomophila 626. COG assessments of the number of encoded phage-associated genes revealed S. entomophila (n = 69) and S. nematodiphila (n = 71) are second to S. proteamaculans (n = 132). S. grimesii, S. marcescens and S. ficaria encoded 34, 49 and 32 respectively. This correlates with the predicted number of phages within the genus, where S. proteamaculans had the most phage elements and S. marcescens, S. ficaria and S. grimesii the fewest. Of interest is the predicted S. entomophila island which has remnant orthologues with high nucleotide identity in the other assessed Serratia genomes. The identification of a phospholipase A1 (KFQ06_18140) associated with this region high nucleotide identity across the assessed Serratia species alludes that earlier DNA acquisition facilitated pathogenic development within the Serratia. Quantification of chromosomally encoded accessory enzymes with a role in virulence in S. entomophila 626 revealed lipases were uniform across the genus. Amino acid sequence comparison shows 84% pairwise identity of phospholipase A1 across all six isolates, with highest amino acid identity (90%) between S. entomophila 626 and S. ficaria.

Although comparable in number to S. ficaria NBRC 102596 the S. entomophila 626 chromosome encodes more predicted genomic islands than S. grimesii DXF1 and S. marcescens Db11 and less than S. proteamaculans 336X and S. nematodiphila DH-S01. This suggests S. entomophila has reduced genomic plasticity compared to S. proteamaculans 336X, but not relative to the other examined species. The increased number of predicted S. entomophila genomic islands relative to some members of the genus may mean that the S. entomophila genome diversified before its association with C. giveni larvae. Evidence for this may be the presence of the species unique Island SeDIN which encodes a predicted phage but was devoid of DNA packaging or capsid genes and encodes a DinI protein. In E. coli DinI physically interacts with RecA to shut off the initiation of the SOS response. Of note the S. entomophila Afp is regulated by the rpoS SOS response regulator [31], therefore the expression of the SeDIN associated DinI may affect gene regulation in this bacterium including that of the Afp.

Assessment of R-M systems located on the chromosomes showed the prevalence of type I systems within the genus. CRISPR-Cas systems [32], in addition to R-M systems [33], are thought to be inhibitors of the flow of HGT in bacteria. CRISPR-Cas systems have been shown to inhibit conjugation transformation and phage integration. Previous research [32] found a Bacillus cereus CRISPR-Cas actively impeded HGT, with active systems correlating with fewer mobile genetic elements. New evidence suggests that phage transduction is promoted by CRISPR-Cas adaptive immune systems in phage-resistant and sensitive populations of Pectobacterium atrosepticum by limiting wild-type phage replication and promoting transduction in phage-sensitive and resistant populations [34]. This suggests that the role of CRISPR-Cas systems is more complex than simply inhibiting HGT, and any effect the presence of CRISPR arrays has on HGT cannot be fully defined via in silico analysis.

Using IslandViewer, fewer predicted genomic islands were identified in those Serratia chromosomes characterised by the presence of one or two R-M types or a CRISPR-Cas system. For example, S. grimesii BXF1 encodes two predicted chromosomal CRISPR-Cas systems with a low prediction score to a third CRISPR-Cas array and encodes the fewest putative genomic islands. Active CRISPR-Cas systems have been implicated as a potential constraint to HGT as demonstrated in Pseudomonas aeruginosa, where the presence of an active CRISPR-Cas system correlated with the reduced number of putative genomic islands [35]. No intact CRISPR-Cas were identified in S. entomophila 626, S. proteamaculans 336X or S. marcescens Db11.

In relation to the potential speciation of 626, a single Type 1 R-M system was identified on the chromosome of S. entomophila 626 which, through its ability to cleave foreign DNA, could limit acquiring of foreign DNA. Further to this the production of extracellular DNase by S. entomophila [16] will likely reduce the opportunity for cell surface HGT DNA acquisition [36].

S. entomophila is the only species within the Serratia genus to encode an itaconate degradation operon, where dissimilar % G + C content and putative genomic island location prediction alludes to species-specific acquisition. The 626::RipC mutant showed a slight growth lag in challenged larvae but did not affect the disease development. However, C. giveni larvae challenged with 626 and 626::RipC revealed that 626 had an initial competitive advantage, as the predominant strain isolated from larvae. Though the 626::RipC mutation did not affect the virulence capacity of the bacterium to challenged C. giveni larvae, the increased fitness of 626 over 626::RipC observed through co-infection and noted in M9 minimal broth, suggested that a substrate of gene products of the itaconate operon is present in C. giveni. In an ecological context, it is also plausible that the 626 encoded pathway may utilize fungal-secreted itaconate as a carbon source [37]. In this context a synergistic relationships between S. entomophila and entomopathogenic fungi were previously reported by Glare [38], and saprophytic fungi are often associated with the cadavers of amber disease-affected larvae. The potential utilization of fungal derived itaconate by S. entomophila through post amber disease saphrophytic decay would prolong the bacterium’s survival external to the host and therefore warrants further investigation.

Conclusions

The complete chromosomal sequence of S. entomophila isolate 626 will enable future analysis exploring the relationship of S. entomophila with C. giveni larvae. Relative to other grass grub and manuka beetle active pathogens such as S. proteamaculans AGR96X and Yersinia entomophaga which cause mortality within 3–10 days post-challenge [39], S. entomophila is a more benign pathogen, with infection taking 3–4 months before mortality [8]. The chronic nature of S. entomophila mediated amber disease would enable S. entomophila to exist in a non-competitive niche. By reducing its DNA acquisition potential through fewer microbial associations, S. entomophila could then decreased production burden of a highly active pathogen [40]. Direct support for this was provided by Dodd [13] and Claus et al. [14] who demonstrated the genome of entomopathogenic S. proteamaculans is more heterogeneous than for S. entomophila.

The presence of R-M systems and fewer genomic islands combined with previous assessments of Dodd et al. [41] and Jackson et al. [8] support the hypothesis that the S. entomophila genome may reflect a lifestyle adaptation suiting an association with C. giveni larvae. Further exploration of isolates of S. entomophila would facilitate determining the evolutionary relationship with C. giveni and allude to whether genome reduction is underway.

Methods

Culture and genome sequencing

Cultures were grown in 3 mL of Luria–Bertani (LB) broth for 16 h at 37 °C for Escherichia coli, and 30 °C for S. entomophila 626 and its derivatives, in a Ratek orbital incubator at 250 rpm. Antibiotic concentrations used for selection and counterselection of S. entomophila 626 and its derivatives were tetracycline 30 μg mL−1 kanamycin 100 μg mL−1, chloramphenicol 90 μg mL−1 and for E. coli were ampicillin 100 μg mL−1, chloramphenicol 30 μg mL−1, kanamycin 50 μg mL−1, and tetracycline 30 μg mL−1.

Luria Bertani and M9 (glucose) minimal growth media were prepared as described in Elbing et al. [42]. To validate the presence of S. entomophila, selective caprylate-thallous agar (CTA), DNase, and itaconate (ITA) plates were prepared and used as outlined by O'Callaghan [16].

For standard growth curves, cultures were initially grown for approximately 16 h (~ 1 × 109 CFU). Starting concentrations were then equalised through the addition of LB broth to a CFU of ~ 1 × 107 CFU/mL and the CFUs validated by serial dilution. Five hundred µL of the equilibrated culture was then pelleted and resuspended in 500 µL phosphate-buffered saline (PBS) before independently inoculated into three flasks containing either 50 mL of LB broth or M9 (glucose) per isolate. CFUs were determined using serial dilutions prepared in PBS buffer by taking 1 mL samples at the time of inoculation and 1, 2, 4, 8, 16, 24, 26, and 48-h post-inoculation (hpi). OD600 was measured in triplicate at each of these time points using a Bio-Rad SmartSpec Plus Spectrophotometer.

DNA preparation and sequencing

Standard molecular techniques were undertaken as outlined by [43]. Genomic DNA extractions were performed with the Bioline ISOLATE II Genomic DNA kit (Meridian Bioscience, UK) following the manufacturer’s instructions. For amplification of genetic regions, Roche platinum taq DNA polymerase was used according to manufacturer’s instructions. Vectors, primers, and amplicons used in this study are listed in Table 11. Plasmid vector DNA and PCR amplicons were purified using the respective Roche high pure plasmid isolation kit or the Roche high pure PCR product purification kits (Roche Diagnostics GmbH, Mannheim, Germany). Yield and purity were determined using agarose gel electrophoresis and NanoDrop 2000 Spectrophotometer (Thermo Scientific).

Table 11 Primers used in this study
Full size table

Genomic DNA was sequenced at Macrogen Korea (South Korea) using the PacBio RSII system with 10 Kb SMRTbell library kit. Illumina DNA sequencing was performed by Macrogen Sequencing Service. PacBio RSII sequencing generated 104,172 reads with an average read length of 12 Kb. Sequencing coverage for isolate 626 was ~ 80X.

PacBio FASTQ reads were assembled using Canu [44] to formulate complete genomic contigs before being corrected using Pilon against S. entomophila Illumina sequences [44, 45]. The assembled contigs were trimmed using Circlator to remove overhangs in circular DNA assemblies [46]. The resultant plasmid assembly [15] (Accession: NC_002523) was identified by size, and BlastN [47] for similarity to S. entomophila plasmid pADAP, and removed from the genome assembly. CheckM was used to assess the quality of the microbial genome [48], with an estimated genome completeness of 99.88% and no contamination identified in the sequence of S. entomophila 626. The S. entomophila 626 chromosome is deposited in GenBank with accession CP074347. Reference sequences from GenBank of the five reference Serratia genomes used in the study are listed in Table 2. Genome annotation was performed by PROKKA Rapid Prokaryotic Genome Annotation software and through GAMOLA2 [49, 50]. COG assessments of S. entomophila isolate 626 were compared to five reference Serratia type strains (Table 2) using the latest COG database [51]. The results were then used to construct a genome atlas for S. entomophila isolate 626 using Genewiz [52], utilizing BlastP with a custom Blast database comprising the five reference strains, COG annotations and in-house software.

Comparative genomics

Core genome analysis was undertaken using ROARY pangenome pipeline, where nucleotide sequences provided from.gff3 annotations were converted into amino acid sequences and undergo all vs all BlastP. Protein percentage sequence identity were set at default cutoff values of 95% [53]. Pangenome analysis was undertaken using the R package micropan [54]. Large-scale genomic changes of locally collinear blocks were assessed using MAUVE [55]. Hmmer3 [56] hmmsearch function was used in parallel with the Pfam motif database to search the genome of S. entomophila 626 for lipases, chitinases, and DNases. Default parameters were used for cutoff threshold (E-value = 10.0) to display all potential hits. Genomic islands were predicted using IslandViewer4 [57]. The PHASTER server (https://phaster.ca/) was used for detection of chromosomally encoded phage regions [58]. RAST annotations [59] were searched for restriction-modification (R-M) systems, and CRISPR regions were identified using CRISPRfinder [60].

Phylogenetic analysis

16S rDNA sequences from selected type isolates of Serratia spp. were extracted from GenBank (refer to Table 2 for selected Serratia spp. and accession numbers). 16S rDNA genes were aligned using ClustalW and plotted using maximum likelihood phylogenetic inference in MEGA7 software [61].

Core genome phylogeny was inferred using whole genomes of 13 representative strains of Serratia available on the Genbank repository, included in this analysis was the genome of recently deposited S. entomophila A1 type strain. To identify single-copy orthologous groups, Orthofinder [62] was then run on the 13 selected Serratia spp. From this analysis, 1434 single-copy gene groups were identified and aligned using MAFFT [63], of which 643 were of suitable length for further analysis. The aligned single-copy gene groups were then tested for recombination using PhiTest via the Phipack package [64], with the window parameter set to 50 nucleotides. Of the groups tested, 13 showed recombination signals and were therefore omitted. The remaining nonrecombinant alignments were then concatenated, with a maximum likelihood tree then inferred using IQ_TREE 2 with the model Q.plant + F + I + R4 and 10,000 bootstraps [65].

FGD analysis was also undertaken which utilizes an ORFeome vs ORFeome analysis to cluster species by ORFeome similarities [24].

Average nucleotide identity scores (ANI’s) were calculated for each comparison between genome including 100% of the chromosomal sequence to determine percentage similarity using an ANI/AAI genome-based distance matrix calculator [66].

Targeted mutagenesis of the itaconate region

The 3,677 bp ita-ripC amplicon generated using the primers ItaF and ItaR (Table 11) was digested with restriction enzyme XbaI and cloned into the analogous site of pUC19 [67] from where a tetracycline cassette was ligated into two Nco1 sites (deleting 547 bp to 792 bp of ripC) to form pUC19-RipC. The construct pUC19-RipC was then digested with EcoRI and the tetracycline tagged fragment then ligated into the analogous site of pJP5603 [68] to form pJPRipC. The sequence validated pJPRipC was then electroporated into E. coli ST18 [69] enabling its conjugation into the S. entomophila isolate 626 following the method of Martínez-García et al. [70]. Tetracycline-resistant transconjugants were patched on LB plates to determine pJP5603 encoded kanamycin sensitivity. Prospective recombinants were validated using the ItaF and ItaR primers (Table 11) and DNA sequencing of the resultant amplicon. The sequence validated ripC recombinant designated 626::RipC.

To construct pACRipC enabling the trans complement of 626::RipC, the ripC amplicon (Table 11) was digested with EcoRV and ligated into the analogous site of pACYC184 [71] to form 626::RipC (pACRipC). The sequence validated vector pACRipC_cm then electroporated into 626::RipC, to form 626::RipC (pACRipC).

Bioassays

Field collected 3rd instar C. giveni were pre-fed from where only healthy, feeding larvae were selected for bioassay assessments as outlined by Hurst et al. [9]. For maximum challenge bioassays the selected larvae were fed carrot (3–4 mm3 in size) inoculated via rolling on a bacterial lawn grown overnight on LB agar plates at 30 °C (approximately 1 × 108 CFU per larvae). Each treatment comprised 12 larvae and was undertaken in duplicate. The treated carrot was administered on day zero, with fresh untreated carrot cubes provided on days three and six. Uninoculated carrot was used as the negative control and the positive controls comprised carrot cubes treated with either S. entomophila strain A1MO2 or S. proteamaculans AGR96X. Symptoms of disease (non-feeding, amber discolouration) were visually assessed on days three, six, nine, and 12.

LC50 was determined using the bioassay method but using different concentrations of the bacteria-derived from a serially diluted overnight culture (1 × 101 to 1 × 104 CFU/ml), where 5 µL of a dilution was pipetted onto a carrot cube.

For co-infection of C. giveni larvae a 50:50 infection was undertaken using a 3 mm3 cube of carrot inoculated with 5 µL of overnight culture (resulting in 3.1 × 107 CFU 626 and 4.8 × 107 CFU 626::RipC per carrot cube) that was fed to healthy grass grub larvae (~ 24 per treatment).

Enumeration of bacteria from larval macerates

Costelytra giveni larvae were weighed before macerating in a total volume of 1 mL dd.H20. Macerates of larvae removed at days 3, 6, 9, and 12 were subjected to serial dilution and plated onto CTA plates selective for wildtype S. entomophila 626 and the colonies then patched to LB agar tetracycline plates selective for 626::RipC. Three larval macerates were assessed at each time point. The isolates were validated as S. entomophila using media as outlined by O'Callaghan [16] and when required using genomic BOX-PCR DNA fingerprinting using the BOXA1R primer was used to validate S. entomophila isolates [72].

Statistical analysis

P-values were generated using a two-sample t-test for bioassay data based on the instance of disease, death, or combined outcome relative to the untreated control for each assay using Minitab 18. Error bars used in graphs of bioassay data and bio infectivity assays generated in GraphPad Prism 9.2 were generated as the standard error of the mean.

Availability of data and materials

The datasets generated and/or analysed during the current study are available in the GenBank NIH genetic sequence database (GenBank: https://www.ncbi.nlm.nih.gov/genbank/) under the accession CP074347 (Table 2). Raw sequencing reads were deposited to the NCBI SRA archive under the accessions SRR19427101- SRR19427102.

Abbreviations

Afp:

Anti-feeding prophage

Amp:

Ampicillin

ANI:

Average nucleotide identity

BlastN:

Nucleotide sequence/ query Blast search

BlastP:

Protein sequence/ query Blast search

bp:

Base pair

CFU:

Colony-forming units

Cm:

Chloramphenicol

COG:

Cluster of Orthologous Group

DNA:

Deoxyribonucleic acid

FGD:

Functional genome distribution

HGT:

Horizontal gene transfer

Kb:

Kilobase

LB:

Luria–Bertani growth medium

LT50 :

Lethal-time 50: minimum time to cause 50% death

Mb:

Mega base

NCBI:

National Center for Biotechnology Information

OD:

Optical density

pADAP:

Amber disease-associated plasmid

PBS:

Phosphate-buffered saline

PCR:

Polymerase chain reaction

RNA:

Ribonucleic acid

rpm:

Rotations per minute

Sep-TC:

Serratia entomophila pathogenicity toxin complex

Tet:

Tetracycline

tRNA:

Transfer-ribonucleic acid

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Acknowledgements

This work was supported by the New Zealand Tertiary Education Commission under the Centre for Research Excellence Programme. We thank Dr Chikako van Koten for statistical assistance as well as Dr Lesley Sitter and Amy Beattie for gDNA preparation.

Funding

TEC-Centre of Excellence Funding.

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Authors and Affiliations

  1. Bio-Protection Research Centre, Lincoln University, Lincoln, Christchurch, New Zealand

    Amy L. Vaughan, Travis R. Glare & Mark R. H. Hurst

  2. AgResearch, Resilient Agriculture, Lincoln Research Centre, Christchurch, New Zealand

    Amy L. Vaughan & Mark R. H. Hurst

  3. AgResearch, Consumer Interface, Hopkirk Research Centre, Palmerston North, New Zealand

    Eric Altermann

  4. Riddet Institute, Massey University, Palmerston North, New Zealand

    Eric Altermann

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  1. Amy L. Vaughan
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  4. Mark R. H. Hurst
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Contributions

ALV conducted genomic and lab -based analysis. EA created genome atlas and undertook COG/ FGD analyses. Project conceptualization by TG and MRHH. All authors contributed to the writing of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Amy L. Vaughan.

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Supplementary Information

Additional file 1.

COG breakdown of Serratia entomophila 626 in comparison to the 5 selected Serratia species from Genbank. No. denotes number of COGs per isolate; % the percentage of the genome made up by this category.

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Vaughan, A.L., Altermann, E., Glare, T.R. et al. Genome sequence of the entomopathogenic Serratia entomophila isolate 626 and characterisation of the species specific itaconate degradation pathway. BMC Genomics 23, 728 (2022). https://doi.org/10.1186/s12864-022-08938-2

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Keywords

BMC Genomics

ISSN: 1471-2164

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