Genome assembly

The paired end (2 × 100 bp) DNA libraries were produced for Acinetobactor lwoffii using Illumina NextSeq 2000. In total, 5.67 million paired end reads (572 Mb) were generated with GC content of 43% and an average coverage of 150X. The raw sequence reads used for whole genome assembly are deposited in NCBI SRA database under bioproject PRJNA804363 (SRR17931548). After quality trimming using Fastp 5.64 million paired end reads (564 Mb) were used for further genome assembly (Supplement−1; Table 1). The genome assembly of Acinetobactor lwoffii was carried out with three different assemblers viz., Velvet, AByss and SPAdes. The genome assembly statistics are given in Table 1. The assembly from the Velvet assembler was obtained as a good assembly. The genome (draft assembly) is also submitted to NCBI genbank with accession.

Table 1 Initial assembly statistics of 3 different assemblers (All statistics with contig size > 200 bp)

Further, the assembly from Velvet assembler was considered for analysis. The gaps between contigs were filled using GFinisher, The A. lwoffii - H7 strain as reference genome. The gap-filled assembly resulted in the assembly size of 3,215,270 bp (3.2 Mb) with 35 scaffolds and N50 260,745 bp and GC content of 43.06%. The largest scaffold size was found to be 434,866 bp with an average scaffold size of 91,864.9 bp. The final genome assembly, assessed using CheckM, exhibited 99.66% completeness with a 1.44% contamination level. The analysis was conducted using CheckM, selecting the Moraxellaceae family as the marker lineage, which included 86 reference genomes and 689 marker sets. The circular genome plotted by GenoVi demonstrated the quality of both the forward and reverse sequences of the genome. Figure 1 indicates both forward sequences (sky blue circle) and reverse sequences (dark blue circle) where the GC content and GC skew were also flaunted for abundance.

Fig. 1The alternative text for this image may have been generated using AI.

Circular DNA plot of A. lwoffii plotted using GenoVi, showing annotated genomic features including coding sequences, GC content, and GC skew across the entire chromosome

Genome annotation

The genome annotation using Prokka resulted in identification of 3032 numbers of genes, five rRNA, 70 tRNA genes, one tmRNA gene and 24 miscellaneous RNAs. The coding sequences (CDS) were annotated using Uniprot, Enzyme Commission (EC) and Clusters of Orthologous genes (COG) databases. Out of 3032 CDS, function of 1968 proteins were predicted and 1064 were predicted as hypothetical proteins. Total 1844 CDS were annotated using UniProt, 1564 were annotated using COG and 1119 were annotated using EC (Table 2).

Table 2 Genome annotation of A. lwoffii

Further GO terms were assigned using uniprot retrieve ID mapping tool. The proteins were classified into “biological process”, “cellular components” and “molecular function” GO terms. The top GOs from biological processes are the regulation of DNA transcription, response to antibiotics, and cell wall organization, suggesting significant activity related to genetic regulation, defense mechanisms against antibiotics, and structural integrity maintenance. The predominant cellular components include the plasma membrane, cytosol, and cytoplasm, indicating the importance of these structures in various cellular functions such as transport, metabolism, and structural support. The major molecular functions include ATP binding, metal ion binding, and identical protein binding, highlighting the importance of energy transfer and storage, metal ion coordination in enzymatic reactions, and protein-protein interactions in the organism’s biology.

The hypothetical proteins identified in this study were further analyzed to detect functional domains using the NCBI Conserved Domains (NCBI-CD) database. In total, 4,872 conserved domains were identified from the hypothetical proteins analyzed. Among these, 836 were classified as specific domains, while 1,728 belonged to the superfamily level, and 2,308 were categorized as non-specific domains. Overall, a diverse range of 3,403 unique domains were detected. Total, 123 proteins were categorized as proteins of unknown function or containing domains of unknown function (DUF). Additionally, 33 proteins were identified as conserved specifically in bacteria, shows their broader bacterial conservation. Furthermore, 18 proteins were found to be specifically conserved within the genus Acinetobacter, reflecting their potential genus-specific functional roles. The analysis revealed various specific domains, including DOMON_murB_like domain, RimL and Acetyltransf_3 domains, TlyC, CorC_HlyC, CNNM, and CBS domains in, as well as DUF4112. Other significant domains identified include SCP2, DUF4917, PiuB and PepSY_TM domains, Tim44, and LPAM_2. Additionally, domains such as TolC, YaiI, DUF188, and PIN_YqxD-like, GlyGly_RbtA, and many other conserved or hypothetical domains across different proteins were observed.

To further assess the functional importance of the annotated genes, we performed Gene Ontology (GO) enrichment analysis. As shown in Fig. 2, the most significantly enriched Biological Process terms include “translation,” “gene expression,” and various metabolic processes (e.g., nitrogen compound metabolic process and biosynthetic process). Within the Molecular Function category, terms such as “catalytic activity,” “binding,” and “ion binding” show high enrichment, showing the abundance of enzymes and transporters that facilitate nutrient acquisition and stress adaptation. The top Cellular Component terms include “intracellular,” “cytoplasm,” and “ribosome,” emphasizing the importance of core cellular machinery in sustaining growth and metabolic activity.

Fig. 2The alternative text for this image may have been generated using AI.

Gene Ontology (GO) enrichment analysis of A. lwoffii, representing the distribution of predicted genes across three major categories: biological processes, molecular functions, and cellular components

Also, the genes from A. lwoffii were classified into different clusters of orthologous groups of proteins (COG). Among these, the most prevalent categories include translation, ribosomal structure and biogenesis, lipid transport and metabolism, Energy production and conversion, amino acid transport and metabolism, and cell wall/membrane/envelope biogenesis, with 190, 127, 124, 122, and 110 genes respectively. These categories highlight the organism’s significant involvement in protein synthesis machinery, lipid metabolism, energy generation, amino acid utilization, and cell envelope integrity, suggesting adaptations crucial for survival, metabolic versatility, and interactions within its ecological niche. Additionally, a diverse array of functional categories such as inorganic ion transport and metabolism, coenzyme transport and metabolism, and Post-translational modifications, protein turnover, chaperones exhibit notable representation, reflecting the organism’s multifaceted metabolic capabilities and adaptive strategies. Furthermore, genes associated with replication, recombination, and repair underscore the importance of DNA maintenance mechanisms for genomic stability and evolutionary resilience (Supplement−2: Fig. 2).

The RAST annotation predicts 3203 Protein Encoding Genes (PEGs) categorized into 275 subsystems. The analysis revealed a subsystem coverage of 28% and non-subsystem coverage of 72%. A total coverage of 858 subsystems and 2272 non-subsystems was predicted for this bacterial strain. Within the subsystem coverage, the sizes of hypothetical and non-hypothetical genes were observed to be 20 and 838, respectively (Supplement−2: Fig. 3A). Notably, the highest percentage of subsystem features was attributed to “amino acids and derivatives”, followed by “protein metabolism”, while the lowest percentages were associated with categories such as “phages, prophages, transposable elements, plasmids”, “dormancy and sporulation”, “potassium metabolism”, and “sulfur metabolism”. In the domain of nitrogen metabolism, specific processes including nitrosative stress (1), cyanate hydrolysis (1), and ammonia assimilation (8) were identified (Supplement−2: Fig. 3C).

Fig. 3The alternative text for this image may have been generated using AI.

Predicted KEGG pathways of A. lwoffii (Global and overview map), generated from annotated genes, displaying the organism’s involvement in various metabolic and cellular processes

Further the genome annotation of A. lwoffii revealed the potential genes associated with plant growth promotion (PGP), noteworthy instances including gltD, which plays a role in nitrogen assimilation, trpABCDE, which is accountable for the synthesis of indole−3-acetic acid (IAA); ilvIH, responsible for the synthesis of acetoin, a plant growth-promoting signaling molecule; pstABC, facilitating the uptake and utilization of phosphate. Moreover, genomic analysis has identified genes possessing antioxidant capabilities that can alleviate oxidative stress in plants under various stress conditions, whether biotic or abiotic. These genes include trxB, msrA, hmp, as well as nhaX and nhaP. trxB and msrA function in suppressing responses to oxidative stress, while hmp acts as a NO-inducible flavohemoprotein aiding in the detoxification of free radicals during stress. Additionally, nhaX and nhaP are involved in preserving ion homeostasis by regulating extracellular ion levels (Table 3).

The genomic analysis of A. lwoffii identified key genes associated with plant growth-promoting traits. Genes involved in indole−3-acetic acid (IAA) biosynthesis, such as syrM1, trpA, trpB, trpC, trpD, and trpE, were detected (Table 3), suggesting the bacterium’s potential for auxin production, which is crucial for root elongation and overall plant growth. Additionally, genes linked to phosphorus metabolism, including pstA, phoU, and phoR, were found, indicating the bacterium’s ability to solubilize phosphate and enhance phosphorus availability in nutrient-limited soils. Furthermore, the presence of biofilm formation-related genes such as mepB and fimA suggests the bacterium’s capacity to establish biofilms, facilitating rhizosphere colonization and increased bacterial persistence under environmental stress.

Table 3 List of PGPR related genes identified in A. lwoffii DJPGP01Pathway analysis

The protein sequences of A. lwoffii were searched against the KEGG database using the KEGG-KAAS server. Total 1602 genes were assigned KEGG Orthology (KO) identifiers. Further these KEGG Orthology (KO) numbers were used in the KEGG reconstruct tool to characterize the pathways. Total 224 pathways were identified. The KEGG classified pathways into different classes such as metabolism, genetic information processing, environmental information processing, cellular processes and organismal systems. Further each of these classes were classified into subclasses. The metabolic pathways (536) is the pathway with more genes in metabolism - Global and overview maps followed by biosynthesis of secondary metabolites (218), microbial metabolism in diverse environments (162) (Fig. 3).

Additional genes related to pathways such as environmental information processing and cellular processes were examined to gather information on genes and pathways associated with promoting plant growth. In terms of environmental information processing, the two-component system exhibited a notable presence with 52 genes, indicating its significant role in signal transduction. Additionally, ATP binding cassette (ABC) transporters, crucial for membrane transport, were represented by 46 genes, suggesting their importance in facilitating environmental responses. Within cellular processes, cellular community dynamics in prokaryotes were evident, in particular in quorum sensing with 25 genes and biofilm formation in various bacteria such as Pseudomonas aeruginosa (21 genes) and Vibrio cholerae (15 genes). Moreover, cellular growth and death mechanisms were observed, including the cell cycle in Caulobacter (10 genes) and biofilm formation in Escherichia coli (10 genes). The involvement of transport and catabolism pathways is notable as well, with seven genes associated with peroxisome function (Supplement−1: Table 2).

The quorum sensing (QS) system plays a vital role in plant growth-promoting rhizobacteria (PGPR) response to environmental stress and induce plant tolerance. The secretion of quorum sensing (QS) molecules is crucial for facilitating the successful colonization of host plants by plant growth-promoting rhizobacteria. In A. lwoffii genome, we identified 25 genes related to quorum sensing pathways. These genes, including PhnA and PhnB, are involved in phosphonate metabolism, while RpfB, regulates various physiological processes including biofilm formation and quorum sensing in bacteria. Also these genes are the biosynthetic proteins in the QS pathway. QseC is a gene that encodes for a histidine sensor kinase protein in bacteria, playing a pivotal role in sensing environmental signals is involved as an autoinducer in QS. The sensing proteins such as Hfq, PhnA, PhnB, PhzC, QseB, Clp, Zur, ToxB, ToxE and ToxI were identified in the QS pathway.

The comparison of this strain along with five other clinical strains of A. lwoffii identified a total of 5840 genes. Of these, 2109 genes were present in almost all isolates (99–100%), while 3731 genes showed variable distribution among the isolates (15–95%). Strain DJPGP01 exhibited a distinct genetic composition, containing genes exclusive to this isolate and absent in all others. Additionally, certain genes found in at least three other clinical isolates were absent in DJPGP01. A total of 403 genes uniquely present in strain DJPGP01. Some of the notable unique genes found exclusively in DJPGP01 include copA_5, yhbO_3, yqhD_2, frmR_2, pks5_2, nicP_2, and hcaB_2. However, 176 genes were absent in DJPGP01 but present in at least three other clinical isolates. Some notable genes from this group include F924_02973, F923_00138, HMPREF0017_02840, F923_00119, F923_03018, F924_03528, and HMPREF0017_00290. The genes epsL_1 and epsL_2 present uniquely in DJPGP01 and which is absent in all other 5 clinical isolates and encodes components of the type II secretion system, which is associated with biofilm formation, an important trait for plant-microbe interactions and colonization efficiency in plant growth-promoting rhizobacteria (PGPR).

Genomic islands (GIs) of A. lwoffii

Genomic islands were predicted using SIGI-HMM and IslandPath-DIMOB from IslandViewer 4. Total 26 genomic islands mostly containing genes of unknown function i.e. hypothetical proteins (186) have been identified in the genome when aligned against reference genome A. lwoffii strain H7 (Fig. 4). These genomic islands are the regions of the genome that provide evidence about the horizontal gene transfer which play an important role in the evolution, and diversification of pathogenic microbes and the adaptation of bacteria to different environments. All genes identified at genomic islands are given in Supplement−1; Table 3.

Fig. 4The alternative text for this image may have been generated using AI.

Genomic islands prediction and circular genome visualization of A. lwoffii DJPGP01. Genomic islands (GIs) were predicted using IslandViewer4, which integrates three methods: IslandPath-DIMOB, SIGI-HMM, and IslandPick. In the figure, blue regions represent GIs predicted by IslandPath-DIMOB, orange regions by SIGI-HMM, and red regions indicate loci predicted by at least one method. The genome visualization includes circular tracks for coding sequences, GC content, and predicted islands

Prediction of secondary metabolite gene clusters

The secondary metabolite gene clusters were predicted using antiSMASH, an online tool. A total five Secondary Metabolite Gene Clusters (SMGCs) were identified from the A. lwoffii genome including 3 beta lactone synthesis gene clusters, RiPP-like, and aryl polyene. The aryl polyene gene cluster contains 39 genes including one core biosynthetic gene (“3-oxoacyl-[acyl-carrier-protein] synthase 1”), one regulatory gene (“Leucine-responsive regulatory protein”), three transport genes, and nine biosynthetic genes (Supplement−2: Fig. 4). The aryl polyene gene clusters predicted were compared and which showed more than 95% similarity with the genes of aryl polyene gene clusters from A. lwoffi.

Analysis of average nucleotide identity (ANI)

The Average Nucleotide Identity (ANI) analysis for the submitted genome showed a high degree of similarity to the reference genome, with an average ANI value of 95.96% based on three different computations: one-way ANI from 14,121 fragments at 95.79%, another one-way ANI from 13,961 fragments at 95.78%, and two-way ANI from 12,529 fragments at 95.96%. The identity distribution histogram displays a mode near the 96% mark, further substantiated by a median of 96.34%. Additionally, the bit-score distribution analysis indicates robust alignment support, evidenced by a mean bit-score of 1568 and a median of 1587, suggesting a close genomic relationship between the query and the reference genomes, which belong to the genus Acinetobacter (Fig. 5).

Fig. 5The alternative text for this image may have been generated using AI.

Whole-genome-based phylogenetic tree of Acinetobacter species, constructed using the Type (Strain) Genome Server (TYGS). Phylogeny was inferred using Genome BLAST Distance Phylogeny (GBDP) with FastME (v2.1.6.1) based on intergenomic distances. The tree includes bootstrap support values (n = 100 replicates) shown at internal nodes. Branch lengths reflect inferred genomic distances, and the isolate DJPGP01 clusters closely with A. lwoffii NCTC 5866, confirming its taxonomic placement

Species identification and phylogenetic analysis of A. lwoffii

Species identification was initially performed through barrnap analysis, which identified five rRNA sequences from the assembled genome, including one 16 S, three 23 S, and one 5 S rRNA. The predicted 16S rRNA sequence was 1533 base pairs in length. Alignment of this sequence with the NCBI ribosomal database showed a 99.66% similarity with A. lwoffii strain DSM 2403 and 99.45% with A. lwoffii strain JCM 6840, exceeding the threshold of ≥ 98.65–99% for species-level classification (Stackebrandt and Ebers 2006; Kim et al. 2014), thus confirming the isolate as A. lwoffii (Supplement−2: Fig. 1).

For comparative analysis, the genome of Acinetobacter sp. was uploaded to the Type (Strain) Genome Server (TYGS). Both 16S rRNA-based and whole genome-based comparisons were performed. The results from the TYGS database, following an extensive genome-based taxonomic analysis, demonstrate significant insights into the phylogenetic relationships and species identification of the submitted genome sequences. The comprehensive analysis incorporated pairwise comparisons of user genomes against type strain genomes, utilizing different GBDP formulas to assess genome-to-genome relatedness and digital DNA–DNA hybridization (dDDH). The findings indicated that Acinetobacter sp. from this study shows varying levels of genomic similarity with several Acinetobacter species. The highest dDDH values were observed with A. lwoffii NCTC 5866, suggesting a close relationship with dDDH values of 79.5% under formula d0 and 79.7% under formula d6, with minimal deviations in G + C content. Conversely, lower similarity scores were recorded with Acinetobacter indicus CIP 110,367 and Acinetobacter guangdongensis KCTC 42,012, highlighting notable genomic divergence characterized by substantial differences in G + C content and dDDH values below 30%.

The phylogenetic trees, both based on 16S rRNA sequences and whole genome sequences, provide comprehensive insights into the relationships and evolutionary pathways within the Acinetobacter genus. In the genome-based tree, A. lwoffii NCTC 5866 and Acinetobacter idrijaensis MII were depicted with a notably close relationship, which suggests a very recent divergence or high genetic similarity. This proximity might indicate that these species have retained many ancestral traits or that their genomes have not undergone significant diversification since their split (Fig. 6).

Fig. 6The alternative text for this image may have been generated using AI.

Phosphate solubilization assay of A. lwoffii DJPGP01. (A) Pikovskaya’s agar plate showing four spot inoculations with visible halo zones around the colonies, indicating phosphate solubilization. (B) Single colony inoculation on Pikovskaya’s agar showing a distinct halo formation

The phylogenetic analysis based on 16S rRNA sequences from the TYGS reveals detailed evolutionary relationships among various species within the Acinetobacter genus. Notably, the tree elucidates a close genetic proximity between A. lwoffii NCTC 5866, Acinetobacter mesopotamicus DSM 26,953, and Acinetobacter idrijaensis MII, supported by a bootstrap value of 100, indicating a robust clade with a recent common ancestry. This suggests that Acinetobacter species share a recent common ancestor with these taxa, indicating a potentially shared evolutionary history and similar ecological or physiological traits. The positioning of Acinetobacter sp. in the tree highlights its evolutionary relevance and possibly underscores its role as a representative model for studying adaptive traits, pathogenic potential, or resistance mechanisms at the genus level (Supplement-2: Fig. 5).

Phosphate solubilization by A. lwoffii

The isolate A. lwoffii DJPGP01 demonstrated phosphate solubilization activity, as evident from the formation of clear halos surrounding the colonies on Pikovskaya’s agar plates (Fig. 6). This experimental validation supports the genomic predictions, where multiple genes associated with phosphate uptake and solubilization, including alkaline phosphatases (phoP), exopolyphosphatases (ppx), and transport systems (pstABC), were identified in the genome of A. lowfii DJPGP01 (Table 3).