Comparative genomics analysis to explore the biodiversity and mining novel target genes of Listeria monocytogenes strains from different regions.

As a common foodborne pathogen, infection with L. monocytogenes poses a significant threat to human life and health. The objective of this study was to employ comparative genomics to unveil the biodiversity and evolutionary characteristics of L. monocytogenes strains from different regions, screening for potential target genes and mining novel target genes, thus providing significant reference value for the specific molecular detection and therapeutic targets of L. monocytogenes strains. Pan-genomic analysis revealed that L. monocytogenes from different regions have open genomes, providing a solid genetic basis for adaptation to different environments. These strains contain numerous virulence genes that contribute to their high pathogenicity. They also exhibit relatively high resistance to phosphonic acid, glycopeptide, lincosamide, and peptide antibiotics. The results of mobile genetic elements indicate that, despite being located in different geographical locations, there is a certain degree of similarity in bacterial genome evolution and adaptation to specific environmental pressures. The potential target genes identified through pan-genomics are primarily associated with the fundamental life activities and infection invasion of L. monocytogenes, including known targets such as inlB, which can be utilized for molecular detection and therapeutic purposes. After screening a large number of potential target genes, we further screened them using hub gene selection methods to mining novel target genes. The present study employed eight different hub gene screening methods, ultimately identifying ten highly connected hub genes (bglF_1, davD, menE_1, tilS, dapX, iolC, gshAB, cysG, trpA, and hisC), which play crucial roles in the pathogenesis of L. monocytogenes. The results of pan-genomic analysis showed that L. monocytogenes from different regions exhibit high similarity in bacterial genome evolution. The PCR results demonstrated the excellent specificity of the bglF_1 and davD genes for L. monocytogenes. Therefore, the bglF_1 and davD genes hold promise as specific molecular detection and therapeutic targets for L. monocytogenes strains from different regions.

Maximum-scoring path sets on pangenome graphs of constant treewidth.

We generalize a problem of finding maximum-scoring segment sets, previously studied by Csurös (IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2004, 1, 139-150), from sequences to graphs. Namely, given a vertex-weighted graph G and a non-negative startup penalty c, we can find a set of vertex-disjoint paths in G with maximum total score when each path's score is its vertices' total weight minus c. We call this new problem maximum-scoring path sets (MSPS). We present an algorithm that has a linear-time complexity for graphs with a constant treewidth. Generalization from sequences to graphs allows the algorithm to be used on pangenome graphs representing several related genomes and can be seen as a common abstraction for several biological problems on pangenomes, including searching for CpG islands, ChIP-seq data analysis, analysis of region enrichment for functional elements, or simple chaining problems.

A genome-based investigation of the Priestia species isolated from anthrax endemic regions in Kruger National Park.

Priestia is a genus that was renamed from the genus Bacillus based on the conserved signature indels (CSIs) in protein sequences that separate Priestia species from Bacillus, with the latter only including species closely related to B. subtilis and B. cereus. Diagnosis of anthrax, a zoonotic disease, is implicated by tripartite anthrax virulence genes (lef, pagA, and cya) and poly-γ-D-glutamic acid capsular genes cap-ABCDE of Bacillus anthracis. Due to the amplification of anthrax virulence genes in Priestia isolates, the search for homologous anthrax virulence genes within the Priestia genomes (n = 9) isolated from animal blood smears was embarked upon through whole genome sequencing. In silico taxonomic identification of the isolates was conducted using genome taxonomy database (GTDB), average nucleotide identity (ANI), and multi-locus sequence typing (MLST), which identified the genomes as P. aryabhattai (n = 5), P. endophytica (n = 2) and P. megaterium (n = 2). A pan-genome analysis was further conducted on the Priestia genomes, including the screening of virulence, antibiotic resistance genes and mobile genetic elements on the sequenced genomes. The oligoribonuclease NrnB protein sequences showed that Priestia spp. possess a unique CSI that is absent in other Bacillus species. Furthermore, the CSI in P. endophytica is unique from other Priestia spp. Pan-genomic analysis indicates that P. endophytica clusters separately from P. aryabhattai and P. megaterium. In silico BLASTn genome analysis using the SYBR primers, Taqman probes and primers that target the chromosomal marker (Ba-1), protective antigen (pagA), and lethal factor (lef) on B. anthracis, showed partial binding to Priestia regions encoding for hypothetical proteins, pyridoxine biosynthesis, hydrolase, and inhibitory proteins. The antibiotic resistance genes (ARG) profile of Priestia spp. showed that the genomes contained no more than two ARGs. This included genes conferring resistance to rifamycin and fosfomycin on P. endophytica, as well as clindamycin on P. aryabhattai and P. megaterium. Priestia genomes lacked B. anthracis plasmids and consisted of plasmid replicon types with unknown functions. Furthermore, the amplification of Priestia strains may result in false positives when qPCR is used to detect the virulence genes of B. anthracis in soil, blood smears, and/or environmental samples.

Reverse Vaccinology Approach to Identify Novel and Immunogenic Targets against Streptococcus gordonii.

Streptococcus gordonii is a gram-positive, mutualistic bacterium found in the human body. It is found in the oral cavity, upper respiratory tract, and intestines, and presents a serious clinical problem because it can lead to opportunistic infections in individuals with weakened immune systems. Streptococci are the most prevalent inhabitants of oral microbial communities, and are typical oral commensals found in the human oral cavity. These streptococci, along with many other oral microbes, produce multispecies biofilms that can attach to salivary pellicle components and other oral bacteria via adhesin proteins expressed on the cell surface. Antibiotics are effective against this bacterium, but resistance against antibodies is increasing. Therefore, a more effective treatment is needed. Vaccines offer a promising method for preventing this issue. This study generated a multi-epitope vaccine against Streptococcus gordonii by targeting the completely sequenced proteomes of five strains. The vaccine targets are identified using a pangenome and subtractive proteomic approach. In the present study, 13 complete strains out of 91 strains of S. gordonii are selected. The pangenomics results revealed that out of 2835 pan genes, 1225 are core genes. Out of these 1225 core genes, 643 identified as non-homologous proteins by subtractive proteomics. A total of 20 essential proteins are predicted from non-homologous proteins. Among these 20 essential proteins, only five are identified as surface proteins. The vaccine construct is designed based on selected B- and T-cell epitopes of the antigenic proteins with the help of linkers and adjuvants. The designed vaccine is docked against TLR2. The expression of the protein is determined using in silico gene cloning. Findings concluded that Vaccine I with adjuvant shows higher interactions with TLR2, suggesting that the vaccine has the ability to induce a humoral and cell-mediated response to treat and prevent infection; this makes it promising as a vaccine against infectious diseases caused by S. gordonii. Furthermore, validation of the vaccine construct is required by in vitro and in vivo trials to check its actual potency and safety for use to prevent infectious diseases caused by S. gordonii.

MEM-based pangenome indexing for k-mer queries.

Pangenomes are growing in number and size, thanks to the prevalence of high-quality long-read assemblies. However, current methods for studying sequence composition and conservation within pangenomes have limitations. Methods based on graph pangenomes require a computationally expensive multiple-alignment step, which can leave out some variation. Indexes based on k-mers and de Bruijn graphs are limited to answering questions at a specific substring length k. We present Maximal Exact Match Ordered (MEMO), a pangenome indexing method based on maximal exact matches (MEMs) between sequences. A single MEMO index can handle arbitrary-length queries over pangenomic windows. MEMO enables both queries that test k-mer presence/absence (membership queries) and that count the number of genomes containing k-mers in a window (conservation queries). MEMO's index for a pangenome of 89 human autosomal haplotypes fits in 2.04 GB, 8.8× smaller than a comparable KMC3 index and 11.4× smaller than a PanKmer index. MEMO indexes can be made smaller by sacrificing some counting resolution, with our decile-resolution HPRC index reaching 0.67 GB. MEMO can conduct a conservation query for 31-mers over the human leukocyte antigen locus in 13.89 seconds, 2.5x faster than other approaches. MEMO's small index size, lack of k-mer length dependence, and efficient queries make it a flexible tool for studying and visualizing substring conservation in pangenomes.

Comparative Genomics and Characterization of Shigella flexneri Isolated from Urban Wastewater.

Shigella species are a group of highly transmissible Gram-negative pathogens. Increasing reports of infection with extensively drug-resistant varieties of this stomach bug has convinced the World Health Organization to prioritize Shigella for novel therapeutic interventions. We herein coupled the whole-genome sequencing of a natural isolate of Shigella flexneri with a pangenome ana-lysis to characterize pathogen genomics within this species, which will provide us with an insight into its existing genomic diversity and highlight the root causes behind the emergence of quick vaccine escape variants. The isolated novel strain of S. flexneri contained ~4,500 protein-coding genes, 57 of which imparted resistance to antibiotics. A comparative pan-genomic ana-lysis revealed genomic variability of ~64%, the shared conservation of core genes in central metabolic processes, and the enrichment of unique/accessory genes in virulence and defense mechanisms that contributed to much of the observed antimicrobial resistance (AMR). A pathway ana-lysis of the core genome mapped 22 genes to 2 antimicrobial resistance pathways, with the bulk coding for multidrug efflux pumps and two component regulatory systems that are considered to work synergistically towards the development of resistance phenotypes. The prospective evolvability of Shigella species as witnessed by the marked difference in genomic content, the strain-specific essentiality of unique/accessory genes, and the inclusion of a potent resistance mechanism within the core genome, strengthens the possibility of novel serotypes emerging in the near future and emphasizes the importance of tracking down genomic diversity in drug/vaccine design and AMR governance.

Prokrustean Graph: A substring index supporting rapid enumeration across a range of k-mer sizes.

Despite the widespread adoption of k -mer-based methods in bioinformatics, a fundamental question persists: How can we quantify the influence of k sizes in applications? With no universal answer available, choosing an optimal k size or employing multiple k sizes remains application-specific, arbitrary, and computationally expensive. The assessment of the primary parameter k is typically empirical, based on the end products of applications which pass complex processes of genome analysis, comparison, assembly, alignment, and error correction. The elusiveness of the problem stems from a limited understanding of the transitions of k -mers with respect to k sizes. Indeed, there is considerable room for improving both practice and theory by exploring k -mer-specific quantities across multiple k sizes. This paper introduces an algorithmic framework built upon a novel substring representation: the Prokrustean graph. The primary functionality of this framework is to extract various k -mer-based quantities across a range of k sizes, but its computational complexity depends only on maximal repeats, not on the k range. For example, counting maximal unitigs of de Bruijn graphs for k = 10 , … , 100 takes just a few seconds with a Prokrustean graph built on a read set of gigabases in size. This efficiency sets the graph apart from other substring indices, such as the FM-index, which are normally optimized for string pattern searching rather than for depicting the substring structure across varying lengths. However, the Prokrustean graph is expected to close this gap, as it can be built using the extended Burrows-Wheeler Transform (eBWT) in a space-efficient manner. The framework is particularly useful in pangenome and metagenome analyses, where the demand for precise multi- k approaches is increasing due to the complex and diverse nature of the information being managed. We introduce four applications implemented with the framework that extract key quantities actively utilized in modern pangenomics and metagenomics.

b-move: faster bidirectional character extensions in a run-length compressed index.

Due to the increasing availability of high-quality genome sequences, pan-genomes are gradually replacing single consensus reference genomes in many bioinformatics pipelines to better capture genetic diversity. Traditional bioinformatics tools using the FM-index face memory limitations with such large genome collections. Recent advancements in run-length compressed indices like Gagie et al.'s r-index and Nishimoto and Tabei's move structure, alleviate memory constraints but focus primarily on backward search for MEM-finding. Arakawa et al.'s br-index initiates complete approximate pattern matching using bidirectional search in run-length compressed space, but with significant computational overhead due to complex memory access patterns. We introduce b-move, a novel bidirectional extension of the move structure, enabling fast, cache-efficient bidirectional character extensions in run-length compressed space. It achieves bidirectional character extensions up to 8 times faster than the br-index, closing the performance gap with FM-index-based alternatives, while maintaining the br-index's favorable memory characteristics. For example, all available complete E. coli genomes on NCBI's RefSeq collection can be compiled into a b-move index that fits into the RAM of a typical laptop. Thus, b-move proves practical and scalable for pan-genome indexing and querying. We provide a C++ implementation of b-move, supporting efficient lossless approximate pattern matching including locate functionality, available at https://github.com/biointec/b-move under the AGPL-3.0 license.

Comparative Genomics Unveils Functional Diversity, Pangenome Openness, and Underlying Biological Drivers among Bacillus subtilis Group.

The Bacillus subtilis group (Bs group), with Bacillus subtilis as its core species, holds significant research and economic value in various fields, including science, industrial production, food, and pharmaceuticals. However, most studies have been confined to comparative genomics analyses and exploration within individual genomes at the level of species, with few conducted within groups across different species. This study focused on Bacillus subtilis, the model of Gram-positive bacteria, and 14 other species with significant research value, employing comparative pangenomics as well as population enrichment analysis to ascertain the functional enrichment and diversity. Through the quantification of pangenome openness, this work revealed the underlying biological drivers and significant correlation between pangenome openness and various factors, including the distribution of toxin-antitoxin- and integrase-related genes, as well as the number of endonucleases, recombinases, repair system-related genes, prophages, integrases, and transfer mobile elements. Furthermore, the functional enrichment results indicated the potential for secondary metabolite, probiotic, and antibiotic exploration in Bacillus licheniformis, Bacillus paralicheniformis, and Bacillus spizizenii, respectively. In general, this work systematically exposed the quantification of pangenome openness, biological drivers, the pivotal role of genomic instability factors, and mobile elements, providing targeted exploration guidance for the Bs group.

Methods for Pangenomic Core Detection.

Computational pangenomics deals with the joint analysis of all genomic sequences of a species. It has already been successfully applied to various tasks in many research areas. Further advances in DNA sequencing technologies constantly let more and more genomic sequences become available for many species, leading to an increasing attractiveness of pangenomic studies. At the same time, larger datasets also pose new challenges for data structures and algorithms that are needed to handle the data. Efficient methods oftentimes make use of the concept of k-mers.Core detection is a common way of analyzing a pangenome. The pangenome's core is defined as the subset of genomic information shared among all individual members. Classically, it is not only determined on the abstract level of genes but can also be described on the sequence level.In this chapter, we provide an overview of k-mer-based methods in the context of pangenomics studies. We first revisit existing software solutions for k-mer counting and k-mer set representation. Afterward, we describe the usage of two k-mer-based approaches, Pangrowth and Corer, for pangenomic core detection.

Comparative genomics, pangenomics, and phenomic studies of Pectobacterium betavasculorum strains isolated from sugar beet, potato, sunflower, and artichoke: insights into pathogenicity, virulence determinants, and adaptation to the host plant.

Introduction: Bacteria of genus Pectobacterium, encompassing economically significant pathogens affecting various plants, includes the species P. betavasculorum, initially associated with beetroot infection. However, its host range is much broader. It causes diseases of sunflower, potato, tomato, carrots, sweet potato, radish, squash, cucumber, and chrysanthemum. To explain this phenomenon, a comprehensive pathogenomic and phenomic characterisation of P. betavasculorum species was performed. Methods: Genomes of P. betavasculorum strains isolated from potato, sunflower, and artichoke were sequenced and compared with those from sugar beet isolates. Metabolic profiling and pathogenomic analyses were conducted to assess virulence determinants and adaptation potential. Pathogenicity assays were performed on potato tubers and chicory leaves to confirm in silico predictions of disease symptoms. Phenotypic assays were also conducted to assess the strains ability to synthesise homoserine lactones and siderophores. Results: The genome size ranged from 4.675 to 4.931 kbp, and GC % was between 51.0% and 51.2%. The pangenome of P. betavasculorum is open and comprises, on average, 4,220 gene families. Of these, 83% of genes are the core genome, and 2% of the entire pangenome are unique genes. Strains isolated from sugar beet have a smaller pangenome size and a higher number of unique genes than those from other plants. Interestingly, genomes of strains from artichoke and sunflower share 391 common CDS that are not present in the genomes of other strains from sugar beet or potato. Those strains have only one unique gene. All strains could use numerous sugars as building materials and energy sources and possessed a high repertoire of virulence determinants in the genomes. P. betavasculorum strains were able to cause disease symptoms on potato tubers and chicory leaves. They were also able to synthesise homoserine lactones and siderophores. Discussion: The findings underscore the adaptability of P. betavasculorum to diverse hosts and environments. Strains adapted to plants with high sugar content in tissues have a different composition of fatty acids in membranes and a different mechanism of replenishing nitrogen in case of deficiency of this compound than strains derived from other plant species. Extensive phenomics and genomic analyses performed in this study have shown that P. betavasculorum species is an agronomically relevant pathogen.

Pfp-fm: an accelerated FM-index.

FM-indexes are crucial data structures in DNA alignment, but searching with them usually takes at least one random access per character in the query pattern. Ferragina and Fischer [1] observed in 2007 that word-based indexes often use fewer random accesses than character-based indexes, and thus support faster searches. Since DNA lacks natural word-boundaries, however, it is necessary to parse it somehow before applying word-based FM-indexing. In 2022, Deng et al. [2] proposed parsing genomic data by induced suffix sorting, and showed that the resulting word-based FM-indexes support faster counting queries than standard FM-indexes when patterns are a few thousand characters or longer. In this paper we show that using prefix-free parsing-which takes parameters that let us tune the average length of the phrases-instead of induced suffix sorting, gives a significant speedup for patterns of only a few hundred characters. We implement our method and demonstrate it is between 3 and 18 times faster than competing methods on queries to GRCh38, and is consistently faster on queries made to 25,000, 50,000 and 100,000 SARS-CoV-2 genomes. Hence, it seems our method accelerates the performance of count over all state-of-the-art methods with a moderate increase in the memory. The source code for PFP - FM is available at https://github.com/AaronHong1024/afm .

Measuring, visualizing, and diagnosing reference bias with biastools.

Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it. Biastools analyzes and categorizes instances of reference bias. It works in various scenarios: when the donor's variants are known and reads are simulated; when donor variants are known and reads are real; and when variants are unknown and reads are real. Using biastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we use biastools to characterize how T2T references improve large-scale bias.

PPanG: a precision pangenome browser enabling nucleotide-level analysis of genomic variations in individual genomes and their graph-based pangenome.

Graph-based pangenome is gaining more popularity than linear pangenome because it stores more comprehensive information of variations. However, traditional linear genome browser has its own advantages, especially the tremendous resources accumulated historically. With the fast-growing number of individual genomes and their annotations available, the demand for a genome browser to visualize genome annotation for many individuals together with a graph-based pangenome is getting higher and higher. Here we report a new pangenome browser PPanG, a precise pangenome browser enabling nucleotide-level comparison of individual genome annotations together with a graph-based pangenome. Nine rice genomes with annotations were provided by default as potential references, and any individual genome can be selected as the reference. Our pangenome browser provides unprecedented insights on genome variations at different levels from base to gene, and reveals how the structures of a gene could differ for individuals. PPanG can be applied to any species with multiple individual genomes available and it is available at https://cgm.sjtu.edu.cn/PPanG .

Anaerostipes hadrus, a butyrate-producing bacterium capable of metabolizing 5-fluorouracil.

Anaerostipes hadrus (A. hadrus) is a dominant species in the human gut microbiota and considered a beneficial bacterium for producing probiotic butyrate. However, recent studies have suggested that A. hadrus may negatively affect the host through synthesizing fatty acid and metabolizing the anticancer drug 5-fluorouracil, indicating that the impact of A. hadrus is complex and unclear. Therefore, comprehensive genomic studies on A. hadrus need to be performed. We integrated 527 high-quality public A. hadrus genomes and five distinct metagenomic cohorts. We analyzed these data using the approaches of comparative genomics, metagenomics, and protein structure prediction. We also performed validations with culture-based in vitro assays. We constructed the first large-scale pan-genome of A. hadrus (n = 527) and identified 5-fluorouracil metabolism genes as ubiquitous in A. hadrus genomes as butyrate-producing genes. Metagenomic analysis revealed the wide and stable distribution of A. hadrus in healthy individuals, patients with inflammatory bowel disease, and patients with colorectal cancer, with healthy individuals carrying more A. hadrus. The predicted high-quality protein structure indicated that A. hadrus might metabolize 5-fluorouracil by producing bacterial dihydropyrimidine dehydrogenase (encoded by the preTA operon). Through in vitro assays, we validated the short-chain fatty acid production and 5-fluorouracil metabolism abilities of A. hadrus. We observed for the first time that A. hadrus can convert 5-fluorouracil to α-fluoro-ß-ureidopropionic acid, which may result from the combined action of the preTA operon and adjacent hydA (encoding bacterial dihydropyrimidinase). Our results offer novel understandings of A. hadrus, exceptionally functional features, and potential applications. IMPORTANCE: This work provides new insights into the evolutionary relationships, functional characteristics, prevalence, and potential applications of Anaerostipes hadrus.

Spatial ecology of Haemophilus and Aggregatibacter in the human oral cavity.

Haemophilus and Aggregatibacter are two of the most common bacterial genera in the human oral cavity, encompassing both commensals and pathogens of substantial ecological and medical significance. In this study, we conducted a metapangenomic analysis of oral Haemophilus and Aggregatibacter species to uncover genomic diversity, phylogenetic relationships, and habitat specialization within the human oral cavity. Using three metrics-pangenomic gene content, phylogenomics, and average nucleotide identity (ANI)-we first identified distinct species and sub-species groups among these genera. Mapping of metagenomic reads then revealed clear patterns of habitat specialization, such as Aggregatibacter species predominantly in dental plaque, a distinctive Haemophilus parainfluenzae sub-species group on the tongue dorsum, and H. sp. HMT-036 predominantly in keratinized gingiva and buccal mucosa. In addition, we found that supragingival plaque samples contained predominantly only one out of the three taxa, H. parainfluenzae, Aggregatibacter aphrophilus, and A. sp. HMT-458, suggesting independent niches or a competitive relationship. Functional analyses revealed the presence of key metabolic genes, such as oxaloacetate decarboxylase, correlated with habitat specialization, suggesting metabolic versatility as a driving force. Additionally, heme synthesis distinguishes H. sp. HMT-036 from closely related Haemophilus haemolyticus, suggesting that the availability of micronutrients, particularly iron, was important in the evolutionary ecology of these species. Overall, our study exemplifies the power of metapangenomics to identify factors that may affect ecological interactions within microbial communities, including genomic diversity, habitat specialization, and metabolic versatility. IMPORTANCE: Understanding the microbial ecology of the mouth is essential for comprehending human physiology. This study employs metapangenomics to reveal that various Haemophilus and Aggregatibacter species exhibit distinct ecological preferences within the oral cavity of healthy individuals, thereby supporting the site-specialist hypothesis. Additionally, it was observed that the gene pool of different Haemophilus species correlates with their ecological niches. These findings shed light on the significance of key metabolic functions in shaping microbial distribution patterns and interspecies interactions in the oral ecosystem.

Pangenomics: A new era in the field of neurodegenerative diseases.

A pangenome is composed of all the genetic variability of a group of individuals, and its application to the study of neurodegenerative diseases may provide valuable insights into the underlying aspects of genetic heterogenetiy for these complex ailments, including gene expression, epigenetics, and translation mechanisms. Furthermore, a reference pangenome allows for the identification of previously undetected structural commonalities and differences among individuals, which may help in the diagnosis of a disease, support the prediction of what will happen over time (prognosis) and aid in developing novel treatments in the perspective of personalized medicine. Therefore, in the present review, the application of the pangenome concept to the study of neurodegenerative diseases will be discussed and analyzed for its potential to enable an improvement in diagnosis and prognosis for these illnesses, leading to the development of tailored treatments for individual patients from the knowledge of the genomic composition of a whole population.

High genetic diversity and different type VI secretion systems in Enterobacter species revealed by comparative genomics analysis.

The human-pathogenic Enterobacter species are widely distributed in diverse environmental conditions, however, the understanding of the virulence factors and genetic variations within the genus is very limited. In this study, we performed comparative genomics analysis of 49 strains originated from diverse niches and belonged to eight Enterobacter species, in order to further understand the mechanism of adaption to the environment in Enterobacter. The results showed that they had an open pan-genome and high genomic diversity which allowed adaptation to distinctive ecological niches. We found the number of secretion systems was the highest among various virulence factors in these Enterobacter strains. Three types of T6SS gene clusters including T6SS-A, T6SS-B and T6SS-C were detected in most Enterobacter strains. T6SS-A and T6SS-B shared 13 specific core genes, but they had different gene structures, suggesting they probably have different biological functions. Notably, T6SS-C was restricted to E. cancerogenus. We detected a T6SS gene cluster, highly similar to T6SS-C (91.2%), in the remote related Citrobacter rodenitum, suggesting that this unique gene cluster was probably acquired by horizontal gene transfer. The genomes of Enterobacter strains possess high genetic diversity, limited number of conserved core genes, and multiple copies of T6SS gene clusters with differentiated structures, suggesting that the origins of T6SS were not by duplication instead by independent acquisition. These findings provide valuable information for better understanding of the functional features of Enterobacter species and their evolutionary relationships.