Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models

Evaluating the Safety of Bacillus cereus GW-01 Obtained from Sheep Rumen Chyme

Bacillus cereus is responsible for 1.4-12% food poisoning outbreaks worldwide. The safety concerns associated with the applications of B. cereus in health and medicine have been controversial due to its dual role as a pathogen for foodborne diseases and a probiotic in humans and animals. In this study, the pathogenicity of B. cereus GW-01 was assessed by comparative genomic, and transcriptome analysis. Phylogenetic analysis based on a single-copy gene showed clustering of the strain GW-01, and 54 B. cereus strains from the NCBI were classified into six major groups (I-VI), which were then associated with the source region and sequence types (STs). Transcriptome results indicated that the expression of most genes related with toxins secretion in GW-01 was downregulated compared to that in the lag phase. Overall, these findings suggest that GW-01 is not directly associated with pathogenic Bacillus cereus and highlight an insightful strategy for assessing the safety of novel B. cereus strains.

Discovering genomic islands in unannotated bacterial genomes using sequence embedding

Motivation

Genomic islands (GEIs) are clusters of genes in bacterial genomes that are typically acquired by horizontal gene transfer. GEIs play a crucial role in the evolution of bacteria by rapidly introducing genetic diversity and thus helping them adapt to changing environments. Specifically of interest to human health, many GEIs contain pathogenicity and antimicrobial resistance genes. Detecting GEIs is, therefore, an important problem in biomedical and environmental research. There have been many previous studies for computationally identifying GEIs. Still, most of these studies rely on detecting anomalies in the unannotated nucleotide sequences or on a fixed set of known features on annotated nucleotide sequences.

Results

Here, we present TreasureIsland, which uses a new unsupervised representation of DNA sequences to predict GEIs. We developed a high-precision boundary detection method featuring an incremental fine-tuning of GEI borders, and we evaluated the accuracy of this framework using a new comprehensive reference dataset, Benbow. We show that TreasureIsland's accuracy rivals other GEI predictors, enabling efficient and faster identification of GEIs in unannotated bacterial genomes.

Availability and implementation

TreasureIsland is available under an MIT license at: https://github.com/FriedbergLab/GenomicIslandPrediction.

DICEP: An integrative approach to augmenting genomic island detection

Mobilization of clusters of genes called genomic islands (GIs) across bacterial lineages facilitates dissemination of traits, such as, resistance against antibiotics, virulence or hypervirulence, and versatile metabolic capabilities. Robust delineation of GIs is critical to understanding bacterial evolution that has a vast impact on different life forms. Methods for identification of GIs exploit different evolutionary features or signals encoded within the genomes of bacteria, however, the current state-of-the-art in GI detection still leaves much to be desired. Here, we have taken a combinatorial approach that accounted for GI specific features such as compositional bias, aberrant phyletic pattern, and marker gene enrichment within an integrative framework to delineate GIs in bacterial genomes. Our GI prediction tool, DICEP, was assessed on simulated genomes and well-characterized bacterial genomes. DICEP compared favorably with current GI detection tools on real and synthetic datasets.

Pan-genome insights into adaptive evolution of bacterial symbionts in mixed host-microbe symbioses represented by human gut microbiota Bacteroides cellulosilyticus

Animal hosts harbor diverse assemblages of microbial symbionts that play crucial roles in the host's lifestyle. The link between microbial symbiosis and host development remains poorly understood. In particular, little is known about the adaptive evolution of gut bacteria in host-microbe symbioses. Recently, symbiotic relationships have been categorized as open, closed, or mixed, reflecting their modes of inter-host transmission and resulting in distinct genomic features. Members of the genus Bacteroides are the most abundant human gut microbiota and possess both probiotic and pathogenic potential, providing an excellent model for studying pan-genome evolution in symbiotic systems. Here, we determined the complete genome of an novel clinical strain PL2022, which was isolated from a blood sample and performed pan-genome analyses on a representative set of Bacteroides cellulosilyticus strains to quantify the influence of the symbiotic relationship on the evolutionary dynamics. B. cellulosilyticus exhibited correlated genomic features with both open and closed symbioses, suggesting a mixed symbiosis. An open pan-genome is characterized by abundant accessory gene families, potential horizontal gene transfer (HGT), and diverse mobile genetic elements (MGEs), indicating an innovative gene pool, mainly associated with genomic islands and plasmids. However, massive parallel gene loss, weak purifying selection, and accumulation of positively selected mutations were the main drivers of genome reduction in B. cellulosilyticus. Metagenomic read recruitment analyses showed that B. cellulosilyticus members are globally distributed and active in human gut habitats, in line with predominant vertical transmission in the human gut. However, existence and/or high abundance were also detected in non-intestinal tissues, other animal hosts, and non-host environments, indicating occasional horizontal transmission to new niches, thereby creating arenas for the acquisition of novel genes. This case study of adaptive evolution under a mixed host-microbe symbiosis advances our understanding of symbiotic pan-genome evolution. Our results highlight the complexity of genetic evolution in this unusual intestinal symbiont.

A comprehensive comparative genomic analysis revealed that plant growth promoting traits are ubiquitous in strains of Stenotrophomonas

Stenotrophomonas strains, which are often described as plant growth promoting (PGP) bacteria, are ubiquitous in many environments. A total of 213 genomes of strains of Stenotrophomonas were analyzed using comparative genomics to better understand the ecological roles of these bacteria in the environment. The pan-genome of the 213 strains of Stenotrophomonas consists of 27,186 gene families, including 710 core gene families, 11,039 unique genes and 15,437 accessory genes. Nearly all strains of Stenotrophomonas harbor the genes for GH3-family cellulose degradation and GH2- and GH31-family hemicellulose hydrolase, as well as intact glycolysis and tricarboxylic acid cycle pathways. These abilities suggest that the strains of this genus can easily obtain carbon and energy from the environment. The Stenotrophomonas strains can respond to oxidative stress by synthesizing catalase, superoxide dismutase, methionine sulfoxide reductase, and disulfide isomerase, as well as managing their osmotic balance by accumulating potassium and synthesizing compatible solutes, such as betaine, trehalose, glutamate, and proline. Each Stenotrophomonas strain also contains many genes for resistance to antibiotics and heavy metals. These genes that mediate stress tolerance increase the ability of Stenotrophomonas strains to survive in extreme environments. In addition, many functional genes related to attachment and plant colonization, growth promotion and biocontrol were identified. In detail, the genes associated with flagellar assembly, motility, chemotaxis and biofilm formation enable the strains of Stenotrophomonas to effectively colonize host plants. The presence of genes for phosphate-solubilization and siderophore production and the polyamine, indole-3-acetic acid, and cytokinin biosynthetic pathways confer the ability to promote plant growth. These strains can produce antimicrobial compounds, chitinases, lipases and proteases. Each Stenotrophomonas genome contained 1-9 prophages and 17-60 genomic islands, and the genes related to antibiotic and heavy metal resistance and the biosynthesis of polyamines, indole-3-acetic acid, and cytokinin may be acquired by horizontal gene transfer. This study demonstrates that strains of Stenotrophomonas are highly adaptable for different environments and have strong potential for use as plant growth-promoting bacteria.

Genomic and environmental controls on Castellaniella biogeography in an anthropogenically disturbed subsurface

Castellaniella species have been isolated from a variety of mixed-waste environments including the nitrate and multiple metal-contaminated subsurface at the Oak Ridge Reservation (ORR). Previous studies examining microbial community composition and nitrate removal at ORR during biostimulation efforts reported increased abundances of members of the Castellaniella genus concurrent with increased denitrification rates. Thus, we asked how genomic and abiotic factors control the Castellaniella biogeography at the site to understand how these factors may influence nitrate transformation in an anthropogenically impacted setting. We report the isolation and characterization of several Castellaniella strains from the ORR subsurface. Five of these isolates match at 100% identity (at the 16S rRNA gene V4 region) to two Castellaniella amplicon sequence variants (ASVs), ASV1 and ASV2, that have persisted in the ORR subsurface for at least 2 decades. However, ASV2 has consistently higher relative abundance in samples taken from the site and was also the dominant blooming denitrifier population during a prior biostimulation effort. We found that the ASV2 representative strain has greater resistance to mixed metal stress than the ASV1 representative strains. We attribute this resistance, in part, to the large number of unique heavy metal resistance genes identified on a genomic island in the ASV2 representative genome. Additionally, we suggest that the relatively lower fitness of ASV1 may be connected to the loss of the nitrous oxide reductase (nos) operon (and associated nitrous oxide reductase activity) due to the insertion at this genomic locus of a mobile genetic element carrying copper resistance genes. This study demonstrates the value of integrating genomic, environmental, and phenotypic data to characterize the biogeography of key microorganisms in contaminated sites.

Host genetic regulation of human gut microbial structural variation

Although the impact of host genetics on gut microbial diversity and the abundance of specific taxa is well established1-6, little is known about how host genetics regulates the genetic diversity of gut microorganisms. Here we conducted a meta-analysis of associations between human genetic variation and gut microbial structural variation in 9,015 individuals from four Dutch cohorts. Strikingly, the presence rate of a structural variation segment in Faecalibacterium prausnitzii that harbours an N-acetylgalactosamine (GalNAc) utilization gene cluster is higher in individuals who secrete the type A oligosaccharide antigen terminating in GalNAc, a feature that is jointly determined by human ABO and FUT2 genotypes, and we could replicate this association in a Tanzanian cohort. In vitro experiments demonstrated that GalNAc can be used as the sole carbohydrate source for F. prausnitzii strains that carry the GalNAc-metabolizing pathway. Further in silico and in vitro studies demonstrated that other ABO-associated species can also utilize GalNAc, particularly Collinsella aerofaciens. The GalNAc utilization genes are also associated with the host's cardiometabolic health, particularly in individuals with mucosal A-antigen. Together, the findings of our study demonstrate that genetic associations across the human genome and bacterial metagenome can provide functional insights into the reciprocal host-microbiome relationship.

Molecular and evolutionary basis of O-antigenic polysaccharide-driven phage sensitivity in environmental pseudomonads

IMPORTANCE

The application of plant-beneficial microorganisms to protect crop plants is a promising alternative to the usage of chemicals. However, biocontrol research often faces difficulties in implementing this approach due to the inconsistency of the bacterial inoculant to establish itself within the root microbiome. Beneficial bacterial inoculants can be decimated by the presence of their natural predators, notably bacteriophages (also called phages). Thus, it is important to gain knowledge regarding the mechanisms behind phage-bacteria interactions to overcome this challenge. Here, we evidence that the major long O-antigenic polysaccharide (O-PS, O-antigen) of the widely used model plant-beneficial bacterium Pseudomonas protegens CHA0 is the receptor of its natural predator, the phage ΦGP100. We examined the distribution of the gene cluster directing the synthesis of this O-PS and identified signatures of horizontal gene acquisitions. Altogether, our study highlights the importance of bacterial cell surface structure variation in the complex interplay between phages and their Pseudomonas hosts.

Systematic comparison of genome information processing and boundary recognition tools used for genomic island detection

Genomic islands are fragments of foreign DNA that are found in bacterial and archaeal genomes, and are typically associated with symbiosis or pathogenesis. While numerous genomic island detection methods have been proposed, there has been limited evaluation of the efficiency of the genome information processing and boundary recognition tools. In this study, we conducted a review of the statistical methods involved in genomic signatures, host signature extraction, informative signature selection, divergence measures, and boundary detection steps in genomic island prediction. We compared the performances of these methods on simulated experiments using alien fragments obtained from both artificial and real genomes. Our results indicate that among the nine genomic signatures evaluated, genomic signature frequency and full probability performed the best. However, their performance declined when normalized to their expectations and variances, such as Z-score and composition vector. Based on our experiments of the E. coli genome, we found that the confidence intervals of the window variances achieved the best performance in the signature extraction of the host, with the best confidence interval being 1.5-2 times the standard error. Ordered kurtosis was most effective in selecting informative signatures from a single genome, without requiring prior knowledge from other datasets. Among the three divergence measures evaluated, the two-sample t-test was the most successful, and a non-overlapping window with a small eye window (size 2) was best suited for identifying compositionally distinct regions. Finally, the maximum of the Markovian Jensen-Shannon divergence score, in terms of GC-content bias, was found to make boundary detection faster while maintaining a similar error rate.

Trade-off in genome turnover events leading to adaptive evolution of Microcystis aeruginosa species complex

BACKGROUND

Numerous studies in the past have expanded our understanding of the genetic differences of global distributed cyanobacteria that originated around billions of years ago, however, unraveling how gene gain and loss drive the genetic evolution of cyanobacterial species, and the trade-off of these evolutionary forces are still the central but poorly understood issues.

RESULTS

To delineate the contribution of gene flow in mediating the hereditary differentiation and shaping the microbial evolution, a global genome-wide study of bloom-forming cyanobacterium, Microcystis aeruginosa species complex, provided robust evidence for genetic diversity, reflected by enormous variation in gene repertoire among various strains. Mathematical extrapolation showed an 'open' microbial pan-genome of M. aeruginosa species, since novel genes were predicted to be introduced after new genomes were sequenced. Identification of numerous horizontal gene transfer's signatures in genome regions of interest suggested that genome expansion via transformation and phage-mediated transduction across bacterial lineage as an evolutionary route may contribute to the differentiation of Microcystis functions (e.g., carbohydrate metabolism, amino acid metabolism, and energy metabolism). Meanwhile, the selective loss of some dispensable genes at the cost of metabolic versatility is as a mean of adaptive evolution that has the potential to increase the biological fitness.

CONCLUSIONS

Now that the recruitment of novel genes was accompanied by a parallel loss of some other ones, a trade-off in gene content may drive the divergent differentiation of M. aeruginosa genomes. Our study provides a genetic framework for the evolution of M. aeruginosa species and illustrates their possible evolutionary patterns.

Genome Study of α-, β-, and γ-Carbonic Anhydrases from the Thermophilic Microbiome of Marine Hydrothermal Vent Ecosystems

Carbonic anhydrases (CAs) are metalloenzymes that can help organisms survive in hydrothermal vents by hydrating carbon dioxide (CO₂). In this study, we focus on alpha (α), beta (β), and gamma (γ) CAs, which are present in the thermophilic microbiome of marine hydrothermal vents. The coding genes of these enzymes can be transferred between hydrothermal-vent organisms via horizontal gene transfer (HGT), which is an important tool in natural biodiversity. We performed big data mining and bioinformatics studies on α-, β-, and γ-CA coding genes from the thermophilic microbiome of marine hydrothermal vents. The results showed a reasonable association between thermostable α-, β-, and γ-CAs in the microbial population of the hydrothermal vents. This relationship could be due to HGT. We found evidence of HGT of α- and β-CAs between Cycloclasticus sp., a symbiont of Bathymodiolus heckerae, and an endosymbiont of Riftia pachyptila via Integrons. Conversely, HGT of β-CA genes from the endosymbiont Tevnia jerichonana to the endosymbiont Riftia pachyptila was detected. In addition, Hydrogenovibrio crunogenus SP-41 contains a β-CA gene on genomic islands (GIs). This gene can be transferred by HGT to Hydrogenovibrio sp. MA2-6, a methanotrophic endosymbiont of Bathymodiolus azoricus, and a methanotrophic endosymbiont of Bathymodiolus puteoserpentis. The endosymbiont of R. pachyptila has a γ-CA gene in the genome. If α- and β-CA coding genes have been derived from other microorganisms, such as endosymbionts of T. jerichonana and Cycloclasticus sp. as the endosymbiont of B. heckerae, through HGT, the theory of the necessity of thermostable CA enzymes for survival in the extreme ecosystem of hydrothermal vents is suggested and helps the conservation of microbiome natural diversity in hydrothermal vents. These harsh ecosystems, with their integral players, such as HGT and endosymbionts, significantly impact the enrichment of life on Earth and the carbon cycle in the ocean.

Genomic plasticity and adaptive capacity of the quaternary alkyl-ammonium compound and copper tolerant Acinetobacter bohemicus strain QAC-21b isolated from pig manure

Here, we present the genomic characterization of an Acinetobacter bohemicus strain QAC-21b which was isolated in the presence of a quaternary alky-ammonium compound (QAAC) from manure of a conventional German pig farm. The genetic determinants for QAAC, heavy metal and antibiotic resistances are reported based of the whole genome shotgun sequence and physiological growth tests. A. bohemicus QAC-21b grew in a species typical manner well at environmental temperatures but not at 37 °C. The strain showed tolerance to QAACs and copper but was susceptible to antibiotics relevant for Acinetobacter treatments. The genome of QAC-21b contained several Acinetobacter typical QAAC and heavy metal transporting efflux pumps coding genes, but no key genes for acquired antimicrobial resistances. The high genomic content of transferable genetic elements indicates that this bacterium can be involved in the transmission of antimicrobial resistances, if it is released with manure as organic fertilizer on agricultural fields. The genetic content of the strain was compared to that of two other A. bohemicus strains, the type strain ANC 3994^T, isolated from forest soil, and KCTC 42081, originally described as A. pakistanensis, a metal resistant strain isolated from a wastewater treatment pond. In contrast to the forest soil strain, both strains from anthropogenically impacted sources showed genetic features indicating their evolutionary adaptation to the anthropogenically impacted environments. Strain QAC-21b will be used as model strain to study the transmission of antimicrobial resistance to environmentally adapted Acinetobacter in agricultural environments receiving high content of pollutants with organic fertilizers from livestock husbandry.

Pan-Chromosome and Comparative Analysis of Agrobacterium fabrum Reveal Important Traits Concerning the Genetic Diversity, Evolutionary Dynamics, and Niche Adaptation of the Species

Agrobacterium fabrum has been critical for the development of plant genetic engineering and agricultural biotechnology due to its ability to transform eukaryotic cells. However, the gene composition, evolutionary dynamics, and niche adaptation of this species is still unknown. Therefore, we established a comparative genomic analysis based on a pan-chromosome data set to evaluate the genetic diversity of A. fabrum. Here, 25 A. fabrum genomes were selected for analysis by core genome phylogeny combined with the average nucleotide identity (ANI), amino acid identity (AAI), and in silico DNA-DNA hybridization (DDH) values. An open pan-genome of A. fabrum exhibits genetic diversity with variable accessorial genes as evidenced by a consensus pan-genome of 12 representative genomes. The genomic plasticity of A. fabrum is apparent in its putative sequences for mobile genetic elements (MGEs), limited horizontal gene transfer barriers, and potentially horizontally transferred genes. The evolutionary constraints and functional enrichment in the pan-chromosome were measured by the Clusters of Orthologous Groups (COG) categories using eggNOG-mapper software, and the nonsynonymous/synonymous rate ratio (dN/dS) was determined using HYPHY software. Comparative analysis revealed significant differences in the functional enrichment and the degree of purifying selection between the core genome and non-core genome. We demonstrate that the core gene families undergo stronger purifying selection but have a significant bias to contain one or more positively selected sites. Furthermore, although they shared similar genetic diversity, we observed significant differences between chromosome 1 (Chr I) and the chromid in their functional features and evolutionary constraints. We demonstrate that putative genetic elements responsible for plant infection, ecological adaptation, and speciation represent the core genome, highlighting their importance in the adaptation of A. fabrum to plant-related niches. Our pan-chromosome analysis of A. fabrum provides comprehensive insights into the genetic properties, evolutionary patterns, and niche adaptation of the species. IMPORTANCE Agrobacterium spp. live in diverse plant-associated niches such as soil, the rhizosphere, and vegetation, which are challenged by multiple stressors such as diverse energy sources, plant defenses, and microbial competition. They have evolved the ability to utilize diverse resources, escape plant defenses, and defeat competitors. However, the underlying genetic diversity and evolutionary dynamics of Agrobacterium spp. remain unexplored. We examined the phylogeny and pan-genome of A. fabrum to define intraspecies evolutionary relationships. Our results indicate an open pan-genome and numerous MGEs and horizontally transferred genes among A. fabrum genomes, reflecting the flexibility of the chromosomes and the potential for genetic exchange. Furthermore, we observed significant differences in the functional features and evolutionary constraints between the core and accessory genomes and between Chr I and the chromid, respectively.

In Silico Evidence of the Multifunctional Features of Lactiplantibacillus pentosus LPG1, a Natural Fermenting Agent Isolated from Table Olive Biofilms

In recent years, there has been a growing interest in obtaining probiotic bacteria from plant origins. This is the case of Lactiplantibacillus pentosus LPG1, a lactic acid bacterial strain isolated from table olive biofilms with proven multifunctional features. In this work, we have sequenced and closed the complete genome of L. pentosus LPG1 using both Illumina and PacBio technologies. Our intention is to carry out a comprehensive bioinformatics analysis and whole-genome annotation for a further complete evaluation of the safety and functionality of this microorganism. The chromosomic genome had a size of 3,619,252 bp, with a GC (Guanine-Citosine) content of 46.34%. L. pentosus LPG1 also had two plasmids, designated as pl1LPG1 and pl2LPG1, with lengths of 72,578 and 8713 bp (base pair), respectively. Genome annotation revealed that the sequenced genome consisted of 3345 coding genes and 89 non-coding sequences (73 tRNA and 16 rRNA genes). Taxonomy was confirmed by Average Nucleotide Identity analysis, which grouped L. pentosus LPG1 with other sequenced L. pentosus genomes. Moreover, the pan-genome analysis showed that L. pentosus LPG1 was closely related to the L. pentosus strains IG8, IG9, IG11, and IG12, all of which were isolated from table olive biofilms. Resistome analysis reported the absence of antibiotic resistance genes, whilst PathogenFinder tool classified the strain as a non-human pathogen. Finally, in silico analysis of L. pentosus LPG1 showed that many of its previously reported technological and probiotic phenotypes corresponded with the presence of functional genes. In light of these results, we can conclude that L. pentosus LPG1 is a safe microorganism and a potential human probiotic with a plant origin and application as a starter culture for vegetable fermentations.

Biotechnologically potential genes in a polysaccharide-degrading epibiont of the Indonesian brown algae Hydroclathrus sp

BACKGROUND

Marine bacteria have recently attracted increasing attention to be harnessed for the production of valuable enzymes, vitamins, and bioactive compounds. Bacteria associated with the surfaces of marine macroalgae, called epibionts, are particularly interesting from ecological and biotechnological points of view, as they often exhibit antimicrobial activities to compete with pathogenic bacteria for nutrients and spaces. In search for biotechnologically potential genes from marine bacteria, we sequenced and analysed the genome of the epibiont HI03-3b, a polysaccharide-degrading bacterium associated with the surface of the Indonesian brown algae Hydroclathrus sp.

RESULTS

The algal epibiont HI03-3b has a genome of approximately 4,860,704 bp in size with 42.02 mol% G + C content, consisting of 5655 open reading frames (ORFs), 4409 genes coding for proteins (CDSs), 94 genes for tRNAs, and 32 genes for rRNAs. The genome sequence of HI03-3b was most closely related to that of Cytobacillus firmus NCTC10335 with the average amino acid identity (AAI) of 95.0 %, average nucleotide identity (ANI) of 94.1 %, and a recommended DNA-DNA hybridization (DDH) of 57.60 %. These scores are lower than the most frequently used standard for species demarcation (95% ANI cutoff) and the new species threshold (DDH > 70.0% for the same bacterial species). Some differences in genome features and gene composition were observed between HI03-3b and NCTC10335, such as genes encoding carbohydrate active enzymes. These suggest that HI03-3b is unique and likely a novel species within Cytobacillus genus, and we therefore proposed its name as Cytobacillus wakatobiense HI03-3b. Genome sequence analyses indicated the presence of genes involved not only in polysaccharide and protein degradation but also in vitamin and secondary metabolite biosynthesis. Some of them encode enzymes and compounds with biotechnological interest, such as protease, chitinase, subtilisin, pullulanase, and bacillolysin, which are often associated with antimicrobial or antibiofilm activities. This antimicrobial potential is supported by our finding that the extracellular protein fraction of this epibiont inhibited the growth of the bacterial pathogen Staphylococcus aureus.

CONCLUSION

The epibiont Cytobacillus HI03-3b harbours genes for polysaccharide and protein degradation as well as for natural product biosynthesis, suggesting its potential ecological roles in outcompeting other bacteria during biofilm formation as well as in protecting its algal host from predation. Due to the presence of genes for vitamin biosynthesis, it might also provide the algal host with vitamins for growth and development. Some of these metabolic genes are biotechnologically important, as they could become a platform for bioengineering to generate various seaweed-derived substances sustainably, such as antibiofilm agents and vitamins, which are beneficial for human health.

Analyzing the genetic diversity and biotechnological potential of Leuconostoc pseudomesenteroides by comparative genomics

Leuconostoc pseudomesenteroides is a lactic acid bacteria species widely exist in fermented dairy foods, cane juice, sourdough, kimchi, apple dumpster, caecum, and human adenoid. In the dairy industry, Ln. pseudomesenteroides strains are usually found in mesophilic starter cultures with lactococci. This species plays a crucial role in the production of aroma compounds such as acetoin, acetaldehyde, and diacetyl, thus beneficially affecting dairy technology. We performed genomic characterization of 38 Ln. pseudomesenteroides from diverse ecological niches to evaluate this species' genetic diversity and biotechnological potential. A mere ~12% of genes conserved across 38 Ln. pseudomesenteroides genomes indicate that accessory genes are the driving force for genotypic distinction in this species. Seven main clades were formed with variable content surrounding mobile genetic elements, namely plasmids, transposable elements, IS elements, prophages, and CRISPR-Cas. All but three genomes carried CRISPR-Cas system. Furthermore, a type IIA CRISPR-Cas system was found in 80% of the CRISPR-Cas positive strains. AMBR10, CBA3630, and MGBC116435 were predicted to encode bacteriocins. Genes responsible for citrate metabolism were found in all but five strains belonging to cane juice, sourdough, and unknown origin. On the contrary, arabinose metabolism genes were only available in nine strains isolated from plant-related systems. We found that Ln. pseudomesenteroides genomes show evolutionary adaptation to their ecological environment due to niche-specific carbon metabolism and forming closely related phylogenetic clades based on their isolation source. This species was found to be a reservoir of type IIA CRISPR-Cas system. The outcomes of this study provide a framework for uncovering the biotechnological potential of Ln. pseudomesenteroides and its future development as starter or adjunct culture for dairy industry.

A comprehensive genomic analysis provides insights on the high environmental adaptability of Acinetobacter strains

Acinetobacter is ubiquitous, and it has a high species diversity and a complex evolutionary pattern. To elucidate the mechanism of its high ability to adapt to various environment, 312 genomes of Acinetobacter strains were analyzed using the phylogenomic and comparative genomics methods. It was revealed that the Acinetobacter genus has an open pan-genome and strong genome plasticity. The pan-genome consists of 47,500 genes, with 818 shared by all the genomes of Acinetobacter, while 22,291 are unique genes. Although Acinetobacter strains do not have a complete glycolytic pathway to directly utilize glucose as carbon source, most of them harbored the n-alkane-degrading genes alkB/alkM (97.1% of tested strains) and almA (96.7% of tested strains), which were responsible for medium-and long-chain n-alkane terminal oxidation reaction, respectively. Most Acinetobacter strains also have catA (93.3% of tested strains) and benAB (92.0% of tested strains) genes that can degrade the aromatic compounds catechol and benzoic acid, respectively. These abilities enable the Acinetobacter strains to easily obtain carbon and energy sources from their environment for survival. The Acinetobacter strains can manage osmotic pressure by accumulating potassium and compatible solutes, including betaine, mannitol, trehalose, glutamic acid, and proline. They respond to oxidative stress by synthesizing superoxide dismutase, catalase, disulfide isomerase, and methionine sulfoxide reductase that repair the damage caused by reactive oxygen species. In addition, most Acinetobacter strains contain many efflux pump genes and resistance genes to manage antibiotic stress and can synthesize a variety of secondary metabolites, including arylpolyene, β-lactone and siderophores among others, to adapt to their environment. These genes enable Acinetobacter strains to survive extreme stresses. The genome of each Acinetobacter strain contained different numbers of prophages (0-12) and genomic islands (GIs) (6-70), and genes related to antibiotic resistance were found in the GIs. The phylogenetic analysis revealed that the alkM and almA genes have a similar evolutionary position with the core genome, indicating that they may have been acquired by vertical gene transfer from their ancestor, while catA, benA, benB and the antibiotic resistance genes could have been acquired by horizontal gene transfer from the other organisms.

The pan-genome of the emerging multidrug-resistant pathogen Corynebacterium striatum

Corynebacterium striatum, a common constituent of the human skin microbiome, is now considered an emerging multidrug-resistant pathogen of immunocompromised and chronically ill patients. However, little is known about the molecular mechanisms in the transition from colonization to the multidrug-resistant (MDR) invasive phenotype in clinical isolates. This study performed a comprehensive pan-genomic analysis of C. striatum, including isolates from "normal skin microbiome" and from MDR infections, to gain insights into genetic factors contributing to pathogenicity and multidrug resistance in this species. For this, three novel genome sequences were obtained from clinical isolates of C. striatum of patients from Brazil, and other 24 complete or draft C. striatum genomes were retrieved from GenBank, including the ATCC6940 isolate from the Human Microbiome Project. Analysis of C. striatum strains demonstrated the presence of an open pan-genome (α = 0.852803) containing 3816 gene families, including 15 antimicrobial resistance (AMR) genes and 32 putative virulence factors. The core and accessory genomes included 1297 and 1307 genes, respectively. The identified AMR genes are primarily associated with resistance to aminoglycosides and tetracyclines. Of these, 66.6% are present in genomic islands, and four AMR genes, including aac(6')-ib7, are located in a class 1-integron. In conclusion, our data indicated that C. striatum possesses genomic characteristics favorable to the invasive phenotype, with high genomic plasticity, a robust genetic arsenal for iron acquisition, and important virulence determinants and AMR genes present in mobile genetic elements.

Analysis of multipartite bacterial genomes using alignment free and alignment-based pipelines

Since the discovery of second chromosome in Rhodobacter sphaeroides 2.4.1 in 1989, multipartite genomes have been reported in over three hundred bacterial species under nine different phyla. This has shattered the unipartite (single chromosome) genome dogma in bacteria. Since then, many questions on various aspects of multipartite genomes in bacteria have been addressed. However, our understanding of how multipartite genomes emerge and evolve is still lacking. Importantly, the knowledge of genetic factors underlying the differences in multipartite and single-chromosome genomes is lacking. In this work, we have performed comparative evolutionary and functional genomics analyses to identify molecular factors that discriminate multipartite from unipartite bacteria, with the goal to decipher taxon-specific factors, and those that are prevalent across the taxa, underlying these traits. We assessed the roles of evolutionary mechanisms, specifically gene gain, in driving the divergence of bacteria with single and multiple chromosomes. In addition, we performed functional genomic analysis to garner support for our findings from comparative evolutionary analysis. We found genes such as those encoding conserved hypothetical proteins in Deinococcus radiodurans R1, and putative phage phi-C31 gp36 major capsid like and hypothetical proteins in Rhodobacter sphaeroides 2.4.1, which are located on accessory chromosomes in these bacteria but were not found in the inferred ancestral sequences, and on the primary chromosomes, as well as were not found in their closest relatives with single chromosome within the same clade. Our study shines a new light on the potential roles of the secondary chromosomes in helping bacteria with multipartite genomes to adapt to specialized environments or growth conditions.

Pan-genomic analysis of Corynebacterium amycolatum gives insights into molecular mechanisms underpinning the transition to a pathogenic phenotype

Corynebacterium amycolatum is a nonlipophilic coryneform which is increasingly being recognized as a relevant human and animal pathogen showing multidrug resistance to commonly used antibiotics. However, little is known about the molecular mechanisms involved in transition from colonization to the MDR invasive phenotype in clinical isolates. In this study, we performed a comprehensive pan-genomic analysis of C. amycolatum, including 26 isolates from different countries. We obtained the novel genome sequences of 8 of them, which are multidrug resistant clinical isolates from Spain and Tunisia. They were analyzed together with other 18 complete or draft C. amycolatum genomes retrieved from GenBank. The species C. amycolatum presented an open pan-genome (α = 0.854905), with 3,280 gene families, being 1,690 (51.52%) in the core genome, 1,121 related to accessory genes (34.17%), and 469 related to unique genes (14.29%). Although some classic corynebacterial virulence factors are absent in the species C. amycolatum, we did identify genes associated with immune evasion, toxin, and antiphagocytosis among the predicted putative virulence factors. Additionally, we found genomic evidence for extensive acquisition of antimicrobial resistance genes through genomic islands.

Genome-Wide Identification and Expression Analysis of the NAC Gene Family in Kandelia obovata, a Typical Mangrove Plant

The NAC (NAM, ATAF1/2, and CUC2) gene family, one of the largest transcription factor families in plants, acts as positive or negative regulators in plant response and adaption to various environmental stresses, including cold stress. Multiple reports on the functional characterization of NAC genes in Arabidopsis thaliana and other plants are available. However, the function of the NAC genes in the typical woody mangrove (Kandelia obovata) remains poorly understood. Here, a comprehensive analysis of NAC genes in K. obovata was performed with a pluri-disciplinary approach including bioinformatic and molecular analyses. We retrieved a contracted NAC family with 68 genes from the K. obovata genome, which were unevenly distributed in the chromosomes and classified into ten classes. These KoNAC genes were differentially and preferentially expressed in different organs, among which, twelve up-regulated and one down-regulated KoNAC genes were identified. Several stress-related cis-regulatory elements, such as LTR (low-temperature response), STRE (stress response element), ABRE (abscisic acid response element), and WUN (wound-responsive element), were identified in the promoter regions of these 13 KoNAC genes. The expression patterns of five selected KoNAC genes (KoNAC6, KoNAC15, KoNAC20, KoNAC38, and KoNAC51) were confirmed by qRT-PCR under cold treatment. These results strongly implied the putative important roles of KoNAC genes in response to chilling and other stresses. Collectively, our findings provide valuable information for further investigations on the function of KoNAC genes.

Insights into Evolutionary, Genomic, and Biogeographic Characterizations of Chryseobacterium nepalense Represented by a Polyvinyl Alcohol-Degrading Bacterium, AC3

Chryseobacterium spp. are Gram-negative rods found ubiquitously in the environment, with certain species being reported as having unusual degrading properties. Polyvinyl alcohol (PVA) is used widely in industry but causes serious global environmental pollution. Here, we report the complete genome sequence of a novel bacterium, AC3, that efficiently degrades PVA. As the representative genome of Chryseobacterium nepalense, key genomic characteristics (e.g., mobile genetic elements, horizontal genes, genome-scale metabolic network, secondary metabolite biosynthesis gene clusters, and carbohydrate-active enzymes) were comprehensively investigated to reveal the potential genetic features of this species. Core genome phylogenetic analysis in combination with average nucleotide identity, average amino acid identity, and in silico DNA-DNA hybridization values provided an accurate taxonomic position of C. nepalense in the genus Chryseobacterium. Comparative genomic analysis of AC3 with closely related species suggested evolutionary dynamics characterized by a species-specific genetic repertoire, dramatic rearrangements, and evolutionary constraints driven by selective pressure, which facilitated the speciation and adaptative evolution of C. nepalense. Biogeographic characterization indicated that this species is ubiquitously distributed not only in soil habitats but also in a variety of other source niches. Bioinformatic analysis revealed the potential genetic basis of PVA degradation in AC3, which included six putative genes associated with the synthesis of PVA dehydrogenase, cytochrome c, oxidized PVA hydrolase, and secondary alcohol dehydrogenase. Our study reports the first complete genome of C. nepalense with PVA-degrading properties, providing comprehensive insights into the genomic characteristics of this species and increasing our understanding of the microbial degradation of PVA. IMPORTANCE Although PVA is a biodegradable polymer, the widespread use of PVA in global industrialization has resulted in serious environmental problems. To date, knowledge of effective and applicable PVA-degrading bacteria is limited, and thus, the discovery of novel PVA biodegraders is pertinent. Here, we isolated a novel bacterial strain, AC3, which efficiently degraded PVA. The complete genome of AC3 was sequenced as the first genome sequence of the species C. nepalense. Comparative genomic analysis was performed to comprehensively investigate the phylogenetic relationships, genome-scale metabolic network, key genomic characteristics associated with genomic evolution, evolutionary dynamics between AC3 and its close relatives, and biogeographic characterization of C. nepalense, particularly regarding the potential genetic basis of PVA degradation. These findings could advance our understanding of the genomic characteristics of C. nepalense and PVA bioremediation.

Exploring the mobilome and resistome of Enterococcus faecium in a One Health context across two continents

Enterococcus faecium is a ubiquitous opportunistic pathogen that is exhibiting increasing levels of antimicrobial resistance (AMR). Many of the genes that confer resistance and pathogenic functions are localized on mobile genetic elements (MGEs), which facilitate their transfer between lineages. Here, features including resistance determinants, virulence factors and MGEs were profiled in a set of 1273 E. faecium genomes from two disparate geographic locations (in the UK and Canada) from a range of agricultural, clinical and associated habitats. Neither lineages of E. faecium, type A and B, nor MGEs are constrained by geographic proximity, but our results show evidence of a strong association of many profiled genes and MGEs with habitat. Many features were associated with a group of clinical and municipal wastewater genomes that are likely forming a new human-associated ecotype within type A. The evolutionary dynamics of E. faecium make it a highly versatile emerging pathogen, and its ability to acquire, transmit and lose features presents a high risk for the emergence of new pathogenic variants and novel resistance combinations. This study provides a workflow for MGE-centric surveillance of AMR in Enterococcus that can be adapted to other pathogens.

Mapping Strengths and Weaknesses of Different Clustering Approaches to Deciphering Bacterial Chimerism

Bacterial genomes are chimeras of DNA of different ancestries. Deconstructing chimeric genomes is central to understanding the evolutionary trajectories of their disparate components and thus the organisms as a whole in the light of their evolutionary contexts. Of specific interest is to delineate and quantify native (vertically inherited) and alien (horizontally acquired) components of bacterial genomes and also specify genomic fractions that represent different donor sources. An agglomerative clustering procedure that prioritizes grouping of proximal similar genomic segments has previously been invoked for this purpose in conjunction with a recursive segmentation procedure. Surprisingly, however, the relative strengths and weaknesses of different clustering approaches to deciphering bacterial chimerism have not yet been investigated, despite the need to robustly interpret tens of thousands of completely sequenced bacterial genomes and nearly complete genome assemblies available in the public databases. To bridge this knowledge gap and develop more robust approaches, we assessed different clustering methods, including segment order based (proximal) clustering, hierarchical clustering, affinity propagation clustering, and a novel network clustering approach on chimeric genomes modeled after bacterial genomes representing a broad spectrum of compositional complexity. Although segment order-based clustering and network clustering compared favorably with the other approaches in discriminating between native and alien DNA at genome optimized settings, network clustering did consistently better than other methods at parametric settings optimized on all test genomes together. Segment order-based clustering and hierarchical clustering outperformed other methods in alien DNA identification while preserving donor identity in the genomes. Our study highlights the strengths and weaknesses of different approaches and suggests how this can be leveraged to achieve a more robust deconstruction of bacterial chimerism.

High-quality pan-genome of Escherichia coli generated by excluding confounding and highly similar strains reveals an association between unique gene clusters and genomic islands

The pan-genome analysis of bacteria provides detailed insight into the diversity and evolution of a bacterial population. However, the genomes involved in the pan-genome analysis should be checked carefully, as the inclusion of confounding strains would have unfavorable effects on the identification of core genes, and the highly similar strains could bias the results of the pan-genome state (open versus closed). In this study, we found that the inclusion of highly similar strains also affects the results of unique genes in pan-genome analysis, which leads to a significant underestimation of the number of unique genes in the pan-genome. Therefore, these strains should be excluded from pan-genome analysis at the early stage of data processing. Currently, tens of thousands of genomes have been sequenced for Escherichia coli, which provides an unprecedented opportunity as well as a challenge for pan-genome analysis of this classical model organism. Using the proposed strategies, a high-quality E. coli pan-genome was obtained, and the unique genes was extracted and analyzed, revealing an association between the unique gene clusters and genomic islands from a pan-genome perspective, which may facilitate the identification of genomic islands.

Genomic Analysis of Carbapenem-Resistant Comamonas in Water Matrices: Implications for Public Health and Wastewater Treatments

Comamonas spp. are Gram-negative bacteria that catabolize a wide range of organic and inorganic substrates. Comamonas spp. are abundant in aquatic and soil environments, including wastewater, and can cause opportunistic infections in humans. Because of their potential in wastewater bioaugmentation and bioremediation strategies, the identification of Comamonas species harboring genes encoding carbapenemases and other clinically important antibiotic resistance genes warrant further investigation. Here, we present an analysis of 39 whole-genome sequences comprising three Comamonas species from aquatic environments in South Australia that were recovered on media supplemented with carbapenems. The analysis includes a detailed description of 33 Comamonas denitrificans isolates, some of which carried chromosomally acquired bla_GES-5, bla_OXA, and aminoglycoside resistance (aadA) genes located on putative genomic islands (GIs). All bla_GES-5- and bla_OXA-containing GIs appear to be unique to this Australian collection of C. denitrificans. Notably, most open reading frames (ORFs) within the GIs, including all antimicrobial resistance (AMR) genes, had adjacent attC sites, indicating that these ORFs are mobile gene cassettes. One C. denitrificans isolate carried an IncP-1 plasmid with genes involved in xenobiotic degradation and response to oxidative stress. Our assessment of the sequences highlights the very distant nature of C. denitrificans to the other Comamonas species and its apparent disposition to acquire antimicrobial resistance genes on putative genomic islands. IMPORTANCE Antimicrobial resistance (AMR) poses a global public health threat, and the increase in resistance to "last-resort drugs," such as carbapenems, is alarming. Wastewater has been flagged as a hot spot for AMR evolution. Comamonas spp. are among the most common bacteria in wastewater and play a role in its bioaugmentation. While the ability of Comamonas species to catabolize a wide range of organic and inorganic substrates is well documented, some species are also opportunistic pathogens. However, data regarding AMR in Comamonas spp. are limited. Here, through the genomic analyses of 39 carbapenem-resistant Comamonas isolates, we make several key observations, including the identification of a subset of C. denitrificans isolates that harbored genomic islands encoding carbapenemase bla_GES-5 or extended-spectrum β-lactamase bla_OXA alleles. Given the importance of Comamonas species in potential wastewater bioaugmentation and bioremediation strategies, as well as their status as emerging pathogens, the acquisition of critically important antibiotic resistance genes on genomic islands warrants future monitoring.

Enabling genomic island prediction and comparison in multiple genomes to investigate bacterial evolution and outbreaks

Outbreaks of virulent and/or drug-resistant bacteria have a significant impact on human health and major economic consequences. Genomic islands (GIs; defined as clusters of genes of probable horizontal origin) are of high interest because they disproportionately encode virulence factors, some antimicrobial-resistance (AMR) genes, and other adaptations of medical or environmental interest. While microbial genome sequencing has become rapid and inexpensive, current computational methods for GI analysis are not amenable for rapid, accurate, user-friendly and scalable comparative analysis of sets of related genomes. To help fill this gap, we have developed IslandCompare, an open-source computational pipeline for GI prediction and comparison across several to hundreds of bacterial genomes. A dynamic and interactive visualization strategy displays a bacterial core-genome phylogeny, with bacterial genomes linearly displayed at the phylogenetic tree leaves. Genomes are overlaid with GI predictions and AMR determinants from the Comprehensive Antibiotic Resistance Database (CARD), and regions of similarity between the genomes are also displayed. GI predictions are performed using Sigi-HMM and IslandPath-DIMOB, the two most precise GI prediction tools based on nucleotide composition biases, as well as a novel blast-based consistency step to improve cross-genome prediction consistency. GIs across genomes sharing sequence similarity are grouped into clusters, further aiding comparative analysis and visualization of acquisition and loss of mobile GIs in specific sub-clades. IslandCompare is an open-source software that is containerized for local use, plus available via a user-friendly, web-based interface to allow direct use by bioinformaticians, biologists and clinicians (at https://islandcompare.ca).

Performance assessment of genomic island prediction tools with an improved version of Design-Island

Genomic Islands (GIs) play an important role in the evolution and adaptation of prokaryotes. The origin and extent of ecological diversity of prokaryotes can be analyzed by comparing GIs across closely or distantly related prokaryotes. Understanding the importance of GI and to study the bacterial evolution, several GI prediction tools have been generated. An unsupervised method, Design-Island, was developed to identify GIs using Monte-Carlo statistical test on randomly selected segments of a chromosome. Here, in the present study Design-Island was modified with the incorporation of majority voting, multiple hypothesis testing correction. The performance of the modified version, Design-Island-II was tested and compared with the existing GI prediction tools. The performance assessment and benchmarking of the GI prediction tools require experimentally validated dataset, which is lacking. So, different datasets, generated or taken from literature were utilized to compare the sensitivity (SN), specificity (SP), precision (PPV) and accuracy (AC) of Design-Island-II. It showed substantial enhancement in term of SN, SP, PPV and AC, and significantly reduced the computation time of the algorithm. The performance of Design-Island-II has also been compared with several GI prediction tools using curated dataset of putative horizontally transferred genes. Design-Island-II showed the highest sensitivity and F1 score, comparable specificity, precision and accuracy in comparison to the other available methods. IslandViewer4 and Islander outperformed all the available methods in terms of AC and PPV respectively. Our study suggested Design-Island-II, IslandViewer4 and GIHunter among the top performing GI prediction tools considering both sensitivity and specificity of the methods.

Comparative Genomic Analysis of Vibrio cincinnatiensis Provides Insights into Genetic Diversity, Evolutionary Dynamics, and Pathogenic Traits of the Species

Vibrio cincinnatiensis is a poorly understood pathogenic Vibrio species, and the underlying mechanisms of its genetic diversity, genomic plasticity, evolutionary dynamics, and pathogenicity have not yet been comprehensively investigated. Here, a comparative genomic analysis of V. cincinnatiensis was constructed. The open pan-genome with a flexible gene repertoire exhibited genetic diversity. The genomic plasticity and stability were characterized by the determinations of diverse mobile genetic elements (MGEs) and barriers to horizontal gene transfer (HGT), respectively. Evolutionary divergences were exhibited by the difference in functional enrichment and selective pressure between the different components of the pan-genome. The evolution on the Chr I and Chr II core genomes was mainly driven by purifying selection. Predicted essential genes in V. cincinnatiensis were mainly found in the core gene families on Chr I and were subject to stronger evolutionary constraints. We identified diverse virulence-related elements, including the gene clusters involved in encoding flagella, secretion systems, several pili, and scattered virulence genes. Our results indicated the pathogenic potential of V. cincinnatiensis and highlighted that HGT events from other Vibrio species promoted pathogenicity. This pan-genome study provides comprehensive insights into this poorly understood species from the genomic perspective.

Prediction and Inferred Evolution of Acid Tolerance Genes in the Biotechnologically Important Acidihalobacter Genus

Acidihalobacter is a genus of acidophilic, gram-negative bacteria known for its ability to oxidize pyrite minerals in the presence of elevated chloride ions, a capability rare in other iron-sulfur oxidizing acidophiles. Previous research involving Acidihalobacter spp. has focused on their applicability in saline biomining operations and their genetic arsenal that allows them to cope with chloride, metal and oxidative stress. However, an understanding of the molecular adaptations that enable Acidihalobacter spp. to thrive under both acid and chloride stress is needed to provide a more comprehensive understanding of how this genus can thrive in such extreme biomining conditions. Currently, four genomes of the Acidihalobacter genus have been sequenced: Acidihalobacter prosperus DSM 5130^T, Acidihalobacter yilgarnensis DSM 105917^T, Acidihalobacter aeolianus DSM 14174^T, and Acidihalobacter ferrooxydans DSM 14175^T. Phylogenetic analysis shows that the Acidihalobacter genus roots to the Chromatiales class consisting of mostly halophilic microorganisms. In this study, we aim to advance our knowledge of the genetic repertoire of the Acidihalobacter genus that has enabled it to cope with acidic stress. We provide evidence of gene gain events that are hypothesized to help the Acidihalobacter genus cope with acid stress. Potential acid tolerance mechanisms that were found in the Acidihalobacter genomes include multiple potassium transporters, chloride/proton antiporters, glutamate decarboxylase system, arginine decarboxylase system, urease system, slp genes, squalene synthesis, and hopanoid synthesis. Some of these genes are hypothesized to have entered the Acidihalobacter via vertical decent from an inferred non-acidophilic ancestor, however, horizontal gene transfer (HGT) from other acidophilic lineages is probably responsible for the introduction of many acid resistance genes.

Genomic Insights into Achromobacter mucicolens IA Antibiotic Resistance

Achromobacter denitrificans is an environmental opportunistic pathogen that is infecting a large number of immunocompromised patients. A more recently identified strain from the historical collection of strains of Achromobacter denitrificans is Achromobacter mucicolens. In hosts with a variety of underlying diseases, Achromobacter spp. can induce a wide spectrum of disorders. Because of the bacterium’s intrinsic genetic constitution and resistance gained over time, antibiotics are challenged to handle A. mucicolens. Due to the fact that A. mucicolens is rare and its taxonomy is not completely understood, it is difficult to define clinical symptoms, acquisition risk factors, and thus the best therapeutic course of action. To help comprehend this intrinsic and acquired resistance, we analyzed the entire genome of the A. mucicolens IA strain and utilized bioinformatics methods to estimate the strain's probable drug resistance profile. In our study, we have isolated and cultured a clinically important A. mucicolens strain and subjected it to antimicrobial susceptibility tests against antibiotics in the Vitek 2 testing system. The strain’s genome sequence as well as an investigation of 27 of its phenotypic traits provides important information regarding this pathogen. The genome of this A. mucicolens IA strain possesses a number of antibiotic resistance genes that code for efflux pump systems and other antibiotic-regulating as well as -modifying enzymes. Our research analysis predicted genes involved in drug resistance, including genes for efflux pump systems, antibiotic efflux, antibiotic inactivation, and antibiotic target alteration. In vitro studies validated the genomic evidence for its ability to exhibit resistance against a wide range of antibiotics. Our investigation paves the way for more research on understanding the functioning of the key discovered genes that contribute toward the pathogenicity of A. mucicolens and hence gives new information and treatment options for this emerging pathogen.

IMPORTANCEAchromobacter species are well-known opportunistic human pathogens that can be found in water and soil and most commonly in hospital settings. They thrive in immunocompromised individuals, producing sporadic cases of pneumonia, septicemia, peritonitis, urinary tract infections, and other illnesses. Achromobacter strains are inherently resistant to a wide spectrum of antibiotics, making them difficult to treat promptly. The strain under study, A. mucicolens, was notably resistant to various antibiotics, and the infection could be controlled only after several rounds of prescription medications at different doses. This consumed a lot of time and put the already immunosuppressed leukemic patient through a great ordeal. The study aimed to raise awareness about the importance of the Achromobacter bacterium’s lethality, and doctors should evaluate the bacterium’s potential for resistance before prescribing antibiotics. Sanitation and other precautions should also be implemented in hospitals and other public places.

Integrative Assessments on Molecular Taxonomy of Acidiferrobacter thiooxydans ZJ and Its Environmental Adaptation Based on Mobile Genetic Elements

Acidiferrobacter spp. are facultatively anaerobic acidophiles that belong to a distinctive Acidiferrobacteraceae family, which are similar to Ectothiorhodospiraceae phylogenetically, and are closely related to Acidithiobacillia class/subdivision physiologically. The limited genome information has kept them from being studied on molecular taxonomy and environmental adaptation in depth. Herein, Af. thiooxydans ZJ was isolated from acid mine drainage (AMD), and the complete genome sequence was reported to scan its genetic constitution for taxonomic and adaptative feature exploration. The genome has a single chromosome of 3,302,271 base pairs (bp), with a GC content of 63.61%. The phylogenetic tree based on OrthoANI highlighted the unique position of Af. thiooxydans ZJ, which harbored more unique genes among the strains from Ectothiorhodospiraceae and Acidithiobacillaceae by pan-genome analysis. The diverse mobile genetic elements (MGEs), such as insertion sequence (IS), clustered regularly interspaced short palindromic repeat (CRISPR), prophage, and genomic island (GI), have been identified and characterized in Af. thiooxydans ZJ. The results showed that Af. thiooxydans ZJ may effectively resist the infection of foreign viruses and gain functional gene fragments or clusters to shape its own genome advantageously. This study will offer more evidence of the genomic plasticity and improve our understanding of evolutionary adaptation mechanisms to extreme AMD environment, which could expand the potential utilization of Af. thiooxydans ZJ as an iron and sulfur oxidizer in industrial bioleaching.

Pan-Genome Analysis of Delftia tsuruhatensis Reveals Important Traits Concerning the Genetic Diversity, Pathogenicity, and Biotechnological Properties of the Species

Delftia tsuruhatensis strains have long been known to promote plant growth and biological control. Recently, it has become an emerging opportunistic pathogen in humans. However, the genomic characteristics of the genetic diversity, pathogenicity, and biotechnological properties have not yet been comprehensively investigated. Here, a comparative pan-genome analysis was constructed. The open pan-genome with a large and flexible gene repertoire exhibited a high degree of genetic diversity. The purifying selection was the main force to drive pan-genome evolution. Significant differences were observed in the evolutionary relationship, functional enrichment, and degree of selective pressure between the different components of the pan-genome. A high degree of genetic plasticity was characterized by the determinations of diverse mobile genetic elements (MGEs), massive genomic rearrangement, and horizontal genes. Horizontal gene transfer (HGT) plays an important role in the genetic diversity of this bacterium and the formation of genomic traits. Our results revealed the occurrence of diverse virulence-related elements associated with macromolecular secretion systems, virulence factors associated with multiple nosocomial infections, and antimicrobial resistance, indicating the pathogenic potential. Lateral flagellum, T1SS, T2SS, T6SS, Tad pilus, type IV pilus, and a part of virulence-related genes exhibited general properties, whereas polar flagellum, T4SS, a part of virulence-related genes, and resistance genes presented heterogeneous properties. The pan-genome also harbors abundant genetic traits related to secondary metabolism, carbohydrate active enzymes (CAZymes), and phosphate transporter, indicating rhizosphere adaptation, plant growth promotion, and great potential uses in agriculture and biological control. This study provides comprehensive insights into this uncommon species from the genomic perspective.

IMPORTANCED. tsuruhatensis is considered a plant growth-promoting rhizobacterium (PGPR), an organic pollutant degradation strain, and an emerging opportunistic pathogen to the human. However, the genetic diversity, the evolutionary dynamics, and the genetic basis of these remarkable traits are still little known. We constructed a pan-genome analysis for D. tsuruhatensis and revealed extensive genetic diversity and genetic plasticity exhibited by open pan-genome, diverse mobile genetic elements (MGEs), genomic rearrangement, and horizontal genes. Our results highlight that horizontal gene transfer (HGT) and purifying selection are important forces in D. tsuruhatensis genetic evolution. The abundant virulence-related elements associated with macromolecular secretion systems, virulence factors, and antimicrobial resistance could contribute to the pathogenicity of this bacterium. Therefore, clinical microbiologists need to be aware of D. tsuruhatensis as an opportunistic pathogen. The genetic profiles of secondary metabolism, carbohydrate active enzymes (CAZymes), and phosphate transporter could provide insight into the genetic armory of potential applications for agriculture and biological control of D. tsuruhatensis in general.

Bifidobacterium castoris strains isolated from wild mice show evidence of frequent host switching and diverse carbohydrate metabolism potential

Members of the gut microbiota genus Bifidobacterium are widely distributed human and animal symbionts believed to exert beneficial effects on their hosts. However, in-depth genomic analyses of animal-associated species and strains are somewhat lacking, particularly in wild animal populations. Here, to examine patterns of host specificity and carbohydrate metabolism capacity, we sequenced whole genomes of Bifidobacterium isolated from wild-caught small mammals from two European countries (UK and Lithuania). Members of Bifidobacterium castoris, Bifidobacterium animalis and Bifodobacterium pseudolongum were detected in wild mice (Apodemus sylvaticus, Apodemus agrarius and Apodemus flavicollis), but not voles or shrews. B. castoris constituted the most commonly recovered Bifidobacterium (78% of all isolates), with the majority of strains only detected in a single population, although populations frequently harboured multiple co-circulating strains. Phylogenetic analysis revealed that the mouse-associated B. castoris clades were not specific to a particular location or host species, and their distribution across the host phylogeny was consistent with regular host shifts rather than host-microbe codiversification. Functional analysis, including in vitro growth assays, suggested that mouse-derived B. castoris strains encoded an extensive arsenal of carbohydrate-active enzymes, including putative novel glycosyl hydrolases such as chitosanases, along with genes encoding putative exopolysaccharides, some of which may have been acquired via horizontal gene transfer. Overall, these results provide a rare genome-level analysis of host specificity and genomic capacity among important gut symbionts of wild animals, and reveal that Bifidobacterium has a labile relationship with its host over evolutionary time scales.

Prediction and Analysis in silico of Genomic Islands in Aeromonas hydrophila

Aeromonas are Gram-negative rods widely distributed in the environment. They can cause severe infections in fish related to financial losses in the fish industry, and are considered opportunistic pathogens of humans causing infections ranging from diarrhea to septicemia. The objective of this study was to determine in silico the contribution of genomic islands to A. hydrophila. The complete genomes of 17 A. hydrophila isolates, which were separated into two phylogenetic groups, were analyzed using a genomic island (GI) predictor. The number of predicted GIs and their characteristics varied among strains. Strains from group 1, which contains mainly fish pathogens, generally have a higher number of predicted GIs, and with larger size, than strains from group 2 constituted by strains recovered from distinct sources. Only a few predicted GIs were shared among them and contained mostly genes from the core genome. Features related to virulence, metabolism, and resistance were found in the predicted GIs, but strains varied in relation to their gene content. In strains from group 1, O Ag biosynthesis clusters OX1 and OX6 were identified, while strains from group 2 each had unique clusters. Metabolic pathways for myo-inositol, L-fucose, sialic acid, and a cluster encoding QueDEC, tgtA5, and proteins related to DNA metabolism were identified in strains of group 1, which share a high number of predicted GIs. No distinctive features of group 2 strains were identified in their predicted GIs, which are more diverse and possibly better represent GIs in this species. However, some strains have several resistance attributes encoded by their predicted GIs. Several predicted GIs encode hypothetical proteins and phage proteins whose functions have not been identified but may contribute to Aeromonas fitness. In summary, features with functions identified on predicted GIs may confer advantages to host colonization and competitiveness in the environment.

The whole-genome sequencing in predicting Mycobacterium tuberculosis drug susceptibility and resistance in Papua, Indonesia

BACKGROUND

Tuberculosis is one of the deadliest disease caused by Mycobacterium tuberculosis. Its treatment still becomes a burden for many countries including Indonesia. Drug resistance is one of the problems in TB treatment. However, a development in the molecular field through Whole-genome sequencing (WGS) can be used as a solution in detecting mutations associated with TB- drugs. This investigation intended to implement this data for supporting the scientific community in deeply understanding any TB epidemiology and evolution in Papua along with detecting any mutations in genes associated with TB-Drugs.

RESULT

A whole-genome sequencing was performed on the random samples from TB Referral Laboratory in Papua utilizing MiSeq 600 cycle Reagent Kit (V3). Furthermore, TBProfiler was used for genome analysis, RAST Server was employed for annotation, while Gview server was applied for BLAST genome mapping and a Microscope server was implemented for Regions of Genomic Plasticity (RGP). The largest genome of M. tuberculosis obtained was at the size of 4,396,040 bp with subsystems number at 309 and the number of coding sequences at 4326. One sample (TB751) contained one RGP. The drug resistance analysis revealed that several mutations associated with TB-drug resistance existed. In details, mutations of rpoB gene which were identified as S450L, D435Y, H445Y, L430P, and Q432K had caused the reduced effectiveness of rifampicin; while the mutases in katG (S315T), kasA (312S), inhA (I21V), and Rv1482c-fabG1 (C-15 T) genes had contributed to the resistance in isoniazid. In streptomycin, the resistance was triggered by the mutations in rpsL (K43R) and rrs (A514C, A514T) genes, and, in Amikacin, its resistance was led by mutations in rrs (A514C) gene. Additionally, in Ethambutol and Pyrazinamide, their reduced effectiveness was provoked by embB gene mutases (M306L, M306V, D1024N) and pncA (W119R).

CONCLUSIONS

The results from whole-genome sequencing of TB clinical sample in Papua, Indonesia could contribute to the surveillance of TB-drug resistance. In the drug resistance profile, there were 15 Multi Drugs Resistance (MDR) samples. However, Extensively Drug-resistant (XDR) samples have not been found, but samples were resistant to only Amikacin, a second-line drug.

A sugar utilization phenotype contributes to the formation of genetic exchange communities in lactic acid bacteria

In prokaryotes, a major contributor to genomic evolution is the exchange of genes via horizontal gene transfer (HGT). Areas with a high density of HGT networks are defined as genetic exchange communities (GECs). Although some phenotypes associated with specific ecological niches are linked to GECs, little is known about the phenotypic influences on HGT in bacterial groups within a taxonomic family. Thanks to the published genome sequences and phenotype data of lactic acid bacteria (LAB), it is now possible to obtain more detailed information about the phenotypes that affect GECs. Here, we have investigated the relationship between HGT and internal and external environmental factors for 178 strains from 24 genera in the Lactobacillaceae family. We found a significant correlation between strains with high utilization of sugars and HGT bias. The result suggests that the phenotype of the utilization of a variety of sugars is key to the construction of GECs in this family. This feature is consistent with the fact that the Lactobacillaceae family contributes to the production of a wide variety of fermented foods by sharing niches such as those in vegetables, dairy products and brewing-related environments. This result provides the first evidence that phenotypes associated with ecological niches contribute to form GECs in the LAB family.

Phylogenomic disentangling of the Bifidobacterium longum subsp. infantis taxon

Members of the Bifidobacterium longum species have been shown to possess adaptive abilities to allow colonization of different mammalian hosts, including humans, primates and domesticated mammalian species, such as dogs, horses, cattle and pigs. To date, three subspecies have formally been recognized to belong to this bifidobacterial taxon, i.e. B. longum subsp. longum, B. longum subsp. infantis and B. longum subsp. suis. Although B. longum subsp. longum is widely distributed in the human gut irrespective of host age, B. longum subsp. infantis appears to play a significant role as a prominent member of the gut microbiota of breast-fed infants. Nevertheless, despite the considerable scientific relevance of these taxa and the vast body of genomic data now available, an accurate dissection of the genetic features that comprehensively characterize the B. longum species and its subspecies is still missing. In the current study, we employed 261 publicly available B. longum genome sequences, combined with those of 11 new isolates, to investigate genomic diversity of this taxon through comparative genomic and phylogenomic approaches. These analyses allowed us to highlight a remarkable intra-species genetic and physiological diversity. Notably, characterization of the genome content of members of B. longum subsp. infantis subspecies suggested that this taxon may have acquired genetic features for increased competitiveness in the gut environment of suckling hosts. Furthermore, specific B. longum subsp. infantis genomic features appear to be responsible for enhanced horizontal gene transfer (HGT) occurrences, underpinning an intriguing dedication toward acquisition of foreign DNA by HGT events.

Genome analysis of Pseudomonas sp. OF001 and Rubrivivax sp. A210 suggests multicopper oxidases catalyze manganese oxidation required for cylindrospermopsin transformation

BACKGROUND

Cylindrospermopsin is a highly persistent cyanobacterial secondary metabolite toxic to humans and other living organisms. Strain OF001 and A210 are manganese-oxidizing bacteria (MOB) able to transform cylindrospermopsin during the oxidation of Mn²⁺. So far, the enzymes involved in manganese oxidation in strain OF001 and A210 are unknown. Therefore, we analyze the genomes of two cylindrospermopsin-transforming MOB, Pseudomonas sp. OF001 and Rubrivivax sp. A210, to identify enzymes that could catalyze the oxidation of Mn²⁺. We also investigated specific metabolic features related to pollutant degradation and explored the metabolic potential of these two MOB with respect to the role they may play in biotechnological applications and/or in the environment.

RESULTS

Strain OF001 encodes two multicopper oxidases and one haem peroxidase potentially involved in Mn²⁺ oxidation, with a high similarity to manganese-oxidizing enzymes described for Pseudomonas putida GB-1 (80, 83 and 42% respectively). Strain A210 encodes one multicopper oxidase potentially involved in Mn²⁺ oxidation, with a high similarity (59%) to the manganese-oxidizing multicopper oxidase in Leptothrix discophora SS-1. Strain OF001 and A210 have genes that might confer them the ability to remove aromatic compounds via the catechol meta- and ortho-cleavage pathway, respectively. Based on the genomic content, both strains may grow over a wide range of O₂ concentrations, including microaerophilic conditions, fix nitrogen, and reduce nitrate and sulfate in an assimilatory fashion. Moreover, the strain A210 encodes genes which may convey the ability to reduce nitrate in a dissimilatory manner, and fix carbon via the Calvin cycle. Both MOB encode CRISPR-Cas systems, several predicted genomic islands, and phage proteins, which likely contribute to their genome plasticity.

CONCLUSIONS

The genomes of Pseudomonas sp. OF001 and Rubrivivax sp. A210 encode sequences with high similarity to already described MCOs which may catalyze manganese oxidation required for cylindrospermopsin transformation. Furthermore, the analysis of the general metabolism of two MOB strains may contribute to a better understanding of the niches of cylindrospermopsin-removing MOB in natural habitats and their implementation in biotechnological applications to treat water.

Identifying genomic islands with deep neural networks

Background

Horizontal gene transfer is the main source of adaptability for bacteria, through which genes are obtained from different sources including bacteria, archaea, viruses, and eukaryotes. This process promotes the rapid spread of genetic information across lineages, typically in the form of clusters of genes referred to as genomic islands (GIs). Different types of GIs exist, and are often classified by the content of their cargo genes or their means of integration and mobility. While various computational methods have been devised to detect different types of GIs, no single method is capable of detecting all types.

Results

We propose a method, which we call Shutter Island, that uses a deep learning model (Inception V3, widely used in computer vision) to detect genomic islands. The intrinsic value of deep learning methods lies in their ability to generalize. Via a technique called transfer learning, the model is pre-trained on a large generic dataset and then re-trained on images that we generate to represent genomic fragments. We demonstrate that this image-based approach generalizes better than the existing tools.

Conclusions

We used a deep neural network and an image-based approach to detect the most out of the correct GI predictions made by other tools, in addition to making novel GI predictions. The fact that the deep neural network was re-trained on only a limited number of GI datasets and then successfully generalized indicates that this approach could be applied to other problems in the field where data is still lacking or hard to curate.

Comparative genomics analysis of Pediococcus acidilactici species

Pediococcus acidilactici is a reliable bacteriocin producer and a promising probiotic species with wide application in the food and health industry. However, the underlying genetic features of this species have not been analyzed. In this study, we performed a comprehensive comparative genomic analysis of 41 P. acidilactici strains from various ecological niches. The bacteriocin production of 41 strains were predicted and three kinds of bacteriocin encoding genes were identified in 11 P. acidilactici strains, namely pediocin PA-1, enterolysin A, and colicin-B. Moreover, whole-genome analysis showed a high genetic diversity within the population, mainly related to a large proportion of variable genomes, mobile elements, and hypothetical genes obtained through horizontal gene transfer. In addition, comparative genomics also facilitated the genetic explanation of the adaptation for host environment, which specify the protection mechanism against the invasion of foreign DNA (i.e. CRISPR/Cas locus), as well as carbohydrate fermentation. The 41 strains of P. acidilactici can metabolize a variety of carbon sources, which enhances the adaptability of this species and survival in different environments. This study evaluated the antibacterial ability, genome evolution, and ecological flexibility of P. acidilactici from the perspective of genetics and provides strong supporting evidence for its industrial development and application.

SSG-LUGIA: Single Sequence based Genome Level Unsupervised Genomic Island Prediction Algorithm

BACKGROUND

Genomic Islands (GIs) are clusters of genes that are mobilized through horizontal gene transfer. GIs play a pivotal role in bacterial evolution as a mechanism of diversification and adaptation to different niches. Therefore, identification and characterization of GIs in bacterial genomes is important for understanding bacterial evolution. However, quantifying GIs is inherently difficult, and the existing methods suffer from low prediction accuracy and precision-recall trade-off. Moreover, several of them are supervised in nature, and thus, their applications to newly sequenced genomes are riddled with their dependency on the functional annotation of existing genomes.

RESULTS

We present SSG-LUGIA, a completely automated and unsupervised approach for identifying GIs and horizontally transferred genes. SSG-LUGIA is a novel method based on unsupervised anomaly detection technique, accompanied by further refinement using cues from signal processing literature. SSG-LUGIA leverages the atypical compositional biases of the alien genes to localize GIs in prokaryotic genomes. SSG-LUGIA was assessed on a large benchmark dataset `IslandPick' and on a set of 15 well-studied genomes in the literature and followed by a thorough analysis on the well-understood Salmonella typhi CT18 genome. Furthermore, the efficacy of SSG-LUGIA in identifying horizontally transferred genes was evaluated on two additional bacterial genomes, namely, those of Corynebacterium diphtheria NCTC13129 and Pseudomonas aeruginosa LESB58. SSG-LUGIA was examined on draft genomes and was demonstrated to be efficient as an ensemble method.

CONCLUSIONS

Our results indicate that SSG-LUGIA achieved superior performance in comparison to frequently used existing methods. Importantly, it yielded a better trade-off between precision and recall than the existing methods. Its nondependency on the functional annotation of genomes makes it suitable for analyzing newly sequenced, yet uncharacterized genomes. Thus, our study is a significant advance in identification of GIs and horizontally transferred genes. SSG-LUGIA is available as an open source software at https://nibtehaz.github.io/SSG-LUGIA/.

Genomic Island Prediction via Chi-Square Test and Random Forest Algorithm

Genomic islands are related to microbial adaptation and carry different genomic characteristics from the host. Therefore, many methods have been proposed to detect genomic islands from the rest of the genome by evaluating its sequence composition. Many sequence features have been proposed, but many of them have not been applied to the identification of genomic islands. In this paper, we present a scheme to predict genomic islands using the chi-square test and random forest algorithm. We extract seven kinds of sequence features and select the important features with the chi-square test. All the selected features are then input into the random forest to predict the genome islands. Three experiments and comparison show that the proposed method achieves the best performance. This understanding can be useful to design more powerful method for the genomic island prediction.

Mobile genetic elements mediate the mixotrophic evolution of novel Alicyclobacillus species for acid mine drainage adaptation

Alicyclobacillus species inhabit diverse environments and have adapted to broad ranges of pH and temperature. However, their adaptive evolutions remain elusive, especially regarding the role of mobile genetic elements (MGEs). Here, we characterized the distributions and functions of MGEs in Alicyclobacillus species across five environments, including acid mine drainage (AMD), beverages, hot springs, sediments, and soils. Nine Alicyclobacillus strains were isolated from AMD and possessed larger genome sizes and more genes than those from other environments. Four AMD strains evolved to be mixotrophic and fell into distinctive clusters in phylogenetic tree. Four types of MGEs including genomic island (GI), insertion sequence (IS), prophage, and integrative and conjugative element (ICE) were widely distributed in Alicyclobacillus species. Further, AMD strains did not possess CRISPR-Cas systems, but had more GI, IS, and ICE, as well as more MGE-associated genes involved in the oxidation of iron and sulfide and the resistance of heavy metal and low temperature. These findings highlight the differences in phenotypes and genotypes between strains isolated from AMD and other environments and the important role of MGEs in rapid environment niche expansions.

Genomic islands and the evolution of livestock-associated Staphylococcus aureus genomes

BACKGROUND

Genomic Islands (GIs) are commonly believed to be relics of horizontal transfer and associated with specific metabolic capacities, including virulence of the strain. Horizontal gene transfer (HGT) plays a vital role in the acquisition of GIs and the evolution and adaptation of bacterial genomes.

OBJECTIVE

The present study was designed to predict the GIs and role of HGT in evolution of livestock-associated Staphylococcus aureus (LA-SA).

METHODS

GIs were predicted with two methods namely, Ensemble algorithm for Genomic Island Detection (EGID) tool, and Seq word Sniffer script. Functional characterization of GI elements was performed with clustering of orthologs. The putative donor predictions of GIs was done with the aid of the pre_GI database.

RESULTS

The present study predicted a pan of 46 GIs across the LA-SA genomes. Functional characterization of GI sequences revealed few unique results like the presence of metabolic operons like leuABCD and folPK genes in GIs and showed the importance of GIs in the adaptation to the host niche. The developed framework for GI donor prediction results revealed Rickettsia and Mycoplasma as the major donors of GI elements.

CONCLUSIONS

The role of GIs during the evolutionary race of LA-SA could be concluded from the present study. Niche adaptation of LA-SA enhanced presumably due to these GIs. Future studies could focus on the evolutionary relationships between Rickettsia and Mycoplasma sp. with S. aureus and also the evolution of Leucine/Isoleucine mosaic operon (leuABCD).

panRGP: a pangenome-based method to predict genomic islands and explore their diversity

MOTIVATION

Horizontal gene transfer (HGT) is a major source of variability in prokaryotic genomes. Regions of genome plasticity (RGPs) are clusters of genes located in highly variable genomic regions. Most of them arise from HGT and correspond to genomic islands (GIs). The study of those regions at the species level has become increasingly difficult with the data deluge of genomes. To date, no methods are available to identify GIs using hundreds of genomes to explore their diversity.

RESULTS

We present here the panRGP method that predicts RGPs using pangenome graphs made of all available genomes for a given species. It allows the study of thousands of genomes in order to access the diversity of RGPs and to predict spots of insertions. It gave the best predictions when benchmarked along other GI detection tools against a reference dataset. In addition, we illustrated its use on metagenome assembled genomes by redefining the borders of the leuX tRNA hotspot, a well-studied spot of insertion in Escherichia coli. panRPG is a scalable and reliable tool to predict GIs and spots making it an ideal approach for large comparative studies.

AVAILABILITY AND IMPLEMENTATION

The methods presented in the current work are available through the following software: https://github.com/labgem/PPanGGOLiN. Detailed results and scripts to compute the benchmark metrics are available at https://github.com/axbazin/panrgp_supdata.

Comparative genome analysis of three Group A Streptococcus dysgalactiae subsp. equisimilis strains isolated in Japan

Introduction . Streptococcus dysgalactiae subsp. equisimilis (SDSE) is a β-hemolytic streptococcus that causes severe invasive streptococcal infections, especially in the elderly and people with underlying diseases. SDSE strains are primarily characterized by Lancefield group G or C antigens.Hypothesis/Gap Statement. We have previously reported the prevalence of Lancefield group A SDSE (GA-SDSE) strains in Japan and have analysed the draft genome sequences of these strains. As GA-SDSE is a rare type of SDSE, only one complete genome has been sequenced to date.Aim. The present study is focused on genetic characteristics of GA-SDSE strains. In order to examine molecular characteristics, we also tested growth inhibition of other streptococci by GA-SDSE.Methodology. We determined the complete genome sequences of three GA-SDSE strains by two new generation sequencing systems (short-read and long-read sequencing data). Using the sequences, we also conducted a comparative analysis of GA-SDSE and group C/G SDSE strains. In addition, we tested multiplex and quantitative PCRs targeting the GA-SDSE, group G SDSE, and S. pyogenes.Results. We found a group-specific conserved region in GA-SDSE strains that is composed of genes encoding predicted anti-bacteriocin and streptococcal lantibiotic (Sal) proteins. Multiplex and quantitative PCRs targeting the GA-SDSE-specific region were able to distinguish between GA-SDSE, other SDSE, and S. pyogenes strains. The growth of GA-SDSE was suppressed in the presence of group G SDSE, indicating a possible explanation for the low frequency of isolation of GA-SDSE.Conclusion. The comparative genome analysis shows that the genome of GA-SDSE has a distinct arrangement, enabling the differentiation between S. pyogenes, GA-SDSE, and other SDSE strains using our PCR methods.

Estimation of pathogenic potential of an environmental Pseudomonas aeruginosa isolate using comparative genomics

The isolation and sequencing of new strains of Pseudomonas aeruginosa created an extensive dataset of closed genomes. Many of the publicly available genomes are only used in their original publication while additional in silico information, based on comparison to previously published genomes, is not being explored. In this study, we defined and investigated the genome of the environmental isolate P. aeruginosa KRP1 and compared it to more than 100 publicly available closed P. aeruginosa genomes. By using different genomic island prediction programs, we could identify a total of 17 genomic islands and 8 genomic islets, marking the majority of the accessory genome that covers ~ 12% of the total genome. Based on intra-strain comparisons, we are able to predict the pathogenic potential of this environmental isolate. It shares a substantial amount of genomic information with the highly virulent PSE9 and LESB58 strains. For both of these, the increased virulence has been directly linked to their accessory genome before. Hence, the integrated use of previously published data can help to minimize expensive and time consuming wetlab work to determine the pathogenetic potential.

Comparative Genomics, from the Annotated Genome to Valuable Biological Information: A Case Study

High availability of fast, cheap, and high-throughput next generation sequencing techniques resulted in acquisition of numerous de novo sequenced and assembled bacterial genomes. It rapidly became clear that digging out useful biological information from such a huge amount of data presents a considerable challenge. In this chapter we share our experience with utilization of several handy open source comparative genomic tools. All of them were applied in the studies focused on revealing inter- and intraspecies variation in pectinolytic plant pathogenic bacteria classified to Dickeya solani and Pectobacterium parmentieri. As the described software performed well on the species within the Pectobacteriaceae family, it presumably may be readily utilized on some closely related taxa from the Enterobacteriaceae family. First of all, implementation of various annotation software is discussed and compared. Then, tools computing whole genome comparisons including generation of circular juxtapositions of multiple sequences, revealing the order of synteny blocks or calculation of ANI or Tetra values are presented. Besides, web servers intended either for functional annotation of the genes of interest or for detection of genomic islands, plasmids, prophages, CRISPR/Cas are described. Last but not least, utilization of the software designed for pangenome studies and the further downstream analyses is explained. The presented work not only summarizes broad possibilities assured by the comparative genomic approach but also provides a user-friendly guide that might be easily followed by nonbioinformaticians interested in undertaking similar studies.