Bacterial Genomes Research Articles

What makes a temperate phage an effective bacterial weapon?

Temperate bacteriophages-viruses that integrate within bacterial DNA-are incredibly common within bacterial genomes and can act as powerful self-amplifying weapons. Bacterial hosts that carry temperate bacteriophages can thus gain a fitness advantage within a given niche by killing competitors. But what makes an effective phage weapon? Here, we first use a simple mathematical model to explore the factors determining bacteriophage weapon utility. Our models suggest that bacteriophage weapons are nuanced and context-dependent; an individual bacteriophage may be beneficial or costly depending upon tiny changes to how it behaves or the bacterial community it inhabits. We then confirm these mathematical predictions experimentally, using phages isolated from cystic fibrosis patients. But, in doing so, we also find that another factor-nutrient availability-plays a key role in shaping bacteriophage-mediated competition. Together, our results provide new insights into how temperate bacteriophages modulate bacterial communities.

Large-scale bacterial genomic and metagenomic analysis reveals Pseudomonas aeruginosa as potential ancestral source of tigecycline resistance gene cluster tmexCD-toprJ

BackgroundThe global dissemination of the multidrug resistance efflux pump gene cluster tmexCD-toprJ has greatly weakened the effects of multiple antibiotics, including tigecycline. However, the potential origin and transmission mechanisms of the gene cluster remain unclear. MethodsHere, we concluded a comprehensive bioinformatics analysis on integrated 73,498 bacterial genomes, including Pseudomonas spp., Klebsiella spp., Aeromonas spp., Proteus spp., and Citrobacter spp., along with 1,152 long-read metagenomic datasets to trace the origin and propagation of tmexCD-toprJ. ResultsOur results demonstrated that tmexCD-toprJ was predominantly found in Pseudomonas aeruginosa sourced from human hosts in Asian countries and North American countries. Phylogenetic and genomic feature analyses showed that tmexCD-toprJ was likely evolved from mexCD-oprJ of some special clones of P. aeruginosa. Furthermore, metagenomic analysis confirmed that P. aeruginosa is the only potential ancestral bacterium for tmexCD-toprJ. A putative mobile genetic structure harboring tmexCD-toprJ, int-int-hp-hp-tnfxB-tmexCD-toprJ, was the predominant genetic context of tmexCD-toprJ across various bacterial genera, suggesting that the two integrase genes play a pivotal role in the horizontal transmission of tmexCD-toprJ. ConclusionsBased on these findings, it is almost certain that the tmexCD-toprJ gene cluster was derived from P. aeruginosa and further spread to other bacteria.

Characterization of Bacillus velezensis TJS119 and its biocontrol potential against insect pathogens

IntroductionThe white-spotted flower chafer (Protaetia brevitarsis seulensis), which is widely distributed in Asian countries, is traditionally used in oriental medicine. However, its larvae are prone to severe damage by green muscardine disease (caused by Metarhizium anisopliae) during breeding. The aim of this study was to characterize Bacillus velezensis TJS119, which has been isolated from freshwater, and investigate its potential as a biocontrol agent against M. anisopliae in insects.MethodsTJS119 was obtained from freshwater samples in the Republic of Korea and was classified as B. velezensis. We evaluated its in vitro antifungal effect, sequenced the bacterial whole genome, mined genes responsible for the synthesis of secondary metabolites, performed secondary metabolite analysis Ultra performance liquid chromatography-mass spectrometry (UPLC–MS/MS), and conducted bioassays for determining green muscardine disease control ability.ResultsBacillus velezensis TJS119 inhibited the mycelial growth of M. anisopliae in vitro. The size of the B. velezensis TJS119 genome was estimated to be 3,890,913 bp with a GC content of 46.67% and 3,750 coding sequences. Biosynthetic gene clusters for secondary metabolites with antifungal activity were identified in the genome. Lipopeptides, including fengycin secreted by TJS119 exhibit antifungal activity. Application of TJS119 for the biocontrol against green muscardine disease increased the viability of white-spotted flower chafer by 94.7% compared to the control.DiscussionThese results indicate that B. velezensis TJS119 is a potential biocontrol agent for insect pathogens.

Parsnp 2.0: Scalable Core-Genome alignment for massive microbial datasets.

Since 2016, the number of microbial species with available reference genomes in NCBI has more than tripled. Multiple genome alignment, the process of identifying nucleotides across multiple genomes which share a common ancestor, is used as the input to numerous downstream comparative analysis methods. Parsnp is one of the few multiple genome alignment methods able to scale to the current era of genomic data; however, there has been no major release since its initial release in 2014. To address this gap, we developed Parsnp v2, which significantly improves on its original release. Parsnp v2 provides users with more control over executions of the program, allowing Parsnp to be better tailored for different use-cases. We introduce a partitioning option to Parsnp, which allows the input to be broken up into multiple parallel alignment processes which are then combined into a final alignment. The partitioning option can reduce memory usage by over 4x and reduce runtime by over 2x, all while maintaining a precise core-genome alignment. The partitioning workflow is also less susceptible to complications caused by assembly artifacts and minor variation, as alignment anchors only need to be conserved within their partition and not across the entire input set. We highlight the performance on datasets involving thousands of bacterial and viral genomes. Parsnp v2 is available at https://github.com/marbl/parsnp.

Hybracter: enabling scalable, automated, complete and accurate bacterial genome assemblies.

Improvements in the accuracy and availability of long-read sequencing mean that complete bacterial genomes are now routinely reconstructed using hybrid (i.e. short- and long-reads) assembly approaches. Complete genomes allow a deeper understanding of bacterial evolution and genomic variation beyond single nucleotide variants. They are also crucial for identifying plasmids, which often carry medically significant antimicrobial resistance genes. However, small plasmids are often missed or misassembled by long-read assembly algorithms. Here, we present Hybracter which allows for the fast, automatic and scalable recovery of near-perfect complete bacterial genomes using a long-read first assembly approach. Hybracter can be run either as a hybrid assembler or as a long-read only assembler. We compared Hybracter to existing automated hybrid and long-read only assembly tools using a diverse panel of samples of varying levels of long-read accuracy with manually curated ground truth reference genomes. We demonstrate that Hybracter as a hybrid assembler is more accurate and faster than the existing gold standard automated hybrid assembler Unicycler. We also show that Hybracter with long-reads only is the most accurate long-read only assembler and is comparable to hybrid methods in accurately recovering small plasmids.

Nonribosomal Peptide Synthetase Specific Genome Amplification Using Rolling Circle Amplification for Targeted Gene Sequencing

Next-generation sequencing has transformed the acquisition of vast amounts of genomic information, including the rapid identification of target gene sequences in metagenomic databases. However, dominant species can sometimes hinder the detection of rare bacterial species. Therefore, a highly sensitive amplification technique that can selectively amplify bacterial genomes containing target genes of interest was developed in this study. The rolling circle amplification (RCA) method can initiate amplification from a single locus using a specific single primer to amplify a specific whole genome. A mixed cell suspension was prepared using Pseudomonas fluorescens ATCC17400 (targeting nonribosomal peptide synthetase [NRPS]) and Escherichia coli (non-target), and a specific primer designed for the NRPS was used for the RCA reaction. The resulting RCA product (RCP) amplified only the Pseudomonas genome. The NRPS was successfully amplified using RCP as a template from even five cells, indicating that the single-priming RCA technique can specifically enrich the target genome using gene-specific primers. Ultimately, this specific genome RCA technique was applied to metagenomes extracted from sponge-associated bacteria, and NRPS sequences were successfully obtained from an unknown sponge-associated bacterium. Therefore, this method could be effective for accessing species-specific sequences of NRPS in unknown bacteria, including viable but non-culturable bacteria.

Metagenomics datasets of water and sediments from eutrophication-impacted artificial lakes in South Africa

We present metagenomes of 16 samples of water and sediment from two lakes, collected from eutrophic and non-eutrophic areas, including pooled samples enriched with phosphate and nitrate. Additionally, we assembled 167 bacterial metagenome-assembled genomes (MAGs). These MAGs were de-replicated into 83 unique genomes representing different species found in the lakes. All the MAGs exhibited >70% completeness and <10% contamination, with 79 MAGs being classified as ‘nearly complete’ (completeness >90%), while 54 falling within 80–90% range and 34 between 75–80% complete. The most abundant MAGs identified across all samples were Proteobacteria (n = 80), Firmicutes_A (n = 35), Firmicutes (n = 13), and Bacteriodota (n = 22). Other groups included Desulfobacteria_I (n = 2), Verrucomicrobiota (n = 4), Campylobacterota (n = 4) and Actinobacteriota (n = 6). Importantly, phylogenomic analysis identified that approximately 50.3% of the MAGs could not be classified to known species, suggesting the presence of potentially new and unknown bacteria in these lakes, warranting further in-depth investigation. This study provides valuable new dataset on the diverse and often unique microbial communities living in polluted lakes, useful in developing effective strategies to manage pollution.

Synthetic bacteria designed using ars operons: a promising solution for arsenic biosensing and bioremediation.

The global concern over arsenic contamination in water due to its natural occurrence and human activities has led to the development of innovative solutions for its detection and remediation. Microbial metabolism and mobilization play crucial roles in the global cycle of arsenic. Many microbial arsenic-resistance systems, especially the ars operons, prevalent in bacterial plasmids and genomes, play vital roles in arsenic resistance and are utilized as templates for designing synthetic bacteria. This review novelty focuses on the use of these tailored bacteria, engineered with ars operons, for arsenic biosensing and bioremediation. We discuss the advantages and disadvantages of using synthetic bacteria in arsenic pollution treatment. We highlight the importance of genetic circuit design, reporter development, and chassis cell optimization to improve biosensors' performance. Bacterial arsenic resistances involving several processes, such as uptake, transformation, and methylation, engineered in customized bacteria have been summarized for arsenic bioaccumulation, detoxification, and biosorption. In this review, we present recent insights on the use of synthetic bacteria designed with ars operons for developing tailored bacteria for controlling arsenic pollution, offering a promising avenue for future research and application in environmental protection.

Quorum sensing in bacteria: in silico protein analysis, ecophysiology, and reconstruction of their evolutionary history

BackgroundQuorum sensing (QS) is a sophisticated cell-to-cell signalling mechanism that allows the coordination of important processes in microbial populations. The AI-1 and AI-2 autoinducer systems are among the best characterized bacterial QS systems at the genetic level.ResultsIn this study, we present data derived from in silico screening of QS proteins from bacterial genomes available in public databases. Sequence analyses allowed identifying candidate sequences of known QS systems that were used to build phylogenetic trees. Eight categories were established according to the number of genes from the two major QS systems present in each genome, revealing a correlation with specific taxa, lifestyles or metabolic traits. Many species had incomplete QS systems, encoding the receptor protein but not the biosynthesis of the quorum sensing molecule (QSMs). Reconstruction of the evolutionary history of the LuxR family and prediction of the 3D structure of the ancestral protein suggested their monomeric configuration in the absence of the signal molecule and the presence of a cavity for its binding.ConclusionsHere we correlate the taxonomic affiliation and lifestyle of bacteria from different genera with the QS systems encoded in their genomes. Moreover, we present the first ancestral reconstruction of the LuxR QS receptors, providing further insight in their evolutionary history.

Detection of florfenicol resistance in opportunistic Acinetobacter spp. infections in rural Thailand

Florfenicol (Ff) is an antimicrobial agent belonging to the class amphenicol used for the treatment of bacterial infections in livestock, poultry, and aquaculture (animal farming). It inhibits protein synthesis. Ff is an analog of chloramphenicol, an amphenicol compound on the WHO essential medicine list that is used for the treatment of human infections. Due to the extensive usage of Ff in animal farming, zoonotic pathogens have developed resistance to this antimicrobial agent. There are numerous reports of resistance genes from organisms infecting or colonizing animals found in human pathogens, suggesting a possible exchange of genetic materials. One of these genes is floR, a gene that encodes for an efflux pump that removes Ff from bacterial cells, conferring resistance against amphenicol, and is often associated with mobile genetic elements and other resistant determinants. In this study, we analyzed bacterial isolates recovered in rural Thailand from patients and environmental samples collected for disease monitoring. Whole genome sequencing was carried out for all the samples collected. Speciation and genome annotation was performed revealing the presence of the floR gene in the bacterial genome. The minimum inhibitory concentration (MIC) was determined for Ff and chloramphenicol. Chromosomal and phylogenetic analyses were performed to investigate the acquisition pattern of the floR gene. The presence of a conserved floR gene in unrelated Acinetobacter spp. isolated from human bacterial infections and environmental samples was observed, suggesting multiple and independent inter-species genetic exchange of drug-resistant determinants. The floR was found to be in the variable region containing various mobile genetic elements and other antibiotic resistance determinants; however, no evidence of HGT could be found. The floR gene identified in this study is chromosomal for all isolates. The study highlights a plausible impact of antimicrobials used in veterinary settings on human health. Ff shares cross-resistance with chloramphenicol, which is still in use in several countries. Furthermore, by selecting for floR-resistance genes, we may be selecting for and facilitating the zoonotic and reverse zoonotic exchange of other flanking resistance markers between human and animal pathogens or commensals with detrimental public health consequences.

Predicting metabolic modules in incomplete bacterial genomes with MetaPathPredict.

The reconstruction of complete microbial metabolic pathways using 'omics data from environmental samples remains challenging. Computational pipelines for pathway reconstruction that utilize machine learning methods to predict the presence or absence of KEGG modules in incomplete genomes are lacking. Here, we present MetaPathPredict, a software tool that incorporates machine learning models to predict the presence of complete KEGG modules within bacterial genomic datasets. Using gene annotation data and information from the KEGG module database, MetaPathPredict employs deep learning models to predict the presence of KEGG modules in a genome. MetaPathPredict can be used as a command line tool or as a Python module, and both options are designed to be run locally or on a compute cluster. Benchmarks show that MetaPathPredict makes robust predictions of KEGG module presence within highly incomplete genomes.

Slings and arrows: sRNAs mediate intragenomic competition

Bacterial genomes are littered with exogenous: competing DNA elements. Here, Sprenger etal. demonstrate that the Vibrio cholerae prophage VP882 modulates host functions via production of regulatory sRNAs to promote phage development. Alternatively, host sRNAs inhibit the VP882 lytic phase by specifically regulating phage genes.

Evaluation of the accuracy of bacterial genome reconstruction with Oxford Nanopore R10.4.1 long-read-only sequencing.

Whole-genome reconstruction of bacterial pathogens has become an important tool for tracking transmission and antimicrobial resistance gene spread, but highly accurate and complete assemblies have largely only historically been achievable using hybrid long- and short-read sequencing. We previously found the Oxford Nanopore Technologies (ONT) R10.4/kit12 flowcell/chemistry produced improved assemblies over the R9.4.1/kit10 combination, however long-read only assemblies contained more errors compared to Illumina-ONT hybrid assemblies. ONT have since released an R10.4.1/kit14 flowcell/chemistry upgrade and recommended the use of Bovine Serum Albumin (BSA) during library preparation, both of which reportedly increase accuracy and yield. They have also released updated basecallers trained using native bacterial DNA containing methylation sites intended to fix systematic basecalling errors, including common adenosine (A) to guanine (G) and cytosine (C) to thymine (T) substitutions. To evaluate these improvements, we successfully sequenced four bacterial reference strains, namely Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus, and nine genetically diverse E. coli bloodstream infection-associated isolates from different phylogroups and sequence types, both with and without BSA. These sequences were de novo assembled and compared against Illumina-corrected reference genomes. In this small evaluation of 13 isolates we found that nanopore long-read-only R10.4.1/kit 14 assemblies with updated basecallers trained using bacterial methylated DNA produce accurate assemblies with ≥40×depth, sufficient to be cost-effective compared with hybrid ONT/Illumina sequencing in our setting.

EVALUATION OF PROPHAGES AND ANTI MICROBIAL RESISTANCE PROFILE OF BACILLUS SUBTILIS USING IN SILICO APPROACH

The main objective of this study was to identify the prophages and antimicrobial resistance profile of  Bacillus subtilis using computational methods. Prophages are potential therapeutic antimicrobial agents against antibiotic- resistant pathogens. The potential of prophage to induce antimicrobial resistance and increase pathogenicity in bacterial genomes resulted in renewed interest in the identification of prophage sequences and their associated antimicrobial resistant genes in bacterial genomes. Sequences of Bacillus subtilis retrieved from the  sequence raw archive (SRA) of the National Centre for Biotechnology Information was submitted to  bacterial viral bioinformatics resource centre for genome assembly. Prophage sequences were identified using the PHASTER server. The region length, region position and GC percentage of nucleotides of prophage sequences were identified. The antimicrobial resistance gene family, drug class, resistance mechanism and length of reference sequences were identified using the resistance gene identifier protocol of the comprehensive antimicrobial resistance database. It can be concluded that the Bacillus subtilis strain evaluated contained prophage sequences associated with antimicrobial resistance genes, there is, therefore, the need to assess the safety of bacteriophages before they are   utilized as alternative to antibiotics.

KmerAperture: Retaining k-mer synteny for alignment-free extraction of core and accessory differences between bacterial genomes.

By decomposing genome sequences into k-mers, it is possible to estimate genome differences without alignment. Techniques such as k-mer minimisers, for example MinHash, have been developed and are often accurate approximations of distances based on full k-mer sets. These and other alignment-free methods avoid the large temporal and computational expense of alignment. However, these k-mer set comparisons are not entirely accurate within-species and can be completely inaccurate within-lineage. This is due, in part, to their inability to distinguish core polymorphism from accessory differences. Here we present a new approach, KmerAperture, which uses information on the k-mer relative genomic positions to determine the type of polymorphism causing differences in k-mer presence and absence between pairs of genomes. Single SNPs are expected to result in contiguous of k unique k-mers per genome. On the other hand, contiguous series > k may be caused by accessory differences of length S-k+1; when the start and end of the sequence are contiguous with homologous sequence. Alternatively, they may be caused by multiple SNPs within k bp from each other and KmerAperture can determine whether that is the case. To demonstrate use cases KmerAperture was benchmarked using datasets including a very low diversity simulated population with accessory content independent from the number of SNPs, a simulated population were SNPs are spatially dense, a moderately diverse real cluster of genomes (Escherichia coli ST1193) with a large accessory genome and a low diversity real genome cluster (Salmonella Typhimurium ST34). We show that KmerAperture can accurately distinguish both core and accessory sequence diversity without alignment, outperforming other k-mer based tools.

Species-level distribution of microbiota with secondary metabolic potential in Chinese Baijiu fermentation

Chinese Baijiu fermentation is a typical spontaneous fermentation with complex microbial community. However, the species-level distribution of microbiota with secondary metabolic potential in Baijiu fermentation has not been well studied so far. In this study, taking soy sauce aroma type Baijiu and light aroma type Baijiu fermentations as examples, we identified 1575 biosynthetic gene clusters (BGCs) belonging to 874 gene cluster families (GCFs) through metagenomic analysis. Bioactivity prediction analysis revealed 210 BGCs producing potential bioactive secondary metabolites (probabilities of bioactivities ≥70%). We recovered 66 bacterial metagenome-assembled genomes (MAGs) to explore distribution of bioactive secondary metabolites at a higher resolution taxonomic level. A total of 16 MAGs were identified as BGC-rich MAGs (>3 BGCs), and they belonged to 11 genera. Four MAGs, annotated to be Bacillus velezensis, Bacillus licheniformis, Kroppenstedtia eburnea and Kroppenstedtia spp., contained more than 3 BGC-producing potential bioactive secondary metabolites and had more than 1 counts per million (CPM) abundance in fermentations. They were identified as the potential producers of bioactive secondary metabolites. This study contributed to characterising the diversity and distribution of microbiota with secondary metabolic potential in Baijiu fermentation, and mining novel secondary metabolites and their producers.

Synesth: Comprehensive Syntenic Reconciliation with Unsampled Lineages

We present Synesth, the most comprehensive and flexible tool for tree reconciliation that allows for events on syntenies (i.e., on sets of multiple genes), including duplications, transfers, fissions, and transient events going through unsampled species. This model allows for building histories that explicate the inconsistencies between a synteny tree and its associated species tree. We examine the combinatorial properties of this extended reconciliation model and study various associated parsimony problems. First, the infinite set of explicatory histories is reduced to a finite but exponential set of Pareto-optimal histories (in terms of counts of each event type), then to a polynomial set of Pareto-optimal event count vectors, and this eventually ends with minimum event cost histories given an event cost function. An inductive characterization of the solution space using different algebras for each granularity leads to efficient dynamic programming algorithms, ultimately ending with an O(mn) time complexity algorithm for computing the cost of a minimum-cost history (m and n: number of nodes in the input synteny and species trees). This time complexity matches that of the fastest known algorithms for classical gene reconciliation with transfers. We show how Synesth can be applied to infer Pareto-optimal evolutionary scenarios for CRISPR-Cas systems in a set of bacterial genomes.

Epistasis, core-genome disharmony, and adaptation in recombining bacteria.

Recombination of short DNA fragments via horizontal gene transfer (HGT) can introduce beneficial alleles, create genomic disharmony through negative epistasis, and create adaptive gene combinations through positive epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome and are frequently observed as tightly linked cassettes with major effects. By contrast, interspecific recombination in the core genome is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma, we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and C. coli that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings, indirect evidence of negative epistasis. However, multiple HGT events enable recovery of the genome's co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred, and independently reinstated in a new genetic background-facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.IMPORTANCEGenetic exchange among bacteria shapes the microbial world. From the acquisition of antimicrobial resistance genes to fundamental questions about the nature of bacterial species, this powerful evolutionary force has preoccupied scientists for decades. However, the mixing of genes between species rests on a paradox: 0n one hand, promoting adaptation by conferring novel functionality; on the other, potentially introducing disharmonious gene combinations (negative epistasis) that will be selected against. Taking an interdisciplinary approach to analyze natural populations of the enteric bacteria Campylobacter, an ideal example of long-range admixture, we demonstrate that genes can independently transfer across species boundaries and rejoin in functional networks in a recipient genome. The positive impact of two-gene interactions appears to be adaptive by expanding metabolic capacity and facilitating niche shifts through interspecific hybridization. This challenges conventional ideas and highlights the possibility of multiple-step evolution of multi-gene traits by interspecific introgression.

Horizontal gene transfer in plant microbiomes: integrons as hotspots for cross-species gene exchange.

Plant microbiomes play important roles in plant health and fitness. Bacterial horizontal gene transfer (HGT) can influence plant health outcomes, driving the spread of both plant growth-promoting and phytopathogenic traits. However, community dynamics, including the range of genetic elements and bacteria involved in this process are still poorly understood. Integrons are genetic elements recently shown to be abundant in plant microbiomes, and are associated with HGT across broad phylogenetic boundaries. They facilitate the spread of gene cassettes, small mobile elements that collectively confer a diverse suite of adaptive functions. Here, we analysed 5,565 plant-associated bacterial genomes to investigate the prevalence and functional diversity of integrons in this niche. We found that integrons are particularly abundant in the genomes of Pseudomonadales, Burkholderiales, and Xanthomonadales. In total, we detected nearly 9,000 gene cassettes, and found that many could be involved in plant growth promotion or phytopathogenicity, suggesting that integrons might play a role in bacterial mutualistic or pathogenic lifestyles. The rhizosphere was enriched in cassettes involved in the transport and metabolism of diverse substrates, suggesting that they may aid in adaptation to this environment, which is rich in root exudates. We also found that integrons facilitate cross-species HGT, which is particularly enhanced in the phyllosphere. This finding may provide an ideal opportunity to promote plant growth by fostering the spread of genes cassettes relevant to leaf health. Together, our findings suggest that integrons are important elements in plant microbiomes that drive HGT, and have the potential to facilitate plant host adaptation.

RecGraph: recombination-aware alignment of sequences to variation graphs.

Bacterial genomes present more variability than human genomes, which requires important adjustments in computational tools that are developed for human data. In particular, bacteria exhibit a mosaic structure due to homologous recombinations, but this fact is not sufficiently captured by standard read mappers that align against linear reference genomes. The recent introduction of pangenomics provides some insights in that context, as a pangenome graph can represent the variability within a species. However, the concept of sequence-to-graph alignment that captures the presence of recombinations has not been previously investigated. In this paper, we present the extension of the notion of sequence-to-graph alignment to a variation graph that incorporates a recombination, so that the latter are explicitly represented and evaluated in an alignment. Moreover, we present a dynamic programming approach for the special case where there is at most a recombination-we implement this case as RecGraph. From a modeling point of view, a recombination corresponds to identifying a new path of the variation graph, where the new arc is composed of two halves, each extracted from an original path, possibly joined by a new arc. Our experiments show that RecGraph accurately aligns simulated recombinant bacterial sequences that have at most a recombination, providing evidence for the presence of recombination events. Our implementation is open source and available at https://github.com/AlgoLab/RecGraph. Supplementary data are available at Bioinformatics online.