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At least 19 records

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.

Computer Vision↗

Speeding genomic island discovery through systematic design of reference database composition

Background Genomic islands (GIs) are mobile genetic elements that integrate site-specifically into bacterial chromosomes, bearing genes that affect phenotypes such as pathogenicity and metabolism. GIs typically occur sporadically among related bacterial strains, enabling comparative genomic approaches to GI identification. For a candidate GI in a query genome, the number of reference genomes with a precise deletion of the GI serves as a support value for the GI. Our comparative software for GI identification was slowed by our original use of large reference genome databases (DBs). Here we explore smaller species-focused DBs. Results With increasing DB size, recovery of our reliable prophage GI calls reached a plateau, while recovery of less reliable GI calls (FPs) increased rapidly as DB sizes exceeded ~500 genomes; i.e., overlarge DBs can increase FP rates. Paradoxically, relative to prophages, FPs were both more frequently supported only by genomes outside the species and more frequently supported only by genomes inside the species; this may be due to their generally lower support values. Setting a DB size limit for our SMA ll R anked T ailored (SMART) DB design speeded runtime ~65-fold. Strictly intra-species DBs would tend to lower yields of prophages for small species (with few genomes available); simulations with large species showed that this could be partially overcome by reaching outside the species to closely related taxa, without an FP burden. Employing such taxonomic outreach in DB design generated redundancy in the DB set; as few as 2984 DBs were needed to cover all 47894 prokaryotic species. Conclusions Runtime decreased dramatically with SMART DB design, with only minor losses of prophages. We also describe potential utility in other comparative genomics projects.

59 BASIC BIOLOGICAL SCIENCES↗

Integrase-On-Demand-Pipeline Data Set

Files needed to run the Integrase-On-Demand-Pipeline, a program designed to provide users with a list of putative attachment site and integrase pairs for a prokaryotic genome of interest. isles.pkl: Serialized python-object file, containing a dictionary of attachment site sequences and reference genomic island information extracted from the Genomic island database ints.gff: Gene format file containing annotations for all integrases referenced in isles.pkl. The source genome, gene coordinates, integrase name, protein IDs and amino acid sequence included. reps.msh: Binary file containing 1000 128-bit MurmurHash3 hashes for >80,000 genomes

McClain, Hannah Marie [Sandia National Laboratorie↗

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.

59 BASIC BIOLOGICAL SCIENCES↗

Improved Mobilome Delineation in Fragmented Genomes

The mobilome of a microbe, i.e., its set of mobile elements, has major effects on its ecology, and is important to delineate properly in each genome. This becomes more challenging for incomplete genomes, and even more so for metagenome-assembled genomes (MAGs), where misbinning of scaffolds and other losses can occur. Genomic islands (GIs), which integrate into the host chromosome, are a major component of the mobilome. Our GI-detection software TIGER, unique in its precise mapping of GI termini, was applied to 74,561 genomes from 2,473 microbial species, each species containing at least one MAG and one isolate genome. A species-normalized deficit of ∼1.6 GIs/genome was measured for MAGs relative to isolates. To test whether this undercount was due to the higher fragmentation of MAG genomes, TIGER was updated to enable detection of split GIs whose termini are on separate scaffolds or that wrap around the origin of a circular replicon. This doubled GI yields, and the new split GIs matched the quality of single-scaffold GIs, except that highly fragmented GIs may lack central portions. Cross-scaffold search is an important upgrade to GI detection as fragmented genomes increasingly dominate public databases. TIGER2 better captures MAG microdiversity, recovering niche-defining GIs and supporting microbiome research aims such as virus-host linking and ecological assessment.

54 ENVIRONMENTAL SCIENCES↗

Characterizing Integrase-Attachment Site Pairs: A Machine Learning Approach

Genomic islands (GIs) are mobile genetic elements that integrate into host genomes via self-encoded integrases at specific DNA sequences known as attachment (att) sites. The ability to predict the target att site from an integrase's protein sequence is a central challenge in genomics due to the sequence diversity of integrases and the subtlety of their DNA recognition motifs.

59 BASIC BIOLOGICAL SCIENCES↗

Relationship and distribution of Salmonella enterica serovar I 4,[5],12:i:- strain sequences in the NCBI Pathogen Detection database

Background: Of the > 2600 Salmonella serovars, Salmonella enterica serovar I 4,[5],12:i:- (serovar I 4,[5],12:i:-) has emerged as one of the most common causes of human salmonellosis and the most frequent multidrug-resistant (MDR; resistance to ≥3 antimicrobial classes) nontyphoidal Salmonella serovar in the U.S. Serovar I 4,[5],12:i:- isolates have been described globally with resistance to ampicillin, streptomycin, sulfisoxazole, and tetracycline (R-type ASSuT) and an integrative and conjugative element with multi-metal tolerance named Salmonella Genomic Island 4 (SGI-4). Results: We analyzed 13,612 serovar I 4,[5],12:i:- strain sequences available in the NCBI Pathogen Detection database to determine global distribution, animal sources, presence of SGI-4, occurrence of R-type ASSuT, frequency of antimicrobial resistance (AMR), and potential transmission clusters. Genome sequences for serovar I 4,[5],12:i:- strains represented 30 countries from 5 continents (North America, Europe, Asia, Oceania, and South America), but sequences from the United States (59%) and the United Kingdom (28%) were dominant. The metal tolerance island SGI-4 and the R-type ASSuT were present in 71 and 55% of serovar I 4,[5],12:i:- strain sequences, respectively. Sixty-five percent of strain sequences were MDR which correlates to serovar I 4,[5],12:i:- being the most frequent MDR serovar. The distribution of serovar I 4,[5],12:i:- strain sequences in the NCBI Pathogen Detection database suggests that swine-associated strain sequences were the most frequent food-animal source and were significantly more likely to contain the metal tolerance island SGI-4 and genes for MDR compared to all other animal-associated isolate sequences. Conclusions: Our study illustrates how analysis of genomic sequences from the NCBI Pathogen Detection database can be utilized to identify the prevalence of genetic features such as antimicrobial resistance, metal tolerance, and virulence genes that may be responsible for the successful emergence of bacterial foodborne pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

Integrase-on-Demand

SAND2025-07449O Integrase-on-Demand is a software tool that allows users to identify regions in genomic sequences where genetic material can be integrated with high probability. It uses a database of integrases and their DNA attachment sites to search against any genomic sequence, producing a list of open sites, the integrase sequence, and the source of the genomic island. The program requires MASH software to be available on the system. It consists of a main script and a precomputed input file, with a taxonomy mode that searches closely related genomes and a search mode that looks for identical attachment site matches in the integrase/attachment input file. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Williams, Kelly [Sandia National Lab. (SNL-CA), Li↗

Natural Horizontal Gene Transfer of Antimicrobial Resistance Genes in Campylobacter spp. From Turkeys and Swine

Antibiotic-resistant Campylobacter constitutes a serious threat to public health. The clonal expansion of resistant strains and/or the horizontal spread of resistance genes to other strains and species can hinder the clinical effectiveness of antibiotics to treat severe campylobacteriosis. Still, gaps exist in our understanding of the risks of acquisition and spread of antibiotic resistance in Campylobacter. While the in vitro transfer of antimicrobial resistance genes between Campylobacter species via natural transformation has been extensively demonstrated, experimental studies have favored the use of naked DNA to obtain transformants. In this study, we used experimental designs closer to real-world conditions to evaluate the possible transfer of antimicrobial resistance genes between Campylobacter strains of the same or different species (Campylobacter coli or Campylobacter jejuni) and originating from different animal hosts (swine or turkeys). This was evaluated in vitro through co-culture experiments and in vivo with dual-strain inoculation of turkeys, followed by whole genome sequencing of parental and newly emerged strains. In vitro, we observed four independent horizontal gene transfer events leading to the acquisition of resistance to beta-lactams (blaOXA), aminoglycosides [aph(2")-If and rpsL] and tetracycline [tet(O)]. Observed events involved the displacement of resistance-associated genes by a mutated version, or the acquisition of genomic islands harboring a resistance determinant by homologous recombination; we did not detect the transfer of resistance-carrying plasmids even though they were present in some strains. In vivo, we recovered a newly emerged strain with dual-resistance pattern and identified the replacement of an existing non-functional tet(O) by a functional tet(O) in the recipient strain. Whole genome comparisons allowed characterization of the events involved in the horizontal spread of resistance genes between Campylobacter following in vitro co-culture and in vivo dual inoculation. Our study also highlights the potential for antimicrobial resistance transfer across Campylobacter species originating from turkeys and swine, which may have implications for farms hosting both species in close proximity.

59 BASIC BIOLOGICAL SCIENCES↗

Expansion of the tmRNA sequence database and new tools for search and visualization

Abstract Transfer–messenger RNA (tmRNA) contributes essential tRNA-like and mRNA-like functions during the process of trans-translation, a mechanism of quality control for the translating bacterial ribosome. Proper tmRNA identification benefits the study of trans-translation and also the study of genomic islands, which frequently use the tmRNA gene as an integration site. Automated tmRNA gene identification tools are available, but manual inspection is still important for eliminating false positives. We have increased our database of precisely mapped tmRNA sequences over 50-fold to 97 179 unique sequences. Group I introns had previously been found integrated within a single subsite within the TψC-loop; they have now been identified at four distinct subsites, suggesting multiple founding events of invasion of tmRNA genes by group I introns, all in the same vicinity. tmRNA genes were found in metagenomic archaeal genomes, perhaps a result of misbinning of bacterial sequences during genome assembly. With the expanded database, we have produced new covariance models for improved tmRNA sequence search and new secondary structure visualization tools.

59 BASIC BIOLOGICAL SCIENCES↗

Permanent Draft Genome of Strain ESFC-1: Ecological Genomics of a Newly Discovered Lineage of Filamentous Diazotrophic Cyanobacteria

The nonheterocystous filamentous cyanobacterium, strain ESFC-1, is a recently described member of the order Oscillatoriales within the Cyanobacteria. ESFC-1 has been shown to be a major diazotroph in the intertidal microbial mat system at Elkhorn Slough, CA, USA. Based on phylogenetic analyses of the 16S RNA gene, ESFC-1 appears to belong to a unique, genus-level divergence; the draft genome sequence of this strain has now been determined. Here we report features of this genome as they relate to the ecological functions and capabilities of strain ESFC-1. The 5,632,035 bp genome sequence encodes 4914 protein-coding genes and 92 RNA genes. One striking feature of this cyanobacterium is the apparent lack of either uptake or bi-directional hydrogenases typically expected within a diazotroph. Additionally, a large genomic island is found that contains numerous low GC-content genes and genes related to extracellular polysaccharide production and cell wall synthesis and maintenance.

R Craig Everroad↗

Divergent selection and climate adaptation fuel genomic differentiation between sister species of Sphagnum (peat moss)

Abstract Background and Aims New plant species can evolve through the reinforcement of reproductive isolation via local adaptation along habitat gradients. Peat mosses (Sphagnaceae) are an emerging model system for the study of evolutionary genomics and have well-documented niche differentiation among species. Recent molecular studies have demonstrated that the globally distributed species Sphagnum magellanicum is a complex of morphologically cryptic lineages that are phylogenetically and ecologically distinct. Here, we describe the architecture of genomic differentiation between two sister species in this complex known from eastern North America: the northern S. diabolicum and the largely southern S. magniae. Methods We sampled plant populations from across a latitudinal gradient in eastern North America and performed whole genome and restriction-site associated DNA sequencing. These sequencing data were then analyzed computationally. Key Results Using sliding-window population genetic analyses we find that differentiation is concentrated within ‘islands’ of the genome spanning up to 400 kb that are characterized by elevated genetic divergence, suppressed recombination, reduced nucleotide diversity and increased rates of non-synonymous substitution. Sequence variants that are significantly associated with genetic structure and bioclimatic variables occur within genes that have functional enrichment for biological processes including abiotic stress response, photoperiodism and hormone-mediated signalling. Demographic modelling demonstrates that these two species diverged no more than 225 000 generations ago with secondary contact occurring where their ranges overlap. Conclusions We suggest that this heterogeneity of genomic differentiation is a result of linked selection and reflects the role of local adaptation to contrasting climatic zones in driving speciation. This research provides insight into the process of speciation in a group of ecologically important plants and strengthens our predictive understanding of how plant populations will respond as Earth’s climate rapidly changes.

58 GEOSCIENCES↗

The genome of the naturally evolved obesity-prone Ossabaw miniature pig

The feral pigs of Ossabaw Island (USA) have an outstanding propensity to obesity and develop complete metabolic syndrome (MetS) upon prolonged high energy dieting. We now report the first high quality genome of the Ossabaw pig with Contig N50 of ~6.03 Mb, significantly higher than most other published pig genomes. Genomic comparison to Duroc reveals that variations including SNPs, INDELs and one ~2 Mb inversion identified in Ossabaw pig may be related to its “thrifty” phenotype. Finally, an important positively selected gene (PSG) was found to be LEPR (leptin receptor) containing two positively selected sites which may lead to pseudogenization of this gene with possible significant effects on obesity and inflammation development. This work provides the first complete mapping of a genome representing a naturally ‘feast and famine’ evolved phenotype of MetS, serving as a blueprint to guide the search for new targets and new biomarkers for obesity comorbidities.

59 BASIC BIOLOGICAL SCIENCES↗

Tailoring a Global Iron Regulon to a Uropathogen

Pathogenicity islands and plasmids bear genes for pathogenesis of various Escherichia coli pathotypes. Although there is a basic understanding of the contribution of these virulence factors to disease, less is known about variation in regulatory networks in determining disease phenotypes. Here, we dissected a regulatory network directed by the conserved iron homeostasis regulator, ferric uptake regulator (Fur), in uropathogenic E. coli (UPEC) strain CFT073. Comparing anaerobic genome-scale Fur DNA binding with Fur-dependent transcript expression and protein levels of the uropathogen to that of commensal E. coli K-12 strain MG1655 showed that the Fur regulon of the core genome is conserved but also includes genes within the pathogenicity/genetic islands. Unexpectedly, regulons indicative of amino acid limitation and the general stress response were also indirectly activated in the uropathogen fur mutant, suggesting that induction of the Fur regulon increases amino acid demand. Using RpoS levels as a proxy, addition of amino acids mitigated the stress. In addition, iron chelation increased RpoS to the same levels as in the fur mutant. The increased amino acid demand of the fur mutant or iron chelated cells was exacerbated by aerobic conditions, which could be partly explained by the O 2 -dependent synthesis of the siderophore aerobactin, encoded by an operon within a pathogenicity island. Taken together, these data suggest that in the iron-poor environment of the urinary tract, amino acid availability could play a role in the proliferation of this uropathogen, particularly if there is sufficient O 2 to produce aerobactin. IMPORTANCE Host iron restriction is a common mechanism for limiting the growth of pathogens. We compared the regulatory network controlled by Fur in uropathogenic E. coli (UPEC) to that of nonpathogenic E. coli K-12 to uncover strategies that pathogenic bacteria use to overcome iron limitation. Although iron homeostasis functions were regulated by Fur in the uropathogen as expected, a surprising finding was the activation of the stringent and general stress responses in the uropathogen fur mutant, which was rescued by amino acid addition. This coordinated global response could be important in controlling growth and survival under nutrient-limiting conditions and during transitions from the nutrient-rich environment of the lower gastrointestinal (GI) tract to the more restrictive environment of the urinary tract. The coupling of the response of iron limitation to increased demand for amino acids could be a critical attribute that sets UPEC apart from other E. coli pathotypes.

59 BASIC BIOLOGICAL SCIENCES↗