Genome Research Articles

Arachis mottle-associated virus, a new polerovirus infecting Pinto peanut.

A new polerovirus, named "arachis mottle-associated virus" (ArMoV), was identified by high-throughput sequencing in a Pinto peanut (Arachis pintoi) plant. The genome sequence was confirmed by Sanger sequencing and contains 5775 nucleotides and seven predicted open reading frames (ORFs), showing a typical polerovirus genome structure. All of the proteins encoded by ArMoV showed less than 90% amino acid sequence identity to those of other poleroviruses, the threshold to establish a new species in the genus. Phylogenetic analysis based on P1-P2 fusion protein and coat protein amino acid sequences showed that tobacco polerovirus 1 and chickpea chlorotic stunt virus, respectively, were the most closely related to ArMoV. These data suggest that ArMoV is a member of a new species of the genus Polerovirus, for which the binomial name "Polerovirus ARMOV " is proposed.

HiFiBGC: an ensemble approach for improved biosynthetic gene cluster detection in PacBio HiFi-read metagenomes.

Microbes produce diverse bioactive natural products with applications in fields such as medicine and agriculture. In their genomes, these natural products are encoded by physically clustered genes known as biosynthetic gene clusters (BGCs). Genome and metagenome sequencing advances have enabled high-throughput identification of BGCs as a promising avenue for natural product discovery. BGC mining from (meta)genomes using in silico tools has allowed access to a vast diversity of potentially novel natural products. However, a fundamental limitation has been the ability to assemble complete BGCs, especially from complex metagenomes. With their fragmented assemblies, short-read technologies struggle to recover complete BGCs, such as the long and repetitive nonribosomal peptide synthetase (NRPS) and polyketide synthase (PKS). Recent advances in long-read sequencing, such as the High Fidelity (HiFi) technology from PacBio, have reduced this limitation and can help retrieve both accurate and complete BGCs from metagenomes, warranting improvement in the existing BGC identification approach for better utilization of HiFi data. Here, we present HiFiBGC, a command-line-based workflow to identify BGCs in PacBio HiFi metagenomes. HiFiBGC leverages an ensemble of assemblies from three HiFi-tailored metagenome assemblers and the reads not represented in these assemblies. Based on our analyses of four HiFi metagenomic datasets from four different environments, we show that HiFiBGC identifies, on average, 78% more BGCs than the top-performing single-assembler-based method. This increase is due to HiFiBGC's ensemble assembly approach, which improves recovery by 25%, as well as from the inclusion of mostly fragmented BGCs identified in the unmapped reads. HiFiBGC is a computational workflow for identifying BGCs in long-read HiFi metagenomes, implemented majorly using Python programming language and workflow manager Snakemake. HiFiBGC is available on GitHub at https://github.com/ay-amityadav/HiFiBGC under the MIT license. The code related to the figures and analyses presented in the manuscript is available at https://github.com/ay-amityadav/HiFiBGC_analyses .

Whole-Genome Sequence and Characterization of Ralstonia solanacearum MLY102 Isolated from Infected Tobacco Stalks

Background/Objectives: Bacterial wilt disease is a soil-borne disease caused by Ralstonia solanacearum that causes huge losses to crop economies worldwide. Methods: In this work, strain MLY102 was isolated and further identified as R. solanacearum from a diseased tobacco stalk. The genomic properties of MLY102 were explored by performing biochemical characterization, genome sequencing, compositional analysis, functional annotation and comparative genomic analysis. Results: MLY102 had a pinkish-red color in the center of the colony surrounded by a milky-white liquid with fluidity on TTC medium. The biochemical results revealed that MLY102 can utilize carbon sources, including D-glucose (dGLU), cane sugar (SAC) and D-trehalose dihydrate (dTRE). Genome sequencing through the DNBSEQ and PacBio platforms revealed a genome size of 5.72 Mb with a G+C content of 67.59%. The genome consists of a circular chromosome and a circular giant plasmid with 5283 protein-coding genes. A comparison of the genomes revealed that MLY102 is closely related to GMI1000 and CMR15 but has 498 special genes and 13 homologous genes in the species-specific gene family, indicating a high degree of genomic uniqueness. Conclusions: The unique characteristics and genomic data of MLY102 can provide important reference values for the prevention and control of bacterial wilt disease.

Complete genome sequence of tsaoko stripe mosaic virus, a novel macluravirus found in Amomum tsaoko.

A novel macluravirus, tentatively named "tsaoko stripe mosaic virus" (TkSMV), was identified in Amomum tsaoko through high-throughput sequencing. The complete genome sequence of TkSMV was determined using RT-PCR and RACE. The genome sequence consists of 8218 nucleotides, excluding the poly(A) tail, and contains a large open reading frame encoding a polyprotein of 2625 amino acids with a molecular weight of approximately 297.13 kDa. TkSMV is most closely related to Alpinia oxyphylla mosaic virus, sharing 71.5% nucleotide and 75.9% amino acid sequence identity. These values are below the species demarcation threshold for the family Potyviridae. These results suggest that TkSMV should be considered a distinct member of the genus Macluravirus.

A novel picorna-like virus in the flatworm Stenostomum leucops (Catenulida).

We present the genome sequence and organization and evidence of persistence of a new picorna-like virus infecting the flatworm Stenostomum leucops. The complete genome sequence belongs to a virus with a positive single-stranded RNA genome with two open reading frames (ORFs) flanked by untranslated regions and a polyadenylated C-terminus. The ORFs encode proteins with conserved motifs typical of members of the order Picornavirales. Phylogenetic analysis confirmed membership in this viral order, and it was found to be closely related to viruses found in Biomphalaria (Mollusca) in France and a virus detected in a metagenomic analysis of water sources from the USA, suggesting widespread distribution. RT-PCR analysis revealed that this virus can be detected in a laboratory-grown worm isolate for at least five years, suggesting persistent infection. However, no apparent deleterious effects were observed in the worms in culture, suggesting a possible commensal relationship between the virus and the worms.

Genomic Architecture Underlying the Striking Colour Variation in the Presence of Gene Flow for the Guinan Toad-Headed Lizard.

How divergence occurs between closely related organisms in the absence of geographic barriers to gene flow stands as one of the long-standing questions in evolutionary biology. Previous studies suggested that the interplay between selection, gene flow and recombination strongly affected the process of divergence with gene flow. However, the extent to which these forces interact to drive divergence remains largely ambiguous. Guinan toad-headed lizards (Phrynocephalus guinanensis) in the Mugetan Desert exhibit striking colour differences from lizards outside the desert and provide an excellent model to address this question. Through extensive sampling and whole genome sequencing, we obtained genotypes for 191 samples from 14 populations inside and outside the desert. Despite the colour differences, continuous and asymmetric gene flow was detected across the desert border. More importantly, 273 highly diverged regions (HDRs) were identified between them, accounting only for 0.47% of the genome but widely distributed across 20 (out of the total 24) chromosomes. Strong signatures of selection were identified in HDRs, and local recombination rates were repressed. Furthermore, five HDRs exhibited significantly higher divergence, which contained key genes associated with crucial functions in animal coloration, including pteridine and melanocyte pigmentation. Genes related to retinal cells and steroid hormones were identified in other HDRs, which might have also contributed to the formation of colour variation in the presence of gene flow. This study provided novel insights into the understanding of the evolutionary mechanisms of genetic divergence in the presence of gene flow.

Isolation, characterization, and whole genome sequencing analysis of Aeromonas veronii from Channa argus in China.

Aeromonas veronii has emerged as a significant pathogen that impacts both fish and mammals. Recently, an infectious disease characterized by multiple ulcers on the body surface with a high mortality rate occurred in Channa argus cultured in Jiangsu Province, China. A Gram-negative bacterial strain (Aer12) was isolated from the body surface of the diseased fish and identified as A. veronii by the physiological, biochemical, and 16S rRNA gene analysis. Intra-peritoneal injection of Aer12 into the healthy C. argus resulted in the development of multiple ulcers on the body surface, and the histopathological results showed that muscle tissue rupture was the most severe symptom. Aer12 showed both protease and lipase activities with no β-hemolytic activity. Furthermore, Aer12 contained seven virulence genes (aer, act, alt, fla, ascV, aexT, and ela) and one antibiotic resistance gene (qnrS) identified by the PCR assay. The results of whole genome sequencing revealed that Aer12 had a circular chromosome that measured 4,719,428bp. It comprised 4301 predicted protein-coding sequences (CDS) in addition to 31 rRNA, 124 tRNA, and 49 sRNA genes. Furthermore, a total of 676 virulence genes and 216 antibiotic resistance genes have been predicted. Aer12 was susceptible to 21 antibiotics, including ampicillin and erythromycin. The results of Chinese herbs susceptibility assay showed that Aer12 was highly susceptible to Sanguisorba officinalis, Galla chinensis, and Schisandra chinensis. The results of this study will serve as a reference for future research on the pathogenic mechanism of A. veronii and the prevention and control of bacterial diseases in C. argus farming.

Whole-genome sequencing of copy number variation analysis in Ethiopian cattle reveals adaptations to diverse environments.

Genomic structural variations (GSVs), notably copy number variations (CNVs), significantly shape genetic diversity and facilitate adaptation in cattle populations. Despite their importance, the genome-wide characterization of CNVs in indigenous Ethiopian cattle breeds-Abigar, Fellata, and Gojjam-Highland remains largely unexplored. In this study, we applied a read-depth approach to whole genome sequencing (WGS) data to conduct the first comprehensive analysis of CNVs in these populations. We identified 3,893 CNV regions (CNVRs) covering 19.15Mb (0.71% of the cattle genome). These CNVRs ranged from 1.60kb to 488.0kb, with an average size of 4.92kb. These CNVRs included deletions (1713), duplications (1929), and mixed events (251) showing notable differences in distribution among the breeds. Four out of five randomly selected CNVRs were successfully validated using real time polymerase chain reaction (qPCR). Further analyses identified candidate genes associated with high-altitude adaptation (GBE1 and SOD1), heat stress adaptation (HSPA13, DNAJC18, and DNAJC8) and resistance to tick infestations (BoLA and KRT33A). In addition, variance stabilizing transformation (VST) statistics highlighted population-specific CNVRs, emphasizing the unique genetic signatures of high-altitude adaptation in the Gojjam-Highland cattle breed. Among the detected CNVRs, 4.93% (192 out of 3,893) overlapped with 520 quantitative traits loci (QTLs) associated with six economically important trait categories suggesting that these CNVRs may significantly contribute to the genetic variation underlying these traits. Our comprehensive analysis reveals significant CNVRs associated with key adaptive traits in Ethiopian cattle breeds highlighting their genetic diversity and resilience. These findings offer valuable insights into the genetic basis of adaptability and can inform sustainable breeding practices and conservation efforts. Future research should prioritize the functional validation of these CNVRs and their integration into breeding programs to enhance traits such as disease resistance and environmental adaptability.

Mutant prevention concentrations, in vitro resistance evolution dynamics, and mechanisms of resistance to imipenem and imipenem/relebactam in carbapenem-susceptible Klebsiella pneumoniae isolates showing ceftazidime/avibactam resistance.

Klebsiella pneumoniae carbapenemase (KPC) variants selected during ceftazidime/avibactam treatment usually develop susceptibility to carbapenems and carbapenem/β-lactamase inhibitors, such as imipenem and imipenem/relebactam. We analyzed imipenem and imipenem/relebactam single-step mutant frequencies, resistance development trajectories and differentially selected resistance mechanisms using two representative K. pneumoniae isolates that had developed ceftazidime/avibactam resistance during therapy (ST512/KPC-31 and ST258/KPC-35). Mutant frequencies and mutant prevention concentrations were measured in Mueller-Hinton agar plates containing incremental concentrations of imipenem or imipenem/relebactam. Resistance dynamics were determined after incubation for 7 days in 10 mL MH tubes containing incremental concentrations of each antibiotic or combination, up to 64 times their baseline MIC. Two colonies per strain from each experiment were characterized by antimicrobial susceptibility testing and whole genome sequencing. The impact of KPC variants identified in resistant mutants on β-lactam resistance was investigated by cloning experiments. Imipenem/relebactam suppressed the emergence of resistant mutants at lower concentrations than imipenem, slowed down resistance development for both strains, and the resulting mutants yielded lower MICs of carbapenems and carbapenem/β-lactamase inhibitors than those selected with imipenem alone. Characterization of resistant mutants revealed that imipenem resistance was mainly caused by inactivation of OmpK36 and mutations in the KPC β-lactamase. Imipenem/relebactam-resistant mutants also maintained OmpK36 alterations, but mutations in KPC were much less frequent compared with those selected with imipenem alone. Genetic and biochemical characterization of the KPC derivatives identified in the resistant mutants confirmed their role in carbapenem resistance. Our data positions imipenem/relebactam as an attractive therapeutic option for combating ceftazidime/avibactam-resistant KPC-producing K. pneumoniae infections.

The chloroplast genome of Cephalanthera nanchuanica (Orchidaceae): comparative and phylogenetic analysis with other Neottieae species.

Cephalanthera nanchuanica is a terrestrial orchid species and has been red listed as a second-grade protected plant due to its limited distributions in China. Initially classified within a monotypicgenus Tangtsinia, this species was later reassigned to Cephalanthera based on morphological and molecular data. However, previous phylogenetic analyses of Cephalanthera using several segment sequences exhibited alow discriminatory power in delineating its relationships. In this study, we characterized and comparatively analyzed the complete chloroplast (cp) genome of C. nanchuanica with those of six previously reported Cephalanthera species. Our findings revealed that the cp genome of C. nanchuanica had the typical quadripartite structure, with a size of 161,365bp and a GC content of 37.27%. A total of 113 unique genes were annotated, among which nearly half of protein-encoding genes (RSCU > 1) showed a preference in codon usage. No structural rearrangements were observed among the cp genomes of Cephalanthera species, except for C. humilis, which displayed structural alterations due to gene loss, relocation, and inverted repeat (IR) expansion/contraction. The cp genomes of Cephalanthera species were highly conserved, with only a small number of SSRs detected, most of which preferred A/T bases. Comparative analysis of cp genomes indicated that IR and coding regions were less divergent than single copy and non-coding regions and eight mutational hotspots were identified. Phylogenetic analysis suggested that the tribe Neottieae was a monophyletic group, divided into five clades. Palmorchis was the earliest-diverging lineage, followed by Cephalanthera. Diplandrorchis was deeply nested within Neottia, forming a clade. Aphyllorchis and Limodorum formed another clade, sister to Epipactis. Within the Cephalanthera clade, C. nanchuanica was sister to C. falcata with astrong support. This study demonstrated that the cp genome characters of C. nanchuanica are highly similar to those of other Cephalanthera species, except for the mycoheterotrophic species C. humilis. Although the cp genomes of Cephalanthera species (excluding C. humilis) exhibited conservation in genome structure and sequence, SSR repeats and mutational hotspots were identified, which could potentially serve as as molecular markers for distinguishing Cephalanthera species. The phylogenetic analysis based on the protein-coding genes provided high-resolution support for the infrageneric classification. Therefore, cp genome data will be instrumental in resolving the phylogeny of the genus Cephalanthera.

Description of genome sequences of arthropod-associated spirochetes of the genus Entomospira.

Spirochetal bacteria isolated from arthropods of the genera Culex and Aedes are termed BR149, BR151 (Entomospira culicis), BR193 (Entomospira entomophila), and BR208 (Entomospira nematocerorum). Genome sizes assembled from Illumina MiSeq and Oxford Nanopore reads varied between 1.67 and 1.78 Mb containing three to six plasmids. GC content ranged from 38.5% to 45.76%.

Rapid detection of the SARS-CoV-2 omicron variants based on high-resolution melting curve analysis.

With the continuous spread of the SARS-CoV-2 globally, viral mutations have accumulated. As a result, SARS-CoV-2 became more contagious, and has a higher risk of immune escape and reinfection. To identify variants and have an awareness of the prevalence of these variants, this study selected four segments containing mutations on the S gene of the SARS-CoV-2. Then a rapid and convenient variants detection method was established using high-resolution melting(HRM) analysis combined with nested polymerase chain reaction(PCR). The total detection process takes about 5h. Through comprehensive analysis of the results from the four reaction systems, the identification of seven important Omicron variants(BA.2, BA.2.75, BA.5.2, BF.7, BQ.1, XBB.1 and XBB.2) can be achieved, with significant differentiation in the melting curves of each variant group. The method established in this study was used to genotype positive specimens in COVID-19 nucleic acid testing, the overall concordance rate compared to whole genome sequencing results was 88.9%, and the positive concordance rate of each sublineage was greater than 80% and the negative concordance rate was greater than 94.4%. The detection of clinical specimens has demonstrated that the HRM analysis established in this study is an effective, rapid and convenient variant identification method, which can be used for monitoring SARS-CoV-2 variants and has important value in addressing public health issues caused by the ongoing mutations of the SARS-CoV-2.

The Genomic SSR Millets Database (GSMDB): enhancing genetic resources for sustainable agriculture.

The global population surge demands increased food production and nutrient-rich options to combat rising food insecurity. Climate-resilient crops are vital, with millets emerging as superfoods due to nutritional richness and stress tolerance. Given limited genomic information, a comprehensive genetic resource is crucial to advance millet research. Whole-genome sequencing provides an unprecedented opportunity, and molecular genetic methodologies, particularly simple sequence repeats (SSRs), play a pivotal role in DNA fingerprinting, constructing linkage maps, and conducting population genetic studies. SSRs are composed of repetitive DNA sequences where one to six nucleotides are repeated in tandem and distributed throughout the genome. Different millet species exhibit genomic variations attributed to the presence of SSRs. While SSRs have been identified in a few millet species, the existing information only covers some of the sequenced genomes. Moreover, there is an absence of complete gene annotation and visualization features for SSRs. Addressing this disparity and leveraging the de-novo millet genome assembly available from the NCBI, we have developed the Genomic SSR Millets Database (GSMDB; https://bioinfo.icgeb.res.in/gsmdb/). This open-access repository provides a web-based tool offering search functionalities and comprehensive details on 6.747645 million SSRs mined from the genomic sequences of seven millet species. The database, featuring unrestricted public access and JBrowse visualization, is a pioneering resource for the research community dedicated to advancing millet cultivars and related species. GSMDB holds immense potential to support myriad studies, including genetic diversity assessments, genetic mapping, marker-assisted selection, and comparative population investigations aiming to facilitate the millet breeding programs geared toward ensuring global food security. Database URL: https://bioinfo.icgeb.res.in/gsmdb/.

Putative evolution of Myxococcus fulvus 124B02 plasmid pMF1 from a chromosomal segment in another Myxococcus species.

Myxobacteria or order Myxococcales (old nomenclature) or phylum Myxococcota (new terminology) are fascinating organisms well known for their diverse peculiar physiological, taxonomic, and genomic properties. Researchers have long sought to identify plasmids within these organisms, yet thus far, only two organisms from different families have been found to harbor a plasmid. This study delves into the putative evolution of one of these plasmids, i.e., pMF1 present in Myxococcus fulvus 124B02 in the suborder Cystobacterineae and family Myxococcaceae. Here, we first reannotated the pMF1 plasmid genome sequence and identified two additional open reading frames or putative genes which were not annotated until now. We further reported that all pMF1 plasmid genes depict homology with Myxococcus stipitatus CYD1 draft genome (contig 28) and a chromosomal segment of M. stipitatus DSM14675 in a syntenic manner, implying the presence of plasmid-like structure in M. stipitatus CYD1, integrated into its chromosome. To comprehend the relationship among these three species, we conducted phylogenetic analyses using 16S and concatenated housekeeping genes and genome-to-genome distance calculator (GGDC) analysis, which confirmed that M. stipitatus CYD1 is a distinct and novel species within the genus Myxococcus. Overall, this comparative genomic study sheds light on the putative emergence of the pMF1 plasmid from a common ancestor of closely related yet distinct species, M. stipitatus CYD1, possibly through the partition from its chromosome as a segment.IMPORTANCEMyxobacteria are not well known to have plasmids. Until now, only two organisms have been shown to have plasmids, raising a pertinent question about how these plasmids evolved randomly within the phylum Myxococcota. The study presented in this manuscript delves into the emergence of the pMF1 plasmid found in Myxococcus fulvus 124B02, a member of the suborder Cystobacterineae and family Myxococcaceae. Our research addresses this intriguing topic of plasmid identification and evolution within myxobacteria, which are a group of fascinating organisms that have garnered significant interest due to their diverse physiological, taxonomic, and genomic properties.

PSATdb 2.0: a database of organellar common, polymorphic, and unique microsatellites.

Microsatellites, or simple sequence repeats (SSRs), are repetitive DNA sequences typically composed of 1-6 nucleotides. These repetitive sequences are found in almost all genomes, including chloroplasts and mitochondria, and are widely distributed throughout the genomes. Microsatellites are highly polymorphic, and their length may differ from species to species. Consequently, microsatellites are widely used as molecular markers and play pivotal roles in various biological research. However, comprehensive information about the length variation of microsatellites in various organellar genome sequences is not available. Therefore, to provide mined information and explore the variability in the length of microsatellites across species, we developed a comprehensive resource named pSATdb 2.0 (polymorphic microSATellites database; https://bioinfo.icgeb.res.in/psatdb/ ). This upgraded version of its predecessor pSATdb provides comprehensive information on the frequency and distribution of 348,894 microsatellites identified in organellar genome sequences. These sequences originate from 15,681 organisms spanning 3252 genera within Metazoa and Viridiplantae. Remarkably, pSATdb 2.0 is the only database that offers information on common and polymorphic microsatellites detected between organisms, along with unique microsatellites specific to each genus. Furthermore, this database features unrestricted access and includes pioneer functionalities such as Advanced Search, BLAST, and JBrowse, which facilitate user-specific microsatellite search and its visualization within the database. The pSATdb holds immense potential for the research community to support diverse studies, including genetic diversity, genetic mapping, marker-assisted selection, and comparative population investigations.

Delineating bacterial genera based on gene content analysis: a case study of the Mycoplasmatales-Entomoplasmatales clade within the class Mollicutes.

Genome-based analysis allows for large-scale classification of diverse bacteria and has been widely adopted for delineating species. Unfortunately, for higher taxonomic ranks such as genus, establishing a generally accepted approach based on genome analysis is challenging. While core-genome phylogenies depict the evolutionary relationships among species, determining the correspondence between clades and genera may not be straightforward. For genotypic divergence, the percentage of conserved proteins and genome-wide average amino acid identity are commonly used, but often do not provide a clear threshold for classification. In this work, we investigated the utility of global comparisons and data visualization in identifying clusters of species based on their overall gene content and rationalized that such patterns can be integrated with phylogeny and other information such as phenotypes for improving taxonomy. As a proof of concept, we selected 177 representative genome sequences from the Mycoplasmatales-Entomoplasmatales clade within the class Mollicutes for a case study. We found that the clustering patterns corresponded to the current understanding of these organisms, namely the split into three above-genus groups: Hominis, Pneumoniae and Spiroplasma-Entomoplasmataceae-Mycoides. However, at the genus level, several important issues were found. For example, recent taxonomic revisions that split the Hominis group into three genera and Entomoplasmataceae into five genera are problematic, as those newly described or emended genera lack clear differentiations in gene content from one another. Moreover, several cases of misclassification were identified. These findings demonstrated the utility of this approach and its potential application to other bacteria.

Neural network-based predictions of antimicrobial resistance phenotypes in multidrug-resistant Acinetobacter baumannii from whole genome sequencing and gene expression.

Whole genome sequencing (WGS) potentially represents a rapid approach for antimicrobial resistance genotype-to-phenotype prediction. However, the challenge still exists to predict fully minimum inhibitory concentrations (MICs) and antimicrobial susceptibility phenotypes based on WGS data. This study aimed to establish an artificial intelligence-based computational approach in predicting antimicrobial susceptibilities of multidrug-resistant Acinetobacter baumannii from WGS and gene expression data. Antimicrobial susceptibility testing (AST) was performed using the broth microdilution method for 10 antimicrobial agents. In silico multilocus sequence typing (MLST), antimicrobial resistance genes, and phylogeny based on cgSNP and cgMLST strategies were analyzed. High-throughput qPCR was performed to measure the expression level of antimicrobial resistance (AMR) genes. Most isolates exhibited a high level of resistance to most of the tested antimicrobial agents, with the majority belonging to the IC2/CC92 lineage. Phylogenetic analysis revealed undetected transmission events or local outbreaks. The percentage agreements between AMR phenotype and genotype ranged from 70.08% to 89.96%, with the coefficient of agreement (κ) extending from 0.025 and 0.881. The prediction of AST employed by deep neural network models achieved an accuracy of up to 98.64% on the testing data set. Additionally, several linear regression models demonstrated high prediction accuracy, reaching up to 86.15% within an error range of one gradient, indicating a linear relationship between certain gene expressions and the corresponding antimicrobial MICs. In conclusion, neural network-based predictions could be used as a tool for the surveillance of antimicrobial resistance in multidrug-resistant A. baumannii.

The genome sequence of bronze sap hoverfly, Ferdinandea cuprea (Scopoli, 1763)

We present a genome assembly from an individual Ferdinandea cuprea (bronze sap hoverfly; Arthropoda; Insecta; Diptera; Syrphidae). The genome sequence has a total length of 560.20 megabases. Most of the assembly (99.92%) is scaffolded into 5 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 16.0 kilobases in length. Gene annotation of this assembly on Ensembl identified 12,662 protein-coding genes.

Discovery of Alanomyces manoharacharyi: A Novel Fungus Identified Using Genome Sequencing and Metabolomic Analysis

Discovery of Alanomyces manoharacharyi: A Novel Fungus Identified Using Genome Sequencing and Metabolomic Analysis

Genomic Surveillance of Foodborne Pathogens: Advances and Obstacles

Context: The genomic surveillance of foodborne pathogens in the United States has grown exponentially in the past decade, grounded in a powerful combination of novel sequencing technologies, bioinformatic approaches, data-sharing networks, and metadata harmonization efforts. This practice report examines recent advances in genomic epidemiology as applied to food safety programs and delineates State, Tribal, Local, and Territorial infrastructure necessary for continued life-saving improvements in public health. Program: National databases of foodborne pathogen genomes, along with data sharing and evaluation networks such as GenomeTrakr and PulseNet, have transformed how connections are made among isolates and how root causes of outbreaks are determined, allowing much more timely interventions to protect public health. Freely available bioinformatics tools such as GalaxyTrakr and the National Center for Biotechnology Information Pathogen Detection database have allowed laboratories with limited local computing resources to participate in surveillance efforts and contribute to traceback investigations. Implementation: In this report, we describe advances in genomic epidemiology that have occurred over the past decade and examine obstacles to fully implementing this technology within State, Tribal, Local, and Territorial public health systems. Evaluation: Despite a clear return on investment from governmental expenditures on genomic surveillance of foodborne pathogens, we identify significant obstacles to further sustained progress. These obstacles include workforce gaps, ineffective data sharing, and lack of constitutive and sustained funding. Discussion: Many public health laboratories face major obstacles to widespread and routine adoption of genomic surveillance technologies. While whole genome sequencing has become an integral part of routine public health microbiology, the seamless integration of these protocols into the existing practices, laboratory workflows, and information systems remains challenging. Centralized efforts to address these issues include (1) support through the Food and Drug Administration Laboratory Flexible Funding Model, (2) training and proficiency assessments, (3) open-source, standardized protocols for collecting high-quality genomic data, and (4) open access informatics software.