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In this study, a deep quantum neural network (DQNN) based on the Lion-based Coot algorithm (LBCA-based Deep QNN) is employed to predict COVID-19. Here, the genome sequences are subjected to feature extraction. The fusion of features is performed using the Bray-Curtis distance and the deep belief network (DBN). Lastly, a deep quantum neural network (Deep QNN) is used to predict COVID-19. The LBCA is obtained by integrating Coot algorithm and LOA. The COVID-19 predictions are done with mutation points. The LBCA-based Deep QNN outperformed with testing accuracy of 0.941, true positive rate of 0.931, and false positive rate of 0.869. [ABSTRACT FROM AUTHOR]

RNA genomes from coronavirus have a length as long as 32 kilobases, and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the outbreak of coronavirus disease 2019 (COVID-19) pandemic has long sequences which made the analysis difficult. Over 20,000 sequences have been submitted to GISAID, and the number is growing fast each day which increased the difficulties in data analysis; however, genome sequence analysis is critical in understanding the COVID-19 and preventing the spread of the disease. In this study, a principal component analysis (PCA) was applied to the aligned large size genome sequences and the numerical numbers were converted from the letters using a published method designed for protein sequence cluster analysis. The study initialized with a shortlist sequence testing, and the PCA score plot showed high tolerance with low-quality data, and the major virus sequences from humans were separated from the pangolin and bat samples. Our study also successfully built a model for a large number of sequences with more than 20,000 sequences which indicate the potential mutation directions for the COVID-19 which can be served as a pretreatment method for detailed studies such as decision tree-based methods. In summary, our study provided a fast tool to analyze the high-volume genome sequences such as the COVID-19 and successfully applied to more than 20,000 sequences which may provide mutation direction information for COVID-19 studies. [ABSTRACT FROM AUTHOR]

Fulvia fulva and Dothistroma septosporum are closely related apoplastic pathogens with similar lifestyles but different hosts: F. fulva is a pathogen of tomato, whilst D. septosporum is a pathogen of pine trees. In 2012, the first genome sequences of these pathogens were published, with F. fulva and D. septosporum having highly fragmented and near-complete assemblies, respectively. Since then, significant advances have been made in unravelling their genome architectures. For instance, the genome of F. fulva has now been assembled into 14 chromosomes, 13 of which have synteny with the 14 chromosomes of D. septosporum, suggesting these pathogens are even more closely related than originally thought. Considerable advances have also been made in the identification and functional characterization of virulence factors (e.g., effector proteins and secondary metabolites) from these pathogens, thereby providing new insights into how they promote host colonization or activate plant defence responses. For example, it has now been established that effector proteins from both F. fulva and D. septosporum interact with cell-surface immune receptors and co-receptors to activate the plant immune system. Progress has also been made in understanding how F. fulva and D. septosporum have evolved with their host plants, whilst intensive research into pandemics of Dothistroma needle blight in the Northern Hemisphere has shed light on the origins, migration, and genetic diversity of the global D. septosporum population. In this review, we specifically summarize advances made in our understanding of the F. fulva-tomato and D. septosporum-pine pathosystems over the last 10 years.

Abstract The SeqCode, formally called the Code of Nomenclature of Prokaryotes Described from Sequence Data, is a new code of nomenclature in which genome sequences are the nomenclatural types for the names of prokaryotic species. While similar to the International Code of Nomenclature of Prokaryotes (ICNP) in structure and rules of priority, it does not require the deposition of type strains in international culture collections. Thus, it allows for the formation of permanent names for uncultured prokaryotes whose nearly complete genome sequences have been obtained directly from environmental DNA as well as other prokaryotes that cannot be deposited in culture collections. Because the diversity of uncultured prokaryotes greatly exceeds that of readily culturable prokaryotes, the SeqCode is the only code suitable for naming the majority of prokaryotic species. The start date of the SeqCode was January 1, 2022, and the online Registry (https://seqco.de/) was created to ensure valid publication of names. The SeqCode recognizes all names validly published under the ICNP before 2022. After that date, names validly published under the SeqCode compete with ICNP names for priority. As a result, species can have only one name, either from the SeqCode or ICNP, enabling effective communication and the creation of unified taxonomies of uncultured and cultured prokaryotes. The SeqCode is administered by the SeqCode Committee, which is comprised of the SeqCode Community and elected administrative components. Anyone with an interest in the systematics of prokaryotes is encouraged to join the SeqCode Community and participate in the development of this resource.

Aim Corallococcus species are diverse in the natural environment with 10 new Corallococcus species having been characterized in just the last 5 years. As well as being an abundant myxobacterial genus, they produce several secondary metabolites, including Corallopyronin, Corramycin, Coralmycin, and Corallorazine. We isolated a novel strain Corallococcus spp RDP092CA from soil in South Wales, UK, using Candida albicans as prey bait and characterized its predatory activities against pathogenic bacteria and yeast. Methods and results The size of the RDP092CA genome was 8.5 Mb with a G + C content of 71.4%. Phylogenetically, RDP092CA is closely related to Corallococcus interemptor, C. coralloides , and C. exiguus. However, genome average nucleotide identity and digital DNA–DNA hybridization values are lower than 95% and 70% when compared to those type strains, implying that it belongs to a novel species. The RDP092CA genome harbours seven types of biosynthetic gene clusters (BGCs) and 152 predicted antimicrobial peptides. In predation assays, RDP092CA showed good predatory activity against Escherichia coli, Pseudomonas aeruginosa, Citrobacter freundii , and Staphylococcus aureus but not against Enterococcus faecalis. It also showed good antibiofilm activity against all five bacteria in biofilm assays. Antifungal activity against eight Candida spp. was variable, with particularly good activity against Meyerozyma guillermondii DSM 6381. Antimicrobial peptide RDP092CA_120 exhibited potent antibiofilm activity with >50% inhibition and >60% dispersion of biofilms at concentrations down to 1 μg/ml. Conclusions We propose that strain RDP092CA represents a novel species with promising antimicrobial activities, Corallococcus senghenyddensis sp. nov. (=NBRC 116490T =CCOS 2109T), based on morphological, biochemical, and genomic features. [ABSTRACT FROM AUTHOR]

Background: The causative agent of the COVID‐19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), is of zoonotic origin and has shown reverse zoonotic transmissibility. Objectives: The aim of this cross‐sectional study was to investigate the serological and molecular prevalence of SARS‐CoV‐2 infection in the domestic cat (Felis catus) population from Latvia in natural conditions and subsequently perform viral genome analysis. Methods: Oropharyngeal and rectal swabs and blood samples were collected from 273 domestic cats during the second wave of COVID‐19 infection in Latvia. Molecular prevalence was determined by using reverse transcriptase‐polymerase chain reaction (RT‐PCR). Serum samples were analysed via double antigen enzyme‐linked immunosorbent assay targeting the antibody against the nucleocapsid protein of SARS‐CoV‐2. Positive swab samples were analysed using whole viral genome sequencing and subsequent phylogenetic analysis of the whole genome sequencing data of the samples was performed. Results: The overall SARS‐CoV‐2 RT‐PCR positivity and seroprevalence was 1.1% (3/273) and 2.6% (7/273), respectively. The SARS‐CoV‐2 genome sequences from three RT‐PCR positive cats were assigned to the three common lineages (PANGOLIN lineage S.1.; B.1.177.60. and B.1.1.7.) circulating in Latvia during the particular period of time. Conclusions: These findings indicate that feline infection with SARS‐CoV‐2 occurred during the second wave of the COVID‐19 pandemic in Latvia, yet the overall prevalence was low. In addition, it seems like no special 'cat' pre‐adaptations were necessary for successful infection of cats by the common lineages of SARS‐CoV‐2. [ABSTRACT FROM AUTHOR]

SARS-CoV-2, also known as COVID-2019, is spreading quickly and threatening our society on a global scale. Every government is employing money, infrastructure, data security equipment, survival evaluations, treatments, and other resources to make major attempts to stop the fatal disease from spreading. Nationwide, COVID-19 sepsis infections are spreading quickly. To allocate resources and classify patients in order to avert death, a reliable and accessible clinical assessment of the severity of human illness is essential. Through the analysis of genome and protein sequences, the study seeks to confirm an early stage of sickness by estimating the likelihood of further alterations depending on their length. A study involving 852 isolates of the COVID-19 Next strain application was conducted. The project included a dashboard showing the distribution and percentages of gene mutations for each base sequence in the genomic data, a transmission chart, and a visual phylogenetic analysis. Additionally, it took basic traits from genetic alterations that might help anticipate more mutations in the future. For 11191 patients, survival analysis parameters were found. [ABSTRACT FROM AUTHOR]

Millets are small-seeded cereals belonging to the family Poaceae. They are considered to be climate-resilient and future nutritional food cereals for humans. Millets are resistant to biotic and abiotic stressors compared to other major cereals and thrive in low-quality soils with little maintenance and less rainfall. The importance of millets is still not well known to many people due to the lack of popularity and cultivation in semi-arid tropics of Asia and Africa. The United Nations has declared 2023 as the International Year of Millets (IYM 2023) to promote millet cultivation and popularize their health benefits globally. A few years ago, the application of molecular biology was in its infancy in millets due to the unavailability of genome sequences. Genome sequences are available for most of the millets on NCBI and Phytozome databases. In this review, we discuss the details of genome sequences for millets, candidate genes identified from the native genome of millets. The current status of quantitative trait loci and genome-wide association studies in millets are also discussed. The utilization of millet genome sequences in functional genomics research and translating the information for crop improvement will help millet and non-millet cereals survive harsh environments in the future. Such efforts will help strengthen food security and reduce malnutrition worldwide in 2050. [ABSTRACT FROM AUTHOR]

Feature extraction is essential in bioinformatics because it transforms genomics sequences into feature vectors, which are needed for clustering to discover the family of newly sequenced genome. Most of the existing feature extraction methods extract similar features for dissimilar sequences, do not extract context-based features and unable to handle millions of genome sequences because they are not scalable. So, to tackle these challenges, we proposed an efficient apache spark-based scalable feature extraction approach that extracts significantly important features from millions of genome sequences in less computational time. The proposed approach extracts features in five stages, i.e., based on the length of the sequence, the frequency of nucleotide bases, the pattern organization of nucleotide bases, distribution of nucleotide bases, and the entropy of the sequence to generate a fixed-length numeric vector consist of only 14 dimensions to describe each genome sequence uniquely. The proposed approach efficiently extracts the context-based features in terms of pattern organization and distribution, also removes the drawback of extracting same features for the dissimilar sequences using a novel power method. The feature extracted with the proposed scalable feature extraction approach is applied on k-means and fuzzy c-means clustering techniques. The experimental results show that the proposed method is highly successful and efficient in terms of computing time in comparison to other state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Abstract Background The causative agent of the COVID‐19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), is of zoonotic origin and has shown reverse zoonotic transmissibility. Objectives The aim of this cross‐sectional study was to investigate the serological and molecular prevalence of SARS‐CoV‐2 infection in the domestic cat (Felis catus) population from Latvia in natural conditions and subsequently perform viral genome analysis. Methods Oropharyngeal and rectal swabs and blood samples were collected from 273 domestic cats during the second wave of COVID‐19 infection in Latvia. Molecular prevalence was determined by using reverse transcriptase‐polymerase chain reaction (RT‐PCR). Serum samples were analysed via double antigen enzyme‐linked immunosorbent assay targeting the antibody against the nucleocapsid protein of SARS‐CoV‐2. Positive swab samples were analysed using whole viral genome sequencing and subsequent phylogenetic analysis of the whole genome sequencing data of the samples was performed. Results The overall SARS‐CoV‐2 RT‐PCR positivity and seroprevalence was 1.1% (3/273) and 2.6% (7/273), respectively. The SARS‐CoV‐2 genome sequences from three RT‐PCR positive cats were assigned to the three common lineages (PANGOLIN lineage S.1.; B.1.177.60. and B.1.1.7.) circulating in Latvia during the particular period of time. Conclusions These findings indicate that feline infection with SARS‐CoV‐2 occurred during the second wave of the COVID‐19 pandemic in Latvia, yet the overall prevalence was low. In addition, it seems like no special ‘cat’ pre‐adaptations were necessary for successful infection of cats by the common lineages of SARS‐CoV‐2.

Serratia marcescens is an opportunistic and nosocomial pathogen found in the intensive care unit (ICU), but its antimicrobial resistance (AMR) is rarely addressed. Here, we reported two blaKPC-2-positive S. marcescens strains, SMBC31 and SMBC50, recovered from the ICU of a hospital in Zhengzhou, China. The minimum inhibitory concentration (MIC) was determined using the broth microdilution method, while S1-PFGE was employed to demonstrate plasmid size approximation. Complete genome sequences were obtained through Illumina NovaSeq 6000 and Oxford Nanopore Technologies. Both strains exhibit resistance to meropenem and harbor the blaKPC-2 and blaSRT-1 resistance genes. The plasmid pSMBC31-39K in strain SMBC31 and pSMBC50-107K in strain SMBC50 were identified as carrying the blaKPC-2 gene. Notably, both of these plasmids were successfully transferred to Escherichia coli strain J53. Phylogenetic analysis based on plasmid sequences revealed that pSMBC31-39K exhibited high homology with plasmids found in Aeromonas caviae, Citrobacter sp., and Pseudomonas aeruginosa, while pSMBC50-107K showed significant similarity to those of E. coli and Klebsiella pneumoniae. Notably, the coexistence of blaKPC-2 and blaSRT-1 was observed in all 94 KPC-2-producing S. marcescens strains by mining all genomes available under the GenBank database, which were mainly isolated from hospitalized patients. The emergence of multidrug-resistant S. marcescens poses significant challenges in treating clinical infections, highlighting the need for increased surveillance of this pathogen.

Cryptosporidium species are a major cause of diarrhea and associated with growth failure. There is currently only limited knowledge of the parasite's genomic variability. We report a genomic analysis of Cryptosporidium parvum isolated from Bangladeshi infants and reanalysis of sequences from the United Kingdom. Human isolates from both locations shared 154 variants not present in the cattle-derived reference genome, suggesting host-specific adaptation of the parasite. Remarkably 34.6% of single-nucleotide polymorphisms unique to human isolates were nonsynonymous and 8.2% of these were in secreted proteins. Linkage disequilibrium decay indicated frequent recombination. The genetic diversity of C. parvum has potential implications for vaccine and therapeutic design. Clinical Trials Registration. NCT02764918. [ABSTRACT FROM AUTHOR]

Abstract Background Eucalyptus urophylla × Eucalyptus grandis, an economically important forest tree, provides important raw material for energy and reduces damage to native forests. However, the absence of a high-quality E. urophylla × E. grandis reference genome has significantly hindered its evolution and genetic analysis. Results We successfully presented a high-quality reference genome of E. urophylla × E. grandis (545.75 Mb; scaffold N50, 51.62 Mb) using a combination of the Illumina, PacBio HiFi, and Hi-C sequencing platforms. A total of 34,502 genes and 58.56% of the repetitive sequences in this genome were annotated. Using genome evolution analyses, we identified a recent whole-genome duplication (WGD) event in E. urophylla × E. grandis. We further found that gene families associated with starch and sucrose metabolism, flavonoid biosynthesis, and plant–pathogen interaction were significantly expanded in E. urophylla × E. grandis. Moreover, comparative genomic and evolutionary analyses showed large structural variations among the different chromosomes of the 34 Eucalyptus accessions, which were divided into six clades. Conclusions Overall, our findings provide a valuable resource for expanding our understanding of the E. urophylla × E. grandis genome evolution, genetic improvement, and its comparative biology.

Millets are small-seeded cereals belonging to the family Poaceae. They are considered to be climate-resilient and future nutritional food cereals for humans. Millets are resistant to biotic and abiotic stressors compared to other major cereals and thrive in low-quality soils with little maintenance and less rainfall. The importance of millets is still not well known to many people due to the lack of popularity and cultivation in semi-arid tropics of Asia and Africa. The United Nations has declared 2023 as the International Year of Millets (IYM 2023) to promote millet cultivation and popularize their health benefits globally. A few years ago, the application of molecular biology was in its infancy in millets due to the unavailability of genome sequences. Genome sequences are available for most of the millets on NCBI and Phytozome databases. In this review, we discuss the details of genome sequences for millets, candidate genes identified from the native genome of millets. The current status of quantitative trait loci and genome-wide association studies in millets are also discussed. The utilization of millet genome sequences in functional genomics research and translating the information for crop improvement will help millet and non-millet cereals survive harsh environments in the future. Such efforts will help strengthen food security and reduce malnutrition worldwide in 2050.

Coronavirus (CoV) disease 2019 (COVID-19) is a severe pandemic affecting millions worldwide. Due to its rapid evolution, researchers have been working on developing diagnostic approaches to suppress its spread. This study presents an effective automated approach based on genomic image processing (GIP) techniques to rapidly detect COVID-19, among other human CoV diseases, with high acceptable accuracy. The GIP technique was applied as follows: first, genomic graphical mapping techniques were used to convert the genome sequences into genomic grayscale images. The frequency chaos game representation (FCGR) and single gray-level representation (SGLR) techniques were used in this investigation. Then, several statistical features were obtained from the images to train and test many classifiers, including the k-nearest neighbors (KNN). This study aimed to determine the efficacy of the FCGR (with different orders) and SGLR images for accurately detecting COVID-19, using a dataset containing both partial and complete genome sequences. The results recommended the fourth-order FCGR image as a proper genomic image for extracting statistical features and achieving accurate classification. Furthermore, the results showed that KNN achieved an overall accuracy of 99.39% in detecting COVID-19, among other human CoV diseases, with 99.48% precision, 99.31% sensitivity, 99.47% specificity, 0.99 F1-score, and 0.99 Matthew's correlation coefficient.

Background: Eucalyptus urophylla × Eucalyptus grandis, an economically important forest tree, provides important raw material for energy and reduces damage to native forests. However, the absence of a high-quality E. urophylla × E. grandis reference genome has significantly hindered its evolution and genetic analysis. Results: We successfully presented a high-quality reference genome of E. urophylla × E. grandis (545.75 Mb; scaffold N50, 51.62 Mb) using a combination of the Illumina, PacBio HiFi, and Hi-C sequencing platforms. A total of 34,502 genes and 58.56% of the repetitive sequences in this genome were annotated. Using genome evolution analyses, we identified a recent whole-genome duplication (WGD) event in E. urophylla × E. grandis. We further found that gene families associated with starch and sucrose metabolism, flavonoid biosynthesis, and plant–pathogen interaction were significantly expanded in E. urophylla × E. grandis. Moreover, comparative genomic and evolutionary analyses showed large structural variations among the different chromosomes of the 34 Eucalyptus accessions, which were divided into six clades. Conclusions: Overall, our findings provide a valuable resource for expanding our understanding of the E. urophylla × E. grandis genome evolution, genetic improvement, and its comparative biology. [ABSTRACT FROM AUTHOR]

S. pneumoniae is a multidrug-resistant bacterium that causes life-threatening infections in humans. 5482291, an active compound that targets the RuvB protein, will be especially useful in overcoming the negative effects of infection. This study presents a rigorous in silico docking research, demonstrating that 5482291 is an active chemical with the lowest binding energy to the designated RuvB protein. Further research into the thermodynamics, solubility pharmacokinetics pharmacodynamics may be able to reduce the organism’s harmful activity. [ABSTRACT FROM AUTHOR]

Abstract Background Biological sequences are increasing rapidly and exponentially worldwide. Nucleotide sequence databases play an important role in providing meaningful genomic information on a variety of biological organisms. Results The getSequenceInfo software tool allows to access sequence information from various public repositories (GenBank, RefSeq, and the European Nucleotide Archive), and is compatible with different operating systems (Linux, MacOS, and Microsoft Windows) in a programmatic way (command line) or as a graphical user interface. getSequenceInfo or gSeqI v1.0 should help users to get some information on queried sequences that could be useful for specific studies (e.g. the country of origin/isolation or the release date of queried sequences). Queries can be made to retrieve sequence data based on a given kingdom and species, or from a given date. This program allows the separation between chromosomes and plasmids (or other genetic elements/components) by arranging each component in a given folder. Some basic statistics are also performed by the program (such as the calculation of GC content for queried assemblies). An empirically designed nucleotide ratio is calculated using nucleotide information in order to tentatively provide a “NucleScore” for studied genome assemblies. Besides the main gSeqI tool, other additional tools have been developed to perform various tasks related to sequence analysis. Conclusion The aim of this study is to democratize the use of public repositories in programmatic ways, and to facilitate sequence data analysis in a pedagogical perspective. Output results are available in FASTA, FASTQ, Excel/TSV or HTML formats. The program is freely available at: https://github.com/karubiotools/getSequenceInfo . getSequenceInfo and supplementary tools are partly available through the recently released Galaxy KaruBioNet platform ( http://calamar.univ-ag.fr/c3i/galaxy_karubionet.html ).

Coronavirus (CoV) disease 2019 (COVID-19) is a severe pandemic affecting millions worldwide. Due to its rapid evolution, researchers have been working on developing diagnostic approaches to suppress its spread. This study presents an effective automated approach based on genomic image processing (GIP) techniques to rapidly detect COVID-19, among other human CoV diseases, with high acceptable accuracy. The GIP technique was applied as follows: first, genomic graphical mapping techniques were used to convert the genome sequences into genomic grayscale images. The frequency chaos game representation (FCGR) and single gray-level representation (SGLR) techniques were used in this investigation. Then, several statistical features were obtained from the images to train and test many classifiers, including the k-nearest neighbors (KNN). This study aimed to determine the efficacy of the FCGR (with different orders) and SGLR images for accurately detecting COVID-19, using a dataset containing both partial and complete genome sequences. The results recommended the fourth-order FCGR image as a proper genomic image for extracting statistical features and achieving accurate classification. Furthermore, the results showed that KNN achieved an overall accuracy of 99.39% in detecting COVID-19, among other human CoV diseases, with 99.48% precision, 99.31% sensitivity, 99.47% specificity, 0.99 F 1 -score, and 0.99 Matthew's correlation coefficient. [ABSTRACT FROM AUTHOR]

We have sequenced the chloroplast genome of red spruce (Picea rubens) for the first time using the single-end, short-reads (44 bp) Illumina sequences, assembled and functionally annotated it, and identified simple sequence repeats (SSRs). The contigs were assembled using SOAPdenovo2 following the retrieval of chloroplast genome sequences using the black spruce (Picea mariana) chloroplast genome as the reference. The assembled genome length was 122,115 bp (gaps included). Comparatively, the P. rubens chloroplast genome reported here may be considered a near-complete draft. Global genome alignment and phylogenetic analysis based on the whole chloroplast genome sequences of Picea rubens and 10 other Picea species revealed high sequence synteny and conservation among 11 Picea species and phylogenetic relationships consistent with their known classical interrelationships and published molecular phylogeny. The P. rubens chloroplast genome sequence showed the highest similarity with that of P. mariana and the lowest with that of P. sitchensis. We have annotated 107 genes including 69 protein-coding genes, 28 tRNAs, 4 rRNAs, few pseudogenes, identified 42 SSRs, and successfully designed primers for 26 SSRs. Mononucleotide A/T repeats were the most common followed by dinucleotide AT repeats. A similar pattern of microsatellite repeats occurrence was found in the chloroplast genomes of 11 Picea species. [ABSTRACT FROM AUTHOR]

With the rapid development of sequencing technologies, followed by the reduction of sequencing cost, numerous ornamental plants have been sequenced, resulting in their genomic studies shifting from gene cloning and marker development to whole genome profiling. A profound understanding of genome structure and function at the whole genome level can not only help to modify ornamental traits, such as fragrance, color and flower shape, through genetic engineering, but also infer the genetic relationship and evolutionary history of ornamental plants via comparative genomics analysis. In this paper, we review the current situation of sequencing strategies and the application of genomics to study the origin and evolution of ornamental plants. We highlight challenges of ornamental plant genomic research. The use of cutting-edge technologies, such as genomics, gene editing and molecular design polymerization breeding, can facilitate our understanding of genetic regulation mechanisms and the germplasm innovation of important traits in ornamental plants. The results can be expected to significantly increase the breeding efficiency of ornamental plants.

In the Northeast of Brazil, Ceará was the second state most impacted by COVID-19 in number of cases and death rate. Despite that, the early dynamics of the pandemic in Ceará was not yet well understood due the low genomic surveillance of SARS-CoV-2 in 2020. In this study, we analyze the circulating lineages and the genomic variation of the virus in Ceará state. Thirty-four genomes were sequenced and combined with sequences available in GISAID database from March 2020 to June 2021 to compose the study dataset. The most prevalent lineages detected were B.1.1.33, in 2020, and P.1, in 2021. Other lineages were found, such as P.2, sublineages of P.1, B.1, B.1.1, B.1.1.28 and B.1.212. Analyzing the mutations, a total of 202 single-nucleotide polymorphisms (SNPs) were identified among the 34 genomes sequenced, of which 127 were missense, 74 synonymous, and one was a nonsense mutation. Among the missense mutations, C14408T, A23403G, T27299C, G28881A G28883C, and T29148C were the most prevalent within the dataset. Although SARS-CoV-2 sequencing data was limited in 2020, our results could provide insights to better understand the genetic diversity of the circulating lineages in Ceará.

Antimicrobial resistance (AMR) may lead to worldwide epidemics through human activities and natural transmission, posing a global public safety threat. Colistin resistance mediated by the mcr-1 gene is the most prevalent among animal-derived Escherichia coli, and mcr-1-carrying E. coli have been frequently detected in central-eastern China. However, animal-derived E. coli with AMR and the prevalence of mcr-1 in the Qinghai Plateau have been rarely investigated. Herein, 375 stool samples were collected from 13 poultry farms in Qinghai Province and 346 E. coli strains were isolated, of which eight carried mcr-1. The AMR rates of the E. coli strains to ampicillin, amoxicillin/clavulanic acid, and tetracycline were all above 90%, and the resistance rates to ciprofloxacin, cefotaxime, ceftiofur, and florfenicol were above 70%. Multidrug-resistant strains accounted for 95.66% of the total isolates. Twelve E. coli strains showed colistin resistance, from which a total of 46 AMR genes and 36 virulence factors were identified through whole-genome sequencing. The mcr-1 gene resided on the IncHI2, IncI2-type and IncY-type plasmids, and mcr-1 was located in the nikA-nikB-mcr-1-pap2 gene cassette (three strains) or the pap2-mcr-1-ISApl1 structure (one strain). Completed IncI2-type plasmid pMCR4D31-3 sequence (62,259 bp) revealed that it may cause the horizontal transmission of mcr-1 and may increase the risk of its spread through the food chain. Taken together, the AMR of chicken-derived E. coli in the plateau is of concern, suggesting that it is very necessary for us to strengthen the surveillance in various regions under the background of one health. [ABSTRACT FROM AUTHOR]

Background: Biological sequences are increasing rapidly and exponentially worldwide. Nucleotide sequence databases play an important role in providing meaningful genomic information on a variety of biological organisms. Results: The getSequenceInfo software tool allows to access sequence information from various public repositories (GenBank, RefSeq, and the European Nucleotide Archive), and is compatible with different operating systems (Linux, MacOS, and Microsoft Windows) in a programmatic way (command line) or as a graphical user interface. getSequenceInfo or gSeqI v1.0 should help users to get some information on queried sequences that could be useful for specific studies (e.g. the country of origin/isolation or the release date of queried sequences). Queries can be made to retrieve sequence data based on a given kingdom and species, or from a given date. This program allows the separation between chromosomes and plasmids (or other genetic elements/components) by arranging each component in a given folder. Some basic statistics are also performed by the program (such as the calculation of GC content for queried assemblies). An empirically designed nucleotide ratio is calculated using nucleotide information in order to tentatively provide a "NucleScore" for studied genome assemblies. Besides the main gSeqI tool, other additional tools have been developed to perform various tasks related to sequence analysis. Conclusion: The aim of this study is to democratize the use of public repositories in programmatic ways, and to facilitate sequence data analysis in a pedagogical perspective. Output results are available in FASTA, FASTQ, Excel/TSV or HTML formats. The program is freely available at: https://github.com/karubiotools/getSequenceInfo. getSequenceInfo and supplementary tools are partly available through the recently released Galaxy KaruBioNet platform (http://calamar.univ-ag.fr/c3i/galaxy_karubionet.html). [ABSTRACT FROM AUTHOR]

Influenza is a disease that represents both a public health and agricultural risk with pandemic potential. Among the subtypes of influenza A virus, H3 influenza virus can infect many avian and mammalian species and is therefore a virus of interest to human and veterinary public health. The primary goal of this study was to train and validate classifiers for the identification of the most likely host species using the hemagglutinin gene segment of H3 viruses. A five-step process was implemented, which included training four machine learning classifiers, testing the classifiers on the validation dataset, and further exploration of the best-performing model on three additional datasets. The gradient boosting machine classifier showed the highest host-classification accuracy with a 98.0 % (95 % CI [97.01, 98.73]) correct classification rate on an independent validation dataset. The classifications were further analyzed using the predicted probability score which highlighted sequences of particular interest. These sequences were both correctly and incorrectly classified sequences that showed considerable predicted probability for multiple hosts. This showed the potential of using these classifiers for rapid sequence classification and highlighting sequences of interest. Additionally, the classifiers were tested on a separate swine dataset composed of H3N2 sequences from 1998 to 2003 from the United States of America, and a separate canine dataset composed of canine H3N2 sequences of avian origin. These two datasets were utilized to look at the applications of predicted probability and host convergence over time. Lastly, the classifiers were used on an independent dataset of environmental sequences to explore the host identification of environmental sequences. The results of these classifiers show the potential for machine learning to be used as a host identification technique for viruses of unknown origin on a species-specific level. • Gradient boosting machine classifier was successfully implemented to be able to identify seven hosts associated with H3 influenza virus genomes with 98.0% accuracy using the HA sequence. • The predicted probabilities associated with HA sequences were used to assess the host change over time on two case studies. A swine H3N2 triple reassortant dataset (data from 1998 to 2003) and a canine H3N2 dataset of avian origin. • The classifiers were used to identify the hosts of environmental sequences with unknown hosts. [ABSTRACT FROM AUTHOR]

Bacteriophages are gaining increasing interest as antimicrobial tools, largely due to the emergence of multi-antibiotic–resistant bacteria. Although their huge diversity and virulence make them particularly attractive for targeting a wide range of bacterial pathogens, it is difficult to select suitable phages due to their high specificity which limits their host range. In addition, other challenges remain such as structural fragility under certain environmental conditions, immunogenicity of phage therapy, or development of bacterial resistance. The use of genetically engineered phages may reduce characteristics that hinder prophylactic and therapeutic applications of phages. Nowadays, there is no systematic method to modify a given phage genome conferring its sought characteristics. We explore the use of artificial intelligence for this purpose as it has the potential to both guide and accelerate genome modification to generate phage variants with unique properties that overcome the limitations of natural phages. We propose an original architecture composed of two deep learning–driven components: a phage–bacterium interaction predictor and a phage genome-sequence generator. The former is a multi-branch 1-D convolutional neural network (1D-CNN) that analyses phage and bacterial genomes to predict interactions. The latter is a recurrent neural network, more particularly a long short-term memory (LSTM), that performs genomic modifications to a phage to offer substantial host range improvement. For this component, we developed two different architectures composed of one or two stacked LSTM layers with 256 neurons each. These generators are used to modify, more precisely to rewrite, the genome sequence of 42 selected phages, while the predictor is used to estimate the host range of the modified bacteriophages across 46 strains of Pseudomonas aeruginosa. The proposed generators, trained with an average accuracy of 96.1%, are able to improve the host range for an average of 18 phages among the 42 under study, increasing both their average host range, by 73.0 and 103.7%, and the maximum host ranges from 21 to 24 and 29, respectively. These promising results showed that the use of deep learning methodologies allows genetic modification of phages to extend, for instance, their host range, confirming the potential of these approaches to guide bacteriophage engineering.

Abstract Genome sequence regulates the life of all living organisms on earth. Genetic diseases cause genomic disorders and therefore early prediction of severe genetic diseases is quite possible by Genome sequence analysis. Genomic disorders refer to the mutation that is rearrangement of bases in the Genome of an organism. Genome sequence analysis and mutation identification can help to classify the diseased genome which can be accomplished using Machine Learning techniques. Feature Extraction plays a crucial role in classification as it is used to convert the Genome sequences into a set of quantitative values. In this article, we propose a novel feature extraction technique called Frequency based Feature Extraction Technique which extracts 120 features from genome sequences for classification. In the current scenario, COVID-19 is the pandemic disease and Corona virus is the source of this disease. So, in this research work, we tested the proposed feature extraction technique with 1000 samples of Genome sequences of Corona virus affected patients across the world. The extracted features were classified using both Machine Learning and Deep Learning techniques. From the results, it is evident that the proposed feature extraction technique performs well with Convolutional Neural Network classifier giving an accuracy of 97.96%. The proposed technique also helps to find the most repeat patterns in the genome sequences. It is discovered that the pattern “TTGTT” is the most repeat pattern in COVID-19 genome.

Campylobacter jejuni subsp. jejuni is a leading bacterial cause of human gastroenteritis. C. jejuni strain P4549 was isolated from an asymptomatic rhesus monkey, Macaca mulatta . We report the genome sequences have a circular chromosome of 1,729,940 bp and two plasmids of 50,482 bp and 7,259 bp, respectively., Competing Interests: The authors declare no conflict of interest.

Staphylococcus aureus (S. aureus) is a frequent cause of eye infections with some isolates exhibiting increased antimicrobial resistance to commonly prescribed antibiotics. The increasing resistance of ocular S. aureus to ciprofloxacin is a serious concern as it is a commonly used as a first line antibiotic to treat S. aureus keratitis. This study aimed to analyse genetic mutations in the genomes of 25 S. aureus isolates from infections or non-infectious ocular conditions from the USA and Australia and their relationship to ciprofloxacin resistance. Overall, 14/25 isolates were phenotypically resistant to ciprofloxacin. All isolates were analyzed for mutations in their quinolone resistance-determining regions (QRDRs) and efflux pump genes. Of the fourteen resistant isolates, 9/14 had ciprofloxacin resistance mutations within their QRDRs, at codons 80 or 84 within the parC subunit and codon 84 within the gyrA subunit of DNA gyrase. The highest resistance (MIC = 2560 μg/mL) was associated with two SNPs in both gyrA and parC. Other resistant isolates (3/14) had mutations within norB. Mutations in genes of other efflux pumps and their regulator (norA, norC, mepA, mdeA, sepA, sdrM, mepR, arlR, and arlS) or the DNA mismatch repair (MMR) system (mutL and mutS) were not associated with increased resistance to ciprofloxacin. The functional mutations associated with ciprofloxacin resistance in QRDRs (gyrA and parC) and norB suggests that these are the most common reasons for ciprofloxacin resistance in ocular isolates. Novel SNPs of gyrA Glu-88-Leu, Asn-860-Thr and Thr-845-Ala and IIe-855-Met, identified in this study, need further gene knock out/in studies to better understand their effect on ciprofloxacin resistance.

Platygaster robiniae Buhl and Duso (Hymenoptera: Platygastridae) is an egg-larvae parasitoid of the black locust gall midge (Obolodiplosis robiniae) (Haldeman) (Diptera: Cecidomyiidae) which is a serious invasive pest in China, where it attacks an important hardwood species, the black locust tree, Robini pseudoacacia L. (Fabales: Fabaceae). Despite the use of P. robiniae as an effective bio-control agent, the absence of sequence data and other molecular markers have limited its genetic applications for pest management in forests. Simple-sequence repeats (SSRs) are valuable molecular markers for population genetic structure studies. In the present study, we identified 14,123 SSRs, of which 7799 SSR primer pairs were successfully designed. Subsequently, 240 SSR were chosen and tested with 48 P. robiniae accessions from two geographically separated populations in north and south China. Of these, 34 were polymorphic, with an average of three alleles (Na) and four genotypes (NG) each. The average values of observed heterozygosity (Ho) was 0.3514, expected heterozygosity (He) 0.4167, Shannon’s information index (I) 0.7143, and polymorphism information content (PIC) 0.3558, respectively. Neighbour joining analysis (bootstrap 1000) revealed that Chengdu (CD) and Dangdong (DD) popluations clustered into two main divisions, and some individuals from two popluations clustered together as the third devision, which indicated the gene flow and genetic differentiation were present between two populations. Our finding indicates that these SSR markers will be useful for further studies on the genotype identification and genetic mapping of the genus Platygaster. [ABSTRACT FROM AUTHOR]

A Gram-stain-negative, non-motile, yellow-pigmented and non-spore forming rod-shaped bacterium, designated strain BN140078T, was isolated from farmland soil, Chungbuk, Republic of Korea. It was able to grow aerobically at 10–40 °C (optimum 28 °C), pH 5.5–7.5 (optimum pH 7.0) and with 0–2.0% (w/v) NaCl concentration (optimum 1.0%) on Reasoner's 2A (R2A) agar medium. Comparative 16S rRNA gene sequence analysis showed that the strain BN140078T had 96.9%, 96.5% and 96.1% 16S rRNA gene similarities with Chitinophaga ginsengihumi KACC 17604T, Chitinophaga rupis KACC 14521T and Chitinophaga japonensis KACC 12057T, respectively. The predominant respiratory quinone was menaquinone MK-7 and the major fatty acids (≥ 5%) were C16:1ω5c, iso-C15:0, iso-C17:0 3-OH and Summed Feature 3 (C16:1ω7c and/or C16:1ω6c). The polar lipids were composed of phosphatidylethanolamine, four unidentified amino lipids and six unidentified lipids. The genomic DNA G+C content was 49.5 mol%. The genome of strain BN140078T comprises a number of biosynthetic gene clusters for secondary metabolites, in particular those for non-ribosomal peptide products. The polyphasic taxonomic study clearly distinguished this strain from its closest phylogenetic neighbors. Thus, we propose that the BN140078T represents a novel species of the genus Chitinophaga, for which the name Chitinophaga agrisoli sp. nov. was proposed. The type strain is BN140078T (=KCTC 62555T = CCTCC AB 2018162T). [ABSTRACT FROM AUTHOR]

In the field of sewage treatment, the identification of polyphosphate-accumulating organisms (PAOs) usually relies on biological experiments. However, biological experiments are not only complicated and time-consuming, but also costly. In recent years, machine learning has been widely used in many fields, but it is seldom used in the water treatment. The present work presented a high accuracy support vector machine (SVM) algorithm to realize the rapid identification and prediction of PAOs. We obtained 6,318 genome sequences of microorganisms from the publicly available microbial genome database for comparative analysis (MBGD). Minimap2 was used to compare the genomes of the obtained microorganisms in pairs, and read the overlap. The SVM model was established using the similarity of the genome sequences. In this SVM model, the average accuracy is 0.9628 ± 0.019 with 10-fold cross-validation. By predicting 2,652 microorganisms, 22 potential PAOs were obtained. Through the analysis of the predicted potential PAOs, most of them could be indirectly verified their phosphorus removal characteristics from previous reports. The SVM model we built shows high prediction accuracy and good stability.

Serratia marcescens is an opportunistic and nosocomial pathogen found in the intensive care unit (ICU), but its antimicrobial resistance (AMR) is rarely addressed. Here, we reported two bla KPC-2 strains, SMBC31 and SMBC50, recovered from the ICU of a hospital in Zhengzhou, China. The minimum inhibitory concentration (MIC) was determined using the broth microdilution method, while S1-PFGE was employed to demonstrate plasmid size approximation. Complete genome sequences were obtained through Illumina NovaSeq 6000 and Oxford Nanopore Technologies. Both strains exhibit resistance to meropenem and harbor the S. marcescens strains, SMBC31 and SMBC50, recovered from the ICU of a hospital in Zhengzhou, China. The minimum inhibitory concentration (MIC) was determined using the broth microdilution method, while S1-PFGE was employed to demonstrate plasmid size approximation. Complete genome sequences were obtained through Illumina NovaSeq 6000 and Oxford Nanopore Technologies. Both strains exhibit resistance to meropenem and harbor the bla KPC-2 and bla SRT-1 resistance genes. The plasmid pSMBC31-39K in strain SMBC31 and pSMBC50-107K in strain SMBC50 were identified as carrying the bla KPC-2 gene. Notably, both of these plasmids were successfully transferred to Escherichia coli strain J53. Phylogenetic analysis based on plasmid sequences revealed that pSMBC31-39K exhibited high homology with plasmids found in Aeromonas caviae , Citrobacter sp., and Pseudomonas aeruginosa , while pSMBC50-107K showed significant similarity to those of E. coli and Klebsiella pneumoniae . Notably, the coexistence of bla KPC-2 and bla SRT-1 was observed in all 94 KPC-2-producing S. marcescens strains by mining all genomes available under the GenBank database, which were mainly isolated from hospitalized patients. The emergence of multidrug-resistant S. marcescens poses significant challenges in treating clinical infections, highlighting the need for increased surveillance of this pathogen., Competing Interests: The authors declare that they have no competing interests., (© 2024 The Authors.)

Vibrio cholerae has caused seven cholera pandemics in the past two centuries. The seventh and ongoing pandemic has been particularly severe on the African continent. Here, we report long read-based genome sequences of six V. cholerae strains isolated in the Democratic Republic of the Congo between 2009 and 2012., Competing Interests: The authors declare no conflict of interest.

Here, we report the draft genome sequences of strains of Bacillus and Salarachaeum that were isolated from hypersaline water samples collected from Lake Karum, Danakil Depression, Ethiopia. The sequences pave the way for more targeted studies into the potential biological activities and secondary metabolite synthesis of these organisms., Competing Interests: The authors declare no conflict of interest.

Leuconostoc carnosum is a bacterial species commonly associated with meat spoilage. However, some strains exhibit preservative effects due to bacteriocin production. Here, we report the complete genome sequences for two strains, L. carnosum 4010 and AMS1. Bacteriocin-related gene clusters were found on the plasmids of both strains., Competing Interests: The authors declare no conflict of interest.

Here, we present the genomes of two soil actinobacteria: Arthrobacter sp. strain AZCC_0090 and Mycobacterium sp. strain AZCC_0083, isolated from oligotrophic subsurface soils in Southern Arizona, USA., Competing Interests: The authors declare no conflict of interest.

Kluyvera is a genus within the family Enterobacteriaceae and can cause various human infections but remains poorly studied. A carbapenem-resistant blaNDM–1-carrying Kluyvera strain 090646T was isolated from a hospital sink in Chengdu, Sichuan province, China. Whole genome sequencing of the strain revealed that it had 28.2 to 42.3% in silico DNA-DNA hybridization (isDDH) scores and 84.15 to 90.10% average nucleotide identity (ANI) values with other Kluyvera species. Both values are well below the ≥ 70.0% isDDH and ≥ 95–96% ANI cutoffs to define bacterial species, suggesting that the strain represents a novel species of the genus Kluyvera, for which the name Kluyvera sichuanensis. nov. is proposed. Type strain of K. sichuanensis is 090646T (=GDMCC 1.1872T =KCTC 82166T). Strain 090646T can be differentiated from other Kluyvera species by its ability to utilize D-sorbitol but not β-galactosidase (ONPG), D-mannose, glycerin, raffinose, nor sucrose. There were 47 genome sequences labeled as Kluyvera in GenBank, which were curated for precise species identification. Only 33 of the 47 genomes were indeed of Kluyvera and four novel Kluyvera genomospecies were identified, highlighting that the species assignation of bacterial genomes in GenBank need to be curated. Genome sequencing for more strains is required to understand the genus Kluyvera.

Kluyvera is a genus within the family Enterobacteriaceae and can cause various human infections but remains poorly studied. A carbapenem-resistant bla NDM–1-carrying Kluyvera strain 090646T was isolated from a hospital sink in Chengdu, Sichuan province, China. Whole genome sequencing of the strain revealed that it had 28.2 to 42.3% in silico DNA-DNA hybridization (is DDH) scores and 84.15 to 90.10% average nucleotide identity (ANI) values with other Kluyvera species. Both values are well below the ≥ 70.0% is DDH and ≥ 95–96% ANI cutoffs to define bacterial species, suggesting that the strain represents a novel species of the genus Kluyvera , for which the name Kluyvera sichuanensis. nov. is proposed. Type strain of K. sichuanensis is 090646T (=GDMCC 1.1872T =KCTC 82166T). Strain 090646T can be differentiated from other Kluyvera species by its ability to utilize D-sorbitol but not β-galactosidase (ONPG), D-mannose, glycerin, raffinose, nor sucrose. There were 47 genome sequences labeled as Kluyvera in GenBank, which were curated for precise species identification. Only 33 of the 47 genomes were indeed of Kluyvera and four novel Kluyvera genomospecies were identified, highlighting that the species assignation of bacterial genomes in GenBank need to be curated. Genome sequencing for more strains is required to understand the genus Kluyvera. [ABSTRACT FROM AUTHOR]

Many fungi (from micro-to macromycetes) interact with plants as a relevant component of plant microbiota. The aim of the review is to focus on the early diverging fungi (Mucoromycota) whose members establish a wide range of beneficial or pathogenic interactions with their green hosts, depending on their phylogenetic position. While Mortierellomycotina are mostly identified as rhizospheric microbes, Glomeromycotina are acknowledged as the most widespread arbuscular mycorrhizal fungi, leading to the establishment of an ancient and ecologically relevant symbiosis with plants. A combination of data from fossils and from novel observations demonstrates how the third subphylum, Mucoromycotina, is a source of so far largely unidentified plant-interacting fungi. In addition to pathogens, other members establish symbiosis with non-vascular plants, Gymnosperms and Angiosperms producing both ecto- and endomycorrhizas. A survey of the so far sequenced genomes illustrates how these fungi share some genetic traits, mirroring their common origin, while other features are specific for each group. In addition to some shared phenotypic traits (aseptate hyphae, multinuclear conditions) endobacteria belonging to the group of Burkholderia -related and to the Mycoplasma-related bacteria are present in many members of the three subphyla, suggesting that the common ancestor was already hosting endobacteria. The review also underlines some idiosyncrasies mostly due to the lack of fossil reports which may confirm phylogenomics as well as the still limited functional data. Image 1 • Focuses on early diverging fungi (Mucoromycota) which interact with plants. • Provides a link between fossil and omics studies. • Introduces the biological features of the three subphyla focusing on their evolution. • Summarizes current biological understanding on the basis of the genome sequencing. • Illustrates how endobacteria are a common marker of plant-interacting Mucormycota. [ABSTRACT FROM AUTHOR]

Although several bacterial lignin-oxidising enzymes have been discovered in recent years, it is not yet clear whether different lignin-degrading bacteria use similar mechanisms for lignin oxidation and degradation of lignin fragments. Genome sequences of 13 bacterial lignin-oxidising bacteria, including new genome sequences for Microbacterium phyllosphaerae and Agrobacterium sp., were analysed for the presence of lignin-oxidising enzymes and aromatic degradation gene clusters that could be used to metabolise the products of lignin degradation. Ten bacterial genomes contain DyP-type peroxidases, and ten bacterial strains contain putative multi-copper oxidases (MCOs), both known to have activity for lignin oxidation. Only one strain lacks both MCOs and DyP-type peroxidase genes. Eleven bacterial genomes contain aromatic degradation gene clusters, of which ten contain the central β-ketoadipate pathway, with variable numbers and types of degradation clusters for other aromatic substrates. Hence, there appear to be diverse metabolic strategies used for lignin oxidation in bacteria, while the β-ketoadipate pathway appears to be the most common route for aromatic metabolism in lignin-degrading bacteria. [ABSTRACT FROM AUTHOR]

Sophora koreensis Nakai, an endemic species distributed only in the Korean Peninsula, is of great geographical, economic, and taxonomic importance. Although its complete chloroplast (cp) genome sequence has been reported, its mitochondrial (mt) genome sequence has not yet been studied. Therefore, in this study, we aimed to investigate its mt genome sequence and compare it with those reported for other Fabaceae species. Total genomic DNA was extracted from fresh S. koreensis leaves collected from natural habitats in Gangwon-do Province, South Korea. This was followed by polymerase chain reaction (PCR) amplification of cpDNA insertions in the mt genome and the detection of microsatellites and dispersed repeats in the cp and mt genomes. Finally, the cp and mt genomes of S. koreensis were compared with those reported for other Fabaceae species. The cp sequence of S. koreensis showed identical gene orders and contents as those previously reported. Only six substitutions and one deletion were detected with 99 % homology. Conversely, the complete mt genome sequence, which was 517,845 bp in length and encoded 61 genes, including 43 protein-coding, 15 transfer RNAs, and 3 ribosomal RNA genes, was considerably different from that of S. japonica in terms of gene order and composition. Further, the mt genome of S. koreensis included ca. 7 and 3 kb insertions, representing an intracellular gene transfer (IGT) event, and the regions with these insertions were determined to be originally present in the cp genome. This IGT event was also confirmed via PCR amplification. IGT events can be induced via biological gene expression control or the use of repetitive sequences, and they provide important insights into the evolutionary lineage of S. koreensis. However, further studies are needed to clarify the gene transfer mechanisms between the two organelles. [ABSTRACT FROM AUTHOR]