PB-LKS: a python package for predicting phage-bacteria interaction through local K-mer strategy.

Bacteriophages can help the treatment of bacterial infections yet require in-silico models to deal with the great genetic diversity between phages and bacteria. Despite the tolerable prediction performance, the application scope of current approaches is limited to the prediction at the species level, which cannot accurately predict the relationship of phages across strain mutants. This has hindered the development of phage therapeutics based on the prediction of phage-bacteria relationships. In this paper, we present, PB-LKS, to predict the phage-bacteria interaction based on local K-mer strategy with higher performance and wider applicability. The utility of PB-LKS is rigorously validated through (i) large-scale historical screening, (ii) case study at the class level and (iii) in vitro simulation of bacterial antiphage resistance at the strain mutant level. The PB-LKS approach could outperform the current state-of-the-art methods and illustrate potential clinical utility in pre-optimized phage therapy design.

Complete genome sequence analysis of Pestalotiopsis microspora, a fungal pathogen causing kiwifruit postharvest rots.

BACKGROUND: The postharvest rot of kiwifruit is one of the most devastating diseases affecting kiwifruit quality worldwide. However, the genomic basis and pathogenicity mechanisms of kiwifruit rot pathogens are lacking. Here we report the first whole genome sequence of Pestalotiopsis microspora, one of the main pathogens causing postharvest kiwifruit rot in China. The genome of strain KFRD-2 was sequenced, de novo assembled, and analyzed. RESULTS: The genome of KFRD-2 was estimated to be approximately 50.31 Mb in size, with an overall GC content of 50.25%. Among 14,711 predicted genes, 14,423 (98.04%) exhibited significant matches to genes in the NCBI nr database. A phylogenetic analysis of 26 known pathogenic fungi, including P. microspora KFRD-2, based on conserved orthologous genes, revealed that KFRD-2's closest evolutionary relationships were to Neopestalotiopsis spp. Among KFRD-2's coding genes, 870 putative CAZy genes spanned six classes of CAZys, which play roles in degrading plant cell walls. Out of the 25 other plant pathogenic fungi, P. microspora possessed a greater number of CAZy genes than 22 and was especially enriched in GH and AA genes. A total of 845 transcription factors and 86 secondary metabolism gene clusters were predicted, representing various types. Furthermore, 28 effectors and 109 virulence-enhanced factors were identified using the PHI (pathogen host-interacting) database. CONCLUSION: This complete genome sequence analysis of the kiwifruit postharvest rot pathogen P. microspora enriches our understanding its disease pathogenesis and virulence. This study establishes a theoretical foundation for future investigations into the pathogenic mechanisms of P. microspora and the development of enhanced strategies for the efficient management of kiwifruit postharvest rots.

Micromonospora solifontis sp. nov., an actinobacterium isolated from hot spring soil.

An actinobacterium strain, PPF5-17T, was isolated from hot spring soil collected from Chiang Rai province, Thailand. The strain exhibited morphological and chemotaxonomic properties similar to those of members of the genus Micromonospora. Colonies of PPF5-17T were strong pinkish red and turned black after sporulation in ISP 2 agar medium. Cells formed single spores directly on the substrate mycelium. Growth was observed from 15 to 45 °C and at pH 5-8. Maximum NaCl concentration for growth was 3 % (w/v). PPF5-17T was found to have meso-diaminopimelic acid, xylose, mannose and glucose in the whole-cell hydrolysate. Diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylinositol and phosphatidylinositolmannosides were observed as the membrane phospholipids. MK-10(H6), MK-9(H6), MK-10(H4) and MK-9(H4) were the major menaquinones. The predominant cellular fatty acids were iso-C15 : 0, iso-C17 : 0, anteiso-C17 : 0 and iso-C16 : 0. PPF5-17T shared the highest 16S rRNA gene sequence similarity with Micromonospora fluminis LMG 30467T (99.3 %). A genome-based taxonomic study revealed that PPF5-17T was closely related to Micromonospora aurantinigra DSM 44815T in the phylogenomic tree with an average nucleotide identity by blast (ANIb) of 87.7 % and a digital DNA-DNA hybridization (dDDH) value of, 36.1 % which were below the threshold values for delineation of a novel species. Moreover, PPF5-17T could be distinguished from its closest neighbours, M. fluminis LMG 30467T and M. aurantinigra DSM 44815T, with respect to a broad range of phenotypic properties. Thus, PPF5-17T represents a novel species, for which the name Micromonospora solifontis sp. nov. is proposed. The type strain is PPF5-17T (= TBRC 8478T = NBRC 113441T).

Gordonia aquimaris sp. nov., a novel marine actinobacterium isolated from seawater in the upper gulf of Thailand.

An actinobacterium strain, SW21T, was isolated from seawater collected in the upper Gulf of Thailand. Cells were Gram-stain-positive, aerobic and rod-shaped. Growth was observed from 15 to 37 °C and at pH 6-8. Maximum NaCl for growth was 14 % (w/v). meso-Diaminopimelic acid, arabinose, galactose, glucose, rhamnose and ribose were detected in the whole-cell hydrolysate. Diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylinositol and phosphatidylinositol mannoside were detected as the phospholipids in the cells. The major menaquinones were MK-9(H2) and MK-7(H2). The major cellular fatty acids were C16 : 0, C18 : 1 ω9c, C18 : 0 and C18 : 010-methyl (TBSA). The 16S rRNA gene sequence data supported the assignment of strain SW21T to the genus Gordonia and showed that Gordonia mangrovi KCTC 49383T (98.7 %) was the closest relative. Moreover, the average nucleotide identity-blast (85.5 %) and digital DNA-DNA hybridization (30.7 %) values between strain SW21T and its closest neighbour were below the threshold values for delineation of a novel species. The combination of genotypic and phenotypic data indicated that strain SW21T is representative of novel species of the genus Gordonia. The name Gordonia aquimaris sp. nov. is proposed for strain SW21T. The type strain is SW21T (=TBRC 15691T=NBRC 115558T).

Proposal of Streptomyces sporoverrucosus Gause et al. 1983 as a later heterotypic synonym of Streptomyces goshikiensis Niida et al. 1966 and an emended description of Streptomyces goshikiensis.

The taxonomic relationship of Streptomyces goshikiensis and Streptomyces sporoverrucosus was re-evaluated using comparative genome analysis. The 16S rRNA gene sequence analysis indicated that S. goshikiensis JCM 4640T and S. sporoverrucosus CGMCC 4.1796T shared 100% sequence similarity. Phylogenetic analysis based on 16S rRNA gene and genomic sequences exhibited that they were closely related to each other. However, the values of average nucleotide identity (ANIb/ANIm) and digital DNA-DNA hybridization (dDDH) between the genomes of two type strains were 98.33%/98.69% and 87.2%, respectively, greater than the two recognized thresholds values of 96.7% ANI and 70% dDDH for species delineation. These results suggested that S. goshikiensis and S. sporoverrucosus should share the same taxonomic position. In addition, this conclusion was further supported by highly similar morphological, cultural, physiological, biochemical and chemotaxonomic characteristics between them. Consequently, it is proposed that S. sporoverrucosus is a later heterotypic synonym of S. goshikiensis.

Molecular epidemiological analysis of Mycobacterium tuberculosis modern Beijing genotype strains isolated in Chiba Prefecture over 10 years.

INTRODUCTION: The prevalence of the phylogenetic groups of Mycobacterium tuberculosis Beijing genotype has been reported to be similar in different areas of Japan. However, recent reports from rural areas of Japan show a low prevalence of modern Beijing strains, suggesting that the distribution of modern Beijing strains may have changed recently. Therefore, multi-locus variable number of tandem repeats analysis (MLVA) and draft whole genome sequence (DWGS) analysis were carried out to investigate the prevalence of particular genotype strains. METHODS: Nine hundred and ninety modern Beijing strains were studied using minimum spanning tree (MST) analysis and neighbor-net analysis of MLVA and WGS data. RESULTS: An MST of M. tuberculosis Beijing genotype strains reconstructed from 12 loci-MLVA data showed two large complexes with the J12-0006 MLVA pattern. In one of the complexes, strains with the pECT07 pattern produced by 24 loci-MLVA and its SLVs were most prevalent. DWGS analysis was carried out for pECT07 and its SLV strains. Neighbor-net and MST analyses of the DWGS data showed that pECT07 and its SLV strains were grouped in separate clusters. When all the combinations of two of the tested strains were analyzed, MST analysis showed that only 9 (1.7%) of the 528 pairs of tested strains had 5 or less SNPs. CONCLUSIONS: The results of this study suggested that pECT07 and its variants were prevalent among M. tuberculosis modern Beijing strains in Chiba Prefecture, but the prevalence of those strains may not have been due to an earlier large-scale latent outbreak.

Spectrum of Protein Location in Proteomes Captures Evolutionary Relationship Between Species.

The native subcellular location (also referred to as localization or cellular compartment) of a protein is the one in which it acts most frequently; it is one aspect of protein function. Do ten eukaryotic model organisms differ in their location spectrum, i.e., the fraction of its proteome in each of seven major cellular compartments? As experimental annotations of locations remain biased and incomplete, we need prediction methods to answer this question. After systematic bias corrections, the complete but faulty prediction methods appeared to be more appropriate to compare location spectra between species than the incomplete more accurate experimental data. This work compared the location spectra for ten eukaryotes: Homo sapiens (human), Gorilla gorilla (gorilla), Pan troglodytes (chimpanzee), Mus musculus (mouse), Rattus norvegicus (rat), Drosophila melanogaster (fruit/vinegar fly), Anopheles gambiae (African malaria mosquito), Caenorhabitis elegans (nematode), Saccharomyces cerevisiae (baker's yeast), and Schizosaccharomyces pombe (fission yeast). The two largest classes were predicted to be the nucleus and the cytoplasm together accounting for 47-62% of all proteins, while 7-21% of the proteins were predicted in the plasma membrane and 4-15% to be secreted. Overall, the predicted location spectra were largely similar. However, in detail, the differences sufficed to plot trees (UPGMA) and 2D (PCA) maps relating the ten organisms using a simple Euclidean distance in seven states (location classes). The relations based on the simple predicted location spectra captured aspects of cross-species comparisons usually revealed only by much more detailed evolutionary comparisons. Most interestingly, known phylogenetic relations were reproduced better by paralog-only than by ortholog-only trees.

Protein-protein and protein-nucleic acid binding residues important for common and rare sequence variants in human.

BACKGROUND: Any two unrelated people differ by about 20,000 missense mutations (also referred to as SAVs: Single Amino acid Variants or missense SNV). Many SAVs have been predicted to strongly affect molecular protein function. Common SAVs (> 5% of population) were predicted to have, on average, more effect on molecular protein function than rare SAVs (< 1% of population). We hypothesized that the prevalence of effect in common over rare SAVs might partially be caused by common SAVs more often occurring at interfaces of proteins with other proteins, DNA, or RNA, thereby creating subgroup-specific phenotypes. We analyzed SAVs from 60,706 people through the lens of two prediction methods, one (SNAP2) predicting the effects of SAVs on molecular protein function, the other (ProNA2020) predicting residues in DNA-, RNA- and protein-binding interfaces. RESULTS: Three results stood out. Firstly, SAVs predicted to occur at binding interfaces were predicted to more likely affect molecular function than those predicted as not binding (p value < 2.2 × 10-16). Secondly, for SAVs predicted to occur at binding interfaces, common SAVs were predicted more strongly with effect on protein function than rare SAVs (p value < 2.2 × 10-16). Restriction to SAVs with experimental annotations confirmed all results, although the resulting subsets were too small to establish statistical significance for any result. Thirdly, the fraction of SAVs predicted at binding interfaces differed significantly between tissues, e.g. urinary bladder tissue was found abundant in SAVs predicted at protein-binding interfaces, and reproductive tissues (ovary, testis, vagina, seminal vesicle and endometrium) in SAVs predicted at DNA-binding interfaces. CONCLUSIONS: Overall, the results suggested that residues at protein-, DNA-, and RNA-binding interfaces contributed toward predicting that common SAVs more likely affect molecular function than rare SAVs.

Hierarchical discovery of large-scale and focal copy number alterations in low-coverage cancer genomes.

BACKGROUND: Detection of DNA copy number alterations (CNAs) is critical to understand genetic diversity, genome evolution and pathological conditions such as cancer. Cancer genomes are plagued with widespread multi-level structural aberrations of chromosomes that pose challenges to discover CNAs of different length scales, and distinct biological origins and functions. Although several computational tools are available to identify CNAs using read depth (RD) signal, they fail to distinguish between large-scale and focal alterations due to inaccurate modeling of the RD signal of cancer genomes. Additionally, RD signal is affected by overdispersion-driven biases at low coverage, which significantly inflate false detection of CNA regions. RESULTS: We have developed CNAtra framework to hierarchically discover and classify 'large-scale' and 'focal' copy number gain/loss from a single whole-genome sequencing (WGS) sample. CNAtra first utilizes a multimodal-based distribution to estimate the copy number (CN) reference from the complex RD profile of the cancer genome. We implemented Savitzky-Golay smoothing filter and Modified Varri segmentation to capture the change points of the RD signal. We then developed a CN state-driven merging algorithm to identify the large segments with distinct copy numbers. Next, we identified focal alterations in each large segment using coverage-based thresholding to mitigate the adverse effects of signal variations. Using cancer cell lines and patient datasets, we confirmed CNAtra's ability to detect and distinguish the segmental aneuploidies and focal alterations. We used realistic simulated data for benchmarking the performance of CNAtra against other single-sample detection tools, where we artificially introduced CNAs in the original cancer profiles. We found that CNAtra is superior in terms of precision, recall and f-measure. CNAtra shows the highest sensitivity of 93 and 97% for detecting large-scale and focal alterations respectively. Visual inspection of CNAs revealed that CNAtra is the most robust detection tool for low-coverage cancer data. CONCLUSIONS: CNAtra is a single-sample CNA detection tool that provides an analytical and visualization framework for CNA profiling without relying on any reference control. It can detect chromosome-level segmental aneuploidies and high-confidence focal alterations, even from low-coverage data. CNAtra is an open-source software implemented in MATLAB®. It is freely available at https://github.com/AISKhalil/CNAtra.

Complete genome sequence of the lytic cold-active Pseudomonas fluorescens bacteriophage VSW-3 from Napahai plateau wetland.

The lytic cold-active bacteriophage VSW-3, belonging to the Podoviridae family and infecting the host Pseudomonas fluorescens SW-3, was isolated from the Napahai plateau wetland in China. With the development of sequencing technology, the study of Pseudomonas genomic diversity has increased; however, knowledge of cold-active phages infecting Pseudomonas is limited. The newly sequenced phage VSW-3 was classified based on virion morphology by transmission electron microscope. Sequence analysis revealed that the genome size was 40,556 bp with an overall GC content of 57.54 % and 46 open reading frames. The genome was organized into several modules containing genes for packaging, structural proteins, replication/transcription, and phage lysis. The sequence contained 45 potential promoters, 3 transcription terminators, and yet no tRNAs. This is the first report of cold-active Pseudomonas fluorescens bacteriophage genome sequencing.

In silico region of difference (RD) analysis of Mycobacterium tuberculosis complex from sequence reads using RD-Analyzer.

BACKGROUND: Whole-genome sequencing is increasingly used in clinical diagnosis of tuberculosis and study of Mycobacterium tuberculosis complex (MTC). MTC consists of several genetically homogenous mycobacteria species which can cause tuberculosis in humans and animals. Regions of difference (RDs) are commonly regarded as gold standard genetic markers for MTC classification. RESULTS: We develop RD-Analyzer, a tool that can accurately infer the species and lineage of MTC isolates from sequence reads based on the presence and absence of a set of 31 RDs. Applied on a publicly available diverse set of 377 sequenced MTC isolates from known major species and lineages, RD-Analyzer achieved an accuracy of 98.14 % (370/377) in species prediction and a concordance of 98.47 % (257/261) in Mycobacterium tuberculosis lineage prediction compared to predictions based on single nucleotide polymorphism markers. By comparing respective sequencing read depths on each genomic position between isolates of different sublineages, we were able to identify the known RD markers in different sublineages of Lineage 4 and provide support for six potential delineating markers having high sensitivities and specificities for sublineage prediction. An extended version of RD-Analyzer was thus developed to allow user-defined RDs for lineage prediction. CONCLUSIONS: RD-Analyzer is a useful and accurate tool for species, lineage and sublineage prediction using known RDs of MTC from sequence reads and is extendable to accepting user-defined RDs for analysis. RD-Analyzer is written in Python and is freely available at https://github.com/xiaeryu/RD-Analyzer .

Abundant sequence divergence in the native Japanese cattle Mishima-Ushi (Bos taurus) detected using whole-genome sequencing.

The native Japanese cattle Mishima-Ushi, a designated national natural treasure, are bred on a remote island, which has resulted in the conservation of their genealogy. We examined the genetic characteristics of 8 Mishima-Ushi individuals by using single nucleotide polymorphisms (SNPs), insertions, and deletions obtained by whole-genome sequencing. Mapping analysis with various criteria showed that predicted heterozygous SNPs were more prevalent than predicted homozygous SNPs in the exonic region, especially non-synonymous SNPs. From the identified 6.54 million polymorphisms, we found 400 non-synonymous SNPs in 313 genes specific to each of the 8 Mishima-Ushi individuals. Additionally, 3,170,833 polymorphisms were found between the 8 Mishima-Ushi individuals. Phylogenetic analysis confirmed that the Mishima-Ushi population diverged from another strain of Japanese cattle. This study provides a framework for further genetic studies of Mishima-Ushi and research on the function of SNP-containing genes as well as understanding the genetic relationship between the domestic and native Japanese cattle breeds.

Discovery and characterization of a novel pathogen Erwinia pyri sp. nov. associated with pear dieback: taxonomic insights and genomic analysis.

In 2022, a novel disease similar to pear fire blight was found in a pear orchard in Zhangye City, Gansu Province, China. The disease mainly damages the branches, leaves, and fruits of the plant. To identify the pathogen, tissue isolation and pathogenicity testing (inoculating the potential pathogen on healthy plant tissues) were conducted. Furthermore, a comprehensive analysis encompassing the pathogen's morphological, physiological, and biochemical characteristics and whole-genome sequencing was conducted. The results showed that among the eight isolates, the symptoms on the detached leaves and fruits inoculated with isolate DE2 were identical to those observed in the field. Verifying Koch's postulates confirmed that DE2 was the pathogenic bacterium that causes the disease. Based on a 16S rRNA phylogenetic tree, isolate DE2 belongs to the genus Erwinia. Biolog and API 20E results also indicated that isolate DE2 is an undescribed species of Erwinia. Isolate DE2 was negative for oxidase. Subsequently, the complete genome sequence of isolate DE2 was determined and compared to the complete genome sequences of 29 other Erwinia species based on digital DNA-DNA hybridization (dDDH) and average nucleotide identity (ANI) analyses. The ANI and dDDH values between strain DE2 and Erwinia species were both below the species thresholds (ANI < 95-96%, dDDH<70%), suggesting that isolate DE2 is a new species of Erwinia. We will temporarily name strain DE2 as Erwinia pyri sp. nov. There were 548 predicted virulence factors in the genome of strain DE2, comprising 534 on the chromosome and 5 in the plasmids. The whole genome sequence of strain DE2 has been submitted to the NCBI database (ASM3075845v1) with accession number GCA_030758455.1. The strain DE2 has been preserved at the China Center for Type Culture Collection (CCTCC) under the deposit number CCTCC AB 2024080. This study represents the initial report of a potentially new bacterial species in the genus Erwinia that causes a novel pear dieback disease. The findings provide a valuable strain resource for the study of the genus Erwinia and establish a robust theoretical foundation for the prevention and control of emerging pear dieback diseases.

Pradimicin U, a promising antimicrobial agent isolated from a newly found Nonomuraea composti sp. nov.

Pradimicin U is a new dihydrobenzo[a]naphthacenequinone compound found to be active on a screen designed to investigate compounds with antimicrobial activity, produced by the actinomycete designated strain FMUSA5-5T. The strain was isolated from a bio-fertilizer of Musa spp. collected from Suphanburi province, Thailand. The chemotaxonomic characteristics and 16S rRNA gene analysis revealed that strain FMUSA5-5T is a member of the genus Nonomuraea. Low genome-based taxonomic criteria, average nucleotide identity (ANI) (82.8-88.3%), average amino-acid identity (AAI) (79.4-87.3%), and digital DNA-DNA hybridization (dDDH) (29.5-38.5%) values and several phenotypic differences between strain FMUSA5-5T and its closest type strains of the genus Nonomuraea indicated that strain FMUSA5-5T represents a novel species of the genus Nonomuraea and the name Nonomuraea composti sp. nov. is proposed for the strain. The crude extract from the culture broth of strain FMUSA5-5T displayed promising antimicrobial activity against several pathogens and led to the isolation of a novel secondary metabolite, pradimicin U. Interestingly, this compound displayed a broad spectrum of biological activities such as antimalarial activity against Plasmodium falciparum K1 (IC50 value = 3.65 µg/mL), anti-Mycobacterium tuberculosis H37Ra (MIC value = 25.0 µg/mL), anti-Alternaria brassicicola BCC 42724 (MIC value = 25.0 µg/mL), anti-Bacillus cereus ATCC 11778 and anti-Staphylococcus aureus ATCC 29213 (MIC values = 6.25 and 1.56 µg/mL, respectively). Moreover, the compound possessed strong anti-human small cell lung cancer (NCI-H187) activity with IC50 value of 5.69 µg/mL, while cytotoxicity against human breast cancer (MCF-7) and Vero cells was very weak (IC50 values of 52.49 and 21.84 µg/mL, respectively).

Whole-genome Sequencing Association Analysis of Quantitative Platelet Traits in A Large Cohort of ß-thalassemia.

Platelet acts as a crucial monitoring indicator for hypercoagulability and thrombosis and a key target for drug regulation. Genotype-phenotype association studies have confirmed that platelet traits are quantitatively regulated by multiple genes. However, there is currently a lack of genetic studies on the heterogeneity of platelet traits in ß-thalassemia under hypercoagulable state. Here, we studied the phenotypic heterogeneity of platelet count (PLT) and mean platelet volume (MPV) in 1020 ß-thalassemia patients. We further performed a functionally informed whole genome sequencing association analysis of common variants and rare variants (RVs) for PLT and MPV in 916 patients through integrative analysis of whole-genome sequencing data and functional annotation data. Extreme phenotypic heterogeneity of platelet traits was observed in ß-thalassemia patients. Additionally, the common variant based gene-level analysis identified the novel gene of RNF144B associated with MPV. The RV analysis identified several novel associations in both coding and noncoding genome, including missense RVs of PPP2R5C associated with PLT and missense RVs of TSSK1B associated with MPV. In conclusion, we performed a comprehensive and systematic whole genome scan of platelet traits in the ß-thalassemia cohort, demonstrating the specificity of genetic regulation of platelet traits in the context of ß-thalassemia, providing potential targets for intervention.

In vitro, in planta, and comparative genomic analyses of Pseudomonas syringae pv. syringae strains of pepper (Capsicum annuum var. annuum).

Pseudomonas syringae pv. syringae (Pss) is an emerging phytopathogen that causes Pseudomonas leaf spot (PLS) disease in pepper plants. Pss can cause serious economic damage to pepper production, yet very little is known about the virulence factors carried by Pss that cause disease in pepper seedlings. In this study, Pss strains isolated from pepper plants showing PLS symptoms in Ohio between 2013 and 2021 (n = 16) showed varying degrees of virulence (Pss populations and disease symptoms on leaves) on 6-week-old pepper seedlings. In vitro studies assessing growth in nutrient-limited conditions, biofilm production, and motility also showed varying degrees of virulence, but in vitro and in planta variation in virulence between Pss strains did not correlate. Comparative whole-genome sequencing studies identified notable virulence genes including 30 biofilm genes, 87 motility genes, and 106 secretion system genes. Additionally, a total of 27 antimicrobial resistance genes were found. A multivariate correlation analysis and Scoary analysis based on variation in gene content (n = 812 variable genes) and single nucleotide polymorphisms within virulence genes identified no significant correlations with disease severity, likely due to our limited sample size. In summary, our study explored the virulence and antimicrobial gene content of Pss in pepper seedlings as a first step toward understanding the virulence and pathogenicity of Pss in pepper seedlings. Further studies with additional pepper Pss strains will facilitate defining genes in Pss that correlate with its virulence in pepper seedlings, which can facilitate the development of effective measures to control Pss in pepper and other related P. syringae pathovars. IMPORTANCE: Pseudomonas leaf spot (PLS) caused by Pseudomonas syringae pv. syringae (Pss) causes significant losses to the pepper industry. Highly virulent Pss strains under optimal environmental conditions (cool-moderate temperatures, high moisture) can cause severe necrotic lesions on pepper leaves that consequently can decrease pepper yield if the disease persists. Hence, it is important to understand the virulence mechanisms of Pss to be able to effectively control PLS in peppers. In our study, in vitro, in planta, and whole-genome sequence analyses were conducted to better understand the virulence and pathogenicity characteristics of Pss strains in peppers. Our findings fill a knowledge gap regarding potential virulence and pathogenicity characteristics of Pss in peppers, including virulence and antimicrobial gene content. Our study helps pave a path to further identify the role of specific virulence genes in causing disease in peppers, which can have implications in developing strategies to effectively control PLS in peppers.

Heterotrophic bacteria in drinking water: evaluating antibiotic resistance and the presence of virulence genes.

Heterotrophic bacteria, impacting those with infections or compromised immunity, pose heightened health risks when resistant to antibiotics. This study investigates heterotrophic plate count bacteria in water from North West-C (NWC) and North West-G (NWG) facilities, revealing prevalent ß-hemolysis (NWC 82.5%, NWG 86.7%), enzyme production (98%), and antibiotic resistance, especially in NWC. NWG exhibits variations in hemolysin (P = 0.013), lipase (P = 0.009), and DNase activity (P = 0.006). Antibiotics, including ciprofloxacin, persist throughout treatment, with high resistance to ß-lactams and trimethoprim (47%-100%), predominantly in NWC. Multiple antibiotic resistance index indicates that 90% of values exceed 0.20, signifying isolates from high antibiotic usage sources. Whole genome sequencing reveals diverse antibiotic resistance genes in heterotrophic strains, emphasizing their prevalence and health risks in water.IMPORTANCEThis study's findings are a stark reminder of a significant health concern: our water sources harbor antibiotic-resistant heterotrophic bacteria, which can potentially cause illness, especially in individuals with weakened immune systems or underlying infections. Antibiotic resistance among these bacteria is deeply concerning, as it threatens the effectiveness of antibiotics, critical for treating various infections. Moreover, detecting virulence factors in a notable proportion of these bacteria highlights their elevated risk to public health. This research underscores the immediate need for enhanced water treatment processes, rigorous water quality monitoring, and the development of strategies to combat antibiotic resistance in the environment. Safeguarding the safety of our drinking water is imperative to protect public health and mitigate the spread of antibiotic-resistant infections, making these findings a compelling call to action for policymakers and public health authorities alike.

Whole genome analysis of Streptomyces sp. RerS4, a Rehmannia glutinosa rhizosphere microbe producing a new lipopeptide.

Rehmannia glutinosa, a valuable medicinal plant, is threatened by ring rot, a condition that greatly affects its yield and quality. Interactions between plant and the rhizosphere soil microbiome in the context of pathogen invasion are generally more specific, with recruitment of specialized microbes potentially antagonistic to a certain pathogen. Isolation of microorganisms from rhizosphere soil of healthy and ring rot-infected R. glutinosa was carried out to screen antifungal microbes. A strain designated RerS4 isolated from ring rot-infected R. glutinosa rhizosphere soil with strong antifungal activities was selected for further study. RerS4 was taxonomically characterized as the genus Streptomyces according to its morphology and 16S rRNA sequences that were most closely related to Streptomyces racemochromogenes NRRL B-5430T (99.72%) and Streptomyces polychromogenes NBRC 13072T (99.72%). A new lipopeptide isolated from RerS4 showed restrained proliferation, but was devoid of significant antibacterial and antioxidant activity with minimum inhibitory concentration (MIC) values of 20.3 ± 2.5 and 70.8 ± 3.7 µg/mL and half-maximal inhibitory concentration (IC50) values of 23.3 ± 0.8 and 58.8 ± 2.9 µg/mL, respectively. In addition, we report the complete genome sequence of Streptomyces sp. RerS4, which consists of a 7,301,482 bp linear chromosome and a 242,139 bp plasmid. Genome analysis revealed that Streptomyces sp. RerS4 contained 25 biosynthetic gene clusters (BGCs) for secondary metabolites, among which 68% had low similarities with known BGCs, leading us to believe that Streptomyces sp. RerS4 could produce valuable bioactive compounds.

Bacillus velezensis TSA32-1 as a Promising Agent for Biocontrol of Plant Pathogenic Fungi.

The use of synthetic fungicides has caused major problems such as soil and water pollution and negatively affects non-target species. Microbial biocontrol agents are needed for crop disease management to reduce agrochemical use. Bacillus and related genera produce secondary metabolites with agricultural applications, such as the pathogen-control agent Bacillus velezensis. We isolated B. velezensis TSA32-1 from soil and identified its characteristics by sequencing its 16S rRNA. B. velezensis TSA32-1 showed enzyme activity and antimicrobial effects against phytopathogenic fungi by inhibiting the growth of Fusarium graminearum, F. fujikuroi, Alternatia alternate, and Diaporthe actinidiae. Additionally, B. velezensis TSA32-1 protected diseases in corn and pepper seeds caused by F. graminearum and Pythium ultimum. The complete genome of B. velezensis TSA32-1 was 4.05 Mb with a G+C content of 46.3 mol % and possessed the bacillaene biosynthesis cluster, a polyketide that inhibits protein biosynthesis. We also detected a surfactin synthesis cluster, known as non-ribosomal peptide synthetases, which biosynthesizes the antibacterial substance lipopeptide. Surfactin, and fengycin family compounds, secondary metabolites known as key factors in biological control, also detected B. velezensis TSA32-1 which shows potential as a biocontrol agent for controlling plant pathogens in agriculture.

Enabling Artificial Intelligence for Genome Sequence Analysis of COVID-19 and Alike Viruses.

Recent pandemic of COVID-19 (Coronavirus) caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) has been growing lethally with unusual speed. It has infected millions of people and continues a mortifying influence on the global population's health and well-being. In this situation, genome sequence analysis and advanced artificial intelligence techniques may help researchers and medical experts to understand the genetic variants of COVID-19 or SARS-CoV-2. Genome sequence analysis of COVID-19 is crucial to understand the virus's origin, behavior, and structure, which might help produce/develop vaccines, antiviral drugs, and efficient preventive strategies. This paper introduces an artificial intelligence based system to perform genome sequence analysis of COVID-19 and alike viruses, e.g., SARS, middle east respiratory syndrome, and Ebola. The system helps to get important information from the genome sequences of different viruses. We perform comparative data analysis by extracting basic information of COVID-19 and other genome sequences, including information of nucleotides composition and their frequency, tri-nucleotide compositions, count of amino acids, alignment between genome sequences, and their DNA similarity information. We use different visualization methods to analyze these viruses' genome sequences and, finally, apply machine learning based classifier support vector machine to classify different genome sequences. The data set of different virus genome sequences are obtained from an online publicly accessible data center repository. The system achieves good classification results with an accuracy of 97% for COVID-19, 96%, SARS, and 95% for MERS and Ebola genome sequences, respectively.