Pseudomonas aeruginosa MutL promotes large chromosomal deletions through non-homologous end joining to prevent bacteriophage predation.

Pseudomonas aeruginosa is an opportunistic pathogen with a relatively large genome, and has been shown to routinely lose genomic fragments during environmental selection. However, the underlying molecular mechanisms that promote chromosomal deletion are still poorly understood. In a recent study, we showed that by deleting a large chromosomal fragment containing two closely situated genes, hmgA and galU, P. aeruginosa was able to form 'brown mutants', bacteriophage (phage) resistant mutants with a brown color phenotype. In this study, we show that the brown mutants occur at a frequency of 227 ± 87 × 10-8 and contain a deletion ranging from ∼200 to ∼620 kb. By screening P. aeruginosa transposon mutants, we identified mutL gene whose mutation constrained the emergence of phage-resistant brown mutants. Moreover, the P. aeruginosa MutL (PaMutL) nicking activity can result in DNA double strand break (DSB), which is then repaired by non-homologous end joining (NHEJ), leading to chromosomal deletions. Thus, we reported a noncanonical function of PaMutL that promotes chromosomal deletions through NHEJ to prevent phage predation.

A Linear Plasmid-Like Prophage of Actinomyces odontolyticus Promotes Biofilm Assembly.

The human oral cavity is home to a large number of bacteria and bacteriophages (phages). However, the biology of oral phages as members of the human microbiome is not well understood. Recently, we isolated Actinomyces odontolyticus subsp. actinosynbacter strain XH001 from the human oral cavity, and genomic analysis revealed the presence of an intact prophage named xhp1. Here, we demonstrated that xhp1 is a linear plasmid-like prophage, which is a newly identified phage of A. odontolyticus The prophage xhp1 genome is a 35-kb linear double-stranded DNA with 10-bp single-stranded, 3' cohesive ends. xhp1 exists extrachromosomally, with an estimated copy number of 5. Annotation of xhp1 revealed 54 open reading frames, while phylogenetic analysis suggests that it has limited similarity with other phages. xhp1 phage particles can be induced by mitomycin C and belong to the Siphoviridae family, according to transmission electron microscopic examination. The released xhp1 particles can reinfect the xhp1-cured XH001 strain and result in tiny blurry plaques. Moreover, xhp1 promotes XH001 biofilm formation through spontaneous induction and the release of host extracellular DNA (eDNA). In conclusion, we identified a linear plasmid-like prophage of A. odontolyticus, which enhances bacterial host biofilm assembly and could be beneficial to the host for its persistence in the oral cavity.IMPORTANCE The biology of phages as members of the human oral microbiome is understudied. Here, we report the characterization of xhp1, a novel linear plasmid-like prophage identified from a human oral isolate, Actinomyces odontolyticus subsp. actinosynbacter strain XH001. xhp1 can be induced and reinfect xhp1-cured XH001. The spontaneous induction of xhp1 leads to the lysis of a subpopulation of bacterial hosts and the release of eDNA that promotes biofilm assembly, thus potentially contributing to the persistence of A. odontolyticus within the oral cavity.

Surface Display of Heterologous ß-Galactosidase in Food-Grade Recombinant Lactococcus lactis.

ß-Galactosidase is an essential enzyme for the metabolism of lactose in human beings and has an important role in the treatment of lactose intolerance (LI). ß-Galactosidase expressed by intestinal microflora, such as lactic acid bacteria (LAB), also alleviates LI. A promising approach to LI management is to exploit a food-grade LAB delivery system that can inhabit the human intestine and overproduce ß-galactosidase. In this study, we constructed a food-grade ß-galactosidase surface display delivery system and then integrated into the chromosome of Lactococcus lactis (L. lactis) NZ9000 using recombination. Western blot and immunofluorescence analyses confirmed that ß-galactosidase was expressed on the cell surface of recombinant L. lactis stain NZ-SDL. The whole-cell biocatalyst exhibits Vmax and Km values of 121.38 ± 7.17 UONPG/g and 65.36 ± 5.54 mM, based on ONPG hydrolysis. The optimum temperature for enzyme activity is 37 °C and the optimum pH is 5.0. Activity of the whole-cell biocatalyst is promoted by Mg2+, Ca2+, and K+, but inhibited by Zn2+, Fe2+, and Fe3+. The system has a thermal stability similar to purified ß-galactosidase but better pH stability, and is also more stable in artificial intestinal juice. Oral administration and intraperitoneal injections of NZ-SDL in mice cause no detectable health effects. In conclusion, we have successfully constructed a food-grade gene expression system in L. lactis that displays ß-galactosidase on the cell surface. This system exhibits good enzyme activity and stability in vitro, and is safe in vivo. It is therefore a promising candidate for use in LI management.

Rule-based classification models of molecular autofluorescence.

Fluorescence-based detection has been commonly used in high-throughput screening (HTS) assays. Autofluorescent compounds, which can emit light in the absence of artificial fluorescent markers, often interfere with the detection of fluorophores and result in false positive signals in these assays. This interference presents a major issue in fluorescence-based screening techniques. In an effort to reduce the time and cost that will be spent on prescreening of autofluorescent compounds, in silico autofluorescence prediction models were developed for selected fluorescence-based assays in this study. Five prediction models were developed based on the respective fluorophores used in these HTS assays, which absorb and emit light at specific wavelengths (excitation/emission): Alexa Fluor 350 (A350) (340 nm/450 nm), 7-amino-4-trifluoromethyl-coumarin (AFC) (405 nm/520 nm), Alexa Fluor 488 (A488) (480 nm/540 nm), Rhodamine (547 nm/598 nm), and Texas Red (547 nm/618 nm). The C5.0 rule-based classification algorithm and PubChem 2D chemical structure fingerprints were used to develop prediction models. To optimize the accuracies of these prediction models despite the highly imbalanced ratio of fluorescent versus nonfluorescent compounds presented in the collected data sets, oversampling and undersampling strategies were applied. The average final accuracy achieved for the training set was 97%, and that for the testing set was 92%. In addition, five external data sets were used to further validate the models. Ultimately, 14 representative structural features (or rules) were determined to efficiently predict autofluorescence in data sets containing both fluorescent and nonfluorescent compounds. Several cases were illustrated in this study to demonstrate the applicability of these rules.

FAT1 inhibits AML autophagy and proliferation via downregulating ATG4B expression.

BACKGROUND: Emerging studies have shown that FAT atypical cadherin 1 (FAT1) and autophagy separately inhibits and promotes acute myeloid leukemia (AML) proliferation. However, it is unknown whether FAT1 were associated with autophagy in regulating AML proliferation. METHODS: AML cell lines, 6-week-old male nude mice and AML patient samples were used in this study. qPCR/Western blot and cell viability/3H-TdR incorporation assays were separately used to detect mRNA/protein levels and cell activity/proliferation. Luciferase reporter assay was used to examine gene promoter activity. Co-IP analysis was used to detect the binding of proteins. RESULTS: In this study, we for the first time demonstrated that FAT1 inhibited AML proliferation by decreasing AML autophagy level. Moreover, FAT1 weakened AML autophagy level via decreasing autophagy related 4B (ATG4B) expression. Mechanistically, we found that FAT1 reduced the phosphorylated and intranuclear SMAD family member 2/3 (smad2/3) protein levels, thus decreasing the activity of ATG4B gene promoter. Furthermore, we found that FAT1 competitively bound to TGF-ßR II which decreased the binding of TGF-ßR II to TGF-ßR I and the subsequent phosphorylation of TGF-ßR I, thus reducing the phosphorylation and intranuclear smad2/3. The experiments in nude mice showed that knockdown of FAT1 promoted AML autophagy and proliferation in vivo. CONCLUSIONS: Collectively, these results revealed that FAT1 downregulates ATG4B expression via inhibiting TGFß-smad2/3 signaling activity, thus decreasing the autophagy level and proliferation activity of AML cells. GENERAL SIGNIFICANCE: Our study suggested that the "FAT1-TGFß-smad2/3-ATG4B-autophagy" pathway may be a novel target for developing new targeted drugs to AML treatment.

Formation, migration, derivation, and generation mechanism of polycyclic aromatic hydrocarbons during frying.

Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic and lipophilic, which can be found in frying system. This review summarized the formation, migration and derivation for PAHs, hypothesized the possible mechanism for PAHs generation during frying and presented the research prospects. Some factors like high oil consumption, high temperature, long time and oil rich in unsaturated fatty acids promoted the formation of PAHs and the presence of antioxidants inhibited the PAHs formation. The effect of proteins and carbohydrates in foods on the formation of PAHs is inconclusive. The formed PAHs were migrated into food and air. Moreover, some PAHs transformed into more toxic PAHs-derivatives during frying. The generation of PAHs may be related to low-barrier free radical-mediated reaction and the unsaturated hydrocarbons may be precursors of PAHs during frying. In future, the isotope tracer technology and on-line detection may be applied to discover intermediates and provide clues for studying PAHs generation mechanisms.

The loss and fate of BaA, Chr, BbF, and BaP (PAH4) tracked by stable isotope during frying.

The objective of this work was to accurately quantify the loss of benzo(a)anthracene, chrysene, benzo(b)fluoranthene, and benzo(a)pyrene (PAH4) and investigate the fate of the lost PAH4 into their derivatives during frying. Stable isotopes (PAH4-d12) were used to simulate the loss and track the conversion of PAH4. The results showed that the rate of loss of PAH4-d12 increased with the increase of frying temperature and the loss rate of benzo(a)pyrene-d12 was the largest, indicating that benzo(a)pyrene had the strongest chemical reactivity during frying. Moreover, the identification of five PAH4 derivatives has confirmed the conversion of lost PAH4. Finally, the loss of PAH4 during frying positively correlated with the oxidation of oil, and a conversion mechanism of PAHs to derivatives was proposed. This work directly proved the loss and conversion of PAH4 and provided a comprehensive perspective for studying the changes in PAH4 during frying.

Migration and Distribution of PAH4 in Oil to French Fries Traced Using a Stable Isotope during Frying.

Isotope-labeled four polycyclic aromatic hydrocarbons (PAH4-d12) were applied to study the migration and distribution of PAH4 in oil to French fries during frying. The results showed that the mobilities of PAH4-d12 showed a downtrend within 0-6 h and then an uptrend, and PAH4-d12 were mainly distributed in the crust of the French fries, especially five-ring PAHs-d12. The correlation analysis showed that PAH4-d12 migration was mainly caused by oil absorption of French fries. The low fluidity of the oil slowed down the PAH4-d12 migration, which was accelerated as the total polar component increased (higher than 15-20%). Additionally, higher frying temperature enhanced the crust ratio and porous structure of French fries, which explained the abundant five-ring PAHs-d12 distributed in the crust. This study provided references for optimizing the frying parameters: the exposure of PAH4 in French fries to humans can be reduced by controlling the oil quality and weakening the crust of the French fries.

A new perspective on the benzo(a)pyrene generated in tea seeds during roasting.

The detection of benzo(a)pyrene (BaP), a strong carcinogen, in edible oil has been widely reported. This work studied the concentration of BaP in different parts of tea seeds generated during roasting from a new perspective. A novel method was established and used to calculate the actual generated concentration of BaP, which is different from the previous direct determination of BaP concentration and also takes into account the concentration of the lost BaP. The results showed that the loss rate of BaP in husks was the highest (92.7%), while that in the peeled tea seeds was the lowest (66.9%). Conversely, the generated concentration of BaP in peeled seeds was the highest (6.7 µg·kg-1), while that in husks was the lowest (2.8 µg·kg-1). The change in concentration of BaP during roasting was mainly related to the components of different parts of tea seeds. Finally, the lost BaP-d12 in tea seeds was detected in other parts of the semi-closed simplified model, which confirmed that BaP will migrate during roasting. This work emphasised that it was necessary to modify the calculation method for the generated concentration of BaP in food during thermal processing, which will be helpful to explore the generation mechanism of BaP.

A comprehensive support vector machine binary hERG classification model based on extensive but biased end point hERG data sets.

The human ether-a-go-go related gene (hERG) potassium ion channel plays a key role in cardiotoxicity and is therefore a key target as part of preclinical drug discovery toxicity screening. The PubChem hERG Bioassay data set, composed of 1668 compounds, was used to construct an in silico screening model. The corresponding trial models were constructed from a descriptor pool composed of 4D fingerprints (4D-FP) and traditional 2D and 3D VolSurf-like molecular descriptors. A final binary classification model was constructed via a support vector machine (SVM). The resultant model was then validated using the PubChem hERG Bioassay data set (AID 376) and an external hERG data set by evaluating the model's ability to determine hERG blockers from nonblockers. The external data set (the test set) consisted of 356 compounds collected from available literature data and consisting of 287 actives and 69 inactives. Four different sampling protocols and a 10-fold cross-correlation analysis--used in the validation process to evaluate classification models--explored the impact of the active--inactive data imbalance distribution of the PubChem high-throughput data set. Four different data sets were explored, and the one employing Lipinski's rule-of-five coupled with measures of relative molecular lipophilicity performed the best in the 10-fold cross-correlation validation of the training data set as well as overall prediction accuracy of the external test sets. The linear SVM binary classification model building strategy was applied to different combinations of MOE (traditional 2D, "21/2D", and 3D VolSurf-like) and 4D-FP molecular descriptors to further explore and refine previously proposed key descriptors, identify new significant features that contribute to the prediction of hERG toxicity, and construct the optimal SVM binary classification model from a shrunken descriptor pool. The accuracy, sensitivity, and specificity of the best model determined from 10-fold cross-validation are 95, 90, and 96%, respectively; the overall accuracy is near 87% for the external set. The models constructed in this study demonstrate the following: (i) robustness based upon performance in accuracy across the structural diversity of the training set, (ii) ability to predict a compound's "predisposition" to block hERG ion channels, and (iii) define and illustrate structural features that can be overlaid onto the chemical structures to aid in the 3D structure-activity interpretation of the hERG blocking effect.

[Spatio-Temporal Characteristics and Potential Source Areas of Seasonal Atmospheric Pollution in Shijiazhuang].

In order to systematically study the transmission characteristics of seasonal and typical pollutants in Shijiazhuang, hourly data of ground-level pollutants(PM2.5, PM10, O3, NO2, SO2, and CO) from 46 state-and provincial-controlled stations, and meteorological(temperature, humidity, and wind speed) data from 17 counties in Shijiazhuang City from December 2018 to November 2019 was analyzed. The interpolation(IDW) and correlation analysis were applied to seasonal and temporal spatial patterns of pollutant concentration. The backward trajectories analysis was performed to explore the seasonal transmission pattern and potential source areas of pollution in Shijiazhuang by combining with the global data assimilation system(GDAS). The results indicate that the different seasons have characteristic pollutants, as follows:spring(PM10, 48.91%), summer(O3, 81.97%), autumn(PM10 and PM2.5, 47.54% and 32.79%), and winter(PM2.5, 74.44%), which are related to the variation of meteorological conditions. Furthermore, the PM10(spring) concentration correlated negatively with the wind speed, presenting a high distribution in the northwest and low in the southeast, with a southerly transmission direction(53.32%). Central and southern Hebei, central and northern Henan, and central Shanxi are the potential sources of pollution(WPCWTij ≥ 160 µg·m-3), impacting western Shandong and northwest Shanxi(WPSCFij ≥ 0.3) with PM10. Moreover, the O3(summer) concentration correlated positively with temperature, and negatively with humidity. The southeast-south(54.24%) is the source direction of the transmission, and the potential source of O3 pollution is an arc area with Shijiazhuang in the center and Cangzhou and Heze as the double wings. Lastly, the PM2.5(autumn and winter) concentration correlated positively with humidity, and the winter concentration shows an increasing gradient from west to east. The trajectories of PM2.5 clustered the source directions:autumn(northeast-southeast, 74.75%), winter(northwest, 55.47%); central and southern Hebei, central and western Shanxi and northern Henan are the concentrated sources of potential pollution(WPCWTij ≥ 180 µg·m-3).

In silico binary classification QSAR models based on 4D-fingerprints and MOE descriptors for prediction of hERG blockage.

Blockage of the human ether-a-go-go related gene (hERG) potassium ion channel is a major factor related to cardiotoxicity. Hence, drugs binding to this channel have become an important biological end point in side effects screening. A set of 250 structurally diverse compounds screened for hERG activity from the literature was assembled using a set of reliability filters. This data set was used to construct a set of two-state hERG QSAR models. The descriptor pool used to construct the models consisted of 4D-fingerprints generated from the thermodynamic distribution of conformer states available to a molecule, 204 traditional 2D descriptors and 76 3D VolSurf-like descriptors computed using the Molecular Operating Environment (MOE) software. One model is a continuous partial least-squares (PLS) QSAR hERG binding model. Another related model is an optimized binary classification QSAR model that classifies compounds as active or inactive. This binary model achieves 91% accuracy over a large range of molecular diversity spanning the training set. Two external test sets were constructed. One test set is the condensed PubChem bioassay database containing 876 compounds, and the other test set consists of 106 additional compounds found in the literature. Both of the test sets were used to validate the binary QSAR model. The binary QSAR model permits a structural interpretation of possible sources for hERG activity. In particular, the presence of a polar negative group at a distance of 6-8 A from a hydrogen bond donor in a compound is predicted to be a quite structure-specific pharmacophore that increases hERG blockage. Since a data set of high chemical diversity was used to construct the binary model, it is applicable for performing general virtual hERG screening.

Adaptation of Pseudomonas aeruginosa to Phage PaP1 Predation via O-Antigen Polymerase Mutation.

Adaptation of bacteria to phage predation poses a major obstacle for phage therapy. Bacteria adopt multiple mechanisms, such as inhibition of phage adsorption and CRISPR/Cas systems, to resist phage infection. Here, a phage-resistant mutant of Pseudomonas aeruginosa strain PA1 under the infection of lytic phage PaP1 was selected for further study. The PaP1-resistant variant, termed PA1RG, showed decreased adsorption to PaP1 and was devoid of long chain O-antigen on its cell envelope. Whole genome sequencing and comparative analysis revealed a single nucleotide mutation in the gene PA1S_08510, which encodes the O-antigen polymerase Wzy that is involved in lipopolysaccharide (LPS) biosynthesis. PA1_Wzy was classified into the O6 serotype based on sequence homology analysis and adopts a transmembrane topology similar to that seem with P. aeruginosa strain PAO1. Complementation of gene wzy in trans enabled the mutant PA1RG to produce the normal LPS pattern with long chain O-antigen and restored the susceptibility of PA1RG to phage PaP1 infection. While wzy mutation did not affect bacterial growth, mutant PA1RG exhibited decreased biofilm production, suggesting a fitness cost of PA1 associated with resistance of phage PaP1 predation. This study uncovered the mechanism responsible for PA1RG resistance to phage PaP1 via wzy mutation and revealed the role of phages in regulating bacterial behavior.

Corrigendum: Characterization of the first double-stranded RNA bacteriophage infecting Pseudomonas aeruginosa.

This corrects the article DOI: 10.1038/srep38795.

Characterization and interstrain transfer of prophage pp3 of Pseudomonas aeruginosa.

Prophages are major contributors to horizontal gene transfer and drive the evolution and diversification of bacteria. Here, we describe the characterization of a prophage element designated pp3 in the clinical Pseudomonas aeruginosa isolate PA1. pp3 spontaneously excises from the PA1 genome and circularizes at a very high frequency of 25%. pp3 is likely to be a defective prophage due to its inability to form plaques on P. aeruginosa indicator strains, and no phage particles could be detected in PA1 supernatants. The pp3-encoded integrase is essential for excision by mediating site-specific recombination at the 26-bp attachment sequence. Using a filter mating experiment, we demonstrated that pp3 can transfer into P. aeruginosa recipient strains that do not possess this element naturally. Upon transfer, pp3 integrates into the same attachment site as in PA1 and maintains the ability to excise and circularize. Furthermore, pp3 significantly promotes biofilm formation in the recipient. Sequence alignment reveals that the 26-bp attachment site recognized by pp3 is conserved in all P. aeruginosa strains sequenced to date, making it possible that pp3 could be extensively disseminated in P. aeruginosa. This work improves our understanding of the ways in which prophages influence bacterial behavior and evolution.

An efficient computer-aided structural elucidation strategy for mixtures using an iterative dynamic programming algorithm.

The identification of chemical structures in natural product mixtures is an important task in drug discovery but is still a challenging problem, as structural elucidation is a time-consuming process and is limited by the available mass spectra of known natural products. Computer-aided structure elucidation (CASE) strategies seek to automatically propose a list of possible chemical structures in mixtures by utilizing chromatographic and spectroscopic methods. However, current CASE tools still cannot automatically solve structures for experienced natural product chemists. Here, we formulated the structural elucidation of natural products in a mixture as a computational problem by extending a list of scaffolds using a weighted side chain list after analyzing a collection of 243,130 natural products and designed an efficient algorithm to precisely identify the chemical structures. The complexity of such a problem is NP-complete. A dynamic programming (DP) algorithm can solve this NP-complete problem in pseudo-polynomial time after converting floating point molecular weights into integers. However, the running time of the DP algorithm degrades exponentially as the precision of the mass spectrometry experiment grows. To ideally solve in polynomial time, we proposed a novel iterative DP algorithm that can quickly recognize the chemical structures of natural products. By utilizing this algorithm to elucidate the structures of four natural products that were experimentally and structurally determined, the algorithm can search the exact solutions, and the time performance was shown to be in polynomial time for average cases. The proposed method improved the speed of the structural elucidation of natural products and helped broaden the spectrum of available compounds that could be applied as new drug candidates. A web service built for structural elucidation studies is freely accessible via the following link ( http://csccp.cmdm.tw/ ).

Transcriptomic and Metabolomics Profiling of Phage-Host Interactions between Phage PaP1 and Pseudomonas aeruginosa.

The basic biology of bacteriophage-host interactions has attracted increasing attention due to a renewed interest in the therapeutic potential of bacteriophages. In addition, knowledge of the host pathways inhibited by phage may provide clues to novel drug targets. However, the effect of phage on bacterial gene expression and metabolism is still poorly understood. In this study, we tracked phage-host interactions by combining transcriptomic and metabolomic analyses in Pseudomonas aeruginosa infected with a lytic bacteriophage, PaP1. Compared with the uninfected host, 7.1% (399/5655) of the genes of the phage-infected host were differentially expressed genes (DEGs); of those, 354 DEGs were downregulated at the late infection phase. Many of the downregulated DEGs were found in amino acid and energy metabolism pathways. Using metabolomics approach, we then analyzed the changes in metabolite levels in the PaP1-infected host compared to un-infected controls. Thymidine was significantly increased in the host after PaP1 infection, results that were further supported by increased expression of a PaP1-encoded thymidylate synthase gene. Furthermore, the intracellular betaine concentration was drastically reduced, whereas choline increased, presumably due to downregulation of the choline-glycine betaine pathway. Interestingly, the choline-glycine betaine pathway is a potential antimicrobial target; previous studies have shown that betB inhibition results in the depletion of betaine and the accumulation of betaine aldehyde, the combination of which is toxic to P. aeruginosa. These results present a detailed description of an example of phage-directed metabolism in P. aeruginosa. Both phage-encoded auxiliary metabolic genes and phage-directed host gene expression may contribute to the metabolic changes observed in the host.

Anti-obesity Effect of Capsaicin in Mice Fed with High-Fat Diet Is Associated with an Increase in Population of the Gut Bacterium Akkermansia muciniphila.

Capsaicin (CAP) reduces body weight mainly through activation of transient receptor potential vanilloid 1 (TRPV1) cation channel. However, recent evidence indicates that the gut microbiota influences many physiological processes in host and might provoke obesity. This study determined whether the anti-obesity effect of CAP is related to the changes in gut microbiota. C57BL/6 mice were fed either with high-fat diet (HFD) or HFD with CAP (HFD-CAP) for 9 weeks. We observed a significantly reduced weight gain and improved glucose tolerance in HFD-CAP-fed mice compared with HFD-fed mice. 16S rRNA gene sequencing results showed a decrease of phylum Proteobacteria in HFD-CAP-fed mice. In addition, HFD-CAP-fed mice showed a higher abundance of Akkermansia muciniphila, a mucin-degrading bacterium with beneficial effects on host metabolism. Further studies found that CAP directly up-regulates the expression of Mucin 2 gene Muc2 and antimicrobial protein gene Reg3g in the intestine. These data suggest that the anti-obesity effect of CAP is associated with a modest modulation of the gut microbiota.

Complete Genome Sequences of T1-Like Phages JMPW1 and JMPW2.

We report the complete genome sequences of phages JMPW1 (49,840 bp) and JMPW2 (50,298 bp), two T1-like Escherichia coli phages isolated from contaminated experiment samples. Although the genomes of JMPW1 and JMPW2 share high identity with T1, they show some differences, which are mainly located in several genes with unknown functions and genes encoding tail fiber proteins and endonucleases.

Characterization of the first double-stranded RNA bacteriophage infecting Pseudomonas aeruginosa.

Bacteriophages (phages) are widely distributed in the biosphere and play a key role in modulating microbial ecology in the soil, ocean, and humans. Although the role of DNA bacteriophages is well described, the biology of RNA bacteriophages is poorly understood. More than 1900 phage genomes are currently deposited in NCBI, but only 6 dsRNA bacteriophages and 12 ssRNA bacteriophages genome sequences are reported. The 6 dsRNA bacteriophages were isolated from legume samples or lakes with Pseudomonas syringae as the host. Here, we report the first Pseudomonas aeruginosa phage phiYY with a three-segmented dsRNA genome. phiYY was isolated from hospital sewage in China with the clinical P. aeruginosa strain, PAO38, as a host. Moreover, the dsRNA phage phiYY has a broad host range, which infects 99 out of 233 clinical P. aeruginosa strains isolated from four provinces in China. This work presented a detailed characterization of the dsRNA bacteriophage infecting P. aeruginosa.