ライフサイエンスコーパス: pathosystem

1 these proteins need to be validated in each pathosystem.

2 y improving the current understanding of the pathosystem.

3 each other to promote their own fitness in a pathosystem.

4 enhance our understanding of the tomato-Pst pathosystem.

5 opted for RT-qPCR experiments involving this pathosystem.

6 een driven forward using the U. maydis-maize pathosystem.

7 veral unique aspects of the leafroll disease pathosystem.

8 th which to describe many aspects of a plant pathosystem.

9 en sufficiently to prevent infection in this pathosystem.

10 and biologically relevant management of this pathosystem.

11 ular interactions that define the wheat-rust pathosystem.

12 enhances susceptibility in the investigated pathosystem.

13 g of these processes in a well-defined model pathosystem.

14 st resistance in the Arabidopsis-Pseudomonas pathosystem.

15 oxylipin cross-talk in the Aspergillus-seed pathosystem.

16 ion in the Capsicum-Tobacco etch virus (TEV) pathosystem.

17 st effective strategies for managing the HLB pathosystem.

18 of the well-studied Arabidopsis-Pseudomonas pathosystem.

19 response in an A. thaliana - P. viridiflava pathosystem.

20 entified and characterized in numerous plant pathosystems.

21 strategy may be widely used in Phytophthora pathosystems.

22 fulvum and tomato, and related gene-for-gene pathosystems.

23 ve been identified for even the best-studied pathosystems.

24 imal roguing schedule-are applicable to many pathosystems.

25 requires careful matching of antagonists to pathosystems.

26 ions, are rapid compared with other arboreal pathosystems.

27 ng detection accuracies exceeding 92% across pathosystems.

28 ed molecular and virulence phenotypes in all pathosystems.

29 ntially enhances disease symptoms in diverse pathosystems.

30 mpetent for bacterial transmission varies by pathosystems.

31 ted by predicting disease development in new pathosystems.

32 s tools for epidemiological studies on other pathosystems.

33 erformed poorly in distantly related nonhost pathosystems.

34 to other characterized interactions in this pathosystem, a compatible Snn3-D1-SnTox3 interaction was

35 p/Arabidopsis interactions as a useful model pathosystem, allowing for application of the vast genomi

36 hts into microbial interactions in non-model pathosystems and contributes to the development of new f

37 The complexity of forest pathosystems and the limitations of genetic analysis, ba

38 cation of this method to various Arabidopsis pathosystems and the wealth of available disease resista

39 We established duckweed-Pseudomonas pathosystems and used growth curves and microscopy to ch

40 Many pathosystems are not accessible for genetic amendments o

41 s are studied as pathosystem components, and pathosystems are studied for their emergent properties.

42 (2) Agricultural plant pathosystems are the focus of research on endophyte dise

43 he information needed to manage a particular pathosystem at an acceptable financial risk; details of

44 We established a pathosystem between the nonvascular plant Marchantia pol

45 ented were based on the BCTV-beet leafhopper pathosystem, but the approach taken (combination of expe

46 The P. ananatis-onion pathosystem can be modeled as a chemical arms race of pa

47 Concepts and approaches developed in this pathosystem can guide future efforts when responding to

48 es and can be easily adapted to various crop pathosystems characterized by airborne inoculum.

49 gy in which virulence factors are studied as pathosystem components, and pathosystems are studied for

50 We show that in the pathosystem considered here, in general large stochastic

51 This naturally coevolving pathosystem contains an amazing level of genetic diversi

52 In the citrus-CTV pathosystem, deletion of the p33 open reading frame in a

53 anipulation syndromes comprehensively within pathosystems, expanding the taxonomic and genetic breadt

54 phic pathogens and their hosts has generated pathosystems featuring extreme complexity and apparent r

55 This novel floral pathosystem for Arabidopsis appears to be highly represe

56 ve population and developed into an in vitro pathosystem for N. attenuata.

57 ys) with Colletotrichum graminicola, a model pathosystem for the study of hemibiotrophy.

58 This pathosystem has allowed us to exploit N. benthamiana as

59 The rice blast pathosystem has been the subject of intense interest in

60 vide evidence that this natural plant-fungus pathosystem has conditionally mutualistic features.

61 Only a few studies, with even fewer pathosystems, have explored non-persistent (NP) virus-ve

62 ew of dynamic interactions in the tripartite pathosystem.IMPORTANCE The ascomycete Cryphonectria para

63 grees of disease control for a wide range of pathosystems, including crops with large plants, and pat

64 The tripartite chestnut/C. parasitica/virus pathosystem involves the dynamic interactions of their g

65 The wheat-Parastagonospora nodorum pathosystem involves the recognition of pathogen-secrete

66 We first developed a pathosystem involving the infection of Arabidopsis acces

67 agricultural crops, the co-evolved pine-rust pathosystem is characterized by steady-state dynamics an

68 suggests that the Stagonospora nodorum-wheat pathosystem is controlled by host-selective toxins (HSTs

69 ilds on the notion that the S. nodorum-wheat pathosystem is largely based on multiple host-toxin inte

70 resistance in this endemic coevolved forest pathosystem is not exclusively polygenic.

71 r basis of gene-for-gene recognition in this pathosystem is the direct physical interaction of the Pt

72 evant tomato-Pseudomonas syringae pv. tomato pathosystem is widely used to explore and understand the

73 As these two pathosystems may co-occur, we studied whether the presen

74 The C. elegans-Orsay virus pathosystem provides a powerful model for investigating

75 A genetically tractable model plant pathosystem, Pseudomonas syringae pv. tomato DC3000 on t

76 dvances in scientific understanding of virus pathosystems, rapid technological innovation, innovative

77 Within a specific pathosystem, refuge size can be estimated in experiments

78 tute of Allergy and Infectious Diseases, the Pathosystems Resource Integration Center (PATRIC) is a g

79 The PathoSystems Resource Integration Center (PATRIC) is one

80 The Pathosystems Resource Integration Center (PATRIC) is the

81 The Pathosystems Resource Integration Center (PATRIC) is the

82 climate variables on infection rates, though pathosystem-specific characteristics make synthesis chal

83 logical functions with obvious roles in this pathosystem, such as biofilm formation, antibiotic metab

84 exhibit less variable gene expression in our pathosystem than previously used genes.

85 of new, unexplored areas of research in this pathosystem that can help identify evolutionarily suscep

86 Here, we describe a novel pathosystem that consists of epitope-tagged Bs2-expressi

87 al importance of endophytes in natural plant pathosystems that are fundamental to biodiversity and co

88 miological characteristics of diverent viral pathosystems, there is no one-size-fits-all approach tow

89 us contorta in the Lophodermella needle cast pathosystem through metabarcoding and metatranscriptomic

90 apply high-throughput RNA sequencing to this pathosystem to identify genes whose expression changes s

91 apsicum annum (pepper)-Xanthomonas perforans pathosystem to investigate the impact of elevated O(3) (

92 We used an Arabidopsis/Pseudomonas syringae pathosystem to investigate the impact of pathogen-induce

93 ome sequence indicate the potential for this pathosystem to serve as a toxin-based, inverse gene-for-

94 To create a robust pathosystem to study AvrBsT immunity in Arabidopsis, the

95 We characterized a Medicago truncatula-ASR pathosystem to study molecular mechanisms of nonhost res

96 olecular plant-microbe interactions for this pathosystem to tailor disease management strategies.

97 Here we used the Arabidopsis-B. cinerea pathosystem to test how plant host and fungal pathogen i

98 mbined with ecological studies in wild plant pathosystems to determine whether disease-modifying fung

99 ingspot virus (CIRV) - Nicotiana benthamiana pathosystems to identify biomolecular condensate formati

100 d leaf physiological functions in citrus HLB pathosystem under shade, and reveal the mechanistic basi

101 s has often been studied in model nonnatural pathosystems under controlled conditions.

102 the establishment of a new biotrophic model pathosystem: Ustilago bromivora and Brachypodium sp.

103 rticillium interactions, we have developed a pathosystem utilizing Arabidopsis thaliana and an isolat

104 gered susceptibility in the wheat-P. nodorum pathosystem vary in their effects depending on the genet

105 Liberibacter solanacearum" (CLso) pathosystem was investigated to dissect CLso-prophage in

106 r beet) cyst nematode (Heterodera schachtii) pathosystem, we have determined that the two Arabidopsis

107 Arabidopsis thaliana-Pseudomonas aeruginosa pathosystem, we provide evidence that SA acts directly o

108 Using a model pathosystem, we studied hitherto cryptic interactions be

109 Machine learning models trained on one pathosystem where then validated by predicting disease d

110 in the "Ca Liberibacter asiaticus"-prophage pathosystem, which maintains the lysogenic cycle in Asia

111 nt role in defense in the G. max-H. glycines pathosystem, with some of the spatially and temporally r

112 ongbing (HLB) is the most destructive citrus pathosystem worldwide.

113 plant disease across a broad range of plant pathosystems, yet simultaneously reveals that complexity