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Molecular Plant Pathology Jan 2009Successful host-pathogen interactions require the presence, maintenance and expression of gene cassettes called 'pathogenicity islands' (PAIs) and 'metabolic islands'... (Review)
Review
Successful host-pathogen interactions require the presence, maintenance and expression of gene cassettes called 'pathogenicity islands' (PAIs) and 'metabolic islands' (MAIs) in the respective pathogen. The products of these genes confer on the pathogen the means to recognize their host(s) and to efficiently evade host defences in order to colonize, propagate within the host and eventually disseminate from the host. Virulence effectors secreted by type III and type IV secretion systems, among others, play vital roles in sustaining pathogenicity and optimizing host-pathogen interactions. Complete genome sequences of plant pathogenic bacteria have revealed the presence of PAIs and MAIs. The genes of these islands possess mosaic structures with regions displaying differences in nucleotide composition and codon usage in relation to adjacent genome structures, features that are highly suggestive of their acquisition from a foreign donor. These donors can be other bacteria, as well as lower members of the Archaea and Eukarya. Genes that have moved from the domains Archaea and Eukarya to the domain Bacteria are true cases of horizontal gene transfer. They represent interdomain genetic transfer. Genetic exchange between distinct members of the domain Bacteria, however, represents lateral gene transfer, an intradomain event. Both horizontal and lateral gene transfer events have been used to facilitate survival fitness of the pathogen.
Topics: Bacteria; Gene Transfer, Horizontal; Genes, Plant; Plants; Virulence
PubMed: 19161360
DOI: 10.1111/j.1364-3703.2008.00518.x -
Environmental Microbiology Dec 2020In Fusarium oxysporum f.sp. lycopersici, all effector genes reported so far - also called SIX genes - are located on a single accessory chromosome which is required for...
In Fusarium oxysporum f.sp. lycopersici, all effector genes reported so far - also called SIX genes - are located on a single accessory chromosome which is required for pathogenicity and can also be horizontally transferred to another strain. To narrow down the minimal region required for virulence, we selected partial pathogenicity chromosome deletion strains by fluorescence-assisted cell sorting of a strain in which the two arms of the pathogenicity chromosome were labelled with GFP and RFP respectively. By testing the virulence of these deletion mutants, we show that the complete long arm and part of the short arm of the pathogenicity chromosome are not required for virulence. In addition, we demonstrate that smaller versions of the pathogenicity chromosome can also be transferred to a non-pathogenic strain and they are sufficient to turn the non-pathogen into a pathogen. Surprisingly, originally non-pathogenic strains that had received a smaller version of the pathogenicity chromosome were much more aggressive than recipients with a complete pathogenicity chromosome. Whole genome sequencing analysis revealed that partial deletions of the pathogenicity chromosome occurred mainly close to repeats, and that spontaneous duplication of sequences in accessory regions is frequent both in chromosome deletion strains and in horizontal transfer strains.
Topics: Chromosome Deletion; Chromosomes, Fungal; Fusarium; Green Fluorescent Proteins; Luminescent Proteins; Plant Diseases; Transcription Factors; Virulence; Red Fluorescent Protein
PubMed: 32452643
DOI: 10.1111/1462-2920.15095 -
BMC Bioinformatics Jun 2022The human body is inhabited by a diverse community of commensal non-pathogenic bacteria, many of which are essential for our health. By contrast, pathogenic bacteria...
BACKGROUND
The human body is inhabited by a diverse community of commensal non-pathogenic bacteria, many of which are essential for our health. By contrast, pathogenic bacteria have the ability to invade their hosts and cause a disease. Characterizing the differences between pathogenic and commensal non-pathogenic bacteria is important for the detection of emerging pathogens and for the development of new treatments. Previous methods for classification of bacteria as pathogenic or non-pathogenic used either raw genomic reads or protein families as features. Using protein families instead of reads provided a better interpretability of the resulting model. However, the accuracy of protein-families-based classifiers can still be improved.
RESULTS
We developed a wide scope pathogenicity classifier (WSPC), a new protein-content-based machine-learning classification model. We trained WSPC on a newly curated dataset of 641 bacterial genomes, where each genome belongs to a different species. A comparative analysis we conducted shows that WSPC outperforms existing models on two benchmark test sets. We observed that the most discriminative protein-family features in WSPC are widely spread among bacterial species. These features correspond to proteins that are involved in the ability of bacteria to survive and replicate during an infection, rather than proteins that are directly involved in damaging or invading the host.
Topics: Bacteria; Genome, Bacterial; Genomics; Humans; Machine Learning; Phylogeny; Virulence
PubMed: 35751023
DOI: 10.1186/s12859-022-04777-w -
APMIS : Acta Pathologica,... 2004Pathogenicity islands (PAIs) are a distinct class of genomic islands (GEIs), which are acquired by horizontal gene transfer. PAIs harbour virulence genes and some, in... (Review)
Review
Pathogenicity islands (PAIs) are a distinct class of genomic islands (GEIs), which are acquired by horizontal gene transfer. PAIs harbour virulence genes and some, in addition, antibiotic resistance genes. More often genes conferring antibiotic resistance are encoded by GEIs not containing virulence genes. Both types of genetic elements are found in genomes of various human, animal and plant pathogens. There are PAIs and GEIs which are specific for a certain serotype(s), strain, or pathotype of a species. Furthermore, there are also PAIs which are more widespread and found in bacterial pathogens causing a certain pathogenic effect in the host. Even the lack of a certain PAI might be characteristic for a defined subspecies. Obviously, PAIs can be used as markers for diagnostic purposes to help identify a certain bacterial pathogen, subtype it, estimate the pathogenic potential, and in some cases predict its antibiotic resistance. This all might be achieved for known PAIs/GEIs without cultivating the microorganism of interest by employing PCR and/or DNA-chip technology. Even yet unknown PAIs can be identified in silico if the genome sequence of the bacterial pathogen under investigation is known. The more PAIs and antibiotic harbouring GEIs are identified and characterized the greater will be the benefits also for diagnostics.
Topics: Bacteria; Bacterial Infections; Drug Resistance, Bacterial; Genome, Bacterial; Genomic Islands; Genomics; Humans; Virulence
PubMed: 15638844
DOI: 10.1111/j.1600-0463.2004.apm11211-1214.x -
[Isolation, identification, and pathogenicity research of brown rot pathogens from Gastrodia elata].Zhongguo Zhong Yao Za Zhi = Zhongguo... May 2022Brown rot is a common disease in the cultivation and production of Gastrodia elata, but its pathogens have not been fully revealed. In this study, the pathogenic fungi...
Brown rot is a common disease in the cultivation and production of Gastrodia elata, but its pathogens have not been fully revealed. In this study, the pathogenic fungi were isolated and purified from tubers of 77 G. elata samples with brown rot. Pathogens were identified by the pathogenicity test and morphological and molecular identification. The pathogenicity of each pathogen and its inhibitory effects on Armillaria gallica were compared. The results showed that 119 strains of fungi were isolated from tubers of G. elata infected with brown rot. Among them, the frequency of separation of Ilyonectria fungi was as high as 42.01%. The pathogenicity test showed that the pathogenicity characteristics of six strains of fungi were consistent with the natural symptoms of brown rot in G. elata. The morphological and molecular identification results showed that the six strains belonged to I. cyclaminicola and I. robusta in the Nectriaceae family of Sordariomycetes class, respectively. Both types of fungi could produce pigments, conidia, and chlamycospore, and the growth rate of I. cyclaminicola was significantly higher than that of I. robusta. The comparison of pathogenicity showed that the spots formed by I. cyclaminicola inoculation were significantly larger than those of I. robusta inoculation, suggesting I. cyclaminicola was superior to I. robusta in pathogenicity. The results of confrontation culture showed that I. cyclaminicola and I. robusta could signi-ficantly inhibit the germination and cordage growth of A. gallica. A. gallica also inhibited the growth of pathogens, and I. cyclaminicola was less inhibited as compared with I. robusta. The results of this study revealed for the first time that I. cyclaminicola and I. robusta were the pathogens responsible for G. elata brown rot.
Topics: Fungi; Gastrodia; Plant Tubers; Spores, Fungal; Virulence
PubMed: 35531674
DOI: 10.19540/j.cnki.cjcmm.20220223.102 -
PloS One 2012The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene...
The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1) deviations in codon usage, G+C content or dinucleotide frequency and (2) insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS). In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands.
Topics: Bacteria; Bacterial Infections; Computational Biology; Genome, Bacterial; Genomic Islands; Software; Virulence
PubMed: 22355329
DOI: 10.1371/journal.pone.0030848 -
Phytopathology Mar 2022Since 2016, devastating bacterial blotch affecting the fruiting bodies of , , , and in China has caused severe economic losses. We isolated 102 bacterial strains and...
Since 2016, devastating bacterial blotch affecting the fruiting bodies of , , , and in China has caused severe economic losses. We isolated 102 bacterial strains and characterized them polyphasically. We identified the causal agent as and confirmed the pathogenicity of the strains. A host range test further confirmed the pathogen's ability to infect multiple hosts. This is the first report in China of bacterial blotch in . caused by . . Whole-genome sequences were generated for three strains: Pt11 (6.48 Mb), Pt51 (6.63 Mb), and Pt53 (6.80 Mb), and pangenome analysis was performed with 13 other publicly accessible . genomes to determine their genetic diversity, virulence, antibiotic resistance, and mobile genetic elements. The pangenome of . is open, and many more gene families are likely to emerge with further genome sequencing. Multilocus sequence analysis using the sequences of four common housekeeping genes (, , , and ) showed high genetic variability among the . strains, with 115 strains clustered into a monophyletic group. The . strains possess various genes for secretion systems, virulence factors, carbohydrate-active enzymes, toxins, secondary metabolites, and antimicrobial resistance genes that are associated with pathogenesis and adapted to different environments. The myriad of insertion sequences, integrons, prophages, and genome islands encoded in the strains may contribute to genome plasticity, virulence, and antibiotic resistance. These findings advance understanding of the determinants of virulence, which can be targeted for the effective control of bacterial blotch disease.
Topics: Genomics; Phylogeny; Plant Diseases; Pseudomonas; Virulence
PubMed: 34293910
DOI: 10.1094/PHYTO-12-20-0550-R -
Proceedings of the National Academy of... Apr 2022Bacterial pathogen identification, which is critical for human health, has historically relied on culturing organisms from clinical specimens. More recently, the...
Bacterial pathogen identification, which is critical for human health, has historically relied on culturing organisms from clinical specimens. More recently, the application of machine learning (ML) to whole-genome sequences (WGSs) has facilitated pathogen identification. However, relying solely on genetic information to identify emerging or new pathogens is fundamentally constrained, especially if novel virulence factors exist. In addition, even WGSs with ML pipelines are unable to discern phenotypes associated with cryptic genetic loci linked to virulence. Here, we set out to determine if ML using phenotypic hallmarks of pathogenesis could assess potential pathogenic threat without using any sequence-based analysis. This approach successfully classified potential pathogenetic threat associated with previously machine-observed and unobserved bacteria with 99% and 85% accuracy, respectively. This work establishes a phenotype-based pipeline for potential pathogenic threat assessment, which we term PathEngine, and offers strategies for the identification of bacterial pathogens.
Topics: Bacteria; Genome, Bacterial; Machine Learning; Phenotype; Virulence; Virulence Factors; Whole Genome Sequencing
PubMed: 35363569
DOI: 10.1073/pnas.2112886119 -
Current Opinion in Plant Biology Aug 2010It was generally considered that necrotrophic plant pathogenic fungi possessed simplistic pathogenic mechanisms being typically reliant on 'blasting their way through... (Review)
Review
It was generally considered that necrotrophic plant pathogenic fungi possessed simplistic pathogenic mechanisms being typically reliant on 'blasting their way through host tissue with a battery of lytic and degradative enzymes. However recent studies have suggested that this is not true and that necrotrophic fungal pathogens can subtly manipulate the host during infection in a manner similar to biotrophic pathogens. For example, it has been demonstrated that the wheat pathogens Stagonospora nodorum and Pyrenophora triticirepentis secrete small unique proteins (effectors) that are internalised by host cells and interact with the host in a gene-for-gene relationship to initiate disease, albeit in an inverse manner compared to biotrophs. This paper reviews recent developments in necrotrophic fungal pathogenicity throughout a critical period that arguably saw this field come of age.
Topics: Evolution, Molecular; Fungi; Necrosis; Plant Diseases; Virulence; Virulence Factors
PubMed: 20684067
DOI: No ID Found -
Annual Review of Microbiology Sep 2022is a globally distributed, lethal pathogen of humans. The virulence armamentarium of appears to have been developed on a scaffold of antiphagocytic defenses found... (Review)
Review
is a globally distributed, lethal pathogen of humans. The virulence armamentarium of appears to have been developed on a scaffold of antiphagocytic defenses found among diverse, mostly free-living species of . Pathoadaptation was further aided by the modularity, flexibility, and interactivity characterizing mycobacterial effectors and their regulators. During emergence of , novel genetic material was acquired, created, and integrated with existing tools. The major mutational mechanisms underlying these adaptations are discussed in this review, with examples. During its evolution, lost the ability and/or opportunity to engage in lateral gene transfer, but despite this it has retained the adaptability that characterizes mycobacteria. exemplifies the evolutionary genomic mechanisms underlying adoption of the pathogenic niche, and studies of its evolution have uncovered a rich array of discoveries about how new pathogens are made.
Topics: Evolution, Molecular; Gene Transfer, Horizontal; Humans; Mycobacterium tuberculosis; Tuberculosis; Virulence; Virulence Factors
PubMed: 35709500
DOI: 10.1146/annurev-micro-121321-093031