Meningococcal Disease-Associated Prophage-Like Elements Are Present in Neisseria gonorrhoeae and Some Commensal Neisseria Species

Suwayyid, Barakat A Al; Rankine-Wilson, Leah; Speers, David; Wise, Michael J.; Coombs, Geoffrey W.; Kahler, Charlene M.

doi:10.1093/gbe/evaa023

Cited by 14 publications

(17 citation statements)

References 37 publications

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“…Specifically, we focused on predictions that are significantly more highly targeted than the backbone, which are more likely to be actual prophages. Consistent with previous findings (33, 34), our results suggest that many known and predicted phages may be able to infect multiple species of Neisseria , including species that are distantly related.…”

Section: Discussionsupporting

confidence: 92%

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Prediction of prophages and their host ranges in pathogenic and commensal Neisseria species

Orazi

Collins

Whitaker

2021

Preprint

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The genus Neisseria includes two pathogenic species, N. gonorrhoeae and N. meningitidis, and numerous commensal species. Neisseria species frequently exchange DNA with one other, primarily via transformation and homologous recombination, and via multiple types of mobile genetic elements (MGEs). Few Neisseria bacteriophages (phages) have been identified and their impact on bacterial physiology is poorly understood. Furthermore, little is known about the range of species that Neisseria phages can infect. In this study, we used three virus prediction tools to scan 248 genomes of 21 different Neisseria species and identified 1302 unique predicted prophages. Using comparative genomics, we found that many predictions are dissimilar from other prophages and MGEs previously described to infect Neisseria species. We also identified similar predicted prophages in genomes of different Neisseria species. Additionally, we examined CRISPR-Cas targeting of each Neisseria genome and predicted prophage. While CRISPR targeting of chromosomal DNA appears to be common among several Neisseria species, we found that 20% of the prophages we predicted are targeted significantly more than the rest of the bacterial genome in which they were identified (i.e., backbone). Furthermore, many predicted prophages are targeted by CRISPR spacers encoded by other species. We then used these results to infer additional host species of known Neisseria prophages and predictions that are highly targeted relative to the backbone. Together, our results suggest that we have identified novel Neisseria prophages, several of which may infect multiple Neisseria species. These findings have important implications for understanding horizontal gene transfer between members of this genus.IMPORTANCEDrug-resistant N. gonorrhoeae is a major threat to human health. Commensal Neisseria species are thought to serve as reservoirs of antibiotic resistance and virulence genes for the pathogenic species N. gonorrhoeae and N. meningitidis. Therefore, it is important to understand both the diversity of mobile genetic elements (MGEs) that can mediate horizontal gene transfer within this genus, and the breadth of species these MGEs can infect. In particular, few bacteriophages (phages) have been identified and characterized in Neisseria species. In this study, we identified a large number of candidate phages integrated within the genomes of commensal and pathogenic Neisseria species, many of which appear to be novel phages. Importantly, we discovered extensive interspecies targeting of predicted phages by Neisseria CRISPR-Cas systems, which may reflect their movement between different species. Uncovering the diversity and host range of phages is essential for understanding how they influence the evolution of their microbial hosts.

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Section: Discussionsupporting

confidence: 92%

“…With the exception of MDAΦ, the impact of phages on Neisseria biology and pathogenicity remains poorly understood (13). Furthermore, few studies have investigated the host ranges of Neisseria phages (33, 34).…”

Section: Introductionmentioning

confidence: 99%

Prediction of prophages and their host ranges in pathogenic and commensal Neisseria species

Orazi

Collins

Whitaker

2021

Preprint

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“…The performance of the tools to identify phages that infect genera such as Neisseria (0.23), Brevibacterium (0.30), and Mesorhizobium (0.33) dropped substantially. Detecting the presence of Neisseria phage and prophage may be important for a diagnostic of invasive meningococcal disease as prophage-like elements are commonly found throughout the Neisseria genera [ 49 ]. The results of the tools on individual genera are meant to demonstrate the variability of tool performance on different genera of phage.…”

Section: Discussionmentioning

confidence: 99%

Simulation study and comparative evaluation of viral contiguous sequence identification tools

2021

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Background Viruses, including bacteriophages, are important components of environmental and human associated microbial communities. Viruses can act as extracellular reservoirs of bacterial genes, can mediate microbiome dynamics, and can influence the virulence of clinical pathogens. Various targeted metagenomic analysis techniques detect viral sequences, but these methods often exclude large and genome integrated viruses. In this study, we evaluate and compare the ability of nine state-of-the-art bioinformatic tools, including Vibrant, VirSorter, VirSorter2, VirFinder, DeepVirFinder, MetaPhinder, Kraken 2, Phybrid, and a BLAST search using identified proteins from the Earth Virome Pipeline to identify viral contiguous sequences (contigs) across simulated metagenomes with different read distributions, taxonomic compositions, and complexities. Results Of the tools tested in this study, VirSorter achieved the best F1 score while Vibrant had the highest average F1 score at predicting integrated prophages. Though less balanced in its precision and recall, Kraken2 had the highest average precision by a substantial margin. We introduced the machine learning tool, Phybrid, which demonstrated an improvement in average F1 score over tools such as MetaPhinder. The tool utilizes machine learning with both gene content and nucleotide features. The addition of nucleotide features improves the precision and recall compared to the gene content features alone.Viral identification by all tools was not impacted by underlying read distribution but did improve with contig length. Tool performance was inversely related to taxonomic complexity and varied by the phage host. For instance, Rhizobium and Enterococcus phages were identified consistently by the tools; whereas, Neisseria prophage sequences were commonly missed in this study. Conclusion This study benchmarked the performance of nine state-of-the-art bioinformatic tools to identify viral contigs across different simulation conditions. This study explored the ability of the tools to identify integrated prophage elements traditionally excluded from targeted sequencing approaches. Our comprehensive analysis of viral identification tools to assess their performance in a variety of situations provides valuable insights to viral researchers looking to mine viral elements from publicly available metagenomic data.

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“…We also used a novel computational search engine, Phaser, which examined translated ORFs to identify LOF loci by any mechanism. The model presented here has many limitations, including the observation that known virulence loci that have multiple copies (pilin, opacity proteins, phages to name a few) could not be included in this analysis as they are not assembled accurately or frequently in unclosed genomes [86,90]. This model did not attempt to examine changes in function attributed to allelic variation, which is known to affect endotoxin structure [67,91] and anaerobic respiration [92].…”

Section: Discussionmentioning

confidence: 99%

Modelling evolutionary pathways for commensalism and hypervirulence in Neisseria meningitidis

et al. 2021

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Neisseria meningitidis , the meningococcus, resides exclusively in humans and causes invasive meningococcal disease (IMD). The population of N. meningitidis is structured into stable clonal complexes by limited horizontal recombination in this naturally transformable species. N. meningitidis is an opportunistic pathogen, with some clonal complexes, such as cc53, effectively acting as commensal colonizers, while other genetic lineages, such as cc11, are rarely colonizers but are over-represented in IMD and are termed hypervirulent. This study examined theoretical evolutionary pathways for pathogenic and commensal lineages by examining the prevalence of horizontally acquired genomic islands (GIs) and loss-of-function (LOF) mutations. Using a collection of 4850 genomes from the BIGSdb database, we identified 82 GIs in the pan-genome of 11 lineages (10 hypervirulent and one commensal lineage). A new computational tool, Phaser, was used to identify frameshift mutations, which were examined for statistically significant association with genetic lineage. Phaser identified a total of 144 frameshift loci of which 105 were shown to have a statistically significant non-random distribution in phase status. The 82 GIs, but not the LOF loci, were associated with genetic lineage and invasiveness using the disease carriage ratio metric. These observations have been integrated into a new model that infers the early events of the evolution of the human adapted meningococcus. These pathways are enriched for GIs that are involved in modulating attachment to the host, growth rate, iron uptake and toxin expression which are proposed to increase competition within the meningococcal population for the limited environmental niche of the human nasopharynx. We surmise that competition for the host mucosal surface with the nasopharyngeal microbiome has led to the selection of isolates with traits that enable access to cell types (non-phagocytic and phagocytic) in the submucosal tissues leading to an increased risk for IMD.

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Meningococcal Disease-Associated Prophage-Like Elements Are Present in Neisseria gonorrhoeae and Some Commensal Neisseria Species

Cited by 14 publications

References 37 publications

Prediction of prophages and their host ranges in pathogenic and commensal Neisseria species

Prediction of prophages and their host ranges in pathogenic and commensal Neisseria species

Simulation study and comparative evaluation of viral contiguous sequence identification tools

Modelling evolutionary pathways for commensalism and hypervirulence in Neisseria meningitidis

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