Interaction dynamics and virus–host range for estuarine actinophages captured by epicPCR

Sakowski, Eric G.; Arora‐Williams, Keith; Tian, Funing; Zayed, Ahmed A.; Zablocki, Olivier; Sullivan, Matthew B.; Preheim, Sarah P.

doi:10.1038/s41564-021-00873-4

Cited by 35 publications

(40 citation statements)

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“…Improved in silico approaches, such as those based on BLAST similarity, k-mers (such as WIsH (Galiez et al, 2017), HostPhinder (Villarroel et al, 2016)), and VirHostMatcher (Wang et al, 2020)), and CRISPR-Cas (Paez-Espino et al, 2016) have been recently proposed to predict the potential hosts of uncultivated viruses, which still need to be thoroughly tested and benchmarked across a variety of dataset types and sizes. Moreover, predictions from these in silico prediction tools need to be complemented with robustly benchmarked, high-throughput experimental methods, e.g., epicPCR, viral tagging, Hi-C (Deng et al, 2014;Bickhart et al, 2019;Yaffe & Relman, 2020;Sakowski et al, 2021) to validate these predictions.…”

Section: Discussionmentioning

confidence: 99%

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

Pratama

Bolduc

Zayed

et al. 2021

PeerJ

Self Cite

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Background Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). Results The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k-mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k-mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ∼5% for virome and ∼75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. For viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ∼95% (whole genomes) down to ∼80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes. Conclusion Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses ‘hidden’ in diverse sequence datasets.

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Section: Discussionmentioning

confidence: 99%

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

Pratama

Bolduc

Zayed

et al. 2021

PeerJ

Self Cite

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“…Our results first show that epicPCR can complement existing methods in CPR isolation by linking CPR to their hosts in the complex microbial community before cultivation efforts are exerted. As is firstly introduced to link the metabolic potential to phylogenetic markers in an environmental community 27 , epicPCR has also been used to reveal the virus-host interaction network in an estuarine environment 28 . In the present study, we use epicPCR to probe CPR sequences and fuse them with the 16S rRNA gene of its host co-encapsulated in picoliter emulsions, making it ideal for detecting the epibiotic landscope in a complex community.…”

Section: Discussionmentioning

confidence: 99%

“…The epicPCR approach is more straightforward, efficient, and target-oriented than the existing methods. Meanwhile, by simply design and validate a set of concatenation PCR primers, epicPCR can efficiently screen a large number of samples and multiple symbiotic targets at the same time, revealing microbial epibiotic relationships at high throughput 28 .…”

Section: Discussionmentioning

confidence: 99%

EpicPCR-Directed Cultivation of a Candidatus Saccharibacteria Symbiont Reveals a Type IV Pili-dependent Epibiotic Lifestyle

Xie

Wang

Nie

et al. 2021

Preprint

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Candidate phyla radiations (CPR), accounting for a major microbial supergroup with remarkably small genomes and reduced sizes, are widely distributed yet mostly uncultured. Limited culture and its obligate reliance upon other bacteria hindered investigation of their lifestyles. In this work we isolated a CPR bacterium, TM7i, with its host Leucobacter aridocollis J1, by combination of Emulsion, Paired Isolation and Concatenation PCR (epicPCR) detection and filtrate co-culture. Genomic profiling of TM7 genomes and microscopic investigation of TM7i-J1 symbiosis suggest the conservation of type IV pili and a pili-dependent lifestyle of TM7. Further, we observed twitching motility of TM7i mediated by pili and its role played in the interaction with its host. Our results shed a light on the lifestyle about this enigmatic bacterial radiation, which may also be adopted by other CPR organisms. The epicPCR-directed isolation method underlines high efficiency of CPR bacteria isolation and thus may be used in other symbiotic or epibiotic microorganisms.

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“…Fused amplicons, each originating from a single droplet, can then be sequenced to identify the specific virus and host that were co-localized. This method was recently used to link uncultivated phages to their host in a tidal estuary environment [61]. Although the lack of a universal viral marker gene remains an issue for epicPCR, PCR primers can be designed for common viral genes that typically target a broader diversity than fluorescent probes [62].…”

Section: Experimental Approaches To Predict Phage-host Relationshipsmentioning

confidence: 99%

Global overview and major challenges of host prediction methods for uncultivated phages

Coclet

Roux

2021

Current Opinion in Virology

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Highlights Global phage diversity is now primarily explored through cultivation-independent metagenomics  Metagenome-derived phages are typically linked to their host(s) via in silico predictions  Multiple alignment-dependent and alignment-free methods for host predictions have been proposed  Recent integrative approaches combining several methods into a single prediction seem most promising  Eventually, complementary in silico predictions and in vitro assays will enable the reconstruction of entire phage-host networks AbstractBacterial communities play critical roles across all of Earth's biomes, affecting human health and global ecosystem functioning. They do so under strong constraints exerted by viruses, i.e., bacteriophages or "phages". Phages can reshape bacterial communities' structure, influence long-term evolution of bacterial populations, and alter host cell metabolism during infection. Metagenomics approaches, i.e., shotgun sequencing of environmental DNA or RNA, recently enabled large-scale exploration of phage genomic diversity, yielding several millions of phage genomes now to be further analyzed and characterized. One major challenge however is the lack of direct host information for these phages. Several methods and tools have been proposed to bioinformatically predict the potential host(s) of uncultivated phages based only on genome sequence information. Here we review these different approaches and highlight their distinct strengths and limitations. We also outline complementary experimental assays which are being proposed to validate and refine these bioinformatic predictions.

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Interaction dynamics and virus–host range for estuarine actinophages captured by epicPCR

Cited by 35 publications

References 100 publications

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

EpicPCR-Directed Cultivation of a Candidatus Saccharibacteria Symbiont Reveals a Type IV Pili-dependent Epibiotic Lifestyle

Global overview and major challenges of host prediction methods for uncultivated phages

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