Evaluation of viral genome assembly and diversity estimation in deep metagenomes

Background

Viruses have unique properties, small genome and regions of high similarity, whose effects on metagenomic assemblies have not been characterized so far. This study uses diverse in silico simulated viromes to evaluate how extensively genomes can be assembled using different sequencing platforms and assemblers. Further, it investigates the suitability of different methods to estimate viral diversity in metagenomes.

Results

We created in silico metagenomes mimicking various platforms at different sequencing depths. The CLC assembler revealed subpar compared to IDBA_UD and CAMERA , which are metagenomic-specific. Up to a saturation point, Illumina platforms proved more capable of reconstructing large portions of viral genomes compared to 454. Read length was an important factor for limiting chimericity, while scaffolding marginally improved contig length and accuracy. The genome length of the various viruses in the metagenomes did not significantly affect genome reconstruction, but the co-existence of highly similar genomes was detrimental. When evaluating diversity estimation tools, we found that PHACCS results were more accurate than those from CatchAll and clustering, which were both orders of magnitude above expected.

Conclusions

Assemblers designed specifically for the analysis of metagenomes should be used to facilitate the creation of high-quality long contigs. Despite the high coverage possible, scientists should not expect to always obtain complete genomes, because their reconstruction may be hindered by co-existing species bearing highly similar genomic regions. Further development of metagenomics-oriented assemblers may help bypass these limitations in future studies. Meanwhile, the lack of fully reconstructed communities keeps methods to estimate viral diversity relevant. While none of the three methods tested had absolute precision, only PHACCS was deemed suitable for comparative studies.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-989) contains supplementary material, which is available to authorized users.     

山东省嘉祥县鼠类肠道病毒组分析

鼠类是重要的病毒储存库和多种病毒的自然宿主,是对人类病毒传播极具威胁的野生动物之一,因此对鼠类携带病毒进行研究并挖掘其携带新病毒对于病毒病的防治具有重要意义。本研究于2016年在山东省嘉祥县采集99只褐家鼠、仓鼠和黑线姬鼠肠道内容物,通过高通量测序对其病毒组成进行研究。分析结果显示,采集的鼠类样本携带病毒主要包括冠状病毒科、呼肠孤病毒科、星状病毒科、小RNA病毒科、小双节病毒科、圆环病毒科、细小病毒科等。挑选可能与疾病相关的病毒进行进一步的序列分析和进化分析。分析结果显示,本研究中发现的冠状病毒为甲型冠状病毒属,与中国浙江发现的Lucheng-19病毒株和英国UKRn3病毒株具有共同祖先;本研究还发现包括Rosavirus、Rabovirus和Kobuvirus三个种在内的6株小RNA病毒科病毒,其中Rabovirus包含4株序列差异较大的病毒株,表明小RNA病毒在鼠类中具有丰富的基因多样性。研究发现该地区鼠类中同时流行多株星状病毒,表明极其丰富的基因多样性,系统发育分析显示,其中1株与猪的星状病毒4型聚在一起,提示可能的跨种传播。此外,样本中发现一株G3P[3]型A组轮状病毒,其VP4和VP7基因与猴的病毒株具有90%左右核苷酸同源性,而其余片段与鼠类的片段同源性最高,说明该病毒株可能是一株猴-鼠重配病毒株。本研究的鼠类病毒组数据为我国提供更丰富的本底资料,为我国应对相关的新发传染病提供了基础数据支持。     

Prediction of the Receptorome for the Human-Infecting Virome

The virus receptors are key for the viral infection of host cells. Identification of the virus receptors is still challenging at present. Our previous study has shown that human virus receptor proteins have some unique features including high N-glycosylation level, high number of interaction partners and high expression level. Here, a random-forest model was built to identify human virus receptorome from human cell membrane proteins with an accepted accuracy based on the combination of the unique features of human virus receptors and protein sequences. A total of 1424 human cell membrane proteins were predicted to constitute the receptorome of the human-infecting virome. In addition, the combination of the random-forest model with protein–protein interactions between human and viruses predicted in previous studies enabled further prediction of the receptors for 693 human-infecting viruses, such as the enterovirus, norovirus and West Nile virus.Finally, the candidate alternative receptors of the SARS-Co V-2 were also predicted in this study. As far as we know, this study is the first attempt to predict the receptorome for the human-infecting virome and would greatly facilitate the identification of the receptors for viruses.     

PHISDetector: A Tool to Detect Diverse In Silico Phage–host Interaction Signals for Virome Studies

Phage–microbe interactions are appealing systems to study coevolution, and have also been increasingly emphasized due to their roles in human health, disease, and the development of novel therapeutics. Phage–microbe interactions leave diverse signals in bacterial and phage genomic sequences, defined as phage–host interaction signals (PHISs), which include clustered regularly interspaced short palindromic repeats (CRISPR) targeting, prophage, and protein–protein interaction signals. In the present study, we developed a novel tool phage–host interaction signal detector (PHISDetector) to predict phage–host interactions by detecting and integrating diverse in silico PHISs, and scoring the probability of phage–host interactions using machine learning models based on PHIS features. We evaluated the performance of PHISDetector on multiple benchmark datasets and application cases. When tested on a dataset of 758 annotated phage–host pairs, PHISDetector yields the prediction accuracies of 0.51 and 0.73 at the species and genus levels, respectively, outperforming other phage–host prediction tools. When applied to on 125,842 metagenomic viral contigs (mVCs) derived from 3042 geographically diverse samples, a detection rate of 54.54% could be achieved. Furthermore, PHISDetector could predict infecting phages for 85.6% of 368 multidrug-resistant (MDR) bacteria and 30% of 454 human gut bacteria obtained from the National Institutes of Health (NIH) Human Microbiome Project (HMP). The PHISDetector can be run either as a web server (http://www.microbiome-bigdata.com/PHISDetector/) for general users to study individual inputs or as a stand-alone version (https://github.com/HIT-ImmunologyLab/PHISDetector) to process massive phage contigs from virome studies.     

Comparison of Viromes in Ticks from Different Domestic Animals in China

Ticks are involved in the transmission of various arboviruses and some tick-borne viruses pose significant threats to the health of humans or livestock. This study aimed to investigate the geographical distribution of tick species and tickassociated viruses in central and eastern China. Total 573 ticks from domestic animals including dogs, sheep and cattle were collected in 2017. Two genera of ticks were identified including Rhipicephalus and Haemaphysalis. Sequencing was performed on Miseq Illumina platform to characterize the tick viromes from the four different sampling locations.Following trimming, 13,640 reads were obtained and annotated to 19 virus families. From these sequences, above 37.74% of the viral reads were related to the RNA viruses. Virome comparison study revealed that the tick viral diversity was considerably different in the two identified tick genera. The viral diversity of R. microplus was significantly different from that of other Rhipicephalus species. On the other hand, substantial overlap in viral species was observed between the same genera. In addition, we found no evidence that the natural host played a major role in shaping virus diversity based on the comparison of their viromes. Rather, the geographic location seems to significantly influence the viral families. Phylogenetic study indicated that the novel negative-sense RNA viruses identified in this study was closely related to Bole tick virus 1 and 3 viruses. In conclusion, the present study provides a baseline for comparing viruses detected in ticks, according to species, natural hosts, and geographic locations.     

Comparative Metagenomic Profiling of Viromes Associated with Four Common Mosquito Species in China

Vast viruses are thought to be associated with mosquitoes. Anopheles sinensis, Armigeres subalbatus, Culex quinquefasciatus, and Culex tritaeniorhynchus are very common mosquito species in China, and whether the virome structure in each species is species-specific has not been evaluated. In this study, a total of 2222 mosquitoes were collected from the same geographic location, and RNAs were sequenced using the Illumina Miseq platform. After querying to the Refseq database, a total of 3,435,781, 2,223,509, 5,727,523, and 6,387,867 paired-end reads were classified under viral sequences from An. sinensis, Ar. subalbatus, Cx. quinquefasciatus, and Cx. tritaeniorhynchus, respectively, with the highest prevalence of virus-associated reads being observed in Cx. quinquefasciatus. The metagenomic comparison analysis showed that the virus-related reads were distributed across 26 virus families, together with an unclassified group of viruses. Anelloviridae, Circoviridae, Genomoviridae, Iridoviridae, Mesoniviridae, Microviridae, Myoviridae, Parvoviridae, Phenuiviridae, and Podoviridae were the top ten significantly different viral families among the four species. Further analysis reveals that the virome is species-specific in four mosquito samples, and several viral sequences which maybe belong to novel viruses are discovered for the first time in those mosquitoes. This investigation provides a basis for a comprehensive knowledge on the mosquito virome status in China.