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Cancer Medicine logoLink to Cancer Medicine
. 2020 Aug 1;9(18):6776–6790. doi: 10.1002/cam4.3325

Virome assembly and annotation in brain tissue based on next‐generation sequencing

Zihao Yuan 1,2, Xiaohua Ye 2, Lisha Zhu 1, Ningyan Zhang 2, Zhiqiang An 2,, W Jim Zheng 1,
PMCID: PMC7520322  PMID: 32738030

Abstract

The glioblastoma multiforme (GBM) is one of the deadliest tumors. It has been speculated that virus plays a role in GBM but the evidences are controversy. Published researches are mainly limited to studies on the presence of human cytomegalovirus (HCMV) in GBM. No comprehensive assessment of the brain virome, the collection of viral material in the brain, based on recently sequenced data has been performed. Here, we characterized the virome from 111 GBM samples and 57 normal brain samples from eight projects in the SRA database by a tested and comprehensive assembly approach. The annotation of the assembled contigs showed that most viral sequences in the brain belong to the viral family Retroviridae. In some GBM samples, we also detected full genome sequence of a novel picornavirus recently discovered in invertebrates. Unlike previous reports, our study did not detect herpes virus such as HCMV in GBM from the data we used. However, some contigs that cannot be annotated with any known genes exhibited antibody epitopes in their sequences. These findings provide several avenues for potential cancer therapy: the newly discovered picornavirus could be a starting point to engineer novel oncolytic virus; and the exhibited antibody epitopes could be a source to explore potential drug targets for immune cancer therapy. By characterizing the virosphere in GBM and normal brain at a global level, the results from this study strengthen the link between GBM and viral infection which warrants the further investigation.

Keywords: assembly, GBM, metagenomics., virosphere


We employed a data driven approach to identify virus species from the GBM NGS sequencing data. These virus could be potential novel therapeutic targets for cancer therapy.

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1. BACKGROUND

In 2019, an estimated 86 970 new cases of brain and other central nervous system (CNS) tumors are expected to be diagnosed in the United States alone. 1 It was projected that 47.7% of primary malignant brain tumors are glioblastoma multiforme (GBM)—one of the most killing tumors with a 5‐year survival rate less than 6% and a 12‐15 months median survival time even with the most advanced treatment. 2 , 3 , 4 , 5 , 6 Although there is rapid advancement in cancer research and therapies, outcomes for GBM patients remain dismal due to the lack of knowledge of GBM etiology. GBM is not usually inherited 7 and the causes of GBM have always been a topic of controversy. Hypothesized causes of GBM include exposure to ionizing radiation, 8 use of electronics, 8 , 9 , 10 , 11 or viral infections. 12 , 13 , 14

Viruses have been identified as important factors in the incidence of various cancers. 15 , 16 Many efforts have been devoted to detect the cancer causing virus or design oncolytic virus for tumor treatment. 17 , 18 For example, a novel Merkel cell polyomarvirus was discovered in Merkel cell carcinoma, 19 , 20 and the herpes virus Epstein‐Barr virus (EBV) was identified from the large B‐cell lymphomas, 21 Burkitt's lymphomas, 22 and gastric carcinoma. 23 In addition, the human papillomaviruses (HPV) have been proven to play essential roles in promoting oncogenesis in cervical carcinoma. 16 The Hepatitis B virus (HBV) and its integrations were also identified as a major risk factors for the development of hepatocellular carcinoma. 24 , 25 , 26 , 27 Furthermore, there have been studies focusing on identifying insertion sites of viruses in the human genome from next‐generation sequencing data in the Cancer Genome Atlas (TCGA). 16 , 28 These studies clearly demonstrate the importance of investigating the association between viruses and cancer development.

Since 2002, there have been significant efforts to investigate the correlation between human cytomegalovirus (HCMV) 12 and GBM occurrence by different methods such as polymerase chain reaction, in situ hybridization, immunohistochemistry, and next‐generation sequencing. Despite of these efforts, the presence of HCMV as well as other herpes virus in brain and their correlation with the development of GBM remains an area of controversy. 12 , 14 , 16 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53

In addition to HCMV, some studies observed the presence of human papillomavirus (HPV) and hepatitis B in low‐grade gliomas (LGG) 52 from next‐generation sequencing data. In these studies, short sequence reads were aligned to the reference viral genome sequences to identify these viruses. One limitation of such approach is the high false positive results due to the congregation of short reads in highly repetitive regions, or in the regions that contain artificial sequences in some of the reference genomes. 54 In addition, traditional approaches had only identified 4021 characterized virus species according to Baltimore virus classification, 55 which only represent a tiny fraction of the virome diversity. Furthermore, a large number of unknown reads that cannot be mapped to any reference genome are discarded. Therefore, current approach does not provide a full depiction of the landscape of the virome in the brain, and a comprehensive assessment of the virome and its correlation to GBM is needed.

The assembly of the metagenomics is vitally important to the quality of viral detection. However, assembly of the viral genome has always been challenging due to the fast evolving and fragmented nature of the viral genome. 56 , 57 In recent decades, several metagenomic assemblers have been designed for the assembly of different sequencing data. 58 , 59 , 60 The assembly software with long k‐mer length can generate contigs more accurately by reducing chimeric sequences. 61 In addition, the annotation of the assembly directly against a reference sequence database via BLAST is an easy and effective approach to characterize sequences. 62

In this study, we applied metagenomics approach to characterize the virosphere of GBM at a global scale and observed some novel viruses previously isolated only from nonhuman organisms. We also observed that the contigs matching the genome sequences of the herpes virus only make up a small portion of the whole viral genome. In addition, we identified some novel sequences with no known annotations. Further analysis showed that these sequences have the signature for antibody epitopes. These findings will provide novel avenues toward future GBM research and therapies.

2. METHODS

2.1. Data source and availability

We searched the NCBI Sequence Read Archive (SRA: https://www.ncbi.nlm.nih.gov/sra), Gene Expression Omnibus (GEO: https://www.ncbi.nlm.nih.gov/geo/), and PubMed literature to collect NGS studies relating to GBM and normal brain tissues. We also identified a set of samples infected with known viruses as our “positive controls” to test if our assembly approaches can detect these viruses from the sequencing data. We limited our study to the data generated from Illumina sequencing platform and the RNA‐seq data were downloaded from SRA database. The list of accessions for the source data are shown in Supplemental File 1.

2.2. Positive controls and brain sample assembly

The raw reads in each study were first trimmed and checked using Trimmomatic (version 0.36) 63 and fastqc. 64 Ambiguous nucleotides (N’s), extreme short reads (<30 nt), and low‐quality bases were trimmed with a sliding window size of 4. The reads were then mapped to the human genome (GRCh38.p13) via STAR. 65 Reads that cannot be mapped to human genome were collected for further analysis.

For the samples with known virus infections, the MEGAHIT was used for contig assembly, and the resulting contigs were compared with the reference viral genomes (Figure 1). For brain RNA‐seq data, viral sequences were detected by the pathogen discovery program, READSCAN. 66 A read is considered as a viral sequence if it covers at least 10% of the reference genome of the virus. The assembly of the viral sequences was conducted with MEGAHIT and Trinity, and their assembly results are compared and evaluated (Figure 2). The pair‐end and single‐end reads were pooled and assembled by MEGAHIT. 67 , 68 Trinity is also an efficient and robust software for de novo assembly of transcriptomes from RNA‐seq data, and was also used for the assembly. The pair‐end and single‐end reads were assembled separately. The longest isoform for each gene assembled was selected using get_longest_isoform_seq_per_trinity_gene.pl. In order to reduce redundancy, the assembly was then processed by CD‐Hit (version 4.5.4) to remove duplicated contigs. 69 The threshold of sequence identity was set at 1.0, with the alignment coverage greater than 90% of the shorter sequence, and word length of 5.

FIGURE 1.

FIGURE 1

The assembled contigs from known viral infections and synteny analysis with their reference genomes. A, Human herpesvirus 5, reference genome accession: NC_006273 contigs: 1. k89_1468; 2. k89_1723; 3. k89_1974; 4. k89_821; 5. k89_887. B, Enterobacteria phage phiX174 reference genome accession: CP004084.1 contigs: 1. k141.3724. C, Hepatitis B virus reference genome accession: M38454.1 contigs: 1. k141.13661. D, Zika virus strain H/PF/2013 reference genome accession: KJ776791.2 contigs: k95.45717. E, Tick‐borne encephalitis virus reference genome accession: NC.001672.1 contigs: k79.90. F, Influenza A virus (A/Puerto Rico/8/34/Mount Sinai(H1N1)) reference genome accession: S‐1: ENA.AF389122.AF38912; S‐2: ENA.AF389121.AF38912; S‐3: ENA.AF389119.AF38911; S‐4: ENA.AF389120.AF38912; S‐5: ENA.AF389115.AF38911; S‐6: ENA.AF389118.AF38911; S‐7: ENA.AF389116.AF38911; S‐8: ENA.AF389117.AF38911; contigs: 1. k59.54; 2. k59.36; 3. k59.42; 4. k59.46; 5. k59.58; 6. k59.53; 7. k59.41; 8. k59.56

FIGURE 2.

FIGURE 2

The assembly approach used for GBM and normal brain RNA‐seq dataset

2.3. Viral contig annotation with RefSeq database

The contigs with length over 500 bp were annotated to known viruses references in both protein and nucleotide databases at NCBI via BLAST 70 and Diamond 71 with the cutoff of e‐value < 1e‐10. For “positive controls,” the annotated virus contigs and its synteny with the virus genome were visualized with Circos using tBLASTN. Ribbons are colored based on the E‐value, with red represents the best hit. 72

The number of reads contributed to the assembly of each “viral” contig from each sample was calculated to ensure the assembly quality (Figure 4) by mapping to the “viral” contigs using Bowtie2 73 and viewed by Tabular. 74 The charts were generated using the R ggplot package. 75

FIGURE 4.

FIGURE 4

The reads abundance for the annotated contigs from Table 1. A, The GBM and B, normal brain. The X‐axis represents the name of contigs (Table 2), the Y‐axis represents the number of reads that can be mapped to the contigs, in log10 scale

2.4. Novel contigs annotation and characterization

The shared contigs that have no annotation from the above analysis are view in Venn diagram (Figure 3). 76 The unknown contigs are extracted and the phylogenetic tree was built using Fast tree (version 1.0.1). 77 The potential viral open reading frames (ORFs) were predicted by ORF finder (https://www.ncbi.nlm.nih.gov/orffinder/). The minimal ORF length was set as 75, with any sense codon and standard genetic code applied. For each of the putative protein‐coding contigs, we applied TMHMM Server v. 2.0 to predict transmembrane domains. 78 Antibody epitope prediction was conducted by Bepipred Linear Epitope Prediction method in Immune Epitope Database (IEDB) (https://www.iedb.org/home_v3.php). 79 , 80 , 81 , 82 In order to ensure the quality of each contig, we calculated the reads coverage for each sample in the samtools, 83 and only kept those contigs with the coverage over 60% of its entire length for analysis.

FIGURE 3.

FIGURE 3

The annotation results from nt‐database, nr‐database, and Swiss‐Prot databases. The annotation results for A, GBM and B, normal brain. The overlap of the unknown annotations in C, GBM and D, normal brain

3. RESULTS

3.1. Assembly of positive controls

To validate our approach, we tested six samples with known viral infections as positive controls to evaluate our methods for viral sequence assembly. These six samples include Human herpesvirus 5 (double stranded DNA virus), Enterobacteria phage phiX174 (single stranded DNA virus), HBV (double stranded DNA virus with reverse transcription), Zika virus (single‐stranded, positive‐sense RNA virus), Tick‐borne Encephalitis virus (single‐stranded, positive‐sense RNA virus), and Influenza A virus H1N1 (fragmented, single‐stranded, negative‐sense RNA virus). These viruses cover major categories of different types of viruses to ensure the validity of our approach.

After trimming and mapping the reads to human genome, the unmapped high‐quality reads from the positive controls were assembled via MEGAHIT. The assembly results from each virus infected samples were compared to its corresponding reference sequences. We observed that for each positive control, the assembled contigs can cover over 90% of the reference genome of the corresponding virus (Figure 1). Five assembled contigs from the human herpesvirus 5 virus sample cover more than 90% of the viral genome (Figure 1A). One assembled contig from phage X174, HBV, zika, and Encephalitis samples each covers more than 90% of the corresponding viral genome (Figure 1B‐E). Furthermore, eight contigs from Influenza A virus infected sample can cover the eight segments of the influenza A H1N1 reference genome, respectively (Figure 1F). These results showed that our assembly approach is suitable and reliable for the metagenomic studies.

3.2. Brain RNA‐Seq reads assembly

We collected 111 GBM and 57 healthy brain data sets from eight different projects. This large number of datasets ensures the quality of contig assembly (Supplemental 2). In total, there are 6609 M (Million) raw sequencing reads for GBM and 2681 M for healthy brain. The low‐quality reads and reads that map to human genome were then removed to yield 210.0 M high quality reads for GBM and 115.4 M for health brain. For each group, reads were pooled together and assembled with MEGAHIT and Trinity, respectively. Using N50, N90 and the number of contigs as a criteria, MEGAHIT performed better than Trinity in assembling the GBM RNA‐Seq reads (Figure 2): MEGAHIT generated 95 642 contigs with N50 = 704 bp while Trinity generated 203 191 contigs with N50 = 400bp. In healthy brain, MEGAHIT generated 71 771 contigs with N50 = 827bp while Trinity generated 113 234 contigs with N50 = 574bp. Therefore, MEGAHIT results were used for further analysis. In total, GBM assembly contains 39 000 contigs longer than 500 nt and the largest contig is 14kb. The normal brain assembly contains 33 640 contigs longer than 500 nt, with largest contig reaching 37.5 kb.

3.3. Assembly annotation

The assembled contigs were annotated with the nucleotide collection database for Blast (nr/nt) at NCBI as well as Swiss‐Prot. Among the 95 642 contigs assembled from GBM samples, 93 228 can be annotated by nt database, 55 200 are annotated by nr database, and 47 070 contigs are annotated by Swiss‐Prot database. Only 959 contigs cannot be annotated by neither of the three databases (Figure 3A,C). Out of 71 771 contigs assembled from healthy brain samples, 69 255 can be annotated by nt database, 49 782 are annotated by nr database and 41 615 are annotated by Swiss‐Prot database, with only 369 contigs cannot be annotated (Figure 3B,D).

Of the annotated contigs over 500 bp long, 57 from GBM and 42 from healthy brain were identified as putative viral sequences of nonhuman origin (Table 1). Most of these contigs have a minimum read depth of 100 over the entire contig (Figure 4A,B, Table 2). Figure 5 shows the detailed information about these contigs. Most of these viral annotations can be characterized as retroviridae. Surprisingly, five contigs were annotated as a novel picornavirus previously identified from invertebrates. 84 These viral contigs were detected in five GBM but none of the healthy brain samples. The synteny analysis shows that these five contigs can match up to more than 90% of the picorna‐like virus 2 reference genome (Figure 6A). This result suggests a possible cross species transmission of the virus.

TABLE 1.

The annotated contigs with length > 500 bp by nr, nt, and Swiss‐Prot in GBM and normal brain. (A) The annotated virus from nr, nt, Swiss‐Prot in GBM. (B) The annotated virus from nr, nt, Swiss‐Prot in normal brain

Swiss‐Prot

>333 AA

Swiss‐Prot

167‐333 AA

NR

>333AA

NR

167‐333AA

NT

>1000

NT

500‐1000

(A)
k141_1966 k141_17176 k141_17176 k141_21057 k141_17176 k141_14851
k141_20413 k141_21082 k141_1966 k141_22611 k141_20413 k141_19740
k141_22611 k141_22611 k141_20413 k141_26285 k141_33111 k141_22611
k141_24342 k141_25917 k141_22611 k141_31289 k141_34506 k141_26285
k141_31655 k141_31289 k141_65527 k141_32573 k141_50766 k141_34855
k141_32066 k141_32573 k141_83074 k141_33111 k141_5616 k141_41235
k141_33111 k141_33111 k141_85368 k141_54776 k141_83074 k141_47897
k141_34506 k141_34506 k141_90342 k141_72529 k141_50766
k141_37037 k141_37401 k141_9526 k141_80924 k141_54776
k141_50766 k141_40368 k141_58075
k141_52202 k141_40862 k141_78048
k141_67072 k141_44479 k141_9526
k141_79178 k141_48992
k141_83074 k141_50917
k141_84281 k141_53095
k141_85368 k141_54776
k141_8782 k141_5936
k141_59436
k141_59727
k141_60933
k141_6834
k141_7441
k141_74451
k141_77374
k141_77641
k141_83074
k141_85368
k141_86666
k141_9065
k141_91608
k141_9526
(B)
k119_16633 k119_11170 k119_11210 k119_12208
k119_20176 k119_12162 k119_12208 k119_33960
k119_23522 k119_12208 k119_17584 k119_54092
k119_31731 k119_12631 k119_20176
k119_47334 k119_13303 k119_23522
k119_56431 k119_16853 k119_66335
k119_58902 k119_17584 k119_7909
k119_60013 k119_18222
k119_18699
k119_20176
k119_21423
k119_21825
k119_25761
k119_26055
k119_37222
k119_37745
k119_3825
k119_43612
k119_44406
k119_45310
k119_46849
k119_47632
k119_48152
k119_48193
k119_50374
k119_5065
k119_55758
k119_56955
k119_59983
k119_60013
k119_7909
k119_7937

TABLE 2.

The assembled contigs annotated as viral origin with number of mapped reads and labels presented in Figure 4

GBM assembly Normal brain assembly
Label Contigs Total reads Label Contigs Total reads
1 k141_41235 128 1 k119_12208 60
2 k141_59727 2354 2 k119_60013 379
3 k141_21082 78 3 k119_33960 531
4 k141_22611 126 4 k119_55758 244
5 k141_83074 6389 5 k119_54092 58 879
6 k141_85368 442 6 k119_3825 1115
7 k141_9526 133 7 k119_11170 1076
8 k141_59436 1824 8 k119_25761 219
9 k141_14851 9209 9 k119_26055 443
10 k141_19740 11 153 10 k119_46849 151
11 k141_34855 6415 11 k119_5065 632
12 k141_47897 14 070 12 k119_50374 107
13 k141_77374 584 13 k119_16633 122
14 k141_65527 58 14 k119_37745 651
15 k141_74451 643 15 k119_20176 734
16 k141_17176 646 16 k119_23522 1084
17 k141_40368 2165 17 k119_21825 251
18 k141_44479 104 18 k119_16853 1018
19 k141_5616 1184 19 k119_45310 90
20 k141_5936 42 20 k119_48193 108
21 k141_86666 377 21 k119_37222 138
22 k141_1966 113 22 k119_44406 1131
23 k141_20413 3011 23 k119_58902 174
24 k141_24342 8541 24 k119_7909 329
25 k141_25917 4573 25 k119_18222 124
26 k141_31289 50 26 k119_47632 4153
27 k141_31655 151 27 k119_31731 172
28 k141_32066 41 520 28 k119_47334 342
29 k141_32573 39 29 k119_13303 23
30 k141_33111 4324 30 k119_48152 9792
31 k141_34506 1697 31 k119_12631 608
32 k141_37037 183 32 k119_43612 461
33 k141_37401 512 33 k119_56955 61
34 k141_40862 2007 34 k119_56431 38
35 k141_48992 110 35 k119_17584 2603
36 k141_50766 3945 36 k119_18699 246
37 k141_50917 15 136 37 k119_21423 734
38 k141_52202 472 38 k119_7937 21
39 k141_53095 108 39 k119_59983 114
40 k141_54776 116 40 k119_11210 82
41 k141_58075 338 41 k119_66335 1 280 118
42 k141_60933 342
43 k141_67072 1032
44 k141_6834 3787
45 k141_72529 54
46 k141_7441 418
47 k141_77641 147
48 k141_79178 2654
49 k141_80924 43
50 k141_84281 481
51 k141_8782 475
52 k141_9065 95 447
53 k141_91608 348
54 k141_26285 77
55 k141_78048 83
56 k141_21057 40
57 k141_90342 64 234 471

FIGURE 5.

FIGURE 5

The distribution of virus contigs in different samples, (phage excluded). A, The GBM and B, normal brain. The X‐axis represents the number of samples that harbor these contigs. The Y‐axis list the individual contigs; the reads abundance is represented by the size of the dot; the color represents the reads density (reads number/sample numbers) in log 10 scale; the taxonomy of the annotated virus is presented on the right of the chart, with the z‐axis for the number of contigs for each order

FIGURE 6.

FIGURE 6

The assembled contigs from known viral infections and synteny analysis with their reference genomes. A, Wenzhou picorna‐like virus 2 strain. Contigs: 1: k141.22611 2: k141.83074; 3: k141.85368; 4: k141.9526; 5. k141.17176. B, Human gammaherpesvirus 4, reference genome accession: MH590571.1 contigs: 1: k141.19740 2: k141.34855 3: k141.14851 4: k141.47897. C, HCMV from seropositive healthy human samples D, HCMV from fetal lung fibroblast cells from naturally infection E, latent HCMV from hematopoietic cell

We also identified four contigs (k141_19740 (length = 664); k141_34855 (length = 739); k141_14851 (length = 753); k141_47897 (length = 501)) that were annotated as EBV, the only herpes virus to be found with moderate length of contigs. However, the synteny analysis showed that they are mapped to the same small region of the EBV reference genome (Figure 6B). In contrast, the synteny analysis of the presence of herpes virus in positive control showed significant number of contigs homologous to the HCMV reference genome (Figure 1). Significant homology over large genomic area is also observed in HCMV contigs from CMV seropositive healthy human samples (Figure 6C), fetal lung fibroblast cells from naturally infected people (Figure 6D), and HCMV latent hematopoietic cell (Figure 6E). In addition, READSCAN analysis of GBM virome does not support the presence of herpesviruses in GBM despite of few reads in few samples appeared to be mapped to a small proportion of the viral genome (Supplemental 3). 64 Therefore, both the contig assembly and sequence reads mapping from our analysis do not support the presence of EVB and other herpesviruses in GBM. However, our analysis cannot rule out the presence of latent herps virus whose genomic DNA is inserted into the genome of GBM tumor cells.

3.4. Novel contig antigen prediction

For unannotated 959 contigs from GBM and 369 from healthy brain (Figure 3C,D), we performed phylogenetic analysis to group them into three major clusters (Supplemental 4A, 4B). ORF was predicted for each contig longer than 500bp. The resulting protein sequences from these predicted ORF were subject to TMHMM v2.0 (http://www.cbs.dtu.dk/services/TMHMM/) analysis to predict the transmembrane domains. Significant transmembrane domains were found in 31 unknown contigs from GBM and three unknown contigs from health brain. Among these transmembrane contigs, we found that the linear B‐cell epitopes were enriched and analyzed. Some of the contigs, such as k141_31618 assembled from 22 out of 110 GBM samples and k141_77976 from 33 of GBM samples, contains putative antigen epitopes (Figure 7). If real and validated by experiments, these contigs can potentially be recognized by immune system and used as targets for drug development.

FIGURE 7.

FIGURE 7

The antibody epitope prediction and sample distribution. The antibody epitope prediction results are on the right, Y‐axis represents the score of the antigen prediction and the X‐axis represents the position of the predicted open reading frame. On the left are the proportion of samples (blue) that harbor this contig out of 110 GBM and 57 normal brain tissues. The number represents the proportion of projects that harbor the contigs

4. DISCUSSION

As the most lethal type of cancer, GBM kills thousands every year. Although many studies have investigated the risk factors of GBM, our knowledge of their etiology is still lacking. 9 , 11 , 12 , 13 , 14 , 85 Emerging evidence suggests that viral infection can cause tumors. For GBM, the main focus was on HCMV, with a small number of studies on other viruses such as EBV 86 or HPV 87 by amplifying viral genome segments. However, the presence and association of virus with GBM is not firmly established and an un‐biased data‐driven approach to investigate the virome in human brain is needed. Analyzing virome in GBM can provide insight on etiology of GBM, and maybe it's unexplainable relationship with other neurological disorder such as Alzheimer's disease.

Next‐generation sequencing technologies had been successfully applied to characterize the virome in various human tissues such as skin and blood. 88 , 89 , 90 Traditional methods for viral detection are based on aligning short sequence reads to the reference viral genome sequences with commonly used software such as PathSequation 91 or RINs. 92 However, these methods could suffer from false positive results where short sequence reads can be congregated in highly repetitive regions. Besides, some reference viral genomes may also contain artificial sequences. 54 Our approach avoided this drawback by first mapping sequence reads to the human genome to filter out human protein‐coding genes and other highly repetitive elements such as human endogenous retrovirus or transposable element sequences. The unmapped reads containing viral sequences were then assembled into relative longer contigs. Our study is the first to explore the GBM virome in an assembly annotation approach, and indeed we identified contigs that match viral sequences. Among them, most were retrovirus sequences, probably due to the close relationship of the retrovirus with human transposable elements. 93 We also found extensive presence of phage sequences in both GBM and healthy brain. Even though it is possible that they come from the gut, 94 previous studies often consider them from bacterial infections contaminated by the commercial phiX174. 88 , 95 , 96

It is surprising to find the sequences of a Picornavirus in five GBM samples (Supplemental 5), as this virus was first reported in invertebrate. 9 , 10 , 11 , 85 However, it is unlikely due to sample contamination or sequence mismatches as the five assembled contigs cover more than 90% of the reference genome of the virus. Picornaviruses are small, single‐stranded positive RNA viruses infecting a wide range of hosts. Given that some viruses infect their hosts ranging from plants to animals, 97 the ubiquitous presence of the Picornaviruses suggests a complex nature of virosphere and an extensive horizontal genetic exchanges of viral genomics. 98 Our finding also indicates that this virus could be a new candidate for oncolytic viral therapy since several other picornaviruses had been proven to have the oncolytic potentials. For example, a recombinant oncolytic poliovirus, PVSRIPO has demonstrated to be oncolytic in a wide range of brain cancer cell lines such as GBM cell lines 99 or astrocytomas cancer cell lines. 100 , 101 Other attenuated polioviruses such as incompetent poliovirus 1 (PV1) replicons have also shown cytotoxicity against various tumors and promising results in prolong survival of GBM mouse models. 102 Taken together, the detection of picornavirus in the GBM but not healthy samples suggests the potential of the discovered picornavirus as a candidate to engineer future oncolytic virus. 103

The presence of EBV in gliomas has always been controversy. 86 Consistent with some of the previous studies, 34 , 35 , 39 , 52 , 104 our results suggest that EBV is absent from gliomas. In addition, contig segments matching herpes virus sequences may come from homologous sequences. However, one possibility we cannot rule out is that the herpes virus is in latent in GBM or inserted into the human genome in various tissues that cannot be captured by RNA‐seq.

A number of contigs cannot be annotated by any databases we used. It is possible that those contigs are artificial or formed from artificial sequences such as vectors or contaminations. However, we observed that various samples from different projects have reads that can cover more than 60% of the contig. For example, over 60% of the length of contig k141‐31618 can be covered by the reads originated from 22 studies from six out of seven projects in the GBM group, making it evident that contigs like this are not contaminations but rather originated from a valid source. Transmembrane analysis and antibody epitope prediction show that significant amount of those contig sequences has antibody epitope sequence signature, suggesting a potential to be used as drug targets for cancer immune therapy.

CONFLICT OF INTEREST

The authors declare that they have no competing interests.

AUTHOR CONTRIBUTIONS

ZY, WJZ, and ZA conceived and designed the study, ZY and LZ performed the analysis, XY, LZ, NZ, ZA and WJZ made revisions, ZA and WJZ supervised the project. All authors support the publication of the manuscript.

Supporting information

Supplementary Material

Supplementary Material

Supplementary Material

Supplementary Material

Supplementary Material

Yuan Z, Ye X, Zhu L, Zhang N, An Z, Jim Zheng W. Virome assembly and annotation in brain tissue based on next-generation sequencing. Cancer Med. 2020;9:6776–6790. 10.1002/cam4.3325

Funding information

The authors used computing resources from the Texas Advanced Computing Center at The University of Texas at Austin, and the Data Science and Informatics Core for Cancer Research at the School of Biomedical Informatics, University of Texas Health Science Center at Houston. This work is partly supported by the Cancer Prevention and Research Institute of Texas grant RP170668 (Zheng), PR150551& RP190561 (An), the National Institutes of Health (NIH) through grants 1UL1TR003167 and R01AG066749 (Zheng) and the Welch Foundation AU‐0042‐20030616 (An).

Contributor Information

Zhiqiang An, Email: zhiqiang.an@uth.tmc.edu.

W. Jim Zheng, Email: zhiqiang.an@uth.tmc.edu, Email: wenjin.j.zheng@uth.tmc.edu.

DATA AVAILABILITY STATEMENT

We searched the NCBI Sequence Read Archive (SRA) (https://www.ncbi.nlm.nih.gov/sra), Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/), and literatures to collect the next‐generation sequencing (NGS) studies relating to GBM and normal brain tissues, as well as samples infected with known virus as “positive controls” to test our assembly approaches. The raw RNA‐seq fastq files from Illumina platform were downloaded from SRA database, and the list of accessions for the source data is shown in the Supplemental File 1.

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Supplementary Materials

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Data Availability Statement

We searched the NCBI Sequence Read Archive (SRA) (https://www.ncbi.nlm.nih.gov/sra), Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/), and literatures to collect the next‐generation sequencing (NGS) studies relating to GBM and normal brain tissues, as well as samples infected with known virus as “positive controls” to test our assembly approaches. The raw RNA‐seq fastq files from Illumina platform were downloaded from SRA database, and the list of accessions for the source data is shown in the Supplemental File 1.


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