Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues

Liguo Zhang, Alexsia Richards,  View ORCID ProfileM. Inmaculada Barrasa,  View ORCID ProfileStephen H. Hughes,  View ORCID ProfileRichard A. Young, and Rudolf Jaenisch

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PNAS May 25, 2021 118 (21) e2105968118; https://doi.org/10.1073/pnas.2105968118

1. Contributed by Rudolf Jaenisch, April 19, 2021 (sent for review March 29, 2021; reviewed by Anton Berns and Anna Marie Skalka)

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Significance

An unresolved issue of SARS-CoV-2 disease is that patients often remain positive for viral RNA as detected by PCR many weeks after the initial infection in the absence of evidence for viral replication. We show here that SARS-CoV-2 RNA can be reverse-transcribed and integrated into the genome of the infected cell and be expressed as chimeric transcripts fusing viral with cellular sequences. Importantly, such chimeric transcripts are detected in patient-derived tissues. Our data suggest that, in some patient tissues, the majority of all viral transcripts are derived from integrated sequences. Our data provide an insight into the consequence of SARS-CoV-2 infections that may help to explain why patients can continue to produce viral RNA after recovery.

Abstract

Prolonged detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA and recurrence of PCR-positive tests have been widely reported in patients after recovery from COVID-19, but some of these patients do not appear to shed infectious virus. We investigated the possibility that SARS-CoV-2 RNAs can be reverse-transcribed and integrated into the DNA of human cells in culture and that transcription of the integrated sequences might account for some of the positive PCR tests seen in patients. In support of this hypothesis, we found that DNA copies of SARS-CoV-2 sequences can be integrated into the genome of infected human cells. We found target site duplications flanking the viral sequences and consensus LINE1 endonuclease recognition sequences at the integration sites, consistent with a LINE1 retrotransposon-mediated, target-primed reverse transcription and retroposition mechanism. We also found, in some patient-derived tissues, evidence suggesting that a large fraction of the viral sequences is transcribed from integrated DNA copies of viral sequences, generating viral–host chimeric transcripts. The integration and transcription of viral sequences may thus contribute to the detection of viral RNA by PCR in patients after infection and clinical recovery. Because we have detected only subgenomic sequences derived mainly from the 3′ end of the viral genome integrated into the DNA of the host cell, infectious virus cannot be produced from the integrated subgenomic SARS-CoV-2 sequences.

- SARS-CoV-2

- reverse transcription

- LINE1

- genomic integration

- chimeric RNAs

Continuous or recurrent positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR tests have been reported in samples taken from patients weeks or months after recovery from an initial infection (1⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓⇓–17). Although bona fide reinfection with SARS-CoV-2 after recovery has recently been reported (18), cohort-based studies with subjects held in strict quarantine after they recovered from COVID-19 suggested that at least some “re-positive” cases were not caused by reinfection (19, 20). Furthermore, no replication-competent virus was isolated or spread from these PCR-positive patients (1⇓–3, 5, 6, 12, 16), and the cause for the prolonged and recurrent production of viral RNA remains unknown. SARS-CoV-2 is a positive-stranded RNA virus. Like other beta-coronaviruses (SARS-CoV-1 and Middle East respiratory syndrome-related coronavirus), SARS-CoV-2 employs an RNA-dependent RNA polymerase to replicate its genomic RNA and transcribe subgenomic RNAs (21⇓⇓–24). One possible explanation for the continued detection of SARS-CoV-2 viral RNA in the absence of virus reproduction is that, in some cases, DNA copies of viral subgenomic RNAs may integrate into the DNA of the host cell by a reverse transcription mechanism. Transcription of the integrated DNA copies could be responsible for positive PCR tests long after the initial infection was cleared. Indeed, nonretroviral RNA virus sequences have been detected in the genomes of many vertebrate species (25, 26), with several integrations exhibiting signals consistent with the integration of DNA copies of viral mRNAs into the germline via ancient long interspersed nuclear element (LINE) retrotransposons (reviewed in ref. 27). Furthermore, nonretroviral RNA viruses such as vesicular stomatitis virus or lymphocytic choriomeningitis virus (LCMV) can be reverse transcribed into DNA copies by an endogenous reverse transcriptase (RT), and DNA copies of the viral sequences have been shown to integrate into the DNA of host cells (28⇓–30). In addition, cellular RNAs, for example the human APP transcripts, have been shown to be reverse-transcribed by endogenous RT in neurons with the resultant APP fragments integrated into the genome and expressed (31). Human LINE1 elements (∼17% of the human genome), a type of autonomous retrotransposons, which are able to retro-transpose themselves and other nonautonomous elements such as Alu, are a source of cellular endogenous RT (32⇓–34). Endogenous LINE1 elements have been shown to be expressed in aged human tissues (35) and LINE1-mediated somatic retrotransposition is common in cancer patients (36, 37). Moreover, expression of endogenous LINE1 and other retrotransposons in host cells is commonly up-regulated upon viral infection, including SARS-CoV-2 infection (38⇓–40).

In this study, we show that SARS-CoV-2 sequences can integrate into the host cell genome by a LINE1-mediated retroposition mechanism. We provide evidence that the integrated viral sequences can be transcribed and that, in some patient samples, the majority of viral transcripts appear to be derived from integrated viral sequences.

Results

Integration of SARS-CoV-2 Sequences into the DNA of Host Cells in Culture.

We used three different approaches to detect genomic SARS-CoV-2 sequences integrated into the genome of infected cells. These approaches were Nanopore long-read sequencing, Illumina paired-end whole genomic sequencing, and Tn5 tagmentation-based DNA integration site enrichment sequencing. All three methods provided evidence that SARS-CoV-2 sequences can be integrated into the genome of the host cell.

To increase the likelihood of detecting rare integration events, we transfected HEK293T cells with LINE1 expression plasmids prior to infection with SARS-CoV-2 and isolated DNA from the cells 2 d after infection (SI Appendix, Fig. S1A). We detected DNA copies of SARS-CoV-2 nucleocapsid (NC) sequences in the infected cells by PCR (SI Appendix, Fig. S1B) and cloned the complete NC gene (SI Appendix, Fig. S1D) from large-fragment cell genomic DNA that had been gel-purified (SI Appendix, Fig. S1C). The viral DNA sequence (NC) was confirmed by Sanger sequencing (Dataset S1). These results suggest that SARS-CoV-2 RNA can be reverse-transcribed, and the resulting DNA could be integrated into the genome of the host cell.

To demonstrate directly that the SARS-CoV-2 sequences were integrated into the host cell genome, DNA isolated from infected LINE1-overexpressing HEK293T cells was used for Nanopore long-read sequencing (Fig. 1A). Fig. 1 B–D shows an example of a full-length viral NC subgenomic RNA sequence (1,662 bp) integrated into the cell chromosome X and flanked on both sides by host DNA sequences. Importantly, the flanking sequences included a 20-bp direct repeat. This target site duplication is a signature of LINE1-mediated retro-integration (41, 42). Another viral integrant comprising a partial NC subgenomic RNA sequence that was flanked by a duplicated host cell DNA target sequence is shown in SI Appendix, Fig. S2 A–C. In both cases, the flanking sequences contained a consensus recognition sequence of the LINE1 endonuclease (43). These results indicate that SARS-CoV-2 sequences can be integrated into the genomes of cultured human cells by a LINE1-mediated retroposition mechanism. Table 1 summarizes all of the linked SARS-CoV-2–host sequences that were recovered. DNA copies of portions of the viral genome were found in almost all human chromosomes. In addition to the two examples given in Fig. 1 and SI Appendix, Fig. S2, we also recovered cellular sequences for 61 integrants for which only one of the two host–viral junctions was retrieved (SI Appendix, Fig. S2 D–F and Table 1; Nanopore reads containing the chimeric sequences summarized in Dataset S2). Importantly, about 67% of the flanking human sequences included either a consensus or a variant LINE1 endonuclease recognition sequence (such as TTTT/A) (SI Appendix, Fig. S2 D–F and Table 1). These LINE1 recognition sequences were either at the chimeric junctions that were directly linked to the 3′ end (poly-A tail) of viral sequences, or within a distance of 8–27 bp from the junctions that were linked to the 5′ end of viral sequences, which is within the potential target site duplication. Both results are consistent with a model in which LINE1-mediated retroposition provides a mechanism to integrate DNA copies of SARS-CoV-2 subgenomic fragments into host genomic DNA. About 71% of the viral sequences were flanked by intron or intergenic cellular sequences and 29% by exons (Fig. 1F and Table 1). Thus, the association of the viral sequences with exons is much higher than would be expected for random integration into the genome [human genome: 1.1% exons, 24% introns, and 75% intergenic DNA (44)], suggestive of preferential integration into exon-associated target sites. While previous studies showed no preference for LINE1 retroposition into exons (45, 46), our finding suggests that LINE1-mediated retroposition of some other RNAs may be different. We noted that viral–cellular boundaries were frequently close to the 5′ or 3′ untranslated regions (UTRs) of the cellular genes, suggesting that there is a preference for integration close to promoters or poly(A) sites in our experimental system.

Fig. 1.

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Fig. 1.

SARS-CoV-2 RNA can be reverse transcribed and integrated into the host cell genome. (A) Experimental workflow. (B) Chimeric sequence from a Nanopore sequencing read showing integration of a full-length SARS-CoV-2 NC subgenomic RNA sequence (magenta) and human genomic sequences (blue) flanking both sides of the integrated viral sequence. Features indicative of LINE1-mediated “target-primed reverse transcription” include the target site duplication (yellow highlight) and the LINE1 endonuclease recognition sequence (underlined). Sequences that could be mapped to both genomes are shown in purple with mismatches to the human genomic sequences in italics. The arrows indicate sequence orientation with regard to the human and SARS-CoV-2 genomes as shown in C and D. (C) Alignment of the Nanopore read in B with the human genome (chromosome X) showing the integration site. The human sequences at the junction region show the target site, which was duplicated when the SARS-CoV-2 cDNA was integrated (yellow highlight) and the LINE1 endonuclease recognition sequence (underlined). (D) Alignment of the Nanopore read in B with the SARS-CoV-2 genome showing the integrated viral DNA is a copy of the full-length NC subgenomic RNA. The light blue highlighted regions are enlarged to show TRS-L (I) and TRS-B (II) sequences (underlined, these are the sequences where the viral polymerase jumps to generate the subgenomic RNA) and the end of the viral sequence at the poly(A) tail (III). These viral sequence features (I–III) show that a DNA copy of the full-length NC subgenomic RNA was retro-integrated. (E) A human–viral chimeric read pair from Illumina paired-end whole-genome sequencing. The read pair is shown with alignment to the human (blue) and SARS-CoV-2 (magenta) genomes. The arrows indicate the read orientations relative to the human and SARS-CoV-2 genomes. The highlighted (light blue) region of the human read mapping is enlarged to show the LINE1 recognition sequence (underlined). (F) Distributions of human–CoV2 chimeric junctions from Nanopore (Left) and Illumina (Right) sequencing with regard to features of the human genome.

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Table 1.

Summary of the human-CoV2 chimeric sequences obtained by Nanopore DNA sequencing of infected LINE1-overexpressing HEK293T cells

To confirm the integration of SARS-CoV-2 sequences into genomic DNA by another method, we subjected DNA isolated from LINE1-transfected and SARS-CoV-2–infected HEK293T cells to Illumina paired-end whole-genome sequencing, using a Tn5-based library construction method (Illumina Nextera) to avoid ligation artifacts. Viral DNA reads were concentrated at the 3′ end of the SARS-CoV-2 genome (SI Appendix, Fig. S3). We recovered 17 viral integrants (sum of two replicates), by mapping human–viral chimeric DNA sequences (Fig. 1E and Table 2, chimeric sequences summarized in Dataset S3); 7 (41%) of the junctions contained either a consensus or a variant LINE1 recognition sequence in the cellular sequences near the junction (Fig. 1E and Table 2), consistent with a LINE1-mediated retroposition mechanism. Similar to the results obtained from Nanopore sequencing, about 76% of the viral sequences were flanked by intron or intergenic cellular sequences and 24% by exons (Fig. 1F and Table 2).

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Table 2.

Summary of the human-CoV2 chimeric sequences obtained by Illumina paired-end whole-genome DNA sequencing of infected LINE1-overexpressing HEK293T cells

About 32% of SARS-CoV-2 sequences (6/21 integration events in Nanopore, 4/10 in Illumina data) were integrated at LINEs, short interspersed nuclear elements, or long terminal repeat elements without evidence for a LINE1 recognition site, suggesting that there may be an alternative reverse transcription/integration mechanism, possibly similar to that reported for cells acutely infected with LCMV, which resulted in integrated LCMV sequences fused to intracisternal A-type particle (IAP) sequences (29).

To assess whether genomic integration of SARS-CoV-2 sequences could also occur in infected cells that did not overexpress RT, we isolated DNA from virus-infected HEK293T and Calu3 cells that were not transfected with an RT expression plasmid (Fig. 2A). Tn5 tagmentation-mediated DNA integration site enrichment sequencing (47, 48) (Fig. 2B and SI Appendix, Fig. S4A) detected a total of seven SARS-CoV-2 sequences fused to cellular sequences in these cells (sum of three independent infections of two cell lines), all of which showed LINE1 recognition sequences close to the human–SARS-CoV-2 sequence junctions (Fig. 2 C–F and SI Appendix, Fig. S4 B–D, chimeric sequences summarized in Dataset S4).

Fig. 2.

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Fig. 2.

Evidence for integration of SARS-CoV-2 cDNA in cultured cells that do not overexpress a reverse transcriptase. (A) Experimental workflow. (B) Experimental design for the Tn5 tagmentation-mediated enrichment sequencing method used to map integration sites in the host cell genome. (C) A human–viral chimeric read pair supporting viral integration. The reads are aligned with the human (blue) and SARS-CoV-2 (magenta) genomic sequences. The arrows indicate the read orientations relative to the human and SARS-CoV-2 genomes as shown in D and E. Sequence of the viral primer used for enrichment is shown with green highlight in the read (corresponding to the green arrow illustrated in B). Sequences that could be mapped to both genomes are shown in purple. (D) Alignment of the read pair in C with the human genome (chromosome 15, blue arrow). The highlighted (light blue) region of the human sequence is enlarged to show the LINE1 recognition sequence (underlined) with a 19-base poly-dT sequence (purple highlight) that could be annealed by the viral poly-A tail for “target-primed reverse transcription.” Additional 5-bp human sequence (GAATG, blue) was captured in read 2 (C), supporting a bona fide integration site. (E) Alignment of the read pair in C with the SARS-CoV-2 genome (magenta). The viral primer sequence is shown with green highlight. (F) Summary of seven human–viral chimeric sequences identified by the enrichment sequencing method in the two cell lines showing the integrated human chromosomes, LINE1 recognition sequences close to the chimeric junction, and human genomic features at the read junction.

Expression of Viral–Cellular Chimeric Transcripts in Infected Cultured Cells and Patient-Derived Tissues.

To investigate the possibility that SARS-CoV-2 sequences integrated into the genome can be expressed, we analyzed published RNA-seq data from SARS-CoV-2–infected cells for evidence of chimeric transcripts (49). Examination of these datasets (50⇓⇓⇓⇓–55) (SI Appendix, Fig. S5) revealed a number of human–viral chimeric reads (SI Appendix, Fig. S6 A and B). These occurred in multiple sample types, including cultured cells and organoids from lung/heart/brain/stomach tissues (SI Appendix, Fig. S6B). The abundance of the chimeric reads positively correlated with viral RNA level across the sample types (SI Appendix, Fig. S6B). Chimeric reads generally accounted for 0.004–0.14% of the total SARS-CoV-2 reads in the samples. A majority of the chimeric junctions mapped to the sequence of the SARS-CoV-2 NC gene (SI Appendix, Fig. S6 C and D). This is consistent with the finding that NC RNA is the most abundant SARS-CoV-2 subgenomic RNA (56), making it the most likely target for reverse transcription and integration. However, recent data showed that up to 1% of RNA-seq reads from SARS-CoV-2–infected cells can be artifactually chimeric as a result of RT switching between RNA templates, which can occur during the cDNA synthesis step in the preparation of a RNA-seq library (57). Thus, because there is a mixture of host mRNAs and positive-strand viral mRNAs in infected cells, the identification of genuine chimeric viral–cellular RNA transcripts is compromised by the generation of artifactual chimeras in the assays.

We reasoned that the orientation of an integrated DNA copy of SARS-CoV-2 RNA should be random with respect to the orientation of the targeted host gene, predicting that about half the viral DNAs that were integrated into an expressed host gene should be in an orientation opposite to the direction of the host cell gene’s transcription (Fig. 3A). As predicted, ∼50% of viral integrants in human genes were in the opposite orientation relative to the host gene in our Nanopore dataset (integration at human genes with LINE1 recognition sequences, Fig. 3B). Thus, for chimeric transcripts derived from integrated viral sequences, we would expect that ∼50% of the chimeric transcripts should contain negative-strand viral sequences linked to positive-strand host RNA sequences. We therefore determined the fraction of the viral and human–viral chimeric transcripts in infected cultured cells/organoids and in patient-derived tissues containing negative-strand viral RNA sequences.

Fig. 3.

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Fig. 3.

Negative-strand viral RNA-seq reads suggest that integrated SARS-CoV-2 sequences are expressed. (A) Schema predicting fractions of positive- or negative-strand SARS-CoV-2 RNA-seq reads that are derived from viral (sub)genomic RNAs or from transcripts of integrated viral sequences. The arrows (Right) showing the orientation of an integrated SARS-CoV-2 (magenta) positive strand relative to the orientation of the host cellular gene (blue). (B) Fractions of SARS-CoV-2 sequences integrated into human genes with same (n = 15) or opposite (n = 13) orientation of the viral positive strand relative to the positive strand of the human gene. A total of 28 integration events at human genes with LINE1 endonuclease recognition sequences were identified from our Nanopore DNA sequencing of infected LINE1-overexpressing HEK293T cells (Fig. 1A). (C) Fraction of total viral reads that are derived from negative-strand viral RNA in acutely infected cells or organoids (see SI Appendix, Table S1 for details). (D) Fraction of human–viral chimeric reads that contain viral sequences derived from negative-strand viral RNA in acutely infected cells or organoids (see SI Appendix, Table S1 for details). (E) Fraction of total viral reads that are derived from negative-strand viral RNA in published patient RNA-seq data (autopsy FFPE samples, GSE150316, samples with no viral reads or of low library strandedness quality not included; see SI Appendix, Table S2 for details; reanalysis results consistent with the original publication). (F) Fraction of human–viral chimeric reads that contain viral sequences derived from negative-strand viral RNA in published patient RNA-seq data (autopsy FFPE samples, GSE150316; see SI Appendix, Table S2 for details). (G) Fraction of total viral reads that are derived from negative-strand viral RNA in published patient RNA-seq data (BALF samples, GSE145926; see SI Appendix, Table S3 for details). The red dashed lines in E–G indicate the level at which 50% of all viral reads (E and G) or viral sequences in human–viral chimeric reads (F) were from negative-strand viral RNAs, a level expected if all the viral sequences were derived from integrated sequences.

The replication of SARS-CoV2 RNA requires the synthesis of negative-strand viral RNA, which serves as template for replication of viral genomic RNA and transcription of viral subgenomic positive-strand RNA (21). To assess the prevalence of negative-strand viral RNA in acutely infected cells, we determined the ratio of total positive to negative-strand RNAs. Between 0 and 0.1% of total viral reads were derived from negative-strand RNA in acutely infected Calu3 cells or lung organoids [our data and published data (50, 58)] (Fig. 3C and SI Appendix, Table S1), similar to what has been reported in clinical samples taken early after infection (59). These results argue that the level of negative-strand viral RNA is at least 1,000-fold lower than that of positive-strand viral RNA in acutely infected cells, due at least in part to a massive production of positive-strand subgenomic RNA during viral replication. This greatly reduces the likelihood that random template switching during the reverse transcription step in the RNA-seq library construction would generate a large fraction of the artifactual chimeric reads that would contain viral negative-strand RNA fused to cellular positive-strand RNA sequences. We determined that between 0 and 1% of human–viral chimeric reads contained negative-strand viral sequences in the acutely infected cells/organoids (Fig. 3D and SI Appendix, Table S1), consistent with a small fraction of viral reads being derived from integrated SARS-CoV-2 sequences.

In contrast to the results obtained with acutely infected Calu3 cells or lung organoids, up to 51% of all viral reads, and up to 42.5% of human–viral chimeric reads, were derived from the negative-strand SARS-CoV-2 RNA in some patient-derived tissues [published data (60, 61), patient clinical background available in the original publications] (Fig. 3 E–G and SI Appendix, Tables S2 and S3). Single-cell analysis of patient lung bronchoalveolar lavage fluid (BALF) cells from patients with severe COVID [published data (61)] showed that up to 40% of all viral reads were derived from the negative-strand SARS-CoV-2 RNA (SI Appendix, Fig. S7). Fractions of negative-strand RNA in tissues from some patients were orders of magnitude higher than those in acutely infected cells or organoids (Fig. 3 C–G). In fixed (formalin-fixed, paraffin-embedded [FFPE]) autopsy samples, in 4 out of 14 patients (Fig. 3E and SI Appendix, Table S2), and in BALF samples, in 4 out of 6 patients (Fig. 3G and SI Appendix, Table S3), at least ∼20% of the viral reads were derived from negative-strand viral RNA. In contrast to acutely infected cells (Fig. 3 C and D and SI Appendix, Table S1), there was little or no evidence for virus reproduction in these autopsy samples (60). As summarized in SI Appendix, Table S2, there were negative-strand viral sequences in a large fraction of the human–viral chimeric reads (up to ∼40%) in samples from one patient. Different samples derived from the same patient revealed a similarly high fraction of negative viral strand–human RNA reads. Several other patient samples revealed lower fraction of negative viral strand RNA–human RNA chimeras, which were, however, still significantly higher than what was found in acutely infected cells (Fig. 3 D and F and SI Appendix, Table S1 and S2). Because the ability to identify viral–human chimeric reads using short-read RNA-seq is limited, our analysis failed to show significant numbers of chimeric reads in patient BALF samples (SI Appendix, Table S3). In summary, our data suggest that in some patient-derived tissues, where the total number of SARS-CoV-2 sequence-positive cells may be small, a large fraction of the viral transcripts could have been transcribed from SARS-CoV-2 sequences integrated into the host genome.

Discussion

We present here evidence that SARS-CoV-2 sequences can be reverse-transcribed and integrated into the DNA of infected human cells in culture. For two of the integrants, we recovered “human–viral–human” chimeric reads encompassing a direct target site repeat (20 or 13 bp), and a consensus recognition site of the LINE1 endonuclease was present on both ends of the host DNA that flanked the viral sequences. These and other data are consistent with a target primed reverse transcription and retroposition integration mechanism (41, 42) and suggest that endogenous LINE1 RT can be involved in the reverse transcription and integration of SARS-CoV-2 sequences in the genomes of infected cells.

Approximately 30% of viral integrants analyzed in cultured cells lacked a recognizable nearby LINE1 endonuclease recognition site. Thus, it is also possible that integration can occur by another mechanism. Indeed, there is evidence that chimeric cDNAs can be produced in cells acutely infected with LCMV by copy choice with endogenous IAP elements during reverse transcription. This mechanism is expected to create a chimeric cDNA complementary to both LCMV and IAP. In some cases, the resulting chimeric cDNAs were integrated without the generation of a target site duplication (29). A recent study has also suggested that the interaction between coronavirus sequences and endogenous retrotransposon could be a potential viral integration mechanism (40).

It will be important, in follow-up studies, to demonstrate the presence of SARS-CoV-2 sequences integrated into the host genome in patient tissues. However, this will be technically challenging because only a small fraction of cells in any patient tissues are expected to be positive for viral sequences (61). Consistent with this notion, it has been estimated that only between 1 in 1,000 and 1 in 100,000 mouse cells infected with LCMV either in culture or in the animal carried viral DNA copies integrated into the genome (30). In addition, only a fraction of patients may carry SARS-CoV-2 sequences integrated in the DNA of some cells. However, with more than 140 million humans infected with SARS-CoV-2 worldwide (as of April, 2021), even a rare event could be of significant clinical relevance. It is also challenging to estimate the frequency of retro-integration events in cell culture assays since infected cells usually die and are lost before sample collection. For the same reason, no clonal expansion of integrated cells is expected in acute infection experiments. Moreover, the chance of integration at the same genomic locus in different patients/tissues may be low, due to a random integration process.

The presence of chimeric virus–host RNAs in cells cannot alone be taken as strong evidence for transcription of integrated viral sequences because template switching can happen during the reverse transcription step of cDNA library preparation. However, we found that only a very small fraction (0–1%) of chimeric reads from acutely infected cells contained negative-strand viral RNA sequences, whereas, in the RNA-seq libraries prepared from some patients, the fraction of total viral reads, and the fraction of human–viral chimeric reads that were derived from negative-strand SARS-CoV-2 RNAs was substantially higher. For retrotransposon-mediated integration events, the orientation of the reverse-transcribed SARS-CoV-2 RNA should be random with respect to the orientation of a host gene. Thus, for chimeric RNAs derived from integrated viral sequences, about half of the chimeric reads will link positive-strand host RNA sequences to negative-strand viral sequences. In some patient samples, negative-strand viral reads accounted for 40–50% of the total viral RNA sequences and a similar fraction of the chimeric reads contained negative-strand viral RNA sequences, suggesting that the majority if not all of the viral RNAs in these samples were derived from integrated viral sequences.

It is important to note that, because we have detected only subgenomic sequences derived mainly from the 3′ end of the viral genome integrated into the DNA of the host cell, infectious virus cannot be produced from such integrated subgenomic SARS-CoV-2 sequences. The possibility that SARS-CoV-2 sequences can be integrated into the human genome and expressed in the form of chimeric RNAs raises several questions for future studies. Do integrated SARS-CoV-2 sequences express viral antigens in patients and might these influence the clinical course of the disease? The available clinical evidence suggests that, at most, only a small fraction of the cells in patient tissues express viral proteins at a level that is detectable by immunohistochemistry. However, if a cell with an integrated and expressed SARS-CoV-2 sequences survives and presents a viral- or neo-antigen after the infection is cleared, this might engender continuous stimulation of immunity without producing infectious virus and could trigger a protective response or conditions such as autoimmunity as has been observed in some patients (62, 63). The presence of LCMV sequences integrated in the genomes of acutely infected cells in mice led the authors to speculate that expression of such sequences “potentially represents a naturally produced form of DNA vaccine” (30). It is not known how many antigen-presenting cells are needed to elicit an antigen response, but derepressed LINE1 expression, induced by viral infection or by exposure to cytokines (38⇓–40), may stimulate SARS-CoV-2 integration into the genome of infected cells in patients. More generally, our results suggest that integration of viral DNA in somatic cells may represent a consequence of a natural infection that could play a role in the effects of other common disease-causing RNA viruses such as dengue, Zika, or influenza virus.

Our results may also be relevant for current clinical trials of antiviral therapies (64). If integration and expression of viral RNA are fairly common, reliance on extremely sensitive PCR tests to determine the effect of treatments on viral replication and viral load may not always reflect the ability of the treatment to fully suppress viral replication because the PCR assays may detect viral transcripts that derive from viral DNA sequences that have been stably integrated into the genome rather than infectious virus.

Materials and Methods

Cell Culture and Plasmid Transfection.

HEK293T cells were obtained from ATCC (CRL-3216) and cultured in DMEM supplemented with 10% heat-inactivated FBS (HyClone; SH30396.03) and 2 mM L-glutamine (MP Biomedicals; IC10180683) following ATCC’s method. Calu3 cells were obtained from ATCC (HTB-55) and cultured in EMEM (ATCC; 30-2003) supplemented with 10% heat-inactivated FBS (HyClone; SH30396.03) following ATCC’s method.

Plasmids for human LINE1 expression, pBS-L1PA1-CH-mneo (CMV-LINE-1), was a gift from Astrid Roy-Engel, Tulane University Health Sciences Center, New Orleans, LA (Addgene plasmid #51288 ; http://addgene.org/51288; RRID:Addgene_51288) (65); EF06R (5′UTR-LINE-1) was a gift from Eline Luning Prak, University of Pennsylvania, Philadelphia, PA (Addgene plasmid #42940 ; http://addgene.org/42940; RRID:Addgene_42940) (66). Transfection was done with Lipofectamine 3000 (Invitrogen; L3000001) following manufacturer’s protocol.

SARS-CoV-2 Infection.

SARS-CoV-2 USA-WA1/2020 (GenBank: MN985325.1) was obtained from BEI Resources and expanded and tittered on Vero cells. Cells were infected in DMEM plus 2% FBS for 48 h using a multiplicity of infection (MOI) of 0.5 for infection of HEK293T cells and an MOI of 1 or 2 for Calu3 cells. All sample processing and harvest with infectious virus were done in the BSL3 facility at the Ragon Institute.

Nucleic Acids Extraction and PCR Assay.

Cellular DNA extraction was done using a published method (31). For purification of genomic DNA, total cellular DNA was fractionated on a 0.4% (wt/vol) agarose/1× TAE gel for 1.5 h with a 3 V/cm voltage, with λ DNA-HindIII Digest (NEB; N3012S) as size markers. Large fragments (>23.13 kb) were cut out, frozen in −80 °C, and then crushed with a pipette tip. Three volumes (vol/wt) of high T-E buffer (10 mM Tris–10 mM EDTA, pH 8.0) were added, and then NaCl was added to give a final concentration of 200 mM. The gel solution was heated at 70 °C for 15 min with constant mixing and then extracted with phenol:chloroform:isoamyl alcohol (25:24:1, vol/vol/vol) (Life Technologies; 15593031) and chloroform:isoamyl alcohol 24:1 (Sigma; C0549-1PT). DNA was precipitated by the addition of sodium acetate and isopropyl alcohol. For samples with low DNA concentration, glycogen (Life Technologies; 10814010) was added as a carrier to aid precipitation.

RNA extraction was done with RNeasy Plus Micro Kit (Qiagen; 74034) following manufacturer’s protocol.

To detect DNA copies of SARS-CoV-2 sequences, we chose four NC gene-targeting PCR primer sets that are used in COVID-19 tests [SI Appendix, Fig. S1A, primer source from World Health Organization (67), modified to match the genome version of NC_045512.2]. See SI Appendix, Table S4 for PCR primer sequences used in this study. PCR was done using AccuPrime Taq DNA Polymerase, high fidelity (Life Technologies; 12346094). PCR products were run on 1% or 2% (wt/vol) agarose gel to show amplifications.

Nanopore DNA Sequencing and Analysis.

A total of 1.6 μg of DNA extracted from HEK293T cells transfected with the pBS-L1PA1-CH-mneo (CMV-LINE-1) plasmid and infected with SARS-CoV-2 was used to make a sequencing library with the SQK-LSK109 kit (Oxford Nanopore Technologies) and sequenced on one R9 PromethION flowcell (FLO-PRO002) for 3 d and 5 min. The sequencing data were base-called using Guppy 4.0.11 (Oxford Nanopore Technologies) using the high-accuracy model.

Nanopore reads were mapped using minimap2 (68) (version 2.15) with parameters “-p 0.3 -ax map-ont” and a fasta file containing the human genome sequence from ENSEMBL release 93 (ftp://ftp.ensembl.org/pub/release-93/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz) concatenated to the SARS-CoV-2 sequence, GenBank ID: MN988713.1, “Severe acute respiratory syndrome coronavirus 2 isolate SARS-CoV-2/human/USA/IL-CDC-IL1/2020, complete genome.” From the SAM file, we selected all the sequences that mapped to the viral genome and divided them into groups based on the human chromosomes they mapped to. We blasted the selected sequences, using blastn, against a BLAST database made with the human and virus sequences described above. We parsed the blast output into a text file containing one row per high-scoring segment pair (HSP) with a custom perl script. We further filtered that file, for each sequence, by selecting all the viral HSPs and the top three human HSPs. We inspected those files visually to identify sequences containing human–viral–human or human–viral junctions. For a few sequences, longer than 30 kb, we inspected the top 15 human HSPs. Additionally, we visually inspected all the identified reads containing human and viral sequences by the University of California, Santa Cruz (UCSC) BLAT (69) tool. Due to errors in Nanopore sequencing and/or base-calling, artifactual “hybrid sequences” exist in a subset of these reads, sometimes with Watson and Crick strands from the same DNA fragment present in the same read. Therefore, we only focused on chimeric sequences showing clear human–viral junctions and analyzed known LINE1-mediated retroposition features such as target-site duplications and LINE1 endonuclease recognition sequences for evidence of integration.

Tn5 Tagmentation-Mediated Integration Site Enrichment.

We used a tagmentation-based method to enrich for viral integration sites (47, 48). Briefly, we used Tn5 transposase (Diagenode; C01070010) to randomly tagment the cellular DNA with adapters (adapter A, the Illumina Nextera system). Tagmentation was done using 100 ng of DNA for 10 min at 55 °C, followed by stripping off the Tn5 transposase from the DNA with SDS. We used a reverse primer targeting the near-5′ end of SARS-CoV-2 NC gene (CCAAGACGCAGTATTATTGGGTAAA) or a forward primer targeting the near-3′ end of SARS-CoV-2 genome (CTTGTGCAGAATGAATTCTCGTAACT) to linearly amplify (PCR0, 45 cycles) the tagmented DNA fragments containing viral sequences. We took the product of PCR0 and amplified the DNA fragments containing adapter and viral sequences (potential integration sites) using 15–20 cycles of PCR1, with a barcoded (i5) Nextera primer (AATGATACGGCGACCACCGAGATCTACACNNNNNNNNTCGTCGGCAGCGTC, NNNNNNNN indicates the barcode) against the adapter sequence and a viral primer. The viral primer was designed to either target the near-5′ end of SARS-CoV-2 NC gene (GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGCCGACGTTGTTTTGATCG, viral sequence underlined) or target the near-3′ end of SRAS-CoV-2 genome (GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGCGCGGAGTACGATCGAGTG, viral sequence underlined). The viral primer also contained an adapter sequence for further PCR amplification. We amplified the PCR1 product by 15–20 cycles of PCR2, using a short primer (AATGATACGGCGACCACCGA) against the i5 Nextera primer sequence and a barcoded (i7) Nextera primer (CAAGCAGAAGACGGCATACGAGATNNNNNNNNGTCTCGTGGGCTCGG, NNNNNNNN indicates the barcode) against the adapter sequence introduced by the viral primer in PCR1. The final product of the PCR2 amplification was fractionated on 1.5% agarose gel (Sage Science; HTC1510) with PippinHT (Sage Science; HTP0001) and 500- to 1,000-bp pieces were selected for Illumina paired-end sequencing. All three PCR steps (PCR0–PCR2) were done with KAPA HiFi HotStart ReadyMix (KAPA;KK2602).

Illumina DNA Sequencing and Analysis.

We constructed libraries for HEK293T cell whole-genome sequencing using the Tn5-based Illumina DNA Prep kit (Illumina; 20018704). The whole-genome sequencing libraries or the libraries from Tn5-mediated integration site enrichment after sizing (described above) were subjected to Illumina sequencing. qPCR was used to measure the concentrations of each library using KAPA qPCR library quant kit according to the manufacturer’s protocol. Libraries were then pooled at equimolar concentrations, for each lane, based on qPCR concentrations. The pooled libraries were denatured using the Illumina protocol. The denatured libraries were loaded onto an SP flowcell on an Illumina NovaSeq 6000 and run for 2 × 150 cycles according to the manufacturer’s instructions. Fastq files were generated and demultiplexed with the bcl2fastq Conversion Software (Illumina).

To identify human–SARS-CoV-2 chimeric DNA reads, raw sequencing reads were aligned with STAR (70) (version 2.7.1a) to a human plus SARS-CoV-2 genome made with a fasta file containing the human genome sequence version hg38 with no alternative chromosomes concatenated to the SARS-CoV-2 sequence from National Center for Biotechnology Information (NCBI) reference sequence NC_045512.2. The following STAR parameters were used to call chimeric reads: –alignIntronMax 1 \–chimOutType Junctions SeparateSAMold WithinBAM HardClip \–chimScoreJunctionNonGTAG 0 \–alignSJstitchMismatchNmax -1–1 -1–1 \–chimSegmentMin 25 \–chimJunctionOverhangMin 25 \–outSAMtype BAM SortedByCoordinate. We extracted viral reads from the generated BAM file by samtools (71) (version 1.11) using command: samtools view -b Aligned.sortedByCoord.out.bam NC_045512v2 > NC_Aligned.sortedByCoord.out.bam. We extracted human–viral chimeric reads by using the read names from the STAR generated Chimeric.out.junction file to get the read alignments from the STAR generated Chimeric.out.sam file by Picard (http://broadinstitute.github.io/picard), using command: java -jar picard.jar FilterSamReads I = Chimeric.out.sam O = hv-Chimeric.out.sam READ_LIST_FILE = hv-Chimeric.out.junction.ids FILTER = includeReadList. We further confirmed each of the chimeric reads and filtered out any unconvincing reads (too short or aligned to multiple sites of the human genome) by visual inspection with the UCSC BLAT (69) tool. We also loaded the STAR generated Aligned.sortedByCoord.out.bam file or the NC_Aligned.sortedByCoord.out.bam file containing extracted viral reads to the UCSC browser SARS-CoV-2 genome (NC_045512.2) to search for additional chimeric reads that were missed by the STAR chimeric calling method. To generate genome coverage file, we used the bamCoverage from the deepTools suite (72) (version 3.5.0) to convert the STAR generated Aligned.sortedByCoord.out.bam file to a bigwig file binned at 10 bp, using command: bamCoverage -b Aligned.sortedByCoord.out.bam -o Aligned.sortedByCoord.out.bw–binSize 10.

RNA-Seq and Analysis.

To identify human–SARS-CoV-2 chimeric reads, published RNA-seq data were downloaded from Gene Expression Omnibus (GEO) with the accession numbers GSE147507 (50), GSE153277 (51), GSE156754 (52), GSE157852 (53), GSE153684 (54), and GSE154998 (55) (summarized in SI Appendix, Fig. S5C). Raw sequencing reads were aligned with STAR (70) (version 2.7.1a) to human plus SARS-CoV-2 genome and transcriptome made with a fasta file containing the human genome sequence version hg38 with no alternative chromosomes concatenated to the SARS-CoV-2 sequence from NCBI reference sequence NC_045512.2, and a gtf file containing the human gene annotations from ENSEMBL version GRCh38.97 concatenated to the SARS-CoV-2 gene annotations from NCBI (http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/bigZips/genes/). The following STAR parameters (56) were used to call chimeric reads unless otherwise specified (SI Appendix, Fig. S5C):–chimOutType Junctions SeparateSAMold WithinBAM HardClip \–chimScoreJunctionNonGTAG 0 \–alignSJstitchMismatchNmax -1–1 -1–1 \–chimSegmentMin 50 \–chimJunctionOverhangMin 50.

For RNA-seq strandedness analysis, we generated RNA-seq data using RNA from SARS-CoV-2–infected Calu3 cells. Stranded libraries were constructed with the Kapa mRNA HyperPrep kit (Roche; 08098115702). Libraries were qPCR'ed using a KAPA qPCR library quant kit as per manufacturer’s protocol. Libraries were then pooled at equimolar concentrations, for each lane, based on qPCR concentrations. The pooled libraries were denatured using the Illumina protocol. The denatured libraries were loaded onto an HiSeq 2500 (Illumina) and sequenced for 120 cycles from one end of the fragments. Basecalls were performed using Illumina offline basecaller (OLB) and then demultiplexed. We downloaded published RNA-seq data (stranded libraries) from GEO with the accession numbers GSE147507 (50) (Calu3, SI Appendix, Table S1), GSE148697 (58) (lung organoids, SI Appendix, Table S1), and GSE150316 (60) (patient FFPE tissues, SI Appendix, Table S2). Raw RNA-seq reads were aligned as described above, using parameters–chimSegmentMin 30 \–chimJunctionOverhangMin 30 to call chimeric reads. We extracted total viral reads and human–viral chimeric reads as described above. We convert the viral read BAM files into Bed files using the bamToBed utility in BEDTools (73). We then counted the total and stranded read numbers in the converted BED files.

Published single-cell RNA-seq data were downloaded from GEO with the accession number GSE145926 (61) (patient BALF samples, SI Appendix, Table S3). For bulk analysis, duplicate reads with the same read1 (UMI) and read2 sequences in raw fastq files were removed by dedup_hash (https://github.com/mvdbeek/dedup_hash). Then the pool of read2 were aligned as described above, using parameters –chimSegmentMin 30 \–chimJunctionOverhangMin 30 to call chimeric reads. Read strandedness was analyzed as described above. For single-cell analysis, we generated a custom genome by Cell Ranger (10× Genomics Cell Ranger 3.0.2) (74) mkref, using a fasta file containing the human genome sequence from ENSEMBL release 93 (ftp://ftp.ensembl.org/pub/release-93/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz) concatenated to the SARS-CoV-2 sequence, GenBank ID: MN988713.1, and a gtf file containing human and viral annotations. Read mapping, assigning reads to cell barcodes and removing PCR duplicates were done with Cell Ranger (10× Genomics Cell Ranger 4.0.0) (74) count, using the custom genome described above. We processed the counts using Seurat (version 3.2.2) (75). We removed cells that had less than 200 genes detected or more than 20% of transcript counts deriving from the mitochondria. For each cell, we counted the number of reads mapping to either the positive or negative viral strand.

Data Availability

All data supporting the findings of this study are available within the article and supporting information. All sequencing data generated in this study have been deposited to the Sequence Read Archive, https://www.ncbi.nlm.nih.gov/sra (accession no. PRJNA721333). All published data analyzed in this study are cited in this article with accession methods provided in Materials and Methods.

Acknowledgments

We thank members in the laboratories of R.J. and R.A.Y. and other colleagues from Whitehead Institute and Massachusetts Institute of Technology (MIT) for helpful discussions and resources. We thank Thomas Volkert and staff from the Whitehead genomics core, and Stuart Levine from the MIT/Koch Institute BioMicro center for sequencing support. We thank Lorenzo Bombardelli for sharing protocol and advice for Tn5 tagmentation-mediated integration enrichment sequencing. We thank Jerold Chun, Inder Verma, Joseph Ecker, and Daniel W. Bellott for discussion and suggestions. This work was supported by grants from the NIH to R.J. (1U19AI131135-01; 5R01MH104610-21) and by a generous gift from Dewpoint Therapeutics and from Jim Stone. S.H.H. was supported by the Intramural Research Program of the Center for Cancer Research of the National Cancer Institute. Finally, we thank Nathans Island for inspiration.

Footnotes

- ↵1To whom correspondence may be addressed. Email: jaenisch@wi.mit.edu.

- Author contributions: L.Z., R.A.Y., and R.J. designed research; L.Z. and A.R. performed experiments; L.Z., A.R., M.I.B., S.H.H., R.A.Y., and R.J. analyzed data; and L.Z. and R.J. wrote the paper with input from all authors.

- Reviewers: A.B., Netherlands Cancer Institute; and A.M.S., Fox Chase Cancer Center.

- Competing interest statement: R.J. is an advisor/co-founder of Fate Therapeutics, Fulcrum Therapeutics, Omega Therapeutics, and Dewpoint Therapeutics. R.A.Y. is a founder and shareholder of Syros Pharmaceuticals, Camp4 Therapeutics, Omega Therapeutics, and Dewpoint Therapeutics.

- This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2105968118/-/DCSupplemental.

- Copyright © 2021 the Author(s). Published by PNAS.

This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

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Eminent MIT Scientists Defend Controversial SARS-CoV-2 Genome Integration Results

Rudolf Jaenisch and Rick Young Report Fragments of SARS-CoV-2 Fuse into Human Genome and Express Non-infectious mRNA in Patient Tissue

By Anjali A. Sarkar, PhD

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A perplexing mystery since the early days of the COVID-19 pandemic has been the recurrence of positive SARS-CoV-2 PCR tests in patients who have long recovered from their initial infection and have not been re-exposed to the virus.

Two eminent biology professors at the Whitehead Institute and the Massachusetts Institute of Technology (MIT)—Rudolf Jaenisch, PhD, and Richard Young, PhD, both members of the National Academy of Sciences—were struck by this curious phenomenon.

“Since both of us have a background in retroviruses, which integrate into the genome as part of their normal life cycle, we hypothesized that the SARS-CoV-2, which does not integrate into the genome as part of its normal life cycle, could be hijacked by retroviral-like transposable elements and get integrated. This could give rise to long-term expression of viral sequences, detectable by PCR, in the absence of infectious virus,” Jaenisch told GEN in an exclusive interview.

The resulting study, recently published in the Proceedings of the National Academy of Sciences—“Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues”—builds on key questions that the team probed as part of an earlier preprint posted on bioRxiv, in their attempts to find a solution to this mystery.

Using three independent sequencing approaches, Jaenisch and his team showed the presence of human–viral chimeric transcripts in infected human HEK293T cells in culture and patient-derived tissues to demonstrate that DNA copies of fragments of SARS-CoV-2’s genomic RNA sequences can integrate into the human genome and can be transcribed into RNA.

At least one of the mechanisms by which this integration occurs is through LINE1 elements—autonomous retrotransposons that can insert themselves (and other sequences) into genomic sites through the back-coding of DNA from an RNA template (reverse transcription). The Whitehead authors showed the presence of consensus or variant LINE1 recognition sites in a majority of human DNA sequences that flank the integrated viral sequences.

These novel findings, no doubt compounded by the pressures of the pandemic, have generated a heated debate in the scientific community.

Gaetan Burgio, MD, PhD, scientist at the Australian National University, has co-led a consortium that has unsuccessfully tried to replicate earlier work from Jaenisch’s team.

Burgio told GEN: “The virus segments inserted into the human genome are rather atypical… some sort of random virus fragments that have attached to a human genome, leading me to think that these sequences are artifactual from the library preparation, contamination during PCR process and sequencing. For example, the polyA tail of the viral genome is missing in these sequences and none of the 3’ end of the viral genome was found in these chimeric sequences. The orientation of the integration of the viral genome doesn’t make sense to me.”

A recently released bioRxiv preprint also suggested that the human SARS-CoV-2 chimeric transcripts detected through RNA sequencing may arise as a sample prep artifact rather than true reverse transcription, integration, and expression.

Ellen Foxman, MD, PhD, assistant professor in the department of laboratory medicine at Yale School of Medicine, reiterated the same concerns. “My overall take on this [PNAS] paper is that it is exploratory research, and that while the data suggests that fragments of the SARS-CoV-2 genome can become integrated in human cells, other explanations for the data are also possible, as the authors discussed.” Foxman’s lab focuses on investigating virus infections in airway passages. She commented here as an expert unrelated to the study.

Foxman added, “Exploratory basic research is very important over the long term, it helps us develop a better understanding of how our bodies and viruses work.”

Jaenisch admitted that the conclusions made in the original bioRxiv preprint were “ill-fated” and the findings, although correct, were not supported by strong evidence.

“Chimeric RNA could be artifactually generated when you prepare your cDNA library for sequencing because the reverse transcriptase jumps between different templates. [In the preprint] we didn’t have direct evidence to show that [viral] DNA integrated into the genome. In the new [PNAS] paper, we now have unambiguous evidence that these viral sequences are integrated into the genome. The most common mechanism [for this] is what’s called LINE1-mediated retroposition, coming from the footprints of the viral sequence in the genome. It’s irrefutable. They can integrate.”

The key question that Jaenisch and his team probe is whether viral sequences integrate and express in patients. This question can only be answered indirectly, as it is technically challenging to obtain direct evidence of rare integration events in the genomic DNA. Analyzing the “sense” or directionality of the sequences of transcribed viral RNA, which are present in greater copy numbers in cells, provides important clues.

The genomic material in SARS-CoV-2 is a positive-sense RNA strand (5’-3’) that has the same polarity as viral mRNA and can be directly translated into viral protein. When SARS-CoV-2 infects and replicates in a host cell, therefore, the plus strand predominates.

“We asked how much minus strand is in [infected] cells. It’s very little. Then we asked, how could minus strands arise? If viral sequences integrate into the genome they integrate in both orientations. DNA analysis shows it is 50–50,” said Jaenisch.

In infected cells where the virus is actively replicating, minus-strand viral RNA counts are 1,000 or less but in patient-derived tissues where there is no clinical evidence for viral replication, up to 50% of the viral transcripts are minus strands.

“This was very convincing evidence for two conclusions: 1) there can indeed be these viral sequences integrating in patients and 2) they can be expressed,” said Jaenisch. The authors detected chimeric sequences that contain minus strand RNA in both infected human HEK293T cells and patient-derived tissues.

One of the concerns regarding evidence of viral integration obtained in human cell culture is whether the same holds true in living organisms. The scarcity of viral integration in host cells poses a technical challenge in answering this question. Jaenisch said, “We would argue human cellular RNA fused to minus strand viral RNA cannot have another explanation. There is integration. RNA is easier to detect since it produces many copies but to detect DNA, you have to see it at the single cell level and that we can’t do.”

Some critics contend that the physiological levels of reverse transcription machinery in human cells are very low and insufficient for cellular integration of SARs-CoV-2. In their cell line experiments, Jaenisch’s team transfected HEK293T cells with LINE1 prior to infection with SARS-CoV-2 to increase the likelihood of detecting rare integration events. This has prompted critics to question the biological relevance of the detected chimeric transcripts.

Burgio said, “These integration events were found in a context of strong overexpression of LINE1 transposable elements, which is not seen in a real-life setting.”

“LINE1 expression is induced in cells under stress,” countered Jaenisch. “Stress can be induced by infection with a virus, by exposure cytokines, by aging, in cancer. So, you could argue when a patient is infected with [SARs-CoV-2] virus it induces LINE1 and that promotes integration… it is a very clear possibility.” The team presented evidence supporting the induction of LINE1 by virus infection. Analogous results have also been observed by other groups.

Young added: “What would be a reasonable hypothesis here is that the stress of the virus infection has elevated the level of reverse transcriptase.” The Whitehead team is pursuing experiments to confirm this hypothesis.

Whether there is any specificity to the site of integration of these viral fragments is currently unresolved, largely due to technical challenges. “These are rare integrations. You cannot clone these cells because the cells die. You have a snapshot of a population. You can’t do the experiments here that you can do with retroviruses,” said Jaenisch.

Young added, “Preliminary data suggests that there are many sites of integration.”

Expressing concerns

Much debate centers around the possibility of these integrated viral sequences generating infectious virus and altering host DNA with deleterious consequences.

“There is no evidence presented that the extremely rare events proposed in this paper would be harmful to human health or could result in live SARS-CoV-2 viruses being produced,” said Foxman.

Jaenisch agreed and emphasized, “The biggest piece of [viral] DNA we find is 5% of the viral genome, 1,600 bps. There is absolutely no way in which infectious virus can be made from these integrated sequences.”

The interpretation of diagnostic PCR tests for SARS-CoV-2, however, acquire a layer of complexity in the light of these findings. “The clear conclusion is that if you are PCR positive it does not mean that you are shedding virus and that you are infectious. You really have to detect infectious virus to make that statement,” said Jaenisch.

A major reason for the charged emotions regarding this study stems from the wider debate about whether mRNA vaccines could similarly integrate into human DNA with potentially deleterious consequences.

Foxman said, “A controversial result such as this one can be important in motivating new areas of research that ultimately lead to big discoveries. However, it would be a mistake to over-interpret this paper as having significance for patient care or vaccines in the current pandemic.”

“There is absolutely no reason to believe that any of the vaccine mRNA is doing the same thing. The viral spike protein mRNA is a tiny piece. Vaccines are not inducing LINE element RTs,” said Young. “Vaccines are protecting against the possibility of long-term seriously debilitating diseases or death.”

The turmoil surrounding the Jaenisch/Young preprint also raises questions regarding the utility of preprints in the scientific process. “In hindsight, preprints are a good thing but to have a review discussion with the public of a paper (which I would have liked to have with the reviewers) is not something I wish to do in the future. If a paper comes out that is not peer reviewed, I don’t think I would like to have a public discussion about it. And that was a very traumatic discussion,” said Jaenisch.

Young added, “Scientific criticism is a key and valuable part of scientists coming to a view about the truth, whether that happens in the form of a preprint or later on… In an emotionally laden environment where some scientific observations are being used for political or other purposes, it is a bit of a perversion of the otherwise quite natural and useful process.”

The Whitehead team’s findings leave numerous questions unanswered. “The key question,” said Jaenisch, “that we do not have an answer to is: are these integrated sequences translated? If they are translated, they could be presented on the cell surface and provoke an immune or autoimmune reaction.” Studies have shown elevated levels of new autoantibodies in some COVID-19 patients.

The Jaenisch/Young team aims to determine which tissues are prone to express viral sequences in patients and are collaborating with Brigham and Women’s Hospital to analyze human tissue samples.

Young said, “Ideas that do not conform to the current way we think about a process are very valuable in exploring a new understanding. It was not thought that these coronaviruses have the means to integrate in the genome. We are proposing that that can happen by a mechanism that is LINE1/RT mediated. It’s naturally going to provoke some interesting discussion. We welcome that discussion.”

“We welcome scientific discussions, not politically motivated distortions,” said Jaenisch.

New research reveals why some patients may test positive for COVID-19 long after recovery

WRITTEN BY

EVA FREDERICK

MAY 06, 2021

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In the early months of the COVID-19 pandemic, healthcare workers analyzing test results began noticing something strange: patients who had already recovered from COVID-19 would sometimes inexplicably test positive on a PCR test weeks or even months later.

Although people can catch COVID-19 for a second time, this did not appear to be the case for these patients; no live viruses were isolated from their samples, and some studies found these false positive results even while holding participants in quarantine. Also, RNAs generally have a short life — most only stick around for a few minutes — so it was unlikely for positive tests to be the result of residual RNAs.

Now, a new paper from the lab of Whitehead Institute Member and MIT professor of biology Rudolf Jaenisch may offer an answer to why some patients continue to test positive after recovery from COVID-19. In the paper, published online May 6 in the Proceedings of the National Academy of Sciences, Jaenisch and collaborators show that genetic sequences from the RNA virus SARS-CoV-2 can integrate into the genome of the host cell through a process called reverse transcription. These sections of the genome can then be “read” into RNAs, which could potentially be picked up by a PCR test.

SARS-CoV-2 is not the only virus that integrates into the human genome. Around eight percent of our DNA consists of the remnants of ancient viruses. Some viruses, called retroviruses, rely on integration into human DNA in order to replicate themselves. “SARS-CoV-2 is not a retrovirus, which means it doesn't need reverse transcription for its replication,” says Whitehead Institute postdoc and first author Liguo Zhang. “However, non-retroviral RNA virus sequences have been detected in the genomes of many vertebrate species, including humans.”

With this in mind, Zhang and Jaenisch began to design experiments to test whether this viral integration could be happening with the novel coronavirus. With the help of Jaenisch lab postdoc Alexsia Richards, the researchers infected human cells with coronavirus in the lab and then sequenced the  DNA from infected cells two days later to see whether it contained traces of the virus’ genetic material.

To ensure that their results could be confirmed with different methodology, they used three different DNA sequencing techniques. In all samples, they found fragments of viral genetic material (though the researchers emphasize that none of the inserted fragments was enough to recreate a live virus).

Zhang, Jaenisch and colleagues then examined the DNA flanking the small viral sequences for clues to the mechanism by which they got there. In these surrounding sequences, the researchers found the hallmark of a genetic feature called a retrotransposon.

Sometimes called “jumping genes,” transposons are sections of DNA that can move from one region of the genome to another. They are often activated to “jump” in conditions of high stress or during cancer or aging, and are powerful agents of genetic change.

One common transposon in the human genome is called the LINE1 retrotransposon, which is made up of a powerhouse combination of DNA-cutting machinery and reverse transcriptase, an enzyme that creates DNA molecules from an RNA template (like the RNA of SARS-CoV-2).

“There’s a very clear footprint for LINE1 integration,” Jaenisch says. “At the junction of the viral sequence to the cellular DNA, it makes a 20 base pair duplication.”

Besides the duplication, another feature as evidence for LINE1-mediated integration is a LINE1 endonuclease recognition sequence. The researchers identified these features in nearly 70 percent of the DNAs that contained viral sequences, but not all, suggesting that the viral RNA may be integrating into cellular DNA via multiple mechanisms.

“The fraction of cells which have the integrating with could be very small,” says Jaenisch. “But even if it's rare, there are more than 140 million people who have been infected already, right?”

To screen for viral integration outside of the lab, the researchers analyzed published datasets of RNA transcripts from different types of samples, including COVID-19 patient samples. With these datasets, Zhang and Jaenisch were able to calculate the fraction of genes that were transcribed in these patients’ cells which contained viral sequences that could be derived from integrated viral copies. The percentage varied from sample to sample, but for some, a relatively large fraction of viral transcripts seem to have been transcribed from viral genetic material integrated into the genome.

A previous draft of the paper with this finding was published online on the preprint server bioRxiv. However, recent research revealed that at least some of the viral-cellular reads could be the product of misleading artefacts of the RNA sequencing method. In the present paper, the researchers were able to eliminate these artefacts that could have been obscuring the results.

Instead of simply tallying transcripts that contained viral material, the researchers looked at which direction the transcripts had been read. If the viral reads were the result of live viruses or existing viral RNAs in the cell, the researchers would expect that most of the viral transcripts would have been read in the correct orientation for the sequences in question; in acutely infected cells in culture, more than 99 percent are in the correct orientation. If the transcripts were the product of random viral integration into the genome, however, there would be a near 50-50 split — half the transcripts would have been read forwards, the other half backwards, relative to the host genes. “This is what we saw in some patient samples,” says Zhang. “It suggests that much of the viral RNA in some samples could be transcribed from integrated sequences.”

Because the dataset they used was quite small, Jaenisch emphasizes that more information is needed to establish exactly how common this phenomenon is in real life and what it might mean for human health.

It is possible that only a very few human cells experience any kind of viral integration at all. In the case of another RNA virus that integrates into the host cell genome, only a fraction of a percent of infected cells (between .001 and .01) contained integrated viral DNA. For SARS-CoV-2, the frequency of integration in humans is still unknown. “The fraction of cells which have the integrating with could be very small,” says Jaenisch. “But even if it's rare, there are more than 140 million people who have been infected already, right?”

In the future, Jaenisch and Zhang plan to investigate whether the fragments of SARS-CoV-2 genetic material could be made into proteins by the cell. “If they do, and trigger immune responses, it may provide continuous protection against the virus,” Zhang says.

They also hope to investigate whether these integrated sections of DNA could be partly to blame for some of the long-term autoimmune consequences that some COVID-19 patients experience. “At this point, we can only speculate,” says Jaenisch. “But one thing we do think we can explain is why some patients are long-term PCR positive.”

Notes

Liguo Zhang, Alexsia Richards, M. Inmaculada Barrasa, Stephen H. Hughes, Richard A. Young, and Rudolf Jaenisch. "Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues." PNAS, May 6, 2020.

The unwanted COVID-19 preprint of Rudolph Jaenisch

Famous MIT lab discovered the coronavirus integrates into human genome and is still transcribed! Between preprint and contributed PNAS paper, three authors and a mechanism were dropped.

BY LEONID SCHNEIDER

MAY 10, 2021

COMMENTS 4

You might recall that preprint claiming SARS-CoV2 would integrate into host’s genome, from the lab of the MIT professor Rudolph Jaenisch at Whitehead Institute. It implied serious consequences for the pandemic, suggesting an infected person would never get rid of the virus, somewhat similar to HIV. The preprint was harshly criticised for its weak science, some demanded its removal for emboldening the antivax movement. Surely now the critics were debunked themselves, because the study passed peer review in the elite journal Proceedings of the National Academy of Sciences of the United States of America (PNAS)!

Oh wait, it did not pass any independent peer review. Being an Academy member, the MIT professor Jaenisch “contributed” the paper, meaning he asked two friendly colleagues, one of them his former postdoc, to write some nice recommendations which were supplied for the antiquated “contributed” track at PNAS.

This was the original preprint, from from December 2020, done in collaboration with Jaenisch’s Whitehead Institute colleague, Richard Young:

Liguo Zhang, Alexsia Richards, Andrew Khalil, Emile Wogram, Haiting Ma, Richard A. Young, Rudolf Jaenisch SARS-CoV-2 RNA reverse-transcribed and integrated into the human genome bioRxiv (2020) doi: 10.1101/2020.12.12.422516

The claim was that the ancient retroviral LINE1 elements residing inside the human genome would somehow get activated and cause a retrotranscription of the SARS-CoV2 RNA genome, thus allowing its genomic integration. People once infected with the coronavirus would still produce its genes like the spike protein, which would result in positive PCR tests results labelling these former COVID-19 patients as active virus careers. Who knows, maybe they would even produce a functional virus, all their lives? A very worrisome thought.

Jaenisch’s preprint was criticised not only on Twitter or in the bioRxiv comment section, like here by Cedric Feschotte. Another preprint Yan et a bioRxiv 2021 declared in February 2021: “the observed HVC [host-virus chimeric] events do not support SARS-CoV2 fusion to cellular genes and/or integration into human genomes.“. Yet another Kazachenka and Kassiotis, bioRxiv 2021 declared:

“human-SARS-CoV-2 chimeric reads found in RNA-seq data may arise during library preparation and do not necessarily signify SARS-CoV-2 reverse transcription, integration in to host DNA and further transcription.“

The Whitehead Institute preprint’s working model of a mechanism was that the coronavirus infection is associated with a dangerous mega-inflammation often called the “cytokine storm” (a popular target of therapies, read here), and it would be this cytokine storm which can somehow re-activate dormant LINE1 elements and cause the genome integration of the virus.

This is where the preprint’s successor, the newly published and “peer reviewed” PNAS paper, gets interesting.

Liguo Zhang, Alexsia Richards, M. Inmaculada Barrasa, Stephen H. Hughes, Richard A. Young, and Rudolf Jaenisch Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues PNAS (2021) doi: 10.1073/pnas.2105968118

The “peer reviewed” study concludes:

“Our data suggest that, in some patient tissues, the majority of all viral transcripts are derived from integrated sequences. Our data provide an insight into the consequence of SARS-CoV-2 infections that may help to explain why patients can continue to produce viral RNA after recovery.”

The mechanism behind SARS-CoV2 genome integration, as provided in the PNAS paper, was:

“we found that DNA copies of SARS-CoV-2 sequences can be integrated into the genome of infected human cells. We found target site duplications flanking the viral sequences and consensus LINE1 endonuclease recognition sequences at the integration sites, consistent with a LINE1 retrotransposon-mediated, target-primed reverse transcription and retroposition mechanism. We also found, in some patient-derived tissues, evidence suggesting that a large fraction of the viral sequences is transcribed from integrated DNA copies of viral sequences, generating viral–host chimeric transcripts.”

No mention of the cytokine storm anymore. What happened? Here a clue: during the “peer review” process between preprint and published PNAS paper, the manuscript mysteriously lost not just the cytokine storm model, but also 3 authors, all postdocs at the Jaenisch lab at Whitehead Institute: Andrew Khalil, Emile Wogram and Haiting Ma.

One of them explained to me:

“The work I contributed to the original draft of the manuscript is no longer included.“

The postdoc added:

“I was/am involved in the myeloid cell-conditioned medium experiments.“

That would mean Figure 3 and Figure S5 of the preprint, which dealt with the cytokine activation of lINE1 elements, and which were dropped from the final paper:

Fig 3 preprint: “LINE-1 expression as an endogenous reverse-transcriptase source in human cells is induced by SARS-CoV-2 infection and cytokine-containing conditioned media treatment.“

Fig S5 preprint: “Cytokine containing media treatment triggers LINE-1 expression in human cells.“

The accompaning text of the preprint explained the concept of the “cytokine storm”:

“Patients infected with SARS-CoV-2 and other corona viruses show evidence of cytokine induction associated with the immune response, and in severe cases experience a cytokine storm35–37, prompting us to investigate whether cytokines alone can induce LINE-1 activation.“

To prove the mechanism, the Whitehead Institute researchers performed the experiments that cancelled postdoc was involved in, and concluded:

“We treated cells with cytokine-containing conditioned media from Myeloid, Microglia, or CAR-T cell cultures and found a ~2-3-fold upregulation of endogenous LINE-1 expression by PCR analysis (Fig. 3f, S5b). Expressed LINE-1 protein (ORF1p) was also confirmed by immunofluorescence staining (Fig. 3g-h, S5a). In summary, our results show induced LINE-1 expression in cells stressed by viral infection or exposed to cytokines, suggesting a molecular mechanism for SARS-CoV-2 retro-integration in human cells.“

That Figure 3 used to be quite central to the preprint’s discovery of molecular mechanism of LINE1 activation due to viral infection, as per preprint’s abstract:

“Human endogenous LINE-1 expression was induced upon SARS-CoV-2 infection or by cytokine exposure in cultured cells, suggesting a molecular mechanism for SARS-CoV-2 retro-integration in patients.”

Now, the preprint may be all about cytokines, but the PNAS paper mentions the word “cytokine” only once:

“It is not known how many antigen-presenting cells are needed to elicit an antigen response, but derepressed LINE1 expression, induced by viral infection or by exposure to cytokines (38⇓–40), may stimulate SARS-CoV-2 integration into the genome of infected cells in patients.“

No, the references 38-40 do not include Jaenisch’s previous preprint. In fact, that preprint is mentioned only once, in passing:

“To investigate the possibility that SARS-CoV-2 sequences integrated into the genome can be expressed, we analyzed published RNA-seq data from SARS-CoV-2–infected cells for evidence of chimeric transcripts (49).“

The postdoc who was once a coauthor said:

“I believe the cytokine work and many of the other data removed from the preprint are still ongoing“

If the work is ongoing, then without this postdoc, apparently? I asked Jaenisch what happened to the 3 preprint authors and the cytokine storm. The MIT professor replied:

“In this paper we addressed the two key questions raised in the preprint in December both of which needed more convincing evidence. The present paper shows clearly that SARS-CoV- sequences can integrate into the genome of cultured cells that were or not transfected with LINE1. The most frequent mechanism of integration is a LINE1-mediated retroposition mechanism because the majority of integrants have all the footprints of this integration process. We felt that the induction of Line 1 by cellular stress, while an interesting and important aspect, needed more data to be totally convincing and we did not address this in the present study (this is why three authors who were involved in these previous experiments but not in the present ones were removed from the author list ). The studies on LIne1 expression are ongoing.“

I wrote back that I understood Jaenisch’s words as dismissal of the cytokine storm mechanism as incorrect. I also argued that even then the removal of the 3 postdocs as co-authors was possibly still not justified. After all, they did contribute to the project experimentally by helping their principal investigator figure out the correct mechanism, or at least dismiss the wrong one. Jaenisch then stated:

“I strongly believe that the LINE1 expression data as presented in the December preprint are correct and significant. But we want to get more data to clearly define what type of elements is induced – our previous results were not conclusive on this issue (and, given the reaction on this ill-fated preprint: we are particularly cautions). The 3 authors who participated in the initial work did not contribute to the PNAS paper so they are not co-authors.“

Wait. Now Jaenisch insists the LINE1 induction via cytokines was “correct and significant“. But he seems not sure if it is specifically LINE1 which causes SARS-CoV2 genome integration, hence the need for “more data to clearly define what type of elements is induced“? But why is the PNAS paper so certain about LINE1 as mechanism then, and concludes in the discussion (without referencing the preprint):

“These and other data are consistent with a target primed reverse transcription and retroposition integration mechanism (41, 42) and suggest that endogenous LINE1 RT can be involved in the reverse transcription and integration of SARS-CoV-2 sequences in the genomes of infected cells.“

It’s all a bit confusing. No wonder the manuscript was previously rejected by another journal. It may be not scientificality convincing enough, while the potential danger of feeding antivaxx paranoia is certainly conceivable. There is this Jaenisch quote in the Science article about the PNAS paper:

“In their new paper, Jaenisch, Young, and colleagues acknowledge that the technique they used accidentally creates human-viral chimeras. “I think it’s a valid point,” Jaenisch says. He adds that when they first submitted the paper to a journal, they knew it needed stronger data, which they hoped to add during the review process. But the journal, like many, requires authors to immediately post all COVID-19 results to a preprint server. “I probably should have said screw you, I won’t put it on bioRxiv. It was a misjudgment,” Jaenisch says.”

Now the crazy thing is that the most heavily criticised aspect of the preprint was NOT about cytokines, but about the reality of SARS-CoV2 genome integration and the alleged role of LINE1 elements therein, which were claimed to be artefacts instead. And yet, the idea of cytokines as mechanism of LINE1 activation, which Jaenisch himself says was correct, was buried, and everyone involved in these experiments thrown off the PNAS paper. Which given PNAS‘ impact factor and status, is no small thing. The Science article ends with:

“And what of the original journal submission? “They rejected it,” Jaenisch says.”

There are actually not many journals which have a preprint mandate at manuscript submission stage, i.e., where posting a preprint is absolutely mandatory to enter peer review. But then again, I was informed that because of the pandemic, many journals mandate that all COVID-19 manuscripts must be first be deposited on a pre-print server and communicated to the WHO before considered for peer review. So unlike I previously speculated, one cannot know which journal Jaenisch first submitted the paper to, but it must have been a big one. Well, PNAS is also very big. In this regard, one of the 3 preprint postdocs who got cancelled told me:

“I was on the original submission, which was based on the preprint that I am listed as an author on.“

So after the manuscript was rejected, Jaenisch could have reconsidered the validity of the whole idea of SARS-CoV2 genome integration. He did reconsider, added another collaboration, and the cytokine data and its 3 contributors were shed. The new manuscript was then contributed to PNAS by Jaenisch, via the journal submission track of same name, meaning he invited his own two peer reviewers and submitted their reports together with the manuscript. A much criticised and often abused track, which turns the whole concept of peer review and editorial gatekeeping on its head.

Surely such a controversial study should have undergone proper peer review before appearing in a high-ranking journal?

Jaenisch however told me:

“I think you fundamentally misunderstand the process of publishing in PNAS: this paper was stringently reviewed, as indicated on the paper, by two eminent scientists, Anton Berns and Ann Skalka, who both have a many decades long track record in retrovirology and in transposon mediated genomic integration issues.“

The point here however is not the eminence of Anton Berns (Jaenisch’s former postdoc) and of Ann Skalka (emeritus director of Fox Chase Cancer Center, where Jaenisch once trained), but that Jaenisch invited their reviews himself. So the MIT professor clarified:

“It is correct that in a contributed paper the NAS member can suggest reviewers. They are carefully and stringently considered by the PNAS board and all correspondence goes between board and reviewer. I suggested the two most competent and eminent scientists in the field I could think of and they agreed to review this paper. It is absolutely wrong to suggest that a PNAS paper is not peer reviewed – the board has very stringent criteria.“

Still doesn’t explain why the contributed track at PNAS, a choice which certainly doesn’t help allay the criticisms. If anything, the moral of the story is about the usefulness of preprints in debunking weak science and in opening the doors to how academic sausages are really made.

MIT Scientists Jaenisch and Young Reiterate SARS-CoV-2 Genome Integration Results

By

Anjali A. Sarkar, PhD

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Coronavirus structure

A curious phenomenon seen as a result of testing during the COVID-19 pandemic has been the small subset of patients who test positive for the disease long after they have recovered from their infection and also have not been re-exposed to the virus.

Two eminent biology professors at the Whitehead Institute and the Massachusetts Institute of Technology (MIT)—Rudolf Jaenisch, Ph.D., and Richard Young, Ph.D., both members of the National Academy of Sciences—were struck by this curious phenomenon and believe they have uncovered why this happens.

“Since both of us have a background in retroviruses, which integrate into the genome as part of their normal life cycle, we hypothesized that the SARS-CoV-2, which does not integrate into the genome as part of its normal life cycle, could be hijacked by retroviral-like transposable elements and get integrated. This could give rise to long-term expression of viral sequences, detectable by PCR, in the absence of infectious virus,” Jaenisch told Clinical OMICs’ sister publication GEN in an exclusive interview.

The resulting study, recently published in the Proceedings of the National Academy of Sciences—“Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues”—builds on key questions that the team probed as part of an earlier preprint posted on bioRxiv, in their attempts to find a solution to this mystery.

Using three independent sequencing approaches, Jaenisch and his team showed the presence of human–viral chimeric transcripts in infected human HEK293T cells in culture and patient-derived tissues to demonstrate that DNA copies of fragments of SARS-CoV-2’s genomic RNA sequences can integrate into the human genome and can be transcribed into RNA.

At least one of the mechanisms by which this integration occurs is through LINE1 elements—autonomous retrotransposons that can insert themselves (and other sequences) into genomic sites through the back-coding of DNA from an RNA template (reverse transcription). The Whitehead authors showed the presence of consensus or variant LINE1 recognition sites in a majority of human DNA sequences that flank the integrated viral sequences.

These novel findings, no doubt compounded by the pressures of the pandemic, have generated a heated debate in the scientific community.

Gaetan Burgio, M.D., Ph.D., scientist at the Australian National University, has co-led a consortium that has unsuccessfully tried to replicate earlier work from Jaenisch’s team.

Burgio said: “The virus segments inserted into the human genome are rather atypical… some sort of random virus fragments that have attached to a human genome, leading me to think that these sequences are artifactual from the library preparation, contamination during PCR process and sequencing. For example, the polyA tail of the viral genome is missing in these sequences and none of the 3’ end of the viral genome was found in these chimeric sequences. The orientation of the integration of the viral genome doesn’t make sense to me.”

A recently released bioRxiv preprint also suggested that the human SARS-CoV-2 chimeric transcripts detected through RNA sequencing may arise as a sample prep artifact rather than true reverse transcription, integration, and expression.

Ellen Foxman, M.D., Ph.D.., assistant professor in the department of laboratory medicine at Yale School of Medicine, reiterated the same concerns. “My overall take on this [PNAS] paper is that it is exploratory research, and that while the data suggests that fragments of the SARS-CoV-2 genome can become integrated in human cells, other explanations for the data are also possible, as the authors discussed.” Foxman’s lab focuses on investigating virus infections in airway passages. She commented here as an expert unrelated to the study.

Foxman added, “Exploratory basic research is very important over the long term, it helps us develop a better understanding of how our bodies and viruses work.”

Jaenisch admitted that the conclusions made in the original bioRxiv preprint were “ill-fated” and the findings, although correct, were not supported by strong evidence.

“Chimeric RNA could be artifactually generated when you prepare your cDNA library for sequencing because the reverse transcriptase jumps between different templates. [In the preprint] we didn’t have direct evidence to show that [viral] DNA integrated into the genome. In the new [PNAS] paper, we now have unambiguous evidence that these viral sequences are integrated into the genome. The most common mechanism [for this] is what’s called LINE1-mediated retroposition, coming from the footprints of the viral sequence in the genome. It’s irrefutable. They can integrate.”

The key question that Jaenisch and his team probe is whether viral sequences integrate and express in patients. This question can only be answered indirectly, as it is technically challenging to obtain direct evidence of rare integration events in the genomic DNA. Analyzing the “sense” or directionality of the sequences of transcribed viral RNA, which are present in greater copy numbers in cells, provides important clues.

The genomic material in SARS-CoV-2 is a positive-sense RNA strand (5’-3’) that has the same polarity as viral mRNA and can be directly translated into viral protein. When SARS-CoV-2 infects and replicates in a host cell, therefore, the plus strand predominates.

“We asked how much minus strand is in [infected] cells. It’s very little. Then we asked, how could minus strands arise? If viral sequences integrate into the genome they integrate in both orientations. DNA analysis shows it is 50–50,” said Jaenisch.

In infected cells where the virus is actively replicating, minus-strand viral RNA counts are 1,000 or less but in patient-derived tissues where there is no clinical evidence for viral replication, up to 50% of the viral transcripts are minus strands.

“This was very convincing evidence for two conclusions: 1) there can indeed be these viral sequences integrating in patients and 2) they can be expressed,” said Jaenisch. The authors detected chimeric sequences that contain minus strand RNA in both infected human HEK293T cells and patient-derived tissues.

One of the concerns regarding evidence of viral integration obtained in human cell culture is whether the same holds true in living organisms. The scarcity of viral integration in host cells poses a technical challenge in answering this question. Jaenisch said, “We would argue human cellular RNA fused to minus strand viral RNA cannot have another explanation. There is integration. RNA is easier to detect since it produces many copies but to detect DNA, you have to see it at the single cell level and that we can’t do.”

Some critics contend that the physiological levels of reverse transcription machinery in human cells are very low and insufficient for cellular integration of SARs-CoV-2. In their cell line experiments, Jaenisch’s team transfected HEK293T cells with LINE1 prior to infection with SARS-CoV-2 to increase the likelihood of detecting rare integration events. This has prompted critics to question the biological relevance of the detected chimeric transcripts.

Burgio said, “These integration events were found in a context of strong overexpression of LINE1 transposable elements, which is not seen in a real-life setting.”

“LINE1 expression is induced in cells under stress,” countered Jaenisch. “Stress can be induced by infection with a virus, by exposure cytokines, by aging, in cancer. So, you could argue when a patient is infected with [SARs-CoV-2] virus it induces LINE1 and that promotes integration… it is a very clear possibility.” The team presented evidence supporting the induction of LINE1 by virus infection. Analogous results have also been observed by other groups.

Young added: “What would be a reasonable hypothesis here is that the stress of the virus infection has elevated the level of reverse transcriptase.” The Whitehead team is pursuing experiments to confirm this hypothesis.

Whether there is any specificity to the site of integration of these viral fragments is currently unresolved, largely due to technical challenges. “These are rare integrations. You cannot clone these cells because the cells die. You have a snapshot of a population. You can’t do the experiments here that you can do with retroviruses,” said Jaenisch.

Young added, “Preliminary data suggests that there are many sites of integration.”

Expressing concerns

Much debate centers around the possibility of these integrated viral sequences generating infectious virus and altering host DNA with deleterious consequences.

“There is no evidence presented that the extremely rare events proposed in this paper would be harmful to human health or could result in live SARS-CoV-2 viruses being produced,” said Foxman.

Jaenisch agreed and emphasized, “The biggest piece of [viral] DNA we find is 5% of the viral genome, 1,600 bps. There is absolutely no way in which infectious virus can be made from these integrated sequences.”

The interpretation of diagnostic PCR tests for SARS-CoV-2, however, acquire a layer of complexity in the light of these findings. “The clear conclusion is that if you are PCR positive it does not mean that you are shedding virus and that you are infectious. You really have to detect infectious virus to make that statement,” said Jaenisch.

A major reason for the charged emotions regarding this study stems from the wider debate about whether mRNA vaccines could similarly integrate into human DNA with potentially deleterious consequences.

Foxman said, “A controversial result such as this one can be important in motivating new areas of research that ultimately lead to big discoveries. However, it would be a mistake to over-interpret this paper as having significance for patient care or vaccines in the current pandemic.”

“There is absolutely no reason to believe that any of the vaccine mRNA is doing the same thing. The viral spike protein mRNA is a tiny piece. Vaccines are not inducing LINE element RTs,” said Young. “Vaccines are protecting against the possibility of long-term seriously debilitating diseases or death.”

The turmoil surrounding the Jaenisch/Young preprint also raises questions regarding the utility of preprints in the scientific process. “In hindsight, preprints are a good thing but to have a review discussion with the public of a paper (which I would have liked to have with the reviewers) is not something I wish to do in the future. If a paper comes out that is not peer reviewed, I don’t think I would like to have a public discussion about it. And that was a very traumatic discussion,” said Jaenisch.

Young added, “Scientific criticism is a key and valuable part of scientists coming to a view about the truth, whether that happens in the form of a preprint or later on… In an emotionally laden environment where some scientific observations are being used for political or other purposes, it is a bit of a perversion of the otherwise quite natural and useful process.”

The Whitehead team’s findings leave numerous questions unanswered. “The key question,” said Jaenisch, “that we do not have an answer to is: are these integrated sequences translated? If they are translated, they could be presented on the cell surface and provoke an immune or autoimmune reaction.” Studies have shown elevated levels of new autoantibodies in some COVID-19 patients.

The Jaenisch/Young team aims to determine which tissues are prone to express viral sequences in patients and are collaborating with Brigham and Women’s Hospital to analyze human tissue samples.

Young said, “Ideas that do not conform to the current way we think about a process are very valuable in exploring a new understanding. It was not thought that these coronaviruses have the means to integrate in the genome. We are proposing that that can happen by a mechanism that is LINE1/RT mediated. It’s naturally going to provoke some interesting discussion. We welcome that discussion.”

“We welcome scientific discussions, not politically motivated distortions,” said Jaenisch.

New Results

SARS-CoV-2 RNA reverse-transcribed and integrated into the human genome

Liguo Zhang, Alexsia Richards, Andrew Khalil, Emile Wogram, Haiting Ma, Richard A. Young, Rudolf Jaenisch

doi: https://doi.org/10.1101/2020.12.12.422516

This article is a preprint and has not been certified by peer review [what does this mean?].

52010456571

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Summary

Prolonged SARS-CoV-2 RNA shedding and recurrence of PCR-positive tests have been widely reported in patients after recovery, yet these patients most commonly are non-infectious1–14. Here we investigated the possibility that SARS-CoV-2 RNAs can be reverse-transcribed and integrated into the human genome and that transcription of the integrated sequences might account for PCR-positive tests. In support of this hypothesis, we found chimeric transcripts consisting of viral fused to cellular sequences in published data sets of SARS-CoV-2 infected cultured cells and primary cells of patients, consistent with the transcription of viral sequences integrated into the genome. To experimentally corroborate the possibility of viral retro-integration, we describe evidence that SARS-CoV-2 RNAs can be reverse transcribed in human cells by reverse transcriptase (RT) from LINE-1 elements or by HIV-1 RT, and that these DNA sequences can be integrated into the cell genome and subsequently be transcribed. Human endogenous LINE-1 expression was induced upon SARS-CoV-2 infection or by cytokine exposure in cultured cells, suggesting a molecular mechanism for SARS-CoV-2 retro-integration in patients. This novel feature of SARS-CoV-2 infection may explain why patients can continue to produce viral RNA after recovery and suggests a new aspect of RNA virus replication.

Introduction

Continuous or recurrent positive SARS-CoV-2 PCR tests have been reported in patients weeks or months after recovery from an initial infection1–14. Although bona fide re-infection of SARS-CoV-2 after recovery has been reported lately15, cohort-based studies with strict quarantine on subjects recovered from COVID-19 suggested “re-positive” cases were not caused by re-infection16,17. Furthermore, no replication-competent virus was isolated or spread from these PCR-positive patients1–3,5,6,12. The cause for such prolonged and recurrent viral RNA production is unknown. As positive-stranded RNA viruses, SARS-CoV-2 and other beta-coronaviruses such as SARS-CoV-1 and MERS employ an RNA-dependent RNA polymerase to replicate their genomic RNA and transcribe their sub-genomic RNAs18–20. One possibility is that SARS-CoV-2 RNAs could be reverse-transcribed and integrated into the human genome, and transcription of the integrated DNA copies could be responsible for positive PCR tests.

Endogenous reverse transcriptase (RT) activity has been observed in human cells, and the products of reverse transcription have been shown to become integrated into the genome21,22. For example, APP transcripts have been shown to be reverse-transcribed by endogenous RT, with resultant APP fragments integrated into the genome of neurons and transcribed22. Human LINE-1 elements (~17% of the human genome), a type of autonomous retrotransposons, are a potential source of endogenous RT, able to retro-transpose themselves and other non-autonomous elements such as Alu21,23.

Results

Expression of viral-cellular chimeric transcripts in infected cultured and in patient-derived cells is consistent with genomic integration of viral sequences

To investigate the possibility of viral integration into virus infected cells we analyzed published RNA-Seq data from SARS-CoV-2-infected cells for evidence of chimeric transcripts, which would be indicative of viral integration into the genome and expression. Examination of these data sets 24–30 (Fig. S1a-b) revealed a substantial number of host-viral chimeric reads (Fig. 1a-c, S1c). These occurred in multiple sample types, including cells and organoids from lung/heart/brain/stomach tissues, as well as BALF cells directly isolated from COVID-19 patients (Fig. 1c). Chimeric read abundance was positively correlated with viral RNA level across the sample types (Fig. 1c). Chimeric reads generally accounted for 0.004% - 0.14% of total SARS-CoV-2 reads across the samples, with a 69.24% maximal number of reads in bronchoalveolar lavage fluid cells derived from severe COVID19 patients and near no chimeric reads from patient blood buffy coat cells (corresponding to almost no total SARS-CoV-2 reads). A majority of chimeric junctions mapped to SARS-CoV-2 nucleocapsid (N) sequence (Fig. 1d-e). This is consistent with the finding that nucleocapsid (N) RNA is the most abundant SARS-CoV-2 sub-genomic RNA31, and thus is most likely to be a target for reverse transcription and integration. These analyses support the hypothesis that SARS-CoV-2 RNA may retro-integrate into the genome of infected cells resulting in the production of chimeric viral-cellular transcripts.

Supplementary Figure 1.

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Supplementary Figure 1.Human – SARS-CoV-2 chimeric reads identified from published RNA-Seq data.

a) Published data used to identify human – CoV2 chimeric reads summarizing GEO accession number (data ID), sample type, infection method/type (MOI: Multiplicity Of Infection), RNA-Seq format (single or paired-end with read length), and threshold to call chimeric reads (Min overhang: minimum number of bases mapped to either human or SARS-CoV-2 genome/transcriptome to call a chimeric reads). b) Comparison of SARS-CoV-2 read fraction of total mappable reads in the published RNA-Seq datasets as shown in a). c) One chimeric read example (149 nt) from Calu3 (infected) RNA-Seq with 57 nt mapped to human Chromosome × (green) and 92 nt (magenta) mapped to the SARS-CoV-2 genome.

Figure 1.

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Figure 1.Human – SARS-CoV-2 chimeric transcripts identified in published data sets of infected cultured and patient-derived cells.

a) Pipeline to identify human-CoV2 chimeric RNA-Seq reads. b) Diagram showing human-CoV2 chimeric reads mapped to potential SARS-CoV-2 integration sites in the human genome from published RNA-Seq data. c) Scatter plot showing human-CoV2 chimeric read number (per million total mappable reads, y-axis) versus SARS-CoV-2 read fraction of total mappable reads (x-axis) in published RNA-Seq datasets (summarized in Supplementary Figure 1a) from different bio-samples with SARS-CoV-2 infection. d-e) Human-CoV2 chimeric read junctions (duplicates removed) mapped to the SARS-CoV-2 genome (d) and distribution among SARS-CoV-2 genes (e, three biological replicates; mean ± s.e.m.). RNA-Seq data is from SARS-CoV-2 infected Calu3 cells (see Supplementary Figure 1a). Chimeric read junction is defined as the “breaking point” of sequences mapped to human or SARS-CoV-2 genome/transcriptome in a given RNA-Seq read.

SARS-CoV-2 RNA can be reverse-transcribed and integrated into the human genome in cells overexpressing a reverse transcriptase

To provide experimental evidence for reverse-transcription and integration of SARS-CoV-2 RNA, we overexpressed human LINE-1 or HIV-1 reverse transcriptase (RT) in HEK293T cells and infected the transduced cells with SARS-CoV-2. The cells were tested 2 days after infection for viral sequences by PCR or fluorescence in situ hybridization (FISH) (Fig. 2a). Considering that the N RNA is the most abundant SARS-CoV-2 sub-genomic RNA31 and is most likely to be retro-integrated (Fig. 1d-e), we chose four N – targeting PCR primer sets that are used in COVID-19 tests (primer source from WHO32, Fig. 2a). PCR amplification of purified cellular DNA showed positive gel-bands in cells with human LINE-1 or HIV-1 RT overexpression (Fig. 2b) but not in non-transfected or non-infected cells. To test whether the DNA copies of N sequences were integrated into the cellular genome, we gel-purified cell genomic DNA (gDNA, >23 kb, Fig. S2a) and qPCR confirmed N sequences in gDNA of cells with expression of all three types of RT (Fig. 2c). Cells with strong expression of LINE-1 driven by a CMV promoter showed ~8-fold higher signals of N sequence detection suggesting a higher copy-number of integrated N sequences than in cells expressing LINE-1 driven by its natural promoter (5’UTR) or HIV-1 RT (Fig. 2c). We were able to clone full-length N DNA from gDNA of cells overexpressing CMV-LINE-1 and confirmed its sequence by Sanger sequencing (Fig. S2b). We did not detect the full-length N sequence from gDNA of cells transfected with 5’UTR-LINE-1 or HIV-1 RT, which may be due to lower expression of RT in these cells (Fig. S2b). We further confirmed that purified SARS-CoV-2 RNA from infected cells can be reverse-transcribed in vitro by lysates of cells expressing either LINE-1 or HIV-1 RT (Fig. S2c-d).

Supplementary Figure 2.

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Supplementary Figure 2.SARS-CoV-2 RNA can be reverse-transcribed in vivo and in vitro by other sources of reverse transcriptase.

a) Gel purification of large-fragment genomic DNA (yellow boxes) from SARS-CoV-2 infected HEK293T cells carrying transfected HIV-1 RT, CMV-LINE1 or 5’UTR-LINE1. b) Cloning and Sanger sequencing of DNA copy of full-length SARS-CoV-2 N sequence (CoV2 fl N, yellow box) from gel-purified HEK293T genomic DNA as shown in a). CoV2 fl N: amplification of full-length N sequence (1.26 kb) by primers targeting the two ends of N. HSPA1A: human HSPA1A gene as a control. Note that we can only detect full-length N sequence in gDNA from cells with CMV-LINE-1 expression, corresponding to the high copy-number of integrated N sequences as shown in Figure 2c. c)In vitro reverse transcription of SARS-CoV-2 RNA by adding RNA purified from SARS-Cov-2 infected HEK293T cells to a commercial reverse transcriptase (I, SSIII, with oligo dT and random hexamer primers, positive control), or HEK293T cell lysate (II), or lysates of HEK293T cells expressing HIV-1 reverse transcriptase without (III) or with (IV) heat inactivation. Gel images showing PCR detection of SARS-CoV-2 N sequences from the in vitro reverse transcription products using primer sets (N1 – N4) as shown in Figure 2a. HSPA1A and TUBB: PCR primer sets against human HSPA1A and TUBB genes as controls. d) Same in vitro reverse transcription and PCR detection setup as in c) using lysates of HEK293T cells expressing HIV-1 reverse transcriptase or human LINE-1.

Figure 2.

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Figure 2.SARS-CoV-2 RNA can be reverse-transcribed and integrated into the host genome in cells with reverse transcriptase expression.

a) Experimental workflow (top), PCR primer sets (shown as amplicons, brown) and single-molecule RNA-FISH probes (red) to detect reverse-transcription and integration of SARS-CoV-2 nucleocapsid (N) sequence (middle, blue). b) PCR detection of SARS-CoV-2 N sequences in cellular DNA purified from mock (left) or SARS-CoV-2 (right) infected HEK293T cells without or with transfection of human LINE-1 (CMV-LINE1 or 5’UTR-LINE1) or HIV-1 RT. HSPA1A: human HSPA1A gene as control; N1 – N4: SARS-CoV-2 N sequences as shown in a). c) qPCR detection and copy-number estimation of SARS-CoV-2 N sequences on gel-purified HEK293T genomic DNA. HSPA1A: human HSPA1A gene as a reference; N2, N3: SARS-CoV-2 N sequences as shown in a). Three biological replicates; mean ± standard error of the mean (s.e.m.). d) Single-molecule RNA-FISH (red) targeting SARS-CoV-2 N sequence using probes shown in a) plus LINE-1 ORF1 protein immuno-staining (green) and merged channels with DAPI (blue) in SARS-CoV-2 infected HEK293T cells with (left) or without (right) transfected LINE-1. Insets: 2.5x enlargement of region in white-box to show nuclear signals of SARS-CoV-2 N sequence (white arrows). Images were single z-slices from 3D optical sections (0.2-μm z-steps). e) Fraction of HEK293T cells infected by SARS-CoV-2 (indicated by cytoplasmic FISH signals) showing nuclear FISH signals of N sequence with (+ LINE-1 O/E, n = 75) or without (-LINE-1 O/E, n = 57) LINE-1 overexpression (indicated by LINE-1 ORF1 protein immuno-staining). Combination of two independent cell samples; Chi-Square Test of Homogeneity.

We conducted single-molecule RNA-FISH (smRNA-FISH) using fluorophore-labeled oligo-nucleotide probes targeting N (Fig. 2a) to confirm that viral N sequences were integrated and detected their transcription in the nucleus. SARS-CoV-2 infected cells showed the expected cytoplasmic FISH signals of N RNA (Fig. S3a). N RNA FISH signals were detected in cell nuclei with cells overexpressing LINE-1 (Fig. 2d, S3b), indicating nascent transcription sites of integrated N sequences. In the same cell population, a significantly higher fraction (~35%) of infected cells overexpressing LINE-1, as indicated by LINE-1 ORF1p immunostaining, showed nuclear N signals than cells not overexpressing LINE-1 (~12%) (Fig. 2e). A significantly higher fraction of infected cells that were transfected with LINE-1 plasmid (~80% transfection efficiency) showed positive nuclear N FISH signals (~30%) as compared to non-transfected cells (13%; Fig. S3c). Infected but not transfected cells also exhibited nuclear N signals, albeit at a lower frequency (~10%; Fig. 2e, S3c), implying integration of SARS-CoV-2 N RNA by cell endogenous RT activity.

Supplementary Figure 3.

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Supplementary Figure 3.SARS-CoV-2 N RNA signals detected in cell nuclei by single-molecule RNA-FISH.

a-b) Example images of single-molecule RNA-FISH (red/grey) targeting SARS-CoV-2 N sequence using probes shown in Figure 2a and merged channels with DAPI (blue) in SARS-CoV-2 infected HEK293T cells without (a) or with (b) human LINE-1 transfection. Insets in b): 4x enlargement of regions in white-boxes to show nuclear signals of SARS-CoV-2 N sequence (white arrows). c) Comparison of nuclear N RNA-FISH signals in SARS-CoV-2 infected HEK293T cells without or with human LINE-1 transfection. Left: example images as in a) and b); Right: fraction of HEK293T cells infected by SARS-CoV-2 (indicated by cytoplasmic FISH signals) showing nuclear N RNA-FISH signals in cell populations without (left bar, n = 109) or with (right bar, n = 103) CMV-LINE-1 plasmid transfection (~80% transfection efficiency). Combination of two independent cell samples; Chi-Square Test of Homogeneity. All images shown were single z-slices from 3D optical sections (0.2-μm z-steps).

Human endogenous LINE-1 expression induced by SARS-CoV-2 infection and cytokines correlates with retro-integration

Human LINE-1 elements are autonomous retro-transposons with their encoded reverse transcriptase (ORF2p) and supporting protein (ORF1p) also aiding non-autonomous elements to retro-transpose, such as Alu and other cellular RNAs21. We found that expression of LINE-1 elements was significantly up-regulated in published RNA-Seq data of cells upon infection with SARS-CoV-2 and correlated with chimeric read abundance (Fig. 3a-b, S4a-d, compare Calu3 cells that are efficiently infected versus NHBE cells that are resistant to infection). Although the upregulation in Calu3 was not higher than that in NHBE, multiple LINE-1 elements were upregulated as compared to just one in NHBE (Fig. 3a, S4b, d). Expression analysis using LINE-1 specific primers33,34 showed a ~3-4-fold up-regulation of LINE-1 in Calu3 cells when infected by SARS-CoV-2 (Fig. 3c). Moreover, PCR analysis on Calu3 cellular DNA showed retro-integration of SARS-CoV-2 N sequences after infection (Fig. 3d-e), possibly by the activated LINE-1 reverse transcriptase.

Supplementary Figure 4.

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Supplementary Figure 4.LINE-1 induction in human cells correlates with SARS-CoV-2 infection.

a, c) Log2 fold-changes (x-axis) of different types of human repetitive elements (y-axis) with significant (FDR < 0.05) expression changes in SARS-CoV-2 versus mock infected Calu3 (a) or NHBE (c) cells from published RNA-Seq data (GSE147507). b, d) Fold changes (y-axis) of different human LINE-1 families (x-axis) with significant (FDR < 0.05) expression changes in SARS-CoV-2 versus mock infected Calu3 (b) or NHBE (d) cells from published RNA-Seq data (GSE147507, see Supplementary Figure 1a).

Figure 3.

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Figure 3.LINE-1 expression as an endogenous reverse-transcriptase source in human cells is induced by SARS-CoV-2 infection and cytokine-containing conditioned media treatment.

a) RNA-Seq (GSE147507, see Supplementary Figure 1a) differential expression analysis for all human repetitive elements in SARS-CoV-2 versus mock-infected Calu3 (left) or NHBE (right) cells. Volcano plots showing −Log10 p-values (y-axis) versus Log2 fold-changes (x-axis) for all human repetitive elements with (orange circle) or without (grey circle) significant expression changes (SARS-CoV-2 versus mock-infected); dots: LINE-1 families with (dark blue) or without (light blue) significant expression changes. b) Scatter plot showing human-CoV2 chimeric read number (per million total mappable reads, y-axis) versus SARS-CoV-2 read fraction of total mappable reads (x-axis) in published RNA-Seq (GSE147507, see Supplementary Figure 1a) from infected Calu3 (magenta) or NHBE (red) cells. c) Endogenous LINE-1 expression fold-changes between SARS-CoV-2 versus mock-infected Calu3 cells measured by RT-qPCR with primers probing 5’UTR, ORF1, or 3’UTR regions of LINE-1. Reference genes: GAPDH and TUBB. Three biological replicates; mean ± s.e.m. d) qPCR detection and copy-number estimation of SARS-CoV-2 N sequences in mock (green) or SARS-CoV-2 infected (magenta) Calu3 cellular DNA. HSPA1A: human HSPA1A gene as a reference; N2, N3: SARS-CoV-2 N sequences as shown in Figure 1a. Three biological replicates; mean ± s.e.m; n.d.: not detected. e) Gel purification of large-fragment genomic DNA (yellow box, top) from SARS-CoV-2 infected Calu3 cells and PCR detection of SARS-CoV-2 N sequences in the purified genomic DNA (bottom) with same primer sets as in d). f) Endogenous LINE-1 expression fold-changes in Calu3 cells comparing Myeloid conditioned versus basal media treatment measured by RT-qPCR with primers probing 5’UTR, ORF1, or 3’UTR regions of LINE-1. Reference genes: GAPDH and TUBB. Three biological replicates; mean ± s.e.m. g) LINE-1 ORF1 protein immuno-staining (magenta, same exposure and intensity scaling) plus merged channels with DAPI (blue) in Calu3 cells cultured in basal or myeloid conditioned media. Scale bar: 10 μm. h) Normalized cellular total LINE-1 ORF1p immuno-staining signals of Calu3 cells cultured in basal (n = 84, mean = 1.0, median = 0.9) or myeloid conditioned media (n = 126, mean = 1.7, median = 1.5). Combination of two independent cell samples. Box plots show median (inside line), means (red dot), interquartile range (IQR, box), and upper/lower quartile ± 1.5-times IQRs (whiskers). Welch’s t-test.

Patients infected with SARS-CoV-2 and other corona viruses show evidence of cytokine induction associated with the immune response, and in severe cases experience a cytokine storm35–37, prompting us to investigate whether cytokines alone can induce LINE-1 activation. We treated cells with cytokine-containing conditioned media from Myeloid, Microglia, or CAR-T cell cultures and found a ~2-3-fold upregulation of endogenous LINE-1 expression by PCR analysis (Fig. 3f, S5b). Expressed LINE-1 protein (ORF1p) was also confirmed by immunofluorescence staining (Fig. 3g-h, S5a). In summary, our results show induced LINE-1 expression in cells stressed by viral infection or exposed to cytokines, suggesting a molecular mechanism for SARS-CoV-2 retro-integration in human cells.

Supplementary Figure 5.

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Supplementary Figure 5.Cytokine containing media treatment triggers LINE-1 expression in human cells.

a) LINE-1 ORF1 protein immuno-staining (magenta, same exposure and intensity scaling, 1st column: no primary antibody control) plus merged channels with DAPI (blue) in HEK293T cells cultured in basal (1st and 2nd columns) or microglia conditioned media (3rd column) or LPS-treated microglia conditioned media (4th column). Scale bar: 10 μm. b) Endogenous LINE-1 expression fold-changes in Calu3 cells between CAR-T conditioned (diluted with basal media at indicated percentage in volume) versus basal media treatment measured by RT-qPCR with primers probing 5’UTR, ORF1, or 3’UTR regions of LINE-1. Reference genes: GAPDH and TUBB. Three independent cell samples treated with two batches of media; mean ± s.e.m.

Discussion

In this study, we showed evidence that SARS-CoV-2 RNAs can be reverse-transcribed and integrated into the human genome by several sources of reverse transcriptase such as activated human LINE-1 or co-infected retrovirus (HIV). We found LINE-1 expression can be induced upon SARS-CoV-2 infection or cytokine exposure, suggesting a molecular mechanism responsible for SARS-CoV-2 retro-integration in patients. Moreover, our results suggest that the integrated SARS-CoV-2 sequences can be transcribed, as shown by RNA-Seq and smRNA-FISH data, providing a possible explanation for the presence of viral sequences at later times after initial virus exposure and in the absence of detectable infectious virus1–14. The retro-inserted SRAS-CoV-2 sequences are most likely sub-genomic fragments, as the integration junctions are mostly enriched at the N sequence (Fig. 1d-e), excluding the production of infectious virus. Our data may also explain that patients, after recovery from disease symptoms, may become again positive for viral sequences as detected by PCR1,8–14.

An important follow-up question is whether these integrated SARS-CoV-2 sequences can express viral antigens. If so, it will be of clinical interest to assess whether viral antigens expressed from integrated virus fragments could trigger an immune response in patients that could affect the course and treatment of the disease. It is possible that the clinical consequences of the integrated viral fragments may depend on their insertion sites in the human genome, and on epigenetic regulation which has been shown in HIV patients38. Careful analysis on SARS-CoV-2 retro-integration sites in patient samples and correlation with disease severity will help to elucidate potential clinical consequences. Furthermore, immune response may vary depending on an individual’s underlying conditions. More generally, our results suggest a novel aspect of infection possibly also for other common disease-causing RNA viruses such as Dengue, Zika or Influenza virus, which could be subject to retro-integration and perhaps affect disease progression.

Human LINE-1 accounts for ~17% of the human genome, ~100 out of 500,000 copies of which are active21,23. LINE-1 – encoded reverse-transcriptase (ORF2p) and supporting protein (ORF1p) are known to retro-transpose not only LINE-1 transcripts (in Cis), but also other RNA species such as Alu (SINE) and cellular mRNA (in Trans, creating processed pseudogenes), with a “target-site – primed reverse transcription” mechanism21. LINE-1 proteins have been shown as nucleic acid chaperones with high RNA binding affinity39, therefore it is perhaps not surprising that they can retro-integrate exogenous viral RNAs. From an evolutionarily perspective, retro-integration of viral RNA by LINE-1 could be an adaptive response by the host to provide sustaining antigen expression possibly enhancing protective immunity. Conversely, retro-integration of viral RNAs could be detrimental and cause a more severe immune response in patients such as a “cytokine storm” or auto-immune reactions.

Our results may also be relevant for current clinical trials of antiviral therapies40. The reliance of PCR tests to assess the effect of treatments on viral replication and viral load may not reflect the efficacy of the treatment to suppress viral replication as the PCR assay may detect viral transcripts from viral sequences stably integrated into the genome rather than infectious virus.

Methods

Cell culture and plasmid transfection

HEK293T cells were obtained from ATCC (CRL-3216) and cultured in DMEM supplemented with 10% heat-inactivated FBS (Hyclone, SH30396.03) and 2mM L-glutamine (MP Biomedicals, IC10180683) following ATCC’s method. Calu3 cells were obtained from ATCC (HTB-55) and cultured in EMEM (ATCC 30-2003) supplemented with 10% heat-inactivated FBS (Hyclone, SH30396.03) following ATCC’s method.

Plasmid for HIV-1 reverse transcriptase expression: pCMV-dR8.2 dvpr was a gift from Bob Weinberg (Addgene plasmid # 8455; http://n2t.net/addgene:8455; RRID:Addgene_8455)41. Plasmids for human LINE-1 expression: pBS-L1PA1-CH-mneo (CMV-LINE-1) was a gift from Astrid Roy-Engel (Addgene plasmid # 51288; http://n2t.net/addgene:51288; RRID:Addgene_51288)42; EF06R (5’UTR-LINE-1) was a gift from Eline Luning Prak (Addgene plasmid # 42940; http://n2t.net/addgene:42940; RRID:Addgene_42940)43. Transfection was done with Lipofectamine™ 3000 (Invitrogen L3000001) following manufacturer’s protocol.

SARS-CoV-2 infection

SARS-CoV-2 USA-WA1/2020 (Gen Bank: MN985325.1) was obtained from BEI Resources and expanded and tittered on Vero cells. Cells were infected in DMEM +2% FBS for 48 hrs using multiplicity (MOI) of 0.5 for infection of HEK293T cells and an MOI of 2 for Calu3 cells. All sample processing and harvest with infectious virus were done in the BSL3 facility at the Ragon Institute.

Nucleic acids extraction, in vitro reverse transcription and PCR/qPCR

DNA extraction was following a published protocol22. For purification of genomic DNA, extracted total cellular DNA was run on 0.4% (w/v) agarose/1x TAE gel for 1.5 hrs with a 3V/cm voltage, with λ DNA-HindIII Digest (NEB N3012S) as size markers. Large fragment bands (>23.13 kb) were cut off, frozen in −80 °C and then crushed by a pipette tip. 3 times of volume (v/w) of high T-E buffer (10 mM Tris – 10 mM EDTA, pH 8.0) was added and then NaCl was added to 200 mM. Gel solution was heated at 70 °C for 15 mins with constant mixing and then extracted with Phenol:Chloroform:Isoamyl Alcohol (25:24:1, v/v) (Life Technologies 15593031) and Chloroform:Isoamyl alcohol 24:1 (Sigma C0549-1PT). DNA was then precipitated by sodium acetate and isopropyl alcohol. For small amount of DNA, glycogen (Life Technologies 10814010) was added as a carrier to aid precipitation.

RNA extraction was done with either TRIzol™ LS Reagent (Invitrogen 10296010) or RNeasy Plus Micro Kit (Qiagen 74034) following manufacturers’ protocols. RNA reverse transcription was done with either SuperScript™ III First-Strand Synthesis SuperMix (oligo dT + random hexamer, Invitrogen 18080400) or qScript cDNA SuperMix (QuantaBio 95048-500), following manufacturers’ protocols. In vitro reverse transcription assay for viral RNA by cell lysates was done following a published protocl22.

PCR was done using AccuPrime Taq DNA Polymerase, high fidelity (Life Technologies 12346094). qPCR was done using SYBR™ Green PCR Master Mix (Applied Biosystems 4309155) or PowerUp™ SYBR™ Green Master Mix (Applied Biosystems A25742) in a QuantStudio™ 6 system (Applied Biosystems). See Supplementary Table 1 for primer sequences used in this study. qPCR plots were generated with Prism 8 (Prism).

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Supplementary Table 1.

Primer sequences used in this study

Immuno-fluorescence staining and single-molecule RNA-FISH

Cells subject to SARS-CoV-2 infection were grown in μ-Slide 8 Well (#1.5 polymer, Ibidi 80826) and fixed with 4% paraformaldehyde/CMF-PBS at room temperature (RT) for 30 mins. Otherwise, cells were grown on 12 mm round coverslips (#1.5, Warner Instruments 64-0712) and fixed with 1.6% paraformaldehyde/CMF-PBS at room temperature (RT) for 15 mins. Cells were permeabilized with 0.5% (v/v) Triton X-100/PBS, blocked with 4% (w/v) BSA/CMF-PBS at RT for 1 hr, incubated with 1:200 diluted anti-LINE-1 ORF1p mouse monoclonal antibody (clone 4H1, Sigma MABC1152, Lot 3493991), and then with 1:400 diluted Donkey-anti-Mouse-Alexa Fluor 594 second antibody (Invitrogen 21203).

Single-molecule RNA-FISH probes (Stellaris®) were ordered from LGC Biosearch Technologies with Quasar® 670 Dye labeling. See Supplementary Table 2 for probe sequences. FISH procedure combining with immuno-fluorescence staining was following previous publications44,45.

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Supplementary Table 2.

Single-molecule RNA FISH probe sequences used in this study

Cells in μ-Slide were mounted with Ibidi Mounting Medium With DAPI (Ibidi 50011). Cells on coverslips were mounted with VECTASHIELD® HardSet™ Antifade Mounting Medium with DAPI (Vector Laboratories H-1500-10).

Microscopy and imaging analysis

3D optical sections were acquired with 0.2-μm z-steps using a DeltaVision Elite Imaging System microscope system with a 100 × oil objective (NA 1.4) and a pco.edge 5.5 camera and DeltaVision SoftWoRx software (GE Healthcare). Image deconvolution was done using SoftWoRx. All figure panel images were prepared using FIJI software (ImageJ, NIH) and Adobe Illustrator 2020 (Adobe), showing deconvolved single z-slices.

To measure the LINE-1 ORF1p immuno-staining signal intensity, we projected cell optical sections (sum, 42 slices) with the “z projection” function in FIJI. We measured the sum of intensity of the entire cell area in the z-projected image as the signal intensity, subtracted the background intensity outside of cells and then divided by the mean of the “Basal media treatment” group to have the normalized signal intensity, as previously described44,45. All images from the same experiment were using the same exposure time and transmitted exciting light. All intensity measurements were done with non-deconvolved raw images. Box plot was done in R (version 4.0.3)46.

RNA-Seq data analysis

RNA-Seq data were downloaded from GEO with the accession numbers GSE14750724, GSE15327725, GSE15675426, GSE15785227, GSE15368428, GSE14592629, GSE15499830 (summarized in Supplementary Figure 1a).

To identify human – SARS-CoV-2 chimeric reads, raw sequencing reads were aligned to concatenated human and SARS-CoV-2 genomes plus transcriptomes by STAR (version 2.7.1a)47. Human genome version hg38 with no alternative chromosomes and gene annotation version GRCh38.97 were used. SARS-CoV-2 genome version NC_045512.2 and gene annotation (http://hgdownload.soe.ucsc.edu/goldenPath/wuhCor1/bigZips/genes/) were used. The following STAR parameters31 were used to call chimeric reads unless otherwise specified (Supplementary Figure 1a): --chimOutType Junctions SeparateSAMold WithinBAM HardClip \ --chimScoreJunctionNonGTAG 0 \ --alignSJstitchMismatchNmax −1 −1 −1 −1 \ --chimSegmentMin 50 \ --chimJunctionOverhangMin 50.

To analyze human LINE-1 expression in RNA-Seq data, a published method, RepEnrich248, was used to map RNA-Seq reads to human repeat annotations, using human repeat masker (hg38). Differential expression was analyzed using EdgeR package (version 3.30.3)49,50 in R (version 4.0.3)46.

Conditioned media production and treatment

As previously described51, myeloid precursors were derived from human pluripotent stem cells. Briefly, human embryonic stem cells were cultured in StemFlex (ThermoFisher) feeder-free medium on Matrigel™-(Corning) coated tissue culture polystyrene. 24 hrs before single-cell harvesting via TrypLE Express (ThermoFisher), cells were treated with 10 μM ROCK Inhibitor (Y-27632) (Stem Cell Technologies) in Essential 8 (E8) medium (ThermoFisher). After harvesting, cells were centrifuged at 300 g for 3 mins in non-adherent U-bottom 96-well plates (Corning) at 10,000 cells per 150 μL/well of embryoid body (EB) medium consisting of 10 μM ROCK Inhibitor, 50 ng/mL BMP-4 (Peprotech), 20 ng/mL SCF (Peprotech), 50 ng/mL VEGF (Peprotech), and 100 U/mL Penn/Strep (ThermoFisher) in E8 base medium. EBs were cultured in the 96-well plates for 4 days with 150 μL/well of EB medium added at day 2. After 4 days, 16 EBs/well were plated in a 6-well tissue culture polystyrene plated coated with Matrigel™ in hematopoietic myeloid medium (HIM) consisting of 2mM GlutaMax (ThermoFisher), 55 μM beta-mercaptoethanol, 100 ng/mL M-CSF (Peprotech), and 25 ng/mL IL-3 (Peprotech) in X-VIVO 15 base medium (Lonza). HIM media was changed every 3-4 days for 2-3 weeks until floating CD14-positive myeloid precursors emerged. Myeloid conditioned media consisted of floating myeloid cells cultured in HIM media for 7 days at a concentration of 0.5 × 106 – 1 × 106 cells/mL. Cells in conditioned media were removed by centrifugation and filtration through 0.2 μM filters. Calu3 cells were cultured in the myeloid conditioned media or HIM media (basal) for two days with daily media change before harvest or fixation.

Microglia were differentiated from human induced pluripotent stem cells (hiPSCs) via embryoid bodies and primitive macrophage precursors (PMPs)51. In brief, hiPSCs (cultured feeder-free on matrigel in StemFlexTM (Gibco)) were dissociated with TrypLE Express (Gibco), and 10,000 cells were plated per well in 96-well ultra-low attachment plates (Corning) in 100 μL embryoid body medium (10 μM ROCK inhibitor, 50 ng/mL BMP-4, 20 ng/mL SCF, and 50 ng/mL VEGF-121 in StemFlex), before centrifugation at 300 × g for 3 mins at 4 °C. Embryoid bodies were cultured for 4 days, with adding 100 μL embryoid body medium after 2 days. 12 to 16 embryoid bodies were plated per well of tissue culture-treated 6-well plates and cultured in 3 mL hematopoetic medium (2 mM GlutaMax, 100 U/mL penicillin, 100 μg/mL streptomycin, 55 μM β-mercaptoethanol, 100 ng/mL M-CSF, 25 ng/mL IL-3, 100 U/mL penicillin, 100 μg/mL streptomycin in X-VIVO 15 (Lonza, BW04418Q). From this point on, 2 mL medium was exchanged every 4–7 days. PMPs were harvested from suspension during medium exchange and plated in microglia differentiation media over 7-14 days to produce microglia like cell monocultures (Neurobasal (Life Technologies 21103049) supplemented with Gem21 NeuroPlex without Vitamin A (GeminiBio, 400-161), 2mM GlutaMAX (Gibco), 100 ng/mL IL-34, and 10 ng/mL GM-CSF, 100 U/mL penicillin, 100 μg/mL streptomycin). For microglia stimulation, microglia differentiation media was exchanged with HEK293T media (DMEM + 10% heat-inactivated FBS + final 2mM L-Glutamine) and supplemented with 100 hg/ml lipopolysaccharide (LPS, Sigma Aldrich L4391-1MG) or PBS. After 24 hrs, the microglia conditioned media was collected, centrifugated (1000 rpm 10min) and the supernatant was directly applied to HEK293T cells. HEK293T cells received microglia conditioned media or basal HEK293T media on three constitutive days before fixation.

Human anti-CD19 CAR-T cells were generated by transduction of primary T cells purified from human peripheral blood mononuclear cells (PBMC) with CD19-CAR expressing retrovirus52. Anti-CD19 CAR-T cells were co-cultured with CD19-expressing beta-like cells52 or WIBR3 cells with a luciferase-2A-CD19 expressing cassette integrated at the AAVS1 locus in RPMI1640 medium with 10% human serum AB. Cells in the conditioned medium were removed by filtration through 0.45 μM filters. RPMI1640 medium with 10% human serum AB was used as basal media control. Calu3 cells were cultured in the CAR-T conditioned media with indicated dilutions or in the basal media for two days before harvest.

Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Author contributions

Project design by R.J. and R.A.Y, execution of experiments and data analysis by L.Z., A.R, R.J and R.A.Y; E.W., A.K., and H.M. generated cells and reagents; Manuscript preparation by L.Z. and R.J. with input from all authors.

Competing interests

R.J. is an advisor/co-founder of Fate Therapeutics, Fulcrum Therapeutics, Omega Therapeutics, and Dewpoint Therapeutics. R.A.Y. is a founder and shareholder of Syros Pharmaceuticals, Camp4 Therapeutics, Omega Therapeutics, and Dewpoint Therapeutics. All other authors declare no competing interests.

Acknowledgements

We thank members in the laboratories of Rudolf Jaenisch and Richard Young and other colleagues from Whitehead Institute and MIT for helpful discussions and resources. We thank Wendy Salmon from the Whitehead W.M. Keck Microscopy Facility and M. Inmaculada Barrasa from the Whitehead Bioinformatics and Research Computing for technical advice. This work was supported by grants from the NIH to RJ (1U19AI131135-01, 5R01MH104610-21) and by a generous gift from Dewpoint Therapeutics and from Jim Stone. ASK would like to acknowledge funding from the NIH (Grant: T32 EB016652). Finally, we thank Nathans Island for inspiration.

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LETTER

No evidence of SARS-CoV-2 reverse transcription and integration as the origin of chimeric transcripts in patient tissues

View ORCID ProfileRhys Parry,  View ORCID ProfileRobert J. Gifford, Spyros Lytras,  View ORCID ProfileStuart C. Ray, and  View ORCID ProfileLachlan J. M. Coin

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PNAS August 17, 2021 118 (33) e2109066118; https://doi.org/10.1073/pnas.2109066118

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- Relationship between Letter and Reply - August 03, 2021

- Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues - May 06, 2021

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There is interest in understanding the mechanisms that underlie reports that patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain PCR positive many weeks after initial infection. The recent paper by Zhang et al. (1) suggests a potential explanation of this phenomenon by claiming that SARS-CoV-2 RNA can integrate into the genome of infected human cells. The authors also reanalyze RNA sequencing (RNA-seq) data and report that SARS-CoV-2−host chimeric reads are present in cells and patient tissues. Given the potential implications of this research on the long-term impacts of COVID-19, we feel that it’s necessary to scrutinize the evidence presented.

To determine whether SARS-CoV-2 RNA might be retrotranscribed and integrated into the genome, the authors conducted a proof-of-principle experiment where human lung cells (Calu3) and kidney cells overexpressing class I transposable elements and wild type (HEK293T-L1/HEK293T) were infected with SARS-CoV-2 and subjected to high-throughput DNA sequencing (1).

The very low frequency of identified chimeric events (Table 1) suggests that SARS-CoV-2 integration into the host genome is unlikely. Given that the HEK293T-L1 model increases detection of “rare integration events” and L1 can retrotranspose any polyadenylated cellular RNA (2) and “insertions” are found preferentially in protein-coding exons, a bias unknown to L1 endonuclease insertions (3), these findings are likely spurious. Additionally, 2 of the identified 61 chimeric nanopore genomic DNA (gDNA) reads contain human DNA from separate chromosomes (chr1,chr22 and chr18,chrX, respectively), suggesting a portion of chimeric gDNA nanopore reads have arisen due to infrequent technical artifacts, such as base-calling software not recognizing an open-pore state between distinct molecules.

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Table 1.

Summary of gDNA sequencing and chimeric reads identified

Further to this, the authors reanalyzed published sequencing data and identified SARS-CoV-2 and human host chimeric reads in vitro and in patient RNA-seq (1). They show that the fraction of human–viral chimeric reads derived from negative-sense SARS-CoV-2 RNAs is higher in patients than that observed in vitro. These data are presented as evidence of SARS-CoV-2 integration and transcription. We question the presented data as evidence for this phenomenon for several key reasons. Firstly, chimeric virus−host reads are often reported in RNA-seq (4), including SARS-CoV-2 (5). This is partly due to complementary DNA fusions introduced during the reverse transcription step of library preparation (6). Secondly, larger pools of negative-sense SARS-CoV-2 chimeric reads may be due to differences in RNA extraction, library preparation, and sequencing platform. Given that negative-sense RNA is formed during the replication of SARS-CoV-2 and a template for messenger RNA production, significant variation of negative-sense reads is expected in patient RNA samples. Finally, there is no evidence of coronaviruses ever having integrated into the germline of host species, as might be expected if retrotranscription and integration occurs in nature, as systematic screening of >750 animal species failed to identify any coronavirus-derived endogenous viral elements (7).

Given the inappropriate interpretation of high-throughput sequencing methods and improper experimental design by the authors (1), we ask for restraint about the conclusions presented by the study. It remains unlikely that retrotranscription and integration of the SARS-CoV-2 genome in patients happens at any notable frequency, or even at all.

Footnotes

- ↵1To whom correspondence may be addressed. Email: r.parry@uq.edu.au or lachlan.coin@unimelb.edu.au.

- Author contributions: R.P., R.J.G., S.L., S.C.R., and L.J.M.C. analyzed data and wrote the paper.

- The authors declare no competing interest.

- Copyright © 2021 the Author(s). Published by PNAS.

This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

References

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Response to Parry et al.: Strong evidence for genomic integration of SARS-CoV-2 sequences and expression in patient tissues

Liguo Zhang, Alexsia Richards,  View ORCID ProfileM. Inmaculada Barrasa,  View ORCID ProfileStephen H. Hughes,  View ORCID ProfileRichard A. Young, and Rudolf Jaenisch

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PNAS August 17, 2021 118 (33) e2109497118; https://doi.org/10.1073/pnas.2109497118

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Our paper (1) draws two conclusions:

- 1) SARS-CoV-2 sequences can integrate into the genome of infected cells that either overexpress (tables 1 and 2 of ref. 1) or do not overexpress (figure 2F of ref. 1) LINE1 by a LINE1-mediated retroposition mechanism.

- 2) We have identified large fractions of chimeric RNAs derived from negative-strand viral RNA in patients. Chimeric sequences containing negative-strand viral RNA are unlikely caused by artifacts associated with sequencing technology and likely derive from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences integrated into genomic DNA.

We summarize our responses to Parry et al. (2).

- 1) Parry et al. state that “SARS-CoV-2 integration into the host genome is unlikely.” Our response is that the “percent of library” calculation is not an estimate of integration frequency, which requires consideration of whole-genome sequencing (WGS) coverage. We identified integration events and observed two to five integrations per 10,000 cells at the current sequencing depth (Table 1). This is similar to the estimated integration frequency of lymphocytic choriomeningitis virus after acute infection (3). “Low frequency” of integration events cannot be interpreted as “unlikely.”

- 2) Parry et al. state that, because “‘insertions’ are found preferentially in protein-coding exons, a bias unknown to L1 endonuclease insertions . . ., these findings are likely spurious.” Our response is that we are not measuring L1 integrations but L1-mediated retroposition of SARS-CoV-2 RNA. Our data suggest that L1-mediated retroposition of RNA may have a different integration preference than L1.

- 3) Parry et al. state that “2 of the identified 61 chimeric nanopore genomic DNA (gDNA) reads contains human DNA from separate chromosomes.” Our response is that it is well known that nanopore sequencing occasionally ligates fragments from different chromosomes. Our demonstration of LINE1-mediated retroposition is based on sequence features of the integrated DNA and is not affected by these rare artifacts.

- 4) Parry et al. state that “larger pools of negative-sense SARS-CoV-2 chimeric reads may be due to differences in RNA extraction, ….” Our response is that there are no “larger pools of negative-sense chimeric reads.” The fraction of negative-strand RNAs produced during virus replication is 1,000- to 10,000-fold lower than that of positive-strand RNAs (figure 3 C and D in ref. 1). The low abundance of negative-strand RNA makes artifactual template fusion unlikely. The fraction of negative-strand viral RNAs detected in some patient tissues, which show no evidence of virus replication, are orders of magnitude higher than in cells with replicating virus (figure 3 E−G in ref. 1).

- 5) Parry et al. state that “there is no evidence of coronaviruses ever having integrated into the germline of host species.” Our response is that the lack of prior evidence is not an argument against new evidence. Whether coronavirus sequences are found in the germline of different species is irrelevant, as our experiments have focused on SARS-CoV2 integration into the genome of somatic cells and not into the germline.

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Table 1.

Summary of gDNA sequencing

Footnotes

- ↵1To whom correspondence may be addressed. Email: jaenisch@wi.mit.edu.

- Author contributions: L.Z., A.R., M.I.B., S.H.H., R.A.Y., and R.J. analyzed data; and L.Z. and R.J. wrote the paper.

- Competing interest statement: R.J. is an advisor/co-founder of Fate Therapeutics, Fulcrum Therapeutics, Omega Therapeutics, and Dewpoint Therapeutics. R.A.Y. is a founder and shareholder of Syros Pharmaceuticals, Camp4 Therapeutics, Omega Therapeutics, and Dewpoint Therapeutics.

- Copyright © 2021 the Author(s). Published by PNAS.

This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

References

1. ↵

- L. Zhang et al

., Reverse-transcribed SARS-CoV-2 RNA can integrate into the genome of cultured human cells and can be expressed in patient-derived tissues.  118, e2105968118 (2021).

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, No evidence of SARS-CoV-2 reverse transcription and integration as the origin of chimeric transcripts in patient tissues.  118, doi:10.1073/pnas.2109066118 (2021).

FREE Full TextGoogle Scholar

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