Case Report|Articles in Press

SARS-CoV-2 Co-Infection in Immunocompromised Host Leads to Generation of Recombinant Strain

Open AccessPublished:March 14, 2023DOI:


      • Homologous recombination due to co-infection is a driving force of viral evolution
      • A specimen suggestive of co-infection was analysed with sequencing and plaque assay
      • Sequencing on primary sample is consistent with double viral population
      • Plaque assay showed a recombinant strain deriving from Delta and Omicron
      • Monitoring co-infections, particularly in immunocompromised patients, is needed


      Recombination related to co-infection is a huge driving force in determining the virus genetic variability, particularly in conditions of partial immune control leading to prolonged infection. Here we characterized a distinctive mutational pattern, highly suggestive of Delta-Omicron double infection, in a lymphoma patient.
      The specimen was characterized through a combined approach, analyzing the results of deep sequencing in primary sample, viral culture and plaque assay.
      Bioinformatic analysis on the sequences deriving from the primary sample supports the hypothesis of a double viral population within the host. Plaque assay on viral culture led to the isolation of a recombinant strain deriving from Delta and Omicron lineages, named XS, which virtually replaced its parent lineages within a single viral propagation.
      It is impossible to establish whether the recombination event happened within the host or in vitro, however it is important to monitor co-infections, especially in the exceptional intra-host environment of immunocompromised patients, as strong driving forces of viral evolution.



      Since late 2020, SARS-CoV-2 has clearly demonstrated its capacity to generate new variants, marked by the emergence of sets of mutations that impact virus characteristics, including transmissibility and antigenicity.
      SARS-CoV-2 evolution is an intricate process related to different mechanisms on the molecular, organism and population scale. The development of point mutations has played a big role in the emergence of new variants [1]; on the other hand, recombination between closely related genotypes occurs readily due to the high sequence identity and may result in the emergence of new strains [2]. Coronaviruses have an intrinsically high intratypic recombination rate (approximately 25%) across the genome. To allow for homologous recombination, co-infection of genetically different viruses must occur in the same host cell. The crossover sites may occur anywhere, but selection pressure can lead them to cluster in certain hotspots [3,4].
      Favorable conditions for co-infection – and subsequent recombination – spike in periods of coexistence of two major lineages. The most recent one in our geographic area happened between October 11th2021 and March 27th 2022, when Omicron succeeded Delta as the predominant lineage but the two variants co-circulated for a time. Co-infections have been reported multiple times [5-7], more recently involving Delta and Omicron [8, 9]. Delta-Omicron recombinants have also been reported [10-13].
      Recombinant viruses were initially identified only through bioinformatic tools, but they have now been isolated in culture as well, which allows for the investigation of their epidemic potential. Most often this has been done on patients who were presumably infected with a recombinant strain to begin with [10, 12, 13]. However, Burel et al were able to monitor a coinfection between B.1.160 and Alpha for 14 months, until its evolution in a recombinant strain, and culture it [14].
      The origin of variants is still a matter of speculation. Several hypotheses take zoonotic origin, selective pressure during treatment with antiviral drugs, monoclonal antibodies or convalescent plasma into consideration and a few studies point to the significance of the intra-host environment of immunocompromised patients to explain the evolution of immune escape variants [15, 16]. Immunocompromised individuals are more likely to be long carriers, which increases the likelihood of subsequent coinfection and recombination events probability.
      As homologous recombination related to co-infection and conditions of partial immune control are strong driving forces of viral evolution, it is very important to monitor such instances. Here we describe the composite approach we used to accurately characterize a peculiar SARS-CoV-2 sequence, suggestive of a double viral population, combining bioinformatic tools and plaque assay on viral culture.

      THE CASE

      A male patient, age 47, diagnosed with stage IVa nodular sclerosing non-Hodgkin lymphoma and diabetes, was admitted to hospital on January 14th 2022 due to severe respiratory distress. Point-of-care testing for SARS-CoV-2 (POCT) was positive, later confirmed by our laboratory on January 21st 2022. Patient death was recorded 17 days following admission (January 31st 2022).
      Sequencing was performed on the nasopharyngeal swab in the context of routine surveillance and monitoring for SARS-CoV-2 variants. Sequence analysis showed an unusually low number of mutations (N=17) compared to the circulating lineages on our territory at the time, Delta (N≈45) and Omicron (N>60). Additionally, several mutations were detected in a lower fraction of the viral population (variant fraction, 70-90%). All analysis softwares used for lineage characterization yielded inconclusive results.
      As this mutational pattern was highly suggestive of a double viral population, the primary sample was re-tested to exclude sequencing errors or contaminations. At the same time, viral culture on the specimen was paired with plaque assay to attempt to isolate and characterize the two populations.


      Sequencing. Whole genome sequencing (WGS) was performed on the original sample using an amplicon-based approach. We implemented the CleanPlex SARS-CoV-2 Panel (Paragon Genomics, Inc., Hayward, United States) for target enrichment and library preparation, which involves multiplex PCR reactions. The sequencing step was conducted on a MiSeq platform (Illumina, Inc., San Diego, United States).
      Bioinformatic tools. Data analysis for consensus sequence generation and mutation calling was performed, according to the supplier's recommendations, with Sophia-DDM-v4 (SOPHiA Genetics, Lausanne, Switzerland). The software operates a cut-off which excludes from reporting all mutations detected below 70%. Consensus sequences were submitted to Pangolin and NextClade for lineage assignment. Additionally, the raw data from the primary sample was aligned and analysed using Lasergene SeqMan Ultra software (DNASTAR Inc, Madison, WI, USA) in order to detect mutations below 70%. Each mutation identified was analyzed compared to the database of all samples sequenced in our lab to date, comprising of 2668 Delta sequences, 1043 Omicron and 1500 Alpha at the time of analysis. Mutations were considered markers of a specific lineage if significantly present within it (>90% samples) and absent in all others (<10%).
      Plaque assay. Viral isolates were propagated from the residual specimen on Vero E6 cell cultures (American Type Culture Collection [ATCC] CRL-1586) as recommended [17]. 500 µL of viral transport media were used to infect a cell monolayer at confluency, allowing for a one-hour adsorption and a 72-hour incubation. Viral replication was then assessed by RT-PCR. Serial dilutions of viral isolate were cultured using 0.5% agarose-added medium, to obtain visible, immobilized focuses of infection (plaque assay). Each focus was then separately eluted, cultured and sequenced, performing data analysis as previously described.


      Double analysis on the primary sample, collected on January 21st 2022, highlighted the presence of respectively 17 and 21 mutations compared to the reference. Most mutations are traceable either to Delta (italics) or Omicron (bold) lineages (Table 1), and several were detected in an unusually low fraction of the viral population (70-90%). The low number of mutations cannot be attributed to data loss, as genome coverage was 99,8% and 99,9% respectively. The most likely explanation is a higher number of mutations with a variant fraction below 70%, which would be hidden by the software cut-off. Marker mutations of multiple lineages, low variant fractions and fluctuating mutational patterns are all hallmarks of co-infections [18].
      Table 1Sequence profiles from the analysis of separate aliquots of the same primary sample and of the viral isolates. Only mutations above 70% are reported. Most mutations are referable either to Delta (italics) or Omicron (bold). The mutational pattern in the primary sample is consistent with the presence of two separate viral lineages within the specimen. Conversely, in the viral isolates the ORF1ab portion is Delta-like (italics), the rest of the genome is Omicron-like (bold). This mutational pattern is consistent with a single viral population, deriving from the recombination of two separate lineages.
      Sequence 1Sequence 2Plaque assay
      Geneproteindepthvar fraction %proteindepthvar fraction (%)geneproteindepthvar fraction (%)geneproteindepthvar fraction (%)geneproteindepthvar fraction (%)
      Phe924=210199.7Phe924=177799.3Phe924=187199.5His69_Val70del300199.9E geneThr9Ile1556100
      Pro2046Leu101771.5Gly934Val185699.5Thr95Ile393199.9M geneAsp3Gly201599.9
      Thr3646Ala399772.2Pro2287Ser422199.6Ser371Pro134100N genePro13Leu570699.9
      This hypothesis was confirmed through analysis with a second alignment software, in order to categorize all mutations below the initial cutoff. As expected, we found across the whole viral genome a very high number of mutations previously undetected and well below 70%, pertaining to both lineages. In two instances, we were able to identify the simultaneous presence of two marker mutations, respectively for Delta and Omicron, at the same genomic position (Table 2 and 3). Once analysed below 70%, the two runs yielded very similar results. In no case, however, we found patient-specific mutations.
      Table 2Sequence profiles from the analysis of aliquot 1 from primary sample. Mutations below 70% are reported. Most mutations are referable either to Delta (italics) or Omicron (bold). The mutational pattern in the primary sample is consistent with the presence of two separate viral lineages within the specimen.
      Sequence 1
      geneproteindepthvar fraction %geneproteindepthvar fraction %geneproteindepthvar fraction %
      Asn1076=36598Glu156_Arg158delinsGly33498E geneThr9Ile60602
      Ala1707=66739Ser371Pro67109M geneAsp3Gly622196
      Ile3758Val431940Pro681His*531079N genePro13Leu457798
      Table 3Sequence profiles from the analysis of aliquot 2 from primary sample. Mutations below 70% are reported. Most mutations are referable either to Delta (italics) or Omicron (bold). The mutational pattern in the primary sample is consistent with the presence of two separate viral lineages within the specimen.
      Sequence 2
      geneproteindepthvar fraction %geneproteindepthvar fraction %geneproteindepthvar fraction %
      Asn1076=30725Gly142_Tyr145delinsAsp1181100E geneThr9Ile78853
      Ala1707=72922Arg214_Asp215insGluProGlu54067M geneAsp3Gly161962
      Ile3758Val392381Asn679Lys260445N genePro13Leu897346
      Conversely, sequences of the initial viral propagation and of 8 separate plaques of infection all yielded next-to-identical results, summarized with a single sequence illustrated in Table 1 (EPI_ISL_12870564) and Figure 1. Variant fractions for all detected mutations are nearing 100%, a strong indicator of a single viral population. Furthermore, the ORF1ab portion is generally consistent with a Delta lineage, and specifically bearing the marker mutation for AY.4 (Ala2529Val) [19]; the rest of the genome is comparable to BA.1.
      Figure 1
      Figure 1Schematic figure representing the recombinant structure with respect to the different lineages.
      These results are compatible with a recombinant strain deriving from Delta and Omicron lineages. Sequence analysis with NextClade offered further confirmation, illustrating a clear breakpoint between ORF1ab and Spike (approximate breakpoint site: 20418-21618).
      The sequence was initially classified as XF, a combination of AY.4 and BA.1 which caused a small cluster in the UK in February 2022 [20, 21], but it has now been re-assigned as XS. The first XS sequence has been deposited on GISAID on February 2nd 2022, coming from North America, as all sequences currently considered XS on GISAID (n=61). This number may be underestimated, as sequences coming from recombinant strains are often difficult to assign and require much longer investigation.


      The ability of SARS-CoV-2 to generate new variants is an intricate process determined by the interplay among different mechanisms on the molecular, organism and population scale. Although the development of point mutations has played a big role, recombination is a huge driving force in determining the virus genetic variability. To allow for homologous recombination, co-infection of genetically different viruses must occur in the same host cell [22].
      Here we describe the characterization in an immunocompromised patient of a peculiar SARS-CoV-2 sequence, suggestive of co-infection. A more accurate bioinformatic analysis on the sequences deriving from the primary sample supports the hypothesis of a double viral population within the host. On the other hand, the sequencing of separate focuses of infection in vitro highlighted identical mosaic structures. The result is a recombinant SARS-CoV-2 strain derived from the combination of AY.4 (Delta) and BA.1 (Omicron), currently categorized as XS, derived from the co-existence of the two lineages.
      It would be very interesting to establish whether the recombination event happened within the host or in vitro. This could be done in two ways: first, through identification of sequencing reads containing markers for both lineages, and second, through generation of PCR products overlapping the putative recombination site. Neither of these methods are feasible in our context: as the last Delta marker was identified at position 20418 and the first Omicron marker at 21618, there are no reads long enough to contain both. As for the detection of recombinant PCR products, it is obvious from Table 2 and 3 that there is a very high presence of parent lineages in the primary sample, as indicated from the balanced percentage of markers of both lineages at the same genomic position; in this context, a negative result would be no indication of a later recombination event, as it could very well stem from a low percentage of recombinant virus in an interfering environment.
      Both Delta-Omicron co-infections and recombinants have now been reported and/or isolated multiple times now [8-13, 23]. Recombinant strains are examined accurately for their epidemic potential and ability to escape neutralization, as they have shown resistance to monoclonal antibodies such as Sotrovimab [12], while the parent lineages are not. However, it is very difficult to monitor the exact moment of the strain generation. At present, and to our knowledge, only Burel and colleagues were able to monitor a coinfection until its evolution in a recombinant strain over the course of 14 months [14], and culture it.
      Our report aims to expand the body of work on the subject. Given the very short time span between first sequencing and patient death, there is a lack of sequential sampling providing more detailed information on viral evolution, which is the main weakness of the study. On the other hand, this also raises the question of a potential rapid development of recombinants under the right environmental conditions.
      The generation of mutated strains in immunocompromised hosts is very well characterized as linked to their higher likelihood to be long carriers, which in turn increases the chance of subsequent co-infection and mutation events [16, 24-26]. This is especially related to variants created through accumulation of point mutations, while it only takes one mutational step to generate a single breakpoint recombinant. It is worth mentioning that contexts of partial immune control favor evolutionary jumps not only through very long infections that cannot be overcome, but also acting as selective pressure [16, 24,25].
      Furthermore, the region between ORF1ab and the Spike gene is a very frequent breakpoint site, not only in Delta-Omicron recombinants, (usually with ORF1ab Delta region and an Omicron region encompassing spike's RBD and C-terminal regions, [10,11-13,23]), but dating as far back as Alpha recombinants [5]. This has been linked to the phenomenon of template switching by viral polymerase during normal transcription, where the polymerase pauses at a transcription-regulatory sequence after transcribing the last open reading frame of one subgenomic RNA and switches to a similar regulatory sequence omitting a looped-out region of the template RNA, which contains at least ORF1ab in the case of SARS-CoV-2 [5]. In a context of co-infection, the availability of alternative template RNA molecules provides an environment that is highly conducive to homologous recombination.
      This study expands on SARS-CoV-2 recombinants and especially on the advantages of pairing sequencing and bioinformatic analysis with culture as to monitor and characterize co-infections and any newly generated strain. Despite our impossibility to pinpoint the time of recombination, it is worth noting the speed with which XS emerged and substituted its parent lineages in vitro. Considering the combination of favorable conditions for a recombinant strain to be generated in relatively short times, this study further stresses the necessity of monitoring immunocompromised patients carefully, not only, but especially in contexts of co-circulation between different lineages.
      Conflict of Interest. All authors declare no conflict of interest.
      Ethical statement: Informed consent was obtained from the participant to have the results of this work published. Information on clinical history, treatment, and SARS-CoV-2 qPCR test results were obtained from medical records.
      Funding: This research was supported by EU funding within the NextGenerationEU-MUR PNRR Extended Partnership initiative on Emerging Infecxtious Diseases (Project n°. PE00000007, INF-ACT)
      Declaration of interests
      ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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