Overview to better understand how hosts respond to viral infection

When performing viral research, it’s just as critical to study the host as it is the virus. Given that viruses require a host for replication, it’s difficult to ascertain any actionable information without investigating host mechanisms that stimulate or inhibit infection. Particularly, it is vital to identify necessary host factors required for infection and characterize the host immune response.[1]

The host genome and transcriptome––including cell- and tissue-specific transcriptomes––are among the most important areas of research. Collectively, they can provide a window into host susceptibility, transmission, disease severity, patient outcomes, and responses to vaccines and antiviral drugs. By studying both the similarities and differences across infected host cells/individuals and comparing them to less affected populations, researchers can uncover vital information that supports downstream intervention strategies and next-generation drug discovery.

To truly understand the full relationship between host and pathogen, researchers need to collect host genomic and transcriptomic data. In this blog, we discuss the impact of host genetics, while supplying some compelling research vignettes that highlight the importance of the hosts.

Host genomics: how the genotypic background alters infection

The presence or absence of specific alleles in a host can strengthen or weaken a virus’s ability to transmit, replicate, and spread. Similarly, specific patients may be more or less likely to respond positively to intervention strategies and therapeutics, depending on their genotype.

Since genetic differences in key genes can offer significant insight into viral infection, researchers commonly perform genomic sequencing of host populations and use their response to viral challenges to perform genome-wide association (GWA) studies.[2] These studies establish correlations between specific alleles and viral infection, susceptibility, and/or patient outcomes to uncover possible host factors critical to infection or resistance.

For example, host studies have sought to understand why portions of human populations appear less susceptible to human noroviruses, despite their prevalence. Norovirus researchers have shown that the presence or absence of histo-blood group antigens (HBGAs) on target tissues massively affects strain-specific susceptibility, since HBGAs are target receptors for these viruses.[3] Thus, alleles responsible for differences in HBGA expression show associations with symptomatic infection. Specifically, the FUT2 gene, which dictates whether HBGAs are expressed in biofluids (aka, secretor status), is particularly important for noroviruses. Nonsense mutations in FUT2 provide individuals with protection from norovirus infection.[4]

As another example, researchers have sought to understand why some individuals appear resistant to COVID-19 infections.[5] One genome-wide CRISPR-screen showed that genetic differences associated with increases in cholesterol biosynthesis and ACE2 sequestration inside cells (i.e., not cell surface exposed) reduced viral susceptibility of human cells. [6]

Similarly, a COVID-19 discordant couple study (where one partner gets sick but the other does not) found that specific genes associated with immune modulation impacted COVID-19 susceptibility.[7] Alleles that led to the down regulation of natural killer (NK) cell cytotoxicity correlated with symptomatic infection. It’s clear that immunological research stands to make significant ground using genome sequencing efforts that aim to deconvolute differences in immune response. These studies offer opportunity to identify high-risk individuals and complement antibody studies performed for epidemiological purposes and vaccine development.

Host transcriptomics: how expression controls viral susceptibility phenotypes

Modern virology doesn’t just rely on genomic information. Researchers often go further, studying host transcriptomes to understand how gene expression impacts viral infection. The presence or absence of an allele is important, but whether the gene is being transcribed and the extent of its expression provide more insight into the host’s response.

The transcriptome comprises all relevant gene transcripts, their relative abundance, and interactions. Viral researchers want to study the host transcriptome before, during, and after viral infection to uncover changes in gene expression. This approach can uncover correlations between specific transcripts and their influence on host susceptibility, patient outcomes, intervention strategies, and more.

Researchers studying host transcriptomes rely heavily on RNA-based techniques, with a particular emphasis on reverse transcription quantitative PCR (RT-qPCR) and RNA sequencing (RNA-seq) for specific or total transcript analysis, respectively.

For RNA-seq, researchers take complex sequencing datasets and resolve them using bioinformatics to establish potential connections between viral infection, immune response, and/or intervention with specific expression changes. While this is an extremely powerful global transcriptomic method, the quality of its output is highly dependent on representative library preps, accurate and sensitive sequencing workflows, and sophisticated software.

Gene expression microarrays provide another powerful approach. In a microarray, nucleic acids complementary to key transcripts are attached to the surface of slides in fixed locations. Extracted RNA is then added to the slide and allowed to hybridize. From here, researchers can determine transcript quantity through the extent of hybridization (often through labeled RNA). While this can only investigate a sub-set of genes, microarrays enable fast and high-throughput assessments of critical transcripts.

Using these methods, researchers can study changes in host transcription to reveal vital information around viral life cycles, immune response, and potential infection biomarkers.

In one such study, researchers from UC San Diego used RNA-seq and RT-qPCR to investigate transcriptomic changes resulting from Zika virus infection.[8] Their research demonstrated that Zika infection could down regulate adaptive immune responses in human cells, while also upregulating transcripts related to host metabolic processes that support sustained viral production.

Transcriptomic data collected from patient samples continues to provide valuable insights, including new clinically relevant biomarkers. Researchers from Texas A&M, Baylor College of Medicine, and NIAID tracked patients infected with Influenza A and other respiratory viruses for three weeks, using RNA-seq and microarray analysis of blood samples.[9] This clinical study showed virus-specific differences in host RNA expression. The researchers also showed distinct stages of host response to influenza infection and compared this information to antibody production.

As another example, researchers found the use of a four-gene expression signature from blood samples could distinguish between systemic inflammation resulting from viral and non-viral etiologies (including bacterial and non-infectious diseases).[10] Importantly, this approach worked across all seven Baltimore virus classification groups, demonstrating its potential as a pan-virus host RNA biomarker approach to inflammation diagnoses.[11]

Looking ahead: deeper host characterization

There is significant value in understanding host genetics in the context of viral infection. While a strong body of research has been established, continued improvements in the sensitivity, speed, and cost-effectiveness of both genomic and transcriptomic methods will drive even deeper insights. One early glimpse: More advanced studies into SARS-CoV-2 host response, COVID-19 severity, and cross-virus comparisons are already flexing the power of these approaches.[12-14] Ultimately, this all helps basic researchers arm public health organizations, clinicians, and drug developers with the information they need to combat viral infection through the lens of the host.

If you’re interested in performing genomic or transcriptomic analysis of viral hosts, Thermo Fisher Scientific can help to streamline your work. For more information and details on relevant research tools, check out our Virology Resource page.

References

  1. Joseph A. (2021) Scientists unlock clues to determining how safe vaccinated people are from Covid-19.STAT News. Published August 16, 2021. Accessed October 15, 2021.
  2. Genome-Wide Association Studies Fact Sheet.National Human Genome Research Institute. Accessed October 15, 2021.
  3. Nordgren J et al. (2019) Genetic Susceptibility to Human Norovirus Infection: An Update. Viruses 11(3), 226.
  4. Kindberg E et al. (2007) Host Genetic Resistance to Symptomatic Norovirus (GGII.4) Infections in Denmark.J. Clinical Microbiology 45(8),2720-2.
  5. Kalaichandran A. (2021) A lucky few seem ‘resistant’ to Covid-19. Scientists want to know why.STAT News. Published August 23, 2021. Accessed October 15, 2021.
  6. Daniloski Z et al. (2020) Identification of Required Host Factors for SARS-CoV-2 Infection in Human Cells. Cell. 184(1), 92-105.
  7. Castelli EC et al. (2021) MHC Variants Associated With Symptomatic Versus Asymptomatic SARS-CoV-2 Infection in Highly Exposed Individuals. Frontiers in Immunology 12, 742881.
  8. Tiwari SK. (2017) Zika virus infection reprograms global transcription of host cells to allow sustained infection. Emerging Microbes & Infections 6, e24.
  9. Zhai Y et al. (2015) Host Transcriptional Response to Influenza and Other Acute Respiratory Viral Infections – A Prospective Cohort Study. PLoS Pathogens 11(6), e1004869.
  10. Sampson DL et al. (2017) A Four-Biomarker Blood Signature Discriminates Systemic Inflammation Due to Viral Infection Versus Other Etiologies. Scientific Reports 7, 2914.
  11. Koonin EV et al. (2021) The Baltimore Classification of Viruses 50 Years Later: How Does It Stand in the Light of Virus Evolution?Microbiology and Molecular Biology Reviews 85(3), e00053-21.
  12. Butler D et al. (2021) Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions. Nature Communications 12, 1660.
  13. Jain R et al. (2021) Host transcriptomic profiling of COVID-19 patients with mild, moderate, and severe clinical outcomes. Computational and Structural Biotechnology Journal 19,153-160.
  14. Thair SI et al. (2021) Transcriptomic similarities and differences in host response between SARS-CoV-2 and other viral infections. iScience 24,101947.

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