COVID-19: Locked in a pro-inflammatory state

Macrophages absorbing cells infected with viable SARS-CoV-2 particles fail to transition into an anti-inflammatory state, potentially contributing to a damaging immune reaction linked to severe forms of COVID-19.
  1. Chiu Wang Chau
  2. Ryohichi Sugimura  Is a corresponding author
  1. School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong

In the last two and a half years, scientists all over the world have worked relentlessly to develop treatments and vaccines against SARS-CoV-2, the virus causing COVID-19. While considerable progress has been made identifying key properties of the virus, several fundamental questions remain. For example, it is still unclear why some people develop long COVID-19, or why others are asymptomatic.

Previous research has shown that some patients with COVID-19 can experience a cytokine storm, which is characterized by a high concentration of pro-inflammatory proteins called cytokines (Wong, 2021; Ragab et al., 2020). Cytokine storms can be an indicator of a poor disease prognosis, and research indicates that they contribute to long-term, and sometimes life-threatening, conditions in patients with long COVID-19 (Rai et al., 2021). Now, in eLife, Larissa Cunha and colleagues at the Universidade de São Paulo – including Ana Salina, Douglas dos-Santos, Tamara Rodrigues, and Marlon Fortes-Rocha as joint first authors – report new insights into how COVID-19 may cause cytokine storms (Salina et al., 2022).

Immune cells called macrophages are the major cell type responsible for cytokine storms in COVID-19 (Merad and Martin, 2020). Typically, they migrate to infected or damaged sites in the body, and upon contact with bacteria, viruses, or chemicals emitted by dying cells, produce proinflammatory cytokines (Figure 1). These, in turn, strengthen the response of other immune cells. Once the pathogens have been eliminated, macrophages stop producing proinflammatory cytokines and instead start releasing anti-inflammatory signals, which promote healing.

Phenotype change of macrophages in response to apoptotic cells.

An epithelial cell (shown in red) attacked by SARS-CoV-2 (white) activates immune cells, known as macrophages (yellow), via the cytokine interferon gamma (blue receptor). The macrophages then differentiate into a proinflammatory state M1 (lilac) and secrete proinflammatory cytokines to activate other immune responses. M1 macrophages also help to clear cell debris and virus particles by engulfing the infected cells, a process known as efferocytosis. Normally, absorbing apoptotic (dying) cells infected with a virus causes M1 macrophages to change into M2 macrophages (green), which secrete anti-inflammatory cytokines. These in turn, stimulate fibroblasts (brown) to help regenerate damaged tissues. However, macrophages that have engulfed viable SARS-CoV-2 particles do not change into the anti-inflammatory phenotype. They also are less able to absorb pathogens and cell debris, which leads to prolonged inflammation.

Image credit: The figure was created with biorender.com.

Previous research has shown that during this transition, macrophages change their phenotype from a proinflammatory state M1 to an anti-inflammatory one, M2 (Kohno et al., 2021). It was, however, unclear how they achieve this. To find out if the same transition happens after infection with COVID-19, Salina et al. used apoptotic lung and kidney cells (that is, cells undergoing regulated cell death) containing either viable SARS-CoV-2 particles, inactivated viral particles, or sterile culture medium. They then investigated if and how engulfing apoptotic cells, a process known as efferocytosis, affects the phenotypic change of the macrophages.

The results revealed that SARS-CoV-2 prevented M1 macrophages from changing into M2 macrophages, thereby increasing the inflammatory potential of these immune cells. In the experiments, only cells infected with viable SARS-CoV-2 blocked the M1 macrophages from changing into M2 macrophages and increased the amount of proinflammatory cytokines produced, such as IL-6. Experiments with another virus species did not achieve the same outcome, suggesting that the overproduction of IL-6 may be specific to SARS-CoV-2.

Salina et al. further tested the effect of antiviral drugs targeting the transcription process of viral RNA and found that viral RNAs appear to play a significant role in preventing macrophages changing into the anti-inflammatory state. Treating macrophages with the antiviral drug Remdesivir after they had engulfed cells with viable SARS-CoV-2 reduced the production of IL-6.

These observations indicate that viral RNAs – once taken up by macrophages – arrest the immune cells to remain in the M1 phenotype, which may contribute to the cytokine storm seen in patients with COVID-19. Moreover, absorbing cells containing viable SARS-CoV-2 reduced the number of proteins responsible for recognizing apoptotic cells. This led to a build-up of cell debris and apoptotic cells.

To find out how defective efferocytosis affects the pathogenesis of COVID-19, Salina et al. stained lung tissue samples from COVID-19 patients with immunofluorescent dyes and assessed the expression of efferocytosis receptor proteins. This revealed that lung samples had a lower level of gene expression linked to efferocytosis, which lead to a reduced clearance of cell debris. It also showed that the production of cytokines was dysfunctional, suggesting that SARS-CoV-2 over-activates macrophages in the lungs. This in turn, led to severe inflammation and impaired tissue regeneration. Furthermore, the residual cell debris induced signaling molecules that activated a type of immune cells, called monocytes, to become M1 macrophages. Combined, these changes could increase inflammation even further and may prolong a dysfunctional immune response long after recovery, potentially leading to long COVID-19 syndromes.

While many questions around COVID-19 and its long-term effects warrant further research, the study of Salina et al. provides valuable insights into the complex mechanisms of cytokine storms and may open new avenues for developing treatment plans for patients with severe COVID-19 (Misra et al., 2021; Gracia-Ramos et al., 2021; Ma et al., 2022; Batlle et al., 2022; Yeung et al., 2021).

References

    1. Wong RSY
    (2021)
    Inflammation in COVID-19: from pathogenesis to treatment
    International Journal of Clinical and Experimental Pathology 14:831–844.

Article and author information

Author details

  1. Chiu Wang Chau

    Chiu Wang Chau is in the School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong

    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7778-3491
  2. Ryohichi Sugimura

    Ryohichi Sugimura is in the School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong

    For correspondence
    rios@hku.hk
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5701-3628

Publication history

  1. Version of Record published: July 7, 2022 (version 1)

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© 2022, Wang Chau and Sugimura

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Chiu Wang Chau
  2. Ryohichi Sugimura
(2022)
COVID-19: Locked in a pro-inflammatory state
eLife 11:e80699.
https://doi.org/10.7554/eLife.80699

Further reading

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    2. Immunology and Inflammation
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    Background:

    The combined impact of immunity and SARS-CoV-2 variants on viral kinetics during infections has been unclear.

    Methods:

    We characterized 1,280 infections from the National Basketball Association occupational health cohort identified between June 2020 and January 2022 using serial RT-qPCR testing. Logistic regression and semi-mechanistic viral RNA kinetics models were used to quantify the effect of age, variant, symptom status, infection history, vaccination status and antibody titer to the founder SARS-CoV-2 strain on the duration of potential infectiousness and overall viral kinetics. The frequency of viral rebounds was quantified under multiple cycle threshold (Ct) value-based definitions.

    Results:

    Among individuals detected partway through their infection, 51.0% (95% credible interval [CrI]: 48.3–53.6%) remained potentially infectious (Ct <30) 5 days post detection, with small differences across variants and vaccination status. Only seven viral rebounds (0.7%; N=999) were observed, with rebound defined as 3+days with Ct <30 following an initial clearance of 3+days with Ct ≥30. High antibody titers against the founder SARS-CoV-2 strain predicted lower peak viral loads and shorter durations of infection. Among Omicron BA.1 infections, boosted individuals had lower pre-booster antibody titers and longer clearance times than non-boosted individuals.

    Conclusions:

    SARS-CoV-2 viral kinetics are partly determined by immunity and variant but dominated by individual-level variation. Since booster vaccination protects against infection, longer clearance times for BA.1-infected, boosted individuals may reflect a less effective immune response, more common in older individuals, that increases infection risk and reduces viral RNA clearance rate. The shifting landscape of viral kinetics underscores the need for continued monitoring to optimize isolation policies and to contextualize the health impacts of therapeutics and vaccines.

    Funding:

    Supported in part by CDC contract #200-2016-91779, a sponsored research agreement to Yale University from the National Basketball Association contract #21-003529, and the National Basketball Players Association.

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    Phage immunoprecipitation sequencing (PhIP-seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-seq for autoantigen discovery, including our previous work (Vazquez et al., 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki disease (KD), multisystem inflammatory syndrome in children (MIS-C), and finally, mild and severe forms of COVID-19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as prodynorphin (PDYN) in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in two patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID-19, including the endosomal protein EEA1. Together, scaled PhIP-seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.