Uncovered the Similarities and Differences Between SARS-CoV-2 And HIV-1 Infections


Researchers from University of Chicago-USA and Northwestern University, Chicago-USA have in a new study uncovered the similarities and differences between SARS-CoV-2 And HIV-1 infections in terms of cellular and immune responses.

The key findings of the study show that:
-Both COVID-19 and HIV-1+ patients show disease-specific inflammatory immune signatures
-COVID-19 patients show more productive humoral responses than HIV-1+ patients
-SARS-CoV-2 elicits more enriched IFN-I signaling relative to HIV-I
-Divergent, impaired metabolic programs distinguish SARS-CoV-2 and HIV-1 infections
-COVID-19-specific IFN-I correlated genes were enriched in MAPK signaling, and p38 MAPK inhibition was previously reported to reduce human coronavirus HCoV-229E viral replication in human lung epithelial cells. Hence, inhibitors targeting MAPK signaling also have the potential to be used for treating COVID-19 patients.

The study findings were published on a preprint server and are currently being peer reviewed. https://www.biorxiv.org/content/10.1101/2022.01.10.475725v1

Since the COVID-19 pandemic, scRNA-seq has been extensively used to study the immune landscape of COVID-19 (Melms et al, 2021; Lee et al, 2020; Wen et al, 2020; Liao et al, 2020). While HIV-1 has been studied for almost 4 decades, the gene expression profile of HIV-1 infection at the single-cell level remains understudied.

In particular, integration of scRNA-seq data across studies remains challenging and few attempts were made to integrate scRNA-seq data from COVID-19 and HIV-1+ patients. Here, we designed a consensus integration strategy that combined the advantages of deep-learning-based label transfer, molecular-profile-correlation-based label transfer and manual-supervised annotation methods that can be readily applied to scRNA-seq datasets.

We leveraged the accuracy and portability of our method to generate a high-quality unified cellular atlas of the immune landscape of PBMCs from COVID-19 and HIV-1+ patients.

While manually supervised annotation offers domain-specific knowledge of known immune subset markers, a correlation-based method such as SingleR (Aran et al., 2019) complements it with unbiased comparisons with sorted a purified immune subset from healthy donors. H

owever, both methods rely on the most typical and commonly known markers of different immune cell types, and neither incorporates disease-specific or context-specific knowledge from past studies of similar disease or context. This limitation can be well addressed with deep-learning based classification methods such as scANVI (Xu et al., 2021).

The deep generative neural network can learn highly non-linear representations of each immune subset from the most finely-manually-annotated disease-specific scRNA-seq atlas and can leverage on the knowledge to classify new cells from the same disease in the same representation space.

Nevertheless, overfitting can be a common issue for deep learning models, and expert knowledge is still required to keep the classification results in check. Thus, our strategy effectively consolidates the advantages of all three methods to annotate scRNA-seq data by

1) overcoming the subjectivity of manual annotation,

2) leveraging existing knowledge of cell phenotypes to quickly and accurately assign labels with a trained model, and

3) validating classified labels with biologically relevant markers.

Besides integration of COVID-19 and HIV-1 PBMC data, we anticipate our integration strategy can be easily adapted for integration of scRNA-seq data from different tissues, organs, or diseases. While we highlighted the integration of manual, correlation-based, and deep-learning-based annotation methods, there is flexibility for the specific software used in each method.

The software we used in this study, namely Seurat, SingleR and scANVI, are all publicly available and highly rated across multiple benchmarking studies (Abdelaal et al., 2019; Huang et al., 2021; Krzak et al., 2019), so the current implementation can be adapted as is.

One potential limitation is that there may not be high quality reference data for training the deep learning model for certain context or disease. However, we envision it will be increasingly easy to overcome this, given multiple ongoing efforts to make large atlases of specific tissues, organs, and diseases easily accessible such as Azimuth (Hao et al., 2021) and the human protein atlas (Uhlen et al., 2017).

Using our integration strategy, we identified 27 different cell types, consisting of 5 B cell subsets, 2 DC subsets, 4 monocyte subsets, 7 CD4+ T cell subsets, 8 CD8+ T cell subsets, and 1 NK cell subset. We also conducted detailed comparison within each immune compartment between each disease against healthy control as well as between the two diseases to identify the key common and differential regulatory pathways.

We found a consistent inflammatory signature highlighted by IFN-I and cytokine-mediated signaling among innate immune cells in both diseases (Bieberich et al., 2021; Hasan et al., 2021; Liu et al., 2021).

However, we also discovered that the types and frequencies of cellular communications among immune cells can be very different between COVID-19 and HIV-1 patients. This allowed us to identify the disease-specific inflammatory and cytotoxic molecules that drive the innate immune response in either disease.

Interestingly, we found an enrichment of inhibitory interactions mediated by CTLA4 and HAVCR2 that were unique to COVID-19 patients, which could be out of necessity to curb the heightened inflammation present in severe COVID-19. Further experiments are necessary to validate these hypotheses.

Consistent with prior literature, we found a strong humoral immune response in both COVID-19 and HIV-1+ patients (Baum, 2010; Wu et al., 2021b) driven by plasmablast maturation and activation. While we could not evaluate the functionality of the antibody repertoire by single-cell RNA-seq analysis, we were able to demonstrate that the HIV-1 repertoire was much less diverse compared to the COVID-19 repertoire.

Our study is aligned with the vaccine efficacy results against both viruses. Multiple SARS-CoV-2 vaccines have shown efficacy due in part to their ability to generate broadly protective neutralizing antibodies, but this is not the case for candidate HIV-1 vaccines (Baden et al., 2021; Baum, 2010; Dangi et al., 2021a; Dangi et al., 2021b; Goel et al., 2021a; Mercado et al., 2020; Polack et al., 2020; Sanchez et al., 2021; Turner et al., 2021).

Repertoire mapping also allowed us to pinpoint high-frequency as well as overlapping combinations and could inspire antibody-based therapeutics to treat comorbid patients. Additionally, we found the COVID-19-specific IGKV1-39/IGHV2-26 combination to have significant enrichment among our patients, which could pose as a promising therapeutic candidate.

IFN-I can play a double-edged role during viral infection; while it restricts viral replication and viral antigen expression in addition to modulating the antigen-specific CD8+ T cell response (Moseman et al., 2016; Palacio et al., 2020), overactive IFN-I signaling can contribute to immune dysfunction, non-canonical inflammasome activation, and pyroptosis (Kopitar-Jerala, 2017; Teijaro et al., 2013; Wilson et al., 2013).

Previous studies comparing the immune response in COVID-19 and influenza have investigated the role of IFN-I signaling in both driving the antiviral response and disease progression (Galani et al., 2021; Lee et al., 2020; Nguyen et al., 2021). While a positive effect of IFN-I has been defined in the immune response to influenza, the role of IFN-I during severe COVID-19 remains unclear.

In acute HIV-1 infection, IFN-I signaling has been generally characterized as beneficial (Abraham et al., 2016; Lavender et al., 2016; Sandler et al., 2014; Wang et al., 2017). However, during the late stages of chronic viral infection, IFN-I signaling shifts toward a pathogenic role by contributing to systemic inflammation (Soper et al., 2017; Teijaro et al., 2013; Utay and Douek, 2016; Wilson et al., 2013). However, the precise role of IFN-I at the single-cell level in COVID-19 (which results in an acutely controlled infection) and HIV-1 (which results in a chronic infection) is still unclear.

We identified IFN-I signaling to be a key pathway induced across various immune cells. IFN-I is critical to prime innate and adaptive immune responses during both SARS-CoV-2 and HIV-1 infection, as well as limiting viral replication and promoting effector cell function (Schreiber, 2020; Sugawara et al., 2019).

As a result, IFN-I therapy has been proposed for both diseases. While IFN-I signaling was upregulated in both COVID-19 and HIV-1 patients relative to healthy controls, our analysis suggests a more robust role of IFN-I in COVID-19. We found that IFN-I signaling in COVID-19 is more intimately tied to important cellular functions such as cell signaling, motility, and cytokine secretion. In support of our findings, previous studies have found that exposure to IFN-I results in upregulation of MAPK signaling cascades (Zhao et al., 2011).

While MAPK signaling regulates important functions such as cellular proliferation and survival, further studies are needed to investigate whether IFN-I mediated MAPK signaling in COVID-19 contributes to antiviral immune response or apoptosis (Zhang and Liu, 2002). Dysregulation of actin cytoskeleton following viral infection activates RLR signaling and downstream IFN-I signaling, which could explain the origin of the IFN-I response in COVID-19 patients (Trono et al., 2021).

Previous studies have reported an antagonistic relationship between IFN-I and IL-1, the prototypical proinflammatory cytokine (Guarda et al., 2011; Mayer-Barber and Yan, 2017). Interestingly, we found that IFN-I signaling in COVID-19 patients is highly correlated with immune-activating cytokine signaling pathways such as IL-2, IL-16, and IL-17, which could provide novel insights on the coregulatory relationship of IFN-I with other effector cytokines.

In contrast, we found a much narrower scope of highly correlated genes and pathways in HIV-1+ patients, including the CD161+ CD8+ T cell signature and TLR signaling. CD161+ CD8+ T cells represent a subset of innate-like memory CD8+ T cells that feature elevated levels of cytotoxicity, cytokine production, and survival, in addition to providing antigen-specific protection against viruses such as HBV, CMV, and influenza (Fergusson et al., 2016; Konduri et al., 2020).

While CD161+ CD8+ T cells have not been well characterized in the context of HIV-1, CD161+ CD8+ T cells have demonstrated increased sensitivity to IFN-I stimulation, synergizing with TCR/CD3 activation to trigger high cytotoxicity and cytokine production (Pavlovic et al., 2020).

Thus, the IFN-I driven CD161+ CD8+ T cell response can be an important antiviral mediator during HIV-1 infection. Additionally, the correlation of TLR signaling with IFN-I signaling is expected, since TLR triggering induces downstream IFN-I responses and subsequent induction of interferon-stimulated genes (Uematsu and Akira, 2007; Wang et al., 2019).

However, the specific enrichment of TLR signaling in HIV-1+ patients could suggest a disease-specific driver of immune activation. Stimulation of TLRs can result in latency reversal (Macedo et al., 2019; Meås et al., 2020), which in turn activates IFN-I production, thereby contributing to chronic inflammation. Overall, our findings show that while IFN-I response is robust in both diseases, they are tied to drastically different biological functions in HIV-1 compared to COVID-19, with the latter featuring a much more diverse spectrum of cellular responses.

These insights are important to consider given the recent proposals to utilize IFN-I as a potential treatment for COVID-19. In agreement with our findings, recent analyses integrating genome-wide association study (GWAS) and transcriptome-wide association study (TWAS) suggested an important role of IFN responses in determining the COVID-19 severity (Pairo-Castineira et al., 2021) .

We reason that our gene expression comparison could elucidate pathways that could be targeted for the treatment of COVID-19 or HIV-1. In particular, our analyses corroborated the contribution of various molecular pathways that regulate COVID-19 pathophysiology, many of which are already considered for COVID-19 treatments. For instance, we found JAK-STAT signaling, IL-4 signaling, and IL-6 signaling to be enriched in COVID-19 patients, and interestingly, all of these pathways have been targeted for the treatment of COVID-19.

Three JAK inhibitors, namely Baricitinib, Tofacitinib, and Ruxolitinib have been used to treat COVID-19 patients by reducing excessive inflammation, among which Baricitinib and Tofacitinib are recommended for hospitalized patients who require high-flow oxygen or noninvasive ventilation according to NIH COVID-19 Treatment Guidelines (Satarker et al., 2021).

In addition, Dupilumab, an IL-4Rα inhibitor, was also reported to be useful for treating COVID-19 patients (Thangaraju et al., 2020). Furthermore, IL-6R inhibitors Sarilumab and Tocilizumab were also shown to be beneficial for COVID-19 patients and were recommended for use in hospitalized patients who require supplemental oxygen, high-flow oxygen, noninvasive ventilation, or invasive mechanical ventilation by NIH COVID-19 Treatment Guidelines.

Interestingly, we also found COVID-19 specific enrichment of MAP3K1, which activates the JNK and ERK pathway. Since JNK inhibition were reported to preclude the development of persistent SARS-CoV infections (Mizutani et al., 2005) and MEK1/2 inhibition can diminish the production of viral progeny of coronavirus (Cai et al., 2007), inhibitors targeting both JNK and ERK pathway have the potential to be used for COVID-19 treatment. Besides, our findings suggest that COVID-19-specific IFN-I correlated genes were enriched in MAPK signaling, and p38 MAPK inhibition was previously reported to reduce human coronavirus HCoV-229E viral replication in human lung epithelial cells (Kono et al., 2008).

Therefore, inhibitors targeting MAPK signaling also have the potential to be used for treating COVID-19 patients. We also found the IFN-γ/IFN-γ receptor interaction between CD8+ T cells and APCs to be enriched in HIV-1+ patients. While IFN-γ production in the acute phase of HIV-1 infection can help curtail infection, it can also contribute to persistent inflammation and tissue damage during the chronic disease (Roff et al., 2014).

We found this interaction to be specifically active between CD8+ T cells and dendritic cells and monocytes in both acute and chronic HIV-1+ patients. Thus, molecules aimed to stimulate or inhibit IFN-γ signaling in specific cell types could help address HIV-1 pathogenesis at different stages of disease. In addition, our studies independently highlighted the significance of JAK and IFN-I in SARS-CoV-2 infection which was suggested by recent human GWAS and TWAS results (Pairo-Castineira et al., 2021).

Notably, our analysis also revealed disease-specific altered metabolism profiles. We characterize a decrease in OXPHOS and ribosome biogenesis in response to both SARS-CoV-2 and HIV-1 infection. Virus-induced reduction of OXPHOS has been previously characterized in other diseases and could be a result of oxidative stress triggered by mitochondrial clustering (Khan et al., 2015). Viral hijacking of ribosomal function is also crucial to viral replication and survival in the host (Li, 2019).

Disruption of these viral interactions could be advantageous for COVID-19 and HIV-1 treatment. We also unveiled molecular metabolic pathways which could also be targeted for therapy. For example, we found enriched proteasomal genes in COVID-19 patients. It has been proposed that proteasome inhibitors may be a possible therapy for COVID-19, since proteasome inhibitor may interfere with the viral replication processes and reduce the cytokine storm associated with various inflammatory conditions (Longhitano et al., 2020). Consistent with our observation of the upregulation of Rho GTPase in COVID-19 patients; the plausibility of using Rho kinase inhibitors to treat COVID-19 has been discussed, as they can restore the activity and level of ACE2 which is inhibited by SARS-CoV-2 without increasing the risk of infection (Abedi et al., 2020b).

Although remained to be investigated in immune cells, a recent study demonstrated that small GTPase RhoA activation drives increased cellular glycolytic capacity (Wu et al., 2021a) which is typically associated with reduced mitochondrial metabolism, in agreement with the upregulation of Rho GTPase and disrupted mitochondrial function in COVID-19 patients. Moreover, Rho GTPases have been linked to additional key metabolic controls such as mTOR signaling pathways. (Mutvei et al., 2020; Senoo et al., 2019).

Finally, we found COVID-19 specific upregulation of the mTOR pathway, and thus its inhibitors may also be used for treatment, since mTOR inhibitors can adjust T cells by induction of autophagy without apoptosis, reduce viral replication, restore T-cell function, and decrease cytokine storm (Mashayekhi-Sardoo and Hosseinjani, 2021).

In conclusion, our study provides a comprehensive comparison of the immunological landscape of SARS-CoV-2 and HIV-1 infections in humans. The high resolution of single-cell RNA sequencing, diversity of patient samples, and large dataset allowed us to unveil important shared and disease-specific features that offer insight into the next generation of antiviral treatments.

Through cell type-specific analysis, we found a common enrichment of activated B cells and plasmablasts, inflammatory monocyte and effector T cell subsets, and cytokine signaling that appear to drive the antiviral response to SARS-CoV-2 and HIV-1.

We also found dendritic cells and monocytes to be highly interactive with adaptive immune cells in both diseases, but found that innate cells in COVID-19 appear to be more capable of immunosuppressive function through CTLA-4 and TIM-3-mediated interactions.

We also found that the cytokine response was more diverse in COVID-19 patients, which is highlighted by IL-2, IL-4, and IL-20 signaling, while HIV-1+ individuals primarily exhibited high levels of NF-kB signaling. Our analysis corroborated pathways in COVID-19 patients that have already shown therapeutic benefits, but further in vitro and in vivo experiments are necessary to measure the contribution of other molecular pathways (such as Rho GTPase and IL-2 signaling) that also appear to be distinctively enriched. Overall, our study provides a roadmap to help develop novel drugs to treat COVID-19 and HIV-1 infections.


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