key: cord-0919243-y3dgz5d2
authors: Hoang, Timothy N.; Pino, Maria; Boddapati, Arun K.; Viox, Elise G.; Starke, Carly E.; Upadhyay, Amit A.; Gumber, Sanjeev; Nekorchuk, Michael; Busman-Sahay, Kathleen; Strongin, Zachary; Harper, Justin L.; Tharp, Gregory K.; Pellegrini, Kathryn L.; Kirejczyk, Shannon; Zandi, Keivan; Tao, Sijia; Horton, Tristan R.; Beagle, Elizabeth N.; Mahar, Ernestine A.; Lee, Michelle YH.; Cohen, Joyce; Jean, Sherrie M.; Wood, Jennifer S.; Connor-Stroud, Fawn; Stammen, Rachelle L.; Delmas, Olivia M.; Wang, Shelly; Cooney, Kimberly A.; Sayegh, Michael N.; Wang, Lanfang; Filev, Peter D.; Weiskopf, Daniela; Silvestri, Guido; Waggoner, Jesse; Piantadosi, Anne; Kasturi, Sudhir P.; Al-Shakhshir, Hilmi; Ribeiro, Susan P.; Sekaly, Rafick P.; Levit, Rebecca D.; Estes, Jacob D.; Vanderford, Thomas H.; Schinazi, Raymond F.; Bosinger, Steven E.; Paiardini, Mirko
title: Baricitinib treatment resolves lower airway macrophage inflammation and neutrophil recruitment in SARS-CoV-2-infected rhesus macaques
date: 2020-11-10
journal: Cell
DOI: 10.1016/j.cell.2020.11.007
sha: 7274328450740a5839e4e9ff18d6d851fc1b519c
doc_id: 919243
cord_uid: y3dgz5d2

SARS-CoV-2 induced hypercytokinemia and inflammation are critically associated with COVID-19 disease severity. Baricitinib, a clinically approved JAK1/2 inhibitor, is currently being investigated in COVID-19 clinical trials. Here, we investigated the immunologic and virologic efficacy of baricitinib in a rhesus macaque model of SARS-CoV-2 infection. Viral shedding measured from nasal and throat swabs, bronchoalveolar lavages and tissues was not reduced with baricitinib. Type-I IFN antiviral responses and SARS-CoV-2-specific T-cell responses remained similar between the two groups. Animals treated with baricitinib showed reduced inflammation, decreased lung infiltration of inflammatory cells, reduced NETosis activity, and more limited lung pathology. Importantly, baricitinib treated animals had a rapid and remarkably potent suppression of lung macrophages production of cytokines and chemokines responsible for inflammation and neutrophil recruitment. These data support a beneficial role for, and elucidate the immunological mechanisms underlying, the use of baricitinib as a frontline treatment for inflammation induced by SARS-CoV-2 infection.

SARS-CoV-2 + Baricitinib n=4 

The rapid emergence and dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and subsequent COVID-19 pandemic has placed an excessive burden on public and private healthcare systems with over 1,000,000 deaths worldwide. Thus, therapeutic approaches aimed at mitigating disease severity are of utmost global priority (https://www.who.int/). SARS-CoV-2 infection results in a wide spectrum of disease severity, ranging from asymptomatic individuals to critically-ill patients leading to death. Severe COVID-19 disease presents with high-grade fever, dry cough, pneumonia, inflammation of the lungs and infiltration of immune cells. It has been noted that individuals with co-morbidities and compromised immune systems are at higher risk for severe clinical manifestations (Guan et al., 2020) .

Immunological features of COVID-19 progression includes a robust pro-inflammatory response driven by innate and adaptive immune cells, with severe cases of COVID-19 having elevated serum levels of pro-inflammatory cytokines and chemokines including: IFNγ, TNFα, IP-10, G-CSF, IL-2, IL-6 IL-8, IL-9, IL-10, and IL-17. Therefore, the use of therapeutics targeted at Janus

Kinases (JAK) have the potential to ameliorate disease severity by limiting the hypercytokinemia and cytokine release syndrome (CRS) seen in COVID-19 patients .

Non-human primate (NHP) models have been used extensively to study pathogenesis and potential vaccine and antiviral candidates for numerous viral diseases (Estes et al., 2018) . We and others have recently used rhesus macaques (RMs) to model SARS-CoV-2 infection and pathogenesis; SARS-CoV-2 infected RMs develop transient respiratory disease and exhibit viral shedding similar to humans, recapitulating mild to moderate infection, and only in rare cases severe disease Munster et al., 2020; Rockx et al., 2020; Williamson et al., 2020; Yu et al., 2020) . Baricitinib is an oral, selective inhibitor of JAK 1 and 2 with potent anti-inflammatory activity approved for treatment of patients with moderate to severe active rheumatoid arthritis (Keystone et al., 2015) . Recently, machine learning algorithms and in vitro data suggested that baricitinib could also inhibit clathrin-mediated endocytosis of SARS-CoV-2 (Cantini et al., 2020; Richardson et al., 2020; Stebbing et al., 2020; Titanji et al., 2020) ; thus, it could provide a dual effect of dampening inflammation and viral infection. In this study, leveraging the ability to perform longitudinal collections, including bronchoalveolar lavages, and the availability of lung tissue for pathology, we tested the immunologic and virologic effects of baricitinib treatment in SARS-CoV-2 infected RMs.

Baricitinib was well-tolerated and detectable in plasma and tissues, but did not limit

J o u r n a l P r e -p r o o f

We inoculated 8 adult RMs (11-17 years old, mean = 14 years, Table S1 ) with a total of 1.1x10 6 PFU SARS-CoV-2 (2019-nCoV/USA-WA1/2020), administered by intranasal (IN) and

intratracheal (IT) routes . Two days post infection (DPI), 8 RMs were randomized to receive 4 mg of oral baricitinib, daily for 8-9 days or observed without treatment until 10-11 DPI when all RMs were euthanized (Figure 1A) . A slight reduction of peripheral monocytes, neutrophils and lymphocytes, which could be due to trafficking to the lung, as well as decreased red blood cell counts (RBC), hematocrit (HCT) and hemoglobin (HGB) were observed starting at 2 DPI in all RMs (Figures S1B-S1G). Blood chemistries showed elevated levels of alkaline phosphatase (ALP) in one untreated animal starting at 2 DPI, and all other values were within the normal range ( Figure S1H ). Body temperature remained stable in all RMs ( Figure S1I) . Overall, treatment with baricitinib was well-tolerated without direct evidence of treatment-induced clinical pathology, nephrotoxicity or hepatotoxicity when compared to untreated SARS-CoV-2 infected RMs. To further monitor response to infection and baricitinib treatment, the health status of all animals was assessed daily by veterinarians, with cage-side assessment and physical examination scored based on a standardized scoring system (modified from previous studies (Chertow et al., 2016; ; main parameters included in the scoring are listed on Tables S2 and S3) . On 1 DPI, all animals exhibited changes to alertness and respiratory pattern ( Figure 1D ). Additional early J o u r n a l P r e -p r o o f signs of disease included: changes to pulse oximetry readings, with one untreated animal dropping below 80% ( Figure 1F) , reduction in appetite, hunched posture, shivering, pale appearance and agitation. Signs of disease persisted during the 10/11-day course of the study, without significant differences between treated and untreated animals ( Figure 1D ). Weight loss was observed in 4/4 untreated and 3/4 baricitinib treated RMs (Figure 1E) , although we cannot discriminate if this is a result of the infection or related to frequent access for sample collection.

We next assessed viral RNA levels by qRT-PCR Munster et al., 2020) . We observed high levels of SARS-CoV-2 RNA in nasal and throat swabs, and bronchoalveolar lavages (BAL), with a peak between 2-4 DPI of 1.4x10 7 , 1.2x10 6 , and 1.9x10 5 copies/mL respectively (Figures 1G-1I ); viral RNA then steadily decreased until 10-11 DPI.

SARS-CoV-2 RNA levels remained similar in nasal, throat, or BAL between the baricitinib treated and the untreated group. Virus was not detected in blood and transiently present in rectal swabs (Figure 1J ). At necropsy (10-11 DPI), viral RNA was detected for most animals in nasopharynx, lower/upper lungs, and hilar lymph nodes; viral RNA was detected in the ileum of 4/4 untreated and 1/4 treated RMs. Viral loads (cycle threshold value) in tissue for treated and untreated RMs were overall comparable ( Figure 1K ). Additionally, in situ RNA hybridization (RNAscope) targeting both positive and negative-sense viral RNA strands identified multifocal clusters of infected cells within the lung parenchyma in both treated and untreated RMs ( Figure   S2A ). Thus, baricitinib treatment starting at 2 DPI was safe and well tolerated, but did not impact the kinetics of SARS-CoV-2 replication.

We then performed multiple analyses to determine the severity of SARS-CoV-2 infection in RMs and the effectiveness of baricitinib to ameliorate the pathophysiologic response. First, x-ray J o u r n a l P r e -p r o o f radiographs (RM6 x-ray; Figure 2A ) were longitudinally (-5, 2, 4, 7 and 10 DPI) performed (blinded scoring by a radiologist as previously reported (Munster et al., 2020; Williamson et al., 2020) ). Pulmonary infiltration and ground glass opacity were observed at multiple experimental timepoints post-infection in 2/4 untreated and 0/4 treated RMs (Figures 2B and 2C (Figures S2H-S2I ). Of note, some of the SARS-CoV-2 infected animals in both groups showed cell infiltration levels similar to uninfected RMs, indicating a resolution of the infiltration at 10-11 DPI, consistent with an earlier peak of pathogenesis in RMs, as previously published Munster et al., 2020; Rockx et al., 2020; Williamson et al., 2020; Yu et al., 2020) . The average pathology score per lobe (measuring the average severity of abnormalities per lobe, independently of how many lobes had been effected, J o u r n a l P r e -p r o o f p=0.0286) and the total pathology score (considering severity and number of effected lobes, p=0.0857) were lower in the baricitinib treated group (0.99 and 22, respectively) as compared to untreated RMs (1.66 and 38.5, respectively) ( Figures 2L-2N) . Overall, these data support a therapeutic role of baricitinib in reducing lung pathology, infiltration of inflammatory cells in the lung, and soluble markers of inflammation associated with disease progression in humans.

To investigate the impact of baricitinib on the lower airway, we performed bulk RNA-Seq profiling of cells isolated from BAL prior to SARS-CoV-2 inoculation (-5 DPI; Baseline); 2 days after virus inoculation, prior to baricitinib treatment (2 DPI); and 4 days after infection, and 48 hours after beginning baricitinib (4 DPI). Relative to pre-infection, we observed a robust upregulation of differentially expressed genes (DEGs) at 2 DPI in both the treated and untreated RMs ( Figure 3A ), however at 4 DPI only a handful of DEGs were detected in the baricitinib treated animals, whereas a robust transcriptional response persisted in the untreated group. To identify immunological pathways perturbed by SARS-CoV-2 infection and baricitinib treatment, we performed gene-set enrichment analysis (GSEA) (Subramanian et al., 2005) . To determine pathways that changed after drug administration, we directly compared gene expression profiles at 2 DPI to 4 DPI. Comparison of GSEA data from 2 DPI to 4 DPI in untreated RMs show robust, highly significant positive enrichment in pathways comprised of genes for inflammatory responses, TNFα and IL6 signaling, neutrophil and granulocyte function -indicating that, in the absence of baricitinib, expression of these genes continues to increase ( Figure 3B ). In stark contrast, when a similar comparison of 2 DPI vs 4 DPI was tested in RMs receiving baricitinib, we observed negative enrichment, indicating that inflammatory genes were expressed at lower levels already after only 2 days of treatment ( Figure 3B ). To confirm the robustness of our enrichment analysis in detecting downregulation of inflammatory pathways with treatment, we J o u r n a l P r e -p r o o f also conducted GSEA analyses using direct cross-sectional comparisons (i.e. 4 DPI untreated vs 4 DPI treated) ; these data demonstrated that inflammatory signatures were significantly lower in animals receiving baricitinib at 4 DPI, although equivalent when comparing 2 DPI samples in which neither group had received the drug (Figures S3A and S3B) .

To explore the impact of baricitinib on the inflammatory responses induced by SARS-CoV-2 infection at the gene level, we examined several pathways in greater detail (Figures 3C-3J) .

One of the highest scoring pathways, neutrophil degranulation, was significantly enriched at 4 DPI relative to 2 DPI in the untreated group (p<0.001) ( Figure 3C) . Strikingly, enrichment of this pathway was completely abrogated in the treated group (p=0.979). When we examined individual genes that were (i) elevated by SARS-CoV-2 infection, and (ii) influenced by baricitinib treatment, we observed that several genes were those encoding degradative and bactericidal enzymes present in neutrophil granules (MMP9, MMP25, BPI, MPO), or highly expressed on polymorphonuclear neutrophils (CXCR1 and CXCR2), the alarmin S100A12, and genes for proteins that act to degrade the extracellular matrix during neutrophil extravasation:

SERPINB10, ADAM8 ( Figure 3G ). Of note, S100A12, (EN-RAGE), for which expression was effectively reduced by baricitinib treatment, has been associated with COVID-19 severity in humans (Arunachalam et al., 2020) . These genes were highly upregulated in BAL samples of untreated RMs, but substantially attenuated in treated animals, many at levels equivalent to preinfection ( Figure 3G) . Collectively, these gene signatures suggest that baricitinib treatment may dampen macrophage inflammation as well as neutrophil recruitment and activity in the lower airway during acute SARS-CoV-2 infection. We also examined the enrichment of neutrophil pathway genes in cross-sectional GSEA comparisons, as shown in Figures S3C and S3D ; this analysis largely mirrored our D2 vs D4 observations. Additionally, we observed several alarmin proteins (S100A8, S100A9) had lost their induction at 4 DPI in animals receiving baricitinib, as did the MPO gene. These genes have been recently demonstrated to be highly expressed in the J o u r n a l P r e -p r o o f myeloid compartment of peripheral blood of patients exhibiting severe COVID-19 disease (Schulte-Schrepping et al., 2020; Silvin et al., 2020) .

Baricitinib treatment also rapidly induced near complete abrogation of inflammation mediators downstream of TNFα signaling and IL6 signaling (Figures 3D and 3E, 3H and 3I ). Within these pathways, amongst the molecules suppressed by baricitinib were chemotactic factors critical for recruitment of neutrophils (CXCL6, CXCL3) and macrophages (CCL2), inflammatory serine protease factors (SERPINB2, TNFAIP6) and cytokines regulating inflammation and immune responses (IL12B). Of note, genes identified as upregulated in rheumatoid arthritis (RA) were found to be significantly enriched (p=0.0448) in untreated as compared to treated animals at 4 DPI, despite similar gene expression at 2 DPI (Figures S3E and S3F ). In the leading-edge analysis of the RA pathway we noted lower expression of several inflammatory mediators such as CXCL8, IL1B, CCL5, CCL3, CCL20, IL18, IL6 and CXCL12 (Figures S3G and S3H) . As baricitinib was developed to ameliorate inflammation in RA by inhibiting JAK1/2 signaling, and consistently with the reduction in the IL-6/JAK/STAT3 signaling pathway ( Figure 3I ), these data confirm the effectiveness of baricitinib in the lower airway of SARS-CoV-2 infected RMs.

Several of the significantly enriched genesets were comprised of genes in Type I interferon signaling ( Figure 3B ) and multiple interferon stimulated genes (ISGs) had elevated expression relative to baseline ( Figure 3J ). In both treated and untreated groups, we observed a slight reduction in expression at 4 DPI relative to 2 DPI (Figures 3B and 3F) . However, unlike genesets associated with inflammation, genes associated with Type I IFN signaling and innate antiviral responses were unperturbed by baricitinib. Thus, baricitinib treatment potently suppressed inflammatory pathways in the lower airway of RMs infected with SARS-CoV-2, but left innate antiviral signaling largely intact.

J o u r n a l P r e -p r o o f

The bulk RNA-Seq data indicated that gene signatures consistent with macrophage activation, neutrophil infiltration and cytokine driven inflammation were evident as early as 2 DPI, and that baricitinib was capable of abrogation of these pathways. To identify the cellular component orchestrating airway inflammation, we performed single-cell RNA-Seq (sc-RNA-Seq) profiling using 10X Genomics-based droplet sequencing. Single cell suspensions of BAL samples from three untreated and two baricitinib treated RMs prior to infection, and at 4 DPI were subjected to 10X droplet capture within 3 hours of collection. After processing to remove erythrocytes and low-quality cells, the captures yielded a cumulative 45,583 cells across all samples for analysis.

The cellular distribution is summarized in the UMAP shown in Figure 4A . Similar to observations reported in sc-RNA-Seq data in humans infected with SARS-CoV-2 (Bost et al., 2020; Chua et al., 2020; Liao et al., 2020) , the vast majority of cells in BALs were predominantly macrophage/myeloid origin (80.7%), followed by lymphocytes (CD4 + /CD8 + T cells/ NK cells) (9.8%) and approximately 3.2% were identified as epithelial. Allocation of cells from the cumulative data by treatment variables (Figure 4B ) demonstrated that the cellular distribution was equivalent amongst the experimental groups and no population was enriched due to batch or technical variation associated with individual captures. We probed the macrophage population for upstream regulators associated with the inflammatory pathways identified in the bulk RNA-Seq analyses, and observed elevated expression of several inflammatory mediators at 4 DPI: IL6, TNFα, IL1β and IL10 (Figures 4C, S4 and S5) . IFNβ was also highly expressed in the macrophage cluster, however, IFNα transcripts were detected in a virtually negligible fraction of cells (Figures 4C, S4 and S5) . Strikingly, and consistent with the bulk RNA-Seq data, we observed that baricitinib treatment virtually dampened expression of TNFα, IL10, IFNβ and IL6 in pulmonary macrophages, and significantly reduced expression of IL1β ( Figure 4C ).

We also observed a robust induction of chemokines driving neutrophil recruitment (CXCL3/MIP2β, CXCL8/IL8), macrophage trafficking (CCL4L1/MIP1β), and CXCL10/IP10

( Figures 4D and 4E) , a pleiotropic chemokine upregulated in several viral infections, and long hypothesized to be associated with pathogenesis in SARS-CoV-1 viral infection and observed in SARS-CoV-1 infection of NHPs (de Lang et al., 2007; Laing et al., 2020; Tang et al., 2005) .

Notably, after 48 hours of baricitinib treatment, expression of these proinflammatory cytokines was reduced to basal levels ( Figures 4D and 4E) . Examination of the expression levels of antiviral ISGs in pulmonary macrophages yielded a much different pattern than those observed for inflammatory genes -although widespread induction of ISGs were observed after SARS-CoV-2 infection, baricitinib treatment had only a very modest impact on these pathways ( Figure   4F ). Collectively, these data support a model in which baricitinib administration strongly reduces airway inflammation and neutrophil accumulation, but has a minimal effect on innate antiviral immunity.

To gain insight into the immunologic effects of baricitinib treatment on cellular distribution within BAL, we applied global high-dimensional mapping of 23-parameter flow cytometry data. As shown in the UMAP representation ( Figure 5A ), untreated and baricitinib treated RMs had different BAL cellular distribution starting from 4 DPI, corresponding with the timepoint of peak inflammation and viremia, including in neutrophils. This was of interest considering the higher frequency of macrophages expressing neutrophil-attracting chemokines in untreated RMs ( Figures 4D and 4E) . Thus, we focused our flow cytometry immunologic analyses in quantifying the longitudinal levels of neutrophils (CD45 + CD3 -CD20 -CD66 + live granulocytes;

representative staining in Figures S6A and S6B ). Analyses of BAL showed an early recruitment of neutrophils in the lung at 4 DPI during the peak of viremia, particularly in the untreated RMs, which all maintained higher frequencies of neutrophils at later stages of J o u r n a l P r e -p r o o f infection (10-11 DPI) as compared to baricitinib treated RMs ( Figure 5B ; p=0.0286). In blood, neutrophils ( Figure 5C ) remained relatively stable post infection as compared to pre-infection and at lower levels in untreated as compared to treated animals at the latest experimental points (p=0.0571), consistently with a higher migration to lung in untreated RMs. The levels of CD14 + CD16 -( Figure 5D ) and CD14 + CD16 + monocytes in the BAL were, on average, slightly higher in untreated RMs at 4, 7, and 10 DPI, with the difference due to 3 of 4 untreated RMs having levels higher than the untreated animals at specific timepoints ( Figure 5D ). Since the flow cytometry data of BAL shows a reduced migration of neutrophils to lung in baricitinibtreated RMs, we next measured neutrophil extracellular trap (NET) activity by quantification of extracellular DNA via Sytox staining, a functional readout of NETosis activity (Figures 5E and   5F ) and by quantification of citrullinated H3 ( Figure 5G) , a systemic marker indicating a posttranslational modification thought to precede DNA decondensation during NETosis. NETs have been reported as an important mechanism of inflammation and microvascular thrombosis in patients with COVID-19 (Skendros et al., 2020) . Baricitinib treated RMs showed decreased NET formation by blood neutrophils at 4 (more evident for citrullinated H3, Figure 5G ; p = 0.0571) and 10 (more evident for Sytox staining, Figure 5F ; p=0.0571) DPI when compared to untreated RMs. Finally, when the formation of NETs was examined directly in the lung by IHC staining for citrullinated H3, 3/4 untreated RMs showed presence of NETs whereas NETs were virtually absent in treated RMs ( Figure 5H ).

Altogether, these data support baricitinib activity in reducing macrophage-derived inflammation and by decreasing pro-inflammatory neutrophilic levels, activity and NETosis.

Our transcriptomic data indicated that baricitinib reduced macrophage expression of multiple cytokines that can induce T cell immune activation. As such, we then analyzed levels of T cells,

and their frequency of activation and proliferation by flow cytometry (gating strategy shown in Figure S6C ). CD4 + T cell levels in blood remained similar between treated and untreated animals, with 1/4 baricitinib treated and 2/4 untreated RMs exhibiting a pronounced reduction in CD4 + T cell frequencies at 10 DPI ( Figure 6A ). We observed an expansion of CD4 + T Regs (CD45 + CD3 + CD4 + CD95 + CD127 -CD25 + FoxP3 + ; representative staining in Figure S6C ) at 4 (p=0.0571) and 6 DPI in the untreated, but not in the baricitinib treated RMs ( Figure 6B ).

Specifically, the mean fold change in CD4 + T Regs frequency at 4 and 6 DPI, as compared to pretreatment baseline (2 DPI), was of 7.43 and 4.36 in untreated and of 1.22 and 1.13 in baricitinib treated RMs, respectively, suggesting higher levels of inflammation in the untreated group resulting in greater expansion of CD4 + T Regs ( Figure 6C ). Peripheral CD8 + T cells were reduced at 10 DPI in 2/4 baricitinib treated and 2/4 untreated RMs ( Figure 6D) . Notably, the frequency of proliferating (Ki-67 + ) memory CD8 + T cells in blood progressively and significantly increased in all 4 untreated animals at 7 and 10 DPI, while significantly decreasing in all baricitinib treated RMs already at 4 DPI. As a result, at 10 DPI the mean frequency of CD8 + Ki-67 + was significantly higher in untreated RMs (24.38% vs 7.38%; p = 0.0286, Figure 6E ).

CD4 + T cells in the BAL remained relatively constant until 7 DPI, when the majority of RMs started experiencing a reduction in their frequencies ( Figure 6F ). Untreated RMs showed an early (present at 4 DPI), large (mean fold change of 3.31 at 7 DPI vs 2 DPI compared to 1.14 in the treated RMs) and prolonged (up to 10 DPI) increase in the frequency of memory CD4 + T cells expressing CD38 (CD38 + HLA-DR -; 4 DPI, p=0.0286, Figure 6G ). Remarkably, different from untreated RMs, the frequency of those activated memory CD4 + T cells decreased in baricitinib treated animals starting at 4 DPI and remained lower than pre-treatment until 10 DPI ( Figure 6G ). Consistent with a reduced pro-inflammatory state of CD4 + T cells, baricitinib treated RMs showed a lower frequency of CD4 + T cells that spontaneously (without stimulation) J o u r n a l P r e -p r o o f produced pro-inflammatory, Th17 related cytokines (IL-17 + ; IL-17 + IL-21 + ; IL-17 + IL-22 + ) when compared to untreated RMs (Figures S7A-S7C) .

As with CD4 + T cells, the reduction in CD8 + T cells was more pronounced in BAL, starting at 7 DPI and maintained until necropsy ( Figure 6H) . Similarly, also in BAL the frequency of CD8 + Ki-67 + T cells increased more extensively in untreated than baricitinib-treated RMs (30.53% vs 11.53% at 7 DPI; 39.95% vs 24.65% at 10 DPI; Figure 6I ); as a result, the fold change (as compared to 2 DPI, pre-treatment) in the frequency of memory CD8 + Ki-67 + T cells was higher in Finally, we assessed the ability of peripheral T cells to respond to ex vivo SARS-CoV-2 specific stimulation (with a SARS-CoV-2 S peptide pool characterized in (Grifoni et al., 2020) ) and to non-antigen specific stimulation (with PMA/ionomycin). Importantly, the levels of SARS-CoV-2 specific CD4 + and CD8 + T cells producing IFNγ, TNFα, IL-2, IL-4 and IL-17a in response to S peptide pool stimulation were similar in both groups of animals (Figures S7D-S7F) . Similarly, the frequency of CD4 + and CD8 + T cells producing IL-17a, IL-21, IL-22, IFNγ, and TNFα were similar among the two groups after PMA/Ionomycin stimulation (Figures S7G and S7H) .

Furthermore, levels of memory CD4 + and CD8 + T cells expressing granzyme B or PD-1 remained similar between untreated and treated RMs both in blood (Figures S7I and S7J ) and

BAL (Figures S7K and S7L ).

Collectively, these findings indicate that baricitinib treatment lead to downstream reduction in T cell activation and proliferation, without an overall detrimental effect to antiviral function of T cells.

In this study, we tested baricitinib, a JAK1/2 inhibitor clinically approved for rheumatoid arthritis, responses. This beneficial anti-inflammatory effect of baricitinib was confirmed by a reduced infiltration of macrophages and neutrophils into the lungs, and a reduced T cell activation in both blood and BAL as compared to untreated animals. Furthermore, we were able to observe an increased NETosis activity of neutrophils upon SARS-CoV-2 infection, previously described in serum from COVID19 patients (Skendros et al., 2020) , which was reduced in baricitinib treated

RMs. Remarkably, single-cell RNA sequencing showed reduced immune activation, neutrophil recruitment, and macrophage trafficking signatures in pulmonary macrophages from treated RMs already after two doses of baricitinib, at 4 DPI. IL-6, TNFα, IL-10, IL-1B, CXCL3/MIP-2β, CXCL8/IL8, CCL4L1/MIP-1β, and CXCL10/IP-10 were all expressed at higher levels in pulmonary macrophages from untreated animals compared to baricitinib treated RMs. These data confirm very recent studies that demonstrated by RNA-Seq analysis that higher levels of inflammatory cytokines in lung macrophages are associated with patients presenting with J o u r n a l P r e -p r o o f severe/critical COVID-19 cases (Liao et al., 2020) . Thus, baricitinib could have clinical benefits in reducing the inflammatory response typically seen in moderate to severe cases of COVID-19 ( Figure 7) . Of note, one of the advantages of baricitinib when compared with other cytokinespecific anti-inflammatory therapies is that it can inhibit production of several cytokines involved in the cytokine storm described in severe cases of COVID-19.

Clinical pathology and laboratory parameters of toxicity remained similar in the treated RMs for the 8-9-day treatment course at a dose comparable to humans (Bronte et al., 2020; Cantini et al., 2020; Titanji et al., 2020) . Baricitinib was found distributed in lungs, a key tissue for SARS-CoV-2 replication, as well as in the central nervous system (CNS). Although several in silico modeling and in vitro studies suggested baricitinib as a possible treatment candidate to COVID-19 due to its potential antiviral activity (Cantini et al., 2020; Richardson et al., 2020; Stebbing et al., 2020; Titanji et al., 2020) , we did not observe changes in viral replication dynamics in the treated animals. One of the main concerns in using a JAK inhibitor such as baricitinib, is that its downstream anti-immune activation effects could limit immune responses necessary to combat SARS-CoV-2. Importantly, we did not identify reduction of SARS-CoV-2 specific and unspecific CD4 + and CD8 + T cell responses in treated animals, and baricitinib did not inhibit genes associated with Type I Interferon antiviral responses, indicating its mode of action in this context is primarily to dampen inflammatory responses while maintaining innate and adaptive antiviral immune responses. While ISGs can certainly be stimulated via the JAK/STAT pathways, ISGs have also been shown to be highly inducible via the STING and RIG-I pathways (Loo et al., 2008; Loo and Gale, 2011; Zevini et al., 2017) , which are not affected by baricitinib. It is possible that these pathways could compensate for the reduced stimulation via the JAK/STAT pathway. subjects (Titanji et al., 2020) . In a separate pilot study, baricitinib was combined with lopinavirritonavir in 12 patients starting treatment 6 days post-symptom onset, with all individuals showing significantly improved clinical and laboratory parameters with no treated individuals requiring ICU care (Cantini et al., 2020) . Being performed in an animal model, this study has some key advantages and some important limitations. Advantages include the ability to correct for parameters that may impact clinical outcome and treatment readout, including using the (Bronte et al., 2020) . Our data provides rationale for baricitinib treatment in COVID-19 to be given in a window where blocking immune inflammation would prevent the formation of a cytokine storm without interfering in the initial responses necessary for preventing viral dissemination and persistence.

In conclusion, this study provides rationale and mechanisms of actions for a beneficial antiinflammatory effect of baricitinib treatment for COVID-19. Statistical analysis was performed using a non-parametric Mann-Whitney Test. See also Figures S1, and S2A, and Tables S1, S2, and S3. 

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Mirko Paiardini (mirko.paiardini@emory.edu).

This study did not generate new unique reagents.

The datasets generated during this study are available at Gene Expression Omnibus (GEO) accession GSE159214 and code can be made available upon requests.

Source data supporting this work are available from the corresponding author upon reasonable request. The following sequencing data have been deposited in GenBank: SARS-CoV-2 viral stock (accession # PENDING). Data tables for expression counts for bulk and single-cell RNA-Seq for BAL are deposited in NCBI's Gene Expression Omnibus and are accessible through GEO accession GSE159214. Custom scripts and supporting documentation on the RNA-Seq analyses will be made available at https://github.com/BosingerLab/. 

Eight (4 female and 4 male) specific-pathogen-free (SPF) Indian-origin rhesus macaques (RM;

Macaca mulatta; Table S1 ) were housed at Yerkes National Primate Research Center (YNPRC) as previously described in the ABSL3 facility. Animals for study assignment were requested to be greater than 11 years old without preference for gender or MHC haplotype. RMs were infected with 1.1x10 6 plaque forming units (PFU) SARS-CoV-2 via both the intranasal (1 mL) and intratracheal (1 mL) routes concurrently. Absent further stratification criteria, four RMs were administered 4 mg Baricitinib (Olumiant, Eli Lilly) starting at day 2 post-infection (DPI) for 8-9 consecutive days. Baricitinib was supplied as a powder that was folded into food items (i.e. honey, yogurt, etc.) or distilled water, which was delivered either orally or as a gavage when animals were being anesthetically accessed, respectively. At each anesthetic access pulse oximetry was recorded and RMs were clinically scored for responsiveness and recumbency; discharges; skin condition; respiration, dyspnea, and cough; food consumption; and fecal consistency (Tables S2 and S3 ). At 10-11 DPI, RMs were administered Baricitinib and subjected to necropsy after 2 hours with blood and cerebrospinal fluid (CSF) collected perimortem to assess pharmacokinetics of baricitinib. Longitudinal tissue collections of peripheral blood (PB); axillary or inguinal lymph node (LN) biopsies; bronchoalveolar lavage (BAL); and nasal, and pharyngeal mucosal swabs in addition to thoracic J o u r n a l P r e -p r o o f X-rays (ventrodorsal and right lateral views) were performed immediately prior to Baricitinib administration as annotated ( Figure 1A) . In addition to the tissues listed above, at necropsy the following tissues were processed for mononuclear cells: hilar LN, lower lung, and upper lung.

Additional necropsy tissues harvested for histology included nasopharynx.

Vero E6 Back titration of viral stocks via plaque assay was used to determine the infectious dose delivered to the RMs. The virus stock was also directly sequenced via metagenomic methods prior to inoculation to confirm the presence of the furin cleavage motif, which has been shown to be lost upon sequential passage of SARS-CoV-2 in culture (Davidson et al., 2020) . Our stock contained fewer than 6% of viral genomes with a mutation that could potentially abrogate furin-mediated cleavage of S.

J o u r n a l P r e -p r o o f SARS-CoV-2 genomic RNA was quantified in nasopharyngeal (NP) swabs, throat swabs, plasma, and bronchoalveolar lavages (BAL). Swabs were placed in 1mL of Viral Transport Medium (VTM-1L, Labscoop, LLC). Viral RNA was extracted from NP swabs, throat swabs, and BAL on fresh specimens, while plasma was frozen for future analysis. Viral RNA was extracted manually using the QiaAmp Viral RNA mini kit according to the manufacturer's protocol.

Quantitative PCR (qPCR) was performed on viral RNA samples using the N2 primer and probe 

An approximately 0.5 cm 3 sample of each tissue was collected at necropsy, placed in 500µL

Nuclisens lysis buffer (Biomerieux), and stored at -80℃. Thawed samples were homogenized with a sterile pestle, treated with 50µL proteinase K (Qiagen) for 30 minutes at 55℃, and pelleted. Total nucleic acid was extracted from 250µL of supernatant using eMAG (Biomerieux) and eluted into 50µL. RT-PCR for SARS-CoV-2 N2 was performed as previously described, and singleplex RT-PCR for RNase P was performed using primers and probes optimized for quantitation, each using 5µL of eluate (Waggoner et al., 2020) . To allow for comparison of J o u r n a l P r e -p r o o f SARS-CoV-2 levels between samples that may have had subtle differences in starting material, the SARS-CoV-2 N2 Ct was normalized to the RNase P control by: 1) calculating the difference between N2 Ct and RNase P Ct for each sample, and 2) adding this to the median RNase P Ct value for the sample type. For the purposes of data visualization, samples in which SARS-CoV-2 N2 was undetected were assigned a Ct value of 40 (the assay limit of detection).

One hundred µL of plasma or CSF samples were extracted with 500 µL of methanol. For tissues like brain and lung, 0.2 to 0.5 g of tissue were homogenized and extracted with 2 mL of methanol. [ 2 H 9 ]-ruxolitinib dissolved in 50% methanol at 500 nM was spiked in plasma/CSF (10 µL) or tissue samples (40 µL) as internal standard before extraction. Calibration curves were generated from standard baricitinib by serial dilutions in blank biometric J o u r n a l P r e -p r o o f samples using the same extraction method described above. For CSF, 0.5% plasma was used as surrogate to make calibration curve. The calibration curves had r 2 value greater than 0.99.

All the chemicals are analytical grade or higher and were obtained commercially from Sigma-Aldrich (St. Louis, MO). [ 2 H 9 ]-ruxolitinib was purchased from ALSACHIM (lllkirch, Alsace, France) with purity greater than 98%.

Serum ferritin (Beckman Coulter; Cat# 33020) and C-Reactive protein (Beckman Coulter; Cat# OSR6147) levels were quantified by Emory Medical Laboratory using manufacturer protocols.

Due to study end point, the animals were euthanized, and a complete necropsy was performed.

For histopathologic examination, various tissue samples including lung, nasal turbinates, trachea, or brain, were fixed in 4% neutral-buffered paraformaldehyde for 24h at room temperature, routinely processed, paraffin-embedded, sectioned at 4µm, and stained with hematoxylin and eosin (H& E). The H&E slides from all tissues were examined by two board certified veterinary pathologists. For each animal, all the lung lobes were used for analysis and affected microscopic fields were scored semi-quantitatively as Grade 0 (None); Grade 1 (Mild);

Grade 2 (Moderate) and Grade 3 (Severe). Scoring was performed based on these criteria: 

RNAscope in situ hybridization was performed as previously described using SARS-CoV2 anti-sense specific probe v-nCoV2019-S (ACD Cat. J o u r n a l P r e -p r o o f normal saline (0.9% NaCl) was administered into the bronchus and re-aspirated to obtain a minimum of 20ml of lavage fluid. BAL was filtered through a 70µm cell strainer.

Lung tissue was cut into small pieces, using blunt end scissors, then digested using 1.5 U/mL DNase I (Roche) and 1 mg/mL of Type I collagenase (Sigma-Aldrich) using gentleMACS C tubes and gentleMACS Dissociator (miltenyi Biotec).

Hilar LN biopsies were collected at necropsy, sectioned using blunt, micro-dissection scissors and mechanically disrupted through a 70µm cell strainer and washed with R-10 media.

Mononuclear cells were counted for viability using a Countess II Automated Cell Counter (Thermo Fisher) with trypan blue stain and were cryo-preserved in aliquots of up to 2x10 7 cells in 10% DMSO in heat-inactivated FBS. Whole tissue segments (0.5 cm 3 ) were snap frozen dry, or stored in RNAlater (Qiagen), or Nuclisens lysis buffer (Biomerieux) for analyses of compound distribution, RNA-seq, and tissue viral quantification, respectively.

Single cell suspensions from BAL were prepared in BSL3 as described above for flow cytometry; for bulk RNA-Seq, 50,000 cells were lysed directly into 700 ul of QIAzol reagent.

RNA was isolated using RNeasy Mini or Micro kits (Qiagen) with on-column DNase digestion.

RNA quality was assessed using an Agilent Bioanalyzer and total RNA was used as input for cDNA synthesis using the Clontech SMART-Seq v4 Ultra Low Input RNA kit ( Takara Bio) according to the manufacturer's instructions. Amplified cDNA was fragmented and appended with dual-indexed bar codes using the NexteraXT DNA Library Preparation kit (Illumina). (Sandler et al., 2014) .

The ReadsPerGene files were used to generate counts in the htseq format using a custom script that also converted the Ensembl ID to gene names using the gtf file. These files were imported in DESeq2 using the DESeqDataSetFromHTSeqCount function. DESeq2 was used for normalization (Love et al.) , producing both a normalized read count table and a regularized log J o u r n a l P r e -p r o o f expression table. Only the protein coding genes defined in the gtf file were used for analysis.

The design used was: ~ Subject + Group where Group was a combination of Timepoint (baseline/2dpi/4dpi) and Condition (Untreated/Treated) factors. The regularized log expression values were obtained using the rlog function with the parameters blind =FALSE and filtType = "parametric". The thresholds of padj < 0.05, fold-change > 1.5 and lfcSE < 1 were used to obtain significant differentially expressed genes. The VennDiagram R library was used to create the venn diagrams. GSEA 4.1.0 (https://www.gsea-msigdb.org/) was used for gene set enrichment analysis with the following gene sets: Hallmark and Canonical pathways (MsigDB), NHP ISGs (Sandler et al.) and Rheumatoid arthritis (KEGG map05323). GSEA was run with default parameters with the permutation type set to gene_set. The input for GSEA was the regularized log expression values obtained from DESeq2 which was filtered to remove genes with mean expression <=0. The regularized log expression values were also used to generate heatmaps using the Complex Heatmap R library.

Bronchoalveolar lavage (BAL) samples from five Rhesus Macaque's were run on 2 Nova Seq 1000 lanes and the resultant bcl files were converted to counts matrices using Cell Ranger v3.1 (10X Genomics). Further, the count matrices for each sample were processed using an inhouse single-cell RNA-seq pipeline that uses Seurat v3.0 (Satija et al., 2018) 

Neutrophils were obtained from peripheral blood of SARS-Cov-2 infected Rhesus Macaques 5 days pre-infection and at days 4, 7, and 10 post-infection. Peripheral blood (0.5-1 ml) was collected using a citrate containing Vacutainer and the upper serum layer was removed. The red blood cell layer was lysed with 2 mL of Red Blood Cell Lysis Buffer (Cat# 11814389001, Roche) in a 15 mL tube. The tube was gently inverted for 10 minutes at room temperature and centrifuged at 500 x g for 7 minutes at room temperature. This step was repeated gently inverting for 5 minutes. Following centrifugation, the cell pellet was re-suspended in a final volume of 2 mL of 1x PBS/EDTA buffer gently. Cells were centrifuged at 500 x g for 7 mins a room temperature and the leukocyte pellet was re-suspended in 1 mL 1x PBS/EDTA buffer and carefully overlaid onto 3 mL of 65% Percoll/EDTA solution. The Percoll cell gradient was centrifuged at 400 x g for 20 mins at room temperature with the brake turned off. The neutrophil cell layer was collected, re-suspended/washed with 5 mL of 1x PBS/EDTA buffer and centrifuged at 500 x g for 10 minutes at room temperature. The neutrophil cellular pellet was resuspended in RPMI 1640 media. Purification of the cell fragment was confirmed using flow cytometry and Wright Giemsa staining.

Abundance of extracellular DNA, a surrogate of NETs, was quantified using the SYTOX green assay. Freshly, isolated non-human primate neutrophils were plated onto a 96-well plate at a density of 10 5 cells per well in 100 µL RPMI 1640 media then stimulated with 50 µg/mL LPS to J o u r n a l P r e -p r o o f induce NET formation. SYTOX green dye (5 µM, #S7020; Invitrogen, Carlsbad, CA) was added to each well and the fluorescence intensity was read with a filter setting at 485-nm excitation/525-nm emission using a Synergy H1 Microplate Reader and Gene5 software (Biotek, Winooski, VT). A fluorescence reading was collected every 15 mins for a total of 2 hours at 37°C. Images of the fluorescent cells were immediately taken using a fluorescent microscope (Olympus).

Paraffin-embedded lung sections were subjected to deparaffinization followed by heat induced antigen retrieval in 10 mM sodium citrate buffer (pH 6.0). Sections were blocked with 10% goat serum in 1x PBS for 1 hour. Primary antibody staining was performed for citrullinated H3 (Cayman Chemical, Cat. No. 17939, 1:50) overnight at 4°C. Slides were then incubated with Alexa Fluor 633 anti-mouse IgG secondary antibody (Thermo Fisher Scientific, Cat. No.

A21052, 1:1000) for 90 mins at room temperature. Images were taken at 20x objective using a Zeiss LSM 800 Airyscan laser scanning confocal microscope.

We quantified citrullinated histone 3 using an ELISA kit (Cayman Cat # 501620) with the antibody clone 11D3 per the manufacturer's instructions. In short, 100 uL sample or standard was added in duplicate to a pre-coated 96-well plate and incubated for 2 hrs on an orbital shaker. All steps were performed at room temperature. After 4 washes with the kit's wash buffer, 100 uL per well horseradish peroxidase (HRP) conjugate working solution was added and the plate incubated for 1 hour on an orbital shaker. Then the plate was washed 4 times again and 100uL 3,3′,5,5′-Tetramethylbenzidine (TMB) solution was added per well then incubated for 30 minutes on an orbital shaker, followed by addition of 100 uL HRP stop solution.

J o u r n a l P r e -p r o o f

The plate was read at 450 nm absorbance using a microplate reader and the amount of citrullinated H3 quantified using the standards.

All statistical analyses were performed two-sided with p-values ≤0.05 deemed significant.

Ranges of significance were graphically annotated as follows: *, p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001. Due to the low number of animals included in our study, p values ≤0.1 have been indicated in the graphs. Analyses, unless otherwise noted, were performed with Prism version 8 (GraphPad).

2018) method was used to visualize the single cells in 2D embedding. We used Blueprint Encode database from SingleR (Aran et al., 2019) to classify cells into different cell subtypes

Differential gene expression between the clusters was assessed by MAST

2019) and others, including databases maintained by the NHP Reagent Resource (MassBiologics), have shown as being cross-reactive in RMs. A panel of the following mAbs was used for longitudinal T-cell phenotyping in PBMCs: anti-CCR7-BB700 (clone 3D12; 2.5 µL; cat. # 566437), anti-CD103-BV421 (clone Ber-ACT8

# 564117), anti-CD8-BUV496 (clone RPA-T8; 2.5 µL; cat. # 612942), anti-CD45-BUV563 (clone D058-1283; 2.5 µL; cat. # 741414), anti-CD49a-BUV661

# 302636), anti-PD-1-BV785 (clone EH12.2H7; 5 µL; cat. # 329930), anti-CD101-PE-Cy7 (clone BB27; 2.5 µL; cat. # 331014), anti-FoxP3-AF647 (clone 150D; 5 µL; cat. # 320014), and anti-CD4-APC-Cy7 (clone OKT4; 2.5 µL; cat. # 317418) all from Biolegend; anti-CD38-FITC (clone AT1anti-CXCR5-PE (clone MU5UBEE; 5 µL; cat. # 12-9185-42), anti-GranzymeB-PE-TexasRed (clone GB11; 2.5 µL; cat. # GRB17), and anti-CD127-PE-Cy5 (clone eBioRDR5; 5 µL; cat. # 15-1278-42) all from Thermo Fisher (Figure S6). mAbs for chemokine receptors (i.e. CCR7) were incubate at 37°C for 15 min, and cells were fixed and permeabilized for 30 min at room temperature using a FoxP3 / Transcription Factor Staining Buffer Kit (Tonbo Biosciences; cat. # TNB-0607-KIT). A panel of the following mAbs was used for the longitudinal phenotyping of innate immune cells in whole blood (500 µL), as described in

RPA-T8; 2.5 µL; cat. # 612942), anti-CD45-BUV563 (clone D058-1283; 2.5 µL; cat. # 741414), anti-CCR2-BUV661 (clone LS132.1D9; 2.5 µL; cat. # 750472), anti-CD16-BUV737 (clone 3G8; 2.5 µL; cat. # 564434), anti-CD69-BUV805 (clone FN50; 2.5 µL; cat. # 748763), and Fixable Viability Stain 700 (2 µL; cat. # 564997) all from BD Biosciences; anti-CD38-FITC (clone AT1; 2.5 µL; cat. # 60131FI) from STEMCELL Technologies; anti-CD161-BV421 (clone HP-3G10

5 µL; cat. # 301644), anti-CD11b-PE (clone ICRF44; 2.5 µL; cat

# GRB17) from Thermo Fisher; anti-CD66abce-PE-Vio770 (clone TET2; 1 µL; cat. # 130-119-849) from Miltenyi Biotec; and anti-CD27-PE-Cy5 (clone 1A4CD27; 2.5 µL; cat. # 6607107) and anti

at 37°C for 15 min, and cells were fixed and permeabilized at room temperature for 15 min with

For each sample a minimum of 1.2x10 5 stopping gate events (live CD3 + T-cells) were recorded except for RB in which a minimum of 5x10 4 stopping gate events were recorded. All samples were fixed with 4% paraformaldehyde and acquired within 24 hours of fixation

Live cells were gated followed by CD45 + cells. UMAP analysis (Uniform Manifold Approximation and Projection for Dimension Reduction) was performed in live CD45 + for unbiased evaluation of the distribution of the key markers. Projection of the density of cells expressing markers of interest were visualized/plotted on a 2-dimensional UMAP

PBMCs were thawed, resuspended in RPMI medium supplemented to contain a final concentration of 10% Fetal Bovine Serum (FBS) (Corning Life Sciences/Media Tech Inc

A) and 1x 2-Mercaptoethanol (GIBCO

Cells were then stimulated for J o u r n a l P r e -p r o o f detection of cytokine production by T cells as described before (Kasturi et al., 2020). Briefly, 2 x 10 6 cells were cultured in 200µL final volume in 5mL polypropylene tubes

A) in the presence of anti-CD28 (1µg/mL) and anti-CD49d (1µg/mL) [BD Biosciences] and the following conditions; a) negative control with DMSO only, b) S peptide pool (Grifoni et al., 2020) and c) PMA

After stimulation, cells were washed and stained for cell surface antigens with two panels. Panel 1: anti-CD3 BUV395 (clone SP34-2; 2.5 µL; cat. # 564117), anti-CD8-BUV496 (clone RPA-T8; 2.5 µL; cat. # 612942), and Fixable Viability Stain 700 (2 µL; cat. # 564997) all from BD Bioscience; anti-CD4 APC/Cy7 (clone OKT4; 2.5 µL; cat. # 317418) from Biolegend; To detect intracellular expression of cytokines, mononuclear cells were fixed and permeabilized with a Cytofix/Cytoperm kit (BD Biosciences) and stained as follows

BV650 (clone MQ1-17H12; 5 µL; cat# 500334) and anti-IFNγ PE/Dazzle 594 (clone B27

cat# 506530) both from Biolegend; anti-IL-17a Alexa Fluor 488 (clone eBio64DEC17; 5 µL; cat# 53-7179-42), anti-IL-22 APC (clone IL22JOP; 5 µL; cat# 17-7222-82), and anti-TNFα PE-Cyanine7 (clone Mab11; 0.5 µL; cat# 25-7349-82) all from Thermo Fisher Scientific

Panel 2: anti-IL-2 Alexa Fluor 488 (clone MQ1-17H12; 3 µL; cat# 500314), anti-CD8a PerCP Cy5.5 (clone RPA-T8; 3 µL; cat# 301032), anti-CD4 BV421 (clone OKT4; 2.5 µL; cat# 317434), and anti-IFNγ Alexa 647 (clone 4S.B3; 3 µL

from BD Biosciences; anti-IL-4 PE (clone 7A3-3; 5 µL; cat# 130-091-647) from Miltenyl Biotech

anti-TNFα PE-Cyanine7 (clone Mab11; 0.5 µL; cat# 25-7349-82), and Live Dead APC-Cy7 (1:1000; cat# 65086514) from Thermo Fisher Scientific. The frequency of SARS-CoV-2 specific CD4 + and CD8 + T-cells producing single or multiple cytokines was determined after background References Coronavirus Disease 2019 -Situation report number 148

Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage

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Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients

Baricitinib restrains the immune dysregulation in severe COVID-19 patients

Baricitinib therapy in COVID-19: A pilot study on safety and clinical impact

SARS-CoV-2 infection protects against rechallenge in rhesus macaques

Influenza A and methicillin-resistant Staphylococcus aureus co-infection in rhesus macaques -A model of severe pneumonia

COVID-19 severity correlates with airway epithelium-immune cell interactions identified by single-cell analysis

Characterisation of the transcriptome and proteome of SARS-CoV-2 reveals a cell passage induced in-frame deletion of the furin-like cleavage site from the spike glycoprotein

Functional genomics highlights differential induction of antiviral pathways in the lungs of SARS-CoV-infected macaques

STAR: ultrafast universal RNA-seq aligner

Nonhuman primate models of human viral infections

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CTLA-4 and PD-1 dual blockade induces SIV reactivation without control of rebound after antiretroviral therapy interruption

Clinical features of patients infected with 2019 novel coronavirus in Wuhan

3M-052, a synthetic TLR

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A dynamic COVID-19 immune signature includes associations with poor prognosis

Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19

Distinct RIG-I and MDA5 signaling by RNA viruses in innate immunity

Immune signaling by RIG-I-like receptors

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

CTLA-4(+)PD-1(-) Memory CD4(+) T Cells Critically Contribute to Viral Persistence in Antiretroviral Therapy-Suppressed, SIV-Infected Rhesus Macaques

DoubletFinder: doublet detection in single-cell RNA sequencing data using artificial nearest neighbors

Umap: Uniform manifold approximation and projection for dimension reduction

Interleukin-21 combined with ART reduces inflammation and viral reservoir in SIV-infected macaques

Respiratory disease in rhesus macaques inoculated with SARS-CoV-2

Type I IFN signaling blockade by a PASylated antagonist during chronic SIV infection suppresses specific inflammatory pathways but does not alter T cell activation or virus replication

Sooty mangabey genome sequence provides insight into AIDS resistance in a natural SIV host

Fingolimod retains cytolytic T cells and limits T follicular helper cell infection in lymphoid sites of SIV persistence

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Type I interferon responses in rhesus macaques prevent SIV infection and slow disease progression

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Elevated Calprotectin and Abnormal Myeloid Cell Subsets Discriminate Severe from Mild COVID-19

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Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients

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• Baricitinib preserves innate antiviral and SARS-CoV-2-specific T-cell responses In Brief: Using a rhesus macaque infection model it is shown that baricitinib treatment started early after infection effectively resolves inflammatory signatures in airway macrophages, with decreased lung pathology and neutrophil infiltration