Dr. Laura Miller - Comparative analysis of signature genes in PRRSV-infected porcine monocyte-derived dendritic cells at differential activation statuses
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Comparative analysis of signature genes in PRRSV-infected porcine monocyte-derived dendritic cells at differential activation statuses - Dr. Laura Miller, Virus and Prion Diseases of Livestock Research Unit, National Animal Disease Center, USDA-ARS, from the 2015 North American PRRS Symposium, December 4 - 5, 2015, Chicago, IL, USA. More presentations at http://www.swinecast.com/2015-north-american-prrs-symposium
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Dr. Laura Miller - Comparative analysis of signature genes in PRRSV-infected porcine monocyte-derived dendritic cells at differential activation statuses
- 1. Comparative analysis of signature genes in PRRSV- infected porcine monocyte-derived dendritic cells at differential activation statuses. Laura Miller, USDA-ARS (Co-PD) Yongming Sang, KSU (PD) Raymond R. R. Rowland, KSU (Co-PD) Frank Blecha, KSU (Co-PD) College of Veterinary Medicine Kansas State University, Manhattan, KS 66506, USA
- 2. Activation statuses of monocytic cells including monocytes, macrophages and dendritic cells (DCs) are critically important for antiviral immunity. In particular, some devastating viruses, including porcine reproductive and respiratory syndrome virus (PRRSV), are capable of directly infecting these cells to subvert host immunity. Introduction
- 3. Table 1. Monocytotropic viruses and pathogenic effect of macrophage manipulation/infection Virus* [genome, family] Macrophage-related primary infection cells/sites Effect of manipulation/infection in monocytes, MΦs and DCs DENV [(+)ssRNA, Flaviviridae] Monocytes, MΦs and DCs in multiple tissues of IFN-αβγR KO mice MΦ-depletion: Tenfold increase in systemic viral titer, and massive infiltration of monocytes RSV [(-)ssRNA, Paramyxoviridae] Blood monocytes, DCs, lung epithelial cells and MΦs in mice/humans MΦ-depletion: Abolished local inflammatory cytokine peak at 1 dpi, and enhanced viral load in the lung at 4 dpi HIV1 [(+)ssRNA, Retroviridae] Macrophages and T cells in humans Deficiency of CCR5, a co-receptor that mediates HIV macrophage-tropism, showed resistance to HIV-1infection WNV [(+)ssRNA, Flaviviridae] Murine keratinocytes and skin-resident DCs, and probable peripheral MΦs and DCs mediating neuroinvasion MΦ-depletion: Higher and extended viremia, and accelerated encephalitis and death. Inhibition of NOS activity of infiltrating MΦs relieved encephalitis and prolonged survival SARS-Cov [(+)ssRNA, Coronaviridae] Human respiratory epithelial cells, and antibody-enhanced infection of macrophages and immune cells Depletion of alveolar MΦs 1-2 day before infection, (but not at 2 dpi), prevented lethal disease, and enhanced viral clearance IAV [Segmented (-)RNA, Orthomyxoviridae] Airway and lung epithelial cells, DCs, and MΦs of mice/humans/pigs MΦ-depletion: Strain-dependent exacerbation of viral replication, increased airway inflammation and viral pneumonia CSFV [(+)ssRNA, Flaviviridae] Porcine blood monocytes/macrophages Viral infection stimulated arginase-1 (ARG-1) but suppressed nitric oxide synthase (iNOS) expression, i.e., induced M1-M2 repolarization PrV [dsRNA, Herpesviridae] Porcine lung epithelial cells and MΦs and spread via infected blood monocytes Acute IFN-α response is important in diminishing the spread of PrV in the connective tissue but not in epithelial cells (IFN cell preferences) ASFV [dsRNA, Asfarviridae] Primarily and persistently infected tissue monocytes/ MΦs and fibroblasts in multiple tissues Massive M1 polarization served as a modulator of the viral pathogenesis including pulmonary edema, hemorrhage, and lymphoid depletion that characterize the disease PCV2 [ssDNA, Circoviridae] Monocyte/MΦ lineage cells, including alveolar MΦs, are the major target cells Acute infection reduced alveolar MΦs phagocytosis and microbicidal capability; and persistence increased inflammatory and pro-apoptotic responses, which led to lymphopenia and immunosuppression FMDV [(+)ssRNA, Picornaviridae] Early infection of porcine T and B cells caused viremia; immunocomplex promoted productive infection and killing of mDCs Increase IL-10 production in infected DCs, loss of pDC cell function coincides with lymphopenia in FMDV-infected pigs; macrophage depletion in vaccinated mice severely decreased vaccine protection PRRSV [(+)ssRNA, Arteriviridae] Tissue macrophages, monocytes and mDCs especially those in reproductive and respiratory tracts. Massive cell death of infected monocytic cells; increase of IL-10 and reduction of phagocytic, microbicidal, pro-inflammatory, and antigen-presentation activity in MΦs and DCs. Pathogenicity-related suppression of IFN-α production in pDCs. Sang Y, Miller LC, Blecha F. Macrophage Polarization in Virus-Host Interactions. J Clin Cell Immunol. 2015 Apr;6(2). pii: 311.
- 4. Objectives Our long-term goal is two-fold: 1) to integrate activation status with antiviral responses in monocytic cells 2) to functionally modulate them for a prototypic cellular adjuvant/vaccine that is ideal for potentiating antiviral immunity.
- 5. Methods • To study how PRRSV infection alters cell activation, we have systematically characterized the activation status and determined, genome-wide, signature genes regulating the activation status in porcine monocytic innate immune cells with PRRSV pathogenicity in ex-vivo stimulated cells using our established RNA-seq procedure. • Porcine monocyte-derived dendritic cells (mDCs) were polarized with mediators (PBS, IFN-γ, IL-4, LPS, IL-10, IFN-α) for 30 hours, then mock-infected, or infected with PRRSV strain VR-2332, or highly pathogenic PRRSV strain HP-PRRSV rJXwn06, for 5 h. • Each sample represents a pooled RNA from four replicates.
- 6. Methods Comparisons were made within each treatment group of activation status (mediator vs. PBS control) and between treatment group for each mediator. CTRL Grp I: Polarization mediators PRRSV (moi: 0.1) 1 PBS - 2 IFNγ - 3 IL4 - 4 LPS - 5 IL10 - 6 IFNα - VR Grp II: Polarization mediators PRRSV (moi: 0.1) 1V PBS VR2332 2V IFNγ VR2332 3V IL4 VR2332 4V LPS VR2332 5V IL10 VR2332 6V IFNα VR2332 HP Grp III: Polarization mediators PRRSV (moi: 0.1) 1H PBS HP-JX 2H IFNγ HP-JX 3H IL4 HP-JX 4H LPS HP-JX 5H IL10 HP-JX 6H IFNα HP-JX Table 1. Sample organization table
- 7. Results and discussion Correlation of cell activation status with PRRSV pathogenicity in ex-vivo stimulated cells.
- 8. Results and discussion PCA by mediator PCA by virus Correlation of cell activation status with PRRSV pathogenicity in ex-vivo stimulated cells.
- 9. Results and discussion Visualization of the DESeq2 dispersion estimates. .
- 10. Results and discussion Heat map of the top 35 most variable genes in the dataset. mediators
- 12. Polarization mediators Control vs PBS VR2332 vs PBS HP-PRRSV vs PBS IFN-γ RNA ALDH POSTN ACT ACAN ACT RNA TNN COL CXCL COL CXCL SAA CXCL SAA UBD POSTN UBD IDO1 COL SAA IL-4 COL THBS1 RNA COL CYTB RNA ACT MMP RNaseP CXCL POSTN CXCL IL-17 SFRP2 CDH2 CDH2 CXCL IL17RB LPS COL TNN RNaseP ACT COL U splicesomal RNA RNA GJA1 RNA SAA IL1B SAA IDO1 SAA MMP IL1B CXCL IL1B IL-10 RNA DEFB133 RNA IFIT1 IL2RA RNaseP RNA S100A1 U splicesomal RNA MMP CELSR1 MMP SAA GTSE1 IL7 IL7 TTC38 MMP IFN-α RNA THBS1 RNA ACT CYTB RNaseP RNaseP IL1B U splicesomal RNA ISG12 ISG12 ISG12 TNF IRG6 XAF1 IFI IFIT1/IFIT2 IFIT1 CTRL Grp I: Polarization mediators PRRSV (moiI: 0.1) 1 PBS - 2 IFNg - 3 IL4 - 4 LPS - 5 IL10 - 6 IFNa - VR Grp II: 1V PBS VR2332 2V IFNg VR2332 3V IL4 VR2332 4V LPS VR2332 5V IL10 VR2332 6V IFNa VR2332 HP Grp III: 1H PBS HP-JX 2H IFNg HP-JX 3H IL4 HP-JX 4H LPS HP-JX 5H IL10 HP-JX 6H IFNa HP-JX 2 vs 1 3 vs 1 4 vs 1 5 vs 1 6 vs 1 2V vs 1V 3V vs 1V 4V vs 1V 5V vs 1V 6V vs 1V 2H vs 1H 3H vs 1H 4H vs 1H 5H vs 1H 6H vs 1H Results and discussion
- 13. DE Polarization mediators VR-2332 HP-PRRS é PBS RNA CXCL10 RNaseP RNA ACT ISG12 ê MORC3 AREG TNN U splicesomal RNA TNFSF10 CXCL2 é IFN-γ ETNPPL IRG6 CYP1A1 COL COL FAM111C ê POSTN RNA CCL11 U splicesomal RNA CAV2 RNaseP é IL-4 RNA RNA RNaseP RNaseP U spliceosomal RNA U splicesomal RNA ê POSTN POSTN IRG6 COL IFIT1/IFIT2 SFRP2 é LPS LAG3 CXCL10 MARCO IRG6 TRBV19 IFIT1/IFIT2/IFIT3 ê TGM2 COL1A2 MMP COL3A1 IL1A POSTN é IL-10 ACT RNA COL RNaseP COL RNA ê UBCH5B CCNL1 IL1A SEPINB2 CXCL2 CXCL2 é IFN-α COL1A2 CXCL10 COL1A2 IRG6 COL6A3 IFIT3/IFIT5/IFIT2 ê PMAIP1 WNT5A RNA AREG CXCL10 MMP 1V vs 1 2V vs 2 3V vs 3 4V vs 4 5V vs 5 6V vs 6 1H vs 1 2H vs 2 3H vs 3 4H vs 4 5H vs 5 6H vs 6 DE Polarization mediators VR2332 vs HP-PRRS PBS CXCL10 IRG6 IFIT1 COL3A1 RNA COL1A2 IFN-γ POSTN MXRA5 IRG6 RNA RNaseP U splicesomal RNA IL-4 CXCL10 IRG6 IFIT1/IFIT2/IFIT3 ACTA2 CAV1 COL3A1/CXCL2 LPS IRG6 CXCL10 IFIT1/IFIT2/IFIT3 COL1A2 COL3A1 SFRP2 IL-10 CXCL10 IRG6 IFIT1 COL3A1 ACTA2 COL1A2 IFN-α CXCL10 IRG6 IFIT3 COL1A2 COL3A1 COL5A2 1H vs 1V 2H vs 2V 3H vs 3V 4H vs 4V 5H vs 5V 6H vs 6V Results and discussion
- 14. • Clustering of samples was consistent with virus strain and then by mediator. • Many of the genes showing the most variability were related to cellular structure and innate immune response. • The magnitude of differentially expressed gene profiles detected in HP-PRRSV rJXwn06 infected mDCs as compared to VR-2332 infected mDCs was consistent with the increased pathogenicity of the HP-PRRSV in vivo. Conclusions
- 15. Experiment I. Group N Treatment Dpi 7 Blood PBMCs, BALF Dpi 14 Blood PBMCs, BALF 1 6 Control – sham # # 2 6 Ing. MLV # # 3 6 VR-2332 # # Experiment II. Group N Treatment Dpi 7 Blood PBMCs, BALF Dpi 14 Blood PBMCs, BALF 1 6 Control – sham # # 2 10 rJXwn06 # # Cytokine and signature gene phenotyping to correlate cell activation statuses with PRRSV pathogenicity. Blood –Whole-blood and PBMCs for isolation of monocytes, cDC and pDCs Broncheo-alveolar lug fluid (BALF) Correlate cell activation status with PRRSV pathogenicity in primary cells isolated from virus-infected pigs. Current/future work Real-time RT-PCR Comparisons: 1) treatments of control, vaccinated and infected; 2) pigs within a treatment; 3) groups of the monocytic cells; and 4) subsets of MФs and DCs. Flow (FSC) PBMC Panel #1 CD4+ CD8+ CD172a+ Panel #2 CD80+ MHCIIHi MHCIIlo Panel #3 CD16+ CD163+ MHCIIHi MHCIIlo Panel #4 CD163+ SDOW17+ BALF Panel #2 CD80+ MHCIIHi MHCIIlo Panel #3 CD16+ CD163+ MHCIIHi MHCIIlo
- 16. Correlate cell activation status with PRRSV pathogenicity in primary cells isolated from virus-infected pigs. Current/future work
- 17. Acknowledgements Technicians: Sarah Anderson USDA ARS NADC Sequencing: ISU DNA facility Bioinformatics: Dr Darrell Bayles, USDA ARS NADC Animal study: Dr Vikas Kulshrestha, Dr Albert Van Geelen, Dr Alexa Buckley, Dr Nestor Montiel, Dr Kelly Lager, Sarah Anderson, NADC animal caretakers Flow cytometry: Sam Humphrey USDA ARS NADC Flow cytometry analyses: Dr Nestor Montiel, Sam Humphrey USDA ARS NADC Funding: This work was supported by USDA NIFA AFRI grant 2013-67015-21236
- 18. CTRL Fluorescent ToFA (2.5 μg/ml) ToFA (5 μg/ml) mDCs infected with DsRed-PRRSV for 48 h Merged ToFA (5-(Tetradecyloxy)-2-furoic acid), a competitive inhibitor of acetyl-CoA carboxylase (ACC) FL1 (PRRSV) 99.42 0.58 100 101 102 103 104 MФsMARC-145 mDCs 6.09 93.91 83.16 16.84 98.52 1.48 43.26 56.74 62.55 37.45 74.51 25.49 86.97 13.02 98.96 1.04 100 101 102 103 104 100 101 102 103 104 FSC-H 1000 800 600 400 200 0 1000 800 600 400 200 0 1000 800 600 400 200 0 MockPRRSVToFA+PRRSV Sang et al. Animal Health Review 2011, 12:149-67. PLoS One. 2014, 9:e87613. and J. Virol. 2014, Oct;88(19):11395-410. Antiviral regulation via AMPK pathway and lipid metabolism Develop a prototypic adjuvant/vaccine system based on functional modulation of activation statuses in porcine monocytic innate immune cells
- 19. ORF1a ORF1b ORF2-7 AflII MluI IFN ORF6X Histidine tag 12-AA protease cleavage site Vector CMV promoter Viral RNA cDNA Sang et al., Viruses. 2012, 4:102-16; J. Virol. 2014, Oct;88(19):11395-410. Anti-PRRSV N Anti-IFNα Merged Virus-replication competent IFN expression: acts against viral suppression of IFN production in situ Validation for Therapeutic Designs
- 20. Sang et al. Animal Health Review 2011, 12:149-67, and J. Virol. 2014, 88(19):11395-410. Brockmeier et al., Clin Vaccine Immunol. 2012, 19:508-14. 3. Synthetic/natural lipids 2. Metabolic mediators, such as ToFA 1. Virus-replication competent IFN expression Regulatory lipid nano-particle (LNP) Validation for Therapeutic Designs
- 21. Cytokine and signature gene phenotyping to correlate cell activation statuses with PRRSV pathogenicity. Blood –Whole-blood and PBMCs for isolation of monocytes, cDC and pDCs (LM) BALF –LM Samples prepped for flow cytometry/sorting RT-PCR (RNAlater) and Searchlight (cytokine buffer.
- 22. The 2015 North American PRRS Symposium wishes to thank the following sponsors for their generous support:
Notas do Editor
- It is in the first year of this 4-yr project, in which we intend to study the antiviral regulation and virus-cell interaction in porcine monocytic cells.
- Activation statuses of monocytic cells including monocytes, macrophages (MΦs) and dendritic cells (DCs) are critically important for antiviral immunity. Unfortunately, the activation status of porcine monocytic cells or how cell activation status functionally interacts with antiviral immunity remains largely unknown. This is a significant omission because many economically important porcine viruses are monocytotropic including our focus, porcine reproductive and respiratory syndrome virus (PRRSV). Understanding the relationships of activation status and antiviral states not only extends the activation paradigm of these cells but also integrates innate immune responses with several aspects of inflammation, tissue repair and overall antimicrobial activity. This is important because most PRRSV infections are syndromes complicated with co-infection from pathogens of other phyla. Therefore, integration of conventional activation status and antiviral states provides a framework for potentiation of overall immune response to PRRS disease. PRRSV is ideal for deciphering how monocytic cell activation statuses interact with antiviral immunity, because it directly infects subsets of MΦs and DCs and subverts overall immune responses.
- Activation statuses of monocytic cells including monocytes, macrophages and dendritic cells (DCs) are critically important for antiviral immunity. In particular, some devastating viruses, including porcine reproductive and respiratory syndrome virus (PRRSV), are capable of directly infecting these cells to subvert host immunity.
- The overall similarity between samples was assessed in heat map plots calculating both the Euclidean distance (Fig. 1A) and Poisson distance (Fig. 1B) between regularized log transformed data to allow equal contribution from all genes. Principal component analysis (PCA) estimates were used to emphasize variations in comparisons (Fig. 1C&D). Poisson distance using the original counts and the technique of multidimensional scaling was used to simplify the clustering.
- Principal component analysis (PCA) estimates were used to emphasize variations in comparisons (Fig. 1C&D). Poisson distance using the original counts and the technique of multidimensional scaling was used to simplify the clustering.
- Whether a gene effect is called significant depends not only on its log fold change in expression, but also on its within-group variability, which DESeq2 quantifies as the dispersion. For strongly expressed genes, the dispersion can be understood as a squared coefficient of variation: a dispersion value of 0.01 means that the gene's expression tends to differ by typically √0.01 =10% between samples of the same treatment group. For weak genes, the Poisson noise is an additional source of noise. The black points are the dispersion estimates for each gene as obtained by considering the information from each gene separately. Unless one has many samples, these values fluctuate strongly around their true values. Therefore, we fit the red trend line, which shows the dispersions' dependence on the mean, and then shrink each gene's estimate towards the red line to obtain the final estimates (blue points) that are then used in the hypothesis test. The blue circles above the main "cloud" of points are genes which have high gene-wise dispersion estimates which are labeled as dispersion outliers. These estimates are therefore not shrunk toward the fitted trend line.
- In these plots, we have not tried to do any comparison of differential expression; rather, we simple look at each gene across all treatments and ask which 35 genes show the most variability. We then create a heat map using those 35 genes. The logic is that the most variable genes are most likely to be the genes that will provide the most resolution for clustering the samples. The bar along the top of the plot highlights the location of the three virus types. The black points are the dispersion estimates for each gene as obtained by considering the information from each gene separately. Unless one has many samples, these values fluctuate strongly around their true values. Therefore, we fit the red trend line, which shows the dispersions' dependence on the mean, and then shrink each gene's estimate towards the red line to obtain the final estimates (blue points) that are then used in the hypothesis test. The blue circles above the main "cloud" of points are genes which have high gene-wise dispersion estimates which are labeled as dispersion outliers. These estimates are therefore not shrunk toward the fitted trend line.
- In these plots, we have not tried to do any comparison of differential expression; rather, we simple look at each gene across all treatments and ask which 35 genes show the most variability. We then create a heat map using those 35 genes. The logic is that the most variable genes are most likely to be the genes that will provide the most resolution for clustering the samples. The bar along the top of the plot highlights the location of the three virus types. The black points are the dispersion estimates for each gene as obtained by considering the information from each gene separately. Unless one has many samples, these values fluctuate strongly around their true values. Therefore, we fit the red trend line, which shows the dispersions' dependence on the mean, and then shrink each gene's estimate towards the red line to obtain the final estimates (blue points) that are then used in the hypothesis test. The blue circles above the main "cloud" of points are genes which have high gene-wise dispersion estimates which are labeled as dispersion outliers. These estimates are therefore not shrunk toward the fitted trend line.
- Cell treatment: Porcine mDCs, polarized with mediators for 30 h, then mock-infected (control: 1-6), infected with VR2332 (1V-6V) or infected with HP-PRRSV (1H-6H, JX strain from Jishu) for 5 h. Each sample represents a pooled samples from four replicates. Comparison: Compare each activation status (2-6) to the PBS treatment within each control and infected groups
- Compare between infected with uninfected, and infected (V) with infected (HP), i.e.:
- We adopt a lipid nanoparticle to combine the antiviral regulatory role of some metabolic mediator and vaccine backbone. For example, we have developed procedure to incorporate ToFA, the lipid metabolism regulator, into a lipid nanoparticle, then the lipid nanoparticle will be used to encapsulate bioengineered vaccine backbone, as I showed you previously, we have validate the antiviral effect of most of these vaccine component in cells. My collaborator, Dr. Laura Miller in USDA, has validated anti-PRRSV effect of the virus expressed IFN, they showed that only timely an effective IFN alone could stimulate effective anti-PRRSV activity. We believe, the system of IFN-expressed PRRSV system, will provide better immune potentiation through introducing both IFN and viral antigens to mimic wide-type PRRSV infection timely and in situ. With this, I will deliver some messages of my research primarily presented so far. (Read out) In the third part, I will brief our validation of potential antiviral approaches in both cells and animals. To potentiate antiviral activity through modulation of lipid metabolism, we have tested dozens of agonists or antagonists in lipid metabolism, one competitive inhibitorof acetyl-CoA carboxylase (ACC) , ToFA, was among several effective drugs to potentiate anti-PRRSV activity in our cell models. At the dose without causing visible cell toxicity, ToFA could suppress nearing 90% PRRSV infection in MARC-145 cell line, and nearing 50% in both porcine macrophages and dendritic cells. And these are the images to show ToFA’s dose dependence in dendritic cells, again ToFA at 5 ug/ml significantly suppressed PRRSV infection.
- As you know, suppression of IFN production is a major mechanism for many viruses to establish infection in animals. To reverse PRRSV’s effect on IFN suppression, we bioengineered PRRSV to express IFN. To achieve this, we manipulated a cDNA infectious clone of a PRRSV, and it is not problem to fuse a IFN gene into the PRRSV’s expression cassette. The problem is to coordinate the IFN expression with virus replication, ie. PRRSV replication-competent IFN expression, because IFN expression is inhibitive to PRRSV replication, but without sufficient PRRSV replication, we can not produce enough IFN, in addition for vaccine design, it is required for virus to replicate to some extent to induce antiviral immunity. To solve this problem, we introduced a leader sequence in front of the IFN coding regions, this leader includes a cleavage site for a macrophage-specific protease (cathepsin), therefore, we can produce enough engineered virus in the MARC-145 cells. As you see, IFN peptide was successfully expressed and cleaved from the leader sequence by a protease treatment, and the overexpression of leader-linked IFN was co-localized in MARC-cells. Significantly, when we infected porcine macrophages with the bioengineered virus and co-infected GFP-labeled PRRSV virus, the IFN-expression virus with expression of full-length of IFNa6 dramatically suppress co-infected PRRSV virus, and this suppression is dependent on the release of IFN peptides by the macrophage protease, and appropriate compartmentalization is also critical for expressed IFN to exert antiviral function, as shown that the virus expressing the leader-linked mature IFN have little effect to suppress PRRSV infection. Not only suppress co-infected PRRSV infection, the transfection of IFNA6-expressed virus also prevent the cells from PRRSV induced cell lysis for 96 h post PRRSV infection.
- We adopt a lipid nanoparticle to combine the antiviral regulatory role of some metabolic mediator and vaccine backbone. For example, we have developed procedure to incorporate ToFA, the lipid metabolism regulator, into a lipid nanoparticle, then the lipid nanoparticle will be used to encapsulate bioengineered vaccine backbone, as I showed you previously, we have validate the antiviral effect of most of these vaccine component in cells. My collaborator, Dr. Laura Miller in USDA, has validated anti-PRRSV effect of the virus expressed IFN, they showed that only timely an effective IFN alone could stimulate effective anti-PRRSV activity. We believe, the system of IFN-expressed PRRSV system, will provide better immune potentiation through introducing both IFN and viral antigens to mimic wide-type PRRSV infection timely and in situ. With this, I will deliver some messages of my research primarily presented so far. (Read out)
- Montanide Gel01 ST adjuvant enhances MLV efficacy ToFA (inhibitor of acetyl Co-A carboxylase, enzyme in lipid metabolism suppresses PRRSV infection