Exosomes are associated with immune activation and oxidative stress in HIV patients Sukrutha Chettimada, David Lorenz, Vikas Misra & Dana Gabuzda # 218 Cancer Immunology & Virology, Dana-Farber Cancer Institute, Boston MA 02115 ABSTRACT RESULTS Exosome markers correlate positively with oxidative stress-related metabolites and Plasma exosomes small RNA-seq analysis negatively with levels of n-3 and n-6 polyunsaturated fatty acids a b Background: Exosomes are nanovesicles released from most cell types including immune cells. Prior studies suggest Table 1: Demographic and clinical characteristics of study cohort Plasma EV small RNA profile % mapped small RNA species % reads mapped to small RNAs c tRNA exosomes play a role in HIV pathogenesis, but little is known about exosome cargo in relation to immune responses and a b tRNA mature_miRNA HIV negative HIV positive Oxidative stress mature_miRNA 19% 15% tRNA oxidative stress. Here, we characterize protein and RNA cargo of circulating exosomes in HIV patients and examine their 64% (n=41) (n=45) 264 26% snoRNA relationship to immunological and oxidative stress markers. 340 snoRNA On ART (%) -- 100 147,164 185 10% Time on ART (months) α -- 32 (18-78) tryptophan piRNA Methods: Plasma exosomes were isolated from 86 subjects (n=45 HIV+, age 37-60 years, 73% male, on ART with suppressed methionine α piRNA 360,904 Age (years) 53 (49-57) 49 (44-53) EPA 1011 or low viral load [undetectable or <2500 HIV RNA copies/ml, respectively] and n=41 HIV- controls matched for age, gender, n3 DPA 6% miRNA Gender (%, male) 70.7 73.3 DHA snoRNA n6 DPA piRNA race). Exosomes were characterized by electron microscopy, nanoparticle tracking analysis (NTA), and immunoblotting for 4% cysteine s-sulfate 56% 0 50 100 150 200 Race White 39.0 42.2 cys-gly, oxidized PUFA exosome markers. The plasma metabolome was characterized by LC-MS/MS to examine inter-relationships between plasma cysteinylglycine small RNA species Black 58.5 42.2 heme kynurenine exosomes and metabolite changes related to immune activation and oxidative stress. Exosomal protein cargo was assessed Other 2.4 15.6 C- glycosyltryptophan methionine sulfone 4000 α e CD4 count (cells/ul) -- 349 (196-461) N1-methyladenosine by LC-MS/MS proteomics and RNA cargo by small RNA sequencing. d miRNA ) 3000 cysteine s Nadir CD4 (cells/ul) α -- 83.5 (29.25-242) cystine t 2000

n HIV-

Results: Plasma exosomes were more abundant in HIV-positive subjects compared to controls based on immunoblotting for HIV- u 1000 α HIV+ 800 CD8 count (cells/ul) -- 855 (716-1148) o c cys-gly, oxidized cysteine cystine n3 DPA n6 DPA EPA 102 HIV+ c

exosome markers and NTA (median 14 vs.10 X 10^11 particles/ml, respectively, p=.039). Plasma exosome markers correlated α d r =0.4098 p= 0.005 r =0.2896 p= 0.024 r =0.3133 p= 0.040 r =-0.2627 p= 0.044 r =-0.2918 p= 0.024 r =-0.4224 p= 0.0009 ) 2.0 2.0 2.0 2.0 2.0 2.0 (38.6%)

0.33 (0.19-0.54) y d

Ratio CD4/CD8 -- t i 96 s

66 e 1.8 1.8 1.8 1.8 1.8 1.8 n n z α e positively with oxidative stress markers (cystine, oxidized cys-gly, p<0.05) and inversely with PUFA (DHA, EPA, DPA, p<0.05). i (25%) i

Plasma HIV Viral Load (copies/ml) -- 82 (40-710) n t t e (36.4%) 600 l i 1.6 1.6 1.6 1.6 1.6 1.6 o r d a p γ e z

9 1.4 1.4 1.4 1.4 1.4 1.4 Untargeted proteomics detected markers of exosomes (CD9, CD63, CD81), immune activation and inflammation (CD14, CRP, viral load <400 copies (%) -- 62.2 l i m a r C D m 1.2 1.2 1.2 1.2 1.2 1.2 o HCV seropositive -- 35.6 α o r HLA-A, HLA-B, CSF1R, LILRB1), and oxidative stress (CAT, PRDX1, PRDX2, TXN, SEPP1) in plasma exosomes. Small RNA-seq ( n 400

Median (Interquartile range) 1.0 1.0 1.0 1.0 1.0 1.0 n

piRNA ( -4 -2 0 2 4 -3 -2 -1 0 1 2 -4 -2 0 2 4 -2 0 2 4 -4 -2 0 2 4 6 Cocaine use (%) β 17.1 51.1 β Based on patient report -3 -2 -1 0 1 2 analysis of exosomal RNA cargo identified several classes of small RNAs, including microRNA (10%), snoRNA (8%), tRNA A γ r =0.3756 p= 0.031 r =0.4409 p= 0.001 r =0.3824 p= 0.033 r =-0.2515 p= 0.084 r =-0.2906 p= 0.045 r =-0.4016 p= 0.004

Viral load below limit of detection ) 2.0 2.0 2.0 2.0 2.0 2.0 N

β y

t HIV+ Smokers (%) 80.5 68.9 i HIV- s -- Not available R n 200 i (20%), and piRNA (60%). MiRNA target enrichment analysis suggested these exosome-associated miRNAs could have n i

e 181 t e

t 1.5 1.5 1.5 1.5 1.5 1.5 n i o m

(17.9%) r d p potential functional roles in pathways involved in HIV infection, Wnt and Notch signaling, inflammation, and stress responses. 375 455 z e 3 i l 6 1.0 1.0 1.0 1.0 1.0 1.0 a D (37.1%) m C (45%)

r 0 o n

( 8 6 p p p p p p p p p p p p p p p p p a p Conclusions: HIV-positive individuals on ART have higher abundance of plasma exosomes compared to HIV-negative 0.5 0.5 0.5 0.5 0.5 0.5 6 4 5 0 1 2 -5 -3 -5 - -5 -5 -5 -5 -5 -5 -5 -5 -3 -5 -3 -5 -5 2 -3 -4 -2 0 2 4 -3 -2 -1 0 1 2 -2 -1 0 1 2 -4 -2 0 2 4 -2 0 2 4 -4 -2 0 2 4 6 a a 9 1 i g a 3 f 5 a d 3 6 6 1 b a Characterization of circulating exosomes isolated from plasma samples -3 -1 6 8 6 2 -7 7 7 2 7 5 9 0 4 8 2 7 7 -3 2 cys-gly, oxidized (scaled intensity) cysteine (scaled intensity) cystine (scaled intensity) n3 DPA (scaled intensity) n6 DPA (scaled intensity) EPA (scaled intensity) 2 4 8 - t - - 4 t- 1 9 1 4 1 6 - 9 iR iR - 1 6 R e t t - e - - -3 - - - 4 t iR - controls, and this increase correlates with markers of oxidative stress. Exosome cargo includes proteins related to immune R - - i l le le R l R R R R R R - le R m m i R R m i i i i i i i R m i m i i m m m m m m m i m activation, inflammation and oxidative stress, and may have pro-inflammatory and redox effects during pathogenesis. Figure 3: (a) Heatmap shows unsupervised hierarchical clustering of metabolites (n=16) associated with oxidative stress, tryptophan m m m Transmission electron microscopy Nano-particle tracking analysis EV concentration Ctrl 1 2 3 4 miRNA Target Enrichment Analysis Exosomal small RNA cargo may also influence pathogenesis and stress responses. a b c d metabolism, and polyunsaturated fatty acid (PUFA) metabolism that distinguish HIV-positive from HIV-negative control subjects (FC>1.3, f 16 45 EV conc. Flotillin-1 p<0.05, FDR<0.10). (b) Metabolites associated with oxidative stress are increased, and the indicated PUFA are decreased in aviremic and 14 40 #

Sample particles/

viremic HIV-positive subjects versus controls (* = p<0.01, ** = p<0.001). Medians represented by horizontal bars, boxes span the IQR, and m 12 ] ml plasma i l whiskers extend to extreme data points within 1.5 times IQR. Outliers are plotted outside 1.5 times the IQR. P-values calculated by Welch’s t- 35 R

CD9 a N

v 10

test (p<0.05; n=26 HIV-negative, n=21 HIV-positive aviremic, n=16 HIV-positive viremic subjects). (c) Pearson correlation matrix r-values show A METHODS Donor 1 5.50E+10 P 30 [ s

8

positive correlation of exosome marker proteins (CD9 and CD63) with metabolites associated with oxidative stress, and negative correlation 0 i n Donor 2 5.46E+10 1 25 CD63 g • Cohort: Plasma samples were collected from 45 HIV+ subjects (age 37-60 years, 73% male, on ART with suppressed or low with n-3 and n-6 PUFA (p<0.05). (d) Correlation scatter plots are shown with correlation coefficients and p-values above each plot. n=36 HIV- 6 T o e l r Donor 3 3.12E+11 positive, 26 HIV-negative. EPA, eicosapentaenoate (20:5n3); DHA, docosahexaenoate (22:6n3); n3 DPA, docosapentaenoate (22:5n3); n6 DPA, - 20 viral load from NNTC and ALIVE), and 41 age/race/gender-matched healthy controls (BioreclamationIVT). HIV subjects 4 m CD81 docosapentaenoate (22:5n6) were further classified as aviremic with VL <400 copies/ml or viremic with low VL between 400-2500 HIV RNA copies/ml. Donor 4 2.60E+11 2 15 Figure 1: Exosomes were isolated from 250 μl plasma using ExoQuick reagent according to the manufacturer’s protocol. Exosome morphology Purification of exosome fraction by immunoaffinity purification 0 10 E E S S E N C Y E Y Y S S S S Y Y K Y Y Y K Y S Exosome isolation: Exosomes were isolated from plasma (0.4 ml) using ExoQuick reagent; exosome size and quality L R L A G _ A N A N A G M G G G G L E E L M M A A G H A R G I G G • M U C IO H 3 S IO M IO IN E IN N IN IN L IR L E E IN R IN A A C IN A S IN IN YC O LE TO Y T P EC TI W T O W T W L T L LI L L E O IN E T T K W W O L W W T W O K W E was examined by TEM (a, scale bar=100 nm; arrows indicate exosomes) and EV concentration was measured by NTA (b). EV concentrations C C C C L I H S H A H A S A A A C T K C S S U H H A O H C N D D EN _ E -A B T T LA O T L T Y A _ R O _ Y Y E T T W H TH N T W I TH E D D E_C U FA E F F O A S S A Y N S N N N N T E T T S S L A A ET N T _ ET F G U U 1 2 3 4 5 Pre-IAP exosome fraction Post-IAP exosomes F G N _ IF N P P A Y P R A IG _ IG G IG IG _ P Y _ _ _ R P P G A A Y A F A O B B _ _ L I N A E P N L _ P S E S SI S S + E C + E E E _ _ N SI P P B P N A P I _ _ _LI IV M IV _ _ _T _ H F_ A S O _ _ N _ _ _ _ 8 R _ 4 N N T T ______R _ B E E assessed by NTA, TEM, and immunoblotting exosome fraction for exosome markers (CD9, CD63, CD81, and HSP70). from 4 plasma donors are shown in table (c). Exosome marker proteins were identified by immunoblotting (d, 15 µl exosome fraction) against V H V IV F E R S H M A U 2 F R 1 D _ Y D U U N A G T G G G G Y T G _ L L I _H O _ I D O T E P A - S C - C R C I M N N N N N E _ N E IC IC H E R F H H N _ N _ R S L M M N C T N _ G _ M M _ W LI N LI LI IN LI H E LI L S S F O _ A N IV A T O F M I - I E IN O E M Y M _ W L A _ N IC E E H _ _ F _ H N S H N M I K M K IV L T IV IM I B A A A _ A A A S A A S V V Figure 4: Left panel shows _T S S O S IO _ R _ P I A _ U U A A _ _ _ G T N D N N N N E R N E _ _ Flotillin-1, CD9, CD63, and CD81 in control (PBS) versus exosome fractions from 4 donors (HIV-, lanes 1-2; HIV+, lanes 3-4 ). F IN N _ A T A A _ _ G E E G E A M A N E G - R G G IG G IG H B G V D K E E F A T M T E A _ T L _ L N N N I IV N N SI N SI S I S _ SI _ E R _O T IO S _ D R L_ R V T N A ER D ER _ IG M _ _ T I IF A _ A _ _ S _ D M _ D V O T A F A I R N T N T IN S A IN G P L C T _ T T H E E 1 E I O Metabolomic profiling: Plasma metabolomic profiling was performed by Metabolon (Durham, NC) using UHLC/MS2/MS, N R C H O A A A C T A O N A _ _ L _ N A A IO H N N C T M C T R W • CD9 immunoblotting for exosome markers O P A P _ R C IR A C R I IN _ IN 4 F I N B N C T IA A A E T I _ R G O IO D E 5 G R N G L D T W I D T O R E E I V B I IO F _ N L I N A A IG W O _W O D R C _ E IP E E T TO D B X B R 3 LI T O LI N S L N E O N R L T A C _ O E - _ R G N A M S IN I_ C C IN L E D T IN A N P A I _ C - S R G (CD9, HSP70, CD81), and albumin in S U _ F E IN K N O _ N _S IN I H A H L N N T F T U IG I F IG E _ N C I_ T O optimized for the detection of acidic or basic metabolites, and GC/MS. Compounds were identified by automated A O S E A E S T O S N O T A G R B O _ I L _ A _ _ IN O N O LG L - T I H E D R R IV N R K I A N C S Plasma exosomes and exosome markers CD9, CD63, and HSP70 are elevated in R IV E E C T O C O T C O N _ plasma (lane 1), albumin depleted- L T M T T C I T T C N G A A A F- N A T Y A R HSP70 R G I I _ C C _ O T comparison of chromatographic and mass spectra properties in samples to metabolomic library entries of purified I E V K U IN N V N P D IL F_ _ A IN N plasma (lane 2), exosome fraction (lane EF M _ E _O _ 6 S viremic HIV-positive subjects on ART compared to controls T _N D F E R 1 N A R O - R P standards. Data analysis was performed using R. 3), pure exosomes from IAP (lane 4), and P IV _A T EX H B FK CD81 IgG control (lane 5). Right panel shows N 500 500 b 150 Proteomic analysis: Plasma exosome fraction was prepared for proteomic analysis by performing three rounds of a p=0.039 p=0.012 ) Figure 5: Small RNA was isolated from exosome fractions of plasma from 12 subjects (6 HIV+ and 6 HIV-). (a) BioAnalyzer histogram of a

• ) l

m TEM image of exosomes in exosome n

n 140 m o

400 400 ( / i representative exosome-small RNA sample is shown. (b) Percentage of each small RNA species in all mapped RNA (left), Percentage of

t

abundant plasma protein depletion using Proteome Purify 12 and Albusorb, followed by exosome immunoprecipitation. s fraction (left) and after exosome IAP e a e z

r 130 l i t mapped reads per small RNA (right). (c) Abundance of each small RNA species mapped in HIV- versus HIV+ groups. (d) Venn diagram

c 300 300 s

i Albumin n

(right). t e

Untargeted LC/MS/MS was performed on an ABSciex 4800Plus MALDI-TOF/ TOF mass spectrometer. Peptide mapping was r V 120 c

a showing unique and common miRNAs (top) and piRNAs (bottom) in HIV- versus HIV+ samples. (e) Abundance of top 21 miRNAs in HIV- E

n

p 200 200

n o 110 0 a performed using Protein Pilot 4.5b. Gene ontology mapping used PANTHER and Biobase TRANSFAC tools. c versus HIV+ groups. (f) miRNA target enrichment analysis showing functional annotation summary. Functional annotation was i

1 d + V 100 100 100 e E E performed on target genes of highly abundant miRNAs in plasma exosomes using the miRSystem tool ( m • RNA-seq: Exosome fractions were incubated with RNAse A to remove extra-exosomal RNA, and treated with RNAse 0 0 90 (http://mirsystem.cgm.ntu.edu.tw). Blue bars indicate p value for each annotation term (left y-axis) and green dots indicate number of HIV neg HIV pos HIV neg HIV pos HIV pos HIV neg HIV pos HIV pos inhibitor prior to isolation of small RNA (miRNeasy kit). RNA quality was assessed by Agilent Bioanalyzer. Small RNA Aviremic Viremic Aviremic Viremic Table 2: Biological classification based on gene ontology annotation of proteins miRNAs in each term (right y-axis). libraries were prepared (NEB smRNA kit) and libraries sequenced on NextSeq SR75. Small RNA (micro-RNA, piRNA, c CD9 CD63 HSP70 2.0 p<0.001 2.0 p=0.005 2.0 p=0.02 identified by mass spectrometry analysis of immunoaffinity-purified plasma exosomes y t

snoRNA, tRNA) was characterized using a customized version of the exceRpt small RNA pipeline. i 1.8

n s SUMMARY AND CONCLUSIONS 1.8 e t 1.6 1.5

n Biological classification HIV-negative (n=3) HIV-positive (n=4)

Experimental workflow i

d 1.6 1.4 e z

i immune ADAM33, AZGP1, BPIFA1, BPIFB1, BTN2A2, CAMP, CD4, CSF1R, ADAM33, BPIFB1, BTN2A2, CAMP, CD14, COLEC10, CPN1, • HIV-positive individuals on ART have higher abundance of plasma exosomes and exosome markers (CD9, CD63, l 1.2 1.0 Plasma Plasma Metabolomics a 1.4 m activation/inflammation CST6, CXCL16, DDR1, DMBT1, ENO1, FERMT3, LILRB1, LILRB2, CRP, CSF1R, DDR1, ENO1, FERMT3, HLA-A, HLA-B, ITGB1, and HSP70) compared to healthy controls. r 1.0 HIV+ (n=45), HIV- (n=41) UHLC/MS2/MS, GC/MS o

N LYZ, PLTP, TFRC ICAM2, LILRB1, PLTP, TFRC 1.2 0.8 0.5 HIV neg HIV pos HIV neg HIV pos HIV neg HIV pos transmembrane signaling CD4, EFNA4, LRP8, NOTCH4, PTRF, TFRC EFNA4, ITGA6, LRP8, NOTCH4, TFRC • Elevated exosome markers correlate positively with oxidative stress metabolites and negatively with levels of n-3 and n-6 polyunsaturated fatty acids. p=0.019 p=0.038 extracellular ANXA2, APMAP, AZGP1, BPIFB1, CAMP, CAT, CD9, CD63, ADAM10, APMAP, ARF1, BPIFB1, CAMP, CDH1, CDC42, 2.0 p=0.006 2.0 2.0 y

Exosomes Isolation t i p<0.001 p=0.015 vesicles/exosomes CD81, CDH1, ENO1, FERMT3, FLNA, GAPDH, HSPA5, LAMP1, CRTAC1, ENO1, FERMT3, GAPDH, GPLD1, LAMP1, MYH9, s 1.8 ExoQuick/ Ultracentrifugation n 1.8 • Proteomic analysis of plasma exosomes reveals proteins associated with extracellular vesicles, inflammation, e LDHA, MYH9, PFN1, PKM, PRDX1, PRDX2, PXDN, RAP1A, PCYOX1, PKM, RAB1A, RAC1, RAP1A, SDCBP, SPTAN1, t

n 1.6 1.5 i immune activation, oxidative stress, and stress responses. SDCBP, TXN, UBA52, YWHAB, ZG16B STOM, TLN1, UBA52 d 1.6

e 1.4 z

l i stress response CAT, CDH1, ENO1, GAPDH, HSPA5, HSPA1L, PRDX1, PRDX2, ADAM10, BMP1, CDH1, ENO1, GAPDH, MAP3K11, RAC1, a 1.2 1.0 1.4 m • Exosomal small RNA sequencing generated an average of 20 million reads per sample, mapping to miRNA, piRNA, r TXN, TYMP, WARS SEPP1 Exosomes QC o 1.0

N snoRNA, and tRNA. miRNA was the most abundant plasma exosome small RNA across both HIV and control TEM/NTA/SDS-PAGE 1.2 0.8 0.5 oxidative stress CAT, ENO1, GAPDH, PRDX1, PRDX2, PXDN, TPM1, TXN, WARS CRP, ENO1, GAPDH, GPX3, ITGB1, RAC1, SLC25A33, HIV neg HIV pos HIV pos groups, while snoRNA was the least abundant. Exosome-associated miRNAs may have potential functional roles in HIV neg HIV pos HIV pos HIV neg HIV pos HIV pos SEPP1 Aviremic Viremic Aviremic Viremic Aviremic Viremic pathways involved in HIV infection, Wnt and Notch signaling, inflammation, and stress responses. fatty acid/ lipid AZGP1, CD36, CETP, DPEP3, FABP5, HGFAC, LRCOL1, PKM, ACOX3, ADIPOQ, ANGPTL3, CD36, CETP, DPEP3, GPLD1, Figure 2: Beeswarm plots show EV concentration (a), and median size (b), measured by NTA in aviremic (n=29) and viremic (n=17) HIV-positive metabolism PLTP HADHA, HGFAC, LRCOL1, PCSK9, PKM, PLTP, SAR1A versus HIV-negative subjects (n=40). Horizontal bars represent means and error bars represent SD. Proteins (25 μg protein per lane) were • Circulating exosomes in ART-treated HIV+ subjects carry protein cargo related to inflammation, immune platelets CD36, FERMT3, ITGA2B, ITGB3, MMRN1 CD36, FERMT3, F11R, ITGA2B, ITGB3, PF4V1 Exosomes - Proteomics Exosomes - small RNA Isolation separated by SDS-PAGE and immunoblotted with exosome marker antibodies against CD9, CD63, and HSP70 (c). Bands in each lane were activation, and oxidative stress, and may have pro-inflammatory and redox effects during HIV pathogenesis. Abundant proteins depletion* QC- Agilent Bioanalyzer normalized to corresponding EV numbers. Box plots in upper panel show exosome marker protein levels in HIV-positive (n=37) versus HIV- Proteomic analysis of plasma exosomes: PANTHER and Biobase TRANSFAC tools were used for gene ontology (GO) mapping of proteins Exosomal small RNA cargo may also influence pathogenesis and stress responses. Immuno-affinity purification of exosomes Small library prep./QC Mass spectrometry, GO analysis Small RNA sequencing negative subjects (n=27). Box plots in lower panel show exosome marker protein levels in aviremic (n=21) and viremic (n=16) HIV-positive versus identified by mass spectrometry analysis of IAP-purified plasma exosomes from 3 HIV-negative and 4 HIV-positive subjects. GO groups were HIV-negative subjects (n=27). Medians are represented by horizontal bars, boxes span the interquartile range (IQR), and whiskers extend to assigned to the indicated biological functions. Individual proteins may be annotated to more than one category. Proteins identified by 2 or * α1-Acid Glycoprotein, α1-Antitrypsin, α2-Macroglobulin, Albumin, ApoA /B, Fibrinogen, Haptoglobin, IgA/G/M, Transferrin extreme data points within 1.5 times IQR. Outliers are plotted outside 1.5 times the IQR. p-values were calculated by Mann-Whitney U test. more unique peptides are shown in bold. This work was supported by National Institute on Drug Abuse (NIDA) grants R01 DA040391 and DA30985 to D.G Abbreviations: ART, Antiretroviral Therapy; VL, viral load; NNTC, National NeuroAIDS Tissue Consortium; ALIVE, AIDS Linked to the IntraVenous Experience; TEM, Transmission electron microscopy; NTA, Nanoparticle Tracking Analysis; MALDI-TOF, matrix assisted laser desorption ionization-time of flight