text:
Influence of hydrocarbon oil structure on adjuvanticity and autoimmunity

Mineral oils are extensively used in our daily life, in food, cosmetics, biomedicine, vaccines and in different industrial applications. However, exposure to these mineral oils has been associated with immune adjuvant effects and the development of autoimmune diseases. Here we investigate the structural impacts of the hydrocarbon oil molecules on their adjuvanticity and autoimmunity. First, we showed that hydrocarbon oil molecules with small atomic differences could result in experimental arthritis in DA rats differing in disease severity, incidence, weight change and serum levels of acute phase proteins. Injection of these hydrocarbon oils resulted in the activation, proliferation and elevated expression of Th1 and especially Th17 cytokines by the T cells, which correlate with the arthritogenicity of the T cells. Furthermore, the more arthritogenic hydrocarbon oils resulted in an increased production of autoantibodies against cartilage joint specific, triple-helical type II collagen epitopes. When injected together with ovalbumin, the more arthritogenic hydrocarbon oils resulted in an increased production of αβ T cell-dependent anti-ovalbumin antibodies. This study shows the arthritogenicity of hydrocarbon oils is associated with their adjuvant properties with implications to not only arthritis research but also other diseases and medical applications such as vaccines in which oil adjuvants are involved.

Mineral oils are often used in food, cosmetics, biomedicine and different industrial applications. However, such oils also have adjuvant properties and have been included in vaccines formulation to enhance immune responses. Importantly, intake of hydrocarbon oils, depending on the amount and route, can result in severe inflammatory reactions such as skin necrosis, loss of hand function, lipogranulomas in lung, lymph nodes and liver 1,2 . Exposure to mineral oils has been associated with an increased risk of developing rheumatoid arthritis (RA) and possibly lupus 3,4 , and intradermal administration of mineral oils can induce arthritis in susceptible rat strains, hereafter referred to as 'adjuvant-induced arthritis' 5,6 . In other arthritis models, different antigens are injected together with the oil adjuvants, such as Freund's incomplete adjuvant (IFA) and Freund's complete adjuvant (CFA). These arthritis models include cartilage-restricted antigen-induced arthritis, which use type II collagen (CII), type XI collagen (CXI) or cartilage oligomeric matrix protein (COMP) as the antigen; and mycobacterial adjuvant-induced arthritis (Mbt-AIA), which induces disease by injection of heat-killed mycobacteria emulsified in IFA. These arthritis models mimic different aspects of RA and have been very useful for identifying arthritis-regulating loci and genes, many of which could not be detected in the past human genome-wide association studies due to various limitations 7,8 . Most arthritis loci regulate multiple arthritis models 9 , while some loci regulate only certain types of arthritis models [10][11][12] . A better understanding of these disease models may thus give invaluable information on the regulatory mechanisms of these disease genes.
For adjuvant-induced arthritis models, different immunostimulatory agents have been described to induce polyarthritis in arthritis-susceptible rat strains, such as DA. These agents include IFA, which is an undefined mixture of oil molecules (oil-induced arthritis, OIA), and also structurally defined hydrocarbon molecules such as pristane (pristane-induced arthritis, PIA), hexadecane (hexadecane-induced arthritis, HXIA) and squalene (squalene-induced arthritis, SIA) 5,6,11,13,14 . These show that non-specific stimulation of the immune system with oil adjuvants alone can elicit joint-specific inflammation. Similar to RA in humans, the susceptibility to these arthritis models are regulated by genes both within and outside the major histocompatibility complex (MHC) 10,11,[13][14][15][16] and are T cell dependent 17, 18 . The exact pathogenic mechanism of these adjuvants remains unclear, although there have been different suggestions [19][20][21][22][23] .
In this study, we compared the elicited immune response at several time points after the injection of different oil adjuvants, including the more widely used ones such as pristane and squalene. With slight structural variation in these oil molecules, we could show that they differed significantly in not only the progression of the induced disease but already in the early phase with different extents of cell expansion, activation and proliferation and also expression of proinflammatory cytokines which correlates with the arthritogenicity of the adjuvant-primed CD4 + T cells. At the peak of arthritis, autoantibody response could be detected, with a stronger response developed in rats injected with the more arthritogenic adjuvants. In addition, we showed that these hydrocarbon adjuvants vary in their stimulatory effects on antigen-specific recall response and antibody production.

Results
Variation in arthritogenicity of different adjuvants. We first evaluated the effect of different structures of oil adjuvants (Fig. 1a) on arthritis development in an arthritis-susceptible rat strain, DA. As shown in Fig. 1b,c, pristane is the most arthritogenic among all the tested adjuvants, resulting in the highest mean arthritis score and greatest weight reduction. Arthritis starts on day 9 and reaches 100% incidence on day 12 (Fig. 1d). Pentadecane, structurally identical to pristane except the absence of four methyl groups on its 15-carbon backbone, induces significantly milder arthritis with lower mean arthritis score, reduced weight reduction and lower disease incidence ( Fig. 1b-d). Hexadecane, which is slightly longer than pentadecane with a 16-carbon backbone, induces mild arthritis, similar to pentadecane. Nevertheless, heptadecane with 17-carbon backbone induces more severe arthritis than pentadecane and hexadecane ( Fig. 1b-d). The presence of a carbon-carbon double bond in hexadecene, however, renders the hydrocarbon non-arthritogenic. In contrast, the presence of a carbon-carbon double bonds in squalene enhance arthritis since the unsaturated squalene developed more severe arthritis than the saturated squalane (Fig. 1b-d). Arlacel A (also named mannide monooleate), an emulsifying agent in IFA, induces severe arthritis as well (Fig. 1b-d).
We next determined the level of an acute phase protein in the serum, α 1 -acid glycoprotein (AGP). In general, the level of AGP correlates with the arthritogenicity of the adjuvants (Table 1). For example, the injection of the most arthritogenic adjuvants, such as pristane, resulted in a higher level of serum AGP, while the non-arthritogenic adjuvants, such as hexadecene, resulted in a lower level of serum AGP. However, this was not a strict correlation. For instance, injection of heptadecane resulted in nearly the highest level of serum AGP, even heptadecane did not induce the most severe form of arthritis. Injection of squalene and Arlacel A induced severe arthritis but resulted in rather low level of serum AGP compared to most other adjuvants (Fig. 1e).
ScIentIfIc RepoRts | 7: 14998 | DOI:10.1038/s41598-017-15096-z Variation in arthritogenicity of T cells primed with different adjuvants. The variation in disease onset and progression suggested different arthritogenic T cell activation by different oil adjuvants. In an adoptive cell transfer experiment, we previously showed that T cells from DA rats required a minimum of 5 days of pristane-priming in vivo to transfer arthritis and 8 days for the T cells to become fully arthritogenic 24 . Based on Fig. 1, we selected four oil adjuvants which varies in arthritogenicity, namely pristane, hexadecane, squalane and squalene, and studied the arthritogenic capacity of T cells that were previously primed in vivo with these adjuvants. Draining lymph node cells were collected 5 and 8 days post injection (p.i.) and stimulated with concanavalin A in vitro, before being adoptively transferred into naive recipient rats. Macroscopic arthritis score, weight change and disease incidence was assessed in these recipient rats.
As expected, T cells harvested 8 days p.i. transferred more severe arthritis with higher disease incidence and a longer disease course than T cells harvested 5 days p.i. for all tested oil adjuvants (Fig. 2). This reflects the increase in arthritogenic capacity of the adjuvant-primed cells with disease progression. In both day 5 ( Fig. 2a-d) and day 8 ( Fig. 2e-h) transfer, pristane-primed T cells are the most arthritogenic, resulting in the recipient rats developing the most severe arthritis with the most weight reduction, the earliest day of disease onset and 100% disease incidence. Hexadecane-primed T cells are more or less as arthritogenic as the pristane-primed T cells. Squalene-primed T cells are less arthritogenic than the pristane-primed and hexadecane-primed T cells, resulting in less severe arthritis with later disease onset in the recipient rats. Squalane-primed T cells are not arthritogenic on day 5 p.i., and only 1 out of 6 rats injected with T cells in vivo primed with squalane for 8 days developed arthritis, which was also very mild.

Arthritogenic adjuvant administration results immune cell expansion and activation and proliferation of CD4 + T cells.
We next performed flow cytometry to investigate the effect of oil adjuvants on different immune cell populations, in particular T cells, in the lymph nodes on day 5 p.i. (Fig. 3) and day 8 p.i. (Supplementary Fig. 2).
We first found that injection of different adjuvants resulted in different extent of cell expansion. The total number of lymph node cells in pristane-primed rats increased to 60 million on day 5 p.i. and 110 million cells on day 8 p.i., which is much greater than the rats injected with squalane that have only 30 million cells on day 5 p.i. and 50 million cells on day 8 p.i. (Fig. 3a, Supplementary Fig. 2). There were also more rapid expansion in the number of B cells, CD11b/c int cells and CD11b/c high cells (which are mainly monocytes and neutrophils respectively) in pristane-and squalene-primed rats on day 5 p.i. (Fig. 3b,e,f). Unexpectedly, the frequency of the CD4 + T cells are lower in pristane-and squalene-primed rats than that of squalane-primed rats (Fig. 3c), although the absolute number of CD4 + T cells remain higher in pristane-and squalene-primed rats (data not shown).
While we did not detect difference in the activation and MHC class II expression on the classical antigen presenting cells (data not shown), we found that injection of different adjuvants resulted in different degree of activation and proliferation of T cells. Pristane-primed CD4 + T cells were the most activated and proliferative, while squalane-primed CD4 + T cells were the least activated and proliferative, as determined by a number of activation and proliferation markers on day 5 after injection. Pristane-primed CD4 + T cell had the highest expression of CD25, CD27, CD71, ICAM-1 and Ki67; whereas squalane-primed CD4 + T cells exhibited the lowest expression of these markers (Fig. 3g-k). Squalene-primed CD4 + T cells are also significantly more activated and proliferative Epitope Autoantibody response 1 Spearman's rank correlation coefficient 2   Table 1. Autoantibody and AGP production and their correlations with arthritis development. 1 The autoantibody response was measured as MFI adjuvant /MFI naive , where MFI adjuvant and MFI naive are the MFI of the corresponding epitopes in the serum harvested from rats injected with adjuvant and from naive rats respectively. 2 Only adjuvant induced arthritis samples were included (n = 131). CIA and naive samples are not included in the correlation analysis. *Denotes p < 0.05, **denotes p < 0.01, ***denotes p < 0.001, ****denotes p < 0.0001. 3 Data obtained from AGP ELISA kit.
than the squalane-primed CD4 + T cells. Compared with squalane-primed CD4 + T cells, pristane-primed and squalene-primed CD4 + T cells comprised a higher frequency of regulatory T cells (CD3 + CD4 + CD25 + Foxp3 + ) ( Fig. 3d) which were also more proliferative (Fig. 3k). This could be necessary to counteract the increased expansion of autoreactive T cells in rats injected with pristane.
Overall, the pattern of activation and proliferation of the CD4 + T cells on day 5 p.i. was also similarly found on day 8 p.i ( Supplementary Fig. 2). Comparing the result of the adoptive cell transfer experiment (Fig. 2) and flow cytometry analysis of the lymph node cells (Fig. 3), the activation and proliferation of T cells largely correlate to the arthritogenicity of the CD4 + T cells, i.e. more activated and proliferative T cells transfer more severe arthritis.

Th17 cytokine gene expression correlates with the arthritogenicity of CD4 + T cells.
Having analysed different immune cell populations and shown that different adjuvant-primed CD4 + T cells differed in their activation and proliferation on day 5 p.i. (Fig. 3g-k), we determined mRNA levels of cytokines and MHC class II in purified CD4 + T cells also on day 5 p.i. (Fig. 4a). We found that the more arthritogenic oil adjuvants pristane and squalene induced significantly higher expression of the proinflammatory cytokine IFN-γ than the less arthritogenic oil adjuvants such as hexadecane or squalane (Fig. 4b). Further, the IL-17A gene expression pattern ( Fig. 4c) correlates very well with the arthritogenicity of CD4 + T cells (Fig. 2b), with similar gene expression pattern shown for other Th17 cytokines IL-22 and IL-21 (Fig. 4d,e). Pristane-primed, which resulted in the most severe arthritis in the recipient rats, measured with AUC (area under the curve), exhibited the highest IL-17A gene expression (Figs 2b and 4c). Hexadecane-primed T cells, with the second highest AUC, has the second highest IL-17A gene expression (Figs 2b and 4c). This is followed by squalene-primed T cells, and squalane-primed T cells with the lowest AUC inducing the lowest IL-17A gene expression (Figs 2b and 4c). There is however no difference in the expression of Th2 cytokines IL-4 and IL-10 ( Fig. 4f,g). Among all oil adjuvants, squalane induces significantly lowest MHC class II expression (Fig. 4h), which has been reported in activated rat T cells 25 . When stimulated with anti-CD3/anti-CD28, squalane-primed lymph node cells produced significantly less IFN-γ and IL-17 compared with other adjuvants (Supplementary Fig. 1). All these data point to the importance of Th1 and especially Th17 lineage in rats in the development of arthritogenic response in adjuvant-induced arthritis models.
Adjuvant induction of autoantibody response against type II collagen and other antigens. The discovery that a large proportion of patients with RA develop autoantibody response has led to extensive research into the use of such autoantibody response as diagnostic and prognostic biomarkers in both humans and rodents 26 . Whereas it is known that adjuvant-induced arthritis models such as PIA is driven by autoreactive T cells, it has been difficult to identify the autoantigens involved in the pathogenesis of arthritis with only very few such autoantigens that have been identified 15,20 . We recently developed a sensitive assay for detecting antibody response (measured as mean florescence intensity, MFI) against a number of autoantigen-derived compared to day 7 after injection; (d,h) disease incidence (%). Statistics were determined with the Mann-Whitney U test. *denotes p < 0.05, **denotes p < 0.01, ***denotes p < 0.001. peptides, including epitopes in triple-helical CII, α-enolase, filaggrin, vimentin, and fibrinogen. Using this assay, we detected autoantibody response in rats injected with different hydrocarbon oil adjuvants, and we used serum from rats with CIA or OIA, and also from naive rats as a control.
In general, a larger proportion of rats injected with the more arthritogenic oil adjuvants such as pristane and heptadecane, developed autoantibody response than rats injected with the non-arthritogenic or weakly arthritogenic adjuvants such as hexadecene and pentadecane (Fig. 5a). Furthermore, as measured in MFI adjuvant /MFI naive ratio, the autoantibody responses against cartilage joint specific triple-helical CII epitopes (CII 256-280 , C1, E10, J1, F4, U1 and E17) were stronger than those against other antigens such as α-enolase, filaggrin, vimentin and fibrinogen (Table 1) and more rats developed autoantibody response against CII than other antigens (Fig. 5a-e).
As shown in Table 1, the four CII epitopes with the strongest autoantibody responses are CII 256-280 , C1, E10, and J1; and the size of the antibody response against each of these epitopes for each oil adjuvant, as measured in MFI, is illustrated in Fig. 5b-e. We investigated if there is any correlation between autoantibody response and arthritis severity in the rats injected with hydrocarbon oil adjuvants using criteria including maximum arthritis score, sampling day arthritis score, arthritis sum score and weight change (Table 1). Among all the assessed autoantibody responses, antibodies against C1 showed the strongest correlation to the development of arthritis (arthritis sum score: r = 0.45, p < 0.0001) (Fig. 5g,h, Table 1). The strength of correlation is similar to the known serum marker AGP (arthritis sum score: r = 0.48, p < 0.0001) ( Table 1). Antibodies against C1 have been shown to be pathogenic and are used to induce an acute form of arthritis in the collagen antibody-induced arthritis (CAIA) model 27 . In this study, we showed that antibodies against C1 could also be detected in adjuvant-induced arthritis, despite at a lower level than CIA, and that C1 antibodies positively correlated with the severity of arthritis.
One of the diagnostic criteria in RA is the level of anti-citrullinated protein antibodies (ACPA) in serum 28 , although most studies so far have suggested that there are little or no ACPAs in rodents. We assessed antibody response against different citrullinated peptides identified in RA patients, including triple-helical CII, α-enolase, filaggrin, vimentin, and fibrinogen 26,29 . We did not detect any significant increase in the antibody response against nearly all of citrullinated epitopes in all 37 PIA and 21 CIA serum samples ( Supplementary Figs 3 and 4).
The effect of adjuvants on antigen-specific recall response and antibody production. We investigated the effect of oil adjuvants on antigen-specific recall response by injecting rats with ovalbumin (as the antigen) and different oil adjuvants. Ten days after immunization, we restimulated the draining lymph node cells in vitro with ovalbumin, and determined the level of various cytokines in the supernatant as a measure of T cell recall response, including IL-2 after 20 hours and interferon-gamma (IFN-γ) and IL-17 after 88 hours. We found that the choice of adjuvants did have a profound effect on the ovalbumin-specific recall response (Fig. 6a-c), in particular, in the production of IFN-γ and IL-17. The use of most arthritogenic adjuvants such as pristane and squalene in vivo had the strongest stimulatory effect on the recall response, compared with the use of weakly arthritogenic adjuvants, such as pentadecane and hexadecane (Fig. 6b,c). Three of the adjuvants however did not strictly follow this trend. The non-arthritogenic adjuvant hexadecene resulted in high production of IL-17 (Fig. 6c); and the weakly arthritogenic adjuvant squalane resulted in the highest production of IFN-γ (Fig. 6b). In addition, we included a second non-arthritogenic adjuvant, phytol ( Supplementary Fig. 5) 30 , and showed that phytol led to a strong stimulatory effect on the recall response as measured by IFN-γ and IL-17 (Fig. 6b,c). We also assessed the serum level of ovalbumin-specific antibody response. While the oil adjuvants used have no effect on the level of OVA-specific IgG1 (data not shown), the choice of adjuvants has a pronounced effect on the level of OVA-specific IgG2b (Fig. 6d), an indication of Th1 response 31 . Using pristane as an adjuvant resulted in the highest titer of OVA-specific IgG2b. Other C 15-17 oil adjuvants and squalene resulted in a lower titer; whereas squalane resulted in the lowest titer of OVA-IgG2b. We further evaluated the importance of αβ T cells on antibody response by in vivo depletion of αβ T cells. We showed that αβ T cell depletion resulted in almost complete abrogation of OVA-specific antibody response in both groups of rats injected with ovalbumin together with squalane or squalene (Fig. 6e), thus confirming the importance of the αβ T cells in the adjuvant regulation of antigen-specific antibody production.

Discussion
In this study, we assess the structural impacts of the hydrocarbon oil molecules on their adjuvanticity and autoimmunity. We showed that atomic differences in the hydrocarbon oil adjuvants could result in dramatic differences in adjuvanticity and autoimmunity, including differences in arthritis induction, acute phase response, immune cell frequency, T cell activation, proliferation and cytokine expression, autoantibody production, and antigen-specific recall response and antibody production. Combining both gene expression and flow cytometry analysis, together with adoptive disease transfer of T cells on day 5 and day 8 after adjuvant administration, we showed the choice of oil adjuvants can have pronounced impact on immune cell responses which resulted in different disease outcomes and the arthritogenicity of hydrocarbon oils is associated with their adjuvant properties. The fact that arthritis can be induced by adjuvants in the absence of other exogenous antigens makes adjuvant-induced arthritis an invaluable model to study the induction of T cell mediated autoimmunity. Adjuvant-induced arthritis show many similarities to human RA in being chronic (shown for pristane 6,17 and squalene 14 ), regulated by T cells and by being associated with the similar genetic loci, both MHC and non-MHC genes 5,7,16,32,33 . Importantly, the most strongly associated non-MHC gene Ncf1, which leads to increased arthritis severity with lower ROS response in the DA rat strain, is a genetic association that is clearly present also in human RA and systemic lupus erythematosus 32,34,35 . Adjuvants are normally present in our body. Pristane originates from exogenous sources. It is present in chlorophyll and is enriched in eukaryotic organisms, and are digested by both rats and humans. Squalene is the biochemical precursor of cholesterol and other steroids, present in sebum in animals but can also lead to chronic arthritis 14 . The challenge is to identify the pathogenic mechanism which these endogenous and 'harmless' adjuvants lead to inflammation. By studying structurally similar but pathogenically very different hydrocarbon adjuvants, we have the possibility to investigate the elements that are important in leading to joint inflammation. It is possible that whether a particular adjuvant can penetrate and cross phospholipid bilayer determines its arthritogenicity. Shorter hydrocarbon molecules (for example, shorter than C 15 backbone) 23 or hydrocarbons of certain shapes (for example, due to the presence or absence of carbon-carbon double bond) are not soluble in cell membranes and are thus less arthritogenic or non-arthritogenic. One of the most arthritogenic adjuvants, pristane, has been shown to interact with phospholipid bilayers and be incorporated into Figure 6. Effect of adjuvants on ovalbumin-specific recall response and antibody production. (a-d) DA rats were injected with ovalbumin together with pristane, pentadecane, phytol, hexadecane, heptadecane, squalane and squalene (n = 8 per group). Draining lymph nodes were harvested 10 days after immunization and restimulated in vitro with ovalbumin. Level of cytokines in the supernatant was determined as a measure of T cell recall response. (a) IL-2 was measured after 20 hours, and (b) IFN-γ and (c) IL-17 were measured after 88 hours of restimulation with ovalbumin. The stimulation index was determined by dividing the level of cytokines produced by the cells cultured in medium with ovalbumin, by the level of cytokines produced by the cells that were cultured in medium without ovalbumin. (d) Levels of ovalbumin-specific antibodies IgG2b in the serum was determined by ELISA and shown as arbitrary unit (AU). (e) Levels of ovalbumin-specific antibodies IgG2b in the serum in rats injected with ovalbumin together with squalane and squalane, with and without αβ T cell depletion (n = 5-6 per group). Data are shown as mean ± SEM. Statistics were determined with the Mann-Whitney U test. *Denotes p < 0.05, **denotes p < 0.01, ***denotes p < 0.001. the plasma membrane 19,36 . Other known effects of pristane include promoting tumour growth 37 , activating the signal transducing protein kinase C important in cell growth and differentiation 38 and also inducing cell death 21 .
Within 1 hour after injection, the injected adjuvants spread rapidly and reached different organs with high selectivity for lymph nodes and rather few oil droplets were distributed to joints 39 . At the lymph nodes, oil adjuvants lead to both local and systemic reaction including hyperplasia and an increased level of acute phase protein such as α 1 -acid glycoprotein (AGP) in the blood 14,17 . Here we clearly showed that the more arthritogenic adjuvants such as pristane induce stronger hyperplasia in the lymph node with the expansion of various cell types (as early as five days after adjuvant administration) accompanied by a stronger AGP response. Both PIA and OIA are known to be αβ T cell dependent and can be adoptive transferred by CD4 + T cells 18,40,41 . We showed that in addition to pristane-primed T cells, T cells in vivo primed with other adjuvants such as hexadecane and squalene can also transfer arthritis. The result of the adoptive cell transfer experiments however are not entirely as we anticipated. As expected, pristane-primed T cells are the most arthritogenic transferring the most severe form of arthritis, which is not surprising since we showed that pristane is the most arthritogenic adjuvants among all the adjuvants assessed in this study. What is unexpected is that, whereas we showed that hexadecane is a milder arthritogenic adjuvant compared with squalene ( Fig. 1), hexadecane-primed T cells are more arthritogenic transferring more severe arthritis than squalene-primed T cells (Fig. 2). Furthermore, whereas hexadecane and squalane induces similarly mild arthritis (Fig. 1), hexadecane-primed T cells are fully arthritogenic (disease incidence 86% and 100% in day 5 and day 8 transfer respectively) but squalane-primed T cells are not (disease incidence 0% and 17% in day 5 and day 8 transfer respectively) (Fig. 2). All these together seem to indicate that T cells in vivo primed with pristane and hexadecane (which are smaller in molecular size) reach their full arthritogenic capacity at an earlier time point than the T cells in vivo primed with squalane and squalene (which are larger in molecular size). Exactly how structural differences in these adjuvant molecules result in different pattern of arthritis induction and arthritogenicity of CD4 + T cells require further investigation. Our analysis, however, showed that the most arthritogenic adjuvant-primed αβTCR + CD4 + cells are the most activated and proliferative with the highest expression of Th1 and Th17 cytokines.
Another important field of adjuvant applications are their use in vaccines, where the use of vaccine adjuvants has also been associated with the elevated production of cytokines such as IFN-γ and IL-17 42 . Adjuvants are added into a vaccine to improve its immunogenicity. The challenge for developing vaccine is therefore to maximise the immunogenicity and to minimize vaccine reactogenicity and the risk of developing any 'adjuvant-induced' autoimmune or chronic degenerative disorders, such as narcolepsy [43][44][45] or Gulf War syndrome 46 . It is known that oil adjuvants induce tissue damage and cell death at the injection site leading to the production of damage-associated-molecular patterns (DAMPs) and inflammasome activation. Here we demonstrated that different adjuvants exert different extent of boosting effect on antigen-specific recall response and antibody production. We showed the importance of αβ T cells on the immune boosting effect of adjuvants, since αβ T cell depletion almost completely abrogated any antigen-specific antibody production. The fact that adjuvants induce arthritis only in genetically susceptible strains 7,17 and autoimmune disorders occurring only in genetically susceptible individuals 47 shows adjuvant induction of autoimmune diseases is partly determined by genetic factors. In future, it will be beneficial to investigate if these genetic factors, some of which have been identified by animal studies in our group 7,11 , also determine whether particular individuals with certain genetic profiles carry a higher risk of developing any adverse reactions upon adjuvant-based vaccination.
Using the Luminex technology, we detected a stronger autoantibody response in rats injected with more arthritogenic adjuvants; and a stronger autoantibody response against triple helical CII peptides than other antigens. In addition, we found that the antibody responses against several CII epitopes, such as C1, significantly correlated to the development of arthritis. The pathogenic roles of antibodies binding to CII epitopes, such as C1, J1 and U1, have been studied and shown for collagen-induced arthritis 27,48-50 , but not for adjuvant-induced arthritis. These CII antibodies are not likely to be involved in arthritis induction since adjuvant-induced arthritis does not depend on B cells or antibody production 40,51 . It remains to be determined whether these autoantibodies play any pathogenic roles or are simply a consequence of the disease development in the adjuvant-induced arthritis models.
This study not only provides novel information on the effects of different hydrocarbon oil adjuvants but is also an example how we can utilize different animal disease models and experimental techniques to characterize different aspects of adjuvant actions in not only arthritis but also other applications which involve the use of oil adjuvants. In this investigation, we showed the effect of slight structural variation in the oil adjuvants can have on both adjuvanticity and autoimmunity. Future research on both cellular and molecular mechanisms underlying adjuvant action potentially help us define the mechanisms critical in driving autoimmune response and also a better understanding of the adjuvants used for vaccines.

Methods
Animals. Inbred DA/Ztm rats were obtained from the Zentralinstitut für Versuchstierzucht (Hannover, Germany) and DA/OlaHsd from Harlan Europe (Netherlands). Rats were maintained by sister-brother mating in a barrier facility at Scheele Laboratory, Karolinska Institutet, and were specific pathogen free according to the Federation of European Animal Laboratory Science Associations guidelines. All animals were housed in a climate-controlled environment with 14 h light/10 h dark cycles, in individually ventilated microisolator-cages (Allentown) containing wood shavings (Tapvei), and fed standard rodent chow (R70, Lantmännen) and had free access to water. 8-12 weeks old, age-and sex-matched rats were used in all experiments.
Disease Induction and Evaluation. Arthritis was induced by intradermal injection of 200 μl of different hydrocarbon adjuvants at the base of the tail. Oil-induced arthritis was induced by intradermal injection of 300 μl Freund's incomplete adjuvant. Collagen-induced arthritis was induced by intradermal injection of 100 µg collagen type II (CII) dissolved in 0.1 M acetic acid and emulsified in an equal volume of Freund's incomplete adjuvant. Pristane (2,6,10,14-tetramethylpentadecane) were purchased from Acros Organics. Other hydrocarbon adjuvants pentadecane, phytol, hexadecane, hexadecane, heptadecane, squalane, squalene and arlacel A were purchased from Sigma Aldrich. Freund's incomplete adjuvant was purchased from Difco, Detroit, MI, USA. Pepsin-digested CII from rat chondrosarcoma was prepared as previously described 52 . Arthritis development was monitored blindly using a macroscopic scoring system. One point is given for each inflamed knuckle or toe and up to five points were given for an affected ankle (maximum score per limb 15 and 60 for a rat). Weight change was used as an objective measurement of disease severity. Disease marker α-1-acid-glycoprotein (AGP) in serum diluted 1:20000 was measured by the AGP ELISA kit (Life Diagnostics). All experiments were approved and performed in accordance with the guidelines of the Swedish National Board for Laboratory Animals and the European Community Council Directive (86/609/EEC). Complementary DNA was synthesized using High Capacity cDNA Reverse Transcription kit (ABI). QRT-PCR was performed on ABI 7900 HT (Applied Biosystems) using SYBR Green (Applied Biosystems) using a two-step PCR protocol (95 °C for 10 min, followed by 40 cycles for 95 °C for 10 sec and 60 °C for 30 sec). Primers were designed using NCBI/Primer-BLAST with sequences retrieved from public databases. Reference genes Actb, Arbp and Hmbs were used; and fold changes were determined using the standard comparative C T method. Primer sequences are listed in Supplementary Table 1.
Ovalbumin immunisation and antibody ELISA. 600 μg ovalbumin (from Sigma) dissolved in PBS and 200 μl adjuvant were injected to each rat at the base of the tail. Serum was taken from the rats 12 days after injection for antibody measurement. For serum antibody ELISA, the plate was coated with 10 μg/ml ovalbumin overnight at 4 °C in PBS. 50 μl serum at 1:250 to 1:10000 dilution was added to each well. Biotinylated anti-rat monoclonal antibodies against IgG2b (clone RG7/11.1; 2 μg/ml) (purchased from BD Pharmingen) were used as secondary reagents. Antibodies were detected using Eu 3+ -conjugated stretavidin (DELFIA) on a Synergy 2 multi-mode plate reader (BioTek).
In brief, 10 6 beads per bead identity were distributed across 96-well plates (Greiner BioOne), washed and re-suspended in phosphate buffer (0.1 M NaH 2 PO 4 , pH 6.2) using a plate magnet and a plate washer (EL406, Biotek). The carboxyl groups on the surface of the beads were activated by 0.5 mg of 1-ethyl-3(3dimethylamino-propyl) carbodiimide (Pierce) and 0.5 mg of N-hydroxysuccinimide (Pierce) in 100 µl phosphate buffer. After 20 min incubation on a shaker (Grant Bio), beads were washed in MES buffer (0.05 M 2-(N-morpholino)ethanesulfonic acid, pH 5.0). 250 µg/ml of NeutraAvidin was prepared in MES buffer and added to the beads. The coupling reaction was allowed to take place for 2 h at room temperature (RT), the beads were then washed 3x in PBS-T (0.05% Tween20 in PBS), re-suspended in 100 µl storage buffer (1% BSA, 0.05% Tween20, ProClin300 in PBS) and stored in plates at 4 °C overnight. Following day, 100 µl of each different biotinylated peptide at 50 µM concentration was added to neutravidin-coated beads. Following an overnight incubation at 4 °C, beads were washed 3x in PBS-T and re-suspended in 100 µl storage buffer. The final antigen suspension bead array was prepared by combining equal volumes of each bead identity.
Immobilization of the peptides was confirmed by the use of monoclonal CII-epitope specific antibodies used in collagen antibody induced arthritis (data not shown).
Using a liquid handler (CyBi-SELMA, CyBio), 45 µl of 1∶10 diluted serum samples were transferred to a 384 well plate containing 5 µl bead array per well. Following incubation at RT on a shaker (Grant Bio) for 75 min, beads were washed 6x with 60 µl PBS-T on a plate washer (EL406, Biotek) and re-suspended in 50 µl of each secondary antibody solution. Anti-rat IgG Fcy-PE diluted 1∶500 in a buffer consisting of 5% BSA, 0.05% Tween20 in PBS and used for detection of antibodies. After incubation with the secondary antibodies for 30 min, the beads were washed 3x with 60 µl PBS-T and re-suspended in 60 µl PBS-T for measurement by a FlexMap3D instrument (Luminex Corp.). The median fluorescence intensity (MFI) was chosen to display serum antibody-peptide interactions. Arthritic serum samples were considered positive for a particular epitope if the MFI of the samples exceeded the mean MFI + 3 SD of the naïve rat samples.
Bioinformatics and statistical analysis. Structure of oil adjuvants were obtained from https://pubchem. ncbi.nlm.nih.gov. For correlation between arthritis development and antibody response, a Spearman rank correlation coefficient, r, and the corresponding p value were calculated. Comparison of citrullinated versus non-citrullinated antibody response were determined with Wilcoxon matched-pairs signed rank test. All other statistical analysis was evaluated by Mann-Whitney U test and performed on Prism 6.0.
Data availability statement. The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.


Genetic variants in the plasminogen activator inhibitor‐1 gene are associated with an increased risk of radiation pneumonitis in lung cancer patients

Abstract Plasminogen activator inhibitor‐1 (PAI‐1) plays a crucial role in the process of lung injury, although its association with radiation pneumonitis (RP) is unclear. We hypothesized that genetic variants in PAI‐1 may influence the risk of RP. In this study, 169 lung cancer patients were genotyped for six single‐nucleotide polymorphisms in PAI‐1 using the Sequenom MassARRAY system. The risk of RP was evaluated by Cox proportional hazards analyses. The cumulative RP probabilities by genotype were assessed using Kaplan–Meier analyses. Univariate and multivariate analyses revealed that PAI‐1:rs7242 GT/GG was correlated with an increased occurrence of grade ≥3 RP (crude hazard ratio = 3.331; 95% confidence interval, 1.168–9.497; P = 0.024). Our results indicated that PAI‐1:rs7242 in the 3′‐untranslated region of PAI‐1 can be a predictor of grade ≥3 RP before radiotherapy.

Introduction
Radiotherapy is a common modality for treating lung cancer [1]. Radiation pneumonitis (RP) is a major side effect associated with radiotherapy which limits the therapeutic ratios of tumor treatment and reduces the living quality in patients who are irradiated for lung cancer. Approximately 16-30% of lung cancer patients experience severe RP after thoracic irradiation [2]. Therefore, the exploration and application of RP biomarkers may help maximize efficacy and minimize adverse effects of radiotherapy. Previous studies have investigated and identified multiple therapeutic and patient-related factors that are associated with the incidence of RP including chemotherapy, smoking status, chronic lung disease, dosimetric parameters, and transforming growth factor (TGF)β plasma concentrations [3][4][5][6][7][8]. However, only a small proportion of patients exposed to similar doses and volumes of irradiation develop RP, indicating that genetic factors perform a crucial role in the RP process. Our previous studies found that single-nucleotide polymorphisms (SNPs) in the TGFβ pathway were associated with RP risk [9,10]. Here, we expand upon our previous work by analyzing SNPs in plasminogen activator inhibitor-1 (PAI-1), an important target gene of TGFβ with RP risk [11].
PAI-1 is the main inhibitor of the plasmin system that blocks fibrinolysis and degradation of the extracellular matrix (ECM) [12]. PAI-1 has been implicated in the progression of inflammatory and fibrotic lung diseases. For example, high levels of PAI-1 in lung edema fluid may affect mortality in acute lung injury [13]. In mouse models, inhibiting PAI-1 expression by small interfering RNA or knockout of PAI-1 attenuates bleomycin-induced lung fibrosis in comparison with wild-type mice [14,15]. Additionally, a ORIGINAL RESEARCH B. Liu et al. SNPs in PAI-1 and Radiation Pneumonitis recent study indicated that a truncated PAI-1 protein (rPAI-123 ) protects against radiation-induced lung injury in a murine model [16]. Overall, these results implied that PAI-1 could be involved in the RP process.
Human PAI-1 is located on chromosome 7q21.3-q22 and consists of eight introns and nine exons. SNPs in PAI-1 may affect the transcriptional activation and plasma concentrations of PAI-1 [17]. Previous studies demonstrated that PAI-1 polymorphisms were associated with keloids, susceptibility to idiopathic interstitial pneumonia, myocardial infarction, and lung cancer prognosis [18][19][20][21]. However, no studies have examined how PAI-1 polymorphisms influence the risk of RP. Here, we investigated the association of SNPs in PAI-1 with RP risk in lung cancer patients treated with radiotherapy.

Study populations
This prospective study (NCT02490319) included 169 lung cancer patients. All patients received radiotherapy between September 2008 and June 2014 at Tongji Hospital (Wuhan, China). The enrolled patients had an expected survival > 6 months, Karnofsky Performance Status > 60, and received a radiation dose more than 45 Gy. Exclusion criteria included respiratory infection or lung fibrosis, pulmonary emboli, cardiac disease, drug toxicity, and previous thoracic irradiation. The Tongji Hospital Review Board approved our study. All patients enrolled in the study signed written informed consents for DNA and clinical information.
All enrolled patients underwent radiotherapy with a 6-MV linear accelerator (Elekta, Stockholm, Sweden). The total radiation dose was reached by administering 1.5-2 Gy per treatment. Dose-volume histogram data were shown in Table S1. Seventy-nine patients received intensitymodulated radiation therapy. One hundred sixty patients received induction chemotherapy followed by radiation or concurrent chemotherapy and radiation, with 32.9% receiving a gemcitabine/cisplatin regimen, 19% a CPT-11/ cisplatin regimen, 19.6% a docetaxel/cisplatin regimen, and 15.8% an etoposide/cisplatin regimen. We used a three-dimensional planning system (Pinnacle software, version 9.2; Philips Healthcare, Cleveland, OH) to delineate critical normal organs and target volumes.
Details of the follow-up schedule and the RP scoring criteria have been described previously [10]. Briefly, RP was diagnosed by two radiation oncologists after reviewing chest X-ray or computed tomography scans, pulmonary function tests, and clinical information, including symptoms, at each follow-up visit. The patients were followed during and 1 month after therapy, then every 3 months. RP was scored according to the Common Terminology Criteria for Adverse Events 4.0. Symptomatic RP interfering with daily activities, or a requirement for oxygen, were defined as grade 3.

Genotyping methods
Genomic DNA from all patients was extracted from peripheral blood via a blood DNA Kit (K1820-01; Invitrogen, Carlsbad, CA). Based on the public HapMap SNP database and HaploView 4.2 software, we searched for SNPs in PAI-1 that had minor allele frequencies greater than 10%, positioned within the 15-kb region or in its upstream or downstream regulatory regions. We found that all eligible SNPs could be captured with r 2 > 0.8 by five tagged SNPs: rs2227631, rs2227667, rs2227672, rs2227692, and rs7242. Together with the well-studied functional SNP rs1799768 (or 4G5G) [20], six SNPs in PAI-1 were selected ( Table 1). The SNPs were genotyped by the Sequenom MassARRAY system (Agena Bioscience, San Diego, CA) as described previously [10].

Statistical analyses
The time for developing grade ≥3 RP was the endpoint used for this analysis. Data from patients were censored if they did not develop grade ≥3 RP within 1 year. SPSS version 19.0 (IBM, Chicago, IL) was used for statistical analyses. The Cox proportional hazards model was applied to estimate hazard ratios with 95% confidence intervals of different genotypes. Multivariate Cox regression analysis was used to adjust other covariates. Kaplan-Meier analyses were used to evaluate influences of the genotypes on RP between groups by log-rank tests. P < 0.05 was considered statistically significant in all tests.

Results
Patient characteristics and association with RP Table 2 lists characteristics of the 169 (125 male and 44 female) lung cancer patients (114 non-small-cell lung carcinoma and 55 small-cell lung carcinoma). The median age of patients was 57 years (28-78 years). One hundred six (62.0%) of the patients were smokers. Among the 169 patients, 145 (85.8%) had stage III-IV disease, 160 (94.7%) were treated with chemotherapy, and 86 (50.9%) underwent surgery before radiotherapy.

RP and PAI-1 polymorphisms
The associations between genetic polymorphisms and the risk of grade ≥3 are shown in Table 4 using the Cox proportional hazards model. A significant association was found between rs7242 and the risk of grade ≥3 RP. Compared with the rs7242 TT genotype, the GT/GG genotypes had increased hazards of grade ≥3 RP (P = 0.024). We found a similar result after multivariate analyses with adjustment for potential confounding factors of RP. The RP-free survival for grade ≥3 RP, according to rs7242 is plotted in Figure 1A. Development of grade ≥3 RP was prolonged in the rs7242 GG/GT genotypes, while no associations with grade ≥3 RP were found for the other SNPs.

PAI-1:rs7242 and dosimetric factors
The cumulative probability of grade ≥3 RP on the basis of genotype and V 20 as a function of time is shown in Figure 1B. The incidence of RP in patients receiving V 20 ≥ 24% and GT/GG genotypes in rs7242 were higher than patients who received V 20 ≥ 24% with the TT genotype in rs7242 (P = 0.013). We also analyzed the cumulative RP incidence on the basis of MLD and genotypes as a function of time (Fig. 1C). Patients with a MLD ≥ 15 Gy and GT/GG genotypes in rs7242 displayed a higher RP hazard than patients with the TT genotype and a MLD ≥ 15 Gy (P = 0.010). However, we did not observe this difference in patients who received V 20 < 24% or a MLD < 15.0 Gy. These results suggest the independent role of rs7242 genotypes in grade ≥3 RP.

Discussion
This study examined whether genetic polymorphisms in PAI-1 gene might be associated with an increased risk of RP in lung cancer patients receiving radiotherapy. We believe this is the first finding of an association between the presence of rs7242 in the 3′-untranslated region (UTR) of PAI-1 and the risk of grade ≥3 RP. We found that patients with the rs7242 GG or GT genotypes exhibited an increased risk of RP following radiotherapy. Our results also indicated that the association between rs7242 and grade ≥ 3 RP risk was independent of V 20 and MLD. Moreover, a group of patients (GT/GG genotypes in rs7242 and V 20 ≥ 24% or MLD ≥ 15 Gy) were found with the highest occurrence of grade ≥3 RP. RP is a common complication following radiotherapy and is characterized by diffuse alveolar damage and subsequent fibrosis with excessive ECM deposition in the lung [22]. PAI-1 is the main inhibitor of the plasmin system and has a crucial role in ECM accumulation by inhibiting fibrinolysis [12]. Although little is known about the association between PAI-1 polymorphisms and RP risk, several facts indicate that this association is biologically plausible. First, genetic variants in PAI-1 influence the plasma levels of PAI-1 and are associated with other inflammatory or fibrotic diseases including keloids, myocardial infarction, and idiopathic interstitial pneumonia [18][19][20]. Second, PAI-1 is implicated in the development of other radiation injury diseases. For example, there is a high level of PAI-1 in radiation-induced nephrosclerosis and the process of radiation enteritis [23,24]. PAI-1 knockout mice have better survival and intestinal function compared with wild-type mice in radiation-induced intestinal injury [25]. Finally, PAI-1 is closely regulated by TGF-β1, the cytokine that has a critical role in the RP process [22,26]. TGF-β1 can regulate PAI-1 expression via SMAD-dependent and -independent pathways in numerous fibrotic diseases [11,[27][28][29][30][31]. Moreover, TGF-β1 increases PAI-1 plasma levels and promotes the epithelialmesenchymal transition (EMT), while PAI-1 small interfering RNA prevents the TGF-β1induced EMT in mouse lung epithelial cells [12].
In this study, rs7242 was associated significantly with grade ≥3 RP. The rs7242 polymorphism is located in the 3′-UTR of PAI-1 and is characterized by the substitution of a guanine with thymine. Studies have examined the relationships between this polymorphism and the risk of myocardial infarction, diffuse-type gastric cancer susceptibility, and primary ovarian insufficiency [19,32,33]. In addition, previous studies found that haplotypes of this polymorphism may affect the plasma level of PAI-1 [32,34]. Other research reported that the rs7242 polymorphism may affect blood insulin concentrations [19]. Because insulin levels play particular roles in lung diseases [35], rs7242 may also modulate the risk of RP by influencing insulin levels in cancer patients.
In summary, these facts suggest that the influence of rs7242 on RP is biologically plausible. However, in this study, we did not observe that other PAI-1 polymorphisms affected the risk of RP. This included rs1799768 that can influence PAI-1 plasma levels and confer an increased risk of several inflammatory or fibrotic diseases such as myocardial infarction, asthma, nephropathy, and idiopathic interstitial pneumonia [20,[36][37][38]. This finding may have been due to the different nature of the diseases and the small size of the study population.
Our study suggested that the rs7242 polymorphism can be used as a predictor of RP. In combination with our previous findings concerning RP susceptibility and SNPs in TGFβ1, ITGB6, PI3CA, AKT2, and MMP1 [9,10,39,40], we can establish a more accurate model using these variants, enabling the prediction of RP by genotyping patients prior to radiotherapy. This would enable patients lacking RP susceptibility genotypes to receive appropriately elevated radiation doses to enhance tumor-related therapies.
In spite of these positive findings, some limitations of our study should be addressed. First, the population of this study was relatively small and thus the results need to be confirmed by further validation. Moreover, we were unable to explore the exact mechanism by which PAI-1 polymorphisms led to RP in lung cancer patients. Finally, as the power in this exploratory study was limited, the P values in this study were not adjusted using Bonferroni corrections. Therefore, our findings are considered preliminary.
In conclusion, this study identified that rs7242 GT/GG genotypes located in the 3′-UTR of PAI-1 were significantly associated with an increased risk of RP in lung cancer patients treated with radiotherapy. Our findings suggested that this polymorphism could be used to predict RP in Figure 1. Kaplan-Meier estimates RP-free survival (RP ≥ grade 3) as a function of time from the start of radiation therapy by genotypes. (A) rs7242; (B) rs7242 and V20; (C) rs7242 and MLD. The rs7242 GT/GG genotypes was associated with a significantly higher risk of RP as compared with TT genotype (P = 0.017). Patients with GT/GG genotype of rs7242 and V20 ≥ 24% or MLD ≥ 15 Gy had the highest grade ≥3 RP risk compared with other groups.


extfieldsofstudy: Biology Medicine Chemistry

s2fieldsofstudy: Biology Chemistry

text:
Imaging specific cellular glycan structures using glycosyltransferases via click chemistry

Abstract Heparan sulfate (HS) is a polysaccharide fundamentally important for biologically activities. T/Tn antigens are universal carbohydrate cancer markers. Here, we report the specific imaging of these carbohydrates using a mesenchymal stem cell line and human umbilical vein endothelial cells (HUVEC). The staining specificities were demonstrated by comparing imaging of different glycans and validated by either removal of target glycans, which results in loss of signal, or installation of target glycans, which results in gain of signal. As controls, representative key glycans including O-GlcNAc, lactosaminyl glycans and hyaluronan were also imaged. HS staining revealed novel architectural features of the extracellular matrix (ECM) of HUVEC cells. Results from T/Tn antigen staining suggest that O-GalNAcylation is a rate-limiting step for O-glycan synthesis. Overall, these highly specific approaches for HS and T/Tn antigen imaging should greatly facilitate the detection and functional characterization of these biologically important glycans.

Introduction
Glycosylation is the most common type of posttranslational protein modification (Khoury et al. 2011). Glycans are assembled by various glycosyltransferases along a pathway starting at the endoplasmic reticulum continuing to the Golgi apparatus, and these structures are expressed on the membrane, or as secreted extracellular matrix elements or soluble glycoproteins (Lairson et al. 2008). Glycan modifications play various biological roles from protein folding and quality control to a large number of biological recognition events (Moremen et al. 2012). For instance, they act as ligands for numerous glycanbinding lectins (Pang et al. 2011), growth factors and cytokines transferase (GALNT), and is completed by addition of a Gal residue by the β-3 galactosyltransferase C1GalT1. Loss of the activity of C1GalT1 in cancer cells results in intermediate product O-GalNAc, also known as "Tn antigen" (Ju and Cummings 2005). T and Tn antigens are hallmarks of cancer (Fuster and Esko 2005;Gilgunn et al. 2013;Pinho and Reis 2015). Heparan sulfate (HS), a linear polysaccharide that has repetitive disaccharide units of HexA-GlcNAc, is a representative glycosaminoglycan found on the cell surface and in ECM (Iozzo 2005;Sarrazin et al. 2011), with the HexA residue being either a GlcA or IdoA. HS is synthesized by exostosins (EXTs), dual enzymes that have both GlcA and GlcNAc transferase activities (Senay et al. 2000). HS is degraded by heparanase (HPSE), an endoglucuronidase that specifically hydrolyzes the βGlcA-1,4-GlcNAc bond in highly sulfated HS domains (Vlodavsky et al. 1999;Mao et al. 2014). HS can also be digested with bacterial lyases such as heparinase III, which leaves an unsaturated GlcA residue (ΔGlcA) at its non-reducing end (Hovingh and Linker 1970). Apart from membrane and extracellular matrix display, proteins within the cytoplasm and nucleus can be modified by O-GlcNAc that plays important regulatory roles in metabolism, diabetes and cancer (Slawson and Hart 2011;Bond and Hanover 2013). O-GlcNAc can be extended with a GalNAc residue by a mutant enzyme B4GalT1Y285L (Ramakrishnan and Qasba 2002).
Despite the abundance of glycans and their important biological functions, glycans are notoriously difficult to image due to lack of high affinity and highly specific binding reagents (Sterner et al. 2016). In the past decade, metabolic labeling using clickable carbohydrate (Hsu et al. 2007;Codelli et al. 2008;Baskin et al. 2010, Kizuka et al. 2016 has revolutionized glycan imaging, as it eliminates the problems associated with low binding affinity via covalent bonding. Subsequently, enzymatic glycan labeling using clickable sugars have been reported (Griffin and Hsieh-Wilson 2016): (1) O-GlcNAc has been imaged by further modification using the mutant galactosyltransferase B4GalT1Y285L (Clark et al. 2008); (2) the Fucα(1-2)Gal epitope has been imaged by a bacterial glycosyltransferases BgtA (Chaubard et al. 2012); (3) LacNAc has been imaged by an H. pylori fucosyltransferase (Zheng et al. 2011); and (4) N-glycans have been imaged by recombinant sialyltransferase ST6Gal1 (Mbua et al. 2013). These methods have shown the promise of specific glycan imaging due to the high specificities of labeling glycosyltransferases. However, the challenge to validate the specificities of these methods still remains.
Previously, GlcNAc transferases GCNT1, B3GNT6 and EXT1/ EXT2 have been found to be permissible to azido-GlcNAc (Wu et al. , 2017, and polypeptide GalNAc transferases GALNT1/ 2/3 have been found to be permissible to azido-GalNAc (Pratt et al. 2004;Wu et al. 2015). Here, we report the imaging of HS and T/Tn antigens along with other related glycans on mammalian cells by in vitro incorporation of azido-sugars using these glycosyltransferases. The incorporated sugars are linked to fluorescent tags via azide-alkyne cycloaddition (Rostovtsev et al. 2002). Using O-GlcNAc as a control, and, HS and T/Tn antigens as examples, the specificities of these methods are systematically investigated through comparing imaging of different glycans, and, imaging before and after removal or installation of the glycans of interests. Leveraging the specificity of these enzymes, the resulting incorporated clickable sugars enable precise detection of the interested glycan motifs and provide key information on the cellular topography of these glycans.

Results
Glycan imaging on transformed mesenchymal stem cells C3H10T1/2 cells were originally established from cells extracted from C3H mouse embryos and are an established transformed mesenchymal stem cell model as they can be differentiated into downstream mesenchymal cell lineages (Reznikoff et al. 1973). As a proof of concept, we imaged O-GlcNAc, O-GalNAc (Tn antigen), terminal sialyllactosamine (sLN), and core-1 O-glycan (T antigen) using B4GalT1Y285L, B3GNT6, FUT7 and GCNT1, respectively, on C3H10T1/2 cells (Table I). B4GalT1Y285L is a mutant enzyme that can transfer a GalNAc residue to a terminal GlcNAc residue (Ramakrishnan and Qasba 2002), and therefore be used for O-GlcNAc detection in the presence of the donor substrate UDP-N 3 -GalNAc. B3GNT6 specifically recognizes O-GalNAc and synthesizes the "core-3" O-glycan (GlcNAcβ1-3GalNAcα1-S/T) (Iwai et al. 2002), and is therefore useful for O-GalNAc detection in the presence of UDP-N 3 -GlcNAc. The α(1,3)fucosyltransferase FUT7 recognizes sialylated type 2 lactosamine (sLN) and synthesizes sLeX structure (Natsuka et al. 1994), and is thus useful for sLN detection in the presence of GDP-N 3 -fucose. GCNT1 transfers a GlcNAc residue to core-1 O-glycan and synthesizes "core-2" O-glycans (Yeh et al. 1999), and can thereby be used to detect core-1 O-glycan in the presence of UDP-N 3 -GlcNAc.
Consistent with results of others (Hart and Akimoto 2009;Wu et al. 2014), B4GalT1Y285L stained strongly in the nuclei and weakly in regions surrounding the nuclei ( Figure 1A). Direct staining for O-GalNAc (Tn antigen) using B3GNT6 resulted in no signal. To assess whether Tn antigen can be detected, it was first installed on cells by GALNT2, a polypeptide GalNAc transferase that transfers a GalNAc residue to serine/threonine residues on nascent polypeptides (Sorensen et al. 1995), and then probed using B3GNT6. The installed O-GalNAc was mainly found in the cytoplasm ( Figure 1B), which is reasonable because the labeled proteins are likely to be nascent polypeptides that contained unmodified Ser/Thr residues. In sharp contrast, FUT7 and GCNT1 labeling appeared to be largely on the cell membrane and the ECM ( Figure 1C and D, respectively). The resultant staining using FUT7 indicates that there are sLN on C3H10T1/2 cells, which is consistent with previous findings that both mouse and human mesenchymal stem cells can be α(1,3)-exofucosylated to enforce sLeX expression (Abdi et al. 2015;Dykstra et al. 2016). The staining observed using GCNT1 indicates that C3H10T1/2 cells express core-1 O-glycan or T antigen.

Glycan imaging on human umbilical vein endothelial cells
Human umbilical vein endothelial cells (HUVEC) are primary endothelial cells commonly used to study the mechanisms of angiogenesis in vitro (Crampton et al. 2007). HUVEC cells were grown in a 24-well plate to confluence and then stained for O-GlcNAc, O-GalNAc, sLN, HS and HA determinants using recombinant human B4GalT1Y285L, B3GNT6, FUT7 and EXT1/2, and recombinant Pasteurella multocida HA synthase (HAS) respectively (Table I). EXT1/2 is a hetero-dimeric HS polymerase of EXT1 and EXT2, which alternatively utilizes UDP-GlcA and UDP-GlcNAc to extend the HS chain in vivo. Previously, we reported that EXT1/2 can incorporate azido-GlcNAc to the nonreducing ends of HS (Wu et al. 2017). HAS is a polymerase that alternatively utilizes UDP-GlcA and UDP-GlcNAc to extend an HA chain at its non-reducing end (DeAngelis et al. 2003).
Similar to C3H10T1/2 cells, O-GlcNAc staining was primarily found in the nuclei and secondarily found in regions close to the nuclei ( Figure 2A). Again, "free" O-GalNAc (Tn antigen) was not identifiable in HUVEC cells so it was installed by GALNT2 prior to B3GNT6 staining, and similar to the C3H10T1/2 cells, the incorporated O-GalNAc was primarily located in the cytoplasm ( Figure 2B). FUT7 staining yielded strong signal on the cell body and weak signal within the ECM ( Figure 2C); suggesting a higher density of sLN on the cell surface than in the ECM. In contrast, EXT1/2 yielded strong staining of the ECM but weak staining of the cell surface ( Figure 2D, see also Supplemental Figure S1). In fact, the staining of cell body by EXT1/2 was so weak that the cell bodies were only revealed by GALNT2 staining in the presence of UDP-N 3 -GalNAc in Figure 2D.
HUVEC cells were also stained for HA (Supplemental Figure S2). While HS was located mainly in ECM and weakly detected on cell body, HA was strictly found on cell body and particularly enriched in nucleus. The HA detected on cell body and nucleus could be those molecules that were bound to their receptors such as CD44 (Aruffo et al. 1990).  In a separate experiment, prior treatment of HUVEC cells with HA lyase abolished HA staining (Supplemental Figure S3), confirming the identity of HA that was detected.

Further confirmation of the specificity of glycan imaging
From the above examples of cell staining, it is clear that different enzymes stained different features on cells, indicating that this glycosyltransferase-mediated staining is specific. To further assess whether staining was indeed on the target glycans that are recognized by the enzymes, we utilized two strategies. The first involved abolishing staining by removal of target glycans using specific glycosidases, which is already shown in HA staining (Supplemental Figure S3). The second involved increased staining by installation of target glycans using glycosyltransferases. In some cases, the results of cell staining were further supported by results obtained from labeling of cellular extracts detected by the GLCC method previously described (Wu et al. 2015).

Specificity of O-GlcNAc staining
Since O-GlcNAc is well known for its cellular localization (Hart and Akimoto 2009), it was chosen for testing the specificity of the current method of imaging. For this purpose, we treated HUVEC cells with O-GlcNAcase (OGA), a glycosidase that specifically removes O-GlcNAc (Dennis et al. 2006) but not terminal GlcNAc, prior to the staining with B4GalT1Y285L ( Figure 3). As expected, the nuclear staining was abolished after the treatment, which confirms that the staining in the nuclei is on O-GlcNAc. The remaining staining in the regions surrounding the nuclei is likely on terminal GlcNAc residues other than O-GlcNAc, as it is known that the mutant B4GalT1 also uses terminal GlcNAc residues on N-glycans and O-glycans as acceptor substrates (Boeggeman et al. 2007).
In a parallel experiment, cytoplasmic and nuclear extracts prepared from HUVEC and HEK 293 cells were treated with OGA first and then labeled with B4GalT1Y285L ( Figure 3C). Both cytoplasmic and nuclear extracts were labeled in the absence of OGA treatment. In contrast, OGA abolished the labeling of nuclear extracts only, again confirming that the labeling in the nuclear extracts was exclusively on O-GlcNAc.

Strict specificity of HS staining
To test the specificity of HS staining, we treated HUVEC cells with heparinase III (Hep III) and heparanse (HPSE), prior to the staining by EXT1/2 ( Figure 4). Hep III digestion on HS results in HS chains ending with Δ4,5-glucuronic acid (ΔGlcA) residues that lacks a C4 -OH group that is needed for HS chain extension by EXT1/2. Indeed, Hep III digestion abolished the labeling by EXT1/2 ( Figure 4B), confirming that the staining is indeed on HS. On the other hand, HPSE digestion on HS results in uniform N-sulfated GlcNAc residue (GlcNS) at the ends of HS chains (Mao et al. 2014). As a result, pretreatment with HPSE significantly increased the labeling (Figure 4C), suggesting that GlcNS can be extended by EXT1/2 and that a significant portion of native HS chains could not be labeled by EXT1/2. Finally, we attempted to label HPSE treated cells without the donor substrate UDP-GlcA. This experiment resulted in almost no labeling in the ECM ( Figure 4D), again confirming that the labeling was on HS, because HS digested by HPSE ends with a GlcNS residue (Mao et al. 2014) that requires the incorporation of a GlcA residue prior to the incorporation of an azido-GlcNAc for HS detection.
To further confirm the staining of HS, wild type of CHO (CHO-K1) and mutant type CHO cells (pgs-745) (Bai et al. 1999) that do not synthesize HS were imaged with EXT1/2. As results, CHO-K1 cells were stained weakly but clearly more intense than the mutant pgsA-745 cells (Supplemental Figure S4). The relative weak staining on CHO-K1 is consistent to HUVEC cell staining in Supplemental Figure S1 and S2. In contrast, no staining was found to be deposited to ECM by CHO-K1. To this end, we suspected that the majority of HS of CHO-K1 cells were secreted to conditioned medium, which was confirmed in a blotting assay (Supplemental Figure S5). Enzyme kinetic assay using a universal glycosyltransferases assay method ) also suggested that EXT1/2 can extend the nonreducing ends on HS created by HPSE digestion (Supplemental Figure S6). To investigate whether there is any preference on proteolgycans for EXT1/2 staining, we labeled various purified proteoglycans (Supplemental Figure S7). As results, syndecan 4, testican 2 and 3, and glypican 1 to 6 were found to be labeled by EXT1/2, suggesting that not all HS proteoglycans are equally recognized by EXT1/2.

ECM morphology revealed by HS staining
While labeled HS was found mainly in the ECM of confluent HUVEC cells ( Figure 2D), it was also found on cells (Supplemental Figure S1 and S2), which is consistent with the literature (Sarrazin et al. 2011). HS staining also revealed some unique morphology of the ECM of HUVEC cells. In one case, the ECM resembled an entangled mesh ( Figure 5A). In another case, the ECM resembled a lush lawn ( Figure 5B). In a third case, the ECM resembled a plain carpet ( Figure 5C), suggesting the cells that had laid out the HS had migrated away from sites of deposition. The unique morphology revealed by HS staining in each case suggests that dynamic alterations in HS topography may dictate cellular distribution in discrete tissue microenvironments. When HS of non-confluent young HUVEC cells was stained, some intermediate structures of ECM were captured (Supplemental Figure S8), revealing the unique process of ECM formation.

Enzymatic synthesis of T and Tn antigens and their specific staining
To assess whether GCNT1 staining observed in Figure 1D is indeed on T antigen (or core-1 O-glycan), we installed T antigen to HUVEC cells that natively do not express the glycan using GALNT2 and C1GalT1. GALNT2 attaches a GalNAc residue to serine or threonine residue on the protein backbone to generate O-GalNAc (Sorensen et al. 1995), and C1GalT1 further adds a Gal residue to the O-GalNAc to complete the core-1 O-glycan (T antigen) synthesis (Ju et al. 2002) (Figure 6A). When the T antigen was fully installed, the staining with GCNT1 was positive ( Figure 6B); while when only Tn antigen was installed, the cell staining by GCNT1 was negative ( Figure 6C). The installation of Tn antigen was confirmed by B3GNT6 staining in Figure 6D. In contrast, only weak background was seen on untreated cells by B3GNT6  staining ( Figure 6E). These experiments demonstrate the strict specificities of GCNT1 and B3GNT6, for T and Tn antigens, respectively. It should be noted that some staining in the ECM by GCNT1 was observed regardless of T antigen installation (indicated with arrows in Figure 6B and C), probably due to mis-folded and incompletely glycosylated protein aggregates. To validate this method for Tn antigen detection, Jurkat cells that are known to express Tn antigen was also imaged (Supplemental Figure S9). Indeed, Jurkat cells were stained, with some cells stained much more intensely than others.
Using the same strategy of Figure 6A, cytoplasmic and nuclear extracts of HUVEC cells and HEK293 cells were installed with Tn and T antigens and then labeled with B3GNT6 and GCNT1. As expected, only Tn antigen was detected by B3GNT6 (Supplemental Figure S10A) and only T antigen was detected by GCNT1 (Supplemental (E) Fixed HUVEC cells were directly stained by B3GNT6. Staining in B and C indicated by the yellow arrows may due to mis-folded and incompletely glycosylated protein aggregates. Antigen staining was revealed by Alexa-Fluor 555 (red) and nuclei were revealed by DAPI (blue). Figure S10B). Also, in sharp contrast to B4GalT1Y285L that can label the unmodified cellular extracts ( Figure 3C), no labeling was observed with either GCNT1 or B3GNT6 on unmodified cellular extracts, suggesting that these cellular extracts were devoid of T and Tn antigens. These results further provided evidence of the strict specificities GCNT1 and B3GNT6. The lack of T and Tn antigens on HUVEC cells and the fact that O-GalNAc can be installed onto fixed HUVEC cells by GALNT2 also suggest that O-GalNAcylation is a rate-limiting step for O-glycan synthesis.
Since there are about 20 GALNTs that can perform O-GalNAcylation (Gerken et al. 2011), the substrate specificities and kinetics of these enzymes will be crucial for the synthesis of O-glycans. To this end, we labeled the cellular extracts of HUVEC cells using GALNT1, 2, 3 with UDP-N 3 -GalNAc (Supplemental Figure S11). The three enzymes exhibited different labeling patterns, confirming their different substrate specificities (Pratt et al. 2004). Moreover, the three enzymes showed synergistic effects on O-GalNAcylation. This experiment suggests that for the synthesis of T and Tn antigen on a particular polypeptide scaffold, the selection of GALNT is critical.

Mass spectrometry analysis of azido-sugar labeled glycoprotein
In addition to the glycan epitopes, it is also imperative to know what host glycans and glycoproteins are tagged using our methods. To this regard, a sample of fetal bovine fetuin that was labeled with azidosialic acid using ST6Gal1 was analyzed by mass spectrometry (Supplemental Figures S12 and S13). The results demonstrated that azido-sugar labeled samples are compatible to mass spectrometry analysis to identify the target glycans and glycoproteins.

Discussion
Currently, antibodies and plant lectins are the most commonly used reagents to detect glycans (Cummings and Etzler 2009). However, there are relatively few anti-glycan antibodies and their specificities are generally not absolute (Sterner et al. 2016). Though many lectins are characterized, these reagents bind with low affinity to their glycan targets and, thus, generally lack both sensitivity and specificity (Ambrosi et al. 2005). Here, we describe imaging methods especially for heparan sulfate and T/Tn antigen detection by in vitro enzymatic incorporation of clickable monosaccharides. The specificity of our methods is achieved through glycosyltransferases that are known to be highly selective for their substrate glycans. By covalent conjugating reporter molecules to target molecules, the sensitivity of the current methods is maximized in theory. The strict specificity of these methods was further confirmed by either removal of target glycans, which resulted in loss of signal, or by installation of a target glycan, which resulted in gain of signal. The images obtained with the described methods either confirm what we already know about a particular glycan or stimulate new questions about the biology of these glycans. In particular, HS staining revealed striking images of the ECM of HUVEC cells, suggesting unique mechanism for HS secretion. T/Tn antigen staining on HUVEC suggested that O-GalNAcylation is a rate-limiting step for O-glycan synthesis. We believe that these new tools for glycan imaging will greatly facilitate us to understand the biological roles of various glycans and glycoconjugates.
T and Tn antigens are hallmarks of many types of cancer and they become the targets for cancer immunotherapy (Posey et al. 2016).
Here we have provided pure enzymatic ways for their synthesis on cellular scaffolds as well as methods for their detection. This enzymatic synthetic approach provides an alternative way for enforcing T and Tn antigens, which may allow for further elucidation of the roles of these glycans in cancer biology. It is also foreseeable that the unprecedented specificities of the labeling enzymes for T/Tn antigen maybe exploited for therapeutic interventions such as for linking various bioactive molecules to target cells. Further studies using these reagents should help unveil how dynamic changes in glycan display mediate cellular processes, such as cell-cell and cell-matrix interactions.

Pretreatment of cells for imaging
For glycan imaging, the cells were pretreated with glycosidases to remove existing glycans or with glycosyltransferases to add glycans. All of the following treatments are referring to the cells in a single well in a 24-well plate. In particular, for O-GlcNAc removal, cells were treated with 2 μg of OGA in 200 μL of 50 mM MES and 100 mM NaCl at pH 5.5 for 1 h at 37°C. For heparan sulfate removal, cells were treated with 2 μg of Hep III in 200 μL of 50 mM Tris and 2 mM CaCl 2 at pH 7.5 for 1 h at 37°C. For heparan sulfate treatment by HPSE, cells were digested by 2 μg of HPSE in 200 μL of 0.1 M NaOAc at pH 4.0 for 1 h at 37°C. For installation of O-GalNAc to cells, 50 nmol of UDP-GalNAc and 2 μg of GALNT2 in 200 μL of 25 mMTris, 150 mM NaCl, 10 mM MnCl 2 at pH 7.5 were added into each well and the cells were then incubated at 37°C for 1h. After the treatment, the cells were thoroughly washed three times with PBS and all solutions were removed by aspiration.

Incorporation of clickable carbohydrate using glycosyltransferases
To incorporate clickable carbohydrates into the cells, 25 mM MES, 0.5% (w/v) Triton ® X-100, 2.5 mM MgCl 2 , 10 mM MnCl 2 , 1.25 mM CaCl 2 and 0.75 mg/mL of BSA at pH 7.0 was used as the Labeling Buffer throughout the course of this study. For imaging lactosamine, a mixture of 20 nmol of GDP-N 3 -fucose and 2 μg of FUT7 in 200 μL Labeling Buffer was prepared. For O-GlcNAc imaging, a mixture of 20 nmol of UDP-N 3 -GalNAc and 2 μg of B4GalT1Y285L in 200 μL Labeling Buffer was prepared. For O-GalNAc imaging, a mixture of 20 nmol of UDP-N 3 -GlcNAc and 2 μg of B3GNT6 in 200 μL Labeling Buffer was prepared. For core-1 O-glycan imaging, a mixture of 20 nmol of UDP-N 3 -GlcNAc and 2 μg of GCNT1 in 200μL Labeling Buffer was prepared. For HS imaging, a mixture of 20 nmol of UDP-N 3 -GlcNAc, 50 nmol of UDP-GlcA and 4 μg of EXT1/2 in 200 μL Labeling Buffer was prepared. For HA imaging, a mixture of 20 nmol of UDP-N 3 -GlcNAc, 50 nmol of UDP-GlcA and 10 μg of HAS in 200 μL Labeling Buffer was prepared. The mixtures were then applied to the wells and incubated at 37°C for 1-2 h, or at room temperature for 16 h.

Conjugation of the clickable carbohydrates to biotin and fluorescent dye
After the incorporation of the azido carbohydrates to cells, a biotin moiety was conjugated to the carbohydrates via copper mediated click chemistry. For each reaction, 20 nmol of Cu 2+ , 10 nmol of Biotinylated Alkyne and 200 nmol of ascorbic acid were combined in less than 10 μL of volume in a test tube and incubated at room temperature for 1 min to let the Cu 2+ reduce to Cu + . The mixture was then diluted with 200 μL of 25 mM Tris, 150 mM NaCl at pH 7.5 and then applied to a single well of cells in a 24-well plate for 30 min at room temperature. The reaction solution was then removed and the cells were washed thoroughly with PBS. A fluorescent dye mix of streptavidin-Alexa Fuor 555 or streptavidin-Alexa Fluor 488 at 10 μg/mL and DAPI at 10 μM in 200 μL of PBS was then applied to the cells for 15 min. The cells were then washed thoroughly with PBS and stored in PBS for imaging. For staining with Cy5, Biotinylated Alkyne was replaced with Cy5-Alkyne.

Imaging of the fluorescent labeled cells
All images were captured on an AXIO Observer microscope (ZEISS) with a ZEISS Axiocam 506 mono camera and Zen 2 Pro software. Images were captured simultaneously through the channels of Alexa Fluor 555 (or Alexa Fluor 488) and DAPI. For most images, exposure time was automatically set by Set Exposure and contrast was adjusted by Best Fit. For comparison of the results of different pretreatment conditions, such as HPSE pretreatment versus Hep III pretreatment on HS staining, same exposure and contrast adjustment parameters were used. The γ ratting was not changed except where indicated.

Cytoplasmic and nuclear extracts preparation and their pretreatment
HUVEC cells were cultured in HUVEC media (R&D system, CCM027) under 5% CO 2 . HEK293 cells were cultured in IMDM media supplemented with 5% FBS and penicillin/streptomycin. About 30 × 10 6 cells were scraped and collected by centrifugation at 2000× rmp for 5 min. The fractionation of cells was done by using NE-PER nuclear and cytoplasmic extraction reagent kit (Thermo, Cat# 78,833) following the manufacturer's instruction. In order to prevent protein degradation, protease inhibitor cocktail (Thermo, Cat# 78,429) and phosphatase inhibitor cocktail (Thermo, Cat# 78,426) were added to the buffers. The nuclear and cytoplasmic fractions were stored at −20°C until it was used. For Tn antigen synthesis, 10 μL of extracts was incubated with 1 μg each of GALNT2 and GALNT3, 10 nmol of UDP-GalNAc in 25 mM Tris, 10 mM Mn 2+ ,150 mM NaCl at pH 7.5 at 37°C for 1 h. For T antigen synthesis, 10 μL of extracts was incubated with 1 μg each of GALNT2 and GALNT3, 1 μg of C1GalT1, 10 nmol of UDP-GalNAc, 10 nmol of UDP-Gal in 25 mM Tris, 10 mM Mn 2+ ,150 mM NaCl at pH 7.5 at 37°C for 1 h. For OGA treatment, 10 μL of extracts was mixed with 10 μL 0.1 M MES at pH 5.0 and 1 μg of OGA and incubated at 37°C for 30 min.

SDS-PAGE and membrane blotting
SDS-PAGE and blotting were performed as described previously (Wu et al. 2015.

Supplementary data
Supplementary data is available at GLYCOBIOLOGY online.