Different lineages and subsets of B cells exist, each exhibiting specific phenotypic characteristics that respond differentially to TLR ligands, pathogens, and/or immunogens. In mammals, four subsets that belong either to the B-1 or B-2 lineages have been clearly defined. B-2 cells consist of two subpopulations: the more conventional follicular (FO) B cells that constitute the major subset in the spleen and trigger the formation of germinal centers and the subsequent production of plasmablasts, plasma cells, and memory B cells with high affinity Ag-binding capacities upon activation of T cell dependent (TD) antigens [reviewed in (9)]; and the marginal zone (MZ) B cells that integrate classical innate and adaptive signaling pathways to mount rapid antibody responses, particularly to blood-borne pathogens [reviewed in (10)]. Similar to MZ B cells, B-1 cells, which can be subdivided further into B1a and B1b based on their CD5 surface expression, have important innate functions such as phagocytosis and production of polyreactive natural Abs in a T cell independent (TI) manner (11, 12). The B-1 cells are predominantly located in the peritoneal cavity (13), but are also present in the spleen and other lymphoid organs at very low levels. While initially thought to lack memory B cell generation, recent data have shown that these innate-like B cells also generate memory B cells during TI immune responses [reviewed in (14–16)].

As the first vertebrate group that possesses all elements of adaptive immunity, teleost fish are able to execute immune functions comparable to that of mammals. Although clear differences exist between the structure and organization of the teleost and mammalian immune systems, functional equivalent lymphoid compartments have been reported [reviewed in (17, 18)]. Analogous to the mammalian bone marrow (BM), the teleost head kidney (HK) serves as both the major hematopoietic tissue and reservoir for long-lived plasma cells (6). In the absence of lymph nodes, teleost spleen constitutes as the main secondary lymphoid organ, where the majority of naïve B cells mature and circulate for continuous immune surveillance. In addition to the systemic lymphoid compartments, teleost peritoneal cavity also houses B cells whose development and migration pathways remain largely unexplored (19). In contrast to mammals, however, teleosts lack follicular structures and do not form distinguishable germinal centers (20). Little is still also known about the characteristics of teleost memory B cells but it appears to have a relatively low proliferation potential (6). Moreover, their systemic Ab responses rely on unswitched low-affinity IgM responses (21).

Three classes of immunoglobulins (Igs) have been identified in teleosts: IgM, IgD, and IgT (or IgZ in some species), with IgM+ being the predominant surface Ig isotype (22). IgD is usually co-expressed on the surface of teleost IgM+ B cells, although single positive IgM+ or IgD+ B cells (23) also exist. IgT+ only B cells comprise a separate lineage of fish B cells that appears to have a main role in mucosal immunity (24). Morphological and functional studies suggest that teleost B cells resemble mammalian B1 cells more than B2 cells (25, 26). In fact, it is hypothesized that mammalian innate-like B cells, characterized by high surface IgM expression (27), evolved from fish IgM+ B cells (18), with the B2 lineage emerging later as a more efficient subset that gradually acquired a dominant role in the mammalian adaptive immunity. Fish B cells exhibit both innate and adaptive immune functions (6), but whether these functions are performed by distinct B cell subsets or not is unknown. Specifically, which B cell subpopulation/s and/or lineages play an important role in protection against infection and/or immunity following vaccination are still open questions in fish immunology.

Cluster of differentiation (CD) is a system used for identifying cell surface markers for various leukocyte subpopulations, including B cells. At present, at least 371 CD proteins have been reported in mammals (28)—making immunophenotyping a rather trivial task. In contrast to the mammalian system where different lineages and subtypes of B cells can be identified and sorted with greater clarity through commercially available marker Abs, studying the dynamics of fish B cell responses has been challenging due to lack of pan and subset-specific markers. For Atlantic salmon, in particular, B cells are currently sorted from the total leukocyte population using surface Igs as sole markers, typically via the predominant IgM isotype (22, 29). While this approach has been extremely useful, the binding of Abs to surface Igs could trigger unwanted activation of the BCR, which may interfere with downstream assays. In addition, since the status of surface Ig expression of salmon B cells at various stages of differentiation (i.e., putative naïve B cells, plasmablasts, plasma cells, or memory B cells) is largely unknown, some of these subsets may not be detected during sorting and hence, will be excluded from further analysis.

To address this current limitation, we aimed to identify CD molecules than can be potentially used as pan- or subsetspecific B cell markers and, in turn, facilitate molecular, and functional investigations of the heterogeneous salmon B cell population. Additionally, we aimed to profile the salmon B cell surface proteome in order to have a better understanding of the phenotypic characteristics of teleost IgM+ B cells.

#### MATERIALS AND METHODS

#### Experimental Fish

Healthy Atlantic salmon (Salmo salar L.) QTL fish strain Aquagen standard (Aquagen, Kyrksæterøra, Norway) were obtained from the Tromsø Aquaculture Research Station (Tromsø, Norway). Fish were kept at 10◦C in tanks supplied with running filtered water, natural light and fed on commercial dry feeds (Skretting, Stavanger, Norway). Estimated weight of fish used for isolation of peripheral blood leukocytes (PBL) and subsequent sorting of IgM+ B cells for proteomics analyses was 700–900 g. Head kidney leukocytes (HKL) were collected separately from the same batch of fish. Peritoneal cavity leukocytes (PeL) and splenocytes (SpL) were collected simultaneously from another batch of smaller fish (estimated mean weight: ∼60 g).

#### Cell Culture

Atlantic Salmon Kidney (ASK) cells (30) and Salmo salar pronephros 9 (SSP-9) cells (31), derived from the major hematopietic tissue of Atlantic salmon, were grown as monolayers at 20◦C in Leibovitz (L-15) medium (Gibco, Life Technologies). ASK cell culture medium was supplemented with P/S (100 units/mL penicillin, 100µg/mL streptomycin) and 12% fetal bovine serum (FBS), while SSP-9 cell culture medium was supplemented with 50µg/mL gentamycin and 8% FBS. Five T-75 flasks were seeded with ASK or SSP-9 cells at a density of ∼2 × 106 cells per flask and collected after 72 h at 90% confluence for subsequent cell surface protein isolation.

#### Tissue Collection and Leukocyte Isolation

Blood was extracted from the caudal vein of Atlantic salmon using a vacutainer with 68 I.U. sodium heparin (Becton Dickinson) and immediately transferred into transport medium (L-15 with P/S, 2% FBS, and 20 IE/mL heparin). Spleen and HK were aseptically collected into transport medium after ensuring that all blood was drained from fish tissues. Cells from salmon peritoneal cavity were obtained by lavage and immediately stored in transport medium.

Leukocyte isolations (PBL, HKL, SpL, or PeL) were performed on Percoll gradients as described previously (32). Blood suspension was placed directly onto 54% Percoll (GE Healthcare) and centrifuged at 400 × g for 40 min at 4◦C. Spleen and HK were homogenized on 100-µm cell strainers (Falcon), loaded onto 25/54% discontinuous Percoll gradients, and centrifuged as above. Similarly, peritoneal cavity cells were loaded onto 25/54% discontinuous Percoll gradient for PeL isolation. Leukocytes at the interface were collected and washed twice in L-15 with P/S before further use.

For stimulation with lipopolysaccharide (LPS), freshly isolated PBLs were seeded in two T25 flasks (Nunclon Delta Surface ThermoFisher Scientific, 6.25 × 106 cells/flask). One flask was treated with 50µg/mL LPS (purified by Phenol extraction from Escherichia coli O111:B4, Sigma-Aldrich) diluted in Dulbecco's Phosphate Buffered Saline (DPBS; Sigma-Aldrich), while control group received only DPBS. Cells were incubated at 14◦C for 72 h before staining, sorting, and surface protein isolation as detailed below.

### Cell Staining and FACS Sorting

Total leukocytes were centrifuged at 500 × g, resuspended in PBS+ (Dulbecco PBS with 1% BSA, filter-sterilized), and stained with anti-salmon IgM (IgF1-18) (1:200 dilution) and/or anti-trout IgT (2µg/mL) monoclonal antibodies (mAbs) for 30 min. These mAbs were generously provided by Dr. Karsten Skjødt and Prof. Oriol Sunyer, respectively. Salmon anti-IgM have been shown to recognize both IgM-A and -B isotypes of Atlantic salmon (29), while trout α-IgT has been previously validated for cross-specificity with Atlantic salmon IgT (22). After two washing steps, leukocytes were incubated with isotype specific secondary Abs: IgG1-RPE (1:400 dilution) and IgG2a-APC (1:400 dilution), respectively, and viability dye FVD780 (1 µL/mL; eBioscience) in PBS+ for 20 min. All staining and centrifugation steps were done at 4◦C.

Stained leukocytes were resuspended in PBS+ at 5.0 × 107 cells/mL for sorting using the BD FACS Aria III flow cytometer (BD Biosciences). Dead cells (FVD780+) and doublets (SSC-A vs. SSC-H) were excluded from the population. Remaining cells were sorted on the basis of their forward scatter (FSC) and side scatter (SSC) profiles, and then on their IgM+ (RPE fluorescence emission) and/or IgT+ (APC fluorescence emission) surface expression. FSClow SSClow subpopulation that excludes granulocytes and myeloid cells was designated lymphoid gate. Cells outside this gate were considered "non-lymphoid" (nL). PBLs with surface IgM expression within the lymphoid gate (PBL L IgM+, **Figure 1A**) were collected in cell culture media and used as samples for surface protein isolation by biotinylation enrichment method.

For the validation of B-cell restrictive expression of candidate pan-B cell markers at the mRNA level, sorted HKL, SpL, and PeL subpopulations were used for RT-qPCR assays. Leukocytes were collected in culture either as suspension (SC) and adherent (AC) cells and stained separately as described above, and then sorted by FACS based on their FSC/SSC gating profile: lymphoid (L) vs. non-lymphoid (cells outside the lymphoid gating, nL) and their IgM and/or IgT surface expression (IgM+ vs. IgM−, IgT+ vs. IgT−). For HKLs, 4 subpopulations were obtained: SC within the lymphoid gate that was either IgM+ (HKL SC-L IgM+) or IgM− (HKL SC-L IgM−); non-lymphoid SC that was IgM− (HKL SC-nL IgM−); and non-lymphoid AC that was IgM− (HKL AC-nL IgM−) (**Figure 2A**). SpLs, which were mostly suspension cells, were sorted as lymphoid cells with either IgM+ (SpL L IgM+); IgT+ (SpL L IgT+), or IgM−IgT− (SpL L IgM−IgT−) surface expression; and non-lymphoid cells without IgM and IgT surface expression (SpL nL IgM−IgT−) (**Figure 3A**). Finally, suspension cells from PeLs were sorted as lymphoid cells expressing either IgM (PeL L IgM+) or IgT (PeL L IgT+) on their surface; and non-lymphoid cells without IgM and IgT surface expression (PeL nL IgM−IgT−) (**Figure 4A**). These HKL, SpL, and PeL subsets were sorted directly on RNAProtect Cell Reagent (Qiagen) and stored at −80◦C until RNA extraction.

# Cell Surface Protein Isolation

Cell surface proteins from Atlantic salmon cell lines and IgM+ PBLs were isolated using the Pierce R Cell Surface Protein Isolation Kit (Thermo Scientific) according to the manufacturer's protocol. ASK and SSP-9 monolayers (∼4 × 107 cells) were quickly washed twice with ice-cold phosphate buffered saline (PBS) followed by incubation with 0.25 mg/mL Sulfo-NHS-SS-Biotin in ice-cold PBS (10 mL biotin solution per flask) on a rocking platform (100 rpm) for 30 min at 4◦C. The biotinylation reaction was quenched by adding 500 µL of the provided Quenching Solution. Cells were harvested by gentle scraping, pooled, rinsed with Tris Buffered Saline (TBS), and lysed using the provided Lysis Buffer with Protease Inhibitor Cocktail (HaltTM ThermoFisher Scientific). Cells were sonicated on ice at low power using five 1 s bursts and then incubated for 30 min on ice with intermittent vortexing. The lysates were centrifuged at 10,000 × g for 2 min at 4◦C to remove cell remnants and the resulting clarified supernatant was added to 500 µL of NeutrAvidin Agarose slurry. Biotinylated proteins were allowed to bind to the NeutrAvidin by incubating for 1 h at room temperature (RT) in the closed column with end-over-end mixing on an orbital rotator. Unbound proteins were removed by centrifugation of the column at 1,000 × g for 1 min followed by repetitive washing using the provided Wash Buffer with protease inhibitor. Finally, the captured surface proteins were eluted from the biotin-NeutrAvidin Agarose by incubation with

FIGURE 2 | Restrictive gene expression of candidate pan-B cell markers in leukocytes from head kidney, a primary lymphoid organ of salmon. Suspension and adherent head kidney leukocytes (HKLs) were collected separately after 72 h in culture and subsequently sorted by flow cytometry based on cell size and granularity (FSC vs. SSC) and then surface IgM expression. Representative dot plot of the HKL subpopulations are shown in (A) with mean percentage of each fraction indicated in the graph. To ensure purity and quality of the sorted HKL subpopulations, expression of several marker genes: igd (B cell subset), mcsfr (macrophage), cd3-z2 (T cells), and cd9 (broad expression) were examined by RT-qPCR assay (B). Upon validation of sorting protocol, gene expression of cd22 and cd79a genes were subsequently determined (C). Each bar represents mean relative expression data from 3 to 4 fish ± SEM. Means with different letters are significantly different (two-tailed t-test with Welch's correction, p < 0.05).

FIGURE 3 | Restrictive gene expression of candidate pan-B cell markers in leukocytes from spleen, a secondary lymphoid organ of salmon. Freshly isolated splenocytes were sorted based on size and granularity (FSC vs. SSC) and then surface expression of IgM or IgT. Representative dot plot of the SpL subpopulations are shown in (A) with mean percentage of each fraction indicated in the graph. Cells within the lymphoid gate were sorted into IgM+, IgT+, or IgM− IgT− subsets (SpL L IgM+, SpL L IgT+, and SpL L IgM− IgT−, respectively). IgM− IgT− cells outside the lymphocyte gate (SpL nL IgM− IgT) was also collected. Expression of cd22 and cd79a genes were subsequently determined in the different splenocyte subpopulations (B). Each bar represents mean relative expression data from three pooled samples (five fish per pooled sample) ± SEM. Means with different letters are significantly different (two-tailed t-test with Welch's correction, p < 0.05). Due to very low cell frequency, sorted IgT data was obtained from a pool of 15 fish.

400 µL SDS-PAGE Sample Buffer (62.5 mM Tris-HCl pH 6.8, 1% SDS, 10% glycerol) containing 50 mM dithiothreitol (DTT) for 1 h at RT on an orbital rotator. The eluted proteins, representing the cell surface proteins, were collected by column centrifugation at 1,000 × g for 2 min.

For surface protein isolation in FACS-sorted IgM+ PBLs, cell suspension was centrifuged at 500 × g for 5 min at 4◦C, washed twice with 3 mL ice-cold PBS to remove residual FBS, and then resuspended in 0.5 mL ice-cold PBS prior to biotinylation (1 × 106 IgM+ cells/mL biotin solution) as described above.

To maximize the quantity of surface proteins for subsequent mass-spectrometry analysis, eluted proteins were concentrated using the PierceTM Protein Concentrator PES 3K MWCO (ThermoFisher Scientific) following the manufacturer's protocol.

#### Mass Spectrometry Analyses

Surface proteins isolated from the ASK and SSP-9 cell lines, naïve IgM+ PBLs, and control vs. LPS-stimulated IgM+ PBLs were subjected to proteomics analyses. Concentrated surface protein samples were directly lysed in 1× NuPAGE LDS sample buffer (ThermoFisher Scientific), heated at 70◦C for 10 min, and then fractionated by SDS-PAGE for 5 min at 200 V followed by Coomassie blue staining (SimplyBlue SafeStain; Thermo Fisher Scientific). Protein bands were cut and subjected to in-gel trypsin digestion before analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS).

Gel slices were subjected to in-gel reduction, alkylation, and protease digestion with 6 ng/µl trypsin (V5111; Promega) (33). OMIX C18 tips (Varian, Inc., Palo Alto, CA, USA) were used for sample cleanup and concentration. Peptide mixtures containing 0.1% formic acid were loaded onto a Thermo Fisher Scientific EASY-nLC 1,000 system and EASY-spray column (C18; 2µm; 100 Å; 50µm; 50 cm). Peptides were fractionated using a 2–100% acetonitrile gradient in 0.1% formic acid over 50 min at a flow rate of 250 nl/min. The separated peptides were analyzed using a ThermoFisher Scientific Q-Exactive mass spectrometer.

Raw files from the QExactive were analyzed using the Proteome Discoverer 2.2 software (Thermo Fisher). The fragmentation spectra was searched against the NCBI nonredundant (nr) Salmo salar 2017\_1 database using an in-house Mascot server (Matrix Sciences, UK). Peptide mass tolerances used in the search were 10 ppm, and fragment mass tolerance was 0.02 Da. Peptide ions were filtered using a false discovery rate (FDR) set to 5 % for peptide identifications.

Relative protein quantitations were done using precursor ion intensities in Proteome Discoverer 2.2. To determine the relative protein amount in each sample, Exponentially Modified Protein Abundance Index (emPAI) values were extracted from mascot search results.

#### RNA Isolation and cDNA Synthesis

Total RNA from sorted cells was extracted using either the RNeasy R Mini (≥500,000 cells) or Micro (< 500,000 cells) Kits (Qiagen), with in-column DNAse I treatment (Qiagen) according to the manufacturer's protocol. For sorted HKL, SpL,

FIGURE 4 | Restrictive gene expression of candidate pan-B cell markers in peritoneal cavity leukocytes of salmon. Freshly isolated peritoneal leukocytes were sorted based on size and granularity (FSC vs. SSC) and then surface expression of IgM or IgT. Representative dot plot of the PeL subpopulations are shown in (A) with mean percentage of each fraction indicated in the graph. PeL subsets included IgM+ or IgT+ cells within the lymphoid gate (PeL L IgM + and PeL L IgT+, respectively) and IgM− IgT− cells within the non-lymphoid gate (PeL nL IgM− IgT−). Expression of cd22 and cd79a genes were investigated in peritoneal leukocyte subpopulations (B). Due to low cell frequency, PeL L IgM+ and PeL L IgT+ bars represent the relative expression data from pooled samples of 15 fish. Relative expression data for PeL nL IgM− IgT− was obtained from the mean of 3 pooled samples (5 fish per pooled sample) ± SEM.

and PeL subsets, an extra centrifugation step at 5,000 × g for 10 min was performed to remove the RNAProtect Cell Reagent before proceeding to RNA extraction of the cell pellet. RNA yield and purity were determined using Nanodrop ND-1,000 Spectrophotometer (Nanodrop Tec. Wilmington, DA, USA) and stored at −80◦C. Isolated RNA (75–150 ng) was reverse transcribed into cDNAs in 20 µl reaction volumes using the QuantiTect Reverse Transription Kit (Qiagen) following the manufacturer's protocol. Resulting cDNA was diluted 1:5 and stored at −20◦C until further use.

#### Gene Expression Analyses

Expression levels of RNA transcripts of selected genes were analyzed by RT-qPCR on an ABI Prism 7500 FAST Cycler (Applied Biosystems). cDNAs from sorted HKL subpopulations (2.5 ng total cDNA input) was used per qPCR reaction (20 µL final volume) using the Fast SYBR R Green Master Mix (Applied Biosystems). For SpL and PeL subsets, total cDNA input was 1.5 ng. Information for all primers used is listed in **Table 1**. The efficiency of the amplification was determined for each primer pair using serial 2-fold dilutions of pooled cDNA, and only primer pairs with efficiencies between 1.90 and 2.10 were used. Each sample was measured in duplicate under the following conditions: 95◦C for 20 s followed by 40 cycles of 95◦C for 3 s and 60◦C for 30 s.

The expression of individual genes was normalized to that of Atlantic salmon elongation factor 1αβ (EF1αβ) and presented as relative expression using the 2−1Ct method, where 1Ct is determined by subtracting the EF-1α value from the target Ct as described previously (35, 36). Negative controls with no template were included in all experiments. A melting curve for each PCR was determined by reading fluorescence every degree between 60 and 95◦C to ensure only a single product had been amplified.

Statistical analyses of RT-qPCR data were performed in GraphPad Prism 5.04 using a two-tailed student t-test with Welch's correction when the F test indicated that the variances of both groups differed significantly. The differences between the mean values were considered significant when p ≤ 0.05.

#### RESULTS

Our mass spectrometry approach was able to identify a combined dataset of 3,140 proteins from our surface proteinenriched salmon B cell and/or HK cell line samples (full list of identified proteins is available at https://doi.org/10.18710/ JU3DWE), of which 21% were deemed to be membrane proteins by GO-annotation or transmembrane predictions. This percentage, however, may have been underestimated due to incomplete annotation in some Atlantic salmon proteins. We subsequently focused on surface protein orthologs that were previously reported as part of the CD molecules in mice and/or humans.

TABLE 1 | Primers used for SYBR green qPCR assays.

aUsed qPCR primers previously designed by Tadiso et al. (34).

#### CD Proteins Exclusively Identified From Atlantic Salmon HK Cell Lines

A total of 38 and 39 CD proteins were identified from ASK and SSP-9 cells, respectively (**Figure 1B**). Nine CD proteins were detected only in ASK cells, while 11 CD proteins were detected only in SSP-9 cells. Twenty-four CD proteins were shared between these two cell lines.

#### CD Proteins Common to Atlantic Salmon B Cells and HK Cell Lines

In agreement with the established broad expression of CD81 in mammals (37), this multifunctional tetraspanin protein was detected in high quantities in all proteomics samples (**Table 2**). Similarly, ubiquitously expressed transmembrane glycoproteins (38–40), CD98 and CD147 were detected in salmon ASK, SSP-9, and IgM+ peripheral B cells. CD147 can bind directly to CD98, which associates with integrins, which is in turn involved in cell adhesion, fusion, proliferation, and growth (41). CD98 was more abundant in LPS-stimulated B cells than control (relative abundance > 2.00; **Table 2**).

The tetraspanin CD63 and transmembrane protein CD156c, also known to be expressed in many cell types (42, 43), were identified in both ASK and B cells. CD63 functions as a transport regulator implicated in intracellular protein trafficking (44). It has been shown to down-regulate CD184 (CXCR4) by serving as a molecular target of the transcriptional repressor Bcl6 (45). CD156c (ADAM10) functions as a molecular scissor that cleaves the extracellular regions of its transmembrane target proteins, which is an important mechanism for the regulation of leukocyte development and function (43).

The transmembrane protein receptor CD40 was detected in both SSP-9 and IgM+ B cells. This member of the TNFR superfamily has been initially characterized on B cells and subsequently found to be expressed on antigen-presenting cells, and many other immune and non-immune cells (46). The binding of CD40 to its CD154 ligand (CD40L) regulates a wide spectrum of cellular processes, including the activation, proliferation, and differentiation of B cells (47). CD40 exhibited the highest increase in salmon B cell surface expression upon stimulation with a TI antigen, with relative abundance value of 8.60 in LPS-treated vs. control B cells (**Table 2**).

### CD Proteins Exclusively Identified From Atlantic Salmon B Cells

Out of the 21 total CD molecules Identified from salmon IgM+ PBLs, 15 were found to be present in these B cell samples only and were not detected in the two salmon hematopoietic organderived cell lines (**Figure 1B**). The receptor-like protein tyrosine phosphatase, CD45, reported to be one of the most abundant cell surface glycoproteins expressed on mammalian leukocytes (48), was the most abundant protein detected in the salmon B cell samples with a relative quantitation value of 1.79 as estimated by emPAI (**Table 2**) based on protein coverage by the peptide matches in the database search result (49).

#### B Cell-Restricted Proteins (CD22 and CD79A)

Two surface proteins (CD22 and CD79A) that previously have been used as B cell-exclusive markers in mammals were identified in the salmon B cell samples. CD22 is a transmembrane glycoprotein that belongs to the sialic acidbinding immunoglobulin-like lectins (SIGLEC) family that serves as a BCR co-receptor (50, 51). In mammals, its expression is predominantly exclusive to subsets of mature B cells, with surface expression appearing simultaneously with surface IgD and is subsequently lost on plasma cells (52–54). CD22 is a wellestablished regulator of innate and adaptive B cell responses in mammals [reviewed in (55)]. One of the main functions of CD22 is to down-regulate the activation threshold of BCR through its association with tyrosine phosphatases and other signaling molecules (51, 56). In addition to BCR signaling, several initial studies in mice have shown that CD22 also regulates TLR

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Continued

**87**

bBelow detection threshold in LPS-stimulated

cBelow threshold level for relative abundance ratio.

dDetected in 1 of 2

naïve/control-stimulated

 B cell samples.

PSM, aNo emPAI value for proteins with weak positive hits.

peptide-spectrum

 match; emPAI, exponentially

 modified protein abundance index.

 B cell sample.

signaling and the survival of B cells (55). However, it has been suggested that CD22 likely functions differently between innatelike B-1 and conventional B-2 cells since CD22 is differentially regulated after BCR-mediated and -independent activation in these B cell lineages (57).

CD79A, on the other hand, is an integral membrane protein belonging to the Ig gene superfamily that associates with membrane Ig on B cell surface and, together with CD79B, forms the signal transduction region of the B cell antigen receptor (BCR) complex (58, 59). Due to their importance in B cell development and induction of B cell activation, CD79 proteins are expressed in virtually all subsets of B cells (60), from the very early stages of B cell development to plasma cells (61–65).

#### Tetraspanins (CD9 and CD53)

Of the four tetraspanin proteins that were identified by proteomics, detectable quantities of CD9 and CD53 were only present in salmon B cells, despite the reported surface expression in different hematopoietic cell types (66, 67) and/or endothelial cells (68) of their mammalian homologs. This protein family consists of four-span transmembrane proteins that have been described as "master organizers" of the plasma membrane (69) and "molecular facilitators" (42) in a variety of biological processes.

#### β2 Integrins (CD11a, CD11c, and CD18)

CD18 (ITGB2), CD11a (ITGAL), and CD11c (ITGAX) that were detected on salmon B cell surface belong to the β2 integrin family of adhesion and signaling molecules. Integrin β chain subunit CD18 can pair with one of four alpha chain subunits (CD11a, CD11b, CD11c, or CD11d) to form the CD11/CD18 complex that play important roles in the recruitment of immune cells to sites of inflammation, cell–cell contact formation, and regulation of downstream effects on cellular signaling (70). In mammals, these β2 integrin complexes are found exclusively on leukocytes, particularly myeloid cells and NK cells, and to a lower expression level, B and T lymphocytes.

#### Chemokine Receptors: CD184, CD185, and CDw199

Three chemokine receptors, CD184 (CXCR4), CD185 (CXCR5), and CDw199 (CCR9) were identified in Atlantic salmon B cells. These are G-protein coupled, seven-transmembrane receptors with CD184 and CD185 classified into the C-X-C (alpha) class and CDw199 into the CC (beta) class. CD184 and CD185 are known to have broad expression across many cell types, including lymphocytes, endothelial, epithelial and hematopoietic stem cells (71). Similarly, CDw199 is expressed in different leukocyte subpopulations such as macrophages, dendritic cells, T cells, and B cells (72–75). These chemokine receptors are important in the migration, maturation, and function of B cells (76–78).

#### Other Surface Proteins (CD68, CD84-H1, CD87, and CD282)

In addition to members of the protein families described above, several other surface proteins were found present on salmon B cells. These included CD68, CD84-H1, CD87, and CD282.

CD68, the human homolog of macrosialin, is a highly glycosylated type I transmembrane protein belonging to the lysosomal-associated membrane protein (LAMP) family of glycoproteins (79). While this protein was initially regarded as a macrophage marker (80), CD68 expression on other hematopoietic and non-hematopoietic cell types have been subsequently reported, including B cell lines (81–83).

CD84-H1 (a.k.a. CD2-F10 and SLAM9) belongs to the signaling lymphocyte activation molecule (SLAM) family of cell surface receptors within the immunoglobulin superfamily (84, 85). This protein has been shown to be widely expressed in many immune cells of humans, including B cells (84, 85). However, the exact function of CD84-H1 in B cells is still unclear. In general, SLAM proteins are said to contribute to the generation of long-term humoral immune response (86, 87).

CD87, also called urokinase plasminogen activator receptor (uPAR), is a surface glycoprotein that mediates a wide range of biological processes beyond plasminogen activation, including cellular adhesion, migration, chemotaxis, and proliferation [reviewed in (88, 89)]. In humans, CD87 is known to be highly expressed on monocytes and granulocytes, particularly on mature cells (90). As such, it is used as a surface marker for terminal granulocytic maturation (91). Resting B and T lymphocytes and cell lines of lymphoid lineage do not seem to express CD87 (90, 92), although surface expression has been reported on activated T cells and NK cells (90). Next to CD45 and CD18, salmon CD87 had the highest emPAI obtained in naïve B cells, with relative abundance comparable between control and LPS-activated B cell samples.

Another surface protein detected on salmon B cell surface was CD282, more commonly known as toll-like receptor 2 (TLR2), a membrane-bound protein that recognizes the evolutionarily conserved bacterial lipopeptides (93). In humans, surface expression of CD282 is found to be highest on innate cells such as monocytes and granulocytes (94). Detectable level of CD282 expression has also been observed on activated but not resting T cells (95, 96), as well as on surface of different B cell subpopulations, albeit mostly at low level (94, 97, 98).

# B Cell-Restrictive Gene Expression of Candidate Salmon Pan-B Cell Markers

Given the known B cell-exclusive surface expression of their mammalian homologs, CD22 and CD79A were shortlisted as potential pan-B cell markers for salmon. In the absence of definitive Abs against these candidate markers, we resorted to qPCR assays for validating their B cell restrictive expression using leukocyte subsets from different lymphoid organs.

Sorted cells from HK (**Figure 2A**) were used as the main source of different leukocyte subpopulations for the RT-qPCR validation assays. As the major hematopoietic organ in teleost, HK consists of a heterogeneous mixture of leukocytes belonging to the lymphoid and myeloid lineages (99). HKL subsets were first examined for gene expression of known markers for B cells, macrophages, and T cells in order to confirm the nature of cells present in each subset, as well as to ensure that no crosscontamination of cell subsets occurred during FACS sorting.

As expected, only the lymphoid subsets had detectable igd expression, with transcript levels highest in the HK suspension cell IgM+ lymphoid subset (HKL SC-L IgM+, **Figure 2B**), in accordance with the reported dual IgM and IgD expression in majority of naïve mature peripheral B cells of mammals [reviewed in (100–102)] and trout (103). Significant albeit much lower igd expression was also observed in HK suspension cell IgM− lymphoid subset (HKL SC-L IgM−), which could suggest the presence of IgD+ only B cells in naïve HKLs. By contrast, the suspension and adherent IgM− non-lymphoid subsets (HKL SC-nL IgM− and HKL AC-nL IgM−, respectively), assumed to consist of myeloid cells (macrophages, monocytes, and/or granulocytes), had very low to non-existent igd expression.

The HK suspension cell IgM+ lymphoid subset had no detectable transcription of the macrophage marker, mcsfr, which was expressed in high levels in the putative myeloid cell subsets, HKL SC-nL IgM− and HKL AC-nL IgM−. Detectable levels of mcsfr transcripts was present in the HK suspension cell IgM− lymphoid subset, which could indicate the presence of contaminating macrophages in this leukocyte subpopulation. Similarly, no detectable cd3-z2 gene expression was observed in the HK suspension cell IgM+ lymphoid subset, while the remaining HKL subsets exhibited relatively low expression of this T cell marker.

Additionally, to ensure that any observed absence of detectable transcripts was not due to poor cDNA/RNA quality of our samples, the mRNA levels of the broadly expressed CD9 tetraspanin were also determined in the sorted HKL subpopulations. In general, relative expression of cd9 was comparably high across all HKL subsets, with the HK suspension cell IgM− non-lymphoid subset having the most expression.

The gene expression of our candidate B cell markers was subsequently investigated. HK suspension cell IgM+ lymphoid subset with a putative B cell phenotype (i.e., significant gene expression of igd and cd9, but not mcsfr and cd3-z2) exhibited the highest cd22 and cd79a expression (**Figure 2C**). By contrast, very low to non-existent mRNA levels were observed in both the suspension and adherent IgM− non-lymphoid subsets (HKL SnL IgM− and HKL AnLIgM−, respectively), consisting mostly of cells from the myeloid lineage and some T lymphocytes as per mcsfr and cd3z gene expression profile. Low but detectable levels of cd22 and cd79a were also observed in the HKL SL IgM− subset, likely due to the presence of IgD+ and IgT+ B cells in this leukocyte subpopulation.

To check whether the apparent B cell restrictive expression of cd22 and cd79a is consistent across different B cells from different lymphoid sources, we also performed the same gene expression assay in leukocyte subsets from spleen (**Figure 3A**) and peritoneal cavity (**Figure 4A**). IgT subpopulation was also added in the analysis to determine cd22 and cd79a expression in a non-IgM B cell isotype. Similar to what was observed in HKLs, highest and lowest cd22 and cd79a mRNA levels were obtained in the spleen IgM+ lymphoid (SpL L IgM+) and IgM− nonlymphoid subsets (SpL nL IgM−), respectively (**Figure 3B**). High mRNA expression for these candidate markers was also found in the spleen IgT+ lymphoid subset (SpL L IgT+) as well as in the IgM− IgT− lymphoid subset (SpL L IgM− IgT−), which could contain IgD only B cells.

For PeLs, comparable levels of cd22 transcription were observed between IgM+ (PeL L IgM+) and IgT+ (PeL L IgT+) lymphoid subsets, while very low cd22 gene expression was obtained in the PeL IgM− IgT− non-lymphoid subset (PeL nL IgM− IgT−) (**Figure 4B**). Gene expression of cd79a, on the other hand, was higher in the IgM+ than IgT+ peritoneal lymphoid cells. Lowest cd79a expression was observed in the IgM− IgT− non-lymphoid subset of the peritoneal leukocytes (PeL nL IgM− IgT−).

#### DISCUSSION

To our knowledge, this is the first report on the profiling of salmon B cell surface protein repertoire. Although proteomics has been employed in some investigations of fish immune responses to various infections [reviewed in (104)], it is not commonly used to characterize the surface protein expression of specific immune-related cells in teleosts. A previous proteomics study on Atlantic salmon focused on profiling changes in fish serum proteins following infection with salmonid alphavirus (105). Our approach focused on B cells and was useful in the identification of 21 CD molecules from salmon IgM+ B cells. The relatively limited number of CD proteins identified could be partially explained by the initial low number of B cells in the starting material (3 × 106 viable IgM+ B cells after 72 h in culture) used in the surface protein isolation. In addition, despite being one of the popular choices for cell surface proteome profiling, the biotinylation technique employed for the enrichment of plasma membrane proteins may not be the most effective method for isolating glycosylated proteins (106). Since majority of cell surface proteins are glycosylated (107), many surface glycoproteins may not have been included in our mass spectrometry samples.

Peripheral blood was used as source of salmon B cells for proteomics due to higher total leukocyte yield [i.e., 15× and 4× more total leukocytes than the spleen and the HK, respectively (108)] and the abundance of IgM+ B cells in this compartment (22). For comparison, surface proteins from two Atlantic salmon head kidney cell lines, ASK and SSP-9, were also identified. Although the exact cell composition of these hematopoietictissue derived cell lines is unknown, these seem to include cells from the myeloid lineage based on their respective proteomics profile. Given its epithelial-like morphology and previously reported gene expression profile (31), SSP-9 is likely comprised of macrophage-like cells. Specifically, majority of the identified SSP-9-exclusive surface proteins (CD2, CD34, CD74, CD151, CD205) are associated with expression on a macrophage subset with antigen-presenting capacity (109–113). Detection of CD203c, a known basophil and mast cell marker in humans (114), suggest that SSP-9 may contain granulocytes.

# Salmon IgM+ B Cell Surface Proteome

All the surface proteins identified from our salmon B cell samples have been previously detected on the surface of mammalian B cells, except for CD87. In teleost, only a few of these B cellassociated proteins have been studied so far. Constitutive gene expression of tetraspanins cd9 and cd63 have been reported in sorted IgM+ B cells of trout from different immune organs (115). Surface expression of CD22 has also been shown in PBLs of tongue sole (116).

In keeping with their established roles in B cell activation, CD40 (117) and CD98 (118) surface expression were significantly higher in LPS-stimulated IgM+ B cell samples. Co-expression of CD40 and IgM+ has been established on B cell surface of zebrafish, with significant up-regulation of CD40 similarly observed following LPS treatment (119). In addition, modest increase in CD40 transcripts has been reported for Atlantic salmon IgM+ B cells in the presence of another TLR agonist, CpG oligodeoxynucleotides (22).

Surprisingly, CD87, which has been reported to be absent on surface of resting B lymphocytes and B cell lines of mammals (90, 92), was detected in our naïve salmon IgM+ B cell samples. It should be noted that CD87 acts as a ligand for β2 integrins such as CD18 and CD11a/c identified on salmon B cells, and thus usually found in close association with these protein complexes on leukocytes (120). CD87 has been demonstrated to mediate cell-cell adhesion by interaction with integrins on the same as well as apposing cells (121). Hence, the CD87 proteins detected in our proteomics experiment may be an artifact from a CD87-β2 integrin complex formed by trans-interaction of salmon B cells with CD87-expressing monocytes or granulocytes. It is unlikely that the proteins were contributed directly by contaminating monocytes or granulocytes since the samples were checked for purity (>98% IgM+ PBLs) before surface protein isolation. Alternatively, it is also possible that salmon, in contrast to mammals, express CD87 on their B cell surface.

Peripheral blood provides the means for cells to move systemically within the animal body; hence, one would expect a mixture of circulating B cell subsets in this compartment. Surface detection of chemokine receptors CXCR4, CXCR5, and CCR9 important in trafficking naïve B lymphocytes (76) seem to suggest that our peripheral IgM B cell population is comprised of a migrating population of B cells from different lymphoid compartments. In humans, the majority of peripheral B cells are of the conventional B-2 cell type bearing both membrane IgM and membrane IgD, which accounts for about 10% of total PBLs (122). Given the current technical constraints, it was not possible to further sort the largely undefined subsets of the salmon IgM+ peripheral B cell subpopulation.

 Thus, it is possible that our LPS-treated peripheral B cells contained some differentiating IgM+ plasmablasts, plasma cells, or memory B cells. However, none of the known markers for these differentiated B cells [i.e., CD27 for memory B cells (125), CD138 for plasma cells (126)] was identified in the stimulated B cell samples. Based on previous studies in trout, this can be partially explained by the relatively short stimulation period (72 h incubation in culture) used in our study. In naïve trout PBLs, significant antibody secreting cell response is observed only after 4 days of LPS stimulation using 4 times higher dose, with peak responses occurring by Day 7 in culture (127). In addition, memory B cell responses to TI and TD antigens are observed only after 4–7 days of in vitro re-stimulation of PBLs from previously immunized trout (108).

It should be emphasized that several other mammalian pan-B cell and subset markers known to be encoded in the Atlantic salmon genome were not detected in our salmon IgM+ B cell samples. Failure to detect a particular surface protein should be interpreted with caution due to previously indicated technical limitations of our experimental approach or their presence at low frequency in our heterogeneous pool of IgM+ B cell subpopulations. Moreover, it should be noted that our shortlist of salmon CD proteins was based on their mammalian counterparts. Other surface proteins that were detected exclusively in the IgM+ samples but without homologs or are not classified as CD molecules in mammals were not included in this list. Further investigation of the "non-CD" surface proteins is therefore needed in order to determine whether or not these can serve as unique B cell markers in salmon.

# Identification of CD22 and CD79A as Potential Salmon B Cell Markers

Due to lack of access to antibodies against salmon IgD and myeloid markers, our analysis was constrained to leukocyte subpopulations sorted by cell size and granularity and subsequent positive selection for IgM+ or IgT+ cells, representing independent salmon B cell lineages. Despite this clear limitation, our current sorting protocol is still a valid useful tool in studying the different salmon leukocyte populations as evidenced by the results of our qPCR validation assays using different leukocyte markers.

In general, cd22 vs. cd79a gene expression patterns of the different leukocyte subsets were comparable across different lymphoid organs. Highest relative expression were observed in all IgM+ B cell subsets, while very low to below detectable level of expression were found in IgM−/IgT− non-lymphoid subset (likely consisting of myeloid cells). Relatively lower but significant level of expression was also found in non-IgM subsets within the lymphoid gate, which likely consist of either a mixed population of IgT+ or IgD+ only B cells (i.e., HKL SC-L IgM−) or IgD+ only B cells (i.e., SpL L IgM− IgT−). While generally regarded as B cell-exclusive proteins (52, 128), it is important to note that mammalian CD22 and CD79A have also been reported to be expressed on the surface of some non-B cell populations, including T cells (129) and various myeloid cells (130–133). However, this is likely not the case for Atlantic salmon given the negligible transcript levels of cd22 and cd79a in all the myeloid-containing leukocyte subsets tested.

Although mRNA levels do not necessarily correlate directly with surface protein expression, gene expression profiles of salmon cd22 and cd79a clearly showed that the B cell exclusivity of our candidate CD molecules extend down to the level of transcription. This B cell-restrictive expression was consistent across different lymphoid compartments (peripheral blood, head kidney, spleen, peritoneal cavity) and different Ig isotypes (IgM and IgT), thus providing strong support to the potential of CD22 and CD79A as pan-B cell markers for salmon.

Extensive gene duplications in the Atlantic salmon genome (134, 135) should be taken into account in finding appropriate B cell markers. Specifically, Atlantic salmon encodes an unusually high number of CD22-like paralogs and isoforms (**Supplementary Table 1**) that could have different regulatory expression and conformation on B cells. Interestingly, peptide sequences specific to only one CD22 paralog was detected on the salmon B cell surface in our mass spectrometry analysis. Based on our qPCR assay, mRNA expression of this particular variant was also specific in salmon B cells. In humans, a CD22 molecule with a different conformation to that found on B cells has been detected on basophils (130). Whether other CD22 variants/isoforms are also expressed in other subpopulations of salmon leukocytes, or in specific subsets of salmon B cells, is still unknown, but is beyond the scope of this study. For simplicity, the particular CD22 paralog (XP\_014021065.1) identified in this study was referred as CD22.

#### Other Potential B Cell Markers

CD45, the most abundant surface protein identified in our salmon B cell samples, exists in different alternative splicing isoforms, which are expressed in cell-type specific patterns on functional subsets of mammalian lymphocytes (48). In mice, a long isoform of CD45 called B220 (136) has been used as a pan B-cell marker due to its specific expression throughout stages of B cell development, including entry into the memory B cell pool (137). A similar long CD45 isoform (CD45RABC) has been identified in human B cells (96), which has been used as marker for certain human B cell subsets (138). This B-cell specific CD45 isoform in mammals consists of all 33 exons of the CD45 gene (139). Atlantic salmon genome encodes for seven CD45 transcript variants in Chromosome 10 (**Supplementary Table 1**), with alternate splicing of three exons (4, 5, 6) producing six CD45 isoforms [GenBank Assembly Accession No. GCA\_000233375.4 (135)]. Given that all exons are present in the B cell-specific isoform, it was not possible to determine whether the long CD45 isoform was the only isoform detected on salmon B cell surface. Hence, further investigation for the presence of other CD45 isoforms in sorted salmon B cell subpopulations (i.e., qPCR assays using primers specific for the other splice variants) is still needed before its potential as another salmon pan-B cell marker can be fully appreciated.

Several other CD molecules identified on salmon B cell samples can be explored for their potential in discriminating specific B cell subsets despite their non-exclusive B cell surface expression. Murine CD9 is expressed on the surface of innatelike B cells and plasma cells, but not on naïve conventional B2 cells (140, 141). In our proteomics data, CD9 was detected in high abundance in all samples of salmon IgM+ peripheral B cells but not in either of the two salmon head kidney cell lines. This implies that the salmon IgM+ peripheral B cell subpopulation are comprised of cells with significantly high expression of this protein. In rainbow trout, cd9 mRNA levels are similar in IgM+

and IgM− B cells from blood and HK (115). In agreement with this, comparable levels of cd9 expression was also observed in the IgM+ and IgM− fractions of our sorted HKL lymphoid cells, but highest constitutive gene expression was still found in the myeloid fractions. Thus, while CD9 cannot be used as the sole and primary marker for salmon B cells, its potential for identifying specific B cell subsets should be explored further.

Other potential B cell subset markers are the CD11 β2 integrins. In contrast to mammals wherein four β2 integrins have been identified, Atlantic salmon genome encodes only two: CD11a and CD11c. Both of these proteins were detected in our salmon IgM+ B cell samples, which could suggest their potential use as markers to functionally-equivalent B cell subsets in mammals. High surface CD11a expression has been associated with a new subpopulation of IFN-γ-secreting innate B cells (142). Expression of CD11c has also been recently used as marker for distinct B cell subsets in mice and humans (143, 144), including CD11clow-expressing plasmablasts that predominantly secrete Ag-specific IgM antibodies in a T cell-independent manner (145) and CD11c+ 'atypical memory B cells' (144).

Interestingly, CD11b, which is used as a marker to differentiate B1 cells that reside in the peritoneal cavity and those that recently migrated into the spleen (146), has not been detected until present. Among salmonids, only coho and Chinook salmon have CD11b-like protein recorded in the sequence database. However, the salmonid sequences of CD11c (ITGAX) is very similar to that of CD11b (70). In fact, Atlantic salmon CD11c (XP\_014014772.1) has 70 and 90% homology with CD11c-like proteins of coho (XP\_020308950.1) and Chinook (XP\_024269535.1) salmon, respectively. Similarly, CD11d, which is only found in coho (XP\_020334852.1), has 95% homology with Atlantic salmon CD11a (XP\_014032228.1). At this point, it is unknown whether Atlantic salmon CD11c-like and CD11a-like proteins have overlapping functions with the mammalian CD11b and CD11d proteins, and whether expression patterns of these mammalian B cell subset markers are similar to their ancestral counterpart in teleosts.

# Salmon IgM+ B Cell Surface Phenotype Is Consistent With Innate-Like B Cells of Mammals

It is worthy to note that several of the surface proteins (CD9, CD11a, CD11c) identified on salmon IgM+ B cells in high abundance are associated with innate-like B cells in mice and humans. CD22, one of the identified potential salmon B cell marker in this study, is also known to be expressed the highest in MZ B cell precursors out of any mammalian B cell subset (147). Additionally, detection of CD282 (TLR2), which has been previously shown to be expressed higher in naïve innate-like B cells than conventional B2 cells (97), implies a possible function of salmon IgM+ peripheral B cells in TI-responses. Altogether, these are consistent with a salmon IgM+ B cell phenotype closer to innate-like B cells (B1 and MZ B2) than conventional B2 cells in mammals. This supports the previously proposed B cell evolution hypothesis (18) which suggests that teleost IgM B cells are the ancestors of the innate-like B cells of mammals (25, 148). Whether these innate-like B cell-associated proteins detected from our B cell samples are evenly expressed on the surface of all salmon IgM+ B cells or only expressed at very high levels on certain sub-populations, is a question that warrants further investigations. This can be determined upon availability of the necessary immunological tools and antibodies to analyze the frequency and level of their surface expression.

Speculations regarding the possible characteristics of salmon IgM B cell populations based solely on pre-conceived notions of the surface phenotype, function, and anatomical distribution of their mammalian counterparts should come with a caveat. Indeed, the conservation of protein functions between mammals and teleosts for many of the B cell-associated CD molecules identified in this study has to be established. Therefore, subsets comprising the salmon IgM+ B cells need to be better defined, in order to facilitate further functional studies of these individual surface proteins.

#### SUMMARY AND CONCLUSION

In summary, our salmon B cell proteomics approach provide novel information on the surface phenotype of salmon IgM B cells as well as some evolutionary insights in reference to their mammalian counterparts. While possible exclusion of several glycosylated and/or less abundant proteins cannot be discounted due to technical limitations of the protocols used, our detection of 21 CD molecules remains a significant advancement in profiling the salmon B cell surface proteome. In addition, identification of CD22 and CD79A as potential pan-B cell markers represents a considerable positive step toward salmon B cell marker development. Further investigation and evaluation of the salmon CD molecules identified in this study would improve our understanding of B cell dynamics in salmon in the presence of TI and TD antigens during immunostimulation, pathogen infection, or vaccination.

#### ETHICS STATEMENT

The authors confirm that the experimental protocols used for the live fish experiments were based on the Animal Welfare Act

#### REFERENCES

(https://www.regjeringen.no/en/dokumenter/animal-welfareact/id571188/) and performed in accordance with relevant guidelines and regulations given by the Norwegian Animal Research Authority.

#### AUTHOR CONTRIBUTIONS

MP performed most of the experimental work (leukocyte isolation, FACS sorting, surface protein isolation, qPCR analyses) and wrote the manuscript. J-AB was responsible for the mass spectrometry analyses. LT performed RNA extraction and cDNA syntheses. IJ and JJ collaborated in obtaining funding, helped designed the experiments, and reviewed the manuscript.

#### FUNDING

This work was supported by the Aquaculture program of The Research Council of Norway (Grant No. 254892): Multiple routes to B cell memory in Atlantic salmon and UiT The Arctic University of Norway. The publication charges for this article have been funded by a grant from the publication fund of UiT The Arctic University of Norway.

#### ACKNOWLEDGMENTS

The authors wish to thank Dr. Karsten Skjødt and Prof. Oriol Sunyer for generously providing the mAbs for sorting IgM and IgT B cells. Toril Anne Grønset, Shiferaw Jenberie, Guro Strandskog, Mikael Fjeld Wold, and Morten Bay Styrvold are also acknowledged for their excellent technical assistance (processing of mass spectrometry samples, cell isolation).

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2019.00037/full#supplementary-material

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**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Peñaranda, Jensen, Tollersrud, Bruun and Jørgensen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Comparative Study of Immune Reaction Against Bacterial Infection From Transcriptome Analysis

#### Shun Maekawa1 , Pei-Chi Wang1,2 \* and Shih-Chu Chen1,2,3,4 \*

*1 Department of Veterinary Medicine, College of Veterinary Medicine, National Pingtung University of Science and Technology, Pingtung, Taiwan, 2 Southern Taiwan Fish Disease Centre, College of Veterinary Medicine, National Pingtung University of Science and Technology, Pingtung, Taiwan, 3 International Degree Program of Ornamental Fish Technology and Aquatic Animal Health, International College, National Pingtung University of Science and Technology, Pingtung, Taiwan, 4 Research Center for Animal Biologics, National Pingtung University of Science and Technology, Pingtung, Taiwan*

#### Edited by:

*Hetron Mweemba Munang'andu, Norwegian University of Life Sciences, Norway*

#### Reviewed by:

*Ming-Wei Lu, National Taiwan Ocean University, Taiwan Syarul Nataqain Baharum, National University of Malaysia, Malaysia*

#### \*Correspondence:

*Pei-Chi Wang<EMAIL_ADDRESS>Shih-Chu Chen<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Comparative Immunology, a section of the journal Frontiers in Immunology*

Received: *29 October 2018* Accepted: *17 January 2019* Published: *05 February 2019*

#### Citation:

*Maekawa S, Wang P-C and Chen S-C (2019) Comparative Study of Immune Reaction Against Bacterial Infection From Transcriptome Analysis. Front. Immunol. 10:153. doi: 10.3389/fimmu.2019.00153* Transcriptome analysis is a powerful tool that enables a deep understanding of complicated physiological pathways, including immune responses. RNA sequencing (RNA-Seq)-based transcriptome analysis and various bioinformatics tools have also been used to study non-model animals, including aquaculture species for which reference genomes are not available. Rapid developments in these techniques have not only accelerated investigations into the process of pathogenic infection and defense strategies in fish, but also used to identify immunity-related genes in fish. These findings will contribute to fish immunotherapy for the prevention and treatment of bacterial infections through the design of more specific and effective immune stimulants, adjuvants, and vaccines. Until now, there has been little information regarding the universality and diversity of immune reactions against pathogenic infection in fish. Therefore, one of the aims of this paper is to introduce the RNA-Seq technique for examination of immune responses in pathogen-infected fish. This review also aims to highlight comparative studies of immune responses against bacteria, based on our previous findings in largemouth bass (*Micropterus salmoides*) against *Nocardia seriolae,* gray mullet (*Mugil cephalus*) against *Lactococcus garvieae,* orange-spotted grouper (*Epinephelus coioides*) against *Vibrio harveyi*, and koi carp (*Cyprinus carpio*) against *Aeromonas sobria*, using RNA-seq techniques. We demonstrated that only 39 differentially expressed genes (DEGs) were present in all species. However, the number of specific DEGs in each species was relatively higher than that of common DEGs; 493 DEGs in largemouth bass against *N. seriolae*, 819 DEGs in mullets against *L. garvieae*, 909 in groupers against *V. harveyi*, and 1471 in carps against *A. sobria.* The DEGs in different fish species were also representative of specific immune-related pathways. The results of this study will enhance our understanding of the immune responses of fish, and will aid in the development of effective vaccines, therapies, and disease-resistant strains.

Keywords: transcriptome, RNA-Seq, immune response, fish disease, bacteria

# INTRODUCTION

Transcriptome analysis is used to study principal pathways of development, cellular fate, physiology, activity, and disease progression. RNA sequencing (RNA-Seq) is a modern technology for transcriptome profiling that uses next-generation sequencing (NGS). Advancements in bioinformatics has significantly supported RNA-Seq technology to accelerate the knowledge on transcriptomes (1).

In the aquaculture field, there is wide utility for RNA-Seq in various applications, such as understanding the development of embryo and larvae, toxicology, environmental stress, effect of dietary conditions, and discovery of novel transcripts (2–4). In addition, RNA-Seq has been used in many studies of fish immunology (5, 6). Pathogenic infection is a major concern for maintaining economic sustainability in natural and farmed fish; it results in high mortality and economical loss in aquaculture. An innate immunity is a front line of host defense, producing effectors that directly to the pathogen and attack it. An adaptive immune system is also present in teleost, including humoral and cellular mechanisms. To reduce disease outbreaks, it is essential to understand the immune mechanisms in fish during pathogenic infections. This knowledge will support the development of effective vaccines and adjuvants against pathogens. However, it has not been reported that the universality and diversity of immune reactions against pathogenic infection in fish.

In this paper, we firstly introduce the RNA-Seq technique and current knowledge for investigations of immune responses in pathogen-infected fish. This review also aims to highlight comparative studies of fish immune responses against bacteria based on our previous studies that we demonstrated the transcriptome of bacteria infected fish, largemouth bass (Micropterus salmoides) against Nocardia seriolae, gray mullet (Mugil cephalus) against Lactococcus garvieae, orange-spotted grouper (Epinephelus coioides) against Vibrio harveyi, and koi carp (Cyprinus carpio) against Aeromonas sobria.

# ADVANTAGE OF RNA-seq ANALYSIS IN FISH AQUACULTURE

Since the 2000s, hybridization-based microarray has been used to examine fish immunology in aquacultures; some early examples included Japanese flounder (Paralichthys olivaceus) (7), rainbow trout (Oncorhynchus mykiss) (8), and Atlantic salmon (Salmo salar) (9). Although species-specific probes should be designed, microarray technology could provide us with high throughput gene expression data. For transcriptome analysis, series analysis of gene expression (SAGE) and cap analysis gene expression (CAGE) have also been utilized. SAGE and CAGE, which are tag-based technology, are more precise; however, the number of genes that can be analyzed at one time is lower as compared with that of microarrays. Recently, the number of reports that uses RNA-Seq in aquaculture studies has rapidly increased. For the complete detail of RNA-Seq methodology, please refer the nicely reviews focused on aquaculture field (3, 6). The advantage of RNA-Seq is that it could determine expression levels of lowlevel transcripts as well as each splice variant isoforms. Current focus in aquaculture fish research is to examine organisms that do not process reference gene sequences; unigenes are obtained via de novo assembly using Trinity or similar programs without requiring reference gene sequences (10). RNA-Seq could provide novel transcript sequences, thereby expanding our current list of known transcripts in fish.

#### ANNOTATION, ENRICHMENT ANALYSIS, AND PATHWAY ANALYSIS USING DE NOVO ASSEMBLY DATA

Although RNA-Seq technology could be applied to non-model animals, there are problems associated with the functional annotation and enrichment analysis of transcripts data. Transcripts sequences following assembly are usually searched via several databases, such as NCBI nucleotide sequences (NT), NCBI non-redundant protein (NR), Clusters of Orthologous Groups (COGs) (11), Kyoto Encyclopedia of Genes and Genomes (KEGG) (12, 13), gene ontology (GO) (14), and InterPro annotation (15). In our previous study on orangespotted grouper (Epinephelus coioides), a total of 79,128 unigenes were identified and aligned with each database; 58,926 (74.47%) in NT, 43,576 (55.07%) in NR, 14,750 (18.64%) in COG, 34711 (43.87%) in KEGG, and 4232 (5.35%) in GO (16). The number of genes aligned with existing genes in the database was the highest in NT, while gene alignment was the lowest in GO. Differences in the number of aligned genes between the databases were similar to those found in other aquaculture studies (17–19). Although the GO database could provide enrichment analysis and pathway analysis, due to low gene alignment, results may be limited to generalized conclusions. There are programs that can convert gene IDs from one database to those of another database. For example, DAVID and ID Converter Systems are able to change gene IDs from NT to that of GO. However, these systems are not very useful in genes of aquaculture species. Currently, the KEGG database shows a relatively high number of aligned genes, which allows for enrichment analysis of aquaculture species. To obtain generalized conclusions using transcriptome data, it is essential that systems are developed to describe non-model organisms. There are databases now under construction that contain transcriptome information of aquaculture species. In the European common carp (Cyprinus carpio), a wide range of data on tissue-specific gene expression and translation (20) has been presented. These datasets will allow us to investigate immune responses in aquaculture species via transcriptome analysis.

# IMMUNE RESPONSES AGAINST PATHOGENS IN TELEOST USING RNA-seq

Although fish are constantly exposed to risk of microorganism pathogens, fish could keep in shape to act immune mechanisms against pathogens. In a first line of immune response, fish are protected by non-specific humoral factors including growth inhibiting substances (transferrin and antiproteases), lysins (lysozyme, C-reactive protein, and bactericidal peptides), and making a link with non-specific phagocyte responses. Second, fish produce antibody constitutes for a specific humoral defense inhibiting bacterial adherence and invasion of non-phagocytic host cells and counteracting toxins from bacterial (21). After developing the technology of molecular biology, the immunerelated gene functions and responses against pathogens have been one of the major topic in fish immunology field. To investigate the expression pattern of immune-associated genes, real-time PCR is usually performed. However, this method is expensive and not recommended for a genome-wide survey of gene expression. As RNA-Seq could provide us with quantitative data on transcript expression levels, this technique has been commonly used to identify genes that respond to pathogenic conditions during exogenous challenge. **Table 1** lists transcriptome analysis studies that examined immune regulations in teleost. In this review, we will also focus on studies that investigated immune responses to pathogen or their mimic molecules, using RNA-Seq analysis.

Aeromonus hydrophila is a Gram-negative bacterium, and causes a wide spectrum of diseases in vertebrates (69, 70). It is a major pathogen in aquaculture farms, and leads to high mortalities and economic losses worldwide (71, 72). In blunt snout bream (Megalobrama amblycephala), RNA-Seq analysis was conducted with RNA from several tissues, and 238 differentially expressed unigenes were identified in infected fish (22). In grass carp (Ctenopharygodon idella), 2121 DEGs were identified in spleens of A. hydrophila (6 hpi)-infected fish, some of which were involved in phagocytosis, the complement system, and cytokine production (25). Using transcriptome analysis, another study showed that A. hydrophila infected grass carp exhibited 2992 DEGs in the spleen, which were associated with the complement and coagulation cascades (26). In golden mahseer (Tor putitora), DEGs in A. hydrophila-infected livers were mainly associated with Th1/2 cell differentiation pathways, as well as in pathogen recognition and complement system (24).

Flavobacterium columnare is a Gram-negative bacterium, and causes columnaris in freshwater fish (73). This disease induces pathological changes, and damages epidermal tissues, gills, and the skin (74). In channel catfish (Ictalurus punctatus), the transcript profile of F. columnare-infected gills was examined using RNA-Seq to investigate differences in susceptibility to F. columnare (34). In resistant fish, the expression level of innate immune-associated genes (iNOS2b, lysozyme C, IL-8, and TNFα) was found to be elevated. In susceptible fish, the expression of secreted mucin forms, mucosal immune factors (CD103 and IL-17a), and rhamnose-binding lectin (34) was upregulated. The transcriptomic profiles of F. columnareinfected and non-infected mandarin fish (Siniperca chuatsi) have been reported using the head kidney F. columnare-infected and non-infected group (35). The results indicated that 1019 genes were differentially expressed between the two groups, of which 27 were immune-related (35). A similar study using the head kidney F. columnare-infected topmouth culter (Culter alburnus) (36) was also conducted. A total of 4037 DEGs (1217 upregulated and 2820 downregulated genes) were identified, and were found to be involved in phagosome formation, carbohydrate metabolism, amino acid metabolism, and lipid metabolism (36).

Streptococcus agalactiae, a Gram-positive round bacterium, is a harmful aquaculture pathogen that leads to enormous economic losses in various teleost (75–78). Transcriptome analysis of hybrid tilapia (Oreochromis spp.) after S. agalactiae infection was conducted, and results indicated that DEGs are mainly involved in immune-related pathways, especially Tolllike receptor signaling and leukocyte transendothelial migration (49). Moreover, time-course expression profile of genes suggested that induction of the NADPH oxidase complex and piscidin is mediated by Toll-like receptor pathways (49). Another research group conducted RNA-Seq analysis in tilapia (Oreochromis niloticus) spleens following S. agalactiae infections (51). A total of 2822 DEGs were detected, many of which were involved in pathogen attachment and recognition, antioxidant/apoptosis, cytoskeletal rearrangement, and immune activation (51). Wang et al. (50) focused on the relation between temperature and bacterial infection. They showed that temperature influences mRNA profiles of the spleen in tilapia during S. agalactiae infections. In addition, it was suggested that DEGs are involved in immune responses and oxygen related metabolisms (50).

Vibrio alginolyticus is a halophilic Gram-negative bacterium that causes septicemias, ulcers, exophthalmia, and corneal opaqueness in marine fish worldwide (79, 80). Transcriptome analysis in larvae of orange-spotted grouper (Epinephelus coioides) revealed that the expression of genes involved in the complement pathway and antimicrobial peptides is enhanced upon V. alginolyticus infection (39). In addition, transcriptome profiles of giant grouper (Epinephelus lanceolatus) larvae infected with Vibrio alginolyticus suggested that TLR5 signaling induces secretion of several cytokines (IL-1β and IL-8) (40).

#### DIVERSITY OF IMMUNE RESPONSES AMONG SPECIES AND PATHOGENS

In the previous section, we introduced various RNA-seq analyses conducted in fish with bacterial infections. We have also previously published **four** research papers that conducted transcriptome analysis on infected fish, namely largemouth bass (Micropterus salmoides) against Nocardia seriolae (17), gray mullet (Mugil cephalus) against Lactococcus garvieae (18), orange-spotted grouper (Epinephelus coioides) against Vibrio harveyi (16), and koi carp (Cyprinus carpio) against Aeromonas sobria (19). Based on the transcriptome data from these reports, we gained a deeper understanding of immune responses to bacterial infections. However, there is little information regarding the universality and diversity of immune reactions of fish against pathogenic infections. Here, we investigated specific genes and pathways that are involved in each bacterial infection in various fish species. In this study, we used DEGs (transcripts from spleen at 1 dpi with log2 > 1 or < −1 between infected and control group) with KEGG-annotations. We **first** identified overlapping and specific genes that were up- or down- regulated in each species. Venn diagrams (**Figure 1**) showed that only 39 DEGs (25 up-regulated and 14 down regulated) were involved in all species. The number of specific DEGs in each species was

*(Continued)*

relatively higher than that of common DEGs; 493 DEGs (167 upregulated and 326 down regulated) were found in largemouth bass against N. seriolae, 819 DEGs (291 up-regulated and 528 down regulated) were found in mullets against L. garvieae, 909 DEGs (601 up-regulated and 308 down regulated) were found in groupers (Epinephelus coioides) against V. harveyi, and 1471 DEGs (1,001 up-regulated and 470 down regulated) were found in carps against A. sobria (**Figure 1**).

Of the common DEGs, we found several immune-related genes that were upregulated, including C4 (complement component 4), CCL19 (C-C motif chemokine 19), and SOCS1 (suppressor of cytokine signaling 1) (**Table S1**). The complement system is an important innate immune system that functions to detect pathogenic infections in both vertebrates and invertebrates. C4 is an important part of the classical and lectin pathways, which form enzymes C3 and C5 convertases (81, 82). CCL19, a CC chemokine that is expressed in lymphoid organs, manages the migration of antigen presenting cells and lymphocytes (83). In teleost, there are also various reports that investigated potential chemokine genes and their chemotactic activity (84–86). SOCS1 is a regulator of JAK/STAT signaling, and is induced by type I interferon (IFN) and IFN-γ via binding and blocking of JAK2 activation (87). It has been reported that SOCS1 acts as an inhibitor of IFN-mediated signaling in Atlantic salmon (Salmo salar) (88). From other reports of the transcriptome analysis (**Table 1**), complement system, JAK/STAT signaling and chemokine systems are also commonly appeared in responding pathways to bacterial infections. Therefore, it is suggested that these genes contribute to early immune responses following bacterial infections (within 24 h).

Nocardia seriolae is a filamentous Gram-positive bacterium that causes nocardiosis with high mortality in many fish species in Japan, Taiwan and Japan. The infected fish showed a lethal granulomatous disease of the skin, muscle, spleen, kidney, and liver tissues (89). Unlike other bacterial species from our previous studies, N. seriolae is an intercellular bacteria. To determine specific DEGs elicited by N. seriolae infections, we performed functional enrichment of the KEGG pathway for specific up-regulated genes in largemouth bass. As shown in **Table S2**, specific upregulated genes were assigned to 11 KEGG pathways; based on the enrichment analysis. From the enrichment analysis, Notch signaling pathway was focused and illustrated using expression levels of RNA-seq data from all four fish species (**Figure 2A**). Results indicated that Notch1 and HES1 (hairy and enhancer of split 1) were specifically upregulated in largemouth bass against N. seriolae. The Notch and HES1 axis present in hematopoietic cells and stroma of the thymus plays an important role in T cell development (90, 91). Additionally, in the "cytokine-cytokine receptor interaction" pathway, IL12RB1 (interleukin 12 receptor β-1) and IL12RB2 (interleukin 12 receptor β2) in largemouth bass against N. seriolae were upregulated. IL12B is a ligand of IL12RBs, and is highly, but not specifically expressed, in largemouth bass (**Figure 2B**). IL-12, a heterodimetric cytokine consisting of p35 and p40 subunits, is a key regulator of T helper 1 development (Th1), which promotes cellular immunity against intracellular pathogens. In Amberjack (Seriola dumerili), administrated recombinant IL-12 and formalin-killed N. seriolae showed the higher survival rates after challenged with N. seriolae, compared to vehicle and FKC only groups (92). These pathways promote immune reactions against N. seriolae during early stages of the infection, and are candidates for infection prevention and adjuvants in fish.

Aeromonas sobria is a Gram-negative, motile, rod-shaped bacterium that has been isolated from many diseased fish (93– 95). In the spleen and head kidney of disease fish, necrotized spleen cells and hemorrhagic pulps were observed (93). From the extracted data of specific up-regulated genes (1001 genes) in koi carp against A sobria (**Figure 1**), we performed functional enrichment of the KEGG pathway for specific up-regulated genes. As shown in **Table S3**, specific upregulated genes of koi carp against A. sobria are associated with 45 KEGG pathways. As shown in **Figure S1**, regulation of the actin cytoskeleton was activated during A. sobria infection. In addition, CXCL12 (C-X-C motif chemokine 12) and CXCR4 (C-X-C motif chemokine receptor 4) in were also up-regulated in koi carps during A sobria infections (**Figure S1**). The CXCL12-CXCR4 axis modulates various immune functions, such as induction of hematopoiesis and accumulation of immune cells in inflamed tissues (96). Therefore, the CXCL12-CXCR4 axis may function in reorganization of hematopoiesis in injured tissues during A. sobria infections.

Vibrio harveyi is one of the major photogenes of a luminescent Gram-negative bacterium, which impacts to wide range of aquaculture species (97–99). The 601 specific upregulated genes in orange-spotted grouper against Vibrio harveyi (**Figure 1**) were assigned to 8 KEGG pathways (**Table S4**). We focused on the ErbB signaling pathway, and found that expression of TGFα (transforming growth factor α) and its receptor, ERBB1 (epidermal growth factor receptor), were upregulated (**Figure S2**). Previous studies have shown that TGFα promotes the expression and activity of TLR5 and TLR9 in skin keratinocytes (100). In our previous study, expressions of TRL5 and its downstream genes in the spleen were found to be enhanced 2 days following V. harveyi infections (16). While the immunological function of TGFα in the spleen of fish is unclear, we hypothesize that TGFα is a key regulator for prevention of V. harveyi infection in fish.

Lactococcus garvieae is a Gram-positive, facultative anaerobic, non-motile bacterium, and affects freshwater and marine cultured fish species worldwide (101, 102). Functional enrichment analysis of the KEGG pathway was performed to determine specific upregulated genes (291 genes) in gray mullets against L. garvieae (**Figure 1**). Specific upregulated genes were mapped to 10 KEGG pathways during L. garvieae infection in gray mullets (**Table S5**). Results indicated that the IL-17 signaling pathway is clearly enhanced during the infection, as illustrated by **Figure S3**. IL-17 is composed of six ligands (IL-17A to F), and plays critical roles in inflammatory responses and host defenses during invasion by extracellular pathogens. Binding of IL-17s to its five perspective receptors (IL-17Rs; IL-17RA to E), induces inflammatory and immune responses (103). In vitro study, exogenous IL-17A induced bacterial clearance in F. tularensis LVS- live vaccine strain infected cells (104). Additionally, in mice model, it has been reported that in vivo

administration of IL-17A moderately delays time of death from lethal infection of Francisella tularensis live vaccine strain (105). While we did not detect expression of IL-17 ligands in this study, we found that expressions of IL-17RB, IL17RC, and IL-17RE were up-regulated in gray mullets infected with L. garvieae. There are studies that aimed to identify and characterize IL-17 and IL17Rs in fish (106, 107). However, functional differentiations of teleost IL-17s and these receptors remain elusive. Our findings on the expression pattern of IL17Rs will provide useful models that can be used to investigate immune functions of IL17s in teleost.

A. sobria and V. harveyi are classified to Gram-negative bacteria. Therefore, we approached to find the immune-related genes and pathways using commonly DEG (379 upregulated genes and 91 downregulated genes) of koi carp against A. sobria and orange-spotted grouper against V. harveyi (**Figure 1**). However, any immune-related pathways were not assigned by KEGG enrichments analysis. TLR4, which is the pathogen recognized receptor for the Gram-negative bacteria specific lipopolysaccharide, is not highly expression in the spleen of koi carp against A. sobria and orange-spotted grouper against V. harveyi. While, we could find the up-regulated immune-related gene of these two species, such as pattern recognition receptors (TLR6 and TLR5), cytokines and chemokines (CSF3 and CCL21), lysosome related genes (LYPLA3 and SLC11A1) and caspase recruitment domain-containing protein (Card) 9 (**Table S6**). N. seriolae and L. garvieae are classified to Gram-positive bacteria. Therefore, we investigated to commonly immune-related genes and pathways in Gram-positive bacteria using commonly DEGs (32 upregulated genes and 63 downregulated genes) of largemouth bass against N. seriolae and gray mullet against L. garvieae (**Figure 1**). Up-regulated immune-related genes of these two species were identified, such as IL-6, TNF Receptor Superfamily Member 11b (TNFRSF11B), interferon regulatory factors (IRF4 and IRF8) and CD83 (**Table S7**). Although it is unclear the pathways to induce these up-regulated genes, these immune related genes may become the marker and immune factors in Gram-negative or positive bacterial infection.

#### CONCLUSION AND FUTURE PERSPECTIVES

In this review, we first introduced applications of the RNA-Seq technology in aquaculture studies. The RNA-Seq technology has allowed us to identify many novel genes, and to investigate the expression patterns at various conditions in non-model teleost. Therefore, findings based on this technology have accelerated research in the aquaculture field. Additionally, high throughput quantification by RNA-seq could be used to identify pathogen, and to evaluate the efficacy of vaccines and adjuvants against pathogen in vivo. We also summarized current knowledge on immune responses to pathogenic challenges via RNA-Seq in teleost. In this study, we could identify the specific pathway in each fish against bacteria species, Noth1 signaling and IL-12 signaling pathway in largemouth bass against N. seriolae, CXCL12 and CXCR4 signaling pathway in koi carp against A. sobria, TGFα signaling pathway in orange-spotted grouper against V. harveyi, and IL-17 signaling pathway in gray mullet against L. garvieae. These types of studies are increasing, and have enormously aided in our understanding of pathogenic strategies and immune defense systems in aquaculture fish. However, there remains certain limitations of RNA-Seq analysis in aquaculture species. Additionally, the RNA-seq technology could be used to expand existing datasets on splicing variants in mRNA and SNP. Currently, differences in immune response against different pathogens are not well-described. In this study, we attempted to investigate both species-specific and common immune related genes that are up-regulated during bacterial infections based on our previous RNA-seq data. Secondary use of RNA-seq datasets may be essential for preparation of future RNA-seq studies in aquaculture species, which can further deepen our understanding of specific immune functions against pathogens. In aquaculture field, these deep and particular understanding of immune response against each pathogens will provide us to more accurate diagnosis of disease and develop a more effective vaccine and adjuvant of each pathogens.

# AUTHOR CONTRIBUTIONS

SM analyzed transcriptome data and wrote the paper. P-CW and S-CC reviewed the paper.

# FUNDING

This research was funded by National Science Council, Taiwan, grant number NSC 104-2622-B-020-002-CC1 and MOST 107- 2313-B-020−012 -MY3.

# ACKNOWLEDGMENTS

We thank Genomics Bioscience Technology Co. Ltd. (Taipei, Taiwan) for assistance with transcriptome analysis.

# SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2019.00153/full#supplementary-material

Figure S1 | Pathway map of Regulation of actin cytoskeleton in KEGG. In each gene boxes, the gene expression levels are shown in 4 fish (C, Carp; G, Grouper; L, Largemouth bass; M, Mullet) spleen 1 day after infection with *A. sobria*, *V. harveyi*, *N. seriolae,* and *L. garvieae*, respectively, when compared to the control group. The lower expression levels of genes are shown in green, and the higher expression levels of genes are shown in red. Undetected genes are shown by white coloring (see color legend in figure).

Figure S2 | Pathway map of ErbB signaling pathway in KEGG. In each gene boxes, the gene expression levels are shown in 4 fish (C, Carp; G, Grouper; L, Largemouth bass; M, Mullet) spleen 1 day after infection with *A. sobria*, *V. harveyi*, *N. seriolae,* and *L. garvieae*, respectively, when compared to the control group. The lower expression levels of genes are shown in green, and the higher expression levels of genes are shown in red. Undetected genes are shown by white coloring (see color legend in figure).

Figure S3 | Pathway map of Il-17 signaling pathway in KEGG. In each gene boxes, the gene expression levels are shown in 4 fish (C, Carp; G, Grouper; L, Largemouth bass; M, Mullet) spleen 1 day after infection with *A. sobria*, *V. harveyi*, *N. seriolae,* and *L. garvieae*, respectively, when compared to the control group. The lower expression levels of genes are shown in green, and the higher expression levels of genes are shown in red. Undetected genes are shown by white coloring (see color legend in figure).

Table S1 | Expression levels of commonly up or down regulated genes among 4 fish infected with bacteria. Each expression data indicated fold-change (log2) of bacterial infection/control groups.

Table S2 | Functional enrichment KEGG pathway for specific up-regulated genes of largemouth bass against *N. seriolae*.

Table S3 | Functional enrichment KEGG pathway for specific up-regulated genes of koi carp against *A. sobria*.

Table S4 | Functional enrichment KEGG pathway for specific up-regulated genes of orange-spotted grouper against *V. harveyi*.

Table S5 | Functional enrichment KEGG pathway for specific up-regulated genes of gray mullet against *Lactococcus garvieae*.

Table S6 | Expression levels of commonly up regulated immune-related genes among koi carp against *A. sobria* and orange-spotted grouper against *V. harveyi*. Each expression data indicated fold-change (log2) of bacterial infection/control groups.

#### REFERENCES

Table S7 | Expression levels of commonly up regulated immune-related genes among largemouth bass against *N. seriolae* and gray mullet against *L. garvieae*. Each expression data indicated fold-change (log2) of bacterial infection/control groups.

with Lactococcus garvieae. Fish Shellfish Immunol. (2016) 58:593–603. doi: 10.1016/j.fsi.2016.10.006

Notothenia coriiceps. Fish Shellfish Immunol. (2016) 55:315–22. doi: 10.1016/j.fsi.2016.06.004

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Maekawa, Wang and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Rainbow Trout (Oncorhynchus Mykiss) Intestinal Epithelial Cells as a Model for Studying Gut Immune Function and Effects of Functional Feed Ingredients

Jie Wang1 , Peng Lei 2 , Amr Ahmed Abdelrahim Gamil 1 , Leidy Lagos 2 , Yang Yue1 , Kristin Schirmer 3,4,5, Liv Torunn Mydland2 , Margareth Øverland2 , Åshild Krogdahl 1 and Trond M. Kortner 1 \*

1 Department of Basic Sciences and Aquatic Medicine, Faculty of Veterinary Medicine, Norwegian University of Life Sciences (NMBU), Oslo, Norway, 2 Department of Animal and Aquacultural Sciences, Faculty of Biosciences, Norwegian University of Life Sciences (NMBU), Oslo, Norway, 3 Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland, 4 EPF Lausanne, School of Architecture, Civil and Environmental Engineering, Lausanne, Switzerland, 5 ETH Zürich, Institute of Biogeochemistry and Pollutant Dynamics, Zurich, Switzerland

#### Edited by:

Roy Ambli Dalmo, UiT The Arctic University of Norway, Norway

#### Reviewed by:

Caterina Faggio, Università degli Studi di Messina, Italy Laura M. Langan, Plymouth University, United Kingdom

> \*Correspondence: Trond M. Kortner<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Comparative Immunology, a section of the journal Frontiers in Immunology

Received: 31 October 2018 Accepted: 17 January 2019 Published: 06 February 2019

#### Citation:

Wang J, Lei P, Gamil AAA, Lagos L, Yue Y, Schirmer K, Mydland LT, Øverland M, Krogdahl Å and Kortner TM (2019) Rainbow Trout (Oncorhynchus Mykiss) Intestinal Epithelial Cells as a Model for Studying Gut Immune Function and Effects of Functional Feed Ingredients. Front. Immunol. 10:152. doi: 10.3389/fimmu.2019.00152 The objective of this study was to evaluate the suitability of the rainbow trout intestinal epithelial cell line (RTgutGC) as an in vitro model for studies of gut immune function and effects of functional feed ingredients. Effects of lipopolysaccharide (LPS) and three functional feed ingredients [nucleotides, mannanoligosaccharides (MOS), and beta-glucans] were evaluated in RTgutGC cells grown on conventional culture plates and transwell membranes. Permeation of fluorescently-labeled albumin, transepithelial electrical resistance (TEER), and tight junction protein expression confirmed the barrier function of the cells. Brush border membrane enzyme activities [leucine aminopeptidase (LAP) and maltase] were detected in the RTgutGC cells but activity levels were not modulated by any of the exposures. Immune related genes were expressed at comparable relative basal levels as these in rainbow trout distal intestine. LPS produced markedly elevated gene expression levels of the proinflammatory cytokines il1b, il6, il8, and tnfa but had no effect on ROS production. Immunostaining demonstrated increased F-actin contents after LPS exposure. Among the functional feed ingredients, MOS seemed to be the most potent modulator of RTgutGC immune and barrier function. MOS significantly increased albumin permeation and il1b, il6, il8, tnfa, and tgfb expression, but suppressed ROS production, cell proliferation and myd88 expression. Induced levels of il1b and il8 were also observed after treatment with nucleotides and beta-glucans. For barrier function related genes, all treatments up-regulated the expression of cldn3 and suppressed cdh1 levels. Beta-glucans increased TEER levels and F-actin content. Collectively, the present study has provided new information on how functional ingredients commonly applied in aquafeeds can affect intestinal epithelial function in fish. Our findings

suggest that RTgutGC cells possess characteristic features of functional intestinal epithelial cells indicating a potential for use as an efficient in vitro model to evaluate effects of bioactive feed ingredients on gut immune and barrier functions and their underlying cellular mechanisms.

Keywords: RTgutGC, in vitro model, lipopolysaccharide, functional feed ingredients, mucosal immune responses, gut barrier

#### INTRODUCTION

The fish intestine is a multifunctional organ responsible for key physiological processes such as digestion, absorption of nutrients, and osmoregulation (1). Furthermore, the intestine has an important immunological role and constitutes a physical barrier against pathogens (1). In order to secure optimal gut health and function in farmed fish, there is now particular focus on various feed additives including functional feed ingredients that are branded not only in terms of their nutritional value, but also based on their health promoting and disease preventing properties. These functional feed ingredients could include intact microbes (e.g., probiotic organisms), mixed or purified extracts from microbial or plant structural components [e.g., mannanoligosaccarides (MOS), beta-glucans], metabolites (e.g., nucleotides) or even conventional nutrients, if their dietary inclusion is higher than the animal's requirement. Functional feeds are typically applied during predicted stressful events or challenging farming conditions, such as grading, sea water transfer, vaccination, and during critical life stages to help the animal ward off pathogens and secure good health (2). Functional feed ingredients are generally believed to exert their main actions locally within the gut, and may have direct modulatory effects on gut microbiota (3), gut barrier, immune, and/or metabolic functions (4–7). For example, nucleotides are of crucial importance for a whole range of normal intestinal functions, such as growth, nutrient metabolism, immune system, tissue repair, and development (8). Beta-glucans can increase cellular and humoral immune responses in immune cells and epithelial tissues of fish (9–11). MOS as an immune modulator has a close relation to pathogen colonization blocking and immune system regulation, as well as improving intestinal morphology and the epithelial brush border (10, 12, 13).

Current knowledge regarding mechanisms underlying effects of functional feed ingredients on fish gut health and function is, however, limited largely due to a lack of targeted research tools. The use of in vitro approaches, such as appropriate cell lines, would facilitate further research on basic functions of the digestive tract and effects of functional feed ingredients on host intestinal immune, barrier and digestive function. It would also reduce the current dependence on large-scale feeding trials, thus contributing to a shift toward 3R studies within fish nutrition research. In mammalian research, intestinal cell lines have proven to be valuable tools for exploration of basic mechanisms of gut function and health and interactions with dietary components. For example, nucleotide supplements in human Caco-2 and rat IEC-6 cell lines have been observed to strengthen intestinal maturation and growth (14). Beta-glucans and plant flavonoids can suppress nuclear factor-kB transactivation, regulate immune response, and strengthen intestinal epithelial barrier function in human Caco-2 cells (15–17).

Until recently, no relevant intestinal cell lines from fish have been available, but promising cultures have been established based on the rainbow trout (Oncorhynchus mykiss) intestinal derived cell line RTgutGC (18). Since their initial isolation, RTgutGC cells have been relatively well-characterized and are now routinely grown as monolayers on permeable supports, leading to a two-compartment intestinal barrier model consisting of a polarized epithelium. The system is divided into an upper (apical) and a lower (basolateral) compartment, thereby mimicking the intestinal lumen and the portal blood, respectively. Reported structural and functional features of the RTgutGC cells include tight junction and desmosome formation between adjacent cells, development of transepithelial resistance and polarization over time to exhibit epithelial and brush border characteristics (18–20). The cell line has, as such, been proposed as a physiologically adequate fish intestinal epithelial model, equivalent to the Caco-2 cell line for human intestinal epithelium (20, 21), and has been used recently in studies on fish intestinal immune and barrier function (18, 22, 23).

The objective of this study was to evaluate the suitability of the RTgutGC cells as an in vitro model for studies of gut immune function and effects of functional feed ingredients. Effects of a prototype pathogen-associated molecular pattern (PAMP), lipopolysaccharide (LPS), and three functional ingredients commonly applied in commercial fish feeds (nucleotides, MOS, and beta-glucans) were evaluated by diverse analyses, including cell viability measurements and proliferation, brush border digestive enzyme activity, barrier function, ROS production, morphology, and relevant gene and protein expression.

#### MATERIALS AND METHODS

#### RTgutGC Cell Culture

Routine RTgutGC cell cultivation was based on the description by Kawano et al. (18). Briefly, RTgutGC cells were cultured in 75-cm2 flasks (TPP, Trasadingen, Switzerland). L-15 complete medium (L-15/C), i.e., Leibovitz's L-15 medium without Phenolred (21083, Gibco Invitrogen, Basel, Switzerland) supplemented with 10% bovine serum (F7524, Sigma Aldrich, Buchs, Switzerland) and gentamicin (15710-049, Invitrogen, Basel, Switzerland) with a final concentration of 100µg/mL, was used to culture cells in a 20◦C incubator under normal atmosphere. Cells were split in a 1:2 ratio using trypsin (0.25% in PBS w/o Ca2+, Mg2+; L0910; Biowest; Nuaillé, France) after reaching confluency.

For cells grown on conventional culture plates without inserts, 1 mL or 3.5 mL cell suspensions (1.5 × 105 cells/mL, 78,947 cells per cm2 for 24-well plates and 54,688 cells per cm2 for 6-well plates) were seeded in 24-well (No.662160, Greiner-Bioone, Frickenhausen, Germany) or 6-well plates (No. 657960, Greiner-Bio-one, Frickenhausen, Germany), respectively, and were cultured to reach at least 80 % confluency before use (3–4 days).

For the two-compartment intestinal barrier model, RTgutGC cells were cultured as described previously (19, 20). Briefly, 24-well plates with 33.6 mm2 transwell inserts (No. 662 630, Greiner-Bio-one, Frickenhausen, Germany) and 6-well plates with 425.4 mm2 transwell inserts (No. 657 630, Greiner-Bio-one, Frickenhausen, Germany) with pore sizes of 3µm were used to simulate gut lumen (apical /upper chamber) and portal blood (basolateral /lower chamber). Cells were seeded adding 300 µL or 3.5 mL cell suspension (8 × 104 cells/mL, 71,429 cells per cm2 for 24-well plates and 65,820 cells per cm2 for 6-well plates) in the apical chamber of 24-well or 6-well plates, respectively. Then, 1 or 3.5 mL of L-15/C were added into the basolateral chamber of 24-well or 6-well plates, respectively. The apical and basolateral medium was changed once per week for a total of 28 days.

#### Exposure Design

Stock solutions were prepared for LPS and the functional ingredients. LPS (L2630, Sigma, Norway) stock solution was prepared to 1 mg/mL in L15/ex medium. The L15/ex medium contains only the inorganic salts, galactose, and pyruvate concentrations of L-15 (24). Nucleotides (T25-1KT, Sigma, Norway) stock solution was prepared to 10 mg/mL using milliQ water. MOS (Active MOS extracted from yeast, Biorigin, São Paulo, Brazil) stock solution was prepared to 20 mg/mL using sterile PBS, and then sonicated in a water bath (30 s/3 times) and centrifuged (500 × g/ 5 min). The supernatant was subsequently transferred into new vials and stored at −20◦C according to previous descriptions (13). Beta-glucans (G5011, Sigma, Norway) stock solution was prepared to 2 mg/mL in sterile PBS according to previous reports (23).

For all exposure tests performed with the two-compartment intestinal barrier model, the stock solutions of LPS and the functional ingredients were diluted in mucosal saline, prepared according to Genz et al. (25) (**Supplementary Table 1**), and added to the apical chamber in order to mimic intestinal lumen conditions. Before performing the exposure tests with LPS and the functional ingredients, L-15/C and mucosal saline acted as exposure medium for RTgutGC cells to evaluate whether the mucosal saline affected cell viability. For exposure tests performed with conventional plates, working solutions were prepared by diluting in mucosal saline or L15 medium, depending on the analytical assay as specified below. To select final working concentrations for further analysis, LPS and the functional ingredients were tested at a range of different concentrations in 6 h exposures in 24-well-conventional plates without inserts (**Supplementary Table 2**).

#### Assessment of Cell Viability

Alamar Blue (AB, DAL1025, Invitrogen, Basel, Switzerland) and 5-carboxyfluorescein diacetate acetoxymethyl ester (CFDA-AM, C1345, Invitrogen, Basel, Switzerland) were used to measure cell viability (24, 26). AB was used to measure cell metabolic activity, whereas CFDA-AM was used to measure cell membrane integrity. After 6 h of incubation, stimulant working solutions were discarded, cells were washed twice using 1 mL PBS and subsequently, a volume of 400 µL of fresh AB and CFDA-AM were added to each well. The plates were then incubated at 20◦C for 30 min in the dark before measurement. The Cytation 3 plate reader (Bio Tek Instruments, Winooski, USA) was used to measure the fluorescence of AB (λex = 530 nm; λex = 595 nm) and CFDA-AM (λex = 493 nm; λex = 541 nm).

### Measurement of Transepithelial Electrical Resistance (TEER)

As a quality measure of monolayer formation, TEER was measured in RTgutGC cells grown in 24-well-culture plates with membrane inserts at day 1, 7, 14, and 28. Additionally, TEER was measured in RTgutGC cells exposed to LPS and the functional ingredients for 6 h after 28 days of culture on transwell membrane inserts in 6-well plates. TEER levels were measured using an EVOM Voltohmmeter with STX2 electrode and Endohm-6 electrode (World Precision Instruments, Berlin, Germany) as described by Geppert et al. (19). TEER was calculated by subtracting the values without cells from the values with cells. TEER values were given as × cm2 .

#### Brush Border Membrane Enzyme Activity

After 3–4 days of culture on conventional 24-well plates, RTgutGC cells were exposed to LPS and the functional ingredients for 6 h. After discarding the mucosal saline with LPS or functional ingredients, cells were harvested by trypsination and centrifugation. Cell pellets were reconstituted in 1 mL ice-cold 2 mM Tris/50 mM mannitol pH 7.1, containing phenyl-methyl-sulphonyl fluoride (P-7626, Sigma, Norway) as serine protease inhibitor. Brush border membrane enzyme activities, i.e., leucine amino peptidase (LAP) and maltase, were subsequently measured. LAP activity was analyzed colorimetrically with a commercial kit (NO. 251, Sigma, Norway) using L-leucine-β-naphthylamide as substrate according to the methods described by Krogdahl et al. (27). Maltase activity was measured using maltose as substrate according to the description of Dahlquist (28). Total protein concentrations were determined using a Bio-Rad Protein Assay (Bio-Rad Laboratories, Munich, Germany). Enzyme activities were expressed as mol substrate hydrolysed per hour per mg protein.

# Albumin Translocation Assay

After 28 days of culture on transwell-membrane inserts in 6-well plates, RTgutGC cells with an initial seeding density of 8 × 104 cells/mL (65,820 cells per cm2 ) were exposed to LPS and the functional ingredients for 6 h. The permeation of fluorescentlabeled albumin was then used to evaluate the barrier potential of the cells. 20 µL albumin (Alexa FluorTM 488 Bovine Serum Albumin, Thermo Fisher Scientific, USA) was added into the apical chamber of each well, and 250 µL of culture medium was collected from the basolateral chamber at the following intervals: 10, 30, 45, 60, and 90 min and temporary stored in the dark at 20 ◦C. After collecting all the samples, 100 µL of each sample was added to a 96- well black plate (M5061-40EA, Sigma, Norway) in duplicate, and fluorescence was measured using a Cytation 3 plate reader (Bio Tek Instruments, Winooski, USA) equipped with a 490 excitation and 525 emission filter.

# Quantitative Real Time PCR (qPCR)

After 28 days of culture on transwell membrane inserts in 6-well plates, RTgutGC cells were exposed to LPS and the functional ingredients for 6 h, and subsequently harvested for gene expression profiling. After discarding the mucosal saline with LPS or functional ingredients, 1 mL of TRIzol (Invitrogen, Thermo Fisher Scientific, USA) was added to each apical chamber. Cells were collected by scarping and flushing the membrane inserts 10 times with the TRIzol solution. The cell homogenate was transferred into a 1.5 mL Eppendorf tube, snap frozen in liquid N2 and subsequently stored at −80 ◦C until RNA extraction. Gene expression levels in RTgutGC cells were compared with those of rainbow trout tissues by using total RNA samples from liver, pyloric, mid and distal intestine obtained from a fresh-water stage female rainbow trout as previously described (29). RNA was subsequently purified using a PureLink RNA mini Kit (Invitrogen, Thermo Fisher Scientific, USA). RNA purity and concentration were measured using an Epoch Microplate Spectrophotometer (BioTeK Instruments, Winooski, USA). The RNA integrity was verified using a 2100 Bioanalyzer in combination with RNA Nano Chip (Agilent Technologies, Santa Clara, USA). First-strand complementary DNA was synthesized from 1.0 µg total RNA from all samples using SuperScript IV VILO Master Mix (InvitrogenTM, ThermoFisher Scientific). Negative controls were performed in parallel by omitting RNA or enzyme.

Twelve target genes with important functions related to immunity, barrier function and metabolism were profiled. The qPCR primers were designed using Primer3web software version 4.0.0 (http://primer3.ut.ee/) or obtained from the literature. Primer details are shown in **Supplementary Table 3**. All primer pairs were first used in gradient reactions in order to determine optimal annealing temperatures. To confirm amplification specificity, the PCR products from each primer pair were subjected to melting curve analysis and visual inspection of the PCR products by agarose gel electrophoresis. PCR efficiency for each gene assay was determined using 2-fold serial dilutions of randomly pooled complementary DNA. The expressions of individual gene targets were analyzed using the LightCycler 96 (Roche Diagnostics, Basel, Switzerland). Each 10 µl DNA amplification reaction contained 2 µl PCR grade water, 2 µl of 1:10 diluted complementary DNA template, 5 µl LightCycler 480 SYBR Green I Master (Roche Diagnostics) and 0.5 µl (10 mM) of each forward and reverse primer. Each sample was assayed in duplicate, including a no-template control. The three-step qPCR run included an enzyme activation step at 95◦C (5 min), forty to forty-five cycles at 95◦C (10 s), 60◦C (10 s), and 72◦C (15 s) and a melting curve step. Target gene expression was normalized to the geometric average of beta-actin (actb) and ribosomal protein s20 (rps20) after confirming reference gene intra- and interspecific stability (30). Mean normalized expression of the target genes was calculated from raw Cq values by relative quantification (31).

# Cell Proliferation Assay

The ability of RTgutGC cells to close a gap during exposure to LPS, MOS and beta-glucans was investigated in a cell proliferation assay by using 2-well-culture inserts (80241, Ibidi GmbH, Martinsried, Germany). The inserts were placed on a conventional cell culture surface, i.e., a µ-Dish 35 mm (81156, Ibidi GmbH, Martinsried, Germany) creating two wells, which were separated by a rubber partition. Approximately 10,000 cells in 70 µL L-15/C were seeded into each well. The cultures were incubated at 20 ◦C for 2 days until confluence. Then, the rubber partition was removed to create a 500µm gap between the cells. Immediately, LPS (50µg/mL), MOS (4 mg/mL), beta-glucans (100µg/mL) and PBS (control), all dissolved in L-15 medium, were added to the cultures and phase contrast pictures were captured at day 0, 1, 2, and 4 (or until the gap was closed) using a ZEISS Axio microscope (with Axiocam 105 color). The image were processed using ImageJ (32). In brief, all images were first adjusted using Adjust tool for achieving a clear contrast between the cell-free area and area covered by cells. Subsequently, the cell-free area was measured using Analyze particles tool. The cell proliferation rate was calculated by dividing the cell-free area at each time point with the cell-free area at day 0.

# Oxidative Stress Detection and Substrate Uptake Assay

After 3–4 days of culture on conventional 6-well plates, RTgutGC cells were exposed to LPS and the functional ingredients for 6 h. After discarding the mucosal saline with LPS or functional ingredients, cells were harvested by trypsination and centrifugation. Cell pellets were reconstituted in 5% FBS in PBS for ROS generation measurement. CellROX R (C10444, Thermo Fisher, Waltham, USA) reagent was added to the cell suspensions at a final concentration of 5 mM, followed by incubation at room temperature for 30 min. After the incubation, cells were washed three times with ice-cold phosphate buffered saline (PBS) and ROS generation was analyzed by flow cytometry (Beckman Coulter Gallios). At least 10,000 events were collected for each sample. Data were analyzed using Kaluza software v.2.1 (Beckman Coulter) and gated using Side scatter (SSC) (granularity) and Forward scatter (FSC) (size) parameters. Discrimination of aggregates from single cells was performed using side scatter-W (SSC-W) vs. side scatter (SSC). ROS was measured at 650/675 nm (FL3).

Fluorescence conjugated Zymosan (Z23373, Thermo Fisher Scientific, USA) and albumin (Alexa FluorTM 488 Bovine Serum Albumin, Thermo Fisher Scientific, USA) were added into culture media at 20 and 12.5µg/ml, respectively for cells growing in 6-well-conventional plates. Cells were trypsinized and centrifuged after 1, 1.5, and 3 h after adding substrates, respectively. Cell pellets were reconstituted in 5% FBS in PBS before flow cytometry (Beckman Coulter Gallios) was performed to analyze the cells with or without fluorescence at 495/519 nm.

#### Immunocytochemistry of F-actin Content

For morphological characterization, confocal laser microscopy was used for imaging. RTgutGC cells in L-15/C were seeded in an 8 chamber tissue cultured treated glass Falcon CultureSlide R (Corning, New York, USA) at a density of 150,000 cells per chamber. When reaching 80% confluence, cells were washed with Dulbecco's Phosphate-Buffered Saline (DPBS) and treated with LPS (50µg/mL), MOS (4 mg/mL), beta-glucans (100µg/mL), and PBS (control), all dissolved in L-15 medium. After 6 h, cells were washed with DPBS and fixed with 3% paraformaldehyde (Sigma-Aldrich) for 20 min at 4◦C. Following fixation, the cells were permeabilized with 0.1% Triton X-100 (Sigma-Aldrich, St. Louis, USA) for 10 min at room temperature. Cells were then incubated in blocking buffer (BB) (10% goat serum, 3% bovine serum albumin, and 0.1% Triton X-100 in DPBS) for 1 h at room temperature. Afterwards, cells were incubated with phalloidin (R425, Thermo Fisher) for F-acin staining according to the manufacturer's instruction. After staining, cells were washed three times for 3 min with DBPS and left to air dry. Once dry, plastic chambers were removed from the slides. Three drops of mounting medium, Fluoroshield (Sigma-Aldrich), containing DAPI were added to the slides, followed by covering with coverslip. The image was analyzed by ImageJ software to investigate the morphology change of the cells under different treatments. Three random pictures were taken from cells under respective treatments. Individual cell numbers were counted based on DAPI-stained nuclear numbers manually. F-actin contents were subsequently calculated by the total fluorescence intensity of phalloidin divided by number of the cells.

# Protein Expression of E-cadherin, Aquaporin 8, and Hsp70 by Western Blot Analysis

RTgutGC cells were seeded on 6-well plates and grown until confluence before 6 h exposure to LPS (50µg/mL), MOS (4 mg/mL), beta-glucans (100µg/mL), and PBS (control), all dissolved in L-15 medium. Cells were harvested by trypsinization and centrifugation and protein was extracted using PARIS Kit (AM 1921, Thermo Fisher) according to the manual. Protein concentrations were measured using Bradford protein assay kit (Bio-Rad, Hercules, California, United States) and 10 or 20 µg of the protein were loaded on SDS page gels. After 40 min electrophoresis at 100 voltage, proteins were transferred to PVDF membranes, blocked with 5% dry milk for 1 h at room temperature, and incubated consecutively with E-cadherin monoclonal antibody (#701134, Thermo Fisher), Heat shock protein 70 (Hsp70) monoclonal antibody (MA3-008, Thermo Fisher), or Aquaporin 8 (Aqp8) polyclonal antibody (kindly provided by Prof. Steffen S. Madsen, Institute of Biology, University of Southern Denmark). After 3 times washing in PBS and incubation of HRP conjugated secondary antibody, the signal was visualized with Bio-Rad Gel Doc system after adding ECL detection reagents (GERPN2209, Sigma-Aldrich) to the membrane. Due to the potential influence of treatments on candidate reference protein expression, the total membrane protein content was visualized with Ponceau S (P3504, Sigma) and used as a qualitative loading control.

# Statistical Analysis

All data were tested for normality and variance homogeneity using histogram and "residual by predicted" plot, respectively, using JMP Pro 13.0.0 (SAS Institute, United States). When necessary, the data were transformed to achieve normal distribution. Further statistical analyses and graphics were made using GraphPad Prism 7 (GraphPad Software, La Jolla, California, United States). The flow cytometry figures were made by Kaluza (Beckman Coulter). Data of albumin translocation and cell proliferation rate were analyzed using two-way ANOVA using time and treatment as class variables followed by Dunnett multiple comparisons tests. Other data were analyzed using oneway ANOVA followed by Dunnett multiple comparisons tests. Data were calculated as mean ± SEM of two or three independent experiments with 3 or 4 technical well or insert replicates (depending on analytical assays, see specifications in figure legends). Asterisks denote the level of statistical significance ( ∗P < 0.05, ∗∗P < 0.01, ∗∗∗ P <0.001).

# RESULTS

#### Key Features of RTgutGC Cells Exposed in Mucosal Saline in Conventional Culture Plates and Transwell Membranes

Compared with RTgutGC cells cultivated in L-15/C medium, cells cultivated in mucosal saline maintained above 80% cell viability after 12 h exposure (**Figure 1A**). When RTgutGC cells were grown on transwell membrane inserts in 24-well plates, TEER levels increased steadily and reached about 26 × cm2 after 4 weeks of culture (**Figure 1B**). After addition of fluorescent albumin to mucosal saline solution in the apical chamber, basolateral fluorescence levels increased steadily with time when no cells were seeded on the membrane whereas with cells, low fluorescence was observed over the 90 min observation period, demonstrating that the RTgutGC cells formed a barrier and strongly attenuated albumin translocation from the apical to the basolateral chamber (**Figure 1C**). Confocal fluorescence microscopy images of RTgutGC cells grown on conventional culture plates illustrated presence of the tight junction protein Claudin 3 (red) and the nuclei (blue) (**Figure 1D**).We also investigated the uptake of albumin and zymozan in RTgutGC cells, grown on conventional support, as a character of functional enterocytes. During a time course of 3 h, albumin uptake into RTgutGC cells increased (**Figure 1E**). However, RTgutGC cells did not take up zymosan as shown in **Figure 1F**.

#### Effects of LPS and Functional Ingredients Cell Viability

Using a cell viability cut-off level of 80% compared to control cells, 6 h of exposure to 50µg/mL LPS (**Figure 2A**), 75µg/mL nucleotides (**Figure 2B**), 4 mg/mL MOS (**Figure 2C**) and 100µg/mL beta-glucans (**Figure 2D**) were selected as final working concentration for further analysis.

FIGURE 1 | Key features of RTgutGC cells grown on conventional culture plates or transwell membranes. (A) Viability of RTgutGC cells in 24-well-culture plates with 1.5 × 105 cells/mL (78,947 cells per cm2 ) exposed to mucosal saline for 12 h. (B) TEER of RTgutGC cells grown up to 4 weeks in 24-well-culture plates with membrane inserts at initial density of 8 × 104 cells/mL (71,429 cells per cm2 ). (C) Fluorescent levels in basolateral media after fluorescent albumin exposure into apical chamber in 24-well-transwell membrane plates with or without RTgutGC cells. (D) Confocal fluorescence microscopy images of the tight junction protein claudin 3 (red) and the nuclei (blue) in RTgutGC cells grown on conventional culture plates. (E,F) Uptake of albumin (E) and zymosan (F) during the 3 h exposure time with cells cultured in conventional 6-well plates. For both panels (E,F), X axis shows the fluorescence signal from albumin or zymosan in cells. Y axis shows the percentage of albumin/zymosan positive cells out of total live cell population. Data represent mean ± SEM of two independent experiments with 3–4 technical replicates each (wells or inserts). Scale bar = 100µm.

#### TEER and Albumin Translocation

After 6 h of exposure to beta-glucans, TEER levels increased significantly compared to control (**Figure 3**, P < 0.05). Other treatments had no effect on TEER levels (**Figure 3**, original TEER values seen in **Supplemental Figure 1**).

After 6 h of exposure to MOS increases in basolateral albumin fluorescent levels were observed compared to control cells, significantly at 30 and 60 min time points (P < 0.05). No significant effects on the fluorescent level were observed for other treatments (**Figure 4**, P > 0.05).

#### Brush Border Membrane Enzymatic Activity

Brush border membrane enzyme activities (LAP and maltase) were detected in the RTgutGC cells. There were no significant effects of LPS or any of the functional ingredients on LAP (**Figure 5A**) or maltase (**Figure 5B**) activities (P > 0.05).

#### Gene Expression

LPS exposure resulted in markedly increased mRNA levels of several pro-inflammatory cytokines, including interleukin 1β (il1b), interleukin 6 (il6), interleukin 8 (il8), and tumor

single mean values are plotted.

necrosis factor alpha (tnfa). Furthermore, LPS up-regulated the expression of the tight junction gene Claudin 3 (cldn3, P < 0.001), but suppressed the intestinal alkaline phosphatase (ialp) expression (**Figure 6**, P < 0.05).

Pro-inflammatory cytokine genes (il1b and il8) were significantly increased after exposing cells to functional ingredients, especially MOS (P < 0.01). MOS also produced a significant up-regulation of transforming growth factor beta (tgfb) following 6 h of exposure (P < 0.05) while expression of myeloid differentiation factor 88 (myd88) and proliferating cell nuclear antigen (pcna) were significantly decreased (**Figure 6**, P < 0.01).

Compared to control, MOS and beta-glucans up-regulated the expression of cldn3 (P < 0.01) while the expression of ialp and Na/K-ATPase (nkaα1b) decreased significantly following exposure to MOS (**Figure 6**, P < 0.05). There was also a significant decrease in the expression of E-cadherin (cdh1) after exposure to the different functional ingredients (P < 0.05). Gene expression levels of the bile acid transporter solute carrier family 10 member 2 (slc10a2) in RTgutGC cells increased significantly after exposure to nucleotides and MOS (P < 0.05).

In general, immune genes were expressed at comparable relative basal levels in RTgutGC cells as in rainbow trout distal intestinal tissue, whereas most genes related to barrier function and metabolism showed lower relative expression (**Supplementary Table 3**). Overall, nucleotides produced little or no effect on analytical endpoints related to barrier function and gene expression. In order to reduce costs, we therefore chose to omit nucleotide exposures in the additional analyses outlined below.

#### Cell Proliferation

In control cells, the gap area of the culture wells was fully closed by day 4 (**Figure 7**). When treated with LPS or beta-glucans, cells were able to close the gap in a similar pace as in the control cells. In contrast, MOS treatment reduced the cell proliferation and consequently the gap closure rate to <50% at day 4 as shown in **Figure 7**.

#### ROS Generation

As shown in **Figures 8A–C**, viable cell numbers were not affected by treatments, while MOS diminished ROS positive cells markedly (96% decreased, P < 0.001). Moreover, mean fluorescence intensity of ROS in cells were significantly smaller than in other groups (P < 0.001).

cells exposed to LPS and functional ingredients for 6 h. Data are expressed as percent of control cells and represent mean + SEM of two independent experiments with 3 technical insert replicates each. Asterisks denote treatment groups statistically different to the control at the same time point (\*P < 0.05, \*\*\*P < 0.001).

#### F-actin Content and E-cadherin, Aquaporin 8, and Hsp70 Protein Expression

As shown in **Figures 9A,B**, intracellular F-actin contents were significantly increased in LPS and beta-glucan groups (P < 0.01), while MOS treated cells remained at control levels. Western blot analyses demonstrated that expressions levels of Aqp8 and Hsp70 were not influenced by any of the treatments. Ecadherin expression was increased in cells treated with LPS, but decreased in beta-glucan and MOS treated groups (P < 0.01) (**Figure 10**).

#### DISCUSSION

Well-characterized in vitro model systems offer many benefits for screening purposes, given their simplicity and relative inexpensiveness compared to experiments using live animals. They could also serve as essential tools to increase the knowledge of cellular and molecular mechanisms underlying effects observed in animal trials. In the present work, we have continued the ongoing characterization of the first established intestinal epithelial cell line from fish, RTgutGC (18) and evaluated its suitability as an in vitro model for studies of effects of LPS and functional feed ingredients.

#### Functional Characterization of RTgutGC Cells

Based on previously established RTgutGC cell features (18–23, 33), we first confirmed the viability and barrier function of the RTgutGC cells when grown on transwell membranes. Barrier formation was assessed by TEER measurements and fluorescent albumin translocation from the apical to basolateral cell chamber. TEER levels in the present study were comparable to those reported previously (19, 20). We also observed a strong and time-dependent increase in basolateral fluorescence of albumin in wells without cells, whereas low and stable values were observed for wells with cells. Thus, our observations confirmed earlier reports (20, 33) demonstrating that RTgutGC cells grown on permeable inserts strongly attenuate fluorescent model molecules' translocation from apical to basolateral chamber. RTgutGC barrier function was further supported by related gene and protein expression (cldn3, cdh1, Claudin 3) as previously demonstrated (19, 20, 22). We also confirmed the findings by Minghetti and co-workers (20) by demonstrating the viability of the RTgutGC cells when exposed to a buffer designed to mimic the intestinal lumen (25), i.e., mucosal saline. Another indication that the RTgutGC cells function as enterocytes is the presence of brush border membrane enzymatic activity. Previous studies have demonstrated that RTgutGC cells possess alkaline phosphatase activity (18). In the current work, we continued to explore RTgutGC brush border features by measuring activity levels of two important brush border digestive enzymes, i.e., LAP and maltase. Activity of both these enzymes were detected in the RTgutGC cells. Higher LAP activity, but very low maltase activity, were found compared to the results of in vivo tests (34). Altogether, the current re-establishment of key barrier and brush border features demonstrates the robustness of the RTgutGC transwell system and shows that RTgutGC cells develop certain intestinal functions similar to the in vivo situation.

#### Effects of LPS Exposure on RTgutGC

We continued to explore RTgutGC cell immune function by detailed exposures to a prototype PAMP, i.e., LPS. LPS showing no effect on cell viability at concentrations up to 100µg/mL is in line with previous reports suggesting that fish cells without TLR4/CD14 signaling system may be less responsive to LPS compared to mammalian cells (18, 35, 36). The LPS used in the present study was derived from E. coli, and it is possible that LPS isolated from a fish pathogen could be more potent in RTgutGC cells. Anyhow, the final working concentration (50µg/mL LPS) was clearly sufficient to induce immune-related gene expression responses and influence cell proliferation and F-actin contents of RTgutGC cells in this study.