Abstract

   Nucleated red blood cells (RBCs) of fish have, in the last decade, been
   implicated in several immune-related functions, such as antiviral
   response, phagocytosis or cytokine-mediated signaling. RNA-sequencing
   (RNA-seq) and label-free shotgun proteomic analyses were carried out
   for in silico functional pathway profiling of rainbow trout RBCs. For
   RNA-seq, a de novo assembly was conducted, in order to create a
   transcriptome database for RBCs. For proteome profiling, we developed a
   proteomic method that combined: (a) fractionation into cytosolic and
   membrane fractions, (b) hemoglobin removal of the cytosolic fraction,
   (c) protein digestion, and (d) a novel step with pH reversed-phase
   peptide fractionation and final Liquid Chromatography Electrospray
   Ionization Tandem Mass Spectrometric (LC ESI-MS/MS) analysis of each
   fraction. Combined transcriptome- and proteome- sequencing data
   identified, in silico, novel and striking immune functional networks
   for rainbow trout nucleated RBCs, which are mainly linked to innate and
   adaptive immunity. Functional pathways related to regulation of
   hematopoietic cell differentiation, antigen presentation via major
   histocompatibility complex class II (MHCII), leukocyte differentiation
   and regulation of leukocyte activation were identified. These
   preliminary findings further implicate nucleated RBCs in immune
   function, such as antigen presentation and leukocyte activation.

   Keywords: rainbow trout, red blood cells, RNA-seq, de novo assembly,
   transcriptome, peptide fractionation, LC ESI-MSMS, proteome, functional
   network, immune response

1. Introduction

   Red blood cells (RBCs) are the most copious cell type in blood
   circulation and are well-known for their roles in respiration. Also,
   other roles such as modulation of angiogenesis, coagulation, vascular
   tone and inflammation have been described for mammalian RBCs (reviewed
   in Akbari A. 2011) [[36]1]. In mammals, mature RBCs lack cell nuclei,
   organelles, and ribosomes [[37]2]. In contrast, in non-mammalian
   vertebrates, RBCs have cell nuclei and organelles in their cytoplasm
   [[38]3]. The role of nucleated RBCs as immune response intermediaries
   is a novel field of research [[39]4]. RBCs, rich in hemoglobin, were
   thought to drive processes of gas exchange to tissues. However, in the
   recent past, a set of biological processes related to immunity, such as
   phagocytosis and presentation [[40]5], interferons production
   [[41]6,[42]7,[43]8,[44]9] and cytokines production
   [[45]7,[46]8,[47]10], have been reported in nucleated RBCs from
   different non-mammal vertebrate species. During the last decade,
   transcriptomic and proteomic sequencing have allowed us to identify
   many more genes and proteins in RBCs. Transcriptome sequencing of
   nucleated RBCs has identified the genes responsible for the expression
   of a wide spectrum of biological processes, including immune response
   [[48]6,[49]11]. On the other hand, proteomics sequencing of
   non-nucleated RBCs has significantly evolved
   [[50]12,[51]13,[52]14,[53]15], allowing us to significantly increase
   the number of identified proteins from a few hundred to almost 2700
   proteins [[54]12,[55]13]. However, to our knowledge, no study on
   nucleated RBCs proteome sequencing has been published (although
   extensive research exists on cell proteome of the different cell types
   during human erythroid differentiation [[56]16]).

   In this manuscript we show a combined transcriptomic and proteomic
   evaluation of rainbow trout nucleated RBCs (see [57]Figure 1 for a
   representative schema of the procedure). In order to achieve this, we
   performed RNA-sequencing (RNA-seq) and label-free shotgun proteomic
   analyses of RBCs pooled from eight fishes. For transcriptome profiling,
   a de novo assembly of rainbow trout RBCs was conducted to create a
   transcriptome database for RBCs gene mapping. For proteome profiling,
   we developed a novel proteomic analysis method that combined: (a)
   fractionation into cytosolic and membrane fractions, (b) hemoglobin
   removal of the cytosolic fraction, (c) protein digestion, and (d) a
   novel step with pH reversed-phase peptide fractionation and final
   Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometric
   (LC ESI-MS/MS) analysis of each of the fractions.

Figure 1.

   [58]Figure 1
   [59]Open in a new tab

   Schema representing the different steps in the experiment described
   here, from sample collection to data analysis.

   In silico functional profiling revealed the presence of novel and
   striking networks for rainbow trout nucleated RBCs, mainly related to
   innate and adaptive immunity. Functional pathways related to regulation
   of hematopoietic cell differentiation, antigen presentation via major
   histocompatibility complex class II (MHCII), leukocyte differentiation,
   and regulation of leukocyte activation were found in rainbow trout RBCs
   transcriptome. This study provides new knowledge on the immune
   functions of nucleated RBCs.

2. Materials and Methods

2.1. Fish

   Rainbow trout (Oncorhynchus mykiss) of approximately 6 cm, obtained
   from a commercial fish farm (PISZOLLA S.L., CIMBALLA FISH FARM,
   Zaragoza, Spain), were maintained at University Miguel Hernandez (UMH)
   facilities at 14 °C, with a re-circulating dechlorinated-water system,
   at a stocking density of 1 fish/3 L, and fed daily with a commercial
   diet (Skretting, Burgos, Spain). Fish were acclimatized to laboratory
   conditions over 2 weeks. All activities involving animal handling and
   animal care were done in accordance with EU Directive EC86/609.

2.2. Blood Sampling and Red Blood Cells Purification

   Rainbow trout RBCs were obtained from the peripheral blood of fish
   which died through overexposure to tricaine (tricaine methanesulfonate,
   Sigma-Aldrich, Madrid, Spain; 0.2 g/L), as previously described
   [[60]8]. Briefly, peripheral blood was sampled from the caudal vein.
   Then, RBCs were purified by two consecutive density gradient
   centrifugations (7206 g, Ficoll 1.007; Sigma-Aldrich). Purity of RBCs
   of 99.9% was estimated by optical microscopy evaluation ([61]Figure
   S1).

2.3. Transcriptome Sequencing

2.3.1. Complementary DNA Library Preparation and Illumina Sequencing

   RBCs isolated from eight fishes (10^6 cells per fish) were lysed with
   9.5 µL of 10× Lysis buffer (Clontech, Takara Bio, Mountain View, CA,
   USA) and 0.5 µL of ribonuclease (RNase) Inhibitor (Invitrogen,
   Thermo-Fischer Scientific Inc., Waltham, MA, USA), and preserved at −80
   °C, until complementary DNA (cDNA) library construction.

   Lysed RBCs from the eight fishes were pooled, and cDNA was directly
   produced from lysed cells using a SMART-Seq v4 Ultra Low Input RNA Kit
   (Clontech, Takara Bio). cDNA integrity was tested using a Bioanalyzer
   2100 (Agilent, Santa Clara, CA, USA). The library construction was
   carried out using an Illumina Nextera XT Library Preparation Kit
   (Illumina Inc., San Diego, CA, USA). Generated cDNA fragments were
   sequenced with the lllumina Hiseq 2500 platform, using 100 bp
   paired-end sequencing reads. Sequence reads are available at SRA-NCBI,
   SRA-NCBI Accession SRP133501. RNA-Seq library preparation and
   sequencing were carried out by STABVida Lda (Caparica, Portugal).

2.3.2. De Novo Assembly Bioinformatics Procedure

   In order to create a transcript database specific to, or enriched for,
   rainbow trout RBCs, a de novo assembly of RBCs expressed short reads
   was carried out. CLC Genomics Workbench (version 9.5.4) [[62]17] was
   used for expressed short reads de novo assembly. Raw data were filtered
   by removing short, duplicated and low quality reads. For each original
   read, the regions of the sequence to be removed were determined
   independently for each type of trimming operation: Quality trimming
   (based on quality ratings), and Ambiguity trimming. The trimming
   parameters applied were: ambiguous limit = 2 nucleotides, quality limit
   = 0.01 (error probability), minimum number of nucleotides = 30. After
   quality trimming, raw sequence data were de novo assembled. One list of
   sequences corresponding to generated contigs, and one mapping file were
   generated. After initial contig creation, reads were mapped back to
   contigs for assembly correction, using the following parameters: word
   size = 54, bubble size = 50, length fraction = 0.8 and similarity
   fraction = 0.8. To remove redundancy from assemblies, generated contigs
   were analyzed with CD HIT EST (Version 4.6) [[63]18,[64]19], using the
   following parameters: -c 0.85 -n 8.

2.3.3. BLASTing of Assembled Contigs, Gene Sequence Retrieval, Red Blood
Cells Transcript Database Construction and Functional Annotation

   De novo assembled contigs were BLASTed (using Nucleotide Basic Local
   Alignment Search Tool, BLASTn,
   [65]https://blast.ncbi.nlm.nih.gov/Blast.cgi), with a cut off E-value
   of 1.00 × 10^−3) against a local Teleostei messenger RNA (mRNA)
   Reference Sequence (RefSeq) database downloaded from NCBI
   ([66]https://www.ncbi.nlm.nih.gov, last update: 20072017), using
   Blast2GO PRO version 4.1.9 [[67]20]. Then, full sequences of the top
   blast hit obtained in the previous step were retrieved from NCBI, based
   on accession ids. Duplicated and similar sequences with 95% similarity
   were removed. These steps were performed using Blast2GO PRO version
   4.1.9. Resulting mRNA RefSeq curated database{Ortega-Villaizan, 2018
   #28} (referred to hereafter as RBCs transcript database [[68]21]), was
   enriched with rainbow trout (NCBI, last update: 09082017), Atlantic
   salmon-Salmo salar-(NCBI, last update: 09082917), and zebrafish-Danio
   rerio-(NCBI, last update: 31072017) mRNA RefSeq annotations in NCBI.
   This curated and enriched database was used as a reference for
   following sample mapping and annotation analyses. The RBCs transcript
   database was finally annotated against local Teleostei protein RefSeq
   database downloaded from NCBI (last update: 17072017), using Basic
   Local Alignment Search Tool (BLASTx,
   [69]https://blast.ncbi.nlm.nih.gov/Blast.cgi) with a cut off E value of
   1.00 × 10^−3.

2.3.4. Red Blood Cells Transcriptome Mapping and Gene Expression Profiling

   Sample raw sequence data was mapped against the RBCs transcript
   database using CLC Genomics Workbench (version 10.1.1) [[70]22]. Before
   mapping, analysis started with the trimming of raw sequences to
   generate high quality data only. For each original read, the regions of
   the sequence to be removed were determined independently for each type
   of trimming operation: Quality trimming (based on quality ratings),
   Ambiguity trimming, and Length trimming. The following trimming
   parameters were applied: ambiguous limit = 2 nucleotides, quality limit
   = 0.01 (error probability), minimum number of nucleotides = 15. High
   quality sequencing reads (approximately 40 million reads) were mapped
   against RBCs transcript database, using the following parameters:
   length fraction = 0.6, similarity fraction = 0.5. Gene prediction and
   annotation was conducted on the RBCs transcripts database. The
   expression level of genes was obtained by counting the number of reads
   mapped to a gene.

2.4. Proteome Sequencing

2.4.1. Protein Digestion

   RBCs isolated from eight fishes (8 × 10^6 cells per fish) were pooled
   and pelleted by centrifugation (5 min, 700× g). Supernatant was
   removed, and cell pellet (~70–100 μL) was mixed with 250 μL of
   deionized water, and then frozen at −80 °C for 3 h. After thawing, it
   was centrifuged at 17,000× g for 20 min at 4 °C, to separate cytosolic
   supernatant and pelleted membrane fractions. To purify the membrane
   fraction, the pellet was washed twice with 500 µL of deionized water,
   and then centrifuged at 20,000× g for 10 min at 4 °C. After washing,
   the new membrane pellet was dissolved with 200 µL of chaotropic lysis
   buffer containing 8.4 M urea (USB Corporation, Cleveland, OH, USA), 2.4
   M thiourea (Sigma-Aldrich), 5% CHAPS (Sigma-Aldrich), 5 mM TCEP
   (Sigma-Aldrich) and a protease inhibitor cocktail (Sigma-Aldrich), for
   15 min, on ice. Homogenization of the membrane pellet was achieved by
   ultrasonication for 5 min on ultrasonic bath Branson 2510 (Marshall
   Scientific, Hampton, NH, USA). The sonicated membrane was centrifuged
   again at 20,000× g for 10 min at 4 °C, and the supernatant containing
   solubilized membrane fraction proteins was used for further analysis.
   Then, 40 µg of protein was precipitated using the methanol/chloroform
   method [[71]23], and re-suspended in 20 µL of multichaotropic sample
   solution composed of 7 M Urea, 2 M thiourea and 10 mM triethylammonium
   bicarbonate (TEAB) (Sigma-Aldrich), called hereafter UTT buffer.

   The cytosolic fraction, approximately 300 μL, was depleted of
   hemoglobin using HemoVoid^TM kit (Biotech Support Group, Monmouth
   Junction, NJ, USA), in accordance with the manufacturer’s instructions
   [[72]24]. After hemoglobin removal, the eluted fraction was transferred
   to a Pall Omega Nanosep^® (Pall Corporation, Port Washington, NY, USA)
   centrifugal filter device (molecular weight cut-off (MWCO) 10 kDa), and
   concentrated by centrifugation at 14,000× g for 15 min at 4 °C.
   Finally, the hemoglobin depleted-cytosolic fraction were dialyzed with
   300 µL of UTT buffer, and concentrated into a volume of ~50–80 µL (20
   min, 14,000× g, 4 °C). Then, 40 µg of protein were diluted with 20 µL
   of multichaotropic sample solution UTT buffer.

   Both protein fractions were reduced with 2 µL of 50 mM TCEP, pH 8.0, at
   37 °C for 60 min, before 1 µL of 200 mM cysteine-blocking reagent MMTS
   (SCIEX, Foster City, CA, USA) was added for 10 min at room temperature.
   Then, the cytosolic and membrane fractions were diluted to 140 µL with
   25 mM TEAB, to reduce the urea concentration. Finally, digestions were
   initiated by adding 6 and 2 µg respectively of Pierce MS-grade trypsin
   (Thermo-Fisher Scientific Inc., Waltham, MA, USA) to each fraction, in
   a ratio of 1:20 (w/w), and then incubated at 37 °C overnight on a
   shaker. The fraction digestions were evaporated to dryness in a vacuum
   concentrator.

2.4.2. pH Reversed-Phase Peptide Fractionation

   Offline high pH reversed-phase peptide fractionation of peptides from
   cytosolic fraction was performed on a SmartLine (Knauer, Berlin,
   Germany) high pressure liquid chromatography (HPLC) system using an
   XBridge C18 column (100 × 2.1 mm, 5 μm particle) (Waters Corporation,
   Milford, MA, USA). Mobile phases A and B were used for chromatography.
   The composition of mobile phase A was 10 mM ammonium hydroxide (pH 9.4)
   (Sigma-Aldrich), whereas composition of mobile phase B was 80% methanol
   (Scharlab S.L, Barcelona, Spain) and 10 mM ammonium hydroxide (pH 9.3).
   Dried-up peptide pellet was dissolved in 100 μL of mobile phase A,
   injected into a sample loop, and then fractionated using a linear
   gradient of 0–100% mobile phase B at 150 μL/min for 90 min. Thirty
   fractions were collected and then pooled, with an alternating numerical
   sequence, into three fractions (i.e., fractions 1 + 4 + 7 + 10 + 13 +
   16 + 19 + 22 + 25 + 28) and dried.

2.4.3. Liquid Chromatography and Mass Spectrometry Analysis

   Peptide fractions were cleaned/desalted using Stage-Tips with Empore 3M
   C18 disks (Sigma-Aldrich). One microgram of each peptide fraction was
   used for a 1D-nano LC ESI-MS/MS analysis, using a nano-liquid
   chromatography system (Eksigent Technologies nano LC Ultra 1D plus;
   SCIEX, Foster City, CA, USA), coupled to a high speed Triple TOF 5600
   mass spectrometer (SCIEX) with a Nanospray III source. The analytical
   column used was a silica-based reversed phase Acquity UPLC^® M-Class
   Peptide BEH C18 Column (Waters Corporation). The trap column was a C18
   Acclaim PepMap^TM 100 (Thermo-Fisher Scientific Inc.), 100 µm × 2 cm, 5
   µm particle diameter, 100 Å pore size, switched on-line with the
   analytical column. A loading pump delivered a solution of 0.1% formic
   acid in water at 2 µL/min. The nano-pump provided a flow-rate of 250
   nL/min, and was operated under gradient elution conditions. Cytosolic
   peptide fractions were separated using a 150 min gradient ranging from
   2% to 90% mobile phase B (mobile phase A: 2% acetonitrile (Scharlab
   S.L), 0.1% formic acid (Sigma-Aldrich); mobile phase B: 100%
   acetonitrile, 0.1% formic acid). Two hundred & fifty minutes’ gradient
   was used for the membrane fraction, using the same gradient conditions.
   Injection volume was 5 µL.

   Data were acquired using an ionspray voltage floating 2300 V, curtain
   gas 35, interface heater temperature 150, ion source gas 125 and
   declustering potential 150 V. For Information-Dependent Acquisition
   (IDA) parameters, 0.25 s mass spectrometry (MS) survey scan in the mass
   range of 350–1250 Da were followed by 35 MS/MS scans of 100 ms in the
   mass range of 100–1800. Switching criteria were set to ions greater
   than mass-to-charge ratio (m/z) 350 and smaller than m/z 1250 with a
   charge state of 2–5 and an abundance threshold >90 counts (cps). Former
   target ions were excluded for 15 s.

2.4.4. Proteomics Data Analysis and Sequence Search

   Mass spectrometry data obtained were processed using PeakView 2.2
   Software (SCIEX [[73]25]) and exported as mgf files, which were then
   searched, using Mascot Server v2.5.1 (Matrix Science, London, UK),
   against a protein database including Teleostei protein sequences from
   Uniprot/Swissprot Knowledgebase (last update: 20170412, 2.542.118
   sequences), together with commonly occurring contaminants. Search
   parameters were set as follows: enzyme, trypsin; allowed missed
   cleavages, 2; methylthiolation (C) as fixed modification; and acetyl
   (Protein N-term), Oxidation (M), Gln → pyro-Glu (N-term Q) and Glu →
   pyro-Glu (N-term E) as variable modifications. Peptide mass tolerance
   was set to ±25 ppm for precursors and 0.05 Da for fragment masses. The
   confidence interval for protein identification was set to ≥95% (p value
   < 0.05) and only peptides with an individual ion score above the 1%
   False Discovery Rate (FDR) at PSM (peptide-to-spectrum matches) level
   were considered to have been correctly identified.

2.5. Pathway Enrichment Analysis

   In order to evaluate functionally grouped Gene Ontology (GO) and
   pathway annotation networks of expressed genes and proteins, pathway
   enrichment analysis was performed using the ClueGO [[74]26] and
   CluePedia [[75]27] Cytoscape [[76]28] plugins. The GO Immune System
   Process functional pathway database was used. p value ≤ 0.05 and Kappa
   score of 0.4 served as threshold values. Protein-protein interaction
   (PPI) networks were analyzed using STRING v10.5
   ([77]http://string.embl.de/) [[78]29], with a medium confidence score
   threshold of 0.4. The Homo sapiens model organism was used for ClueGO
   and STRING analyses. Gene symbols were obtained through sequence
   homology of RBCs transcript database genes with Homo sapiens
   orthologues, using Blast2GO version 4.1.9.

2.6. RNA Extraction and Reverse Transcription Real Time Polymerase Chain
Reaction Analysis

   RNA extraction and reverse transcription real time polymerase chain
   reaction (RT-qPCR) was performed as previously described [[79]8], using
   specific primers and probe for mhcII gene (Forward:TGCCATGCTGATGTGCAG;
   Reverse: GTCCCTCAGCCAGGTCACT; Probe: CGCCTATGACTTCTACCCCAAACAAAT)
   [[80]30]. Gene expression was analyzed by the 2^−ΔCt method [[81]31]
   and ef1α gene (Forward: ACCCTCCTCTTGGTCGTTTC; Reverse:
   TGATGACACCAACAGCAACA; Probe: GCTGTGCGTGACATGAGGCA) [[82]32] was used as
   endogenous control.

   Besides, RNA extracted from RTS-11 cell line [[83]33] (donated by Dr.
   Niels Bols) and RTG-2 cell line (ATCC^® CCL-55™) were respectively used
   as antigen presenting cell (APC) and non-APC cell types, for mhcII gene
   expression comparison.

2.7. RBCs Single-Cell Sorting

   RBCs from one fish were single-cell sorted, in order to obtain a sample
   of pure RBCs (20–30 cells), using BD FACSJazz™ cell sorter (BD
   Biosciences, Madrid, Spain). Sorted RBCs were visualized using an IN
   Cell Analyzer 6000 (GE Healthcare, Little Chalfont, UK) cell imaging
   system. The sample was lysed with 9.5 µL of 10× Lysis buffer and 0.5 µL
   of RNase Inhibitor, and preserved at −80 °C until cDNA library
   construction.

3. Results and Discussion

   RBCs transcriptome profiling identified 14,008 genes, from which 13,937
   genes were considered expressed since they were detected above a
   threshold of 10 reads mapped. [84]Table 1 shows statistics of de novo
   assembly, RNA-seq raw data and mapping. Conversely, proteome profiling
   identified 1.770 proteins, where 724 proteins had more than 2 PSMs.
   Among those genes with more than 10 gene reads and proteins with more
   than 2 PSMs and 670 genes and proteins ([85]Table S1), were common to
   both transcriptome and proteome profiling respectively ([86]Figure S2).
   A Cytoscape pathway enrichment analysis, with Immune System Process
   GO-terms, was performed in order to evaluate functionally grouped
   GO-terms and pathway annotation networks which are mainly represented
   in rainbow trout nucleated RBCs immune response. Results showed five
   strongly represented networks of interest: (i) regulation of
   hematopoietic stem cell differentiation, (ii) neutrophil degranulation,
   (iii) positive regulation of leukocyte activation, (iv) antigen
   processing and presentation of exogenous peptide antigen via MHCII, and
   (v) leukocyte differentiation ([87]Figure 2a,b, [88]Table S2).
   Subsequently, an interactome network was built for each GO-term set of
   proteins, to identify protein-protein interactions, and predict
   functional associations. We found that proteins grouped in antigen
   processing and presentation of exogenous peptide antigen via MHCII
   network highly interacted with each other ([89]Figure 3), with a FDR p
   value 1.37 × 10^−27 and PPI enrichment p value < 1.0 × 10^−16. Fourteen
   proteins identified in this GO-term were: ACTR1B (ARP1 actin related
   protein 1 homolog B), AP1B1 (adaptor related protein complex 1 beta 1
   subunit), AP2A1 (adaptor related protein complex 2 alpha 1 subunit),
   AP2A2 (adaptor related protein complex 2 alpha 2 subunit), ARF1 (ADP
   ribosylation factor 1), CANX (calnexin), CAPZA1 (capping actin protein
   of muscle Z-line alpha subunit 1), CLTA (clathrin light chain A), CLTC
   (clathrin heavy chain), CTSD (cathepsin D), DNM2 (dynamin 2), DYNC1H1
   (dynein cytoplasmic 1 heavy chain 1), DYNLL2 (dynein light chain
   LC8-type 2), RAB7A (member RAS oncogene family). Moreover, the
   expression of these genes was corroborated in a single-cell sorted RBCs
   RNA-seq. Gene reads are indicated in [90]Table S3. Besides, MHCII gene
   reads were detectable in single-cell sorted RBCs RNA-seq ([91]Table
   S3).

Table 1.

   De novo assembly, RNA-sequencing (RNA-seq) raw data and mapping
   statistics.
   De Novo Assembly
        Total reads 404,825,036
        Number of aligned reads 286,555,140
        Total contigs 1,056,546
        Contigs after CD HIT EST c 0.85 862,667
   RBCs Transcript Database
        Genes after assembly BLAST, gene retrieval, removal of duplicates
   and 95% similar sequences 106,361
        Genes after adding Oncorhynchus mykiss, Salmo salar, and Danio
   rerio NCBI sequences 137,444
   Raw Data and Mapping
        Total reads 93,177,954
        Reads after trimming 92,391,474
        Mapped reads 52,118,053
        Un-mapped reads 40,273,421
   [92]Open in a new tab

Figure 2.

   [93]Figure 2
   [94]Open in a new tab

   Cytoscape pathway network of significantly over-represented Immune
   System Process Gene Ontology (GO)-terms in RBCs transcriptome and
   proteome profiling common genes and proteins. (a) Pathway network. Each
   node represents a GO-term from Immune System Process. Node size shows
   GO-term significance (p value): smaller p value, larger node size. Edge
   (lines) between nodes indicate the presence of common genes: thicker
   line implies a larger overlap. GO-terms are classified into several
   function groups (different node color). The label of the most
   significant GO-term for each group is highlighted. (b) A pie chart of
   Immune System Process function groups. Asterisks denote GO-term
   significance. Functional groups are labelled as follows: Dark pink =
   regulation of hematopoietic stem cell differentiation, dark blue =
   neutrophil degranulation, light blue = positive regulation of leukocyte
   activation, light green = antigen processing and presentation of
   exogenous peptide antigen via MHCII, and dark green = leukocyte
   differentiation. A list of all over-represented terms and statistics is
   provided in [95]Table S2.

Figure 3.

   [96]Figure 3
   [97]Open in a new tab

   Constructed protein-protein interactions of a set of proteins of
   antigen processing and presentation of exogenous peptide antigen via
   MHCII GO-term using STRING software. Nodes represent proteins, while
   edges denote the interactions between two proteins. Red nodes highlight
   proteins functionally annotated with STRING software in GO-term antigen
   processing and presentation of exogenous peptide antigen via MHCII.
   White nodes represent proteins not functionally annotated in the
   highlighted GO-term. Network edge line thickness indicates the strength
   of data support.

   These proteins, among others, may provide nucleated RBCs with the
   essential machinery to participate in the production of antigenic
   peptides, and their loading onto MHCII molecules within the
   compartments of endosomal–lysosomal system [[98]34]. Unlike MHCI
   molecule—which is widely expressed on the cell surface of nearly all
   nucleated cells, including nucleated RBCs [[99]35]—MHCII molecules are
   generally restricted to some endothelial cells and a subset of
   antigen-presenting cells (APCs), such as macrophages, dendritic cells,
   and B cells [[100]36]. To our knowledge, there is only one record
   describing low levels of transcripts expression for MHC II in chicken
   nucleated RBCs [[101]37]. We have also observed transcripts expression
   in rainbow trout nucleated RBCs ([102]Figure S3). Moreover, it has been
   described how rainbow trout nucleated RBCs were shown to engulf Candida
   albicans, and presented it to macrophages [[103]5]. Taken altogether,
   this evidence strongly suggests that nucleated RBCs may participate in
   antigen presentation, via MHCII, as professional APCs.

   These findings have broad implications in the knowledge of nucleated
   RBCs immune functions, since they open a novel topic of investigation
   where nucleated RBCs may act as professional APCs, and may be
   participants of the immunological synapse of T- and NK-cells. The
   function of MHCII pathway molecules in nucleated RBCs, and their role
   under viral infection scenarios, remains to be studied, and constitutes
   a part of our ongoing research.

Acknowledgments