\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[greek,ngerman,english]{babel}



\usepackage{float}








\begin{document}

\title{Splenocytes with fucosylation deficiency promote T cell proliferation
and differentiation through thrombospondin-1 downregulation}



\author[1]{Joo Youn Oh}%
\author[1]{Jung Hwa Ko}%
\author[1]{Jin Suk Ryu}%
\affil[1]{Seoul National University Hospital Department of Ophthalmology}%


\vspace{-1em}



  
  \date{May 20, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Fucosylation plays a critical role in cell-to-cell interactions and
disease progression. However, the effects of fucosylation on splenocytes
and their interactions with T cells remain unclear. In this study, we
aimed to explore the transcriptome profiles of splenocytes deficient in
fucosyltransferase (FUT) 1, an enzyme that mediates fucosylation, and
investigate their impact on the proliferation and differentiation of T
cells. We analyzed and compared the transcriptomes of splenocytes
isolated from \emph{Fut1} knockout (KO) mice and those from wild-type
(WT) mice using RNA-seq. Additionally, we examined the effects of
\emph{Fut1} KO splenocytes on CD4 T cell proliferation and
differentiation, in comparison to WT splenocytes, and elucidated the
mechanisms involved. The comparative analysis of transcriptomes between
\emph{Fut1} KO and WT splenocytes revealed that thrombospondin (THBS)-1,
among the genes related to immune response and inflammation, was the
most highly downregulated gene in \emph{Fut1} KO splenocytes. The
reduced expression of THBS1 was further confirmed using qRT-PCR and flow
cytometry. In coculture experiments, \emph{Fut1} KO splenocytes promoted
the proliferation of CD4 T cells and drove their differentiation towards
Th1 and Th17 cells, compared to WT splenocytes. Moreover, the levels of
IL-2, IFN-\selectlanguage{greek}γ \selectlanguage{english}and IL-17 were increased, while IL-10 was decreased, in T
cells cocultured with \emph{Fut1} KO splenocytes compared to those with
WT splenocytes. These effects of \emph{Fut1} KO splenocytes on T cells
were reversed when THBS1 was replenished. Taken together, our results
demonstrate that splenocytes with \emph{Fut1} deficiency promote CD4 T
cell proliferation and Th1/Th17 differentiation at least in part through
THBS1 downregulation.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Fucosylation is a biological process that involves the transfer of a
fucose residue to oligosaccharide chains carried by cell-surface
glycoproteins or glycolipids, and is regulated by fucosyltransferases
(FUTs) (1). Depending on the site of the oligosaccharide chain to which
the fucose is added, fucosylation is categorized into two types, core
fucosylation and terminal fucosylation, which are mediated by different
FUTs. These fucosylated carbohydrate moieties play a crucial role in
regulating various biological processes within cells, including cell
survival, adhesion, cellular signaling and function, and cell-to-cell or
cell-to-environment interactions. In effect, recent research has
revealed that altered fucosylation in cells and tissues is associated
with a number of diseases, ranging from inflammatory conditions such as
collagen-induced arthritis (2), rheumatoid arthritis (3, 4), allergic
airway inflammation (5), bacterial intestinal inflammation (6) and dry
eye disease (7) to multiple types of cancers (8).

In our previous study (7), we observed increased inflammatory responses
on the ocular surface and activation of CD4 T cells in
\emph{Fut1}knockout (KO) mice with a deficiency in terminal fucosylation
mediated by FUT1, resulting in a dry eye disease phenotype. While the
role of FUT1-mediated fucosylation has been previously investigated in
vascular endothelial cells (3, 9) and synovial fibroblasts at the
cellular level (4), its effects on immune cells and their interactions
with T cells remain unclear. Therefore, in this current study, we
analyzed the transcriptome profiles of splenocytes in \emph{Fut1} KO
mice compared to wild-type (WT) mice, and investigated the impact of
these profiles on T cell proliferation and differentiation.

\textbf{Materials and methods}

\emph{Cell culture and reagents}

Under the approval of the Institutional Animal Care and Use Committee of
Seoul National University Biomedical Research Institute, spleens and
corneas were collected from 8-week-old \emph{Fut1} KO mice (C57BL/6
background, B6.129-Fut1tm1Sdo/J; Jackson laboratory, Bar Harbor, ME) and
C57BL/6 mice (Jackson laboratory), respectively. The confirmation
of\emph{Fut1} gene knockdown in \emph{Fut1} KO mice was performed
following the genotyping protocols provided by Jackson laboratory (10).

Splenocytes were prepared by mashing the spleen, and \emph{Fut1} gene
knockdown was further confirmed in the cells using real-time RT-PCR
(\textbf{Fig. S1} ). CD4 cells were isolated from splenocytes using
mouse CD4 microbeads (CD4 (L3T4) MicroBeads, Miltenyi Biotec, Bergisch
Gladbach, Germany). CD4 cells were then cocultured with splenocytes at a
ratio of 1 : 1 on plates coated with 5 \selectlanguage{greek}µ\selectlanguage{english}g/mL mouse anti-CD3 and
anti-CD28 mAbs (BD pharmingen, San Jose, CA) in RPMI1640 media (Welgene,
Daegu, Korea) containing 10\% fetal bovine serum (Gibco/Thermo Fisher
Scientific, Waltham, MA) for 5 d.

Recombinant mouse thrombospondin-1 (THBS1) protein (5 \selectlanguage{greek}µ\selectlanguage{english}g/mL) (R\&D
Systems, Minneapolis MN) was added to some cocultures.

\emph{RNA sequencing}

Total RNA was isolated from \emph{Fut1} KO and C57BL/6 WT splenocytes,
and RNA quality was assessed using Agilent 2100 bioanalyzer with the RNA
6000 Nano Chip (Agilent Technologies, Amstelveen, The Netherlands). A
total of 500 ng of RNA from each group was used for RNA sequencing.

For RNA sequencing, library construction was performed using the
QuantSeq 3' mRNA-Seq Library Prep Kit (Lexogen, Vienna, Austria)
according to the manufacturer's instructions. The completed library was
purified to remove PCR components. High-throughput sequencing was
carried out as single-end 75 sequencing using the NextSeq 500 platform
(Illumina, San Diego, CA).

For data analysis, the QuantSeq 3' mRNA-Seq reads were aligned using
Bowtie2. Bowtie2 indices were either generated from genome assembly
sequence or the representative transcript sequences for aligning to the
genome and transcriptome. The resulting alignment file was used for
transcript assembly, abundance estimation and detection of differential
gene expression. Differentially expressed genes (DEGs) were determined
based on counts from unique and multiple alignments using coverage in
Bedtools (11). The Read Count data were processed using the quantile
normalization method with EdgeR within R using Bioconductor (12). Gene
classification was performed based on searches conducted by DAVID
(http://david.abcc.ncifcrf.gov/) and Medline databases
(http://www.ncbi.nlm.nih.gov/).

\emph{qRT-PCR}

Splenocytes or corneal tissues were lysed using RNA isolation reagent
(RNA Bee, Tel-Test, Friendswood, TX) and homogenized with an ultrasound
sonicator (Ultrasonic Processor, Cole Parmer Instruments, Vernon Hills,
IL). Total RNA was extracted using RNeasy Mini kit (Qiagen, Hilden,
Germany), and first-strand cDNA was synthesized by reverse transcription
(High Capacity RNA-to-cDNA\textsuperscript{TM} Kit, Applied Biosystems,
Carlsbad, CA). Real-time amplification was performed using
TaqMan\selectlanguage{ngerman}\textsuperscript{®} Universal PCR Master Mix (Applied Biosystems)
on an automated instrument (ABI 7500 Real Time PCR System, Applied
Biosystems) for \emph{Fut1} or \emph{Thbs1} . The data were normalized
to\emph{Gapdh} and expressed as fold changes relative to controls. All
PCR probe sets were purchased from Applied Biosystems
(TaqMan\textsuperscript{®} Gene Expression Assay kits, Applied
Biosystems).

\emph{ELISA}

The cell-free supernatants from the cell cultures were collected after
centrifugation, and their concentrations of IL-2, IFN-\selectlanguage{greek}γ, \selectlanguage{english}IL-17 and IL-10
were measured using the DuoSet\selectlanguage{ngerman}\textsuperscript{®} ELISA kits (R\&D
Systems, Minneapolis MN).

\emph{Carboxyfluorescein succinimidyl ester (CFSE) assay}

For cell proliferation assay, CD4 cells were incubated with 5 \selectlanguage{greek}μ\selectlanguage{english}M CFSE
(CellTrace CFSE Cell Proliferation Kit, Invitrogen/Thermo Fisher
Scientific, Waltham, MA) at 37\selectlanguage{ngerman}°C for 10 min. After PBS washing, the
CFSE-labeled CD4\textsuperscript{+} cells were seeded onto anti-CD3- and
anti-CD28-coated plates, and cocultured with \emph{Fut1} KO or C57BL/6
WT splenocytes as described above. The CFSE fluorescence was measured
using a flow cytometer (Cytek Aurora Flow Cytometer, Cytek biosciences,
Fremont, CA).

\emph{Flow cytometry}

The cells were stained with fluorescence-conjugated Abs against THBS1
(Cat \# MA5-13398, Invitrogen/Thermo Fisher Scientific, Waltham, MA),
CD4, IFN\selectlanguage{english}-\selectlanguage{greek}γ, \selectlanguage{english}IL-17 or Foxp3 (eBioscience, San Diego, CA). For
intracellular staining of cytokines, the cells were treated with an
intracellular fixation buffer (eBioscience IC Fixation Buffer,
Invitrogen/Thermo Fisher Scientific) before staining. For Foxp3
staining, eBioscience Foxp3/Transcription Factor Staining Buffer Set
(Cat \# 00-5523-00, Invitrogen/Thermo Fisher Scientific) was used. The
stained cells were assayed using a flow cytometer (Cytek Aurora Flow
Cytometer, Cytek biosciences) and data were analyzed using FlowJo
software (Tree Star, Inc., Ashland, OR).

\emph{Statistical analysis}

Statistical analysis was performed using Prism software (GraphPad, San
Diego, CA). The normal distribution of data in each group was assessed
using the Shapiro-Wilk test and the Kolmogorov-Smirnov test. For
comparisons between more than two groups, one-way ANOVA with Tukey's
test or Kruskal-Wallis test with Dunn's multiple-comparisons test was
employed to determine significant differences in mean values.
Student's\emph{t} -test was used for comparisons between two groups. The
data were presented as mean \selectlanguage{ngerman}± SD. Statistical significance was defined
as \emph{p}\textless{} 0.05.

\textbf{Results}

\emph{Comparative transcriptome analysis of Fut1 KO vs. WT splenocytes}

To investigate the impact of FUT1-mediated terminal fucosylation on the
immune response in splenocytes, we isolated splenocytes from
\emph{Fut1}KO and WT mice, and analyzed both transcriptomes using
QuantSeq 3\selectlanguage{english}' mRNA sequencing (\textbf{Fig. 1A} ) (13). The comparative
analysis of the transcriptomes identified a total of 124 DEGs with a
fold change of \textgreater{} 2 and a \emph{p} value \textless{} 0.05.
Among these DEGs, 69 transcripts were significantly upregulated, whereas
55 transcripts were downregulated in \emph{Fut1} KO splenocytes when
compared to WT splenocytes (\textbf{Fig. 1A-D} ).

Further categorization of the DEGs based on gene ontology revealed that
7 genes related to immune or inflammatory response were upregulated,
while 4 genes were downregulated in \emph{Fut1} KO splenocytes compared
to WT splenocytes (\textbf{Fig. 1C, E} ). The up-regulated genes in the
immune response or inflammation categories were \emph{Gp2, Hist1h2bk,
Sdc1, Cfb, Fas} and \emph{Mx1} , and the down-regulated genes
included\emph{Thbs1, Orm3, Ccl24} and \emph{Tnfrsf11a} (\textbf{Fig.
1E).}Remarkably, \emph{Thbs1} , which encodes thrombospondin-1, was the
most highly down-regulated gene (4.8-fold) in \emph{Fut1} KO splenocytes
compared to WT splenocytes.

\emph{Reduced THBS1 expression in Fut1 KO splenocytes compared to WT
splenocytes}

To validate the RNA-seq data, we performed real-time RT-PCR assays
on\emph{Fut1} KO and WT splenocytes. The results confirmed a 5.9-fold or
greater increase in THBS1 transcript levels in \emph{Fut1} KO
splenocytes compared to WT splenocytes (\textbf{Fig. 1F} ). In contrast,
THBS1 transcript levels in the corneal tissue did not show any
significant difference between \emph{Fut1} KO and WT mice (\textbf{Fig.
1F} ).

Moreover, we assessed the proportion of THBS1-expressing cells in
splenocytes using flow cytometry. The percentage of
THBS1\textsuperscript{+} cells among total splenocytes was significantly
higher in \emph{Fut1} KO mice than in WT mice (\textbf{Fig. 1G} ).

Taken together, the results indicate that FUT1 deficiency in splenocytes
leads to a reduction in the expression of THBS1 at both mRNA and protein
levels.

\emph{Impact of Fut1 KO splenocytes and THBS1 on T cell proliferation
and differentiation}

Next, to investigate the effects of \emph{Fut1} KO splenocytes and their
reduced levels of THBS1 on the proliferation and differentiation of CD4
T cells, we cocultured CD4\textsuperscript{+} cells isolated from WT
mice with either \emph{Fut1} KO splenocytes or WT splenocytes
(\textbf{Fig. 2A} ). The CFSE dilution assay revealed that the
proliferation of CD4\textsuperscript{+} cells cocultured with\emph{Fut1}
KO splenocytes was significantly higher than those cocultured with WT
splenocytes (\textbf{Fig. 2B} ). Remarkably, the addition of THBS1 to
the coculture reversed the effects of \emph{Fut1}KO splenocytes on CD4+
cell proliferation (\textbf{Fig. 2A} ).

Similar findings were observed with CD4 T cell differentiation. The
coculture of CD4\textsuperscript{+} cells with \emph{Fut1} KO
splenocytes significantly induced the differentiation of
CD4\textsuperscript{+} cells into
IFN-\selectlanguage{greek}γ\selectlanguage{english}\textsuperscript{+}CD4\textsuperscript{+} Th1 cells and
IL-17\textsuperscript{+}CD4\textsuperscript{+} Th17 cells, compared to
the coculture with WT splenocytes (\textbf{Fig. 2C} ). The replenishment
of THBS1 in CD4\textsuperscript{+} cell-\emph{Fut1} KO splenocyte
cocultures effectively suppressed the differentiation of
CD4\textsuperscript{+} cells into Th1 and Th17 subsets (\textbf{Fig. 2C}
). However, neither \emph{Fut1} KO splenocytes nor THBS1 affected the
differentiation of CD4\textsuperscript{+} cells into
Foxp3\textsuperscript{+} regulatory T cells (Tregs) (\textbf{Fig. 2D} ).

Furthermore, we examined the levels of inflammatory cytokines in the
coculture supernatants. The secretion of IL-2, IFN-\selectlanguage{greek}γ \selectlanguage{english}and IL-17 were
significantly increased, while IL-10 was reduced, in
CD4\textsuperscript{+} cells cocultured with \emph{Fut1} KO splenocytes
compared to those cocultured with WT splenocytes (\textbf{Fig. 2E} ).
THBS1 was also effective in reducing the levels of IL-2, IFN-\selectlanguage{greek}γ \selectlanguage{english}and
IL-17, as well as enhancing IL-10, in the coculture of
CD4\textsuperscript{+} cells and \emph{Fut1} KO splenocytes
(\textbf{Fig. 2E} ).

These results suggest that \emph{Fut1} KO splenocytes promote CD4 T cell
proliferation and the differentiation towards Th1 and Th17 cells through
reduced levels of THBS1 at least in part.

\textbf{Discussion}

Our data demonstrated that \emph{Fut1} KO splenocytes exhibited distinct
transcriptome profiles from WT splenocytes, with \emph{Thbs1} showing
the most significant down-regulation in \emph{Fut1} KO splenocytes.
Since THBS1 was effective in inhibiting CD4 T cell proliferation and
Th1/Th17 differentiation, \emph{Fut1} KO splenocytes more significantly
enhanced the proliferation of CD4 T cells and the differentiation into
Th1/Th17 subsets compared to WT splenocytes.

Previous studies have investigated the effects of fucosylation on immune
cells. For instance, T cells treated with the pan-fucosylation inhibitor
2-deoxy-2-fluorofucose (2FF) were shown to be more easily activated by
peptide-major histocompatibility complex (MHC) (14), while treatment
with the terminal FUT1/2 inhibitor, 2-deoxy-D-galactose (2-D-gal),
promoted Th17 cell differentiation (1). Also, 2FF was reported to
upregulate MHC class II, CD83, CD86 and CD40 on dendritic cells (DCs)
(14). Moreover, the overexpression of type I Lewis antigens, which are
terminal fucosylated carbohydrate epitopes, in colon cancer cells
induced an immunosuppressive phenotype in DCs (15). In contrast, it was
reported that 2-D-gal suppressed the expression of MHC class II and CD86
on macrophages and disrupted the interaction between antigen-presenting
cells (APCs) and T cells (2). In addition to these previous findings,
our study showed that deficiency in FUT1-mediated terminal fucosylation
in splenocytes potentiated the stimulating effects of splenocytes as
APCs on CD4 T cell proliferation and Th1/Th17 differentiation due to the
reduced expression of THBS1. Further studies are needed to identify the
specific cell types within splenocytes that exhibit altered THBS1
production in response to FUT1 deficiency, and to investigate the
underlying molecular pathways through which FUT1-mediated fucosylation
regulates THBS1 expression in these cells.

THBS1 is a matricellular glycoprotein that plays crucial roles in
angiogenesis, cancer and inflammation. It is secreted by diverse cell
types, including endothelial cells, fibroblasts, adipocytes, smooth
muscle cells and APCs, reflecting the involvement of THBS1 in regulating
multiple cellular processes associated with tissue repair and
inflammation resolution (16,17). While THBS-1 has long been investigated
in the context of vascular health and disease, recent research has shed
light on its emerging role in the immune response. Especially, THBS1
derived from APCs was reported to suppress the capacity of APCs to
allosensitize CD4 T cells, promoting the survival of corneal allografts
(18). It was also observed that THBS1 expression by APCs was necessary
for TGF-\selectlanguage{greek}β\selectlanguage{english}\textsubscript{2}-expressing APCs to induce
Foxp3\textsuperscript{+} Tregs (19). Furthermore, exogenous THBS1 was
found to inhibit the differentiation of CD4 T cells into Th17 cells and
stimulate their differentiation towards Tregs (20), confirming the role
of THBS1 as a negative regulator of pro-inflammatory T cell activation.
Consistent with these findings, in our study, THBS1 significantly
abrogated the effects of \emph{Fut1} KO splenocytes on the induction of
CD4 T cell proliferation and Th1/Th17 differentiation, although it did
not affect Treg differentiation.

In conclusion, we herein demonstrate that \emph{Fut1} deficiency in
splenocytes leads to reduced THBS1 secretion, thereby promoting CD4 T
cell proliferation and driving Th1/Th17 differentiation. These findings
contribute to our understanding of the interplay between splenocyte
fucosylation, THBS1 expression and T cell responses. Future strategies
aimed at modulating fucosylation in APCs to upregulate THBS1 expression
may hold promise as potential therapeutic approaches for the management
of T-cell-mediated immune disorders.

\textbf{References}

\begin{enumerate}
\tightlist
\item
  Li J, Hsu HC, Mountz JD, Allen JG. Unmasking Fucosylation: from Cell
  Adhesion to Immune System Regulation and Diseases. Cell Chem Biol
  (2018) 17;25:499-512. doi: 10.1016/j.chembiol.2018.02.005.
\item
  Li J, Hsu HC, Ding Y, Li H, Wu Q, Yang P, et al. Inhibition of
  fucosylation reshapes inflammatory macrophages and suppresses type II
  collagen-induced arthritis. Arthritis Rheumatol (2014) 66:2368-79.
  doi: 10.1002/art.38711.
\item
  Isozaki T, Amin MA, Ruth JH, Campbell PL, Tsou PS, Ha CM, et al.
  Fucosyltransferase 1 mediates angiogenesis in rheumatoid arthritis.
  Arthritis Rheumatol (2014) 66:2047-58. doi: 10.1002/art.38648.
\item
  Isozaki T, Ruth JH, Amin MA, Campbell PL, Tsou PS, Ha CM, et al.
  Fucosyltransferase 1 mediates angiogenesis, cell adhesion and
  rheumatoid arthritis synovial tissue fibroblast proliferation.
  Arthritis Res Ther (2014) 16:R28. doi: 10.1186/ar4456.
\item
  Saku A, Hirose K, Ito T, Iwata A, Sato T, Kaji H, et al.
  Fucosyltransferase 2 induces lung epithelial fucosylation and
  exacerbates house dust mite-induced airway inflammation. J Allergy
  Clin Immunol (2019) 144:698-709.e9. doi: 10.1016/j.jaci.2019.05.010.
\item
  Goto Y, Obata T, Kunisawa J, Sato S, Ivanov II, Lamichhane A, et al.
  Innate lymphoid cells regulate intestinal epithelial cell
  glycosylation. Science (2014) 12;345:1254009. doi:
  10.1126/science.1254009.
\item
  Kim KW, Ryu JS, Ko JH, Kim JY, Kim HJ, Lee HJ, et al. FUT1 deficiency
  elicits immune dysregulation and corneal opacity in steady state and
  under stress. Cell Death Dis (2020) 11:285. doi:
  10.1038/s41419-020-2489-x.
\item
  Blanas A, Sahasrabudhe NM, Rodr\selectlanguage{ngerman}íguez E, van Kooyk Y, van Vliet SJ.
  Fucosylated Antigens in Cancer: An Alliance toward Tumor Progression,
  Metastasis, and Resistance to Chemotherapy. Front Oncol (2018) 8:39.
  doi: 10.3389/fonc.2018.00039.
\item
  Amin MA, Campbell PL, Ruth JH, Isozaki T, Rabquer BJ, Alex Stinson W,
  et al. A key role for Fut1-regulated angiogenesis and ICAM-1
  expression in K/BxN arthritis. Ann Rheum Dis (2015) 74:1459-66. doi:
  10.1136/annrheumdis-2013-204814.
\item
  Domino SE, Zhang L, Gillespie PJ, Saunders TL, Lowe JB. Deficiency of
  reproductive tract alpha(1,2)fucosylated glycans and normal fertility
  in mice with targeted deletions of the FUT1 or FUT2
  alpha(1,2)fucosyltransferase locus. Mol Cell Biol (2001) 21:8336-45.
  doi: 10.1128/MCB.21.24.8336-8345.2001.
\item
  Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for
  comparing genomic features. Bioinformatics (2010) 26:841-2. doi:
  10.1093/bioinformatics/btq033.
\item
  Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et
  al. Bioconductor: open software development for computational biology
  and bioinformatics. Genome Biol (2004) 5:R80. doi:
  10.1186/gb-2004-5-10-r80.
\item
  Moll P, Ante, M, Seitz A, Reda T. QuantSeq 3\selectlanguage{english}' mRNA sequencing for RNA
  quantification. Nat Methods (2014) 11:i--iii.
  https://doi.org/10.1038/nmeth.f.376.
\item
  Field JJ, Okeley NM, Zeng W, Law C, Senter PD, Gardai SJ. Abstract
  4005: Understanding the mechanism of 2FF-induced immune modulation.
  Cancer Res (2016) 76 (14\_Supplement):4005.
  https://doi.org/10.1158/1538-7445.AM2016-4005.
\item
  Nonaka M, Ma BY, Murai R, Nakamura N, Baba M, Kawasaki N, et al.
  Glycosylation-dependent interactions of C-type lectin DC-SIGN with
  colorectal tumor-associated Lewis glycans impair the function and
  differentiation of monocyte-derived dendritic cells. J Immunol (2008)
  180:3347-56. doi: 10.4049/jimmunol.180.5.3347.
\item
  Lopez-Dee Z, Pidcock K, Gutierrez LS. Thrombospondin-1: multiple paths
  to inflammation. Mediators Inflamm (2011) 2011:296069. doi:
  10.1155/2011/296069.
\item
  Ramirez MU, Stirling ER, Emenaker NJ, Roberts DD, Soto-Pantoja DR.
  Thrombospondin-1 interactions regulate eicosanoid metabolism and
  signaling in cancer-related inflammation. Cancer Metastasis Rev (2018)
  37:469-476. doi: 10.1007/s10555-018-9737-x.
\item
  Saban DR, Bock F, Chauhan SK, Masli S, Dana R. Thrombospondin-1
  derived from APCs regulates their capacity for allosensitization. J
  Immunol (2010) 185:4691-7. doi: 10.4049/jimmunol.1001133.
\item
  Mir FA, Contreras-Ruiz L, Masli S. Thrombospondin-1-dependent immune
  regulation by transforming growth factor-\selectlanguage{greek}β\selectlanguage{english}2-exposed antigen-presenting
  cells. Immunology (2015) 146:547-56. doi: 10.1111/imm.12517.
\item
  Rodr\selectlanguage{ngerman}íguez-Jiménez P, Chicharro P, Llamas-Velasco M, Cibrian D,
  Trigo-Torres L, Vara A, et al. Thrombospondin-1/CD47 Interaction
  Regulates Th17 and Treg Differentiation in Psoriasis. Front Immunol
  (2019) 10:1268. doi: 10.3389/fimmu.2019.01268.
\end{enumerate}

\textbf{Figure captions}

\textbf{Figure 1. \emph{Fut1} KO splenocytes exhibit decreased levels of
THBS1 in comparison to WT splenocytes.}

\textbf{A.} Experimental protocol. Splenocytes were isolated from WT
or\emph{Fut1} KO mice and subsequently subjected to assays. Scatter plot
from RNA sequencing. The plot displays the normalized data in a
logarithmic scale for each gene, comparing WT splenocytes on the x-axis
to \emph{Fut1} KO splenocytes on the y-axis.

\textbf{B.} Volcano plot comparison of gene expression
between\emph{Fut1} KO and WT splenocytes. The x-axis indicates the fold
change in a logarithmic scale, while the y-axis indicates the
statistical significance of the difference in expression (\emph{p} value
from a\emph{t} test). Red dots represent 69 transcripts that were
upregulated (\textgreater{} 2-fold, \emph{p-} value \textless{} 0.05),
while green dots represent 55 transcripts that were downregulated in
\emph{Fut1} KO splenocytes compared to WT splenocytes.

\textbf{C.} Bar chart comparison of gene expression based on gene
ontology categories. The y axis represents the percentage of DEGs out of
the total genes in each category. The number displayed above each bar
represents the count of genes upregulated (red bar) or downregulated
(green bar) in the specific category.

\textbf{D, E.} Heat maps of RNA sequencing data of \emph{Fut1} KO
splenocytes compared to WT splenocytes. The heat map in D represents the
complete list of DEGs, while the heat map in E presents the DEGs within
the gene ontology category of immune or inflammatory
response.\emph{Thbs1} exhibited the most pronounced downregulation in
\emph{Fut1}KO splenocytes when compared to WT splenocytes.

\textbf{F.} qRT-PCR for Thbs1 in splenocytes or corneal tissues
collected from WT and \emph{Fut1} KO mice. The mRNA levels are presented
as fold changes relative to the levels in the WT control group.

\textbf{G.} Representative and quantitative flow cytometry results for
THBS1\textsuperscript{+} cells in WT or \emph{Fut1} KO splenocytes.

***p \textless{} 0.001, ****p \textless{} 0.0001, ns: not significant,
as analyzed by one-way ANOVA with Tukey's test (F) or Student's\emph{t}
-test (G)

\textbf{Figure 2. \emph{Fut1} KO splenocytes enhance T cell
proliferation and differentiation, while replenishing THBS1 reverses
these effects.}

\textbf{A.} Experimental design. CD4\textsuperscript{+} cells isolated
from WT mice were cocultured with either splenocytes isolated from WT
mice or splenocytes from \emph{Fut1} KO mice for 5 d, after which the
cells were subjected to further assays. In some cocultures, 5 \selectlanguage{greek}µ\selectlanguage{english}g/mL
recombinant THBS-1 was added.

\textbf{B.} CFSE dilution assay for CD4\textsuperscript{+} cell
proliferation

\textbf{C, D.} Representative and quantitative flow cytometry results
for IFN-\selectlanguage{greek}γ\selectlanguage{english}\textsuperscript{+}CD4\textsuperscript{+} and
IL-17\textsuperscript{+}CD4\textsuperscript{+} cells (C) and for
Foxp3\textsuperscript{+}CD4\textsuperscript{+} cells (D)

\textbf{E.} ELISA for secreted levels of IL-2, IFN-\selectlanguage{greek}γ, \selectlanguage{english}IL-17 and IL-10 in
the cocultures of CD4\textsuperscript{+} cells and splenocytes.

*p \textless{} 0.05, **p \textless{} 0.01, ***p \textless{} 0.001, ****p
\textless{} 0.0001, ns: not significant, as analyzed by one-way ANOVA
with Tukey's test or Kruskal-Wallis test with Dunn's
multiple-comparisons test (D)\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fig-1/Fig-1}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fig-2/Fig-2}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

