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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Microbiol.</journal-id>
<journal-title>Frontiers in Microbiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Microbiol.</abbrev-journal-title>
<issn pub-type="epub">1664-302X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmicb.2017.01726</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Microbiology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title><italic>In Silico</italic> Screening of the Human Gut Metaproteome Identifies Th17-Promoting Peptides Encrypted in Proteins of Commensal Bacteria</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Hidalgo-Cantabrana</surname> <given-names>Claudio</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Moro-Garc&#x00ED;a</surname> <given-names>Marco A.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Blanco-M&#x00ED;guez</surname> <given-names>Aitor</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Fdez-Riverola</surname> <given-names>Florentino</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Louren&#x00E7;o</surname> <given-names>An&#x00E1;lia</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Alonso-Arias</surname> <given-names>Rebeca</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>S&#x00E1;nchez</surname> <given-names>Borja</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn001"><sup>&#x002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/197995/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Microbiology and Biochemistry of Dairy Products, Instituto de Productos L&#x00E1;cteos de Asturias, Consejo Superior de Investigaciones Cient&#x00ED;ficas</institution> <country>Villaviciosa, Spain</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Immunology, Hospital Universitario Central de Asturias</institution> <country>Oviedo, Spain</country></aff>
<aff id="aff3"><sup>3</sup><institution>Escuela Superior de Ingenier&#x00ED;a Inform&#x00E1;tica &#x2013; Department of Computer Science, University of Vigo</institution> <country>Vigo, Spain</country></aff>
<aff id="aff4"><sup>4</sup><institution>Centro de Investigaciones Biom&#x00E9;dicas, University of Vigo</institution> <country>Vigo, Spain</country></aff>
<aff id="aff5"><sup>5</sup><institution>Centre of Biological Engineering, University of Minho</institution> <country>Braga, Portugal</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: <italic>Philippe Langella, Institut National de la Recherche Agronomique (INRA), France</italic></p></fn>
<fn fn-type="edited-by"><p>Reviewed by: <italic>Maria de los Angeles Serradell, Consejo Nacional de Investigaciones Cient&#x00ED;ficas y T&#x00E9;cnicas (CONICET), Argentina; Odile Tresse, INRA Centre Angers-Nantes Pays de la Loire, France</italic></p></fn>
<fn fn-type="corresp" id="fn001"><p>&#x002A;Correspondence: <italic>Borja S&#x00E1;nchez, <email>borja.sanchez@csic.es</email></italic></p></fn>
<fn fn-type="other" id="fn002"><p>This article was submitted to Food Microbiology, a section of the journal Frontiers in Microbiology</p></fn></author-notes>
<pub-date pub-type="epub">
<day>08</day>
<month>09</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="collection">
<year>2017</year>
</pub-date>
<volume>8</volume>
<elocation-id>1726</elocation-id>
<history>
<date date-type="received">
<day>28</day>
<month>05</month>
<year>2017</year>
</date>
<date date-type="accepted">
<day>24</day>
<month>08</month>
<year>2017</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2017 Hidalgo-Cantabrana, Moro-Garc&#x00ED;a, Blanco-M&#x00ED;guez, Fdez-Riverola, Louren&#x00E7;o, Alonso-Arias and S&#x00E1;nchez.</copyright-statement>
<copyright-year>2017</copyright-year>
<copyright-holder>Hidalgo-Cantabrana, Moro-Garc&#x00ED;a, Blanco-M&#x00ED;guez, Fdez-Riverola, Louren&#x00E7;o, Alonso-Arias and S&#x00E1;nchez</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>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) or licensor 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.</p></license>
</permissions>
<abstract>
<p>Scientific studies focused on the role of the human microbiome over human health have generated billions of gigabits of genetic information during the last decade. Nowadays integration of all this information in public databases and development of pipelines allowing us to biotechnologically exploit this information are urgently needed. Prediction of the potential bioactivity of the products encoded by the human gut microbiome, or metaproteome, is the first step for identifying proteins responsible for the molecular interaction between microorganisms and the immune system. We have recently published the Mechanism of Action of the Human Microbiome (MAHMI) database (<ext-link ext-link-type="uri" xlink:href="http://www.mahmi.org">http://www.mahmi.org</ext-link>), conceived as a resource compiling peptide sequences with a potential immunomodulatory activity. Fifteen out of the 300 hundred million peptides contained in the MAHMI database were synthesized. These peptides were identified as being encrypted in proteins produced by gut microbiota members, they do not contain cleavage points for the major intestinal endoproteases and displayed high probability to have immunomodulatory bioactivity. The bacterial peptides FR-16 and LR-17 encrypted in proteins from <italic>Bifidobacterium longum</italic> DJ010A and <italic>Bifidobacterium fragilis</italic> YCH46 respectively, showed the higher immune modulation capability over human peripheral blood mononuclear cells. Both peptides modulated the immune response toward increases in the Th17 and decreases in the Th1 cell response, together with an induction of IL-22 production. These results strongly suggest the combined use of bioinformatics and <italic>in vitro</italic> tools as a first stage in the screening of bioactive peptides encrypted in the human gut metaproteome.</p>
</abstract>
<kwd-group>
<kwd>bacterial peptides</kwd>
<kwd>Th17 response</kwd>
<kwd>CD4 cytokines</kwd>
<kwd>flow cytometry</kwd>
<kwd>microbiome</kwd>
<kwd>gut metaproteome</kwd>
</kwd-group>
<contract-num rid="cn001">AGL2013-44039R</contract-num>
<contract-num rid="cn002">PS-2016</contract-num>
<contract-sponsor id="cn001">Ministerio de Econom&#x00ED;a y Competitividad<named-content content-type="fundref-id">10.13039/501100003329</named-content></contract-sponsor>
<contract-sponsor id="cn002">Fundaci&#x00F3;n Cient&#x00ED;fica Asociaci&#x00F3;n Espa&#x00F1;ola Contra el C&#x00E1;ncer<named-content content-type="fundref-id">10.13039/501100002704</named-content></contract-sponsor>
<counts>
<fig-count count="4"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="47"/>
<page-count count="9"/>
<word-count count="0"/>
</counts>
</article-meta>
</front>
<body>
<sec><title>Introduction</title>
<p>The composition of the human microbiome has revealed strong associations with human health. Alterations in the intestinal microbial populations when compared to control groups, denominated dysbiosis, are nowadays associated with several diseases from intestinal and extraintestinal nature (<xref ref-type="bibr" rid="B42">Shreiner et al., 2015</xref>). Modulation of the human microbiome in order to balance the microbial populations toward a healthy situation is a promising intervention to improve human health in the framework of many diseases (<xref ref-type="bibr" rid="B10">Drew, 2016</xref>).</p>
<p>The human microbiome performs key metabolic roles such as production of vitamins, short-chain fatty acids and other essential compounds, digestion of several components of the diet such as fibers, gut homeostasis maintenance and modulation of the host immune response (<xref ref-type="bibr" rid="B33">O&#x2019;Toole et al., 2017</xref>). Gut microbiota and human cells communicate with each other through surface-associate proteins or extracellular components, in a dialog denominated molecular cross-talk (<xref ref-type="bibr" rid="B16">Hevia et al., 2015</xref>). Moreover, bacteria structural components have their own receptors in the innate immune system; in this way, the constant fraction of the surface-associated flagellin is recognized by Toll-like receptor 5 (TLR-5) and the cell-wall component lipopolysaccharide by TLR-4 (<xref ref-type="bibr" rid="B41">Sanchez et al., 2011</xref>). These ligands are denominated microbial associated molecular patterns (MAMPs) and their recognizing counterparts on the human host are termed pattern recognition receptors (PRRs). Recognition and binding of MAMPs to PRRs triggers different intracellular signalization pathways that led to changes on the surface molecules of the immune cells and in their effector secretion profiles, among interleukins and other cytokines (<xref ref-type="bibr" rid="B22">Ley et al., 2006</xref>). The type, amount and temporal pattern of MAMP-PRR interaction will finally determine the type of immune response that can be roughly divided into proinflammatory (mainly Th1, Th2 and Th17) or regulatory responses (Treg) (<xref ref-type="bibr" rid="B37">Ruiz et al., 2016a</xref>).</p>
<p>Extracellular and surface-associated proteins of the gut microbiota have been studied in the last years as candidates responsible for part of the immunomodulatory action of intestinal microorganisms, given that these proteins performs important roles in the interaction with the host and the environment (<xref ref-type="bibr" rid="B38">Ruiz et al., 2016b</xref>). Many of this research has been focused on the identification of molecules responsible for the expansion of Treg cells, a Tcell subset essential in the maintenance of a controlled and low-grade inflammation status of the gut mucosa (<xref ref-type="bibr" rid="B21">Levy et al., 2017</xref>). Few proteins involved in gut homeostasis maintenance and produced by gut bacteria have been identified so far. <italic>Faecalibacterium prausnitzii</italic> is a bacterium whose absence from the human gut microbiome is associated with Crohn&#x2019;s Disease, and which produces a small protein with anti-inflammatory properties by inhibiting the proinflammatory NF-&#x03BA;B pathway (<xref ref-type="bibr" rid="B36">Quevrain et al., 2016</xref>). Lactic acid bacteria are transitory members of the human gut microbiota in individuals with fermented product intake within their diets. It has been shown that some lactobacilli species are able to produce immunomodulatory peptides encrypted in larger extracellular proteins. One of these peptides is STp, which when recognized by dendritic cells isolated from Ulcerative Colitis patients induced a switch toward an anti-inflammatory cytokine profile (<xref ref-type="bibr" rid="B6">Bernardo et al., 2012</xref>; <xref ref-type="bibr" rid="B1">Al-Hassi et al., 2014</xref>).</p>
<p>Therefore, the protein content of an intestinal microorganism may play a key role in the way it modulates the immune system functions in the host (<xref ref-type="bibr" rid="B12">Furusawa et al., 2015</xref>). Identifying the molecules responsible for all the molecular crosstalk mechanisms as well as the immune receptors/signalization pathways induced/repressed by the different MAMPs are needed for understanding the immune mechanism of action of a gut microbiota taken as a whole. With these limitations in mind, our research group has developed the Mechanism of Action of the Human Microbiome (MAHMI) database<sup><xref ref-type="fn" rid="fn01">1</xref></sup> (<xref ref-type="bibr" rid="B7">Blanco-Miguez et al., 2017</xref>). MAHMI is an online resource for the prediction of peptide bioactivity based on their amino acid sequence which is fuelled by public Metahit project metagenomes<sup><xref ref-type="fn" rid="fn02">2</xref></sup>. This database is a unique resource for the organization and processing of potential immunomodulatory peptides encrypted in the human gut metaproteome.</p>
<p>In this work, we have identified 15 potential bioactive peptides through MAHMI pipeline, to test whether this database was able to identify potential immunomodulatory peptides. The <italic>in silico</italic> test was completed with an <italic>in vitro</italic> test where 15 peptides were incubated with human peripheral blood mononuclear cells (PBMCs), and coupled to a multiplex secreted cytokine assay. Main results are discussed next.</p>
</sec>
<sec id="s1" sec-type="materials|methods">
<title>Materials and Methods</title>
<p>Ethics approval for this study (reference code AGL2013-44039-R) was obtained from the Regional Ethics Committee for Clinical Research (<italic>Comit&#x00E9; de &#x00C9;tica de la Investigaci&#x00F3;n del Principado de Asturias</italic>) in compliance with the Declaration of Helsinki. Samples used in this study were obtained from anonymous donors of our blood donation system.</p>
<sec><title>Bioactivity Prediction</title>
<p>The bacterial peptides used in this study were previously selected regarding their theoretical bioactivity based on <italic>in silico</italic> analyses performed through the MAHMI database<sup>1</sup> (<xref ref-type="bibr" rid="B7">Blanco-Miguez et al., 2017</xref>). Briefly, the pipeline starts with the <italic>in silico</italic> digestion of the proteins obtained from the human gut microbiome (gut metaproteome). Potential bioactivity of the encrypted peptides is performed by comparison of their amino acid sequence to a curated database of immunomodulatory peptides. Selected peptides (<bold>Table <xref ref-type="table" rid="T1">1</xref></bold>) were synthesized at GeneCust facilities (Ellange, Luxemburg). Peptides were resuspended in phosphate buffered saline (PBS) (Oxoid Limited, Hampshire, United Kingdom) at a concentration of 2 mg mL<sup>-1</sup> and stored at -80&#x00B0;C until their use.</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Potential immunomodulatory peptides used in this work and information associated.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<th valign="top" align="left">Peptide</th>
<th valign="top" align="left">Peptide sequence</th>
<th valign="top" align="left">Uniprot ID</th>
<th valign="top" align="left">Uniprot protein</th>
<th valign="top" align="left">Uniprot organism</th>
<th valign="top" align="center">Uniprot gene</th>
<th valign="top" align="center">Bioactivity prediction</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">QE14</td>
<td valign="top" align="left">QHVENNKSTPLPME</td>
<td valign="top" align="left">P54355</td>
<td valign="top" align="left">ENTM_BACFG Fragilysin</td>
<td valign="top" align="left"><italic>Bacteroides fragilis</italic></td>
<td valign="top" align="center">btfP</td>
<td valign="top" align="center">60</td></tr>
<tr>
<td valign="top" align="left">LR17</td>
<td valign="top" align="left">LPLAFFVLTFLWALILR</td>
<td valign="top" align="left">Q3V815</td>
<td valign="top" align="left">MTGA_BACFR Monofunctional biosynthetic peptidoglycan transglycosylase</td>
<td valign="top" align="left"><italic>Bacteroides fragilis</italic> YCH46</td>
<td valign="top" align="center">mtgA</td>
<td valign="top" align="center">80</td></tr>
<tr>
<td valign="top" align="left">DW15</td>
<td valign="top" align="left">DEILENVDEVLGNDW</td>
<td valign="top" align="left">Q45119</td>
<td valign="top" align="left">TNPA_BACFG Transposase for insertion sequence element IS21-like</td>
<td valign="top" align="left"><italic>Bacteroides fragilis</italic></td>
<td valign="top" align="center">tnpA</td>
<td valign="top" align="center">75</td></tr>
<tr>
<td valign="top" align="left">KF14</td>
<td valign="top" align="left">KETILEPVEGVGHF</td>
<td valign="top" align="left">Q08425</td>
<td valign="top" align="left">TETQ_BACFG Tetracycline resistance protein TetQ</td>
<td valign="top" align="left"><italic>Bacteroides fragilis</italic></td>
<td valign="top" align="center">tetQ</td>
<td valign="top" align="center">66</td></tr>
<tr>
<td valign="top" align="left">KE13</td>
<td valign="top" align="left">KKMTPANEARPIE</td>
<td valign="top" align="left">D4QFE7</td>
<td valign="top" align="left">BGAL_BIFBI Beta-galactosidase BbgII</td>
<td valign="top" align="left"><italic>Bifidobacterium bifidum</italic></td>
<td valign="top" align="center">bbgII</td>
<td valign="top" align="center">75</td></tr>
<tr>
<td valign="top" align="left">SW14</td>
<td valign="top" align="left">SASLVDGIARKDPW</td>
<td valign="top" align="left">D4QFE7</td>
<td valign="top" align="left">BGAL_BIFBI Beta-galactosidase BbgII</td>
<td valign="top" align="left"><italic>Bifidobacterium bifidum</italic></td>
<td valign="top" align="center">bbgII</td>
<td valign="top" align="center">66</td></tr>
<tr>
<td valign="top" align="left">EY12</td>
<td valign="top" align="left">EMVEDILTGQCY</td>
<td valign="top" align="left">C6H178</td>
<td valign="top" align="left">BGAL2_LACAI Beta-galactosidase LacA</td>
<td valign="top" align="left"><italic>Lactobacillus acidophilus</italic></td>
<td valign="top" align="center">lacA</td>
<td valign="top" align="center">60</td></tr>
<tr>
<td valign="top" align="left">GR16</td>
<td valign="top" align="left">GTSFEGNEYFEGPSIR</td>
<td valign="top" align="left">P48790</td>
<td valign="top" align="left">XYLA_CLOSR Xylosidase/arabinosidase</td>
<td valign="top" align="left"><italic>Clostridium stercorarium</italic></td>
<td valign="top" align="center">xylA</td>
<td valign="top" align="center">100</td>
</tr>
<tr>
<td valign="top" align="left">AR15</td>
<td valign="top" align="left">AIQDEIDQLSTEIDR</td>
<td valign="top" align="left">P80583</td>
<td valign="top" align="left">FLA_CLOTY Flagellin (Fragment)</td>
<td valign="top" align="left"><italic>Clostridium tyrobutyricum</italic></td>
<td valign="top" align="center">fla</td>
<td valign="top" align="center">75</td>
</tr>
<tr>
<td valign="top" align="left">FR16</td>
<td valign="top" align="left">FAIVDEVDSILIDEAR</td>
<td valign="top" align="left">B3DR89</td>
<td valign="top" align="left">SECA_BIFLD Protein translocase subunit SecA</td>
<td valign="top" align="left"><italic>Bifidobacterium longum</italic> DJO10A</td>
<td valign="top" align="center">secA</td>
<td valign="top" align="center">100</td>
</tr>
<tr>
<td valign="top" align="left">WK19</td>
<td valign="top" align="left">WIEAVGYSLTQHPDPELEK</td>
<td valign="top" align="left">E8MGH8</td>
<td valign="top" align="left">HYBA1_BIFL2 Non-reducing end beta-L-arabinofuranosidase</td>
<td valign="top" align="left"><italic>Bifidobacterium longum subsp. longum</italic> ATCC 15707</td>
<td valign="top" align="center">hypBA1</td>
<td valign="top" align="center">100</td>
</tr>
<tr>
<td valign="top" align="left">VF10</td>
<td valign="top" align="left">VPSEKKAELF</td>
<td valign="top" align="left">P38059</td>
<td valign="top" align="left">SLAP_LACHE S-layer protein</td>
<td valign="top" align="left"><italic>Lactobacillus helveticus</italic></td>
<td valign="top" align="center">slpH</td>
<td valign="top" align="center">80</td>
</tr>
<tr>
<td valign="top" align="left">HK11</td>
<td valign="top" align="left">HIGVHSDPVDK</td>
<td valign="top" align="left">P30269</td>
<td valign="top" align="left">AMY_BUTFI Alpha-amylase</td>
<td valign="top" align="left"><italic>Butyrivibrio fibrisolvens</italic></td>
<td valign="top" align="center">amyA</td>
<td valign="top" align="center">75</td>
</tr>
<tr>
<td valign="top" align="left">AF16</td>
<td valign="top" align="left">ASPEDEAASMEKAKAF</td>
<td valign="top" align="left">A6L1Z2</td>
<td valign="top" align="left">G1095_BACV8 Glycosyl hydrolase family 109 protein 5</td>
<td valign="top" align="left"><italic>Bacteroides vulgatus</italic> ATCC 8482</td>
<td valign="top" align="center">BVU_2041</td>
<td valign="top" align="center">80</td>
</tr>
<tr>
<td valign="top" align="left">NR15</td>
<td valign="top" align="left">NAALASYSLASDLDR</td>
<td valign="top" align="left">Q9XD84</td>
<td valign="top" align="left">TIBA_ECOH1 Adhesin/invasin TibA autotransporter</td>
<td valign="top" align="left"><italic>Escherichia coli O78:H11</italic> (H10407)</td>
<td valign="top" align="center">tibA</td>
<td valign="top" align="center">100</td></tr>
</tbody></table>
</table-wrap>
</sec>
<sec><title>Peripheral Blood Mononuclear Cells (PBMC) Isolation</title>
<p>The capability of synthetic bacterial peptides to induce immune modulation <italic>in vitro</italic> was assessed using a PBMC model. PBMCs were isolated from the buffy coat of 5 healthy donors from the Community Center for Blood and Tissues of Asturias (Oviedo, Spain). Then, 5 mL of each buffy were diluted with one volume of PBS and added on the top of a 5 mL of Ficoll-Hypaque (Lymphoprep; Nycomed, Oslo, Norway) for gradient separation. Cells were separated by centrifugation (1,800 rpm, 30 min) with two further washes with PBS; the first one at 1,200 rpm, 10 min (to discard platelets) and the second one at 1,500 rpm, 5 min. The number of PBMCs was estimated using a Neubauer chamber (Brand, VWRI Eurolab, Barcelona, Spain) and adjusted to a final concentration of 2 &#x00D7; 106 mL<sup>-1</sup> in RPMI 1640 broth (Lonza, Basilea, Switzerland) supplemented with 10% (v/v) fetal bovine serum and antibiotics (Sigma-Aldrich, San Luis, MO, United States).</p>
</sec>
<sec><title>Co-cultivation of Peptides and PBMCs</title>
<p>Peripheral blood mononuclear cells were cultivated in round bottom 96 wells microplates using 200 &#x03BC;L of the cell suspension described above. Bacterial peptides were added at a final concentration of 50 &#x03BC;g mL<sup>-1</sup>, based on previous studies of the immunomodulatory peptide STp (<xref ref-type="bibr" rid="B6">Bernardo et al., 2012</xref>). PBMCs were activated with 100 ng mL<sup>-1</sup> of anti-CD3 added to the RPMI media. For each donor positive (LPS, 1 &#x03BC;g mL<sup>-1</sup>) and negative controls of PBMCs stimulation were included. Microplates were incubated for 5 days at 37&#x00B0;C with 5% CO<sub>2</sub>.</p>
</sec>
<sec><title>Cytokine Quantification</title>
<p>After 5 days, supernatant was collected and stored at -80&#x00B0;C for multiplexed cytokine analyses. The production of 18 different cytokines (GM-CSF, IFN&#x03B3;, IL-1&#x03B2;, Il-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12p70, IL-13, IL-17A, IL-18, IL-21, IL-22, IL-23, IL-27, and TNF&#x03B1;) were quantified using the Th1/Th2/Th9/Th17/Th22/Treg Cytokine 18-Plex Human ProcartaPlex<sup>TM</sup> Panel (Affymetrix eBioscience, San Diego, CA, United States) and the Luminex<sup>&#x00AE;</sup> xMap Technology equipment following manufacturer&#x2019;s settings. The results for each cytokine were represented using box plot diagrams and differences between peptides were statistically analyzed.</p>
<p>In the case of peptides FR-16 and LR-17, the following ratios were calculated for each sample: IL10/TNF&#x03B1;, IL10/IFN&#x03B3;, IL10/IL17, IL10/IL4, IFN&#x03B3;/IL17, Th1/Th2, Th17/Th1, Th17/Th2, Th1/Treg, Th2/Treg, Th1 + Th2 + Th17/Treg, Th17/Treg, Th22/Th1, Th22/Th2, Th22/Th17, Th22/Treg and Th22 + Th17/Th1 + Th2. These ratios were calculated considering the T-cell response cytokines, either signature or induced cytokines (<bold>Figure <xref ref-type="fig" rid="F1">1</xref></bold>) and represented using boxplots. Cytokines were included in each ratio according to the review of Wan and Flavell with the addition of the Th22 subset (<xref ref-type="bibr" rid="B45">Wan and Flavell, 2009</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption><p>Schematic representation of the main CD4+ effector T cells and their inducing/signature cytokines. Ratios calculated in this work were calculated taken into account this distribution. <sup>&#x2217;</sup>These cytokines were not included in the ratios as TGF&#x03B2; and TNF&#x03B2; have not been quantified.</p></caption>
<graphic xlink:href="fmicb-08-01726-g001.tif"/>
</fig>
</sec>
<sec><title>Statistical Analyses</title>
<p>All experiments were performed in independent biological quintuplicates. Data distribution did not follow normality, so initial comparisons were performed with the non-parametric Wilcoxon and Tukey pairwise tests. Differences in the value ranks between two conditions were assessed with the Mann&#x2013;Whitney <italic>U</italic> tests for equal medians with Monte Carlo permutations (<italic>n</italic> = 99,999). Comparisons with a <italic>p</italic>-value &#x2264; 0.05 were considered statistically significant. Whisker and boxes plots were generated using ggplot2 in R environment, Past3 v3.15 (<xref ref-type="bibr" rid="B13">Hammer et al., 2001</xref>) and the IBM SPSS Statistics package (SPSS Inc., Chicago, IL, United States).</p>
</sec>
</sec>
<sec><title>Results and Discussion</title>
<p>In the present work we have synthesized 15 peptides (<bold>Table <xref ref-type="table" rid="T1">1</xref></bold>) encrypted in proteins produced by the human gut microbiome and selected due to their high potential immune modulatory properties predicted through the MAHMI pipeline<sup><xref ref-type="fn" rid="fn03">3</xref></sup>. To determine the immune response elicited by these bacterial peptides we selected an <italic>in vitro</italic> PBMC model from human healthy donors, as monocyte-derived dendritic cells have been shown as not suitable for these purposes (unpublished data). Eighteen cytokines related to T-cell response were quantified in the PBMC supernatants of five healthy donors after 5 days of co-culture with the peptides. Cytokine levels were measured basally (PBMCs without anti-CD3), in the activation control (PBMCs with anti-CD3), in the positive control (LPS + activated PBMCs) and for each peptide of study (peptide + activated PBMCs) (<bold>Supplementary Figure <xref ref-type="supplementary-material" rid="SM1">S1</xref></bold>).</p>
<p>In general every peptide was sensed by PBMCs, which reacted with changes in their secreted cytokine profiles compared to the activation control. All the peptides displayed an effect modulating the production of at least one cytokine, although few of them induced consistently the production of interleukins from single T-cell response pathways, represented in <bold>Figure <xref ref-type="fig" rid="F1">1</xref></bold>. For instance, the production of IL-2 and IL-6 were statistically induced (<italic>p</italic> &#x003C; 0.05) by peptides FR-16, LR-17, AR-15, EY-12, KE-13 when compared to the control, as well as the LPS (<bold>Supplementary Figure <xref ref-type="supplementary-material" rid="SM1">S1</xref></bold>). Peptides FR-16 and LR-17, with an immunomodulatory bioactivity prediction in MAHMI database of 100 and 80% respectively (<bold>Table <xref ref-type="table" rid="T1">1</xref></bold>), showed the higher immune modulation capability as reflected in the cytokine secretion induced over PBMCs (<bold>Figure <xref ref-type="fig" rid="F2">2</xref></bold>).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption><p>Main cytokine levels affected by the presence of peptides LR17 and FR16. Boxplots represent median and interquartile range for the selected cytokines (see all in <bold>Supplementary Figure <xref ref-type="supplementary-material" rid="SM1">S1</xref></bold>). These were quantified in the supernatants after 5 days of <italic>in vitro</italic> co-culture of human PBMCs and the bacterial peptides FR-16 and LR-17, from <italic>B. longum</italic> DJO10A and <italic>B. fragilis</italic> YCH46, respectively. Significant differences were assessed by the non-parametric Mann&#x2013;Whitney <italic>U</italic> test and are represented with <sup>&#x2217;</sup>, <sup>&#x2217;&#x2217;</sup>, or <sup>&#x2217;&#x2217;&#x2217;</sup> (<italic>p</italic> &#x003C; 0.05, 0.01, or 0.001 respectively). Significant differences refer to control conditions (PBMCs + anti-CD3).</p></caption>
<graphic xlink:href="fmicb-08-01726-g002.tif"/>
</fig>
<p>FR-16 and LR-17 are bacterial peptides encrypted in proteins from <italic>Bifidobacterium longum</italic> DJ010A and <italic>Bacteroides fragilis</italic> YCH46, species that are amongst the more abundant members of the human microbiome (<xref ref-type="bibr" rid="B3">Arboleya et al., 2016</xref>; <xref ref-type="bibr" rid="B24">Lloyd-Price et al., 2016</xref>). As shown in <bold>Figure <xref ref-type="fig" rid="F2">2</xref></bold>, both peptides increased the production of IL-6, IL17a, IL12p70, IL22, IL23 and TNF&#x03B1; either significantly or at the same levels than LPS did (with <italic>p</italic>-values very close to 0.05). All these cytokines are important in the Th17 and Th22 differentiation pathways (<xref ref-type="bibr" rid="B45">Wan and Flavell, 2009</xref>).</p>
<p>As the T cell response in our model seemed to be modulated by FR16 and LR17, different ratios were calculated taken into account the inducing and signature cytokines for each pathway and also key cytokines such as IL10, TNF&#x03B1; or IFN&#x03B3; (<bold>Supplementary Figure <xref ref-type="supplementary-material" rid="SM2">S2</xref></bold>). As it can be shown in <bold>Figure <xref ref-type="fig" rid="F3">3</xref></bold>, the Th17/Th1 and the Th17/Th2 ratio was consistently higher for both peptides compared with the anti-CD3 activation control. When Th22/Th1 and Th22/Th17 ratios were computed, the basal conditions were displaced toward the Th22 pathway and addition of the anti-CD3 antibody induced production of both Th1 and Th17 cytokines. Interestingly, increase in the Th22 pathway was significantly higher for both peptides whatever the pathway used for calculate the ratio, and always compared to the activation control.</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption><p>Ratios affected by the presence of peptides LR17 and FR16. Boxplots represent median and interquartile range for the ratios (see all in <bold>Supplementary Figure <xref ref-type="supplementary-material" rid="SM2">S2</xref></bold>). Significant differences were assessed by the non-parametric Mann&#x2013;Whitney <italic>U</italic> test and are represented with <sup>&#x2217;</sup>, <sup>&#x2217;&#x2217;</sup>, or <sup>&#x2217;&#x2217;&#x2217;</sup> (<italic>p</italic> &#x003C; 0.05, 0.01, or 0.001 respectively). Significant differences refer to control conditions (PBMCs + anti-CD3).</p></caption>
<graphic xlink:href="fmicb-08-01726-g003.tif"/>
</fig>
<p>Th17 and Th22 response develop important roles in the maintenance of gut homeostasis. In general, it has been reported that commensal microbiota influence the balance between Th1/Th2 (<xref ref-type="bibr" rid="B44">Ventura et al., 2012</xref>). Some probiotic bacteria possess immunomodulatory properties either by acting over immune cell populations and epithelial cells. This is the case of the yogurt starter <italic>Lactobacillus delbrueckii</italic> subsp. <italic>bulgaricus</italic> 8481 which reduced the concentration of cytokine IL-8 in serum following yogurt consumption. IL8 is an important pro-inflammatory chemokine produced by epithelial cells (and also macrophages) with induces chemotaxis in many immune cells, attracting them to infection sites (<xref ref-type="bibr" rid="B31">Moro-Garcia et al., 2013</xref>).</p>
<p>In bifidobacteria, the capability to induce different immune responses is a strain-dependent trait (<xref ref-type="bibr" rid="B27">Lopez et al., 2010</xref>), and for instance <italic>B. bifidum</italic> LMG13195 is able to induce Treg response (<xref ref-type="bibr" rid="B25">Lopez et al., 2011</xref>). On the other hand, surface proteins like the sortase-dependent pili from <italic>B. bifidum</italic> PRL2010 induced a Th1 response (<xref ref-type="bibr" rid="B43">Turroni et al., 2013</xref>). Other surface-associated protein are more related in regulating inflammatory responses such as <italic>Lactobacillus acidophilus</italic> S-layer A, which has been shown to protect mouse against experimentally induced colitis through a specific interaction with SIGNR3 (<xref ref-type="bibr" rid="B23">Lightfoot et al., 2015</xref>). Treg cells have become one of the main focuses of study in immune modulation properties of probiotics, and the balance between Treg/Th responses plays a key role in the maintenance of gut homeostasis (<xref ref-type="bibr" rid="B28">Maloy and Powrie, 2011</xref>). Treg induction has been previously demonstrated for where the surface associated proteins may play a key role. In our study, no significant differences were found regarding Treg cell differentiation induction by our selected peptides. However, interleukin 2 was upregulated by peptides FR-16 and LR-17 (and other peptides) (<bold>Supplementary Figure <xref ref-type="supplementary-material" rid="SM1">S1</xref></bold>). IL-2 is directly related with Treg proliferation and maintenance of the subset population, and indeed Treg cells express the receptor for IL-2 (which is CD25) (<xref ref-type="bibr" rid="B9">Boyman and Sprent, 2012</xref>).</p>
<p>Expansion of Th17 cells is characteristic of segmented filamentous bacteria, which inhabits the murine gut and whose presence is directly linked with this specific T cell response (<xref ref-type="bibr" rid="B17">Ivanov et al., 2009</xref>; <xref ref-type="bibr" rid="B11">Farkas et al., 2015</xref>). Indeed presence of these bacteria confers resistance to the intestinal pathogen <italic>Citrobacter rodentium</italic> (<xref ref-type="bibr" rid="B17">Ivanov et al., 2009</xref>). There is strong scientific evidence of the key role of the gut microbiota in Th17 differentiation to promote a balance in the immune response to ensure a healthy status (<xref ref-type="bibr" rid="B18">Ivanov et al., 2008</xref>). In general, the Th17 pathway serves as protection against extracellular pathogens through recruitment of neutrophils (IL-17) and induction of anti-microbial peptides (IL-22). Th17 cells contribute to the resistance and the clearance of different enteropathogens such as <italic>Salmonella</italic> or <italic>Listeria</italic>, but also for airways pathogens such as <italic>Klebsiella pneumoniae</italic> (<xref ref-type="bibr" rid="B14">Happel et al., 2005</xref>; <xref ref-type="bibr" rid="B19">Kleinschek et al., 2006</xref>).</p>
<p>IL-22 is the signature cytokine of the Th22 cell subset and it has been related with the maintenance of the intestinal epithelium (tissue regeneration and cell proliferation) and contributing to the mucosal integrity ensuring the intestinal barrier function against pathogens (<xref ref-type="bibr" rid="B39">Rutz et al., 2014</xref>). It has also a role regulating CD4+ T cell response to commensal bacteria (<xref ref-type="bibr" rid="B35">Parks et al., 2016</xref>). One of the main roles of Th22 cells is to keep the epithelial barrier and reinforce it against potential pathogens such as <italic>Clostridium difficile</italic> (<xref ref-type="bibr" rid="B15">Hasegawa et al., 2014</xref>). IL-22 develops also important roles in intestinal epithelial cell proliferation and survival, two factors that are compromised in the course of an infection, and IL-22 is mainly produced by Th17 cells, Innate Lymphoid Cells, &#x03B3;&#x03B4; T cells, and Natural Killer T cells (<xref ref-type="bibr" rid="B34">Ouyang et al., 2011</xref>). Human Th22 cells are characterized by producing low amounts of IL-17 and differenciate from na&#x00EF;ve CD4+ T cells with IL-6 and without TGF-&#x03B2; (<xref ref-type="bibr" rid="B47">Zheng et al., 2007</xref>).</p>
<p>LR-17 but not FR-16 induced production of GM-CSF and IL-1&#x03B2;, very similar to the action of LPS over PBMCs (<bold>Figure <xref ref-type="fig" rid="F4">4</xref></bold>). These suggests that LR-17 action could be related to macrophage activation, which are important cells in inflammation with roles including elimination of pathogens and debris clearance. Macrophages show high degree of functional plasticity and may acquire different roles depending on the activation signals. It is well known that IFN&#x03B3;-activated macrophages (Th1) are pro-inflammatory and antimicrobial, and their dysregulation is key in development of several inflammatory disorders, whereas IL4/IL13-activated macrophages (Th2) have anti-inflammatory roles (<xref ref-type="bibr" rid="B4">Arnold et al., 2015</xref>). Macrophages are very abundant in the inflammation sites, and indeed their numbers correlate with Th17 activity, contrarily to other antigen presenting cells such as dendritic cells (<xref ref-type="bibr" rid="B2">Allam et al., 2011</xref>). High amounts of IL-1&#x03B2; were produced in the presence of LR-17, but not in the presence of FR-16. IL-1&#x03B2; is produced by activated macrophages and is an important mediator of the inflammatory response and for Th17 expansion (<xref ref-type="bibr" rid="B20">Lasiglie et al., 2011</xref>), supporting Th17 expansion through macrophage activation as the mechanism of action of LR-17. In fact, the higher concentration of IL-1&#x03B2; induced by LR-17 correlates with the higher amounts of IL-22 detected, as the former induce Th17 cells to produce IL-22 (<xref ref-type="bibr" rid="B30">Monteiro et al., 2013</xref>). Finally this suggests the existence of a specific LR-17 receptor on antigen presentation cells, although this hypothesis deserves further research.</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption><p>Proposed mechanism of action of LR17 and FR16 over the human immune system as supported by cytokine measurement. Significant differences were assessed by the non-parametric Mann&#x2013;Whitney <italic>U</italic> test (<sup>&#x2217;&#x2217;</sup><italic>p</italic>&#x003C; 0.01). Significant differences refer to control conditions (PBMCs + anti-CD3).</p></caption>
<graphic xlink:href="fmicb-08-01726-g004.tif"/>
</fig>
<p>Why LR-17 and not FR-16 activated macrophages is out of the scope of our experimental setup. Strains of the species <italic>Bacteroides fragilis</italic> are known for the production of Polysaccharide A (PSA), an extracellular glycan with anti-inflammatory properties (<xref ref-type="bibr" rid="B29">Mazmanian et al., 2008</xref>), but many other surface components have been shown to possess immunomodulatory activity (<xref ref-type="bibr" rid="B46">Wexler and Goodman, 2017</xref>). On the contrary, higher abundances of commensal bifidobacteria are linked to Treg promoting pathways (<xref ref-type="bibr" rid="B26">Lopez et al., 2012</xref>), and many of the probiotic products targeting intestinal inflammatory disorders contain bifidobacteria (<xref ref-type="bibr" rid="B32">Ng et al., 2010</xref>). The cellular type targeted by bifidobacterial FR-16 peptide remains a mystery.</p>
<p>It must be considered that dysregulation of both Th17 and Th22 pathways are linked to inflammatory and autoimmune diseases. For instance higher production of IL-22 in the colonic mucosa has been observed in patients suffering from inflammatory bowel disease (<xref ref-type="bibr" rid="B35">Parks et al., 2016</xref>), and a pathogenic role for the overproduction of this cytokine has been proposed in rheumatoid arthritis (<xref ref-type="bibr" rid="B39">Rutz et al., 2014</xref>). However, increasing the Th17 response may be protective in other autoimmune diseases such as type 1 diabetes, so this type of encrypted peptides could have an application in the remission of these disorders (<xref ref-type="bibr" rid="B40">Sanchez et al., 2015</xref>). In addition, <italic>in vivo</italic> studies suggest that infection by <italic>Citrobacter rodentium</italic> in IL-23 -/- mice can be prevented by transferring Th22 but not Th17 cells (<xref ref-type="bibr" rid="B5">Basu et al., 2012</xref>). Further research will elucidate precisely the mechanism of action of this type of peptides over CD4+ effector T cells.</p>
</sec>
<sec><title>Conclusion</title>
<p>All bacterial peptides analyzed in this study were able to modulate, <italic>in vitro</italic>, the immune response of human PBMCs, based on the cytokine pattern production. These results corroborated the <italic>in silico</italic> prediction performed with MAHMI database showing the usefulness of this tool to make accurate prediction for a screening in the selection of bioactive peptides. Results obtained for these peptides using human PBMCs strongly suggested that these Th17-promoting peptides might be detected by specific receptors, although this is a speculative statement deserving further experiments. The peptides FR-16 and LR-17, encrypted within the human gut metaproteome, were able to induce a higher immune response that is related with Th17 and Th22 responses. Incubation of these peptides with PBMCs allowed us to test the hypothesis of whether our gut microbiota is able to interact with the immune system through peptides encrypted in larger proteins. We propose the possibility to use bacterial peptides encrypted in the human microbiome proteins, as key inductors to modulate the human immune response for several immunological disorders, as recently reviewed (<xref ref-type="bibr" rid="B8">Blanco-M&#x00ED;guez et al., 2016</xref>).</p>
</sec>
<sec><title>Author Contributions</title>
<p>BS conceived the experiments and wrote the manuscript. RA-A and MM-G designed the immunological study, AB-M, FF-R, and AL participated in the design of the MAHMI database and peptide retrieval, and CH-C and MM-G performed the experiments and drafted the first version of the manuscript. All authors reviewed the final version of the manuscript.</p>
</sec>
<sec><title>Conflict of Interest Statement</title>
<p>BS and CH-C are on the scientific board and co-founders of Microviable Therapeutics. The other 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.</p>
</sec>
</body>
<back>
<fn-group>
<fn fn-type="financial-disclosure">
<p><bold>Funding.</bold> This work was financed by the Spanish &#x201C;Programa Estatal de Investigaci&#x00F3;n, Desarrollo e Inovaci&#x00F3;n Orientada a los Retos de la Sociedad&#x201D; (Grant AGL2013-44039R). Research in our laboratory is funded by the &#x201C;Fundaci&#x00F3;n Cient&#x00ED;fica Asociaci&#x00F3;n Espa&#x00F1;ola Contra el C&#x00E1;ncer&#x201D; (Grant agreement PS-2016).</p>
</fn>
</fn-group>
<sec sec-type="supplementary material">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="http://journal.frontiersin.org/article/10.3389/fmicb.2017.01726/full#supplementary-material">http://journal.frontiersin.org/article/10.3389/fmicb.2017.01726/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Image_1.PDF" id="SM1" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>FIGURE S1</label>
<caption><p>Boxplots represent median and interquartile range of cytokines (pg/mL) quantified in the supernatants after 5 days of <italic>in vitro</italic> co-culture of human PBMCs and bacterial peptides.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Image_1.PDF" id="SM4" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Image_2.PDF" id="SM2" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink">
<label>FIGURE S2</label>
<caption><p>Ratios among the different cytokines taken into account the distribution depicted in <bold>Figure <xref ref-type="fig" rid="F1">1</xref></bold>.</p></caption>
</supplementary-material>
<supplementary-material xlink:href="Image_2.PDF" id="SM3" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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