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<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">PLoS ONE</journal-id>
<journal-id journal-id-type="publisher-id">plos</journal-id>
<journal-id journal-id-type="pmc">plosone</journal-id>
<journal-title-group>
<journal-title>PLOS ONE</journal-title>
</journal-title-group>
<issn pub-type="epub">1932-6203</issn>
<publisher>
<publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, CA USA</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.1371/journal.pone.0288084</article-id>
<article-id pub-id-type="publisher-id">PONE-D-23-05036</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Proteomics</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Research and analysis methods</subject><subj-group><subject>Database and informatics methods</subject><subj-group><subject>Biological databases</subject><subj-group><subject>Proteomic databases</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Proteomics</subject><subj-group><subject>Proteomic databases</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Organisms</subject><subj-group><subject>Eukaryota</subject><subj-group><subject>Animals</subject><subj-group><subject>Invertebrates</subject><subj-group><subject>Molluscs</subject><subj-group><subject>Cephalopods</subject><subj-group><subject>Octopus</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Zoology</subject><subj-group><subject>Animals</subject><subj-group><subject>Invertebrates</subject><subj-group><subject>Molluscs</subject><subj-group><subject>Cephalopods</subject><subj-group><subject>Octopus</subject></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Metabolism</subject><subj-group><subject>Metabolic processes</subject><subj-group><subject>Proteolysis</subject></subj-group></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Proteins</subject><subj-group><subject>Proteolysis</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Research and analysis methods</subject><subj-group><subject>Storage and handling</subject><subj-group><subject>Specimen storage</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Physical sciences</subject><subj-group><subject>Mathematics</subject><subj-group><subject>Optimization</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Proteins</subject><subj-group><subject>Nutrient and storage proteins</subject></subj-group></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v3">
<subject>Biology and life sciences</subject><subj-group><subject>Biochemistry</subject><subj-group><subject>Proteins</subject><subj-group><subject>Muscle proteins</subject></subj-group></subj-group></subj-group></subj-group></article-categories>
<title-group>
<article-title>Better late than never: Optimising the proteomic analysis of field-collected octopus</article-title>
<alt-title alt-title-type="running-head">Proteomic analysis for field-collected organisms</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes" xlink:type="simple">
<contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-3128-7273</contrib-id>
<name name-style="western">
<surname>Hua</surname>
<given-names>Qiaz Q. H.</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role content-type="http://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role content-type="http://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role content-type="http://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role content-type="http://credit.niso.org/contributor-roles/project-administration/">Project administration</role>
<role content-type="http://credit.niso.org/contributor-roles/resources/">Resources</role>
<role content-type="http://credit.niso.org/contributor-roles/validation/">Validation</role>
<role content-type="http://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-original-draft/">Writing – original draft</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff001"><sup>1</sup></xref>
<xref ref-type="corresp" rid="cor001">*</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-3945-286X</contrib-id>
<name name-style="western">
<surname>Young</surname>
<given-names>Clifford</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role content-type="http://credit.niso.org/contributor-roles/project-administration/">Project administration</role>
<role content-type="http://credit.niso.org/contributor-roles/resources/">Resources</role>
<role content-type="http://credit.niso.org/contributor-roles/validation/">Validation</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff002"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff003"><sup>3</sup></xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0001-7391-1436</contrib-id>
<name name-style="western">
<surname>Pukala</surname>
<given-names>Tara L.</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/project-administration/">Project administration</role>
<role content-type="http://credit.niso.org/contributor-roles/resources/">Resources</role>
<role content-type="http://credit.niso.org/contributor-roles/validation/">Validation</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff004"><sup>4</sup></xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Martino</surname>
<given-names>Jasmin C.</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/resources/">Resources</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff002"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Hoffmann</surname>
<given-names>Peter</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/funding-acquisition/">Funding acquisition</role>
<role content-type="http://credit.niso.org/contributor-roles/resources/">Resources</role>
<role content-type="http://credit.niso.org/contributor-roles/validation/">Validation</role>
<xref ref-type="aff" rid="aff002"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff003"><sup>3</sup></xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple">
<name name-style="western">
<surname>Gillanders</surname>
<given-names>Bronwyn M.</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role content-type="http://credit.niso.org/contributor-roles/project-administration/">Project administration</role>
<role content-type="http://credit.niso.org/contributor-roles/resources/">Resources</role>
<role content-type="http://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role content-type="http://credit.niso.org/contributor-roles/validation/">Validation</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff001"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author" corresp="yes" xlink:type="simple">
<name name-style="western">
<surname>Doubleday</surname>
<given-names>Zoe A.</given-names>
</name>
<role content-type="http://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role content-type="http://credit.niso.org/contributor-roles/funding-acquisition/">Funding acquisition</role>
<role content-type="http://credit.niso.org/contributor-roles/project-administration/">Project administration</role>
<role content-type="http://credit.niso.org/contributor-roles/resources/">Resources</role>
<role content-type="http://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role content-type="http://credit.niso.org/contributor-roles/validation/">Validation</role>
<role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing – review &amp; editing</role>
<xref ref-type="aff" rid="aff002"><sup>2</sup></xref>
<xref ref-type="corresp" rid="cor001">*</xref>
</contrib>
</contrib-group>
<aff id="aff001"><label>1</label> <addr-line>Environment Institute and School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia</addr-line></aff>
<aff id="aff002"><label>2</label> <addr-line>Future Industries Institute, University of South Australia, Mawson Lakes, South Australia, Australia</addr-line></aff>
<aff id="aff003"><label>3</label> <addr-line>Clinical &amp; Health Sciences, University of South Australia, Adelaide, South Australia, Australia</addr-line></aff>
<aff id="aff004"><label>4</label> <addr-line>Department of Chemistry, School of Physics, Chemistry and Earth Sciences, University of Adelaide, Adelaide, South Australia, Australia</addr-line></aff>
<contrib-group>
<contrib contrib-type="editor" xlink:type="simple">
<name name-style="western">
<surname>Tanaka-Azevedo</surname>
<given-names>Anita Mitico</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"/>
</contrib>
</contrib-group>
<aff id="edit1"><addr-line>Instituto Butantan, BRAZIL</addr-line></aff>
<author-notes>
<fn fn-type="conflict" id="coi001">
<p>The authors have declared that no competing interests exist.</p>
</fn>
<corresp id="cor001">* E-mail: <email xlink:type="simple">qiaz.qh.hua@gmail.com</email> (QQHH); <email xlink:type="simple">zoe.doubleday@unisa.edu.au</email> (ZAD)</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>12</day>
<month>7</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>18</volume>
<issue>7</issue>
<elocation-id>e0288084</elocation-id>
<history>
<date date-type="received">
<day>20</day>
<month>2</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>19</day>
<month>6</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-year>2023</copyright-year>
<copyright-holder>Hua et al</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">
<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:href="info:doi/10.1371/journal.pone.0288084"/>
<abstract>
<p>Proteomics, the temporal study of proteins expressed by an organism, is a powerful technique that can reveal how organisms respond to biological perturbations, such as disease and environmental stress. Yet, the use of proteomics for addressing ecological questions has been limited, partly due to inadequate protocols for the sampling and preparation of animal tissues from the field. Although RNA<italic>later</italic> is an ideal alternative to freezing for tissue preservation in transcriptomics studies, its suitability for the field could be more broadly examined. Moreover, existing protocols require samples to be preserved immediately to maintain protein integrity, yet the effects of delays in preservation on proteomic analyses have not been thoroughly tested. Hence, we optimised a proteomic workflow for wild-caught samples. First, we conducted a preliminary in-lab test using SDS-PAGE analysis on aquaria-reared <italic>Octopus berrima</italic> confirming that RNA<italic>later</italic> can effectively preserve proteins up to 6 h after incubation, supporting its use in the field. Subsequently, we collected arm tips from wild-caught <italic>Octopus berrima</italic> and preserved them in homemade RNA<italic>later</italic> immediately, 3 h, and 6 h after euthanasia. Processed tissue samples were analysed by liquid chromatography tandem mass spectrometry to ascertain protein differences between time delay in tissue preservation, as well as the influence of sex, tissue type, and tissue homogenisation methods. Over 3500 proteins were identified from all tissues, with bioinformatic analysis revealing protein abundances were largely consistent regardless of sample treatment. However, nearly 10% additional proteins were detected from tissues homogenised with metal beads compared to liquid nitrogen methods, indicating the beads were more efficient at extracting proteins. Our optimised workflow demonstrates that sampling non-model organisms from remote field sites is achievable and can facilitate extensive proteomic coverage without compromising protein integrity.</p>
</abstract>
<funding-group>
<award-group id="award001">
<funding-source>
<institution>University of South Australia</institution>
</funding-source>
<award-id>FIA049</award-id>
<principal-award-recipient>
<name name-style="western">
<surname>Doubleday</surname>
<given-names>Zoe A.</given-names>
</name>
</principal-award-recipient>
</award-group>
<award-group id="award002">
<funding-source>
<institution-wrap>
<institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/501100001786</institution-id>
<institution>University of Adelaide</institution>
</institution-wrap>
</funding-source>
<award-id>University of Adelaide Research Scholarship</award-id>
<principal-award-recipient>
<contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-3128-7273</contrib-id>
<name name-style="western">
<surname>Hua</surname>
<given-names>Qiaz Q. H.</given-names>
</name>
</principal-award-recipient>
</award-group>
<funding-statement>This work was supported by the Future Industries Accelerator Scheme, University of South Australia to ZAD (grant no. FIA049). QQHH is supported by the University of Adelaide Research Scholarship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement>
</funding-group>
<counts>
<fig-count count="4"/>
<table-count count="1"/>
<page-count count="12"/>
</counts>
<custom-meta-group>
<custom-meta id="data-availability">
<meta-name>Data Availability</meta-name>
<meta-value>Data are available via ProteomeXchange with identifier PXD043096.</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="sec001" sec-type="intro">
<title>Introduction</title>
<p>Understanding a species response to external biological perturbations such as diseases and environmental stress can be achieved by studying the underlying molecular mechanisms. Proteomics is a discipline that examines the functional products of temporal gene expression (proteins), but has not been extensively applied in ecology [<xref ref-type="bibr" rid="pone.0288084.ref001">1</xref>]. Proteomics allows the examination of changes in protein quantities and their post-translational modification status [<xref ref-type="bibr" rid="pone.0288084.ref002">2</xref>]. While amino acid sequences may reveal biological function and origin [<xref ref-type="bibr" rid="pone.0288084.ref003">3</xref>], functional analysis of the proteome yields information on important physiological mechanisms, such as cellular stress responses [<xref ref-type="bibr" rid="pone.0288084.ref004">4</xref>]. Proteins that are expressed at any given time reveal information on the cellular state and active cellular pathways [<xref ref-type="bibr" rid="pone.0288084.ref003">3</xref>]. Technological advances in mass spectrometry technology and data search programs coupled with the increasingly affordable sequencing technology are also opening new research avenues for proteomics data, such as examining environmental stress, adaptation strategies, immune defence mechanisms, seafood provenance, venomics, and complementing genomic findings [<xref ref-type="bibr" rid="pone.0288084.ref002">2</xref>, <xref ref-type="bibr" rid="pone.0288084.ref003">3</xref>, <xref ref-type="bibr" rid="pone.0288084.ref005">5</xref>–<xref ref-type="bibr" rid="pone.0288084.ref008">8</xref>].</p>
<p>Despite its clear advantages and broad applications, there is a relative lack of ecological studies that use proteomics to understand human impacts and stressors, such as global warming and ocean acidification. This is partly attributed to the shortage of protocols optimised for field-collected organisms. The first step to any successful proteomic analyses is obtaining and preserving tissues without compromising protein integrity. Thus, existing protocols require samples to be preserved immediately. However, this is often impractical for field-based ecological applications. For instance, field sampling sites may be remote and sampling may take place within awkward, confined spaces, such as a moving boat, where only ice may be available. This greatly limits the ability to follow standard protocols of immediate preservation, and challenging fieldwork conditions often mean delays in preserving tissues. However, the effects of such time delays in tissue preservation on proteomic analysis has not been extensively examined. In addition to this time factor, the standard practice of preserving tissues in liquid nitrogen (LN<sub>2</sub>) or freezing temperatures (-20°C or -80°C) is not practical given that most field locations lack the required infrastructure. The use of LN<sub>2</sub> and ethanol also poses a safety concern in the field especially for long-distance travel or in the confined spaces of a vehicle. These necessitate safer and more practical alternatives such as the use of the storage reagent RNA<italic>later</italic>, which can successfully preserve DNA, RNA and proteins [<xref ref-type="bibr" rid="pone.0288084.ref009">9</xref>, <xref ref-type="bibr" rid="pone.0288084.ref010">10</xref>].</p>
<p>To date, proteomic approaches have been used to study environmental impacts on mussels [<xref ref-type="bibr" rid="pone.0288084.ref011">11</xref>], gobies [<xref ref-type="bibr" rid="pone.0288084.ref012">12</xref>], crabs [<xref ref-type="bibr" rid="pone.0288084.ref013">13</xref>], sea squirts [<xref ref-type="bibr" rid="pone.0288084.ref014">14</xref>], oysters [<xref ref-type="bibr" rid="pone.0288084.ref015">15</xref>], plants [<xref ref-type="bibr" rid="pone.0288084.ref016">16</xref>], limpets [<xref ref-type="bibr" rid="pone.0288084.ref017">17</xref>] and zebrafish [<xref ref-type="bibr" rid="pone.0288084.ref018">18</xref>], and venom characterisation such as in snakes [<xref ref-type="bibr" rid="pone.0288084.ref019">19</xref>] and octopus [<xref ref-type="bibr" rid="pone.0288084.ref020">20</xref>]. However, these studies have largely been performed using captive organisms, highlighting the fact that ecological proteomics remains limited due to a lack of established protocols for field-collected samples, especially for tough muscular tissues present in octopuses and other molluscs. Proteomics has enormous potential to be applied in more marine and terrestrial organisms, especially in the face of climate change, but establishing protocols to allow proteomic analysis of field-collected organisms needs to be first developed and tested.</p>
<p>In this study, we optimised proteomic methods for both sample preservation and preparation using remote field-caught octopus. To fulfil our aims of method optimisation, we examined the arm proteome as octopus arms can be rapidly sampled both in the laboratory and field compared to other tissues such as organs. Given that existing protocols typically use soft tissues, muscular tissues like octopus arms require further optimisation to ensure efficient protein extraction. We first determined the suitability of RNA<italic>later</italic> to maintain protein integrity using fresh octopus tissues preserved according to standard protocols. Next, we conducted comparative proteomic analyses on wild-caught octopus tissues obtained from field settings and compared among different tissue types, sexes, tissue homogenisation methods and time delay in preservation. By comparing the number of proteins identified and their relative abundances between samples, we obtained key information that provides recommendations for the future proteomic analyses of wild specimens.</p>
</sec>
<sec id="sec002" sec-type="materials|methods">
<title>Materials and methods</title>
<sec id="sec003">
<title>Optimisation of test samples with RNA<italic>later</italic></title>
<p>Three female <italic>Octopus berrima</italic> (biological replicates) were collected directly from a commercial fishery in South Australia and raised in aquaria for three months until spawning and hatching of embryos. They were then euthanised in the lab in accordance with the Australian code for the care and use of animals for scientific purposes [<xref ref-type="bibr" rid="pone.0288084.ref021">21</xref>] by exposure to 1.5% magnesium chloride for 10 min, followed by exposure to 3.5% magnesium chloride for 30 min. Arm sections were dissected and immediately stored at -20°C, which is a recommended temperature for storage of proteomics samples and these samples were hence used as the control in this study. To determine if RNA<italic>later</italic> incubation helped maintain protein integrity, we compared samples from three timepoints: immediately, after 3 h and 6 h in the presence or absence of RNA<italic>later</italic>, during which samples were maintained at 4°C. These timepoints were based on the time necessary to complete the fieldwork. We then compared the effect of homemade (<xref ref-type="supplementary-material" rid="pone.0288084.s001">S1 Table</xref>) and commercial RNA<italic>later</italic> (Thermo Fisher Scientific, Waltham, USA) on protein quality and quantity. We additionally compared these samples maintained at 4°C without RNA<italic>later</italic> with those incubated at room temperature without RNA<italic>later</italic> to ascertain if cold storage was sufficient for maintaining protein quality. For samples with RNA<italic>later</italic>, 5X volume of RNA<italic>later</italic> was added to each arm section for the durations stated above.</p>
<p>Thawed tissues (approximately 10 mg each) were prepared according to the above conditions before being transferred into a 2 ml tube containing 200 μl RIPA buffer and four 50 mg metal beads for tissue lysis on the Precellys Evolution homogeniser (Bertin Technologies, Montigny-le-Bretonneux, France) at 5000 rpm. Samples were homogenised for 3 rounds of 30 seconds, placed on ice for 5 min to prevent excess heat generation, and then homogenised again for 3 rounds of 30 seconds before sonication for 5 min. Protein content was quantified using an EZQ Protein Quantitation kit (Thermo Fisher Scientific). For protein visualisation by SDS-PAGE, 10 μg of protein from each sample was mixed with 5 μl of 4X lithium dodecyl sulfate and 50 mM dithiothreitol before heating at 95°C for 5 min. Each sample was then loaded into a pre-cast NuPAGE<sup>TM</sup> 4 to 12% Bis-Tris polyacrylamide gel (Thermo Fisher Scientific). Gels were run at 180 V for 60 min and fixed briefly before staining overnight with Coomassie Brilliant Blue G-250 (Sigma Aldrich, Burlington, USA). Upon de-staining with Milli-Q water, the gels were imaged on a GelDoc Imaging System (Bio-Rad, Hercules, USA).</p>
<p>All experiments were approved by The University of Adelaide Animal Ethics Committee (approval no. S-2020-063) and by the University of South Australia Animal Ethics Committee (permit no. U24-19), where they were carried out in accordance with the Australian code for the care and use of animals for scientific purposes. The Department for Environment and Water in South Australia gave informed, written consent in the form of a permit (MR00149-1) for conducting sampling in marine protected areas. The commercial fishery also gave informed, verbal consent to conduct collaborative research fishing under their research permit (MRP004).</p>
</sec>
<sec id="sec004">
<title>Optimisation of wild specimens</title>
<sec id="sec005">
<title>Sample collection and preservation</title>
<p><italic>Octopus berrima</italic> were collected directly from a commercial fishery from remote locations in South Australia as previously described [<xref ref-type="bibr" rid="pone.0288084.ref022">22</xref>]. Octopus were euthanised in an ice slurry onboard a small, commercial vessel and transported to land. Subsequently, one arm tip from each octopus was dissected, rinsed with phosphate-buffered saline, and preserved in 5X volume of homemade RNA<italic>later</italic>. Depending on sampling location and travel times to a field location for dissection, tissues were preserved in RNA<italic>later</italic> immediately (sampling from 0 to 30 min and classed as the control group), 3 hours (sampling from two to three hours), or 6 hours (sampling from five to six hours) after euthanasia. Preserved samples were then stored at 4°C overnight as recommended by the manufacturer’s instructions of commercial RNA<italic>later</italic> (Thermo Fisher Scientific) before being frozen at -20°C in the field for a duration less than 24 hours. After transportation to the laboratory, tissues were stored at -80°C until analysis.</p>
</sec>
<sec id="sec006">
<title>Sample preparation and mass spectrometry</title>
<p>Tissues were prepared according to the four proposed comparisons (<xref ref-type="fig" rid="pone.0288084.g001">Fig 1</xref>). As skin is tougher than the underlying tissues and may contain abundant proteins that make detection of lower-abundant proteins difficult, we investigated if skin influenced the extraction efficiency and dynamic range using only the LN<sub>2</sub> homogenisation method by comparing tissues with and without skin. We also compared the efficiency of two common tissue homogenisation methods, LN<sub>2</sub> and metal beads, using only samples without skin due to the limited amount of sample available. Lastly, using an optimised approach based on our results from comparing sexes, tissue types and tissue homogenisation methods, we then compared the time delay in RNA<italic>later</italic> preservation using only samples without skin and homogenised using metal beads (<xref ref-type="fig" rid="pone.0288084.g001">Fig 1</xref>). Four octopuses were used in the comparisons of sex, tissue types and tissue homogenisation methods, whereas nine different octopuses were used for the comparison of time delay in preservation.</p>
<fig id="pone.0288084.g001" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0288084.g001</object-id>
<label>Fig 1</label>
<caption>
<title>Workflow for the optimisation of wild specimens comprising field (orange) and lab (blue) work for proteomic analyses.</title>
<p>Four types of comparisons were made using <italic>Octopus berrima</italic> arm tips: sex (male and female), tissue types (with and without skin), homogenisation methods of tissues (LN<sub>2</sub> and metal beads) as well as immediate or delayed tissue preservation [immediate (control), 3 h, and 6 h]. Tissue types were compared using the LN<sub>2</sub> homogenisation method, whereas tissue homogenisation methods were compared using only samples without skin. Using an optimised approach based on our results, time delay in preservation was then compared using only samples without skin and homogenised using metal beads. All samples irrespective of comparison type underwent protein denaturation and digestion before liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.g001" xlink:type="simple"/>
</fig>
<p>Tissues (approximately 5 mg) were homogenised by either immersion in LN<sub>2</sub> and crushing into a powder using a mortar and pestle, or by combining metal beads (7X tissue weight) and 375 μl homemade RIPA buffer (<xref ref-type="supplementary-material" rid="pone.0288084.s001">S1 Table</xref>) in a tube using the Bullet Blender Storm 24 (Next Advance, Troy, USA) for tough muscular tissues such as octopus arms. The latter consisted of 1 min bead-beating and 30 seconds of cooling to prevent excess heat generation, which was repeated three more times before centrifugation for 30 minutes at 4°C, 20000 ×<italic>g</italic>. The supernatant was then transferred to cold acetone (6X volume of tissue weight for LN<sub>2</sub>; 4X for beads; Chem-Supply, Port Adelaide, Australia) and stored overnight at -20°C. Upon centrifugation (4°C, 20000 ×<italic>g</italic>), the pellets were air-dried and dissolved in 8 M urea (Merck, Darmstadt, Germany) with 50 mM ammonium hydrogen carbonate (Merck) and sonicated twice for a minute. Protein was quantified using an EZQ Protein Quantitation kit (Thermo Fisher Scientific). The solution was combined with 10 mM dithiothreitol (Roche, Basel, Switzerland) for 45 minutes at room temperature followed by the addition of 20 mM iodoacetamide (Honeywell, Charlotte, USA) for a 30 minute in-the-dark incubation at room temperature. Urea was diluted to 1 M using 50 mM ammonium hydrogen carbonate, with 1 μg trypsin (Promega, Madison, USA) added to 50 μg protein for overnight incubation at 37°C. The digestion was halted by formic acid (Sigma Aldrich, Burlington, USA). Upon peptide clean-up using ZipTips (Merck, Co Wicklow, Ireland), 1 μg of peptide sample was analysed by LC-MS/MS on an Ultimate 3000 RSLCnano or EASY-nLC 1200 system connected to an Orbitrap Exploris 480 mass spectrometer (Thermo Fisher Scientific). Peptides were resuspended in 0.1% formic acid and loaded onto a 25 cm fused silica column (75 μm inner diameter, 360 um outer diameter) heated to 50°C. The column was packed in-house with 1.9 um ReproSil-Pur 120 C18-AQ particles (Dr. Maisch, Ammerbuch, Germany). Peptide separation was conducted over a 70-minute linear gradient (3 to 20% acetonitrile in 0.1% formic acid) at a flow rate of 300 nl/min. Compensation voltages (-50 and -70 V) were applied from a FAIMS Pro interface (Thermo Fisher Scientific) to filter the entry of ionised peptides into the mass spectrometer. For each compensation voltage, the cycle time was limited to 1.5 seconds and the dynamic exclusion period set to 40 seconds. MS scans (<italic>m/z</italic> 300 to 1500) were measured at resolution 60000 (<italic>m/z</italic> 200) in positive ion mode. MS/MS scans were acquired at resolution 15000 in a data-dependent manner (minimum threshold of 1 x 10<sup>4</sup> precursor ions), with peptide fragmentation performed with 27.5% higher-energy collision dissociation.</p>
</sec>
<sec id="sec007">
<title>Data analysis</title>
<p>To ensure statistical independence, bioinformatics analyses were conducted one comparison at a time using separate datasets differing by only one variable (e.g. sex). Raw files were processed with Proteome Discoverer 2.5 software (Thermo Fisher Scientific), using the Sequest HT search engine and a UniProt unreviewed “Cephalopoda” database (version 2021_03; 73232 protein entries). Carbamidomethylation of cysteine was set as a fixed modification, while variable modifications consisted of methionine oxidation, N-terminus acetylation, N-terminus loss of methionine and N-terminus loss of both methionine and acetylation. Other parameters in this workflow were at default settings i.e. maximum two missed cleavages, with a 10 ppm precursor mass tolerance and 0.1 Da fragment mass tolerance. Peptide group abundances were based on the intensity of their precursors, while protein abundances were calculated as the summation of their associated peptide group abundances. Protein ratio calculations were based on pairwise ratios using ANOVA, with other parameters at default settings i.e. protein and peptide false discovery rates were set to 0.01, peptide confidence was set to at least ‘High’ and at least one peptide sequence was required to identify a protein.</p>
<p>This analysis was repeated for other tissue comparisons, with each protein list filtered for Master proteins possessing a ‘High’ protein false discovery rate confidence to obtain totals of unique proteins for every comparison. To determine if experimental conditions in each comparison were significantly different, the protein lists were further filtered with an additional criterion (p-value ≤ 0.05 for adjusted abundance ratio) before heat maps (using normalized protein abundances) and volcano plots were generated. All mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [<xref ref-type="bibr" rid="pone.0288084.ref023">23</xref>] partner repository with the dataset identifier PXD043096.</p>
</sec>
</sec>
</sec>
<sec id="sec008" sec-type="results">
<title>Results</title>
<p>In order to assess whether RNA<italic>later</italic> would be a suitable medium for tissue storage, we first evaluated protein integrity using SDS-PAGE (<xref ref-type="fig" rid="pone.0288084.g002">Fig 2</xref>). Raw gel images can be found in <xref ref-type="supplementary-material" rid="pone.0288084.s007">S1 Raw</xref> images. The higher band intensities for lower-mass proteins and the lower abundance of higher-mass proteins in samples without RNA<italic>later</italic> compared to those with RNA<italic>later</italic> suggest higher levels of protein degradation occurred when tissues were not preserved in RNA<italic>later</italic>. This pattern was more pronounced at the 6 h timepoint, even when samples without RNA<italic>later</italic> were stored at 4°C. There were also higher band intensities for lower-mass proteins in samples without RNA<italic>later</italic> stored at room temperature compared to those stored at 4°C, which were prominent at the 3 h and 6 h timepoints, suggesting higher amounts of degraded proteins were present after room temperature storage. Lastly, as RNA<italic>later</italic> can be made in-house or bought commercially at a high cost, we also wanted to determine if homemade RNA<italic>later</italic> was suitable for proteomic analyses. We showed that homemade RNA<italic>later</italic> worked as well as the commercial RNA<italic>later</italic> due to similar band intensities and thereby the same negligible protein degradation. Based on these findings, we used cold storage and/or homemade RNA<italic>later</italic> for the analysis of wild-caught specimens in subsequent proteomic experiments.</p>
<fig id="pone.0288084.g002" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0288084.g002</object-id>
<label>Fig 2</label>
<caption>
<title>SDS-PAGE gels comparing the influence of RNA<italic>later</italic> on <italic>Octopus berrima</italic> proteins.</title>
<p><italic>Octopus berrima</italic> tissues without RNA<italic>later</italic> were compared with those incubated in homemade and commercial RNA<italic>later</italic> for three durations: 0 h (a), 3 h (b) and 6 h (c). For samples without RNA<italic>later</italic>, tissues stored at 4°C were compared with those stored at room temperature. Red boxes indicate higher band intensities for lower-mass proteins while yellow boxes indicate lower band intensities for higher-mass proteins, suggesting higher levels of protein degradation in samples without RNA<italic>later</italic>.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.g002" xlink:type="simple"/>
</fig>
<p>In order to optimise in-lab methods for tough muscular tissues such as in octopus, we examined the effect of different conditions (tissue types, sex, and tissue homogenisation methods) on the proteomic analysis of wild-caught octopus. We successfully identified over 3500 protein groups from all tissues (<xref ref-type="table" rid="pone.0288084.t001">Table 1</xref>), where unique protein groups were distinguished by at least one unique peptide. Higher protein numbers were obtained using the metal beads compared to LN<sub>2</sub>, where there was an increase in the abundance of 672 proteins prepared from metal beads compared to an increase in abundance of 175 proteins prepared from LN<sub>2</sub> (<xref ref-type="fig" rid="pone.0288084.g003">Fig 3</xref>). Some of the higher abundance proteins from the metal bead method were muscle-specific proteins such as actin, myophilin and tropomyosin (<xref ref-type="supplementary-material" rid="pone.0288084.s002">S2 Table</xref>). A comprehensive list of proteins which differed significantly in abundance from using metal beads and LN<sub>2</sub> is provided in <xref ref-type="supplementary-material" rid="pone.0288084.s003">S3</xref> and <xref ref-type="supplementary-material" rid="pone.0288084.s004">S4</xref> Tables respectively, whereas a complete list of proteins for this comparison is provided in <xref ref-type="supplementary-material" rid="pone.0288084.s005">S5 Table</xref>. No significant differences in protein abundance ratios were found between sexes and tissue types. Based on these findings, we conducted the subsequent experiment using metal beads and tissues without skin for the analysis of time delay before tissue preservation.</p>
<fig id="pone.0288084.g003" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0288084.g003</object-id>
<label>Fig 3</label>
<caption>
<title>Significant protein abundance differences between tissue homogenisation methods.</title>
<p>Magnified volcano plot showing greater number of proteins with higher abundance obtained using metal beads (672 proteins) compared to LN<sub>2</sub> (175 proteins). Each dot represents one protein. Red dots represent proteins of significantly higher abundance (p ≤ 0.05; log<sub>2</sub> fold change &gt;1) for metal beads while blue dots represent proteins of significantly higher abundance for LN<sub>2</sub> (p ≤ 0.05; log<sub>2</sub> fold change &lt;-1). Grey dots represent proteins with log<sub>2</sub> fold changes between -1 and 1. Ten proteins with higher significance values and fold changes are labelled.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.g003" xlink:type="simple"/>
</fig>
<table-wrap id="pone.0288084.t001" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0288084.t001</object-id>
<label>Table 1</label> <caption><title>Total number of unique proteins identified in the optimisation of wild specimens for comparisons between: Male (M) and female (F), tissues with (WS) and without skin (WoS), tissues homogenisation method (LN<sub>2</sub> and metal beads), and immediate and delayed tissue preservation.</title></caption>
<alternatives>
<graphic id="pone.0288084.t001g" mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.t001" xlink:type="simple"/>
<table>
<colgroup>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
<col align="left" valign="middle"/>
</colgroup>
<thead>
<tr>
<th align="center" rowspan="2">Experiment</th>
<th align="center" colspan="2">Sex</th>
<th align="center" colspan="2">Skin</th>
<th align="center" colspan="2">Tissue Homogenisation</th>
<th align="center" colspan="3">Time Delay in Preservation (hours)</th>
</tr>
<tr>
<th align="center">M</th>
<th align="center">F</th>
<th align="center">WS</th>
<th align="center">WoS</th>
<th align="center">LN<sub>2</sub></th>
<th align="center">MetalBeads</th>
<th align="center">Immed-iate</th>
<th align="center">3</th>
<th align="center">6</th>
</tr>
</thead>
<tbody>
<tr>
<td align="center" rowspan="2">Total number of proteins</td>
<td align="center">3700 (WoS)</td>
<td align="center">3527 (WoS)</td>
<td align="center" rowspan="2">3952</td>
<td align="center" rowspan="2">3750</td>
<td align="center" rowspan="2">3996</td>
<td align="center" rowspan="2">4356</td>
<td align="center" rowspan="2">3708</td>
<td align="center" rowspan="2">3709</td>
<td align="center" rowspan="2">3703</td>
</tr>
<tr>
<td align="center">3868 (WS)</td>
<td align="center">3829 (WS)</td>
</tr>
</tbody>
</table>
</alternatives>
</table-wrap>
<p>Lastly, we examined the effect of time delay before tissue preservation on the protein integrity of wild-caught specimens in field settings, which resulted in the identification of over 3700 protein groups from all tissues (<xref ref-type="table" rid="pone.0288084.t001">Table 1</xref>). Although pairwise analyses with ANOVA indicated no significant differences in overall protein abundance ratios found between immediate and delayed preservation, the 6 h time-point replicates in the heat map clustered together (<xref ref-type="fig" rid="pone.0288084.g004">Fig 4</xref>). This suggests that while tissue storage in the cold allows for comprehensive proteomic analyses, earlier storage with RNA<italic>later</italic> can more suitably preserve proteome integrity. A complete list of proteins identified in the comparison of time delay in preservation is provided in <xref ref-type="supplementary-material" rid="pone.0288084.s006">S6 Table</xref>.</p>
<fig id="pone.0288084.g004" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0288084.g004</object-id>
<label>Fig 4</label>
<caption>
<title>Protein abundance did not differ between immediate and delayed tissue preservation.</title>
<p>Heat map of identified proteins from immediate (control), 3 h and 6 h delayed tissue preservation (n = 9). The intensity of red reflects protein z-scores (-3.3 to 4.0), with grey denoting absent proteins.</p>
</caption>
<graphic mimetype="image" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.g004" xlink:type="simple"/>
</fig>
</sec>
<sec id="sec009" sec-type="conclusions">
<title>Discussion</title>
<p>Proteomics is a powerful technique in ecological applications, but the lack of optimised protocols for field-collected samples has contributed to its under-utilisation. Our study has provided an optimised approach at various stages of collecting and analysing wild specimens. Our initial findings showed that RNA<italic>later</italic> was effective in slowing protein degradation, even up to the 6 h timepoint where intact proteins were still present and did not hinder protein analyses. This finding is likely due to the high concentrations of quaternary ammonium sulfates that denature proteases (including DNAses and RNAses), thereby preserving proteins and nucleic acids [<xref ref-type="bibr" rid="pone.0288084.ref009">9</xref>, <xref ref-type="bibr" rid="pone.0288084.ref010">10</xref>]. This result suggests that storing samples in RNA<italic>later</italic> can overcome tissue preservation challenges associated with the lack of infrastructure during remote fieldwork. We also found that homemade RNA<italic>later</italic> was as effective in preserving proteins as commercial RNA<italic>later</italic>. Since the cost of commercial RNA<italic>later</italic> was 5X that of homemade RNA<italic>later</italic>, this finding allows for significant cost savings as has been the case for subsequent analyses in this study. This makes RNA<italic>later</italic> an ideal storage reagent for other ecological proteomics studies that require the examination of wild specimens.</p>
<p>Over 3500 proteins were successfully identified from octopus arm tips collected from remote field locations using an optimised sample preservation and preparation workflow. Since similar protein abundances and numbers were obtained between immediate and delayed tissue preservation, this indicates that the inevitable delays in tissue preservation associated with challenging field work conditions do not hinder the identification and quantification of thousands of proteins. Taking results from both experiments together, proteins can be successfully preserved and identified with the use of ice and RNA<italic>later</italic>, indicating that these should be the minimum materials required to conduct proteomic analyses. We note that samples from the in-field experiment could only be preserved on ice in the boat before being preserved in RNA<italic>later</italic> on land, and it is likely that protein degradation started to occur especially after 6 h on the boat, as observed by the slightly higher band intensities from the in-lab experiment for samples stored at 4°C without RNA<italic>later</italic>. Although this suggests that protein degradation is inevitable under in-field collections where only ice is available and that care should be taken to limit the amount of delay for tissue preservation, the low level of protein degradation and the eventual use of RNA<italic>later</italic> still permitted an extensive number of proteins to be identified and quantified. This is further supported by the fact that no significant differences were found in the protein abundances between immediate and delayed preservation. Moreover, samples in this study were obtained from real-life, remote field conditions in confined, moving spaces where only ice and/or RNA<italic>later</italic> were practical to use. Hence, there is further scope for applying proteomics to a broader range of ecological situations, particularly in cases where tissue preservation may be delayed up to 6 h. However, the long-term protective capabilities of RNA<italic>later</italic> on proteins remains to be established.</p>
<p>The use of metal beads to homogenise octopus arms yielded a higher number of proteins than LN<sub>2</sub>, and the significant increase in abundance of muscular proteins indicate that these metal beads are more efficient in breaking up muscular tissues. Bead-beating has been a traditional method of tissue homogenisation used to disrupt the tissue matrix in order to release nucleic acids and/or proteins [<xref ref-type="bibr" rid="pone.0288084.ref024">24</xref>]. This finding may be applicable to other molluscan tissues which may be tougher to homogenise than softer tissues, such as fish and soft-bodied insects.</p>
<p>Although tissues with and without skin did not exhibit significant differences, various factors must be considered when deciding to include skin in analyses. In cases where skin proteins form the research topic or where time is lacking, the extra effort in dissecting and removing skin may not be worthwhile, but one must ensure consistent proportions of skin to muscle to enable fair comparisons. Otherwise, as consistent skin to muscle ratio can also be challenging in terms of reproducibility, skin removal should be done for all tissues.</p>
<p>Finally, the lack of significant protein differences between the sexes could be due to the same section of arm muscle tissue being collected and the arm tip samples being anatomically similar. In addition, male-specific mating arms (hectocotylus) were not used in any of the comparisons. Future reproductive studies in cephalopods could investigate proteomic differences between sex-specific arms.</p>
<p>A major limitation of proteomics is the reliance on reference genome information, as confident protein identifications are highly dependent on sequence databases [<xref ref-type="bibr" rid="pone.0288084.ref025">25</xref>], which may not be readily available for uncommon organisms. The ability to obtain more physiologically relevant information is also dependent on how extensively the databases are annotated, as well as reliability of the curation itself. While several octopus genomes have been sequenced [<xref ref-type="bibr" rid="pone.0288084.ref026">26</xref>–<xref ref-type="bibr" rid="pone.0288084.ref029">29</xref>], the species in this study, <italic>Octopus berrima</italic>, has not been sequenced. Even within the current database for cephalopod proteins, many functional annotations are missing, and numerous proteins remain unreviewed, hence this could limit the usefulness of proteomic analyses. To minimise this limitation, a cross-species, homologous protein sequence database within Cephalopoda from UniProt was used to identify proteins in our samples. However, reliable proteomic analyses will still depend on factors beyond our control as future studies continue working on creating curated protein databases. Nevertheless, other cephalopods could potentially be studied by proteomic analyses in the future using databases such as UniProt.</p>
<p>In summary, our optimised protocol assists the development of proteomics research in unique ecological applications. We have demonstrated the usefulness of ice and RNA<italic>later</italic> in preserving proteins, making it safe and suitable for many ecological applications. We have also shown that extensive proteomic coverage can be obtained even when challenging field sampling conditions result in delayed tissue preservation, provided the samples are stored in ice and RNA<italic>later</italic>. We also recommend the use of metal beads, especially when homogenising tough tissues because of the higher protein numbers obtained with this method. It is worth noting that with ecological proteomics still in its infancy, reliably curated and annotated genomes for various organisms of interest remain necessary to facilitate protein identifications.</p>
</sec>
<sec id="sec010" sec-type="supplementary-material">
<title>Supporting information</title>
<supplementary-material id="pone.0288084.s001" mimetype="application/pdf" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.s001" xlink:type="simple">
<label>S1 Table</label>
<caption>
<title>Recipe for homemade RNA<italic>later</italic> and RIPA buffer.</title>
<p>(PDF)</p>
</caption>
</supplementary-material>
<supplementary-material id="pone.0288084.s002" mimetype="application/pdf" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.s002" xlink:type="simple">
<label>S2 Table</label>
<caption>
<title>List of muscular proteins that were significantly higher in abundance in samples homogenised using metal beads compared to homogenisation with LN<sub>2</sub>.</title>
<p>(PDF)</p>
</caption>
</supplementary-material>
<supplementary-material id="pone.0288084.s003" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.s003" xlink:type="simple">
<label>S3 Table</label>
<caption>
<title>List of proteins that were statistically significantly higher in abundance in samples homogenised using metal beads compared to homogenisation with LN<sub>2</sub>.</title>
<p>Adjusted p-values can be found in column AB.</p>
<p>(XLSX)</p>
</caption>
</supplementary-material>
<supplementary-material id="pone.0288084.s004" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.s004" xlink:type="simple">
<label>S4 Table</label>
<caption>
<title>List of proteins that were statistically significantly higher in abundance in samples homogenised with LN<sub>2</sub> compared to homogenisation using metal beads.</title>
<p>Adjusted p-values can be found in column AB.</p>
<p>(XLSX)</p>
</caption>
</supplementary-material>
<supplementary-material id="pone.0288084.s005" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.s005" xlink:type="simple">
<label>S5 Table</label>
<caption>
<title>Complete list of proteins identified from samples homogenised with metal beads or LN<sub>2</sub>.</title>
<p>Adjusted p-values can be found in column AB.</p>
<p>(XLSX)</p>
</caption>
</supplementary-material>
<supplementary-material id="pone.0288084.s006" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.s006" xlink:type="simple">
<label>S6 Table</label>
<caption>
<title>List of proteins identified from immediate (control), 3 h and 6 h delayed tissue preservation.</title>
<p>Adjusted p-values can be found in columns AC, AD and AE.</p>
<p>(XLSX)</p>
</caption>
</supplementary-material>
<supplementary-material id="pone.0288084.s007" mimetype="application/pdf" position="float" xlink:href="info:doi/10.1371/journal.pone.0288084.s007" xlink:type="simple">
<label>S1 Raw images</label>
<caption>
<title/>
<p>(PDF)</p>
</caption>
</supplementary-material>
</sec>
</body>
<back>
<ack>
<p>We are extremely grateful to Leon van Weenen and Lily Perone (SA Premium Octopus) for assistance in octopus collection, as well as Chris Cursaro (Adelaide Proteomics Centre), Enzo Huang (Thermo Fisher Scientific), and Brooke Dilmetz (Mass Spectrometry and Proteomics Facility) for their technical assistance and expertise, without which this project would not be possible.</p>
</ack>
<ref-list>
<title>References</title>
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<named-content content-type="letter-date">20 Apr 2023</named-content>
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<p><!-- <div> -->PONE-D-23-05036<!-- </div> --><!-- <div> -->Better late than never: optimising the proteomic analysis of field-collected organisms<!-- </div> --><!-- <div> -->PLOS ONE</p>
<p>Dear Dr. Hua,</p>
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<p>[Note: HTML markup is below. Please do not edit.]</p>
<p>Reviewers' comments:</p>
<p>Reviewer's Responses to Questions</p>
<p><!-- <font color="black"> --><bold>Comments to the Author</bold></p>
<p>1. Is the manuscript technically sound, and do the data support the conclusions?</p>
<p>The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. <!-- </font> --></p>
<p>Reviewer #1: Partly</p>
<p>Reviewer #2: Yes</p>
<p>**********</p>
<p><!-- <font color="black"> -->2. Has the statistical analysis been performed appropriately and rigorously? <!-- </font> --></p>
<p>Reviewer #1: I Don't Know</p>
<p>Reviewer #2: I Don't Know</p>
<p>**********</p>
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<p>Reviewer #1: No</p>
<p>Reviewer #2: Yes</p>
<p>**********</p>
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<p>Reviewer #1: Yes</p>
<p>Reviewer #2: Yes</p>
<p>**********</p>
<p><!-- <font color="black"> -->5. Review Comments to the Author</p>
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<p>Reviewer #1: Authors reported a study on the optimization of sample collection and processing for proteomic analysis of field-collected octopus. The study design is straight-forward and is relevant to answer the research question. However, there are a number of issues which compromise the quality of the paper and authors should attempt to address these to satisfaction before the manuscript can be considered for publication.</p>
<p>1. Title: it should be field-collected octopus -- as appeared in the title stated in other parts of the submission (supplementary files). Authors only performed the work on octopus, not all representative organisms.</p>
<p>2. I understand that authors wanted to study the "proteomics" of "octopus" using the octopus tissues which were stored and processed differently (hence the optimizing methods). However authors need to be clear in the beginning and state in the introduction what "proteomes" are they looking for, and subsequently the justification of the materials and techniques applied.</p>
<p>3. Other suggestions for introduction:</p>
<p>Line 77: what is traceability of seafood - this seems a bit out of place in the context of this statement.</p>
<p>Also, in the context of animal studies, proteomics has been widely applied in snakes to unravel the venom complexity and diversity including intra- and inter-species variation, which carries ecological, evolutionary and medical significance. This part of information should be included. Suggest references (some examples of reviews on snake venomics):</p>
<p>- <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fphar.2021.768015/full" xlink:type="simple">https://www.frontiersin.org/articles/10.3389/fphar.2021.768015/full</ext-link></p>
<p>- <ext-link ext-link-type="uri" xlink:href="https://www.mdpi.com/2072-6651/14/4/247" xlink:type="simple">https://www.mdpi.com/2072-6651/14/4/247</ext-link></p>
<p>- <ext-link ext-link-type="uri" xlink:href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408369/" xlink:type="simple">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408369/</ext-link></p>
<p>Line 80-81: ... proteomics-based in ecology - please be specific regarding which aspect of ecology studies authors feel that proteomics is lacking?</p>
<p>Line 97-99: storage solutions - what about undenatured ethanol? This is a very commonly and easy-to-use method for tissue sampling in the wild. Authors should include this in the introduction and provide justification.</p>
<p>4. Methods:</p>
<p>Line 136: How long were the octopus were kept and raised in aquaria?</p>
<p>Line 140-141: .......arm sections were dissected and immediately stored at -20 C... was this in the presence of RNAlatere? What is the ratio of RNAlater to the tissue?</p>
<p>Line 142... maintained at 4 C. with those at room temperature without RNAlater... the description is unclear. What is the volume, duration, amount of tissue etc.... these technical information needs to be included and described clearly.</p>
<p>Section: Proteomics</p>
<p>- How did authors define "protein abundances"? Do authors mean relative fold-change in "protein expression"? How was this measured, is it by the number of proteins identified per sample, or by the amount of protein (in terms of relative weight) per sample? Please provide the quantitative determination of the protein abundance for each proteome.</p>
<p>As a common practice in sequencing and proteomics/genomics study, the raw data of MS should be deposited and archived in a repository for public access. If this is available, please provide the repository accordingly.</p>
<p>Results and Discussion:</p>
<p>Provide the statistical significance of all parameters used in comparison, in tables and figures.</p>
<p>Suggest to include limitations of the work.</p>
<p>Reviewer #2: Dear authors, thank you for the opportunity to review such a clearly and convincingly written paper. Unfortunately, I am an ecologist and am far from qualified to judge whether the chemistry or bioinformatics were appropriate for the task. Indeed, probably half of the paper, from the methods through the results could have been completely made up and I wouldnt be able to tell. However, given the clarity of the writing and knowing that Zoe Doubleday and Bronwyn Gillanders were part of the research and the paper, I fully trust that this was the not case.</p>
<p>I had a couple of questions/comments:</p>
<p>I might have missed it (or misunderstood), in which case it could be made clearer, but I was a little uncertain as to what the RNAlater preserved samples were compared against. This confusion arose somewhere around the first sentence of the methods. I understood that they were compared against samples that were not treated with RNAlater, but wouldnt it have made most sense to also understand how they performed against the current lab best-practice for handling of samples for proteomic analyses, presumably freezing immediately at -80C (or being treated with some other less-transportable preservative)? Its not a deal-breaker but might be worth clarifying for a non-proteomics expert if/where you think it would be appropriate in the paper.</p>
<p>Very minor detail: the wording of the sentence L86-88 is a little strange and sounds like the sampling sites are inside a moving car. It would be worth adjusting the wording there slightly.</p>
<p>Other than that, well done!, and I hope that the second reviewer had some knowledge in proteomics... or at least chemistry... or bioinformatics... to be able to give you feedback on those sections of the manuscript.</p>
<p>All the best...</p>
<p>**********</p>
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<p>**********</p>
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<named-content content-type="author-response-date">13 Jun 2023</named-content>
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<p>We would like to thank the editor and reviewers for their valuable feedback. Please find our specific responses in the uploaded documents ("Response to Reviewers" and "New Cover Letter").</p>
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<named-content content-type="letter-date">19 Jun 2023</named-content>
</p>
<p>Better late than never: optimising the proteomic analysis of field-collected octopus</p>
<p>PONE-D-23-05036R1</p>
<p>Dear Dr. Hua,</p>
<p>We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.</p>
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<p>Kind regards,</p>
<p>Anita Mitico Tanaka-Azevedo</p>
<p>Academic Editor</p>
<p>PLOS ONE</p>
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<article-id pub-id-type="doi">10.1371/journal.pone.0288084.r004</article-id>
<title-group>
<article-title>Acceptance letter</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name name-style="western">
<surname>Tanaka-Azevedo</surname>
<given-names>Anita Mitico</given-names>
</name>
<role>Academic Editor</role>
</contrib>
</contrib-group>
<permissions>
<copyright-year>2023</copyright-year>
<copyright-holder>Anita Mitico Tanaka-Azevedo</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<related-object document-id="10.1371/journal.pone.0288084" document-id-type="doi" document-type="article" id="rel-obj004" link-type="peer-reviewed-article"/>
</front-stub>
<body>
<p>
<named-content content-type="letter-date">4 Jul 2023</named-content>
</p>
<p>PONE-D-23-05036R1 </p>
<p>­­Better late than never: optimising the proteomic analysis of field-collected octopus </p>
<p>Dear Dr. Hua:</p>
<p>I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. </p>
<p>If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact <email xlink:type="simple">onepress@plos.org</email>.</p>
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<p>Thank you for submitting your work to PLOS ONE and supporting open access. </p>
<p>Kind regards, </p>
<p>PLOS ONE Editorial Office Staff</p>
<p>on behalf of</p>
<p>Dr. Anita Mitico Tanaka-Azevedo </p>
<p>Academic Editor</p>
<p>PLOS ONE</p>
</body>
</sub-article>
</article>