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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Mar. Sci.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Marine Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Mar. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2296-7745</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
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<article-meta>
<article-id pub-id-type="doi">10.3389/fmars.2026.1789052</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Toxicity screening of eight <italic>Prorocentrum lima</italic> (Dinophyceae) strains of coastal China</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Feng</surname><given-names>Junkai</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
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<contrib contrib-type="author">
<name><surname>Wei</surname><given-names>Xueru</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name><surname>Ren</surname><given-names>Pengrui</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Zhang</surname><given-names>Peipei</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="aff5"><sup>5</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3348073/overview"/>
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<contrib contrib-type="author">
<name><surname>Liu</surname><given-names>Minlu</given-names></name>
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<contrib contrib-type="author">
<name><surname>Gao</surname><given-names>Yue</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
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<aff id="aff1"><label>1</label><institution>Key Laboratory of Marine Ecological Conservation and Restoration, Ministry of Natural Resources /Fujian Provincial Key Laboratory of Marine Ecological Conservation and Restoration</institution>, <city>Fujian</city>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Dalian Ocean University</institution>, <city>Dalian</city>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff3"><label>3</label><institution>State Environmental Protection Key Laboratory of Coastal Ecosystem, National Marine Environmental Monitoring Center</institution>, <city>Dalian</city>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff4"><label>4</label><institution>Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology, Dalian University of Technology</institution>, <city>Dalian</city>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff5"><label>5</label><institution>Fujian Key Laboratory of Conservation and Sustainable Utilization of Marine Biodiversity, College of Geography and Oceanography, Minjiang University</institution>, <city>Fuzhou</city>,&#xa0;<country country="cn">China</country></aff>
<aff id="aff6"><label>6</label><institution>State Key Laboratory of Marine Environmental Science, Xiamen University</institution>, <city>Xiamen</city>,&#xa0;<country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Peipei Zhang, <email xlink:href="mailto:ppzhang@nmemc.org.cn">ppzhang@nmemc.org.cn</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-02-27">
<day>27</day>
<month>02</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>13</volume>
<elocation-id>1789052</elocation-id>
<history>
<date date-type="received">
<day>16</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="accepted">
<day>10</day>
<month>02</month>
<year>2026</year>
</date>
<date date-type="rev-recd">
<day>04</day>
<month>02</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Feng, Wei, Ren, Zhang, Liu and Gao.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Feng, Wei, Ren, Zhang, Liu and Gao</copyright-holder>
<license>
<ali:license_ref start_date="2026-02-27">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<p>Diarrhetic shellfish poisoning, caused by Okadaic acid (OA) and its analogues, threatens nearshore ecosystems and public health. This study systematically compared eight <italic>Prorocentrum lima</italic> strains isolated from China&#x2019;s coastal waters with respect to growth characteristics, toxin profiles and concentrations, toxin esterification status, and cytotoxicity. A multidimensional evaluation of toxin-producing potential and biological effects was conducted by integrating full-cycle culturing, LC&#x2013;MS/MS analysis, and a Neuro-2a cell-based MTT bioassay. The results showed that OA and Diarrhetic shellfish toxin-1 (DTX-1) were detected in all strains, whereas DTX-2 was not detected. Total toxin levels measured after hydrolysis ranged from 17.07 to 31.84 pg OA-eq&#xb7;cell<sup>&#x2212;</sup>&#xb9;, and esterification ratios differed markedly among strains (53.37%&#x2013;93.07%), with strain 1115 exhibiting the highest ratio. Growth kinetics varied among strains, and a resource-allocation trade-off was observed between growth rate and toxin production. Cytotoxicity assays showed that toxicity increased with both concentration and exposure duration; overall, free toxin extracts were significantly more toxic than total toxin extracts (<italic>p</italic> &lt; 0.05), and toxic potency differed significantly among strains. OA-equivalent fitted concentrations back-calculated from the 24 h OA dose&#x2013;response curve were generally higher than LC&#x2013;MS/MS-measured concentrations, and fitted concentrations were significantly positively correlated with esterification ratios, suggesting that the contribution of esterified forms or their metabolites to overall toxicity may be underestimated by chemical analysis. In summary, <italic>P. lima</italic> exhibited pronounced intraspecific heterogeneity in toxin yield, chemotype, and biological effects. Integrating chemical analysis with cell-based bioassays enables a more comprehensive and accurate assessment of strain-associated ecological and public health risks.</p>
</abstract>
<kwd-group>
<kwd>diarrhetic shellfish poisoning</kwd>
<kwd>LC&#x2013;MS/MS</kwd>
<kwd>neuro-2a bioassay</kwd>
<kwd><italic>Prorocentrum lima</italic></kwd>
<kwd>toxicity screening</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. The project was supported by the Fund of Key Laboratory of Marine Ecological Conservation and Restoration, Ministry of Natural Resources/Fujian Provincial Key Laboratory of Marine Ecological Conservation and Restoration, (EPR2024001), Open Project of Fujian Key Laboratory of Conservation and Sustainable Utilization of Marine Biodiversity, Minjiang University (Grant No. CSUMBL2024-2), Fundamental Research Projects of Science &amp; Technology Innovation and development Plan in Yantai City[2023JCYJ091] ,  Shandong Provincial Natural Science Foundation [ZR2023QD193].</funding-statement>
</funding-group>
<counts>
<fig-count count="8"/>
<table-count count="6"/>
<equation-count count="6"/>
<ref-count count="58"/>
<page-count count="14"/>
<word-count count="7310"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Aquatic Microbiology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Diarrhetic shellfish poisoning (DSP) is a recurrent food-safety problem in coastal regions worldwide that poses a serious threat to human health and has become a major concern in both marine environmental science and public health (<xref ref-type="bibr" rid="B38">Park et&#xa0;al., 2023</xref>). Diarrhetic shellfish toxins (DSTs) mainly consist of okadaic acid (OA) and its analogues, dinophysistoxins (DTXs) (<xref ref-type="bibr" rid="B1">Alexander et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B47">Tarazona-Janampa et&#xa0;al., 2020</xref>). These lipophilic toxins are readily accumulated by filter-feeding bivalves(e.g., mussels) (<xref ref-type="bibr" rid="B3">Blanco, 2018</xref>; <xref ref-type="bibr" rid="B50">Trainer et&#xa0;al., 2013</xref>) and undergo transformation and esterification within the shellfish (<xref ref-type="bibr" rid="B41">Rossignoli et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B49">Torgersen et&#xa0;al., 2008</xref>), thereby altering their toxicological profiles and bioavailability. Accumulation of DSTs in mussels can reduce feeding and clearance rates (<xref ref-type="bibr" rid="B14">Dam et&#xa0;al., 2020</xref>), impair digestive gland function, and adversely affect growth and reproductive parameters (<xref ref-type="bibr" rid="B18">Faustino et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B36">Neves et&#xa0;al., 2019</xref>); histologically, epithelial damage, cell necrosis, and oxidative stress responses in the digestive gland and other tissues are commonly observed (<xref ref-type="bibr" rid="B2">Auriemma and Battistella, 2004</xref>; <xref ref-type="bibr" rid="B39">Prego-Faraldo et&#xa0;al., 2016</xref>), and these individual-level impacts further affect population viability and community stability (<xref ref-type="bibr" rid="B7">Bouda et&#xa0;al., 2026</xref>). Altered feeding and reproductive metrics have also been reported for crustaceans and other benthic invertebrates (<xref ref-type="bibr" rid="B20">Gorokhova et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B29">Kozlowsky-Suzuki et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B46">Tang et&#xa0;al., 2023</xref>). Via trophic transfer, consumption of contaminated shellfish can also cause DSP in humans, posing a direct threat to public health and marine ecosystem services (<xref ref-type="bibr" rid="B48">Taylor et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B56">Zhang et&#xa0;al., 2024</xref>).</p>
<p>The genus <italic>Prorocentrum</italic> is one of the principal producers of DSTs; more than 60 species have been described to date, of which at least nine benthic species are known to produce DSTs (<xref ref-type="bibr" rid="B21">Hoppenrath et&#xa0;al., 2013</xref>). <italic>Prorocentrum lima</italic>, the most extensively studied toxigenic species, is widely distributed across tropical and temperate waters and can be divided into at least two genetically distinct clades, with strains in each clade capable of producing toxins (<xref ref-type="bibr" rid="B34">Nagahama et&#xa0;al., 2011</xref>). Strains of <italic>P. lima</italic> from different geographic origins show significant differences in toxin yield and composition: the total algal toxin concentration in coastal waters of China ranged from 0.551 to 10.26 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;, and compared to the South China Sea, algal toxins in the Bohai Sea and Yellow Sea exhibited a more diverse toxin composition (<xref ref-type="bibr" rid="B13">Chen et&#xa0;al., 2025</xref>; <xref ref-type="bibr" rid="B31">Luo et&#xa0;al., 2017</xref>). Twenty strains from Fleet Lagoon in the United Kingdom were found to primarily produce OA (0.4&#x2013;17.1 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;) and DTX-1 (0.4&#x2013;11.3 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;), while DTX-2 was not detected (<xref ref-type="bibr" rid="B35">Nascimento et&#xa0;al., 2005</xref>). The IO66&#x2013;01 strain from Lisbon Bay, Portugal, produced OA (8.8&#x2013;41 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;) and DTX-1 (2.5&#x2013;12 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;) (<xref ref-type="bibr" rid="B52">Vale et&#xa0;al., 2009</xref>). Among strains from the Galician coast of Spain, the highest OA-producing strain (PL16V) and the highest DTX-1-producing strain (PL12V) reached 12.9 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9; and 12.4 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;, respectively, whereas DTX-2 and its esters were detected only in trace amounts (<xref ref-type="bibr" rid="B8">Bravo et&#xa0;al., 2001</xref>). The CSIRCSMCRI005 strain from the Bay of Bengal in the northern Indian Ocean predominantly produced OA and its esters, with a total toxin concentration of 0.0223 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9; (<xref ref-type="bibr" rid="B37">Oyeku and Mandal, 2021</xref>). Taken together, total toxin concentration of P. lima strains worldwide span a very wide range (0.0223&#x2013;41 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;), with OA and DTX-1 comprising the dominant toxin components and DTX-2&#x2013;related derivatives detected in only a few regions (<xref ref-type="bibr" rid="B38">Park et&#xa0;al., 2023</xref>). This pronounced intraspecific variability in toxin profiles is closely linked to geographic distribution and oceanographic factors (e.g., temperature and nutrient availability), further corroborating the ecological adaptability of P. lima and the geographic specificity of its toxin biosynthesis. Thus, geographic variation appears to be a key factor underlying the observed diversity in cell morphology, pigment and toxin concentration among P. lima strains.</p>
<p>To date, research on the toxicity of <italic>P. lima</italic>, addressing the complex issue of toxin diversity, has mainly focused on quantifying the concentrations of free and esterified toxin forms using chemical analytical methods, with these measurements serving as the basis for toxicity assessment (<xref ref-type="bibr" rid="B49">Torgersen et&#xa0;al., 2008</xref>). However, reliance solely on chemical concentrations does not fully capture the true toxicological risk (<xref ref-type="bibr" rid="B6">Bodero et&#xa0;al., 2018b</xref>; <xref ref-type="bibr" rid="B32">Manita et&#xa0;al., 2017</xref>). The traditional view, rooted in the self-protective physiological mechanisms of algal cells, holds that non-hydrolyzed esterified toxins(particularly sulfated diesters) exist within intact cells as low-toxicity or non-toxic &#x201c;precursors,&#x201d; and that their toxicity is far weaker than that of the free toxins released upon hydrolysis (<xref ref-type="bibr" rid="B22">Hu et&#xa0;al., 1995a</xref>, <xref ref-type="bibr" rid="B23">1995</xref>; <xref ref-type="bibr" rid="B58">Zhou and Fritz, 1994</xref>). But once the structural integrity of algal cells is compromised, this self-protective mechanism is disrupted. Mouse bioassays conducted on crude extracts of <italic>P. lima</italic> have shown that esterified forms of OA and DTX-1 exhibit higher toxicity compared with their free counterparts (<xref ref-type="bibr" rid="B55">Wu et&#xa0;al., 2020</xref>). Further studies have found that a single esterified toxin isolated directly from algal biomass (e.g., an OA C9-diol ester) also displays potent <italic>in vitro</italic> cytotoxicity comparable to that of free OA standards (<xref ref-type="bibr" rid="B27">Ji et&#xa0;al., 2025</xref>). Collectively, these lines of evidence indicate that, once removed from the algal cell environment, esterified toxins themselves represent an important source of risk whose toxicity should not be overlooked. Therefore, combining chemical analytical methods with bioassays is of considerable scientific and practical significance for comprehensively and accurately assessing the potential risks posed by algal strains. Among various bioassay models, and in comparison with non-neurogenic cell lines such as MCF-7 and intestinal epithelial cell lines, as well as other neurogenic cell models (<xref ref-type="bibr" rid="B10">Ca&#xf1;ete and Diog&#xe8;ne, 2008</xref>; <xref ref-type="bibr" rid="B45">Soli&#xf1;o et&#xa0;al., 2015</xref>),the mouse neuroblastomaNeuro-2a cells has been established as a robust <italic>in vitro</italic> toxicological assessment platform due to its high sensitivity and reproducibility in detecting a range of lipophilic algal toxins. This model is widely applied for risk screening of diarrhetic shellfish toxins (e.g., OA, DTX-1, and DTX-2) in bivalves and other seafood (<xref ref-type="bibr" rid="B4">Bodero et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B10">Ca&#xf1;ete and Diog&#xe8;ne, 2008</xref>; <xref ref-type="bibr" rid="B26">Ikehara et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B44">S&#xe9;randour et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B45">Soli&#xf1;o et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B57">Zhao et&#xa0;al., 2025</xref>). The assay is relatively simple, high-throughput, and capable of reflecting the integrated biological effects of toxin mixtures; therefore, the Neuro-2a bioassay can serve as an important complementary tool to chemical methods.</p>
<p>To systematically assess the toxin-producing characteristics and overall toxicity of <italic>P. lima</italic> from China&#x2019;s coastal waters, this study used eight <italic>P. lima</italic> strains isolated from these waters as research subjects and employed a combination of liquid chromatography&#x2013;tandem mass spectrometry (LC&#x2013;MS/MS) and bioassay techniques to conduct comprehensive toxicity evaluations of the strains. This study carried out a comprehensive toxicity assessment across multiple dimensions, including algal cell growth, analysis of toxin composition and concentrations, and quantitative evaluation of cytotoxicity. It aims to systematically reveal differences in toxin-producing potential and toxicity risk among the strains, thereby enhancing the capacity to predict the ecological and public health risks of harmful algal blooms (HABs) in nearshore waters, and providing key theoretical support and technical references for risk prevention and control.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title><italic>P. lima</italic> culture and growth</title>
<sec id="s2_1_1">
<label>2.1.1</label>
<title><italic>P. lima</italic> culture</title>
<p>The toxic dinoflagellate P. lima used in this study was provided by the Center for Collections of Marine Algae, Xiamen University, China. Strain codes and sampling locations of the <italic>P. lima</italic> isolates are shown in <xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>. Seawater for culturing was collected near Dalian, filtered through 0.45 &#xb5;m membrane filters, and autoclaved at 121 &#xb0;C for 30 min. All strains at an initial density of (3.5 &#xb1; 1) &#xd7; 10&#xb3; cells&#xb7;mL<sup>&#x2212;</sup>&#xb9; were cultured in L1 medium at 20 &#xb1; 1 &#xb0;C under a 12 h light: 12 h dark photoperiod for 56-day. Late exponential phase cultures were used for subsequent experimental procedures. All experiments were conducted in triplicate.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Strain codes and sampling locations of the eight <italic>P. lima</italic> strains.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Strain ID</th>
<th valign="top" align="center">Strain ID in the Xiamen University Algal Culture Collection</th>
<th valign="top" align="center">Sampling location</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">401</td>
<td valign="top" align="center">CCMA-043</td>
<td valign="top" align="center">Zhanjiang</td>
</tr>
<tr>
<td valign="top" align="center">403</td>
<td valign="top" align="center">CCMA-557</td>
<td valign="top" align="center">Shenzhen Bay</td>
</tr>
<tr>
<td valign="top" align="center">404</td>
<td valign="top" align="center">CCMA-558</td>
<td valign="top" align="center">Sanya</td>
</tr>
<tr>
<td valign="top" align="center">405</td>
<td valign="top" align="center">CCMA-559</td>
<td valign="top" align="center">Sanya</td>
</tr>
<tr>
<td valign="top" align="center">406</td>
<td valign="top" align="center">CCMA-560</td>
<td valign="top" align="center">Gulf of Tonkin</td>
</tr>
<tr>
<td valign="top" align="center">407</td>
<td valign="top" align="center">CCMA-561</td>
<td valign="top" align="center">Gulf of Tonkin</td>
</tr>
<tr>
<td valign="top" align="center">408</td>
<td valign="top" align="center">CCMA-562</td>
<td valign="top" align="center">Weizhou Island</td>
</tr>
<tr>
<td valign="top" align="center">1115</td>
<td valign="top" align="center">CCMA-269</td>
<td valign="top" align="center">Dongshan</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2_1_2">
<label>2.1.2</label>
<title>Cell counting and growth-rate calculation</title>
<p>For each collection, 5 mL of algal solution was fixed with 100 &#x3bc;L Lugol&#x2019;s iodine solution in a centrifuge tube. Algal cell density was determined using a Sedgewick&#x2013;Rafter counting chamber under a microscope(Revolve Generation 2, ECHO, USA). The specific growth rate is measured to reflect the alterations in algal growth. The following formula represents the specific growth rate (&#x3bc;):</p>
<disp-formula>
<mml:math display="block" id="M1"><mml:mrow><mml:mi>&#x3bc;</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mi>ln</mml:mi><mml:msub><mml:mi>N</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>&#x2212;</mml:mo><mml:mi>ln</mml:mi><mml:msub><mml:mi>N</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mi>t</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>&#x2212;</mml:mo><mml:msub><mml:mi>t</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:math>
</disp-formula>
<p>where &#x3bc; is the specific growth rate, d<sup>&#x2013;1</sup>; N<sub>2</sub> is the number of cells per unit when the growth time of algae is t<sub>2</sub>, cells&#xb7; mL<sup>&#x2013;1</sup>; N<sub>1</sub> is the number of algal cells per unit at the growth time of t<sub>1</sub>, cells&#xb7; mL<sup>&#x2013;1</sup> and t1 and t<sub>2</sub> is the corresponding growth days, d.</p>
<p>After fitting the growth curve of algae, the growth process of algae was consistent with the log-transformed Logistic equation. The calculation equation is expressed as follows:</p>
<disp-formula>
<mml:math display="block" id="M2"><mml:mrow><mml:mi>ln</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mfrac><mml:mrow><mml:mi>K</mml:mi><mml:mo>&#x2212;</mml:mo><mml:mi>N</mml:mi></mml:mrow><mml:mi>N</mml:mi></mml:mfrac><mml:mo stretchy="false">)</mml:mo><mml:mo>=</mml:mo><mml:mi>&#x3b1;</mml:mi><mml:mo>&#x2212;</mml:mo><mml:mi>r</mml:mi><mml:mi>t</mml:mi></mml:mrow></mml:math>
</disp-formula>
<p>where K is the maximum algal cell density value for predicting algal growth, cells&#xb7; mL<sup>&#x2013;1</sup>; N is the algal cell density at culture time t, cells&#xb7; mL<sup>&#x2013;1</sup>; t is the culture time; &#x3b1; is the curve intercept, and r is the intrinsic growth rate, d<sup>&#x2013;1</sup>. The parameters were initially estimated. The range of K was determined by the maximum algal cell density. To estimate the values of &#x3b1; and r, the least-squares regression analysis was performed to obtain the slope and intercept of the equation.</p>
</sec>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Chemical analysis of DSTs</title>
<sec id="s2_2_1">
<label>2.2.1</label>
<title>Sample preparation and extraction</title>
<p>Determination of free DSTs: Three 300 mL replicates of algal culture were centrifuged at 4,000 rpm for 10 min. The supernatant was discarded, and 10 mL of methanol was added to the algal cell pellet. The pellet was sonicated at 4 &#xb0;C for 10 min and then centrifuged. The resulting supernatant was collected. The pellet was extracted a second time under the same conditions with 9 mL of methanol. The toxin extract was mixed, and a 1 mL aliquot was filtered through a 0.22 &#xb5;m nylon membrane. The filtrate was collected into a sample vial for LC-MS/MS analysis and cytotoxicity assays.</p>
<p>Total DSTs were determined as follows: A 1 mL aliquot of the toxin extract was added to a 1.5 mL microcentrifuge tube containing 125 &#xb5;L of 2.5 mol&#xb7;L<sup>&#x2212;</sup>&#xb9; NaOH solution. The mixture was vortexed for 30 s, the tube was sealed, and then incubated at 76 &#xb0;C for 40 min. After cooling, the sample was neutralized with 125 &#xb5;L of 2.5 mol&#xb7;L<sup>&#x2212;</sup>&#xb9; HCl, vortexed again, filtered through a 0.22 &#xb5;m nylon membrane, and collected into a sample vial for subsequent instrumental analysis and cytotoxicity assays.</p>
</sec>
<sec id="s2_2_2">
<label>2.2.2</label>
<title>DSTs analysis</title>
<p>DSTs were quantified using an Ultimate 3000/API 4000 LC-MS/MS system. The mass spectrometer was operated in negative electrospray ionization (ESI) mode with multiple reaction monitoring (MRM). Specific MRM parameters for OA, DTX-1, and DTX-2 are listed in <xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>. The ion source temperature was maintained at 600 &#xb0;C and the ESI voltage was set to &#x2212;4500 V. Gas pressures were set as follows: curtain gas, 13 psi; collision gas, 5 psi; ion source gas 1 (GS1), 60 psi; and ion source gas 2 (GS2), 50 psi.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Parameters for mass spectrometry.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Toxin</th>
<th valign="middle" align="center">Precursor ion m/z</th>
<th valign="middle" align="center">DP (volts)</th>
<th valign="middle" align="center">CE (volts)</th>
<th valign="middle" align="center">CXP (volts)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="3" align="center">OA</td>
<td valign="middle" rowspan="3" align="center">803</td>
<td valign="middle" align="center">-80</td>
<td valign="middle" align="center">-65</td>
<td valign="middle" align="center">-20</td>
</tr>
<tr>
<td valign="middle" align="center">-80</td>
<td valign="middle" align="center">-60</td>
<td valign="middle" align="center">-13</td>
</tr>
<tr>
<td valign="middle" align="center">-80</td>
<td valign="middle" align="center">-60</td>
<td valign="middle" align="center">-13</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">DTX1</td>
<td valign="middle" rowspan="3" align="center">817</td>
<td valign="middle" align="center">-80</td>
<td valign="middle" align="center">-60</td>
<td valign="middle" align="center">-13</td>
</tr>
<tr>
<td valign="middle" align="center">-80</td>
<td valign="middle" align="center">-60</td>
<td valign="middle" align="center">-13</td>
</tr>
<tr>
<td valign="middle" align="center">-80</td>
<td valign="middle" align="center">-60</td>
<td valign="middle" align="center">-13</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">DTX2</td>
<td valign="middle" rowspan="3" align="center">803</td>
<td valign="middle" align="center">-80</td>
<td valign="middle" align="center">-55</td>
<td valign="middle" align="center">-13</td>
</tr>
<tr>
<td valign="middle" align="center">-80</td>
<td valign="middle" align="center">-55</td>
<td valign="middle" align="center">-13</td>
</tr>
<tr>
<td valign="middle" align="center">-80</td>
<td valign="middle" align="center">-55</td>
<td valign="middle" align="center">-13</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>For liquid chromatography, an XBridge C18 column (Waters; 100 mm &#xd7; 2.1 mm, 3.5 &#xb5;m) was used. The flow rate was 0.4 mL&#xb7;min<sup>&#x2212;</sup>&#xb9;, the column temperature was maintained at 40 &#xb0;C, and the injection volume was 10 &#xb5;L. The mobile phase consisted of (A) 2 mmol&#xb7;L<sup>&#x2212;</sup>&#xb9; ammonium formate and (B) a mixture of acetonitrile and 2 mmol&#xb7;L<sup>&#x2212;</sup>&#xb9; ammonium formate (95:5, v/v). A gradient elution program was used, with details provided in <xref ref-type="table" rid="T3"><bold>Table&#xa0;3</bold></xref>.</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Gradient elution conditions of the mobile phase.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Time (min)</th>
<th valign="middle" align="center">Mobile phase A (%)</th>
<th valign="middle" align="center">Mobile phase B (%)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">0.0</td>
<td valign="middle" align="center">90</td>
<td valign="middle" align="center">10</td>
</tr>
<tr>
<td valign="middle" align="center">2.0</td>
<td valign="middle" align="center">90</td>
<td valign="middle" align="center">10</td>
</tr>
<tr>
<td valign="middle" align="center">10.0</td>
<td valign="middle" align="center">10</td>
<td valign="middle" align="center">90</td>
</tr>
<tr>
<td valign="middle" align="center">13.0</td>
<td valign="middle" align="center">10</td>
<td valign="middle" align="center">90</td>
</tr>
<tr>
<td valign="middle" align="center">15.0</td>
<td valign="middle" align="center">90</td>
<td valign="middle" align="center">10</td>
</tr>
<tr>
<td valign="middle" align="center">19.0</td>
<td valign="middle" align="center">90</td>
<td valign="middle" align="center">10</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2_2_3">
<label>2.2.3</label>
<title>Calculation of OA equivalents and esterification ratio</title>
<p>The total toxicity of diarrhetic shellfish toxins (DSTs) in algal samples was expressed as okadaic acid equivalents (OA-eq). OA-eq values were calculated based on toxicity equivalence factors (TEFs), using the following equation:</p>
<disp-formula>
<mml:math display="block" id="M3"><mml:mrow><mml:msub><mml:mrow><mml:mtext>OA</mml:mtext></mml:mrow><mml:mrow><mml:mi>e</mml:mi><mml:mi>q</mml:mi></mml:mrow></mml:msub><mml:mo>=</mml:mo><mml:munderover><mml:mo>&#x2211;</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mi>n</mml:mi></mml:munderover><mml:msub><mml:mi>X</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>&#xb7;</mml:mo><mml:msub><mml:mi>r</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im1"><mml:mrow><mml:msub><mml:mrow><mml:mtext>OA</mml:mtext></mml:mrow><mml:mrow><mml:mi>e</mml:mi><mml:mi>q</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math></inline-formula> represents the total toxicity expressed as okadaic acid equivalents (&#xb5;g&#xb7;kg<sup>&#x2212;</sup>&#xb9;), <inline-formula>
<mml:math display="inline" id="im2"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> denotes the concentration of each DST analogue (&#xb5;g&#xb7;kg<sup>&#x2212;</sup>&#xb9;), and <inline-formula>
<mml:math display="inline" id="im3"><mml:mrow><mml:msub><mml:mi>r</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is the corresponding toxicity equivalence factor (TEF).</p>
<p>According to previous toxicological evaluations and regulatory recommendations, the TEF values applied in this study were set to 1 for okadaic acid (OA) and dinophysistoxin-1 (DTX-1), and 0.6 for dinophysistoxin-2 (DTX-2) (<xref ref-type="bibr" rid="B1">Alexander et&#xa0;al., 2008</xref>). As DTX-2 was not detected in any of the analyzed samples, OA-eq values in this study were calculated as the sum of OA and DTX-1 concentrations, each multiplied by their respective TEF values.</p>
<p>The esterification ratio is defined as the proportion of esterified toxins relative to the total toxin concentration. It was calculated using the following equation:</p>
<disp-formula>
<mml:math display="block" id="M4"><mml:mrow><mml:mtext>esterification&#xa0;ratio</mml:mtext><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mtext>total&#xa0;toxin</mml:mtext><mml:mo>&#x2212;</mml:mo><mml:mtext>free&#xa0;toxin</mml:mtext></mml:mrow><mml:mrow><mml:mtext>total&#xa0;toxin</mml:mtext></mml:mrow></mml:mfrac><mml:mo>&#xd7;</mml:mo><mml:mn>100</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math>
</disp-formula>
<p>where total toxin refers to the OA-eq concentration measured after hydrolysis; free toxin refers to the OA-eq concentration measured without hydrolysis. The esterification ratios are presented as percentages in the manuscript.</p>
</sec>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Cytotoxicity assessment</title>
<sec id="s2_3_1">
<label>2.3.1</label>
<title>Cell culture and seeding</title>
<p>Cytotoxicity was assessed using the murine neuroblastoma cell line Neuro-2a. Cells were cultured in Minimum Essential Medium (MEM) supplemented with 10% fetal bovine serum (FBS), 1 mM sodium pyruvate, 1&#xd7; GlutaMAX&#x2122;, 1&#xd7; non-essential amino acids (NEAA), and an antibiotic solution (0.5% v/v; 10 mg&#xb7;mL<sup>&#x2212;</sup>&#xb9; streptomycin, 1000 U&#xb7;mL<sup>&#x2212;</sup>&#xb9; penicillin). They were maintained at 37 &#xb0;C in a humidified atmosphere of 5% CO<sub>2</sub>. To ensure continuous exponential growth, cells were subcultured weekly using 0.25% (w/v) trypsin-EDTA. For toxicity assays, cells were seeded in 96-well plates at a density of 20,000 cells per well, grown for 72 h to near confluence (~100%), and then exposed to toxins.</p>
</sec>
<sec id="s2_3_2">
<label>2.3.2</label>
<title>Cytotoxicity assay</title>
<p>Neuro-2a cells were seeded into 96-well plates at 20,000 cells per well and incubated at 37 &#xb0;C with 5% CO<sub>2</sub> for 72 h. Free and total toxin extracts from the eight <italic>P. lima</italic> strains were serially diluted in Minimum Essential Medium (MEM) to obtain a dilution series (10&#xd7;, 100&#xd7;, 200&#xd7;, 500&#xd7;, 1000&#xd7;, and 2000&#xd7;). Cells were exposed to 100 &#xb5;L of each dilution per well and incubated for 24 h and 48 h under standard conditions (37 &#xb0;C, 5% CO<sub>2</sub>). Negative controls included: (1) cells in medium without any test substance; and (2) a methanol vehicle control, i.e., cells treated with methanol diluted in MEM at the same final concentration and volume as in the toxin-treated wells. The positive control consisted of cells exposed to the OA standard under identical conditions. Dose&#x2013;response curves for okadaic acid (OA) were established by treating cells with an OA standard serially diluted in MEM to eight concentrations (ranging from 19.42 to 2485.76 nM) following an identical exposure protocol. All treatments were conducted in biological triplicates.</p>
</sec>
<sec id="s2_3_3">
<label>2.3.3</label>
<title>Cell viability measurement and IC<sub>50</sub> calculation</title>
<p>Cell viability was assessed via the MTT assay (<xref ref-type="bibr" rid="B5">Bodero et&#xa0;al., 2018a</xref>). Following toxin exposure for 24 h and 48 h, the culture medium in each well was replaced with 60 &#xb5;L of MTT solution (0.8 mg&#xb7;mL<sup>&#x2212;</sup>&#xb9; in serum-free medium). The plates were subsequently incubated at 37 &#xb0;C under 5% CO<sub>2</sub> for 4 h. Thereafter, the MTT solution was carefully aspirated, and the resulting formazan crystals were dissolved by adding 100 &#xb5;L of dimethyl sulfoxide (DMSO) to each well. To ensure complete dissolution, the plates were shaken at 600 rpm for 10 min on an orbital shaker. Finally, absorbance was measured at 455 nm using a Multiskan FC microplate reader (Thermo Fisher Scientific, USA). All steps were performed under sterile and light-protected conditions.</p>
</sec>
<sec id="s2_3_4">
<label>2.3.4</label>
<title>Construction and fitting of the OA dose&#x2013;response curve</title>
<p>Following the MTT assay, cell viability was expressed as a percentage relative to the untreated control (set to 100%), calculated using the formula below.</p>
<disp-formula>
<mml:math display="block" id="M5"><mml:mrow><mml:mtext>Viability</mml:mtext><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mrow><mml:mtext>OD</mml:mtext></mml:mrow><mml:mrow><mml:mtext>treated</mml:mtext></mml:mrow></mml:msub><mml:mo>&#x2212;</mml:mo><mml:msub><mml:mrow><mml:mtext>OD</mml:mtext></mml:mrow><mml:mrow><mml:mtext>blank</mml:mtext></mml:mrow></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mtext>OD</mml:mtext></mml:mrow><mml:mrow><mml:mtext>contro</mml:mtext></mml:mrow></mml:msub><mml:mo>&#x2212;</mml:mo><mml:msub><mml:mrow><mml:mtext>OD</mml:mtext></mml:mrow><mml:mrow><mml:mtext>blank</mml:mtext></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:mo>&#xd7;</mml:mo><mml:mn>100</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math>
</disp-formula>
<p>Using GraphPad Prism 9.0 software, the relationship between OA concentration and cell viability was analyzed by nonlinear regression based on a four-parameter logistic (4PL) model. The equation for the model is as follows:</p>
<disp-formula>
<mml:math display="block" id="M6"><mml:mrow><mml:mtext>y</mml:mtext><mml:mo>=</mml:mo><mml:mtext>min</mml:mtext><mml:mo>+</mml:mo><mml:mfrac><mml:mrow><mml:mtext>max</mml:mtext><mml:mo>&#x2212;</mml:mo><mml:mtext>min</mml:mtext></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mfrac><mml:mtext>x</mml:mtext><mml:mrow><mml:msub><mml:mrow><mml:mtext>IC</mml:mtext></mml:mrow><mml:mrow><mml:mn>50</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:mfrac><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mrow><mml:mtext>Hillslope</mml:mtext></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mrow></mml:math>
</disp-formula>
<p>Where y denotes the percentage of cell viability, x represents the concentration of OA in nM, min is the lower asymptote (indicating the minimum possible viability), max is the upper asymptote, typically representing the maximum viability, which often approaches 100%, IC50 is the half-maximal inhibitory concentration, and the Hill slope reflects the steepness of the dose&#x2013;response relationship.</p>
</sec>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Data analysis</title>
<p>All statistical analyses were performed with SPSS 19 software (IBM, USA). Data are presented as mean &#xb1; SD. The half-maximal inhibitory concentration (IC<sub>50</sub>) was determined by probit analysis. Pearson&#x2019;s product moment correlation coefficient was used to determine the strength of the association between fitted free toxin/fitted total toxin and strain esterification ratios. For data meeting the assumption of normality, differences among experimental groups and the control were assessed using one-way analysis of variance (ANOVA). Data visualization and figure generation were accomplished using Origin 2019b (OriginLab, USA) and GraphPad Prism 10.1.2 (GraphPad Software, USA). Statistical significance was defined as <italic>p</italic> &lt; 0.05.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Growth curve of <italic>P. lima</italic></title>
<p>In the 56-day laboratory cultivation, all eight <italic>P. lima</italic> strains exhibited population growth that closely followed the Logistic model (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>), with excellent fit (R&#xb2; = 0.972&#x2013;0.987). Growth rates differed among strains over the full cultivation cycle (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2</bold></xref>), with the maximum and minimum rates observed in strains 408 (0.046 d<sup>&#x2212;</sup>&#xb9;) and 1115 (0.037 d<sup>&#x2212;</sup>&#xb9;), respectively. During the exponential phase, strain 408 also showed the highest rate (0.071 d<sup>&#x2212;</sup>&#xb9;), while strain 1115 again exhibited the lowest (0.045 d<sup>&#x2212;</sup>&#xb9;). Strain 1115 reached the lowest final density~3 &#xd7; 10<sup>4</sup> cells&#xb7;mL<sup>&#x2212;</sup>&#xb9; (from an initial ~3.5 &#xd7; 10&#xb3; cells&#xb7;mL<sup>&#x2212;</sup>&#xb9;), whereas strains 401, 404, 405, and 408 achieved significantly higher densities (<italic>p</italic> &lt; 0.05).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>The growth curve of eight <italic>P. lima</italic> strains.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-13-1789052-g001.tif">
<alt-text content-type="machine-generated">Line graph comparing cell density in cells per milliliter over time in days for eight groups, each represented by a different color and R-squared value; error bars indicate variation.</alt-text>
</graphic></fig>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>The Growth rate of eight <italic>P. lima</italic> strains.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-13-1789052-g002.tif">
<alt-text content-type="machine-generated">Line graph showing growth rates over time for eight different groups, labeled 401, 403, 404, 405, 406, 407, 408, and 1115. Growth rates decrease steadily for all groups from day zero to day fifty-six, reaching near zero by the end.</alt-text>
</graphic></fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Toxin production and profile variation among eight <italic>P. lima</italic> strains</title>
<p>As shown in <xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3</bold></xref>, OA and DTX-1 were detected in all eight <italic>P. lima</italic> strains, while DTX-2 was not found. Significant inter-strain differences were observed for both free and total toxin concentrations (<italic>p</italic> &lt; 0.05). The ranking of free toxin content (non-hydrolyzed) was 406 &gt; 401 &#x2248; 404 &#x2248; 403 &gt; 407 &gt; 408 &#x2248; 405 &gt; 1115. For total toxin content (hydrolyzed), the order was 401 &gt; 404 &gt; 406 &gt; 403 &gt; 407 &gt; 405 &gt; 1115 &gt; 408. The proportion of esterified toxins (total minus free) varied considerably, with strain 406 having the lowest esterification ratio (53.37%) and strain 1115 the highest (93.07%). OA concentrations increased markedly upon hydrolysis, from 1.22&#x2013;2.24 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9; to 7.73&#x2013;20.2 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;. In contrast, DTX-1 levels changed only slightly, from 0.02&#x2013;11.8 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9; to 0.09&#x2013;13.5 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;. The calibration range, regression model, and corresponding coefficients of determination (R&#xb2;) for the LC-MS/MS quantification are detailed in <xref ref-type="supplementary-material" rid="SF1"><bold>Supplementary Materials</bold></xref>(<xref ref-type="supplementary-material" rid="SF1"><bold>Supplementarys Figure&#xa0;1</bold></xref>&#x2013;<xref ref-type="supplementary-material" rid="SF3"><bold>3</bold></xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Free and total toxin production of eight <italic>P. lima</italic> strains statistical differences among strains were evaluated using one-way analysis of variance (ANOVA) followed by Tukey&#x2019;s honestly significant difference (HSD) <italic>post hoc</italic> test (<italic>p</italic> &lt; 0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-13-1789052-g003.tif">
<alt-text content-type="machine-generated">Stacked bar graph comparing toxin content per cell in various samples, with OA represented in red and DTX-1 in blue. Each sample shows &#x201c;Free&#x201d; and &#x201c;Total&#x201d; toxin values with error bars.</alt-text>
</graphic></fig>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Cytotoxicity assessment</title>
<sec id="s3_3_1">
<label>3.3.1</label>
<title>Cytotoxicity of <italic>P. lima</italic> toxins on neuro-2a cells</title>
<p>Toxin extracts from the eight <italic>P. lima</italic> strains were cytotoxic to Neuro-2a cells, as assessed by the MTT assay. The cytotoxicity, observed for both free and total toxin fractions, was concentration- and time-dependent (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4</bold></xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>The effect of eight <italic>P. lima</italic> strains toxins on the viability of Neuro-2a cells was measured using the MTT assay, Data are the means &#xb1; SD, n=3. <bold>(A)</bold> 24 hours of free toxin exposure. <bold>(B)</bold> 24 hours of total toxin exposure. <bold>(C)</bold> 48 hours of free toxin exposure. <bold>(D)</bold> 48 hours of total toxin exposure, error bars represent the standard deviations of the measurements.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-13-1789052-g004.tif">
<alt-text content-type="machine-generated">Four-panel figure showing line graphs A, B, C, and D with cell viability percentages on the y-axis and toxin concentration (Log, nM) on the x-axis. Each panel presents cell viability for eight color-coded groups labeled 0401, 0403, 0404, 0405, 0406, 0407, 0408, and 1115. Cell viability generally decreases as toxin concentration increases, with variability among groups and experimental conditions. Error bars indicate variability across replicate measurements.</alt-text>
</graphic></fig>
<p>Toxic potency was found to differ significantly among the strains (<italic>p</italic> &lt; 0.05, <xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5</bold></xref>). Under hydrolyzed conditions (total toxin), strain 1115 was identified as the most toxic, with a 24 h IC<sub>50</sub> of 12.82 nM. In contrast, strains 408, 401, 407, and 403 exhibited the weakest toxicity. When the exposure was extended to 48 h, the IC<sub>50</sub> for strain 1115 was further reduced to 4.38 nM. At this time point, the weakest toxicity was observed in strain 404, with a 48 h IC<sub>50</sub> of 49.81 nM. Notably, across all strains, the toxicity of free toxins was significantly greater than that of total toxins (<italic>p</italic> &lt; 0.05). Under non-hydrolyzed conditions (free toxin), the strongest free toxin potency was shown by strain 1115 (24 h IC<sub>50</sub>: 0.85 nM), while the weakest was displayed by strain 408 (24 h IC<sub>50</sub>: 33.34 nM). After 48 h of exposure, the IC<sub>50</sub> for strain 1115 was further decreased to 0.40 nM. The weakest free toxin toxicity at 48 h was exhibited by strain 407, with an IC<sub>50</sub> of 13.24 nM. The ranking of toxin toxicity among the strains was altered following hydrolysis. For the 24 h exposure group, the three most toxic strains remained 1115, 405, and 406. However, a substantial change in the ranking was noted for the 48 h exposure group. Detailed differences are provided in <xref ref-type="table" rid="T4"><bold>Table&#xa0;4</bold></xref>.</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>IC<sub>50</sub> (nM) of free toxin and total toxin from different algal strains in Neuro-2a cells after 24-h and 48-h exposures. <bold>(A)</bold> IC50&#x2013;24 hours of free toxin exposure, <bold>(B)</bold> IC50&#x2013;24 hours of total toxin exposure, <bold>(C)</bold> IC50&#x2013;48 hours of free toxin exposure, <bold>(D)</bold> IC50&#x2013;48 hours of total toxin exposure. Different lowercase letters above the boxes indicate statistically significant differences among the strains, as determined by one-way ANOVA followed by Tukey&#x2019;s HSD <italic>post hoc</italic> test (<italic>p</italic> &lt; 0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-13-1789052-g005.tif">
<alt-text content-type="machine-generated">Four-panel scientific figure featuring box plots labeled A, B, C, and D, each displaying IC&#x2085;&#x2080; values (nM) for different sample groups identified as 401, 403, 404, 405, 406, 407, 408, and 1115 along the x-axes. Panels show variations in IC&#x2085;&#x2080; distributions, with significant differences indicated by letter annotations above each box. All panels use light blue fill for box plots and present data on a white background with consistent formatting.</alt-text>
</graphic></fig>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>IC<sub>50</sub> (nM) of free toxin and total toxin from different algal strains in Neuro-2a cells after 24-h and 48-h exposures (Values within the 20&#x2013;80% viability range are used for the IC<sub>50</sub> calculation to ensure accurate fitting).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Strain</th>
<th valign="middle" align="center">24h IC<sub>50</sub> (total toxin)</th>
<th valign="middle" align="center">24h rank (total toxin)</th>
<th valign="middle" align="center">24h IC<sub>50</sub><break/>(free toxin)</th>
<th valign="middle" align="center">24h rank (free toxin)</th>
<th valign="middle" align="center">Ranking differences</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">1115</td>
<td valign="middle" align="center">12.82 &#xb1; 2.03<sup>c</sup></td>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0.85 &#xb1; 0.44<sup>d</sup></td>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="center">405</td>
<td valign="middle" align="center">45.17 &#xb1; 5.62<sup>b</sup></td>
<td valign="middle" align="center">2</td>
<td valign="middle" align="center">10.51 &#xb1; 4.17<sup>cd</sup></td>
<td valign="middle" align="center">2</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="center">406</td>
<td valign="middle" align="center">46.20 &#xb1; 3.61<sup>b</sup></td>
<td valign="middle" align="center">3</td>
<td valign="middle" align="center">12.53 &#xb1; 2.07<sup>cd</sup></td>
<td valign="middle" align="center">3</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="center">404</td>
<td valign="middle" align="center">67.67 &#xb1; 8.92<sup>ab</sup></td>
<td valign="middle" align="center">4</td>
<td valign="middle" align="center">17.33 &#xb1; 1.32<sup>abc</sup></td>
<td valign="middle" align="center">5</td>
<td valign="middle" align="center">-1</td>
</tr>
<tr>
<td valign="middle" align="center">408</td>
<td valign="middle" align="center">80.95 &#xb1; 16.39<sup>a</sup></td>
<td valign="middle" align="center">5</td>
<td valign="middle" align="center">30.10 &#xb1; 6.33<sup>ab</sup></td>
<td valign="middle" align="center">7</td>
<td valign="middle" align="center">-2</td>
</tr>
<tr>
<td valign="middle" align="center">401</td>
<td valign="middle" align="center">81.83 &#xb1; 8.07<sup>a</sup></td>
<td valign="middle" align="center">6</td>
<td valign="middle" align="center">15.76 &#xb1; 3.01<sup>bcd</sup></td>
<td valign="middle" align="center">4</td>
<td valign="middle" align="center">2</td>
</tr>
<tr>
<td valign="middle" align="center">407</td>
<td valign="middle" align="center">81.86 &#xb1; 7.98<sup>a</sup></td>
<td valign="middle" align="center">7</td>
<td valign="middle" align="center">33.34 &#xb1; 12.83<sup>a</sup></td>
<td valign="middle" align="center">8</td>
<td valign="middle" align="center">-1</td>
</tr>
<tr>
<td valign="middle" align="center">403</td>
<td valign="middle" align="center">88.61 &#xb1; 9.51<sup>a</sup></td>
<td valign="middle" align="center">8</td>
<td valign="middle" align="center">20.26 &#xb1; 5.12<sup>abc</sup></td>
<td valign="middle" align="center">6</td>
<td valign="middle" align="center">2</td>
</tr>
</tbody>
<tbody>
<tr>
<th valign="middle" align="center">Strain</th>
<th valign="middle" align="center">48h IC<sub>50</sub> (total toxin)</th>
<th valign="middle" align="center">48h rank (total toxin)</th>
<th valign="middle" align="center">48h IC<sub>50</sub><break/>(free toxin)</th>
<th valign="middle" align="center">48h rank (free toxin)</th>
<th valign="middle" align="center">Ranking differences</th>
</tr>
<tr>
<td valign="middle" align="center">1115</td>
<td valign="middle" align="center">4.38 &#xb1; 0.87<sup>d</sup></td>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0.40 &#xb1; 0.01<sup>d</sup></td>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="center">408</td>
<td valign="middle" align="center">15.98 &#xb1; 0.69<sup>c</sup></td>
<td valign="middle" align="center">2</td>
<td valign="middle" align="center">9.68 &#xb1; 0.12<sup>ab</sup></td>
<td valign="middle" align="center">6</td>
<td valign="middle" align="center">-4</td>
</tr>
<tr>
<td valign="middle" align="center">406</td>
<td valign="middle" align="center">16.83 &#xb1; 1.19<sup>c</sup></td>
<td valign="middle" align="center">3</td>
<td valign="middle" align="center">9.73 &#xb1; 1.29<sup>ab</sup></td>
<td valign="middle" align="center">7</td>
<td valign="middle" align="center">-4</td>
</tr>
<tr>
<td valign="middle" align="center">405</td>
<td valign="middle" align="center">21.91 &#xb1; 3.79<sup>c</sup></td>
<td valign="middle" align="center">4</td>
<td valign="middle" align="center">2.63 &#xb1; 0.43<sup>cd</sup></td>
<td valign="middle" align="center">2</td>
<td valign="middle" align="center">2</td>
</tr>
<tr>
<td valign="middle" align="center">401</td>
<td valign="middle" align="center">28.78 &#xb1; 2.67<sup>b</sup></td>
<td valign="middle" align="center">5</td>
<td valign="middle" align="center">6.04 &#xb1; 0.45<sup>bc</sup></td>
<td valign="middle" align="center">3</td>
<td valign="middle" align="center">2</td>
</tr>
<tr>
<td valign="middle" align="center">403</td>
<td valign="middle" align="center">31.96 &#xb1; 1.42<sup>b</sup></td>
<td valign="middle" align="center">6</td>
<td valign="middle" align="center">8.14 &#xb1; 2.93<sup>b</sup></td>
<td valign="middle" align="center">5</td>
<td valign="middle" align="center">1</td>
</tr>
<tr>
<td valign="middle" align="center">407</td>
<td valign="middle" align="center">34.32 &#xb1; 2.53<sup>b</sup></td>
<td valign="middle" align="center">7</td>
<td valign="middle" align="center">13.24 &#xb1; 3.81<sup>a</sup></td>
<td valign="middle" align="center">8</td>
<td valign="middle" align="center">-1</td>
</tr>
<tr>
<td valign="middle" align="center">404</td>
<td valign="middle" align="center">49.81 &#xb1; 3.57<sup>a</sup></td>
<td valign="middle" align="center">8</td>
<td valign="middle" align="center">6.09 &#xb1; 0.41<sup>bc</sup></td>
<td valign="middle" align="center">4</td>
<td valign="middle" align="center">4</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>IC<sub>50</sub> was determined by probit analysis. Tukey&#x2019;s HSD test indicated that the differences between each toxin treatment group and the control, as well as between treatment groups, were statistically significant (p &lt; 0.05). Data are the means &#xb1; SD, n=3.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3_2">
<label>3.3.2</label>
<title>Construction of OA dose&#x2013;response curves and comparison of toxic equivalents.</title>
<p>OA was observed to exert a typical dose-dependent toxic effect on Neuro-2a cells (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6</bold></xref>). The dose&#x2013;response relationships for both 24 h and 48 h exposures were fitted with a four-parameter logistic (4PL) model, and a high goodness-of-fit was shown for both curves (R&#xb2; &gt; 0.97). However, cellular sensitivity to the toxin was enhanced by 48 h exposure, which resulted in a narrower linear range of the dose&#x2013;response curve. To ensure an accurate and reliable estimation of toxic equivalents (TEQs) via interpolation (<xref ref-type="bibr" rid="B51">Tubaro et&#xa0;al., 1996</xref>), the 24 h standard curve was selected as the reference for subsequent analyses, due to its wider linear range and greater fitting stability.</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Dose&#x2013;response curves of OA in Neuro-2a cells. Cells were exposed to various concentrations of OA (19.42&#x2013;2486.12 nM) for 24 h or 48 h, and cell viability was assessed by the MTT assay. Data points represent the mean of three independent experiments. The solid line shows the fit of a four-parameter logistic (4PL) model. The figure indicates the goodness of fit (R&#xb2;) and the half-maximal inhibitory concentration (IC<sub>50</sub>).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-13-1789052-g006.tif">
<alt-text content-type="machine-generated">Line graph illustrating cell viability percentage versus toxin concentration in nanomolar at two time points: 24 hours (red, IC50 equals 680.8 nanomolar) and 48 hours (blue, IC50 equals 53.03 nanomolar). Both curves show a dose-dependent decrease in cell viability, with viability declining more sharply at 48 hours than at 24 hours. R squared values are 0.9826 and 0.9782 for 24 and 48 hours, respectively.</alt-text>
</graphic></fig>
<p>Based on the established OA 24&#xa0;h dose&#x2013;response curve, the OA-equivalent concentrations (hereafter referred to as &#x201c;fitted concentrations&#x201d;) for both the free and total toxin preparations of the eight P.&#xa0;lima strains were calculated by interpolation. These fitted concentrations, representing OA concentrations with equivalent cytotoxic effects, were then compared with the summed concentrations of OA&#xa0;+&#xa0;DTX 1 measured by LC&#x2013;MS/MS (expressed as OA equivalents, hereafter &#x201c;measured concentrations&#x201d;). Overall, the fitted concentrations were found to be higher than the measured concentrations (<xref ref-type="table" rid="T5"><bold>Table&#xa0;5</bold></xref>). Notably, the discrepancy between fitted and measured concentrations was generally greater in the free toxin group than in the total toxin group. For example, strain&#xa0;1115, which exhibited the highest esterification ratio (approximately&#xa0;93%), showed a fitted concentration of about 153.44&#xa0;pg&#xb7;cell<sup>&#x2212;</sup>&#xb9; and a measured concentration of about 18.90&#xa0;pg&#xb7;cell<sup>&#x2212;</sup>&#xb9; in the total toxin group. In the free toxin group, its fitted concentration was approximately 183.59&#xa0;pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;, while the measured concentration was only about 1.31&#xa0;pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;. This pattern is consistent with its high esterification ratio and suggests that the toxicity contribution of esterified toxins may be underestimated by chemical analysis. Although some strains had similar measured concentrations, their fitted concentrations differed markedly. For instance, strains&#xa0;408 and&#xa0;1115 had measured total toxin concentrations of 17.07 and 18.90&#xa0;pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;, respectively, yet their fitted total toxin concentrations were 32.95 and 153.44&#xa0;pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;. Similarly, Although strains&#xa0;401,&#xa0;403, and&#xa0;404 had similar measured free toxin concentrations (&#x2248;&#xa0;11&#x2013;12&#xa0;pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;), their fitted concentrations revealed marked differences: approximately 104.95, 87.44, and 67.80&#xa0;pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;, respectively. This indicates a clear divergence in their toxic potency.</p>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>Measured (LC-MS/MS) and fitted (OA dose-response curve-based) OA-equivalent concentrations of total and free toxins from different <italic>P. lima</italic> strains (pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Strain</th>
<th valign="middle" align="center">Fitted total toxin concentrations</th>
<th valign="middle" align="center">Total toxin concentrations</th>
<th valign="middle" align="center">Fitted free toxin<break/>concentrations</th>
<th valign="middle" align="center">Free toxin concentrations</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">401</td>
<td valign="middle" align="center">32.334</td>
<td valign="middle" align="center">31.84</td>
<td valign="middle" align="center">104.95</td>
<td valign="middle" align="center">12.06</td>
</tr>
<tr>
<td valign="middle" align="center">403</td>
<td valign="middle" align="center">33.60</td>
<td valign="middle" align="center">26.60</td>
<td valign="middle" align="center">87.44</td>
<td valign="middle" align="center">11.20</td>
</tr>
<tr>
<td valign="middle" align="center">404</td>
<td valign="middle" align="center">75.20</td>
<td valign="middle" align="center">30.62</td>
<td valign="middle" align="center">67.80</td>
<td valign="middle" align="center">11.20</td>
</tr>
<tr>
<td valign="middle" align="center">405</td>
<td valign="middle" align="center">62.99</td>
<td valign="middle" align="center">21.72</td>
<td valign="middle" align="center">57.00</td>
<td valign="middle" align="center">7.31</td>
</tr>
<tr>
<td valign="middle" align="center">406</td>
<td valign="middle" align="center">88.77</td>
<td valign="middle" align="center">29.18</td>
<td valign="middle" align="center">95.07</td>
<td valign="middle" align="center">13.61</td>
</tr>
<tr>
<td valign="middle" align="center">407</td>
<td valign="middle" align="center">35.91</td>
<td valign="middle" align="center">23.45</td>
<td valign="middle" align="center">33.80</td>
<td valign="middle" align="center">9.14</td>
</tr>
<tr>
<td valign="middle" align="center">408</td>
<td valign="middle" align="center">32.95</td>
<td valign="middle" align="center">17.07</td>
<td valign="middle" align="center">28.38</td>
<td valign="middle" align="center">7.60</td>
</tr>
<tr>
<td valign="middle" align="center">1115</td>
<td valign="middle" align="center">153.44</td>
<td valign="middle" align="center">18.90</td>
<td valign="middle" align="center">183.59</td>
<td valign="middle" align="center">1.31</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Fitted OA-equivalent concentrations were calculated by interpolation based on a four-parameter logistic (4PL) model. Data are means of three replicates (n=3).</p></fn>
</table-wrap-foot>
</table-wrap>
<p>To explore the relationship between fitted concentrations and strain esterification ratios, Pearson correlation analysis was performed. A significant correlation between esterification ratios and fitted concentrations was observed (<xref ref-type="table" rid="T6"><bold>Table&#xa0;6</bold></xref>). Specifically, fitted total toxin concentrations showed a significant positive correlation with esterification ratios (Pearson r=&#xa0;0.796, <italic>p</italic> &#xa0;&lt;&#xa0;0.05), and fitted free toxin concentrations were also significantly positively correlated with esterification ratios (Pearson r&#xa0;=&#xa0;0.764, p &lt;&#xa0;0.05). These results indicate that variation in esterification ratios is associated with differences in toxicity inferred from the bioassay.</p>
<table-wrap id="T6" position="float">
<label>Table&#xa0;6</label>
<caption>
<p>Pearson correlation analysis between fitted total and free toxin concentrations and strain esterification ratios.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Variable</th>
<th valign="middle" align="center">AVG</th>
<th valign="middle" align="center">SD</th>
<th valign="middle" align="center">PCC</th>
<th valign="middle" align="center">Sig</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">Fitted total toxin concentrations</td>
<td valign="middle" align="center">64.398</td>
<td valign="middle" align="center">42.120</td>
<td valign="middle" align="center">0.796</td>
<td valign="middle" align="center">0.018</td>
</tr>
<tr>
<td valign="middle" align="center">Fitted free toxin concentrations</td>
<td valign="middle" align="center">82.255</td>
<td valign="middle" align="center">49.384</td>
<td valign="middle" align="center">0.764</td>
<td valign="middle" align="center">0.027</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>This study conducted a comprehensive analysis of eight <italic>P. lima</italic> strains isolated from the coastal waters of China, focusing on inter-strain differences in growth rates, toxin production, and cytotoxicity. The findings provide empirical evidence for intraspecific heterogeneity and ecological adaptation strategies associated with the production of DSTs.</p>
<sec id="s4_1">
<label>4.1</label>
<title>Toxin-production diversity among <italic>P. lima</italic> strains and algal survival strategies</title>
<p>Regarding toxin yield, the eight <italic>P. lima</italic> strains examined in this study exhibited pronounced diversity in toxin production. The range of total toxin concentration after hydrolysis (17.07&#x2013;31.84 pg OAeq&#xb7;cell<sup>&#x2212;</sup>&#xb9;) was higher than that recently reported for Chinese coastal strains by <xref ref-type="bibr" rid="B13">Chen et&#xa0;al. (2025)</xref> (0.551&#x2013;10.26 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;), indicating that even within the coastal waters of a single country, the toxin-producing potential can vary substantially among strains isolated from different locations (<xref ref-type="bibr" rid="B13">Chen et&#xa0;al., 2025</xref>). However, the toxin concentration range observed in this study overlaps with values reported from other temperate marine regions worldwide. For instance, strain IO66&#x2013;01 from Lisbon Bay, Portugal, has been reported to produce up to 41.0 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9; of toxins at specific growth stages (<xref ref-type="bibr" rid="B52">Vale et&#xa0;al., 2009</xref>), while strains from Fleet Lagoon in the United Kingdom can produce 0.4&#x2013;17.1 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9; (<xref ref-type="bibr" rid="B35">Nascimento et&#xa0;al., 2005</xref>); this indicates that the strains examined in this study possess toxin-producing capacities comparable to those of certain high-yield temperate strains.</p>
<p>In terms of toxin composition, OA and DTX-1 were detected in all strains, while DTX-2 was not detected. This pattern is highly consistent with the findings of Luo et&#xa0;al. in the northern South China Sea and those of <xref ref-type="bibr" rid="B8">Bravo et&#xa0;al. (2001)</xref> on the Galician coast of Spain (<xref ref-type="bibr" rid="B8">Bravo et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B31">Luo et&#xa0;al., 2017</xref>); in the latter study, OA and DTX-1 were likewise the predominant components among 19 strains, with only a few strains containing trace amounts of DTX-2. This observation also aligns with the description by <xref ref-type="bibr" rid="B35">Nascimento et&#xa0;al. (2005)</xref> of strains from Fleet Lagoon, UK (<xref ref-type="bibr" rid="B35">Nascimento et&#xa0;al., 2005</xref>), further supporting the view that OA and DTX-1 constitute the core toxin components of <italic>P. lima</italic> in temperate regions, whereas DTX-2 is not a widespread or predominant product in these algal populations. Notably, strain 1115 in this study displayed a distinctive chemotype almost exclusively dominated by OA (18.81 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;), with a very low DTX-1 concentration (0.096 pg&#xb7;cell<sup>&#x2212;</sup>&#xb9;). This chemotype is not unique: <xref ref-type="bibr" rid="B37">Oyeku and Mandal (2021)</xref> similarly reported an OA-only profile for strain CSIRCSMCRI005 isolated from the Bay of Bengal in the northern Indian Ocean (<xref ref-type="bibr" rid="B37">Oyeku and Mandal, 2021</xref>). These findings confirm that the toxin signatures of <italic>P. lima</italic> exhibit pronounced geographic diversity and strain specificity; differences in geographic habitats can drive the development of distinct toxin profiles among regional strains, and such characteristic profiles may serve as key discriminative markers for distinguishing strains of different geographic origins.</p>
<p>The pronounced differences in toxin yield and composition observed among strains not only reflect the geographic diversity of their origins but also likely underpin distinct physiological adaptations and survival strategies. Based on these findings, we further analyzed the relationship between growth and toxin production and identified a trade-off in resource allocation between growth rate and toxin biosynthesis; this phenomenon aligns with the previously proposed &#x201c;growth&#x2013;defense&#x2013;metabolism&#x201d; trade-off in dinoflagellates and provides direct experimental support for the operation of this strategy in our study system (<xref ref-type="bibr" rid="B9">Brown and Kubanek, 2020</xref>; <xref ref-type="bibr" rid="B30">Lee et&#xa0;al., 2016</xref>). Specifically, the synthesis of secondary metabolites (e.g., DSP toxins) requires substantial energy and precursor molecules (e.g., acetyl-CoA and glycerol-3-phosphate), whereas fast-growing strains tend to reallocate metabolic resources away from secondary metabolite biosynthesis, prioritizing core resources, carbon and nitrogen, for nucleic acid and protein synthesis to support cell division, thereby constraining metabolic investment in toxin production (<xref ref-type="bibr" rid="B9">Brown and Kubanek, 2020</xref>; <xref ref-type="bibr" rid="B30">Lee et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B33">Morton et&#xa0;al., 1994</xref>; <xref ref-type="bibr" rid="B42">Roussel et&#xa0;al., 2023</xref>). In this study, strains 408 and 405 exhibited significantly higher specific growth rates than the other strains but produced the lowest total toxin amounts. This pattern can be explained by the resource-allocation priority theory: in Chinese coastal waters, where eutrophication is frequent and interspecific competition is intense, the adaptive advantage of rapid colonization to secure ecological niches may outweigh the benefits of toxin-based defenses. Such a metabolic strategy may confer ecological advantages in environments where rapid colonization is essential for survival, but it also implies that under favorable conditions, the energetic demands of rapid growth may limit toxin-producing capacity; this mechanism has been reported in <italic>Prorocentrum</italic> species and other toxigenic dinoflagellates (<xref ref-type="bibr" rid="B15">David et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B25">Hwang et&#xa0;al., 2025</xref>; <xref ref-type="bibr" rid="B42">Roussel et&#xa0;al., 2023</xref>; <xref ref-type="bibr" rid="B53">Varkitzi et&#xa0;al., 2010</xref>). Conversely, slower-growing strains (e.g., 406 and 404) produced significantly higher toxin concentrations. These observations further support the hypothesis that toxin production is more likely to occur in slower-growing strains, serving as a defensive mechanism against grazers or competing species (<xref ref-type="bibr" rid="B37">Oyeku and Mandal, 2021</xref>; <xref ref-type="bibr" rid="B43">Selander et&#xa0;al., 2006</xref>; <xref ref-type="bibr" rid="B47">Tarazona-Janampa et&#xa0;al., 2020</xref>). Previous studies commonly report that under stressful or slow-growth conditions, dinoflagellates tend to increase secondary metabolite synthesis to enhance their survival and competitive ability.</p>
</sec>
<sec id="s4_2">
<label>4.2</label>
<title>Relationship between <italic>P. lima</italic> toxicity and toxin esterification ratio</title>
<p>The chemical state of the toxins (i.e., toxin esterification) is one of the key factors influencing the overall toxicity of <italic>P. lima</italic> strains. In the eight strains examined in this study, esterification ratios ranged from 53.37% to 93.07%. Strain 1115 exhibited the highest esterification ratio (93.07%) and markedly low free toxin concentration, suggesting a toxin-sequestration strategy that may protect cells from damage induced by free toxins; this phenomenon is not unique in natural populations. <xref ref-type="bibr" rid="B13">Chen et&#xa0;al. (2025)</xref> reported that esterified toxins accounted for 43.9%&#x2013;92.2% of total toxins in Chinese coastal strains, with esterification levels in Bohai&#x2013;Yellow Sea isolates comparable to those of strain 1115 in the present study (<xref ref-type="bibr" rid="B13">Chen et&#xa0;al., 2025</xref>). This high-esterification strategy has important toxicological implications: in our study, strains with high esterification ratios exhibited significantly greater cytotoxicity than those with low esterification ratios. <xref ref-type="bibr" rid="B55">Wu et&#xa0;al. (2020)</xref> similarly observed that algal cell extracts rich in esterified toxins exhibited markedly greater acute toxicity in mice than did free toxins, indicating that esterified derivatives or their metabolites constitute an important component of overall toxicity (<xref ref-type="bibr" rid="B55">Wu et&#xa0;al., 2020</xref>). Moreover, different toxin analogues within the same strain exhibit specificity in their esterification behavior. For example, <xref ref-type="bibr" rid="B8">Bravo et&#xa0;al. (2001)</xref> reported that DTX-1 tends not to form esterified derivatives, whereas OA does the opposite. This aligns with our observation of a pronounced increase in OA levels after hydrolysis (<xref ref-type="bibr" rid="B8">Bravo et&#xa0;al., 2001</xref>). Furthermore, <xref ref-type="bibr" rid="B27">Ji et&#xa0;al. (2025)</xref>&#x2019;s structural and activity studies on novel diol esters further indicate that esterification generates a large array of structurally diverse compounds with varying bioactivities (<xref ref-type="bibr" rid="B27">Ji et&#xa0;al., 2025</xref>). These structurally diverse esterified derivatives typically have low bioavailability and may be stored intracellularly in a &#x201c;dormant&#x201d; state, forming a stable toxin reservoir; however, if environmental conditions change or cellular stress triggers their release, they can substantially elevate acute toxicity risk (<xref ref-type="bibr" rid="B13">Chen et&#xa0;al., 2025</xref>, <xref ref-type="bibr" rid="B12">2023</xref>; <xref ref-type="bibr" rid="B24">Hu et&#xa0;al., 1992</xref>; <xref ref-type="bibr" rid="B28">Kilcoyne et&#xa0;al., 2020</xref>).</p>
<p>In Neuro-2a cytotoxicity assays, most samples exhibited increased IC<sub>50</sub> values after hydrolysis, indicating an overall attenuation of toxicity. Concurrently, LC&#x2013;MS/MS measurements revealed several unidentified chromatographic peaks in the non-hydrolyzed extracts (<xref ref-type="fig" rid="f7"><bold>Figure&#xa0;7</bold></xref>) that could not be quantified due to the limited availability of analytical standards (<xref ref-type="bibr" rid="B27">Ji et&#xa0;al., 2025</xref>). Notably, these unidentified peaks were markedly reduced or absent following hydrolysis, accompanied by corresponding changes in the peak areas of OA and DTX-1 (<xref ref-type="fig" rid="f8"><bold>Figure&#xa0;8</bold></xref>). These unknown or unquantified toxins may not only exert independent cytotoxic effects but also act additively or synergistically with OA and DTX-1, thereby amplifying the overall toxicity of the extracts (<xref ref-type="bibr" rid="B55">Wu et&#xa0;al., 2020</xref>). Additionally, esterified toxins, owing to their retained acyl side chains, are generally more hydrophobic and may influence their cellular partitioning and bioavailability, potentially affecting the relationship between chemical analytical results and observed biological effects (<xref ref-type="bibr" rid="B11">Cavion et&#xa0;al., 2025</xref>; <xref ref-type="bibr" rid="B19">Fu et&#xa0;al., 2019</xref>). When fitted OA-eq concentrations inferred from the OA dose&#x2013;response curve model were compared with LC&#x2013;MS/MS-measured total OA-eq concentrations, several strains, particularly those in the free toxin group, exhibited fitted values markedly higher than the chemically measured values; moreover, fitted concentrations were significantly positively correlated with strain esterification ratios. Integrating results from cytotoxicity assays, LC&#x2013;MS/MS chemical quantification, and fitted toxin concentration analyses, we suggest that differences in esterification ratios and the presence of unidentified components are important factors associated with the divergence between LC&#x2013;MS/MS-quantified toxin levels and the toxicities of strains observed in cell-based assays. Therefore, in assessing P. lima toxicity, &#x201c;chemical equivalents&#x201d; derived from LC&#x2013;MS/MS should be regarded as complementary to, rather than fully equivalent to, &#x201c;bioequivalents&#x201d; derived from cell-based toxicity assays. Although hydrolysis can improve the detectability of esterified toxin components in targeted analytical methods (<xref ref-type="bibr" rid="B17">Doucet et&#xa0;al., 2007</xref>), the concomitant changes in chemical speciation do not necessarily align biological effects with levels implied by stoichiometric chemical measurements (<xref ref-type="bibr" rid="B40">Rodrigues et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B54">Villar-Gonz&#xe1;lez et&#xa0;al., 2008</xref>). Incorporating bioassay-based approaches or factoring in esterification ratios can more comprehensively reflect the overall toxicological profile of algal toxin mixtures. Furthermore, future studies should employ high-resolution mass spectrometry techniques (e.g., LC&#x2013;HRMS) (<xref ref-type="bibr" rid="B16">Dom et&#xa0;al., 2018</xref>) to systematically screen and structurally characterize unidentified chromatographic peaks, and combine chromatographic fractionation with activity-guided bioassays to elucidate the relative contributions and interaction mechanisms of different toxin components to overall toxicity. This integrated methodology will provide a more robust theoretical and methodological foundation for toxin risk assessment that integrates chemical analysis with biological effects.</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>LC&#x2013;MS analysis of free toxins in eight <italic>P. lima</italic> strains.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-13-1789052-g007.tif">
<alt-text content-type="machine-generated">Panel of eight chromatograms displays intensity versus time for toxin analysis in clam samples. Peaks for DTX-1 and OA are clearly labeled, and areas for unknown toxins are highlighted in green boxes.</alt-text>
</graphic></fig>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>LC&#x2013;MS analysis of total toxins in eight <italic>P. lima</italic> strains.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-13-1789052-g008.tif">
<alt-text content-type="machine-generated">Eight-panel graphic displays chromatograms with two primary peaks labeled OA and DTX-1 between seven and eight minutes on the time axis in each panel. Peak heights and retention times are consistent across all charts, indicating quantitative analysis of similar samples.</alt-text>
</graphic></fig>
</sec>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusion</title>
<p>In the context of HABs risk assessment, this study systematically compared eight <italic>P. lima</italic> strains from China&#x2019;s coastal waters with respect to growth characteristics, toxin composition and concentrations, toxin esterification status, and cytotoxicity. Results indicate pronounced intraspecific heterogeneity among strains in growth strategies and toxicity expression, and that potential toxic risk cannot be accurately assessed solely by growth rate or measured toxin concentration. LC&#x2013;MS/MS measurements showed that OA and DTX-1 were the principal toxin components across strains, although esterification ratios differed markedly among them. Combined analysis of cytotoxicity assays and OA dose&#x2013;response&#x2013;based toxic equivalent back-calculations revealed that highly esterified strains do not necessarily exhibit higher toxin levels by targeted chemical quantification. However, they display stronger toxic responses in cell-based assays, and fitted toxic equivalents are significantly positively correlated with esterification ratios. The results suggest that targeted chemical quantification(LC&#x2013;MS/MS with available standards) carry a risk of underestimation when unquantified or structurally uncharacterized bioactive components are present. Confirming that targeted quantification systematically underestimates biological risk will require broader chemical coverage (e.g., LC&#x2013;HRMS) and activity-guided verification experiments to assign toxicity to specific unquantified components. Overall, this study underscores the importance of incorporating toxin esterification characteristics and biological effect data into integrated assessment frameworks, thereby providing a scientific basis for the evaluation and monitoring of HABs toxicity risk.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p></sec>
<sec id="s7" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>Ethical approval was not required for the studies on animals in accordance with the local legislation and institutional requirements because only commercially available established cell lines were used.</p></sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>JF: Methodology, Formal analysis, Writing &#x2013; original draft, Data curation. XW: Writing &#x2013; original draft, Methodology, Visualization. PR: Investigation, Validation, Writing &#x2013; original draft. PZ: Data curation, Writing &#x2013; review &amp; editing, Conceptualization, Supervision, Project administration, Funding acquisition. ML: Writing &#x2013; review &amp; editing, Supervision, Conceptualization. YG: Writing &#x2013; review &amp; editing, Methodology, Resources.</p></sec>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p></sec>
<sec id="s11" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p></sec>
<sec id="s12" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec>
<sec id="s13" 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="https://www.frontiersin.org/articles/10.3389/fmars.2026.1789052/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmars.2026.1789052/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Image1.jpg" id="SF1" mimetype="image/jpeg"><label>Supplementary Figure&#xa0;1</label>
<caption>
<p>LC&#x2013;MS/MS calibration curve for okadaic acid (OA).</p>
</caption></supplementary-material>
<supplementary-material xlink:href="Image2.jpg" id="SF2" mimetype="image/jpeg"><label>Supplementary Figure&#xa0;2</label>
<caption>
<p>LC&#x2013;MS/MS calibration curve for dinophysistoxin-1 (DTX-1).</p>
</caption></supplementary-material>
<supplementary-material xlink:href="Image3.jpg" id="SF3" mimetype="image/jpeg"><label>Supplementary Figure&#xa0;3</label>
<caption>
<p>LC&#x2013;MS/MS calibration curve for dinophysistoxin-2 (DTX-2).</p>
</caption></supplementary-material></sec>
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<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/596552">Hongbo Jiang</ext-link>, Shenyang Agricultural University, China</p></fn>
<fn id="n2" fn-type="custom" custom-type="reviewed-by">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1733867">Lianbao Chi</ext-link>, Chinese Academy of Sciences (CAS), China</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2831336">Yu Ding</ext-link>, WeihaI Vocational College, China</p></fn>
</fn-group>
</back>
</article>