Article(id=1238813324108952201, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1238813307784712441, articleNumber=null, orderNo=null, doi=10.13343/j.cnki.wsxb.20250586, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1753718400000, receivedDateStr=2025-07-29, revisedDate=null, revisedDateStr=null, acceptedDate=1765296000000, acceptedDateStr=2025-12-10, onlineDate=1773285712505, onlineDateStr=2026-03-12, pubDate=1772553600000, pubDateStr=2026-03-04, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773285712505, onlineIssueDateStr=2026-03-12, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773285712505, creator=13701087609, updateTime=1773285712505, updator=13701087609, issue=Issue{id=1238813307784712441, tenantId=1146029695717560320, journalId=1192105938417971205, year='2026', volume='66', issue='3', pageStart='961', pageEnd='1466', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773285708614, creator=13701087609, updateTime=1773291912509, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1238839328915378858, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1238813307784712441, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1238839328915378859, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1238813307784712441, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1412, endPage=1425, ext={EN=ArticleExt(id=1238813325828616883, articleId=1238813324108952201, tenantId=1146029695717560320, journalId=1192105938417971205, language=EN, title=Application of fluorescence-activated cell sorting in the study of functional groups of microalgae, columnId=1194702985843413943, journalTitle=Acta Microbiologica Sinica, columnName=Technology and Method, runingTitle=null, highlight=null, articleAbstract=

Objective Mixotrophy that combines phototrophic autotrophy and phagotrophic heterotrophy is widespread among unicellular eukaryotic microalgae and plays a key ecological role in energy flow within food webs and in elemental biogeochemical cycles. However, identifying and characterizing mixotrophic microalgae in natural waters remains technically challenging. Improving current approaches to accurately reveal the diversity of mixotrophic microalgae is an urgent task in this field. Methods Fluorescently labeled prey surrogates and feeding experiments were employed to trace phagotrophic microalgae within plankton communities. Target organisms were captured at the single-cell level through fluorescence-activated cell sorting (FACS), followed by multiple-displacement amplification (MDA) and 18S rRNA gene sequencing for taxonomic identification. On the basis of this FACS-MDA workflow, we established a methodological framework for studying the functional groups of microalgae. Results Applying this approach to multiple freshwater and seawater samples from China, we identified twenty phagotrophic microalgal species belonging to six classes and twelve genera, as well as heterotrophic consumers representing one class and three genera, demonstrating the robustness and broad applicability of this method. Conclusion This study applies the combined FACS-MDA technology to the identification of functional groups of microalgae in natural water bodies. The established technology has broad application prospects in microbial ecology. It enables deeper insights into the functional diversity and in situ feeding activities of environmental microalgae.

, correspAuthors=Haixia JIANG, authorNote=null, correspAuthorsNote=
*E-mail:
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#These authors contributed equally to this work.

, authorsList=Ying WANG, Qian LI, Jie XU, Wei SUN, Haixia JIANG), CN=ArticleExt(id=1238813326810084125, articleId=1238813324108952201, tenantId=1146029695717560320, journalId=1192105938417971205, language=CN, title=荧光激活单细胞分选技术在微藻功能类群研究中的应用, columnId=1194702986061517752, journalTitle=微生物学报, columnName=技术与方法, runingTitle=null, highlight=null, articleAbstract=

目的 兼具光合与摄食功能的混合营养策略在单细胞真核微藻中广泛存在,其在食物网能量流动以及元素生物地球化学循环中发挥着重要作用。研究自然水体中混养微藻的种类构成存在技术难题,因此提升现有手段以准确揭示其多样性是该领域亟待解决的科学问题。 方法 通过添加荧光猎物标记物并开展摄食实验,追踪群落中的摄食型微藻;利用荧光激活流式细胞分选技术在单细胞水平上捕捉目标生物,结合基因组扩增与18S rRNA基因鉴定其物种,最终建立了一种单细胞分选与基因组扩增相结合的FACS-MDA联用方法。 结果 利用该方法检测了来自我国淡水与海水环境中多个样品的混养微藻,获取了隶属于6纲12属的20个摄食型微藻物种,以及1纲3属的异养摄食者,证实了该方法的有效性。 结论 本研究将FACS-MDA联用技术应用于天然水体微藻功能群鉴定,所建立的荧光激活分选和单细胞测序技术在微生物生态学领域具有广泛的应用前景,有助于加深对环境微藻功能类群及其原位摄食活动的认知。

, correspAuthors=蒋海霞, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=RUBdClqz2viZ5ufezhhRMQ==, magXml=45oRnhv0xVWqE6fUBnnX8Q==, pdfUrl=null, pdf=0iBF7Gf8dPu8nk44cCEedA==, pdfFileSize=1812974, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=5eg29bxT97mUdq9lnqq55A==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=vfReX+HepvSTHjI4RZLrhw==, mapNumber=null, authorCompany=null, fund=null, authors=

作者贡献声明

王莹:采样,完成实验;李倩:项目提出,设计实验,数据收集与分析,文章写作与修订;许杰:项目审阅,提供资源;孙伟:提供资源,文章审阅;蒋海霞:完成荧光激活单细胞分选实验,文章审阅与修订。

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A-B: Gating of positive chlorophyll fluorescence signal of PerCP-Cy5.5-A (shaded area) using algal cultures of Prymnesium parvum (A) and Amphidinium carterae (B); C: Gating of positive prey fluorescence of FITC (shaded area) using 1.0 μm green fluorescence beads (The small boxes on the left-bottom corner of each panel denote noises); D-F: Fluorescent microscopic images demonstrate the fluorescent intensity of the algae and fluorescent beads used for the gating in panel A-C (Note that panel F is a mixture of 1.0 μm and 0.5 μm-sized beads; The shaded areas in panels A-C represent positive PerCP-Cy5.5 and FITC fluorescent signals, used to distinguish populations of microalgae and fluorescent beads, respectively). All scale bars in D-F are 5 μm., figureFileSmall=J+3IOyUrKsIlfv0MkQXtZQ==, figureFileBig=J6iIVcov1ftUnnDpzfMdBw==, tableContent=null), ArticleFig(id=1238891101751398960, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1238813324108952201, language=CN, label=图1, caption=基于纯培养藻株和荧光微球对照组圈门及荧光信号阈值界定, figureFileSmall=J+3IOyUrKsIlfv0MkQXtZQ==, figureFileBig=J6iIVcov1ftUnnDpzfMdBw==, tableContent=null), ArticleFig(id=1238891101927559746, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1238813324108952201, language=EN, label=Figure 2, caption=Significance analysis of the proportion of mixed microalgae among the three environments based on intergroup t-test (A), and feeding-type microalgal events detected by flow cytometry at different stations (B-I). A: The averaged value of relative abundance of mixotrophs (mixo, %) across three different environments, including four seasonal samples from the lake, three samples from SCS-inshore, and three samples in SCS-offshore, matching the station classification and values listed in the table in Table 1; B-I: Populations of actively-feeding mixotrophs (blue boxes with blue dots) across the lake (B-C), SCS-inshore (D-F), and offshore samples (G-I); Note that, to save space, only 8 out of 12 stations/samples are demonstrated; In all flow cytometry graphs, total microaglae populations (euks) identified by flow cytometry were denoted in green dots; Free beads not ingested were color-coded in black dots (prey) and all other events were in grey color (possibly Prochlorococcus in SCS samples and noises in the lake samples). *P<0.05, indicating significant differences., figureFileSmall=XHCRIYCrjvdR5JKxN8cKWw==, figureFileBig=RQHP/RgVoyoK+OhGBz6/8A==, tableContent=null), ArticleFig(id=1238891103454286413, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1238813324108952201, language=CN, label=图2, caption=混养微藻在三大环境中平均占比水平的显著性差异分析(A),以及流式细胞仪检测的不同站位的摄食型微藻事件(B-I), figureFileSmall=XHCRIYCrjvdR5JKxN8cKWw==, figureFileBig=RQHP/RgVoyoK+OhGBz6/8A==, tableContent=null), ArticleFig(id=1238891103575921238, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1238813324108952201, language=EN, label=Figure 3, caption=Whole-genome and 18S rRNA gene amplification results from partially sorted microalgal cells (A), and representative evidence of prey ingestion by representative species observed under fluorescence microscopy (B). A: Representative gel images with successful and failed bands amplification from MDA (left-side) and 18S rRNA genes (right-side); B: Fluorescent microscopic images show beads/prey ingestion evidence (indicated by white arrows) of commonly found mixotrophs in the lake samples, including Dinobryon, Cyrptomonas, and Pedinellales; The last two columns indicate total numbers of cells that were successfully sorted and annotated as eukaryotes, as well as the possibility of being a mixotroph based on previous research evidence; Arrows in panel A denote the correct gene sizes in base pairs., figureFileSmall=UbHXnkz5ezO8QtTwiPMenQ==, figureFileBig=/3A2+f0JoUEF2KLKHLgUWw==, tableContent=null), ArticleFig(id=1238891103710138976, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1238813324108952201, language=CN, label=图3, caption=部分分选微藻细胞全基因组和18S rRNA基因扩增结果(A)以及荧光显微镜下获得的代表物种摄食证据(B), figureFileSmall=UbHXnkz5ezO8QtTwiPMenQ==, figureFileBig=/3A2+f0JoUEF2KLKHLgUWw==, tableContent=null), ArticleFig(id=1238891103844356718, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1238813324108952201, language=EN, label=Table 1, caption=

Station coordinates (latitude and longitude), abundance proportion of mixotrophic microalgae relative to total microalgae, and total microalgal abundance (euks)

, figureFileSmall=null, figureFileBig=null, tableContent=
HabitatStation/SeasonLatitude (N)Longitude (E)Mixo (%)Euks (cells/mL)
SCS-inshoreSCS-2821.7°113.1°22.6×104
SCS-4622.2°113.7°15.8×104
SCS-5122.7°113.7°12.2×105
Inshore-offshore transitSCS-3620.7°113.4°257.3×104
SCS-J118.0°110.0°171.0×103
SCS-offshoreSCS-J718.0°113.0°192.0×102
SCS-J1918.0°119.0°339.3×102
SCS-D4016.0°116.0°281.0×103
LakeSpring31.0°121.4°52.6×104
Summer126.9×103
Autumn15.2×103
Winter228.8×103
), ArticleFig(id=1238891103961797236, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1238813324108952201, language=CN, label=表1, caption=

各站位经纬度信息及混养藻类占比和总微藻丰度

, figureFileSmall=null, figureFileBig=null, tableContent=
HabitatStation/SeasonLatitude (N)Longitude (E)Mixo (%)Euks (cells/mL)
SCS-inshoreSCS-2821.7°113.1°22.6×104
SCS-4622.2°113.7°15.8×104
SCS-5122.7°113.7°12.2×105
Inshore-offshore transitSCS-3620.7°113.4°257.3×104
SCS-J118.0°110.0°171.0×103
SCS-offshoreSCS-J718.0°113.0°192.0×102
SCS-J1918.0°119.0°339.3×102
SCS-D4016.0°116.0°281.0×103
LakeSpring31.0°121.4°52.6×104
Summer126.9×103
Autumn15.2×103
Winter228.8×103
), ArticleFig(id=1238891104070849150, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1238813324108952201, language=EN, label=Table 2, caption=

Taxonomic composition of identified mixotrophic microalgae from seven investigated samples

, figureFileSmall=null, figureFileBig=null, tableContent=
ClassGenus (species No.)EnvironmentCell No.Mixotroph
CryptophyceaeCryptomonas (3)SCS-51, lake-autumn4Yes
MAST-3Uncultured (1)SCS-281Maybe
CercozoanUncultured (1)SCS-281Maybe
Uncultured (1)SCS-191Maybe
PelagophyceaeUncultured (1)SCS-191Maybe
ChrysophyceaeDinobryon (2)Lake-winter26Yes
Spiniferomonas (2)Lake-spring, winter3Yes
Spumella (1)Lake-autumn1No
Pedospumella (2)Lake-spring16No
Ochromonas (1)Lake-autumn1Yes
Paraphysomonas (1)Lake-spring6No
Uroglenopsis (2)Lake-spring3Yes
DinophyceaeWoloszynskia (1)Lake-autumn1Yes
PerkinseaPararosarium (1)Lake-winter10Maybe
Pedinella (2)Lake-spring3Yes
DictyochophyceaePseudopedinella (2)Lake-spring, autumn2Yes
Helicopedinella (1)Lake-spring2Yes
Kirchneriella (1)Lake-autumn1Maybe
Monoraphidium (1)Lake-autumn1Maybe
ChlorophyceaeChoricystis (1)Lake-spring1Maybe
Minidiscus (1)SCS-281No
TrebouxiophyceaeMediolabrus (1)SCS-282No
Nitzschia (2)Lake-autumn5No
BacillariophyceaeDiscostella (1)SCS-511No
Skeletonema (1)SCS-46, SCS-514No
Cyclotella (1)Lake-autumn3No
), ArticleFig(id=1238891104167318158, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1238813324108952201, language=CN, label=表2, caption=

七个环境样品中鉴定出的混养微藻的分类组成

, figureFileSmall=null, figureFileBig=null, tableContent=
ClassGenus (species No.)EnvironmentCell No.Mixotroph
CryptophyceaeCryptomonas (3)SCS-51, lake-autumn4Yes
MAST-3Uncultured (1)SCS-281Maybe
CercozoanUncultured (1)SCS-281Maybe
Uncultured (1)SCS-191Maybe
PelagophyceaeUncultured (1)SCS-191Maybe
ChrysophyceaeDinobryon (2)Lake-winter26Yes
Spiniferomonas (2)Lake-spring, winter3Yes
Spumella (1)Lake-autumn1No
Pedospumella (2)Lake-spring16No
Ochromonas (1)Lake-autumn1Yes
Paraphysomonas (1)Lake-spring6No
Uroglenopsis (2)Lake-spring3Yes
DinophyceaeWoloszynskia (1)Lake-autumn1Yes
PerkinseaPararosarium (1)Lake-winter10Maybe
Pedinella (2)Lake-spring3Yes
DictyochophyceaePseudopedinella (2)Lake-spring, autumn2Yes
Helicopedinella (1)Lake-spring2Yes
Kirchneriella (1)Lake-autumn1Maybe
Monoraphidium (1)Lake-autumn1Maybe
ChlorophyceaeChoricystis (1)Lake-spring1Maybe
Minidiscus (1)SCS-281No
TrebouxiophyceaeMediolabrus (1)SCS-282No
Nitzschia (2)Lake-autumn5No
BacillariophyceaeDiscostella (1)SCS-511No
Skeletonema (1)SCS-46, SCS-514No
Cyclotella (1)Lake-autumn3No
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荧光激活单细胞分选技术在微藻功能类群研究中的应用
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王莹 1 , 李倩 1 , 许杰 2 , 孙伟 2 , 蒋海霞 2, *
微生物学报 | 技术与方法 2026,66(3): 1412-1425
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微生物学报 | 技术与方法 2026, 66(3): 1412-1425
荧光激活单细胞分选技术在微藻功能类群研究中的应用
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王莹1, 李倩1, 许杰2, 孙伟2, 蒋海霞2, *
作者信息
  • 1.上海交通大学 海洋学院,上海
  • 2.上海交通大学 生命科学技术学院,仪器共享与技术服务平台,上海
Application of fluorescence-activated cell sorting in the study of functional groups of microalgae
Ying WANG1, Qian LI1, Jie XU2, Wei SUN2, Haixia JIANG2, *
Affiliations
  • 1.School of Oceanography, Shanghai Jiao Tong University, Shanghai, China
  • 2.Core Facility and Technical Service Center, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
出版时间: 2026-03-04 doi: 10.13343/j.cnki.wsxb.20250586
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目的 兼具光合与摄食功能的混合营养策略在单细胞真核微藻中广泛存在,其在食物网能量流动以及元素生物地球化学循环中发挥着重要作用。研究自然水体中混养微藻的种类构成存在技术难题,因此提升现有手段以准确揭示其多样性是该领域亟待解决的科学问题。 方法 通过添加荧光猎物标记物并开展摄食实验,追踪群落中的摄食型微藻;利用荧光激活流式细胞分选技术在单细胞水平上捕捉目标生物,结合基因组扩增与18S rRNA基因鉴定其物种,最终建立了一种单细胞分选与基因组扩增相结合的FACS-MDA联用方法。 结果 利用该方法检测了来自我国淡水与海水环境中多个样品的混养微藻,获取了隶属于6纲12属的20个摄食型微藻物种,以及1纲3属的异养摄食者,证实了该方法的有效性。 结论 本研究将FACS-MDA联用技术应用于天然水体微藻功能群鉴定,所建立的荧光激活分选和单细胞测序技术在微生物生态学领域具有广泛的应用前景,有助于加深对环境微藻功能类群及其原位摄食活动的认知。

荧光激活分选  /  单细胞  /  全基因组扩增  /  混合营养  /  微藻

Objective Mixotrophy that combines phototrophic autotrophy and phagotrophic heterotrophy is widespread among unicellular eukaryotic microalgae and plays a key ecological role in energy flow within food webs and in elemental biogeochemical cycles. However, identifying and characterizing mixotrophic microalgae in natural waters remains technically challenging. Improving current approaches to accurately reveal the diversity of mixotrophic microalgae is an urgent task in this field. Methods Fluorescently labeled prey surrogates and feeding experiments were employed to trace phagotrophic microalgae within plankton communities. Target organisms were captured at the single-cell level through fluorescence-activated cell sorting (FACS), followed by multiple-displacement amplification (MDA) and 18S rRNA gene sequencing for taxonomic identification. On the basis of this FACS-MDA workflow, we established a methodological framework for studying the functional groups of microalgae. Results Applying this approach to multiple freshwater and seawater samples from China, we identified twenty phagotrophic microalgal species belonging to six classes and twelve genera, as well as heterotrophic consumers representing one class and three genera, demonstrating the robustness and broad applicability of this method. Conclusion This study applies the combined FACS-MDA technology to the identification of functional groups of microalgae in natural water bodies. The established technology has broad application prospects in microbial ecology. It enables deeper insights into the functional diversity and in situ feeding activities of environmental microalgae.

fluorescence-activated cell sorting (FACS)  /  single cell  /  whole genome amplification  /  mixotrophy  /  microalgae
王莹, 李倩, 许杰, 孙伟, 蒋海霞. 荧光激活单细胞分选技术在微藻功能类群研究中的应用. 微生物学报, 2026 , 66 (3) : 1412 -1425 . DOI: 10.13343/j.cnki.wsxb.20250586
Ying WANG, Qian LI, Jie XU, Wei SUN, Haixia JIANG. Application of fluorescence-activated cell sorting in the study of functional groups of microalgae[J]. Acta Microbiologica Sinica, 2026 , 66 (3) : 1412 -1425 . DOI: 10.13343/j.cnki.wsxb.20250586
随着浮游微生物生态学研究的深入,人们发现兼具光合与摄食功能的混合营养代谢策略广泛存在于微型浮游生物中,涵盖各大常见的真核微藻门类[1-4]。其中,自养过程特指光合固碳作用,异养过程则主要通过吸收溶解有机物或吞噬颗粒态有机物(即猎物)来实现。后者这种同时具备光合自养和吞噬异养能力的摄食型微藻是本研究的关注对象[5],以下简称为“混养藻类”。通过摄食富含氮磷元素的细菌,混合营养可以有效缓解藻类的营养盐限制。来自猎物的额外资源能够进一步刺激混养藻类的光合作用与碳固定,这种正反馈使得混合营养类群与非混合营养类群相比可能更具竞争优势[6-7]。此外,混合营养能够“缩短”食物链长度,增加底层食物网能量向高营养级的传输,提升下沉有机碎屑的产量以及生物泵储碳效率。相较于传统的“浮游植物-浮游动物”二分法,将混合营养纳入食物网模型后,全球海洋颗粒有机碳的输出通量提高了30%[8],具有显著的生态学及环境学意义。
调查不同环境中混养藻类的物种多样性和群落结构是研究混合营养生理生态学的基础。除硅藻尚未被证实存在摄食功能且被认为其硅质外壳不具备吞噬能力外[5],混合营养模式已在甲藻、定鞭藻、硅鞭藻、绿藻、金藻、隐藻等真核藻类谱系中得到广泛证实[3,9-13]。目前,对混养微藻种类的鉴定大多基于纯培养,通过分离微藻株系,在实验室内通过培养实验证实其营养模式与吞噬功能。然而该方法容易受到技术瓶颈限制,因为能够被纯培养的藻类物种有限。为了进一步阐明“谁在行使混合营养”这一问题,需要在群落水平上对其进行整体研究。可通过荧光食物标记和显微镜观察对摄食型微藻进行定性与定量研究,但该技术在某些情况下难以判断猎物与细胞膜的确切位置,尤其是对于体积较小的微藻类群[14]。激光共聚焦三维成像系统能够在一定程度上解决这个问题[11]。催化沉积荧光原位杂交技术(CARD-FISH)利用引物杂交特异性,能够在较高分类水平上识别摄食者类群,但仍存在一些限制性问题:例如该方法通常依赖荧光信号进行人为判读,存在一定的主观性误差[15];此外,实验结果还可能受到探针覆盖率和杂交效率的影响,一些丰度较低的类群也可能存在检测困难等难题[16-17]。目前,酸性食物泡探针技术也已被应用于区分混养藻类的研究中[18-20],但依旧存在囊腔结构等非特异性染色导致错误分选的风险[14]
相比上述方法,流式细胞术在分辨率和通量上具有显著优势。首先,依据散射光及多种荧光信号能够准确识别藻类的大小、内部结构和特征色素等,包括粒径较小的皮微型真核藻类。其次,流式细胞术具有极高的通量,每秒可检测成千上万个颗粒,能够在较短时间内获得足够的数据,提高样本覆盖范围和统计稳健性[21-22]。荧光激活细胞分选技术则能够直接捕获目标生物,进一步结合基因组测序技术,能够在单细胞水平上识别鉴定其物种,实现对天然水体中混养藻类最高分类水平的多样性调查[23]
该研究的目的在于开发一种基于流式细胞分选技术的环境微生物鉴定识别方法。结合上游培养实验对目标生物进行荧光标注,下游则通过多重置换扩增对分选的单细胞基因组进行富集,最终结合18S rRNA标记基因测序对物种进行逐一鉴定,进而回答“谁在哪里”和“行使什么功能”这两大生态系统层面的问题。本研究旨在将荧光激活细胞分选技术应用于我国典型水生生境的混合营养型微藻调查,以期为进一步深化对微藻生态功能的理解提供方法学支持。
本研究的12个样品分别采集自我国南海北部沿岸(20.7-22.7°N, 113-113.7°E)、中部海盆/外海(16-18°N, 110-119°E),以及地处上海市的一处内陆浅水湖(31.0°N, 121.4°E)。南海样品通过搭载国家自然科学基金委员会2023年与2024年夏季南海共享航次进行采集,具体包括南海沿岸(SCS-inshore)的SCS-28、SCS-46、SCS-51站位,外海海域(SCS-offshore)的SCS-J7、SCS-D40、SCS-J19站位,以及沿岸至外海过渡区(inshore-offshore transit)的SCS-36、SCS-J1站位。对于淡水湖,开展了4次季节性水样采集,包括2023年春季、冬季以及2024年的夏季和秋季。所有水样均采自表层,其中湖水样品水深约1 m,南海北部与中部海域样品分别为CTD收集的2 m和5 m层海水。需要指出的是,由于分选样品对保存时效性要求较高,上述12个样品中共有7个样品进行了分选处理,剩余5个样品仅有丰度占比分析数据(详见结果部分)。
对于南海样品,同时记录CTD传感器收集的温盐深等基础物理参数;湖水的温度和光强等参数使用多参数水质测量仪(Xylem公司)检测获得。原位水样经20 μm筛网预过滤后,添加0.5% (终浓度)电镜级戊二醛(Macklin公司)固定保存,在陆地上冻融后通过分析型流式细胞仪检测原位微生物群落。利用高红色荧光信号(叶绿素特征荧光)和前向/侧向散射光(代表细胞大小)计数微藻丰度。
在陆地或船载实验室内将20 μm尼龙筛网预过滤的海水分装至500 mL PC瓶中,添加终浓度约2×105 particles/mL的1.0 μm荧光微球(Sigma-Aldrich公司),模拟原位环境开始摄食培养实验。依据前期的研究结果,该1.0 μm荧光微球作为猎物替代物,相较于常用的荧光标记灭活细菌(fluorescently labeled bacteria, FLB)[24]和0.5 μm微球不存在显著的摄食偏好,且经由流式细胞仪检验效果更佳[25]。有关温度和光强条件,南海样品在20-28 ℃和5 400 lx,湖水在14-18 ℃和3 780 lx条件下培养2-12 h,直至观察到充足的摄食证据(方法描述见1.3节)。为减少荧光微球与藻细胞之间的黏附作用,向培养样品添加终浓度0.01%的Pluronic F68表面活性剂(ThermoFisher Scientific公司)。实验结束后,湖水样品立即经由流式细胞仪进行检验与分选,南海样品则通过终浓度2%的甜菜碱(betaine,99%纯度级别,ThermoFisher Scientific公司)于-80 ℃冷冻保存[26],返回陆地后解冻,上机检验并分选。此外,取20 mL培养样品加入终浓度0.5%的电镜级戊二醛固定,经终浓度0.1 μg/mL的DAPI染色后(Sigma-Aldrich公司)过滤至孔径2.0 μm的聚碳酸酯滤膜,-20 ℃冷冻保存直至镜检。
样品上机分选之前,将冷存碳酸脂膜通过荧光显微镜进行观察以获取摄食证据,镜检方法详见文献[25]。简单来讲,叶绿体、荧光微球和细胞核分别采用蓝、绿和紫外光进行激发识别。利用长带宽滤光片或者双通路叠加同时收集叶绿体和荧光微球信号,同时具备叶绿体和荧光微球的细胞被视为摄食型混合营养微藻。通过细胞大小、形状以及叶绿体的个数和形态对部分微藻进行形态学分类,如含橙黄光藻胆色素的隐藻、具有特殊外壳形状和易聚团的锥囊藻,以及含多个质体的硅鞭藻等。
取上述观察到摄食行为的样品,经分选型流式细胞仪(BD公司)进行检验分选。为确定合适的荧光信号分选阈值,挑取2株常见微藻:小定鞭金藻(Prymnesium parvum)和强壮前沟藻(Amphidinium carterae),取其藻液测定叶绿素荧光信号,分别为7×102-2×104 a.u.和2×102-1×105 a.u. (图1A1B1D1E),其绿色荧光信号均低于1×102 a.u.。相比之下,微球的绿色荧光数值均大于1×103 a.u.,叶绿素信号均小于2×102 a.u. (图1C1F)。结合藻类与微球对照组检测结果判断叶绿素荧光与绿色荧光阴性区域基线分别为2×102 a.u.和1×102 a.u.,高于上述基线的荧光信号被界定为双阳性事件,即摄食了微球的混养微藻。
为了检验细胞与微球粘连造成的假阳性事件占比,以及进一步确认目标生物分选事件的准确性,开展了基于微藻纯体系的摄食时间序列实验。通过追踪活跃摄食者在对照组(健康藻细胞)与处理组(无摄食能力藻细胞)之间的差异,以及摄食类群占比随时间变化的趋势,确认培养初始T0时存在很低的细胞粘连事件(占比2%-3%),对照组中的双阳性摄食事件在40 min内增加了6倍。相比之下,处理组中的双阳性事件在40 min内下降了50%。尽管存在一定比例的黏附事件,但在数小时培养实验结束后该事件相比摄食事件占比较低(<20%),该结果进一步验证了本研究双阳性区域划分的科学性。
对于环境样品中微藻的辨识,依据不同站位微藻群落差异作出适当调整,将高于1×102-1×103 a.u.的群体划分为微藻。依据约1×103 a.u.的微球荧光通道阈值确认猎物阳性信号。进一步结合叶绿素和猎物双阳性信号识别具备摄食功能的微藻,即混合营养型微藻(叶绿素荧光>1×102 a.u.,绿色荧光>1×103 a.u.)。基于来自纯培养藻株和环境样品(共14个样品)的检验结果,分选型流式细胞仪的信噪比区间约1%-33%。对目标类群进行单细胞分选,分选时在双阳性区域内随机选定目标细胞,以最低流速10 μL/min经鞘液分选单一细胞至已添加1 μL PBS缓冲液的无菌PCR管中。单细胞样本分选完成后立即密封PCR管,保存于-80 ℃超低温冰箱待后续分析。
将分选后的细胞解冻,使用REPLI-g Single Cell Kit (Qiagen公司)的DLB缓冲液进行裂解变性,并开展等温基因组扩增反应。该试剂盒采用REPLI-g sc Polymerase,通过多重置换扩增(multiple-displacement amplification, MDA)技术实现单细胞全基因组扩增,可确保全基因组范围内实现高度均匀扩增。尽管该技术主要应用于哺乳动物细胞和细菌,但已有少数研究成功将其用于海洋原生生物(Chen等[27];Wilken等[14];Florenza等[28])。多重置换扩增反应需严格遵循产品说明书操作:首先将裂解与变性反应体系(含3 μL预配裂解缓冲液)于65 ℃孵育10 min,随后加入3 μL终止液停止反应。变性后的DNA样品与29 μL Repli-g sc反应缓冲液、9 μL超纯水和2 μL REPLI-g sc Polymerase混合,30 ℃孵育8 h,最后在65 ℃加热5 min终止反应。将扩增后的基因组DNA (gDNA)稀释100倍,作为下游PCR扩增模板。采用TaqMan聚合酶PCR系统(Mei5bio)和真核生物近全长18S rRNA基因引物Euk63F (5′-ACGCTTGTCT CAAAGATTA-3′)和Euk1818R (5′-ACGGAAAC CTTGTTACGA-3′)进行PCR扩增。PCR反应体系(25 μL):2×Phanta Max Mix 12.5 μL,上、下游引物(10 μmol/L)各1 μL,DNA模板0.5 μL,ddH2O 10 μL。PCR反应条件:94 ℃预变性10 min;94 ℃变性1 min,55 ℃退火45 s,72 ℃延伸30 s,共30个循环;72 ℃终延伸5 min。扩增产物经纯化后,使用正向引物Euk63F进行Sanger测序,获得840-900 bp的基因序列。所得序列通过NCBI BLAST数据库(https://blast.ncbi.nlm.nih.gov)进行同源性比对分析,采用默认参数与Genbank数据库参考序列进行同源性比对,最终选取最高匹配度(序列相似性≥98%,E-value≤1×10-50)的比对结果作为物种鉴定依据。本研究获得的18S rRNA基因序列已存入NCBI数据库,登录号为PV348919-PV348940。
对比各个采样环境中的微藻群落丰度,南海北部沿岸站位(SCS-inshore)的整体丰度最高,最低值为SCS-28站位的2.6×104 cells/mL,最高值为SCS-51站位的2.2×105 cells/mL (表1)。中部海盆(SCS-offshore)的微藻丰度数值明显下降,仅为(0.2-1.0)×103 cells/mL。相比之下,淡水湖的微藻丰度介于南海北部沿岸与中部海盆的数值之间,且呈现出季节间差异,春季最高,为2.6×104 cells/mL;秋季最低,为5.2×103 cells/mL;冬季与夏季介于两者之间,为(6.9-8.8)×103 cells/mL。
基于微球和叶绿素双阳性信号成功检测到各站位活跃摄食的混养藻类(图2)。混养微藻活跃摄食者占比总微藻群落的1%-33%,在不同站位、海区与季节间呈现出差异。最高占比出现在位于南海中部海盆的SCS-J19站位,比例为33% (表1图2I);最低占比位于南海北部沿岸的SCS-46、SCS-28和SCS-51站位(表1、图2D-2F)。淡水湖3个季节样品中摄食微藻占比为1%-22%,其中冬季最高,为22% (表1图2C);秋季最低,为1% (表1);春季居中,为5% (表1图2B)。值得指出的是,该方法检测到的目标生物类群仅代表当下行使活跃摄食功能的藻类,潜在混养微藻数目可能更多。
本研究将来自湖泊(lake)、南海河口陆架区(SCS-inshore)、与海盆区(SCS-offshore) 3类环境中混养微藻占比的数据进行组间T检验。结果显示,南海河口-近岸与海盆站位之间的数值存在显著性差异(P<0.05),表明寡营养开阔海域的摄食藻类占比明显高于所调查的河口近岸站位(图2A)。这很大程度上可由光照和营养盐的资源格局来解释。由于南海海盆长期处于分层和贫营养状态,溶解无机氮、磷等营养盐普遍处于限制水平,此时混合营养微藻通过摄食细菌等获得再生养分与有机碳,从而导致整体微藻群落中摄食个体比例上升。相比之下,湖水冬季的高丰度摄食类群可能与光限制相关。上述模式与本研究此前基于实验操作和野外观测所得到的结论高度一致,即营养盐和光限制均能够刺激藻类的混合营养行为[10,25]
不同样品中整体微藻群落的叶绿素荧光信号值也存在差异,这与当地环境中的藻类类群和叶绿素含量相关。例如,南海寡营养海盆区(SCS-J19站位)的微藻不但丰度最低,叶绿素信号区间也偏低,位于102-104 a.u.之间,推测大多为粒径较小的皮微型真核藻类(图2I)。相比之下,南海北部沿岸富营养海域(如SCS-28和SCS-51站位) (图2E2F),微藻丰度与叶绿素荧光信号均显著升高,PerCP-Cy5.5介于103-106 a.u.之间,有可能被高叶绿素信号的硅藻主导(结合单细胞分选测序结果推断)。对淡水湖样品而言,微藻群落聚团形态与南海不同,尤其是冬季样品,可明显看到介于103-105 a.u.以及小于103 a.u.的高、低叶绿素信号区间类群(图2C)。
此外,活跃摄食微藻类群的荧光信号区间以及聚类形状也呈现区别。湖水冬季样品是聚团最明显、边界最清晰的样品,有可能被某一种主要的混养微藻类群主导(图2C)。站位SCS-J7、SCS-D40和SCS-J19摄食类群的聚团情况较为类似,存在单一与多个微球摄食数目之间的差异(依据FITC荧光信号识别) (图2G-2I)。南海北部沿岸的SCS-46站位摄食微藻呈现另外一种聚团结构,聚团类群的叶绿素荧光信号集中在105 a.u.左右(图2D)。因为不同藻类所含色素量不同,上述叶绿素荧光数值间的差异很有可能指示不同站位间的主导摄食型微藻类群也存在区别。
全部样品共获得175个单细胞,获得155个全基因组阳性事件(成功扩增出>15 kb基因组片段),其中104个细胞扩增得到18S rRNA基因阳性条带(图3A表2)。在104个真核生物中,72个属于水生环境中的摄食类群,其余为气溶胶生真菌污染。72个水生真核生物包括48个微藻和24个异养鞭毛虫。另有4个物种无法注释营养模式,它们是来自肉足虫纲(Cercozoa)、海金藻纲(Pelagophyceae)和不等定鞭门(Stramenopiles)的未培养物种,可能具备混合营养功能(表2)。剩余的18S rRNA基因序列中有10个物种均来自囊泡虫纲的Pararosarium属。据文献报道该物种可寄生在其他甲藻中进行繁殖,其是否具备吞噬能力未知,本研究将其界定为未知或可能。其余19个物种均来自硅藻,隶属6个不同的种属。依据文献报道硅藻被视为不具备吞噬能力,因此本研究将其归为非吞噬型混合营养物种(表2)。
该研究获得的自分选至18S rRNA基因扩增成功的数目比为175:104,即真核生物的分选与扩增效率为59%。其中,水生真核生物和混养微藻与总的18S rRNA基因阳性事件的占比分别为72:104 (69%)和48:104 (46%)。此外,对比结果显示,混养微藻的分选效率与占比随站位和季节呈现显著差异,可能受到群落结构及不同条件下原位摄食活动的影响。具体而言,湖水春季的分选效率最高,为73%;冬季次之,为52%。相比之下,南海北部沿岸样品中混养微藻占比最低,其中硅藻贡献了全部分选物种的75% (表2)。
对成功分选的48个混养微藻进行系统发育分析,依据与已知同源物种序列比对结果,这些混养微藻隶属于6大纲的12个微藻属,在98%相似度操作分类单元(operational taxonomic unit, OTU)水平上归为20个OTUs物种(表2)。上述混养微藻大多来自淡水湖样品。来自南海的3个未知物种,尤其是能够归类至肉足虫纲和海金藻纲的物种,有较高可能性是混养微藻,因为这两大门类均被证实具有吞噬型混合营养的能力。若纳入这些潜在的混养微藻,本研究共获得来自9纲15个属的混合营养型藻类。在所有混养微藻类群中金藻纲为主导类群,占分选类群总数的69%;其次为硅鞭藻纲(Dictyochophyceae),占比15%。其余4个纲包括隐藻纲(Cryptophyceae)、绿藻纲(Chlorophyceae)、共球藻纲(Trebouxiophyceae)和甲藻纲(Dinophyceae),各自占比2%-6%。全部湖水样品中的异养物种均来自金藻纲(Chrysophyceae),涵盖PedospumellaSpumellaParaphysomonas 3大属。来自南海SCS-28站位的异养真核生物隶属海洋中常见的异养鞭毛虫类群MAST-3,目前仅有少数物种被分离培养(表2)。
在属或目级水平上,混养微藻的优势类群为金藻纲的锥囊藻属(Dinobryon)和硅鞭藻纲的柄钟藻目(Pedinellales),分别占总混养微藻类群的55%和15%。其余属的相对占比较低(2%-6%),包括金藻纲的SpiniferomonasUroglenopsisOchromonas,绿藻纲的MonoraphidiumKirchneriella,共球藻纲的Choricystis,隐藻纲的Cryptomonas,以及甲藻纲的Woloszynskia。基于独特的形态学和叶绿体特征,某些种属能够通过显微镜观察获得其摄食证据,例如锥囊藻属(Dinobryon)的原生质体被包裹在圆筒至漏斗形的外壳中,并具有眼点;柄钟藻目(Pedinellales)细胞周缘分布着3-6个叶绿体;隐藻属(Cryptomonas)具有六边形的周质板,并呈现由藻胆素发出的橙色荧光。上述3种混养微藻类群均在显微镜样品中普遍存在(图3B)。
值得指出的是,利用显微镜观察对比了湖水微藻群落对不同猎物潜在的摄食偏好,猎物包括含1.0 μm微球、0.5 μm微球和天然细菌聚球藻。本研究统计了超过1 000个藻细胞的摄食情况,包括摄食猎物种类和数量,发现锥囊藻属对0.5 μm微球有显著的摄食偏好性,绿藻和其他微藻对聚球藻有一定的摄食偏好,但无显著性差异。全部混养微藻均能够吞噬1.0 μm微球,验证了该猎物替代品方法的有效性。综上所述,针对冬季湖泊样品中观察到的大量摄食型金藻(锥囊藻),并非由于微球摄食偏好导致误差。相反,1.0 μm微球可能在一定程度上低估了该类群的摄食占比。
本研究将荧光激活细胞分选(FACS)和多重置换基因组扩增(MDA)与测序相结合,即采用FACS-MDA联用技术建立了一种在单细胞水平识别原位微藻功能类群的技术路径。基于该综合研究手段,获取了淡水与海水环境中的摄食型混养微藻,并能在单细胞水平上对其进行物种注释。最终获得了隶属于6个纲和12个属的混合营养型微藻类群,以及3个未培养的潜在混养微藻物种。此外,分选样品中还扩增出来自金藻和MAST-3类群的异养摄食类群。在155个分选阳性事件中最终有104个真核生物得以扩增,其中含46%藻类摄食者、3%潜在藻类摄食者以及23%异养摄食者,淡水与海水环境中的目标生物类群结构存在明显差异。上述结果验证了该方法在靶向分选微藻功能类群和真核生物摄食者方面的可行性与代表性。
本研究结果显示,利用该方法对湖泊环境中混养微藻的整体分选效率约50%,这一结果与Florenza等[28]的研究基本一致。具体而言,Florenza等[28]在温带寡营养型湖泊采用类似方法,在1 837个单细胞分选事件中有943个为摄食型混养微藻。Florenza等获得的混养微藻优势类群为硅鞭藻和金藻[28],也基本与本研究湖水样本的结果吻合。FACS-MDA联用技术在水生真核生物类群鉴定中的应用还十分有限,本研究将该技术拓展应用至我国富营养淡水湖和南海海域,证实了荧光激活分选技术在获取微藻目标生物方面具有普适性。与此同时,本研究的FACS-MDA联用路线与Florenza等[28]存在一定差别。在猎物标记方面,Florenza等[28]采用酸性食物泡荧光染料对藻细胞进行直接染色鉴定,显色即为吞噬型混合营养物种。相比之下,本研究选取表面羧酸盐修饰的荧光微球能够避免食物泡潜在的非特异性染色[14]并有效还原荧光标记信号。基于荧光微球标记,能够直接鉴定原位环境中正在活跃摄食的类群,排除了潜在的摄食者(食物泡存在但未摄食),分选结果能更真实地反映生态系统中的摄食活动。
值得指出的是,FACS-MDA联用技术在揭示自然水体群落多样性方面存在一定的局限性,在微藻功能类群筛选应用中仍面临若干挑战。以该研究为例,从175个分选事件到155个基因组阳性事件,可能由分选失败或全基因组扩增失败导致。分选失败可从仪器技术方面进行改进,例如提升信噪比和物理捕获能力等;基因组扩增失败可从改善单细胞裂解和扩增体系等方面来解决。从155个基因组阳性事件到104个18S rRNA基因扩增,可能由基因扩增失败导致,可从改善扩增条件和引物通用性等方面来解决。104个18S rRNA基因中有74个来自水生真核生物,其余47%的事件均来自外源真菌污染,可通过更加彻底的无菌环境操作来避免污染。74个水生真核生物最终获得48-52个(含未知物种)混养微藻、23个异养摄食者、10个寄生型囊泡虫以及19个硅藻,目标生物占比65%-70%。其中,异养真核生物落入叶绿素阳性区间可能是因为这些鞭毛虫吞噬了含色素的藻类。已有研究表明硅藻细胞表面常伴随细菌或其他真核微生物的附着或共生[29-31],因此检测到的信号并不一定代表胞内吞噬。Flynn等[5]作为混合营养生态学专家认为,硅藻很有可能是唯一不具备吞噬功能的藻类,原因是其特殊的硅质细胞膜外壳和弱游动力代表进化过程中摄食能力的丢失。对于寄生性囊泡虫,现有文献中尚无直接证据支持其具备混合营养功能,但考虑到部分寄生型原生生物与宿主存在复杂的营养物质界面交换,本研究也无法完全排除这种可能性,需要进一步开展实验来明确这些结果。
使用任何一种猎物替代物都可能对分选结果造成潜在影响。尽管荧光微球长期被视为追踪微型浮游生物摄食行为的有效示踪工具,但作为猎物替代物,它们在揭示混养微藻真实摄食偏好与策略方面仍存在一定局限。首先,微球缺乏天然猎物的营养成分、表面化学特征与可识别分子信号,这可能导致某些类群的摄食反应被低估或高估[32]。其次,微球的尺寸、密度与表面特性通常较为单一,难以全面覆盖自然界中细菌与微型颗粒的异质性,使得实验条件下的摄食行为与自然环境中的粒径谱并不完全一致。因此未来研究建议结合多种类型的示踪工具与探针,例如不同粒径与材质的荧光微球、荧光标记细菌甚至是基于代谢或组学信号的猎物追踪方法,进而更可靠地解析混养微藻在自然环境中的营养获取与生态角色。
综上所述,荧光激活单细胞分选技术在微藻功能类群识别中展现出较高的定向性与通量优势,适用于从复杂原位群落中快速富集目标生物,并结合下游分子手段获取准确的物种信息。未来研究应联合摄食实验获得分物种的摄食速率并进行摄食碳通量估算,以加深对理解混合营养型微藻在细菌消耗以及碳循环中生态功能的理解。最后,为进一步提升FACS-MDA联用方法的应用效能,仍需在分选效率优化、扩增方法与条件摸索、污染控制和类群识别标准化等方面加强工作,以提高对目标功能类群的准确捕获与识别能力。未来可结合多组学分析、AI影像识别以及实时FACS成像等交叉手段和技术,全方位提升其在微生物生态学中的应用前景。
本研究构建并优化了一种基于荧光激活单细胞分选与基因组扩增的技术流程,用以识别鉴定浮游微生物的特定功能类群。这也是首次在国内将FACS-MDA联用技术应用于天然水体微藻功能群鉴定的研究。该方法在检测识别原位环境中混合营养型微藻的研究领域展现出较高的适用性,为研究微藻的摄食策略、多样性组成及其生态功能方面提供了一项可靠工具。尽管面临非特异性分选及单细胞基因组扩增等瓶颈,该技术在天然水体中应用的可操作性与通用性已得到验证。未来通过优化分选参数、提升基因扩增效率和降低污染等操作,有望进一步拓宽其在环境微生物生态学中的应用边界,特别是在特异功能类群识别与摄食功能追踪方面的研究。
  • 国家自然科学基金(42476120)
  • 国家自然科学基金(42106097)
  • 中国科技部海洋负排放国际大科学计划
  • 上海交通大学决策咨询课题(JCZXSJB2025-27)
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2026年第66卷第3期
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doi: 10.13343/j.cnki.wsxb.20250586
  • 接收时间:2025-07-29
  • 首发时间:2026-03-12
  • 出版时间:2026-03-04
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  • 收稿日期:2025-07-29
  • 录用日期:2025-12-10
基金
National Natural Science Foundation of China(42476120)
国家自然科学基金(42476120)
National Natural Science Foundation of China(42106097)
国家自然科学基金(42106097)
Ministry of Science and Technology (MOST) ONCE Project
中国科技部海洋负排放国际大科学计划
Decision-making Consultation Project of Shanghai Jiao Tong University(JCZXSJB2025-27)
上海交通大学决策咨询课题(JCZXSJB2025-27)
作者信息
    1.上海交通大学 海洋学院,上海
    2.上海交通大学 生命科学技术学院,仪器共享与技术服务平台,上海

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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