No evidence of Phago‐mixotropy in <i>Micromonas</i><i>polaris</i> (Mamiellophyceae), the Dominant Picophytoplankton Species in the Arctic

Jiménez, Valeria; Burns, John A.; Gall, Florence Le; Not, Fabrice; Vaulot, Daniel

doi:10.1111/jpy.13125

Cited by 20 publications

(25 citation statements)

References 80 publications

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“…The contrasting claims are reconcilable when considering that the prediction score of 0.43 attained for this alga, abutting the phago-mixotroph threshold, is likely due to incompleteness of the transcriptome data. Indeed, previous predictions of an earlier annotation of this same MMTESP Mantoniella antarctica transcriptome provided a phagotroph score of 0.09 [45], emphasizing the sensitivity of the model to annotation methods. More experimental and sequencing efforts are needed to clarify these issues.…”

Section: Discussionmentioning

confidence: 71%

“…Our predictions showed phago-mixotrophic potential for some members, including D. tenuilepis and Crustomastix stigmatica, the former of which was also experimentally confirmed to ingest bacteria. However, whether or not other members like Micromonas CCMP2099 are capable of consuming bacteria remains debated [14,45] and needs to be further investigated. In addition, the limited detection of prasinophyte bacterivory in situ may be attributable to the association of feeding with particular environmental conditions, even for a bacterivorous class, such as the Pyramimonadophyceae for which reports of bacterivory are more frequent from polar systems [13,63].…”

Section: Discussionmentioning

confidence: 99%

“…Regarding green algae, the tool used three chlorophycean green algal genomes during training, scoring as photo-autotrophs, Chlamydomonas reinhardtii, Chlorella variabilis, and Volvox carteri, as well as one prasinophyte, Cymbomonas tetramitiformis, scoring as a phago-mixotroph. The prediction outputs were visualized by mapping four dimensions with three degrees of freedom (phagocytosis, photosynthesis, prototrophy, and a fourth dependent dimension for absence of each trophic mode) into color space using scripts modified from the R package "pavo" [44] and projecting the 4D data onto a 2D circular Mollweide projection as described in Jimenez et al [45].…”

Section: Predictions Of Phago-mixotrophy Using a Genebased Modelmentioning

confidence: 99%

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Experimental identification and in silico prediction of bacterivory in green algae

et al. 2021

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While algal phago-mixotrophs play a major role in aquatic microbial food webs, their diversity remains poorly understood. Recent studies have indicated several species of prasinophytes, early diverging green algae, to be able to consume bacteria for nutrition. To further explore the occurrence of phago-mixotrophy in green algae, we conducted feeding experiments with live fluorescently labeled bacteria stained with CellTracker Green CMFDA, heat-killed bacteria stained with 5-(4,6-dichlorotriazin-2-yl) aminofluorescein (DTAF), and magnetic beads. Feeding was detected via microscopy and/or flow cytometry in five strains of prasinophytes when provided with live bacteria: Pterosperma cristatum NIES626, Pyramimonas parkeae CCMP726, Pyramimonas parkeae NIES254, Nephroselmis pyriformis RCC618, and Dolichomastix tenuilepis CCMP3274. No feeding was detected when heat-killed bacteria or magnetic beads were provided, suggesting a strong preference for live prey in the strains tested. In parallel to experimental assays, green algal bacterivory was investigated using a gene-based prediction model. The predictions agreed with the experimental results and suggested bacterivory potential in additional green algae. Our observations underline the likelihood of widespread occurrence of phago-mixotrophy among green algae, while additionally highlighting potential biases introduced when using prey proxy to evaluate bacterial ingestion by algal cells.

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Section: Discussionmentioning

confidence: 71%

Section: Discussionmentioning

confidence: 99%

Section: Predictions Of Phago-mixotrophy Using a Genebased Modelmentioning

confidence: 99%

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Experimental identification and in silico prediction of bacterivory in green algae

et al. 2021

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“…ML approaches have been recently shown to be capable of accurate functional prediction and cell type annotation using genetic input, in particular for cancer cell prediction (Shipp et al, 2002; Bashiri et al, 2017; Tabl et al, 2019), and functional gene and phenotype prediction in plants (Mahood et al, 2020). Recently, these approaches have been applied to culture and environmental transcriptomic data to predict trophic mode using currently available trophy annotations (Lambert et al, 2021; Burns et al, 2018; Jimenez et al, 2021). Here, we apply an independent machine learning model to the eukaryotic TOPAZ MAGs to predict each organisms’ capacity for various metabolisms.…”

Section: Resultsmentioning

confidence: 99%

Eukaryotic genomes from a global metagenomic dataset illuminate trophic modes and biogeography of ocean plankton

Alexander

Krinos

et al. 2021

Preprint

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Molecular and genomic approaches that target mixed microbial communities (e.g., metagenomics or metatranscriptomics) provide insight into the ecological roles, evolutionary histories, and physiological capabilities of the microorganisms and the processes in the environment. Computational tools that harness large-scale sequence surveys have become a valuable resource for characterizing the genetic make-up of the bacterial and archaeal component of the marine microbiome. Yet, fewer studies have focused on the unicellular eukaryotic fraction of the community. Here, we developed the EukHeist automated computational pipeline, to retrieve eukaryotic and prokaryotic metagenome assembled genomes (MAGs). We applied EukHeist to the eukaryote-dominated large-size fraction data (0.8-2000 μm) from the Tara Oceans survey to recover both eukaryotic and prokaryotic MAGs, which we refer to as TOPAZ (Tara Oceans Particle-Associated MAGs). The TOPAZ MAGs consisted of more than 900 eukaryotic MAGs representing environmentally-relevant microbial and multicellular eukaryotes in addition to over 4,000 bacterial and archaeal MAGs. The bacterial and archaeal TOPAZ MAGs retrieved with EukHeist complement previous efforts by expanding the existing phylogenetic diversity through the increase in coverage of many likely particle- and host-associated taxa. We also demonstrate how the novel eukaryotic genomic content recovered from this study might be used to infer functional traits, such as trophic mode. By coupling MAGs and metatranscriptomic data, we explored ecologically-significant protistan groups, such as the Stramenopiles. A global survey of both eukaryotic and prokaryotic MAGs enabled the identification of ecological cohorts, driven by specific environmental factors, and putative host-microbe associations. Accessible and scalable computational tools, such as EukHeist, are likely to accelerate the identification of meaningful genetic signatures from large datasets, ultimately expanding the eukaryotic tree of life.

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“…However, the phagocytosis capacity of such small chlorophytes has long been debated. For instance, a recent study questioned the phagotrophic capability of the Arctic strain of Micromonas as there was no evidence from grazing experiments or in silico predictions (Jimenez et al 2021). Therefore, there is a critical need for more exploration of whether mixotrophy exists in green algae.…”

mentioning

confidence: 99%

Evidence for mixotrophy in pico‐chlorophytes from a new Picochlorum (Trebouxiophyceae) strain

Pang

Liu

2021

Journal of Phycology

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Mixotrophs are increasingly recognized for their wide distribution in aquatic ecosystems and significant contributions to biogeochemical cycling. Many taxa within the phyla Chrysophyta, Cryptophyta, and Haptophyta are capable of phago-mixotrophy, however, phagotrophy in the Chlorophyta remains controversial due to insufficient research and solid evidence. In this study, we identified a new strain, Picochlorum sp. GLMF1 (Trebouxiophyceae), using 18S rRNA gene analysis and morphological observations. It displayed multi-cell division through autosporulation (two-or four-cell daughters) and has two unequal flagella that have never been reported in the genus Picochlorum. By using multiple methods, including 3D bioimaging analysis, acidic food vacuolelike compartment staining, and prey reduction calculation, we discovered and confirmed bacterivory in Picochlorum, which provided strong evidence for phago-mixotrophy in this green alga. In addition, we found that Picochlorum sp. GLMF1 cannot grow under complete darkness or prey-depleted conditions, suggesting that both light and bacteria are indispensable for this strain, and its mixotrophic nutrition mode is obligate. Like other phagophototrophs, Picochlorum sp. GLMF1 is capable of regulating their growth and ingestion rates according to light intensity and inorganic nutrient concentration. The confirmation of mixotrophy in this Picochlorum strain advances our understanding of the trophic roles of green algae, as well as the photosynthetic picoeukaryotes, in marine microbial food webs.

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No evidence of Phago‐mixotropy in Micromonaspolaris (Mamiellophyceae), the Dominant Picophytoplankton Species in the Arctic

Cited by 20 publications

References 80 publications

Experimental identification and in silico prediction of bacterivory in green algae

Experimental identification and in silico prediction of bacterivory in green algae

Eukaryotic genomes from a global metagenomic dataset illuminate trophic modes and biogeography of ocean plankton

Evidence for mixotrophy in pico‐chlorophytes from a new Picochlorum (Trebouxiophyceae) strain

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