Single-cell transcriptomics of small microbial eukaryotes: limitations and potential

Hu, Sarah K.; Campbell, Victoria; Tatters, Avery O.; Heidelberg, Karla B.; Caron, David A.

doi:10.1038/ismej.2016.190

Cited by 28 publications

(48 citation statements)

References 12 publications

(15 reference statements)

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“…A bacterial cell in the sunlit and relatively nutrient rich seawater has on average 200-2000 mRNA molecules per cell 7 , and levels in subsurface microbes should be even lower given the extreme energy limitation 8 . In contrast, eukaryotic phytoplankton have relatively large genomes and a single cell can have up to 50,000 mRNA molecules 9 , and thus it would only take nucleic acids from small number of contaminating eukaryotic phytoplankton from seawater to swamp an entire metatranscriptome sequencing run on such low biomass samples.…”

Section: Main Textmentioning

confidence: 99%

Contesting the evidence for gene expression in lower oceanic crust

Orsi

2020

Preprint

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Li et al [Nature 579, 250-255 (2020)] report microbial gene expression in deep ocean 18 crust, from microbial communities that have concentrations as low as 100 cell per cubic cm. This 19would be incredible, since that would be the lowest biomass sample ever analyzed for gene 20 expression for a deep biosphere sample by several orders of magnitude. However, I have 21reanalyzed the data and show that the author's data are derived from contamination via seawater, 22

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Section: Main Textmentioning

confidence: 99%

Contesting the evidence for gene expression in lower oceanic crust

Orsi

2020

Preprint

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“…fraction of two or more cells encapsulated together), and (v) the possibility to obtain phenotypic information to further identify and select/filter cells ( figure 1c,d). Singlecell pipetting with microcapillary tubes, manually or using automated devices, is the simplest yet probably the most widely used approach to isolating single eukaryotic cells for diversity and ecological studies [14][15][16]36]. Albeit slow and tedious, accurate observation of cells under the microscope is sometimes essential to find the target cells in complex communities where only morphological information is available for cell identification.…”

Section: (B) Isolation Of Single Cellsmentioning

confidence: 99%

“…B 374: 20190098 (qPCR) [14,42]. However, the restrictive cell size ranges of these chips [40] can be a limiting factor for cells out of the size range [14] or for a mixture of cells of very different sizes. Other limitations of the C1 system are the low throughput (tens to hundreds of cells) and high cost.…”

Section: (B) Isolation Of Single Cellsmentioning

confidence: 99%

Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes

Sebé-Pedrós

2019

Phil. Trans. R. Soc. B

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Understanding the diversity and evolution of eukaryotic microorganisms remains one of the major challenges of modern biology. In recent years, we have advanced in the discovery and phylogenetic placement of new eukaryotic species and lineages, which in turn completely transformed our view on the eukaryotic tree of life. But we remain ignorant of the life cycles, physiology and cellular states of most of these microbial eukaryotes, as well as of their interactions with other organisms. Here, we discuss how high-throughput genome-wide gene expression analysis of eukaryotic single cells can shed light on protist biology. First, we review different single-cell transcriptomics methodologies with particular focus on microbial eukaryote applications. Then, we discuss single-cell gene expression analysis of protists in culture and what can be learnt from these approaches. Finally, we envision the application of single-cell transcriptomics to protist communities to interrogate not only community components, but also the gene expression signatures of distinct cellular and physiological states, as well as the transcriptional dynamics of interspecific interactions. Overall, we argue that single-cell transcriptomics can significantly contribute to our understanding of the biology of microbial eukaryotes. This article is part of a discussion meeting issue ‘Single cell ecology’.

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“…Most current methodologies are restricted to polyadenylated transcripts, losing information on small noncoding RNAs and some long noncoding RNAs ( 93 ). Transcript recovery rates can be low, even for deep sequencing ( 94 ), and the low RNA content in small microbes can further diminish recovery ( 95 ). The decision of whether to examine large numbers of cells at a low sequence depth or small numbers of cells at an increased depth depends very much on the motivation for the experiment ( 93 , 96 ), yet carefully designed experiments with these limitations in mind are still revealing.…”

Section: Transcriptomic Studies Of Malariamentioning

confidence: 99%

Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions

Lee

Georgiadou

Otto

et al. 2018

Microbiol Mol Biol Rev

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SUMMARYTranscriptomics, the analysis of genome-wide RNA expression, is a common approach to investigate host and pathogen processes in infectious diseases. Technical and bioinformatic advances have permitted increasingly thorough analyses of the association of RNA expression with fundamental biology, immunity, pathogenesis, diagnosis, and prognosis. Transcriptomic approaches can now be used to realize a previously unattainable goal, the simultaneous study of RNA expression in host and pathogen, in order to better understand their interactions. This exciting prospect is not without challenges, especially as focus moves from interactions in vitro under tightly controlled conditions to tissue- and systems-level interactions in animal models and natural and experimental infections in humans. Here we review the contribution of transcriptomic studies to the understanding of malaria, a parasitic disease which has exerted a major influence on human evolution and continues to cause a huge global burden of disease. We consider malaria a paradigm for the transcriptomic assessment of systemic host-pathogen interactions in humans, because much of the direct host-pathogen interaction occurs within the blood, a readily sampled compartment of the body. We illustrate lessons learned from transcriptomic studies of malaria and how these lessons may guide studies of host-pathogen interactions in other infectious diseases. We propose that the potential of transcriptomic studies to improve the understanding of malaria as a disease remains partly untapped because of limitations in study design rather than as a consequence of technological constraints. Further advances will require the integration of transcriptomic data with analytical approaches from other scientific disciplines, including epidemiology and mathematical modeling.

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Single-cell transcriptomics of small microbial eukaryotes: limitations and potential

Cited by 28 publications

References 12 publications

Contesting the evidence for gene expression in lower oceanic crust

Contesting the evidence for gene expression in lower oceanic crust

Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes

Transcriptomic Studies of Malaria: a Paradigm for Investigation of Systemic Host-Pathogen Interactions

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