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Single-cell transcriptomics is a key tool for unravelling metabolism and tissue diversity in model organisms. Its potential for elucidating the ecological roles of microeukaryotes, especially non-model ones, remains largely unexplored. This study employed the Smart-seq2 protocol on Ochromonas triangulata, a microeukaryote lacking a reference genome, showcasing how transcriptional states align with two distinct growth phases: a fast-growing phase and a slow-growing phase. Besides the two expected expression clusters, each corresponding to either growth phase, a third transcriptional state was identified across both growth phases. Metabolic mapping revealed a boost of photosynthetic activity in the fast growth over the slow growth stage, as well as downregulation trend in pathways associated with ribosome functioning, CO2 fixation, and carbohydrate catabolism characteristic of the third transcriptional state. In addition, carry-over rRNA reads recapitulated the taxonomic identity of the target while revealing distinct bacterial communities, in co-culture with the eukaryote, each associated with distinct transcriptional states. This study underscores single-cell transcriptomics as a powerful tool for characterizing metabolic states in microeukaryotes without a reference genome, offering insights into unknown physiological states and individual-level interactions with different bacterial taxa. This approach holds broad applicability to describe the ecological roles of environmental microeukaryotes, culture-free, and reference-free, surpassing alternative methods like metagenomics or metatranscriptomics.

Mixotrophic protists are capable of acting both as primary producers and primary consumers at the base of the aquatic food web, thus constituting key organisms in ecosystems where they are abundant. However, their identity, abundance, ecological dynamics, and biogeochemical impact in aquatic ecosystems remain understudied in comparison to classically demarcated autotrophs or heterotrophs. In this study, we make use of fluorescently labeled prey and fluorescence-activated cell sorting to taxonomically identify actively-feeding individual mixotrophic flagellates from lake water. Replicated experiments were carried out to assess the performance of three different fluorescently labeled prey types and a fluorescent dye targeting food vacuoles. In the experiments, water from an oligotrophic lake was exposed independently to each type of reporter and cells were individually sorted based on fluorescent signals for predation and chlorophyll a. A total of 927 individual single cells were successfully recovered, with all fluorescent reporters exhibiting high sensitivity for putative mixotrophic taxa: overall, 87% of the occurrences could be assigned to dictyochophytes, 9% to chrysophytes, and 3% to dinoflagellates. As a result, we were able to detect cryptic diversity within pedinellid algae and report a Prorocentrum-like freshwater occurrence. We argue that this procedure can be a valuable tool to uncover relevant and unexpected active mixotrophic species in a wider range of aquatic environments, and could easily be coupled to other techniques to describe the finer details of the trophic status of aquatic microbial communities.

ABSTRACT: Microeukaryote predation on bacteria is a fundamental phenomenon to understand energy and nutrient dynamics at the base of the aquatic food web. To date, the most prevalent way to estimate grazing rates is by using epifluorescence microscopy to enumerate ingestion events of fluorescently labelled tracers (FLTs) after short-term incubation experiments. However, this approach can be sensitive to the type of FLT, requires skillful preparation of the samples and is limited to small sample sizes. We tested the susceptibility of rate estimates to the choice of prey and made a side-by-side comparison between microscopy and flow cytometry when recording ingestion by a bacterivorous flagellate. Short-term uptake experiments were established using 5 types of FLTs differing in quality (living, dead or inert) and size (large or small), with <i>Ochromonas triangulata</i> as a model flagellate. The experiments showed that (1) each of the different prey types yielded different clearing rates, ranging from 0.5 to 3.6 nl cell^-1 h^-1, with the largest differences (3-fold or higher) between small prey (lower rates) and large prey (higher rates); (2) the cytometry estimate differed significantly from the microscopy estimate in 3 out of 4 experimental configurations; and (3) the precision of the cytometric analysis was greater, with >3-fold higher uncertainty associated with microscopy counting. Our results validate that flow cytometry provides a more precise bacterivory estimate, and that the choice of FLT influences the grazing rate estimate to a high extent regardless of the analytical method used.

Mixotrophy in aquatic protists is pivotal for our understanding of aquatic microbial food web dynamics. This thesis is centered around aquatic unicellular mixotrophs, and comprises three methodological approaches aimed to tackle mixotroph ecology at single-cell resolution: the identification of actively feeding mixotrophs in natural samples, the determination of specific interactions among mixotrophs and bacterial prey, and the profiling of two distinct mixotrophic populations based on the gene expression of their constitutive individuals.

First, we investigated the feasibility of cytometrically sorting actively feeding mixotrophs from a natural community. The approach was based on the use of fluorescently labelled feeding tracers (FLTs) in conjunction with chloroplast autofluorescence from the feeding cell to retrieve mixotrophic individuals for subsequent single cell characterization by sequencing of a taxonomic marker gene. The preference for different FLT types showed that for mixotrophs in culture, FLT size was the strongest factor influencing FLT-based capture. This approach was then used to identify actively feeding mixotrophs from a lake water sample. The method proved to be both highly selective and specific and allowed the identification of an active natural mixotrophic community of unexpected diversity.

Secondly, we explored the potential of adapting emulsion, paired-isolation and concatenation PCR (epicPCR) to uncover physical connections between individual unicellular eukaryotes and their associated bacterial cohort. The results from three proof-of-concept experiments, however, did not conform to the expectations and showcased several deficiencies that need to be addressed. Mainly, the frequency of recovered links showed that the protocol, as deployed in our experiments, was prone to yield spurious abundance-driven associations between the eukaryotes and bacteria, since the most abundant bacteria were the ones driving the strongest associations with our test predators. Nevertheless, we identify possible solutions and point to avenues for future development to overcome the current limitations.

Finally, the capability of full-transcript single-cell RNA sequencing was surveyed to provide a reliable transcriptomic landscape of a non-mammalian, non-model eukaryotic organism with no available reference genome. We could show that, while some of the detailed functional information might remain uncharacterized, the workflow provide sufficient raw data to resolve population structure based on expression profiles.

In summary, with varying degrees of success, these attempts to expose and study mixotrophic unicellular eukaryotes demonstrate that the time is ripe to explore the ecology of mixotrophs at single-cell level.

Interactions between unicellular eukaryotes and bacteria are difficult to characterize in the environment owing to their large number and inherently microscopic scale. Although particular co-occurrences can be recovered through targeted approaches, e.g. single-cell sequencing or fluorescence in situ hybridization, the vast majority of the interactions remain unseen. Here, we discuss Emulsion, Paired Isolation and Concatenation polymerase chain reaction (epicPCR) as a tool to uncover these interactions in very high throughput. Originally developed for taxonomy-to-function linkage in bacterial communities, epicPCR has the potential to recover the complete interaction network in a given environment at single-cell resolution. This approach relies on the encapsulation of protistan single cells in emulsion droplets that can subsequently be gelified into beads. In this way, encapsulated cells can be exposed to lysis reagents and further phylogenetic paired marker amplification. A bacterium that physically co-occurs with the eukaryote will be jointly trapped, and the amplification will generate a concatenated PCR product containing physically coupled taxonomic markers from both partners, creating a link. Further amplification and sequencing enable the construction of an association pattern with statistically verified physical co-occurrences. Here, we discuss the potential, challenges and limitations of epicPCR. We argue that the microscopic scale at which epicPCR operates, the high throughput it delivers and its exploratory nature make it an unparalleled approach to unravel associations between microbes directly from environmental samples.

This article is part of a discussion meeting issue 'Single cell ecology'.

Single-cell transcriptomics has rapidly become a standard tool for decoding cell identity, fate and interactions in mammalian model organisms. Adopting such techniques to uncover functional dynamics in aquatic single-celled organisms holds huge potential, but evidence of applicability to non-model, poorly understood microeukaryotes remains limited. In the present study, live Ochromonas triangulata cells from fast and slow growth phases were FACS-sorted based on food vacuole staining and chlorophyll fluorescence, and single-cell transcriptomic libraries were prepared following the Smart-seq2 protocol. In total, 744 transcriptomes were Illumina sequenced. Lacking a reference genome, transcriptomes were assembled de novo using Trinity and resulting transcripts were annotated by BLAST using the Swiss-Prot database. Following read mapping, differential gene expression was evaluated using DESeq2 and metabolic maps were generated based on pathways from the KEGG Orthology database. Clustering the read counts revealed the identity of the two expected transcriptional states corresponding to each growth phase as well as a third distinct cluster of cells present in both growth phases. This cryptic group showed extensive downregulation of genes in pathways associated with ribosome-functioning, CO₂ fixation and core carbohydrate catabolism such as glycolysis, β oxidation of fatty acids and tricarboxylic acid cycle. Nevertheless, the biological underpinnings of this population, which would have remained unnoticed in an integrated approach, could not be clarified. Additionally, the possibility of using carry-over rRNA reads for taxonomic annotation was tested, verifying the identity of 88% of the O. triangulata cells. In conclusion, we demonstrate the power of single cell transcriptomics for metabolic mapping of microeukaryotes for which reference resources might be limited and thereby highlight its potential as a tool to gain access to microeukaryote dynamics in natural communities.

Mixotrophic protists are capable of acting both as primary producers and primary consumers at the base of the aquatic food web, thus constituting key organisms in ecosystems where they are abundant. However, their identity, abundance, ecological dynamics and biogeochemical impact in aquatic ecosystems remain understudied in comparison to classically demarcated autotrophs or heterotrophs. In this study, we make use of fluorescently labelled prey surrogates and fluorescence-activated cell sorting to taxonomically identify actively-feeding individual mixotrophic flagellates from lake water. Replicated experiments were carried out to assess the performance of three different fluorescently labelled prey types and a fluorescent dye targeting food vacuoles. In the experiments, water from an oligotrophic lake was exposed independently to each type of reporter and cells were individually sorted based on fluorescent signals for predation and chlorophyll a. A total of 927 individual single cells were successfully recovered, with all fluorescent reporters exhibiting high sensitivity for putative mixotrophic taxa: overall, 87% of the occurrences could be assigned to dictyochophytes, 9% to chrysophytes and 3% to dinoflagellates. As a result, we were able to detect cryptic diversity within pedinellid algae and report a Prorocentrum-like freshwater occurrence. We argue that this procedure can be a valuable tool to uncover relevant and unexpected active mixotrophic species in a wider range of aquatic environments, and could easily be coupled to other techniques to describe the finer details of the trophic status of aquatic microbial communities.

Physical interactions between microeukaryotes and their prokaryotic counterparts abound in nature but are laborious to characterize due to their large number and microscopic dimension. Emulsion, paired-isolation and concatenation PCR (epicPCR) has the potential to uncover these interactions at a large scale while maintaining the resolution of individual cells. In this approach, single eukaryotic cells are trapped inside polyacrylamide beads together with their physically associated bacterial partners. This is followed by molecular barcoding of taxonomic marker genes of both parts in a compartmentalized manner. In this study, we report the first iteration in the evaluation of this workflow when adapted to recover eukaryote-prokaryote associations via SSU rRNA gene linkage. Predatory associations between two cultured mixotrophic flagellates and their co-cultured bacterial cohort were our target. Three sets of experiments were carried out, in which the model flagellates were 1) encapsulated on their own, 2) with a bacterial community assembled artificially or 3) with a wastewater sample. In all cases, the most frequent associations between either of the mixotrophs and bacterial constituents were those that involved the most abundant bacterial taxa in the samples. This was most evident in experiment from the second set, where the strongest associations corresponded to those between the eukaryotes and the most abundant members of the mock bacterial community. This result points to the loss of single cell resolution at some point during the protocol. We hypothesize that the erosion of the compartmentalization principle might arise from two sources. First, the extreme polydispersity in droplet size of the polymerizing emulsion, combined with much smaller cell size and much higher population density of the bacteria relative to the eukaryotes, can cause random co-encapsulation of cells that are not physically attached. Second, the design of the barcoding reaction as implemented here might be prone to generate a large number of non-barcoded fragments susceptible to be spuriously tagged during nested PCR, ruining the signature of individual separation. Although technical limitations exist, avenues for further development remain open. The vast exploratory potential of the epicPCR technique justifies further research to overcome these technical constrains.