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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.

The permanently anoxic waters in meromictic lakes create suitable niches for the growth of bacteria using sulphur metabolisms like sulphur oxidation. In Lake Pavin, the anoxic water mass hosts an active cryptic sulphur cycle that interacts narrowly with iron cycling, however the metabolisms of the microorganisms involved are poorly known. Here we combined metagenomics, single-cell genomics, and pan-genomics to further expand our understanding of the bacteria and the corresponding metabolisms involved in sulphur oxidation in this ferruginous sulphide- and sulphate-poor meromictic lake. We highlighted two new species within the genus Sulfurimonas that belong to a novel clade of chemotrophic sulphur oxidisers exclusive to freshwaters. We moreover conclude that this genus holds a key-role not only in limiting sulphide accumulation in the upper part of the anoxic layer but also constraining carbon, phosphate and iron cycling.

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.

Dendritic cells and macrophages are integral parts of the innate immune system and gatekeepers against infection. The protozoan pathogen, Toxoplasma gondii, is known to hijack host immune cells and modulate their immune response, making it a compelling model to study host-pathogen interactions. Here we utilize single cell Dual RNA-seq to parse out heterogeneous transcription of mouse bone marrow-derived dendritic cells (BMDCs) infected with two distinct genotypes of T. gondii parasites, over multiple time points post infection. We show that the BMDCs elicit differential responses towards T. gondii infection and that the two parasite lineages distinctly manipulate subpopulations of infected BMDCs. Co-expression networks define host and parasite genes, with implications for modulation of host immunity. Integrative analysis validates previously established immune pathways and additionally, suggests novel candidate genes involved in host-pathogen interactions. Altogether, this study provides a comprehensive resource for characterizing host-pathogen interplay at high-resolution.

Background: Prokaryotes dominate the biosphere and regulate biogeochemical processes essential to all life. Yet, our knowledge about their biology is for the most part limited to the minority that has been successfully cultured. Molecular techniques now allow for obtaining genome sequences of uncultivated prokaryotic taxa, facilitating in-depth analyses that may ultimately improve our understanding of these key organisms.

Results: We compared results from two culture-independent strategies for recovering bacterial genomes: single-amplified genomes and metagenome-assembled genomes. Single-amplified genomes were obtained from samples collected at an offshore station in the Baltic Sea Proper and compared to previously obtained metagenome-assembled genomes from a time series at the same station. Among 16 single-amplified genomes analyzed, seven were found to match metagenome-assembled genomes, affiliated with a diverse set of taxa. Notably, genome pairs between the two approaches were nearly identical (average 99.51% sequence identity; range 98.77-99.84%) across overlapping regions (30-80% of each genome). Within matching pairs, the single-amplified genomes were consistently smaller and less complete, whereas the genetic functional profiles were maintained. For the metagenome-assembled genomes, only on average 3.6% of the bases were estimated to be missing from the genomes due to wrongly binned contigs.

Conclusions: The strong agreement between the single-amplified and metagenome-assembled genomes emphasizes that both methods generate accurate genome information from uncultivated bacteria. Importantly, this implies that the research questions and the available resources are allowed to determine the selection of genomics approach for microbiome studies.

Background: Infectious disease involving multiple genetically distinct populations of pathogens is frequently concurrent, but difficult to detect or describe with current routine methodology. Cryptosporidium sp. is a widespread gastrointestinal protozoan of global significance in both animals and humans. It cannot be easily maintained in culture and infections of multiple strains have been reported. To explore the potential use of single cell genomics methodology for revealing genome-level variation in clinical samples from Cryptosporidium-infected hosts, we sorted individual oocysts for subsequent genome amplification and full-genome sequencing. Results: Cells were identified with fluorescent antibodies with an 80 % success rate for the entire single cell genomics workflow, demonstrating that the methodology can be applied directly to purified fecal samples. Ten amplified genomes from sorted single cells were selected for genome sequencing and compared both to the original population and a reference genome in order to evaluate the accuracy and performance of the method. Single cell genome coverage was on average 81 % even with a moderate sequencing effort and by combining the 10 single cell genomes, the full genome was accounted for. By a comparison to the original sample, biological variation could be distinguished and separated from noise introduced in the amplification. Conclusions: As a proof of principle, we have demonstrated the power of applying single cell genomics to dissect infectious disease caused by closely related parasite species or subtypes. The workflow can easily be expanded and adapted to target other protozoans, and potential applications include mapping genome-encoded traits, virulence, pathogenicity, host specificity and resistance at the level of cells as truly meaningful biological units.

The mitochondrial hypervariable regions I and II have proven to be a useful target for analysis of forensic materials, in which the amount of DNA is limited or highly degraded. Conventional mitochondrial DNA (mtDNA) sequencing can be time-consuming and expensive, limitations that can be minimized using a faster and less expensive typing assay. We have evaluated the exclusion capacity of the linear array mtDNA HVI/HVII region-sequence typing assay (Roche Applied Science) in 16 forensic cases comprising 90 samples. Using the HVI/HVII mtDNA linear array, 56% of the samples were excluded and thus less than half of the samples require further sequencing due to a match or inconclusive results. Of all the samples that were excluded by sequence analysis, 79% could be excluded using the HVI/HVII linear array alone. Using the HVI/HVII mtDNA linear array assay, we demonstrate the potential to decrease sequencing efforts substantially and thereby reduce the cost and the turn-around time in casework analysis.

Microarray-based single nucleotide polymorphism (SNP) genotyping enables simultaneous and rapid detection of a large number of markers and is thus an attractive method for forensic individual acid identification. This assay relies on a one-color detection system and minisequencing in solution before hybridization to universal tag arrays. The minisequencing reaction is based on incorporation of a fluorescent dideoxynucleotide to a primer containing a tag-sequence flanking the position to be interrogated. This one-color system detects C and T polymorphisms in separate reactions on multiple polymerase chain reaction targets with the fluorophore TAMRA coupled to the respective dideoxynucleotide. After incorporation, tagged primer sequences are hybridized through their complementary sequence on the array, and positive signals are detected by a confocal laser-scanner.

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.