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Johansson Beves, E.

Publications and source records attributed to Johansson Beves, E..

2 recordsLinked to original sources

Integrating microscopy and transcriptomics from individual uncultured eukaryotic plankton

Eukaryotic plankton comprises organisms as diverse as diatoms and pelagic larvae, covering a wide spectrum of shapes, molecular compositions, and ecological functions. Plankton research is often approached using either optical methods, especially for taxonomic purposes, or genomics, which excels at describing the biochemistry of microbial communities. This technological dichotomy hampers efforts to link the morpho-optical properties of each species with its genetic and biomolecular makeup, leading to fragmented information and limited reproducibility. Methods to simultaneously acquire multimodal, i.e. optical and genetic, information on planktonic organisms would provide a connection between organismal appearance and function, improve taxonomic prediction, and strengthen ecological analysis. Here we present Ukiyo-e-Seq, an approach to generate paired optical and transcriptomic data from individual eukaryotic plankton. We performed Ukiyo-e-Seq on 66 microscopic organisms from Coogee, NSW, Australia and assembled transcriptomic contigs using a merge-split strategy. While overall phylogenetic heterogeneity spanned hundreds of taxa, diversity in individual wells was low, enabling accurate classification of both microbial plankton and marine larvae. We then combined Ukiyo-e-Seq with AlphaFold 3, a protein language model, and could confidently infer (i) the joint structure and interactions of 34 photosynthesis proteins from a single Chaetoceros diatom, and (ii) the cellular and developmental functions of novel proteins highly expressed in one trout larva. In summary, Ukiyo-e-Seq is a precise tool to connect morphological and genetic information of eukaryotic plankton.

microbiology↗

High-throughput detection and quantification of phosphatidylcholines and sphingomyelins from single cells by chip-based nanoelectrospray ionisation

Recent advances in single-cell genomics and transcriptomics technologies have transformed our understanding of cellular heterogeneity in growth, development, ageing and disease; however, methods for single-cell lipidomics have comparatively lagged behind in development. We have developed a high-throughput method for the detection and quantification of a wide range of phosphatidylcholine (PC) and sphingomyelin (SM) species from single cells that combines fluorescence-assisted cell sorting (FACS) with automated chip-based nanoelectrospray ionization (nanoESI) and shotgun lipidomics. We show herein that our method is capable of quantifying more than 50 different PC and SM species from single cells and can easily distinguish between cells of different lineages or cells treated with exogenous fatty acids. Moreover, our method can detect more subtle differences in the lipidome between cell lines of the same cancer type. Our approach can be run in parallel with other single-cell technologies to deliver near-complete multi-omics data on cells with a similar phenotype and has the capacity to significantly advance our current knowledge on cellular heterogeneity.

biochemistry↗