Shida, Y. | bioRxiv Science

bioRxiv2022

A new microfluidic device for simultaneous detection of enzyme secretion and elongation of a single hypha

Fungal cells perform enzyme secretion and elongation by exocytosis in the apical region. The widespread branching of hyphae and the inability to control environmental conditions over long periods make it difficult to observe and analyze single hyphae with conventional assays. Therefore, although hyphal morphology is closely linked to productivity, no real-time measurements of morphology and exoenzymes have been carried out. In this study, a microfluidic system was developed to compartmentalize a single hypha germinated from a single spore. This allowed detailed observation of a single hypha and provided new insights, such as the fact that enlarged vacuoles inhibit nuclear movement. Furthermore, a cellulase detection assay based on subtle differences in molecular polarity was developed to detect hyphal growth and enzyme secretion in real-time using Trichoderma reesei, a potent cellulase-producing hypha, as a model. When the fluorescence from the detection assay was compared with the GFP fluorescence intensity using a strain fused with cellulase CBHI and GFP, a strong correlation was observed. As T. reesei secretes a series of cellulases, these results prove that the extracellular enzymes can be measured in real time. This microfluidic system has enabled real-time visualization and analysis of cellular heterogeneity, hyphal and enzyme dynamics associated with carbon source exchange, and quantitative dynamics of gene expression. The technology can be applied to a wide range of other biosystems exhibiting similar polar cell growth, from bioenergy production to human health. IMPORTANCEHyphal morphology and productivity of filamentous fungi are linked by exocytosis. Conventional assay methods make it difficult to observe and analyze single hyphae. Here, a robust and high-performance microfluidic system was developed to compartmentalize single hyphae germinated from a single spore, enabling their long-term observation. Using the potent cellulase-producing fungus Trichoderma reesei, the system made it possible to visualize and analyze cell heterogeneity, hyphae, enzyme dynamics, and quantitative gene expression dynamics associated with carbon source exchange. The technique can be immediately extended to various other biosystems exhibiting similar polar cell growth and is expected to contribute significantly to the elucidation of filamentous fungi production systems.

microbiology↗

bioRxiv2021

Intracellular and intercellular gene regulatory networks inference from time-course individual RNA-Seq

Gene regulatory network (GRN) inference is an effective approach to understand the molecular mechanisms underlying biological events. Generally, GRN inference mainly targets intracellular regulatory relationships such as transcription factors and their associated targets. In multicellular organisms, there are both intracellular and intercellular regulatory mechanisms. Thus, we hypothesize that GRNs inferred from time-course individual (whole embryo) RNA-Seq during development can reveal intercellular regulatory relationships (signaling pathways) underlying the development. Here, we conducted time-course bulk RNA-Seq of individual mouse embryos during early development, followed by pseudo-time analysis and GRN inference. The results demonstrated that GRN inference from RNA-Seq with pseudo-time can be applied for individual bulk RNA-Seq similar to scRNA-Seq. Validation using an experimental-source-based database showed that our approach could significantly infer GRN for all transcription factors in the database. Furthermore, the inferred ligand-related and receptor-related downstream genes were significantly overlapped. Thus, the inferred GRN based on whole organism could include intercellular regulatory relationships, which cannot be inferred from scRNA-Seq based only on gene expression data. Overall, inferring GRN from time-course bulk RNA-Seq is an effective approach for understanding the regulatory relationships underlying biological events in multicellular organisms.

bioinformatics↗