Functions of complex natural microbial communities are realized by single cells that contribute differently to the overall performance of a community. In addition to using molecular and, more recently, deep-sequencing technologies for detailed phylogenetic or functional capacity analyses of microbial communities we want to explore the potential of microbial Cytomics to describe the function of microorganisms in natural ecosystems. The term Cytomics originates from clinical background and is the central tactic to explore the cells role in individual human bodies. Likewise, in microbiology Cytomics comprises microbial communities in certain environments performing particular functions like a human microbiome, wastewater or biogas communities or microbial communities that origin from drinking or surface water systems. Cytomics investigates the role of single cells within respective natural communities, their specific characteristics, functions, interrelationships and dynamic behavior. Cytomics explores how single cells or subsets of cells contribute to the overall function of a microbial community of interest. The obvious way to do so is the combination of high throughput single cell analytics like flow cytometry with genomics via cell sorting of subcommunities or even single cells. This step increases the understanding of the functional operation of cells in microbial ecosystems because abundance information from the cytometric data are combined with the molecular information obtained from the sorted cells. Subcommunity transcriptome or proteome analyses will further add to functional understanding.
Besides the role of flow cytometry within these highly informative and sophisticated approaches, the technique is valuable on its own by measuring certain cell features and corresponding cell abundances within specific microbial systems. Analogous to other known ‘omics’ technologies, Cytomics can explore the role of a subset of microorganism(s) within a community when visualized by a specific marker. Furthermore, first bioinformatic tools, similar to those used for evaluation of sequencing data, are launched that help to understand interrelationships between cells in ecosystems. Single cell analysis may be on its way to a leading tool in microbiology when powerful bioinformatic tools provide background information on fast cell dynamics. Key-subcommunities need to be identified; functions need to be correlated to specific cell types. Both the cytometric data and their evaluation will ease the selection of cells for genomic and proteomic sorting approaches and will contribute to the above mentioned high resolution methods in order to understand ecosystem functioning.
Within this topic we welcome contributions that use various single cell techniques to explore microbial ecosystems both in health (e.g. by investigating the impact of bacteria on the human system) and environment (e.g. by unraveling specific cell dynamics and functions within soil, groundwater or marine ecosystems). In addition, applications within managed microbial systems are encouraged that focus on drinking water quality, stability of wastewater treatment plants or efficiency of biogas communities. Especially welcome are new bioinfomatic approaches that enable to handle cytometric datasets and interpret community function and evolution.
Functions of complex natural microbial communities are realized by single cells that contribute differently to the overall performance of a community. In addition to using molecular and, more recently, deep-sequencing technologies for detailed phylogenetic or functional capacity analyses of microbial communities we want to explore the potential of microbial Cytomics to describe the function of microorganisms in natural ecosystems. The term Cytomics originates from clinical background and is the central tactic to explore the cells role in individual human bodies. Likewise, in microbiology Cytomics comprises microbial communities in certain environments performing particular functions like a human microbiome, wastewater or biogas communities or microbial communities that origin from drinking or surface water systems. Cytomics investigates the role of single cells within respective natural communities, their specific characteristics, functions, interrelationships and dynamic behavior. Cytomics explores how single cells or subsets of cells contribute to the overall function of a microbial community of interest. The obvious way to do so is the combination of high throughput single cell analytics like flow cytometry with genomics via cell sorting of subcommunities or even single cells. This step increases the understanding of the functional operation of cells in microbial ecosystems because abundance information from the cytometric data are combined with the molecular information obtained from the sorted cells. Subcommunity transcriptome or proteome analyses will further add to functional understanding.
Besides the role of flow cytometry within these highly informative and sophisticated approaches, the technique is valuable on its own by measuring certain cell features and corresponding cell abundances within specific microbial systems. Analogous to other known ‘omics’ technologies, Cytomics can explore the role of a subset of microorganism(s) within a community when visualized by a specific marker. Furthermore, first bioinformatic tools, similar to those used for evaluation of sequencing data, are launched that help to understand interrelationships between cells in ecosystems. Single cell analysis may be on its way to a leading tool in microbiology when powerful bioinformatic tools provide background information on fast cell dynamics. Key-subcommunities need to be identified; functions need to be correlated to specific cell types. Both the cytometric data and their evaluation will ease the selection of cells for genomic and proteomic sorting approaches and will contribute to the above mentioned high resolution methods in order to understand ecosystem functioning.
Within this topic we welcome contributions that use various single cell techniques to explore microbial ecosystems both in health (e.g. by investigating the impact of bacteria on the human system) and environment (e.g. by unraveling specific cell dynamics and functions within soil, groundwater or marine ecosystems). In addition, applications within managed microbial systems are encouraged that focus on drinking water quality, stability of wastewater treatment plants or efficiency of biogas communities. Especially welcome are new bioinfomatic approaches that enable to handle cytometric datasets and interpret community function and evolution.
