Matches in SemOpenAlex for { <https://semopenalex.org/work/W1846643054> ?p ?o ?g. }
Showing items 1 to 95 of
95
with 100 items per page.
- W1846643054 endingPage "16" @default.
- W1846643054 startingPage "15" @default.
- W1846643054 abstract "It is estimated that over 99% of microorganisms have not as yet been cultivated (Whitman et al., 1998). These uncultured microbes are the ‘dark matter’ of the microbiological world and play important roles in natural ecosystems and the human microbiome (Lagier et al., 2012; Rinke et al., 2013); however, their ecological role and function remain largely elusive (Lasken, 2012; Li et al., 2012a,b). Furthermore, these uncultured bacteria represent a significant, yet largely untapped, genetic resource for use in synthetic biology for the provision of novel bioparts or biobricks, in medicine for new drug biosynthesis, in industry for robust biocatalysts and biofuel synthesis, and in environmental bioremediation for new biodegradation genes. Metagenomics circumvents the cultivation issue by extracting the total DNA from an environmental sample, and directly sequencing it (Handelsman, 2004), and this approach has revealed an unprecedented view of the diversity and complexity of microbial communities. However, such approaches are usually unable to define or validate the specific role of individual members of the usually complex microbiota. Single cell biotechnology, which characterizes microbial cells in their native microbiota one by one, offers a new approach to study uncultured bacteria. An ideal platform is to integrate accurate and ‘contamination-free’ single cell sorting tools with powerful next-generation DNA sequencing. This will usher in a new area of single cell omics (genomics, transcriptomics, proteomics and metabolomics). For single cell biotechnology, there are a number of key challenges: non-invasive and in-vivo cell analysis, the linking of cell phenotypes to specific ecological functions (e.g. substrate metabolism), overcoming limitations in measurement parameters, systematic differentiation of the given ‘state’ or phenotype of a cell and isolation of live single cells from complex samples in-situ. Among the various single cell sorting techniques (Lasken, 2012; Li et al., 2012a,b), an emerging approach is Raman-activated cell sorting (RACS), which overcomes the requirement for external labelling. Single cell Raman spectra (SCRS) provide a label-free, non-invasive and intrinsic phenotypic profile of individual cells which can be used to characterize cell type, physiological state and cell functionalities (Huang et al., 2004; 2007a,b,c; Harz et al., 2009; Li et al., 2012a,b; Wang et al., 2014). A typical SCRS provides an intrinsic chemical ‘fingerprint’ of a single cell, and usually contains multi-parameter (> 1000 readings) including rich information on nucleic acids, protein, carbohydrates and lipids (Li et al., 2012a,b). Since SCRS measures the vibration of molecular bonds, it is sensitive to stable isotope compounds and SCRS undergoes Raman shift when cells incorporate stable isotope compounds (e.g. 13C-, 15N-substrates or 2H from heavy water D2O) into the cell's building blocks (e.g. DNA, lipids, protein or carbohydrate) (Huang et al., 2004; 2007a,b,c; Wang et al., 2013). SCRS offers a unique way to link cells to specific functions (e.g. C/N metabolism and metabolic activity) and to define cells of interest at a single cell level. A RACS system consists of a SCRS detection system and a cell isolation system that can be optical tweezers (Huang et al., 2009), a microfluidic device (Li et al., 2012a,b) or a single cell ejection system (Wang et al., 2013). RACS would identify cells of interest and isolate them for downstream single cell omics analysis. The isolated single cells would be processed on microfluidic chips for DNA/RNA extraction and amplification. The DNA/RNA can then be quantified or sequenced to decode the genomes or transcriptomes of the particular cells. Such a platform directly establishes the links between genotype and phenotype of individual cells, thus offering unprecedented opportunities to study how variability of environmental and genetic impacts on the phenotype of single cells. Single cell biotechnology will not only be a powerful tool to microbiology, but also herald single cell biology as a new frontier of cell biology. A single cell is the basic functional unit of life and all living organisms start from single cells. Learning how cells work by studying the individual cell is an important component of cell biology and single cell technology promotes a deeper understanding of cell biology. Recent research from the studies of single cells reveals that individual cells within the same population may differ dramatically in function, and these differences have profound biological implications, ranging from bacterial physiology to embryotic cell development, tissue differentiation, cancer cell formation and evolution. In summary, during the next decade, just like DNA sequencing, single cell biotechnologies are expected to rapidly move into bench tops of biology laboratory, and to permeate all branches of life sciences and biotechnology. They promise to uncover fundamental biological principles and ultimately improve the diagnosis and treatment of diseases, unravel the ecological role of bacteria in soils, plants and humans, and promote the discovery of new gene functions for use in industry. None declared." @default.
- W1846643054 created "2016-06-24" @default.
- W1846643054 creator A5000871229 @default.
- W1846643054 creator A5013473081 @default.
- W1846643054 creator A5081633974 @default.
- W1846643054 date "2015-01-01" @default.
- W1846643054 modified "2023-10-14" @default.
- W1846643054 title "Single cell biotechnology to shed a light on biological ‘dark matter’ in nature" @default.
- W1846643054 cites W1760389142 @default.
- W1846643054 cites W1978470271 @default.
- W1846643054 cites W1981495536 @default.
- W1846643054 cites W1985676839 @default.
- W1846643054 cites W1997712011 @default.
- W1846643054 cites W1998786168 @default.
- W1846643054 cites W2029811376 @default.
- W1846643054 cites W2051397417 @default.
- W1846643054 cites W2055398959 @default.
- W1846643054 cites W2065600707 @default.
- W1846643054 cites W2079818745 @default.
- W1846643054 cites W2118001436 @default.
- W1846643054 cites W2145596490 @default.
- W1846643054 cites W2147783737 @default.
- W1846643054 cites W2156521321 @default.
- W1846643054 cites W2166123725 @default.
- W1846643054 doi "https://doi.org/10.1111/1751-7915.12249" @default.
- W1846643054 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4321360" @default.
- W1846643054 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25627841" @default.
- W1846643054 hasPublicationYear "2015" @default.
- W1846643054 type Work @default.
- W1846643054 sameAs 1846643054 @default.
- W1846643054 citedByCount "20" @default.
- W1846643054 countsByYear W18466430542015 @default.
- W1846643054 countsByYear W18466430542016 @default.
- W1846643054 countsByYear W18466430542017 @default.
- W1846643054 countsByYear W18466430542018 @default.
- W1846643054 countsByYear W18466430542019 @default.
- W1846643054 countsByYear W18466430542020 @default.
- W1846643054 countsByYear W18466430542021 @default.
- W1846643054 countsByYear W18466430542022 @default.
- W1846643054 countsByYear W18466430542023 @default.
- W1846643054 crossrefType "journal-article" @default.
- W1846643054 hasAuthorship W1846643054A5000871229 @default.
- W1846643054 hasAuthorship W1846643054A5013473081 @default.
- W1846643054 hasAuthorship W1846643054A5081633974 @default.
- W1846643054 hasBestOaLocation W18466430542 @default.
- W1846643054 hasConcept C104317684 @default.
- W1846643054 hasConcept C141231307 @default.
- W1846643054 hasConcept C143121216 @default.
- W1846643054 hasConcept C150903083 @default.
- W1846643054 hasConcept C15151743 @default.
- W1846643054 hasConcept C189206191 @default.
- W1846643054 hasConcept C191908910 @default.
- W1846643054 hasConcept C199465337 @default.
- W1846643054 hasConcept C21565614 @default.
- W1846643054 hasConcept C54355233 @default.
- W1846643054 hasConcept C60644358 @default.
- W1846643054 hasConcept C70721500 @default.
- W1846643054 hasConcept C86803240 @default.
- W1846643054 hasConceptScore W1846643054C104317684 @default.
- W1846643054 hasConceptScore W1846643054C141231307 @default.
- W1846643054 hasConceptScore W1846643054C143121216 @default.
- W1846643054 hasConceptScore W1846643054C150903083 @default.
- W1846643054 hasConceptScore W1846643054C15151743 @default.
- W1846643054 hasConceptScore W1846643054C189206191 @default.
- W1846643054 hasConceptScore W1846643054C191908910 @default.
- W1846643054 hasConceptScore W1846643054C199465337 @default.
- W1846643054 hasConceptScore W1846643054C21565614 @default.
- W1846643054 hasConceptScore W1846643054C54355233 @default.
- W1846643054 hasConceptScore W1846643054C60644358 @default.
- W1846643054 hasConceptScore W1846643054C70721500 @default.
- W1846643054 hasConceptScore W1846643054C86803240 @default.
- W1846643054 hasIssue "1" @default.
- W1846643054 hasLocation W18466430541 @default.
- W1846643054 hasLocation W18466430542 @default.
- W1846643054 hasLocation W18466430543 @default.
- W1846643054 hasLocation W18466430544 @default.
- W1846643054 hasOpenAccess W1846643054 @default.
- W1846643054 hasPrimaryLocation W18466430541 @default.
- W1846643054 hasRelatedWork W1577826155 @default.
- W1846643054 hasRelatedWork W2958564218 @default.
- W1846643054 hasRelatedWork W2963984501 @default.
- W1846643054 hasRelatedWork W2969529002 @default.
- W1846643054 hasRelatedWork W2987445723 @default.
- W1846643054 hasRelatedWork W3108029194 @default.
- W1846643054 hasRelatedWork W3149998985 @default.
- W1846643054 hasRelatedWork W4210316040 @default.
- W1846643054 hasRelatedWork W4211121339 @default.
- W1846643054 hasRelatedWork W4386025850 @default.
- W1846643054 hasVolume "8" @default.
- W1846643054 isParatext "false" @default.
- W1846643054 isRetracted "false" @default.
- W1846643054 magId "1846643054" @default.
- W1846643054 workType "article" @default.