{"refrec":{"BRefID":288223,"RR":"Props, R.; Monsieurs, P.; Mysara, M.; Clement, L.; Boon, N. (2016). Measuring the biodiversity of microbial communities by flow cytometry. Methods Ecol. Evol. 7(11): 1376-1385. https://dx.doi.org/10.1111/2041-210x.12607","BEntID":280251,"PublicFlag":1,"CheckedFlag":0,"wosflag":1,"vabbflag":1,"RefStringPartII":". Methods Ecol. Evol. 7(11): 1376-1385. https://dx.doi.org/10.1111/2041-210x.12607","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":1,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Props, R.; Monsieurs, P.; Mysara, M.; Clement, L.; Boon, N.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Props, R. et al.","Englishabstract":"Measuring the microbial diversity in natural and engineered environments is important for ecosystem characterization, ecosystem monitoring and hypothesis testing. Although the conventional assessment through single marker gene surveys has resulted in major advances, the complete procedure remains slow (i.e. weeks to months), labour-intensive and susceptible to multiple sources of laboratory and data processing bias. Growing interest, in highly resolved, temporal surveys of microbial diversity, necessitates rapid, inexpensive and robust analytical platforms that require limited computational effort.Here, we demonstrate that sensitive single-cell measurements of phenotypic attributes, obtained via flow cytometry, can provide fast (i.e. within minutes) first-line assessments of microbial diversity dynamics, without demanding extensive sample preparation and downstream data processing. We developed a data processing pipeline that fits bivariate kernel density functions to phenotypic parameter combinations of an entire microbial community and concatenates them to a single one-dimensional phenotypic fingerprint. By calculating established diversity metrics from such phenotypic fingerprints, we construct an alternative interpretation of the microbial diversity that incorporates distinct phenotypic traits underlying cell-to-cell heterogeneity (i.e. morphology and nucleic acid content).Based on a detailed longitudinal study of a highly dynamic microbial ecosystem, our approach delivered temporal alpha diversity profiles that strongly correlated with the reference diversity, as estimated by 16S rRNA amplicon sequencing. This strongly suggests that the distribution of a limited amount of phenotypic features within a microbial community already provides sufficient resolving power for the measurement of diversity dynamics at the species level.We present a fast, robust analysis method for monitoring the microbial biodiversity of natural and engineered ecosystems that correlates well with the conventional marker gene surveys. Our work has both applied and fundamental implications that stretch from ecosystem monitoring and studies on microbial community dynamics, to supervised sampling strategies. Furthermore, our approach offers perspectives for the development of online and in situ monitoring systems for microbial ecosystems.","AbstractOtherLang":null,"BibLvlCode":"AS","StandardTitle":"Measuring the biodiversity of microbial communities by flow cytometry","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2026-04-19 01:31:51.453073","timezone_type":1,"timezone":"+02:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":"16S rRNA gene;environmental microbiology;flow cytometry;microbial community dynamics;microbial diversity;microbial ecology;single-cell analysis","OtherDescriptors":null,"Notes":null,"AnaPub":2016,"MonPub":null,"DateUpdate":"2017-08-17","DateCreate":"2017-08-17","SecASFANote":null,"ConfID":null,"PeerRev":1,"VlizCoreFlag":1,"WoScode":"WOS:000387669600014","VABBcode":null,"OpenAcc":0,"DOI":"10.1111/2041-210x.12607"},"refs":null,"anarec":{"AnaID":288223,"PubliDate":2016,"Pagination":"1376-1385","XtraPublOfAnaID":null,"ISBN":null,"Volume":"7","Issue":"11","BRefMon":null,"BRefMonRR":null,"BRefXtra":null,"BRefXtraRR":null,"SerBRefID":205126,"SerRR":"Methods in Ecology and Evolution. Wiley: Hoboken. ISSN 2041-2096; e-ISSN 2041-210X","StandardTitleSer":"Methods in Ecology and Evolution","ISSN":"2041-2096","AbbrevSer":"Methods Ecol. Evol.","StandardTitleMon":null,"StartPage":1376,"Pages":10,"ToPubliDate":null,"BRefBibLvlCode":"S","SerNotes":null},"monrec":null,"serrec":null,"relations":null,"relationsRev":null,"addrec":null,"othpubs":null,"ownerships":null,"authors":[{"AutName":"Props","Firstname":"Ruben","Initials":"R.","Affiliation":"Center for Microbial Ecology and Technology (CMET), Ghent University","Discriminator":null,"CorporateFlag":0,"BEntID":280251,"AutID":266541,"OrderNr":1,"DegrID":null,"EditorFlag":0,"CorrespFlag":0,"IllustratorFlag":0,"ReviserFlag":0,"TranslatorFlag":0,"InsAcronym":"CMET","InsFSN":"Ghent University; Faculty of Bioscience Engineering; Department of Biotechnology; Center for Microbial Ecology and Technology","ORCID":null,"PersID":36098,"InsID":6702},{"AutName":"Monsieurs","Firstname":"Pieter","Initials":"P.","Affiliation":"Belgian Nuclear Research Centre (SCK•CEN)","Discriminator":null,"CorporateFlag":0,"BEntID":280251,"AutID":266537,"OrderNr":2,"DegrID":null,"EditorFlag":0,"CorrespFlag":0,"IllustratorFlag":0,"ReviserFlag":0,"TranslatorFlag":0,"InsAcronym":null,"InsFSN":"Belgian Nuclear Research Centre","ORCID":"0000-0003-2214-6652","PersID":36131,"InsID":8797},{"AutName":"Mysara","Firstname":"Mohamed","Initials":"M.","Affiliation":"Belgian Nuclear Research Centre (SCK•CEN)","Discriminator":null,"CorporateFlag":0,"BEntID":280251,"AutID":266543,"OrderNr":3,"DegrID":null,"EditorFlag":0,"CorrespFlag":0,"IllustratorFlag":0,"ReviserFlag":0,"TranslatorFlag":0,"InsAcronym":null,"InsFSN":"Belgian Nuclear Research Centre","ORCID":null,"PersID":36130,"InsID":8797},{"AutName":"Clement","Firstname":"Lieven","Initials":"L.","Affiliation":"Department of Applied Mathematics, Informatics and Statistics, Ghent University","Discriminator":null,"CorporateFlag":0,"BEntID":280251,"AutID":266544,"OrderNr":4,"DegrID":null,"EditorFlag":0,"CorrespFlag":0,"IllustratorFlag":0,"ReviserFlag":0,"TranslatorFlag":0,"InsAcronym":null,"InsFSN":null,"ORCID":"0000-0002-9050-4370","PersID":15563,"InsID":null},{"AutName":"Boon","Firstname":"Nico","Initials":"N.","Affiliation":"Center for Microbial Ecology and Technology (CMET), Ghent University","Discriminator":null,"CorporateFlag":0,"BEntID":280251,"AutID":248938,"OrderNr":5,"DegrID":null,"EditorFlag":0,"CorrespFlag":0,"IllustratorFlag":0,"ReviserFlag":0,"TranslatorFlag":0,"InsAcronym":"CMET","InsFSN":"Ghent University; Faculty of Bioscience Engineering; Department of Biotechnology; Center for Microbial Ecology and Technology","ORCID":"0000-0002-7734-3103","PersID":15308,"InsID":6702}],"mapdetails":null,"datasets":null,"monographs":null,"monparts":null,"serparts":null,"BEntOpen":null,"BEntPrivate":null,"availability":[{"BInstID":305525,"LibID":36,"BRefID":288223,"EmbargoDate":null,"FullEmbargoDate":null,"PhysMedID":16,"hasOCRd":1,"ShelfLocCode":"305525","RFID":null,"PaidValue":null,"Medium":"Server","Description":"Interne VLIZ documenten","Acronym":"VLIZ","Library":"Vlaams Instituut voor de Zee","DutchTerm":"Non-open access","URL":null,"ClassifID":228,"Classification":"Non-open access","ReqLink":1,"ClassifTypID":3,"URLLocation":"https://www.vliz.be/imisdocs/publications/","SubDir":1,"InternalReq":1,"LoggedInReq":1,"Disclaimer":"Disclaimer_VLIZ_Intern","DutchDisclaimer":"
Deze publicatie is enkel beschikbaar voor persoonlijk gebruik binnen de Innovocean site en mag op geen enkele manier verder worden verspreid.