Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies

Detalhes bibliográficos
Autor(a) principal: Amaral, A. Luís
Data de Publicação: 2017
Outros Autores: Abreu, H., Leal, C., Mesquita, Daniela P., Castro, L. M., Ferreira, Eugénio C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/47494
Resumo: Polyhydroxyalkanoates (PHAs) produced from mixed microbial cultures (MMC), regarded as potential substitutes of petrochemical plastics, can be found as intracellular granules in various microorganisms under limited nutrient conditions and excess of carbon source. PHA is traditionally quantified by laborious and time-consuming chromatography analysis, and a simpler and faster method to assess PHA contents from MMC, such as quantitative image analysis (QIA), is of great interest. The main purpose of the present work was to upgrade a previously developed QIA methodology (Mesquita et al., 2013a, 2015) for MMC intracellular PHA contents quantification, increase the studied intracellular PHA concentration range and extend to different sequencing batch reactor (SBR) operation strategies. Therefore, the operation of a new aerobic dynamic feeding (ADF) SBR allowed further extending the studied operating conditions, dataset, and range of the MMC intracellular PHA contents from the previously reported anaerobic/aerobic cycle SBR. Nile Blue A (NBA) staining was employed for epifluorescence microscope visualization and image acquisition, further fed to a custom developed QIA. Data from each of the feast and famine cycles of both SBR were individually processed using chemometrics analysis, obtaining the correspondent partial least squares (PLS) models. The PHA concentrations determined from PLS models were further plotted against the results obtained in the standard chromatographic method. For both SBR the predicted ability was higher at the end of the feast stage than for the famine stage. Indeed, an independent feast and famine QIA data treatment was found to be fundamental to obtain the best prediction abilities. Furthermore, a promising overall correlation (R2 of 0.83) could be found combining the overall QIA data regarding the PHA prediction up to a concentration of 1785.1 mgL-1 (37.3 wt%). Thus, the results confirm that the presented QIA methodology can be seen as promising for estimating higher intracellular PHA concentrations for a larger reactors operation systems and further extending the prediction range of previous studies.
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spelling Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategiesSequencing batch reactors (SBR)Mixed microbial cultures (MMC)Polyhydroxyalkanoates (PHA)Nile BlueA (NBA) stainingQuantitative image analysis (QIA)Partial least squares (PLS)Science & TechnologyPolyhydroxyalkanoates (PHAs) produced from mixed microbial cultures (MMC), regarded as potential substitutes of petrochemical plastics, can be found as intracellular granules in various microorganisms under limited nutrient conditions and excess of carbon source. PHA is traditionally quantified by laborious and time-consuming chromatography analysis, and a simpler and faster method to assess PHA contents from MMC, such as quantitative image analysis (QIA), is of great interest. The main purpose of the present work was to upgrade a previously developed QIA methodology (Mesquita et al., 2013a, 2015) for MMC intracellular PHA contents quantification, increase the studied intracellular PHA concentration range and extend to different sequencing batch reactor (SBR) operation strategies. Therefore, the operation of a new aerobic dynamic feeding (ADF) SBR allowed further extending the studied operating conditions, dataset, and range of the MMC intracellular PHA contents from the previously reported anaerobic/aerobic cycle SBR. Nile Blue A (NBA) staining was employed for epifluorescence microscope visualization and image acquisition, further fed to a custom developed QIA. Data from each of the feast and famine cycles of both SBR were individually processed using chemometrics analysis, obtaining the correspondent partial least squares (PLS) models. The PHA concentrations determined from PLS models were further plotted against the results obtained in the standard chromatographic method. For both SBR the predicted ability was higher at the end of the feast stage than for the famine stage. Indeed, an independent feast and famine QIA data treatment was found to be fundamental to obtain the best prediction abilities. Furthermore, a promising overall correlation (R2 of 0.83) could be found combining the overall QIA data regarding the PHA prediction up to a concentration of 1785.1 mgL-1 (37.3 wt%). Thus, the results confirm that the presented QIA methodology can be seen as promising for estimating higher intracellular PHA concentrations for a larger reactors operation systems and further extending the prediction range of previous studies.This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE01-0145-FEDER-000004) funded by European Regional Development Fundunder the scope ofNorte2020 - ProgramaOperacional Regional do Norte.The authors also acknowledge the financial support to Cristiano S. Leal (PTDC/EBB-EBI/103147/2008, FCOMP-01-0124-FEDER009704) and Daniela P. Mesquita through the FCT postdoctoral grant (SFRH/BPD/82558/2011).info:eu-repo/semantics/publishedVersionSpringer NatureUniversidade do MinhoAmaral, A. LuísAbreu, H.Leal, C.Mesquita, Daniela P.Castro, L. M.Ferreira, Eugénio C.2017-062017-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/47494engAmaral, A. Luís; Abreu, H.; Leal, C.; Mesquita, Daniela P.; Castro, L. M.; Ferreira, Eugénio C., Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies. Environmental Science and Pollution Research, 24(17), 15148-15156, 20170944-13441614-749910.1007/s11356-017-9132-028500546http://www.springer.com/environment/journal/11356info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-16T01:19:54Zoai:repositorium.sdum.uminho.pt:1822/47494Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:49:10.050171Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies
title Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies
spellingShingle Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies
Amaral, A. Luís
Sequencing batch reactors (SBR)
Mixed microbial cultures (MMC)
Polyhydroxyalkanoates (PHA)
Nile BlueA (NBA) staining
Quantitative image analysis (QIA)
Partial least squares (PLS)
Science & Technology
title_short Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies
title_full Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies
title_fullStr Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies
title_full_unstemmed Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies
title_sort Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies
author Amaral, A. Luís
author_facet Amaral, A. Luís
Abreu, H.
Leal, C.
Mesquita, Daniela P.
Castro, L. M.
Ferreira, Eugénio C.
author_role author
author2 Abreu, H.
Leal, C.
Mesquita, Daniela P.
Castro, L. M.
Ferreira, Eugénio C.
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Amaral, A. Luís
Abreu, H.
Leal, C.
Mesquita, Daniela P.
Castro, L. M.
Ferreira, Eugénio C.
dc.subject.por.fl_str_mv Sequencing batch reactors (SBR)
Mixed microbial cultures (MMC)
Polyhydroxyalkanoates (PHA)
Nile BlueA (NBA) staining
Quantitative image analysis (QIA)
Partial least squares (PLS)
Science & Technology
topic Sequencing batch reactors (SBR)
Mixed microbial cultures (MMC)
Polyhydroxyalkanoates (PHA)
Nile BlueA (NBA) staining
Quantitative image analysis (QIA)
Partial least squares (PLS)
Science & Technology
description Polyhydroxyalkanoates (PHAs) produced from mixed microbial cultures (MMC), regarded as potential substitutes of petrochemical plastics, can be found as intracellular granules in various microorganisms under limited nutrient conditions and excess of carbon source. PHA is traditionally quantified by laborious and time-consuming chromatography analysis, and a simpler and faster method to assess PHA contents from MMC, such as quantitative image analysis (QIA), is of great interest. The main purpose of the present work was to upgrade a previously developed QIA methodology (Mesquita et al., 2013a, 2015) for MMC intracellular PHA contents quantification, increase the studied intracellular PHA concentration range and extend to different sequencing batch reactor (SBR) operation strategies. Therefore, the operation of a new aerobic dynamic feeding (ADF) SBR allowed further extending the studied operating conditions, dataset, and range of the MMC intracellular PHA contents from the previously reported anaerobic/aerobic cycle SBR. Nile Blue A (NBA) staining was employed for epifluorescence microscope visualization and image acquisition, further fed to a custom developed QIA. Data from each of the feast and famine cycles of both SBR were individually processed using chemometrics analysis, obtaining the correspondent partial least squares (PLS) models. The PHA concentrations determined from PLS models were further plotted against the results obtained in the standard chromatographic method. For both SBR the predicted ability was higher at the end of the feast stage than for the famine stage. Indeed, an independent feast and famine QIA data treatment was found to be fundamental to obtain the best prediction abilities. Furthermore, a promising overall correlation (R2 of 0.83) could be found combining the overall QIA data regarding the PHA prediction up to a concentration of 1785.1 mgL-1 (37.3 wt%). Thus, the results confirm that the presented QIA methodology can be seen as promising for estimating higher intracellular PHA concentrations for a larger reactors operation systems and further extending the prediction range of previous studies.
publishDate 2017
dc.date.none.fl_str_mv 2017-06
2017-06-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/47494
url https://hdl.handle.net/1822/47494
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Amaral, A. Luís; Abreu, H.; Leal, C.; Mesquita, Daniela P.; Castro, L. M.; Ferreira, Eugénio C., Quantitative image analysis of polyhydroxyalkanoates inclusions from microbial mixed cultures under different SBR operation strategies. Environmental Science and Pollution Research, 24(17), 15148-15156, 2017
0944-1344
1614-7499
10.1007/s11356-017-9132-0
28500546
http://www.springer.com/environment/journal/11356
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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