Literature DB >> 29079975

Sensor manufacturer, temperature, and cyanobacteria morphology affect phycocyanin fluorescence measurements.

Caroline M Hodges1, Susanna A Wood1,2, Jonathan Puddick2, Christopher G McBride1, David P Hamilton3,4.   

Abstract

Sensors to measure phycocyanin fluorescence in situ are becoming widely used as they may provide useful proxies for cyanobacterial biomass. In this study, we assessed five phycocyanin sensors from three different manufacturers. A combination of culture-based experiments and a 30-sample field study was used to examine the effect of temperature and cyanobacteria morphology on phycocyanin fluorescence. Phycocyanin fluorescence increased with decrease in temperature, although this varied with manufacturer and cyanobacterial density. Phycocyanin fluorescence and cyanobacterial biovolume were strongly correlated (R 2 > 0.83, P < 0.05) for single-celled and filamentous species. The relationship was generally weak for a colonial strain of Microcystis aeruginosa. The colonial culture was divided into different colony size classes and phycocyanin measured before and after manual disaggregation. No differences were measured, and the observation that fluorescence spiked when large colonial aggregates drifted past the light source suggests that sample heterogeneity, rather than lack of light penetration into the colonies, was the main cause of the poor relationship. Analysis of field samples showed a strong relationship between in situ phycocyanin fluorescence and spectrophotometrically measured phycocyanin (R 2 > 0.7, P < 0.001). However, there was only a weak relationship between phycocyanin fluorescence and cyanobacterial biovolume for two sensors (R 2 = 0.22-0.29, P < 0.001) and a non-significant relationship for the third sensor (R 2 = 0.29, P > 0.4). The five sensors tested in our study differed in their output of phycocyanin fluorescence, upper working limits (1200 to > 12,000 μg/L), and responses to temperature, highlighting the need for comprehensive sensor calibration and knowledge on the limitations of specific sensors prior to deployment.

Entities:  

Keywords:  Aphanizomenon; Cyanobacterial blooms; Dolichospermum; Environmental monitoring; Microcystis; Nodularia

Mesh:

Substances:

Year:  2017        PMID: 29079975     DOI: 10.1007/s11356-017-0473-5

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  16 in total

1.  Use of in vivo phycocyanin fluorescence to monitor potential microcystin-producing cyanobacterial biovolume in a drinking water source.

Authors:  N McQuaid; A Zamyadi; M Prévost; D F Bird; S Dorner
Journal:  J Environ Monit       Date:  2010-12-15

Review 2.  Cyanobacterial toxins: risk management for health protection.

Authors:  Geoffrey A Codd; Louise F Morrison; James S Metcalf
Journal:  Toxicol Appl Pharmacol       Date:  2005-03-15       Impact factor: 4.219

3.  Detection and estimation of potentially toxic cyanobacteria in raw water at the drinking water treatment plant by in vivo fluorescence method.

Authors:  Jakub Gregor; Blahoslav Marsálek; Helena Sípková
Journal:  Water Res       Date:  2006-10-02       Impact factor: 11.236

4.  Lytic organisms and photooxidative effects: influence on blue-green algae (cyanobacteria) in lake mendota, wisconsin.

Authors:  R D Fallon; T D Brock
Journal:  Appl Environ Microbiol       Date:  1979-09       Impact factor: 4.792

5.  Measurement of cyanobacteria using in-vivo fluoroscopy -- effect of cyanobacterial species, pigments, and colonies.

Authors:  De-Wei Chang; Peter Hobson; Michael Burch; Tsair-Fuh Lin
Journal:  Water Res       Date:  2012-07-07       Impact factor: 11.236

6.  Remote estimation of phycocyanin (PC) for inland waters coupled with YSI PC fluorescence probe.

Authors:  Kaishan Song; Lin Li; Lenore Tedesco; Nicole Clercin; Bob Hall; Shuai Li; Kun Shi; Dawei Liu; Ying Sun
Journal:  Environ Sci Pollut Res Int       Date:  2013-02-10       Impact factor: 4.223

7.  A fluorometric method for the differentiation of algal populations in vivo and in situ.

Authors:  M Beutler; K H Wiltshire; B Meyer; C Moldaenke; C Lüring; M Meyerhöfer; U-P Hansen; H Dau
Journal:  Photosynth Res       Date:  2002       Impact factor: 3.573

8.  Alternative alert system for cyanobacterial bloom, using phycocyanin as a level determinant.

Authors:  Chi-Yong Ahn; Seung-Hyun Joung; Sook-Kyoung Yoon; Hee-Mock Oh
Journal:  J Microbiol       Date:  2007-04       Impact factor: 3.422

9.  Complementary chromatic adaptation in a filamentous blue-green alga.

Authors:  A Bennett; L Bogorad
Journal:  J Cell Biol       Date:  1973-08       Impact factor: 10.539

10.  High levels of structural diversity observed in microcystins from Microcystis CAWBG11 and characterization of six new microcystin congeners.

Authors:  Jonathan Puddick; Michèle R Prinsep; Susanna A Wood; Sangata A F Kaufononga; Stephen Craig Cary; David P Hamilton
Journal:  Mar Drugs       Date:  2014-11-13       Impact factor: 5.118

View more
  5 in total

1.  Accuracy of data buoys for measurement of cyanobacteria, chlorophyll, and turbidity in a large lake (Lake Erie, North America): implications for estimation of cyanobacterial bloom parameters from water quality sonde measurements.

Authors:  Justin D Chaffin; Douglas D Kane; Keara Stanislawczyk; Eric M Parker
Journal:  Environ Sci Pollut Res Int       Date:  2018-06-25       Impact factor: 4.223

Review 2.  Microbial biosensors for recreational and source waters.

Authors:  H D Alan Lindquist
Journal:  J Microbiol Methods       Date:  2020-09-15       Impact factor: 2.363

3.  The Lake Erie HABs Grab: A binational collaboration to characterize the western basin cyanobacterial harmful algal blooms at an unprecedented high-resolution spatial scale.

Authors:  Justin D Chaffin; John F Bratton; Edward M Verhamme; Halli B Bair; Amber A Beecher; Caren E Binding; Johnna A Birbeck; Thomas B Bridgeman; Xuexiu Chang; Jill Crossman; Warren J S Currie; Timothy W Davis; Gregory J Dick; Kenneth G Drouillard; Reagan M Errera; Thijs Frenken; Hugh J MacIsaac; Andrew McClure; R Michael McKay; Laura A Reitz; Jorge W Santo Domingo; Keara Stanislawczyk; Richard P Stumpf; Zachary D Swan; Brenda K Snyder; Judy A Westrick; Pengfei Xue; Colleen E Yancey; Arthur Zastepa; Xing Zhou
Journal:  Harmful Algae       Date:  2021-07-23       Impact factor: 5.905

4.  Preparation and Properties of Cyanobacteria-Based Carbon Quantum Dots/Polyvinyl Alcohol/ Nanocellulose Composite.

Authors:  Li Xu; Ying Li; Shiyu Gao; Yue Niu; Huaxuan Liu; Changtong Mei; Jiabin Cai; Changyan Xu
Journal:  Polymers (Basel)       Date:  2020-05-17       Impact factor: 4.329

5.  Chlorophyll soft-sensor based on machine learning models for algal bloom predictions.

Authors:  Alberto Mozo; Jesús Morón-López; Stanislav Vakaruk; Ángel G Pompa-Pernía; Ángel González-Prieto; Juan Antonio Pascual Aguilar; Sandra Gómez-Canaval; Juan Manuel Ortiz
Journal:  Sci Rep       Date:  2022-08-08       Impact factor: 4.996

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.