Unité Molécules de Communication et Adaptation des Microorganismes (MCAM, UMR 7245), Muséum National d'Histoire Naturelle, CNRS, Case 39, 57 Rue Cuvier, 75005, Paris, France; INRA, IEES Paris, Université Pierre et Marie Curie (UPMC), 4 Place Jussieu, 75005, Paris, France.
Unité Molécules de Communication et Adaptation des Microorganismes (MCAM, UMR 7245), Muséum National d'Histoire Naturelle, CNRS, Case 39, 57 Rue Cuvier, 75005, Paris, France.
Water Res. 2016 Sep 15;101:341-350. doi: 10.1016/j.watres.2016.05.081. Epub 2016 May 27.
Over the last decade reports of animal poisoning following accidental consumption of neurotoxin-producing benthic cyanobacteria (mainly Phormidium spp.) have increased. There is a need for rapid and cost-effective tools to survey benthic cyanobacteria. In this study we assessed the performance of the BenthoTorch, a fluorometric probe that provides in situ estimations of cyanobacteria, diatoms and green algae biomass in biofilms. Biofilms (n = 288) were analysed from two rivers in France and eight in New Zealand. Correlations between chlorophyll-a measured using the BenthoTorch and spectrophotometry were higher for thin (<2 mm) compared to thick (>2 mm) biofilms (r(2) = 0.58 and 0.27 respectively; p < 0.001). When cyanobacteria represented less than 50% of the total biomass (based on biovolumes), microscopic and BenthoTorch compositional estimations were significantly correlated (r(2) = 0.53, p < 0.001). Conversely, there was no correlation when cyanobacteria exceeded 50% of the total biomass. Under this scenario diatoms were overestimated. Our results suggest that the observed biases occur because the BenthoTorch only measures the upper biofilm layer and it underestimates the biomass of phycoerythrin-containing cyanobacteria. To improve the performance of this sensor and render it a useful tool for a rapid evaluation of benthic cyanobacterial biomass in rivers, we propose that: (i) the algorithms based on the LEDs responses currently available on this tool need revision, (ii) new excitation wavelengths should be included that allow the fingerprints of phycoerythrin-containing cyanobacteria to be discriminated, and (iii) a sensor that penetrates the biofilms is needed to obtain more accurate estimates of cyanobacterial biomass.
在过去的十年中,有越来越多的关于动物误食产生神经毒素的底栖蓝藻(主要为 Phormidium 属)而中毒的报告。因此,我们需要快速且具有成本效益的工具来调查底栖蓝藻。本研究评估了 BenthoTorch 的性能,BenthoTorch 是一种荧光探针,可提供生物膜中蓝藻、硅藻和绿藻生物量的原位估计。从法国的两条河和新西兰的八条河中分析了生物膜(n=288)。与分光光度法相比,BenthoTorch 测量的叶绿素 a 与薄(<2mm)生物膜的相关性更高(r2分别为 0.58 和 0.27;p<0.001)。当蓝藻占总生物量的比例小于 50%(基于生物体积)时,显微镜和 BenthoTorch 组成估计值显著相关(r2=0.53,p<0.001)。相反,当蓝藻超过总生物量的 50%时,就没有相关性。在这种情况下,硅藻被高估了。我们的结果表明,观察到的偏差是因为 BenthoTorch 仅测量上层生物膜层,并且低估了含有藻红蛋白的蓝藻的生物量。为了提高该传感器的性能并使其成为快速评估河流中底栖蓝藻生物量的有用工具,我们建议:(i)目前可在该工具上使用的基于 LED 响应的算法需要修订,(ii)应包括新的激发波长,以区分含有藻红蛋白的蓝藻的指纹,以及(iii)需要一种穿透生物膜的传感器,以更准确地估计蓝藻生物量。