Seasonal Dynamics of Photosynthetic Picoeukaryotes in a Monsoon-Influenced Tropical Bay: a Flow Cytometric and Chemotaxonomic Approach.
Smita MitbavkarSamantha D'souzaPublished in: Microbial ecology (2022)
The composition and ecology of photosynthetic picoeukaryotes (PPE) are essential for understanding microbial food web functioning. We hypothesize that the simultaneous use of flow cytometry (FCM) and high-performance liquid chromatography (HPLC) tools will aid in discerning the dominant PPE groups contributing to abundance and biomass under prevailing environmental conditions. The PPE seasonal community abundance and pigment biomass were investigated from a southwest monsoon-influenced tropical bay from June 2015 to May 2016. A size-fractionated (<3 µm) approach using FCM and HPLC revealed five and six PPE groups, respectively. Picocryptophytes dominated the PPE biomass under varied environmental conditions, whereas picodiatoms contributed substantially, being abundant under turbulent, low-temperature, nutrient (NO 3 - , SiO 4 4- )-enriched conditions. The picochlorophytes dominated the community numerically. The relatively higher abundance and biomass of picoprasinophytes and a positive correlation with NO 3 - and NH 4 + imply proliferation under higher nutrient concentrations. The least contributors to biomass were dinoflagellates and picoprymnesiophytes. The relatively larger cell size of picocryptophytes and picodiatoms resulted in higher cumulative biomass, signifying their role in the microbial food web. Our study proposes incorporation of additional indicator pigments in algorithms used to estimate coastal picophytoplankton contribution to total phytoplankton biomass to avoid discrepancies.
Keyphrases
- wastewater treatment
- high performance liquid chromatography
- anaerobic digestion
- antibiotic resistance genes
- simultaneous determination
- climate change
- ms ms
- flow cytometry
- human health
- tandem mass spectrometry
- solid phase extraction
- healthcare
- mass spectrometry
- machine learning
- single cell
- stem cells
- risk assessment
- bone marrow
- deep learning
- cell therapy
- heavy metals
- ionic liquid