Concentration of dissolved phosphates and total phosphorus in seawater near the Cape Utrish, Black Sea

Dynamics of growth of natural phytoplankton and bacterioplankton in deep seawater upwelled to the upper sea layer were studied. Seawater from the lower part of the aerobic zone of the Black Sea was shown to have high bio-productive potential and can be used as an environment for algae and bacteria cultivation.

Abundance and Biomass from heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus in the Aegean Sea in April 2008 during SES_GR1

The HCMR_SES_LAGRANGIAN_GR1_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during April 2008. The objectives were to measure the standing stocks and calculate the production of the microbial compartment of the food web, describe the vertical distribution pattern and characterize its structure and function through the water column as influenced by the BSW. Heterotrophic bacteria, Synechococcus, Prochlorococcus and Virus abundance: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Heterotrophic Nanoflagellate abundance: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Ciliate abundance: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Heterotrophic bacteria, Synechococcus, Prochlorococcus biomass: Subsamples for virus, heterotrophic bacteria and cyanobacteria (Synechococcus spp. and Prochlorococcus spp.) counting were analyzed using a FACSCalibur (Becton Dickinson) flow cytometer equipped with a standard laser (488 nm) and filter set and using deionized water as sheath fluid. Fluorescent beads with a diameter of 0.97 µm (Polysciences) were added to each sample as an internal standard, and all parameters were normalized to the beads and expressed as relative units. SYBRGreen I stain (Molecular Probe) was used to stain viral and heterotrophic bacterial DNA. Viruses were counted according to (Brussaard 1984). In order to avoid bulk consentrations of viruses samples we dilluted to Tris-EDTA (pH=8,0) buffer to a final sollution of 1/5 to 1/100. Total abundance and nucleid content classes were calculated using the Paint-A-Gate software (Becton Dickinson). Abundance data were converted into C biomass using 250 fgC cell-1 (Kana & Glibert 1987) for Synechococcus, 50 fgC cell-1 (Campbell et al. 1994) for Prochlorococcus and 20fgC cell-1 (Lee & Fuhrman 1987) for heterotrophic bacteria. Heterotrophic Nanoflagellate biomass: Subsamples (30-150 ml) were concentrated on 25mm black polycarbonate filters of porosity 0.6µm and stained with DAPI for 10 min (Porter and Feig 1980). Under epifluorescence microscopy heterotrophic nanoflagellates (HNAN) were distinguished using UV and blue excitation and enumerated. Nanoflagellates were classified in size categories and the biovolume was calculated. Abundance data were converted into C biomass using 183 fgC µm**3 (Caron et al. 1995). Ciliate biomass: For ciliate identification and enumeration, 100-3000 ml samples were left for 24h-4d for sedimentation and then observed under an inverted microscope. Ciliates were counted, distinguished into size-classes and major taxonomic groups and identified down to genus or species level where possible (Pitta et al. 2005). Ciliate cell sizes were measured and converted into cell volumes using appropriate geometric formulae using image analysis. For biomass estimation, the conversion factor 190 fgC µm**3 was used (Putt and Stoecker 1989).

Comparison of fecal indicators with pathogenic bacteria and rotavirus in rural Bangladesh groundwater

Groundwater is routinely analyzed for fecal indicators but direct comparisons of fecal indicators to the presence of bacterial and viral pathogens are rare. This study was conducted in rural Bangladesh where the human population density is high, sanitation is poor, and groundwater pumped from shallow tubewells is often contaminated with fecal bacteria. Five indicator microorganisms (E. coli, total coliform, F+RNA coliphage, Bacteroides and human-associated Bacteroides (HuBacteroides)) and various environmental parameters were compared to the direct detection of waterborne pathogens by quantitative PCR in groundwater pumped from 50 tubewells. Rotavirus was detected in groundwater filtrate from the largest proportion of tubewells (40%), followed by Shigella (10%), Vibrio (10%), and pathogenic E. coli (8%). Spearman rank correlations and sensitivity-specificity calculations indicate that some, but not all, combinations of indicators and environmental parameters can predict the presence of pathogens. Culture-dependent fecal indicator bacteria measured on a single date did not predict bacterial pathogens, but annually averaged monthly measurements of culturable E. coli did improve prediction for total bacterial pathogens. F+RNA coliphage were neither correlated nor sufficiently sensitive towards rotavirus, but were predictive of bacterial pathogens. A qPCR-based E. coli assay was the best indicator for the bacterial pathogens, rotavirus and all pathogens combined. Since groundwater cannot be excluded as a significant source of diarrheal disease in Bangladesh and neighboring countries with similar characteristics, the need to develop more effective methods for screening tubewells with respect to microbial contamination is necessary.