34 resultados para Bacteria (microorganisms)

em Publishing Network for Geoscientific


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Microorganisms play an important role in the transformation of material within the earth's crust. The storage of CO2 could affect the composition of inorganic and organic components in the reservoir, consequently influencing microbial activities. To study the microbial induced processes together with geochemical, petrophysical and mineralogical changes, occurring during CO2 storage, long-term laboratory experiments under simulated reservoir P-T conditions were carried out. Clean inner core sections, obtained from the reservoir region at the CO2 storage site in Ketzin (Germany) from a depth of about 650 m, were incubated in high pressure vessels together with sterile synthetic formation brine under in situ P-T conditions of 5.5 MPa and 40°C. A 16S rDNA based fingerprinting method was used to identify the dominant species in DNA extracts of pristine sandstone samples. Members of the alpha- and beta-subdivisions of Proteobacteria and the Actinobacteria were identified. So far sequences belonging to facultative anaerobic, chemoheterotrophic bacteria (Burkholderia fungorum, Agrobacterium tumefaciens) gaining their energy from the oxidation of organic molecules and a genus also capable of chemolithoautotrophic growth (Hydrogenophaga) was identified. During CO2 incubation minor changes in the microbial community composition were observed. The majority of microbes were able to adapt to the changed conditions. During CO2 exposure increased concentrations of Ca**2+, K**+, Mg**2+ and SO4**2- were observed. Partially, concentration rises are (i) due to equilibration between rock pore water and synthetic brine, and (ii) between rock and brine, and are thus independent on CO2 exposure. However, observed concentrations of Ca**2+, K**+, Mg**2+ are even higher than in the original reservoir fluid and therefore indicate mineral dissolution due to CO2 exposure.

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Bacterioplankton in the photic layer of the Sodruzhestvo Sea area and adjoining waters consists in summer primarily of cocci, with fractions smaller than 2 ?m predominating. The average abundance and biomass of microorganisms are 427 thousand cells/ml and 438 mg C/m**2, with ranges of 150-1770 thousand cells/ml and 221-1146 mg C/m**2. The average daily production and bacterial destruction increase from 49 and 104 mg C/m**2 at the beginning of the growth period to 85 and 180 mg C/m**2 in the middle of the period and remain at this level till the end. Despite low rate of increase (daily P/B coefficient averages 0.12), because of its high abundance bacterioplankton in Antarctic waters plays a major role in destruction of organic matter, accounting for 60-85% of energy consumed by heterotrophs.

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We determined the numbers of free-living and associated (aggregated or bonded with particles) bacteria in the coastal water of King George Island at an offshore (St. 1) and a nearshore station (St. 2) as a function of physico-chemical parameters. Water sampIes were collected between March and October at St. 1 and between April and October at St. 2. Direct counts of total bacteria varied from 0.53*10**8 to 5.02*10**8 cells/l. Associated microorganisms accounted for 5 to 20 % of the total number of bacteria. Strong Spearman and Pearson correlations were observed (R = 0.82; P = 0.001) between the numbers of free-living and associated bacteria at St. 1. These two groups of bacteria were nearly evenly distributed in the horizontal transects from inshore to offshore waters at depths of 1-10 m in Ardley Cove. There were no substantial differences in the numbers of either free-living or associated bacteria in vertical transects too. Their number at St. 1, but not at St. 2, correlated significantly with all tested environmental parameters (salinity, temperature, solar radiation, nitrate, phosphate and chlorophyll a concentrations), except nitrite concentrations in water. The most probable reason for these correlations is that a common seasonal trend is characteristic of most tested parameters during the March to October period.

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Diversity of endolithic Dry Valley rock microorganisms was studied by evaluating the presence of morphotypes in enrichments. Storage of rock samples for 16 h over dry ice affected the diversity of endolithic organisms, especially that of algae and fungi. Diversity in various samples depended on rock location and exposure, on the rock type, and to some extent on the pH of the pulverized rock samples. In most cases sandstone contained more morphotypes than dolerite or granite. Presence of many different phototrophs resulted in greater diversity of the heterotrophs in the enrichments. Samples from Linnaeus Terrace and Battleship Promontory had higher morphotype (MT) numbers than those from more exposed sites such as New Mountain, University Valley, Dais, or Mt. Fleming. Beacon sandstone (13 samples) from Linnaeus Terrace varied greatly with respect to MT numbers, although the pH values ranged only from 4.2-5.3. The highest MT number of 24 per sample was obtained from the upper surface of a flat boulder tilted to the North. Only two MT's were found in a hard sandstone sample from the wind-exposed and more shaded east side of the Terrace. 15 sandstone samples from Battleship Promontory contained more diverse populations: there occurred a total of 131 different MT's in these samples as compared to only 68 in Linnaeus Terrace samples. Cysts of colorless flagellates were found in some Battleship Promontory samples; rnost samples were populated with a wealth of different cyanobacteria. Studies on the distribution of actinomycete morphotypes in Linnaeus Terrace sandstone revealed great differences between individual boulders. Identification tests and lipid analyses made with representative strains of the isolated 1500 pure cultures led to genus names such as Caulobacter, Blastobacter, Hyphomicrobium, Micrococcus, Arthrobacter, Brevibacterium, Corynebacterium, Bifidobacterium, Mycobacterium, Nocardia (Amycolata), Micromonospora, Streptomyces, Blastococcus, and Deinococcus. Our data demonstrate the great diversity of Antarctic endolithic microbial populations.

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The HCMR_SES_LAGRANGIAN_GR2_ MICROBIAL PARAMETERS dataset is based on samples collected in the framework of the project SESAME, in the North Aegean Sea during October 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 0.6?m 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 bacteria: 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).

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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).