971 resultados para Bacterial-dna


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Background Urinary tract infections (UTI) are frequent in outpatients. Fast pathogen identification is mandatory for shortening the time of discomfort and preventing serious complications. Urine culture needs up to 48 hours until pathogen identification. Consequently, the initial antibiotic regimen is empirical. Aim To evaluate the feasibility of qualitative urine pathogen identification by a commercially available real-time PCR blood pathogen test (SeptiFast®) and to compare the results with dipslide and microbiological culture. Design of study Pilot study with prospectively collected urine samples. Setting University hospital. Methods 82 prospectively collected urine samples from 81 patients with suspected UTI were included. Dipslide urine culture was followed by microbiological pathogen identification in dipslide positive samples. In parallel, qualitative DNA based pathogen identification (SeptiFast®) was performed in all samples. Results 61 samples were SeptiFast® positive, whereas 67 samples were dipslide culture positive. The inter-methodological concordance of positive and negative findings in the gram+, gram- and fungi sector was 371/410 (90%), 477/492 (97%) and 238/246 (97%), respectively. Sensitivity and specificity of the SeptiFast® test for the detection of an infection was 0.82 and 0.60, respectively. SeptiFast® pathogen identifications were available at least 43 hours prior to culture results. Conclusion The SeptiFast® platform identified bacterial DNA in urine specimens considerably faster compared to conventional culture. For UTI diagnosis sensitivity and specificity is limited by its present qualitative setup which does not allow pathogen quantification. Future quantitative assays may hold promise for PCR based UTI pathogen identification as a supplementation of conventional culture methods.

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Background Inappropriate cross talk between mammals and their gut microbiota may trigger intestinal inflammation and drive extra-intestinal immune-mediated diseases. Epithelial cells constitute the interface between gut microbiota and host tissue, and may regulate host responses to commensal enteric bacteria. Gnotobiotic animals represent a powerful approach to study bacterial-host interaction but are not readily accessible to the wide scientific community. We aimed at refining a protocol that in a robust manner would deplete the cultivable intestinal microbiota of conventionally raised mice and that would prove to have significant biologic validity. Methodology/Principal Findings Previously published protocols for depleting mice of their intestinal microbiota by administering broad-spectrum antibiotics in drinking water were difficult to reproduce. We show that twice daily delivery of antibiotics by gavage depleted mice of their cultivable fecal microbiota and reduced the fecal bacterial DNA load by 400 fold while ensuring the animals' health. Mice subjected to the protocol for 17 days displayed enlarged ceca, reduced Peyer's patches and small spleens. Antibiotic treatment significantly reduced the expression of antimicrobial factors to a level similar to that of germ-free mice and altered the expression of 517 genes in total in the colonic epithelium. Genes involved in cell cycle were significantly altered concomitant with reduced epithelial proliferative activity in situ assessed by Ki-67 expression, suggesting that commensal microbiota drives cellular proliferation in colonic epithelium. Conclusion We present a robust protocol for depleting conventionally raised mice of their cultivatable intestinal microbiota with antibiotics by gavage and show that the biological effect of this depletion phenocopies physiological characteristics of germ-free mice.

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PURPOSE: The low diagnostic yield of vitrectomy specimen analysis in chronic idiopathic uveitis (CIU) has been related to the complex nature of the underlying disease and to methodologic and tissue immanent factors in older studies. In an attempt to evaluate the impact of recently acquired analytic methods, the authors assessed the current diagnostic yield in CIU. METHODS: Retrospective analysis of consecutive vitrectomy specimens from patients with chronic endogenous uveitis (n = 56) in whom extensive systemic workup had not revealed a specific diagnosis (idiopathic) and medical treatment had not resulted in a satisfying clinical situation. Patients with acute postoperative endophthalmitis served a basis for methodologic comparison (Group 2; n = 21). RESULTS: In CIU, a specific diagnosis provided in 17.9% and a specific diagnosis excluded in 21.4%. In 60.7% the laboratory investigations were inconclusive. In postoperative endophthalmitis, microbiological culture established the infectious agent in 47.6%. In six of eight randomly selected cases, eubacterial PCR identified bacterial DNA confirming the culture results in three, remaining negative in two with a positive culture and being positive in three no growth specimens. A double negative result never occurred, suggesting a very high detection rate, when both tests were applied. CONCLUSIONS: The diagnostic yield of vitrectomy specimen analysis has not been improved by currently routinely applied methods in recent years in contrast to the significantly improved sensitivity of combined standardized culture and PCR analysis in endophthalmitis. Consequently, the low diagnostic yield in CIU has to be attributed to insufficient understanding of the underlying pathophysiologic mechanisms.

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Here we determined the analytical sensitivities of broad-range real-time PCR-based assays employing one of three different genomic DNA extraction protocols in combination with one of three different primer pairs targeting the 16S rRNA gene to detect a panel of 22 bacterial species. DNA extraction protocol III, using lysozyme, lysostaphin, and proteinase K, followed by PCR with the primer pair Bak11W/Bak2, giving amplicons of 796 bp in length, showed the best overall sensitivity, detecting DNA of 82% of the strains investigated at concentrations of < or =10(2) CFU in water per reaction. DNA extraction protocols I and II, using less enzyme treatment, combined with other primer pairs giving shorter amplicons of 466 bp and 342 or 346 bp, respectively, were slightly more sensitive for the detection of gram-negative but less sensitive for the detection of gram-positive bacteria. The obstacle of detecting background DNA in blood samples spiked with bacteria was circumvented by introducing a broad-range hybridization probe, and this preserved the minimal detection limits observed in samples devoid of blood. Finally, sequencing of the amplicons generated using the primer pair Bak11W/Bak2 allowed species identification of the detected bacterial DNA. Thus, broad-spectrum PCR targeting the 16S rRNA gene in the quantitative real-time format can achieve an analytical sensitivity of 1 to 10 CFU per reaction in water, avoid detection of background DNA with the introduction of a broad-range probe, and generate amplicons that allow species identification of the detected bacterial DNA by sequencing. These prerequisites are important for its application to blood-containing patient samples.

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Background: Periodontitis and caries are common diseases in older adults. Aims: To test if rinsing with chlorhexidine over five years has an impact on the subgingival microbiota. Methods: In a double blind randomized five years chlorhexidine rinse study clinical oral data and subgingival plaque samples were analyzed by the checkerboard DNA-DNA hybridization method. Results: At year 5 subject mean age was 71.2 years (S.D. + 4.1) (56.2% women). Only in subjects with no bone loss did the chlorhexidine rinse group subjects presented with lower total bacterial (DNA) counts (mean diff: 63.1 (x105), S.E diff + 30.1 (x105), 95%CI: 0.8 to 120.5 (x105), p<0.05) [(i.e.Lactobacillus acidophilicus (p<0.05) , Streptococcus oralis (p<0.05), Eikenella. corrodens (p< 0.05), C. gracilis (p<0.01), F.nucl.sp. nucleatum (p< 0.02), Fusobacterium nucl. sp. polymorphum (p<0.02), Neisseria mucosa (p<0.02), Leptothrichia buccalis (p<0.02), and Selenomonas noxia (p<0.050)]. Higher bacterial loads were found for the green (p<0.05), yellow (streptococci spp) (p<0.01), and the ‘other' complexes (p<0.01). Conclusions: Independent of probing pocket depth, older subjects carry a large variety of bacteria associated with periodontitis. The oral microbiota in older subjects is linked to alveolar bone loss and not to probing depth. Chlorhexidine may provide a benefit in preventing periodontitis in older persons.

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Molecular diagnosis of canine bartonellosis can be extremely challenging and often requires the use of an enrichment culture approach followed by PCR amplification of bacterial DNA. HYPOTHESES: (1) The use of enrichment culture with PCR will increase molecular detection of bacteremia and will expand the diversity of Bartonella species detected. (2) Serological testing for Bartonella henselae and Bartonella vinsonii subsp. berkhoffii does not correlate with documentation of bacteremia. ANIMALS: Between 2003 and 2009, 924 samples from 663 dogs were submitted to the North Carolina State University, College of Veterinary Medicine, Vector Borne Diseases Diagnostic Laboratory for diagnostic testing with the Bartonella α-Proteobacteria growth medium (BAPGM) platform. Test results and medical records of those dogs were retrospectively reviewed. METHODS: PCR amplification of Bartonella sp. DNA after extraction from patient samples was compared with PCR after BAPGM enrichment culture. Indirect immunofluorescent antibody assays, used to detect B. henselae and B. vinsonii subsp. berkhoffii antibodies, were compared with PCR. RESULTS: Sixty-one of 663 dogs were culture positive or had Bartonella DNA detected by PCR, including B. henselae (30/61), B. vinsonii subsp. berkhoffii (17/61), Bartonella koehlerae (7/61), Bartonella volans-like (2/61), and Bartonella bovis (2/61). Coinfection with more than 1 Bartonella sp. was documented in 9/61 dogs. BAPGM culture was required for PCR detection in 32/61 cases. Only 7/19 and 4/10 infected dogs tested by IFA were B. henselae and B. vinsonii subsp. berkhoffii seroreactive, respectively. CONCLUSIONS AND CLINICAL IMPORTANCE: Dogs were most often infected with B. henselae or B. vinsonii subsp. berkhoffii based on PCR and enrichment culture, coinfection was documented, and various Bartonella species were identified. Most infected dogs did not have detectable Bartonella antibodies.

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Musculoskeletal infections are infections of the bone and surrounding tissues. They are currently diagnosed based on culture analysis, which is the gold standard for pathogen identification. However, these clinical laboratory methods are frequently inadequate for the identification of the causative agents, because a large percentage (25-50%) of confirmed musculoskeletal infections are false negatives in which no pathogen is identified in culture. My data supports these results. The goal of this project was to use PCR amplification of a portion of the 16S rRNA gene to test an alternative approach for the identification of these pathogens and to assess the diversity of the bacteria involved. The advantages of this alternative method are that it should increase sample sensitivity and the speed of detection. In addition, bacteria that are non-culturable or in low abundance can be detected using this molecular technique. However, a complication of this approach is that the majority of musculoskeletal infections are polymicrobial, which prohibits direct identification from the infected tissue by DNA sequencing of the initial 16S rDNA amplification products. One way to solve this problem is to use denaturing gradient gel electrophoresis (DGGE) to separate the PCR products before DNA sequencing. Denaturing gradient gel electrophoresis (DGGE) separates DNA molecules based on their melting point, which is determined by their DNA sequence. This analytical technique allows a mixture of PCR products of the same length that electrophoreses through agarose gels as one band, to be separated into different bands and then used for DNA sequence analysis. In this way, the DGGE allows for the identification of individual bacterial species in polymicrobial-infected tissue, which is critical for improving clinical outcomes. By combining the 16S rDNA amplification and the DGGE techniques together, an alternative approach for identification has been used. The 16S rRNA gene PCR-DGGE method includes several critical steps: DNA extraction from tissue biopsies, amplification of the bacterial DNA, PCR product separation by DGGE, amplification of the gel-extracted DNA, and DNA sequencing and analysis. Each step of the method was optimized to increase its sensitivity and for rapid detection of the bacteria present in human tissue samples. The limit of detection for the DNA extraction from tissue was at least 20 Staphylococcus aureus cells and the limit of detection for PCR was at least 0.05 pg of template DNA. The conditions for DGGE electrophoreses were optimized by using a double gradient of acrylamide (6 – 10%) and denaturant (30-70%), which increased the separation between distinct PCR products. The use of GelRed (Biotium) improved the DNA visualization in the DGGE gel. To recover the DNA from the DGGE gels the gel slices were excised, shredded in a bead beater, and the DNA was allowed to diffuse into sterile water overnight. The use of primers containing specific linkers allowed the entire amplified PCR product to be sequenced and then analyzed. The optimized 16S rRNA gene PCR-DGGE method was used to analyze 50 tissue biopsy samples chosen randomly from our collection. The results were compared to those of the Memorial Hermann Hospital Clinical Microbiology Laboratory for the same samples. The molecular method was congruent for 10 of the 17 (59%) culture negative tissue samples. In 7 of the 17 (41%) culture negative the molecular method identified a bacterium. The molecular method was congruent with the culture identification for 7 of the 33 (21%) positive cultured tissue samples. However, in 8 of the 33 (24%) the molecular method identified more organisms. In 13 of the 15 (87%) polymicrobial cultured tissue samples the molecular method identified at least one organism that was also identified by culture techniques. Overall, the DGGE analysis of 16S rDNA is an effective method to identify bacteria not identified by culture analysis.

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Attention has recently been drawn to Enterococcus faecium because of an increasing number of nosocomial infections caused by this species and its resistance to multiple antibacterial agents. However, relatively little is known about the pathogenic determinants of this organism. We have previously identified a cell-wall-anchored collagen adhesin, Acm, produced by some isolates of E. faecium, and a secreted antigen, SagA, exhibiting broad-spectrum binding to extracellular matrix proteins. Here, we analysed the draft genome of strain TX0016 for potential microbial surface components recognizing adhesive matrix molecules (MSCRAMMs). Genome-based bioinformatics identified 22 predicted cell-wall-anchored E. faecium surface proteins (Fms), of which 15 (including Acm) had characteristics typical of MSCRAMMs, including predicted folding into a modular architecture with multiple immunoglobulin-like domains. Functional characterization of one [Fms10; redesignated second collagen adhesin of E. faecium (Scm)] revealed that recombinant Scm(65) (A- and B-domains) and Scm(36) (A-domain) bound to collagen type V efficiently in a concentration-dependent manner, bound considerably less to collagen type I and fibrinogen, and differed from Acm in their binding specificities to collagen types IV and V. Results from far-UV circular dichroism measurements of recombinant Scm(36) and of Acm(37) indicated that these proteins were rich in beta-sheets, supporting our folding predictions. Whole-cell ELISA and FACS analyses unambiguously demonstrated surface expression of Scm in most E. faecium isolates. Strikingly, 11 of the 15 predicted MSCRAMMs clustered in four loci, each with a class C sortase gene; nine of these showed similarity to Enterococcus faecalis Ebp pilus subunits and also contained motifs essential for pilus assembly. Antibodies against one of the predicted major pilus proteins, Fms9 (redesignated EbpC(fm)), detected a 'ladder' pattern of high-molecular-mass protein bands in a Western blot analysis of cell surface extracts from E. faecium, suggesting that EbpC(fm) is polymerized into a pilus structure. Further analysis of the transcripts of the corresponding gene cluster indicated that fms1 (ebpA(fm)), fms5 (ebpB(fm)) and ebpC(fm) are co-transcribed, a result consistent with those for pilus-encoding gene clusters of other Gram-positive bacteria. All 15 genes occurred frequently in 30 clinically derived diverse E. faecium isolates tested. The common occurrence of MSCRAMM- and pilus-encoding genes and the presence of a second collagen-binding protein may have important implications for our understanding of this emerging pathogen.

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Enterococcus faecium recently evolved from a generally avirulent commensal into a multidrug-resistant health care-associated pathogen causing difficult-to-treat infections, but little is known about the factors responsible for this change. We previously showed that some E. faecium strains express a cell wall-anchored collagen adhesin, Acm. Here we analyzed 90 E. faecium isolates (99% acm(+)) and found that the Acm protein was detected predominantly in clinically derived isolates, while the acm gene was present as a transposon-interrupted pseudogene in 12 of 47 isolates of nonclinical origin. A highly significant association between clinical (versus fecal or food) origin and collagen adherence (P

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Enterococcus faecium has recently emerged as an important cause of nosocomial infections. We previously identified 15 predicted surface proteins with characteristics of MSCRAMMs and/or pili and demonstrated that their genes were frequently present in 30 clinical E. faecium isolates studied; one of these, acm, has been studied in further detail. To determine the prevalence of the other 14 genes among various E. faecium populations, we have now assessed 433 E. faecium isolates, including 264 isolates from human clinical infections, 69 isolates from stools of hospitalized patients, 70 isolates from stools of community volunteers, and 30 isolates from animal-related sources. A variable distribution of the 14 genes was detected, with their presence ranging from 51% to 98% of isolates. While 81% of clinical isolates carried 13 or 14 of the 14 genes tested, none of the community group isolates and only 13% of animal isolates carried 13 or 14 genes. The presence of these genes was most frequent in endocarditis isolates, with 11 genes present in all isolates, followed by isolates from other clinical sources. The number of genes significantly associated with clinical versus fecal or animal origin (P = 0.04 to <0.0001) varied from 10 to 13, depending on whether comparisons were made against individual clinical subgroups (endocarditis, blood, and other clinical isolates) or against all clinical isolates combined as one group. The strong association of these genes with clinical isolates raises the possibility that their preservation/acquisition has favored the adaptation of E. faecium to nosocomial environments and/or patients.

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Cathelicidins constitute potent antimicrobial peptides characterized by a high cationic charge that enables strong interactions with nucleic acids. In fact, the only human cathelicidin LL-37 triggers rapid sensing of nucleic acids by plasmacytoid dendritic cells (pDC). Among the porcine cathelicidins, phylogenetic analysis of the C-terminal mature peptide showed that porcine myeloid antimicrobial peptide (PMAP)-36 was the most closely related of the 11 porcine cathelicidins to human LL-37. Despite several investigations evaluating potent antimicrobial functions of porcine cathelicidins, nothing is known about their ability to promote pDC activation. We therefore investigated the capacity of the proline-arginine-rich 39-aa peptide, PMAP-23, PMAP-36, and protegrin-1 to complex with bacterial DNA or synthetic RNA molecules and facilitate pDC activation. We demonstrate that these peptides mediate a rapid and efficient uptake of nucleic acids within minutes, followed by robust IFN-α responses. The highest positively charged cathelicidin, PMAP-36, was found to be the most potent peptide tested for this effect. The peptide-DNA complexes were internalized and also found to associate with the cell membranes of pDC. The amphipathic conformation typical of PMAP-36 was not required for IFN-α induction in pDC. We also demonstrate that PMAP-36 can mediate IFN-α induction in pDC stimulated by Escherichia coli, which alone fail to activate pDC. This response was weaker with a scrambled PMAP-36, relating to its lower antimicrobial activity. Collectively, our data suggest that the antimicrobial and nucleic acid-complexing properties of cathelicidins can mediate pDC activation-promoting adaptive immune responses against microbial infections.

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Background. Large field studies in travelers' diarrhea (TD) in multiple destinations are limited by the need to perform stool cultures on site in a timely manner. A method for the collection, transport and storage of fecal specimens that does not require immediate processing, refrigeration and is stable for months would be advantageous. ^ Objectives. Determine if enteric pathogen bacterial DNA can be identified in cards routinely used for evaluation of fecal occult blood. ^ Methods. U.S. students traveling to Mexico in 2005-07 were followed for occurrence of diarrheal illness. When ill, students provided a stool specimen for culture and occult blood by the standard method. Cards were then stored at room temperature prior to DNA extraction. A multiplex fecal PCR was performed to identify enterotoxigenic Escherichia coli and enteroaggregative E. coli (EAEC) in DNA extracted from stools and occult blood cards. ^ Results. Significantly more EAEC cases were identified by PCR done in DNA extracted from cards (49%) or from frozen feces (40%) than by culture followed by HEp-2 adherence assays (13%). Similarly more ETEC cases were detected in card DNA (38%) than fecal DNA (30%) or culture followed by hybridization (10%). Sensitivity and specificity of the card test was 75% and 62%, respectively, and 50% and 63%, respectively, when compared to EAEC and ETEC culture, respectively, and 53% and 51%, respectively compared to EAEC multiplex fecal PCR and 56% and 70%, respectively, compared to ETEC multiplex fecal PCR. ^ Conclusions. DNA extracted from fecal cards used for detection of occult blood is of use in detecting enteric pathogens. ^

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The dataset is based on samples collected in the framework of the project SESAME, in the Ionian, Libyan and Aegean Sea during March- 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. 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).

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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).