Sections measured from the tree base up to the diameter of approximately check details 7–9 cm in the thinner end of the stem were distinguished on the windfalls: (1) 0.5 m-long sections and (2) sections comprising 10% stem lengths of fallen trees without tops (Fig. 1). 0.5 m-sections distinguished in such a manner so that the last section also equalled 0.5 m and the final diameter was within the range of 7–9 cm. Then, the trees were measured for: (1) the diameter at breast height and diameter over bark in the mid-length of each stem section, (2) the initial

diameter, (3) the final diameter and (4) the total length and the length of the lying tree without top. Fig. 1 a P. abies windfall. b The windfall after branch and top removal; marked are the boundaries of fifty 0.5 m-long sections and the ten 10% stem length sections (length of a fallen tree without

top is 25 m, diameter at the thinner end is 8 cm) The sex ratio and the number of I. typographus maternal galleries were calculated using the method of entomological section-based analysis. It consisted in the removal of bark plates from the successive 0.5 m-long stem sections. To avoid bark damage during its removal the circumference, sides and upper part were incised in the successive sections of the stem. For each 0.5 m-long section two bark pieces from the upper area and one bark piece from the bottom area of the stem were taken. The bark pieces collected from the stems were transported to the laboratory on the same day. In addition to the R428 purchase I. typographus maternal galleries (1) the number of galleries of Pityogenes chalcographus and Ips amitinus, (2) the number of maternal galleries of Hylurgops palliatus and Dryocoetes autographus, (3) the number of entrances of Xyloterus lineatus to wood were counted. The stem form of a coniferous tree can be expressed by Kunze’s equation (Inoue 2006): $$ r = \sqrt bl^c $$ (1)where r is stem radius, l is stem length from tree tip, b and

c are coefficients. The stem surface area s of the tree can be computed by the following Hydroxychloroquine formula: $$ s = 2\pi \int\limits_0^h r\sqrt 1 + \left( \fracdrdl \right)^2 dl $$ (2)where h is the length of the lying tree without top. The total colonisation density of each P. abies stem was calculated: (1) after summing of I. typographus maternal galleries in all 0.5 m-long sections and (2) after calculating the stem surface area. One-way ANOVA followed by post hoc Fisher’s least significant difference (LSD) procedure (α = 0.05) for multiple comparisons was used to analyse differences in I. typographus attack densities in individual sections of windfalls. To determine the relationships between the number of I. typographus maternal galleries in selected 0.5 m-long stem sections and the total density of stem infestation the analyses of correlation and regression were used.

subtilis SigB in response to physical stress. This activation occurs via Obg’s

physical Z-VAD-FMK nmr interaction with upstream Rsb regulators of SigB [16]. Further, the GTP-binding pocket of crystallized Obg of B. subtilis contains guanosine 5′ diphosphate, 3′ phosphate (ppGpp) [16]. ppGpp is a guanosine nucleotide known as an alarmone in bacteria. Alarmones are produced in response to amino acid starvation, and they act as signaling intermediates to slow cell growth or to initiate stress-induced differentiation pathways, including sporulation. In bacteria, the synthesis of ppGpp is performed by two enzymes, called RelA and SpoT [17–19]. In E. coli, SpoT is one of the proteins known to interact with Obg [20]. In V. cholerae, depletion of the Obg homologue CgtA results in a global gene expression pattern reflecting the low-nutrient stress reaction called the “”stringent”" response [21]. In V. cholerae, CgtA interacts with SpoT, and this interaction decreases SpoT

activity leading to the repression of the stringent response [21]. Another interesting example of Obg’s association with stress comes from the pathogen Legionella pneumophila, where its expression is elevated during intracellular survival [22]. Recent studies indicate that Obg associates with ribosomes of bacteria and interacts with ribosomal proteins. In B. subtilis, Obg coelutes with ribosomal proteins and interacts specifically with the ribosomal protein L13, a component of the CYTH4 50 S ribosomal subunit [23]. The Obg orthologues of C. crescentus [24],

V. harveyi [25] and E. coli [20, 26] also cofractionate with the 50 S ribosomal subunit. Finally, bacterial Obg selleck screening library has also been implicated in chromosomal partitioning [11] and replication regulation [27]. Mycobacterium tuberculosis is an intracellular pathogen and causative agent of tuberculosis in humans. The recent emergence of multidrug (MDR-TB) and extremely drug resistant (XTR-TB) M. tuberculosis strains now poses serious threats to people in the developing world [27], and combating the disease requires the development of new anti-tuberculosis drugs. However, design and development of new drugs for TB largely depends upon the identification and characterization of novel drug targets in M. tuberculosis. The fact that Obg is an essential protein for growth in bacteria, including M. tuberculosis [28], and its association with ribosomes makes it a potential target for future antimicrobials [29, 30]. Thus, this study was undertaken to understand the basic properties of Obg of M. tuberculosis. Results and Discussion Overexpressed M. tuberculosis Obg binds to, and hydrolyzes, GTP A single copy of the gene coding for Obg (Rv2440c) is present in the genome of M. tuberculosis, between the genes proB (Rv2439c) and rpmA (Rv2441c). The deduced amino acid sequence of the M. tuberculosis Obg protein shows significant similarities with the Obg proteins of B. subtilis, S. coelicolor and other bacterial species (Additional file 1).

To assure proper adhesion of the deposited material to a Ge-wetted substrate surface and to avoid water ice crystal growth, which leads to the increase of substrate roughness, the system should operate at the lowest possible pressures and all the time on the high temperature side of the p-T diagram shown in Figure 3. Optimum deposition temperature Figure 4 shows temperature-dependent plots of surface

morphology parameters: ten-point height, average height, and RMS roughness values measured using AFM on 30-nm-thick Ag films for deposition at temperatures above that of sublimation. Notice the vertical scale different from that in Figure 2. Within the range 230 to 350 K, RMS roughness has nearly selleck inhibitor the same value. Two other criteria have minimum values at RT. Figure 4 Three surface morphology parameters measured using AFM on 3 × 3 μm 2 area of 30-nm-thick Ag layers. Thin Ag films were deposited on sapphire substrates with Ge wetting monolayer at temperatures in the range 170 to 400 K. The morphology of crystalline 30-nm-thick Ag layers was analyzed using two-dimensional X-ray diffraction (XRD2). The XRD2 pattern from one of the 30-nm-thick Ag samples deposited at 295 K has a bright spot from the double-sided epi-polished

Al2O3 single-crystal substrate oriented in c-plane (0001) and the weak arc from silver nanocrystallites with periodicity 3.88 Å and random orientation in space (see Additional file 1). Similar XRD2 patterns were obtained also for 10-nm-thick Ag films deposited at temperatures in the range 200 to 350 K. Finally, we consider Vorinostat concentration the roughness of very thin silver

layers, which are important for construction of hyperbolic metamaterials [26, 27] and plasmonic nanolenses [28–32]. Moreover, nanometer-thick Ag films with low surface roughness and fine crystallinity have low electron oscillation damping loss and thus can guide long-range plasmons [33, 34]. In the 10-nm-thick Ag film, all three morphology parameters are considerably reduced due to the residual influence of the Ag-Ge surface adhesive force. Figure 5a, b shows a 2D AFM image and a 1D profile of the 10-nm Ag film with the lowest value, achieved with physical vapor deposition, ever reported: RMS = 0.22 nm and ten-point height equal selleck kinase inhibitor to 1.05 nm. An example of SEM image of the same sample is presented as supporting data in Additional file 2. To illustrate roughness increase with metal film thickness, we show an AFM profile of the 30-nm Ag film in Figure 5c. Figure 5 AFM image and profiles. (a) AFM image of 10-nm-thick Ag film deposited at 295 K. The lowest ever reported morphology parameters for e-beam deposition technique are as follows: ten-point height value = 1.05 nm, average height = 0.9 nm, and RMS height = 0.22 nm. AFM profiles of (b) 10- and (c) 30-nm-thick Ag films deposited at 295 K.

ITS amplicons from single tips were directly sequenced. Heterogeneous mixtures of sequences were either used to construct ITS clone libraries or used directly for phylochip hybridisation. Figure 2 The different procedures used for molecular genotyping of ECM root tips and evaluation of the phylochip.

DNA was extracted from individual ECM root tips or from pooled ECM root tips and subjected to PCR amplification to produce specific Daporinad research buy ECM ITS sequence or a heterogeneous mixture of ITS sequences, respectively. Individual ITS sequences were directly sequenced. The heterogeneous mixture of ITS sequences (ITS clone libraries) were either separated into individual molecules by cloning in bacterial plasmids or used directly for microarray hybridisation. The results of these three different technical approaches were analysed and compared. In addition, to test the specificity of the spotted oligonucleotides, the phylochips were hybridised with a heterogeneous

mixture of ITS sequences from identified fungal sporocarps. The ECM roots (up to 100 mg fresh weight depending on the sample) were freeze-dried and ground in a ball mill MM200 (Retsch®, Haan, Germany). Ground tissue was resuspended in 400 μl AP1 buffer from the DNeasy Plant Mini Kit (Qiagen, Courtaboeuf, France), and the DNA was extracted according to the Selumetinib chemical structure manufacturer’s instructions. Purified DNA was solubilised in dH2O (~100 ng/μl) and stored at -80°C. The ITS was amplified as described in Buée et al. [5], using primers ITS1F and ITS4 [9] and/or NSI1 and NLB4 [25]. PCR products were purified using a 96-well filtration system (MultiScreen-PCR plates, Millipore Corporation, MA, USA) and sequenced with ITS1F and/or ITS4 primers and the Genome Lab DTCS Quick Start Kit (Beckman Coulter, Roissy CDG, France), using a CEQ 8000XL sequencer and the CEQ 8000 Genetic Analysis System.

ITS sequences were assembled with the Sequencher program for Macintosh, version 4.1.2 (Gene Codes Corporation, Ann Arbor, MI, USA), when sharing ≥ 97.0% identity. To identify the ECM fungi, BlastN was performed using ITS sequences that are available in the following public databases: NCBI http://​www.​ncbi.​nlm.​nih.​gov/​, UNITE http://​unite.​ut.​ee/​ and MycorWeb http://​mycor.​nancy.​inra.​fr/​. ECM fungal morphotypes were considered to be identified at the species level when they shared ≥ 97% of their ITS region sequence identity with a Amisulpride sequence in these public databases [35]. Sporocarp collection and taxonomic identification Three times per year, during the autumnal periods of 2004 to 2007, fungal sporocarps of all epigeous fungi were surveyed at the Breuil-Chenue experimental site, and mature fungal fruiting bodies that exhibited all the characteristics necessary for an unequivocal identification, were collected. An expert mycologist, Jean Paul Maurice (Groupe Mycologique Vosgien, 88300 Neufchâteau, France), used traditional mycological methods for taxonomic determination of the sporocarps [39].

The severity of serious fibrosis varied between studies, with prevalence of cirrhosis in one study [22] being less than half that in the other studies Seven studies evaluated its performance in the identification of cirrhosis or cirrhosis /severe

fibrosis although only 4 of these reported AUROC values. One study reported results for the identification of patients with no or mild fibrosis. The AUROCs for the 3 studies identifying cirrhosis were discrepant −0.78, 0.80 and 0.93. The median AUC for predicting severe fibrosis/cirrhosis =0.79 (range 0.69-0.93). Overall the LRs and predictive values showed that HA was better at excluding cirrhosis/ severe fibrosis than detecting it, with NPVs consistently high ~90% for cirrhosis.

There are two direct comparisons of a panel find more and HA. These showed differing results. In the larger study [25] there was no significant difference between panel (Fibrotest) and HA at both identifying cirrhosis and moderate /severe fibrosis. In the other study [28] most of the panel tests had greater AUC values in predicting cirrhosis than HA alone (but 95% CI were overlapping) but at lower levels of fibrosis the performance of HA and panels are more similar. Overall HA was better at identifying cirrhosis alone than moderate/severe fibrosis (AUROC ~ 0.80) or milder fibrosis. ii) Other single markers There were more limited data on five other single markers, with only three studies presenting AUROC analyses. Prothrombin buy YAP-TEAD Inhibitor 1 index had high LR + and predictive values in the identification of cirrhosis in two studies. One study reported performance of TIMP1 and

PIIINP in the same population of patients as single markers and as part of a panel. The study found that the AUROC values were next lower than in other studies of the same markers [29]. However this study population differed from the other studies in having a very high alcohol consumption over a long period of time Marker panels Cirrhosis/severe fibrosis (Figure 1, Table 3). Eight studies assessed the performance in detecting cirrhosis/severe fibrosis, five of which reported AUROCs. Four studies were external validations of previously derived panels [25, 27–30]. Several panels (Fibrotest, Fibrometer, Hepascore, ELF) showed promise in detection of cirrhosis with AUROCs >0.9, although one was small (ELF n = 64), and one showed no statistically significant difference to HA in direct comparison (Fibrotest). Common components of these panels are HA (in 3 panels), alpha macroglobulin (in 2 panels), GGT (in 2 panels). One panel (Tran index) reported a very high specificity and PPV compared to other panels.

aureus 43300(106 CFU/ml) intranasally Group 2: Mice were administered S. aureus 43300, left for a period of 48 hours to allow

nasal colonisation followed by intranasal administration of I-BET-762 cell line 50 μl of phage (107 PFU/ml) given twice (at an interval of 24 hours). Group 3: Mice were administered S. aureus 43300, left for a period of 48 hours to allow nasal colonisation followed by intranasal administration of 50 μl of mupirocin (5 mg/kg dissolved in water; given once) the next day. Group 4: Mice were administered S. aureus 43300, left for a period of 48 hours to allow nasal colonisation followed by intranasal administration of phage as well as mupirocin (5 mg/kg) the next day. The parameters used to monitor colonization included a) Bacterial load (CFU/ml) in nares b) Phage counts in nares c) Nasal myeloperoxidase (MPO) levels and e) Histopathological examination Nasal bacterial Pirfenidone in vivo load Four mice from each of group were taken and sacrificed on day 2, 5, 7, 10, 12 post treatment by cervical dislocation. The nasal region was wiped

externally with 70% ethanol, nose was removed along with nasal bone. The entire nasal tissue was excised using sterile scissors and homogenized. The homogenates were plated quantitatively on nutrient agar containing 20 μg/ml of ampicillin to select S. aureus 43300 after overnight incubation at 37°C. Nasal homogenates were also processed to determine the phage titer by modified double layer agar method [20]. Myeloperoxidase (MPO) estimation Mice from each group (same groups as those categorized for phage protection studies with 20 animals per group) were killed

and their nasal tissue was excised and homogenised in 50 mM PBS (pH 7.4). Nasal samples were processed for MPO determination as per the method of Greenberger et al. [21]. The absorbance was read immediately at 490 nm over a period of 4 minutes. MPO was calculated as the change in optical density (O.D) x dilution factor (D.F). Histopathological examination Extent of injury caused by S. aureus and healing of the colonized mouse nose following therapy with phage or antibiotic was assessed on the basis of histopathological analysis of the injured and recovered nose according to the method of Brans et al. [22]. The sections were picked Nitroxoline on separate slides, stained with hematoxylin and eosin (Hi-Media, Mumbai) and the slides then examined under a microscope to evaluate the extent of damage. Statistical methods The data is expressed as mean ± standard deviation of replicated values where indicated. The statistical significance of differences between groups was determined by Student’s t-test (two groups),one-way ANOVA followed by a Tukey test using Sigma Stat, Graph pad prism (Graph pad software, San Diego, CA). p value of less than 0.05 and 0.01 was considered statistically significant for a confidence interval of 95% and 99% respectively. Results The nasal epithelial cells were isolated from mouse nasal tissue and cultured at 37°C in presence of 5% CO2.

SiRNA

mediated check details knockdown of HDAC8 UCCs were seeded in 6-well plates and grown for 24 h before transfection. Cells were transfected with 10 nM HDAC8 Silencer® Select validated siRNA (#4390824, s31698, Ambion, Life Technologies, Darmstadt, Germany) or a Silencer® Select Negative Control #2 validated siRNA (#4390846, Ambion, Life Technologies, Darmstadt, Germany) using Lipofectamine RNAi MAX (Invitrogen, Life Technologies, Darmstadt, Germany), according to the manufacturer’s protocol. After transfection cells were incubated for 72 h before use for further experiments. Determination of mean inhibitory concentrations (IC50) and viability The mean inhibitory concentrations (IC50) and cell viability were measured trough total cellular ATP as an indicator for viable cells using the CellTiter-Glo® Luminescent Cell Viability Assay (Promega, Mannheim, Germany). UCCs were seeded into 96-well plates and grown for 24 h before inhibitor treatment with the indicated drug FK228 cell line concentration or DMSO and further grown for 72 h. In another experiment, cells were plated in 6-well plates and grown for 24 h before siRNA-mediated knockdown of HDAC8. Viability measurements were performed after 72 h by transferring the cells into 96-well plates using CellTiter-Glo Reagent according

to manufacturer’s protocol in a Wallac Victor 1420 Multilabel Counter (PerkinElmer, Rodgau, Germany). Colony forming assay and Giemsa-staining The colony forming assay was carried out 72 h after siRNA mediated HDAC8 knockdown and HDAC8 inhibitor treatment. Then, cells were plated in 6-well plates at a density of 500 to 1,000 cells per well. After 10 days, cells were washed with PBS (Biochrom, Merck Millipore, Berlin, Germany), shortly fixed in 50% methanol and incubated for 10 min in 100% methanol. The colonies were

stained with Giemsa (Merck, Darmstadt, Germany). Colony number and size was determined with ImageJ software (http://​rsbweb.​nih.​gov/​ij/​). Cell cycle analysis by flow cytometry UCCs were transfected with HDAC8 siRNA or an irrelevant control siRNA or, in another experiment, cultured with the determined IC50 concentrations of the HDAC8 selective inhibitors c2, c5 and c6, the pan HDAC-inhibitor SAHA (2.5 μM) or DMSO. Cell cycle analysis was performed after 72 h by staining the attached cells and cells in the supernatant with a PI-buffer containing Adenosine 50 μg/ml propidium iodide, 0.1% sodium citrate and 0.1% Triton X-100 [42] and flow cytometry using a BD LSR Fortessa cell analyzer system and FACSDiva software 6.2 (Becton Dickinson Biosciences, Heidelberg, Germany). Migration assay Cell migration was determined in wound healing assays by means of Ibidi Culture-Insert (Ibidi, Martinsried, Germany). The cell suspension was placed in both compartments allowing growth in the designated area only. The cells were treated with IC50 concentrations of c2, c5, c6 or 2.5 μM SAHA 48 h prior to plating.

Serial 4-5 μm sections were cut and adhered

onto microscope slides. Paraffin was removed from the sections using Xylene; the samples were rehydrated, and processed using the streptavidin-biotin-peroxidase complex immunohistochemical technique. To ascertain immunoreactivity, antigen unmasking was performed by microwave treatment with 10 mM citrate buffer. Incubation with 10% normal goat serum in phosphate-buffered saline (PBS) was performed to eliminate nonspecific staining. After incubating for five minutes in 3% hydrogen peroxide, the slides were then incubated FDA-approved Drug Library ic50 for 30 minutes at room temperature with primary antibody, VEGF-specific mouse monoclonal IgG (dilution 1:25; Dako). Detection of primary antibody

was achieved with a secondary antibody detection kit (LSAB+kit, Dako, Denmark). Bound antigens were visualized using 3, 3-diaminobenzidine as a chromogen. Finally, the sections were counterstained with Mayer’s hematoxylin, dehydrated, and mounted for analysis. Negative control was performed by incubating with Tris-buffered saline (TBS) instead of primary antibody. Colon carcinoma, shown to strongly express VEGF, was used as positive control. Immunohistochemical analysis We intended to focus on the positivity in viable tumor tissue and to analyze the “”hot spots”" of immunoreactivity. The cells showing positive staining for VEGF were defined morphologically by hematoxylin and eosin (H&E) staining, using the serial sections. We compared immunohistochemical stains

with preceding H&E slides to ascertain the exact location of immunoreactivity. Only cancer cells immunostained for VEGF were measured. MG-132 supplier The number of positive cells per 200 × field was assessed. In each slide three fields were evaluated. Semiquantitative expression levels of VEGF were determined by assessing both the percentage and intensity of stained tumour cells. The percentage of positive cells was rated as follows: cases with <1% positive cells were rated Interleukin-2 receptor as 0 point, 1-25% positive cells were rated 1 point; 26-50% positive cells, 2 points; 51-75% positive cells, 3 points; 76-100% positive cells, 4 points. The staining intensity was rated as follows: 1 point, weak intensity; 2 points, moderate intensity; 3 points, strong intensity. Points for staining intensity and percentage of positive cells were added, and specimens were classified into 2 groups according to their overall score: weak expression 0-2 points; and strong expression, 3-7 points. Statistical analysis Descriptive statistics and 95% confidence intervals were calculated to describe data. Data distribution was analyzed with the Smirnov-Kolmogorov test. According to the type of distribution, an appropriate parametric or an equivalent non-parametric test was used. The cutoff value for determining VEGF low and high expression score was performed by the receiver operating characteristic (ROC) curve analysis [28].

However, there have been no reported RCTs that directly compared the overall and renal outcomes prospectively in different phosphate-level arms. Therefore, there is no evidence about the extent to which the phosphate level should be lowered. Recently,

FGF23, a newly-found phosphaturic hormone, has been demonstrated to be a strong GDC-0941 supplier prognostic marker of overall, cardiovascular, and renal outcomes in CKD patients. An increase in the level of FGF23 in the serum is known to precede that of phosphate and is evoked by daily oral phosphorus intake. Accordingly, even within the reference range of phosphate, some CKD patients could be at risk of a phosphate overload and subsequently a poorer outcome. Thus, theoretically it is preferable to keep the level of serum phosphate as low as possible within the reference range in CKD patients. Since there is very little evidence demonstrating the benefit of treatment or modification of diet to achieve lower serum phosphate levels in CKD patients, no recommendation for specific intervention is provided here. More studies are required. Bibliography 1. Block GA, et al. J Am Soc Nephrol. 2004;15:2208–18. (Level 4)   2. Young EW, et al. Kidney

Int. 2005;67:1179–87. (Level 4)   3. Kalantar-Zadeh K, Rapamycin datasheet et al. Kidney Int. 2006;70:771–80. (Level 4)   4. Floege J, et al. Nephrol Dial Transplant. 2011;26:1948–55. (Level 4)   5. Palmer SC, et al. JAMA. 2011;305:1119–27. (Level 4)   6. Schwarz S, et al. Clin J Am Soc Nephrol. 2006;1:825–31. (Level 4)   7. Tangri N, et al. JAMA. 2011;305:1553–9. (Level 4)   8. Voormolen N, et al. Nephrol Dial Transplant. 2007;22:2909–16. (Level 4)   9. Chue CD, et al. Nephrol Dial Transplant. 2011;26:2576–82. (Level 4)   10. Moore J, et al. Clin Transplant. 2011;25:406–16. (Level 4)   11. Sampaio

MS, et al. Clin J Am Soc Nephrol. 2011;6:2712–21. (Level 4)   12. Dhingra R, et al. Arch Intern Med. 2007;167:879–85. (Level 4)   13. O’Seaghdha CM, et al. Nephrol Dial Transplant. 2011;26:2885–90. (Level 4)   14. Isakova T, et al. http://www.selleck.co.jp/products/Docetaxel(Taxotere).html Kidney Int. 2011;79:1370–8. (Level 4)   15. Nakano C, et al. Clin J Am Soc Nephrol. 2012;7:810–9. (Level 4)   16. Fliser D, et al. J Am Soc Nephrol. 2007;18:2600–8. (Level 4)   17. Parker BD, et al. Ann Intern Med. 2010;152:640–8. (Level 4)   18. Isakova T, et al. JAMA. 2011;305:2432–9. (Level 4)   19. Wolf M, et al. J Am Soc Nephrol. 2011;22:956–66. (Level 4)   20. Murtaugh MA, et al. Nephrol Dial Transplant. 2012;27:990–6. (Level 4)   21. Kovesdy CP, et al. Am J Kidney Dis. 2010;56:842–51. (Level 4)   Do serum parathyroid hormone (PTH) levels affect the mortality of patients with CKD? Many studies have demonstrated that phosphate is closely associated with all-cause and CVD mortality. However, the relationship between serum PTH levels and mortality in patients with CKD remains ambiguous.

However, the control and reduction of bacterial production by the two mortality agents have been observed in other aquatic systems [18, 21, 22].

Such variability in possible responses could be due to the initial www.selleckchem.com/products/PLX-4720.html bacterial community composition and environmental conditions. The increase in bacterial production with the presence of both predators (flagellates and viruses) could be explained by the fact that grazing activity and viral lysis are likely to release inorganic and organic nutrients which may stimulate bacterial activity. Obviously, the absence of direct measurements of grazing rates of flagellates on heterotrophic bacteria communities, for instance using fluorescently labelled bacteria (FLB) [40], prevented us from drawing firm conclusions about the grazing pressure of HNF on bacteria and our results should be considered in light of that. However, it has been suggested that a minimal proportion of 1,000 heterotrophic bacteria for one heterotrophic flagellate is characteristic of microbial food webs in which flagellates preferentially consume bacteria [39, 41, 42]. The value for this ratio was higher than 1,000 in each treatment (VFA vs. VF) and for each experiment (early spring vs. summer). Indeed it varied between 1,632 and 3,866 bacteria per flagellate

in Lake Annecy (mean value: this website 2,795), and between 2,619 and 8,857 in Lake Bourget (mean value: 5899), suggesting that heterotrophic bacteria were abundant enough to support the development of the heterotrophic flagellates that were present. Seasonal variability in the stimulation of bacterial production seemed to be more important than the trophic status variability, with highest mean values recorded in summer (+33.5% and +37.5%

in Lakes Bourget and Annecy, respectively), a period which corresponds to low total phosphorus conditions and high temperature in surface waters (Table 1). Thus, the input of nutrient resources by viral and grazing activities, under such summer conditions, is likely to stimulate the bacterial community much more than under the cold early-spring conditions (temperature = 6-7°C). Moreover, Thomas et al. [32] observed that the abundance of HDNA (high nucleic acid containing bacteria) is lower in spring than in summer in Lake Bourget (less than 40% of the total bacterial abundance), and Vitamin B12 this group is considered to be more active in comparison to LDNA (low nucleic acid bacteria) [43, 44]. This could also explain the low stimulation of bacterial production in early spring compared to that in summer. For most experiments (LA1, LB1 and LB2), the stimulation of bacterial production, at the end of experiments, was much higher in VFA than in the VF treatment (Figure 4) which could be attributed to an increase in substrate availability and regenerated nutrients, resulting from grazing pressure of flagellates on both heterotrophic bacteria and autotrophic communities, in treatment VFA [45, 46].