8 research outputs found
PPARγ protein level is unchanged upon stimulation with sodium butyrate and/or <i>S</i>. <i>salivarius</i> supernatant.
<p>A- The protein level of PPARγ and GAPDH were determined by western-blot on total protein extracted from HT-29 cells exposed to culture medium (CDM), <i>S</i>. <i>salivarius</i> JIM8777 supernatant in addition with sodium butyrate (Control + Butyrate; JIM8777 + Butyrate) for 24 h. B- Quantifications of total PPARγ protein normalized to GAPDH protein level. Protein expression is represented as fold change compared to the sodium butyrate stimulation in presence of culture media (Control + Butyrate). Data are represented as mean ± standard deviation (SD) of the effect of 5 independent bacterial cultures.</p
<i>S</i>. <i>salivarius</i> supernatants do not affect PPARγ-independent ANGPTL4 reporter system.
<p>ANGPTL4-reporter system cell-line was activated with sodium butyrate (2mM) with or without <i>S</i>. <i>salivarius</i> supernatant (JIM8772, JIM8777 or K12). <i>Angtpl4</i> expression was measured by luciferase activity and expressed as fold increase towards its control: growth-medium alone (left panel) and growth-medium + sodium butyrate (right panel). Data are expressed as means ± standard deviations (SD) of triplicate measurements from one representative experiment out of three independent experiments. ***P<0.001, **P<0.005, *P<0,05 compared with controls (Student's t-test).</p
The <i>S</i>. <i>salivarius</i>–dependent down-regulation of PPARγ activity relies on secreted molecules.
<p>PPARγ was activated (+ But) or not (- But) in HT-29 reporter cells using sodium butyrate (2mM) in the presence of control medium (Control) or as indicated live bacteria (A), bacterial supernatants (B) or lysates (C). The values represent the luciferase activity normalized towards their respective control. Data are expressed as means ± standard deviations (SD) of triplicate measurements from one representative experiment out of three independent experiments. ***P<0.001, **P<0.005, compared with controls (Student's t-test).</p
Determination of the nature and molecular mass of the secreted bioactive compounds.
<p>A- Serial dilutions of <i>S</i>. <i>salivarius</i> JIM8777 supernatant were tested on HT-29-PPARγ cells prior to activation with sodium butyrate (2mM). B- Exposure to high temperature (100°C/10 min) and heat shock were applied to <i>S</i>. <i>salivarius</i> JIM8777 supernatant prior to addition to activated HT-29-PPARγ cells. C- Butyrate-activated HT-29-PPARγ cells were incubated with <i>S</i>. <i>salivarius</i> supernatants fractions derived from ultrafiltration through 3 and 10 kDa cutoff membranes. >10kDa/>3kDa and <10kDa/<3kDa represent the retained and filtered fractions respectively. Data are expressed as means ± standard deviations (SD) of triplicate measurements from one representative experiment out of three independent experiments. ***P<0.001, **P<0.005, *P<0,05 compared with controls (Student's t-test).</p
Transcriptional regulation of PPARγ and PPARγ-target genes upon stimulation with rosiglitazone and/or <i>S</i>. <i>salivarius</i> supernatant.
<p>The mRNA expression of <i>I-FABP</i> (A), <i>Angptl4</i> (B) and <i>PPARγ</i> (C) were determined by Quantitative real-time PCR on total RNA extracted from HT-29 cells exposed to culture medium (CDM), <i>S</i>. <i>salivarius</i> JIM8777 supernatant (Sn) alone or in addition with the PPARγ specific activator rosiglitazone (CDM+Rosi; Sn+Rosi) for 6 h. Expression is represented as fold change compared to the absence of any stimulation (CDM medium only). Data are represented as mean ± standard deviation (SD) of 2 to 3 independent repetitions done in triplicates. **P<0.005, *P<0,05 compared with controls (Student's t-test).</p
The <i>S</i>. <i>salivarius</i>–dependent down-regulation of PPARγ activity is independent of the epithelial cell-line or the specific PPARγ-ligand used.
<p>A- PPARγ was activated (+ But) or not (- But) in Caco-2 reporter cells (Caco2-PPARγ) using sodium butyrate (2mM) in the presence of control medium (Control) or supernatants. B- HT-29-PPARγ reporter cell-line was activated with different activators: rosiglitazone (Rosi, 10μM), pioglitazone (Pio, 10μM) and sodium butyrate (But, 2mM) in presence of <i>S</i>. <i>salivarius</i> JIM8777 supernatant. The values represent the luciferase activity normalized towards their respective control. Data are expressed as means ± standard deviations (SD) of triplicate measurements from one representative experiment out of three independent experiments. ***P<0.001, **P<0.005, *P<0,05 compared with controls (Student's t-test).</p
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<p>Biofilm formation is crucial for bacterial community development and host colonization by Streptococcus salivarius, a pioneer colonizer and commensal bacterium of the human gastrointestinal tract. This ability to form biofilms depends on bacterial adhesion to host surfaces, and on the intercellular aggregation contributing to biofilm cohesiveness. Many S. salivarius isolates auto-aggregate, an adhesion process mediated by cell surface proteins. To gain an insight into the genetic factors of S. salivarius that dictate host adhesion and biofilm formation, we developed a screening method, based on the differential sedimentation of bacteria in semi-liquid conditions according to their auto-aggregation capacity, which allowed us to identify twelve mutations affecting this auto-aggregation phenotype. Mutations targeted genes encoding (i) extracellular components, including the CshA surface-exposed protein, the extracellular BglB glucan-binding protein, the GtfE, GtfG and GtfH glycosyltransferases and enzymes responsible for synthesis of cell wall polysaccharides (CwpB, CwpK), (ii) proteins responsible for the extracellular localization of proteins, such as structural components of the accessory SecA2Y2 system (Asp1, Asp2, SecA2) and the SrtA sortase, and (iii) the LiaR transcriptional response regulator. These mutations also influenced biofilm architecture, revealing that similar cell-to-cell interactions govern assembly of auto-aggregates and biofilm formation. We found that BglB, CshA, GtfH and LiaR were specifically associated with bacterial auto-aggregation, whereas Asp1, Asp2, CwpB, CwpK, GtfE, GtfG, SecA2 and SrtA also contributed to adhesion to host cells and host-derived components, or to interactions with the human pathogen Fusobacterium nucleatum. Our study demonstrates that our screening method could also be used to identify genes implicated in the bacterial interactions of pathogens or probiotics, for which aggregation is either a virulence trait or an advantageous feature, respectively.</p
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<p>Biofilm formation is crucial for bacterial community development and host colonization by Streptococcus salivarius, a pioneer colonizer and commensal bacterium of the human gastrointestinal tract. This ability to form biofilms depends on bacterial adhesion to host surfaces, and on the intercellular aggregation contributing to biofilm cohesiveness. Many S. salivarius isolates auto-aggregate, an adhesion process mediated by cell surface proteins. To gain an insight into the genetic factors of S. salivarius that dictate host adhesion and biofilm formation, we developed a screening method, based on the differential sedimentation of bacteria in semi-liquid conditions according to their auto-aggregation capacity, which allowed us to identify twelve mutations affecting this auto-aggregation phenotype. Mutations targeted genes encoding (i) extracellular components, including the CshA surface-exposed protein, the extracellular BglB glucan-binding protein, the GtfE, GtfG and GtfH glycosyltransferases and enzymes responsible for synthesis of cell wall polysaccharides (CwpB, CwpK), (ii) proteins responsible for the extracellular localization of proteins, such as structural components of the accessory SecA2Y2 system (Asp1, Asp2, SecA2) and the SrtA sortase, and (iii) the LiaR transcriptional response regulator. These mutations also influenced biofilm architecture, revealing that similar cell-to-cell interactions govern assembly of auto-aggregates and biofilm formation. We found that BglB, CshA, GtfH and LiaR were specifically associated with bacterial auto-aggregation, whereas Asp1, Asp2, CwpB, CwpK, GtfE, GtfG, SecA2 and SrtA also contributed to adhesion to host cells and host-derived components, or to interactions with the human pathogen Fusobacterium nucleatum. Our study demonstrates that our screening method could also be used to identify genes implicated in the bacterial interactions of pathogens or probiotics, for which aggregation is either a virulence trait or an advantageous feature, respectively.</p