21 research outputs found
HIV Testing Practices by Clinical Service before and after Revised Testing Guidelines in a Swiss University Hospital
OBJECTIVES: To determine 1) HIV testing practices in a 1400-bed university hospital where local HIV prevalence is 0.4% and 2) the effect on testing practices of national HIV testing guidelines, revised in March 2010, recommending Physician-Initiated Counselling and Testing (PICT).
METHODS: Using 2 hospital databases, we determined the number of HIV tests performed by selected clinical services, and the number of patients tested as a percentage of the number seen per service ('testing rate'). To explore the effect of the revised national guidelines, we examined testing rates for two years pre- and two years post-PICT guideline publication.
RESULTS: Combining the clinical services, 253,178 patients were seen and 9,183 tests were performed (of which 80 tested positive, 0.9%) in the four-year study period. The emergency department (ED) performed the second highest number of tests, but had the lowest testing rates (0.9-1.1%). Of inpatient services, neurology and psychiatry had higher testing rates than internal medicine (19.7% and 9.6% versus 8%, respectively). There was no significant increase in testing rates, either globally or in the majority of the clinical services examined, and no increase in new HIV diagnoses post-PICT recommendations.
CONCLUSIONS: Using a simple two-database tool, we observe no global improvement in HIV testing rates in our hospital following new national guidelines but do identify services where testing practices merit improvement. This study may show the limit of PICT strategies based on physician risk assessment, compared to the opt-out approach
The Lipid Transfer Protein CERT Interacts with the Chlamydia Inclusion Protein IncD and Participates to ER-Chlamydia Inclusion Membrane Contact Sites
Bacterial pathogens that reside in membrane bound compartment manipulate the host cell machinery to establish and maintain their intracellular niche. The hijacking of inter-organelle vesicular trafficking through the targeting of small GTPases or SNARE proteins has been well established. Here, we show that intracellular pathogens also establish direct membrane contact sites with organelles and exploit non-vesicular transport machinery. We identified the ER-to-Golgi ceramide transfer protein CERT as a host cell factor specifically recruited to the inclusion, a membrane-bound compartment harboring the obligate intracellular pathogen Chlamydia trachomatis. We further showed that CERT recruitment to the inclusion correlated with the recruitment of VAPA/B-positive tubules in close proximity of the inclusion membrane, suggesting that ER-Inclusion membrane contact sites are formed upon C. trachomatis infection. Moreover, we identified the C. trachomatis effector protein IncD as a specific binding partner for CERT. Finally we showed that depletion of either CERT or the VAP proteins impaired bacterial development. We propose that the presence of IncD, CERT, VAPA/B, and potentially additional host and/or bacterial factors, at points of contact between the ER and the inclusion membrane provides a specialized metabolic and/or signaling microenvironment favorable to bacterial development
RNAi screen reveals host cell kinases specifically involved in Listeria monocytogenes spread from cell to cell.
Intracellular bacterial pathogens, such as Listeria monocytogenes and Rickettsia conorii display actin-based motility in the cytosol of infected cells and spread from cell to cell through the formation of membrane protrusions at the cell cortex. Whereas the mechanisms supporting cytosolic actin-based motility are fairly well understood, it is unclear whether specific host factors may be required for supporting the formation and resolution of membrane protrusions. To address this gap in knowledge, we have developed high-throughput fluorescence microscopy and computer-assisted image analysis procedures to quantify pathogen spread in human epithelial cells. We used the approach to screen a siRNA library covering the human kinome and identified 7 candidate kinases whose depletion led to severe spreading defects in cells infected with L. monocytogenes. We conducted systematic validation procedures with redundant silencing reagents and confirmed the involvement of the serine/threonine kinases, CSNK1A1 and CSNK2B. We conducted secondary assays showing that, in contrast with the situation observed in CSNK2B-depleted cells, L. monocytogenes formed wild-type cytosolic tails and displayed wild-type actin-based motility in the cytosol of CSNK1A1-depleted cells. Furthermore, we developed a protrusion formation assay and showed that the spreading defect observed in CSNK1A1-depleted cells correlated with the formation of protrusion that did not resolve into double-membrane vacuoles. Moreover, we developed sending and receiving cell-specific RNAi procedures and showed that CSNK1A was required in the sending cells, but was dispensable in the receiving cells, for protrusion resolution. Finally, we showed that the observed defects were specific to Listeria monocytogenes, as Rickettsia conorii displayed wild-type cell-to-cell spread in CSNK1A1- and CSNK2B-depleted cells. We conclude that, in addition to the specific host factors supporting cytosolic actin-based motility, such as CSNK2B, Listeria monocytogenes requires specific host factors, such as CSNK1A1 in order to form productive membrane protrusions and spread from cell to cell
Characterization of membrane protrusion formation in mock-treated and CSNK1A1-depleted cells.
<p>(A) Representative images showing protrusion formation in mock-treated and CSNK1A1-depleted cells transiently transfected with membrane-targeted RFP. Top panel; bright field. Bottom panel; fluorescence (green, bacteria; red, plasma membrane). (B) Representative images of bacteria protrusions (top panel), double membrane vacuole (middle panel) and not associated with membrane marker (bottom panel). Left: merged image: green, bacteria; red, plasma membrane. Right: plasma membrane only. (C) Quantification of bacteria that crossed the cell boundary in mock-treated and CSNK1A1-depleted cells and found in protrusions, vacuoles or not associated with the membrane-RFP marker. Values represent the mean and standard deviation of 5 independent experiments.</p
CSNK1A1 is required in sending cells, but not in receiving cells.
<p>(A) Representative image of CSNK1A1-depleted cells expressing membrane-GFP marker (green) infected with GFP-expressing <i>L. monocytogenes</i> and sending bacteria into mock-treated cells labeled with CMTPX (red). The doted line indicates the position of the YZ section shown on the right. Arrow indicates a protrusion in the CMTPX-labeled neighboring cell. (B) Representative image of mock-treated cells expressing membrane-GFP marker (green) infected with GFP-expressing <i>L. monocytogenes</i> and sending bacteria into CSNK1A1-depleted cells labeled with CMTPX (red). The doted line indicates the position of the YZ section shown on the right. Arrow indicates a free bacterium in the CMTPX-labeled neighboring cell.</p
<i>R. conorii</i> spread from cell to cell does not rely on CSNK1A1, CSNK2B or ARPC4.
<p>Mock- or siRNA-treated cells were infected with <i>R. conorii</i> for 48 hrs and subjected to fluorescence microscopy. Red, Nuclei and green, Bacteria. The images show a representative example of the bacterial foci for each treatment. The graph shows quantification of the area covered by the bacterial foci for each treatment. Values represent the mean and standard deviation for 20 foci for each treatment. The area values were normalized with the highest value (ARPC4), which was given an arbitrary value of 100 (Relative average area).</p
Fluorescence microscopy and image analysis of bacterial pathogen spread from cell to cell.
<p>Mock- and ARPC4-treated cells were infected with GFP-expressing wild type (<i>10403S</i>) or mutant (<i>10403SΔactA</i>) <i>L. monocytogenes</i> for 10 hrs. Left panel, Nuclei; middle panel, Bacteria and right panel, Image analysis. Computer-assisted image analysis was used to determine the number of nuclei corresponding to uninfected and infected cells (red and green objects, respectively).</p