Use of flow cytometry method to detect contaminations of platelet suspensions

In this study, it was aimed to investigate bacterial contamination in apheresis platelet suspensions (APS) by automated blood culture system and flow cytometry method (FCM).33 spiked APS each using 11 bacterial strains (5 standard strains, 6 clinical isolates), were prepared in three different dilutions (1-10, 10-50, 50-100 cfu/mL), incubated in two different temperatures (35-37 °C and 22-24 °C) and different incubation times (18-96 h) evaluated by FCM. This three different dilutions were also inoculated into special platelet culture bottles (BacT/ALERT® BPA) and loaded into the blood culture system. Additionally 80 APSs routinely prepared in the Transfusion Center were evaluated by both FCM and the blood culture system. Platelets were lysed by freeze-thaw method.All spiked samples were positive with BacT/ALERT® BPA in 12-18 h. In 96 h incubation at 22-24 °C, the presence of bacteria was detected by FCM in all other samples (31/33) except low dilutions (1-10 and 10-100 CFU/ml) of K.pneumoniae standard strain. In the 35-37 °C, the presence of bacteria was detected by FCM in all samples (33/33) after 48 h of incubation. In routine APS one sample detected as positive (Bacillus simplex) with BacT/ALERT® BPA and no positivity was detected by FCM.The freeze-thaw method, which we have optimized for the lysis of platelets, is very practical and can be easily applied. The BacT/ALERT® system has been found to be very sensitive in detecting bacterial contamination in PSs. Flow cytometry method has been found to be successful, fast, easy to use and low cost in detecting bacterial contamination in PSs.

Conventional culture method and qPCR using 16S rDNA for tissue bank: a comparison using a model of cardiac tissue contamination

Real-time polymerase chain reaction (qPCR) using 16S rDNA is an alternative to conventional culture-based tests. The aim of this study was to compare the conventional culture method with qPCR using 16S rDNA in a model of cardiac tissue contamination. Samples of cardiac tissue for artificial contamination with Escherichia coli and control samples were submitted for DNA extraction, which was conducted by selective and alkaline lysis and purification steps. A standard curve for 16S rDNA was constructed to determine the efficiency and analytical sensitivity of the assay in concentrations from 10⁶ to 10² c.f.u. ml^-1 using TaqMan Master Mix. 16S rDNA was detected in all contaminated samples; however, it was not detected in the the final washing step solution of the sample with a bioburden of 10² c.f.u. ml^-1. Using qPCR is a potential alternative to conventional culture for microbiological safety testing of allograft tissues for biobanking, reducing the time and labour input required.

RT-PCR testing of allograft musculoskeletal tissue: is it time for culture-based methods to move over?

Allograft musculoskeletal tissue samples are assessed for microbial bioburden to reduce the risk of post-transplant infection. Traditionally, solid agar and broth culture media have been used however, nucleic acid testing, such as real-time (RT) polymerase chain reaction (PCR), has been described as more sensitive. This study evaluated the recovery of low numbers of challenge organisms from inoculated swab and musculoskeletal biopsy samples using solid agar culture, cooked meat medium, blood culture bottles and a RT-PCR assay. It was found that broth culture methods were the most sensitive with RT-PCR unable to detect low numbers of bacteria from these samples. Investigation of other non-culture methods may be worthwhile.

Three different bacterial detection systems for platelet concentrates under inter-laboratory conditions

BACKGROUND

A variety of screening methods are currently used worldwide in order to decrease the risk of transfusion-transmitted sepsis and improve the safety of PCs.

METHODS/MATERIALS

PCs inoculated with five different transfusion-relevant species of bacteria at concentrations of 1, 10, and 100 colony-forming units (CFU)ml(-1) were stored at 22°C for 7 days. Flow cytometry (FACS), BacT/Alert automated culturing, and a quantitative real-time PCR (Q-PCR) were then used to detect the presence of bacteria in samples prepared from these PCs.

RESULTS

At the initial spiking concentrations of 1, 10, and 100 CFU ml(-1), Q-PCR detected all five bacterial species tested. Screening with the BacT/Alert culture-based system allowed bacterial detection (inoculated on day 0) within a mean time of 15.13 h for all three spiking concentrations. Using FACS, positive signals were obtained for all three concentrations of Escherichia coli and Bacillus cereus on day 1 and for initial spiking concentrations of Pseudomonas aeruginosa and Staphylococcus aureus of 1 CFU ml(-1) on day 2. For Staphylococcus epidermidis, detection of an initial inoculum of 1 CFU ml(-1) was possible only beginning on day 6.

CONCLUSION

This study shows that under standard laboratory conditions the sensitivity of FACS in the detection of bacterial contamination of PCs was lower than that of either the BacT/Alert automated culturing method or Q-PCR.

A consideration of biomarkers to be used for evaluation of inflammation in human nutritional studies

To monitor inflammation in a meaningful way, the markers used must be valid: they must reflect the inflammatory process under study and they must be predictive of future health status. In 2009, the Nutrition and Immunity Task Force of the International Life Sciences Institute, European Branch, organized an expert group to attempt to identify robust and predictive markers, or patterns or clusters of markers, which can be used to assess inflammation in human nutrition studies in the general population. Inflammation is a normal process and there are a number of cells and mediators involved. These markers are involved in, or are produced as a result of, the inflammatory process irrespective of its trigger and its location and are common to all inflammatory situations. Currently, there is no consensus as to which markers of inflammation best represent low-grade inflammation or differentiate between acute and chronic inflammation or between the various phases of inflammatory responses. There are a number of modifying factors that affect the concentration of an inflammatory marker at a given time, including age, diet and body fatness, among others. Measuring the concentration of inflammatory markers in the bloodstream under basal conditions is probably less informative compared with data related to the concentration change in response to a challenge. A number of inflammatory challenges have been described. However, many of these challenges are poorly standardised. Patterns and clusters may be important as robust biomarkers of inflammation. Therefore, it is likely that a combination of multiple inflammatory markers and integrated readouts based upon kinetic analysis following defined challenges will be the most informative biomarker of inflammation.