This study was designed to investigate and validate methods for sampling and retrieval of micro-organisms from contaminated uniform/work-wear. Recent guidance in the United Kingdom states there is no conclusive evidence that work-wear poses an infection transmission risk in the healthcare environment. Although some studies have identified the presence of pathogenic organisms on uniforms, the link between healthcare associated infection (HCAI) and work-wear has not been established in the current literature. A key aspect of such investigations is the ability to reproducibly recover and detect the number of micro-organisms on the garments under investigation. Therefore, in order to undertake further research into contamination levels of uniforms, the methods used to retrieve organisms need to be validated for this particular purpose. In this study swatches of standard, sterile work-wear polyester mix material were inoculated with Staphylococcus aureus, Bacillus subtilis and Bacillus atrophaeus to represent potentially pathogenic organisms likely to be implicated in HCAI. Following incubation, four sampling methods were tested in a laboratory setting (swabbing, carpet sampler, Sartorius air sampler, Casella slit sampler) against the reference method (stomaching) and the numbers of colony forming units (cfu) recovered from the swatches were then recorded. The carpet sampler was the most efficient method in recovering microbiological contamination that had been applied dry to the sterile swatches. At the higher inoculum levels, the carpet sampler retrieved 51% of the challenge organisms compared to the Sartorius air sampler (6%), Casella slit sampler (10%) and swabbing (6%). The reference method of stomaching recovered 104%. The results demonstrated that wet contamination of certain materials can lead to signifi cant binding of microorganisms to the test fabric. Advantages of the carpet sampler compared to other methods include the requirement for less equipment, ease of use in a clinical environment and the capacity to test large numbers rapidly.