Directed Evaluation of Enterotoxigenic Escherichia coli Autotransporter Proteins as Putative Vaccine Candidates

Diarrheal diseases are responsible for more than 1.5 million deaths annually in developing countries. Enterotoxigenic E. coli (ETEC) are among the most common bacterial causes of diarrhea, accounting for an estimated 300,000–500,000 deaths each year, mostly in young children. There unfortunately is not yet a vaccine that can offer sustained, broad-based protection against ETEC. While most vaccine development effort has focused on plasmid-encoded finger-like ETEC adhesin structures known as colonization factors, additional effort is needed to identify conserved target antigens. Epidemiologic studies suggest that immune responses to uncharacterized, chromosomally encoded antigens could contribute to protection resulting from repeated infections. Earlier studies of immune responses to ETEC infection had identified a class of surface-expressed molecules known as autotransporters (AT). Therefore, available ETEC genome sequences were examined to identify conserved ETEC autotransporters not shared by the commensal E. coli HS strain, followed by studies of the immune response to these antigens, and tests of their utility as vaccine components. Two chromosomally encoded ATs, identified in ETEC, but not in HS, were found to be immunogenic and protective in an animal model, suggesting that conserved AT molecules contribute to protective immune responses that follow natural ETEC infection and offering new potential targets for vaccines

Specificity of HLA class I antigen recognition by human NK clones: evidence for clonal heterogeneity, protection by self and non-self alleles, and influence of the target cell type

Prior studies using polyclonal populations of natural killer (NK) cells have revealed that expression of certain major histocompatibility complex (MHC) class I molecules on the membrane of normal and transformed hematopoietic target cells can prevent NK cell-mediated cytotoxicity. However, the extent of clonal heterogeneity within the NK cell population and the effect of self versus non-self MHC alleles has not been clearly established. In the present study, we have generated more than 200 independently derived human NK cell clones from four individuals of known human histocompatibility leukocyte antigens (HLA) type. NK clones were analyzed for cytolytic activity against MHC class I-deficient Epstein Barr virus (EBV) transformed B lymphoblastoid cell lines (B-LCL) stably transfected with several HLA-A,-B, or-C genes representing either self or non-self alleles. All NK clones killed the prototypic HLA-negative erythroleukemia K562 and most lysed the MHC class I-deficient C1R and 721.221 B-LCL. Analysis of the panel of HLA-A,-B, and-C transfectants supported the following general conclusions. (a) Whereas recent studies have suggested that HLA-C antigens may be preferentially recognized by NK cells, our findings indicate that 70 % or more of all NK clones are able to recognize certain HLA-B alleles and many also recognize HLA-A alleles. Moreover, a single NK clone has the potential to recogniz

Flow cytometric method transfer: Recommendations for best practice

As with many aspects of the validation and monitoring of flow cytometric methods, the method transfer processes and acceptance criteria described for other technologies are not fully applicable. This is due to the complexity of the highly configurable instrumentation, the complexity of cellular measurands, the lack of qualified reference materials for most assays, and limited specimen stability. There are multiple reasons for initiating a method transfer, multiple regulatory settings, and multiple context of use. All of these factors influence the specific requirements for the method transfer. This recommendation paper describes the considerations and best practices for the transfer of flow cytometric methods and provides individual case studies as examples. In addition, the manuscript emphasizes the importance of appropriately conducting a method transfer on data reliability