Combinational usage of next generation sequencing and qPCR for the analysis of tumor samples.

The combination of multiple techniques especially those adding complementary information have proven to be beneficial in terms of data consistency. The employment of quantitative PCR (qPCR) prior to next generation sequencing (NGS) methods such as RNA-Seq and mutational analysis presented here does not only enhance data in terms of CNV integration and sample choice, but also allows a faster and more efficient workflow. Correct analysis of libraries prior to sequencing has proven to be a vital step for specific assumption and to some extent for a more parallel testing. By illustrating the combination of qPCR and NGS in oncological examples, the potential of this approach is presented.

Obtaining Reliable RT-qPCR Results in Molecular Diagnostics-MIQE Goals and Pitfalls for Transcriptional Biomarker Discovery.

In this review, we discuss the development pipeline for transcriptional biomarkers in molecular diagnostics and stress the importance of a reliable gene transcript quantification strategy. Hence, a further focus is put on the MIQE guidelines and how to adapt them for biomarker discovery, from signature validation up to routine diagnostic applications. First, the advantages and pitfalls of the holistic RNA sequencing for biomarker development will be described to establish a candidate biomarker signature. Sequentially, the RT-qPCR confirmation process will be discussed to validate the discovered biomarker signature. Examples for the successful application of RT-qPCR as a fast and reproducible quantification method in routinemolecular diagnostics are provided. Based on the MIQE guidelines, the importance of "key steps" in RT-qPCR is accurately described, e.g., reverse transcription, proper reference gene selection and, finally, the application of automated RT-qPCR data analysis software. In conclusion, RT-qPCR proves to be a valuable tool in the establishment of a disease-specific transcriptional biomarker signature and will have a great future in molecular diagnostics or personalized medicine.

Chemokine receptor Ccr5 deficiency induces alternative macrophage activation and improves long-term renal allograft outcome.

The chemokine (C-C motif) receptor 5 (CCR5) has been implicated in experimental and clinical allograft rejection. To dissect the function of CCR5 in acute and chronic renal allograft rejection, bilaterally nephrectomized WT and Ccr5-/- C57BL/6 mice were used as recipients of WT BALB/c renal allografts and analyzed 7 and 42 days after transplantation. Lesion scores (glomerular damage, vascular rejection, tubulointerstitial inflammation) and numbers of CD4+, CD8+, CD11c+ and alpha smooth muscle actin (alphaSMA)+ cells were reduced in allografts from Ccr5-/- recipients during the chronic phase. Increasing creatinine levels indicated deterioration of allograft function over time. While mRNA expression of Th1-associated markers decreased between 7 and 42 days, Th2-associated markers increased. Markers for alternatively activated macrophages (arginase 1, chitinase 3-like 3, resistin-like alpha, mannose receptor, C type 1), were strongly upregulated (mRNA and/or protein level) only in allografts from Ccr5-/- recipients at 42 days. Ccr5 deficiency shifted intragraft immune responses during the chronic phase towards the Th2 type and led to accumulation of alternatively activated macrophages. Additionally, splenocytes from unchallenged Ccr5-/- mice showed significantly increased arginase 1 and mannose receptor 1 mRNA levels, suggesting constitutive alternative activation of splenic macrophages. We conclude that Ccr5 deficiency favors alternative macrophage activation. This finding may be relevant for other inflammatory diseases that involve macrophage activation and may also influence future therapeutic strategies targeting CCR5.

Microinjection of Cre recombinase protein into zygotes enables specific deletion of two eukaryotic selection cassettes and enhances the expression of a DsRed2 reporter gene in Ccr2/Ccr5 double-deficient mice.

The chemokine receptors CCR2 and CCR5 represent potential novel therapeutic targets to treat important inflammatory and infectious diseases, including atherosclerosis and HIV infection. To study the functions of both receptors in vivo, we aimed to generate Ccr2/Ccr5 double-deficient mice. As these genes are separated by <20 kb, they were inactivated consecutively by two rounds of gene targeting in embryonic stem (ES) cells. Thereby neomycin and hygromycin selection cassettes flanked by four identical loxP recognition sequences for Cre recombinase were integrated into the ES cell genome together with EGFP and DsRed2 reporter genes. Both selection cassettes could be deleted in vitro by transiently transfecting ES cells with Cre expression vectors. However, after blastocyst microinjection these cells yielded only weak chimeras, and germline transmission was not achieved. Therefore, Ccr2/Ccr5 double-deficient mice were generated from ES cells still carrying both selection cassettes. Microinjection of zygotes with a recombinant fusion protein consisting of maltose-binding protein and Cre (MBP-Cre) allowed the selective deletion of both cassettes. All sequences in between and both reporter genes were left intact. Deletion of both selection cassettes resulted in enhanced DsRed2 reporter gene expression. Cre protein microinjection of zygotes represents a novel approach to perform complex recombination tasks.

Microarray bioinformatics.

Bioinformatics has become an increasingly important tool for molecular biologists, especially for the analysis of microarray data. Microarrays can produce vast amounts of information requiring a series of consecutive analyses to render the data interpretable. The direct output of microarrays cannot be directly interpreted to show differences in settings, conditions of samples, or time points. To make microarray experiments interpretable, it is necessary that a series of algorithms and approaches be applied. After normalization of generated data, which is necessary to make a comparison feasible, significance analysis, clustering of samples and biological compounds of interest and visualization are generally performed. This chapter will focus on providing a basic understanding of the generally approaches and algorithms currently employed in microarray bioinformatics.