Effect of the irradiated microenvironment on the expression and retrotransposition of intracisternal type A particles in hematopoietic cells

Bone marrow-derived stem cells and radiation response

The recovery of tissues and organs from ionizing irradiation is critically dependent on the repopulation of resident stem cells, defined as the subset of cells with capacity for both self-renewal and differentiation. Stem cells of both hematopoietic and epithelial origin reside in defined areas of the cellular microenvironment (recently defined as the stem cell "niche"). Experiments using serial repopulation assays in serial generations of total body irradiated mice receiving transplanted marrow and in continuous bone marrow cultures both identified specific microanatomic sites that comprise the bone marrow stem cell niche. Supportive cells of the hematopoietic microenvironment not only contribute to stem cell repopulation capacity but also to the maintenance of their quiescent or nonproliferative state, which allows the most primitive hematopoietic stem cells to stay in a noncycling state protected from both direct ionizing radiation-induced cell-cycle phase-specific killing and indirect cytokine and free radical mediated killing. Recent evidence has defined both cell contact and humoral mechanisms of protection of hematopoietic stem cells by stromal cells. There is also recent evidence for multilineage differentiation capacity of cells of the hematopoietic microenvironment termed bone marrow stromal cells (mesenchymal stem cells). Both hematopoietic stem cells and mesenchymal stem cell populations have been shown to be involved in the repair of ionizing irradiation damage of distant epithelial as well as other hematopoietic sites through their capacity to migrate through the circulation. The radiobiology of these 2 bone marrow stem cell populations is the subject of intense investigation. This review defines the status of research in the areas of stem cell quiescence, niche contact, and migratory responses to ionizing irradiation.

Quantitative RT-PCR gene expression analysis of laser microdissected tissue samples

Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is a valuable tool for measuring gene expression in biological samples. However, unique challenges are encountered when studies are performed on cells microdissected from tissues derived from animal models or the clinic, including specimen-related issues, variability of RNA template quality and quantity, and normalization. qRT-PCR using small amounts of mRNA derived from dissected cell populations requires adaptation of standard methods to allow meaningful comparisons across sample sets. The protocol described here presents the rationale, technical steps, normalization strategy and data analysis necessary to generate reliable gene expression measurements of transcripts from dissected samples. The entire protocol from tissue microdissection through qRT-PCR analysis requires approximately 16 h.

Assessment of normalization strategies for quantitative RT-PCR using microdissected tissue samples

Gene expression measurement techniques such as quantitative reverse transcriptase (qRT)-PCR require a normalization strategy to allow meaningful comparisons across biological samples. Typically, this is accomplished through the use of an endogenous housekeeping gene that is presumed to show stable expression levels in the samples under study. There is concern regarding how precisely specific genes can be measured in limited amounts of mRNA such as those from microdissected (MD) tissues. To address this issue, we evaluated three different approaches for qRT-PCR normalization of dissected samples; cell count during microdissection, total RNA measurement, and endogenous control genes. The data indicate that both cell count and total RNA are useful in calibrating input amounts at the outset of a study, but do not provide enough precision to serve as normalization standards. However, endogenous control genes can accurately determine the relative abundance of a target gene relative to the entire cellular transcriptome. Taken together, these results suggest that precise gene expression measurements can be made from MD samples if the appropriate normalization strategy is employed.