5 research outputs found

    Epidermal growth factor (EGF) withdrawal masks gene expression differences in the study of pituitary adenylate cyclase-activating polypeptide (PACAP) activation of primary neural stem cell proliferation

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    BACKGROUND: The recently discovered adult neural stem cells, which maintain continuous generation of new neuronal and glial cells throughout adulthood, are a promising and expandable source of cells for use in cell replacement therapies within the central nervous system. These cells could either be induced to proliferate and differentiate endogenously, or expanded and differentiated in culture before being transplanted into the damaged site of the brain. In order to achieve these goals effective strategies to isolate, expand and differentiate neural stem cells into the desired specific phenotypes must be developed. However, little is known as yet about the factors and mechanisms influencing these processes. It has recently been reported that pituitary adenylate cyclase-activating polypeptide (PACAP) promotes neural stem cell proliferation both in vivo and in vitro. RESULTS: We used cDNA microarrays with the aim of analysing the transcriptional changes underlying PACAP induced proliferation of neural stem cells. The primary neural stem/progenitor cells used were neurospheres, generated from the lateral ventricle wall of the adult mouse brain. The results were compared to both differentiation and proliferation controls, which revealed an unexpected and significant differential expression relating to withdrawal of epidermal growth factor (EGF) from the neurosphere growth medium. The effect of EGF removal was so pronounced that it masked the changes in gene expression patterns produced by the addition of PACAP. CONCLUSION: Experimental models aiming at transcriptional analysis of induced proliferation in primary neural stem cells need to take into consideration the significant effect on transcription caused by removal of EGF. Alternatively, EGF-free culture conditions need to be developed

    Transcriptome analysis in primary neural stem cells using a tag cDNA amplification method

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    BACKGROUND: Neural stem cells (NSCs) can be isolated from the adult mammalian brain and expanded in culture, in the form of cellular aggregates called neurospheres. Neurospheres provide an in vitro model for studying NSC behaviour and give information on the factors and mechanisms that govern their proliferation and differentiation. They are also a promising source for cell replacement therapies of the central nervous system. Neurospheres are complex structures consisting of several cell types of varying degrees of differentiation. One way of characterising neurospheres is to analyse their gene expression profiles. The value of such studies is however uncertain since they are heterogeneous structures and different populations of neurospheres may vary significantly in their gene expression. RESULTS: To address this issue, we have used cDNA microarrays and a recently reported tag cDNA amplification method to analyse the gene expression profiles of neurospheres originating from separate isolations of the lateral ventricle wall of adult mice and passaged to varying degrees. Separate isolations as well as consecutive passages yield a high variability in gene expression while parallel cultures yield the lowest variability. CONCLUSIONS: We demonstrate a low technical amplification variability using the employed amplification strategy and conclude that neurospheres from the same isolation and passage are sufficiently similar to be used for comparative gene expression analysis

    Transcript profiling of small tissue samples using microarray technology

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    Through a number of biological, technological and computational achievements during the 20th century and the devoted work of hundreds of researchers the sequence of the human and other genomes are now available in public databases. The current challenge is to begin to understand the information encoded by the DNA sequence, to elucidate the functions of the proteins and RNA molecules encoded by the genes as well as how they are regulated. For this purpose new technologies within the area of functional genomics are being developed. Among those are powerful tools for gene expression analysis, such as microarrays, providing means to investigate when and where certain genes are used. This thesis describes a method that was developed to enable gene expression analysis, on the transcriptome level, in small tissue samples. It relies on PCR amplification of the 3’-ends of cDNA (denoted 3’-end signature tags). PCR is a powerful technology for amplification of nucleic acids, but has not been used much for transcript profiling since it is generally considered to introduce biases, distorting the original relative transcript levels. The described method addresses this issue by generating uniformly sized representatives of the transcripts/cDNAs prior to amplification. This is achieved through sonication which, unlike restriction enzymes, does not require a specific recognition sequence and fragments each transcript randomly. The method was evaluated using cDNA microarrays, Affymetrix™ oligonucleotide arrays and real-time quantitative PCR. It was shown to perform well, yielding transcript profiles that correlate well to the original, unamplified material, as well as being highly reproducible. The developed method was applied to stem cell biology. The variability in gene expression between different populations of cultured neural stem cells (neurospheres) was investigated. It was shown that neurospheres isolated from different animals or passaged to different degrees show large fluctuations in gene expression, while neurospheres isolated and cultured under identical conditions are more similar and suitable for gene expression analysis. A second study showed that withdrawing epidermal growth factor (EGF) from the culture medium when treating the cells with an agent of interest has profound effects on gene expression, something which should be taken into consideration in future neurosphere studies.QC 2010100
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