Biomedical subjects

Leonid Bystrykh

Publications and source records attributed to Leonid Bystrykh.

3 recordsLinked to original sources

PubMed2006

Selective expression of cholesterol metabolism genes in normal CD34+CD38- cells with a heterogeneous expression pattern in AML cells.

OBJECTIVE: To identify adenosine triphosphate-binding-cassette (ABC) transporters that are selectively expressed in normal and/or leukemic CD34+CD38- stem cells. METHODS: Microarray experiments on murine stem cells identified 13 ABC transporters with a high expression level. Corresponding human transporters were analyzed in normal CD34+CD38- and CD34+CD38+ bone marrow cells by quantitative reverse transcriptase polymerase chain reaction. RESULTS: Five ABC transporters, including ABCG1, were differentially expressed with a higher expression in CD34+CD38- cells. Besides ABCG1, known to be involved in cholesterol metabolism, expression of another major cholesterol transporter (ABCA1), some cholesterol metabolism genes (3-hydroxy-3-methyl-glutaryl-CoA reductase, low-density lipoprotein receptor), and the transcription factor controlling ABCA1 and ABCG1 expression, liver-X-receptor-alpha (LXR-alpha), were assessed. All these genes were predominantly expressed in the more primitive subpopulation, indicating a high rate of cholesterol metabolism and transport. Conversely in acute myeloid leukemia (AML), a heterogeneous expression pattern was found consisting of a considerably higher expression of particularly LXR-alpha in CD34+ cells and a reverse expression pattern in a subset of AML CD34+CD38+ cells. CONCLUSION: These data suggest an active cholesterol metabolism and efflux in normal CD34+CD38- cells, although a subgroup of AMLs potentially demonstrate a hyperactive cholesterol metabolism.

ADP-ribosyl Cyclase 1↗

PubMed2006

Modern genome-wide genetic approaches to reveal intrinsic properties of stem cells.

PURPOSE OF REVIEW: The clinical use of hematopoietic stem cells, which produce all mature blood cell lineages in the circulation, is continuously increasing. Identification of genes and gene networks specifying either stemness or commitment will not only be of major relevance for a fundamental understanding of developmental biology, but also for the emerging fields of tissue engineering and regenerative medicine. Our appreciation of the transcriptional machinery that distinguishes stem cells from their nonstem cell progeny is, however, rudimentary. State-of-the art genome-wide tools are now becoming available to elucidate intrinsic properties of stem cells. Here, we review recent progress that has been made in this field. RECENT FINDINGS: Approaches to study stem cell-specific genes and gene networks include genetical genomics, mRNA and microRNA expression profiling of carefully selected cells, proteomics, chromatin studies using 'CHIP-on-chip' tools, genome-wide binding site analyses for transcription factors and chromatin-remodeling proteins, and tools to study the three-dimensional organization of gene loci. It is promising to see that the combined application of these tools has resulted in the identification of multiple novel genes that regulate stem cell self-renewal. SUMMARY: Exploitation of the available technology and integrating the data by translation into a dynamic model of networks, operating in all four dimensions, will be essential to fully comprehend the elusive concept of 'stemness'. It is time to harvest.

Animals↗

PubMed2005

Uncovering regulatory pathways that affect hematopoietic stem cell function using 'genetical genomics'.

We combined large-scale mRNA expression analysis and gene mapping to identify genes and loci that control hematopoietic stem cell (HSC) function. We measured mRNA expression levels in purified HSCs isolated from a panel of densely genotyped recombinant inbred mouse strains. We mapped quantitative trait loci (QTLs) associated with variation in expression of thousands of transcripts. By comparing the physical transcript position with the location of the controlling QTL, we identified polymorphic cis-acting stem cell genes. We also identified multiple trans-acting control loci that modify expression of large numbers of genes. These groups of coregulated transcripts identify pathways that specify variation in stem cells. We illustrate this concept with the identification of candidate genes involved with HSC turnover. We compared expression QTLs in HSCs and brain from the same mice and identified both shared and tissue-specific QTLs. Our data are accessible through WebQTL, a web-based interface that allows custom genetic linkage analysis and identification of coregulated transcripts.

Carrier Proteins↗