Dynamic interaction networks in a hierarchically organized tissue

Kirouac, Daniel C.; Ito, Caryn Y.; Csaszar, Elizabeth; Roch, Aline; Yu, Mei; Sykes, Edward A.; Bader, Gary D.; Zandstra, Peter W.

doi:10.1038/msb.2010.71

Cited by 128 publications

(123 citation statements)

References 39 publications

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“…It was shown several years ago that megakaryocyte-derived stimulatory growth factors can promote self-renewal of human HSPCs. 63 Using combined genomic and phenotype data, this work has recently been expanded to generate a directional cell-cell communication network between 12 human hematopoietic cell types isolated from umbilical cord blood. 64 Microfluidics technology already offers opportunities to monitor single cells responding to an external signal, as well as to quantify signaling molecules secreted by individual HSPCs.…”

Section: Discussionmentioning

confidence: 99%

Regulatory network control of blood stem cells

Göttgens

2015

Blood

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Hematopoietic stem cells (HSCs) are characterized by their ability to execute a wide range of cell fate choices, including selfrenewal, quiescence, and differentiation into the many different mature blood lineages. Cell fate decision making in HSCs, as indeed in other cell types, is driven by the interplay of external stimuli and intracellular regulatory programs. Given the pivotal nature of HSC decision making for both normal and aberrant hematopoiesis, substantial research efforts have been invested over the last few decades into deciphering some of the underlying mechanisms. Central to the intracellular decision making processes are transcription factor proteins and their interactions within gene regulatory networks. More than 50 transcription factors have been shown to affect the functionality of HSCs. However, much remains to be learned about the way in which individual factors are connected within wider regulatory networks, and how the topology of HSC regulatory networks might affect HSC function. Nevertheless, important progress has been made in recent years, and new emerging technologies suggest that the pace of progress is likely to accelerate. This review will introduce key concepts, provide an integrated view of selected recent studies, and conclude with an outlook on possible future directions for this field. (Blood. 2015;125(17):2614-2620 Building blocks of transcriptional regulatory networksThe primary components of transcriptional regulatory networks are transcription factor (TF) proteins and the gene regulatory DNA sequences that they bind to.1 By binding to specific DNA sequence motifs within gene regulatory regions, TF proteins are central players for this primary step of decoding gene regulatory instructions. TF proteins typically contain a number of distinct modules, such as DNA binding, transcriptional activation, and protein/protein interaction domains, with the latter 2 being essential for the recruitment of the basal transcriptional machinery and the assembly of higherorder TF complexes. Based on sequence similarity within the DNA binding domain, TF proteins can be categorized into distinct families, such as homeobox, basic helix-loop-helix, or zinc finger TFs. Members of a given TF family often bind to similar DNA sequences, and proteinprotein interactions are common both within and between the different TF families.Individual TFs bind short sequence motifs that are often no longer than 4 to 6 bp. Any given 6-bp sequence will occur on average approximately once every 4000 bp. Consequently, there will be ;750 000 occurrences just by chance within the 3 000 000 000 bp of the human genome. The number of possible binding sites therefore far exceeds the 20 000 or so human genes, and it has long been assumed that only a small minority of all motif instances play a role in transcriptional regulation. Functional gene regulatory regions should therefore display characteristics that go beyond the mere occurrence of a specific sequence motif. One such characteristic is the presence of clusters of b...

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Section: Discussionmentioning

confidence: 99%

Regulatory network control of blood stem cells

Göttgens

2015

Blood

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“…Alternatively, the chemical micro-and macro-environment in a tissue can be studied by computational modeling (Kalig et al, 2013;Kirouac et al, 2010). However, the validity of a mathematical model depends on the availability of input parameters.…”

Section: Fig 1: Microenvironmental Factors Affecting Cell Behaviormentioning

confidence: 99%

State-of-the-art of 3D cultures (organs-on-a-chip) in safety testing and pathophysiology

Alépée

Bahinski

Daneshian

et al. 2014

ALTEX

172

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* a report of t 4 -the transatlantic think tank for toxicology, a collaboration of the toxicologically oriented chairs in Baltimore, Konstanz and Utrecht sponsored by the Doerenkamp-Zbinden Foundation; participants do not represent their institutions and do not necessarily endorse all recommendations made. Summary Integrated approaches using different in vitro methods in combination with bioinformatics can (i) increase the success rate and speed of drug development; (ii) improve the accuracy of toxicological risk assessment

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“…Most studies currently remain focused on local level networks within a set of related genes or protein expressions (Bapat et al, 2010;Kirouac et al, 2010). Yet a combination of different levels of networks can be connected to overview the whole system.…”

Section: Comprehensive Vs Focused Metabolomicsmentioning

confidence: 99%