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Hendriks, J.

Publications and source records attributed to Hendriks, J..

2 recordsLinked to original sources

Single-cell ID-seq identifies BMP signaling as a driver of a late stage epidermal differentiation program.

AbstractEpidermal homeostasis requires balanced and coordinated adult stem cell renewal and differentiation. These processes are controlled by both extracellular signaling and by cell intrinsic transcription regulatory networks, yet how these control mechanisms are integrated to achieve this unclear. Here, we developed single-cell ID-seq and measured 69 antibody-DNA conjugates (including 34 phospho-specific epitopes) to study the activation state of signaling pathways during epidermal differentiation at the single-cell level. Computational pseudo-timing inference revealed activation of the JAK-STAT, WNT and BMP pathways along the epidermal differentiation trajectory. During differentiation, cells start producing BMP2 ligands and activate the canonical intracellular effectors SMAD1/5/9. Mechanistically, the BMP pathway is responsible for directly activating a specific transcription program that includes the key differentiation transcription factors MAF and MAFB to allow terminal differentiation. We propose that incorporating autocrine signaling pathway activation into a transcription regulatory network enables regional coordination of transcription programs during epidermal differentiation.

developmental biology

Maintaining maximal metabolic flux by gene expression control

Many evolutionarily successful bacteria attain high growth rates across growth-permissive conditions. They express metabolic networks that synthesise all cellular components at a high rate. Metabolic reaction rates are bounded by the concentration of the catalysing enzymes and cells have finite resources available for enzyme synthesis. Therefore, bacteria that grow fast should express needed metabolic enzymes at precisely tuned concentrations. To maintain fast growth in a dynamic environment, cells should adjust gene expression of metabolic enzymes. The activity of many of the associated transcription factors is regulated by their binding to intracellular metabolites. We study optimal metabolite-mediated regulation of metabolic-gene expression that preserves maximisation of metabolic fluxes across varying conditions. We logically derive the underlying control logic of this type of optimal regulation, which we term Specific Flux (q) Optimization by Robust Adaptive Control (qORAC), and illustrate it with several examples. We show that optimal metabolic flux can be maintained in the face of K changing parameters only if the number of transcription-factor-binding metabolites is at least equal to K. qORAC-regulation of metabolism can generally be achieved with basic biochemical interactions, indicating that metabolism can operate close to optimality. The theory that we present is directly applicable to synthetic biology, biotechnology and fundamental studies of the regulation of metabolism.

systems biology