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Cells decode information of signaling activation at a scale of tens of minutes by downstream gene expression with a scale of hours to days, leading to cell fate decisions such as cell differentiation. However, no system identification method with such different time scales exists. Here we used compressed sensing technology and developed a system identification method using data of different time scales by recovering signals of missing time points. We measured phosphorylation of ERK and CREB, immediate early gene expression products, and mRNAs of decoder genes for neurite elongation in PC12 cell differentiation and performed system identification, revealing the input-output relationships between signaling and gene expression with sensitivity such as graded or switch-like response and with time delay and gain, representing signal transfer efficiency. We predicted and validated the identified system using pharmacological perturbation. Thus, we provide a versatile method for system identification using data with different time scales.

The upregulation of brown or brown-like beige adipocytes is a potential strategy for the prevention or treatment of diabetes and coronary artery diseases in obese patients. Epicardial adipose tissue (EAT) differs significantly from subcutaneous fat tissue (SAT) in metabolic properties. To investigate properties of EAT further, thermogenesis gene expression was investigated in human autopsy and murine samples, and adipocytes differentiated from EAT mesenchymal cells. Subsequently, analyzed EAT volume alterations were observed to be associated with weight reduction in obese patients by imaging. Gene expression analyses of autopsy samples revealed that UCP‑1 mRNA levels in EAT were significantly increased compared with SAT, and β3‑adrenergic receptor (AR) levels tended to be increased; this finding was verified in comparing EAT with SAT in mice. Browning stimulation of human EAT‑derived MCs increased uncoupling protein‑1 and β3‑AR levels by 3.2 fold‑ and 12.6‑fold compared with SAT‑derived MCs, respectively. Subsequent imaging for EAT volume measurement using multi‑detector computed tomography in 10 obese patients revealed that mean EAT volumes did not significantly decrease following weight loss therapy. The EAT volume alterations were not correlated with weight changes, whereas positive correlations were observed in SAT and visceral adipose tissue. Therefore, the studies in man and mouse on EAT properties demonstrated that susceptibilities of EAT and SAT for browning‑gene expression and diet‑induced volume reduction were grossly different. The data suggest a potential association of EAT with local thermogenetic and metabolic homeostasis in cardiac and/or cardiovascular cells, in conjunction with systemic energy metabolism. [ABSTRACT FROM AUTHOR]

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells. [ABSTRACT FROM AUTHOR]

The dynamic activity of the serine/threonine kinase Akt is crucial for the regulation of diverse cellular functions, but the precise spatiotemporal control of its activity remains a critical issue. Herein, we present a photo-activatable Akt (PA-Akt) system based on a light-inducible protein interaction module of Arabidopsis thaliana cryptochrome2 (CRY2) and CIB1. Akt fused to CRY2phr, which is a minimal light sensitive domain of CRY2 (CRY2-Akt), is reversibly activated by light illumination in several minutes within a physiological dynamic range and specifically regulates downstream molecules and inducible biological functions. We have generated a computational model of CRY2-Akt activation that allows us to use PA-Akt to control the activity quantitatively. The system provides evidence that the temporal patterns of Akt activity are crucial for generating one of the downstream functions of the Akt-FoxO pathway; the expression of a key gene involved in muscle atrophy (Atrogin-1). The use of an optical module with computational modeling represents a general framework for interrogating the temporal dynamics of biomolecules by predictive manipulation of optogenetic modules. [ABSTRACT FROM AUTHOR]

Abstract: To identify candidate serum molecules associated with the progression of type 2 diabetes mellitus (T2DM), we carried out differential proteomic analysis using the KK-Ay mouse, an animal model of T2DM with obesity. We employed an iTRAQ-based quantitative proteomic approach to analyze the proteomic changes in the sera collected from a pair of 4-week-old KK-Ay versus C57BL/6 mice. Among the 227 proteins identified, a total of 45 proteins were differentially expressed in KK-Ay versus C57BL/6 mice. We comparatively analyzed a series of the sera collected at 4 and 12weeks of age from KK-Ay and C57BL/6 mice for the target protein using multiple reaction monitoring analysis, and identified 8 differentially expressed proteins between the sera of these mice at both time points. Among them, serine (or cysteine) peptidase inhibitor, clade A, member 3K (SERPINA3K) levels were elevated significantly in the sera of KK-Ay mice compared to C57BL/6 mice. An in vitro assay revealed that the human homologue SERPINA3 increased the transendothelial permeability of retinal microvascular endothelial cells, which may be involved in the pathogenesis of diabetes and/or diabetic retinopathy. With the identified proteins, our proteomics study could provide valuable clues for a better understanding of the underlying mechanisms associated with T2DM. Biological significance: In this paper, we investigated the serum proteome of KK-Ay mice in a pre-diabetic state compared to that of wild type controls in an attempt to uncover early diagnostic markers of diabetes that are maintained through a diabetic phenotype. We used iTRAQ-based two-dimensional LC–MS/MS serum profiling, and identified several differentially expressed proteins at the pre-diabetic stage. The differential expression was confirmed by multiple reaction monitoring assay, which is fast gaining ground as a sensitive, specific, and cost-effective methodology for relative quantification of the candidate proteins. Using these techniques, we have identified eight candidate proteins of interest including SERPINA3K, which may be important in the pathology of T2DM and/or diabetic retinopathy. [Copyright &y& Elsevier]