Learning feedback molecular network models using integer linear programming.

Analysis of intracellular molecular networks has many applications in understanding of the molecular bases of some complex diseases and finding effective therapeutic targets for drug development. To perform such analyses, the molecular networks need to be converted into computational models. In general, network models constructed using literature and pathway databases may not accurately predict experimental network data.

Exploring extreme signaling failures in intracellular molecular networks.

Developing novel methods for the analysis of intracellular signaling networks is essential for understanding interconnected biological processes that underlie complex human disorders. A fundamental goal of this research is to quantify the vulnerability of a signaling network to the dysfunction of one or multiple molecules, when the dysfunction is defined as an incorrect response to the input signals. In this study, we propose an efficient algorithm to identify the extreme signaling failures that can induce the most detrimental impact on the physiological function of a molecular network.

Modeling and measurement of signaling outcomes affecting decision making in noisy intracellular networks using machine learning methods.

Characterization of decision-making in cells in response to received signals is of importance for understanding how cell fate is determined. The problem becomes multi-faceted and complex when we consider cellular heterogeneity and dynamics of biochemical processes. In this paper, we present a unified set of decision-theoretic, machine learning and statistical signal processing methods and metrics to model the precision of signaling decisions, in the presence of uncertainty, using single cell data.

Computation capacities of a broad class of signaling networks are higher than their communication capacities.

Due to structural and functional abnormalities or genetic variations and mutations, there may be dysfunctional molecules within an intracellular signaling network that do not allow the network to correctly regulate its output molecules, such as transcription factors. This disruption in signaling interrupts normal cellular functions and may eventually develop some pathological conditions. In this paper, computation capacity of signaling networks is introduced as a fundamental limit on signaling capability and performance of such networks.

Computation and measurement of cell decision making errors using single cell data.

In this study a new computational method is developed to quantify decision making errors in cells, caused by noise and signaling failures. Analysis of tumor necrosis factor (TNF) signaling pathway which regulates the transcription factor Nuclear Factor κB (NF-κB) using this method identifies two types of incorrect cell decisions called false alarm and miss. These two events represent, respectively, declaring a signal which is not present and missing a signal that does exist.

Advanced fault diagnosis methods in molecular networks.

Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network.

Quantitative analysis of intracellular communication and signaling errors in signaling networks.

Background: Intracellular signaling networks transmit signals from the cell membrane to the nucleus, via biochemical interactions. The goal is to regulate some target molecules, to properly control the cell function. Regulation of the target molecules occurs through the communication of several intermediate molecules that convey specific signals originated from the cell membrane to the specific target outputs.

AKT/GSK3 signaling pathway and schizophrenia.

Schizophrenia is a prevalent complex trait disorder manifested by severe neurocognitive dysfunctions and lifelong disability. During the past few years several studies have provided direct evidence for the involvement of different signaling pathways in schizophrenia. In this review, we mainly focus on AKT/GSK3 signaling pathway in schizophrenia.

Fault diagnosis engineering in molecular signaling networks: an overview and applications in target discovery.

Fault diagnosis engineering is a key component of modern industrial facilities and complex systems, and has gone through considerable developments in the past few decades. In this paper, the principles and concepts of molecular fault diagnosis engineering are reviewed. In this area, molecular intracellular networks are considered as complex systems that may fail to function, due to the presence of some faulty molecules.

Complex human disorders and molecular system engineering: historical perspective and potential impacts.

The challenging nature of complex human disorders has taught us that we can not untangle a disorder unless we understand how the "engine" of molecular systems works. After learning the basic physiology of different organs in the human body, a "molecular revolution" occurred, which has now generated a huge amount of information regarding the function of individual molecules in human cells. The difficult task, however, is to understand how thousands of molecules communicate and work together to deliver a specific function, and more importantly, what goes wrong when the system fails and causes different diseases.

Identification of critical molecules via fault diagnosis engineering.

Systems biology envisions that the application of complex system engineering approaches to cell signaling molecular networks can lead to novel understandings of complex human disorders. In this paper we show that by developing biologically-driven vulnerability assessment methods, the vulnerability of complex signaling networks to the dysfunction of each molecule can be determined. We have analyzed signaling networks that regulate mitosis and the activity of the transcription factor CREB.

NMDA receptor phosphorylation at a site affected in schizophrenia controls synaptic and behavioral plasticity.

Phosphorylation of the NR1 subunit of NMDA receptors (NMDARs) at serine (S) 897 is markedly reduced in schizophrenia patients. However, the role of NR1 S897 phosphorylation in normal synaptic function and adaptive behaviors are unknown. To address these questions, we generated mice in which the NR1 S897 is replaced with alanine (A).

Fault diagnosis engineering of digital circuits can identify vulnerable molecules in complex cellular pathways.

The application of complex system engineering approaches to cell signaling networks should lead to novel understandings and, subsequently, new treatments for complex disorders. In the area of circuit fault diagnosis engineering, there are various methods to identify the defective or vulnerable components of complex digital electronic circuits. In biological systems, however, knowledge is limited regarding the vulnerability of interconnected signaling pathways to the dysfunction of each specific molecule.

Lithium therapy improves neurological function and hippocampal dendritic arborization in a spinocerebellar ataxia type 1 mouse model.

Background: Spinocerebellar ataxia type 1 (SCA1) is a dominantly inherited neurodegenerative disorder characterized by progressive motor and cognitive dysfunction. Caused by an expanded polyglutamine tract in ataxin 1 (ATXN1), SCA1 pathogenesis involves a multifactorial process that likely begins with misfolding of ATXN1, which has functional consequences on its interactions, leading to transcriptional dysregulation. Because lithium has been shown to exert neuroprotective effects in a variety of conditions, possibly by affecting gene expression, we tested the efficacy of lithium treatment in a knock-in mouse model of SCA1 (Sca1(154Q/2Q) mice) that replicates many features of the human disease.

Decreased phosphorylation of NMDA receptor type 1 at serine 897 in brains of patients with Schizophrenia.

NMDA receptor hypofunction in schizophrenia has been inferred by a large number of clinical and preclinical observations; however, whether and how NMDA receptors are exactly involved in the pathogenesis of schizophrenia are still unknown and subject to interpretation. Here we show, in two independent samples of brains from patients with schizophrenia, a significant decrease in the phosphorylation level at serine 897 (S897) of the NMDA receptor type 1 (NR1) subunit. Our finding, together with a previous report that antipsychotics increase phosphorylation of NR1 at S897 in vivo, strongly suggests that insufficient phosphorylation at S897 may contribute to the neuronal pathology underlying schizophrenia.

Convergent evidence for impaired AKT1-GSK3beta signaling in schizophrenia.

AKT-GSK3beta signaling is a target of lithium and as such has been implicated in the pathogenesis of mood disorders. Here, we provide evidence that this signaling pathway also has a role in schizophrenia. Specifically, we present convergent evidence for a decrease in AKT1 protein levels and levels of phosphorylation of GSK3beta at Ser9 in the peripheral lymphocytes and brains of individuals with schizophrenia; a significant association between schizophrenia and an AKT1 haplotype associated with lower AKT1 protein levels; and a greater sensitivity to the sensorimotor gating-disruptive effect of amphetamine, conferred by AKT1 deficiency.

Serine 776 of ataxin-1 is critical for polyglutamine-induced disease in SCA1 transgenic mice.

Polyglutamine-induced neurodegeneration in transgenic mice carrying the spinocerebellar ataxia type 1 (SCA1) gene is modulated by subcellular distribution of ataxin-1 and by components of the protein folding/degradation machinery. Since phosphorylation is a prominent mechanism by which these processes are regulated, we examined phosphorylation of ataxin-1 and found that serine 776 (S776) was phosphorylated. Residue 776 appeared to affect cellular deposition of ataxin-1[82Q] in that ataxin-1[82Q]-A776 failed to form nuclear inclusions in tissue culture cells.

Prenatal viral infection leads to pyramidal cell atrophy and macrocephaly in adulthood: implications for genesis of autism and schizophrenia.

We investigated the role of maternal exposure to human influenza virus (H1N1) in C57BL/6 mice on Day 9 of pregnancy on pyramidal and nonpyramidal cell density, pyramidal nuclear area, and overall brain size in Day 0 neonates and 14-week-old progeny and compared them to sham-infected cohorts. Pyramidal cell density increased significantly (p < 0.0038) by 170% in Day 0 infected mice vs.

Amino acids in a region of ataxin-1 outside of the polyglutamine tract influence the course of disease in SCA1 transgenic mice.

Spinocerebellar ataxia type 1 (SCA1) belongs to a family of polyglutamine induced neurodegenerative disorders. Transgenic mice that overexpress a mutant allele of the SCA1 gene develop a progressive ataxia and Purkinje cell pathology. In this report, the pathological importance of a segment of ataxin-1 previously shown to be important for protein-protein interactions was examined.