Induced pluripotent stem cells (iPSCs) derived from somatic cells of patients represent a powerful tool for biomedical research and may provide a source for replacement therapies. However, the use of viruses encoding the reprogramming factors represents a major limitation of the current technology since even low vector expression may alter the differentiation potential of the iPSCs or induce malignant transformation. Here, we show that fibroblasts from five patients with idiopathic Parkinson’s disease can be efficiently reprogrammed and subsequently differentiated into dopaminergic neurons. Moreover, we derived hiPSCs free of reprogramming factors using Cre-recombinase excisable viruses. Factorfree hiPSCs maintain a pluripotent state and show a global gene expression profile, more closely related to hESCs than to hiPSCs carrying the transgenes. Our results indicate that residual transgene expression in virus-carrying hiPSCs can affect their molecular characteristics and that factor-free hiPSCs therefore represent a more suitable source of cells for modeling of human disease.

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The isolation of human induced pluripotent stem cells (iPSCs)1-3 offers a novel strategy for modeling human disease. Recent studies have reported the derivation and differentiation of disease-specific human iPSCs4-7. However, a key challenge in the field is the demonstration of disease-related phenotypes and the ability to model pathogenesis and treatment of disease in iPSCs. Familial dysautonomia (FD) is a rare but fatal peripheral neuropathy caused by a point mutation in IKBKAP8 involved in transcriptional elongation9. The disease is characterized by the depletion of autonomic and sensory neurons. The specificity to the peripheral nervous system and the mechanism of neuron loss in FD are poorly understood due to the lack of an appropriate model system. Here we report the derivation of patient specific FD-iPSCs and the directed differentiation into cells of all three germ layers including peripheral neurons. Gene expression analysis in purified FD-iPSC derived lineages demonstrates tissue specific mis-splicing of IKBKAP in vitro. Patient-specific neural crest precursors express particularly low levels of normal IKBKAP transcript suggesting a mechanism for disease specificity. FD pathogenesis is further characterized by transcriptome analysis and cell based assays revealing marked defects in neurogenic

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Synthetic gene networks: what have we learned and what do we need? The engineering of mechanical, electrical and chemical systems is enabled by well-established frameworks for handling complexity, reliable means of probing and manipulating system states and the use of testing platforms-tools that are largely lacking in the engineering of biology. Developing properly functioning biological circuits can involve complicated protocols for DNA construction, rudimentary modelguided and rational design, and repeated rounds of trial and error followed by fine-tuning. Limitations in characterizing kinetic processes and interactions between synthetic components and other unknown constituents in vivo make troubleshooting and modeling frustrating and prohibitively time consuming. As a result, the design cycle for engineering synthetic gene networks remains slow and error prone. Fortunately, advances are being made in streamlining the physical construction of artificial biological systems, in the form of resources and methods for building larger engineered DNA systems from smaller defined parts Despite these advances in molecular construction, the task of building synthetic gene networks that function as desired remains extremely challenging. Accelerated, large-scale diversification 34 and the use of characterized component libraries in conjunction with in silico models for a priori design 22 are proving useful in helping to fine-tune network performance toward desired outputs. Even so, in general, synthetic biologists are often fundamentally limited by a dearth of interoperable and modular biological parts, predictive computational modeling capabilities, reliable means of characterizing information flow through engineered gene networks and test platforms for rapidly designing and constructing synthetic circuits. In the following subsections, we discuss four important research efforts that will improve and accelerate the design cycle for next-generation synthetic gene networks: first, advancing and expanding the toolkit of available parts and modules; second, modeling and fine-tuning Ten years since the introduction of the field's inaugural devices-the genetic toggle switch (J.J.C. and colleagues) 1 and repressilator 2 -synthetic biologists have successfully engineered a wide range of functionality into artificial gene circuits, creating switches 1,3-9 , oscillators 2,10-12 , digital logic evaluators 13,14 , filters Thus, despite all of its successes, many more challenges remain in advancing synthetic biology to the realm of higher-order networks with programmable functionality and real-world applicability. Here, instead of reviewing the progress that has been made in synthetic biology, we present challenges and goals for next-generation synthetic gene networks, and describe some of the more compelling circuits to be developed and application areas to be considered. Synthetic biology is focused on the rational construction of biological systems based on engineering principles. During the field's first decade of development, significant progress has been made in designing biological parts and assembling them into genetic circuits to achieve basic functionalities. These circuits have been used to construct proof-of-principle systems with promising results in industrial and medical applications. However, advances in synthetic biology have been limited by a lack of interoperable parts, techniques for dynamically probing biological systems and frameworks for the reliable construction and operation of complex, higher-order networks. As these challenges are addressed, synthetic biologists will be able to construct useful next-generation synthetic gene networks with real-world applications in medicine, biotechnology, bioremediation and bioenergy. rationally programmed based on sequence specificity Next-generation synthetic gene networks Libraries of well-characterized, interoperable parts, such as transcription factors and recombinases, would vastly enhance the ability of synthetic biologists to build more complex gene networks with greater reliability and real-world applicability. In addition to libraries of individual parts, it would be of great value to have well-characterized and interoperable modules (e.g., switches, oscillators and interfaces) that could be used in a plug-and-play fashion to create higher-order networks and programmable cells. As the number of parts and modules expands, high-throughput, combinatorial efforts for quantifying the levels of interference and cross-talk between multiple components within cells will be increasingly important as guides for choosing the most appropriate components for network assembly.

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Alzheimer's disease (AD) is the most common form of age-related dementia, characterized by progressive memory loss and cognitive disturbance. Mutations of presenilin 1 (PS1) and presenilin 2 (PS2) are causative factors for autosomal-dominant early-onset familial AD (FAD). Induced pluripotent stem cell (iPSC) technology can be used to model human disorders and provide novel opportunities to study cellular mechanisms and establish therapeutic strategies against various diseases, including neurodegenerative diseases. Here we generate iPSCs from fibroblasts of FAD patients with mutations in PS1 (A246E) and PS2 (N141I), and characterize the differentiation of these cells into neurons. We find that FAD-iPSC-derived differentiated neurons have increased amyloid b42 secretion, recapitulating the molecular pathogenesis of mutant presenilins. Furthermore, secretion of amyloid b42 from these neurons sharply responds to g-secretase inhibitors and modulators, indicating the potential for identification and validation of candidate drugs. Our findings demonstrate that the FAD-iPSC-derived neuron is a valid model of AD and provides an innovative strategy for the study of age-related neurodegenerative diseases.

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Infections by the Ebola (EboV) and Marburg (MarV) filoviruses cause a rapidly fatal hemorrhagic fever in humans for which no approved antivirals are available1. Filovirus entry is mediated by the viral spike glycoprotein (GP), which attaches viral particles to the cell surface, delivers them to endosomes, and catalyzes fusion between viral and endosomal membranes2. Additional host factors in the endosomal compartment are likely required for viral membrane fusion. However, despite considerable efforts, these critical host factors have defied molecular identification3,4,5. Here we describe a genome-wide haploid genetic screen in human cells to identify host factors required for EboV entry. Our screen uncovered 67 mutations disrupting all six members of the HOPS multisubunit tethering complex, which

The common marmoset (Callithrix jacchus) is increasingly attractive for use as a non-human primate animal model in biomedical research. It has a relatively high reproduction rate for a primate, making it potentially suitable for transgenic modification. Although several attempts have been made to produce non-human transgenic primates, transgene expression in the somatic tissues of live infants has not been demonstrated by objective analyses such as polymerase chain reaction with reverse transcription or western blots. Here we show that the injection of a self-inactivating lentiviral vector in sucrose solution into marmoset embryos results in transgenic common marmosets that expressed the transgene in several organs. Notably, we achieved germline transmission of the transgene, and the transgenic offspring developed normally. The successful creation of transgenic marmosets provides a new animal model for human disease that has the great advantage of a close genetic relationship with humans. This model will be valuable to many fields of biomedical research.