Antibodies against specific extracellular epitopes of the glucagon receptor block glucagon binding.

Polyclonal antibodies were prepared against synthetic peptides corresponding to four different extramembrane segments of the rat glucagon receptor. The antibodies bound specifically to native glucagon receptor as judged by immunofluorescence microscopy of cultured cells expressing a synthetic gene for the receptor. Antibodies to peptides designated PR-15 and DK-12 were directed against amino acid residues 103-117 and 126-137, respectively, of the extracellular N-terminal tail. Antibody to peptide KD-14 was directed against residues 206-219 of the first extracellular loop, and antibody to peptide ST-18, against the intracellular C-terminal tail, residues 468-485. The DK-12 and KD-14 antibodies, but not the PR-15 and ST-18 antibodies, could effectively block binding of 125I-labeled glucagon to its receptor in liver membranes. Incubation of these antibodies with rat liver membranes resulted in both a decrease in the maximal hormonal binding capacity and an apparent decrease in glucagon affinity for its receptor. These effects were abolished in the presence of excess specific peptide antigen. In addition, DK-12 and KD-14 antibodies, but not PR-15 and ST-18 antibodies, interfered with glucagon-induced adenylyl cyclase activation in rat liver membranes and behaved as functional glucagon antagonists. These results demonstrate that DK-12 and KD-14 antibodies are pharmacologically active glucagon antagonists and strongly suggest that residues 126-137 of the N-terminal tail and residues 206-219 of the first extracellular loop contain determinants of ligand binding and may comprise the primary ligand-binding site on the glucagon receptor.

The antimicrobial action of pseudin-2

The amphibian antimicrobial peptide pseudin-2 is a peptide derived from the skin of the South-American frog Pseudis paradoxa (Olson et al., 2001). This peptide possesses tremendous potential as a therapeutic lead since it has been shown to possess both antimicrobial as well insulin-releasing properties (Olson et al., 2001; Abdel-Wahab et al., 2008). This study aimed to develop pseudin-2’s potential by understanding and improving its properties as an antimicrobial agent. The structure-function relationships of pseudin-2 were explored using a combination of in-vitro and in-silico techniques, with an aim to predict how the structure of the peptide may be altered in order to improve its efficacy. A library of pseudin-2 mutants was generated by randomizing codons at positions 10, 14 and 18 of a synthetic gene, using NNK saturation mutagenesis. Analysis of these novel peptides broadly confirmed, in line with literature precedent, that anti-microbial activity increases with increased positive charge. Specifically, 2 positively-charged residues at positions 10 and 14 and a hydrophobic at position 18 are preferred. However, substitution at position 14 with some polar, non-charged residues also created peptides with antimicrobial activity. Interestingly, the pseudin-2 analogue [10-E, 14-Q, 18-L] which is identical to pseudin-2, except that the residues at positions 10 and 14 are switched, showed no anti-microbial activity at all. Molecular dynamics simulations of pseudin-2 showed that the peptide possesses two equilibrium structures in a membrane environment: a linear and a kinked a-helix which both embed into the membrane at an angle. Biophysical characterization using circular dichroism spectroscopy confirmed that the peptide is helical within the membrane environment whilst linear dichroism established that the peptide has no defined orientation within the membrane. Collectively, these data indicate that Pseudin-2 exerts its antimicrobial activity via the carpet model.

Regulatable and modulable background expression control in prokaryotic synthetic circuits by auxiliary repressor binding sites.

Expression control in synthetic genetic circuitry, for example, for construction of sensitive biosensors, is hampered by the lack of DNA parts that maintain ultralow background yet achieve high output upon signal integration by the cells. Here, we demonstrate how placement of auxiliary transcription factor binding sites within a regulatable promoter context can yield an important gain in signal-to-noise output ratios from prokaryotic biosensor circuits. As a proof of principle, we use the arsenite-responsive ArsR repressor protein from Escherichia coli and its cognate operator. Additional ArsR operators placed downstream of its target promoter can act as a transcription roadblock in a distance-dependent manner and reduce background expression of downstream-placed reporter genes. We show that the transcription roadblock functions both in cognate and heterologous promoter contexts. Secondary ArsR operators placed upstream of their promoter can also improve signal-to-noise output while maintaining effector dependency. Importantly, background control can be released through the addition of micromolar concentrations of arsenite. The ArsR-operator system thus provides a flexible system for additional gene expression control, which, given the extreme sensitivity to micrograms per liter effector concentrations, could be applicable in more general contexts.

Controlling gene expression in enterobacteriaceae: studies on sRNAs and strategies for synthetic biology

Dissertation presented to obtain the Master Degree in Molecular, Genetics and Biomedicine

Human synthetic lethal inference as potential anti-cancer target gene detection

Background: Two genes are called synthetic lethal (SL) if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods. Results: In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes) in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases) as well as on existent approved drugs (DrugBank database) supports our selection of cancer-therapy candidates.Conclusions: Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.

Synthetic and natural polycations for gene therapy: State of the art and new perspectives

Currently, the major drawback of gene therapy is the gene transfection rate. The two main types of vectors that. are used in gene therapy are based on viral or non-viral gene delivery systems. There are several non-viral systems that can be used to transfer foreign genetic material into the human body. In order to do so, the DNA to be transferred must escape the processes that affect the disposition of macromolecules. These processes include the interaction with blood components, vascular endothelial cells and uptake by the reticuloendothelial system. Furthermore, the degradation of therapeutic DNA by serum nucleases is also a potential obstacle for functional delivery to the target cell. Cationic polymers have a great potential for DNA complexation and may be useful as non-viral vectors for gene therapy applications. The objective of this review was to address the state of the art in gene therapy using synthetic and natural polycations and the latest strategies to improve the efficiency of gene transfer into the cell.

Acquisition of a natural resistance gene renders a clinical strain of methicillin-resistant Staphylococcus aureus resistant to the synthetic antibiotic linezolid.

Linezolid, which targets the ribosome, is a new synthetic antibiotic that is used for treatment of infections caused by Gram-positive pathogens. Clinical resistance to linezolid, so far, has been developing only slowly and has involved exclusively target site mutations. We have discovered that linezolid resistance in a methicillin-resistant Staphylococcus aureus hospital strain from Colombia is determined by the presence of the cfr gene whose product, Cfr methyltransferase, modifies adenosine at position 2503 in 23S rRNA in the large ribosomal subunit. The molecular model of the linezolid-ribosome complex reveals localization of A2503 within the drug binding site. The natural function of cfr likely involves protection against natural antibiotics whose site of action overlaps that of linezolid. In the chromosome of the clinical strain, cfr is linked to ermB, a gene responsible for dimethylation of A2058 in 23S rRNA. Coexpression of these two genes confers resistance to all the clinically relevant antibiotics that target the large ribosomal subunit. The association of the ermB/cfr operon with transposon and plasmid genetic elements indicates its possible mobile nature. This is the first example of clinical resistance to the synthetic drug linezolid which involves a natural resistance gene with the capability of disseminating among Gram-positive pathogenic strains.

Oscillatory genetic circuits: new designs and mathematical models

Introduction and motivation: A wide variety of organisms have developed in-ternal biomolecular clocks in order to adapt to cyclic changes of the environment. Clock operation involves genetic networks. These genetic networks have to be mod¬eled in order to understand the underlying mechanism of oscillations and to design new synthetic cellular clocks. This doctoral thesis has resulted in two contributions to the fields of genetic clocks and systems and synthetic biology, generally. The first contribution is a new genetic circuit model that exhibits an oscillatory behav¬ior through catalytic RNA molecules. The second and major contribution is a new genetic circuit model demonstrating that a repressor molecule acting on the positive feedback of a self-activating gene produces reliable oscillations. First contribution: A new model of a synthetic genetic oscillator based on a typical two-gene motif with one positive and one negative feedback loop is pre¬sented. The originality is that the repressor is a catalytic RNA molecule rather than a protein or a non-catalytic RNA molecule. This catalytic RNA is a ribozyme that acts post-transcriptionally by binding to and cleaving target mRNA molecules. This genetic clock involves just two genes, a mRNA and an activator protein, apart from the ribozyme. Parameter values that produce a circadian period in both determin¬istic and stochastic simulations have been chosen as an example of clock operation. The effects of the stochastic fluctuations are quantified by a period histogram and autocorrelation function. The conclusion is that catalytic RNA molecules can act as repressor proteins and simplify the design of genetic oscillators. Second and major contribution: It is demonstrated that a self-activating gene in conjunction with a simple negative interaction can easily produce robust matically validated. This model is comprised of two clearly distinct parts. The first is a positive feedback created by a protein that binds to the promoter of its own gene and activates the transcription. The second is a negative interaction in which a repressor molecule prevents this protein from binding to its promoter. A stochastic study shows that the system is robust to noise. A deterministic study identifies that the oscillator dynamics are mainly driven by two types of biomolecules: the protein, and the complex formed by the repressor and this protein. The main conclusion of this study is that a simple and usual negative interaction, such as degradation, se¬questration or inhibition, acting on the positive transcriptional feedback of a single gene is a sufficient condition to produce reliable oscillations. One gene is enough and the positive transcriptional feedback signal does not need to activate a second repressor gene. At the genetic level, this means that an explicit negative feedback loop is not necessary. Unlike many genetic oscillators, this model needs neither cooperative binding reactions nor the formation of protein multimers. Applications and future research directions: Recently, RNA molecules have been found to play many new catalytic roles. The first oscillatory genetic model proposed in this thesis uses ribozymes as repressor molecules. This could provide new synthetic biology design principles and a better understanding of cel¬lular clocks regulated by RNA molecules. The second genetic model proposed here involves only a repression acting on a self-activating gene and produces robust oscil¬lations. Unlike current two-gene oscillators, this model surprisingly does not require a second repressor gene. This result could help to clarify the design principles of cellular clocks and constitute a new efficient tool for engineering synthetic genetic oscillators. Possible follow-on research directions are: validate models in vivo and in vitro, research the potential of second model as a genetic memory, investigate new genetic oscillators regulated by non-coding RNAs and design a biosensor of positive feedbacks in genetic networks based on the operation of the second model Resumen Introduccion y motivacion: Una amplia variedad de organismos han desarro-llado relojes biomoleculares internos con el fin de adaptarse a los cambios ciclicos del entorno. El funcionamiento de estos relojes involucra redes geneticas. El mo delado de estas redes geneticas es esencial tanto para entender los mecanismos que producen las oscilaciones como para diseiiar nuevos circuitos sinteticos en celulas. Esta tesis doctoral ha dado lugar a dos contribuciones dentro de los campos de los circuitos geneticos en particular, y biologia de sistemas y sintetica en general. La primera contribucion es un nuevo modelo de circuito genetico que muestra un comportamiento oscilatorio usando moleculas de ARN cataliticas. La segunda y principal contribucion es un nuevo modelo de circuito genetico que demuestra que una molecula represora actuando sobre el lazo de un gen auto-activado produce oscilaciones robustas. Primera contribucion: Es un nuevo modelo de oscilador genetico sintetico basado en una tipica red genetica compuesta por dos genes con dos lazos de retroa-limentacion, uno positivo y otro negativo. La novedad de este modelo es que el represor es una molecula de ARN catalftica, en lugar de una protefna o una molecula de ARN no-catalitica. Este ARN catalitico es una ribozima que actua despues de la transcription genetica uniendose y cortando moleculas de ARN mensajero (ARNm). Este reloj genetico involucra solo dos genes, un ARNm y una proteina activadora, aparte de la ribozima. Como ejemplo de funcionamiento, se han escogido valores de los parametros que producen oscilaciones con periodo circadiano (24 horas) tanto en simulaciones deterministas como estocasticas. El efecto de las fluctuaciones es-tocasticas ha sido cuantificado mediante un histograma del periodo y la función de auto-correlacion. La conclusion es que las moleculas de ARN con propiedades cataliticas pueden jugar el misnio papel que las protemas represoras, y por lo tanto, simplificar el diseno de los osciladores geneticos. Segunda y principal contribucion: Es un nuevo modelo de oscilador genetico que demuestra que un gen auto-activado junto con una simple interaction negativa puede producir oscilaciones robustas. Este modelo ha sido estudiado y validado matematicamente. El modelo esta compuesto de dos partes bien diferenciadas. La primera parte es un lazo de retroalimentacion positiva creado por una proteina que se une al promotor de su propio gen activando la transcription. La segunda parte es una interaction negativa en la que una molecula represora evita la union de la proteina con el promotor. Un estudio estocastico muestra que el sistema es robusto al ruido. Un estudio determinista muestra que la dinamica del sistema es debida principalmente a dos tipos de biomoleculas: la proteina, y el complejo formado por el represor y esta proteina. La conclusion principal de este estudio es que una simple y usual interaction negativa, tal como una degradation, un secuestro o una inhibition, actuando sobre el lazo de retroalimentacion positiva de un solo gen es una condition suficiente para producir oscilaciones robustas. Un gen es suficiente y el lazo de retroalimentacion positiva no necesita activar a un segundo gen represor, tal y como ocurre en los relojes actuales con dos genes. Esto significa que a nivel genetico un lazo de retroalimentacion negativa no es necesario de forma explicita. Ademas, este modelo no necesita reacciones cooperativas ni la formation de multimeros proteicos, al contrario que en muchos osciladores geneticos. Aplicaciones y futuras lineas de investigacion: En los liltimos anos, se han descubierto muchas moleculas de ARN con capacidad catalitica. El primer modelo de oscilador genetico propuesto en esta tesis usa ribozimas como moleculas repre¬soras. Esto podria proporcionar nuevos principios de diseno en biologia sintetica y una mejor comprension de los relojes celulares regulados por moleculas de ARN. El segundo modelo de oscilador genetico propuesto aqui involucra solo una represion actuando sobre un gen auto-activado y produce oscilaciones robustas. Sorprendente-mente, un segundo gen represor no es necesario al contrario que en los bien conocidos osciladores con dos genes. Este resultado podria ayudar a clarificar los principios de diseno de los relojes celulares naturales y constituir una nueva y eficiente he-rramienta para crear osciladores geneticos sinteticos. Algunas de las futuras lineas de investigation abiertas tras esta tesis son: (1) la validation in vivo e in vitro de ambos modelos, (2) el estudio del potential del segundo modelo como circuito base para la construction de una memoria genetica, (3) el estudio de nuevos osciladores geneticos regulados por ARN no codificante y, por ultimo, (4) el rediseno del se¬gundo modelo de oscilador genetico para su uso como biosensor capaz de detectar genes auto-activados en redes geneticas.

A synthetic cryIC gene, encoding a Bacillus thuringiensis δ-endotoxin, confers Spodoptera resistance in alfalfa and tobacco

Spodoptera species, representing widespread polyphagous insect pests, are resistant to Bacillus thuringiensis δ-endotoxins used thus far as insecticides in transgenic plants. Here we describe the chemical synthesis of a cryIC gene by a novel template directed ligation–PCR method. This simple and economical method to construct large synthetic genes can be used when routine resynthesis of genes is required. Chemically phosphorylated adjacent oligonucleotides of the gene to be synthesized are assembled and ligated on a single-stranded, partially homologous template derived from a wild-type gene (cryIC in our case) by a thermostable Pfu DNA ligase using repeated cycles of melting, annealing, and ligation. The resulting synthetic DNA strands are selectively amplified by PCR with short specific flanking primers that are complementary only to the new synthetic DNA. Optimized expression of the synthetic cryIC gene in alfalfa and tobacco results in the production of 0.01–0.2% of total soluble proteins as CryIC toxin and provides protection against the Egyptian cotton leafworm (Spodoptera littoralis) and the beet armyworm (Spodoptera exigua). To facilitate selection and breeding of Spodoptera-resistant plants, the cryIC gene was linked to a pat gene, conferring resistance to the herbicide BASTA.

Structure and function in rhodopsin: high level expression of a synthetic bovine opsin gene and its mutants in stable mammalian cell lines.

Stable mammalian cell lines harboring a synthetic bovine opsin gene have been derived from the suspension-adapted HEK293 cell line. The opsin gene is under the control of the immediate-early cytomegalovirus promoter/enhancer in an expression vector that also contains a selectable marker (Neo) governed by a relatively weak promoter. The cell lines expressing the opsin gene at high levels are selected by growth in the presence of high concentrations of the antibiotic geneticin. Under the conditions used for cell growth in suspension, opsin is produced at saturated culture levels of more than 2 mg/liter. After reconstitution with 11-cis-retinal, rhodopsin is purified to homogeneity in a single step by immunoaffinity column chromatography. Rhodopsin thus prepared (> 90% recovery at concentrations of up to 15 microM) is indistinguishable from rhodopsin purified from bovine rod outer segments by the following criteria: (i) UV/Vis absorption spectra in the dark and after photobleaching and the rate of metarhodopsin II decay, (ii) initial rates of transducin activation, and (iii) the rate of phosphorylation by rhodopsin kinase. Although mammalian cell opsin migrates slower than rod outer segment opsin on SDS/polyacrylamide gels, presumably due to a different N-glycosylation pattern, their mobilities after deglycosylation are identical. This method has enabled the preparation of several site-specific mutants of bovine opsin in comparable amounts.

Learning Models of Gene Expression from Synthetic DNA Sequences

Thesis (Ph.D.)--University of Washington, 2016-06

Synthetic regulation of eukaryotic gene expression by noncoding RNA

Synthetic biological systems promise to combine the spectacular diversity of biological functionality with engineering principles to design new life to address many pressing needs. As these engineered systems advance in sophistication, there is ever-greater need for customizable, situation-specific expression of desired genes. However, existing gene control platforms are generally not modular, or do not display performance requirements required for robust phenotypic responses to input signals. This work expands the capabilities of eukaryotic gene control in two important directions.

For development of greater modularity, we extend the use of synthetic self-cleaving ribozyme switches to detect changes in input protein levels and convey that information into programmed gene expression in eukaryotic cells. We demonstrate both up- and down-regulation of levels of an output transgene by more than 4-fold in response to rising input protein levels, with maximal output gene expression approaching the highest levels observed in yeast. In vitro experiments demonstrate protein-dependent ribozyme activity modulation. We further demonstrate the platform in mammalian cells. Our switch devices do not depend on special input protein activity, and can be tailored to respond to any input protein to which a suitable RNA aptamer can be developed. This platform can potentially be employed to regulate the expression of any transgene or any endogenous gene by 3’ UTR replacement, allowing for more complex cell state-specific reprogramming.

We also address an important concern with ribozyme switches, and riboswitch performance in general, their dynamic range. While riboswitches have generally allowed for versatile and modular regulation, so far their dynamic ranges of output gene modulation have been modest, generally at most 10-fold. We address this shortcoming by developing a modular genetic amplifier for near-digital control of eukaryotic gene expression. We combine ribozyme switch-mediated regulation of a synthetic TF with TF-mediated regulation of an output gene. The amplifier platform allows for as much as 20-fold regulation of output gene expression in response to input signal, with maximal expression approaching the highest levels observed in yeast, yet being tunable to intermediate and lower expression levels. EC50 values are more than 4 times lower than in previously best-performing non-amplifier ribozyme switches. The system design retains the modular-input architecture of the ribozyme switch platform, and the near-digital dynamic ranges of TF-based gene control.

Together, these developments suggest great potential for the wide applicability of these platforms for better-performing eukaryotic gene regulation, and more sophisticated, customizable reprogramming of cellular activity.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.