Elizabeth A. Strychalski

Bio: Elizabeth A. Strychalski is an academic researcher from National Institute of Standards and Technology. The author has contributed to research in topics: Synthetic biology & Medicine. The author has an hindex of 14, co-authored 37 publications receiving 2096 citations. Previous affiliations of Elizabeth A. Strychalski include Cornell University.

Design and synthesis of a minimal bacterial genome

Abstract: We used whole-genome design and complete chemical synthesis to minimize the 1079-kilobase pair synthetic genome of Mycoplasma mycoides JCVI-syn1.0. An initial design, based on collective knowledge of molecular biology combined with limited transposon mutagenesis data, failed to produce a viable cell. Improved transposon mutagenesis methods revealed a class of quasi-essential genes that are needed for robust growth, explaining the failure of our initial design. Three cycles of design, synthesis, and testing, with retention of quasi-essential genes, produced JCVI-syn3.0 (531 kilobase pairs, 473 genes), which has a genome smaller than that of any autonomously replicating cell found in nature. JCVI-syn3.0 retains almost all genes involved in the synthesis and processing of macromolecules. Unexpectedly, it also contains 149 genes with unknown biological functions. JCVI-syn3.0 is a versatile platform for investigating the core functions of life and for exploring whole-genome design.

Genetic circuit design automation

Abstract: INTRODUCTION Cells respond to their environment, make decisions, build structures, and coordinate tasks. Underlying these processes are computational operations performed by networks of regulatory proteins that integrate signals and control the timing of gene expression. Harnessing this capability is critical for biotechnology projects that require decision-making, control, sensing, or spatial organization. It has been shown that cells can be programmed using synthetic genetic circuits composed of regulators organized to generate a desired operation. However, the construction of even simple circuits is time-intensive and unreliable. RATIONALE Electronic design automation (EDA) was developed to aid engineers in the design of semiconductor-based electronics. In an effort to accelerate genetic circuit design, we applied principles from EDA to enable increased circuit complexity and to simplify the incorporation of synthetic gene regulation into genetic engineering projects. We used the hardware description language Verilog to enable a user to describe a circuit function. The user also specifies the sensors, actuators, and “user constraints file” (UCF), which defines the organism, gate technology, and valid operating conditions. Cello (www.cellocad.org) uses this information to automatically design a DNA sequence encoding the desired circuit. This is done via a set of algorithms that parse the Verilog text, create the circuit diagram, assign gates, balance constraints to build the DNA, and simulate performance. RESULTS Cello designs circuits by drawing upon a library of Boolean logic gates. Here, the gate technology consists of NOT/NOR logic based on repressors. Gate connection is simplified by defining the input and output signals as RNA polymerase (RNAP) fluxes. We found that the gates need to be insulated from their genetic context to function reliably in the context of different circuits. Each gate is isolated using strong terminators to block RNAP leakage, and input interchangeability is improved using ribozymes and promoter spacers. These parts are varied for each gate to avoid breakage due to recombination. Measuring the load of each gate and incorporating this into the optimization algorithms further reduces evolutionary pressure. Cello was applied to the design of 60 circuits for Escherichia coli , where the circuit function was specified using Verilog code and transformed to a DNA sequence. The DNA sequences were built as specified with no additional tuning, requiring 880,000 base pairs of DNA assembly. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts). Across all circuits, 92% of the 412 output states functioned as predicted. CONCLUSION Our work constitutes a hardware description language for programming living cells. This required the co-development of design algorithms with gates that are sufficiently simple and robust to be connected by automated algorithms. We demonstrate that engineering principles can be applied to identify and suppress errors that complicate the compositions of larger systems. This approach leads to highly repetitive and modular genetics, in stark contrast to the encoding of natural regulatory networks. The use of a hardware-independent language and the creation of additional UCFs will allow a single design to be transformed into DNA for different organisms, genetic endpoints, operating conditions, and gate technologies.

Size-dependent DNA mobility in nanochannels

Abstract: Nanofluidic slits are used to investigate surface interactions during electrophoresis between DNA molecules and channel walls. The channels have vertical dimensions of 19 and 70nm and contain no sieving matrix. Size-dependent mobility is observed for DNA in the 19nm channels. We present a model for double stranded DNA mobility in the nanochannels that accurately predicts the size dependence of the DNA mobility in the range of 2000–10000bp. Due to surface interactions, the DNA mobility in the nanochannels scales as N−1∕2. These results suggest that the notion of free solution DNA electrophoresis breaks down due to surface interactions in nanoscale environments.

Nanofluidic structures with complex three-dimensional surfaces

Abstract: Nanofluidic devices have typically explored a design space of patterns limited by a single nanoscale structure depth. A method is presented here for fabricating nanofluidic structures with complex three-dimensional (3D) surfaces, utilizing a single layer of grayscale photolithography and standard integrated circuit manufacturing tools. This method is applied to construct nanofluidic devices with numerous (30) structure depths controlled from approximately 10 to approximately 620 nm with an average standard deviation of 1 cm. A prototype 3D nanofluidic device is demonstrated that implements size exclusion of rigid nanoparticles and variable nanoscale confinement and deformation of biomolecules.

Diffusion of DNA in Nanoslits

Abstract: We observed the free diffusion of individual 10 kbp, (1/2)λ (24.2 kbp), and λ (48.5 kbp) double-stranded deoxyribonucleic acid (DNA) molecules in fused-silica nanoslits with depths from 541 to 24 nm using epifluorescence video microscopy. Diffusivity, D, scaled with nanoslit depth, h, according to D ∝ hα, where α was 0.47 ± 0.05, 0.51 ± 0.06, and 0.47 ± 0.05 for 10 kbp, (1/2)λ, and λ DNA, respectively, in disagreement with the value of two-thirds predicted by blob theory. We observed no change in scaling behavior for h less than the persistence length of DNA, as predicted by reflecting rod theory. The scaling of D with DNA length, N, followed D ∝ N−1, indicating hydrodynamic screening in accordance with Rouse dynamics. Our results establish these scaling exponents for smaller h and greater DNA confinement than previous studies.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

A global genetic interaction network maps a wiring diagram of cellular function

Abstract: INTRODUCTION Genetic interactions occur when mutations in two or more genes combine to generate an unexpected phenotype. An extreme negative or synthetic lethal genetic interaction occurs when two mutations, neither lethal individually, combine to cause cell death. Conversely, positive genetic interactions occur when two mutations produce a phenotype that is less severe than expected. Genetic interactions identify functional relationships between genes and can be harnessed for biological discovery and therapeutic target identification. They may also explain a considerable component of the undiscovered genetics associated with human diseases. Here, we describe construction and analysis of a comprehensive genetic interaction network for a eukaryotic cell. RATIONALE Genome sequencing projects are providing an unprecedented view of genetic variation. However, our ability to interpret genetic information to predict inherited phenotypes remains limited, in large part due to the extensive buffering of genomes, making most individual eukaryotic genes dispensable for life. To explore the extent to which genetic interactions reveal cellular function and contribute to complex phenotypes, and to discover the general principles of genetic networks, we used automated yeast genetics to construct a global genetic interaction network. RESULTS We tested most of the ~6000 genes in the yeast Saccharomyces cerevisiae for all possible pairwise genetic interactions, identifying nearly 1 million interactions, including ~550,000 negative and ~350,000 positive interactions, spanning ~90% of all yeast genes. Essential genes were network hubs, displaying five times as many interactions as nonessential genes. The set of genetic interactions or the genetic interaction profile for a gene provides a quantitative measure of function, and a global network based on genetic interaction profile similarity revealed a hierarchy of modules reflecting the functional architecture of a cell. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections associated with defects in cell cycle progression or cellular proteostasis. Importantly, the global network illustrates how coherent sets of negative or positive genetic interactions connect protein complex and pathways to map a functional wiring diagram of the cell. CONCLUSION A global genetic interaction network highlights the functional organization of a cell and provides a resource for predicting gene and pathway function. This network emphasizes the prevalence of genetic interactions and their potential to compound phenotypes associated with single mutations. Negative genetic interactions tend to connect functionally related genes and thus may be predicted using alternative functional information. Although less functionally informative, positive interactions may provide insights into general mechanisms of genetic suppression or resiliency. We anticipate that the ordered topology of the global genetic network, in which genetic interactions connect coherently within and between protein complexes and pathways, may be exploited to decipher genotype-to-phenotype relationships.

Principles and applications of nanofluidic transport

Abstract: The evolution from microfluidic to nanofluidic systems has been accompanied by the emergence of new fluid phenomena and the potential for new nanofluidic devices. This review provides an introduction to the theory of nanofluidic transport, focusing on the various forces that influence the movement of both solvents and solutes through nanochannels, and reviews the applications of nanofluidic devices in separation science and energy conversion.

A Review: Electrospinning of Biopolymer Nanofibers and their Applications

Abstract: Electrospinning is a fabrication technique, which can be used to create nanofibrous non‐wovens from a variety of starting materials. The structure, chemical and mechanical stability, functionality, and other properties of the mats can be modified to match end applications. In this review, an introduction to biopolymers and the electrospinning process, as well as an overview of applications of nanofibrous biopolymer mats created by the electrospinning process will be discussed. Biopolymers will include polysaccharides (cellulose, chitin, chitosan, dextrose), proteins (collagen, gelatin, silk, etc.), DNA, as well as some biopolymer derivatives and composites.