Automated Isolation of Translational Efficiency Bias that Resists the Confounding Effect of GC(AT)-Content

Genomic sequencing projects are an abundant source of information for biological studies ranging from the molecular to the ecological in scale; however, much of the information present may yet be hidden from casual analysis. One such information domain, trends in codon usage, can provide a wealth of information about an organism\u27s genes and their expression. Degeneracy in the genetic code allows more than one triplet codon to code for the same amino acid, and usage of these codons is often biased such that one or more of these synonymous codons is preferred. Detection of this bias is an important tool in the analysis of genomic data, particularly as a predictor of gene expressivity. Methods for identifying codon usage bias in genomic data that rely solely on genomic sequence data are susceptible to being confounded by the presence of several factors simultaneously influencing codon selection. Presented here is a new technique for removing the effects of one of the more common confounding factors, GC(AT)-content, and of visualizing the search-space for codon usage bias through the use of a solution landscape. This technique successfully isolates expressivity-related codon usage trends, using only genomic sequence information, where other techniques fail due to the presence of GC(AT)-content confounding influences

Adaptive laboratory evolution of a genome-reduced Escherichia coli.

Synthetic biology aims to design and construct bacterial genomes harboring the minimum number of genes required for self-replicable life. However, the genome-reduced bacteria often show impaired growth under laboratory conditions that cannot be understood based on the removed genes. The unexpected phenotypes highlight our limited understanding of bacterial genomes. Here, we deploy adaptive laboratory evolution (ALE) to re-optimize growth performance of a genome-reduced strain. The basis for suboptimal growth is the imbalanced metabolism that is rewired during ALE. The metabolic rewiring is globally orchestrated by mutations in rpoD altering promoter binding of RNA polymerase. Lastly, the evolved strain has no translational buffering capacity, enabling effective translation of abundant mRNAs. Multi-omic analysis of the evolved strain reveals transcriptome- and translatome-wide remodeling that orchestrate metabolism and growth. These results reveal that failure of prediction may not be associated with understanding individual genes, but rather from insufficient understanding of the strain's systems biology

Novel tools for engineering eukaryotic cells using a systems level approach.

Engineered cellular systems are a promising avenue for production of a wide range of useful products including renewable fuels, commodity and specialty chemicals, industrial enzymes, and pharmaceuticals. Achieving this breadth of biological products is facilitated by the diversity of organisms found in nature. Using biological and engineering principles, this diversity can be harnessed to make efficient and renewable bio-based products. Such advancements rely upon our ability to modify host genetics and metabolism. This work focuses on the development of new biotechnological tools which enable cellular engineering, and the implementation of these tools in eukaryotic systems. Mammalian cell engineering has important implications in protein therapeutics and gene therapy. One major limitation, however, is the ability to predictably control gene expression. We address this challenge by examining critical aspects of gene expression in human cells. First, we evaluate the impact of selection markers, a common mammalian expression element, on cell line development. In doing so, we determine that Zeocin is the best selection agent for human cells. Next, we identify loci across the genome that support high level expression of recombinant DNA and demonstrate their advantage for stable integration. Finally, we optimize a Cre recombinase based methodology that enables efficient retargeting of genomic loci. Collectively, this work augments the current genetic toolbox for human cell lines. Beyond basic gene expression, there is interest in understanding global interactions within the cell and how they relate to phenomena including gene regulation, expression and disease states. Although our tools are not yet sufficient to study these phenomena in many hosts, methods can be developed in lower eukaryotes and then adapted for more complex hosts later. We demonstrated two methods in S. cerevisiae that utilize a systems-level approach to understand complex phenotypes. First, we developed condition-specific codon optimization that utilizes systems biology information to optimize gene sequence in a condition-specific manner. Additionally, we developed a Graded Dominant Mutant Approach which can be used to dissect multifunctional proteins, understand epigenetic factors, and quantitatively determine protein-DNA interactions. Both can be implemented in many cellular hosts and expand our ability to engineer complex phenotypes in eukaryotic cell systems.Chemical Engineerin

RNA amplification for successful gene profiling analysis

The study of clinical samples is often limited by the amount of material available to study. While proteins cannot be multiplied in their natural form, DNA and RNA can be amplified from small specimens and used for high-throughput analyses. Therefore, genetic studies offer the best opportunity to screen for novel insights of human pathology when little material is available. Precise estimates of DNA copy numbers in a given specimen are necessary. However, most studies investigate static variables such as the genetic background of patients or mutations within pathological specimens without a need to assess proportionality of expression among different genes throughout the genome. Comparative genomic hybridization of DNA samples represents a crude exception to this rule since genomic amplification or deletion is compared among different specimens directly. For gene expression analysis, however, it is critical to accurately estimate the proportional expression of distinct RNA transcripts since such proportions directly govern cell function by modulating protein expression. Furthermore, comparative estimates of relative RNA expression at different time points portray the response of cells to environmental stimuli, indirectly informing about broader biological events affecting a particular tissue in physiological or pathological conditions. This cognitive reaction of cells is similar to the detection of electroencephalographic patterns which inform about the status of the brain in response to external stimuli. As our need to understand human pathophysiology at the global level increases, the development and refinement of technologies for high fidelity messenger RNA amplification have become the focus of increasing interest during the past decade. The need to increase the abundance of RNA has been met not only for gene specific amplification, but, most importantly for global transcriptome wide, unbiased amplification. Now gene-specific, unbiased transcriptome wide amplification accurately maintains proportionality among all RNA species within a given specimen. This allows the utilization of clinical material obtained with minimally invasive methods such as fine needle aspirates (FNA) or cytological washings for high throughput functional genomics studies. This review provides a comprehensive and updated discussion of the literature in the subject and critically discusses the main approaches, the pitfalls and provides practical suggestions for successful unbiased amplification of the whole transcriptome in clinical samples

Circulating tumor cells isolation: The “post-EpCAM era”

Circulating tumor cells (CTCs) represent a submicroscopic fraction detached from a primary tumor and in transit to a secondary site. The prognostic significance of CTCs in metastatic cancer patients was demonstrated for the first time more than ten years ago. To date, it seems clear enough that CTCs are highly heterogeneous and dynamically change their shape. Thus, the inadequacy of epithelial cell adhesion molecule (EpCAM) as universal marker for CTCs detection seems unquestionable and alternative methods able to recognize a broader spectrum of phenotypes are definitely needed. In this review the pleiotropic functions of EpCAM are discussed in detail and the role of the molecule in the biology of CTCs is critically dissected

Smoothing membrane protein structure determination by initial upstream stage improvements

Membrane proteins (MP) constitute 20-30% of all proteins encoded by the genome of various organisms and perform a wide range of essential biological functions. However, despite they represent the largest class of protein drug targets, a relatively small number high-resolution 3D structures have been obtained yet. Membrane protein biogenesis is more complex than that of the soluble proteins and its recombinant biosynthesis has been a major drawback, thus delaying their further structural characterization. Indeed, the major limitation in structure determination of MP is the low yield achieved in recombinant expression, usually coupled to low functionality, pinpointing the optimization target in recombinant MP research. Recently, the growing attention that have been dedicated to the upstream stage of MP bioprocesses allowed great advances, permitting the evolution of the number of MP solved structures. In this review, we analyse and discuss effective solutions and technical advances at the level of the upstream stage using prokaryotic and eukaryotic organisms foreseeing an increase in expression yields of correctly folded MP and that may facilitate the determination of their three-dimensional structure. A section on techniques used to protein quality control and further structure determination of MP is also included. Lastly, a critical assessment of major factors contributing for a good decision-making process related to the upstream stage of MP is presented.publishe

Fast and efficient microfluidic cell filter for isolation of circulating tumor cells from unprocessed whole blood of colorectal cancer patients

Liquid biopsy offers unique opportunities for low invasive diagnosis, real-time patient monitoring and treatment selection. The phenotypic and molecular profile of circulating tumor cells (CTCs) can provide key information about the biology of tumor cells, contributing to personalized therapy. CTC isolation is still challenging, mainly due to their heterogeneity and rarity. To overcome this limitation, a microfluidic chip for label-free isolation of CTCs from peripheral blood was developed. This device, the CROSS chip, captures CTCs based on their size and deformability with an efficiency of 70%. Using 2 chips, 7.5 ml of whole blood are processed in 47 minutes with high purity, as compared to similar technologies and assessed by in situ immunofluorescence. The CROSS chip performance was compared to the CellSearch system in a set of metastatic colorectal cancer patients, resulting in higher capture of DAPI+/CK+/CD45- CTCs in all individuals tested. Importantly, CTC enumeration by CROSS chip enabled stratification of patients with different prognosis. Lastly, cells isolated in the CROSS chip were lysed and further subjected to molecular characterization by droplet digital PCR, which revealed a mutation in the APC gene for most patient samples analyzed, confirming their colorectal origin and the versatility of the technology for downstream applications