A novel yeast expression system for the overproduction of quality-controlled membrane proteins

Saturation of the cell's protein folding capacity and accumulation of inactive incompletely folded protein often accompanying the overexpression of membrane proteins (MPs) presents an obstacle to their efficient purification in a functional form for structural studies. We present a novel strategy for optimization of functional MP expression in Saccharomyces cerevisiae. This approach exploits the unfolded protein response (UPR) pathway, a stress signaling mechanism that senses the accumulation of unfolded proteins in the endoplasmic reticulum. We demonstrate that a high level of UPR induction upon expression of a MP reflects impaired functional expression of that protein. Tuning the expression level of the protein so as to avoid or minimize UPR induction results in its increased functional expression. UPR status can therefore serve as a proxy variable for the extent of impaired expression of a MP that may even be applicable in the absence of knowledge of the protein's biological function.     

Benchmarking and optimization of a high-throughput sequencing based method for transgene sequence variant analysis in biotherapeutic cell line development

In recent years, High-Throughput Sequencing (HTS) based methods to detect mutations in biotherapeutic transgene products have become a key quality step deployed during the development of manufacturing cell line clones. Previously we reported on a higher throughput, rapid mutation detection method based on amplicon sequencing (targeting transgene RNA) and detailed its implementation to facilitate cell line clone selection. By gaining experience with our assay in a diverse set of cell line development programs, we improved the computational analysis as well as experimental protocols. Here we report on these improvements as well as on a comprehensive benchmarking of our assay. We evaluated assay performance by mixing amplicon samples of a verified mutated antibody clone with a non-mutated antibody clone to generate spike-in mutations from ∼60% down to ∼0.3% frequencies. We subsequently tested the effect of 16 different sample and HTS library preparation protocols on the assay's ability to quantify mutations and on the occurrence of false-positive background error mutations (artifacts). Our evaluation confirmed assay robustness, established a high confidence limit of detection of ∼0.6%, and identified protocols that reduce error levels thereby significantly reducing a source of false positives that bottlenecked the identification of low-level true mutations.     

Flow cytometric estimation of ‘labile iron pool’ in human white blood cells reveals a positive association with ageing

A small part of cellular iron, usually called ‘labile iron pool’ (LIP), is not securely stored and has the potential to catalyse the formation of highly reactive oxygen species. The present work estimated LIP levels in human white cells by using the analytical power of flow cytometry. The method relies essentially on already established principles but has the added value of monitoring LIP in different subpopulations of human blood cells concurrently in a single sample. Examination of 41 apparently healthy individuals revealed a positive correlation between LIP levels and the age of the donors (r=0.656, 0.572 and 0.702 for granulocytes, lymphocytes and monocytes, respectively, p<0.0001), indicating that cells of older individuals are prone to oxidations in conditions of oxidative stress. It is suggested that LIP estimation may represent a valuable tool in examinations searching for links between iron and a variety of oxidative stress-related pathological conditions.     

A simulation model of the Devils Hole pupfish population using monthly length-frequency distributions

The Devils Hole pupfish, Cyprinodon diabolis, is a federally-endangered fish that is endemic to Devils Hole, a discontiguous part of Death Valley National Park in Nye County, Nevada. Due to its status, Devils Hole pupfish monitoring must be non-obtrusive and thereby exclude techniques that require handling fish. Due to a recent decline in pupfish abundance, Devils Hole pupfish managers have expressed a need for a model that describes population dynamics. This population model would be used to identify vulnerable life history stage(s) and inform management actions. We constructed a set of individual-based simulation models designed to explore effects of population processes and evaluate assumptions. We developed a baseline model, whose output best resembled both observed length-frequency data and predicted intra-annual abundance patterns. We then ran simulations with 5 % increases in egg-larval, juvenile, and adult survival rates to better understand Devils Hole pupfish life history, thereby helping identify vulnerable life history stages that should become the target of management actions. Simulation models with temporally constant adult, juvenile, and egg-larval survival rates were able to reproduce observed length-frequency distributions and predicted intra-annual population patterns. In particular, models with monthly adult and juvenile survival rates of 80 % and an egg-larval survival rate of 4.7 % replicated patterns in observed data. Population growth was most affected by 5 % increases in egg-larval survival, whereas adult and juvenile survival rates had similar but lesser effects on population growth. Outputs from the model were used to assess factors suspected of influencing Devils Hole pupfish population decline.     

Does My Face FIT?: A Face Image Task Reveals Structure and Distortions of Facial Feature Representation

Despite extensive research on face perception, few studies have investigated individuals’ knowledge about the physical features of their own face. In this study, 50 participants indicated the location of key features of their own face, relative to an anchor point corresponding to the tip of the nose, and the results were compared to the true location of the same individual’s features from a standardised photograph. Horizontal and vertical errors were analysed separately. An overall bias to underestimate vertical distances revealed a distorted face representation, with reduced face height. Factor analyses were used to identify separable subconfigurations of facial features with correlated localisation errors. Independent representations of upper and lower facial features emerged from the data pattern. The major source of variation across individuals was in representation of face shape, with a spectrum from tall/thin to short/wide representation. Visual identification of one’s own face is excellent, and facial features are routinely used for establishing personal identity. However, our results show that spatial knowledge of one’s own face is remarkably poor, suggesting that face representation may not contribute strongly to self-awareness.     

High-Throughput miRNA and mRNA Sequencing of Paired Colorectal Normal,Tumor and Metastasis Tissues and Bioinformatic Modeling of miRNA-1 Therapeutic Applications

MiRNAs are discussed as diagnostic and therapeutic molecules. However, effective miRNA drug treatments with miRNAs are, so far, hampered by the complexity of the miRNA networks. To identify potential miRNA drugs in colorectal cancer, we profiled miRNA and mRNA expression in matching normal, tumor and metastasis tissues of eight patients by Illumina sequencing. We validated six miRNAs in a large tissue screen containing 16 additional tumor entities and identified miRNA-1, miRNA-129, miRNA-497 and miRNA-215 as constantly de-regulated within the majority of cancers. Of these, we investigated miRNA-1 as representative in a systems-biology simulation of cellular cancer models implemented in PyBioS and assessed the effects of depletion as well as overexpression in terms of miRNA-1 as a potential treatment option. In this system, miRNA-1 treatment reverted the disease phenotype with different effectiveness among the patients. Scoring the gene expression changes obtained through mRNA-Seq from the same patients we show that the combination of deep sequencing and systems biological modeling can help to identify patient-specific responses to miRNA treatments. We present this data as guideline for future pre-clinical assessments of new and personalized therapeutic options.