Coevolving Residues and the Expansion of Substrate Permissibility in LAGLIDADG Homing Endonucleases

Genome-editing (GE) is a form of genetic engineering that permits the deliberate manipulation of genetic material for the study of biological processes, agricultural and industrial biotechnologies, and developing targeted therapies to cure human disease. While the potential application of GE is wide-ranging, the efficacy of most strategies is dependent upon the ability to accurately introduce a double-stranded break at the genomic location where alterations are desired. LAGLIDADG homing endonucleases (LHEs) are a class of mobile genetic element that recognize and cleave 22-bp sequences of DNA. Given this high degree of specificity, LHEs are powerful GE reagents, but re-engineering their recognition sites has been hindered by a limited understanding of structural constraints within the family, and how cleavage specificity is regulated in the central target site region. In the present studies, a covariation analysis of the LHE family recognized a set of coevolving residues within the enzyme active site. These positions were found to modulate catalytic efficiency, and are thought to create a barrier to active site evolution and re-engineering by constraining the LHE fitness landscape towards a set of functionally permissive combinations. Interestingly, mutation of these positions led to the identification of a catalytic residue variant that demonstrates cleavage activity against a greater number of central target site substrates than wild-type enzymes. To facilitate these investigations, high-throughput and unbiased methods were developed to functionally screen large mutagenic libraries and simultaneously profile cleavage specificity against 256 different substrates. Lastly, structural studies aimed at increasing our understanding of the LHE coevolving network led to the discovery of direct protein-DNA contacts in the central target site region. Significantly, these findings increase our understanding of functionally important structural constraints within the LHE family and have the potential to increase the sequence targeting capacity of LHE scaffolds. More broadly, the methodologies described in this thesis can assist large-scale structure-function studies and facilitate investigations of substrate specificity for most DNA-binding proteins. Finally, the thorough biochemical validation I provide for computational predictions of coevolution showcases a strategy to infer protein function-structure from genetic information and emphasizes the need to expand these studies to other protein families

Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis.

BACKGROUND: Experimental designs that take advantage of high-throughput sequencing to generate datasets include RNA sequencing (RNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), sequencing of 16S rRNA gene fragments, metagenomic analysis and selective growth experiments. In each case the underlying data are similar and are composed of counts of sequencing reads mapped to a large number of features in each sample. Despite this underlying similarity, the data analysis methods used for these experimental designs are all different, and do not translate across experiments. Alternative methods have been developed in the physical and geological sciences that treat similar data as compositions. Compositional data analysis methods transform the data to relative abundances with the result that the analyses are more robust and reproducible. RESULTS: Data from an in vitro selective growth experiment, an RNA-seq experiment and the Human Microbiome Project 16S rRNA gene abundance dataset were examined by ALDEx2, a compositional data analysis tool that uses Bayesian methods to infer technical and statistical error. The ALDEx2 approach is shown to be suitable for all three types of data: it correctly identifies both the direction and differential abundance of features in the differential growth experiment, it identifies a substantially similar set of differentially expressed genes in the RNA-seq dataset as the leading tools and it identifies as differential the taxa that distinguish the tongue dorsum and buccal mucosa in the Human Microbiome Project dataset. The design of ALDEx2 reduces the number of false positive identifications that result from datasets composed of many features in few samples. CONCLUSION: Statistical analysis of high-throughput sequencing datasets composed of per feature counts showed that the ALDEx2 R package is a simple and robust tool, which can be applied to RNA-seq, 16S rRNA gene sequencing and differential growth datasets, and by extension to other techniques that use a similar approach

Robust Eye Gaze Estimation

Eye gaze detection under challenging lighting conditions is a non-trivial task. Pixel intensity and the shades around the eye region may change depending on the time of day, location, or due to artificial lighting. This paper introduces a lighting-adaptive solution for robust eye gaze detection. First, we propose a binarization and cropping technique to limit our region of interest. Then we develop a gradient-based method for eye-pupil detection; and finally, we introduce an adaptive eye-corner detection technique that altogether lead to robust eye gaze estimation. Experimental results show the outperformance of the proposed method compared with related techniques

MISTIC2: Comprehensive server to study coevolution in protein families

Correlated mutations between residue pairs in evolutionarily related proteins arise from constraints needed to maintain a functional and stable protein. Identifying these inter-related positions narrows down the search for structurally or functionally important sites. MISTIC is a server designed to assist users to calculate covariation in protein families and provide them with an interactive tool to visualize the results. Here, we present MISTIC2, an update to the previous server, that allows to calculate four covariation methods (MIp, mfDCA, plmDCA and gaussianDCA). The results visualization framework has been reworked for improved performance, compatibility and user experience. It includes a circos representation of the information contained in the alignment, an interactive covariation network, a 3D structure viewer and a sequence logo. Others components provide additional information such as residue annotations, a roc curve for assessing contact prediction, data tables and different ways of filtering the data and exporting figures. Comparison of different methods is easily done and scores combination is also possible. A newly implemented web service allows users to access MISTIC2 programmatically using an API to calculate covariation and retrieve results. MISTIC2 is available at: https://mistic2.leloir.org.ar.Fil: Colell, Eloy A.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Iserte, Javier Alonso. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Marino Buslje, Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentin

RT-GENE: Real-time eye gaze estimation in natural environments

In this work, we consider the problem of robust gaze estimation in natural environments. Large camera-to-subject distances and high variations in head pose and eye gaze angles are common in such environments. This leads to two main shortfalls in state-of-the-art methods for gaze estimation: hindered ground truth gaze annotation and diminished gaze estimation accuracy as image resolution decreases with distance. We first record a novel dataset of varied gaze and head pose images in a natural environment, addressing the issue of ground truth annotation by measuring head pose using a motion capture system and eye gaze using mobile eyetracking glasses. We apply semantic image inpainting to the area covered by the glasses to bridge the gap between training and testing images by removing the obtrusiveness of the glasses. We also present a new real-time algorithm involving appearance-based deep convolutional neural networks with increased capacity to cope with the diverse images in the new dataset. Experiments with this network architecture are conducted on a number of diverse eye-gaze datasets including our own, and in cross dataset evaluations. We demonstrate state-of-the-art performance in terms of estimation accuracy in all experiments, and the architecture performs well even on lower resolution images

Saccharomyces cerevisiae chitin biosynthesis activation by N-acetylchitooses depends on size and structure of chito-oligosaccharides

<p>Abstract</p> <p>Background</p> <p>To explore chitin synthesis initiation, the effect of addition of exogenous oligosaccharides on <it>in vitro </it>chitin synthesis was studied. Oligosaccharides of various natures and lengths were added to a chitin synthase assay performed on a <it>Saccharomyces cerevisiae </it>membrane fraction.</p> <p>Findings</p> <p><it>N</it>-acetylchito-tetra, -penta and -octaoses resulted in 11 to 25% [¹⁴C]-GlcNAc incorporation into [¹⁴C]-chitin, corresponding to an increase in the initial velocity. The activation appeared specific to <it>N</it>-acetylchitooses as it was not observed with oligosaccharides in other series, such as beta-(1,4), beta-(1,3) or alpha-(1,6) glucooligosaccharides.</p> <p>Conclusions</p> <p>The effect induced by the <it>N</it>-acetylchitooses was a saturable phenomenon and did not interfere with free GlcNAc and trypsin which are two known activators of yeast chitin synthase activity <it>in vitro</it>. The magnitude of the activation was dependent on both oligosaccharide concentration and oligosaccharide size.</p

Profound variation in dihydropyrimidine dehydrogenase activity in human blood cells: major implications for the detection of partly deficient patients

Dihydropyrimidine dehydrogenase (DPD) is responsible for the breakdown of the widely used antineoplastic agent 5-fluorouracil (5FU), thereby limiting the efficacy of the therapy. To identify patients suffering from a complete or partial DPD deficiency, the activity of DPD is usually determined in peripheral blood mononuclear cells (PBM cells). In this study, we demonstrated that the highest activity of DPD was found in monocytes followed by that of lymphocytes, granulocytes and platelets, whereas no significant activity of DPD could be detected in erythrocytes. The activity of DPD in PBM cells proved to be intermediate compared with the DPD activity observed in monocytes and lymphocytes. The mean percentage of monocytes in the PBM cells obtained from cancer patients proved to be significantly higher than that observed in PBM cells obtained from healthy volunteers. Moreover, a profound positive correlation was observed between the DPD activity of PBM cells and the percentage of monocytes, thus introducing a large inter- and intrapatient variability in the activity of DPD and hindering the detection of patients with a partial DPD deficiency. © 1999 Cancer Research Campaig