Ancient components of the ribosome, inferred from a consensus of previous work, were constructed in silico, in vitro and in vivo. The resulting model of the ancestral ribosome presented here incorporates ∼20% of the extant 23S rRNA and fragments of five ribosomal proteins. We test hypotheses that ancestral rRNA can: (i) assume canonical 23S rRNA-like secondary structure, (ii) assume canonical tertiary structure and (iii) form native complexes with ribosomal protein fragments. Footprinting experiments support formation of predicted secondary and tertiary structure. Gel shift, spectroscopic and yeast three-hybrid assays show specific interactions between ancestral rRNA and ribosomal protein fragments, independent of other, more recent, components of the ribosome. This robustness suggests that the catalytic core of the ribosome is an ancient construct that has survived billions of years of evolution without major changes in structure. Collectively, the data here support a model in which ancestors of the large and small subunits originated and evolved independently of each other, with autonomous functionalities.

BackgroundWhole genome sequencing is poised to revolutionize personalized medicine, providing the capacity to classify individuals into risk categories for a wide range of diseases. Here we begin to explore how whole genome sequencing (WGS) might be incorporated alongside traditional clinical evaluation as a part of preventive medicine. The present study illustrates novel approaches for integrating genotypic and clinical information for assessment of generalized health risks and to assist individuals in the promotion of wellness and maintenance of good health.MethodsWhole genome sequences and longitudinal clinical profiles are described for eight middle-aged Caucasian participants (four men and four women) from the Center for Health Discovery and Well Being (CHDWB) at Emory University in Atlanta. We report multivariate genotypic risk assessments derived from common variants reported by genome-wide association studies (GWAS), as well as clinical measures in the domains of immune, metabolic, cardiovascular, musculoskeletal, respiratory, and mental health.ResultsPolygenic risk is assessed for each participant for over 100 diseases and reported relative to baseline population prevalence. Two approaches for combining clinical and genetic profiles for the purposes of health assessment are then presented. First we propose conditioning individual disease risk assessments on observed clinical status for type 2 diabetes, coronary artery disease, hypertriglyceridemia and hypertension, and obesity. An approximate 2:1 ratio of concordance between genetic prediction and observed sub-clinical disease is observed. Subsequently, we show how more holistic combination of genetic, clinical and family history data can be achieved by visualizing risk in eight sub-classes of disease. Having identified where their profiles are broadly concordant or discordant, an individual can focus on individual clinical results or genotypes as they develop personalized health action plans in consultation with a health partner or coach.ConclusionThe CHDWB will facilitate longitudinal evaluation of wellness-focused medical care based on comprehensive self-knowledge of medical risks.

The three-dimensional structure of the ribosomal large subunit (LSU) reveals a single morphological element, although the 23S rRNA is contained in six secondary structure domains. Based upon maps of inter-and intra-domain interactions and proposed evolutionary pathways of development, we hypothesize that Domain III is a truly independent structural domain of the LSU. Domain III is primarily stabilized by intra-domain interactions, negligibly perturbed by inter-domain interactions, and is not penetrated by ribosomal proteins or other rRNA. We have probed the structure of Domain III rRNA alone and when contained within the intact 23S rRNA using SHAPE (selective 29-hydroxyl acylation analyzed by primer extension), in the absence and presence of magnesium. The combined results support the hypothesis that Domain III alone folds to a near-native state with secondary structure, intra-domain tertiary interactions, and inter-domain interactions that are independent of whether or not it is embedded in the intact 23S rRNA or within the LSU. The data presented support previous suggestions that Domain III was added relatively late in ribosomal evolution.

We have developed a novel structure-based evaluation for missense variants that explicitly models protein structure and amino acid properties to predict the likelihood that a variant disrupts protein function. A structural disruption score (SDS) is introduced as a measure to depict the likelihood that a case variant is functional. The score is constructed using characteristics that distinguish between causal and neutral variants within a group of proteins. The SDS score is correlated with standard sequence-based deleteriousness, but shows promise for improving discrimination between neutral and causal variants at less conserved sites. The prediction was performed on 3-dimentional structures of 57 gene products whose homozygous SNPs were identified as case-exclusive variants in an exome sequencing study of epilepsy disorders. We contrasted the candidate epilepsy variants with scores for likely benign variants found in the EVS database, and for positive control variants in the same genes that are suspected to promote a range of diseases. To derive a characteristic profile of damaging SNPs, we transformed continuous scores into categorical variables based on the score distribution of each measurement, collected from all possible SNPs in this protein set, where extreme measures were assumed to be deleterious. A second epilepsy dataset was used to replicate the findings. Causal variants tend to receive higher sequence-based deleterious scores, induce larger physico-chemical changes between amino acid pairs, locate in protein domains, buried sites or on conserved protein surface clusters, and cause protein destabilization, relative to negative controls. These measures were agglomerated for each variant. A list of nine high-priority putative functional variants for epilepsy was generated. Our newly developed SDS protocol facilitates SNP prioritization for experimental validation.

A person infected with drug-resistant tuberculosis (DR-TB) is the one who does not respond to typical TB treatment. DR-TB necessitates a longer treatment period and a more difficult treatment protocol. In addition, it can spread and infect individuals in the same manner as regular TB, despite the fact that early detection of DR-TB could reduce the cost and length of TB treatment. This study provided a fast and effective classification scheme for the four subtypes of TB: Drug-sensitive tuberculosis (DS-TB), drug-resistant tuberculosis (DR-TB), multidrug-resistant tuberculosis (MDR-TB), and extensively drug-resistant tuberculosis (XDR-TB). The drug response classification system (DRCS) has been developed as a classification tool for DR-TB subtypes. As a classification method, ensemble deep learning (EDL) with two types of image preprocessing methods, four convolutional neural network (CNN) architectures, and three decision fusion methods have been created. Later, the model developed by EDL will be included in the dialog-based object query system (DBOQS), in order to enable the use of DRCS as the classification tool for DR-TB in assisting medical professionals with diagnosing DR-TB. EDL yields an improvement of 1.17–43.43% over the existing methods for classifying DR-TB, while compared with classic deep learning, it generates 31.25% more accuracy. DRCS was able to increase accuracy to 95.8% and user trust to 95.1%, and after thae trial period, 99.70% of users were interested in continuing the utilization of the system as a supportive diagnostic tool.