The origin of genetic coding and translation in protocells

The origin of the genetic code is a longstanding problem at the centre of biology. The code is the essential informational framework through which cells are able to self-replicate and evolve, but the process in which it emerged is unknown. One through-line in the literature is that the code may be an emergent property of the biochemistry of amino acid polymerization, but this is rarely stated explicitly. This thesis explores the chemistry of translation and investigates the idea that the polymerization mechanisms used by biology could occur spontaneously in mixtures of amino acids and nucleotides. The focus of this is the centrality of adenine nucleotides in translation. Initially, I utilise molecular dynamics simulations to explore the formation of ATP, a key reactant in translation, and link these results to prior laboratory studies. Using the same pipeline developed for these simulations, I find that adenine nucleotides readily self-organise in ways that should predispose the key chemical steps preceding amino acid polymerization to occur. However, the reason for adenine nucleotides’ universality in this process remains unclear and may either be related to their proclivity of to form triphosphates, or other chemical properties related to reactivity. Similar investigative approaches are then turned towards biological information. Through literature review, extensive molecular dynamics simulations and NMR, I present evidence that fundamental biophysical properties of amino acids and nucleotides can bias their interactions in ways which reproduce the patterns and structure of the modern genetic code. These patterns are principally related to hydrophobicity, which is identified as a significant factor for interactions, and elevated affinities for cognate anticodonic nucleotides. Overall, this thesis describes how spontaneous reactions and interactions may have provided sufficient foundations for the genetic code, foundations which were then augmented by the evolution of the biological translational machinery but never fully replaced

The Dixmier property and tracial states for C*-algebras

A.T. was partially supported by an NSERC Postdoctoral Fellowship and through the EPSRC grant EP/N00874X/1. Acknowledgements We are grateful to Luis Santiago for helpful discussions at an early stage of this investigation. We would also like to thank the referee for providing helpful comments, which have led to a number of improvements.Peer reviewedPublisher PD

The Balkan Definite Article and Pseudo-Second Position

Proceedings of the Eighteenth Annual Meeting of the Berkeley Linguistics Society: General Session and Parasession on The Place of Morphology in a Grammar (1992), pp. 338-34

A biophysical basis for the emergence of the genetic code in protocells

The origin of the genetic code is an abiding mystery in biology. Hints of a 'code within the codons' suggest biophysical interactions, but these patterns have resisted interpretation. Here, we present a new framework, grounded in the autotrophic growth of protocells from CO2 and H2. Recent work suggests that the universal core of metabolism recapitulates a thermodynamically favoured protometabolism right up to nucleotide synthesis. Considering the genetic code in relation to an extended protometabolism allows us to predict most codon assignments. We show that the first letter of the codon corresponds to the distance from CO2 fixation, with amino acids encoded by the purines (G followed by A) being closest to CO2 fixation. These associations suggest a purine-rich early metabolism with a restricted pool of amino acids. The second position of the anticodon corresponds to the hydrophobicity of the amino acid encoded. We combine multiple measures of hydrophobicity to show that this correlation holds strongly for early amino acids but is weaker for later species. Finally, we demonstrate that redundancy at the third position is not randomly distributed around the code: non-redundant amino acids can be assigned based on size, specifically length. We attribute this to additional stereochemical interactions at the anticodon. These rules imply an iterative expansion of the genetic code over time with codon assignments depending on both distance from CO2 and biophysical interactions between nucleotide sequences and amino acids. In this way the earliest RNA polymers could produce non-random peptide sequences with selectable functions in autotrophic protocells

Cost-effectiveness of Implementing Low-Tidal Volume Ventilation in Patients With Acute Lung Injury

Background: Despite widespread guidelines recommending the use of lung-protective ventilation (LPV) in patients with acute lung injury (ALI), many patients do not receive this lifesaving therapy. We sought to estimate the incremental clinical and economic outcomes associated with LPV and determined the maximum cost of a hypothetical intervention to improve adherence with LPV that remained cost-effective. Methods: Adopting a societal perspective, we developed a theoretical decision model to determine the cost-effectiveness of LPV compared to non-LPV care. Model inputs were derived from the literature and a large population-based cohort of patients with ALI. Cost-effectiveness was determined as the cost per life saved and the cost per quality-adjusted life-years (QALYs) gained. Results: Application of LPV resulted in an increase in QALYs gained by 15% (4.21 years for non-LPV vs 4.83 years for LPV), and an increase in lifetime costs of $7,233 per patient with ALI ($99,588 for non-LPV vs $106,821 for LPV). The incremental cost-effectiveness ratios for LPV were$22,566 per life saved at hospital discharge and $11,690 per QALY gained. The maximum, cost-effective, per patient investment in a hypothetical program to improve LPV adherence from 50 to 90$9,482. Results were robust to a wide range of economic and patient parameter assumptions. Conclusions: Even a costly intervention to improve adherence with low-tidal volume ventilation in patients with ALI reduces death and is cost-effective by current societal standards.NIH F32HL090220.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/84154/1/Cooke - CEA LPV.pd

The Diploid Genome Sequence of an Individual Human

Presented here is a genome sequence of an individual human. It was produced from ~32 million random DNA fragments, sequenced by Sanger dideoxy technology and assembled into 4,528 scaffolds, comprising 2,810 million bases (Mb) of contiguous sequence with approximately 7.5-fold coverage for any given region. We developed a modified version of the Celera assembler to facilitate the identification and comparison of alternate alleles within this individual diploid genome. Comparison of this genome and the National Center for Biotechnology Information human reference assembly revealed more than 4.1 million DNA variants, encompassing 12.3 Mb. These variants (of which 1,288,319 were novel) included 3,213,401 single nucleotide polymorphisms (SNPs), 53,823 block substitutions (2-206 bp), 292,102 heterozygous insertion/deletion events (indels)(1-571 bp), 559,473 homozygous indels (1-82,711 bp), 90 inversions, as well as numerous segmental duplications and copy number variation regions. Non-SNP DNA variation accounts for 22% of all events identified in the donor, however they involve 74% of all variant bases. This suggests an important role for non-SNP genetic alterations in defining the diploid genome structure. Moreover, 44% of genes were heterozygous for one or more variants. Using a novel haplotype assembly strategy, we were able to span 1.5 Gb of genome sequence in segments >200 kb, providing further precision to the diploid nature of the genome. These data depict a definitive molecular portrait of a diploid human genome that provides a starting point for future genome comparisons and enables an era of individualized genomic information

Biophysical Interactions Underpin the Emergence of Information in the Genetic Code

The genetic code conceals a ‘code within the codons’, which hints at biophysical interactions between amino acids and their cognate nucleotides. Yet, research over decades has failed to corroborate systematic biophysical interactions across the code. Using molecular dynamics simulations and NMR, we have analysed interactions between the 20 standard proteinogenic amino acids and 4 RNA mononucleotides in 3 charge states. Our simulations show that 50% of amino acids bind best with their anticodonic middle base in the −1 charge state common to the backbone of RNA, while 95% of amino acids interact most strongly with at least 1 of their codonic or anticodonic bases. Preference for the cognate anticodonic middle base was greater than 99% of randomised assignments. We verify a selection of our results using NMR, and highlight challenges with both techniques for interrogating large numbers of weak interactions. Finally, we extend our simulations to a range of amino acids and dinucleotides, and corroborate similar preferences for cognate nucleotides. Despite some discrepancies between the predicted patterns and those observed in biology, the existence of weak stereochemical interactions means that random RNA sequences could template non-random peptides. This offers a compelling explanation for the emergence of genetic information in biology

Reflective plasmonic color filters based on lithographically patterned silver nanorod arrays

10.1039/c3nr01419cNanoscale5146243-624

Accurate Whole-Genome Sequencing and Haplotyping from 10 to 20 Human Cells

Recent advances in whole genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, Long Fragment Read (LFR) technology, similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ~100 pg of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants (SNVs) were assembled into long haplotype contigs. Removal of false positive SNVs not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10 Mb. Cost-effective and accurate genome sequencing and haplotyping from 10-20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications