731 research outputs found
Spatiotemporal Control of Chemical Reaction Networks using Droplet Microfluidics
A number of cellular organisms, such as yeast, bacteria and slime moulds, exhibit dynamic behaviour, in particular switching and rhythms that are controlled by feedback mechanisms in enzyme-catalysed reactions. The mechanisms of these processes are well understood, and recently there has been a focus on generating similar reactions in synthetic biocatalytic systems to establish bioinspired analogues for applications in materials and medicine. In this context, compartmentalisation of biochemical reactions within synthetic cell models such as micelles, vesicles, and W/O/W-based double emulsions is attracting growing attention for applications in the field of therapeutics. In this respect, it is necessary to adopt easier-to-use stimuli-responsive (react to pH, temperature or light) biochemical reactions, to apply artificial cell models to the biomedical context, and regulate artificial cell communication in a spatiotemporal controlled way. As a first step, it is crucial to control the output of a chemical reaction that maybe exploited for applications in the field of programmable materials and biomedicine. Droplet emulsion and synthetic vesicle systems have been widely employed as bioinspired micro- or nanoreactors for production of materials such as hydrogels and ceramic particles. They also provide test platform for biomimetic cell like behaviour.
To address this, we have developed and fine-tuned a platform with synthetic bottom-up chemistry that has enabled us to systematically and thoroughly investigate the effects of entrapment on a feedback-driven enzymatic reaction. As a result of this process, we have revealed a system that is more intricate than originally thought. Firstly, taking advantage from pressure driven droplet microfluidics, we developed a system of enzyme-encapsulated (urea-urease) double emulsion (W/O/W) droplets to obtain a localised pH pulse, with a controllable induction time to program material properties. The urease-catalysed hydrolysis of urea (urea-urea reaction), has a feedback through the production of the base (NH3). This leads to a change from an acidic to a basic pH after an induction time (Tind), resulting in an environment with auto-changing pH conditions. Reaction was initiated by addition of urea and a pulse in base (ammonia) was observed in the droplets after a time lag of the order of minutes. The pH-time profile can be manipulated by the diffusion timescale of urea and ammonia through the oil layer, resulting in localised pH changes not accessible in bulk solutions.
Secondly, we performed a computational investigation of the nonlinear reaction chemistry (urea-urease) within the designed platform of the W/O/W-based reactor. A radially distributed reaction diffusion model is presented for a layered sphere mimicking a double emulsion. Here we have combined the experiments with simulations (shell-core model) to demonstrate the influence of urea transport triggered by the shell, the core and the external solution surrounding the cell model (µ-reactor) on the induction time/period (Tind) of urea-urease reaction.
Third, inspired from natural cellular systems (e.g. bacterial quorum sensing), we focus on the use of urea-urease reaction confined to double emulsions to investigate chemical communications. We observed a system that resulted in a system of microreactors acting as individual units with distinct induction periods (Tind) for the first time. We show that in contrast to other systems, the release of ammonia can accelerate the reaction in all the droplets but there is no evident synchronisation of activity characterised by a wide distribution of induction times across the population of micro-reactors. However, the investigation of behaviour of population/group of µ-reactors as a function of substrate urea concentration and the density of µ-reactors highlights the possibility of transitions to collective behaviours.
Finally, we aimed to use the double emulsion template for potential biomedical and therapeutic applications using the autocatalytic urea-urease reaction. We used the platform to produce thiol-acrylate gels in the form of double emulsion loaded gel films and spherical microcapsules for potential drug delivery applications. In addition, we employed the encapsulated double emulsion platform of the enzyme urease to study the inhibition of the enzyme itself; which is important in the development of anti-microbials for ureolytic bacteria.
By building this platform, we have not only learned how to control the kinetic output of the reaction (urea-urease), but have also demonstrated its potential in future applications
R-Pyocin Regulation, Release, and Susceptibility in Pseudomonas aeruginosa
Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen and a major determinant of declining lung function in individuals with cystic fibrosis (CF). P. aeruginosa possesses many intrinsic antibiotic resistance mechanisms and isolates from chronic CF lung infections develop increasing resistance to multiple antibiotics over time. Chronic infection with P. aeruginosa remains one of the main causes of mortality and morbidity in CF patients, thus new therapeutic interventions are necessary.
R-type pyocins are narrow spectrum, phage tail-like bacteriocins, specifically produced by P. aeruginosa to kill other strains of P. aeruginosa. Due to their specific anti-pseudomonal activity and similarity to bacteriophage, R-pyocins have potential as additional therapeutics for P. aeruginosa, either in isolation, in combination with antibiotics, or as an alternative to phage therapy. There are five subtypes of R-pyocin (types R1-R5), and it is thought that each P. aeruginosa strain uniquely produces only one of these, suggesting a degree of strain-specificity. P. aeruginosa from CF lung infections develop increasing resistance to antibiotics, making new treatment approaches essential. It is known P. aeruginosa populations in CF chronic lung infection become phenotypically and genotypically diverse over time, however, little is known of the efficacy of R-pyocins against heterogeneous populations. Even less is known regarding the timing and regulation of R-pyocins in CF lung infections, or if P. aeruginosa utilizes R-pyocin production during infection for competition or otherwise – which may influence pressure towards R-pyocin resistance.
In this work, I evaluated R-pyocin type and susceptibility among P. aeruginosa isolates sourced from CF infections and found that (i) R1-pyocins are the most prevalent R-type among respiratory infection and CF strains; (ii) a large proportion of P. aeruginosa strains lack R-pyocin genes entirely; (iii) isolates from P. aeruginosa populations collected from the same patient at a single time point have the same R-pyocin type; (iv) there is heterogeneity in susceptibility to R-pyocins within P. aeruginosa populations and (v) susceptibility is likely driven by diversity of LPS phenotypes within clinical populations. These findings suggest that there is likely heterogeneity in response to other types of LPS-binding antimicrobials, including phage, which is important for consideration of antimicrobials as therapeutics.
To investigate the prevalence of R2-pyocin susceptible strains in CF, I then utilized 110 isolates of P. aeruginosa collected from five individuals with CF to test for R2-pyocin susceptibility and identify LPS phenotypes. From our collection we i) estimated that approximately 83% of sputum samples contain heterogenous P. aeruginosa populations without R2-pyocin resistant isolates and all sputum samples contained susceptible isolates; ii) we found that there is no correlation between R2-pyocin susceptibility and LPS phenotypes, and iii) we estimate that approximately 76% of isolates sampled from sputum lack O-specific antigen, 42% lack common antigen, and 27% exhibit altered LPS cores. This finding highlights that perhaps LPS packing density may play a more influential role in mediating R-pyocin susceptibility in infection. Finding the majority of our sampled P. aeruginosa populations to be R2-pyocin susceptible further supports the potential of these narrow-spectrum antimicrobials despite facing heterogenous susceptibility among diverse populations.
In order to evaluate how R-pyocins may influence strain competition and growth in CF lung infection, I assessed R-pyocin activity in an infection-relevant environment (Synthetic Cystic Fibrosis Sputum Medium; SCFM2) and found that (i) R-pyocins genes are transcribed more in the CF nutrient environment than in rich laboratory medium and (ii) in a structured, CF-like environment, R-pyocin induction is costly to producing strains in competition rather than beneficial. Our work suggests that R-pyocins may not be essential in CF lung infection and can be costly to producing cells in the presence of stress response-inducing stimuli, such as those commonly found in infection.
In this thesis I have studied R-pyocin susceptibility, regulation and release utilizing a biobank of whole populations of P. aeruginosa collected from 11 individuals with CF, as well as the CF infection model (SCFM) to understand the mechanisms of R-pyocin activity in an infection-relevant context and the role R-pyocins play in shaping P. aeruginosa populations during infection. The findings of this work have illuminated the impact of P. aeruginosa heterogeneity on R-pyocin susceptibility, furthered our understanding of R-pyocins as potential therapeutics, and built upon our knowledge of bacteriocin-mediated interactions.Ph.D
Investigating the role of enhancer-mediated gene expression in the human brain and its potential contribution to psychiatric disorders
Autism spectrum disorder (ASD) and schizophrenia (SCZ) are two neuropsychiatric conditions with variable times of onset and are influenced by both genetic and environmental factors. Genome-wide association studies (GWASs) have led to the identification of numerous genetic loci common to both these disorders, however our understanding remains far from complete, with many clinical cases without a genetic cause. While increasing the statistical power of genome-wide association studies (GWASs) to find additional risk variants could rule-in or rule out rare cases of ASD and SCZ, this presently remains a difficult task. Furthermore, the biological functions for genetic susceptibility loci remains poorly understood, particularly for more-recent discoveries of loci devoid of gene bodies. On the other hand, recent biotechnological developments have made it possible to conduct high-resolution experimental measurements of the three-dimensional architecture of the genome, including enhancer-promoter interactions (EPIs). Such data have been used to connect GWAS risk variants to their potential target genes which, in turn, provide insights into underlying molecular mechanisms and cellular processes. The functions of enhancer-promoter interactions in controlling gene expression programmes is crucial to how implicated genes mediate neurological function and disease. Yet, knowledge on enhancer-promoter interactions remains to be used in conjunction with GWAS data, particularly on such data from specific brain cell types, which may be useful to uncover the biological underpinnings of psychiatric conditions. This thesis examines the role of enhancer-mediated gene expression in the human brain and its potential contribution to psychiatric conditions. In Chapter 2, I report on the identification of significant chromosomal interactions from studies of brain Hi-C data generated from neuronal and glial cells, with the goal to investigate the impact of EPIs genome-wide, as well as to provide a template for an in-depth understanding of how EPIs impact transcriptional regulation. In the Chapter 3, I discuss a novel approach integrating Activity by Contact (ABC) and gene set enrichment analyses of GWAS data in two steps. In the first step, ABC is used to predict enhancer-gene regulatory interactions in a given cell type (e.g., glial cells, neurons). Secondly, Hi-C coupled multi-marker analysis of genomic annotation (H-MAGMA) is used to assign the SNPs located in the regulatory regions identified by ABC to each gene and calculate gene-level association p-values. I applied this novel framework (ABC-HMAGMA) to GWAS data from SCZ and ASD, to identify novel SCZ and ASD trait-associated genes and molecular pathways. In Chapter 4, I have evaluated a potential novel mechanism for the regulation of enhancer activity within cells. I hypothesized that, in addition to its known roles in DNA replication and transcription, Topoisomerase I may regulate enhancer activity in brain cells. To test this hypothesis, I employed RNA-seq and transient transcriptome sequencing (TT-seq) data, a method that enriches for short-lived enhancer derived RNAs. These data showed that Topoisomerase I inhibition leads to significant changes in eRNA expression and offers evidence that such changes are relevant to the homeostatic functions for Top 1 in cellular gene expression regulation
On marked declaratives, exclamatives, and discourse particles in Castilian Spanish
This book provides a new perspective on prosodically marked declaratives, wh-exclamatives, and discourse particles in the Madrid variety of Spanish. It argues that some marked forms differ from unmarked forms in that they encode modal evaluations of the at-issue meaning. Two epistemic evaluations that can be shown to be encoded by intonation in Spanish are linguistically encoded surprise, or mirativity, and obviousness. An empirical investigation via an audio-enhanced production experiment finds that mirativity and obviousness are associated with distinct intonational features under constant focus scope, with stances of (dis)agreement showing an impact on obvious declaratives. Wh-exclamatives are found not to differ significantly in intonational marking from neutral declaratives, showing that they need not be miratives. Moreover, we find that intonational marking on different discourse particles in natural dialogue correlates with their meaning contribution without being fully determined by it. In part, these findings quantitatively confirm previous qualitative findings on the meaning of intonational configurations in Madrid Spanish. But they also add new insights on the role intonation plays in the negotiation of commitments and expectations between interlocutors
Applying Unsupervised Multi-Omic Learning to Identify Patterns of Human Genomic Regulatory Regions with an Emphasis in Characterizing HERVH Loci.
With the increase of diverse genomic data types, machine learning provides an opportunity to integrate several omics datasets into one cohesive annotation. In this dissertation, I apply an unsupervised clustering approach to a novel representation of 3D chromosome conformation data and chromatin mark data. Specifically I use this new method to annotate the regulatory function of human endogenous retrovirus H (HERVH). In chapter 1, I propose a synthesized model of HERVH function as an activating lncRNA based on previously published work. As HERVH and transposable elements in general are repetitive due to their methods of retrotransposition, in chapter 2 I explore the mappability of transposable elements using traditional short read approaches. This mappability study validates that most transposable element loci are in fact highly mappable in the human genome. In chapter 3, I present a novel aggregation method to integrate both 3D chromatin conformation data and chromatin state labels to be used for downstream clustering. I show that this method provides additional annotation beyond chromatin conformation data of chromatin state data alone. Finally in chapter 4, I perform a meta-analysis of individual HERVH loci by synthesizing data from over 10 years of past research and applying the method developed in chapter 3. I propose that 5’ and 3’ HERVH LTRs may function as promoters and enhancers, respectively, and that the act of transcription and accompanying chromatin marks at the 5’ LTR are essential for DNA folding. This dissertation aims to present a novel method for condensing multi-omics data into whole genome annotation
SIMULATING CONSUMABLE ORDER FULFILLMENT VIA ADDITIVE MANUFACTURING TECHNOLOGIES
Operational availability of naval aircraft through material readiness is critical to ensuring combat power. Supportability of aircraft is a crucial aspect of readiness, influenced by several factors including access to 9B Cognizance Code (COG) aviation consumable repair parts at various supply echelons. Rapidly evolving additive manufacturing (AM) technologies are transforming supply chain dynamics and the traditional aircraft supportability construct. As of June 2022, there are 595 AM assets within the Navy’s inventory—all for research and development purposes. This report simulates 9B COG aviation consumable fulfillment strategies within the U.S. Indo-Pacific sustainment network for a three-year span, inclusive of traditional supply support avenues and a developed set of user-variable capability inputs. Simulated probabilistic demand configurations are modeled from historical trends that exploit a heuristic methodology to assign a “printability” score to each 9B COG requirement, accounting for uncertainty, machine failure rates, and other continuous characteristics of the simulated orders. The results measure simulated lead time across diverse planning horizons in both current and varied operationalized AM sustainment network configurations. This research indicates a measurable lead time reduction of approximately 10% across all 9B order lead times when AM is employed as an order fulfillment source for only 0.5% of orders.NPS Naval Research ProgramThis project was funded in part by the NPS Naval Research Program.Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited
NARRATIVE INSIGHT INTO HOW RURAL, FIRST-GENERATION COLLEGE STUDENTS AND THEIR FAMILIES ESTABLISH NON-DEFICIT, MULTI-SITED IDENTITIES
This study explores the ways in which rural, first-generation college (RFGC) students position themselves in relation to dominant cultural master narratives and potentially competing alternative narratives related to community and family processes, norms, life pathways, and choices after college. Evidence is drawn from in-depth narrative interviews with 15 RFGC students conducted both at school and in students’ home communities. The study contributes to an anti-deficit understanding of rural first-generation college students’ college experiences and identity by focusing not on challenges and barriers but on the ways individuals both align and agentically reject dominant cultural narratives as well as the ways rural youth create new stories and possibilities
Translational and clinical research applications of exome sequencing to neurodevelopmental disorders of childhood
Neurodevelopmental disabilities (NDDs) are a group of chronic clinically distinct disorders sharing a documented disturbance, quantitative, qualitative, or both, in developmental progress in one or more developmental domains compared with established norms. These domains are not mutually independent or exclusive and include: (1) motor (gross or fine), (2) speech and language, (3) cognition, (4) personal-social, and (5) activities of daily living (Shevell et al., 2008). Whole Exome Sequencing (WES) has provided a huge contribution to the discovery of disease-causing variants for rare diseases, especially neurodevelopmental disorders. Furthemore, the use of WES in clinical practice has improved the diagnostic rate in several rare genetic conditions, including neurodevelopmental disorders, which previously remained unexplained (Xue et al., 2014). This has led to a relevant improvement in patient management in selected disorders. Indeed, the better understanding of the pathophysiology underlying a specific condition has helped clinicians in developing a disease-specific approach in patient care. Furthermore, the identification of several new possible therapeutic targets has promoted the development of new therapeutic strategies or specific drugs. In this study, we investigated the use of exome sequencing in three different genomic research approaches: genotype-phenotype correlations; pathophysiological mechanisms; gene discovery. Our findings show that NGS techniques play a pivotal role in the NDDs research
ACARORUM CATALOGUS IX. Acariformes, Acaridida, Schizoglyphoidea (Schizoglyphidae), Histiostomatoidea (Histiostomatidae, Guanolichidae), Canestrinioidea (Canestriniidae, Chetochelacaridae, Lophonotacaridae, Heterocoptidae), Hemisarcoptoidea (Chaetodactylidae, Hyadesiidae, Algophagidae, Hemisarcoptidae, Carpoglyphidae, Winterschmidtiidae)
The 9th volume of the series Acarorum Catalogus contains lists of mites of 13 families, 225 genera and 1268 species of the superfamilies Schizoglyphoidea, Histiostomatoidea, Canestrinioidea and Hemisarcoptoidea. Most of these mites live on insects or other animals (as parasites, phoretic or commensals), some inhabit rotten plant material, dung or fungi. Mites of the families Chetochelacaridae and Lophonotacaridae are specialised to live with Myriapods (Diplopoda). The peculiar aquatic or intertidal mites of the families Hyadesidae and Algophagidae are also included.Publishe
What is hidden in the darkness? Deep-learning assisted large-scale protein family curation uncovers novel protein families and folds
Driven by the development and upscaling of fast genome sequencing and assembly pipelines, the number of protein-coding sequences deposited in public protein sequence databases is increasing exponentially. Recently, the dramatic success of deep learning-based approaches applied to protein structure prediction has done the same for protein structures. We are now entering a new era in protein sequence and structure annotation, with hundreds of millions of predicted protein structures made available through the AlphaFold database. These models cover most of the catalogued natural proteins, including those difficult to annotate for function or putative biological role based on standard, homology-based approaches. In this work, we quantified how much of such "dark matter" of the natural protein universe was structurally illuminated by AlphaFold2 and modelled this diversity as an interactive sequence similarity network that can be navigated at https://uniprot3d.org/atlas/AFDB90v4 . In the process, we discovered multiple novel protein families by searching for novelties from sequence, structure, and semantic perspectives. We added a number of them to Pfam, and experimentally demonstrate that one of these belongs to a novel superfamily of toxin-antitoxin systems, TumE-TumA. This work highlights the role of large-scale, evolution-driven protein comparison efforts in combination with structural similarities, genomic context conservation, and deep-learning based function prediction tools for the identification of novel protein families, aiding not only annotation and classification efforts but also the curation and prioritisation of target proteins for experimental characterisation
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