Biosynthesis, processing and engineering of circularin A

The global antibiotic resistance crisis demands urgent solutions. Ribosomally synthesized and post-translationally modified peptides (RiPPs) offer a diverse range of antimicrobial possibilities. Among them, circular bacteriocins are well-known for their remarkable stability, making them attractive for various applications, including food and pharmaceutical purposes. Despite their potential, the biosynthesis mechanism of circular bacteriocins remains underexplored, limiting their use in novel antibiotic development. This thesis focuses on investigating the biosynthesis, bioactivity and bioengineering potential of circularin A, a circular bacteriocin from Clostridium beijerinckii ATCC 25752. We first developed robust systems for circularin A production in Lactococcus lactis NZ9000 and established efficient methods for activity screening and peptide purification of engineered circularin A variants. These methods facilitated extensive mutagenesis studies of circularin A and functional investigations of its biosynthetic proteins. Mutagenesis studies indicated that the terminal residues near the circularization site, rather than the leader sequence, probably engage in interactions with biosynthetic proteins. The aromatic and cationic residues play important roles in circularin A biosynthesis and bioactivity. Furthermore, we have demonstrated promising prospects for engineering circular bacteriocins and recognized the critical role of structural flexibility in achieving the optimal antimicrobial activity of circularin A. Through functional investigations of biosynthetic proteins, we propose that CirC is responsible for catalyzing leader removal and possible circularization, whereas CirB and CirD form an ABC transporter for bacteriocin secretion. Overall, our work advances the understanding of the biosynthesis, bioactivity and bioengineering potential of circularin A, providing valuable insights for the development of novel antimicrobial agents with circular bacteriocins

Statistical methods in detecting differential expressed genes, analyzing insertion tolerance for genes and group selection for survival data

The thesis is composed of three independent projects: (i) analyzing transposon-sequencing data to infer functions of genes on bacteria growth (chapter 2), (ii) developing semi-parametric Bayesian method method for differential gene expression analysis with RNA-sequencing data (chapter 3), (iii) solving group selection problem for survival data (chapter 4). All projects are motivated by statistical challenges raised in biological research. The first project is motivated by the need to develop statistical models to accommodate the transposon insertion sequencing (Tn-Seq) data, Tn-Seq data consist of sequence reads around each transposon insertion site. The detection of transposon insertion at a given site indicates that the disruption of genomic sequence at this site does not cause essential function loss and the bacteria can still grow. Hence, such measurements have been used to infer the functions of each gene on bacteria growth. We propose a zero-inflated Poisson regression method for analyzing the Tn-Seq count data, and derive an Expectation-Maximization (EM) algorithm to obtain parameter estimates. We also propose a multiple testing procedure that categorizes genes into each of the three states, hypo-tolerant, tolerant, and hyper-tolerant, while controlling false discovery rate. Simulation studies show our method provides good estimation of model parameters and inference on gene functions. In the second project, we model the count data from RNA-sequencing experiment for each gene using a Poisson-Gamma hierarchical model, or equivalently, a negative binomial (NB) model. We derive a full semi-parametric Bayesian approach with Dirichlet process as the prior for the fold changes between two treatment means. An inference strategy using Gibbs algorithm is developed for differential expression analysis. We evaluate our method with several simulation studies, and the results demonstrate that our method outperforms other methods including the popularly applied ones such as edgeR and DESeq. In the third project, we develop a new semi-parametric Bayesian method to address the group variable selection problem and study the dependence of survival outcomes on the grouped predictors using the Cox proportional hazard model. We use indicators for groups to induce sparseness and obtain the posterior inclusion probability for each group. Bayes factors are used to evaluate whether the groups should be selected or not. We compare our method with one frequentist method (HPCox) based on several simulation studies and show that our method performs better than HPCox method. In summary, this dissertation tackles several statistical problems raised in biological research, including high-dimensional genomic data analysis and survival analysis. All proposed methods are evaluated with simulation studies and show satisfactory performances. We also apply the proposed methods to real data analysis

An ontology-based approach to Automatic Generation of GUI for Data Entry

This thesis reports an ontology-based approach to automatic generation of highly tailored GUI components that can make customized data requests for the end users. Using this GUI generator, without knowing any programming skill a domain expert can browse the data schema through the ontology file of his/her own field, choose attribute fields according to business\u27s needs, and make a highly customized GUI for end users\u27 data requests input. The interface for the domain expert is a tree view structure that shows not only the domain taxonomy categories but also the relationships between classes. By clicking the checkbox associated with each class, the expert indicates his/her choice of the needed information. These choices are stored in a metadata document in XML. From the viewpoint of programmers, the metadata contains no ambiguity; every class in an ontology is unique. The utilizations of the metadata can be various; I have carried out the process of GUI generation. Since every class and every attribute in the class has been formally specified in the ontology, generating GUI is automatic. This approach has been applied to a use case scenario in meteorological and oceanographic (METOC) area. The resulting features of this prototype have been reported in this thesis

Platinum group elements in the precipitation of the dry region of Xinjiang and factors affecting their deposition to land: the case of Changii City, China

AbstractPlatinum group elements and their compounds are a class of incident allergens and some platinum group element compounds also have carcinogenic effects. They accumulate in city environment as a result of emissions from catalysts used for vehicle exhausts. In this study, sixteen precipitation samples were collected on the north campus of Changji University located in the center of Changji. They were analyzed for palladium (Pd), platinum (Pt), and rhodium (Rh) by inductively coupled plasma–mass spectrometry. The average concentrations of Pd, Pt, and Rh were found to be 26.73ng L-1 (range: 3.18–84.25ng L-1), 1.71ng L-1 (range: below the detection limit to 6.38ng L-1), and 1.49ng L-1 (range: below the detection limit to 3.53ng L-1), respectively. Pd deposition was most pronounced for single precipitation events, reaching 35.47ng m-2 (range: 1.27–101.10ng m-2), followed by Rh (max. 4.96ng m-2, range: 0–14.85ng m-2) and Pt (max. 1.38ng m-2, range: 0-7.66ng m-2). Both Pd and Pt were higher in winter than in other seasons in terms of their wet deposition amounts and their concentrations in precipitation, whereas Rh was lower in winter. Moreover, the results indicated that discharge from coal combustion in winter, the amount of precipitation, and the number of dry days before rainfall events all significantly affected the wet deposition amount and precipitation concentration of platinum group elements. Pd deposition flux was highest (reaching 5.47×103 ng m-2) corresponding to 18 and 16 times the Rh and Pt fluxes, respectively. Finally, vehicle exhaust catalyst emissions from motor vehicles were not the only source of atmospheric platinum group metals in the city environment; in fact, combustion of coal in winter was found to be the dominant contributor of Pt and Pd in the atmosphere