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Exploration of the antimicrobial capabilities of Pantoea: Insights into a metabolically diverse genus
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Biology, University of Regina. xiii, 167 p.The rise of antimicrobial resistance has once again renewed interest in the
development of novel antimicrobials for the treatment of resistant pathogens. The genus
of bacteria Pantoea, a member of the Erwiniaceae, has been shown to produce several
unique antimicrobials with diverse targets. Chapter one gives a review of the known
antimicrobials produced by Pantoea including their discovery, genetic origins,
biosynthetic pathways, structures, mechanisms of action and resistance, distributions, and
insights into their evolutionary histories. Chapter two describes a replica-plating
technique that was developed to quickly and easily screen transposon mutant libraries to
discover the biosynthetic gene clusters responsible for antimicrobial biosynthesis in
bacteria, using Pantoea as a model. This method uses filter paper to transfer up to 200
mutants simultaneously onto soft agar overlays or spread plates containing a target
microbe to screen for loss of antibiotic production. The efficacy of this method was
demonstrated by re-screening for antibiotic biosynthetic gene clusters for three previously
identified Pantoea antibiotics: Pantoea natural product (PNP) 1, 2, and 3. This method
was then used to identify the biosynthetic gene cluster that was producing an unknown
antibiotic in the clinical isolate P. agglomerans 20KB447973, which we named PNP-5.
The recovered biosynthetic gene cluster for PNP-5 shows similarity to the broadspectrum
dithiolopyrrolone antibiotic, holomycin. PNP-5 shows broad-spectrum activity
against members of the Enterobacteriaceae, Erwiniaceae, and Streptococcaceae,
including clinically relevant pathogens such as Klebsiella spp. and Escherichia coli. We
also identified a second antibiotic produced by P. agglomerans 20KB447973: pantocin
A. Chapter three aims to uncover the distribution and provide insight into the potential
evolutionary history of known Pantoea antimicrobial biosynthetic gene clusters. A
survey of 12 known clusters against public databases and our genome collection show
that some clusters are found strictly in Pantoea, while others are more broadly distributed
in distantly related genera within Vibrionaceae, Pectobacteriaceae, Yersiniaceae,
Morganellaceae, and Hafniaceae. We compared the evolutionary history of these gene
clusters to a cpn60-based species tree, considering the flanking regions of each cluster to
provide some context for potential horizontal transfer events. Our analyses identified
potential occurrences of horizontal gene transfer in most clusters, supporting relatively
frequent exchanges of these metabolite biosynthetic genes. Chapter four provides
conclusions and future directions for this work. Overall, this work provides insight into
the antimicrobial versatility of Pantoea and its potential for providing novel antimicrobial
scaffolds that may be useful for therapeutic development.
Keywords: Pantoea, antimicrobial resistance, bacterial natural products, antimicrobial
biosynthetic gene clustersStudentye
Engagement with Interactive Displays from Static to Dynamic
No full textPresentation at the 2024 Saskatchewan Libraries Conference
Elucidating mechanisms of acid tolerance and antibiotic resistance in Salmonella and Klebsiella using transposon insertion sequencing (INSeq) and whole genome sequencing
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Biology, University of Regina. xiv, 236 p.Salmonella enterica and Klebsiella pneumoniae are two major public health concerns that
are responsible for millions of illnesses every year throughout the world. Much remains to
explore the genes and mechanisms that are critical for their pathogenesis and antibiotic
resistance. I used transposon Insertion Sequencing (INSeq), a powerful high-throughput
screening technique that can link bacterial genes to phenotypes and identify genes that are
essential for bacterial survival, to determine genes that are associated with survivability of
Salmonella Typhimurium in Luria Bertani (LB), E-minimal medium (EMM) and under
acid stress, and of K. pneumoniae under exposure to five classes of antibiotics. Growing a
pool of 450,000 mutants on LB identified a total of 362 essential genes, the majority of
which (90.6%) are within the S. Typhimurium core genome. The pCol1B9 replication
initiation and its regulator, repZ and repY, are among the essential genes found in the
strain's accessory genome. Comparing essential genes identified in LB to two earlier
studies of S. Typhimurium strains and identifying genes that are conditionally essential in
EMM suggest that a single growth environment and strain cannot provide a comprehensive
understanding of essential genes at the species level. S. Typhimurium is hypothesized to
have a special acid tolerance system in which the cytoplasm becomes more acidic. I applied
INSeq to find genes that contribute to acid tolerance at pH 4.0 and pH 5.0. For which I
developed a modified INSeq approach capable of identifying genes required for persistence
in non-growth conditions. In addition to several known genes, this project identified novel
acid tolerance genes including trxB (thioredoxin reductase), pykF (pyruvate kinase), sspA
(starvation protein), and revealed that as the stress increases through time and decreasing
pH, additional tolerance mechanisms are required to protect cells. Next, I used INSeq to
find intrinsic resistance genes in a clinical isolate of multidrug resistant K. pneumoniae.
We found pstB (ABC transporter ATP binding protein), gltA (Citrate synthase), tgt (tRNA
guanosine transglycosylase), fabF (fatty acid synthase), and glycosyltransferase encoding
genes: pgaptmp_000142, pgaptmp_000147, and pgaptmp_000148, each contribute to
resistance across multiple classes of antibiotics. Considering all the INSeq data, healthy
cell envelopes were found to be crucial for optimum growth and cell protection, regardless
of the growth environment, which included laboratory conditions under acid and antibiotic
stresses. In addition, numerous known genes were identified for corresponding features,
such as phoP-phoQ system for acid tolerance and acrAB-tolC for multidrug resistance,
confirming the effectiveness of INSeq. I next used whole genome sequencing to find
genetic changes in S. Typhimurium isolates to characterize a sugar metabolism and an
antibiotic resistance phenotype. First, I helped characterize how a C→T transition in the
dctA promoter allows for growth at lower orotate concentrations by creating an improved
binding site for the transcriptional activator CRP. Secondly, by progressively challenging
cells with higher concentrations of antibiotics, I discovered an A→T transition in codon
466 of gyrB reduces ciprofloxacin sensitivity in a S. Typhimurium mutant that cannot
synthesize the intracellular signaling molecule cAMP.
Both Salmonella and Klebsiella are considered top priority pathogens for research and
development of new antibiotics; this PhD thesis provides an improved understanding of
the biology of both organisms and simultaneously identifies high-quality candidate genes
that can be targeted for the development of improved antibiotics and other therapeutics.Studentye
Prevalence of Current Chronic Pain in Royal Canadian Mounted Police Cadets
No full textBackground: Nearly half of active duty Royal Canadian Mounted Police (RCMP) officers (i.e.,
43%) report experiencing current chronic pain (i.e., pain lasting longer than 3 months). Most
RCMP officers (i.e., 91%) who report chronic pain indicate that the pain started after working as
RCMP officers. Baseline data on chronic pain prevalence among RCMP cadets has not been
available. Aims: The current study was designed to provide cross-sectional estimates of chronic
pain prevalence among RCMP cadets starting the Cadet Training Program and to assess for
sociodemographic differences among participants. Methods: The RCMP Study uses a
longitudinal prospective sequential experimental cohort design to create a clustered randomized
trial that engages individual participants for 5.5 years. The current manuscript provides cross-
sectional associations between chronic pain prevalence and sociodemographic characteristics.
Participants were RCMP cadets (n=770) starting the Cadet Training Program. Location, intensity
(i.e., on a 0-10 scale, and days per week experienced), and duration (i.e., number of months) of
chronic pain was reported. Differences across sociodemographic characteristics were examined.
Results: Few RCMP cadets reported experiencing chronic pain (i.e., 10%); lower back pain was
rated as the most severe in terms of intensity and duration, and second most frequently reported
in number of days experienced per week. Prevalence of chronic pain was lower among RCMP
cadets than RCMP officers. Conclusions: Chronic pain prevalence among active duty RCMP
officers may result from or be moderated by operational duties, as well as routine aging. Future
researchers could examine ways to mitigate chronic pain development during RCMP officer
careers.The authors disclosed the receipt of the following financial support for the research and
authorship of this article: The RCMP Study is funded by support from the RCMP, the
Government of Canada, and the Ministry of Public Safety and Emergency Preparedness. The
development, analyses, and distribution of the current article was made possible by a generous
and much-appreciated grant from the Medavie Foundation. R. N. Carleton is supported by
CIPSRT, Canadian Institutes of Health Research, Canada Ministry of Public Safety and
Emergency Preparedness, Royal Canadian Mounted Police, a Medavie Foundation Project Grant.
G. J. G. Asmundson is supported by a University of Regina President’s Research Chair
Victim blaming in the courtroom: The influence of lawyer gender and style on juror decision-making
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Science in Experimental and Applied Psychology, University of Regina. viii, 116 p.Despite the present Canadian laws meant to protect victims of sexual assault during the trial process, it is common for defence lawyers to employ stereotypes against the victim (a process known as “whacking”; Tanovich, 2015). It is unclear whether the gender of the defence lawyer is a determining factor in the influence of such stereotypes. Only a limited number of studies have examined the effects of lawyer gender, which yielded conflicting findings (Levi et al., 2022; Villemur & Hyde, 1983). Moreover, the previous studies did not explore whether the lawyers’ cross-examination style or the juror’s level of sexism factor into their verdict choice. This thesis extended previous literature by examining the potential impact of defence lawyer gender, cross-examination style, and jurors’ benevolent sexist attitudes on the outcomes of sexual assault trials and lawyer perceptions. A community sample (N = 212) of jury-eligible Canadians were recruited to read a mock sexual assault trial transcript. The defence lawyer’s gender (woman/man) and cross-examination content (whacking/no whacking) were manipulated. Following the trial transcript, participants delivered an individual verdict and completed measures of ambivalent sexism, rape myth acceptance, and perceived lawyer capability. Three-way interactions were not observed between lawyer gender, cross-examination style, and juror sexism on the verdict outcome or lawyer capability. However, benevolent sexism did directly predict perceptions of the defence lawyer, and the whacking manipulation indirectly affected the verdict outcome via mock jurors’ perceptions of the victim’s culpability. Of most interest, implementing the whacking tactic increased the defence lawyer’s chance at obtaining a not-guilty verdict if the lawyer and the juror were men. Keywords: Juror-decision making, lawyer gender, benevolent sexism, rape myth acceptance, sexual assault trials, victim blamingStudentye
A commercial pathway for evaluating the performance of a novel amine solvent blend in a mini-pilot plant for carbon capture
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Process Systems Engineering, University of Regina. xvi, 142 p.This study investigates the performance of a novel solvent bi-blend, 4M (2:2) AMP:1-(2HE) PRLD, for CO2 capture through absorption and desorption, providing a potential alternative to the conventional 5M Monoethanolamine (MEA). The pathway utilized to assess the performance of the amine bi-blend for commercial application involved conducting carbon capture experiments in a laboratory bench-scale mini-pilot plant. This approach aimed to validate the solvent's performance under conditions that mimic a full-scale commercial industrial CO2 capture plant. The research also addresses the urgent need for more efficient and cost-effective carbon capture solutions to combat increasing greenhouse gas emissions and global warming.
Experiments were conducted with varying feed gas compositions, with CO2 concentrations ranging from 4.5% to 30%, to simulate different industrial emission scenarios. Key performance metrics, including CO2 absorption efficiency, cyclic capacity, mass transfer rates, and energy consumption for solvent regeneration, were meticulously evaluated. For a CO2 partial pressure of 4.5%, the novel solvent blend demonstrated significant performance enhancements compared to 5M MEA. Specifically, the 4M (2:2) AMP:1-(2HE) PRLD blend exhibited an enhancement in absorption efficiency by up to 25% at a reboiler temperature of 110 °C, 41% at 100 °C, and over 700% at 90 °C. Additionally, there was a reduction in regeneration energy requirements by approximately 30% at 110 °C, 43% at 100 °C, and 84% at 90 °C. The novel blend showed robust performance across a wide range of these parameters, indicating its versatility and suitability for diverse industrial applications.
The study also revealed an average increase of 150% in the overall gas phase volumetric mass transfer coefficient (KGav) and 110% for the overall liquid-phase volumetric mass transfer coefficient (KLav). These significant improvements emphasize the novel blend's superior mass transfer performance, which is crucial for maximizing CO2 capture efficiency and column design. Parametric studies were conducted to understand the influence of various operational parameters on mass transfer performance. It was observed that the absorption efficiency and mass transfer rates were significantly influenced by CO2 loading, gas flow rate, desorption temperature and pressure. Results from this exercise showed that there is a strong positive correlation between the reboiler temperature and the efficiency as well as the overall mass transfer coefficient. It was also noted that the mass transfer was mainly controlled by the liquid phase while increasing the desorber pressure had an inverse effect on the lean amine loading which was attributed to the higher gas solubility at the higher pressure. The effect of CO2 partial pressure was also studied and a negative correlation was observed between CO2 partial pressure and the absorber efficiency, overall gas phase mass transfer coefficient.
Heat duty analysis revealed that the novel solvent blend required less energy for regeneration, thus offering a more energy-efficient solution. The specific energy consumption for the AMP-PRLD blend was found to be significantly lower than that for 5M MEA, highlighting its potential to reduce operational costs and environmental impacts. The study concludes that the novel solvent blend not only provides a more efficient CO2 capture solution but also aligns with the goals of reducing greenhouse gas emissions and achieving net-zero emissions from the indirect co-combustion of natural gas and biomass for energy generation even at relatively lower desorption temperature (100-110 °C) thus significantly contributing to energy savings.Studentye
Coping with the distribution change in soil classification with LIBS
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Electronic Systems Engineering, University of Regina. xii, 164 p.Accurate classification of soil types is crucial for crop productivity. Among the soil analysis techniques,
laser-induced breakdown spectroscopy (LIBS) has become a prominent technology for
real-time characterization of soil properties. The recent rise in the use of machine learning (ML)
techniques for processing LIBS spectra has made LIBS more attractive. However, due to variations
in the physical properties and/or chemical composition of the soil samples, the distribution
of spectral emission lines can be highly variable, which may lead to different distributions of LIBS
spectra and make the training and test spectra not representative of each other. Hence the test performance
of an ML model trained with only samples from the training distribution may degrade
when applied to the test distribution. We propose multiple ML algorithms to handle the spectra
distribution problem in this work.
We first propose using the test data calibration with training distribution as a reference. The
median of principal components (PCs) is suggested to be calibrated in the process. The median
of the training’s and test’s PCs are independently calculated, and then the test’s median is adjusted
based on its differences with the training’s. With the calibrated PCs, the test spectra are
reconstructed accordingly. The performance of the proposed calibration algorithm is tested with
the challenging Euro-Mediterranean symposium on laser-induced breakdown spectroscopy (EMSLIBS)
dataset, and it is found that it can efficiently improve the test performance by 3% compared
with the contest winners.
However, some information is lost after data reconstruction with calibration. To keep all
the test data information but improve the test performance, we propose a novel class-balanced
self-paced learning, a type of self-learning, to avoid the gradual dominance of large classes in a
pseudo-label generation. Instead of using universal class selection proportions for all classes, the
proposed class-balanced self-paced learning method customizes the class selection proportions to
avoid model bias in the self-training process. The proposed method is tested with the challenging
LIBS dataset, which shows the proposed method can effectively handle the spectra distribution
change and achieves comparable test accuracy with the EMSLIBS contest winners.
The proposed class-balanced self-paced learning method effectively handles the distribution
change. However, it takes 20 iterations of co-training, and the test accuracy cannot be improved
any further. To address the distribution issue more efficiently, we propose pseudo-labelling the
misclassified test samples based on similarity confidence using pseudo-shot learning with Siamese
networks instead of conducting pseudo-labelling by prediction confidence. Considering the domain
transfer differences among classes, we categorize the classes as hard, normal, and easy to reflect
the class transfer difficulties in domain adaptation (DA). We mainly focus on the hard classes
as samples from these classes are not representative of the source domain and can easily be misclassified
in the prediction phase. Few-shot learning is used to find the spectra from hard classes
but misclassified into their similar classes. These spectra are included to co-train the model with
source samples to improve the test performance of hard classes. Our framework is tested with the
EMSLIBS dataset, which shows that it can effectively overcome the spectra distribution shift and
achieves 94.12% test accuracy.
To validate the effectiveness of the proposed algorithms, a case study is conducted with our
experimental data. We simulate the data streaming in real-time, where the spectra are collected
with different experimental setups. To conquer the data size limitation and changes in the sample
preparations and apparatus in the data streaming, we propose a framework based on transfer learning
to use limited experimental data and adapt to the emission line variation in the LIBS streaming.
The collected spectra from different experiments are fed into our model in chunks. These chunks
of experimental data are then fed into the pre-trained model, and data evolution is dynamically
learned by self-balanced learning to self-adapt to the domain shift. Self-balanced learning is undertaken
for each chunk by repeatedly predicting the current chunk using the model trained by
recent chunks and then taking the confident predictions as pseudo-labels for co-training the model.
In this way, the model can adapt to changes in LIBS measurements due to experimental variation
and matrix effects and improve the model’s generalization.Studentye
Catalyst-aided CO2 capture from exhaust gases of industrial point sources for utilization in cement-based industry
No full textA Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Process Systems Engineering, University of Regina. xiv, 169 p.The utilization of solid-base catalysts to improve CO2 capture in amine-based postcombustion
processes represents a significant technological advance. However, addressing
both cost and catalytic efficiency remains crucial. Given the inherently expensive nature
of amine-based post-combustion, there is an urgent need to explore innovative strategies
to alleviate financial burdens. Research has shown that costs can be reduced by eliminating
the desorption tower and utilizing enriched solvent directly from the absorber column.
Accelerating the capture process via catalyst introduction reduces column height and
further cuts costs. The primary focus of our study was to develop an alkaline catalyst to
enhance CO2 loading in Potassium Glycinate salt solution. Our ultimate goal was to apply
this enriched solution in the cement-based industry for producing concrete,
mortar, and grout.
In the course of this research, a total of twelve super basic catalysts were
synthesized and rigorously assessed using a semi-batch apparatus. Their initial absorption
rates were meticulously scrutinized and juxtaposed against the baseline scenario devoid of
any catalyst. Notably, the introduction of most catalysts yielded a marked acceleration in
CO2 absorption, resulting in remarkably increased absorption rates. These initial
absorption rates were observed to follow a discernible ascending order Ce/CaO < K/MgO
< Blank < AGO* < K/MgO + AGO < K/MgO + GO < Ce/MgO < AC (H) < AC (H) +
MgO < GO < AGO + AC (H) < K-MgO/AC (C) < AGO. Outstandingly, AGO exhibited
the highest initial absorption rate at 5.12×10-2 (mol CO2/l.min), closely traced by KMgO/
AC (C) at 4.77×10-2 (mol CO2/l.min), while Ce/CaO and K/MgO displayed
relatively lower performance at 3.56×10-2 and 3.63×10-2, respectively. Intriguingly, it was
noted that Ce/CaO and K/MgO, rather than facilitating CO2 absorption by the Potassium
Glycinate salt solution, reverted to their starting materials, Ca(OH)2 and Mg(OH)2
respectively, in the presence of water which formed carbonates with the CO2, diminishing
the readily available CO2 for the Potassium Glycinate salt solution to capture.
Considering the intricate and potentially hazardous nature of the AGO preparation
process, along with environmental and safety concerns related to the chemicals used, KMgO/
AC (C) was selected as the preferred catalyst for this study. It exhibited a 25.2%
enhancement in the absorption process, in contrast to the 34.4% improvement achieved by
AGO. K-MgO/AC (C) underwent comprehensive characterization to determine both its
chemical and physical properties, and the findings are meticulously documented in this
study. Moreover, the results derived from the characterization of K-MgO/AC (C) were
juxtaposed with existing data on AC (H) and K/MgO from literature, providing insights
into and comparisons of the performance of these three catalysts based on their respective
characteristics.
In an effort to assess the stability of the K-MgO/AC (C) catalyst, two distinct
approaches were employed. In the first approach, the same catalyst was utilized for three
consecutive runs, with fresh solvent introduced between each run. In the second approach,
the catalyst underwent washing, drying, and high-temperature calcination to eliminate any
residual deposits before being reused. The stability analysis outcomes corroborated the
robust stability of the K-MgO/AC (C) catalyst for up to three successive cycles of usage,
a conclusion reinforced by the results obtained from thermal gravimetric analysis (TGA).
Worth noting is the fact that all experiments conducted during the course of this study
remained well within the acceptable margin of error, not exceeding 8%.Studentye
Beyond free condoms and exit strategies: developing a working model of practice with sex working clients through a field practicum experience
No full textA Practicum Report Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Social Work, University of Regina. v, 76 p.Studentye
I know that person! Why can’t I remember?
No full textA Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science (Honours) in Psychology, University of Regina. 26 p.The butcher-on-the-bus phenomenon refers to repeatedly encountering a person in a specific context and later failing to recognize them in a novel context. Despite the failure to recognize the person, a strong sense of familiarity occurs. Although this phenomenon commonly occurs, little is known about its underlying cause. One possibility is that the informativeness of the context increases the strength of the association between context and identity. This association may then interfere with recognizing the same person in a novel context. This study was designed to examine the following question: Is recognition of faces in previously-unseen contexts influenced by the allocation of attention to previously-seen contexts? Attention to context was manipulated by altering whether the context provided identity-specific information such as the target’s occupation or hobbies, and whether the context was consistent (mimicking the experience of repeatedly encountering a face in the same context) or varied. Unexpectedly, I found that identities first encountered in an informative context were later recognized better in a new context than those encountered in uninformative contexts. This suggests that the informativeness of context provides a powerful cue that aids in the learning of a new face, surpassing the benefit of exposure to within-person variability