High susceptibility of MDR and XDR Gram-negative pathogens to biphenyl-diacetylene-based difluoromethyl-allo-threonyl-hydroxamate LpxC inhibitors.

OBJECTIVES: Inhibitors of uridine diphosphate-3-O-(R-3-hydroxymyristoyl)-N-acetylglucosamine deacetylase (LpxC, which catalyses the first, irreversible step in lipid A biosynthesis) are a promising new class of antibiotics against Gram-negative bacteria. The objectives of the present study were to: (i) compare the antibiotic activities of three LpxC inhibitors (LPC-058, LPC-011 and LPC-087) and the reference inhibitor CHIR-090 against Gram-negative bacilli (including MDR and XDR isolates); and (ii) investigate the effect of combining these inhibitors with conventional antibiotics. METHODS: MICs were determined for 369 clinical isolates (234 Enterobacteriaceae and 135 non-fermentative Gram-negative bacilli). Time-kill assays with LPC-058 were performed on four MDR/XDR strains, including Escherichia coli producing CTX-M-15 ESBL and Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii producing KPC-2, VIM-1 and OXA-23 carbapenemases, respectively. RESULTS: LPC-058 was the most potent antibiotic and displayed the broadest spectrum of antimicrobial activity, with MIC90 values for Enterobacteriaceae, P. aeruginosa, Burkholderia cepacia and A. baumannii of 0.12, 0.5, 1 and 1 mg/L, respectively. LPC-058 was bactericidal at 1× or 2× MIC against CTX-M-15, KPC-2 and VIM-1 carbapenemase-producing strains and bacteriostatic at ≤4× MIC against OXA-23 carbapenemase-producing A. baumannii. Combinations of LPC-058 with β-lactams, amikacin and ciprofloxacin were synergistic against these strains, albeit in a species-dependent manner. LPC-058's high efficacy was attributed to the presence of the difluoromethyl-allo-threonyl head group and a linear biphenyl-diacetylene tail group. CONCLUSIONS: These in vitro data highlight the therapeutic potential of the new LpxC inhibitor LPC-058 against MDR/XDR strains and set the stage for subsequent in vivo studies.

Data to Decision in a Dynamic Ocean: Robust Species Distribution Models and Spatial Decision Frameworks

Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

Acoustic and Magnetic Techniques for the Isolation and Analysis of Cells in Microfluidic Platforms

Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.

The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.

The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.