Identification and localization of polyketide synthase genes from cultures of diarrheic shellfish poisoning toxin producing dinoflagellates of the genus Prorocentrum

Aquatic toxins are responsible for a number of acute and chronic diseases in humans. Okadaic acid (OA) and other dinoflagellate derived polyketide toxins pose serious health risks on a global scale. Ingestion of OA contaminated shellfish causes diarrheic shellfish poisoning (DSP). Some evidence also suggests tumor promotion in the liver by OA. Microcystin-LR (MC-LR) is produced by cyanobacteria and is believed to be the most common freshwater toxin in the US. Humans may be exposed to this acute hepatotoxin through drinking or recreational use of contaminated waters. ^ OA producing dinoflagellates have not been cultured axenically. The presence of associated bacteria raises questions about the ultimate source of OA. Identification of the toxin-producing organism(s) is the first step in identifying the biosynthetic pathways involved in toxin production. Polyketide synthase (PKS) genes of toxic and non-toxic species were surveyed by construction of clonal libraries from PCR amplicons of various toxic and non-toxic species of Prorocentrum in an effort to identify genes, which may be part of the biosynthetic pathway of OA. Analysis of the PKS sequences revealed that toxic species shared identical PKS genes not present in non-toxic species. Interestingly, the same PKS genes were identified in a library constructed from associated bacteria. ^ Subsequent bacterial small subunit RNA (16S) clonal libraries identified several common bacterial species. The most frequent 16S sequences found were identified as species of the genus Roseobacter which has previously been implicated in the production of OA. Attempts to culture commonly occurring bacteria resulted in the isolation of Oceanicaulis alexandrii , a novel marine bacterium previously isolated from the dinoflagellate Alexandrium tamarense, from both P. lima, and P. hoffmanianum. ^ Metabolic studies of microcystin-LR, were conducted to probe the activity of the major human liver cytochromes (CYP) towards the toxin. CYPs may provide alternate routes of detoxification of toxins when the usual routes have been inhibited. For example, some research indicates that cyanobacterial xenobiotics, in particular, lipopolysaccharides may inhibit glutathione S-transferases allowing the toxin to persist long enough to be acted upon by other enzymes. These studies found that at least one human liver CYP was capable of metabolizing the toxin. ^

Development of test-based wind-driven rain intrusion model for hurricane-induced building interior and contents damage

Major portion of hurricane-induced economic loss originates from damages to building structures. The damages on building structures are typically grouped into three main categories: exterior, interior, and contents damage. Although the latter two types of damages, in most cases, cause more than 50% of the total loss, little has been done to investigate the physical damage process and unveil the interdependence of interior damage parameters. Building interior and contents damages are mainly due to wind-driven rain (WDR) intrusion through building envelope defects, breaches, and other functional openings. The limitation of research works and subsequent knowledge gaps, are in most part due to the complexity of damage phenomena during hurricanes and lack of established measurement methodologies to quantify rainwater intrusion. This dissertation focuses on devising methodologies for large-scale experimental simulation of tropical cyclone WDR and measurements of rainwater intrusion to acquire benchmark test-based data for the development of hurricane-induced building interior and contents damage model. Target WDR parameters derived from tropical cyclone rainfall data were used to simulate the WDR characteristics at the Wall of Wind (WOW) facility. The proposed WDR simulation methodology presents detailed procedures for selection of type and number of nozzles formulated based on tropical cyclone WDR study. The simulated WDR was later used to experimentally investigate the mechanisms of rainwater deposition/intrusion in buildings. Test-based dataset of two rainwater intrusion parameters that quantify the distribution of direct impinging raindrops and surface runoff rainwater over building surface — rain admittance factor (RAF) and surface runoff coefficient (SRC), respectively —were developed using common shapes of low-rise buildings. The dataset was applied to a newly formulated WDR estimation model to predict the volume of rainwater ingress through envelope openings such as wall and roof deck breaches and window sill cracks. The validation of the new model using experimental data indicated reasonable estimation of rainwater ingress through envelope defects and breaches during tropical cyclones. The WDR estimation model and experimental dataset of WDR parameters developed in this dissertation work can be used to enhance the prediction capabilities of existing interior damage models such as the Florida Public Hurricane Loss Model (FPHLM).^

Boardwalk and mangrove forest canopy damaged by Hurricane Wilma, Shark River Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

A Markov chain location-allocation meta-model for hurricane relief

An emergency is a deviation from a planned course of events that endangers people, properties, or the environment. It can be described as an unexpected event that causes economic damage, destruction, and human suffering. When a disaster happens, Emergency Managers are expected to have a response plan to most likely disaster scenarios. Unlike earthquakes and terrorist attacks, a hurricane response plan can be activated ahead of time, since a hurricane is predicted at least five days before it makes landfall. This research looked into the logistics aspects of the problem, in an attempt to develop a hurricane relief distribution network model. We addressed the problem of how to efficiently and effectively deliver basic relief goods to victims of a hurricane disaster. Specifically, where to preposition State Staging Areas (SSA), which Points of Distributions (PODs) to activate, and the allocation of commodities to each POD. Previous research has addressed several of these issues, but not with the incorporation of the random behavior of the hurricane's intensity and path. This research presents a stochastic meta-model that deals with the location of SSAs and the allocation of commodities. The novelty of the model is that it treats the strength and path of the hurricane as stochastic processes, and models them as Discrete Markov Chains. The demand is also treated as stochastic parameter because it depends on the stochastic behavior of the hurricane. However, for the meta-model, the demand is an input that is determined using Hazards United States (HAZUS), a software developed by the Federal Emergency Management Agency (FEMA) that estimates losses due to hurricanes and floods. A solution heuristic has been developed based on simulated annealing. Since the meta-model is a multi-objective problem, the heuristic is a multi-objective simulated annealing (MOSA), in which the initial solution and the cooling rate were determined via a Design of Experiments. The experiment showed that the initial temperature (T0) is irrelevant, but temperature reduction (δ) must be very gradual. Assessment of the meta-model indicates that the Markov Chains performed as well or better than forecasts made by the National Hurricane Center (NHC). Tests of the MOSA showed that it provides solutions in an efficient manner. Thus, an illustrative example shows that the meta-model is practical.