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. ^

A novel 3-D segmentation algorithm for anatomic liver and tumor volume calculations for liver cancer treatment planning

Three-Dimensional (3-D) imaging is vital in computer-assisted surgical planning including minimal invasive surgery, targeted drug delivery, and tumor resection. Selective Internal Radiation Therapy (SIRT) is a liver directed radiation therapy for the treatment of liver cancer. Accurate calculation of anatomical liver and tumor volumes are essential for the determination of the tumor to normal liver ratio and for the calculation of the dose of Y-90 microspheres that will result in high concentration of the radiation in the tumor region as compared to nearby healthy tissue. Present manual techniques for segmentation of the liver from Computed Tomography (CT) tend to be tedious and greatly dependent on the skill of the technician/doctor performing the task. ^ This dissertation presents the development and implementation of a fully integrated algorithm for 3-D liver and tumor segmentation from tri-phase CT that yield highly accurate estimations of the respective volumes of the liver and tumor(s). The algorithm as designed requires minimal human intervention without compromising the accuracy of the segmentation results. Embedded within this algorithm is an effective method for extracting blood vessels that feed the tumor(s) in order to plan effectively the appropriate treatment. ^ Segmentation of the liver led to an accuracy in excess of 95% in estimating liver volumes in 20 datasets in comparison to the manual gold standard volumes. In a similar comparison, tumor segmentation exhibited an accuracy of 86% in estimating tumor(s) volume(s). Qualitative results of the blood vessel segmentation algorithm demonstrated the effectiveness of the algorithm in extracting and rendering the vasculature structure of the liver. Results of the parallel computing process, using a single workstation, showed a 78% gain. Also, statistical analysis carried out to determine if the manual initialization has any impact on the accuracy showed user initialization independence in the results. ^ The dissertation thus provides a complete 3-D solution towards liver cancer treatment planning with the opportunity to extract, visualize and quantify the needed statistics for liver cancer treatment. Since SIRT requires highly accurate calculation of the liver and tumor volumes, this new method provides an effective and computationally efficient process required of such challenging clinical requirements.^