The large-scale, four-year 'PharmaSea' project, which began in October 2012, brings together 24 partners from 13 countries and involves the collection of mud and sediment samples from extreme oceanic trenches up to nine kilometres deep; the creation of small-molecule extract libraries from marine bacteria isolated from these samples; and biological screening of these extracts to identify chemical compounds with drug-like properties. These molecules will be developed further as drug leads in three indication areas – inflammation, infectious diseases, and CNS disorders.
Only a handful of samples from deep-sea trenches have ever been collected and studied, so the project is breaking new ground. One PharmaSea partner, Deeptek –an SME based in Scotland – has developed new instrumentation for sampling from the ocean bottoms using engineering technology based on salvaging operations that can considerably cut down costs. PharmaSea will also search for new microbes in other unique environments (e.g. thermal vents and whale falls) in collaboration with partners from New Zealand and Norway. "PharmaSea will not only be exploring new territory at the bottom of the oceans, but also new areas in 'chemical space'," says Esguerra.
KU Leuven's lab is contributing to the third work package, which focuses on bioassays and screening. Senior scientist Alex Crawford explains: "Our lab will help isolate novel neuroactive compounds using zebrafish assays. In a first phase of screening, we will observe what zebrafish larvae do in the presence of the various deep sea extracts. By flashing a burst of light to trigger a startle response, we are able determine whether a given deep sea extract is associated with an atypical photo-motor response. If so, that extract is identified as having a neuroactive behavioural footprint and is set aside for further testing."
Determining a sample's behavioural footprint is the first step in isolating a novel molecule or compound for drug development. "Based on preliminary experiments we expect an appreciable number of extracts to show neuroactivity in this zebrafish screen. The next step is to identify the active molecule in the extract – the classic challenge of natural product discovery," says Crawford.
Molecule isolation is achieved through an iterative process of bioactivity analysis and chromatographic separation. "Neuroactive extracts go on to a secondary, disease-specific screening and then undergo a 'fractionation' process. These fractions are then re-tested for neuroactivity and active fractions are separated down to the molecular level using methods like microfractionation, mass spectrometry and NMR spectroscopy." Fractionation and molecular-level analysis will be carried out by consortium scientists at the University of Aberdeen and University College Cork, respectively. Professor Marcel Jaspars, head of the Marine Biodiscovery Centre at the University of Aberdeen, is Project Leader of PharmaSea.
The researchers hope the neuroactive compounds and molecules isolated from the deep-sea samples can be developed into seizure-inhibiting drugs. Esguerra: "At the moment, over 30% of patients with epilepsy do not respond to currently available anti-epileptic drugs. Therefore their seizures remain uncontrolled, leading to high mortality or cognitive and locomotor impairments. Over the last several years, our laboratory has established a number of different zebrafish seizure models. With the help of these models, we are quite hopeful the we will find a number of exciting new drug leads."
Tine Heylen of Leuven Research & Development (LRD) is one of two Project Managers for PharmaSea, and provides crucial administrative support for the project. Doctoral researcher Daniëlle Koopmans has optimized the behavioral fingerprinting assay, and will focus her PhD thesis on identifying and characterizing neuroactive compounds in the context of PharmaSea.
AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.