Shedding light on the Global Ocean microbiome with algorithms and data collection
Federico Lauro1,2, Martin Ostrowski3,4, Caroline Chénard1, Enzo Acerbi1, Ian Paulsen3,4, Rachelle Jensen2 and Indigo V Expeditions, (1)Nanyang Technological University, (2)Indigo V Expeditions, (3)Macquarie University, (4)Indigo V Expeditions, Australia
Abstract:
In the Global Oceans, the marine microbiome plays a critical role in biogeochemical cycling of nutrients, but surveying marine microbial communities requires ship time for sample collection, economically constraining the number of samples collected. An integrative understanding of the microbiome’s activity and performance requires the collection of high-density data, both temporally and spatially in a cost-effective way. We have overcome this bottleneck by crowdsourcing the data collection to vessels of opportunity, including bluewater sailing yachts. Sailors know the oceans, and experience first-hand the declines in ocean productivity and the effects of pollution and climate change. Moreover, simply the ability to sample a microbial community during anomalous or inclement weather conditions is a major advance in sampling strategy. Our approach inherently incorporates the benefit of outreach and participation of people in scientific research, gaining positive media attention for sailors, scientists and concerned citizens alike.
We have tested the basic methods during a 2013 Indian Ocean Concept Cruise, from Cape Town to Singapore, performing experimental work and reaching sampling locations inaccessible to traditional Oceanographic Vessels. At the same time we developed a small, yacht-adapted automated sampling device that takes a variety of biological and chemical measurements. In 2015 our first beta-cruisers sampled the Pacific Ocean in the first ever citizen-oceanography transect at high and low latitudes in both hemispheres. The collected samples were characterized with next-gen sequencing technology and analysed with a combination of novel algorithmic approaches. With big data management, machine learning algorithms and agent-based models we show that it is possible to deconvolute the complexity of the Ocean Microbiome for the scientific management of fisheries, marine protected areas and preservation of the oceans and seas for generations to come.
