A changing climate is altering many ocean properties that consequently will modify marine productivity. Previous phytoplankton manipulation studies have focused on individual or subsets of these properties. Here, we investigate the cumulative e ects of multi-faceted change on a subantarctic diatom Pseudonitzschia multiseries by concurrently manipulating five stressors (light/nutrients/CO 2 /temperature/iron) that primarily control its physiology, and explore underlying reasons for altered physiological performance. Climate change enhances diatom growth mainly owing to warming and iron enrichment, and both properties decrease cellular nutrient quotas, partially o setting any e ects of decreased nutrient supply by 2100. Physiological diagnostics and comparative proteomics demonstrate the joint importance of individual and interactive e ects of temperature and iron, and reveal biased future predictions from experimental outcomes when only a subset of multi-stressors is considered. Our findings for subantarctic waters illustrate how composite regional studies are needed to provide accurate global projections of future shifts in productivity and distinguish underlying species-specific physiological mechanisms.A n ongoing major challenge is to grasp how climate-changemediated alteration of environmental conditions will influence biota across different scales, from organismal health to community structure 1,2 . Oceanographers have employed climate-change models 3,4 , time-series observations 5 and manipulation experiments 6 to understand the biological ramifications of global change. Phytoplankton manipulation studies reveal how alteration of individual properties, such as CO 2 , affects physiology 2,6,7 . However, the validity of such singleparameter findings 6,8,9 , in the context of complex ocean change 1,2 , is challenged by research that reveals interactive effects between multi-stressors on phytoplankton physiology 10,11 . We need to diagnose and understand the physiological mechanisms that underpin interconnected responses to multi-stressors, which together set the cumulative response of phytoplankton species to changing conditions 4,6,8 .Understanding the combined effects, across the global ocean, of complex change on phytoplankton physiology requires a gradualist approach 12,13 . Individual provinces will encounter different permutations of multi-faceted change 14 , and each is characterized by a range of resident phytoplankton groups (termed biomes 5 ). Earth System models provide a framework of projections of regional change 14 that stimulate improved experimental design to understand the biological effects of oceanic change. In return, a new generation of manipulation studies must deliver estimates of the combined effects of complex change on many phytoplankton species, and distinguish the underlying mechanisms that underpin these physiological outcomes.Here, we target subantarctic diatoms, which are ubiquitous and bloom-formers 15 . We experimentally manipulate a representative species 6,15 (Pseudonitzschi...

BackgroundOcean acidification as a result of increased anthropogenic CO2 emissions is occurring in marine and estuarine environments worldwide. The coastal ocean experiences additional daily and seasonal fluctuations in pH that can be lower than projected end-of-century open ocean pH reductions. In order to assess the impact of ocean acidification on marine invertebrates, Pacific oysters (Crassostrea gigas) were exposed to one of four different p CO2 levels for four weeks: 400 μatm (pH 8.0), 800 μatm (pH 7.7), 1000 μatm (pH 7.6), or 2800 μatm (pH 7.3).ResultsAt the end of the four week exposure period, oysters in all four p CO2 environments deposited new shell, but growth rate was not different among the treatments. However, micromechanical properties of the new shell were compromised by elevated p CO2. Elevated p CO2 affected neither whole body fatty acid composition, nor glycogen content, nor mortality rate associated with acute heat shock. Shotgun proteomics revealed that several physiological pathways were significantly affected by ocean acidification, including antioxidant response, carbohydrate metabolism, and transcription and translation. Additionally, the proteomic response to a second stress differed with p CO2, with numerous processes significantly affected by mechanical stimulation at high versus low p CO2 (all proteomics data are available in the ProteomeXchange under the identifier PXD000835).ConclusionsOyster physiology is significantly altered by exposure to elevated p CO2, indicating changes in energy resource use. This is especially apparent in the assessment of the effects of p CO2 on the proteomic response to a second stress. The altered stress response illustrates that ocean acidification may impact how oysters respond to other changes in their environment. These data contribute to an integrative view of the effects of ocean acidification on oysters as well as physiological trade-offs during environmental stress.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-951) contains supplementary material, which is available to authorized users.

No abstract

In principle, tandem mass spectrometry can be used to detect and quantify the peptides present in a microbiome sample, enabling functional and taxonomic insight into microbiome metabolic activity. However, the phylogenetic diversity constituting a particular microbiome is often unknown, and many of the organisms present may not have assembled genomes. In ocean microbiome samples, with particularly diverse and uncultured bacterial communities, it is difficult to construct protein databases that contain the bulk of the peptides in the sample without losing detection sensitivity due to the overwhelming number of candidate peptides for each tandem mass spectrum. We describe a method for deriving “metapeptides” (short amino acid sequences that may be represented in multiple organisms) from shotgun metagenomic sequencing of microbiome samples. In two ocean microbiome samples, we constructed site-specific metapeptide databases to detect more than one and a half times as many peptides as by searching against predicted genes from an assembled metagenome, and more than three times as many peptides as by searching against the NCBI environmental proteome database. The increased peptide yield can be used to enrich the taxonomic characterization of sample metaproteomes.