Dissolution dominating calcification process in polar pteropods close to the point of aragonite undersaturation

Thecosome pteropods are abundant upper-ocean zooplankton that build aragonite shells. Ocean acidification results in the lowering of aragonite saturation levels in the surface layers, and several incubation studies have shown that rates of calcification in these organisms decrease as a result. This study provides a weight-specific net calcification rate function for thecosome pteropods that includes both rates of dissolution and calcification over a range of plausible future aragonite saturation states (Omega_Ar). We measured gross dissolution in the pteropod Limacina helicina antarctica in the Scotia Sea (Southern Ocean) by incubating living specimens across a range of aragonite saturation states for a maximum of 14 days. Specimens started dissolving almost immediately upon exposure to undersaturated conditions (Omega_Ar,0.8), losing 1.4% of shell mass per day. The observed rate of gross dissolution was different from that predicted by rate law kinetics of aragonite dissolution, in being higher at Var levels slightly above 1 and lower at Omega_Ar levels of between 1 and 0.8. This indicates that shell mass is affected by even transitional levels of saturation, but there is, nevertheless, some partial means of protection for shells when in undersaturated conditions. A function for gross dissolution against Var derived from the present observations was compared to a function for gross calcification derived by a different study, and showed that dissolution became the dominating process even at Omega_Ar levels close to 1, with net shell growth ceasing at an Omega_Ar of 1.03. Gross dissolution increasingly dominated net change in shell mass as saturation levels decreased below 1. As well as influencing their viability, such dissolution of pteropod shells in the surface layers will result in slower sinking velocities and decreased carbon and carbonate fluxes to the deep ocean

Monotonicity of Fitness Landscapes and Mutation Rate Control

A common view in evolutionary biology is that mutation rates are minimised. However, studies in combinatorial optimisation and search have shown a clear advantage of using variable mutation rates as a control parameter to optimise the performance of evolutionary algorithms. Much biological theory in this area is based on Ronald Fisher's work, who used Euclidean geometry to study the relation between mutation size and expected fitness of the offspring in infinite phenotypic spaces. Here we reconsider this theory based on the alternative geometry of discrete and finite spaces of DNA sequences. First, we consider the geometric case of fitness being isomorphic to distance from an optimum, and show how problems of optimal mutation rate control can be solved exactly or approximately depending on additional constraints of the problem. Then we consider the general case of fitness communicating only partial information about the distance. We define weak monotonicity of fitness landscapes and prove that this property holds in all landscapes that are continuous and open at the optimum. This theoretical result motivates our hypothesis that optimal mutation rate functions in such landscapes will increase when fitness decreases in some neighbourhood of an optimum, resembling the control functions derived in the geometric case. We test this hypothesis experimentally by analysing approximately optimal mutation rate control functions in 115 complete landscapes of binding scores between DNA sequences and transcription factors. Our findings support the hypothesis and find that the increase of mutation rate is more rapid in landscapes that are less monotonic (more rugged). We discuss the relevance of these findings to living organisms

The impact of ocean acidification on the functional morphology of foraminifera

This work was supported by the NERC UK Ocean Acidification Research Programme grant NE/H017445/1. WENA acknowledges NERC support (NE/G018502/1). DMP received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland). MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions.Culturing experiments were performed on sediment samples from the Ythan Estuary, N. E. Scotland, to assess the impacts of ocean acidification on test surface ornamentation in the benthic foraminifer Haynesina germanica. Specimens were cultured for 36 weeks at either 380, 750 or 1000 ppm atmospheric CO2. Analysis of the test surface using SEM imaging reveals sensitivity of functionally important ornamentation associated with feeding to changing seawater CO2 levels. Specimens incubated at high CO2 levels displayed evidence of shell dissolution, a significant reduction and deformation of ornamentation. It is clear that these calcifying organisms are likely to be vulnerable to ocean acidification. A reduction in functionally important ornamentation could lead to a reduction in feeding efficiency with consequent impacts on this organism’s survival and fitness.Publisher PDFPeer reviewe

Extensive dissolution of live pteropods in the Southern Ocean

The carbonate chemistry of the surface ocean is rapidly changing with ocean acidification, a result of human activities. In the upper layers of the Southern Ocean, aragonite—a metastable form of calcium carbonate with rapid dissolution kinetics—may become undersaturated by 2050 (ref. 2). Aragonite undersaturation is likely to affect aragonite-shelled organisms, which can dominate surface water communities in polar regions. Here we present analyses of specimens of the pteropod Limacina helicina antarctica that were extracted live from the Southern Ocean early in 2008. We sampled from the top 200m of the water column, where aragonite saturation levels were around 1, as upwelled deep water is mixed with surface water containing anthropogenic CO2. Comparing the shell structure with samples from aragonite-supersaturated regions elsewhere under a scanning electron microscope, we found severe levels of shell dissolution in the undersaturated region alone. According to laboratory incubations of intact samples with a range of aragonite saturation levels, eight days of incubation in aragonite saturation levels of 0.94– 1.12 produces equivalent levels of dissolution. As deep-water upwelling and CO2 absorption by surface waters is likely to increase as a result of human activities2,4, we conclude that upper ocean regions where aragonite-shelled organisms are affected by dissolution are likely to expand

Exposure of mediterranean countries to ocean acidification

This study examines the potential effects of ocean acidification on countries and fisheries of the Mediterranean Sea. The implications for seafood security and supply are evaluated by examining the sensitivity of the Mediterranean to ocean acidification at chemical, biological, and macro-economic levels. The limited information available on impacts of ocean acidification on harvested (industrial, recreational, and artisanal fishing) and cultured species (aquaculture) prevents any biological impact assessment. However, it appears that non-developed nations around the Mediterranean, particularly those for which fisheries are increasing, yet rely heavily on artisanal fleets, are most greatly exposed to socioeconomic consequences from ocean acidification. © 2014 by the authors; licensee MDPI, Basel, Switzerland

Microbial laboratory evolution in the era of genome-scale science

Advances in DNA sequencing, high-throughput technologies, and genetic manipulation systems have enabled empirical studies of the molecular and genomic bases of adaptive evolution. This review discusses key insights learned from direct observation of the evolution process

Retrograde semaphorin-plexin signalling drives homeostatic synaptic plasticity.

Homeostatic signalling systems ensure stable but flexible neural activity and animal behaviour. Presynaptic homeostatic plasticity is a conserved form of neuronal homeostatic signalling that is observed in organisms ranging from Drosophila to human. Defining the underlying molecular mechanisms of neuronal homeostatic signalling will be essential in order to establish clear connections to the causes and progression of neurological disease. During neural development, semaphorin-plexin signalling instructs axon guidance and neuronal morphogenesis. However, semaphorins and plexins are also expressed in the adult brain. Here we show that semaphorin 2b (Sema2b) is a target-derived signal that acts upon presynaptic plexin B (PlexB) receptors to mediate the retrograde, homeostatic control of presynaptic neurotransmitter release at the neuromuscular junction in Drosophila. Further, we show that Sema2b-PlexB signalling regulates presynaptic homeostatic plasticity through the cytoplasmic protein Mical and the oxoreductase-dependent control of presynaptic actin. We propose that semaphorin-plexin signalling is an essential platform for the stabilization of synaptic transmission throughout the developing and mature nervous system. These findings may be relevant to the aetiology and treatment of diverse neurological and psychiatric diseases that are characterized by altered or inappropriate neural function and behaviour

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events