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Alzheimer’s disease is a neurodegenerative disease characterized by the impairment of cognitive function and loss of memory, affecting millions of individuals worldwide. With the dramatic increase in the prevalence of Alzheimer’s disease, it is expected to impose extensive public health and economic burden. However, this burden is particularly heavy on the caregivers of Alzheimer’s disease patients eliciting neuropsychiatric symptoms that include mood swings, hallucinations, and depression. Interestingly, these neuropsychiatric symptoms are shared across symptoms of bipolar disorder, schizophrenia, and major depression disorder. Despite the similarities in symptomatology, comorbidities of Alzheimer’s disease and these neuropsychiatric disorders have not been studied in the Alzheimer’s disease model. Here, we explore the comprehensive changes in gene expression of genes that are associated with bipolar disorder, schizophrenia, and major depression disorder through the microarray of an Alzheimer’s disease animal model, the forebrain specific PSEN double knockout mouse. To analyze the genes related with these three neuropsychiatric disorders within the scope of our microarray data, we used selected 1207 of a total of 45,037 genes that satisfied our selection criteria. These genes were selected on the basis of 14 Gene Ontology terms significantly relevant with the three disorders which were identified by previous research conducted by the Psychiatric Genomics Consortium. Our study revealed that the forebrain specific deletion of Alzheimer’s disease genes can significantly alter neuropsychiatric disorder associated genes. Most importantly, most of these significantly altered genes were found to be involved with schizophrenia. Taken together, we suggest that the synaptic dysfunction by mutation of Alzheimer’s disease genes can lead to the manifestation of not only memory loss and impairments in cognition, but also neuropsychiatric symptoms.

Deep-sea hydrothermal vents may provide one of the largest reservoirs on Earth for hydrogen-oxidizing microorganisms. Depending on the type of geological setting, hydrothermal environments can be considerably enriched in hydrogen (up to millimolar concentrations). As hot, reduced hydrothermal fluids ascend to the seafloor they mix with entrained cold, oxygenated seawater, forming thermal and chemical gradients along their fluid pathways. Consequently, in these thermally and chemically dynamic habitats biochemically distinct hydrogenases (adapted to various temperature regimes, oxygen and hydrogen concentrations) from physiologically and phylogenetically diverse Bacteria and Archaea can be expected. Hydrogen oxidation is one of the important inorganic energy sources in these habitats, capable of providing relatively large amounts of energy (237 kJ/mol H-2) for driving ATP synthesis and autotrophic CO2 fixation. Therefore, hydrogen-oxidizing organisms play a key role in deep-sea hydrothermal vent ecosystems as they can be considerably involved in light-independent primary biomass production. So far, the specific role of hydrogen-utilizing microorganisms in deep-sea hydrothermal ecosystems has been investigated by isolating hydrogen-oxidizers, measuring hydrogen consumption (ex situ), studying hydrogenase gene distribution and more recently by analyzing metatranscriptomic and metaproteomic data. Here we summarize this available knowledge and discuss the advent of new techniques for the identification of novel hydrogen-uptake and - evolving enzymes from hydrothermal vent microorganisms.

eLife digest Many animals show automatic responses to light, from moths, which are attracted to light sources, to cockroaches, which are repelled by them. This phenomenon, known as phototaxis, is thought to help animals navigate through their environment. It is an evolutionarily ancient behavior, as revealed by its widespread presence in the animal kingdom. One animal with a simple visual system for phototactic behavior is the marine worm Platynereis dumerilii. Platynereis is a segmented worm (annelid) with four eyes on the top of its head, two on the right and two on the left. Exposure to light triggers the contraction of muscles that run along the length of the body, causing the worm to bend and thus change the direction it is swimming in. Now, using a combination of high-resolution microscopy and behavioral experiments in larvae, Randel et al. have mapped the neural circuits underlying the worm's phototactic behavior. A 3-day-old Platynereis larva was sectioned to produce almost 1700 slices, each less than 50 nanometers thick, which were then viewed under a transmission electron microscope. By tracing individual neurons from one slice to the next, it was possible to reconstruct the entire visual system and all of its connections. This ‘visual connectome’ consisted of 71 neurons—21 light-sensitive cells, 42 interneurons, and 8 muscle-controlling motorneurons—organized into a circuit with 1106 connections. Shining light onto living larvae triggered phototaxis, with some larvae consistently swimming towards the light and others away from it. Using a laser to destroy all four eyes abolished this behavior, as did the removal of both eyes on either side of the head. By contrast, removing one eye from each side had no effect. This was because these larvae were still able to simultaneously compare the amounts of light reaching the left and right sides of their body, and to use any difference in these levels as a directional cue to guide swimming. By revealing the circuitry underlying phototaxis in a marine worm, Randel et al. have provided clues to the mechanisms that support this behavior in other species. The data could also provide insights into the processes that contributed to the evolution of more complex visual systems. DOI: http://dx.doi.org/10.7554/eLife.02730.002 Animals use spatial differences in environmental light levels for visual navigation; however, how light inputs are translated into coordinated motor outputs remains poorly understood. Here we reconstruct the neuronal connectome of a four-eye visual circuit in the larva of the annelid Platynereis using serial-section transmission electron microscopy. In this 71-neuron circuit, photoreceptors connect via three layers of interneurons to motorneurons, which innervate trunk muscles. By combining eye ablations with behavioral experiments, we show that the circuit compares light on either side of the body and stimulates body bending upon left-right light imbalance during visual phototaxis. We also identified an interneuron motif that enhances sensitivity to different light intensity contrasts. The Platynereis eye circuit has the hallmarks of a visual system, including spatial light detection and contrast modulation, illustrating how image-forming eyes may have evolved via intermediate stages contrasting only a light and a dark field during a simple visual task. DOI: http://dx.doi.org/10.7554/eLife.02730.001

Stalactites (CaCO3 and salt) from water seeps are frequently encountered in ceilings of mine tunnels whenever they intersect water-bearing faults or fractures. To determine whether stalactites could be mineralized traps for indigenous fracture water microorganisms, we analyzed stalactites collected from three different mines ranging in depth from 1.3 to 3.1 km. During sampling in Beatrix gold mine (1.4 km beneath the surface), central South Africa, CaCO3 stalactites growing on the mine tunnel ceiling were collected and observed, in two cases, to contain a living obligate brackish water/marine nematode species, Monhystrella parvella. After sterilization of the outer surface, mineral layers were physically removed from the outside to the interior, and DNA extracted. Based upon 16S and 18S rRNA gene sequencing, Archaea, Bacteria, and Eukarya in different combinations were detected for each layer. Using CT scan and electron microscopy the inner structure of CaCO3 and salt stalactites were analyzed. CaCO3 stalactites show a complex pattern of lamellae carrying bacterially precipitated mineral structures. Nematoda were clearly identified between these layers confirming that bacteria and nematodes live inside the stalactites and not only in the central straw. Salt stalactites exhibit a more uniform internal structure. Surprisingly, several Bacteria showing highest sequence identities to marine species were identified. This, together with the observation that the nematode M. parvella recovered from Beatrix gold mine stalactite can only survive in a salty environment makes the origin of the deep subsurface colonization enigmatic. The possibility of a Permian origin of fracture fluids is discussed. Our results indicate stalactites are suitable for biodiversity recovery and act as natural traps for microorganisms in the fissure water long after the water that formed the stalactite stopped flowing.

Bacteria of the Vibrio genus are the most predominant infectious agents threatening marine wildlife and aquaculture. Due to the large genetic diversity of these pathogens, the molecular determinants of Vibrio virulence are only poorly understood. Furthermore, studies tend to ignore co-evolutionary interactions between different host populations and their locally encountered Vibrio communities. Here, we explore the molecular targets of such co-evolutionary interactions by analyzing the genomes of nine Vibrio strains from the Splendidus-clade showing opposite virulence patterns towards two populations of Pacific oysters introduced into European Wadden Sea. By contrasting Vibrio phylogeny to their host specific virulence patterns, we could identify two core genome genes (OG1907 and OG 3159) that determine the genotype by genotype (G × G) interactions between oyster larvae and their sympatric Vibrio communities. Both genes show positive selection between locations targeting only few amino acid positions. Deletion of each gene led to a loss of the host specific virulence patterns while complementation with OG3159 alleles from both locations could recreate the wild type phenotypes matching the origin of the allele. This indicates that both genes can act as a genetic switch for Vibrio-oyster coevolution demonstrating that local adaptation in distinct Vibrio lineages can rely on only few genes independent of larger pathogenicity islands or plasmids. International audience

Exploring the genomic architecture of species and populations divergence aids understanding how lineages evolve and adapt, and ultimately can show the repeatability of evolutionary processes. Yet, the genomic signatures associated with divergence are still relatively unexplored, leading to a knowledge gap on whether species divergence ultimately differs in its genetic architecture from divergence at other spatial scales (i.e., populations, ecotypes). Our goal in this research was to determine whether genomic islands of speciation are more prone to harbor within-species differentiation due to genomic features, suppressed recombination, smaller effective population size or increased drift, across repeated hierarchically nested levels of divergence. We used two species of Phaseolus beans with strong genepool and population sub-structure produced by multiple independent domestications each especially in Andean and Mesoamerican / Middle American geographies. We genotyped 22,531 GBS-derived SNP markers in 209 individuals of wild and cultivated Phaseolus vulgaris and Phaseolus lunatus. We identified six regions for species-associated divergence. Out of these divergence peaks, 21% were recovered in the four within-species between-genepool comparisons and in the five within-genepool wild-cultivated comparisons (some of the latter did retrieve genuine signatures of the well described multiple domestication syndromes). However, genomic regions with overall high relative differentiation (measured by FST) coincided with regions of low SNP density and regions of elevated delta divergence between-genepools (ΔDiv), independent of the scale of divergence. The divergence in chromosome Pv10 further coincided with a between-species pericentric inversion. These convergences suggest that shared variants are being recurrently fixed at replicated regions of the genome, and in a similar manner across different hierarchically nested levels of divergence, likely as result of genomic features that make certain regions more prone to accumulate islands of speciation and within-species divergence. In summary, neighboring signatures of speciation, adaptation and domestication in Phaseolus beans are influenced by ubiquitous genomic constrains, which may continue to fortuitously shape genomic differentiation at various others scales of divergence.

eLife digest DNA is often referred to as the ‘blueprint of life’, as this molecule contains the instructions that are required to build a living organism from a single cell. But these instructions largely play out through the proteins that DNA encodes; and most proteins do not work alone. Instead they come together in different combinations, or complexes, and a single protein may participate in many complexes with different activities. Proteins are so small that it is difficult to get clear information about what they look like. Visualizing protein complexes is even harder. Most protein–protein interactions remain poorly understood, even in the best-studied organisms such as humans, yeast, and bacteria. Proteins are made from smaller molecules, called amino acids, strung together one after the other. The order in which different amino acids are arranged in a protein determines the protein’s shape and ultimately its function. Like DNA, protein sequences can change over time. Sometimes, the sequence of one protein changes in a way that prevents it binding to another protein. If these two proteins must work together for an organism to survive, the second protein will often develop a compensating change that allows the protein–protein complex to reform. Identifying pairs of changes in the sequences of pairs of proteins suggests that the two proteins interact and gives some information about how the proteins fit together. Different species can have copies of the same proteins that have slightly different sequences. Since the DNA sequences from many different organisms are already known, there are now many opportunities to find sites in pairs of proteins that have evolved together, or co-evolved, over time. To find sites that seem to have co-evolved, Hopf et al. used a computer program based on an approach from statistical physics to look at pairs of proteins that were already known to form complexes. Co-evolving sites were found in over 300 pairs of proteins; including 76 where the structure of the complex was already known. When sites that were predicted to be co-evolving were then mapped to these known complex structures, the co-evolving sites were remarkably close to the true protein–protein contacts. This indicates that the information from the co-evolved sequences is sufficient to show how two proteins fit together. Hopf et al. then turned their attention to 82 pairs of proteins that were thought to interact, but where a structure was unavailable. For 32 of these pairs, structures of the entire complex could be predicted, showing how the two proteins might interact. Furthermore, when other researchers subsequently worked out the structure of one of these complexes, the prediction was a good match to the solved complex structure. The machinery of life is largely made up of proteins, which must interact in ever-changing but precise ways. The new methods developed by Hopf et al. provide a new way to discover and investigate the details of these interactions. DOI: http://dx.doi.org/10.7554/eLife.03430.002 Protein–protein interactions are fundamental to many biological processes. Experimental screens have identified tens of thousands of interactions, and structural biology has provided detailed functional insight for select 3D protein complexes. An alternative rich source of information about protein interactions is the evolutionary sequence record. Building on earlier work, we show that analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We evaluate prediction performance in blinded tests on 76 complexes of known 3D structure, predict protein–protein contacts in 32 complexes of unknown structure, and demonstrate how evolutionary couplings can be used to distinguish between interacting and non-interacting protein pairs in a large complex. With the current growth of sequences, we expect that the method can be generalized to genome-wide elucidation of protein–protein interaction networks and used for interaction predictions at residue resolution. DOI: http://dx.doi.org/10.7554/eLife.03430.001