Passive Optical Sample Assembly (POSA)

A Passive Optical Sample Assembly (POSA) unit was mounted and flown in the cargo bay of the space shuttle Columbia during the first Orbital Flight Test (OFT-1). A similar unit was mounted in a different location in the cargo bay during the postflight operations. The samples in both POSA arrays were subjected to a series of optical and analytical measurements prior to delivery for installation in the cargo bay and after retrieval of the flight hardware. The final results of a comparison of the two series of measurements are presented. These STS-1 results are based on data obtained from only a portion of one of the ten Induced Environment Contamination Monitor instruments to be flown on several shuttle flights beginning with STS-2. These limited results do not indicate shuttle contamination levels in excess of those anticipated

Operations summary for the convection and moisture experiment (CAMEX)

During the fall of 1993, NASA sponsored a field program called the Convection and Moisture Experiment (CAMEX) at Wallops Island, Virginia. CAMEX was a multidisciplinary experiment design to measure the three dimensional moisture fields over Wallops Island and to characterize the multifrequency radiometric signature of tropical convection over the Gulf Stream and southeastern Atlantic Ocean. This document summarizes the daily CAMEX activities, including ground and aircraft (NASA ER-2) operations, and includes 'quick-look' summaries of data acquisition along with data examples provided by the various CAMEX PI's

Protein co-evolution, co-adaptation and interactions

Co-evolution has an important function in the evolution of species and it is clearly manifested in certain scenarios such as host–parasite and predator–prey interactions, symbiosis and mutualism. The extrapolation of the concepts and methodologies developed for the study of species co-evolution at the molecular level has prompted the development of a variety of computational methods able to predict protein interactions through the characteristics of co-evolution. Particularly successful have been those methods that predict interactions at the genomic level based on the detection of pairs of protein families with similar evolutionary histories (similarity of phylogenetic trees: mirrortree). Future advances in this field will require a better understanding of the molecular basis of the co-evolution of protein families. Thus, it will be important to decipher the molecular mechanisms underlying the similarity observed in phylogenetic trees of interacting proteins, distinguishing direct specific molecular interactions from other general functional constraints. In particular, it will be important to separate the effects of physical interactions within protein complexes (‘co-adaptation') from other forces that, in a less specific way, can also create general patterns of co-evolution

Cellular costs underpin micronutrient limitation in phytoplankton

Micronutrients control phytoplankton growth in the ocean, influencing carbon export and fisheries. It is currently unclear how micronutrient scarcity affects cellular processes and how interdependence across micronutrients arises. We show that proximate causes of micronutrient growth limitation and interdependence are governed by cumulative cellular costs of acquiring and using micronutrients. Using a mechanistic proteomic allocation model of a polar diatom focused on iron and manganese, we demonstrate how cellular processes fundamentally underpin micronutrient limitation, and how they interact and compensate for each other to shape cellular elemental stoichiometry and resource interdependence. We coupled our model with metaproteomic and environmental data, yielding an approach for estimating biogeochemical metrics, including taxon-specific growth rates. Our results show that cumulative cellular costs govern how environmental conditions modify phytoplankton growth

GO4genome: A Prokaryotic Phylogeny Based on Genome Organization

Determining the phylogeny of closely related prokaryotes may fail in an analysis of rRNA or a small set of sequences. Whole-genome phylogeny utilizes the maximally available sample space. For a precise determination of genome similarity, two aspects have to be considered when developing an algorithm of whole-genome phylogeny: (1) gene order conservation is a more precise signal than gene content; and (2) when using sequence similarity, failures in identifying orthologues or the in situ replacement of genes via horizontal gene transfer may give misleading results. GO4genome is a new paradigm, which is based on a detailed analysis of gene function and the location of the respective genes. For characterization of genes, the algorithm uses gene ontology enabling a comparison of function independent of evolutionary relationship. After the identification of locally optimal series of gene functions, their length distribution is utilized to compute a phylogenetic distance. The outcome is a classification of genomes based on metabolic capabilities and their organization. Thus, the impact of effects on genome organization that are not covered by methods of molecular phylogeny can be studied. Genomes of strains belonging to Escherichia coli, Shigella, Streptococcus, Methanosarcina, and Yersinia were analyzed. Differences from the findings of classical methods are discussed

Heritability of seed weight in Maritime pine, a relevant trait in the transmission of environmental maternal effects

Quantitative seed provisioning is an important life-history trait with strong effects on offspring phenotype and fitness. As for any other trait, heritability estimates are vital for understanding its evolutionary dynamics. However, being a trait in between two generations, estimating additive genetic variation of seed provisioning requires complex quantitative genetic approaches for distinguishing between true genetic and environmental maternal effects. Here, using Maritime pine as a long-lived plant model, we quantified additive genetic variation of cone and seed weight (SW) mean and SW within-individual variation. We used a powerful approach combining both half-sib analysis and parent-offspring regression using several common garden tests established in contrasting environments to separate G, E and G x E effects. Both cone weight and SW mean showed significant genetic variation but were also influenced by the maternal environment. Most of the large variation in SW mean was attributable to additive genetic effects (h(2) = 0.55-0.74). SW showed no apparent G x E interaction, particularly when accounting for cone weight covariation, suggesting that the maternal genotypes actively control the SW mean irrespective of the amount of resources allocated to cones. Within-individual variation in SW was low (12%) relative to between-individual variation (88%), and showed no genetic variation but was largely affected by the maternal environment, with greater variation in the less favourable sites for pine growth. In summary, results were very consistent between the parental and the offspring common garden tests, and clearly indicated heritable genetic variation for SW mean but not for within-individual variation in SW.This study was financed by the Spanish National Research Grants RTA2007-100 and AGL2012-40151 (FENOPIN), both co-financed by EU-FEDER. The progeny trials and the clonal seed orchards are part of the experimental set up of the Maritime pine breeding programme developed by the Centro de Investigacion Forestal de Lourizan, Xunta de Galicia.Spanish National Research Grant RTA2007-100Spanish National Research Grant AGL2012-40151 (FENOPIN)EU-FEDERPeer reviewe

Phylogenomic Analysis of Marine Roseobacters

Background: Members of the Roseobacter clade which play a key role in the biogeochemical cycles of the ocean are diverse and abundant, comprising 10–25 % of the bacterioplankton in most marine surface waters. The rapid accumulation of whole-genome sequence data for the Roseobacter clade allows us to obtain a clearer picture of its evolution. Methodology/Principal Findings: In this study about 1,200 likely orthologous protein families were identified from 17 Roseobacter bacteria genomes. Functional annotations for these genes are provided by iProClass. Phylogenetic trees were constructed for each gene using maximum likelihood (ML) and neighbor joining (NJ). Putative organismal phylogenetic trees were built with phylogenomic methods. These trees were compared and analyzed using principal coordinates analysis (PCoA), approximately unbiased (AU) and Shimodaira–Hasegawa (SH) tests. A core set of 694 genes with vertical descent signal that are resistant to horizontal gene transfer (HGT) is used to reconstruct a robust organismal phylogeny. In addition, we also discovered the most likely 109 HGT genes. The core set contains genes that encode ribosomal apparatus, ABC transporters and chaperones often found in the environmental metagenomic and metatranscriptomic data. These genes in the core set are spread out uniformly among the various functional classes and biological processes. Conclusions/Significance: Here we report a new multigene-derived phylogenetic tree of the Roseobacter clade. Of particular interest is the HGT of eleven genes involved in vitamin B12 synthesis as well as key enzynmes fo

Transcriptome of Aphanomyces euteiches: New Oomycete Putative Pathogenicity Factors and Metabolic Pathways

Aphanomyces euteiches is an oomycete pathogen that causes seedling blight and root rot of legumes, such as alfalfa and pea. The genus Aphanomyces is phylogenically distinct from well-studied oomycetes such as Phytophthora sp., and contains species pathogenic on plants and aquatic animals. To provide the first foray into gene diversity of A. euteiches, two cDNA libraries were constructed using mRNA extracted from mycelium grown in an artificial liquid medium or in contact to plant roots. A unigene set of 7,977 sequences was obtained from 18,864 high-quality expressed sequenced tags (ESTs) and characterized for potential functions. Comparisons with oomycete proteomes revealed major differences between the gene content of A. euteiches and those of Phytophthora species, leading to the identification of biosynthetic pathways absent in Phytophthora, of new putative pathogenicity genes and of expansion of gene families encoding extracellular proteins, notably different classes of proteases. Among the genes specific of A. euteiches are members of a new family of extracellular proteins putatively involved in adhesion, containing up to four protein domains similar to fungal cellulose binding domains. Comparison of A. euteiches sequences with proteomes of fully sequenced eukaryotic pathogens, including fungi, apicomplexa and trypanosomatids, allowed the identification of A. euteiches genes with close orthologs in these microorganisms but absent in other oomycetes sequenced so far, notably transporters and non-ribosomal peptide synthetases, and suggests the presence of a defense mechanism against oxidative stress which was initially characterized in the pathogenic trypanosomatids

Long-Branch Attraction Bias and Inconsistency in Bayesian Phylogenetics

Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias—which is apparent under both controlled simulation conditions and in analyses of empirical sequence data—also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages—that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis

Largest recent impact craters on Mars: Orbital imaging and surface seismic co-investigation.

Two >130-meter-diameter impact craters formed on Mars during the later half of 2021. These are the two largest fresh impact craters discovered by the Mars Reconnaissance Orbiter since operations started 16 years ago. The impacts created two of the largest seismic events (magnitudes greater than 4) recorded by InSight during its 3-year mission. The combination of orbital imagery and seismic ground motion enables the investigation of subsurface and atmospheric energy partitioning of the impact process on a planet with a thin atmosphere and the first direct test of martian deep-interior seismic models with known event distances. The impact at 35°N excavated blocks of water ice, which is the lowest latitude at which ice has been directly observed on Mars