Polarimetry of Water Ice Particles Providing Insights on Grain Size and Degree of Sintering on Icy Planetary Surfaces

The polarimetry of the light scattered by planetary surfaces is a powerful tool to provide constraints on their microstructure. To improve the interpretation of polarimetric data from icy surfaces, we have developed the POLarimeter for ICE Samples (POLICES) complementing the measurement facilities of the Ice Laboratory at the University of Bern. The new setup uses a high precision Stokes polarimeter to measure the degree of polarization in the visible light scattered by surfaces at moderate phase angles (from 1.5 to 30{\deg}). We present the photometric and polarimetric phase curves measured on various surfaces made of pure water ice particles having well-controlled size and shape (spherical, crushed, frost). The results show how the amplitude and the shape of the negative polarization branch change with the particles sizes and the degree of metamorphism of the ice. We found that fresh frost formed by water condensation on cold surfaces has a phase curve characterized by resonances (Mie oscillations) indicating that frost embryos are transparent micrometer-sized particles with a narrow size distribution and spherical shape. Comparisons of these measurements with polarimetric observations of the icy satellites of the Solar System suggest that Europa is possibly covered by relatively coarser (~40-400 {\mu}m) and more sintered grains than Enceladus and Rhea, more likely covered by frost-like particles of few micrometers in average. The great sensitivity of polarization to grain size and degree of sintering makes it an ideal tool to detect hints of ongoing processes on icy planetary surfaces, such as cryovolcanism.Comment: 36 pages, 1 table, 11 figures, 2 data sets, accepted in Journal of Geophysical Research: Planet

M-ORBIS: Mapping of mOleculaR Binding sItes and Surfaces

M-ORBIS is a Molecular Cartography approach that performs integrative high-throughput analysis of structural data to localize all types of binding sites and associated partners by homology and to characterize their properties and behaviors in a systemic way. The robustness of our binding site inferences was compared to four curated datasets corresponding to protein heterodimers and homodimers and protein–DNA/RNA assemblies. The Molecular Cartographies of structurally well-detailed proteins shows that 44% of their surfaces interact with non-solvent partners. Residue contact frequencies with water suggest that ∼86% of their surfaces are transiently solvated, whereas only 15% are specifically solvated. Our analysis also reveals the existence of two major binding site families: specific binding sites which can only bind one type of molecule (protein, DNA, RNA, etc.) and polyvalent binding sites that can bind several distinct types of molecule. Specific homodimer binding sites are for instance nearly twice as hydrophobic than previously described and more closely resemble the protein core, while polyvalent binding sites able to form homo and heterodimers more closely resemble the surfaces involved in crystal packing. Similarly, the regions able to bind DNA and to alternatively form homodimers, are more hydrophobic and less polar than previously described DNA binding sites

Laboratory Experiments to Understand Comets

In order to understand the origin and evolution of comets, one must decipher the processes that formed and processed cometary ice and dust. Cometary materials have diverse physical and chemical properties and are mixed in various ways. Laboratory experiments are capable of producing simple to complex analogues of comet-like materials, measuring their properties, and simulating the processes by which their compositions and structures may evolve. The results of laboratory experiments are essential for the interpretations of comet observations and complement theoretical models. They are also necessary for planning future missions to comets. This chapter presents an overview of past and ongoing laboratory experiments exploring how comets were formed and transformed, from the nucleus interior and surface, to the coma. Throughout these sections, the pending questions are highlighted, and the perspectives and prospects for future experiments are discussed.Comment: 36 pages, 13 figures, Chapter accepted for publication on February 24th 2023, now in press for the book Comets III, edited by K. Meech, M. Combi, D. Bockelee-Morvan, S. Raymond and M. Zolensky, University of Arizona Pres

Comparison of eukaryotic phylogenetic profiling approaches using species tree aware methods

<p>Abstract</p> <p>Background</p> <p>Phylogenetic profiling encompasses an important set of methodologies for <it>in silico </it>high throughput inference of functional relationships between genes. The simplest profiles represent the distribution of gene presence-absence in a set of species as a sequence of 0's and 1's, and it is assumed that functionally related genes will have more similar profiles. The methodology has been successfully used in numerous studies of prokaryotic genomes, although its application in eukaryotes appears problematic, with reported low accuracy due to the complex genomic organization within this domain of life. Recently some groups have proposed an alternative approach based on the correlation of homologous gene group sizes, taking into account all potentially informative genetic events leading to a change in group size, regardless of whether they result in a <it>de novo </it>group gain or total gene group loss.</p> <p>Results</p> <p>We have compared the performance of classical presence-absence and group size based approaches using a large, diverse set of eukaryotic species. In contrast to most previous comparisons in Eukarya, we take into account the species phylogeny. We also compare the approaches using two different group categories, based on orthology and on domain-sharing. Our results confirm a limited overall performance of phylogenetic profiling in eukaryotes. Although group size based approaches initially showed an increase in performance for the domain-sharing based groups, this seems to be an overestimation due to a simplistic negative control dataset and the choice of null hypothesis rejection criteria.</p> <p>Conclusion</p> <p>Presence-absence profiling represents a more accurate classifier of related versus non-related profile pairs, when the profiles under consideration have enough information content. Group size based approaches provide a complementary means of detecting domain or family level co-evolution between groups that may be elusive to presence-absence profiling. Moreover positive correlation between co-evolution scores and functional links imply that these methods could be used to estimate functional distances between gene groups and to cluster them based on their functional relatedness. This study should have important implications for the future development and application of phylogenetic profiling methods, not only in eukaryotic, but also in prokaryotic datasets.</p

OrthoInspector: comprehensive orthology analysis and visual exploration

<p>Abstract</p> <p>Background</p> <p>The accurate determination of orthology and inparalogy relationships is essential for comparative sequence analysis, functional gene annotation and evolutionary studies. Various methods have been developed based on either simple blast all-versus-all pairwise comparisons and/or time-consuming phylogenetic tree analyses.</p> <p>Results</p> <p>We have developed OrthoInspector, a new software system incorporating an original algorithm for the rapid detection of orthology and inparalogy relations between different species. In comparisons with existing methods, OrthoInspector improves detection sensitivity, with a minimal loss of specificity. In addition, several visualization tools have been developed to facilitate in-depth studies based on these predictions. The software has been used to study the orthology/in-paralogy relationships for a large set of 940,855 protein sequences from 59 different eukaryotic species.</p> <p>Conclusion</p> <p>OrthoInspector is a new software system for orthology/paralogy analysis. It is made available as an independent software suite that can be downloaded and installed for local use. Command line querying facilitates the integration of the software in high throughput processing pipelines and a graphical interface provides easy, intuitive access to results for the non-expert.</p

Strategies for Reliable Exploitation of Evolutionary Concepts in High Throughput Biology

The recent availability of the complete genome sequences of a large number of model organisms, together with the immense amount of data being produced by the new high-throughput technologies, means that we can now begin comparative analyses to understand the mechanisms involved in the evolution of the genome and their consequences in the study of biological systems. Phylogenetic approaches provide a unique conceptual framework for performing comparative analyses of all this data, for propagating information between different systems and for predicting or inferring new knowledge. As a result, phylogeny-based inference systems are now playing an increasingly important role in most areas of high throughput genomics, including studies of promoters (phylogenetic footprinting), interactomes (based on the presence and degree of conservation of interacting proteins), and in comparisons of transcriptomes or proteomes (phylogenetic proximity and co-regulation/co-expression). Here we review the recent developments aimed at making automatic, reliable phylogeny-based inference feasible in large-scale projects. We also discuss how evolutionary concepts and phylogeny-based inference strategies are now being exploited in order to understand the evolution and function of biological systems. Such advances will be fundamental for the success of the emerging disciplines of systems biology and synthetic biology, and will have wide-reaching effects in applied fields such as biotechnology, medicine and pharmacology

SAGETTARIUS: a program to reduce the number of tags mapped to multiple transcripts and to plan SAGE sequencing stages

SAGE (Serial Analysis of Gene Expression) experiments generate short nucleotide sequences called ‘tags’ which are assumed to map unambiguously to their original transcripts (1 tag to 1 transcript mapping). Nevertheless, many tags are generated that do not map to any transcript or map to multiple transcripts. Current bioinformatics resources, such as SAGEmap and TAGmapper, have focused on reducing the number of unmapped tags. Here, we describe SAGETTARIUS, a new high-throughput program that performs successive precise Nla3 and Sau3A tag to transcript mapping, based on specifically designed Virtual Tag (VT) libraries. First, SAGETTARIUS decreases the number of tags mapped to multiple transcripts. Among the various mapping resources compared, SAGETTARIUS performed the best in this respect by decreasing up to 11% the number of multiply mapped tags. Second, SAGETTARIUS allows the establishment of a guideline for SAGE experiment sequencing efforts through efficient mapping of the CRT (Cytoplasmic Ribosomal protein Transcripts)-specific tags. Using all publicly available human and mouse Nla3 SAGE experiments, we show that sequencing 100 000 tags is sufficient to map almost all CRT-specific tags and that four sequencing stages can be identified when carrying out a human or mouse SAGE project. SAGETTARIUS is web interfaced and freely accessible to academic users

AlexSys: a knowledge-based expert system for multiple sequence alignment construction and analysis

Multiple sequence alignment (MSA) is a cornerstone of modern molecular biology and represents a unique means of investigating the patterns of conservation and diversity in complex biological systems. Many different algorithms have been developed to construct MSAs, but previous studies have shown that no single aligner consistently outperforms the rest. This has led to the development of a number of ‘meta-methods’ that systematically run several aligners and merge the output into one single solution. Although these methods generally produce more accurate alignments, they are inefficient because all the aligners need to be run first and the choice of the best solution is made a posteriori. Here, we describe the development of a new expert system, AlexSys, for the multiple alignment of protein sequences. AlexSys incorporates an intelligent inference engine to automatically select an appropriate aligner a priori, depending only on the nature of the input sequences. The inference engine was trained on a large set of reference multiple alignments, using a novel machine learning approach. Applying AlexSys to a test set of 178 alignments, we show that the expert system represents a good compromise between alignment quality and running time, making it suitable for high throughput projects. AlexSys is freely available from http://alnitak.u-strasbg.fr/∼aniba/alexsys

Controversies in modern evolutionary biology: the imperative for error detection and quality control

<p>Abstract</p> <p>Background</p> <p>The data from high throughput genomics technologies provide unique opportunities for studies of complex biological systems, but also pose many new challenges. The shift to the genome scale in evolutionary biology, for example, has led to many interesting, but often controversial studies. It has been suggested that part of the conflict may be due to errors in the initial sequences. Most gene sequences are predicted by bioinformatics programs and a number of quality issues have been raised, concerning DNA sequencing errors or badly predicted coding regions, particularly in eukaryotes.</p> <p>Results</p> <p>We investigated the impact of these errors on evolutionary studies and specifically on the identification of important genetic events. We focused on the detection of asymmetric evolution after duplication, which has been the subject of controversy recently. Using the human genome as a reference, we established a reliable set of 688 duplicated genes in 13 complete vertebrate genomes, where significantly different evolutionary rates are observed. We estimated the rates at which protein sequence errors occur and are accumulated in the higher-level analyses. We showed that the majority of the detected events (57%) are in fact artifacts due to the putative erroneous sequences and that these artifacts are sufficient to mask the true functional significance of the events.</p> <p>Conclusions</p> <p>Initial errors are accumulated throughout the evolutionary analysis, generating artificially high rates of event predictions and leading to substantial uncertainty in the conclusions. This study emphasizes the urgent need for error detection and quality control strategies in order to efficiently extract knowledge from the new genome data.</p