Differences in lateral gene transfer in hypersaline versus thermal environments

<p>Abstract</p> <p>Background</p> <p>The role of lateral gene transfer (LGT) in the evolution of microorganisms is only beginning to be understood. While most LGT events occur between closely related individuals, inter-phylum and inter-domain LGT events are not uncommon. These distant transfer events offer potentially greater fitness advantages and it is for this reason that these "long distance" LGT events may have significantly impacted the evolution of microbes. One mechanism driving distant LGT events is microbial transformation. Theoretically, transformative events can occur between any two species provided that the DNA of one enters the habitat of the other. Two categories of microorganisms that are well-known for LGT are the thermophiles and halophiles.</p> <p>Results</p> <p>We identified potential inter-class LGT events into both a thermophilic class of Archaea (Thermoprotei) and a halophilic class of Archaea (Halobacteria). We then categorized these LGT genes as originating in thermophiles and halophiles respectively. While more than 68% of transfer events into Thermoprotei taxa originated in other thermophiles, less than 11% of transfer events into Halobacteria taxa originated in other halophiles.</p> <p>Conclusions</p> <p>Our results suggest that there is a fundamental difference between LGT in thermophiles and halophiles. We theorize that the difference lies in the different natures of the environments. While DNA degrades rapidly in thermal environments due to temperature-driven denaturization, hypersaline environments are adept at preserving DNA. Furthermore, most hypersaline environments, as topographical minima, are natural collectors of cellular debris. Thus halophiles would in theory be exposed to a greater diversity and quantity of extracellular DNA than thermophiles.</p

A fresh look at the evolution and diversification of photochemical reaction centers

In this review, I reexamine the origin and diversification of photochemical reaction centers based on the known phylogenetic relations of the core subunits, and with the aid of sequence and structural alignments. I show, for example, that the protein folds at the C-terminus of the D1 and D2 subunits of Photosystem II, which are essential for the coordination of the water-oxidizing complex, were already in place in the most ancestral Type II reaction center subunit. I then evaluate the evolution of reaction centers in the context of the rise and expansion of the different groups of bacteria based on recent large-scale phylogenetic analyses. I find that the Heliobacteriaceae family of Firmicutes appears to be the earliest branching of the known groups of phototrophic bacteria; however, the origin of photochemical reaction centers and chlorophyll synthesis cannot be placed in this group. Moreover, it becomes evident that the Acidobacteria and the Proteobacteria shared a more recent common phototrophic ancestor, and this is also likely for the Chloroflexi and the Cyanobacteria. Finally, I argue that the discrepancies among the phylogenies of the reaction center proteins, chlorophyll synthesis enzymes, and the species tree of bacteria are best explained if both types of photochemical reaction centers evolved before the diversification of the known phyla of phototrophic bacteria. The primordial phototrophic ancestor must have had both Type I and Type II reaction centers

Simplified mathematical model of proton exchange membrane fuel cell based on horizon fuel cell stack

This paper presents a simplified zero-dimensional mathematical model for a self-humidifying proton exchange membrane (PEM) fuel cell stack of 1 kW. The model incorporates major electric and thermodynamic variables and parameters involved in the operation of the PEM fuel cell under different operational conditions. Influence of each of these parameters and variables upon the operation and the performance of the PEM fuel cell are investigated. The mathematical equations are modeled by using Matlab–Simulink tools in order to simulate the operation of the developed model with a commercial available 1 kW horizon PEM fuel cell stack (H-1000), which is used for the purposes of model validation and tuning of the developed model. The model can be extrapolated to higher wattage fuel cells of similar arrangements. New equation is presented to determine the impact of using air to supply the PEM fuel cell instead of pure oxygen upon the concentration losses and the output voltage when useful current is drawn from it

Assessing Performance of Orthology Detection Strategies Applied to Eukaryotic Genomes

Orthology detection is critically important for accurate functional annotation, and has been widely used to facilitate studies on comparative and evolutionary genomics. Although various methods are now available, there has been no comprehensive analysis of performance, due to the lack of a genomic-scale ‘gold standard’ orthology dataset. Even in the absence of such datasets, the comparison of results from alternative methodologies contains useful information, as agreement enhances confidence and disagreement indicates possible errors. Latent Class Analysis (LCA) is a statistical technique that can exploit this information to reasonably infer sensitivities and specificities, and is applied here to evaluate the performance of various orthology detection methods on a eukaryotic dataset. Overall, we observe a trade-off between sensitivity and specificity in orthology detection, with BLAST-based methods characterized by high sensitivity, and tree-based methods by high specificity. Two algorithms exhibit the best overall balance, with both sensitivity and specificity>80%: INPARANOID identifies orthologs across two species while OrthoMCL clusters orthologs from multiple species. Among methods that permit clustering of ortholog groups spanning multiple genomes, the (automated) OrthoMCL algorithm exhibits better within-group consistency with respect to protein function and domain architecture than the (manually curated) KOG database, and the homolog clustering algorithm TribeMCL as well. By way of using LCA, we are also able to comprehensively assess similarities and statistical dependence between various strategies, and evaluate the effects of parameter settings on performance. In summary, we present a comprehensive evaluation of orthology detection on a divergent set of eukaryotic genomes, thus providing insights and guides for method selection, tuning and development for different applications. Many biological questions have been addressed by multiple tests yielding binary (yes/no) outcomes but no clear definition of truth, making LCA an attractive approach for computational biology

New Assembly, Reannotation and Analysis of the Entamoeba histolytica Genome Reveal New Genomic Features and Protein Content Information

Entamoeba histolytica is an anaerobic parasitic protozoan that causes amoebic dysentery. The parasites colonize the large intestine, but under some circumstances may invade the intestinal mucosa, enter the bloodstream and lead to the formation of abscesses such amoebic liver abscesses. The draft genome of E. histolytica, published in 2005, provided the scientific community with the first comprehensive view of the gene set for this parasite and important tools for elucidating the genetic basis of Entamoeba pathogenicity. Because complete genetic knowledge is critical for drug discovery and potential vaccine development for amoebiases, we have re-examined the original draft genome for E. histolytica. We have corrected the sequence assembly, improved the gene predictions and refreshed the functional gene assignments. As a result, this effort has led to a more accurate gene annotation, and the discovery of novel features, such as the presence of genome segmental duplications and the close association of some gene families with transposable elements. We believe that continuing efforts to improve genomic data will undoubtedly help to identify and characterize potential targets for amoebiasis control, as well as to contribute to a better understanding of genome evolution and pathogenesis for this parasite

Depicting the tree of life in museums: guiding principles from psychological research

The Tree of Life is revolutionizing our understanding of life on Earth, and, accordingly, evolutionary trees are increasingly important parts of exhibits on biodiversity and evolution. The authors argue that in using these trees to effectively communicate evolutionary principles, museums need to take into account research results from cognitive, developmental, and educational psychology while maintaining a focus on visitor engagement and enjoyment. Six guiding principles for depicting evolutionary trees in museum exhibits distilled from this research literature were used to evaluate five current or recent museum trees. One of the trees was then redesigned in light of the research while preserving the exhibit’s original learning goals. By attending both to traditional factors that influence museum exhibit design and to psychological research on how people understand diagrams in general and Tree of Life graphics in particular, museums can play a key role in fostering 21st century scientific literacy

Genomes of the Most Dangerous Epidemic Bacteria Have a Virulence Repertoire Characterized by Fewer Genes but More Toxin-Antitoxin Modules

We conducted a comparative genomic study based on a neutral approach to identify genome specificities associated with the virulence capacity of pathogenic bacteria. We also determined whether virulence is dictated by rules, or if it is the result of individual evolutionary histories. We systematically compared the genomes of the 12 most dangerous pandemic bacteria for humans ("bad bugs") to their closest non-epidemic related species ("controls").We found several significantly different features in the "bad bugs", one of which was a smaller genome that likely resulted from a degraded recombination and repair system. The 10 Cluster of Orthologous Group (COG) functional categories revealed a significantly smaller number of genes in the "bad bugs", which lacked mostly transcription, signal transduction mechanisms, cell motility, energy production and conversion, and metabolic and regulatory functions. A few genes were identified as virulence factors, including secretion system proteins. Five "bad bugs" showed a greater number of poly (A) tails compared to the controls, whereas an elevated number of poly (A) tails was found to be strongly correlated to a low GC% content. The "bad bugs" had fewer tandem repeat sequences compared to controls. Moreover, the results obtained from a principal component analysis (PCA) showed that the "bad bugs" had surprisingly more toxin-antitoxin modules than did the controls.We conclude that pathogenic capacity is not the result of "virulence factors" but is the outcome of a virulent gene repertoire resulting from reduced genome repertoires. Toxin-antitoxin systems could participate in the virulence repertoire, but they may have developed independently of selfish evolution

“Microbiota, symbiosis and individuality summer school” meeting report

How does microbiota research impact our understanding of biological individuality? We summarize the interdisciplinary summer school on “Microbiota, symbiosis and individuality: conceptual and philosophical issues” (July 2019), which was supported by a European Research Council starting grant project “Immunity, DEvelopment, and the Microbiota” (IDEM). The summer school centered around interdisciplinary group work on four facets of microbiota research: holobionts, individuality, causation, and human health. The conceptual discussion of cutting-edge empirical research provided new insights into microbiota and highlights the value of incorporating into meetings experts from other disciplines, such as philosophy and history of science

More Than 1,001 Problems with Protein Domain Databases: Transmembrane Regions, Signal Peptides and the Issue of Sequence Homology

Large-scale genome sequencing gained general importance for life science because functional annotation of otherwise experimentally uncharacterized sequences is made possible by the theory of biomolecular sequence homology. Historically, the paradigm of similarity of protein sequences implying common structure, function and ancestry was generalized based on studies of globular domains. Having the same fold imposes strict conditions over the packing in the hydrophobic core requiring similarity of hydrophobic patterns. The implications of sequence similarity among non-globular protein segments have not been studied to the same extent; nevertheless, homology considerations are silently extended for them. This appears especially detrimental in the case of transmembrane helices (TMs) and signal peptides (SPs) where sequence similarity is necessarily a consequence of physical requirements rather than common ancestry. Thus, matching of SPs/TMs creates the illusion of matching hydrophobic cores. Therefore, inclusion of SPs/TMs into domain models can give rise to wrong annotations. More than 1001 domains among the 10,340 models of Pfam release 23 and 18 domains of SMART version 6 (out of 809) contain SP/TM regions. As expected, fragment-mode HMM searches generate promiscuous hits limited to solely the SP/TM part among clearly unrelated proteins. More worryingly, we show explicit examples that the scores of clearly false-positive hits, even in global-mode searches, can be elevated into the significance range just by matching the hydrophobic runs. In the PIR iProClass database v3.74 using conservative criteria, we find that at least between 2.1% and 13.6% of its annotated Pfam hits appear unjustified for a set of validated domain models. Thus, false-positive domain hits enforced by SP/TM regions can lead to dramatic annotation errors where the hit has nothing in common with the problematic domain model except the SP/TM region itself. We suggest a workflow of flagging problematic hits arising from SP/TM-containing models for critical reconsideration by annotation users