Evolution of the Archaea

Archaea, members of the third domain of life, are bacterial-looking prokaryotes that harbour many unique genotypic and phenotypic properties, testifying for their peculiar evolutionary status. The archaeal ancestor was probably a hyperthermophilic anaerobe. Two archaeal phyla are presently recognized, the Euryarchaeota and the Crenarchaeota. Methanogenesis was the main invention that occurred in the euryarchaeal phylum and is now shared by several archaeal groups. Adaptation to aerobic conditions occurred several times independently in both Euryarchaeota and Crenarchaeota. Recently, many new groups of Archaea that have not yet been cultured have been detected by PCR amplification of 16S ribosomal RNA from environmental samples. The phenotypic and genotypic characterization of these new groups is now a top priority for further studies on archaeal evolution.     

Network Analysis of Metabolite GWAS Hits: Implication of CPS1 and the Urea Cycle in Weight Maintenance

Background and Scope

Weight loss success is dependent on the ability to refrain from regaining the lost weight in time. This feature was shown to be largely variable among individuals, and these differences, with their underlying molecular processes, are diverse and not completely elucidated. Altered plasma metabolites concentration could partly explain weight loss maintenance mechanisms. In the present work, a systems biology approach has been applied to investigate the potential mechanisms involved in weight loss maintenance within the Diogenes weight-loss intervention study.

Methods and Results

A genome wide association study identified SNPs associated with plasma glycine levels within the CPS1 (Carbamoyl-Phosphate Synthase 1) gene (rs10206976, p-value = 4.709e-11 and rs12613336, p-value = 1.368e-08). Furthermore, gene expression in the adipose tissue showed that CPS1 expression levels were associated with successful weight maintenance and with several SNPs within CPS1 (cis-eQTL). In order to contextualize these results, a gene-metabolite interaction network of CPS1 and glycine has been built and analyzed, showing functional enrichment in genes involved in lipid metabolism and one carbon pool by folate pathways.

Conclusions

CPS1 is the rate-limiting enzyme for the urea cycle, catalyzing carbamoyl phosphate from ammonia and bicarbonate in the mitochondria. Glycine and CPS1 are connected through the one-carbon pool by the folate pathway and the urea cycle. Furthermore, glycine could be linked to metabolic health and insulin sensitivity through the betaine osmolyte. These considerations, and the results from the present study, highlight a possible role of CPS1 and related pathways in weight loss maintenance, suggesting that it might be partly genetically determined in humans.     

Polyanxanthone A, B and C, three xanthones from the wood trunk of Garcinia polyantha Oliv

Three xanthones, polyanxanthone A (1), B (2) and C (3) have been isolated from the methanol extract of the wood trunk of Garcinia polyantha, along with five known xanthones: 1,3,5-trihydroxyxanthone (4); 1,5-dihydroxyxanthone (5); 1,3,6,7-tetrahydroxyxanthone (6); 1,6-dihydroxy-5-methoxyxanthone (7) and 1,3,5,6-tetrahydroxyxanthone (8). Their structures were determined by means of 1D- and 2D-NMR techniques. Some of the above compounds were screened for their anticholinesterase activity on acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes.     

Identification of a new segment involved in cagA 3' region variation of Helicobacter pylori

The cagA 3' region shows marked variation among Helicobacter pylori strains. Two segments of 102 bp and 57 bp are reportedly responsible for this variation. We analysed the cagA 3' region in 70 H. pylori strains using polymerase chain reaction and sequencing. We found that another segment, namely beta segment, was also involved in the variation of this region. The beta segment was 105 bp long and located between the aforementioned two segments. Six genotypes were identified based on the structure of the cagA 3' region. No relationship was found between these genotypes and the clinical outcomes or vacA genotypes. The numbers of tyrosine phosphorylation sites within the cagA 3' region varied among strains, but this was not related to the cagA genotypes. Our data suggest that the cagA 3' region is significantly variable. It appears that the variation of the cagA 3' region might contribute to the modification of virulence.     

Pleiotropy in the melanocortin system: expression levels of this system are associated with melanogenesis and pigmentation in the tawny owl (Strix aluco)

The adaptive function of melanin‐based coloration is a long‐standing debate. A recent genetic model suggested that pleiotropy could account for covariations between pigmentation, behaviour, morphology, physiology and life history traits. We explored whether the expression levels of genes belonging to the melanocortin system (MC1R, POMC, PC1/3, PC2 and the antagonist ASIP), which have many pleiotropic effects, are associated with melanogenesis (through variation in the expression of the genes MITF, SLC7A11, TYR, TYRP1) and in turn melanin‐based coloration. We considered the tawny owl (Strix aluco) because individuals vary continuously from light to dark reddish, and thus, colour variation is likely to stem from differences in the levels of gene expression. We measured gene expression in feather bases collected in nestlings at the time of melanin production. As expected, the melanocortin system was associated with the expression of melanogenic genes and pigmentation. Offspring of darker reddish fathers expressed PC1/3 to lower levels but tended to express PC2 to higher levels. The convertase enzyme PC1/3 cleaves the POMC prohormone to obtain ACTH, while the convertase enzyme PC2 cleaves ACTH to produce α‐melanin‐stimulating hormone (α‐MSH). ACTH regulates glucocorticoids, hormones that modulate stress responses, while α‐MSH induces eumelanogenesis. We therefore conclude that the melanocortin system, through the convertase enzymes PC1/3 and PC2, may account for part of the interindividual variation in melanin‐based coloration in nestling tawny owls. Pleiotropy may thus account for the covariation between phenotypic traits involved in social interactions (here pigmentation) and life history, morphology, behaviour and physiology.     

Repeatability and correlation of physiological traits: Do ectotherms have a “thermal type”?

Across a range of taxa, individuals within a species differ in suites of correlated traits. These trait complexes, known as syndromes, can have dramatic evolutionary consequences as they do not evolve independently but rather as a unit. Current research focuses primarily on syndromes relating to aspects of behavior and life history. What is less clear is whether physiological traits also form a syndrome. We measured 10 thermal traits in the delicate skink, Lampropholis delicata, to test this idea. Repeatability was calculated and their across‐context correlations evaluated. Our results were in alignment with our predictions in that individual thermal traits varied consistently and were structured into a physiological syndrome, which we are referring to as the thermal behavior syndrome (TBS). Within this syndrome, lizards exhibited a “thermal type” with each being ranked along a cold–hot continuum. Hot types had faster sprint speeds and higher preferred body temperatures, whereas the opposite was true for cold types. We conclude that physiological traits may evolve as a single unit driven by the need to maintain optimal temperatures that enable fitness‐related behaviors to be maximized.     

Evaluating the influence of quality control decisions and software algorithms on SNP calling for the affymetrix 6.0 SNP array platform

Objective: Our goal was to evaluate the influence of quality control (QC) decisions using two genotype calling algorithms, CRLMM and Birdseed, designed for the Affymetrix SNP Array 6.0. Methods: Various QC options were tried using the two algorithms and comparisons were made on subject and call rate and on association results using two data sets. Results: For Birdseed, we recommend using the contrast QC instead of QC call rate for sample QC. For CRLMM, we recommend using the signal-to-noise rate ≥4 for sample QC and a posterior probability of 90% for genotype accuracy. For both algorithms, we recommend calling the genotype separately for each plate, and dropping SNPs with a lower call rate (<95%) before evaluating samples with lower call rates. To investigate whether the genotype calls from the two algorithms impacted the genome-wide association results, we performed association analysis using data from the GENOA cohort; we observed that the number of significant SNPs were similar using either CRLMM or Birdseed. Conclusions: Using our suggested workflow both algorithms performed similarly; however, fewer samples were removed and CRLMM took half the time to run our 854 study samples (4.2 h) compared to Birdseed (8.4 h).     

Use of Single-Point Genome Signature Tags as a Universal Tagging Method for Microbial Genome Surveys

We developed single-point genome signature tags (SP-GSTs), a generally applicable, high-throughput sequencing-based method that targets specific genes to generate identifier tags from well-defined points in a genome. The technique yields identifier tags that can distinguish between closely related bacterial strains and allow for the identification of microbial community members. SP-GSTs are determined by three parameters: (i) the primer designed to recognize a conserved gene sequence, (ii) the anchoring enzyme recognition sequence, and (iii) the type IIS restriction enzyme which defines the tag length. We evaluated the SP-GST method in silico for bacterial identification using the genes rpoC, uvrB, and recA and the 16S rRNA gene. The best distinguishing tags were obtained with the restriction enzyme Csp6I upstream of the 16S rRNA gene, which discriminated all organisms in our data set to at least the genus level and most organisms to the species level. The method was successfully used to generate Csp6I-based tags upstream of the 16S rRNA gene and allowed us to discriminate between closely related strains of Bacillus cereus and Bacillus anthracis. This concept was further used successfully to identify the individual members of a defined microbial community.