Male sterility at extreme temperatures: a significant but neglected phenomenon for understanding Drosophila climatic adaptations

The thermal range for viability is quite variable among Drosophila species and it has long been known that these variations are correlated with geographic distribution: temperate species are on average more cold tolerant but more heat sensitive than tropical species. At both ends of their viability range, sterile males have been observed in all species investigated so far. This symmetrical phenomenon restricts the temperature limits within which permanent cultures can be kept in the laboratory. Thermal heat sterility thresholds are very variable across species from 23 degrees C in heat sensitive species up to 31 degrees C in heat tolerant species. In Drosophila melanogaster, genetic variations are observed among geographic populations. Tropical populations are more tolerant to heat induced sterility and recover more rapidly than temperate ones. A genetic analysis revealed that about 50% of the difference observed between natural populations was due to the Y chromosome. Natural populations have not reached a selection limit, however: thermal tolerance was still increased by keeping strains at a high temperature, close to the sterility threshold. On the low temperature side, a symmetrical reverse phenomenon seems to exist: temperate populations are more tolerant to cold than tropical ones. Compared to Mammals, drosophilids exhibit two major differences: first, male sterility occurs not only at high temperature, but also at a low temperature; second, sterility thresholds are not evolutionarily constrained, but highly variable. Altogether, significant and sometimes major genetic variations have been observed between species, between geographic races of the same species, and even between strains kept in the laboratory under different thermal regimes. In each case, it is easily argued that the observed variations correspond to adaptations to climatic conditions, and that male sterility is a significant component of fitness and a target of natural selection.     

Development and validation of a UPLC/MS method for a nutritional metabolomic study of human plasma

In order to study the effect of a diet on metabolites found in body fluids such as plasma, we have developed and validated a UPLC/MS method. While methods using NMR have been well established to analyse different biological tissues, recent studies have described robust untargeted UPLC-MS methods for plasma analysis. One major concern when profiling plasma is the presence of an important quantity of proteins which have to be precipitated without any loss of metabolites prior to LC/MS analysis. The utilization of untargeted approaches in nutritional metabolomics still suffers from the lack of identification of specific biomarkers. We therefore suggest an alternative method still using a global approach but focusing at the same time on metabolites previously described in human plasma in order to detect biomarkers of metabolic dysregulations. Thus, to fulfil our objectives, analytical parameters were tested (i) the anticoagulant type for sample collection, (ii) the protein precipitation method and (iii) UPLC/MS analytical conditions. Three protein precipitation methods and two anticoagulants were tested and compared. The method utilizing blood collection on heparin and methanol precipitation was chosen for giving the most reproducible results while keeping the complexity of the sample. Finally, a validation was proposed to evaluate the stability of this analytical method applied to a large batch of samples for nutritional metabolomic studies.     

Primary structure of sorghum malate dehydrogenase (NADP) deduced from cDNA sequence. Homology with malate dehydrogenase (NAD)

Malate dehydrogenase (NADP) (NADP-MDH) is an important enzyme of the photosynthetic CO2 fixation pathway of C4 plants. We have isolated two clones from a sorghum lambda gt11 cDNA library (CM3, 932 bp, and CM7, 1441 bp). Nucleotide sequence analysis of the cDNAs CM3 and CM7 showed the existence of two NADP-MDH mRNA species encoding different enzyme subunits. Microsequencing of the N-terminus of the mature protein indicated that a specific cleavage of 13 amino acids occurred during the purification steps of the enzyme. The full-length cDNA CM7 contains a large open reading frame encoding an NH2-terminal transit peptide of 40 amino acids and a mature protein of 389 amino acids (42.207 kDa). Alignment of the NADP-MDH sequence with those of several malate dehydrogenases revealed some similarities with NAD-MDHs.     

Structural specificity in plant–filamentous pathogen interactions

Plant diseases bear names such as leaf blights, root rots, sheath blights, tuber scabs, and stem cankers, indicating that symptoms occur preferentially on specific parts of host plants. Accordingly, many plant pathogens are specialized to infect and cause disease in specific tissues and organs. Conversely, others are able to infect a range of tissues, albeit often disease symptoms fluctuate in different organs infected by the same pathogen. The structural specificity of a pathogen defines the degree to which it is reliant on a given tissue, organ, or host developmental stage. It is influenced by both the microbe and the host but the processes shaping it are not well established. Here we review the current status on structural specificity of plant–filamentous pathogen interactions and highlight important research questions. Notably, this review addresses how constitutive defence and induced immunity as well as virulence processes vary across plant organs, tissues, and even cells. A better understanding of the mechanisms underlying structural specificity will aid targeted approaches for plant health, for instance by considering the variation in the nature and the amplitude of defence responses across distinct plant organs and tissues when performing selective breeding.     

Transferability,development of simple sequence repeat (SSR) markers and application to the analysis of genetic diversity and population structure of the African fan palm (Borassus aethiopum Mart.) in Benin

Biological pathways play an important role in the occurrence, development and recovery of complex diseases, such as cancers, which are multifactorial complex diseases that are generally caused by mutation of multiple genes or dysregulation of pathways. We propose a path-specific effect statistic (PSE) to detect the differential specific paths under two conditions (e.g. case VS. control groups, exposure Vs. nonexposure groups). In observational studies, the path-specific effect can be obtained by separately calculating the average causal effect of each directed edge through adjusting for the parent nodes of nodes in the specific path and multiplying them under each condition. Theoretical proofs and a series of simulations are conducted to validate the path-specific effect statistic. Applications are also performed to evaluate its practical performances. A series of simulation studies show that the Type I error rates of PSE with Permutation tests are more stable at the nominal level 0.05 and can accurately detect the differential specific paths when comparing with other methods. Specifically, the power reveals an increasing trends with the enlargement of path-specific effects and its effect differences under two conditions. Besides, the power of PSE is robust to the variation of parent or child node of the nodes on specific paths. Application to real data of Glioblastoma Multiforme (GBM), we successfully identified 14 positive specific pathways in mTOR pathway contributing to survival time of patients with GBM. All codes for automatic searching specific paths linking two continuous variables and adjusting set as well as PSE statistic can be found in supplementary materials.  The proposed PSE statistic can accurately detect the differential specific pathways contributing to complex disease and thus potentially provides new insights and ways to unlock the black box of disease mechanisms.     

Disturbances, elevation, topography and spatial proximity drive vegetation patterns along an altitudinal gradient of a top biodiversity hotspot

The correlation between vegetation patterns (species distribution and richness) and altitudinal variation has been widely reported for tropical forests, thereby providing theoretical basis for biodiversity conservation. However, this relationship may have been oversimplified, as many other factors may influence vegetation patterns, such as disturbances, topography and geographic distance. Considering these other factors, our primary question was: is there a vegetation pattern associated with substantial altitudinal variation (10–1,093 m a.s.l.) in the Atlantic Rainforest—a top hotspot for biodiversity conservation—and, if so, what are the main factors driving this pattern? We addressed this question by sampling 11 1-ha plots, applying multivariate methods, correlations and variance partitioning. The Restinga (forest on sandbanks along the coastal plains of Brazil) and a lowland area that was selectively logged 40 years ago were floristically isolated from the other plots. The maximum species richness (>200 spp. per hectare) occurred at approximately 350 m a.s.l. (submontane forest). Gaps, multiple stemmed trees, average elevation and the standard deviation of the slope significantly affected the vegetation pattern. Spatial proximity also influenced the vegetation pattern as a structuring environmental variable or via dispersal constraints. Our results clarify, for the first time, the key variables that drive species distribution and richness across a large altitudinal range within the Atlantic Rainforest.