Genetic differentiation between alpine and lowland populations of a butterfly is related to PGI enzyme genotype

Understanding the ecological process of population differentiation and identifying the molecular changes that contribute to adaptation is a central aspect of evolutionary biology. In this study we analyzed the geographic variation in allozyme allele frequencies (based on 15 enzyme systems representing 18 loci) across 18 populations of the butterfly Lycaena tityrus from different altitudes. Population genetic analyses showed that within population genetic diversity (e.g. mean number of alleles per loci: 1.8; expected heterozygosity: 12%) was within the typical value range for the Lepidoptera. The populations of L. tityrus investigated showed a remarkable genetic differentiation (F_ST: 0.065), being clearly divided into an alpine (high-altitude) and a non-alpine (low-altitude) cluster. This differentiation was almost entirely caused by variation at a single enzyme locus, PGI. Although the involvement of historical events cannot be ruled out, several lines of evidence suggest that the specific pattern of allozyme (and in this case particularly PGI) variation found is caused by thermal selection. For example, genetic variation was highly locus-specific rather than relatively uniform, as should be expected for effects of natural selection. Further, the PGI 2–2 genotype dominating in alpine (in contrast to low-altitude) populations is known to exhibit increased cold stress resistance and relatively long development times typical of alpine populations. Thus, PGI (or possibly a closely linked gene) is an obvious target for thermal selection in L. tityrus . This study exemplifies how allozyme analyses can be used to detect candidate loci likely to be under selection.     

Density Gradient Centrifugation Compromises Bone Marrow Mononuclear Cell Yield

Bone marrow mononuclear cells (BMNCs) are widely used in regenerative medicine, but recent data suggests that the isolation of BMNCs by commonly used Ficoll-Paque density gradient centrifugation (DGC) causes significant cell loss and influences graft function. The objective of this study was to determine in an animal study whether and how Ficoll-Paque DGC affects the yield and composition of BMNCs compared to alternative isolation methods such as adjusted Percoll DGC or immunomagnetic separation of polymorphonuclear cells (PMNs). Each isolation procedure was confounded by a significant loss of BMNCs that was maximal after Ficoll-Paque DGC, moderate after adjusted Percoll DGC and least after immunomagnetic PMN depletion (25.6±5.8%, 51.5±2.3 and 72.3±6.7% recovery of total BMNCs in lysed bone marrow). Interestingly, proportions of BMNC subpopulations resembled those of lysed bone marrow indicating symmetric BMNC loss independent from the isolation protocol. Hematopoietic stem cell (HSC) content, determined by colony-forming units for granulocytes-macrophages (CFU-GM), was significantly reduced after Ficoll-Paque DGC compared to Percoll DGC and immunomagnetic PMN depletion. Finally, in a proof-of-concept study, we successfully applied the protocol for BMNC isolation by immunodepletion to fresh human bone marrow aspirates. Our findings indicate that the common method to isolate BMNCs in both preclinical and clinical research can be considerably improved by replacing Ficoll-Paque DGC with adapted Percoll DGC, or particularly by immunodepletion of PMNs.     

Maternal Smoking and the Risk of Cancer in Early Life – A Meta-Analysis

BackgroundIn spite of the well-known harmful effects on the fetus, many women continue smoking during pregnancy. Smoking as an important source of toxic chemicals may contribute to the developmental origin of diseases.ObjectivesThe aim of this work was to pursue the possible association between maternal smoking and cancer in early life. Specifically, we wanted to identify the associated early life cancer types, and to quantify the associations.MethodsIn a systematic literature search 825 articles were identified in PubMed and Web of Science, and 55 more through the reference lists. Of these 62 fulfilled the criteria for inclusion in meta-analyses. Using Mantel-Haenszel or DerSimonian and Laird method, depending on heterogeneity of the studies, pooled estimates and 95% confidence intervals for eight cancer types were calculated.ResultsSmoking during pregnancy was associated with an increased risk for for brain and central nervous system tumors (OR = 1.09; 95% CI = 1.02–1.17). Although the risk for lymphoma was also associated (OR = 1.21; 95% CI = 1.05–1.34), it did not hold up in subgroup analyses. Leukemia was not found to be associated with maternal smoking. Five other cancer types (bone, soft tissue, renal, hepatic, and germ cell cancer) were also examined, but the number of studies was too limited to exclude the possibility of maternal smoking as a risk factor for cancer in offspring.ConclusionsAccording to our meta-analyses, maternal smoking is associated with nervous system cancers, but not with leukemia in early life. Confirming or rejecting associations of maternal smoking with lymphoma and the five other cancer types requires further studies.     

Experimente mit Hefe (2)

The so‐called iodine test is ideal for demonstrating the role of the enzyme “amylase” in simple experiments based on a colour reaction when a yeast dough rises, when carbohydrates are digested or when dishes are washed in the dishwasher. The experiments presented can be used to clarify the question of which everyday substances are capable of degrading starch or whether a food contains starch or not. The central question of the experiments is, how yeast makes the bread dough rise despite of its “starch intolerance”.     

The population genetics of the fundamental cytotype-shift in invasive <Emphasis Type="Italic">Centaurea stoebe</Emphasis> s.l.: genetic diversity,genetic differentiation and small-scale genetic structure differ between cytotypes but not between ranges

Polyploids are overrepresented in invasive species. Yet, the role of genetic diversity and drift in colonization success of polyploids remains unclear. Here, we investigate genetic diversity, genetic differentiation and small-scale genetic structure in our model system, the three geo-cytotypes of Centaurea stoebe: monocarpic diploids and polycarpic (allo)tetraploids coexist in the native range (Eurasia), but only tetraploids are reported from the invasive range (North America). For each geo-cytotype, we investigated 18–20 populations varying in size and habitat type (natural vs. ruderal). Population genetic analyses were conducted at eight microsatellite loci. Compared to diploids, tetraploids revealed higher genetic diversity and lower genetic differentiation, whereas both were comparable in tetraploids between both ranges. Within spatial distances of a few meters, diploid individuals were more strongly related to one another than tetraploids. In addition, expected heterozygosity in diploids increased with population size and was higher in natural than in ruderal habitats. However, neither relationship was found for tetraploids. The higher genetic diversity of tetraploid C. stoebe may have enhanced its colonization abilities, if genetic diversity is correlated with fitness and adaptive capabilities. Furthermore, the inheritance of a duplicated chromosome set as well as longevity and frequent gene flow reduces drift in tetraploids. This counteracts genetic depletion during initial introductions and in subsequent phases of small or fluctuating population sizes in ruderal habitats. Our findings advocate the importance of studying colonization genetic processes to gain a more mechanistic understanding of the role of polyploidy in invasion dynamics.     

MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data

There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce     

Treatment of Chronic Experimental Autoimmune Encephalomyelitis with Epigallocatechin-3-Gallate and Glatiramer Acetate Alters Expression of Heme-Oxygenase-1

We previously demonstrated that epigallocatechin-3-gallate (EGCG) synergizes with the immunomodulatory agent glatiramer acetate (GA) in eliciting anti-inflammatory and neuroprotective effects in the relapsing-remitting EAE model. Thus, we hypothesized that mice with chronic EAE may also benefit from this combination therapy. We first assessed how a treatment with a single dose of GA together with daily application of EGCG may modulate EAE. Although single therapies with a suboptimal dose of GA or EGCG led to disease amelioration and reduced CNS inflammation, the combination therapy had no effects. While EGCG appeared to preserve axons and myelin, the single GA dose did not improve axonal damage or demyelination. Interestingly, the neuroprotective effect of EGCG was abolished when GA was applied in combination. To elucidate how a single dose of GA may interfere with EGCG, we focused on the anti-inflammatory, iron chelating and anti-oxidant properties of EGCG. Surprisingly, we observed that while EGCG induced a downregulation of the gene expression of heme oxygenase-1 (HO-1) in affected CNS areas, the combined therapy of GA+EGCG seems to promote an increased HO-1 expression. These data suggest that upregulation of HO-1 may contribute to diminish the neuroprotective benefits of EGCG alone in this EAE model. Altogether, our data indicate that neuroprotection by EGCG in chronic EAE may involve regulation of oxidative processes, including downmodulation of HO-1. Further investigation of the re-dox balance in chronic neuroinflammation and in particular functional studies on HO-1 are warranted to understand its role in disease progression.     

NetSurfP-2.0: Improved prediction of protein structural features by integrated deep learning

The ability to predict local structural features of a protein from the primary sequence is of paramount importance for unraveling its function in absence of experimental structural information. Two main factors affect the utility of potential prediction tools: their accuracy must enable extraction of reliable structural information on the proteins of interest, and their runtime must be low to keep pace with sequencing data being generated at a constantly increasing speed. Here, we present NetSurfP-2.0, a novel tool that can predict the most important local structural features with unprecedented accuracy and runtime. NetSurfP-2.0 is sequence-based and uses an architecture composed of convolutional and long short-term memory neural networks trained on solved protein structures. Using a single integrated model, NetSurfP-2.0 predicts solvent accessibility, secondary structure, structural disorder, and backbone dihedral angles for each residue of the input sequences. We assessed the accuracy of NetSurfP-2.0 on several independent test datasets and found it to consistently produce state-of-the-art predictions for each of its output features. We observe a correlation of 80% between predictions and experimental data for solvent accessibility, and a precision of 85% on secondary structure 3-class predictions. In addition to improved accuracy, the processing time has been optimized to allow predicting more than 1000 proteins in less than 2 hours, and complete proteomes in less than 1 day.     

Trafficking and assembly of the cold-sensitive TRPM8 channel

TRPM (transient receptor potential melastatin-like) channels are distinct from many other members of the transient receptor potential family in regard to their overall size (>1000 amino acids), the lack of N-terminal ankyrin-like repeats, and hydrophobicity predictions that may allow for more than six transmembrane regions. Common to each TRPM member is a prominent C-terminal coiled coil region. Here we have shown that TRPM8 channels assemble as multimers using the putative coiled coil region within the intracellular C terminus and that this assembly can be disturbed by a single point mutation within the coiled coil region. This mutant neither gives rise to functional channels nor do its subunits interact or form protein complexes that correspond to a multimer. However, they are still transported to the plasma membrane. Furthermore, wild-type currents can be suppressed by expressing the membrane-attached C-terminal region of TRPM8. To separate assembly from trafficking, we investigated the maturation of TRPM8 protein by identifying and mutating the relevant N-linked glycosylation site and showing that glycosylation is neither essential for multimerization nor for transport to the plasma membrane per se but appears to facilitate efficient multimerization and transport.