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Background
Invasive fungal infections with Candida albicans (C. albicans) occur frequently in extremely low birthweight (ELBW) infants and are associated with poor outcome. Phagocytosis of C.albicans initializes apoptosis in monocytes (phagocytosis induced cell death, PICD). PICD is reduced in neonatal cord blood monocytes (CBMO).
Hypothesis
Phagocytosis of C. albicans causes PICD which differs between neonatal monocytes (CBMO) and adult peripheral blood monocytes (PBMO) due to lower stimulation of TLR-mediated immune responses.
Methods
The ability to phagocytose C. albicans, expression of TLRs, the induction of apoptosis (assessment of sub-G1 and nick-strand breaks) were analyzed by FACS. TLR signalling was induced by agonists such as lipopolysaccharide (LPS), Pam3Cys, FSL-1 and Zymosan and blocked (neutralizing TLR2 antibodies and MYD88 inhibitor).
Results
Phagocytic indices of PBMO and CBMO were similar. Following stimulation with agonists and C. albicans induced up-regulation of TLR2 and consecutive phosphorylation of MAP kinase P38 and expression of TNF-α, which were stronger on PBMO compared to CBMO (p < 0.005). Downstream, TLR2 signalling initiated caspase-3-dependent PICD which was found reduced in CBMO (p < 0.05 vs PBMO).
Conclusion
Our data suggest direct involvement of TLR2-signalling in C. albicans-induced PICD in monocytes and an alteration of this pathway in CBMO.
Attraction to ethanol is common in both flies and humans, but the neuromodulatory mechanisms underlying this innate attraction are not well understood. Here, we dissect the function of the key regulator of serotonin signaling—the serotonin transporter–in innate olfactory attraction to ethanol in Drosophila melanogaster. We generated a mutated version of the serotonin transporter that prolongs serotonin signaling in the synaptic cleft and is targeted via the Gal4 system to different sets of serotonergic neurons. We identified four serotonergic neurons that inhibit the olfactory attraction to ethanol and two additional neurons that counteract this inhibition by strengthening olfactory information. Our results reveal that compensation can occur on the circuit level and that serotonin has a bidirectional function in modulating the innate attraction to ethanol. Given the evolutionarily conserved nature of the serotonin transporter and serotonin, the bidirectional serotonergic mechanisms delineate a basic principle for how random behavior is switched into targeted approach behavior.
Recently, a genome-wide analysis identified DNA methylation of the HIF3A (hypoxia-inducible factor 3A) as strongest correlate of BMI. Here we tested the hypothesis that HIF3A mRNA expression and CpG-sites methylation in adipose tissue (AT) and genetic variants in HIF3A are related to parameters of AT distribution and function. In paired samples of subcutaneous AT (SAT) and visceral AT (VAT) from 603 individuals, we measured HIF3A mRNA expression and analyzed its correlation with obesity and related traits. In subgroups of individuals, we investigated the effects on HIF3A genetic variants on its AT expression (N = 603) and methylation of CpG-sites (N = 87). HIF3A expression was significantly higher in SAT compared to VAT and correlated with obesity and parameters of AT dysfunction (including CRP and leucocytes count). HIF3A methylation at cg22891070 was significantly higher in VAT compared to SAT and correlated with BMI, abdominal SAT and VAT area. Rs8102595 showed a nominal significant association with AT HIF3A methylation levels as well as with obesity and fat distribution. HIF3A expression and methylation in AT are fat depot specific, related to obesity and AT dysfunction. Our data support the hypothesis that HIF pathways may play an important role in the development of AT dysfunction in obesity.
Sequence Logos and its variants are the most commonly used method for visualization of multiple sequence alignments (MSAs) and sequence motifs. They provide consensus-based summaries of the sequences in the alignment. Consequently, individual sequences cannot be identified in the visualization and covariant sites are not easily discernible. We recently proposed Sequence Bundles, a motif visualization technique that maintains a one-to-one relationship between sequences and their graphical representation and visualizes covariant sites. We here present Alvis, an open-source platform for the joint explorative analysis of MSAs and phylogenetic trees, employing Sequence Bundles as its main visualization method. Alvis combines the power of the visualization method with an interactive toolkit allowing detection of covariant sites, annotation of trees with synapomorphies and homoplasies, and motif detection. It also offers numerical analysis functionality, such as dimension reduction and classification. Alvis is user-friendly, highly customizable and can export results in publication-quality figures. It is available as a full-featured standalone version (http://www.bitbucket.org/rfs/alvis) and its Sequence Bundles visualization module is further available as a web application (http://science-practice.com/projects/sequence-bundles).
Mutation Detection in Patients with Retinal Dystrophies Using Targeted Next Generation Sequencing
(2016)
Retinal dystrophies (RD) constitute a group of blinding diseases that are characterized by clinical variability and pronounced genetic heterogeneity. The different nonsyndromic and syndromic forms of RD can be attributed to mutations in more than 200 genes. Consequently, next generation sequencing (NGS) technologies are among the most promising approaches to identify mutations in RD. We screened a large cohort of patients comprising 89 independent cases and families with various subforms of RD applying different NGS platforms. While mutation screening in 50 cases was performed using a RD gene capture panel, 47 cases were analyzed using whole exome sequencing. One family was analyzed using whole genome sequencing. A detection rate of 61% was achieved including mutations in 34 known and two novel RD genes. A total of 69 distinct mutations were identified, including 39 novel mutations. Notably, genetic findings in several families were not consistent with the initial clinical diagnosis. Clinical reassessment resulted in refinement of the clinical diagnosis in some of these families and confirmed the broad clinical spectrum associated with mutations in RD genes.
Prey selection is a key factor shaping animal populations and evolutionary dynamics. An optimal forager should target prey that offers the highest benefits in terms of energy content at the lowest costs. Predators are therefore expected to select for prey of optimal size. Stalking predators do not pursue their prey long, which may lead to a more random choice of prey individuals. Due to difficulties in assessing the composition of available prey populations, data on prey selection of stalking carnivores are still scarce. We show how the stalking predator Eurasian lynx (Lynx lynx) selects prey individuals based on species identity, age, sex and individual behaviour. To address the difficulties in assessing prey population structure, we confirm inferred selection patterns by using two independent data sets: (1) data of 387 documented kills of radio-collared lynx were compared to the prey population structure retrieved from systematic camera trapping using Manly’s standardized selection ratio alpha and (2) data on 120 radio-collared roe deer were analysed using a Cox proportional hazards model. Among the larger red deer prey, lynx selected against adult males—the largest and potentially most dangerous prey individuals. In roe deer lynx preyed selectively on males and did not select for a specific age class. Activity during high risk periods reduced the risk of falling victim to a lynx attack. Our results suggest that the stalking predator lynx actively selects for size, while prey behaviour induces selection by encounter and stalking success rates.
Insects inhabiting the temperate zones measure seasonal changes in day or night length to enter the overwintering diapause. Diapause induction occurs after the duration of the night exceeds a critical night length (CNL). Our understanding of the time measurement mechanisms is continuously evolving subsequent to Bünning’s proposal that circadian systems play the clock role in photoperiodic time measurement (Bünning, 1936). Initially, the photoperiodic clocks were considered to be either based on circadian oscillators or on simple hour-glasses, depending on ‘positive’ or ‘negative’ responses in Nanda–Hamner and Bünsow experiments (Nanda & Hammer, 1958; Bünsow, 1960).
However, there are also species whose responses can be regarded as neither ‘positive’, nor as ‘negative’, such as the Northern Drosophila species Drosophila ezoana, which is investigated in the present study. In addition, modelling efforts show that the ‘positive’ and ‘negative’ Nanda–Hamner responses can also be provoked by circadian oscillators that are damped to different degrees: animals with highly sustained circadian clocks will respond ‘positive’ and those with heavily damped circadian clocks will respond ‘negative’. In the present study, an experimental assay is proposed that characterizes the photoperiodic oscillators by determining the effects of non-24-h light/dark cycles (T-cycles) on critical night length. It is predicted that there is (i) a change in the critical night length as a function of T-cycle period in sustained-oscillator-based clocks and (ii) a fxed night-length measurement (i.e. no change in critical night length) in damped-oscillator-based clocks. Drosophila ezoana flies show a critical night length of approximately 7 h irrespective of T-cycle period, suggesting a damped-oscillator-based photoperiodic clock. The conclusion is strengthened by activity recordings revealing that the activity rhythm of D. ezoana flies also dampens in constant darkness.
Chronobiological studies of individual activity rhythms in social insects can be constrained by the artificial isolation of individuals from their social context. We present a new experimental set-up that simultaneously measures the temperature rhythm in a queen-less but brood raising mini colony and the walking activity rhythms of singly kept honey bees that have indirect social contact with it. Our approach enables monitoring of individual bees in the social context of a mini colony under controlled laboratory conditions. In a pilot experiment, we show that social contact with the mini colony improves the survival of monitored young individuals and affects locomotor activity patterns of young and old bees. When exposed to conflicting Zeitgebers consisting of a light-dark (LD) cycle that is phase-delayed with respect to the mini colony rhythm, rhythms of young and old bees are socially synchronized with the mini colony rhythm, whereas isolated bees synchronize to the LD cycle. We conclude that the social environment is a stronger Zeitgeber than the LD cycle and that our new experimental set-up is well suited for studying the mechanisms of social entrainment in honey bees.
Background
Tropical mountain forests are hotspots of biodiversity hosting a huge but little known diversity of insects that is endangered by habitat destruction and climate change. Therefore, rapid assessment approaches of insect diversity are urgently needed to complement slower traditional taxonomic approaches. We empirically compare different DNA-based species delimitation approaches for a rapid biodiversity assessment of hyperdiverse leaf beetle assemblages along an elevational gradient in southern Ecuador and explore their effect on species richness estimates.
Methodology/Principal Findings
Based on a COI barcode data set of 674 leaf beetle specimens (Coleoptera: Chrysomelidae) of 266 morphospecies from three sample sites in the Podocarpus National Park, we employed statistical parsimony analysis, distance-based clustering, GMYC- and PTP-modelling to delimit species-like units and compared them to morphology-based (parataxonomic) species identifications. The four different approaches for DNA-based species delimitation revealed highly similar numbers of molecular operational taxonomic units (MOTUs) (n = 284–289). Estimated total species richness was considerably higher than the sampled amount, 414 for morphospecies (Chao2) and 469–481 for the different MOTU types. Assemblages at different elevational levels (1000 vs. 2000 m) had similar species numbers but a very distinct species composition for all delimitation methods. Most species were found only at one elevation while this turnover pattern was even more pronounced for DNA-based delimitation.
Conclusions/Significance
Given the high congruence of DNA-based delimitation results, probably due to the sampling structure, our study suggests that when applied to species communities on a regionally limited level with high amount of rare species (i.e. ~50% singletons), the choice of species delimitation method can be of minor relevance for assessing species numbers and turnover in tropical insect communities. Therefore, DNA-based species delimitation is confirmed as a valuable tool for evaluating biodiversity of hyperdiverse insect communities, especially when exact taxonomic identifications are missing.
Mining biomedical images towards valuable information retrieval in biomedical and life sciences
(2016)
Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries.