Priming by Chemokines Restricts Lateral Mobility of the Adhesion Receptor LFA-1 and Restores Adhesion to ICAM-1 Nano-Aggregates on Human Mature Dendritic Cells

LFA-1 is a leukocyte specific β2 integrin that plays a major role in regulating adhesion and migration of different immune cells. Recent data suggest that LFA-1 on mature dendritic cells (mDCs) may function as a chemokine-inducible anchor during homing of DCs through the afferent lymphatics into the lymph nodes, by transiently switching its molecular conformational state. However, the role of LFA-1 mobility in this process is not yet known, despite that the importance of lateral organization and dynamics for LFA-1-mediated adhesion regulation is broadly recognized. Using single particle tracking approaches we here show that LFA-1 exhibits higher mobility on resting mDCs compared to monocytes. Lymphoid chemokine CCL21 stimulation of the LFA-1 high affinity state on mDCs, led to a significant reduction of mobility and an increase on the fraction of stationary receptors, consistent with re-activation of the receptor. Addition of soluble monomeric ICAM-1 in the presence of CCL21 did not alter the diffusion profile of LFA-1 while soluble ICAM-1 nano-aggregates in the presence of CCL21 further reduced LFA-1 mobility and readily bound to the receptor. Overall, our results emphasize the importance of LFA-1 lateral mobility across the membrane on the regulation of integrin activation and its function as adhesion receptor. Importantly, our data show that chemokines alone are not sufficient to trigger the high affinity state of the integrin based on the strict definition that affinity refers to the adhesion capacity of a single receptor to its ligand in solution. Instead our data indicate that nanoclustering of the receptor, induced by multi-ligand binding, is required to maintain stable cell adhesion once LFA-1 high affinity state is transiently triggered by inside-out signals.Peer ReviewedPostprint (published version

miR-19a-3p containing exosomes improve function of ischemic myocardium upon shock wave therapy

AIMS: As many current approaches for heart regeneration exert unfavorable side-effects, the induction of endogenous repair mechanisms in ischemic heart disease is of particular interest. Recently, exosomes carrying angiogenic miRNAs have been described to improve heart function. However, it remains challenging to stimulate specific release of reparative exosomes in ischemic myocardium. In the present study, we sought to test the hypothesis that the physical stimulus of shock wave therapy (SWT) causes the release of exosomes. We aimed to substantiate the pro-angiogenic impact of the released factors, to identify the nature of their cargo, and to test their efficacy in vivo supporting regeneration and recovery after myocardial ischemia. METHODS AND RESULTS: Mechanical stimulation of ischemic muscle via SWT caused extracellular vesicle (EV) release from endothelial cells both in vitro and in vivo. Characterization of EVs via electron microscopy, nanoparticle tracking analysis and flow cytometry revealed specific exosome morphology and size with presence of exosome markers CD 9, CD81 and CD63. Exosomes exhibited angiogenic properties activating protein kinase b (Akt) and extracellular-signal regulated kinase (ERK) resulting in enhanced endothelial tube formation and proliferation. A miRNA array and transcriptome analysis via next-generation sequencing were performed to specify exosome content. miR-19a-3p was identified as responsible cargo, antimir-19a-3p antagonized angiogenic exosome effects. Exosomes and target miRNA were injected intramyocardially in mice after left anterior descending artery (LAD) ligation. Exosomes resulted in improved vascularization, decreased myocardial fibrosis and increased left ventricular ejection fraction as shown by transthoracic echocardiography. CONCLUSIONS: The mechanical stimulus of SWT causes release of angiogenic exosomes. miR-19a-3p is the vesicular cargo responsible for the observed effects. Released exosomes induce angiogenesis, decrease myocardial fibrosis and improve left ventricular function after myocardial ischemia. Exosome release via SWT could develop an innovative approach for the regeneration of ischemic myocardium

How to identify essential genes from molecular networks?

<p>Abstract</p> <p>Background</p> <p>The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion.</p> <p>Results</p> <p>By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for <it>Saccharomyces cerevisiae</it>, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined.</p> <p>Conclusion</p> <p>The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes.</p

Of Mice and ‘Convicts’: Origin of the Australian House Mouse, Mus musculus

The house mouse, Mus musculus, is one of the most ubiquitous invasive species worldwide and in Australia is particularly common and widespread, but where it originally came from is still unknown. Here we investigated this origin through a phylogeographic analysis of mitochondrial DNA sequences (D-loop) comparing mouse populations from Australia with those from the likely regional source area in Western Europe. Our results agree with human historical associations, showing a strong link between Australia and the British Isles. This outcome is of intrinsic and applied interest and helps to validate the colonization history of mice as a proxy for human settlement history

Industrial Systems Biology of Saccharomyces cerevisiae Enables Novel Succinic Acid Cell Factory.

Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the alpha-keto-glutarate dehydrogenase catalyzed conversion of alpha-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2nd-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals

Internal Transcribed Spacer 2 (nu ITS2 rRNA) Sequence-Structure Phylogenetics: Towards an Automated Reconstruction of the Green Algal Tree of Life

L). Some have advocated the use of the nuclear-encoded, internal transcribed spacer two (ITS2) as an alternative to the traditional chloroplast markers. However, the ITS2 is broadly perceived to be insufficiently conserved or to be confounded by introgression or biparental inheritance patterns, precluding its broad use in phylogenetic reconstruction or as a DNA barcode. A growing body of evidence has shown that simultaneous analysis of nucleotide data with secondary structure information can overcome at least some of the limitations of ITS2. The goal of this investigation was to assess the feasibility of an automated, sequence-structure approach for analysis of IT2 data from a large sampling of phylum Chlorophyta.Sequences and secondary structures from 591 chlorophycean, 741 trebouxiophycean and 938 ulvophycean algae, all obtained from the ITS2 Database, were aligned using a sequence structure-specific scoring matrix. Phylogenetic relationships were reconstructed by Profile Neighbor-Joining coupled with a sequence structure-specific, general time reversible substitution model. Results from analyses of the ITS2 data were robust at multiple nodes and showed considerable congruence with results from published phylogenetic analyses.Our observations on the power of automated, sequence-structure analyses of ITS2 to reconstruct phylum-level phylogenies of the green algae validate this approach to assessing diversity for large sets of chlorophytan taxa. Moreover, our results indicate that objections to the use of ITS2 for DNA barcoding should be weighed against the utility of an automated, data analysis approach with demonstrated power to reconstruct evolutionary patterns for highly divergent lineages

A surge of light at the birth of a supernova.

It is difficult to establish the properties of massive stars that explode as supernovae. The electromagnetic emission during the first minutes to hours after the emergence of the shock from the stellar surface conveys important information about the final evolution and structure of the exploding star. However, the unpredictable nature of supernova events hinders the detection of this brief initial phase. Here we report the serendipitous discovery of a newly born, normal type IIb supernova (SN 2016gkg), which reveals a rapid brightening at optical wavelengths of about 40 magnitudes per day. The very frequent sampling of the observations allowed us to study in detail the outermost structure of the progenitor of the supernova and the physics of the emergence of the shock. We develop hydrodynamical models of the explosion that naturally account for the complete evolution of the supernova over distinct phases regulated by different physical processes. This result suggests that it is appropriate to decouple the treatment of the shock propagation from the unknown mechanism that triggers the explosion

Quantitative Amyloid imaging in autosomal Dominant Alzheimer's disease: Results from the DIAN study group

Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer's Network (DIAN), an autosomal dominant Alzheimer's disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer's disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p

Combined measurement of differential and total cross sections in the H → γγ and the H → ZZ* → 4ℓ decay channels at s=13 TeV with the ATLAS detector

A combined measurement of differential and inclusive total cross sections of Higgs boson production is performed using 36.1 fb−1 of 13 TeV proton–proton collision data produced by the LHC and recorded by the ATLAS detector in 2015 and 2016. Cross sections are obtained from measured H→γγ and H→ZZ*(→4ℓ event yields, which are combined taking into account detector efficiencies, resolution, acceptances and branching fractions. The total Higgs boson production cross section is measured to be 57.0−5.9 +6.0 (stat.) −3.3 +4.0 (syst.) pb, in agreement with the Standard Model prediction. Differential cross-section measurements are presented for the Higgs boson transverse momentum distribution, Higgs boson rapidity, number of jets produced together with the Higgs boson, and the transverse momentum of the leading jet. The results from the two decay channels are found to be compatible, and their combination agrees with the Standard Model predictions