Highly Invasive Listeria monocytogenes Strains Have Growth and Invasion Advantages in Strain Competition

Multiple Listeria monocytogenes strains can be present in the same food sample; moreover, infection with more than one L. monocytogenes strain can also occur. In this study we investigated the impact of strain competition on the growth and in vitro virulence potential of L. monocytogenes. We identified two strong competitor strains, whose growth was not (or only slightly) influenced by the presence of other strains and two weak competitor strains, which were outcompeted by other strains. Cell contact was essential for growth inhibition. In vitro virulence assays using human intestinal epithelial Caco2 cells showed a correlation between the invasion efficiency and growth inhibition: the strong growth competitor strains showed high invasiveness. Moreover, invasion efficiency of the highly invasive strain was further increased in certain combinations by the presence of a low invasive strain. In all tested combinations, the less invasive strain was outcompeted by the higher invasive strain. Studying the effect of cell contact on in vitro virulence competition revealed a complex pattern in which the observed effects depended only partially on cell-contact suggesting that competition occurs at two different levels: i) during co-cultivation prior to infection, which might influence the expression of virulence factors, and ii) during infection, when bacterial cells compete for the host cell. In conclusion, we show that growth of L. monocytogenes can be inhibited by strains of the same species leading potentially to biased recovery during enrichment procedures. Furthermore, the presence of more than one L. monocytogenes strain in food can lead to increased infection rates due to synergistic effects on the virulence potential.     

ANG II AT1 and AT2 receptors both inhibit bFGF-induced proliferation of bovine adrenocortical cells

Angiotensin II(ANG II) has long been known for its pressor and growth-promotingeffects, which are both mediated by theAT₁ receptor. By contrast, theAT₂ receptor has recently beenreported to mediate inhibition of proliferation through as yetundefined mechanisms. We report here that in bovine adrenal fasciculata cells ANG II by itself does not affect growth but inhibits basic fibroblast growth factor (bFGF)-induced DNA synthesis and blocks thecells in G₁ phase. Consistent withthis, ANG II inhibits cyclin D₁ expression and cyclinD₁-associated kinase activity. Theantimitogenic effect of ANG II is partly mimicked by theAT₂-selective agonist CGP-42112.It is also blocked partly and in an additive fashion by theAT₁- andAT₂-selective antagonists losartanand PD-123319, indicating the contribution of both receptor subtypes tothis response. AT₁-dependentantiproliferation is selectively blocked by the cyclooxygenaseinhibitor indomethacin and restored by prostaglandin E₂, whereasAT₂-receptor-mediated inhibitionof growth is suppressed by the tyrosine phosphatase inhibitorsorthovanadate and bpV(pic). Both pathways are, however,pertussis toxin sensitive. We hypothesize that, in fasciculatacells, the AT₁ receptor inhibitsbFGF-induced proliferation by stimulating prostaglandin synthesis,whereas the AT₂ receptor mediatesits effect through a pathway that requires protein tyrosine phosphataseactivation.

     

A phylogenomic resolution for the taxonomy of Aegean green lizards

Lacerta pamphylica and Lacerta trilineata are two currently recognized green lizard species with a historically problematic taxonomy. In cases of tangled phylogenies, next-generation sequencing and double-digest restriction-site-associated DNA protocols can provide a wealth of genomic data and resolve difficult taxonomic issues. Here, we generated genome-wide SNPs and mitochondrial sequences, and applied molecular species delimitation approaches to provide a stable taxonomy for the Aegean green lizards. Mitochondrial gene trees, genetic cluster delimitation and population structure analyses converged into recognizing the populations of (a) L. pamphylica, (b) east Aegean islands, Anatolia and Thrace (diplochondrodes lineage), (c) central Aegean islands (citrovittata), and (d) remaining Balkan populations and islands (trilineata), as separate clusters. Phylogenomic analyses revealed a split into two major clades, east and west of the Aegean Barrier, unambiguously showing a sister–clade relationship between pamphylica and diplochondrodes, rendering L. trilineata paraphyletic. Species delimitation models were tested in a Bayesian framework using the genomic SNPs: lumping all populations into a single ‘species’ had the lowest likelihood but the current taxonomy was also outperformed by all other models. All lines of evidence support the Pamphylian green lizard as a valid species; thus, east Aegean L. trilineata should also be considered a distinct species under the name Lacerta diplochondrodes. Finally, evidence from the mitochondrial and nuclear genomes is overwhelmingly in favour of recognizing the morphologically distinct Cycladian green lizards as a distinct species. We propose their elevation to full species under the name Lacerta citrovittata. All remaining insular and continental populations of the Balkan Peninsula represent the species L. trilineata.     

Hybrid physics-based and data-driven modeling for bioprocess online simulation and optimization

Model-based online optimization has not been widely applied to bioprocesses due to the challenges of modeling complex biological behaviors, low-quality industrial measurements, and lack of visualization techniques for ongoing processes. This study proposes an innovative hybrid modeling framework which takes advantages of both physics-based and data-driven modeling for bioprocess online monitoring, prediction, and optimization. The framework initially generates high-quality data by correcting raw process measurements via a physics-based noise filter (a generally available simple kinetic model with high fitting but low predictive performance); then constructs a predictive data-driven model to identify optimal control actions and predict discrete future bioprocess behaviors. Continuous future process trajectories are subsequently visualized by re-fitting the simple kinetic model (soft sensor) using the data-driven model predicted discrete future data points, enabling the accurate monitoring of ongoing processes at any operating time. This framework was tested to maximize fed-batch microalgal lutein production by combining with different online optimization schemes and compared against the conventional open-loop optimization technique. The optimal results using the proposed framework were found to be comparable to the theoretically best production, demonstrating its high predictive and flexible capabilities as well as its potential for industrial application.     

Identification and Characterization of Circular RNAs As a New Class of Putative Biomarkers in Human Blood

Covalently closed circular RNA molecules (circRNAs) have recently emerged as a class of RNA isoforms with widespread and tissue specific expression across animals, oftentimes independent of the corresponding linear mRNAs. circRNAs are remarkably stable and sometimes highly expressed molecules. Here, we sequenced RNA in human peripheral whole blood to determine the potential of circRNAs as biomarkers in an easily accessible body fluid. We report the reproducible detection of thousands of circRNAs. Importantly, we observed that hundreds of circRNAs are much higher expressed than corresponding linear mRNAs. Thus, circRNA expression in human blood reveals and quantifies the activity of hundreds of coding genes not accessible by classical mRNA specific assays. Our findings suggest that circRNAs could be used as biomarker molecules in standard clinical blood samples.