Differential adhesion between migrating neurons and transient radial glial fibers enables the deployment of neurons into appropriate layers in the developing cerebral cortex. The identity of radial glial signals that regulate the termination of migration remains unclear. Here, we identified a radial glial surface antigen, SPARC (secreted protein acidic and rich in cysteine)-like 1, distributed predominantly in radial glial fibers passing through the upper strata of the cortical plate (CP) where neurons end their migration. Neuronal migration and adhesion assays indicate that SPARC-like 1 functions to terminate neuronal migration by reducing the adhesivity of neurons at the top of the CP. Cortical neurons fail to achieve appropriate positions in the absence of SPARC-like 1 function in vivo. Together, these data suggest that antiadhesive signaling via SPARC-like 1 on radial glial cell surfaces may enable neurons to recognize the end of migration in the developing cerebral cortex.

BackgroundNon-coding RNAs (ncRNAs) are key regulatory elements that control a wide range of cellular processes in all bacteria in which they have been studied. Taking advantage of recent technological innovations, we set out to fully explore the ncRNA potential of the multicellular, antibiotic-producing Streptomyces bacteria.ResultsUsing a comparative RNA sequencing analysis of three divergent model streptomycetes (S. coelicolor, S. avermitilis and S. venezuelae), we discovered hundreds of novel cis-antisense RNAs and intergenic small RNAs (sRNAs). We identified a ubiquitous antisense RNA species that arose from the overlapping transcription of convergently-oriented genes; we termed these RNA species ‘cutoRNAs’, for convergent untranslated overlapping RNAs. Conservation between different classes of ncRNAs varied greatly, with sRNAs being more conserved than antisense RNAs. Many species-specific ncRNAs, including many distinct cutoRNA pairs, were located within antibiotic biosynthetic clusters, including the actinorhodin, undecylprodigiosin, and coelimycin clusters of S. coelicolor, the chloramphenicol cluster of S. venezuelae, and the avermectin cluster of S. avermitilis.ConclusionsThese findings indicate that ncRNAs, including a novel class of antisense RNA, may exert a previously unrecognized level of regulatory control over antibiotic production in these bacteria. Collectively, this work has dramatically expanded the ncRNA repertoire of three Streptomyces species and has established a critical foundation from which to investigate ncRNA function in this medically and industrially important bacterial genus.

Streptomyces are predominantly soil-dwelling bacteria that are best known for their multicellular life cycle and their prodigious metabolic capabilities. They are also renowned for their regulatory capacity and flexibility, with each species encoding >60 sigma factors, a multitude of transcription factors, and an increasing number of small regulatory RNAs. Here, we describe our characterization of a conserved small RNA (sRNA), scr4677. In the model species Streptomyces coelicolor, this sRNA is located in the intergenic region separating SCO4677 (an anti-sigma factor-encoding gene) and SCO4676 (a putative regulatory protein-encoding gene), close to the SCO4676 translation start site in an antisense orientation. There appears to be considerable genetic interplay between these different gene products, with wild type expression of scr4677 requiring function of the anti-sigma factor SCO4677, and scr4677 in turn influencing the abundance of SCO4676-associated transcripts. The scr4677-mediated effects were independent of RNase III (a double stranded RNA-specific nuclease), with RNase III having an unexpectedly positive influence on the level of SCO4676-associated transcripts. We have shown that both SCO4676 and SCO4677 affect the production of the blue-pigmented antibiotic actinorhodin under specific growth conditions, and that this activity appears to be independent of scr4677.

A microscale wildfire model, QES-Fire, that dynamically couples the fire front to microscale winds was developed using a simplified physics rate of spread (ROS) model, a kinematic plume-rise model and a mass-consistent wind solver. The model is three-dimensional and couples fire heat fluxes to the wind field while being more computationally efficient than other coupled models. The plume-rise model calculates a potential velocity field scaled by the ROS model’s fire heat flux. Distinct plumes are merged using a multiscale plume-merging methodology that can efficiently represent complex fire fronts. The plume velocity is then superimposed on the ambient winds and the wind solver enforces conservation of mass on the combined field, which is then fed into the ROS model and iterated on until convergence. QES-Fire’s ability to represent plume rise is evaluated by comparing its results with those from an atmospheric large-eddy simulation (LES) model. Additionally, the model is compared with data from the FireFlux II field experiment. QES-Fire agrees well with both the LES and field experiment data, with domain-integrated buoyancy fluxes differing by less than 17% between LES and QES-Fire and less than a 10% difference in the ROS between QES-Fire and FireFlux II data.

Background Modelling of fire front progression is challenging due to the large range of spatial and temporal scales involved in the interactions between the atmosphere and fire fronts. Further modelling complications arise when heterogeneous terrain and fuels are considered. Aims The aim of this study was to create a new parameterisation for wildfire-induced winds that accounts for the effects of heterogeneous terrain and fuels within the QES-Fire modelling framework – a fast-response wildfire model. Methods QES-Fire’s new turbulent plume merging model allows for distinct plumes to be merged together from fires burning in heterogeneous terrain with heterogeneous fuels. Additionally, fuel inputs from the LANDFIRE database developed for the Rothermel rate of spread (ROS) model, are translated to the Balbi ROS model. Key results The model was evaluated against the forested RxCADRE field experiment, with and without the effects of heterogeneity. Inclusion of heterogeneity reduced the relative error in burned area from 36 to 6%. Conclusions Small variations in terrain and fuel heterogeneity lead to large errors in rate and direction of fire front spread. Implications The modelled effects of terrain and fuel heterogeneity indicated the importance of capturing the complex coupled wildfire–atmospheric dynamics at the fire front.