Twitching motility-mediated biofilm expansion is a complex, multicellular behavior that enables the active colonization of surfaces by many species of bacteria. In this study we have explored the emergence of intricate network patterns of interconnected trails that form in actively expanding biofilms of Pseudomonas aeruginosa. We have used high-resolution, phase-contrast time-lapse microscopy and developed sophisticated computer vision algorithms to track and analyze individual cell movements during expansion of P. aeruginosa biofilms. We have also used atomic force microscopy to examine the topography of the substrate underneath the expanding biofilm. Our analyses reveal that at the leading edge of the biofilm, highly coherent groups of bacteria migrate across the surface of the semisolid media and in doing so create furrows along which following cells preferentially migrate. This leads to the emergence of a network of trails that guide mass transit toward the leading edges of the biofilm. We have also determined that extracellular DNA (eDNA) facilitates efficient traffic flow throughout the furrow network by maintaining coherent cell alignments, thereby avoiding traffic jams and ensuring an efficient supply of cells to the migrating front. Our analyses reveal that eDNA also coordinates the movements of cells in the leading edge vanguard rafts and is required for the assembly of cells into the "bulldozer" aggregates that forge the interconnecting furrows. Our observations have revealed that large-scale self-organization of cells in actively expanding biofilms of P. aeruginosa occurs through construction of an intricate network of furrows that is facilitated by eDNA.collective behavior | t4p | type IV pili | tfp | swarming

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Bacteria form biofilms to facilitate colonization of biotic and abiotic surfaces, and biofilm formation on indwelling medical devices is a common cause of hospital-acquired infection. Although it is well-recognized that the exopolysaccharide capsule is one of the key bacterial components for biofilm formation, the underlying biophysical mechanism is poorly understood. In the present study, nanomechanical measurements of wild type and specific mutants of the pathogen, Klebsiella pneumoniae, were performed in situ using atomic force microscopy (AFM). Theoretical modeling of the mechanical data and static microtiter plate biofilm assays show that the organization of the capsule can influence bacterial adhesion, and thereby biofilm formation. The capsular organization is affected by the presence of type 3 fimbriae. Understanding the biophysical mechanisms for the impact of the structural organization of the bacterial polysaccharide capsule on biofilm formation will aid the development of strategies to prevent biofilm formation.

Highly efficient magnetic sewage sludge biochar (MSSBC) discloses feasible fabrication process with lower production cost, superior adsorption capacity, usage of waste sewage sludge as resource, selected by external magnetic field and exceptional regeneration property. 2gL MSSBC exhibited a high adsorption capacity of 249.00mgg in 200ppmPb(II) and the lead-MSSBC equilibrium was achieved within one hour, owing to the existence of the copious active sites. The adsorption kinetics was well described by the pseudo-second-order model while the adsorption isotherm could be fitted by Langmuir model. Mechanism study demonstrated the adsorption involved electrostatic attraction, ion exchange, inner-sphere complexation and formation of co-precipitates at the surface of MSSBC. Additionally, adsorption performance maintained remarkable in a broad pH window. These outcomes demonstrated the promising waste resource utilization by a feasible approach that turns the solid waste of sewage sludge into biochar adsorbent with auspicious applications in elimination of Pb(II) from wastewater.

In recent years, landslide hazard assessment has played an important role in developing land utilization regulations aimed at minimizing the loss of lives and damage to property. A variety of approaches has been used in landslide assessment and these can be classified into qualitative factor overlay, statistical models, geotechnical process models, etc. However, there is little work on the satisfactory integration of these models with geographic information systems (GIS) to support slope management and landslide hazard mitigation. This paper deals with several aspects of landslide hazard assessment by presenting a focused review of GIS-based landslide hazard assessment: it starts with a framework for GIS-based assessment of landslide hazard; continues with a critical review of the state of the art in using GIS and digital elevation models (DEM) for mapping and modelling landslide hazards; and concludes with a description of an integrated system for effective landslide hazard assessment and zonation incorporating artificial intelligence and data mining technology in a GIS-based framework of knowledge discovery.