Intercellular adhesion promotes clonal mixing in growing bacterial populations

Dense bacterial communities, known as biofilms, can have functional spatial organization driven by self-organizing chemical and physical interactions between cells, and their environment. In this work, we investigated intercellular adhesion, a pervasive property of bacteria in biofilms, to identify effects on the internal structure of bacterial colonies. We expressed the self-recognizing ag43 adhesin protein in Escherichia coli to generate adhesion between cells, which caused aggregation in liquid culture and altered microcolony morphology on solid media. We combined the adhesive phenotype with an artificial colony patterning system based on plasmid segregation, which marked clonal lineage domains in colonies grown from single cells. Engineered E. coli were grown to colonies containing domains with varying adhesive properties, and investigated with microscopy, image processing and computational modelling techniques. We found that intercellular adhesion elongated the fractal-like boundary between cell lineages only when both domains within the colony were adhesive, by increasing the rotational motion during colony growth. Our work demonstrates that adhesive intercellular interactions can have significant effects on the spatial organization of bacterial populations, which can be exploited for biofilm engineering. Furthermore, our approach provides a robust platform to study the influence of intercellular interactions on spatial structure in bacterial populations.For this research, A.K. and T.J.R. were supported by the EC FP7project no. 612146 (PLASWIRES) awarded to J.P.H., A.K. has also been supported by a BBSRC CASE studentship in partnership with Microsoft Research, F.F. was supported by the UK Biotechnological and Biological Sciences Research Council (BBSRC) Synthetic Biology Research Centre ‘OpenPlant’ award (BB/L014130/1), CONICYT-PAI/Concurso Nacional de Apoyo al Retorno de Investigadores/as desde el Extranjero Folio 182130027, Fondo de Desarrollo de Areas Prioritarias (FONDAP) Center for Genome Regulation 1(15090007), Millennium Nucleus Center for Plant Systems and Synthetic Biology 1(NC130030) and Fondecyt Iniciación 111140776. T.J.R. has also been supported by Fondecyt Iniciación 11161046

Design principles for spatio-temporal organisation of cell populations

Non UBCUnreviewedAuthor affiliation: Universidad Católica de ChileFacult

Effects of intrinsic and extrinsic noise can accelerate juxtacrine pattern formation

Epithelial pattern formation is an important phenomenon that, for example, has roles in embryogenesis, development and wound-healing. The ligand Epithelial Growth Factor (EGF) and its receptor EGF-R, constitute a system that forms lateral induction patterns by juxtacrine signalling—binding of membrane-bound ligands to receptors on neighbouring cells. Owen et al. developed a generic ordinary differential equation model of juxtacrine lateral induction that exhibits stable patterning under some conditions. The model predicts relatively slow pattern formation. We examine here the effects of both intrinsic and extrinsic cellular noise arising from the stochastic treatment of this model, and show that this noise could have an accelerating effect on the patterning process

Leveraging TLS as a Calibration and Validation Tool for MLS and ULS Mapping of Savanna Structure and Biomass at Landscape-Scales

Savanna ecosystems are challenging to map and monitor as their vegetation is highly dynamic in space and time. Understanding the structural diversity and biomass distribution of savanna vegetation requires high-resolution measurements over large areas and at regular time intervals. These requirements cannot currently be met through field-based inventories nor spaceborne satellite remote sensing alone. UAV-based remote sensing offers potential as an intermediate scaling tool, providing acquisition flexibility and cost-effectiveness. Yet despite the increased availability of lightweight LiDAR payloads, the suitability of UAV-based LiDAR for mapping and monitoring savanna 3D vegetation structure is not well established. We mapped a 1 ha savanna plot with terrestrial-, mobile- and UAV-based laser scanning (TLS, MLS, and ULS), in conjunction with a traditional field-based inventory (n = 572 stems > 0.03 m). We treated the TLS dataset as the gold standard against which we evaluated the degree of complementarity and divergence of structural metrics from MLS and ULS. Sensitivity analysis showed that MLS and ULS canopy height models (CHMs) did not differ significantly from TLS-derived models at spatial resolutions greater than 2 m and 4 m respectively. Statistical comparison of the resulting point clouds showed minor over- and under-estimation of woody canopy cover by MLS and ULS, respectively. Individual stem locations and DBH measurements from the field inventory were well replicated by the TLS survey (R2 = 0.89, RMSE = 0.024 m), which estimated above-ground woody biomass to be 7% greater than field-inventory estimates (44.21 Mg ha−1 vs 41.08 Mg ha−1). Stem DBH could not be reliably estimated directly from the MLS or ULS, nor indirectly through allometric scaling with crown attributes (R2 = 0.36, RMSE = 0.075 m). MLS and ULS show strong potential for providing rapid and larger area capture of savanna vegetation structure at resolutions suitable for many ecological investigations; however, our results underscore the necessity of nesting TLS sampling within these surveys to quantify uncertainty. Complementing large area MLS and ULS surveys with TLS sampling will expand our options for the calibration and validation of multiple spaceborne LiDAR, SAR, and optical missions

Leveraging TLS as a Calibration and Validation Tool for MLS and ULS Mapping of Savanna Structure and Biomass at Landscape-Scales

Savanna ecosystems are challenging to map and monitor as their vegetation is highly dynamic in space and time. Understanding the structural diversity and biomass distribution of savanna vegetation requires high-resolution measurements over large areas and at regular time intervals. These requirements cannot currently be met through field-based inventories nor spaceborne satellite remote sensing alone. UAV-based remote sensing offers potential as an intermediate scaling tool, providing acquisition flexibility and cost-effectiveness. Yet despite the increased availability of lightweight LiDAR payloads, the suitability of UAV-based LiDAR for mapping and monitoring savanna 3D vegetation structure is not well established. We mapped a 1 ha savanna plot with terrestrial-, mobile- and UAV-based laser scanning (TLS, MLS, and ULS), in conjunction with a traditional field-based inventory (n = 572 stems > 0.03 m). We treated the TLS dataset as the gold standard against which we evaluated the degree of complementarity and divergence of structural metrics from MLS and ULS. Sensitivity analysis showed that MLS and ULS canopy height models (CHMs) did not differ significantly from TLS-derived models at spatial resolutions greater than 2 m and 4 m respectively. Statistical comparison of the resulting point clouds showed minor over- and under-estimation of woody canopy cover by MLS and ULS, respectively. Individual stem locations and DBH measurements from the field inventory were well replicated by the TLS survey (R2 = 0.89, RMSE = 0.024 m), which estimated above-ground woody biomass to be 7% greater than field-inventory estimates (44.21 Mg ha−1 vs 41.08 Mg ha−1). Stem DBH could not be reliably estimated directly from the MLS or ULS, nor indirectly through allometric scaling with crown attributes (R2 = 0.36, RMSE = 0.075 m). MLS and ULS show strong potential for providing rapid and larger area capture of savanna vegetation structure at resolutions suitable for many ecological investigations; however, our results underscore the necessity of nesting TLS sampling within these surveys to quantify uncertainty. Complementing large area MLS and ULS surveys with TLS sampling will expand our options for the calibration and validation of multiple spaceborne LiDAR, SAR, and optical missions

Recollection and familiarity in dense hippocampal amnesia: A case study.

In the amnesia literature, disagreement exists over whether anterograde amnesia involves recollective-based recognition processes and/or familiarity-based ones depending on whether the anatomical damage is restricted to the hippocampus or also involves adjacent areas, particularly the entorhinal and perirhinal cortices. So far, few patients with well documented anatomical lesions and detailed assessment of recollective and recognition performance have been described. We report a comprehensive neuroanatomical assessment and detailed investigation of the anterograde memory functions of a previously described severe amnesic patient (VC). The results of four previously published neuroradiological investigations (resting PET, qualitative MRIs, volumetric MRI and functional MRI) together with the results of two new investigations (voxel-based morphometry and magnetic resonance spectroscopy) are presented. The consistent finding across these different qualitative and quantitative examinations of VC's brain has shown that there is primarily structural and functional abnormality located selectively in the hippocampus bilaterally. Marked impairments in both verbal and non-verbal recall and recognition standardized memory tests were documented in the context of VC's intact cognitive profile and normal semantic memory. The results of five new experimental recognition memory tests tapping recollection and familiarity using verbal, topographical (buildings and landscapes) and unknown human faces memoranda revealed striking differential effects according to the type of stimuli used. A receiver operating characteristic analysis revealed that VC's recollective- and familiarity-based recognition processes were well preserved for unknown human faces. In contrast, recollective-based recognition for verbal and topographical material was at floor. Familiarity-based recognition was also impaired, significantly below controls for verbal and buildings memoranda and quite weak, although not reaching significance, for landscapes. These data suggest that the hippocampus is involved in recollective processes of verbal and topographical stimuli. It also plays an appreciable role in familiarity processes for these stimuli. However, recollection and familiarity of human faces appear not to depend on this region