Visualization of Flagella during Bacterial Swarming

When cells of Escherichia coli are grown in broth and suspended at low density in a motility medium, they swim independently, exploring a homogeneous, isotropic environment. Cell trajectories and the way in which these trajectories are determined by flagellar dynamics are well understood. When cells are grown in a rich medium on agar instead, they elongate, produce more flagella, and swarm. They move in coordinated packs within a thin film of fluid, in intimate contact with one another and with two fixed surfaces, a surfactant monolayer above and an agar matrix below: they move in an inhomogeneous, anisotropic environment. Here we examine swarm-cell trajectories and ways in which these trajectories are determined by flagellar motion, visualizing the cell bodies by phase-contrast microscopy and the flagellar filaments by fluorescence microscopy. We distinguish four kinds of tracks, defining stalls, reversals, lateral movement, and forward movement. When cells are stalled at the edge of a colony, they extend their flagellar filaments outwards, moving fluid over the virgin agar; when cells reverse, changes in filament chirality play a crucial role; when cells move laterally, they are pushed sideways by adjacent cells; and when cells move forward, they are pushed by flagellar bundles in the same way as when they are swimming in bulk aqueous media. These maneuvers are described in this report.Molecular and Cellular Biolog

Non-equilibrium raft-like membrane domains under continuous recycling

We present a model for the kinetics of spontaneous membrane domain (raft) assembly that includes the effect of membrane recycling ubiquitous in living cells. We show that the domains have a broad power-law distribution with an average radius that scales with the 1/4 power of the domain lifetime when the line tension at the domain edges is large. For biologically reasonable recycling and diffusion rates the average domain radius is in the tens of nm range, consistent with observations. This represents one possible link between signaling (involving rafts) and traffic (recycling) in cells. Finally, we present evidence that suggests that the average raft size may be the same for all scale-free recycling schemes.Comment: 8 pages, 5 figure

Empirical and Bayesian approaches to fossil only divergence times: A study across three reptile clades

Estimating divergence times on phylogenies is critical in paleontological and neontological studies. Chronostratigraphically-constrained fossils are the only direct evidence of absolute timing of species divergence. Strict temporal calibration of fossil-only phylogenies provides minimum divergence estimates, and various methods have been proposed to estimate divergences beyond these minimum values. We explore the utility of simultaneous estimation of tree topology and divergence times using BEAST tip-dating on datasets consisting only of fossils by using relaxed morphological clocks and birth-death tree priors that include serial sampling (BDSS) at a constant rate through time. We compare BEAST results to those from the traditional maximum parsimony (MP) and undated Bayesian inference (BI) methods. Three overlapping datasets were used that span 250 million years of archosauromorph evolution leading to crocodylians. The first dataset focuses on early Sauria (31 taxa, 240 chars.), the second on early Archosauria (76 taxa, 400 chars.) and the third on Crocodyliformes (101 taxa, 340 chars.). For each dataset three time-calibrated trees (timetrees) were calculated: a minimum-age timetree with node ages based on earliest occurrences in the fossil record; a ‘smoothed’ timetree using a range of time added to the root that is then averaged over zero-length internodes; and a tip-dated timetree. Comparisons within datasets show that the smoothed and tip-dated timetrees provide similar estimates. Only near the root node do BEAST estimates fall outside the smoothed timetree range. The BEAST model is not able to overcome limited sampling to correctly estimate divergences considerably older than sampled fossil occurrence dates. Conversely, the smoothed timetrees consistently provide node-ages far older than the strict dates or BEAST estimates for morphologically conservative sister-taxa when they sit on long ghost lineages. In this latter case, the relaxed-clock model appears to be correctly moderating the node-age estimate based on the limited morphological divergence. Topologies are generally similar across analyses, but BEAST trees for crocodyliforms differ when clades are deeply nested but contain very old taxa. It appears that the constant-rate sampling assumption of the BDSS tree prior influences topology inference by disfavoring long, unsampled branches.AHT was supported under National Science Foundation Awards EAR 1349654 and DEB 1257485. ACP was supported under an National Science Foundation Doctoral Dissertation Improvement Grant Award (DEB 1501851) to AHT and ACP. NJM was supported by a NIMBioS fellowship under National Science Foundation Award #EFJ0832858, Australian Research Council DECRA fellowship DE150101773, and his work on BEASTmasteR began while supported by National Science Foundation 0919124

PIK3CA mutation enrichment and quantitation from blood and tissue

PIK3CA is one of the two most frequently mutated genes in breast cancers, occurring in 30-40% of cases. Four frequent 'hotspot' PIK3CA mutations (E542K, E545K, H1047R and H1047L) account for 80-90% of all PIK3CA mutations in human malignancies and represent predictive biomarkers. Here we describe a PIK3CA mutation specific nuclease-based enrichment assay, which combined with a low-cost real-time qPCR detection method, enhances assay detection sensitivity from 5% for E542K and 10% for E545K to 0.6%, and from 5% for H1047R to 0.3%. Moreover, we present a novel flexible prediction method to calculate initial mutant allele frequency in tissue biopsy and blood samples with low mutant fraction. These advancements demonstrated a quick, accurate and simple detection and quantitation of PIK3CA mutations in two breast cancer cohorts (first cohort n = 22, second cohort n = 25). Hence this simple, versatile and informative workflow could be applicable for routine diagnostic testing where quantitative results are essential, e.g. disease monitoring subject to validation in a substantial future study

The impact of air-sea coupling and ocean biases on the seasonal cycle of southern West African precipitation

The biannual seasonal rainfall regime over the southern part of West Africa is characterised by two wet seasons, separated by the `Little Dry Season' in July-August. Lower rainfall totals during this intervening dry season may be detrimental for crop yields over a region with a dense population that depends on agricultural output. Coupled Model Intercomparison Project Phase 5 (CMIP5) models do not correctly capture this seasonal regime, and instead generate a single wet season, peaking at the observed timing of the Little Dry Season. Hence, the realism of future climate projections over this region is questionable. Here, the representation of the Little Dry Season in coupled model simulations is investigated, to elucidate factors leading to this misrepresentation. The Global Ocean Mixed Layer configuration of the Met Office Unified Model is particularly useful for exploring this misrepresentation, as it enables separating the effects of coupled model ocean biases in different ocean basins while maintaining air-sea coupling. Atlantic Ocean SST biases cause the incorrect seasonal regime over southern West Africa.Upper level descent in August reduces ascent along the coastline, which is associated with the observed reduction in rainfall during the Little Dry Season. When coupled model Atlantic Ocean biases are introduced, ascent over the coastline is deeper and rainfall totals are higher during July-August. Hence, this study indicates detrimental impacts introduced by Atlantic Ocean biases, and highlights an area of model development required for production of meaningful climate change projections over the West Africa region

Electroconvulsive Therapy Response in Major Depressive Disorder: a Pilot Functional Network Connectivity Resting State FMRI Investigation

Major depressive disorder (MDD) is associated with increased functional connectivity in specific neural networks. Electroconvulsive therapy (ECT), the gold-standard treat- ment for acute, treatment-resistant MDD, but temporal dependencies between networks associated with ECT response have yet to be investigated. In the present longitudinal, case–control investigation, we used independent component analysis to identify distinct networks of brain regions with temporally coherent hemodynamic signal change and func- tional network connectivity (FNC) to assess component time course correlations across these networks. MDD subjects completed imaging and clinical assessments immediately prior to the ECT series and a minimum of 5 days after the last ECT treatment. We focused our analysis on four networks affected in MDD: the subcallosal cingulate gyrus, default mode, dorsal lateral prefrontal cortex, and dorsal medial prefrontal cortex (DMPFC). In an older sample of ECT subjects (n = 12) with MDD, remission associated with the ECT series reverses the relationship from negative to positive between the posterior default mode (p_DM) and two other networks: the DMPFC and left dorsal lateral prefrontal cortex (l_DLPFC). Relative to demographically healthy subjects (n = 12), the FNC between the p_DM areas and the DMPFC normalizes with ECT response. The FNC changes following treatment did not correlate with symptom improvement; however, a direct comparison between ECT remitters and non-remitters showed the pattern of increased FNC between the p_DM and l_DLPFC following ECT to be specific to those who responded to the treat- ment.The differences between ECT remitters and non-remitters suggest that this increased FNC between p_DM areas and the left dorsolateral prefrontal cortex is a neural correlate and potential biomarker of recovery from a depressed episode

Relationship of PIK3CA mutation and pathway activity with antiproliferative response to aromatase inhibition

INTRODUCTION: PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit α) somatic mutations are the most common genetic alteration in breast cancer (BC). Their prognostic value and that of the phosphatidylinositol 3-kinase (PI3K) pathway in BC remains only partly defined. The effect of PIK3CA mutations and alterations of the PI3K pathway on the antiproliferative response to aromatase inhibitor treatment was determined. METHODS: The Sequenom MassARRAY System was used to determine the presence of 20 somatic mutations across the PIK3CA gene in 85 oestrogen receptor–positive (ER+) BC patients treated with 2 weeks of anastrozole before surgery. Whole-genome expression profiles were used to interrogate gene signatures (GSs) associated with the PI3K pathway. Antiproliferative activity was assessed by the change in Ki67 staining between baseline and surgery. Three GSs representing the PI3K pathway were assessed (PIK3CA-GS (Loi), PI3K-GS (Creighton) and PTEN-loss-GS (Saal)). RESULTS: In our study sample, 29% of tumours presented with either a hotspot (HS, 71%) or a nonhotspot (non-HS, 29%) PIK3CA mutation. Mutations were associated with markers of good prognosis such as progesterone receptor positivity (PgR+) (P = 0.006), low grade (P = 0.028) and luminal A subtype (P = 0.039), with a trend towards significance with degree of ER positivity (P = 0.051) and low levels of Ki67 (P = 0.051). Non-HS mutations were associated with higher PgR (P = 0.014) and ER (P < 0.001) expression than both wild-type (WT) and HS-mutated samples, whereas neither biomarker differed significantly between WT and HS mutations or between HS and non-HS mutations. An inverse correlation was found between the Loi signature and both the Creighton and Saal signatures, and a positive correlation was found between the latter signatures. Lower pretreatment Ki67 levels were observed in mutation compared with WT samples (P = 0.051), which was confirmed in an independent data set. Mutation status did not predict change in Ki67 in response to 2 weeks of anastrozole treatment; there was no significant difference between HS and non-HS mutations in this regard. CONCLUSIONS: PIK3CA mutations are associated with classical markers of good prognosis and signatures of PI3K pathway activity. The presence of a PIK3CA mutation does not preclude a response to neoadjuvant anastrozole treatment