Characterisation of the Physical Composition and Microbial Community Structure of Biofilms within a Model Full-Scale Drinking Water Distribution System

Within drinking water distribution systems (DWDS), microorganisms form multi-species biofilms on internal pipe surfaces. A matrix of extracellular polymeric substances (EPS) is produced by the attached community and provides structure and stability for the biofilm. If the EPS adhesive strength deteriorates or is overcome by external shear forces, biofilm ismobilised into the water potentially leading to degradation of water quality. However, little is known about the EPS within DWDS biofilms or how this is influenced by community composition or environmental parameters, because of the complications in obtaining biofilm samples and the difficulties in analysing EPS. Additionally, although biofilms may contain various microbial groups, research commonly focuses solely upon bacteria. This research applies an EPS analysis method based upon fluorescent confocal laser scanning microscopy (CLSM) in combination with digital image analysis (DIA), to concurrently characterize cells and EPS (carbohydrates and proteins) within drinking water biofilms from a full-scale DWDS experimental pipe loop facility with representative hydraulic conditions. Application of the EPS analysismethod, alongside DNA fingerprinting of bacterial, archaeal and fungal communities, was demonstrated for biofilms sampled from different positions around the pipeline, after 28 days growth within the DWDS experimental facility. The volume of EPS was 4.9 times greater than that of the cells within biofilms, with carbohydrates present as the dominant component. Additionally, the greatest proportion of EPS was located above that of the cells. Fungi and archaea were established as important components of the biofilm community, although bacteria were more diverse.Moreover, biofilms from different positions were similar with respect to community structure and the quantity, composition and three-dimensional distribution of cells and EPS, indicating that active colonisation of the pipe wall is an important driver inmaterial accumulation within the DWDS

Allelic Exchange of Pheromones and Their Receptors Reprograms Sexual Identity in Cryptococcus neoformans

Cell type specification is a fundamental process that all cells must carry out to ensure appropriate behaviors in response to environmental stimuli. In fungi, cell identity is critical for defining “sexes” known as mating types and is controlled by components of mating type (MAT) loci. MAT–encoded genes function to define sexes via two distinct paradigms: 1) by controlling transcription of components common to both sexes, or 2) by expressing specially encoded factors (pheromones and their receptors) that differ between mating types. The human fungal pathogen Cryptococcus neoformans has two mating types (a and α) that are specified by an extremely unusual MAT locus. The complex architecture of this locus makes it impossible to predict which paradigm governs mating type. To identify the mechanism by which the C. neoformans sexes are determined, we created strains in which the pheromone and pheromone receptor from one mating type (a) replaced the pheromone and pheromone receptor of the other (α). We discovered that these “αa” cells effectively adopt a new mating type (that of a cells); they sense and respond to α factor, they elicit a mating response from α cells, and they fuse with α cells. In addition, αa cells lose the α cell type-specific response to pheromone and do not form germ tubes, instead remaining spherical like a cells. Finally, we discovered that exogenous expression of the diploid/dikaryon-specific transcription factor Sxi2a could then promote complete sexual development in crosses between α and αa strains. These data reveal that cell identity in C. neoformans is controlled fully by three kinds of MAT–encoded proteins: pheromones, pheromone receptors, and homeodomain proteins. Our findings establish the mechanisms for maintenance of distinct cell types and subsequent developmental behaviors in this unusual human fungal pathogen

The Crowdsourced Replication Initiative: Investigating Immigration and Social Policy Preferences. Executive Report.

In an era of mass migration, social scientists, populist parties and social movements raise concerns over the future of immigration-destination societies. What impacts does this have on policy and social solidarity? Comparative cross-national research, relying mostly on secondary data, has findings in different directions. There is a threat of selective model reporting and lack of replicability. The heterogeneity of countries obscures attempts to clearly define data-generating models. P-hacking and HARKing lurk among standard research practices in this area.This project employs crowdsourcing to address these issues. It draws on replication, deliberation, meta-analysis and harnessing the power of many minds at once. The Crowdsourced Replication Initiative carries two main goals, (a) to better investigate the linkage between immigration and social policy preferences across countries, and (b) to develop crowdsourcing as a social science method. The Executive Report provides short reviews of the area of social policy preferences and immigration, and the methods and impetus behind crowdsourcing plus a description of the entire project. Three main areas of findings will appear in three papers, that are registered as PAPs or in process

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

Strains.

<p>Strains.</p

α x α^a crosses proceed through sexual development only in the presence of Sxi2a.

<p>(A) Sexual development assays were carried out on V8 for 72 hours, and the peripheries of crosses are shown under 200× magnification. Panels: 1) <b>a</b> x α, 2) <b>a</b> x α<i>^mfαΔ</i>, 3) <b>a</b> x α<i>^{mfαΔ, STE3a}</i>, 4) <b>a</b> x α<b>^a</b>, 5) α x α, 6) α x α<i>^mfαΔ</i>, 7) α x α<i>^{mfαΔ, STE3}</i>^{<b><i>a</i></b>}, 8) α x α<b>^a</b>, 9) <b>a </b><i>sxi2</i><b><i>a</i></b><i>Δ</i> x α, 10) α <i>sxi1αΔ</i> + <i>SXI2</i><b><i>a</i></b> x α<b>^a</b>. Complete sexual development is observed only in panels 1 and 10. (B) Dikaryotic filaments are produced in the α <i>sxi1αΔ</i> + <i>SXI2</i><b><i>a</i></b> x α<b>^a</b> cross. Calcofluor stained filaments appear blue, and Sytox Green strained nuclei appear green. Both an <b>a</b> x α cross (left) and the α <i>sxi1αΔ</i> + <i>SXI2</i><b><i>a</i></b> x α<b>^a</b> cross (right) produce dikaryotic filaments (400× magnification). (C) Basidia and spores are produced in the α <i>sxi1αΔ</i> + <i>SXI2</i><b><i>a</i></b> x α<b>^a</b> cross. High resolution microscopy reveals the formation of basidia and spores from an <b>a</b> x α cross (left), and from the α <i>sxi1αΔ</i> + <i>SXI2</i><b><i>a</i></b> x α<b>^a</b> cross (right) (1000× magnification). (D) Addition of the <i>SXI2</i><b><i>a</i></b> gene to α<b>^a</b>/α diploids results in sexual development. Diploids were incubated on V8 for 72 hours, and test spot peripheries are shown under 200× magnification as follows: wild type <b>a</b>/α diploid (panel 1), α<b>^a</b>/α diploid (panel 2), and α<b>^a</b>/α + <i>SXI2</i><b><i>a</i></b> (panel 3).</p

α^a cells undergo α fruiting.

<p>Fruiting assays were carried out on filament agar for 14 days at room temperature in the dark. The peripheries of colonies are shown at 100× magnification. Left panel: wild type <b>a</b> cells. Middle panel: wild type α cells. Right panel: α<b>^a</b> cells.</p

Southern and northern analyses of wild-type and modified α strains.

<p>(A) Schematic of the <i>STE3</i><b><i>a</i></b>/<i>NAT</i> integration event to generate the α<i>^{mfαΔ, STE3}</i>^{<b><i>a</i></b>} strain (left). Southern blot analysis confirms a single integration of the <i>STE3</i><b><i>a</i></b><i>-NAT</i> construct into the <i>STE3α</i> locus (Lane 1: ∼3 kb wild type band. Lane 2: ∼5 kb insertion band, right). (B) Schematic of the <i>MF</i><b><i>a</i></b><i>1</i>/<i>NEO</i> construct to generate the α<b>^a</b> strain (left). Southern blot analysis reveals that 3 copies of the <i>MF</i><b><i>a</i></b><i>1</i> gene integrated into the genome. Lane 1: three wild type bands present in <b>a</b> cells. Lane 2: no <i>MF</i><b><i>a</i></b> signal in α cells. Lane 3: three randomly integrated copies of <i>MF</i><b><i>a</i></b> in α<b>^a</b> cells (right). (C) Northern blot analysis of pheromone receptors (<i>STE3</i><b><i>a</i></b> and <i>STE3α</i>) and pheromones (<i>MF</i><b><i>a</i></b> and <i>MFα</i>). Genotypes of the test strains are indicated over the panels and probes are indicated to the left. A probe to <i>GPD1</i> was used as a loading and hybridization control. Each lane contains RNA from the following strains or crosses: Lane 1 wild type <b>a</b>, Lane 2 wild type α, Lane 3 α<i>^mfαΔ</i>, Lane 4 α <i>^{mfαΔ, STE3}</i>^{<b><i>a</i></b>}, Lane 5 α<b>^a</b>, and Lane 6 <b>a</b> x α.</p

α^a cells are α cells that express a pheromone and the pheromone receptor from a cells.

<p>A schematic of pheromones and pheromone receptors produced by <b>a</b> cells (left), α cells (middle), and α<b>^a</b> cells (right) is represented. <b>a</b> cells (pink) produce the Ste3<b>a</b> pheromone receptor (pink half circle/stick structure) and MF<b>a</b> pheromones (pink squares). α cells (blue) produce the Ste3α receptor (blue Y-shaped structure) and MFα pheromones (blue circles). α<b>^a</b> cells produce only the Ste3<b>a</b> pheromone receptor and the MF<b>a</b>1 pheromone.</p