Fabrication and Use of MicroEnvironment microArrays (MEArrays)

The interactions between cells and their surrounding microenvironment have functional consequences for cellular behaviour. On the single cell level, distinct microenvironments can impose differentiation, migration, and proliferation phenotypes, and on the tissue level the microenvironment processes as complex as morphogenesis and tumorigenesis¹. Not only do the cell and molecular contents of microenvironments impact the cells within, but so do the elasticity² and geometry³ of the tissue. Defined as the sum total of cell-cell, -ECM, and -soluble factor interactions, in addition to physical characteristics, the microenvironment is complex. The phenotypes of cells within a tissue are partially due to their genomic content and partially due to the combinatorial interactions with the microenviroment. A major challenge is to link specific combinations of microenvironmental components with distinctive behaviours.Here, we present the microenvironment microarray (MEArray) platform for cell-based functional screening of interactions with combinatorial microenvironments⁴. The method allows for simultaneous control of the molecular composition and the elastic modulus, and combines the use of widely available microarray and micropatterning technologies. MEArray screens require as few as 10,000 cells per array, which facilitates functional studies of rare cell types such as adult progenitor cells. A limitation of the technology is that entire tissue microenvironments cannot be completely recapitulated on MEArrays. However, comparison of responses in the same cell type to numerous related microenvironments, for instance pairwise combinations of ECM proteins that characterize a given tissue, will provide insights into how microenvironmental components elicit tissue-specific functional phenotypes.MEArrays can be printed using a wide variety of recombinant growth factors, cytokines, and purified ECM proteins, and combinations thereof. The platform is limited only by the availability of specific reagents. MEArrays are amenable to time-lapsed analysis, but most often are used for end point analyses of cellular functions that are measureable with fluorescent probes. For instance, DNA synthesis, apoptosis, acquisition of differentiated states, or production of specific gene products are commonly measured. Briefly, the basic flow of an MEArray experiment is to prepare slides coated with printing substrata and to prepare the master plate of proteins that are to be printed. Then the arrays are printed with a microarray robot, cells are allowed to attach, grow in culture, and then are chemically fixed upon reaching the experimental endpoint. Fluorescent or colorimetric assays, imaged with traditional microscopes or microarray scanners, are used to reveal relevant molecular and cellular phenotypes (Figure 1).     

No Evidence‐Based Restoration Without a Sound Evidence Base: A Reply to Guldemond et al.

Evidence‐based practice is not possible without an evidence base. Guldemond et al. confuse our attempt at assessing the status of the evidence base of restoration programs in South Africa with attempting to assess whether restoration is evidence‐based. While we fully agree with them that there is a need to assess whether practitioners use evidence in their decision‐making, we assert that use of evidence is the last step in the evidence‐based approach. It is preceded by the generation (and documentation) of evidence through baseline condition assessment, proper goal setting, sound monitoring of the impacts of the chosen intervention as well as effective dissemination of resulting evidence. To answer the question whether restoration is evidence‐based would require the assessment of all stages from generation to use. We chose to start at the beginning, a logical place to start.     

Taxonomic and functional homogenization of an endemic desert fish fauna

Aim The highly endemic fishes of the arid Southwest USA have been heavily impacted by human activities resulting in one of the most threatened fish faunas in the world. The aim of this study was to examine the patterns and drivers of taxonomic and functional beta diversity of freshwater fish in the Lower Colorado River Basin across the 20th century. Location Lower Colorado River Basin (LCRB). Methods The taxonomic and functional similarities of watersheds were quantified to identify patterns of biotic homogenization or differentiation over the period 1900–1999. Path analysis was used to identify the relative influence of dam density, urban land use, precipitation regimes and non‐native species richness on observed changes in fish faunal composition. Results The fish fauna of the LCRB has become increasingly homogenized, both taxonomically (1.1% based on β_sim index) and functionally (6.2% based on Bray–Curtis index), over the 20th century. The rate of homogenization varied substantially; range declines of native species initially caused taxonomic differentiation (?7.9% in the 1960s), followed by marginal homogenization (observed in the 1990s) in response to an influx of non‐native species introductions. By contrast, functional homogenization of the basin was evident considerably earlier (in the 1950s) because of the widespread introduction of non‐native species sharing similar suites of biological traits. Path analysis revealed that both taxonomic and functional homogenization were positively related to the direct and indirect (facilitation by dams and urbanization) effects of non‐native species richness. Main conclusions Our study simultaneously examines rates of change in multiple dimensions of the homogenization process. For the endemic fish fauna of the LCRB, we found that the processes of taxonomic and functional homogenization are highly dynamic over time, varying both in terms of the magnitude and rate of change over the 20th century.     

Nonparametric Analysis of Thermal Proteome Profiles Reveals Novel Drug-binding Proteins*

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Highlights

• •Method for the analysis of response curves from thermal proteome profiling (TPP).
• •NPARC uses nonparametric statistics and provides false discovery-rate (FDR) control.
• •Increased proteome coverage and sensitivity to identify drug-binding proteins.

     

Ecosystem productivity can be predicted from potential relative growth rate and species abundance

We show that ecosystem-specific aboveground net primary productivity (SANPP, g g⁻¹ day⁻¹, productivity on a per gram basis) can be predicted from species-level measures of potential relative growth rate (RGR_max), but only if RGR_max is weighted according to the species' relative abundance. This is in agreement with Grime's mass-ratio hypothesis. Productivity was measured in 12 sites in a French Mediterranean post-agricultural succession, while RGR_max was measured on 26 of the most abundant species from this successional sere, grown hydroponically. RGR_max was only weakly correlated ( r ² = 0.12, P  < 0.05) with field age when species abundance was not considered, but the two variables were strongly correlated ( r ² = 0.81, P  < 0.001) when the relative abundance of species in each field was taken into account. SANPP also decreased significantly with field age. This resulted in a tight relationship ( r ² = 0.77, P  < 0.001) between productivity and RGR_max weighted according to species relative biomass contribution. Our study shows that scaling-up from the potential properties of individual species is possible, and that information on potential and realized species traits can be integrated to predict ecosystem functioning.     

Trade-off assessments between environmental and economic indicators in cropping systems of Pampa region (Argentina)

An overall sustainability assessment should include changes in the economic return, the social benefits and the human intervention on the biophysical resources in order to highlight potential trade-off or synergies among them. In this work, we studied the performance of 36 cropping systems (CS) of the Pampa region, Argentina, which include three different crops, three increasing levels of technology adoption in four contrasting site conditions. For each CS, we simultaneously assessed 1) the ecosystem energy flow using the emergy synthesis; 2) the pesticide ecotoxicity using a simple dose-response model; and 3) the economic profit, in order to evaluate the influence of crop identity, technological level, and site location on the indicators values as well as to detect potential trade-offs between indicators. Results revealed that maize crop entailed the most sustainable indicator profile by exhibiting relative high emergy return, low non-renewable emergy use, low pesticide ecotoxicity, and high gross income. In addition, results showed a significant trade-off between economic profit and ecotoxicological risk in the CS studied. Further studies should be conducted for including more contrasting indicators in order to explore the potential trade-off among other ecosystem components as a promising way to identify sustainable crop management regimes for different production zones.     

Host plant effects on the functional response of Stethorus gilvifrons to strawberry spider mites

The functional response of adult females of the coccinellid beetle Stethorus gilvifrons Mulsant to juveniles of strawberry spider mite, Tetranychus turkestani Ugarov & Nikolski was determined on cowpea, castor bean and cucumber leaves in the laboratory at 25°C and a 14 h L: 10 h D photoperiod. Beetles were isolated singly for 24 h in 9-cm Petri dishes with either 2, 4, 8, 16, 32, 64, or 128 nymphal stages of T. turkestani. Results showed a typical type II response on all plants tested, with up to 110.7, 100.8, and 53.0 prey attacked when 128 nymphal stages were provided on cowpea, castor bean, and cucumber leaves, respectively. Based on the Rogers random attack equation, the highest estimated attack rate and the lowest handling time were obtained on cowpea. It was therefore concluded that the host plant species can affect the predation rate and functional response components of S. gilvifrons, a specific and effective predator of spider mites.