Lessons learned and recommendations in conducting solutions-driven environmental and public health research.

Solutions-driven research is a transdisciplinary approach that incorporates diverse forms of expertise to identify solutions to stakeholder-identified environmental problems. This qualitative evaluation of early solutions-driven research projects provides transferable recommendations to improve researcher and stakeholder experiences and outcomes in transdisciplinary environmental research projects. Researchers with the U.S. Environmental Protection Agency (EPA) Office of Research and Development recently piloted a solutions-driven research approach in two parallel projects; one addressing nutrient management related to coastal waters and another studying wildland fire smoke impacts on indoor air quality. Studying the experiences of those involved with these pilots can enhance the integration of researcher and experiential expertise, improving solutions-driven research outcomes. Data collection included semi-structured interviews with 17 EPA researchers and 12 other stakeholders and reflective case narratives from the authors. We used conventional content analysis to qualitatively analyze perspectives on implementing innovative engagement and research approaches in a solutions-driven process. Findings that reflect common perspectives include the importance of continuous engagement, the challenges of differing timelines and priorities for researchers and stakeholders, and the need to define consistent markers of success across researchers and stakeholders. Key lessons to improve transdisciplinary research identified from the analysis are (1) improving clarity of roles and responsibilities; (2) planning to provide sufficient, continuous project funding over multiple years; (3) expecting research needs and plans to adapt to evolving circumstances; and (4) clearly defining the end of the project.

The synthesis of xyloglucan, an abundant plant cell wall polysaccharide, requires CSLC function.

Xyloglucan (XyG) is an abundant component of the primary cell walls of most plants. While the structure of XyG has been well studied, much remains to be learned about its biosynthesis. Here we employed reverse genetics to investigate the role of Arabidopsis cellulose synthase like-C (CSLC) proteins in XyG biosynthesis. We found that single mutants containing a T-DNA in each of the five Arabidopsis CSLC genes had normal levels of XyG. However, higher-order cslc mutants had significantly reduced XyG levels, and a mutant with disruptions in all five CSLC genes had no detectable XyG. The higher-order mutants grew with mild tissue-specific phenotypes. Despite the apparent lack of XyG, the cslc quintuple mutant did not display significant alteration of gene expression at the whole-genome level, excluding transcriptional compensation. The quintuple mutant could be complemented by each of the five CSLC genes, supporting the conclusion that each of them encodes a XyG glucan synthase. Phylogenetic analyses indicated that the CSLC genes are widespread in the plant kingdom and evolved from an ancient family. These results establish the role of the CSLC genes in XyG biosynthesis, and the mutants described here provide valuable tools with which to study both the molecular details of XyG biosynthesis and the role of XyG in plant cell wall structure and function.

DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology.

The proper biogenesis, morphogenesis, and dynamics of subcellular organelles are essential to their metabolic functions. Conventional techniques for identifying, classifying, and quantifying abnormalities in organelle morphology are largely manual and time-consuming, and require specific expertise. Deep learning has the potential to revolutionize image-based screens by greatly improving their scope, speed, and efficiency. Here, we used transfer learning and a convolutional neural network (CNN) to analyze over 47,000 confocal microscopy images from Arabidopsis wild-type and mutant plants with abnormal division of one of three essential energy organelles: chloroplasts, mitochondria, or peroxisomes. We have built a deep-learning framework, DeepLearnMOR (Deep Learning of the Morphology of Organelles), which can rapidly classify image categories and identify abnormalities in organelle morphology with over 97% accuracy. Feature visualization analysis identified important features used by the CNN to predict morphological abnormalities, and visual clues helped to better understand the decision-making process, thereby validating the reliability and interpretability of the neural network. This framework establishes a foundation for future larger-scale research with broader scopes and greater data set diversity and heterogeneity.

What Goes Up Must Come Down: Integrating Air and Water Quality Monitoring for Nutrients.

Excess nitrogen and phosphorus ("nutrients") loadings continue to affect ecosystem function and human health across the U.S. Our ability to connect atmospheric inputs of nutrients to aquatic end points remains limited due to uncoupled air and water quality monitoring. Where connections exist, the information provides insights about source apportionment, trends, risk to sensitive ecosystems, and efficacy of pollution reduction efforts. We examine several issues driving the need for better integrated monitoring, including: coastal eutrophication, urban hotspots of deposition, a shift from oxidized to reduced nitrogen deposition, and the disappearance of pristine lakes. Successful coordination requires consistent data reporting; collocating deposition and water quality monitoring; improving phosphorus deposition measurements; and filling coverage gaps in urban corridors, agricultural areas, undeveloped watersheds, and coastal zones.

Ecosystem services in the Great Lakes.

A comprehensive inventory of ecosystem services across the entire Great Lakes basin is currently lacking and is needed to make informed management decisions. A greater appreciation and understanding of ecosystem services, including both use and non-use services, may have avoided misguided resource management decisions in the past that have resulted in legacies inherited by future generations. Given the interest in ecosystem services and lack of a coherent approach to addressing this topic in the Great Lakes, a summit was convened involving 28 experts working on various aspects of ecosystem services in the Great Lakes. The invited attendees spanned a variety of social and natural sciences. Given the unique status of the Great Lakes as the world's largest collective repository of surface freshwater, and the numerous stressors threatening this valuable resource, timing was propitious to examine ecosystem services. Several themes and recommendations emerged from the summit. There was general consensus that 1) a comprehensive inventory of ecosystem services throughout the Great Lakes is a desirable goal but would require considerable resources; 2) more spatially and temporally intensive data are needed to overcome our data gaps, but the arrangement of data networks and observatories must be well-coordinated; 3) trade-offs must be considered as part of ecosystem services analyses; and 4) formation of a Great Lakes Institute for Ecosystem Services, to provide a hub for research, meetings, and training is desirable. Several challenges also emerged during the summit, which are discussed in the paper.

In vivo imaging of the S-locus receptor kinase, the female specificity determinant of self-incompatibility, in transgenic self-incompatible Arabidopsis thaliana.

BACKGROUND AND AIMS: The S-locus receptor kinase (SRK), which is expressed in stigma epidermal cells, is responsible for the recognition and inhibition of 'self' pollen in the self-incompatibility (SI) response of the Brassicaceae. The allele-specific interaction of SRK with its cognate pollen coat-localized ligand, the S-locus cysteine-rich (SCR) protein, is thought to trigger a signalling cascade within the stigma epidermal cell that leads to the arrest of 'self' pollen at the stigma surface. In addition to the full-length signalling SRK receptor, stigma epidermal cells express two other SRK protein species that lack the kinase domain and whose role in the SI response is not understood: a soluble version of the SRK ectodomain designated eSRK and a membrane-tethered form designated tSRK. The goal of this study was to describe the sub-cellular distribution of the various SRK protein species in stigma epidermal cells as a prelude to visualizing receptor dynamics in response to SCR binding. METHODS: The Arabidopsis lyrata SRKb variant was tagged with the Citrine variant of yellow fluorescent protein (cYFP) and expressed in A. thaliana plants of the C24 accession, which had been shown to exhibit a robust SI response upon transformation with the SRKb-SCRb gene pair. The transgenes used in this study were designed for differential production and visualization of the three SRK protein species in stigma epidermal cells. Transgenic stigmas were analysed by pollination assays and confocal microscopy. KEY RESULTS AND CONCLUSIONS: Pollination assays demonstrated that the cYFP-tagged SRK proteins are functional and that the eSRK is not required for SI. Confocal microscopic analysis of cYFP-tagged SRK proteins in live stigma epidermal cells revealed the differential sub-cellular localization of the three SRK protein species but showed no evidence for redistribution of these proteins subsequent to incompatible pollination.

Using ecosystem services to inform decisions on U.S. air quality standards.

The ecosystem services (ES) framework provides a link between changes in a natural system's structure and function and public welfare. This systematic integration of ecology and economics allows for more consistency and transparency in environmental decision making by enabling valuation of nature's goods and services in a manner that is understood by the public. This policy analysis (1) assesses the utility of the ES conceptual framework in the context of setting a secondary National Ambient Air Quality Standard (NAAQS), (2) describes how economic valuation was used to summarize changes in ES affected by NOx and SOx in the review, and (3) uses the secondary NOxSOx NAAQS review as a case study to highlight the advantages and challenges of quantifying air pollutant effects on ES in a decision making context. Using an ES framework can benefit the decision making process by accounting for environmental, ecological, and social elements in a holistic manner. As formal quantitative linkages are developed between ecosystem structure and function and ES, this framework will increasingly allow for a clearer, more transparent link between changes in air quality and public welfare.

A transgenic self-incompatible Arabidopsis thaliana model for evolutionary and mechanistic studies of crucifer self-incompatibility.

Molecular genetic studies of self-incompatibility (SI) can be difficult to perform in non-model self-incompatible species. Recently, an Arabidopsis thaliana transgenic model was developed for analysis of the SI system that operates in the Brassicaceae by inter-species transfer of genes encoding the S-locus receptor kinase (SRK) and its ligand, the S-locus cysteine-rich (SCR) protein, which are the determinants of SI specificity in the stigma and pollen, respectively. This article reviews the various ways in which the many advantages of A. thaliana and the extensive tools and resources available in this model species have allowed the use of transgenic self-incompatible SRK-SCR plants to address long-standing issues related to the mechanism and evolution of SI in the Brassicaceae. It also presents the unexpected results of a candidate gene approach aimed at determining if genes related to genes previously reported to be involved in the SI response of Brassica and genes required for disease resistance, which exhibits many similarities to the SI response, are required for SI in A. thaliana. These various studies have provided a novel insight into the basis of specificity in the SRK-SCR interaction, the nature of the signalling cascade that culminates in the inhibition of 'self' pollen, and the physiological and morphological changes that are associated with transitions between the outbreeding and inbreeding modes of mating in the Brassicaceae.

Self-incompatibility systems: barriers to self-fertilization in flowering plants.

Flowering plants (angiosperms) are the most prevalent and evolutionarily advanced group of plants. Success of these plants is owed to several unique evolutionary adaptations that aid in reproduction: the flower, the closed carpel, double fertilization, and the ultimate products of fertilization, seeds enclosed in the fruit. Angiosperms exhibit a vast array of reproductive strategies, including both asexual and sexual, the latter of which includes both self-fertilization and cross-fertilization. Asexual reproduction and self-fertilization are important reproductive strategies in a variety of situations, such as when mates are scarce or when the environment remains relatively stable. However, reproductive strategies promoting cross-fertilization are critical to angiosperm success, since they contribute to the creation of genetically diverse populations, which increase the probability that at least one individual in a population will survive given changing environmental conditions. The evolution of several physical and genetic barriers to self-fertilization or fertilization among closely related individuals is thus widespread in angiosperms. A major genetic barrier to self-fertilization is self-incompatibility (SI), which allows female reproductive cells to discriminate between "self" and "non-self" pollen, and specifically reject self pollen. Evidence for the importance of SI in angiosperm evolution lies in the highly diverse set of mechanisms used by various angiosperm families for recognition of self pollen tube development and preventing self-fertilization.