Colorful Niches of Phytoplankton Shaped by the Spatial Connectivity in a Large River Ecosystem: A Riverscape Perspective

Large rivers represent a significant component of inland waters and are considered sentinels and integrators of terrestrial and atmospheric processes. They represent hotspots for the transport and processing of organic and inorganic material from the surrounding landscape, which ultimately impacts the bio-optical properties and food webs of the rivers. In large rivers, hydraulic connectivity operates as a major forcing variable to structure the functioning of the riverscape, and–despite increasing interest in large-river studies–riverscape structural properties, such as the underwater spectral regime, and their impact on autotrophic ecological processes remain poorly studied. Here we used the St. Lawrence River to identify the mechanisms structuring the underwater spectral environment and their consequences on pico- and nanophytoplankton communities, which are good biological tracers of environmental changes. Our results, obtained from a 450 km sampling transect, demonstrate that tributaries exert a profound impact on the receiving river’s photosynthetic potential. This occurs mainly through injection of chromophoric dissolved organic matter (CDOM) and non-algal material (tripton). CDOM and tripton in the water column selectively absorbed wavelengths in a gradient from blue to red, and the resulting underwater light climate was in turn a strong driver of the phytoplankton community structure (prokaryote/eukaryote relative and absolute abundances) at scales of many kilometers from the tributary confluence. Our results conclusively demonstrate the proximal impact of watershed properties on underwater spectral composition in a highly dynamic river environment characterized by unique structuring properties such as high directional connectivity, numerous sources and forms of carbon, and a rapidly varying hydrodynamic regime. We surmise that the underwater spectral composition represents a key integrating and structural property of large, heterogeneous river ecosystems and a promising tool to study autotrophic functional properties. It confirms the usefulness of using the riverscape approach to study large-river ecosystems and initiate comparison along latitudinal gradients

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Agent-Based Model of Therapeutic Adipose-Derived Stromal Cell Trafficking during Ischemia Predicts Ability To Roll on P-Selectin

Intravenous delivery of human adipose-derived stromal cells (hASCs) is a promising option for the treatment of ischemia. After delivery, hASCs that reside and persist in the injured extravascular space have been shown to aid recovery of tissue perfusion and function, although low rates of incorporation currently limit the safety and efficacy of these therapies. We submit that a better understanding of the trafficking of therapeutic hASCs through the microcirculation is needed to address this and that selective control over their homing (organ- and injury-specific) may be possible by targeting bottlenecks in the homing process. This process, however, is incredibly complex, which merited the use of computational techniques to speed the rate of discovery. We developed a multicell agent-based model (ABM) of hASC trafficking during acute skeletal muscle ischemia, based on over 150 literature-based rules instituted in Netlogo and MatLab software programs. In silico, trafficking phenomena within cell populations emerged as a result of the dynamic interactions between adhesion molecule expression, chemokine secretion, integrin affinity states, hemodynamics and microvascular network architectures. As verification, the model reasonably reproduced key aspects of ischemia and trafficking behavior including increases in wall shear stress, upregulation of key cellular adhesion molecules expressed on injured endothelium, increased secretion of inflammatory chemokines and cytokines, quantified levels of monocyte extravasation in selectin knockouts, and circulating monocyte rolling distances. Successful ABM verification prompted us to conduct a series of systematic knockouts in silico aimed at identifying the most critical parameters mediating hASC trafficking. Simulations predicted the necessity of an unknown selectin-binding molecule to achieve hASC extravasation, in addition to any rolling behavior mediated by hASC surface expression of CD15s, CD34, CD62e, CD62p, or CD65. In vitro experiments confirmed this prediction; a subpopulation of hASCs slowly rolled on immobilized P-selectin at speeds as low as 2 µm/s. Thus, our work led to a fundamentally new understanding of hASC biology, which may have important therapeutic implications

C-Type Lectin in Chlamys farreri (CfLec-1) Mediating Immune Recognition and Opsonization

Background: C-type lectins are a superfamily of Ca 2+ dependent carbohydrate-recognition proteins that play significant diverse roles in nonself-recognition and clearance of invaders. Though they are well characterized in vertebrates, the study of the potential function and mechanism of C-type lectins in invertebrate immunity is still in its infancy. Methodology: A C-type lectin (CfLec-1) from scallop Chlamys farreri, a dominant cultured mollusk species in China, was selected to investigate its mRNA expression, localization and the possible functions in innate immunity in the present study. After scallop was stimulated by three typical PAMPs, the mRNA expression of CfLec-1 in hemocytes was poles apart. It was significantly up-regulated (p,0.01) after scallops were stimulated by LPS or b-glucan, but significantly down-regulated (p,0.01) after PGN stimulation. The binding ability of recombinant CfLec-1 (designated as rCfLec-1) towards eight PAMPs was investigated subsequently by PAMPs microarray, which revealed rCfLec-1 could bind LPS, PGN and mannan in vitro, indicating CfLec-1 served as a PRR involved in the pathogen recognition. Immunofluorescence assay with polyclonal antibody specific for CfLec-1 revealed that CfLec-1 was mainly located in the mantle and gill of the scallop. CfLec-1 could bind to the surface of scallop hemocytes and recruited hemocytes to enhance their encapsulation in vitro, and this process could be specifically blocked by anti-rCfLec-1 antibody. Meanwhile, rCfLec-1 could also enhance the phagocytic activity of scallop hemocytes against Escherichia coli

Distamycin A Inhibits HMGA1-Binding to the P-Selectin Promoter and Attenuates Lung and Liver Inflammation during Murine Endotoxemia

Background: The architectural transcription factor High Mobility Group-A1 (HMGA1) binds to the minor groove of AT-rich DNA and forms transcription factor complexes (“enhanceosomes”) that upregulate expression of select genes within the inflammatory cascade during critical illness syndromes such as acute lung injury (ALI). AT-rich regions of DNA surround transcription factor binding sites in genes critical for the inflammatory response. Minor groove binding drugs (MGBs), such as Distamycin A (Dist A), interfere with AT-rich region DNA binding in a sequence and conformation-specific manner, and HMGA1 is one of the few transcription factors whose binding is inhibited by MGBs. Objectives: To determine whether MGBs exert beneficial effects during endotoxemia through attenuating tissue inflammation via interfering with HMGA1-DNA binding and modulating expression of adhesion molecules. Methodology/Principal Findings: Administration of Dist A significantly decreased lung and liver inflammation during murine endotoxemia. In intravital microscopy studies, Dist A attenuated neutrophil-endothelial interactions in vivo following an inflammatory stimulus. Endotoxin induction of P-selectin expression in lung and liver tissue and promoter activity in endothelial cells was significantly reduced by Dist A, while E-selectin induction was not significantly affected. Moreover, Dist A disrupted formation of an inducible complex containing NF-κB that binds an AT-rich region of the P-selectin promoter. Transfection studies demonstrated a critical role for HMGA1 in facilitating cytokine and NF-κB induction of P-selectin promoter activity, and Dist A inhibited binding of HMGA1 to this AT-rich region of the P-selectin promoter in vivo. Conclusions/Significance: We describe a novel targeted approach in modulating lung and liver inflammation in vivo during murine endotoxemia through decreasing binding of HMGA1 to a distinct AT-rich region of the P-selectin promoter. These studies highlight the ability of MGBs to function as molecular tools for dissecting transcriptional mechanisms in vivo and suggest alternative treatment approaches for critical illness

Differential DARC/ACKR1 expression distinguishes venular from non-venular endothelial cells in murine tissues

This work was supported by the National Institutes of Health (NIH) grant AI112521 and the John and Virginia Kaneb Fellowship

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe