Comprehensive indicators for eutrophication in lakes

Anthropogenic influences such as urbanization, agricultural intensification, use of chemical fertilizers,and the release of sewage emit nutrients (nitrogen and phosphorus) into freshwater lakes. Excessiveamounts of nitrogen and phosphorus lead to eutrophication, which is a global water quality concern,with typical impacts such as the growth of harmful algal blooms, hypoxia and fish kills. The currentwater quality indicators used to monitor lake eutrophication focus only on water quality constituents(e.g., total phosphorus and total nitrogen). The response of lakesto nutrient inputs, however, dependson its interaction with climate, basin characteristics that include land use, hydrology andanthropogenic activities. In this study, we present a set of comprehensive indicators that account fornutrient sources and biogeochemical pathways in the lake basins and demonstrate their interactionsusing a causal network. The causal network provides a holistic perspective of nutrient dynamics andthe interactive effects of the indicators on water quality in lake basins, which is key to improving waterquality management. The indicators from this study can be used as proxies to monitor water qualitystatus. The comprehensive indicators improve mechanistic understanding of the lake nutrientdynamics, by systematically considering mechanisms of sources and factors of nutrients emission inthe basin. They can consequently fill the gap in water quality monitoring data, especially in data scarceregions such as Asia and Africa. These indicators can be used to set realistic water quality targets andare therefore beneficial in long-term policy making and sustainable water quality management

Recent advancement in water quality indicators for eutrophication in global freshwater lakes

Excessive nutrient (nitrogen and phosphorus) loadings to freshwater lakes cause eutrophication, which is a global water quality issue. Anthropogenic activities in lake basins emit nutrients, either as point- (e.g., sewage) or diffuse sources (e.g., agricultural runoff). Their typical impacts on lake water quality include the occurrence of harmful algal blooms, hypoxia and fish kills. These impacts are likely to worsen due to climate change, population growth and economic development. The response of lakes to a change in nutrient inputs depends on their interactions with the climate, land-use, hydrology and socio-economic conditions of a lake basin. These feedback mechanisms, however, are not often included in the eutrophication assessments for lakes. In this study, we present a new causal network of the drivers-pressure-state-impact-response (DPSIR) framework using a total of 58 sub-indicators to characterize all the DPSIR elements and systematically conceptualize the complex interactions of nutrients in freshwater lake basins. The network provides a holistic perspective on nutrient dynamics of multiple indicators and their interactive effects on water quality in lake basins, which is key to improving water quality management. Furthermore, we disentangle the complex eutrophication mechanisms using drivers and pressures, that represent different sources and nutrient pathways. The study highlights coupling of lake systems in water quality modeling frameworks and assessments which is required to understand its impact on water quality from human activities in the basin. The drivers and pressures can be used as proxies to provide meaningful information on nutrient emissions and biogeochemical pathways, that can fill the gap in water quality monitoring data, especially in data scarce regions such as Asia and Africa. These indicators can be used to set realistic water quality targets, and are, therefore, beneficial in long-term policy making and sustainable water quality management

Recent advancement in water quality indicators for eutrophication in global freshwater lakes

Eutrophication is a major global concern in lakes, caused by excessive nutrient loadings (nitrogen and phosphorus) from human activities and likely exacerbated by climate change. Present use of indicators to monitor and assess lake eutrophication is restricted to water quality constituents (e.g. total phosphorus, total nitrogen) and does not necessarily represent global environmental changes and the anthropogenic influences within the lake’s drainage basin. Nutrients interact in multiple ways with climate, basin conditions (e.g. socio-economic development, point-source, diffuse source pollutants), and lake systems. It is therefore essential to account for complex feedback mechanisms and non-linear interactions that exist between nutrients and lake ecosystems in eutrophication assessments. However, the lack of a set of water quality indicators that represent a holistic understanding of lake eutrophication challenges such assessments, in addition to the limited water quality monitoring data available. In this review, we synthesize the main indicators of eutrophication for global freshwater lake basins that not only include the water quality constituents but also the sources, biogeochemical pathways and responses of nutrient emissions. We develop a new causal network (i.e. multiple links of indicators) using the DPSIR (drivers-pressure-state-impact-response) framework that highlights complex interrelationships among the indicators and provides a holistic perspective of eutrophication dynamics in freshwater lake basins. We further review the 30 key indicators of drivers and pressures using seven cross-cutting themes: (i) hydro-climatology, (ii) socio-economy, (iii) land use, (iv) lake characteristics, (v) crop farming and livestock, (vi) hydrology and water management, and (vii) fishing and aquaculture. This study indicates a need for more comprehensive indicators that represent the complex mechanisms of eutrophication in lake systems, to guide the global expansion of water quality monitoring networks, and support integrated assessments to manage eutrophication. Finally, the indicators proposed in this study can be used by managers and decision-makers to monitor water quality and set realistic targets for sustainable water quality management to achieve clean water for all, in line with Sustainable Development Goal 6

Detection of small RNAs in Pseudomonas aeruginosa by RNomics and structure-based bioinformatic tools.

Inactivation of the Pseudomonas aeruginosa (PAO1) hfq gene, encoding the Sm-like Hfq protein, resulted in pleiotropic effects that included an attenuated virulence. As regulation by Hfq often involves the action of small regulatory RNAs (sRNAs), we have used a shotgun cloning approach (RNomics) and bioinformatic tools to identify sRNAs in strain PAO1. For cDNA library construction, total RNA was extracted from PAO1 cultures either grown to stationary phase or exposed to human serum. The cDNA libraries were generated from small-sized RNAs of PAO1 after co-immunoprecipitation with Hfq. Of 400 sequenced cDNA clones, 11 mapped to intergenic regions. Band-shift assays and Northern blot analyses performed with two selected sRNAs confirmed that Hfq binds to and affects the steady-state levels of these RNAs. A proteome study performed upon overproduction of one sRNA, PhrS, implicated it in riboregulation. PhrS contains an ORF, and evidence for its translation is presented. In addition, based on surveys with structure-based bioinformatic tools, we provide an electronic compilation of putative sRNA and non-coding RNA genes of PAO1 based on their evolutionarily conserved structure

Small RNAs as regulators of primary and secondary metabolism in Pseudomonas species.

Small RNAs (sRNAs) exert important functions in pseudomonads. Classical sRNAs comprise the 4.5S, 6S, 10Sa and 10Sb RNAs, which are known in enteric bacteria as part of the signal recognition particle, a regulatory component of RNA polymerase, transfer-messenger RNA (tmRNA) and the RNA component of RNase P, respectively. Their homologues in pseudomonads are presumed to have analogous functions. Other sRNAs of pseudomonads generally have little or no sequence similarity with sRNAs of enteric bacteria. Numerous sRNAs repress or activate the translation of target mRNAs by a base-pairing mechanism. Examples of this group in Pseudomonas aeruginosa are the iron-repressible PrrF1 and PrrF2 sRNAs, which repress the translation of genes encoding iron-containing proteins, and PhrS, an anaerobically inducible sRNA, which activates the expression of PqsR, a regulator of the Pseudomonas quinolone signal. Other sRNAs sequester RNA-binding proteins that act as translational repressors. Examples of this group in P. aeruginosa include RsmY and RsmZ, which are central regulatory elements in the GacS/GacA signal transduction pathway, and CrcZ, which is a key regulator in the CbrA/CbrB signal transduction pathway. These pathways largely control the extracellular activities (including virulence traits) and the selection of the energetically most favourable carbon sources, respectively, in pseudomonads

Distinctive features of the Gac‐Rsm

Productive plant–bacteria interactions, either beneficial or pathogenic, require that bacteria successfully sense, integrate and respond to continuously changing environmental and plant stimuli. They use complex signal transduction systems that control a vast array of genes and functions. The Gac-Rsm global regulatory pathway plays a key role in controlling fundamental aspects of the apparently different lifestyles of plant beneficial and phytopathogenic Pseudomonas as it coordinates adaptation and survival while either promoting plant health (biocontrol strains) or causing disease (pathogenic strains). Plant-interacting Pseudomonas stand out for possessing multiple Rsm proteins and Rsm RNAs, but the physiological significance of this redundancy is not yet clear. Strikingly, the components of the Gac-Rsm pathway and the controlled genes/pathways are similar, but the outcome of its regulation may be opposite. Therefore, identifying the target mRNAs bound by the Rsm proteins and their mode of action (repression or activation) is essential to explain the resulting phenotype. Some technical considerations to approach the study of this system are also given. Overall, several important features of the Gac-Rsm cascade are now understood in molecular detail, particularly in Pseudomonas protegens CHA0, but further questions remain to be solved in other plant-interacting Pseudomonas.This research was supported by grants BIO2014-55075-P and BIO2017-83533-P from the ERDF/Spanish Ministry of Science, Innovation and Universities - State Research Agency. M.D.F. was supported by a FPU contract from the Spanish MECD/MEFP (ECD/1619/2013)