The Arabidopsis CURVY1 (CVY1) gene encoding a novel receptor-like protein kinase regulates cell morphogenesis, flowering time and seed production.

BACKGROUND: A molecular-level understanding of the loss of CURVY1 (CVY1) gene expression (which encodes a member of the receptor-like protein kinase family) was investigated to gain insights into the mechanisms controlling cell morphogenesis and development in Arabidopsis thaliana. RESULTS: Using a reverse genetic and cell biology approaches, we demonstrate that CVY1 is a new DISTORTED gene with similar phenotypic characterization to previously characterized ARP2/3 distorted mutants. Compared to the wild type, cvy1 mutant displayed a strong distorted trichome and altered pavement cell phenotypes. In addition, cvy1 null-mutant flowers earlier, grows faster and produces more siliques than WT and the arp2/3 mutants. The CVY1 gene is ubiquitously expressed in all tissues and seems to negatively regulate growth and yield in higher plants. CONCLUSIONS: Our results suggest that CURVY1 gene participates in several biochemical pathways in Arabidopsis thaliana including (i) cell morphogenesis regulation through actin cytoskeleton functional networks, (ii) the transition of vegetative to the reproductive stage and (iii) the production of seeds.

Stormwater biofilter response to high nitrogen loading under transient flow conditions: Ammonium and nitrate fates, and nitrous oxide emissions.

Nitrogen (N) in urban runoff is often treated with green infrastructure including biofilters. However, N fates across biofilters are insufficiently understood because prior studies emphasize low N loading under laboratory conditions, or use "steady-state" flow regimes over short time scales. Here, we tested field scale biofilter N fates during simulated storms delivering realistic transient flows with high N loading. Biofilter outflow ammonium (NH4+-N) was 60.7 to 92.3% lower than that of the inflow. Yet the characteristic times for nitrification (days to weeks) and denitrification (days) relative to N residence times (7 to 30 h) suggested low N transformation across the biofilters. Still, across 7 successive storms, total outflow nitrate (NO3--N) greatly exceeded (3100 to 3900%) inflow nitrate, a result only explainable by biofilter soil N nitrification occurring between storms. Archaeal, and bacterial amoA gene copies (2.1 × 105 to 1.2 × 106 gc g soil-1), nitrifier presence by16S rRNA gene sequencing, and outflow δ18O-NO3- values (-3.0 to 17.1 ‰) reinforced that nitrification was occurring. A ratio of δ18O-NO3- to δ15N-NO3- of 1.83 for soil eluates indicated additional processes: N assimilation, and N mineralization. Denitrification potential was suggested by enzyme activities and soil denitrifying gene copies (nirK + nirS: 3.0 × 106 to 1.8 × 107; nosZ: 5.0 × 105 to 2.2 × 106 gc g soil-1). However, nitrous oxide (N2O-N) emissions (13.5 to 84.3 µg N m - 2 h - 1) and N2O export (0.014 g N) were low, and soil nitrification enzyme activities (0.45 to 1.63 mg N kg soil-1day-1) exceeded those for denitrification (0.17 to 0.49 mg N kg soil-1 day-1). Taken together, chemical, bacterial, and isotopic metrics evidenced that storm inflow NH4+sorbs and, along with mineralized soil N, nitrifies during biofilter dry-down; little denitrification and associated N2O emissions ensue, and thus subsequent storms export copious NO3--N. As such, pulsed pass-through biofilters require redesign to promote plant assimilation and/or denitrification of mineralized and nitrified N, to minimize NO3--N generation and export.

The influence of complex matrices on method performance in extracting and monitoring for microplastics.

Previous studies have evaluated method performance for quantifying and characterizing microplastics in clean water, but little is known about the efficacy of procedures used to extract microplastics from complex matrices. Here we provided 15 laboratories with samples representing four matrices (i.e., drinking water, fish tissue, sediment, and surface water) each spiked with a known number of microplastic particles spanning a variety of polymers, morphologies, colors, and sizes. Percent recovery (i.e., accuracy) in complex matrices was particle size dependent, with ∼60-70% recovery for particles >212 µm, but as little as 2% recovery for particles <20 µm. Extraction from sediment was most problematic, with recoveries reduced by at least one-third relative to drinking water. Though accuracy was low, the extraction procedures had no observed effect on precision or chemical identification using spectroscopy. Extraction procedures greatly increased sample processing times for all matrices with the extraction of sediment, tissue, and surface water taking approximately 16, 9, and 4 times longer than drinking water, respectively. Overall, our findings indicate that increasing accuracy and reducing sample processing times present the greatest opportunities for method improvement rather than particle identification and characterization.

Highly variable removal of pathogens, antibiotic resistance genes, conventional fecal indicators and human-associated fecal source markers in a pilot-scale stormwater biofilter operated under realistic stormflow conditions.

Green stormwater infrastructure systems, such as biofilters, provide many water quality and other environmental benefits, but their ability to remove human pathogens and antibiotic resistance genes (ARGs) from stormwater runoff is not well documented. In this study, a field scale biofilter in Southern California (USA) was simultaneously evaluated for the breakthrough of a conservative tracer (bromide), conventional fecal indicators, bacterial and viral human-associated fecal source markers (HF183, crAssphage, and PMMoV), ARGs, and bacterial and viral pathogens. When challenged with a 50:50 mixture of untreated sewage and stormwater (to mimic highly contaminated storm flow) the biofilter significantly removed (p < 0.05) 14 of 17 microbial markers and ARGsin descending order of concentration reduction: ermB (2.5 log(base 10) reduction) > Salmonella (2.3) > adenovirus (1.9) > coliphage (1.5) > crAssphage (1.2) > E. coli (1.0) ∼ 16S rRNA genes (1.0) ∼ fecal coliform (1.0) ∼ intl1 (1.0) > Enterococcus (0.9) ∼ MRSA (0.9) ∼ sul1 (0.9) > PMMoV (0.7) > Entero1A (0.5). No significant removal was observed for GenBac3, Campylobacter, and HF183. From the bromide data, we infer that 0.5 log-units of attenuation can be attributed to the dilution of incoming stormwater with water stored in the biofilter; removal above this threshold is presumably associated with non-conservative processes, such as physicochemical filtration, die-off, and predation. Our study documents high variability (>100-fold) in the removal of different microbial contaminants and ARGs by a field-scale stormwater biofilter operated under transient flow and raises further questions about the utility of human-associated fecal source markers as surrogates for pathogen removal.

Synthetic microfiber emissions to land rival those to waterbodies and are growing.

Synthetic microfibers are found virtually everywhere in the environment, but emission pathways and quantities are poorly understood. By connecting regionalized global datasets on apparel production, use, and washing with emission and retention rates during washing, wastewater treatment, and sludge management, we estimate that 5.6 Mt of synthetic microfibers were emitted from apparel washing between 1950 and 2016. Half of this amount was emitted during the last decade, with a compound annual growth rate of 12.9%. Waterbodies received 2.9 Mt, while combined emissions to terrestrial environments (1.9 Mt) and landfill (0.6 Mt) were almost as large and are growing. Annual emissions to terrestrial environments (141.9 kt yr-1) and landfill (34.6 kt yr-1) combined are now exceeding those to waterbodies (167.2 kt yr-1). Improving access to wastewater treatment is expected to further shift synthetic microfiber emissions from waterbodies to terrestrial environments. Preventing emissions at the source would therefore be a more effective mitigation measure.