Characterization of a Tryptophan 6-Halogenase from Streptomyces albus and Its Regioselectivity Determinants

Tryptophan halogenases are found in diverse organisms and catalyze regiospecific halogenation. They play an important role in the biosynthesis of halogenated indole alkaloids, which are biologically active and of therapeutic importance. Here, a tryptophan 6-halogenase (SatH) from Streptomyces albus was characterized by using a whole-cell reaction system in Escherichia coli. SatH showed substrate specificity for chloride and bromide ions, leading to regiospecific halogenation at the C6-position of l -tryptophan. In addition, SatH exhibited higher performance in bromination than that of previously reported tryptophan halogenases in the whole-cell reaction system. Through structure-based protein mutagenesis, it has been revealed that two consecutive residues, A78/V79 in SatH and G77/I78 in PyrH, are key determinants in the regioselectivity difference between tryptophan 6- and 5-halogenases. Substituting the AV with GI residues switched the regioselectivity of SatH by moving the orientation of tryptophan. These data contribute to an understanding of the key residues that determine the regioselectivity of tryptophan halogenases.     

Tributary use and large-scale movements of grass carp in Lake Erie

Infrequent captures of invasive, non-native grass carp (Ctenopharyngodon idella) have occurred in Lake Erie over the last 30+ years, with recent evidence suggesting wild reproduction in the lake’s western basin (WB) is occurring. Information on grass carp movements in the Laurentian Great Lakes is lacking, but an improved understanding of large-scale movements and potential areas of aggregation will help inform control strategies and risk assessment if grass carp spread to other parts of Lake Erie and other Great Lakes. Twenty-three grass carp captured in Lake Erie’s WB were implanted with acoustic transmitters and released. Movements were monitored with acoustic receivers deployed throughout Lake Erie and elsewhere in the Great Lakes. Grass carp dispersed up to 236 km, with approximately 25% of fish dispersing greater than 100 km from their release location. Mean daily movements ranged from <0.01 to 2.49 km/day, with the highest daily averages occurring in the spring and summer. The Sandusky, Detroit, and Maumee Rivers, and Plum Creek were the most heavily used WB tributaries. Seventeen percent of grass carp moved into Lake Erie’s central or eastern basins, although all fish eventually returned to the WB. One fish emigrated from Lake Erie through the Huron-Erie Corridor and into Lake Huron. Based on our results, past assessments may have underestimated the potential for grass carp to spread in the Great Lakes. We recommend focusing grass carp control efforts on Sandusky River and Plum Creek given their high use by tagged fish, and secondarily on Maumee and Detroit Rivers.     

Building a research network to better understand climate governance in the Great Lakes

Climate-driven disturbances threaten the sustainability of coastal communities in the Great Lakes Basin. Because such disturbances are unpredictable, their magnitude, number and intensity are changing, and they occur at varying temporal and spatial scales. Consequently, communities struggle to respond in effective ways. The expected intensification of climate-driven disturbances will require that community capacity and governance structures match the spatial and temporal scales of these disturbances, as the most sustainable social and economic systems will be those that can respond at similar frequencies to key natural system drivers. The Climate Governance Variability in the Great Lakes Research Coordination Network (CGVG-RCN) was recently established to address questions about the relationship between climate-driven disturbances and community response. The objective of this short communication is to introduce the ideas behind the CGVG-RCN, outline its goals, and facilitate engagements and collaboration with social and natural scientists interested in social-ecological systems in the Great Lakes Basin.     

Importance of nonindigenous harpacticoids (Crustacea: Copepoda) decrease with depth in Lake Ontario

Harpacticoid copepods can be a substantial component of the meiobenthic community in lakes and serve an ecological role as detritivores. Here we present the first species-level lake-wide quantitative assessment of the harpacticoid assemblage of Lake Ontario with emphasis on the status of nonindigenous species. Additionally, we provide COI-5P sequences of harpacticoid taxa through Barcode of Life Data System (BOLD). Harpacticoids were collected at depths from 0.1 to 184 m and from a range of substrates from August to September 2018 as part of the Cooperative Science and Monitoring Initiative (CSMI) offshore benthic survey. Twenty-six meiobenthic samples were analyzed using microscopy for community composition analysis of harpacticoids. We found thirteen indigenous and three nonindigenous species of harpacticoid, with the introduced species dominating at shallow depths. The community transitioned from nonindigenous to indigenous species dominance as depth increased. Nonindigenous species accounted for 79% of the community (by abundance) at depths <20 m, 55% from 20 to 40 m, and only 24% at depths >40 m. The nonindigenous species encountered included the first detections of Schizopera borutzkyi (Monchenko, 1967) and Heteropsyllus nunni (Coull, 1975) from Lake Ontario. S. borutzkyi was the most abundant harpacticoid species in the lake, approaching a maximum density of 50,000/m² and a lake-wide average density of 7,900/m². Numerically important indigenous species included Bryocamptus nivalis (Willey, 1925), Canthocamptus robertcokeri (Wilson, 1958), Canthocamptus staphylinoides (Pearse, 1905), and Moraria cristata (Chappuis, 1929). The prevalence of nonindigenous harpacticoids in the meiobenthos of Lake Ontario suggests further investigations of Great Lakes meiofauna communities are warranted.     

Dreissena in Lake Ontario 30 years post-invasion

We examined three decades of changes in dreissenid populations in Lake Ontario and predation by round goby (Neogobius melanostomus). Dreissenids (almost exclusively quagga mussels, Dreissena rostriformis bugensis) peaked in 2003, 13 years after arrival, and then declined at depths <90 m but continued to increase deeper through 2018. Lake-wide density also increased from 2008 to 2018 along with average mussel lengths and lake-wide biomass, which reached an all-time high in 2018 (25.2 ± 3.3 g AFTDW/m²). Round goby densities were estimated at 4.2 fish/m² using videography at 10 to 35 m depth range in 2018. This density should impact mussel populations based on feeding rates, as indicated in the literature. While the abundance of 0–5 mm mussels appears to be high in all three years with measured length distributions (2008, 2013, 2018), the abundance of 5 to 12 mm dreissenids, the size range most commonly consumed by round goby, was low except at >90 m depths. Although the size distributions indicate that round goby is affecting mussel recruitment, we did not find a decline in dreissenid density in the nearshore and mid-depth ranges where goby have been abundant since 2005. The lake-wide densities and biomass of quagga mussels have increased over time, due to both the growth of individual mussels in the shallower depths, and a continuing increase in density at >90 m. Thus, the ecological effects of quagga mussels in Lake Ontario are likely to continue into the foreseeable future.     

A comprehensive approach to evaluating watershed models for predicting river flow regimes critical to downstream ecosystem services

Selection of strategies that help reduce riverine inputs requires numerical models that accurately quantify hydrologic processes. While numerous models exist, information on how to evaluate and select the most robust models is limited. Toward this end, we developed a comprehensive approach that helps evaluate watershed models in their ability to simulate flow regimes critical to downstream ecosystem services. We demonstrated the method using the Soil and Water Assessment Tool (SWAT), the Hydrological Simulation Program–FORTRAN (HSPF) model, and Distributed Large Basin Runoff Model (DLBRM) applied to the Maumee River Basin (USA). The approach helped in identifying that each model simulated flows within acceptable ranges. However, each was limited in its ability to simulate flows triggered by extreme weather events, owing to algorithms not being optimized for such events and mismatched physiographic watershed conditions. Ultimately, we found HSPF to best predict river flow, whereas SWAT offered the most flexibility for evaluating agricultural management practices.     

Variability of sedimentary phosphorus fractions in the western and Sandusky basins of Lake Erie

Surface sediments and three sediment cores from the western basin and one sediment core from the Sandusky basin were analyzed to document spatial and temporal changes in five phosphorus fractions and total phosphorus (TP). The areal distributions of the bioavailable fractions NaCl-Pi, NaBD-Pi, and NaOH-Pi and the refractory organic fraction Res-P were broadly consistent and contrasted with those of the detrital fraction HCl-Pi which showed that high concentrations occurred mostly in high-energy littoral zones and low concentrations largely in profundal depositional areas. The contrasting distributions were induced by interactions among tributary inputs, wave action, circulation, and biogeochemical cycling and transfer in the basin. As revealed by the Sandusky basin sediment record, the detrital fraction HCl-Pi was dominant (70% of TP) during European settlement and decreased rapidly by 28.0% in the early 1910s due largely to impoundments of the Maumee and Sandusky Rivers. While HCl-Pi has ever since remained relatively constant, NaCl-Pi, NaBD-Pi, and NaOH-Pi increased significantly between 1950 and 1970 in the two basins. However, the post-regulation sediment records differed considerably among these coring sites. There was a marked increase of TP in two cores, corresponding to recent return of eutrophication and massive harmful algal blooms but contrasting with a relatively constant, low loading into the lake. This signified the role of internal loading as derived partialy from legacy pollution. Furthermore, NaCl-Pi has increased progressively throughout all the records. We conclude that the increased levels of NaCl-Pi in surface sediments may have altered the internal loading and contributed to the resurgences of harmful algal blooms in Lake Erie.     

Improving classification-based diagnosis of batch processes through data selection and appropriate pretreatment

This work considers the application of classification algorithms for data-driven fault diagnosis of batch processes. A novel data selection methodology is proposed which enables online classification of detected disturbances without requiring the estimation of unknown (future) process behavior, as is the case in previously reported approaches.The proposed method is benchmarked in two case studies using the Pensim process model of Birol et al. (2002) implemented in RAYMOND. Both a simple k Nearest Neighbors (k-NN) and complex Least Squares Support Vector Machine (LS-SVM) are employed for classification to demonstrate the generic nature of the proposed approach. In addition, the influence of different data pretreatment methods on the classification performance is discussed, together with a motivation for selecting the correct pretreatment steps. Finally, the influence of the number of available training batches is studied.The results demonstrate that a good classification performance can be achieved with the proposed data selection method even with a low number of faulty training batches by exploiting knowledge on the nature of the to-be-diagnosed faults in the data pretreatment. This provides a proof of concept for classification-based batch diagnosis and demonstrates the importance of incorporating process insight in the construction of data-driven process monitoring and diagnosis tools.