A model for community-driven development of best practices: the Ocean Observatories Initiative Biogeochemical Sensor Data Best Practices and User Guide

The field of oceanography is transitioning from data-poor to data-rich, thanks in part to increased deployment of in-situ platforms and sensors, such as those that instrument the US-funded Ocean Observatories Initiative (OOI). However, generating science-ready data products from these sensors, particularly those making biogeochemical measurements, often requires extensive end-user calibration and validation procedures, which can present a significant barrier. Openly available community-developed and -vetted Best Practices contribute to overcoming such barriers, but collaboratively developing user-friendly Best Practices can be challenging. Here we describe the process undertaken by the NSF-funded OOI Biogeochemical Sensor Data Working Group to develop Best Practices for creating science-ready biogeochemical data products from OOI data, culminating in the publication of the GOOS-endorsed OOI Biogeochemical Sensor Data Best Practices and User Guide. For Best Practices related to ocean observatories, engaging observatory staff is crucial, but having a “user-defined” process ensures the final product addresses user needs. Our process prioritized bringing together a diverse team and creating an inclusive environment where all participants could effectively contribute. Incorporating the perspectives of a wide range of experts and prospective end users through an iterative review process that included “Beta Testers’’ enabled us to produce a final product that combines technical information with a user-friendly structure that illustrates data analysis pipelines via flowcharts and worked examples accompanied by pseudo-code. Our process and its impact on improving the accessibility and utility of the end product provides a roadmap for other groups undertaking similar community-driven activities to develop and disseminate new Ocean Best Practices

Identification of Ciliary Localization Sequences within the Third Intracellular Loop of G Protein-coupled Receptors

Primary cilia are sensory organelles present on most mammalian cells. The functions of cilia are defined by the signaling proteins localized to the ciliary membrane. Certain G protein–coupled receptors (GPCRs), including somatostatin receptor 3 (Sstr3) and serotonin receptor 6 (Htr6), localize to cilia. As Sstr3 and Htr6 are the only somatostatin and serotonin receptor subtypes that localize to cilia, we hypothesized they contain ciliary localization sequences. To test this hypothesis we expressed chimeric receptors containing fragments of Sstr3 and Htr6 in the nonciliary receptors Sstr5 and Htr7, respectively, in ciliated cells. We found the third intracellular loop of Sstr3 or Htr6 is sufficient for ciliary localization. Comparison of these loops revealed a loose consensus sequence. To determine whether this consensus sequence predicts ciliary localization of other GPCRs, we compared it with the third intracellular loop of all human GPCRs. We identified the consensus sequence in melanin-concentrating hormone receptor 1 (Mchr1) and confirmed Mchr1 localizes to primary cilia in vitro and in vivo. Thus, we have identified a putative GPCR ciliary localization sequence and used this sequence to identify a novel ciliary GPCR. As Mchr1 mediates feeding behavior and metabolism, our results implicate ciliary signaling in the regulation of body weight

Mg 2+

Thymidylate synthase (TSase) produces the sole intracellular de novo source of thymidine (i.e. the DNA base T) and thus is a common target for antibiotic and anticancer drugs. Mg(2+) has been reported to affect TSase activity, but the mechanism of this interaction has not been investigated. Here we show that Mg(2+) binds to the surface of Escherichia coli TSase and affects the kinetics of hydride transfer at the interior active site (16 Å away). Examination of the crystal structures identifies a Mg(2+) near the glutamyl moiety of the folate cofactor, providing the first structural evidence for Mg(2+) binding to TSase. The kinetics and NMR relaxation experiments suggest that the weak binding of Mg(2+) to the protein surface stabilizes the closed conformation of the ternary enzyme complex and reduces the entropy of activation on the hydride transfer step. Mg(2+) accelerates the hydride transfer by ca. 7-fold but does not affect the magnitude or temperature-dependence of the intrinsic kinetic isotope effect. These results suggest that Mg(2+) facilitates the protein motions that bring the hydride donor and acceptor together, but it does not change the tunneling ready state of the hydride transfer. These findings highlight how variations in cellular Mg(2+) concentration can modulate enzyme activity through long-range interactions in the protein, rather than binding at the active site. The interaction of Mg(2+) with the glutamyl-tail of the folate cofactor and nonconserved residues of bacterial TSase may assist in designing antifolates with poly-glutamyl substitutes as species-specific antibiotic drugs

DataSheet_1_A model for community-driven development of best practices: the Ocean Observatories Initiative Biogeochemical Sensor Data Best Practices and User Guide.pdf

The field of oceanography is transitioning from data-poor to data-rich, thanks in part to increased deployment of in-situ platforms and sensors, such as those that instrument the US-funded Ocean Observatories Initiative (OOI). However, generating science-ready data products from these sensors, particularly those making biogeochemical measurements, often requires extensive end-user calibration and validation procedures, which can present a significant barrier. Openly available community-developed and -vetted Best Practices contribute to overcoming such barriers, but collaboratively developing user-friendly Best Practices can be challenging. Here we describe the process undertaken by the NSF-funded OOI Biogeochemical Sensor Data Working Group to develop Best Practices for creating science-ready biogeochemical data products from OOI data, culminating in the publication of the GOOS-endorsed OOI Biogeochemical Sensor Data Best Practices and User Guide. For Best Practices related to ocean observatories, engaging observatory staff is crucial, but having a “user-defined” process ensures the final product addresses user needs. Our process prioritized bringing together a diverse team and creating an inclusive environment where all participants could effectively contribute. Incorporating the perspectives of a wide range of experts and prospective end users through an iterative review process that included “Beta Testers’’ enabled us to produce a final product that combines technical information with a user-friendly structure that illustrates data analysis pipelines via flowcharts and worked examples accompanied by pseudo-code. Our process and its impact on improving the accessibility and utility of the end product provides a roadmap for other groups undertaking similar community-driven activities to develop and disseminate new Ocean Best Practices.</p