Maternity Leave and its Consequences for Subsequent Careers in Germany

Mentor: Joseph Schraibman From the Washington University Undergraduate Research Digest: WUURD, Volume 7, Issue 2, Spring 2012. Published by the Office of Undergraduate Research, Joy Zalis Kiefer Director of Undergraduate Research and Assistant Dean in the College of Arts & Sciences; Kristin Sobotka, Editor

Molybdenum Cofactor Catabolism Unravels the Physiological Role of the Drug Metabolizing Enzyme Thiopurine S-Methyltransferase

Therapy of molybdenum cofactor (Moco) deficiency has received US Food and Drug Administration (FDA) approval in 2021. Whereas urothione, the urinary excreted catabolite of Moco, is used as diagnostic biomarker for Moco-deficiency, its catabolic pathway remains unknown. Here, we identified the urothione-synthesizing methyltransferase using mouse liver tissue by anion exchange/size exclusion chromatography and peptide mass fingerprinting. We show that the catabolic Moco S-methylating enzyme corresponds to thiopurine S-methyltransferase (TPMT), a highly polymorphic drug-metabolizing enzyme associated with drug-related hematotoxicity but unknown physiological role. Urothione synthesis was investigated in vitro using recombinantly expressed human TPMT protein, liver lysates from Tpmt wild -type and knock-out (Tpmt(-/-)) mice as well as human liver cytosol. Urothione levels were quantified by liquid-chromatography tandem mass spectrometry in the kidneys and urine of mice. TPMT-genotype/phenotype and excretion levels of urothione were investigated in human samples and validated in an independent population-based study. As Moco provides a physiological substrate (thiopterin) of TPMT, thiopterin-methylating activity was associated with TPMT activity determined with its drug substrate (6-thioguanin) in mice and humans. Urothione concentration was extremely low in the kidneys and urine of Tpmt-/- mice. Urinary urothione concentration in TPMT-deficient patients depends on common TPMT polymorphisms, with extremely low levels in homozygous variant carriers (TPMT*3A/*3A) but normal levels in compound heterozygous carriers (TPMT*3A/*3C) as validated in the population-based study. Our work newly identified an endogenous substrate for TPMT and shows an unprecedented link between Moco catabolism and drug metabolism. Moreover, the TPMT example indicates that phenotypic consequences of genetic polymorphisms may differ between drug-and endogenous substrates

Benchmarking plant diversity of Palaearctic grasslands and other open habitats

Abstract Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m² and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology

Benchmarking plant diversity of Palaearctic grasslands and other open habitats

Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m(2) and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file "GrassPlot Diversity Benchmarks" and the web tool "GrassPlot Diversity Explorer" are now available online () and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology