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In animals, the response to chronic hypoxia is mediated by prolyl hydroxylases (PHDs) that regulate the levels of hypoxia-inducible transcription factor α (HIFα). PHD homologues exist in other types of eukaryotes and prokaryotes where they act on non HIF substrates. To gain insight into the factors underlying different PHD substrates and properties, we carried out biochemical and biophysical studies on PHD homologues from the cellular slime mold, Dictyostelium discoideum, and the protozoan parasite, Toxoplasma gondii, both lacking HIF. The respective prolyl-hydroxylases (DdPhyA and TgPhyA) catalyze prolyl-hydroxylation of S-phase kinase-associated protein 1 (Skp1), a reaction enabling adaptation to different dioxygen availability. Assays with full-length Skp1 substrates reveal substantial differences in the kinetic properties of DdPhyA and TgPhyA, both with respect to each other and compared with human PHD2; consistent with cellular studies, TgPhyA is more active at low dioxygen concentrations than DdPhyA. TgSkp1 is a DdPhyA substrate and DdSkp1 is a TgPhyA substrate. No cross-reactivity was detected between DdPhyA/TgPhyA substrates and human PHD2. The human Skp1 E147P variant is a DdPhyA and TgPhyA substrate, suggesting some retention of ancestral interactions. Crystallographic analysis of DdPhyA enables comparisons with homologues from humans, Trichoplax adhaerens, and prokaryotes, informing on differences in mobile elements involved in substrate binding and catalysis. In DdPhyA, two mobile loops that enclose substrates in the PHDs are conserved, but the C-terminal helix of the PHDs is strikingly absent. The combined results support the proposal that PHD homologues have evolved kinetic and structural features suited to their specific sensing roles.

A. I. Aptekarev and M. L. Yattselev
Trans. Moscow Math. Soc. 83 (), 251-268.
Abstract, references and article information

M. A. Stepanova
Trans. Moscow Math. Soc. 83 (), 1-13.
Abstract, references and article information

Sand: Monitoring and management for a sustainable future 2 March 2021 — 1:00PM TO 2:00PM Anonymous (not verified) 18 February 2021 Online

In partnership with the Global Sand Observatory Initiative, this event outlines the sand challenge, what actions are currently underway to address it, and what else needs to be done.

Please complete your registration on Zoom:

After water, sand is the raw material that the world consumes in the greatest quantity. It is no exaggeration to say that fine sand and coarser materials – the medium-to-coarse-grained pebbles, gravel and rock fragments used in construction – are the building blocks of the modern world.

When bound with cement, sand becomes concrete; when mixed with bitumen, it becomes asphalt; and when heated, it becomes glass. Without sand, we would have no highways, high-rises or high-speed trains. Yet sand – which is used here as shorthand for sand, gravel and crushed rock together – is a resource that is both abundant and finite.

In global terms, it is abundant, especially when compared with many other raw materials, albeit often not available close to where it is needed. It is finite in that the rate at which we are using it far exceeds the natural rate at which it is being replenished by the weathering of rocks by wind and water.

Industrialization, population growth and urbanization have fuelled explosive growth in the demand for sand. Precise data on sand extraction are hard to come by and the lack of data compounds the challenge of managing the resource sustainably.

However, the UN estimates that overall extraction could be in the region of 40 billion tonnes per year, driven primarily by construction sector demand. That equates to 18 kilograms of sand each day for every person on the planet and signals how strategically important these resources are for future sustainable development. Post-COVID-19 recovery investment in infrastructure, digital technologies, tourism and other economic activities are dependent on sand resources.

Current efforts to improve the management of sand resources at local, national and global levels are uneven. This is partly due to unique geological features and geography, but also differences in local manifestations of the ‘sand challenge’, national and regional demand for sand resources, as well as capacities to enforce or implement best practice assessment procedures, extractive practices, environmental management and restoration requirements.

We must put stronger conditions in place for a rapid, just and scaled transition to sustainable sand management. But where to focus our efforts for the greatest positive impact?

Haiyong Wang
Math. Comp. 93 (), 2861-2884.
Abstract, references and article information

Katherine Baker, Lehel Banjai and Mariya Ptashnyk
Math. Comp. 93 (), 2711-2743.
Abstract, references and article information

T. De Ryck and S. Mishra
Math. Comp. 93 (), 2643-2677.
Abstract, references and article information

Constantin Carle and Marlis Hochbruck
Math. Comp. 93 (), 2611-2641.
Abstract, references and article information

Jian Li
Proc. Amer. Math. Soc. 152 (), 5207-5217.
Abstract, references and article information

Donghyeok Lim and Christian Maire
Proc. Amer. Math. Soc. 152 (), 5013-5024.
Abstract, references and article information

N. Kuznetsov
St. Petersburg Math. J. 35 (), 467-472.
Abstract, references and article information

When using the distinct count function in SAS Visual Analytics reports, you might find that a negative value is displayed instead of the actual distinct count: imgalt="distinct_count" src="{fusion_66562_1_disti

Programmed cell death protein 1 (PD-1) is a critical inhibitory receptor that limits excessive T cell responses. Cancer cells have evolved to evade these immunoregulatory mechanisms by upregulating PD-1 ligands and preventing T cell–mediated anti-tumor responses. Consequently, therapeutic blockade of PD-1 enhances T cell–mediated anti-tumor immunity, but many patients do not respond and a significant proportion develop inflammatory toxicities. To improve anti-cancer therapy, it is critical to reveal the mechanisms by which PD-1 regulates T cell responses. We performed global quantitative phosphoproteomic interrogation of PD-1 signaling in T cells. By complementing our analysis with functional validation assays, we show that PD-1 targets tyrosine phosphosites that mediate proximal T cell receptor signaling, cytoskeletal organization, and immune synapse formation. PD-1 ligation also led to differential phosphorylation of serine and threonine sites within proteins regulating T cell activation, gene expression, and protein translation. In silico predictions revealed that kinase/substrate relationships engaged downstream of PD-1 ligation. These insights uncover the phosphoproteomic landscape of PD-1–triggered pathways and reveal novel PD-1 substrates that modulate diverse T cell functions and may serve as future therapeutic targets. These data are a useful resource in the design of future PD-1–targeting therapeutic approaches.

Clostridium difficile is an anaerobic and spore-forming bacterium responsible for 15–25% of postantibiotic diarrhea and 95% of pseudomembranous colitis. Peptidoglycan is a crucial element of the bacterial cell wall that is exposed to the host, making it an important target for the innate immune system. The C. difficile peptidoglycan is largely N-deacetylated on its glucosamine (93% of muropeptides) through the activity of enzymes known as N-deacetylases, and this N-deacetylation modulates host–pathogen interactions, such as resistance to the bacteriolytic activity of lysozyme, virulence, and host innate immune responses. C. difficile genome analysis showed that 12 genes potentially encode N-deacetylases; however, which of these N-deacetylases are involved in peptidoglycan N-deacetylation remains unknown. Here, we report the enzymes responsible for peptidoglycan N-deacetylation and their respective regulation. Through peptidoglycan analysis of several mutants, we found that the N-deacetylases PdaV and PgdA act in synergy. Together they are responsible for the high level of peptidoglycan N-deacetylation in C. difficile and the consequent resistance to lysozyme. We also characterized a third enzyme, PgdB, as a glucosamine N-deacetylase. However, its impact on N-deacetylation and lysozyme resistance is limited, and its physiological role remains to be dissected. Finally, given the influence of peptidoglycan N-deacetylation on host defense against pathogens, we investigated the virulence and colonization ability of the mutants. Unlike what has been shown in other pathogenic bacteria, a lack of N-deacetylation in C. difficile is not linked to a decrease in virulence.

Managing natural resources

Research analyzing options for the sustainable management of natural resources and how to use them in a way that enhances the resilience of ecosystems.

Areas of focus include examining what is the future for fossil fuels and other extractive industries (especially coal, oil and natural gas), forest governance in light of continued illegal logging and deforestation, and ocean governance.

Natural resources are vital for the future sustainability of major industries such as agriculture, mining, tourism, fisheries and forestry. Research is carried out in areas such as land use planning, water management, biodiversity conservation, and the scientific and technical understanding of resources governance.

Broad-specificity glycoside hydrolases (GHs) contribute to plant biomass hydrolysis by degrading a diverse range of polysaccharides, making them useful catalysts for renewable energy and biocommodity production. Discovery of new GHs with improved kinetic parameters or more tolerant substrate-binding sites could increase the efficiency of renewable bioenergy production even further. GH5 has over 50 subfamilies exhibiting selectivities for reaction with β-(1,4)–linked oligo- and polysaccharides. Among these, subfamily 4 (GH5_4) contains numerous broad-selectivity endoglucanases that hydrolyze cellulose, xyloglucan, and mixed-linkage glucans. We previously surveyed the whole subfamily and found over 100 new broad-specificity endoglucanases, although the structural origins of broad specificity remained unclear. A mechanistic understanding of GH5_4 substrate specificity would help inform the best protein design strategies and the most appropriate industrial application of broad-specificity endoglucanases. Here we report structures of 10 new GH5_4 enzymes from cellulolytic microbes and characterize their substrate selectivity using normalized reducing sugar assays and MS. We found that GH5_4 enzymes have the highest catalytic efficiency for hydrolysis of xyloglucan, glucomannan, and soluble β-glucans, with opportunistic secondary reactions on cellulose, mannan, and xylan. The positions of key aromatic residues determine the overall reaction rate and breadth of substrate tolerance, and they contribute to differences in oligosaccharide cleavage patterns. Our new composite model identifies several critical structural features that confer broad specificity and may be readily engineered into existing industrial enzymes. We demonstrate that GH5_4 endoglucanases can have broad specificity without sacrificing high activity, making them a valuable addition to the biomass deconstruction toolset.

Arabinogalactan proteins (AGPs) are plant proteoglycans with functions in growth and development. However, these functions are largely unexplored, mainly because of the complexity of the sugar moieties. These carbohydrate sequences are generally analyzed with the aid of glycoside hydrolases. The exo-β-1,3-galactanase is a glycoside hydrolase from the basidiomycete Phanerochaete chrysosporium (Pc1,3Gal43A), which specifically cleaves AGPs. However, its structure is not known in relation to its mechanism bypassing side chains. In this study, we solved the apo and liganded structures of Pc1,3Gal43A, which reveal a glycoside hydrolase family 43 subfamily 24 (GH43_sub24) catalytic domain together with a carbohydrate-binding module family 35 (CBM35) binding domain. GH43_sub24 is known to lack the catalytic base Asp conserved among other GH43 subfamilies. Our structure in combination with kinetic analyses reveals that the tautomerized imidic acid group of Gln263 serves as the catalytic base residue instead. Pc1,3Gal43A has three subsites that continue from the bottom of the catalytic pocket to the solvent. Subsite −1 contains a space that can accommodate the C-6 methylol of Gal, enabling the enzyme to bypass the β-1,6–linked galactan side chains of AGPs. Furthermore, the galactan-binding domain in CBM35 has a different ligand interaction mechanism from other sugar-binding CBM35s, including those that bind galactomannan. Specifically, we noted a Gly → Trp substitution, which affects pyranose stacking, and an Asp → Asn substitution in the binding pocket, which recognizes β-linked rather than α-linked Gal residues. These findings should facilitate further structural analysis of AGPs and may also be helpful in engineering designer enzymes for efficient biomass utilization.

Methionine, through S-adenosylmethionine, activates a multifaceted growth program in which ribosome biogenesis, carbon metabolism, and amino acid and nucleotide biosynthesis are induced. This growth program requires the activity of the Gcn4 transcription factor (called ATF4 in mammals), which facilitates the supply of metabolic precursors that are essential for anabolism. However, how Gcn4 itself is regulated in the presence of methionine is unknown. Here, we discover that Gcn4 protein levels are increased by methionine, despite conditions of high cell growth and translation (in which the roles of Gcn4 are not well-studied). We demonstrate that this mechanism of Gcn4 induction is independent of transcription, as well as the conventional Gcn2/eIF2α-mediated increased translation of Gcn4. Instead, when methionine is abundant, Gcn4 phosphorylation is decreased, which reduces its ubiquitination and therefore degradation. Gcn4 is dephosphorylated by the protein phosphatase 2A (PP2A); our data show that when methionine is abundant, the conserved methyltransferase Ppm1 methylates and alters the activity of the catalytic subunit of PP2A, shifting the balance of Gcn4 toward a dephosphorylated, stable state. The absence of Ppm1 or the loss of the PP2A methylation destabilizes Gcn4 even when methionine is abundant, leading to collapse of the Gcn4-dependent anabolic program. These findings reveal a novel, methionine-dependent signaling and regulatory axis. Here methionine directs the conserved methyltransferase Ppm1 via its target phosphatase PP2A to selectively stabilize Gcn4. Through this, cells conditionally modify a major phosphatase to stabilize a metabolic master regulator and drive anabolism.

Pyrroline-5-carboxylate reductase 1 (PYCR1) catalyzes the biosynthetic half-reaction of the proline cycle by reducing Δ1-pyrroline-5-carboxylate (P5C) to proline through the oxidation of NAD(P)H. Many cancers alter their proline metabolism by up-regulating the proline cycle and proline biosynthesis, and knockdowns of PYCR1 lead to decreased cell proliferation. Thus, evidence is growing for PYCR1 as a potential cancer therapy target. Inhibitors of cancer targets are useful as chemical probes for studying cancer mechanisms and starting compounds for drug discovery; however, there is a notable lack of validated inhibitors for PYCR1. To fill this gap, we performed a small-scale focused screen of proline analogs using X-ray crystallography. Five inhibitors of human PYCR1 were discovered: l-tetrahydro-2-furoic acid, cyclopentanecarboxylate, l-thiazolidine-4-carboxylate, l-thiazolidine-2-carboxylate, and N-formyl l-proline (NFLP). The most potent inhibitor was NFLP, which had a competitive (with P5C) inhibition constant of 100 μm. The structure of PYCR1 complexed with NFLP shows that inhibitor binding is accompanied by conformational changes in the active site, including the translation of an α-helix by 1 Å. These changes are unique to NFLP and enable additional hydrogen bonds with the enzyme. NFLP was also shown to phenocopy the PYCR1 knockdown in MCF10A H-RASV12 breast cancer cells by inhibiting de novo proline biosynthesis and impairing spheroidal growth. In summary, we generated the first validated chemical probe of PYCR1 and demonstrated proof-of-concept for screening proline analogs to discover inhibitors of the proline cycle.

Visual Abstract

Visual Abstract

Toma Keser
Dec 29, 2020; 0:RA120.002433v1-mcp.RA120.002433
Research

Litong Nie
Dec 1, 2020; 19:2015-2029
Research

Sylwia Struk
Dec 28, 2020; 0:RA119.001766v1-mcp.RA119.001766
Research

David Durán
Nov 19, 2020; 0:RA120.002276v1-mcp.RA120.002276
Research

Xinting Zhang
Dec 8, 2020; 0:RA120.002306v1-mcp.RA120.002306
Research

Juntuo Zhou
Nov 30, 2020; 0:RA120.002384v1-mcp.RA120.002384
Research

Colin T. McDowell
Nov 24, 2020; 0:RA120.002256v1-mcp.RA120.002256
Research

Daniel J. Geiszler
Dec 1, 2020; 0:TIR120.002216v1-mcp.TIR120.002216
Technological Innovation and Resources

Johannes Griss
Dec 1, 2020; 19:2115-2124
Technological Innovation and Resources

Diana Samodova
Dec 1, 2020; 19:2139-2156
Technological Innovation and Resources

Protein quality control is maintained by a number of integrated cellular pathways that monitor the folding and functionality of the cellular proteome. Defects in these pathways lead to the accumulation of misfolded or faulty proteins that may become insoluble and aggregate over time. Protein aggregates significantly contribute to the development of a number of human diseases such as amyotrophic lateral sclerosis, Huntington's disease, and Alzheimer's disease. In vitro, imaging-based, cellular studies have defined key biomolecular components that recognize and clear aggregates; however, no unifying method is available to quantify cellular aggregates, limiting our ability to reproducibly and accurately quantify these structures. Here we describe an ImageJ macro called AggreCount to identify and measure protein aggregates in cells. AggreCount is designed to be intuitive, easy to use, and customizable for different types of aggregates observed in cells. Minimal experience in coding is required to utilize the script. Based on a user-defined image, AggreCount will report a number of metrics: (i) total number of cellular aggregates, (ii) percentage of cells with aggregates, (iii) aggregates per cell, (iv) area of aggregates, and (v) localization of aggregates (cytosol, perinuclear, or nuclear). A data table of aggregate information on a per cell basis, as well as a summary table, is provided for further data analysis. We demonstrate the versatility of AggreCount by analyzing a number of different cellular aggregates including aggresomes, stress granules, and inclusion bodies caused by huntingtin polyglutamine expansion.

Montgomery Blencowe
Dec 23, 2020; 0:jlr.RA120000713v1-jlr.RA120000713
Research Articles

You encounter this issue when the table metadata matches the data source. In this scenario, no metadata update is required.

In SAS Business Rules Manager 3.3, the initial loading of a rule set and a rule flow takes significantly longer than it does in release 3.2. When this problem happens, long time gaps are evident in the local

In SAS Life Science Analytics Framework 4.6, group membership removal fails with an exception if a user is set as assignee, a candidate, or a notification recipient in a user task for a Process Flow . The Process

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SAS  Episode Analytics 3.1 requires the ability to capture user interactions with the user interface for auditing purposes. To support the required functionality a new table has been add

When viewing a SAS Visual Analytics report, you might intermittently see an error that includes content similar to the following:

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When you publish a model to SAS Metadata Repository by using SAS Model Manager, the publishing process fails and the following error is generated: "The model model-name has a function of ';Transformation';, which is not supported for

Genome-wide association studies (GWAS) have implicated ~380 genetic loci for plasma lipid regulation. However, these loci only explain 17-27% of the trait variance and a comprehensive understanding of the molecular mechanisms has not been achieved. In this study, we utilized an integrative genomics approach leveraging diverse genomic data from human populations to investigate whether genetic variants associated with various plasma lipid traits, namely total cholesterol (TC), high and low density lipoprotein cholesterol (HDL and LDL), and triglycerides (TG), from GWAS were concentrated on specific parts of tissue-specific gene regulatory networks. In addition to the expected lipid metabolism pathways, gene subnetworks involved in ‘interferon signaling’, ‘autoimmune/immune activation’, ‘visual transduction’, and ‘protein catabolism’ were significantly associated with all lipid traits. Additionally, we detected trait-specific subnetworks, including cadherin-associated subnetworks for LDL, glutathione metabolism for HDL, valine, leucine and isoleucine biosynthesis for TC, and insulin signaling and complement pathways for TG. Finally, utilizing gene-gene relations revealed by tissue-specific gene regulatory networks, we detected both known (e.g. APOH, APOA4, and ABCA1) and novel (e.g. F2 in adipose tissue) key regulator genes in these lipid-associated subnetworks. Knockdown of the F2 gene (Coagulation Factor II, Thrombin) in 3T3-L1 and C3H10T1/2 adipocytes reduced gene expression of Abcb11, Apoa5, Apof, Fabp1, Lipc, and Cd36, reduced intracellular adipocyte lipid content, and increased extracellular lipid content, supporting a link between adipose thrombin and lipid regulation. Our results shed light on the complex mechanisms underlying lipid metabolism and highlight potential novel targets for lipid regulation and lipid-associated diseases.