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Introduction SUV measurements from static brain [ 18 F]FDG PET acquisitions are a commonly used tool in preclinical research, providing a simple alternative for kinetic modelling, which requires complex and time-consuming dynamic acquisitions. However, SUV can be severely affected by the animal handling and preconditioning protocols, primarily by those that may induce changes in blood glucose levels (BGL). Here, we aimed at developing and investigating the feasibility of SUV-based approaches for a wide range of BGL far beyond normal values, and consequently, to develop and validate a new model to generate standardized and reproducible SUV measurements for any BGL. Material and methods We performed dynamic and static brain [ 18 F]FDG PET acquisitions in 52 male Sprague-Dawley rats sorted into control (n = 10), non-fasting (n = 14), insulin-induced hypoglycemia (n = 12) and glucagon-induced hyperglycemia (n = 16) groups. Brain [ 18 F]FDG PET images were cropped, aligned and co-registered to a standard template to calculate whole-brain and regional SUV. Cerebral Metabolic Rate of Glucose (CMRglc) was also estimated from 2-Tissue Compartment Model (2TCM) and Patlak plot for validation purposes. Results Our results showed that BGL=100±6 mg/dL can be considered a reproducible reference value for normoglycemia. Furthermore, we successfully established a 2nd-degree polynomial model (C 1 =0.66E-4, C 2 =-0.0408 and C 3 =7.298) relying exclusively on BGL measures at pre-[ 18 F]FDG injection time, that characterizes more precisely the relationship between SUV and BGL for a wide range of BGL values (from 10 to 338 mg/dL). We confirmed the ability of this model to generate corrected SUV estimations that are highly correlated to CMRglc estimations (R 2 = 0.54 2TCM CMRgluc and R 2 = 0.49 Patlak CMRgluc). Besides, slight regional differences in SUV were found in animals from extreme BGL groups, showing that [ 18 F]FDG uptake is mostly directed toward central regions of the brain when BGLs are significantly decreased. Conclusion Our study successfully established a non-linear model that relies exclusively on pre-scan BGL measurements to characterize the relationship between [ 18 F]FDG SUV and BGL. The extensive validation confirmed its ability to generate SUV-based surrogates of CMRglu along a wide range of BGL and it holds the potential to be adopted as a standard protocol by the preclinical neuroimaging community using brain [ 18 F]FDG PET imaging., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Rare earth elements (REE) are essential ingredients in many modern technologies, yet their purification remains either environmentally harmful or economically unviable. Adsorption, or biosorption, of REE onto bacterial cell membranes offers a sustainable alternative to traditional solvent extraction methods. But in order for biosorption-based REE purification to compete economically, the capacity and specificity of biosorption sites must be enhanced. Although there have been some recent advances in characterizing the genetics of REE-biosorption, the variety and complexity of bacterial membrane surface sites make targeted genetic engineering difficult. Here, we propose using multiple rounds of in vivo random mutagenesis induced by the MP6 plasmid combined with plate-throughput REE-biosorption screening to improve a microbe's capacity and selectivity for biosorbing REE. We engineered a strain of Vibrio natriegens capable of biosorbing 210% more dysprosium compared to the wild-type and produced selectivity improvements of up to 50% between the lightest (lanthanum) and heaviest (lutetium) REE. We believe that mutations we observed in ABC transporters as well as a nonessential protein in the BAM outer membrane β-barrel protein insertion complex likely contribute to some─but almost certainly not all─of the biosorption changes we observed. Given the ease of finding significant biosorption mutants, these results highlight just how many genes likely contribute to biosorption as well as the power of random mutagenesis in identifying genes of interest and optimizing a biological system for a task.

Rare earth elements (REE) are essential ingredients of sustainable energy technologies, but separation of individual REE is one of the hardest problems in chemistry today. Biosorption, where molecules adsorb to the surface of biological materials, offers a sustainable alternative to environmentally harmful solvent extractions currently used for separation of rare earth elements (REE). The REE-biosorption capability of some microorganisms allows for REE separations that, under specialized conditions, are already competitive with solvent extractions, suggesting that genetic engineering could allow it to leapfrog existing technologies. To identify targets for genomic improvement we screened 3,373 mutants from the whole genome knockout collection of the known REE-biosorbing microorganism Shewanella oneidensis MR-1. We found 130 genes that increased biosorption of the middle REE europium, and 112 that reduced it. We verified biosorption changes from the screen for a mixed solution of three REE (La, Eu, Yb) using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) in solution conditions with a range of ionic strengths and REE concentrations. We identified 18 gene ontologies and 13 gene operons that make up key systems that affect biosorption. We found, among other things, that disruptions of a key regulatory component of the arc system (hptA), which regulates cellular response to anoxic environments and polysaccharide biosynthesis related genes (wbpQ, wbnJ, SO_3183) consistently increase biosorption across all our solution conditions. Our largest total biosorption change comes from our SO_4685, a capsular polysaccharide (CPS) synthesis gene, disruption of which results in an up to 79% increase in biosorption; and nusA, a transcriptional termination/anti-termination protein, disruption of which results in an up to 35% decrease in biosorption. Knockouts of glnA, pyrD, and SO_3183 produce small but significant increases (≈ 1%) in relative biosorption affinity for ytterbium over lanthanum in multiple solution conditions tested, while many other genes we explored have more complex binding affinity changes. Modeling suggests that while these changes to lanthanide biosorption selectivity are small, they could already reduce the length of repeated enrichment process by up to 27%. This broad exploratory study begins to elucidate how genetics affect REE-biosorption by S. oneidensis, suggests new areas of investigation for better mechanistic understanding of the membrane chemistry involved in REE binding, and offer potential targets for improving biosorption and separation of REE by genetic engineering., (© 2023. Springer Nature Limited.)

Bioleaching of rare earth elements (REEs), using microorganisms such as Gluconobacter oxydans, offers a sustainable alternative to environmentally harmful thermochemical extraction, but is currently not very efficient. Here, we generate a whole-genome knockout collection of single-gene transposon disruption mutants for G. oxydans B58, to identify genes affecting the efficacy of REE bioleaching. We find 304 genes whose disruption alters the production of acidic biolixiviant. Disruption of genes underlying synthesis of the cofactor pyrroloquinoline quinone (PQQ) and the PQQ-dependent membrane-bound glucose dehydrogenase nearly eliminates bioleaching. Disruption of phosphate-specific transport system genes enhances bioleaching by up to 18%. Our results provide a comprehensive roadmap for engineering the genome of G. oxydans to further increase its bioleaching efficiency., (© 2021. The Author(s).)