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1. Introducing the ArsR-Regulated Arsenic Stimulon

   https://doi.org/10.3389/fmicb.2021.630562  

   Rawle, Rachel ; Saley, Tara C. ; Kang, Yoon-Suk ; Wang, Qian ; Walk, Seth ; Bothner, Brian ; McDermott, Timothy R. ( March 2021 , Frontiers in Microbiology)

   null (Ed.)

   The microbial ars operon encodes the primary bacterial defense response to the environmental toxicant, arsenic. An important component of this operon is the arsR gene, which encodes ArsR, a member of the family of proteins categorized as DNA-binding transcriptional repressors. As currently documented, ArsR regulates its own expression as well as other genes in the same ars operon. This study examined the roles of four ArsR proteins in the well-developed model Gram-negative bacterium Agrobacterium tumefaciens 5A. RNASeq was used to compare and characterize gene expression profiles in ± arsenite-treated cells of the wild-type strain and in four different arsR mutants. We report that ArsR-controlled transcription regulation is truly global, extending well beyond the current ars operon model, and includes both repression as well as apparent activation effects. Many cellular functions are significantly influenced, including arsenic resistance, phosphate acquisition/metabolism, sugar transport, chemotaxis, copper tolerance, iron homeostasis, and many others. While there is evidence of some regulatory overlap, each ArsR exhibits its own regulatory profile. Furthermore, evidence of a regulatory hierarchy was observed; i.e. ArsR1 represses arsR4 , ArsR4 activates arsR2 , and ArsR2 represses arsR3 . Additionally and unexpectedly, aioB (arsenite oxidase small subunit) expression was shown to be under partial positive control by ArsR2 and ArsR4. Summarizing, this study demonstrates the regulatory portfolio of arsenite-activated ArsR proteins and includes essentially all major cellular functions. The broad bandwidth of arsenic effects on microbial metabolism assists in explaining and understanding the full impact of arsenic in natural ecosystems, including the mammalian gut. 

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2. Protein-Cadmium Interactions in Crowded Biomolecular Environments Probed by In-cell and Lysate NMR Spectroscopy

   Sachin S. Katti, Tatyana I. ( November 2023 , bioRxiv)

   One of the mechanisms by which toxic metal ions interfere with cellular functions is ionic mimicry, where they bind to protein sites in lieu of native metals Ca2+ and Zn2+. The influence of crowded intracellular environments on these interactions is not well understood. Here, we demonstrate the application of in-cell and lysate NMR spectroscopy to obtain atomic-level information on how a potent environmental toxin cadmium interacts with its protein targets. The experiments, conducted in intact E. coli cells and their lysates, revealed that Cd2+ can profoundly affect the quinary interactions of its protein partners, and can replace Zn2+ in both labile and non-labile protein structural sites without significant perturbation of the membrane binding function. Surprisingly, in crowded molecular environments Cd2+ can effectively target not only all-sulfur and mixed sulfur/nitrogen but also all-oxygen coordination sites. The sulfur-rich coordination environments show significant promise for bioremedial applications, as demonstrated by the ability of the designed protein scaffold α3DIV to sequester intracellular cadmium. Our data suggests that in-cell NMR spectroscopy is a powerful tool for probing interactions of toxic metal ions with their potential protein targets, and for the assessment of potency of sequestering agents. 

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3. Manganese Is Required for the Rapid Recovery of DNA Synthesis following Oxidative Challenge in Escherichia coli

   https://doi.org/10.1128/JB.00426-19  

   Hutfilz, Corinne R. ; Wang, Natalie E. ; Hoff, Chettar A. ; Lee, Jessica A. ; Hackert, Brandy J. ; Courcelle, Justin ; Courcelle, Charmain T. ; Metcalf, William W. ( December 2019 , Journal of Bacteriology)

   ABSTRACT Divalent metals such as iron and manganese play an important role in the cellular response to oxidative challenges and are required as cofactors by many enzymes. However, how these metals affect replication after oxidative challenge is not known. Here, we show that replication in Escherichia coli is inhibited following a challenge with hydrogen peroxide and requires manganese for the rapid recovery of DNA synthesis. We show that the manganese-dependent recovery of DNA synthesis occurs independent of lesion repair, modestly improves cell survival, and is associated with elevated rates of mutagenesis. The Mn-dependent mutagenesis involves both replicative and translesion polymerases and requires prior disruption by H 2 O 2 to occur. Taking these findings together, we propose that replication in E. coli is likely to utilize an iron-dependent enzyme(s) that becomes oxidized and inactivated during oxidative challenges. The data suggest that manganese remetallates these or alternative enzymes to allow genomic DNA replication to resume, although with reduced fidelity. IMPORTANCE Iron and manganese play important roles in how cell’s cope with oxygen stress. However, how these metals affect the ability of cells to replicate after oxidative challenges is not known. Here, we show that replication in Escherichia coli is inhibited following a challenge with hydrogen peroxide and requires manganese for the rapid recovery of DNA synthesis. The manganese-dependent recovery of DNA synthesis occurs independently of lesion repair and modestly improves survival, but it also increases the mutation rate in cells. The results imply that replication in E. coli is likely to utilize an iron-dependent enzyme(s) that becomes oxidized and inactivated during oxidative challenges. We propose that manganese remetallates these or alternative enzymes to allow genomic DNA replication to resume, although with reduced fidelity. 

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4. Bayesian varying coefficient kernel machine regression to assess neurodevelopmental trajectories associated with exposure to complex mixtures

   https://doi.org/10.1002/sim.7947  

   Liu, Shelley H. ; Bobb, Jennifer F. ; Claus Henn, Birgit ; Gennings, Chris ; Schnaas, Lourdes ; Tellez‐Rojo, Martha ; Bellinger, David ; Arora, Manish ; Wright, Robert O. ; Coull, Brent A. ( September 2018 , Statistics in Medicine)

   Exposure to environmental mixtures can exert wide‐ranging effects on child neurodevelopment. However, there is a lack of statistical methods that can accommodate the complex exposure‐response relationship between mixtures and neurodevelopment while simultaneously estimating neurodevelopmental trajectories. We introduce Bayesian varying coefficient kernel machine regression (BVCKMR), a hierarchical model that estimates how mixture exposures at a given time point are associated with health outcome trajectories. The BVCKMR flexibly captures the exposure‐response relationship, incorporates prior knowledge, and accounts for potentially nonlinear and nonadditive effects of individual exposures. This model assesses the directionality and relative importance of a mixture component on health outcome trajectories and predicts health effects for unobserved exposure profiles. Using contour plots and cross‐sectional plots, BVCKMR also provides information about interactions between complex mixture components. The BVCKMR is applied to a subset of data from PROGRESS, a prospective birth cohort study in Mexico city on exposure to metal mixtures and temporal changes in neurodevelopment. The mixture include metals such as manganese, arsenic, cobalt, chromium, cesium, copper, lead, cadmium, and antimony. Results from a subset of Programming Research in Obesity, Growth, Environment and Social Stressors data provide evidence of significant positive associations between second trimester exposure to copper and Bayley Scales of Infant and Toddler Development cognition score at 24 months, and cognitive trajectories across 6‐24 months. We also detect an interaction effect between second trimester copper and lead exposures for cognition at 24 months. In summary, BVCKMR provides a framework for estimating neurodevelopmental trajectories associated with exposure to complex mixtures.

    

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5. mebipred : identifying metal-binding potential in protein sequence

   https://doi.org/10.1093/bioinformatics/btac358  

   Aptekmann, A. A. ; Buongiorno, J. ; Giovannelli, D. ; Glamoclija, M. ; Ferreiro, D. U. ; Bromberg, Y. ; Cowen, ed., Lenore ( May 2022 , Bioinformatics)

   metal-binding proteins have a central role in maintaining life processes. Nearly one-third of known protein structures contain metal ions that are used for a variety of needs, such as catalysis, DNA/RNA binding, protein structure stability, etc. Identifying metal-binding proteins is thus crucial for understanding the mechanisms of cellular activity. However, experimental annotation of protein metal-binding potential is severely lacking, while computational techniques are often imprecise and of limited applicability.

   we developed a novel machine learning-based method, mebipred, for identifying metal-binding proteins from sequence-derived features. This method is over 80% accurate in recognizing proteins that bind metal ion-containing ligands; the specific identity of 11 ubiquitously present metal ions can also be annotated. mebipred is reference-free, i.e. no sequence alignments are involved, and is thus faster than alignment-based methods; it is also more accurate than other sequence-based prediction methods. Additionally, mebipred can identify protein metal-binding capabilities from short sequence stretches, e.g. translated sequencing reads, and, thus, may be useful for the annotation of metal requirements of metagenomic samples. We performed an analysis of available microbiome data and found that ocean, hot spring sediments and soil microbiomes use a more diverse set of metals than human host-related ones. For human microbiomes, physiological conditions explain the observed metal preferences. Similarly, subtle changes in ocean sample ion concentration affect the abundance of relevant metal-binding proteins. These results highlight mebipred’s utility in analyzing microbiome metal requirements.

   mebipred is available as a web server at services.bromberglab.org/mebipred and as a standalone package at https://pypi.org/project/mymetal/.

   Supplementary data are available at Bioinformatics online.

    

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