Biology subjects

Young, T. R.

Publications and source records attributed to Young, T. R..

4 recordsLinked to original sources

bioRxiv2022

Hyperaerated metalation calculator for E. coli strain JM109 (DE3) grown in LB media

We recently produced three web-based calculators that predict in vivo metal occupancies of proteins, based on the metal affinities of a protein of interest along with estimates of the availabilities of the labile buffered pools of metals inside a cell. Metal availabilities were calculated from the calibrated responses of DNA-binding, metal-sensing, transcriptional regulators. The availability of intracellular Fe(II) was estimated to be similar in E. coli grown under anaerobic conditions compared to cells grown aerobically in LB medium. The purpose of this article is to archive the background data that underpins the release of a new calculator for hyperaerated cells grown in flasks with baffles, with relatively low culture volumes plus high shaking speeds to give elevated oxygenation. The intracellular availability of Fe(II) calculated from the responses of the intracellular Fe(II) sensor Fur was estimated to be significantly lower in these hyperaerated cells than either of the previous values determined for anaerobic or aerobic cultures. The total number of atoms of Mn(II) per cell increased in hyperaerated cells albeit with only modest change in intracellular Mn(II) availability as estimated from the responses of the Mn(II) sensor MntR. Accurate determination of intracellular Ni(II) availability will require further calibration of the magnitude of the responses of the Ni(II) sensor NikR in hyperaerated cells to take account of the state of Fnr. The hyperaerated metalation calculator is made available online and as a spreadsheet, for use by others.

biochemistry↗

bioRxiv2022

Metalation calculators for E. coli strain JM109 (DE3): Aerobic, anaerobic and hydrogen peroxide exposed cells cultured in LB media

Three web-based calculators, and three analogous spreadsheets, have been generated that predict in vivo metal occupancies of proteins based on known metal affinities. The calculations exploit estimates of the availabilities of the labile buffered pools of different metals inside a cell. Here, metal availabilities have been estimated for a strain of E. coli that is commonly used in molecular biology and biochemistry research, for example in the production of recombinant proteins. Metal availabilities have been examined for cells grown in LB medium aerobically, anaerobically and in response to H2O2 by monitoring the abundance of a selected set of metal-responsive transcripts by qPCR. The selected genes are regulated by DNA-binding metal sensors that have been thermodynamically characterised in related bacterial cells enabling gene expression to be read-out as a function of intracellular metal availabilities expressed as free energies for forming metal complexes. The calculators compare these values with the free energies for forming complexes with the protein of interest, derived from metal affinities, to estimate how effectively the protein can compete with exchangeable binding sites in the intracellular milieu. The calculators then inter-compete the different metals, limiting total occupancy of the site to a maximum stoichiometry of 1, to output percentage occupancies with each metal. In addition to making these new and conditional calculators available, an original purpose of this article was to provide a tutorial which discusses constraints of this approach and presents ways in which such calculators might be exploited in basic and applied research, and in next-generation manufacturing.

cell biology↗

bioRxiv2020

Calculating metalation in cells reveals CobW acquires CoII for vitamin B12 biosynthesis upon binding nucleotide

Protein metal-occupancy (metalation) in vivo has been elusive. Here we develop a metalation-calculator which accounts for inter-metal competition and changing metal-availabilities inside cells. The calculations are based on available free-energies of metals determined from the responses of metal sensors. We use the calculator to understand the function and mechanism of CobW, a predicted CoII-chaperone for vitamin B12. CobW is calculated to acquire negligible metal alone: But, upon binding nucleotide (GTP) and MgII, CobW assembles a high-affinity site that can obtain CoII or ZnII from the intracellular milieu. In idealised cells with sensors at the mid-points of their responses, competition within the cytosol enables CoII to outcompete ZnII for binding CobW. Thus, CoII is the cognate metal. However, after growth in different [CoII], CoII-occupancy ranges from 10 to 97% which matches CobW-dependent B12 synthesis. The calculator reveals how CobW acquires its metal and is made available for use with other proteins.

biochemistry↗

bioRxiv2018

CD117/c-kit in Cancer Stem Cell-Mediated Progression and Therapeutic Resistance

Metastasis is the primary cause of cancer patient morbidity and mortality but due to persisting gaps in our knowledge, it remains untreatable. Metastases often occur as patients' tumors progress or recur after initial therapy. Tumor recurrence at the primary site may be driven by a cancer stem-like cell or tumor progenitor cell, while recurrence at a secondary site is driven by metastatic cancer stem cells or metastasis-initiating cells. Ongoing efforts are aimed at identifying and characterizing these stem-like cells driving recurrence and metastasis. One potential marker for the cancer stem-like cell subpopulation is CD117/c-kit, a tyrosine kinase receptor associated with cancer progression and normal stem cell maintenance. In our analyses, CD117 was expressed in several tissues and was highly expressed in bone marrow progenitor cells. Also, we uncovered that CD117 gene amplifications and mutations occurred in multiple cancers. Further, activation of CD117 by its ligand stem cell factor (SCF; kit ligand) in the progenitor cell niche stimulates several signaling pathways driving proliferation, survival, and migration. These signaling pathways were commonly altered in patients with CD117 amplifications and mutations. Here, we examine evidence that the SCF/CD117 signaling axis controls cancer progression through the regulation of stemness and resistance to tyrosine kinase inhibitors.\n\nAbbreviations

cancer biology↗