Biology subjects

Robinson, N. J.

Publications and source records attributed to Robinson, N. J..

8 recordsLinked to original sources

bioRxiv2025

Morphine regulates astrocyte transcriptional dynamics in the ventral tegmental area by stimulation of glucocorticoid signaling

Opioids are potent analgesics often prescribed for the treatment of chronic pain, a condition affecting millions worldwide. Although pain states increase vulnerability to opioid use disorders, the neural mechanisms underlying this interaction remain incompletely understood. The ventral tegmental area (VTA) is a key site for opioid actions, and emerging evidence suggests that pain states and opioid experience both induce transcriptional, molecular, and circuit adaptations in the VTA that contribute to motivated behaviors. However, the transcriptional responses of distinct VTA cell types to each of these factors (alone or in combination) have not been identified. Here, we employed single-nucleus RNA sequencing to comprehensively define transcriptional alterations in the rat VTA to acute morphine administration in a chronic inflammatory pain model. We report that morphine induces gene expression changes primarily in glial cells and dopamine neurons, with minimal effects in other neuronal cell types. Surprisingly, VTA astrocytes and oligodendrocytes exhibited the most robust transcriptional responses to opioid exposure, despite lacking detectable opioid receptor expression. Among the most highly regulated glial genes was Fkbp5, which encodes a co-chaperone protein that acts in concert with heat shock proteins to modulate stress responses. Using pharmacological and CRISPR-based approaches in rat glial cells and human astrocytes, we demonstrate that regulation of Fkbp5 is mediated indirectly through glucocorticoid signaling rather than direct opioid receptor activation. These findings reveal that glial cells within reward circuits undergo profound transcriptional reprogramming in response to opioids through indirect, stress-hormone mediated mechanisms, highlighting a previously unappreciated non-neuronal contribution to opioid-induced neural adaptations.

neuroscience↗

bioRxiv2025

Metalation calculator for E. coli strain BW25113 grown in M9 minimal media

Here we provide the background data supporting an additional web-based calculator to predict in-cell metalation of proteins within E. coli BW25113 grown in M9 media. Intracellular metal availabilities have been estimated from the calibrated responses of DNA-binding, metal-sensing, transcriptional regulators. We have previously tested and validated metalation calculator predictions. They confirm that when proteins are expressed heterologously in E. coli in LB medium, they can become mismatched to metal availability and be mismetalated. Mg2+GTP-CobW from Rhodobacter is predicted to be correctly metalated with cobalt in E. coli grown in M9 media, although mismetalated with zinc in LB-grown heterologous cells. Similarly, MncA from Synechocystis PCC 6803 is predicted to be correctly metalated with manganese in E. coli grown in M9 media, although mismetalated with iron in LB-grown heterologous cells. The M9 metalation calculator is available online and as a spreadsheet for use in optimising metalation in engineering biology. An MncA-refined metalation calculator for idealised cells, reflecting the midpoint of intracellular metal availabilities, is also included and available online.

biochemistry↗

bioRxiv2024

Accurate sample deconvolution of pooled snRNA-seq using sex-dependent gene expression patterns

Single-nucleus RNA sequencing (snRNA-seq) technology offers unprecedented resolution for studying cell type-specific gene expression patterns. However, snRNA-seq poses high costs and technical limitations, often requiring the pooling of independent biological samples and the loss of individual sample-level data. Deconvolution of sample identity using inherent features would enable the incorporation of pooled barcoding and sequencing protocols, thereby increasing data throughput and analytical sample size without requiring increases in experimental sample size and sequencing costs. In this study, we demonstrate a proof of concept that sex-dependent gene expression patterns can be leveraged for the deconvolution of pooled snRNA-seq data. Using previously published snRNA-seq data from the rat ventral tegmental area, we trained a range of machine learning models to classify cell sex using genes differentially expressed in cells from male and female rats. Models that used sex-dependent gene expression predicted cell sex with high accuracy (93-95%) and outperformed simple classification models using only sex chromosome gene expression (88-90%). The generalizability of these models to other brain regions was assessed using an additional published data set from the rat nucleus accumbens. Within this data set, model performance remained highly accurate in cell sex classification (90-92% accuracy) with no additional training. This work provides a model for future snRNA-seq studies to perform sample deconvolution using a two-sex pooled sample sequencing design and benchmarks the performance of various machine learning approaches to deconvolve sample identification from inherent sample features.

genomics↗

bioRxiv2023

A peptide that regulates metalation of the Arabidopsis ethylene receptor.

Ethylene signalling represents one of the classic hormonal pathways in plants, with diverse roles in development and stress responses. The dimeric ethylene receptor localizes to the endoplasmic reticulum (ER) and contains Cu(I) ions essential for ethylene binding and signal transduction. We previously discovered that mutants in the Arabidopsis gene POLARIS (PLS), encoding a 36 amino acid peptide, exhibit enhanced ethylene signalling responses, suggestive of reduced receptor activity, but the role and activity of the peptide in this signalling cascade has not been defined. Here we report PLS binds copper as a 1:2 thiol-dependent Cu(I):PLS2 complex, with an affinity of 3.79 ({+/-}1.5) x1019 M-2, via two cysteine residues also found in the related species Camelina sativa. These residues are also essential for biological function. This affinity precludes PLS as a cytosolic Cu chaperone. We demonstrate that PLS localizes to endomembranes and interacts with the transmembrane domain of receptor protein ETR1. PLS-ETR1 binding is increased in the presence of copper, and this interaction provides a Cu-dependent mechanism for mediating a repression of ethylene responses. PLS transcription is up-regulated by auxin and down-regulated by ethylene, and so PLS-ETR1 interactions also provide a mechanism to modulate ethylene responses in high auxin tissues.

plant biology↗

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↗

bioRxiv2019

Spatial distribution of epibionts on olive ridley sea turtles at Playa Ostional, Costa Rica

There is a wealth of published information on the epibiont communities of sea turtles, yet many of these studies have exclusively sampled epibionts found only on the carapace. Considering that epibionts may be found on almost all body-surfaces and that it is highly plausible to expect different regions of the body to host distinct epibiont taxa, there is a need for quantitative comparative studies to investigate spatial variation in the epibiont communities of turtles. To achieve this, we measured how total epibiont abundance and biomass on olive ridley turtles Lepidochelys olivacea varies among four body-areas of the hosts (n = 30). We show that epibiont loads on olive ridleys are higher, both in terms of number and biomass, on the skin than they are on the carapace or plastron. This contrasts with previous findings for other hard-shelled sea turtles, where epibionts are usually more abundant on the carapace. Moreover, the arguably most ubiquitous epibiont taxon for other hard-shelled sea turtles, the barnacle Chelonibia spp., only occurs in relatively low numbers on olive ridleys, while the barnacles Stomatolepas elegans and Platylepas hexastylos are far more abundant. We postulate that these differences between the epibiont communities of different sea turtle taxa could indicate that the carapaces of olive ridley turtles provide a more challenging substratum for epibionts than do the hard shells of other sea turtles. In addition, we conclude that it is important to conduct full body surveys when attempting to produce a holistic qualitative or quantitative characterization of the epibiont communities of sea turtles.

zoology↗