Biology subjects

Noble, B.

Publications and source records attributed to Noble, B..

6 recordsLinked to original sources

bioRxiv2025

Engineering protein expression dynamics with Tet-ON and dTAG degron systems: from precise control to oscillations

Precise temporal control of protein expression is essential for dissecting protein function and dynamic cellular processes. We present a framework for engineering tunable oscillatory protein expression (repeated pulses in expression) using widely adopted molecular tools, applying them to modulate NGN3 expression. Single-cell time-lapse microscopy reveals that the Tet-On system unexpectedly generates asynchronous oscillations in protein expression under continuous doxycycline administration. These oscillations are dependent on protein instability and are not tunable by doxycycline concentration. In contrast, the dTAG degron system enables precise, reversible, concentration-dependent control of protein degradation and reaccumulation. Coupled with a constitutive promoter, we achieve synchronous oscillatory protein expression (COD: Constituitive promoter driving Oscillations via Degradation). Mathematical modelling identifies optimal dTAG drug addition and removal timings using the COD system to flexibly tune NGN3 oscillation periods while maintaining other oscillatory parameters (mean level and peak-to-trough fold-change). Using microfluidics (COD+CHIPS) we reproduce model-predicted 5 and 10 hours periodicities while maintaining similar mean levels and peak-to-trough fold-changes. This work introduces a generalisable, programmable approach for generating and modulating protein oscillations, allowing investigation into how dynamic protein expression governs cellular function.

developmental biology↗

bioRxiv2025

HES1 oscillations are required for cell cycle progression and re-entry in oestrogen receptor positive breast cancer cells

Long-term recurrence in breast cancer is driven by reactivation of dormant disseminated tumour cells (DTCs) and remains a major clinical challenge, particularly in oestrogen receptor positive (ER) tumours. This process is underpinned by regulation of the cell cycle machinery that controls quiescence maintenance and exit. HES1, a Notch pathway transcription factor, regulates key cell cycle genes and has been shown to demonstrate protein expression oscillations. Here, we sought to establish whether HES1 oscillations may regulate ER+ cancer cell quiescence and reactivation. To investigate this, we developed a fundamental in vitro model of cell cycle arrest and re-entry based on reversible CDK4/6 inhibition (CDK4/6i) with palbociclib, compatible with quantitative single-cell live-imaging of a knock-in endogenous HES1 reporter. Consistent with earlier findings, HES1 exhibited [~]24-hour protein oscillations in cycling cells demonstrating a reproducible dip in protein expression prior to S-Phase. During CDK4/6i-mediated arrest, the [~]24h HES1 oscillation was lost, HES1 levels were maintained at a moderately higher level and HES1 exhibited smaller dips. Similar changes were observed in unperturbed, spontaneously quiescent cells. Following release from CDK4/6i and cell cycle re- entry, these alterations were reversed and the characteristic G1/S HES1 dip was observed. Preventing this dip at the point of release, by inducibly sustaining HES1 with a Tet-On system, upregulated the cell cycle inhibitor p21, impeded cell cycle re-entry and induced cell death. These findings suggest that manipulating HES1 dynamics could represent a promising therapeutic approach to prevent reactivation of dormant tumour cells. Significance StatementBreast cancer can recur years after initial treatment due to reactivation of dormant tumour cells. Understanding how these cells exit dormancy is crucial for preventing relapse. We investigated HES1, a transcription factor with rhythmic protein oscillations, and its role in regulating quiescence in oestrogen receptor-positive (ER) breast cancer cells. Using live-cell imaging and a reversible cell cycle arrest model, we show that HES1 dynamics change during dormancy and reactivation, and that disrupting these oscillations prevents cell cycle re-entry and induces cell death. These findings reveal HES1 protein dynamics as a potential therapeutic vulnerability and highlight a novel strategy to target dormant cancer cells to prevent their reactivation.

cancer biology↗

bioRxiv2025

Analgesic actions of Intrathecal NaV 1.7 antisense in rats: loss of antagonist channel binding, message depletion, and neuraxial distribution of oligonucleotide

BackgroundGenome targeting strategies to address NaV 1.7 mediated signaling in nociceptive afferents produce highly selective and persistent analgesic outcomes. Here, we analyze the concentration-dependent effects of the reduction of primary afferent NaV 1.7 channel expression by intrathecal delivery of an antisense oligonucleotide on pain behaviors and the covariance of Scn9a knock-down on NaV 1.7 message expression and channel binding. MethodsMale Sprague-Dawley rats were implanted with lumbar intrathecal catheters and dosed with different NaV 1.7 ASO concentrations (100 to 3000 g;10 L). Pain behavior assays were conducted 0-28 days after ASO injections. Brain, spinal cords (SC) and dorsal root ganglia (DRGs) were collected. Quantification of ASO knock-down was assessed through RT-qPCR. NaV 1.7 expression was assessed by binding of NaV 1.7 fluorescent labeled antagonist (ATTO488PTx-II). Distribution studies were performed using anti-ASO antibody staining in brain, SCs and DRGs. ResultsNaV 1.7 message was detected in nerve, DRG and SC. Intrathecal ASO induced a concentration dependent gradient of knock down in DRGs (lumbar to cervical) of Scn9a mRNA and ATTO488PTx-II binding in small DRG neurons, and in spinal parenchyma, and a suppression of pain behaviors initiated by mechanical compression, inflammation and following intraplantar NaV1.7 agonist (OD1) or formalin. At 1000 {micro}g, there was a 47% reduction in phase 2 flinching, a 60% reduction in DRG mRNA and a 36% reduction in ATTO488PTx-II DRG binding in comparison with mismatch controls. Although marked changes were seen at the sensory ganglia level and spinal dorsal horn, no changes in NaV 1.7 binding or mRNA were detected in sciatic nerves. Reduction in DRG message displayed a rostrocaudal gradient that corresponded with ASO distribution. ConclusionsThe study presents how NaV 1.7 ASOs reduce primary afferent channel binding through an effective knock-down on Scn9a mRNA, and channel binding leading to a covariate reduction in pain behavior.

neuroscience↗

bioRxiv2025

Combining machine learning and publicly available aerial data (NAIP and NEON) to achieve high-resolution remote sensing of grass-shrub-tree mosaics in the Central Great Plains (U.S.A.)

Woody plant encroachment (WPE)--a phenomenon similar to species invasion--is shifting many grasslands and savannas into shrub and evergreen-dominated ecosystems. Tracking WPE is difficult because shrubs and small trees are much smaller than the coarse resolution of common remote sensing platforms (> 10 m2) and the impassibility of encroaching woody thickets slows ground-based approaches. Many agencies have been investing in fine resolution (< 2 m2) remote sensing through programs such as the United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) and the National Ecological Observatory Network (NEON). Both use low-flying planes and provide data to end users in an easy-to-use format at large spatial extents. By removing entry barriers, these publicly available open-source programs could increase the accessibility and extent of remote sensing. We compared two common methods of machine learning classification of land cover (random forests and support vector machines) factorially crossed with these two freely available remote sensing platforms to determine if we could quickly and accurately develop remote sensing of major vegetation types in a tallgrass prairie landscape undergoing encroachment by shrubs and trees. Our work took place at Konza Prairie Biological Station--a landscape scale experiment that results in a wide range of land cover types. All models had very high overall classification accuracy (>90%), with the NEON-based models a few percent more accurate than NAIP. A model using both inputs had the highest accuracy. However, the accuracies of NAIP and NEON models differed for woody vegetation: compared to NEON, NAIP accuracy was, 82-93% compared to 94-98% for shrubs, 72-92% compared to 93-98% for deciduous trees, and 52-78% compared to 83-86% for evergreen trees (specifically Juniperus virginiana). NEON-based models relied on canopy height (LiDAR) to make classifications, whereas the several bands of light make similar contributions to accuracy in the NAIP models. Finally, we found that both machine learning approaches had similar accuracy, but random forests ran substantially faster. We conclude that with large training datasets, publicly available aerial imagery and similar products (e.g., UAVs, micro-satellites) can produce fine-scale, high-accuracy remote sensing of WPE in this region with low up-front costs.

ecology↗

bioRxiv2024

PrP turnover in vivo and the time to effect of prion disease therapeutics

PrP lowering is effective against prion disease in animal models and is being tested clinically. Therapies in the current pipeline lower PrP production, leaving pre-existing PrP to be cleared according to its own half-life. We hypothesized that PrPs half-life may be a rate-limiting factor for the time to effect of PrP-lowering drugs, and one reason why late treatment of prion-infected mice is not as effective as early treatment. Using isotopically labeled diet with targeted mass spectrometry, as well as antisense oligonucleotide treatment followed by timed PrP measurement, we estimate a half-life of 5-6 days for PrP in the brain. PrP turnover is not affected by over-or under-expression. Mouse PrP and human PrP have similar turnover rates measured in wild-type or humanized knock-in mice. CSF PrP appears to mirror brain PrP in real time in rats. PrP in the colon is readily quantifiable and has a half-life just slightly shorter than in brain. An under-expressed pathogenic mutant PrP, corresponding to D178N in humans, exhibits an accelerated turnover rate. Our data may inform the design of both preclinical and clinical studies of PrP-lowering drugs. Author SummaryPrion disease is a fatal brain disease caused by misfolding of the prion protein (PrP). Emerging therapies for prion disease seek to reduce the amount of PrP produced in the brain in order to delay onset of disease or slow progression. Mouse studies have shown that if these therapies are initiated too late, their benefit is limited or they may not help at all. Here we measure the half-life of PrP in the mouse brain, and find that it is about 5 days. When drugs are used to lower PrP by cutting up the RNA that encodes PrP, the RNA drops rapidly while the protein lags behind, and does not reach its minimum level until 4 weeks after the drug is dosed. This half-life is about the same regardless of the species of PrP (mouse or human) and whether or not the brain is infected with prions. Cerebrospinal fluid appears to reflect the real-time levels of brain PrP with no appreciable lag. PrP can be measured in colon, which may be useful in animal studies of systemic drugs to lower PrP. PrP turns over more quickly in the presence of a pathogenic genetic variant, the equivalent of the human D178N variant. These findings suggest that clinical trials can monitor PrP in cerebrospinal fluid to look at drug activity, but should plan timepoints far enough post-dose to account for PrPs rate of turnover, and should focus on patients who will survive long enough to benefit from the drug.

neuroscience↗

bioRxiv2023

Low-threshold, high-resolution, chronically stable intracortical microstimulation by ultraflexible electrodes

Intracortical microstimulation (ICMS) enables applications ranging from neuroprosthetics to causal circuit manipulations. However, the resolution, efficacy, and chronic stability of neuromodulation is often compromised by the adverse tissue responses to the indwelling electrodes. Here we engineer ultraflexible stim-Nanoelectronic Threads (StimNETs) and demonstrate low activation threshold, high resolution, and chronically stable ICMS in awake, behaving mouse models. In vivo two-photon imaging reveals that StimNETs remain seamlessly integrated with the nervous tissue throughout chronic stimulation periods and elicit stable, focal neuronal activation at low currents of 2 A. Importantly, StimNETs evoke longitudinally stable behavioral responses for over eight months at markedly low charge injection of 0.25 nC/phase. Quantified histological analysis show that chronic ICMS by StimNETs induce no neuronal degeneration or glial scarring. These results suggest that tissue-integrated electrodes provide a path for robust, long-lasting, spatially-selective neuromodulation at low currents which lessen risks of tissue damage or exacerbation of off-target side-effects.

neuroscience↗