Biology subjects

Gilbert, M.

Publications and source records attributed to Gilbert, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Vaccination targeting the novel endogenous tumor-associated antigen Gpr149 induces protective immunity against checkpoint inhibitor-refractory SB28 glioblastoma

Background: Glioblastoma is a lethal brain tumor notable for its limited spontaneous induction of CD8+ T cell responses. Vaccination may overcome this limitation by generating tumor-specific CD8+ T cells capable of mediating anti-tumor immunity in the brain. However, preclinical vaccine development is constrained by a lack of immunologically stringent glioblastoma models with defined endogenous antigens. We therefore sought to identify endogenous, vaccine-targetable antigens expressed by the immune checkpoint-refractory SB28 syngeneic mouse glioblastoma model and to evaluate their targetability using a heterologous prime-boost regimen with the chimpanzee adenovirus ChAdOx1 and the modified vaccinia Ankara (MVA) viral vector-based vaccines. Methods: RNA sequencing and whole-exome sequencing were used to identify candidate tumor-associated antigens (TAAs) and neoantigens, and tumor-specific expression was validated by RT-qPCR. ChAdOx1 and MVA vectors encoding candidate antigens were generated and evaluated for immunogenicity and anti-tumor efficacy. Antigen-specific CD8+ T cell responses and minimal epitopes were characterized by ex vivo restimulation, MHC-I binding assays, tetramer staining, and tumor cytotoxicity assays. Results: We identified five candidate TAAs (Gpr149, Cdh6, Fbn2, Igf2bp1, and Shox2) but no suitable neoantigen targets in SB28. Vaccination induced CD8+ T cell responses against the candidate TAAs, and immunogenic minimal epitopes were identified for each. Among the candidates, Gpr149 elicited the strongest vaccine-induced CD8+ T cell responses. In mice challenged intracranially with SB28, Gpr149-targeted ChAdOx1/MVA vaccination combined with immune checkpoint blockade significantly prolonged median survival and resulted in long-term survival in 50% of mice, whereas vaccination targeting the other TAAs did not improve survival. CD8+ T cells recognizing the immunodominant Gpr149128-135 epitope (VCYNFYTM) specifically recognized and lysed wild-type SB28 cells, but not Gpr149-knockout SB28 cells, confirming endogenous processing and presentation of the targeted epitope. Conclusions: Gpr149 is an endogenous SB28 tumor antigen that can be effectively targeted by ChAdOx1/MVA vaccination to generate protective anti-tumor immunity against intracranial glioblastoma. Protection was associated with a dominant CD8+ T cell response to the Gpr149128-135 epitope VCYNFYTM. These findings establish endogenously expressed Gpr149 in SB28 as a physiologically relevant model for evaluating antigen-targeted immunotherapies and provide a systematic approach for identifying endogenous vaccine targets in other preclinical models.

immunology↗

bioRxiv2026

Persistent, Multi-Species Outbreaks and Long-Range Transmissions of a Measles-Like Virus

Canine distemper--a measles-like disease with high mortality and presently without a cure--poses a major threat to wild and domestic carnivores globally. Domestic dogs are generally considered to be the main reservoir and long-range transmitter of the disease, but the role of wildlife is likely underestimated and the long-term persistence of CDV in wildlife has never been assessed. We sequenced canine distemper virus (CDV) full and partial genomes that were sampled over a decade (2012-2021) from Arctic foxes and other canids in Alaska and Yellowstone, and compiled a dataset of all published CDV genomes sampled across 32 species globally. We show the first ever evidence of persistence of CDV in wildlife (for almost a decade) with explosive transmission dynamics crossing host species barriers. Strains sampled from the Arctic for the first time connect North America to Eurasia, and are distinct from the Yellowstone strain and other known North American lineages. This suggests that separate wildlife outbreaks occur concurrently in North America, with possible introductions from Eurasia. The long-term persistence, long-range movement and explosive spread of this devastating panzootic virus that we document within wildlife is alarming and highlights the need for increased monitoring efforts to better protect wildlife populations globally.

genomics↗

bioRxiv2026

Systemic viral vector vaccination induces brain resident memory T cells to drive anti-glioblastoma immunity

Glioblastoma is a lethal brain tumor that is unresponsive to current cancer immunotherapeutic approaches, including immune checkpoint blockade (ICB). This suggests that initial priming of T cells, rather than their expansion and licensing as effectors, is a restricting feature in this tumor setting. To overcome the limited initiation of CD8+ T cell responses, we employed a strong heterologous prime-boost vaccination with the simian adenovirus ChAdOx1 and poxvirus modified vaccinia Ankara (MVA). Vaccination conferred therapeutic efficacy against orthotopic, immune checkpoint-blockade (ICB)-refractory SB28 murine glioblastoma. Vaccination was effective against both the murine tumor antigen, P1A, and a newly identified glioblastoma-associated antigen, Gpr149. Additional treatment with ICB provided no additional benefit. Systemic ChAdOx1/MVA vaccination induced robust infiltration of antigen-specific T cells in tumor-challenged brains, the majority of which exhibited a CD103+CD69+CD8+ tissue-resident memory (TRM)-like phenotype. These cells were polyfunctional, durable in brains with sustained tumor control, and mediated tissue-specific immunological memory. Moreover, intracranial adoptive transfer of glioblastoma-derived antigen-specific TRM-like cells was sufficient to protect naive recipients from subsequent orthotopic tumor challenge. Together, these findings establish that viral vector vaccination can generate tumor-specific TRM-like cells that mediate effective anti-glioblastoma immunity, providing a rationale for clinical evaluation of ChAdOx1/MVA-based strategies in glioblastoma.

immunology↗

bioRxiv2026

Ovothiol A mediates singlet oxygen resistance and acclimation in Chlamydomonas

Light is essential for photosynthetic organisms, but excess light can generate toxic levels of reactive oxygen species (ROS). To neutralize these ROS, plants and algae produce a variety of antioxidants like carotenoids, tocopherols, and glutathione. However, the role of alternative ROS scavengers, such as ovothiols, has not been studied in the context of oxidative stress in photosynthetic organisms. Here, we report that many algal groups have the potential for the biosynthesis of ovothiols, a group of thiohistidines. We discovered that the model green microalga Chlamydomonas reinhardtii produces millimolar concentrations of ovothiol A, whose biosynthesis is mediated by the ovothiol synthase OVOA1. Using CRISPR-generated ovoa1 knockout mutants, we found that ovothiol production is essential for resistance and acclimation to singlet oxygen, a prominent ROS in photosynthetic organisms. Finally, we demonstrated that OVOA1 expression is activated by singlet oxygen and light signaling pathways in which we identified the major regulatory factors. Overall, our results show that ovothiol A is a major, previously overlooked antioxidant in Chlamydomonas. This work broadens our understanding of cellular mechanisms that combat the damaging effects of oxidative stress. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/702910v2_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@cddb9corg.highwire.dtl.DTLVardef@10d0a43org.highwire.dtl.DTLVardef@11cc087org.highwire.dtl.DTLVardef@a40cc5_HPS_FORMAT_FIGEXP M_FIG C_FIG

plant biology↗

bioRxiv2025

Development of a metabolic signature of post-weaning diarrhoea in pigs

In the agricultural sector, antibiotics have been used to improve swine growth performance. This application is banned nowadays, due to increased risk of antibiotic resistance. In piglets this results in a higher prevalence of post-weaning diarrhoea, deteriorating both animal health and performance. Our goal was to find a metabolite signature separating piglets with low faecal consistency score (FCS) from piglets with normal faecal consistency and determine which pathways were enriched in this signature. By using direct infusion mass spectrometry on blood spots, we built machine learning (ML) models that aimed to differentiate between low and normal FCS. To test the general predictive capability of these models, we applied a Leave-One-Country-Out (LOCO) strategy for cross validation. Our second approach after LOCO was finding the optimal number of features to include in a feature-reduced model. To determine the order in which features were to be eliminated, we ranked them based on a combination of t-test and fold-change significance scores. Enrichment analysis using mummichog was used to gain insights into the final signature set of m/z values found using this ranking and ML models. Models trained both using all countries and leaving out specific countries from training showed a limited ability to predict FCS category. Furthermore, the LOCO results were mixed, with some countries showing a predictive signal present in the data, but others with predictive capability that was no better than random. Signature analysis using t-test and fold-change results did not result in any KEGG pathways that were enriched in this signature as compared to random. Using these methods, we could predict the FCS category to a limited degree. Although no common signature for low faecal consistency could be determined using this method, given that some countries showed more reliable LOCO results, further analysis into specifically the samples from those countries could be a valuable next step. No metabolite signature enriched in changes to KEGG pathways was found in the data using the combined t-test and fold-change analysis ranking method. We have shared the data with the community through the MetaboLights repository.

bioinformatics↗

bioRxiv2025

TBCK Deficiency Alters Ribosomal Function, RNA Splicing, and miRNA Networks: Insights from Multi-Omics Analyses

TBC1 domain-containing kinase (TBCK) is an important protein with implications in brain development. Biallelic variants in the TBCK gene are known to cause TBCK-related neurodevelopmental disorder (OMIM #616900) [1], a rare genetic multisystemic disease characterized by developmental delay, variable developmental regression, seizures, and premature death in late childhood for which no cure is currently available. Though previous work has provided a better understanding of the proteins role, the mechanism for how TBCK variants affect gene expression and protein regulation has remained understudied. To better understand the impact of these alterations, and using an unbiased approach, we employed the power of multi-omics to define the cellular consequences at the transcript and protein level. Our comprehensive analysis uncovered significant disruptions in ribosomal and translation-related pathways with widespread alternative splicing defects, and key miRNA changes that validate previously reported molecular findings. This work provides a clearer molecular framework for TBCK dysfunction in TBCK-/- cells and offers a valuable foundation to identify potential therapeutic targets.

genetics↗

bioRxiv2025

Downscaling local distribution of cattle over Guadeloupe archipelago: an adapted method for disaggregating census data

Gridded livestock distribution datasets have been produced for several years and are used in various fields, including epidemiology, livestock impact assessment, and territory management. Those datasets are based on census conducted at national/sub-national scale which are then downscaled using machine learning algorithm and relevant spatial-explicit environmental predictors. The most known dataset of livestock disaggregated observations is the Gridded Livestock of the World (GLW), which produces global maps of livestock density at 10 km spatial resolution for several livestock species. Though this spatial resolution can be appropriate to describe livestock distribution at the global scale, it inherently leads to a coarse representation of breeding species density for smaller territories such as the Caribbean Islands. In this study, we propose an adaptation of the GLW methodology that accounts for the spatial autocorrelation in observed cattle distribution, thereby better capturing the specific characteristics of geographically limited areas such as the Guadeloupean archipelago. Cattle census data were collected for the 32 municipalities of the archipelago and associated to environmental predictors derived from remote sensing and land cover datasets. Together with the Random Forest (RF) algorithm used in the standard GLW methodology, we tested the performance of a Geographical Random Forest (GRF), a novel methodology allowing for taking into account the spatial autocorrelation of the response variable. The GRF algorithm demonstrated significantly better performance compared to the RF algorithm, albeit with longer processing times, and allowed us producing cattle distribution maps for the entire Guadeloupe archipelago at a spatial resolution of 225 m using both algorithms. The approach developed holds potential for application to other small territories, including other islands in the Caribbean.

bioinformatics↗

bioRxiv2025

Comparative performance of novel viral landscape phylogeography approaches

The fast rate of evolution in RNA viruses implies that their evolutionary and ecological processes occur on the same time scale. Genome sequences of these pathogens can therefore contain information about the processes that govern their transmission and dispersal. In particular, landscape phylogeographic approaches use phylogeographic reconstructions to investigate the impact of environmental factors and variables on the spatial spread of viruses. Here, we extend and improve existing approaches and develop three novel landscape phylogeographic methods that can test the impact of continuous environmental factors on the diffusion velocity of viral lineages. In order to evaluate the different methods, we also implemented two simulation frameworks to test and compare their statistical performance. The results enable us to formulate clear guidelines for the use of three complementary landscape phylogeographic approaches that have sufficient statistical power and low rates of false positives. Our open-source methods are available to the scientific community and can be used to investigate the drivers of viral spread, with potential benefits for understanding virus epidemiology and designing tailored intervention strategies.

evolutionary biology↗

bioRxiv2024

Estimating survival of an anadromous salmonid using Bayesian hierarchical models applied to acoustic telemetry, biological, and environmental data

Hierarchical modelling is frequently used to model ecological processes because of its ability to handle complex ecological phenomena by decomposing them into naturally explainable sub-models. Hierarchical Bayesian approaches have gained widespread use in health, social, and environmental sciences, including in the estimation of demo-graphic parameters such as survival. In this study, we combine Bayesian hierarchical models with acoustic telemetry data to estimate survival probabilities for high-latitude populations of an anadromous salmonid, the Arctic char (Salvelinus alpinus), while in-corporating environmental and biological covariates to assess their impact on survival. The model we present here can also account for temporally varying detection probabilities due to changes to the acoustic receiver array design and seasonal variation in the detection probabilities related to environmental conditions (e.g., ice vs. no ice). As previously documented in this species, survival was high (> 0.87) and we found that the covariates pertaining to sea ice coverage and Fultons condition factor impacted the survival probabilities. Contrary to our expectations, high-condition fish had lower survival rates. Survival was also considerably lower during the summer (open-water) compared to winter (ice-covered) seasons. While the biological explanations and implications of these findings require further exploration, they nonetheless demonstrate the utility of this approach. Specifically, we present a hierarchical Bayesian model that can consider environmental and biological covariates while accounting for varying detection probabilities, a major concern of acoustic telemetry studies. The model can be easily adapted for other taxa with similar life histories where mark recapture data are available and can be extended to include additional environmental (e.g., salinity) and biological parameters (e.g., sex).

ecology↗

bioRxiv2024

Global risk mapping of highly pathogenic avian influenza H5N1 and H5Nx in the light of epidemic episodes occurring from 2020 onward

Avian influenza (AI) is a highly contagious viral disease affecting poultry and wild water birds, posing significant global challenges due to its high mortality rates and economic impacts. Highly pathogenic avian influenza (HPAI) outbreaks, particularly those caused by H5N1 and its variants, have surged since their first occurrence in 1959. The HPAI H5N1 clade 2.3.4.4b viruses have notably expanded their geographical reach, affecting numerous countries, diverse avian species, and now wild and domestic mammals. Using an ecological niche modelling approach, this study aims to elucidate the environmental factors associated with the increased HPAI H5 cases since 2020, investigate potential shifts in ecological niches, and predict new areas suitable for local viral circulation. Focusing on H5N1 and H5Nx strains, we have developed ecological niche models for HPAI cases in both wild and domestic birds while considering two distinct periods: 2015-2020 and 2020-2022. Key environmental predictors include chicken and duck population density, human density, distance to water bodies, and several land cover variables. Post-2020, we observe a notable increase in the relative influence of some of these predictors, such as intensive chicken population density and cultivated vegetation. The resulting risk maps reveal notable ecological suitability for local HPAI H5 circulation in Europe, Asia, as well as North and South America, with notable expansions of the areas at risk post-2020. The spatial distribution of HPAI H5 occurrences in wild birds appears to be primarily correlated with urban areas and open water regions. Overall, global risk maps derived from our models identify regions at risk where surveillance and control measures should be prioritised. Finally, our analyses also highlight a potential shift in the diversity of wild bird species affected by HPAI outbreaks, with a higher variety of avian species, particularly sea birds, being impacted post-2020. This increased diversity could suggest that ecological shifts in HPAI H5 circulation may be accompanied by a broader range of susceptible species. Overall, these results further contribute to the understanding of HPAI epidemiology.

ecology↗

bioRxiv2024

Plasticity in the pectoral fin skeleton is induced by altered foraging regime in a South American cichlid

The fins of fishes are remarkably diverse, and this variation is tied to the ecology and locomotor mode of a species. While numerous genetic factors are known to pattern fins in development, it is unclear how developmental plasticity shapes the fin skeleton. Here, we analyze the cichlid Satanoperca daemon, raised under three distinct feeding regimes, and show that plasticity is pervasive across the pectoral fin skeleton with foraging mode impacting patterning of both the endoskeleton and dermal skeleton. Radials and fin rays were {micro}CT scanned and analyzed using a combination of linear measures and geometric morphometrics. Anteroposterior patterning of both radials and fin rays are affected by feeding regime. Notably, S. daemon pectoral fin rays show distinct patterns of fin ray branching between treatments, suggesting altered fin stiffness. We argue that the observed changes in the fin likely reflect developmental plasticity resultant from altered swimming behaviors when fishes are challenged to forage in different ways. These data show how non-genetic mechanisms can shape both the endoskeleton and dermal skeleton of fins, and that foraging mode can induce plastic changes in skeletal elements that do not directly interface with food items.

evolutionary biology↗

bioRxiv2024

What if...? Computational anatomy in the cerebellar microzone, the middle layer of the cerebellar network

The cerebellum is a large brain structure. Most of the mass and volume of the cerebellum is made up by the cerebellar cortex. The outer layer of the cerebellar cortex is divided functionally into long, thin strips called microzones. We argue that the cerebellar microzone computation is the aggregate of simple unit computations and a passive effect of anatomy, unaided and unlearned, which we recreate in silico. This is likely to polarise opinion. In the traditional view, data processing by the cerebellum (stated very briefly) is the effect of learned synaptic changes. However, this has become difficult to reconcile with evidence that rate information is linearly conserved in cerebellar signalling. We present an alternative interpretation of cell morphologies and network architecture in the light of linear communication. Parallel fibre synaptic memory has a supporting role in the network computation. Lay summaryIt is not fully understood how the cerebellum represents information and uses it to generate motor outputs, and how outputs are coordinated to control movement. We model the cerebellar network computation, with a focus on the microzone computation, the middle layer of the network. The main proposal is the contentious idea that the core computation is a passive and unlearned effect of neuroanatomy, unit functions are linear, and the computation is mathematically unsophisticated. To provide functional context, we propose that the topography of input and output of cerebellar motor circuits could be a functional extension of modular cerebellar wiring which automates motor sequences. To illustrate how that could work, we present a simple model of anguilliform (eel-like) swimming.

neuroscience↗

bioRxiv2024

A 20+ Ma old enamel proteome from Canada's High Arctic reveals diversification of Rhinocerotidae in the middle Eocene-Oligocene

In the past decade, ancient protein sequences have emerged as a valuable source of data for deep-time phylogenetic inference. Still, the recovery of protein sequences providing novel phylogenetic insights does not exceed 3.7 Ma (Pliocene). Here, we push this boundary back to 21-24 Ma (early Miocene), by retrieving enamel protein sequences of an early-diverging rhinocerotid (Epiaceratherium sp. - CMNF-59632) from the Canadian High Arctic. We recover partial sequences of seven enamel proteins (AHSG, ALB, AMBN, AMELX, AMTN, ENAM, MMP20) and over 1000 peptide-spectrum matches, spanning over at least 251 amino acids. Authentic endogeneity of these sequences is supported by indicators of protein damage, including several spontaneous and irreversible post-translational modifications accumulated during prolonged diagenesis and reaching near-complete occupancy at many sites. Bayesian tip-dating, across 15 extant and extinct perissodactyl taxa, places the divergence time of CMNF-59632 in the middle Eocene-Oligocene, and identifies a later divergence time for Elasmotheriinae in the Oligocene. The finding weakens alternative models suggesting a deep basal split between Elasmotheriinae and Rhinocerotinae. This divergence time of CMNF-59632 coincides with a phase of high diversification of rhinocerotids, and supports a Eurasian origin of this clade in the late Eocene or Oligocene. The findings are consistent with previous hypotheses on the origin of the enigmatic fauna of the Haughton crater, which, in spite of their considerable degree of endemism, also display similarity to distant Eurasian faunas. Our findings demonstrate the potential of palaeoproteomics in obtaining phylogenetic information from a specimen that is ten times older than any sample from which endogenous DNA has been obtained.

paleontology↗

bioRxiv2024

Post-Eocene Rhinocerotid Dispersal via the North Atlantic

The North Atlantic Land Bridge (NALB), which connected Europe to North America, enabled high latitude dispersal, particularly during globally warm periods such as the Paleocene-Eocene Thermal Maximum, a period of dramatic faunal reorganization. It has been generally accepted by paleontologists, based on faunal comparisons between Europe and North America, that terrestrial vertebrates did not disperse via the NALB more recently than the early Eocene. Herein, we describe a new Early Miocene rhinocerotid species from the Canadian High Arctic with proximity to the NALB and present novel phylogenetic hypotheses for rhinocerotids. The new species, a member of the genus Epiaceratherium, is differentiated from the four other members of the genus by characteristics of the P3, M1-2, mandible, and lower premolars. Global-scale biogeographic analyses reveal a high number of dispersals between Europe and North America, in both directions; cumulatively, they near the number of dispersals within Eurasia. Notably, multiple dispersals occurred in the Oligo-Miocene, suggesting that the NALB may have been crossable for mammals for at least 20 Ma longer than previously considered, consistent with emerging geological and palaeoclimatological models. We thus provide insight into the importance of the NALB as persistent high latitude connector of geographically disparate terrestrial faunas, underscoring the pivotal role of the Arctic in mammalian evolution.

paleontology↗

bioRxiv2024

ACSS2 upregulation enhances neuronal resilience to aging and tau-associated neurodegeneration

Epigenetic mechanisms, including histone acetylation, are pivotal for learning and memory, with a role in neuronal function in Alzheimers disease and Related Dementia (ADRD). Acetyl-CoA synthetase 2 (ACSS2), an enzyme that generates acetyl-CoA, is central to histone acetylation and gene regulation, particularly in neurons, due to their unique metabolic demands and postmitotic state. ACSS2 can be recruited to the nucleus and chromatin, locally supplying acetyl-CoA to directly fuel histone acetyltransferase enzymes and key neuronal gene expression. This regulatory mechanism may be a promising target for therapeutic intervention in neurodegenerative diseases. Previously we showed that systemic ACSS2 deletion in mice, although largely normal in physiology, is greatly impaired in memory. Here we investigated whether increasing ACSS2 levels could protect neurons against disease and age-associated cognitive decline. Given the role of tau in ADRD, we used primary hippocampal neurons that mimic the sporadic development of tau pathology and the P301S transgenic mouse model for tau-induced memory decline. Our results show that ACSS2 upregulation mitigates tau-induced transcriptional alterations, enhances neuronal resilience against tau pathology, improves long-term potentiation, and ameliorates memory deficits. Expanding upon these findings, we reveal that increasing histone acetylation through ACSS2 upregulation improves age-associated memory decline. These findings indicate that increasing ACSS2 is highly effective in countering age- and tau-induced transcriptome changes, preserving elevated levels of synaptic genes, and safeguarding synaptic integrity. We thus highlight ACSS2 as a key player in the epigenetic regulation of cognitive aging and ADRD, providing a foundation for targeted therapeutics to enhance brain resilience and function. SummaryACSS2 upregulation protects neurons from disease and age-related decline by enhancing synaptic and longevity gene expression.

neuroscience↗

bioRxiv2024

Spatial distribution of poultry farms using point pattern modelling: a method to address livestock environmental impacts and disease transmission risks

The distribution of farm locations and sizes is paramount to characterize patterns of disease spread. With some regions undergoing rapid intensification of livestock production, resulting in increased clustering of farms in peri-urban areas, measuring changes in the spatial distribution of farms is crucial to design effective interventions. However, those data are not available in many countries, their generation being resource-intensive. Here, we develop a farm distribution model (FDM), which allows the prediction of locations and sizes of poultry farms in countries with scarce data. The model combines (i) a Log-Gaussian Cox process model to simulate the farm distribution as a spatial Poisson point process, and (ii) a random forest model to simulate farm sizes (i.e. the number of animals per farm). Spatial predictors were used to calibrate the FDM on intensive broiler and layer farm distributions in Bangladesh, Gujarat (Indian state) and Thailand. The FDM yielded realistic farm distributions in terms of spatial clustering, farm locations and sizes, while providing insights on the factors influencing these distributions. Finally, we illustrate the relevance of modelling realistic farm distributions in the context of epidemic spread by simulating pathogen transmission on an array of spatial distributions of farms. We found that farm distributions generated from the FDM yielded spreading patterns consistent with simulations using observed data, while random point patterns underestimated the probability of large outbreaks. Indeed, spatial clustering increases vulnerability to epidemics, highlighting the need to account for it in epidemiological modelling studies. As the FDM maintains a realistic distribution of farm location and sizes, its use to inform mathematical models of disease transmission is particularly relevant for regions where these data are not available.

bioinformatics↗

bioRxiv2024

SIRT7 regulates NUCKS1 chromatin binding to elicit metabolic and inflammatory gene expression in senescence and liver aging

Sirtuins, a class of highly conserved histone/protein deacetylases, are heavily implicated in senescence and aging. The regulation of sirtuin proteins is tightly controlled both transcriptionally and translationally and via localization within the cell. While Sirtiun proteins are implicated with aging, how their levels are regulated during aging across cell types and eliciting tissue specific age-related cellular changes is unclear. Here, we demonstrate that SIRT7 is targeted for degradation during senescence and liver aging. To uncover the significance of SIRT7 loss, we performed proteomics analysis and identified a new SIRT7 interactor, the HMG box protein NUCKS1. We found that the NUCKS1 transcription factor is recruited onto chromatin during senescence and this is mediated by SIRT7 loss. Further, depletion of NUCKS1 delayed senescence upon DNA damage leading to reduction of inflammatory gene expression. Examination of NUCKS1 transcriptional regulation during senescence revealed gene targets of transcription factors NFKB1, RELA, and CEBP{beta}. Consistently, in both Sirt7 KO mouse liver and in naturally aged livers, Nucks1 was recruited to chromatin. Further, Nucks1 was bound at promoters and enhancers of age-related genes, including transcription factor Rela, and, moreover, these bound sites had increased accessibility during aging. Overall, our results uncover NUCKS1 as a novel interactor of SIRT7, and show that loss of SIRT7 during senescence and liver aging promotes NUCKS1 chromatin binding to regulate metabolic and inflammatory genes.

cell biology↗

bioRxiv2023

Low-resolution neuronal code: a theory

We present a theory of the inner layer of the cerebellar cortex, the granular layer, where the main excitatory input to the cerebellum is received. We ask how input signals are converted into an internal code and what form that has. While there is a computational element, and the ideas are quantified with a computer simulation, the approach is primarily evidence-led and aimed at experimenters rather than the computational community. Network models are often simplified to provide a noiseless medium for sophisticated computations. We propose, with evidence, the reverse: physiology is highly adapted to provide a noiseless medium for straightforward computations. We find that input data are converted to a hyper low-resolution internal code. Information is coded in the joint activity of large cell groups and therefore has minimum spatial dimensions - the dimensions of a code group. The conversion exploits statistical effects of random sampling. Code group dimensions are an effect of topography, cell morphologies and granular layer architecture. The activity of a code group is the smallest unit of information but not the smallest unit of code - the same information is coded in any random sample of signals. Code in this form is unexpectedly wasteful - there is a huge sacrifice of resolution - but may be a solution to fundamental problems involved in the biological representation of information.

neuroscience↗