Biology subjects

Barrett, L.

Publications and source records attributed to Barrett, L..

16 recordsLinked to original sources

bioRxiv2026

Aberrant chromatin remodeling influences human neural cell fate change in Trisomy 21

Correct neural progenitor cell (NPC) fate specification is essential to produce the full complement of neurons and glia needed for proper brain structure and function. Neurodevelopmental disorders, including the autosomal aneuploidy Down syndrome (DS), or Trisomy 21 (T21), are frequently associated with impaired cell fate decisions which ultimately drive differences in overall brain size and cell type composition through unknown mechanisms. To uncover mechanisms driving altered NPC fate in T21, we leverage paired single-nuclei transcriptomic and epigenomic analyses of human induced pluripotent stem cell (iPSC)-derived NPCs and their differentiated progeny coupled with in depth clonal cell fate, cell cycle, and proteomic analyses. Here we show that T21 NPCs fail to activate an orchestrated neurogenic program during the earliest stages of fate specification, instead maintaining a repressive chromatin structure over neurogenic loci, leading to reduced neurogenesis and continued NPC proliferation. We identify novel enrichment of the repressive histone mark H3K27me3 at fate instructive genes dysregulated across diverse cell and tissue types in T21, with corresponding genome-wide changes in H3K27me3 binding in T21 NPCs. Moreover, pharmacological treatment with an inhibitor of the Polycomb repressive complex 2 (PRC2) which catalyzes H3K27 methylation, is sufficient to partially restore neurogenesis in T21 cells. Collectively, our analyses reveal a chromatin mechanism influencing neurogenic defects in T21.

neuroscience↗

bioRxiv2025

Single Cell Analysis of pBMCs of Psoriasis patients reveals distinct CD4+ T cell phenotypes associated with response to IL-23 blockade.

The use of IL-23 inhibitors (IL-23i) for psoriatic diseases has resulted in significant improvement in disease symptoms for many patients. The extent of disease improvement following IL-23 blockade varies across patients with psoriasis; however, the immunologic factors associated with a good or poor response to IL-23 blockade remain unclear. Here, we utilized peripheral blood mononuclear cells (pBMCs) collected through the MINIMA clinical trial (NCT04271540) and applied single-cell RNA sequencing to profile circulating immune populations from 27 patients with psoriasis or psoriatic arthritis, aiming to identify cellular features associated with a response to IL-23 blockade. We identified populations of CD4+ T cells whose abundance in circulation before treatment was associated with improved skin disease following IL-23i treatment. Circulating CD4+ T cells that demonstrate transcriptomic features of Th1-like cells were associated with better psoriasis skin improvement and had transcriptomic signatures resembling T cells identified in psoriasis lesional skin. Further, decrease in levels of IL-17A and IFN{gamma} in serum each correlated with improvement in PASI levels. These results suggest that immune cell features detectable in blood may be informative in identifying patients with psoriasis who are likely to have a robust clinical response to IL-23 blockade.

immunology↗

bioRxiv2024

The problem of unmeasured variables in animal social network analysis: can edge-based multilevel models provide a reliable solution?

Recent approaches to analysing social networks suggest that modeling the edges of the network and using multilevel models will produce more informative estimates. These recent methods have been proposed as a way to better handle the dependency structures of social networks, account for biases in data collection, and retain uncertainty when making inferences about social network structures. We find that they have the potential to also effectively handle unmeasured variables that act as statistical confounds in social network analysis. Using simulated data, we highlight that static social network analyses can be used to identify patterns in social networks, but generally cannot be used to identify the underlying mechanisms behind the patterns. To identify mechanisms, we show that taking a dynamic approach and using edge-based models with additive and multiplicative random effects provides a means to identify mechanisms even when statistical confounds are present. Additive and multiplicative random effects also provide information about social structures not captured by the predictors, facilitating exploratory analysis. We suggest that a keep-it-maximal approach for random effects structures is beneficial for edge-based multilevel models of social networks, and that such approaches can be particularly effective when there are unmeasured variables that are not captured by model predictors.

animal behavior and cognition↗

bioRxiv2024

E. coli phylogeny drives co-amoxiclav resistance through variable expression of blaTEM-1

Co-amoxiclav resistance in E. coli is a clinically important phenotype associated with increased mortality. The class A beta-lactamase blaTEM-1 is often carried by co- amoxiclav-resistant pathogens, but exhibits high phenotypic heterogeneity, making genotype-phenotype predictions challenging. We present a curated dataset of n=377 E. coli isolates representing all 8 known phylogroups, where the only acquired beta- lactamase is blaTEM-1. For all isolates, we generate hybrid assemblies and co-amoxiclav MICs, and for a subset (n=67/377), blaTEM-1 qPCR expression data. First, we test whether certain E. coli lineages are intrinsically better or worse at expressing blaTEM-1, for example, due to lineage differences in regulatory systems, which are challenging to directly quantify. Using genotypic features of the isolates (blaTEM-1 promoter variants and copy number), we develop a hierarchical Bayesian model for blaTEM-1 expression that controls for phylogeny. We establish that blaTEM-1 expression intrinsically varies across the phylogeny, with some lineages (e.g. phylogroups B1 and C, ST12) better at expression than others (e.g. phylogroups E and F, ST372). Next, we test whether phylogenetic variation in expression influences the resistance of the isolates. With a second model, we use genotypic features (blaTEM-1 promoter variants, copy number, duplications; ampC promoter variants; efflux pump AcrF presence) to predict isolate MIC, again controlling for phylogeny. Lastly, we use a third model to demonstrate that the phylogenetic influence on blaTEM-1 expression causally drives the variation in co- amoxiclav MIC. This underscores the importance of incorporating phylogeny into genotype-phenotype predictions, and the study of resistance more generally.

microbiology↗

bioRxiv2024

Comparison of direct cDNA and PCR-cDNA Nanopore sequencing of Escherichia coli isolates

2.Whole-transcriptome (long-read) RNA sequencing (Oxford Nanopore Technologies, ONT) holds promise for agnostic analysis of differential gene expression (DGE) in pathogenic bacteria, including for antimicrobial resistance genes (ARGs). However, direct cDNA ONT sequencing requires large concentrations of polyadenylated mRNA, and amplification protocols may introduce technical bias. Here we evaluated the impact of direct cDNA and cDNA PCR-based ONT sequencing on transcriptomic analysis of clinical Escherichia coli. Four E. coli bloodstream infection-associated isolates (n=2 biological replicates/isolate) were sequenced using the ONT Direct cDNA Sequencing SQK-DCS109 and PCR-cDNA Barcoding SQK-PCB111.24 kits. Biological and technical replicates were distributed over 8 flow cells using 16 barcodes to minimise batch/barcoding bias. Reads were mapped to a transcript reference and transcript abundance quantified after in silico depletion of low abundance and rRNA genes. We found there were strong correlations between read counts using both kits and when restricting the analysis to include only ARGs. We highlighted correlations were weaker for genes with a higher GC content. Read lengths were longer for the direct cDNA kit compared to the PCR-cDNA kit whereas total yield was higher for the PCR-cDNA kit. In this small but methodologically rigorous evaluation of biological and technical replicates of isolates sequenced with the direct cDNA and PCR-cDNA ONT sequencing kits, we demonstrated that PCR-based amplification substantially improves yield with largely unbiased assessment of core gene and ARG expression. However, users of PCR-based kits should be aware of a small risk of technical bias which appears greater for genes with an unusually high (>52%)/low (<44%) GC-content. 3. Impact statementRNA sequencing allows quantification of RNA within a biological sample providing information on the expression of genes at a particular time. This helps understand the expression of antimicrobial resistance genes (ARGs). In RNA-Seq experimental workflows extra steps of reverse transcription may be needed to generate more stable cDNA to allow for amplification by PCR if starting RNA input was low. Two current methods of long-read RNA sequencing include direct cDNA and PCR-cDNA based sequencing (Oxford Nanopore Technologies, ONT). However, few studies have compared these two methods of RNA-sequencing using clinical bacterial isolates. We therefore undertook a study to compare both kits using a methodological balanced design of biological and technical replicates of E. coli. Our study showed that direct cDNA and PCR-cDNA sequencing is highly reproducible between biological and technical E. coli replicates with very small differences in gene expression signatures generated between kits. The PCR-cDNA kit generates increased sequencing yield but a smaller proportion of mappable reads, the generation of shorter reads of lower quality and some PCR-associated bias. PCR-based amplification greatly increased sequencing yield of core genes and ARGs, however there may be a small risk of PCR-bias in genes that have a higher GC content. 4. Data summaryThe transcript reads of the four sequenced Escherichia coli strains have been deposited in the Figshare, DOI: 10.6084/m9.figshare.25044051. The authors confirm all supporting data (available in Figshare), code (available at: https://github.com/samlipworth/rna_methods) and protocols have been provided within the article or through supplementary data files.

molecular biology↗

bioRxiv2023

Regulation of coronavirus nsp15 cleavage specificity by RNA structure

SARS-CoV-2, the etiologic agent of the COVID-19 pandemic, has had an enduring impact on global public health. However, SARS-CoV-2 is only one of multiple pathogenic human coronaviruses (CoVs) to have emerged since the turn of the century. CoVs encode for several nonstructural proteins (NSPS) that are essential for viral replication and pathogenesis. Among them is nsp15, a uridine-specific viral endonuclease that is important in evading the host immune response and promoting viral replication. Despite the established function of nsp15 as a uridine-specific endonuclease, little is known about other determinants of its cleavage specificity. In this study we investigate the role of RNA secondary structure in SARS-CoV-2 nsp15 endonuclease activity. Using a series of in vitro endonuclease assays, we observed that thermodynamically stable RNA structures were protected from nsp15 cleavage relative to RNAs lacking stable structure. We leveraged the s2m RNA from the SARS 3UTR as a model for our structural studies as it adopts a well-defined structure with several uridines, two of which are unpaired and thus high probably targets for nsp15 cleavage. We found that SARS-CoV-2 nsp15 specifically cleaves s2m at the unpaired uridine within the GNRNA pentaloop of the RNA. Further investigation revealed that the position of uridine within the pentaloop also impacted nsp15 cleavage efficiency, suggesting that positioning within the pentaloop is necessary for optimal presentation of the scissile uridine and alignment within the nsp15 catalytic pocket. Our findings indicate that RNA secondary structure is an important determinant of nsp15 cleavage and provides insight into the molecular mechanisms of recognition of RNA by nsp15.

microbiology↗

bioRxiv2022

Cell-type specific developmental defects in PTEN-mutant cortical organoids converge on abnormal circuit activity

De novo heterozygous loss-of-function mutations in PTEN are strongly associated with Autism spectrum disorders (ASD); however, it is unclear how heterozygous mutations in this gene affects different cell types during human brain development, and how these effects vary across individuals. Here, we used human cortical organoids from different donors to identify cell-type-specific developmental events that are affected by heterozygous mutations in PTEN. We profiled individual organoids by single-cell RNA-seq, proteomics and spatial transcriptomics, and revealed abnormalities in developmental timing in human outer radial glia progenitors and deep layer cortical projection neurons, which varied with the donor genetic background. Calcium imaging in intact organoids showed that both accelerated and delayed neuronal development phenotypes resulted in similar abnormal activity of local circuits, irrespective of genetic background. The work reveals donor-dependent, cell-type specific developmental phenotypes of PTEN heterozygosity that later converge on disrupted neuronal activity.

neuroscience↗

bioRxiv2021

Sick and Tired: Polyparasitism, Food Stress and Sickness Behaviour in a Gregarious Mammal

Although sickness behaviour in response to non-lethal parasites has been documented in wild animals, it remains unclear how social and environmental stress might also shape an animals behavioural response to parasitism, nor do we know whether simultaneous infection with more than one parasite changes the way animals respond. Here, we combine physiological, environmental, behavioural and parasite measures to investigate behavioural responses to infection in wild vervet monkeys (Chlorocebus pygerythrus) living in a semi-arid region of South Africa. We quantified both activity budget and behavioural predictability to investigate the occurrence of sickness behaviour and infection with two non-lethal gastrointestinal parasite genera. Higher parasite load was linked to an increase in the time spent resting. However, the nature of the relationship with other behaviours was contingent on both the parasite genus in question, and how parasite species interacted, highlighting the importance of considering co-infection. Overall, food availability was the dominant predictor of behavioural change suggesting that, for monkeys living in a more extreme environment, coping with ecological stress may override the ability to modulate behaviour in response to other physiological stressors. Our findings provide insight into how animals living in harsh environments find ways to cope with parasite infection, avoidance, and transmission.

animal behavior and cognition↗

bioRxiv2020

SARS-CoV-2 proteins and anti-COVID-19 drugs induce lytic reactivation of an oncogenic virus

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of Coronavirus Disease-2019 (COVID-19), a respiratory disease, has infected over 34,000,000 people since the end of 2019, killed over 1,000,000, and caused worldwide social and economic disruption. Due to the mechanisms of SARS-CoV-2 infection to host cells and its pathogenesis remain largely unclear, there are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Besides severe respiratory and systematic symptoms, several comorbidities may also increase risk of fatal disease outcome. Therefore, it is required to investigate the impacts of COVID-19 on pre-existing diseases of patients, such as cancer and other infectious diseases. In the current study, we have reported that SARS-CoV-2 encoded proteins and some anti-COVID-19 drugs currently used are able to induce lytic reactivation of Kaposis sarcoma-associated herpesvirus (KSHV), one of major human oncogenic viruses through manipulation of intracellular signaling pathways. Our data indicate that those KSHV+ patients especially in endemic areas exposure to COVID-19 or undergoing the treatment may have increased risks to develop virus-associated cancers, even after they have fully recovered from COVID-19.

microbiology↗

bioRxiv2020

Infrared thermography cannot be used to approximate core body temperature in wild primates

Understanding the physiological processes that underpin primate performance is key if we are to assess how a primate might respond when navigating new and changing environments. Given the connection between an animals ability to thermoregulate and the changing demands of its thermal environment, increasing attention is being devoted to the study of thermoregulatory processes as a means to assess primate performance. Infrared thermography can be used to record the body surface temperatures of free-ranging animals. However, some uncertainty remains as to how these measurements can be used to approximate core body temperature. Here, we use data collected from wild vervet monkeys (Chlorocebus pygerythrus) to examine the relationship between infrared body surface, core body, and local climate, to determine to what extent surface temperatures reflect core body temperature. While we report a positive association between surface and core body temperature - a finding that has previously been used to justify the use of surface temperature measurements as a proxy for core temperature regulation - when we controlled for the effect of the local climate in our analyses, this relationship was no longer observed. That is, body surface temperatures were solely predicted by local climate, and not core body temperatures, suggesting that surface temperatures tell us more about the environment a primate is in, and less about the thermal status of its body core in that environment. Despite the advantages of a non-invasive means to detect and record animal temperatures, infrared thermography alone cannot be used to approximate core body temperature in wild primates.

physiology↗

bioRxiv2020

Natural gene drives offer potential pathogen control strategies in plants

O_LIGlobally, fungal pathogens cause enormous crop losses and current control practices are not always effective, economical or environmentally sustainable. Tools enabling genetic management of wild pathogen populations could potentially solve many problems associated with plant diseases. C_LIO_LIA natural gene drive from a heterologous species can be used in the globally important cereal pathogen, Fusarium graminearum, to remove pathogenic traits from contained populations of the fungus. The gene drive element became fixed in a freely crossing populations in only three generations. C_LIO_LIRepeat induce point mutation, a natural genome defence mechanism in fungi, may be useful to recall the gene drive following release, should a failsafe mechanism be required. C_LIO_LIWe propose that gene drive technology is a potential tool to control plant pathogens. C_LI

genetics↗

bioRxiv2019

Increasing motor skill acquisition by driving theta-gamma coupling

Skill learning is a fundamental adaptive process, but the mechanisms remain poorly understood. Hippocampal learning is closely associated with gamma activity, which is amplitude-modulated by the phase of underlying theta activity. Whether such nested activity patterns also underpin skill acquisition in non-hippocampal tasks is unknown. Here we addressed this question by using transcranial alternating current stimulation (tACS) over sensorimotor cortex to modulate theta-gamma activity during motor skill acquisition, as an exemplar of a non-hippocampal-dependent task. We demonstrated, and then replicated, a significant improvement in skill acquisition with theta-gamma tACS, which outlasted the stimulation by an hour. Our results suggest that theta-gamma activity may be a common mechanism for learning across the brain and provides a putative novel intervention for optimising functional improvements in response to training or therapy.

neuroscience↗

bioRxiv2019

Network reaction norms: taking into account network position and network plasticity in response to environmental change.

Recent studies have highlighted the link between consistent inter-individual differences in behaviour and consistency in social network position. There is also evidence that network structures can show temporal dynamics, suggesting that consistency in social network position across time does not preclude some form of plasticity in response to environmental variation. To better consider variation in network position and plasticity simultaneously we introduce the network reaction norm (NRN) approach. As an illustrative example, we used behavioural data on chacma baboons, collected over a period of seven years, to construct a time series of networks, using a moving window. Applying an NRN approach with these data, we found that most of the variation in network centrality could be explained by inter-individual differences in mean centrality. There was also evidence, however, for individual differences in network plasticity. These differences suggest that environmental conditions may influence which individuals are most central, i.e., they lead to an individual x environment interaction. We suggest that expanding from measures of repeatability in social networks to network reaction norms can provide a more temporally nuanced way to investigate social phenotypes within groups, and lead to a better understanding of the development and maintenance of individual variation in social behaviour.

animal behavior and cognition↗

bioRxiv2019

Ranking the Ranking Methodologies: Determining Temporal Stability in Dominance Hierarchies

The importance of social hierarchies has led to the development of many techniques for inferring social ranks, leaving researchers with an overwhelming array of options to choose from. Many of our research questions involve longitudinal analyses, so we were interested in a method that would provide reliable ranks across time. But how does one determine which method performs best?\n\nWe attempt to answer this question by using a training-testing procedure to compare 13 different approaches for calculating dominance hierarchies (seven methods, plus 6 analytical variants of these). We assess each methods performance, its efficiency, and the extent to which the calculated ranks obtained from the training dataset accurately predict the outcome of observed aggression in the testing dataset.\n\nWe found that all methods tested performed well, despite some differences in inferred rank order. With respect to the need for a \"burn-in\" period to enable reliable ranks to be calculated, again, all methods were efficient and able to infer reliable ranks from the very start of the study period (i.e., with little to no burn-in period). Using a common 6-month burn-in period to aid comparison, we found that all methods could predict aggressive outcomes accurately for the subsequent 10 months. Beyond this 10-month threshold, accuracy in prediction decreased as the testing dataset increased in length. The decay was rather shallow, however, indicating overall rank stability during this period.\n\nIn general, a training-testing approach allows researchers to determine the most appropriate method for their dataset, given sampling effort, the frequency of agonistic interactions, the steepness of the hierarchy, and the nature of the research question being asked. Put simply, we did not find a single best method, but our approach offers researchers a valuable tool for identifying the method that will work best for them.\n\nHighlightsO_LIAll ranking methods tested performed well at predicting future aggressive outcomes, despite some differences in inferred rank order.\nC_LIO_LIAll ranking methods appear to be efficient in inferring reliable ranks from the very start (i.e., with little to no burn-in period), but all showed improvement as the burn-in period increased.\nC_LIO_LIUsing a common 6-month burn-in period, we found that all methods could predict aggressive outcomes accurately for the subsequent 10 months. Beyond this threshold, accuracy in prediction decreased as the testing dataset increased in length.\nC_LIO_LISwitching to a data-driven approach to assign k-values, via the training/validation/testing procedure, resulted in a marked improvement in performance in the modified Elo-rating method.\nC_LI

animal behavior and cognition↗

bioRxiv2018

Functional Social Structure in Baboons: Modelling Interactions Between Social and Environmental Structure in Group-Level Foraging

In mobile social groups, cohesion is thought to be driven by patterns of attraction at both the individual and group level. In long-lived species with high group stability and repeated interactions, such as baboons, individual-to-individual attractions have the potential to play a large role in group cohesion and overall movement patterns. In previous work, we used GPS mapping of a group of baboons in De Hoop, Western Cape, South Africa, to demonstrate the influence of such attractions on movement patterns. We also demonstrated the existence of emergent group-level structures, which arose as a consequence of individual social influence. Specifically, we found a core-periphery structure, in which a subset of influential animals exerted an influence on each other and those animals in the periphery, while those in the periphery were influenced by the core but did not exert any influence over others. Here, we use agent-based modelling of baboon groups to investigate whether this group-level structure has any functional consequences for foraging behaviour. By varying individual level attractions, we produced baboon groups that contained influence structures that varied from more to less centralized. Our results suggest that varying centrality affects both the ability of the group to detect resource structure in the environment, as well as the ability of the group to exploit these resources. Our models predict that foraging groups with more centralized social structures will show a reduction in detection and an increase in exploitation of resources in their environment, and will produce more extreme foraging outcomes. More generally, our results highlight the link between social and environmental structure on functional outcomes for mobile social groups of animals.

animal behavior and cognition↗

bioRxiv2017

Evidence for a Large-Scale Brain System Supporting Allostasis and Interoception in Humans

AbstractLarge-scale intrinsic brain systems have been identified for exteroceptive senses (e.g., sight, hearing, touch). We introduce an analogous system for representing sensations from within the body, called interoception, and demonstrate its relation to regulating peripheral systems in the body, called allostasis. Employing the recently introduced Embodied Predictive Interoception Coding (EPIC) model, we used tract-tracing studies of macaque monkeys, followed by two intrinsic functional magnetic resonance imaging samples (N = 280 and N = 270) to evaluate the existence of an intrinsic allostatic/interoceptive system in the human brain. Another sample (N = 41) allowed us to evaluate the convergent validity of the hypothesized allostatic/interoceptive system by showing that individuals with stronger connectivity between system hubs performed better on an implicit index of interoceptive ability related to autonomic fluctuations. Implications include novel insights for the brains functional architecture, dissolving the artificial boundary between mind and body, and unifying mental and physical illness.

neuroscience↗