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Smith, J.

Publications and source records attributed to Smith, J..

At least 109 records · Page 6Linked to original sources

Location bias contributes to functionally selective responses of biased CXCR3 agonists

Some G protein-coupled receptor (GPCR) ligands act as "biased agonists" which preferentially activate specific signaling transducers over others. Although GPCRs are primarily found at the plasma membrane, GPCRs can traffic to and signal from many subcellular compartments. Here, we determine that differential subcellular signaling contributes to the biased signaling generated by three endogenous ligands of the chemokine GPCR CXCR3. The signaling profile of CXCR3 changed as it trafficked from the plasma membrane to endosomes in a ligand-specific manner. Endosomal signaling was critical for biased activation of G proteins, {beta}-arrestins, and ERK1/2. In CD8+ T cells, the chemokines promoted unique transcriptional responses predicted to regulate inflammatory pathways. In a mouse model of contact hypersensitivity, {beta}-arrestin-biased CXCR3-mediated inflammation was dependent on receptor internalization. Our work demonstrates that differential subcellular signaling is critical to the overall biased response observed at CXCR3, which has important implications for drugs targeting chemokine receptors and other GPCRs.

biochemistry↗

Effect sizes of causal variants for gene expression and complex traits differ between populations

Despite the growing number of genome-wide association studies (GWAS), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWAS are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate although this is not significant, likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.

genetics↗

A framework for defining livestock ecotypes based on ecological modelling and exploring genomic environmental adaptation: the example of Ethiopian village chicken

In evolutionary ecology, an ecotype is a population that is genetically adapted to specific environmental conditions. Environmental and genetic characterisation of livestock ecotypes can play a crucial role in conservation and breeding improvement, particularly to achieve climate resilience. However, livestock ecotypes are often arbitrarily defined without a detailed characterisation of their agro-ecologies. In this study, we employ a novel integrated approach, combining Ecological Niche Modelling (ENM) with genomics, to delineate ecotypes based on environmental characterisation of population habitats and unravel the signatures of adaptive selection in the ecotype genomes. The method was applied on 25 Ethiopian village chicken populations representing diverse agro-climatic conditions. ENM identified six key environmental drivers of adaptation and delineated 12 ecotypes. Within- ecotype selection signature analyses (using Hp and iHS methods) identified 1,056 candidate sweep regions (SRs) associated with diverse biological processes. A few biological pathways were shared amongst most ecotypes and the involved genes showed functions important for scavenging chickens, e.g. neuronal development/processes, immune response, vision development, and learning. Genotype-environment association using Redundancy Analysis (RDA) allowed for correlating [~]33% of the SRs with major environmental drivers. Inspection of some strong candidate genes from selection signature analysis and RDA showed highly relevant functions in relation to the major environmental drivers of corresponding ecotypes. This integrated approach offers a powerful tool to gain insight into the complex processes of adaptive evolution including the genotype x environment (GxE) interactions.

genetics↗

Paracrine role for endothelial IGF-1 receptor in white adipocyte beiging

There are at least two distinct types of thermogenic adipocyte in mammals: a pre-existing form established during development, termed classical brown adipocytes and an inducible form, beige adipocytes1-3. Various environmental cues can stimulate a process frequently referred to as beiging of white adipose tissue (WAT), leading to enhanced thermogenesis and obesity resistance 4, 5. Whilst beiging of WAT as a therapeutic goal for obesity and obesity-related complications has attracted much attention6-9; therapeutics stimulating beiging without deleterious side-effects remain elusive10. The endothelium lines all blood vessels and is therefore in close proximity to all cells. Many studies support the possibility that the endothelium acts as a paracrine organ11-14. We explored the potential role of endothelial insulin-like growth factor-1 receptor (IGF-1R) as a paracrine modulator of WAT phenotype. Here we show that a reduction in endothelial IGF-1R expression in the presence of nutrient excess leads to white adipocyte beiging, increases whole-body energy expenditure and enhances insulin sensitivity via a non-cell autonomous paracrine mechanism. We demonstrate that this is mediated by endothelial release of malonic acid, which we show, using prodrug analogues, has potentially therapeutically-relevant properties in the treatment of metabolic disease.

cell biology↗

Locus-Specific DNA Methylation Editing in Mammalian Cells using a CRISPR-Based System

DNA methylation is a key epigenetic modification implicated in the pathogenesis of numerous human diseases, including cancer development and metastasis. Gene promoter methylation changes are widely associated with transcriptional deregulation and disease progression. The advent of CRISPR-based technologies has provided a powerful toolkit for locus-specific manipulation of the epigenome. Here, we describe a comprehensive global workflow for the design and application of a dCas9-SunTag-based tool for editing a DNA methylation locus in human melanoma cells, alongside protocols for downstream techniques used to evaluate subsequent methylation and gene expression changes in methylation-edited cells. Using transient system delivery, we demonstrate both highly efficacious methylation and demethylation of the EBF3 promoter, a putative epigenetic driver of melanoma metastasis, achieving up to 304.00% gain of methylation and 99.99% relative demethylation, respectively. Further, we employ a novel, targeted screening approach to confirm minimal off-target activity and high on-target specificity of our editing sys-tem within our target locus.

molecular biology↗

Compound Screening with Deep Learning for Neglected Diseases: Leishmaniasis

AO_SCPLOWBSTRACTC_SCPLOWDeep learning provides a tool for improving screening of candidates for drug re-purposing to treat neglected diseases. We show how a new pipeline can be developed to address the needs of repurposing for Leishmaniasis. In combination with traditional molecular docking techniques, this allows top candidates to be selected and analyzed, including for molecular descriptor similarity.

molecular biology↗

Evaluating the utility of identity-by-descent segment numbers for relatedness inference via information theory and classification

Despite decades of methods development for classifying relatives in genetic studies, pairwise relatedness methods recalls are above 90% only for first through third degree relatives. The top-performing approaches, which leverage identity-by-descent (IBD) segments, often use only kinship coefficients, while others, including ERSA, use the number of segments relatives share. To quantify the potential for using segment numbers in relatedness inference, we leveraged information theory measures to analyze exact (i.e., produced by a simulator) IBD segments from simulated relatives. Over a range of settings, we found that the mutual information between the relatives degree of relatedness and a tuple of their kinship coefficient and segment number is on average 4.6% larger than between the degree and the kinship coefficient alone. We further evaluated IBD segment number utility by building a Bayes classifier to predict first through sixth degree relationships using different feature sets. When trained and tested with exact segments, the inclusion of segment numbers improves the recall by between 0.0028 and 0.030 for second through sixth degree relatives. However, the recalls improve by less than 0.018 per degree when using inferred segments, suggesting limitations due to IBD detection accuracy. Lastly, we compared our Bayes classifier that includes segment numbers with ERSA and IBIS and found comparable results, with the Bayes classifier and ERSA slightly outperforming each other across different degrees. Overall, this study shows that IBD segment numbers can improve relatedness inference but that errors from current SNP array-based detection methods yield dampened signals in practice.

genetics↗

Simultaneous in vivo Pharmacokinetics and Pharmacodynamics of TDF Intravaginal Ring during High-dose Vaginal SHIV Challenge in Pigtail Macaques

The demonstration of complete protection of macaques in a repeated low dose virus challenge by a tenofovir disoproxil fumarate (TDF) intravaginal ring (IVR) and the success of the dapivirine IVR in clinical trials highlighted the potential of IVRs as pre- exposure prophylaxis against HIV. Efficacy of TDF ring was not investigated in sexually active women. Our understanding of the mechanisms of protection is limited. To address this knowledge gap, we performed simultaneous pharmacokinetic and pharmacodynamic analysis of a TDF-IVR at the site of SIV challenge in pigtail macaques at the anatomical and cellular level. Specifically, we challenged TDF-IVR administered pigtail macaques with a single high dose of a non-replicative SIV-based vector containing a dual reporter system that helped us to identify the earliest targets of SIV infection within the mucosa. Two and three days after challenge, the macaques were euthanized and tenofovir (TFV) concentrations were measured in the female reproductive tract (FRT) by HPLC-MS/MS to correlate drug concentrations and SIV-vector transduction efficiency. TFV formed a gradient through the mucosal tissue, with the highest concentrations near the ring, in the upper vagina and endocervix. Despite this, several transduction events were identified with the most common sites being in the ovaries. Moreover, proviral DNA was detected in the cervix and vagina. Thus, our studies demonstrate an uneven distribution of TFV in the FRT of macaques after release from a TDF-IVR that leads to incomplete FRT protection from high viral dose challenge.

pharmacology and toxicology↗

Regulation of auditory fear discrimination by the novel Kv3 voltage-gated potassium channel modulator AUT00206

Psychiatric diseases like anxiety-related disorders and schizophrenia are characterized by impaired cognition and emotional regulation linked to corticolimbic disinhibition. Restoring the balance between excitation and inhibition in corticolimbic circuits may therefore ameliorate certain features of these disorders, such as inappropriately attributing affective salience to innocuous cues. Corticolimbic activity is tightly controlled by parvalbumin-expressing GABAergic interneurons, which also regulate fear discrimination. The voltage-gated potassium channels Kv3.1 and Kv3.2 are highly expressed in these neurons, therefore Kv3.1/3.2 modulation may have potential for treating disorders associated with cognitive and emotional dysregulation. We determined the effects of the novel Kv3.1/3.2 positive modulator AUT00206 on fear discrimination. Female rats underwent limited or extended auditory fear discrimination training that we previously showed leads to discrimination or generalization, respectively, based on passive fear responding (i.e. freezing). We also assessed darting as an active fear response. We found that limited training resulted in discrimination based on freezing, which was unaffected by AUT00206. In contrast, we found that extended training resulted in generalization based on freezing and the emergence of discrimination based on darting. Importantly, AUT00206 had dissociable effects on fear discrimination and expression with extended training. While AUT00206 mitigated generalization without affecting expression based on freezing, it reduced expression without affecting discrimination based on darting. Our results indicate that Kv3.1/3.2 modulation regulates the attribution of affective significance to threat- and safety-related cues in a response-specific manner. This suggests that targeting Kv3.1 and Kv3.2 channels may provide a promising avenue for treating cognitive and emotional dysregulation in psychiatric disease.

neuroscience↗

Broadening a SARS-CoV-1 neutralizing antibody for potent SARS-CoV-2 neutralization through directed evolution

The emergence of SARS-CoV-2 underscores the need for strategies to rapidly develop neutralizing monoclonal antibodies that can function as prophylactic and therapeutic agents and to help guide vaccine design. Here, we demonstrate that engineering approaches can be used to refocus an existing neutralizing antibody to a related but resistant virus. Using a rapid affinity maturation strategy, we engineered CR3022, a SARS-CoV-1 neutralizing antibody, to bind SARS-CoV-2 receptor binding domain with >1000-fold improved affinity. The engineered CR3022 neutralized SARS-CoV-2 and provided prophylactic protection from viral challenge in a small animal model of SARS-CoV-2 infection. Deep sequencing throughout the engineering process paired with crystallographic analysis of an enhanced antibody elucidated the molecular mechanisms by which engineered CR3022 can accommodate sequence differences in the epitope between SARS-CoV-1 and SARS-CoV-2. The workflow described provides a blueprint for rapid broadening of neutralization of an antibody from one virus to closely related but resistant viruses.

bioengineering↗

Online Closed-Loop Real-Time tES-fMRI for Brain Modulation: Feasibility, Noise/Safety and Pilot Study

Recent studies suggest that transcranial electrical stimulation (tES) can be performed during functional magnetic resonance imaging (fMRI). The novel approach of using concurrent tES-fMRI to modulate and measure targeted brain activity/connectivity may provide unique insights into the causal interactions between the brain neural responses and psychiatric/neurologic signs and symptoms, and importantly, guide the development of new treatments. However, tES stimulation parameters to optimally influence the underlying brain activity in health and disorder may vary with respect to phase, frequency, intensity and electrodes montage. Here, we delineate how a closed-loop tES-fMRI study of frontoparietal network modulation can be designed and performed. We also discuss the challenges of running a concurrent tES-fMRI, describing how we can distinguish clinically meaningful physiological changes caused by tES from tES-related artifacts. There is a large methodological parameter space including electrode types, electrolytes, electrode montages, concurrent tES-fMRI hardware, online fMRI processing pipelines and closed-loop optimization algorithms that should be carefully selected for closed-loop tES-fMRI brain modulation. We also provide technical details on how safety and quality of tES-fMRI settings can be tested, and how these settings can be monitored during the study to ensure they do not exceed safety standards. The initial results of feasibility and applicability of closed-loop tES-fMRI are reported and potential hypotheses for the outcomes are discussed. Highlight pointsO_LIMethodological details of a closed-loop tES-fMRI study protocol are provided. C_LIO_LIThe protocol is performed successfully on a frontoparietal network without side-effects. C_LIO_LIThe temperature of electrodes in concurrent tES-fMRI remains in the safe range. C_LIO_LIProperly setup concurrent tES does not introduce MRI artifacts and noise. C_LIO_LISimplex optimizer could be used to find an optimal tES stimulation parameter. C_LI

neuroscience↗

ChromWave: Deciphering the DNA-encoded competition between transcription factors and nucleosomes with deep neural networks

Transcription factors (TFs) regulate gene expression by recognising and binding specific DNA sequences. At times, these regulatory elements may be occluded by nucleosomes, making them inaccessible for TF-binding. The competition for DNA occupancy between TFs and nucleosomes, and associated gene regulatory outputs, are important consequences of the cis-regulatory information encoded in the genome. However, these sequence patterns are subtle and remain difficult to interpret. Here, we introduce ChromWave, a deep-learning model that, for the first time, predicts the competing profiles for TF and nucleosomes occupancies with remarkable accuracy. Models trained using short- and long-fragment MNase-Seq data successfully learn the sequence preferences underlying TF and nucleosome occupancies across the entire yeast genome. They recapitulate nucleosome evictions from regions containing "strong" TF binding sites and knock-out simulations show nucleosomes gaining occupancy in the absence of these TFs, accompanied by lateral rearrangement of adjacent nucleosomes. At a local level, models anticipate with high accuracy the outcomes of detailed experimental analysis of partially unwrapped nucleosomes at the GAL4 UAS locus. Finally, we trained a ChromWave model that successfully predicts nucleosome positions at promoters in the human genome. We find that human promoters generally contain few sites at which simple sequence changes can alter nucleosome occupancies and that these positions align well with causal variants linked to DNase hypersensitivity.

genomics↗

Complex population dynamics in a spatial microbial ecosystem with Physarum polycephalum

This research addresses the interactions between the unicellular slime mold Physarum polycephalum and a red yeast in a spatial ecosystem over week-long imaging experiments. An inverse relationship between the growth rates of both species is shown, where P. polycephalum has positive growth when the red yeast has a negative growth rate and vice versa. The data also captures successional/oscillatory dynamics between both species. An advanced image analysis methodology for semantic segmentation is used to quantify population density over time, for all components of the ecosystem. We suggest that P. polycephalum is capable of exhibiting a sustainable feeding strategy by depositing a nutritive slime trail, allowing yeast to serve as a periodic food source. This opens a new direction of P. polycephalum research, where the population dynamics of spatial ecosystems can be readily quantified and complex ecological dynamics can be studied.

ecology↗

Synthetic algal-bacteria consortia for space-efficient microalgal growth in a simple hydrogel system

Photosynthetic microalgae are an attractive source of food, fuel or nutraceuticals, but commercial production of microalgae is limited by low spatial efficiency. In the present study, we developed a simple photosynthetic hydrogel system that cultivates the green microalga, Marinichlorella kaistiae KAS603, together with a novel strain of the bacteria Erythrobacter sp.. We tested the performance of the co-culture in the hydrogel using a combination of chlorophyll-a fluorimetry, microsensing and bio-optical measurements. Our results showed that growth rates in algal-bacterial hydrogels were about 3-fold enhanced compared to hydrogels with algae alone. Chlorophyll-a fluorimetry based light curves found that electron transport rates were enhanced about 20% for algal-bacterial hydrogels compared to algal hydrogels for intermediate irradiance levels. We also show that the living hydrogel is stable under different environmental conditions and when exposed to natural seawater. Our study provides a potential bio-inspired solution for problems that limit the space-efficient cultivation of microalgae for biotechnological applications.

microbiology↗

A high-quality Genome and Comparison of Short versus Long Read Transcriptome of the Palaearctic duck Aythya fuligula (Tufted Duck)

BackgroundThe tufted duck is a non-model organism that suffers high mortality in highly pathogenic avian influenza out-breaks. It belongs to the same bird family (Anatidae) as the mallard, one of the best-studied natural hosts of low-pathogenic avian influenza viruses. Studies in non-model bird species are crucial to disentangle the role of the host response in avian influenza virus infection in the natural reservoir. Such endeavour requires a high-quality genome assembly and transcriptome. ResultsThis study presents the first high-quality, chromosome-level reference genome assembly of the tufted duck using the Vertebrate Genomes Project pipeline. We sequenced RNA (cDNA) from brain, ileum, lung, ovary, spleen and testis using Illumina short-read and PacBio long-read sequencing platforms, which was used for annotation. We found 34 autosomes plus Z and W sex chromosomes in the curated genome assembly, with 99.6% of the sequence assigned to chromosomes. Functional annotation revealed 14,099 protein-coding genes that generate 111,934 transcripts, which implies an average of 7.9 isoforms per gene. We also identified 246 small RNA families. ConclusionsThis annotated genome contributes to continuing research into the host response in avian influenza virus infections in a natural reservoir. Our findings from a comparison between short-read and long-read reference transcriptomics contribute to a deeper understanding of these competing options. In this study, both technologies complemented each other. We expect this annotation to be a foundation for further comparative and evolutionary genomic studies, including many waterfowl relatives with differing susceptibilities to the avian influenza virus.

genomics↗

Relating simulation studies by provenance--Developing a family of Wnt signaling models

For many biological systems, a variety of simulation models exist. A new simulation model is rarely developed from scratch, but rather revises and extends an existing one. A key challenge, however, is to decide which model might be an appropriate starting point for a particular problem and why. To answer this question, we need to identify entities and activities that contributed to the development of a simulation model. Therefore, we exploit the provenance data model, PROV-DM, of the World Wide Web Consortium and, building on previous work, continue developing a PROV ontology for simulation studies. Based on a case study of 19 Wnt/{beta}-catenin signaling models, we identify crucial entities and activities as well as useful metadata to both capture the provenance information from individual simulation studies and relate these forming a family of models. The approach is implemented in WebProv, a web application for inserting and querying provenance information. Our specialization of PROV-DM contains the entities Research Question, Assumption, Requirement, Qualitative Model, Simulation Model, Simulation Experiment, Simulation Data, and Wet-lab Data as well as activities referring to building, calibrating, validating, and analyzing a simulation model. We show that most Wnt simulation models are connected to other Wnt models by using (parts of) these models. However, the overlap, especially regarding the Wet-lab Data used for calibration or validation of the models is small. Making these aspects of developing a model explicit and queryable is an important step for assessing and reusing simulation models more effectively. Exposing this information helps to integrate a new simulation model within a family of existing ones and may lead to the development of more robust and valid simulation models. We hope that our approach becomes part of a standardization effort and that modelers adopt the benefits of provenance when considering or creating simulation models. Author summaryWe revise a provenance ontology for simulation studies of cellular biochemical models. Provenance information is useful for understanding the creation of a simulation model because it not only contains information about the entities and activities that have led to a simulation model but also their relations, all of which can be visualized. It provides additional structure by explicitly recording research questions, assumptions, and requirements and relating them along with data, qualitative models, simulation models, and simulation experiments through a small set of predefined but extensible activities. We have applied our concept to a family of 19 Wnt signaling models and implemented a web-based tool (WebProv) to store the provenance information from these studies. The resulting provenance graph visualizes the story line of simulation studies and demonstrates the creation and calibration of simulation models, the successive attempts of validation and extension, and shows, beyond an individual simulation study, how the Wnt models are related. Thereby, the steps and sources that contributed to a simulation model are made explicit. Our approach complements other approaches aimed at facilitating the reuse and assessment of simulation products in systems biology such as model repositories as well as annotation and documentation guidelines.

bioinformatics↗

Defining the Yeast Resistome through in vitro Evolution and Whole Genome Sequencing

In vitro evolution and whole genome analysis were used to comprehensively identify the genetic determinants of chemical resistance in the model microbe, Saccharomyces cerevisiae. Analysis of 355 curated, laboratory-evolved clones, resistant to 80 different compounds, demonstrates differences in the types of mutations that are identified in selected versus neutral evolution and reveals numerous new, compound-target interactions. Through enrichment analysis we further identify a set of 137 genes strongly associated with or conferring drug resistance as indicated by CRISPR-Cas9 engineering. The set of 25 most frequently mutated genes was enriched for transcription factors and for almost 25 percent of the compounds, resistance was mediated by one of 100 independently derived, gain-of-function, single nucleotide variants found in 170-amino-acid domains in two Zn2C6 transcription factors, YRR1 and YRM1 (p < 1x 10 -100). This remarkable enrichment for transcription factors as drug resistance genes may explain why it is challenging to develop effective antifungal killing agents and highlights their important role in evolution.

genetics↗

Targeting of TP53-independent cell cycle checkpoints overcomes FOLFOX resistance in Metastatic Colorectal Cancer

Patients with colorectal cancer (CRC) frequently develop liver metastases during the course of their disease. A substantial proportion of them receive neoadjuvant FOLFOX (5-Fluorouracil, Oxaliplatin, Leucovorin) prior to surgery in an attempt to enable successful surgical removal of their metastases and to reduce the risk of recurrence. Yet, the majority of patients progress during treatment or recur following surgery, and molecular mechanisms that contribute to FOLFOX resistance remain poorly understood. Here, using a combination of phenotypic, transcriptomic and genomic analyses of both tumor samples derived from patients with metastatic CRC and matching patient-derived tumor organoids (PDTOs), we characterize a novel FOLFOX resistance mechanism and identify inhibitors that target this mechanism to resensitize metastatic organoids to FOLFOX. Resistant PDTOs, identified after in vitro exposure to FOLFOX, exhibited elevated expression of E2F pathway, S phase, G2/M and spindle assembly checkpoints (SAC) genes. Similar molecular features were detected in CRLM from patients with progressive disease while under neoadjuvant FOLFOX treatment, highlighting the relevance of this finding. FOLFOX resistant PDTOs displayed inactivating mutations of TP53 and exhibited transcriptional features of P53 pathway downregulation. We found that they accumulated in early S-phase and underwent significant DNA damage during FOLFOX exposure, thereafter arresting in G2/M while they repaired their DNA after FOLFOX withdrawal. In parallel, results of a large kinase inhibitor screen indicated that drugs targeting regulators of the DNA damage response, G2M checkpoint and SAC had cytotoxic effects on PDTOs generated from patients whose disease progressed during treatment with FOLFOX. Corroborating this finding, CHK1 and WEE1 inhibitors were found to synergize with FOLFOX and sensitize previously resistant PDTOs. Additionally, targeting the SAC master regulator MPS1 using empesertib after exposure to FOLFOX, when cells accumulate in G2M, was also very effective to kill FOLFOX-resistant PDTOs. Our results indicate that targeted and timely inhibition of specific cell cycle checkpoints shows great potential to improve response rates to FOLFOX in patients with metastatic CRC, for whom therapeutic alternatives remain extremely limited.

cancer biology↗