Biology subjects

Lamb, D.

Publications and source records attributed to Lamb, D..

6 recordsLinked to original sources

bioRxiv2026

Leveraging cis- and trans-variants to improve protein expression level prediction for proteome-wide association studies

Since genetic effects are often mediated through proteins, the analysis of proteomic data can provide insights into disease etiology. However, most studies lack proteomic data. To address this problem, we developed TransCisPredict to perform proteome-wide association studies (PWAS) at a biobank scale. TransCisPredict reduces computational burden through linkage-disequilibrium block selection which facilitates incorporating cis- and trans-variants to predict protein expression and performs protein-phenotype association analyses. To account for differences in protein regulatory architecture, four prediction methods are used for weight estimation, i.e., BayesR, Elastic Net, LASSO, and SuSiE. Five-fold cross-validation (CV) is used to select the optimal method for each protein. Weight estimation was performed using White British UK Biobank study subjects (N=42,644) with proteomic and genotype array data. Of the 2,920 available protein expression levels, 2,339 could be predicted with a CV-R2>0.05 when cis- and trans-variants were used. Since most methods are limited to cis-variation, for comparison only cis-variants were used for prediction yielding 466 proteins with a CV-R2>0.05. A PWAS was performed for 2,339 predicted protein expression levels and type 2 diabetes (T2D) using White British UK Biobank study subjects without proteomic data (N=364,132) followed by two-sample Mendelian randomization using a method that controls for horizontal pleiotropy for validation. Forty proteins were associated with T2D and validated. For the 466 cis-only predicted protein expression levels, three proteins were associated with T2D and validated. Incorporating both cis- and trans-variation using TransCisPredict facilitates the prediction of many more proteins compared to using cis-only variants thereby increasing the power of PWAS.

genetics↗

bioRxiv2024

Structural basis for CCR6 modulation by allosteric antagonists

The CC chemokine receptor 6 (CCR6) is a potential target for chronic inflammatory diseases such as psoriasis and inflammatory bowel disease. Previously, we reported an active CCR6 structure in complex with its cognate chemokine CCL20, revealing the molecular basis of CCR6 activation mediated by CCL20. Here, we present two inactive CCR6 structures determined by cryo-EM in ternary complexes with different allosteric antagonists, CCR6/SQA1/OXM1 and CCR6/SQA1/OXM2. OXM1 and OXM2 are oxomorpholine (OXM) analogues which are highly selective for CCR6 and disrupt the molecular network critical for receptor activation by binding to an extracellular allosteric pocket within the transmembrane domain. A U-shaped conformation stabilized by intramolecular interactions was revealed by structural and NMR studies of active OXM analogues. SQA1 is a squaramide (SQA) derivative with close-in analogues that were previously reported to be antagonists of CCR6 and other chemokine receptors. Our structures reveal an intracellular pocket occupied by SQA1 that overlaps with the G protein binding site. In addition, SQA1 stabilizes a closed conformation of the intracellular pocket, a hallmark of the inactive state of GPCRs. Minimal communication was found between the two allosteric pockets. Overall, our work provides new evidence of the versatility of GPCR antagonism by small molecules, complementing previous knowledge on CCR6 activation, and sheds light on drug discovery approaches to target CCR6 for autoimmune disorders.

biochemistry↗

bioRxiv2021

Characterization of a flexible AAV-DTR/DT mouse model of acute epithelial lung injury

Background & aimRecurring epithelial injury and aberrant repair are considered as a major driver of idiopathic pulmonary fibrosis (IPF) leading to chronic inflammation, fibroblast activation and ultimately to scarring and stiffening of the lung. As decline of lung function is the first reported symptom by IPF patients and occurs once fibrosis is firmly established, animal models are required to study early disease-driving mechanisms. MethodsWe developed a novel and flexible mouse model of acute epithelial injury based on adeno-associated virus (AAV) variant 6.2 mediated expression of the human diphtheria toxin receptor (DTR). Following intratracheal administration of diphtheria toxin (DT), a cell-specific death of bronchial epithelial and alveolar epithelial type II cells can be observed. ResultsDetailed characterization of the AAV-DTR/DT mouse model revealed increasing cell numbers in bronchoalveolar lavage (BAL; macrophages, neutrophils, and atypical cells) and elevation of apoptotic cells and infiltrated leukocytes in lung tissue, which were dependent of viral genome load and DT dose. Cytokine levels in BAL fluid showed different patterns dependent of viral genome load with IFN{gamma}, TNF, and IP-10 increasing and IL-5 and IL-6 decreasing, while lung function was not affected. Additionally, laser-capture microdissection-based proteomics of bronchial and alveolar epithelium showed upregulated immune and inflammatory response in all epithelial cell regions and extracellular matrix deposition in infiltrated alveoli, while proteins involved in pulmonary surfactant synthesis, alveolar fluid clearance and alveolar-capillary barrier were downregulated in the parenchyma. ConclusionOur novel AAV-DTR/DT model resembles specific aspects of pulmonary diseases like IPF and acute respiratory distress syndrome. Short summary for social mediaA novel and flexible mouse model of acute epithelial lung injury based on AAV-mediated expression of the human diphtheria toxin receptor followed by intratracheal instillation of diphtheria toxin resembles specific aspects of pulmonary diseases like IPF.

cell biology↗

bioRxiv2021

Molecular dissection of pro-fibrotic signaling identifies the mechanism underlying IL11-driven fibrosis gene translation, reveals non-specific effects of STAT3 and suggests a new mechanism of action for nintedanib

In fibroblasts, TGF{beta}1 stimulates IL11 upregulation that leads to an autocrine loop of IL11-dependent pro-fibrotic protein translation. The signalling pathways downstream of IL11 are contentious and both STAT3 and ERK have been implicated. Here we show that TGF{beta}1- or IL11-induced ERK activation is consistently associated with fibrogenesis whereas STAT3 phosphorylation (pSTAT3) is unrelated to fibroblast activation. Surprisingly, recombinant human IL11, which has been used extensively in mouse experiments to infer STAT3 activity downstream of IL11, non-specifically increases pSTAT3 in Il11ra1 null mouse fibroblasts. Pharmacologic inhibition of STAT3 prevents TGF{beta}1-induced fibrogenesis but this effect was found to reflect fibroblast dysfunction due to severe proteotoxic ER stress. In contrast, inhibition of MEK/ERK prevented fibrosis in the absence of ER stress. TGF{beta}1-stimulated ERK/mTOR/P70RSK-driven protein translation was IL11-dependent and selectivity for pro-fibrotic protein synthesis was ascribed to an EPRS-related mechanism. In TGF{beta}1-stimulated fibroblasts, the anti-fibrotic drug nintedanib caused dose-dependent ER stress, reduced pSTAT/pERK and inhibited pro-fibrotic protein translation, similarly to generic STAT3 inhibitors or ER stressors. Pirfenidone, while anti-fibrotic, had no effect on ER stress whereas anti-IL11 inhibited the ERK/mTOR axis while reducing ER stress. These studies discount a specific role for STAT3 in pro-fibrotic signaling, suggest a novel mechanism of action for nintedanib and prioritise further the IL11 pathway as a therapeutic target for fibrosis.

molecular biology↗

bioRxiv2019

Loss of cell cycle control renders cells nonresponsive to local extrinsic differentiation cues

Objective and approachesAberrantly proliferating cells are linked to a number of diseases including cancers and developmental defects.To determine the extent to which local extrinsic signals contribute to or ameliorate mutant cell behaviors, we examined survival and differentiation of mutant cells in wild-type retinal environments by generating chimeric zebrafish embryos comprised of unlabeled host cells and GFP-labeled neural progenitor donor cells. In addition, we examined the fate of retinal progenitor cells when cdkn1c, a cyclin dependent kinase inhibitor, was induced in clones within wild-type and hdac1 mutant retinae.\n\nResultsWe found that seven of the ten mutants examined exhibited apoptosis when grafted into wild-type tissue, with cells from two slowly cycling mutants, elys and emi1, noticeably differentiating in a wild-type environment. Observations of the one hyperproliferative mutant, hdac1, revealed that these mutant cells did not appear to die or differentiate but instead survived and formed tumor-like rosettes in a wild-type environment. Ectopic expression of cdkn1c was unable to force cell cycle exit and differentiation of the majority of hdac1 mutant cells.\n\nConclusionsTogether, these results suggest that although a wild-type environment rarely encourages cell cycle exit and differentiation of neural progenitors with cell cycle defects, wild-type survival signals may enable hyperproliferative progenitor cells to persist instead of die.

developmental biology↗

bioRxiv2018

Quantitative single-molecule three-color Förster resonance energy transfer by photon distribution analysis

Single-molecule Forster resonance energy transfer (FRET) is a powerful tool to study conformational dynamics of biomolecules. Using solution-based single-pair FRET by burst analysis, conformational heterogeneities and fluctuations of fluorescently labeled proteins or nucleic acids can be studied by monitoring a single distance at a time. Three-color FRET is sensitive to three distances simultaneously and can thus elucidate complex coordinated motions within single molecules. While three-color FRET has been applied on the single-molecule level before, a detailed quantitative description of the obtained FRET efficiency distributions is still missing. Direct interpretation of three-color FRET data is additionally complicated by an increased shot noise contribution when converting photon counts to FRET efficiencies. However, to address the question of coordinated motion, it is of special interest to extract information about the underlying distance heterogeneity, which is not easily extracted from the FRET efficiency histograms directly. Here, we present three-color photon distribution analysis (3C-PDA), a method to extract distributions of inter-dye distances from three-color FRET measurements. We present a model for diffusion-based three-color FRET experiments and apply Bayesian inference to extract information about the physically relevant distance heterogeneity in the sample. The approach is verified using simulated data sets and experimentally applied to triple-labeled DNA duplexes. Finally, 3C-FRET experiments on the Hsp70 chaperone BiP reveal conformational coordinated changes between individual domains. The possibility to address the co-occurrence of intramolecular distances makes 3C-PDA a powerful method to study the coordination of domain motions within biomolecules during conformational changes.\n\nSignificanceIn solution-based single-molecule Forster resonance energy transfer (FRET) experiments, biomolecules are studied as they freely diffuse through the observation volume of a confocal microscope, resulting in bursts of fluorescence from single molecules. Using three fluorescent labels, one can concurrently measure three distances in a single molecule but the experimentally limited number of photons is not sufficient for a straight-forward analysis. Here, we present a probabilistic framework, called three-color photon distribution analysis (3C-PDA), to extract quantitative information from single-molecule three-color FRET experiments. By extracting distributions of interdye distances from the data, the method provides a three-dimensional description of the conformational space of biomolecules, enabling the detection of coordinated movements during conformational changes.

biophysics↗