Biology subjects

Gonzalez, J. R.

Publications and source records attributed to Gonzalez, J. R..

15 recordsLinked to original sources

bioRxiv2025

Stationary-Phase Pseudomonas aeruginosa Fluoroquinolone Persisters Mostly Avoid DNA Double-Stranded Breaks

When susceptible bacterial cultures are treated with antibiotics, some cells can survive treatment without heritable resistance, giving rise to susceptible daughter cells in a phenomenon termed antibiotic persistence. Current models of fluoroquinolone (FQ) persistence in stationary-phase cultures posit that post-treatment resuscitation is dependent on double-stranded break (DSB) repair through RecA-mediated homology-directed repair. Previously, we found that stationary-phase P. aeruginosa does not depend on RecA to persist. In this work, we ask whether P. aeruginosa FQ persisters from stationary-phase cultures require DSB repair at all. We measured DSB formation in Levofloxacin (LVX)-treated cells recovering from treatment using strains expressing fluorescently labeled DSB-binding protein, Gam. We find that, surprisingly, the majority of P. aeruginosa LVX persisters survive treatment without apparent DSBs. Persisters that have evidence of DSBs take longer until their first division compared to persisters without DSBs, and the phenotypes of their progeny suggest how persisters cope with DSBs--via repair or by damage sequestration--in order to successfully propagate. These observations pave the way for mechanistic studies into P. aeruginosa FQ persistence and highlight the need for single-cell tools to track FQ-induced damage.

microbiology↗

bioRxiv2024

Differential biological effect of low doses of ionizing radiation depending on the radiosensitivity in a cell line model

PurposeExposure to low doses (LD) of ionizing radiation (IR), such as the ones employed in computed tomography (CT) examination, can be associated with cancer risk. However, not all individuals respond the same to IR, and cancer development could depend on the individual radiosensitivity. Notably, inter-individual differences in the response to IR have been very well studied for high and medium doses, but not for LD. In the present study, we wanted to evaluate the differences in the response to a CT-scan radiation dose of 20 mGy in two lymphoblastoid cell lines with different radiosensitivity. Materials and MethodsSeveral parameters were studied: gene expression, DNA damage, and its repair (by analyzing gamma-H2AX foci, chromosome breaks, and sister chromatid exchange), as well as cell viability, proliferation, and death. ResultsAfter 20 mGy of IR, the radiosensitive (RS) cell line showed an increase in DNA damage, and higher cell proliferation and apoptosis, whereas the radioresistant (RR) cell line was insensitive to this LD. Interestingly, gene expression analysis showed a higher expression of an antioxidant gene in the RR cell line, which could be used by the cells as a protective mechanism. After a dose of 500 mGy, both cell lines were affected by IR but with significant differences. The RS cells presented an increase in DNA damage and apoptosis, but a decrease in cell proliferation and cell viability, as well as less antioxidant response. ConclusionsA differential biological effect was observed between two cell lines with different radiosensitivity, and these differences are especially interesting after a CT scan dose. If this is confirmed by further studies, one could think that individuals with radiosensitivity-related genetic variants may be more vulnerable to long-term effects of IR, potentially increasing cancer risk after LD exposure.

molecular biology↗

bioRxiv2023

The Shape of Cannabis sativa L. Seeds for the Differentiation of Commercial Medicinal Cultivars from Argentina.

The Cannabis sativa L. plant has been used since ancient times as food, a source of fiber, and medicine, resulting in crosses that led to hybridization that currently does not allow for morphological differentiation among the three varieties of the genus (sativa, indica, and ruderalis). Currently, three chemotypes are differentiated based on their cannabinoid content (THC/CBD). Starting in the year 2023, seeds of two contrasting chemotype medicinal cultivars developed by CONICET (National Council for Scientific and Technical Research) and registered with INASE (National Institute of Seeds) can be commercialized in Argentina. In a previous study, we reported a relationship between the shape of Cannabis seeds and the chemical fingerprint associated with the chemotype. The objective of this study is to morphometrically characterize the seeds of two cultivars of Cannabis sativa L. with contrasting chemotypes: type I (high THC) and type III (high CBD). For this purpose, 2D geometric morphometrics based on landmarks and semilandmarks were used, allowing for the independent study of shape and size variation. Seed size between cultivars was compared using univariate statistics of an unbiased size estimator. To understand the magnitude and direction of shape change and determine shape characters that maximize separation between cultivars, a multivariate statistical approach was employed. Seeds belonging to the Malvina cultivar (type I cultivar, THC only) had, on average, smaller size and a rounded shape, whereas seeds from the Pachamama cultivar (type III, high CBD content) had larger size and a tendency towards an elongated oval shape. The use of a discriminant function based on seed shape allowed for over 97% correct assignments between cultivars. Our results could be used for implementing seed shape as a quality and authenticity seal for registered cultivars in the Argentine Cannabis market.

plant biology↗

bioRxiv2022

Early life tolerance depends on a subset of specialized dendritic cells and is reinforced by the skin microbiota

Early life establishment of tolerance to commensal bacteria at barrier surfaces carries enduring implications for immune health but remains poorly understood. Here we show that this process is controlled by microbial interaction with a specialized subset of antigen presenting cells. More particularly, we identify CD301b+ type 2 conventional dendritic cells (DC) as a subset in neonatal skin specifically capable of uptake, presentation and generation of regulatory T cells (Tregs) to commensal antigens. In early life, CD301b+ DC2 are enriched for programs of phagocytosis and maturation, while also expressing tolerogenic markers. In both human and murine skin, these signatures were reinforced by microbial uptake. In contrast to their adult counterparts or other early life DC subsets, neonatal CD301b+ DC2 highly expressed the retinoic acid-producing enzyme, RALDH2, deletion of which limited commensal-specific Tregs. Thus, synergistic interactions between bacteria and a specialized DC subset critically support early life tolerance at the cutaneous interface.

immunology↗

bioRxiv2020

Identification of blood autosomal cis-expression quantitative trait methylation (cis-eQTMs) in children

BackgroundThe identification of expression quantitative trait methylation (eQTMs), defined as associations between DNA methylation levels and gene expression, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis eQTMs in childrens blood, using data from 832 children of the Human Early Life Exposome (HELIX) project. MethodsBlood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (1 Mb window centered at the transcription start site, TSS) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, cohort, and blood cell composition. ResultsWe identified 39,749 blood autosomal cis eQTMs, representing 21,966 unique CpGs (eCpGs, 5.7% of total CpGs) and 8,886 unique transcript clusters (eGenes, 15.3% of total transcript clusters, equivalent to genes). In 87.9% of these cis eQTMs, the eCpG was located at <250 kb from eGenes TSS; and 58.8% of all eQTMs showed an inverse relationship between the methylation and expression levels. Only around half of the autosomal cis-eQTMs eGenes could be captured through annotation of the eCpG to the closest gene. eCpGs had less measurement error and were enriched for active blood regulatory regions and for CpGs reported to be associated with environmental exposures or phenotypic traits. 40.4% of eQTMs had at least one genetic variant associated with methylation and expression levels. The overlap of autosomal cis eQTMs in childrens blood with those described in adults was small (13.8%), and age-shared cis eQTMs tended to be proximal to the TSS and enriched for genetic variants. ConclusionsThis catalogue of autosomal cis eQTMs in childrens blood can help the biological interpretation of EWAS findings and is publicly available at https://helixomics.isglobal.org/. Funding: The study has received funding from the European Communitys Seventh Framework Programme (FP7/2007-206) under grant agreement no 308333 (HELIX project); the H2020-EU.3.1.2. - Preventing Disease Programme under grant agreement no 874583 (ATHLETE project); from the European Unions Horizon 2020 research and innovation programme under grant agreement no 733206 (LIFECYCLE project), and from the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL and Instituto de Salud Carlos III) under the grant agreement no AC18/00006 (NutriPROGRAM project). The genotyping was supported by the project PI17/01225, funded by the Instituto de Salud Carlos III and co-funded by European Union (ERDF, "A way to make Europe") and the Centro Nacional de Genotipado-CEGEN (PRB2-ISCIII).

genomics↗

bioRxiv2020

Bayesian neural networks for the optimisation of biological clocks in humans

DNA methylation is related to aging. Some researchers, such as Horvath or Levine have managed to create epigenetic and biological clocks that predict chronological age using methylation data. These authors used Elastic Net methodology to build age predictors that had a high prediction accuracy. In this article, we propose to improve their performance by incorporating an additional step using neural networks trained with Bayesian learning. We shown that this approach outperforms the results obtained when using Horvaths method, neural networks directly, or when using other training algorithms, such as Levenberg-Marquardts algorithm. The R-squared value obtained when using our proposed approach in empirical (out-of sample) data was 0.934, compared to 0.914 when using a different training algorithm (Levenberg Marquard), or 0.910 when applying the neural network directly (e.g. without first reducing the dimensionality of the data). The results were also tested in independent datasets that were not used during the training phase. Our method obtained better R-squared values and RMSE than Horvaths and Levines method in 8 independent datasets. We demonstrate that building an age predictor using a Bayesian based algorithm provides accurate age predictions. This method is implemented in an R function, which is available through a package created for predicting purposes and is applicable to methylation data. This will help to elucidate the role of DNA methylation age in complex diseases or traits related to aging.

bioinformatics↗

bioRxiv2019

Polymorphic inversions underlie the shared genetic susceptibility to prevalent common diseases

The burden of several common diseases including obesity, diabetes, hypertension, asthma, and depression is increasing in most world populations. However, the mechanisms underlying the numerous epidemiological and genetic correlations among these disorders remain largely unknown. We investigated whether common polymorphic inversions underlie the shared genetic influence of these disorders. We performed the largest inversion association analysis to date, including 21 inversions and 25 obesity-related traits, on a total of 408,898 Europeans, and validated the results in 67,299 independent individuals. Seven inversions were associated with multiple diseases while inversions at 8p23.1, 16p11.2 and 11q13.2 were strongly associated with the co-occurrence of obesity with other common diseases. Transcriptome analysis across numerous tissues revealed strong candidate genes of obesity-related traits. Analyses in human pancreatic islets indicated the potential mechanism of inversions in the susceptibility of diabetes by disrupting the cis-regulatory effect of SNPs from their target genes. Our data underscore the role of inversions as major genetic contributors to the joint susceptibility to common complex diseases.

genetics↗

bioRxiv2019

Association between DNA methylation and ADHD symptoms from birth to school age: A prospective meta-analysis

Attention-deficit and hyperactivity disorder (ADHD) is a common childhood disorder with a substantial genetic component. However, the extent to which epigenetic mechanisms play a role in the etiology of the disorder is not known. We performed epigenome-wide association studies (EWAS) within the Pregnancy And Childhood Epigenetics (PACE) Consortium to identify DNA methylation sites associated with ADHD symptoms at two methylation assessment periods: birth and school-age. We examined associations of DNA methylation in cord blood with repeatedly assessed ADHD symptoms (age range 4-15 years) in 2477 children from five cohorts and DNA methylation at school-age with concurrent ADHD symptoms (age 7-11 years) in 2374 children from ten cohorts. CpGs identified with nominal significance (p<0.05) in either of the EWAS were correlated between timepoints ({rho}=0.30), suggesting overlap in associations, however, top signals were very different. At birth, we identified nine CpGs that were associated with later ADHD symptoms (P<1*10-7), including ERC2 and CREB5. Peripheral blood DNA methylation at one of these CpGs (cg01271805 located in the promotor region of ERC2, which regulates neurotransmitter release) was previously associated with brain methylation. Another (cg25520701) lies within the gene body of CREB5, which was associated with neurite outgrowth and an ADHD diagnosis in previous studies. In contrast, at school-age, no CpGs were associated with ADHD with P<1*10-7. In conclusion, we found evidence in this study that DNA methylation at birth is associated with ADHD. Future studies are needed to confirm the utility of methylation variation as biomarker and its involvement in causal pathways.

genetics↗

bioRxiv2019

Historical recombination variability contributes to deciphering the genetic basis of phenotypic traits

Recombination is a main source of genetic variability. However, the potential role of the variation generated by recombination in phenotypic traits, including diseases, remains unexplored as there is currently no method to infer chromosomal subpopulations based on recombination patterns differences. We developed recombClust, a method that uses SNP-phased data to detect differences in historic recombination in a chromosome population. We validated our method by performing simulations and by using real data to accurately predict the alleles of well known recombination modifiers, including common inversions in Drosophila melanogaster and human, and the chromosomes under selective pressure at the lactase locus in humans. We then applied recombClust to the complex human 1q21.1 region, where nonallelic homologous recombination produces deleterious phenotypes. We discovered and validated the presence of two different recombination histories in these regions that significantly associated with the differential expression of ANKRD35 in whole blood and that were in high linkage with variants previously associated with hypertension. By detecting differences in historic recombination, our method opens a way to assess the influence of recombination variation in phenotypic traits.

bioinformatics↗

bioRxiv2019

A robust estimation of mosaic loss of chromosome Y from genotype-array-intensity data to improve disease risk associations and transcriptional effects

Accurate protocols and methods to robustly detect the mosaic loss of chromosome Y (mLOY) are needed given its reported role in cancer, several age-related disorders and overall male mortality. Intensity SNP-array data have been used to infer mLOY status and to determine its prominent role in male disease. However, discrepancies of reported findings can be due to the uncertainty and variability of the methods used for mLOY detection and to the differences in the tissue-matrix used. We proposed MADloy, the first publicly available software tool that incorporates previous methods and includes a new robust approach, allowing efficient calling in large studies and comparisons between methods. The new method implemented in MADloy optimizes mLOY calling by correctly modeling the underlying reference population with no-mLOY status and incorporating B-deviation information. We observed improvements in the calling accuracy with respect to previous methods, using experimentally validated samples, and an increment in the statistical power to detect associations with disease and mortality, using simulation studies and real dataset analyses. We applied MADloy to detect the increment of mLOY cellularity in blood on 18 individuals after 3 years, and to confirm that its detection in saliva was sub-optimal (41%). We illustrate the use of MADloy to detect the down-regulation genes in the chromosome Y in kidney and bladder tumors with mLOY, and to perform pathway analyses for the detection of mLOY in blood. MADloy is a new software tool implemented in R for easy and robust calling of mLOY status in men aimed to facilitate its study in large epidemiological studies.

genomics↗

bioRxiv2019

Are methylation beta-values simplex distributed?

DNA methylation plays an important role in the development and progression of disease. Beta-values are the standard methylation measures. Different statistical methods have been proposed to assess differences in methylation between conditions. However, most of them do not completely account for the distribution of beta-values. The simplex distribution can accommodate beta-values data. We hypothesize that simplex is a quite flexible distribution which is able to model methylation data.\n\nTo test our hypothesis, we conducted several analyses using four real data sets obtained from microarrays and sequencing technologies. Standard data distributions were studied and modelled in comparison to the simplex. Besides, some simulations were conducted in different scenarios encompassing several distribution assumptions, regression models and sample sizes. Finally, we compared DNA methylation between females and males in order to benchmark the assessed methodologies under different scenarios.\n\nAccording to the results obtained by the simulations and real data analyses, DNA methylation data are concordant with the simplex distribution in many situations. Simplex regression models work well in small sample size data sets. However, when sample size increases, other models such as the beta regression or even the linear regression can be employed to assess group comparisons and obtain unbiased results. Based on these results, we can provide some practical recommendations when analyzing methylation data: 1) use data sets of at least 10 samples per studied condition for microarray data sets or 30 in NGS data sets, 2) apply a simplex or beta regression model for microarray data, 3) apply a linear model in any other case.

bioinformatics↗

bioRxiv2018

Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

We conducted genome-wide association study (GWAS) meta-analyses of relative caloric intake from fat, protein, carbohydrates and sugar in over 235,000 individuals. We identified 21 approximately independent lead SNPs. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg {approx} 0.15 - 0.5). Relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood poverty (|rg| {approx} 0.1 - 0.3). Overall, our results show that the relative intake of each macronutrient has a distinct genetic architecture and pattern of genetic correlations suggestive of health implications beyond caloric content.

genetics↗

bioRxiv2018

Genome-wide study identifies 611 loci associated with risk tolerance and risky behaviors

Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. We identified 611 approximately independent genetic loci associated with at least one of our phenotypes, including 124 with general risk tolerance. We report evidence of substantial shared genetic influences across general risk tolerance and risky behaviors: 72 of the 124 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is moderately to strongly genetically correlated ([Formula] to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated SNPs are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We find no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.

genetics↗

bioRxiv2017

A measure of agreement to distinguish between condition levels: Reproducibility of co-expression networks across tissues

There is great interest to study how co-expression gene networks change across tissues. However, the reproducibility assessment of these studies is challenged by a lack of fully confirmatory experiments from independent researchers. While an increment in the number of studies with expression data for several tissues is expected, statistical measures are still needed to assess the reproducibility between studies. We identified a gap in the statistical literature concerning the assessment of agreement between studies that independently measure the effect of a varying condition on a population sample. The gap precluded us to test, using standard statistics, the level of agreement between the GTEX (RNAseq) and BRAINEAC (microarray) studies to distinguish the structure of co-expression networks across four brain tissues. We, therefore, generalized a classical measure of agreement, Cohens{kappa} , derived its distributional characteristics and determined its reliability properties. In the gene expression studies, we found full agreement of genome-wide networks in BRAINEAC benchmarked against GTEX, and highest agreement for brain specific pathways. Our highly interpretable measure can contribute to anticipated efforts on reproducibility research.

systems biology↗

bioRxiv2017

A Comprehensive Reanalysis Of Publicly Available GWAS Datasets Reveals An X Chromosome Rare Regulatory Variant Associated With High Risk For Type 2 Diabetes.

The reanalysis of publicly available GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics and pathophysiology of complex diseases. We demonstrate this by gathering and reanalyzing public type 2 diabetes (T2D) GWAS data for 70,127 subjects, using an innovative imputation and association strategy based on multiple reference panels (1000G and UK10K). This approach led us replicate and fine map 50 known T2D loci, and identify seven novel associated regions: five driven by common variants in or near LYPLAL1, NEUROG3, CAMKK2, ABO and GIP genes; one by a low frequency variant near EHMT2; and one driven by a rare variant in chromosome Xq23, associated with a 2.7-fold increased risk for T2D in males, and located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a known modulator of insulin sensitivity. We further show that the risk T allele reduces binding of a nuclear protein, resulting in increased enhancer activity in muscle cells. Beyond providing novel insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel analytical approaches.

genetics↗