Biology subjects

Castro, M.

Publications and source records attributed to Castro, M..

47 records · Page 3Linked to original sources

bioRxiv2020

Pre-TCR signaling intensity shapes the TCRβ repertoire

Signaling via pre-TCR is essential for initial T cell differentiation. How the signal is triggered and whether its alteration impacts on lymphocyte repertoires is nevertheless debated. We show that a mutation in the transmembrane domain of the CD3{zeta} chain impairs murine thymocyte development at the double negative (DN) stage coinciding with reduced levels of steady-state pre-TCR signaling. Single particle tracking and TIRF microscopy on mouse primary DN3/DN4 thymocytes shows that wild-type pre-TCR form particles with a broad range of fluorescent intensities whereas mutant complexes are less intensely labeled and move faster, suggesting reduced pre-TCR nanoclustering. Notably, the mutant early-pre-TCR-selected-DP population shows less TCR{beta} repertoire diversity. We thus propose that the pre-TCR forms stable nanoclusters, the size of which determines signaling efficacy. This signaling does not merely promote maturation of any thymocyte expressing a rearranged TCR{beta} chain, but shapes the repertoire of DP thymocytes that can audition for positive and negative selection.

immunology↗

bioRxiv2020

DNA Methylation-based Signatures Classify Sporadic Pituitary Tumors According to Clinicopathological Features.

BackgroundDistinct genome-wide methylation patterns have consistently clustered pituitary neuroendocrine tumors (PT) into molecular groups associated with specific clinicopathological features. Here we aim to identify, characterize and validate the methylation signatures that objectively classify PT into those molecular groups. MethodsCombining in-house and publicly available data, we conducted an analysis of the methylome profile of a comprehensive cohort of 177 tumor and 20 non-tumor specimens from the pituitary gland. We also retrieved methylome data from an independent pituitary tumor (PT) cohort (N=86) to validate our findings. ResultsWe identified three methylation clusters associated with functional status and adenohypophyseal cell lineages using an unsupervised approach. We also identified signatures based on differentially methylated CpG probes (DMP), some of which overlapped with pituitary-specific transcription factors genes (SF1 and Tpit), that significantly distinguished pairs of clusters related to functional status and adenohypophyseal cell lineage. These findings were reproduced in an independent cohort, validating these methylation signatures. The DMPs were mainly annotated in enhancer regions associated with pathways and genes involved in cell identity and tumorigenesis. ConclusionsWe identified and validated methylation signatures that distinguished PT by distinct functional status and adenohypophyseal cell lineages. These signatures, annotated in enhancer regions, indicate the importance of these elements in pituitary tumorigenesis. They also provide an unbiased approach to classify pituitary tumors according to the most recent classification recommended by the WHO 2017 using methylation profiling. Key-pointsO_LIDistinct methylation landscapes define PT groups with specific functional status/subtypes and adenohypophyseal lineages subtypes. C_LIO_LIMethylation abnormalities in each cluster mainly occur in CpG annotated in distal regions overlapping predicted enhancers regions associated with pathways and genes involved in cell identity and tumorigenesis. C_LIO_LIDNA methylation signatures provide an unbiased approach to classify PT. C_LI Importance of the studyThis study harnessed the largest methylome data to date from a comprehensive cohort of pituitary specimens obtained from four different institutions. We identified and validated methylation signatures that distinguished pituitary tumors into molecular groups that reflect the functionality and adenohypophyseal cell lineages of these tumors. These signatures, mainly located in enhancers, are associated with pathways and genes involved in cell identity and tumorigenesis. Our results show that methylome profiling provides an objective approach to classify PT according to the most recent classification of PT recommended by the 2017 WHO.

cancer biology↗

bioRxiv2020

Purine metabolism regulates DNA repair and therapy resistance in glioblastoma

Intratumoral genomic heterogeneity in glioblastoma (GBM) is a barrier to overcoming therapy resistance, and new strategies that are effective independent of genotype are urgently needed. By correlating intracellular metabolite levels with radiation resistance across dozens of genomically-distinct models of GBM, we found that purine metabolites strongly correlated with radiation resistance. Inhibiting purine, but not pyrimidine, synthesis radiosensitized GBM cells and patient-derived neurospheres by impairing DNA repair in a nucleoside-dependent fashion. Likewise, administration of exogenous purine nucleosides protected sensitive GBM models from radiation by promoting DNA repair. Combining an FDA-approved inhibitor of de novo purine synthesis with radiation arrested growth in GBM xenograft models and depleted intratumoral guanylates. High expression of the rate-limiting enzyme of de novo GTP synthesis was associated with shorter survival in GBM patients. Together, these findings indicate that inhibiting de novo purine synthesis may be a promising strategy to overcome therapy resistance in this genomically heterogeneous disease.

neuroscience↗

bioRxiv2020

CCR5 deficiency impairs CD4+ T cell memory responses and antigenic sensitivity through increased ceramide synthesis

In CD4+ T cells, CCR5 is not only a coreceptor for HIV-1 infection, but also contributes to their functional fitness. Here we show that by limiting GATA-1-induced transcription of specific ceramide synthases, CCR5 signaling reduces ceramide levels and thereby increases T cell antigen receptor (TCR) nanoclustering in antigen-experienced mouse and human CD4+ T cells. This activity is CCR5-specific and independent of CCR5 costimulatory activity. CCR5-deficient mice showed reduced production of high affinity class-switched antibodies, but only after antigen rechallenge, which implies an impaired memory CD4+ T cell response. This study identifies a CCR5 function in the generation of CD4+ T cell memory responses, and establishes an antigen-independent mechanism that regulates TCR nanoclustering by altering specific lipid species.

immunology↗

bioRxiv2020

The Neural Basis for a Persistent Internal State in Drosophila Females

Sustained changes in mood or action require persistent changes in neural activity, but it has been difficult to identify and characterize the neural circuit mechanisms that underlie persistent activity and contribute to long-lasting changes in behavior. Here, we focus on changes in the behavioral state of Drosophila females that persist for minutes following optogenetic activation of a single class of central brain neurons termed pC1. We find that female pC1 neurons drive a variety of persistent behaviors in the presence of males, including increased receptivity, shoving, and chasing. By reconstructing cells in a volume electron microscopic image of the female brain, we classify 7 different pC1 cell types and, using cell type specific driver lines, determine that one of these, pC1-Alpha, is responsible for driving persistent female shoving and chasing. Using calcium imaging, we locate sites of minutes-long persistent neural activity in the brain, which include pC1 neurons themselves. Finally, we exhaustively reconstruct all synaptic partners of a single pC1-Alpha neuron, and find recurrent connectivity that could support the persistent neural activity. Our work thus links minutes-long persistent changes in behavior with persistent neural activity and recurrent circuit architecture in the female brain.

neuroscience↗

bioRxiv2020

Testing structural identifiability by a simple scaling method

Successful mathematical modeling of biological processes relies on the expertise of the modeler to capture the essential mechanisms in the process at hand and on the ability to extract useful information from empirical data. The very structure of the model limits the ability to infer numerical values for the parameters, a concept referred to as structural identifiability. Most of the available methods to test the structural identifiability of a model are either too complex mathematically for the general practitioner to be applied, or require involved calculations or numerical computation for complex non-linear models. In this work, we present a new analytical method to test structural identifiability of models based on ordinary differential equations, based on the invariance of the equations under the scaling transformation of its parameters. The method is based on rigorous mathematical results but it is easy and quick to apply, even to test the identifiability of sophisticated highly non-linear models. We illustrate our method by example and compare its performance with other existing methods in the literature. Author summaryTheoretical Biology is a useful approach to explain, generate hypotheses, or discriminate among competing theories. A well-formulated model has to be complex enough to capture the relevant mechanisms of the problem, and simple enough to be fitted to data. Structural identifiability tests aim to recognize, in advance, if the structure of the model allows parameter fitting even with unlimited high-quality data. Available methods require advanced mathematical skills, or are too costly for high-dimensional non-linear models. We propose an analytical method based on scale invariance of the equations. It provides definite answers to the structural identifiability problem while being simple enough to be performed in a few lines of calculations without any computational aid. It favorably compares with other existing methods.

systems biology↗

bioRxiv2019

Binary and analog variation of synapses between cortical pyramidal neurons

Learning from experience depends at least in part on changes in neuronal connections. We present the largest map of connectivity to date between cortical neurons of a defined type (L2/3 pyramidal cells), which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects. We used the map to identify constraints on the learning algorithms employed by the cortex. Previous cortical studies modeled a continuum of synapse sizes (Arellano et al. 2007) by a log-normal distribution (Loewenstein, Kuras, and Rumpel 2011; de Vivo et al. 2017; Santuy et al. 2018). A continuum is consistent with most neural network models of learning, in which synaptic strength is a continuously graded analog variable. Here we show that synapse size, when restricted to synapses between L2/3 pyramidal cells, is well-modeled by the sum of a binary variable and an analog variable drawn from a log-normal distribution. Two synapses sharing the same presynaptic and postsynaptic cells are known to be correlated in size (Sorra and Harris 1993; Koester and Johnston 2005; Bartol et al. 2015; Kasthuri et al. 2015; Dvorkin and Ziv 2016; Bloss et al. 2018; Motta et al. 2019). We show that the binary variables of the two synapses are highly correlated, while the analog variables are not. Binary variation could be the outcome of a Hebbian or other synaptic plasticity rule depending on activity signals that are relatively uniform across neuronal arbors, while analog variation may be dominated by other influences. We discuss the implications for the stability-plasticity dilemma.

neuroscience↗

bioRxiv2019

Selectivity and engineering of the sialoglycan-binding spectrum in Siglec-like adhesins

The Siglec-like Serine-Rich Repeat (SRR) adhesins mediate bacterial attachment to mammalian hosts via sialoglycan receptors. Here, we combine structural, computational, biochemical, and phylogenetic approaches to elucidate the determinants of the sialoglycan-binding spectrum across the family of Siglec-like SRR adhesins. We further identified mutable positions that disproportionately affect sialoglycan selectivity, as demonstrated by increases in binding to alternative ligands of 2- to 3-orders of magnitude. Biologically, these studies highlight how bacteria nimbly modulate the receptor interaction during coevolution of host and pathogen. These studies additionally created binding proteins specific for sialyl-T antigen or 6S-sialyl LewisX that can recognize glycosylation of human plasma proteins. The engineered binding proteins can facilitate the characterization of normal cellular glycan modifications or may be used as diagnostic tools in disease states with altered glycosylation.\n\nSignificanceThe ability of bacteria to bind selectively to host receptors underlies both commensalism and pathogenesis. Here, we identify the molecular basis for receptor selectivity in streptococci that bind to sialoglycan receptors. This revealed how to convert these adhesins into selective probes that measure triand tetrasacharides within the context of larger glycosylations. These probes that can be used in a laboratory with no specialized equipment and can be used to address biological questions relating to sialoglycan-dependent signaling and adhesion.

biochemistry↗

bioRxiv2019

Programmatic goals and spatial epidemiology influence the merit of targeted versus of population-wide interventions for yaws eradication

Infectious disease eradication programs often pursue spatially targeted interventions, but how well they perform might depend on the underlying spatial epidemiology and the specific goal of the program. We use a stochastic compartmental metapopulation model of yaws transmission to investigate how total targeted treatment (TTT) performs compared to mass drug administration (MDA) in different settings. While TTT can efficiently control the prevalence of active yaws disease, we consistently found that multiple rounds of TTT are required to match the impact of 1 round of MDA on the prevalence of latent yaws infection. When complete eradication of yaws is the goal, MDA can achieve the same result as TTT more quickly and probably at lower cost. We found that the performance of TTT is improved when there is little mixing between subpopulations and when there is spatial heterogeneity in transmissibility, but even in these settings, our model suggests that MDA will still outperform TTT.\n\nSignificance StatementYaws is a neglected tropical disease that causes skin lesions. Eradicating yaws is challenging because people can be infected but not show any signs or symptoms for years. Using simulations, we found that targeting antibiotics to people with active yaws and to their neighbors is a good way to combat active yaws, but treating entire populations is a better way to get rid of all infections, including the hidden ones. Also, targeted treatment works better in populations in which people do not move around much and in which how easily the disease is transmitted varies from place to place. Overall, a targeted treatment strategy uses fewer antibiotics but takes longer than mass treatment to achieve results.

epidemiology↗

bioRxiv2017

An integrated genomic analysis of anaplastic meningioma identifies prognostic molecular signatures

Anaplastic meningioma is a rare and aggressive brain tumor characterised by intractable recurrences and dismal outcomes. Here, we present an integrated analysis of the whole genome, transcriptome and methylation profiles of primary and recurrent anaplastic meningioma. A key finding was the delineation of two distinct molecular subgroups that were associated with diametrically opposed survival outcomes. Relative to lower grade meningiomas, anaplastic tumors harbored frequent driver mutations in SWI/SNF complex genes, which were confined to the poor prognosis subgroup. Our analyses discern two biologically distinct variants of anaplastic meningioma with potential prognostic and therapeutic significance.

genomics↗

bioRxiv2017

Exposure to Wood Smoke is Associated with Increased Risk of Asthma and Respiratory Symptoms in a Honduran Population

BackgroundExposure to environmental pollutants has been shown to be associated with asthma, but few studies have evaluated the effect of wood smoke on asthma and disease severity in a developing country, where use of stoves powered by solid fuels is a common practice.\n\nObjectiveIn a population in Olancho, Honduras, we evaluated the association between cooking fuel, stove type and asthma. We also evaluated the effects of these factors on asthma symptoms, lung function, and atopy.\n\nMethodsParticipants with physician-diagnosed asthma (n = 597) and controls without asthma (n = 429) were recruited from the Olancho province in Honduras. Participants were interviewed using a questionnaire and their baseline pulmonary function was measured using spirometry.\n\nResultsThe prevalence of use of wood as a cooking fuel was 66.9% in the study population, of which 42.1% of participants used wood as their only fuel. Use of wood as a cooking fuel was more prevalent among households with lower income, lower maternal education, and less urbanization. The prevalence of use of an open wood stove as the primary cooking stove among participants with asthma was 6.2% higher (95% CI 0.8 - 11.7%, p = .02) than among healthy controls. In a multiple logistic regression model, we identified a significant association between use of an open wood stove and asthma (OR = 1.80, 95% CI = 1.17 - 2.78, p = 0.007), compared to the referent (electric) stove category. Among participants with asthma, we identified a significant association between use of wood as cooking fuel and increased daytime respiratory symptoms (OR = 1.46, CI: 1.01 - 2.58, p = 0.046) and nocturnal symptoms (OR = 2.51, CI: 1.04 - 2.62, p = 0.04), though not with pulmonary function. Among control participants without asthma, use of wood as cooking fuel was associated with atopy (OR = 1.94, CI = 1.14 - 3.33, p = 0.015) and cough (OR = 2.22, CI = 1.09 - 4.88, p = 0.04).\n\nConclusionsUse of an open wood stove for cooking in a developing country appears to be a significant risk factor for asthma and respiratory symptoms. Exposure to wood smoke may play a role in atopic sensitization and respiratory symptoms, leading to the development of obstructive lung disease in susceptible individuals.

epidemiology↗