Biology subjects

Oliveira, R.

Publications and source records attributed to Oliveira, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Age-Group Differences in Skeletal Age, Anabolic Hormones, and Physical Fitness in Elite Youth Football Players from Under-13 to Under-16

ObjectivesFootball players between the ages of 13 and 16 were the subjects of this study to (i) compare skeletal age, growth hormone (GH), insulin-like growth factor-1 (IGF-1), VO2max, countermovement jump (CMJ) performance, and playing time across four consecutive age groups (under-13 to under-16), and (ii) investigate correlations between these metrics within each age group. Designcross-sectional research study. MethodsThe U13, U14, U15, and U16 groups included 122 elite male youth football players (14.13 {+/-} 1.14 years; 169.39 {+/-} 9.82 cm; 55.56 {+/-} 10.10 kg). The Fels method was used to determine skeletal age. Anthropometric measures included height, weight, and sitting height. The CMJ and Yo-Yo (VO2max) tests were used to assess physical fitness. GH and IGF-1 were measured in blood samples. Pearson correlation and one-way ANOVA were used. ResultsAnthropometric assessment, skeletal age, VO2max, CMJ, IGF-1, football training, and minutes playing all showed significant group differences, with the U16 group demonstrating the highest values and the U13 group the lowest (p < 0.001). There were no significant differences in GH (p = 0.172). Although there were no consistent relationships between GH or IGF-1 and height or weight, these variables did correlate with other factors; however, these associations varied by group. ConclusionsAcross the under-13 to under-16 span, skeletal age, physical fitness, and IGF-1 increased progressively between age groups, whereas GH did not differ. The impact of biological maturation on performance was demonstrated by the fact that older, more experienced players performed better than younger ones. The absence of a between-group difference in GH, despite progressive changes in the other measures, points to maturity-driven adaptations rather than a uniform hormonal response.

Developmental Biology↗

bioRxiv2026

Genome-wide DNA methylation profiling of the zebrafish forebrain

The zebrafish forebrain is a central hub for cognitive and social behaviors, yet a comprehensive, region-specific DNA methylation reference for this tissue is not available. To address this gap, we generated a genome-wide methylation map of the adult zebrafish forebrain using Oxford Nanopore Technologies (ONT) long-read sequencing. Forebrains from six individuals were profiled, enabling direct detection of multiple DNA base modifications at single-base resolution. The resulting dataset includes CpG-associated 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), as well as non-CpG 5mC and N6-methyladenine (6mA), with 96.8% genome coverage. CpG methylation was widespread, with 64.2% of CpG sites classified as highly 5mC-modified. In contrast, 5hmC and non-CpG methylation were markedly less abundant, and 6mA was detected at very low levels. CpG islands showed a bimodal distribution of methylation, promoter regions displayed elevated variability compared to gene bodies, and CC-context non-CpG methylation exhibited significant strand asymmetry. This resource provides a high-resolution epigenomic baseline for the adult zebrafish forebrain.

genomics↗

bioRxiv2026

Validating Neurite EXchange Imaging (NEXI) using diffusion Monte Carlo simulations in realistic numerical gray matter substrates

NEXI is a gray matter (GM) microstructural model designed to probe brain tissue microstructure in vivo using diffusion MRI. NEXI describes GM as two exchanging Gaussian compartments - neurites, modeled as randomly oriented, infinitely long sticks, and the extracellular space - allowing the estimation of biophysically interpretable parameters related to neurite microstructure and intercompartmental exchange. While modeling cell processes as sticks and each compartment as Gaussian are common assumptions for brain biophysical models of diffusion, neurite structural irregularities and the presence of somas, particularly in GM, may violate them and bias NEXI parameter estimates. Furthermore, the barrier-limited exchange assumed in the Karger model that underlies NEXI may also be violated in realistic conditions. Therefore, in this work, we evaluate NEXIs accuracy in numerical substrates that incorporate realistic GM features and membrane permeability. To this end, we generated several GM-like substrates with neurite beading, undulation, orientation dispersion, and somas across a range of membrane permeabilities. Diffusion signals were generated with Monte Carlo simulations of water diffusion and subsequently fitted with NEXI. Overall, NEXI accurately recovered exchange times across permeability levels and successfully disentangled exchange effects from other microstructural features, showing only minor bias in estimates from the realistic geometries. These results support its potential for in vivo GM microstructure mapping and studies of brain disorders.

neuroscience↗

bioRxiv2025

Continental-scale genomic surveillance of Plasmodium falciparum malaria with rapid nanopore sequencing

In sub-Saharan Africa, continental-scale genomic surveillance of Plasmodium falciparum malaria is needed to track the spread of antimalarial drug resistance and diagnostic test evasion, as well as to monitor parasite evolutionary responses to vaccine rollout. Yet implementation of malaria genomic surveillance at a continental-scale is hindered by resource constraints, the vastness of the continent, and the lack of sequencing protocols suitable for most local laboratories. To address this, we developed an approach to enable a decentralized scale-up of P. falciparum genomic surveillance and established it in six African countries in one year, locally sequencing 1,065 samples. The approach includes a rapid ([~] 5 hours) and cost-efficient (<$25 USD/sample) nanopore sequencing protocol that provides surveillance of drug resistance-associated genes, hrp2/3 deletions, the vaccine target csp, and the polymorphic gene ama1. We coupled this to a bioinformatics dashboard that runs offline on a laptop and displays mapping and variant calling results in real-time. We demonstrate robust sequencing coverage across parasitemia levels and laboratories, accurate identification of antimalarial resistance markers and hrp2/3 deletions; and, with a novel variant caller, sensitive detection of mutations carried by minor clones. Our approach will accelerate genomic surveillance of P. falciparum malaria across sub-Saharan Africa at a time of urgent need.

genomics↗

bioRxiv2025

Nonapeptide molecular evolution during the adaptive radiation of Tanganyika cichlids

Oxytocin (OT) and vasotocin (VT) are evolutionarily conserved nonapeptides that regulate a wide range of physiological and behavioural processes in vertebrates. Their receptor families have undergone gene duplications that facilitated functional diversification throughout vertebrate evolution. Using the diverse cichlid species in Lake Tanganyika, which have undergone repeated evolutionary transitions between social phenotypes, we investigated the molecular evolution of the nonapeptide system and its potential involvement in social behaviour. We performed a positive selection analysis based on the dN/dS ratio and examined the correlation between amino acid variants and two social phenotypes. We also analysed gene expression data to explore associations between brain receptor expression and social phenotype variation. Our findings reveal that, while most sites in nonapeptide receptors are under strong purifying selection, a few sites - primarily in the extended intracellular loop 3 (IL3) of VTR2A receptors - show signatures of positive selection. Additionally, a specific amino acid in VTR2Aa correlates with pair-bonding, suggesting its potential role in social attachment. Together, our results provide new insights into the evolution of the nonapeptide system and its contribution to social diversity in cichlids.

evolutionary biology↗

bioRxiv2025

Using supervised machine learning to quantify cleaning behaviour

Cleaner fish engage in mutualistic interactions by removing ectoparasites from client species, a behaviour that has traditionally been quantified through labour-intensive manual video analysis. This method is not only time-consuming but also susceptible to human error and bias. In this study, we developed a semi-automated system to track and classify cleaning interactions between the cleaner wrasse (Labroides dimidiatus) and the powder blue tang (Acanthurus leucosternon) in a controlled three-dimensional laboratory setting. We employed DeepLabCut (DLC), a deep learning-based tool for markerless pose estimation, to track both fish species simultaneously. The resulting model reliably tracked both individuals with low error rates. Using the tracking data, we designed a classification algorithm that detected cleaning interactions with 90% accuracy. Although the algorithm misclassified approximately 15% of non-interactions as interactions, it successfully identified 25% of video content as containing interactions, thereby reducing the amount of footage requiring manual annotation by 75%. This approach significantly decreases human labour while maintaining high classification performance. Overall, our system represents a valuable step toward automating behavioural analysis in marine mutualisms and can serve as a foundation for broader applications in ethology and conservation research.

animal behavior and cognition↗

bioRxiv2025

Forest conversion to cashew orchards delays the diel activity of diurnal mammals in West Africa

Land-use change is the main driver of biodiversity loss worldwide. However, less is known about how species adapt their behavior to persist in human-altered habitats. We addressed this gap by examining mammal responses in terms of habitat use and diel activity patterns to forest conversion into cashew orchards in West Africa. We surveyed mammals using camera-trapping in 12 forest sites and 12 cashew orchards in the Cantanhez National Park in southwest Guinea-Bissau, West Africa. We grouped mammals into (1) diurnal and cathemeral and (2) nocturnal species according to their diel activity periods and assessed their use and diel activity between habitat types. Based on 709 trap-days, we obtained 842 records of 12 diurnal or cathemeral species (18.3% of the records) and 13 nocturnal species (81.7%). Mammal habitat use was similar between forests and cashew orchards for both diurnal/cathemeral and nocturnal species. However, the peak of diurnal/cathemeral species shifted from the morning period ([~]11h00) in the forests to the afternoon period in the cashew orchards ([~]16h30), resulting in little overlap in activity of diurnal/cathemeral species between habitat types. No differences were observed in the diel activity of nocturnal mammals. Although mammals can make use of altered habitats, diurnal species are able to delay their activity, probably to avoid direct contact with humans. Our study highlights the ability of species in adapting their behaviour to persist in newly human-modified landscapes in the tropics.

ecology↗

bioRxiv2025

Mammal responses to habitat degradation induced by cashew expansion in West Africa

Tropical landscapes are perishing due to high rates of land-use change. In West Africa, Guinea-Bissau lost 77% of its closed-canopy forest over the last 25 years, mostly to the expansion of cashew monoculture. To date, understanding how species cope with such changes remains a conservation priority for the region. Here we examine mammal species composition, richness, and abundance, in addition to trophic-guild abundance across closed-canopy sub-humid forests and cashews orchards in the Cantanhez National Park, southwest Guinea-Bissau. Mammals were surveyed using one camera trap at each of the 24 sites, half in forest and half in cashew orchards, and their local and landscape-scale variables were measured. Based on 709 trap-nights, we collected 842 records from 25 mammal species. Local habitat structure--including canopy openness, floor obstruction, density of both lianas, palms and trees, tree species richness and height--sharply contrasted between forests and cashew orchards. As expected, mammal species composition differed between forests and cashew orchards, and the estimated, but not the observed, species richness declined towards cashew-like habitats. Although overall mammal abundance remained unaffected by the variables considered, carnivores were more abundant in cashew-like habitats, whereas insectivores and herbivores were more abundant in forest-like habitats. Human activity and distance to forest did not affect the response variables considered. Forest conversion into cashew orchards negatively affects mammals by profoundly changing the local habitat structure. Guild-level responses further unveiled specificity in their vulnerability to this form of land-use change, alerting for a potential disruption in the ecosystem functioning. We emphasize the need for policies that limit monoculture expansion, while safeguarding the remaining forests, thus maximising biodiversity persistence across the Afrotropics.

ecology↗

bioRxiv2025

ISME - Incoherent Sampling of Multi-Echo data to minimize cardiac-induced noise in brain maps of R2* and magnetic susceptibility

AbstractO_ST_ABSPurposeC_ST_ABSMaps of the MRI parameters R2* and magnetic susceptibility () enable the investigation of microscopic tissue changes in brain disease. However, cardiac-induced signal instabilities increase the variability of brain maps of R2* and . In this study, we introduce ISME - a sampling strategy that minimizes the level of cardiac-induced instabilities in brain maps of R2* and . MethodsISME uses phase-encoding gradients to shift the k-space frequency of the acquired data between consecutive readouts of a multi-echo train. As a result, the multi-echo data at a given k-space index is acquired at different phases of the cardiac cycle. We compare the variability of R2* and maps acquired with ISME and with standard multi-echo trajectories in N=10 healthy volunteers. We investigate the effect of both trajectories on the spatial aliasing of pulsating MR signals and propose a weighted-least squares (NWLS) approach for the estimation of R2* that accounts for the increase of the residuals with echo time. ResultsISME reduces the variability of R2* and maps across repetitions by 25/26/21% and 24/32/23% in the cerebellum/brainstem/whole brain, respectively. With ISME, the spatial aliasing of pulsating MR signals is incoherent between raw echo images, leading to visually sharper R2* maps. The proposed NWLS approach for the estimation of R2* reduces the dependence of the fitting residuals on echo time and the variability of R2* by an additional 3/2/1% in the cerebellum/brainstem/whole brain. ConclusionISME allows the mitigation of cardiac-induced signal instabilities in brain maps of R2* and , improving reproducibility.

neuroscience↗

bioRxiv2025

Discrimination between Mycobacterium tuberculosis and Mycobacterium bovis using Fourier Transform Infrared Spectroscopy

Zoonotic tuberculosis (TB) caused by Mycobacterium bovis (Mb) is a neglected disease that hinders efforts to eradicate human tuberculosis. Developing a rapid, high-throughput diagnostic test to distinguish Mb from Mycobacterium tuberculosis (Mtb) isolates could enhance global zoonotic TB diagnostics and surveillance. This study aimed to evaluate the ability of Fourier Transform Infrared Spectroscopy (FT-IRS), using the IR Biotyper(R) system, to differentiate clinical isolates of Mb and Mtb. Two bacterial inactivation protocols-- paraformaldehyde and boiling--were tested using Mtb and BCG strains grown in liquid culture. While both methods allowed FT-IRS analysis, boiling was preferred due to its ease of use and efficiency in biomass recovery. Subsequently, Mtb and Mb isolates were analyzed using FT-IRS, and the resulting spectra were used to construct a sample classifier employing machine learning algorithms. Linear Discriminant Analysis (LDA) and a UPGMA dendrogram demonstrated clear separations between Mtb and Mb ecotypes. Additionally, a classifier built and internally validated using artificial neural networks achieved 99% accuracy in distinguishing Mb and Mtb. Further FT-IRS analysis of few available Mycobacterium africanum (Maf) strains demonstrated its capacity to differentiate Maf from Mtb and Mb, expanding its utility in regions where Maf is endemic. This is the first study to apply FT-IRS to distinguish tuberculous mycobacteria. FT-IRS proved to be a highly effective, rapid, and accurate diagnostic tool for differentiating Mb and Mtb strains, with promising applications for other tuberculous mycobacteria such as Maf. IMPORTANCEZoonotic tuberculosis (TB) caused by Mycobacterium bovis (Mb) remains a major threat due to its clinical similarity to human TB, higher rates of extrapulmonary cases, and resistance to pyrazinamide, complicating treatment. Current diagnostic methods used to differentiate M. tuberculosis (Mtb) from Mb and are limited by costs, resource needs, and technical complexity. We developed a method based on Fourier Transform Infrared Spectroscopy (FT-IRS) to differentiate Mb and Mtb clinical isolates with high accuracy. This diagnostic assay offers advantages over traditional molecular techniques by eliminating the need for DNA extraction, requiring less technical expertise, and providing fast, accurate differentiation of Mtb and Mb strains. This innovative approach can improve global diagnostics and surveillance of zoonotic TB.

microbiology↗

bioRxiv2024

Data acquisition strategies to reduce cardiac-induced noise in brain maps of R2* and magnetic susceptibility

Maps of the transverse relaxation rate R2* and magnetic susceptibility () are computed from gradient- echo data acquired at multiple echo times and are sensitive to signal instabilities induced by cardiac pulsation. Here, we introduce two k-space sampling strategies that aim to mitigate the impact of cardiac-induced noise in brain maps of R2* and . The proposed strategies are based on the higher level of cardiac-induced noise near the k-space centre compared to the periphery. Using a CArtesian trajectory with Spiral PRofile (CASPR), the first strategy allows for the acquisition of a specific number of averages at each k-space location, derived from the local level of cardiac-induced noise. The second strategy synchronizes the acquisition near the k-space centre with the cardiac cycle in real time. We compared the variability across 4 repetitions of R2* and maps computed from data acquired using both strategies and with a standard linear trajectory. Data was acquired in 10 healthy volunteers. Compared to linear trajectory, the CASPR trajectory reduced the variability of R2* and maps across repetitions by 26/28/22% and 19/18/16% in the brainstem/cerebellum/whole brain, for a 14% increase in scan time. The CASPR trajectory also reduced the level of aliasing artifacts from pulsating blood vessels. The synchronized trajectory did not reduce the variability of R2* or maps. CASPR trajectories can be designed to mitigate cardiac-induced noise in brain maps of the MRI parameters R2* and . Synchronization of data acquisition with the cardiac cycle did not reduce the level of cardiac-induced noise.

neuroscience↗

bioRxiv2024

Optimistic and pessimistic cognitive judgement bias modulates the stress response and cancer progression in zebrafish

Cognitive judgement bias in decision-making under ambiguity occurs both in animals and humans, with some individuals interpreting ambiguous stimulus as positive (optimism) and others as negative (pessimism). We hypothesize that judgement bias is a personality trait and that individuals with a pessimistic bias would be more reactive to stressors and therefore more susceptible to stress-related diseases than optimistic ones. Here, we show that zebrafish judgment bias is a consistent behavioral trait over time, and that pessimistic and optimistic fish express phenotype-specific neurogenomic responses to stress. Furthermore, both phenotypes show differential activation of the hypothalamic-pituitary-interrenal axis in response to chronic stress, suggesting that optimists have a lower stress reactivity. Accordingly, optimists seem to be more resilient to disease than pessimists, as shown by a lower tumorigenesis in a zebrafish melanoma line [Tg(mtifa:HRAS-GFP)]. Together these results indicate that judgement bias is paralleled by differences in the stress response with implications for disease resilience.

animal behavior and cognition↗

bioRxiv2024

Statistical design of a synthetic microbiome that clears a multi-drug resistant gut pathogen

Engineering functional microbiomes is challenging due to complex interactions between bacteria and their environments1-6. Using a set of 848 gut commensal strains and clearance of multi-drug resistant Klebsiella pneumoniae (Kp-MH258) as a target function, we engineered a functional 15-member synthetic microbiome--SynCom15--through a statistical approach agnostic to strain phenotype, mechanism of action, bacterial interactions, or composition of natural microbiomes. Our approach involved designing, building, and testing 96 metagenomically diverse consortia, learning a generative model using community strain presence/absence as input, and distilling model constraints through statistical inference. SynCom15 cleared Kp-MH258 across in vitro, ex vivo, and in vivo environments, matching the efficacy of a fecal microbiome transplant in a clinically relevant murine model of infection. The mechanism of suppression by SynCom15 was related to fatty acid production coupled with environmental acidification. SynCom15 also suppressed other pathogens--Clostridioides difficile, Escherichia coli, and other K. pneumoniae strains--but through different mechanisms. Sensitivity analysis revealed models trained on strain presence/absence captured the statistical structure of pathogen suppression, illustrating that community representation was key to our approach succeeding. Our framework, Constraint Distillation, could be a general and efficient strategy for building emergent complex systems, offering a path towards synthetic ecology more broadly.

synthetic biology↗

bioRxiv2023

Non-exponential transverse relaxation decay in subcortical grey matter

According to theoretical studies, the MRI signal decay due to transverse relaxation, in brain tissue with magnetic inclusions (e.g. blood vessels, myelin, iron-rich cells), exhibits a transition from a Gaussian behaviour at short echo times to exponential at long echo times. Combined, the Gaussian and exponential decay parameters carry information about the inclusions (e.g., size, volume fraction) and provide a unique insight into brain tissue microstructure. However, gradient echo decays obtained experimentally typically only capture the long-time exponential behaviour. Here, we provide experimental evidence of non-exponential transverse relaxation signal decay at short times in human subcortical grey matter, from MRI data acquired in vivo at 3T. The detection of the non-exponential behaviour of the signal decay allows the subsequent characterization of the magnetic inclusions in the subcortex. The gradient-echo data was collected with short inter-echo spacings, a minimal echo time of 1.25 ms and novel acquisition strategies tailored to mitigate the effect of motion and cardiac pulsation. The data was fitted using both a standard exponential model and non-exponential theoretical models describing the impact of magnetic inclusions on the MRI signal. The non-exponential models provided superior fits to the data, indicative of a better representation of the observed signal. The strongest deviations from exponential behaviour were detected in the substantia nigra and globus pallidus. Numerical simulations of the signal decay, conducted from histological maps of iron concentration in the substantia nigra, closely replicated the experimental data - highlighting that non-heme iron can be at the source of the non-exponential signal decay. To investigate the potential of the non-exponential signal decay as a tool to characterize brain microstructure, we attempted to estimate the properties of the inclusions at the source of this decay behaviour using two available analytical models of transverse relaxation. Under the assumption of the static dephasing regime, the magnetic susceptibility and volume fractions of the inclusions was estimated to range from 1.8 to 4 ppm and from 0.02 to 0.04 respectively. Alternatively, under the assumption of the diffusion narrowing regime, the typical inclusion size was estimated to be [~]2.4 m. Both simulations and experimental data point towards an intermediate regime with a non-negligible effect of water diffusion to signal decay. Non-exponential transverse relaxation decay provides new means to characterize the spatial distribution of magnetic material within subcortical grey matter tissue with increased specificity, with potential applications to Parkinsons disease and other pathologies.

neuroscience↗

bioRxiv2023

Statistical analyses of motion-corrupted MRI relaxometry data

Consistent noise variance across data points (i.e. homoscedasticity) is required to ensure the validity of statistical analyses of MRI data conducted using linear regression methods. However, head motion leads to degradation of image quality, introducing noise heteroscedasticity into ordinary-least square analyses. The recently introduced QUIQI method restores noise homoscedasticity by means of weighted least square analyses in which the weights, specific for each dataset of an analysis, are computed from an index of motion-induced image quality degradation. QUIQI was first demonstrated in the context of brain maps of the MRI parameter R2*, which were computed from a single set of images with variable echo time. Here, we extend this framework to quantitative maps of the MRI parameters R1, R2*, and MTsat, which are computed from multiple sets of images. QUIQI allows for optimization of the noise model by using metrics quantifying heteroscedasticity and free energy. QUIQI restores homoscedasticity more effectively than insertion of an image quality index in the analysis design and yields higher sensitivity than simply removing the datasets most corrupted by head motion from the analysis. In sum, QUIQI provides an optimal approach to group-wise analyses of a range of quantitative MRI parameter maps that is robust to inherent homoscedasticity.

neuroscience↗

bioRxiv2022

Single-subject EEG measurement of interhemispheric transfer-time for the in-vivo estimation of axonal morphology

Assessing axonal morphology in-vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of MRI data and EEG measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject-specific IHTTs are computed in a data-driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject-specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between-session variability was comparable to the differences in IHTT between subjects. The scale parameter of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 0.79 m. The change in axonal g-ratio with axonal radius ranged from 0.62 to 0.81 m-. The single-subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single-subject axonal morphology estimates.

neuroscience↗

bioRxiv2022

Overview of the SARS-CoV-2 genotypes circulating in Latin America during 2021

Latin America is one of the regions in which the COVID-19 pandemic has had a stronger impact, with more than 72 million reported infections and 1.6 million deaths until June 2022. Since this region is ecologically diverse and is affected by enormous social inequalities, efforts to identify genomic patterns of the circulating SARS-CoV-2 genotypes are necessary for the suitable management of the pandemic. To contribute to the genomic surveillance of the SARS-CoV-2 in Latin America, we extended the number of SARS-CoV-2 genomes available from the region by sequencing and analyzing the viral genome from COVID-19 patients from seven countries (Argentina, Brazil, Costa Rica, Colombia, Mexico, Bolivia and Peru). Subsequently, we analyzed the genomes circulating mainly during 2021 including records from GISAID database from Latin America. A total of 1534 genome sequences were generated from seven countries, demonstrating the laboratory and bioinformatics capabilities for genomic surveillance of pathogens that have been developed locally. For Latin America, patterns regarding several variants associated with multiple re-introductions, a relatively low percentage of sequenced samples, as well as an increment in the mutation frequency since the beginning of the pandemic, are in line with worldwide data. Besides, some variants of concern (VOC) and variants of interest (VOI) such as Gamma, Mu and Lambda, and at least 83 other lineages have predominated locally with a country-specific enrichments. This work has contributed to the understanding of the dynamics of the pandemic in Latin America as part of the local and international efforts to achieve timely genomic surveillance of SARS-CoV-2.

microbiology↗

bioRxiv2022

Targeting C5aR1 signaling reduced neutrophil extracellular traps and ameliorates COVID-19 pathology

Patients with severe COVID-19 develop acute respiratory distress syndrome (ARDS) that may progress to cytokine storm syndrome, organ dysfunction, and death. Considering that complement component 5a (C5a), through its cellular receptor C5aR1, has potent proinflammatory actions, and plays immunopathological roles in inflammatory diseases, we investigated whether C5a/C5aR1 pathway could be involved in COVID-19 pathophysiology. C5a/C5aR1 signaling increased locally in the lung, especially in neutrophils of critically ill COVID-19 patients compared to patients with influenza infection, as well as in the lung tissue of K18-hACE2 Tg mice (Tg mice) infected with SARS-CoV-2. Genetic and pharmacological inhibition of C5aR1 signaling ameliorated lung immunopathology in Tg-infected mice. Mechanistically, we found that C5aR1 signaling drives neutrophil extracellular trap (NET)s-dependent immunopathology. These data confirm the immunopathological role of C5a/C5aR1 signaling in COVID-19 and indicate that antagonist of C5aR1 could be useful for COVID-19 treatment.

immunology↗