Biology subjects

Oliveira, L. G.

Publications and source records attributed to Oliveira, L. G..

6 recordsLinked to original sources

bioRxiv2024

Application of a Bayesian model based on probability of occurrence to evaluate the effect of an environmental gradient on the turnover of aquatic insect genera in Cerrado streams

In ecology, understanding and quantifying the species turnover rates among different locations is essential for a more concise and predictive science. However, little is known about how the turnover occurs among environmentally similar locations and how it may be related to habitat integrity. Using the communities of Ephemoptera, Plecoptera, and Trichoptera sampled from streams in the Brazilian Cerrado, we tested the following hypotheses: a) genus turnover between similar streams will higher in more preserved streams; b) the relationship between proportional genus turnover and the environment is influenced by the taxonomic group. We estimated parameters related to the number of potentials, observed, and alternation of these genera across a habitat integrity gradient in 101 observed streams using a model with Bayesian inference. Genera turnover among environmentally similar sites was directly related to the environmental integrity of the stream. Only the genera Plecoptera showed a pattern similar to the hypothesis we elaborated, showing an increased turnover among well-preserved streams. For the other orders, the turnover presented two peaks in the environmental gradient, one in impacted sites and the other in preserved ones.

ecology↗

bioRxiv2023

Crafting negative training datasets for a high-performance classification of bacterial proteins secreted via non-classical pathways

Understanding protein secretion pathways is paramount in studying diseases caused by bacteria and their respective treatments. Most such paths must signal ways to identify secretion. However, some proteins, known as non-classical secreted proteins, do not have signaling ways. This study aims to classify such proteins from predictive machine-learning techniques. We collected a set of physical-chemical characteristics of amino acids from the AA index site, bolding known protein motifs, like hydrophobicity. We developed a six-step method (Alignment, Preliminary classification, mean outliers, two Clustering algorithms, and Random choice) to filter data from raw genomes and compose a negative dataset in contrast to a positive dataset of 141 proteins from the literature. Using a conventional Random Forest machine-learning algorithm, we obtained an accuracy of 91% on classifying non-classical secreted proteins in a validation dataset with 14 positive and 92 negative proteins - sensitivity and specificity of 91 and 86%, respectively, performance compared to state of the art for non-classical secretion classification. However, this works novelty resides in the fastness of executing non-CSP classification: instead of dozens of seconds to just one second considering a few dozen protein samples or only ten seconds to classify one hundred thousand proteins. Such fastness is more suitable for pan-genomic analyses than current methods without losing accuracy. Therefore, this research has shown that selecting an appropriate descriptors set and an expressive training dataset compensates for not using an advanced machine learning algorithm for the secretion by non-classical pathways purpose. Available at https://github.com/santosardr/non-CSPs.

bioinformatics↗

bioRxiv2021

SARS-CoV-2 Infection Impacts Carbon Metabolism and Depends on Glutamine for Replication in Syrian Hamster Astrocytes

Coronaviruses belong to a well-known family of enveloped RNA viruses and are the causative agent of the common cold. Although the seasonal coronaviruses do not pose a threat to human life, three members of this family, i.e., SARS-CoV, MERS-CoV and recently, SARS-CoV2, may cause severe acute respiratory syndrome and lead to death. Unfortunately, COVID-19 has already caused more than 4.4 million deaths worldwide. Although much is better understood about the immunopathogenesis of the lung disease, important information about systemic disease is still missing, mainly concerning neurological parameters. In this context, we sought to evaluate immunometabolic changes using in vitro and in vivo models of hamsters infected with SARS-CoV-2. Here we show that, besides infecting hamsters astrocytes, SARS-CoV-2 induces changes in protein expression and metabolic pathways involved in carbon metabolism, glycolysis, mitochondrial respiration, and synaptic transmission. Interestingly, many of the differentially expressed proteins are concurrent with proteins that correlate with neurological diseases, such as Parkinsonss disease, multiple sclerosis, amyotrophic lateral sclerosis, and Huntingtons disease. Metabolic analysis by high resolution real-time respirometry evidenced hyperactivation of glycolysis and mitochondrial respiration. Further metabolomics analysis confirmed the consumption of many metabolites, including glucose, pyruvate, glutamine, and alpha ketoglutarate. Interestingly, we observed that glutamine was significantly reduced in infected cultures, and the blockade of mitochondrial glutaminolysis significantly reduced viral replication and pro-inflammatory response. SARS-CoV-2 was confirmed in vivo as hippocampus, cortex, and olfactory bulb of intranasally infected hamsters were positive for viral genome several days post-infection. Altogether, our data reveals important changes in overall protein expression, mostly of those related to carbon metabolism and energy generation, causing an imbalance in important metabolic molecules and neurotransmitters. This may suggest that some of the neurological features observed during COVID-19, as memory and cognitive impairment, may rely on altered energetic profile of brain cells, as well as an unbalanced glutamine/glutamate levels, whose importance for adequate brain function is unquestionable.

immunology↗

bioRxiv2021

Zika Virus Infection of Murine and Human Neutrophils and their Function as Trojan Horses to the Placenta

ZIKV is a 11Kb positive stranded flavivirus transmitted by infected Aedes aegypti and by sexual intercourse. After a short period of viremia of 5-7 days, the virus is cleared, and infection resolved in 80% of individuals. However, around 27% of the fetuses from pregnant infected mothers may develop several fetal brain and ocular pathology. Here we show that murine and peripheral blood human neutrophils support ZIKV infection and replication both in vitro and in vivo, which may correlate to the facilitation of vertical transmission. ZIKV did not interfere with cell viability, neither induced ROS production nor the release of NETs by infected neutrophils. Also, ZIKV infection of neutrophils did not trigger a pro-inflammatory profile, as evidenced by qPCR and proteomic analysis. Interestingly, ZIKV-infected neutrophils were isolated from the placenta were highly infected. The transference of in vitro ZIKV-infected neutrophils to pregnant female mice favored the transference of viral particles to the fetus. Conversely, neutrophil depletion with monoclonal antibodies reduced fetal viral loads whereas the treatment with recombinant G-CSF has the opposite effect. In summary, although it has already been shown that circulating monocytes harbor ZIKV, to our knowledge, this is the first report demonstrating the role of neutrophils during ZIKV infection, and most important, that it may act as a trojan horse to placental tissue directly impacting the pathogenesis of congenital syndrome.

immunology↗

bioRxiv2021

Gas6 drives Zika virus-induced neurological complications in humans and congenital syndrome in immunocompetent mice

Zika virus (ZIKV) has the ability to cross placental and brain barriers, causing congenital malformations in neonates and neurological disorders in adults. However, the pathogenic mechanisms of ZIKV-induced neurological complications in adults and congenital malformations remain unknown. Gas6 is a soluble TAM receptor ligand able to promote flavivirus internalization and downregulation of immune responses. Here we demonstrate high Gas6 levels in the serum of patients with neurological complications which correlated with downregulation of genes associated with the type I IFN responses as consequence of Socs1 upregulation. Gas6 gamma-carboxylation is essential for ZIKV replication in monocytes, the main source of this protein. Gas6 also facilitates ZIKV replication in adult immunocompetent mice enabled susceptibility to transplacental infection and congenital malformations. Our data thus indicate that ZIKV promotes the upregulation of its ligand Gas6, which contributes to viral infectivity and drives the development of severe adverse outcomes during ZIKV infection.

microbiology↗

bioRxiv2020

Deviation from mendelian transmission of autosomal SNPs can be used to estimate germline mutations in humans exposed to ionizing radiation

We aimed to estimate the rate of germline mutations in the offspring of individuals accidentally exposed to Cesium-137 ionizing radiation. Performed analysis considered two distinct groups: a group males and females accidentally exposed to low doses of ionizing radiation from Cs137, the case group, and a control group of non-exposed participants. The case group included 37 participants (11 couples and 15 children born after the accident). The dose absorbed by exposed participants ranged from 0.2 to 0.5 Gray. The control group included 15 families from the state of Goias, with no history of radiation exposure. DNA samples from peripheral blood were analyzed with the Affymetrix GeneChip(R) CytoScanHD to assess de novo SNP-type mutations. A set of scripts previously developed was used to detect de novo mutations by comparing parent and offspring genotypes in each SNP marker. Overall numbers of observed Mendelian deviations were statistically significant between the exposed and control groups. Offspring from the population accidentally exposed to low IR doses showed [~] 46.5% more de novo Mendelian deviations than the control group. Parent-of-origin and type of nucleotide substitution were also inferred. Estimates of age-adjusted de novo germline mutation rates were obtained and correlated to Cs-137 radiation dose exposure to evaluate the usefulness of the rate of Mendelian deviations observed in polymorphic SNPs as a biomarker for exposure. This proved useful in a retrospective estimation of the rate of de novo germline mutations in a human population accidentally exposed to low doses of radiation from Cs-137. Obtained results suggest that observed burden of germline mutations identified in offspring could potentially be a useful biomarker to estimate levels of parental exposure to ionizing radiation.

genetics↗