Biology subjects

Fonseca, F.

Publications and source records attributed to Fonseca, F..

4 recordsLinked to original sources

bioRxiv2023

Relationship between the colors of the rivers in the Amazon and the incidence of malaria

BackgroundMalaria is an infection caused by parasites of the genus Plasmodium, which are transmitted to humans via the bite of the female Anopheles mosquito. In Brazil, approximately 99% of malaria cases are concentrated in the Amazon region. Os rios desempenham um papel importante no ciclo de vida da malaria, uma vez que o vetor se reproduz em ambiente aquatico. The waters of the rivers in the Amazon have distinct chemical characteristics and this prompted us to analyze the influence of the color of the waters of the rivers in the Amazon on the distribution of malaria. MethodologyThis study was conducted for a period of seventeen years (2003-2019) in 50 municipalities in the state of Amazonas, Brazil. A generalized linear mixed model was developed to analyze the association of malaria incidence and three types of river color: white, black and mixed. Principal FindingsThe results suggest that there is a trend towards a decrease in malaria cases until 2015, with a possible resumption of the incidence of the disease from 2017 onwards, in all types of river color. In addition, the research indicates that places located near black-or mixed-water rivers have a higher incidence of malaria when compared to places on the banks of white-water rivers. ConclusionsHistorically, the hydrological regime has played an important role in the dynamics of malaria in the Amazon, but little is known about the relationship between river colors and the incidence of the disease. In this sense, our results, by showing a significant association between the colors of the rivers and the incidence of malaria over time, seem to expand the understanding between physical-chemical characteristics of the rivers and the occurrence of malaria. Author summaryMalaria is a disease that has a major impact on morbidity in tropical and subtropical countries. In Brazil, most of the cases registered in the country are concentrated in the northern region. A variety of factors can contribute to the occurrence of malaria outbreaks or epidemics, and rivers play an important role in the transmission of the disease. The waters of the rivers in the Amazon have distinct chemical characteristics and this study sought to analyze the influence of the color of the waters of the rivers in the Amazon on the distribution of malaria. Data on the incidence of malaria, from 2003 to 2019, in 50 municipalities in the state of Amazonas, Brazil, were associated with three types of river coloration: white, black and mixed. The results demonstrated the existence of a trend towards a decrease in malaria over the years, in all types of river coloration, and that this trend does not seem to be associated with the different types of water. However, the research indicates that places located near black-or mixed-water rivers have a higher incidence of malaria, when compared to places on the banks of white-water rivers.

ecology↗

bioRxiv2023

Biosys-LiDeOGraM: A visual analytics framework for interactive modelling of multiscale biosystems

In this paper, we present a test of an interactive modelling scheme in real conditions. The aim is to use this scheme to identify the physiological responses of microorganisms at different scales in a real industrial application context. The originality of the proposed tool, Biosys-LiDeOGraM, is to generate through a human-machine cooperation a consistent and concise model from molecules to microbial population scales: If multi-omics measurements can be connected relatively easily to the response of the biological system at the molecular scale, connecting them to the macroscopic level of the biosystem remains a difficult task, where human knowledge plays a crucial role. The use-case considered here pertains to an engineering process of freeze-drying and storage of Lactic Acid Bacteria. Producing a satisfying model of this process is a challenge due to (i) the scarcity and variability of the experimental dataset, (ii) the complexity and multi-scale nature of biological phenomena, and (iii) the wide knowledge about the biological mechanisms involved in this process. The Biosys-LiDeOGraM tool has two main components that can have to be utilized in an iterative manner: the Genomic Interactive Clustering (GIC) module and the Interactive Multi-Scale modellIng Exploration (IMSIE) module, both involve users in their learning loops. Applying our approach to a dataset of 2,741 genes, an initial model, as a graph involving 33 variables and 165 equations, was first built. Then the system was able to interactively improve a synthetic version of this model using only 27 variables and 16 equations. The final graph providing a consistent and explainable biological model. This graphical representation allows various user interpretations at local and global scales, an easy confrontation with data, and an exploration of various assumptions. Finally Biosys-LiDeOGraM is easily transferable to other use-cases of multi-scale modelling using functional graphs. Author summaryThe use of "omics" data for understanding biological systems has become prevalent in several research domains. However, the data generated from diverse macroscopic scales used for this purpose is highly heterogeneous and challenging to integrate. Yet, it is crucial to incorporate this information to gain a comprehensive understanding of the underlying biological system. Although various integrative analysis methods that have been developed provide predictive molecular-scale models, they only offer a mechanistic view of the biological system at the cellular level. In addition, they often focus on specific biological hypotheses through dedicated case studies, making it difficult to apply their results to other scientific problems. To address these issues, we propose an interactive multi-scale modelling approach to integrate cross-scale relationships providing predictive and potentially explanatory models. A proof-of-concept tool has been developed and was validated in the context of the bioproduction of Lactococcus lactis, a bacterial species of high economic interest in the food industry and for which the control of the bioprocess is essential to guarantee its viability and functionality. Our approach can be applied to any biological system that can be defined through a set of variables, constraints and scales.

bioengineering↗

bioRxiv2021

Monoclonal antibodies against cell wall chitooligomers as accessory tools for the control of cryptococcosis

Therapeutic strategies against systemic mycoses can involve antifungal resistance and significant toxicity. Thus, novel therapeutic approaches to fight fungal infections are urgent. Monoclonal antibodies (mAbs) are promising tools to fight systemic mycoses. In this study, mAbs of the IgM isotype were developed against chitin oligomers. Chitooligomers derive from chitin, an essential component of the fungal cell wall and a promising therapeutic target, as it is not synthesized by humans or animals. Surface plasmon resonance (SPR) assays and cell-binding tests showed that the mAbs recognizing chitooligomers have high affinity and specificity for the chitin derivatives. In vitro tests showed that the chitooligomer mAbs increased the fungicidal capacity of amphotericin B against Cryptococcus neoformans. The chitooligomer-binding mAbs interfered with two essential properties related to cryptococcal pathogenesis: biofilm formation and melanin production. In a murine model of C. neoformans infection, the combined administration of the chitooligomer-binding mAb and subinhibitory doses of amphotericin B promoted disease control. The data obtained in this study support the hypothesis that chitooligomer antibodies are of great potential as accessory tools in the control of cryptococcosis.

microbiology↗

bioRxiv2019

Linkage disequilibrium and haplotype block patterns in popcorn populations

Linkage disequilibrium (LD) analysis provides information on evolutionary aspects of the populations and allows selecting populations and single nucleotide polymorphisms (SNPs) for association studies. Recently, haplotype blocks have been used to increase the power of quantitative trait loci detection in genome-wide association studies and the prediction accuracy with genomic selection. The objectives of this study were to compare the degree of LD, the LD decay, the LD decay extent, and the number and length of haplotype blocks in the populations and to elaborate the first LD map for maize, for elucidating if the maize chromosomes also had a pattern of interspaced regions of high and low rates of recombination. We used a biparental temperate population, a tropical synthetic, and a tropical breeding population, genotyped for approximately 75,000 SNPs. The level of LD expressed by the r2 values is surprisingly low (0.02, 0.04, and 0.04), but comparable to some non-isolated human populations. The general evidence is that the synthetic is the population with higher LD. It is not expected a significant advantage of haplotype-based association study and along generations genomic selection due to the reduced number of SNPs in the haplotype blocks (2 to 3). The results concerning LD decay (rapid decay after 5-10 kb) and LD decay extent (along up to 300 kb) are in the range observed with maize inbred line panels. Our most important result is that maize chromosomes had a pattern of regions of extensive LD interspaced with regions of low LD. However, our simple simulated LD map provides evidence that this pattern can reflect regions with differences of allele frequencies and LD level (expressed by D) and not regions with high and low rates of recombination.

genetics↗