Biology subjects

Lima, D.

Publications and source records attributed to Lima, D..

6 recordsLinked to original sources

bioRxiv2026

Genetic Diversity of Cytochrome P450 Genes in Apis mellifera Subspecies

The western honey bee (Apis mellifera) is an essential pollinator facing unprecedented threats from pesticide exposure. While pesticide resistance evolution is well documented in agricultural pests, our understanding of genetic variation in honey bee detoxification systems remains limited. This represents a missed opportunity, as harnessing naturally occurring detoxification diversity could provide new avenues for pollinator protection. Cytochrome P450 monooxygenases (CYPs), which are central to xenobiotic metabolism, offer a promising starting point. Here, we present the first comprehensive analysis of CYP genetic diversity in A. mellifera. We analysed the CYPome of 1,467 individuals representing 18 A. mellifera subspecies from 25 countries and identified 5,756 single-nucleotide polymorphisms (SNPs) in 46 CYP genes. Imputed McDonald-Kreitman testing revealed that 56% of non-synonymous CYP substitutions were driven by positive selection. Of the 1,302 haplotypes identified, 84% resided in CYP3, concentrated in the CYP9 and CYP6AS subfamilies implicated in xenobiotic detoxification. Population-level analysis of nucleotide diversity, Tajimas D selection signatures, FST-based differentiation, and McDonald-Kreitman testing pointed to CYP3 clan genes as the primary locus of adaptive variation. This work provides the first step toward building a comprehensive pharmacogenomic resource for honey bees, enabling the prediction of population-specific pesticide vulnerabilities and leveraging naturally occurring detoxification variants to enhance pollinator resilience - a critical step toward sustainable pollinator management.

genomics↗

bioRxiv2024

WHO WINS? COMPARISON BETWEEN EMERGENT MACROPHYTES AND PONTEDERIA CRASSIPES (WATER HYACINTH) AS NATURE-BASED SOLUTIONS FOR NUTRIENT PHYTOREMEDIATION AND CYANOBACTERIA MITIGATION

AO_SCPLOWBSTRACTC_SCPLOWEmergent macrophytes are commonly used to control eutrophication in Constructed Floating Wetlands (CFW) systems. However, tropical emergent macrophyte species, particularly from South America, are underrepresented in these applications. This study aims to investigate the potential of five emergent macrophytes, Alternanthera philoxeroides, Ludwigia leptocarpa, Polygonum ferrugineum, Typha domingensis, and Urochloa mutica in controlling eutrophication and inhibiting cyanobacterial growth, compared to the floating macrophyte Pontederia crassipes, the most studied macrophyte for this purpose. Phytoremediation experiments were performed ex-situ in mesocosms (50 L) with high soluble reactive phosphorus (SRP) concentration (400 {micro}g L-1). Allelopathic effects of the macrophytes root exudates on cyanobacteria were tested in vitro using a strain of Microcystis aeruginosa. While P. crassipes reduced SRP concentration by 86% in 14 days, the tested macrophytes reduced SRP concentration by > 94%, except for T. domingensis, which showed a reduction of 64%. NH4+ and NO3- removal in 14 days were 96% and 62%, respectively, for P. crassipes. These values corresponded to 96% and 63% for the five tested macrophytes. Root exudates of A. philoxeroides, L. leptocarpa, and P. ferrugineum caused inhibition of M. aeruginosa growth with no detection of Chl-a after 7 days. Thus, three emergent macrophytes were more efficient in removing nutrients than P. crassipes. and showed allelopathic potential against cyanobacteria, indicating that using local emergent macrophytes in CFW systems can be a valuable and sustainable tool to mitigate eutrophication and its consequences in aquatic environments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/603719v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@e09e31org.highwire.dtl.DTLVardef@b1d4a7org.highwire.dtl.DTLVardef@1003e0borg.highwire.dtl.DTLVardef@e97e22_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIEmergent macrophytes were similarly efficient to P. crassipes in nutrient removal C_LIO_LILudwigia leptocarpa was the most efficient in SRP removal in 7 days C_LIO_LIAllelopathy on cyanobacterium M. aeruginosa by A. philoxeroides, L. leptocarpa, and P. ferrugineum root exudates C_LIO_LIAdapting emergent macrophytes in CFW structures can be helpful in in situ phytoremediation. C_LI SO_SCPLOWTATEMENTC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWOFC_SCPLOW NO_SCPLOWOVELTYC_SCPLOWThis study lies in its comparative analysis of underrepresented tropical emergent macrophytes from South America against the widely studied floating macrophyte, Pontederia crassipes (water hyacinth). By focusing on these local emergent macrophytes, the research addresses a significant knowledge gap. It provides insights into their potential application in Constructed Floating Wetlands (CFWs) for nutrient removal and cyanobacteria control. Key findings demonstrate that the selected emergent macrophytes outperform P. crassipes in reducing soluble reactive phosphorus (SRP) concentrations and exhibit substantial nitrogen removal efficiencies. Furthermore, the allelopathic potential of A. philoxeroides, L. leptocarpa, and P. ferrugineum against the harmful cyanobacterium Microcystis aeruginosa showcases their dual functionality in mitigating eutrophication and inhibiting harmful algal blooms.

ecology↗

bioRxiv2023

MetFinder: a neural network-based tool for automated quantitation of metastatic burden in histological sections from animal models

Diagnosis of most diseases relies on expert histopathological evaluation of tissue sections by an experienced pathologist. By using standardized staining techniques and an expanding repertoire of markers, a trained eye is able to recognize disease-specific patterns with high accuracy and determine a diagnosis. As efforts to study mechanisms of metastasis and novel therapeutic approaches multiply, researchers need accurate, high-throughput methods to evaluate effects on tumor burden resulting from specific interventions. However, current methods of quantifying tumor burden are low in either resolution or throughput. Artificial neural networks, which can perform in-depth image analyses of tissue sections, provide an opportunity for automated recognition of consistent histopathological patterns. In order to increase the outflow of data collection from preclinical studies, we trained a deep neural network for quantitative analysis of melanoma tumor content on histopathological sections of murine models. This AI-based algorithm, made freely available to academic labs through a web-interface called MetFinder, promises to become an asset for researchers and pathologists interested in accurate, quantitative assessment of metastasis burden.

cancer biology↗

bioRxiv2021

iEC7871 Quercus suber model: the first multi-tissue diel cycle genome-scale metabolic model of a woody tree

In the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behavior at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871), the first of a woody plant. The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyze the pathways associated with the synthesis of suberin monomers. Nevertheless, the models developed in this work can provide insights into other aspects of the metabolism of Q. suber, such as its secondary metabolism and cork formation.

systems biology↗

bioRxiv2021

merlin v4.0: an updated platform for the reconstruction of high-quality genome-scale metabolic models

Genome-scale metabolic models have been recognised as useful tools for better understanding living organisms metabolism. merlin (https://www.merlin-sysbio.org/) is an open-source and user-friendly resource that hastens the models reconstruction process, conjugating manual and automatic procedures, while leveraging the users expertise with a curation-oriented graphical interface. An updated and redesigned version of merlin is herein presented. Since 2015, several features have been implemented in merlin, along with deep changes in the software architecture, operational flow, and graphical interface. The current version (4.0) includes the implementation of novel algorithms and third-party tools for genome functional annotation, draft assembly, model refinement, and curation. Such updates increased the user base, resulting in multiple published works, including genome metabolic (re-)annotations and model reconstructions of multiple (lower and higher) eukaryotes and prokaryotes. merlin version 4.0 is the only tool able to perform template based and non-template based draft reconstructions, while achieving competitive performance compared to state-of-the art tools both for well and less-studied organisms.

bioinformatics↗

bioRxiv2019

Effects of moderate and high intensity isocaloric aerobic training upon microvascular reactivity and myocardial oxidative stress in rats

Systemic and central cardiovascular adaptations may vary in response to chronic exercise performed with different intensities and volumes. This study compared the effects of aerobic training with different intensities but equivalent volume upon microvascular reactivity in cremaster muscle and myocardial biomarkers of oxidative stress in Wistar rats. After peak oxygen uptake (VO2peak) assessment, rats (n=24) were assigned into three groups: moderate-intensity exercise training (MI); high-intensity exercise training (HI); sedentary control (SC). Treadmill training occurred during 4 weeks, with exercise bouts matched by the energy expenditure (3.0-3.5 Kcal). Microvascular reactivity was assessed in vivo by intravital microscopy in cremaster muscle arterioles, while biomarkers of oxidative stress and eNOS expression were quantified at left ventricle and at aorta, respectively. Similar increasing vs. sedentary control group (SC) occurred in moderate intensity training group (MI) and high-intensity training group (HI) for endothelium-dependent vasodilation (10-4M: MI: 168.7%, HI: 164.6% vs. SC: 146.6%, P=0.0004). Superoxide dismutase (SOD) (HI: 0.13 U/mg vs. MI: 0.09 U/mg and SC: 0.06 U/mg; P=0.02), glutathione peroxidase (GPX) (HI: 0.00038 U/mg vs. MI: 0.00034 U/mg and SC: 0.00024 U/mg; P=0.04), and carbonyl protein content (HI: 0.04 U/mg vs. MI: 0.03 U/mg and SC: 0.01 U/mg; P=0.003) increased only in HI. No difference across groups was detected for catalase (CAT) (P=0.12), Thiobarbituric acid reactive substances (TBARS) (P = 0.38) or eNOS expression in aorta (P=0.44). In conclusion, higher exercise intensity induced greater improvements in myocardium antioxidant defenses, while gains in microvascular reactivity appeared to rely more on exercise volume than intensity.

physiology↗