Sex-specific vulnerabilities in human astrocytes underpin the differential impact of palmitic acid.

Obesity and neurometabolic diseases have been linked to neurodegenerative diseases. Our hypothesis is that the endogenous estrogenic component of human astrocytes plays a critical role in cell response during lipotoxic damage, given that obesity can disrupt hormonal homeostasis and cause brain inflammation. Our findings showed that high concentrations of palmitic acid (PA) significantly reduced cell viability more in male astrocytes, indicating sex-specific vulnerabilities. PA induced a greater increase in cytosolic reactive oxygen species (ROS) production in males, while female astrocytes exhibited higher superoxide ion levels in mitochondria. In addition, female astrocytes treated with PA showed increased expression of antioxidant proteins, including catalase, Gpx-1 and Nrf2 suggesting a stronger cellular defence mechanism. Interestingly, there was a difference in the expression of estrogenic components, such as estrogen, androgens, and progesterone receptors, as well as aromatase and 5α-reductase enzymes, between males and females. PA induced their expression mainly in females, indicating a potential protective mechanism mediated by endogenous hormones. In summary, our findings highlight the impact of sex on the response of human astrocytes to lipotoxicity. Male astrocytes appear to be more susceptible to cellular damage when exposed to high concentrations of fatty acids.

Changes in Bacterial Gut Composition in Parkinson's Disease and Their Metabolic Contribution to Disease Development: A Gut Community Reconstruction Approach.

Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease with the major symptoms comprising loss of movement coordination (motor dysfunction) and non-motor dysfunction, including gastrointestinal symptoms. Alterations in the gut microbiota composition have been reported in PD patients vs. controls. However, it is still unclear how these compositional changes contribute to disease etiology and progression. Furthermore, most of the available studies have focused on European, Asian, and North American cohorts, but the microbiomes of PD patients in Latin America have not been characterized. To address this problem, we obtained fecal samples from Colombian participants (n = 25 controls, n = 25 PD idiopathic cases) to characterize the taxonomical community changes during disease via 16S rRNA gene sequencing. An analysis of differential composition, diversity, and personalized computational modeling was carried out, given the fecal bacterial composition and diet of each participant. We found three metabolites that differed in dietary habits between PD patients and controls: carbohydrates, trans fatty acids, and potassium. We identified six genera that changed significantly in their relative abundance between PD patients and controls, belonging to the families Lachnospiraceae, Lactobacillaceae, Verrucomicrobioaceae, Peptostreptococcaceae, and Streptococcaceae. Furthermore, personalized metabolic modeling of the gut microbiome revealed changes in the predicted production of seven metabolites (Indole, tryptophan, fructose, phenylacetic acid, myristic acid, 3-Methyl-2-oxovaleric acid, and N-Acetylneuraminic acid). These metabolites are associated with the metabolism of aromatic amino acids and their consumption in the diet. Therefore, this research suggests that each individual's diet and intestinal composition could affect host metabolism. Furthermore, these findings open the door to the study of microbiome-host interactions and allow us to contribute to personalized medicine.

Association between VDR Gene Polymorphisms and Melanoma Susceptibility in a Colombian Population.

BACKGROUND: The vitamin D receptor (VDR) is responsible for mediating the effects of vitamin D through regulation of other gene transcriptions. There are several polymorphisms that alter the gene expression or the function of this protein. We aimed to analyze the association between two SNPs  of VDR gene and melanoma cancer in Colombian patients. METHODS: We included 120 healthy individual as controls and 120 melanoma cancer patients as cases . Patients in both groups were matched in terms of gender and age. The genotyping of rs731236 and rs2228570 polymorphisms was performed using PCR-RFLP. The SNPStats program was used to carry out the statistical analysis through a logistic regression model. RESULTS: Under dominant model, we found that rs2228570 polymorphism was associated with melanoma cancer risk (C/C vs C/T-T/T, OR: 5.10, 95% CI: 2.85-9.14), whereas rs731236 polymorphism was associated with a protective effect against this cancer (T/T vs T/C, OR: 0.27, 95% CI: 0.14-0.53). CONCLUSION: Our results suggested that both polymorphisms were involved in the development of melanoma cancer, increasing or decreasing this risk.

Metabolomic Analysis of Human Astrocytes in Lipotoxic Condition: Potential Biomarker Identification by Machine Learning Modeling.

The association between neurodegenerative diseases (NDs) and obesity has been well studied in recent years. Obesity is a syndrome of multifactorial etiology characterized by an excessive accumulation and release of fatty acids (FA) in adipose and non-adipose tissue. An excess of FA generates a metabolic condition known as lipotoxicity, which triggers pathological cellular and molecular responses, causing dysregulation of homeostasis and a decrease in cell viability. This condition is a hallmark of NDs, and astrocytes are particularly sensitive to it, given their crucial role in energy production and oxidative stress management in the brain. However, analyzing cellular mechanisms associated with these conditions represents a challenge. In this regard, metabolomics is an approach that allows biochemical analysis from the comprehensive perspective of cell physiology. This technique allows cellular metabolic profiles to be determined in different biological contexts, such as those of NDs and specific metabolic insults, including lipotoxicity. Since data provided by metabolomics can be complex and difficult to interpret, alternative data analysis techniques such as machine learning (ML) have grown exponentially in areas related to omics data. Here, we developed an ML model yielding a 93% area under the receiving operating characteristic (ROC) curve, with sensibility and specificity values of 80% and 93%, respectively. This study aimed to analyze the metabolomic profiles of human astrocytes under lipotoxic conditions to provide powerful insights, such as potential biomarkers for scenarios of lipotoxicity induced by palmitic acid (PA). In this work, we propose that dysregulation in seleno-amino acid metabolism, urea cycle, and glutamate metabolism pathways are major triggers in astrocyte lipotoxic scenarios, while increased metabolites such as alanine, adenosine, and glutamate are suggested as potential biomarkers, which, to our knowledge, have not been identified in human astrocytes and are proposed as candidates for further research and validation.

Anaerobic sulfatase maturase AslB from Escherichia coli activates human recombinant iduronate-2-sulfate sulfatase (IDS) and N-acetylgalactosamine-6-sulfate sulfatase (GALNS).

Maturation of type I sulfatases requires the conversion of the cysteine (Cys) or serine (Ser) present in the active site to formylglycine (FGly). This activation represents a limiting step during the production of recombinant sulfatases in bacteria and eukaryotic hosts. AslB, YdeM and YidF have been proposed to participate in the activation of sulfatases in Escherichia coli. In this study, we combined in-silico and experimental approaches to study the interaction between Escherichia coli BL21(DE3) AslB and human sulfatases, more specifically iduronate-2-sulfate sulfatase (IDS) and N-acetylgalactosamine-6-sulfate sulfatase (GALNS). In-silico results show that AslB has a higher affinity for the residual motif of GALNS (-9.4kcalmol-1), Cys- and Ser-type, than for the one of IDS (-8.0kcalmol-1). However, the distance between the AslB active residue and the target motif favors the interaction with IDS (4.4Å) more than with GALNS (5.5Å). Experimental observations supported in-silico results where the co-expression of AslB with GALNS Cys- and Ser-type presented an activity increment of 2.0- and 1.5-fold compared to the control cultures, lacking overexpressed AslB. Similarly, IDS activity was increased in 4.6-fold when co-expressed with AslB. The higher sulfatase activity of AslB-IDS suggests that the distance between the AslB active residue and the motif target is a key parameter for the in-silico search of potential sulfatase activators. In conclusion, our results suggest that AslB is involve in the maturation of heterologous human sulfatases in E. coli BL21(DE3), and that it can have important implications in the production of recombinant sulfatases for therapeutic purposes and research.

"In Silico" Characterization of 3-Phytase A and 3-Phytase B from Aspergillus niger.

Phytases are used for feeding monogastric animals, because they hydrolyze phytic acid generating inorganic phosphate. Aspergillus niger 3-phytase A (PDB: 3K4Q) and 3-phytase B (PDB: 1QFX) were characterized using bioinformatic tools. Results showed that both enzymes have highly conserved catalytic pockets, supporting their classification as histidine acid phosphatases. 2D structures consist of 43% alpha-helix, 12% beta-sheet, and 45% others and 38% alpha-helix, 12% beta-sheet, and 50% others, respectively, and pI 4.94 and 4.60, aliphatic index 72.25 and 70.26 and average hydrophobicity of -0,304 and -0.330, respectively, suggesting aqueous media interaction. Glycosylation and glycation sites allowed detecting zones that can affect folding and biological activity, suggesting fragmentation. Docking showed that H59 and H63 act as nucleophiles and that D339 and D319 are proton donor residues. MW of 3K4Q (48.84 kDa) and 1QFX (50.78 kDa) is similar; 1QFX forms homodimers which will originate homotetramers with several catalytic center accessible to the ligand. 3K4Q is less stable (instability index 45.41) than 1QFX (instability index 33.66), but the estimated lifespan for 3K4Q is superior. Van der Waals interactions generate hydrogen bonds between the active center and O2 or H of the phytic acid phosphate groups, providing greater stability to these temporal molecular interactions.

Proteína LIC10494 de Leptospira interrogans serovar Copenhageni: modelo estructural y regiones funcionales asociadas / Protein LIC10494 of Leptospira interrogans serovar Copenhageni: structural model and associated functional regions / Proteína LIC10494 de Leptospira interrogans serovar Copenhageni: modelo estrutural e regiões funcionais associadas

Objetivo. Predecir computacionalmente la estructura tridimensional de la proteína antigénica LIC10494 e inferir las regiones funcionales asociadas importantes para su antigenicidad e inmunogenicidad. Materiales y métodos. Se realizó un análisis computacional de la estructura primaria de LIC10494 a partir de los servidores BLAST, PROTPARAM, PROTSCALE, DAS, SOSUI, TOPPRED, TMAP, TMPRED, SPLIT4, PHDHTM, TMHMM2, HMMTOP2, GLOBPLOT y PROSITE. La estructura secundaria se obtuvo por consenso de los algoritmos SOPM, PREDATOR GOR4, DPM y DSC. La aproximación a la estructura terciaria se obtuvo con el algoritmo MUSTER. La minimización de energía se obtuvo a partir del campo de fuerza AMBER94 de la suite de análisis molecular SCHRODINGER, y la validación tanto estereoquímica como energética del modelo se realizó con el servidor RAMPAGE. El modelo final fue visualizado con el programa PyMol v.0,98. Resultados. En el presente estudio se propone un modelo computacional que detalla la estructura tridimensional de la lipoproteína hipotética LIC10494 y está de acuerdo con reportes experimentales previos; el estudio demuestra la existencia de patrones que podrían tener un papel importante en la patogenicidad y la protección de la bacteria frente al sistema inmune del hospedero; la presencia de una región desordenada entre los aminoácidos 80 y 140; y la presencia de un segmento transmembrana entre los aminoácidos 8 y 22. Conclusión. La coincidencia entre segmentos estructurales y funcionales sugiere que el modelo puede usarse para predecir ciertos aspectos del comportamiento biológico de la proteína en cuanto a la patogenicidad e inmunogenicidad de la bacteria.

Objective. Predict by computational means the 3D structure of the antigenic protein LIC10494 and report associated important functional regions for its pathogenicity and immunogenicity. Materials and methods. We performed a computational analysis of the primary structure of LIC10494 using the servers BLAST, PROTPARAM, PROTSCALE, DAS, SOSUI, TOPPRED, TMAP, TMpred, SPLIT4, PHDHTM, TMHMM2, HMMTOP2, GLOBPLOT and PROSITE. The secondary structure was obtained by consensus of the algorithms SOPM, PREDATOR GOR4, DPM and DSC. The approach to the tertiary structure was obtained using the algorithm MUSTER. The energy minimization was done using the AMBER94 force field of the Schrodinger suite of molecular analysis, and the stereochemistry and energy model validation was performed by the RAMPAGE server. The final model was visualized using PyMol V.0,98. Results. This study proposes a computational model that describes the 3D structure of the hypothetical lipoprotein LIC10494 and agrees with previous experimental reports; thus, our study demonstrates the existence of patterns that could play an important role in the pathogenicity and protection of the bacteria against the host immune system; the presence of a disorganized region between amino acids 80 and 140, and of a transmembrane segment between amino acids 8 and 22. Conclusion. The coincidence between structural and functional segments suggests that our model can be used to predict certain aspects of the biological behaviour of the protein according to the pathogenic and immunogenic characteristics of the bacteria.

Objetivo. Predizer computacionalmente a estrutura tridimensional da proteína antigênica LIC10494 e inferir as regiões funcionais associadas importantes para a sua antigenicidade e imunogenicidade. Materiais e métodos. Foi realizada uma análise computacional da estrutura primária da LIC10494 nos servidores, BLAST, PROTPARAM, PROTSCALE, DAS, SOSUI, TOPPRED, TMAP, TMPRED, SPLIT4, PHDHTM, TMHMM2, HMMTOP2, GLOBPLOT e PROSITE. A estrutura secundária foi obtida por consenso dos algoritmos SOPM, PREDATOR GOR4, DPM e DSC. A aproximação para a estrutura terciária foi obtida com o algoritmo MUSTER. A minimização de energia foi obtida a partir do campo de força AMBER94 do conjunto de análise molecular SCHRODINGER, e a validação estereoquímica e energética do modelo foi realizada utilizando o servidor RAMPAGE. O modelo final foi visualizado com o programa PyMol V. 0,98. Resultados. Este estudo propõe um modelo computacional que descreve a estrutura tridimensional da lipoproteína hipotética LIC10494 e concorda com anteriores relatórios experimental; o estudo demonstra a existência de padrões que poderiam desempenhar um papel importante na patogenicidade e na proteção da bactéria ao sistema imune do hospedeiro; a presença de uma região desordenada entre os aminoácidos 80 e 140, e a presença de um segmento transmembrana entre os aminoácidos 8 e 22. Conclusão. A coincidência entre os segmentos estruturais e funcionais sugere que o modelo pode ser utilizado para prever determinados aspectos do comportamento biológico da proteína na patogenicidade e imunogenicidade da bactéria.