Conformational Study of Human Serum Albumin in Pre-denaturation Temperatures by Differential Scanning Calorimetry, Circular Dichroism and UV Spectroscopy Circular dichroism;Conformational changes;Differential scanning microcalorimetry;HSA;Sodium dodecyl sulphate; Thermal conformational changes of human serum albumin (HSA) in phosphate buffer, 10 mM at pH = 7 are investigated using differential scanning calorimetric (DSC), circular dichroism (CD) and UV spectroscopic methods. The results indicate that temperature increment from $25^{\circ}C$ to $55^{\circ}C$ induces reversible conformational changes in the structure of HSA. Conformational change of HSA are shown to be a three-step process. Interestingly, melting temperature of the last domain is equal to the maximum value of fever in pathological conditions, i.e. $42^{\circ}C$. These conformational alterations are accompanied by a mild alteration of secondary structures. Study of HSA-SDS (sodium dodecyl sulphate) interaction at $45^{\circ}C$ and $35^{\circ}C$ reveals that SDS affects the HSA structure at least in three steps: the first two steps result in more stabilization and compactness of HSA structure, while the last one induces the unfolding of HSA. Since HSA has a more affinity for SDS at $45^{\circ}C$ compared to $35^{\circ}C$, It is suggested that the net negative charge of HSA is decreased in fever, which results in the decrease of HSA-associated cations and plasma osmolarity, and consequently, heat removal via the increase in urine volume.
24 March 2020 in Bioprocess and Biosystems Engineering
Neurodegenerative diseases (NDDs) are increasing serious menaces to human health in the recent years. Despite exhibiting different clinical phenotypes and selective neuronal loss, there are certain common features in these disorders, suggesting the presence of commonly dysregulated pathways. Identifying causal genes and dysregulated pathways can be helpful in providing effective treatment in these diseases. Interestingly, in spite of the considerable researches on NDDs, to the best of our knowledge, no dysregulated genes and/or pathways were reported in common across all the major NDDs so far. In this study, for the first time, we have applied the three-way interaction model, as an approach to unravel sophisticated gene interactions, to trace switch genes and significant pathways that are involved in six major NDDs. Subsequently, a gene regulatory network was constructed to investigate the regulatory communication of statistically significant triplets. Finally, KEGG pathway enrichment analysis was applied to find possible common pathways. Because of the central role of neuroinflammation and immune system responses in both pathogenic and protective mechanisms in the NDDs, we focused on immune genes in this study. Our results suggest that "cytokine-cytokine receptor interaction" pathway is enriched in all of the studied NDDs, while "osteoclast differentiation" and "natural killer cell mediated cytotoxicity" pathways are enriched in five of the NDDs each. The results of this study indicate that three pathways that include "osteoclast differentiation", "natural killer cell mediated cytotoxicity" and "cytokine-cytokine receptor interaction" are common in five, five and six NDDs, respectively. Additionally, our analysis showed that Rps27a as a switch gene, together with the gene pair {Il-18, Cx3cl1} form a statistically significant and biologically relevant triplet in the major NDDs. More specifically, we suggested that Cx3cl1 might act as a potential upstream regulator of Il-18 in microglia activation, and in turn, might be controlled with Rps27a in triggering NDDs.
Background: The problem of accurate prediction of protein secondary structure continues to be one of the challenging problems in Bioinformatics. It has been previously suggested that amino acid relative solvent accessibility (RSA) might be an effective factor for increasing the accuracy of protein secondary structure prediction. Previous studies have either used a single constant threshold to classify residues into discrete classes (buries vs. exposed), or used the real-value predicted RSAs in their prediction method.Results: We studied the effect of applying different RSA threshold types (namely, fixed thresholds vs. residue-dependent thresholds) on a variety of secondary structure prediction methods. With the consideration of DSSP-assigned RSA values we realized that improvement in the accuracy of prediction strictly depends on the selected threshold(s). Furthermore, we showed that choosing a single threshold for all amino acids is not the best possible parameter. We therefore used residue-dependent thresholds and most of residues showed improvement in prediction. Next, we tried to consider predicted RSA values, since in the real-world problem, protein sequence is the only available information. We first predicted the RSA classes by RVP-net program and then used these data in our method. Using this approach, improvement in prediction was also obtained.Conclusion: The success of applying the RSA information on different secondary structure prediction methods suggest that prediction accuracy can be improved independent of prediction approaches. Thus, solvent accessibility can be considered as a rich source of information to help the improvement of these methods.
13 January 2017 in Systems Biology in Reproductive Medicine
About 15% of couples experience difficulty in conceiving a child, of which half of the cases are thought to be male-related. Asthenozoospermia, or low sperm motility, is one of the frequent types of male infertility. Although energy metabolism is suggested to be central to the etiology of asthenozoospermia, very few attempts have been made to identify its underlying metabolic pathways. Here, we reconstructed SpermNet, the first proteome-scale model of the sperm cell by using whole-proteome data and the mCADRE algorithm. The reconstructed model was then analyzed using the COBRA toolbox. Genes were knocked-out in the model to investigate their effect on ATP production. A total of 78 genes elevated ATP production rate considerably of which most encode components of oxidative phosphorylation, fatty acid oxidation, the Krebs cycle, and members of the solute carrier 25 family. Among them, we identified 11 novel genes which have previously not been associated with sperm cell energy metabolism and may thus be implicated in asthenozoospermia. We further examined the reconstructed model by in silico knock out of currently known asthenozoospermia implicated-genes that were not predicted by our model. The pathways affected by knocking out these genes were also related to energy metabolism, confirming previous findings. Therefore, our model not only predicts the known pathways, it also identifies several non-glycolytic genes for deficient energy metabolism in asthenozoospermia. Finally, this model supports the notion that metabolic pathways besides glycolysis such as oxidative phosphorylation and fatty acid oxidation are essential for sperm energy metabolism and if validated, may form a basis for fertility recovery. Abbreviations: mCADRE: metabolic context-specificity assessed by deterministic reaction evaluation; ATP: adenosine triphosphate; RNA: ribonucleic acid; FBA: flux balance analysis; FVA: flux variability analysis; DAVID: database for annotation, visualization and integrated discovery; OXPHOS: oxidative phosphorylation; ETC: electron transfer chain; SLC: solute carrier; DLD: dihydrolypoamide dehydrogenase; DLST: dihydrolypoamide S-succinyl transferase; OGDH: oxoglutarate dehydrogenase; CS: citrate synthase; FH: fumarate hydratase; IDH: isocitrate dehydrogenase; SUCLG1: succinate-CoA ligase; SD: succinate dehydrogenase; HADHA: hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, subunit A; HADHB: hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, subunit B; PPA2: pyrophosphatase (inorganic) 2; PPi: inorganic phosphate; GALT: galactose-1-phosphate uridylyltransferase