New insights into the codon usage patterns of the bactericidal/permeability-increasing (BPI) gene across nine species

Bactericidal/Permeability-Increasing Protein Improves Cognitive Impairment in Diabetic Mice via Blockade of the LPS-LBP-TLR4 Signaling Pathway

Emerging evidence suggests that the bactericidal/permeability-increasing protein (BPI) is involved in the process of cognitive impairment in diabetes. However, its underlying mechanism remains elusive. In this study, we found that BPI affects cognitive impairment due to diabetes through the lipopolysaccharide (LPS)-lipopolysacharide-binding protein (LBP)-toll-like receptor 4 (TLR4) signaling pathway. We examined the expression of BPI, LPS, LBP, CD14, and TLR4 in established mouse models of diabetes induced by high-fat diet (HFD) in combination with streptozotocin (STZ). Diabetic mice were then injected with adeno-associated-virus carrying BPI overexpression vectors and LPS. Fasting blood glucose, plasma insulin, and serum levels of inflammatory factors were examined. Then, glucose tolerance and, insulin resistance tests were used to measure systemic insulin sensitivity. Next, hippocampal tissue injury and cell apoptosis were examined by hematoxylin-eosin (HE) and terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling (TUNEL) staining. Diabetic mice displayed increased LPS expression and activation of the LPS-CD14-TLR4 signaling pathway. HFD mice following LPS treatment showed significantly increased serum levels of tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, and IL-6, and expressions of Bcl-2-associated X protein (Bax) and Aβ but decreased expression of Bcl-2 in hippocampal tissues, as well as enhanced fasting blood glucose, plasma insulin, glucose tolerance, insulin tolerance, cell apoptosis, aggravated hippocampal tissue injury and, ultimately, cognitive impairment. However, overexpression of BPI was able to rescue the aforementioned phenotypes driven by LPS treatment. Taken together, BPI could potentially provide relief from cognitive impairment in diabetic mice by disrupting the LPS-LBP-TLR4 signaling pathway, underscoring a possible alternative therapeutic strategy against the cognitive impairment associated with diabetes.

Amino acid compositions contribute to the proteins' evolution under the influence of their abundances and genomic GC content

Inconsistent results on the association between evolutionary rates and amino acid composition of proteins have been reported in eukaryotes. However, there are few studies of how amino acid composition can influence evolutionary rates in bacteria. Thus, we constructed linear regression models between composition frequencies of amino acids and evolutionary rates for bacteria. Compositions of all amino acids can on average explain 21.5% of the variation in evolutionary rates among 273 investigated bacterial organisms. In five model organisms, amino acid composition contributes more to variation in evolutionary rates than protein abundance, and frequency of optimal codons. The contribution of individual amino acid composition to evolutionary rate varies among organisms. The closer the GC-content of genome to its maximum or minimum, the better the correlation between the amino acid content and the evolutionary rate of proteins would appear in that genome. The types of amino acids that significantly contribute to evolutionary rates can be grouped into GC-rich and AT-rich amino acids. Besides, the amino acid with high composition also contributes more to evolutionary rates than amino acid with low composition in proteome. In summary, amino acid composition significantly contributes to the rate of evolution in bacterial organisms and this in turn is impacted by GC-content.