Association of ACACB gene polymorphism (rs2268388, G > A) with type 2 diabetes and end stage renal disease in Pakistani Punjabi population

Discovery of Bacterial Key Genes from 16S rRNA-Seq Profiles That Are Associated with the Complications of SARS-CoV-2 Infections and Provide Therapeutic Indications

SARS-CoV-2 infections, commonly referred to as COVID-19, remain a critical risk to both human life and global economies. Particularly, COVID-19 patients with weak immunity may suffer from different complications due to the bacterial co-infections/super-infections/secondary infections. Therefore, different variants of alternative antibacterial therapeutic agents are required to inhibit those infection-causing drug-resistant pathogenic bacteria. This study attempted to explore these bacterial pathogens and their inhibitors by using integrated statistical and bioinformatics approaches. By analyzing bacterial 16S rRNA sequence profiles, at first, we detected five bacterial genera and taxa (Bacteroides, Parabacteroides, Prevotella Clostridium, Atopobium, and Peptostreptococcus) based on differentially abundant bacteria between SARS-CoV-2 infection and control samples that are significantly enriched in 23 metabolic pathways. A total of 183 bacterial genes were found in the enriched pathways. Then, the top-ranked 10 bacterial genes (accB, ftsB, glyQ, hldD, lpxC, lptD, mlaA, ppsA, ppc, and tamB) were selected as the pathogenic bacterial key genes (bKGs) by their protein-protein interaction (PPI) network analysis. Then, we detected bKG-guided top-ranked eight drug molecules (Bemcentinib, Ledipasvir, Velpatasvir, Tirilazad, Acetyldigitoxin, Entreatinib, Digitoxin, and Elbasvir) by molecular docking. Finally, the binding stability of the top-ranked three drug molecules (Bemcentinib, Ledipasvir, and Velpatasvir) against three receptors (hldD, mlaA, and lptD) was investigated by computing their binding free energies with molecular dynamic (MD) simulation-based MM-PBSA techniques, respectively, and was found to be stable. Therefore, the findings of this study could be useful resources for developing a proper treatment plan against bacterial co-/super-/secondary-infection in SARS-CoV-2 infections.

Variation in Acetyl-CoA Carboxylase Beta Gene and Its Effect on Carcass and Meat Traits in Gannan Yaks

Acetyl-CoA carboxylase beta (ACACB) is a functional candidate gene that impacts fat deposition. In the present study, we sequenced exon 37-intron 37, exon 46-intron 46, and intron 47 of yak ACACB using hybrid pool sequencing to search for variants and genotyped the gene in 593 Gannan yaks via Kompetitive allele-specific polymerase chain (KASP) reaction to determine the effect of ACACB variants on carcass and meat quality traits. Seven single nucleotide polymorphisms were detected in three regions. Eight effective haplotypes and ten diplotypes were constructed. Among them, a missense variation g.50421 A > G was identified in exon 37 of ACACB, resulting in an amino acid shift from serine to glycine. Correlation analysis revealed that this variation was associated with the cooking loss rate and yak carcass weight (p = 0.024 and 0.012, respectively). The presence of haplotypes H5 and H6 decreased Warner-Bratzler shear force (p = 0.049 and 0.006, respectively), whereas that of haplotypes H3 and H4 increased cooking loss rate and eye muscle area (p = 0.004 and 0.034, respectively). Moreover, the presence of haplotype H8 decreased the drip loss rate (p = 0.019). The presence of one and two copies of haplotypes H1 and H8 decreased the drip loss rate (p = 0.028 and 0.004, respectively). However, haplotype H1 did not decrease hot carcass weight (p = 0.011), whereas H3 increased the cooking loss rate (p = 0.007). The presence of one and two copies of haplotype H6 decreased Warner-Bratzler shear force (p = 0.014). The findings of the present study suggest that genetic variations in ACACB can be a preferable biomarker for improving yak meat quality.

A systematic analysis of natural α-glucosidase inhibitors from flavonoids of Radix scutellariae using ultrafiltration UPLC-TripleTOF-MS/MS and network pharmacology

BACKGROUND

Flavonoids from plant medicines are supposed to be viable alternatives for the treatment of type 2 diabetes (T2D) as less toxicity and side effects. Radix scutellariae (RS) is a widely used traditional medicine in Asia. It has shown great potential in the research of T2D. However, the pharmacological actions remain obscured due to the complex chemical nature of plant medicines.

METHODS

In the present study, a systematic method combining ultrafiltration UPLC-TripleTOF-MS/MS and network pharmacology was developed to screen α-glucosidase inhibitors from flavonoids of RS, and explore the underlying mechanism for the treatment of T2D.

RESULTS

The n-butanol part of ethanol extract from RS showed a strong α-glucosidase inhibition activity (90.55%, IC50 0.551 mg/mL) against positive control acarbose (90.59%, IC50 1.079 mg/mL). A total of 32 kinds of flavonoids were identified from the extract, and their ESI-MS/MS behaviors were elucidated. Thirteen compounds were screened as α-glucosidase inhibitors, including viscidulin III, 2',3,5,6',7-pentahydroxyflavanone, and so on. A compound-target-pathway (CTP) network was constructed by integrating these α-glucosidase inhibitors, target proteins, and related pathways. This network exhibited an uneven distribution and approximate scale-free property. Chrysin (k = 87), 5,8,2'-trihydroxy-7-methoxyflavone (k = 21) and wogonin (k = 20) were selected as the main active constituents with much higher degree values. A protein-protein interaction (PPI) weighted network was built for target proteins of these α-glucosidase inhibitors and drug targets of T2D. PPARG (Cd = 0.165, Cb = 0.232, Cc = 0.401), ACACB (Cd = 0.155, Cb = 0.184, Cc = 0.318), NFKB1 (Cd = 0.233, Cb = 0.161, Cc = 0.431), and PGH2 (Cd = 0.194, Cb = 0.157, Cc = 0.427) exhibited as key targets with the highest scores of centrality indices. Furthermore, a core subnetwork was extracted from the CTP and PPI weighted network. Type II diabetes mellitus (hsa04930) and PPAR signaling pathway (hsa03320) were confirmed as the critical pathways.

CONCLUSIONS

These results improved current understanding of natural flavonoids on the treatment of T2D. The combination of ultrafiltration UPLC-TripleTOF-MS/MS and network pharmacology provides a novel strategy for the research of plant medicines and complex diseases.

Genome-wide association studies of albuminuria: towards genetic stratification in diabetes?

Genome-wide association studies (GWAS) have been very successful in unraveling the polygenic structure of several complex diseases and traits. In the case of albuminuria, despite the large sample size achieved by some studies, results look sparse with a limited number of loci reported so far. This review searched for GWAS studies of albumin excretion, albuminuria, and proteinuria. The resulting picture sets elements of uniqueness for albuminuria GWAS with respect to other complex traits. So far, very few loci associated with albuminuria have been validated by means of genome-wide significant evidence or formal replication. With rare exceptions, the validated loci are ethnicity specific. Within a given ethnicity, variants are common and have relatively large effects, especially in the presence of diabetes. In most cases, the identified variants were functional and a biological involvement of the target genes in renal damage was established. Recently reported variants associated with albuminuria in diabetes may be potentially combined into a genetic risk score, making it possible to rank diabetic patients by increasing risk of albuminuria. Validation of this model is required. To expand the understanding of the biological basis of albumin excretion regulation, future initiatives should achieve larger sample sizes and favor a transethnic study design.