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

Md Kaderi Kibria; Md Ahad Ali; Muhammad Yaseen; Imran Ahmad Khan; Mashooq Ahmad Bhat; Md Ariful Islam; Rashidul Alam Mahumud; Md Nurul Haque Mollah

doi:10.3390/ph17040432

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

Pharmaceuticals (Basel). 2024 Mar 28;17(4):432. doi: 10.3390/ph17040432.

Authors

Md Kaderi Kibria^{1

2}, Md Ahad Ali^{1

3}, Muhammad Yaseen⁴, Imran Ahmad Khan⁵, Mashooq Ahmad Bhat⁶, Md Ariful Islam¹, Rashidul Alam Mahumud⁷, Md Nurul Haque Mollah¹

Affiliations

¹ Bioinformatics Laboratory, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh.
² Department of Statistics, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh.
³ Department of Chemistry, University of Rajshahi, Rajshahi 6205, Bangladesh.
⁴ Institute of Chemical Sciences, University of Swat, Main Campus, Charbagh 19130, Pakistan.
⁵ Department of Chemistry, Government College University, Faisalabad 38000, Pakistan.
⁶ Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh 11421, Saudi Arabia.
⁷ NHMRC Clinical Trials Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia.

Abstract

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.

Keywords: 16S rRNA-seq profiles; SARS-CoV-2 infections; bacterial co-infections; bacterial key genes (bKGs); bioinformatics analysis; drug repurposing.

Abstract

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