Tapping uncultured microorganisms through metagenomics for drug discovery

Natural products have been an important historical source of therapeutic agents. Microorganisms are major source of bioactive natural products, and several microbial products including antibiotics, anti-inflammatory, anti-tumour, immunosuppressants and others are currently used as therapeutic agents for human and  domestic animals. Most of these products were obtained from cultured environmental microorganisms. However, it is widely accepted that a very large majority of the microorganisms present in natural  environments are not readily cultured under laboratory conditions, and therefore are not accessible for drug  discovery. Metagenomics is a recent culture-independent approach that has been developed to access the  collective genomes of natural bacterial populations. It enables discovery of the diverse biosynthetic pathways encoded by diverse microbial assemblages that are known to be present in the environment but not-yet  cultured. Recently, several new bioactive molecules and proteins have been discovered using a metagenomic approach. This review highlights the recent methodologies, limitations, and applications of metagenomics for the discovery of new drugs. Moreover, it shows how a multidisciplinary approach combining metagenomics with other technologies can expedite and revolutionize drug discovery from diverse environmental microorganisms.Key words: Microbial diversity, metagenomics, natural products, drug discovery, microbial ecology

Coinfections with bacteria, fungi, and respiratory viruses in patients with sars-cov-2: A systematic review and meta-analysis

Background: Coinfection with bacteria, fungi, and respiratory viruses in SARS-CoV-2 is of particular importance due to the possibility of increased morbidity and mortality. In this meta-analysis, we calculated the prevalence of such coinfections. Methods: Electronic databases were searched from 1 December 2019 to 31 March 2021. Effect sizes of prevalence were pooled with 95% confidence intervals (CIs). To minimize heterogeneity, we performed sub-group analyses. Results: Of the 6189 papers that were identified, 72 articles were included in the systematic review (40 case series and 32 cohort studies) and 68 articles (38 case series and 30 cohort studies) were included in the meta-analysis. Of the 31,953 SARS-CoV-2 patients included in the meta-analysis, the overall pooled proportion who had a laboratory-confirmed bacterial infection was 15.9% (95% CI 13.6–18.2, n = 1940, 49 studies, I2 = 99%, p \u3c 0.00001), while 3.7% (95% CI 2.6–4.8, n = 177, 16 studies, I2 = 93%, p \u3c 0.00001) had fungal infections and 6.6% (95% CI 5.5–7.6, n = 737, 44 studies, I2 = 96%, p \u3c 0.00001) had other respiratory viruses. SARS-CoV-2 patients in the ICU had higher co-infections compared to ICU and non-ICU patients as follows: bacterial (22.2%, 95% CI 16.1–28.4, I2 = 88% versus 14.8%, 95% CI 12.4–17.3, I2 = 99%), and fungal (9.6%, 95% CI 6.8–12.4, I2 = 74% versus 2.7%, 95% CI 0.0–3.8, I2 = 95%); however, there was an identical other respiratory viral co-infection proportion between all SARS-CoV-2 patients [(ICU and non-ICU) and the ICU only] (6.6%, 95% CI 0.0–11.3, I2 = 58% versus 6.6%, 95% CI 5.5–7.7, I2 = 96%). Funnel plots for possible publication bias for the pooled effect sizes of the prevalence of coinfections was asymmetrical on visual inspection, and Egger’s tests confirmed asymmetry (p values \u3c 0.05). Conclusion: Bacterial co-infection is relatively high in hospitalized patients with SARS-CoV-2, with little evidence of S. aureus playing a major role. Knowledge of the prevalence and type of co-infections in SARS-CoV-2 patients may have diagnostic and management implications