Impact of innovative nanoadditives on biodigesters microbiome

Abstract

Nanoparticles (NPs) supplementation to biodigesters improves the digestibility of biowaste and the generation of biogas. This study investigates the impact of innovative nanoadditives on the microbiome of biodigesters. Fresh cow manure was anaerobically incubated in a water bath under mesophilic conditions for 30 days. Three different NPs (zinc ferrite, zinc ferrite with 10% carbon nanotubes and zinc ferrite with 10% C76 fullerene) were separately supplemented to the biodigesters at the beginning of the incubation period. Methane and hydrogen production were monitored daily. Manure samples were collected from the digesters at different time points and the microbial communities inside the biodigesters were investigated via real‐time PCR and 16 S rRNA gene amplicon‐sequencing. The results indicate that zinc ferrite NPs enhanced biogas production the most. The microbial community was significantly affected by NPs addition in terms of archaeal and bacterial 16 S rRNAgene copy numbers. The three ZF formulations NPs augmented the abundance of members within the hydrogenotrophic methanogenic phyla Methanobacteriaceae. While Methanomassiliicoccacaea were enriched in ZF/C76 supplemented biodigester due to a significant increase in hydrogen partial pressure, probably caused by the enrichment of Spirochaetaceae (genus Treponema). Overall, NPs supplementation significantly enriched acetate‐producing members within Hungateiclostridiaceae in ZF/CNTs, Dysgonomonadaceae in ZF and Spirochaetaceae ZF/C76 biodigesters.

Patterned PCL/PGS Nanofibrous Hyaluronic Acid-Coated Scaffolds Promote Cellular Response and Modulate Gene Expression Profiles

“…Additionally, principal component analysis (PCA) was performed on the data, which was transformed using the regularized logarithm approach within the DESeq2 package. 27 To identify enriched gene sets from the normalized count data, a gene set enrichment analysis was performed. Functional enrichment against the GO was carried out using clusterProfiler.…”

“…Genes were categorized as differentially expressed if they had an FDR-adjusted P-value below 0.05 and exhibited a fold change of greater than 2 or less than 0.5. Additionally, principal component analysis (PCA) was performed on the data, which was transformed using the regularized logarithm approach within the DESeq2 package . To identify enriched gene sets from the normalized count data, a gene set enrichment analysis was performed.…”