Comparison of culture-independent and dependent approaches for identification of native arsenic-resistant bacteria and their potential use for arsenic bioremediation

Abstract

Arsenic is a common contaminant in gold mine soil and tailings. Microbes present an opportunity for bio-treatment of arsenic, since it is a sustainable and cost-effective approach to remove arsenic from water. However, the development of existing bio-treatment approaches depends on isolation of arsenic-resistant microbes from arsenic contaminated samples. Microbial cultures are commonly used in bio-treatment; however, it is not established whether the structure of the cultured isolates resembles the native microbial community from arsenic-contaminated soil. In this milieu, a culture-independent approach using Illumina sequencing technology was used to profile the microbial community in situ. This was coupled with a culture-dependent technique, that is, isolation using two different growth media, to analyse the microbial population in arsenic laden tailing dam sludge based on the culture-independent sequencing approach, 4 phyla and 8 genera were identified in a sample from the arsenic-rich gold mine. Firmicutes (92.23%) was the dominant phylum, followed by Proteobacteria (3.21%), Actinobacteria (2.41%), and Bacteroidetes (1.49%). The identified genera included Staphylococcus (89.8%), Pseudomonas (1.25), Corynebacterium (0.82), Prevotella (0.54%), Megamonas (0.38%) and Sphingomonas (0.36%). The Shannon index value (3.05) and Simpson index value (0.1661) indicated low diversity in arsenic laden tailing. The culture dependent method exposed significant similarities with culture independent methods at the phylum level with Firmicutes, Proteobacteria and Actinobacteria, being common, and Firmicutes was the dominant phylum whereas, at the genus level, only Pseudomonas was presented by both methods. It showed high similarities between culture independent and dependent methods at the phylum level and large differences at the genus level, highlighting the complementarity between the two methods for identification of the native population bacteria in arsenic-rich mine. As a result, the present study can be a resource on microbes for bio-treatment of arsenic in mining waste.