RESUMEN
This study aimed at molecular and biochemical characterization of low-density polyethene (LDPE) degrading fungi and bacteria from Dandora dumpsite, Nairobi. Twenty bacterial and 10 fungal isolates were identified using 16S rDNA and 18S rDNA sequences for bacteria and fungi, respectively. The highest fungal degradation was attributed to Aspergillus oryzae strain A5,1 while the highest bacterial degradation was attributed to Bacillus cereus strain A5,a and Brevibacillus borstelensis strain B2,2, respectively. Isolates were screened for their ability to produce extracellular laccase and esterase; Aspergillus fumigatus strain B2,2 exhibited the highest presence of laccase (15.67 mm) while Aspergillus oryzae strain A5,1 exhibited the highest presence of esterase (14.33 mm). Alkane hydroxylase-encoding genes were screened for using primer AlkB 1 which amplified the fragment of size 870 bp. Four bacterial samples were positive for the gene. Optimum growth temperature of the fungal isolates was 30°C. The possession of laccase, esterase, and alkane hydroxylase activities is suggested as key molecular basis for LDPE degrading capacity. Knowledge of optimum growth conditions will serve to better utilize microbes in the bioremediation of LDPE. The application of Aspergillus oryzae strain A5,1 and Bacillus cereus strain A5,a in polyethene degradation is a promising option in this kind of bioremediation as they exhibited significantly high levels of biodegradation. Further investigation of more alkane degrading genes in biodegrading microbes will inform the choice of the right microbial consortia for bioaugmentation strategies.
RESUMEN
BACKGROUND: Lake Magadi and little Magadi are hypersaline, alkaline lakes situated in the southern part of Kenyan Rift Valley. Solutes are supplied mainly by a series of alkaline hot springs with temperatures as high as 86 °C. Previous culture-dependent and culture-independent studies have revealed diverse groups of microorganisms thriving under these conditions. Previous culture independent studies were based on the analysis of 16S rDNA but were done on less saline lakes. For the first time, this study combined illumina sequencing and analysis of amplicons of both total community rDNA and 16S rRNA cDNA to determine the diversity and community structure of bacteria and archaea within 3 hot springs of L. Magadi and little Magadi. METHODS: Water, wet sediments and microbial mats were collected from springs in the main lake at a temperature of 45.1 °C and from Little Magadi "Nasikie eng'ida" (temperature of 81 °C and 83.6 °C). Total community DNA and RNA were extracted from samples using phenol-chloroform and Trizol RNA extraction protocols respectively. The 16S rRNA gene variable region (V4 - V7) of the extracted DNA and RNA were amplified and library construction performed following Illumina sequencing protocol. Sequences were analyzed done using QIIME while calculation of Bray-Curtis dissimilarities between datasets, hierarchical clustering, Non Metric Dimensional Scaling (NMDS) redundancy analysis (RDA) and diversity indices were carried out using the R programming language and the Vegan package. RESULTS: Three thousand four hundred twenty-six and one thousand nine hundred thirteen OTUs were recovered from 16S rDNA and 16S rRNA cDNA respectively. Uncultured diversity accounted for 89.35 % 16S rDNA and 87.61 % 16S rRNA cDNA reads. The most abundant phyla in both the 16S rDNA and 16S rRNA cDNA datasets included: Proteobacteria (8.33-50 %), Firmicutes 3.52-28.92 %, Bacteroidetes (3.45-26.44 %), Actinobacteria (0.98-28.57 %) and Euryarchaeota (3.55-34.48 %) in all samples. NMDS analyses of taxonomic composition clustered the taxa into three groups according to sample types (i.e. wet sediments, mats and water samples) with evident overlap of clusters between wet sediments and microbial mats from the three sample types in both DNA and cDNA datasets. The hot spring (45.1 °C) contained less diverse populations compared to those in Little Magadi (81-83 °C). CONCLUSION: There were significant differences in microbial community structure at 95 % level of confidence for both total diversity (P value, 0.009) based on 16S rDNA analysis and active microbial diversity (P value, 0.01) based on 16S rRNA cDNA analysis, within the three hot springs. Differences in microbial composition and structure were observed as a function of sample type and temperature, with wet sediments harboring the highest diversity.