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Human pathogens can survive and grow in hot springs. For water quality assessment, Escherichia coli or Enterococci are the main thermotolerant enteric bacteria commonly used to estimate the load of pathogenic bacteria in water. However, most of the environmental bacteria are unculturable thus culture methods may cause bias in detection of most pathogens. Illumina sequencing can provide a more comprehensive and accurate insight into environmental bacterial pathogens, which can be used to develop better risk assessment methods and promote public health awareness. In this study, high-throughput Illumina sequencing was used to identify bacterial pathogens from five hot springs; Maiwooi, Akwar, Garbanabra, Elegedi and Gelti, in Eritrea. Water samples were collected from the five hot springs. Total community DNA was extracted from samples using the phenol-chloroform method. The 16S rRNA gene variable region (V4-V7) of the extracted DNA was amplified and library construction done according to Illumina sequencing protocol. The sequence reads (length >200 bp) from Illumina sequencing libraries ranged from 22,091 sequences in the wet sediment sample from Garbanabra to 155,789 sequences in the mat sample from Elegedi. Taxonomy was assigned to each OTU using BLASTn against a curated database derived from GreenGenes, RDPII, SILVA SSU Reference 119 and NCBI. The proportion of potential pathogens from the water samples was highest in Maiwooi (17.8%), followed by Gelti (16.7%), Akwar (13.6%) and Garbanabra (10.9%). Although the numbers of DNA sequence reads from Illumina sequencing were very high for the Elegedi (104,328), corresponding proportion of potential pathogens very low (3.6%). Most of the potential pathogenic bacterial sequences identified were from Proteobacteria and Firmicutes. Legionella and Clostridium were the most common detected genera with different species. Most of the potential pathogens were detected from the water samples. However, sequences belonging to Clostridium were observed more abundantly from the mat samples. This study employed high-throughput sequencing technologies to determine the presence of pathogenic bacteria in the five hot springs in Eritrea.

Background: Total community rDNA was used to determine the diversity of bacteria and archaea from water, wet sediment and microbial mats samples of hot springs in the Eastern lowlands of Eritrea. The temperatures of the springs range from 49.5 °C to 100 °C while pH levels varied from 6.97 to 7.54. Akwar and Maiwooi have high carbonate levels. The springs near the seashore, Garbanabra and Gelti, are more saline with higher levels of sodium and chlorides. Elegedi, situated in the Alid volcanic area, has the highest temperature, iron and sulfate concentrations., Results: The five hot springs shared 901 of 4371 OTUs recovered while the three sample types (water, wet sediment and microbial mats) also shared 1429 OTUs. The Chao1 OTU estimate in water sample was significantly higher than the wet sediment and microbial mat samples. As indicated by NMDS, the community samples at genus level showed location specific clustering. Certain genera correlated with temperature, sodium, carbonate, iron, sulfate and ammonium levels in water. The abundant phyla included Proteobacteria (6.2-82.3%), Firmicutes (1.6-63.5%), Deinococcus-Thermus (0.0-19.2%), Planctomycetes (0.0-11.8%), Aquificae (0.0-9.9%), Chlorobi (0.0-22.3%) and Bacteroidetes (2.7-8.4%)., Conclusion: There were significant differences in microbial community structure within the five locations and sample types at OTU level. The occurence of Aquificae, Deinococcus-Thermus, some Cyanobacteria and Crenarchaeota were highly dependent on temperature. The Halobacterium, unclassified Thaumarchaeota, Actinobacteria and Cyanobacteria showed significant correlation with salinity occurring abundantly in Garbanabra and Gelti. Firmicutes and unclassified Rhodocylaceae were higher in the microbial mat samples, while Archaea were prominent in the wet sediment samples.