Laboratory of Molecular Bioremediation and Nanobiotechnology, Department of Environmental Biotechnology, School of Environmental Sciences, Bharathidasan University, Tiruchirappalli, 620 024, Tamil Nadu, India.
Department of Civil Engineering, Priyadarshini Engineering College, Vaniyambadi, Tirupattur, 635 751, Tamil Nadu, India.
Environ Res. 2023 Nov 1;236(Pt 2):116779. doi: 10.1016/j.envres.2023.116779. Epub 2023 Jul 28.
The impact of environmental pollution in air and water is reflected mainly in the soil ecosystem as it impairs soil functions. Also, since the soil is the habitat for billions of organisms, the biodiversity is in turn altered. Microbes are precise sensors of ecological contamination, and bacteria have a key and important function in terms of bioremediation of the contaminated soil. Hence in the current work, we aimed at assessing the unidentified bacterial population through Illumina MiSeq sequencing technology and their community structural changes in different levels of petroleum-contaminated soil and sludge samples (aged, sludge, and leakage soil) to identify unique bacteria for their potential application in remediation. The studies showed that major bacterial consortiums namely, Proteobacteria (57%), Alphaproteobacteria (31%), and Moraxellaceae (23%) were present in aged soil, whereas Proteobacteria (52%), Alphaproteobacteria (33%), and Rhodobacteraceae (28%) were dominantly found in sludge soil. In leakage soil, Proteobacteria (59%), Alphaproteobacteria (33%), and Rhodobacteraceae (29%) were abundantly present. The Venn diagrams are used to analyze the distribution of abundances in individual operational taxonomic units (OTUs) within three soil samples. After data filtering, they were grouped into OTU clusters and 329 OTUs were identified from the three soil samples. Among the 329, 160 OTUs were common in the three soil samples. The bacterial diversity is estimated using alpha diversity indices and Shanon index and was found to be 4.490, 4.073 and 4.631 in aged soil, sludge soil and leakage soil, respectively and similarly richness was found to be 618, 417 and 418. The heat map was generated by QIIME software and from the top 50 enriched genera few microbes such as Pseudomonas, Bacillus, Mycobacterium, Sphingomonas and Paracoccus, were shown across all the samples. In addition, we also analyzed various physicochemical properties of soil including pH, temperature, salinity, electrical conductivity, alkalinity, total carbon, total organic matter, nitrogen, phosphorus and potassium to calculate the soil quality index (SQI). The SQI of aged, sludge and leakage soil samples were 0.73, 0.64, and 0.89, respectively. These findings show the presence of unexplored bacterial species which could be applied for hydrocarbon remediation and further they can be exploited for the same.
环境污染对空气和水的影响主要反映在土壤生态系统中，因为它会损害土壤功能。此外，由于土壤是数十亿种生物的栖息地，生物多样性也随之发生变化。微生物是生态污染的精确传感器，而细菌在受污染土壤的生物修复方面具有关键和重要的功能。因此，在目前的工作中，我们旨在通过 Illumina MiSeq 测序技术评估未识别的细菌种群，并研究其在不同水平的石油污染土壤和污泥样本（老化土壤、污泥和泄漏土壤）中的群落结构变化，以鉴定具有潜在应用于修复的特有细菌。研究表明，主要的细菌联合体，即变形菌（57%）、α变形菌（31%）和莫拉氏菌科（23%）存在于老化土壤中，而在污泥土壤中主要发现的是变形菌（52%）、α变形菌（33%）和红杆菌科（28%）。在泄漏土壤中，变形菌（59%）、α变形菌（33%）和红杆菌科（29%）含量丰富。Venn 图用于分析三个土壤样本中个体操作分类单元（OTU）的丰度分布。在数据过滤后，它们被分为 OTU 簇，从三个土壤样本中鉴定出 329 个 OTU。在这 329 个 OTU 中，有 160 个 OTU在三个土壤样本中是共同的。使用α多样性指数和 Shannon 指数估计细菌多样性，分别在老化土壤、污泥土壤和泄漏土壤中发现为 4.490、4.073 和 4.631，类似地，丰富度分别为 618、417 和 418。热图由 QIIME 软件生成，从前 50 个富集属中可以看出，假单胞菌、芽孢杆菌、分枝杆菌、鞘氨醇单胞菌和副球菌等少数微生物在所有样本中都有显示。此外，我们还分析了土壤的各种物理化学性质，包括 pH 值、温度、盐度、电导率、碱度、总碳、总有机碳、氮、磷和钾，以计算土壤质量指数（SQI）。老化、污泥和泄漏土壤样本的 SQI 分别为 0.73、0.64 和 0.89。这些发现表明存在未被探索的细菌物种，可用于烃类修复，并且可以进一步用于该目的。
