A Retrospective Review of Microbiological Methods Applied in Studies Following the Deepwater Horizon Oil Spill

Deciphering the recent trends in pesticide bioremediation using genome editing and multi-omics approaches: a review

Pesticide pollution in recent times has emerged as a grave environmental problem contaminating both aquatic and terrestrial ecosystems owing to their widespread use. Bioremediation using gene editing and system biology could be developed as an eco-friendly and proficient tool to remediate pesticide-contaminated sites due to its advantages and greater public acceptance over the physical and chemical methods. However, it is indispensable to understand the different aspects associated with microbial metabolism and their physiology for efficient pesticide remediation. Therefore, this review paper analyses the different gene editing tools and multi-omics methods in microbes to produce relevant evidence regarding genes, proteins and metabolites associated with pesticide remediation and the approaches to contend against pesticide-induced stress. We systematically discussed and analyzed the recent reports (2015-2022) on multi-omics methods for pesticide degradation to elucidate the mechanisms and the recent advances associated with the behaviour of microbes under diverse environmental conditions. This study envisages that CRISPR-Cas, ZFN and TALEN as gene editing tools utilizing Pseudomonas, Escherichia coli and Achromobacter sp. can be employed for remediation of chlorpyrifos, parathion-methyl, carbaryl, triphenyltin and triazophos by creating gRNA for expressing specific genes for the bioremediation. Similarly, systems biology accompanying multi-omics tactics revealed that microbial strains from Paenibacillus, Pseudomonas putida, Burkholderia cenocepacia, Rhodococcus sp. and Pencillium oxalicum are capable of degrading deltamethrin, p-nitrophenol, chlorimuron-ethyl and nicosulfuron. This review lends notable insights into the research gaps and provides potential solutions for pesticide remediation by using different microbe-assisted technologies. The inferences drawn from the current study will help researchers, ecologists, and decision-makers gain comprehensive knowledge of value and application of systems biology and gene editing in bioremediation assessments.

The Influence of Kerosene on Microbiomes of Diverse Soils

One of the most important challenges for soil science is to determine the limits for the sustainable functioning of contaminated ecosystems. The response of soil microbiomes to kerosene pollution is still poorly understood. Here, we model the impact of kerosene leakage on the composition of the topsoil microbiome in pot and field experiments with different loads of added kerosene (loads up to 100 g/kg; retention time up to 360 days). At four time points we measured kerosene concentration and sequenced variable regions of 16S ribosomal RNA in the microbial communities. Mainly alkaline Dystric Arenosols with low content of available phosphorus and soil organic matter had an increased fraction of Actinobacteriota, Firmicutes, Nitrospirota, Planctomycetota, and, to a lesser extent, Acidobacteriota and Verrucomicobacteriota. In contrast, in highly acidic Fibric Histosols, rich in soil organic matter and available phosphorus, the fraction of Acidobacteriota was higher, while the fraction of Actinobacteriota was lower. Albic Luvisols occupied an intermediate position in terms of both physicochemical properties and microbiome composition. The microbiomes of different soils show similar response to equal kerosene loads. In highly contaminated soils, the proportion of anaerobic bacteria-metabolizing hydrocarbons increased, whereas the proportion of aerobic bacteria decreased. During the field experiment, the soil microbiome recovered much faster than in the pot experiments, possibly due to migration of microorganisms from the polluted area. The microbial community of Fibric Histosols recovered in 6 months after kerosene had been loaded, while microbiomes of Dystric Arenosols and Albic Luvisols did not restore even after a year.

Metatranscriptomic Analysis of Oil-Exposed Seawater Bacterial Communities Archived by an Environmental Sample Processor (ESP)

The use of natural marine bacteria as "oil sensors" for the detection of pollution events can be suggested as a novel way of monitoring oil occurrence at sea. Nucleic acid-based devices generically called genosensors are emerging as potentially promising tools for in situ detection of specific microbial marker genes suited for that purpose. Functional marker genes are particularly interesting as targets for oil-related genosensing but their identification remains a challenge. Here, seawater samples, collected in tanks with oil addition mimicking a realistic oil spill scenario, were filtered and archived by the Environmental Sample Processor (ESP), a fully robotized genosensor, and the samples were then used for post-retrieval metatranscriptomic analysis. After extraction, RNA from ESP-archived samples at start, Day 4 and Day 7 of the experiment was used for sequencing. Metatranscriptomics revealed that several KEGG pathways were significantly enriched in samples exposed to oil. However, these pathways were highly expressed also in the non-oil-exposed water samples, most likely as a result of the release of natural organic matter from decaying phytoplankton. Temporary peaks of aliphatic alcohol and aldehyde dehydrogenases and monoaromatic ring-degrading enzymes (e.g., ben, box, and dmp clusters) were observed on Day 4 in both control and oil-exposed and non-exposed tanks. Few alkane 1-monooxygenase genes were upregulated on oil, mostly transcribed by families Porticoccaceae and Rhodobacteraceae, together with aromatic ring-hydroxylating dioxygenases, mostly transcribed by Rhodobacteraceae. Few transcripts from obligate hydrocarbonoclastic genera of Alcanivorax, Oleispira and Cycloclasticus were significantly enriched in the oil-treated exposed tank in comparison to control the non-exposed tank, and these were mostly transporters and genes involved in nitrogen and phosphorous acquisition. This study highlights the importance of seasonality, i.e., phytoplankton occurrence and senescence leading to organic compound release which can be used preferentially by bacteria over oil compounds, delaying the latter process. As a result, such seasonal effect can reduce the sensitivity of genosensing tools employing bacterial functional genes to sense oil. A better understanding of the use of natural organic matter by bacteria involved in oil-biodegradation is needed to develop an array of functional markers enabling the rapid and specific in situ detection of anthropogenic pollution.

Identification of a novel archaea virus, detected in hydrocarbon polluted Hungarian and Canadian samples

Metagenomics is a helpful tool for the analysis of unculturable organisms and viruses. Viruses that target bacteria and archaea play important roles in the microbial diversity of various ecosystems. Here we show that Methanosarcina virus MV (MetMV), the second Methanosarcina sp. virus with a completely determined genome, is characteristic of hydrocarbon pollution in environmental (soil and water) samples. It was highly abundant in Hungarian hydrocarbon polluted samples and its genome was also present in the NCBI SRA database containing reads from hydrocarbon polluted samples collected in Canada, indicating the stability of its niche and the marker feature of this virus. MetMV, as the only currently identified marker virus for pollution in environmental samples, could contribute to the understanding of the complicated network of prokaryotes and their viruses driving the decomposition of environmental pollutants.

Gene Editing and Systems Biology Tools for Pesticide Bioremediation: A Review

Bioremediation is the degradation potential of microorganisms to dissimilate the complex chemical compounds from the surrounding environment. The genetics and biochemistry of biodegradation processes in datasets opened the way of systems biology. Systemic biology aid the study of interacting parts involved in the system. The significant keys of system biology are biodegradation network, computational biology, and omics approaches. Biodegradation network consists of all the databases and datasets which aid in assisting the degradation and deterioration potential of microorganisms for bioremediation processes. This review deciphers the bio-degradation network, i.e., the databases and datasets (UM-BBD, PAN, PTID, etc.) aiding in assisting the degradation and deterioration potential of microorganisms for bioremediation processes, computational biology and multi omics approaches like metagenomics, genomics, transcriptomics, proteomics, and metabolomics for the efficient functional gene mining and their validation for bioremediation experiments. Besides, the present review also describes the gene editing tools like CRISPR Cas, TALEN, and ZFNs which can possibly make design microbe with functional gene of interest for degradation of particular recalcitrant for improved bioremediation.