Metatranscriptome sequencing and analysis of agriculture soil provided significant insights about the microbial community structure and function

Unlocking the potential of soil microbial communities for bioremediation of emerging organic contaminants: omics-based approaches

The remediation of emerging contaminants presents a pressing environmental challenge, necessitating innovative approaches for effective mitigation. This review article delves into the untapped potential of soil microbial communities in the bioremediation of emerging contaminants. Bioremediation, while a promising method, often proves time-consuming and requires a deep comprehension of microbial intricacies for enhancement. Given the challenges presented by the inability to culture many of these microorganisms, conventional methods are inadequate for achieving this goal. While omics-based methods provide an innovative approach to understanding the fundamental aspects, processes, and connections among microorganisms that are essential for improving bioremediation strategies. By exploring the latest advancements in omics technologies, this review aims to shed light on how these approaches can unlock the hidden capabilities of soil microbial communities, paving the way for more efficient and sustainable remediation solutions.

Metatranscriptomic insight into the possible role of clay microbiome in skin disease management

Even though the scientific documentation is limited, microbiome of healing clay is gradually gaining attention of the scientific community, as a therapeutic force playing an indispensable role in skin disease management. The present study explores the metatranscriptome profile of the Chamliyal clay, widely known for its efficacy in managing various skin problems, using Illumina NextSeq sequencing technology. The gene expression profile of the clay microbial community was analyzed through SEED subsystems of the MG-RAST server. Due to the unavailability of metatranscriptomic data on other therapeutic clays, Chamliyal's profile was compared to non-therapeutic soils, as well as healthy and diseased human skin microbiomes. The study identified Firmicutes, Proteobacteria, and Actinobacteria as the primary active microbial phyla in Chamliyal clay. These resemble those abundant in a healthy human skin microbiome. This is significant as lower levels of these phyla in the skin are linked to inflammatory skin conditions like psoriasis. Interestingly, pathogenic microbes actively metabolizing in the clay were absent. Importantly, 6% of the transcripts annotated to sulfur and iron metabolism, which are known to play a major role in skin disease management. This study provides the most comprehensive and a novel overview of the metatranscriptome of any of the healing clay available worldwide. The findings offer valuable insights into the clay microbiome's potential in managing skin disorders, inspiring future endeavors to harness these insights for medical applications.

Soil metatranscriptome demonstrates a shift in C, N, and S metabolisms of a grassland ecosystem in response to elevated atmospheric CO2

Soil organisms play an important role in the equilibrium and cycling of nutrients. Because elevated CO₂ (eCO₂) affects plant metabolism, including rhizodeposition, it directly impacts the soil microbiome and microbial processes. Therefore, eCO₂ directly influences the cycling of different elements in terrestrial ecosystems. Hence, possible changes in the cycles of carbon (C), nitrogen (N), and sulfur (S) were analyzed, alongside the assessment of changes in the composition and structure of the soil microbiome through a functional metatranscriptomics approach (cDNA from mRNA) from soil samples taken at the Giessen free-air CO₂ enrichment (Gi-FACE) experiment. Results showed changes in the expression of C cycle genes under eCO₂ with an increase in the transcript abundance for carbohydrate and amino acid uptake, and degradation, alongside an increase in the transcript abundance for cellulose, chitin, and lignin degradation and prokaryotic carbon fixation. In addition, N cycle changes included a decrease in the transcript abundance of N₂O reductase, involved in the last step of the denitrification process, which explains the increase of N₂O emissions in the Gi-FACE. Also, a shift in nitrate (NO3-) metabolism occurred, with an increase in transcript abundance for the dissimilatory NO3- reduction to ammonium (NH4+) (DNRA) pathway. S metabolism showed increased transcripts for sulfate (SO42-) assimilation under eCO₂ conditions. Furthermore, soil bacteriome, mycobiome, and virome significantly differed between ambient and elevated CO₂ conditions. The results exhibited the effects of eCO₂ on the transcript abundance of C, N, and S cycles, and the soil microbiome. This finding showed a direct connection between eCO₂ and the increased greenhouse gas emission, as well as the importance of soil nutrient availability to maintain the balance of soil ecosystems.

Advancement of Metatranscriptomics towards Productive Agriculture and Sustainable Environment: A Review

While chemical fertilisers and pesticides indeed enhance agricultural productivity, their excessive usage has been detrimental to environmental health. In addressing this matter, the use of environmental microbiomes has been greatly favoured as a ‘greener’ alternative to these inorganic chemicals’ application. Challenged by a significant proportion of unidentified microbiomes with unknown ecological functions, advanced high throughput metatranscriptomics is prudent to overcome the technological limitations in unfolding the previously undiscovered functional profiles of the beneficial microbiomes. Under this context, this review begins by summarising (1) the evolution of next-generation sequencing and metatranscriptomics in leveraging the microbiome transcriptome profiles through whole gene expression profiling. Next, the current environmental metatranscriptomics studies are reviewed, with the discussion centred on (2) the emerging application of the beneficial microbiomes in developing fertile soils and (3) the development of disease-suppressive soils as greener alternatives against biotic stress. As sustainable agriculture focuses not only on crop productivity but also long-term environmental sustainability, the second half of the review highlights the metatranscriptomics’ contribution in (4) revolutionising the pollution monitoring systems via specific bioindicators. Overall, growing knowledge on the complex microbiome functional profiles is imperative to unlock the unlimited potential of agricultural microbiome-based practices, which we believe hold the key to productive agriculture and sustainable environment.

Metatranscriptome-based investigation of flavor-producing core microbiota in different fermentation stages of dajiang, a traditional fermented soybean paste of Northeast China

Dajiang, or naturally fermented soybean paste, has a unique flavor that is influenced by the resident microflora. However, the association between flavor and the core microbiota is unclear. Recent advances in RNA sequencing have identified genes that are actively expressed in complex microbial communities. To this end, we analyzed the time-dependent changes in the microbiota and the metabolite profiles of Dajiang using metatranscriptome sequencing, HS-SPME-GC-MS and amino acid analysis identified 10 volatile compounds that contribute to the development of soybean paste flavor. Further analysis of the correlation between the active microorganisms and the physicochemical characteristics and flavor substances in soybean paste indicated that Lactobacillus and Tetragenococcus were the core genera affecting chromaticity and flavor. These microorganisms produce enzymes that catalyze a series of metabolic pathways that generate flavor substances. Our findings provide new insights into the role of the microbiota in the development of flavor in fermented foods.

Indicators for assessment of soil quality: a mini-review

Soil quality is the competence of soil to perform necessary functions that are able to maintain animal and plant productivity of the soil. Soil consists of various physical, chemical, and biological parameters, and all these parameters are involved in the critical functioning of soil. There is a need for continuous assessment of soil quality as soil is a complex and dynamic constituent of Earth's biosphere that is continuously changing by natural and anthropogenic disturbances. Any perturbations in the soil cause disturbances in the physical (soil texture, bulk density, etc.), chemical (pH, salinity, organic carbon, etc.), and biological (microbes and enzymes) parameters. These physical, chemical, and biological parameters can serve as indicators for soil quality assessment. However, soil quality assessment cannot be possible by evaluating only one parameter out of physical, chemical, or biological. So, there is an emergent need to establish a minimum dataset (MDS) which shall include physical, chemical, and biological parameters to assess the quality of the given soil. This review attempts to describe various physical, chemical, and biological parameters, combinations of which can be used in the establishment of MDS.

Metatranscriptomics: an approach for retrieving novel eukaryotic genes from polluted and related environments

Metatranscriptomics, a subset of metagenomics, provides valuable information about the whole gene expression profiling of complex microbial communities of an ecosystem. Metagenomic studies mainly focus on the genomic content and identification of microbes present within a community, while metatranscriptomics provides the diversity of the active genes within such community, their expression profile and how these levels change due to change in environmental conditions. Metatranscriptomics has been applied to different types of environments, from the study of human microbiomes, to those found in plants, animals, within soils and in aquatic systems. Metatranscriptomics, based on the utilization of mRNA isolated from environmental samples, is a suitable approach to mine the eukaryotic gene pool for genes of biotechnological relevance. Also, it is imperative to develop different bioinformatic pipelines to analyse the data obtained from metatranscriptomic analysis. In the present review, we summarise the metatranscriptomics applied to soil environments to study the functional diversity, and discuss approaches for isolating the genes involved in organic matter degradation and providing tolerance to toxic metals, role of metatranscriptomics in microbiome research, various bioinformatics pipelines used in data analysis and technical challenges for gaining biologically meaningful insight of this approach.

Comparative metatranscriptome analysis revealed broad response of microbial communities in two soil types, agriculture versus organic soil

BACKGROUND

Studying expression of genes by direct sequencing and analysis of metatranscriptomes at a particular time and space can disclose structural and functional insights about microbial communities. The present study reports comparative analysis of metatranscriptome from two distinct soil ecosystems referred as M1 (agriculture soil) and O1 (organic soil).

RESULTS

Analysis of sequencing reads revealed Proteobacteria as major dominant phyla in both soil types. The order of the top 3 abundant phyla in M1 sample was Proteobacteria > Ascomycota > Firmicutes, whereas in sample O1, the order was Proteobacteria > Cyanobacteria > Actinobacteria. Analysis of differentially expressed genes demonstrated high expression of transcripts related to copper-binding proteins, proteins involved in electron carrier activity, DNA integration, endonuclease activity, MFS transportation, and other uncharacterized proteins in M1 compared to O1. Of the particular interests, several transcripts related to nitrification, ammonification, stress response, and alternate carbon fixation pathways were highly expressed in M1. In-depth analysis of the sequencing data revealed that transcripts of archaeal origin had high expression in M1 compared to O1 indicating the active role of Archaea in metal- and pesticide-contaminated environment. In addition, transcripts encoding 4-hydroxyphenylpyruvate dioxygenase, glyoxalase/bleomycin resistance protein/dioxygenase, metapyrocatechase, and ring hydroxylating dioxygenases of aromatic hydrocarbon degradation pathways had high expression in M1. Altogether, this study provided important insights about the transcripts and pathways upregulating in the presence of pesticides and herbicides.

CONCLUSION

Altogether, this study claims a high expression of microbial transcripts in two ecosystems with a wide range of functions. It further provided clue about several molecular markers which could be a strong indicator of metal and pesticide contamination in soils. Interestingly, our study revealed that Archaea are playing a significant role in nitrification process as compared to bacteria in metal- and pesticide-contaminated soil. In particular, high expression of transcripts related to aromatic hydrocarbon degradation in M1 soil indicates their important role in biodegradation of pollutants, and therefore, further investigation is needed.

Metatranscriptome Analysis Deciphers Multifunctional Genes and Enzymes Linked With the Degradation of Aromatic Compounds and Pesticides in the Wheat Rhizosphere

Agricultural soils are becoming contaminated with synthetic chemicals like polyaromatic compounds, petroleum hydrocarbons, polychlorinated biphenyls (PCBs), phenols, herbicides, insecticides and fungicides due to excessive dependency of crop production systems on the chemical inputs. Microbial degradation of organic pollutants in the agricultural soils is a continuous process due to the metabolic multifunctionalities and enzymatic capabilities of the soil associated communities. The plant rhizosphere with its complex microbial inhabitants and their multiple functions, is amongst the most live and dynamic component of agricultural soils. We analyzed the metatranscriptome data of 20 wheat rhizosphere samples to decipher the taxonomic microbial communities and their multifunctionalities linked with the degradation of organic soil contaminants. The analysis revealed a total of 21 different metabolic pathways for the degradation of aromatic compounds and 06 for the xenobiotics degradation. Taxonomic annotation of wheat rhizosphere revealed bacteria, especially the Proteobacteria, actinobacteria, firmicutes, bacteroidetes, and cyanobacteria, which are shown to be linked with the degradation of aromatic compounds as the dominant communities. Abundance of the transcripts related to the degradation of aromatic amin compounds, carbazoles, benzoates, naphthalene, ketoadipate pathway, phenols, biphenyls and xenobiotics indicated abundant degradation capabilities in the soils. The results highlighted a potentially dominant role of crop rhizosphere associated microbial communities in the remediation of contaminant aromatic compounds.