A robust, cost-effective method for DNA, RNA and protein co-extraction from soil, other complex microbiomes and pure cultures

Soil Metaproteomics for Microbial Community Profiling: Methodologies and Challenges

Soil represents a complex and dynamic ecosystem, hosting a myriad of microorganisms that coexist and play vital roles in nutrient cycling and organic matter transformation. Among these microorganisms, bacteria and fungi are key members of the microbial community, profoundly influencing the fate of nitrogen, sulfur, and carbon in terrestrial environments. Understanding the intricacies of soil ecosystems and the biological processes orchestrated by microbial communities necessitates a deep dive into their composition and metabolic activities. The advent of next-generation sequencing and 'omics' techniques, such as metagenomics and metaproteomics, has revolutionized our understanding of microbial ecology and the functional dynamics of soil microbial communities. Metagenomics enables the identification of microbial community composition in soil, while metaproteomics sheds light on the current biological functions performed by these communities. However, metaproteomics presents several challenges, both technical and computational. Factors such as the presence of humic acids and variations in extraction methods can influence protein yield, while the absence of high-resolution mass spectrometry and comprehensive protein databases limits the depth of protein identification. Notwithstanding these limitations, metaproteomics remains a potent tool for unraveling the intricate biological processes and functions of soil microbial communities. In this review, we delve into the methodologies and challenges of metaproteomics in soil research, covering aspects such as protein extraction, identification, and bioinformatics analysis. Furthermore, we explore the applications of metaproteomics in soil bioremediation, highlighting its potential in addressing environmental challenges.

Psychrophilic and mesophilic anaerobic treatment of synthetic dairy wastewater with long chain fatty acids: Process performances and microbial community dynamics

Facilitating the anaerobic degradation of long chain fatty acids (LCFA) is the key to unlock the energy potential of lipids-rich wastewater. In this study, the feasibility of psychrophilic anaerobic treatment of LCFA-containing dairy wastewater was assessed and compared to mesophilic anaerobic treatment. The results showed that psychrophilic treatment at 15 ℃ was feasible for LCFA-containing dairy wastewater, with high removal rates of soluble COD (>90%) and LCFA (∼100%). However, efficient long-term treatment required prior acclimation of the biomass to psychrophilic temperatures. The microbial community analysis revealed that putative syntrophic fatty acid bacteria and Methanocorpusculum played a crucial role in LCFA degradation during both mesophilic and psychrophilic treatments. Additionally, a fungal-bacterial biofilm was found to be important during the psychrophilic treatment. Overall, these findings demonstrate the potential of psychrophilic anaerobic treatment for industrial wastewaters and highlight the importance of understanding the microbial communities involved in the process.

Enhanced anaerobic digestion of dairy wastewater in a granular activated carbon amended sequential batch reactor

This study investigated the potential of granular activated carbon (GAC) supplementation to enhance anaerobic degradation of dairy wastewater. Two sequential batch reactors (SBRs; 0.8 L working volume), one control and another amended with GAC, were operated at 37°C and 1.5-1.6 m/h upflow velocity for a total of 120 days (four cycles of 30 days each). The methane production at the end of each cycle run increased by about 68%, 503%, 110%, and 125% in the GAC-amended SBR, compared with the Control SBR. Lipid degradation was faster in the presence of GAC. Conversely, the organic compounds, especially lipids, accumulated in the absence of the conductive material. In addition, a reduction in lag phase duration by 46%-100% was observed at all four cycles in the GAC-amended SBR. The peak methane yield rate was at least 2 folds higher with GAC addition in all cycles. RNA-based bacterial analysis revealed enrichment of Synergistes (0.8% to 29.2%) and Geobacter (0.4% to 11.3%) in the GAC-amended SBR. Methanolinea (85.8%) was the dominant archaea in the biofilm grown on GAC, followed by Methanosaeta (11.3%), at RNA level. Overall, this study revealed that GAC supplementation in anaerobic digesters treating dairy wastewater can promote stable and efficient methane production, accelerate lipid degradation and might promote the activity of electroactive microorganisms.

Omics-based ecosurveillance for the assessment of ecosystem function, health, and resilience

Current environmental monitoring efforts often focus on known, regulated contaminants ignoring the potential effects of unmeasured compounds and/or environmental factors. These specific, targeted approaches lack broader environmental information and understanding, hindering effective environmental management and policy. Switching to comprehensive, untargeted monitoring of contaminants, organism health, and environmental factors, such as nutrients, temperature, and pH, would provide more effective monitoring with a likely concomitant increase in environmental health. However, even this method would not capture subtle biochemical changes in organisms induced by chronic toxicant exposure. Ecosurveillance is the systematic collection, analysis, and interpretation of ecosystem health-related data that can address this knowledge gap and provide much-needed additional lines of evidence to environmental monitoring programs. Its use would therefore be of great benefit to environmental management and assessment. Unfortunately, the science of ‘ecosurveillance’, especially omics-based ecosurveillance is not well known. Here, we give an overview of this emerging area and show how it has been beneficially applied in a range of systems. We anticipate this review to be a starting point for further efforts to improve environmental monitoring via the integration of comprehensive chemical assessments and molecular biology-based approaches. Bringing multiple levels of omics technology-based assessment together into a systems-wide ecosurveillance approach will bring a greater understanding of the environment, particularly the microbial communities upon which we ultimately rely to remediate perturbed ecosystems.

Mycobacterium microti at the Environment and Wildlife Interface

An unexpected high presence of Mycobacterium microti in wild boar in Northern Italy (Garda Lake) has been reported since 2003, but the factors contributing to the maintenance of this pathogen are still unclear. In this study, we investigated the presence of M. microti in wild rodents and in water and soil samples collected at wild boar aggregation areas, such as watering holes, with the aim of clarifying their role in M. microti transmission. In total, 8 out of 120 captured animals tested positive for the Mycobacterium tuberculosis complex (MTBC) as assessed by real-time PCR, and six samples were confirmed to be M. microti. A strain with a genetic profile similar to those previously isolated in wild boars in the same area was isolated from one sample. Of the 20 water and 19 mud samples, 3 and 1, respectively, tested positive for the presence of MTBC, and spacer oligotype SB0118 (vole type) was detected in one sample. Our study suggests that wild rodents, in particular Apodemus sylvaticus, Microtus sp. and Apodemus flavicollis, play roles in the maintenance of M. microti infections in wild boar through ingestion or by contact with either infected excreta or a contaminated environment, such as at animal aggregation sites.

Meta-omic evaluation of bacterial microbial community structure and activity for the environmental assessment of soils: overcoming protein extraction pitfalls

Microorganisms play unique, essential and integral roles in the biosphere. This work aims to assess the utility of soil's metaomics for environmental diagnosis. Doñana National Park (DNP) was selected as a natural lab since it contains a strictly protected core that is surrounded by numerous threats of pollution. Culture-independent high-throughput molecular tools were used to evaluate the alterations of the global structure and metabolic activities of the microbiome. 16S rRNA sequencing shows lower bacterial abundance and diversity in areas historically exposed to contamination that surround DNP. For metaproteomics, an innovative post-alkaline protein extraction protocol was developed. After NaOH treatment, successive washing with Tris-HCl buffer supplemented with glycerol was essential to eliminate interferences. Starting from soils with different physicochemical characteristics, the method renders proteins with a remarkable resolution on SDS-PAGE gels. The proteins extracted were analysed by using an in-house database constructed from the rRNA data. LC-MS/MS analysis identified 2182 non-redundant proteins with 135 showing significant differences in relative abundance in the soils around DNP. Relevant global biological processes were altered in response to the environmental changes, such as protective and antioxidant mechanisms, translation, folding and homeostasis of proteins, membrane transport and aerobic respiratory metabolism.

Challenges, Strategies, and Perspectives for Reference-Independent Longitudinal Multi-Omic Microbiome Studies

In recent years, multi-omic studies have enabled resolving community structure and interrogating community function of microbial communities. Simultaneous generation of metagenomic, metatranscriptomic, metaproteomic, and (meta) metabolomic data is more feasible than ever before, thus enabling in-depth assessment of community structure, function, and phenotype, thus resulting in a multitude of multi-omic microbiome datasets and the development of innovative methods to integrate and interrogate those multi-omic datasets. Specifically, the application of reference-independent approaches provides opportunities in identifying novel organisms and functions. At present, most of these large-scale multi-omic datasets stem from spatial sampling (e.g., water/soil microbiomes at several depths, microbiomes in/on different parts of the human anatomy) or case-control studies (e.g., cohorts of human microbiomes). We believe that longitudinal multi-omic microbiome datasets are the logical next step in microbiome studies due to their characteristic advantages in providing a better understanding of community dynamics, including: observation of trends, inference of causality, and ultimately, prediction of community behavior. Furthermore, the acquisition of complementary host-derived omics, environmental measurements, and suitable metadata will further enhance the aforementioned advantages of longitudinal data, which will serve as the basis to resolve drivers of community structure and function to understand the biotic and abiotic factors governing communities and specific populations. Carefully setup future experiments hold great potential to further unveil ecological mechanisms to evolution, microbe-microbe interactions, or microbe-host interactions. In this article, we discuss the challenges, emerging strategies, and best-practices applicable to longitudinal microbiome studies ranging from sampling, biomolecular extraction, systematic multi-omic measurements, reference-independent data integration, modeling, and validation.

Soil Metaproteomics for the Study of the Relationships Between Microorganisms and Plants: A Review of Extraction Protocols and Ecological Insights

Soil is a complex matrix where biotic and abiotic components establish a still unclear network involving bacteria, fungi, archaea, protists, protozoa, and roots that are in constant communication with each other. Understanding these interactions has recently focused on metagenomics, metatranscriptomics and less on metaproteomics studies. Metaproteomic allows total extraction of intracellular and extracellular proteins from soil samples, providing a complete picture of the physiological and functional state of the “soil community”. The advancement of high-performance mass spectrometry technologies was more rapid than the development of ad hoc extraction techniques for soil proteins. The protein extraction from environmental samples is biased due to interfering substances and the lower amount of proteins in comparison to cell cultures. Soil sample preparation and extraction methodology are crucial steps to obtain high-quality resolution and yields of proteins. This review focuses on the several soil protein extraction protocols to date to highlight the methodological challenges and critical issues for the application of proteomics to soil samples. This review concludes that improvements in soil protein extraction, together with the employment of ad hoc metagenome database, may enhance the identification of proteins with low abundance or from non-dominant populations and increase our capacity to predict functional changes in soil.

The guanidine thiocyanate-high EDTA method for total microbial RNA extraction from severely heavy metal-contaminated soils

Molecular analyses relying on RNA, as a direct way to unravel active microbes and their functional genes, have received increasing attention from environmental researchers recently. However, extracting sufficient and high‐quality total microbial RNA from seriously heavy metal‐contaminated soils is still a challenge. In this study, the guanidine thiocyanate‐high EDTA (GTHE) method was established and optimized for recovering high quantity and quality of RNA from long‐term heavy metal‐contaminated soils. Due to the low microbial biomass in the soils, we combined multiple strong denaturants and intense mechanical lysis to break cells for increasing RNA yields. To minimize RNAase and heavy metals interference on RNA integrity, the concentrations of guanidine thiocyanate and EDTA were increased from 0.5 to 0.625 ml g⁻¹ soil and 10 to 100 mM, respectively. This optimized GTHE method was applied to seven severely contaminated soils, and the RNA recovery efficiencies were 2.80 ~ 59.41 μg g⁻¹ soil. The total microbial RNA of non‐Cr(VI) (NT) and Cr(VI)‐treated (CT) samples was utilized for molecular analyses. The result of qRT‐PCR demonstrated that the expressions of two tested genes, chrA and yieF, were respectively upregulated 4.12‐ and 62.43‐fold after Cr(VI) treatment. The total microbial RNA extracted from NT and CT samples, respectively, reached to 26.70 μg and 30.75 μg, which were much higher than the required amount (5 μg) for metatranscriptomic library construction. Besides, ratios of mRNA read were more than 86%, which indicated the high‐quality libraries constructed for metatranscriptomic analysis. In summary, the GTHE method is useful to study microbes of contaminated habitats.

Microbial Community Redundancy and Resilience Underpins High-Rate Anaerobic Treatment of Dairy-Processing Wastewater at Ambient Temperatures

High-rate anaerobic digestion (AD) is a reliable, efficient process to treat wastewaters and is often operated at temperatures exceeding 30°C, involving energy consumption of biogas in temperate regions, where wastewaters are often discharged at variable temperatures generally below 20°C. High-rate ambient temperature AD, without temperature control, is an economically attractive alternative that has been proven to be feasible at laboratory-scale. In this study, an ambient temperature pilot scale anaerobic reactor (2 m³) was employed to treat real dairy wastewater in situ at a milk processing plant, at organic loading rates of 1.3 ± 0.6 to 10.6 ± 3.7 kg COD/m³/day and hydraulic retention times (HRT) ranging from 36 to 6 h. Consistent high levels of COD removal efficiencies, ranging from 50 to 70% for total COD removal and 70 to 84% for soluble COD removal, were achieved during the trial. Within the reactor biomass, stable active archaeal populations were observed, consisting mainly of Methanothrix (previously Methanosaeta) species, which represented up to 47% of the relative abundant active species in the reactor. The decrease in HRT, combined with increases in the loading rate had a clear effect on shaping the structure and composition of the bacterial fraction of the microbial community, however, without affecting reactor performance. On the other hand, perturbances in influent pH had a strong impact, especially when pH went higher than 8.5, inducing shifts in the microbial community composition and, in some cases, affecting negatively the performance of the reactor in terms of COD removal and biogas methane content. For example, the main pH shock led to a drop in the methane content to 15%, COD removals decreased to 0%, while the archaeal population decreased to ~11% both at DNA and cDNA levels. Functional redundancy in the microbial community underpinned stable reactor performance and rapid reactor recovery after perturbations.

A Robust and Universal Metaproteomics Workflow for Research Studies and Routine Diagnostics Within 24 h Using Phenol Extraction, FASP Digest, and the MetaProteomeAnalyzer

The investigation of microbial proteins by mass spectrometry (metaproteomics) is a key technology for simultaneously assessing the taxonomic composition and the functionality of microbial communities in medical, environmental, and biotechnological applications. We present an improved metaproteomics workflow using an updated sample preparation and a new version of the MetaProteomeAnalyzer software for data analysis. High resolution by multidimensional separation (GeLC, MudPIT) was sacrificed to aim at fast analysis of a broad range of different samples in less than 24 h. The improved workflow generated at least two times as many protein identifications than our previous workflow, and a drastic increase of taxonomic and functional annotations. Improvements of all aspects of the workflow, particularly the speed, are first steps toward potential routine clinical diagnostics (i.e., fecal samples) and analysis of technical and environmental samples. The MetaProteomeAnalyzer is provided to the scientific community as a central remote server solution at www.mpa.ovgu.de.