Simple discovery of bacterial biocatalysts from environmental samples through functional metaproteomics

Activity- and Enrichment-Based Metaproteomics Insights into Active Urease from the Rumen Microbiota of Cattle

Regulation of microbial urease activity plays a crucial role in improving the utilization efficiency of urea and reducing nitrogen emissions to the environment for ruminant animals. Dealing with the diversity of microbial urease and identifying highly active urease as the target is the key for future regulation. However, the identification of active urease in the rumen is currently limited due to large numbers of uncultured microorganisms. In the present study, we describe an activity- and enrichment-based metaproteomic analysis as an approach for the discovery of highly active urease from the rumen microbiota of cattle. We conducted an optimization method of protein extraction and purification to obtain higher urease activity protein. Cryomilling was the best choice among the six applied protein extraction methods (ultrasonication, bead beating, cryomilling, high-pressure press, freeze-thawing, and protein extraction kit) for obtaining protein with high urease activity. The extracted protein by cryomilling was further enriched through gel filtration chromatography to obtain the fraction with the highest urease activity. Then, by using SDS-PAGE, the gel band including urease was excised and analyzed using LC-MS/MS, searching against a metagenome-derived protein database. Finally, we identified six microbial active ureases from 2225 rumen proteins, and the identified ureases were homologous to those of Fibrobacter and Treponema. Moreover, by comparing the 3D protein structures of the identified ureases and known ureases, we found that the residues in the β-turn of flap regions were nonconserved, which might be crucial in influencing the flexibility of flap regions and urease activity. In conclusion, the active urease from rumen microbes was identified by the approach of activity- and enrichment-based metaproteomics, which provides the target for designing a novel efficient urease inhibitor to regulate rumen microbial urease activity.

A roadmap for metagenomic enzyme discovery

Covering: up to 2021Metagenomics has yielded massive amounts of sequencing data offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While genome-resolved information about microbial communities from nearly every environment on earth is now available, the ability to accurately predict biocatalytic functions directly from sequencing data remains challenging. Compared to primary metabolic pathways, enzymes involved in secondary metabolism often catalyze specialized reactions with diverse substrates, making these pathways rich resources for the discovery of new enzymology. To date, functional insights gained from studies on environmental DNA (eDNA) have largely relied on PCR- or activity-based screening of eDNA fragments cloned in fosmid or cosmid libraries. As an alternative, shotgun metagenomics holds underexplored potential for the discovery of new enzymes directly from eDNA by avoiding common biases introduced through PCR- or activity-guided functional metagenomics workflows. However, inferring new enzyme functions directly from eDNA is similar to searching for a 'needle in a haystack' without direct links between genotype and phenotype. The goal of this review is to provide a roadmap to navigate shotgun metagenomic sequencing data and identify new candidate biosynthetic enzymes. We cover both computational and experimental strategies to mine metagenomes and explore protein sequence space with a spotlight on natural product biosynthesis. Specifically, we compare in silico methods for enzyme discovery including phylogenetics, sequence similarity networks, genomic context, 3D structure-based approaches, and machine learning techniques. We also discuss various experimental strategies to test computational predictions including heterologous expression and screening. Finally, we provide an outlook for future directions in the field with an emphasis on meta-omics, single-cell genomics, cell-free expression systems, and sequence-independent methods.

Metaproteomic Discovery and Characterization of a Novel Lipolytic Enzyme From an Indian Hot Spring

Lipolytic enzymes are produced by animals, plants and microorganisms. With their chemo-, regio-, and enantio-specific characteristics, lipolytic enzymes are important biocatalysts useful in several industrial applications. They are widely used in the processing of fats and oils, detergents, food processing, paper and cosmetics production. In this work, we used a new functional metaproteomics approach to screen sediment samples of the Indian Bakreshwar hot spring for novel thermo- and solvent-stable lipolytic enzymes. We were able to identify an enzyme showing favorable characteristics. DS-007 showed high hydrolytic activity with substrates with shorter chain length (C10, significantly less hydrolytic activity was observed. A preference for short chain acyl groups is characteristic for esterases, suggesting that DS-007 is an esterase. Consistent with the high temperature at its site of isolation, DS-007 showed a temperature optimum at 55°C and retained 80% activity even after prolonged exposure to temperatures as high as 60°C. The enzyme showed optimum activity at pH 9.5, with more than 50% of its optimum activity between pH 8.0 and pH 9.5. DS-007 also exhibited tolerance toward organic solvents at a concentration of 1% (v/v). One percent of methanol increased the activity of DS-007 by 40% in comparison to the optimum conditions without solvent. In the presence of 10% methanol, DMSO or isopropanol DS-007 still showed around 50% activity. This data indicates that DS-007 is a temperature- and solvent-stable thermophilic enzyme with reasonable activity even at lower temperatures as well as a catalyst that can be used at a broad range of pH values with an optimum in the alkaline range, showing the adaptation to the habitat's temperature and alkaline pH.

A multi-omic screening approach for the discovery of thermoactive glycoside hydrolases

Next-generation sequencing and computational biology have facilitated the implementation of new combinatorial screening approaches to discover novel enzymes of biotechnological interest. In this study, we describe the successful establishment of a multi-omic approach for the identification of thermostable hydrolase-encoding genes by determination of gene expression levels. We applied this combinatorial approach using an anaerobic enrichment culture from an Azorean hot spring sample grown on green coffee beans as recalcitrant substrate. An in-depth analysis of the microbial community resulted in microorganisms capable of metabolizing the selected substrate, such as the genera Caloramator, Dictyoglomus and Thermoanaerobacter as active and abundant microorganisms. To discover glycoside hydrolases, 90,342 annotated genes were screened for specific reaction types. A total number of 106 genes encoding cellulases (EC 3.2.1.4), beta-glucosidases (EC 3.2.1.21) and endo-1,4-beta-mannosidases (EC 3.2.1.78) were selected. Mapping of RNA-Seq reads to the related metagenome led to expression levels for each gene. Amongst those, 14 genes, encoding glycoside hydrolases, showed highest expression values, and were used for further cloning. Four proteins were biochemically characterized and were identified as thermoactive glycoside hydrolases with a broad substrate range. This work demonstrated that a combinatory omic approach is a suitable strategy identifying unique thermoactive enzymes from environmental samples.

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.

Digitalization in microbiology - Paving the path to sustainable circular bioeconomy

The transition to a sustainable bio-based circular economy requires cutting edge technologies that ensure economic growth with environmentally responsible action. This transition will only be feasible when the opportunities of digitalization are also exploited. Digital methods and big data handling have already found their way into life sciences and generally offer huge potential in various research areas. While computational analyses of microbial metagenome data have become state of the art, the true potential of bioinformatics remains mostly untapped so far. In this article we present challenges and opportunities of digitalization including multi-omics approaches in discovering and exploiting the microbial diversity of the planet with the aim to identify robust biocatalysts for application in sustainable bioprocesses as part of the transition from a fossil-based to a bio-based circular economy. This will contribute to solving global challenges, including utilization of natural resources, food supply, health, energy and the environment.

Characterization and comparison of metaproteomes in traditional and commercial dajiang, a fermented soybean paste in northeast China

Dajiang is a popular Chinese fermented soybean condiment. Here, a comparative metaproteomic analysis of traditional and commercial dajiang was performed during fermentation. A total of 4250 and 1421 peptide sequences were obtained from 3493 and 1987 proteins in traditional and commercial dajiang, respectively. 4299 differentially expressed microbial proteins show a high metabolic heterogeneity between the two types of dajiang. The KEGG annotation indicated that there were some pathways related to human diseases, which suggest that some microbes in traditional dajiang fermentation may have greater food safety hazards. In combination with qualitative metabolomic analysis, we further traced metabolic intermediates and key enzymes in several main fermentation pathways of dajiang to be mainly affiliated with Penicillium, Tetracoccus and Bacillus in traditional samples, as well as Aspergilus in commercial samples. These results could provide information for the selection of strains that are more suitable to produce high quality dajiang and other fermented products.

Metagenomics: Is it a powerful tool to obtain lipases for application in biocatalysis?

In recent years, metagenomic strategies have been widely used to isolate and identify new enzymes from uncultivable components of microbial communities. Among these enzymes, various lipases have been obtained from metagenomic libraries from different environments and characterized. Although many of these lipases have characteristics that could make them interesting for application in biocatalysis, relatively little work has been done to evaluate their potential to catalyze industrially important reactions. In the present article, we highlight the latest research on lipases obtained through metagenomic tools, focusing on studies of activity and stability and investigations of application in biocatalysis. We also discuss the challenges of metagenomic approaches for the bioprospecting of new lipases.

An integrated metagenomic/metaproteomic investigation of microbiota in dajiang-meju, a traditional fermented soybean product in Northeast China

Dajiang-meju have been used as major ingredients for the preparation of traditional spontaneously fermented soybean paste in Northeast China. In this work, we sequenced and analyzed the metagenome of 12 dajiang-meju samples. To complement the metagenome analysis, we analyzed the taxonomic and functional diversity of the microbiota by metaproteomics (LC-MS/MS). The analysis of metagenomic data revealed that the communities were primarily dominated by Enterobacter, Enterococcus, Leuconostoc, Lactobacillus, Citrobacter and Leclercia. Moreover, changes in the functional levels were monitored, and metaproteomic analysis revealed that most of the proteins were mainly expressed by members of Rhizopus, Penicillium and Geotrichum. The number of sequences allocated to fungi in the fermentation process decreased, whereas the number of sequences assigned to bacteria increased with time of fermentation. In addition, functional metagenomic profiling indicated that a series of sequences related to carbohydrates and amino acids metabolism were enriched. Additionally, enzymes associated with glycolysis metabolic pathways were presumed to contribute to the generation of flavor in dajiang-meju. Proteins from different dajiang-meju samples involved in global and overview maps, carbohydrate metabolism, nucleic acid metabolism and energy metabolism were differentially expressed. This information improves the understanding of microbial metabolic patterns with respect to the metaproteomes of dajiang-meju and provides a powerful tool for studying the fermentation process of soybean products.

Characterization of ML-005, a Novel Metaproteomics-Derived Esterase

A novel gene encoding for a lipolytic enzyme, designated ML-005, was recently identified using a functional metaproteomics approach. We heterologously expressed this protein in Escherichia coli and biochemically characterized it. ML-005 exhibited lipolytic activity toward short-chained substrates with the preferred substrate being p-nitrophenyl-butyrate, suggesting that ML-005 is an esterase. According to homology analysis and site-directed mutagenesis, the catalytic triad of the enzyme was identified as Ser-99, Asp-164, and His-191. Its optimal pH was determined to be at pH 8. Optimal activity was observed at 45°C. It also exhibited temperature, pH and salt tolerance. Residual relative activity after incubating at 50–60°C for 360 min was above 80% of its initial activity. It showed tolerance over a broad range of pH (5–12) and retained most of its initial activity. Furthermore, incubating ML-005 in 1 – 5M NaCl solution had negligible effect on its activity. DTT, EDTA, and ß-mercaptoethanol had no significant effect on ML-005’s activity. However, addition of PMSF led to almost complete inactivation consistent with ML-005 being a serine hydrolase. ML-005 remains stable in the presence of a range of metal ions, but addition of Cu²⁺ significantly reduces its relative activity. Organic solvents have an inhibitory effect on ML-005, but it retained 21% of activity in 10% methanol. SDS had the most pronounced inhibitory effect on ML-005 among all detergents tested and completely inactivated it. Furthermore, the V_max of ML-005 was determined to be 59.8 μM/min along with a K_m of 137.9 μM. The k_cat of ML-005 is 26 s^-1 and k_cat/K_m is 1.88 × 10⁵ M^-1 s^-1.

The Holo-Transcriptome of the Zoantharian Protopalythoa variabilis (Cnidaria: Anthozoa): A Plentiful Source of Enzymes for Potential Application in Green Chemistry, Industrial and Pharmaceutical Biotechnology

Marine invertebrates, such as sponges, tunicates and cnidarians (zoantharians and scleractinian corals), form functional assemblages, known as holobionts, with numerous microbes. This type of species-specific symbiotic association can be a repository of myriad valuable low molecular weight organic compounds, bioactive peptides and enzymes. The zoantharian Protopalythoa variabilis (Cnidaria: Anthozoa) is one such example of a marine holobiont that inhabits the coastal reefs of the tropical Atlantic coast and is an interesting source of secondary metabolites and biologically active polypeptides. In the present study, we analyzed the entire holo-transcriptome of P. variabilis, looking for enzyme precursors expressed in the zoantharian-microbiota assemblage that are potentially useful as industrial biocatalysts and biopharmaceuticals. In addition to hundreds of predicted enzymes that fit into the classes of hydrolases, oxidoreductases and transferases that were found, novel enzyme precursors with multiple activities in single structures and enzymes with incomplete Enzyme Commission numbers were revealed. Our results indicated the predictive expression of thirteen multifunctional enzymes and 694 enzyme sequences with partially characterized activities, distributed in 23 sub-subclasses. These predicted enzyme structures and activities can prospectively be harnessed for applications in diverse areas of industrial and pharmaceutical biotechnology.