Edited by: Eric Altermann, AgResearch Ltd., New Zealand
Reviewed by: William John Kelly, AgResearch Ltd., New Zealand; Diego Mora, University of Milan, Italy
*Correspondence: Avelino Alvarez-Ordóñez, Teagasc Food Research Centre, Moorepark, Fermoy, Cork, Ireland
This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology
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Microorganisms are found throughout nature, thriving in a vast range of environmental conditions. The majority of them are unculturable or difficult to culture by traditional methods. Metagenomics enables the study of all microorganisms, regardless of whether they can be cultured or not, through the analysis of genomic data obtained directly from an environmental sample, providing knowledge of the species present, and allowing the extraction of information regarding the functionality of microbial communities in their natural habitat. Function-based screenings, following the cloning and expression of metagenomic DNA in a heterologous host, can be applied to the discovery of novel proteins of industrial interest encoded by the genes of previously inaccessible microorganisms. Functional metagenomics has considerable potential in the food and pharmaceutical industries, where it can, for instance, aid (i) the identification of enzymes with desirable technological properties, capable of catalyzing novel reactions or replacing existing chemically synthesized catalysts which may be difficult or expensive to produce, and able to work under a wide range of environmental conditions encountered in food and pharmaceutical processing cycles including extreme conditions of temperature, pH, osmolarity, etc; (ii) the discovery of novel bioactives including antimicrobials active against microorganisms of concern both in food and medical settings; (iii) the investigation of industrial and societal issues such as antibiotic resistance development. This review article summarizes the state-of-the-art functional metagenomic methods available and discusses the potential of functional metagenomic approaches to mine as yet unexplored environments to discover novel genes with biotechnological application in the food and pharmaceutical industries.
Recent advances in molecular microbiology have revealed that the microbial world extends far beyond what can be revealed by traditional microbiological techniques. Environments once believed to be devoid of life have now been shown to support the growth of microbes. As a consequence, it is now accepted that microorganisms thrive throughout nature, and that at least some microorganisms can be found in almost all known environments. This is due to the fact that microbial life has adjusted to survive under a wide range of harsh or unaccommodating conditions, resulting in a variety of diverse microorganisms adapted to specific niches. This review article explores the molecular methods that can provide access to these specially adapted microbes and, more specifically, their potentially useful genes/molecules and outlines how these approaches can be harnessed by the food and pharmaceutical industries.
Traditional microbiology generally involves obtaining a pure culture as a major step in any study. However, it is estimated that standard laboratory culturing techniques provide information on 1% or less of the bacterial diversity in a given environmental sample (Torsvik et al.,
Metagenomics presents a molecular tool to study microorganisms
In this review article, functional metagenomics is discussed as an emerging molecular technique with potential applications in industrial settings. An overview of the current methodological strategies employed for functional metagenomic analysis of microbial populations, with emphasis on the use of phenotypic-based metagenomic screens for the discovery of novel small molecules, enzymes, and bioactives is provided. The applications of such compounds to the food and pharmaceutical industries are discussed, while highlighting recent successes in this area.
Metagenomic analyses begin with the isolation of microbial DNA from an environmental sample. The acquired metagenomic DNA specimen should be as pure and of as high quality as possible, and should accurately represent all species present both qualitatively and quantitatively. Direct sequencing of extracted metagenomic DNA, followed by appropriate bioinformatics analyses, can facilitate the elucidation of the functional traits of microorganisms colonizing particular environments (Figure
The initial break from culture-dependent to culture-independent approaches for the microbiological analysis of an environmental sample involved the sequencing of genes encoding microbial ribosomal RNAs (rRNAs). Highly conserved primer binding sites within the bacterial 16S rRNA gene facilitate the amplification and sequencing of hypervariable regions that can provide species-specific signature sequences useful for bacterial identification in an environmental sample (Lane et al.,
Environmental DNA random shotgun sequencing, where total metagenomic DNA is sequenced, assembled and annotated, has been shown to be a more useful tool which may be used to analyse at a molecular/species level the metagenome of an environmental sample. In this instance, the functional potential of a microbial population is revealed by directly sequencing the environmental DNA rather than predicting its functional potential based on 16S rRNA data. Some examples of large scale metagenomic studies involving shotgun sequencing are those carried out by Venter et al. (
Nevertheless, the sequence-based approaches to analysing environmental samples are limited to the study and identification of genes and DNA sequences homologous to those that are already known. Consequently, the possibility of using sequence-based methods for the discovery of proteins encoded by novel sequences is restricted. Phenotypic-based screening of constructed metagenomic expression libraries, described in the next section of the manuscript, is better suited to the unearthing of previously undescribed proteins and small molecules.
Functional metagenomic analyses can be carried out on metagenomic libraries
An alternative option for the identification of novel genes, the Substrate-Induced Gene EXpression screening (SIGEX), was developed by Uchiyama et al. (
Despite the potential usefulness of such systems, phenotypic-based functional metagenomic approaches face a number of complications, to which potential resolutions are currently being devised. To successfully identify a useful gene or protein candidate a series of sequential steps in the cloning and screening process must occur adequately and effectively. Transcription of the entire gene, translation of its mRNA, correct protein folding, and secretion of the active protein from the surrogate host must all be achieved before functional screening even begins. Suitable and efficient screening methods must also be applied to detect the presence of an interesting gene within the metagenomic library. As the probability of identifying a metagenomic clone, among possibly thousands of others, with a specific desired activity is low (Uchiyama and Miyazaki,
One aspect of the methodological approach that can be particularly challenging relates to expressing DNA fragments isolated from microorganisms native to diverse and exotic environments in a relatively domesticated host such as
Certain microbial enzymes are of particular interest to the food and pharmaceutical industries for the catalysis of reactions which may be difficult or expensive to maintain. This interest stems from the fact that there is often difficulty in synthesizing chemical catalysts that truly mimic the complexity of biological enzymes. Many industrial processes are associated with a large environmental burden. Substituting traditional chemical processes used to produce certain compounds or molecules with enzymatic pathways naturally sourced is a more environmentally friendly approach to large-scale production. As microorganisms can catalyze a vast range of reactions, they are an obvious source of enzymes for industrial applications. Several authors have explored this avenue in the last decade (Table
Four lipolytic enzymes | Moderate identity (<50%) to lipolytic proteins from |
Activity based screening of |
Soil from a meadow, a sugar beet field and the Nieme River valley, Germany | Henne et al., |
Low pH, thermostable α-amylase | High sequence similarity to α-amylase of |
Function-based screening of |
Deep sea and acid soil | Richardson et al., |
12 esterases, 9 endo-β-1,4-glucanases, and 1 cyclodextrinase | Various putative source organisms | Functional screening of lambda phage library transformed into |
Rumen of dairy cow | Ferrer et al., |
Three ß-glucanases | Low sequence identities to known ß-glucanases. Other sequences present in one of the inserts showed identity to |
Function-based screening of |
Large bowel of mouse | Walter et al., |
β-agarase | 77% identity to corresponding protein in |
Activity based screening of |
Soil | Voget et al., |
Two esterases | One esterase showed 83% identity to metagenome-derived EstA3 (AAZ48934) and 59% identity to a betalactamase (YP_003266771) of |
Activity based screening of two separate libraries: (plasmid and fosmid) transformed into |
Soil Water | Ouyang et al., |
Two esterases | One esterase showed 51% identity to a class C ß-lactamase from |
Activity based screening of two |
Soil Drinking water | Elend et al., |
Esterase | Unidentified mesophilic soil microbe | Activity based screening of |
Environmental soil samples: mudflats, beaches, forests | Kim et al., |
Thermostable esterase | 64% similarity to an enzyme from |
Activity based screening of |
Mud Sediment-rich water | Rhee et al., |
Two esterases | One esterase showed highest identity (64.9%) to a putative esterase (YP_220901) from |
Activity based screening of |
Surface seawater, South China Sea | Chu et al., |
Six lipolytic clones | The six clones individually showed highest identity to the following proteins: (i) Esterase/lipase (ZP_00034241), |
Activity based screening of |
Forest topsoil | Lee et al., |
Cellulase (β-glucosidase activity) | Low sequence identity to |
Function-based screening of |
Soil | Jiang et al., |
Glycosyl hydrolase | >60% identity to β-1-4-endoglucanase from |
Functional screening of lambda phage library transformed into |
Cow rumen fluid | Palackal et al., |
137 nitrilase genes (Relevant in fine chemical synthesis in drug manufacture) | Varying degrees of amino acid sequence similarity to proteins from several sequence clades within the nitrilase subfamily | A phagemid library expressed in |
Soil Water | Robertson et al., |
Halotolerant and moderately thermostable tannase | New member of tannase superfamily | Activity-based screening of |
Cotton field soil | Yao et al., |
Three carboxylic ester hydrolases | 77% amino acid identity to lipolytic enzyme (AEM45126) from German forest soil-derived metagenomic library | Activity-based screening of |
Forest soil | Biver and Vandenbol, |
Alkaline serine protease | Most closely related to an alkaline protease isolated from |
Activity-based screening of IPTG-inducible vector library expressed in |
Forest soil | Biver et al., |
Fibrinolytic metalloprotease (zinc-dependent) | Amino acid sequence showed 46% identity to metallopeptidase from |
Activity-based screening of |
Mud, Korean west coast | Lee et al., |
Two serine proteases | First novel protease: 52% amino acid identity to a thermophilic alkaline protease from |
Activity-based screening of |
Surface sand from Gobi and Death Valley deserts | Neveu et al., |
Alkaline serine protease | 98% sequence similarity with uncharacterized proteases of various |
Activity-based screening of |
Goat skin surface | Pushpam et al., |
Cold-active lipase | 91% identity to a known lipase from |
Activity based screening of |
Oil-contaminated soil, Northern Germany | Elend et al., |
Moderately thermostable (and thermally activated) lipase | Activity based screening of |
Soil, Brazilian Atlantic Forest | Faoro et al., |
|
Five esterases | Two did not show significant sequence identity to known esterases, the remaining genes showed low to moderate identity to known esterases | Activity based screening of |
Brine: seawater interface, Uranian hypersaline basin | Ferrer et al., |
Thermostable family VII esterase with high stability in organic solvents | 45% identity to |
Activity based screening of |
Compost | Kang et al., |
Alkaline-stable family IV lipase | 83% identity with a cold-active esterase from a deep-sea metagenomic library (ADA70028). 59% identity with an esterase from |
Activity based screening of |
Marine sediment, South China Sea | Peng et al., |
Protease-insensitive feruloyl esterase | 56% identity to predicted esterase from |
Function-based screening of |
China Holstein cow rumen | Cheng et al., |
Xylanase | 44% identity to glycoside hydrolase family protein from |
Function-based screening of |
China Holstein cow rumen | Cheng et al., |
Two UDP glycotransferase (UGT) genes. One is a novel macroside glycotransferase (MGT) | The first one is weakly similar (71% similarity) to hypothetical UGT from |
Thin layer chromatography (TLC)-based functional screening of |
Elephant feces, Hagenbeck Zoo, Germany. Tidal flat sediment, Elbe river, Germany. | Rabausch et al., |
Cold-adapted ß-galactosidase | Highest percentage identities to β-galactosidases from |
Function-based screening of |
Topsoil samples, Daqing oil field, Heilongjiang Province in China | Wang et al., |
Cold-active ß-galactosidase | 53% identity to β-galactosidases from |
Function-based screening of |
Ikaite columns SW Greenland | Vester et al., |
ß-galactosidase | Not available | Function-based screening of |
Not available | Wang et al., |
11 amidase genes (Three novel) | Three novel amidases: the first showed highest identity (54%) to putative isochorismatase hydrolase from |
PIGEX-based screening of benzoate-responsive sensor plasmid library transformed into |
Activated sludge from aeration tank of a coke plant; wastewater treatment plant, Japan | Uchiyama and Miyazaki, |
Periplasmic α-amylase | 100% similarity with |
PIGEX-based screening of maltose-induced plasmid library transformed into |
Cow dung, India | Pooja et al., |
37 genes with lipolytic activity | 29–90% sequence identity to known and putative proteins from numerous different species, including uncultured bacteria | Activity based screening of |
Forest soil, Germany | Nacke et al., |
Novel enzymes from natural sources are extremely useful in food processing reactions. Many of these relate to reactions that occur in nature to process food for energy but are difficult to mimic on an industrial level, e.g., degradation of starch. In other instances, the search has focused on enzymes that can carry out reactions under extreme conditions, which often prevail in food processing, e.g., high temperatures and extremes of pH. Indeed, microbial enzymes are used for brewing, baking, synthesis of sugar and corn syrups, starch and food processing, texture and flavoring, processing of fruit juices, and production of dairy products and fermented foods, among others, either as recombinant enzymes or by using starter cultures with desirable activities. The following are some examples of industrial food processes which have benefited (and may continue to do so) from access to the diverse repository of enzymes possessed by microorganisms.
In the food industry, starch harvested from sources such as maize, wheat, and potatoes is processed to yield food products such as glucose and fructose syrups, starch hydrolysates, maltodextrins, and cyclodextrins (reviewed by van der Maarel et al.,
Lipases and esterases are hydrolytic enzymes which play important roles in the food and pharmaceutical industries. Lipases hydrolyze fats into fatty acids and glycerol at the water lipid interface and reverse the reaction in the non-aqueous phase (Gupta et al.,
Esterases catalyze the hydrolysis of an ester into its alcohol and an acid in aqueous solution. They are distinguished from lipases in that they hydrolyze short-chain over long-chain acylglycerols. In the food industry, esterases are used in fat and oil modification and in the fruit juices and alcoholic beverages industries to produce certain flavors and fragrances, as reviewed by Panda and Gowrishankar (
ß-galactosidases are widely used in the dairy industry for the hydrolysis of lactose to glucose and galactose. Lactose content in milk is reduced to improve taste (lactose is known to absorb undesirable flavors and odors), to accelerate the ripening of cheeses made from treated milk and for the removal of lactose for the production of lactose-free products for intolerant consumers (reviewed by Panesar et al.,
Flavonoids are plant secondary metabolites found in numerous dietary fruits and vegetables and whose consumption is beneficial to human health (Ververidis et al.,
Proteases hydrolyze peptide bonds and therefore catalyze the degradation of proteins. They have numerous uses in the food industry, including the tenderizing of meat (Ashie et al.,
Tannins are naturally occurring water soluble polyphenols which constitute a large percentage of plant material. Tannases catalyze the hydrolysis of tannins, releasing gallic acid, and glucose. Tannases are used in the food industry as a clarifying agent in the manufacture of beverages such as instant teas, fruit juices, beer, and certain wines (Cantarelli et al.,
As with the food industry, the use of microbial enzymes is of particular interest for the biosynthesis of pharmaceutical products previously synthesized
Pederin | >80% identity to sequences from |
Targeted sequencing-based strategy | Piel, |
|
Biotin | Highest identity to proteins from |
Selelction-based screening of enriched cosmid library in |
Horse excrement | Entcheva et al., |
Known siderophore: vibrioferrin | 98% identity to proteins from |
Function-based screening of |
Tidal-flat sediment, Ariake Sea | Fujita et al., |
Polyketide synthase (PKS) gene | 55–59% identity to hypothetical PKS from |
Targeted sequencing-based strategy | Marine sponge |
Schirmer et al., |
Novel serine protease inhibitor (serpin) gene | Moderate identities to serpins from |
Sequence-based screening of |
Uncultured marine organisms | Jiang et al., |
Borregomycin A and B encoded by |
ORFs showing 32–86% identity to species from the following genera: |
Homology guided screening | Soil, Anza-Borrego Desert (CA) | Chang and Brady, |
Hypothetical protein with NF-kB pathway stimulatory activity | 42% of predicted genes coverage to |
Activity-based screening using a reporter cell line of an |
Human gut microbiota of Crohn's Disease patients | Lakhdari et al., |
Novel prebiotic degradation pathways (11 contigs) | Sequence homology to species of |
Hydrolytic activity-based selective screening of two |
Human ileum mucosa and fecal microbiota samples | Cecchini et al., |
Five novel putative salt tolerance genes | Identity to hypothetical proteins from genus |
Function-based screening of |
Human gut microbiota | Culligan et al., |
Novel salt tolerance gene | Not homologous to any sequence at time of study, highest BLAST score to hypothetical protein from |
Function-based screening of |
Faecal sample, healthy 26 year old Caucasian male | Culligan et al., |
15 acid resistance genes | 37–90% identity to proteins and hypothetical proteins from the following genera: |
Function-based screening of six |
Planktonic and rhizosphere microbial communities of the Tinto River. Five libraries from |
Guazzaroni et al., |
Walter et al. (
The development of novel therapeutic strategies relies heavily on gaining a better understanding of human commensals and host-microbe relationships. Lakhdari et al. (
Maintaining gut microbiota homeostasis has been shown to contribute to the overall sustaining of human gut health. Probiotics are an oral infusion of high numbers of live beneficial gut microbes formulated into various yogurts and dairy beverage products that, when ingested in adequate amounts, confer a health benefit on the host (Joint,
Another avenue to maintain human gut health is to promote the growth of beneficial bacteria already present in one's lower GI tract through the use of prebiotics. Prebiotics are non-digestible oligosaccharides (NGOs), usually present in plant material, that are resistant to human digestion in the upper GI tract and are hydrolyzed in the gut by beneficial microbiota to produce SCFAs and organic acids that provide nutritional value to the human host (Gibson and Roberfroid,
A major driving force behind the biotechnological applications of functional metagenomics is the search for novel antimicrobials effective in medical settings. Microorganisms produce antibiotic molecules to alleviate competitors in their natural habitat. Natural sources have proved fruitful in the past for providing antibiotic molecules, from the discovery of penicillin produced by
Long-chain |
No identity to bacteria cultured at that time. Some similarity to predicted proteins from |
Activity-based screening of |
Seven soil samples, Ithaca, NY Boston, MA Costa Rica | Brady et al., |
Highest similarity to hypothetical protein (MJ1207) from |
Activity-based screening of |
Soil | Brady and Clardy, |
|
Two isocyanide biosynthetic genes encoding isocyanide-containing antibiotic | Not available. Some identity to known and predicted proteins | Activity -based screening of |
Soil, Boston, MA | Brady and Clardy, |
Violacein biosynthetic gene cluster | Moderate identity to |
Activity -based screening of |
Soil, Ithaca, NY | Brady et al., |
Two ORFs within a clone encoding a transcriptional regulatory protein and a putative indole oxygenase | The indole oxygenase-like protein showed high identity to naphthocyclinone hydroxylase (NcnH) from |
Activity -based screening of |
Forest topsoil, Jindong Valley, Korea | Lim et al., |
Turbomycin A, B | The ORFs encoding the turbomycins A and B show 53% identity to legiolysin from |
Activity-based screening of |
Soil | Gillespie et al., |
Uncharacterized protein with antimicrobial activity | Low to moderate sequence identity (26–58%) to proteins and hypothetical proteins from |
Activity-based screening of |
Soil sample from a deciduous forest, Belgium | Biver et al., |
Novel chitinase with chitobiosidase activity (identified by the sequence-based approach) | 45% identity to chitinase from an uncultured bacterium (Uchiyama and Watanabe, |
Targeted sequence-based analysis and activity-based screening of |
Soil, Swedish University of Agricultural Sciences, Uppsala, Sweden | Hjort et al., |
Six clones with antimicrobial activity: two with cell wall-degrading activity, three proteases and a lipolytic enzyme | 54–31% identity to known amidase, lytic transglycosylase and proteases from |
Activity-based screening of broad-host cosmid shuttle vector library expressed in |
Soil, Sonoran Desert, Arizona, USA | Iqbal et al., |
Six clones encoding a lysostaphin gene | All six clones expressed the lysostaphin gene from the |
High throughput activity-based screening of |
Library derived from three native staphylococcal strains: |
Scanlon et al., |
Two novel lactonases | One had 53% similarity to amino acid sequence from |
Activity-based screening of |
Soil, University of Göttingen, Germany | Schipper et al., |
Clone expressing NAHL-lactonase activity | Most closely related to Zn-dependent hydrolase from |
Functional-based screening of |
Pasture soil, France | Riaz et al., |
Two novel pairs of LuxR/LuxI genes | QS pair 1: LuxI homolog: 42% amino acid similarity to putative LuxI in |
Activity-based screening of two fosmid libraries expressed in a biosensor |
Activated sludge from a coke plant, Japan. Forest soil samples, Tsukuba city, Japan | Nasuno et al., |
Novel bacterial NAHLase | Most likely belonging to species of unknown Proteobacterium | Activity-based screening using an |
Rhizosphere of |
Tannieres et al., |
Three novel pair of LuxR/LuxI genes | QS pair 1: 47% identity to |
Activity-based screening using an |
Activated sludge Soil | Hao et al., |
Novel NADP-dependent short-chain dehydrogenase/reductase | 61% identical to chromosome segregation protein SMC in |
Activity-based screening of |
Soil, University of Göttingen, Germany | Bijtenhoorn et al., |
Novel florfenicol and chloramphenicol resistance gene | 33% amino acid identity to drug resistance transporters from |
Function-based screening of |
Soil samples from an island in the Tanana River near Fairbanks, Alaska | Lang et al., |
Two novel genes conferring resistance to kanamycin and ceftazidime | Both showed highest similarity to uncultured soil microorganisms | Activity-based screening of |
Soil from apple orchard, southern Wisconsin | Donato et al., |
Resistance genes to chloramphenicol, ampicillin and kanamycin. Multidrug resistant clone conferring ampicillin and kanamycin resistance | Multidrug resistant clone showed highest identity (95%) to a ß-lactamase from |
Functional screening of metagenomic BAC, plasmid, and phagemid vector libraries expressed in |
Activated sludge | Parsley et al., |
Novel chloramphenicol hydrolase (resistance to chloramphenicol and florfenicol) | 14 ORFs varying in similarity (30–77%) to corresponding proteins from known microorganisms. Highest similarity overall to proteins from the bacterial phylum |
Activity-based screening of |
Alluvial soil | Tao et al., |
Novel carboxylesterase | Highest identity (58%) to ß-lactamase (YP_004154831) from |
Activity-based screening of |
Soil from the Upo wetland, South Korea | Jeon et al., |
31 previously undescribed antibiotic resistance genes to ampicillin, amoxicillin, tetracycline, and penicillin. This includes class A and C β-lactamases and six different tetracycline resistance genes | Significant similarity to proteins from multiple genera from the ARDB and GenBank databases | Activity-based screening of |
Fecal samples of Herring gulsl, Appledore Island, ME and Rochester, NH, USA | Martiny et al., |
39 clones conferring resistance to kanamycin, gentamicin, chloramphenicol, rifampin, trimethoprim, and tetracycline | Highest homology to the following phyla: |
Activity-based screening of |
Urban soil, Seattle, WA, USA | McGarvey et al., |
110 antibiotic resistance genes conferring resistance to ß-lactams, aminoglycosides, amphenicols, sulfonamides, and tetracyclines, including 55 ß-lactamases | 18 resistance genes showed 100% identity to known human pathogens | Activity-based screening of metagenomic library expressed in |
11 soil samples, USA | Forsberg et al., |
95 unique antimicrobial resistance eDNA inserts. 10 novel β-lactamase gene families | Average of 69.5% nucleotide identity to GenBank sequences. 15 β-lactamase resistance genes showed high identity (>90%) to known human pathogens | Activity-based screening of metagenomic library expressed in |
Human saliva and fecal samples | Sommer et al., |
A novel kanamycin resistance gene fusion (to a hypothetical protein domain) | N-terminus was 42% identical to AAC(6') from |
Activity-based screening of |
Four human fecal samples | Cheng et al., |
45 clones resistant to tetracycline, minocycline, aminoglycosides, streptomycin, gentamicin, kanamycin, amikacin, chloramphenicol, and rifampicin | 26–92% similarity to known proteins in the GenBank database | Activity-based screening of |
Four agricultural soil samples, China | Su et al., |
Five clones conferring Fluoroquinolone resistance, cephalosporin resistance, and trimethoprim resistance | High similarity to homologs in species of |
Activity-based screening of two |
Retail spinach | Berman and Riley, |
Ampicillin resistance and kanamycin resistance | Homology to |
Activity-based screening of an |
Mozzarella di Bufala Campana (MBC) Cheese, produced in Central and Southern Itlaly | Devirgiliis et al., |
Certain cell-to-cell communication or quorum sensing molecules and agents with quorum sensing inhibitory (QSI) activities have been also discovered through function-based screening of metagenomic libraries (Table
Certain antimicrobial strategies used in clinical settings could also be applied to the control of bacterial persistence in food development and manufacturing processes. In industrial settings contamination of food products occurs at various stages throughout the food processing cycle. The raw food itself is usually a source of initial contamination. Food can also become contaminated or re-contaminated during its processing, e.g., re-contamination of milk post-pasteurization, resulting in an unsafe or spoiled product. The removal of harmful or spoilage microorganisms from food products and the prevention of microorganisms entering or persisting in food processing is highly desirable. This needs to occur without damaging the structure, texture, taste, and overall quality of food. A potentially powerful application of functional metagenomics with respect to the food industry is screening natural sources for bioactive molecules that function as antimicrobials or inhibitory compounds for use in food safety maintenance strategies. Once the compounds have been identified and mass produced, the ultimate goal is for them to be formulated into safe sanitization products that will not influence the quality of the food product. As microorganisms are widely used and often beneficial to the food industry (e.g., cheese manufacture, brewing), the aim would be to eliminate only those microorganisms which pose a threat to food safety and quality. Screening is performed in a targeted manner to identify isolates producing compounds that inhibit or eliminate the presence of a given problematic microorganism present in the food product or processing equipment. Due to their specificity, bioactives isolated from microorganisms may be used in combination with existing sanitization products. Extremophiles are of particular interest as these could target undesirable microorganisms in extreme environments, which are often present in food processing.
Functional metagenomics can be used to combat antimicrobial resistance via two strategies; through the discovery of novel antibiotics and anti-infectives (as mentioned above) and through the identification of resistance genes in microbial populations. As resistance is transferable, horizontal gene transfer (HGT) being the most common method by which resistance is acquired by previously susceptible strains, resistant genes possessed by environmental bacteria may be acquired by human pathogens. Functional metagenomics can be used to identify novel resistance mechanisms used by bacteria in nature which may not have manifested in the clinical setting yet and so can allow one to predict possible routes
Unusual or unexpected antimicrobial resistance mechanisms can be found in nature. Some studies investigating the resistome of uncultured bacteria have explored areas and environments which have not been previously exposed to clinical antibiotics and where endogenous microorganisms have therefore not faced selective pressure to develop antibiotic resistance. A recent study by Fouhy et al. (
Metagenomics grants access to the huge diversity of the microbial world and has led to significant progress among research communities and in industrial settings with respect to understanding and benefitting from unculturable microbes. Functional metagenomics is a powerful tool for the discovery of novel enzymes and bioactives sourced from as yet uncultured microorganisms. As a relatively new technology, functional metagenomics faces challenges that have yet to be overcome. However, the promise of a technique that has already proven to be fruitful even in its early years suggests that there can be significant rewards if appropriate solutions and further optimization takes place. The development of new screening and selection techniques along with faster and cheaper sequencing technologies will allow for the expansion of a very promising field in microbiology, genetics and the food and pharmaceutical industries.
This article discusses the potential of functional metagenomics to facilitate the development of novel industrial products sourced from as yet uncultured microorganisms. Nonetheless, following the identification of useful proteins and bioactives, challenges ensue in another area, that being the development of a consumer friendly and commercially viable product that can be manufactured in industrially relevant quantities, retains its activity when scaled up (for example when present in high amounts in a large industrial reaction vessel), can be purified and formulated appropriately into a finished product and maintains its stability during shipping and storage. The product also needs to be reasonably easy to use and must be applicable to current industrial demands, i.e., the product must perform efficiently under the proposed/outlined conditions to carry out the job it was bought to do. A successful reaction achieved under laboratory conditions may be difficult to reproduce on an industrial scale. Pilot plant studies must be carried out initially to identify any variables or short comings in the reaction that were not evident at the laboratory stages of development. These studies are a stepping stone between discovery of the interesting active agent and its formulation into a final commercial product. Once deficiencies and other problems have been corrected in the pilot plant phase, further studies must be conducted to qualify the agent at an industrial level and guarantee the development of a robust product that is efficient and true to its intended purpose. The acceptability of the novel enzyme or bioactive and its source microorganism to the relevant regulatory authorities must also be considered.
Once all these limitations are overcome, through access to the seemingly infinite diversity of the microbial world, functional metagenomics presents an opportunity to develop novel innovative products that offer something new and useful to industrial processes or even change for the better or make more convenient the way a current process is carried out.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The financial support of Science Foundation Ireland (SFI) under Grant Number 13/SIRG/2157 is acknowledged.