Marine Metagenomics As a Source for Bioprospecting

MARGEN-00353; No of Pages 10 Marine Genomics xxx (2015) xxx–xxx

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Marine Genomics

journal homepage: www.elsevier.com/locate/margen

Marine metagenomics as a source for bioprospecting

Rimantas Kodzius a,c,d,⁎,TakashiGojoboria,b,d a Computational Bioscience Research Center (CBRC), Saudi Arabia b Biological and Environmental Sciences and Engineering Division (BESE), Saudi Arabia c Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE), Saudi Arabia d King Abdullah University of Science and Technology (KAUST), Saudi Arabia article info abstract

Article history: This review summarizes usage of genome-editing technologies for metagenomic studies; these studies are used Received 31 March 2015 to retrieve and modify valuable microorganisms for production, particularly in marine metagenomics. Organisms Received in revised form 15 June 2015 may be cultivable or uncultivable. Metagenomics is providing especially valuable information for uncultivable Accepted 1 July 2015 samples. The novel genes, pathways and genomes can be deducted. Therefore, metagenomics, particularly Available online xxxx genome engineering and system biology, allows for the enhancement of biological and chemical producers and the creation of novel bioresources. With natural resources rapidly depleting, genomics may be an effective Keywords: ﬁ ﬁ Microorganism way to ef ciently produce quantities of known and novel foods, livestock feed, fuels, pharmaceuticals and ne Producer or bulk chemicals. Bioprospecting © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license Metabolic engineering (http://creativecommons.org/licenses/by/4.0/). Genetic engineering Synthetic biology

Contents

1. Introduction...... 0 2. Metagenomicsasatooltostudytheenvironment...... 0 2.1. Diversityofmicroorganisms...... 0 3. Bioprospecting—theprocessofdiscoveryandcommercializationofnewproductsbasedonbiologicalresources...... 0 3.1. Sequence-basedscreening...... 0 3.2. Assessmentofmetabolicpotentialbyfunction-basedscreening...... 0 4. Metabolicengineeringasatoolforcellfactories...... 0 4.1. Establishedproductionstrains...... 0 4.1.1. E. coli asaproducer...... 0 4.1.2. Algaeasaproducer...... 0 4.1.3. S. cerevisiae asaproducer...... 0 4.2. Toolstoimprovethefunctionofstrains...... 0 4.2.1. Geneticengineeringusingmolecularbiologytools...... 0 4.2.2. Neworganismscreatedbysyntheticbiology...... 0 5. Conclusion/outlook...... 0 References...... 0

1. Introduction

Microbes are ubiquitous and an essential part of all life on Earth. They may be considered a major bioresource, acting as powerful chemical factories that transform environmental chemicals (carbon, hydro- ⁎ Corresponding author at: King Abdullah University of Science and Technology, gen, nitrogen, oxygen, phosphorus and sulfur) into more biologically Thuwal 23955-6900, Saudi Arabia. E-mail addresses: [email protected] (R. Kodzius), accessible molecules, which are then used by higher organisms [email protected] (T. Gojobori). (Adkins et al., 2012). All higher life forms, including plants and animals,

http://dx.doi.org/10.1016/j.margen.2015.07.001 1874-7787/© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Please cite this article as: Kodzius, R., Gojobori, T., Marine metagenomics as a source for bioprospecting, Mar. Genomics (2015), http://dx.doi.org/ 10.1016/j.margen.2015.07.001 2 R. Kodzius, T. Gojobori / Marine Genomics xxx (2015) xxx–xxx host over orders of magnitude from millions to trillions of microbes. Some to a mosaic of multiple populations (Sharon and Banfield, 2013; Culley make necessary nutrients and vitamins or help to digest and convert food. et al., 2006). By simplifying the complex environmental population Microbes also benefit the environment by removing contaminants and “composite genomes,” can be obtained and sequence variation can be pollutants from soil, groundwater, sediment and surface water. However, studied (Allen and Banfield, 2005)orgenomecontentscanbeinferred our understanding of these complex communities remains limited. (Tyson et al., 2004; Martin et al., 2006). Perhaps not surprisingly, Marine environments comprise over 70% of the earth's surface, rang- less complex communities were obtained from samples of extreme en- ing from habitats in the freezing Arctic and Antarctic to the warm vironments such as acid mines (high acidity) and thermal geysers (high waters of the tropics. Microorganisms thrive throughout oceans, temperature) (Zarraonaindia et al., 2013). Communities can be further reaching depths of 11,000 m (mean depth 3200 m), with pressures fractionated by cell size (filtration through defined pore size filters), exceeding 100 MPa and temperatures higher than 100 °C in deep-sea DNA composition (GC% gradients), flow cytometry (fluorescence hydrothermal vents (Kennedy et al., 2010). Typically, they associate activated cell sorting), affinity purification or by particular metabolic with other organisms: countless communities comprise bacteria, processes (Suenaga, 2012). Recent advancements permit the isolation archaea, protists, fungi and viruses. Furthermore, single-celled and of single cells that can be lysed to extract genomic DNA (or RNA) multicellular microorganisms are responsible for 98% of primary followed by amplification and sequencing. Single-cell genomics is an productivity in marine ecosystems, making them integral to marine emerging method, getting more and more popularity due to the food chains and specifically to carbon and energy cycles (Sogin et al., constantly lowering sequencing costs (Kodzius and Gojobori, accepted 2006). Their evolution over the past 3.5 billion years has produced a for publication). Quake sequenced five single cells of an ammonia- high diversity in genetic and phenotypic variation. Marine meta- oxidizing archaea Nitrosoarchaeum limnia isolated from low-salinity genomics is, therefore, an excellent tool for reading the abundance of sediments in the San Francisco Bay (Blainey et al., 2011). By combining novel genetic information and unlocking the immensity of metabolic single-cell genomic and metagenomic approaches a high-quality draft diversity available from microorganisms. genome revealing features unique to N. limnia's low-salinity environment was obtained. Because in single-cell genomics, genes expressed 2. Metagenomics as a tool to study the environment in the cell can be decoded and complete metabolic pathways can be established in a single genome (rather than in multiple distinct Antonie van Leeuwenhoek observed single-celled organisms discov- genomes), Quake could prove that N. limnia uses a modified version of ering microorganisms using microscopic lenses already in the 17th the 3-hydroxypropionate/4-hydroxybutyrate pathway for carbon century. Now, microbes are used by industries to cultivate various live- fixation (Blainey et al., 2011). While computational tools can help to stock feeds and nutrients; they are also used as energy sources and in solve certain scientific questions, the combination of metagenomics the production of pharmaceuticals. In the late 20th century, prokaryotic and single-cell genomics on a sample undoubtedly provides the communities were typically deciphered using 16S rRNA gene sequenc- means to more easily assemble contigs and a clearer view of the data. ing from total genomic DNA extracted from the whole community. For example, the combined single cell/metagenomic approach enabled Moreover, 18S rRNA gene sequencing was introduced to translate the Quake to test the single cell assemblies for completeness and the eukaryotic community (Rivas et al., 2004). metagenome for contamination (Blainey et al., 2011). Of course, the sample handling, storage and choice of DNA extraction At present, there is a shift from a gene-centric towards a more method have impact on the final multiple community genomic DNA organism-centric approach to encompass community genomics (i.e., representation. The environmental strains can vary in yield of DNA ecogenomics or environmental genomics) (DeLong et al., 2006; following even the same extraction protocol. The disruption of the cell Worden et al., 2006; McMahon, 2015). For example, DeLong et al. depends on the cell wall structure. For example, it is known that used sequence variation to analyze surface to near sea-floor depths of Gram-positive bacteria have a much thicker layer (20–80 nm) of pepti- planktonic microbial communities in the North Pacific Subtropical doglycan that encircles the cell, compared to Gram-negative bacteria Gyre (DeLong et al., 2006). From the genetic material obtained, they (10 nm). Additionally teichoic acid in Gram-positive bacteria stabilizes were able to infer both phylogeny and function of the material collected, the cell wall and makes it stronger. While it is relatively simple to dis- including uncultivable microbes. Knowledge gained from comparative rupt the Gram-negative cells (for example by bead-beating), additional genomic analysis of microbial communities provides insight freezing and thawing are used for more efficient disruption of Gram- into higher-order community organization and dynamics. McMahon positive bacterial envelope. Chemical and enzymatic lysis methods are recognizes the importance of generating the draft genomes from used in combination with mechanical and temperature control to weak- metagenomes, then pairing these reference genomes with the en and disrupt the cell wall (El Bali et al., 2014; Wesolowska-Andersen metatranscriptome datasets. Summarizing the current advancements, et al., 2014). The spores, yeast and mycobacteria are even more difficult McMahon calls all these “Metagenomics 2.0” (McMahon, 2015). Interest to break, as the cell wall is more complicated than Gram-negative and is also growing in “high-resolution genomics”, where multiple Gram-positive bacteria (Vingataramin and Frost, 2015). The extraction metagenomic samples (usually from the same source) are sequenced, methods are adapted to deal with the presence of possible inhibitors in and sequencing reads are assembled into genes. The groups of genes the soil (such as humic acids), also metabolites of the cells (Greco et al., that covary in abundance are thought to belong to the same genome 2014). There are additional challenges with possibility to gain additional (Mick and Sorek, 2014). For example, the covariation of gene abundance information by separately isolating intracellular and extracellular DNAs can be used to resolve a structure of a complex microbial sample. (Alawi et al., 2014). To increase the sample processing throughput, auto- The reconstruction of whole genomes that is possible using data mated DNA extraction platforms are offered by several companies. An ar- from metagenomics enables not only sequencing of complete genes ticle by Oldham et al. describes a comparison of such platforms for the and metabolic pathways, but also the construction of evolutionary extraction of DNA from seawater and oil samples (Oldham et al., 2012). trees. The combination of deep sequencing and bioinformatic While amplicon sequencing is still the dominating method, we approaches allows for metagenome-based genome recovery, even foresee that with the development of next generation sequencing from very complex systems. For example, both bacterial phylum TM7 methods, the standard will be to conduct shotgun sequencing of micro- and phylum bacteriodetes were assembled separately into a single bial community DNA and cDNA (to access expressed genes) (Tringe continuous sequence (one contig), basically as a single circular chromo- et al., 2005). Shotgun metagenomic sequencing allows not only the some that is complete genome. The relative metagenome abundance of sequencing of microbial, eukaryotic and archaeal genomes, but also of the completely assembled TM7 and bacteriodetes is ~(0.47–1.58)% viral genomes. In 2006, Culley et al. analyzed coastal RNA viral commu- (Albertsen et al., 2013). In addition, complete genomes have been nities. However, assembly of sequenced reads was problematic and led obtained from organisms that constitute ~1% of the community in

Please cite this article as: Kodzius, R., Gojobori, T., Marine metagenomics as a source for bioprospecting, Mar. Genomics (2015), http://dx.doi.org/ 10.1016/j.margen.2015.07.001 R. Kodzius, T. Gojobori / Marine Genomics xxx (2015) xxx–xxx 3 oceans, sediments and even from the adult human gut (Sharon and a niche of favorable conditions, recently discovered extremely large Banfield, 2013; Albertsen et al., 2013). Although genomes can be obtain- DNA viruses such as the pandoravirus and the mimivirus, which are ed from uncultivable cells, the average genome completeness is lower considered to exist in a parasitic fourth domain (Claverie, 2013; than that for cultivable cells. Rinke et al. recovered 201 partial genomes Philippe et al., 2013). By mining the Global Ocean Sampling environ- with 40–55% genome completeness, ranging from a few percent to mental sequence database, the closest relatives to Mimivirus were greater than 90% (Rinke et al., 2013). The variation may be attributed found in the sea (Claverie, 2013). to the bias of the single cell DNA amplification reaction — freshwater and marine samples yielded the highest percentages of successfully am- 3. Bioprospecting—the process of discovery and commercialization plified genomes (up to 40%), whereas the success rates for soil samples of new products based on biological resources tended to be low (b10%) (Rinke et al., 2014). Single-cell genome sequencing is a complimentary approach to metagenomics (Kodzius Metagenomics is not a new tool in the science. It is already and Gojobori, accepted for publication; Rinke et al., 2013; Kashtan established in the scientific field, revealing secrets of the earth's micro- et al., 2014). We expect that single-cell genomics will improve by parallel bial communities. In addition to studies of microbial taxonomic diversi- sequencing a few of the same cells, better covering fragmented genomes. ty, ecology and evolution, metagenomics is an important tool for It has been suggested that genomes with possible variations be stored as environmental resources (earth and life sciences, bioenergy, bioremedi- reference genomes rather than as individual sequences. This would allow ation, and biotechnology), agriculture (food production and safety), easier storage, handling of the data and genome comparison for the devel- biomedicine (biomedical sciences, biotechnology, biodefense and opment of evolutionary trees (Kahn, 2011; Nelson et al., 2010). Because microbial forensics), sustainability and ecology (N.R. Council, 2007). most microbes cannot be predictively cultured, rRNA phylotyping and metagenomics are favorable approaches to explain the microbial commu- 3.1. Sequence-based screening nity thriving in a particular environment. In a sequence-driven analysis, the PCR primers are designed based 2.1. Diversity of microorganisms on conserved DNA sequences. The metagenomics library is cloned into vector DNA and transformed into the producer. The clones are screened Using metagenomics, the genes and pathways of both cultivable and for the sequence of interest (Schloss and Handelsman, 2003). Of course, uncultivable organisms can be discovered. Estimates from deposited such sequence-driven approach has limitation. We can expect more total 16S rRNA sequences indicate that cultivable organisms constitute novel information obtained by sequencing environmental samples much less than 1% (12,000) (Yarza et al., 2013; Cole et al., 2014)ofan without prior knowledge on known sequences in databases. For exam- estimated total microbial populations (4 million) (Quast et al., 2013). ple, metagenome sequencing data from bacterial communities helps to Prokaryotes may comprise 106 to 108 separate genospecies (Sleator identify genes that encode for natural products. Global sequencing of et al., 2008). Konstantinidis recommended that prokaryotic organisms samples to assess biosynthetic diversity has indicated that the biosyn- be classified (especially the uncultivable) and that their vast but finite thetic potential of microorganisms remains untapped, particularly diversity be described using metagenomics (Konstantinidis and because a large number of producers are uncultivable (Zhang and Rosselló-Móra, 2015). There have been some studies to assess the envi- Moore, 2015; Wilson et al., 2014). Often the potential producers are ronmental sample diversity. A study by Zachary Charlop-Powers et al. cohabitating in the closed environment. This can be observed in the have investigated soil samples from around the world and found that marine environment, such as microbial symbionts in sponges (Zhang there is little overlap between samples collected from different global et al., 2015)orcorals(Lema et al., 2012). Wilson et al. used single- locations (less than 3%); the strongest sequence homology was detected cell- and metagenomic-based approaches to discover a group of in samples collected in close proximity (Zhang and Moore, 2015; producers known as Entotheonella. The candidate genus Entotheonella Charlop-Powers et al., 2015). Kashtan et al. applied metagenomics and is a co-inhabitant of the chemically and microbially rich marine sponge single-cell genomics by sequencing 90 individual cell genomes on the Theonella swinhoei. The Entotheonella producer DNA was detected by globally abundant marine cyanobacterium Prochlorococcus in Bermuda PCR primers specific for genes encoding the respective pathways. The (Kashtan et al., 2014). A cell-by-cell genomic diversity assessment authors proved that a single member of the highly diverse microbiome evidenced the coexistence of Prochlorococcus subpopulations, where of the sponge host T. swinhoei is the source of almost all the polyketides they maintained a relatively stable population size in highly mixed and peptides that have been isolated from this sponge (Wilson et al., habitats (Kashtan et al., 2014).Using metagenomics approach, there is 2014). no need to isolate or cultivate the microorganisms. Directly isolated Using a metagenomic library (Fig. 1) simplifies the discovery of nuclei acids provide information on the metabolic and functional genes. In fact, it has facilitated the discovery of many novel enzymes capacity of a specific microbial community (Simon and Daniel, 2011). and biocatalysts from uncultivable bacteria. There are two main strate- Metatranscriptomics helps to explain which metabolic pathways and gies to identify and assign sequence tags to the related species genes are expressed in a given place at a given time. In parallel, it is (Sharpton, 2014). In binning, every metagenomic sequence is assigned possible to prepare and sequence both genomic DNA and total RNA to a taxonomic group. It is done through comparison to the referential libraries, and there are several reports on metatrascriptome studies data or clustering into groups based on shared characteristics (such as performed on samples taken from marine waters (Mason et al., 2012; GC content). In assembly, the sequencing reads are assembled by possi- Poretsky et al., 2009; Shi et al., 2009). Going forward, we believe that bly generating longer sequences, allowing later easier mapping and standard sample collection and processing protocols will include not bioinformatics analysis. Here the strain or species can be identified in only the analysis of DNA, but also of RNA, proteins and metabolites. In metagenomes using genome-specific markers, such as k-mers this way not only the taxonomic, but also functional diversity of the (Tu et al., 2014). After the sequence pre-processing and clustering, environmental communities, as well as the expressed genes and bioinformatics is used for gene prediction and for further functional metabolic activity in the chosen environment can be assessed. annotation (Richardson and Watson, 2013). Resolving and quantifying Metagenomics goes hand in hand with next generation sequencing taxonomic diversity allows to understand the biological function of and high-performance supercomputing, all of which enable broad the community, as the presence of specific species will indicate the access to microorganism diversity and function (Knight et al., 2012). function of described taxa. We envision improved bioinformatics Metagenomics is a useful tool to explore and discover the unknown. analysis by combination of short reads (such as Illumina) with long It is believed that there are other undiscovered branches on the tree of ones (for example from Pacific Biosciences), allowing better species life (Woyke and Rubin, 2014). While the RNA world may still exist in identification and gene prediction.

Fig. 1. The discovery process involves marine sampling, DNA sequencing and contig generation. Previously unknown genes, pathways and even whole genomes are being discovered.

The development of commercially available compounds favors the 3′-ends of a gene can be sequenced by high-throughput methods to use of large sequence databases (Sugawara et al., 2008; Kodama et al., recover many clusters and discover a large variety of genes (Iwai et al., 2012; Kryukov et al., 2012) to look for previously unknown membrane 2010). proteins, antibiotics and especially enzymes (Gabor et al., 2004; Gupta et al., 2002). Enzymes are used by industries in foods, agriculture and 3.2. Assessment of metabolic potential by function-based screening livestock feed, paper and leather production, textile processing, deter- gents, personal care products, as well as in the production of fine and In sequence-based screening, the isolation of newly discovered bulk chemicals (DeSantis et al., 2002). enzymes is based on homological sequences, which often reveal only While newly discovered enzymes and other useful biomolecules can partial sequences: it is limited to known sequences of interest that do be found in metagenomic sequence reads and assembled contigs, a not allow for the discovery of information about the biochemical func- sequence-based approach is to design DNA primers derived from tions of the encoded enzymes. Activity-based assays can be performed conserved regions, amplifying the variety of novel variants of proteins to isolate genes that encode for novel biomolecules or biological activi- by PCR. Numerous genes have been found to encode for several newly ties. This “function-based screening” uses metagenomic libraries discovered enzymes such as nitrile reductases, chitinases, dioxygenases, constructed in expression vectors to express in a chosen host; sequence hydrogenases, glycerol dehydratases and specific enzyme-degrading information is not required. On the other hand functional screens enable compounds (Simon and Daniel, 2011). In the absence of sequencing, the identification of novel gene classes that encode for previously quantitative PCR alone can be used to analyze the diversity and abun- unknown or known functions (Ferrer et al., 2009; Handelsman, 2005; dance of certain genes. For example, Zaprasis found and quantified Riesenfeld et al., 2004). However, function-driven approaches are (per gram of soil) many previously unknown herbicide-degrading much slower because genes must be expressed in a selected vector, dioxygenases by quantitative PCR (Zaprasis et al., 2010). This is done where enzymes are ensured to be correctly folded. Although function- by designing the degenerated primer sets from conserved regions of based approaches are becoming more popular, their set-up and devel- genes of interest (such as dioxygenase). While the quantitative PCR is opment are time consuming and tedious; and because hit rates are a tool to analyze the gene expression of certain genes, the analysis of low, high-throughput screening is required. Miniaturization and the certain genes might well be used for diversity studies of process- application of microfluidic technologies are key to the success of geno- associated bacteria, determining the diversity of genotypes represented mics in the future (Wu et al., 2012, 2014; F.Q. Li et al., 2014). Reliable in gene libraries (Zaprasis et al., 2010). Furthermore, PCR can be and sensitive enzymatic assays also require sophisticated substrates combined with high-throughput sequencing, which allowed Varaljay and highly sensitive analytical methods (such as high-performance to obtain 62,000 sequences gathered into N700 clusters of environmen- liquid chromatography) to detect biomolecules. On the other hand, tal dimethylsulfoniopropionate demethylase (dmdA) sequences function-based screening permits the detection of clones that contain (Varaljay et al., 2010). This was all done using primers designed from previously unknown, active enzymes, from which conclusions about the DNA of one free-living marine bacterioplankton. Because PCR prod- enzyme physicochemical parameters and activities can be drawn ucts are of limited size and sequencing usually reveals only incomplete (Rabausch et al., 2013; Parachin and Gorwa-Grauslund, 2011). Subse- gene sequences, Iwai et al. introduced “gene-targeted metagenomics” quently, protein engineering through in vitro evolution can be used to to recover full versions of the target genes. They did this by designing create enzymes with improved properties by mutational exploration probes from collected sequence information from which the 5′-and and selection of the best candidates.

In addition to enzymes, compound screens have also been shown to building blocks), fuels and bulk chemicals (ethanol, solvents, polymer be successful. For example, a study that combined single-cell- and building blocks and feed additives like amino acids). metagenomic-based approaches discovered that the bacterial symbiont Entotheonella species expresses unique chemical bioactive compounds 4.1.1. E. coli as a producer including bioactive polyketides and peptides (Wilson et al., 2014). E. coli is a well-studied organism with a complex system of 4627 genes, 5827 regulatory interactions (including transcription initiation, 4. Metabolic engineering as a tool for cell factories transcription attenuation, regulation of translation and enzyme modulation) and 2528 unique compounds (Keseler et al., 2013; Feist 4.1. Established production strains et al., 2007); its metabolism is well understood. E. coli is an ideal candidate for both metabolic engineering and industrial-scale production of Industries are using various strains of bacteria, yeast and algae to desirable bioproducts. E. coli encompasses excellent properties such as deliver valuable products such as cheese, wine and beer as well as rapid doubling time and growth rate, facilitation of high-cell-density other biotechnological and pharmaceutical products on a large scale. fermentation and low-cost production (Chen et al., 2013). E. coli is For this reason, cost-saving approaches have the potential for a huge im- known for the production of various biofuels (hydrogen, bioethanol, pact on industries. Before the 1990s, microorganisms were genetically 1-butanol, isopropanol, 1-propanol, acetate, pyruvate, lactic and modified by chemicals, and the mutant strain that overexpressed the succinic acids); amino acids (phenylalanine, threonine, tryptophan, desired metabolite was used in production. However, random mutation tyrosine and valine); sugars and alcohols (mannitol, xylitol); diols and is problematic because the modified genes or DNA location was not polymers (such as precursors for polyesters) (Chen et al., 2013). As known, and untargeted pathways were affected (Torres and Voit, biosynthetic pathways in microorganisms thriving in marine waters 2002). Other early technologies used the random insertion of specific are uncovered, we will likely see E. coli used more and more as a genes into a living cell. This blind insertion method is similarly limited chemical producer. Ongley demonstrated a high-titer heterologous by unknown effects on unrelated pathways and subsequent unwanted production of lyngbyatoxin in E. coli, a protein kinase C activator from effects. Any changes in cell metabolic pathways may have drastic effects an uncultivable marine cyanobacterium (Ongley et al., 2013). The on the viability of the cell (Vemuri and Aristidou, 2005). With the following are a few examples of companies using E. coli to produce advancement of genome engineering and genome-editing technologies, high volumes of various metabolites for industrial purposes: it is now possible to remove, insert or replace specific DNA sequences in Dupont (1,3-propanediol, butanol and ethanol from lignocellulosics); the cell. Instead of a direct deletion or an overexpression of the genes DSM (the antibiotic cephalexin); BASF (vitamin B2 and riboflavin); that encode the related metabolic enzymes, it is now more common Novozymes and Cargill (3-hydroxypropionic acid); and Gevo to target regulatory networks. In this way, particular pathways and/or (isobutanol) (Hong, 2012; Hong and Nielsen, 2012). the maximum output of a desired metabolite can be enhanced or suppressed in a cell (even nonnative pathways), with the possibility of 4.1.2. Algae as a producer scaling up entire processes, such that the cell remains viable under In the presence of sunlight, CO2, water and nutrients (nitrogen, production conditions. potassium and phosphorous) algae can produce an oil used for biofuels. Typically, the desired product to be synthesized is identified, and the Algae can be single-celled or multicellular; some algae have short sexual related reactions and pathways that can produce the desired product cycles and rapid growth that allows for easy manipulation, and some are selected. The most suitable organism to synthesize the product algae can grow in wastewater, salty water or nonarable land (Hannon is chosen from genetic and chemical information. It is important to et al., 2010). Algal strains vary in their requirements for growth medi- consider how easily the organism's pathways can be modified, how um, their growth rate and their biomass productivity; they are not all easily the organism is to grow and maintain and the volume, value photosynthetic, and they have various lipid profiles and levels of resis- and cleanliness of the final product. A wide range of microorganisms tance to pathogens (Georgianna and Mayfield, 2012). Algal strains established as cell factories for industrial purposes are currently used should be optimized for tolerance to high temperatures, various light for metabolic engineering: recombinant bacterial strains of Bacillus conditions, salinity, high oxygen concentration and nutrient composi- subtilis, Corynebacterium glutamicum, Escherichia coli, filamentous tion. Ideally, cells should be able to grow and produce lipids simulta- fungi Aspergillus niger and Aspergillus oryzae, various microalgae (e.g., neously, and it would be best if the lipids produced were excreted Arthrospira, Botryococcus, Chaetoceros calcitrans, Chara vulgaris, Chorella outside cells. From the total 40,000 algal species (with some estimates protothecoides, Chlorella vulgaris, Clamydomonas, Cyanobacteria, of up to 72,500 algal species worldwide (Guiry, 2012)), only a few thou- Dunaliella, Nannochloris, Nannochloropsis, Ostreococcus, Pavlova lutheri, sand strains (~3000) are kept in collections and only half-a-dozen are Phaeodactylum tricornutum, Porphyridium cruentum, Thalassiosira cultivated in industrial quantities. To date, only approximately 10 differ- pseudonana, Thraustochytrium spp.) and the yeast Saccharomyces ent algal species can be transformed and fewer than 50 whole genomes cerevisiae. The availability of references and databases about the have been sequenced (Walker et al., 2005; Wijffels and Barbosa, 2010). genomic and chemical information, reactions and metabolic pathways for the production of product or a wanted result is essential. Each of 4.1.3. S. cerevisiae as a producer the producers has their own advantages and suffers from some prob- S. cerevisiae's genome was the first eukaryotic organism to be lems. For example, B. subtilis is capable producing riboflavin, butanediol, sequenced, and, therefore, it has been used widely as a model organism isobutanol, cellulase and other substances. Production of these in many fundamental studies. The yeast S. cerevisiae naturally metabo- substances can be enhanced by gene modification (Hao et al., 2013). lizes hexoses (glucose, fructose and galactose) and a few dimers such The genome-scale metabolic models of B. subtilis are very useful for as sucrose and maltose. Yeasts can tolerate high ethanol and sugar the rapid and accurate prediction of the cellular response to gene knock- concentrations (resistant to osmotic stress), a high cell density, high out, media conditions and environmental changes. It is important to be temperatures, low pH values and low sulfite concentrations (Basso able to scale up the production from the laboratory to the industrial et al., 2008). For these reasons yeasts are able to grow under environ- scale. The volume of a product produced by engineered cells varies. mental conditions where other organisms cannot survive. In addition, High-value products (and usually low volume) include pharmaceuticals yeasts are immune to contamination by phages (compared to E. coli). (recombinant proteins, statins and other natural products) and food However, there are certain limitations to S. cerevisiae,suchasan ingredients (vitamins, antioxidants and flavors). On the other hand, inability to metabolize pentoses present in hemicelluloses, their conver- biorefineries seek larger volume products (even if the value of the sion and growth rates are lower than those for E. coli and it is more product is lower) such as fine chemicals (antibiotics, enzymes and chiral difficult to engineer yeast than E. coli (Hong and Nielsen, 2012). Despite

Please cite this article as: Kodzius, R., Gojobori, T., Marine metagenomics as a source for bioprospecting, Mar. Genomics (2015), http://dx.doi.org/ 10.1016/j.margen.2015.07.001 6 R. Kodzius, T. Gojobori / Marine Genomics xxx (2015) xxx–xxx these limitations, many strains of S. cerevisiae have been developed engineered to overproduce (5-fold) the normal amount of isoprenoid for the production of biofuels (ethanol, biodiesels and butanol); lycopene, an antioxidant linked to anticancer properties that is bulk chemicals (pyruvic acid, succinic acid, 1-lactic acid, 1,2- produced industrially. His work was completed in three days using a propanediol, d-ribose and ribitol and polyhydroxy-alkanoates); ﬁne complex pool of synthetic DNA, creating over 4.3 billion combinatorial chemicals (1-ascorbic acid, antifungal diterpene, methylmalonyl- genomic variants (Wang et al., 2009). The accelerated growth of E. coli coenzyme A, nonribosomal peptides and Se-methylselenocysteine); was integral to the speed at which Church was able to improve and and protein drugs (immunoglobulin G, hepatitis B virus surface antigen, discover new properties (Wang et al., 2009). epidermal growth factor, insulin-like growth factor, single-chain anti- Producers in marine waters have been discovered and improved. For bodies and glucagon) (Hong and Nielsen, 2012). Many genes discovered example, a marine actinomycete Marinactinospora thermotolerans found in marine life can be expressed in S. cerevisiae; for example, a gene in deep-sea marine sediment was genetically modiﬁed to increase its encoding fatty acid desaturase was cloned from the marine fungus yield by ∼25-fold compared to the wild-type strain for its use in the pro- Thraustochytrium sp. and expressed at a very high conversion rate duction of antimicrobial nucleoside antibiotic A201A. M. thermotolerans (56.40%) in S. cerevisiae (Huang et al., 2011). was also shown to be a source of antibacterial agents (Zhu et al., 2012).

4.2.1. Genetic engineering using molecular biology tools 4.2. Tools to improve the function of strains It is known that many of the organisms identified through metagenomics are unculturable. Advances in metagenomics and micro- We seek to improve wild-type producers to better suit our needs. biology allow to identify new media, expanding the list of potential The evolution of agriculture, for example, began around 10,000 BC, producers. Genomic mining of the metagenomics data allows to identify when humans transitioned from hunting to farming. Over time, crops biochemical diversity of specific gene families. For example, 31 beneficial to agricultural output have been selected. Although unaware cyanobactin gene clusters (family of cyclic ribosomal peptides) from of genomic DNA, people began to understand that genetic material is 126 genomes of cyanobacteria were identified by Leikoski et al. passed from parents to their offspring. Therefore, genetic material (2013). The gene families and pathways found can be inserted into can be altered by either random mutation events, such as irradiation the known producer strains. by X-rays, or by genome-targeted editing technologies, to make improvements to strains in a short period of time (Fig. 2). Similarly, established microbial strains have been improved in many 4.2.1.1. Meganucleases as a tool for genome engineering. Meganucleases ways— from random strain mutations to advanced methods, such as are enzymes capable of recognizing and cutting large DNA sequences metabolic engineering, when specific genes and pathways are changed. (from 12 to 40 bp); they provide a more sophisticated approach to Advances in molecular biology and genetic sciences have developed genome engineering than do random mutation techniques (Stoddard, genome engineering, which enables targeted mutations in genomes. 2005). However, naturally occurring meganucleases do not serve for In 2009, Church automated a process called multiplex-automated the purpose of engineering because it is impossible to match an exact genome engineering, which generated a diverse set of genetic changes meganuclease to act on a specific DNA sequence. Therefore, many (mismatches, deletions and/or insertions) that enabled E. coli to be meganucleases are created (Smith et al., 2006)byeitherbymutagenesis

Fig. 2. The typical steps followed to improve a producer strain using genetic engineering tools to modify genomic DNA by mutagenesis and pathway perturbation, followed by high- throughput screening. The best producer is used to scale up the production process.

(Seligman et al., 2002) or by combinatorial assembly, whereby protein mutations have been successfully introduced in the genomes of Strepto- subunits from different enzymes are fused (Arnould et al., 2006). coccus pneumoniae and E. coli using CRISPR system (Jiang et al., 2013). Currently, a fully rational design process (“directed nuclease editor”) Currently, targeted genome editing by CRISPR can be applied to micro- is being used to create highly specific engineered meganucleases for organisms harboring inducible plasmid (Jiang et al., 2013). any location in a genome (Gao et al., 2010). The more stringent the Today, the CRISPR system is recognized as the most efficient and DNA sequence recognition is of the meganuclease, the less toxic it is easiest system for genome engineering. CRISPR should be used to create for the cell. and modify producer strains and to improve and enhance the produc- Actinomycetes are Gram-positive mycelial bacteria, known to tion of a chemical of interest. A high-throughput system environment produce a wide variety of industrially and medically relevant com- is essential for CRISPR system function, and combined with single-cell pounds (antibiotics, chemotherapeutics, fungicides, herbicides and technologies, for example, the best performing producers could be immunosuppressants). Using meganuclease I-SceI from S. cerevisiae, quickly and easily selected. In the near future, we expect these methods the gene cluster for the red-pigmented tripyrrole compound that to lead to more producer strains for various industrially relevant output remains associated with the mycelium was deleted in actinomycetes products. Marine metagenomics is not only a source to explain bacterial Streptomyces coelicolor. The changed genotype and phenotype were and archaeal CRISPR-related gene sequences and their acquired resis- confirmed (Fernandez-Martinez and Bibb, 2014). tance to viruses (Heidelberg et al., 2009; Anderson et al., 2011), but it is also a source for identifying ways to improve parts of the CRISPR 4.2.1.2. ZNF and TALEN as a tool for genome engineering. Zinc finger system (Anderson et al., 2011; Zhang et al., 2014; Smedile et al., nucleases (ZFNs) and transcription activator-like effectors (TALEs) 2013); new producer strains can be obtained from marine sources and (Baker, 2012) are two DNA sequence-recognizing peptides that can modified/improved using CRISPR. CRISPR/Cas systems can contain be combined with a FokI endonuclease catalytic domain, which genes that encode highly divergent proteins (Makarova et al., 2011). have different recognition and cleaving sites. As a result, a construct All these are a valuable source for the synthetic biology. There are at with multiple recognition domains for recognizing multiple compos- least two studies which presented CRISPR-based transcriptional ite sequences over 24 bp can be created. Although ZNF (Kim et al., cascades for synthetic circuits, such as transcriptional activators and 1996)andTALEN(Li et al., 2011; Christian et al., 2010) are time con- repressors (Vogt, 2014). Voltage-dependent changes led to the change suming and expensive technologies, they have been used successful- to fluorescence resonance energy transfer (FRET) signals or changes to ly to genetically engineer many species, validating their role as endogenous protein fluorescence. While this was done in mammalian protein engineers. cells, it is also applicable for transfer to prokaryotes or other cells. The TALEN has successfully been applied to genetically modified sea shift from observation to application is beginning to take place. anemone Nematostella vectensis (Ikmi et al., 2014), sea urchin embryos (Hosoi et al., 2014), amphioxus Branchiostoma belcheri (G. Li et al., 4.2.2. New organisms created by synthetic biology 2014), marine annelid Platynereis dumerilii (Bannister et al., 2014)and Synthetic biology opens the door to a new era of producer improve- ascidian Ciona intestinalis (Yoshida et al., 2014). ment that could even lead to the creation of new organisms (Channon et al., 2008). Advances in oligonucleotide synthesis, where longer pieces 4.2.1.3. RE-TOFs as a tool for genome engineering. However, ZNF are being produced, are enabling the recreation of entire genomic DNA and TALEN, are limited by the fact that their constructs must be re- from certain cells. In addition to the development of pathways and engineered for each new DNA target. On one hand, restriction enzyme components, biological parts can be standardized (Baker et al., 2006), triple-helix-forming oligonucleotide (RE-TFO) conjugates offer an and the functional units are being introduced into organisms, with the easier approach to performing genome engineering (Silanskas et al., potential to construct entire organisms de novo. 2012; Eisenschmidt et al., 2005), where only DNA triple-helix-forming In 2000, a 9.6 kbp hepatitis C virus genome was synthesized (Blight nucleotides are used for binding specificity (no protein engineering is et al., 2000). Two years of work later, a synthetic 7.7 kbp poliovirus required). On the other hand, RE-TFO conjugates are restricted by the genome was developed (Couzin, 2002). The next year, the synthesis complicated methodology required to conjugate oligonucleotides to and construction of a 5.4 kbp bacteriophage Phi X 174 genome took the nuclease module, by the slow formation of the triple helix and by only two weeks (Smith et al., 2003). In 2006, the J. Craig Venter Institute the low-targeting frequency. constructed a synthetic genome of a newly discovered minimal bacteri- um Mycoplasma laboratorium (Gibson et al., 2008). In 2010, Venter 4.2.1.4. CRISPR as a tool for genome engineering. The latest development demonstrated the synthetic assembly of a 1.08-M-bp Mycoplasma in genome-editing technology is the CRISPR/Cas system. CRISPR is an mycoides genome (Gibson et al., 2010). Eukaryotic algal chromosomes RNA-based bacterial defense mechanism (in other words bacterial and of up to 500 kb have been assembled in yeast at the Craig Venter archaeal immune systems) designed to recognize and eliminate foreign Institute (Karas et al., 2013). It is likely that fully synthetic eukaryotic DNA from invading bacteriophages and plasmids (Horvath and producers will soon be synthesized and assembled. Other developments Barrangou, 2010). RNA-guided DNA endonuclease uses guide RNA for include expanding the natural genetic code (which consists of four target-site recognition, and Cas endonuclease cleaves the DNA. The bases A, C, G and T) to an extra base pair (denoted by X and Y artificial main advantage to using CRISPR is the speed and simplicity of this nucleotides) (Malyshev et al., 2014). The production of new life forms assay — no protein engineering is required and only synthesized RNA and new proteins encoded from previously unknown and from devel- is used. Multiplexing is possible, which would allow for more changes oped amino acids is expected in the future (Suzuki et al., 2001; in the genome with one experiment (Cong et al., 2013; Gasiunas and Nakamura et al., 2000; Suzuki and Gojobori, 1999). Siksnys, 2013). The CRISPR approach has shown high potential and The first synthetic cell created by Venter cost 40 million USD genome-editing flexibility that can be applied to numerous DNA (Sleator, 2010). However, as DNA synthesis and sequencing technolo- targeting applications including transcriptional control (Barrangou gies improve and prices fall, we can expect not only further discovery and Marraffini, 2014). To date, CRISPR has been primarily used in the of naturally occurring organisms, but also the development of more engineering of eukaryotic cell lines; however, we can expect more engineered microorganisms. Many companies are involved in creating applications for genetic engineering in microorganisms in the near synthetic cells to capture CO2 and produce renewable fuels such as future. Although there is evidence that CRISPR-mediated cleavage of Joule Unlimited in Cambridge, LS9 Inc. in San Francisco, Amyris Biotech- chromosomes leads to cell death in many bacteria (Marraffini and nologies in California, Synthetic Genomics Inc. in California (a company Sontheimer, 2010; Edgar and Qimron, 2010; Bikard et al., 2012)and founded by Dr. Venter) and the Exxon Mobil Corporation in Texas. archaea (Gudbergsdottir et al., 2011; Fischer et al., 2012), precise Synthetic biology serves to benefitfrommarinemetagenomicsbecause

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Please cite this article as: Kodzius, R., Gojobori, T., Marine metagenomics as a source for bioprospecting, Mar. Genomics (2015), http://dx.doi.org/ 10.1016/j.margen.2015.07.001