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As we move from gene-addition to genereplacement therapy, we must consider not only efficacy but also safety. Although off-target effects of nucleases are a real concern, they are likely to diminish as targeting specificity improves. The technology clearly works, but there are manufacturing issues that must be resolved for clinical application to become more widely feasible. Looking forward, with an increasing number of gene-editing tools available and a plethora of clinical targets, it is now time to go the extra mile and repair damaged genomes.

COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. 1. Wang, J. et al. Nat. Biotech. 33, 1256–1263 (2015). 2. Mussolino, C., Mlambo, T. & Cathomen, T. Curr. Opin. Pharmacol. 24, 105–112 (2015). 3. Tebas, P. et al. N. Engl. J. Med. 370, 901–910 (2014). 4. Merling, R.K. et al. Mol. Ther. 23, 147–157 (2015). 5. Dreyer, A.K. et al. Biomaterials 69, 191–200 (2015). 6. Rio, P. et al. EMBO Mol. Med. 6, 835–848 (2014). 7. Sebastiano, V. et al. Stem Cells 29, 1717–1726 (2011). 8. Genovese, P. et al. Nature 510, 235–240 (2014). 9. Hoban, M.D. et al. Blood 125, 2597–2604 (2015). 10. Sather, B.D. et al. Sci. Transl. Med. 7, 307ra156 (2015). 11. Fares, I. et al. Science 345, 1509–1512 (2014).

Your gut microbiome, deconstructed Dylan Dodd, Carolina Tropini & Justin L Sonnenburg Use of sophisticated reductionist and whole-system approaches are providing much-needed technologies to unravel the complex mélange of microbiome functions. “Intermittent flavors of the constituent elements mingle with the remembered taste of unified chowder.” —US chef Anthony Bourdain (from No Reservations: DC, aired 30 November 2009) Modern chefs often deconstruct traditional dishes and present the individual components to their patrons in reimagined ways. Although such deconstruction enables precise preparation of individual ingredients, some critics complain that the benefits of tasting the whole dish together are lost. In an analogous juxtaposition of different analytical strategies in microbiology, one approach is to isolate individual bacteria from the microbiome and study interactions among them in model systems as a way to inform the design of targeted interventions that aim to manipulate the microbiota1. A contrasting approach is to analyze highdimensional data from individual microbiome members as a means to uncover dynamic Dylan Dodd is at the Department of Pathology and the Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA. Carolina Tropini and Justin L. Sonnenburg are at the Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, California, USA. e-mail: [email protected]

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changes in their growth under different conditions2. Leveraging the opportunities and synergism of reductionist and whole-microbiome studies will increasingly be important in developing a more mature understanding of the complete ingredients list of microbiome functions. High-dimensional datasets produced by a multitude of -omics technologies are enabling the characterization of microbial communities present in our gastrointestinal tracts on an unprecedented scale. Even so, our ability to translate these datasets into a mechanistic understanding of microbiota remains limited, partly as a result of the complexity of microbial communities and interactions. For example, establishing whether a dysbiotic microbiota is the cause of a disease, or simply associated with it, is challenging. A better understanding of microbiome function is reliant on our ability to detect small but important signals embedded within the huge amount of noise present in microbiome datasets. Three recent reports exemplify the different strategies that researchers are applying to probe microbiome functions. One describes a method for analyzing metagenomic sequencing data that enabled investigators to quantify growth metrics for individual members of complex microbial communities in the gut2. Another used defined sets of bacteria to assemble communities that reconstitute biologically meaningful host responses3, and a third screened multispecies

mutant libraries to provide unprecedented molecular insights by deconstructing the microbiota into its constituent parts1. Korem et al.2 exploited subtle, yet robust, trends in metagenomic sequence coverage across a bacterial genome to infer populationwide growth rates (Fig. 1a). This basic and fundamental measure of the state of microbiota, which was previously unobtainable, is a much-needed advance. Being able to monitor the growth dynamics of even closely related bacterial strains, rather than merely observing the relative proportions of individual bacteria at a given time point, makes it possible to distinguish actively-dividing bacteria from those that are quiescent. The authors were able to correlate growth rates of individual bacterial species, as well as global growth rates, for an entire microbiome with facets of host physiology, such as blood glucose, or disease states, such as Crohn’s disease and type 2 diabetes. Although establishing a causal relationship between the growth of a bacterial species and host biology remains out of reach, this approach generates informed hypotheses about candidate organisms for future research. Korem et al.’s method could also shed light on how specific perturbations, ranging from antibiotic use to probiotic consumption, affect microbial growth dynamics in the intestine. Although -omics tools provide a useful means of analyzing microbial communities in situ, the use of defined mixtures of bacteria can provide mechanistic insight into the functions of the microbiome. For example, researchers have deconstructed the gut microbiota from individual fecal donors into extensive culture collections that, although limited to the subset of culturable bacteria, recapitulate key physiological properties of the donor stool4. Individual bacteria from personalized fecal culture collections are arrayed and archived as frozen glycerol stocks. One benefit of this experimental design is that the contributions of individual bacteria to specific physiological readouts can be assessed in gnotobiotic mice (Fig. 1b). Faith et al.3 used combinatorial libraries of cultivable human gut bacteria to ascertain which bacteria modulate colonic regulatory T cells (Tregs), adiposity and cecal metabolite concentrations in a murine host. By reducing combinatorial communities of culturable organisms to individual bacteria, they discovered that several Bacteroides species induce colonic Tregs in mono-colonized mice. A similar approach was used to identify 17 strains of clostridia as inducers of colonic Tregs (ref. 5). Understanding bacteria-induced Treg development has important implications for the treatment of inflammatory bowel disease. These

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Arrayed culture collection

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Figure 1 New techniques in the functional analysis of gut bacteria. (a) Inference of growth dynamics from metagenomic sequence data2. Bacterial chromosomes are replicated bidirectionally from the origin of replication. Therefore, when cells are actively dividing, the copy number of DNA along the chromosome varies. The peak and trough are defined as positions along the bacterial chromosome where read abundance is highest and lowest, respectively. The peak-to-trough ratio (PTR) provides an estimate of the community-averaged growth rate for a single bacterium. Cells that are growing more rapidly will have a higher PTR, whereas the PTR for nondividing cells is 1. (b) Culture arrays to assign physiological functions to specific bacteria3,4. Stool from a human donor is used to stably colonize germ free mice (humanization) and to produce culture collections. Groups of cultivable strains chosen at random are introduced into germ-free mice (combinatorial gnotobiotics) and analyzed for the capacity to recapitulate functions in the humanized mice. Finally, individual strains unique to combinatorial gnotobiotic groups that recapitulate functions are then used in mono-colonization experiments to identify individual strains capable of inducing the physiological property in question. (c) In vivo transposon mutagenesis via INSeq1,6. Isogenic mutants with single transposon integrations are generated in vitro and then used in gnotobiotic experiments. After specific perturbations are applied to the system, the relative abundance of each transposon mutant is assessed by INSeq. Mutants that decrease in abundance over time impart a fitness defect to the bacterium.

studies have set the stage for an evaluation of the contribution of specific gene products or metabolic pathways to Treg induction in mice. Another way of deconstructing the microbiota is to use transposon mutagenesis, which enables isolation of isogenic mutants. For example, Goodman et al.6 modified an

existing mariner-based transposon system in Bacteroides spp. to enable high-throughput sequencing of specific integrants. The power of this approach, named INSeq, is that an entire transposon-mutant library can be introduced into and tested in gnotobiotic animals (rather than each mutant being tested

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individually). By monitoring the relative abundance of specific mutants, insights into genetic determinants of bacterial fitness can be obtained (Fig. 1c)6. Using this transposon mutagenesis method, Wu et al.1 created libraries of four different strains of Bacteroides, which were then simultaneously introduced into gnotobiotic mice along with 11 common gut bacteria1. In the context of specific dietary shifts, the authors then used INSeq to evaluate the in vivo fitness of each gene in the four Bacteroides within this defined community. Complementary transcriptional profiling with RNA-seq revealed that for capsular polysaccharide synthesis (CPS), the most important locus for fitness was not necessarily the most highly expressed locus. A prebiotic polysaccharide, arabinoxylan, was administered together with a high-fat and high-sugar diet in an attempt to complement a fitness defect in a Bacteroides cellulosilyticus locus involved in the use of xylan. Arabinoxylan supplementation selectively enriched for this xylan-degrading bacterium and eliminated the fitness defect of the arabinoxylan-degrading gene cluster mutants, suggesting functional redundancy with another arabinoxylan utilization locus within this bacterium. Notably, addition of arabinoxylan to the diet rendered additional genes, such as those involved in the biosynthesis of certain amino acids, important in B. cellulosilyticus fitness. This study showcases the depth of functional insight that can be gained by combining the deconstruction of microbial communities with transposon mutagenesis. Although testing defined communities in gnotobiotic mice clearly has value, it is a complex model with meaningful limitations for studying the human gut microbiome, such as limited accessibility for reagent addition, high-throughput screening or real-time imaging of community dynamics. One approach to tackling the real-time imaging challenge has been to peer into the zebrafish, a transparent vertebrate host7. Using in vitro and in silico model systems could provide different insights not feasible using vertebrate hosts. For example, microfluidic tools have been used to study mucosal-associated microorganisms while reconstituting many physiological conditions8. Mouse gut organoids, which are simplified models of gastrointestinal physiology, have been used to analyze metabolic responses of the gut to two common gut-resident bacteria, establishing a promising in vitro approach9. As microbiology becomes increasingly quantitative, the integration of different model systems with clinical studies will guide discoveries in the microbiome field. However, we must not 1239

news and views fall into the trap of losing the original flavor of the dish. Translation of results back into the complex human microbial community will be crucial to transform cream and clams into an authentic-tasting unified chowder. COMPETING FINANCIAL INTERESTS The authors declare no competing financial interests. 1. Wu, M. et al. Science 350, aac5992 (2015). 2. Korem, T. et al. Science 349, 1101–1106 (2015).

3. Faith, J.J., Ahern, P.P., Ridaura, V.K., Cheng, J. & Gordon, J.I. Sci. Transl. Med. 6, 220ra211 (2014). 4. Goodman, A.L. et al. Proc. Natl. Acad. Sci. USA 108, 6252–6257 (2011). 5. Atarashi, K. et al. Nature 500, 232–236 (2013). 6. Goodman, A.L. et al. Cell Host Microbe 6, 279–289 (2009). 7. Jemielita, M. et al. mBio 5, e01751-14 (2014). 8. Bhatia, S.N. & Ingber, D.E. Nat. Biotechnol. 32, 760–772 (2014). 9. Lukovac, S. et al. mBio 5, e01438-14 (2014).

Cas9 gets a classmate

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Erik J Sontheimer & Scot A Wolfe Cpf1 is one of a growing number of class II CRISPR-Cas effectors that expand both our understanding of bacterial immunity and our genomeediting toolset. Despite the enormous interest in CRISPR-Cas (clustered, regularly interspaced, short palindromic repeats–CRISPR-associated protein) systems, much remains to be discovered about the evolutionary origins and functional diversity of the RNA-guided DNA endonucleases involved. Comprehensive bioinformatic analyses of bacterial and archaeal genomes to identify divergent CRISPR-Cas systems are shedding light on the origins of CRISPR and revealing new variants with beneficial properties for applications in biomedicine and agriculture. In a recent issue of Cell, Zetsche and colleagues1 functionally characterize one newly discovered CRISPR system, the Cpf1 family of candidate interference effectors, and identify it as a new group of RNA-guided DNA endonuclease complexes. Their analyses provide a small taste of the incredible diversity of CRISPR-based defense systems that exist in nature and that can potentially be repurposed into new genome-engineering and generegulation tools. The identification of previously unknown components of CRISPR-Cas–related loci across bacterial and archaeal species is complicated by the rapid evolution of these enzymes, which has involved both architectural rearrangements and the incorporation of new Erik J. Sontheimer is at the RNA Therapeutics Institute, Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA. Scot A. Wolfe is in the Department of Molecular, Cell and Cancer Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA. e-mail: [email protected] or [email protected]

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components through horizontal gene transfer. A recent bioinformatic analysis2 identified two new putative CRISPR-Cas systems (types IV and V). This expansion prompted the division of the five current CRISPR-Cas types into two overarching classes: class I (comprising types I, III and IV), which employs multisubunit CRISPR RNA (crRNA)-effector modules, and class II (comprising types II and V), which employs single-subunit CRISPR RNA (crRNA)-effector modules. Type V systems, like type II systems (Fig. 1a), are nearly all found in bacteria. They each encode a large (~1,200- to 1,500-amino-acid) protein, Cpf1, that has some similarities to the type II crRNA-effector Cas9, but also numerous differences1,2. Like Cas9, Cpf1 contains a RuvC nuclease domain segmented into three components. However, other regions of Cpf1 do not show homology to Cas9. In particular, Cpf1 does not have a second nuclease domain capable of cleaving the second DNA strand in a target (a task that Cas9 carries out via the HNH domain). The absence of an obvious trans-activating crRNA (tracrRNA) near the CRISPR array is another distinguishing feature of type V systems (Fig. 1a). These differences imply that type V systems might have propensities and properties for DNA targeting that facilitate applications different from (or complementary to) those of Cas9based systems. Zetsche and colleagues1 performed a functional analysis of the type V system from Francisella novicida U112, beginning with its reconstitution in E. coli and the definition of the minimal components necessary for genetic interference (in this case, preventing the establishment of a transformed plasmid).

Immediately, several differences from type II systems emerged. First, the protospaceradjacent motif (PAM) for FnCpf1 was shown to lie 5′ to the protospacer, as opposed to Cas9’s 3′-flanking PAM (Fig. 1b). Second, type V systems require only a single RNA guide, as no equivalent of the tracrRNA, which is an essential component of type II systems, was needed for crRNA processing or interference. Third, the order of sequence elements within the type V crRNA was inverted, with the CRISPR repeat at the 5′ end and the target-complementary spacer (23–25 nucleotides (nt)) at the 3′ end. RNA binding to the FnCpf1 protein is most likely mediated by the crRNA direct repeat elements, which form a single 5′ hairpin (Fig. 1b). The mechanistic details of target cleavage by the Cpf1-crRNA complex also differ from those of Cas9. Cleavage of the target sequence is distant from the PAM (18 base pairs removed on the crRNA-noncomplementary strand) and produces a double-strand break (DSB) with a 5-nt 5′ overhang (Fig. 1b). In contrast, Cas9 produces primarily blunt DSBs (Fig. 1b). Like Cas9 (ref. 3), the seed region for the Cpf1crRNA complex (the heteroduplex region most sensitive to mismatches) neighbors the PAM element. Unlike Cas9, however, the Cpf1 seed region does not contain the DNA cleavage site. Truncations of the guide sequence indicate that a minimum of 18 nt are required for target cleavage in vitro. Because the 5-nt overhanging DSB begins 18 base pairs from the start of the heteroduplex, this indicates that Cpf1 could potentially cleave one of the DNA strands within a duplex DNA region. Finally, mutation of catalytic residues within the FnCpf1 RuvC domain, instead of generating a nickase as observed for Cas9 (refs. 4,5), completely eliminates nuclease activity on both DNA strands. The chromatographic properties of Cpf1 suggest that it exists as a preformed dimer. Consequently, DSB formation at a target site may involve cleavage by RuvC domains from both subunits. To demonstrate the potential utility of type V systems for genome engineering, Zetsche and colleagues1 examine the activity of a panel of 16 representative Cpf1 orthologs from evolutionarily distant species. In a heterologous bacterial interference assay, the majority displayed a strong preference for a T-rich, 5′-flanking PAM sequence. Interestingly, only a subset of the crRNAs from these orthologs could guide FnCpf1 interference, suggesting that orthogonal Cpf1–crRNA combinations can be independently and simultaneously programmed in the same cell, much like evolutionarily distant Cas9 orthologs6. Only two Cpf1 orthologs (AsCpf1 and LbCpf1) showed robust activity when transfected into human

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Your gut microbiome, deconstructed.

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