Manipulating the 3D organization of the largest synthetic yeast chromosome.

Whether synthetic genomes can power life has attracted broad interest in the synthetic biology field. Here, we report de novo synthesis of the largest eukaryotic chromosome thus far, synIV, a 1,454,621-bp yeast chromosome resulting from extensive genome streamlining and modification. We developed megachunk assembly combined with a hierarchical integration strategy, which significantly increased the accuracy and flexibility of synthetic chromosome construction. Besides the drastic sequence changes, we further manipulated the 3D structure of synIV to explore spatial gene regulation. Surprisingly, we found few gene expression changes, suggesting that positioning inside the yeast nucleoplasm plays a minor role in gene regulation. Lastly, we tethered synIV to the inner nuclear membrane via its hundreds of loxPsym sites and observed transcriptional repression of the entire chromosome, demonstrating chromosome-wide transcription manipulation without changing the DNA sequences. Our manipulation of the spatial structure of synIV sheds light on higher-order architectural design of the synthetic genomes.

Analysis of homeodomain specificities allows the family-wide prediction of preferred recognition sites.

We describe the comprehensive characterization of homeodomain DNA-binding specificities from a metazoan genome. The analysis of all 84 independent homeodomains from D. melanogaster reveals the breadth of DNA sequences that can be specified by this recognition motif. The majority of these factors can be organized into 11 different specificity groups, where the preferred recognition sequence between these groups can differ at up to four of the six core recognition positions. Analysis of the recognition motifs within these groups led to a catalog of common specificity determinants that may cooperate or compete to define the binding site preference. With these recognition principles, a homeodomain can be reengineered to create factors where its specificity is altered at the majority of recognition positions. This resource also allows prediction of homeodomain specificities from other organisms, which is demonstrated by the prediction and analysis of human homeodomain specificities.

The geometric influence on the Cys2His2 zinc finger domain and functional plasticity.

The Cys2His2 zinc finger is the most common DNA-binding domain expanding in metazoans since the fungi human split. A proposed catalyst for this expansion is an arms race to silence transposable elements yet it remains poorly understood how this domain is able to evolve the required specificities. Likewise, models of its DNA binding specificity remain error prone due to a lack of understanding of how adjacent fingers influence each other's binding specificity. Here, we use a synthetic approach to exhaustively investigate binding geometry, one of the dominant influences on adjacent finger function. By screening over 28 billion protein-DNA interactions in various geometric contexts we find the plasticity of the most common natural geometry enables more functional amino acid combinations across all targets. Further, residues that define this geometry are enriched in genomes where zinc fingers are prevalent and specificity transitions would be limited in alternative geometries. Finally, these results demonstrate an exhaustive synthetic screen can produce an accurate model of domain function while providing mechanistic insight that may have assisted in the domains expansion.

Linking the environment, DAF-7/TGFß signaling and LAG-2/DSL ligand expression in the germline stem cell niche.

The developmental accumulation of proliferative germ cells in the C. elegans hermaphrodite is sensitive to the organismal environment. Previously, we found that the TGFß signaling pathway links the environment and proliferative germ cell accumulation. Neuronal DAF-7/TGFß causes a DAF-1/TGFßR signaling cascade in the gonadal distal tip cell (DTC), the germline stem cell niche, where it negatively regulates a DAF-3 SMAD and DAF-5 Sno-Ski. LAG-2, a founding DSL ligand family member, is produced in the DTC and activates the GLP-1/Notch receptor on adjacent germ cells to maintain germline stem cell fate. Here, we show that DAF-7/TGFß signaling promotes expression of lag-2 in the DTC in a daf-3-dependent manner. Using ChIP and one-hybrid assays, we find evidence for direct interaction between DAF-3 and the lag-2 promoter. We further identify a 25 bp DAF-3 binding element required for the DTC lag-2 reporter response to the environment and to DAF-7/TGFß signaling. Our results implicate DAF-3 repressor complex activity as a key molecular mechanism whereby the environment influences DSL ligand expression in the niche to modulate developmental expansion of the germline stem cell pool.

A yeast optogenetic toolkit (yOTK) for gene expression control in Saccharomyces cerevisiae.

Optogenetic tools for controlling gene expression are ideal for tuning synthetic biological networks due to the exquisite spatiotemporal control available with light. Here we develop an optogenetic system for gene expression control integrated with an existing yeast toolkit allowing for rapid, modular assembly of light-controlled circuits in the important chassis organism Saccharomyces cerevisiae. We reconstitute activity of a split synthetic zinc-finger transcription factor (TF) using light-induced dimerization mediated by the proteins CRY2 and CIB1. We optimize function of this split TF and demonstrate the utility of the toolkit workflow by assembling cassettes expressing the TF activation domain and DNA-binding domain at different levels. Utilizing this TF and a synthetic promoter we demonstrate that light intensity and duty cycle can be used to modulate gene expression over the range currently available from natural yeast promoters. This study allows for rapid generation and prototyping of optogenetic circuits to control gene expression in S. cerevisiae.

A systematic survey of the Cys2His2 zinc finger DNA-binding landscape.

Cys2His2 zinc fingers (C2H2-ZFs) comprise the largest class of metazoan DNA-binding domains. Despite this domain's well-defined DNA-recognition interface, and its successful use in the design of chimeric proteins capable of targeting genomic regions of interest, much remains unknown about its DNA-binding landscape. To help bridge this gap in fundamental knowledge and to provide a resource for design-oriented applications, we screened large synthetic protein libraries to select binding C2H2-ZF domains for each possible three base pair target. The resulting data consist of >160 000 unique domain-DNA interactions and comprise the most comprehensive investigation of C2H2-ZF DNA-binding interactions to date. An integrated analysis of these independent screens yielded DNA-binding profiles for tens of thousands of domains and led to the successful design and prediction of C2H2-ZF DNA-binding specificities. Computational analyses uncovered important aspects of C2H2-ZF domain-DNA interactions, including the roles of within-finger context and domain position on base recognition. We observed the existence of numerous distinct binding strategies for each possible three base pair target and an apparent balance between affinity and specificity of binding. In sum, our comprehensive data help elucidate the complex binding landscape of C2H2-ZF domains and provide a foundation for efforts to determine, predict and engineer their DNA-binding specificities.

Deep sequencing of large library selections allows computational discovery of diverse sets of zinc fingers that bind common targets.

The Cys2His2 zinc finger (ZF) is the most frequently found sequence-specific DNA-binding domain in eukaryotic proteins. The ZF's modular protein-DNA interface has also served as a platform for genome engineering applications. Despite decades of intense study, a predictive understanding of the DNA-binding specificities of either natural or engineered ZF domains remains elusive. To help fill this gap, we developed an integrated experimental-computational approach to enrich and recover distinct groups of ZFs that bind common targets. To showcase the power of our approach, we built several large ZF libraries and demonstrated their excellent diversity. As proof of principle, we used one of these ZF libraries to select and recover thousands of ZFs that bind several 3-nt targets of interest. We were then able to computationally cluster these recovered ZFs to reveal several distinct classes of proteins, all recovered from a single selection, to bind the same target. Finally, for each target studied, we confirmed that one or more representative ZFs yield the desired specificity. In sum, the described approach enables comprehensive large-scale selection and characterization of ZF specificities and should be a great aid in furthering our understanding of the ZF domain.

Exploring the DNA-recognition potential of homeodomains.

The recognition potential of most families of DNA-binding domains (DBDs) remains relatively unexplored. Homeodomains (HDs), like many other families of DBDs, display limited diversity in their preferred recognition sequences. To explore the recognition potential of HDs, we utilized a bacterial selection system to isolate HD variants, from a randomized library, that are compatible with each of the 64 possible 3' triplet sites (i.e., TAANNN). The majority of these selections yielded sets of HDs with overrepresented residues at specific recognition positions, implying the selection of specific binders. The DNA-binding specificity of 151 representative HD variants was subsequently characterized, identifying HDs that preferentially recognize 44 of these target sites. Many of these variants contain novel combinations of specificity determinants that are uncommon or absent in extant HDs. These novel determinants, when grafted into different HD backbones, produce a corresponding alteration in specificity. This information was used to create more explicit HD recognition models, which can inform the prediction of transcriptional regulatory networks for extant HDs or the engineering of HDs with novel DNA-recognition potential. The diversity of recovered HD recognition sequences raises important questions about the fitness barrier that restricts the evolution of alternate recognition modalities in natural systems.

Synthetic gene expression perturbation systems with rapid, tunable, single-gene specificity in yeast.

A general method for the dynamic control of single gene expression in eukaryotes, with no off-target effects, is a long-sought tool for molecular and systems biologists. We engineered two artificial transcription factors (ATFs) that contain Cys(2)His(2) zinc-finger DNA-binding domains of either the mouse transcription factor Zif268 (9 bp of specificity) or a rationally designed array of four zinc fingers (12 bp of specificity). These domains were expressed as fusions to the human estrogen receptor and VP16 activation domain. The ATFs can rapidly induce a single gene driven by a synthetic promoter in response to introduction of an otherwise inert hormone with no detectable off-target effects. In the absence of inducer, the synthetic promoter is inactive and the regulated gene product is not detected. Following addition of inducer, transcripts are induced >50-fold within 15 min. We present a quantitative characterization of these ATFs and provide constructs for making their implementation straightforward. These new tools allow for the elucidation of regulatory network elements dynamically, which we demonstrate with a major metabolic regulator, Gcn4p.

Characterization of the DNA-binding properties of the Mohawk homeobox transcription factor.

The homeobox transcription factor Mohawk (Mkx) is a potent transcriptional repressor expressed in the embryonic precursors of skeletal muscle, cartilage, and bone. MKX has recently been shown to be a critical regulator of musculoskeletal tissue differentiation and gene expression; however, the genetic pathways through which MKX functions and its DNA-binding properties are currently unknown. Using a modified bacterial one-hybrid site selection assay, we determined the core DNA-recognition motif of the mouse monomeric Mkx homeodomain to be A-C-A. Using cell-based assays, we have identified a minimal Mkx-responsive element (MRE) located within the Mkx promoter, which is composed of a highly conserved inverted repeat of the core Mkx recognition motif. Using the minimal MRE sequence, we have further identified conserved MREs within the locus of Sox6, a transcription factor that represses slow fiber gene expression during skeletal muscle differentiation. Real-time PCR and immunostaining of in vitro differentiated muscle satellite cells isolated from Mkx-null mice revealed an increase in the expression of Sox6 and down-regulation of slow fiber structural genes. Together, these data identify the unique DNA-recognition properties of MKX and reveal a novel role for Mkx in promoting slow fiber type specification during skeletal muscle differentiation.

Recognition models to predict DNA-binding specificities of homeodomain proteins.

MOTIVATION: Recognition models for protein-DNA interactions, which allow the prediction of specificity for a DNA-binding domain based only on its sequence or the alteration of specificity through rational design, have long been a goal of computational biology. There has been some progress in constructing useful models, especially for C(2)H(2) zinc finger proteins, but it remains a challenging problem with ample room for improvement. For most families of transcription factors the best available methods utilize k-nearest neighbor (KNN) algorithms to make specificity predictions based on the average of the specificities of the k most similar proteins with defined specificities. Homeodomain (HD) proteins are the second most abundant family of transcription factors, after zinc fingers, in most metazoan genomes, and as a consequence an effective recognition model for this family would facilitate predictive models of many transcriptional regulatory networks within these genomes. RESULTS: Using extensive experimental data, we have tested several machine learning approaches and find that both support vector machines and random forests (RFs) can produce recognition models for HD proteins that are significant improvements over KNN-based methods. Cross-validation analyses show that the resulting models are capable of predicting specificities with high accuracy. We have produced a web-based prediction tool, PreMoTF (Predicted Motifs for Transcription Factors) (http://stormo.wustl.edu/PreMoTF), for predicting position frequency matrices from protein sequence using a RF-based model.

Engineered transcription-associated Cas9 targeting in eukaryotic cells.

DNA targeting Class 2 CRISPR-Cas effector nucleases, including the well-studied Cas9 proteins, evolved protospacer-adjacent motif (PAM) and guide RNA interactions that sequentially license their binding and cleavage activities at protospacer target sites. Both interactions are nucleic acid sequence specific but function constitutively; thus, they provide intrinsic spatial control over DNA targeting activities but naturally lack temporal control. Here we show that engineered Cas9 fusion proteins which bind to nascent RNAs near a protospacer can facilitate spatiotemporal coupling between transcription and DNA targeting at that protospacer: Transcription-associated Cas9 Targeting (TraCT). Engineered TraCT is enabled when suboptimal PAM interactions limit basal activity in vivo and when one or more nascent RNA substrates are still tethered to the actively transcribing target DNA in cis. We further show that this phenomenon can be exploited for selective editing at one of two identical targets in distinct gene loci, or, in diploid allelic loci that are differentially transcribed. Our work demonstrates that temporal control over Cas9's targeting activity at specific DNA sites may be engineered without modifying Cas9's core domains and guide RNA components or their expression levels. More broadly, it establishes RNA binding in cis as a mechanism that can conditionally stimulate CRISPR-Cas DNA targeting in eukaryotes.

A universal deep-learning model for zinc finger design enables transcription factor reprogramming.

Cys2His2 zinc finger (ZF) domains engineered to bind specific target sequences in the genome provide an effective strategy for programmable regulation of gene expression, with many potential therapeutic applications. However, the structurally intricate engagement of ZF domains with DNA has made their design challenging. Here we describe the screening of 49 billion protein-DNA interactions and the development of a deep-learning model, ZFDesign, that solves ZF design for any genomic target. ZFDesign is a modern machine learning method that models global and target-specific differences induced by a range of library environments and specifically takes into account compatibility of neighboring fingers using a novel hierarchical transformer architecture. We demonstrate the versatility of designed ZFs as nucleases as well as activators and repressors by seamless reprogramming of human transcription factors. These factors could be used to upregulate an allele of haploinsufficiency, downregulate a gain-of-function mutation or test the consequence of regulation of a single gene as opposed to the many genes that a transcription factor would normally influence.

Engineered dual selection for directed evolution of SpCas9 PAM specificity.

The widely used Streptococcus pyogenes Cas9 (SpCas9) nuclease derives its DNA targeting specificity from protein-DNA contacts with protospacer adjacent motif (PAM) sequences, in addition to base-pairing interactions between its guide RNA and target DNA. Previous reports have established that the PAM specificity of SpCas9 can be altered via positive selection procedures for directed evolution or other protein engineering strategies. Here we exploit in vivo directed evolution systems that incorporate simultaneous positive and negative selection to evolve SpCas9 variants with commensurate or improved activity on NAG PAMs relative to wild type and reduced activity on NGG PAMs, particularly YGG PAMs. We also show that the PAM preferences of available evolutionary intermediates effectively determine whether similar counterselection PAMs elicit different selection stringencies, and demonstrate that negative selection can be specifically increased in a yeast selection system through the fusion of compensatory zinc fingers to SpCas9.

A systematic characterization of factors that regulate Drosophila segmentation via a bacterial one-hybrid system.

Specificity data for groups of transcription factors (TFs) in a common regulatory network can be used to computationally identify the location of cis-regulatory modules in a genome. The primary limitation for this type of analysis is the paucity of specificity data that is available for the majority of TFs. We describe an omega-based bacterial one-hybrid system that provides a rapid method for characterizing DNA-binding specificities on a genome-wide scale. Using this system, 35 members of the Drosophila melanogaster segmentation network have been characterized, including representative members of all of the major classes of DNA-binding domains. A suite of web-based tools was created that uses this binding site dataset and phylogenetic comparisons to identify cis-regulatory modules throughout the fly genome. These tools allow specificities for any combination of factors to be used to perform rapid local or genome-wide searches for cis-regulatory modules. The utility of these factor specificities and tools is demonstrated on the well-characterized segmentation network. By incorporating specificity data on an additional 66 factors that we have characterized, our tools utilize approximately 14% of the predicted factors within the fly genome and provide an important new community resource for the identification of cis-regulatory modules.

A Multireporter Bacterial 2-Hybrid Assay for the High-Throughput and Dynamic Assay of PDZ Domain-Peptide Interactions.

The accurate determination of protein-protein interactions has been an important focus of molecular biology toward which much progress has been made due to the continuous development of existing and new technologies. However, current methods can have limitations, including scale and restriction to high affinity interactions, limiting our understanding of a large subset of these interactions. Here, we describe a modified bacterial-hybrid assay that employs combined selectable and scalable reporters that enable the sensitive screening of large peptide libraries followed by the sorting of positive interactions by the level of reporter output. We have applied this tool to characterize a set of human and E. coli PDZ domains. Our results are consistent with prior characterization of these proteins, and the improved sensitivity increases our ability to predict known and novel in vivo binding partners. This approach allows for the recovery of a wide range of affinities with a high throughput method that does not sacrifice the scale of the screen.

The State of Systems Genetics in 2017.

Cell Systems invited 16 experts to share their views on the field of systems genetics. In questions repeated in the headings, we asked them to define systems genetics, highlight its relevance to researchers outside the field, discuss what makes a strong systems genetics paper, and paint a picture of where the field is heading in the coming years. Their responses, ordered by the journal but otherwise unedited, make it clear that deciphering genotype to phenotype relationships is a central challenge of systems genetics and will require understanding how networks and higher-order properties of biological systems underlie complex traits. In addition, our experts illuminate the applications and relevance of systems genetics to human disease, the gut microbiome, development of tools that connect the global research community, sustainability, drug discovery, patient-specific disease and network models, and personalized treatments. Finally, a table of suggested reading provides a sample of influential work in the field.

Multi-reporter selection for the design of active and more specific zinc-finger nucleases for genome editing.

Engineered nucleases have transformed biological research and offer great therapeutic potential by enabling the straightforward modification of desired genomic sequences. While many nuclease platforms have proven functional, all can produce unanticipated off-target lesions and have difficulty discriminating between homologous sequences, limiting their therapeutic application. Here we describe a multi-reporter selection system that allows the screening of large protein libraries to uncover variants able to discriminate between sequences with substantial homology. We have used this system to identify zinc-finger nucleases that exhibit high cleavage activity (up to 60% indels) at their targets within the CCR5 and HBB genes and strong discrimination against homologous sequences within CCR2 and HBD. An unbiased screen for off-target lesions using a novel set of CCR5-targeting nucleases confirms negligible CCR2 activity and demonstrates minimal off-target activity genome wide. This system offers a straightforward approach to generate nucleases that discriminate between similar targets and provide exceptional genome-wide specificity.

Understanding DNA-binding specificity by bacteria hybrid selection.

Understanding how sequence-specific protein-DNA interactions direct cellular function is of great interest to the research community. High-throughput methods have been developed to determine DNA-binding specificities; one such technique, the bacterial one-hybrid (B1H) system, confers advantages including ease of use, sensitivity and throughput. In this review, we describe the evolution of the B1H system as a tool capable of screening large DNA libraries to investigate protein-DNA interactions of interest. We discuss how DNA-binding specificities produced by the B1H system have been used to predict regulatory targets. Additionally, we examine how this approach has been applied to characterize two common DNA-binding domain families-homeodomains and Cys2His2 zinc fingers-both in organism-wide studies and with synthetic approaches. In the case of the former, the B1H system has produced large catalogs of protein specificity and nuanced information about previously recovered DNA targets, thereby improving our understanding of these proteins' functions in vivo and increasing our capacity to predict similar interactions in other species. In the latter, synthetic screens of the same DNA-binding domains have further refined our models of specificity, through analyzing comprehensive libraries to uncover all proteins able to bind a complete set of targets, and, for instance, exploring how context-in the form of domain position within the parent protein-may affect specificity. Finally, we recognize the limitations of the B1H system and discuss its potential for use in the production of designer proteins and in studies of protein-protein interactions.

Rapid synthesis and screening of chemically activated transcription factors with GFP-based reporters.

Synthetic biology aims to rationally design and build synthetic circuits with desired quantitative properties, as well as provide tools to interrogate the structure of native control circuits. In both cases, the ability to program gene expression in a rapid and tunable fashion, with no off-target effects, can be useful. We have constructed yeast strains containing the ACT1 promoter upstream of a URA3 cassette followed by the ligand-binding domain of the human estrogen receptor and VP16. By transforming this strain with a linear PCR product containing a DNA binding domain and selecting against the presence of URA3, a constitutively expressed artificial transcription factor (ATF) can be generated by homologous recombination. ATFs engineered in this fashion can activate a unique target gene in the presence of inducer, thereby eliminating both the off-target activation and nonphysiological growth conditions found with commonly used conditional gene expression systems. A simple method for the rapid construction of GFP reporter plasmids that respond specifically to a native or artificial transcription factor of interest is also provided.