A conserved function of corepressors is to nucleate assembly of the transcriptional preinitiation complex.

The plant corepressor TPL is recruited to diverse chromatin contexts, yet its mechanism of repression remains unclear. Previously, we have leveraged the fact that TPL retains its function in a synthetic transcriptional circuit in the yeast model Saccharomyces cerevisiae to localize repressive function to two distinct domains. Here, we employed two unbiased whole genome approaches to map the physical and genetic interactions of TPL at a repressed locus. We identified SPT4, SPT5 and SPT6 as necessary for repression with the SPT4 subunit acting as a bridge connecting TPL to SPT5 and SPT6. We also discovered the association of multiple additional constituents of the transcriptional preinitiation complex at TPL-repressed promoters, specifically those involved in early transcription initiation events. These findings were validated in yeast and plants through multiple assays, including a novel method to analyze conditional loss of function of essential genes in plants. Our findings support a model where TPL nucleates preassembly of the transcription activation machinery to facilitate rapid onset of transcription once repression is relieved.

Whole-genome screens reveal regulators of differentiation state and context-dependent migration in human neutrophils.

Neutrophils are the most abundant leukocyte in humans and provide a critical early line of defense as part of our innate immune system. We perform a comprehensive, genome-wide assessment of the molecular factors critical to proliferation, differentiation, and cell migration in a neutrophil-like cell line. Through the development of multiple migration screen strategies, we specifically probe directed (chemotaxis), undirected (chemokinesis), and 3D amoeboid cell migration in these fast-moving cells. We identify a role for mTORC1 signaling in cell differentiation, which influences neutrophil abundance, survival, and migratory behavior. Across our individual migration screens, we identify genes involved in adhesion-dependent and adhesion-independent cell migration, protein trafficking, and regulation of the actomyosin cytoskeleton. This genome-wide screening strategy, therefore, provides an invaluable approach to the study of neutrophils and provides a resource that will inform future studies of cell migration in these and other rapidly migrating cells.

Fundamental limits on the rate of bacterial growth and their influence on proteomic composition.

Despite abundant measurements of bacterial growth rate, cell size, and protein content, we lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we estimate the basic requirements and physical constraints on steady-state growth by considering key processes in cellular physiology across a collection of Escherichia coli proteomic data covering ≈4,000 proteins and 36 growth rates. Our analysis suggests that cells are predominantly tuned for the task of cell doubling across a continuum of growth rates; specific processes do not limit growth rate or dictate cell size. We present a model of proteomic regulation as a function of nutrient supply that reconciles observed interdependences between protein synthesis, cell size, and growth rate and propose that a theoretical inability to parallelize ribosomal synthesis places a firm limit on the achievable growth rate. A record of this paper's transparent peer review process is included in the supplemental information.

Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time.

Advances in DNA sequencing have revolutionized our ability to read genomes. However, even in the most well-studied of organisms, the bacterium Escherichia coli, for ≈65% of promoters we remain ignorant of their regulation. Until we crack this regulatory Rosetta Stone, efforts to read and write genomes will remain haphazard. We introduce a new method, Reg-Seq, that links massively parallel reporter assays with mass spectrometry to produce a base pair resolution dissection of more than a E. coli promoters in 12 growth conditions. We demonstrate that the method recapitulates known regulatory information. Then, we examine regulatory architectures for more than 80 promoters which previously had no known regulatory information. In many cases, we also identify which transcription factors mediate their regulation. This method clears a path for highly multiplexed investigations of the regulatory genome of model organisms, with the potential of moving to an array of microbes of ecological and medical relevance.

Sequence-dependent dynamics of synthetic and endogenous RSSs in V(D)J recombination.

Developing lymphocytes of jawed vertebrates cleave and combine distinct gene segments to assemble antigen-receptor genes. This process called V(D)J recombination that involves the RAG recombinase binding and cutting recombination signal sequences (RSSs) composed of conserved heptamer and nonamer sequences flanking less well-conserved 12- or 23-bp spacers. Little quantitative information is known about the contributions of individual RSS positions over the course of the RAG-RSS interaction. We employ a single-molecule method known as tethered particle motion to track the formation, lifetime and cleavage of individual RAG-12RSS-23RSS paired complexes (PCs) for numerous synthetic and endogenous 12RSSs. We reveal that single-bp changes, including in the 12RSS spacer, can significantly and selectively alter PC formation or the probability of RAG-mediated cleavage in the PC. We find that some rarely used endogenous gene segments can be mapped directly to poor RAG binding on their adjacent 12RSSs. Finally, we find that while abrogating RSS nicking with Ca2+ leads to substantially shorter PC lifetimes, analysis of the complete lifetime distributions of any 12RSS even on this reduced system reveals that the process of exiting the PC involves unidentified molecular details whose involvement in RAG-RSS dynamics are crucial to quantitatively capture kinetics in V(D)J recombination.

Theoretical investigation of a genetic switch for metabolic adaptation.

Membrane transporters carry key metabolites across the cell membrane and, from a resource standpoint, are hypothesized to be produced when necessary. The expression of membrane transporters in metabolic pathways is often upregulated by the transporter substrate. In E. coli, such systems include for example the lacY, araFGH, and xylFGH genes, which encode for lactose, arabinose, and xylose transporters, respectively. As a case study of a minimal system, we build a generalizable physical model of the xapABR genetic circuit, which features a regulatory feedback loop via membrane transport (positive feedback) and enzymatic degradation (negative feedback) of an inducer. Dynamical systems analysis and stochastic simulations show that the membrane transport makes the model system bistable in certain parameter regimes. Thus, it serves as a genetic "on-off" switch, enabling the cell to only produce a set of metabolic enzymes when the corresponding metabolite is present in large amounts. We find that the negative feedback from the degradation enzyme does not significantly disturb the positive feedback from the membrane transporter. We investigate hysteresis in the switching and discuss the role of cooperativity and multiple binding sites in the model circuit. Fundamentally, this work explores how a stable genetic switch for a set of enzymes is obtained from transcriptional auto-activation of a membrane transporter through its substrate.

Neutrophil-like HL-60 cells expressing only GFP-tagged ß-actin exhibit nearly normal motility.

Observations of actin dynamics in living cells using fluorescence microscopy have been foundational in the exploration of the mechanisms underlying cell migration. We used CRISPR/Cas9 gene editing to generate neutrophil-like HL-60 cell lines expressing GFP-ß-actin from the endogenous locus (ACTB). In light of many previous reports outlining functional deficiencies of labeled actin, we anticipated that HL-60 cells would only tolerate a monoallelic edit, as biallelic edited cells would produce no normal ß-actin. Surprisingly, we recovered viable monoallelic GFP-ß-actin cells as well as biallelic edited GFP-ß-actin cells, in which one copy of the ACTB gene is silenced and the other contains the GFP tag. Furthermore, the edited cells migrate with similar speeds and persistence as unmodified cells in a variety of motility assays, and have nearly normal cell shapes. These results might partially be explained by our observation that GFP-ß-actin incorporates into the F-actin network in biallelic edited cells at similar efficiencies as normal ß-actin in unedited cells. Additionally, the edited cells significantly upregulate γ-actin, perhaps helping to compensate for the loss of normal ß-actin. Interestingly, biallelic edited cells have only modest changes in global gene expression relative to the monoallelic line, as measured by RNA sequencing. While monoallelic edited cells downregulate expression of the tagged allele and are thus only weakly fluorescent, biallelic edited cells are quite bright and well-suited for live cell microscopy. The nondisruptive phenotype and direct interpretability of this fluorescent tagging approach make it a promising tool for studying actin dynamics in these rapidly migrating and highly phagocytic cells.

Predictive shifts in free energy couple mutations to their phenotypic consequences.

Mutation is a critical mechanism by which evolution explores the functional landscape of proteins. Despite our ability to experimentally inflict mutations at will, it remains difficult to link sequence-level perturbations to systems-level responses. Here, we present a framework centered on measuring changes in the free energy of the system to link individual mutations in an allosteric transcriptional repressor to the parameters which govern its response. We find that the energetic effects of the mutations can be categorized into several classes which have characteristic curves as a function of the inducer concentration. We experimentally test these diagnostic predictions using the well-characterized LacI repressor of Escherichia coli, probing several mutations in the DNA binding and inducer binding domains. We find that the change in gene expression due to a point mutation can be captured by modifying only the model parameters that describe the respective domain of the wild-type protein. These parameters appear to be insulated, with mutations in the DNA binding domain altering only the DNA affinity and those in the inducer binding domain altering only the allosteric parameters. Changing these subsets of parameters tunes the free energy of the system in a way that is concordant with theoretical expectations. Finally, we show that the induction profiles and resulting free energies associated with pairwise double mutants can be predicted with quantitative accuracy given knowledge of the single mutants, providing an avenue for identifying and quantifying epistatic interactions.

Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression.

It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles' heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input-output function describing how the level of expression depends upon the parameters of the regulated gene-for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles' heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.

Mapping DNA sequence to transcription factor binding energy in vivo.

Despite the central importance of transcriptional regulation in biology, it has proven difficult to determine the regulatory mechanisms of individual genes, let alone entire gene networks. It is particularly difficult to decipher the biophysical mechanisms of transcriptional regulation in living cells and determine the energetic properties of binding sites for transcription factors and RNA polymerase. In this work, we present a strategy for dissecting transcriptional regulatory sequences using in vivo methods (massively parallel reporter assays) to formulate quantitative models that map a transcription factor binding site's DNA sequence to transcription factor-DNA binding energy. We use these models to predict the binding energies of transcription factor binding sites to within 1 kBT of their measured values. We further explore how such a sequence-energy mapping relates to the mechanisms of trancriptional regulation in various promoter contexts. Specifically, we show that our models can be used to design specific induction responses, analyze the effects of amino acid mutations on DNA sequence preference, and determine how regulatory context affects a transcription factor's sequence specificity.

Systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria.

Gene regulation is one of the most ubiquitous processes in biology. However, while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. At present, characterizing the molecular mechanisms by which individual regulatory sequences operate requires focused efforts using low-throughput methods. Here, we take a first step toward multipromoter dissection and show how a combination of massively parallel reporter assays, mass spectrometry, and information-theoretic modeling can be used to dissect multiple bacterial promoters in a systematic way. We show this approach on both well-studied and previously uncharacterized promoters in the enteric bacterium Escherichia coli In all cases, we recover nucleotide-resolution models of promoter mechanism. For some promoters, including previously unannotated ones, the approach allowed us to further extract quantitative biophysical models describing input-output relationships. Given the generality of the approach presented here, it opens up the possibility of quantitatively dissecting the mechanisms of promoter function in E. coli and a wide range of other bacteria.

Tuning Transcriptional Regulation through Signaling: A Predictive Theory of Allosteric Induction.

Allosteric regulation is found across all domains of life, yet we still lack simple, predictive theories that directly link the experimentally tunable parameters of a system to its input-output response. To that end, we present a general theory of allosteric transcriptional regulation using the Monod-Wyman-Changeux model. We rigorously test this model using the ubiquitous simple repression motif in bacteria by first predicting the behavior of strains that span a large range of repressor copy numbers and DNA binding strengths and then constructing and measuring their response. Our model not only accurately captures the induction profiles of these strains, but also enables us to derive analytic expressions for key properties such as the dynamic range and [EC50]. Finally, we derive an expression for the free energy of allosteric repressors that enables us to collapse our experimental data onto a single master curve that captures the diverse phenomenology of the induction profiles.

Microfluidic-based manufacture of siRNA-lipid nanoparticles for therapeutic applications.

A simple, efficient, and scalable manufacturing technique is required for developing siRNA-lipid nanoparticles (siRNA-LNP) for therapeutic applications. In this chapter we describe a novel microfluidic-based manufacturing process for the rapid manufacture of siRNA-LNP, together with protocols for characterizing the size, polydispersity, RNA encapsulation efficiency, RNA concentration, and total lipid concentration of the resultant nanoparticles.

Lipid Nanoparticles Containing siRNA Synthesized by Microfluidic Mixing Exhibit an Electron-Dense Nanostructured Core.

Lipid nanoparticles (LNP) containing ionizable cationic lipids are the leading systems for enabling therapeutic applications of siRNA; however, the structure of these systems has not been defined. Here we examine the structure of LNP siRNA systems containing DLinKC2-DMA(an ionizable cationic lipid), phospholipid, cholesterol and a polyethylene glycol (PEG) lipid formed using a rapid microfluidic mixing process. Techniques employed include cryo-transmission electron microscopy, (31)P NMR, membrane fusion assays, density measurements, and molecular modeling. The experimental results indicate that these LNP siRNA systems have an interior lipid core containing siRNA duplexes complexed to cationic lipid and that the interior core also contains phospholipid and cholesterol. Consistent with experimental observations, molecular modeling calculations indicate that the interior of LNP siRNA systems exhibits a periodic structure of aqueous compartments, where some compartments contain siRNA. It is concluded that LNP siRNA systems formulated by rapid mixing of an ethanol solution of lipid with an aqueous medium containing siRNA exhibit a nanostructured core. The results give insight into the mechanism whereby LNP siRNA systems are formed, providing an understanding of the high encapsulation efficiencies that can be achieved and information on methods of constructing more sophisticated LNP systems.

Microfluidic Synthesis of Highly Potent Limit-size Lipid Nanoparticles for In Vivo Delivery of siRNA.

Lipid nanoparticles (LNP) are the leading systems for in vivo delivery of small interfering RNA (siRNA) for therapeutic applications. Formulation of LNP siRNA systems requires rapid mixing of solutions containing cationic lipid with solutions containing siRNA. Current formulation procedures employ macroscopic mixing processes to produce systems 70-nm diameter or larger that have variable siRNA encapsulation efficiency, homogeneity, and reproducibility. Here, we show that microfluidic mixing techniques, which permit millisecond mixing at the nanoliter scale, can reproducibly generate limit size LNP siRNA systems 20 nm and larger with essentially complete encapsulation of siRNA over a wide range of conditions with polydispersity indexes as low as 0.02. Optimized LNP siRNA systems produced by microfluidic mixing achieved 50% target gene silencing in hepatocytes at a dose level of 10 µg/kg siRNA in mice. We anticipate that microfluidic mixing, a precisely controlled and readily scalable technique, will become the preferred method for formulation of LNP siRNA delivery systems.

Lipid nanoparticle siRNA systems for silencing the androgen receptor in human prostate cancer in vivo.

The androgen receptor (AR) plays a critical role in the progression of prostate cancer. Silencing this protein using short-hairpin RNA (shRNA) has been correlated with tumor growth inhibition and decreases in serum prostate specific antigen (PSA). In our study, we have investigated the ability of lipid nanoparticle (LNP) formulations of small-interfering RNA (siRNA) to silence AR in human prostate tumor cell lines in vitro and in LNCaP xenograft tumors following intravenous (i.v.) injection. In vitro screening studies using a panel of cationic lipids showed that LNPs containing the ionizable cationic lipid 2,2-dilinoleyl-4-(2-dimethylaminoethyl)-[1,3]-dioxolane (DLin-KC2-DMA) exhibited the most potent AR silencing effects in LNCaP cells. This is attributed to an optimized ability of DLin-KC2-DMA-containing LNP to be taken up into cells and to release the siRNA into the cell cytoplasm following endocytotic uptake. DLin-KC2-DMA LNPs were also effective in silencing the AR in a wild-type AR expressing cell line, LAPC-4, and a variant AR expressing cell line, CWR22Rv1. Importantly, it is demonstrated that LNP AR-siRNA systems containing DLin-KC2-DMA can silence AR gene expression in distal LNCaP xenograft tumors and decrease serum PSA levels following i.v. injection. To our knowledge, this is the first report demonstrating the feasibility of LNP delivery of siRNA for silencing AR gene expression in vivo.