Learning causal networks using inducible transcription factors and transcriptome-wide time series.

We present IDEA (the Induction Dynamics gene Expression Atlas), a dataset constructed by independently inducing hundreds of transcription factors (TFs) and measuring timecourses of the resulting gene expression responses in budding yeast. Each experiment captures a regulatory cascade connecting a single induced regulator to the genes it causally regulates. We discuss the regulatory cascade of a single TF, Aft1, in detail; however, IDEA contains > 200 TF induction experiments with 20 million individual observations and 100,000 signal-containing dynamic responses. As an application of IDEA, we integrate all timecourses into a whole-cell transcriptional model, which is used to predict and validate multiple new and underappreciated transcriptional regulators. We also find that the magnitudes of coefficients in this model are predictive of genetic interaction profile similarities. In addition to being a resource for exploring regulatory connectivity between TFs and their target genes, our modeling approach shows that combining rapid perturbations of individual genes with genome-scale time-series measurements is an effective strategy for elucidating gene regulatory networks.

Dual threshold optimization and network inference reveal convergent evidence from TF binding locations and TF perturbation responses.

A high-confidence map of the direct, functional targets of each transcription factor (TF) requires convergent evidence from independent sources. Two significant sources of evidence are TF binding locations and the transcriptional responses to direct TF perturbations. Systematic data sets of both types exist for yeast and human, but they rarely converge on a common set of direct, functional targets for a TF. Even the few genes that are both bound and responsive may not be direct functional targets. Our analysis shows that when there are many nonfunctional binding sites and many indirect targets, nonfunctional sites are expected to occur in the cis-regulatory DNA of indirect targets by chance. To address this problem, we introduce dual threshold optimization (DTO), a new method for setting significance thresholds on binding and perturbation-response data, and show that it improves convergence. It also enables comparison of binding data to perturbation-response data that have been processed by network inference algorithms, which further improves convergence. The combination of dual threshold optimization and network inference greatly expands the high-confidence TF network map in both yeast and human. Next, we analyze a comprehensive new data set measuring the transcriptional response shortly after inducing overexpression of a yeast TF. We also present a new yeast binding location data set obtained by transposon calling cards and compare it to recent ChIP-exo data. These new data sets improve convergence and expand the high-confidence network synergistically.

Simultaneous Profiling of DNA Accessibility and Gene Expression Dynamics with ATAC-Seq and RNA-Seq.

This chapter describes sequencing-based methods for profiling dynamic changes in DNA accessibility and gene expression in Saccharomyces cerevisiae. Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-Seq) is a powerful technique for identifying nucleosome-free regions of the genome. Combining ATAC-Seq with RNA Sequencing (RNA-Seq) is a rapid approach for studying the relationship between genome structure and changes in global patterns of gene expression from a single experiment. A laboratory protocol is presented for these methods as well as examples of typical results and visualizations.

A new experimental platform facilitates assessment of the transcriptional and chromatin landscapes of aging yeast.

Replicative aging of Saccharomyces cerevisiae is an established model system for eukaryotic cellular aging. A limitation in yeast lifespan studies has been the difficulty of separating old cells from young cells in large quantities. We engineered a new platform, the Miniature-chemostat Aging Device (MAD), that enables purification of aged cells at sufficient quantities for genomic and biochemical characterization of aging yeast populations. Using MAD, we measured DNA accessibility and gene expression changes in aging cells. Our data highlight an intimate connection between aging, growth rate, and stress. Stress-independent genes that change with age are highly enriched for targets of the signal recognition particle (SRP). Combining MAD with an improved ATAC-seq method, we find that increasing proteasome activity reduces rDNA instability usually observed in aging cells and, contrary to published findings, provide evidence that global nucleosome occupancy does not change significantly with age.

Corrigendum: The extracellular interactome of the human adenovirus family reveals diverse strategies for immunomodulation.

This corrects the article DOI: 10.1038/ncomms11473.

The extracellular interactome of the human adenovirus family reveals diverse strategies for immunomodulation.

Viruses encode secreted and cell-surface expressed proteins essential to modulate host immune defenses and establish productive infections. However, to date there has been no systematic study of the extracellular interactome of any human virus. Here we utilize the E3 proteins, diverse and rapidly evolving transmembrane-containing proteins encoded by human adenoviruses, as a model system to survey the extracellular immunomodulatory landscape. From a large-scale protein interaction screen against a microarray of more than 1,500 human proteins, we find and validate 51 previously unidentified virus-host interactions. Our results uncover conserved strategies as well as substantial diversity and multifunctionality in host targeting within and between viral species. Prominent modulation of the leukocyte immunoglobulin-like and signalling lymphocyte activation molecule families and a number of inhibitory receptors were identified as hubs for viral perturbation, suggesting unrecognized immunoregulatory strategies. We describe a virus-host extracellular interaction map of unprecedented scale that provides new insights into viral immunomodulation.

Defining the ligand specificity of the deleted in colorectal cancer (DCC) receptor.

The growth and guidance of many axons in the developing nervous system require Netrin-mediated activation of Deleted in Colorectal Cancer (DCC) and other still unknown signaling cues. Commissural axon guidance defects are more severe in DCC mutant mice than Netrin-1 mutant mice, suggesting additional DCC activating signals besides Netrin-1 are involved in proper axon growth. Here we report that interaction screens on extracellular protein microarrays representing over 1,000 proteins uniquely identified Cerebellin 4 (CBLN4), a member of the C1q-tumor necrosis factor (TNF) family, and Netrin-1 as extracellular DCC-binding partners. Immunofluorescence and radio-ligand binding studies demonstrate that Netrin-1 competes with CBLN4 binding at an overlapping site within the membrane-proximal fibronectin domains (FN) 4-6 of DCC and binds with ∼5-fold higher affinity. CBLN4 also binds to the DCC homolog, Neogenin-1 (NEO1), but with a lower affinity compared to DCC. CBLN4-null mice did not show a defect in commissural axons of the developing spinal cord but did display a transient increase in the number of wandering axons in the brachial plexus, consistent with a role in axon guidance. Overall, the data solidifies CBLN4 as a bona fide DCC ligand and strengthens its implication in axon guidance.

LUZ-Y, a novel platform for the mammalian cell production of full-length IgG-bispecific antibodies.

The ability of bispecific antibodies to simultaneously bind two unique antigens has great clinical potential. However, most approaches utilized to generate bispecific antibodies yield antibody-like structures that diverge significantly from the structure of archetype human IgG, and those that do approach structural similarity to native antibodies are often challenging to engineer and manufacture. Here, we present a novel platform for the mammalian cell production of bispecific antibodies that differ from their parental mAbs by only a single point mutation per heavy chain. Central to this platform is the addition of a leucine zipper to the C terminus of the C(H)3 domain of the antibody that is sufficient to drive the heterodimeric assembly of antibody heavy chains and can be readily removed post-purification. Using this approach, we developed various antibody constructs including one-armed Abs, bispecific antibodies that utilize a common light chain, and bispecific antibodies that pair light chains to their cognate heavy chains via peptide tethers. We have applied this technology to various antibody pairings and will demonstrate the engineering, purification, and biological activity of these antibodies herein.