PDF file 146K, This file contains the legends to Supplementary Figures 1-7 and Supplementary methods

PDF file 1227K, This file contains Supplemental Figures 1-7, which provide additional supporting information for each of the main figures

S1 XLSX file 63K, This Supplementary Table contains the results of ORF screen to identify genes that can rescue the suppression of TBK1 in a KRAS-dependent cell line

Cell-to-cell heterogeneity is a characteristic feature of the tumor necrosis factor (TNF)-stimulated inflammatory response mediated by the transcription factor NF-κB, motivating an exploration of the underlying sources of this noise. Here we combined single-transcript measurements with computational models to study transcriptional noise at six NF-κB-regulated inflammatory genes. In the basal state, NF-κB-target genes displayed an inverse correlation between mean and noise. TNF stimulation increased transcription while maintaining noise, except for the most repressed genes. By fitting transcript distributions to a two-state model of promoter activity, we found that TNF primarily stimulated transcription by increasing burst size while maintaining burst frequency. Burst size increases were associated with enrichment of initiated-but-paused RNA polymerase II at the promoter, and blocking the release of paused RNAPII with a small molecule inhibitor decreased TNF-stimulated burst size. Finally, we used a mathematical model to show that TNF positive feedback further amplified gene expression noise resulting from burst-size mediated transcription, leading to diverse TNF functional outputs. Our results reveal potential sources of noise underlying intercellular heterogeneity in the TNF-mediated inflammatory response.

Global insights into cellular organization and function require comprehensive understanding of interactome networks. Similar to how a reference genome sequence revolutionized human genetics, a reference map of the human interactome network is critical to fully understand genotype-phenotype relationships. Here we present the first human “all-by-all” binary reference interactome map, or “HuRI”. With ~53,000 high-quality protein-protein interactions (PPIs), HuRI is approximately four times larger than the information curated from small-scale studies available in the literature. Integrating HuRI with genome, transcriptome and proteome data enables the study of cellular function within essentially any physiological or pathological cellular context. We demonstrate the use of HuRI in identifying specific subcellular roles of PPIs and protein function modulation via splicing during brain development. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI thus represents an unprecedented, systematic reference linking genomic variation to phenotypic outcomes.

In a diploid cell, maternal and paternal alleles are generally assumed to be equally expressed. However, genome-wide allele specific sequencing has challenged this assumption, and instead demonstrates that allelic imbalance in expression is quite common. Some imbalances may arise transiently in individual cells simply from bursts of transcription, but others are epigenetically encoded and mitotically stable even as they affect gene expression level, strongly suggesting that they are functionally important. To determine how allelic imbalance could affect cellular behavior, we carried out a systematic theoretical analysis of the influence of allelic imbalance on signal-response relationships and functional behaviors across a set of signaling motifs with different topologies. By introducing allelic imbalance at individual network nodes either independently or in combination, we examined its impact on the resulting network dynamics using ensemble simulations, varying expression to mimicking cell-to-cell variability. We found that the differences between 'monoallelic' (high allelic bias) and 'biallelic' (low allelic bias) expression ensembles were strikingly dependent on network motif topology and signal-response behavior.The presence of regulatory loops such as feedback or feedforward loops in a signaling motif could redistribute the effect of allelic imbalance. Our analyses therefore show that the functional impact of allelic imbalance in the expression of a gene strongly depends on the signaling motif in which it appears and on its position in this motif; certain motifs are permissive while others provide robustness against allelic imbalance. Overall, our work shows that the interplay between allelic imbalance, cell-to-cell variation in gene expression and network motif composition together can create a rich array of tunable or robust input-output behaviors in signal transduction networks.

The NF-κB transcription regulation system governs a diverse set of responses to various cytokine stimuli. With tools from in vitro biochemical characterizations, to omics-based whole genome investigations, great strides have been made in understanding how NF-κB transcription factors control the expression of specific sets of genes. Nonetheless, these efforts have also revealed a very large number of potential binding sites for NF-κB in the human genome, and a puzzle emerges when trying to explain how NF-κB selects from these many binding sites to direct cell-type- and stimulus-specific gene expression patterns. In this review, we surmise that target gene transcription can broadly be thought of as a function of the nuclear abundance of the various NF-κB dimers, the affinity of NF-κB dimers for the regulatory sequence and the availability of this regulatory site. We use this framework to place quantitative information that has been gathered about the NF-κB transcription regulation system into context and thus consider questions it answers, and questions it raises. We end with a brief discussion of some of the future prospects that new approaches could bring to our understanding of how NF-κB transcription factors orchestrate diverse responses in different biological contexts.

The transcription factor NF-κB promotes inflammatory and stress-responsive gene transcription across a range of cell types in response to the cytokine tumor necrosis factor-α (TNF). Although NF-κB signaling exhibits significant variability across single cells, some target genes exhibit fold-change detection of NF-κB, which may buffer against stochastic variation in signaling molecules. However, this observation was made at target genes supporting high levels of TNF-inducible transcription. It is unknown if fold-change detection is maintained at NF-κB target genes with low levels of TNF-inducible transcription, for which stochastic promoter events may be more pronounced. Here we used a microfluidic cell-trapping device to measure how TNF-induced activation of NF-κB controls transcription in single Jurkat T cells at the promoters of integrated HIV and the endogenous cytokine gene IL6 , which produce only a few transcripts per cell. We tracked TNF-stimulated NF-κB RelA nuclear translocation by live-cell imaging and then quantified transcript number by RNA FISH in the same cell. We found that TNF-induced transcription correlates with fold change in nuclear NF-κB with similar strength at low versus high abundance target genes. A computational model of TNF-NF-κB signaling, which implements fold-change detection from competition for binding to κB motifs, was sufficient to reproduce fold-change detection across the experimentally measured range of transcript outputs. Nevertheless, we found that gene-specific trends in transcriptional noise and levels of promoter-bound NF-κB predicted by the model were inconsistent with our experimental observations at low abundance gene targets. Our results reveal a gap in our understanding of RelA-mediated transcription for low abundance transcripts and suggest that cells use additional biological mechanisms to maintain robustness of NF-κB fold-change detection while tuning transcriptional output.

Noisy gene expression generates diverse phenotypes, but little is known about mechanisms that modulate noise. Combining experiments and modeling, we studied how tumor necrosis factor (TNF) initiates noisy expression of latent HIV via the transcription factor nuclear factor κB (NF-κB) and how the HIV genomic integration site modulates noise to generate divergent (low-versus-high) phenotypes of viral activation. We show that TNF-induced transcriptional noise varies more than mean transcript number and that amplification of this noise explains low-versus-high viral activation. For a given integration site, live-cell imaging shows that NF-κB activation correlates with viral activation, but across integration sites, NF-κB activation cannot account for differences in transcriptional noise and phenotypes. Instead, differences in transcriptional noise are associated with differences in chromatin state and RNA polymerase II regulation. We conclude that, whereas NF-κB regulates transcript abundance in each cell, the chromatin environment modulates noise in the population to support diverse HIV activation in response to TNF.

Computational analyses of a half-million circuit topologies provide a rationale for why certain fold-change detection topologies are more prevalent in nature.

In tissues and tumours, cell behaviours are regulated by multiple time-varying signals. While in the laboratory cells are often exposed to a stimulus for the duration of the experiment, in vivo exposures may be much shorter. In this study, we monitored NF-κB and caspase signalling in human cancer cells treated with a short pulse of Tumour Necrosis Factor (TNF). TNF is an inflammatory cytokine that can induce both the pro-survival NF-κB-driven gene transcription pathway and the pro-apoptotic caspase pathway. We find that a few seconds of exposure to TNF is sufficient to activate the NF-κB pathway in HeLa cells and induce apoptotic cell death in both HeLa and Kym-1 cells. Strikingly, a 1-min pulse of TNF can be more effective at killing than a 1-hour pulse, indicating that in addition to TNF concentration, duration of exposure also coordinates cell fate decisions.

Genetically identical cells respond heterogeneously to uniform environmental stimuli. Consequently, investigating the signaling networks that control these cell responses using 'average' bulk cell measurements can obscure underlying mechanisms and misses information emerging from cell-to-cell variability. Here we review recent technological advances including live-cell fluorescence imaging-based approaches and microfluidic devices that enable measurements of signaling networks, dynamics, and responses in single cells. We discuss how these single-cell tools have uncovered novel mechanistic insights for canonical signaling pathways that control cell proliferation (ERK), DNA-damage responses (p53), and innate immune and stress responses (NF-κB). Future improvements in throughput and multiplexing, analytical pipelines, and in vivo applicability will all significantly expand the biological information gained from single-cell measurements of signaling pathways.

The human FGF receptors (FGFRs) play critical roles in various human cancers, and several FGFR inhibitors are currently under clinical investigation. Resistance usually results from selection for mutant kinases that are impervious to the action of the drug or from up-regulation of compensatory signaling pathways. Preclinical studies have demonstrated that resistance to FGFR inhibitors can be acquired through mutations in the FGFR gatekeeper residue, as clinically observed for FGFR4 in embryonal rhabdomyosarcoma and neuroendocrine breast carcinomas. Here we report on the use of a structure-based drug design to develop two selective, next-generation covalent FGFR inhibitors, the FGFR irreversible inhibitors 2 (FIIN-2) and 3 (FIIN-3). To our knowledge, FIIN-2 and FIIN-3 are the first inhibitors that can potently inhibit the proliferation of cells dependent upon the gatekeeper mutants of FGFR1 or FGFR2, which confer resistance to first-generation clinical FGFR inhibitors such as NVP-BGJ398 and AZD4547. Because of the conformational flexibility of the reactive acrylamide substituent, FIIN-3 has the unprecedented ability to inhibit both the EGF receptor (EGFR) and FGFR covalently by targeting two distinct cysteine residues. We report the cocrystal structure of FGFR4 with FIIN-2, which unexpectedly exhibits a "DFG-out" covalent binding mode. The structural basis for dual FGFR and EGFR targeting by FIIN3 also is illustrated by crystal structures of FIIN-3 bound with FGFR4 V550L and EGFR L858R. These results have important implications for the design of covalent FGFR inhibitors that can overcome clinical resistance and provide the first example, to our knowledge, of a kinase inhibitor that covalently targets cysteines located in different positions within the ATP-binding pocket.