GPR161 structure uncovers the redundant role of sterol-regulated ciliary cAMP signaling in the Hedgehog pathway.

The orphan G protein-coupled receptor (GPCR) GPR161 is enriched in primary cilia, where it plays a central role in suppressing Hedgehog signaling1. GPR161 mutations lead to developmental defects and cancers2,3,4. The fundamental basis of how GPR161 is activated, including potential endogenous activators and pathway-relevant signal transducers, remains unclear. To elucidate GPR161 function, we determined a cryogenic-electron microscopy structure of active GPR161 bound to the heterotrimeric G protein complex Gs. This structure revealed an extracellular loop 2 that occupies the canonical GPCR orthosteric ligand pocket. Furthermore, we identify a sterol that binds to a conserved extrahelical site adjacent to transmembrane helices 6 and 7 and stabilizes a GPR161 conformation required for Gs coupling. Mutations that prevent sterol binding to GPR161 suppress cAMP pathway activation. Surprisingly, these mutants retain the ability to suppress GLI2 transcription factor accumulation in cilia, a key function of ciliary GPR161 in Hedgehog pathway suppression. By contrast, a protein kinase A-binding site in the GPR161 C-terminus is critical in suppressing GLI2 ciliary accumulation. Our work highlights how unique structural features of GPR161 interface with the Hedgehog pathway and sets a foundation to understand the broader role of GPR161 function in other signaling pathways.

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods to clinical data from 6 million patients (24,000 pancreatic cancer cases) in Denmark (Danish National Patient Registry (DNPR)) and from 3 million patients (3,900 cases) in the United States (US Veterans Affairs (US-VA)). We trained machine learning models on the sequence of disease codes in clinical histories and tested prediction of cancer occurrence within incremental time windows (CancerRiskNet). For cancer occurrence within 36 months, the performance of the best DNPR model has area under the receiver operating characteristic (AUROC) curve = 0.88 and decreases to AUROC (3m) = 0.83 when disease events within 3 months before cancer diagnosis are excluded from training, with an estimated relative risk of 59 for 1,000 highest-risk patients older than age 50 years. Cross-application of the Danish model to US-VA data had lower performance (AUROC = 0.71), and retraining was needed to improve performance (AUROC = 0.78, AUROC (3m) = 0.76). These results improve the ability to design realistic surveillance programs for patients at elevated risk, potentially benefiting lifespan and quality of life by early detection of this aggressive cancer.

CellBox: Interpretable Machine Learning for Perturbation Biology with Application to the Design of Cancer Combination Therapy.

Systematic perturbation of cells followed by comprehensive measurements of molecular and phenotypic responses provides informative data resources for constructing computational models of cell biology. Models that generalize well beyond training data can be used to identify combinatorial perturbations of potential therapeutic interest. Major challenges for machine learning on large biological datasets are to find global optima in a complex multidimensional space and mechanistically interpret the solutions. To address these challenges, we introduce a hybrid approach that combines explicit mathematical models of cell dynamics with a machine-learning framework, implemented in TensorFlow. We tested the modeling framework on a perturbation-response dataset of a melanoma cell line after drug treatments. The models can be efficiently trained to describe cellular behavior accurately. Even though completely data driven and independent of prior knowledge, the resulting de novo network models recapitulate some known interactions. The approach is readily applicable to various kinetic models of cell biology. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.

Multiplexed measurement of variant abundance and activity reveals VKOR topology, active site and human variant impact.

Vitamin K epoxide reductase (VKOR) drives the vitamin K cycle, activating vitamin K-dependent blood clotting factors. VKOR is also the target of the widely used anticoagulant drug, warfarin. Despite VKOR's pivotal role in coagulation, its structure and active site remain poorly understood. In addition, VKOR variants can cause vitamin K-dependent clotting factor deficiency or alter warfarin response. Here, we used multiplexed, sequencing-based assays to measure the effects of 2,695 VKOR missense variants on abundance and 697 variants on activity in cultured human cells. The large-scale functional data, along with an evolutionary coupling analysis, supports a four transmembrane domain topology, with variants in transmembrane domains exhibiting strongly deleterious effects on abundance and activity. Functionally constrained regions of the protein define the active site, and we find that, of four conserved cysteines putatively critical for function, only three are absolutely required. Finally, 25% of human VKOR missense variants show reduced abundance or activity, possibly conferring warfarin sensitivity or causing disease.

Evidence that regulation of intramembrane proteolysis is mediated by substrate gating during sporulation in Bacillus subtilis.

During the morphological process of sporulation in Bacillus subtilis two adjacent daughter cells (called the mother cell and forespore) follow different programs of gene expression that are linked to each other by signal transduction pathways. At a late stage in development, a signaling pathway emanating from the forespore triggers the proteolytic activation of the mother cell transcription factor σK. Cleavage of pro-σK to its mature and active form is catalyzed by the intramembrane cleaving metalloprotease SpoIVFB (B), a Site-2 Protease (S2P) family member. B is held inactive by two mother-cell membrane proteins SpoIVFA (A) and BofA. Activation of pro-σK processing requires a site-1 signaling protease SpoIVB (IVB) that is secreted from the forespore into the space between the two cells. IVB cleaves the extracellular domain of A but how this cleavage activates intramembrane proteolysis has remained unclear. Structural studies of the Methanocaldococcus jannaschii S2P homolog identified closed (substrate-occluded) and open (substrate-accessible) conformations of the protease, but the biological relevance of these conformations has not been established. Here, using co-immunoprecipitation and fluorescence microscopy, we show that stable association between the membrane-embedded protease and its substrate requires IVB signaling. We further show that the cytoplasmic cystathionine-ß-synthase (CBS) domain of the B protease is not critical for this interaction or for pro-σK processing, suggesting the IVB-dependent interaction site is in the membrane protease domain. Finally, we provide evidence that the B protease domain adopts both open and closed conformations in vivo. Collectively, our data support a substrate-gating model in which IVB-dependent cleavage of A on one side of the membrane triggers a conformational change in the membrane-embedded protease from a closed to an open state allowing pro-σK access to the caged interior of the protease.

A Systematic p53 Mutation Library Links Differential Functional Impact to Cancer Mutation Pattern and Evolutionary Conservation.

The TP53 gene is frequently mutated in human cancer. Research has focused predominantly on six major "hotspot" codons, which account for only ∼30% of cancer-associated p53 mutations. To comprehensively characterize the consequences of the p53 mutation spectrum, we created a synthetically designed library and measured the functional impact of ∼10,000 DNA-binding domain (DBD) p53 variants in human cells in culture and in vivo. Our results highlight the differential outcome of distinct p53 mutations in human patients and elucidate the selective pressure driving p53 conservation throughout evolution. Furthermore, while loss of anti-proliferative functionality largely correlates with the occurrence of cancer-associated p53 mutations, we observe that selective gain-of-function may further favor particular mutants in vivo. Finally, when combined with additional acquired p53 mutations, seemingly neutral TP53 SNPs may modulate phenotypic outcome and, presumably, tumor progression.

Pathway and network analysis of cancer genomes.

Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations.

Protein structure determination by combining sparse NMR data with evolutionary couplings.

Accurate determination of protein structure by NMR spectroscopy is challenging for larger proteins, for which experimental data are often incomplete and ambiguous. Evolutionary sequence information together with advances in maximum entropy statistical methods provide a rich complementary source of structural constraints. We have developed a hybrid approach (evolutionary coupling-NMR spectroscopy; EC-NMR) combining sparse NMR data with evolutionary residue-residue couplings and demonstrate accurate structure determination for several proteins 6-41 kDa in size.

Regulated spatial organization and sensitivity of cytosolic protein oxidation in Caenorhabditis elegans.

Cells adjust their behaviour in response to redox events by regulating protein activity through the reversible formation of disulfide bridges between cysteine thiols. However, the spatial and temporal control of these modifications remains poorly understood in multicellular organisms. Here we measured the protein thiol-disulfide balance in live Caenorhabditis elegans using a genetically encoded redox sensor and found that it is specific to tissues and is patterned spatially within a tissue. Insulin signalling regulates the sensor's oxidation at both of these levels. Unexpectedly, we found that isogenic individuals exhibit large differences in the sensor's thiol-disulfide balance. This variation contrasts with the general view that glutathione acts as the main cellular redox buffer. Indeed, our work suggests that glutathione converts small changes in its oxidation level into large changes in its redox potential. We therefore propose that glutathione facilitates the sensitive control of the thiol-disulfide balance of target proteins in response to cellular redox events.

Off-target effects dominate a large-scale RNAi screen for modulators of the TGF-ß pathway and reveal microRNA regulation of TGFBR2.

BACKGROUND: RNA interference (RNAi) screens have been used to identify novel components of signal-transduction pathways in a variety of organisms. We performed a small interfering (si)RNA screen for novel members of the transforming growth factor (TGF)-ß pathway in a human keratinocyte cell line. The TGF-ß pathway is integral to mammalian cell proliferation and survival, and aberrant TGF-ß responses have been strongly implicated in cancer. RESULTS: We assayed how strongly single siRNAs targeting each of 6,000 genes affect the nuclear translocation of a green fluorescent protein (GFP)-SMAD2 reporter fusion protein. Surprisingly, we found no novel TGF-ß pathway members, but we did find dominant off-target effects. All siRNA hits, whatever their intended direct target, reduced the mRNA levels of two known upstream pathway components, the TGF-ß receptors 1 and 2 (TGFBR1 and TGFBR2), via micro (mi)RNA-like off-target effects. The scale of these off-target effects was remarkable, with at least 1% of the sequences in the unbiased siRNA library having measurable off-target effects on one of these two genes. It seems that relatively minor reductions of message levels via off-target effects can have dominant effects on an assay, if the pathway output is very dose-sensitive to levels of particular pathway components. In search of mechanistic details, we identified multiple miRNA-like sequence characteristics that correlated with the off-target effects. Based on these results, we identified miR-20a, miR-34a and miR-373 as miRNAs that inhibit TGFBR2 expression. CONCLUSIONS: Our findings point to potential improvements for miRNA/siRNA target prediction methods, and suggest that the type II TGF-ß receptor is regulated by multiple miRNAs. We also conclude that the risk of obtaining misleading results in siRNA screens using large libraries with single-assay readout is substantial. Control and rescue experiments are essential in the interpretation of such screens, and improvements to the methods to reduce or predict RNAi off-target effects would be beneficial.

Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs.

Transfection of small RNAs (such as small interfering RNAs (siRNAs) and microRNAs (miRNAs)) into cells typically lowers expression of many genes. Unexpectedly, increased expression of genes also occurs. We investigated whether this upregulation results from a saturation effect--that is, competition among the transfected small RNAs and the endogenous pool of miRNAs for the intracellular machinery that processes small RNAs. To test this hypothesis, we analyzed genome-wide transcript responses from 151 published transfection experiments in seven different human cell types. We show that targets of endogenous miRNAs are expressed at significantly higher levels after transfection, consistent with impaired effectiveness of endogenous miRNA repression. This effect exhibited concentration and temporal dependence. Notably, the profile of endogenous miRNAs can be largely inferred by correlating miRNA sites with gene expression changes after transfections. The competition and saturation effects have practical implications for miRNA target prediction, the design of siRNA and short hairpin RNA (shRNA) genomic screens and siRNA therapeutics.

MicroRNA profiling of the murine hematopoietic system.

BACKGROUND: MicroRNAs (miRNAs) are a class of recently discovered noncoding RNA genes that post-transcriptionally regulate gene expression. It is becoming clear that miRNAs play an important role in the regulation of gene expression during development. However, in mammals, expression data are principally based on whole tissue analysis and are still very incomplete. RESULTS: We used oligonucleotide arrays to analyze miRNA expression in the murine hematopoietic system. Complementary oligonucleotides capable of hybridizing to 181 miRNAs were immobilized on a membrane and probed with radiolabeled RNA derived from low molecular weight fractions of total RNA from several different hematopoietic and neuronal cells. This method allowed us to analyze cell type-specific patterns of miRNA expression and to identify miRNAs that might be important for cell lineage specification and/or cell effector functions. CONCLUSION: This is the first report of systematic miRNA gene profiling in cells of the hematopoietic system. As expected, miRNA expression patterns were very different between hematopoietic and non-hematopoietic cells, with further subtle differences observed within the hematopoietic group. Interestingly, the most pronounced similarities were observed among fully differentiated effector cells (Th1 and Th2 lymphocytes and mast cells) and precursors at comparable stages of differentiation (double negative thymocytes and pro-B cells), suggesting that in addition to regulating the process of commitment to particular cellular lineages, miRNAs might have an important general role in the mechanism of cell differentiation and maintenance of cell identity.