Multimodal perturbation analyses of cyclin-dependent kinases reveal a network of synthetic lethalities associated with cell-cycle regulation and transcriptional regulation.

Cell-cycle control is accomplished by cyclin-dependent kinases (CDKs), motivating extensive research into CDK targeting small-molecule drugs as cancer therapeutics. Here we use combinatorial CRISPR/Cas9 perturbations to uncover an extensive network of functional interdependencies among CDKs and related factors, identifying 43 synthetic-lethal and 12 synergistic interactions. We dissect CDK perturbations using single-cell RNAseq, for which we develop a novel computational framework to precisely quantify cell-cycle effects and diverse cell states orchestrated by specific CDKs. While pairwise disruption of CDK4/6 is synthetic-lethal, only CDK6 is required for normal cell-cycle progression and transcriptional activation. Multiple CDKs (CDK1/7/9/12) are synthetic-lethal in combination with PRMT5, independent of cell-cycle control. In-depth analysis of mRNA expression and splicing patterns provides multiple lines of evidence that the CDK-PRMT5 dependency is due to aberrant transcriptional regulation resulting in premature termination. These inter-dependencies translate to drug-drug synergies, with therapeutic implications in cancer and other diseases.

A Neighborhood Grid Clustering Algorithm for Solving Localization Problem in WSN Using Genetic Algorithm.

Finding the location of sensors in wireless sensor networks (WSNs) is a major test, particularly in a wide region. A salient clustering approach is laid out to achieve better performance in such a network using an evolutional algorithm. This paper developed a clustered network called neighborhood grid cluster which has a node assuming the part of a cluster center focused in every grid. Grid-based clustering is less difficult and possesses a lot of benefits compared to other clustering techniques. Besides, we proposed a localization algorithm that centers around assessing the target area by considering the least estimated distance embedded with the genetic algorithm. Performance standards incorporate the energy representation, connectivity stratagem, and distance measure as fitness functions that assess our localization problem to demonstrate its viability. Simulation results confirm that our approach further improves localization accuracy, energy utilization, node lifetime, and localization coverage.

Uncovering Tumorigenesis Circuitry with Combinatorial CRISPR.

Oncogenesis relies on the alteration of multiple driver genes, but precisely which groups of alterations lead to cancer is not well understood. To chart these combinations, Zhao and colleagues use the CRISPR-Cas9 system to knockout all pairwise combinations among 52 tumor suppressor genes, with the goal of identifying groups of alterations that collaborate to promote cell growth. Interaction screens are performed across multiple models of tumorigenesis in cell cultures and mice, revealing clear cooperation among NF2, PTEN, and TP53 in multiple models. These and other strongly synergistic interactions are characterized further by single-cell transcriptomic profiling. This methodology presents a scalable approach to move beyond single-gene drivers to map the complex gene networks that give rise to tumorigenesis.See related article by Zhao et al., p. 6090.

Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients.

Cell-line screens create expansive datasets for learning predictive markers of drug response, but these models do not readily translate to the clinic with its diverse contexts and limited data. In the present study, we apply a recently developed technique, few-shot machine learning, to train a versatile neural network model in cell lines that can be tuned to new contexts using few additional samples. The model quickly adapts when switching among different tissue types and in moving from cell-line models to clinical contexts, including patient-derived tumor cells and patient-derived xenografts. It can also be interpreted to identify the molecular features most important to a drug response, highlighting critical roles for RB1 and SMAD4 in the response to CDK inhibition and RNF8 and CHD4 in the response to ATM inhibition. The few-shot learning framework provides a bridge from the many samples surveyed in high-throughput screens (n-of-many) to the distinctive contexts of individual patients (n-of-one).

GW190521 as a Merger of Proca Stars: A Potential New Vector Boson of 8.7×10

Advanced LIGO-Virgo have reported a short gravitational-wave signal (GW190521) interpreted as a quasicircular merger of black holes, one at least populating the pair-instability supernova gap, that formed a remnant black hole of M_{f}∼142 M_{⊙} at a luminosity distance of d_{L}∼5.3 Gpc. With barely visible pre-merger emission, however, GW190521 merits further investigation of the pre-merger dynamics and even of the very nature of the colliding objects. We show that GW190521 is consistent with numerically simulated signals from head-on collisions of two (equal mass and spin) horizonless vector boson stars (aka Proca stars), forming a final black hole with M_{f}=231_{-17}^{+13} M_{⊙}, located at a distance of d_{L}=571_{-181}^{+348} Mpc. This provides the first demonstration of close degeneracy between these two theoretical models, for a real gravitational-wave event. The favored mass for the ultralight vector boson constituent of the Proca stars is µ_{V}=8.72_{-0.82}^{+0.73}×10^{-13} eV. Confirmation of the Proca star interpretation, which we find statistically slightly preferred, would provide the first evidence for a long sought dark matter particle.

Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells.

Most drugs entering clinical trials fail, often related to an incomplete understanding of the mechanisms governing drug response. Machine learning techniques hold immense promise for better drug response predictions, but most have not reached clinical practice due to their lack of interpretability and their focus on monotherapies. We address these challenges by developing DrugCell, an interpretable deep learning model of human cancer cells trained on the responses of 1,235 tumor cell lines to 684 drugs. Tumor genotypes induce states in cellular subsystems that are integrated with drug structure to predict response to therapy and, simultaneously, learn biological mechanisms underlying the drug response. DrugCell predictions are accurate in cell lines and also stratify clinical outcomes. Analysis of DrugCell mechanisms leads directly to the design of synergistic drug combinations, which we validate systematically by combinatorial CRISPR, drug-drug screening in vitro, and patient-derived xenografts. DrugCell provides a blueprint for constructing interpretable models for predictive medicine.

A Fast and Flexible Framework for Network-Assisted Genomic Association.

We present an accessible, fast, and customizable network propagation system for pathway boosting and interpretation of genome-wide association studies. This system-NAGA (Network Assisted Genomic Association)-taps the NDEx biological network resource to gain access to thousands of protein networks and select those most relevant and performative for a specific association study. The method works efficiently, completing genome-wide analysis in under 5 minutes on a modern laptop computer. We show that NAGA recovers many known disease genes from analysis of schizophrenia genetic data, and it substantially boosts associations with previously unappreciated genes such as amyloid beta precursor. On this and seven other gene-disease association tasks, NAGA outperforms conventional approaches in recovery of known disease genes and replicability of results. Protein interactions associated with disease are visualized and annotated in Cytoscape, which, in addition to standard programmatic interfaces, allows for downstream analysis.

Strategies for Network GWAS Evaluated Using Classroom Crowd Science.

Biological networks can substantially boost power to identify disease genes in genome-wide association studies. To explore different network GWAS methods, we challenged students of a UC San Diego graduate level bioinformatics course, Network Biology and Biomedicine, to explore and improve such algorithms during a four-week-long classroom competition. Here, we report the many creative solutions and share our experiences in conducting classroom crowd science as both a research and pedagogical tool.

DDOT: A Swiss Army Knife for Investigating Data-Driven Biological Ontologies.

Systems biology requires not only genome-scale data but also methods to integrate these data into interpretable models. Previously, we developed approaches that organize omics data into a structured hierarchy of cellular components and pathways, called a "data-driven ontology." Such hierarchies recapitulate known cellular subsystems and discover new ones. To broadly facilitate this type of modeling, we report the development of a software library called the Data-Driven Ontology Toolkit (DDOT), consisting of a Python package (https://github.com/idekerlab/ddot) to assemble and analyze ontologies and a web application (http://hiview.ucsd.edu) to visualize them. Using DDOT, we programmatically assemble a compendium of ontologies for 652 diseases by integrating gene-disease mappings with a gene similarity network derived from omics data. For example, the ontology for Fanconi anemia describes known and novel disease mechanisms in its hierarchy of 194 genes and 74 subsystems. DDOT provides an easy interface to share ontologies online at the Network Data Exchange.

Central neuropeptide B administration activates stress hormone secretion and stimulates feeding in male rats.

Neuropeptide B (NPB) was identified to be an endogenous, peptide ligand for the orphan receptors GPR7 and GPR8. Because GPR7 is expressed in rat brain and, in particular, in the hypothalamus, we hypothesized that NPB might interact with neuroendocrine systems that control hormone release from the anterior pituitary gland. No significant effects of NPB were observed on the in vitro releases of prolactin, adrenocorticotropic hormone (ACTH) or growth hormone (GH) when log molar concentrations ranging from 1 pM to 100 nM NPB were incubated with dispersed anterior pituitary cells harvested from male rats. In addition NPB (100 nM) did not alter the concentration response stimulation of prolactin secretion by thyrotropin-releasing hormone, ACTH secretion by corticotropin-releasing factor (CRF) and GH secretion by GH-releasing hormone. However, NPB, when injected into the lateral cerebroventricle (i.c.v.) of conscious, unrestrained male rats, elevated prolactin and corticosterone, and lowered GH levels in circulation. The threshold dose for the effect on corticosterone and prolactin levels was 1.0 nmol, while that for the effect on GH release was 3.0 nmol NPB. Pretreatment with a polyclonal anti-CRF antiserum completely blocked the ability of NPB to stimulate ACTH release and significantly inhibited the effect of NPB on plasma corticosterone levels. NPB administration i.c.v. did not significantly alter plasma vasopressin and oxytocin levels in conscious rats. It did stimulate feeding (minimum effective dose 1.0 nmol) in sated animals in a manner similar to that of the other endogenous ligand for GPR7, neuropeptide W. We conclude that NPB can act in the brain to modulate neuroendocrine signals accessing the anterior pituitary gland, but does not itself act as a releasing or inhibiting factor in the gland, at least with regard to prolactin, ACTH and GH secretion.

Effects of raclopride in the nucleus accumbens on ethanol seeking and consumption.

BACKGROUND: Nucleus accumbens dopamine has been shown to play a role in the processing of behaviorally relevant stimuli and to mediate ethanol-reinforced responding. Previous research that used a fixed-ratio schedule of responding maintained by the presentation of small dippers (0.1 ml) of ethanol demonstrated that the dopamine D2 antagonist, raclopride, decreased total responding for ethanol by both delaying the onset of responding and causing the early termination of lever-press behavior. Because these studies required animals to continuously respond to obtain access to small amounts of ethanol over a period of self-administration, this procedure assessed a combination of appetitive (seeking) and consummatory (drinking) behavior. The paradigm used in the present study separated the appetitive or seeking response from the consummatory response to assess the effects of raclopride on both types of ethanol-related behaviors. METHODS: Male Long-Evans rats were trained to emit a fixed number of lever-press responses that resulted in access to a drinking tube that contained 10% ethanol for 20 min, once each day. We measured the effects of microinjections of raclopride (1.0, 3.0, and 10.0 microg/subject) into the nucleus accumbens, before the sessions, on appetitive and consummatory responding. RESULTS: Raclopride delayed the onset of ethanol-seeking (appetitive responding) at all doses and decreased the number of responses made at the low and high doses. The rate of responding, however, was unaffected. Raclopride had no effect on the latency to begin consuming ethanol or on any of the characteristics of the initial bout of ethanol intake at all doses tested. Total ethanol intake was decreased, after an initially "normal" pattern of self-administration, following only the highest dose of raclopride. Mean ethanol intake (g/kg) was 0.54 (+/-0.03) after no injection, 0.51 (+/-0.04) after sham treatment, and 0.38 (+/-0.05) after 10 microg of raclopride. CONCLUSIONS: The procedural separation of the seeking and intake responses used in this experiment allowed us to assess the effects of dopamine receptor antagonism in the nucleus accumbens on these two different behaviors. Overall, appetitive responding that preceded the delivery of an ethanol solution was more sensitive to raclopride treatment than was consummatory responding. These findings are consistent with a stimulus-processing function of the mesolimbic dopamine system.

Measuring ethanol-seeking behavior: the effect of using repeated extinction trials.

The development of a reliable measure of the level of ethanol-seeking behavior in an animal model is important to understanding the concept of craving. However, most existing models do not allow for the separation of the behavior associated with obtaining ethanol from that involved in consumption of ethanol. In this study, we determined the ability of repeated, single-session extinction tests in an appetitive and consummatory procedure of ethanol self-administration to assess the level of seeking behavior. The findings indicated that there were no major effects of previous extinction trials on later trials, when there were at least four reinforced sessions between tests. During reinforced sessions, the rats were consuming an average of 0.80 g of ethanol per kilogram of body weight in less than 20 min from a sipper tube. In addition, the amount of extinction responding was found to be similar to a previous measure of the appetitive strength of ethanol by using a breakpoint procedure. This method of repeated extinction tests seems to be valuable for examining the effects of pharmacological treatments that might alter ethanol seeking.

Effect of naloxone on appetitive and consummatory phases of ethanol self-administration.

BACKGROUND: The opioid system has been implicated in ethanol self-administration. Morphine, an opiate agonist, can sometimes increase the amount of ethanol consumed, and opiate antagonists such as naloxone and naltrexone decrease the amount of ethanol consumed in both animals and humans. The objective of this study was to examine the effect of naloxone on appetitive (or seeking) and consummatory behaviors by using an operant model developed to separate these two phases of self-administration. METHODS: Intraperitoneal injections of naloxone (0.3-10 mg/kg) or vehicle were given before operant self-administration sessions to assess the effect on lever pressing (appetitive behavior) and subsequent consumption. Effects were measured in two groups of rats: one self-administered a 3% sucrose solution and the other a 10% ethanol solution. RESULTS: Naloxone dose-dependently decreased ethanol and sucrose consumption by an earlier cessation of drinking in the session compared with vehicle injection days. There were some effects on appetitive responding after treatment with naloxone, but none was statistically significant. CONCLUSIONS: Naloxone may decrease ethanol self-administration by decreasing the postingestive or pharmacological effects of alcohol. This model provides a new method for examining the effects of potential pharmacotherapeutics on alcohol self-administration behavior.

Injected muscimol in pedunculopontine tegmental nucleus alters ethanol self-administration.

The pedunculopontine tegmental nucleus (PPN) has been implicated in a variety of behavioral functions, including stimulus selection. Given the PPN interactions with the mesolimbic system, it was considered important to determine its involvement in ethanol self-administration. Long-Evans male rats were trained to self-administer 10% ethanol by using a sucrose-substitution procedure. After implantation of cannula guides, microinjections of 30, 100, and 300 ng of muscimol into the PPN before the self-administration session were performed. Ethanol self-administration was decreased at the 300-ng dose, in a manner similar to the actions of dopamine agonists microinjected in the nucleus accumbens. It is hypothesized that loss of PPN cholinergic input to the mesolimbic system affects the integrative activity of the nucleus accumbens and underlies the observed change in ethanol self-administration behavior.

Effects of acamprosate on ethanol-seeking and self-administration in the rat.

BACKGROUND: Acamprosate (calcium acetyl homotaurinate) has been used clinically to treat relapse in alcoholics. In rats, it has been shown to decrease ethanol, but not water, self-administration after ethanol deprivation. METHODS: To further investigate the effect of acamprosate on reinforced behaviors in rats, the present experiment used: (1) both ethanol and sucrose reinforcer solutions to better assess the distinct effects of acamprosate on ethanol-directed behaviors, and (2) an operant model that procedurally separates the "cost" to begin drinking from consuming the reinforcer solutions to dissociate the effects of acamprosate on appetitive versus consummatory processes. In daily sessions (5 days/week), rats (n = 6/group) were trained to make 30 lever-press responses to gain access for 20 min to a sipper tube containing either ethanol (10%) or sucrose (3%). After stable responding, acamprosate treatment was given. Three doses were tested (50, 100, and 200 mg/kg/injection, intraperitoneally), one dose per week. Each week, a total of four injections were given (21 and 2 hr before the operant sessions over 2 consecutive days). RESULTS: At these doses, acamprosate had no effect on the measures of appetitive responding for either solution. However, all doses reliably decreased ethanol consumption on the 2nd day of treatment (from an average of 0.83 to 0.63 g/kg). Analysis of the pattern of ethanol consumption showed that the effects of acamprosate occurred after the onset of a normal pattern of intake, as measured by lick rate and size of the initial bout of drinking, which suggested that acamprosate is most effective when combined with the pharmacological effects of ethanol. Sucrose intake was unaffected by all acamprosate treatments, which indicated that the treatment effects were specific to ethanol and not due to a general decrease in consummatory behavior. CONCLUSIONS: Overall, these results suggest that acamprosate is effective at reducing total ethanol intake, but may not reliably alter subjects propensity to begin a drinking bout as measured by this model. However, whether this applies to the clinical use of acamprosate, where other types of reinforcement may also precipitate relapse drinking, is not certain.

Effects of SR141716A on ethanol and sucrose self-administration.

BACKGROUND: Previous studies have demonstrated that administration of central cannabinoid receptor (CB1) ligands can produce marked effects on ingestive behaviors. However, the possible relationship to ethanol self-administration has not been fully examined. The present series of experiments was designed to characterize further the role of CB1 receptors in appetitive and consummatory behaviors related to sucrose and ethanol. METHODS: To determine the relative contribution of CB1 receptors to ethanol seeking and consumption, a series of experiments was designed using the sipper-tube model. In this paradigm, the appetitive and consummatory phases of ethanol and sucrose self-administration are separated. In the appetitive phase, animals are required to complete a response requirement (16 lever presses) within 20 min. If the requirement is successfully completed, access to a sipper tube containing either sucrose or ethanol (consummatory phase) is made available for 20 min. RESULTS: In the ethanol condition, the CB1 receptor antagonist SR141716A (0.3-3.0 mg/kg, ip) produced dose-related decreases in the probability of response requirement completion without significantly affecting latency to first lever press or overall lever press rate. In the sucrose condition, SR141716A (0.3-3.0 mg/kg, ip) increased first lever press latency without affecting lever press rate. In the consummatory phase, SR141716A (0.3-3.0 mg/kg, ip) administration markedly decreased total intake and the total number of licks for both ethanol and sucrose. CONCLUSIONS: These data indicate that CB1 receptors are involved in mediating both appetitive and consummatory aspects of ingestive behaviors related to sucrose and ethanol.

Muscimol injected into the medial prefrontal cortex of the rat alters ethanol self-administration.

The role of the rodent prefrontal cortex in the regulation of ethanol self-administration has not been widely explored. Understanding the role of GABAergic transmission in this area in relation to ethanol self-administration is important, as the GABA system may be one of several targets for alcohol's actions in the brain. Rats were initiated to drink 10% ethanol from a dipper using a sucrose-substitution procedure. When baseline behavior was stable, bilateral microinjections of muscimol (a GABA(A) agonist) into the prefrontal cortex were tested at doses of 17.5, 30, 100 and 300 ng/microl. Ethanol self-administration was decreased by approximately 40% at the 30-ng dose and 30% at the 100-ng dose. No effects were observed at either the 17.5- or 300-ng dose. The effect on the pattern of self-administration was to shorten the size of the first run of drinking without affecting the rate of drinking. The hypothesis is put forward that the injections increased glutamatergic output to the nucleus accumbens (nAcc) that in turn increased accumbens output. This increased output is proposed as similar to the effects of dopaminergic (DA) manipulations within this system.

The microstructure of ethanol drinking: genetic and behavioral factors in the control of drinking patterns.

The concept of craving can be examined in many different ways, depending upon the individual definition of the term. Using the concepts and procedures of regulatory behavior analysis, this review explores behavioral studies in rats that have some relationships to some of the possible processes that underlie the concept of craving in humans. Data are reviewed from studies employing both limited and continuous access to ethanol, examining the role of access availability, ethanol initiation, response cost, time since last access, composition of the ethanol containing solution and genetic selection. From this review, it is clear that rat models can implicate important variables involved in the control of human alcohol consumption.