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bioRxiv2018

Differential Metabolic and Multi-tissue Transcriptomic Responses to Fructose Consumption among Genetically Diverse Mice

High fructose intake is a major risk for metabolic syndrome; however, its effects seem to vary across individuals. To determine main factors involved in the inter-individual responses to fructose, we fed inbred mouse strains C57BL/6J (B6), DBA/2J (DBA) and FVB/NJ (FVB) with fructose. DBA mice showed the highest susceptibility to gain adiposity and glucose intolerance. Elevated insulin was found in DBA and FVB mice, and cholesterol levels were uniquely elevated in B6 mice. The transcriptional profiles of liver, hypothalamus, and adipose tissues showed strain- and tissue-specific pathways altered by fructose, such as fatty acid and cholesterol pathways for B6 and PPAR signaling for DBA in liver, and oxidative phosphorylation for B6 and protein processing for DBA in hypothalamus. Using network modeling, we predicted potential strain-specific key regulators of fructose response such as Fgf21 (DBA) and Lss (B6) in liver, and validated strain-biased responses as well as the regulatory actions of Fgf21 and Lss in primary hepatocytes. Our findings support that fructose perturbs individualized tissue networks and pathways and associates with distinct features of metabolic dysfunctions across genetically diverse mice. Our results elucidate the molecular pathways and gene regulatory mechanisms underlying inter-individual variability in response to high fructose diet.

systems biology↗

bioRxiv2018

In vivo phosphoproteomics reveals pathogenic signaling changes in diabetic islets

Progressive decline of pancreatic beta cells function is key to the pathogenesis of type 2 diabetes. Protein phosphorylation is the central mechanism controlling glucose-stimulated insulin secretion in beta cells. However, if and how signaling networks are remodeled in diabetic islets in vivo remain unknowns. Here we applied high-sensitivity mass spectrometry-based proteomics and quantified the levels of about 6,500 proteins and 13,000 phosphopeptides in islets of obese diabetic mice and matched controls. This highlighted drastic remodeling of key kinase hubs and signaling pathways. We integrated our phosphoproteomic dataset with a literature-derived signaling network, which revealed a crucial and conserved role of GSK3 kinase in the control of the beta cells-specific transcription factor PDX1 and insulin secretion, which we functionally verified. Our resource will enable the community to investigate potential mechanisms and drug targets in type 2 diabetes.

systems biology↗

bioRxiv2018

Host Genetic Background and Gut Microbiota Contribute to Differential Metabolic Responses to High Fructose Consumption in Mice

BackgroundIt is unclear how high fructose consumption induces disparate metabolic responses in genetically diverse mouse strains. ObjectiveWe aim to investigate whether the gut microbiota contributes to differential metabolic responses to fructose. MethodsEight-week-old male C57BL/6J (B6), DBA/2J (DBA), and FVB/NJ (FVB) mice were given 8% fructose solution or regular water (control) for 12 weeks. The gut microbiota composition in cecum and feces was analyzed using 16S rDNA sequencing, and PERMANOVA was used to compare community across mouse strains, treatments, and time points. Microbiota abundance was correlated with metabolic phenotypes and host gene expression in hypothalamus, liver and adipose tissues using Biweight midcorrelation. To test the causal role of the gut microbiota in determining fructose response, we conducted fecal transplants from B6 to DBA mice and vice versa for 4 weeks, as well as gavaged antibiotic-treated DBA mice with Akkermansia for 9 weeks, accompanied with or without fructose treatment. ResultsCompared to B6 and FVB, DBA mice had significantly higher Firmicutes/Bacteroidetes ratio and lower baseline levels of Akkermansia and S24-7 (P < 0.05), accompanied by metabolic dysregulation after fructose consumption. Fructose altered specific microbial taxa in individual mouse strains, such as a 7.27-fold increase in Akkermansia in B6 and 0.374-fold change in Rikenellaceae in DBA (FDR < 5%), which demonstrated strain-specific correlations with host metabolic and transcriptomic phenotypes. Fecal transplant experiments indicated that B6 microbes conferred resistance to fructose-induced weight gain in DBA mice (F = 43.1, P < 0.001), and Akkermansia colonization abrogated the fructose-induced weight gain (F = 17.8, P <0.001) and glycemic dysfunctions (F = 11.8, P = 0.004) in DBA mice. ConclusionsOur findings support that differential microbiota composition between mouse strains is partially responsible for host metabolic sensitivity to fructose, and that Akkermansia is a key bacterium that confers resistance to fructose-induced metabolic dysregulation.

systems biology↗

bioRxiv2018

Designing metabolic division of labor in microbial communities

Microbes face a tradeoff between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A \"gedanken experiment\" to investigate this tradeoff would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation, and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed integer linear programming to identify tradeoff solutions in communities of Escherichia coli strains. The strategies we found reveal a large space of nuanced and nonintuitive metabolic division of labor opportunities, including, for example, splitting the TCA cycle into two separate halves. The systematic computation of possible division of labor solutions for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displays a nonlinear boundary, indicating that the loss of an intracellular reaction is not necessarily compensated by a single imported metabolite. Different regions in this landscape are associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable, but outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor.

systems biology↗

bioRxiv2018

Master regulators of genetic interaction networks mediating statin drug response in Saccharomyces cerevisiae vary with genetic background

Determination of genetic interaction networks (GINs) surrounding drug targets identifies buffering genes and provides molecular insight into drug response in individuals. Here we used backcross methodology to create Saccharomyces cerevisiae deletion libraries in three genetic backgrounds resistant to statins, which are additional to the statin-sensitive S288C deletion library that has provided much of what is known about GINs in eukaryotes. Whole genome sequencing and linkage group analysis confirmed the genomic authenticity of the new deletion libraries. Statin response was probed by drug-gene interactions with atorvastatin and cerivastatin treatments, as well as gene-gene interactions with the statin target HMG1 and HMG2 genes or the sterol homeostatic ARV1 gene. The 20 GINs generated from these interactions were not conserved by function or topology across the four genetic backgrounds. Centrality measures and hierarchical agglomerative clustering identified master regulators that if removed collapsed the networks. Community structure distinguished a characteristic early secretory pathway pattern of gene usage in each genetic background. ER stress in statin-resistant backgrounds was buffered by protein folding genes, which was confirmed by reduced activation of the unfolded protein response in statin-resistant backgrounds relative to the statin-sensitive S288C background. These network analyses of new gene deletion libraries provide insight into the complexity of GINs underlying individual drug response.

systems biology↗

bioRxiv2018

In situ 10-cell RNA sequencing in tissue and tumor biopsy samples

Single-cell transcriptomic methods classify new and existing cell types very effectively, but alternative approaches are needed to quantify the individual regulatory states of cells in their native tissue context. We combined the tissue preservation and single-cell resolution of laser capture with an improved preamplification procedure enabling RNA sequencing of 10 microdissected cells. This in situ 10-cell RNA sequencing (10cRNA-seq) can exploit fluorescent reporters of cell type in genetically engineered mice and is compatible with freshly cryoembedded clinical biopsies from patients. Through recombinant RNA spike-ins, we estimate dropout-free technical reliability as low as ~250 copies and a 50% detection sensitivity of ~45 copies per 10-cell reaction. By using small pools of microdissected cells, 10cRNA-seq improves per-cell reliability and sensitivity beyond existing approaches for single-cell RNA sequencing (scRNA-seq). Accordingly, in multiple tissue and tumor settings, we observe 1.5-2-fold increases in genes detected and overall alignment rates compared to scRNA-seq. Combined with existing approaches to deconvolve small pools of cells, 10cRNA-seq offers a reliable, unbiased, and sensitive way to measure cell-state heterogeneity in tissues and tumors.

systems biology↗

bioRxiv2018

Roles of Polycomb gene EED in pathogenesis and prognosis of acute myeloid leukemia and diffuse large B cell lymphoma

In this study, we performed correlation analysis of polycomb gene EED and hematologic malignancies using the omics and clinical data of acute myeloid leukemia (LAML) and diffuse large B-Cell lymphoma (DLBC) from TCGA database. We found that: (1) High EED mRNA level was associated with poor prognosis and high CALGB cytogenetics risk of LAML patients. (2) EED mRNA level in DLBC cancer cells was higher than control cells. (3) EED gene expression could be regulated by both copy number alterations and DNA methylation. (4) Additionally, there were different EED co-expression genes nets in the two kinds of hematologic malignancies. In all, we confirmed that there are potential clinical significance of EED gene in pathogenesis and prognosis of hematologic malignancies.

systems biology↗

bioRxiv2018

Experiments and simulations on short chain fatty acid production in a colonic bacterial community

Understanding how production of specific metabolites by gut microbes is modulated by interactions with surrounding species and by environmental nutrient availability is an important open challenge in microbiome research. As part of this endeavor, this work explores interactions between F. prausnitzii, a major butyrate producer, and B. thetaiotaomicron, an acetate producer, under three different in vitro media conditions in monoculture and coculture. In silico Genome-scale dynamic flux balance analysis (dFBA) models of metabolism in the system using COMETS (Computation of Microbial Ecosystems in Time and Space) are also tested for explanatory, predictive and inferential power. Experimental findings indicate enhancement of butyrate production in coculture relative to F. prausnitzii monoculture but defy a simple model of monotonic increases in butyrate production as a function of acetate availability in the medium. Simulations recapitulate biomass production curves for monocultures and accurately predict the growth curve of coculture total biomass, using parameters learned from monocultures, suggesting that the model captures some aspects of how the two bacteria interact. However, a comparison of data and simulations for environmental acetate and butyrate changes suggest that the organisms adopt one of many possible metabolic strategies equivalent in terms of growth efficiency. Furthermore, the model seems not to capture subsequent shifts in metabolic activities observed experimentally under low-nutrient regimes. Some discrepancies can be explained by the multiplicity of possible fermentative states for F. prausnitzii. In general, these results provide valuable guidelines for design of future experiments aimed at better determining the mechanisms leading to enhanced butyrate in this ecosystem.\n\nImportanceStudies associating butyrate levels with human colonic health have inspired research on therapeutic microbiota consortia that would optimize butyrate production if implanted in the human colon. Faecalibacterium prausnitzii is commonly observed in human fecal samples and produces butyrate as a product of fermentation. Previous studies indicate that Bacteroides thetaiotaomicron, also commonly found in human fecal samples, may enhance butyrate production in F. prausnitzi when the two species are co-localized. This possibility is investigated here under different environmental conditions using experimental methods paired with computer simulations of the whole metabolism of bacterial cells. Initial findings indicate that interactions between these two species result in enhanced butyrate production. However, results also paint a nuanced picture, suggesting the existence of a multiplicity of equivalently efficient metabolic strategies and complex interactions between acetate and butyrate production in these species that appear highly dependent on specific environmental conditions.

systems biology↗

bioRxiv2018

Cold-Induced Thermogenesis Increases Acetylation on the Brown Fat Proteome and Metabolome

Stimulating brown adipose tissue (BAT) energy expenditure could be a therapy for obesity and related metabolic diseases. Achieving this requires a systems-level understanding of the biochemical underpinnings of thermogenesis. To identify novel metabolic features of active BAT, we measured protein abundance, protein acetylation, and metabolite levels in BAT isolated from mice living in their thermoneutral zone or in colder environments. We find that the enzymes which synthesize lipids from cytosolic acetyl-coA are among the most robustly increased proteins after cold acclimation, consistent with recent studies highlighting the importance of anabolic de novo lipogenesis in BAT. In addition, many mitochondrial proteins are hyperacetylated by cold acclimation, including several sites on UCP1, which may have functional relevance. Metabolomics analysis further reveals cold-dependent increases to acetylated carnitine and several amino acids. This BAT multi-omics resource highlights widespread proteomic and metabolic changes linked to acetyl-CoA synthesis and utilization that may be useful in unraveling the remarkable metabolic properties of active BAT.

systems biology↗

bioRxiv2018

The triangle of ageing: a model of how repair, resilience to damage and asymmetric segregation are responses to replicative ageing

Accumulation of damaged proteins is a hallmark of ageing, occurring in organisms ranging from bacteria and yeast to mammalian cells. During cell division in Saccharomyces cerevisiae, damaged proteins are retained within the mother cell, resulting in a new daughter cell with full replicative potential and an ageing mother with a reduced replicative lifespan (RLS). The cell-specific features determining the lifespan remain elusive. It has been suggested that the RLS is dependent on the ability of the cell to repair and retain pre-existing damage. To deepen the understanding of how these factors influence the life span of individual cells, we developed and experimentally validated a dynamic model of damage accumulation accounting for replicative ageing. The model includes five essential properties: cell growth, damage formation, damage repair, cell division and cell death, represented in a theoretical framework describing the conditions allowing for replicative ageing, starvation, immortality or clonal senescence. We introduce the resilience to damage, which can be interpreted as the difference in volume between an old and a young cell. We show that the capacity to retain damage deteriorates with high age, that asymmetric division allows for retention of damage, and that there is a trade-off between retention and the resilience property. Finally, we derive the maximal degree of asymmetry as a function of resilience, proposing that asymmetric cell division is beneficial with respect to replicative ageing as it increases the RLS of a given organism. The proposed model contributes to a deeper understanding of the ageing process in eukaryotic organisms.

systems biology↗

bioRxiv2018

Ring shape Golden Ratio multicellular structures are algebraically afforded by asymmetric mitosis and one to one cell adhesion

Golden Ratio proportions are found throughout the world of multicellular organisms but the underlying mechanisms behind their appearance and their adaptive value if any remain unknown. The Golden Ratio is a real-valued number but cell population counts are whole numbered. Binet's formula connects the Golden Ratio to the whole numbered Fibonacci sequence (fn+1 = fn + fn-1 where f1 = 1 and f2 = 2), so we seek a cellular mechanism that yields Fibonacci cell kinetics. Drawing on Fibonaccis description of growth patterns in rabbits, we develop a matrix model of Fibonacci cell kinetics based on an asymmetric pause between mitoses by daughter cells. We list candidate molecular mechanisms for asymmetric mitosis such as epigenetically asymmetric chromosomal sorting at anaphase due to cytosine-DNA methylation. A collection of Fibonacci-sized cell groups produced each by mitosis needs to assemble into a larger multicellular structure. We find that the mathematics for this assembly are afforded by a simple molecular cell surface configuration where each cell in each group has four cell to cell adhesion slots. Two slots internally cohere a cell group and two adhere to cells in other cell groups. We provide a notation for expressing each cells participation in dual Fibonacci recurrence relations. We find that single class of cell to cell adhesion molecules suffices to hold together a large assembly of chained Fibonacci groups having Golden Ratio patterns. Specialized bindings between components of various sizes are not required. Furthermore, the notation describes circumstances where chained Fibonacci-sized cell groups may leave adhesion slots unoccupied unless the chained groups anneal into a ring. This unexpected result suggests a role for Fibonacci cell kinetics in the formation of multicellular ring forms such as hollow and tubular structures. In this analysis, a complex molecular pattern behind asymmetric mitosis coordinates with a simple molecular cell adhesion pattern to generate useful multicellular assemblies. Furthermore, this reductively unifies two of the hypothesized evolutionary steps: multicellularity and cellular eusociality.

systems biology↗

bioRxiv2018

A physiology-based model of bile acid metabolism shows altered tissue concentrations after drug administration and in specific genotype subgroups

Drug-induced liver injuries (DILI) are an important issue in drug development and patient safety and often lead to termination of drug-development programs or late withdrawals of drugs. Since DILI events are hard to diagnose in preclinical settings, a need for alternative prediction methods such as computational modeling emerges. Impairment of bile acid (BA) metabolism, known as cholestasis, is a frequent form of DILI. Being rather a systemic then a single organ related disease, whole-body physiology-based modeling is a predestined approach for cholestasis modeling. The objectives of the presented study were 1) the development of a physiology-based model for human bile acid metabolism, 2) model validation and characterization for a virtual population, and 3) prediction and quantification of the effects of genetic predispositions and drug interaction on bile acid metabolism. The developed physiology-based bile acid (PBBA) model is based on the standard PBPK model of PKSim(R) and describes the bile acid circulation in a healthy reference individual. Active processes such as the hepatic synthesis, gallbladder emptying upon meal intake, transition through the gastrointestinal tract, reabsorption into the liver, distribution within the body, and excretion are included. The kinetics of active processes for the surrogate BA glycochenodeoxycholic acid were fitted to time-concentration profiles of blood BA levels reported in literature. The robustness of our PBBA model is underlined by the comparison of simulated plasma BA concentrations in a virtual population of 1,000 healthy individuals with reported data. In addition to plasma concentrations, the PBBA model allows simulations of BA exposure in relevant tissues like the liver and can therefore enhance the mechanistic understanding of cholestasis. This feature was used to analyse the reported increased risk of cholestatic DILI in Benign Recurrent Intrahepatic Cholestasis type 2 (BRIC2) patients. Simulations of the PBBA model suggest a higher susceptibility of BRIC2 patients towards cholestatic DILI due to BA accumulation in hepatocytes. Apart from these intrinsic effects, drug-interactions and their effect on the systemic bile acid metabolism were simulated by combining the PBBA model with a drug PBPK model of cyclosporine A (CsA). The results of which confirmed the reported higher risk of developing DILI as a consequence of CsA intake. Altogether, the presented model enhances our mechanistic understanding of cholestasis, allows the identification of drug-interactions leading to altered BA levels in blood and organs, and could be used to prevent clinical cases of cholestasis and enhance patient safety.

systems biology↗

bioRxiv2018

Long Range Order and Short Range Disorder in Saccharomyces cerevisiae Biofilm

AbstractBiofilm, a colony forming cooperative response of microorganisms under environmental stress, is a major concern for food safety, water safety and drug resistance. Most current works focus on controlling biofilm growth by targeting single genes. Here, we investigated transcriptome-wide expressions of the biofilm yeast Saccharomyces cerevisiae in wildtype, and 6 previously identified biofilm regulating overexpression strains (DIG1, SAN1, TOS8, ROF1, SFL1, HEK2). When tested across various statistical distributions, all transcriptome-wide data fitted well with lognormal distribution above TPM value of 5. Using this threshold as a low expression filter, Pearson auto-and cross-correlation reveal a strong transcriptome-wide invariance among all genotypes, which is also reflected by the random selection of 50 gene expressions. Focusing on the 50 highly expressed genes, however, they differ significantly between the genotypes. Principal components analysis (PCA) shows global similarity between DIG1, SAN1, ROF1, SFL1 and HEK2. Thus, although single overexpression strains may show significant favourable local and acute expression changes (short range disorder), the almost unperturbed global and collective structure between the genotypes indicate gradual adaptive response converging to original stable biofilm states (long range order). Hierarchical clustering and Gene Ontology show 11 groups of local (e.g. mitochondria processes, amine & nucleotide metabolic processes) and 6 groups of global (e.g. transcription, translation & cell cycle) processes for all genotypes. These data indicate that there is a strong global regulatory structure that keeps the overall biofilm stable in all investigated strains.

systems biology↗

bioRxiv2018

A multiscale model of epigenetic heterogeneity reveals the kinetic routes of pathological cell fate reprogramming

The inherent capacity of somatic cells to switch their phenotypic status in response to damage stimuli in vivo might have a pivotal role in ageing and cancer. However, how the entry-exit mechanisms of phenotype reprogramming are established remains poorly understood. In an attempt to elucidate such mechanisms, we herein introduce a stochastic model of combined epigenetic regulation (ER)-gene regulatory network (GRN) to study the plastic phenotypic behaviours driven by ER heterogeneity. Furthermore, based on the existence of multiple scales, we formulate a method for stochastic model reduction, from which we derive an efficient hybrid simulation scheme that allows us to deal with such complex systems. Our analysis of the coupled system reveals a regime of tristability in which pluripotent stem-like and differentiated steady-states coexist with a third indecisive state. Crucially, ER heterogeneity of differentiation genes is for the most part responsible for conferring abnormal robustness to pluripotent stem-like states. We then formulate epigenetic heterogeneity-based strategies capable of unlocking and facilitating the transit from differentiation-refractory (pluripotent stem-like) to differentiation-primed epistates. The application of the hybrid numerical method validated the likelihood of such switching involving solely kinetic changes in epigenetic factors. Our results suggest that epigenetic heterogeneity regulates the mechanisms and kinetics of phenotypic robustness of cell fate reprogramming. The occurrence of tunable switches capable of modifying the nature of cell fate reprogramming from pathological to physiological might pave the way for new therapeutic strategies to regulate reparative reprogramming in ageing and cancer.\n\nAuthor summaryCertain modifications of the structure and functioning of the protein/DNA complex called chromatin can allow adult, fully differentiated cells to adopt a stem cell-like pluripotent state in a purely epigenetic manner, not involving changes in the underlying DNA sequence. Such reprogramming-like phenomena may constitute an innate reparative route through which human tissues respond to injury and could also serve as a novel regenerative strategy in human pathological situations in which tissue or organ repair is impaired. However, it should be noted that in vivo reprogramming would be capable of maintaining tissue homeostasis provided the acquisition of pluripotency features is strictly transient and accompanied by an accurate replenishment of the specific cell types being lost. Crucially, an excessive reprogramming to pluripotency in the absence of controlled re-differentiation would impair the repair or the replacement of damaged cells, thereby promoting pathological alterations of cell fate. A mechanistic understanding of how the degree of chromatin plasticity dictates the reparative versus pathological behaviour of in vivo reprogramming to rejuvenate aged tissues while preventing tumorigenesis is urgently needed, including especially the intrinsic epigenetic heterogeneity of the tissue resident cells being reprogrammed. We here introduce a novel method that mathematically captures how epigenetic heterogeneity is actually the driving force that governs the routes and kinetics to entry into and exit from a pathological pluripotent-like state. Moreover, our approach computationally validates the likelihood of unlocking chronic, unrestrained pluripotent states and drive their differentiation down the correct path by solely manipulating the intensity and direction of few epigenetic control switches. Our approach could inspire new therapeutic approaches based on in vivo cell reprogramming for efficient tissue regeneration and rejuvenation and cancer treatment.

systems biology↗

bioRxiv2018

Testing the Gene Expression Classification of the EMT Spectrum

The epithelial-mesenchymal transition (EMT) plays a central role in cancer metastasis and drug resistance - two persistent clinical challenges. Epithelial cells can undergo a partial or full EMT, attaining either a hybrid epithelial/mesenchymal (E/M) or mesenchymal phenotype, respectively. Recent studies have emphasized that hybrid E/M cells may be more aggressive than their mesenchymal counterparts. However, mechanisms driving hybrid E/M phenotypes remain largely elusive. Here, to better characterize the hybrid E/M phenotype(s) and tumor aggressiveness, we integrate two computational methods - (a) RACIPE - to identify the robust gene expression patterns emerging from the dynamics of a given gene regulatory network, and (b) EMT scoring metric - to calculate the probability that a given gene expression profile displays a hybrid E/M phenotype. We apply the EMT scoring metric to RACIPE-generated gene expression data generated from a core EMT regulatory network and classify the gene expression profiles into relevant categories (epithelial, hybrid E/M, mesenchymal). This categorization is broadly consistent with hierarchical clustering readouts of RACIPE-generated gene expression data. We show that the EMT scoring metric can be used to distinguish between samples composed of exclusively hybrid E/M cells and those containing mixtures of epithelial and mesenchymal subpopulations using the RACIPE-generated gene expression data.

systems biology↗

bioRxiv2018

Signatures of cell death and proliferation in perturbation transcriptomics data - from confounding factor to effective prediction

Transcriptomics perturbation signatures are valuable data sources for functional genomic studies. They can be effectively used to identify mechanism of action for new compounds and to infer functional activity of different cellular processes. Linking perturbation signatures to phenotypic studies opens up the possibility to model selected cellular phenotypes from gene expression data and to predict drugs interfering with the phenotype. At the same time, close association of transcriptomics changes with phenotypes can potentially mask the compound specific signatures. By linking perturbation transcriptomics data from the LINCS-L1000 project with cell viability phenotypic information upon genetic (from Achilles project) and chemical (from CTRP screen) perturbations for more than 90,000 signature - cell viability pairs, we show here that a cell death signature is a major factor behind perturbation signatures. We use this relationship to effectively predict cell viability from transcriptomics signatures, and identify and experimentally validate compounds that induce either cell death or proliferation. We also show that cellular toxicity can lead to an unexpected similarity of toxic compound signatures confounding the mechanism of action discovery. Consensus compound signatures predict cell-specific anti-cancer drug sensitivity, even if the drug signature is not measured in the same cell line. These signatures outperform conventional drug-specific features like nominal target and chemical fingerprints. Our results can help removing confounding factors of large scale transcriptomics perturbation screens and show that expression signatures boost prediction of drug sensitivity.

systems biology↗

bioRxiv2018

Salicylate increases fitness cost associated with MarA-mediated antibiotic resistance

Antibiotic resistance is generally associated with a fitness deficit resulting from the burden of producing and maintaining resistance machinery. This additional cost suggests that resistant bacteria will be outcompeted by susceptible bacteria in conditions without antibiotics. However, in practice this process is slow due in part to regulation that minimizes expression of these genes in the absence of antibiotics. This suggests that if it were possible to turn on their expression, the cost would increase, thereby accelerating removal of resistant strains. Experimental and theoretical studies have shown that environmental chemicals can change the fitness cost associated with resistance and therefore have a significant impact on population dynamics. MarA (multiple antibiotic resistance activator) is a clinically important regulator in Escherichia coli which activates downstream genes to increase resistance against multiple classes of antibiotics. Salicylate is an inducer of MarA which can be found in the environment and de-represses marAs expression. In this study, we sought to unravel the interplay between salicylate and the fitness cost of MarA-mediated antibiotic resistance. Using salicylate as a natural inducer of MarA, we found that a wide spectrum of concentrations can increase burden in resistant strains compared to susceptible strains. Induction resulted in rapid exclusion of resistant bacteria from mixed populations of antibiotic resistant and susceptible cells. A mathematical model captures the process and predicts its effect in various environmental conditions. Our work provides a quantitative understanding of salicylate exposure on the fitness of different MarA variants, and suggests that salicylate can lead to selection against MarA-mediated resistant strains. More generally, our findings show that natural inducers may serve to bias population membership and could impact antibiotic resistance and other important phenotypes.

systems biology↗

bioRxiv2018

A multi-modal proteomics strategy for characterizing posttranslational modifications of tumor suppressor p53 reveals many sites but few modified forms

Post-translational modifications (PTMs) are found on most proteins, particularly on \"hub\" proteins like the tumor suppressor p53, which has over 100 possible PTM sites. Substantial crosstalk between PTM sites underlies the ability of such proteins to integrate diverse signals and coordinate downstream responses. However, disentangling the combinatorial explosion in global PTM patterns across an entire protein (\"modforms\") has been challenging, as conventional peptide-based mass spectrometry strategies (so-called \"bottom-up\" MS) destroy such global correlations. Alternatively, direct analysis of intact and modified proteins using \"top-down\" MS retains global information. Here, we applied both strategies to recombinant p53 phosphorylated in vitro with Chk1 kinase, which exhibited 41 modified sites by bottom-up MS, but no more than 8 modified sites per molecule detected by top-down MS. This observation that many low-abundance modifications comprise relatively few modforms above a 1% threshold indicates that endogenous p53 PTM complexity may be more definable than previously thought.

systems biology↗