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bioRxiv2018

Limits to the rate of information transmissionthrough MAPK pathway

Two important signaling pathways of NF-{kappa}B and ERK transmit merely one bit of information about the level of extracellular stimulation. It is thus unclear how such systems can coordinate complex cell responses to external cues. Here, we analyze information transmission in the MAPK/ERK pathway that features relaxation oscillations and responds to EGF by pulses of activated ERK. Based on an experimentally verified computational model of the MAPK/ERK pathway, we demonstrate that when input sequences of EGF pulses are transcoded to output sequences of ERK activity pulses, transmitted information increases nearly linearly with time. Moreover, the information channel capacity C (defined as the upper limit of information that can be transmitted over a sufficiently long time t, divided by t), is not limited by the bandwidth B = 1/{tau}, where {tau} {approx} 1 hour is the relaxation time. Specifically, when input is provided in the form of sequences of short binary EGF pulses separated by varying intervals that are multiples of {tau}/n (but are not shorter than {tau}), then for n = 2, C {approx} 1.39 bit/hour; and for n = 4, C {approx} 1.86 bit/hour. We hypothesize that the primary mode of operation of the MAPK pathway is to translate extracellular growth factor \"bursts\" into precisely timed intracellular ERK \"spikes\" of a predefined amplitude. Such pulse-interval transcoding allows to relay more information than the amplitude-amplitude transcoding considered previously for the ERK and NF-{kappa}B pathways.\n\nAuthor summaryTo coordinate their actions, cells communicate with each other by sending, receiving, and interpreting cytokine signals. Cells recognize chemical identity of signaling molecules and process quantitative and temporal properties of stimulation: amplitude, duration, or frequency. Previous studies indicated that the MAPK pathway transmits about one bit of information about the amplitude (concentration) of a stimulating cytokine, EGF. Sending more information may be enabled by temporal signal modulation. Here, we use the conceptual framework of information theory to support a hypothesis that the MAPK pathway, analyzed as a noisy information channel, reaches maximum information transmission rate when receiving sequences of EGF pulses that are transcoded to sequences of activity pulses of an effector kinase of the pathway, ERK. Since the pathway resetting time is about 1 hour, one could expect that--when sending EGF pulses of \"0\" or \"1\" amplitude every hour--the pathway is able transmit up to 1 bit per hour. We show, however, that when EGF pulses are separated by intervals that are not shorter than 1 hour and are multiples of 15 min (60, 75, 90 min, etc.), information rate can be nearly 2 bits per hour. We hypothesize that high information rate is necessary to control cell proliferation and motility.

systems biology↗

bioRxiv2018

SIS-seq, a molecular ‘time machine’, connects single cell fate with gene programs

Conventional single cell RNA-seq methods are destructive, such that a given cell cannot also then be tested for fate and function, without a time machine. Here, we develop a clonal method SIS-seq, whereby single cells are allowed to divide, and progeny cells are assayed separately in SISter conditions; some for fate, others by RNA-seq. By cross-correlating progenitor gene expression with mature cell fate within a clone, and doing this for many clones, we can identify the earliest gene expression signatures of dendritic cell subset development. SIS-seq could be used to study other populations harboring clonal heterogeneity, including stem, reprogrammed and cancer cells to reveal the transcriptional origins of fate decisions.

systems biology↗

bioRxiv2018

Genetic control of the HDL proteome

High-density lipoproteins (HDL) are nanoparticles with >80 associated proteins, phospholipids, cholesterol and cholesteryl esters. A comprehensive genetic analysis of the regulation of proteome of HDL isolated from a panel of 100 diverse inbred strains of mice, Hybrid Mouse Diversity Panel (HMDP), revealed widely varied HDL protein levels across the strains. Some of this variation was explained by local, cis-acting regulation, termed cis-protein quantitative trait loci. Variations in apolipoprotein A-II and apolipoprotein C-3 affected the abundance of multiple HDL proteins indicating a coordinated regulation. We identified modules of co-varying proteins and define a protein-protein interaction network describing the protein composition of the naturally occurring subspecies of HDL in mice. Sterol efflux capacity varied up to 3-fold across the strains and HDL proteins displayed distinct correlation patterns with macrophage and ABCA1 specific cholesterol efflux capacity and cholesterol exchange, suggesting that subspecies of HDL participate in discrete functions. The baseline and stimulated sterol efflux capacity phenotypes associated with distinct QTLs with smaller effect size suggesting a multi genetic regulation. Our results highlight the complexity of HDL particles by revealing high degree of heterogeneity and intercorrelation, some of which is associated with functional variation, supporting the concept that HDL-cholesterol alone is not an accurate measure of HDLs properties such as protection against CAD.

systems biology↗

bioRxiv2018

Coupled active systems encode emergent behavioral dynamics of the unicellular predator Lacrymaria olor

Multiple active systems in a cell work together to produce sophisticated cellular behaviors such as motility and search. However, it is often unclear how this coupling specifies the complex emergent dynamics that define such behaviors. As a model system, we analyzed the hunting strategy of Lacrymaria olor, a unicellular predatory ciliate that uses extreme morphological changes to extend, contract and whip an apparent \"cell neck\" over many body lengths to capture prey. Tracking millions of unique subcellular morphologies over time revealed that these fast dynamics encode a comprehensive local search behavior apparent only at longer timescales. This hunting behavior emerges as a tug-of-war between active sub-cellular structures that use surface cilia and cortex contractility to deform the structure of the neck. The resulting search space can be described mathematically using a small number of normal shape modes that change amplitude rapidly during hunts. The distribution of these shape modes in space and time reveals a transition point between tense and compressed neck morphologies at the mean neck length, such that new shapes are readily sampled by repeatedly extending and retracting across this critical length. Molecular perturbations to the cell-signaling controller show that coupling between ciliary and contractile programs is needed to maintain this length/shape relationship; neither system alone provides the dynamic repertoire of shapes necessary for comprehensive search. Our results highlight the utility of coupling antagonistic active systems as a strategy for encoding or engineering complex behaviors in molecular machines.\n\nOne Sentence Summary: Analysis of millions of unique cellular morphologies of the highly dynamic single-celled predator Lacrymaria olor reveals that it programs a comprehensive search space and emergent hunting behavior through coupling surface based active cilia and cortex based contractile molecular systems together.

systems biology↗

bioRxiv2018

Modeling slow-processing of toxin messenger RNAs in type-I Toxin-Antitoxin systems: post-segregational killing and noise filtering

In type-I toxin-antitoxin (TA) systems, the action of growth-inhibiting toxin proteins is counteracted by the antitoxin small RNAs (sRNAs) that prevent the translation of toxin messenger RNAs (mRNAs). When a TA module is encoded on a plasmid, the short lifetime of antitoxin sRNA compared to toxin mRNAs mediates post-segregational killing (PSK) that contribute the plasmid maintenance, while some of the chromosomal encoded TA loci have been reported to contribute to persister formation in response to a specific upstream signal. Some of the well studied type-I TA systems such as hok/sok are known to have a rather complex regulatory mechanism. Transcribed full-length toxin mRNAs fold such that the ribosome binding site is not accessible and hence cannot be translated. The mRNAs are slowly processed by RNases, and the truncated mRNAs can be either translated or bound by antitoxin sRNA to be quickly degraded. We analyze the role of this extra processing by a mathematical model. We first consider the PSK scenario, and demonstrate that the extra processing compatibly ensures the high toxin expression upon complete plasmid loss, without inducing toxin expression upon acquisition of a plasmid or decrease of plasmid number to a non-zero number. We further show that the extra processing help filtering the transcription noise, avoiding random activation of toxins in transcriptionally regulated TA systems as seen in chromosomal ones. The present model highlights impacts of the slow processing reaction, offering insights on why the slow processing reactions are commonly identified in multiple type-I TA systems.

systems biology↗

bioRxiv2018

ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra

In metabolomics, the detection of new biomarkers from NMR spectra is a promising approach. However, this analysis remains difficult due to the lack of a whole workflow that handles spectra pre-processing, automatic identification and quantification of metabolites and statistical analyses.\n\nWe present ASICS, an R package that contains a complete workflow to analyse spectra from NMR experiments. It contains an automatic approach to identify and quantify metabolites in a complex mixture spectrum and uses the results of the quantification in untargeted and targeted statistical analyses. ASICS was shown to improve the precision of quantification in comparison to existing methods on two independant datasets. In addition, ASICS successfully recovered most metabolites that were found important to explain a two level condition describing the samples by a manual and expert analysis based on bucketting. It also found new relevant metabolites involved in metabolic pathways related to risk factors associated with the conditions.\n\nThis workflow is available through the R package ASICS, available on the Bioconductor platform.

systems biology↗

bioRxiv2018

Comparison of null models for combination drug therapy reveals Hand model as biochemically most plausible

Null models for the effect of combination therapies are widely used to evaluate synergy and antagonism of drugs. Due to the relevance of null models, their suitability is continuously discussed. Here, we contribute to the discussion by investigating the properties of five null models. Our study includes the model proposed by David J. Hand, which we refer to as Hand model. The Hand model has been introduced almost 20 years ago but hardly was used and studied. We show that the Hand model generalizes the principle of dose equivalence compared to the Loewe model and resolves the ambiguity of the Tallarida model. This provides a solution to the persisting conflict about the compatibility of two essential model properties: the sham combination principle and the principle of dose equivalence. By embedding several null models into a common framework, we shed light in their biochemical validity and provide indications that the Hand model is biochemically most plausible. We illustrate the practical implications and differences between null models by examining differences of null models on published data.

systems biology↗

bioRxiv2018

Integrative analysis of Paneth cell proteomic data from intestinal organoids reveals functional processes affected in Crohn’s disease due to autophagy impairment

Summary statementUsing an integrative approach encompassing intestinal organoid culture, proteomics, transcriptomics and protein-protein interaction networks, we list Paneth cell functions dependent on autophagy.\n\nAbstractPaneth cells are key epithelial cells providing an antimicrobial barrier and maintaining integrity of the small intestinal stem cell niche. Paneth cell abnormalities are unfortunately detrimental to gut health and often associated with digestive pathologies such as Crohns disease or infections. Similar alterations are observed in individuals with impaired autophagy, a process which recycles cellular components. The direct effect of autophagy-impairment on Paneth cells has not been analysed. To investigate this, we generated a mouse model lacking Atg16l1 specifically in intestinal epithelial cells making these cells impaired in autophagy. Using 3D intestinal organoids enriched for Paneth cells, we compared the proteomic profiles of wild-type (WT) and autophagy-impaired organoids. We used an integrated computational approach combining protein-protein interaction networks, autophagy targeted proteins and functional information to identify the mechanistic link between autophagy-impairment and disrupted pathways. Of the 284 altered proteins, 198 (70%) were more abundant in autophagy-impaired organoids, suggesting reduced protein degradation. Interestingly, these differentially abundant proteins comprised 116 proteins (41%), predicted targets of the selective autophagy proteins p62, LC3 and ATG16L1. Our integrative analysis revealed autophagy-mediated mechanisms degrading proteins key to Paneth cell functions, such as exocytosis, apoptosis and DNA damage repair. Transcriptomic profiling of additional organoids confirmed that 90% of the observed changes upon autophagy alteration affect protein level and not gene expression. We performed further validation experiments showing differential lysozyme secretion, confirming our computationally inferred down-regulation of exocytosis. Our observations could explain how protein level alterations affect Paneth cell homeostatic functions upon autophagy impairment.

systems biology↗

bioRxiv2018

Stage specific classification of DEGs via statistical profiling and network analysis reveals potential biomarker associated with various stages of TB

BackgroundTuberculosis (TB) is a deadly transmissible disease that can infect almost any body-part of the host but is mostly infect the lungs. It is one of the top 10 causes of death worldwide. In the 30 high TB burden countries, 87% of new TB cases occurred in 2016. Seven countries: India, Indonesia, China, Philippines, Pakistan, Nigeria, and South Africa accounted for 64% of the new TB cases. To stop the infection and progression of the disease, early detection of TB is important. In our study, we used microarray data set and compared the gene expression profiles obtained from blood samples of patients with different datasets of Healthy control, Latent infection, Active TB and performed network-based analysis of DEGs to identify potential biomarker.\n\nObjectivesWe want to observe the transition of genes from normal condition to different stages of the TB and identify, annotate those genes/pathways/processes that play key role in the progression of TB disease during its cyclic interventions in human body.\n\nResultsWe identified 319 genes that are differentially expressed in various stages of TB (Normal to LTTB, Normal to Active TB and LTTB to active TB) and allocated to pathways from multiple databases which comprised of curated class of associated genes. These pathways importance was then evaluated according to the no. of DEGs present in the pathway and these genes show the broad spectrum of processes that take part in every state. In addition, we studied the regulatory networks of these classified genes, network analysis does consider the interactions between genes (specific for TB) or proteins provide us new facts about TB disease, which in turn can be used for potential biomarkers identification. We identified total 29 biomarkers from various comparison groups of TB stages in which 14 genes are over expressed as host responses against pathogen, but 15 genes are down regulated that means these genes has allowed the process of host defense to cease and give time to pathogen for its progression.\n\nConclusionsThis study revealed that gene-expression profiles can be used to identify and classified the genes on stage specific pattern among normal, LTTB and active TB and network modules associated with various stages of TB were elucidated, which in turn provided a basis for the identification of potential pathways and key regulatory genes that may be involved in progression of TB disease.

systems biology↗

bioRxiv2018

Immune differentiation regulator p100 tunes NF-κB responses to TNF

Stringent regulation of TNF signaling prevents aberrant inflammation. TNF engages the canonical NF-{kappa}B pathway for activating the RelA:p50 heterodimer, which mediates specific expressions of pro-inflammatory and immune response genes. Importantly, the NF-{kappa}B system discriminates between time-varied TNF inputs. Negative feedback regulators of the canonical pathway, including I{kappa}B, are thought to ensure transient RelA:p50 responses to brief TNF stimulations. The noncanonical NF-{kappa}B pathway controls a separate RelB activity associated with immune differentiation. In a systems modeling approach, we uncovered an unexpected role of p100, a constituent of the noncanonical pathway, in TNF signaling. Brief TNF stimulation of p100-deficient cells produced an additional late NF-{kappa}B activity consisted of the RelB:p50 heterodimer, which distorted the TNF-induced gene-expression program. Periodic TNF pulses augmented this RelB:p50 activity, which was reinforced by NF-{kappa}B-dependent RelB synthesis. In sum, the NF-{kappa}B system seems to engage distantly related molecules for enforcing dynamical and gene controls of immune-activating TNF signaling.

systems biology↗

bioRxiv2018

Reconciling high-throughput gene essentiality data with metabolic network reconstructions

The identification of genes essential for bacterial growth and survival represents a promising strategy for the discovery of antimicrobial targets. Essential genes can be identified on a genome-scale using transposon mutagenesis approaches; however, variability between screens and challenges with interpretation of essentiality data hinder the identification of both condition-independent and condition-dependent essential genes. To illustrate the scope of these challenges, we perform a large-scale comparison of multiple published Pseudomonas aeruginosa gene essentiality datasets, revealing substantial differences between the screens. We then contextualize essentiality using genome-scale metabolic network reconstructions and demonstrate the utility of this approach in providing functional explanations for essentiality and reconciling differences between screens. Genome-scale metabolic network reconstructions also enable a high-throughput, quantitative analysis to assess the impact of media conditions on the identification of condition-independent essential genes. Our computational model-driven analysis provides mechanistic insight into essentiality and contributes novel insights for design of future gene essentiality screens and the identification of core metabolic processes.\n\nAuthor SummaryWith the rise of antibiotic resistance, there is a growing need to discover new therapeutic targets to treat bacterial infections. One attractive strategy is to target genes that are essential for growth and survival. Essential genes can be identified with transposon mutagenesis approaches; however, variability between screens and challenges with interpretation of essentiality data hinder the identification and analysis of essential genes. We performed a large-scale comparison of multiple gene essentiality screens of the microbial pathogen Pseudomonas aeruginosa. We implemented a computational model-driven approach to provide functional explanations for essentiality and reconcile differences between screens. The integration of computational modeling with high-throughput experimental screens may enable the identification of drug targets with high-confidence and provide greater understanding for the development of novel therapeutic strategies.

systems biology↗

bioRxiv2018

Multiple sources of signal amplification within the B cell Ras/MAPK pathway

The Ras-Map kinase (MAPK) cascade underlies functional decisions in a wide range of cell types and organisms. In B cells, positive feedback-driven Ras activation is the proposed source of the digital (all-or-none) MAPK responses following antigen stimulation. However, an inability to measure endogenous Ras activity in living cells has hampered our ability to test this model directly. Here we leverage biosensors of endogenous Ras and ERK activity to revisit this question. We find that BCR ligation drives switch-like Ras activation and that lower BCR signaling output is required for the maintenance versus the initiation of Ras activation. Surprisingly, digital ERK responses persist in the absence of positive feedback-mediated Ras activation, and digital ERK is observed at a threshold level of Ras activation. These data suggest an independent analog-to-digital switch downstream of Ras activation, and reveals that multiple sources of signal amplification exist within the Ras-ERK module of the BCR pathway.

systems biology↗

bioRxiv2018

Persistent alterations in plasma lipid profiles prior to introduction of gluten in the diet associate with progression to celiac disease

Background and AimsCeliac disease (CD) is a chronic enteropathy characterized by an autoimmune reaction in the small intestine in genetically-susceptible individuals. Gluten is the required environmental trigger of clinical CD, but the underlying causes of the autoimmune reaction remain unknown. Herein, we apply lipidomics to elucidate the early events preceding clinical CD in a prospective study of children observed from birth until diagnosis of CD and subsequent introduction of a gluten-free diet.\n\nMethodsMass spectrometry-based lipidomics profiling was applied to a longitudinal series of 233 plasma samples from the Type 1 Diabetes Prediction and Prevention (DIPP) study, spanning the period between birth and the introduction of a gluten-free diet following CD diagnosis (n=23 CD progressors, n=23 controls matched for gender, HLA risk, period of birth, and age).\n\nResults23 children progressed to CD at a mean age of 4.8 years. They showed increased amounts of triacylglycerols (TGs) of low carbon number and double bond count and a decreased level of phosphatidylcholines by 3 months of age as compared to controls. These differences were exacerbated with age but were not observed at birth. No significant differences were observed in essential (dietary) TGs such as those containing polyunsaturated fatty acids.\n\nConclusionOur findings suggest that abnormal lipid metabolism associated with development of clinical CD may occur prior to the introduction of gluten to the diet. Moreover, our data suggest that the specific TGs found elevated in CD progressors may be due to a host response to compromised intake of essential lipids in the small intestine, requiring de novo lipogenesis.

systems biology↗

bioRxiv2018

Metabolic modeling of Streptococcus mutans reveals complex nutrient requirements of an oral pathogen

Streptococcus mutans is a Gram positive bacterium that thrives under acidic conditions and is a primary cause of tooth decay (dental caries). To better understand the metabolism of S. mutans on a systematic level, we manually constructed a genome-scale metabolic model of the S. mutans type strain UA159. The model, called iSMU, contains 656 reactions involving 514 metabolites and the products of 488 genes.\n\nWe interrogated S. mutans nutrient requirements using model simulations and nutrient removal experiments in defined media. The iSMU model matched experimental results in greater than 90% of the conditions tested. We also simulated effects of single gene deletions. The models predictions agreed with 78.1% and 84.4% of the gene essentiality predictions from two experimental datasets. Our manually curated model is more accurate than S. mutans models generated from automated reconstruction pipelines. We believe the iSMU model is an important resource for understanding how metabolism enables the cariogenicity of S. mutans.

systems biology↗

bioRxiv2018

Rewiring of RSK-PDZ interactions by linear motif phosphorylation

Protein phosphorylation is a key regulator of protein-protein interactions. How does the interactome of a protein change during extracellular stimulations? While many individual examples of phosphorylation-regulated interactions were described previously, studies addressing the interactome changes induced by a particular phosphorylation event remain scarce. Here, we try to answer this question, by focusing on interactions between a phosphorylable PDZ-binding linear motif and the entire complement of human PDZ domains. Using a combination of in vitro quantitative techniques and cell-based approaches, we demonstrate that the activation of the mitotic effector kinase RSK1 causes dramatic changes in its connectivity with PDZ domain containing proteins. These changes consist of modulations of the binding affinity of numerous interactions, rather than on/off switching of a few interactions. Our results highlight the previously unappreciated role of phosphorylation in the complex and subtle rewiring of large numbers of protein-protein interactions.

systems biology↗

bioRxiv2018

Computational framework for exploring the interplay of diet and gut microbiota in autism

Autism spectrum disorder (ASD)1 refers to the set of complex neurological disorders characterized by repetitive behaviour. The reported occurrence of abnormal gut bacteria, along with prevalence of gastrointestinal disorders in ASD indicate its strong correlation with the gut microflora. Our study aims to understand the role of diet and gut bacteria in ASD via an integrated constraint-based and PBPK model. Genome scale models of five major gut bacteria, which were reported to be associated with ASD, were integrated with the human host, i.e., the combined small intestinal enterocyte and neuronal brain model. Simultaneously, a permeability-limited two sub compartment PBPK model was developed to determine the distribution of bacteria-derived toxins in the body. The important results include, (i) inclusion of probiotics into the diet of autistic case restores gut balance, majorly seen as a result of reduced oxidative stress in the brain and the gut, (ii) microbiome and diet together mediate host metabolism in autism, majorly via the nucleotide, central carbon, amino acid, and reactive oxygen species metabolisms, and (iii) gut bacterial-specific secretions contribute to autistic metabotype. Thus, the presented integrated model is the first ever quantitative model, providing a mechanistic basis for autism pathogenesis, capturing known biomarkers, as well as, highlighting the potential of novel dietary modifications in alleviating the symptoms of autism.

systems biology↗

bioRxiv2018

Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies

Mechanistic modeling of signaling pathways mediating patient-specific response to therapy can help to unveil resistance mechanisms and improve therapeutic strategies. Yet, creating such models for patients, in particular for solid malignancies, is challenging. A major hurdle to build these models is the limited material available, that precludes the generation of large-scale perturbation data. Here, we present an approach that couples ex vivo high-throughput screenings of cancer biopsies using microfluidics with logic-based modeling to generate patient-specific dynamic models of extrinsic and intrinsic apoptosis signaling pathways. We used the resulting models to investigate heterogeneity in pancreatic cancer patients, showing dissimilarities especially in the PI3K-Akt pathway. Variation in model parameters reflected well the different tumor stages. Finally, we used our dynamic models to efficaciously predict new personalized combinatorial treatments. Our results suggest our combination of microfluidic experiments and mathematical model can be a novel tool toward cancer precision medicine.

systems biology↗

bioRxiv2018

Inhibition of nucleotide synthesis mediates replicative senescence of human mammary epithelial cells

Cellular senescence is a mechanism by which cells permanently withdraw from the cell cycle in response to stresses including telomere shortening, DNA damage, or oncogenic signaling. Senescent cells contribute to both age-related degeneration and hyperplastic pathologies, including cancer. In culture, normal human epithelial cells enter senescence after a limited number of cell divisions, known as replicative senescence. Here, to investigate how metabolic pathways regulate replicative senescence, we used LC-MS-based metabolomics to analyze senescent primary human mammary epithelial cells (HMECs). We did not observe significant changes in glucose uptake or lactate secretion in senescent HMECs. However, analysis of intracellular metabolite pool sizes indicated that senescent cells exhibit depletion of metabolites from nucleotide synthesis pathways. Furthermore, stable isotope tracing with 13C-labeled glucose or glutamine revealed a dramatic blockage of flux of these two metabolites into nucleotide synthesis pathways in senescent HMECs. To test whether cellular immortalization would reverse these observations, we expressed telomerase in HMECs. In addition to preventing senescence, telomerase expression maintained metabolic flux from glucose into nucleotide synthesis pathways. Finally, we investigated whether inhibition of nucleotide synthesis in proliferating HMECs is sufficient to induce senescence. In proliferating HMECs, both pharmacological and genetic inhibition of ribonucleotide reductase regulatory subunit M2 (RRM2), a rate-limiting enzyme in dNTP synthesis, induced premature senescence with concomitantly decreased metabolic flux from glucose into nucleotide synthesis. Taken together, our results suggest that nucleotide synthesis inhibition plays a causative role in the establishment of replicative senescence in HMECs.

systems biology↗