NF-κB memory coordinates transcriptional responses to dynamic inflammatory stimuli

Many scenarios in cellular communication requires cells to interpret multiple dynamic signals. It is unclear how exposure to immune stimuli alters transcriptional responses to subsequent stimulus under inflammatory conditions. Using high-throughput microfluidic live cell analysis, we systematically profiled the NF-κB response to different signal sequences in single cells. We found that NF-κB dynamics stores the history of signals received by cells: depending on the dose and type of prior pathogenic and cytokine signal, the NF-κB response to subsequent stimuli varied widely, from no response to full activation. Using information theory, we revealed that these stimulus-dependent changes in the NF-κB response encode and reflect information about the identity and dose of the prior stimulus. Small-molecule inhibition, computational modeling, and gene expression profiling show that this encoding is driven by stimulus-dependent engagement of negative feedback modules. These results provide a model for how signal transduction networks process sequences of inflammatory stimuli to coordinate cellular responses in complex dynamic environments.

Can Systems Biology Advance Clinical Precision Oncology?

Precision oncology is perceived as a way forward to treat individual cancer patients. However, knowing particular cancer mutations is not enough for optimal therapeutic treatment, because cancer genotype-phenotype relationships are nonlinear and dynamic. Systems biology studies the biological processes at the systems’ level, using an array of techniques, ranging from statistical methods to network reconstruction and analysis, to mathematical modeling. Its goal is to reconstruct the complex and often counterintuitive dynamic behavior of biological systems and quantitatively predict their responses to environmental perturbations. In this paper, we review the impact of systems biology on precision oncology. We show examples of how the analysis of signal transduction networks allows to dissect resistance to targeted therapies and inform the choice of combinations of targeted drugs based on tumor molecular alterations. Patient-specific biomarkers based on dynamical models of signaling networks can have a greater prognostic value than conventional biomarkers. These examples support systems biology models as valuable tools to advance clinical and translational oncological research.

Social Evolution With Decoupling of Multiple Roles of Biogenic Amines Into Different Phenotypes in Hymenoptera

Convergent evolution of eusociality with the division of reproduction and its plastic transition in Hymenoptera has long attracted the attention of researchers. To explain the evolutionary scenario of the reproductive division of labor, several hypotheses had been proposed. Among these, we focus on the most basic concepts, i.e., the ovarian ground plan hypothesis (OGPH) and the split-function hypothesis (SFH). The OGPH assumes the physiological decoupling of ovarian cycles and behavior into reproductive and non-reproductive individuals, whereas the SFH assumes that the ancestral reproductive function of juvenile hormone (JH) became split into a dual function. Here, we review recent progress in the understanding of the neurohormonal regulation of reproduction and social behavior in eusocial hymenopterans, with an emphasis on biogenic amines. Biogenic amines are key substances involved in the switching of reproductive physiology and modulation of social behaviors. Dopamine has a pivotal role in the formation of reproductive skew irrespective of the social system, whereas octopamine and serotonin contribute largely to non-reproductive social behaviors. These decoupling roles of biogenic amines are seen in the life cycle of a single female in a solitary species, supporting OGPH. JH promotes reproduction with dopamine function in primitively eusocial species, whereas it regulates non-reproductive social behaviors with octopamine function in advanced eusocial species. The signal transduction networks between JH and the biogenic amines have been rewired in advanced eusocial species, which could regulate reproduction in response to various social stimuli independently of JH action.

Metabolites in the Tumor Microenvironment Reprogram Functions of Immune Effector Cells Through Epigenetic Modifications

Cellular metabolism of both cancer and immune cells in the acidic, hypoxic, and nutrient-depleted tumor microenvironment (TME) has attracted increasing attention in recent years. Accumulating evidence has shown that cancer cells in TME could outcompete immune cells for nutrients and at the same time, producing inhibitory products that suppress immune effector cell functions. Recent progress revealed that metabolites in the TME could dysregulate gene expression patterns in the differentiation, proliferation, and activation of immune effector cells by interfering with the epigenetic programs and signal transduction networks. Nevertheless, encouraging studies indicated that metabolic plasticity and heterogeneity between cancer and immune effector cells could provide us the opportunity to discover and target the metabolic vulnerabilities of cancer cells while potentiating the anti-tumor functions of immune effector cells. In this review, we will discuss the metabolic impacts on the immune effector cells in TME and explore the therapeutic opportunities for metabolically enhanced immunotherapy.

Differential Interaction between RAC/ROP-GTPases and RIC-Effectors: A Network Hub for Broader Signal Transduction in Pollen Tubes

To date knowledge about plant RAC/ROP-GTPase effectors and downstream targets is still limited. This work aims on elucidation of related signal transduction networks involved in pollen tube growth. Yeast two-hybrid and Pull Down methodology were used to identify and characterize hitherto unknown components of RAC-related protein complexes from Nicotiana tabacum. Nt-RIC11pt specifically interacts with diverse active tobacco RAC-GTPases, and it is particularly significant, that their binding affinity is differential, thus implicating a multifaceted role in an interconnected RIC-RAC network. Moreover, Y2H-screening for Nt-RIC11pt targets identified Nt-CAR4, which is phylogenetically assigned to a multifaceted family of novel unusual GTPase activating proteins (GAP). It is argued that scaffold Nt-RIC11pt connects active Nt-RAC3 with membrane-bound Nt-CAR4, thus relaying GAP-activity. Quantitative RT-PCR demonstrates Nt-RIC11pt is primarily expressed in pollen and YFP-fusion proteins show homogeneous cytoplasmic localization in growing tubes, what builds the prerequisite for a proposed role in broader signal transduction. By synoptically integrating experimental data, bioinformatic sequence comparison, phylogenetic analyses, and detailed literature review, this study hypothesizes a concept in which RIC-effectors collectively constitute a multifaceted network hub linking diverse GTPase-dependent processes.

The Effect of Infertility on the Liver Structure, Endocrinology, and Gene Network in Japanese Flounder

The liver can synthesize vitellogenin, the precursor of vitellin, which is needed for oocyte development and maturation. Here, we investigated the effects of infertility on liver structure, hormone regulation, and gene and protein networks in Japanese flounder (Paralichthys olivaceus). Results showed that the liver of infertile fish had fewer vacuoles and significantly lower serum vitellogenin (VTG) level than in liver of fertile fish. Whole transcriptomics analysis between infertile and fertile groups identified 2076 significantly differentially expressed (DE) mRNAs, 431 DE lncRNAs, 265 DE circRNAs, and 53 DE miRNAs. Proteomics analysis identified 838 DE proteins. Integrated analysis of whole transcriptomics and proteomics revealed 60 significantly DE genes and proteins associated with metabolism, immunity, signal transduction, and steroid biosynthesis. Moreover, non-coding RNA (miRNAs, circRNA, and lncRNA) transcripts involved in metabolism, immunity, and signal transduction in infertile liver were identified. In conclusion, this study shows that gonadal infertility is associated with not only changes in histological structure and hormone secretion but also changes in metabolism, immunity, and signal transduction networks in the liver. These results provide valuable information concerning the mechanism underlying infertility in fish.

CrossTORC and WNTegration in Disease: Focus on Lymphangioleiomyomatosis

The mechanistic target of rapamycin (mTOR) and wingless-related integration site (Wnt) signal transduction networks are evolutionarily conserved mammalian growth and cellular development networks. Most cells express many of the proteins in both pathways, and this review will briefly describe only the key proteins and their intra- and extracellular crosstalk. These complex interactions will be discussed in relation to cancer development, drug resistance, and stem cell exhaustion. This review will also highlight the tumor-suppressive tuberous sclerosis complex (TSC) mutated, mTOR-hyperactive lung disease of women, lymphangioleiomyomatosis (LAM). We will summarize recent advances in the targeting of these pathways by monotherapy or combination therapy, as well as future potential treatments.

Signaling Pathway Mediating Myeloma Cell Growth and Survival

The multiple myeloma (MM) bone marrow (BM) microenvironment consists of different types of accessory cells. Both soluble factors (i.e., cytokines) secreted from these cells and adhesion of MM cells to these cells play crucial roles in activation of intracellular signaling pathways mediating MM cell growth, survival, migration, and drug resistance. Importantly, there is crosstalk between the signaling pathways, increasing the complexity of signal transduction networks in MM cells in the BM microenvironment, highlighting the requirement for combination treatment strategies to blocking multiple signaling pathways.

Individualised Proteogenomics Applied to Analysis of Amino Acid Variants in Malignant Melanoma

Analysis of patient-specific nucleotide variants is a cornerstone of personalised medicine. Although only 2% of the genomic sequence is protein-coding, mutations occurring in these regions have the potential to influence protein structure and may have severe impact on disease aetiology. Of special importance are variants that affect modifiable amino acid residues, as protein modifications involved in signal transduction networks cannot be analysed by genomics. Proteogenomics enables analysis of proteomes in context of patient- or tissue-specific non-synonymous nucleotide variants. Here we developed an individualised proteogenomics workflow and applied it to study resistance to BRAF inhibitor vemurafenib in malignant melanoma cell line A375. This approach resulted in high identification and quantification of non-synonymous nucleotide variants, transcripts and (phospho)proteins. We integrated multi-omic datasets to reconstruct the perturbed signalling networks associated with BRAFi resistance, prioritise key actionable nodes and predict drug therapies with potential to disrupt BRAFi resistance mechanism in A375 cells. Notably, we showed that AURKA inhibition is effective and specific against BRAFi resistant A375 cells. Furthermore, we investigated nucleotide variants that interfere with protein modification status and potentially influence signal transduction networks. Mass spectrometry (MS) measurements confirmed variant-driven modification changes in approximately 50 proteins; among them was the transcription factor RUNX1 displaying a variant on a known phosphorylation site S(Ph)276L. We confirmed the loss of phosphorylation site by MS and demonstrated the impact of this variant on RUNX1 interactome. Our study paves the way for large-scale application of proteogenomics in melanoma.