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EGFR upregulation is an established biomarker of treatment resistance and aggressiveness in head and neck cancers (HNSCC). EGFR-targeted therapies have shown benefits for HPV-negative HNSCC; surprisingly, inhibiting EGFR in HPV-associated HNSCC led to inferior therapeutic outcomes suggesting opposing roles for EGFR in the two HNSCC subtypes. The current study aimed to understand the link between EGFR and HPV-infected HNSCC particularly the regulation of HPV oncoproteins E6 and E7. We demonstrate that EGFR overexpression suppresses cellular proliferation and increases radiosensitivity of HPV-positive HNSCC cell lines. EGFR overexpression inhibited protein expression of BRD4, a known cellular transcriptional regulator of HPV E6/E7 expression and DNA damage repair facilitator. Inhibition of EGFR by cetuximab restored the expression of BRD4 leading to increased HPV E6 and E7 transcription. Concordantly, pharmacological inhibition of BRD4 led to suppression of HPV E6 and E7 transcription, delayed cellular proliferation and sensitised HPV-positive HNSCC cells to ionising radiation. This effect was shown to be mediated through EGFR-induced upregulation of microRNA-9-5p and consequent silencing of its target BRD4 at protein translational level, repressing HPV E6 and E7 transcription and restoring p53 tumour suppressor functions. These results suggest a novel mechanism for EGFR inhibition of HPV E6/E7 oncoprotein expression through an epigenetic pathway, independent of MAPK, but mediated through microRNA-9-5p/BRD4 regulation. Therefore, targeting EGFR may not be the best course of therapy for certain cancer types including HPV-positive HNSCC, while targeting specific signalling pathways such as BRD4 could provide a better and potentially new treatment to improve HNSCC therapeutic outcome.

Despite remarkable advances in therapeutic interventions, malignant melanoma (MM) remains a life-threating disease. Following high initial response rates to targeted kinase-inhibition metastases quickly acquire resistance and present with enhanced tumor progression and invasion, demanding alternative treatment options. We show 2nd generation hexameric TRAIL-receptor-agonist IZI1551 (IZI) to effectively induce apoptosis in MM cells irrespective of the intrinsic BRAF/NRAS mutation status. Conditioning to the EC50 dose of IZI converted the phenotype of IZI-sensitive parental MM cells into a fast proliferating and invasive, IZI-resistant metastasis. Mechanistically, we identified focal adhesion kinase (FAK) to play a dual role in phenotype-switching. In the cytosol, activated FAK triggers survival pathways in a PI3K- and MAPK-dependent manner. In the nucleus, the FERM domain of FAK prevents activation of wtp53, as being expressed in the majority of MM, and consequently intrinsic apoptosis. Caspase-8-mediated cleavage of FAK as well as FAK knockdown, and pharmacological inhibition, respectively, reverted the metastatic phenotype-switch and restored IZI responsiveness. FAK inhibition also re-sensitized MM cells isolated from patient metastasis that had relapsed from targeted kinase inhibition to cell death, irrespective of the intrinsic BRAF/NRAS mutation status. Hence, FAK-inhibition alone or in combination with 2nd generation TRAIL-receptor agonists may be recommended for treatment of initially resistant and relapsed MM, respectively.

Project-based learning (PBL) is a dynamic student-centred teaching method that encourages students to solve real-life problems while fostering engagement and critical thinking. Here, we report on a PBL course on metabolic network modelling that has been running for several years within the Master in Integrated Systems Biology (MISB) at the University of Luxembourg. This 2-week full-time block course comprises an introduction into the core concepts and methods of constraint-based modelling (CBM), applied to toy models and large-scale networks alongside the preparation of individual student projects in week 1 and, in week 2, the presentation and execution of these projects. We describe in detail the schedule and content of the course, exemplary student projects, and reflect on outcomes and lessons learned. PBL requires the full engagement of students and teachers and gives a rewarding teaching experience. The presented course can serve as a role model and inspiration for other similar courses.

In recent years, there has been increasing interest in plant microbiota; however, despite medicinal plant relevance, very little is known about their highly complex endophytic communities. In this work, we report on the genomic and phenotypic characterization of the antimicrobial compound producer Rheinheimera sp. EpRS3, a bacterial strain isolated from the rhizospheric soil of the medicinal plant Echinacea purpurea. In particular, EpRS3 is able to inhibit growth of different bacterial pathogens (Bcc, Acinetobacter baumannii, and Klebsiella pneumoniae) which might be related to the presence of gene clusters involved in the biosynthesis of different types of secondary metabolites. The outcomes presented in this work highlight the fact that the strain possesses huge biotechnological potential; indeed, it also shows antimicrobial effects upon well-described multidrug-resistant (MDR) human pathogens, and it affects plant root elongation and morphology, mimicking indole acetic acid (IAA) action.

Understanding plant&ndash, microbe interactions is crucial for improving plants&rsquo, productivity and protection. Constraint-based metabolic modeling is one of the possible ways to investigate the bacterial adaptation to different ecological niches and may give insights into the metabolic versatility of plant pathogenic bacteria. We reconstructed a raw metabolic model of the emerging plant pathogenic bacterium Pectobacterium parmentieri SCC3193 with the use of KBase. The model was curated by using inParanoind and phenotypic data generated with the use of the OmniLog system. Metabolic modeling was performed through COBRApy Toolbox v. 0.10.1. The curated metabolic model of P. parmentieri SCC3193 is highly reliable, as in silico obtained results overlapped up to 91% with experimental data on carbon utilization phenotypes. By mean of flux balance analysis (FBA), we predicted the metabolic adaptation of P. parmentieri SCC3193 to two different ecological niches, relevant for the persistence and plant colonization by this bacterium: soil and the rhizosphere. We performed in silico gene deletions to predict the set of essential core genes for this bacterium to grow in such environments. We anticipate that our metabolic model will be a valuable element for defining a set of metabolic targets to control infection and spreading of this plant pathogen.

Acinetobacter baumannii is a clinical threat to human health, causing major infection outbreaks worldwide. As new drugs against Gram-negative bacteria do not seem to be forthcoming, and due to the microbial capability of acquiring multi-resistance, there is an urgent need for novel therapeutic targets. Here we have derived a list of new potential targets by means of metabolic reconstruction and modelling of A. baumannii ATCC 19606. By integrating constraint-based modelling with gene expression data, we simulated microbial growth in normal and stressful conditions (i.e. following antibiotic exposure). This allowed us to describe the metabolic reprogramming that occurs in this bacterium when treated with colistin (the currently adopted last-line treatment) and identify a set of genes that are primary targets for developing new drugs against A. baumannii, including colistin-resistant strains. It can be anticipated that the metabolic model presented herein will represent a solid and reliable resource for the future treatment of A. baumannii infections.

Background In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. Results We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution. Conclusions Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3311-0) contains supplementary material, which is available to authorized users.

We report here the draft genome sequence of the Pseudomonas sp. TAA207 and Pseudomonas sp. TAD18 strains, isolated from Antarctic sediments during a summer campaign near coastal areas of Terra Nova Bay (Antarctica). Genome sequence knowledge allowed the identification of genes associated with the production of bioactive compounds and antibiotic resistance. Furthermore, it will be instrumental for comparative genomics and the fulfillment of both basic and application-oriented investigations.

We announce here the draft genome sequence of Pseudomonas sp. strain EpS/L25, isolated from the stem/leaves of the medicinal plant Echinacea purpurea . This genome will allow for comparative genomics in order to identify genes associated with the production of bioactive compounds and antibiotic resistance.

To date, more than 50 enzymes are known to contain Mo and most of them occur in prokaryotes while only six were found in eukaryotes. In all organisms studied so far, the Mo-cofactor is synthesized by a highly conserved biosynthetic pathway that can be divided into four steps, each producing a specific biochemical intermediate. Different nomenclatures were introduced for genes and gene products involved in Mo-co formation according to the organism they belong. On the basis of the active site structure and catalytic function, molybdenum-dependent enzymes can be grouped into two categories: bacterial nitrogenases and pterin-based enzymes. Human and plants Mo-co deficiency are also described.

Nitrogen fixation is the most important input of biologically available nitrogen in Earth's ecosystems and is a metabolic ability possessed only by some Prokaryotes. To date four classes of nitrogenase enzymes have been characterized. Three nitrogenases are homologous enzymes with similar protein subunit composition and metal cofactor structure; these are the Mo-nitrogenase, V-nitrogenase, and Fe-only nitrogenase. How these three systems evolved and which of them first appeared on Earth is still under debate. The best studied system is the Fe-Mo-co based although several comparative analyses have been performed in past years.

Molybdenum and tungsten share several atomic properties. Hence, in order to distinguish them, microorganisms have evolved discriminating systems either at the level of metal insertion into the cofactor or during the possible interplay of molybdo-enzyme specific chaperones when incorporating the cofactor. Several different Mo transport systems have been identified in Prokaryotes and Eucaryotes with their relatively different regulation and storage systems.

The distribution of life on Earth is constrained by the distribution of 20 bio-essential nutrients. Particularly, the availability of those elements required as cofactor might have influenced the timing of origin and evolution of metabolic pathways. Since the amount of bio-available Mo strongly changed during evolution to form anoxic to oxygenic environments, it is interesting to speculate about the appearance of Mo containing enzymes in relation to other metals with similar chemical characteristics.