Microbial engineering of new streptomyces sp. from extreme environments for novel antibiotics and anticancer drugs

Today there is a tremendous need for new antibiotics and novel cytotoxic compounds against cancer cells to develop efficient alternative treatment to chemotherapy. We have searched for highly active Streptomyces strains in the driest desert in the world, the Atacama desert in northern Chile. We have identified several new strains and found many novel antibiotics and anticancer agents (“Chaxamycins”, “Chaxalactins” and “Atacamycins”) from Streptomyces C34 and C38. A genome scale model of the metabolism of Streptomyces leeuwenhoekii C34 has been developed from its genome sequence. The model, iVR1007, has 1726 reactions including 239 for transport, reactions for secondary metabolite biosynthesis, 1463 metabolites and 1007 genes. The model was validated with experimental data of growth in 89, 54 and 23 sole carbon, nitrogen and phosphorous sources, respectively, and showed a high level of accuracy (82.5 %). We have included reactions for desferrioxamines, ectoine, Chaxamycins, Chaxalactins and for the hybrid polyketides/non-ribosomal peptide synthesized by the halogenase cluster. A detailed Metabolic Flux Balance Analysis was carried out in order to study the metabolic pathways of Chaxalactins, Chaxamycins and the product of the halogenase cluster, by recognizing overexpression targets and useful knock-out sites to increase production of these secondary metabolites. Alternatively we have identified the gene cluster in S. leeuwenhoekii C34 responsible for the biosynthesis of the Chaxamycins and Chaxalactins and have cloned the whole gene cluster in a much more efficient strain of Streptomyces, namely S. coelicolor A3 whose heterologous expression of gene clusters from other Streptomyces strains has been successfully tested. Our recent results concerning these two alternative strategies for identification and overproduction of these important secondary metabolites will be presented and discussed in this presentation

A Mathematical model for Astrocytes mediated LTP at Single Hippocampal Synapses

Many contemporary studies have shown that astrocytes play a significant role in modulating both short and long form of synaptic plasticity. There are very few experimental models which elucidate the role of astrocyte over Long-term Potentiation (LTP). Recently, Perea & Araque (2007) demonstrated a role of astrocytes in induction of LTP at single hippocampal synapses. They suggested a purely pre-synaptic basis for induction of this N-methyl-D- Aspartate (NMDA) Receptor-independent LTP. Also, the mechanisms underlying this pre-synaptic induction were not investigated. Here, in this article, we propose a mathematical model for astrocyte modulated LTP which successfully emulates the experimental findings of Perea & Araque (2007). Our study suggests the role of retrograde messengers, possibly Nitric Oxide (NO), for this pre-synaptically modulated LTP.Comment: 51 pages, 15 figures, Journal of Computational Neuroscience (to appear

Actinomycete integrative and conjugative elements

This paper reviews current knowledge on actinomycete integrative and conjugative elements (AICEs). The best characterised AICEs, pSAM2 of Streptomyces ambofaciens (10.9 kb), SLP1 (17.3 kb) of Streptomyces coelicolor and pMEA300 of Amycolatopsis methanolica (13.3 kb), are present as integrative elements in specific tRNA genes, and are capable of conjugative transfer. These AICEs have a highly conserved structural organisation, with functional modules for excision/integration, replication, conjugative transfer, and regulation. Recently, it has been shown that pMEA300 and the related elements pMEA100 of Amycolatopsis mediterranei and pSE211 of Saccharopolyspora erythraea form a novel group of AICEs, the pMEA-elements, based on the unique characteristics of their replication initiator protein RepAM. Evaluation of a large collection of Amycolatopsis isolates has allowed identification of multiple pMEA-like elements. Our data show that, as AICEs, they mainly coevolved with their natural host in an integrated form, rather than being dispersed via horizontal gene transfer. The pMEA-like elements could be separated into two distinct populations from different geographical origins. One group was most closely related to pMEA300 and was found in isolates from Australia and Asia and pMEA100-related sequences were present in European isolates. Genome sequence data have enormously contributed to the recent insight that AICEs are present in many actinomycete genera. The sequence data also provide more insight into their evolutionary relationships, revealing their modular composition and their likely combined descent from bacterial plasmids and bacteriophages. Evidence is accumulating that AICEs act as modulators of host genome diversity and are also involved in the acquisition of secondary metabolite clusters and foreign DNA via horizontal gene transfer. Although still speculative, these AICEs may play a role in the spread of antibiotic resistance factors into pathogenic bacteria. The novel insights on AICE characteristics presented in this review may be used for the effective construction of new vectors that allows us to engineer and optimise strains for the production of commercially and medically interesting secondary metabolites, and bioactive proteins

Genome-wide analysis of the role of GlnR in Streptomyces venezuelae provides new insights into global nitrogen regulation in actinomycetes

<p>Abstract</p> <p>Background</p> <p>GlnR is an atypical response regulator found in actinomycetes that modulates the transcription of genes in response to changes in nitrogen availability. We applied a global <it>in vivo </it>approach to identify the GlnR regulon of <it>Streptomyces venezuelae</it>, which, unlike many actinomycetes, grows in a diffuse manner that is suitable for physiological studies. Conditions were defined that facilitated analysis of GlnR-dependent induction of gene expression in response to rapid nitrogen starvation. Microarray analysis identified global transcriptional differences between <it>glnR</it>⁺and <it>glnR </it>mutant strains under varying nitrogen conditions. To differentiate between direct and indirect regulatory effects of GlnR, chromatin immuno-precipitation (ChIP) using antibodies specific to a FLAG-tagged GlnR protein, coupled with microarray analysis (ChIP-chip), was used to identify GlnR binding sites throughout the <it>S. venezuelae </it>genome.</p> <p>Results</p> <p>GlnR bound to its target sites in both transcriptionally active and apparently inactive forms. Thirty-six GlnR binding sites were identified by ChIP-chip analysis allowing derivation of a consensus GlnR-binding site for <it>S. venezuelae</it>. GlnR-binding regions were associated with genes involved in primary nitrogen metabolism, secondary metabolism, the synthesis of catabolic enzymes and a number of transport-related functions.</p> <p>Conclusions</p> <p>The GlnR regulon of <it>S. venezuelae </it>is extensive and impacts on many facets of the organism's biology. GlnR can apparently bind to its target sites in both transcriptionally active and inactive forms.</p

Structures of DPAGT1 explain glycosylation disease mechanisms and advance TB antibiotic design

Summary: Protein N-glycosylation is a widespread post-translational modification. The first committed step in this process is catalysed by dolichyl-phosphate N-acetylglucosamine-phosphotransferase DPAGT1 (GPT/E.C. 2.7.8.15). Missense DPAGT1 variants cause congenital myasthenic syndrome and disorders of glycosylation. In addition, naturally-occurring bactericidal nucleoside analogues such as tunicamycin are toxic to eukaryotes due to DPAGT1 inhibition, preventing their clinical use. Our structures of DPAGT1 with the substrate UDP-GlcNAc and tunicamycin reveal substrate binding modes, suggest a mechanism of catalysis, provide an understanding of how mutations modulate activity (thus causing disease) and allow design of non-toxic “lipid-altered” tunicamycins. The structure-tuned activity of these analogues against several bacterial targets allowed the design of potent antibiotics for Mycobacterium tuberculosis, enabling treatment in vitro, in cellulo and in vivo, providing a promising new class of antimicrobial drug

A flexible mathematical model platform for studying branching networks : experimentally validated using the model actinomycete, Streptomyces coelicolor

Branching networks are ubiquitous in nature and their growth often responds to environmental cues dynamically. Using the antibiotic-producing soil bacterium Streptomyces as a model we have developed a flexible mathematical model platform for the study of branched biological networks. Streptomyces form large aggregates in liquid culture that can impair industrial antibiotic fermentations. Understanding the features of these could aid improvement of such processes. The model requires relatively few experimental values for parameterisation, yet delivers realistic simulations of Streptomyces pellet and is able to predict features, such as the density of hyphae, the number of growing tips and the location of antibiotic production within a pellet in response to pellet size and external nutrient supply. The model is scalable and will find utility in a range of branched biological networks such as angiogenesis, plant root growth and fungal hyphal networks

A Kinetic Model of Dopamine- and Calcium-Dependent Striatal Synaptic Plasticity

Corticostriatal synapse plasticity of medium spiny neurons is regulated by glutamate input from the cortex and dopamine input from the substantia nigra. While cortical stimulation alone results in long-term depression (LTD), the combination with dopamine switches LTD to long-term potentiation (LTP), which is known as dopamine-dependent plasticity. LTP is also induced by cortical stimulation in magnesium-free solution, which leads to massive calcium influx through NMDA-type receptors and is regarded as calcium-dependent plasticity. Signaling cascades in the corticostriatal spines are currently under investigation. However, because of the existence of multiple excitatory and inhibitory pathways with loops, the mechanisms regulating the two types of plasticity remain poorly understood. A signaling pathway model of spines that express D1-type dopamine receptors was constructed to analyze the dynamic mechanisms of dopamine- and calcium-dependent plasticity. The model incorporated all major signaling molecules, including dopamine- and cyclic AMP-regulated phosphoprotein with a molecular weight of 32 kDa (DARPP32), as well as AMPA receptor trafficking in the post-synaptic membrane. Simulations with dopamine and calcium inputs reproduced dopamine- and calcium-dependent plasticity. Further in silico experiments revealed that the positive feedback loop consisted of protein kinase A (PKA), protein phosphatase 2A (PP2A), and the phosphorylation site at threonine 75 of DARPP-32 (Thr75) served as the major switch for inducing LTD and LTP. Calcium input modulated this loop through the PP2B (phosphatase 2B)-CK1 (casein kinase 1)-Cdk5 (cyclin-dependent kinase 5)-Thr75 pathway and PP2A, whereas calcium and dopamine input activated the loop via PKA activation by cyclic AMP (cAMP). The positive feedback loop displayed robust bi-stable responses following changes in the reaction parameters. Increased basal dopamine levels disrupted this dopamine-dependent plasticity. The present model elucidated the mechanisms involved in bidirectional regulation of corticostriatal synapses and will allow for further exploration into causes and therapies for dysfunctions such as drug addiction

Insights into Ligand–Protein Binding from Local Mechanical Response

Computational studies of ligand–protein binding are crucial for properly designing novel compounds of potential pharmacological interest. In this respect, researchers are increasingly interested in steered molecular dynamics for ligand–protein binding and unbinding studies. In particular, it has been suggested that analyzing the work profiles along the ligand–protein undocking paths could be fruitful. Here, we propose that small portions of work profiles, termed “local mechanical responses” of the system to a steering force, could serve as a universal measure for capturing relevant information about the system under investigation. Specifically, we first collected a high number of steering trajectories using two biological systems of increasing complexity (i.e., alanine dipeptide and (R)-roscovitine/CDK5 complex). Then, we devised a novel postprocessing tool to be applied to the local mechanical responses, to extract structural information related to the biological processes under investigation. Despite the out-of-equilibrium character of the trajectories, the analysis carried out on the work profiles provided pivotal information about the investigated biological processes. This could eventually be applied to drug design

Absence of pathogenic mitochondrial DNA mutations in mouse brain tumors

BACKGROUND: Somatic mutations in the mitochondrial genome occur in numerous tumor types including brain tumors. These mutations are generally found in the hypervariable regions I and II of the displacement loop and unlikely alter mitochondrial function. Two hypervariable regions of mononucleotide repeats occur in the mouse mitochondrial genome, i.e., the origin of replication of the light strand (O(L)) and the Arg tRNA. METHODS: In this study we examined the entire mitochondrial genome in a series of chemically induced brain tumors in the C57BL/6J strain and spontaneous brain tumors in the VM mouse strain. The tumor mtDNA was compared to that of mtDNA in brain mitochondrial populations from the corresponding syngeneic mouse host strain. RESULTS: Direct sequencing revealed a few homoplasmic base pair insertions, deletions, and substitutions in the tumor cells mainly in regions of mononucleotide repeats. A heteroplasmic mutation in the 16srRNA gene was detected in a spontaneous metastatic VM brain tumor. CONCLUSION: None of the mutations were considered pathogenic, indicating that mtDNA somatic mutations do not likely contribute to the initiation or progression of these diverse mouse brain tumors