Applicability ofMathematicalModels in Defining the Behaviour Kinetics Distinction Among Microbial Strains

Mathematical models were applied to define the behaviour kinetics distinction among microbial strains. In the first series of experiments the growth kinetics of microbial colonies of several S. rimosus mutant strains cultivated on agar plates were compared. Then, the interest was focused on the chosen two strains, in order to express mathematically their differences with respect to their colony growth and antibiotic biosynthesis kinetics. Finally, the behaviour of selected three S. rimosus derivative strains at different culture conditions was subjected to the study, with an aim to define strain distinction parameters. Mathematical models based on the three-dimensional growth concept and describing the microorganism growth, substrate uptake and antibiotic biosynthesis kinetics were developed. The computer simulation was applied to verify the applicability of mathematical models. The excellent agreement of computer simulation with experimental data confirmed the hypothesis that the kinetics parameters can be successfully applied to define the behaviour distinction among different S. rimosus strains. In the case of selected three strains, S. rimosus R6–500, S. rimosus MV9R-1 and MV9R-2, it was established that they can be distinguished by their growth kinetics parameters, their substrate uptake kinetics parameters and their antibiotic biosynthesis kineticsparameters. The strain S. rimosus R6–500 showed to be superior with respect to all kinetics parameters, the strain S. rimosus MV9R-2 showed to be slightly inferior to it, whereas the strain S. rimosus MV9R-1 showed to be inferior with respect to the both mentioned strains, especially because it showed the pronounced active biomass reduction rate at all investigated culture conditions. Based on these and the corresponding previous results one can conclude that appropriate mathematical models can be recommended for defining parameters of microbial behaviour distinction among different microbial strains of S. rimosus species

In silico Design of "Un-Natural" Natural Products

Poliketidi i neribosomski sintetizirani peptidi su vrlo važne kemijske supstancije za farmaceutsku industriju i agroindustriju. Njihov biosintetski put obuhvaća spajanje jednostavnih građevnih jedinica u složene kemijske strukture katalitičkim djelovanjem enzimskih kompleksa poliketid-sintaza ili sintetaza neribosomskih peptida. U posljednjem desetljeću u znanstvenoj javnosti postoji osobito zanimanje za oblikovanje novih supstancija u proizvodnji novih lijekova manipulacijom genskih nakupina tih enzimskih kompleksa u uvjetima in vitro, postupcima kombinatorne biosinteze. Međutim, značajna je prepreka napretku na tom području što većina promjena u uvjetima in vitro ne dovodi do sinteze produkta ili su mu prinosi vrlo mali. Jedno od mogućih rješenja toga problema bilo bi oblikovanje novih genskih nakupina homolognom rekombinacijom u uvjetima in vivo jer bi se tako omogućilo spajanje identičnih sekvencija i smanjile poteškoće zbog pojave nefunkcionalnih čvorišta te opće nedovoljne identičnosti različitih modula. Osim toga, homolognom bi se rekombinacijom povećala učestalost rekombinacije te potaknula kombinatorna raznolikost rekombinanata. U tijeku je razvoj integralnih računalnih programskih paketa, CompGen i ClustScan, za modeliranje tih procesa u uvjetima in silico. Okosnica je programskog paketa CompGen specifično strukturirana baza podataka koja povezuje biosintetski put sinteze sa sekvencijama DNA genskih nakupina. Povezanost sekvencija DNA s biosintetskim putem omogućuje njezinu povezanost sa strukturom produkta. Jedna je od funkcija računalnoga programskog paketa, temeljena na toj povezanosti, sposobnost oblikovanja virtualnih rekombinanata između genskih nakupina. To se obavlja pomoću modela rekombinacije da bi se in silicopredvidjele sekvencije DNA u kojima dolazi do homologne rekombinacije. CompGen iz tih podataka predviđa kemijsku strukturu nove supstancije i sprema je u bazu podataka virtualnih kemijskih struktura radi daljnjega molekulskog modeliranja. Računalni programski paket omogućuje i analizu tzv. "obrnutom genetikom". Naime, ako se pretpostavi poželjna kemijska struktura, program može predvidjeti kako bi trebala izgledati genska nakupina poliketid-sintazâ ili sintetaza neribosomskih peptida, koja bi sintetizirala takvu strukturu na temelju građevnih jedinica genskih nakupina u bazi podataka. U cjelini, CompGen će omogućiti oblikovanje baze podataka novih prirodnih kemijskih entiteta u uvjetima in silico, koja se zatim može upotrijebiti za istraživanja na području tehnologije računalnoga dizajna novih lijekova. Drugi će integralni generički računalni programski paket, ClustScan, moći prepoznati i anotirati nove genske nakupine iz sekvencija cjelovitih mikrobnih genoma ili genskih nakupina u metagenomima mikroorganizama koji žive u tlu ili u simbiozi s morskim organizmima.Polyketides and non-ribosomal peptides represent a large class of structurally diverse natural products much studied over recent years because the enzymes that synthesise them, the modular polyketide synthases (PKSs) and the non-ribosomal peptide synthetases (NRPSs), share striking architectural similarities that can be exploited to generate "un-natural" natural products. PKS and NRPS proteins are multifunctional, composed of a co-linear arrangement of discrete protein domains representing each enzymic activity needed for chain elongation using either carboxylic acid or amino acid building blocks. Each domain is housed within larger modules which form the complex. Polyketide and peptide antibiotics, antifungals, antivirals, cytostatics, immunosuppressants, antihypertensives, antidiabetics, antimalarials and anticholesterolemics are in clinical use. Of commercial importance are also polyketide and peptide antiparasitics, coccidiostatics, animal growth promoters and natural insecticides. Polyketides are assembled through serial condensations of activated coenzyme-A thioester monomers derived from simple organic acids such as acetate, propionate and butyrate. The choice of organic acid allows the introduction of different chiral centres into the polyketide backbone. The active sites required for condensation include an acyltransferase (AT), an acyl carrier protein (ACP) and a ß-ketoacylsynthase (KS). Each condensation results in a ß-keto group that undergoes all, some or none of a series of processing steps. Active sites that perform these reactions are contained within the following domains; ketoreductase (KR), dehydratase (DH) and an enoylreductase (ER). The absence of any ß-keto processing results in the incorporation of a ketone group into the growing polyketide chain, a KR alone gives rise to a hydroxyl moiety, a KR and DH produce an alkene, while the combination of KR, DH and ER domains lead to complete reduction to an alkane. Most often, the last module contains the thioesterase domain (TE) responsible for the release of linear polyketide chain from the enzyme and final cyclisation. After assembly, the polyketide backbone typically undergoes post-PKS modifications such as hydroxylation(s), methylation(s) and glycosylation(s) to give the final active compound. Non-ribosomal peptides are assembled by the so-called "multiple carrier thio-template mechanism". Three domains are necessary for an elongation module: an adenylation (A) domain that selects the substrate amino acid, analogous to a polyketide AT domain, and activates it as an amino acyl adenylate; a peptidyl carrier protein (PCP) that binds the co-factor 4-phosphopantetheine to which the activated amino acid is covalently attached, analogous to the ACP of a PKS; and a condensation (C) domain that catalyzes peptide bond formation, again analogous to the KS in modular PKSs. The NRPSs also contain a (Te) domain located at the C-terminal of the protein which is essential for release of linear, cyclic or branched cyclic peptides. Auxiliary activities can further enlarge the structural diversity of the peptide especially common are epimerization domains (Epim) that convert the thioester-bound amino acid from an L- to D- configuration. There has been a lot of interest in the last few years in generating new compounds for the production of novel drugs by manipulating the programming of such clusters in vitro (e.g. the idea of combinatorial biosynthesis). However, an important barrier to the progress is the fact that most changes made by in vitro methods result in very low yields or no detectable product. A possible solution to the yield problem would be the generation of novel clusters by homologous recombination in vivo, because this would favour more closely related sequences and should reduce problems caused by non-functional incompatible junctions. The Unified Modeling Language (UML) was used to define the platform independent integral generic program packages, CompGen and ClustScan, which are under development to model these processes in silico. The heart of CompGen is a specially structured database, based on BioSQL v1.29, which connects the biosynthetic order of synthase/synthetase enzymes to the sequences of the component polypeptides. The additional linkage to the gene sequences allows the integration of DNA sequence with product structure. The database contains sequences of the well-characterised PKS/NRPS clusters, and non-annotated sequenced clusters whose structure and function is yet unknown, to act as building blocks for the production of novel products. It is easy to add custom sequences to the database and to annotate them by the use of propriety protein profiles designed by Pfam database and HMMER. One function of the program is the ability to generate virtual recombinants between clusters. This can be done using a recombination model (with optional parameters) to predict sites for homologous recombination or by user defined recombination sites (e.g. to model in vitro genetic manipulation such as module replacement). The program predicts the linear polyketide structure of the resulting "un-natural" natural products with a chemical description using isomeric SMILES. Molecular modelling of the subsequent spontaneous cyclisation process produces structures for a virtual compound database for further molecular modelling studies using PASS and CDD technology. An optional "reverse genetics" module analyses a given chemical structure to see if it could be produced by a novel PKS/NRPS synthesis cluster and suggests the DNA sequence of a suitable cluster based on building blocks derived from clusters contained in the database. Overall, the CompGen allows in silico generation of the database of novel "un-natural" natural chemical compounds that can be used for in silico screening using PASS or CDD technology. The other integral generic program package, ClustScan, will recognise and annotate new gene clusters from microbial genome sequencing projects or in metagenomes of soil and/or marine microorganisms

In silico Design of "Un-Natural" Natural Products

Polyketides and non-ribosomal peptides represent a large class of structurally diverse natural products much studied over recent years because the enzymes that synthesise them, the modular polyketide synthases (PKSs) and the non-ribosomal peptide synthetases (NRPSs), share striking architectural similarities that can be exploited to generate "un-natural" natural products. PKS and NRPS proteins are multifunctional, composed of a co-linear arrangement of discrete protein domains representing each enzymic activity needed for chain elongation using either carboxylic acid or amino acid building blocks. Each domain is housed within larger modules which form the complex. Polyketide and peptide antibiotics, antifungals, antivirals, cytostatics, immunosuppressants, antihypertensives, antidiabetics, antimalarials and anticholesterolemics are in clinical use. Of commercial importance are also polyketide and peptide antiparasitics, coccidiostatics,animal growth promoters and natural insecticides.Polyketides are assembled through serial condensations of activated coenzyme-A thioester monomers derived from simple organic acids such as acetate, propionate and butyrate. The choice of organic acid allows the introduction of different chiral centres into the polyketide backbone. The active sites required for condensation include an acyltransferase (AT), an acyl carrier protein (ACP) and a ß-ketoacylsynthase (KS). Each condensation results in a ß-keto group that undergoes all, some or none of a series of processing steps. Active sites that perform these reactions are contained within the following domains; ketoreductase (KR), dehydratase (DH) and an enoylreductase (ER). The absence of any ß-keto processing results in the incorporation of a ketone group into the growing polyketide chain, a KR alone gives rise to a hydroxyl moiety, a KR and DH produce an alkene, while the combination of KR, DH and ER domains lead to complete reduction to an alkane. Most often, the last module contains the thioesterase domain (TE) responsible for the release of linear polyketide chain from the enzyme and final cyclisation. After assembly, the polyketide backbone typically undergoes post-PKS modifications such as hydroxylation(s), methylation(s) and glycosylation(s) to give the final active compound.Non-ribosomal peptides are assembled by the so-called "multiple carrier thio-template mechanism". Three domains are necessary for an elongation module: an adenylation (A) domain that selects the substrate amino acid, analogous to a polyketide AT domain, and activates it as an amino acyl adenylate; a peptidyl carrier protein (PCP) that binds the co-factor 4-phosphopantetheine to which the activated amino acid is covalently attached, analogous to the ACP of a PKS; and a condensation (C) domain that catalyzes peptide bond formation, again analogous to the KS in modular PKSs. The NRPSs also contain a (Te) domain located at the C-terminal of the protein which is essential for release of linear, cyclic or branched cyclic peptides. Auxiliary activities can further enlarge the structural diversity of the peptide especially common are epimerization domains (Epim) that convert the thioester-bound amino acid from an L- to D- configuration.There has been a lot of interest in the last few years in generating new compounds for the production of novel drugs by manipulating the programming of such clusters in vitro (e.g. the idea of combinatorial biosynthesis). However, an important barrier to the progress is the fact that most changes made by in vitro methods result in very low yields or no detectable product. A possible solution to the yield problem would be the generation of novel clusters by homologous recombination in vivo, because this would favour more closely related sequences and should reduce problems caused by non-functional incompatible junctions.The Unified Modeling Language (UML) was used to define the platform independent integral generic program packages, CompGen and ClustScan, which are under development to model these processes in silico. The heart of CompGen is a specially structured database, based on BioSQL v1.29, which connects the biosynthetic order of synthase/synthetase enzymes to the sequences of the component polypeptides. The additional linkage to the gene sequences allows the integration of DNA sequence with product structure. The database contains sequences of the well-characterised PKS/NRPS clusters, and non-annotated sequenced clusters whose structure and functionis yet unknown, to act as building blocks for the production of novel products. It is easy to add custom sequences to the database and to annotate them by the use of propriety protein profiles designed by Pfam database and HMMER. One function of the program is the ability to generate virtual recombinants between clusters. This can be done using a recombination model (with optional parameters) to predict sites for homologous recombination or by user defined recombination sites (e.g. to model in vitro genetic manipulation such as module replacement). The program predicts the linear polyketide structure of the resulting "un-natural" natural products with a chemical description using isomeric SMILES. Molecular modelling of the subsequent spontaneous cyclisation process produces structures for a virtual compound database for further molecular modelling studies using PASS and CDD technology. An optional "reverse genetics" module analyses a given chemical structure to see if it could be produced by a novel PKS/NRPS synthesis cluster and suggests the DNA sequence of a suitable cluster based on building blocks derived from clusters contained in the database.Overall, the CompGen allows in silico generation of the database of novel "un-natural" natural chemical compounds that can be used for in silico screening using PASS or CDD technology. The other integral generic program package, ClustScan, will recognise and annotate new gene clusters from microbial genome sequencing projects or in metagenomes of soil and/or marine microorganisms

Polyketide synthase genes and the natural products potential of Dictyostelium discoideum

MOTIVATION: The genome of the social amoeba Dictyostelium discoideum contains an unusually large number of polyketide synthase (PKS) genes. An analysis of the genes is a first step towards understanding the biological roles of their products and exploiting novel products. RESULTS: A total of 45 Type I iterative PKS genes were found, 5 of which are probably pseudogenes. Catalytic domains that are homologous with known PKS sequences as well as possible novel domains were identified. The genes often occurred in clusters of 2-5 genes, where members of the cluster had very similar sequences. The D.discoideum PKS genes formed a clade distinct from fungal and bacterial genes. All nine genes examined by RT-PCR were expressed, although at different developmental stages. The promoters of PKS genes were much more divergent than the structural genes, although we have identified motifs that are unique to some PKS gene promoters

Proposed arrangement of proteins forming a bacterial type II polyketide synthase.

SummaryAklanonic acid is synthesized by a type II polyketide synthase (PKS) composed of eight protein subunits. The network of protein interactions within this complex was investigated using a yeast two-hybrid system, by coaffinity chromatography and by two different computer-aided protein docking simulations. Results suggest that the ketosynthase (KS) α and β subunits interact with each other, and that the KSα subunit also probably interacts with a malonyl-CoA:ACP acyltransferase (DpsD), forming a putative minimal synthase. We speculate that DpsD may physically inhibit the priming reaction, allowing the choice of propionate rather than acetate as the starter unit. We also suggest a structural role for the cyclase (DpsY) in maintaining the overall structural integrity of the complex