Systems biology and biotechnology of Streptomyces species for the production of secondary metabolites

1. K S Hwang et al., 2014
Biotechnology advances 32(2014)255-269
Presented by
NEERAJ CHAUHAN
M.Sc 2nd year
DMBT
www.Fmicrobewiki.kenyon.edu
Systems biology and biotechnology of Streptomyces
species for the production of secondary metabolites

2. http://imgkid.com/cute-question-mark-wallpaper.shtml

3. System biology
 Holistic approach
 To understand biological complexity
 The study of biological systems, viewed as integrated and interrelated
networks of genes, proteins, and biochemical reactions
http://genomics.energy.gov/

4. System Biology
https://www.systemsbiology.org/about-systems-biology

5. Applications of system biology
 Investigate complex processes involved in the development of
diseases
 Identify therapeutic targets and drugs.
 Overcome pathway redundancy causing resistance to
treatment in cancer and other diseases.
 Determine the relevance of specific molecule or pathway for
the overall behaviour of the system or in the pathogenesis of a
disease.
 Assess the suitability of new chemical or biological entities
as drugs
 De-risk scientific decisions and reduce research costs

6. Systems Biology is used to understand the development
stages from a single Streptomyces cell to a large
antibiotic producing bacterial colony.

7. Streptomyces
 Scientific classification
Kingdom: Bacteria
Phylum: Actinobacteria
Class: Actinobacteria
Order: Actinomycetales
Family: Streptomycetaceae
Genus: Streptomyces
 Aerobic and Gram-positive soil bacteria .
 Filamentous growth.
(Global Biodiversity Information Facility)
http://mml.sjtu.edu.cn/

9.  Linear chromosome (8 Mb-10Mb) with high GC content
(about 72 % ).
 Biosynthetic gene cluster
Secondary metabolites
Polyketide , Nonribosomal
peptides , Lactams , Terpenes
(K.S Hwang et al.,2014)Tylosin
Clavulanate

10. Secondary
metabolites
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11.  Secondary metabolites produced during shifting phase from
substrate mycelium to sporulation (Dyson, 2011; Flardh and Buttner,
2009).
 Important source of medicines
 Antibiotics( e.g., daptomycin)
 Immunosuppressants (e.g., rapamycin)
 Antifungals (e.g., amphotericin B)
 Antiparasitics (e.g., ivermectin )
 Anticancers (e.g., doxorubicin)
(Newman and Cragg, 2007)

12. Secondary metabolism of Streptomyces species
Secondary
Metabolites
Polyketides
Nonribosomal
peptides

13. Polyketides
 Diverse group of natural products
 Synthesized through decarboxylative condensation of
carboxylic acids by polyketide synthases (PKSs).
Polyketide
synthases
Type I Type II Type III
(Yu et al., 2012)

14.  Type I PKSs- Multifunctional and multimodular proteins
 Example macrolides ( tylosin ).
 Consist several modules.
 Each module carries three core domains:
 acyltransferase (AT)
 acyl carrier protein (ACP)
 ketosynthase.
 Type II PKSs - Complex of monofunctional proteins
 producing aromatic polyketides (e.g., tetracyclines and
actinorhodin)
 Type III PKS- Homodimer of keto-reductase enzyme.
 Five groups are characterized to date .
 Example-Flaviolin
 RppA from the Gram-positive, filamentous bacterium Streptomyces
griseus.
 It catalyzes the synthesis of 1,3,6,8-tetrahydroxynaphthalene (THN)
(Yu et al., 2012)

15. Nonribosomal peptide
 Short (2 to about 50 amino acids)
 Synthesized by nonribosomal peptide synthetases
(NRPSs),
 Multimodular and multifunctional enzymes
 Each module consists of
 adenylation
 peptidyl carrier protein (PCP or thiolation),
 condensation domains
 Epimerization domains
 Examples – Actinomycin B , Coelichelin

16. Regulation and signal transduction of
secondary metabolism
 When the cell senses a stressful condition of
 nutrient depletion,
 or specific small signaling molecules (butyrolactones )
 In regulation
 global transcriptional regulators ( AdpA ) and
 two-component systems (PhoP/R ) play role

17. AdpA - Transcriptional Activator
(T. Beppu et al.,1995)

18. PhoR-PhoP- for phosphate control in S.
coelicolor
 Secondary metabolites repressed by high inorganic phosphate concentrations.
 Thus production has to be performed under phosphate-limiting conditions
 Actinorhodin and undecylprodigiosin increased in phoP or phoR-phoP
deletion mutants
 PhoR -sensor protein of two-component systems
 PhoP - related to ROII subfamily of response regulators
 Mutants unable to synthesize alkaline phosphatase
 Formation of secondary metabolites occur under phosphate-limiting
conditions
 Nothing is known about the molecular mechanism of phosphate control of
expression of the corresponding biosynthetic genes

19. Databases to knowledgebases for understanding and
engineering secondary metabolism of Streptomyces
species
 Databases provide genomic information of Streptomyces species
 Emphasize on gene clusters involved in secondary metabolism.
Classification of
Databases and
Knowledgebases
Genome
annotation/mining
database
Secondary
metabolites
Database

20. Classification Database name URL Refs
Genome
annotation/
mining database
DoBISCUIT http://www.bio.nite.go.j
p/pks/
Ichikawa et
al.(2013)
antiSMASH http://antismash.second
arymetabolites.org
Blin et
al.(2013)
Secondary
metabolites
database
NORINE http://bioinfo.lifl.fr/nori
ne/
Caboche et
al.(2008)
Novel Antibiotics
Database
http://www.antibiotics.o
r.jp/journal/database/da
tabase-top.htm
Caboche et
al.(2008)
(K.S. Hwang et al.,2014)

21. DoBISCUIT

22. antiMASH

23. Norine

24. Novel antibiotics Database

25. Constraint-based Flux analysis of Metabolism
 Flux balance analysis
 mathematical approach
 analyze the flow of metabolites through a metabolic
network.
Constraint-based reconstruction and analysis
(COBRA)
 Constraint-based flux analyses
 Simulate metabolic network models,
 Used to design strategies of systems metabolic
engineering for different Streptomyces species
 Identification of genes
 Analysis of intracellular flux distributions

26. System metabolic engineering of
Streptomyces
 Engineering biosynthetic pathways for low cost production
of useful products .
 Rational metabolic engineering play role in strain
improvement
 for the overproduction of secondary metabolites using
Streptomyces species.

27.  Representative engineering approaches include:
 Improving precursor and cofactor pools
 Removing competing pathways
 Over expressing transcriptional regulators
 Improving enzyme conversion rates
 Over expressing genes conferring tolerance for the toxicity of produced
antibiotics
 Systems biology provide targets for gene
manipulations and bioprocess engineering for the
maximal production of secondary metabolites of
interest

28. Approaches of system metabolic
engineering
Approaches
of system
metabolic
engineering
Comparative
trans-
criptome
analysis
Constraint
based flux
analysis
Bioprocess
engineering

29. Comparative transcriptome analysis
 Transcriptome profiling allow
 Parallel analysis of dynamic expression of all genes
 Enhance the production of actinorhodin in S. coelicolor.
 Gene downregulator (pfkA2) of actinorhodin biosynthesis is deleted.
 pfkA2 gene- encode 6-phosphofructokinase in S. coelicolor
• Inactivate pfkA2 gene
• Redirect fluxes towards the pentose phosphate pathway
• Increased the NADPH production
• Enriched acetyl-CoA pool
• Both necessary for the production of actinorhodin.
Hwang et al.,2014

30. Constraint based flux analysis
 Boost production of Tacrolimus
 immunosuppressant from Streptomyces tsukubaensis
Genome scale metabolic
model constructed
Subjected to minimization
of metabolic adjustment
Maximal specific growth
rate fixed
Non-zero fluxes increased
Overexpression targets
predicted
Selected as targets if
contribute to tacrolimus
production
2 gene knockout targets
(gdhA, ppc) and 4 gene
amplification targets (dahp,
gdhA, accA2, and zwf2)
selected
Mutant in which gdhA
deleted and dahp, accA2,
and zwf2 overexpressed
Results in 2.8-fold increase
profduction
Hwang et al.,2014

31. Constraint-based reconstruction and analysis approaches to the
study of Streptomyces species
Host
organism
Metabolic model Simulation method Refs
Streptomyces
coelicolor
Metabolic model
having over 200
reactions
Maximizing biomass formation rate at
limited consumption rates of carbon,
nitrogen, sulfur, phosphate, and
potassium
Naeimpoor and
Mavituna
(2000)
Streptomyces
coelicolor
Genome-scale
metabolic model
having over 400
reactions
Maximizing CDA production rate
under limited glucose consumption
rate and constrained biomass
formation rate
Single gene knockout simulations to
improve CDA production rate
Kim et al.,2004
Streptomyces
roseosprorus
A metabolic model
having 138 reactions
and 109 metabolites
Comparison of flux distributions
under two optimizations:
maximization of daptomycin
biosynthesis rate and specific
Hung et al.,2012

32. Bioprocess engineering
 Systems metabolic engineering
 Considers the effects of variables
 As effect microbial metabolism
 Recent examples include effects of varying
 Initial seeding volumes
 Components in the medium for cell
cultivation and secondary metabolite
production.
 Initial seeding volume represented by
pitching ratio,
 Affect the production titer of
streptolydigin from Streptomyces lydicus.
 Streptolydigin production was
greater at 30% pitching ratio (v/v),
compared to 1% or 10% ratio.
Hwang et al.,2014

33. Production of novel secondary metabolites
Homology based approach
 Search for homologues of secondary metabolite producing
genes in the target microorganism.
 Identification of novel gene clusters
 Lead to systems metabolic engineering for the enhanced
production of secondary metabolites
 Disadvantage
 Not suitable for screening of novel compounds as
 Certain secondary metabolites produce under special
circumstances
 Relationships between the compound of interest and
their biosynthetic genes.
(Gottelt et al., 2010)

34. Approaches of system biology
Approaches
of system
biology
MS +
Genome
mining
Microbial
adaptive
evolution
Genome
mining of
silent gene
clusters

35. Mass spectrometry combined with genome
mining (Chen et al., 2012)
 Identifies novel secondary metabolites .
 Able to detect expressed genes and their products
 For discovery of novel gene clusters and their products
 DNA sequence for novel NRPSs and PKSs and LC–MS analysis of the cell supernatant
used to deduce the structure of unknown secondary metabolites.
Hwang et al.,2014

36. Microbial adaptive evolution (Charusanti et al.,
2012) Streptomyces species to produce novel metabolites.
 Demonstrated with a competition-based adaptive laboratory evolution platform
 When multiple Streptomyces clavuligerus replicates were adaptively evolved against
methicillin resistant Staphylococcus aureus N315 in this manner, a strain emerged that
acquired the ability to constitutively produce holomycin.
Continue…Charusanti et al., 2012

37. • genome resequencing revealed that the evolved strain had lost pSCL4, a
large 1.8 Mbp plasmid
• acquired several single nucleotide polymorphisms in genes that have been
shown to affect secondary metabolite biosynthesis.
Hwang et al.,2014

38. Genome mining of silent gene clusters
(Baltz, 2011)
 To identify and produce novel secondary metabolites from silent gene clusters that are
not expressed under the typical lab settings
 The key is to select an ideal heterologous host and a set of strong promoters for the
proper expression of the silent gene cluster.
 Bioinformatics analysis of the completely sequenced genome of Streptomyces
chattanoogensis L10 revealed a silent angucycline biosynthetic gene cluster. The
overexpression of a pathway-specific activator gene under the constitutive ermE*
promoter successfully triggered the expression of theangucycline biosynthetic genes.
Hwang et al.,2014

39. Conclusion
 Streptomyces species -source of medically
useful compounds
 Many biochemical mysteries need to
be elucidated
 Search for novel secondary metabolites
and their biosynthetic gene clusters
 Relevant genomic databases on Streptomyces species
constructed.
 Systems biological approaches useful in the discovery and
engineering studies of Streptomyces species