1. 70%
50%
40%
YEAST
WORM
30%
Percentage of
known genes
BACTERIA
FLY
No. of genes identified
No. of genes not identified

2. Gene
Protein
Cellular process
Phenotype
Biological activity
Process by which information from a gene is used in the synthesis of a
functional gene product to generate the macromolecular machinery for
life in the form of protein
In order to make proteins, the gene from the DNA is copied by each of the
chemical bases into mRNA

3. Gene is not an independent
identity
Proteins they encode—function
in the intact organism
There is no gene in
isolation
Study true phenotype ‗n‘
number of genes
So far there has been means
and ways

4. High-throughput approaches to understanding gene
function and mapping architecture in bacteria

5. Outline of Seminar
• Approaches to know gene function
• Platforms for mapping
• Some of the HTA for mapping
• Map and their architecture
• Some websites and databases for mapping
• Applications and its limitation
• Future prospective
• Conclusion

6. Approaches to know gene function
Forward genetics
Phenotype
Genotype
Reverse genetics
Genotype
Phenotype

7. Forward genetics
Poorly understood phenomenon
Forward genetics starts with
phenotype and lead to identification of
interesting genotype
Reverse genetics
Protein of known functions
Reverse genetics starts with a
known genotype and finally end up
with phenotype
Compared to forward genetic approach , reverse genetics screens are
more advanced in gene function discovery in bacteria

8. Reverse genetic approaches
L OF
Loss of function
GOF
Gain of function
Downregulation
Upregulation

9. • In reverse genetic approaches, LOF/GOF libraries are
grown then libraries go through selection and only mutants
withstanding the selection are identified
• With the use of interaction between proteins and genes, the
libraries are then used in a reverse genetics manner and
assessed accurately for every mutant in the library

10. List of available ordered LOF and GOF libraries in microbes

11. Why interactions ?
 Biological processes
 Potential new players
 Pathway architecture
 Genetic wiring diagrams

12. Interaction platforms
• Gene–gene interactions
• Protein-protein interactions

13. Gene–gene interactions
Negative interactions
Negative interactions (aggravating
interactions) describe double mutants
exhibiting a more severe phenotype than
expected
Positive interactions
Positive interactions (alleviating
interactions) describe double mutants
exhibiting a less severe phenotype
than expected

14. Negative interactions
Within pathway genetic interactions

15. Between pathway genetic interactions

16. Positive interactions
Positive interactions are interesting, because it is proposed that they can provide
insight into biochemical relationships between gene products and help define the
architecture of biological pathways

17. Protein-Protein Interactions(PPI)
• Protein-protein interaction network and protein interactome is at
cutting-edge to expand our understanding on biological processes and
networks of bacteria
• Comparatively
systematic
mapping
of
protein–protein
interaction(PPI) can advance understanding of interactome networks
with applications ranging from protein functional characterization in a
system biology

18. Protein-Protein Interactions(PPI)
Fundamental to all
biological processes Involved in different
pathways
Understanding -integrated
system

19. Cont..
Biological processes
signal transduction and stress responses




At the molecular level, PPI could be important in
Phosphorylation,
Transcriptional co-factor recruitment,
Assembly of cytoskeleton,
transporter activation and many others
Thus, identifying, quantifying, localizing, and modeling entire PPI
map/networks (protein ‗interactome‘) is a key prerequisite for
understanding the biophysical basis of all cellular processes and for
creating a framework to characterize the function

20. Protein-Protein interaction mapping
Bacterial -2-hybrid system ( HT- B2H)
Bimolecular Fluorescence Complementation (BiFC)
MALDI-TOF
Microarrays

21. Bimolecular fluorescence complementation
(BiFC)
• Based on the reconstitution of split non-fluorescent GFP variants to
form a fluorescent and active protein complex emitting fluorescent
signal
•
Basically, the bait proteins and target proteins will be fused,
binding of the bait and target proteins will lead to the fusion of the two
combinatory parts of the fluorescent proteins, which can be observed by
fluorescent microscopy

22. •
Therefore, through the visualization and analysis of the
intensity and distribution of fluorescence in these cells, one
can identify both the location and interaction partners of
proteins of interest
• In addition, the intensity of the fluorescence emitted is
proportional to the strength of the interaction

23. MALDI-TOF
• Allows off-line analysis of protein interaction
• MALDI-TOF analysis is very fast
K. G. Standing
2000

24. Select a colony
Prepare onto a MALDI target plate
Insert the dried target plate into apparatus
Data interpretation
Run the apparatus

25. Steps involved
Protein molecules embedded in matrix plate
Absorb laser energy
Desorption: a rapid, explosive evaporation to carry the
proteins into the gas phase
Ionization: Matrix is acidic and donates positive charge to the
proteins

26. Microarray
This technique is used to generate data from
protein-protein interaction,
which allow
researchers to investigate the expression state of a
large number of genes/proteins a single
experiment.
Microarrays “appear to be the ideal tool to assess the diversity of the bacterial world”
Huyghe et al. 2009

27. Steps involved in microarray
analysis in bacteria

28. Methods
Bacterial twohybrid (B2H)
Pros
Cons
High-throughput
High false positive rate . Only
binary interaction detected.
Bimolecular
fluorescence
complementation
(BiFC)
Localize the interaction
complex in cell Highly
sensitive to enable
detection of weak and
transient
Interactions
Optimal for the highthroughput assay some what
slow
Matrix Assisted
Laser Desroption
Ionization Time Of
Flight
(MALDI-TOF )
High-throughput, High
sensitivity
Poor mass
resolution,Photodegradation by
ionization
High-throughput
Microarray
Limited number
of samples used

29. Protein interaction mapping by using functional shotgun
sequence of Rickettsia sibirica
Rickettsia….. The bacteria invade endothelial cells
and cause lysis after large amounts of progeny
have accumulated
Rickettsia sibirica
Joel et al.,2005

30. Along with analysis of the combined genomic sequence and
protein-protein interaction data, set of six subunits
virulence related Type IV secretion system (T4SS) proteins
revealed over 284 interactions and will provide insight into
the mechanism of Rickettsial pathogenicity

31. • The need for large-scale protein interaction analyses, a
bacterial two-hybrid system was coupled with a whole
genome shotgun sequencing approach for microbial analysis
• The B2H system used in this study was
Hochschild et al.,
developed by
• Constructs were renamed pBAIT and pPREY respectively
Hochschild et al.,

32. Bacterial two-hybrid vectors
• A protein of interest (the bait) is
fused to λcI, a DNA binding domain,
which binds to a λ operator sequence,
OR2, placed upstream of a weak
promoter
• In addition, a second protein of
interest (the prey) is fused to the RNA
polymerase (RNAP) a subunit, an
activation domain, which is part of
the RNAP holoenzyme
Activation
domain
RNAP
Target
bait
DNA binding
protein
λcI

33. Bacterial Two-Hybrid System
A protein interaction between the bait and prey
protein recruits the complex

34. Functional shotgun sequencing of Rickettsia sibirica
•
Randomly sheared fragments of Rickettsia sibirica
adapted with BstXI adapters and ligated into pBAIT.
• Shotgun library is constructed in the bait vector, followed
by determination of open reading frame (ORF) fragments
that are cloned in the correct frame and can be used as bait

35. (i) Genomic DNA is sheared and
cloned into bait and prey vectors
(ii) Randomly selected bait clones are
sequenced, the data assembled and
the genome annotated
(iii) Clones determined to contain
fragments of genes expressed in the
correct frame are re-arrayed for
screening. A copy of the set is
pooled, and the inserts transferred to
the prey vector creating the fragment
ORF prey library
(iv) Baits from proteins of interest are
either screened against the
Sequencing of positive clones directly from
selected colonies is conducted with pBAIT or
previously created sheared genomic
pPREY specific primers.
prey library, or from the ORF prey
library

36. Screening in the bacterial two-hybrid system
•
For screening, the Bacteriomatch reporter strain (Stratagene USA) was used
•
Each peptide of interest was transformed using 100 µl of Bacteriomatch
reporter strain cells, 50 ng of pBAIT and 50 ng of either ORF library or
shotgun library pPREY DNA
•




Dual transformants were plated on LB agar supplemented with
25 mg/ml IPTG
300 mg/ml carbenicillin
2 mg/ml tetracycline, 50 mg/ml kanamycin and
12.5 mg/ml chloramphenicol
•
Screening was also conducted on minimal media plates containing the same
antibiotics, IPTG amounts, but with lactose as the sole carbon source.

37. Result : Percent prediction in Rickettsiae genomes
Rickettsiae sibirica
Average protein-coding gene length (bp)
787
% coding
77.7
Protein-coding regions
1234

38. Categorization and validation of interactions
Interactions were categorized as follows:
• Observed once, were assigned score 1
• More than once were assigned score 2
• More than once by different fragments were
assigned score 3

39. Screening yielded 284 distinct interactions
between 155 protein families
162 interactions -category 1 (observed once)
48 interaction -category 2 (observed two times)
74 interaction - category 3 (observed more than two using different
fragments)

40. • The region of the genome including the virulence cluster
VirD4-VirB8 was selected for further study because of their
apparent role in virulence and their relationship to the Type
IV secretion system (T4SS)
• Among 284 interactions six T4SS subunits were screened,
two intra-complex interactions was identified newly among
T4SS subunits not previously detected in studies of other
organisms using the B2H

41. Map of T4SS protein interactions
The six T4SS subunits screened

42. Bacterial two hybrid system
Methods
Bacterial twohybrid (B2H)
Pros
High-throughput
Cons
High false positive rate .
Only binary interaction
detected.

43. High-throughput, quantitative analyses of genetic
interactions in E. coli
Athanasios et al., 2011

44. • A method based on F factor–driven conjugation, which allows
for high-throughput generation of double mutants in
Escherichia coli. This method, termed genetic interaction
analysis technology for E. coli (GIANT-coli), permits us to
systematically generate and array double-mutant cells on solid
media in high-density
• Genetic interaction analysis technology for E. coli (GIANT-coli)
method to permit rapid, large-scale genetic interaction studies in
E. coli

45. Development of GIANT-coli
The high-throughput mating system has 3 steps
•
In step 1: mated the donor strain, Hfr containing a single gene deletion marked
with the kanamycin-resistance gene, (kan)on agar plates to a complete set of E.
coli K-12 archives recipient strains, a set of single-gene knockouts marked
with the chloramphenicol-resistance gene (cat). In high-throughput format,
arrayed recipient strains on agar plates in the desired format
•
step 2: Transferred cells using a robot from the mating plates onto plates
containing kanamycin (‘intermediate selection’)
•
Step 3: Pinned the cells from the intermediate selection plate onto a plate
containing both antibiotics to select for double recombinants

46. Flowchart - different steps used in GIANT-coli. An Hfr donor (male) strain carrying a selectable
marker (kan) replacing an open reading frame A is mated on agar plates with arrayed F– recipients
carrying a different selectable marker (cat) replacing another open reading frame
Images of two representative plates used for generating a mating plate are shown below. After
mating, cells are subjected to an intermediate selection on kanamycin and then to a final selection
for double mutants using both antibiotics.

47. Quantification of the plate
• To assess our strategy for mapping genetic interactions in E. coli, we
performed a 12 x12 genetic cross
• Choice of genes surA, ybaY, ycbS, ompC, yraI, cpxR, degP, pal, ompA,
yfgL,yraP and basR
A representative 1,536- colony format, M9-glycerol plate showing the
double mutants resulting from crossing 12 strains

48. Validation of GIANT-coli
• Genes are allowed to array each recipient multiple times on
the same plate so that we could assess reproducibility,
compare with different media rich (LB) versus minimal
(M9-glycerol)) and evaluate growth differences
• Several new positive, lethal and sick interactions were
observed

49. Heat maps representing 12 x12 crosses in LB and M9-glycerol

50. Interactions detected in the 12x12 genetic
interaction experiment
Pairs
Interaction
Pairs
Interaction
degP-surA
Lethal
degP-surA
ND
pal-surA
Lethal
pal-surA
ND
pal-yfgL
Lethal
pal-yfgL
Lethal
pal-ompA
Sick
pal-ompA
Lethal
degP-yfgL
Sick
degP-yfgL
ND
degP-pal
Slightly sick
degP-pal
ND
cpxR-pal
Sick
cpxR-pal
Slightly Sick
ompA-yraP
Slightly sick
ompA-yraP
Sick
pal-yraP
Positive
pal-yraP
ND
ompA-degP
Slightly positive
ompA-degP
Positive
ompA-surA
Positive
ompA-surA
ND
cpxR-ompA
Positive
cpxR-ompA
Slightly Positive
LB versus M9-glycerol

51. Optimized critical parameters
(i) Efficient mating between donor and recipient
(ii) Efficiency of transfer

52. Mapping Architecture
Proteins as ―nodes‖
Node
Protein–protein interaction indicated by ―line or
edge‖
Smaller circuit patterns termed NETWORK MOTIFS
In protein interaction networks, fully connected sub
graphs, i.e. motifs with every node linked to every other
node, the so-called CLIQUES
Edge
Node

53. Network model
Transcriptional network
Protein interaction network
Metabolic network

55. Bacillus subtilis protein interaction network, which is
composed of 112 specific interactions between 78
proteins
DNA replication
Signal transduction
Mobility
stress and proteolysis
metabolism
protein synthesis
Transcription
Unknown

56. The first large-scale genetic interaction map in E. coli was recently published,
and focused on biogenesis pathways of the cell envelope

57. Databases
Sequence
EMBL, genbank
Enzyme and interaction
Brenda
Protein Annotation
interaction
Swissprot, STRING
Pathway
Ecocyc
Libraries
Bruker daltonics
Structure
PDB, SCOP

58. STRING
Search Tool for the Retrieval of Interacting
Genes/Proteins

59. •
STRING
(De)
Search Tool for the Retrieval of Interacting Genes/Proteins
http://www.bork.embl-heidelberg.de/STRING

62. Limitation
Advantages
• A large number of tests
can be carried out in a
short period of time
• It requires skill and
experience
• Quality Data
obtained
• Initial cost is more
can
be

63. Future perspective
• High-throughput genetic interaction screens provide
dynamic cellular network
snapshots of a
• As high-throughput technologies are applied to bacterial system, we can
expect rapid progress towards a comprehensive examination of bacterial
interactome
• Novel information obtained by using HTA will greatly improve our
understanding of the mechanisms that control protein interaction and
organize molecular structures of bacteria
• In the future, the combination of high-throughput genotyping and
phenotypic profiling techniques should provide even higher resolution and
functionally relevant genetic interaction maps

64. Conclusion