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Post-Genomic Microbiology
Francisco Rodriguez-Valera
Outline
• How has genomics improved the power of
Microbiology to understand microbes?
• What new concepts and paradigms have been
advanced?
• Future challenges
Outline
• How has genomics improved the power of
Microbiology to understand microbes?
• What new concepts and paradigms have been
advanced?
• Future challenges
r-strategists
• Fast growers
• Easy to retrieve in pure culture

• Not very abundant in the environment
• Sporadic blooms
• E.g. Roseobacter, Alteromonas

K-strategists
• slow growers
• Dificult to retrieve in pure culture

• Very abundant in the environment
• Steady numbers
• E.g. Pelagibacter, Prochlorococcus
Growth curve of Pelagibacter ubique SAR 11
The square archaeon Haloquadratum walsbyi !
1 mm

HASH-Agarose plates
plus Na-Pyruvate and 0.01% YE

WE GOT IT !!!
Strain HBSQ001
• Extract 5 μg of DNA (100 ml liquid culture)
• 1/24th of Illumina lane 1.5 Gbp (500x a 3Mbp
genome

• 350€!!
• Assembly???
• Annotation YES
What do you learn from the genome
Ghai et al, NSR 2013
What do you learn from the genome
• General features (Size, GC content, tetranucleotide frequencies, coding density, etc)
Genomic taxonomy
• DNA-DNA
hybridization>70%
• 16S rRNA >97% similarity

• ANI >95%
• Synteny over the core
genome
Some Alteromonas genomes
Flagella glycosylation

O-chain

O-chain related

Alteromonas australica
98,6%

Alt170

ANI

75,0%

A. macleodii
80,7%

AltATCC
82,6%

Alt199
1.0 Mbp

2.0 Mbp

3.0 Mbp

4.0 Mbp
What do you learn from the genome
• General features (Size, GC content, tetranucleotide frequencies, coding density, etc)
• Precise phylogenetic/taxonomic placement
Ivars et al, ISME J 2008
What do you learn from the genome
• General features (Size, GC content, tetranucleotide frequencies, coding density, etc)
• Precise phylogenetic/taxonomic placement
• Predictions for metabolism (e.g transporters)

• Prediction for ecology (survival
strategies, environmental
parameters, motility)
Figure 4
Put genomes in the picture
Genome recruitment
40000

% identity

30000

% identity

Number of hits

35000

100

100

34252
90

80

90

80

25000
20000

Prochlorococcus marinus subsp. pastoris CCMP1986

70
0

500000

1000000

Candidatus Pelagibacter sp. HTCC7211

70
0

1500000

500000

1000000

1500000

15000
10000
5432
5000
0

2465

1561

1509

1472

1421

1196

1070

1048
Evapora.
Ratio
(Vi/Vo)

36-70 g/l

Carbonate
Domain
70-140 g/l

Intermediate
140-220 g/l

Gypsum
Domain
220-290 g/l

Diatoms
Cyanobacteria
Green Algae

Halite
Domain
>290 g/l

Haloarchaea
Sulphur Phototrophic Bacteria
Artenia Salina
Dunaliella

No
life
• Na+ driven respiratory chain or transport
unusual in freshwater or soils
• Rhodopsins or photolyases
• Transporters
• Motility
• Low pI halophiles
What do you learn from the genome
• General features (Size, GC content, tetranucleotide frequencies, coding density, etc)
• Precise phylogenetic/taxonomic placement
• Predictions for metabolism (e.g transporters)
• Prediction for ecology (survival
strategies, environmental
parameters, motility)
SCIENTIFIC ASPECTS
Hybrid cluster PKS-NRPS in pAMDE1
What do you learn from the genome
• General features (Size, GC content, tetranucleotide frequencies, coding density, etc)
• Precise phylogenetic/taxonomic placement
• Predictions for metabolism (e.g transporters)
• Prediction for ecology (survival
strategies, environmental
parameters, motility)
• Biotechnological potential
Mutreja et al
3-4
SNPs/year/geno
me

Cholera in Haiti comes from Nepal
SCIENTIFIC ASPECTS
Alteromonas macleodii from the deep Mediterranean
Outline
• How has genomics improved the power of
Microbiology to understand microbes?
• What new concepts and paradigms have been
advanced?
• Future challenges
THE BACTERIAL PAN-GENOME: a new paradigm in Microbiology
Welch et al, 2002

Pan-genome

Core
genome

Flexible
genome
The Bacterial PAN-GENOME

Escherichia coli K12
genome
4721 genes

Escherichia coli
core-genome
2167genes

Escherichia coli
PAN-GENOME
139.000 gene families
(293 genomes)
Prokaryotes

Eukaryotes

Intra-species variation

1 genome is NOT enough to represent the species

PANGENOME
95%

• ANI >95%
• Synteny over the
core genome
METAGENOMIC ISLANDS
GOS marine metagenomes
GENOMIC ISLANDS

O-chain LPS

Giant protein

Pili

Exo-polysaccharide

EXTRACELLULAR COMPONENTS IN GENOMIC ISLANDS

Transporters
Other

Prochlorococcus marinus MED4

Prochlorococcus marinus MIT9301

Pelagibacter ubique HTCC1062

% sim.

100%
Pelagibacter ubique HTCC1062

(1308759 bp)

Burkholderia sp. 383 chr.1

Synechococcus sp. WH812

Pili
Giant Exoprotein polysaccharide
related

O-chain LPS

Pili
Transporters

Shewanella sp. MR-4

Aeromonas hydrophila subs. hydrophila
ATCC 7966

50%

Pelagibacter ubique HTCC1002

contigs

% sim.

100%

50%
Transmembrane/
Outer membrane
proteins

O-chain LPS

Pili
Transporters

Respiratory system
Fe transporter

Giant
protein
Pili
Solar salter metagenomes

Pelagibacter ubique HTCC7211
100%

O-chain LPS

Pili

Zn transporter, Phosphonate
and Phosphate metabolism

Pili

O-chain
LPS

Salinibacter ruber DSM 13855

100

95

Haloquadratum walsbyi DSM 16790

95
Y Axis Title

50%

Y Axis Title

% sim.

100

90
85
80

90
85
80

Exo-polysaccharide

75
0

500000

75

Cell surface

0
500000
1000000 1500000 2000000 2500000 3000000 3500000 glycoproteins

X Axis Title

1000000

1500000

X Axis Title

2000000

Cell surface
2500000
3000000
glycoproteins
H. walsbyi is a unique species
Num. Mbp over 95% id (in 70% length) = 398.8
A
100
95

%id

90
85
80
75
2

4

6

8

10

12

14

16

18

20

22

24

26

28

Haloquadratum walsbyi HSBQ001 chr. (3132494 bp)

B

Metagenome

House-keeping genes

C

AtpB
SecY

Num. Seqs.

Num. Seqs.

Tef2

%id

398.8Mp

RadA

%id

30
Low recruiting genes (MGIs and islets)
• Coding for exposed features: O-chain of
LPS, glycoproteins etc, pili, flagella
• Transporters
• Sensors and regulators (behaviour)
• Sub-niche specialization e.g. microaerophilic
growth
“constant diversity”

Cell Surface

Niche
“constant diversity”

O-chain

Transport
“constant diversity”
Outline
• How has genomics improved the power of
Microbiology to understand microbes?
• What new concepts and paradigms have been
advanced?
• Future challenges
Third generation*
Microbiology
• Know
(rather than the
meager 0.1%)
• Know their
(rather
than a single strain)
• Understand their
in nature (rather
than in the lab)
• Understand their contribution to the

*

First generationPhysiology 1865-1952
Second generation Molecular Biology 1952-1995
Third generationGenomics and Metagenomics 1995-
Questions please

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Post genomic microbiology rodriguez valera

  • 2. Outline • How has genomics improved the power of Microbiology to understand microbes? • What new concepts and paradigms have been advanced? • Future challenges
  • 3. Outline • How has genomics improved the power of Microbiology to understand microbes? • What new concepts and paradigms have been advanced? • Future challenges
  • 4.
  • 5. r-strategists • Fast growers • Easy to retrieve in pure culture • Not very abundant in the environment • Sporadic blooms • E.g. Roseobacter, Alteromonas K-strategists • slow growers • Dificult to retrieve in pure culture • Very abundant in the environment • Steady numbers • E.g. Pelagibacter, Prochlorococcus
  • 6. Growth curve of Pelagibacter ubique SAR 11
  • 7. The square archaeon Haloquadratum walsbyi ! 1 mm HASH-Agarose plates plus Na-Pyruvate and 0.01% YE WE GOT IT !!! Strain HBSQ001
  • 8. • Extract 5 μg of DNA (100 ml liquid culture) • 1/24th of Illumina lane 1.5 Gbp (500x a 3Mbp genome • 350€!! • Assembly??? • Annotation YES
  • 9. What do you learn from the genome
  • 10.
  • 11.
  • 12.
  • 13.
  • 14. Ghai et al, NSR 2013
  • 15. What do you learn from the genome • General features (Size, GC content, tetranucleotide frequencies, coding density, etc)
  • 16.
  • 17. Genomic taxonomy • DNA-DNA hybridization>70% • 16S rRNA >97% similarity • ANI >95% • Synteny over the core genome
  • 18. Some Alteromonas genomes Flagella glycosylation O-chain O-chain related Alteromonas australica 98,6% Alt170 ANI 75,0% A. macleodii 80,7% AltATCC 82,6% Alt199 1.0 Mbp 2.0 Mbp 3.0 Mbp 4.0 Mbp
  • 19. What do you learn from the genome • General features (Size, GC content, tetranucleotide frequencies, coding density, etc) • Precise phylogenetic/taxonomic placement
  • 20.
  • 21. Ivars et al, ISME J 2008
  • 22. What do you learn from the genome • General features (Size, GC content, tetranucleotide frequencies, coding density, etc) • Precise phylogenetic/taxonomic placement • Predictions for metabolism (e.g transporters) • Prediction for ecology (survival strategies, environmental parameters, motility)
  • 23. Figure 4 Put genomes in the picture Genome recruitment 40000 % identity 30000 % identity Number of hits 35000 100 100 34252 90 80 90 80 25000 20000 Prochlorococcus marinus subsp. pastoris CCMP1986 70 0 500000 1000000 Candidatus Pelagibacter sp. HTCC7211 70 0 1500000 500000 1000000 1500000 15000 10000 5432 5000 0 2465 1561 1509 1472 1421 1196 1070 1048
  • 24. Evapora. Ratio (Vi/Vo) 36-70 g/l Carbonate Domain 70-140 g/l Intermediate 140-220 g/l Gypsum Domain 220-290 g/l Diatoms Cyanobacteria Green Algae Halite Domain >290 g/l Haloarchaea Sulphur Phototrophic Bacteria Artenia Salina Dunaliella No life
  • 25. • Na+ driven respiratory chain or transport unusual in freshwater or soils • Rhodopsins or photolyases • Transporters • Motility • Low pI halophiles
  • 26. What do you learn from the genome • General features (Size, GC content, tetranucleotide frequencies, coding density, etc) • Precise phylogenetic/taxonomic placement • Predictions for metabolism (e.g transporters) • Prediction for ecology (survival strategies, environmental parameters, motility)
  • 27. SCIENTIFIC ASPECTS Hybrid cluster PKS-NRPS in pAMDE1
  • 28.
  • 29. What do you learn from the genome • General features (Size, GC content, tetranucleotide frequencies, coding density, etc) • Precise phylogenetic/taxonomic placement • Predictions for metabolism (e.g transporters) • Prediction for ecology (survival strategies, environmental parameters, motility) • Biotechnological potential
  • 32. SCIENTIFIC ASPECTS Alteromonas macleodii from the deep Mediterranean
  • 33. Outline • How has genomics improved the power of Microbiology to understand microbes? • What new concepts and paradigms have been advanced? • Future challenges
  • 34. THE BACTERIAL PAN-GENOME: a new paradigm in Microbiology Welch et al, 2002 Pan-genome Core genome Flexible genome
  • 35. The Bacterial PAN-GENOME Escherichia coli K12 genome 4721 genes Escherichia coli core-genome 2167genes Escherichia coli PAN-GENOME 139.000 gene families (293 genomes)
  • 36. Prokaryotes Eukaryotes Intra-species variation 1 genome is NOT enough to represent the species PANGENOME
  • 37. 95% • ANI >95% • Synteny over the core genome
  • 38. METAGENOMIC ISLANDS GOS marine metagenomes GENOMIC ISLANDS O-chain LPS Giant protein Pili Exo-polysaccharide EXTRACELLULAR COMPONENTS IN GENOMIC ISLANDS Transporters Other Prochlorococcus marinus MED4 Prochlorococcus marinus MIT9301 Pelagibacter ubique HTCC1062 % sim. 100% Pelagibacter ubique HTCC1062 (1308759 bp) Burkholderia sp. 383 chr.1 Synechococcus sp. WH812 Pili Giant Exoprotein polysaccharide related O-chain LPS Pili Transporters Shewanella sp. MR-4 Aeromonas hydrophila subs. hydrophila ATCC 7966 50% Pelagibacter ubique HTCC1002 contigs % sim. 100% 50% Transmembrane/ Outer membrane proteins O-chain LPS Pili Transporters Respiratory system Fe transporter Giant protein Pili Solar salter metagenomes Pelagibacter ubique HTCC7211 100% O-chain LPS Pili Zn transporter, Phosphonate and Phosphate metabolism Pili O-chain LPS Salinibacter ruber DSM 13855 100 95 Haloquadratum walsbyi DSM 16790 95 Y Axis Title 50% Y Axis Title % sim. 100 90 85 80 90 85 80 Exo-polysaccharide 75 0 500000 75 Cell surface 0 500000 1000000 1500000 2000000 2500000 3000000 3500000 glycoproteins X Axis Title 1000000 1500000 X Axis Title 2000000 Cell surface 2500000 3000000 glycoproteins
  • 39. H. walsbyi is a unique species Num. Mbp over 95% id (in 70% length) = 398.8 A 100 95 %id 90 85 80 75 2 4 6 8 10 12 14 16 18 20 22 24 26 28 Haloquadratum walsbyi HSBQ001 chr. (3132494 bp) B Metagenome House-keeping genes C AtpB SecY Num. Seqs. Num. Seqs. Tef2 %id 398.8Mp RadA %id 30
  • 40. Low recruiting genes (MGIs and islets) • Coding for exposed features: O-chain of LPS, glycoproteins etc, pili, flagella • Transporters • Sensors and regulators (behaviour) • Sub-niche specialization e.g. microaerophilic growth
  • 44. Outline • How has genomics improved the power of Microbiology to understand microbes? • What new concepts and paradigms have been advanced? • Future challenges
  • 45. Third generation* Microbiology • Know (rather than the meager 0.1%) • Know their (rather than a single strain) • Understand their in nature (rather than in the lab) • Understand their contribution to the * First generationPhysiology 1865-1952 Second generation Molecular Biology 1952-1995 Third generationGenomics and Metagenomics 1995-