Post genomic microbiology rodriguez valera

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Post genomic microbiology rodriguez valera

  1. 1. Post-Genomic Microbiology Francisco Rodriguez-Valera
  2. 2. Outline • How has genomics improved the power of Microbiology to understand microbes? • What new concepts and paradigms have been advanced? • Future challenges
  3. 3. Outline • How has genomics improved the power of Microbiology to understand microbes? • What new concepts and paradigms have been advanced? • Future challenges
  4. 4. 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
  5. 5. Growth curve of Pelagibacter ubique SAR 11
  6. 6. The square archaeon Haloquadratum walsbyi ! 1 mm HASH-Agarose plates plus Na-Pyruvate and 0.01% YE WE GOT IT !!! Strain HBSQ001
  7. 7. • 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
  8. 8. What do you learn from the genome
  9. 9. Ghai et al, NSR 2013
  10. 10. What do you learn from the genome • General features (Size, GC content, tetranucleotide frequencies, coding density, etc)
  11. 11. Genomic taxonomy • DNA-DNA hybridization>70% • 16S rRNA >97% similarity • ANI >95% • Synteny over the core genome
  12. 12. 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
  13. 13. What do you learn from the genome • General features (Size, GC content, tetranucleotide frequencies, coding density, etc) • Precise phylogenetic/taxonomic placement
  14. 14. Ivars et al, ISME J 2008
  15. 15. 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)
  16. 16. 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
  17. 17. 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
  18. 18. • Na+ driven respiratory chain or transport unusual in freshwater or soils • Rhodopsins or photolyases • Transporters • Motility • Low pI halophiles
  19. 19. 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)
  20. 20. SCIENTIFIC ASPECTS Hybrid cluster PKS-NRPS in pAMDE1
  21. 21. 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
  22. 22. Mutreja et al
  23. 23. 3-4 SNPs/year/geno me Cholera in Haiti comes from Nepal
  24. 24. SCIENTIFIC ASPECTS Alteromonas macleodii from the deep Mediterranean
  25. 25. Outline • How has genomics improved the power of Microbiology to understand microbes? • What new concepts and paradigms have been advanced? • Future challenges
  26. 26. THE BACTERIAL PAN-GENOME: a new paradigm in Microbiology Welch et al, 2002 Pan-genome Core genome Flexible genome
  27. 27. 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)
  28. 28. Prokaryotes Eukaryotes Intra-species variation 1 genome is NOT enough to represent the species PANGENOME
  29. 29. 95% • ANI >95% • Synteny over the core genome
  30. 30. 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
  31. 31. 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
  32. 32. 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
  33. 33. “constant diversity” Cell Surface Niche
  34. 34. “constant diversity” O-chain Transport
  35. 35. “constant diversity”
  36. 36. Outline • How has genomics improved the power of Microbiology to understand microbes? • What new concepts and paradigms have been advanced? • Future challenges
  37. 37. 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-
  38. 38. Questions please

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