Marine microbial metagenomics - PowerPoint PPT Presentation

1 / 21
About This Presentation
Title:

Marine microbial metagenomics

Description:

25936.50 41260.10 476.01 26.00 150.00 7/20/2000. 26003.89 41297.90 476.51 27.00 150.00 7/20/2000. 26296.01 41417.30 479.03 28.00 150.00 7/20/2000. – PowerPoint PPT presentation

Number of Views:482
Avg rating:3.0/5.0
Slides: 22
Provided by: joi56
Category:

less

Transcript and Presenter's Notes

Title: Marine microbial metagenomics


1
Marine microbial metagenomics - the need to
integrate environmental and genomic databases
Ian Joint Plymouth Marine Laboratory
2
(No Transcript)
3
Nothing stands still
6 - 12 June 2004
13 - 19 June 2004
4
Redfield Ratio
5
Satellite Remote Sensing
6
(No Transcript)
7
Using Genomics The goal is to understand
Functional biodiversity
8
Effect of temperature on bacterial activity
9
Relationship between optimum temperature for
bacterial activity
and ambient temperature
30
25
20
C
15
10
5
1-Oct
1-Dec
31-Jan
1-Apr
1-Jun
1-Aug
1-Oct
1-Dec
Oct
Apr
Jun
Feb
Oct
Dec
Dec
Aug
10
Seasonal variation in the bacterial community
11
Seasonal variation in the archaeal community
1
2
19
4
6
8
15
9
16
12
13
12
Bacterial consortia
Molecular basis of a bacterial consortium
interspecies catabolism of atrazine M L de Souza
et al. (1998) AEM 64, 178-184
13
(No Transcript)
14
Zoospores aggregate aroundan AHL source
control
3O-C12-HSL
Zoospores collect around a dried spot of
3O-C12-HSL after 10 minutes in the dark
15
Shewanella B21 AHL quenching
AHLs detected at 12h, but not at 18h 24h Due
to enzymatic lactonolysis?
16
Aquatic Microbial Genomes and Biogeochemical
Cycles NERC PGP directed programme A consortium
built on hypothesis testing Hypothesis 1 That
microbes in the ocean exist in definable
communities and that biogeochemical fluxes depend
on microbial community structure. Hypothesis 2
That the oligotrophic ocean is ultimately limited
by the availability of nitrogen and that the
scale of nitrogen limitation is a function of
interactions between microbes in the assemblage.
Hypothesis 3 That marine microbial activity is
a major source of atmospheric biogases, much of
which involves anaerobic metabolism in an aerobic
environment.
17
Participant Groups (PI) 1. Plymouth Marine
Laboratory (Ian Joint) 2. Aberdeen University
(James Prosser) 3. Cardiff University (Andrew
Weightman) 4. CEH Oxford (Dawn Field, Andrew
Whiteley) 5. Essex University (David Nedwell) 6.
Liverpool University (Clive Edwards) 7.
Newcastle University (Ian Head) 8. Sheffield
University (Mark Osborn) 9. NOC Southampton (Mike
Zubkov) 10. Stirling University (Michael
Wyman) 11. Warwick University (Colin Murrell)
12. Warwick University (David Scanlan) 13.
Warwick University (Nick Mann)
18
Approaches 1. Metagenome sequencing from water
column and sediment - BAC, fosmids, gt70000 reads
- 150k budget for sequencing.
2. Microarrays - development of small, functional
gene-specific arrays, leading to a large array
of many genomes and functional genes, 200k
budget for arrays)
3. SIP experiments - analysis of metagenome clone
databases to investigate metabolic pathways in
natural assemblages
4. Field experiments - English Channel, Bergen
mesocosm, Priest Pot - integration of
BODC-type data on physical and biological
parameters e.g. nutrients, nitrogen cycling
rates, primary production etc.
5. Integration utilise large datasets, placing
molecular information in global context
19
Seawater pH change in a high CO2 world
The pH of seawater is decreasing rapidly as
increasing atmospheric CO2 dissolves in the sea.
What are the consequences for marine microbial
biodiversity and function?
In spring 2006, we plan a mesocosm experiment in
Norway to adjust pCO2 to that projected for the
next century. We will investigate how the
microbial assemblage will respond to decreased
pH.
20
Finding and characterising genes and genomes in
the environment
  • Lets get past stamp collecting acknowledge
    the complexity of the system
  • Do hypothesis driven science
  • Relate directly to the environment by developing
    inclusive databases
  • Challenges
  • Metadata
  • Unique identifiers for every sample
  • Archiving of samples much more difficult and
    expensive than archiving data

21
(No Transcript)
Write a Comment
User Comments (0)
About PowerShow.com