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Microbial loop and nutrient cycling

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Presentation on theme: "Microbial loop and nutrient cycling"— Presentation transcript:

1 Microbial loop and nutrient cycling
International Short-Course Series Bioremediation and Phytoremediation of Organics and Nutrients University of Ljubljana Biotechnical faculty Vecna pot 111, SI-1000 Ljubljana, Slovenia Microbial loop and nutrient cycling David Stopar October, 2001 Nova Gorica

2 hn O2, CO2, other gases CH4 DMS 0-200 m 200-11000 m organic material
Phytoplankton POM GRAZING hn Zooplankton Fish aggregates DOM Viruses Bacteria bentos Protozoa C, N, P, S, Fe,... solubilization SEDIMENTATION MICROBIAL LOOP

3 Microbial loop 50 % 20 % 10 % primary producer protozoa
DNA, RNA, sugars, ions DNA, RNA, sugars, ions

4 Why bacteria die? starvation disease (phages) programmed cell death
predation lethal environment time (h) CFU starvation disease (phages) programmed cell death

5 Vibrio gazogenes organic carbon sources
Sugars glucose D-fructose D-mannose maltose D-xylose sucrose trehalose L-arabinose D-galactose D-ribose Fatty acids acetate propionate butyrate caprate Polymers gelatin DNA cellobiose peptone yeast extract Organic acids succinate DL-malate DL-lactate citrate a-ketoglutarate piruvate Amino acids L-serine L-glutamat L-proline L-aspartate Alcoholes D-manitol D-sorbitol glycerol

6 Vibrio lysate as a source of organic carbon for a bacterial community
Natural bacterial community is able to grow on bacterial lysate CFU lysate x 108 lysate + mN +mN x 108 PYE x 108 initial x 105 Out of 26 different natural bacterial isolates tested, 20 bacterial isolates were able to use bacteria lysate as a source of organic carbon. no growth growth

7 Why bacteria die? starvation disease (phages) programmed cell death
predation lethal environment

8 Phage life cycle

9 Phage abundances phages are probably the most abundant living entities in the ecosystem sea water /ml fresh water /ml sediments /g soil ND

10 Phage role in the ecosystem
phages mediate horizontal gene exchange phages mediate community structure phages influence the flow of energy and carbon

11 Impact of lysogenic viruses on nutrient cycling
Bacteriophage induction experiment OD t (min) No phages with TEM Phages control OD OD660 = 0.5 mitomycin C t (min)

12 In vitro phage induction from bacterial isolates
75 % of all tested strains were lysogenic 51 % of all tested strains were polylysogenic

13 In situ induction of phages from a sea water samples
58 % of bacterial community induced Aerobic incubation to control Mit-C 32 % of bacterial community induced Anaerobic incubation to control Mit-C

14 Impact of lytic viruses on nutrient cycling
L-E B E R t (min) phage titer MFT tG L

15 Simulating phage production with and without mean free time simplification

16 Phage growth as a function of host density: theoretical versus experimental
o phage titer  exponential decay  MFT function  MFT function, Eqn2

17 Impact of host density on phage latent-period optima

18 Impact of host quality on latent period optima
glucose glycerol acetate  high quality host, control  E-varied  k-varied  R-varied  E + R + k varied

19 Why bacteria die? starvation disease (phages) programmed cell death
predation lethal environment developmental processes (i.e. sporulation) altruistic suicide ageing antibiotics or stress related factors

20 What is the benefit for unicellular organism of committing a suicide?
no obvious reason unless we consider a unicellular organism as being part of a complex microbial community better use of resources reduced mutation rate (elimination of DNA damaged cells) reducing the impact of infection by pathogens lowering the probability of take over mutants facilitating genetic exchange

21 Population of Vibrio committing a suicide after entering a stationary phase
At high cell density in a rich medium a sub population of cells commit suicide. In the lysate viruses are present. At low host density cell in a poor medium there are no viruses present. PYE 5 PYE 2

22 Survival of rare cells in a population
sensitivity of the whole population to a programme cell death could eliminate the whole clonal population (a contraproductive strategy) experimentally it is known that the entire population is not sensitive to the external damaging effect (i.e. UV, antbiotics) a random variation of regulator molecules can induce or prevent a suicide program

23 Survival of rare cells after induction with mitomycin C
rich growth conditions poor growth conditions

24 Pheromones and quorum sensing (a coordinated response to stress environment)
cells aggregate cells attracted by pheromone cell producing pheromone

25 Genetic competence in Bacillus subtilis
develops during stationary phase, when 1-10% cells become competent and ready to uptake foreign DNA genetic competence is under nutritional control and cell density control i.e. quorum sensing it is cell last chance to avoid sporulation time (h) Cell density % competence

26 Quorum sensing players in Bacillus subtilis
comX comQ comP comA Response regulator Receptor kinase Pheromone precursor Modification maturation kinase domain ComP P ComA DNA pre-ComX ComQ ComX ATP

27 Pheromone comX specificity test
producer strain comP srfA-lacZ tester strain lacZ activity comQXP comX

28 Quorum-sensing specificities
comQX comPA producer Tester strain strain RO-C2 RO-FF1 RO-E2 RO-H1 RO-B2 NAF4 RO-C RO-FF RO-E RO-A RO-PP RO-H RO-B RO-DD RO-B NAF * Strains are grouped according to phylogenetic relationship

29 ComX(s) purification and characterization
1- comQ and comX cloning and expression in E. coli 2- Purification by reverse phase chromatography srfA-lacZ

30 ComX(s) characteristics
Strain Sequence Δ Mass (A)DPITRQWGD RO-C TREWDG RO-E GIFWEQ RS-B (M)MDWHY RO-H (M)LDWKY RO-B (Y)TNGNWVPS *Δ Mass = obtained mass - calculated mass Modification masses are consistent with farnesylation or geranylation of com X in addition ComQ resembles a farnesyl-geranyl transferase

31 Why bacteria die? starvation disease (phages) programmed cell death
predation lethal environment

32 Bacterial and viral loop facilitate nutrient cycling
DNA, RNA, sugars, ions DNA, RNA, sugars, ions

33 Acknowledgements Ivan Mahne Ines Mandič-Mulec Kaja Gnezda Aleša Černe
Andrej Žagar Duško Odič Dave Dubnaw, New York University, USA Valentina Turk, National Institute of Biology, SI Mateja Poljšak-Prijatelj, Institute of Microbiology and Immunology, SI Stephen T. Abedon, Ohio State University, USA

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