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Shewanella oneidensis MR1 Knock Out Experiment Kim Parker Rachel Neurath Savannah Sanchez Alton Lee Dimitri Kalenitchenko Hopkins Microbiology 2013 Slide 2 Outline 1.Background a.Shewanella oneidensis b.Chemostat versus batch 2.Objectives and Hypotheses 3.Experimental Design 4.Results 5.Discussion www.odec.ca Slide 3 Shewanella oneidensis MR1 Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion PNNL (2009) Gram-negative -proteobacteria Primarily marine, also found stratified sedimentary systems and soils Anaerobe, facultative aerobe Initially recognized for dissimilatory metabolism of manganese and iron oxides Genome.jgi-psf.org Biotech-weblog.com Slide 4 Shewanella oneidensis: Metabolism Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Shewanella oneidensis MR-1 is characterized by a complex and highly versatile metabolism: ELECTRON DONORS: wide range of organic compounds ELECTRON ACCEPTORS: O 2, Mn-oxides, Fe-oxides, uranium, chromium, plutonium, selenite, etc. CARBON SOURCE: wide range of organic compounds Can perform solid-state electron transfer Contain 42 putative c-type cytochromes Fredrickson et al. (2008): Nature Reviews Microbiology Slide 5 Shewanella oneidensis: Ecological Significance Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Well-developed sensing and regulatory systems, along with diverse metabolism and tolerance to extreme conditions, allow for success in wide range of environments Applications: Bioremediation and biotechnology Reference organism for understanding C-metabolic pathways Park et al. (2011): Journal of Hazardous Materials Slide 6 Batch Culture Prescott et al. X, V, S Kinetics : Ln (Xt) = Ln(Xo) + t Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 7 Batch Culture Prescott et al. X, V, S Kinetics : Ln (Xt) = Ln(Xo) + t Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Closed System with finite nutrients Slide 8 Serial Batch Culture Prescott et al. X, V, S Kinetics : Ln (Xt) = Ln(Xo) + t Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Closed System with finite nutrients Accumulation of cells / byproducts Slide 9 Batch Culture Prescott et al. X, V, S Kinetics : Ln (Xt) = Ln(Xo) + t Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Closed System with finite nutrients Accumulation of cells / byproducts No regulation of growth phase Slide 10 Serial Batch Culture Prescott et al. X, V, S Kinetics : Ln (Xt) = Ln(Xo) + t Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Closed System with finite nutrients Accumulation of cells / byproducts No regulation of growth phase X, V, S Slide 11 Chemo Continuous Culture Mass Balance: In + Accumulated + Generated = Out + Consumed Substrate Mass Balance: X = Y ( S in S) Bacterial Mass Balance: = F/V = D S in FLOW RATE X, V, S S Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 12 Chemo Continuous Culture Mass Balance: In + Accumulated + Generated = Out + Consumed Substrate Mass Balance: X = Y ( S in S) Bacterial Mass Balance: = F/V = D Low continuous concentrations of nutrient S in FLOW RATE X, V, S S Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 13 Chemo Continuous Culture Mass Balance: In + Accumulated + Generated = Out + Consumed Substrate Mass Balance: X = Y ( S in S) Bacterial Mass Balance: = F/V = D Low continuous concentrations of nutrient Flux of chemical species S in FLOW RATE X, V, S S Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 14 Chemo Continuous Culture Mass Balance: In + Accumulated + Generated = Out + Consumed Substrate Mass Balance: X = Y ( S in S) Bacterial Mass Balance: = F/V = D Low continuous concentrations of nutrient Flux of chemical species Control natural environment to study adaptation/natural physiology S in FLOW RATE X, V, S S Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 15 BIG PICTURE: Batch vs Chemostat Dynamics Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Prescott et al. Slide 16 Comparing Batch and Chemostat Systems The batch system goes through twice as many generations as the chemostat succession progresses at double the rate Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 17 ~5hrs @ 30 C ( OD600 2.0) S. oneidensis MR-1 Knock Out Library Experiment 4058 3977 ~5hrs @ 30 C ( OD600 2.0) 50L O/N @ 30 C 3 mL O/N @ 30 C Sample 1mL Pellet Cells Extract DNA PCR Barcode Sequence Sample 1mL Pellet Cells Extract DNA PCR Barcode Sequence Repeat for T F = 72 hrs Slide 18 Objectives Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion 1.Compare temporal changes in relative abundance of knock out genes in batch and chemostat systems 2.Examine ecological and selective pressures exerted by chemostat and batch systems, using Arkin Lab experiment 3.Link sensitive genes to metabolic and functional pathways Slide 19 Hypotheses Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion 1.Batch and chemostat systems will selectively favor certain gene knock-outs 2.Arkin Lab experimental conditions that are high in nutrients and relatively stable will more closely resemble the batch system; stress conditions will more closely resemble the chemostat 3.Declines in relative abundance will be associated with metabolic pathways and functions that are essential 4.Increases in relative abundance will be associated with metabolic pathways and functions that are either non- essential or even unfavorable Slide 20 Results Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Hau and Gralnick (2007): Annual Review of Microbiology Slide 21 Rate of Change in Relative Abundance 1.How does the distribution of relative abundance values change over sampling time points in the batch and chemostat systems? 1.What is the rate of change in relative abundance between time points? a.Calculation of rate of change: a.What this measure may indicate: i.Rapid decline: knock-out was highly detrimental ii.Rapid increase: knock-out was highly advantageous to the organism (at least relative to other organisms) Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 22 Distribution of Relative Abundance: Batch Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 23 Rate of Change in Relative Abundance: Batch Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 24 Distribution of Relative Abundance: Chemostat Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 25 Rate of Change in Relative Abundance: Chemostat Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 26 Shannon Index of Diversity: Where: i =n/N n = species N = # of individual in species s = # of species Simpson Index of Diversity: Pielous Evenness Index: Purvis and Hector (2000): Nature Richnes s Evenne ss Knocking Out Diversity Background | Objectives and Hypotheses | Experimental Design | Results | Discussion Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 27 Temporal Changes in Diversity: Batch versus Chemostat Batch: Diversity and evenness are constant Chemostat: Decline in diversity and evenness over time Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 28 Temporal Changes in Diversity: Biofilm Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 29 -diversity on our experiment Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 30 Arkin Dataset Anaerobic Variety of organic and inorganic electron acceptors Stress Grown on microplate Heat (42 C) /cold (4 C) exposure Motility Isolate cells that can travel from point of innoculation Carbon Source Variety of sources of carbon N/S/P Source Variety of sources of nitrogen, sulfur, or phosphorous Temperature and pH pH ranged from 6-9 Temperature ranged from 15C to 35C Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 31 Workflow for Data Consolidation UP DOW N Consolidate SO (loci) data based on insertion quality Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 32 Workflow for Data Consolidation Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion UP DOW N Consolidate SO (loci) data based on insertion quality MATCH / MERGE/ REMOVE OUTLIERS UP/DOWN MERGED Slide 33 Up and Down Libraries: Not Exactly Duplicates Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 34 Up and Down Libraries: Not Exactly Duplicates Evaluate (x Up -x Down ) Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 35 Up and Down Libraries: Not Exactly Duplicates Evaluate (x Up -x Down ) Trim off discrepancies Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 36 PCA with Arkin Dataset is Uninformative Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 37 Multidimensional Scaling -Visualizes similarity among samples. -Attempts to maintain calculated distances among samples. -Need to define a distance metric. Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 38 Arkin Dataset Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 39 Chemostat Data Clusters Further Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 40 Motility Experiments Also Cluster Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 41 Biofilm Experiment Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 42 Workflow for Data Consolidation SUBSETS Positive Chemostat Negative Chemostat Negative Chemostat Positive Batch Positive All Positive All Negative All Negative All Positive/ Negative Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion UP DOW N Consolidate SO (loci) data based on insertion quality MATCH / MERGE/ REMOVE OUTLIERS UP/DOWN MERGED Slide 43 Batch Vs Chemostat Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 44 MSHA Mannose-sensitive hemagglutinin type 4 pilus Batch (-) Chemostat ++++ Motility Assay ++ Biofilm Formation - - - Biogenesis Protein Pilin Protein Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 45 MSHA Mannose-sensitive hemagglutinin type 4 pilus Batch (-) Chemostat ++++ Motility Assay ++ Biofilm Formation - - - (( )) Pili have minimal effect on apparent relative abundance. Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 46 MSHA Mannose-sensitive hemagglutinin type 4 pilus Batch (-) Chemostat ++++ Motility Assay ++ Biofilm Formation - - - (( )) Pili have minimal effect on apparent relative abundance. Pili prevent cells from reaching sampling location. Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 47 MSHA Mannose-sensitive hemagglutinin type 4 pilus Batch (-) Chemostat ++++ Motility Assay ++ Biofilm Formation - - - (( )) Pili have minimal effect on apparent relative abundance. Pili prevent cells from reaching sampling location. Pili allow cells to adhere to surface. Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 48 MSHA Mannose-sensitive hemagglutinin type 4 pilus Batch (-) Chemostat ++++ Motility Assay ++ Biofilm Formation - - - S (( )) Pili have minimal effect on apparent relative abundance. Pili prevent cells from reaching sampling location. Pili allow cells to adhere to surface. Shouldnt pili prevent cells from washing out? But Pili prevent cells from being sampled. Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 49 Obligate Offenders Subunit Subunit Nqr B Nqr D Ubiquinol Cytochrome C Reductase Fe S Subunit NADH:Quinone Oxidoreductase, Na+ Slide 50 NADH:Ubiquinone Oxidoreductase Na + translocating Out In Na + NADH + H + + UbiquinoneNAD + + Ubiquinol Verkhovsky & Bogachev, 2009 Preferential to Complex I? - Enzymatic inefficiency - [Na] in natural environment Slide 51 Pathway overview Pathways Tool Software Shewanella Pathway map with relative abundance Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 52 Chemostat overview 24h 48h72h Slide 53 Chemostat overview 24h 48h72h Slide 54 Chemostat overview 24h 48h72h Slide 55 Fermentation Pathway Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 56 Fermentation Pathway Why Knocking out the pyruvate kinase have a positive effect ? Knocking out the Pyruvate kinase will strongly affect the metabolism No positive effect ??? Metabolic Flux Responses to Pyruvate Kinase Knockout in Escherichia coli, 2002, Emmerling et al. Slide 57 Fermentation Pathway Knocking out a gene always have a bad effect in this part of the pathway !!! Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 58 Arobic respiration Pathway Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 59 Aerobic respiration Pathway Always a negative effect Clue for aerobic activity Why do we see respiration and fermentation at the same time ? No interest for a cell to ferment if she could respire Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 60 Possibilities Micro-aerobic condition due to big bubble bubbling Perfect size will be 300m Motarjemi and Jameson, 1978 Heterogeneous chemostat Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 61 And in the batch Same pattern than in the chemostat for the respiration versus fermentation. No huge effect in comparison with the chemostat Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 62 And in the batch Same pattern than in the chemostat for the respiration versus fermentation. No huge effect in comparison with the chemostat But keep in mind that mutants have already been selected in LB batch culture media Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 63 One more thing Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 64 Relative Abundances of Chemotaxis/ Flagella Proteins Across Conditions Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 65 Flagellar Assembly Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 66 rpoN flrA flrB flrC RNAP 28 cheW cheY cheV MCP cheA cheB cheR FlgG FliI FlgF FlgH FlgB FlgJ FlhF flhA Flhb flgT FlgE FlgL FliK FlgI motA motB FliM FliC Pathways from KEGG and Wu et. al (2011) PLoS ONE 6(6): e21479 Flagella-related genes Chemotaxis-related Regulatory factor Regulatory factors A Pathway View For The Chemostat at 72h Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 67 Batch Reactor vs Chemostat Most growth occurs while substrate is in excess. Most growth occurs while substrate is limited. Energy Substrates Essential Functions Auxiliary Functions Energy Substrates Essential Functions Auxiliary Functions Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Slide 68 Batch Reactor vs Chemostat Most growth occurs while substrate is in excess. Most growth occurs while substrate is limited. Energy Substrates Essential Functions Auxiliary Functions Energy Substrates Essential Functions Auxiliary Functions Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion Energy Substrates Essential Functions Flagella Energy Substrates Essential Functions Flagella Slide 69 Returning to Our Hypotheses Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion 1.Batch and chemostat systems will selectively favor certain gene knock-outs 2.Arkin Lab experimental conditions that are high in nutrients and relatively stable will more closely resemble the batch system; stress conditions will more closely resemble the chemostat 3.Declines in relative abundance will be associated with metabolic pathways and functions that are essential 4.Increases in relative abundance will be associated with metabolic pathways and functions that are either non- essential or even unfavorable Slide 70 Returning to Our Hypotheses Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion 1.Batch and chemostat systems will selectively favor certain gene knock-outs YES, and the chemostat and batch system selectively favored certain knock-outs. Differences in selection in the chemostat and batch system were most likely driven by substrate availability and growth phase of organisms, driving a rate:yield relationship. Slide 71 Returning to Our Hypotheses Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion 2. Arkin Lab experimental conditions that are high in nutrients and relatively stable will more closely resemble the batch system; stress conditions will more closely resemble the chemostat SOMEWHAT.The most significant finding was that the Arkin conditions selecting for motility were clustered furthest from the our chemostat conditions. Slide 72 Returning to Our Hypotheses Background | Objectives and Hypotheses | Experimental Design | Results | Conclusion 3. Declines in relative abundance will be associated with metabolic pathways and functions that are essential 4. Increases in relative abundance will be associated with metabolic pathways and functions that are either non- essential or even unfavorable Probably, it seems that knock-out of genes associated with essential pathways such as NADH dehydrogenase had negative relative abundances. Knock-out of non- essential genes such as flagella had increases in relative abundance. Slide 73 Questions?