Stress Response Study of Zea mays Root by Incorporating Omics Information into its Genome-Scale Metabolic Model

Niaz Bahar Chowdhury Author

04/04/2021 Added

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[00:00:01.040]Hello, welcome to my presentation.
[00:00:02.530]I'm a first year PhD student in the Chemical and
[00:00:04.740]Biomolecular Engineering Department with Dr. Rajib Saha
[00:00:07.810]and today we're talking about my recent project
[00:00:09.807]on "Stress Response Study of Zea Mays Root by Incorporating
[00:00:13.250]Omics Information into its Genome-Scale Metabolic Model.
[00:00:19.720]Briefly, my talk will be divided into three sections.
[00:00:22.660]First, I'll discuss about the importance of maize research
[00:00:25.450]and delivery importance from the study
[00:00:26.780]in nutrient stress on maize root growth.
[00:00:29.660]Second I'll discuss about the Genome Scale Metabolic Model
[00:00:32.080]development of the maize root and third
[00:00:34.050]I'll discuss about the metabolic reprogramming
[00:00:35.440]of maize under different stress condition.
[00:00:40.160]Now I'll focus on the importance of a maize root.
[00:00:43.660]So maize is an important source of food and seed
[00:00:46.700]and according to the report from the USDA
[00:00:49.190]around 20% of the maize production were used
[00:00:51.510]as food and seed, back in 2017.
[00:00:54.390]The remaining of the maize also work
[00:00:56.000]as a promising source of a ethanol production
[00:00:57.740]and can help to mitigate the poor sustainability issue
[00:01:01.010]and among other uses, animal feeding
[00:01:02.740]and export up to manufacture.
[00:01:05.180]So maize depends on its root to collect different nutrient
[00:01:08.520]from the soil like nitrate, phosphorous, sulphate
[00:01:10.755]and other element as well and when there are not enough
[00:01:15.020]of these nutrient maize root show
[00:01:16.480]a distinct phenotypical effect.
[00:01:19.140]This is a figure from literature showing distinct root
[00:01:21.860]architecture in the nitrogen and phosphorous starvation
[00:01:25.330]and the key question here is that under nutrient
[00:01:27.780]starvation conditions, what metabolic reprogramming of
[00:01:30.640]maize root drives these phenotypical changes?
[00:01:36.140]Next I'll discuss the construction procedure
[00:01:38.050]of the Genome Scale Metabolic Model of a maize root,
[00:01:40.660]experimental data collection and integration
[00:01:42.600]of Omics information in the model.
[00:01:46.010]So we use different biochemical database such as gene
[00:01:50.925]and metasite for coming up with the reaction list
[00:01:55.950]and once the reaction list is completed then we conduct
[00:01:59.280]a daily mental and charge the length of its reaction
[00:02:02.240]and then we construct another biomass
[00:02:05.080]equation from experimental measurement
[00:02:07.200]and then we make sure that the network connectivity is there
[00:02:10.240]and the thermodynamic feasibility
[00:02:11.840]and finally we come up with the stoichiometric matrix.
[00:02:16.620]So once the stoichiometric matrix is developed,
[00:02:20.610]we then came up with the pseudo steady-state mass balance
[00:02:24.410]and from that pseudo steady-state mass balance
[00:02:26.550]and how long the restriction on the different reaction
[00:02:29.810]and environmental constrain we come up with the
[00:02:32.447]flux balance analysis for the maize root.
[00:02:37.590]So next we'll discuss about the collection
[00:02:39.187]and integration of Omics data.
[00:02:41.130]So we used two different system in our study,
[00:02:43.360]hydroponically grown maize and solid-medium grown maize.
[00:02:46.300]We perform gene expression profiling of nitrogen stress
[00:02:49.350]and phosphorous stress condition through cDNA microarray.
[00:02:52.450]Then we extract some of the key metabolite and perform
[00:02:54.970]transcriptomic analysis and metabolomic analysis.
[00:03:00.730]We then integrated trascriptomics data with the model
[00:03:03.400]through E-Flux algorithm and E-Flux algorithm is the
[00:03:05.910]valve based approach we set the gene expression
[00:03:08.070]as the upper limit of reaction flux.
[00:03:10.220]We then use gene-protein reaction association to
[00:03:12.450]calculate the reaction flux from gene expression diagram.
[00:03:15.870]We use metabolite pool size as a proxy for the
[00:03:18.290]metabolic concentration to calculate the pool size,
[00:03:21.030]we use Flux sum algorithm which
[00:03:23.640]basically take the absolute distortion.
[00:03:25.610]The stoichiometry average value of flux produced
[00:03:27.830]and consumed for a certain metabolite.
[00:03:31.250]So in nitrogen starvation condition we notice
[00:03:35.010]significant increase in the biomass production
[00:03:37.210]comparing to the end plus,
[00:03:39.830]comparing to the end plus vital condition
[00:03:42.120]and these finding is supported by the literature
[00:03:44.490]and intuitively in nitrogen stress condition
[00:03:46.380]maize root explore deeper into the medium
[00:03:49.710]to search for the more nitrogen.
[00:03:51.420]In this figure we can see the effect of
[00:03:52.940]Omics base regulation on the flux.
[00:03:55.380]Some prediction compare with the experimental trend
[00:03:57.610]in the metabolic concentration and the accuracy
[00:04:00.260]in predicting the increasing which is up arrow
[00:04:02.240]or decreasing which is down arrow trend in
[00:04:04.230]metabolic change between end plus world type condition
[00:04:07.710]and then when it's world type condition is displayed.
[00:04:11.310]So in this case the true prediction
[00:04:13.128]increased from 18% to 70%,
[00:04:15.120]false prediction reduced from 30% to 82%
[00:04:18.501]and critical metabolites in TCA cycles such as
[00:04:21.812]2-oxoglutarate, succinate, fumarate
[00:04:23.620]and malate were successfully predicted.
[00:04:26.044]Among other growth related amino acids such as lysine,
[00:04:28.920]arginine, methionine, cysteine, leucine, histidine
[00:04:30.437]and valine were also successfully predicted.
[00:04:34.760]So next I'll discuss the metabolic reprogramming of maize
[00:04:37.093]root under, maize root under different stress condition in
[00:04:40.300]both hydroponic and solid medium system.
[00:04:42.950]So the bar graph represent metabolic reprogramming
[00:04:45.550]of root for nitrogen starvation
[00:04:46.950]condition in hydroponic system.
[00:04:48.940]Metabolites in sphingolipid path to as others
[00:04:50.820]distinguished in one phosphital are known as a signaling
[00:04:53.620]in molecules and plays an important role
[00:04:55.500]in nutrient biotic and abiotic stress.
[00:04:59.680]We can see now overall reaction classes through
[00:05:01.602]this sphingolipid metabolism pathway
[00:05:03.620]increase in nitrogen as stress condition.
[00:05:06.380]The final product of Benzoxazinoid,
[00:05:09.040]which is DIMBOA, plays a key role in attracting
[00:05:11.840]rhizo bacteria to help root fix more nitrogen.
[00:05:14.540]Reaction classes through Benzoxazinoid pathway also
[00:05:17.240]increases in the nitrogen stress condition.
[00:05:20.723]Fatty acid the key component of root biomass
[00:05:23.230]and due to nitrogen as stress condition, more carbon
[00:05:26.156]are available to form more biomass as maize root
[00:05:29.021]is maximizing its biomass and more carbon are available
[00:05:31.717]and increase reaction flux through
[00:05:33.820]fatty acid metabolism is also absorbed.
[00:05:37.670]For amino acid metabolism the reaction plus become a
[00:05:40.050]resource allocation problem and due to the less
[00:05:44.034]nitrogen availability, metabolic pathway tend to produce
[00:05:46.940]more amino acid with a higher carbon to nitrogen ratio
[00:05:49.550]and eventually we observed an increase reaction plus in
[00:05:51.990]growth related amino acid metabolic pathway
[00:05:54.549]process has part in glutamine, beta alanine, cysteine,
[00:05:57.083]methionine, glycine, serine, valine, leucine et cetera.
[00:06:02.230]So next in nitrogen stress condition we express
[00:06:06.060]a gene expression from hydroponically grown maize root
[00:06:08.500]and solid medium grown maize root exhibited
[00:06:10.670]very weak correlation and the Pearson correlation
[00:06:12.810]are exhibiting in the slide
[00:06:15.070]and so biomass growth of N minus world type condition
[00:06:17.510]and P minus one fifth condition,
[00:06:20.137]outweighs the N plus world type condition in
[00:06:22.700]the third group and second group is respectively.
[00:06:25.800]To support this inferences on a biomass mode
[00:06:27.920]over the period of three weeks next slide
[00:06:29.990]we'll discuss metabolic reprogramming of a maize root.
[00:06:35.320]So from the metabolic reprogramming of a maize root
[00:06:38.070]over the period of three week we observed that for
[00:06:40.340]week three, nitrogen starvation, amino acid
[00:06:43.560]and fatty acid metabolism do not show elevated
[00:06:45.760]reaction plus and it indicated that the increase its growth
[00:06:49.740]in third week and the nitrogen stress condition is not
[00:06:52.730]because of amino acid and metabolism.
[00:06:54.900]We are good and the biomass components
[00:06:57.030]such as starch, carbohydrate and polysaccharide
[00:06:59.110]might have played an important role in the third week
[00:07:01.190]biomass growth and the nitrogen stress condition.
[00:07:03.970]For phosphorous starvation we observed an increased
[00:07:06.480]reaction flux as in fatty acid metabolism for week two
[00:07:09.840]and for week three we observed an increase
[00:07:13.340]reaction flux both amino acid and fatty acid metabolism.
[00:07:16.560]So the sudden increase of biomass growth in third week of
[00:07:20.600]phosphorous starvation condition may be the
[00:07:23.280]combined effect of increasing reaction fluxes
[00:07:25.380]through both amino acid and fatty acid metabolism.
[00:07:30.350]So in summary we build a Genome Scale Metabolic Model
[00:07:33.230]of maize root, incorporation of Omics data
[00:07:36.400]into the Genome Scale Metabolic Model
[00:07:38.540]significantly improved the model prediction.
[00:07:40.820]Incorporation of Omics data into the Genome Scale
[00:07:43.156]Metabolic Model revealed critical metabolic reprogramming
[00:07:45.950]under nitrogen and phosphorous stress condition.
[00:07:48.600]So currently we are working on building tissue-specific
[00:07:51.190]model of maize roots, seed, leaf and stalk
[00:07:55.620]and integrate those into a whole-plant metabolic model
[00:07:58.460]and that will allow us to capture metabolic changes
[00:08:00.720]in whole plant under different stress condition
[00:08:03.350]and as a future direction,
[00:08:06.870]as a future direction knowledge gained from transcriptomic
[00:08:09.190]analysis under regulatory relationship
[00:08:11.110]will be useful to guide the development of a
[00:08:14.510]stress tolerant maize root.
[00:08:16.480]So I acknowledge my supervisor, my lab mates
[00:08:18.610]and my other collaborators from UNL
[00:08:21.110]and from other universities,
[00:08:22.770]and also the funding source
[00:08:24.210]and thank you very much
[00:08:25.130]and I would appreciate if there is any question.
[00:08:27.230]Thank you, bye.

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Stress Response Study of Zea mays Root by Incorporating Omics Information into its Genome-Scale Metabolic Model

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