Improving the Efficacy of the Tracer Algorithm as a Gap-Filling and Pathway Prediction Tool for Metabolic Models

Jared Coffelt Author

07/29/2020 Added

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The Tracer Gap-Filling Algorithm is a tool designed to fill gaps in pathways in metabolic models. Still in developmental phases, research focused on improving the performance of the model and validation of its results.

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[00:00:02.532]Hello, my name is Jared Coffelt
[00:00:04.430]and today I will be presenting on
[00:00:06.163]"Improving the Efficacy of the
[00:00:07.720]Tracer Algorithm as a Gap-Filling
[00:00:09.385]and Pathway Prediction Tool
[00:00:10.669]for Metabolic Models."
[00:00:18.199]Genome-scale metabolic models are
[00:00:20.098]important tools
[00:00:20.959]that link an organism's genes,
[00:00:22.508]proteins, and reactions in
[00:00:24.118]reconstructions of their metabolic
[00:00:25.856]network. These models can predict cellular
[00:00:28.116]functions by simulating the flow
[00:00:29.703]of compounds, or metabolites,
[00:00:31.520]through this network.
[00:00:33.420]However, missing reactions
[00:00:34.850]known as "gaps" in these
[00:00:36.098]reconstructions lead to dead-end,
[00:00:38.190]or blocked, metabolites
[00:00:39.384]and hence limits application of the model.
[00:00:43.487]The Tracer algorithm is a novel
[00:00:45.175]gap-filling tool that uses
[00:00:46.509]a brute-force, confidence-based approach to solve blockages.
[00:00:49.858]The tool attempts to enable blocked pathways
[00:00:51.730]using reactions from
[00:00:52.615]other species contained in a set of
[00:00:53.737]databases.
[00:00:55.646]Once a viable pathway is found,
[00:00:57.059]its confidence score is calculated
[00:00:58.989]based on the origin of each reaction.
[00:01:01.420]If the confidence score falls
[00:01:02.592]within a user-determined threshold,
[00:01:04.358]the pathway is passed as
[00:01:05.561]a solution.
[00:01:06.874]After enough unsuccessful attempts,
[00:01:08.312]the algorithm attempts to
[00:01:09.632]solve the blockage by gradually
[00:01:12.209]relaxing parameters, a process
[00:01:14.205]known as rule-breaking.
[00:01:20.086]As the Tracer algorithm is a new
[00:01:21.411]and developing tool, the
[00:01:22.576]primary objectives of this
[00:01:23.761]research included optimization
[00:01:24.846]of the algorithm and validation
[00:01:26.714]of its results.
[00:01:31.073]To develop and test
[00:01:32.520]the algorithm, a model of the
[00:01:34.356]plant species, maize, was used.
[00:01:36.476]The Present Database then
[00:01:37.419]contained all the maize reactions,
[00:01:39.100]the Super Database contained
[00:01:40.361]reactions from closely-related plants,
[00:01:42.435]the Ortholog Database contained orthologs
[00:01:44.411](or genes with the same function in
[00:01:46.293]different organisms) for each of the
[00:01:48.151]species in the Super Database,
[00:01:49.762]and the Master Database contained
[00:01:51.088]all known plant reactions.
[00:01:54.648]However, formatting
[00:01:55.444]inconsistencies in the Super and
[00:01:57.057]Ortholog databases prevented
[00:01:58.740]the algorithm from assigning accurate
[00:02:00.544]confidence scores according to
[00:02:01.875]the gene-protein-reaction, or GPR,
[00:02:04.198]association-based process
[00:02:05.570]depicted in Figure 3.
[00:02:08.303]To address the issue,
[00:02:09.386]a standardized format was
[00:02:10.615]applied to the GPR information
[00:02:12.260]contained within the Super
[00:02:13.071]Database to improve readability
[00:02:15.482]and the algorithm was adapted
[00:02:16.641]to read this new
[00:02:17.466]format.
[00:02:18.764]Additionally, a new
[00:02:19.764]Ortholog Database was compiled
[00:02:21.126]using the original, as well as five
[00:02:23.462]open-source databases containing
[00:02:25.415]the orthologs for each species.
[00:02:28.161]The gene names were then
[00:02:28.997]translated to match the
[00:02:29.633]naming convention of the genes
[00:02:31.583]in the Super Database.
[00:02:34.487]By analyzing information
[00:02:35.649]from each trial, it was
[00:02:37.196]determined that the
[00:02:37.846]algorithm was testing
[00:02:38.553]reactions in a haphazard
[00:02:39.806]manner.
[00:02:40.960]The diversification of the pool of
[00:02:42.478]possible reactions--intended to enable
[00:02:44.919]a more thorough search once
[00:02:46.052]the original pool had failed--was
[00:02:47.995]being applied ineffectively and
[00:02:49.383]reactions were being
[00:02:50.165]tested in a random order.
[00:02:52.378]Additionally,
[00:02:53.009]the algorithm was
[00:02:53.544]testing a large number
[00:02:54.351]of pathways that had
[00:02:55.790]previously failed due to delayed
[00:02:57.511]rule-breaking and failure of a
[00:02:58.604]metabolite, which
[00:02:59.587]resulted in long run-times.
[00:03:03.193]Finally, to begin validation
[00:03:04.277]of the algorithm, the reaction
[00:03:06.056]producing pelargonidin 3-glucoside
[00:03:08.721]from pelargonidin--part of the
[00:03:10.581]well-studied anthocyanin subsystem
[00:03:12.562]found in many plant species--was
[00:03:14.319]removed from the model. The algorithm
[00:03:16.627]was then executed to
[00:03:17.664]solve this blockage and the
[00:03:19.004]result compared to the known pathway.
[00:03:24.084]According to the previous analysis,
[00:03:25.683]changes were made to the algorithm
[00:03:26.955]to improve its functionality. In
[00:03:29.337]the most recent version,
[00:03:30.590]diversification of the reaction
[00:03:32.382]pool occurred once the
[00:03:33.688]original pool had been exhausted,
[00:03:35.474]rather than on every even trial,
[00:03:37.056]like the original algorithm.
[00:03:39.155]Instead of randomly testing reactions
[00:03:40.582]from the solution pool,
[00:03:42.452]reactions were tested in order
[00:03:43.589]from best to worst confidence score.
[00:03:46.367]FInally, the algorithm, which originally
[00:03:47.734]checked only every ten
[00:03:48.973]trials to see if it had exhausted
[00:03:50.412]all possibilities and should engage
[00:03:52.180]rule-breaking or fail a metabolite early,
[00:03:54.902]also began to check for exhaustion
[00:03:56.064]of possibilities after the
[00:03:57.448]reaction pool had been
[00:03:58.047]diversified.
[00:04:01.263]As shown here, the updated
[00:04:02.636]algorithm was able to solve more
[00:04:04.160]blocked metabolites and provide a GPR
[00:04:05.939]verification for about
[00:04:07.571]sixty-four percent of the
[00:04:08.551]reactions it added, compared to
[00:04:09.797]twenty-two percent
[00:04:10.618]in the original algorithm. Finally
[00:04:12.984]the updated algorithm used about
[00:04:14.413]forty percent of the number
[00:04:15.557]of trials as the original.
[00:04:21.995]Finally, the algorithm was
[00:04:23.058]able to successfully fill the gap
[00:04:24.640]introduced in the anthocyanin
[00:04:26.070]pathway as shown in the figure.
[00:04:32.563]The ability of the Tracer algorithm
[00:04:34.120]to fill the gap introduced
[00:04:35.201]in the anthocyanin
[00:04:36.201]pathway suggests that the
[00:04:37.687]algorithm can be used to
[00:04:38.971]assist with modelling of
[00:04:40.069]subsystems typically overlooked
[00:04:41.740]by other gap-filling algorithms.
[00:04:44.434]The large path functionality of
[00:04:45.355]the Tracer algorithm, which enables
[00:04:47.044]the creation of extensive, sprawling
[00:04:48.528]pathways, can also help with pathway
[00:04:51.199]discovery by generating targets
[00:04:52.683]for lab verification.
[00:04:59.205]Before the Tracer algorithm can be
[00:05:00.559]used extensively, additional
[00:05:02.374]verification must be
[00:05:03.615]conducted using more complex pathways.
[00:05:06.865]The algorithm should also be
[00:05:08.199]generalized to work with any
[00:05:09.505]species--given the correct inputs--
[00:05:11.486]and its user-interface and pipeline
[00:05:12.999]should be improved to facilitate
[00:05:14.382]this process.
[00:05:18.810]This work was funded by the National
[00:05:20.135]Science Foundation, and I would like
[00:05:21.853]to thank them, and the University
[00:05:23.630]of Nebraska - Lincoln, Center for Root
[00:05:25.608]and Rhizobiome Innovation,
[00:05:27.418]for their support.
[00:05:28.765]Thank you.

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Improving the Efficacy of the Tracer Algorithm as a Gap-Filling and Pathway Prediction Tool for Metabolic Models

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