Abstract

Improving the bioproduction ability of efficient host microorganisms is a central aim in bioengineering. To control biosynthesis in living cells, the regulatory system of the whole biosynthetic pathway should be clearly understood. In this study, we applied our network modeling method to infer the regulatory system for triacylglyceride (TAG) biosynthesis in Lipomyces starkeyi, using factor analyses and structural equation modeling to construct a regulatory network model. By factor analysis, we classified 89 TAG biosynthesis-related genes into nine groups, which were considered different regulatory sub-systems. We constructed two different types of regulatory models. One is the regulatory model for oil productivity, and the other is the whole regulatory model for TAG biosynthesis. From the inferred oil productivity regulatory model, the well characterized genes DGA1 and ACL1 were detected as regulatory factors. Furthermore, we also found unknown feedback controls in oil productivity regulation. These regulation models suggest that the regulatory factor induction targets should be selected carefully. Within the whole regulatory model of TAG biosynthesis, some genes were detected as not related to TAG biosynthesis regulation. Using network modeling, we reveal that the regulatory system is helpful for the new era of bioengineering.

Highlights

  • The improvement of the bioproduction ability in microorganisms is one of the important themes in bioengineering fields

  • Among the several host microorganisms used in bioproduction, the oleaginous yeast Lipomyces starkeyi is quite important

  • We developed an approach based on structural equation modeling (SEM) [22,23], which has been utilized to elucidate causal relationships in disparate fields, such as econometrics, sociology and psychology [24,25,26]

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Summary

Introduction

The improvement of the bioproduction ability in microorganisms is one of the important themes in bioengineering fields. Several types of empirical breeding approaches, such as constructing random mutant strains [1,2,3] and improving key enzyme activities within the biosynthesis pathways [4,5], have been developed over the years and applied to expand the capabilities of microorganisms. Those approaches have yielded useful host strains, but their development is quite time-consuming and costly. Improving the oil production by this oleaginous yeast is a fascinating goal, for bioengineering and in industrial use as an alternative to palm oil

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