In silico prediction of protein-protein interaction network induced by manganese II in Meyerozyma guilliermondii.

Abstract

Recently, there has been an increasing interest in the use of yeast to produce biosorbent materials, because yeast is economical to use, adaptable to a variety of conditions, and amenable to morphological manipulations to yield better raw biomaterials. Previous studies from our laboratory have shown that Meyerozyma guilliermondii, a nonpathogenic haploid yeast (ascomycete), exhibits excellent biosorption capacity for Mn2+, as demonstrated by kinetic analyses. Shotgun/bottom-up analyses of soluble fractions revealed a total of 1257 identified molecules, with 117 proteins expressed in the absence of Mn2+ and 69 expressed only in the presence of Mn2+. In this article, we describe the first in silico prediction and screening of protein–protein interactions (PPIs) in M. guilliermondii using experimental data from shotgun/bottom-up analyses. We also present the categorization of biological processes (BPs), molecular functions (MFs), and metabolic pathways of 71 proteins upregulated in the M. guilliermondii proteome in response to stress caused by an excess of Mn2+ ions. Most of the annotated proteins were related to oxidation–reduction processes, metabolism, and response to oxidative stress. We identified seven functional enrichments and 42 metabolic pathways; most proteins belonged to pathways related to metabolic pathways (19 proteins) followed by the biosynthesis of secondary metabolites (10 proteins) in the presence of Mn2+. Using our data, it is possible to infer that defense mechanisms minimize the impact of Mn2+ via the expression of antioxidant proteins, thus allowing adjustment during the defense response. Previous studies have not considered protein interactions in this genus in a manner that permits comparisons. Consequently, the findings of the current study are innovative, highly relevant, and provide a description of interactive complexes and networks that yield insight into the cellular processes of M. guilliermondii. Collectively, our data will allow researchers to explore the biotechnological potential of M. guilliermondii in future bioremediation processes.