A computational learning paradigm to targeted discovery of biocatalysts from metagenomic data: A case study of lipase identification.

The growing adoption of enzymes as biocatalysts in various industries has accentuated the demand for acquiring access to the great natural diversity and, in the meantime, the advent and advancements of metagenomics and high-throughput sequencing technologies have offered an unprecedented opportunity to explore this extensive resource. Lipases, enzymes responsible for the biological turnover of lipids, are among the most commercialized biocatalysts with numerous applications in different domains and therefore are of high industrial value. The relatively costly and time-consuming wet-lab experimental pipelines commonly used for novel enzyme discovery, highlight the necessity of agile in silico approaches to keep pace with the exponential growth of available sequencing data. In the present study, an in-depth analysis of a tannery wastewater metagenome, including taxonomic and enzymatic profiling, was performed. Using sequence homology-based screening methods and supervised machine learning-based regression models aimed at prediction of lipases' pH and temperature optima, the metagenomic data set was screened for lipolytic enzymes, which led to the isolation of alkaline and highly thermophilic novel lipase. Moreover, MeTarEnz (metagenomic targeted enzyme miner) software was developed and made freely accessible (at https://cbb.ut.ac.ir/MeTarEnz) as a part of this study. MeTarEnz offers several functions to automate the process of targeted enzyme mining from high-throughput sequencing data. This study highlights the competence of computational approaches in exploring vast biodiversity within environmental niches, while providing a set of practical in silico tools as well as a generalized methodology to facilitate the sequence-based mining of biocatalysts.

The Metabolic Signature of Biomass Formation in Barley.

The network analysis of genome-wide transcriptome responses, metabolic signatures and enzymes' relationship to biomass formation has been studied in a diverse panel of 12 barley accessions during vegetative and reproductive stages. The primary metabolites and enzymes involved in central metabolism that determine the accumulation of shoot biomass at the vegetative stage of barley development are primarily being linked to sucrose accumulation and sucrose synthase activity. Interestingly, the metabolic and enzyme links which are strongly associated with biomass accumulation during reproductive stages are related to starch accumulation and tricarboxylic acid (TCA) cycle intermediates citrate, malate, trans-aconitate and isocitrate. Additional significant associations were also found for UDP glucose, ATP and the amino acids isoleucine, valine, glutamate and histidine during the reproductive stage. A network analysis resulted in a combined identification of metabolite and enzyme signatures indicative for grain weight accumulation that was correlated with the activity of ADP-glucose pyrophosphorylase (AGPase), a rate-limiting enzyme involved in starch biosynthesis, and with that of alanine amino transferase involved in the synthesis of storage proteins. We propose that the mechanism related to vegetative and reproductive biomass formation vs. seed biomass formation is being linked to distinct fluxes regulating sucrose, starch, sugars and amino acids as central resources. These distinct biomarkers can be used to engineer biomass production and grain weight in barley.

Distribution of indole-3-acetic acid in Petunia hybrida shoot tip cuttings and relationship between auxin transport, carbohydrate metabolism and adventitious root formation.

To determine the contribution of polar auxin transport (PAT) to auxin accumulation and to adventitious root (AR) formation in the stem base of Petunia hybrida shoot tip cuttings, the level of indole-3-acetic acid (IAA) was monitored in non-treated cuttings and cuttings treated with the auxin transport blocker naphthylphthalamic acid (NPA) and was complemented with precise anatomical studies. The temporal course of carbohydrates, amino acids and activities of controlling enzymes was also investigated. Analysis of initial spatial IAA distribution in the cuttings revealed that approximately 40 and 10 % of the total IAA pool was present in the leaves and the stem base as rooting zone, respectively. A negative correlation existed between leaf size and IAA concentration. After excision of cuttings, IAA showed an early increase in the stem base with two peaks at 2 and 24 h post excision and, thereafter, a decline to low levels. This was mirrored by the expression pattern of the auxin-responsive GH3 gene. NPA treatment completely suppressed the 24-h peak of IAA and severely inhibited root formation. It also reduced activities of cell wall and vacuolar invertases in the early phase of AR formation and inhibited the rise of activities of glucose-6-phosphate dehydrogenase and phosphofructokinase during later stages. We propose a model in which spontaneous AR formation in Petunia cuttings is dependent on PAT and on the resulting 24-h peak of IAA in the rooting zone, where it induces early cellular events and also stimulates sink establishment. Subsequent root development stimulates glycolysis and the pentose phosphate pathway.