Embracing enzyme promiscuity with activity-based compressed biosensing

Genome-scale activity-based profiling of proteases requires identifying substrates that are specific to each individual protease. However, this process becomes increasingly difficult as the number of target proteases increases because most substrates are promiscuously cleaved by multiple proteases. We introduce a method - Substrate Libraries for Compressed sensing of Enzymes (SLICE) - for selecting complementary sets of promiscuous substrates to compile libraries that classify complex protease samples (1) without requiring deconvolution of the compressed signals and (2) without the use of highly specific substrates. SLICE ranks substrate libraries according to two features: substrate orthogonality and protease coverage. To quantify these features, we design a compression score that was predictive of classification accuracy across 140 in silico libraries (Pearson r = 0.71) and 55 in vitro libraries (Pearson r = 0.55) of protease substrates. We demonstrate that a library comprising only two protease substrates selected with SLICE can accurately classify twenty complex mixtures of 11 enzymes with perfect accuracy. We envision that SLICE will enable the selection of peptide libraries that capture information from hundreds of enzymes while using fewer substrates for applications such as the design of activity-based sensors for imaging and diagnostics.

Dual Activity BLEG-1 from Bacillus lehensis G1 Revealed Structural Resemblance to B3 Metallo-β-Lactamase and Glyoxalase II: An Insight into Its Enzyme Promiscuity and Evolutionary Divergence

Metallo-β-lactamases (MBLs) are class B β-lactamases from the metallo-hydrolase-like MBL-fold superfamily which act on a broad range of β-lactam antibiotics. A previous study on BLEG-1 (formerly called Bleg1_2437), a hypothetical protein from Bacillus lehensis G1, revealed sequence similarity and activity to B3 subclass MBLs, despite its evolutionary divergence from these enzymes. Its relatedness to glyoxalase II (GLXII) raises the possibility of its enzymatic promiscuity and unique structural features compared to other MBLs and GLXIIs. This present study highlights that BLEG-1 possessed both MBL and GLXII activities with similar catalytic efficiencies. Its crystal structure revealed highly similar active site configuration to YcbL and GloB GLXIIs from Salmonella enterica, and L1 B3 MBL from Stenotrophomonas maltophilia. However, different from GLXIIs, BLEG-1 has an insertion of an active-site loop, forming a binding cavity similar to B3 MBL at the N-terminal region. We propose that BLEG-1 could possibly have evolved from GLXII and adopted MBL activity through this insertion.

Conserved Metabolic and Evolutionary Themes in Microbial Degradation of Carbamate Pesticides

Carbamate pesticides are widely used as insecticides, nematicides, acaricides, herbicides and fungicides in the agriculture, food and public health sector. However, only a minor fraction of the applied quantity reaches the target organisms. The majority of it persists in the environment, impacting the non-target biota, leading to ecological disturbance. The toxicity of these compounds to biota is mediated through cholinergic and non-cholinergic routes, thereby making their clean-up cardinal. Microbes, specifically bacteria, have adapted to the presence of these compounds by evolving degradation pathways and thus play a major role in their removal from the biosphere. Over the past few decades, various genetic, metabolic and biochemical analyses exploring carbamate degradation in bacteria have revealed certain conserved themes in metabolic pathways like the enzymatic hydrolysis of the carbamate ester or amide linkage, funnelling of aryl carbamates into respective dihydroxy aromatic intermediates, C1 metabolism and nitrogen assimilation. Further, genomic and functional analyses have provided insights on mechanisms like horizontal gene transfer and enzyme promiscuity, which drive the evolution of degradation phenotype. Compartmentalisation of metabolic pathway enzymes serves as an additional strategy that further aids in optimising the degradation efficiency. This review highlights and discusses the conclusions drawn from various analyses over the past few decades; and provides a comprehensive view of the environmental fate, toxicity, metabolic routes, related genes and enzymes as well as evolutionary mechanisms associated with the degradation of widely employed carbamate pesticides. Additionally, various strategies like application of consortia for efficient degradation, metabolic engineering and adaptive laboratory evolution, which aid in improvising remediation efficiency and overcoming the challenges associated with in situ bioremediation are discussed.

Metabolic Rewiring and the Characterization of Oncometabolites

The study of low-molecular-weight metabolites that exist in cells and organisms is known as metabolomics and is often conducted using mass spectrometry laboratory platforms. Definition of oncometabolites in the context of the metabolic phenotype of cancer cells has been accomplished through metabolomics. Oncometabolites result from mutations in cancer cell genes or from hypoxia-driven enzyme promiscuity. As a result, normal metabolites accumulate in cancer cells to unusually high concentrations or, alternatively, unusual metabolites are produced. The typical oncometabolites fumarate, succinate, (2R)-hydroxyglutarate and (2S)-hydroxyglutarate inhibit 2-oxoglutarate-dependent dioxygenases, such as histone demethylases and HIF prolyl-4-hydroxylases, together with DNA cytosine demethylases. As a result of the cancer cell acquiring this new metabolic phenotype, major changes in gene transcription occur and the modification of the epigenetic landscape of the cell promotes proliferation and progression of cancers. Stabilization of HIF1α through inhibition of HIF prolyl-4-hydroxylases by oncometabolites such as fumarate and succinate leads to a pseudohypoxic state that promotes inflammation, angiogenesis and metastasis. Metabolomics has additionally been employed to define the metabolic phenotype of cancer cells and patient biofluids in the search for cancer biomarkers. These efforts have led to the uncovering of the putative oncometabolites sarcosine, glycine, lactate, kynurenine, methylglyoxal, hypotaurine and (2R,3S)-dihydroxybutanoate, for which further research is required.

Enzyme promiscuity in natural environments: alkaline phosphatase in the ocean

Alkaline phosphatase (APase) is one of the marine enzymes used by oceanic microbes to obtain inorganic phosphorus (Pi) from dissolved organic phosphorus to overcome P-limitation. Marine APase is generally recognized to perform P-monoesterase activity. Here we integrated a biochemical characterization of a specific APase enzyme, examination of global ocean databases, and field measurements, to study the type and relevance of marine APase promiscuity. We performed an in silico mining of phoA homologs, followed by de novo synthesis and heterologous expression in E. coli of the full-length gene from Alteromonas mediterranea, resulting in a recombinant PhoA. A global analysis using the TARA Oceans, Malaspina and other metagenomic databases confirmed the predicted widespread distribution of the gene encoding the targeted PhoA in all oceanic basins throughout the water column. Kinetic assays with the purified PhoA enzyme revealed that this enzyme exhibits not only the predicted P-monoester activity, but also P-diesterase, P-triesterase and sulfatase activity as a result of a promiscuous behavior. Among all activities, P-monoester bond hydrolysis exhibited the highest catalytic activity of APase despite its lower affinity for phosphate monoesters. APase is highly efficient as a P-monoesterase at high substrate concentrations, whereas promiscuous activities of APase, like diesterase, triesterase, and sulfatase activities are more efficient at low substrate concentrations. Strong similarities were observed between the monoesterase:diesterase ratio of the purified PhoA protein in the laboratory and in natural seawater. Thus, our results reveal enzyme promiscuity of APase playing potentially an important role in the marine phosphorus cycle.

Enzyme Promiscuity Prediction Using Hierarchy-Informed Multi-Label Classification

Motivation As experimental efforts are costly and time consuming, computational characterization of enzyme capabilities is an attractive alternative. We present and evaluate several machine-learning models to predict which of 983 distinct enzymes, as defined via the Enzyme Commission (EC) numbers, are likely to interact with a given query molecule. Our data consists of enzyme-substrate interactions from the BRENDA database. Some interactions are attributed to natural selection and involve the enzyme’s natural substrates. The majority of the interactions however involve non-natural substrates, thus reflecting promiscuous enzymatic activities. Results We frame this “enzyme promiscuity prediction” problem as a multi-label classification task. We maximally utilize inhibitor and unlabelled data to train prediction models that can take advantage of known hierarchical relationships between enzyme classes. We report that a hierarchical multi-label neural network, EPP-HMCNF, is the best model for solving this problem, outperforming k-nearest neighbours similarity-based and other machine learning models. We show that inhibitor information during training consistently improves predictive power, particularly for EPP-HMCNF. We also show that all promiscuity prediction models perform worse under a realistic data split when compared to a random data split, and when evaluating performance on non-natural substrates compared to natural substrates. Availability and implementation We provide Python code for EPP-HMCNF and other models in a repository termed EPP (Enzyme Promiscuity Prediction) at https://github.com/hassounlab/EPP. Supplementary information Supplementary data are available at Bioinformatics online.

Ancestral class-promiscuity as a driver of functional diversity in the BAHD acyltransferase family in plants

ABSTRACTGene duplication-divergence and enzyme promiscuity drive metabolic diversification in plants, but how they contribute to functional innovation in enzyme families is not clearly understood. In this study, we addressed this question using the large BAHD acyltransferase family as a model. This fast-evolving family, which uses diverse substrates, expanded drastically during land plant evolution. In vitro characterization of 11 BAHDs against a substrate panel and phylogenetic analyses revealed that the ancestral enzymes prior to origin of land plants were likely capable of promiscuously utilizing most of the substrate classes used by current, largely specialized enzymes. Motif enrichment analysis in anthocyanin/flavonoid-acylating BAHDs helped identify two motifs that potentially contributed to specialization of the ancestral anthocyanin-acylation capability. Molecular dynamic simulations and enzyme kinetics further resolved the potential roles of these motifs in the path towards specialization. Our results illuminate how promiscuity in robust and evolvable enzymes contributes to functional diversity in enzyme families.