Revealing the hidden functional diversity of an enzyme family.

Millions of protein database entries are not assigned reliable functions, preventing the full understanding of chemical diversity in living organisms. Here, we describe an integrated strategy for the discovery of various enzymatic activities catalyzed within protein families of unknown or little known function. This approach relies on the definition of a generic reaction conserved within the family, high-throughput enzymatic screening on representatives, structural and modeling investigations and analysis of genomic and metabolic context. As a proof of principle, we investigated the DUF849 Pfam family and unearthed 14 potential new enzymatic activities, leading to the designation of these proteins as ß-keto acid cleavage enzymes. We propose an in vivo role for four enzymatic activities and suggest key residues for guiding further functional annotation. Our results show that the functional diversity within a family may be largely underestimated. The extension of this strategy to other families will improve our knowledge of the enzymatic landscape.

The CanOE strategy: integrating genomic and metabolic contexts across multiple prokaryote genomes to find candidate genes for orphan enzymes.

Of all biochemically characterized metabolic reactions formalized by the IUBMB, over one out of four have yet to be associated with a nucleic or protein sequence, i.e. are sequence-orphan enzymatic activities. Few bioinformatics annotation tools are able to propose candidate genes for such activities by exploiting context-dependent rather than sequence-dependent data, and none are readily accessible and propose result integration across multiple genomes. Here, we present CanOE (Candidate genes for Orphan Enzymes), a four-step bioinformatics strategy that proposes ranked candidate genes for sequence-orphan enzymatic activities (or orphan enzymes for short). The first step locates "genomic metabolons", i.e. groups of co-localized genes coding proteins catalyzing reactions linked by shared metabolites, in one genome at a time. These metabolons can be particularly helpful for aiding bioanalysts to visualize relevant metabolic data. In the second step, they are used to generate candidate associations between un-annotated genes and gene-less reactions. The third step integrates these gene-reaction associations over several genomes using gene families, and summarizes the strength of family-reaction associations by several scores. In the final step, these scores are used to rank members of gene families which are proposed for metabolic reactions. These associations are of particular interest when the metabolic reaction is a sequence-orphan enzymatic activity. Our strategy found over 60,000 genomic metabolons in more than 1,000 prokaryote organisms from the MicroScope platform, generating candidate genes for many metabolic reactions, of which more than 70 distinct orphan reactions. A computational validation of the approach is discussed. Finally, we present a case study on the anaerobic allantoin degradation pathway in Escherichia coli K-12.

Novel High-Throughput Fluorescence-Based Assay for the Identification of Nematocidal Compounds That Target the Blood-Feeding Pathway.

Hookworm infections cause a neglected tropical disease (NTD) affecting ~740 million people worldwide, principally those living in disadvantaged communities. Infections can cause high morbidity due to their impact on nutrient uptake and their need to feed on host blood, resulting in a loss of iron and protein, which can lead to severe anaemia and impaired cognitive development in children. Currently, only one drug, albendazole is efficient to treat hookworm infection and the scientific community fears the rise of resistant strains. As part of on-going efforts to control hookworm infections and its associated morbidities, new drugs are urgently needed. We focused on targeting the blood-feeding pathway, which is essential to the parasite survival and reproduction, using the laboratory hookworm model Nippostrongylus brasiliensis (a nematode of rodents with a similar life cycle to hookworms). We established an in vitro-drug screening assay based on a fluorescent-based measurement of parasite viability during blood-feeding to identify novel therapeutic targets. A first screen of a library of 2654 natural compounds identified four that caused decreased worm viability in a blood-feeding-dependent manner. This new screening assay has significant potential to accelerate the discovery of new drugs against hookworms.

The Contribution of lincRNAs at the Interface between Cell Cycle Regulation and Cell State Maintenance.

Cell cycle progression is controlled by the interplay of established cell cycle regulators. Changes in these regulators' activity underpin differences in cell cycle kinetics between cell types. We investigated whether long intergenic noncoding RNAs (lincRNAs) contribute to embryonic stem cell cycle adaptations. Using single-cell RNA sequencing data for mouse embryonic stem cells (mESCs) staged as G1, S, or G2/M we found differentially expressed lincRNAs are enriched among cell cycle-regulated genes. These lincRNAs (CC-lincRNAs) are co-expressed with genes involved in cell cycle regulation. We tested the impact of two CC-lincRNA candidates and show using CRISPR activation that increasing their expression is associated with deregulated cell cycle progression. Interestingly, CC-lincRNAs are often differentially expressed between G1 and S, their promoters are enriched in pluripotency transcription factor (TF) binding sites, and their transcripts are frequently co-regulated with genes involved in the maintenance of pluripotency, suggesting a contribution of CC-lincRNAs to mESC cell cycle adaptations.

cis-Acting Complex-Trait-Associated lincRNA Expression Correlates with Modulation of Chromosomal Architecture.

Intergenic long noncoding RNAs (lincRNAs) are the largest class of transcripts in the human genome. Although many have recently been linked to complex human traits, the underlying mechanisms for most of these transcripts remain undetermined. We investigated the regulatory roles of a high-confidence and reproducible set of 69 trait-relevant lincRNAs (TR-lincRNAs) in human lymphoblastoid cells whose biological relevance is supported by their evolutionary conservation during recent human history and genetic interactions with other trait-associated loci. Their enrichment in enhancer-like chromatin signatures, interactions with nearby trait-relevant protein-coding loci, and preferential location at topologically associated domain (TAD) boundaries provide evidence that TR-lincRNAs likely regulate proximal trait-relevant gene expression in cis by modulating local chromosomal architecture. This is consistent with the positive and significant correlation found between TR-lincRNA abundance and intra-TAD DNA-DNA contacts. Our results provide insights into the molecular mode of action by which TR-lincRNAs contribute to complex human traits.

Metabolic diversity among main microorganisms inside an arsenic-rich ecosystem revealed by meta- and proteo-genomics.

By their metabolic activities, microorganisms have a crucial role in the biogeochemical cycles of elements. The complete understanding of these processes requires, however, the deciphering of both the structure and the function, including synecologic interactions, of microbial communities. Using a metagenomic approach, we demonstrated here that an acid mine drainage highly contaminated with arsenic is dominated by seven bacterial strains whose genomes were reconstructed. Five of them represent yet uncultivated bacteria and include two strains belonging to a novel bacterial phylum present in some similar ecosystems, and which was named 'Candidatus Fodinabacter communificans.' Metaproteomic data unravelled several microbial capabilities expressed in situ, such as iron, sulfur and arsenic oxidation that are key mechanisms in biomineralization, or organic nutrient, amino acid and vitamin metabolism involved in synthrophic associations. A statistical analysis of genomic and proteomic data and reverse transcriptase-PCR experiments allowed us to build an integrated model of the metabolic interactions that may be of prime importance in the natural attenuation of such anthropized ecosystems.