A refined picture of the native amine dehydrogenase family revealed by extensive biodiversity screening.

Native amine dehydrogenases offer sustainable access to chiral amines, so the search for scaffolds capable of converting more diverse carbonyl compounds is required to reach the full potential of this alternative to conventional synthetic reductive aminations. Here we report a multidisciplinary strategy combining bioinformatics, chemoinformatics and biocatalysis to extensively screen billions of sequences in silico and to efficiently find native amine dehydrogenases features using computational approaches. In this way, we achieve a comprehensive overview of the initial native amine dehydrogenase family, extending it from 2,011 to 17,959 sequences, and identify native amine dehydrogenases with non-reported substrate spectra, including hindered carbonyls and ethyl ketones, and accepting methylamine and cyclopropylamine as amine donor. We also present preliminary model-based structural information to inform the design of potential (R)-selective amine dehydrogenases, as native amine dehydrogenases are mostly (S)-selective. This integrated strategy paves the way for expanding the resource of other enzyme families and in highlighting enzymes with original features.

SulfAtlas, the sulfatase database: state of the art and new developments.

SulfAtlas (https://sulfatlas.sb-roscoff.fr/) is a knowledge-based resource dedicated to a sequence-based classification of sulfatases. Currently four sulfatase families exist (S1-S4) and the largest family (S1, formylglycine-dependent sulfatases) is divided into subfamilies by a phylogenetic approach, each subfamily corresponding to either a single characterized specificity (or few specificities in some cases) or to unknown substrates. Sequences are linked to their biochemical and structural information according to an expert scrutiny of the available literature. Database browsing was initially made possible both through a keyword search engine and a specific sequence similarity (BLAST) server. In this article, we will briefly summarize the experimental progresses in the sulfatase field in the last 6 years. To improve and speed up the (sub)family assignment of sulfatases in (meta)genomic data, we have developed a new, freely-accessible search engine using Hidden Markov model (HMM) for each (sub)family. This new tool (SulfAtlas HMM) is also a key part of the internal pipeline used to regularly update the database. SulfAtlas resource has indeed significantly grown since its creation in 2016, from 4550 sequences to 162 430 sequences in August 2022.

Carrageenan catabolism is encoded by a complex regulon in marine heterotrophic bacteria.

Macroalgae contribute substantially to primary production in coastal ecosystems. Their biomass, mainly consisting of polysaccharides, is cycled into the environment by marine heterotrophic bacteria using largely uncharacterized mechanisms. Here we describe the complete catabolic pathway for carrageenans, major cell wall polysaccharides of red macroalgae, in the marine heterotrophic bacterium Zobellia galactanivorans. Carrageenan catabolism relies on a multifaceted carrageenan-induced regulon, including a non-canonical polysaccharide utilization locus (PUL) and genes distal to the PUL, including a susCD-like pair. The carrageenan utilization system is well conserved in marine Bacteroidetes but modified in other phyla of marine heterotrophic bacteria. The core system is completed by additional functions that might be assumed by non-orthologous genes in different species. This complex genetic structure may be the result of multiple evolutionary events including gene duplications and horizontal gene transfers. These results allow for an extension on the definition of bacterial PUL-mediated polysaccharide digestion.

Profiling the orphan enzymes.

The emergence of Next Generation Sequencing generates an incredible amount of sequence and great potential for new enzyme discovery. Despite this huge amount of data and the profusion of bioinformatic methods for function prediction, a large part of known enzyme activities is still lacking an associated protein sequence. These particular activities are called "orphan enzymes". The present review proposes an update of previous surveys on orphan enzymes by mining the current content of public databases. While the percentage of orphan enzyme activities has decreased from 38% to 22% in ten years, there are still more than 1,000 orphans among the 5,000 entries of the Enzyme Commission (EC) classification. Taking into account all the reactions present in metabolic databases, this proportion dramatically increases to reach nearly 50% of orphans and many of them are not associated to a known pathway. We extended our survey to "local orphan enzymes" that are activities which have no representative sequence in a given clade, but have at least one in organisms belonging to other clades. We observe an important bias in Archaea and find that in general more than 30% of the EC activities have incomplete sequence information in at least one superkingdom. To estimate if candidate proteins for local orphans could be retrieved by homology search, we applied a simple strategy based on the PRIAM software and noticed that candidates may be proposed for an important fraction of local orphan enzymes. Finally, by studying relation between protein domains and catalyzed activities, it appears that newly discovered enzymes are mostly associated with already known enzyme domains. Thus, the exploration of the promiscuity and the multifunctional aspect of known enzyme families may solve part of the orphan enzyme issue. We conclude this review with a presentation of recent initiatives in finding proteins for orphan enzymes and in extending the enzyme world by the discovery of new activities.

Gene expression signature for spontaneous cancer regression in melanoma pigs.

Incomplete spontaneous regression of melanoma is common. However, complete melanoma regression is still a very rare phenomenon. Because melanoma is the most immunogenic human malignancy, the mechanisms leading to regression, based on accumulative evidence, are the host's immune responses. Unfortunately, therapies aiming to enhance the patient's natural immunity against melanoma have yet to meet their expectations. Reasons for failure include various immune escape mechanisms, induced by the tumor, that subsequently lead to tolerance. Here, we performed time-dependent gene expression profiling to unravel molecular changes involved in the transition of progressive melanoma to complete tumor regression using a porcine model. The melanoblastomabearing Libechov minipigs are highly suitable for this study because these animals exhibit naturally occurring and regressing melanomas. We were able to identify a molecular signature of the melanoma regression process. Genes regulated in this signature were associated with 1) cell cycle, 2) immune response, and 3) melanocyte differentiation. These genes may shed light on molecular mechanisms involved in complete melanoma regression and indicate what improvements are needed for successful antimelanoma therapy.

Dividing the large glycoside hydrolase family 13 into subfamilies: towards improved functional annotations of alpha-amylase-related proteins.

Family GH13, also known as the alpha-amylase family, is the largest sequence-based family of glycoside hydrolases and groups together a number of different enzyme activities and substrate specificities acting on alpha-glycosidic bonds. This polyspecificity results in the fact that the simple membership of this family cannot be used for the prediction of gene function based on sequence alone. In order to establish robust groups that show an improved correlation between sequence and enzymatic specificity, we have performed a large-scale analysis of 1691 family GH13 sequences by combining clustering, similarity search and phylogenetic methods. About 80% of the sequences could be reliably classified into 35 subfamilies. Most subfamilies appear monofunctional (i.e. contain enzymes with the same substrate and the same product). The close examination of the other, apparently polyspecific, subfamilies revealed that they actually group together enzymes with strongly related (or even sometimes virtually identical) activities. Overall our subfamily assignment allows to set the limits for genomic function prediction on this large family of biologically and industrially important enzymes.

Evolutionary and mechanistic relationships between glycosidases acting on alpha- and beta-bonds.

Because of the fast accumulation of sequences derived from genome sequencing efforts, the sampling of the sequence space in glycosidase and related enzyme families is such that sensitive sequence similarity detection methods like PSI-BLAST are now able to reveal distant, but clear, structural and evolutionary relations between glycosidases acting on alpha- and beta-bonds. We have observed this trend within groups of glycosidases with completely different folds. We postulate that the evolutionary interconversion between alpha- and beta-acting glycosidases was greatly facilitated by the fact that both types share a similar axial orientation of the glycosidic bond in the reactive bound substrate. Glycosides in the beta anomeric configuration, require a sugar ring distortion, resulting in an axial orientation of the glycosidic bond, equivalent to that of an alpha glycosidic bond, prior to displacement by nucleophilic substitution.

Carbohydrate-active enzymes involved in the secondary cell wall biogenesis in hybrid aspen.

Wood formation is a fundamental biological process with significant economic interest. While lignin biosynthesis is currently relatively well understood, the pathways leading to the synthesis of the key structural carbohydrates in wood fibers remain obscure. We have used a functional genomics approach to identify enzymes involved in carbohydrate biosynthesis and remodeling during xylem development in the hybrid aspen Populus tremula x tremuloides. Microarrays containing cDNA clones from different tissue-specific libraries were hybridized with probes obtained from narrow tissue sections prepared by cryosectioning of the developing xylem. Bioinformatic analyses using the sensitive tools developed for carbohydrate-active enzymes allowed the identification of 25 xylem-specific glycosyltransferases belonging to the Carbohydrate-Active EnZYme families GT2, GT8, GT14, GT31, GT43, GT47, and GT61 and nine glycosidases (or transglycosidases) belonging to the Carbohydrate-Active EnZYme families GH9, GH10, GH16, GH17, GH19, GH28, GH35, and GH51. While no genes encoding either polysaccharide lyases or carbohydrate esterases were found among the secondary wall-specific genes, one putative O-acetyltransferase was identified. These wood-specific enzyme genes constitute a valuable resource for future development of engineered fibers with improved performance in different applications.

Why are there so many carbohydrate-active enzyme-related genes in plants?

Plants contain far more carbohydrate-active enzyme-encoding genes than any other organism sequenced to date. The extremely large number of glycosidase and glycosyltransferase-related genes in plant genomes can be explained by the complex structure of the plant cell wall, by ancient genome duplication and by recent local duplications, but also by the recent emergence of novel and unrelated protein functions based on widely available pre-existing scaffolds.