Palantir: a springboard for the analysis of secondary metabolite gene clusters in large-scale genome mining projects.

SUMMARY: To support small and large-scale genome mining projects, we present Post-processing Analysis tooLbox for ANTIsmash Reports (Palantir), a dedicated software suite for handling and refining secondary metabolite biosynthetic gene cluster (BGC) data annotated with the popular antiSMASH pipeline. Palantir provides new functionalities building on NRPS/PKS predictions from antiSMASH, such as improved BGC annotation, module delineation and easy access to sub-sequences at different levels (cluster, gene, module and domain). Moreover, it can parse user-provided antiSMASH reports and reformat them for direct use or storage in a relational database. AVAILABILITY AND IMPLEMENTATION: Palantir is released both as a Perl API available on CPAN (https://metacpan.org/release/Bio-Palantir) and as a web application (http://palantir.uliege.be). As a practical use case, the web interface also features a database built from the mining of 1616 cyanobacterial genomes, of which 1488 were predicted to encode at least one BGC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The GEN-ERA toolbox: unified and reproducible workflows for research in microbial genomics.

BACKGROUND: Microbial culture collections play a key role in taxonomy by studying the diversity of their strains and providing well-characterized biological material to the scientific community for fundamental and applied research. These microbial resource centers thus need to implement new standards in species delineation, including whole-genome sequencing and phylogenomics. In this context, the genomic needs of the Belgian Coordinated Collections of Microorganisms were studied, resulting in the GEN-ERA toolbox. The latter is a unified cluster of bioinformatic workflows dedicated to both bacteria and small eukaryotes (e.g., yeasts). FINDINGS: This public toolbox allows researchers without a specific training in bioinformatics to perform robust phylogenomic analyses. Hence, it facilitates all steps from genome downloading and quality assessment, including genomic contamination estimation, to tree reconstruction. It also offers workflows for average nucleotide identity comparisons and metabolic modeling. TECHNICAL DETAILS: Nextflow workflows are launched by a single command and are available on the GEN-ERA GitHub repository (https://github.com/Lcornet/GENERA). All the workflows are based on Singularity containers to increase reproducibility. TESTING: The toolbox was developed for a diversity of microorganisms, including bacteria and fungi. It was further tested on an empirical dataset of 18 (meta)genomes of early branching Cyanobacteria, providing the most up-to-date phylogenomic analysis of the Gloeobacterales order, the first group to diverge in the evolutionary tree of Cyanobacteria. CONCLUSION: The GEN-ERA toolbox can be used to infer completely reproducible comparative genomic and metabolic analyses on prokaryotes and small eukaryotes. Although designed for routine bioinformatics of culture collections, it can also be used by all researchers interested in microbial taxonomy, as exemplified by our case study on Gloeobacterales.

Nonribosomal peptides in fungal cell factories: from genome mining to optimized heterologous production.

Fungi are notoriously prolific producers of secondary metabolites including nonribosomal peptides (NRPs). The structural complexity of NRPs grants them interesting activities such as antibiotic, anti-cancer, and anti-inflammatory properties. The discovery of these compounds with attractive activities can be achieved by using two approaches: either by screening samples originating from various environments for their biological activities, or by identifying the related clusters in genomic sequences thanks to bioinformatics tools. This genome mining approach has grown tremendously due to recent advances in genome sequencing, which have provided an incredible amount of genomic data from hundreds of microbial species. Regarding fungal organisms, the genomic data have revealed the presence of an unexpected number of putative NRP-related gene clusters. This highlights fungi as a goldmine for the discovery of putative novel bioactive compounds. Recent development of NRP dedicated bioinformatics tools have increased the capacity to identify these gene clusters and to deduce NRPs structures, speeding-up the screening process for novel metabolites discovery. Unfortunately, the newly identified compound is frequently not or poorly produced by native producers due to a lack of expression of the related genes cluster. A frequently employed strategy to increase production rates consists in transferring the related biosynthetic pathway in heterologous hosts. This review aims to provide a comprehensive overview about the topic of NRPs discovery, from gene cluster identification by genome mining to the heterologous production in fungal hosts. The main computational tools and methods for genome mining are herein presented with an emphasis on the particularities of the fungal systems. The different steps of the reconstitution of NRP biosynthetic pathway in heterologous fungal cell factories will be discussed, as well as the key factors to consider for maximizing productivity. Several examples will be developed to illustrate the potential of heterologous production to both discover uncharacterized novel compounds predicted in silico by genome mining, and to enhance the productivity of interesting bio-active natural products.

Consensus assessment of the contamination level of publicly available cyanobacterial genomes.

Publicly available genomes are crucial for phylogenetic and metagenomic studies, in which contaminating sequences can be the cause of major problems. This issue is expected to be especially important for Cyanobacteria because axenic strains are notoriously difficult to obtain and keep in culture. Yet, despite their great scientific interest, no data are currently available concerning the quality of publicly available cyanobacterial genomes. As reliably detecting contaminants is a complex task, we designed a pipeline combining six methods in a consensus strategy to assess the contamination level of 440 genome assemblies of Cyanobacteria. Two methods are based on published reference databases of ribosomal genes (SSU rRNA 16S and ribosomal proteins), one is indirectly based on a reference database of marker genes (CheckM), and three are based on complete genome analysis. Among those genome-wide methods, Kraken and DIAMOND blastx share the same reference database that we derived from Ensembl Bacteria, whereas CONCOCT does not require any reference database, instead relying on differences in DNA tetramer frequencies. Given that all the six methods appear to have their own strengths and limitations, we used the consensus of their rankings to infer that >5% of cyanobacterial genome assemblies are highly contaminated by foreign DNA (i.e., contaminants were detected by 5 or 6 methods). Our results will help researchers to check the quality of publicly available genomic data before use in their own analyses. Moreover, we argue that journals should make mandatory the submission of raw read data along with genome assemblies in order to facilitate the detection of contaminants in sequence databases.

Tablet potency of Tianeptine in coated tablets by near infrared spectroscopy: model optimisation, calibration transfer and confidence intervals.

A near infrared (NIR) method was developed for determination of tablet potency of active pharmaceutical ingredient (API) in a complex coated tablet matrix. The calibration set contained samples from laboratory and production scale batches. The reference values were obtained by high performance liquid chromatography (HPLC) and partial least squares (PLS) regression was used to establish a model. The model was challenged by calculating tablet potency of two external test sets. Root mean square errors of prediction were respectively equal to 2.0% and 2.7%. To use this model with a second spectrometer from the production field, a calibration transfer method called piecewise direct standardisation (PDS) was used. After the transfer, the root mean square error of prediction of the first test set was 2.4% compared to 4.0% without transferring the spectra. A statistical technique using bootstrap of PLS residuals was used to estimate confidence intervals of tablet potency calculations. This method requires an optimised PLS model, selection of the bootstrap number and determination of the risk. In the case of a chemical analysis, the tablet potency value will be included within the confidence interval calculated by the bootstrap method. An easy to use graphical interface was developed to easily determine if the predictions, surrounded by minimum and maximum values, are within the specifications defined by the regulatory organisation.

Development of a Process Analytical Technology (PAT) for in-line monitoring of film thickness and mass of coating materials during a pan coating operation.

The aim of this study was to perform in-line Near Infrared (NIR) measurements inside a pan coater to monitor a coating operation in real-time, by predicting the increases in mass of coating materials and coating thickness. A polymer combination of ethylcellulose/poly(vinyl-alcohol)-poly(ethylene-glycol) graft copolymer was used as functional aqueous coating. Coated tablets were sampled at regular intervals during the coating operation, then subjected to either simple and fast weighing (n=50) or accurate and non-destructive Terahertz Pulsed Imaging (TPI) measurements (n=3). Off-line NIR spectra analysis revealed that the coating operation could efficiently be controlled by focusing on two distinct NIR regions, related to absorption bands of ethylcellulose. Principal component analysis of in-line NIR spectra gave a clear classification of the collected coated tablets. Real-time quantitative monitoring of the coating operation was successfully performed from partial least square calibration models built using either TPI or weighing as reference method. Coating thicknesses as well as mass of coating materials used as primary values provided accurate NIR predictions. A comparison study demonstrated that both reference methods led to reliable and accurate real-time monitoring of the coating operation. This work demonstrated that in-line NIR measurements associated with multivariate analyses can be implemented to monitor in real-time a pan coating operation in order to fulfil the expectations of ICH Q8 guideline on pharmaceutical development, especially in terms of PAT control strategy and reduced end-product testing.