3D-printed structured adsorbents for molecular separation

Most adsorbents are produced as porous, micron-sized powder materials and are thus not suitable to be directly used in adsorption processes. In order to avoid excessive pressure drop during flow of gas or liquid streams through a packed bed of adsorbent, these powders are shaped into larger particles or structured adsorbents. Extrudates, beads or pellets with a size of several millimeters are widely used in industrial processes. The most important disadvantages of such particles include the relatively large pressure drop they generate at high flow rates and the presence of mass transfer limitations as a result of slow diffusion of molecules to the core of the particles. A trade-off between these two effects limits the possibilities to optimize packed bed adsorptive separation processes; e.g. decreasing pellet size allows to reduce mass transfer limitations but this in turn leads to larger pressure drops. In practice, bed geometry (length/width of the packed bed) is adapted to limit pressure drop. Nevertheless, classical packed beds are not ideal for processes in which very short cycle times or very high gas or liquid velocities are required. Other types of adsorbent formulation that allow eliminating the limitations mentioned above are thus of large interest. Monolithic adsorbents are superior to classical packed bed adsorbents in terms of pressure drop and mass transfer kinetics. The honeycomb structure, mostly known from catalytic exhaust treatment in the automotive industry, is a well-known example, but monolithic structures are also used in liquid chromatography and heterogeneous catalysis. Nevertheless, the production of monoliths is complicated; classical extrusion processes only offer a very limited flexibility in the geometric properties of the monolith while polymerization processes are not suited for the production of materials for high temperature applications. Please click Additional Files below to see the full abstract

Strategy for the identification of micro-organisms producing food and feed products : bacteria producing food enzymes as study case

Recent European regulations require safety assessments of food enzymes (FE) before their commercialization. FE are mainly produced by micro-organisms, whose viable strains nor associated DNA can be present in the final products. Currently, no strategy targeting such impurities exists in enforcement laboratories. Therefore, a generic strategy of first line screening was developed to detect and identify, through PCR amplification and sequencing of the 16S-rRNA gene, the potential presence of FE producing bacteria in FE preparations. First, the specificity was verified using all microbial species reported to produce FE. Second, an in-house database, with 16S reference sequences from bacteria producing FE, was constructed for their fast identification through blast analysis. Third, the sensitivity was assessed on a spiked FE preparation. Finally, the applicability was verified using commercial FE preparations. Using straightforward PCR amplifications, Sanger sequencing and blast analysis, the proposed strategy was demonstrated to be convenient for implementation in enforcement laboratories

Novel norovirus recombinants and of GII.4 sub-lineages associated with outbreaks between 2006 and 2010 in Belgium

<p>Abstract</p> <p>Background</p> <p>Noroviruses (NoVs) are an important cause of acute gastroenteritis in humans worldwide. To gain insight into the epidemiologic patterns of NoV outbreaks and to determine the genetic variation of NoVs strains circulating in Belgium, stool samples originating from patients infected with NoVs in foodborne outbreak investigations were analysed between December 2006 and December 2010.</p> <p>Results</p> <p>NoVs were found responsible of 11.8% of all suspected foodborne outbreaks reported in the last 4 years and the number of NoV outbreaks reported increased along the years representing more than 30% of all foodborne outbreaks in 2010. Genogroup II outbreaks largely predominated and represented more than 90% of all outbreaks. Phylogenetic analyses were performed with 63 NoV-positive samples for the partial polymerase (N = 45) and/or capsid gene (N = 35) sequences. For 12 samples, sequences covering the ORF1-ORF2 junction were obtained. A variety of genotypes was found among genogroups I and II; GII.4 was predominant followed in order of importance by GII.2, GII.7, GII.13, GI.4 and GI.7. In the study period, GII.4 NoVs variants 2006a, 2006b, 2007, 2008 and 2010 were identified. Moreover, phylogenetic analyses identified different recombinant NoV strains that were further characterised as intergenotype (GII.e/GII.4 2007, GII.e/GII.3 and GII.g/GII.1) and intersub-genotype (GII.4 2006b/GII.4 2007 and GII.4 2010/GII.4 2010b) recombinants.</p> <p>Conclusions</p> <p>NoVs circulating in the last 4 years in Belgium showed remarkable genetic diversity either by small-scale mutations or genetic recombination. In this period, GII.4 2006b was successfully displaced by the GII.4 2010 subtype, and previously reported epidemic GII.b recombinants seemed to have been superseded by GII.e recombinants in 2009 and GII.g recombinants in 2010. This study showed that the emergence of novel GII.4 variants together with novel GII recombinants could lead to an explosion in NoV outbreaks, likewise to what was observed in 2008 and 2010. Among recombinants detected in this study, two hitherto unreported strains GII.e/GII.3 and GII.g/GII.1 were characterised. Surveillance will remain important to monitor contemporaneously circulating strains in order to adapt preventive and curative strategies.</p

Strain-level metagenomic data analysis of enriched in vitro and in silico spiked food samples : paving the way towards a culture-free foodborne outbreak investigation using STEC as a case study

Culture-independent diagnostics, such as metagenomic shotgun sequencing of food samples, could not only reduce the turnaround time of samples in an outbreak investigation, but also allow the detection of multi-species and multi-strain outbreaks. For successful foodborne outbreak investigation using a metagenomic approach, it is, however, necessary to bioinformatically separate the genomes of individual strains, including strains belonging to the same species, present in a microbial community, which has up until now not been demonstrated for this application. The current work shows the feasibility of strain-level metagenomics of enriched food matrix samples making use of data analysis tools that classify reads against a sequence database. It includes a brief comparison of two database-based read classification tools, Sigma and Sparse, using a mock community obtained by in vitro spiking minced meat with a Shiga toxin-producing Escherichia coli (STEC) isolate originating from a described outbreak. The more optimal tool Sigma was further evaluated using in silico simulated metagenomic data to explore the possibilities and limitations of this data analysis approach. The performed analysis allowed us to link the pathogenic strains from food samples to human isolates previously collected during the same outbreak, demonstrating that the metagenomic approach could be applied for the rapid source tracking of foodborne outbreaks. To our knowledge, this is the first study demonstrating a data analysis approach for detailed characterization and phylogenetic placement of multiple bacterial strains of one species from shotgun metagenomic WGS data of an enriched food sample

A practical method to implement strain-level metagenomics-based foodborne outbreak investigation and source tracking in routine

The management of a foodborne outbreak depends on the rapid and accurate identification of the responsible food source. Conventional methods based on isolation of the pathogen from the food matrix and target-specific real-time polymerase chain reactions (qPCRs) are used in routine. In recent years, the use of whole genome sequencing (WGS) of bacterial isolates has proven its value to collect relevant information for strain characterization as well as tracing the origin of the contamination by linking the food isolate with the patient’s isolate with high resolution. However, the isolation of a bacterial pathogen from food matrices is often time-consuming and not always successful. Therefore, we aimed to improve outbreak investigation by developing a method that can be implemented in reference laboratories to characterize the pathogen in the food vehicle without its prior isolation and link it back to human cases. We tested and validated a shotgun metagenomics approach by spiking food pathogens in specific food matrices using the Shiga toxin-producing Escherichia coli (STEC) as a case study. Different DNA extraction kits and enrichment procedures were investigated to obtain the most practical workflow. We demonstrated the feasibility of shotgun metagenomics to obtain the same information as in ISO/TS 13136:2012 and WGS of the isolate in parallel by inferring the genome of the contaminant and characterizing it in a shorter timeframe. This was achieved in food samples containing different E. coli strains, including a combination of different STEC strains. For the first time, we also managed to link individual strains from a food product to isolates from human cases, demonstrating the power of shotgun metagenomics for rapid outbreak investigation and source tracking

The benefits of whole genome sequencing for foodborne outbreak investigation from the perspective of a national reference laboratory in a smaller country

Gradually, conventional methods for foodborne pathogen typing are replaced by whole genome sequencing (WGS). Despite studies describing the overall benefits, National Reference Laboratories of smaller countries often show slower uptake of WGS, mainly because of significant investments required to generate and analyze data of a limited amount of samples. To facilitate this process and incite policy makers to support its implementation, a Shiga toxin-producing Escherichia coli (STEC) O157:H7 (stx1+, stx2+, eae+) outbreak (2012) and a STEC O157:H7 (stx2+, eae+) outbreak (2013) were retrospectively analyzed using WGS and compared with their conventional investigations. The corresponding results were obtained, with WGS delivering even more information, e.g., on virulence and antimicrobial resistance genotypes. Besides a universal, all-in-one workflow with less hands-on-time (five versus seven actual working days for WGS versus conventional), WGS-based cgMLST-typing demonstrated increased resolution. This enabled an accurate cluster definition, which remained unsolved for the 2013 outbreak, partly due to scarce epidemiological linking with the suspect source. Moreover, it allowed detecting two and one earlier circulating STEC O157:H7 (stx1+, stx2+, eae+) and STEC O157:H7 (stx2+, eae+) strains as closely related to the 2012 and 2013 outbreaks, respectively, which might have further directed epidemiological investigation initially. Although some bottlenecks concerning centralized data-sharing, sampling strategies, and perceived costs should be considered, we delivered a proof-of-concept that even in smaller countries, WGS offers benefits for outbreak investigation, if a sufficient budget is available to ensure its implementation in surveillance. Indeed, applying a database with background isolates is critical in interpreting isolate relationships to outbreaks, and leveraging the true benefit of WGS in outbreak investigation and/or prevention

Application of a strain- level shotgun metagenomics approach on food samples : resolution of the source of a Salmonella food-borne outbreak

Food- borne outbreak investigation currently relies on the time- consuming and challenging bacterial isolation from food, to be able to link food- derived strains to more easily obtained isolates from infected people. When no food isolate can be obtained, the source of the outbreak cannot be unambiguously determined. Shotgun metagenomics approaches applied to the food samples could circumvent this need for isolation from the suspected source, but require downstream strain- level data analysis to be able to accurately link to the human isolate. Until now, this approach has not yet been applied outside research settings to analyse real food- borne outbreak samples. In September 2019, a Salmonella outbreak occurred in a hotel school in Bruges, Belgium, affecting over 200 students and teachers. Following standard procedures, the Belgian National Reference Center for human salmonellosis and the National Reference Laboratory for Salmonella in food and feed used conventional analysis based on isolation, serotyping and MLVA (multilocus variable number tandem repeat analysis) comparison, followed by wholegenome sequencing, to confirm the source of the contamination over 2 weeks after receipt of the sample, which was freshly prepared tartar sauce in a meal cooked at the school. Our team used this outbreak as a case study to deliver a proof of concept for a short- read strain- level shotgun metagenomics approach for source tracking. We received two suspect food samples: the full meal and some freshly made tartar sauce served with this meal, requiring the use of raw eggs. After analysis, we could prove, without isolation, that Salmonella was present in both samples, and we obtained an inferred genome of a Salmonella enterica subsp. enterica serovar Enteritidis that could be linked back to the human isolates of the outbreak in a phylogenetic tree. These metagenomics- derived outbreak strains were separated from sporadic cases as well as from another outbreak circulating in Europe at the same time period. This is, to our knowledge, the first Salmonella food- borne outbreak investigation uniquely linking the food source using a metagenomics approach and this in a fast time frame

Diverse roles of androgen receptor (AR) domains in AR-mediated signaling

Androgens control male sexual development and maintenance of the adult male phenotype. They have very divergent effects on their target organs like the reproductive organs, muscle, bone, brain and skin. This is explained in part by the fact that different cell types respond differently to androgen stimulus, even when all these responses are mediated by the same intracellular androgen receptor. To understand these tissue- and cell-specific readouts of androgens, we have to learn the many different steps in the transcription activation mechanisms of the androgen receptor (NR3C4). Like all nuclear receptors, the steroid receptors have a central DNA-binding domain connected to a ligand-binding domain by a hinge region. In addition, all steroid receptors have a relatively large amino-terminal domain. Despite the overall structural homology with other nuclear receptors, the androgen receptor has several specific characteristics which will be discussed here. This receptor can bind two types of androgen response elements (AREs): one type being similar to the classical GRE/PRE-type elements, the other type being the more divergent and more selective AREs. The hormone-binding domain has low intrinsic transactivation properties, a feature that correlates with the low affinity of this domain for the canonical LxxLL-bearing coactivators. For the androgen receptor, transcriptional activation involves the alternative recruitment of coactivators to different regions in the amino-terminal domain, as well as the hinge region. Finally, a very strong ligand-induced interaction between the amino-terminal domain and the ligand-binding domain of the androgen receptor seems to be involved in many aspects of its function as a transcription factor. This review describes the current knowledge on the structure-function relationships within the domains of the androgen receptor and tries to integrate the involvement of different domains, subdomains and motifs in the functioning of this receptor as a transcription factor with tissue- and cell-specific readouts

Validation strategy of a bioinformatics whole genome sequencing workflow for Shiga toxin-producing Escherichia coli using a reference collection extensively characterized with conventional methods

Whole genome sequencing (WGS) enables complete characterization of bacterial pathogenic isolates at single nucleotide resolution, making it the ultimate tool for routine surveillance and outbreak investigation. The lack of standardization, and the variation regarding bioinformatics workflows and parameters, however, complicates interoperability among (inter)national laboratories. We present a validation strategy applied to a bioinformatics workflow for Illumina data that performs complete characterization of Shiga toxin-producing Escherichia coli (STEC) isolates including antimicrobial resistance prediction, virulence gene detection, serotype prediction, plasmid replicon detection and sequence typing. The workflow supports three commonly used bioinformatics approaches for the detection of genes and alleles: alignment with blast+, kmer-based read mapping with KMA, and direct read mapping with SRST2. A collection of 131 STEC isolates collected from food and human sources, extensively characterized with conventional molecular methods, was used as a validation dataset. Using a validation strategy specifically adopted to WGS, we demonstrated high performance with repeatability, reproducibility, accuracy, precision, sensitivity and specificity above 95 % for the majority of all assays. The WGS workflow is publicly available as a ‘push-button’ pipeline at https://galaxy.sciensano.be. Our validation strategy and accompanying reference dataset consisting of both conventional and WGS data can be used for characterizing the performance of various bioinformatics workflows and assays, facilitating interoperability between laboratories with different WGS and bioinformatics set-ups