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Pronk, M.

Publications and source records attributed to Pronk, M..

8 recordsLinked to original sources

Loss of hemagglutination ability by H3N2 influenza A virus, subclade K.

Seasonal human H3N2 influenza viruses, subclade K (J.2.4.1), have been the predominant influenza A viruses in the Northern hemisphere influenza season of 2025/2026. Since 2024, the vaccine virus A/Darwin/6/21 has emerged in different antigenic variants. Antigenic changes are frequently caused by amino acid substitutions near the hemagglutinin (HA) receptor-binding pocket, which can also affect receptor binding properties, such as hemagglutination. Hemagglutination is crucial for assessing antigenicity using the hemagglutination inhibition (HAI) assay, and a loss of binding to turkey erythrocytes could significantly hamper this process. In this study, we explored how substitutions in or around the HA receptor-binding site affect binding to glycans at the molecular level. We employed ELISA, glycan array, flow cytometry, hemagglutination assays, and tissue staining. Substitutions at positions 140, 192, and 223 establish clade J viruses that emerged in 2024. Computational analysis of HA in complex with an elongated glycan reveals that mutation F192 forms a CH-Pi interaction to stabilize the binding. Based on this background, substitutions in antigenic sites A and B within subclade K viruses exhibit a binding preference for elongated glycans, which are not displayed on turkey erythrocytes. Conversely, our previously established glyco-remodeled erythrocytes are efficiently bound by these subclade K H3N2 viruses and could support influenza surveillance and vaccine development.

microbiology↗

Emergence and antigenic characterisation of influenza A(H3N2) viruses with hemagglutinin substitutions N158K and K189R during the 2024/25 influenza season

BackgroundSeasonal human influenza viruses can escape from antibody-mediated neutralization when amino acid changes occur in the hemagglutinin protein. Routine surveillance identified circulation of an A(H3N2) virus variant in the Netherlands with amino acid substitutions at hemagglutinin positions 158 and 189. These amino acid positions were previously responsible for antigenic change of influenza A(H3N2) viruses and potentially lead to escape of this variant from vaccine-mediated immunity. AimTo characterize the emergence and antigenic properties of N158K and K189R double substitution virus variants. MethodsWe analyzed the geographical and temporal dynamics of the double-substitution variant using a phylogeographic approach and used hemagglutination inhibition assays and antigenic cartography methods to map its antigenic properties. ResultsA(H3N2) viruses carrying K189R were first detected in Guatemala in June 2024, before subsequently gaining the N158K substitution, which was intially detected in Colombia in November 2024, followed by detection in the Netherlands in December 2024. However, detections within Europe remained almost entirely confined to the Netherlands. The proportion of viruses carrying the N158K and K189R substitutions increased to 16% - 24% per collection week of sequenced Dutch viruses during the peak of the epidemic of the 2024-2025 respiratory season. Antigenic characterization of viruses with N158K and K189R substitutions indicated that these are antigenically distinct from the A(H3N2) components of 2025-2026 Northern Hemisphere vaccines, showing 8-192-fold reduction in hemagglutination inhibition titers with antisera against the vaccine strain compared to antisera against the homologous virus. ConclusionsInfluenza A(H3N2) viruses with N158K and K189R escaped recognition by antibodies raised against the 2024-2025 and 2025/2026 Northern Hemipshere vaccine strains in hemagglutination inhibition assays. These variants circulated widely in the Netherlands during the 2024-2025 influenza season, raising concerns about reduced vaccine-mediated protection if such variants would spread more broadly during 2025-2026 Northern Hemipshere season.

microbiology↗

NovoLign: metaproteomics by sequence alignment

Tremendous advances in mass spectrometric and bioinformatic approaches have expanded proteomics into the field of microbial ecology. The commonly used spectral annotation method for metaproteomics data relies on database searching, which requires sample-specific databases obtained from whole metagenome sequencing experiments. However, creating these databases is complex, time-consuming, and prone to errors, potentially biasing experimental outcomes and conclusions. This asks for alternative approaches that can provide rapid and orthogonal insights into metaproteomics data. Here we present NovoLign, a de novo metaproteomics pipeline that performs sequence alignment of de novo sequences from complete metaproteomics experiments. The pipeline enables rapid taxonomic profiling of complex communities and evaluates the taxonomic coverage of metaproteomics outcomes obtained from database searches. Furthermore, the NovoLign pipeline supports the creation of reference sequence databases for database searching to ensure comprehensive coverage. The NovoLign pipeline is publicly available via: https://github.com/hbckleikamp/NovoLign.

systems biology↗

Production of extracellular polymeric substances in granular sludge under selection for Accumulibacter and Competibacter

Granular sludge intensifies the removal of nutrients from wastewater. Granules structured by extracellular polymeric substances (EPS) can be recovered as biomaterial. Links between microbial selection and EPS formation during granulation need to get uncovered. We inoculated anaerobic-aerobic sequencing batch reactors with either flocs or granules to study the relationships between microbial selection, bioaggregation, exopolymer formation, and EPS composition. Selection for slow-growing organisms like the model polyphosphate- accumulating organism "Candidatus Accumulibacter" (max. 83% vs. amplicon sequencing read counts) and glycogen-accumulating organism "Ca. Competibacter" (max. 45%) sustained granulation. Gel-forming exopolymers were produced as high as above 40% of the volatile solids of the biomass by stepwise increase of the organic loading rate (0.3 to 2.0 g CODAc d-1 LR-1). Confocal laser scanning microscopy, FT-IR spectroscopy, and HPAE-PAD chromatography revealed the complex and dynamic chemical compositions of the structural EPS in relation to microbial population shifts along reactor regimes. The analysis of 20 representative genomes of "Ca. Accumulibacter" and "Ca. Competibacter" recovered from public databases revealed their functional potential to produce EPS among other representative wastewater microorganisms. The more than 40 functional gene categories annotated highlight the complexity of EPS metabolic networks from monomers processing to assembly, export, and epimerizations. The combination of ecological engineering principles and systems microbiology will help unravel and direct the production of EPS from wastewater, valorizing residual granular sludge into beneficial biomaterials for the circular economy. HighlightsO_LISelection for slow-growing organisms like PAOs and GAOs fostered a robust granulation. C_LIO_LIStructural EPS were produced above 40% of biomass volatile content under high loading. C_LIO_LIChemical composition of EPS evolved together with the microbial community composition. C_LIO_LIGenomic insights highlighted the genetic potential of PAOs and GAOs for EPS formation. C_LIO_LIMicrobial communities are complex; further are their EPS compositions and metabolisms. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/534144v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@a163e2org.highwire.dtl.DTLVardef@1a4ab94org.highwire.dtl.DTLVardef@1fc93d4org.highwire.dtl.DTLVardef@14d4b7f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

Comparative metaproteomics demonstrates different views on the complex granular sludge microbiome

The tremendous progress in sequencing technologies has made 16S amplicon and whole metagenome sequencing routine in microbiome studies. Furthermore, advances in mass spectrometric techniques has expanded conventional proteomics into the field of microbial ecology. Commonly referred to as metaproteomics, this approach measures the gene products (i.e., proteins) to subsequently identify the actively-expressed metabolic pathways and the protein-biomass composition of complete microbial communities. However, more systematic studies on metaproteomic and genomic approaches are urgently needed, to determine the orthogonal character of these approaches. Here we describe a deep, comparative metaproteomic study on the complex aerobic granular sludge microbiome obtained from different wastewater treatment plants. Thereby, we demonstrate the different views that can be obtained on the central nutrient-removing organisms depending on the omic approach and reference sequence databases. Furthermore, we demonstrate a homogenized Genome Taxonomy Database (GTDB) that subsequently enables a more accurate interpretation of data from different omics approaches. Ultimately, our systematic study underscores the importance of metaproteomics in the characterization of complex microbiomes; and the necessity of accurate reference sequence databases to improve the comparison between approaches and accuracy in scientific reporting.

systems biology↗

Metagenomic profiling and transfer dynamics of antibiotic resistance determinants in a full-scale granular sludge wastewater treatment plant

In the One Health context, wastewater treatment plants (WWTPs) are central to safeguard water resources. Nonetheless, many questions remain about their effectiveness to prevent the dissemination of antimicrobial resistance (AMR). Most surveillance studies monitor the levels and removal of selected antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) in intracellular DNA (iDNA) extracted from WWTP influents and effluents. The role of extracellular free DNA (exDNA) in wastewater is mostly overlooked. In this study, we analyzed the transfer of ARGs and MGEs in a full-scale Nereda(R) reactor removing nutrients with aerobic granular sludge. We tracked the composition and fate of the iDNA and exDNA pools of influent, sludge, and effluent samples. Metagenomics was used to profile the microbiome, resistome, and mobilome signatures of iDNA and exDNA extracts. Selected ARGs and MGEs were analyzed by qPCR. From 2,840 ARGs identified, the genes arr-3 (2%), tetC (1.6%), sul1 (1.5%), oqxB (1.2%), and aph(3")-Ib (1.2%) were the most abundant among all sampling points and bioaggregates. Pseudomonas, Acinetobacter, Aeromonas, Acidovorax, Rhodoferax, and Streptomyces populations were the main hosts of ARGs in the sludge. In the effluent, 478 resistance determinants were detected, of which 89% from exDNA potentially released by cell lysis during aeration in the reactor. MGEs and multiple ARGs were co-localized on the same extracellular genetic contigs. These can pose a risk for AMR dissemination by transformation into microorganisms of receiving water bodies. Total intracellular ARGs decreased 3-42% as a result of wastewater treatment. However, the ermB and sul1 genes increased by 2 and 1 log gene copies mL-1, respectively, in exDNA from influent to effluent. The exDNA fractions need to be considered in AMR surveillance, risk assessment, and mitigation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/482492v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1a5eedcorg.highwire.dtl.DTLVardef@e4da78org.highwire.dtl.DTLVardef@c324bforg.highwire.dtl.DTLVardef@1a18138_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA DNA database from an AGS reactor was constructed to study the system resistome, mobilome, and microbiome. C_LIO_LIThe genera Pseudomonas and Rhodoferax were the predominant ARG carriers in the system. C_LIO_LIMGEs and ARGs often co-localize on contigs recovered from the exDNA of the effluent. C_LIO_LIAGS plants are efficient at reducing ARB. C_LIO_LIThe exDNA is an underestimated DNA fraction containing ARGs in the effluent. C_LI

bioengineering↗

Quantitative profiling of microbial communities by de novo metaproteomics

Metaproteomics has emerged as one of the most promising approaches for determining the composition and metabolic functions of complete microbial communities. Conventional metaproteomics approaches however, rely on the construction of protein sequence databases and efficient peptide-spectrum matching algorithms. Thereby, very large sequence databases impact on computational efforts and sensitivity. More recently, advanced de novo sequencing strategies--which annotate peptide sequences without the requirement for a database--have become (again) increasingly proposed for proteomics applications. Such approaches would vastly expand many metaproteomics applications by enabling rapid community profiling and by capturing unsequenced community members, which otherwise remain inaccessible for further interpretation. Nevertheless, because of the lack of efficient pipelines and validation procedures, those strategies have only rarely been employed for community proteomics. Here we report on a newly established de novo metaproteomics pipeline which was evaluated for its quantitative performance using synthetic and natural communities. Additionally, we introduce a novel validation strategy and investigate the actual content of community members within community proteomics data.

systems biology↗

Rapid SARS-CoV-2 whole genome sequencing for informed public health decision making in the Netherlands

SARS-CoV-2 is a novel coronavirus that has rapidly spread across the globe. In the Netherlands, the first case of SARS-CoV-2 has been notified on the 27th of February. Here, we describe the first three weeks of the SARS-CoV-2 outbreak in the Netherlands, which started with several different introductory events from Italy, Austria, Germany and France followed by local amplification in, and later also, outside the South of the Netherlands. The timely generation of whole genome sequences combined with epidemiological investigations facilitated early decision making in an attempt to control local transmission of SARS-CoV-2 in the Netherlands.

genomics↗