Biology subjects

den Bakker, H. C.

Publications and source records attributed to den Bakker, H. C..

4 recordsLinked to original sources

bioRxiv2025

Metagenomic Profiling of Bacterial (16S) and Fungal (ITS) Communities on D'Anjou Pears during Long-Term Controlled Atmosphere Storage

DAnjou pears are routinely stored for up to nine months under controlled atmosphere (CA) conditions to meet market demands. While this practice maintains fruit quality, limited information exists on pears natural microbiota throughout storage. The objective of this study was to describe fungal and bacterial composition on marketable and unmarketable conventional, whole, intact pears under two storage practices (bulk vs wrapped) at 3, 6, and 9 months in long-term CA cold storage. Storage practices had a significant effect on the composition and succession of both fungal and bacterial communities. Overall, fungal communities exhibited lower estimated Chao1 alpha diversity (mean 18.3) compared to bacterial communities (mean 166.4). No significant differences in Chao1 index were found between the bacterial and fungal communities on marketable or unmarketable pears. Trends in Chao1 indices of fungal and bacterial communities peaked at mid-storage and declined by 9 months, with wrapped pears showing parallel trends and bulk pears exhibiting a sharper late-stage reduction. No distinct clusters could be found for 3- and 6-month fungal communities, irrespective of marketability or being bulk or wrapped. The principal coordinate analysis of the bacterial communities showed tight clustering by time point for the individually wrapped pears, irrespective of their marketability. Bacterial communities included genera common in food-processing and plant environments, such as Pseudomonas and Acinetobacter. Fungal communities shifted over time, with spoilage-associated genera like Aureobasidium, Penicillium, Botrytis, and Mucor present at different storage stages. SignificanceThis study highlights the influence of storage duration and packaging on microbial succession, establishing initial benchmarks of pear surface microbiomes. The observed lack of significant differences in microbial diversity between marketable and unmarketable pears suggests that these baseline community profiles can serve as critical reference points for identifying other influential factors. Variables such as handling practices may exert a more direct effect on microbial dynamics and, consequently, product quality. Establishing these baselines is essential because they provide a foundation for detecting deviations linked to spoilage or safety risks. Moreover, understanding these patterns can guide the development of targeted microbial control strategies in postharvest systems, enabling interventions that maintain fruit quality, reduce losses, and improve food safety throughout the supply chain.

microbiology↗

bioRxiv2023

Fasten with Pipes

Fasten is a versatile bioinformatics tool suite developed to address gaps in the manipulation of sequence data files in the fastq format. Existing tools often lack support for interleaved fastq files and Unix-style pipe file control. Fasten provides a solution by allowing bioinformaticians to efficiently work with paired-end sequence data, facilitating data transformation, and offering competitive speeds. This suite, implemented in Rust, offers a comprehensive manual, continuous integration, and seamless integration into the command line with Unix pipes. Fasten is poised to become an invaluable resource for routine command-line bioinformatics tasks, enhancing the accessibility and flexibility of data processing in the field.

bioinformatics↗

bioRxiv2022

Phenotypic characterization and analysis of complete genomes of two distinct strains of the proposed species "L. swaminathanii"

Recently, a new Listeria species, "Listeria swaminathanii", was proposed. Here, we phenotypically and genotypically characterize two additional strains that were previously obtained from soil samples and compare the results to the type strain. Complete genomes for both strains were assembled from hybrid Illumina and Nanopore sequencing reads and annotated. Further genomic analysis including average nucleotide identity (ANI) and detection of mobile genetic elements and genes of interest (e.g., virulence-associated) were conducted. The strains showed 98.7-98.8% ANI with the type strain. The UTK C1-0015 genome contained a partial monocin locus and a plasmid while the UTK C1-0024 genome contained a full monocin locus and a prophage. Phenotypic characterization consistent with those performed on the proposed type strain was conducted to assess consistency of phenotypes across a greater diversity of the proposed species (n=3 instead of n=1). Only a few findings were notably different from those of the type strain, such as catalase activity, glycerol metabolism, starch metabolism, and growth at 41{degrees}C. This study further expands our understanding of this newly proposed sensu stricto Listeria species.

microbiology↗

bioRxiv2020

High-resolution genomic comparisons within Salmonella enterica serotypes derived from beef feedlot cattle: parsing the roles of cattle source, pen, animal, sample type and production period

Salmonella enterica is a major foodborne pathogen, and contaminated beef products have been identified as the primary source of Salmonella-related outbreaks. Pathogenicity and antibiotic resistance of Salmonella are highly serotype- and subpopulation-specific, which makes it essential to understand high-resolution Salmonella population dynamics in cattle. Time of year, source of cattle, pen, and sample type(i.e., feces, hide or lymph nodes) have previously been identified as important factors influencing the serotype distribution of Salmonella (e.g., Anatum, Lubbock, Cerro, Montevideo, Kentucky, Newport, and Norwich) that were isolated from a longitudinal sampling design in a research feedlot. In this study, we performed high-resolution genomic comparisons of Salmonella isolates within each serotype using both single-nucleotide polymorphism (SNP)-based maximum likelihood phylogeny and hierarchical clustering of core-genome multi-locus sequence typing. The importance of the aforementioned features on clonal Salmonella expansion was further explored using a supervised machine learning algorithm. In addition, we identified and compared the resistance genes, plasmids, and pathogenicity island profiles of the isolates within each sub-population. Our findings indicate that clonal expansion of Salmonella strains in cattle was mainly influenced by the randomization of block and pen, as well as the origin/source of the cattle; that is, regardless of sampling time and sample type (i.e., feces, lymph node or hide). Further research is needed concerning the role of the feedlot pen environment prior to cattle placement to better understand carry-over contributions of existing strains of Salmonella and their bacteriophages. ImportanceSalmonella serotypes isolated from outbreaks in humans can also be found in beef cattle and feedlots. Virulence factors and antibiotic resistance are among the primary defense mechanisms of Salmonella, and are often associated with clonal expansion. This makes understanding the subpopulation dynamics of Salmonella in cattle critical for effective mitigation. There remains a gap in the literature concerning subpopulation dynamics within Salmonella serotypes in feedlot cattle from the beginning of feeding up until slaughter. Here, we explore Salmonella population dynamics within each serotype using core genome phylogeny and hierarchical classifications. We used machine-learning to quantitatively parse the relative importance of both hierarchical and longitudinal clustering among cattle host samples. Our results reveal that Salmonella populations in cattle are highly clonal over a 6-month study period, and that clonal dissemination of Salmonella in cattle is mainly influenced spatially by experimental block and pen, as well by the geographical origin of the cattle.

microbiology↗