Biology subjects

Blom, J.

Publications and source records attributed to Blom, J..

11 recordsLinked to original sources

bioRxiv2026

The insecticidal potential of Bacillus cereus group strains from insect-dense regions of the United Kingdom

Entomopathogenic Bacillus cereus group members (e.g. B. thuringiensis) are arguably the most important source of biopesticides globally and are widely used for industrial-scale crop protection. However, the application of biopesticidal B. cereus group strains is currently threatened by increasing resistance among insects, necessitating the development of novel insecticides. Here, we used whole-genome sequencing to characterize 13 novel B. cereus group strains from sites with high-density insect populations, including six isolates from an insect cadaver. Overall, diverse B. cereus group members were observed, encompassing three panC groups (II, IV and VI) and seven sequence types. Five strains possessed insecticidal Cry toxin-encoding genes with predicted target ranges that included insect species present at the respective sampling locations. Moreover, the genomes were computationally mined for biosynthetic gene clusters (BGCs; clusters of genes governing secondary metabolite synthesis). In total, 274 BGCs were observed, of which the majority (170 BGCs; 62.04%) did not cluster with known BGCs. Taken together, our study indicates that sampling B. cereus group bacteria from insect-rich ecological niches may yield Cry toxins against the self-same insects, as well as novel and unexplored BGCs, suggesting that targeted sampling efforts could generate compound leads for biopesticide development.

microbiology↗

bioRxiv2026

Predicted Bacterial uRBSs Reveal Translational Coupling and Ribosome Mediated RBS Occlusion as Gene-Controlling Mechanisms

Upstream open reading frames (uORFs) in the 5' leader of bacterial mRNAs can modulate gene expression, yet genome-wide identification remains limited. We combined bioinformatic prediction of ribosome-binding sites (RBSs) - a Shine-Dalgarno sequence and a start codon - with experimental validation to uncover new uORFs in Sinorhizobium meliloti 2011. From totally 1106 predicted upstream RBSs (uRBSs), we first examined 15 candidates using eGFP reporters and integrating existing RNA-seq and Ribo-seq data. Translation was detected at 13 sites, with fluorescence intensity broadly correlating with predicted initiation rates. Two uRBSs correspond to gene start sites, thereby refining gene annotations. In nine cases, uRBS mutations affected downstream gene expression in reporter fusions. Among others, the data suggests that a Type I secretion system operon, the RNA chaperone gene hfq, and metabolic genes are regulated by uORFs. Four uORFs acted through translational coupling. We also identified uRBSs that were ribosome-occupied yet (nearly) silent in eGFP assays, and closely spaced to the downstream main RBS (mRBS). These uRBSs probably mediate ribosomal occlusion downregulating lacR and SM2011_RS36230. A re-screen of the prediction set revealed 335 close uRBS/mRBS pairs. Three of them were analyzed, supporting the proposed ribosomal occlusion mechanism for SM2011_RS03630 and SM2011_RS22110, while for glnK translational coupling to an uORF was suggested. These results indicate that uORFs are more widespread in bacteria than previously recognized and suggest that direct ribosomal occlusion of the mRBS is a novel mechanism for down-regulating protein synthesis.

molecular biology↗

bioRxiv2025

Large-scale insights into the biosynthetic potential of the Bacillus cereus group

Bacterial secondary metabolites (SMs) are a critical source of natural product-derived drugs. However, SM discovery efforts have focused overwhelmingly on Actinomycetes, potentially overlooking other key producers. Here, we explore the biosynthetic potential of the Bacillus cereus group, an underexplored complex of SM producers. Using a combined rule- and machine learning-based approach, we mine an unprecedented number of B. cereus group genomes (n = 9,744) for SM-producing biosynthetic gene clusters (BGCs; n = 200,196). Notably, 158,678 B. cereus group BGCs (78.2%) did not cluster with previously described BGCs, suggesting new chemical scaffolds to be explored. B. pseudomycoides was particularly prolific in terms of its SM production potential (30.8 BGC families/genome, Kruskal-Wallis p < 0.0001), and we identify a previously uncharacterized, B. pseudomycoides-unique peptide. Overall, our study represents the largest survey of B. cereus group biosynthetic potential to date and posits the complex as an under-queried SM resource.

microbiology↗

bioRxiv2025

Scalable and interpretable secretion system annotation with Sismis

Secretion systems play critical roles in bacterial growth, survival, and pathogenesis. Genes encoding secretion system components often co-occur together as gene clusters in bacterial (meta)genomes. However, existing tools for secretion system annotation are unable to utilize genomic context to make predictions and are unable to detect secretion systems of novel architecture. Here, we present Sismis (secretion system discovery tool; https://github.com/lmc297/Sismis), a scalable, interpretable, machine learning-based tool, which detects and classifies single-locus secretion systems in bacterial (meta)genomes with high accuracy (test set area-under-the-curve [AUC] values of 0.71 and 0.92 for precision-recall [PR] and receiver operating characteristic [ROC] curves, respectively). When applied to {approx}700k prokaryotic (meta)genomes, Sismis identifies 747, 439 total secretion systems comprising 15, 612 major secretion system families, >80% of which contain no previously known/annotated secretion systems. To facilitate further exploration of these data, we present the Sismis Atlas (https://sismis.microbe.dev/), an interactive secretion system database, which we use to identify a largely uncharacterized cluster of secretion systems with tight adherence (Tad) pili-like characteristics. Altogether, Sismis and its companion atlas enable accurate and interpretable secretion system annotation, exploration, and discovery at an unprecedented scale. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/675188v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@89dec2org.highwire.dtl.DTLVardef@17fa652org.highwire.dtl.DTLVardef@18064b9org.highwire.dtl.DTLVardef@54deaa_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Fast, flexible gene cluster family delineation with IGUA

Prokaryotic genomes harbor a variety of functional elements encoded as contiguous multi-gene clusters, with biosynthetic gene clusters (BGCs, genetic determinants of secondary metabolite biosynthesis) serving as a notable example. In a typical workflow, BGCs are clustered into Gene Cluster Families (GCFs), units that group BGCs encoding similar biosynthetic pathways together. However, existing methods cannot readily scale to massive datasets and cannot be used for GCF delineation tasks beyond BGC clustering. Here, we present IGUA (Iterative Gene clUster Analysis; https://github.com/zellerlab/IGUA), a scalable, flexible GCF delineation method for genomic segments with multi-gene architectures. On a BGC clustering task, IGUA is [≥]10x faster than the state-of-the-art (BiG-SCAPE/BiG-SLiCE), without sacrificing accuracy. To highlight its scalability, we use IGUA to cluster >2.8 million BGCs from {approx}1 million prokaryotic genomes in <18 hours (n = 2,829,071 BGCs to 56,960 GCFs). To showcase its utility beyond BGC clustering, we use IGUA to cluster (i) secretion systems and (ii) prophages into GCFs (n = 10,576 and 356,776 gene clusters to 2,744 and 213,699 GCFs, respectively). Overall, IGUA represents a versatile GCF delineation tool with unmatched computational efficiency and flexibility, enabling (meta)genomic mining applications at unprecedented scales. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/654203v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1f27216org.highwire.dtl.DTLVardef@203ccborg.highwire.dtl.DTLVardef@7766c8org.highwire.dtl.DTLVardef@fcd4b5_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2023

Interpretable Machine Learning Decodes Soil Microbiome's Response to Drought Stress

BackgroundExtreme weather events induced by climate change, particularly droughts, have detrimental consequences for crop yields and food security. Concurrently, these conditions provoke substantial changes in the soil metagenome and affect plant health. Early recognition of soil affected by drought enables farmers to implement appropriate agricultural management practices. In this context, interpretable Machine Learning holds immense potential for drought stress classification in the soil metagenome based on marker taxa. ResultsThis study demonstrates that the metagenomic approach of Differential Abundance Analysis methods and Machine Learning-based Shapley Additive Explanation values provide similar information. They exhibit their potential as complementary approaches for identifying marker taxa and investigating their enrichment or depletion under drought stress in grass lineages. Additionally, the Random Forest Classifier trained on a diverse range of relative abundance data from the soil metagenome of various plant species achieves a high accuracy of 92.3 % at the genus rank for drought stress prediction. It demonstrates its generalization capacity for the lineages tested. ConclusionsIn the detection of drought stress in the soil metagenome, this study emphasizes the potential of an optimized and generalized location-based ML classifier. By identifying marker taxa, this approach holds promising implications for microbe-assisted plant breeding programs and contributes to the development of sustainable agriculture practices. These findings are crucial for preserving global food security in the face of climate change.

bioinformatics↗

bioRxiv2021

Bakta: Rapid & standardized annotation of bacterial genomes via alignment-free sequence identification

Command line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command line software pipelines heavily depend on taxon specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command line software tool for the robust, taxon-independent, thorough and nonetheless fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross references. Annotation results are exported in GFF3 and INSDC-compliant flat files as well as comprehensive JSON files facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references whilst providing comparable wall clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://github.com/oschwengers/bakta. An accompanying web version is available at https://bakta.computational.bio.

bioinformatics↗

bioRxiv2021

Phylogenetic study of thermophilic genera Anoxybacillus, Geobacillus, Parageobacillus, and proposal of a new classification Quasigeobacillus gen. nov.

A phylogenetic study of Anoxybacillus, Geobacillus and Parageobacillus was performed using publicly available whole genome sequences. A total of 113 genomes were selected for phylogenomic metrics including calculation of Average Nucleotide Identity (ANI) and Average Amino acid Identity (AAI), and a maximum likelihood tree was built from alignment of a set of 662 orthologous core genes. The combined results from the core gene tree and ANI and AAI dendrograms show that the genomes split into two main clades, clade I containing all Geobacillus, all Parageobacillus and some species of Anoxybacillus, and clade II, containing the majority of Anoxybacillus species. Clade I is further partitioned into three clades, consisting separately of Geobacillus, Parageobacillus, and a third clade which we suggest should be elevated to a new genus Quasigeobacillus gen. nov. Two species of Anoxybacillus showed inconsistent positioning among the trees produced by differing methods and could not be clearly resolved into any of the three existing genera or the new genus. This research shows the importance of considering closely related genera together when studying phylogeny or assigning genomic affinities.

microbiology↗

bioRxiv2020

Cryptosporulation in Kurthia spp. forces a rethinking of asporogenesis in Firmicutes

Sporulation is a complex morphophysiological process resulting in a cellular structure that is more resistant than the vegetative form. In Firmicutes, this structure is produced within the mother cell, and is called an endospore. Endospore formation is thought to have evolved in the common ancestor of Firmicutes. However, sporulation has apparently been lost in some extant lineages that are defined as asporogenic. We isolated strain 11kri321, a representative of the genus Kurthia, from an oligotrophic geothermal reservoir. While Kurthia spp. is considered to comprise only asporogenic species, strain 11kri321 produced spores. Genomic reconstruction of the sporulation pathway shows elements typical of sporulation in Bacilli, including the signaling for sporulation onset. However, key genes were missing, including those involved in engulfment and dipicolinic acid synthesis. Based on the results for strain 11kri321, sporulation was investigated in other Kurthia strains. Genes involved in signaling, cell division and spore coat formation were detected in three available Kurthia genomes. Moreover, endosporulation was clearly visualized in at least two of the four strains tested. These results show that Kurthia is an endospore-forming Firmicute lineage. However, the genetic background of sporulation in this genus deviates from the known sporulation pathway in Firmicutes and even within Bacilli, suggesting that a revision of the minimal set of genes used for genomic detection of sporulation is required. Based on our findings we propose the term cryptosporulant to refer to putative asporogenic Firmicutes for which a detailed genomic and physiological characterization of sporulating is missing. ImportanceEndospore-forming Firmicutes include many environmental and medical relevant bacterial clades. In these microorganisms, the ability to produce endospores is essential for survival in the environment and even for pathogenesis. The minimum core of genes required to produce a viable and resistant spore, the distinction between endospore-forming and asporogenic groups, as well as the evolution of sporulation have been a subject of investigation and debate for decades. Here, we demonstrate endosporulation in the genus Kurthia, considered as asporogenic. Morphological, physiological and genomic analyses were undertaken to demonstrate that sporulation is not lost within this lineage. Based on our results we propose a re-examination of the minimal genetic requirements of sporulation and the use of the term cryptosporulant to describe lineages of Firmicutes that have not previously been observed to sporulate, but for which a detailed analysis is still missing.

microbiology↗

bioRxiv2019

Comparative genomic analyses reveal diverse virulence factors and antimicrobial resistance mechanisms in clinical Elizabethkingia meningoseptica strains

Three human clinical isolates of bacteria (designated strains Em1, Em2 and Em3) had high average nucleotide identity (ANI) to Elizabethkingia meningoseptica. Their genome sizes (3.89, 4.04 and 4.04 Mb) were comparable to those of other Elizabethkingia species and strains, and exhibited open pan-genome characteristics, with two strains being nearly identical and the third divergent. These strains were susceptible only to trimethoprim/sulfamethoxazole and ciprofloxacin amongst 16 antibiotics in minimum inhibitory tests. The resistome exhibited a high diversity of resistance genes, including 5 different lactamase- and 18 efflux protein-encoding genes. Forty-four genes encoding virulence factors were conserved among the strains. Sialic acid transporters and curli synthesis genes were well conserved in E. meningoseptica but absent in E. anophelis and E. miricola. E. meningoseptica carried several genes contributing to biofilm formation. 58 glycoside hydrolases (GH) and 25 putative polysaccharide utilization loci (PULs) were found. The strains carried numerous genes encoding two-component system proteins (56), transcription factor proteins (187~191), and DNA-binding proteins (6~7). Several prophages and CRISPR/Cas elements were uniquely present in the genomes.

microbiology↗

bioRxiv2018

The ‘zoo’ accompanying Botryococcus braunii: Unraveling the fundamentals of algae-bacteria biocoenosis

Bacteria occupy all major ecosystems and maintain an intensive relationship to the eukaryotes, developing together into complex biomes (i.e., phycosphere and rhizosphere). Interactions between eukaryotes and bacteria range from cooperative to competitive, with the associated microorganisms affecting their hosts development, growth, health and disease. Since the advent of non-culture dependent analytical techniques such as metagenome sequencing, consortia have been described but owing to the complex interactions rarely functionally dissected. Multifaceted analysis of the microbial consortium of the ancient phytoplankton Botryococcus as an attractive model food web revealed that its all abundant bacterial members belong to a distinct niche of biotin auxotrophs, essentially depending on the microalga. In addition, hydrocarbonoclastic bacteria without vitamin auxotrophies, which adversely affect the algal cell morphology, appear evidently decimated. Synthetic rearrangement of a minimal community consisting of alga, mutualistic and parasitic bacteria underpins the model of a eukaryote that domesticates its own mutualistic bacterial "zoo" to manipulate and control its surrounding biosphere. This model of domestication of mutualistic bacteria for the defense against destruents by a eukaryotic host could represent ecologically relevant interactions that cross species boundaries. Metabolic and system reconstruction disentangles the relationships and provide a blueprint for the construction of mutually beneficial synthetic ecosystems.

microbiology↗