Biology subjects

Van Leuven, J. T.

Publications and source records attributed to Van Leuven, J. T..

13 recordsLinked to original sources

bioRxiv2026

Propidium monoazide (PMA) with quantitative PCR to detect and quantify viable Paenibacillus larvae and Melissococcus plutonius in honeybee hive samples

Paenibacillus larvae and Melissococcus plutonius are the bacterial agents responsible for American and European foulbrood diseases, respectively, and pose significant economic threats to apiculture worldwide. Early detection of these pathogens is critical for effective disease prevention and management in honeybee colonies. P. larvae forms highly persistent spores that can remain infectious on hive equipment for decades, whereas the non-spore-forming M. plutonius can survive for over a year in contaminated materials. Although various decontamination and treatment strategies are available or under development, reliable methods for quantifying these pathogens are essential for accurately assessing their effectiveness. Culture-based techniques and quantitative PCR (qPCR) are commonly used to detect and quantify foulbrood pathogens in hive-associated samples; however, culturing is labor-intensive and sometimes inconsistent, while qPCR does not distinguish between viable and dead cells. Propidium monoazide (PMA) selectively binds DNA from dead cells and prevents its amplification during qPCR, enabling viable-cell quantification. Despite this advantage, the performance of PMA-qPCR for detecting P. larvae and M. plutonius in hive samples has not previously been assessed. In this study, we evaluated PMA-qPCR using both pure cultures and environmentally relevant honeycomb samples before and after ozone treatment. PMA treatment greatly reduced the erroneous detection of dead cells by several orders of magnitude in both culture and hive samples, supporting its utility for AFB and EFB risk assessment and treatment evaluation. However, incomplete suppression of dead-cell DNA at high cell densities indicates that further optimization of PMA treatment conditions may be necessary.

microbiology↗

bioRxiv2025

Hive-associated bacteria improve honeybee survival during Paenibacillus larvae infection

Honeybees (Apis mellifera L.) are the most common pollinators of crops. Honeybee larvae are susceptible to Paenibacillus larvae, a spore-forming Gram-positive bacterium that causes American Foulbrood (AFB), one of the most destructive brood diseases worldwide. Existing antibiotic treatments are undesirable due to increasing pathogen resistance and their residual accumulation in bee products. Consequently, there is increasing interest in biological agents and natural strategies for AFB control. However, most studies remain limited to in vitro or in vivo experiments and rarely evaluate impacts on adult bees. In this study, we systematically investigated hive-associated bacteria for their potential to enhance larval survival during P. larvae infection. Bacteria isolated from AFB-infected combs were sequenced and screened for antagonistic activity. Several Bacillus species--including B. zhangzhouensis, B. subtilis, B. amyloliquefaciens, B. licheniformis, and B. mojavensis--inhibited one or more P. larvae strains. Notably, the lysate of B. licheniformis suppressed all tested strains; Further characterization revealed that its main antibacterial component consists of heat-stable proteins between 30-50 kDa. Two Bacillus strains were selected for larval infection assays using laboratory-reared honeybee larvae: both significantly improved survival by 42% and 71%, respectively. To evaluate potential effects on adult bees, newly emerged workers were caged and fed B. licheniformis ASx lysate. Their survival differed from that of untreated controls but remained comparable to the Terra-Pro-fed bees, a Terramycin-based AFB treatment, and their gut microbiome remained similar to that of untreated controls. Overall, our findings suggest that hive-associated Bacillus species offer promising, low-impact candidates for AFB disease management.

microbiology↗

bioRxiv2025

{Phi}X174 bacteriophage viability predicted by protein biophysical modeling

The relationship between genotype and phenotype underlies our ability to understand and predict evolution. Efforts to build genotype-phenotype (GP) maps have revealed several unifying rules: epistasis is pervasive, fitness effects are not normally distributed, and the GP map is non-linear and complicated for high-level phenotypes. A critical step in developing GP maps is evaluating how well predictive models do in explaining observed phenotypes. We utilize the simplicity of a bacteriophage ({Phi}X174) study system to test if an intermediate phenotype (predicted stability of the G capsid protein) explains more complex phenotypes. In doing so, we compare the predictive performance of free energies of folding and binding obtained using numerous molecular modeling methods as well as phylogenetic and basic biochemical/biophysical properties of amino acid substitutions. By creating a large mutational library, we find that {Phi}X174 tolerates about 50% of the amino acid substitutions we inserted into the G protein and that molecular modeling compliments other substitution models for predicting viability. Mutations predicted to have large destabilizing effects are especially informative and are almost universally detrimental. These large-effect substitutions often coincide with the most conserved residues in the G protein. Apart from large-effect mutations, our ability to predict {Phi}X174 phenotypes is fairly poor and we explore various potential confounding factors (e.g., codon bias) that could be considered to improve viability predictions.

molecular biology↗

bioRxiv2025

Bacteriophage density influences the rate of resistance evolution

The antagonistic relationship between bacteria and bacteriophages (phages) drives genetic changes that result in phage resistance. Phage resistance mutations arise in natural microbial communities and during the treatment of diseases with phages (phage therapy), making it important to understand the dynamics of resistance acquisition. It is well-established that when bacteria are challenged with phages in dense liquid cultures, bacterial populations quickly become dominated by phage-resistant variants. However, these conditions--well-mixed liquid cultures with high phage concentrations--are not necessarily common in microbial ecosystems. We developed a simplified mathematical model of phage resistance evolution to explore how phage and host concentration impact the dynamics of resistance evolution. The model was parameterized with microbial growth data from two pathogens and their phages: Pseudomonas aeruginosa and Paenibacillus larvae. Our analyses revealed two fundamental discoveries about resistance evolution. First, phage resistance evolution is predictably governed by a core set of parameters that exhibited high resolution across all bacterial strains: intrinsic growth rate of susceptible bacteria, resistance acquisition rate, fitness cost of resistance, and phage adsorption rate. Second, competitive interactions and fitness costs are the primary drivers of resistance patterns rather than intrinsic mutation rates. We observed three distinct growth patterns--delayed growth, two phase growth, and complete suppression--corresponding to specific parameter regimes as initial phage concentration increased. Two phase growth patterns emerged when competitive dynamics remained balanced, enabling coexistence of susceptible and resistant populations. Complete suppression patterns occurred when low proliferation thresholds combined with extreme competitive asymmetries created unsustainable conditions for resistant bacteria. These findings demonstrate that phage resistance evolution is fundamentally an ecological process where competitive context determines outcomes independently of mutation capacity, with important implications for phage therapy design.

evolutionary biology↗

bioRxiv2025

Modeling the Relationship between the Capsid Spike Protein Stability and Fitness in {varphi}X174 Bacteriophage

BackgroundProtein function depends on the stable folding or binding of peptide chains, and the extent to which an amino acid substitution disrupts this stability can be a strong predictor of the mutations impact on the proteins function and the organisms fitness. This study seeks to understand this relationship in bacteriophage {phi}X174 using an experimental technique of deep mutational scanning and computationally predicted protein stability. ResultsAnalyzing the viability data using a newly developed multistage binomial model confirms that highly destabilizing mutations predict inviability. For single-site variants, the model predicts that {Delta}{Delta}G of folding greater than ~3 kcal/mol and {Delta}{Delta}G of binding greater than ~6 kcal/mol cuts the probability of survival by half of the maximum. The maximum probability, even for minimal {Delta}{Delta}G values, plateaus at around 87%, reflecting the influence of unobserved factors. Fitting of double-site variants data shows similar results. In contrast, a linear regression analysis of viable mutants reveals that the effect of protein stability is too weak to be a reliable predictor of fitness. ConclusionIn this study, we introduce a novel modeling technique to explore the relationship between protein stability and survival outcomes. While large destabilization often indicates inviability, most destabilizing mutations exert only small to moderate effects and do not reliably predict survival. Although protein stability is a crucial biophysical property influencing biological systems, it represents just one of multiple factors that contribute to fitness and survival.

bioinformatics↗

bioRxiv2024

Directed evolution of bacteriophages: impacts of prolific prophage

Various directed evolution methods exist that seek to procure bacteriophages with expanded host ranges, typically targeting phage-resistant or non-permissive bacterial hosts. The general premise of these methods is to propagate phage on multiple bacterial hosts, pool the lysate, and repeat the propagation process until phage(s) can form plaques on the target host(s). In theory, this propagation process produces a phage lysate that contains input phages and their evolved phage progeny. However, in practice, this phage lysate can also include prophages originating from bacterial hosts. Here we describe our experience implementing one directed evolution method, the Appelmans protocol, to study phage evolution in the Pseudomonas aeruginosa phage-host system, in which we observed rapid host-range expansion of the phage cocktail. Further experimentation and sequencing analysis revealed that this observed host-range expansion was due to a Casadabanvirus prophage that originated from one of the Appelmans hosts. Host-range analysis of the prophage showed that it could infect five of eight bacterial hosts initially used, allowing it to proliferate and persist through the end of the experiment. This prophage was represented in half of the sequenced phage samples isolated from the Appelmans experiment. This work highlights the impact of prophages in directed evolution experiments and the importance of incorporating sequencing data in analyses to verify output phages, particularly for those attempting to procure phages intended for phage therapy applications. This study also notes the usefulness of intraspecies antagonism assays between bacterial host strains to establish a baseline for inhibitory activity and determine presence of prophage. IMPORTANCEDirected evolution is a common strategy for evolving phages to expand host range, often targeting pathogenic strains of bacteria. In this study we investigated phage host-range expansion using directed evolution in the Pseudomonas aeruginosa system. We show that prophage are active players in directed evolution and can contribute to observation of host-range expansion. Since prophage are prevalent in bacterial hosts, particularly pathogenic strains of bacteria, and all directed evolution approaches involve iteratively propagating phage on one or more bacterial hosts, the presence of prophage in phage preparations is a factor that needs to be considered in experimental design and interpretation of results. These results highlight the importance of screening for prophages either genetically or through intraspecies antagonism assays during selection of bacterial strains and will contribute to improving experimental design of future directed evolution studies.

microbiology↗

bioRxiv2021

Global composition of the bacteriophage community in honeybees

The microbial communities in animal digestive systems are critical to host development and health. These assemblages of primarily viruses, bacteria, and fungi stimulate the immune system during development, synthesize important chemical compounds like hormones, aid in digestion, competitively exclude pathogens, etc. The bacteriophages in animal microbiomes are harder to characterize than the bacterial or fungal components of the microbiome and thus we know comparatively little about the temporal and spatial dynamics of bacteriophage communities in animal digestive systems. Recently, the bacteriophages of the honeybee gut were characterized in two European bee populations. Most of the bacteriophages described in these two reports were novel, encoded many metabolic genes in their genomes, and had a community structure that suggests coevolution with their bacterial hosts. To describe the conservation of bacteriophages in bees and begin to understand their role in the bee microbiome, we sequenced the virome of Apis mellifera from Austin, Texas and compared bacteriophage composition between three locations around the world. We found that the majority of bacteriophages from Austin are novel, sharing no sequence similarity to anything in public repositories. However, many bacteriophages are shared among the three bee viromes, indicating specialization of bacteriophages in the bee gut. Our study along with the two previous bee virome studies shows that the bee gut bacteriophage community is simple compared to that of many animals, consisting of several hundred types of bacteriophages that primarily infect four of the dominant bacterial phylotypes in the bee gut.

microbiology↗

bioRxiv2020

Rhinovirus reduces the severity of subsequent respiratory viral infections, which is associated with dampened inflammatory responses

Coinfection by unrelated viruses in the respiratory tract is common and can result in changes in disease severity compared to infection by individual virus strains. We have previously shown that inoculation of mice with rhinovirus (RV) two days prior to inoculation with a lethal dose of influenza A virus (PR8), provides complete protection against mortality and reduces morbidity. In this study, we extended that finding to a second lethal respiratory virus, pneumonia virus of mice (PVM) and analyzed potential mechanisms whereby RV reduces lethal viral pneumonia caused by PR8 and PVM. RV prevented mortality and weight loss associated with PVM infection, suggesting that RV-mediated protection is more effective against PVM than PR8. Major changes in host gene expression upon PVM infection were delayed compared to PR8, which likely provides a larger time frame for RV-induced gene expression to alter the course of disease. Overall, RV induced earlier recruitment of inflammatory cells, while these populations were reduced at later times in RV-inoculated mice. Findings common to both virus pairs included upregulated expression of mucin-associated genes and dampening of inflammation-related genes in mice that were inoculated with RV prior to lethal virus infection. However, type I IFN signaling was required for RV-mediated protection against PR8, but not PVM. IFN signaling had minor effects on PR8 replication and contributed to controlling neutrophilic inflammation and subsequent hemorrhagic lung pathology in RV/PR8 infected mice. These findings, combined with differences in virus replication levels and disease severity, suggest that the suppression of inflammation in RV/PVM infected mice may be due to early, IFN-independent suppression of viral replication, while in RV/PR8 infected mice may be due to IFN-dependent modulation of immune responses. Thus, a mild upper respiratory viral infection can reduce the severity of a subsequent severe viral infection in the lungs through virus-dependent mechanisms. Author SummaryRespiratory viruses from diverse families co-circulate in human populations and are frequently detected within the same host. Though clinical studies suggest that infection by more than one unrelated respiratory virus may alter disease severity, animal models in which we can control the doses, timing, and strains of coinfecting viruses are critical to understand how coinfection affects disease severity. In this study, we compared gene expression and immune cell recruitment between two pairs of viruses (RV/PR8 and RV/PVM) inoculated sequentially in mice that both result in reduced severity compared to lethal infection by PR8 or PVM alone. Reduced disease severity was associated with suppression of inflammatory responses in the lungs. However, differences in disease kinetics and host and viral gene expression suggest that protection by coinfection with RV may be due to distinct molecular mechanisms. Indeed, we found that antiviral cytokine signaling was required for RV-mediated protection against lethal infection by PR8, but not PVM.

microbiology↗

bioRxiv2020

{Phi}X174 Attenuation by Whole Genome Codon Deoptimization

Natural selection acting on synonymous mutations in protein-coding genes influences genome composition and evolution. In viruses, introducing synonymous mutations in genes encoding structural proteins can drastically reduce viral growth, providing a means to generate potent, live attenuated vaccine candidates. However, an improved understanding of what compositional features are under selection and how combinations of synonymous mutations affect viral growth is needed to predictably attenuate viruses and make them resistant to reversion. We systematically recoded all non-overlapping genes of the bacteriophage {Phi}X174 with codons rarely used in its E. coli host. The fitness of recombinant viruses decreases as additional deoptimizing mutations are made to the genome, although not always linearly, and not consistently across genes. Combining deoptimizing mutations may reduce viral fitness more or less than expected from the effect size of the constituent mutations and we point out difficulties in untangling correlated compositional features. We test our model by optimizing the same genes and find that the relationship between codon usage and fitness does not hold for optimization, suggesting that wild-type {Phi}X174 is at a fitness optimum. This work highlights the need to better understand how selection acts on patterns of synonymous codon usage across the genome and provides a convenient system to investigate the genetic determinants of virulence.

genomics↗

bioRxiv2019

Saturation mutagenesis genome engineering of infective {Phi}X174 bacteriophage via unamplified oligo pools and golden gate assembly

Here we present a novel protocol for the construction of saturation single-site--and massive multi-site--mutant libraries of a bacteriophage. We segmented the {Phi}X174 genome into 14 non-toxic and non-replicative fragments compatible with golden gate assembly. We next used nicking mutagenesis with oligonucleotides prepared from unamplified oligo pools with individual segments as templates to prepare near-comprehensive single-site mutagenesis libraries of genes encoding the F capsid protein (421 amino acids scanned) and G spike protein (172 amino acids scanned). Libraries possessed greater than 99% of all 11,860 programmed mutations. Golden Gate cloning was then used to assemble the complete {Phi}X174 mutant genome and generate libraries of infective viruses. This protocol will enable reverse genetics experiments for studying viral evolution and, with some modifications, can be applied for engineering of therapeutically relevant bacteriophages with larger genomes.

genomics↗

bioRxiv2018

Cicada endosymbionts have tRNAs that are correctly processed despite having genomes that do not encode all of the tRNA processing machinery

Gene loss and genome reduction are defining characteristics of nutritional endosymbiotic bacteria. In extreme cases, even essential genes related to core cellular processes such as replication, transcription, and translation are lost from endosymbiont genomes. Computational predictions on the genomes of the two bacterial symbionts of the cicada Diceroprocta semicincta, \"Candidatus Hodgkinia cicadicola\" (Alphaproteobacteria) and \"Ca. Sulcia muelleri\" (Betaproteobacteria), find only 26 and 16 tRNA, and 15 and 10 aminoacyl tRNA synthetase genes, respectively. Furthermore, the original \"Ca. Hodgkinia\" genome annotation is missing several essential genes involved in tRNA processing, such as RNase P and CCA tRNA nucleotidyltransferase, as well as several RNA editing enzymes required for tRNA maturation. How \"Ca. Sulcia\" and \"Ca. Hodgkinia\" preform basic translation-related processes without these genes remains unknown. Here, by sequencing eukaryotic mRNA and total small RNA, we show that the limited tRNA set predicted by computational annotation of \"Ca. Sulcia\" and \"Ca. Hodgkinia\" is likely correct. Furthermore, we show that despite the absence of genes encoding tRNA processing activities in the symbiont genomes, symbiont tRNAs have correctly processed 5 and 3 ends, and seem to undergo nucleotide modification. Surprisingly, we find that most \"Ca. Hodgkinia\"and \"Ca. Sulcia\" tRNAs exist as tRNA halves. Finally, and in contrast with other related insects, we show that cicadas have experienced little horizontal gene transfer that might complement the activities missing from the endosymbiont genomes. We conclude that \"Ca. Sulcia\" and \"Ca. Hodgkinia\" tRNAs likely function in bacterial translation, but require host-encoded enzymes to do so.

evolutionary biology↗

bioRxiv2017

Selecting among three basic fitness landscape models: additive, multiplicative and stickbreaking

Fitness landscapes map genotypes to organismal fitness. Their topography depends on how mutational effects interact-epistasis-and is important for understanding evolutionary processes such as speciation, the rate of adaptation, the advantage of recombination, and predictability versus stochasticity of evolution. The growing amount of empirical data has made it possible to better test landscape models empirically. We argue that this endeavor will benefit from the development and use of meaningful null models against which to compare more complex models. Here we develop statistical and computational methods for fitting fitness data from mutation combinatorial networks to three simple models: additive, multiplicative and stickbreaking. We employ a Bayesian framework for doing model selection. Using simulations, we demonstrate that our methods work and we explore their statistical performance: bias, error, and the power to discriminate among models. We then illustrate our approach and its flexibility by analyzing several previously published datasets. An R-package that implements our methods is available in the CRAN repository under the name Stickbreaker.

evolutionary biology↗

bioRxiv2016

Lung epithelial cells have virus-specific and shared gene expression responses to infection by diverse respiratory viruses

The severity and outcome of respiratory viral infections is partially determined by the cellular response mounted by infected lung epithelial cells. Disease prevention and treatment is dependent on our understanding of the shared and unique responses elicited by diverse viruses, yet few studies compare host responses to different viruses while controlling other experimental parameters. We compared changes in gene expression of murine lung epithelial cells infected individually by three respiratory viruses causing mild (rhinovirus, RV1B), moderate (coronavirus, MHV-1), and severe (influenza A virus, PR8) disease in mice. RV1B infection caused numerous gene expression changes, but the differential effect peaked at 12 hours post-infection. PR8 altered an intermediate number of genes whose expression continued to change through 24 hours. MHV-1 had comparatively few effects on host gene expression. The viruses elicited highly overlapping responses in antiviral genes, though MHV-1 induced a lower type I interferon response than the other two viruses. Signature genes were identified for each virus and included host defense genes for PR8, tissue remodeling genes for RV1B, and transcription factors for MHV-1. Our comparative approach identified universal and specific transcriptional signatures of virus infection that can be used to discover mechanisms of pathogenesis in the respiratory tract.

immunology↗