Fitness Of Mutants Research Articles

A new framework for SubtiWiki, the database for the model organism Bacillus subtilis.

Bacillus subtilis is a Gram-positive model bacterium and one of the most-studied and best understood organisms. The complex information resulting from its investigation is compiled in the database SubtiWiki (https://subtiwiki.uni-goettingen.de/v5) in an integrated and intuitive manner. To enhance the utility of SubtiWiki, we have added novel features such as a viewer to interrogate conserved genomic organization, a widget that shows mutant fitness data for all non-essential genes, and a widget showing protein structures, structure predictions and complex structures. Moreover, we have integrated metabolites as new entities. The new framework also includes a documented API, enabling programmatic access to data for computational tasks. Here we present the recent developments of SubtiWiki and the current state of the data for this organism.

Organismal metabolism regulates the expansion of oncogenic PIK3CA mutant clones in normal esophagus.

Oncogenic PIK3CA mutations generate large clones in aging human esophagus. Here we investigate the behavior of Pik3ca mutant clones in the normal esophageal epithelium of transgenic mice. Expression of a heterozygous Pik3caH1047R mutation drives clonal expansion by tilting cell fate toward proliferation. CRISPR screening and inhibitor treatment of primary esophageal keratinocytes confirmed the PI3K-mTOR pathway increased mutant cell competitive fitness. The antidiabetic drug metformin reduced mutant cell advantage in vivo and in vitro. Conversely, metabolic conditions such as type 1 diabetes or diet-induced obesity enhanced the competitive fitness of Pik3caH1047R cells. Consistently, we found a higher density of PIK3CA gain-of-function mutations in the esophagus of individuals with high body mass index compared with those with normal weight. We conclude that the metabolic environment selectively influences the evolution of the normal epithelial mutational landscape. Clinically feasible interventions to even out signaling imbalances between wild-type and mutant cells may limit the expansion of oncogenic mutants in normal tissues.

HIV broadly neutralizing antibody escapability drives the therapeutic efficacy of vectored immunotherapy.

Broadly neutralizing antibodies (bNAbs) have shown great promise for prevention and treatment of HIV infection. Breadth of bNAb neutralization, measured in vitro across panels of diverse viral isolates, is often used as a predictor of clinical potential. However, recent prevention studies demonstrate that the clinical efficacy of a broad and potent bNAb (VRC01) is undermined by neutralization resistance of circulating strains. Using HIV-infected humanized mice, we find that therapeutic efficacy of bNAbs delivered as Vectored ImmunoTherapy (VIT) is a function of both the fitness cost and resistance benefit of mutations that emerge during viral escape, which we term 'escapability'. Applying this mechanistic framework, we find that the sequence of the envelope V5-loop alters the resistance benefits of mutants that arise during escape, thereby impacting the therapeutic efficacy of VIT-mediated viral suppression. We also find that an emtricitabine-based antiretroviral drug regimen dramatically enhances the efficacy of VIT, by reducing the fitness of mutants along the escape path. Our findings demonstrate that bNAb escapability is a key determinant to consider in the rational design of antibody regimens with maximal efficacy and illustrates a tractable means of minimizing viral escape from existing bNAbs.

Systematic analysis of the Candida albicans kinome reveals environmentally contingent protein kinase-mediated regulation of filamentation and biofilm formation in vitro and in vivo.

Protein kinases are critical regulatory proteins in both prokaryotes and eukaryotes. Accordingly, protein kinases represent a common drug target for a wide range of human diseases. Therefore, understanding protein kinase function in human pathogens such as the fungus Candida albicans is likely to extend our knowledge of its pathobiology and identify new potential therapies. To facilitate the study of C. albicans protein kinases, we constructed a library of 99 non-essential protein kinase homozygous deletion mutants marked with barcodes in the widely used SN genetic background. Here, we describe the construction of this library and the characterization of the competitive fitness of the protein kinase mutants under 11 different growth and stress conditions. We also screened the library for protein kinase mutants with altered filamentation and biofilm formation, two critical virulence traits of C. albicans. An extensive network of protein kinases governs these virulence traits in a manner highly dependent on the specific environmental conditions. Studies on specific protein kinases revealed that (i) the cell wall integrity MAPK pathway plays a condition-dependent role in filament initiation and elongation; (ii) the hyper-osmolar glycerol MAPK pathway is required for both filamentation and biofilm formation, particularly in the setting of in vivo catheter infection; and (iii) Sok1 is dispensable for filamentation in hypoxic environments at the basal level of a biofilm but is required for filamentation in normoxia. In addition to providing a new genetic resource for the community, these observations emphasize the environmentally contingent function of C. albicans protein kinases.IMPORTANCECandida albicans is one of the most common causes of fungal disease in humans for which new therapies are needed. Protein kinases are key regulatory proteins and are increasingly targeted by drugs for the treatment of a wide range of diseases. Understanding protein kinase function in C. albicans pathogenesis may facilitate the development of new antifungal drugs. Here, we describe a new library of 99 protein kinase deletion mutants to facilitate the study of protein kinases. Furthermore, we show that the function of protein kinases in two virulence-related processes, filamentation and biofilm formation, is dependent on the specific environmental conditions.

Rationally Designed Pooled CRISPRi-Seq Uncovers an Inhibitor of Bacterial Peptidyl-tRNA Hydrolase.

Bacterial mutant libraries in which antibiotic targets are downregulated are useful tools to functionally characterize novel antimicrobials. These libraries are used for chemical-genetic profiling as target-compound interactions can be inferred by differential fitness of mutants during pooled growth. Mutants that are functionally related to the antimicrobial mode of action are usually depleted from the pool upon exposure to the drug. Although powerful, this method can fail when the unequal proliferation of mutant strains before exposure causes mutants to fall below the detection level in the library pool. To address this issue, we constructed an arrayed essential gene mutant library (EGML) in the antibiotic-resistant bacterium Burkholderia cenocepacia using CRISPR interference (CRISPRi) and analyzed the growth parameters of individual mutant strains. We then modelled depletion levels during pooled growth and used the model to rationally design an optimized CRISPR interference-mediated pooled library of essential genes (CIMPLE). By adjusting the initial inoculum of the knockdown mutants, we achieved coverage of the bacterial essential genome with mutant sensitization. We exposed CIMPLE to a recently discovered antimicrobial of a novel class and discovered it inhibits the peptidyl-tRNA hydrolase, an essential bacterial enzyme. In summary, we demonstrate the utility of CIMPLE and CRISPRi-Seq to uncover the mechanism of action of novel antimicrobial compounds.

Estimating mutation rates under heterogeneous stress responses.

Exposure to environmental stressors, including certain antibiotics, induces stress responses in bacteria. Some of these responses increase mutagenesis and thus potentially accelerate resistance evolution. Many studies report increased mutation rates under stress, often using the standard experimental approach of fluctuation assays. However, single-cell studies have revealed that many stress responses are heterogeneously expressed in bacterial populations, which existing estimation methods have not yet addressed. We develop a population dynamic model that considers heterogeneous stress responses (subpopulations of cells with the response off or on) that impact both mutation rate and cell division rate, inspired by the DNA-damage response in Escherichia coli (SOS response). We derive the mutant count distribution arising in fluctuation assays under this model and then implement maximum likelihood estimation of the mutation-rate increase specifically associated with the expression of the stress response. Using simulated mutant count data, we show that our inference method allows for accurate and precise estimation of the mutation-rate increase, provided that this increase is sufficiently large and the induction of the response also reduces the division rate. Moreover, we find that in many cases, either heterogeneity in stress responses or mutant fitness costs could explain similar patterns in fluctuation assay data, suggesting that separate experiments would be required to identify the true underlying process. In cases where stress responses and mutation rates are heterogeneous, current methods still correctly infer the effective increase in population mean mutation rate, but we provide a novel method to infer distinct stress-induced mutation rates, which could be important for parameterising evolutionary models.

Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli.

The evolution of antimicrobial resistance (AMR) in bacteria is a major public health concern, and antibiotic restriction is often implemented to reduce the spread of resistance. These measures rely on the existence of deleterious fitness effects (i.e. costs) imposed by AMR mutations during growth in the absence of antibiotics. According to this assumption, resistant strains will be outcompeted by susceptible strains that do not pay the cost during the period of restriction. The fitness effects of AMR mutations are generally studied in laboratory reference strains grown in standard growth environments; however, the genetic and environmental context can influence the magnitude and direction of a mutation's fitness effects. In this study, we measure how three sources of variation impact the fitness effects of Escherichia coli AMR mutations: the type of resistance mutation, the genetic background of the host, and the growth environment. We demonstrate that while AMR mutations are generally costly in antibiotic-free environments, their fitness effects vary widely and depend on complex interactions between the mutation, genetic background, and environment. We test the ability of the Rough Mount Fuji fitness landscape model to reproduce the empirical data in simulation. We identify model parameters that reasonably capture the variation in fitness effects due to genetic variation. However, the model fails to accommodate the observed variation when considering multiple growth environments. Overall, this study reveals a wealth of variation in the fitness effects of resistance mutations owing to genetic background and environmental conditions, which will ultimately impact their persistence in natural populations.

Modeling spatial evolution of multi-drug resistance under drug environmental gradients.

Multi-drug combinations to treat bacterial populations are at the forefront of approaches for infection control and prevention of antibiotic resistance. Although the evolution of antibiotic resistance has been theoretically studied with mathematical population dynamics models, extensions to spatial dynamics remain rare in the literature, including in particular spatial evolution of multi-drug resistance. In this study, we propose a reaction-diffusion system that describes the multi-drug evolution of bacteria based on a drug-concentration rescaling approach. We show how the resistance to drugs in space, and the consequent adaptation of growth rate, is governed by a Price equation with diffusion, integrating features of drug interactions and collateral resistances or sensitivities to the drugs. We study spatial versions of the model where the distribution of drugs is homogeneous across space, and where the drugs vary environmentally in a piecewise-constant, linear and nonlinear manner. Although in many evolution models, per capita growth rate is a natural surrogate for fitness, in spatially-extended, potentially heterogeneous habitats, fitness is an emergent property that potentially reflects additional complexities, from boundary conditions to the specific spatial variation of growth rates. Applying concepts from perturbation theory and reaction-diffusion equations, we propose an analytical metric for characterization of average mutant fitness in the spatial system based on the principal eigenvalue of our linear problem, λ1. This enables an accurate translation from drug spatial gradients and mutant antibiotic susceptibility traits to the relative advantage of each mutant across the environment. Our approach allows one to predict the precise outcomes of selection among mutants over space, ultimately from comparing their λ1 values, which encode a critical interplay between growth functions, movement traits, habitat size and boundary conditions. Such mathematical understanding opens new avenues for multi-drug therapeutic optimization.

Amplifiers of selection for the Moran process with both Birth-death and death-Birth updating.

Populations evolve by accumulating advantageous mutations. Every population has some spatial structure that can be modeled by an underlying network. The network then influences the probability that new advantageous mutations fixate. Amplifiers of selection are networks that increase the fixation probability of advantageous mutants, as compared to the unstructured fully-connected network. Whether or not a network is an amplifier depends on the choice of the random process that governs the evolutionary dynamics. Two popular choices are Moran process with Birth-death updating and Moran process with death-Birth updating. Interestingly, while some networks are amplifiers under Birth-death updating and other networks are amplifiers under death-Birth updating, so far no spatial structures have been found that function as an amplifier under both types of updating simultaneously. In this work, we identify networks that act as amplifiers of selection under both versions of the Moran process. The amplifiers are robust, modular, and increase fixation probability for any mutant fitness advantage in a range r ∈ (1, 1.2). To complement this positive result, we also prove that for certain quantities closely related to fixation probability, it is impossible to improve them simultaneously for both versions of the Moran process. Together, our results highlight how the two versions of the Moran process differ and what they have in common.

An expanded transcriptome atlas for Bacteroides thetaiotaomicron reveals a small RNA that modulates tetracycline sensitivity.

Plasticity in gene expression allows bacteria to adapt to diverse environments. This is particularly relevant in the dynamic niche of the human intestinal tract; however, transcriptional networks remain largely unknown for gut-resident bacteria. Here we apply differential RNA sequencing (RNA-seq) and conventional RNA-seq to the model gut bacterium Bacteroides thetaiotaomicron to map transcriptional units and profile their expression levels across 15 in vivo-relevant growth conditions. We infer stress- and carbon source-specific transcriptional regulons and expand the annotation of small RNAs (sRNAs). Integrating this expression atlas with published transposon mutant fitness data, we predict conditionally important sRNAs. These include MasB, which downregulates tetracycline tolerance. Using MS2 affinity purification and RNA-seq, we identify a putative MasB target and assess its role in the context of the MasB-associated phenotype. These data-publicly available through the Theta-Base web browser ( http://micromix.helmholtz-hiri.de/bacteroides/ )-constitute a valuable resource for the microbiome community.

A method to correct for local alterations in DNA copy number that bias functional genomics assays applied to antibiotic-treated bacteria.

Functional genomics techniques, such as transposon insertion sequencing and RNA-sequencing, are key to studying relative differences in bacterial mutant fitness or gene expression under selective conditions. However, certain stress conditions, mutations, or antibiotics can directly interfere with DNA synthesis, resulting in systematic changes in local DNA copy numbers along the chromosome. This can lead to artifacts in sequencing-based functional genomics data when comparing antibiotic treatment to an unstressed control. Further, relative differences in gene-wise read counts may result from alterations in chromosomal replication dynamics, rather than selection or direct gene regulation. We term this artifact "chromosomal location bias" and implement a principled statistical approach to correct it by calculating local normalization factors along the chromosome. These normalization factors are then directly incorporated into statistical analyses using standard RNA-sequencing analysis methods without modifying the read counts themselves, preserving important information about the mean-variance relationship in the data. We illustrate the utility of this approach by generating and analyzing a ciprofloxacin-treated transposon insertion sequencing data set in Escherichia coli as a case study. We show that ciprofloxacin treatment generates chromosomal location bias in the resulting data, and we further demonstrate that failing to correct for this bias leads to false predictions of mutant drug sensitivity as measured by minimum inhibitory concentrations. We have developed an R package and user-friendly graphical Shiny application, ChromoCorrect, that detects and corrects for chromosomal bias in read count data, enabling the application of functional genomics technologies to the study of antibiotic stress.IMPORTANCEAltered gene dosage due to changes in DNA replication has been observed under a variety of stresses with a variety of experimental techniques. However, the implications of changes in gene dosage for sequencing-based functional genomics assays are rarely considered. We present a statistically principled approach to correcting for the effect of changes in gene dosage, enabling testing for differences in the fitness effects or regulation of individual genes in the presence of confounding differences in DNA copy number. We show that failing to correct for these effects can lead to incorrect predictions of resistance phenotype when applying functional genomics assays to investigate antibiotic stress, and we provide a user-friendly application to detect and correct for changes in DNA copy number.

Citrate cross-feeding by Pseudomonas aeruginosa supports lasR mutant fitness.

Cross-feeding of metabolites between subpopulations can affect cell phenotypes and population-level behaviors. In chronic Pseudomonas aeruginosa lung infections, subpopulations with loss-of-function (LOF) mutations in the lasR gene are common. LasR, a transcription factor often described for its role in virulence factor expression, also impacts metabolism, which, in turn, affects interactions between LasR+ and LasR- genotypes. Prior transcriptomic analyses suggested that citrate, a metabolite secreted by many cell types, induces virulence factor production when both genotypes are together. An unbiased analysis of the intracellular metabolome revealed broad differences including higher levels of citrate in lasR LOF mutants. Citrate consumption by LasR- strains required the CbrAB two-component system, which relieves carbon catabolite repression and is elevated in lasR LOF mutants. Within mixed communities, the citrate-responsive two-component system TctED and its gene targets OpdH (porin) and TctABC (citrate transporter) that are predicted to be under catabolite repression control were induced and required for enhanced RhlR/I-dependent signaling, pyocyanin production, and fitness of LasR- strains. Citrate uptake by LasR- strains markedly increased pyocyanin production in co-culture with Staphylococcus aureus, which also secretes citrate and frequently co-infects with P. aeruginosa. This citrate-induced restoration of virulence factor production by LasR- strains in communities with diverse species or genotypes may offer an explanation for the contrast observed between the markedly deficient virulence factor production of LasR- strains in monocultures and their association with the most severe forms of cystic fibrosis lung infections. These studies highlight the impact of secreted metabolites in mixed microbial communities.IMPORTANCECross-feeding of metabolites can change community composition, structure, and function. Here, we unravel a cross-feeding mechanism between frequently co-observed isolate genotypes in chronic Pseudomonas aeruginosa lung infections. We illustrate an example of how clonally derived diversity in a microbial communication system enables intra- and inter-species cross-feeding. Citrate, a metabolite released by many cells including P. aeruginosa and Staphylococcus aureus, was differentially consumed between genotypes. Since these two pathogens frequently co-occur in the most severe cystic fibrosis lung infections, the cross-feeding-induced virulence factor expression and fitness described here between diverse genotypes exemplify how co-occurrence can facilitate the development of worse disease outcomes.

Functional redundancy revealed by the deletion of the mimivirus GMC-oxidoreductase genes.

The mimivirus 1.2 Mb genome was shown to be organized into a nucleocapsid-like genomic fiber encased in the nucleoid compartment inside the icosahedral capsid. The genomic fiber protein shell is composed of a mixture of two GMC-oxidoreductase paralogs, one of them being the main component of the glycosylated layer of fibrils at the surface of the virion. In this study, we determined the effect of the deletion of each of the corresponding genes on the genomic fiber and the layer of surface fibrils. First, we deleted the GMC-oxidoreductase, the most abundant in the genomic fiber, and determined its structure and composition in the mutant. As expected, it was composed of the second GMC-oxidoreductase and contained 5- and 6-start helices similar to the wild-type fiber. This result led us to propose a model explaining their coexistence. Then we deleted the GMC-oxidoreductase, the most abundant in the layer of fibrils, to analyze its protein composition in the mutant. Second, we showed that the fitness of single mutants and the double mutant were not decreased compared with the wild-type viruses under laboratory conditions. Third, we determined that deleting the GMC-oxidoreductase genes did not impact the glycosylation or the glycan composition of the layer of surface fibrils, despite modifying their protein composition. Because the glycosylation machinery and glycan composition of members of different clades are different, we expanded the analysis of the protein composition of the layer of fibrils to members of the B and C clades and showed that it was different among the three clades and even among isolates within the same clade. Taken together, the results obtained on two distinct central processes (genome packaging and virion coating) illustrate an unexpected functional redundancy in members of the family Mimiviridae, suggesting this may be the major evolutionary force behind their giant genomes.

Coevolutionary Information Captures Catalytic Functions and Reveals Divergent Roles of Terpene Synthase Interdomain Connections.

Inferring the historical and biophysical causes of diversity within protein families is a complex puzzle. A key to unraveling this problem is characterizing the rugged topography of sequence-function adaptive landscapes. Using biochemical data from a 29 = 512 combinatorial library of tobacco 5-epi-aristolochene synthase (TEAS) mutants engineered to make the native major product of Egyptian henbane premnaspirodiene synthase (HPS) and a complementary 512 mutant HPS library, we address the question of how product specificity is controlled. These data sets reveal that HPS is far more robust and resistant to mutations than TEAS, where most mutants are promiscuous. We also combine experimental data with a sequence Potts Hamiltonian model and direct coupling analysis to quantify mutant fitness. Our results demonstrate that the Hamiltonian captures variation in product outputs across both libraries, clusters native family members based on their substrate specificities, and exposes the divergent catalytic roles of couplings between the catalytic and noncatalytic domains of TEAS versus HPS. Specifically, we found that the role of the interdomain connectivities in specifying product output is more important in TEAS than connectivities within the catalytic domain. Despite being 75% identical, this property is not shared by HPS, where connectivities within the catalytic domain are more important for specificity. By solving the X-ray crystal structure of HPS, we assessed structural bases for their interdomain network differences. Last, we calculate the product profile Shannon entropies of the two libraries, which showcases that site-site connectivities also play divergent roles in catalytic accuracy.

Characteristics of famoxadone-resistant mutants of Phytophthora litchii and their effect on lychee fruit quality

Lychee downy blight (LDB), a common disease caused by the oomycete Phytophthora litchii, poses a significant threat to both pre- and post-harvest stages, leading to substantial economic losses. Famoxadone, a quinone outside inhibitor fungicide, was registered for controlling LDB in China in 2002. However, limited information is available regarding the risk, mechanism, and impact on lychee fruit quality associated with famoxadone resistance. In this study, we determined the sensitivity of 133 P. litchii isolates to famoxadone, yielding a mean EC50 value of 0.46 ± 0.21 μg/mL. Through fungicide adaption, we derived resistant mutants with M124I and Y131C substitutions in PlCyt b (Cytochrome b in P. litchii) from wild-type isolates. In vitro assessments revealed that the fitness of the resistant mutants was significantly lower compared to the parental isolates. These laboratory findings demonstrate a moderate resistance risk of P. litchii to famoxadone. Molecular docking analyses indicated that the M124I and Y131C alterations disrupted hydrogen bonds and weakened the binding energy between famoxadone and PlCyt b. This indicates that the M124I and Y131C changes do indeed confer famoxadone resistance in P. litchii. Infection caused by famoxadone-resistant mutants exhibited a decreased or comparable impact on the characteristic traits of lychee fruit compared to the sensitive isolate. For future detection of famoxadone-resistant strains, AS-PCR primers were designed based on the M124I substitution.

Sensitivity and resistance risk analysis of Didymella bryoniae populations to fluopyram

Fluopyram is an succinate dehydrogenase inhibitors (SDHI) fungicide that has been registered in China to control gummy stem blight (GSB) in watermelons for many years. However, whether the field pathogens of GSB are still sensitive to fluopyram or not is unknown. Therefore, we collected 69 Didymellabryoniae isolates from the fields that usually use fluopyram to control GSB to determine the sensitivity change. The EC50 (50% inhibition effect) values of fluopyram against D. bryoniae ranged from 0.0691 to 0.3503 μg mL–1 and the variation factor was 5.07. The mean EC50 value was (0.1579±0.0669) μg mL–1 and the curve of sensitivity was unimodal. No resistant strains were found in the isolates, which means that the pathogens were still sensitive to fluopyram. The minimal inhibition concentration (MIC) of fluopyram against D. bryoniae was 3 μg mL–1. Four low-resistant mutants and two medium-resistant mutants were obtained using fungicide taming and the resistance of mutants could be inherited stably. The growth rate of mutants decreased significantly compared with that of wild-type strains while the biomass of most mutants was similar to that of wild-type strains. The sensitivity of most resistant mutants to various stresses was increased compared with that of wild-type strains. The virulence of mutants receded except for low-resistant mutant XN51FR-1, which had the same lesion area as XN51 on the watermelon leaves. The results indicated that the fitness of resistant mutants was decreased compared with that of wild-type strains. The cross-resistance assay indicated that fluopyram-resistant mutants were positive cross-resistant to all six SDHI fungicides in this test but were still sensitive to fluazinam and tebuconazole. So the resistance risk of D. bryoniae to fluopyram was moderate. In addition, we found that the SdhB gene of low-resistant mutant XN30FR-1 had three new point mutations at positions K258N, A259P, and H277N. Medium-resistant mutant XN52FR-1 showed a mutation at position H277N and other mutants did not have any point mutation.

Evaluating E. coli genome-scale metabolic model accuracy with high-throughput mutant fitness data.

The Escherichia coli genome-scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision-recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene-protein-reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high-throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

Genetic and Phenotypic Analysis of Phage-Resistant Mutant Fitness Triggered by Phage-Host Interactions.

The emergence of phage-resistant bacterial strains is one of the biggest challenges for phage therapy. However, the emerging phage-resistant bacteria are often accompanied by adaptive trade-offs, which supports a therapeutic strategy called "phage steering". The key to phage steering is to guide the bacterial population toward an evolutionary direction that is favorable for treatment. Thus, it is important to systematically investigate the impacts of phages targeting different bacterial receptors on the fitness of the bacterial population. Herein, we employed 20 different phages to impose strong evolutionary pressure on the host Pseudomonas aeruginosa PAO1 and examined the genetic and phenotypic responses of their phage-resistant mutants. Among these strains with impaired adsorptions, four types of mutations associated with bacterial receptors were identified, namely, lipopolysaccharides (LPSs), type IV pili (T4Ps), outer membrane proteins (OMPs), and exopolysaccharides (EPSs). PAO1, responding to LPS- and EPS-dependent phage infections, mostly showed significant growth impairment and virulence attenuation. Most mutants with T4P-related mutations exhibited a significant decrease in motility and biofilm formation ability, while the mutants with OMP-related mutations required the lowest fitness cost out of the bacterial populations. Apart from fitness costs, PAO1 strains might lose their resistance to antibiotics when counteracting with phages, such as the presence of large-fragment mutants in this study, which may inspire the usage of phage-antibiotic combination strategies. This work provides methods that leverage the merits of phage resistance relative to obtaining therapeutically beneficial outcomes with respect to phage-steering strategies.

Three point mutations in AaCYP51 combined with induced overexpression of AaCYP51 conferred low-level resistance to mefentrifluconazole in Alternaria alternata

Tomato early blight is a significant disease that causes substantial losses to tomato yield and quality. Mefentrifluconazole, an isopropanol-azole subgroup of triazole fungicides, has been registered in China for controlling various plant diseases, including tomato early blight, grape anthracnose, and apple brown spot. However, limited information is available on the mefentrifluconazole resistance risk and mechanism in plant pathogens. The sensitivity to mefentrifluconazole of 122 isolates of Alternaria alternata, one of the causal agents of tomato early blight, collected from different provinces in China, was evaluated. The results showed a unimodal curve for the sensitivity frequency, with an average EC50 of 0.306 μg/mL. Through fungicide adaption, six resistant mutants (N4, N5, T4, T5, NG1, and NG10) were obtained from three parental isolates, with a mutation frequency of 3.28 × 10−4 and resistance factors ranging between 19 and 147. The survival fitness of the resistant mutants, except for NG1, was significantly lower than that of their parental isolates. Positive cross-resistance was observed between mefentrifluconazole and difenoconazole or fenbuconazole, whereas no cross-resistance was found with three non-DMI fungicides. Furthermore, three distinct point mutations were detected in the AaCYP51 protein of the resistant mutants: I300S in T4 and T5; A303T in N4, NG1, and NG10; and A303V in N5. Compared to the parental isolates, the AaCYP51 gene was overexpressed in all six resistant mutants when treated with mefentrifluconazole. In summary, the resistance risk of A. alternata to mefentrifluconazole was low, and point mutations and overexpression of the AaCYP51 gene were identified as contributing factors to mefentrifluconazole resistance in A. alternata.

Mutualism reduces the severity of gene disruptions in predictable ways across microbial communities

Predicting evolution in microbial communities is critical for problems from human health to global nutrient cycling. Understanding how species interactions impact the distribution of fitness effects for a focal population would enhance our ability to predict evolution. Specifically, does the type of ecological interaction, such as mutualism or competition, change the average effect of a mutation (i.e., the mean of the distribution of fitness effects)? Furthermore, how often does increasing community complexity alter the impact of species interactions on mutant fitness? To address these questions, we created a transposon mutant library in Salmonella enterica and measured the fitness of loss of function mutations in 3,550 genes when grown alone versus competitive co-culture or mutualistic co-culture with Escherichia coli and Methylorubrum extorquens. We found that mutualism reduces the average impact of mutations, while competition had no effect. Additionally, mutant fitness in the 3-species communities can be predicted by averaging the fitness in each 2-species community. Finally, we discovered that in the mutualism S. enterica obtained vitamins and more amino acids than previously known. Our results suggest that species interactions can predictably impact fitness effect distributions, in turn suggesting that evolution may ultimately be predictable in multi-species communities.