Purine and pyrimidine synthesis differently affect the strength of the inoculum effect for aminoglycoside and ß-lactam antibiotics.

The inoculum effect has been observed for nearly all antibiotics and bacterial species. However, explanations accounting for its occurrence and strength are lacking. We previously found that growth productivity, which captures the relationship between [ATP] and growth, can account for the strength of the inoculum effect for bactericidal antibiotics. However, the molecular pathway(s) underlying this relationship, and therefore determining the inoculum effect, remain undiscovered. We show that nucleotide synthesis can determine the relationship between [ATP] and growth, and thus the strength of inoculum effect in an antibiotic class-dependent manner. Specifically, and separate from activity through the tricarboxylic acid cycle, we find that transcriptional activity of genes involved in purine and pyrimidine synthesis can predict the strength of the inoculum effect for ß-lactam and aminoglycosides antibiotics, respectively. Our work highlights the antibiotic class-specific effect of purine and pyrimidine synthesis on the severity of the inoculum effect and paves the way for intervention strategies to reduce the inoculum effect in the clinic.

Sub-inhibitory antibiotic treatment selects for enhanced metabolic efficiency.

Bacterial growth and metabolic rates are often closely related. However, under antibiotic selection, a paradox in this relationship arises: antibiotic efficacy decreases when bacteria are metabolically dormant, yet antibiotics select for resistant cells that grow fastest during treatment. That is, antibiotic selection counterintuitively favors bacteria with fast growth but slow metabolism. Despite this apparent contradiction, antibiotic resistant cells have historically been characterized primarily in the context of growth, whereas the extent of analogous changes in metabolism is comparatively unknown. Here, we observed that previously evolved antibiotic-resistant strains exhibited a unique relationship between growth and metabolism whereby nutrient utilization became more efficient, regardless of the growth rate. To better understand this unexpected phenomenon, we used a simplified model to simulate bacterial populations adapting to sub-inhibitory antibiotic selection through successive bottlenecking events. Simulations predicted that sub-inhibitory bactericidal antibiotic concentrations could select for enhanced metabolic efficiency, defined based on nutrient utilization: drug-adapted cells are able to achieve the same biomass while utilizing less substrate, even in the absence of treatment. Moreover, simulations predicted that restoring metabolic efficiency would re-sensitize resistant bacteria exhibiting metabolic-dependent resistance; we confirmed this result using adaptive laboratory evolutions of Escherichia coli under carbenicillin treatment. Overall, these results indicate that metabolic efficiency is under direct selective pressure during antibiotic treatment and that differences in evolutionary context may determine both the efficacy of different antibiotics and corresponding re-sensitization approaches.IMPORTANCEThe sustained emergence of antibiotic-resistant pathogens combined with the stalled drug discovery pipelines highlights the critical need to better understand the underlying evolution mechanisms of antibiotic resistance. To this end, bacterial growth and metabolic rates are often closely related, and resistant cells have historically been characterized exclusively in the context of growth. However, under antibiotic selection, antibiotics counterintuitively favor cells with fast growth, and slow metabolism. Through an integrated approach of mathematical modeling and experiments, this study thereby addresses the significant knowledge gap of whether antibiotic selection drives changes in metabolism that complement, and/or act independently, of antibiotic resistance phenotypes.

Tradeoff between lag time and growth rate drives the plasmid acquisition cost.

Conjugative plasmids drive genetic diversity and evolution in microbial populations. Despite their prevalence, plasmids can impose long-term fitness costs on their hosts, altering population structure, growth dynamics, and evolutionary outcomes. In addition to long-term fitness costs, acquiring a new plasmid introduces an immediate, short-term perturbation to the cell. However, due to the transient nature of this plasmid acquisition cost, a quantitative understanding of its physiological manifestations, overall magnitudes, and population-level implications, remains unclear. To address this, here we track growth of single colonies immediately following plasmid acquisition. We find that plasmid acquisition costs are primarily driven by changes in lag time, rather than growth rate, for nearly 60 conditions covering diverse plasmids, selection environments, and clinical strains/species. Surprisingly, for a costly plasmid, clones exhibiting longer lag times also achieve faster recovery growth rates, suggesting an evolutionary tradeoff. Modeling and experiments demonstrate that this tradeoff leads to counterintuitive ecological dynamics, whereby intermediate-cost plasmids outcompete both their low and high-cost counterparts. These results suggest that, unlike fitness costs, plasmid acquisition dynamics are not uniformly driven by minimizing growth disadvantages. Moreover, a lag/growth tradeoff has clear implications in predicting the ecological outcomes and intervention strategies of bacteria undergoing conjugation.

Interactions between metabolism and growth can determine the co-existence of Staphylococcus aureus and Pseudomonas aeruginosa.

Most bacteria exist and interact within polymicrobial communities. These interactions produce unique compounds, increase virulence and augment antibiotic resistance. One community associated with negative healthcare outcomes consists of Pseudomonas aeruginosa and Staphylococcus aureus. When co-cultured, virulence factors secreted by P. aeruginosa reduce metabolism and growth in S. aureus. When grown in vitro, this allows P. aeruginosa to drive S. aureus toward extinction. However, when found in vivo, both species can co-exist. Previous work has noted that this may be due to altered gene expression or mutations. However, little is known about how the growth environment could influence the co-existence of both species. Using a combination of mathematical modeling and experimentation, we show that changes to bacterial growth and metabolism caused by differences in the growth environment can determine the final population composition. We found that changing the carbon source in growth media affects the ratio of ATP to growth rate for both species, a metric we call absolute growth. We found that as a growth environment increases the absolute growth for one species, that species will increasingly dominate the co-culture. This is due to interactions between growth, metabolism, and metabolism-altering virulence factors produced by P. aeruginosa. Finally, we show that the relationship between absolute growth and the final population composition can be perturbed by altering the spatial structure in the community. Our results demonstrate that differences in growth environment can account for conflicting observations regarding the co-existence of these bacterial species in the literature, provides support for the intermediate disturbance hypothesis, and may offer a novel mechanism to manipulate polymicrobial populations.

Infections caused by multiple types of bacteria are tough to treat. For example, co-infections with Staphylococcus aureus and Pseudomonas aeruginosa are so difficult to cure they may persist for years in humans and cause serious illness. But when these two types of bacteria are grown together in the laboratory, P. aeruginosa kills off all the S. aureus. Learning why these two types of bacteria can coexist in people but not in the laboratory may lead to new treatments to clear infections. It may also help scientists grow beneficial bacteria mixes that break down pollution or produce biofuels. Pajon and Fortoul et al. show that interactions between bacterial metabolism and growth rate determine whether S. aureus and P. aeruginosa coexist. In the experiments, they grew both types of bacteria in different environments with different food sources. They measured their growth and metabolism and how many bacteria of each species survived over time. Then, they used their data to develop a mathematical model and tested its predictions in the laboratory again. The type of bacteria that had more energy also grew faster and outcompeted the other species. Measuring the growth rate of the two species allowed the scientists to predict which one would win out and what the tipping point would be. Physically disrupting the mix of bacteria disrupted this relationship. These results may help explain what allows these bacteria to coexist in some settings but not others. It may enable scientists to develop new ways to treat infections with P. aeruginosa and S. aureus that work by manipulating growth in the two species. Bacterial growth and metabolism are known to drive antibacterial resistance. Studies in mice using drugs or other therapies to manipulate growth and metabolism may help scientists thwart these resistance mechanisms. The results may also help scientists design and grow beneficial multispecies bacteria communities.

Disturbing the Spatial Organization of Biofilm Communities Affects Expression of agr-Regulated Virulence Factors in Staphylococcus aureus.

Staphylococcus aureus uses quorum sensing and nutrient availability to control the expression of agr-regulated virulence factors. Quorum sensing is mediated by autoinducing peptide (AIP), which at a high concentration reduces expression of surface attachment proteins (coa, fnbpA) and increases expression of exotoxins (lukS) and proteases (splA). Nutrient availability can be sensed through the saeS/saeR system. Low nutrients increase expression of saeR, which augments expression of coa and fnbpA, distinct from the activity of AIP. The formation of spatial structure, such as biofilms, can alter quorum sensing and nutrient acquisition. In natural environments, biofilms encounter forces that may alter their spatial structure. These forces may impact quorum sensing and/or nutrient acquisition and thus affect the expression of agr-regulated virulence factors. However, this has not been studied. We show that periodically disturbing biofilms composed of S. aureus using a physical force affected the expression of agr-regulated virulence factors. In nutrient-poor environments, disturbance increased the expression of coa, fnbpA, lukS, and splA. Disturbance in a nutrient-rich environment at low or high disturbance amplitudes moderately reduced expression of coa and fnbpA but increased expression of lukS and splA. Interestingly, at an intermediate amplitude, the overall expression of agr-regulated virulence factors was the lowest; expression of lukS and splA remained unchanged relative to an undisturbed biofilm, while expression of coa and fnbpA significantly decreased. We hypothesize that these changes are a result of disturbance-driven changes in access to AIP and nutrients. Our results may allow the identification of environments where virulence is enhanced, or reduced, owing to a disturbance. IMPORTANCE Bacteria, such as Staphylococcus aureus, integrate signals from the environment to regulate genes encoding virulence factors. These signals include those produced by quorum-sensing systems and nutrient availability. We show that disturbing the spatial organization of S. aureus populations can lead to changes in the expression of virulence factors, likely by altering the ways in which S. aureus detects these signals. Our work may allow us to identify environments that increase or reduce the expression of virulence factors in S. aureus.

Metabolic genes on conjugative plasmids are highly prevalent in Escherichia coli and can protect against antibiotic treatment.

Conjugative plasmids often encode antibiotic resistance genes that provide selective advantages to their bacterial hosts during antibiotic treatment. Previous studies have predominantly considered these established genes as the primary benefit of antibiotic-mediated plasmid dissemination. However, many genes involved in cellular metabolic processes may also protect against antibiotic treatment and provide selective advantages. Despite the diversity of such metabolic genes and their potential ecological impact, their plasmid-borne prevalence, co-occurrence with canonical antibiotic resistance genes, and phenotypic effects remain widely understudied. To address this gap, we focused on Escherichia coli, which can often act as a pathogen, and is known to spread antibiotic resistance genes via conjugation. We characterized the presence of metabolic genes on 1,775 transferrable plasmids and compared their distribution to that of known antibiotic resistance genes. We found high abundance of genes involved in cellular metabolism and stress response. Several of these genes demonstrated statistically significant associations or disassociations with known antibiotic resistance genes at the strain level, indicating that each gene type may impact the spread of the other across hosts. Indeed, in vitro characterization of 13 statistically relevant metabolic genes confirmed that their phenotypic impact on antibiotic susceptibility was largely consistent with in situ relationships. These results emphasize the ecological importance of metabolic genes on conjugal plasmids, and that selection dynamics of E. coli pathogens arises as a complex consequence of both canonical mechanisms and their interactions with metabolic pathways.

Growth productivity as a determinant of the inoculum effect for bactericidal antibiotics.

Understanding the mechanisms by which populations of bacteria resist antibiotics has implications in evolution, microbial ecology, and public health. The inoculum effect (IE), where antibiotic efficacy declines as the density of a bacterial population increases, has been observed for multiple bacterial species and antibiotics. Several mechanisms to account for IE have been proposed, but most lack experimental evidence or cannot explain IE for multiple antibiotics. We show that growth productivity, the combined effect of growth and metabolism, can account for IE for multiple bactericidal antibiotics and bacterial species. Guided by flux balance analysis and whole-genome modeling, we show that the carbon source supplied in the growth medium determines growth productivity. If growth productivity is sufficiently high, IE is eliminated. Our results may lead to approaches to reduce IE in the clinic, help standardize the analysis of antibiotics, and further our understanding of how bacteria evolve resistance.

Horizontal gene transfer enables programmable gene stability in synthetic microbiota.

The functions of many microbial communities exhibit remarkable stability despite fluctuations in the compositions of these communities. To date, a mechanistic understanding of this function-composition decoupling is lacking. Statistical mechanisms have been commonly hypothesized to explain such decoupling. Here, we proposed that dynamic mechanisms, mediated by horizontal gene transfer (HGT), also enable the independence of functions from the compositions of microbial communities. We combined theoretical analysis with numerical simulations to illustrate that HGT rates can determine the stability of gene abundance in microbial communities. We further validated these predictions using engineered microbial consortia of different complexities transferring one or more than a dozen clinically isolated plasmids, as well as through the reanalysis of data from the literature. Our results demonstrate a generalizable strategy to program the gene stability of microbial communities.

Population structure of blaKPC-harbouring IncN plasmids at a New York City medical centre and evidence for multi-species horizontal transmission.

BACKGROUND: Carbapenem-resistant Enterobacterales (CRE) are highly concerning MDR pathogens. Horizontal transfer of broad-host-range IncN plasmids may contribute to the dissemination of the Klebsiella pneumoniae carbapenemase (KPC), spreading carbapenem resistance among unrelated bacteria. However, the population structure and genetic diversity of IncN plasmids has not been fully elucidated. OBJECTIVES: We reconstructed blaKPC-harbouring IncN plasmid genomes to characterize shared gene content, structural variability, and putative horizontal transfer within and across patients and diverse bacterial clones. METHODS: We performed short- and long-read sequencing and hybrid assembly on 45 CRE isolates with blaKPC-harbouring IncN plasmids. Eight serial isolates from two patients were included to assess intra-patient plasmid dynamics. Comparative genomic analysis was performed to assess structural and sequence similarity across plasmids. Within IncN sublineages defined by plasmid MLST and kmer-based clustering, phylogenetic analysis was used to identify closely related plasmids. RESULTS: Comparative analysis of IncN plasmid genomes revealed substantial heterogeneity including large rearrangements in serial patient plasmids and differences in structure and content across plasmid clusters. Within plasmid sublineages, core genome content and resistance gene regions were largely conserved. Closely related plasmids (≤1 SNP) were found in highly diverse isolates, including ten pST6 plasmids found in eight bacterial clones from three different species. CONCLUSIONS: Genomic analysis of blaKPC-harbouring IncN plasmids revealed the presence of several distinct sublineages as well as substantial host diversity within plasmid clusters suggestive of frequent mobilization. This study reveals complex plasmid dynamics within a single plasmid family, highlighting the challenge of tracking plasmid-mediated transmission of blaKPC in clinical settings.

Phylogenomics of two ST1 antibiotic-susceptible non-clinical Acinetobacter baumannii strains reveals multiple lineages and complex evolutionary history in global clone 1.

Acinetobacter baumannii is an opportunistic pathogen that is difficult to treat due to its resistance to extreme conditions, including desiccation and antibiotics. Most strains causing outbreaks around the world belong to two main global lineages, namely global clones 1 and 2 (GC1 and GC2). Here, we used a combination of Illumina short read and MinION (Oxford Nanopore) long-read sequence data with a hybrid assembly approach to complete the genome sequence of two antibiotic-sensitive GC1 strains, Ex003 and Ax270, recovered in Lebanon from water and a rectal swab of a cat, respectively. Phylogenetic analysis of Ax270 and Ex003 with 186 publicly available GC1 genomes revealed two major clades, including five main lineages (L1-L5), and four single-isolate lineages outside of the two clades. Ax270 and Ex003, along with AB307-0294 and MRSN7213 (both predicted antibiotic-susceptible isolates) represent these individual lineages. Antibiotic resistance islands and transposons interrupting the comM gene remain important features in L1-L5, with L1 associated with the AbaR-type resistance islands, L2 with AbaR4, L3 strains containing either AbaR4 or its variants as well as Tn6022::ISAba42, and L4 and L5 associated with Tn6022 or its variants. Analysis of the capsule (KL) and outer core (OCL) polysaccharide loci further revealed a complex evolutionary history probably involving many recombination events. As more genomes become available, more GC1 lineages continue to emerge. However, genome sequence data from more diverse geographical regions are needed to draw a more accurate population structure of this globally distributed clone.

Honey bee sHSP are responsive to diverse proteostatic stresses and potentially promising biomarkers of honey bee stress.

The pollination services provided by the honey bee are critical in both natural and agricultural ecosystems. Honey bee colonies in the United States have suffered from an increased rate of die-off in recent years, stemming from a complex set of interacting stresses that remain poorly described. Defining specific common cellular processes and cellular stress responses impacted by multiple stressors represent a key step in understanding these synergies. Proteotoxic stresses negatively impact protein synthesis, folding, and degradation. Diverse proteotoxic stresses induce expression of genes encoding small heat shock proteins (sHSP) of the expanded lethal (2) essential for life (l(2)efl) gene family. In addition to upregulation by the Integrated Stress Response (ISR), the Heat Shock Response (HSR), and the Oxidative Stress Response (OSR), our data provide first evidence that sHSP genes are upregulated by the Unfolded Protein Response (UPR). As these genes appear to be part of a core stress response that could serve as a useful biomarker for cellular stress in honey bees, we designed and tested an RT-LAMP assay to detect increased l(2)efl gene expression in response to heat-stress. While this assay provides a powerful proof of principle, further work will be necessary to link changes in sHSP gene expression to colony-level outcomes, to adapt our preliminary assay into a Point of Care Testing (POCT) assay appropriate for use as a diagnostic tool for use in the field, and to couple assay results to management recommendations.

Quantitative Microbial Risk Assessment of Antimicrobial Resistant and Susceptible Staphylococcus aureus in Reclaimed Wastewaters.

The annual risks of colonization, skin infection, bloodstream infection (BSI), and disease burden from exposures to antibiotic-resistant and susceptible Staphylococcus aureus (S. aureus) were estimated using quantitative microbial risk assessment (QMRA). We estimated the probability of nasal colonization after immersion in wastewater (WW) or greywater (GW) treated across a range of treatment alternatives and subsequent infection. Horizontal gene transfer was incorporated into the treatment model but had little effect on the predicted risk. The cumulative annual probability of infection (resulting from self-inoculation) was most sensitive to the treatment log10 reduction value (LRV), S. aureus concentration, and the newly calculated morbidity ratios and was below the health benchmark of 10-4 infections per person per year (ppy) given a treatment LRV of roughly 3.0. The predicted annual disability-adjusted life years (DALYs), which were dominated by BSI, were below the health benchmark of 10-6 DALYs ppy for resistant and susceptible S. aureus, given LRVs of 4.5 and 3.5, respectively. Thus, the estimated infection risks and disease burdens resulting from nasal colonization are below the relevant health benchmarks for risk-based, nonpotable, or potable reuse systems but possibly above for immersion in minimally treated GW or WW. Strain-specific data to characterize dose-response and concentration in WW are needed to substantiate the QMRA.

Thermal stress induces tissue damage and a broad shift in regenerative signaling pathways in the honey bee digestive tract.

Honey bee colonies in the USA have suffered from increased die-off in the last few years with a complex set of interacting stresses playing a key role. With changing climate, an increase in the frequency of severe weather events, such as heat waves, is anticipated. Understanding how these changes may contribute to stress in honey bees is crucial. Individual honey bees appear to have a high capacity to endure thermal stress. One reason for this high-level endurance is likely their robust heat shock response (HSR), which contributes to thermotolerance at the cellular level. However, less is known about other mechanisms of thermotolerance, especially those operating at the tissue level. To elucidate other determinants of resilience in this species, we used thermal stress coupled with RNAseq and identified broad transcriptional remodeling of a number of key signaling pathways in the honey bee, including those pathways known to be involved in digestive tract regeneration in the fruit fly such as the Hippo and JAK/STAT pathways. We also observed cell death and shedding of epithelial cells, which likely leads to induction of this regenerative transcriptional program. We found that thermal stress affects many of these pathways in other tissues, suggesting a shared program of damage response. This study provides important foundational characterization of the tissue damage response program in this key pollinating species. In addition, our data suggest that a robust regeneration program may also be a critical contributor to thermotolerance at the tissue level, a possibility which warrants further exploration in this and other species.

Digital Insights Into Nucleotide Metabolism and Antibiotic Treatment Failure.

Nucleotide metabolism plays a central role in bacterial physiology, producing the nucleic acids necessary for DNA replication and RNA transcription. Recent studies demonstrate that nucleotide metabolism also proactively contributes to antibiotic-induced lethality in bacterial pathogens and that disruptions to nucleotide metabolism contributes to antibiotic treatment failure in the clinic. As antimicrobial resistance continues to grow unchecked, new approaches are needed to study the molecular mechanisms responsible for antibiotic efficacy. Here we review emerging technologies poised to transform understanding into why antibiotics may fail in the clinic. We discuss how these technologies led to the discovery that nucleotide metabolism regulates antibiotic drug responses and why these are relevant to human infections. We highlight opportunities for how studies into nucleotide metabolism may enhance understanding of antibiotic failure mechanisms.

Quantitative analysis of horizontal gene transfer in complex systems.

Horizontal gene transfer (HGT) plays a significant role in rapidly propagating diverse traits throughout bacterial populations, thereby accelerating natural evolution and leading to complex community structures. Critical gene transfer rates underlying these occurrences dictate the efficiency and speed of gene spread; these rates are often highly specific to HGT mechanism and environmental context, and have historically been challenging to reliably quantify. In this review, we examine recent works that leverage rigorous quantitative methods to precisely measure these rates in a variety of settings beginning with in vitro studies and advancing to in situ measurements; we emphasize contexts where quantification across multiple scales of complexity has led to fundamental biological insights. Finally, we highlight the applications of these measurements and suggest potential methodological advances to improve our understanding.

Investigation of the prevalence and catalytic activity of rubredoxin-fused alkane monooxygenases (AlkBs).

Interest in understanding the environmental distribution of the alkane monooxygenase (AlkB) enzyme led to the identification of over 100 distinct alkane monooxygenase (AlkB) enzymes containing a covalently bound, or fused, rubredoxin. The rubredoxin-fused AlkB from Dietzia cinnamea was cloned as a full-length protein and as a truncated protein with the rubredoxin domain deleted. A point mutation (V91W) was introduced into the full-length protein, with the goal of assessing how steric bulk in the putative substrate channel might affect selectivity. Based on activity studies with alkane and alkene substrates, the rubredoxin-fused AlkB oxidizes a similar range of alkane substrates relative to its rubredoxin domain-deletion counterpart. Oxidation of terminal alkenes generated both an epoxide and a terminal aldehyde. The products of V91W-mutant-catalyzed oxidation of alkenes had a higher aldehyde-to-epoxide ratio than the products formed in the presence of the wild type protein. These results are consistent with this mutation causing a structural change impacting substrate positioning.

Conjugation dynamics depend on both the plasmid acquisition cost and the fitness cost.

Plasmid conjugation is a major mechanism responsible for the spread of antibiotic resistance. Plasmid fitness costs are known to impact long-term growth dynamics of microbial populations by providing plasmid-carrying cells a relative (dis)advantage compared to plasmid-free counterparts. Separately, plasmid acquisition introduces an immediate, but transient, metabolic perturbation. However, the impact of these short-term effects on subsequent growth dynamics has not previously been established. Here, we observed that de novo transconjugants grew significantly slower and/or with overall prolonged lag times, compared to lineages that had been replicating for several generations, indicating the presence of a plasmid acquisition cost. These effects were general to diverse incompatibility groups, well-characterized and clinically captured plasmids, Gram-negative recipient strains and species, and experimental conditions. Modeling revealed that both fitness and acquisition costs modulate overall conjugation dynamics, validated with previously published data. These results suggest that the hours immediately following conjugation may play a critical role in both short- and long-term plasmid prevalence. This time frame is particularly relevant to microbiomes with high plasmid/strain diversity considered to be hot spots for conjugation.

Clinically relevant mutations in core metabolic genes confer antibiotic resistance.

Although metabolism plays an active role in antibiotic lethality, antibiotic resistance is generally associated with drug target modification, enzymatic inactivation, and/or transport rather than metabolic processes. Evolution experiments of Escherichia coli rely on growth-dependent selection, which may provide a limited view of the antibiotic resistance landscape. We sequenced and analyzed E. coli adapted to representative antibiotics at increasingly heightened metabolic states. This revealed various underappreciated noncanonical genes, such as those related to central carbon and energy metabolism, which are implicated in antibiotic resistance. These metabolic alterations lead to lower basal respiration, which prevents antibiotic-mediated induction of tricarboxylic acid cycle activity, thus avoiding metabolic toxicity and minimizing drug lethality. Several of the identified metabolism-specific mutations are overrepresented in the genomes of >3500 clinical E. coli pathogens, indicating clinical relevance.

Predictive biology: modelling, understanding and harnessing microbial complexity.

Predictive biology is the next great chapter in synthetic and systems biology, particularly for microorganisms. Tasks that once seemed infeasible are increasingly being realized such as designing and implementing intricate synthetic gene circuits that perform complex sensing and actuation functions, and assembling multi-species bacterial communities with specific, predefined compositions. These achievements have been made possible by the integration of diverse expertise across biology, physics and engineering, resulting in an emerging, quantitative understanding of biological design. As ever-expanding multi-omic data sets become available, their potential utility in transforming theory into practice remains firmly rooted in the underlying quantitative principles that govern biological systems. In this Review, we discuss key areas of predictive biology that are of growing interest to microbiology, the challenges associated with the innate complexity of microorganisms and the value of quantitative methods in making microbiology more predictable.

Environmental and genetic determinants of plasmid mobility in pathogenic Escherichia coli.

Plasmids are key vehicles of horizontal gene transfer (HGT), mobilizing antibiotic resistance, virulence, and other traits among bacterial populations. The environmental and genetic forces that drive plasmid transfer are poorly understood, however, due to the lack of definitive quantification coupled with genomic analysis. Here, we integrate conjugative phenotype with plasmid genotype to provide quantitative analysis of HGT in clinical Escherichia coli pathogens. We find a substantial proportion of these pathogens (>25%) able to readily spread resistance to the most common classes of antibiotics. Antibiotics of varied modes of action had less than a 5-fold effect on conjugation efficiency in general, with one exception displaying 31-fold promotion upon exposure to macrolides and chloramphenicol. In contrast, genome sequencing reveals plasmid incompatibility group strongly correlates with transfer efficiency. Our findings offer new insights into the determinants of plasmid mobility and have implications for the development of treatments that target HGT.