The impact of bottlenecks on microbial survival, adaptation, and phenotypic switching in host-pathogen interactions

Adaptive evolution in asymptomatic host confers MDR Salmonella with enhanced environmental persistence and virulence

As a common cause for food-borne diseases, the Salmonella spp. are generally prevalent among livestock, whereby they are likely to be transmitted to human via environmental contamination. To explore the potential mechanism for prevalence of MDR Salmonella and its risk for dissemination via contaminated environments, we profiled the colonization dynamics of MDR Salmonella in chicken, herein we found that an adaptive evolution, driven by mutagenesis in a small protein-encoding gene (STM14_1829), conferred the multidrug resistant (MDR) Salmonella with increased fitness in asymptomatic host. Then the mechanistic study demonstrated that only one amino acid substitution in small protein STM14_1829 rendered MDR Salmonella capable to better invade and persist in phagocytotic cells by modulating bacterial flagella overexpression. Concerningly, the evolved Salmonella was also more resilient to the potential stressors generally found in environments and food processing, including heat, cold, adverse pH and oxidations. It implied that the evolved subpopulations are plausibly more persistent in environments once they contaminated through animal manure or human excreta. Moreover, the evolution promoted the pathogenesis caused by MDR Salmonella in susceptible hosts, resulting in higher risk for dissemination of pathogens via contaminated environments. Together, our data provided the novel insights into that in vivo adaptive evolution benefits Salmonella colonization, persistence and pathogenesis, by promoting bacterial tolerance via modulating flagella expression. These findings may explain the rationale behind the increasing prevalence of certain MDR Salmonella clones in livestock and associated environment, and underscoring the need for advanced strategies to tackle the possible evolution of such zoonotic pathogens.

Novel method for prediction of combinatorial phase-variable gene expression states

Short sequence repeat mediated phase variation results in diverse phenotype presentation in many bacteria including Campylobacter and Neisseria species. Current methods for identifying the expression states of phase-variable genes involve taking a high number of single colonies. This approach is subject to bias, sampling effects and high workloads that reduce the ability to perform intermediary sampling. The use of high concentration colony sweeps provides a work around but reduces the resolution of combinatorial expression profiles (termed phasotypes). A parsimonious approach combining both single colony and sweep data was developed to overcome these limitations. The critical methodological advance is the use of an algorithm that utilises the experimental data from the two sample types and a parsimonious, iterative mathematical analysis that outputs the phasotype distribution with the highest likelihood of underpinning the experimental data sets. The advantages of this unified method are increased resolution and accuracy of gene expression state combinations as compared to conventional single colony sampling, reduced requirement for sampling large numbers of colonies leading to reduced costs, and a higher capacity for collecting samples and replicates.•Inputting of sweep and single colony data into an algorithm for a rapid determination of the combinatorial phase variation states (phasotypes) for repeat-mediated phase-variable bacterial genes•This method reduces the number of single colony samples required to produce accurate estimates of phasotypes•This method will reduce the costs of phasotype analyses and increase potential to analyse more time points or sample sites leading to an improved understanding of how phase variation contributes to bacterial host persistence and the ability to cause disease.

Neisseria gonorrhoeae MtrCDE Efflux Pump During In Vivo Experimental Genital Tract Infection in Men and Mice Reveals the Presence of Within-Host Colonization Bottleneck

The MtrCDE efflux pump of Neisseria gonorrhoeae exports a wide range of antimicrobial compounds that the gonococcus encounters at mucosal surfaces during colonization and infection. Here, we evaluate the role of this efflux pump system in strain FA1090 in human male urethral infection with a Controlled Human Infection Model. Using the strategy of competitive multi-strain infection with wild-type FA1090 and an isogenic mutant strain that does not contain a functional MtrCDE pump, we found that the presence of the efflux pump during human experimental infection did not confer a competitive advantage. This finding is in contrast to previous findings in female mice, which demonstrated that gonococci of strain FA19 lacking a functional MtrCDE pump had a significantly reduced fitness compared to the wild type strain in the lower genital tract of female mice. We conducted competitive infections in female mice with FA19 and FA1090 strains, including mutants that do not assemble a functional Mtr efflux pump, demonstrating the fitness advantage provided byt the MtrCDE efflux pump during infection of mice is strain dependent. Our data indicate that new gonorrhea treatment strategies targeting the MtrCDE efflux pump functions may not be universally efficacious in naturally occurring infections. Owing to the equal fitness of FA1090 strains in men, our experiments unexpectedly demonstrated the likely presence of an early colonization bottleneck of N. gonorrhoeae in the human male urethra.

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Clinicaltrials.gov NCT03840811 .

The effect of bottleneck size on evolution in nested Darwinian populations

Previous work has shown how a minimal ecological structure consisting of patchily distributed resources and recurrent dispersal between patches can scaffold Darwinian properties onto collections of cells. When the timescale of dispersal is long compared with the time to consume resources, patch fitness increases but comes at a cost to cell growth rates. This creates conditions that initiate evolutionary transitions in individuality. A key feature of the scaffold is a bottleneck created during dispersal, causing patches to be founded by single cells. The bottleneck decreases competition within patches and, hence, creates a strong hereditary link at the level of patches. Here, we construct a fully stochastic model to investigate the effect of bottleneck size on the evolutionary dynamics of both cells and collectives. We show that larger bottlenecks simply slow the dynamics, but, at some point, which depends on the parameters of the within-patch model, the direction of evolution towards the equilibrium reverses. Introduction of random fluctuations in bottleneck sizes with some positive probability of smaller sizes counteracts this, even when the probability of smaller bottlenecks is minimal.

Preexisting Heterogeneity of Inducible Nitric Oxide Synthase Expression Drives Differential Growth of Mycobacterium tuberculosis in Macrophages

Mycobacterium tuberculosis infection is initiated by the inhalation and implantation of bacteria in the lung alveoli, where they are phagocytosed by macrophages. Even a single bacterium may be sufficient to initiate infection. Thereafter, the clinical outcome is highly variable between individuals, ranging from sterilization to active disease, for reasons that are not well understood. Here, we show that the rate of intracellular bacterial growth varies markedly between individual macrophages, and this heterogeneity is driven by cell-to-cell variation of inducible nitric oxide synthase (iNOS) activity. At the single-cell level, iNOS expression fluctuates over time, independent of infection or activation with gamma interferon. We conclude that chance encounters between individual bacteria and host cells randomly expressing different levels of an antibacterial gene can determine the outcome of single-cell infections, which may explain why some exposed individuals clear the bacteria while others develop progressive disease. IMPORTANCE In this report, we demonstrate that fluctuations in the expression of antimicrobial genes can define how single host cells control bacterial infections. We show that preexisting cell-to-cell variation in the expression of a single gene, that for inducible nitric oxide synthase, is sufficient to explain why some macrophages kill intracellular M. tuberculosis while others fail to control bacterial replication, possibly leading to disease progression. We introduce the concept that chance encounters between heterogeneous bacteria and host cells can determine the outcome of a host-pathogen interaction. This concept is particularly relevant for all the infectious diseases in which the number of interacting pathogens and host cells is small at some point during the infection.

Evolutionary history and strength of selection determine the rate of antibiotic resistance adaptation

Bacterial adaptation to stressful environments often produces evolutionary constraints whereby increases in resistance are associated with reduced fitness in a different environment. The exploitation of this resistance-cost trade-off has been proposed as the basis of rational antimicrobial treatment strategies designed to limit the evolution of drug resistance in bacterial pathogens. Recent theoretical, laboratory, and clinical studies have shown that fluctuating selection can maintain drug efficacy and even restore drug susceptibility, but can also increase the rate of adaptation and promote cross-resistance to other antibiotics. In this paper, we combine mathematical modeling, experimental evolution, and whole-genome sequencing to follow evolutionary trajectories towards β-lactam resistance under fluctuating selective conditions. Our experimental model system consists of eight populations of Escherichia coli K12 evolving in parallel to a serial dilution protocol designed to dynamically control the strength of selection for resistance. We implemented adaptive ramps with mild and strong selection, resulting in evolved populations with similar levels of resistance, but with different evolutionary dynamics and diverging genotypic profiles. We found that mutations that emerged under strong selection are unstable in the absence of selection, in contrast to resistance mutations previously selected in the mild selection regime that were stably maintained in drug-free environments and positively selected for when antibiotics were reintroduced. Altogether, our population dynamics model and the phenotypic and genomic analysis of the evolved populations show that the rate of resistance adaptation is contingent upon the strength of selection, but also on evolutionary constraints imposed by prior drug exposures.

Single cell variability of CRISPR-Cas interference and adaptation

While CRISPR-Cas defence mechanisms have been studied on a population level, their temporal dynamics and variability in individual cells have remained unknown. Using a microfluidic device, time-lapse microscopy and mathematical modelling, we studied invader clearance in Escherichia coli across multiple generations. We observed that CRISPR interference is fast with a narrow distribution of clearance times. In contrast, for invaders with escaping PAM mutations we found large cell-to-cell variability, which originates from primed CRISPR adaptation. Faster growth and cell division and higher levels of Cascade increase the chance of clearance by interference, while slower growth is associated with increased chances of clearance by priming. Our findings suggest that Cascade binding to the mutated invader DNA, rather than spacer integration, is the main source of priming heterogeneity. The highly stochastic nature of primed CRISPR adaptation implies that only subpopulations of bacteria are able to respond quickly to invading threats. We conjecture that CRISPR-Cas dynamics and heterogeneity at the cellular level are crucial to understanding the strategy of bacteria in their competition with other species and phages.

Refined Quantification of Infection Bottlenecks and Pathogen Dissemination with STAMPR

Pathogen population dynamics during infection are critical determinants of infection susceptibility and define patterns of dissemination. However, deciphering these dynamics, particularly founding population sizes in host organs and patterns of dissemination between organs, is difficult because measuring bacterial burden alone is insufficient to observe these patterns. Introduction of allelic diversity into otherwise identical bacteria using DNA barcodes enables sequencing-based measurements of these parameters, in a method known as STAMP (Sequence Tag-based Analysis of Microbial Populations). However, bacteria often undergo unequal expansion within host organs, resulting in marked differences in the frequencies of barcodes in input and output libraries. Here, we show that these differences confound STAMP-based analyses of founding population sizes and dissemination patterns. We present STAMPR, a successor to STAMP, which accounts for such population expansions. Using data from systemic infection of barcoded extraintestinal pathogenic E. coli, we show that this new framework, along with the metrics it yields, enhances the fidelity of measurements of bottlenecks and dissemination patterns. STAMPR was also validated on an independent barcoded Pseudomonas aeruginosa data set, uncovering new patterns of dissemination within the data. This framework (available at https://github.com/hullahalli/stampr_rtisan), when coupled with barcoded data sets, enables a more complete assessment of within-host bacterial population dynamics. IMPORTANCE Barcoded bacteria are often employed to monitor pathogen population dynamics during infection. The accuracy of these measurements is diminished by unequal bacterial expansion rates. Here, we develop computational tools to circumvent this limitation and establish additional metrics that collectively enhance the fidelity of measuring within-host pathogen founding population sizes and dissemination patterns. These new tools will benefit future studies of the dynamics of pathogens and symbionts within their respective hosts and may have additional barcode-based applications beyond host-microbe interactions.

Common Adaptive Strategies Underlie Within-Host Evolution of Bacterial Pathogens

Within-host adaptation is a hallmark of chronic bacterial infections, involving substantial genomic changes. Recent large-scale genomic data from prolonged infections allow the examination of adaptive strategies employed by different pathogens and open the door to investigate whether they converge toward similar strategies. Here, we compiled extensive data of whole-genome sequences of bacterial isolates belonging to miscellaneous species sampled at sequential time points during clinical infections. Analysis of these data revealed that different species share some common adaptive strategies, achieved by mutating various genes. Although the same genes were often mutated in several strains within a species, different genes related to the same pathway, structure, or function were changed in other species utilizing the same adaptive strategy (e.g., mutating flagellar genes). Strategies exploited by various bacterial species were often predicted to be driven by the host immune system, a powerful selective pressure that is not species specific. Remarkably, we find adaptive strategies identified previously within single species to be ubiquitous. Two striking examples are shifts from siderophore-based to heme-based iron scavenging (previously shown for Pseudomonas aeruginosa) and changes in glycerol-phosphate metabolism (previously shown to decrease sensitivity to antibiotics in Mycobacterium tuberculosis). Virulence factors were often adaptively affected in different species, indicating shifts from acute to chronic virulence and virulence attenuation during infection. Our study presents a global view on common within-host adaptive strategies employed by different bacterial species and provides a rich resource for further studying these processes.

Yeast Fermentate-Mediated Reduction of Salmonella Reading and Typhimurium in an in vitro Turkey Cecal Culture Model

Salmonella Reading is an ongoing public health issue in the turkey industry, leading to significant morbidity in humans in the United States. Pre-harvest intervention strategies that contribute to the reduction of foodborne pathogens in food animals, such as the yeast fermentation metabolites of Original XPCTM (XPC), may become the key to multi-hurdle farm to fork strategies. Therefore, we developed an anaerobic in vitro turkey cecal model to assess the effects of XPC on the ceca of commercial finisher tom turkeys fed diets void of XPC and antibiotics. Using the in vitro turkey cecal culture method, ceca were tested with and without XPC for their anti-Salmonella Reading and the previously defined anti-Typhimurium (ST97) effects. Ultimately, the anti-Salmonella effects were independent of serovar (P > 0.05). At 0 h post inoculation (hpi), Salmonella levels were equivalent between treatments at 7.3 Log10 CFU/mL, and at 24 hpi, counts in XPC were reduced by 5 Log10 CFU/mL, which was 2.1 Log10 lower than the control (P < 0.05). No differences in serovar prevalence existed (P > 0.05), with a 92% reduction in Salmonella positive XPC-treated ceca cultures by 48 hpi (P < 0.05). To evaluate changes to the microbiota independent of the immune response, the 16S rDNA was sequenced using the Illumina MiSeq platform. Data indicated a profound effect of time and treatment for the reduction of Salmonella irrespective of serovar. XPC sustained diversity metrics compared to the control, demonstrating a reduction in diversity over time (Q < 0.05).

Quantification of Brucella abortus population structure in a natural host

Cattle are natural hosts of the intracellular pathogen Brucella abortus, which inflicts a significant burden on the health and reproduction of these important livestock. The primary routes of infection in field settings have been described, but it is not known how the bovine host shapes the structure of B. abortus populations during infection. We utilized a library of uniquely barcoded B. abortus strains to temporally and spatially quantify population structure during colonization of cattle through a natural route of infection. Introducing 10⁸ bacteria from this barcoded library to the conjunctival mucosa resulted in expected levels of local lymph node colonization at a 1-wk time point. We leveraged variance in strain abundance in the library to demonstrate that only 1 in 10,000 brucellae introduced at the site of infection reached a parotid lymph node. Thus, cattle restrict the overwhelming majority of B. abortus introduced via the ocular conjunctiva at this dose. Individual strains were spatially restricted within the host tissue, and the total B. abortus census was dominated by a small number of distinct strains in each lymph node. These results define a bottleneck that B. abortus must traverse to colonize local lymph nodes from the conjunctival mucosa. The data further support a model in which a small number of spatially isolated granulomas founded by unique strains are present at 1 wk postinfection. These experiments demonstrate the power of barcoded transposon tools to quantify infection bottlenecks and to define pathogen population structure in host tissues.

Bottleneck size and selection level reproducibly impact evolution of antibiotic resistance

During antibiotic treatment, the evolution of bacterial pathogens is fundamentally affected by bottlenecks and varying selection levels imposed by the drugs. Bottlenecks-that is, reductions in bacterial population size-lead to an increased influence of random effects (genetic drift) during bacterial evolution, and varying antibiotic concentrations during treatment may favour distinct resistance variants. Both aspects influence the process of bacterial evolution during antibiotic therapy and thereby treatment outcome. Surprisingly, the joint influence of these interconnected factors on the evolution of antibiotic resistance remains largely unexplored. Here we combine evolution experiments with genomic and genetic analyses to demonstrate that bottleneck size and antibiotic-induced selection reproducibly impact the evolutionary path to resistance in pathogenic Pseudomonas aeruginosa, one of the most problematic opportunistic human pathogens. Resistance is favoured-expectedly-under high antibiotic selection and weak bottlenecks, but-unexpectedly-also under low antibiotic selection and severe bottlenecks. The latter is likely to result from a reduced probability of losing favourable variants through drift under weak selection. Moreover, the absence of high resistance under low selection and weak bottlenecks is caused by the spread of low-resistance variants with high competitive fitness under these conditions. We conclude that bottlenecks, in combination with drug-induced selection, are currently neglected key determinants of pathogen evolution and outcome of antibiotic treatment.

Selective and non-selective bottlenecks as drivers of the evolution of hypermutable bacterial loci

Bottlenecks reduce the size of the gene pool within populations of all life forms with implications for their subsequent survival. Here, we examine the effects of bottlenecks on bacterial commensal-pathogens during transmission between, and dissemination within, hosts. By reducing genetic diversity, bottlenecks may alter individual or population-wide adaptive potential. A diverse range of hypermutable mechanisms have evolved in infectious agents that allow for rapid generation of genetic diversity in specific genomic loci as opposed to the variability arising from increased genome-wide mutation rates. These localised hypermutable mechanisms include multi-gene phase variation (PV) of outer membrane components, multi-allele PV of restriction systems and recombination-driven antigenic variation. We review selected experimental and theoretical (mathematical) models pertaining to the hypothesis that localised hypermutation (LH) compensates for fitness losses caused by bottlenecks and discuss whether bottlenecks have driven the evolution of hypermutable loci.

Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments

Nongenetic phenotypic variation can either speed up or slow down adaptive evolution. We show that it can speed up evolution in environments where available carbon and energy sources change over time. To this end, we use an experimentally validated model of Escherichia coli growth on two alternative carbon sources, glucose and acetate. On the superior carbon source (glucose), all cells achieve high growth rates, while on the inferior carbon source (acetate) only a small fraction of the population manages to initiate growth. Consequently, populations experience a bottleneck when the environment changes from the superior to the inferior carbon source. Growth on the inferior carbon source depends on a circuit under the control of a transcription factor that is repressed in the presence of the superior carbon source. We show that noise in the expression of this transcription factor can increase the probability that cells start growing on the inferior carbon source. In doing so, it can decrease the severity of the bottleneck and increase mean population fitness whenever this fitness is low. A modest amount of noise can also enhance the fitness effects of a beneficial allele that increases the fraction of a population initiating growth on acetate. Additionally, noise can protect this allele from extinction, accelerate its spread, and increase its likelihood of going to fixation. Central to the adaptation-enhancing principle we identify is the ability of noise to mitigate population bottlenecks, particularly in environments that fluctuate periodically. Because such bottlenecks are frequent in fluctuating environments, and because periodically fluctuating environments themselves are common, this principle may apply to a broad range of environments and organisms.

Meningococcal core and accessory phasomes vary by clonal complex

Neisseria meningitidis is a Gram-negative human commensal pathogen, with extensive phenotypic plasticity afforded by phase-variable (PV) gene expression. Phase variation is a stochastic switch in gene expression from an ON to an OFF state, mediated by localized hypermutation of simple sequence repeats (SSRs). Circulating N. meningitidis clones vary in propensity to cause disease, with some clonal complexes (ccs) classified as hypervirulent and others as carriage-associated. We examined the PV gene repertoires, or phasome, of these lineages in order to determine whether phase variation contributes to disease propensity. We analysed 3328 genomes representative of nine circulating meningococcal ccs with PhasomeIt, a tool that identifies PV genes by the presence of SSRs and homologous gene clusters. The presence, absence and functions of all identified PV gene clusters were confirmed by annotation or blast searches within the Neisseria PubMLST database. While no significant differences were detected in the number of PV genes or the core, conserved phasome content between hypervirulent and carriage lineages, individual ccs exhibited major variations in PV gene numbers. Phylogenetic clusters produced by phasome or core genome analyses were similar, indicating co-evolution of PV genes with the core genome. While conservation of PV clusters is high, with 76 % present in all meningococcal isolates, maintenance of an SSR is variable, ranging from conserved in all isolates to present only in a single cc, indicating differing evolutionary trajectories for each lineage. Diverse functional groups of PV genes were present across the meningococcal lineages; however, the majority directly or indirectly influence bacterial surface antigens and could impact on future vaccine development. Finally, we observe that meningococci have open pan phasomes, indicating ongoing evolution of PV gene content and a significant potential for adaptive changes in this clinically relevant genus.

The Effect of Population Bottleneck Size and Selective Regime on Genetic Diversity and Evolvability in Bacteria

Population bottlenecks leading to a drastic reduction of the population size are common in the evolutionary dynamics of natural populations; their occurrence is known to have implications for genome evolution due to genetic drift, the consequent reduction in genetic diversity, and the rate of adaptation. Nevertheless, an empirical characterization of the effect of population bottleneck size on evolutionary dynamics of bacteria is currently lacking. In this study, we show that selective conditions have a stronger effect on the evolutionary history of bacteria in comparison to population bottlenecks. We evolved Escherichia coli populations under three different population bottleneck sizes (small, medium, and large) in two temperature regimes (37 °C and 20 °C). We find a high genetic diversity in the large in comparison to the small bottleneck size. Nonetheless, the cold temperature led to reduced genetic diversity regardless the bottleneck size; hence, the temperature has a stronger effect on the genetic diversity in comparison to the bottleneck size. A comparison of the fitness gain among the evolved populations reveals a similar pattern where the temperature has a significant effect on the fitness. Our study demonstrates that population bottlenecks are an important determinant of bacterial evolvability; their consequences depend on the selective conditions and are best understood via their effect on the standing genetic variation.

Shortsighted Evolution Constrains the Efficacy of Long-Term Bet Hedging

To survive unpredictable environmental change, many organisms adopt bet-hedging strategies that are initially costly but provide a long-term fitness benefit. The temporal extent of these deferred fitness benefits determines whether bet-hedging organisms can survive long enough to realize them. In this article, we examine a model of microbial bet hedging in which there are two paths to extinction: unpredictable environmental change and demographic stochasticity. In temporally correlated environments, these drivers of extinction select for different switching strategies. Rapid phenotype switching ensures survival in the face of unpredictable environmental change, while slower-switching organisms become extinct. However, when both switching strategies are present in the same population, then demographic stochasticity-enforced by a limited population size-leads to extinction of the faster-switching organism. As a result, we find a novel form of evolutionary suicide whereby selection in a fluctuating environment can favor bet-hedging strategies that ultimately increase the risk of extinction. Population structures with multiple subpopulations and dispersal can reduce the risk of extinction from unpredictable environmental change and shift the balance so as to facilitate the evolution of slower-switching organisms.

Mutation and Selection in Bacteria: Modelling and Calibration

Temporal evolution of a clonal bacterial population is modelled taking into account reversible mutation and selection mechanisms. For the mutation model, an efficient algorithm is proposed to verify whether experimental data can be explained by this model. The selection–mutation model has unobservable fitness parameters, and, to estimate them, we use an Approximate Bayesian Computation algorithm. The algorithms are illustrated using in vitro data for phase variable genes of Campylobacter jejuni.

Random Genetic Drift and Selective Pressures Shaping the Blattabacterium Genome

Estimates suggest that at least half of all extant insect genera harbor obligate bacterial mutualists. Whereas an endosymbiotic relationship imparts many benefits upon host and symbiont alike, the intracellular lifestyle has profound effects on the bacterial genome. The obligate endosymbiont genome is a product of opposing forces: genes important to host survival are maintained through physiological constraint, contrasted by the fixation of deleterious mutations and genome erosion through random genetic drift. The obligate cockroach endosymbiont, Blattabacterium - providing nutritional augmentation to its host in the form of amino acid synthesis - displays radical genome alterations when compared to its most recent free-living relative Flavobacterium. To date, eight Blattabacterium genomes have been published, affording an unparalleled opportunity to examine the direction and magnitude of selective forces acting upon this group of symbionts. Here, we find that the Blattabacterium genome is experiencing a 10-fold increase in selection rate compared to Flavobacteria. Additionally, the proportion of selection events is largely negative in direction, with only a handful of loci exhibiting signatures of positive selection. These findings suggest that the Blattabacterium genome will continue to erode, potentially resulting in an endosymbiont with an even further reduced genome, as seen in other insect groups such as Hemiptera.