Fitness Consequences Research Articles

Evolutionary rescue of bacterial populations by heterozygosity on multicopy plasmids

Bacterial plasmids and other extrachromosomal DNA elements frequently carry genes with important fitness effects for their hosts. Multicopy plasmids can additionally carry distinct alleles of host-fitness-relevant genes on different plasmid copies, allowing for heterozygosity not possible for loci on haploid chromosomes. Plasmid-mediated heterozygosity may increase the fitness of bacterial cells in circumstances where there is an advantage to having multiple distinct alleles (heterozyogote advantage); however, plasmid-mediated heterozygosity is also subject to constant loss due to random segregation of plasmid copies on cell division. We analyze a multitype branching process model to study the evolution and maintenance of plasmid-mediated heterozygosity under a heterozygote advantage. We focus on an evolutionary rescue scenario in which a novel mutant allele on a plasmid must be maintained together with the wild-type allele to allow population persistance (although our results apply more generally to the maintenance of heterozygosity due to heterozygote advantage). We determine the probability of rescue and derive an analytical expression for the threshold on the fitness of heterozygotes required to overcome segregation and make rescue possible; this threshold decreases with increasing plasmids copy number. We further show that the formation of cointegrates from the fusion of plasmid copies increases the probability of rescue. Overall, our results provide a rigorous quantitative assessment of the conditions under which bacterial populations can adapt to multiple stressors through plasmid-mediated heterozygosity. Many of the results are furthermore applicable to the related problem of the maintenance of incompatible plasmids in the same cell under selection for both.

Diagnosis of Wind Turbine Yaw System Based on Self-Attention–Long Short-Term Memory (LSTM)

Addressing the challenges and significant risks associated with diagnosing faults in wind turbine yaw systems, along with the typically low diagnostic accuracy, this study introduces a Long Short-Term Memory (LSTM) neural network augmented by a self-attention mechanism (SAM) as a novel fault diagnosis technique for wind turbine yaw systems. The method integrates the automatic weighting capability of the self-attention mechanism on input features with the advantage of LSTM in processing time series data, thereby effectively capturing key information and long-term dependencies in the operating data of the yawing system. This combination enhances the accuracy of fault feature extraction to more accurately identify various types of fault modes within the yawing system. Six types of feature parameters are extracted from the raw data collected by the SCADA (Supervisory Control And Data Acquisition) system of the wind turbine and are utilized as inputs for the diagnostic model. These parameters are then fed into the self-attention–LSTM neural network model to diagnose the health status of the yaw system, including yaw bearing damage, yaw gearbox failure, yaw motor failure, and sensor failure. The experimental results demonstrate that the accuracy of LSTM fault diagnosis, when enhanced with the self-attention mechanism, can reach 98.67% with an appropriate amount of training samples, verifying its significant advantages in terms of accuracy and stability of fault diagnosis. The proposed fault diagnosis method exhibits a better model fitting effect, strong generalization ability, and high accuracy compared to other methods, providing robust support for the reliable operation and maintenance of wind turbines.

Predicting hearing aids outcomes using machine learning.

Introduction The aim of this study is to measure the effectiveness of hearing aid fitting in improving understanding in quiet and in noise, and to investigate the factors that significantly influence these results. This study will be carried out through a retrospective analysis of the results obtained from patients fitted with hearing aids at hearing-aid centers between 2018 and 2021. This study explores and classifies the predictive factors of patient outcomes, looking at the impact of the choice of hearing aid technology (category level), the personalized adjustments made by the hearing care professional (amplification level, binaural loudness balancing) and the patient follow-up and daily use (data logging). Methods Hearing impaired people were fitted in hearing-aid centers from 2018 to 2021. This included 77,661 patients. In the first part of the study, the data are statistically analyzed, and various correlations are studied. Then, machine learning and feature explanatory algorithms are used for prediction, in particular, a neural network based on PyTorch and the eXtreme Gradient Boosting (XGBoost). For explanatory power, the SHapley Additive exPlanation (SHAP) method was used to evaluate the individual contribution of each variable. Results Using predictive models (SHAP value and XGBoost), the effect of technology level on Speech Perception In Noise (SPIN) and Speech Perception In Quiet (SPIQ) scores is significant, and binaural loudness compensation is significant for improving test results by the same amount. Finally, linear relationships were found between the initial Speech Noise Ratio (SNR) and the adjusted SNR, as well as for the Speech Recognition Threshold (SRT). Finally, the effect of wearing hearing aids for more than 9 hours per day was analyzed and resulted in better recovery. This is a retrospective study. This bias is compensated by the large amount of data. Conclusion Big data analysis is a new method to evaluate predictive factors for hearing aid outcomes.

Nonlinear associations of the hs-CRP/HDL-C index with metabolic dysfunction-associated steatotic liver disease and advanced liver fibrosis in US adults: insights from NHANES 2017–2018

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a globally widespread chronic liver condition that may progress to severe liver diseases, including advanced liver fibrosis. The high-sensitivity C-reactive protein-to-high-density lipoprotein cholesterol (hs-CRP/HDL-C) index may be a potential indicator for MASLD and advanced liver fibrosis, given its relevance to inflammation and plasma lipids. In this study, the hs-CRP/HDL-C index was investigated in relation to prevalent MASLD and advanced liver fibrosis. The study analyzed secondary data from the National Health and Nutrition Examination Survey (NHANES) 2017–2018 database. The hs-CRP/HDL-C index was calculated by the quotient of hs-CRP and HDL-C. Multiple logistic regression models, Cochran-Armitage trend tests, smooth curve fitting, threshold effect analyses, and stratified analyses were used to evaluate whether the hs-CRP/HDL-C index associated with MASLD and advanced liver fibrosis. The study cohort comprised 3684 participants, of whom 1268 (34.42%) were diagnosed with MASLD and 156 (12.28%) with advanced liver fibrosis. Logistic analyses adjusted for covariates revealed positive associations of the hs-CRP/HDL-C index with MASLD and advanced liver fibrosis, consistent across all subgroups. Smooth curve fitting and threshold effect analyses revealed nonlinear relationships of hs-CRP/HDL-C index with MASLD and advanced liver fibrosis, with inflection points at 0.8 for MASLD and 1.2 for advanced liver fibrosis. Additionally, significant interactions were observed between MASLD and covariates such as gender, smoking status, chronic kidney disease (CKD), and cancer. Similarly, the hs-CRP/HDL-C index exhibited positive correlations with advanced liver fibrosis across diverse subgroups, with notable interactions related to cancer. MASLD and advanced liver fibrosis were associated with hs-CRP/HDL-C index, indicating its potential utility as a clinical marker for these conditions.

Template switching during DNA replication is a prevalent source of adaptive gene amplification

Copy number variants (CNVs) are an important source of genetic variation underlying rapid adaptation and genome evolution. Whereas point mutation rates vary with genomic location and local DNA features, the role of genome architecture in the formation and evolutionary dynamics of CNVs is poorly understood. Previously, we found the GAP1 gene in Saccharomyces cerevisiae undergoes frequent amplification and selection in glutamine-limitation. The gene is flanked by two long terminal repeats (LTRs) and proximate to an origin of DNA replication (autonomously replicating sequence, ARS), which likely promote rapid GAP1 CNV formation. To test the role of these genomic elements on CNV-mediated adaptive evolution, we evolved engineered strains lacking either the adjacent LTRs, ARS, or all elements in glutamine-limited chemostats. Using a CNV reporter system and neural network simulation-based inference (nnSBI) we quantified the formation rate and fitness effect of CNVs for each strain. Removal of local DNA elements significantly impacts the fitness effect of GAP1 CNVs and the rate of adaptation. In 177 CNV lineages, across all four strains, between 26% and 80% of all GAP1 CNVs are mediated by Origin Dependent Inverted Repeat Amplification (ODIRA) which results from template switching between the leading and lagging strand during DNA synthesis. In the absence of the local ARS, distal ones mediate CNV formation via ODIRA. In the absence of local LTRs, homologous recombination can mediate gene amplification following de novo retrotransposon events. Our study reveals that template switching during DNA replication is a prevalent source of adaptive CNVs.

Template switching during DNA replication is a prevalent source of adaptive gene amplification.

Copy number variants (CNVs) are an important source of genetic variation underlying rapid adaptation and genome evolution. Whereas point mutation rates vary with genomic location and local DNA features, the role of genome architecture in the formation and evolutionary dynamics of CNVs is poorly understood. Previously, we found the GAP1 gene in Saccharomyces cerevisiae undergoes frequent amplification and selection in glutamine-limitation. The gene is flanked by two long terminal repeats (LTRs) and proximate to an origin of DNA replication (autonomously replicating sequence, ARS), which likely promote rapid GAP1 CNV formation. To test the role of these genomic elements on CNV-mediated adaptive evolution, we evolved engineered strains lacking either the adjacent LTRs, ARS, or all elements in glutamine-limited chemostats. Using a CNV reporter system and neural network simulation-based inference (nnSBI) we quantified the formation rate and fitness effect of CNVs for each strain. Removal of local DNA elements significantly impacts the fitness effect of GAP1 CNVs and the rate of adaptation. In 177 CNV lineages, across all four strains, between 26% and 80% of all GAP1 CNVs are mediated by Origin Dependent Inverted Repeat Amplification (ODIRA) which results from template switching between the leading and lagging strand during DNA synthesis. In the absence of the local ARS, distal ones mediate CNV formation via ODIRA. In the absence of local LTRs, homologous recombination can mediate gene amplification following de novo retrotransposon events. Our study reveals that template switching during DNA replication is a prevalent source of adaptive CNVs.

Inferring demographic and selective histories from population genomic data using a two-step approach in species with coding-sparse genomes: an application to human data.

The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

The effects of age, fitness, and health on the passive stiffness of the intact low back and its impact on seated work in a healthy, working, female population

Age is associated with increased tissue stiffness and a higher risk of low back pain, particularly in older, sedentary workers who spend long periods sitting. This study explored how trunk stiffness changes with age and its relationship with posture during prolonged sitting in a sample of 37 women aged 20–65 years. Age was assessed as both Chronological Age and Fitness Age, with trunk stiffness measured using a passive trunk flexion apparatus. Participants sat at a computer workstation for 60 minutes, and spine posture was recorded every 10 minutes. The study found that trunk stiffness significantly increased with age, especially when considering Fitness Age (r = 0.517, p = 0.003). Additionally, trunk stiffness was negatively correlated with spine motion during sitting (r = −0.435, p = 0.023). These findings suggest that workers with poorer health move less while sitting and could be more susceptible to the deleterious effects of sedentary work.

Variable stressor exposure shapes fitness within and across generations

Environmental variation has long been considered a key driver of evolutionary change, predicted to shape different strategies, such as genetic specialization, plasticity, or bet-hedging to maintain fitness. However, little evidence is available with regards to how the periodicity of stressors may impact fitness across generations. To address this gap, I conducted a reciprocal split-brood experiment using the freshwater crustacean, Daphnia magna, and an ecologically relevant environmental stressor, ultraviolet radiation (UVR). I exposed one group to constant and another group to fluctuating UVR conditions. Despite receiving the same dose of UVR, the first experimental generation displayed significant treatment-by-genotype interactions with respect to survival and reproductive output, as well as a delayed reproductive maturity under fluctuating UVR conditions. In the following experimental generation individuals exposed to fluctuating UVR exhibited higher fitness than those in a constant UVR regime. The ancestral conditions, i.e., maternal environment, however affected the survival probability and reproductive output, but did not significantly influence the maturation date. Overall, I demonstrate that the delivery of a stressor, not just its intensity, can have profound fitness consequences across generations, with important implications for seasonal succession of genotype–phenotype patterns in natural environments.

Functional innovation through new genes as a general evolutionary process.

In the past decade, our understanding of how new genes originate in diverse organisms has advanced substantially, and more than a dozen molecular mechanisms for generating initial gene structures were identified, in addition to gene duplication. These new genes have been found to integrate into and modify pre-existing gene networks primarily through mutation and selection, revealing new patterns and rules with stable origination rates across various organisms. This progress has challenged the prevailing belief that new proteins evolve from pre-existing genes, as new genes may arise de novo from noncoding DNA sequences in many organisms, with high rates observed in flowering plants. New genes have important roles in phenotypic and functional evolution across diverse biological processes and structures, with detectable fitness effects of sexual conflict genes that can shape species divergence. Such knowledge of new genes can be of translational value in agriculture and medicine.

Nonlinear association between liver fat content and lumbar bone mineral density in overweight and obese individuals: evidence from a large-scale health screening data in China.

The impact of fatty liver disease on lumbar bone mineral density (BMD) represents an intriguing area of study, particularly in light of established research linking obesity to bone metabolism. However, there remains limited investigation into the correlation between quantifying liver fat content (LFC) and lumbar BMD among overweight and obese populations, particularly within the Chinese demographic. This study aims to accurately quantify LFC and investigate its association with lumbar BMD in overweight or obese individuals. This cross-sectional study was conducted at the Health Management Center of Henan Provincial People's Hospital from January 2019 to February 2023, involving 6996 participants with a body mass index (BMI) of 24 kg/m² or higher. LFC and lumbar BMD were assessed using computed tomography. The study utilized one-way ANOVA, subgroup analysis, multifactor regression analysis, smooth curve fitting, and threshold and saturation effect analysis to explore the relationship between LFC and lumbar BMD. Furthermore, inflammatory cell analysis was included to investigate the potential mediating role of inflammatory cells in the association between LFC and lumbar BMD. After adjusting for confounding variables, multivariate regression analysis revealed a significant negative association between LFC and lumbar BMD (β = -0.323, 95% CI: -0.464 to -0.183, P < 0.001). Particularly, participants in the highest baseline LFC quartile (Q4 group) exhibited a more pronounced negative impact on lumbar BMD compared to those in the lowest quartile (Q1 group) (β = -5.026, 95% CI: -7.040 to -3.012, P < 0.001). Threshold saturation effect analysis identified a turning point in the LFC-BMD relationship (K = 5.4). Below this point, LFC showed a positive correlation with lumbar BMD (β = 0.962, 95% CI: 0.016-1.907, P < 0.05), whereas above it, LFC was significantly negatively correlated with lumbar BMD (β = -0.405, 95% CI: -0.558 to -0.253, P < 0.001). Additionally, mediation analysis indicated that leukocytes and monocytes potentially mediated the association between LFC and lumbar BMD, with mediation ratios of -5.78 and -6.68%, respectively. Among individuals categorized as overweight or obese, elevated levels of LFC were associated with reduced lumbar BMD, particularly noticeable above a threshold of 5.4%. Additionally, various types of inflammatory cells are presumed to exert a substantial mediating influence on the correlation between LFC and lumbar BMD.

Non-linear relationship between urinary creatinine and diabetic kidney disease: implications for clinical practice

ObjectiveThis study aims to investigate the relationship between urinary creatinine (UCr) and the risk and severity of Diabetic Kidney Disease (DKD) in patients with Type 2 Diabetes Mellitus (T2DM). The goal is to establish UCr as a potential biomarker for early DKD detection and severity assessment.MethodsA retrospective cross-sectional analysis was conducted using medical records of T2DM patients. Patients were classified into groups with and without DKD, and relevant clinical data, including demographic, blood, and urine parameters, were collected. Logistic regression and receiver operating characteristic (ROC) curve analysis evaluated the association between UCr levels and DKD. Curve fitting and threshold effect model were used to further evaluate the relationship between UCr and the incidence and severity of DKD.ResultsA total of 302 T2DM patients were analyzed, with 137 diagnosed with DKD. Significant differences in clinical parameters were observed between the DKD and non-DKD groups, particularly in UCr, urine albumin levels, and eGFR. UCr levels demonstrated a strong association with DKD. Moreover, a non-linear relationship was identified, with specific inflection points indicating different correlation patterns of UCr with DKD occurrence and progression.ConclusionThe findings of this study highlight the potential of UCr as a valuable biomarker for early detection and assessment of DKD in T2DM patients. Incorporating UCr measurements into routine clinical practice could enhance early identification of patients at risk for kidney complications, leading to timely intervention and improved patient outcomes.

Phenotypic and fitness consequences of plasticity in the rhythmic replication of malaria parasites.

The environments that parasites experience within hosts change dramatically over 24 h. How rhythms shape host-parasite-vector interactions is poorly understood owing to the challenges of disentangling the roles of rhythms of multiple interacting species in the context of the complex lifecycles of parasites. Using canonical circadian clock-disrupted hosts, we probe the limits of flexibility in the rhythmic replication of malaria (Plasmodium) parasites and quantify the consequences for fitness proxies of both parasite and host. We reveal that parasites alter the duration of their replication rhythm to resonate with host rhythms that have short (21 h) daily T-cycles as accurately as when infecting hosts with 24 h cycles, but appear less capable of extending their replication rhythm in hosts with long (27 h) cycles. Despite matching the period of short T-cycle hosts, parasites are unable to lock to the correct phase, likely leading to lower within-host productivity and a reduction in transmission potential. However, parasites in long T-cycle hosts do not experience substantial fitness costs. Furthermore, T-cycle duration does not affect disease severity in clock-disrupted hosts. Understanding the rhythmic replication of malaria parasites offers the opportunity to interfere with parasite timing to improve health and reduce transmission.This article is part of the Theo Murphy meeting issue issue 'Circadian rhythms in infection and immunity'.

Association of anxiety status and anxiety duration with constipation in adult Americans: a cross-sectional study using data from the NHANES 2007–2010

BackgroundConstipated patients may exhibit anxious behaviors, but the relationship between the two remains unclear. This population-based study aims to investigate the relationships of anxiety status and anxiety duration with constipation among U.S. adults.MethodsUsing data from the National Health and Nutrition Examination Survey (NHANES) database spanning from 2007 to 2010, a cross-sectional study included 8945 participants was performed to assess the relationships of anxiety status and anxiety duration with constipation. Participants’ characteristics were presented using mean or proportion. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using multivariable logistic regression models. The analysis accounted for potential confounding factors, including gender, age, race/ethnicity, education level, marital status, PIR, BMI, smoking status, drinking status, chronic diseases, and dietary intake. Subgroup analyses were conducted to ensure the stability of the results. Smoothed curve fitting was applied to investigate both linear and nonlinear associations between anxiety duration and constipation risk. Threshold effects were assessed using two-piecewise linear regression models.ResultsOf the 8945 participants, 922 reported constipation, with a prevalence of 10.3%. After adjusting for confounding factors, individuals with anxiety status exhibited an increased risk of constipation (OR: 1.49, 95% CI: 1.28–1.73). Stratified analyses indicated that the association between anxiety status and constipation remained relatively stable across different stratification levels. Smoothed curve fitting and threshold effect analyses revealed a linear association between anxiety duration and constipation among adults aged 20–60, while a nonlinear inverted U-shaped relationship was observed in those aged 60 and older, with an inflection point at 10 days. The two variables correlated positively on the left side of the inflection point but not on the right.ConclusionThis study showed that a significant association between anxiety status and constipation among U.S. adults. Additionally, an age-dependent association between anxiety duration and constipation was observed, particularly among individuals aged 60 and older.

Inference of the demographic histories and selective effects of human gut commensal microbiota over the course of human history.

Despite the importance of gut commensal microbiota to human health, there is little knowledge about their evolutionary histories, including their demographic histories and distributions of fitness effects (DFE) of mutations. Here, we infer the demographic histories and DFEs for amino-acid changing mutations of 39 of the most prevalent and abundant commensal gut microbial species found in Westernized individuals over timescales exceeding human generations. Some species display contractions in population size and others expansions, with several of these events coinciding with several key historical moments in human history. DFEs across species vary from highly to mildly deleterious, with differences between accessory and core gene DFEs largely driven by genetic drift. Within genera, DFEs tend to be more congruent, reflective of underlying phylogenetic relationships. Together, these findings suggest that gut microbes have distinct demographic and selective histories.

Sleep-disordered breathing and cardiometabolic and inflammatory markers in children with overweight/obesity: The role of cardiorespiratory fitness.

To investigate the association of sleep-disordered breathing (SDB) severity with cardiometabolic and inflammatory markers independently of the adiposity levels; and to explore the role of cardiorespiratory fitness in these associations in children with overweight/obesity. A total of 109 children aged 8-11 years with overweight/obesity were included in this cross-sectional study. SDB was assessed using a scale of the reduce version of the Paediatric Sleep Questionnaire. Cardiometabolic markers included fasting blood lipids biomarkers (i.e., low- and high-density lipoprotein cholesterol, and triglycerides), blood pressure, insulin, glucose, and the homeostatic model assessment index. Inflammatory markers (i.e., interleukin-6, interleukin-1β, C-reactive protein [CRP], and tumour necrosis factor alpha) were analysed. Cardiorespiratory fitness was assessed by the 20 m shuttle-run test. No significant associations were found between SDB severity and most of the cardiometabolic markers after correcting for adiposity and multiple comparisons (all p's >0.05). SDB severity was positively related to CRP (β = 0.352, p = 0.002), yet not with the remaining inflammatory markers analysed. The interaction effect of cardiorespiratory fitness presented a positive trend in the association of SDB with CRP (p = 0.1). When stratified analyses by cardiorespiratory fitness levels were conducted, a positive relation was found between SDB and CRP in the low cardiorespiratory fitness group (β = 0.465, p = 0.014), but not in the high cardiorespiratory fitness group (β = 0.236, p = 0.108). SDB severity was positively associated with CRP independently of the adiposity levels, but not with other inflammatory or cardiometabolic risk factors in children with overweight/obesity. Moreover, our results suggest that higher levels of cardiorespiratory fitness may attenuate the adverse effect of SDB severity on systematic inflammation in children with overweight/obesity.

Gut Competition Dynamics of Live Bacterial Therapeutics Are Shaped by Microbiome Complexity, Diet, and Therapeutic Transgenes.

Competitive exclusion is conventionally believed to prevent the establishment of a secondary strain of the same bacterial species in the gut microbiome, raising concerns for the deployment of live bacterial therapeutics (LBTs), especially if the bacterial chassis is a strain native to the gut. In this study, we investigated factors influencing competition dynamics in the murine gut using isogenic native Escherichia coli strains. We found that competition outcomes are context-dependent, modulated by microbiome complexity, LBT transgene expression, intestinal inflammation, and host diet. Furthermore, we demonstrated that native LBTs can establish long-term engraftment in the gut alongside a parental strain, with transgene-associated fitness effects influencing competition. We identified various interventions, including strategic dosing and dietary modulation, that significantly enhanced LBT colonization levels by 2 to 3 orders of magnitude. These insights provide a framework for optimizing LBT engraftment and efficacy, supporting their potential translation for human therapeutic applications.

When Brands Don’t Practice What They Preach: A Proposed Model of the Effects of Brand Hypocrisy and Brand-Cause Fit on Women’s Responses to Femvertisements

Given the uptick in brands employing femvertisements, it is important to better understand factors that influence the success of these campaigns. Research shows that brands with female target markets reap greater rewards from femvertising due to high brand–cause fit. Brands that femvertise and “practice what they preach” by supporting women’s causes more holistically likely have greater outcomes relative to other brands with actions that suggest hypocrisy, such as when their corporate practices do not support their advertised claims. This study proposes a model of women’s responses to femvertisements that examines how two situational brand factors, brand–cause fit and brand hypocrisy (or say–do fit), impact perceived brand hypocrisy, brand authenticity, brand credibility, and brand trust. The model is tested through two studies with a sample size of 353 and 292 participants). Results suggest that consumers perceive brands with low say–do fit as hypocritical, resulting in negative effects on brand trust, credibility, and authenticity, which in turn affects brand attitudes. Among those brands with low say–do fit, high brand–cause fit may act as a buffer because consumers see such brands as less hypocritical than those with low brand–cause fit. Managerial implications are addressed herein, as well as contributions to the literature. Study limitations are noted, and directions for future research are presented.

Assessing spacer acquisition rates in E. coli type I-E CRISPR arrays.

CRISPR/Cas is an adaptive defense mechanism protecting prokaryotes from viruses and other potentially harmful genetic elements. Through an adaptation process, short "spacer" sequences, captured from these elements and incorporated into a CRISPR array, provide target specificity for the immune response. CRISPR arrays and array expansion are also central to many emerging biotechnologies. The rates at which spacers integrate into native arrays within bacterial populations have not been quantified. Here, we measure naïve spacer acquisition rates in Escherichia coli Type I-E CRISPR, identify factors that affect these rates, and model this process fundamental to CRISPR/Cas defense. Prolonged Cas1-Cas2 expression produced fewer new spacers per cell on average than predicted by the model. Subsequent experiments revealed that this was due to a mean fitness reduction linked to array-expanded populations. In addition, the expression of heterologous non-homologous end-joining DNA-repair genes was found to augment spacer acquisition rates, translating to enhanced phage infection defense. Together, these results demonstrate the impact of intracellular factors that modulate spacer acquisition and identify an intrinsic fitness effect associated with array-expanded populations.

Understanding the influence of ride-sharing value on consumers’ continuance intention

PurposeThis study aims to understand the mechanism by which the value of ride-sharing services influences consumers’ continuance intention.Design/methodology/approachThe authors collected data from 484 Chinese ride-sharing respondents and analyzed them using partial least squares structural equation modeling.FindingsThe results show that hedonic value, social connection value and environmental value positively affect consumers’ cognitive fit and emotional fit, while utilitarian value has no significant effect on either cognitive fit or emotional fit. In addition, both cognitive fit and emotional fit significantly affect consumers’ satisfaction and continuance intention. Furthermore, satisfaction mediates the effects of cognitive and emotional fit on continuance intention.Practical implicationsRide-sharing practitioners should have a clear understanding of all the value dimensions of ride-sharing services, which would subsequently increase customers’ continuance intention.Originality/valueThis study defines and divides the dimensions of ride-sharing value and demonstrates the significant impact of environmental value on the sustainability of ride-sharing services. This study extends fit theory by dividing it into two dimensions.