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Understanding the interplay between genotype and fitness is a core question in evolutionary biology. Here, we address this challenge in the context of microbial adaptation to environmental stressors. This study explores the role of epistasis in bacterial adaptation by examining genetic and phenotypic changes in silver-adapted Escherichia coli populations, focusing on the role of beneficial mutations in two-component response systems (TCRS). To do this, we measured 24-hour growth assays and conducted whole-genome DNA and RNA sequencing on E. coli mutants that confer resistance to ionic silver. We showed recently that the R15L cusS mutation is central to silver resistance, primarily through upregulation of the cus efflux system. However, here we show that this mutation’s effectiveness is significantly enhanced by epistatic interactions with additional mutations in regulatory genes such as ompR, rho, and fur. These interactions reconfigure global stress response networks, resulting in robust and varied resistance strategies across different populations. This study underscores the critical role of epistasis in bacterial adaptation, illustrating how interactions between multiple mutations and how genetic backgrounds shape the resistance phenotypes of E. coli populations. This work also allowed for refinement of our model describing the role TCRS genes play in bacterial adaptation by now emphasizing that adaptation to environmental stressors is a complex, context-dependent process, driven by the dynamic interplay between genetic and environmental factors. These findings have broader implications for understanding microbial evolution and developing strategies to combat antimicrobial resistance.

 

Introduction:Two-component response systems (TCRS) are the main mechanism by which prokaryotes acclimate to changing environments. These systems are composed of a membrane bound histidine kinase (HK) that senses external signals and a response regulator (RR) that activates transcription of response genes. Despite their known role in acclimation, little is known about the role TCRS play in environmental adaptation. Several experimental evolution studies have shown the acquisition of mutations in TCRS during adaptation, therefore here we set out to characterize the adaptive mechanism resulting from these mutations and evaluate whether single nucleotide changes in one gene could induce variable genotype-by-environment (GxE) interactions.

Methods:To do this, we assessed fitness changes and differential gene expression for four adaptive mutations incusS, the gene that encodes the HK CusS,acquired byEscherichia coliduring silver adaptation.

Results:Fitness assays showed that as the environment changed, each mutant displayed a unique fitness profile with greatest fitness in the original selection environment. RNAseq then indicated that, in ± silver nitrate, each mutant induces a primary response that upregulatescusS,its RRcusR, and constitutively expresses the target response genescusCFBA. This then induces a secondary response via differential expression of genes regulated by the CusR through TCRS crosstalk. Finally, each mutant undergoes fitness tuning through unique tertiary responses that result in gene expression patterns specific for the genotype, the environment and optimized for the original selection conditions.

Discussion:This three-step response shows that different mutations in a single gene leads to individualized phenotypes governed by unique GxE interactions that not only contribute to transcriptional divergence but also to phenotypic plasticity.

 

Innovations by engineers and physical scientists working at the frontiers of microbiome engineering and discovery requires in-depth understanding of microbiome systems with parallel skills in bioinformatics and biostatistics. Despite the importance of integrating bioinformatics and biology into graduate student training in fields outside traditional biological sciences, academic institutions remain challenged with including these disciplines across departmental boundaries. Furthermore, it is critical for students in engineering, bioinformatics, and biostatistics to understand fundamentals behind the biological systems they model, and for biology students to gain competencies in applying bioinformatics and biostatistics to biological questions. To address these needs, we developed the Integrative Bioinformatics for Investigating and Engineering Microbiomes (IBIEM) graduate training partnership between Duke University and North Carolina Agricultural and Technical State University, which was funded by the National Science Foundation Research Traineeship (NRT) program. IBIEM’s goals include training interdisciplinary groups of students to: (a) transform conceptualization and develop skills for application of quantitative biology in microbiome areas; (b) perform cutting edge research requiring interdisciplinary team skills; and to (c) communicate their research across disciplinary barriers and to diverse audiences. The pedagogical framework adapted to foster trainee engagement is learner-centered teaching which emphasizes the importance of selfdirected learning with parallel ongoing assessment to optimize student outcomes. Since IBIEM trainees’ goals as well as entry-level knowledge and skills across disciplines varied greatly, program implementation was found to be challenging and required rigorous evaluation and refinements for effective training across disciplines and skill levels. A comprehensive program evaluation over five years found that the strongest learning and skills outcomes were linked to several “best practices”. Early provision of depth in fundamentals in R programming and reproducible research was found to be critical to “jump start” students without programming backgrounds. Addition of an overview of microbiome experimental design and analysis added important context as to how and where in the research process informatics fits into design progression and was highly motivating to students. Course modality was found to impact trainee outcomes with in-person classes that included hands-on practice and feedback showing greater improvements in training outcomes over hybrid, flipped and virtual course modalities. Furthermore, introduction of low, medium, and high level “challenges” along with in-person tutoring was found to be impactful in building a common foundation to span expertise levels and for engaging students across entry and advanced levels. Training impacts peaked during year four with cumulative implementation of revised strategies. Innovative training revisions and inclusion of critical elements was strongly linked to program satisfaction and ratings of advances in technical, professional and career skills as well as post-training carry over into trainees’ own research and leadership in their labs and careers. Furthermore, this training collaboration and partnership provided the foundation and training model for the newly funded NSF Engineering Research Center for Precision Microbiome Engineering (PreMiEr) for work in the critical area of engineering the microbiome in built environments. 

The prevalence of multidrug-resistant bacteria and their increased pathogenicity has led to a growing interest in metallic antimicrobial materials and bacteriophages as potential alternatives to conventional antibiotics. This study examines how resistance to excess iron (III) influences the evolution of bacteriophage resistance in the bacterium Escherichia coli. We utilized experimental evolution in E. coli to test the effect of the evolution of phage T7 resistance on populations resistant to excess iron (III) and populations without excess iron resistance. Phage resistance evolved rapidly in both groups. Dual-resistant (iron (III)/phage) populations were compared to their controls (excess iron (III)-resistant, phage-resistant, no resistance to either) for their performance against each stressor, excess iron (III) and phage; and correlated resistances to excess iron (II), gallium (III), silver (I) and conventional antibiotics. Excess iron (III)/phage-resistant populations demonstrated superior 24 h growth compared to all other populations when exposed to increasing concentrations of iron (II, III), gallium (III), ampicillin, and tetracycline. No differences in 24 h growth were shown between excess iron (III)/phage-resistant and excess iron (III)-resistant populations in chloramphenicol, sulfonamide, and silver (I). The genomic analysis identified selective sweeps in the iron (III) resistant (rpoB, rpoC, yegB, yeaG), phage-resistant (clpX →/→ lon, uvaB, yeaG, fliR, gatT, ypjF, waaC, rpoC, pgi, and yjbH) and iron (III)/phage resistant populations (rcsA, hldE, rpoB, and waaC). E. coli selected for resistance to both excess iron (III) and T7 phage showed some evidence of a synergistic effect on various components of fitness. Dual selection resulted in correlated resistances to ionic metals {iron (II), gallium (III), and silver (I)} and several conventional antibiotics. There is a likelihood that this sort of combination antimicrobial treatment may result in bacterial variants with multiple resistances.