Evolutionary potential, cross-stress behavior and the genetic basis of acquired stress resistance in Escherichia coli

Mimicking the Effects of Antimicrobial Blue Light: Exploring Single Stressors and Their Impact on Microbial Growth

Antimicrobial blue light (aBL) has become a promising non-invasive method that uses visible light, typically within the 405-470 nm wavelength range, to efficiently inactivate a wide variety of pathogens. However, the mechanism of antimicrobial blue light (aBL) has not been fully understood. In this study, our research group investigated the sensitivity of Escherichia coli BW25113 single-gene deletion mutants to individual stressors generated by aBL. Sixty-four aBL-sensitive mutants were tested under conditions mimicking the stress generated by irradiation with aBL, with their growth defects compared to the wild-type strain. Results revealed no positive correlation between aBL and single stressors, indicating that aBL's effectiveness is due to the simultaneous generation of multiple stressors. This multifactorial effect suggests that aBL targets microbial cells more precisely than single stressors such as hydrogen peroxide. No single gene knockout conferred specific resistance, highlighting aBL's potential as an antimicrobial strategy.

Heterofermentative Lentilactobacillus buchneri and low dry matter reduce high-risk antibiotic resistance genes in corn silage by regulating pathogens and mobile genetic element

The study of antibiotic resistance in the silage microbiome has attracted initial attention. However, the influences of lactic acid bacteria inoculants and dry matter (DM) content on antibiotic resistance genes (ARGs) reduction in whole-plant corn silage remain poorly studied. This study accessed the ARGs' risk and transmission mechanism in whole-plant corn silage with different DM levels and treated with Lactiplantibacillus plantarum or Lentilactobacillus buchneri. The macrolide and tetracycline were the main ARGs in corn silage. The dominant species (Lent. buchneri and Lactobacillus acetotolerans) were the main ARGs carriers in whole-plant corn silage. The application of Lent. buchneri increased total ARGs abundance regardless of corn DM. Whole-plant corn silage with 30 % DM reduced the abundances of integrase and plasmid compared with 40 % DM. The correlation and structural equation model analysis demonstrated that bacterial community succession, resulting from changes in DM content, was the primary driving factor influencing the ARGs distribution in whole-plant corn silage. Interestingly, whole-plant corn silage inoculated with Lent. buchneri reduced abundances of high-risk ARGs (mdtG, mepA, tetM, mecA, vatE and tetW) by regulating pathogens (Escherichia coli), mobile genetic elements (MGEs) genes (IS3 and IS1182), and this effect was more pronounced at 30 % DM level. In summary, although whole-plant corn silage inoculated with Lent. buchneri increased the total ARGs abundance at both DM levels, it decreased the abundance of high-risk ARGs by reducing the abundances of the pathogens and MGEs, and this effect was more noticeable at 30 % DM level.

Reactive Oxygen Species Mediate the Bactericidal Activity of Chlorine Against Salmonella

Chlorine and its derivatives have been used as an antibacterial agent to reduce Salmonella contamination in poultry meat during processing. We evaluated the survival of 4 different Salmonella serotypes (Typhimurium, Enteritidis, Heidelberg, and Gaminara) in the presence of 50 ppm sodium hypochlorite (NaOCl) alone or with the addition of thiourea (radical scavenger) or Dip (iron chelator) to determine the contribution of reactive oxygen species (ROS) in the bactericidal activity of NaOCl. The result showed that for all four serotypes the addition of thiourea or Dip significantly increased the % survival as compared to the respective NaOCl treatment groups, while it was significantly higher with thiourea as compared to Dip (P < 0.05). We also evaluated the survival of 11 deletion mutants of S. Typhimurium, which were demonstrated to increase (∆atpC, ∆cyoA, ∆gnd, ∆nuoG, ∆pta, ∆sdhC, and ∆zwf) or decrease the production of ROS (∆edd, ∆fumB, ∆pykA, and ∆tktB) in Escherichia coli (E. coli), in the presence of 50 ppm. The results showed that only two (∆sdhC and ∆zwf) out of 7 ROS-increasing mutants showed reduced % survival as compared to the wild-type (P < 0.05), while all four deletion ROS-decreasing mutants showed significantly higher % survival as compared to the wild-type (P < 0.05). This work suggests that the production of ROS is a major component of the bactericidal activity of NaOCl against Salmonella serotypes and there might be a significant difference in the metabolic pathways involved in ROS production between Salmonella and E. coli.

Achieving robust synthetic tolerance in industrial E. coli through negative auto-regulation of a DsrA-Hfq module

In industrial fermentation processes, microorganisms often encounter acid stress, which significantly impact their productivity. This study focused on the acid-resistant module composed of small RNA (sRNA) DsrA and the sRNA chaperone Hfq. Our previous study had shown that this module improved the cell growth of Escherichia coli MG1655 at low pH, but failed to obtain this desired phenotype in industrial strains. Here, we performed a quantitative analysis of DsrA-Hfq module to determine the optimal expression mode. We then assessed the potential of the CymR-based negative auto-regulation (NAR) circuit for industrial application, under different media, strains and pH levels. Growth assay at pH 4.5 revealed that NAR-05D04H circuit was the best acid-resistant circuit to improve the cell growth of E. coli MG1655. This circuit was robust and worked well in the industrial lysine-producing strain E. coli SCEcL3 at a starting pH of 6.8 and without pH control, resulting in a 250 % increase in lysine titer and comparable biomass in shaking flask fermentation compared to the parent strain. This study showed the practical application of NAR circuit in regulating DsrA-Hfq module, effectively and robustly improving the acid tolerance of industrial strains, which provides a new approach for breeding industrial strains with tolerance phenotype.

Evolutionary Dynamics of Accelerated Antiviral Resistance Development in Hypermutator Herpesvirus

Antiviral therapy is constantly challenged by the emergence of resistant pathogens. At the same time, experimental approaches to understand and predict resistance are limited by long periods required for evolutionary processes. Here, we present a herpes simplex virus 1 mutant with impaired proofreading capacity and consequently elevated mutation rates. Comparing this hypermutator to parental wild type virus, we study the evolution of antiviral drug resistance in vitro. We model resistance development and elucidate underlying genetic changes against three antiviral substances. Our analyzes reveal no principle difference in the evolutionary behavior of both viruses, adaptive processes are overall similar, however significantly accelerated for the hypermutator. We conclude that hypermutator viruses are useful for modeling adaptation to antiviral therapy. They offer the benefit of expedited adaptation without introducing apparent bias and can therefore serve as an accelerator to predict natural evolution.

Climate warming promotes collateral antibiotic resistance development in cyanobacteria

Both cyanobacterial blooms and antibiotic resistance have aggravated worldwide and posed a great threat to public health in recent years. As a significant source and reservoir of water environmental resistome, cyanobacteria exhibit confusing discrepancy between their reduced susceptibility and their chronic exposure to antibiotic mixtures at sub-inhibitory concentrations. How the increasing temperature affects the adaptive evolution of cyanobacteria-associated antibiotic resistance in response to low-level antibiotic combinations under climate change remains unclear. Here we profiled the antibiotic interaction and collateral susceptibility networks among 33 commonly detected antibiotics in 600 cyanobacterial strains isolated from 50 sites across four eutrophicated lakes in China. Cyanobacteria-associated antibiotic resistance level was found positively correlated to antibiotic heterogeneity across all sites. Among 528 antibiotic combinations, antagonism was observed for 62 % interactions and highly conserved within cyanobacterial species. Collateral resistance was detected in 78.5 % of pairwise antibiotic interaction, leading to a widened or shifted upwards mutant selection window for increased opportunity of acquiring second-step mutations. We quantified the interactive promoting effect of collateral resistance and increasing temperature on the evolution of both phenotypic and genotypic cyanobacteria-associated resistance under chronic exposure to environmental level of antibiotic combinations. With temperature increasing from 16 °C to 36 °C, the evolvability index and genotypic resistance level increased by 1.25 - 2.5 folds and 3 - 295 folds in the collateral-resistance-informed lineages, respectively. Emergence of resistance mutation pioneered by tolerance, which was jointly driven by mutation rate and persister fraction, was found to be accelerated by increased temperature and antibiotic switching rate. Our findings provided mechanic insights into the boosting effect of climate warming on the emergence and development of cyanobacteria-associated resistance against collateral antibiotic phenotypes.

Trade-offs, trade-ups, and high mutational parallelism underlie microbial adaptation during extreme cycles of feast and famine

Microbes are evolutionarily robust organisms capable of rapid adaptation to complex stress, which enables them to colonize harsh environments. In nature, microbes are regularly challenged by starvation, which is a particularly complex stress because resource limitation often co-occurs with changes in pH, osmolarity, and toxin accumulation created by metabolic waste. Often overlooked are the additional complications introduced by eventual resource replenishment, as successful microbes must withstand rapid environmental shifts before swiftly capitalizing on replenished resources to avoid invasion by competing species. To understand how microbes navigate trade-offs between growth and survival, ultimately adapting to thrive in environments with extreme fluctuations, we experimentally evolved 16 Escherichia coli populations for 900 days in repeated feast/famine conditions with cycles of 100-day starvation before resource replenishment. Using longitudinal population-genomic analysis, we found that evolution in response to extreme feast/famine is characterized by narrow adaptive trajectories with high mutational parallelism and notable mutational order. Genetic reconstructions reveal that early mutations result in trade-offs for biofilm and motility but trade-ups for growth and survival, as these mutations conferred positively correlated advantages during both short-term and long-term culture. Our results demonstrate how microbes can navigate the adaptive landscapes of regularly fluctuating conditions and ultimately follow mutational trajectories that confer benefits across diverse environments.

Advance of tolerance engineering on microbes for industrial production

Industrial microbes have become the core of biological manufacturing, which utilized as the cell factory for production of plenty of chemicals, fuels and medicine. However, the challenge that the extreme stress conditions exist in production is unavoidable for cell factory. Consequently, to enhance robustness of the chassis cell lays the foundation for development of bio-manufacturing. Currently, the researches on cell tolerance covered various aspects, involving reshaping regulatory network, cell membrane modification and other stress response. In fact, the strategies employed to improve cell robustness could be summarized into two directions, irrational engineering and rational engineering. In this review, the metabolic engineering technologies on enhancement of microbe tolerance to industrial conditions are summarized. Meanwhile, the novel thoughts emerged with the development of biological instruments and synthetic biology are discussed.

Mechanism of furfural toxicity and metabolic strategies to engineer tolerance in microbial strains

Lignocellulosic biomass represents a carbon neutral cheap and versatile source of carbon which can be converted to biofuels. A pretreatment step is frequently used to make the lignocellulosic carbon bioavailable for microbial metabolism. Dilute acid pretreatment at high temperature and pressure is commonly utilized to efficiently solubilize the pentose fraction by hydrolyzing the hemicellulose fibers and the process results in formation of furans-furfural and 5-hydroxymethyl furfural-and other inhibitors which are detrimental to metabolism. The presence of inhibitors in the medium reduce productivity of microbial biocatalysts and result in increased production costs. Furfural is the key furan inhibitor which acts synergistically along with other inhibitors present in the hydrolysate. In this review, the mode of furfural toxicity on microbial metabolism and metabolic strategies to increase tolerance is discussed. Shared cellular targets between furfural and acetic acid are compared followed by discussing further strategies to engineer tolerance. Finally, the possibility to use furfural as a model inhibitor of dilute acid pretreated lignocellulosic hydrolysate is discussed. The furfural tolerant strains will harbor an efficient lignocellulosic carbon to pyruvate conversion mechanism in presence of stressors in the medium. The pyruvate can be channeled to any metabolite of interest by appropriate modulation of downstream pathway of interest. The aim of this review is to emphasize the use of hydrolysate as a carbon source for bioproduction of biofuels and other compounds of industrial importance.

Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs

RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.

Evidence of Homeostatic Regulation in Mycobacterium avium Subspecies paratuberculosis as an Adaptive Response to Copper Stress

Background: Bacteria are capable of responding to various stressors, something which has been essential for their adaptation, evolution, and colonization of a wide range of environments. Of the many stressors affecting bacteria, we can highlight heavy metals, and amongst these, copper stands out for its great antibacterial capacity. Using Mycobacterium tuberculosis (Mtb) as a model, the action of proteins involved in copper homeostasis has been put forward as an explanation for the tolerance or adaptive response of this mycobacteria to the toxic action of copper. Therefore, the aim of this study was to confirm the presence and evaluate the expression of genes involved in copper homeostasis at the transcriptional level after challenging Mycobacterium avium subsp. paratuberculoisis (MAP) with copper ions. Methodology: Buffer inoculated with MAP was treated with two stressors, the presence of copper homeostasis genes was confirmed by bioinformatics and genomic analysis, and the response of these genes to the stressors was evaluated by gene expression analysis, using qPCR and the comparative ΔΔCt method. Results: Through bioinformatics and genomic analysis, we found that copper homeostasis genes were present in the MAP genome and were overexpressed when treated with copper ions, which was not the case with H2O2 treatment. Conclusion: These results suggest that genes in MAP that code for proteins involved in copper homeostasis trigger an adaptive response to copper ions.

Effect of preliminary stresses on the induction of viable but non-culturable Escherichia coli O157:H7 NCTC 12900 and Staphylococcus aureus ATCC 6538

As a novel non-thermal pasteurization technology, high pressure carbon dioxide (HPCD) has been used in food processing. However, it could induce microorganisms into a viable but nonculturable (VBNC) state, posing a potential risk to food safety and public health. In this study, we attempted to investigate the effect of various preliminary stresses including cold, heat, osmosis, acidity and oxidation on HPCD-induced VBNC formation. The results indicated that there was no effect of preliminary stresses on VBNC Staphylococcus aureus induction. However, heat, acidity and long-term (24 h) cultivation preadaptation could significantly increase the VBNC E. coli production induced by HPCD. Transcriptome analysis revealed that genes involved in ATP production were significantly decreased in these three stress-treated cells, and further ATP levels determination revealed that the ATP levels of the cell were significantly decreased after heat, acidity and long-term cultivation preadaptation, implying the decrease of ATP level caused by these stresses might be the reason for increasing VBNC production. To further study the relationship between ATP level and VBNC cell ratios after preadaptation. We artificially decreased the ATP levels, and detect their VBNC ratios after HPCD treatment. We found that with the ATP concentration decreasing after exposure to carbonyl cyanide m-chlorophenyl hydrazine (CCCP), the VBNC ratios were increased after HPCD treatment, indicating that the ATP contents were highly negatively correlated with VBNC ratios. This study proved that the preadaptation of heat, acidity and long-term cultivation could promote VBNC induction by decreasing the intracellular ATP level. In general, the obtained result gave the instruction about the storage environment for food materials, helped to further develop and optimize the HPCD processing to prevent VBNC formation and accelerate the development of HPCD technology in food industry.

Metagenomics reveals the response of antibiotic resistance genes to elevated temperature in the Yellow River

Climate warming may aggravate the threat of antibiotic resistance genes (ARGs) to environmental and human health. However, whether temperature can predict ARGs and influence their assembly processes remains unknown. Here, we used metagenomic sequencing to explore how gradually elevated water temperature (23 °C, 26 °C, 29 °C, 32 °C, 35 °C) influences ARG and mobile genetic element (MGE) profiles in the Yellow River. In total, 30 ARG types including 679 subtypes were detected in our water samples. Gradually increased temperature remarkably reduced ARG diversity but increased ARG abundance. Approximately 37 % of ARGs and 42 % of MGEs were predicted by temperature, while most others were not sensitive to temperature. For each 1 °C increase in temperature, the ARG abundance rose by 2133 TPM (Transcripts Per kilobase of exon model per Million mapped reads) abundance, and multidrug, tetracycline and peptide resistance genes had the fastest increases. Proteobacteria and Actinobacteria were the primary ARG hosts, with 558 and 226 ARG subtypes, respectively. Although ARG profiles were mainly governed by stochastic process, elevated temperature increased the deterministic process of ARGs in the Yellow River. The abundance of five high-risk ARGs (tetM, mecA, bacA, vatE and tetW) significantly increased with elevated water temperature, and these ARGs co-occurred with several opportunistic pathogens (Delftia, Legionella and Pseudomonas), implying that antibiotic resistance risk may increase under climate warming. Our study explored the possibility of predicting resistomes and their health risks through temperature, providing a novel approach to predict and control ARGs in water environments under climate warming.

Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape

The fitness landscape represents the complex relationship between genotype or phenotype and fitness under a given environment, the structure of which allows the explanation and prediction of evolutionary trajectories. Although previous studies have constructed fitness landscapes by comprehensively studying the mutations in specific genes, the high dimensionality of genotypic changes prevents us from developing a fitness landscape capable of predicting evolution for the whole cell. Herein, we address this problem by inferring the phenotype-based fitness landscape for antibiotic resistance evolution by quantifying the multidimensional phenotypic changes, i.e., time-series data of resistance for eight different drugs. We show that different peaks of the landscape correspond to different drug resistance mechanisms, thus supporting the validity of the inferred phenotype-fitness landscape. We further discuss how inferred phenotype-fitness landscapes could contribute to the prediction and control of evolution. This approach bridges the gap between phenotypic/genotypic changes and fitness while contributing to a better understanding of drug resistance evolution.

Gene Networks and Pathways Involved in Escherichia coli Response to Multiple Stressors

Stress response helps microorganisms survive extreme environmental conditions and host immunity, making them more virulent or drug resistant. Although both reductionist approaches investigating specific genes and systems approaches analyzing individual stress conditions are being used, less is known about gene networks involved in multiple stress responses. Here, using a systems biology approach, we mined hundreds of transcriptomic data sets for key genes and pathways involved in the tolerance of the model microorganism Escherichia coli to multiple stressors. Specifically, we investigated the E. coli K-12 MG1655 transcriptome under five stresses: heat, cold, oxidative stress, nitrosative stress, and antibiotic treatment. Overlaps of transcriptional changes between studies of each stress factor and between different stressors were determined: energy-requiring metabolic pathways, transport, and motility are typically downregulated to conserve energy, while genes related to survival, bona fide stress response, biofilm formation, and DNA repair are mainly upregulated. The transcription of 15 genes with uncharacterized functions is higher in response to multiple stressors, which suggests they may play pivotal roles in stress response. In conclusion, using rank normalization of transcriptomic data, we identified a set of E. coli stress response genes and pathways, which could be potential targets to overcome antibiotic tolerance or multidrug resistance.

How does UV-B stress affect secondary metabolites of Scutellaria baicalensis in vitro shoots grown at different 6-benzyl aminopurine concentrations?

Ultraviolet-B (UV-B) radiation is one of the abiotic stresses that can significantly affect the secondary metabolite accumulation in in vitro tissue cultures of medicinal plants. The present study investigated the effects of UV-B radiation on the secondary metabolites and antioxidant activities of Scutellaria baicalensis in vitro shoots grown at different concentrations of 6-benzyl aminopurine (6-BA), which is the cytokinin most widely used in plant tissue culture. The UV-B radiation caused significant increases in lipid peroxidation, total phenolic, and flavonoid contents, and antioxidant activities in the in vitro shoots grown at lower 6-BA concentrations (0 and 1 mg L^-1 ), while it did not cause any significant changes in those grown at higher 6-BA concentrations (2 and 3 mg L^-1 ). However, the UV-B radiation significantly altered the contents of main individual flavonoids at both lower and higher 6-BA concentrations. Upon UV-B radiation, aglycones (including baicalein, wogonin, and scutellarein) increased, while glucuronides such as baicalin and wogonoside decreased; this was more evident at higher 6-BA concentrations. This study demonstrated that the effects of UV-B radiation on the secondary metabolites of S. baicalensis in vitro shoots highly depended on the 6-BA concentration in the culture medium.

Global pleiotropic effects in adaptively evolved Escherichia coli lacking CRP reveal molecular mechanisms that define the growth physiology

Evolution facilitates emergence of fitter phenotypes by efficient allocation of cellular resources in conjunction with beneficial mutations. However, system-wide pleiotropic effects that redress the perturbations to the apex node of the transcriptional regulatory networks remain unclear. Here, we elucidate that absence of global transcriptional regulator CRP in Escherichia coli results in alterations in key metabolic pathways under glucose respiratory conditions, favouring stress- or hedging-related functions over growth-enhancing functions. Further, we disentangle the growth-mediated effects from the CRP regulation-specific effects on these metabolic pathways. We quantitatively illustrate that the loss of CRP perturbs proteome efficiency, as evident from metabolic as well as ribosomal proteome fractions, that corroborated with intracellular metabolite profiles. To address how E. coli copes with such systemic defect, we evolved Δcrp mutant in the presence of glucose. Besides acquiring mutations in the promoter of glucose transporter ptsG, the evolved populations recovered the metabolic pathways to their pre-perturbed state coupled with metabolite re-adjustments, which altogether enabled increased growth. By contrast to Δcrp mutant, the evolved strains remodelled their proteome efficiency towards biomass synthesis, albeit at the expense of carbon efficiency. Overall, we comprehensively illustrate the genetic and metabolic basis of pleiotropic effects, fundamental for understanding the growth physiology.

Induction of resistance mechanisms in Rhodotorula toruloides for growth in sugarcane hydrolysate with high inhibitor content

The oleaginous yeast Rhodotorula toruloides is a potential lipid producer for biodiesel production. However, this yeast shows growth inhibition due to harmful compounds when cultivated in hemicellulose hydrolysate. Here, we present a comparative analysis of colony selection and heterologous adaptive laboratory enhancement (ALE) strategies for obtaining robust strains. We implemented these ALE strategies for R. toruloides in a culture medium containing sugarcane hemicellulose hydrolysate. Our comparison study showed that the strain obtained with heterogeneous ALE strategy (Rth) reached a µ_max of 55% higher than the parental strain. It also exhibited higher biomass production (6.51 g/l) and lipid content (60%). ALE with colony selection strategy (Rtc) had a fitness gain in terms of shortening of the lag phase (9 h) when compared to Rth and parental strain (11.67, 12.33 h, respectively). When cultivated in Eucalyptus urograndis hemicellulose hydrolysate, the Rth strain achieved a high lipid content, 64%. Kinetics studies showed a strong effect of acetic acid as a repressor of xylose consumption during R. toruloides cultivation.Key points• Distinct adaptive laboratory strategies resulted in strains with different physiologies.• Heterologous adaptive laboratory enhancement provided the best results (fitness gain of 55% in µmax).• The Rth strain achieved a lipid content of 64.3% during cultivation in eucalyptus hemicellulose hydrolysate.

Adaptive evolution of sulfite tolerance in Brettanomyces bruxellensis

Brettanomyces bruxellensis is considered one of the most problematic microbes associated with wine production. Sulfur dioxide is commonly used to inhibit the growth of B. bruxellensis and limit the potential wine spoilage. Brettanomyces bruxellensis wine isolates can grow at higher concentrations of this preservative than isolates from other sources. Thus, it has been suggested that the use of sulfite may have selected for B. bruxellensis strains better adapted to survive in the winemaking environment. We utilized laboratory adaptive evolution to determine the potential for this to occur. Three B. bruxellensis strains, representative of known genetic variation within the species, were subjected to increasing sublethal sulfur dioxide concentrations. Individual clones isolated from evolved populations displayed enhanced sulfite tolerance, ranging from 1.6 to 2.5 times higher than the corresponding parental strains. Whole-genome sequencing of sulfite-tolerant clones derived from two of the parental strains revealed structural variations affecting 270 genes. The region containing the sulfite efflux pump encoding gene, SSU1, showed clear copy number variants in all sequenced clones. Regardless of parental strain genetic background, SSU1 copy number changes were reproducibly associated with one SSU1 haplotype. This work clearly demonstrates adaptive evolution of B. bruxellensis when exposed to sublethal sulfites and suggests that, similar to Saccharomyces cerevisiae wine yeast, the mechanism responsible involves the gene SSU1.

Antibiotic-Resistant Bacteria in Aquaculture and Climate Change: A Challenge for Health in the Mediterranean Area

Aquaculture is the productive activity that will play a crucial role in the challenges of the millennium, such as the need for proteins that support humans and the respect for the environment. Aquaculture is an important economic activity in the Mediterranean basin. A great impact is presented, however, by aquaculture practices as they involve the use of antibiotics for treatment and prophylaxis. As a consequence of the use of antibiotics in aquaculture, antibiotic resistance is induced in the surrounding bacteria in the column water, sediment, and fish-associated bacterial strains. Through horizontal gene transfer, bacteria can diffuse antibiotic-resistance genes and mobile resistance genes further spreading genetic determinants. Once triggered, antibiotic resistance easily spreads among aquatic microbial communities and, from there, can reach human pathogenic bacteria, making vain the use of antibiotics for human health. Climate change claims a significant role in this context, as rising temperatures can affect cell physiology in bacteria in the same way as antibiotics, causing antibiotic resistance to begin with. The Mediterranean Sea represents a 'hot spot' in terms of climate change and aspects of antibiotic resistance in aquaculture in this area can be significantly amplified, thus increasing threats to human health. Practices must be adopted to counteract negative impacts on human health, with a reduction in the use of antibiotics as a pivotal point. In the meantime, it is necessary to act against climate change by reducing anthropogenic impacts, for example by reducing CO2 emissions into the atmosphere. The One Health type approach, which involves the intervention of different skills, such as veterinary, ecology, and medicine in compliance with the principles of sustainability, is necessary and strongly recommended to face these important challenges for human and animal health, and for environmental safety in the Mediterranean area.

Engineering of the Small Noncoding RNA (sRNA) DsrA Together with the sRNA Chaperone Hfq Enhances the Acid Tolerance of Escherichia coli

Acid tolerance of microorganisms is a desirable phenotype for many industrial fermentation applications. In Escherichia coli, the stress response sigma factor RpoS is a promising target for engineering acid-tolerant phenotypes. However, the simple overexpression of RpoS alone is insufficient to confer these phenotypes. In this study, we show that the simultaneous overexpression of the noncoding small RNA (sRNA) DsrA and the sRNA chaperone Hfq, which act as RpoS activators, significantly increased acid tolerance in terms of cell growth under modest acidic pH, as well as cell survival upon extreme acid shock. Directed evolution of the DsrA-Hfq module further improved the acid tolerance, with the best mutants showing a 51 to 72% increase in growth performance at pH 4.5 compared with the starting strain, MG1655. Further analyses found that the improved acid tolerance of these DsrA-Hfq strains coincided with activation of genes associated with proton-consuming acid resistance system 2 (AR2), protein chaperone HdeB, and reactive oxygen species (ROS) removal in the exponential phase. This study illustrated that the fine-tuning of sRNAs and their chaperones can be a novel strategy for improving the acid tolerance of E. coli IMPORTANCE Many of the traditional studies on bacterial acid tolerance generally focused on improving cell survival under extreme-pH conditions, but cell growth under less harsh acidic conditions is more relevant to industrial applications. Under normal conditions, the general stress response sigma factor RpoS is maintained at low levels in the growth phase through a number of mechanisms. This study showed that RpoS can be activated prior to the stationary phase via engineering its activators, the sRNA DsrA and the sRNA chaperone Hfq, resulting in significantly improved cell growth at modest acidic pH. This work suggests that the sigma factors and likely other transcription factors can be retuned or retimed by manipulating the respective regulatory sRNAs along with the sufficient supply of the respective sRNA chaperones (i.e., Hfq). This provides a novel avenue for strain engineering of microbes.

Rapid selection response to ethanol in Saccharomyces eubayanus emulates the domestication process under brewing conditions

Although the typical genomic and phenotypic changes that characterize the evolution of organisms under the human domestication syndrome represent textbook examples of rapid evolution, the molecular processes that underpin such changes are still poorly understood. Domesticated yeasts for brewing, where short generation times and large phenotypic and genomic plasticity were attained in a few generations under selection, are prime examples. To experimentally emulate the lager yeast domestication process, we created a genetically complex (panmictic) artificial population of multiple Saccharomyces eubayanus genotypes, one of the parents of lager yeast. Then, we imposed a constant selection regime under a high ethanol concentration in 10 replicated populations during 260 generations (6 months) and compared them with propagated controls exposed solely to glucose. Propagated populations exhibited a selection differential of 60% in growth rate in ethanol, mostly explained by the proliferation of a single lineage (CL248.1) that competitively displaced all other clones. Interestingly, the outcome does not require the entire time‐course of adaptation, as four lineages monopolized the culture at generation 120. Sequencing demonstrated that de novo genetic variants were produced in all propagated lines, including SNPs, aneuploidies, INDELs and translocations. In addition, the different propagated populations showed correlated responses resembling the domestication syndrome: genomic rearrangements, faster fermentation rates, lower production of phenolic off‐flavours and lower volatile compound complexity. Expression profiling in beer wort revealed altered expression levels of genes related to methionine metabolism, flocculation, stress tolerance and diauxic shift, likely contributing to higher ethanol and fermentation stress tolerance in the evolved populations. Our study shows that experimental evolution can rebuild the brewing domestication process in ‘fast motion’ in wild yeast, and also provides a powerful tool for studying the genetics of the adaptation process in complex populations.

A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach

Tolerance to stress conditions is vital for organismal survival, including bacteria under specific environmental conditions, antibiotics, and other perturbations. Some studies have described common modulation and shared genes during stress response to different types of disturbances (termed as perturbome), leading to the idea of central control at the molecular level. We implemented a robust machine learning approach to identify and describe genes associated with multiple perturbations or perturbome in a Pseudomonas aeruginosa PAO1 model. Using microarray datasets from the Gene Expression Omnibus (GEO), we evaluated six approaches to rank and select genes: using two methodologies, data single partition (SP method) or multiple partitions (MP method) for training and testing datasets, we evaluated three classification algorithms (SVM Support Vector Machine, KNN K-Nearest neighbor and RF Random Forest). Gene expression patterns and topological features at the systems level were included to describe the perturbome elements. We were able to select and describe 46 core response genes associated with multiple perturbations in P. aeruginosa PAO1 and it can be considered a first report of the P. aeruginosa perturbome. Molecular annotations, patterns in expression levels, and topological features in molecular networks revealed biological functions of biosynthesis, binding, and metabolism, many of them related to DNA damage repair and aerobic respiration in the context of tolerance to stress. We also discuss different issues related to implemented and assessed algorithms, including data partitioning, classification approaches, and metrics. Altogether, this work offers a different and robust framework to select genes using a machine learning approach.

Biocide-Induced Emergence of Antibiotic Resistance in Escherichia coli

Biocide use is essential and ubiquitous, exposing microbes to sub-inhibitory concentrations of antiseptics, disinfectants, and preservatives. This can lead to the emergence of biocide resistance, and more importantly, potential cross-resistance to antibiotics, although the degree, frequency, and mechanisms that give rise to this phenomenon are still unclear. Here, we systematically performed adaptive laboratory evolution of the gut bacteria Escherichia coli in the presence of sub-inhibitory, constant concentrations of ten widespread biocides. Our results show that 17 out of 40 evolved strains (43%) also decreased the susceptibility to medically relevant antibiotics. Through whole-genome sequencing, we identified mutations related to multidrug efflux proteins (mdfA and acrR), porins (envZ and ompR), and RNA polymerase (rpoA and rpoBC), as mechanisms behind the resulting (cross)resistance. We also report an association of several genes (yeaW, pyrE, yqhC, aes, pgpA, and yeeP-isrC) and specific mutations that induce cross-resistance, verified through mutation repairs. A greater capacity for biofilm formation with respect to the parent strain was also a common feature in 11 out of 17 (65%) cross-resistant strains. Evolution in the biocides chlorophene, benzalkonium chloride, glutaraldehyde, and chlorhexidine had the most impact in antibiotic susceptibility, while hydrogen peroxide and povidone-iodine the least. No cross-resistance to antibiotics was observed for isopropanol, ethanol, sodium hypochlorite, and peracetic acid. This work reinforces the link between exposure to biocides and the potential for cross-resistance to antibiotics, presents evidence on the underlying mechanisms of action, and provides a prioritized list of biocides that are of greater concern for public safety from the perspective of antibiotic resistance.

SIGNIFICANCE STATEMENT

Bacterial resistance and decreased susceptibility to antimicrobials is of utmost concern. There is evidence that improper biocide (antiseptic and disinfectant) use and discard may select for bacteria cross-resistant to antibiotics. Understanding the cross-resistance emergence and the risks associated with each of those chemicals is relevant for proper applications and recommendations. Our work establishes that not all biocides are equal when it comes to their risk of inducing antibiotic resistance; it provides evidence on the mechanisms of cross-resistance and a risk assessment of the biocides concerning antibiotic resistance under residual sub-inhibitory concentrations.

Nature versus Nurture: Assessing the Impact of Strain Diversity and Pregrowth Conditions on Salmonella enterica, Escherichia coli, and Listeria Species Growth and Survival on Selected Produce Items

Inoculation studies are important when assessing microbial survival and growth in food products. These studies typically involve the pregrowth of multiple strains of a target pathogen under a single condition; this emphasizes strain diversity. To gain a better understanding of the impacts of strain diversity ("nature") and pregrowth conditions ("nurture") on subsequent bacterial growth in foods, we assessed the growth and survival of Salmonella enterica (n = 5), Escherichia coli (n = 6), and Listeria (n = 5) inoculated onto tomatoes, precut lettuce, and cantaloupe rind, respectively. Pregrowth conditions included (i) 37°C to stationary phase (baseline), (ii) low pH, (iii) high salt, (iv) reduced water activity, (v) log phase, (vi) minimal medium, and (vii) 21°C. Inoculated tomatoes were incubated at 21°C; lettuce and cantaloupe were incubated at 7°C. Bacterial counts were assessed over three phases, including initial reduction (phase 1), change in bacterial numbers over the first 24 h of incubation (phase 2), and change over the 7-day incubation (phase 3). E. coli showed overall decline in counts (<1 log) over the 7-day period, except for a <1-log increase after pregrowth in high salt and to mid-log phase. In contrast, S. enterica and Listeria showed regrowth after an initial reduction. Pregrowth conditions had a substantial and significant effect on all three phases of S. enterica and E. coli population dynamics on inoculated produce, whereas strain did not show a significant effect. For Listeria, both pregrowth conditions and strain affected changes in phase 2 but not phases 1 and 3.IMPORTANCE Our findings suggest that inclusion of multiple pregrowth conditions in inoculation studies can best capture the range of growth and survival patterns expected for Salmonella enterica and Escherichia coli present on produce. This is particularly important for fresh and fresh-cut produce, where stress conditions encountered by pathogens prior to contamination can vary widely, making selection of a typical pregrowth condition virtually impossible. Pathogen growth and survival data generated using multiple pregrowth conditions will allow for more robust microbial risk assessments that account more accurately for uncertainty.

Adaptive laboratory evolution of the fast-growing cyanobacterium Synechococcus elongatus PCC 11801 for improved solvent tolerance

Cyanobacteria hold promise as cell factories for the photoautotrophic conversion of carbon dioxide to useful chemicals. For the eventual commercial viability of such processes, cyanobacteria need to be engineered for (i) efficient channeling of carbon flux toward the product of interest and (ii) improved product tolerance, the latter being the focus of this study. We chose the recently reported, fast-growing, high light and CO₂ tolerant cyanobacterium Synechococcus elongatus PCC 11801 for adaptive laboratory evolution. In two parallel experiments that lasted over 8400 h of culturing and 100 serial passages, S. elongatus PCC 11801 was evolved to tolerate 5 g/L n-butanol or 30 g/L 2,3-butanediol representing a 100% improvement in concentrations tolerated. The evolved strains retained alcohol tolerance even after being passaged several times without the alcohol stress suggesting that the changes were permanent. Whole genome sequencing of the n-butanol evolved strains revealed mutations in a number of stress responsive genes encoding translation initiation factors, RpoB and an ABC transporter. In 2,3-butanediol evolved strains, genes for ClpC, a different ABC transporter, glyceraldehyde-3-phosphate dehydrogenase and phosphoribulokinase were found to be mutated. Furthermore, the evolved strains showed significant improvement in tolerance toward several other alcohols. Notably, the n-butanol evolved strain could tolerate up to 32 g/L ethanol, thereby making it a promising host for photosynthetic production of biofuels via metabolic engineering.

High-throughput laboratory evolution reveals evolutionary constraints in Escherichia coli

Understanding the constraints that shape the evolution of antibiotic resistance is critical for predicting and controlling drug resistance. Despite its importance, however, a systematic investigation of evolutionary constraints is lacking. Here, we perform a high-throughput laboratory evolution of Escherichia coli under the addition of 95 antibacterial chemicals and quantified the transcriptome, resistance, and genomic profiles for the evolved strains. Utilizing machine learning techniques, we analyze the phenotype-genotype data and identified low dimensional phenotypic states among the evolved strains. Further analysis reveals the underlying biological processes responsible for these distinct states, leading to the identification of trade-off relationships associated with drug resistance. We also report a decelerated evolution of β-lactam resistance, a phenomenon experienced by certain strains under various stresses resulting in higher acquired resistance to β-lactams compared to strains directly selected by β-lactams. These findings bridge the genotypic, gene expression, and drug resistance gap, while contributing to a better understanding of evolutionary constraints for antibiotic resistance.

Ethanol in Combination with Oxidative Stress Significantly Impacts Mycobacterial Physiology

Here, we investigate the mycobacterial response to the combined stress of an organic oxidant (cumene hydroperoxide [CHP]) and a solvent (ethanol). To understand the interaction between the two stressors, we treated Mycobacterium smegmatis cells to a range of ethanol concentrations (2.5% to 10% [vol/vol]) in combination with a subinhibitory concentration of 1 mM CHP. It was observed that the presence of CHP increases the efficacy of ethanol in inducing rapid cell death. The data further suggest that ethanol reacts with the alkoxy radicals to produce ethanol-derived peroxides. These radicals induce significant membrane damage and lead to cell lysis. The ethanol-derived radicals were primarily recognized by the cells as organic radicals, as was evident by the differential upregulation of the ohr-ohrR genes that function in cells treated with the combination of ethanol and CHP. The role of organic peroxide reductase, Ohr, was further confirmed by the significantly higher sensitivity of the deletion mutant to CHP and the combined stress treatment of CHP and ethanol. Moreover, we also observed the sigma factor σ^B to be important for the cells treated with ethanol alone as well as the aforementioned combination. A ΔsigB mutant strain had significantly higher susceptibility to the stress conditions. This finding was correlated with the σ^B-dependent transcriptional regulation of ohr and ohrR In summary, our data indicate that the combination of low levels of ethanol and organic peroxides induce ethanol-derived organic radicals that lead to significant oxidative stress on the cells in a concentration-dependent manner.IMPORTANCE Bacterial response to a combination of stresses can be unexpected and very different compared with that of an individual stress treatment. This study explores the physiological and transcriptional response of mycobacteria in response to the combinatorial treatment of an oxidant with the commonly used solvent ethanol. The presence of a subinhibitory concentration of organic peroxide increases the effectiveness of ethanol by inducing reactive peroxides that destroy the membrane integrity of cells in a significantly short time span. Our work elucidates a mechanism of targeting the complex mycobacterial membrane, which is its primary source of intrinsic resistance. Furthermore, it also demonstrates the importance of exploring the effect of various stress conditions on inducing bacterial clearance.

Accelerated knowledge discovery from omics data by optimal experimental design

How to design experiments that accelerate knowledge discovery on complex biological landscapes remains a tantalizing question. We present an optimal experimental design method (coined OPEX) to identify informative omics experiments using machine learning models for both experimental space exploration and model training. OPEX-guided exploration of Escherichia coli’s populations exposed to biocide and antibiotic combinations lead to more accurate predictive models of gene expression with 44% less data. Analysis of the proposed experiments shows that broad exploration of the experimental space followed by fine-tuning emerges as the optimal strategy. Additionally, analysis of the experimental data reveals 29 cases of cross-stress protection and 4 cases of cross-stress vulnerability. Further validation reveals the central role of chaperones, stress response proteins and transport pumps in cross-stress exposure. This work demonstrates how active learning can be used to guide omics data collection for training predictive models, making evidence-driven decisions and accelerating knowledge discovery in life sciences.

How to design experiments that accelerate knowledge discovery on complex biological landscapes remains a tantalizing question. Here, the authors present OPEX, an optimal experimental design method to identify informative omics experiments for both experimental space exploration and model training.

Evolution of an Escherichia coli PTS- strain: a study of reproducibility and dynamics of an adaptive evolutive process

Adaptive laboratory evolution (ALE) has been used to study and solve pressing questions about evolution, especially for the study of the development of mutations that confer increased fitness during evolutionary processes. In this contribution, we investigated how the evolutionary process conducted with the PTS^- mutant of Escherichia coli PB11 in three parallel batch cultures allowed the restoration of rapid growth with glucose as the carbon source. The significant findings showed that genomic sequence analysis of a set of newly evolved mutants isolated from ALE experiments 2-3 developed some essential mutations, which efficiently improved the fast-growing phenotypes throughout different fitness landscapes. Regulator galR was the target of several mutations such as SNPs, partial and total deletions, and insertion of an IS1 element and thus indicated the relevance of a null mutation of this gene in the adaptation of the evolving population of PB11 during the parallel ALE experiments. These mutations resulted in the selection of MglB and GalP as the primary glucose transporters by the evolving population, but further selection of at least a second adaptive mutation was also necessary. We found that mutations in the yfeO, rppH, and rng genes improved the fitness advantage of evolving PTS^- mutants and resulted in amplification of leaky activity in Glk for glucose phosphorylation and upregulation of glycolytic and other growth-related genes. Notably, we determined that these mutations appeared and were fixed in the evolving populations between 48 and 72 h of cultivation, which resulted in the selection of fast-growing mutants during one ALE experiments in batch cultures of 80 h duration.Key points• ALE experiments selected evolved mutants through different fitness landscapes in which galR was the target of different mutations: SNPs, deletions, and insertion of IS.• Key mutations in evolving mutants appeared and fixed at 48-72 h of cultivation.• ALE experiments led to increased understanding of the genetics of cellular adaptation to carbon source limitation.

Cross-Stress Adaptation in a Piezophilic and Hyperthermophilic Archaeon From Deep Sea Hydrothermal Vent

Hyperthermophiles, living in environments above 80°C and usually coupling with multi-extreme environmental stresses, have drawn great attention due to their application potential in biotechnology and being the primitive extant forms of life. Studies on their survival and adaptation mechanisms have extended our understanding on how lives thrive under extreme conditions. During these studies, the "cross-stress" behavior in various organisms has been observed between the extreme high temperature and other environmental stresses. Despite the broad observation, the global view of the cross-stress behavior remains unclear in hyperthermophiles, leaving a knowledge gap in our understanding of extreme adaptation. In this study, we performed a global quantitative proteomic analysis under extreme temperatures, pH, hydrostatic pressure (HP), and salinity on an archaeal strain, Thermococcus eurythermalis A501, which has outstanding growth capability on a wide range of temperatures (50-100°C), pH (4-9), and HPs (0.1-70 MPa), but a narrow range of NaCl (1.0-5.0 %, w/v). The proteomic analysis (79.8% genome coverage) demonstrated that approximately 61.5% of the significant differentially expressed proteins (DEPs) responded to multiple stresses. The responses to most of the tested stresses were closely correlated, except the responses to high salinity and low temperature. The top three enriched universal responding processes include the biosynthesis and protection of macromolecules, biosynthesis and metabolism of amino acids, ion transport, and binding activities. In addition, this study also revealed that the specific dual-stress responding processes, such as the membrane lipids for both cold and HP stresses and the signal transduction for both hyperosmotic and heat stresses, as well as the sodium-dependent energetic processes might be the limiting factor of the growth range in salinity. The present study is the first to examine the global cross-stress responses in a piezophilic hyperthermophile at the proteomic level. Our findings provide direct evidences of the cross-stress adaptation strategy (33.5% of coding-genes) to multiple stresses and highlight the specific and unique responding processes (0.22-0.63% of coding genes for each) to extreme temperature, pH, salinity, and pressure, which are highly relevant to the fields of evolutionary biology as well as next generation industrial biotechnology (NGIB).

Short- and Long-Term Transcriptomic Responses of Escherichia coli to Biocides: a Systems Analysis

The mechanisms of the bacterial response to biocides are poorly understood, despite their broad application. To identify the genetic basis and pathways implicated in the biocide stress response, we exposed Escherichia coli populations to 10 ubiquitous biocides. By comparing the transcriptional responses between a short-term exposure (30 min) and a long-term exposure (8 to 12 h) to biocide stress, we established the common gene and pathway clusters that are implicated in general and biocide-specific stress responses. Our analysis revealed a temporal choreography, starting from the upregulation of chaperones to the subsequent repression of motility and chemotaxis pathways and the induction of an anaerobic pool of enzymes and biofilm regulators. A systematic analysis of the transcriptional data identified a zur-regulated gene cluster to be highly active in the stress response against sodium hypochlorite and peracetic acid, presenting a link between the biocide stress response and zinc homeostasis. Susceptibility assays with knockout mutants further validated our findings and provide clear targets for downstream investigation of the implicated mechanisms of action.IMPORTANCE Antiseptics and disinfectant products are of great importance to control and eliminate pathogens, especially in settings such as hospitals and the food industry. Such products are widely distributed and frequently poorly regulated. Occasional outbreaks have been associated with microbes resistant to such compounds, and researchers have indicated potential cross-resistance with antibiotics. Despite that, there are many gaps in knowledge about the bacterial stress response and the mechanisms of microbial resistance to antiseptics and disinfectants. We investigated the stress response of the bacterium Escherichia coli to 10 common disinfectant and antiseptic chemicals to shed light on the potential mechanisms of tolerance to such compounds.

Understanding metabolic adaptation by using bacterial laboratory evolution and trans-omics analysis

Many diseases such as metabolic syndrome, cancer, inflammatory diseases, and pathological phenomena can be understood as an adaptive reconstitution of the metabolic state (metabolic adaptation). One of the effective approaches to reveal the property of metabolic networks is using model organisms such as microorganisms that are easier to experiment with than higher organisms. Using the laboratory evolution approach, we can elucidate the evolutionary dynamics in various stress environments, which provide us an understanding of the metabolic adaptation. In addition, the integration of omics data and phenotypic data enables us to clarify the genetic and phenotypic alterations during adaptation. In this review, we describe our recent studies on bacterial laboratory evolution and the omics approach to clarify the stress adaptation process. We have also obtained high-dimensional phenotypic data using our automated culture system. By combining these genomic and transcriptomic data within high-throughput phenotypic data, we can discuss the complex trans-omics network of metabolic adaptation.

Compounding Effects of Climate Warming and Antibiotic Resistance

Bacteria have evolved diverse mechanisms to survive environments with antibiotics. Temperature is both a key factor that affects the survival of bacteria in the presence of antibiotics and an environmental trait that is drastically increasing due to climate change. Therefore, it is timely and important to understand links between temperature changes and selection of antibiotic resistance. This review examines these links by synthesizing results from laboratories, hospitals, and environmental studies. First, we describe the transient physiological responses to temperature that alter cellular behavior and lead to antibiotic tolerance and persistence. Second, we focus on the link between thermal stress and the evolution and maintenance of antibiotic resistance mutations. Finally, we explore how local and global changes in temperature are associated with increases in antibiotic resistance and its spread. We suggest that a multidisciplinary, multiscale approach is critical to fully understand how temperature changes are contributing to the antibiotic crisis.

The Landscape of Adaptive Evolution of a Gut Commensal Bacteria in Aging Mice

Aging is a complex process, with many associated time-dependent phenotypes. The gut microbiota have long been postulated as an important factor in shaping healthy aging [1, 2]. During aging, changes in the microbiota composition occur, with taxa that are rare in adults becoming dominant in the elderly [3, 4]. Increased inflammation associated with aging is also known to modulate and be modulated by the microbiota [5]. Ecological interactions are known to affect the evolution of bacteria both in vitro [6] and in vivo [7], but the extent to which these and the host age-dependent inflammatory environment can alter the pattern of evolutionary change of a gut commensal lineage is still unknown [8]. Here, we provide the first genomic analysis of such evolution in cohorts of old mice, under controlled host genetics and lifestyle conditions. We find that Escherichia coli evolution when colonizing the gut of old mice significantly differs from its evolution in young mice. Evolution toward metabolic adaptation is slower in old than young mice, and mutational targets concerning stress-related functions were found specifically in the inflamed gut of old mice. Taking the genetic basis of E. coli short-term evolution as a reflection of the environment it experiences, the sequencing data indicate that aging imposes a more stressful environment to this important colonizer of the mammalian gut.

Microbial regulation of natural antibiotic resistance: Understanding the protist-bacteria interactions for evolution of soil resistome

The emergence, evolution and spread of antibiotic resistance genes (ARGs) in the environment represent a global threat to human health. Our knowledge of antibiotic resistance in human-impacted ecosystems is rapidly growing with antibiotic use, organic fertilization and wastewater irrigation identified as key selection pressures. However, the importance of biological interactions, especially predation and competition, as a potential driver of antibiotic resistance in the natural environment with limited anthropogenic disturbance remains largely overlooked. Stress-affected bacteria develop resistance to maximize competition and survival, and similarly bacteria may develop resistance to fight stress under the predation pressure of protists, an essential component of the soil microbiome. In this article, we summarized the major findings for the prevalence of natural ARGs on our planet and discussed the potential selection pressures driving the evolution and development of antibiotic resistance in natural settings. This is the first article that reviewed the potential links between protists and the antibiotic resistance of bacteria, and highlighted the importance of predation by protists as a crucial selection pressure of antibiotic resistance in the absence of anthropogenic disturbance. We conclude that an improved ecological understanding of the protists-bacteria interactions and other biological relationships would greatly expand our ability to predict and mitigate the environmental antibiotic resistance under the context of global change.

CgSTE11 mediates cross tolerance to multiple environmental stressors in Candida glabrata

Candida glabrata is a human commensal and an opportunistic human fungal pathogen. It is more closely related to the model yeast Saccharomyces cerevisiae than other Candida spp. Compared with S. cerevisiae, C. glabrata exhibits higher innate tolerance to various environmental stressors, including hyperthermal stress. Here we investigate the molecular mechanisms of C. glabrata adaptation to heat stress via adaptive laboratory evolution. We show that all parallel evolved populations readily adapt to hyperthermal challenge (from 47 °C to 50 °C) and exhibit convergence in evolved phenotypes with extensive cross-tolerance to various other environmental stressors such as oxidants, acids, and alcohols. Genome resequencing identified fixation of mutations in CgSTE11 in all parallel evolved populations. The CgSTE11 homolog in S. cerevisiae plays crucial roles in various mitogen-activated protein kinase (MAPK) signaling pathways, but its role is less understood in C. glabrata. Subsequent verification confirmed that CgSTE11 is important in hyperthermal tolerance and the observed extensive cross-tolerance to other environmental stressors. These results support the hypothesis that CgSTE11 mediates cross-talks between MAPK signaling pathways in C. glabrata in response to environmental challenges.

The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology

Harnessing the process of natural selection to obtain and understand new microbial phenotypes has become increasingly possible due to advances in culturing techniques, DNA sequencing, bioinformatics, and genetic engineering. Accordingly, Adaptive Laboratory Evolution (ALE) experiments represent a powerful approach both to investigate the evolutionary forces influencing strain phenotypes, performance, and stability, and to acquire production strains that contain beneficial mutations. In this review, we summarize and categorize the applications of ALE to various aspects of microbial physiology pertinent to industrial bioproduction by collecting case studies that highlight the multitude of ways in which evolution can facilitate the strain construction process. Further, we discuss principles that inform experimental design, complementary approaches such as computational modeling that help maximize utility, and the future of ALE as an efficient strain design and build tool driven by growing adoption and improvements in automation.

Benzalkonium Chlorides: Uses, Regulatory Status, and Microbial Resistance

Benzalkonium chlorides (BACs) are chemicals with widespread applications due to their broad-spectrum antimicrobial properties against bacteria, fungi, and viruses. This review provides an overview of the market for BACs, as well as regulatory measures and available data on safety, toxicity, and environmental contamination. We focus on the effect of frequent exposure of microbial communities to BACs and the potential for cross-resistant phenotypes to emerge. Toward this goal, we review BAC concentrations in consumer products, their correlation with the emergence of tolerance in microbial populations, and the associated risk potential. Our analysis suggests that the ubiquitous and frequent use of BACs in commercial products can generate selective environments that favor microbial phenotypes potentially cross-resistant to a variety of compounds. An analysis of benefits versus risks should be the guidepost for regulatory actions regarding compounds such as BACs.

Contingency and determinism in evolution: Replaying life’s tape

Historical processes display some degree of “contingency,” meaning their outcomes are sensitive to seemingly inconsequential events that can fundamentally change the future. Contingency is what makes historical outcomes unpredictable. Unlike many other natural phenomena, evolution is a historical process. Evolutionary change is often driven by the deterministic force of natural selection, but natural selection works upon variation that arises unpredictably through time by random mutation, and even beneficial mutations can be lost by chance through genetic drift. Moreover, evolution has taken place within a planetary environment with a particular history of its own. This tension between determinism and contingency makes evolutionary biology a kind of hybrid between science and history. While philosophers of science examine the nuances of contingency, biologists have performed many empirical studies of evolutionary repeatability and contingency. Here, we review the experimental and comparative evidence from these studies. Replicate populations in evolutionary “replay” experiments often show parallel changes, especially in overall performance, although idiosyncratic outcomes show that the particulars of a lineage’s history can affect which of several evolutionary paths is taken. Comparative biologists have found many notable examples of convergent adaptation to similar conditions, but quantification of how frequently such convergence occurs is difficult. On balance, the evidence indicates that evolution tends to be surprisingly repeatable among closely related lineages, but disparate outcomes become more likely as the footprint of history grows deeper. Ongoing research on the structure of adaptive landscapes is providing additional insight into the interplay of fate and chance in the evolutionary process.

Understanding and engineering alcohol-tolerant bacteria using OMICS technology

Microbes are capable of producing alcohols, making them an important source of alternative energy that can replace fossil fuels. However, these alcohols can be toxic to the microbes themselves, retaring or inhibiting cell growth and decreasing the production yield. One solution is improving the alcohol tolerance of such alcohol-producing organisms. Advances in omics technologies, including transcriptomic, proteomic, metabolomic, and genomic technologies, have helped us understand the complex mechanisms underlying alcohol toxicity, and such advances could assist in devising strategies for engineering alcohol-tolerant strains. This review highlights these advances and discusses strategies for improving alcohol tolerance using omics analyses.

Modeling the multi-scale mechanisms of macromolecular resource allocation

As microbes face changing environments, they dynamically allocate macromolecular resources to produce a particular phenotypic state. Broad 'omics' data sets have revealed several interesting phenomena regarding how the proteome is allocated under differing conditions, but the functional consequences of these states and how they are achieved remain open questions. Various types of multi-scale mathematical models have been used to elucidate the genetic basis for systems-level adaptations. In this review, we outline several different strategies by which microbes accomplish resource allocation and detail how mathematical models have aided in our understanding of these processes. Ultimately, such modeling efforts have helped elucidate the principles of proteome allocation and hold promise for further discovery.

Predicting the evolution of Escherichia coli by a data-driven approach

A tantalizing question in evolutionary biology is whether evolution can be predicted from past experiences. To address this question, we created a coherent compendium of more than 15,000 mutation events for the bacterium Escherichia coli under 178 distinct environmental settings. Compendium analysis provides a comprehensive view of the explored environments, mutation hotspots and mutation co-occurrence. While the mutations shared across all replicates decrease with the number of replicates, our results argue that the pairwise overlapping ratio remains the same, regardless of the number of replicates. An ensemble of predictors trained on the mutation compendium and tested in forward validation over 35 evolution replicates achieves a 49.2 ± 5.8% (mean ± std) precision and 34.5 ± 5.7% recall in predicting mutation targets. This work demonstrates how integrated datasets can be harnessed to create predictive models of evolution at a gene level and elucidate the effect of evolutionary processes in well-defined environments.

How reproducible evolutionary processes are remains an important question in evolutionary biology. Here, the authors compile a compendium of more than 15,000 mutation events for Escherichia coli under 178 distinct environmental settings, and develop an ensemble of predictors to predict evolution at a gene level.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.

Stressor interaction networks suggest antibiotic resistance co-opted from stress responses to temperature

Environmental factors like temperature, pressure, and pH partly shaped the evolution of life. As life progressed, new stressors (e.g., poisons and antibiotics) arose as part of an arms race among organisms. Here we ask if cells co-opted existing mechanisms to respond to new stressors, or whether new responses evolved de novo. We use a network-clustering approach based purely on phenotypic growth measurements and interactions among the effects of stressors on population growth. We apply this method to two types of stressors-temperature and antibiotics-to discover the extent to which their cellular responses overlap in Escherichia coli. Our clustering reveals that responses to low and high temperatures are clearly separated, and each is grouped with responses to antibiotics that have similar effects to cold or heat, respectively. As further support, we use a library of transcriptional fluorescent reporters to confirm heat-shock and cold-shock genes are induced by antibiotics. We also show strains evolved at high temperatures are more sensitive to antibiotics that mimic the effects of cold. Taken together, our results strongly suggest that temperature stress responses have been co-opted to deal with antibiotic stress.

Engineered global regulator H-NS improves the acid tolerance of E. coli

Background

Acid stress is often encountered during industrial fermentation as a result of the accumulation of acidic metabolites. Acid stress increases the intracellular acidity and can cause DNA damage and denaturation of essential enzymes, thus leading to a decrease of growth and fermentation yields. Although acid stress can be relieved by addition of a base to the medium, fermentations with acid-tolerant strains are generally considered much more efficient and cost-effective.

Results

In this study, the global regulator H-NS was found to have significant influence on the acid tolerance of E. coli. The final OD₆₀₀ of strains overexpressing H-NS increased by 24% compared to control, when cultured for 24 h at pH 4.5 using HCl as an acid agent. To further improve the acid tolerance, a library of H-NS was constructed by error-prone PCR and subjected to selection. Five mutants that conferred a significant growth advantage compared to the control strain were obtained. The final OD₆₀₀ of strains harboring the five H-NS mutants was enhanced by 26–53%, and their survival rate was increased by 10- to 100-fold at pH 2.5. Further investigation showed that the improved acid tolerance of H-NS mutants coincides with the activation of multiple acid resistance mechanisms, in particular the glutamate- and glutamine-dependent acid resistance system (AR2). The improved acid tolerance of H-NS mutants was also demonstrated in media acidified by acetic acid and succinic acid, which are common acidic fermentation by-products or products.

Conclusions

The results obtained in this work demonstrate that the engineering of H-NS can enhance the acid tolerance of E. coli. More in general, this study shows the potential of the engineering of global regulators acting as repressors, such as H-NS, as a promising method to obtain phenotypes of interest. This approach could expand the spectrum of application of global transcription machinery engineering.

Electronic supplementary material

The online version of this article (10.1186/s12934-018-0966-z) contains supplementary material, which is available to authorized users.

Assessing the benefits of horizontal gene transfer by laboratory evolution and genome sequencing

BACKGROUND

Recombination is widespread across the tree of life, because it helps purge deleterious mutations and creates novel adaptive traits. In prokaryotes, it often takes the form of horizontal gene transfer from a donor to a recipient bacterium. While such transfer is widespread in natural communities, its immediate fitness benefits are usually unknown. We asked whether any such benefits depend on the environment, and on the identity of donor and recipient strains. To this end, we adapted Escherichia coli to two novel carbon sources over several hundred generations of laboratory evolution, exposing evolving populations to various DNA donors.

RESULTS

At the end of these experiments, we measured fitness and sequenced the genomes of 65 clones from 34 replicate populations to study the genetic changes associated with adaptive evolution. Furthermore, we identified candidate de novo beneficial mutations. During adaptive evolution on the first carbon source, 4-Hydroxyphenylacetic acid (HPA), recombining populations adapted better, which was likely mediated by acquiring the hpa operon from the donor. In contrast, recombining populations did not adapt better to the second carbon source, butyric acid, even though they suffered fewer extinctions than non-recombining populations. The amount of DNA transferred, but not its benefit, strongly depended on the donor-recipient strain combination.

CONCLUSIONS

To our knowledge, our study is the first to investigate the genomic consequences of prokaryotic recombination and horizontal gene transfer during laboratory evolution. It shows that the benefits of recombination strongly depend on the environment and the foreign DNA donor.

Functional Prediction of Hypothetical Transcription Factors of Escherichia coli K-12 Based on Expression Data

The repertoire of 304 DNA-binding transcription factors (TFs) in Escherichia coli K-12 has been described recently, with 196 TFs experimentally characterized and 108 proteins predicted by sequence comparisons. Based on 303 expression profile patterns retrieved from the Colombos database 12 clusters were identified, including hypothetical and experimentally characterized TFs, using a spectral clustering algorithm based on a 3NN graph built using 14 principal components that represent 65% of the variance of the expression data. In a posterior step, clusters were characterized in terms of their associated overrepresented functions, based on KEGG, Supfam annotations and Pfam assignments among other functional categories using an enrichment test, reinforcing the notion that the identified clusters are functionally similar among them. Based on these data, the we identified 12 clusters in which hypothetical and known TFs share similar regulatory and physiological functions, such as module associations of toxin-antitoxin (TA) systems with DNA repair mechanisms, amino acid biosynthesis, and carbon metabolism/transport, among others. This analysis has increased our knowledge about gene regulation in E. coli K-12 and can be further expanded to other organisms.