Adaptive evolution reveals a tradeoff between growth rate and oxidative stress during naphthoquinone-based aerobic respiration

Adaptive laboratory evolution for improved tolerance of vitamin K in Bacillus subtilis

Menaquinone-7 (MK-7), a subtype of vitamin K2 (VK2), assumes crucial roles in coagulation function, calcium homeostasis, and respiratory chain transmission. The production of MK-7 via microbial fermentation boasts mild technological conditions and high biocompatibility. Nevertheless, the redox activity of MK-7 imposes constraints on its excessive accumulation in microorganisms. To address this predicament, an adaptive laboratory evolution (ALE) protocol was implemented in Bacillus subtilis BS011, utilizing vitamin K3 (VK3) as a structural analog of MK-7. The resulting strain, BS012, exhibited heightened tolerance to high VK3 concentrations and demonstrated substantial enhancements in biofilm formation and total antioxidant capacity (T-AOC) when compared to BS011. Furthermore, MK-7 production in BS012 exceeded that of BS011 by 76% and 22% under static and shaking cultivation conditions, respectively. The molecular basis underlying the superior performance of BS012 was elucidated through genome and transcriptome analyses, encompassing observations of alterations in cell morphology, variations in central carbon and nitrogen metabolism, spore formation, and antioxidant systems. In summation, ALE technology can notably enhance the tolerance of B. subtilis to VK and increase MK-7 production, thus offering a theoretical framework for the microbial fermentation production of other VK2 subtypes. Additionally, the evolved strain BS012 can be developed for integration into probiotic formulations within the food industry to maintain intestinal flora homeostasis, mitigate osteoporosis risk, and reduce the incidence of cardiovascular disease. KEY POINTS: • Bacillus subtilis was evolved for improved vitamin K tolerance and menaquinone-7 (MK-7) production • Evolved strains formed wrinkled biofilms and elongated almost twofold in length • Evolved strains induced sporulation to improve tolerance when carbon was limited.

Rapid HPLC method reveals dynamic shifts in coenzyme Q redox state

Ubiquinol or coenzyme Q (CoQ) is a lipid-soluble electron carrier in the respiratory chain and an electron acceptor for various enzymes in metabolic pathways that intersect at this cofactor hub in the mitochondrial inner membrane. The reduced form of CoQ is an antioxidant, which protects against lipid peroxidation. In this study, we have optimized a UV-detected HPLC method for CoQ analysis from biological materials, which involves a rapid single-step extraction into n-propanol followed by direct sample injection onto a column. Using this method, we have measured the oxidized, reduced and total CoQ pools, and monitored shifts in the CoQ redox status in response to cell culture conditions and bioenergetic perturbations. We find that hypoxia or sulfide exposure induces a reductive shift in the intracellular CoQ pool. The effect of hypoxia is however, rapidly reversed by exposure to ambient air. Interventions at different loci in the electron transport chain can induce sizeable redox shifts in the oxidative or reductive direction, depending on whether they are up- or downstream of complex III. We have also used this method to confirm that CoQ levels are higher and more reduced in murine heart versus brain. In summary, the availability of a convenient HPLC-based method described herein, will facilitate studies on CoQ redox dynamics in response to environmental, nutritional and endogenous alterations.

Novel ecological interactions alter physiological responses of range-extending tropical and local temperate fishes under ocean warming

Global warming facilitates species range-expansions, leading to novel biological interactions between local and range-expanding species. Little is still known of how such novel interactions modify the performance of interacting species or how these interactions might be altered under climate change. Here, we used an aquarium experiment to investigate the novel ecological interactions between a poleward range-extending coral reef damselfish ("tropical-vagrant") and a local temperate species ("temperate-local") collected from a climate warming hotspot in SE Australia. We measured the effect of novel interactions (isolated vs. paired fish species) on energy expenditure (activity levels, oxidative stress, and antioxidant responses), energy gain (feeding rates), and growth rates of both fish species under present-day (23 °C) and future ocean temperatures (26 °C). Short-term growth rates were faster in both species under novel interactions (paired species), regardless of elevated temperature. Compared to isolated species, activity level, feeding rate and oxidative stress level were also higher in the paired temperate fish but not in the paired tropical fish. The tropical fish showed an increased feeding rate and long-term growth under elevated temperature, irrespective of novel interactions. We conclude that novel ecological interactions under climate change can be an important driver of physiological traits in sympatric tropical and temperate fishes and can mediate critical physiological performance of fishes under ocean warming.

Improving microbial bioproduction under low-oxygen conditions

Microbial bioconversion provides access to a wide range of sustainably produced chemicals and commodities. However, industrial-scale bioproduction process operations are preferred to be anaerobic due to the cost associated with oxygen transfer. Anaerobic bioconversion generally offers limited substrate utilization profiles, lower product yields, and reduced final product diversity compared with aerobic processes. Bioproduction under conditions of reduced oxygen can overcome the limitations of fully aerobic and anaerobic bioprocesses, but many microbial hosts are not developed for low-oxygen bioproduction. Here, we describe advances in microbial strain engineering involving the use of redox cofactor engineering, genome-scale metabolic modeling, and functional genomics to enable improved bioproduction processes under low oxygen and provide a viable path for scaling these bioproduction systems to industrial scales.

Investigation of Weak Noncovalent Interactions Directed by the Amino Substituent of Pyrido- and Pyrimido-[1,2-a]benzimidazole-8,9-diones

Quinones are small redox-active molecules that are able to form intra- and intermolecular interactions both in the solid state and in solution. On the basis of 6-amino-substituted pyrido- and pyrimido-[1,2-a]benzimidazole-8,9-diones, weak interactions were investigated by single-crystal X-ray and 1H NMR spectroscopy methods. Crystallization of quinone derivatives containing a -NH-CH2- fragment led to the formation of both chiral and achiral crystals. The presence of two forms with (endo form) and without (exo form) an intramolecular hydrogen bond was experimentally detected by X-ray crystallography analysis and variable-temperature (VT) 1H NMR experiments in the cases of isopentylamino- and benzylamino-substituted derivatives. Interestingly, the exo form dominates both in the solid state and in solution.

A multi-scale expression and regulation knowledge base for Escherichia coli

Transcriptomic data is accumulating rapidly; thus, scalable methods for extracting knowledge from this data are critical. Here, we assembled a top-down expression and regulation knowledge base for Escherichia coli. The expression component is a 1035-sample, high-quality RNA-seq compendium consisting of data generated in our lab using a single experimental protocol. The compendium contains diverse growth conditions, including: 9 media; 39 supplements, including antibiotics; 42 heterologous proteins; and 76 gene knockouts. Using this resource, we elucidated global expression patterns. We used machine learning to extract 201 modules that account for 86% of known regulatory interactions, creating the regulatory component. With these modules, we identified two novel regulons and quantified systems-level regulatory responses. We also integrated 1675 curated, publicly-available transcriptomes into the resource. We demonstrated workflows for analyzing new data against this knowledge base via deconstruction of regulation during aerobic transition. This resource illuminates the E. coli transcriptome at scale and provides a blueprint for top-down transcriptomic analysis of non-model organisms.

Effect of Biofloc Technology Enriches the Growth of Litopenaeus vannamei (Boone, 1931)

The use of probiotics in shrimp farms has expanded as an alternative to antibiotics, improving shrimp health, growth, disease control and water quality. However, the efficacy of probiotics in intensive systems using biofloc remains uncertain. This study investigated bioremediation and biocontrol of commercial probiotics using biofloc, analysing water quality and bacterial groups influencing shrimp performance. Thirteen microbial colonies were observed in the biofloc samples, and their evolutionary history was inferred using the neighbour-joining method. Analysis using MEGA6 software revealed 99.6% similarity between colony 1P1 and Virgibacillus sp. and 99.8% similarity between colony 2P2 and Bacillus kochii. The study analysed the biochemical and amino acid content of shrimp cultured using biofloc technology for 85 days. The study found that biofloc-cultured L. Vannamei flesh had higher levels of moisture (31%), ash (15.2%), protein (34%) and lipid (12.6%). No seasonal variations were observed between biofloc samples in winter and summer seasons. Protein levels were found to be appropriate for shrimp growth in both ex situ and in situ biofloc systems. The average growth rate (kg/m2) of biofloc-cultured shrimp was significantly greater than in normal pond shrimp in both samples. The feed conversion ratio in the biofloc tank was lower than in the usual pond-cultured shrimp, possibly due to lower growth rate, lower feeding frequency (2 times per day) and higher density. The growth of L. vannamei shrimp is influenced by stocking density, with higher stocking density affecting the average weight. The study also examined the growth biochemical and amino acid content of shrimp cultured using biofloc technology.

Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance

Relationships between the genome, transcriptome, and metabolome underlie all evolved phenotypes. However, it has proved difficult to elucidate these relationships because of the high number of variables measured. A recently developed data analytic method for characterizing the transcriptome can simplify interpretation by grouping genes into independently modulated sets (iModulons). Here, we demonstrate how iModulons reveal deep understanding of the effects of causal mutations and metabolic rewiring. We use adaptive laboratory evolution to generate E. coli strains that tolerate high levels of the redox cycling compound paraquat, which produces reactive oxygen species (ROS). We combine resequencing, iModulons, and metabolic models to elucidate six interacting stress-tolerance mechanisms: (1) modification of transport, (2) activation of ROS stress responses, (3) use of ROS-sensitive iron regulation, (4) motility, (5) broad transcriptional reallocation toward growth, and (6) metabolic rewiring to decrease NADH production. This work thus demonstrates the power of iModulon knowledge mapping for evolution analysis.

Recent advances in access to overcome cancer drug resistance by nanocarrier drug delivery system

Cancer is currently one of the most intractable diseases causing human death. Although the prognosis of tumor patients has been improved to a certain extent through various modern treatment methods, multidrug resistance (MDR) of tumor cells is still a major problem leading to clinical treatment failure. Chemotherapy resistance refers to the resistance of tumor cells and/or tissues to a drug, usually inherent or developed during treatment. Therefore, an urgent need to research the ideal drug delivery system to overcome the shortcoming of traditional chemotherapy. The rapid development of nanotechnology has brought us new enlightenments to solve this problem. The novel nanocarrier provides a considerably effective treatment to overcome the limitations of chemotherapy or other drugs resulting from systemic side effects such as resistance, high toxicity, lack of targeting, and off-target. Herein, we introduce several tumor MDR mechanisms and discuss novel nanoparticle technology applied to surmount cancer drug resistance. Nanomaterials contain liposomes, polymer conjugates, micelles, dendrimers, carbon-based, metal nanoparticles, and nucleotides which can be used to deliver chemotherapeutic drugs, photosensitizers, and small interfering RNA (siRNA). This review aims to elucidate the advantages of nanomedicine in overcoming cancer drug resistance and discuss the latest developments.

The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions

Fit phenotypes are achieved through optimal transcriptomic allocation. Here, we performed a high-resolution, multi-scale study of the transcriptomic tradeoff between two key fitness phenotypes, stress response (fear) and growth (greed), in Escherichia coli. We introduced twelve RNA polymerase (RNAP) mutations commonly acquired during adaptive laboratory evolution (ALE) and found that single mutations resulted in large shifts in the fear vs. greed tradeoff, likely through destabilizing the rpoB-rpoC interface. RpoS and GAD regulons drive the fear response while ribosomal proteins and the ppGpp regulon underlie greed. Growth rate selection pressure during ALE results in endpoint strains that often have RNAP mutations, with synergistic mutations reflective of particular conditions. A phylogenetic analysis found the tradeoff in numerous bacteria species. The results suggest that the fear vs. greed tradeoff represents a general principle of transcriptome allocation in bacteria where small genetic changes can result in large phenotypic adaptations to growth conditions.

The role of oxidative stress in genome destabilization and adaptive evolution of bacteria

The review is devoted to bacterial genome destabilization by oxidative stress. The article discusses the main groups of substances causing such stress. Stress regulons involved in destabilization of genetic material and mechanisms enhancing mutagenesis, bacterial genome rearrangements, and horizontal gene transfer, induced by oxidative damage to cell components are also considered. Based on the analysis of publications, it can be claimed that rapid development of new food substrates and ecological niches by microorganisms occurs due to acceleration of genetic changes induced by oxidative stress, mediated by several stress regulons (SOS, RpoS and RpoE) and under selective pressure. The authors conclude that non-lethal oxidative stress is probably-one of the fundamental processes that guide evolution of prokaryotes and a powerful universal trigger for adaptive destabilization of bacterial genome under changing environmental conditions.

Regulation of phosphate starvation-specific responses in Escherichia coli

Toxic agents added into the medium of rapidly growing Escherichia coli induce specific stress responses through the activation of specialized transcription factors. Each transcription factor and downstream regulon (e.g. SoxR) are linked to a unique stress (e.g. superoxide stress). Cells starved of phosphate induce several specific stress regulons during the transition to stationary phase when the growth rate is steadily declining. Whereas the regulatory cascades leading to the expression of specific stress regulons are well known in rapidly growing cells stressed by toxic products, they are poorly understood in cells starved of phosphate. The intent of this review is to both describe the unique mechanisms of activation of specialized transcription factors and discuss signalling cascades leading to the induction of specific stress regulons in phosphate-starved cells. Finally, I discuss unique defence mechanisms that could be induced in cells starved of ammonium and glucose.

Laboratory evolution reveals general and specific tolerance mechanisms for commodity chemicals

Although strain tolerance to high product concentrations is a barrier to the economically viable biomanufacturing of industrial chemicals, chemical tolerance mechanisms are often unknown. To reveal tolerance mechanisms, an automated platform was utilized to evolve Escherichia coli to grow optimally in the presence of 11 industrial chemicals (1,2-propanediol, 2,3-butanediol, glutarate, adipate, putrescine, hexamethylenediamine, butanol, isobutyrate, coumarate, octanoate, hexanoate), reaching tolerance at concentrations 60%-400% higher than initial toxic levels. Sequencing genomes of 223 isolates from 89 populations, reverse engineering, and cross-compound tolerance profiling were employed to uncover tolerance mechanisms. We show that: 1) cells are tolerized via frequent mutation of membrane transporters or cell wall-associated proteins (e.g., ProV, KgtP, SapB, NagA, NagC, MreB), transcription and translation machineries (e.g., RpoA, RpoB, RpoC, RpsA, RpsG, NusA, Rho), stress signaling proteins (e.g., RelA, SspA, SpoT, YobF), and for certain chemicals, regulators and enzymes in metabolism (e.g., MetJ, NadR, GudD, PurT); 2) osmotic stress plays a significant role in tolerance when chemical concentrations exceed a general threshold and mutated genes frequently overlap with those enabling chemical tolerance in membrane transporters and cell wall-associated proteins; 3) tolerization to a specific chemical generally improves tolerance to structurally similar compounds whereas a tradeoff can occur on dissimilar chemicals, and 4) using pre-tolerized starting isolates can hugely enhance the subsequent production of chemicals when a production pathway is inserted in many, but not all, evolved tolerized host strains, underpinning the need for evolving multiple parallel populations. Taken as a whole, this study provides a comprehensive genotype-phenotype map based on identified mutations and growth phenotypes for 223 chemical tolerant isolates.

Respiratory Quinone Switches from Menaquinone to Polyketide Quinone during the Development Cycle in Streptomyces sp. Strain MNU77

Type III polyketide synthases (PKSs) found across Streptomyces species are primarily known for synthesis of a vast repertoire of clinically and industrially relevant secondary metabolites. However, our understanding of the functional relevance of these bioactive metabolites in Streptomyces physiology is still limited. Recently, a role of type III PKS harboring gene cluster in producing alternate electron carrier, polyketide quinone (PkQ) was established in a related member of the Actinobacteria, Mycobacteria, highlighting the critical role these secondary metabolites play in primary cellular metabolism of the producer organism. Here, we report the developmental stage-specific transcriptional regulation of homologous type III PKS containing gene cluster in freshwater Streptomyces sp. strain MNU77. Gene expression analysis revealed the type III PKS gene cluster to be stringently regulated, with significant upregulation observed during the dormant sporulation stage of Streptomyces sp. MNU77. In contrast, the expression levels of only known electron carrier, menaquinone biosynthetic genes were interestingly found to be downregulated. Our liquid chromatography-high-resolution mass spectrometry (LC-HRMS) analysis of a metabolite extract from the Streptomyces sp. MNU77 spores also showed 10 times more metabolic abundance of PkQs than menaquinones. Furthermore, through heterologous complementation studies, we demonstrate that Streptomyces sp. MNU77 type III PKS rescues a respiratory defect of the Mycobacterium smegmatis type III PKS deletion mutant. Together, our studies reveal that freshwater Streptomyces sp. MNU77 robustly produces novel PkQs during the sporulation stage, suggesting utilization of PkQs as alternate electron carriers across Actinobacteria during dormant hypoxic conditions. IMPORTANCE The complex developmental life cycle of Streptomyces sp. mandates efficient cellular respiratory reconfiguration for a smooth transition from aerated nutrient-rich vegetative hyphal growth to the hypoxic-dormant sporulation stage. Polyketide quinones (PkQs) have recently been identified as a class of alternate electron carriers from a related member of the Actinobacteria, Mycobacteria, that facilitates maintenance of membrane potential in oxygen-deficient niches. Our studies with the newly identified freshwater Streptomyces sp. strain MNU77 show conditional transcriptional upregulation and metabolic abundance of PkQs in the spore state of the Streptomyces life cycle. In parallel, the levels of menaquinones, the only known Streptomyces electron carrier, were downregulated, suggesting deployment of PkQs as universal electron carriers in low-oxygen, unfavorable conditions across the Actinobacteria family.

Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes

Genotype-fitness maps of evolution have been well characterized for biological components, such as RNA and proteins, but remain less clear for systems-level properties, such as those of metabolic and transcriptional regulatory networks. Here, we take multi-omics measurements of 6 different E. coli strains throughout adaptive laboratory evolution (ALE) to maximal growth fitness. The results show the following: (i) convergence in most overall phenotypic measures across all strains, with the notable exception of divergence in NADPH production mechanisms; (ii) conserved transcriptomic adaptations, describing increased expression of growth promoting genes but decreased expression of stress response and structural components; (iii) four groups of regulatory trade-offs underlying the adjustment of transcriptome composition; and (iv) correlates that link causal mutations to systems-level adaptations, including mutation-pathway flux correlates and mutation-transcriptome composition correlates. We thus show that fitness landscapes for ALE can be described with two layers of causation: one based on system-level properties (continuous variables) and the other based on mutations (discrete variables). IMPORTANCE Understanding the mechanisms of microbial adaptation will help combat the evolution of drug-resistant microbes and enable predictive genome design. Although experimental evolution allows us to identify the causal mutations underlying microbial adaptation, it remains unclear how causal mutations enable increased fitness and is often explained in terms of individual components (i.e., enzyme rate) as opposed to biological systems (i.e., pathways). Here, we find that causal mutations in E. coli are linked to systems-level changes in NADPH balance and expression of stress response genes. These systems-level adaptation patterns are conserved across diverse E. coli strains and thus identify cofactor balance and proteome reallocation as dominant constraints governing microbial adaptation.

Chemistry of Lipoquinones: Properties, Synthesis, and Membrane Location of Ubiquinones, Plastoquinones, and Menaquinones

Lipoquinones are the topic of this review and are a class of hydrophobic lipid molecules with key biological functions that are linked to their structure, properties, and location within a biological membrane. Ubiquinones, plastoquinones, and menaquinones vary regarding their quinone headgroup, isoprenoid sidechain, properties, and biological functions, including the shuttling of electrons between membrane-bound protein complexes within the electron transport chain. Lipoquinones are highly hydrophobic molecules that are soluble in organic solvents and insoluble in aqueous solution, causing obstacles in water-based assays that measure their chemical properties, enzyme activities and effects on cell growth. Little is known about the location and ultimately movement of lipoquinones in the membrane, and these properties are topics described in this review. Computational studies are particularly abundant in the recent years in this area, and there is far less experimental evidence to verify the often conflicting interpretations and conclusions that result from computational studies of very different membrane model systems. Some recent experimental studies have described using truncated lipoquinone derivatives, such as ubiquinone-2 (UQ-2) and menaquinone-2 (MK-2), to investigate their conformation, their location in the membrane, and their biological function. Truncated lipoquinone derivatives are soluble in water-based assays, and hence can serve as excellent analogs for study even though they are more mobile in the membrane than the longer chain counterparts. In this review, we will discuss the properties, location in the membrane, and syntheses of three main classes of lipoquinones including truncated derivatives. Our goal is to highlight the importance of bridging the gap between experimental and computational methods and to incorporate properties-focused considerations when proposing future studies relating to the function of lipoquinones in membranes.

Advanced transcriptomic analysis reveals the role of efflux pumps and media composition in antibiotic responses of Pseudomonas aeruginosa

Pseudomonas aeruginosa is an opportunistic pathogen and major cause of hospital-acquired infections. The virulence of P. aeruginosa is largely determined by its transcriptional regulatory network (TRN). We used 411 transcription profiles of P. aeruginosa from diverse growth conditions to construct a quantitative TRN by identifying independently modulated sets of genes (called iModulons) and their condition-specific activity levels. The current study focused on the use of iModulons to analyze the biofilm production and antibiotic resistance of P. aeruginosa. Our analysis revealed: (i) 116 iModulons, 81 of which show strong association with known regulators; (ii) novel roles of regulators in modulating antibiotics efflux pumps; (iii) substrate-efflux pump associations; (iv) differential iModulon activity in response to beta-lactam antibiotics in bacteriological and physiological media; (v) differential activation of 'Cell Division' iModulon resulting from exposure to different beta-lactam antibiotics and (vi) a role of the PprB iModulon in the stress-induced transition from planktonic to biofilm lifestyle. In light of these results, the construction of an iModulon-based TRN provides a transcriptional regulatory basis for key aspects of P. aeruginosa infection, such as antibiotic stress responses and biofilm formation. Taken together, our results offer a novel mechanistic understanding of P. aeruginosa virulence.

Signatures of polygenic adaptation align with genome-wide methylation patterns in wild strawberry plants

Epigenetic inheritance can drive adaptive evolution independently of DNA sequence variation. However, to what extent epigenetic variation represents an autonomous evolutionary force remains largely elusive. Through gene ontology and comparative analyses of genomic and epigenomic variation of wild strawberry plants raised in distinct drought settings, we characterised genome-wide covariation between single nucleotide polymorphisms (SNPs) and differentially methylated cytosines (DMCs). Covariation between SNPs and DMCs was independent of genomic proximity, but instead associated with fitness-related processes such as stress responses, genome regulation and reproduction. We expected this functional SNP-DMC covariation to be driven by adaptive evolution canalising SNP and DMC variation, but instead observed significantly lower covariation with DMCs for adaptive rather than for neutral SNPs. Drought-induced DMCs frequently co-varied with tens of SNPs, suggesting high genomic redundancy as a broad potential basis for polygenic adaptation of gene expression. Our findings suggest that stress-responsive DMCs initially co-vary with many SNPs under increased environmental stress, and that natural selection acting upon several of these SNPs subsequently reduces standing covariation with stress-responsive DMCs. Our study supports DNA methylation profiles that represent complex quantitative traits rather than autonomous evolutionary forces. We provide a conceptual framework for polygenic regulation and adaptation shaping genome-wide methylation patterns in plants.

A review on enzyme complexes of electron transport chain from Mycobacterium tuberculosis as promising drug targets

Energy metabolism is a universal process occurring in all life forms. In Mycobacterium tuberculosis (Mtb), energy production is carried out in two possible ways, oxidative phosphorylation (OxPhos) and substrate-level phosphorylation. Mtb is an obligate aerobic bacterium, making it dependent on OxPhos for ATP synthesis and growth. Mtb inhabits varied micro-niches during the infection cycle, outside and within the host cells, which alters its primary metabolic pathways during the pathogenesis. In this review, we discuss cellular respiration in the context of the mechanism and structural importance of the proteins and enzyme complexes involved. These protein-protein complexes have been proven to be essential for Mtb virulence as they aid the bacteria's survival during aerobic and hypoxic conditions. ATP synthase, a crucial component of the electron transport chain, has been in the limelight, as a prominent drug target against tuberculosis. Likewise, in this review, we have explored other protein-protein complexes of the OxPhos pathway, their functional essentiality, and their mechanism in Mtb's diverse lifecycle. The review summarises crucial target proteins and reported inhibitors of the electron transport chain pathway of Mtb.

The respiratory lipoquinone, menaquinone, functions as an inducer of genes regulated by the Mycobacterium smegmatis repressor MSMEG_2295

A previous study reported that the Mycobacterium smegmatis (Msm) protein MSMEG_2295 is a repressor controlling the expression of several genes, including that for MSMEG_5125, a putative isoprenoid binding protein belonging to the YceI family, and DinB2, a DNA damage repair enzyme. This repressor is encoded by the first gene of the operon that also expresses the gene for DinB2. Targeted inhibition of MSMEG_5125 using CRISPRi technology resulted in a significant loss of Msm's respiratory activity and viability. Since this protein has been predicted to be an isoprenoid binding protein, we suspected a role of menaquinones, which are isoprenoid naphthoquinones, in the observed phenomenon. Accordingly, we tested whether MSMEG_5125's deficiency-induced lethality could be reversed by adding menaquinone. The result was positive, implying cooperation between MSMEG_5125 and menaquinone in bringing about respiration. Inhibition of MSMEG_5125 expression led to the induction of MSMEG_0089 and 2296, two hallmark genes of the MSMEG_2295 regulon. This result suggests that when MSMEG_5125 becomes limiting, a feedback-loop derepresses the MSMEG_2295 regulon genes, including its own. Interestingly, menaquinone functioned as an inducer of MSMEG_5125, indicating that it is likely to mediate the feedback mechanism. This result also strengthens our hypothesis that the functions of menaquinone and MSMEG_5125 are interrelated. Menaquinone also induced the MSMEG_2295-controlled operon MSMEG_2295-2294 (dinB2) not induced following the inactivation of MSMEG_5125. Therefore, the activation mechanism of MSMEG_2295-regulated genes may not be the same for all, although derepression is likely to be a common feature. In vitro, menaquinone abolished MSMEG_2295's DNA binding activity by interacting with it, confirming its role as an inducer. Therefore, a menaquinone-MSMEG_5125-regulated gene expression circuit controls Msm respiration and possibly oxidative stress-induced DNA damage repair.

Machine learning from Pseudomonas aeruginosa transcriptomes identifies independently modulated sets of genes associated with known transcriptional regulators

The transcriptional regulatory network (TRN) of Pseudomonas aeruginosa coordinates cellular processes in response to stimuli. We used 364 transcriptomes (281 publicly available + 83 in-house generated) to reconstruct the TRN of P. aeruginosa using independent component analysis. We identified 104 independently modulated sets of genes (iModulons) among which 81 reflect the effects of known transcriptional regulators. We identified iModulons that (i) play an important role in defining the genomic boundaries of biosynthetic gene clusters (BGCs), (ii) show increased expression of the BGCs and associated secretion systems in nutrient conditions that are important in cystic fibrosis, (iii) show the presence of a novel ribosomally synthesized and post-translationally modified peptide (RiPP) BGC which might have a role in P. aeruginosa virulence, (iv) exhibit interplay of amino acid metabolism regulation and central metabolism across different carbon sources and (v) clustered according to their activity changes to define iron and sulfur stimulons. Finally, we compared the identified iModulons of P. aeruginosa with those previously described in Escherichia coli to observe conserved regulons across two Gram-negative species. This comprehensive TRN framework encompasses the majority of the transcriptional regulatory machinery in P. aeruginosa, and thus should prove foundational for future research into its physiological functions.

Inhibition of NPC1L1 disrupts adaptive responses of drug-tolerant persister cells to chemotherapy

Entering a drug‐tolerant persister (DTP) state of cancer cells is a transient self‐adaptive mechanism by which a residual cell subpopulation accelerates tumor progression. Here, we identified the acquisition of a DTP phenotype in multidrug‐resistant (MDR) cancer cells as a tolerance response to routine combination treatment. Characterization of MDR cancer cells with a DTP state by RNA‐seq revealed that these cells partially prevented chemotherapy‐triggered oxidative stress by promoting NPC1L1‐regulated uptake of vitamin E. Treatment with the NPC1L1 inhibitor ezetimibe further enhanced the therapeutic effect of combinatorial therapy by inducing methuosis. Mechanistically, we demonstrated that NRF2 was involved in transcriptional regulation of NPC1L1 by binding to the −205 to −215 bp site on its promoter. Decreased DNA methylation was also related partially to this process. Furthermore, we confirmed that a triple‐combination of chemotherapeutic agents, verapamil, and ezetimibe, had a significant anti‐tumor effect and prevented tumor recurrence in mice. Together, our study provides a novel insight into the role of DTP state and emphasizes the importance of disrupting redox homeostasis during cancer therapy.

Chiroptical Switching and Quantitative Chirality Sensing with (Pseudo)halogenated Quinones

(Pseudo)halogenated quinones react smoothly with chiral amines, amino alcohols, and amino acids toward push-pull conjugates with optical sensing and switching applications. The chiroptically active conjugates serve as redox switches between two reversibly interconverting states with remarkably different UV and CD signatures. Addition of sodium borohydride generates a hydroquinone derivative that is quantitatively re-oxidized to the original quinone upon exposure to air. This chiroptical quinone/hydroquinone redox switch system combines several attractive features such as simple set-up, use of inexpensive chemicals, short response time, and thermal and photochemical stability. A conceptually new sensing approach that is based on integrated chiroptical amplification and redox switching enables on-the-fly deconvolution of otherwise overlapping CD spectra and is used for quantitative er analysis of challenging samples containing constitutional isomers in varying enantiomeric compositions.

Changes in the distribution of fitness effects and adaptive mutational spectra following a single first step towards adaptation

Historical contingency and diminishing returns epistasis have been typically studied for relatively divergent genotypes and/or over long evolutionary timescales. Here, we use Saccharomyces cerevisiae to study the extent of diminishing returns and the changes in the adaptive mutational spectra following a single first adaptive mutational step. We further evolve three clones that arose under identical conditions from a common ancestor. We follow their evolutionary dynamics by lineage tracking and determine adaptive outcomes using fitness assays and whole genome sequencing. We find that diminishing returns manifests as smaller fitness gains during the 2^nd step of adaptation compared to the 1^st step, mainly due to a compressed distribution of fitness effects. We also find that the beneficial mutational spectra for the 2^nd adaptive step are contingent on the 1^st step, as we see both shared and diverging adaptive strategies. Finally, we find that adaptive loss-of-function mutations, such as nonsense and frameshift mutations, are less common in the second step of adaptation than in the first step.

Analyses of both natural and experimental evolution suggest that adaptation depends on the evolutionary past and adaptive potential decreases over time. Here, by tracking yeast adaptation with DNA barcoding, the authors show that such evolutionary phenomena can be observed even after a single adaptive step.

Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

Sustaining a robust metabolic network requires a balanced and fully functioning proteome. In addition to amino acids, many enzymes require cofactors (coenzymes and engrafted prosthetic groups) to function properly. Extensively validated resource allocation models, such as genome-scale models of metabolism and gene expression (ME-models), have the ability to compute an optimal proteome composition underlying a metabolic phenotype, including the provision of all required cofactors. Here we apply the ME-model for Escherichia coli K-12 MG1655 to computationally examine how environmental conditions change the proteome and its accompanying cofactor usage. We found that: (1) The cofactor requirements computed by the ME-model mostly agree with the standard biomass objective function used in models of metabolism alone (M-models); (2) ME-model computations reveal non-intuitive variability in cofactor use under different growth conditions; (3) An analysis of ME-model predicted protein use in aerobic and anaerobic conditions suggests an enrichment in the use of peroxyl scavenging acids in the proteins used to sustain aerobic growth; (4) The ME-model could describe how limitation in key protein components affect the metabolic state of E. coli. Genome-scale models have thus reached a level of sophistication where they reveal intricate properties of functional proteomes and how they support different E. coli lifestyles.

Escherichia coli is capable of growing in many environments, each of which requires a different collection of enzymes to metabolize the nutrients within that environment. Each individual enzyme requires its own set of amino acids and oftentimes cofactors, which are accessory molecules essential for the enzyme to function. Thus, the composition of the micronutrients (amino acids, cofactors, etc.) within a cell will differ depending on its metabolic needs. The presented work is the first effort to employ metabolic models to probe the connection between E. coli’s diverse growth environments and its biomass composition. We first show how differences in model-predicted enzyme use for aerobic or anaerobic growth results in distinct amino acid and cofactor usage. Alternatively, we show that the metabolic models can predict how modifying the cell’s biomass composition will affect growth. For example, by modeling the exposure of E. coli to trimethoprim or sulfamethoxazole—two antibiotics that target folate (vitamin B9) synthesis—we predicted how E. coli could adapt to grow under folate-limited conditions. This work demonstrates how models can be used to study antibiotic resistance of drugs that target amino acid or cofactor synthesis.

Liposoluble quinone promotes the reduction of hydrophobic mineral and extracellular electron transfer of Shewanella oneidensis MR-1

A large number of reaction systems are composed of hydrophobic interfaces and microorganisms in natural environment. However, it is not clear how microorganisms adjust their breathing patterns and respond to hydrophobic interfaces. Here, Shewanella oneidensis MR-1 was used to reduce ferrihydrite of a hydrophobic surface. Through Fe(II) kinetic analysis, it was found that the reduction rate of hydrophobic ferrihydrite was 1.8 times that of hydrophilic one. The hydrophobic surface of the mineral hinders the way the electroactive microorganism uses the water-soluble electron mediator riboflavin for indirect electron transfer and promotes MR-1 to produce more liposoluble quinones. Ubiquinone can mediate electron transfer at the hydrophobic interface. Ubiquinone-30 (UQ-6) increases the reduction rate of hydrophobic ferrihydrite from 38.5 ± 4.4 to 52.2 ± 0.8 μM·h⁻¹. Based on the above experimental results, we propose that liposoluble electron mediator ubiquinone can act on the extracellular hydrophobic surface, proving that the metabolism of hydrophobic minerals is related to endogenous liposoluble quinones. Hydrophobic modification of minerals encourages electroactive microorganisms to adopt differentiated respiratory pathways. This finding helps in understanding the electron transfer behavior of the microbes at the hydrophobic interface and provides new ideas for the study of hydrophobic reactions that may occur in systems, such as soil and sediment.

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Extracellular electron transfer can be regulated by wettability of mineral surface

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Hydrophobic surface hinders the transport of water-soluble mediator riboflavin

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Ubiquinone can mediate extracellular electron transfer at the hydrophobic interface

Persistent Cancer Cells: The Deadly Survivors

Persistent cancer cells are the discrete and usually undetected cells that survive cancer drug treatment and constitute a major cause of treatment failure. These cells are characterized by their slow proliferation, highly flexible energy consumption, adaptation to their microenvironment, and phenotypic plasticity. Mechanisms that underlie their persistence offer highly coveted and sought-after therapeutic targets, and include diverse epigenetic, transcriptional, and translational regulatory processes, as well as complex cell-cell interactions. Although the successful clinical targeting of persistent cancer cells remains to be realized, immense progress has been made in understanding their persistence, yielding promising preclinical results.

Restoration of fitness lost due to dysregulation of the pyruvate dehydrogenase complex is triggered by ribosomal binding site modifications

Pyruvate dehydrogenase complex (PDC) functions as the main determinant of the respiro-fermentative balance because it converts pyruvate to acetyl-coenzyme A (CoA), which then enters the TCA (tricarboxylic acid cycle). PDC is repressed by the pyruvate dehydrogenase complex regulator (PdhR) in Escherichia coli. The deletion of the pdhR gene compromises fitness in aerobic environments. We evolve the E. coli pdhR deletion strain to examine its achievable growth rate and the underlying adaptive strategies. We find that (1) optimal proteome allocation to PDC is critical in achieving optimal growth rate; (2) expression of PDC in evolved strains is reduced through mutations in the Shine-Dalgarno sequence; (3) rewiring of the TCA flux and increased reactive oxygen species (ROS) defense occur in the evolved strains; and (4) the evolved strains adapt to an efficient biomass yield. Together, these results show how adaptation can find alternative regulatory mechanisms for a key cellular process if the primary regulatory mode fails.

Regulation of coenzyme Q biosynthesis pathway in eukaryotes

Coenzyme Q (CoQ, ubiquinone/ubiquinol) is a ubiquitous and unique molecule that drives electrons in mitochondrial respiratory chain and an obligatory step for multiple metabolic pathways in aerobic metabolism. Alteration of CoQ biosynthesis or its redox stage are causing mitochondrial dysfunctions as hallmark of heterogeneous disorders as mitochondrial/metabolic, cardiovascular, and age-associated diseases. Regulation of CoQ biosynthesis pathway is demonstrated to affect all steps of proteins production of this pathway, posttranslational modifications and protein-protein-lipid interactions inside mitochondria. There is a bi-directional relationship between CoQ and the epigenome in which not only the CoQ status determines the epigenetic regulation of many genes, but CoQ biosynthesis is also a target for epigenetic regulation, which adds another layer of complexity to the many pathways by which CoQ levels are regulated by environmental and developmental signals to fulfill its functions in eukaryotic aerobic metabolism.

Independent component analysis recovers consistent regulatory signals from disparate datasets

The availability of bacterial transcriptomes has dramatically increased in recent years. This data deluge could result in detailed inference of underlying regulatory networks, but the diversity of experimental platforms and protocols introduces critical biases that could hinder scalable analysis of existing data. Here, we show that the underlying structure of the E. coli transcriptome, as determined by Independent Component Analysis (ICA), is conserved across multiple independent datasets, including both RNA-seq and microarray datasets. We subsequently combined five transcriptomics datasets into a large compendium containing over 800 expression profiles and discovered that its underlying ICA-based structure was still comparable to that of the individual datasets. With this understanding, we expanded our analysis to over 3,000 E. coli expression profiles and predicted three high-impact regulons that respond to oxidative stress, anaerobiosis, and antibiotic treatment. ICA thus enables deep analysis of disparate data to uncover new insights that were not visible in the individual datasets.

Cells adapt to diverse environments by regulating gene expression. Genome-wide measurements of gene expression levels have exponentially increased in recent years, but successful integration and analysis of these datasets are limited. Recently, we showed that independent component analysis (ICA), a signal deconvolution algorithm, can separate a large bacterial gene expression dataset into groups of co-regulated genes. This previous study focused on data generated by a standardized pipeline and did not address whether ICA extracts the same quantitative co-expression signals across expression profiling platforms. In this study, we show that ICA finds similar co-regulation patterns underlying multiple gene expression datasets and can be used as a tool to integrate and interpret diverse datasets. Using a dataset containing over 3,000 expression profiles, we predicted three new regulons and characterized their activities. Since large, standardized expression datasets only exist for a few bacterial strains, these results broaden the possible applications of this tool to better understand transcriptional regulation across a wide range of microbes.

iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning

Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated gene sets (iModulons), inferring their activities across a range of conditions, and enabling their association to known genetic regulators. By grouping and analyzing genes based on observations from big data alone, iModulons can provide a novel perspective into how the composition of the transcriptome adapts to environmental conditions. Here, we present iModulonDB (imodulondb.org), a knowledgebase of prokaryotic transcriptional regulation computed from high-quality transcriptomic datasets using ICA. Users select an organism from the home page and then search or browse the curated iModulons that make up its transcriptome. Each iModulon and gene has its own interactive dashboard, featuring plots and tables with clickable, hoverable, and downloadable features. This site enhances research by presenting scientists of all backgrounds with co-expressed gene sets and their activity levels, which lead to improved understanding of regulator-gene relationships, discovery of transcription factors, and the elucidation of unexpected relationships between conditions and genetic regulatory activity. The current release of iModulonDB covers three organisms (Escherichia coli, Staphylococcus aureus and Bacillus subtilis) with 204 iModulons, and can be expanded to cover many additional organisms.

Machine learning uncovers independently regulated modules in the Bacillus subtilis transcriptome

The transcriptional regulatory network (TRN) of Bacillus subtilis coordinates cellular functions of fundamental interest, including metabolism, biofilm formation, and sporulation. Here, we use unsupervised machine learning to modularize the transcriptome and quantitatively describe regulatory activity under diverse conditions, creating an unbiased summary of gene expression. We obtain 83 independently modulated gene sets that explain most of the variance in expression and demonstrate that 76% of them represent the effects of known regulators. The TRN structure and its condition-dependent activity uncover putative or recently discovered roles for at least five regulons, such as a relationship between histidine utilization and quorum sensing. The TRN also facilitates quantification of population-level sporulation states. As this TRN covers the majority of the transcriptome and concisely characterizes the global expression state, it could inform research on nearly every aspect of transcriptional regulation in B. subtilis.

The systems-level regulatory structure underlying gene expression in bacteria can be inferred using machine learning algorithms. Here we show this structure for Bacillus subtilis, present five hypotheses gleaned from it, and analyse the process of sporulation from its perspective.

Synthesizing Systems Biology Knowledge from Omics Using Genome-Scale Models

Omic technologies have enabled the complete readout of the molecular state of a cell at different biological scales. In principle, the combination of multiple omic data types can provide an integrated view of the entire biological system. This integration requires appropriate models in a systems biology approach. Here, genome-scale models (GEMs) are focused upon as one computational systems biology approach for interpreting and integrating multi-omic data. GEMs convert the reactions (related to metabolism, transcription, and translation) that occur in an organism to a mathematical formulation that can be modeled using optimization principles. A variety of genome-scale modeling methods used to interpret multiple omic data types, including genomics, transcriptomics, proteomics, metabolomics, and meta-omics are reviewed. The ability to interpret omics in the context of biological systems has yielded important findings for human health, environmental biotechnology, bioenergy, and metabolic engineering. The authors find that concurrent with advancements in omic technologies, genome-scale modeling methods are also expanding to enable better interpretation of omic data. Therefore, continued synthesis of valuable knowledge, through the integration of omic data with GEMs, are expected.

Independent component analysis of E. coli's transcriptome reveals the cellular processes that respond to heterologous gene expression

Achieving the predictable expression of heterologous genes in a production host has proven difficult. Each heterologous gene expressed in the same host seems to elicit a different host response governed by unknown mechanisms. Historically, most studies have approached this challenge by manipulating the properties of the heterologous gene through methods like codon optimization. Here we approach this challenge from the host side. We express a set of 45 heterologous genes in the same Escherichia coli strain, using the same expression system and culture conditions. We collect a comprehensive RNAseq set to characterize the host's transcriptional response. Independent Component Analysis of the RNAseq data set reveals independently modulated gene sets (iModulons) that characterize the host response to heterologous gene expression. We relate 55% of variation of the host response to: Fear vs Greed (16.5%), Metal Homeostasis (19.0%), Respiration (6.0%), Protein folding (4.5%), and Amino acid and nucleotide biosynthesis (9.0%). If these responses can be controlled, then the success rate with predicting heterologous gene expression should increase.

Advances in menaquinone biosynthesis: sublocalisation and allosteric regulation

Menaquinones (vitamin K2) are a family of redox-active small molecules with critical functions across all domains of life, including energy generation in bacteria and bone health in humans. The enzymes involved in menaquinone biosynthesis also have bioengineering applications and are potential antimicrobial drug targets. New insights into the essential roles of menaquinones, and their potential to cause redox-related toxicity, have highlighted the need for this pathway to be tightly controlled. Here, we provide an overview of our current understanding of the classical menaquinone biosynthesis pathway in bacteria. We also review recent discoveries on protein-level allostery and sublocalisation of membrane-bound enzymes that have provided insight into the regulation of flux through this biosynthetic pathway.

Revealing 29 sets of independently modulated genes in Staphylococcus aureus, their regulators, and role in key physiological response

Staphylococcus aureus infections impose an immense burden on the healthcare system. To establish a successful infection in a hostile host environment, S. aureus must coordinate its gene expression to respond to a wide array of challenges. This balancing act is largely orchestrated by the transcriptional regulatory network. Here, we present a model of 29 independently modulated sets of genes that form the basis for a segment of the transcriptional regulatory network in clinical USA300 strains of S. aureus. Using this model, we demonstrate the concerted role of various cellular systems (e.g., metabolism, virulence, and stress response) underlying key physiological responses, including response during blood infection.

The ability of Staphylococcus aureus to infect many different tissue sites is enabled, in part, by its transcriptional regulatory network (TRN) that coordinates its gene expression to respond to different environments. We elucidated the organization and activity of this TRN by applying independent component analysis to a compendium of 108 RNA-sequencing expression profiles from two S. aureus clinical strains (TCH1516 and LAC). ICA decomposed the S. aureus transcriptome into 29 independently modulated sets of genes (i-modulons) that revealed: 1) High confidence associations between 21 i-modulons and known regulators; 2) an association between an i-modulon and σS, whose regulatory role was previously undefined; 3) the regulatory organization of 65 virulence factors in the form of three i-modulons associated with AgrR, SaeR, and Vim-3; 4) the roles of three key transcription factors (CodY, Fur, and CcpA) in coordinating the metabolic and regulatory networks; and 5) a low-dimensional representation, involving the function of few transcription factors of changes in gene expression between two laboratory media (RPMI, cation adjust Mueller Hinton broth) and two physiological media (blood and serum). This representation of the TRN covers 842 genes representing 76% of the variance in gene expression that provides a quantitative reconstruction of transcriptional modules in S. aureus, and a platform enabling its full elucidation.

Quality-quantity trade-offs drive functional trait evolution in a model microalgal 'climate change winner'

Phytoplankton are the unicellular photosynthetic microbes that form the base of aquatic ecosystems, and their responses to global change will impact everything from food web dynamics to global nutrient cycles. Some taxa respond to environmental change by increasing population growth rates in the short-term and are projected to increase in frequency over decades. To gain insight into how these projected 'climate change winners' evolve, we grew populations of microalgae in ameliorated environments for several hundred generations. Most populations evolved to allocate a smaller proportion of carbon to growth while increasing their ability to tolerate and metabolise reactive oxygen species (ROS). This trade-off drives the evolution of traits that underlie the ecological and biogeochemical roles of phytoplankton. This offers evolutionary and a metabolic frameworks for understanding trait evolution in projected 'climate change winners' and suggests that short-term population booms have the potential to be dampened or reversed when environmental amelioration persists.