Antibiotics elicit drastic changes in microbial gene expression, including the induction of stress response genes. While certain stress responses are known to "cross-protect" bacteria from other stressors, it is unclear whether cellular responses to antibiotics have a similar protective role. By measuring the genome-wide transcriptional response dynamics of Escherichia coli to four antibiotics, we found that trimethoprim induces a rapid acid stress response that protects bacteria from subsequent exposure to acid. Combining microfluidics with time-lapse imaging to monitor survival and acid stress response in single cells revealed that the noisy expression of the acid resistance operon gadBC correlates with single-cell survival. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. The seemingly random single-cell survival under acid stress can therefore be predicted from gadBC expression and rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap for identifying the molecular mechanisms of single-cell cross-protection between antibiotics and other stressors.

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Retrons are genetic retroelements, commonly found in bacterial genomes and recently repurposed as genome editing tools. Their encoded reverse transcriptase (RT) produces a multi-copy single-stranded DNA (msDNA). Despite our understanding of their complex biosynthesis, the function of msDNAs and therefore, the physiological role of retrons has remained elusive. We establish that the retron-Sen2 in Salmonella Typhimurium encodes a toxin, which we have renamed as RcaT (Retron cold-anaerobic Toxin). RcaT is activated when msDNA biosynthesis is perturbed and its toxicity is higher at ambient temperatures or during anaerobiosis. The RT and msDNA form together the antitoxin unit, with the RT binding RcaT, and the msDNA enabling the antitoxin activity. Using another E. coli retron, we establish that this toxin/antitoxin function is conserved, and that RT-toxin interactions are cognate.Altogether, retrons constitute a novel family of tripartite toxin/antitoxin systems..

Sudden stress often triggers diverse, temporally structured gene expression responses in microbes, but it is largely unknown how variable in time such responses are and if genes respond in the same temporal order in every single cell. Here, we quantified timing variability of individual promoters responding to sublethal antibiotic stress using fluorescent reporters, microfluidics, and time‐lapse microscopy. We identified lower and upper bounds that put definite constraints on timing variability, which varies strongly among promoters and conditions. Timing variability can be interpreted using results from statistical kinetics, which enable us to estimate the number of rate‐limiting molecular steps underlying different responses. We found that just a few critical steps control some responses while others rely on dozens of steps. To probe connections between different stress responses, we then tracked the temporal order and response time correlations of promoter pairs in individual cells. Our results support that, when bacteria are exposed to the antibiotic nitrofurantoin, the ensuing oxidative stress and SOS responses are part of the same causal chain of molecular events. In contrast, under trimethoprim, the acid stress response and the SOS response are part of different chains of events running in parallel. Our approach reveals fundamental constraints on gene expression timing and provides new insights into the molecular events that underlie the timing of stress responses.

18Bacteria carry dozens of Toxin/Antitoxin systems (TAs) in their chromosomes. Upon growth, 19 the antitoxin is co-expressed and neutralizes the toxin. TAs can be activated and inhibit growth, 20 but when and how this occurs has largely remained enigmatic, hindering our understanding of 21 their physiological roles. We developed TIC/TAC (Toxin Inhibition/Activation Conjugation), a 22 wide E. coli overexpression libraries, we identified dozens of triggers and blockers for the 68 retron-Sen2, enriched in phage-origin proteins. Phage proteins are sensed by the retron-TA 69 via multiple mechanisms, which are inherent to the tripartite architecture of the TA system. We 70 propose that the retron-TA acts as an anti-phage defense system, and we provide a method 71 that can be readily applied to uncover the physiological role of any TA system. 72 73 RESULTS 74A new systematic method for identifying TA blockers and triggers 75To survey for molecular cues of TA systems, we used genome-wide E. coli single-gene 76 overexpression libraries (MOB; p1 25 and TransBac; p2 26 ) in tandem with strains carrying 77 appropriate TA-expressing plasmids (Fig. 1A). We reasoned that this would allow us to identify 78 Fig. 1D). This inconsistency has many reasons: stringent cutoffs (hence false negatives), 105 quality of libraries (missing genes, plasmid mutations, or cloning errors), and importance of 106 trigger levels (e.g., MOB vectors are medium-copy 25 , while TransBac vectors are single-copy 107 26 ). 108 109To ensure that the identified triggers inhibit growth by specifically activating RcaT, we selected 110 15 triggers, sequenced the plasmid-inserts, and conjugated them again into E. coli strains 111 expressing either an empty vector, p-retron, p-retron-ΔrcaT, or p-rcaT. All 15 were benign 112 when co-expressed only with the antitoxin (p-retron-ΔrcaT plasmid), but inhibited growth when 113 expressed with the full retron (ED Fig. 2A), suggesting that they trigger RcaT. As in the screen, 114 different triggers displayed varying degrees of RcaT-activation, and required different IPTG 115 induction-levels to manifest their effect (ED Fig. 2B). We noticed that several triggers, 116 especially strong ones, were prophage-encoded genes (enrichment p-val = 0.01-0.025, 117 depending on library and induction level - Table S1) -recE (Rac-prophage), tfaP & ymfH (e14-118 prophage), retron RT-Eco1 (P2-like-prophage gene in E. coli BL21), and B21_03469 119 (prophage in E. coli BL21). Although dam is part of the E. coli core genome, Dam methylases 120 are also commonly found in phages 28 . Other triggers belonged to house-keeping processes, 121 such as translation (tufA, rplL, rplP, rplV), DNA-binding/transcription (rdgC, rraB, betI, bolA), 122 protein quality control and translocation (slyD, secB, yajC), chorismate-tetrahydrofolate 123 biosynthesis (folA, gcvR, aroF, aroK), but also orphan genes (ygfB, ydiE, ecpE, gnsA). 124 125Conversely to the TAC screen, we reasoned that strains able to grow upon p-rcaT induction, 126 carried library plasmi...

Antibiotics affect bacterial cell physiology at many levels. Rather than just compensating for the direct cellular defects caused by the drug, bacteria respond to antibiotics by changing their morphology, macromolecular composition, metabolism, gene expression and possibly even their mutation rate. Inevitably, these processes affect each other, resulting in a complex response with changes in the expression of numerous genes. Genome-wide approaches can thus help in gaining a comprehensive understanding of bacterial responses to antibiotics. In addition, a combination of experimental and theoretical approaches is needed for identifying general principles that underlie these responses. Here, we review recent progress in our understanding of bacterial responses to antibiotics and their combinations, focusing on effects at the levels of growth rate and gene expression. We concentrate on studies performed in controlled laboratory conditions, which combine promising experimental techniques with quantitative data analysis and mathematical modeling. While these basic research approaches are not immediately applicable in the clinic, uncovering the principles and mechanisms underlying bacterial responses to antibiotics may, in the long term, contribute to the development of new treatment strategies to cope with and prevent the rise of resistant pathogenic bacteria.

Dose-response relationships are a general concept for quantitatively describing biological systems across multiple scales, from the molecular to the whole-cell level. A clinically relevant example is the bacterial growth response to antibiotics, which is routinely characterized by dose-response curves. The shape of the dose-response curve varies drastically between antibiotics and plays a key role in treatment, drug interactions, and resistance evolution. However, the mechanisms shaping the dose-response curve remain largely unclear. Here, we show in Escherichia coli that the distinctively shallow dose-response curve of the antibiotic trimethoprim is caused by a negative growth-mediated feedback loop: Trimethoprim slows growth, which in turn weakens the effect of this antibiotic. At the molecular level, this feedback is caused by the upregulation of the drug target dihydrofolate reductase (FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim but follows a universal trend line that depends primarily on the growth rate, irrespective of its cause. Rewiring the feedback loop alters the dose-response curve in a predictable manner, which we corroborate using a mathematical model of cellular resource allocation and growth. Our results indicate that growth-mediated feedback loops may shape drug responses more generally and could be exploited to design evolutionary traps that enable selection against drug resistance.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global threat to human health and has compromised economic stability. In addition to the development of an effective vaccine, it is imperative to understand how SARS-CoV-2 hijacks host cellular machineries on a system-wide scale so that potential host-directed therapies can be developed. In situ proteome-wide abundance and thermal stability measurements using thermal proteome profiling (TPP) can inform on global changes in protein activity. Here we adapted TPP to high biosafety conditions amenable to SARS-CoV-2 handling. We discovered pronounced temporal alterations in host protein thermostability during infection, which converged on cellular processes including cell cycle, microtubule and RNA splicing regulation. Pharmacological inhibition of host proteins displaying altered thermal stability or abundance during infection suppressed SARS-CoV-2 replication. Overall, this work serves as a framework for expanding TPP workflows to globally important human pathogens that require high biosafety containment and provides deeper resolution into the molecular changes induced by SARS-CoV-2 infection.