Beta-lactamase dependent and independent evolutionary paths to high-level ampicillin resistance.

The incidence of beta-lactam resistance among clinical isolates is a major health concern. A key method to study the emergence of antibiotic resistance is adaptive laboratory evolution. However, in the case of the beta-lactam ampicillin, bacteria evolved in laboratory settings do not recapitulate clinical-like resistance levels, hindering efforts to identify major evolutionary paths and their dependency on genetic background. Here, we used the Microbial Evolution and Growth Arena (MEGA) plate to select ampicillin-resistant Escherichia coli mutants with varying degrees of resistance. Whole-genome sequencing of resistant isolates revealed that ampicillin resistance was acquired via a combination of single-point mutations and amplification of the gene encoding beta-lactamase AmpC. However, blocking AmpC-mediated resistance revealed latent adaptive pathways: strains deleted for ampC were able to adapt through combinations of changes in genes involved in multidrug resistance encoding efflux pumps, transcriptional regulators, and porins. Our results reveal that combinations of distinct genetic mutations, accessible at large population sizes, can drive high-level resistance to ampicillin even independently of beta-lactamases.

Systematic identification of gene-altering programmed inversions across the bacterial domain.

Programmed chromosomal inversions allow bacteria to generate intra-population genotypic and functional heterogeneity, a bet-hedging strategy important in changing environments. Some programmed inversions modify coding sequences, producing different alleles in several gene families, most notably in specificity-determining genes such as Type I restriction-modification systems, where systematic searches revealed cross phylum abundance. Yet, a broad, gene-independent, systematic search for gene-altering programmed inversions has been absent, and little is known about their genomic sequence attributes and prevalence across gene families. Here, identifying intra-species variation in genomes of over 35 000 species, we develop a predictive model of gene-altering inversions, revealing key attributes of their genomic sequence attributes, including gene-pseudogene size asymmetry and orientation bias. The model predicted over 11,000 gene-altering loci covering known targeted gene families, as well as novel targeted families including Type II restriction-modification systems, a protein of unknown function, and a fusion-protein containing conjugative-pilus and phage tail domains. Publicly available long-read sequencing datasets validated representatives of these newly predicted inversion-targeted gene families, confirming intra-population genetic heterogeneity. Together, these results reveal gene-altering programmed inversions as a key strategy adopted across the bacterial domain, and highlight programmed inversions that modify Type II restriction-modification systems as a possible new mechanism for maintaining intra-population heterogeneity.

Waning of SARS-CoV-2 booster viral-load reduction effectiveness.

The BNT162b2 COVID-19 vaccine has been shown to reduce viral load of breakthrough infections (BTIs), an important factor affecting infectiousness. This viral-load protective effect has been waning with time post the second vaccine and later restored with a booster shot. It is currently unclear though for how long this regained effectiveness lasts. Analyzing Ct values of SARS-CoV-2 qRT-PCR tests of over 22,000 infections during a Delta-variant-dominant period in Israel, we find that this viral-load reduction effectiveness significantly declines within months post the booster dose. Adjusting for age, sex and calendric date, Ct values of RdRp gene initially increases by 2.7 [CI: 2.3-3.0] relative to unvaccinated in the first month post the booster dose, yet then decays to a difference of 1.3 [CI: 0.7-1.9] in the second month and becomes small and insignificant in the third to fourth months. The rate and magnitude of this post-booster decline in viral-load reduction effectiveness mirror those observed post the second vaccine. These results suggest rapid waning of the booster's effectiveness in reducing infectiousness, possibly affecting community-level spread of the virus.

Minimizing treatment-induced emergence of antibiotic resistance in bacterial infections.

Treatment of bacterial infections currently focuses on choosing an antibiotic that matches a pathogen's susceptibility, with less attention paid to the risk that even susceptibility-matched treatments can fail as a result of resistance emerging in response to treatment. Combining whole-genome sequencing of 1113 pre- and posttreatment bacterial isolates with machine-learning analysis of 140,349 urinary tract infections and 7365 wound infections, we found that treatment-induced emergence of resistance could be predicted and minimized at the individual-patient level. Emergence of resistance was common and driven not by de novo resistance evolution but by rapid reinfection with a different strain resistant to the prescribed antibiotic. As most infections are seeded from a patient's own microbiota, these resistance-gaining recurrences can be predicted using the patient's past infection history and minimized by machine learning-personalized antibiotic recommendations, offering a means to reduce the emergence and spread of resistant pathogens.

SARS-CoV-2 RT-qPCR Test Detection Rates Are Associated with Patient Age, Sex, and Time since Diagnosis.

Quantifying the detection rate of the widely used quantitative RT-PCR (RT-qPCR) test for severe acute respiratory syndrome coronavirus 2 and its dependence on patient demographic characteristics and disease progression is key in designing epidemiologic strategies. Analyzing 843,917 test results of 521,696 patients, a "positive period" was defined for each patient between diagnosis of coronavirus disease 2019 and the last positive test result. The fraction of positive test results within this period was then used to estimate detection rate. Regression analyses were used to determine associations of detection with time of sampling after diagnosis, patient demographic characteristics, and viral RNA copy number based on RT-qPCR cycle threshold values of the next positive test result. The overall detection rate in tests performed within 14 days after diagnosis was 83.1%. This rate was higher at days 0 to 5 after diagnosis (89.3%). Furthermore, detection rate was strongly associated with age and sex. Finally, the detection rate with the Allplex 2019-nCoV RT-qPCR kit was associated, at the single-patient level, with viral RNA copy number (P < 10-9). These results show that the reliability of the test result is reduced in later days as well as for women and younger patients, in whom the viral loads are typically lower.

Viral loads of Delta-variant SARS-CoV-2 breakthrough infections after vaccination and booster with BNT162b2.

The effectiveness of the coronavirus disease 2019 (COVID-19) BNT162b2 vaccine in preventing disease and reducing viral loads of breakthrough infections (BTIs) has been decreasing, concomitantly with the rise of the Delta variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, it is unclear whether the observed decreased effectiveness of the vaccine in reducing viral loads is inherent to the Delta variant or is dependent on time from immunization. By analyzing viral loads of over 16,000 infections during the current, Delta-variant-dominated pandemic wave in Israel, we found that BTIs in recently fully vaccinated individuals have lower viral loads than infections in unvaccinated individuals. However, this effect starts to decline 2 months after vaccination and ultimately vanishes 6 months or longer after vaccination. Notably, we found that the effect of BNT162b2 on reducing BTI viral loads is restored after a booster dose. These results suggest that BNT162b2 might decrease the infectiousness of BTIs even with the Delta variant, and that, although this protective effect declines with time, it can be restored, at least temporarily, with a third, booster, vaccine dose.

Rapid methicillin resistance diversification in Staphylococcus epidermidis colonizing human neonates.

Early in life, infants are colonized with multiple bacterial strains whose differences in gene content can have important health consequences. Metagenomics-based approaches have revealed gene content differences between different strains co-colonizing newborns, but less is known about the rate, mechanism, and phenotypic consequences of gene content diversification within strains. Here, focusing on Staphylococcus epidermidis, we whole-genome sequence and phenotype more than 600 isolates from newborns. Within days of birth, infants are co-colonized with a highly personalized repertoire of S. epidermidis strains, which are spread across the newborn body. Comparing the genomes of multiple isolates of each strain, we find very little evidence of adaptive evolution via single-nucleotide polymorphisms. By contrast, we observe gene content differences even between otherwise genetically identical cells, including variation of the clinically important methicillin resistance gene, mecA, suggesting rapid gene gain and loss events at rates higher than point mutations. Mapping the genomic architecture of structural variants by long-read Nanopore sequencing, we find that deleted regions were always flanked by direct repeats, consistent with site-specific recombination. However, we find that even within a single genetic background, recombination occurs at multiple, often non-canonical repeats, leading to the rapid evolution of patient-specific diverse structural variants in the SCCmec island and to differences in antibiotic resistance.

Community-level evidence for SARS-CoV-2 vaccine protection of unvaccinated individuals.

Mass vaccination has the potential to curb the current COVID-19 pandemic by protecting individuals who have been vaccinated against the disease and possibly lowering the likelihood of transmission to individuals who have not been vaccinated. The high effectiveness of the widely administered BNT162b vaccine from Pfizer-BioNTech in preventing not only the disease but also infection with SARS-CoV-2 suggests a potential for a population-level effect, which is critical for disease eradication. However, this putative effect is difficult to observe, especially in light of highly fluctuating spatiotemporal epidemic dynamics. Here, by analyzing vaccination records and test results collected during the rapid vaccine rollout in a large population from 177 geographically defined communities, we find that the rates of vaccination in each community are associated with a substantial later decline in infections among a cohort of individuals aged under 16 years, who are unvaccinated. On average, for each 20 percentage points of individuals who are vaccinated in a given population, the positive test fraction for the unvaccinated population decreased approximately twofold. These results provide observational evidence that vaccination not only protects individuals who have been vaccinated but also provides cross-protection to unvaccinated individuals in the community.

Initial report of decreased SARS-CoV-2 viral load after inoculation with the BNT162b2 vaccine.

Beyond their substantial protection of individual vaccinees, coronavirus disease 2019 (COVID-19) vaccines might reduce viral load in breakthrough infection and thereby further suppress onward transmission. In this analysis of a real-world dataset of positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) test results after inoculation with the BNT162b2 messenger RNA vaccine, we found that the viral load was substantially reduced for infections occurring 12-37 d after the first dose of vaccine. These reduced viral loads hint at a potentially lower infectiousness, further contributing to vaccine effect on virus spread.

Evaluation of COVID-19 RT-qPCR Test in Multi sample Pools.

BACKGROUND: The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a current pandemic of unprecedented scale. Although diagnostic tests are fundamental to the ability to detect and respond, overwhelmed healthcare systems are already experiencing shortages of reagents associated with this test, calling for a lean immediately applicable protocol. METHODS: RNA extracts of positive samples were tested for the presence of SARS-CoV-2 using reverse transcription quantitative polymerase chain reaction, alone or in pools of different sizes (2-, 4-, 8-, 16-, 32-, and 64-sample pools) with negative samples. Transport media of additional 3 positive samples were also tested when mixed with transport media of negative samples in pools of 8. RESULTS: A single positive sample can be detected in pools of up to 32 samples, using the standard kits and protocols, with an estimated false negative rate of 10%. Detection of positive samples diluted in even up to 64 samples may also be attainable, although this may require additional amplification cycles. Single positive samples can be detected when pooling either after or prior to RNA extraction. CONCLUSIONS: As it uses the standard protocols, reagents, and equipment, this pooling method can be applied immediately in current clinical testing laboratories. We hope that such implementation of a pool test for coronavirus disease 2019 would allow expanding current screening capacities, thereby enabling the expansion of detection in the community, as well as in close organic groups, such as hospital departments, army units, or factory shifts.

Escape mutations circumvent a tradeoff between resistance to a beta-lactam and resistance to a beta-lactamase inhibitor.

Beta-lactamase inhibitors are increasingly used to counteract antibiotic resistance mediated by beta-lactamase enzymes. These inhibitors compete with the beta-lactam antibiotic for the same binding site on the beta-lactamase, thus generating an evolutionary tradeoff: mutations that increase the enzyme's beta-lactamase activity tend to increase also its susceptibility to the inhibitor. Here, we investigate how common and accessible are mutants that escape this adaptive tradeoff. Screening a deep mutant library of the blaampC beta-lactamase gene of Escherichia coli, we identified mutations that allow growth at beta-lactam concentrations far exceeding those inhibiting growth of the wildtype strain, even in the presence of the enzyme inhibitor (avibactam). These escape mutations are rare and drug-specific, and some combinations of avibactam with beta-lactam drugs appear to prevent such escape phenotypes. Our results, showing differential adaptive potential of blaampC to combinations of avibactam and different beta-lactam antibiotics, suggest that it may be possible to identify treatments that are more resilient to evolution of resistance.

Genomic and epidemiological evidence of bacterial transmission from probiotic capsule to blood in ICU patients.

Probiotics are routinely administered to hospitalized patients for many potential indications1 but have been associated with adverse effects that may outweigh their potential benefits2-7. It is particularly alarming that probiotic strains can cause bacteremia8,9, yet direct evidence for an ancestral link between blood isolates and administered probiotics is lacking. Here we report a markedly higher risk of Lactobacillus bacteremia for intensive care unit (ICU) patients treated with probiotics compared to those not treated, and provide genomics data that support the idea of direct clonal transmission of probiotics to the bloodstream. Whole-genome-based phylogeny showed that Lactobacilli isolated from treated patients' blood were phylogenetically inseparable from Lactobacilli isolated from the associated probiotic product. Indeed, the minute genetic diversity among the blood isolates mostly mirrored pre-existing genetic heterogeneity found in the probiotic product. Some blood isolates also contained de novo mutations, including a non-synonymous SNP conferring antibiotic resistance in one patient. Our findings support that probiotic strains can directly cause bacteremia and adaptively evolve within ICU patients.

Personal clinical history predicts antibiotic resistance of urinary tract infections.

Antibiotic resistance is prevalent among the bacterial pathogens causing urinary tract infections. However, antimicrobial treatment is often prescribed 'empirically', in the absence of antibiotic susceptibility testing, risking mismatched and therefore ineffective treatment. Here, linking a 10-year longitudinal data set of over 700,000 community-acquired urinary tract infections with over 5,000,000 individually resolved records of antibiotic purchases, we identify strong associations of antibiotic resistance with the demographics, records of past urine cultures and history of drug purchases of the patients. When combined together, these associations allow for machine-learning-based personalized drug-specific predictions of antibiotic resistance, thereby enabling drug-prescribing algorithms that match an antibiotic treatment recommendation to the expected resistance of each sample. Applying these algorithms retrospectively, over a 1-year test period, we find that they greatly reduce the risk of mismatched treatment compared with the current standard of care. The clinical application of such algorithms may help improve the effectiveness of antimicrobial treatments.

Evolthon: A community endeavor to evolve lab evolution.

In experimental evolution, scientists evolve organisms in the lab, typically by challenging them to new environmental conditions. How best to evolve a desired trait? Should the challenge be applied abruptly, gradually, periodically, sporadically? Should one apply chemical mutagenesis, and do strains with high innate mutation rate evolve faster? What are ideal population sizes of evolving populations? There are endless strategies, beyond those that can be exposed by individual labs. We therefore arranged a community challenge, Evolthon, in which students and scientists from different labs were asked to evolve Escherichia coli or Saccharomyces cerevisiae for an abiotic stress-low temperature. About 30 participants from around the world explored diverse environmental and genetic regimes of evolution. After a period of evolution in each lab, all strains of each species were competed with one another. In yeast, the most successful strategies were those that used mating, underscoring the importance of sex in evolution. In bacteria, the fittest strain used a strategy based on exploration of different mutation rates. Different strategies displayed variable levels of performance and stability across additional challenges and conditions. This study therefore uncovers principles of effective experimental evolutionary regimens and might prove useful also for biotechnological developments of new strains and for understanding natural strategies in evolutionary arms races between species. Evolthon constitutes a model for community-based scientific exploration that encourages creativity and cooperation.

Antibiotic Resistance.

Bacterial mechanisms of drug resistance operate at sequential lines of defense tackling drug at entry, accumulation, target binding, or downstream toxicity. These mechanisms are encoded by genomic changes ranging in scale from point mutations, through assembly of preexisting genetic elements, to horizontal import of genes from the environment. A many-to-many relationship prevails between resistance mechanisms and the spectrum of genetic changes encoding them.

Identification and characterization of roles for Puf1 and Puf2 proteins in the yeast response to high calcium.

Members of the yeast family of PUF proteins bind unique subsets of mRNA targets that encode proteins with common functions. They therefore became a paradigm for post-transcriptional gene control. To provide new insights into the roles of the seemingly redundant Puf1 and Puf2 members, we monitored the growth rates of their deletions under many different stress conditions. A differential effect was observed at high CaCl2 concentrations, whereby puf1Δ growth was affected much more than puf2Δ, and inhibition was exacerbated in puf1Δpuf2Δ double knockout. Transcriptome analyses upon CaCl2 application for short and long terms defined the transcriptional response to CaCl2 and revealed distinct expression changes for the deletions. Intriguingly, mRNAs known to be bound by Puf1 or Puf2 were affected mainly in the double knockout. We focused on the cell wall regulator Zeo1 and observed that puf1Δpuf2Δ fails to maintain low levels of its mRNA. Complementarily, puf1Δpuf2Δ growth defect in CaCl2 was repaired upon further deletion of the Zeo1 gene. Thus, these proteins probably regulate the cell-wall integrity pathway by regulating Zeo1 post-transcriptionally. This work sheds new light on the roles of Puf proteins during the cellular response to environmental stress.

Spatiotemporal microbial evolution on antibiotic landscapes.

A key aspect of bacterial survival is the ability to evolve while migrating across spatially varying environmental challenges. Laboratory experiments, however, often study evolution in well-mixed systems. Here, we introduce an experimental device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that allowed visual observation of mutation and selection in a migrating bacterial front. While resistance increased consistently, multiple coexisting lineages diversified both phenotypically and genotypically. Analyzing mutants at and behind the propagating front, we found that evolution is not always led by the most resistant mutants; highly resistant mutants may be trapped behind more sensitive lineages. The MEGA-plate provides a versatile platform for studying microbial adaption and directly visualizing evolutionary dynamics.

Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments.

Antibiotic-sensitive and -resistant bacteria coexist in natural environments with low, if detectable, antibiotic concentrations. Except possibly around localized antibiotic sources, where resistance can provide a strong advantage, bacterial fitness is dominated by stresses unaffected by resistance to the antibiotic. How do such mixed and heterogeneous conditions influence the selective advantage or disadvantage of antibiotic resistance? Here we find that sub-inhibitory levels of tetracyclines potentiate selection for or against tetracycline resistance around localized sources of almost any toxin or stress. Furthermore, certain stresses generate alternating rings of selection for and against resistance around a localized source of the antibiotic. In these conditions, localized antibiotic sources, even at high strengths, can actually produce a net selection against resistance to the antibiotic. Our results show that interactions between the effects of an antibiotic and other stresses in inhomogeneous environments can generate pervasive, complex patterns of selection both for and against antibiotic resistance.

Genetic variation of a bacterial pathogen within individuals with cystic fibrosis provides a record of selective pressures.

Advances in sequencing technologies have enabled the identification of mutations acquired by bacterial pathogens during infection. However, it remains unclear whether adaptive mutations fix in the population or lead to pathogen diversification within the patient. Here we study the genotypic diversity of Burkholderia dolosa within individuals with cystic fibrosis by resequencing individual colonies and whole populations from single sputum samples. We find extensive intrasample diversity, suggesting that mutations rarely fix in a patient's pathogen population--instead, diversifying lineages coexist for many years. Under strong selection, multiple adaptive mutations arise, but none of these sweep to fixation, generating lasting allele diversity that provides a recorded signature of past selection. Genes involved in outer-membrane components, iron scavenging and antibiotic resistance all showed this signature of within-patient selection. These results offer a general and rapid approach for identifying the selective pressures acting on a pathogen in individual patients based on single clinical samples.

The Escherichia coli extracellular death factor EDF induces the endoribonucleolytic activities of the toxins MazF and ChpBK.

Escherichia coli (E. coli) mazEF is a toxin-antitoxin (TA) stress-induced module that mediates cell death requiring the quorum-sensing pentapeptide NNWNN designated EDF (extracellular death factor). E. coli toxin MazF is a sequence-specific endoribonuclease cleaving single-stranded mRNAs at ACA sequences. E. coli ChpBK, a toxin homologous to MazF, is a sequence-specific endoribonuclease cleaving single-stranded mRNAs at ACA, ACG, and ACU sequences. Here we report that, in vitro, the signaling molecule EDF significantly amplifies the endoribonucleolytic activities of both MazF and ChpBK. EDF also overcomes the inhibitory activity of the antitoxins MazE over the toxin MazF and ChpBI over ChpBK. EDF sequence is important for both functions. Moreover, direct sequence-specific binding of EDF to MazF has been confirmed. Peptide-protein modeling revealed parallel contacts between EDF-MazF and MazE-MazF. These findings are intriguing, since most known quorum-sensing molecules monitor gene expression on the transcriptional level, while EDF monitors posttranscriptionally.