Explore the vast range of titles available.

Antibiotic resistance spreads among bacteria through horizontal transfer of antibiotic resistance genes (ARGs). Here, we set out to determine predictive features of ARG transfer among bacterial clades. We use a statistical framework to identify putative horizontally transferred ARGs and the groups of bacteria that disseminate them. We identify 152 gene exchange networks containing 22,963 bacterial genomes. Analysis of ARG-surrounding sequences identify genes encoding putative mobilisation elements such as transposases and integrases that may be involved in gene transfer between genomes. Certain ARGs appear to be frequently mobilised by different mobile genetic elements. We characterise the phylogenetic reach of these mobilisation elements to predict the potential future dissemination of known ARGs. Using a separate database with 472,798 genomes from Streptococcaceae, Staphylococcaceae and Enterobacteriaceae, we confirm 34 of 94 predicted mobilisations. We explore transfer barriers beyond mobilisation and show experimentally that physiological constraints of the host can explain why specific genes are largely confined to Gram-negative bacteria although their mobile elements support dissemination to Gram-positive bacteria. Our approach may potentially enable better risk assessment of future resistance gene dissemination. Antibiotic resistance spreads among bacteria through horizontal transfer of antibiotic resistance genes (ARGs). Here, Ellabaan et al. use a statistical approach to identify putative mobilisation elements and other features associated with ARG transfer among bacterial clades to predict the potential future dissemination of known ARGs.

Risk assessment for the development of antibiotic resistance against a new drug candidate is of paramount importance in preclinical development. In this Opinion article, Sommer et al . propose a new preclinical paradigm for the prediction of antibiotic resistance. Predicting the future is difficult, especially for evolutionary processes that are influenced by numerous unknown factors. Still, this is what is required of drug developers when they assess the risk of resistance arising against a new antibiotic candidate during preclinical development. In this Opinion article, we argue that the traditional procedures that are used for the prediction of antibiotic resistance today could be markedly improved by including a broader analysis of bacterial fitness, infection dynamics, horizontal gene transfer and other factors. This will lead to more informed preclinical decisions for continuing or discontinuing the development of drug candidates.

Soil microbiota represent one of the ancient evolutionary origins of antibiotic resistance and have been proposed as a reservoir of resistance genes available for exchange with clinical pathogens. Using a high-throughput functional metagenomic approach in conjunction with a pipeline for the de novo assembly of short-read sequence data from functional selections (termed PARFuMS), we provide evidence for recent exchange of antibiotic resistance genes between environmental bacteria and clinical pathogens. We describe multidrug-resistant soil bacteria containing resistance cassettes against five classes of antibiotics (β-lactams, aminoglycosides, amphenicols, sulfonamides, and tetracyclines) that have perfect nucleotide identity to genes from diverse human pathogens. This identity encompasses noncoding regions as well as multiple mobilization sequences, offering not only evidence of lateral exchange but also a mechanism by which antibiotic resistance disseminates.

To understand the process by which antibiotic resistance genes are acquired by human pathogens, we functionally characterized the resistance reservoir in the microbial flora of healthy individuals. Most of the resistance genes we identified using culture-independent sampling have not been previously identified and are evolutionarily distant from known resistance genes. By contrast, nearly half of the resistance genes we identified in cultured aerobic gut isolates (a small subset of the gut microbiome) are identical to resistance genes harbored by major pathogens. The immense diversity of resistance genes in the human microbiome could contribute to future emergence of antibiotic resistance in human pathogens.

It has been hypothesized that some antibiotic resistance genes (ARGs) found in pathogenic bacteria derive from antibiotic-producing actinobacteria. Here we provide bioinformatic and experimental evidence supporting this hypothesis. We identify genes in proteobacteria, including some pathogens, that appear to be closely related to actinobacterial ARGs known to confer resistance against clinically important antibiotics. Furthermore, we identify two potential examples of recent horizontal transfer of actinobacterial ARGs to proteobacterial pathogens. Based on this bioinformatic evidence, we propose and experimentally test a ‘carry-back’ mechanism for the transfer, involving conjugative transfer of a carrier sequence from proteobacteria to actinobacteria, recombination of the carrier sequence with the actinobacterial ARG, followed by natural transformation of proteobacteria with the carrier-sandwiched ARG. Our results support the existence of ancient and, possibly, recent transfers of ARGs from antibiotic-producing actinobacteria to proteobacteria, and provide evidence for a defined mechanism. Some antibiotic resistance genes found in pathogenic bacteria might derive from antibiotic-producing actinobacteria. Here, Jiang et al . provide bioinformatic and experimental evidence supporting this hypothesis, and propose a specific mechanism for the transfer of these genes between bacterial phyla.

A transition toward sustainable bio-based chemical production is important for green growth. However, productivity and yield frequently decrease as large-scale microbial fermentation progresses, commonly ascribed to phenotypic variation. Yet, given the high metabolic burden and toxicities, evolutionary processes may also constrain bio-based production. We experimentally simulate large-scale fermentation with mevalonic acid-producing Escherichia coli . By tracking growth rate and production, we uncover how populations fully sacrifice production to gain fitness within 70 generations. Using ultra-deep (>1000×) time-lapse sequencing of the pathway populations, we identify multiple recurring intra-pathway genetic error modes. This genetic heterogeneity is only detected using deep-sequencing and new population-level bioinformatics, suggesting that the problem is underestimated. A quantitative model explains the population dynamics based on enrichment of spontaneous mutant cells. We validate our model by tuning production load and escape rate of the production host and apply multiple orthogonal strategies for postponing genetically driven production declines. The declining performance of scale-up bioreactor cultures is commonly attributed to phenotypic and physical heterogeneities. Here, the authors reveal multiple recurring intra-pathway error modes that limit engineered E . coli mevalonic acid production over time- and industrial-scale fermentations.

The gut microbiome significantly impacts human health, yet cultivation challenges hinder its exploration. Here, we combine deep whole-metagenome sequencing with culturomics to selectively enrich for taxa and functional capabilities of interest. Using a modified commercial base medium, 50 growth modifications were evaluated, spanning antibiotics, physico-chemical conditions, and bioactive compounds. Whole-metagenome sequencing identified medium additives, like caffeine, that enhance taxa often associated with healthier subjects (e.g., Lachnospiraceae, Oscillospiraceae, Ruminococcaceae ). We also explore the impact of modifications on the composition of cultured communities and establish a link between medium preference and microbial phylogeny. Leveraging these insights, we demonstrate that combinations of media modifications can further enhance the targeted enrichment of taxa and metabolic functions, such as Collinsella aerofaciens , or strains harboring biochemical pathways involved in dopamine metabolism. This streamlined, scalable approach unlocks the potential for selective enrichment, advancing microbiome research by understanding the impact of different cultivation parameters on gut microbes. Cultivation challenges hinder the exploration of the gut microbiota. Here, authors combine whole metagenome sequencing with culturomics to selectively enrich for specific taxa, uncovering medium modifications such as caffeine, that improve the cultivation of specific microbes or metabolic pathways.

Key Points All animals need a means by which to distinguish sensory inputs caused by their own movements from sensory inputs that are due to sources in the outside world. One such means is provided by corollary discharge (CD), a movement-command copy that is routed to sensory structures. Many different types of CD have evolved, and each is suited to the motor-induced problems faced by the organism. These differences lend themselves to a functional taxonomic classification. The CD taxonomy consists of higher- and lower-order categories that are based on the operational impact of the signal on the nervous system. Lower-order CD signalling is used for functions such as reflex inhibition and sensory filtration, whereas higher-order signalling participates in functions such as sensory analysis and stability, as well as sensorimotor planning and learning. Inhibition mediated by CD enables reflex coordination in animals such as nematodes, tadpoles and gastropods. Sensory filtration mechanisms regulate traffic through the differing sensory systems of animals such as the crayfish, the cockroach, the dogfish, the cricket, the marmoset and the macaque. CD for sensory analysis and stability enables organisms such as the macaque, the rat, the mormyrid and the bat to move and yet experience the world as it is (stable and continuous) rather than as it is sensed at the receptor level (in a chaotic and piecemeal fashion). These CDs allow brain structures to carry out appropriate adjustments in anticipation of the sensory input that results from a movement and to thus construct a stable representation of the world. CD for sensorimotor planning and learning provides internal feedback about movements that enables animals such as monkeys and birds to rapidly learn and execute sequences of motor patterns. As a result, behaviours can be prepared for the future (planning) and can be modified based on the lessons of the past (learning). As one ascends from lower-order CD through the stages of higher-order CD, the sensory target occupies increasingly higher tiers of the nervous system. This illustrates that there is no single type of CD: rather there are numerous subtypes that correspond both to anatomical levels of the source and the target and to functional utilities. Future CD studies should examine CDs at multiple resolutions, identify them in neglected sensory systems and determine the functional range of single CD circuits. The ultimate goal will be to discover how CD influences perception. When an animal moves, it must distinguish between sensory inputs caused by its own movement and those caused by another agent. Sommer and Crapse review how corollary discharge, neural signals that travel from the motor to the sensory structures, enable the coordination of movements and sensory analyses across a wide range of species. Our movements can hinder our ability to sense the world. Movements can induce sensory input (for example, when you hit something) that is indistinguishable from the input that is caused by external agents (for example, when something hits you). It is critical for nervous systems to be able to differentiate between these two scenarios. A ubiquitous strategy is to route copies of movement commands to sensory structures. These signals, which are referred to as corollary discharge (CD), influence sensory processing in myriad ways. Here we review the CD circuits that have been uncovered by neurophysiological studies and suggest a functional taxonomic classification of CD across the animal kingdom. This broad understanding of CD circuits lays the groundwork for more challenging studies that combine neurophysiology and psychophysics to probe the role of CD in perception.

Antibiotic resistance is a major challenge to global public health. Discovery of new antibiotics is slow and to ensure proper treatment of bacterial infections new strategies are needed. One way to curb the development of antibiotic resistance is to design drug combinations where the development of resistance against one drug leads to collateral sensitivity to the other drug. Here we study collateral sensitivity patterns of the globally distributed extended-spectrum β-lactamase CTX-M-15, and find three non-synonymous mutations with increased resistance against mecillinam or piperacillin–tazobactam that simultaneously confer full susceptibility to several cephalosporin drugs. We show in vitro and in mice that a combination of mecillinam and cefotaxime eliminates both wild-type and resistant CTX-M-15. Our results indicate that mecillinam and cefotaxime in combination constrain resistance evolution of CTX-M-15, and illustrate how drug combinations can be rationally designed to limit the resistance evolution of horizontally transferred genes by exploiting collateral sensitivity patterns. Development of bacterial resistance to an antibiotic can lead to collateral sensitivity to another drug. Here, the authors study collateral sensitivity conferred by mutations in the horizontally acquired β-lactamase CTX-M-15, and identify antibiotic combinations that constrain the evolution of resistance.