Slightly beneficial genes are retained by bacteria evolving DNA uptake despite selfish elements

FicD genes in invertebrates: A tale of transposons, pathogenic and integrated viruses

Many gene families are shared across the tree of life between distantly related species because of horizontal gene transfers (HGTs). However, the frequency of HGTs varies strongly between gene families and biotic realms suggesting differential selection pressures and functional bias. One gene family with a wide distribution are FIC-domain containing enzymes (FicDs). FicDs catalyze AMPylation, a post-translational protein modification consisting in the addition of adenosine monophosphate to accessible residues of target proteins. Beside the well-known conservation of FicDs in deuterostomes, we report the presence of a conserved FicD gene ortholog in a large number of protostomes and microbial eukaryotes. We also reported additional FicD gene copies in the genomes of some rotifers, parasitic worms and bivalves. A few dsDNA viruses of these invertebrates, including White spot syndrome virus, Cherax quadricarinatus iridovirus, Ostreid herpesvirus-1 and the beetle nudivirus, carry copies of FicDs, with phylogenetic analysis suggesting a common origin of these FicD copies and the duplicated FicDs of their invertebrate hosts. HGTs and gene duplications possibly mediated by endogenous viruses or genetic mobile elements seem to have contributed to the transfer of AMPylation ability from bacteria and eukaryotes to pathogenic viruses, where this pathway could have been hijacked to promote viral infection.

Silicon versus Superbug: Assessing Machine Learning's Role in the Fight against Antimicrobial Resistance

In his 1945 Nobel Prize acceptance speech, Sir Alexander Fleming warned of antimicrobial resistance (AMR) if the necessary precautions were not taken diligently. As the growing threat of AMR continues to loom over humanity, we must look forward to alternative diagnostic tools and preventive measures to thwart looming economic collapse and untold mortality worldwide. The integration of machine learning (ML) methodologies within the framework of such tools/pipelines presents a promising avenue, offering unprecedented insights into the underlying mechanisms of resistance and enabling the development of more targeted and effective treatments. This paper explores the applications of ML in predicting and understanding AMR, highlighting its potential in revolutionizing healthcare practices. From the utilization of supervised-learning approaches to analyze genetic signatures of antibiotic resistance to the development of tools and databases, such as the Comprehensive Antibiotic Resistance Database (CARD), ML is actively shaping the future of AMR research. However, the successful implementation of ML in this domain is not without challenges. The dependence on high-quality data, the risk of overfitting, model selection, and potential bias in training data are issues that must be systematically addressed. Despite these challenges, the synergy between ML and biomedical research shows great promise in combating the growing menace of antibiotic resistance.

Metacommunity structure preserves genome diversity in the presence of gene-specific selective sweeps under moderate rates of horizontal gene transfer

The horizontal transfer of genes is fundamental for the eco-evolutionary dynamics of microbial communities, such as oceanic plankton, soil, and the human microbiome. In the case of an acquired beneficial gene, classic population genetics would predict a genome-wide selective sweep, whereby the genome spreads clonally within the community and together with the beneficial gene, removing genome diversity. Instead, several sources of metagenomic data show the existence of "gene-specific sweeps", whereby a beneficial gene spreads across a bacterial community, maintaining genome diversity. Several hypotheses have been proposed to explain this process, including the decreasing gene flow between ecologically distant populations, frequency-dependent selection from linked deleterious allelles, and very high rates of horizontal gene transfer. Here, we propose an additional possible scenario grounded in eco-evolutionary principles. Specifically, we show by a mathematical model and simulations that a metacommunity where species can occupy multiple patches, acting together with a realistic (moderate) HGT rate, helps maintain genome diversity. Assuming a scenario of patches dominated by single species, our model predicts that diversity only decreases moderately upon the arrival of a new beneficial gene, and that losses in diversity can be quickly restored. We explore the generic behaviour of diversity as a function of three key parameters, frequency of insertion of new beneficial genes, migration rates and horizontal transfer rates.Our results provides a testable explanation for how diversity can be maintained by gene-specific sweeps even in the absence of high horizontal gene transfer rates.

Identifying and tracking mobile elements in evolving compost communities yields insights into the nanobiome

Microbial evolution is driven by rapid changes in gene content mediated by horizontal gene transfer (HGT). While mobile genetic elements (MGEs) are important drivers of gene flux, the nanobiome-the zoo of Darwinian replicators that depend on microbial hosts-remains poorly characterised. New approaches are necessary to increase our understanding beyond MGEs shaping individual populations, towards their impacts on complex microbial communities. A bioinformatic pipeline (xenoseq) was developed to cross-compare metagenomic samples from microbial consortia evolving in parallel, aimed at identifying MGE dissemination, which was applied to compost communities which underwent periodic mixing of MGEs. We show that xenoseq can distinguish movement of MGEs from demographic changes in community composition that otherwise confounds identification, and furthermore demonstrate the discovery of various unexpected entities. Of particular interest was a nanobacterium of the candidate phylum radiation (CPR) which is closely related to a species identified in groundwater ecosystems (Candidatus Saccharibacterium), and appears to have a parasitic lifestyle. We also highlight another prolific mobile element, a 313 kb plasmid hosted by a Cellvibrio lineage. The host was predicted to be capable of nitrogen fixation, and acquisition of the plasmid coincides with increased ammonia production. Taken together, our data show that new experimental strategies combined with bioinformatic analyses of metagenomic data stand to provide insight into the nanobiome as a driver of microbial community evolution.

Catch me if you can: capturing microbial community transformation by extracellular DNA using Hi-C sequencing

The transformation of environmental microorganisms by extracellular DNA is an overlooked mechanism of horizontal gene transfer and evolution. It initiates the acquisition of exogenous genes and propagates antimicrobial resistance alongside vertical and conjugative transfers. We combined mixed-culture biotechnology and Hi-C sequencing to elucidate the transformation of wastewater microorganisms with a synthetic plasmid encoding GFP and kanamycin resistance genes, in the mixed culture of chemostats exposed to kanamycin at concentrations representing wastewater, gut and polluted environments (0.01-2.5-50-100 mg L^-1). We found that the phylogenetically distant Gram-negative Runella (102 Hi-C links), Bosea (35), Gemmobacter (33) and Zoogloea (24) spp., and Gram-positive Microbacterium sp. (90) were transformed by the foreign plasmid, under high antibiotic exposure (50 mg L^-1). In addition, the antibiotic pressure shifted the origin of aminoglycoside resistance genes from genomic DNA to mobile genetic elements on plasmids accumulating in microorganisms. These results reveal the power of Hi-C sequencing to catch and surveil the transfer of xenogenetic elements inside microbiomes.

Evolution of genome fragility enables microbial division of labor

Division of labor can evolve when social groups benefit from the functional specialization of its members. Recently, a novel means of coordinating the division of labor was found in the antibiotic-producing bacterium Streptomyces coelicolor, where specialized cells are generated through large-scale genomic re-organization. We investigate how the evolution of a genome architecture enables such mutation-driven division of labor, using a multiscale computational model of bacterial evolution. In this model, bacterial behavior-antibiotic production or replication-is determined by the structure and composition of their genome, which encodes antibiotics, growth-promoting genes, and fragile genomic loci that can induce chromosomal deletions. We find that a genomic organization evolves, which partitions growth-promoting genes and antibiotic-coding genes into distinct parts of the genome, separated by fragile genomic loci. Mutations caused by these fragile sites mostly delete growth-promoting genes, generating sterile, and antibiotic-producing mutants from weakly-producing progenitors, in agreement with experimental observations. This division of labor enhances the competition between colonies by promoting antibiotic diversity. These results show that genomic organization can co-evolve with genomic instabilities to enable reproductive division of labor.

Investigating and Modeling the Regulation of Extracellular Antibiotic Resistance Gene Bioavailability by Naturally Occurring Nanoparticles

Extracellular antibiotic resistance genes (eARGs) are widespread in the environment and can genetically transform bacteria. This work examined the role of environmentally relevant nanoparticles (NPs) in regulating eARG bioavailability. eARGs extracted from antibiotic-resistant B. subtilis were incubated with nonresistant recipient B. subtilis cells. In the mixture, particle type (either humic acid coated nanoparticles (HASNPs) or their micron-sized counterpart (HASPs)), DNase I concentration, and eARG type were systematically varied. Transformants were counted on selective media. Particles decreased bacterial growth and eARG bioavailability in systems without nuclease. When DNase I was present (≥5 μg/mL), particles increased transformation via chromosomal (but not plasmid-borne) eARGs. HASNPs increased transformation more than HASPs, indicating that the smaller nanoparticle with greater surface area per volume is more effective in increasing eARG bioavailability. These results were also modeled via particle aggregation theory, which represented eARG-bacteria interactions as transport leading to collision, followed by attachment. Using attachment efficiency as a fitting factor, the model predicted transformant concentrations within 35% of experimental data. These results confirm the ability of NPs to increase eARG bioavailability and suggest that particle aggregation theory may be a simplified and suitable framework to broadly predict eARG uptake.

Transposable elements promote the evolution of genome streamlining

Eukaryotes and prokaryotes have distinct genome architectures, with marked differences in genome size, the ratio of coding/non-coding DNA, and the abundance of transposable elements (TEs). As TEs replicate independently of their hosts, the proliferation of TEs is thought to have driven genome expansion in eukaryotes. However, prokaryotes also have TEs in intergenic spaces, so why do prokaryotes have small, streamlined genomes? Using an in silico model describing the genomes of single-celled asexual organisms that coevolve with TEs, we show that TEs acquired from the environment by horizontal gene transfer can promote the evolution of genome streamlining. The process depends on local interactions and is underpinned by rock-paper-scissors dynamics in which populations of cells with streamlined genomes beat TEs, which beat non-streamlined genomes, which beat streamlined genomes, in continuous and repeating cycles. Streamlining is maladaptive to individual cells, but improves lineage viability by hindering the proliferation of TEs. Streamlining does not evolve in sexually reproducing populations because recombination partially frees TEs from the deleterious effects they cause. This article is part of the theme issue 'The secret lives of microbial mobile genetic elements'.

Inferring microbiota functions from taxonomic genes: a review

Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes-compared with the human microbiota-especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.

Comparing the topology of phylogenetic network generators

Phylogenetic networks represent evolutionary history of species and can record natural reticulate evolutionary processes such as horizontal gene transfer and gene recombination. This makes phylogenetic networks a more comprehensive representation of evolutionary history compared to phylogenetic trees. Stochastic processes for generating random trees or networks are important tools in evolutionary analysis, especially in phylogeny reconstruction where they can be utilized for validation or serve as priors for Bayesian methods. However, as more network generators are developed, there is a lack of discussion or comparison for different generators. To bridge this gap, we compare a set of phylogenetic network generators by profiling topological summary statistics of the generated networks over the number of reticulations and comparing the topological profiles.

Bacterial cooperation through horizontal gene transfer

Cooperation exists across all scales of biological organization, from genetic elements to complex human societies. Bacteria cooperate by secreting molecules that benefit all individuals in the population (i.e., public goods). Genes associated with cooperation can spread among strains through horizontal gene transfer (HGT). We discuss recent findings on how HGT mediated by mobile genetic elements promotes bacterial cooperation, how cooperation in turn can facilitate more frequent HGT, and how the act of HGT itself may be considered as a form of cooperation. We propose that HGT is an important enforcement mechanism in bacterial populations, thus creating a positive feedback loop that further maintains cooperation. To enforce cooperation, HGT serves as a homogenizing force by transferring the cooperative trait, effectively eliminating cheaters.

Genic Selection Within Prokaryotic Pangenomes

Understanding the evolutionary forces shaping prokaryotic pangenome structure is a major goal of microbial evolution research. Recent work has highlighted that a substantial proportion of accessory genes appear to confer niche-specific adaptations. This work has primarily focused on selection acting at the level of individual cells. Herein, we discuss a lower level of selection that also contributes to pangenome variation: genic selection. This refers to cases where genetic elements, rather than individual cells, are the entities under selection. The clearest examples of this form of selection are selfish mobile genetic elements, which are those that have either a neutral or a deleterious effect on host fitness. We review the major classes of these and other mobile elements and discuss the characteristic features of such elements that could be under genic selection. We also discuss how genetic elements that are beneficial to hosts can also be under genic selection, a scenario that may be more prevalent but not widely appreciated, because disentangling the effects of selection at different levels (i.e., organisms vs. genes) is challenging. Nonetheless, an appreciation for the potential action and implications of genic selection is important to better understand the evolution of prokaryotic pangenomes.

Mathematical Models of Plasmid Population Dynamics

With plasmid-mediated antibiotic resistance thriving and threatening to become a serious public health problem, it is paramount to increase our understanding of the forces that enable the spread and maintenance of drug resistance genes encoded in mobile genetic elements. The relevance of plasmids as vehicles for the dissemination of antibiotic resistance genes, in addition to the extensive use of plasmid-derived vectors for biotechnological and industrial purposes, has promoted the in-depth study of the molecular mechanisms controlling multiple aspects of a plasmids' life cycle. This body of experimental work has been paralleled by the development of a wealth of mathematical models aimed at understanding the interplay between transmission, replication, and segregation, as well as their consequences in the ecological and evolutionary dynamics of plasmid-bearing bacterial populations. In this review, we discuss theoretical models of plasmid dynamics that span from the molecular mechanisms of plasmid partition and copy-number control occurring at a cellular level, to their consequences in the population dynamics of complex microbial communities. We conclude by discussing future directions for this exciting research topic.

Identical sequences found in distant genomes reveal frequent horizontal transfer across the bacterial domain

Horizontal gene transfer (HGT) is an essential force in microbial evolution. Despite detailed studies on a variety of systems, a global picture of HGT in the microbial world is still missing. Here, we exploit that HGT creates long identical DNA sequences in the genomes of distant species, which can be found efficiently using alignment-free methods. Our pairwise analysis of 93,481 bacterial genomes identified 138,273 HGT events. We developed a model to explain their statistical properties as well as estimate the transfer rate between pairs of taxa. This reveals that long-distance HGT is frequent: our results indicate that HGT between species from different phyla has occurred in at least 8% of the species. Finally, our results confirm that the function of sequences strongly impacts their transfer rate, which varies by more than three orders of magnitude between different functional categories. Overall, we provide a comprehensive view of HGT, illuminating a fundamental process driving bacterial evolution.

Quantitative analysis of horizontal gene transfer in complex systems

Horizontal gene transfer (HGT) plays a significant role in rapidly propagating diverse traits throughout bacterial populations, thereby accelerating natural evolution and leading to complex community structures. Critical gene transfer rates underlying these occurrences dictate the efficiency and speed of gene spread; these rates are often highly specific to HGT mechanism and environmental context, and have historically been challenging to reliably quantify. In this review, we examine recent works that leverage rigorous quantitative methods to precisely measure these rates in a variety of settings beginning with in vitro studies and advancing to in situ measurements; we emphasize contexts where quantification across multiple scales of complexity has led to fundamental biological insights. Finally, we highlight the applications of these measurements and suggest potential methodological advances to improve our understanding.

Environmental hotspots for antibiotic resistance genes

Bacterial resistance toward broad-spectrum antibiotics has become a major concern in recent years. The threat posed by the infectious bacteria and the pace with which resistance determinants are transmitted needs to be deciphered. Soil and water contain unique and diverse microbial communities as well as pools of naturally occurring antibiotics resistant genes. Overuse of antibiotics along with poor sanitary practices expose these indigenous microbial communities to antibiotic resistance genes from other bacteria and accelerate the process of acquisition and dissemination. Clinical settings, where most antibiotics are prescribed, are hypothesized to serve as a major hotspot. The predisposition of the surrounding environments to a pool of antibiotic-resistant bacteria facilitates rapid antibiotic resistance among the indigenous microbiota in the soil, water, and clinical environments via horizontal gene transfer. This provides favorable conditions for the development of more multidrug-resistant pathogens. Limitations in detecting gene transfer mechanisms have likely left us underestimating the role played by the surrounding environmental hotspots in the emergence of multidrug-resistant bacteria. This review aims to identify the major drivers responsible for the spread of antibiotic resistance and hotspots responsible for the acquisition of antibiotic resistance genes.

Evolutionary mechanisms that determine which bacterial genes are carried on plasmids

The evolutionary pressures that determine the location (chromosomal or plasmid‐borne) of bacterial genes are not fully understood. We investigate these pressures through mathematical modeling in the context of antibiotic resistance, which is often found on plasmids. Our central finding is that gene location is under positive frequency‐dependent selection: the higher the frequency of one form of resistance compared to the other, the higher its relative fitness. This can keep moderately beneficial genes on plasmids, despite occasional plasmid loss. For these genes, positive frequency dependence leads to a priority effect: whichever form is acquired first—through either mutation or horizontal gene transfer—has time to increase in frequency and thus becomes difficult to displace. Higher rates of horizontal transfer of plasmid‐borne than chromosomal genes therefore predict moderately beneficial genes will be found on plasmids. Gene flow between plasmid and chromosome allows chromosomal forms to arise, but positive frequency‐dependent selection prevents these from establishing. Further modeling shows that this effect is particularly pronounced when genes are shared across a large number of species, suggesting that antibiotic resistance genes are often found on plasmids because they are moderately beneficial across many species. We also revisit previous theoretical work—relating to the role of local adaptation in explaining gene location and to plasmid persistence—in light of our findings.

Mechanisms That Shape Microbial Pangenomes

Analyses of multiple whole-genome sequences from the same species have revealed that differences in gene content can be substantial, particularly in prokaryotes. Such variation has led to the recognition of pangenomes, the complete set of genes present in a species - consisting of core genes, present in all individuals, and accessory genes whose presence is variable. Questions now arise about how pangenomes originate and evolve. We describe how gene content variation can arise as a result of the combination of several processes, including random drift, selection, gain/loss balance, and the influence of ecological and epistatic interactions. We believe that identifying the contributions of these processes to pangenomes will need novel theoretical approaches and empirical data.

Enabling rational gut microbiome manipulations by understanding gut ecology through experimentally-evidenced in silico models

The gut microbiome has emerged as a contributing factor in non-communicable disease, rendering it a target of health-promoting interventions. Yet current understanding of the host-microbiome dynamic is insufficient to predict the variation in intervention outcomes across individuals. We explore the mechanisms that underpin the gut bacterial ecosystem and highlight how a more complete understanding of this ecology will enable improved intervention outcomes. This ecology varies within the gut over space and time. Interventions disrupt these processes, with cascading consequences throughout the ecosystem. In vivo studies cannot isolate and probe these processes at the required spatiotemporal resolutions, and in vitro studies lack the representative complexity required. However, we highlight that, together, both approaches can inform in silico models that integrate cellular-level dynamics, can extrapolate to explain bacterial community outcomes, permit experimentation and observation over ecological processes at high spatiotemporal resolution, and can serve as predictive platforms on which to prototype interventions. Thus, it is a concerted integration of these techniques that will enable rational targeted manipulations of the gut ecosystem.

The ecology of plasmid-coded antibiotic resistance: a basic framework for experimental research and modeling

Many antibiotic resistance genes are associated with plasmids. The ecological success of these mobile genetic elements within microbial communities depends on varying mechanisms to secure their own propagation, not only on environmental selection. Among the most important are the cost of plasmids and their ability to be transferred to new hosts through mechanisms such as conjugation. These are regulated by dynamic control systems of the conjugation machinery and genetic adaptations that plasmid-host pairs can acquire in coevolution. However, in complex communities, these processes and mechanisms are subject to a variety of interactions with other bacterial species and other plasmid types. This article summarizes basic plasmid properties and ecological principles particularly important for understanding the persistence of plasmid-coded antibiotic resistance in aquatic environments. Through selected examples, it further introduces to the features of different types of simulation models such as systems of ordinary differential equations and individual-based models, which are considered to be important tools to understand these complex systems. This ecological perspective aims to improve the way we study and understand the dynamics, diversity and persistence of plasmids and associated antibiotic resistance genes.

Can mobile genetic elements rescue genes from extinction?

Bacteria and other prokaryotes evolve primarily through rapid changes in their gene content by quickly losing and gaining genes whenever an ecological opportunity emerges. As gene loss and horizontal gene transfer (HGT) appear to be the most common events across the prokaryotic tree of life, we need to think beyond gradual sequence evolution if we wish to understand the microbial world. Especially genes that reside on mobile genetic elements (MGEs) may spread much more rapidly through a microbial population than genes that reside on the bacterial chromosome. This raises the question: why are some genes associated with MGEs, while others are not? Here, I briefly review a recently proposed class of genes for which we have coined the term "rescuable genes". The fitness effect of carrying these genes is so small, either constantly or on average, that they are prone to be lost from a microbial population. I argue that HGT, even when costly to the individual cells, may play an important role in maintaining these rescuable genes in microbial communities.