Search bioRxiv⌕ Search

Biology subjects

Gencel, M.

Publications and source records attributed to Gencel, M..

5 recordsLinked to original sources

A strong-to-weak interaction shift during microbiome succession is coupled to colonizer-dependent antimicrobial resistance

The outcome of ecological succession is often attributed to the characteristics of the invader or the resident community, but rarely to how the community's interaction network reorganizes during assembly. Here, we track intraspecific lineage dynamics and infer time-resolved community interaction networks using Dynamic Covariance Mapping during ecological invasion of the mouse gut by a chromosomally barcoded, spectinomycin-resistant Escherichia coli K12 colonizer. The network is initially dominated by strong, predominantly inhibitory interactions, but as community diversity recovers, the distribution of interaction strengths contracts toward zero, producing a community increasingly dominated by weak and near-neutral interactions. The dominant eigenvalue of the DCM-inferred interaction matrix moves toward marginal stability predicted for dynamically assembling ecological networks. This pattern replicates across eight independent mice in two experimental cohorts, at both inter- and intra-species resolution. The ecological transition coincides with the reproducible resurgence of Paenibacillaceae to high relative abundance and persistent coexistence with E. coli under continued spectinomycin pressure. Whole-genome sequencing of recovered Paenibacillus macerans isolates identifies recurrent mutations in ribosomal protein S5 region associated with spectinomycin binding and strongly implicating this variant in resistance. Strikingly, under antibiotic pressure but without E. coli K12 invasion, resident Paenibacillaceae never blooms, indicating that expansion of the resistant population depends on the ecological context established by the colonizer. These findings show that gut microbiome succession is accompanied by a reproducible transition from strong toward weak interactions and link this network reorganization to the colonizer-dependent ecological benefit of antimicrobial resistance.

ecology↗

HP1-enhanced chromatin compaction stabilizes a synthetic metabolic circuit in yeast

Chromatin compaction defines genome topology, evolution, and function. The Saccharomycotina subphylum, including the fermenting yeast Saccharomyces cerevisiae have a decompacted genome, possibly because they lost two genes mediating a specific histone lysine methylation and histone binding protein heterochromatin protein 1 (HP1). This decompaction may result in the higher-than-expected mutation and meiotic recombination rates observed in this species. To test this hypothesis, we retro-engineered S. cerevisiae to compact the genome by expressing the HP1 homologue of Schizosaccharomyces pombe SpSwi6 and H3K9 methyltransferase SpClr4. The resulting strain had significantly more compact chromatin and reduced rates of mutation and meiotic recombination. The increased genomic stability significantly prolongs the optogenetic control of an engineered strain designed to grow only in blue light. This result demonstrates the potential of our approach to enhance the stability of strains for metabolic engineering and other synthetic biology applications, which are prone to lose activities due to genetic instability.

synthetic biology↗

Doblin: Inferring dominant clonal lineages from DNA barcoding time-series

MotivationThe lineage dynamics and history of cells in a population reflect the interplay of evolutionary forces they experience, namely mutation, drift, and selection. When the population is polyclonal, lineage dynamics also manifest the extent of clonal competition among co-existing mutational variants. If the population exists in a community of other species, the lineage dynamics could also reflect the populations ecological interaction with the rest of the community. Recent advances in high-resolution lineage tracking via DNA barcoding, coupled with next-generation sequencing of bacteria, yeast, and mammalian cells, allow for precise quantification of clonal dynamics in these organisms. ResultsIn this work, we introduce Doblin, an R suite for identifying dominant barcode lineages based on high-resolution lineage tracking data. We first benchmarked Doblins accuracy using lineage data from evolutionary simulations, showing that it recovers clones identity and relative fitness in the simulation. Subsequently, we applied Doblin to analyze clonal dynamics in laboratory evolutions of E. coli populations undergoing antibiotic treatment and in colonization experiments of the gut microbial community. Doblins versatility allows it to be applied to lineage time-series data across different experimental setups. Availability and implementationThe source code and data are available at https://github.com/dagagf/doblin.

bioinformatics↗

The fitness effects of codon composition of the horizontally transferred antibiotic resistance genes intensify at sub-lethal antibiotic levels.

The rampant variability in codon bias existing between bacterial genomes is expected to interfere with horizontal gene transfer (HGT), a phenomenon that drives bacterial adaptation. However, delineating the constraints imposed by codon bias on functional integration of the transferred genes is complicated by multiple genomic and functional barriers controlling HGT, and by the dependence of the evolutionary outcomes of HGT on the hosts environment. Here, we designed an experimental system in which codon composition of the transferred genes is the only variable triggering fitness change of the host. We replaced E. colis chromosomal folA gene encoding dihydrofolate reductase, an essential enzyme that constitutes a target for trimethoprim, with combinatorial libraries of synonymous codons of folA genes from trimethoprim-sensitive Listeria grayi and trimethoprim-resistant Neisseria sicca. The resulting populations underwent selection at a range of trimethoprim concentrations, and the ensuing changes in variant frequencies were used to infer the fitness effects of the individual combinations of codons. We found that when HGT causes overstabilization of the 5-end mRNA, the fitness contribution of mRNA folding stability dominates over that of codon optimality. The 5-end overstabilization can also lead to mRNA accumulation outside of the polysome, thus preventing the decay of the foreign transcripts despite the codon composition-driven reduction in translation efficiency. Importantly, the fitness effects of mRNA stability or codon optimality become apparent only at sub-lethal levels of trimethoprim individually tailored for each library, emphasizing the central role of the hosts environment in shaping the codon bias compatibility of horizontally transferred genes.

microbiology↗

Intra- and inter-species interactions drive early phases of invasion in mice gut microbiota

The stability and dynamics of ecological communities are dictated by interaction networks typically quantified at the level of species.1-10 But how such networks are influenced by intra-species variation (ISV) is poorly understood.11-14 Here, we use ~500,000 chromosomal barcodes to track high-resolution intra-species clonal lineages of Escherichia coli invading mice gut with the increasing complexity of gut microbiome: germ-free, antibiotic-perturbed, and innate microbiota. By co-clustering the dynamics of intra-species clonal lineages and those of gut bacteria from 16S rRNA profiling, we show the emergence of complex time-dependent interactions between E. coli clones and resident gut bacteria. With a new approach, dynamic covariance mapping (DCM), we differentiate three phases of invasion in susceptible communities: 1) initial loss of community stability as E. coli enters; 2) recolonization of some gut bacteria; and 3) recovery of stability with E. coli coexisting with resident bacteria in a quasi-steady state. Comparison of the dynamics, stability and fitness from experimental replicates and different cohorts suggest that phase 1 is driven by mutations in E. coli before colonization, while phase 3 is by de novo mutations. Our results highlight the transient nature of interaction networks in microbiomes driven by the persistent coupling of ecological and evolutionary dynamics. One-Sentence SummaryHigh-resolution lineage tracking and dynamic covariance mapping (DCM) define three distinct phases during early gut microbiome invasion.

evolutionary biology↗