Arrayed in vivo barcoding for multiplexed sequence verification of plasmid DNA and demultiplexing of pooled libraries.

Sequence verification of plasmid DNA is critical for many cloning and molecular biology workflows. To leverage high-throughput sequencing, several methods have been developed that add a unique DNA barcode to individual samples prior to pooling and sequencing. However, these methods require an individual plasmid extraction and/or in vitro barcoding reaction for each sample processed, limiting throughput and adding cost. Here, we develop an arrayed in vivo plasmid barcoding platform that enables pooled plasmid extraction and library preparation for Oxford Nanopore sequencing. This method has a high accuracy and recovery rate, and greatly increases throughput and reduces cost relative to other plasmid barcoding methods or Sanger sequencing. We use in vivo barcoding to sequence verify >45 000 plasmids and show that the method can be used to transform error-containing dispersed plasmid pools into sequence-perfect arrays or well-balanced pools. In vivo barcoding does not require any specialized equipment beyond a low-overhead Oxford Nanopore sequencer, enabling most labs to flexibly process hundreds to thousands of plasmids in parallel.

Analysis and culturing of the prototypic crAssphage reveals a phage-plasmid lifestyle.

The prototypic crAssphage (Carjivirus communis) is one of the most abundant, prevalent, and persistent gut bacteriophages, yet it remains uncultured and its lifestyle uncharacterized. For the last decade, crAssphage has escaped plaque-dependent culturing efforts, leading us to investigate alternative lifestyles that might explain its widespread success. Through genomic analyses and culturing, we find that crAssphage uses a phage-plasmid lifestyle to persist extrachromosomally. Plasmid-related genes are more highly expressed than those implicated in phage maintenance. Leveraging this finding, we use a plaque-free culturing approach to measure crAssphage replication in culture with Phocaeicola vulgatus, Phocaeicola dorei, and Bacteroides stercoris, revealing a broad host range. We demonstrate that crAssphage persists with its hosts in culture without causing major cell lysis events or integrating into host chromosomes. The ability to switch between phage and plasmid lifestyles within a wide range of hosts contributes to the prolific nature of crAssphage in the human gut microbiome.

Spindle architecture constrains karyotype in budding yeast.

The eukaryotic cell division machinery must rapidly and reproducibly duplicate and partition the cell's chromosomes in a carefully coordinated process. However, chromosome number varies dramatically between genomes, even on short evolutionary timescales. We sought to understand how the mitotic machinery senses and responds to karyotypic changes by using a set of budding yeast strains in which the native chromosomes have been successively fused. Using a combination of cell biological profiling, genetic engineering, and experimental evolution, we show that chromosome fusions are well tolerated up until a critical point. However, with fewer than five centromeres, outward forces in the metaphase spindle cannot be countered by kinetochore-microtubule attachments, triggering mitotic defects. Our findings demonstrate that spindle architecture is a constraining factor for karyotype evolution.

Arrayed in vivo barcoding for multiplexed sequence verification of plasmid DNA and demultiplexing of pooled libraries.

Sequence verification of plasmid DNA is critical for many cloning and molecular biology workflows. To leverage high-throughput sequencing, several methods have been developed that add a unique DNA barcode to individual samples prior to pooling and sequencing. However, these methods require an individual plasmid extraction and/or in vitro barcoding reaction for each sample processed, limiting throughput and adding cost. Here, we develop an arrayed in vivo plasmid barcoding platform that enables pooled plasmid extraction and library preparation for Oxford Nanopore sequencing. This method has a high accuracy and recovery rate, and greatly increases throughput and reduces cost relative to other plasmid barcoding methods or Sanger sequencing. We use in vivo barcoding to sequence verify >45,000 plasmids and show that the method can be used to transform error-containing dispersed plasmid pools into sequence-perfect arrays or well-balanced pools. In vivo barcoding does not require any specialized equipment beyond a low-overhead Oxford Nanopore sequencer, enabling most labs to flexibly process hundreds to thousands of plasmids in parallel.

Evolution of haploid and diploid populations reveals common, strong, and variable pleiotropic effects in non-home environments.

Adaptation is driven by the selection for beneficial mutations that provide a fitness advantage in the specific environment in which a population is evolving. However, environments are rarely constant or predictable. When an organism well adapted to one environment finds itself in another, pleiotropic effects of mutations that made it well adapted to its former environment will affect its success. To better understand such pleiotropic effects, we evolved both haploid and diploid barcoded budding yeast populations in multiple environments, isolated adaptive clones, and then determined the fitness effects of adaptive mutations in 'non-home' environments in which they were not selected. We find that pleiotropy is common, with most adaptive evolved lineages showing fitness effects in non-home environments. Consistent with other studies, we find that these pleiotropic effects are unpredictable: they are beneficial in some environments and deleterious in others. However, we do find that lineages with adaptive mutations in the same genes tend to show similar pleiotropic effects. We also find that ploidy influences the observed adaptive mutational spectra in a condition-specific fashion. In some conditions, haploids and diploids are selected with adaptive mutations in identical genes, while in others they accumulate mutations in almost completely disjoint sets of genes.

Improved Sugarcane-Based Fermentation Processes by an Industrial Fuel-Ethanol Yeast Strain.

In Brazil, sucrose-rich broths (cane juice and/or molasses) are used to produce billions of liters of both fuel ethanol and cachaça per year using selected Saccharomyces cerevisiae industrial strains. Considering the important role of feedstock (sugar) prices in the overall process economics, to improve sucrose fermentation the genetic characteristics of a group of eight fuel-ethanol and five cachaça industrial yeasts that tend to dominate the fermentors during the production season were determined by array comparative genomic hybridization. The widespread presence of genes encoding invertase at multiple telomeres has been shown to be a common feature of both baker's and distillers' yeast strains, and is postulated to be an adaptation to sucrose-rich broths. Our results show that only two strains (one fuel-ethanol and one cachaça yeast) have amplification of genes encoding invertase, with high specific activity. The other industrial yeast strains had a single locus (SUC2) in their genome, with different patterns of invertase activity. These results indicate that invertase activity probably does not limit sucrose fermentation during fuel-ethanol and cachaça production by these industrial strains. Using this knowledge, we changed the mode of sucrose metabolism of an industrial strain by avoiding extracellular invertase activity, overexpressing the intracellular invertase, and increasing its transport through the AGT1 permease. This approach allowed the direct consumption of the disaccharide by the cells, without releasing glucose or fructose into the medium, and a 11% higher ethanol production from sucrose by the modified industrial yeast, when compared to its parental strain.

Experimental evolution for cell biology.

Evolutionary cell biology explores the origins, principles, and core functions of cellular features and regulatory networks through the lens of evolution. This emerging field relies heavily on comparative experiments and genomic analyses that focus exclusively on extant diversity and historical events, providing limited opportunities for experimental validation. In this opinion article, we explore the potential for experimental laboratory evolution to augment the evolutionary cell biology toolbox, drawing inspiration from recent studies that combine laboratory evolution with cell biological assays. Primarily focusing on approaches for single cells, we provide a generalizable template for adapting experimental evolution protocols to provide fresh insight into long-standing questions in cell biology.

Paths to adaptation under fluctuating nitrogen starvation: The spectrum of adaptive mutations in Saccharomyces cerevisiae is shaped by retrotransposons and microhomology-mediated recombination.

There are many mechanisms that give rise to genomic change: while point mutations are often emphasized in genomic analyses, evolution acts upon many other types of genetic changes that can result in less subtle perturbations. Changes in chromosome structure, DNA copy number, and novel transposon insertions all create large genomic changes, which can have correspondingly large impacts on phenotypes and fitness. In this study we investigate the spectrum of adaptive mutations that arise in a population under consistently fluctuating nitrogen conditions. We specifically contrast these adaptive alleles and the mutational mechanisms that create them, with mechanisms of adaptation under batch glucose limitation and constant selection in low, non-fluctuating nitrogen conditions to address if and how selection dynamics influence the molecular mechanisms of evolutionary adaptation. We observe that retrotransposon activity accounts for a substantial number of adaptive events, along with microhomology-mediated mechanisms of insertion, deletion, and gene conversion. In addition to loss of function alleles, which are often exploited in genetic screens, we identify putative gain of function alleles and alleles acting through as-of-yet unclear mechanisms. Taken together, our findings emphasize that how selection (fluctuating vs. non-fluctuating) is applied also shapes adaptation, just as the selective pressure (nitrogen vs. glucose) does itself. Fluctuating environments can activate different mutational mechanisms, shaping adaptive events accordingly. Experimental evolution, which allows a wider array of adaptive events to be assessed, is thus a complementary approach to both classical genetic screens and natural variation studies to characterize the genotype-to-phenotype-to-fitness map.

An improved algorithm for inferring mutational parameters from bar-seq evolution experiments.

BACKGROUND: Genetic barcoding provides a high-throughput way to simultaneously track the frequencies of large numbers of competing and evolving microbial lineages. However making inferences about the nature of the evolution that is taking place remains a difficult task. RESULTS: Here we describe an algorithm for the inference of fitness effects and establishment times of beneficial mutations from barcode sequencing data, which builds upon a Bayesian inference method by enforcing self-consistency between the population mean fitness and the individual effects of mutations within lineages. By testing our inference method on a simulation of 40,000 barcoded lineages evolving in serial batch culture, we find that this new method outperforms its predecessor, identifying more adaptive mutations and more accurately inferring their mutational parameters. CONCLUSION: Our new algorithm is particularly suited to inference of mutational parameters when read depth is low. We have made Python code for our serial dilution evolution simulations, as well as both the old and new inference methods, available on GitHub ( https://github.com/FangfeiLi05/FitMut2 ), in the hope that it can find broader use by the microbial evolution community.

Fit-Seq2.0: An Improved Software for High-Throughput Fitness Measurements Using Pooled Competition Assays.

The fitness of a genotype is defined as its lifetime reproductive success, with fitness itself being a composite trait likely dependent on many underlying phenotypes. Measuring fitness is important for understanding how alteration of different cellular components affects a cell's ability to reproduce. Here, we describe an improved approach, implemented in Python, for estimating fitness in high throughput via pooled competition assays.

Yca1 metacaspase: diverse functions determine how yeast live and let die.

The Yca1 metacaspase was discovered due to its role in the regulation of apoptosis in Saccharomyces cerevisiae. However, the mechanisms that drive apoptosis in yeast remain poorly understood. Additionally, Yca1 and other metacaspase proteins have recently been recognized for their involvement in other cellular processes, including cellular proteostasis and cell cycle regulation. In this minireview, we outline recent findings on Yca1 that will enable the further study of metacaspase multifunctionality and novel apoptosis pathways in yeast and other nonmetazoans. In addition, we discuss advancements in high-throughput screening technologies that can be applied to answer complex questions surrounding the apoptotic and nonapoptotic functions of metacaspase proteins across a diverse range of species.

How to Use the Candida Genome Database.

The Candida Genome Database provides access to biological information about genes and proteins of several medically important Candida species. The website is organized into easily navigable pages that enable data retrieval and analysis. This chapter shows how to explore the CGD Home page and Locus Summary pages, which are the main access points to the database. It also provides a description of how to use the GO analysis tools, GO Term Finder, and GO Slim Mapper and how to browse large-scale datasets using the JBrowse genome browser. Finally, it shows how to search and retrieve data for user-defined sets of genes using the Advanced Search and Batch Download tools.

S. cerevisiae Cells Can Grow without the Pds5 Cohesin Subunit.

During DNA replication, the newly created sister chromatids are held together until their separation at anaphase. The cohesin complex is in charge of creating and maintaining sister chromatid cohesion (SCC) in all eukaryotes. In Saccharomyces cerevisiae cells, cohesin is composed of two elongated proteins, Smc1 and Smc3, bridged by the kleisin Mcd1/Scc1. The latter also acts as a scaffold for three additional proteins, Scc3/Irr1, Wpl1/Rad61, and Pds5. Although the HEAT-repeat protein Pds5 is essential for cohesion, its precise function is still debated. Deletion of the ELG1 gene, encoding a PCNA unloader, can partially suppress the temperature-sensitive pds5-1 allele, but not a complete deletion of PDS5. We carried out a genetic screen for high-copy-number suppressors and another for spontaneously arising mutants, allowing the survival of a pds5Δ elg1Δ strain. Our results show that cells remain viable in the absence of Pds5 provided that there is both an elevation in the level of Mcd1 (which can be due to mutations in the CLN2 gene, encoding a G1 cyclin), and an increase in the level of SUMO-modified PCNA on chromatin (caused by lack of PCNA unloading in elg1Δ mutants). The elevated SUMO-PCNA levels increase the recruitment of the Srs2 helicase, which evicts Rad51 molecules from the moving fork, creating single-stranded DNA (ssDNA) regions that serve as sites for increased cohesin loading and SCC establishment. Thus, our results delineate a double role for Pds5 in protecting the cohesin ring and interacting with the DNA replication machinery. IMPORTANCE Sister chromatid cohesion is vital for faithful chromosome segregation, chromosome folding into loops, and gene expression. A multisubunit protein complex known as cohesin holds the sister chromatids from S phase until the anaphase stage. In this study, we explore the function of the essential cohesin subunit Pds5 in the regulation of sister chromatid cohesion. We performed two independent genetic screens to bypass the function of the Pds5 protein. We observe that Pds5 protein is a cohesin stabilizer, and elevating the levels of Mcd1 protein along with SUMO-PCNA accumulation on chromatin can compensate for the loss of the PDS5 gene. In addition, Pds5 plays a role in coordinating the DNA replication and sister chromatid cohesion establishment. This work elucidates the function of cohesin subunit Pds5, the G1 cyclin Cln2, and replication factors PCNA, Elg1, and Srs2 in the proper regulation of sister chromatid cohesion.

Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics.

The rate of adaptive evolution depends on the rate at which beneficial mutations are introduced into a population and the fitness effects of those mutations. The rate of beneficial mutations and their expected fitness effects is often difficult to empirically quantify. As these 2 parameters determine the pace of evolutionary change in a population, the dynamics of adaptive evolution may enable inference of their values. Copy number variants (CNVs) are a pervasive source of heritable variation that can facilitate rapid adaptive evolution. Previously, we developed a locus-specific fluorescent CNV reporter to quantify CNV dynamics in evolving populations maintained in nutrient-limiting conditions using chemostats. Here, we use CNV adaptation dynamics to estimate the rate at which beneficial CNVs are introduced through de novo mutation and their fitness effects using simulation-based likelihood-free inference approaches. We tested the suitability of 2 evolutionary models: a standard Wright-Fisher model and a chemostat model. We evaluated 2 likelihood-free inference algorithms: the well-established Approximate Bayesian Computation with Sequential Monte Carlo (ABC-SMC) algorithm, and the recently developed Neural Posterior Estimation (NPE) algorithm, which applies an artificial neural network to directly estimate the posterior distribution. By systematically evaluating the suitability of different inference methods and models, we show that NPE has several advantages over ABC-SMC and that a Wright-Fisher evolutionary model suffices in most cases. Using our validated inference framework, we estimate the CNV formation rate at the GAP1 locus in the yeast Saccharomyces cerevisiae to be 10-4.7 to 10-4 CNVs per cell division and a fitness coefficient of 0.04 to 0.1 per generation for GAP1 CNVs in glutamine-limited chemostats. We experimentally validated our inference-based estimates using 2 distinct experimental methods-barcode lineage tracking and pairwise fitness assays-which provide independent confirmation of the accuracy of our approach. Our results are consistent with a beneficial CNV supply rate that is 10-fold greater than the estimated rates of beneficial single-nucleotide mutations, explaining the outsized importance of CNVs in rapid adaptive evolution. More generally, our study demonstrates the utility of novel neural network-based likelihood-free inference methods for inferring the rates and effects of evolutionary processes from empirical data with possible applications ranging from tumor to viral evolution.

Quantifying rapid bacterial evolution and transmission within the mouse intestine.

Due to limitations on high-resolution strain tracking, selection dynamics during gut microbiota colonization and transmission between hosts remain mostly mysterious. Here, we introduced hundreds of barcoded Escherichia coli strains into germ-free mice and quantified strain-level dynamics and metagenomic changes. Mutations in genes involved in motility and metabolite utilization are reproducibly selected within days. Even with rapid selection, coprophagy enforced similar barcode distributions across co-housed mice. Whole-genome sequencing of hundreds of isolates revealed linked alleles that demonstrate between-host transmission. A population-genetics model predicts substantial fitness advantages for certain mutants and that migration accounted for ∼10% of the resident microbiota each day. Treatment with ciprofloxacin suggests interplay between selection and transmission. While initial colonization was mostly uniform, in two mice a bottleneck reduced diversity and selected for ciprofloxacin resistance in the absence of drug. These findings highlight the interplay between environmental transmission and rapid, deterministic selection during evolution of the intestinal microbiota.

Changes in the distribution of fitness effects and adaptive mutational spectra following a single first step towards adaptation.

Historical contingency and diminishing returns epistasis have been typically studied for relatively divergent genotypes and/or over long evolutionary timescales. Here, we use Saccharomyces cerevisiae to study the extent of diminishing returns and the changes in the adaptive mutational spectra following a single first adaptive mutational step. We further evolve three clones that arose under identical conditions from a common ancestor. We follow their evolutionary dynamics by lineage tracking and determine adaptive outcomes using fitness assays and whole genome sequencing. We find that diminishing returns manifests as smaller fitness gains during the 2nd step of adaptation compared to the 1st step, mainly due to a compressed distribution of fitness effects. We also find that the beneficial mutational spectra for the 2nd adaptive step are contingent on the 1st step, as we see both shared and diverging adaptive strategies. Finally, we find that adaptive loss-of-function mutations, such as nonsense and frameshift mutations, are less common in the second step of adaptation than in the first step.

Evolutionary dynamics and structural consequences of de novo beneficial mutations and mutant lineages arising in a constant environment.

BACKGROUND: Microbial evolution experiments can be used to study the tempo and dynamics of evolutionary change in asexual populations, founded from single clones and growing into large populations with multiple clonal lineages. High-throughput sequencing can be used to catalog de novo mutations as potential targets of selection, determine in which lineages they arise, and track the fates of those lineages. Here, we describe a long-term experimental evolution study to identify targets of selection and to determine when, where, and how often those targets are hit. RESULTS: We experimentally evolved replicate Escherichia coli populations that originated from a mutator/nonsense suppressor ancestor under glucose limitation for between 300 and 500 generations. Whole-genome, whole-population sequencing enabled us to catalog 3346 de novo mutations that reached > 1% frequency. We sequenced the genomes of 96 clones from each population when allelic diversity was greatest in order to establish whether mutations were in the same or different lineages and to depict lineage dynamics. Operon-specific mutations that enhance glucose uptake were the first to rise to high frequency, followed by global regulatory mutations. Mutations related to energy conservation, membrane biogenesis, and mitigating the impact of nonsense mutations, both ancestral and derived, arose later. New alleles were confined to relatively few loci, with many instances of identical mutations arising independently in multiple lineages, among and within replicate populations. However, most never exceeded 10% in frequency and were at a lower frequency at the end of the experiment than at their maxima, indicating clonal interference. Many alleles mapped to key structures within the proteins that they mutated, providing insight into their functional consequences. CONCLUSIONS: Overall, we find that when mutational input is increased by an ancestral defect in DNA repair, the spectrum of high-frequency beneficial mutations in a simple, constant resource-limited environment is narrow, resulting in extreme parallelism where many adaptive mutations arise but few ever go to fixation.

Adaptation is influenced by the complexity of environmental change during evolution in a dynamic environment.

The environmental conditions of microorganisms' habitats may fluctuate in unpredictable ways, such as changes in temperature, carbon source, pH, and salinity to name a few. Environmental heterogeneity presents a challenge to microorganisms, as they have to adapt not only to be fit under a specific condition, but they must also be robust across many conditions and be able to deal with the switch between conditions itself. While experimental evolution has been used to gain insight into the adaptive process, this has largely been in either unvarying or consistently varying conditions. In cases where changing environments have been investigated, relatively little is known about how such environments influence the dynamics of the adaptive process itself, as well as the genetic and phenotypic outcomes. We designed a systematic series of evolution experiments where we used two growth conditions that have differing timescales of adaptation and varied the rate of switching between them. We used lineage tracking to follow adaptation, and whole genome sequenced adaptive clones from each of the experiments. We find that both the switch rate and the order of the conditions influences adaptation. We also find different adaptive outcomes, at both the genetic and phenotypic levels, even when populations spent the same amount of total time in the two different conditions, but the order and/or switch rate differed. Thus, in a variable environment adaptation depends not only on the nature of the conditions and phenotypes under selection, but also on the complexity of the manner in which those conditions are combined to result in a given dynamic environment.