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

Li, Fangfei; Tarkington, Jason; Sherlock, Gavin

doi:10.1007/s00239-023-10098-0

Cited by 14 publications

(10 citation statements)

References 40 publications

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“…To scale the inference pipeline to large datasets with > 10, 000 barcodes, we use the ADVI algorithm 7 to fit a variational posterior distribution. The main difference between our method and previous inference pipelines, such as Li et al [23], is that the present analysis provides interpretable errors on the inferred fitness values. The reported uncertainty intervals—known as credible regions—can be formally interpreted as capturing the corresponding probability mass of finding the true value of the parameter given the model, the prior information, and the data.…”

Section: Discussionmentioning

confidence: 88%

Bayesian inference of relative fitness on high-throughput pooled competition assays

Razo-Mejia,

Mani,

Petrov

2023

Preprint

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The tracking of lineage frequencies via DNA barcode sequencing enables the quantification of microbial fitness. However, experimental noise coming from biotic and abiotic sources complicates the computation of a reliable inference. We present a Bayesian pipeline to infer relative microbial fitness from high-throughput lineage tracking assays. Our model accounts for multiple sources of noise and propagates uncertainties throughout all parameters in a systematic way. Furthermore, using modern variational inference methods based on automatic differentiation, we are able to scale the inference to a large number of unique barcodes. We extend this core model to analyze multi-environment assays, replicate experiments, and barcodes linked to genotypes. On simulations, our method recovers known parameters within posterior credible intervals. This work provides a generalizable Bayesian framework to analyze lineage tracking experiments. The accompanying open-source software library enables the adoption of principled statistical methods in experimental evolution.

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Section: Discussionmentioning

confidence: 88%

Bayesian inference of relative fitness on high-throughput pooled competition assays

Razo-Mejia,

Mani,

Petrov

2023

Preprint

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“…We sequenced the barcodes in these populations to monitor the dynamics of evolution and to quantify the distribution of fitness effects. Using the approach implemented in software FitMut1 (Levy et al 2015; F. Li, Tarkington, and Sherlock 2023), we quantified the distribution of fitness effects for these populations and the original evolution experiment.…”

Section: Resultsmentioning

confidence: 99%

A shift from pleiotropic to modular adaptation revealed by a high-resolution two-step adaptive walk

Kinsler,

Li,

Sherlock

et al. 2024

Preprint

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Evolution by natural selection is expected to be a slow and gradual process. In particular, the mutations that drive evolution are predicted to be small and modular, incrementally improving a small number of traits. However, adaptive mutations identified early in microbial evolution experiments, cancer, and other systems often provide substantial fitness gains and pleiotropically improve multiple traits at once. We asked whether such pleiotropically adaptive mutations are common throughout adaptation or are instead a rare feature of early steps in evolution that tend to target key signaling pathways. To do so, we conducted barcoded second-step evolution experiments initiated from five first-step mutations identified from a prior yeast evolution experiment. We then isolated hundreds of second-step mutations from these evolution experiments, measured their fitness and performance in several growth phases, and conducted whole-genome sequencing of the second-step clones. Here, we found that while the vast majority of mutants isolated from the first-step of evolution in this condition show patterns of pleiotropic adaptation - improving both performance in fermentation and respiration growth phases - second-step mutations show a shift towards modular adaptation, mostly improving respiration performance and only rarely improving fermentation performance. We also identified a shift in the molecular basis of adaptation from genes in cellular signaling pathways towards genes involved in respiration and mitochondrial function. Our results suggest that the genes in cellular signaling pathways are particularly capable of providing large, adaptively pleiotropic benefits to the organism due to their ability to coherently affect many phenotypes at once. As such, these genes may serve as the source of pleiotropic adaptation in the early stages of evolution, and once these become exhausted, organisms then adapt more gradually, acquiring smaller, more modular mutations.

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“…54 To make these measurement high-throughput, host strains with unique sequence barcodes in their chromosomes and transformed with different engineered plasmids or DNA constructs could be simultaneously competed all-against-one-another in bulk competitive fitness assays. 55,56 Researchers can take actions to improve the constructability and stability of especially burdensome engineered DNA sequences. Most obviously, using low-or medium-copy plasmids rather than high-copy ones or integrating constructs into the chromosome of a bacterium to make them single-copy will often reduce burden into the cloneable and stable ranges.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Measuring the burden of hundreds of BioBricks defines an evolutionary limit on constructability in synthetic biology

Radde,

Mortensen,

Bhat

et al. 2024

Preprint

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Engineered DNA will slow the growth of a host cell if it redirects limiting resources or otherwise interferes with homeostasis. Populations of engineered cells can rapidly become dominated by “escape mutants” that evolve to alleviate this burden by inactivating the intended function. Synthetic biologists working with bacteria rely on genetic parts and devices encoded on plasmids, but the burden of different engineered DNA sequences is rarely characterized. We measured how 301 BioBricks on high-copy plasmids affected the growth rate ofEscherichia coli. Of these, 59 (19.6%) negatively impacted growth. The burden imposed by engineered DNA is commonly associated with diverting ribosomes or other gene expression factors away from producing endogenous genes that are essential for cellular replication. In line with this expectation, BioBricks exhibiting burden were more likely to contain highly active constitutive promoters and strong ribosome binding sites. By monitoring how much each BioBrick reduced expression of a chromosomal GFP reporter, we found that the burden of most, but not all, BioBricks could be wholly explained by diversion of gene expression resources. Overall, no BioBricks reduced the growth rate ofE. coliby >45%, which agreed with a population genetic model that predicts such plasmids should be “unclonable” because escape mutants will take over during growth of a bacterial colony or small laboratory culture from a transformed cell. We made this model available as an interactive web tool for synthetic biology education and added our burden measurements to the iGEM Registry descriptions of each BioBrick.

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

Cited by 14 publications

References 40 publications

Bayesian inference of relative fitness on high-throughput pooled competition assays

Bayesian inference of relative fitness on high-throughput pooled competition assays

A shift from pleiotropic to modular adaptation revealed by a high-resolution two-step adaptive walk

Measuring the burden of hundreds of BioBricks defines an evolutionary limit on constructability in synthetic biology

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