Lessons from a Minimal Genome: What Are the Essential Organizing Principles of a Cell Built from Scratch?

Tarnopol, Rebecca L.; Bowden, Sierra; Hinkle, Kevin J.; Balakrishnan, Krithika; Nishii, Akira; Kaczmarek, Caleb J.; Pawloski, Tara; Vecchiarelli, Anthony G.

doi:10.1002/cbic.201900249

Cited by 9 publications

(5 citation statements)

References 101 publications

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“…In the pangenome context, the “complexity hypothesis” was coined to depict the dependency of gene horizontal transferability on the network connectivity and biological process 81 , 82 , with the former playing a dominant role 83 , 84 , 85 . As many as 92% of gene families in bacteria have evidence of horizontal transfer 86 , and the observed variation in network connectivity and network rewiring level in Sinorhizobium core genome provides valuable pangenome evolutionary information for further synthetic biology studies 87 .…”

Section: Resultsmentioning

confidence: 99%

“…This value is close to the average size of a bacterial minimal genome (394 ± 36; 95% confidence interval) 70 , implying that this subset may represent the ES genome of the last common ancestor of extant Sinorhizobium strains. This procedure may be generalized to provide a robust minimal genome reference for both ancestral genome reconstruction of the last common ancestor of extant sibling species 88 and the bottom‐up design of a synthetic cell 87 .…”

Section: Resultsmentioning

confidence: 99%

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Cofitness network connectivity determines a fuzzy essential zone in open bacterial pangenome

Zhang,

et al. 2024

mLife

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Most in silico evolutionary studies commonly assumed that core genes are essential for cellular function, while accessory genes are dispensable, particularly in nutrient‐rich environments. However, this assumption is seldom tested genetically within the pangenome context. In this study, we conducted a robust pangenomic Tn‐seq analysis of fitness genes in a nutrient‐rich medium for Sinorhizobium strains with a canonical open pangenome. To evaluate the robustness of fitness category assignment, Tn‐seq data for three independent mutant libraries per strain were analyzed by three methods, which indicates that the Hidden Markov Model (HMM)‐based method is most robust to variations between mutant libraries and not sensitive to data size, outperforming the Bayesian and Monte Carlo simulation‐based methods. Consequently, the HMM method was used to classify the fitness category. Fitness genes, categorized as essential (ES), advantage (GA), and disadvantage (GD) genes for growth, are enriched in core genes, while nonessential genes (NE) are over‐represented in accessory genes. Accessory ES/GA genes showed a lower fitness effect than core ES/GA genes. Connectivity degrees in the cofitness network decrease in the order of ES, GD, and GA/NE. In addition to accessory genes, 1599 out of 3284 core genes display differential essentiality across test strains. Within the pangenome core, both shared quasi‐essential (ES and GA) and strain‐dependent fitness genes are enriched in similar functional categories. Our analysis demonstrates a considerable fuzzy essential zone determined by cofitness connectivity degrees in Sinorhizobium pangenome and highlights the power of the cofitness network in understanding the genetic basis of ever‐increasing prokaryotic pangenome data.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Cofitness network connectivity determines a fuzzy essential zone in open bacterial pangenome

Zhang,

et al. 2024

mLife

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show abstract

“…In the pangenome context, the "complexity hypothesis" was coined to depict the dependency of gene horizontal transferability on the network connectivity and biological process 57,58 , with the former playing a dominant role 51,52,59 . As many as 92% gene families in bacteria have evidence of horizontal transfer 60 , the observed variation in network connectivity and network rewiring level in Sinorhizobium core genome provides valuable pangenome evolutionary information for further synthetic biology studies 61 .…”

Section: Co-fitness Network Analysis Revealed a Fuzzy Essential Zone ...mentioning

confidence: 99%

“…This value is close to the average size of a bacterial minimal genome (394 ± 36; 95% confidence interval) 41 , implying that this subset may represent the essential genome of the last common ancestor of extant Sinorhizobium strains. This procedure may be generalized to provide a robust minimal genome reference for both ancestral genome reconstruction of the last common ancestor of extant sibling species 62 and the bottom-up design of a synthetic cell 61 .…”

Section: Evolutionary and Functional Insights Into The Co-fitness Net...mentioning

confidence: 99%

Co-fitness network connectivity determines a fuzzy essential zone in Sinorhizobium of canonical open pangenome

Zhang

Zhang²,

Ji³

et al. 2023

Preprint

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Most in silico evolutionary studies commonly assumed that core genes are essential for cellular function, while accessory genes are dispensable, particularly in nutrient-rich environments. However, this assumption is seldom tested genetically within the pangenome context. Here we conducted a robust pangenomic Tn-seq analysis of fitness genes in a nutrient-rich medium for Sinorhizobium strains with a canonical open pangenome. The Hidden Markov Model-based method is the most robust to variations among mutant libraries per strain and non-sensitive to data size. Fitness genes, categorized as essential (ES), advantage (GA) and disadvantage (GD) for growth, are enriched in core genes, while nonessential genes (NE) are over-represented in accessory genes. Connectivity degrees in predicted protein-protein interaction networks decline in the order of ES, GA, GD and NE, and those in the co-fitness network decreases from ES to GA/GD to NE. Notably, 1599 out of 3284 core genes display differential essentiality across test strains. Within pangenome core, both shared quasi-essential (ES and GA) and strain-dependent fitness genes are enriched in similar functional categories. Our analysis demonstrates a considerable fuzzy essential zone determined by co-fitness connectivity degrees in Sinorhizobium pangenome, and highlights the power of co-fitness network in understanding genetic basis of ever-increasing prokaryotic pangenome data.

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“…This can give a good idea of genes necessary for life across all species, but these alone would not be sufficient for survival. Accessory genes and metabolic genes are also required for survival in the given environment ( Tarnopol et al, 2019 ). Additionally, proteins with similar functions may not necessarily have sequence similarities ( Riley and Serres, 2000 ).…”

Section: Designing a Reduced-genome Bacteriummentioning

confidence: 99%

Bacterial genome reductions: Tools, applications, and challenges

LeBlanc

Charles

2022

Front. Genome Ed.

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Bacterial cells are widely used to produce value-added products due to their versatility, ease of manipulation, and the abundance of genome engineering tools. However, the efficiency of producing these desired biomolecules is often hindered by the cells’ own metabolism, genetic instability, and the toxicity of the product. To overcome these challenges, genome reductions have been performed, making strains with the potential of serving as chassis for downstream applications. Here we review the current technologies that enable the design and construction of such reduced-genome bacteria as well as the challenges that limit their assembly and applicability. While genomic reductions have shown improvement of many cellular characteristics, a major challenge still exists in constructing these cells efficiently and rapidly. Computational tools have been created in attempts at minimizing the time needed to design these organisms, but gaps still exist in modelling these reductions in silico. Genomic reductions are a promising avenue for improving the production of value-added products, constructing chassis cells, and for uncovering cellular function but are currently limited by their time-consuming construction methods. With improvements to and the creation of novel genome editing tools and in silico models, these approaches could be combined to expedite this process and create more streamlined and efficient cell factories.

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Lessons from a Minimal Genome: What Are the Essential Organizing Principles of a Cell Built from Scratch?

Cited by 9 publications

References 101 publications

Cofitness network connectivity determines a fuzzy essential zone in open bacterial pangenome

Cofitness network connectivity determines a fuzzy essential zone in open bacterial pangenome

Co-fitness network connectivity determines a fuzzy essential zone in Sinorhizobium of canonical open pangenome

Bacterial genome reductions: Tools, applications, and challenges

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