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Systematic perturbation of cytoskeletal function reveals a linear scaling relationship between cell geometry and fitness.

ABSTRACT: Diversification of cell size is hypothesized to have occurred through a process of evolutionary optimization, but direct demonstrations of causal relationships between cell geometry and fitness are lacking. Here, we identify a mutation from a laboratory-evolved bacterium that dramatically increases cell size through cytoskeletal perturbation and confers a large fitness advantage. We engineer a library of cytoskeletal mutants of different sizes and show that fitness scales linearly with respect to cell size over a wide physiological range. Quantification of the growth rates of single cells during the exit from stationary phase reveals that transitions between "feast-or-famine" growth regimes are a key determinant of cell-size-dependent fitness effects. We also uncover environments that suppress the fitness advantage of larger cells, indicating that cell-size-dependent fitness effects are subject to both biophysical and metabolic constraints. Together, our results highlight laboratory-based evolution as a powerful framework for studying the quantitative relationships between morphology and fitness.

SUBMITTER: Monds RD

PROVIDER: S-EPMC6586469 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Systematic perturbation of cytoskeletal function reveals a linear scaling relationship between cell geometry and fitness.

Monds Russell D RD Lee Timothy K TK Colavin Alexandre A Ursell Tristan T Quan Selwyn S Cooper Tim F TF Huang Kerwyn Casey KC

Cell reports 20141113 4

Diversification of cell size is hypothesized to have occurred through a process of evolutionary optimization, but direct demonstrations of causal relationships between cell geometry and fitness are lacking. Here, we identify a mutation from a laboratory-evolved bacterium that dramatically increases cell size through cytoskeletal perturbation and confers a large fitness advantage. We engineer a library of cytoskeletal mutants of different sizes and show that fitness scales linearly with respect t ...[more]

PMID: 25456141

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Project description:The coupled-cluster (CC) singles and doubles with perturbative triples [CCSD(T)] method is frequently referred to as the "gold standard" of modern computational chemistry. However, the high computational cost of CCSD(T) [O(N7)], where N is the number of basis functions, limits its applications to small-sized chemical systems. To address this problem, efficient implementations of linear-scaling coupled-cluster methods, which employ the systematic molecular fragmentation (SMF) approach, are reported. In this study, we aim to do the following: (1) To achieve exact linear scaling and to obtain a pure ab initio approach, we revise the handling of nonbonded interactions in the SMF approach, denoted by LSSMF. (2) A new fragmentation algorithm, which yields smaller-sized fragments, that better fits high-level CC methods is introduced. (3) A modified nonbonded fragmentation scheme is proposed to enhance the existent algorithm. Performances of the LSSMF-CC approaches, such as LSSMF-CCSD(T), are compared with their canonical versions for a set of alkane molecules, CnH2n+2 (n = 6-10), which includes 142 molecules. Our results demonstrate that the LSSMF approach introduces negligible errors compared with the canonical methods; mean absolute errors (MAEs) are between 0.20 and 0.59 kcal mol-1 for LSSMF(3,1)-CCSD(T). For a larger alkanes set (L12), CnH2n+2 (n = 50-70), the performance of LSSMF for the second-order perturbation theory (MP2) is investigated. For the L12 set, various bonded and nonbonded levels are considered. Our results demonstrate that the combination of bonded level 6 with nonbonded level 2, LSSMF(6,2), provides very accurate results for the MP2 method with a MAE value of 0.32 kcal mol-1. The LSSMF(6,2) approach yields more than a 26-fold reduction in errors compared with LSSMF(3,1). Hence, we obtain substantial improvements over the original SMF approach. To illustrate the efficiency and applicability of the LSSMF-CCSD(T) approach, we consider an alkane molecule with 10,004 atoms. For this molecule, the LSSMF(3,1)-CCSD(T)/cc-pVTZ energy computation, on a Linux cluster with 100 nodes, 4 cores, and 5 GB of memory provided to each node, is performed just in ∼24 h. As a second test, we consider a biomolecular complex (PDB code: 1GLA), which includes 10,488 atoms, to assess the efficiency of the LSSMF approach. The LSSMF(3,1)-FNO-CCSD(T)/cc-pVTZ energy computation is completed in ∼7 days for the biomolecular complex. Hence, our results demonstrate that the LSSMF-CC approaches are very efficient. Overall, we conclude the following: (1) The LSSMF(m, n)-CCSD(T) methods can be reliably used for large-scale chemical systems, where the canonical methods are not computationally affordable. (2) The accuracy of bonded level 3 is not satisfactory for large chemical systems. (3) For high-accuracy studies, bonded level 5 (or higher) and nonbonded level 2 should be employed.

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Systematic perturbation of cytoskeletal function reveals a linear scaling relationship between cell geometry and fitness.

Publications

Systematic perturbation of cytoskeletal function reveals a linear scaling relationship between cell geometry and fitness.

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