The ability to efficiently and dynamically change information stored in genomes would enable powerful strategies for studying cell biology and controlling cellular phenotypes. Current recombineering-mediated DNA writing platforms in bacteria are limited to specific laboratory conditions, often suffer from suboptimal editing efficiencies, and are not suitable for in situ applications. To overcome these limitations, we engineered a retroelement-mediated DNA writing system that enables efficient and precise editing of bacterial genomes without the requirement for target-specific elements or selection. We demonstrate that this DNA writing platform enables a broad range of applications, including efficient, scarless, and cis-element-independent editing of targeted microbial genomes within complex communities, the high-throughput mapping of spatial information and cellular interactions into DNA memory, and the continuous evolution of cellular traits.

Genome-scale models of metabolism (GEMs) are key computational tools for the systems-level study of metabolic networks. Here, we describe the "GEM life cycle," which we subdivide into four stages: inception, maturation, specialization, and amalgamation. We show how different types of GEM reconstruction workflows fit in each stage and proceed to highlight two fundamental bottlenecks for GEM quality improvement: GEM maturation and content removal. We identify common characteristics contributing to increasing quality of maturing GEMs drawing from past independent GEM maturation efforts. We then shed some much-needed light on the latent and unrecognized but pervasive issue of content removal, demonstrating the substantial effects of model pruning on its solution space. Finally, we propose a novel framework for content removal and associated confidence-level assignment which will help guide future GEM development efforts, reduce duplication of effort across groups, potentially aid automated reconstruction platforms, and boost the reproducibility of model development.

Comment in Cell Syst. 2021 Sep 22;12(9):839-841.

Despite abundant measurements of bacterial growth rate, cell size, and protein content, we lack a rigorous understanding of what sets the scale of these quantities and when protein abundances should (or should not) depend on growth rate. Here, we estimate the basic requirements and physical constraints on steady-state growth by considering key processes in cellular physiology across a collection of Escherichia coli proteomic data covering ≈4,000 proteins and 36 growth rates. Our analysis suggests that cells are predominantly tuned for the task of cell doubling across a continuum of growth rates; specific processes do not limit growth rate or dictate cell size. We present a model of proteomic regulation as a function of nutrient supply that reconciles observed interdependences between protein synthesis, cell size, and growth rate and propose that a theoretical inability to parallelize ribosomal synthesis places a firm limit on the achievable growth rate. A record of this paper's transparent peer review process is included in the supplemental information.

Identifying the particular transcription factors that maintain cell type in vitro is important for manipulating cell type. Identifying such transcription factors by their cell-type-specific expression or their involvement in developmental regulation has had limited success. We hypothesized that because cell type is often resilient to perturbations, the transcriptional response to perturbations would reveal identity-maintaining transcription factors. We developed perturbation panel profiling (P3) as a framework for perturbing cells across many conditions and measuring gene expression responsiveness transcriptome-wide. In human iPSC-derived cardiac myocytes, P3 showed that transcription factors important for cardiac myocyte differentiation and maintenance were among the most frequently upregulated (most responsive). We reasoned that one function of responsive genes may be to maintain cellular identity. We identified responsive transcription factors in fibroblasts using P3 and found that suppressing their expression led to enhanced reprogramming. We propose that responsiveness to perturbations is a property of transcription factors that help maintain cellular identity in vitro. A record of this paper's transparent peer review process is included in the supplemental information.

eIF4F plays diverse roles in human cancers, which complicate the development of an overarching understanding of its functional and regulatory impacts across tumor types. Typically, eIF4F drives initiation from the mRNA 5' end (cap) and is composed of eIF4G1, eIF4A1, and cap-binding eIF4E. Cap-independent initiation is possible without eIF4E, from internal ribosomal entry sites (IRESs). By analyzing large public datasets, we found that cancers selectively overexpress EIF4G1 more than EIF4E. That expression imbalance supports EIF4G1 as a prognostic indicator in patients with cancer. It also attenuates "housekeeping" pathways that are usually regulated in a tissue-specific manner via cap-dependent initiation in healthy tissues and reinforce regulation of cancer-preferred pathways in cap-independent contexts. Cap-independent initiation is mechanistically attributable to eIF4G1 hyperphosphorylation that promotes binding to eIF4A1 and reduced eIF4E availability. Collectively, these findings reveal a novel model of dysregulated eIF4F function and highlight the clinical relevance of cap-(in)dependent initiation in cancer.

Amyloid disorders such as Alzheimer's disease (AD) involve the aggregation of secreted proteins. However, it is largely unclear how secretory-pathway proteins contribute to amyloid formation. We developed a systems biology framework integrating expression data with protein-protein interaction networks to estimate a tissue's fitness for producing specific secreted proteins and analyzed the fitness of the secretory pathway of various brain regions and cell types for synthesizing the AD-associated amyloid precursor protein (APP). While key amyloidogenic pathway components were not differentially expressed in AD brains, we found Aβ deposition correlates with systemic down- and upregulation of the secretory-pathway components proximal to APP and amyloidogenic secretases, respectively, in AD. Our analyses suggest that perturbations from three AD risk loci cascade through the APP secretory-support network and into the endocytosis pathway, connecting amyloidogenesis to dysregulation of secretory-pathway components supporting APP and suggesting novel therapeutic targets for AD. A record of this paper's transparent peer review process is included in the supplemental information.

Comment on Cell Syst. 2021 Sep 22;12(9):900-906.e5.