About

This repository contains datasets from primary literature, as well as RegulonDB and EcoCyc, related to transcriptional regulation, proteome allocation, promoter engineering, genome streamlining, and more.

Usage

After cloning this repository, edit the relevant configuration paths in dnadesign or deg2tfbs so that they point here (i.e., to the local path where these data folders live).

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Data Sources by Category

Below is a breakdown of the major datasets included, grouped by broad themes. Each entry includes its folder name, title, DOI, thematic association (e.g., “stringent response,” “antibiotic stress response”), and comments (blurb on article findings or data types).

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Comparative Omics (RNA‐seq, Absolute Proteomics)

Most of these datasets compare omics readouts between a single “target” and “reference” condition, enabling the identification of up- and down-regulated genes. Some studies provide full raw data, which lets us reproduce results, apply custom thresholds, and isolate differentially expressed genes ourselves (as is done in deg2tfbs). Other articles do not share raw data but instead list up- and down-regulated genes directly, in which case we simply import those gene sets into deg2tfbs to identify the associated transcription factors and their DNA-binding sites. These binding sites can then later be used in dnadesign.

Diverse Media Conditions

• Mori et al.

  • Title: From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions
  • DOI: 10.15252/msb.20209536
  • Association: Proteomic allocation
  • Comments: Quantification of >2,000 proteins in E. coli across 60+ growth conditions (nutrient limitations, stress, etc.).
  • Format: Full source dataset available ✅

• Schmidt et al.

  • Title: The quantitative and condition-dependent Escherichia coli proteome
  • DOI: 10.1038/nbt.3418
  • Association: Ratio of TF proteins in given environments
  • Comments: Table S6 includes global absolute abundances, providing a resource for stoichiometric modeling of TF:DNA interactions.
  • Format: Full source dataset available ✅

The Stringent Response

• Durfee et al.

  • Title: Transcription profiling of the stringent response in Escherichia coli
  • DOI: 10.1128/JB.01092-07
  • Association: Stringent response
  • Comments: Conducted a transcriptomic study by inducing ppGpp accumulation; curated a list of differentially expressed genes within 5 minutes of stringent response onset.
  • Format: List of up- and down-regulated genes available.

• Fragoso‐Jimenez et al.

  • Title: Glucose consumption rate-dependent transcriptome profiling of Escherichia coli provides insight on performance as microbial factories
  • DOI: 10.1186/s12934-022-01909-y
  • Association: Carbon uptake / diauxic growth
  • Comments: RNA‐seq on E. coli with attenuated growth and substrate‐uptake rates; identifies negative correlations (genes up while uptake down).
  • Format: List of up- and down-regulated genes available.

• Franchini et al. (a), (b)

  • DOIs: 10.1371/journal.pone.0133793 and 10.1099/mic.0.28939-0
  • Association: Stringent response under glucose limitation
  • Comments: Transcriptomic studies in E. coli ΔrpoS and Δcya mutants under glucose‐limited continuous culture (Franchini a). Also a long‐term adaptation dataset (Franchini b).
  • Format: List of up- and down-regulated genes available.

• Gummesson et al.

  • Title: Valine‐Induced Isoleucine Starvation in E. coli Studied by Spike‐In Normalized RNA Sequencing
  • DOI: 10.3389/fgene.2020.00144
  • Association: Stringent response
  • Comments: PC1/PC2 scores for all genes and a list of 506 genes ≥2.0 fold up after 80 min of isoleucine starvation, plus top 100 most strongly activated genes.
  • Format: Full source dataset available ✅

• Houser et al.

  • Title: Controlled Measurement and Comparative Analysis of Cellular Components in E. coli
  • DOI: 10.1371/journal.pcbi.1004400
  • Association: Stringent response
  • Comments: Detailed time‐course characterization (two weeks) of E. coli growth and starvation. Supplemental Table 4 highlights RNAs significantly changing through starvation.
  • Format: List of up- and down-regulated genes available.

• Lu et al.

  • Title: Genome-wide transcriptional responses of Escherichia coli to glyphosate, a potent inhibitor of the shikimate pathway enzyme 5-enolpyruvylshikimate-3-phosphate synthase
  • DOI: 10.1039/C2MB25374G
  • Association: Stringent response
  • Comments: Transcriptome analysis of E. coli exposed to 200 mM glyphosate revealed differential expression of 1,040 genes (~23% of the genome), highlighting wide-reaching metabolic stress.
  • Format: List of up- and down-regulated genes available.

• Sanchez‐Vazquez et al.

  • Title: Genome-wide effects on Escherichia coli transcription from ppGpp binding to its two sites on RNA polymerase
  • DOI: 10.1073/pnas.1819682116
  • Association: Stringent response
  • Comments: RNA‐seq of E. coli with and without ppGpp‐binding sites on RNAP; extensive gene expression changes at 5–10 min.
  • Format: Full source dataset available ✅

• Traxler et al.

  • Title: Discretely calibrated regulatory loops controlled by ppGpp partition gene induction across the 'feast to famine' gradient in Escherichia coli
  • DOI: 10.1111/j.1365-2958.2010.07498.x
  • Association: Stringent response
  • Comments: Identified gene sets requiring ppGpp, Lrp, and RpoS for induction across the “feast to famine” gradient.

• Wu et al.

  • Title: Enzyme expression kinetics by Escherichia coli during transition from rich to minimal media depends on proteome reserves
  • DOI: 10.1038/s41564-022-01310-w
  • Association: Nutrient shift protein abundances
  • Comments: Proteome allocation in rich vs. minimal media, plus transitions. Supplementary Table 9 has proteomic fractions.
  • Format: Full source dataset available ✅

• Zhu et al.

  • Title: Stringent response ensures the timely adaptation of bacterial growth to nutrient downshift
  • DOI: 10.1038/s41467-023-36254-0
  • Association: Stringent response
  • Comments: Proteomic profiling of >2500 proteins during nutrient downshift in wild‐type and relA‐deficient strains.
  • Format: Full source dataset available ✅

Metabolic Burden

• Ceroni et al.

  • Title: Burden‐driven feedback control of gene expression
  • DOI: 10.1038/nmeth.4635
  • Association: Metabolic burden
  • Comments: RNA‐seq plus in vivo assays identify major transcriptional changes when strong synthetic constructs are over‐expressed.
  • Format: Full source dataset available ✅

• Rajacharya et al.

  • Title: Proteomics and metabolic burden analysis to understand the impact of recombinant protein production in E. coli
  • DOI: 10.1038/s41598-024-63148-y
  • Association: Metabolic burden
  • Comments: Investigated wild type vs. recombinant strains (inducing recombinant protein acyl-ACP reductase at various time points) via proteomics to track expression burden.
  • Format: Full source dataset available ✅

Membrane Stress and Fatty Acid Production

• Emani et al.

  • Title: Periplasmic stress contributes to a trade-off between protein secretion and cell growth in Escherichia coli Nissle 1917
  • DOI: 10.1093/synbio/ysad013
  • Association: Protein secretion
  • Comments: RNA‐seq used to probe growth–secretion trade‐offs in E. coli Nissle 1917 secreting sfGFP via the curli system.
  • Format: Partial source dataset available.

• Vazulka et al.

  • Title: RNA-seq reveals multifaceted gene expression response to Fab production in Escherichia coli fed-batch processes with particular focus on ribosome stalling
  • DOI: 10.1186/s12934-023-02278-w
  • Association: Fab production
  • Comments: Characterized the gene expression response in E. coli BL21(DE3) and HMS174(DE3) to periplasmic Fab expression via fed-batch RNA‐seq.
  • Format: List of up- and down-regulated genes available.

Antibiotic Stress

• Bie et al.

  • Title: Comparative Analysis of Transcriptomic Response of Escherichia coli K-12 MG1655 to Nine Representative Classes of Antibiotics
  • DOI: 10.1128/spectrum.00317-23
  • Association: Antibiotic response
  • Comments: Performed transcriptomic analysis on how E. coli responds to nine representative classes of antibiotics (tetracycline, mitomycin C, imipenem, ceftazidime, kanamycin, ciprofloxacin, polymyxin E, erythromycin, and chloramphenicol).
  • Format: Full source dataset available ✅

• Deter et al.

  • Title: Antibiotic tolerance is associated with a broad and complex transcriptional response in E. coli
  • DOI: 10.1038/s41598-021-85509-7
  • Association: Ampicillin resistance
  • Comments: Generated RNA-seq data on both antibiotic-treated and -untreated populations emerging from stationary phase.
  • Format: Full source dataset available ✅

• Radzikowski et al.

  • Title: Bacterial persistence is an active σS stress response to metabolic flux limitation
  • DOI: 10.15252/msb.20166998
  • Association: Stringent response
  • Comments: Developed and verified a model linking metabolic flux collapse to E. coli persistence under severe stress.
  • Format: Full source dataset available ✅

Heat Shock Response

• Kim et al.

  • Title: Heat-responsive and time-resolved transcriptome and metabolome analyses of Escherichia coli uncover thermo-tolerant mechanisms
  • DOI: 10.1038/s41598-020-74606-8
  • Association: Heat shock response
  • Comments: Applied RNA‐seq to capture early, middle, and late stages of heat stress (2 min–40 h), illuminating initiation, adaptation, and phenotypic plasticity phases in E. coli.
  • Format: Full source dataset available ✅

• Zhang et al.

  • Title: Heat-Shock Response Transcriptional Program Enables High-Yield and High-Quality Recombinant Protein Production in Escherichia coli
  • DOI: 10.1021/cb5004477
  • Association: Heat shock response
  • Comments: Demonstrated that a σ^32‐I54N HSR-like reprogrammed proteostasis network can boost soluble, folded, and functional recombinant proteins
  • Format: List of up-regulated genes (no down-regulated) available.

Phage Shock Response

• Jovanovic et al.

  • Title: Induction and Function of the Phage Shock Protein Extracytoplasmic Stress Response in Escherichia coli

  • DOI: 10.1074/jbc.M602323200

  • Association: Phage shock response

  • Comments: Generated a microarray dataset comparing E. coli strains with and without Psp-inducing protein IV secretin stress.

  • The module identifies up- and down-regulated genes using IQR-based outlier detection applied to the log 'Fold regulation' distribution from a microarray dataset.

  • Format: List of up- and down-regulated genes available.

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PRECISE‐2K (High‐Coverage RNA‐seq Compendium)

• Lamoureux et al.
  • Title: PRECISE 2.0 - an expanded high-quality RNA-seq compendium for Escherichia coli K-12 reveals high-resolution transcriptional regulatory structure
  • DOI: 10.1101/2021.04.08.439047
  • Association: Independent component analysis
  • Comments: A set of 278 standardized RNA‐seq datasets for E. coli K‐12 MG1655; used ICA to define 218 iModulons describing global regulatory structure.

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Genome Streamlining & Reduced‐Genome Strains

• Baumgart et al.

  • Title: Corynebacterium glutamicum Chassis C1 Building and Testing a Novel Platform Host for Synthetic Biology and Industrial Biotechnology
  • DOI: 10.1021/acssynbio.7b00261
  • Association: Genome streamlining
  • Comments: Created 26 genome‐reduced C. glutamicum strains with minimal fitness costs.

• Lastiri‐Pancardo et al.

  • Title: A quantitative method for proteome reallocation using minimal regulatory interventions
  • DOI: 10.1038/s41589-020-0593-y
  • Association: Proteome allocation
  • Comments: Designed ReProMin to remove TFs in E. coli that maximizes release of resources for cell growth or synthetic usage.

• Loffler et al.

  • Title: Engineering E. coli for large-scale production - Strategies considering ATP expenses and transcriptional responses
  • DOI: 10.1016/j.ymben.2016.06.008
  • Association: Cell maintenance costs
  • Comments: Identified top 20 energy‐consuming genes during large‐scale production; relevant to stringent response economics.

• Posfai et al.

  • Title: Emergent properties of reduced‐genome Escherichia coli
  • DOI: 10.1126/science.1126439
  • Association: Genome streamlining
  • Comments: Reduced the E. coli genome by ~20%; listed all deleted genes in strain MGS43.

• Ziegler et al.

  • Title: Transcriptional profiling of the stringent response mutant strain E. coli SR reveals enhanced robustness to large-scale conditions
  • DOI: 10.1016/j.ymben.2021.05.011
  • Association: Genome streamlining
  • Comments: Provided list of genes deleted in strain RM214, which showed a lower maintenance coefficient under simulated large‐scale conditions.

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Promoter/Regulatory Element Datasets

• EcoCyc data
  In this repository, EcoCyc‐derived gene annotations, regulatory interactions, and functional groupings are stored for integration with deg2tfbs and dnadesign.

• RegulonDB data

  • Promoter datasets: Promoters curated from RegulonDB, releases 11 and 13.
  • Binding sites datasets: TF binding sites from ChIP‐seq/footprinting.
  • High‐throughput experimental datasets: Additional promoter characterization datasets.

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Promoter Engineering

• Hernandez et al.

  • Title: PromoterLCNN: A Light CNN-Based Promoter Prediction and Classification Model
  • DOI: 10.3390/genes13071126
  • Association: Promoter prediction
  • Comments: Built a multiclass CNN for promoter identification/classification using a RegulonDB v9.3 dataset.

• Hossain et al.

  • Title: Automated design of thousands of nonrepetitive parts for engineering stable genetic systems
  • DOI: 10.1038/s41587-020-0584-2
  • Association: Promoter characterization
  • Comments: Created/characterized 4,350 E. coli promoters and 1,722 yeast promoters, achieving large dynamic range.

• Johns et al.

  • Title: Metagenomic mining of regulatory elements enables programmable species-selective gene expression
  • DOI: 10.1038/nmeth.4633
  • Association: Promoter prediction
  • Comments: Large‐scale analysis of diverse bacterial regulatory sequences for species‐selective gene expression.

• Kosuri et al.

  • Title: Composability of regulatory sequences controlling transcription and translation in Escherichia coli
  • DOI: 10.1073/pnas.1301301110
  • Association: Promoter engineering
  • Comments: Synthesized 12,563 combinations of common promoters and ribosome binding sites and simultaneously measured DNA, RNA, and protein levels from the entire library.

• LaFleur et al.

  • Title: Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria
  • DOI: 10.1038/s41467-022-32829-5
  • Association: Promoter characterization
  • Comments: Combined high‐throughput assays, biophysical models, and machine learning to design 34k+ promoters.

• Sun Yim et al.

  • Title: Multiplex transcriptional characterizations across diverse bacterial species using cell-free systems
  • DOI: 10.15252/msb.20198875
  • Association: Promoter prediction
  • Comments: Used active lysates from 10 bacterial species to measure transcription activities of thousands of regulatory sequences.

• Thomason et al.

  • Title: Global Transcriptional Start Site Mapping Using Differential RNA Sequencing Reveals Novel Antisense RNAs in Escherichia coli
  • DOI: 10.1128/JB.02096-14
  • Association: Transcription start site mapping
  • Comments: dRNA‐seq approach to distinguish primary vs. processed transcripts, with an automated TSS‐calling algorithm.

• Urtecho et al.

  • Title: Systematic Dissection of Sequence Elements Controlling σ70 Promoters Using a Genomically Encoded Multiplexed Reporter Assay in Escherichia coli
  • DOI: 10.1021/acs.biochem.7b01069
  • Association: Promoter characterization
  • Comments: A 10,898‐variant library dissecting −35, −10, UP elements, and spacers to evaluate σ70‐dependent expression.

• Xiaowo et al.

  • Title: Systematic representation and optimization enable the inverse design of cross-species regulatory sequences in bacteria
  • DOI: 10.1038/s41467-025-57031-1
  • Association: Promoter characterization
  • Comments: Generated 24,000 synthetic regulatory elements and characterized them in vivo in E. coli and P. aeruginosa as part of develop their DeepCROSS model.

• Yu et al.

  • Title: Multiplexed characterization of rationally designed promoter architectures deconstructs combinatorial logic for IPTG-inducible systems
  • DOI: 10.1038/s41467-020-20094-3
  • Association: Promoter characterization
  • Comments: Profiled expression of 8269 IPTG‐inducible promoters that vary RNAP and LacI‐binding sites.

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Other Curated Literature

• Baba et al.

  • Title: Construction of Escherichia coli K‐12 in‐frame, single‐gene knockout mutants: The Keio collection
  • DOI: 10.1038/msb4100050
  • Association: Keio collection
  • Comments: Systematic single‐gene deletions in E. coli K‐12; standard for genetic knockouts.

• Freddolino et al.

  • Title: Dynamic landscape of protein occupancy across the Escherichia coli chromosome
  • DOI: 10.1371/journal.pbio.3001306
  • Association: Protein occupancy on chromosome
  • Comments: Parallel monitoring of DNA‐binding protein occupancy states under various genetic and environmental perturbations.

• Gao et al.

  • Title: A balancing act in transcription regulation by response regulators titration of transcription factor activity by decoy DNA binding sites
  • DOI: 10.1093/nar/gkab935
  • Association: TF protein/TFBS ratio
  • Comments: Computed TF/TFBS ratios in 19 growth conditions, highlighting potential “decoy” DNA effects.

• Kumar et al.

  • Title: Amino acid supplementation for enhancing recombinant protein production in E. coli
  • DOI: 10.1002/bit.27371
  • Association: Universal stress proteins
  • Comments: Discusses the accumulation of universal stress proteins in E. coli when encountering any growth arrest.

• McKee et al.

  • Title: Manipulation of the carbon storage regulator system for metabolite remodeling and biofuel production in Escherichia coli
  • DOI: 10.1186/1475-2859-11-79
  • Association: CsrA‐regulated genes
  • Comments: Generated hundreds of predicted CsrA binding sites from shotgun proteomics.

• Peebo et al.

  • Title: Proteome reallocation in Escherichia coli with increasing specific growth rate
  • DOI: 10.1039/C4MB00721B
  • Association: Proteomic allocation
  • Comments: Covariance analysis between protein‐expression costs and growth rate, identifying which proteins have highest “synthesis priority.”
  • Format: Full source dataset available ✅

• Schink et al.

  • Title: Analysis of proteome adaptation reveals a key role of the bacterial envelope in starvation survival
  • DOI: 10.15252/msb.202211160
  • Association: Maintenance rate & bacterial envelope
  • Comments: Trade‐offs between growth and survival to identify proteins correlated with E. coli death rates.
  • Format: Full source dataset available ✅

• Youssef et al.

  • Title: Dynamic remodeling of Escherichia coli interactome in response to environmental perturbations
  • DOI: 10.1002/pmic.202200404
  • Association: Protein complex interaction remodeling
  • Comments: Used co‐fractionation mass spectrometry across ten conditions to quantify ~2000 protein–protein interactions.

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Notes on Folder Organization

Each dataset above typically corresponds to its own folder (or subfolder), named in a way that reflects the first author, short title, or reference year. Inside each folder, you may find:

• Raw or processed CSV/TSV files
• Supplemental spreadsheets
• Scripts or metadata describing how the data were sourced or filtered

When using them in dnadesign or deg2tfbs, confirm that:

1. The folder structure aligns with your config file(s).
2. You cite the appropriate DOIs and references if publishing results derived from these datasets.

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Last updated: 2025-01-27 @e-south