Protocols, datasets, and software for engineering biology

Description

Published protocols, datasets, and software for engineering biology from the Cellular Engineering Group.

 

Protocols

• Romantseva E., Ross D., Alperovich N., Strychalski E., Automated DNA template preparation and quantitation methods, https://www.protocols.io, March 23, 2022, https://dx.doi.org/10.17504/protocols.io.j8nlkk8rdl5r/v1
• Romantseva E., Tack D., Alperovich N., Ross D., Strychalski E. (2022) Best Practices for DNA Template Preparation Toward Improved Reproducibility in Cell-Free Protein Production. In: Karim A.S., Jewett M.C. (eds) Cell-Free Gene Expression. Methods in Molecular Biology, vol 2433. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1998-8_1
• Alperovich N., Scott, B.M., Ross D. Automation protocol for high-efficiency and high-quality genomic DNA extraction from Saccharomyces cerevisiae. PLOS One (2023). https://doi.org/10.1371/journal.pone.0292401
• Ross D., Tonner P., Vasilyeva, O. Method for reproducible automated bacterial cell culture and measurement. Synthetic Biology (2022). https://doi.org/10.1093/synbio/ysac013
• Protocols related to large-scale sequence-function protein measurements in bacteria (Ross D. and Alperovich N.)
  • https://www.protocols.io/view/singleplex-assay-for-fitness-measurements-8epv5xye4g1b/v1
  • https://www.protocols.io/view/transcription-factor-binding-singleplex-assay-for-81wgbzq5qgpk/v3
  • https://www.protocols.io/view/pooled-growth-based-assays-5qpvokq1bl4o/v1
  • https://www.protocols.io/view/library-bottlenecking-protocols-x54v9227pl3e/v3
  • https://www.protocols.io/view/automated-bar-seq-library-preparation-and-pooling-3byl49qdjgo5/v3

Datasets

• LacI protein genotype-phenotype landscape data
  • Description: Large-scale sequence to function dataset for LacI variants
  • Dataset: https://data.nist.gov/od/id/mds2-2259
  • Relevant publication: https://www.embopress.org/doi/full/10.15252/msb.202010179
• Align-to-innovate protein sequence to function
  • Description: The Cellular Engineering Group is collaborating with Align to Innovate and other institutions to develop standardized methods for the collection, analysis, and reporting of large-scale, quantitative protein sequence–function datasets that will span multiple function types.
  • Datasets: https://alignbio.org/datasets-protein-to-function
     

Software

• Ligify
  • Description: Bacteria respond to chemical cues using protein transcription regulators. Ligify is a web-based search tool used to mine regulators responsive to user-defined metabolites. Ligify will also generate plasmids for testing putative regulators.
  • Website: https://ligify.streamlit.app/
  • Relevant publication: Ligify: Automated Genome Mining for Ligand-Inducible Transcription Factors
• LANTERN
  • Description: LANTERN (landscape interpretable nonparametric model) is a hierarchical Bayesian model that distills genotype–phenotype landscape (GPL) measurements into a low-dimensional feature space that represents the fundamental biological mechanisms of the system while also enabling straightforward, explainable predictions.
  • GitHub: https://github.com/usnistgov/lantern
  • Relevant Publication: Interpretable modeling of genotype–phenotype landscapes with state-of-the-art predictive power
• FlowGateNIST
  • Description: A Python package for automated analysis of bacterial flow cytometry data. The main components of FlowGateNIST perform automatic gating to differentiate between cells and background events and then between singlet and multiplet events. FlowGateNIST also includes a method for automatic calibration of fluorescence signals using fluorescence calibration beads.
  • GitHub: https://github.com/djross22/flowgatenist  
  • Relevant publication: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0250753
• ctRSD simulator
  • Description: A Python package for simulating the kinetics of cotranscriptionally encoded RNA strand displacement (ctRSD) circuits. The package also has a sequence compiler for generating DNA sequences for user-specified ctRSD components for experimental testing.
  • Documentation: https://ctrsd-simulator.readthedocs.io/en/latest/
  • GitHub: https://github.com/usnistgov/ctRSD-simulator/tree/main/ctRSD-simulator-2.0
  • Relevant publication: https://pubs.acs.org/doi/abs/10.1021/acssynbio.3c00079 

Created June 18, 2024, Updated May 15, 2026