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Global Regulatory Systems

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Global regulatory systems in bacteria enable rapid and coordinated responses to environmental changes by integrating sensory inputs with gene expression, ensuring efficient adaptation to fluctuating conditions. Key global regulatory mechanisms include regulons, two-component systems, sigma factors, and secondary messengers.Regulons and Global RegulatorsA regulon is a collection of genes and operons controlled by a common global regulator. These regulators enable bacteria to prioritize resource...
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Transcription01:10

Transcription

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Overview
Transcription is the process of synthesizing RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in the proper synthesis of messenger RNA (mRNA). Regulation of transcription is responsible for the differentiation of all the different types of cells and often for the proper cellular response to environmental signals.
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Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...
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Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
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Bacterial growth is closely tied to nutrient availability, with cells proliferating exponentially under favorable conditions and entering a stationary phase when resources become scarce. This transition is mediated by a regulatory mechanism known as the stringent response, which allows bacteria to adapt to nutrient deprivation by modulating gene expression and metabolic activity.During nutrient scarcity, intracellular amino acid levels decline. It results in the accumulation of uncharged tRNAs...
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Quorum sensing is a mechanism of bacterial communication that enables coordinated gene expression in response to changes in population density. This facilitates collective behaviors that enhance survival, resource acquisition, and ecological adaptation. This process relies on small signaling molecules called autoinducers that accumulate as bacterial populations grow. When a critical threshold concentration of autoinducers is reached, bacterial cells collectively modify gene expression,...
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Genome-scale transcriptional dynamics and environmental biosensing.

Garrett Graham1, Nicholas Csicsery1, Elizabeth Stasiowski1

  • 1Department of Bioengineering, University of California San Diego, La Jolla, CA 92093.

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|January 25, 2020
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Summary

This study introduces the Dynomics platform for real-time monitoring of gene expression. Coupled with AI, it analyzes cellular responses and acts as a biosensor for environmental contaminants like heavy metals.

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E. coli transcriptomicsbiosensordynamicsexplainable AIhigh-throughput microfluidics

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Area of Science:

  • Molecular biology
  • Systems biology
  • Bioengineering

Background:

  • Cells utilize complex regulatory feedback for environmental response.
  • High-throughput temporal data collection and analysis are crucial for understanding cellular dynamics.
  • Existing technologies require advancement for real-time, large-scale transcriptional monitoring.

Purpose of the Study:

  • To develop a novel microfluidic platform for monitoring temporal gene expression.
  • To integrate deep neural networks (DNN) and explainable artificial intelligence (XAI) for analyzing transcriptional data.
  • To demonstrate the platform's capability as a field-deployable real-time biosensor.

Main Methods:

  • Development of the Dynomics microfluidic platform to monitor over 2,000 gene promoters.
  • Application of DNN and XAI algorithms to analyze genome-scale transcriptional data.
  • Testing the platform's biosensing capabilities using *Escherichia coli* promoter profiles.

Main Results:

  • The Dynomics platform successfully monitored temporal gene expression from over 2,000 promoters.
  • Machine learning algorithms identified patterns and key genes in transcriptional data.
  • The platform accurately predicted heavy metal presence in environmental samples as a real-time biosensor.

Conclusions:

  • The Dynomics platform offers a powerful tool for high-throughput temporal gene expression analysis.
  • Integration with AI enables deep insights into cellular regulatory networks.
  • The platform demonstrates significant potential for environmental monitoring and biosensing applications.