AIMC Topic: Escherichia coli

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Extending visual range of bacteria with upconversion nanoparticles and constructing NIR-responsive bio-microrobots.

Journal of colloid and interface science
The motility of bacteria is crucial for navigating competitive environments and is closely linked to physiological activities essential for their survival, such as biofilm development. Precise regulation of bacterial motility enhances our understandi...

Bacteriophage-Activated DNAzyme Hydrogels Combined with Machine Learning Enable Point-of-Use Colorimetric Detection of Escherichia coli.

Advanced materials (Deerfield Beach, Fla.)
Developing cost-effective, consumer-accessible platforms for point-of-use environmental and clinical pathogen testing is a priority, to reduce reliance on laborious, time-consuming culturing approaches. Unfortunately, a system offering ultrasensitive...

Immunoinformatics investigation on pathogenic Escherichia coli proteome to develop an epitope-based peptide vaccine candidate.

Molecular diversity
Escherichia coli (E. coli), a gram-negative bacterium, quickly colonizes in the human gastrointestinal tract after birth and typically sustains a long-term, symbiotic relationship with the host. However, certain virulent strains of E. coli can cause ...

Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning.

Nature communications
mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from its sequence, due to the many coupled interactions that control degradation rate. Here, we carried ou...

Machine learning accelerates the discovery of epitope-based dual-bioactive peptides against skin infections.

International journal of antimicrobial agents
OBJECTIVES: Skin injuries and infections are an inevitable part of daily human life, particularly with chronic wounds, becoming an increasing socioeconomic burden. In treating skin infections and promoting wound healing, bioactive peptides may hold s...

Management of experimental workflows in robotic cultivation platforms.

SLAS technology
In the last decades, robotic cultivation facilities combined with automated execution of workflows have drastically increased the speed of research in biotechnology. In this work, we present the design and deployment of a digital infrastructure for r...

Multicellular artificial neural network-type architectures demonstrate computational problem solving.

Nature chemical biology
Here, we report a modular multicellular system created by mixing and matching discrete engineered bacterial cells. This system can be designed to solve multiple computational decision problems. The modular system is based on a set of engineered bacte...

Prediction of Solubility of Proteins in Escherichia coli Based on Functional and Structural Features Using Machine Learning Methods.

The protein journal
Protein solubility is a critical parameter that determines the stability, activity, and functionality of proteins, with broad and far-reaching implications in biotechnology and biochemistry. Accurate prediction and control of protein solubility are e...

Machine Learning-Driven Discovery and Evaluation of Antimicrobial Peptides from Mucus Proteome.

Marine drugs
Marine antimicrobial peptides (AMPs) represent a promising source for combating infections, especially against antibiotic-resistant pathogens and traditionally challenging infections. However, traditional drug discovery methods face challenges such a...

Deep Learning Powers Protein Identification from Precursor MS Information.

Journal of proteome research
Proteome analysis currently heavily relies on tandem mass spectrometry (MS/MS), which does not fully utilize MS1 features, as many precursors remain unselected for MS/MS fragmentation, especially in the cases of low abundance samples and wide abundan...