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Related Concept Videos

Urinary Tract Infection I: Introduction01:26

Urinary Tract Infection I: Introduction

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Urinary tract infections (UTIs) impact various parts of the urinary system, including the kidneys, ureters, bladder, and urethra. These infections are generally bacterial, with Escherichia coli being the most common causative agent, often originating from the gastrointestinal tract. However, other bacteria, such as Staphylococcus saprophyticus, Klebsiella pneumoniae, and Proteus mirabilis, are also known to cause UTIs. The type, location, and underlying complexity of the UTI guide both...
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Urinary Tract Infection II: Pathophysiology01:25

Urinary Tract Infection II: Pathophysiology

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The pathophysiology of urinary tract infections (UTIs) encompasses several progressive stages, beginning with bacterial colonization and culminating in potential systemic complications if untreated. UTIs are primarily initiated by bacteria, such as Escherichia coli, which often originate from the gastrointestinal tract and migrate to the urinary system through the periurethral area. This migration can occur via several routes, including improper hygiene practices, sexual activity, or...
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Urine Studies II: Urine Culture and Sensitivity Test01:26

Urine Studies II: Urine Culture and Sensitivity Test

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A urine culture and sensitivity test is a diagnostic procedure used to identify urinary tract bacterial infections and determine the most effective antibiotics for treatment. This test is generally preferred when a patient shows manifestations of a urinary tract infection, such as frequent or painful urination, cloudy or foul-smelling urine, or lower abdominal pain.Purpose of the TestThe primary goals of a urine culture and sensitivity test are to:Determine the specific bacteria causing the...
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Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Combined Effects of Drugs: Synergism01:27

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Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
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Isolation of Single Intracellular Bacterial Communities Generated from a Murine Model of Urinary Tract Infection for Downstream Single-cell Analysis
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Using Functional Annotations to Study Pairwise Interactions in Urinary Tract Infection Communities.

Elena G Lara1, Isabelle van der Windt2, Douwe Molenaar1

  • 1Systems Biology Lab, AIMMS, Vrije Universiteit, 1081 HZ Amsterdam, The Netherlands.

Genes
|August 27, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a computational method to predict microbial interactions in urinary tract infections (UTIs). The approach identified that Enterococcus spp. growth is enhanced by other UTI microbes, confirmed by folic acid supplementation.

Keywords:
gene annotationmicrobial communitymicrobial interactionurinary tract infection

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Area of Science:

  • Microbiology
  • Computational Biology
  • Bioinformatics

Background:

  • Microbial community behavior is influenced by environmental factors and member interactions.
  • Urinary tract infection (UTI) microbial communities exhibit complex interdependencies.
  • Understanding these interactions is crucial for explaining microbial growth dynamics.

Purpose of the Study:

  • To develop a computational approach for predicting metabolic interactions between microbial pairs in UTI communities.
  • To identify metabolic pathways that correlate with observed pairwise growth effects.
  • To provide a rapid in silico screening tool for microbial community interactions.

Main Methods:

  • Utilized indices of complementarity and competition based on metabolic gene annotation.
  • Applied the method to 66 genomes from 6 genera commonly found in UTI communities.
  • Correlated computational predictions with experimentally derived growth data.

Main Results:

  • Identified metabolic pathways showing high correlation between complementarity indices and growth data.
  • Found that Enterococcus spp. metabolism is significantly complemented by other UTI community members.
  • Experimental folic acid supplementation validated predicted interactions, increasing Enterococcus population density.

Conclusions:

  • The developed computational method offers a rapid in silico screening for predicting metabolic interactions in microbial communities.
  • Enterococcus spp. growth in UTIs can be potentially enhanced by metabolites from other community members.
  • This approach aids in understanding the complex ecological dynamics within UTI microbiomes.