Impact of Iron Deficiency on the Growth and Bioelectrical Profile of Different Gut Bacteria

ABSTRACT Scope: Iron deficiency (ID) is the most common nutritional deficiency worldwide, impacting gut bacteria's metabolism and cellular biochemistry, but its effects on the microbiota‐gut‐brain axis (MGB) are poorly understood. Early‐life ID‐related dysbiosis is linked to neurodevelopmental...

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Main Authors: Elisa Quarta, Marwane Bourqqia‐Ramzi, David Muñoz‐Rodriguez, María Teresa García‐Esteban, Antonio Murciano‐Cespedosa, Álvaro Mateos González, Francisco José Conejero‐Meca, Juan Lombardo‐Hernandez, Jesús Mansilla‐Guardiola, Simona Baroni, Simonetta Geninatti Crich, Stefano Geuna, Luca Munaron, Deborah Chiabrando, Celia Herrera‐Rincon
Format: Article
Language:English
Published: Wiley 2025-06-01
Series:MicrobiologyOpen
Subjects:
Online Access:https://doi.org/10.1002/mbo3.70015
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author Elisa Quarta
Marwane Bourqqia‐Ramzi
David Muñoz‐Rodriguez
María Teresa García‐Esteban
Antonio Murciano‐Cespedosa
Álvaro Mateos González
Francisco José Conejero‐Meca
Juan Lombardo‐Hernandez
Jesús Mansilla‐Guardiola
Simona Baroni
Simonetta Geninatti Crich
Stefano Geuna
Luca Munaron
Deborah Chiabrando
Celia Herrera‐Rincon
author_facet Elisa Quarta
Marwane Bourqqia‐Ramzi
David Muñoz‐Rodriguez
María Teresa García‐Esteban
Antonio Murciano‐Cespedosa
Álvaro Mateos González
Francisco José Conejero‐Meca
Juan Lombardo‐Hernandez
Jesús Mansilla‐Guardiola
Simona Baroni
Simonetta Geninatti Crich
Stefano Geuna
Luca Munaron
Deborah Chiabrando
Celia Herrera‐Rincon
author_sort Elisa Quarta
collection DOAJ
description ABSTRACT Scope: Iron deficiency (ID) is the most common nutritional deficiency worldwide, impacting gut bacteria's metabolism and cellular biochemistry, but its effects on the microbiota‐gut‐brain axis (MGB) are poorly understood. Early‐life ID‐related dysbiosis is linked to neurodevelopmental impairments like autism and attention deficit hyperactivity disorder. Studying ID's impact on bacterial signaling can guide interventions to target MGB in iron‐deficient populations. This study examined the responses of Escherichia coli (E. coli) and Limosilactobacillus reuteri (L. reuteri) to in‐vitro ID conditions using the iron chelator 2,2’‐Bipyridyl (BP). Methods and Results: We assessed and modeled their growth and cultivability and explored their bioelectric profiles using the voltage‐sensitive dye DiBAC4(3). Results showed differential responses: L. reuteri's growth and cultivability were unaffected by BP, while E. coli's growth rate and cultivability decreased under ID. Additionally, we created a deterministic mathematical model that demonstrated a decrease in the population's average reproduction rate in E. coli under ID. Only E. coli exhibited an altered bioelectric profile, marked by increased cell depolarization in ID conditions, which was largely rescued upon the addition of a saturating concentration of iron. Conclusion: These findings highlight specific bioelectrical responses in gut bacteria to ID. Understanding this variability is crucial for deciphering the microbiota's role in health and disease, particularly concerning nutritional iron imbalance and bacterial signaling in the MGB.
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spelling doaj-art-48a465f1f9b34064ac907fbc7f0d64d62025-08-20T03:30:04ZengWileyMicrobiologyOpen2045-88272025-06-01143n/an/a10.1002/mbo3.70015Impact of Iron Deficiency on the Growth and Bioelectrical Profile of Different Gut BacteriaElisa Quarta0Marwane Bourqqia‐Ramzi1David Muñoz‐Rodriguez2María Teresa García‐Esteban3Antonio Murciano‐Cespedosa4Álvaro Mateos González5Francisco José Conejero‐Meca6Juan Lombardo‐Hernandez7Jesús Mansilla‐Guardiola8Simona Baroni9Simonetta Geninatti Crich10Stefano Geuna11Luca Munaron12Deborah Chiabrando13Celia Herrera‐Rincon14Department of Biodiversity, Ecology & Evolution, and Modeling, Data Analysis & Computational Tools for Biology Research Group, Biomathematics Unit, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainDepartment of Biodiversity, Ecology & Evolution, and Modeling, Data Analysis & Computational Tools for Biology Research Group, Biomathematics Unit, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainDepartment of Biodiversity, Ecology & Evolution, and Modeling, Data Analysis & Computational Tools for Biology Research Group, Biomathematics Unit, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainDepartment of Genetic, Physiology and Microbiology, Unit of Microbiology, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainDepartment of Biodiversity, Ecology & Evolution, and Modeling, Data Analysis & Computational Tools for Biology Research Group, Biomathematics Unit, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainDepartment of Biodiversity, Ecology & Evolution, and Modeling, Data Analysis & Computational Tools for Biology Research Group, Biomathematics Unit, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainDepartment of Biodiversity, Ecology & Evolution, and Modeling, Data Analysis & Computational Tools for Biology Research Group, Biomathematics Unit, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainDepartment of Biodiversity, Ecology & Evolution, and Modeling, Data Analysis & Computational Tools for Biology Research Group, Biomathematics Unit, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainDepartment of Biodiversity, Ecology & Evolution, and Modeling, Data Analysis & Computational Tools for Biology Research Group, Biomathematics Unit, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainDepartment of Molecular Biotechnology and Health Sciences, Molecular Biotechnology Center “Guido Tarone” University of Torino Turin ItalyDepartment of Molecular Biotechnology and Health Sciences, Molecular Biotechnology Center “Guido Tarone” University of Torino Turin ItalyDepartment of Clinical and Biological Sciences University of Torino Turin ItalyDepartment of Life Science and Systems Biology (DBIOS) University of Torino Turin ItalyDepartment of Molecular Biotechnology and Health Sciences, Molecular Biotechnology Center “Guido Tarone” University of Torino Turin ItalyDepartment of Biodiversity, Ecology & Evolution, and Modeling, Data Analysis & Computational Tools for Biology Research Group, Biomathematics Unit, Faculty of Biological Sciences Complutense University of Madrid Madrid SpainABSTRACT Scope: Iron deficiency (ID) is the most common nutritional deficiency worldwide, impacting gut bacteria's metabolism and cellular biochemistry, but its effects on the microbiota‐gut‐brain axis (MGB) are poorly understood. Early‐life ID‐related dysbiosis is linked to neurodevelopmental impairments like autism and attention deficit hyperactivity disorder. Studying ID's impact on bacterial signaling can guide interventions to target MGB in iron‐deficient populations. This study examined the responses of Escherichia coli (E. coli) and Limosilactobacillus reuteri (L. reuteri) to in‐vitro ID conditions using the iron chelator 2,2’‐Bipyridyl (BP). Methods and Results: We assessed and modeled their growth and cultivability and explored their bioelectric profiles using the voltage‐sensitive dye DiBAC4(3). Results showed differential responses: L. reuteri's growth and cultivability were unaffected by BP, while E. coli's growth rate and cultivability decreased under ID. Additionally, we created a deterministic mathematical model that demonstrated a decrease in the population's average reproduction rate in E. coli under ID. Only E. coli exhibited an altered bioelectric profile, marked by increased cell depolarization in ID conditions, which was largely rescued upon the addition of a saturating concentration of iron. Conclusion: These findings highlight specific bioelectrical responses in gut bacteria to ID. Understanding this variability is crucial for deciphering the microbiota's role in health and disease, particularly concerning nutritional iron imbalance and bacterial signaling in the MGB.https://doi.org/10.1002/mbo3.70015bioelectricitymembrane potentialmicrobiota‐gut‐brain axisnutritional deficiency
spellingShingle Elisa Quarta
Marwane Bourqqia‐Ramzi
David Muñoz‐Rodriguez
María Teresa García‐Esteban
Antonio Murciano‐Cespedosa
Álvaro Mateos González
Francisco José Conejero‐Meca
Juan Lombardo‐Hernandez
Jesús Mansilla‐Guardiola
Simona Baroni
Simonetta Geninatti Crich
Stefano Geuna
Luca Munaron
Deborah Chiabrando
Celia Herrera‐Rincon
Impact of Iron Deficiency on the Growth and Bioelectrical Profile of Different Gut Bacteria
MicrobiologyOpen
bioelectricity
membrane potential
microbiota‐gut‐brain axis
nutritional deficiency
title Impact of Iron Deficiency on the Growth and Bioelectrical Profile of Different Gut Bacteria
title_full Impact of Iron Deficiency on the Growth and Bioelectrical Profile of Different Gut Bacteria
title_fullStr Impact of Iron Deficiency on the Growth and Bioelectrical Profile of Different Gut Bacteria
title_full_unstemmed Impact of Iron Deficiency on the Growth and Bioelectrical Profile of Different Gut Bacteria
title_short Impact of Iron Deficiency on the Growth and Bioelectrical Profile of Different Gut Bacteria
title_sort impact of iron deficiency on the growth and bioelectrical profile of different gut bacteria
topic bioelectricity
membrane potential
microbiota‐gut‐brain axis
nutritional deficiency
url https://doi.org/10.1002/mbo3.70015
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