Influences of Adhesion Variability on the “Living” Dynamics of Filamentous Bacteria in Microfluidic Channels

Jahnke, Justin P.; Terrell, Jessica L.; Smith, Austin M.; Cheng, Xuanhong; Stratis‐Cullum, Dimitra N.

doi:10.3390/molecules21080985

Cited by 10 publications

(12 citation statements)

References 76 publications

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“…Filament formation by bacteria has been shown to increase surface attachment and exhibit different biofilm structure . Their dynamics also respond to the sheer force of fluid with which they are in contact . Our results indicate that the growth of filaments in the formation of elongation is promoted by attachment to a surface.…”

Section: Resultsmentioning

confidence: 66%

“…Few investigations have studied filamentous bacteria's attachment to surfaces . Filament formation by bacteria has been shown to increase surface attachment and exhibit different biofilm structure .…”

Section: Resultsmentioning

confidence: 99%

“…Among other effects, antibiotics can cause bacteria to form filaments, consisting of living bacteria . The impact of filamentous bacteria on biofilm formation is not clear.…”

Section: Introductionmentioning

confidence: 99%

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Cell‐Wall‐Targeting Antibiotics Cause Lag‐Phase Bacteria to Form Surface‐Mediated Filaments Promoting the Formation of Biofilms and Aggregates

et al. 2019

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Antibiotics are known to promote bacterial formation of enhanced biofilms, the mechanism of which is not well understood. Here, using biolayer interferometry, we have shown that bacterial cultures containing antibiotics that target cell walls cause biomass deposition on surfaces over time with a linear profile rather than the Langmuir‐like profiles exhibited by bacterial adherence in the absence of antibiotics. We observed about three times the initial rate and 12 times the final biomass deposition on surfaces for cultures containing carbenicillin than without. Unexpectedly, in the presence of antibiotics, the rate of biomass deposition inversely correlated with bacterial densities from different stages of a culture. Detailed studies revealed that carbenicillin caused faster growth of filaments that were seeded on surfaces from young bacteria (from lag phase) than those from high‐density fast‐growing bacteria, with rates of filament elongation of about 0.58 and 0.13 μm min−1, respectively. With surfaces that do not support bacterial adherence, few filaments were observed even in solution. These filaments aggregated in solution and formed increased amounts of biofilms on surfaces. These results reveal the lifestyle of antibiotic‐induced filamentous bacteria, as well as one way in which the antibiotics promote biofilm formation.

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Section: Resultsmentioning

confidence: 66%

Section: Resultsmentioning

confidence: 99%

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Cell‐Wall‐Targeting Antibiotics Cause Lag‐Phase Bacteria to Form Surface‐Mediated Filaments Promoting the Formation of Biofilms and Aggregates

et al. 2019

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“…if N → ∞, then , that is, is properly normalized. However, and while to the best of our knowledge a precise quantification is missing, the unconstrained growth of cells seems unrealistic and a maximal cutoff value for N constitutes a more reasonable hypothesis, that is, cells cannot grow indefinitely 39 , 40 . In that case we notice that , i.e.…”

Section: Resultsmentioning

confidence: 98%

A Markovian Approach towards Bacterial Size Control and Homeostasis in Anomalous Growth Processes

Chen

Baños²,

Buceta

2018

Sci Rep

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Regardless of the progress achieved during recent years, the mechanisms coupling growth and division to attain cell size homeostasis in bacterial populations are still not well understood. In particular, there is a gap of knowledge about the mechanisms controlling anomalous growth events that are ubiquitous even in wild-type phenotypes. Thus, when cells exceed the doubling size the divisome dynamics sets a characteristic length scale that suggests a sizer property. Yet, it has been recently shown that the size at birth and the size increment still satisfy an adder-like correlation. Herein we propose a Markov chain model, that we complement with computational and experimental approaches, to clarify this issue. In this context, we show that classifying cells as a function of the characteristic size set by the divisome dynamics provides a compelling framework to understand size convergence, growth, and division at the large length scale, including the adaptation to, and rescue from, filamentation processes. Our results reveal the independence of size homeostasis on the division pattern of long cells and help to reconcile sizer concepts at the single cell level with an adder-like behavior at a population level.

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“…In contrast to yeast display, bacterial display is faster due to the rapid (approximately 20 min 30 ) doubling time of Escherichia coli . The resulting peptide affinity reagents can be produced off-cell for use in a variety of sensing platforms 16 17 26 and have potential for use as living materials when displayed on-cell 2 31 32 . As compared to monoclonal antibodies for recognition of specific targets, peptides are much smaller and more flexible, and peptide display libraries can be easily manipulated at the DNA level to avoid specific amino acids, such as cysteine 33 .…”

Section: Introductionmentioning

confidence: 99%

Semi-automated Biopanning of Bacterial Display Libraries for Peptide Affinity Reagent Discovery and Analysis of Resulting Isolates

Sarkes

Jahnke

Stratis‐Cullum

2017

JoVE

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Biopanning bacterial display libraries is a proven technique for peptide affinity reagent discovery for recognition of both biotic and abiotic targets. Peptide affinity reagents can be used for similar applications to antibodies, including sensing and therapeutics, but are more robust and able to perform in more extreme environments. Specific enrichment of peptide capture agents to a protein target of interest is enhanced using semi-automated sorting methods which improve binding and wash steps and therefore decrease the occurrence of false positive binders. A semi-automated sorting method is described herein for use with a commercial automated magnetic-activated cell sorting device with an unconstrained bacterial display sorting library expressing random 15-mer peptides. With slight modifications, these methods are extendable to other automated devices, other sorting libraries, and other organisms. A primary goal of this work is to provide a comprehensive methodology and expound the thought process applied in analyzing and minimizing the resulting pool of candidates. These techniques include analysis of on-cell binding using fluorescence-activated cell sorting (FACS), to assess affinity and specificity during sorting and in comparing individual candidates, and the analysis of peptide sequences to identify trends and consensus sequences for understanding and potentially improving the affinity to and specificity for the target of interest.

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Influences of Adhesion Variability on the “Living” Dynamics of Filamentous Bacteria in Microfluidic Channels

Cited by 10 publications

References 76 publications

Cell‐Wall‐Targeting Antibiotics Cause Lag‐Phase Bacteria to Form Surface‐Mediated Filaments Promoting the Formation of Biofilms and Aggregates

Cell‐Wall‐Targeting Antibiotics Cause Lag‐Phase Bacteria to Form Surface‐Mediated Filaments Promoting the Formation of Biofilms and Aggregates

A Markovian Approach towards Bacterial Size Control and Homeostasis in Anomalous Growth Processes

Semi-automated Biopanning of Bacterial Display Libraries for Peptide Affinity Reagent Discovery and Analysis of Resulting Isolates

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