Recombinant Shigella dysenteriae serotype 1 UPF0060 membrane protein YnfA (ynfA)

What is the YnfA protein in Shigella and what is its functional significance?

YnfA is a small integral membrane protein that functions as an efflux transporter belonging to the Small Multidrug Resistance (SMR) family. In Shigella species, this protein plays a critical role in antimicrobial resistance by extruding various antimicrobial compounds from the bacterial cell . Studies have demonstrated that YnfA is approximately 11.9 kDa in size and consists of 108 amino acids, forming a structure with four α-transmembrane helices, which is characteristic of the SMR superfamily members .

The functional significance of YnfA has been established through genetic disruption studies, which demonstrate that mutant Shigella strains lacking functional YnfA show increased susceptibility to certain antimicrobial compounds . Specifically, the loss of YnfA significantly affects the bacteria's ability to transport compounds such as ethidium bromide and acriflavine, indicating its role in exporting these substances from the cell .

How is the structural organization of YnfA characterized, and what techniques have been used for its analysis?

YnfA is characterized as a small integral inner membrane protein with four α-transmembrane helices, a structural feature that is consistent with other members of the SMR superfamily . This structural characterization has been achieved through multiple complementary approaches:

• Computational prediction tools such as TMHMM and TMpred have been employed to predict the transmembrane topology of YnfA .

• Multiple sequence alignment using tools like Clustal-Omega has helped identify conserved motifs that are essential for the proper functioning of the transporter .

• Three-dimensional structural predictions have been generated using I-TASSER (Iterative Threading ASSEmbly Refinement) and verified using the AlphaFold protein structure database .

The predicted 3D structure of YnfA has been found to be similar to the known structure of EmrE, another well-characterized SMR family transporter, with coverage of 0.95 and a Normalized Z-score of 2.15, indicating good alignment and threading score .

How does YnfA in Shigella relate to homologs in other bacteria?

YnfA is relatively widespread among Gram-negative bacteria, with homologs identified in various pathogenic species . Phylogenetic analysis using the MEGA software and the maximum composite likelihood method has demonstrated that YnfA represents a distinct subfamily within the SMR family of transporters .

Multiple sequence alignment of YnfA homologs from different Gram-negative bacteria reveals high conservation of amino acid residues, suggesting functional importance across species . Specifically, YnfA from Shigella flexneri shows close similarity to homologs found in Escherichia coli, Salmonella, Citrobacter, Klebsiella, and Yersinia species . This conservation suggests that findings regarding YnfA function in Shigella may be applicable to understanding similar transporters in related pathogens.

What specific amino acid residues are critical for YnfA function, and how do mutations affect antimicrobial resistance profiles?

Research has identified critical conserved motifs in YnfA that are essential for its proper functioning . Mutational studies focusing on these conserved amino acid residues have demonstrated significant alterations in both resistance profiles and efflux activity of the YnfA transporter .

While specific details about every critical residue are not provided in the search results, the research approach has involved:

These studies provide crucial information about structure-function relationships in YnfA and may identify potential targets for inhibitor development to combat antimicrobial resistance .

How does the 3D structure of YnfA inform our understanding of its transport mechanism?

The three-dimensional structure of YnfA provides significant insights into its transport mechanism. Computational modeling using I-TASSER has used the crystal structure of the EmrE transporter (PDB ID: 3b61) from E. coli as a template for predicting YnfA's structure . This modeling revealed that:

• YnfA possesses four alpha-transmembrane helices, consistent with the structural organization of other SMR family transporters .

• The threading alignment between YnfA and EmrE shows good coverage (0.95) and alignment score (Normalized Z-score of 2.15) .

• The AlphaFold protein structure database confirms the four alpha-transmembrane helical model predicted by I-TASSER .

This structural similarity to EmrE suggests that YnfA likely functions through a similar transport mechanism, which may involve the binding of substrates within a hydrophobic pocket formed by the transmembrane helices and subsequent conformational changes that facilitate substrate extrusion from the cell.

What experimental approaches have been most effective in characterizing YnfA's contribution to antimicrobial resistance?

Several complementary experimental approaches have proven effective in characterizing YnfA's role in antimicrobial resistance:

These approaches collectively provide a comprehensive understanding of YnfA's function, from its molecular structure to its role in whole-cell antimicrobial resistance. The combination of genetic, biochemical, and computational techniques has been particularly powerful in elucidating the characteristics of this previously uncharacterized transporter .

What are effective genetic approaches for studying YnfA function in Shigella?

Effective genetic approaches for studying YnfA function include:

• Gene Disruption/Knockout Studies: Creating YnfA-deficient mutants has been instrumental in demonstrating the transporter's role in antimicrobial resistance. When the YnfA gene is disrupted, Shigella strains show increased susceptibility to certain antimicrobial compounds and reduced transport activity against substrates like ethidium bromide and acriflavine .

• Site-Directed Mutagenesis: This approach has been used to systematically modify conserved amino acid residues in YnfA to assess their functional importance. By mutating specific residues and then evaluating changes in resistance profiles and transport activity, researchers have identified amino acids that are critical for YnfA function .

• Complementation Studies: Reintroducing functional YnfA into knockout strains can confirm that observed phenotypic changes are specifically due to the absence of YnfA rather than secondary effects. This approach helps establish a direct causal relationship between YnfA and antimicrobial resistance phenotypes.

• Dual Gene Disruption: Studies have also assessed the effect of disrupting both YnfA and other SMR family efflux pumps simultaneously, providing insights into potential functional redundancy or synergy between different transporters in Shigella .

When designing such genetic studies, it is important to include appropriate controls and to verify the genetic modifications through sequencing to ensure accurate interpretation of results.

What computational tools and approaches are most useful for analyzing YnfA structure and function?

Several computational tools have proven valuable for analyzing YnfA structure and function:

When employing these tools, researchers should:

• Use multiple complementary approaches to increase confidence in predictions

• Validate computational predictions with experimental data when possible

• Consider the limitations of each tool and the confidence scores provided

• Integrate findings across different tools to develop a comprehensive understanding of the protein

This integrated computational approach has been effective in characterizing YnfA structure and providing insights into its function even before detailed experimental characterization .

How can researchers effectively measure YnfA transport activity in vitro and in vivo?

Measuring YnfA transport activity requires specialized approaches for both in vitro and in vivo assessments:

In vivo transport assays:

• Fluorescent substrate accumulation: Using fluorescent substrates like ethidium bromide or acriflavine and measuring their intracellular accumulation in wild-type versus YnfA-deficient strains. Lower accumulation in wild-type cells indicates active efflux .

• Antimicrobial susceptibility testing: Comparing minimum inhibitory concentrations (MICs) of various antimicrobial compounds between wild-type and YnfA mutant strains to identify specific substrates of the transporter .

• Real-time efflux assays: Loading cells with fluorescent substrates and then monitoring the rate of efflux over time in the presence of an energy source.

In vitro transport assays:

• Reconstituted proteoliposome assays: Purified YnfA protein can be reconstituted into liposomes, and transport activity can be measured by monitoring substrate movement across the liposomal membrane.

• Membrane vesicle transport: Inside-out membrane vesicles prepared from cells expressing YnfA can be used to measure transport activity in a more native membrane environment.

For both approaches, it is essential to include appropriate controls, such as:

• Energy-depleted cells or systems (negative control)

• Known efflux pump inhibitors to confirm specificity

• Cells expressing well-characterized transporters (positive control)

These methodologies have successfully demonstrated YnfA's role in transporting compounds like ethidium bromide and acriflavine, confirming its function as an efflux transporter .

How should researchers interpret changes in antimicrobial susceptibility when YnfA is disrupted or mutated?

When analyzing antimicrobial susceptibility changes in YnfA-disrupted or mutated strains, researchers should consider the following factors:

A comprehensive interpretation should integrate these different aspects to develop a nuanced understanding of YnfA's specific role in antimicrobial resistance.

What are the best practices for presenting YnfA structural and functional data in publications?

Effective presentation of YnfA structural and functional data should follow these best practices:

When following these guidelines, researchers can effectively communicate complex information about YnfA structure and function in a manner that enhances understanding and reproducibility.

What are the current knowledge gaps regarding YnfA function in Shigella dysenteriae?

Despite progress in understanding YnfA, several knowledge gaps remain:

Addressing these knowledge gaps would provide a more comprehensive understanding of YnfA's role in antimicrobial resistance in Shigella dysenteriae.

How might YnfA be targeted for antimicrobial drug development?

YnfA presents several potential opportunities for antimicrobial drug development strategies:

• Direct efflux pump inhibitors: Compounds that specifically bind to and inhibit YnfA function could be developed based on the structural insights gained from computational modeling and mutational studies. These inhibitors could work synergistically with existing antibiotics by preventing their efflux .

• Competitive substrates: Designing molecules that are preferentially transported by YnfA but lack antimicrobial activity could competitively inhibit the efflux of actual antibiotics, effectively increasing their intracellular concentration.

• Targeting conserved motifs: The identified conserved motifs in YnfA represent potential targets for inhibitor design, particularly if they are essential for transport function but distinct from motifs in human transporters .

• Expression inhibitors: Compounds that downregulate YnfA expression could potentially increase bacterial susceptibility to certain antibiotics.

• Structure-based drug design: The predicted 3D structure of YnfA, particularly its similarity to EmrE, provides a foundation for structure-based approaches to inhibitor design .

The development of such inhibitors could help combat antimicrobial resistance in Shigella and potentially in other Gram-negative pathogens with YnfA homologs, offering a new strategy to extend the useful life of existing antibiotics.

What emerging technologies might advance our understanding of YnfA and related efflux transporters?

Several emerging technologies hold promise for advancing YnfA research:

• Cryo-electron microscopy: This technology could provide high-resolution structural information about YnfA in different conformational states during the transport cycle, offering insights beyond computational predictions.

• Single-molecule fluorescence studies: These techniques could track the dynamic conformational changes of YnfA during substrate binding and transport, revealing the mechanistic details of efflux.

• CRISPR-Cas9 genome editing: More precise genetic modifications could help dissect the specific contributions of YnfA in complex genetic backgrounds and in clinical isolates.

• Microfluidic devices: These systems could enable real-time monitoring of efflux activity in living bacterial cells under various conditions and in response to potential inhibitors.

• Molecular dynamics simulations: Advanced computational approaches could model the interaction between YnfA and various substrates or inhibitors, guiding rational drug design.

• Artificial intelligence for drug discovery: Machine learning approaches could identify novel inhibitors by analyzing the relationship between chemical structures and their ability to inhibit YnfA function.

Integration of these technologies would provide a more comprehensive understanding of YnfA function and potentially accelerate the development of strategies to combat YnfA-mediated antimicrobial resistance in Shigella dysenteriae and related pathogens.