BNI4 Antibody

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Description

Structure and Function of BNI4

BNI4 is a 73-kDa protein that interacts with septin neck filaments and Skt5p to tether chitin synthase III (Chs3p) to the bud neck . It contains a RVXF motif near its C-terminus, enabling binding to the type 1 protein phosphatase Glc7 . This interaction is critical for asymmetric localization of Glc7 and chitin synthase III to the mother side of the bud neck, ensuring proper chitin ring deposition .

Key Features of BNI4 Antibody:

FeatureDescription
TargetBNI4 scaffold protein
ApplicationsImmunofluorescence, co-immunoprecipitation, FRET assays
LocalizationMother-side of bud neck in cycling cells; symmetric rings under stress

Role in Cell Wall Synthesis

BNI4 recruits Chs4 (catalytic subunit of chitin synthase III) to the bud neck via septin binding . Disruption of BNI4 function leads to:

  • Elongated buds due to defective chitin deposition .

  • Mislocalization of Chs4, impairing cell wall integrity .

Experimental Evidence:

  • FRET Assays: Confirmed Bni4-Glc7 interaction at the bud neck .

  • Time-Lapse Imaging: Bni4-GFP localizes to the mother side during bud emergence, transitioning to symmetric rings in arrested cells .

Localization Dynamics and Regulation

BNI4 exhibits dynamic localization patterns regulated by phosphorylation:

  1. Asymmetric Localization: Restricts to the mother side during bud growth .

  2. Symmetric Rings: Forms under energy depletion or cell cycle arrest (e.g., hsl1Δ mutants) .

  3. Phosphorylation: Pho85-kinase complexes (Pcl1/2-Pho85) phosphorylate Bni4, stabilizing its localization .

Stress-Induced Changes:

Stress ConditionLocalization Pattern
Energy DepletionSymmetric rings
Hydroxyurea TreatmentStabilizes Swe1 at the neck
glc7-129 MutantLoss of asymmetry

Applications in Research

The BNI4 Antibody is essential for:

  • Septin Dynamics: Tracking septin ring formation and disruptions .

  • Cell Cycle Studies: Monitoring morphogenesis checkpoints (e.g., Swe1 stabilization) .

  • Chitin Synthesis: Co-localization with Chs4 and Glc7 .

Methodologies:

  • Immunofluorescence: Visualizes Bni4 at the bud neck .

  • Co-IP/FRET: Confirms interactions with septins and Glc7 .

Clinical and Biotechnological Relevance

While BNI4 is yeast-specific, its study informs:

  • Fungal Pathogenesis: Analogous proteins in pathogenic fungi (e.g., Candida spp.) may regulate cell wall integrity .

  • Biotechnology: Insights into septin organization could optimize industrial yeast strains .

Product Specs

Buffer
Preservative: 0.03% Proclin 300
Constituents: 50% Glycerol, 0.01M Phosphate Buffered Saline (PBS), pH 7.4
Form
Liquid
Lead Time
Made-to-order (14-16 weeks)
Synonyms
BNI4 antibody; YNL233W antibody; N1146Protein BNI4 antibody
Target Names
BNI4
Uniprot No.

Q&A

What are broadly neutralizing antibodies (bNAbs) and how do they function in HIV research?

Broadly neutralizing antibodies (bNAbs) are specialized antibodies that can recognize and neutralize multiple variants of HIV by targeting relatively conserved regions of the viral envelope glycoprotein. Unlike conventional antibodies that may only recognize specific strains, bNAbs can neutralize diverse viral isolates, making them valuable for therapeutic and vaccine development approaches.

In HIV research, bNAbs function by binding to conserved epitopes on the HIV envelope, preventing viral entry into host cells. Recent clinical trials have demonstrated the feasibility of achieving sustained virologic suppression in PLWH using HIV-specific bNAbs in the absence of antiretroviral therapy . Beyond direct neutralization, bNAbs offer the additional advantage of potentially modulating immune responses and enhancing HIV-specific T-cell immunity compared to conventional ART .

What methodologies are used to evaluate bNAb neutralization capacity?

The standard methodology for evaluating bNAb neutralization capacity involves TZM-bl-based neutralization/suppression assays. This approach enables researchers to:

  • Determine sensitivity of viral isolates to specific bNAbs

  • Calculate neutralization potency (IC50 values)

  • Compare effectiveness across different antibodies

  • Assess breadth against diverse viral isolates

In recent studies, this methodology has been employed to test viral isolates against panels of bNAbs including 3BNC117, 10-1074, VRC01, VRC07, N6, 10E8, PGDM1400, and PGT121 . The results are typically expressed as IC50 values (concentration of antibody required for 50% inhibition), enabling quantitative comparison of neutralization potency.

How do researchers distinguish between effective and ineffective antibodies against viral targets?

Researchers distinguish between effective and ineffective antibodies through multiple complementary approaches:

Functional Assays:

  • BRE-signal data (bone morphogenetic protein responsive element) to classify antibodies as:

    • Functionally inactive

    • Weak inhibitors

    • Strong inhibitors

Epitope Binding Analysis:
Effectiveness often correlates with specific epitope targeting. For example, with anti-BMP4 antibodies, those targeting the BMPR1 binding region showed superior effectiveness compared to those targeting other regions . Similarly, in HIV research, bNAbs targeting conserved regions of the viral envelope demonstrate greater breadth of neutralization.

Western Blot Confirmation:
Verification that antibodies recognize the mature dimeric form of the target (e.g., ~34 kDa band for mature BMP4 dimer) rather than inactive precursor forms correlates with functional activity .

What experimental approaches are used to evaluate ex vivo sensitivity of multidrug-resistant HIV to broadly neutralizing antibodies?

The evaluation of multidrug-resistant (MDR) HIV sensitivity to bNAbs involves sophisticated ex vivo approaches:

Viral Isolation Protocol:

  • Collection of blood samples from PLWH with MDR HIV

  • Isolation of infectious viral isolates through co-culture with activated CD4+ T cells

  • Expansion of viral isolates to sufficient quantities for testing

Neutralization/Suppression Assay:

  • TZM-bl cell-based assay system expressing CD4, CCR5, and an HIV LTR-driven luciferase reporter gene

  • Incubation of viral isolates with serial dilutions of bNAbs

  • Measurement of infection by quantifying luciferase activity

  • Calculation of IC50 values to determine sensitivity

Comprehensive bNAb Panel Testing:
As demonstrated in recent studies, viral isolates should be tested against a diverse panel of bNAbs targeting different epitopes (3BNC117, 10-1074, VRC01, VRC07, N6, 10E8, PGDM1400, and PGT121) and anti-CD4 antibodies (ibalizumab and UB-421) .

What are the key challenges in designing immunogens to elicit broadly neutralizing antibodies for HIV vaccines?

Designing immunogens to elicit bNAbs faces several complex challenges:

Viral Antigenic Diversity:
HIV's rapid mutation rate means that antibodies must recognize many variants. This requires sophisticated computational frameworks that consider the viral fitness landscape to design effective antigen panels .

Three-Step Vaccination Strategy:
Current approaches propose a three-stage process:

  • Special purpose antigens to activate correct naïve B cells

  • Intermediate antigens to induce somatic mutations and recognition of native virus

  • Sequential or mixed antigens to increase antibody breadth

Balancing Antigenic Frustration:
In silico simulations suggest that administering multiple antigens simultaneously may induce too much frustration in antibody maturation. Sequential administration of antigens appears more effective for developing breadth .

Integration of Structural and Fitness Data:
Optimal antigen design requires combining:

  • Atomistic understanding of antibody-antigen interactions

  • HIV gp160 fitness landscape models to identify mutations tolerable to the virus

  • Usage maps of key residues in critical epitopes like CD4 binding site (CD4bs)

How does viral escape pressure influence bNAb development, and what methodologies address this challenge?

The constant battle between HIV evolution and antibody pressure creates significant challenges for bNAb development:

Fitness Landscape Analysis:
Researchers use computational models of the gp160 fitness landscape to predict:

  • The difficulty for HIV to escape immune pressure

  • Fitness penalties associated with specific mutations

  • Epistatic couplings between mutations that affect viral fitness

Strategic Targeting of High-Cost Escape Residues:
By comparing residue usage (how frequently residues interact with bNAbs) with fitness costs (how difficult it is for the virus to mutate these residues), researchers can:

  • Identify residues that are both critical for antibody binding and costly for the virus to mutate

  • Design antigens that force antibody maturation toward targeting these high-cost escape residues

Molecular Dynamics Simulations:
To understand antibody-antigen interactions at molecular resolution:

  • Simulations of antigen (e.g., BG505 SOSIP) with antibodies at different maturation stages

  • Analysis of interactions between mature antibodies (e.g., VRC01), putative germline (VRC01GL), and immature precursors (DRVIA7)

  • Identification of key contact residues that should be preserved in immunogen design

How do researchers evaluate the effectiveness of bNAbs compared to other antibody-based approaches for HIV treatment?

Comparative evaluation of different antibody-based approaches is critical for advancing HIV treatment strategies:

Comprehensive Neutralization/Suppression Profiling:
Studies have directly compared:

  • HIV-specific bNAbs (3BNC117, 10-1074, VRC01, etc.)

  • Anti-CD4 antibodies (ibalizumab and UB-421)

  • Conventional monoclonal antibodies

Intact Proviral DNA Assessment:
Measurement of intact HIV proviral DNA burden provides insights into the reservoir-targeting potential of different antibody approaches. Recent studies have shown comparable levels between MDR HIV patients and ART-naïve viremic individuals (P = 0.29) .

Immune Activation and Exhaustion Analysis:
Evaluation of activation and exhaustion markers (PD-1, TIGIT, 2B4, CD160, and CD38+/HLA-DR+) on CD8+ T cells helps assess the immunomodulatory effects of different antibody approaches. MDR HIV patients show significantly lower levels of these markers compared to ART-naïve individuals .

Resistance Pattern Characterization:
The table below summarizes findings from a recent study on viral sensitivity patterns to different antibody approaches:

Antibody TypeResistance Pattern in MDR HIVPotential Application
bNAbs (varied epitope targets)Resistance to at least 2 bNAbs per patientCombination therapy targeting multiple epitopes
CD4-binding site bNAbsVariable sensitivityPaired with non-CD4-binding site bNAbs
Ibalizumab (anti-CD4)Majority sensitive, some with reduced sensitivityPotential for most MDR patients
UB-421 (anti-CD4 D1)No resistance observed in 93 viral isolatesPromising universal option for MDR HIV

What are the most promising methodological approaches for developing next-generation broadly neutralizing antibodies?

Several innovative methodological approaches are advancing the development of next-generation bNAbs:

VHH (Llama-Derived) Antibody Development:
Single-domain antibodies derived from llamas (VHHs) offer potential advantages over conventional antibodies:

  • Small size (~15 kDa)

  • Lack of light chains

  • Enhanced stability and binding affinity

  • Superior specificity compared to natural antagonists and small molecule inhibitors

Targeted Epitope Selection:
Research has demonstrated that antibodies targeting specific functional regions (like the BMPR1 binding area) exhibit superior neutralization capabilities:

  • Higher specificity

  • Greater effectiveness at nanomolar concentrations

  • Better ability to recognize and inhibit diverse viral variants

Sequential Immunization Strategies:
Computational frameworks now enable the design of optimal antigen panels for sequential immunization:

  • Initial immunogens to activate naïve B cells

  • Intermediate immunogens to guide antibody maturation

  • Final immunogens to maximize breadth

  • Design guided by both structural information and fitness landscape models

Computational Integration of Multiple Data Sources:
Advanced computational frameworks integrate:

  • Crystallographic structures of antibody-antigen complexes

  • Viral fitness landscape data

  • Sequence conservation analysis

  • Molecular dynamics simulations

  • In silico antibody maturation models

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