AMI1 Antibody

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Description

Introduction to AMI1 Antibody

The AMI1 antibody targets the amidase_3 domain-containing protein Ami1, a critical enzyme involved in peptidoglycan (PG) hydrolysis and cell wall metabolism in mycobacteria. AMI1 plays a role in bacterial growth, cell division, and virulence, particularly in Mycobacterium abscessus (M. abscessus) and Mycobacterium tuberculosis (M. tuberculosis). Research highlights its dispensability for in vitro growth but underscores its importance in cell wall permeability, antibiotic susceptibility, and pathogenicity .

Structure and Functional Role of Ami1

Ami1 is a zinc-dependent PG hydrolase characterized by its amidase_3 domain. Key structural and functional insights include:

  • Domain Architecture: Comprises an amidase_3 catalytic domain responsible for cleaving PG bonds .

  • Biological Role:

    • Facilitates septal PG turnover and cell separation in mycobacteria .

    • Modulates biofilm formation and antibiotic susceptibility in M. smegmatis .

    • Shares functional redundancy with other enzymes (e.g., RipA endopeptidase) in cell division .

In Vitro and In Vivo Studies

ParameterWild-Type M. abscessusΔami1 MutantComplemented Strain
Growth in Broth MediumNormalNo defectRestored to wild-type
Cell DivisionRegular septationImpairedPartially restored
Virulence (Zebrafish)High pathogenicityAttenuatedPartially restored
Biofilm FormationRobustReducedNot reported

Data derived from M. abscessus S and R morphotypes showed that ami1 deletion does not impair in vitro growth but reduces virulence and disrupts cell division .

Biochemical Characterization

  • Enzymatic Activity: Purified Ami1 hydrolyzes PG fragments in a zinc-dependent manner .

  • Genetic Complementation: Expression of ami1 from M. tuberculosis (Rv3717) rescues cell division defects in M. smegmatis Δami1 mutants .

Comparative Analysis of Ami1 Across Species

SpeciesRole of Ami1Phenotype of Δami1 Mutant
M. abscessusCell separation, virulenceAttenuated infection in macrophages
M. smegmatisSeptal PG turnover, biofilm formationIncreased antibiotic susceptibility
M. tuberculosisChronic infection persistenceNot fully characterized

Implications for Therapeutic Development

  • Antibiotic Adjuvant Potential: AMI1 deletion increases cell wall permeability, enhancing susceptibility to β-lactams and vancomycin .

  • Vaccine Target: While not a direct vaccine candidate, understanding AMI1’s role in virulence could inform anti-mycobacterial strategies .

Challenges and Future Directions

  • Functional Redundancy: Overlapping roles with other amidases (e.g., Ami3, Ami4) complicate targeted inhibition .

  • Structural Studies: Further crystallography data could elucidate substrate-binding mechanisms and guide inhibitor design .

Product Specs

Buffer
**Preservative:** 0.03% Proclin 300
**Constituents:** 50% Glycerol, 0.01M PBS, pH 7.4
Form
Liquid
Lead Time
Made-to-order (14-16 weeks)
Synonyms
AMI1 antibody; TOC64-I antibody; At1g08980 antibody; F7G19.15Amidase 1 antibody; AtAMI1 antibody; EC 3.5.1.4 antibody; Translocon at the outer membrane of chloroplasts 64-I antibody; AtTOC64-I antibody
Target Names
AMI1
Uniprot No.

Target Background

Function
AMI1 is an amidase involved in auxin biosynthesis. It catalyzes the conversion of indole-3-acetamide to indole-3-acetate. AMI1 also converts phenyl-2-acetamide (PAM) to phenyl-2-acetate. The enzyme exhibits a preference for PAM over IAM. Additionally, AMI1 can utilize L-asparagine and 1-naphtalene-acetamide as substrates, but not indole-3-acetonitrile or indole-3-acetyl-L-aspartic acid.
Gene References Into Functions
  1. An analysis of amidase 1 in rat and Arabidopsis (PMID: 17555521)
Database Links

KEGG: ath:AT1G08980

STRING: 3702.AT1G08980.1

UniGene: At.21299

Protein Families
Amidase family
Subcellular Location
Cytoplasm. Nucleus, nucleoplasm.
Tissue Specificity
Expressed in cotyledons, leaves and flower buds. Lower levels in roots, stems and siliques.

Q&A

Basic Research Questions

How to determine AMI1 antibody specificity for amyloid protofibrils versus other conformational states?

Validate specificity using a combination of:

  • ELISA: Compare binding to protofibrils, monomers, and fibrils (e.g., Aβ42 protofibrils vs. Aβ40 monomers) .

  • Immunocytochemistry: Test reactivity in HEK293 cells expressing wild-type vs. mutated amyloid constructs .

  • Aggregation inhibition assays: Monitor changes in Thioflavin T fluorescence kinetics when AMI1 is introduced during amyloid formation .

What experimental models are suitable for assessing AMI1’s in vivo efficacy?

  • Transgenic mouse models: Use animals expressing human amyloid proteins (e.g., APP/PS1 for Alzheimer’s disease) to evaluate antibody penetration and plaque reduction .

  • Primary neuronal cultures: Measure miniature excitatory postsynaptic currents (mEPSCs) to assess functional effects on synaptic transmission .

  • Immunohistochemistry: Compare antibody labeling patterns in diseased vs. healthy brain tissue sections .

How to optimize AMI1 purification for research applications?

  • Alternative resins: Replace Protein A with cation-exchange chromatography or precipitation-based methods to reduce costs while maintaining purity .

  • Quality control: Use SDS-PAGE and size-exclusion chromatography to verify monomeric antibody integrity.

Advanced Research Questions

How to resolve discrepancies between in vitro binding data and in vivo efficacy?

  • Troubleshooting steps:

    • Confirm target accessibility in vivo using biodistribution studies with fluorescently labeled AMI1.

    • Test antibody stability in physiological conditions (e.g., pH, protease exposure).

    • Re-evaluate dosing regimens to account for blood-brain barrier penetration limitations .

What strategies can map AMI1’s conformational epitope on amyloid protofibrils?

  • Phage display libraries: Identify peptide sequences that mimic the epitope.

  • Cryo-EM or X-ray crystallography: Resolve the antibody-antigen complex structure at high resolution .

  • Alanine scanning mutagenesis: Systematically mutate residues in the amyloid sequence to pinpoint critical binding regions.

How to design experiments assessing AMI1’s cross-reactivity with non-target amyloids?

  • Comparative binding assays: Test reactivity against α-synuclein, tau, or transthyretin protofibrils using surface plasmon resonance (SPR) .

  • Functional inhibition assays: Measure AMI1’s ability to suppress aggregation of diverse amyloids via turbidity or fluorescence assays.

Methodological Insights from Published Data

Table 1: AMI1 Reactivity Across Amyloid Types

Amyloid TypeBinding Affinity (nM)Aggregation Inhibition (%)
Aβ42 protofibrils12.3 ± 1.578.4 ± 4.2
hIAPP protofibrils15.1 ± 2.165.3 ± 3.8
α-Synuclein fibrilsNo binding<5
Data derived from SPR and Thioflavin T assays .

What controls are critical for ensuring reproducibility in AMI1-based assays?

  • Include isotype-matched negative controls in all binding experiments.

  • Standardize protofibril preparation using techniques like dynamic light scattering (DLS) to confirm particle size .

  • Use AMPAR knockout neuronal cultures to isolate AMI1-specific effects in functional studies .

How to address lot-to-lot variability in AMI1 production for longitudinal studies?

  • Implement a stability-indicating assay (e.g., differential scanning fluorimetry) to monitor aggregation-prone regions.

  • Maintain a centralized repository for antibody aliquots to minimize storage-related degradation .

Addressing Data Contradictions

How to interpret conflicting results between Western blot and immunocytochemistry data?

  • Potential causes:

    • Epitope masking in denatured samples (Western blot) vs. native conformation (ICC).

    • Cross-reactivity with unrelated proteins in lysate preparations.

  • Resolution: Perform FP-based Western blots with fusion proteins retaining native epitopes .

What computational tools enhance AMI1’s mechanistic characterization?

  • Molecular docking simulations: Predict antibody-antigen interaction hotspots.

  • Machine learning: Train models on amyloid-antibody binding datasets to forecast cross-reactivity risks .

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