Recombinant Branchiostoma floridae NADH-ubiquinone oxidoreductase chain 4L (ND4L)

What is the basic structure and function of ND4L in Branchiostoma floridae?

ND4L (NADH-ubiquinone oxidoreductase chain 4L) is a small, highly hydrophobic subunit of respiratory Complex I. In Branchiostoma, as in other organisms, ND4L forms part of the core transmembrane region of Complex I, which is the largest of the respiratory complexes in the electron transport chain. The protein typically weighs approximately 11 kDa and consists of around 98 amino acids . ND4L contributes to the proton-pumping function of Complex I, helping to generate the electrochemical gradient necessary for ATP synthesis.

Experimental approaches to study ND4L structure include:

• X-ray crystallography of purified Complex I

• Cryo-electron microscopy for structural visualization

• Hydropathy plot analysis to confirm transmembrane domains

• Site-directed mutagenesis to identify functional residues

How does ND4L gene organization in Branchiostoma compare to other species?

In most vertebrates, the ND4L gene (MT-ND4L) is located in the mitochondrial genome. The human MT-ND4L gene spans base pairs 10,469 to 10,765 in the mitochondrial DNA . An unusual feature in humans and likely conserved in other vertebrates is the 7-nucleotide overlap between the last three codons of MT-ND4L and the first three codons of MT-ND4 .

To study gene organization:

• Complete mitochondrial genome sequencing

• Comparative genomic analysis across chordate lineages

• Gene synteny mapping to identify conserved regions

What are the most effective expression systems for recombinant Branchiostoma floridae ND4L?

For expressing recombinant Branchiostoma floridae ND4L, researchers should consider the following systems based on the protein's hydrophobic nature:

• Bacterial expression systems:

  • E. coli C41(DE3) or C43(DE3) strains specifically designed for membrane proteins

  • Fusion with solubility enhancers like MBP or SUMO

  • Lower induction temperatures (16-20°C) to reduce inclusion body formation

• Eukaryotic expression systems:

  • Insect cell (Sf9, Hi5) expression with baculovirus

  • Yeast systems (Pichia pastoris) for proper membrane insertion

• Cell-free expression systems:

  • Supplemented with appropriate lipids or detergents to accommodate hydrophobicity

Optimization protocol should include:

• Codon optimization for the chosen expression system

• Signal peptide modification for proper targeting

• Detergent screening (DDM, LMNG, digitonin) for extraction

• Strategic placement of purification tags to minimize functional interference

How can researchers effectively purify recombinant ND4L while maintaining its functional integrity?

Purifying recombinant ND4L presents challenges due to its hydrophobicity and tendency to aggregate. A methodological approach includes:

• Membrane fraction isolation:

  • Gentle cell lysis using French press or sonication

  • Differential centrifugation (10,000g followed by 100,000g)

  • Careful resuspension of membrane pellets

• Solubilization optimization:

  • Detergent screening table:

  Detergent	Concentration Range	Advantages	Limitations
  DDM	0.5-2%	Mild, maintains complex integrity	Larger micelles
  LMNG	0.1-0.5%	Small micelles, stability	Higher cost
  Digitonin	0.5-1%	Preserves supercomplexes	Lower yield
  FC-12	0.1-0.5%	Efficient solubilization	May denature

• Purification strategy:

  • IMAC (if His-tagged) with specialized protocols for membrane proteins

  • Size exclusion chromatography to remove aggregates

  • Lipid nanodisc reconstitution for stability

• Functional validation:

  • NADH:ubiquinone oxidoreductase activity assays

  • Monitoring protein stability through thermal shift assays

What methods are most appropriate for analyzing genetic variations in ND4L across Branchiostoma populations?

To effectively analyze genetic variations in ND4L across Branchiostoma populations:

• DNA isolation and sequencing:

  • Whole mitochondrial genome amplification using long-range PCR

  • Next-generation sequencing with >12.5X coverage as demonstrated in Branchiostoma belcheri studies

  • Targeted amplicon sequencing of ND4L using species-specific primers

• Variant calling and analysis:

  • Use specialized pipelines for mitochondrial variant calling

  • Apply population genetics software (DnaSP, Arlequin)

  • Analyze in context of population structure using:

    • STRUCTURE

    • Principal Component Analysis

    • Admixture analysis

• Functional prediction of variants:

  • Apply algorithms like SIFT, PolyPhen-2 to predict "probably damaging" mutations

  • Rare variants (MAF<0.05) should receive particular attention as they may relate to intracellular digestive capacity differences in Branchiostoma

• Demographic inference:

  • Apply methods like BEAST or PSMC to detect historical population size changes

  • Research has shown Branchiostoma populations experienced reductions during glaciations followed by expansion in interglacial periods

How do mutations in ND4L affect Complex I assembly and function in Branchiostoma floridae?

Mutations in ND4L can significantly impact Complex I assembly and function through several mechanisms:

• Assembly defects:

  • ND4L is part of the minimal assembly of core proteins required for Complex I function

  • Mutations may disrupt interaction with other subunits, particularly those encoded by mitochondrial genes (ND1, ND2, ND3, ND4, ND5, ND6)

  • Experimental approach: Blue Native PAGE to visualize complex assembly intermediates

• Functional impairment:

  • ND4L contributes to the proton-pumping pathway in the membrane domain

  • Mutations in transmembrane regions may affect proton translocation

  • Methodology: Measure Complex I activity using spectrophotometric assays with artificial electron acceptors

• Stability changes:

  • Hydrophobic core mutations may destabilize the entire complex

  • Approach: Thermal stability assays of isolated Complex I from wild-type vs. mutant lines

• In vivo assessment:

  • Oxygen consumption rate (OCR) measurements

  • Membrane potential analysis using potentiometric dyes

  • ROS production measurement as indicator of electron leakage

What role does ND4L play in G-quadruplex (G4) RNA regulation within Branchiostoma mitochondria?

G-quadruplex (G4) structures form in GC-skewed regions of mitochondrial genomes, affecting RNA stability and processing. Research on the relationship between ND4L and G4 regulation should consider:

• G4 prediction and mapping:

  • Computational tools to identify potential G4-forming sequences in and around the ND4L gene

  • Experimental validation using G4-specific antibodies or G4-sensitive fluorescent ligands

• Interaction with G4 regulatory proteins:

  • The quasi-RNA recognition motif (qRRM) protein GRSF1 cooperates with mitochondrial degradosome to prevent accumulation of G4-containing transcripts in human mitochondria

  • Investigate whether Branchiostoma homologs of GRSF1 interact with ND4L transcripts

• Functional consequences:

  • G4 structures can affect transcription, processing, and translation

  • In vitro reconstitution experiments can test if G4-melting proteins facilitate ND4L transcript processing

• Evolutionary considerations:

  • GRSF1 and related qRRM proteins are found only in vertebrates

  • Investigate whether Branchiostoma possesses alternative mechanisms for G4 regulation

How does recombinant ND4L interact with other Complex I subunits during assembly?

Understanding the assembly pathway of Complex I involving ND4L requires sophisticated experimental approaches:

• Sequential assembly analysis:

  • Pulse-chase labeling of newly synthesized proteins

  • Time-course isolation of assembly intermediates

  • Mass spectrometry to identify interaction partners at each stage

• Interaction mapping:

  • Crosslinking mass spectrometry (XL-MS) to identify residues in proximity

  • Co-immunoprecipitation with tagged ND4L variants

  • Split-reporter assays (split-GFP, BRET) for interaction validation

• Assembly model development:

  Assembly Stage	Interacting Subunits	Detection Method	Validation Approach
  Early	ND1, ND3	BN-PAGE	Knockdown studies
  Intermediate	ND2, ND4L, ND6	XL-MS	Mutational analysis
  Late	ND4, ND5	Proteomics	In vitro assembly

• Species-specific considerations:

  • Compare assembly pathway in Branchiostoma with other chordates

  • Investigate whether nuclear-encoded ND4L (as in Chlamydomonas ) follows different assembly routes than mitochondrially-encoded versions

How has the ND4L gene evolved across chordate lineages compared to Branchiostoma floridae?

The evolutionary trajectory of ND4L across chordate lineages reveals important adaptations:

• Sequence conservation analysis:

  • Multiple sequence alignment of ND4L across chordates

  • Identification of conserved functional domains versus variable regions

  • Calculation of dN/dS ratios to detect selection pressure

• Genomic location transitions:

  • In most vertebrates, ND4L is encoded in the mitochondrial genome

  • In some species like Chlamydomonas reinhardtii, ND4L is encoded in the nuclear genome (NUO11)

  • Investigate whether any chordate lineages show evidence of ND4L gene transfer to the nucleus

• Structural adaptations:

  • Analysis of amino acid substitutions in transmembrane domains

  • Correlation with environmental factors (temperature, oxygen availability)

  • 3D structural modeling to predict functional consequences of evolutionary changes

• Evolutionary rate analysis:

  • Compare substitution rates of ND4L with other mitochondrial and nuclear genes

  • Test for accelerated evolution in specific lineages

  • Demographic inference has shown Branchiostoma populations experienced changes during glaciation periods with subsequent expansion

What can genomic studies of Branchiostoma ND4L reveal about mitochondrial genome evolution?

Genomic studies of Branchiostoma ND4L provide insights into mitochondrial genome evolution:

• Comparative genomic analysis:

  • Whole-genome resequencing studies have identified 594 SNPs and 148 Indels in Branchiostoma mitochondrial genomes

  • Synteny analysis of mitochondrial gene order across deuterostomes

  • Investigation of selection pressures on mitochondrial genes

• Nucleotide composition and bias:

  • GC skew analysis in mitochondrial genomes

  • Correlation with G-quadruplex forming potential

  • Codon usage bias analysis

• Methodological approach:

  • Next-generation sequencing with ~12.5X depth using Illumina systems

  • Mapping to reference genomes for variant identification

  • Application of population genetics tools to infer historical demographic changes

• Evolutionary implications:

  • Detection of adaptive evolution in response to environmental changes

  • Investigation of purifying selection on functional domains

  • Analysis of rare variants with potential functional effects on intracellular digestion

What bioinformatic approaches are most effective for analyzing ND4L sequence data from Branchiostoma floridae?

Effective bioinformatic analysis of Branchiostoma floridae ND4L requires a multi-layered approach:

• Sequence quality control and preprocessing:

  • Quality filtering of sequencing reads (PHRED score >30)

  • Adapter trimming and contaminant removal

  • Read mapping to reference mitochondrial genome using Bowtie v2.1.0

• Variant detection and annotation:

  • SNP and indel calling using specialized mitochondrial variant callers

  • Annotation using tools like ANNOVAR and SNPeff

  • Functional prediction of variants using algorithms like SIFT and PolyPhen-2

• Structural and functional analysis:

  • Transmembrane domain prediction

  • Protein modeling and molecular dynamics simulations

  • Evolutionary conservation mapping

  • G-quadruplex prediction in transcripts

• Population genetics analysis:

  • Calculation of nucleotide diversity (π) and Tajima's D

  • Detection of selection signatures

  • Demographic history reconstruction

  • Rare variant analysis, particularly focusing on variants with MAF<0.05

How can researchers integrate multiple omics data to understand ND4L function in Branchiostoma?

Integrating multiple omics approaches provides a comprehensive understanding of ND4L function:

• Multi-omics data collection and processing:

  • Genomics: Whole-genome or targeted sequencing

  • Transcriptomics: RNA-Seq with special attention to mitochondrial transcripts

  • Proteomics: Mass spectrometry of purified Complex I

  • Metabolomics: Analysis of TCA cycle intermediates and NADH/NAD+ ratios

• Data integration methods:

  • Correlation network analysis

  • Pathway enrichment analysis

  • Machine learning approaches for feature selection

  • Bayesian network modeling

• Functional validation experiments:

  • CRISPR-Cas9 editing of ND4L

  • Phenotypic characterization of mutants

  • Respiratory capacity measurements

  • Intracellular digestion capacity assessment

• Visualization and interpretation:

  • Interactive pathway maps

  • Protein-protein interaction networks

  • Multi-omics data browsers

  Omics Layer	Key Methods	Integration Approach	Expected Insights
  Genomics	WGS, variant calling	Variant effect prediction	Genetic basis of phenotypic variation
  Transcriptomics	RNA-Seq, qPCR	Expression correlation networks	Regulatory relationships
  Proteomics	LC-MS/MS, BN-PAGE	Protein complex modeling	Assembly dynamics, PTMs
  Metabolomics	GC-MS, LC-MS	Flux analysis	Functional consequences

What computational methods can predict the impact of ND4L mutations on Complex I function?

Predicting the functional impact of ND4L mutations requires sophisticated computational approaches:

• Sequence-based prediction:

  • Conservation analysis across species

  • Application of algorithms like SIFT, PolyPhen-2, and PROVEAN

  • Machine learning classifiers trained on known pathogenic mutations

• Structure-based analysis:

  • Homology modeling based on available Complex I structures

  • Molecular dynamics simulations to assess structural stability

  • Binding free energy calculations for subunit interactions

  • Prediction of changes in hydrophobic interactions within the membrane domain

• Systems-level prediction:

  • Flux balance analysis to predict metabolic consequences

  • Protein-protein interaction network perturbation analysis

  • Integration with experimental data on "probably damaging" mutations

• Validation approaches:

  • In silico validation through evolutionary analysis

  • Comparison with experimental mutagenesis data

  • Cross-validation using multiple prediction algorithms