NeuralBlitz Molecular Biology
What I Do
I provide comprehensive molecular biology tools including PCR design, cloning strategies, DNA sequencing analysis, gene expression quantification, CRISPR guide design, and cell culture calculations for biotechnology applications.
When to Use Me
- PCR primer design
- Cloning strategy planning
- DNA sequence analysis
- Gene expression studies
- CRISPR genome editing
- Vector construction
Core Concepts
- PCR: Primers, annealing, extension, cycle number
- Cloning: Restriction enzymes, ligation, transformation
- Sequencing: Sanger, NGS, read quality, assembly
- Gene Expression: RT-qPCR, RNA-Seq, normalization
- CRISPR: gRNA design, off-target prediction
- Transformation: Efficiency, selection markers
- Protein Expression: Promoters, vectors, purification
- Flow Cytometry: Fluorescence, cell sorting
Code Examples
PCR Calculations
def calculate_tm(sequence):
if len(sequence) < 14:
return 2 * (sequence.count('A') + sequence.count('T')) + 4 * (sequence.count('G') + sequence.count('C'))
return 64.9 + 41 * (sequence.count('G') + sequence.count('C') - 16.4) / len(sequence)
def recommended_annealing_temp(forward, reverse):
Tm_f = calculate_tm(forward)
Tm_r = calculate_tm(reverse)
return (Tm_f + Tm_r) / 2 - 5
def optimal_gc_content(sequence):
return (sequence.count('G') + sequence.count('C')) / len(sequence) * 100
def amplicon_size(forward, reverse, template):
return len(forward) + len(reverse)
forward = "ATGAGTGTGCTG"
reverse = "TTACACACACCA"
print(f"Tm (forward): {calculate_tm(forward):.1f}°C")
print(f"Annealing temp: {recommended_annealing_temp(forward, reverse):.1f}°C")
Primer Design
PRIMER_CONSTRAINTS = {
'min_length': 18,
'max_length': 25,
'min_tm': 55,
'max_tm': 65,
'max_gc': 60,
'min_gc': 40,
'max_self_complementarity': 4,
'max_3end_gc': 3
}
def validate_primer(sequence):
errors = []
gc = optimal_gc_content(sequence)
if len(sequence) < PRIMER_CONSTRAINTS['min_length']:
errors.append(f"Too short: {len(sequence)}")
if len(sequence) > PRIMER_CONSTRAINTS['max_length']:
errors.append(f"Too long: {len(sequence)}")
if gc < PRIMER_CONSTRAINTS['min_gc']:
errors.append(f"GC too low: {gc:.1f}%")
if gc > PRIMER_CONSTRAINTS['max_gc']:
errors.append(f"GC too high: {gc:.1f}%")
return {'valid': len(errors) == 0, 'errors': errors}
def find_primers(target_sequence, product_size_range):
potential_primers = []
for i in range(len(target_sequence) - 17):
fwd = target_sequence[i:i+18]
gc = optimal_gc_content(fwd)
if 40 <= gc <= 60:
potential_primers.append(('forward', i, fwd))
return potential_primers
print(f"Primer validation: {validate_primer('ATGCGATCGATCGATCG')}")
Gene Expression Analysis
def delta_delta_ct_method(ct_treated, ct_control, ref_treated, ref_control):
dct_treated = ct_treated - ref_treated
dct_control = ct_control - ref_control
ddct = dct_treated - dct_control
fold_change = 2 ** (-ddct)
return fold_change, ddct
def rpkm_normalization(mapped_reads, gene_length, total_reads):
return mapped_reads / (gene_length / 1000 * total_reads / 1e6)
def tpm_normalization(mapped_reads, gene_length, rpkm_sum):
rpkm = rpkm_normalization(mapped_reads, gene_length, sum(mapped_reads))
return (rpkm / rpkm_sum) * 1e6
ct_gene = 22.5
ct_ref = 18.2
fold_change, ddct = delta_delta_ct_method(ct_gene, 25.0, ct_ref, 17.8)
print(f"Fold change: {fold_change:.2f}x")
CRISPR gRNA Design
PAM_SEQUENCE = "NGG"
def find_spCas9_sites(sequence):
sites = []
for i in range(len(sequence) - 2):
motif = sequence[i:i+3]
if motif[1:] == "GG":
guide = sequence[i:i+20]
sites.append({
'position': i,
'gRNA': guide,
'PAM': motif,
'score': predict_guide_score(guide)
})
return sorted(sites, key=lambda x: x['score'], reverse=True)
def predict_guide_score(gRNA):
scores = {
'G': 0.5, 'C': 0.5, 'A': 0.3, 'T': 0.2,
'GG': 0.2, 'CC': 0.2, 'AA': 0.1, 'TT': 0.1
}
score = 0
for i in range(len(gRNA) - 1):
dinuc = gRNA[i:i+2]
score += scores.get(dinuc, 0)
return score
def check_off_targets(gRNA, genome, mismatch_limit=3):
off_targets = []
for i in range(len(genome) - len(gRNA) + 1):
mismatches = sum(1 for j in range(len(gRNA)) if genome[i+j] != gRNA[j])
if mismatches <= mismatch_limit:
off_targets.append({'position': i, 'mismatches': mismatches})
return off_targets
sequence = "ATGCGTAGCTAGCTAGCTAGCGGATCC"
sites = find_spCas9_sites(sequence)
print(f"Found {len(sites)} potential gRNA sites")
Cloning Calculations
def calculate_ligation_efficiency(insert_conc, vector_conc, insert_size, vector_size):
insert_moles = insert_conc / insert_size
vector_moles = vector_conc / vector_size
molar_ratio = insert_moles / vector_moles
return min(molar_ratio / 3, 1.0) # 3:1 molar ratio recommended
def calculate_transformation_efficiency(colonies, volume_plated, dilution_factor, DNA_amount):
cfu_per_µg = colonies * dilution_factor * (1000 / volume_plated) / DNA_amount
return cfu_per_µg
def digest_calculation(DNA_amount, units_enzyme, incubation_time):
units_per_µg = units_enzyme / DNA_amount
return {
'units_per_µg': units_per_µg,
'suggested_incubation': f"{max(incubation_time, 60)} min at 37°C"
}
insert_ng, vector_ng = 50, 100
insert_bp, vector_bp = 500, 3000
eff = calculate_ligation_efficiency(insert_ng/500, vector_ng/3000, 500, 3000)
print(f"Ligation efficiency: {eff:.2f}")
Best Practices
- Primer Design: Avoid hairpins and dimers
- qPCR: Include technical replicates
- CRISPR: Validate off-target effects
- Controls: Include positive and negative controls
- Replication: Multiple biological replicates
Common Patterns
# Codon usage optimization
CODON_USAGE = {
'A': ['GCT', 'GCC', 'GCA', 'GCG'],
'K': ['AAA', 'AAG']
}
def optimize_codon_usage(sequence, host='E.coli'):
optimized = ''
for aa in translate_dna(sequence):
best_codon = max(CODON_USAGE.get(aa, [sequence[i:i+3]]))
optimized += best_codon
return optimized
# Sanger sequencing trace analysis
def analyze_trace_quality(trace_file):
peak_heights = extract_peak_heights(trace_file)
return {
'Q20_bases': sum(1 for h in peak_heights if h > 100),
'average_quality': np.mean(peak_heights)
}
Core Competencies
- PCR and primer design
- Gene expression quantification
- CRISPR guide RNA design
- Cloning and transformation
- Sequence analysis and assembly