Imp urease positive oxidase positive catalase positive and etc for neet pg which are important

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Here is a complete, high-yield NEET PG biochemical reactions cheat sheet compiled from authoritative microbiology textbooks (Jawetz & Sherris Medical Microbiology, Quick Compendium of Clinical Pathology):

High-Yield Biochemical Reactions for NEET PG - Microbiology

1. CATALASE TEST

Detects conversion of H₂O₂ → H₂O + O₂ (bubbles = positive)

Algorithm for differentiating Gram-positive cocci using catalase and coagulase

Result	Organisms
Positive	Staphylococcus, Bacillus, Aspergillus, Nocardia, Enterobacteriaceae (most gram-negatives), Listeria, H. pylori
Negative	All Streptococci, Enterococcus, Clostridium, Bacteroides

Key trick: Catalase separates Staph (positive) from Strep (negative) - the most tested distinction!

2. COAGULASE TEST

Converts fibrinogen to fibrin. Done only after catalase positive (Staphylococcus) is confirmed.

Result	Organism	Notes
Positive	S. aureus	Both slide (bound) and tube (free) coagulase
Negative	S. epidermidis, S. saprophyticus, others (CoNS)
Special	S. lugdunensis	Slide coagulase positive, tube coagulase NEGATIVE - clinically mimics S. aureus

3. OXIDASE TEST

Detects cytochrome C oxidase. Positive = blue/purple color on the strip.

Result	Organisms
Positive	Pseudomonas, Neisseria, Vibrio, Campylobacter, Helicobacter, Moraxella, Aeromonas, Brucella, Pasteurella
Negative	ALL Enterobacteriaceae (E. coli, Klebsiella, Salmonella, Shigella, Proteus, etc.)

Key rule: Oxidase negative = Enterobacteriaceae. This is the first test to separate them from all other gram-negative rods.

4. UREASE TEST

Urea → NH₃ + CO₂. Positive = pink/red color (alkaline pH). Rapid positivity (within 4 hours) is significant.

Result	Organisms
Strongly/Rapidly Positive	Proteus spp., H. pylori, Ureaplasma urealyticum, Cryptococcus neoformans
Weakly/Slowly Positive	Klebsiella, Pseudomonas, Brucella, Yersinia enterocolitica, Helicobacter
Negative	E. coli, Salmonella, Shigella, Streptococci

NEET favorite: H. pylori urease is the basis of the CLO test (rapid urease test) and urea breath test (UBT). Proteus urease causes struvite kidney stones.

5. INDOLE TEST

Tests tryptophan → indole. Red color with Kovacs reagent = positive.

Result	Organisms
Positive	E. coli, Proteus vulgaris, Vibrio cholerae, Klebsiella oxytoca
Negative	Proteus mirabilis, Klebsiella pneumoniae, Salmonella, Shigella (most)

Trick: Proteus vulgaris = indole +, Proteus mirabilis = indole - (classic MCQ pair!)

6. CITRATE UTILIZATION TEST (Simmons citrate)

Citrate as sole carbon source → alkaline pH → blue color = positive.

Result	Organisms
Positive	Klebsiella, Enterobacter, Citrobacter, Serratia, Proteus mirabilis, Salmonella (except Typhi)
Negative	E. coli, Salmonella Typhi, Shigella, Proteus vulgaris

NEET trick: E. coli = citrate negative (helps distinguish it from Klebsiella on IMViC test: E. coli = ++-- and Klebsiella = --++)

7. H₂S PRODUCTION

Blackening of iron-containing media (e.g., TSI agar).

Result	Organisms
Positive	Salmonella, Proteus, Citrobacter, Francisella tularensis (weakly)
Negative	Shigella, E. coli, Klebsiella

8. IMViC TESTS (for E. coli vs Klebsiella vs others)

Indole / Methyl Red / Voges-Proskauer / Citrate

Organism	I	M	V	C
E. coli	+	+	-	-
Klebsiella / Enterobacter	-	-	+	+
Salmonella	-	+	-	+

9. CAMP TEST

S. agalactiae (Group B Strep) and Listeria monocytogenes produce CAMP factor that enhances hemolysis of S. aureus beta-lysin.

Positive	Negative
Streptococcus agalactiae (Group B), Listeria monocytogenes	Most other streptococci

Note: Listeria CAMP test is positive but its arrow of hemolysis points TOWARDS the S. aureus streak (different pattern from S. agalactiae).

10. OPTOCHIN / BILE SOLUBILITY

Test	Positive (Sensitive)	Negative (Resistant)
Optochin	S. pneumoniae	Viridans streptococci
Bile solubility	S. pneumoniae	Viridans streptococci

11. PYR TEST (Pyrrolidonyl arylamidase)

Positive	Negative
S. pyogenes (Group A Strep), Enterococcus	Group B, C, G Strep

12. BACITRACIN SENSITIVITY

Sensitive	Resistant
Group A Strep (S. pyogenes)	Group B, C, G Strep

13. NOVOBIOCIN SENSITIVITY (for CoNS)

Sensitive	Resistant
S. epidermidis	S. saprophyticus

NEET classic: Young female with UTI, novobiocin-resistant CoNS = S. saprophyticus!

QUICK MNEMONICS

Urease+ organisms - "Proteus Helps Kill Certain Bacteria Yearly" (Proteus, H. pylori, Klebsiella, Cryptococcus, Brucella, Yersinia)

Oxidase+ gram-negatives - "Pee Never Very Carefully Haemorrhaging" (Pseudomonas, Neisseria, Vibrio, Campylobacter, Helicobacter/Haemophilus)

Catalase-negative gram-positives - All Streptococci + Enterococcus

Coagulase+ - Only S. aureus (+ S. intermedius, S. hyicus in animals)

BONUS: RAPID UREASE TEST for H. pylori

The CLO test (campylobacter-like organism test) is done on gastric biopsy. Color changes from yellow to pink/magenta = urease positive = H. pylori. The urea breath test (¹³C-UBT) works on the same principle non-invasively.

Jawetz Melnick & Adelbergs Medical Microbiology 28E (Table 3-2, Figure 3-1)
Quick Compendium of Clinical Pathology 5th Ed (Section 3.5.1)
Sherris & Ryan's Medical Microbiology 8th Ed

Create a high-yield biochemical tests identification flowchart PDF for quick revision

Reading File

Running Command

mkdir -p /tmp/workspace/biochem-flowchart && ls /tmp/workspace/biochem-flowchart/

Writing File

~/biochem-flowchart/create_pdf.py

from reportlab.lib.pagesizes import A4
from reportlab.lib import colors
from reportlab.lib.units import mm, cm
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, HRFlowable, KeepTogether
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.enums import TA_CENTER, TA_LEFT
from reportlab.platypus.flowables import Flowable
import reportlab.graphics.shapes as shapes
from reportlab.graphics import renderPDF
from reportlab.graphics.shapes import Drawing, Rect, String, Line, Polygon
from reportlab.pdfbase import pdfmetrics


# ── Color palette ────────────────────────────────────────────────────────────
C_HEADER      = colors.HexColor("#1a237e")   # deep navy
C_HEADER_BG   = colors.HexColor("#e8eaf6")   # lavender tint
C_POS_BG      = colors.HexColor("#e8f5e9")   # light green
C_POS_TEXT    = colors.HexColor("#1b5e20")   # dark green
C_NEG_BG      = colors.HexColor("#ffebee")   # light red
C_NEG_TEXT    = colors.HexColor("#b71c1c")   # dark red
C_BOX_BORDER  = colors.HexColor("#3949ab")   # indigo
C_ACCENT      = colors.HexColor("#f57f17")   # amber for tips
C_ACCENT_BG   = colors.HexColor("#fffde7")   # cream
C_MNEM_BG     = colors.HexColor("#e3f2fd")   # light blue
C_MNEM_TEXT   = colors.HexColor("#0d47a1")   # blue
C_TABLE_HEAD  = colors.HexColor("#3949ab")   # indigo
C_TABLE_ALT   = colors.HexColor("#f3f4ff")   # very light blue
C_WHITE       = colors.white
C_BLACK       = colors.HexColor("#212121")
C_GOLD        = colors.HexColor("#ff8f00")
C_SPEC_BG     = colors.HexColor("#fce4ec")   # pink tint for special organisms
C_SPEC_TEXT   = colors.HexColor("#880e4f")

# ── Page setup ───────────────────────────────────────────────────────────────
OUTPUT = "/tmp/workspace/biochem-flowchart/Biochemical_Tests_NEET_PG.pdf"
doc = SimpleDocTemplate(
    OUTPUT,
    pagesize=A4,
    rightMargin=15*mm, leftMargin=15*mm,
    topMargin=15*mm, bottomMargin=15*mm,
    title="High-Yield Biochemical Tests – NEET PG Quick Revision",
    author="Orris Medical"
)

W = A4[0] - 30*mm   # usable width

# ── Styles ───────────────────────────────────────────────────────────────────
base = getSampleStyleSheet()

def style(name, parent="Normal", **kw):
    s = ParagraphStyle(name, parent=base[parent])
    for k, v in kw.items():
        setattr(s, k, v)
    return s

sTitle = style("sTitle", "Title",
               fontSize=20, textColor=C_HEADER,
               alignment=TA_CENTER, spaceAfter=4,
               fontName="Helvetica-Bold")
sSubtitle = style("sSubtitle",
               fontSize=11, textColor=colors.HexColor("#5c6bc0"),
               alignment=TA_CENTER, spaceAfter=2,
               fontName="Helvetica")
sSectionHead = style("sSectionHead",
               fontSize=13, textColor=C_WHITE,
               alignment=TA_LEFT, leading=18,
               fontName="Helvetica-Bold",
               leftIndent=6, spaceAfter=0, spaceBefore=0)
sCell = style("sCell", fontSize=9, leading=13,
              fontName="Helvetica", textColor=C_BLACK)
sCellBold = style("sCellBold", fontSize=9, leading=13,
                  fontName="Helvetica-Bold", textColor=C_BLACK)
sCellPos = style("sCellPos", fontSize=9, leading=13,
                 fontName="Helvetica-Bold", textColor=C_POS_TEXT)
sCellNeg = style("sCellNeg", fontSize=9, leading=13,
                 fontName="Helvetica-Bold", textColor=C_NEG_TEXT)
sTip = style("sTip", fontSize=9, leading=13,
             fontName="Helvetica-Oblique", textColor=colors.HexColor("#e65100"),
             leftIndent=8)
sMnem = style("sMnem", fontSize=9, leading=13,
              fontName="Helvetica-Bold", textColor=C_MNEM_TEXT,
              leftIndent=8)
sBody = style("sBody", fontSize=9, leading=13,
              fontName="Helvetica", textColor=C_BLACK)
sFooter = style("sFooter", fontSize=7.5, textColor=colors.grey,
                alignment=TA_CENTER, fontName="Helvetica-Oblique")


# ── Helper: section header ───────────────────────────────────────────────────
def section_header(num, title, color=C_HEADER):
    data = [[Paragraph(f"<b>{num}. {title}</b>", sSectionHead)]]
    t = Table(data, colWidths=[W])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), color),
        ("ROWPADDING", (0,0), (-1,-1), 5),
        ("TOPPADDING", (0,0), (-1,-1), 6),
        ("BOTTOMPADDING", (0,0), (-1,-1), 6),
        ("ROUNDEDCORNERS", [4,4,4,4]),
    ]))
    return t

def tip_box(text, bg=C_ACCENT_BG, text_color="#e65100"):
    tip_style = style(f"tip_{hash(text)}", fontSize=9, leading=13,
                      fontName="Helvetica-Oblique",
                      textColor=colors.HexColor(text_color))
    data = [[Paragraph(f"★  {text}", tip_style)]]
    t = Table(data, colWidths=[W])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), colors.HexColor(bg) if isinstance(bg, str) else bg),
        ("ROWPADDING", (0,0), (-1,-1), 4),
        ("TOPPADDING", (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("BOX", (0,0), (-1,-1), 0.5, colors.HexColor("#f57f17")),
        ("ROUNDEDCORNERS", [3,3,3,3]),
    ]))
    return t

def mnem_box(text):
    data = [[Paragraph(f"🔑  {text}", sMnem)]]
    t = Table(data, colWidths=[W])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (-1,-1), C_MNEM_BG),
        ("ROWPADDING", (0,0), (-1,-1), 4),
        ("TOPPADDING", (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("BOX", (0,0), (-1,-1), 0.5, colors.HexColor("#1565c0")),
    ]))
    return t

def main_table(headers, rows, col_widths, pos_col=None, neg_col=None):
    """Build a styled data table."""
    # header row
    header_row = [Paragraph(f"<b>{h}</b>",
                  style(f"th_{i}", fontSize=9, fontName="Helvetica-Bold",
                        textColor=C_WHITE, alignment=TA_CENTER))
                  for i, h in enumerate(headers)]
    data = [header_row]
    for row in rows:
        formatted = []
        for ci, cell in enumerate(row):
            if ci == 0:
                formatted.append(Paragraph(str(cell), sCellBold))
            elif pos_col and ci == pos_col:
                formatted.append(Paragraph(str(cell), sCellPos))
            elif neg_col and ci == neg_col:
                formatted.append(Paragraph(str(cell), sCellNeg))
            else:
                formatted.append(Paragraph(str(cell), sCell))
        data.append(formatted)

    t = Table(data, colWidths=col_widths, repeatRows=1)
    style_cmds = [
        ("BACKGROUND", (0,0), (-1,0), C_TABLE_HEAD),
        ("TEXTCOLOR", (0,0), (-1,0), C_WHITE),
        ("ALIGN", (0,0), (-1,-1), "LEFT"),
        ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
        ("ROWPADDING", (0,0), (-1,-1), 4),
        ("TOPPADDING", (0,0), (-1,-1), 5),
        ("BOTTOMPADDING", (0,0), (-1,-1), 5),
        ("GRID", (0,0), (-1,-1), 0.4, colors.HexColor("#c5cae9")),
        ("ROWBACKGROUNDS", (0,1), (-1,-1), [C_WHITE, C_TABLE_ALT]),
    ]
    t.setStyle(TableStyle(style_cmds))
    return t


# ═══════════════════════════════════════════════════════════════════════════
# BUILD CONTENT
# ═══════════════════════════════════════════════════════════════════════════
story = []
sp = lambda n=4: Spacer(1, n)

# ── Cover banner ─────────────────────────────────────────────────────────────
banner_data = [[
    Paragraph("HIGH-YIELD BIOCHEMICAL TESTS", sTitle),
    Paragraph("NEET PG  |  Quick Revision Flowchart  |  Microbiology", sSubtitle),
]]
banner = Table([[Paragraph("HIGH-YIELD BIOCHEMICAL TESTS", sTitle)],
                [Paragraph("NEET PG  ·  Quick Revision Flowchart  ·  Microbiology", sSubtitle)]],
               colWidths=[W])
banner.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (-1,-1), C_HEADER_BG),
    ("ROWPADDING", (0,0), (-1,-1), 6),
    ("BOX", (0,0), (-1,-1), 1.5, C_BOX_BORDER),
    ("TOPPADDING", (0,0), (0,0), 10),
    ("BOTTOMPADDING", (0,-1), (-1,-1), 10),
]))
story.append(banner)
story.append(sp(8))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 1 – CATALASE
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(1, "CATALASE TEST  (H₂O₂ → H₂O + O₂)  |  Bubbles = Positive"))
story.append(sp(3))
story.append(main_table(
    ["Result", "Organisms", "Key Notes"],
    [
        ["POSITIVE ✓",
         "Staphylococcus spp., Bacillus, Listeria, Nocardia,\nAspergillus, most Enterobacteriaceae",
         "Gram-positive cocci: separates Staph from Strep"],
        ["NEGATIVE ✗",
         "All Streptococci, Enterococcus,\nClostridium, Bacteroides",
         "Gram-positive cocci: all Strep are catalase –"],
    ],
    col_widths=[W*0.18, W*0.48, W*0.34],
    pos_col=0
))
story.append(sp(3))
story.append(tip_box("NEET CLASSIC: Catalase POSITIVE = Staph   |   Catalase NEGATIVE = Strep  (most tested distinction!)"))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 2 – COAGULASE
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(2, "COAGULASE TEST  (Fibrinogen → Fibrin)  |  Done after Catalase +ve confirmed"))
story.append(sp(3))
story.append(main_table(
    ["Result", "Organism", "Clinical Importance"],
    [
        ["POSITIVE ✓", "Staphylococcus aureus", "Major pathogen – skin, SSTI, endocarditis, osteomyelitis, TSS"],
        ["NEGATIVE ✗", "S. epidermidis, S. saprophyticus (CoNS)", "S. saprophyticus = UTI in young women"],
        ["SPECIAL ⚠", "S. lugdunensis", "Slide coagulase + but tube coagulase –; mimics S. aureus clinically!"],
    ],
    col_widths=[W*0.18, W*0.32, W*0.50],
    pos_col=0
))
story.append(sp(3))
story.append(tip_box("S. lugdunensis: slide coagulase POSITIVE, tube coagulase NEGATIVE — favourite MCQ trap!",
                     bg=C_SPEC_BG, text_color=C_SPEC_TEXT.hexval().lstrip('#')))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 3 – OXIDASE
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(3, "OXIDASE TEST  (Cytochrome C oxidase)  |  Positive = Purple/Blue color", color=colors.HexColor("#1a237e")))
story.append(sp(3))
story.append(main_table(
    ["Result", "Organisms", "Trick"],
    [
        ["POSITIVE ✓",
         "Pseudomonas, Neisseria, Vibrio, Campylobacter,\nHelicobacter, Moraxella, Aeromonas, Brucella, Pasteurella",
         "None of these are Enterobacteriaceae"],
        ["NEGATIVE ✗",
         "ALL Enterobacteriaceae: E. coli, Klebsiella,\nSalmonella, Shigella, Proteus, Serratia, Enterobacter",
         "Oxidase –ve = Enterobacteriaceae (key rule!)"],
    ],
    col_widths=[W*0.18, W*0.52, W*0.30],
    pos_col=0
))
story.append(sp(3))
story.append(mnem_box("Mnemonic: 'Pee Never Very Carefully Haemorrhaging'  →  Pseudomonas, Neisseria, Vibrio, Campylobacter, Helicobacter/Haemophilus"))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 4 – UREASE
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(4, "UREASE TEST  (Urea → NH₃ + CO₂)  |  Positive = Pink/Red (alkaline pH)", color=colors.HexColor("#4a148c")))
story.append(sp(3))
story.append(main_table(
    ["Speed", "Organisms", "Clinical Relevance"],
    [
        ["Rapid+ (< 4 h)",
         "Proteus spp., H. pylori, Ureaplasma urealyticum,\nCryptococcus neoformans",
         "H. pylori → CLO test, Urea Breath Test (UBT);\nProteus → struvite kidney stones"],
        ["Slow/Weak+",
         "Klebsiella, Pseudomonas, Brucella,\nYersinia enterocolitica, Helicobacter",
         "Klebsiella – weakly positive"],
        ["NEGATIVE ✗",
         "E. coli, Salmonella, Shigella, Streptococci",
         "Helps distinguish from Proteus/Klebsiella"],
    ],
    col_widths=[W*0.22, W*0.42, W*0.36],
))
story.append(sp(3))
story.append(mnem_box("Mnemonic: 'Proteus Helps Kill Certain Bacteria Yearly'  →  Proteus, H. pylori, Klebsiella, Cryptococcus, Brucella, Yersinia"))
story.append(sp(3))
story.append(tip_box("CLO test (campylobacter-like organism test) = rapid urease test on gastric biopsy → yellow→pink/magenta = H. pylori +ve"))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 5 – INDOLE
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(5, "INDOLE TEST  (Tryptophan → Indole)  |  Red color with Kovacs reagent = Positive", color=colors.HexColor("#01579b")))
story.append(sp(3))
story.append(main_table(
    ["Result", "Organisms", "Notes"],
    [
        ["POSITIVE ✓",
         "E. coli, Proteus vulgaris, Vibrio cholerae, Klebsiella oxytoca",
         "E. coli – used for quick ID in urine culture"],
        ["NEGATIVE ✗",
         "Proteus mirabilis, K. pneumoniae, Salmonella, most Shigella",
         "P. mirabilis vs P. vulgaris – classic MCQ pair"],
    ],
    col_widths=[W*0.18, W*0.47, W*0.35],
    pos_col=0
))
story.append(sp(3))
story.append(tip_box("P. vulgaris = Indole POSITIVE  |  P. mirabilis = Indole NEGATIVE  (high-yield pair!)"))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 6 – IMViC TABLE
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(6, "IMViC TESTS  (Indole / Methyl Red / Voges-Proskauer / Citrate)", color=colors.HexColor("#1b5e20")))
story.append(sp(3))

imvic_data = [
    [Paragraph("<b>Organism</b>", sCellBold),
     Paragraph("<b>Indole (I)</b>", sCellBold),
     Paragraph("<b>Methyl Red (M)</b>", sCellBold),
     Paragraph("<b>Voges-Proskauer (V)</b>", sCellBold),
     Paragraph("<b>Citrate (C)</b>", sCellBold)],
    [Paragraph("E. coli", sCell),
     Paragraph("+", sCellPos), Paragraph("+", sCellPos),
     Paragraph("−", sCellNeg), Paragraph("−", sCellNeg)],
    [Paragraph("Klebsiella / Enterobacter", sCell),
     Paragraph("−", sCellNeg), Paragraph("−", sCellNeg),
     Paragraph("+", sCellPos), Paragraph("+", sCellPos)],
    [Paragraph("Salmonella", sCell),
     Paragraph("−", sCellNeg), Paragraph("+", sCellPos),
     Paragraph("−", sCellNeg), Paragraph("+ (not Typhi)", sCell)],
    [Paragraph("Shigella", sCell),
     Paragraph("−", sCellNeg), Paragraph("+", sCellPos),
     Paragraph("−", sCellNeg), Paragraph("−", sCellNeg)],
    [Paragraph("Proteus mirabilis", sCell),
     Paragraph("−", sCellNeg), Paragraph("+", sCellPos),
     Paragraph("−", sCellNeg), Paragraph("+", sCellPos)],
    [Paragraph("Proteus vulgaris", sCell),
     Paragraph("+", sCellPos), Paragraph("+", sCellPos),
     Paragraph("−", sCellNeg), Paragraph("−", sCellNeg)],
]
imvic_t = Table(imvic_data, colWidths=[W*0.32, W*0.17, W*0.17, W*0.17, W*0.17])
imvic_t.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (-1,0), C_TABLE_HEAD),
    ("TEXTCOLOR", (0,0), (-1,0), C_WHITE),
    ("ALIGN", (1,0), (-1,-1), "CENTER"),
    ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
    ("ROWPADDING", (0,0), (-1,-1), 4),
    ("TOPPADDING", (0,0), (-1,-1), 5),
    ("BOTTOMPADDING", (0,0), (-1,-1), 5),
    ("GRID", (0,0), (-1,-1), 0.4, colors.HexColor("#c5cae9")),
    ("ROWBACKGROUNDS", (0,1), (-1,-1), [C_WHITE, C_TABLE_ALT]),
]))
story.append(imvic_t)
story.append(sp(3))
story.append(tip_box("E. coli = + + − −   |   Klebsiella/Enterobacter = − − + +   (mirror image!)"))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 7 – CITRATE
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(7, "CITRATE UTILIZATION (Simmons)  |  Blue = Positive  (citrate = sole carbon source)", color=colors.HexColor("#006064")))
story.append(sp(3))
story.append(main_table(
    ["Result", "Organisms"],
    [
        ["POSITIVE ✓", "Klebsiella, Enterobacter, Citrobacter, Serratia, Proteus mirabilis, Salmonella (except Typhi)"],
        ["NEGATIVE ✗", "E. coli, Salmonella Typhi, Shigella, Proteus vulgaris"],
    ],
    col_widths=[W*0.18, W*0.82],
    pos_col=0
))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 8 – H2S
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(8, "H₂S PRODUCTION  |  Black precipitate on TSI / SIM agar = Positive", color=colors.HexColor("#37474f")))
story.append(sp(3))
story.append(main_table(
    ["Result", "Organisms", "Note"],
    [
        ["POSITIVE ✓", "Salmonella, Proteus, Citrobacter, Francisella (weak)", "Key in TSI agar identification"],
        ["NEGATIVE ✗", "Shigella, E. coli, Klebsiella", "Shigella vs Salmonella: Salmonella H₂S+, Shigella H₂S−"],
    ],
    col_widths=[W*0.18, W*0.45, W*0.37],
    pos_col=0
))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 9 – GRAM-POSITIVE SPECIAL TESTS
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(9, "GRAM-POSITIVE IDENTIFICATION TESTS", color=colors.HexColor("#880e4f")))
story.append(sp(3))

gp_data = [
    [Paragraph("<b>Test</b>", sCellBold),
     Paragraph("<b>Sensitive / Positive</b>", sCellBold),
     Paragraph("<b>Resistant / Negative</b>", sCellBold),
     Paragraph("<b>Clinical Use</b>", sCellBold)],
    [Paragraph("Optochin", sCell),
     Paragraph("S. pneumoniae ✓", sCellPos),
     Paragraph("Viridans Streptococci ✗", sCellNeg),
     Paragraph("Distinguishes S. pneumoniae from Viridans strep", sCell)],
    [Paragraph("Bile Solubility", sCell),
     Paragraph("S. pneumoniae ✓", sCellPos),
     Paragraph("Viridans Streptococci ✗", sCellNeg),
     Paragraph("Confirmatory for S. pneumoniae", sCell)],
    [Paragraph("Bacitracin", sCell),
     Paragraph("Group A Strep (S. pyogenes) ✓", sCellPos),
     Paragraph("Group B, C, G Strep ✗", sCellNeg),
     Paragraph("ID of S. pyogenes (Group A)", sCell)],
    [Paragraph("PYR Test", sCell),
     Paragraph("S. pyogenes (Grp A), Enterococcus ✓", sCellPos),
     Paragraph("Group B, C, G Strep ✗", sCellNeg),
     Paragraph("More specific than Bacitracin", sCell)],
    [Paragraph("CAMP Test", sCell),
     Paragraph("S. agalactiae (Grp B), Listeria ✓", sCellPos),
     Paragraph("Other Strep ✗", sCellNeg),
     Paragraph("Listeria: arrowhead pointing TOWARDS streak", sCell)],
    [Paragraph("Novobiocin", sCell),
     Paragraph("S. epidermidis (Sensitive) ✓", sCellPos),
     Paragraph("S. saprophyticus (Resistant) ✗", sCellNeg),
     Paragraph("Young female UTI → S. saprophyticus (resistant)", sCell)],
    [Paragraph("6.5% NaCl growth", sCell),
     Paragraph("Enterococcus ✓", sCellPos),
     Paragraph("Streptococcus ✗", sCellNeg),
     Paragraph("Distinguishes Enterococcus from Strep", sCell)],
]
gp_t = Table(gp_data, colWidths=[W*0.18, W*0.26, W*0.25, W*0.31])
gp_t.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (-1,0), C_TABLE_HEAD),
    ("TEXTCOLOR", (0,0), (-1,0), C_WHITE),
    ("ALIGN", (0,0), (-1,-1), "LEFT"),
    ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
    ("ROWPADDING", (0,0), (-1,-1), 4),
    ("TOPPADDING", (0,0), (-1,-1), 5),
    ("BOTTOMPADDING", (0,0), (-1,-1), 5),
    ("GRID", (0,0), (-1,-1), 0.4, colors.HexColor("#f8bbd0")),
    ("ROWBACKGROUNDS", (0,1), (-1,-1), [C_WHITE, C_SPEC_BG]),
]))
story.append(gp_t)
story.append(sp(3))
story.append(tip_box("S. saprophyticus = Novobiocin RESISTANT — young female with uncomplicated UTI (classic NEET scenario!)"))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 10 – TSI AGAR PATTERNS
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(10, "TRIPLE SUGAR IRON (TSI) AGAR PATTERNS", color=colors.HexColor("#1a237e")))
story.append(sp(3))

tsi_data = [
    [Paragraph("<b>Organism</b>", sCellBold),
     Paragraph("<b>Slant</b>", sCellBold),
     Paragraph("<b>Butt</b>", sCellBold),
     Paragraph("<b>Gas</b>", sCellBold),
     Paragraph("<b>H₂S</b>", sCellBold)],
    [Paragraph("E. coli", sCell),
     Paragraph("A (yellow)", sCellPos),
     Paragraph("A (yellow)", sCellPos),
     Paragraph("+", sCellPos),
     Paragraph("−", sCellNeg)],
    [Paragraph("Salmonella", sCell),
     Paragraph("K (red/alk)", sCellNeg),
     Paragraph("A (yellow)", sCellPos),
     Paragraph("+", sCellPos),
     Paragraph("+", sCellPos)],
    [Paragraph("Shigella", sCell),
     Paragraph("K (red/alk)", sCellNeg),
     Paragraph("A (yellow)", sCellPos),
     Paragraph("−", sCellNeg),
     Paragraph("−", sCellNeg)],
    [Paragraph("Klebsiella", sCell),
     Paragraph("A (yellow)", sCellPos),
     Paragraph("A (yellow)", sCellPos),
     Paragraph("++", sCellPos),
     Paragraph("−", sCellNeg)],
    [Paragraph("Pseudomonas", sCell),
     Paragraph("K (alk)", sCellNeg),
     Paragraph("K (alk)", sCellNeg),
     Paragraph("−", sCellNeg),
     Paragraph("−", sCellNeg)],
    [Paragraph("Proteus", sCell),
     Paragraph("K (red/alk)", sCellNeg),
     Paragraph("A (yellow)", sCellPos),
     Paragraph("+", sCellPos),
     Paragraph("+", sCellPos)],
]
tsi_t = Table(tsi_data, colWidths=[W*0.30, W*0.20, W*0.20, W*0.15, W*0.15])
tsi_t.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (-1,0), C_TABLE_HEAD),
    ("TEXTCOLOR", (0,0), (-1,0), C_WHITE),
    ("ALIGN", (1,0), (-1,-1), "CENTER"),
    ("VALIGN", (0,0), (-1,-1), "MIDDLE"),
    ("ROWPADDING", (0,0), (-1,-1), 4),
    ("TOPPADDING", (0,0), (-1,-1), 5),
    ("BOTTOMPADDING", (0,0), (-1,-1), 5),
    ("GRID", (0,0), (-1,-1), 0.4, colors.HexColor("#c5cae9")),
    ("ROWBACKGROUNDS", (0,1), (-1,-1), [C_WHITE, C_TABLE_ALT]),
]))
story.append(tsi_t)
story.append(sp(3))
story.append(tip_box("A = Acid (yellow)  |  K = Alkaline (red/pink)  |  Salmonella & Proteus: K/A + H₂S (classic!)"))
story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 11 – QUICK SUMMARY FLOWCHART (Text-based)
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(11, "MASTER IDENTIFICATION FLOWCHART (Text)", color=colors.HexColor("#212121")))
story.append(sp(3))

flowchart_steps = [
    ("GRAM STAIN", "First step always", "#1a237e", C_WHITE),
    ("GRAM +ve COCCI", "→ CATALASE TEST", "#4caf50", C_WHITE),
    ("Catalase POSITIVE", "→ Staphylococcus → COAGULASE TEST:\n  Coagulase + = S. aureus\n  Coagulase − = CoNS (S. epidermidis, etc.)\n  Novobiocin test for CoNS: Resistant = S. saprophyticus", "#388e3c", C_WHITE),
    ("Catalase NEGATIVE", "→ Streptococcus / Enterococcus → HEMOLYSIS + OPTOCHIN/BACITRACIN:\n  β-hemolytic + Bacitracin S = S. pyogenes (Grp A)\n  β-hemolytic + CAMP+ = S. agalactiae (Grp B)\n  α-hemolytic + Optochin S = S. pneumoniae\n  α-hemolytic + Optochin R = Viridans Strep\n  6.5% NaCl growth = Enterococcus", "#c62828", C_WHITE),
    ("GRAM −ve RODS", "→ OXIDASE TEST", "#1565c0", C_WHITE),
    ("Oxidase NEGATIVE", "→ Enterobacteriaceae → IMViC + TSI + Urease + H₂S\n  E. coli (I+ M+ V− C−, Urease−)\n  Klebsiella (I− M− V+ C+, Urease+)\n  Salmonella (I− M+ V− C+, H₂S+)\n  Shigella (I− M+ V− C−, H₂S−)\n  Proteus mirabilis (I− Urease++, H₂S+, Swarming)\n  Proteus vulgaris (I+ Urease+)", "#0d47a1", C_WHITE),
    ("Oxidase POSITIVE", "→ Non-Enterobacteriaceae GNR:\n  Pseudomonas (non-fermenter, green pigment, grape odor)\n  Vibrio (curved rod, NaCl requirement)\n  Campylobacter (microaerophilic, comma-shaped)\n  Neisseria (diplococcus, not rod)", "#6a1b9a", C_WHITE),
]

for step, detail, bg_hex, txt_color in flowchart_steps:
    step_style = style(f"fs_{step[:5]}", fontSize=10, fontName="Helvetica-Bold",
                       textColor=txt_color if txt_color == C_WHITE else C_BLACK)
    detail_style = style(f"fd_{step[:5]}", fontSize=8.5, fontName="Helvetica",
                         textColor=colors.HexColor("#37474f"), leading=13)
    row_data = [[Paragraph(f"<b>{step}</b>", step_style),
                 Paragraph(detail, detail_style)]]
    t = Table(row_data, colWidths=[W*0.26, W*0.74])
    t.setStyle(TableStyle([
        ("BACKGROUND", (0,0), (0,-1), colors.HexColor(bg_hex)),
        ("BACKGROUND", (1,0), (1,-1), colors.HexColor("#f5f5f5")),
        ("VALIGN", (0,0), (-1,-1), "TOP"),
        ("ROWPADDING", (0,0), (-1,-1), 5),
        ("TOPPADDING", (0,0), (-1,-1), 6),
        ("BOTTOMPADDING", (0,0), (-1,-1), 6),
        ("BOX", (0,0), (-1,-1), 0.5, colors.HexColor("#bdbdbd")),
        ("GRID", (0,0), (-1,-1), 0.3, colors.HexColor("#e0e0e0")),
    ]))
    story.append(t)
    story.append(sp(2))

story.append(sp(6))

# ════════════════════════════════════════════════════════════════════════════
# SECTION 12 – MNEMONICS BOX
# ════════════════════════════════════════════════════════════════════════════
story.append(section_header(12, "HIGH-YIELD MNEMONICS AT A GLANCE", color=colors.HexColor("#e65100")))
story.append(sp(3))

mnem_rows = [
    ("Urease+ organisms",
     "Proteus Helps Kill Certain Bacteria Yearly\n→ Proteus, H. pylori, Klebsiella, Cryptococcus, Brucella, Yersinia"),
    ("Oxidase+ gram-negatives",
     "Pee Never Very Carefully Haemorrhaging\n→ Pseudomonas, Neisseria, Vibrio, Campylobacter, Helicobacter"),
    ("Catalase negative gram+",
     "All Streptococci + Enterococcus = Catalase NEGATIVE"),
    ("Coagulase+",
     "Only S. aureus (among clinically relevant Staphylococci)"),
    ("S. saprophyticus",
     "Young female + uncomplicated UTI + Novobiocin RESISTANT = S. saprophyticus"),
    ("Optochin rule",
     "S. pneumoniae = Optochin SENSITIVE = 'PnOSitive for Optochin'"),
    ("Indole pair",
     "P. vulgaris = Indole +   vs   P. mirabilis = Indole −"),
    ("IMViC mirror",
     "E. coli = + + − −   vs   Klebsiella = − − + +  (complete mirror)"),
]

m_data = [[Paragraph("<b>Topic</b>", sCellBold), Paragraph("<b>Mnemonic / Rule</b>", sCellBold)]]
for topic, mnem in mnem_rows:
    m_data.append([Paragraph(topic, sCellBold), Paragraph(mnem, sCell)])

m_t = Table(m_data, colWidths=[W*0.28, W*0.72])
m_t.setStyle(TableStyle([
    ("BACKGROUND", (0,0), (-1,0), colors.HexColor("#bf360c")),
    ("TEXTCOLOR", (0,0), (-1,0), C_WHITE),
    ("ALIGN", (0,0), (-1,-1), "LEFT"),
    ("VALIGN", (0,0), (-1,-1), "TOP"),
    ("ROWPADDING", (0,0), (-1,-1), 4),
    ("TOPPADDING", (0,0), (-1,-1), 5),
    ("BOTTOMPADDING", (0,0), (-1,-1), 5),
    ("GRID", (0,0), (-1,-1), 0.4, colors.HexColor("#ffccbc")),
    ("ROWBACKGROUNDS", (0,1), (-1,-1), [C_WHITE, colors.HexColor("#fff3e0")]),
]))
story.append(m_t)
story.append(sp(8))

# ════════════════════════════════════════════════════════════════════════════
# FOOTER
# ════════════════════════════════════════════════════════════════════════════
story.append(HRFlowable(width=W, thickness=0.5, color=colors.HexColor("#9fa8da")))
story.append(sp(3))
story.append(Paragraph(
    "High-Yield Biochemical Tests – NEET PG Quick Revision  |  Sources: Jawetz Medical Microbiology 28E, Sherris & Ryan 8E, Quick Compendium of Clinical Pathology 5E",
    sFooter
))

# ════════════════════════════════════════════════════════════════════════════
# BUILD PDF
# ════════════════════════════════════════════════════════════════════════════
doc.build(story)
print(f"PDF created: {OUTPUT}")

Running Command

cd /tmp/workspace/biochem-flowchart && python create_pdf.py 2>&1

Running Command

ls -lh /tmp/workspace/biochem-flowchart/Biochemical_Tests_NEET_PG.pdf

Your PDF is ready! Download it here:

Biochemical Tests NEET PG

PDF Document · PDF

Here is what's inside the PDF (12 color-coded sections, A4, print-ready):

Section	Content
1	Catalase Test - Positive vs Negative organisms, key rule
2	Coagulase Test - S. aureus, CoNS, S. lugdunensis trap
3	Oxidase Test - All oxidase+ organisms, Enterobacteriaceae rule
4	Urease Test - Rapid vs slow positives, CLO test, struvite stones
5	Indole Test - P. vulgaris vs P. mirabilis classic pair
6	IMViC Table - E. coli vs Klebsiella vs Salmonella vs Shigella
7	Citrate Utilization - Positive vs Negative organisms
8	H₂S Production - TSI agar patterns
9	Gram-Positive Tests - Optochin, Bacitracin, PYR, CAMP, Novobiocin, NaCl
10	TSI Agar Patterns - Slant/Butt/Gas/H₂S for all major organisms
11	Master Flowchart - Gram stain → Catalase → Coagulase → Oxidase → IMViC decision tree
12	High-Yield Mnemonics - All key mnemonics in one box

Color coding: green = positive results, red = negative results, amber = NEET tips, blue = mnemonics.

Prepapre poster card for revision with simple notes about laryngeal muscles and nv supply and function Vocal cords important points

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