Every Chapter Four guide you have opened assumes a questionnaire: a bio-data table, a four-point mean against 2.50, a chi-square. You have thirty plates, a grid of biochemical reactions and a page of zone diameters in millimetres. The chapter is not harder than the questionnaire version. It is four tables in a fixed order, and each one has a sentence pattern that turns a measurement into a finding.
What Chapter Four is when your data came off a plate
A microbiology project produces measurements, not opinions, and the chapter is organised by what was measured rather than by research question alone. Nigerian departments accept the same four-table spine for almost every undergraduate topic in the field, whether you sampled sachet water, ready-to-eat food from a campus canteen, hospital door handles, urine specimens or wound swabs. Table one gives the counts: how much grew, per millilitre or per gram, by sample or by location. Table two gives the identification: the colonial and microscopic appearance and the biochemical reactions that let you name each isolate. Table three gives frequency: how many of each organism, and what percentage of the total that is. Table four gives the antibiotic susceptibility: a zone diameter in millimetres for every isolate against every disc, and beside it the letter that interprets it. A plant extract project replaces table four with zones at graded concentrations plus a minimum inhibitory concentration, but the spine does not change. Write the tables in that order, number them Table 4.1 upward, and give each one a title that names the variable and the source, not the word Results.
The counts table and the identification grid
The counts table carries one number per sample with its unit written into the column heading, not into every cell: colony-forming units per millilitre for a liquid, per gram for a solid, per square centimetre for a swabbed surface. Report the dilution factor you multiplied by in the table note, because a panel member will ask, and give the mean of your replicate plates rather than one plate chosen because it counted nicely. If your topic implies a limit, compare against it explicitly and cite the document and its edition: the Standards Organisation of Nigeria publishes a drinking water standard your department will hold a copy of, and a food or water topic that never compares its counts to a stated limit has produced numbers instead of a finding.
The identification grid is the table students most often build wrongly, because they present it as prose. It is a matrix: isolate codes down the left, and across the top the colonial morphology, Gram reaction, cell shape, then one column per biochemical test you actually ran, and a final column headed Probable organism. Catalase, coagulase, oxidase, indole, citrate, urease, motility, triple sugar iron and the sugar fermentations are the usual set. Fill the cells with plus and minus signs, not sentences, and state in the text below which key you read them against; Bergey’s Manual of Determinative Bacteriology is the reference Nigerian departments expect to see cited for conventional identification, and naming it is what converts a grid of symbols into an identification you can defend. Write probable organism, not confirmed organism, unless you ran a confirmatory method, and say so in Chapter Five as a limitation.
The susceptibility table, and the standard you read it against
A zone diameter on its own means nothing. Twenty millimetres is susceptible for one organism and drug pair and resistant for another, and the only thing that makes your table interpretable is a named breakpoint document with its edition. Two exist, and a Nigerian student can use either, but must use one of them consistently and say which in Chapter Three.
| Document | What it is | Current edition | Cost | Method it assumes |
|---|---|---|---|---|
| CLSI M100 | Performance Standards for Antimicrobial Susceptibility Testing, published by the Clinical and Laboratory Standards Institute | 36th edition, published 26 January 2026 | Purchased from CLSI | Valid only if the procedures in CLSI M02 for disk diffusion, M07 for dilution in aerobes and M11 for anaerobes were followed |
| EUCAST breakpoint tables | Clinical breakpoint tables of the European Committee on Antimicrobial Susceptibility Testing | v16.1, valid 24 June 2026 to 31 December 2026 | Free to download | EUCAST disk diffusion and MIC methodology, with its own dosages document at v16.0 effective 1 January 2026 |
CLSI M02, the disk diffusion standard the M100 tables depend on, is in its fourteenth edition, published 19 March 2024. If your laboratory ran Kirby-Bauer on Mueller-Hinton agar and read the zones with a ruler or callipers, you followed a CLSI-shaped method and M100 is the natural table to interpret against; if your department has no current copy, the free EUCAST tables are the honest alternative, and using them is not a weakness provided Chapter Three says the EUCAST methodology was followed rather than silently mixing the two. The commonest single error in a Nigerian microbiology Chapter Four is a susceptibility table interpreted against a breakpoint document that is never named, or named without an edition or version. Write it in full once, in Chapter Three, and refer to it by name under every susceptibility table thereafter.
The second commonest error is the letter I. Under EUCAST, since 2019, I no longer means intermediate: the committee redefined it so that a microorganism is categorised as susceptible, increased exposure when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection. If you are using EUCAST tables, write the category out in words the first time and do not gloss it as intermediate anywhere in the chapter. A panel member from a clinical microbiology background will notice, and it is the cheapest correction you will ever make.
The MAR index: one calculation that upgrades the whole chapter
If you tested each isolate against a panel of antibiotics, you already hold the data for the multiple antibiotic resistance index, and computing it costs one column. For each isolate, divide the number of antibiotics to which it was resistant by the total number tested. An isolate resistant to six of ten discs has an index of 0.6. The convention comes from Krumperman’s 1983 paper in Applied and Environmental Microbiology, which proposed indexing to identify high-risk sources of faecal contamination and set the threshold above which a source is treated as high risk at 0.2. The reference in APA form is Krumperman, P. H. (1983). Multiple antibiotic resistance indexing of Escherichia coli to identify high-risk sources of fecal contamination of food. Applied and Environmental Microbiology, 46(1), 165 to 170.
The index earns its place because it converts a wall of letters into one number per isolate that a reader can compare, and because the threshold gives you a claim: isolates above 0.2 came from environments where antibiotics are heavily used, which for a sachet water or street food topic is the whole argument of your Chapter Five. Add the column to your susceptibility table, add a sentence stating how many isolates exceeded the threshold and what proportion of the total that is, and the discussion writes itself. For a project on the antibacterial activity of a plant extract the equivalent upgrade is the pair of endpoints: the minimum inhibitory concentration, the lowest concentration of extract at which no visible growth appeared in the tube or well, and the minimum bactericidal concentration, established by subculturing the clear tubes onto fresh agar and reporting the lowest concentration that produced no growth on the plate. Report both in the same unit, usually milligrams per millilitre, and state the solvent and the negative control, because an extract dissolved in dimethyl sulfoxide needs a solvent-only control before any zone you measured belongs to the plant.
Writing the discussion: three moves under every table
Nigerian departments differ on whether the discussion sits inside Chapter Four or opens Chapter Five, so follow your own department’s format, but the moves are the same wherever it lives. Move one restates the result in words with the number in it, without repeating the whole table: the highest mean count was recorded in samples from the motor park, at a figure you quote once. Move two compares it with published work, and this is where a microbiology discussion is won or lost, because the comparison must be with studies on the same organism from a comparable setting, and Nigerian journals are where those live. The African Journal of Clinical and Experimental Microbiology and the microbiology titles hosted on African Journals Online carry the isolation-and-susceptibility studies from Nigerian states that your examiner has read; a discussion that compares a Kano sachet water result only with European clinical isolates reads as though the literature search stopped at the first search engine page. Move three explains the difference, in one sentence, with a mechanism rather than a shrug: a higher resistance rate than an earlier study in the same state is attributable to something nameable, and if you cannot name it, say the design cannot separate the possibilities and put that in the limitations. The same discipline in stating findings applies here as anywhere, and the ladder of how strongly you can state a finding is worth reading before you write the word proves.
Two structural points that panels raise every session. First, every table needs the interpretation paragraph beneath it, and the general architecture of that paragraph is set out in the guide to writing Chapter Four table by table; the microbiology version simply substitutes a count or a zone for a mean. Second, if you ran any inferential test, name it and its assumption: comparing mean counts across three sampling sites is an analysis of variance, and comparing resistance frequency between two sources is a chi-square on counts, never on percentages. The decision table in the guide to choosing a statistical test covers both. Many microbiology projects report only descriptive statistics, which is acceptable when the objectives were framed descriptively, but a project whose objectives promise a comparison and then delivers only percentages will be asked why at the defence, and the inventory of questions panels actually ask lists that one under methodology.
Carrying it into Chapter Five
The summary in Chapter Five is built from your table titles, one sentence each, in the order the tables appeared. The conclusion answers each objective in turn: whether the samples were contaminated, which organisms predominated, and what the susceptibility profile means for treatment or for the safety of the product. Recommendations must be addressed to named bodies, which in a microbiology project are usually regulators, hospital infection control committees, vendors or the state ministry of health, not the vague public. The contribution to knowledge is the one your panel examines hardest, and for an isolation-and-susceptibility project it is almost always local and current: a susceptibility profile for a named organism from a named source in a named location at a stated date, which did not exist before you produced it. The structure of the whole chapter is set out in the guide to writing Chapter Five section by section, and the sister case of an engineering project with laboratory rather than survey data is worked through in what goes in Chapter Four when there is no questionnaire.
Where Tesify fits when the plates are read and the chapter is blank
The laboratory work is finished and the writing is what is left, which is the part that takes weeks you no longer have. Paste your counts, your identification grid and your zone diameters into Tesify and it drafts the presentation paragraph under each table in the pattern above, the interpretation sentence that names the breakpoint document and the category, and the three-move discussion for each finding with the comparison left open for the Nigerian study you choose to cite. The automatic bibliography formats Krumperman, the standards and the journal articles in your department’s style so the reference list stops being an evening’s work, and the AI editor tightens the prose without touching a figure. The free plan is the entry point and asks for no card. Everything it produces is drafted from the numbers you measured, which is the only version you can stand behind when a panel member points at Table 4.4 and asks how you arrived at that letter.
Turn your plates and zones into Chapter Four this week
Start on the free plan, paste your counts, identification grid and susceptibility readings, and get the tables, the interpretation paragraphs and the discussion moves drafted in the order your department expects.
Frequently asked questions
What goes in Chapter Four of a microbiology project?
Four tables in order: colony counts with their units, the isolate identification grid of morphology and biochemical reactions, the frequency and percentage of each organism, and the antibiotic susceptibility table of zone diameters with their interpreted categories. Each table carries an interpretation paragraph beneath it.
Which breakpoints should I use, CLSI or EUCAST?
Either, provided you use one consistently and name it with its edition in Chapter Three. CLSI M100 is in its 36th edition, published 26 January 2026, and is purchased; the EUCAST clinical breakpoint tables at v16.1 are free to download and valid to 31 December 2026.
Does I mean intermediate in a susceptibility table?
Not under EUCAST. Since 2019 the category means susceptible, increased exposure, defined as a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection. Write it out in words rather than glossing it as intermediate.
How do I calculate the multiple antibiotic resistance index?
Divide the number of antibiotics to which an isolate was resistant by the total number tested. An isolate resistant to six of ten discs scores 0.6. Following Krumperman’s 1983 paper, an index above 0.2 marks the sample as coming from a high-risk source.
Do I need statistical tests in a microbiology project?
Only if your objectives promise a comparison. Descriptive percentages are acceptable for a purely descriptive objective, but an objective that compares sites or sources needs an analysis of variance on means or a chi-square on counts, never on percentages.
Can I say I identified an organism if I only ran biochemical tests?
Write probable organism and name the key you read the reactions against, usually Bergey’s Manual of Determinative Bacteriology. Conventional identification without a confirmatory method belongs in Chapter Five as a stated limitation, which panels accept when it is declared.
What do I report for a plant extract project?
Zones of inhibition at each concentration, the minimum inhibitory concentration as the lowest concentration with no visible growth, and the minimum bactericidal concentration from subculturing the clear tubes. State the solvent and include a solvent-only negative control.
Where do I find Nigerian studies to compare my results with?
The African Journal of Clinical and Experimental Microbiology and the microbiology titles hosted on African Journals Online carry isolation and susceptibility studies from Nigerian states, which are the comparable settings your examiner expects to see in the discussion.
How much does Tesify cost?
The free plan is the entry point and needs no card. Paid plan prices are shown on the Tesify site, where local payment options are listed.