16S rRNA sequencing service and the QC around a sequencing run

Scoping the work

1. Choose amplicon or genome from the question. Composition across many samples suits a marker gene survey. Strain level resolution, function and antimicrobial genes need whole genome sequencing. Deciding after sampling is the expensive route.
2. Name the region for an amplicon survey. Different variable regions give different apparent composition and different resolution, and results across regions are not comparable. Fix the region and report it with every result.
3. Run contamination controls in low biomass work. Reagents and kits carry their own bacterial DNA, which dominates low biomass samples. Extraction blanks and no template controls carried all the way through sequencing are essential rather than optional.
4. Quantify libraries properly before pooling. A pool balanced on a rough concentration gives wildly uneven read counts. Quantification by amplification or by an appropriate fluorometric method, plus a size check, is what makes a pool even.
5. Check adapter and index compatibility. Index collisions and adapter mismatches waste a run. Confirm the index set is compatible with the instrument's chemistry and with any other libraries sharing the flow cell.
6. Agree deliverables and controls in writing. Raw reads, the pipeline with versions, the reference database and its version, per sample quality metrics, and the blanks sequenced alongside. A composition table alone cannot be re-analysed.

The database is part of the result

Taxonomic assignment depends on the reference database and its version, and the same reads assigned against two databases produce different tables. That is a methodological choice, not a detail.

Report the database and version with the composition, and keep the reads so the assignment can be redone when the database improves.

Low biomass is a different discipline

Below a certain input, reagent contamination and index hopping contribute a substantial share of the reads. Studies in that regime need blanks, dedicated reagent lots and a sceptical analysis.

Decide early whether your samples are in that regime, because the controls have to be designed in rather than added later.

target sequencing and what it does not cover

target sequencing reads a chosen region deeply rather than a whole genome, which is what makes rare variant detection affordable and what makes the panel's design the limit of the experiment. Uniformity across targets and the depth at the worst covered base are the quality figures. Where the question might move outside the region, a broader assay is cheaper than two panels.

target enrichment next generation sequencing, and the two ways to do it

target enrichment next generation sequencing is either hybridisation capture with baits, which tolerates larger regions and gives even coverage, or amplicon based, which needs less input and is faster but carries primer bias. Input amount and sample quality usually decide between them. Duplicate rates and on target percentage are what a provider should report per sample.

custom probes and what a design has to specify

custom probes for capture or for in situ work are specified by the target region, the melting temperature window, the modification and the purification, and a design is only as good as its specificity check against the whole genome. Probe pooling and the balance between probes decide coverage evenness. Lot to lot documentation matters for anything that will be repeated.

one step qpcr and where the convenience costs something

one step qpcr does reverse transcription and amplification in the same tube, which reduces handling and contamination risk at the cost of a compromise buffer and no option to re-use the complementary DNA for another target. For a single assay on many samples it is the right choice; for a panel across one precious sample the two step route gives more per extraction.

sgrna libraries and the coverage they need

sgrna libraries are specified by guides per gene, vector format and whether they knock out, inhibit or activate, and coverage at every step from plasmid to surviving cells is what makes a hit list believable. Representation is reported as cells per guide. A library amplified carelessly loses its balance, which is why the amplification protocol travels with it.

crispr cas12a and how it differs

crispr cas12a uses a different protospacer requirement and leaves staggered cuts rather than blunt ones, and it processes its own guide RNA, which is what makes multiplexed arrays simpler than with the more common nuclease. For a laboratory the practical consequences are the target site choice and the different repair outcomes, so an editing protocol is not transferable between the two.

synthetic oligonucleotides and what varies between orders

synthetic oligonucleotides differ by scale, purification, modification and quality control, and the same sequence at two purities behaves differently in a sensitive assay. Full length yield falls with length, so a long oligonucleotide is dominated by purification rather than by scale. Mass confirmation is worth specifying for anything modified, since a coupling failure is invisible in a gel.

Common questions

Does a 16S rRNA sequencing service tell you what the community does?

No. It tells you what is there, at a resolution set by the region chosen. Function requires whole genome or transcriptome sequencing, and inferring it from composition is an estimate rather than a measurement.

Why sequence blanks?

Because extraction kits and reagents carry bacterial DNA that can dominate a low biomass sample. Without blanks carried through the whole process, contaminant taxa are indistinguishable from real ones.

Why are my read counts so uneven?

Library quantification before pooling, usually. Rough concentration measurements do not account for adapter ligation efficiency or fragment size, and the pool ends up unbalanced.

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