Table 1 Types of contamination and strategies to exclude them
A Types of contamination | ||
Class | Type | Comments |
1A | Molecular biology reagents | If contaminated, the same signal will be present in all samples |
1B | Sample contamination during dissection | Expect environmental contaminants such as spores, pollens, and skin microbes (caution, skin microbes have been implicated in several human diseases) |
2A | Lifelong in vivo biocontamination from blood and the environment | Environmental contaminants such as microparticles of the same size as spores and pollens have been demonstrated to enter tissues; microbes of a similar size rapidly enter human tissues |
2B | In vivo biocontamination: perimortem | When analyzing a tissue in relation to human disease, contamination may arise from in vivo dissemination of microbes (e.g., respiratory disease) unrelated to the primary disorder; invasion of diseased tissue may be a consequence rather than a cause of tissue degeneration |
BStrategies to exclude contaminants | ||
Method | Strategy | Comments |
Negative controls | Exclude all signals present in blank workups | Negative controls alone are not sufficient to detect all contaminating species. In addition, RNA-seq data rarely have blank controls because these are rejected as errors by the sequencing instrument |
Common contaminants | Consider excluding common contaminant species such as those listed in Salter et al. [80] and Sanabria et al. [83] | Caution is urged because common contaminant microbes may themselves be the cause of disease |
Within-batch consistency | Exclude signals that are present at similar levels in all samples | Caution is urged because, if applied to gut or lung, this would exclude many of the major species that are known to be present |
Between-batch consistency | Only include signals that are present (and at different levels) in independent datasets from the same tissue | A major caveat is that, in different individuals with the same pathology, diverse organisms can be the cause of that pathology (e.g., viruses, bacteria, and fungi can all cause inflammatory lung disease). |
Differential signals | Only include differential signals between, for example, disease samples versus controls | Consistent differential signals point unambiguously to species that are not contaminants |
Microheterogeneity | High-resolution strain/substrain mapping. Contaminants introduced during sample work-up are likely to be of the same specific genotypes in different samples, whereas true signals are most likely heterogeneous in their exact sequences | Download sequences from different samples of the target tissue and prepare phylogenetic trees |