Extensive Profiling of a Complex Microbial Community by High-Throughput Sequencing
Bibliographic record
Abstract
Complex microbial communities remain poorly characterized despite their ubiquity and importance to human and animal health, agriculture, and industry. Attempts to describe microbial communities by either traditional microbiological methods or molecular methods have been limited in both scale and precision. The availability of genomics technologies offers an unprecedented opportunity to conduct more comprehensive characterizations of microbial communities. Here we describe the application of an established molecular diagnostic method based on the chaperonin-60 sequence, in combination with high-throughput sequencing, to the profiling of a microbial community: the pig intestinal microbial community. Four libraries of cloned cpn60 sequences were generated by two genomic DNA extraction procedures in combination with two PCR protocols. A total of 1,125 cloned cpn60 sequences from the four libraries were sequenced. Among the 1,125 cloned cpn60 sequences, we identified 398 different nucleotide sequences encoding 280 unique peptide sequences. Pairwise comparisons of the 398 unique nucleotide sequences revealed a high degree of sequence diversity within the library. Identification of the likely taxonomic origins of cloned sequences ranged from imprecise, with clones assigned to a taxonomic subclass, to precise, for cloned sequences with 100% DNA sequence identity with a species in our reference database. The compositions of the four libraries were compared and differences related to library construction parameters were observed. Our results indicate that this method is an alternative to 16S rRNA sequence-based studies which can be scaled up for the purpose of performing a potentially comprehensive assessment of a given microbial community or for comparative studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".