Current knowledge and perspectives of Paenibacillus: a review
Bibliographic record
Abstract
Isolated from a wide range of sources, the genus Paenibacillus comprises bacterial species relevant to humans, animals, plants, and the environment. Many Paenibacillus species can promote crop growth directly via biological nitrogen fixation, phosphate solubilization, production of the phytohormone indole-3-acetic acid (IAA), and release of siderophores that enable iron acquisition. They can also offer protection against insect herbivores and phytopathogens, including bacteria, fungi, nematodes, and viruses. This is accomplished by the production of a variety of antimicrobials and insecticides, and by triggering a hypersensitive defensive response of the plant, known as induced systemic resistance (ISR). Paenibacillus-derived antimicrobials also have applications in medicine, including polymyxins and fusaricidins, which are nonribosomal lipopeptides first isolated from strains of Paenibacillus polymyxa. Other useful molecules include exo-polysaccharides (EPS) and enzymes such as amylases, cellulases, hemicellulases, lipases, pectinases, oxygenases, dehydrogenases, lignin-modifying enzymes, and mutanases, which may have applications for detergents, food and feed, textiles, paper, biofuel, and healthcare. On the negative side, Paenibacillus larvae is the causative agent of American Foulbrood, a lethal disease of honeybees, while a variety of species are opportunistic infectors of humans, and others cause spoilage of pasteurized dairy products. This broad review summarizes the major positive and negative impacts of Paenibacillus: its realised and prospective contributions to agriculture, medicine, process manufacturing, and bioremediation, as well as its impacts due to pathogenicity and food spoilage. This review also includes detailed information in Additional files 1, 2, 3 for major known Paenibacillus species with their locations of isolation, genome sequencing projects, patents, and industrially significant compounds and enzymes. Paenibacillus will, over time, play increasingly important roles in sustainable agriculture and industrial biotechnology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".