Magnetotactic Bacteria: Isolation, Imaging, and Biomineralization
Bibliographic record
Abstract
Magnetotactic bacteria (MTB) are a specialized group of bacteria that produce very small magnets inside their cells.There are a number of reasons that I decided to study these particular microorganisms.MTB are universally found in aquatic environments and they can be isolated with a simple magnet.These bacteria have the distinct ability to synthesize nanometer-scale crystals of magnetite (Fe 3 O 4 ) or greigite (Fe 3 S 4 ) inside their cells.This type of biomineralization serves as a model for mineral formation in more complex organisms such as birds, bees, and fish.The magnetite from MTB can be used as a biomarker, called magnetofossils, for past life on earth as well as possible extraterrestrial life forms (e.g., putative magnetofossils in Martian meteorites such as the Allan Hills meteorite).Magnetofossils are novel biomarkers because the magnetite from MTB has a specific crystal shape, narrow size range, and flawless chemical composition, which make them easily identified as biological origin.These same crystallographic attributes could also be exploited in biomimicry.For example, in vitro synthesis of magnetic crystals could have applications in medicine, electronic storage devices, and even environmental remediation.The work in this dissertation touches on all of these concepts.For the environmental isolation of MTB, I collected water samples from two field sites, an arsenic-rich hot spring in Oregon (Mickey Hot Spring) and a freshwater, microbialite-containing lake in British Columbia, Canada (Pavilion Lake).These sites were selected because MTB have never been isolated from these locations, and these two iii sites are often used as proxies for conditions on the early Earth or extraterrestrial bodies.To isolate MTB from these two samples, I used a relatively simple method that takes advantage of a bar magnet and capillary racetrack created using a cotton-plugged glass pipette.The MTB from Mickey Hot Spring in Oregon were rod to vibrioid-shaped cells that were 2.2 (± 0.6) µm long and 0.62 (± 0.1) µm wide.The magnetosomes were composed of bullet-shaped crystals of magnetite that were 84 (± 17) nm long and 39 (± 8) nm wide.These magnetosomes from the Mickey Hot Spring specimens were usually arranged in a single chain.The 16S rRNA gene sequence analysis identified the Mickey Hot Spring specimens as part of the Nitrospirae phylum.MTB isolated from Lake Pavilion in British Columbia were spirillum-shaped cells that were 2.9 (± 0.6) µm long 0.34 (± 0.02) µm wide (n = 7).Their magnetite crystals were 47 (± 5) nm long and 44 (± 5) nm wide.The magnetosomes were arranged in a single chain.The 16S rRNA analysis showed that the Lake Pavilion cells were from the Alphaproteobacteria phylum.After isolating MTB from two different environments, I turned my attention to the biomineralization of magnetite within MTB.For this portion of my dissertation, I examined a protein called Mms-6, which has recently been shown to play a key role in the nucleation and/or growth of magnetite.I used high-resolution transmission electron microscopy (TEM) to examine gold-conjugated, immunolabeled Mms-6 in thin sections of Magnetospirillum magneticum AMB-1.I found that the Mms-6 proteins are not located on the cell membrane or within the cytoplasm, but are only clustered on the magnetosome membrane.This was confirmed by using confocal laser scanning microscopy on Mms-6 proteins labeled with green fluorescence proteins in cells of M. after 75 months of doing my PhD it is hard to remember everyone.Steven Lower and Brian Lower for advising me, providing me with support and giving me the opportunity
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".