Bibliographic record
Abstract
In what some researchers believe to be one of the biggest cellular migrations in the 3.5-billion-year history of Earth, cyanobacteria armed with unique photosynthesizing capabilities used their predators as vehicles to carry them beyond the planet’s ancient oceans onto land, where, together with their hosts, they gave rise to plants. Cyanobacteria are now every place you look, coloring plant leaves green on land and floating wild in the seas. Today, bacteria not only travel far and wide, but they also go deep. For example, a diverse array of these biochemically clever little cells, along with their sister prokaryotes, the Archaea, have recently been discovered alive and well in a subglacial lake 800 meters below the West Antarctic Ice Sheet. “We don’t know the absolute age of the ecosystem, but the lake has been there for at least centuries,” says Brent Christner at Louisiana State University, in Baton Rouge. Christner and 26 colleagues from around the world used direct sequencing and other approaches to characterize the ecology of water and sediments from subglacial Lake Whillans and revealed a previously hidden microbial community, as they described in the 21 August 2014 issue of Nature. “Water enters and exits the lake so microbes and nutrients are continuously available. Although the lake may be isolated from the atmosphere, it has ample opportunity to interact with the hydrologic and sedimentary systems beneath the Antarctic ice sheet,” Christner explains. “This work provides a glimpse of the [rich] microbial life that lurks under more than 5 million square miles of ice,” he adds. The results of another innovative study using deep sequencing show that modern bacteria are able to colonize new—albeit considerably smaller— spaces within days, not decades. Jack A. Gilbert, at the University of Chicago, in Chicago, Illinois, leading an international scientific team, recently tracked the microbiology of seven ethnically diverse families and their homes over a 6-week period. Indoor environments harbor distinct microbial fingerprints that reflect the microbiomes of their occupants, report the researchers. They also discovered that a bacterial takeover occurred within a day or two of a change in human tenants: The new microbiomes quickly superseded any existing competitive microbial colonization, according to Gilbert. “Bacteria are experts at adapting to just about any ecological niche and thriving despite overwhelming adversity,” Jiadong Chen and Susan Gottesman wrote in the 22 August 2014 issue of Science magazine. “The successful bacterium doesn’t waste valuable resources such as RNA and protein for unnecessary processes and this requires the ability to sense and respond to changing conditions,” they noted. RNA-based regulation plays an important role in this sensing ability of bacteria, according to Danielle A. Garsin, at the University of Texas Health Center at Houston. Garsin and her colleagues have spent the past eight years working out the biochemical and genetic mechanisms of an integrated RNA-based bacterial switching system that turns the pathway for the use of a nutrient called ethanolamine on and off. When ethanolamine is sensed in the environment, a regulatory protein turns the nutrient’s degrading system on, and its bits and pieces are used as food. However, when coenzyme B12, a vitamin derivative that helps degrade ethanolamine, is not available but the nutrient itself is, a small regulatory RNA (sRNA) blocks the synthesis of ethanolamine-degrading proteins (which without a coenzyme to help would be a waste) and acts as an off switch, according to Garsin. It also appears that, when B12 is available, it binds to the sRNA and shortens it. The shortened sRNA can no longer block expression of ethanolamine-degradation genes; “thus, the proteins that degrade ethanolamine are generated,” Garsin explains. Such multiple levels of RNA regulation are not unexpected, conclude Chen and Gottesman, who expect many more to be found. RNAist Ronald Breaker at Yale University explains that, in contrast to other known noncoding RNAs, riboswitches form binding pockets that hold specific metabolites tight. However, he notes that “today’s riboswitches compete for binding with proteins which are very common and also can have higher affinity and greater specificity, making them an excellent option for evolving new sensors. Thus, a protein rather than RNA will most likely be tapped by a cell when a new metabolite-sensing factor is needed for gene control.” The fact that metabolic-binding riboswitches are widespread in the face of fierce competition from proteins is evidence that RNA evolved first, making it likely that cyanobacteria as well as all the other bacteria colonizing Earth today inherited some of their most sophisticated biochemical skills from long-ago ancestors in the RNA world. “Thus, it’s not only possible, it’s probable, that the riboswitches we see in modern cells are distant relatives of the metabolite-binding RNAs present before the evolution of proteins,” Breaker asserts.
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 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 | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.011 |
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; both teacher heads agree on what is shown here.
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".