The viriosphere: the greatest biological diversity on Earth and driver of global processes
Bibliographic record
Abstract
The future is at least as opaque to me as it is to others, but even to a non-clairvoyant it is becoming apparent that a new paradigm is unfolding that incorporates viruses into the global ecosystem and its processes. From an earlier perspective of viruses as purveyors of disease and tools of genetic engineering we have realized that viruses are the most abundant ‘life forms’ on Earth, are crucial cogs in the biosphere and likely harbour its greatest genetic diversity. We can be certain that the relationship between viruses and other organisms is very ancient, and in the case of bacteriophages likely predates the evolution of eukaryotes. Although fossils of tailed phages have yet to be found, we can speculate that they predate photosynthesis. Tailed phages infect both heterotrophic bacteria and cyanobacteria, consistent with their existence before the cyanobacterial divergence. Hence, life on our world originally consisted of prokaryotes and their phage predators. The phage kept populations in check, maintained biological diversity through selective mortality, recycled nutrients by cell lysis and facilitated genetic exchange via transduction and through corrupted viral replication. It is becoming abundantly clear that the viriosphere extends to every surface of the planet, to the deepest depths of the oceans and far below the Earth's surface. Metagenomic approaches reveal a stunning array of virus-associated genetic diversity (Breitbart et al., 2002) of which only a third has recognizable similarity to reported sequences. In contrast, metagenomic data from marine prokaryotic communities have much higher similarity to deposited sequences. Similarly, gene-targeted approaches suggest the sea contains a plethora of previously unknown virus families (Culley et al., 2003). Equally striking are observations (Van Etten et al., 2002) that some aquatic viruses infecting microalgae contain putative genes that are most similar to other viruses, bacteria, archaea and eukaryotes, all on the same genome! What is the significance of the tremendous abundance of viruses and the massive diversity of virus-encoded genetic information? I suspect that viruses may be an archive of all genetic information on Earth. Aquatic systems will likely provide the platform to address these questions. There also needs to be a concerted effort to increase our knowledge of viruses and viral-mediated processes in terrestrial systems, and look beyond their well-established roles as causative agents of disease. It is clear through studies of turnover of viral particles and visibly infected cells that a significant proportion of the prokaryotic and protist communities are lost to viral lysis daily. Yet, there is a dearth of quantitative data on the impact of viral-mediated cell lysis on nutrient release and recycling even though culture studies and back-of-the-envelope modelling efforts suggest this is quantitatively an extremely important process. Moreover, nutrients released through viral lysis will be compositionally different and consequently have a different fate than other mechanisms of nutrient regeneration. For example, one would expect virus-released metals and macronutrients to be organically complexed. This will increase availability to some organisms and decrease availability to others. Over the next few years I expect we will see dedicated attempts to quantify the fate of nutrient release via viral lysis, and its impact on ecosystems. Unlike losses resulting from grazing, viral mediated mortality is typically strain specific, with only a small subset of any given species being susceptible to lysis by a given virus strain. This has led to the tenet that viruses maintain species diversity by selectively killing the most abundant strains, because of the higher encounter rates. Although an attractive hypothesis, there is scant evidence that this is the case, and some studies suggest that rapid selection for resistance results in little effect on community composition. Undoubtedly there will be (or at least should be) research dedicated to untangling the relative importance of viral lysis on mortality and community structure. Finally, we need to multiply our efforts to begin to document the genetic richness in natural virus communities. This should not be restricted to tailed bacteriophages, but should include other DNA and RNA viruses. We need to isolate far more viruses from the environment and sequence them, so we can begin to make sense of the metagenomic data. The few environmental virus isolates that have been sequenced have often proven to be very different than other characterized viruses. I am optimistic that in the next few years, significant progress will be made on all these fronts.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".