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Record W4385358759 · doi:10.1242/jeb.246347

Muscle boosts tobacco hornworm immunity, but at a cost

2023· article· en· W4385358759 on OpenAlexaboutno aff
Kathryn Knight

Bibliographic record

VenueJournal of Experimental Biology · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicInvertebrate Immune Response Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsManduca sextaCreaturesBiologyTollImmunityImmune systemTask (project management)InsectNeuroscienceImmunologyEcologyManagement

Abstract

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Multi-tasking is in all parts of our lives, from fiddling with phones when walking to managing homelife and careers, but we didn't invent priority juggling. Shelley Adamo from Dalhousie University, Canada, explains that seemingly unrelated tissues can multi-task, playing pivotal roles in apparently unconnected situations. For example, the immune system of insects requires large injections of glucose when fighting an infection, but much of the essential fuel comes from an unexpected source: muscle. So how much of a toll does warding off illness take on the muscles of insects, which the creatures depend on for protection and movement? For example, when under attack, tobacco hornworms – the caterpillars of tobacco hawkmoths (Manduca sexta) – thrash from side to side. Might fighting an infection weaken the caterpillars’ muscles and their ability to stand up for themselves? Adamo and Laura McMillan, with a team of graduate students and undergraduate helpers (all from Dalhousie University), decided to find out whether mounting an immune response impacts tobacco hornworm muscles.Knowing that, in insects, infection triggers the release of immune proteins and other compounds from an organ known as the fat body (the insect equivalent of the liver), the team set out to discover whether some of the key genes involved in the infection fighting machine are switched on in muscle when tobacco hornworms suffer an infection. The team injected the caterpillars with a cocktail of dead fungus and bacteria – to trick the insects into trying to fend off an infection without making them ill – to find out what they did. Sure enough, these key genes were activated in the caterpillar muscle after the fake infection, so the muscles do contribute to the infection response. And when the team took a closer look, the muscles also showed activation of the genes encoding infection-fighting molecules that contributed to their protection. But can muscle also liberate glucose from its glycogen stores, releasing it into the insect's blood to fuel the fight?This time, the team collected the caterpillars’ muscles after injection of the pathogen cocktail and, sure enough, the amount of glycogen stored in the muscle, ready to be converted into glucose, fell significantly. The caterpillars appeared to be releasing glycogen from their muscles to fight the simulated infection. And, when the team tricked healthy caterpillars into thinking that they were being attacked by a bird, using tweezers, the insect's muscle glycogen levels crashed as they fought back. However, when they tested how much glycogen the fake-infected insects released from muscle when under attack, it was less than when the insect was fighting an infection alone, as though the muscle was holding back some of its glycogen from combating the infection in the hope of improving its strength to fend off predators (which don't hold back just because their prey is poorly).The team then checked how strong the insects were having received the mock infection by tricking them again into defending themselves against a tweezer attack. The insects that had been exposed to the fake infection were physically weaker after being pecked with tweezers and less able to fend off parasitic wasps that wanted to lay eggs on their luscious bodies. So, tobacco hornworms pay a price for co-opting their muscles to fend off infection. While they benefit from the boost to their immune response provided by glycogen from muscle, this takes a toll on the caterpillar's ability to defend itself from physical attack. This inability to defend themselves is an unintended consequence of fighting infection, when multitasking muscle steps in to provide support.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.004

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.

Opus teacher head0.026
GPT teacher head0.292
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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