Evidence map›Paper›PMID 42587116›Full record

ReviewNature2026

Shared principles of human and bacterial antiviral immunity.

Philip J Kranzusch

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Philip J KranzuschDepartment of Microbiology, Harvard Medical School, Boston, MA, USA. philip_kranzusch@dfci.harvard.edu.ORCID http://orcid.org/0000-0002-4943-733X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Defence against viral infection is a conserved feature of all cellular life. From single-cell bacteria to humans and complex multicellular animals, constitutive and inducible forms of immunity are required to inhibit viruses and safeguard cellular fitness. Recent studies reveal that the components of human antiviral immunity are surprisingly ancient, originating billions of years ago in bacteria as pathways that defend against phage replication. The unification of previously disparate fields of human and bacterial immunity creates a foundation to explain key features of host-virus interactions. This Review defines principles of pathogen recognition, signal amplification and immune effector function that shape mechanisms of antiviral immunity that are shared across kingdoms of life. Shared forms of immunity, including cGAS-STING, inflammasomes, argonautes and viperin, reveal ancient features of antiviral defence. Similarly, direct comparisons of pattern recognition receptors and interferon-stimulated genes in human cells with CRISPR immunity and anti-phage defence systems in bacteria explain prevalent strategies to effectively sense and inhibit viral replication. Cross-kingdom analysis reveals universal rules that control host-virus interactions and highlights open questions in understanding of antiviral immunity.

Indexed as

BacteriaHost-Pathogen InteractionsImmunity, InnateVirus DiseasesVirusesAnimalscGAS-STING Signaling PathwayCyclic Guanosine Monophosphate-Adenosine Monophosphate SynthaseHumansInflammasomesInnate Immunity RecognitionMembrane ProteinsNucleotidyltransferasesReceptors, Pattern RecognitionSTING ProteinViperin ProteincGAS protein, humanCyclic Guanosine Monophosphate-Adenosine Monophosphate SynthaseInflammasomesMembrane ProteinsNucleotidyltransferasesReceptors, Pattern RecognitionSTING1 protein, humanSTING ProteinViperin Protein

Identifiers

PMID42587116

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.