Evidence map›Paper›PMID 42532990›Full record

ArticleNature communications2026

Rapid and quantitative measurement of bacteriophage infectivity via fully automated droplet digital PCR.

Yanfei Liu, Huiwei Zhao, Xinyue Cao, Shize Jiang, Jun Fu, Junjing Xue, Caiming Li, Zhangrun Xu, Ming Li, Wenbin Du

Abstract read
In one paragraph

Article in Nature communications, 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

10 authors.

Yanfei LiuResearch Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang, Liaoning, China.
Huiwei ZhaoState Key Laboratory of Microbial Diversity and Innovative Utilization, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China. zhaohw@im.ac.cn.ORCID 0000-0001-9993-9795
Xinyue CaoDepartment of Microbial Physiological & Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Shize JiangState Key Laboratory of Microbial Diversity and Innovative Utilization, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Jun FuMaccura Biotechnology Co., Ltd, Chengdu, China.
Junjing XueState Key Laboratory of Microbial Diversity and Innovative Utilization, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Caiming LiInstitute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore, Singapore.
Zhangrun XuResearch Center for Analytical Sciences, Department of Chemistry, College of Sciences, Northeastern University, Shenyang, Liaoning, China. xuzr@mail.neu.edu.cn.ORCID 0000-0003-3834-1145
Ming LiState Key Laboratory of Microbial Diversity and Innovative Utilization, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China. lim_im@im.ac.cn.ORCID 0000-0002-0634-8396
Wenbin DuState Key Laboratory of Microbial Diversity and Innovative Utilization, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China. wenbin@im.ac.cn.ORCID 0000-0002-7401-1410

Funding

CAS | State Key Laboratory of Microbial Resources (State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences) XDB0810000National Natural Science Foundation of China (National Science Foundation of China) 22374016National Natural Science Foundation of China (National Science Foundation of China) 32370090
6 · The paper itself

Abstract

The clinical translation of phage therapy for multidrug-resistant infections is constrained by the lack of rapid, standardized therapeutic phage selection. Here, we introduce digital phage susceptibility testing (dPhaST), an automated droplet digital PCR workflow that quantifies phage-induced DNA release as a molecular signature of lysis. By targeting conserved 16S rRNA regions, dPhaST measures lytic activity across diverse bacterial pathogens within 3 h. Across 122 phage-host combinations involving 19 bacterial strains from six species, dPhaST shows 95.9% concordance with spot tests while resolving weak and heterogeneous lytic activities that are not readily distinguished phenotypically. It remains robust during the early infection window despite phage-encoded nuclease activity and tolerates phage cross-contamination better than spot tests. The method captures defense-mediated interactions involving CRISPR-Cas and Sir2-HerA systems. In this work, we show that automated digital quantification enables rapid and mechanistically informative profiling of early phage lytic efficacy across Gram-positive and Gram-negative pathogens.

Indexed as

BacteriophagesPolymerase Chain ReactionAutomationBacteriaDNA, ViralPhage TherapyRNA, Ribosomal, 16SDNA, ViralRNA, Ribosomal, 16S

Identifiers

PMID42532990
PMCPMC13424325

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.