Droplet Encoding‐Pairing Enabled Multiplexed Digital Loop‐Mediated Isothermal Amplification for Simultaneous Quantitative Detection of Multiple Pathogens Article Swipe
Dongyang Cai
,
Yu Wang
,
Jingjing Zou
,
Zhujun Li
,
Enqi Huang
,
Xiuyun Ouyang
,
Zhiquan Que
,
Yanzhang Luo
,
Zhenhua Chen
,
Yanqing Jiang
,
Guohao Zhang
,
Hongkai Wu
,
Dayu Liu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1002/advs.202205863
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1002/advs.202205863
Despite the advantages of digital nucleic acid analysis (DNAA) in terms of sensitivity, precision, and resolution, current DNAA methods commonly suffer a limitation in multiplexing capacity. To address this issue, a droplet encoding‐pairing enabled DNAA multiplexing strategy is developed, wherein unique tricolor combinations are deployed to index individual primer droplets. The template droplets and primer droplets are sequentially introduced into a microfluidic chip with a calabash‐shaped microwell array and are pairwise trapped and merged in the microwells. Pre‐merging and post‐amplification image analysis with a machine learning algorithm is used to identify, enumerate, and address the droplets. By incorporating the amplification signals with droplet encoding information, simultaneous quantitative detection of multiple targets is achieved. This strategy allows for the establishment of flexible multiplexed DNAA by simply adjusting the primer droplet library. Its flexibility is demonstrated by establishing two multiplexed (8‐plex) droplet digital loop‐mediated isothermal amplification (mddLAMP) assays for individually detecting lower respiratory tract infection and urinary tract infection causative pathogens. Clinical sample analysis shows that the microbial detection outcomes of the mddLAMP assays are consistent with those of the conventional assay. This DNAA multiplexing strategy can achieve flexible high‐order multiplexing on demand, making it a desirable tool for high‐content pathogen detection.
Related Topics
Concepts
Loop-mediated isothermal amplification
Multiplexing
Pairing
Encoding (memory)
Loop (graph theory)
Isothermal process
Biological system
Computational biology
Computer science
Chemistry
Physics
Biology
Genetics
Telecommunications
DNA
Mathematics
Thermodynamics
Artificial intelligence
Quantum mechanics
Combinatorics
Superconductivity
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/advs.202205863
- OA Status
- gold
- Cited By
- 34
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4316653794
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4316653794Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1002/advs.202205863Digital Object Identifier
- Title
-
Droplet Encoding‐Pairing Enabled Multiplexed Digital Loop‐Mediated Isothermal Amplification for Simultaneous Quantitative Detection of Multiple PathogensWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-16Full publication date if available
- Authors
-
Dongyang Cai, Yu Wang, Jingjing Zou, Zhujun Li, Enqi Huang, Xiuyun Ouyang, Zhiquan Que, Yanzhang Luo, Zhenhua Chen, Yanqing Jiang, Guohao Zhang, Hongkai Wu, Dayu LiuList of authors in order
- Landing page
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https://doi.org/10.1002/advs.202205863Publisher landing page
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1002/advs.202205863Direct OA link when available
- Concepts
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Loop-mediated isothermal amplification, Multiplexing, Pairing, Encoding (memory), Loop (graph theory), Isothermal process, Biological system, Computational biology, Computer science, Chemistry, Physics, Biology, Genetics, Telecommunications, DNA, Mathematics, Thermodynamics, Artificial intelligence, Quantum mechanics, Combinatorics, SuperconductivityTop concepts (fields/topics) attached by OpenAlex
- Cited by
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34Total citation count in OpenAlex
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2025: 18, 2024: 8, 2023: 8Per-year citation counts (last 5 years)
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52Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.of | 4, 12, 109, 120, 169, 177 |
| abstract_inverted_index.on | 190 |
| abstract_inverted_index.to | 46, 90 |
| abstract_inverted_index.Its | 131 |
| abstract_inverted_index.The | 51 |
| abstract_inverted_index.and | 15, 54, 69, 73, 79, 93, 154 |
| abstract_inverted_index.are | 44, 57, 70, 173 |
| abstract_inverted_index.can | 185 |
| abstract_inverted_index.for | 117, 147, 197 |
| abstract_inverted_index.the | 2, 76, 95, 99, 118, 127, 165, 170, 178 |
| abstract_inverted_index.two | 137 |
| abstract_inverted_index.DNAA | 18, 35, 123, 182 |
| abstract_inverted_index.This | 114, 181 |
| abstract_inverted_index.acid | 7 |
| abstract_inverted_index.chip | 63 |
| abstract_inverted_index.into | 60 |
| abstract_inverted_index.that | 164 |
| abstract_inverted_index.this | 29 |
| abstract_inverted_index.tool | 196 |
| abstract_inverted_index.used | 89 |
| abstract_inverted_index.with | 64, 83, 102, 175 |
| abstract_inverted_index.array | 68 |
| abstract_inverted_index.image | 81 |
| abstract_inverted_index.index | 47 |
| abstract_inverted_index.lower | 150 |
| abstract_inverted_index.shows | 163 |
| abstract_inverted_index.terms | 11 |
| abstract_inverted_index.those | 176 |
| abstract_inverted_index.tract | 152, 156 |
| abstract_inverted_index.(DNAA) | 9 |
| abstract_inverted_index.allows | 116 |
| abstract_inverted_index.assay. | 180 |
| abstract_inverted_index.assays | 146, 172 |
| abstract_inverted_index.issue, | 30 |
| abstract_inverted_index.making | 192 |
| abstract_inverted_index.merged | 74 |
| abstract_inverted_index.primer | 49, 55, 128 |
| abstract_inverted_index.sample | 161 |
| abstract_inverted_index.simply | 125 |
| abstract_inverted_index.suffer | 21 |
| abstract_inverted_index.unique | 41 |
| abstract_inverted_index.Despite | 1 |
| abstract_inverted_index.achieve | 186 |
| abstract_inverted_index.address | 28, 94 |
| abstract_inverted_index.current | 17 |
| abstract_inverted_index.demand, | 191 |
| abstract_inverted_index.digital | 5, 141 |
| abstract_inverted_index.droplet | 32, 103, 129, 140 |
| abstract_inverted_index.enabled | 34 |
| abstract_inverted_index.machine | 85 |
| abstract_inverted_index.mddLAMP | 171 |
| abstract_inverted_index.methods | 19 |
| abstract_inverted_index.nucleic | 6 |
| abstract_inverted_index.signals | 101 |
| abstract_inverted_index.targets | 111 |
| abstract_inverted_index.trapped | 72 |
| abstract_inverted_index.urinary | 155 |
| abstract_inverted_index.wherein | 40 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Clinical | 160 |
| abstract_inverted_index.analysis | 8, 82, 162 |
| abstract_inverted_index.commonly | 20 |
| abstract_inverted_index.deployed | 45 |
| abstract_inverted_index.droplets | 53, 56 |
| abstract_inverted_index.encoding | 104 |
| abstract_inverted_index.flexible | 121, 187 |
| abstract_inverted_index.learning | 86 |
| abstract_inverted_index.library. | 130 |
| abstract_inverted_index.multiple | 110 |
| abstract_inverted_index.outcomes | 168 |
| abstract_inverted_index.pairwise | 71 |
| abstract_inverted_index.pathogen | 199 |
| abstract_inverted_index.strategy | 37, 115, 184 |
| abstract_inverted_index.template | 52 |
| abstract_inverted_index.tricolor | 42 |
| abstract_inverted_index.(mddLAMP) | 145 |
| abstract_inverted_index.achieved. | 113 |
| abstract_inverted_index.adjusting | 126 |
| abstract_inverted_index.algorithm | 87 |
| abstract_inverted_index.capacity. | 26 |
| abstract_inverted_index.causative | 158 |
| abstract_inverted_index.desirable | 195 |
| abstract_inverted_index.detecting | 149 |
| abstract_inverted_index.detection | 108, 167 |
| abstract_inverted_index.droplets. | 50, 96 |
| abstract_inverted_index.identify, | 91 |
| abstract_inverted_index.infection | 153, 157 |
| abstract_inverted_index.microbial | 166 |
| abstract_inverted_index.microwell | 67 |
| abstract_inverted_index.(8‐plex) | 139 |
| abstract_inverted_index.advantages | 3 |
| abstract_inverted_index.consistent | 174 |
| abstract_inverted_index.detection. | 200 |
| abstract_inverted_index.developed, | 39 |
| abstract_inverted_index.enumerate, | 92 |
| abstract_inverted_index.individual | 48 |
| abstract_inverted_index.introduced | 59 |
| abstract_inverted_index.isothermal | 143 |
| abstract_inverted_index.limitation | 23 |
| abstract_inverted_index.pathogens. | 159 |
| abstract_inverted_index.precision, | 14 |
| abstract_inverted_index.flexibility | 132 |
| abstract_inverted_index.microwells. | 77 |
| abstract_inverted_index.multiplexed | 122, 138 |
| abstract_inverted_index.resolution, | 16 |
| abstract_inverted_index.respiratory | 151 |
| abstract_inverted_index.combinations | 43 |
| abstract_inverted_index.conventional | 179 |
| abstract_inverted_index.demonstrated | 134 |
| abstract_inverted_index.establishing | 136 |
| abstract_inverted_index.high‐order | 188 |
| abstract_inverted_index.individually | 148 |
| abstract_inverted_index.information, | 105 |
| abstract_inverted_index.microfluidic | 62 |
| abstract_inverted_index.multiplexing | 25, 36, 183, 189 |
| abstract_inverted_index.quantitative | 107 |
| abstract_inverted_index.sensitivity, | 13 |
| abstract_inverted_index.sequentially | 58 |
| abstract_inverted_index.simultaneous | 106 |
| abstract_inverted_index.Pre‐merging | 78 |
| abstract_inverted_index.amplification | 100, 144 |
| abstract_inverted_index.establishment | 119 |
| abstract_inverted_index.incorporating | 98 |
| abstract_inverted_index.high‐content | 198 |
| abstract_inverted_index.loop‐mediated | 142 |
| abstract_inverted_index.calabash‐shaped | 66 |
| abstract_inverted_index.encoding‐pairing | 33 |
| abstract_inverted_index.post‐amplification | 80 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 99 |
| corresponding_author_ids | https://openalex.org/A5010630057 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 13 |
| corresponding_institution_ids | https://openalex.org/I4210098034, https://openalex.org/I90610280 |
| citation_normalized_percentile.value | 0.9519275 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |