Evidence map›Paper›PMID 38358316›Full record

ArticleMicrobial genomics2024

A novel synthetic nucleic acid mixture for quantification of microbes by mNGS.

Hailing Wanghu, Yingzhen Li, Jin Huang, Kangze Pu, Fengming Guo, Peiwen Zhong, Ting Wang, Jianying Yuan, Yan Yu, Jiachang Chen and 3 more

Abstract read
In one paragraph

Article in Microbial genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Observational
  4. Article
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

13 authors.

Hailing WanghuGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Yingzhen LiGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Jin HuangGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Kangze PuGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Fengming GuoGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Peiwen ZhongGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Ting WangGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Jianying YuanGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Yan YuChangsha KingMed Diagnostics Group Co., Ltd., Changsha, Huna, 410000, PR China.
Jiachang ChenGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Jun LiuGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Jason J ChenGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.
Chaohui HuGuangzhou KingCreate Biotechnology Co., Ltd., Guangzhou, Guangdong, 510005, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metagenomic next-generation sequencing (mNGS) provides considerable advantages in identifying emerging and re-emerging, difficult-to-detect and co-infected pathogens; however, the clinical application of mNGS remains limited primarily due to the lack of quantitative capabilities. This study introduces a novel approach, KingCreate-Quantification (KCQ) system, for quantitative analysis of microbes in clinical specimens by mNGS, which co-sequence the target DNA extracted from the specimens along with a set of synthetic dsDNA molecules used as Internal-Standard (IS). The assay facilitates the conversion of microbial reads into their copy numbers based on IS reads utilizing a mathematical model proposed in this study. The performance of KCQ was systemically evaluated using commercial mock microbes with varying IS input amounts, different proportions of human genomic DNA, and at varying amounts of sequence analysis data. Subsequently, KCQ was applied in microbial quantitation in 36 clinical specimens including blood, bronchoalveolar lavage fluid, cerebrospinal fluid and oropharyngeal swabs. A total of 477 microbe genetic fragments were screened using the bioinformatic system. Of these 83 fragments were quantitatively compared with digital droplet PCR (ddPCR), revealing a correlation coefficient of 0.97 between the quantitative results of KCQ and ddPCR. Our study demonstrated that KCQ presents a practical approach for the quantitative analysis of microbes by mNGS in clinical samples.

Indexed as

Nucleic AcidsBronchoalveolar Lavage FluidComputational BiologyDNAHigh-Throughput Nucleotide SequencingHumansDNANucleic Acidsinternal-standardsmicrobial quantificationmNGS

Identifiers

PMID38358316
PMCPMC10926700

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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.