Startseite Rapid diagnosis of intra-amniotic infection using nanopore-based sequencing
Artikel Open Access

Rapid diagnosis of intra-amniotic infection using nanopore-based sequencing

  • Piya Chaemsaithong EMAIL logo , Roberto Romero EMAIL logo , Pisut Pongchaikul EMAIL logo , Pornpun Vivithanaporn , Waranyu Lertrut , Adithep Jaovisidha , Paninee Mongkolsuk , Perapon Nitayanon , Khontawan Pongsuktavorn , Threebhorn Kamlungkuea , Eunjung Jung , Manaphat Suksai , Arunee Singhsnaeh , Piroon Jenjaroenpun EMAIL logo , Iyarit Thaipisuttikul EMAIL logo und Thidathip Wongsurawat EMAIL logo
Veröffentlicht/Copyright: 13. Dezember 2022

Abstract

Objectives

Early diagnosis and treatment of intra-amniotic infection is crucial. Rapid pathogen identification allows for a definite diagnosis and enables proper management. We determined whether the 16S amplicon sequencing performed by a nanopore sequencing technique make possible rapid bacterial identification at the species level in intra-amniotic infection.

Methods

Five cases of confirmed intra-amniotic infection, determined by either cultivation or 16S rDNA polymerase chain reaction (PCR) Sanger sequencing, and 10 cases of women who underwent mid-trimester genetic amniocentesis were included. DNA was extracted from amniotic fluid and PCR was performed on the full-length 16S rDNA. Nanopore sequencing was performed. The results derived from nanopore sequencing were compared with those derived from cultivation and Sanger sequencing methods.

Results

Bacteria were successfully detected from amniotic fluid using nanopore sequencing in all cases of intra-amniotic infection. Nanopore sequencing identified additional bacterial species and polymicrobial infections. All patients who underwent a mid-trimester amniocentesis had negative cultures, negative 16S PCR Sanger sequencing and nanopore sequencing. Identification of the microorganisms using nanopore sequencing technique at the bacterial species level was achieved within 5–9 h from DNA extraction.

Conclusions

This is the first study demonstrating that the nanopore sequencing technique is capable of rapid diagnosis of intra-amniotic infection using fresh amniotic fluid samples.

Introduction

The amniotic cavity is normally sterile, and microbial invasion elicits an inflammatory response in patients with spontaneous preterm labor [1], cervical insufficiency [2], and clinical chorioamnionitis at term [3], among other obstetrical syndromes. Intra-amniotic inflammation is defined by an elevation of the interleukin-6 (IL-6) concentration (IL-6 ≥2.6 ng/mL), and intra-amniotic infection is a combination of demonstrable microorganisms in the amniotic cavity and intra-amniotic inflammation [1]. The accurate diagnosis of infection requires identification of microorganisms from samples obtained from the suspected infection site, and in clinical medicine, this is accomplished with cultivation techniques, which have remained the gold standard for microbial identification for more than 100 years [4]. However, the result of a culture takes days to become available, and this delay has been a major obstacle for the successful and timely treatment of intra-amniotic infection in obstetrics and other infections, virtually in every field of medicine. Molecular microbiologic techniques promise to address this problem by analysis of nucleic acids of microorganisms. The most widely used approach is the combination of the polymerase chain reaction (PCR) of the conserved region of the microbial genomes, also known as 16S rDNA PCR (16S ribosomal DNA), and of sequencing of the amplicon to identify genus and specificity. However, this technique generally takes days. Nanopore sequencing has recently emerged as a unique scalable method that enables direct real-time analysis of long DNA fragments, thus making possible rapid identification of bacteria, viruses, or fungi with great specificity [5, 6]. This technology has been successfully used to diagnose infection based on sequencing of organisms grown in culture, pus, cerebrospinal fluid, blood, as well as prosthetic devices [7]. The present study was conducted to determine whether nanopore sequencing can identify bacteria directly from amniotic fluid of patients suspected to have intra-amniotic infection.

Materials and methods

Nanopore sequencing of DNA obtained from amniotic fluid samples of cases and controls was performed. The control group comprised patients who underwent genetic amniocentesis in the mid-trimester and who had a negative amniotic fluid culture and negative 16S rDNA PCR Sanger sequencing, as well as a delivery at term (n=10). Cases consisted of patients with preterm pre-labor ruptured of membranes (preterm PROM) who underwent transabdominal amniocentesis to determine the microbial state in the amniotic cavity and were found to have microorganisms by either cultivation or 16S rDNA PCR Sanger sequencing (n=5). Each patient provided written informed consent, and the use of biological specimens and clinical data for research purposes was approved by Institutional Review Boards of Faculty of Medicine Ramathibodi Hospital, Mahidol University (COA.MURA2021/254 and COA.MURA2021/968).

Background technical controls included DNA extractions performed on (1) DNA extraction kits without amniotic fluid samples; (2) extraction kits with bead tubes exposed to room air for 20 min during amniocentesis; (3) extraction kits with bead tubes exposed to conditions similar to those of amniotic fluid samples undergoing testing (i.e., alcohol, betadine, and container). Amniotic fluid IL-6 concentrations (ng/mL) were determined by enzyme-linked immunosorbent assay (ELISA; R&D Systems, Minneapolis, MN, USA). The details and performance of the ELISAs were previously described [3]. Intra-amniotic inflammation was considered to be present if the amniotic fluid IL-6 concentration was ≥2.6 ng/mL [3]. Intra-amniotic infection was defined as the presence of intra-amniotic inflammation with demonstrable microorganism in the amniotic cavity [1].

Detection of bacteria by the 16S rDNA PCR Sanger sequencing method

Amniotic fluid was centrifuged at 5,000×g, 4 °C for 10 min. Amniotic fluid supernatant was collected for IL-6 determination. The genomic DNA was extracted from 1 mL of fresh amniotic fluid using the ZymoBIOMICS kit (Zymo Research Corporation, Irvine, CA, USA) and then the genomic DNA was used as a template for amplifying full-length 16S rDNA genes. 16s rDNA PCR was performed by using 27F and 1492R primers with 35 cycles. DNA sequencing of the amplicon was determined by the Sanger method [8]. Raw DNA sequences were manually visualized and curated in BioEdit [9, 10]. Bacterial identification was performed by searching the curated DNA sequences via nucleotide BLAST [11].

Nanopore sequencing technique

The 16S Barcoding Kit (SQK-RAB204; Oxford Nanopore Technologies, Oxford, United Kingdom) [12] was used for DNA library preparation. PCR amplification was conducted with LongAmp™ Taq 2× Master Mix (New England Biolabs, Ipswich, MA, USA). Amplification was performed under the following conditions: initial denaturation at 95 °C for 1 min, 25 cycles of 95 °C for 20 s, 55 °C for 30 s, and 65 °C for 2 min, followed by a final extension at 65 °C for 5 min. The PCR product of each sample was cleaned up and concentrated with AMPure XP (Beckman Coulter, Indianapolis, IN, USA). A total of 10 μL purified DNA was used for library preparation. MinION Mk1C sequencing was performed by using R9.4.1 flow cells (ONT) [5, 13].

Bioinformatics analysis

The nanopore raw data (fast5 files) were base-called and de-multiplexed with ONT’s Guppy™ software version 6.2.1 “super accuracy” model (-c dna_r9.4.1_450 bps_sup.cfg). The adapter sequences were trimmed by using Porechop software v.2.6.0 (https://github.com/rrwick/Porechop). During data preprocessing, reads were filtered with NanoFilt to retain only near full-length 16S rDNA reads. Reads with a length below 1,000 base pairs (bp) or a Q-score below 9 were discarded. Fastq 16S workflows in the cloud-based bioinformatics platform EPI2ME identified the pathogens.

Results

The clinical characteristics of the patients are shown in Table 1. DNA samples of the background technical controls had negative cultures, negative 16S rDNA PCR Sanger sequencing and negative nanopore sequencing results. All patients in the control group (mid-trimester amniocentesis with a negative amniotic fluid culture and no evidence of microorganisms determined by 16S rDNA Sanger sequencing) had no bacteria detected by nanopore sequencing. On the other hand, using nanopore sequencing, bacterial nucleic acid was detected in all 5 patients diagnosed with intra-amniotic infection (either by cultivation or 16S rDNA Sanger sequencing). All bacterial genera identified by culture or Sanger sequencing were also detected by nanopore sequencing; however, nanopore sequencing identified additional species of bacteria in 3 of the 5 cases (case #1, #2 and #4) (Table 1).

Table 1:

Clinical characteristics of patients with intra-amniotic infection.

Patient number Diagnosis Gestational age at amniocentesis, weeks of gestation Gestational age at delivery, weeks of gestation Maternal WBC, /mm3 and C-reactive protein, mg/dL Amniotic fluid interleukin-6, ng/mL Amniotic fluid culture result 16S rDNA PCR Sanger sequencing result Nanopore sequencing result Placental histopathology
1 Preterm PROM 31+2 31+3 18,890 and 22.92 43.6 Streptococcus anginosus Streptococcus anginosus
  • Streptococcus vaginalis

  • Streptococcus intermedius

  • Streptococcus constellatus

Acute chorioamnionitis stage 2 grade 2
2 Preterm PROM 32 32 22,760 and 7.95 19.6 Streptococcus mitis Unknown
  • Streptococcus mitis

  • Streptococcus oralis

  • Peptoniphilus spp.

  • Prevotella bivia

Acute chorioamnionitis stage 2 grade 2
3 Preterm PROM 21 21+3 15,400 and 76.4 103.6 No growth Ureaplasma urealyticum
  • Ureaplasma urealyticum

Acute chorioamnionitis stage 2 grade 2
4 Preterm PROM 32+1 33+5 9,970 and 6.72 8.2 No growth Veillonella spp.
  • Veillonella montpellierensis

  • Ureaplasma parvum

  • Veillonella atypica

Acute chorioamnionitis stage 2 grade 2
5 Preterm PROM 27+4 27+4 16,530 and 70 18.2 Gardnerella vaginalis Gardnerella vaginalis Gardnerella vaginalis Acute chorioamnionitis stage 2 grade 2
  1. 16S rDNA PCR, 16S rDNA-based polymerase chain reaction; PROM, prelabor ruptured of membranes; WBC, white blood cell count. Intra-amniotic inflammation is defined as an amniotic fluid interleukin-6 concentration ≥2.6 ng/mL.

None of the patients had evidence of clinical chorioamnionitis and all patients with intra-amniotic infection had intra-amniotic inflammation, as well as acute histologic chorioamnionitis. In 2 cases (#3 and #5), there was concordance among the results of either culture or 16S rDNA PCR Sanger sequencing, and nanopore sequencing. In case #1, the culture and 16S rDNA PCR Sanger sequencing yielded Streptococcus anginosus, but nanopore sequencing identified 3 additional species: Streptococcus vaginalis, Streptococcus intermedius and Streptococcus constellatus. In case #4, culture of amniotic fluid was negative; however, 16S rDNA PCR Sanger sequencing identified Veillonella spp., and nanopore sequencing identified Veillonella montpellierensis, Veillonella atypica, and Ureaplasma parvum, which were not identified by 16S rDNA PCR Sanger sequencing or by culture.

Discussion

This is the first report of the successful use of nanopore sequencing to diagnose intra-amniotic infection. A key observation is that nanopore sequencing detected bacteria by analyzing a fresh biological sample, e.g., amniotic fluid rather than material obtained from culture. One study has reported the identification of bacteria in cerebrospinal fluid in cases of suspected meningitis [14]. Other biological specimens in which nanopore sequencing has been used for the same purpose include whole blood, plasma, serum, sputum, feces, and sonicated fluid obtained from a prosthetic joint infection [7].

Molecular sequencing-based microbial identification has allowed to improve the accuracy of diagnosis of infection by enhancing the identification of non-culturable organisms [15]. The 16S rDNA-based PCR assay, that amplifies phylogenetically informative regions of the 16S rDNA gene sequence, identifies microbes across broad taxonomic fields, including previously uncharacterized species [15]. Several generations of gene sequencing techniques have emerged over time. The most widely used is 16S amplicon sequencing by short-read technology is less optimal than long-read technology in the identification of bacteria at the species level.

Nanopore sequencing, a third-generation sequencing technique, makes possible real-time analysis. Long read technology (up to several million base pairs) allows identification of microorganisms at the species level [6, 16]. The advantages of nanopore sequencing are two-fold: the technique is faster and more sensitive than culture and it can be used when patients have been treated with antibiotics. Due to the fastidious nature of microorganisms causing intra-amniotic infection, the standard culture may take 2–7 days while nanopore sequencing identifies bacteria within 5–9 h from DNA extraction (Figure 1) [14, 17]. In the present study, nanopore sequencing identified bacterial species within 4.5 h after the DNA extraction process. However, the time required to generate results depends on the microbial burden. Importantly, nanopore sequencing can detect polymicrobial infections, which can be a challenge when using 16S rDNA PCR Sanger sequencing [5, 6]. The accessibility and portability of this sequencing technique are features that promise a timely point-of-care test to detect intra-amniotic infection in the clinical setting in order to improve the clinical care of mothers and newborns. Knowledge of the presence of bacteria and the specific species can accelerate decision-making to deliver or to administer a particular antibiotic to treat a specific microorganism. In practice, a rapid IL-6 or a rapid bedside MMP-8 test of amniotic fluid can be used for the rapid diagnosis of intra-amniotic inflammation [18], [19], [20], [21] and nanopore sequencing would allow the diagnosis of the causative microbe or, in the absence of microorganisms, sterile intra-amniotic inflammation. The knowledge of the specific microorganism could be particularly helpful to the neonatologist to select the antimicrobial agents appropriate for each particular newborn. For example, the identification of candida or genital mycoplasmas would require antibiotics not used as part of standard of care in newborn intensive care units. Further studies are needed to confirm our findings and to optimize nanopore sequencing methods for amniotic fluid samples, targeted organisms, the amount of nucleic acid isolated, the sequencing approach, and the preparation of a proper genomic DNA library.

Figure 1: 
Estimated turnaround time of each diagnostic method. The conventional bacterial cultivation usually requires 2–7 days to identify the bacteria. The 16S Sanger sequencing method usually lasts 26–32 h. The time analysis of Sanger sequencing is based on Shadi Shokralla et al. [17]. However, the time-to-result of Sanger sequencing depends on the number of samples. 16S nanopore sequencing can provide the result for the identification of intra-amniotic infection within 9 h from DNA extraction. Indeed, the nanopore and Sanger sequencing methods require approximately 3 h for 16S rRNA PCR amplification. However, the library preparation (dideoxy sequencing reaction) of 16S Sanger sequencing takes considerably longer (∼10–15 h) compared to 16S nanopore sequencing. For nanopore sequencing, the library preparation takes approximately 0.2–1.5 h as the clean PCR amplicon can be immediately attached to the rapid adaptor. Then, the library can be loaded and the analysis can be performed in real-time, which may take up to 3 h to obtain the result.
Figure 1:

Estimated turnaround time of each diagnostic method. The conventional bacterial cultivation usually requires 2–7 days to identify the bacteria. The 16S Sanger sequencing method usually lasts 26–32 h. The time analysis of Sanger sequencing is based on Shadi Shokralla et al. [17]. However, the time-to-result of Sanger sequencing depends on the number of samples. 16S nanopore sequencing can provide the result for the identification of intra-amniotic infection within 9 h from DNA extraction. Indeed, the nanopore and Sanger sequencing methods require approximately 3 h for 16S rRNA PCR amplification. However, the library preparation (dideoxy sequencing reaction) of 16S Sanger sequencing takes considerably longer (∼10–15 h) compared to 16S nanopore sequencing. For nanopore sequencing, the library preparation takes approximately 0.2–1.5 h as the clean PCR amplicon can be immediately attached to the rapid adaptor. Then, the library can be loaded and the analysis can be performed in real-time, which may take up to 3 h to obtain the result.

Conclusions

Nanopore sequencing technology is a promising method to detect intra-amniotic infection, given rapid library preparation, real-time sequencing, and simplicity. This method represents an improvement over current molecular microbiologic techniques by allowing cataloging the organisms present within complex polymicrobial bacterial communities, directly from patient specimens. The real-time technology is ideal for detecting and identifying pathogens in patients in labor and delivery units, as timing is crucial when initiating antibiotic treatment or delivery. This report is the first to demonstrate that this technique can identify bacteria from a fresh sample of amniotic fluid within 9 h from DNA extraction. In addition, nanopore sequencing is superior to traditional cultivation and 16S rDNA Sanger sequencing in several aspects, i.e., its ability to detect polymicrobial infections and non-culturable bacteria.


Corresponding authors: Piya Chaemsaithong, MD, PhD, Department of Obstetrics and Gynecology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, MI, USA; Perinatalogy Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U. S. Department of Health and Human Services, Bethesda, MD, and an Detroit, MI, USA, E-mail: ; Roberto Romero, MD, DMedSci, Perinatalogy Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, NICHD/NIH/DHHS, Hutzel Women’s Hospital, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U. S. Department of Health and Human Services, Bethesda, MD, and Detroit, MI, USA; Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, USA; Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA; Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, USA; and Detroit Medical Center, Detroit, MI, USA, Phone: (313) 993-2700, E-mail: ; Pisut Pongchaikul, MD, PhD, Faculty of Medicine Ramathibodi Hospital, Chakri Naruebodindra Medical Institute, Mahidol University, Samut Prakarn, Thailand; Integrative Computational Bioscience (ICBS) Center, Mahidol University, Nakorn Pathom, Thailand; and Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK, E-mail: ; Piroon Jenjaroenpun, PhD and Thidathip Wongsurawat, PhD, Division of Medical Bioinformatics, Department of Research, Faculty of Medicine Siriraj Hospital, Mahidol University, Thailand; and Siriraj Long-Read Lab (Si-LoL), Department of Research, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, E-mail: (P. Jenjaroenpun), (T. Wongsurawat); and Iyarit Thaipisuttikul, MD, PhD, Department of Microbiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand, E-mail:

Award Identifier / Grant number: Contract No. HHSN275201300006C

  1. Research funding: This research paper is supported by Specific League Funds from Mahidol University, Ramathibodi Funding Research RF-65048 and Faculty of Medicine Ramathibodi Hospital, Mahidol University (Decentralized funding for CNMI, RF_65090). This research was also supported, in part, by the Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services (NICHD/NIH/DHHS); and, in part, with Federal funds from NICHD/NIH/DHHS under Contract No. HHSN275201300006C. Dr. Romero has contributed to this work as part of his official duties as an employee of the United States Federal Government.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: The authors declare no conflicts of interest.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: Research involving human subjects complied with all relevant national regulations and institutional policies; is in accordance with the tenets of the Helsinki Declaration (as revised in 2013); and has been approved by the Institutional Review Boards of Faculty of Medicine Ramathibodi Hospital, Mahidol University (COA.MURA2021/254 and COA.MURA2021/968).

References

1. Romero, R, Dey, SK, Fisher, SJ. Preterm labor: one syndrome, many causes. Science 2014;345:760–5. https://doi.org/10.1126/science.1251816.Suche in Google Scholar PubMed PubMed Central

2. Lee, SE, Romero, R, Park, CW, Jun, JK, Yoon, BH. The frequency and significance of intraamniotic inflammation in patients with cervical insufficiency. Am J Obstet Gynecol 2008;198:633.e1–8. https://doi.org/10.1016/j.ajog.2007.11.047.Suche in Google Scholar PubMed

3. Romero, R, Pacora, P, Kusanovic, JP, Jung, E, Panaitescu, B, Maymon, E, et al.. Clinical chorioamnionitis at term X: microbiology, clinical signs, placental pathology, and neonatal bacteremia – implications for clinical care. J Perinat Med 2021;49:275–98. https://doi.org/10.1515/jpm-2020-0297.Suche in Google Scholar PubMed PubMed Central

4. Bonnet, M, Lagier, JC, Raoult, D, Khelaifia, S. Bacterial culture through selective and non-selective conditions: the evolution of culture media in clinical microbiology. New Microbes New Infect 2020;34:100622. https://doi.org/10.1016/j.nmni.2019.100622.Suche in Google Scholar PubMed PubMed Central

5. Brown, CG, Clarke, J. Nanopore development at Oxford nanopore. Nat Biotechnol 2016;34:810–1. https://doi.org/10.1038/nbt.3622.Suche in Google Scholar PubMed

6. Deamer, D, Akeson, M, Branton, D. Three decades of nanopore sequencing. Nat Biotechnol 2016;34:518–24. https://doi.org/10.1038/nbt.3423.Suche in Google Scholar PubMed PubMed Central

7. Zhu, X, Yan, S, Yuan, F, Wan, S. The applications of nanopore sequencing technology in pathogenic microorganism detection. Can J Infect Dis Med Microbiol 2020;2020:6675206. https://doi.org/10.1155/2020/6675206.Suche in Google Scholar PubMed PubMed Central

8. Sanger, F, Nicklen, S, Coulson, AR. DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci U S A 1977;74:5463–7. https://doi.org/10.1073/pnas.74.12.5463.Suche in Google Scholar PubMed PubMed Central

9. Hall, TA. BioEdit: a user-friendly biological sequence alignment editor and analysis program for windows 95/98/NT. Nucleic Acids Symp Ser 1999;41:95–8.Suche in Google Scholar

10. Kommedal, O, Karlsen, B, Saebo, O. Analysis of mixed sequencing chromatograms and its application in direct 16S rRNA gene sequencing of polymicrobial samples. J Clin Microbiol 2008;46:3766–71. https://doi.org/10.1128/jcm.00213-08.Suche in Google Scholar PubMed PubMed Central

11. Altschul, SF, Gish, W, Miller, W, Myers, EW, Lipman, DJ. Basic local alignment search tool. J Mol Biol 1990;215:403–10. https://doi.org/10.1016/s0022-2836(05)80360-2.Suche in Google Scholar

12. Ashton, PM, Nair, S, Dallman, T, Rubino, S, Rabsch, W, Mwaigwisya, S, et al.. MinION nanopore sequencing identifies the position and structure of a bacterial antibiotic resistance island. Nat Biotechnol 2015;33:296–300. https://doi.org/10.1038/nbt.3103.Suche in Google Scholar PubMed

13. Jain, M, Koren, S, Miga, KH, Quick, J, Rand, AC, Sasani, TA, et al.. Nanopore sequencing and assembly of a human genome with ultra-long reads. Nat Biotechnol 2018;36:338–45. https://doi.org/10.1038/nbt.4060.Suche in Google Scholar PubMed PubMed Central

14. Moon, J, Kim, N, Kim, TJ, Jun, JS, Lee, HS, Shin, HR, et al.. Rapid diagnosis of bacterial meningitis by nanopore 16S amplicon sequencing: a pilot study. Int J Med Microbiol: IJMM 2019;309:151338. https://doi.org/10.1016/j.ijmm.2019.151338.Suche in Google Scholar PubMed

15. Clarridge, JE3rd. Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases. Clin Microbiol Rev 2004;17:840–62. https://doi.org/10.1128/cmr.17.4.840-862.2004.Suche in Google Scholar

16. Johnson, JS, Spakowicz, DJ, Hong, BY, Petersen, LM, Demkowicz, P, Chen, L, et al.. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nat Commun 2019;10:5029. https://doi.org/10.1038/s41467-019-13036-1.Suche in Google Scholar PubMed PubMed Central

17. Shokralla, S, Porter, TM, Gibson, JF, Dobosz, R, Janzen, DH, Hallwachs, W, et al.. Massively parallel multiplex DNA sequencing for specimen identification using an Illumina MiSeq platform. Sci Rep 2015;5:9687. https://doi.org/10.1038/srep09687.Suche in Google Scholar PubMed PubMed Central

18. Chaemsaithong, P, Romero, R, Korzeniewski, SJ, Dong, Z, Yeo, L, Hassan, SS, et al.. A point of care test for the determination of amniotic fluid interleukin-6 and the chemokine CXCL-10/IP-10. J Matern Fetal Neonatal Med 2015;28:1510–9. https://doi.org/10.3109/14767058.2014.961417.Suche in Google Scholar PubMed PubMed Central

19. Chaemsaithong, P, Romero, R, Korzeniewski, SJ, Martinez-Varea, A, Dong, Z, Yoon, BH, et al.. A rapid interleukin-6 bedside test for the identification of intra-amniotic inflammation in preterm labor with intact membranes. J Matern Fetal Neonatal Med 2016;29:349–59. https://doi.org/10.3109/14767058.2015.1006620.Suche in Google Scholar PubMed PubMed Central

20. Chaemsaithong, P, Romero, R, Korzeniewski, SJ, Martinez-Varea, A, Dong, Z, Yoon, BH, et al.. A point of care test for interleukin-6 in amniotic fluid in preterm prelabor rupture of membranes: a step toward the early treatment of acute intra-amniotic inflammation/infection. J Matern Fetal Neonatal Med 2016;29:360–7. https://doi.org/10.3109/14767058.2015.1006621.Suche in Google Scholar PubMed PubMed Central

21. Chaemsaithong, P, Romero, R, Docheva, N, Chaiyasit, N, Bhatti, G, Pacora, P, et al.. Comparison of rapid MMP-8 and interleukin-6 point-of-care tests to identify intra-amniotic inflammation/infection and impending preterm delivery in patients with preterm labor and intact membranes. J Matern Fetal Neonatal Med 2018;31:228–44. https://doi.org/10.1080/14767058.2017.1281904.Suche in Google Scholar PubMed PubMed Central

Received: 2022-10-18
Accepted: 2022-11-17
Published Online: 2022-12-13
Published in Print: 2023-07-26

© 2023 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Heruntergeladen am 21.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/jpm-2022-0504/html
Button zum nach oben scrollen