Appendiceal microbiome in uncomplicated and complicated acute appendicitis: A prospective cohort study

Sanja Vanhatalo; Eveliina Munukka; Teemu Kallonen; Suvi Sippola; Juha Grönroos; Jussi Haijanen; Antti J. Hakanen; Paulina Salminen

doi:10.1371/journal.pone.0276007

Abstract

Background

Uncomplicated and complicated acute appendicitis seem to be two different forms of this common abdominal emergency. The contribution of appendiceal microbiota to appendicitis pathogenesis has been suggested, but differences between uncomplicated and complicated appendicitis are largely unknown. We compared the appendiceal microbiota in uncomplicated and complicated acute appendicitis.

Methods

This prospective single-center clinical cohort study was conducted as part of larger multicenter MAPPAC trial enrolling adult patients with computed tomography or clinically confirmed uncomplicated or complicated acute appendicitis. The microbial composition of the appendiceal lumen was determined using 16S rRNA gene amplicon sequencing.

Results

Between April 11, 2017, and March 29, 2019, 118 samples (41 uncomplicated and 77 complicated appendicitis) were available. After adjusting for age, sex, and BMI, alpha diversity in complicated appendicitis was higher (Shannon p = 0.011, Chao1 p = 0.006) compared to uncomplicated appendicitis. Microbial compositions were different between uncomplicated and complicated appendicitis (Bray-Curtis distance, P = 0.002). Species poor appendiceal microbiota composition with specific predominant bacteria was present in some patients regardless of appendicitis severity.

Conclusion

Uncomplicated and complicated acute appendicitis have different appendiceal microbiome profiles further supporting the disconnection between these two different forms of acute appendicitis.

Study registration

ClinicalTrials.gov NCT03257423.

Citation: Vanhatalo S, Munukka E, Kallonen T, Sippola S, Grönroos J, Haijanen J, et al. (2022) Appendiceal microbiome in uncomplicated and complicated acute appendicitis: A prospective cohort study. PLoS ONE 17(10): e0276007. https://doi.org/10.1371/journal.pone.0276007

Editor: Vipa Thanachartwet, Mahidol University, Faculty of Tropical Medicine, THAILAND

Received: March 7, 2022; Accepted: September 12, 2022; Published: October 14, 2022

Copyright: © 2022 Vanhatalo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The clinical patient data is available only by request and this data includes sensitive information despite the deidentification and thus cannot be shared based on legal restrictions by Finnish GDPR rules. The point of contact is the Ethics Committee of Hospital District of Southwest Finland (eettinen.toimikunta@tyks.fi). The raw 16S-data set is available at the Sequence Read Archive (SRA) portal of NCBI under project number PRJNA869932 (http://www.ncbi.nlm.nih.gov/bioproject/869932).

Funding: The MAPPAC study was supported by research grants from the Mary and Georg C. Ehrnrooth Foundation, the Sigrid Jusélius Foundation, the Finnish Academy, Government research grant awarded to Turku University Hospital (EVO foundation), The Maud Kuistila Memorial Foundation, Paulo Foundation, Doctoral Program in Clinical Research at the University of Turku, and Turku University foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: EM is currently working as full-time Medical Advisor for Biocodex Nordics. PS reports receiving personal fees for lectures form Merck and Orion Pharma. AJH reports receiving personal fees for lectures from BioCodex, Merck and Pfizer. This does not alter our adherence to PLOS ONE policies on sharing data and materials. All other authors declare no competing interests.

Introduction

With current knowledge, acute appendicitis can be both epidemiologically and clinically classified by severity in two different entities of uncomplicated and complicated acute appendicitis [1–3] allowing a stratified approach to management [2]. The dogma of acute appendicitis inevitably always progressing to perforation without early appendicectomy seems to apply only to complicated acute appendicitis. As non-operative management of uncomplicated appendicitis has been identified as feasible and safe [4–9], it has become very relevant to clinically differentiate between uncomplicated and complicated acute appendicitis. This differential diagnosis still remains challenging and evident findings of complicated acute appendicitis include perforation, abscess or a suspicion of a tumor. The presence of an appendicolith has also been shown to be associated with a more complicated course of the disease [8,9] and should be considered a finding of complicated acute appendicitis not eligible for non-operative treatment [6,7,10]. Despite appendicitis being one of the most common general surgical emergencies worldwide, the ethiology still remains poorly understood and bridging the knowledge gaps in the pathogenesis of these different forms of appendicitis severity is necessary [2].

The understanding of both microbiological etiology of acute appendicitis and the potential differences in etiology and pathogenesis between uncomplicated and complicated acute appendicitis is very limited, but the involvement of bacteria or the appendicular microbiome has been suggested [2]. As majority of bacteria in the appendix are anaerobes, the role of culturing methods is limited and next generation sequencing (NGS) methods are somewhat a necessity in the detection of the microbiological factors in the appendicitis etiology. All studies that have characterised the appendiceal microbiome by NGS show that appendiceal microbiome is highly diverse harboring large interindividual variation in both healthy and inflamed appendixes [11–15]. Members of gram negative Fusobacteria were considered to be infectious, associating with more severe appendicitis in a study using fluorescence in situ hybridization (FISH) [16]. Studies using 16S rRNA gene amplicon sequencing with both adult and pediatric patients have indeed confirmed Fusobacteria as an important microbial factor [11,12,17–19]. In addition, increased levels of Parvimonas and Porphyromonas in pediatric appendicitis samples have been reported [17,18].

To our knowledge, only one previous study utilizing NGS has specifically compared the microbial composition of the appendix in adult patients with uncomplicated and complicated appendicitis showing no significant difference between perforated and unperforated acute appendicitis samples [14]. However, this study was limited by both a very small sample size and lack of standardized clinical definitions of appendicitis severity focusing on the methodological comparison of bacterial culture and NGS. In light of the limited available data, we performed this prospective study consisting of patients with CT-confirmed uncomplicated or complicated acute appendicitis with thorough prospective clinical data and standardized appendix samples aiming to assess the potential differences in appendiceal microbiota composition between uncomplicated and complicated appendicitis using 16S rRNA gene amplicon sequencing.

Methods

Study design and patients

This prospective cohort study was a single-center arm of a multicenter MAPPAC (Microbiology Appendicitis Acuta) trial (ClinicalTrials.gov NCT03257423) and was conducted at Turku University Hospital in Finland. Study design and key methods have been reported previously [20]. The study enrolled adult patients with CT or clinically confirmed either uncomplicated or complicated acute appendicitis undergoing appendicectomy in order to have the appendix both as the reference standard for the clinical diagnosis and the availability of appendiceal samples. MAPPAC trial was conducted concurrently with two randomized controlled trials (RCTs) APPAC II [7] and APPACIII [10] enrolling patients with a CT-confirmed uncomplicated acute appendicitis. APPAC II was an open-label, noninferiority trial comparing oral moxifloxacin with intravenous ertapenem followed by oral levofloxacin and metronidazole. APPAC III was a double-blind, placebo-controlled, superiority study comparing antibiotic therapy (intravenous ertapenem followed by oral levofloxacin and metronidazole) with placebo in the treatment of uncomplicated appendicitis.

Intramural neutrophil invasion in the histopathological examination of the removed appendix was required for the diagnosis of acute appendicitis. Acute appendicitis was defined uncomplicated if no features of complicated acute appenditis was present. Complicated appendicitis was defined as the presence of an appendicolith, perforation, abscess, gangrene, or suspicion of tumor or the combination of these. To validate the accuracy of the differential diagnosis between uncomplicated and complicated acute appendicitis, all patients were assessed using clinical data, CT, surgical, and histopathological findings by two investigators (S.S. and J.H.) unaware of the other’s evaluation. In cases of disagreement, the clinical diagnosis was reviewed by a third investigator (P.S.).

Outcomes

The objective of this study was to compare the microbial composition of an inflamed appendix between uncomplicated and complicated acute appendicitis. Microbial composition was assessed by the relative levels of bacterial phyla, genera, and species. Species richness and diversity, as well as dissimilarity of microbiomes, i.e. beta diversity, were measured and differential abundance analysis was used to identify differentiating phyla, genera, and species associated with appendicitis severity.

Sample collection and processing

Microbiological swabs from the appendiceal lumen were collected right after the appendicectomy. Sample collection and bacterial DNA extraction have been previously described in detail [20]. Briefly, extraction of DNA from appendiceal swabs was performed by semiautomated GXT Stool Extraction kit (Hain Lifescience GmbH, Nehren, Germany). DNA concentration was quantified with Qubit fluorometer (Life Technologies, Carlsbad, California, USA).

16S rRNA amplicon sequencing

16S rRNA amplicon sequencing was performed targeting the V3-V4 hypervariable region. Negative and positive control samples were included in the sequencing: negative DNA extraction control, negative PCR control, and a mock community (ZymoBiomics microbial community DNA standard, Zymo Research, Irvine, California, USA) as a positive control. Amplicon libraries were generated following the Illumina protocol (https://support.illumina.com/documents/documentation/chemistry_documentation/16s/16s-metagenomic-library-prep-guide-15044223-b.pdf) with the exception that increased amount of 75 ng of DNA template was used in the amplicon PCR reaction. Amplicon libraries were quantified using Qubit fluorometer and 10% of Phix (Illumina, San Diego, California, USA) was added to each equimolar pool. Sequencing was performed using MiSeq Reagent Kit v3 and paired-end 2×300 bp protocol on a MiSeq System (Illumina).

Statistical and bioinformatical analysis

Group differences in numerical (age, body mass index (BMI)) and categorical (sex) baseline characteristics were tested with Wilcoxon rank sum test and Pearson´s chi-squared test, respectively. All bioinformatical analyses were performed in R 4.0.3. Amplicon sequence variants (ASVs) of the 16S rRNA gene sequences were formed using the dada2 package, version 1.18.0 [21]. Raw reads were quality filtered and trimmed using the function filterAndTrim. The ASVs were assigned to taxa using the SILVA rRNA (v. 138) database as reference [22–24]. Contaminants, eukaryotes and mitochondrial sequences were removed from bacterial data. Archaeal sequences remained in the data. Decontamination was performed using R package decontam with the method “Prevalence” and a threshold of 0.225 [25]. This method compares prevalence of each ASV in true samples to the prevalence in negative controls to identify contaminants. To ensure that decontamination worked well, results were inspected and manually corrected. In normalization and all further analyses, the samples with more than 1800 sequences were included. Shannon’s index did not strongly correlate with library sizes of samples even in the in non-normalized raw data (Pearson correlation = 0.17). Thus, raw sequence counts of ASVs were transformed to relative abundances that were used in downstream analyses and for alpha diversity calculations [26]. Principal coordinate analysis (PCoA) was calculated using function cmdscale in R package vegan [27] and permutational multivariate analysis of variance (PERMANOVA), with control variables age, sex and BMI, was performed using function multiconstrained in R package BiodiversityR. Both analyses were based on Bray-Curtis dissimilarities. Significantly differentiating bacterial species, genus, and phyla between groups were detected using the DESeq2 method [28]. The p-values were adjusted using Benjamini-Hochberg method and adjusted p-values <0.01 were considered as statistically significant. All the reported p-values related to differential abundance analyses are adjusted p-values. Alpha diversity analyses were performed using standard linear regression models with alpha diversity measure (Chao1, Shannon entropy or number of observed species) as the response variable and appendicitis severity, age, sex, and BMI as the predictors.

Study approval

This study has been accepted by the Ethical Committee of the Hospital district of Southwest Finland (Turku University Hospital) and Finnish Medicines Agency (Fimea). Trial was performed in accordance with the Declaration of Helsinki and all patients and in the case of minors their legal guardians gave written informed consent to participate in the study.

Results

Altogether 308 patients were enrolled in the MAPPAC study between April 11, 2017, and March 29, 2019; Fig 1 shows the study flow. Out of the 169 patients with uncomplicated or complicated acute appendicitis undergoing appendicectomy, 118 (70%) samples were included in the final NGS analysis (41 uncomplicated, 77 complicated appendicitis) with 51 patients excluded due to failed library preparation (n = 26), incomplete sample collection (n = 21), or too low 16S amplicon library size (n = 4). Patient baseline characteristics and the subtypes of complicated appendicitis are presented in Table 1. The groups were similar regarding age and BMI, but the proportion of women in the uncomplicated appendicitis group was higher compared to the complicated appendicitis group (66% vs. 45%, respectively, p = 0.0346). Out of the 77 patients with complicated acute appendicitis, an appendicolith was present in 57 (74%) patients.

Download:

Fig 1. Flow chart of the study.

*Appendectomy for primary acute appendicitis. Only patients treated with appendectomy and histopathologically confirmed acute appendicitis study were included in the analysis to have the microbiological sample and to have confirmation for the differential diagnosis. a) Randomized, multicenter, open-label, noninferiority clinical trial comparing oral moxifloxacin with intravenous ertapenem followed by oral levofloxacin and metronidazole. b) Randomized, multicentre, placebo-controlled, double-blind trial comparing antibiotic therapy with placebo in the treatment of uncomplicated acute appendicitis.

https://doi.org/10.1371/journal.pone.0276007.g001

Download:

Table 1. Patient baseline characteristics and subtypes of complicated appendicitis.

https://doi.org/10.1371/journal.pone.0276007.t001

Differing microbial signatures in uncomplicated and complicated acute appendicitis

Appendiceal microbiome composition in uncomplicated acute appendicitis was significantly different compared with complicated acute appendicitis regarding both alpha and beta diversities. Alpha diversity indices Shannon and Chao1 describing diversity and richness were lower in uncomplicated acute appendicitis compared to complicated appendicitis samples (Fig 2A, p = 0.011 and p = 0.006, respectively). Similar to alpha diversity, Principal coordinate analysis based on Bray-Curtis dissimilarity (Fig 2B) also indicated different beta diversities in appendiceal microbiota between the two forms of appendicitis severity. Pairwise comparisons revealed significantly different Bray-Curtis distance measure between the two groups (p = 0.002).

Download:

Fig 2. The difference in appendiceal microbiota between uncomplicated and complicated acute appendicitis.

A) Violin plot representing alpha diversity measures Shannon index and Chao1 in uncomplicated and complicated acute appendicitis. * p < 0.05 and ** p < 0.01). B) Principal Coordinates Analysis (PCoA), i.e. beta diversity, based on Bray-Curtis distances. The percentage of variation explained by the two first PCoA dimensions is indicated on the respective axes. C) Barplot showing significantly (adj p < 0.01) differentiating species in uncomplicated compared to complicated that were present in meaningful levels (average relative abundance >0.1%). Species are listed along the y-axis and x-axis indicates the log2 fold change. UNK = unknown species.

https://doi.org/10.1371/journal.pone.0276007.g002

To investigate which bacteria are responsible for the observed beta diversity difference, the relative abundances of bacteria between groups were compared in phylum, genus, and species level. When a complete taxonomical name was not possible to assign to species level, they are referred as unknown (UNK) species. Bacterial species in which abundance differed statistically significantly (p<0.01) between uncomplicated and complicated acute appendicitis (S1 Table) and that were present at average relative abundance >0.1%, are illustrated in Fig 2C. Seven species that were more abundant in uncomplicated acute appendicitis were Aggregatibacter aphrophilus, B. fragilis, Enterobacteriaceae UNK, Haemophilus UNK, Streptococcus UNK, Veillonella parvula, and Veillonella UNK. Seven species were more abundant in complicated acute appendicitis: Bacteroides faecis, Christensenellaceae UNK, Clostridia UCG-014, Dialister UNK, Oscillospiraceae UCG-005 UNK, Phocaeicola abscessus, and Porphyromonas endodontalis. Genus Aggregatibacter was more abundant in uncomplicated acute appendicitis (adj. p = 0.00016), where the mean relative abundance was 6.4% compared with 1.0% in complicated acute appendicitis. Nine other, significantly different genera were Veillonella and an unknown genus from the family Enterobacteriaceae, which were enriched in uncomplicated acute appendicitis and an unknown genus from Christensenellaceae, Defluviitaleaceae UCG-011 UNK, Family XIII UCG-001, Oscillibacter, Paludicola, Phocaeicola, and Subdoligranulum were more abundant in complicated acute appendicitis (S1 Table). The abundances of bacterial phyla were not significantly different between uncomplicated and complicated acute appendicitis.

Species poor appendiceal microbiomes are predominated by specific bacterial species

The overall microbial profiles of the appendiceal lumen are illustrated at species level in Fig 3 and in phylum and genus level in S1 Fig. Interindividual variation in both the composition and diversity was high in both forms of appendicitis severity. Further, in some samples only few predominant species were present at significant levels reflected in the low values of alpha diversity (Fig 3), while in other samples, hundreds of species were present and comprised an even microbial profile. The appendiceal microbiome was dominated by one bacterial species with a relative abundance of more than 50% in 17% (7/41) and 12% (9/77) of patients with uncomplicated and complicated acute appendicitis, respectively. B. fragilis and Escherichia UNK appeared as predominating species regardless of appendicitis severity. Aggregatibacter aphrophilus or segnis, and Streptococcus UNK (Fig 3) were found to dominate only in uncomplicated appendicitis and Fusobacterium UNK, Haemophilus parainfluenzae, B. faecis, B. dorei or Bacteroides UNK only in complicated appendicitis. Altogether 419 different genera and 599 different species were identified. Mean relative abundances of bacterial species composing more than 0.1% in each group are presented in S2 Table.

Download:

Fig 3. Stacked barplots of appendiceal microbiome (n = 118) in species level in uncomplicated and complicated acute appendicitis.

Microbiome profiles of individual appendix samples with the 40 most abundant species plotted and lower abundance species grouped to “other”. On top of barchart is overlaid the number of observed species in each sample as a line chart. UNK = unknown species.

https://doi.org/10.1371/journal.pone.0276007.g003

Discussion

In this prospective clinical study on 118 patients with confirmed acute appendicitis, multiple differences between uncomplicated (n = 41) and complicated acute appendicitis (n = 77) patient samples were detected in the microbial composition of the appendiceal lumen supporting the theory of dividing acute appendicitis into two separate forms of acute inflammation processes with different clinical presentation and fates. There were differences in overall alpha and beta diversities between uncomplicated and complicated acute appendicitis. In addition, several bacterial taxa were identified to be significantly different between these two forms of appendicitis severity.

The microbial signatures in uncomplicated and complicated acute appendicitis were different, but in both forms of appendicitis severity, we found several opportunistic pathogens. Patients with uncomplicated acute appendicitis presented with a higher proportion of gram negative Aggregatibacter species (spp) consisting mainly of A. segnis and A. aphrophilus (former Haemophilus aphrophilus). Aggregatibacter belongs to the HACEK group (gram negative bacteria Haemophilus, Aggregatibacter, Cardiobacterium, Eikenella, and Kingella) that are most notable for causing infective endocarditis, but they are also significant causes of periodontitis, abscesses, and septic arthritis [29]. In addition Veillonella parvula and an unknown species from the genus Streptococcus both linked to gastrointestinal tract and oral microbiota [30,31], were found to be enriched in uncomplicated acute appendicitis. In complicated acute appendicitis, a group of gram negative bacteria Porphyromonas endodontalis, an unknown species from the genus Dialister, and Phocaeicola abscessus were more abundant and all of these are considered to be oral pathogens [32,33]. Genera Porphyromonas and Dialister have been previously associated with complicated appendicitis in pediatric patients [18,34].

Microbial diversity was lower in uncomplicated acute appendicitis compared to complicated acute appendicitis. In both forms of appendicitis severity, we observed individual samples with very low diversity. These species poor appendiceal microbiomes were often dominated by one bacteria representing at least 50% of the appendiceal microbiota. The observed predominance may play a role as an etiological factor on an individual level as it could be an indication of infection by these specific predominant species. Both uncomplicated and complicated acute appendicitis had microbial profiles where either B. fragilis or Escherichia UNK were the predominant bacteria, which are well reported in appendicitis [13,35]. A. aphrophilus or A. segnis and Streptococcus UNK were predominant only in patients with uncomplicated acute appendicitis. The most abundant Fusobacteria species F. UNK and F. nucleatum were present in both disease forms. However F. UNK as the predomint species was discovered only in the complicated appendicitis samples. Fusobacteria is the only group prominently associated with appendicitis [12,16] and our results corroborate the previous studies suggesting it to be specifically associated with complicated acute appendicitis [16].

Based on the results of this study, both infection and a disturbance of normal appendiceal microbiota could be etiological factors for some patients in both uncomplicated and complicated acute appendicitis. However, the observed difference in the microbiota diversity suggests that an infection may be more common in uncomplicated acute appendicitis partially associated with different bacterial species. This is further supported by the presence of an appendicolith in the majority (74%) of patients presenting with complicated acute appendicitis as appendicoliths often lead to obstruction of the appendiceal lumen [36]. In large RCTs, the presence of an appendicolith has been shown to be associated with a more complicated course of the disease [8,9].

This study has several limitations. First, a major limitation of the study is the lack of a healthy non-appendicitis control group. The perception of appendicitis as an opportunistic infection, where the abruption of the healthy appendiceal microbiota would drive the inflammation, is gaining ground [12,13]. In the search for etiological agents of a disease where the infection site contains normal microbiota, a healthy control group would be crucial. However, the acquisition of healthy appendix and appendiceal microbiota for this purpose is naturally both clinically and ethically impossible as the negative appendicectomy rate with the current CT diagnostic accuracy is very low and appendicectomy for healthy patients would be unethical. Second, further limitation is that patients received standard prophylactic antibiotics preoperatively, which could have affected the microbial composition of the appendiceal microbiota. However, all patients received antibiotics and the time between antibiotics administration and appendicectomy was relatively short. Third weakness of the study is the utilization of 16S rRNA gene amplicon sequencing, which is partly insufficient in species level analysis. Strain level identification is required in some bacteria to fully estimate the pathogenicity of bacteria present in the sample. For example, it has been suggested that specific virulent strains of E. coli [37] or the enterotoxic strains of B. fragilis [38] might be involved in the infection of the appendix and the resolution of taxonomical information gained in this study characterising appendiceal microbiota can be considered too low to drawn conclusions about the role of these bacteria in different forms of appendicitis severity. Future studies should harness methods, such as shotgun metagenomic sequencing combined with culturing methods, enabling the assessment of appendiceal microbiome function and virulence.

To our knowledge, this is the first prospective study with a large patient cohort and standardized clinical definitions of appendicitis severity comparing the microbial composition of the appendix in adult patients between uncomplicated and complicated acute appendicitis. The thorough prospective clinical data is a major strength in our study in addition to the so far largest number of patients.

In conclusion, uncomplicated and complicated acute appendicitis have different appendiceal microbiome profiles further supporting the disconnection between these two different forms of appendicitis severity.

Supporting information

S1 Fig. Appendiceal microbiome in phylum and genus level in uncomplicated and complicated acute appendicitis.

https://doi.org/10.1371/journal.pone.0276007.s001

(PDF)

S1 Table. Differentially abundant bacterial species and genera between uncomplicated and complicated appendicitis.

https://doi.org/10.1371/journal.pone.0276007.s002

(PDF)

S2 Table. Relative abundance of species in uncomplicated and complicated appendicitis.

https://doi.org/10.1371/journal.pone.0276007.s003

(PDF)

Acknowledgments

We thank Aluke Oy, which contributed to the bioinformatic analysis of sequencing data. We thank our research coordinator Susanna Kulmala and laboratory technician Anna Musku. In addition we thank all of the surgeons on-call who took part in the enrollment of MAPPAC patients and collected the microbiological samples.

References

1. Andersson RE, Petzold MG. Nonsurgical treatment of appendiceal abscess or phlegmon: A systematic review and meta-analysis. Ann Surg. 2007;246: 741–748. pmid:17968164
- View Article
- PubMed/NCBI
- Google Scholar
2. Bhangu A, Søreide K, Di Saverio S, Assarsson JH, Drake FT. Acute appendicitis: Modern understanding of pathogenesis, diagnosis, and management. Lancet. 2015;386: 1278–1287. pmid:26460662
- View Article
- PubMed/NCBI
- Google Scholar
3. Livingston EH, Fomby TB, Woodward WA, Haley RW. Epidemiological Similarities Between Appendicitis and Diverticulitis Suggesting a Common Underlying Pathogenesis. Arch Surg. 2011;146: 308–314. pmid:21422362
- View Article
- PubMed/NCBI
- Google Scholar
4. Minneci PC, Hade EM, Lawrence AE, Sebastião Y V, Saito JM, Mak GZ, et al. Association of Nonoperative Management Using Antibiotic Therapy vs Laparoscopic Appendectomy With Treatment Success and Disability Days in Children With Uncomplicated Appendicitis. JAMA. 2020;324: 581–593. pmid:32730561
- View Article
- PubMed/NCBI
- Google Scholar
5. Salminen P, Tuominen R, Paajanen H, Rautio T, Nordström P, Aarnio M, et al. Five-Year Follow-up of Antibiotic Therapy for Uncomplicated Acute Appendicitis in the APPAC Randomized Clinical Trial. JAMA—J Am Med Assoc. 2018;320: 1259–1265. pmid:30264120
- View Article
- PubMed/NCBI
- Google Scholar
6. Salminen P, Paajanen H, Rautio T, Nordstrom P, Aarnio M, Rantanen T, et al. Antibiotic Therapy vs Appendectomy for Treatment of Uncomplicated Acute Appendicitis: The APPAC Randomized Clinical Trial. Jama. 2015;313: 2340–2348. pmid:26080338
- View Article
- PubMed/NCBI
- Google Scholar
7. Sippola S, Haijanen J, Grönroos J, Rautio T, Nordström P, Rantanen T, et al. Effect of Oral Moxifloxacin vs Intravenous Ertapenem plus Oral Levofloxacin for Treatment of Uncomplicated Acute Appendicitis: The APPAC II Randomized Clinical Trial. JAMA—J Am Med Assoc. 2021;325: 353–362. pmid:33427870
- View Article
- PubMed/NCBI
- Google Scholar
8. Flum DR, Davidson GH, Monsell SE et al. A Randomized Trial Comparing Antibiotics with Appendectomy for Appendicitis. N Engl J Med. 2020;383: 1907–1919. pmid:33017106
- View Article
- PubMed/NCBI
- Google Scholar
9. Vons C, Barry C, Maitre S, Pautrat K, Leconte M, Costaglioli B, et al. Amoxicillin plus clavulanic acid versus appendicectomy for treatment of acute uncomplicated appendicitis: an open-label, non-inferiority, randomised controlled trial. Lancet (London, England). 2011;377: 1573–1579. pmid:21550483
- View Article
- PubMed/NCBI
- Google Scholar
10. Sippola S, Gronroos J, Sallinen V, Rautio T, Nordstrom P, Rantanen T, et al. A randomised placebo-controlled double-blind multicentre trial comparing antibiotic therapy with placebo in the treatment of uncomplicated acute appendicitis: APPAC III trial study protocol. BMJ Open. 2018;8: e02362–023623. pmid:30391919
- View Article
- PubMed/NCBI
- Google Scholar
11. Guinane CM, Tadrous A, Fouhy F, Ryan CA, Dempsey EM, Murphy B, et al. Microbial composition of human appendices from patients following appendectomy. MBio. 2013;4: pmid:23322636
- View Article
- PubMed/NCBI
- Google Scholar
12. Arlt A, Bharti R, Ilves I, Häsler R, Miettinen P, Paajanen H, et al. Characteristic changes in microbial community composition and expression of innate immune genes in acute appendicitis. Innate Immun. 2015;21: 30–41. pmid:24336024
- View Article
- PubMed/NCBI
- Google Scholar
13. Oh SJ, Pimentel M, Leite GGS, Celly S, Villanueva-Millan MJ, Lacsina I, et al. Acute appendicitis is associated with appendiceal microbiome changes including elevated Campylobacter jejuni levels. BMJ Open Gastroenterol. 2020;7: 1–10. pmid:32499276
- View Article
- PubMed/NCBI
- Google Scholar
14. Yuan J, Li W, Qiu E, Han S, Li Z. Metagenomic NGS optimizes the use of antibiotics in appendicitis patients: Bacterial culture is not suitable as the only guidance. Am J Transl Res. 2021;13: 3010–3021. pmid:34017469
- View Article
- PubMed/NCBI
- Google Scholar
15. Munakata S, Tohya M, Matsuzawa H, Tsuchiya Y, Amemiya K, Hagiwara T, et al. Analysis of appendectomy samples identified dysbiosis in acute appendicitis. Biosci Microbiota, Food Heal. 2021;40: 92–97. pmid:33996365
- View Article
- PubMed/NCBI
- Google Scholar
16. Swidsinski A, Dorffel Y, Loening-Baucke V, Theissig F, Ruckert JC, Ismail M, et al. Acute appendicitis is characterised by local invasion with Fusobacterium nucleatum/necrophorum. Gut. 2011;60: 34–40. pmid:19926616
- View Article
- PubMed/NCBI
- Google Scholar
17. Zhong D, Brower-Sinning R, Firek B, Morowitz MJ. Acute appendicitis in children is associated with an abundance of bacteria from the phylum Fusobacteria. J Pediatr Surg. 2014;49: 441–446. pmid:24650474
- View Article
- PubMed/NCBI
- Google Scholar
18. Jackson HT, Mongodin EF, Davenport KP, Fraser CM, Sandler AD, Zeichner SL. Culture-independent evaluation of the appendix and rectum microbiomes in children with and without appendicitis. PLoS One. 2014;9: e95414. pmid:24759879
- View Article
- PubMed/NCBI
- Google Scholar
19. Salo M, Marungruang N, Roth B, Sundberg T, Stenstrom P, Arnbjornsson E, et al. Evaluation of the microbiome in children’s appendicitis. Int J Colorectal Dis. 2017;32: 19–28. pmid:27613729
- View Article
- PubMed/NCBI
- Google Scholar
20. Vanhatalo S, Munukka E, Sippola S, Jalkanen S, Grönroos J, Marttila H, et al. Prospective multicentre cohort trial on acute appendicitis and microbiota, aetiology and effects of antimicrobial treatment: Study protocol for the MAPPAC (Microbiology APPendicitis ACuta) trial. BMJ Open. 2019;9. pmid:31494621
- View Article
- PubMed/NCBI
- Google Scholar
21. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13: 581–583. pmid:27214047
- View Article
- PubMed/NCBI
- Google Scholar
22. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013;41: 590–596. pmid:23193283
- View Article
- PubMed/NCBI
- Google Scholar
23. Callahan B. Silva taxonomic training data formatted for DADA2 (Silva version 132). 2018 [cited 21 Apr 2021].
- View Article
- Google Scholar
24. McLaren MR. Silva SSU taxonomic training data formatted for DADA2 (Silva version 138). 2020 [cited 21 Apr 2021].
- View Article
- Google Scholar
25. Davis NM, Proctor DM, Holmes SP, Relman DA, Callahan BJ. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. bioRxiv. 2017; 1–14.
- View Article
- Google Scholar
26. Kindt R, Coe R. Tree diversity analysis. 2005;3.
- View Article
- Google Scholar
27. Oksanen J, Legendre P, O’Hara B, Stevens MHH, Oksanen MJ, Suggests M. The vegan package. Community Ecol Packag. 2007;10: 631–637.
- View Article
- Google Scholar
28. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15: 1–21. pmid:25516281
- View Article
- PubMed/NCBI
- Google Scholar
29. Nørskov-Lauritsen N., Classification, identification, and clinical significance of Haemophilus and Aggregatibacter species with host specificity for humans. Clin Microbiol Rev. 2014;27: 214–240. pmid:24696434
- View Article
- PubMed/NCBI
- Google Scholar
30. Said HS, Suda W, Nakagome S, Chinen H, Oshima K, Kim S, et al. Dysbiosis of salivary microbiota in inflammatory bowel disease and its association with oral immunological biomarkers. DNA Res. 2014;21: 15–25. pmid:24013298
- View Article
- PubMed/NCBI
- Google Scholar
31. van den Bogert B, Erkus O, Boekhorst J, de Goffau M, Smid EJ, Zoetendal EG, et al. Diversity of human small intestinal Streptococcus and Veillonella populations. FEMS Microbiol Ecol. 2013;85: 376–388. pmid:23614882
- View Article
- PubMed/NCBI
- Google Scholar
32. Bedran TBL, Marcantonio RAC, Neto RS, Mayer MPA, Grenier D, Spolidorio LC, et al. Porphyromonas endodontalis in chronic periodontitis: A clinical and microbiological cross-sectional study. J Oral Microbiol. 2012;4: 1–7. pmid:22232719
- View Article
- PubMed/NCBI
- Google Scholar
33. Nóbrega LMM, Montagner F, Ribeiro AC, Mayer MAP, Gomes BPF de A. Bacterial diversity of symptomatic primary endodontic infection by clonal analysis. Braz Oral Res. 2016;30: e103. pmid:27737357
- View Article
- PubMed/NCBI
- Google Scholar
34. Schülin S, Schlichting N, Blod C, Opitz S, Suttkus A, Stingu CS, et al. The intra- and extraluminal appendiceal microbiome in pediatric patients. Med (United States). 2017;96: 1–7. pmid:29384958
- View Article
- PubMed/NCBI
- Google Scholar
35. Elhag KM, Alwan MH, Al-Adnani MS, Sherif RA. Bacteroides fragilis is a silent pathogen in acute appendicitis. J Med Microbiol. 1986;21: 245–249. pmid:3517340
- View Article
- PubMed/NCBI
- Google Scholar
36. Ranieri DM, Enzerra MD, Pickhardt PJ. Prevalence of appendicoliths detected at CT in adults with suspected appendicitis. Am J Roentgenol. 2020;216: 677–682. pmid:33474985
- View Article
- PubMed/NCBI
- Google Scholar
37. Saxén H, Tarkka E, Hannikainen P, Nikku R, Rautio M, Siitonen A. Escherichia coli and appendicitis: Phenotypic characteristics of E. coli isolates from inflamed and noninflamed appendicesfile://utuhome.utu.fi/sahevan/MAPPAC/artikkelit luet/23-5-1038.pdf. Clin Infect Dis. 1996;23: 1038–1042. pmid:8922799
- View Article
- PubMed/NCBI
- Google Scholar
38. Martirosian G, Bulanda M, Wojcik-Stojek B, Obuch-Woszczatynski P, Rouyan G, Heczko P, et al. Acute appendicitis: the role of enterotoxigenic strains of Bacteroides fragilis and Clostridium difficile. Med Sci Monit. 2001;7: 382–386. pmid:11386013
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Andersson RE, Petzold MG. Nonsurgical treatment of appendiceal abscess or phlegmon: A systematic review and meta-analysis. Ann Surg. 2007;246: 741–748. pmid:17968164
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. Bhangu A, Søreide K, Di Saverio S, Assarsson JH, Drake FT. Acute appendicitis: Modern understanding of pathogenesis, diagnosis, and management. Lancet. 2015;386: 1278–1287. pmid:26460662
View Article
PubMed/NCBI
Google Scholar

[6] View Article

[7] PubMed/NCBI

[8] Google Scholar

[ref3] 3. Livingston EH, Fomby TB, Woodward WA, Haley RW. Epidemiological Similarities Between Appendicitis and Diverticulitis Suggesting a Common Underlying Pathogenesis. Arch Surg. 2011;146: 308–314. pmid:21422362
View Article
PubMed/NCBI
Google Scholar

[10] View Article

[11] PubMed/NCBI

[12] Google Scholar

[ref4] 4. Minneci PC, Hade EM, Lawrence AE, Sebastião Y V, Saito JM, Mak GZ, et al. Association of Nonoperative Management Using Antibiotic Therapy vs Laparoscopic Appendectomy With Treatment Success and Disability Days in Children With Uncomplicated Appendicitis. JAMA. 2020;324: 581–593. pmid:32730561
View Article
PubMed/NCBI
Google Scholar

[14] View Article

[15] PubMed/NCBI

[16] Google Scholar

[ref5] 5. Salminen P, Tuominen R, Paajanen H, Rautio T, Nordström P, Aarnio M, et al. Five-Year Follow-up of Antibiotic Therapy for Uncomplicated Acute Appendicitis in the APPAC Randomized Clinical Trial. JAMA—J Am Med Assoc. 2018;320: 1259–1265. pmid:30264120
View Article
PubMed/NCBI
Google Scholar

[18] View Article

[19] PubMed/NCBI

[20] Google Scholar

[ref6] 6. Salminen P, Paajanen H, Rautio T, Nordstrom P, Aarnio M, Rantanen T, et al. Antibiotic Therapy vs Appendectomy for Treatment of Uncomplicated Acute Appendicitis: The APPAC Randomized Clinical Trial. Jama. 2015;313: 2340–2348. pmid:26080338
View Article
PubMed/NCBI
Google Scholar

[22] View Article

[23] PubMed/NCBI

[24] Google Scholar

[ref7] 7. Sippola S, Haijanen J, Grönroos J, Rautio T, Nordström P, Rantanen T, et al. Effect of Oral Moxifloxacin vs Intravenous Ertapenem plus Oral Levofloxacin for Treatment of Uncomplicated Acute Appendicitis: The APPAC II Randomized Clinical Trial. JAMA—J Am Med Assoc. 2021;325: 353–362. pmid:33427870
View Article
PubMed/NCBI
Google Scholar

[26] View Article

[27] PubMed/NCBI

[28] Google Scholar

[ref8] 8. Flum DR, Davidson GH, Monsell SE et al. A Randomized Trial Comparing Antibiotics with Appendectomy for Appendicitis. N Engl J Med. 2020;383: 1907–1919. pmid:33017106
View Article
PubMed/NCBI
Google Scholar

[30] View Article

[31] PubMed/NCBI

[32] Google Scholar

[ref9] 9. Vons C, Barry C, Maitre S, Pautrat K, Leconte M, Costaglioli B, et al. Amoxicillin plus clavulanic acid versus appendicectomy for treatment of acute uncomplicated appendicitis: an open-label, non-inferiority, randomised controlled trial. Lancet (London, England). 2011;377: 1573–1579. pmid:21550483
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref10] 10. Sippola S, Gronroos J, Sallinen V, Rautio T, Nordstrom P, Rantanen T, et al. A randomised placebo-controlled double-blind multicentre trial comparing antibiotic therapy with placebo in the treatment of uncomplicated acute appendicitis: APPAC III trial study protocol. BMJ Open. 2018;8: e02362–023623. pmid:30391919
View Article
PubMed/NCBI
Google Scholar

[38] View Article

[39] PubMed/NCBI

[40] Google Scholar

[ref11] 11. Guinane CM, Tadrous A, Fouhy F, Ryan CA, Dempsey EM, Murphy B, et al. Microbial composition of human appendices from patients following appendectomy. MBio. 2013;4: pmid:23322636
View Article
PubMed/NCBI
Google Scholar

[42] View Article

[43] PubMed/NCBI

[44] Google Scholar

[ref12] 12. Arlt A, Bharti R, Ilves I, Häsler R, Miettinen P, Paajanen H, et al. Characteristic changes in microbial community composition and expression of innate immune genes in acute appendicitis. Innate Immun. 2015;21: 30–41. pmid:24336024
View Article
PubMed/NCBI
Google Scholar

[46] View Article

[47] PubMed/NCBI

[48] Google Scholar

[ref13] 13. Oh SJ, Pimentel M, Leite GGS, Celly S, Villanueva-Millan MJ, Lacsina I, et al. Acute appendicitis is associated with appendiceal microbiome changes including elevated Campylobacter jejuni levels. BMJ Open Gastroenterol. 2020;7: 1–10. pmid:32499276
View Article
PubMed/NCBI
Google Scholar

[50] View Article

[51] PubMed/NCBI

[52] Google Scholar

[ref14] 14. Yuan J, Li W, Qiu E, Han S, Li Z. Metagenomic NGS optimizes the use of antibiotics in appendicitis patients: Bacterial culture is not suitable as the only guidance. Am J Transl Res. 2021;13: 3010–3021. pmid:34017469
View Article
PubMed/NCBI
Google Scholar

[54] View Article

[55] PubMed/NCBI

[56] Google Scholar

[ref15] 15. Munakata S, Tohya M, Matsuzawa H, Tsuchiya Y, Amemiya K, Hagiwara T, et al. Analysis of appendectomy samples identified dysbiosis in acute appendicitis. Biosci Microbiota, Food Heal. 2021;40: 92–97. pmid:33996365
View Article
PubMed/NCBI
Google Scholar

[58] View Article

[59] PubMed/NCBI

[60] Google Scholar

[ref16] 16. Swidsinski A, Dorffel Y, Loening-Baucke V, Theissig F, Ruckert JC, Ismail M, et al. Acute appendicitis is characterised by local invasion with Fusobacterium nucleatum/necrophorum. Gut. 2011;60: 34–40. pmid:19926616
View Article
PubMed/NCBI
Google Scholar

[62] View Article

[63] PubMed/NCBI

[64] Google Scholar

[ref17] 17. Zhong D, Brower-Sinning R, Firek B, Morowitz MJ. Acute appendicitis in children is associated with an abundance of bacteria from the phylum Fusobacteria. J Pediatr Surg. 2014;49: 441–446. pmid:24650474
View Article
PubMed/NCBI
Google Scholar

[66] View Article

[67] PubMed/NCBI

[68] Google Scholar

[ref18] 18. Jackson HT, Mongodin EF, Davenport KP, Fraser CM, Sandler AD, Zeichner SL. Culture-independent evaluation of the appendix and rectum microbiomes in children with and without appendicitis. PLoS One. 2014;9: e95414. pmid:24759879
View Article
PubMed/NCBI
Google Scholar

[70] View Article

[71] PubMed/NCBI

[72] Google Scholar

[ref19] 19. Salo M, Marungruang N, Roth B, Sundberg T, Stenstrom P, Arnbjornsson E, et al. Evaluation of the microbiome in children’s appendicitis. Int J Colorectal Dis. 2017;32: 19–28. pmid:27613729
View Article
PubMed/NCBI
Google Scholar

[74] View Article

[75] PubMed/NCBI

[76] Google Scholar

[ref20] 20. Vanhatalo S, Munukka E, Sippola S, Jalkanen S, Grönroos J, Marttila H, et al. Prospective multicentre cohort trial on acute appendicitis and microbiota, aetiology and effects of antimicrobial treatment: Study protocol for the MAPPAC (Microbiology APPendicitis ACuta) trial. BMJ Open. 2019;9. pmid:31494621
View Article
PubMed/NCBI
Google Scholar

[78] View Article

[79] PubMed/NCBI

[80] Google Scholar

[ref21] 21. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13: 581–583. pmid:27214047
View Article
PubMed/NCBI
Google Scholar

[82] View Article

[83] PubMed/NCBI

[84] Google Scholar

[ref22] 22. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013;41: 590–596. pmid:23193283
View Article
PubMed/NCBI
Google Scholar

[86] View Article

[87] PubMed/NCBI

[88] Google Scholar

[ref23] 23. Callahan B. Silva taxonomic training data formatted for DADA2 (Silva version 132). 2018 [cited 21 Apr 2021].
View Article
Google Scholar

[90] View Article

[91] Google Scholar

[ref24] 24. McLaren MR. Silva SSU taxonomic training data formatted for DADA2 (Silva version 138). 2020 [cited 21 Apr 2021].
View Article
Google Scholar

[93] View Article

[94] Google Scholar

[ref25] 25. Davis NM, Proctor DM, Holmes SP, Relman DA, Callahan BJ. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. bioRxiv. 2017; 1–14.
View Article
Google Scholar

[96] View Article

[97] Google Scholar

[ref26] 26. Kindt R, Coe R. Tree diversity analysis. 2005;3.
View Article
Google Scholar

[99] View Article

[100] Google Scholar

[ref27] 27. Oksanen J, Legendre P, O’Hara B, Stevens MHH, Oksanen MJ, Suggests M. The vegan package. Community Ecol Packag. 2007;10: 631–637.
View Article
Google Scholar

[102] View Article

[103] Google Scholar

[ref28] 28. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15: 1–21. pmid:25516281
View Article
PubMed/NCBI
Google Scholar

[105] View Article

[106] PubMed/NCBI

[107] Google Scholar

[ref29] 29. Nørskov-Lauritsen N., Classification, identification, and clinical significance of Haemophilus and Aggregatibacter species with host specificity for humans. Clin Microbiol Rev. 2014;27: 214–240. pmid:24696434
View Article
PubMed/NCBI
Google Scholar

[109] View Article

[110] PubMed/NCBI

[111] Google Scholar

[ref30] 30. Said HS, Suda W, Nakagome S, Chinen H, Oshima K, Kim S, et al. Dysbiosis of salivary microbiota in inflammatory bowel disease and its association with oral immunological biomarkers. DNA Res. 2014;21: 15–25. pmid:24013298
View Article
PubMed/NCBI
Google Scholar

[113] View Article

[114] PubMed/NCBI

[115] Google Scholar

[ref31] 31. van den Bogert B, Erkus O, Boekhorst J, de Goffau M, Smid EJ, Zoetendal EG, et al. Diversity of human small intestinal Streptococcus and Veillonella populations. FEMS Microbiol Ecol. 2013;85: 376–388. pmid:23614882
View Article
PubMed/NCBI
Google Scholar

[117] View Article

[118] PubMed/NCBI

[119] Google Scholar

[ref32] 32. Bedran TBL, Marcantonio RAC, Neto RS, Mayer MPA, Grenier D, Spolidorio LC, et al. Porphyromonas endodontalis in chronic periodontitis: A clinical and microbiological cross-sectional study. J Oral Microbiol. 2012;4: 1–7. pmid:22232719
View Article
PubMed/NCBI
Google Scholar

[121] View Article

[122] PubMed/NCBI

[123] Google Scholar

[ref33] 33. Nóbrega LMM, Montagner F, Ribeiro AC, Mayer MAP, Gomes BPF de A. Bacterial diversity of symptomatic primary endodontic infection by clonal analysis. Braz Oral Res. 2016;30: e103. pmid:27737357
View Article
PubMed/NCBI
Google Scholar

[125] View Article

[126] PubMed/NCBI

[127] Google Scholar

[ref34] 34. Schülin S, Schlichting N, Blod C, Opitz S, Suttkus A, Stingu CS, et al. The intra- and extraluminal appendiceal microbiome in pediatric patients. Med (United States). 2017;96: 1–7. pmid:29384958
View Article
PubMed/NCBI
Google Scholar

[129] View Article

[130] PubMed/NCBI

[131] Google Scholar

[ref35] 35. Elhag KM, Alwan MH, Al-Adnani MS, Sherif RA. Bacteroides fragilis is a silent pathogen in acute appendicitis. J Med Microbiol. 1986;21: 245–249. pmid:3517340
View Article
PubMed/NCBI
Google Scholar

[133] View Article

[134] PubMed/NCBI

[135] Google Scholar

[ref36] 36. Ranieri DM, Enzerra MD, Pickhardt PJ. Prevalence of appendicoliths detected at CT in adults with suspected appendicitis. Am J Roentgenol. 2020;216: 677–682. pmid:33474985
View Article
PubMed/NCBI
Google Scholar

[137] View Article

[138] PubMed/NCBI

[139] Google Scholar

[ref37] 37. Saxén H, Tarkka E, Hannikainen P, Nikku R, Rautio M, Siitonen A. Escherichia coli and appendicitis: Phenotypic characteristics of E. coli isolates from inflamed and noninflamed appendicesfile://utuhome.utu.fi/sahevan/MAPPAC/artikkelit luet/23-5-1038.pdf. Clin Infect Dis. 1996;23: 1038–1042. pmid:8922799
View Article
PubMed/NCBI
Google Scholar

[141] View Article

[142] PubMed/NCBI

[143] Google Scholar

[ref38] 38. Martirosian G, Bulanda M, Wojcik-Stojek B, Obuch-Woszczatynski P, Rouyan G, Heczko P, et al. Acute appendicitis: the role of enterotoxigenic strains of Bacteroides fragilis and Clostridium difficile. Med Sci Monit. 2001;7: 382–386. pmid:11386013
View Article
PubMed/NCBI
Google Scholar

[145] View Article

[146] PubMed/NCBI

[147] Google Scholar

Figures

Abstract

Background

Methods

Results

Conclusion

Study registration

Introduction

Methods

Study design and patients

Outcomes

Sample collection and processing

16S rRNA amplicon sequencing

Statistical and bioinformatical analysis

Study approval

Results

Differing microbial signatures in uncomplicated and complicated acute appendicitis

Species poor appendiceal microbiomes are predominated by specific bacterial species

Discussion

Supporting information

S1 Fig. Appendiceal microbiome in phylum and genus level in uncomplicated and complicated acute appendicitis.

S1 Table. Differentially abundant bacterial species and genera between uncomplicated and complicated appendicitis.

S2 Table. Relative abundance of species in uncomplicated and complicated appendicitis.

Acknowledgments

References