Studying on the Difference Between Two Kinds of Osteomyelitis

Sponsor

Nanfang Hospital of Southern Medical University (Other)

Overall Status

Completed

CT.gov ID

NCT04240964

Collaborator

(none)

Enrollment

Location

Actual Duration (Months)

1.6

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

To explore the microbial differences of diabetic foot osteomyelitis and osteomyelitis without diabetes.

Condition or Disease	Intervention/Treatment	Phase
Diabetic Foot Osteomyelitis Diabetic Foot Infection Microbiome

Detailed Description

Diabetic foot osteomyelitis (Dd group) subjects (sample size ≥ 10 cases) and foot osteomyelitis without diabetes (ND group) subjects (sample size ≥ 10 cases) were collected in accordance with the inclusion criteria. Surgeons collected intra-operative bone specimens from all 28 patients who required surgical intervention (debridement or amputation) for management of their osteomyelitis[10]. Avoided soft tissue or sinus tract cultures, because they were not sufficiently accurate in predicting bone pathogens[11]. Following surgical debridement of infected or necrotic tissue, cleansed by sterile saline solution, deep bone specimens were harvested using sterile instruments. We routinely obtained adequate bone specimens and divided them into three parts. One for routine microbiology culture and antibiotic sensitivity testing, one for the histopathology, and the other one for DNA sequencing analysis. This process to obtain bone specimens could reduce chances of contamination by wound tissue colonizing bacteria.

16S rRNA high-throughput sequencing Two specimens were sent to the laboratory for conventional culturing and histopathological tests. The bone specimen left were placed in sterile pipes without any transport medium and stored at 4℃ for 24 hours and then frozen at -80C until DNA extraction. Genomic DNA was extracted using DNA extraction kit (YiRui,ShenZhen,China) according to the manufacturer's instructions. Extracted DNA was quantitative and quality control by agarose gel electrophoresis(JS-power 300, PeiQin, ShangHai, China). Then we amplified the V3-V4 variable region of the 16S rRNA gene for sequencing using a forward and a reverse fusion primer-（341F：5'-CCTAYGGGRBGCASCAG-3' and 806R：5'-GGACTACNNGGGTATCTAAT-3）(ABI GeneAmp 9700 PCR Instrument). PCR products were amplified by removing short sequences, singleton sequences and noisy reads. The PCR reaction was performed in a total volume of 60 μl, containing 6 μl of 10× Ex Tap PCR buffer, 6 μl of dNTP mixture, 0.6μl of bovine serum albumin (BSA), 0.3 μl Ex Tag, 1μl DNA, 1.2μl forward and reverse primers, and 43.7 μlH 2O. The PCR amplification was conducted under following conditions: initial denaturing was conducted at 94°Cfor5min, which was followed by 27 cycles at94°Cfor30s, 55°Cfor30s, and72°C for 45s. A final extension was performed at 72°C for 10min from 28 samples (including DFO and SFO patients) were sequenced over two separate runs on Illumina Miseq. To get high-quality clean reads, raw reads were filtered according to the following rules: (1) remove reads containing morethan10% ofunknown nucleotides and(2) removereads containing less than 80% of bases with quality (Q-value)>20. The filtered reads were then assembled into tags according to overlap between paired-end reads with more than 10bp overlap, and less than 2% mismatch. The software Mothur (v.1.34.0) was used to remove the redundant tags to get unique tags. The obtained unique tags were then used to calculate the abundance.Then we clustered sequences into operational taxonomic units (OTUs) using the Greengene. Taxonomy was assigned to OTUs using the BLASTto the Greengene database at 97% similarity to identify microorganisms at the genera level (species level where possible). A phylogenetic tree was built from aligned representative OTU sequences using figtree.The total species diversity in a landscape was determined by two different parameters, the mean species diversity in sites or habitats at a more local scale (alpha diversity) and the differentiation among those habitats (beta diversity). Alpha diversity included both community diversity and richness: community richness was represented by the ACE estimator or the Chao1 estimator. Beta diversity was the calculation of differences(distance) between microbiome community structure and membership based on the evolution of species. This kind of distance was calculated using Weighted Unifrac and can be performanced by Principal Co-ordinates Analysis diagram.

Metagenomes Analysis A metagenome DNA libraries from specimens were constructed using TruSeq Nano DNA kit (FC-121-4002) according to the manufacturer's instructions, with slight modifications. In brief, the length conformed DNA(350 bp) was obtained by sonication. DNA fragments were end-repaired and the appropriate library size was selected, then the samples were A-tailed and ligated to adapters. The NovaSeq 6000 sequencing systems（Illumina）were used for sequencing and library validation Raw Data obtained by sequencing have a certain proportion of low-quality dataaccording to the following rules: (1) remove reads containing morethan10% ofunknown nucleotides and(2) removereads containing less than 80% of bases with quality (Q-value)>20 . Megahit was used to splice the sequences（clean data） after quality control, and contigs were obtained.Contigs were filtered below 1000bp. The vector and host sequences were filtered by BLASTN, with an E-value cutoff of 1e-5. The remaining reads were mapped to the human genome by SOAP alignment, and the matching reads were removed as being contaminants from the host genome.The taxonomic classifications were performed on assembled contigs and singletons using BLAST against the NCBI database. And the best BLAST hit was used to refer the taxonomic rank of each sequence. All the analyses have been performed in R and p values were corrected for multiple testing with the false discovery rate method.

Study Design

Study Type:

Observational

Actual Enrollment :

28 participants

Observational Model:

Case-Control

Time Perspective:

Prospective

Official Title:

Studying on the Difference Between Foot Osteomyelitis Patients With or Without Diabetes

Actual Study Start Date :

Jul 1, 2017

Actual Primary Completion Date :

Dec 1, 2018

Actual Study Completion Date :

Dec 1, 2018

Arms and Interventions

Arm	Intervention/Treatment
Dd group Patients with diabetic foot osteomyelitis
ND group Foot osteomyelitis without diabetes

Outcome Measures

Primary Outcome Measures

Composition and Diversity of DFO with 16S rRNA Gene Data [2017-2018]
Subjects who met the inclusion criteria for diabetic foot osteomyelitis (DFO) (sample size ≥ 10) and osteomyelitis without NDFO (sample size ≥ 10) were collected for debridement and amputation for 16s rDNA high-throughput sequencing. Compare microbe composition and diversity between the two groups.
Composition of the DFO Metagenome [2018-2019]
Subjects who met the inclusion criteria for diabetic foot osteomyelitis (DFO) (sample size ≥ 10) and osteomyelitis without NDFO (sample size ≥ 10) were collected for debridement and amputation for Metagenomic Analysis. Compare microbe composition and diversity between the two groups.

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years to 80 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

age≥18 years old.
diagnosed as foot osteomyelitis, and wounds were located below the knee joint.
nfected bone exposure or positive probe-to-bone test.
The patients were good physical condition.
Patients were able to tolerate debridement or operation treatment.
patients and their families agreed to participate in the study.

Exclusion Criteria:

Serious skin diseases around the wound surface;
tumors affecting the wound of osteomyelitis;
long-term use of immunosuppressive therapy before admission;
patients that do not cooperate.

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Department of Endocrinology and Metabolism, NanFang Hospital, Southern Medical University	Guangzhou	Guangdong	China	510515

Sponsors and Collaborators

Nanfang Hospital of Southern Medical University

Investigators

Principal Investigator: ying cao, doctor, Nanfang Hospital of Southern Medical University

Study Documents (Full-Text)

None provided.

More Information

Publications

Responsible Party:

Ying Cao, associate professor, Nanfang Hospital of Southern Medical University

ClinicalTrials.gov Identifier:

NCT04240964

Other Study ID Numbers:

NFEC-2017-013

First Posted:

Jan 27, 2020

Last Update Posted:

Jan 27, 2020

Last Verified:

Jan 1, 2020

Individual Participant Data (IPD) Sharing Statement:

Undecided

Plan to Share IPD:

Undecided

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Keywords provided by Ying Cao, associate professor, Nanfang Hospital of Southern Medical University

Diabetic Foot Osteomyelitis

16S rRNA

Metagenomes

Microbiome

Additional relevant MeSH terms:

Osteomyelitis

Diabetic Foot

Study Results

No Results Posted as of Jan 27, 2020