1. Introduction
Burkholderia cepacia is found as part of the B. cepacia complex (Bcc), a collection of highly pathogenic organisms. The Bcc is present almost everywhere in nature; however, it is most prevalent in damp settings, plant roots, and soils. Moreover, Bcc is a major source of morbidity and death in patients due to its high intrinsic antibiotic resistance. Immunocompromised people, particularly those with cystic fibrosis, are the most typically affected ( 1 ).
B. cepacia is a gram-negative bacteria that is rod-shaped, non-sporeforming, motile, catalase-positive, and lactose-intolerant. It is a common environmental species that has been isolated as free-living microorganisms, and they dwell in close proximity to a variety of animals, plants, ameobozoon hosts, and fungal spores. The emergence of microbial genes involved in the biodegradation of foreign body molecules has the potential to be a significant and beneficial advance in the battle against pollution. Many strains of these bacteria have been isolated from various plants and have been documented to promote host plant growth, produce antifungal metabolites, and degrade organic contaminants ( 2 ).
B. cepacia is a complex of organisms that includes nine distinct genomovars. While the phenotype of genomovars is similar, the genotype is distinct. Some of them have already been given their own genus and species names. Genomovar III, which comprises some of B. cenocepacia's most infectious strains, was transferred to the species designation in 2002.
Until the mid-1980s, when it was discovered as a nosocomial infection in cystic fibrosis clinics, this bacteria remained virtually unknown as a human disease ( 3 ). B. cepacia, like many other opportunistic infections, may infect anyone in any situation. However, for reasons that are now unknown, the organism "prefers" the lungs of cystic fibrosis patients. According to a 2016 research conducted by the Cystic Fibrosis Foundation's National Patient Registry, B. cepacia was discovered in 2.6 percent of all cystic fibrosis patients in the United States ( 4 ). Furthermore, the B. cepacia strain or B. cenosepacia from genomovar III appears to be the primary source of these more severe illnesses. Although different genomovars can cause infections in cystic fibrosis patients, genomovar III is responsible for nearly half of all cystic fibrosis infections in the United States and 80% in Canada.
2. Materials and Methods
2.1. Samples Collection and Inoculation
Samples were collected from patients suffering from diabetic foot ulcers, urine, burn, wound, sputum, and discharge from the eyes, who attended Al-Sader Medical City, Al-Hakim General Hospital in AL-Najaf, Iraq, between September 2020 and February 2021. The samples were obtained from both sexes with the age range of 1-75 years. The specimens were carried by sterile transport swabs and injected onto culture media using a direct technique of inoculation, as well as a specific medium solely for B. cepacia development was used. The inoculation was performed at 37°C for 18-24 h, as previously described by Cheesbrough ( 5 ). After staining with Gram stain, all probable isolates were examined under the microscope and revealed to be gram-negative single short bacilli. The B. cepacia isolates cultured on MacConkey agar medium emerged as non-lactose fermenters, tiny, light-pink color colonies that became dark-pink to red after 4-7 days, due to lactose oxidation. Table 1 shows the distribution of 280 samples: the lowest prevalence was in the age groups above (61-75) 7%, and the highest incidence was in the age group of (31-45) 26.4 %.
| Sex | Age group No. (%) | |||||
|---|---|---|---|---|---|---|
| 1-15 | 16-30 | 31-45 | 46-60 | 61-75 | total | |
| Female | 21 (8.4) | 9 (3.6) | 13 (5.2) | 9 (3.6) | 2 (0.8) | 54 (21.6) |
| Male | 41 (16.4) | 45 (18) | 55 (22) | 43 (17.2) | 12 (4.8) | 196 (78.4) |
| Total | 62 (24.8) | 54 (21.6) | 68 (27.2) | 52 (20.8) | 14 (5.6) | 250 (100%) |
2.2. Morphologically Characterization
Initial identification of bacterial isolates acquired from clinical samples was based on culture morphology, microscopic features, and biochemical assays. The B. cepacia seemed to be a gram-negative bacilli under the microscope; however cultural identification of B. cepacia was based on colonial morphology. Since B. cepacia colonies were cultivated on blood agar, they appear to be diffuse-haemolytic ( 6 , 7 ).
Non-lactose fermenting colonies of B. cepacia grew on MacConkey agar and generated pigment on other medium, as shown in figure 1. According to the previously described method ( 8 ).
Figure 1. Growth of B. cepacia on (A) β-hemolytic on blood agar medium, (B) MacConkey agar medium
3. Results and Discussion
3.1. Biochemical Testing
The results of biochemical tests are shown in table 2. The biochemical tests are regarded as a useful addition to the initial identification of the B. cepacia isolate. Isolates were positive for oxidase, catalase, motility, citrate utilization, gelatinize, and dirt-like odor. The isolates were negative for urease production, Voges-Proskauer, and methyl red test, which is consistent with Alnasrawy and AL-Aammar ( 7 ), while indole production and H2S production tests were positive.
| No. | Biochemical test | Result | No. of the total samples (80) | Percentage | No. samples based on PCR (20) | Percentage |
|---|---|---|---|---|---|---|
| 1 | Catalase | + | 60 | 75% | 20 | 100% |
| 2 | H2S production | + | 40 | 50% | 16 | 80% |
| - | 40 | 50% | 4 | 20% | ||
| 3 | Triple sugar iron (TSI) | K/A | 50 | 62.5% | 20 | 100% |
| 4 | Oxidase | + | 55 | 68.7% | 13 | 65% |
| - | 25 | 31.3% | 7 | 35% | ||
| 5 | Indole production | + | 42 | 52.5% | 15 | 75% |
| - | 38 | 47.5% | 5 | 25% | ||
| 6 | Citrate utilization | + | 35 | 43.7% | 20 | 100% |
| 7 | Motility | + | 62 | 77.5% | 20 | 100% |
| 8 | Growth at 42oC | + | 20 | 25% | 3 | 15% |
| - | 60 | 75% | 16 | 80% | ||
| 9 | Voges-Proskauer (VP) | - | 62 | 77.5% | 20 | 100% |
| 10 | Smell | Dirt-like odor | 46 | 57.5% | 20 | 100% |
3.2. ID-GNB Cards and the VITEK 2 System
The results showed that from 45 identified samples, 16 (20%) isolates were with confidence values of 99-96% (excellent identification), 9 (11.2%) isolates showed confidence values of 96-95% (very good identification), and only 20 (25%) isolates manifested confidence values of 89% according to the initial examination of the Gram stain. The B. cepacia isolates were divided into 11 groups, each assigned to a bio-pattern based on the obtained results.
3.3. Analytical Profile Index (API) Microsystems
The API 20E test revealed that from 80 samples, 33 (41.3%) isolates were exactly identified, 22 (27.5%) showed the nearest identification, and 25 (31.2%) had no identity (Table 3).
| Description of groups | Codes of test results | Numbers of isolates |
|---|---|---|
| First group (Exact identity) | (6 300 009) | 1,4,6,10,13,8,9,16,20,21,30,31,33,36,39,41,64,68,71,73,75,59,60,62,63,66,69,70,72,74,78,79 |
| Second group (nearest identity) | (6 301 007) | 3,14,17,22,12,23,26,27,34,35,42,46,48,50,52,53,56, 44,45,49,51,58 |
| Third group (no identity) | (6 301 000) | 5,7,24,25,28,29,32,37,38,40,43,47,54,55,57,61,65,67,76,77,15,18,19,11,2 |
3.4. RecA Gene Identification of B. cepacia
The recA gene was used to detect the bacterium B. cepacia. The present study found that the recA gene was found in 30 of 45 samples tested using the VITEK 2 System, as shown in figure 2.
Figure 2. PCR results of B. cepacia isolates amplified with recA gene primers, having a product size of 429 bp. DNA molecular size marker Lane (L) (100-bp ladder).
The recA gene has been widely utilized in bacterial systematics. It has proven to be particularly beneficial for identifying Bcc species. The recA gene with a phylogenetic analysis of sequence variation within the gene allows all nine current species within the Bcc to be distinguished.
However, the original recA-based PCR primers, BCR1 and BCR2, are specific to members of the Bcc and do not amplify this gene in other B. cepacia species. While this can be a useful way of confirming an isolate's location within the complex, it limits the technique's application to classifying other B. species in different natural environments ( 9 ).
3.5. 16S rDNA Gene
As shown in figure 3, the 16S rDNA was found in all B. cepacia isolates. The 16S rDNA gene comprises highly conserved nucleotide sequences interspersed with genus- or species-specific variable sections. Bacteria can be classified by analyzing the nucleotide sequence of the PCR result and comparing it to known sequences in a database ( 10 ). Due to the widespread use of PCR and DNA sequencing in clinical microbiology laboratories over the last decade, 16S rDNA sequencing has played a critical role in the correct identification of bacterial isolates and the discovery of novel bacteria.
Figure 3. PCR results of B. cepacia isolates amplified with 16S rDNA gene primers, having a product size of 1020 bp. Lane (L): DNA molecular size marker (100-bp ladder); all isolates had positive 16S rDNA gene.
In the case of bacteria with unusual phenotypic profiles, uncommon bacteria, slow-growing bacteria, uncultivable bacteria, and culture-negative illnesses, 16S rDNA sequencing is very significant for bacterial identification. It has not only provided study into the etiologies of infectious diseases, but it has also assisted clinicians in selecting medicines, determining the length of therapy, and managing infection measures. Of 215 new bacterial species, 29 belonged to unique genera and were found in human specimens using 16S rDNA sequencing in the twenty-first century (2001-2007) ( 11 ).
3.6. Numerical Taxonomy and Cluster Analysis
Many studies used numerical taxonomy to classify and identify problems of bacteria and other microorganisms. Cluster analysis refers to a class of methods of data reduction used to sort events, results, or variables from a given data set into homogeneous classes that differ from each other ( 7 ). The numerical review focused on the results of the research on the general characteristics, bio-patterns, anti-bio patterns, and virulence patterns of the B. cepacia isolates under study:
Depending on Sj and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) clustering from numerical analysis of the biochemical tests (Table 4), the dendrogram (Figure 4) consists of three major clusters, A, B, and C, which could be distinguished at Sj ≥ 33.3%.
| biochemical tests | Percentage of positive tests | ||
|---|---|---|---|
| Cluster A | Cluster B | Cluster C | |
| TSI | 100% | 100% | 100% |
| H2S production | 62.5% | 85.7% | 100% |
| VP | 0 | 0 | 0 |
| Catalase | 100% | 100% | 100% |
| Oxidase | 75% | 57.1% | 60% |
| Motility | 100% | 100% | 100% |
| Indole production | 100% | 57.1% | 60% |
| Citrate utilization | 100% | 100% | 100% |
| Growth at 42oC | 25% | 14.2% | 0 |
| Smell | 100% | 100% | 100% |
| Growth on Cetrimide agar medium | 25% | 57.1% | 80% |
Figure 4. Hierarchical tree chart for B. cepacia 20 isolates obtained from cluster analysis using Jaccard’s Coefficient depending on biochemical tests patterns. Cluster A included 10 (50%) B. cepacia isolates and was divided into several sub-clusters, namely (18, 15, 17, 10, 12, 3, 8, 5, 14). Cluster B isolates included 4 (20%) B. cepacia isolates and was divided into sub-clusters (2, 11, 16, 6). Cluster C isolates included 6 (30%) of B. cepacia isolates and were divided into several sub-clusters, namely (4, 19, 1, 9, 13, 7).
Cluster A (Sj≥33.3%) included 10 (50%) B. cepacia isolates which were divided into several sub-clusters. Cluster A isolates belong to (9) bio-patterns, namely (18, 15, 17, 10, 12, 3, 8, 5, 14), to (9) anti-bio patterns, namely (20, 15, 17, 10, 12, 3, 8, 5, 14), and also belongs to (7) virulence patterns, namely (20, 15, 17, 10, 12, 8, 5).
Cluster B isolates (Sj ≥ 32.6%) included 4 (20%) B. cepacia isolates and were divided into some sub-clusters, namely (2, 11, 16, 6). Cluster B isolates belong to (2) anti-bio patterns, namely (11, 6), and to (1) virulence pattern, namely (2).
Cluster C isolates (Sj≥33.9%) included 6 (30%) B. cepacia isolates and were divided into several sub-clusters, namely (4, 19, 1, 9, 13, 7).
From the numerical analysis of the virulence factor tests (Table 5) and based on Sj and UPGMA clustering, there are two major clusters, A and B, as shown in the dendrogram (Figure 5), which could be distinguished at Sj ≥ 67.9%.
| Virulence factors | Percentage of positive tests | |
|---|---|---|
| Cluster A | Cluster B | |
| Phospholipase C | 100% | 100% |
| Urease | 68.7% | 50% |
| Siderophore production | 100% | 100% |
| Capsule Detection | 100% | 100% |
| Gelatinase | 68.7% | 100% |
| Hemolysis on blood agar | 50% | 75% |
| Biofilm Formation | 100% | 0 |
Figure 5. Hierarchical tree chart for B. cepacia 40 isolate obtained from cluster analysis using Jaccard’s Coefficient depending on virulence patterns. Cluster A included 15 (75%) B. cepacia isolates and were divided into several sub-clusters, namely (10, 17, 6, 11, 16, 8, 19, 4, 5, 13, 12, 15). Cluster B isolates included 4 (20%) B. cepacia isolates and were divided into some sub-clusters, namely (3, 9, 2, 14).
Cluster A (Sj≥67.9%) included 15 (75%) B. cepacia isolates and were divided into several sub-clusters. Cluster A isolates belong to (12) bio-patterns, namely (10, 17, 6, 11, 16, 8, 19, 4, 5, 13, 12, 15) and to (12) anti-bio patterns, and also belong to (10) biochemical tests patterns, namely (20, 10, 17, 6, 11, 16, 8, 5, 12, 15). Cluster B isolates (Sj≥67.9%) included 4 (20%) B. cepacia isolates and were divided into some sub-clusters, namely (3, 9, 2, 14). Cluster B isolates belong to (1) biochemical pattern, namely (9).
From the numerical analysis of the bio-patterns (Table 6), depending on Sj and UPGMA clustering, there are two major clusters, A and B, as shown in the dendrogram (Figure 6) which could be distinguished at Sj ≥ 7.16%.
| Tests | Percentage of positive tests | Tests | percentage of positive tests | Tests | percentage of positive tests | |||
|---|---|---|---|---|---|---|---|---|
| Cluster A | Cluster B | Cluster A | Cluster B | Cluster A | Cluster B | |||
| APPA | 35.7% | 50% | PLE | 0 | 83.3% | dMAN | 0 | 33.3% |
| ADO | 35.7% | 16.6% | TyrA | 14.2% | 83.3% | BXYL | 0 | 16.6% |
| PyrA | 0 | 0 | URE | 14.2% | 16.6% | BAIap | 14.2% | 33.3% |
| IARL | 85.7% | 50% | dSOR | 7.1% | 50% | ProA | 16.6% | 50% |
| dCEL | 71.4% | 33.3% | SAC | 7.1% | 33.3% | LIP | 7.1% | 16.6% |
| BGAL | 0 | 33.3% | dTAG | 7.1% | 33.3% | CMT | 50% | 83.3% |
| H2S | 42.8% | 50% | dTRE | 14.2% | 16.6% | BGUR | 16.6% | 0 |
| BNAG | 14.2% | 16.6% | CIT | 42.8% | 66.6% | O129R | 35.7% | 83.3% |
| AGLTp | 78.5% | 50% | MNT | 35.7% | 50% | GGAA | 0 | 16.6% |
| dGLU | 85.7% | 100% | 5KG | 0 | 0 | ODC | 7.1% | 0 |
| GGT | 14.2% | 50% | ILATK | 28.5% | 83.3% | LDC | 0 | 33.3% |
| OFF | 14.2% | 0 | AGLU | 14.2% | 0 | IHISa | 0 | 0 |
| BGLU | 0 | 50% | SUCT | 7.1% | 66.6% | IMLTa | 14.2% | 66.6% |
| dMAL | 25% | 33.3% | NAGA | 0 | 16.6% | GIyA | 7.1% | 0 |
| ELLM | 0 | 33.3% | AGAL | 0 | 50% | |||
| ILATa | 0 | 16.6% | PHOS | 7.1% | 16.6% | |||
Figure 6. Hierarchical tree chart for B. cepacia 40 isolates obtained from cluster analysis using Jaccard’s Coefficient depending on VITEK 2 System. Cluster A included 17 (85%) B. cepacia isolates divided into several sub-clusters. Cluster B included 3 (15%) B. cepacia isolates were divided into one sub-cluster (7, 20, 1) and a single isolate number (1).
Cluster A (Sj≥7.16%) included 17 (85%) B. cepacia isolates which were divided into several sub clusters. Cluster A isolates belong to (13) virulence patterns,
namely (17, 19, 12, 8, 13, 10, 16, 18, 11, 5, 15, 4) and belong to (14) anti-bio patterns, namely (9, 17, 19, 12, 8, 13, 2, 10, 3, 16, 14, 5, 15, 4).
Cluster B (Sj≥7.16%) included 3 (15%) B. cepacia isolates that were divided into one sub-cluster and a single isolate number (1). Cluster B isolates belong to (1) anti-bio patterns, namely (1).
Figure 7 shows the numerical analysis of the anti-bio patterns (Table 7), depending on Sj and UPGMA clustering. As shown by the dendrogram, there are two major clusters, A and B, which could be distinguished at Sj ≥ 37.2%.
Figure 7. The hierarchical tree chart for B. cepacia 20 isolates was obtained from cluster analysis using Jaccard’s Coefficient depending on anti-bio patterns only. Cluster A included 16 (80%) B. cepacia isolates divided into several sub-clusters and five single isolates (3, 10, 4, 14, 2, 20). Cluster B included 4 (20%) B. cepacia isolates divided into two sub-clusters isolates (11, 18, 1, 6).
| Antibiotic pattern | Percentage of positive tests | |
|---|---|---|
| Cluster A | Cluster B | |
| GM | 25% | 25% |
| CIP | 12.5% | 25% |
| AK | 18.7% | 50% |
| IMP | 50% | 0 |
| MEM | 50% | 0 |
| AZM | 56.2% | 75% |
| B | 18.7% | 100% |
| TOB | 12.5% | 0 |
| CAZ | 68.7% | 100% |
| OFX | 0 | 0 |
| LEV | 31.2% | 0 |
| PRL | 12.5% | 0 |
| TIM | 6.2% | 25% |
| FEP | 6.2% | 0 |
Cluster A (Sj≥37.2%) included 16 (80%) B. cepacia isolates which were divided into several sub-clusters and five single isolates, namely (3, 10, 4, 14, 2, 20).
Cluster A isolates belong to (12) virulence patterns, namely (17, 19, 5, 12, 10, 4, 8, 16, 13, 15, 7, 20), belong to (9) biochemical patterns, namely (17, 3, 5, 12, 10, 8, 15, 14, 20), and also belong to (11) bio-patterns, namely (9, 17, 19, 5, 12, 4, 8, 16, 13, 15, 14).
Cluster B (Sj≥37.2%) included 4 (20%) B. cepacia isolates that were divided into two sub-clusters isolates, namely (11, 18, 1, 6). Cluster B isolates belong to (1) biochemical patterns, namely (1), and belong to (1) bio-patterns, namely (1).
As shown in Figure 8, the dendrogram consists of two major clusters, A and B, based on all bio-patterns, anti-bio patterns, virulence patterns, and biochemical tests.
Figure 8. The hierarchical tree chart for B.cepacia 40 isolates was obtained from cluster analysis using Jaccard’s Coefficient depending on all bio-, anti-bio, virulence patterns, and biochemical tests.
From these variations, we also achieved the numerical taxonomy of these dendrograms and the similarities between B. cepacia isolates in this study showed that different strains of cepacia bacteria were present in certain hospitals in Al-Najaf Al-Ashraf city, Iraq.
Authors' Contribution
Study concept and design: S. A. A.
Acquisition of data: S. A. A.
Analysis and interpretation of data: L. M. A.
Drafting of the manuscript: S. M. J.
Critical revision of the manuscript for important intellectual content: L. M. A.
Statistical analysis: S. A. A.
Administrative, technical, and material support: L. M. A.
Ethics
The human study was approved by Altoosi University College, Najaf, Iraq Review Board.
Conflict of Interest
The authors declare that they have no conflict of interest.
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