Isolation and Characterization of an unusually small aquatic bacterium
Sam Dempster
Introduction:
Humans like to think we are the top organisms on Earth; we live on every continent, we are numerous (~7 Billion individuals) and we can survive well in our environment. Humans for thousands of years had this superiority complex, but then something odd was discovered; microbes. These were found to outnumber humans billions to one. We had to accept that something that we can’t normally see with the unaided eye lives all around us, on us, and in us, and they’ve been doing it for billions of years before we showed up.
Microorganisms (or microbes for short) can be found in all domains of life; Bacteria, Archaea and Eukarya. I took Microbiology wanting to learn more about microbes and the world that they live in. For my semester long project of isolating and identifying a bacteria, I decided to sample the biofilm that forms in my aquarium and study a microbe that grew on my agar. I wanted to know if I could get a microbe that reduced ammonia or its byproducts like nitrate or nitrite. These bacteria are extremely important not just for natural bodies of water but for aquariums too, which reduce ammonia from fish metabolism to much less harmful nitrate.
Today, I will be presenting my data and try to identify my bacteria based on my physiological and genetic tests. I hypothesize that my bacteria will be a nitrogen reducer (known as a denitrifier), as these can be the most common microbe in many aquarium environments.
Methods:
To facilitate the tests for the semester, the bacteria had to be sampled from the environment. To do this, I used a sterile swab moistened with sterile water to take a sample of the biofilm that forms on top of my aquarium water. The sample was then streaked across a Tryptic Soy Agar (TSA) plate. These were sealed with parafilm and left to incubate in an open bag on top of the refrigerator upside down to prevent condensation.
A few days later, I observed a multitude of different bacteria colony growth on the TSA plate. During the second lab, I selected a small, fairly isolated yellow colony from the TSA plate and used the Quadrant Streak Method to try to isolate my bacteria for further tests. I let it incubate at 37oC in the sealed plate in between each streak. After 9 individual re-streaks, a pure isolate was finally achieved.
Once I believed I had a pure isolate, I performed a battery of physiological tests to profile my bacteria. These tests include: Gram Staining, fluid thioglycollate, streaking on MacConkey agar, catalase test strip and oxidase tests.
After physiological tests, I then performed whole genome sequencing to attempt to identify my isolate. I then extracted my bacteria’s DNA following the procedure laid out in Lab 5 using the PowerSoil ® DNA Isolation Kit. The DNA extract was then sent to the UAF Institute of Arctic Biology DNA Core Lab to be sequenced on an Illumina Miseq. I then performed two API test strips; the API 20E and API 20 STAPH. Interperating the results in Lab 6, my test strips gave me negative results across the board. I then analyzed the genomic data provided from the Illumina Miseq as outlined in Lab 7. This involved using applications on BaseSpace to assemble and analyze my data. Using SPAdes Genome Assembler, KRAKEN Metagenomics and Prokka Genome Annotation apps, I was able to narrow down the identification of bacterium as discussed below.
Results
I performed a battery of tests to try to identify my isolate. After performing the gram stain five times, my results point to a Gram-negative bacillus bacterium (Table 1). Oxidase and Catalayse tests both came back positive (Table 1). The fluid Thilloglycate tube tests suggested that my bacteria was a strict aerobe (Table 1). Genetic information points the identity of my bacteria towards Microbacterium sp., with the KRAKEN Metagenomics database giving an initial percentage of 92% unclassified and 2% Microbacterium (Figure 1). Of the 2% Microbacterium match, 62% of the DNA was attributed to Microbacterium testaceum (Figure 2). Reanalysis of the 92% unclassified contigs from Figure 1 show that 47% was attributed to Microbacterium testaceum (Figure 3). I then used BLAST to analyze the 34% unclassified contigs from Figure 3 and the two top results that showed both a Query Coverage and Identification Confidence score of 90% were Microbacterium paraoxydans and Microbacterium sp.
I tested my isolates antibiotic susceptible as outlined in Lab 9. This included doing two disk diffusion tests testing Cefoperazone, Vancomycin, Amikacin, Trimethoprim, Gentamicin, Oxacillin, Tobramycin and Cefazolin (Table 4). My isolate was susceptible to all antibiotics tested except Tobramycin, which was intermediate (Table 4).
In the tables below, x# represents the number of times a successful result was recorded (example: Gram Stain x5 means the Gram Stain was preformed 5 individual times resulting in the same data).
Table 1. Physiological traits of isolate
| Gram Stain x5 | Negative (-) |
| Cell physiology | Very Small, Rod Shaped (Bacillus) |
| Colony Phenotype | Glossy, yellow, slightly raised colonies |
| Catalase Test | Positive (+) |
| Oxidase Test x3 | Positive (+) |
| Fluid Thilloglycate Test | Strict Aerobe |
Table 2. Results of the API 20E test strip
| API 20E Physiological Test ID | API Test Result |
| ONPG | Negative (-) |
| ADH | Negative (-) |
| LDC | Negative (-) |
| CIT | Negative (-) |
| H2S | Negative (-) |
| URE | Negative (-) |
| TDA | Negative (-) |
| IND | Negative (-) |
| VP | Negative (-) |
| GEL | Negative (-) |
| GLU | Negative (-) |
| MAN | Negative (-) |
| INO | Negative (-) |
| SOR | Negative (-) |
| RHA | Negative (-) |
| SAC | Negative (-) |
| MEL | Negative (-) |
| AMY | Negative (-) |
| ARA | Negative (-) |
Table 3. Results of API 20 STAPH test strip
| API 20 STAPH Physiological Test ID | API Test Result |
| 0 | Negative (-) |
| GLU | Negative (-) |
| FRU | Negative (-) |
| MNE | Negative (-) |
| MAL | Negative (-) |
| LAC | Negative (-) |
| TRE | Negative (-) |
| MAN | Negative (-) |
| XLT | Negative (-) |
| MEL | Negative (-) |
| NIT | Negative (-) |
| PAL | Negative (-) |
| VP | Negative (-) |
| RAF | Negative (-) |
| XYL | Negative (-) |
| SAC | Negative (-) |
| MDC | Negative (-) |
| NAG | Negative (-) |
| ADH | Negative (-) |
| URE | Negative (-) |
Table 4. Results of Lab 9 antibiotic susceptibility tests
| Antibiotic | Zone of Inhibition (mm) | Susceptibility (mm) | Test conclusion |
| Cefoperazone | 26 | ≥18 | Susceptible |
| Vancomycin | 20 | ≥17 | Susceptible |
| Amikacin | 29 | ≥17 | Susceptible |
| Trimethoprim | 25 | ≥16 | Susceptible |
| Gentamicin | 28 | ≥15 | Susceptible |
| Oxacillin | 26 | ≥(13,18,20) | Susceptible |
| Tobramycin | 14 | ≥15 | Intermediate |
| Cefazolin | 22 | ≥18 | Susceptible |
Figure 1 showing the results of analyzed genomic data. This shows that a great majority of the genome (~92%) is unclassified in the KRAKEN Metagenomics database. This shows that 2% of the genome can be attributed to Microbacterium sp.
Figure 2 shows the zoomed in porting of the previous figure (fig 1). This shows that out of the different species under the family Microbacteriuaceae, 4,169 reads were attributed to Microbacterium tesstaceum.
Figure 3 showing the identification results of the unidentified contigs from the previous (fig 1) KRAKEN Metagenomics analysis. Out of the 92% unclassified genome, 47% was attributed to Microbacterium testaceum.
Figure 4 shows the BLAST results of the unclassified data from the previous figure (fig 3). The highest matches confirm the KRAKEN Metagenomics analysis. The two highest matches tied at 90% Query cover and Identification certainty are Microbacterium paraoxydans and Microbacterium sp.
Discussion
According to research, Microbacterium sp. can be found in many places, including being isolated on a potato leaf (Wang et al., 2010). Microbacterium sp., under the phylum of Actinobacteria, are known to be ubiquitous in soil and water environments (Embley and Stackebrandt 1994), and have even been isolated from the livers of lab mice (Buczolits et al., 2008). They have many different lifestyles and metabolic pathways (Servin et al., 2007). In the end, my hypothesis of my isolate being a denitrifier was neither supported nor denied as I do not believe the API test strips were designed to test the metabolic functions of my genus of bacteria.
There was one very serious discrepancy between genomic analysis and physiological tests. This being the gram stain test, with Microbacterium sp. should always Gram stain positive. As referenced in Table 1, five individual Gram stains found the bacterium to be Gram negative. Microbacterium is in the phylum Actinobacteria, which a defining characteristic being that they are all gram-positive bacteria. A closely related bacterium in the same phylum, Mycobacteria, is known as acid-fast Gram positive. When a bacteria shows acid-fastness, this means the bacteria will stain abnormally due to the presence of one of many different factors. These can range from the presence of mycolic acid in their cell walls to other cellular inclusions which either resist the ethanol or acid based de-colorization process. This can result in a negative result when the cell cannot retain the stain (perhaps like my bacteria) and it washes out with the ethanol (Morello et al., 2006).
To better identify my bacterium, I would potentially perform several more tests. This includes an acid-fast stain, perhaps the Ziehl—Neelsen stain. This would allow me to see if my bacterium is acid-fast positive, meaning it would Gram stain negative but have a Gram-positive physiology. I would also like to perform several different API test strips to try to determine what metabolic pathways my isolate possesses.
References
Buczolits, S., Schumann, P., Valens, M., Rosselló-Mora, R., & Busse, H. (2008). Identification of a bacterial strain isolated from the liver of a laboratory mouse as Microbacterium paraoxydans and emended description of the species Microbacterium paraoxydans Laffineur et al 2003. Indian Journal Of Microbiology, 48(2), 243-251. doi:10.1007/s12088-008-0035-0
Embley TM, Stackebrandt E. The molecular phylogeny and systematics of the Actinomycetes, Annu Rev Microbiol , 1994, vol. 48 (pg. 257-289)
Morello, Josephine A., Paul A. Granato, Marion E. Wilson, and Verna Morton. Laboratory Manual and Workbook in Microbiology: Applications to Patient Care. 10th ed. Boston: McGraw-Hill Higher Education, 2006. Print.
Servin, J., Herbold, C., Skophammer, R., & Lake, J. (2007). Evidence Excluding the Root of the Tree of Life from the Actinobacteria. Molecular Biology And Evolution, 25(1), 1-4. doi:10.1093/molbev/msm249
Wang, W., Morohoshi, T., Ikenoya, M., Someya, N., & Ikeda, T. (2010). AiiM, a Novel Class of N-Acylhomoserine Lactonase from the Leaf-Associated Bacterium Microbacterium testaceum. Applied And Environmental Microbiology, 76(8), 2524-2530. doi:10.1128/aem.02738-09
