Source tracking and community profiles of antibiotic resistant bacteria in wastewater samples

Jesús Sigala and Felly Rose Montelya

Mentor: Dr. Adrian UncPlant and Environmental Sciences,

NMSU

NEW MEXICO AMPALLIANCE FOR MINORITY PARTICIPATION

Research background and relevance

Wastewater treatment plants treat waste generated from various sources including residential, industrial, schools, hospital and medical centers:

screening and removal of non-degradable solids, physical removal of suspended solids to produce biosolids, biological treatment chemical treatment (chlorination)

Treated wastewater is ultimately discharged to surface waters

However, some microbes survive treatment; these may include pathogens and antibiotic resistant microbes

Discharge of antibiotic resistant microbes affect water quality, has ecological concerns, and poses public health concerns

Wastewater samples

Pretreatment—influent After treatment—effluent

Previous results

Antib

iotic

resi

stan

ce (%

cfu

E. c

oli)

Tetrac

ycline

Nalidix

ic Acid

Kanam

ycin Su

lfate

Gentam

icin Su

lfate

Doxycy

cline

Ciprofl

oxacin

HCL

Cefaclo

r

100

80

60

40

20

0

Sampling point

Final clarifiersChlorination/dechlorination

InfluentPrimary clarifiersRoughing filtersAeration basins

Ratio of antibiotic resistant E. coli at different wastewater treatment stages

Two observations: 1) For all antibiotics, the proportion of antibiotic resistant E. coli generally increases throughout the treatment with significant selection during aeration stage 2) Chlorination is most effective at eliminating resistant E. coli (but not perfect)

Research goalsAssess a source tracking method that allows identification of pre-treatment sources Profile the antibiotic resistant bacterial community in wastewater using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE)

Determine the impact of wastewater sources on the microbial quality of effluent discharge

Microbial Source Tracking

Common method to identify source of pollution in food and water contamination sources

Compare source and environmental samples

Specific characteristics to compare include antibiotic resistance, mutation, or DNA fingerprint (Pillai and Vega, 2007)

Wastewater sampling

Four lifting stations representing distinct sources Residential Industrial University Hospital

Six stages of treatment Influent Primary clarifier Trickling (roughing) filters Aeration basin Secondary clarifier Chlorination tank

Three samples from each location over a period of two days for composite samples

Lifting stations and wastewater treatment plant

Primary clarifiers at the treatment plantUniversity wastewater lifting station

Lab methods

Selection of antibiotic resistant populations by plating on MH agar using antibiotic agar dilution method at four concentrations according to EUCAST (www.eucast.org) Antibiotics included: Erythromycin, Doxycycline, Cefaclor, Ciprofloxacin

Extraction of DNA from the antibiotic selected populations (MoBio extraction kit)

Quantification of DNA by UV absorbance at 260 nm PCR amplification

rpoB primers (rpoB 1698F, with GC clamp at 5’ end, and rpoB 2041R)

Thermocycler program as described by Peixoto et al. (2002) Polyacrylamide gels (6%) cast for DGGE (40% to 60% denaturing gradient)

DGGE performed for 14 hours at 85 V DGGE gels were silver stained

Results and discussion

Microbial growth from all samples and antibiotic concentrations

DGGE and analysis for all samples to be completed

DGGE will allow comparison of population diversity between different samples with interest in Dissimilarity between lifting stations Similarity between lifting stations and wastewater treatment samples

DGGE

• Lane 1: DGGE standard• Lanes 2-7: samples• Lane 8: (empty)• Lane 9: DGGE standard

Future goals

Complete DGGE for all samples

Analyze DGGE fingerprints using statistical methods

Propose a novel source tracking method for identification of sources of antibiotic resistant microbial contaminants

Propose future research aimed at improved targeting of the actual treatment protocols

ConclusionSampling of lifting stations and wastewater treatment plant allows us to separate different sources

PCR/DGGE can be used to profile bacterial diversity and develop a source tracking method

Source impact on antibiotic resistance microbial load and community profile in wastewater treatment can be determined

Acknowledgements

NM AMP NSF Grant #NSF HRD 083171 and NM WRRI for their support and interest in our research

Dr. Unc for the support, guidance, review, and assistance during sampling and lab work

Jeanne Garland, Polina Chemishanova, Gloria Vasquez, Joy Pugh, and other AMP staff who contributed in various ways to the research project

References

Bitton, G. 2005. Wastewater microbiology, 3rd ed. Wiley, Hoboken, New Jersey.

Dahllöf, I., H. Baillie, and S. Kjelleberg. 2000. rpoB-Based microbial community analysis avoids limitations inherent in 16S rRNA gene intraspecies heterogeneity. Applied and Environmental Microbiology. 66: 3376-3380.

Felske, A., and A. M. Osborn. 2005. DNA fingerprinting of microbial communities. In A. M. Osborn and C. J. Smith (ed.), Molecular microbial ecology. Taylor & Francis Group, New York.

Peixoto, R. S., H. L. da Costa Countinho, N. G. Rumjaneck, A. Macrae, and A. S. Rosado. 2002. Use of rpoB and 16S rRNA genes to analyse bacterial diversity of a tropical soil using PCR and DGGE. Letters in Applied Microbiology. 35: 316-320.

Pillai, S., and E. Vega. 2007. Molecular detection and characterization tools. In J. W. Santo Domingo and M. J. Sadowsky (ed.) Microbial source tracking. ASM, Washington.

Wiegand, I., K. Hilpert, and R. E. W. Hancock. 2008. Agar and broth dilution methods to determine the minimal inhibitory concentration (MIC) of antimicrobial substances. Nature Protocols. 3: 163-175.