Student performance study: the outcomes of metabolic, molecular and physical-chemical characterization of intestinal tract microbiome on a four mammalian species model

Authors

  • Nataša CIBER Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Tina ZUPANČIČ Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Tamara ZORAN Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Katarina ŠIMUNOVIĆ Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Anja PUGELJ Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Bojan PAPIĆ Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Nika KLINEC Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Andreja GAZVODA Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Benjamin DRAKSLAR Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Mateja DOLENC Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Group for Microbiology and Microbial Biotechnology, Microbiology MSc Student Joint Research Project 2013, Groblje 3, SI-1230 Domžale, Slovenia
  • Blaž STRES Univ. of Ljubljana, Biotechnical Fac., Dept. of Animal Science, Groblje 3, SI-1230 Domžale, Slovenia

DOI:

https://doi.org/10.14720/aas.2014.104.2.4

Keywords:

microbiology, mammals, intestinal tract, microbiota, metabolic profiling, student work, quality

Abstract

Many environmental factors influence the structure of microbial communities, their activity and properties of the environment of the digestive tract. Contrary to constant disturbances, the system provides the basis for energy conversion and thus the long-term stable coexistence of different hosts and their specific intestinal microbiota over geological timescales. Since the methodological approaches proved to be the largest source of systematic errors in comparisons of microbial communities among different organisms of the same species or between different species, we tested a number of methods on samples from different species of mammals in order to verify the feasibility of this approach for future routine analysis of microbiomes:(i) analyses of physical-chemical parameters;(ii)the metabolic properties of attached, planktonic fractions in comparison to the total;(iii)structure of microbial communities of bacteria and archaea; (iv)data analysis. We used a model of intestinal samples from four species of mammals, encompassing the differences between the various types of intestinal tracts: ruminants and rodents (such as pre- and post- peptic fermentors), omnivores and carnivores. The second purpose of the study was to(i)assess the extent of spread of data due to the cooperation of the various operators on the data obtained, and(ii) to evaluate the skills of the students to carry out industry-oriented investigations and measurements in 1st year of MSc study Microbiology; and(iii) to promote awareness of the importance of routine laboratory work day and the corresponding duties. The results suggest(i)that the operators independently organized and shared tasks;(ii)successfully completed all methods;(iii)obtain relevant information;(iv)critically evaluated and interpreted within the extent of their knowledge;(v) that relative standard deviation(RSD) typically could be compared to those of the automated analytical procedures(<10 %) and therefore represented the maximum extent of the variability of the biological material itself. It follows that the motivated MSc students were able to uphold the unknown protocols under supervision and perform laboratory and analytical complex experimental task, process and interpret results, and approximate performance of analytical procedures in industrial laboratories to generate data sets of acceptable high-quality.

References

Clescerl L.S., Greenberg A.E., Eaton A.D. 1999. Standard Methods for Examination of Water & Wastewater. 20th edition. Washington, DC: American Public Health Association.

De Graaf A.A., Maathuis A., de Waard P., Deutz N.E.P., Dijkema C. et. al. 2010. Profiling human gut bacterial metabolism and its kinetics using [U-13C] glucose and NMR. NMR Biomed., 23: 2–12, doi:10.1002/nbm.1418 DOI: https://doi.org/10.1002/nbm.1418

Dumas M.E., Barton R.H., Toye A., Cloarec O., Blancher C., Rothwell A., Fearnside J., Tatoud R., Blanc V., Lindon J.C., Mitchell S.C., Holmes E., McCarthy M.I., Scott J., Gauguier D., Nicholson J.K. 2006. Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice. Proc. Natl. Acad. Sci. USA, 103, 33: 12511–12516, doi:10.1073/pnas.0601056103 DOI: https://doi.org/10.1073/pnas.0601056103

Gueimonde M., Tölkkö S., Korpimäki T., Salminen S. 2004. New Real-Time Quantitative PCR Procedure for Quantification of Bifidobacteria in Human Fecal Samples. Appl Environ Microbiol.: 4165–4169, doi:10.1128/AEM.70.7.4165-4169.2004 DOI: https://doi.org/10.1128/AEM.70.7.4165-4169.2004

Hammer Ø., Harper D.A.T., Ryan P.D. 2001. PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica, 4, 1: 9 p.

Holmes E., Li J.V., Athanasiou T., Ashrafian H., Nicholson J.K. 2011. Understanding the role of gut microbiome–host metabolic signal disruption in health and disease. Trends in Microbiology, 19, 7: 349–359, doi:10.1016/j.tim.2011.05.006 DOI: https://doi.org/10.1016/j.tim.2011.05.006

Jacobs D.M., Gaudier E., van Duynhoven J., Vaughan E.E. 2009. Non-digestible food ingredients, colonic microbiota and the impact on gut health and immunity: a role for metabolomics. Curr Drug Metab., 10, 1: 41–54, doi:10.2174/138920009787048383 DOI: https://doi.org/10.2174/138920009787048383

Jin J.S., Touyama M., Kibe R., Tanaka Y., Benno Y., Kobayashi T., Shimakawa M., Maruo T., Toda T., Matsuda I., Tagami H., Matsumoto M., Seo G., Chonan O., Benno Y. 2012. Analysis of the human intestinal microbiota from 92 volunteers after ingestion of identical meals. Benef Microbes, 4, 2: 187–193, doi:10.3920/BM2012.0045 DOI: https://doi.org/10.3920/BM2012.0045

Kolbl S., Paloczi A., Panjan J., Stres B. 2014. Addressing case specific biogas plant tasks: Industry oriented methane yields derived from 5L Automatic Methane Potential Test Systems in batch or semi-continuous tests using realistic inocula, substrate particle sizes and organic loading. Bioresource technology, 153: 180–188, doi:10.1016/j.biortech.2013.12.010 DOI: https://doi.org/10.1016/j.biortech.2013.12.010

Lever M. 1977. Carbohydrate determination with 4-hydroxybenzoic acid hydrazide (PAHBAH): Effect of bismuth on the reaction. Analytical Biochemistry, 81: 21–27, doi:10.1016/0003-2697(77)90594-2 DOI: https://doi.org/10.1016/0003-2697(77)90594-2

Ley R.E., Hamady M., Lozupone C., Turnbaugh P.J., Ramey R.R., Bircher J.S., Schlegel M.L., Tucker T.A., Schrenzel M.D., Knight R., Gordon J.I. 2008. Evolution of mammals and their gut microbes. Science, 320: 1647–1651, doi:10.1126/science.1155725 DOI: https://doi.org/10.1126/science.1155725

Li F., Hullar M.A.J., Lampe J.W. 2007. Optimization of terminal restriction fragment polymorphism (TRFLP) analysis of human gut microbiota. J Microbiol Methods, 68, 2: 303–311, doi:10.1016/j.mimet.2006.09.006 DOI: https://doi.org/10.1016/j.mimet.2006.09.006

Lin C., Raskin L., Stahl D.A. 1997. Microbial community structure in gastrointestinal tracts of domestic animals: comparative analyses using rRNA-targeted oligonucleotide probes. FEMS Microbiol. Ecol., 22: 281–294, doi:10.1111/j.1574-6941.1997.tb00380.x DOI: https://doi.org/10.1111/j.1574-6941.1997.tb00380.x

Lozupone C.A., Stombaugh J.I., Gordon J.I., Jansson J.K., Knight R. 2012. Diversity, stability and resilience of the human gut microbiota. Nature, 489, 7415: 220–230, doi:10.1038/nature11550 DOI: https://doi.org/10.1038/nature11550

Marchesi J.R., Holmes E., Khan F., Kochhar S., Scanlan P., Shanahan F., Wilson I.D., Wang Y. 2007. Rapid and noninvasive metabonomic characterization of inflammatory bowel disease. J Proteome Res, 6: 546–551, doi:10.1021/pr060470d DOI: https://doi.org/10.1021/pr060470d

Pieper R., Kröger S., Richter J. F., Wang J., Martin L., Bindelle J., Htoo J.K., Smolinski D., Vahjen W., Zentek J., Kessel A.G. 2012. Fermentable Fiber Ameliorates Fermentable Protein-Induced Changes in Microbial Ecology, but Not the Mucosal Response, in the Colon of Piglets. J Nutr., 142, 4: 661–66, doi:10.3945/jn.111.156190 DOI: https://doi.org/10.3945/jn.111.156190

Simpson J.M., Kocherginskaya S.A., Aminov R.I., Skerlos L.T., Bradley T.M., Mackie R.I. et al. 2002. Comparative microbial diversity in the gastrointestinal tracts of food animal species. Integr Comp Biol, 42: 327–331, doi:10.1093/icb/42.2.327 DOI: https://doi.org/10.1093/icb/42.2.327

Stres B., Danevcic T., Pal L. et al. 2008. Influence of temperature and soil water content on bacterial, archaeal and denitrifying microbial communities in drained fen grassland soil microcosms. FEMS Microbiol Ecol. 66: 110–122, doi:10.1111/j.1574-6941.2008.00555.x DOI: https://doi.org/10.1111/j.1574-6941.2008.00555.x

Turnbaugh P.J., Hamady M., Yatsunenko T., Cantarel B.L., Duncan A., Ley R.E., Sogin M.L. et al. 2009. A core gut microbiome in obese and lean twins. Nature, 457: 480–484, doi:10.1038/nature07540 DOI: https://doi.org/10.1038/nature07540

Tlaskalová-Hogenová H., Stěpánková R., Kozáková H., Hudcovic T., Vannucci L., Tučková L., Rossmann P., Hrnčíř T., Kverka M., Zákostelská Z., Klimešová K., Přibylová J., Bártová J., Sanchez D., Fundová P., Borovská D., Srůtková D., Zídek Z., Schwarzer M., Drastich P., Funda D.P. 2011. The role of gut microbiota (commensal bacteria) and the mucosal barrier in the pathogenesis of inflammatory and autoimmune diseases and cancer: contribution of germ-free and gnotobiotic animal models of human diseases. Cell Mol Immunol, 8: 110–120, doi:10.1038/cmi.2010.67 DOI: https://doi.org/10.1038/cmi.2010.67

Tims S., Zoetendal E.G., de Vos W.M., Kleerebezem M. 2010. Chapter 2: Host Genotype and the Effect on Microbial Communities. In: Metagenomics of the Human Body. Nelson K.E. (ed.). Springer: 15–41 DOI: https://doi.org/10.1007/978-1-4419-7089-3_2

TNO. 2013. Gastrointestinal models (TIM) with high predictive power. Netherlands Organisation for Applied Scientific Research TNO. http://www.tno.nl/content.cfm?context=thema&content =markt_product&laag1=891&laag2=195&laag3=320&item_id=1100&Taal=2 (20. Oct. 2013)

Twardowski M.S., Boss E., Sullivan J.M., Donaghay P.L. 2004. Modeling the spectral shape of absorption by chromophoric dissolved organic matter. Marine Chemistry, 89, 1–4: 69–88, doi:10.1016/j.marchem.2004.02.008 DOI: https://doi.org/10.1016/j.marchem.2004.02.008

Zajec N., Stres B., Avguštin G. 2012. Distinct approaches for the detection and removal of chimeric 16S rRNA sequences can significantly affect the outcome of between-site comparisons. Aquat. Microb. Ecol., 66: 13–21, doi:10.3354/ame01510 DOI: https://doi.org/10.3354/ame01510

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Published

25. 11. 2015

Issue

Section

Animal Science section

How to Cite

CIBER, N., ZUPANČIČ, T., ZORAN, T., ŠIMUNOVIĆ, K., PUGELJ, A., PAPIĆ, B., KLINEC, N., GAZVODA, A., DRAKSLAR, B., DOLENC, M., & STRES, B. (2015). Student performance study: the outcomes of metabolic, molecular and physical-chemical characterization of intestinal tract microbiome on a four mammalian species model. Acta Agriculturae Slovenica, 104(2), 91–98. https://doi.org/10.14720/aas.2014.104.2.4