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Dr. rer. nat. A.U.S. (Anna) Heintz Buschart

Assistant Professor
Faculty of Science
Swammerdam Institute for Life Sciences
Photographer: Anna Heintz-Buschart

Visiting address
  • Science Park 904
  • Room number: C2.205
Postal address
  • Postbus 1212
    1000 BE Amsterdam
  • “Microbial metagenomics” – what’s that?

    microbial:    The study of microbes

    meta:            in communities

    genomics:     and development of the necessary computational instruments to read their genomes (and learn what they do).

  • Why?

    I believe that the study of microbial communities and their appreciation as interactive agents holds potential for:

    • a better understanding of our world
    • explanations of problems, e.g., disease of humans, animals, and plants
    • predictions of responses to environmental and lifestyle change
    • highlighting innovative possibilities for improving and maintaining quality of life.
  • Some background
    The meta-omics framework for microbiome research

    For most of the 20th century, microbes were studied in isolation. Central insights into fundamental and general molecular mechanisms were gained due to the ease of handling and genetic modification of model organisms, such as E. coli or baker’s yeast. While it was obvious that these organisms do not occur in isolation in nature, the vast diversity of microbial communities only became apparent with the application of high-throughput sequencing (from around 2004 onwards): Most microbes in most environments had never been cultured and whole branches of the tree of life had been hidden from science. “Metagenomics” became the discoverer’s ship or the moon rover of microbiology. But in addition to cataloguing what is out there (or in here, in the case of the human microbiome), there were new questions.

  • What are metagenomics questions?

    What does that world of microbes do with us?

    Do microbes, as communities, affect our well-being?

    Or that of other organisms, e.g., the plants that we eat?

    And do the ecological rules governing these communities determine those effects?

  • How do researchers answer such questions?

    As a start, formal (read: mathematical) descriptions needed to be defined. Because metagenomics and high-throughput marker gene sequencing generate a census of microbial communities, numerical methods from community ecology were imported. Despite a high degree of adaptation to the specific characteristics and meanings of ecological data, those methods share common inheritance with the statistical methods employed in many other analytical research fields. In addition, microbial ecology inherited minds and methods from omics in cellular biology or biomedical sciences (I, for example first practiced transcriptome analysis before I became a microbiome researcher).

    taxa x sample matrix

    In consequence, there is now a lively ecosystem of statistical and machine learning methods that wrangle community matrices (taxa x samples; and less frequently, but increasingly: functions x samples). With their aid, researchers reveal microbiome trends and patterns which are associated with environmental or host characteristics. These patterns can be informative about host health or the status of natural or biotechnological ecosystems. The microbes or combination of microbes in which these patterns are most striking are of interest as marker species or because they can carry special relevance for the microbial processes.

    Given the multitude of processes in which microbiomes play roles that are not even gauged and the diversity of microbes that may provide the key to steering microbial systems, or at least be a valuable marker, application of the microbiome bioinformatics and data analysis methods collection continues to unearth new findings.

  • Some examples of my work

    You can roughly divide my microbiome work into three fields:

    • plant-microbe interactions and soil microbiome;
    • human microbiome;
    • wastewater treatment, trans-environmental microbiome research, and one-health.

    Here are links to selected related publications:

    Plant-microbe interactions and soil microbiome


    Human microbiome


    Wastewater treatment, trans-environmental microbiome research, and one-health



  • More in-depth, what are the most interesting challenges and ways ahead in microbial metagenomics?

    Microbiome data are not like other data: in contrast to community ecology data, they are the product of omics measurements (or at least high-throughput marker gene sequencing). They are also not the same as genomics (or transcriptomics/proteomics) of single, and in particular model-, organisms. Bioinformatics and data analysis for microbiomes may borrow methods from these fields, but they need to meet further challenges. One set of challenges stems from the entanglement of our ability to detect, recognize, and observe a microorganism and its quantifiability: microorganisms and part of genomes that are already known are more easily detected and precisely quantified – yet, these make up only a small part of most microbial systems. Rare organisms or genomic regions are more difficult to describe and to recognize unequivocally, so measurement errors remain large. Like with many high-throughput technologies, there is often a trade-off between measurement effort and precision and/or sensitivity, but this dimension is seldom explored in microbiome research and often neglected in interpretations. Similar issues exist for the sample processing and measurements: paradoxically, despite the high analytical costs and lengthy computational efforts, microbiome experiments are not usually better designed than others (including the frequent lack of controls and replication that would have been part of simpler studies). These challenges can be met, if the bioinformatics methods that delineate and detect microbial or functional signatures from the omics data report uncertainties. Data analysis methods that incorporate this information and that are more robust and/or adaptable to very specific experimental designs need to be developed and employed.

    What is most interesting to study within a microbiome? In theory, it is possible to focus on any aspect of a meta-omics survey (including both well-known and new entities, e.g., how many different microbial taxa are present? or which strains of a particular genus of microbes? or how abundant are transcripts with a particular function compared to others? or does microbiomes under condition A change more quickly than under condition B?). Yet, there’s always a risk of aspects outside the focus confounding the view. Choosing these aspects (or features as a data scientist would say) wisely is difficult, but of paramount importance. It requires both microbiological knowledge (e.g., is information on genus identity helpful or should my data be resolved to strain-level? do I need to make a distinction between enzymes that likely operate at different pH or can I lump-sum all the enzymes in a pathway?) and the abovementioned bioinformatics insights into the certainty with which data at any level can be obtained. In addition, there is no reason why microbiome research should be stuck with traditional features (e.g., species, a cocept that is awkward to apply to non-sexually reproducing microbes): Advances in bioinformatics open the door for new categories, for example structurally similar proteins or protein surfaces. Once bioinformatics and statistics methods that recognize and handle them are established, these categories may prove relevant in host-microbiome interactions.

    Asking single-aspect questions like the ones introduced at the beginning of the previous paragraph and streamlining bioinformatics and data analysis tools for such studies has been very productive. However, this approach is overly simplistic: in human microbiome research, focusing on a single aspect without taking into account the rest of the picture has led to discussions more akin to “is the dress blue or white?” than scientific theory building. It is especially self-limiting in multi-meta-omics studies: here, a common strategy is to process each meta-omics data set with a particular focus (say, metagenomics for which taxa are present, metatranscriptomics for what functions do transcripts have, and metabolomics for which molecules are how abundant) and then hope that data analysis will magically find links that were purposefully disregarded during data processing. Preserving the links that are already present in sequence-based data or making use of existing knowledge on links (e.g., between enzyme classes and metabolites) is a much more promising approach. This strategy should be statistically more powerful. And it can distinguish different mechanisms behind observations and pinpoint functionally important community members. Methods development for both the storage and handling of this interconnected data and its analysis is imperative if we really want to transform microbiome research from a collection of citable curiosities to an impactful science.

  • Research community

    When I say “we”, I mean a growing community of researchers with different backgrounds: microbiologists, ecologist, medical researchers, soil scientists, plant scientists, biotechnologists, bioinformaticians, biostatisticians, data scientists, modelers, and the first “microbiome natives” (who learned about microbiomes during their university education) meet in microbiome research. Scientific research often requires different insight from multiple perspectives and contributions from several experts. My research is testament to this: if you skim through the list of publications below, you see that I wrote hardly any of them on my own. Moreover, the authors of the vast majority of them come from different places, involving individuals from more than 60 institutes or universities. I am fascinated by their different perspectives and the paradigms in their fields: what kind of questions do they ask? what assumptions do they make? why? can their approach be applied in a different field?

    Open Science allows wide access to scientific advances. It prevents misconduct and innocent misunderstandings. For my own research, I use pre-print servers as much as possible, where manuscripts can be freely downloaded even before they have been peer-reviewed. The raw data that I have generated during my time of wet-lab science is in public repositories and I enforce publication of data in projects that I lead. The software that I have (co-)developed and maintain is open-source software (see for example my github). Below, you can find links to course materials and to the Science Park Study Group, who are a group of like-minded colleagues who promote skill sharing and open data in biology and beyond.

    I am part of the Biosystems Data Analysis (BDA) group at the Swammerdam Institute for Life Sciences (SILS) of the University of Amsterdam. BDA leads the omics and systems biology data science at SILS, together with its collaboration partners. It blends a wide range of pertinent expertise, including biology, bio-analytics, data processing and mining, data analysis/machine learning, data fusion, and modelling. Our biological data science and methods development makes use of biological knowledge and validated models to limit the computational problems to those parts that can effectively be tackled by algorithms based on realistic data sizes.


  • Links
  • Metagenomics and metabarcoding course materials
  • Publications



    • Breitkreuz, C., Heintz-Buschart, A., Buscot, F., Wahdan, S. F. M., Tarkka, M., & Reitz, T. (2021). Can We Estimate Functionality of Soil Microbial Communities from Structure-Derived Predictions? A Reality Test in Agricultural Soils. Microbiology spectrum, e0027821.
    • Busi, S. B., de Nies, L., Habier, J., Wampach, L., Fritz, J. V., Heintz Buschart, A. U. S., May, P., Halder, R., de Beaufort, C., & Wilmes, P. (2021). Persistence of birth mode-dependent effects on gut microbiome composition, immune system stimulation and antimicrobial resistance during the first year of life. ISME Communications, 1, [8].
    • Chakaroun, R. M., Massier, L., Heintz-Buschart, A., Said, N., Fallmann, J., Crane, A., Schütz, T., Dietrich, A., Blüher, M., Stumvoll, M., Musat, N., & Kovacs, P. (2021). Circulating bacterial signature is linked to metabolic disease and shifts with metabolic alleviation after bariatric surgery. Genome Medicine, 13, [105]. [details]
    • De Mesquita, C. P. B., Nichols, L. M., Gebert, M. J., Vanderburgh, C., Bocksberger, G., Lester, J. D., Kalan, A. K., Dieguez, P., McCarthy, M. S., Agbor, A., Varona, P. Á., Ayimisin, A. E., Bessone, M., Chancellor, R., Cohen, H., Coupland, C., Deschner, T., Egbe, V. E., Goedmakers, A., ... Heintz-Buschart, A. (2021). Structure of chimpanzee gut microbiomes across tropical Africa. mSystems, 6(3), [e01269-20].
    • Eisenhauer, N., Buscot, F., Heintz-Buschart, A., Jurburg, S. D., Küsel, K., Sikorski, J., Vogel, H. J., & Guerra, C. A. (2021). The multidimensionality of soil macroecology. Global Ecology and Biogeography, 30(1), 4-10.
    • Ferlian, O., Goldmann, K., Eisenhauer, N., Tarkka, M. T., Buscot, F., & Heintz Buschart, A. U. S. (2021). Distinct effects of host and neighbour tree identity on arbuscular and ectomycorrhizal fungi along a tree diversity gradient. ISME Communications, 1, [40].
    • Ganther, M., Vetterlein, D., Heintz-Buschart, A., & Tarkka, M. T. (2021). Transcriptome sequencing analysis of maize roots reveals the effects of substrate and root hair formation in a spatial context. Plant and Soil.
    • Gebauer, L., Bouffaud, M. L., Ganther, M., Yim, B., Vetterlein, D., Smalla, K., Buscot, F., Heintz-Buschart, A., & Tarkka, M. T. (2021). Soil Texture, Sampling Depth and Root Hairs Shape the Structure of ACC Deaminase Bacterial Community Composition in Maize Rhizosphere. Frontiers in Microbiology, 12, [616828].
    • Marselle, M. R., Hartig, T., Cox, D. T. C., de Bell, S., Knapp, S., Lindley, S., Triguero-Mas, M., Böhning-Gaese, K., Braubach, M., Cook, P. A., de Vries, S., Heintz-Buschart, A., Hofmann, M., Irvine, K. N., Kabisch, N., Kolek, F., Kraemer, R., Markevych, I., Martens, D., ... Bonn, A. (2021). Pathways linking biodiversity to human health: A conceptual framework. Environment International, 150, [106420].
    • Moll, J., Heintz-Buschart, A., Bässler, C., Hofrichter, M., Kellner, H., Buscot, F., & Hoppe, B. (2021). Amplicon Sequencing-Based Bipartite Network Analysis Confirms a High Degree of Specialization and Modularity for Fungi and Prokaryotes in Deadwood. mSphere, 6(1), 1-13.
    • Prada-Salcedo, L. D., Goldmann, K., Heintz-Buschart, A., Reitz, T., Wambsganss, J., Bauhus, J., & Buscot, F. (2021). Fungal guilds and soil functionality respond to tree community traits rather than to tree diversity in European forests (vol 30, pg 572, 2021). Molecular Ecology, 30(8), 1936-1937.
    • Prada-Salcedo, L. D., Goldmann, K., Heintz-Buschart, A., Reitz, T., Wambsganss, J., Bauhus, J., & Buscot, F. (2021). Fungal guilds and soil functionality respond to tree community traits rather than to tree diversity in European forests. Molecular Ecology, 30(2), 572-591.
    • Purahong, W., Wahdan, S. F. M., Heinz, D., Jariyavidyanont, K., Sungkapreecha, C., Tanunchai, B., Sansupa, C., Sadubsarn, D., Alaneed, R., Heintz-Buschart, A., Schädler, M., Geissler, A., Kressler, J., & Buscot, F. (2021). Back to the Future: Decomposability of a Biobased and Biodegradable Plastic in Field Soil Environments and Its Microbiome under Ambient and Future Climates. Environmental Science and Technology.
    • Smith, L. C., Orgiazzi, A., Eisenhauer, N., Cesarz, S., Lochner, A., Jones, A., Bastida, F., Patoine, G., Reitz, T., Buscot, F., Rillig, M. C., Heintz-Buschart, A., Lehmann, A., & Guerra, C. A. (2021). Large-scale drivers of relationships between soil microbial properties and organic carbon across Europe. Global Ecology and Biogeography, 30(10), 2070-2083.
    • Wahdan, S. F. M., Heintz-Buschart, A., Sansupa, C., Tanunchai, B., Wu, Y. T., Schädler, M., Noll, M., Purahong, W., & Buscot, F. (2021). Targeting the Active Rhizosphere Microbiome of Trifolium pratense in Grassland Evidences a Stronger-Than-Expected Belowground Biodiversity-Ecosystem Functioning Link. Frontiers in Microbiology, 12, [629169].
    • Wahdan, S. F. M., Reitz, T., Heintz-Buschart, A., Schädler, M., Roscher, C., Breitkreuz, C., Schnabel, B., Purahong, W., & Buscot, F. (2021). Organic agricultural practice enhances arbuscular mycorrhizal symbiosis in correspondence to soil warming and altered precipitation patterns. Environmental Microbiology, 6163-6176. [details]
    • de Nies, L., Lopes, S., Busi, S. B., Galata, V., Heintz-Buschart, A., Laczny, C. C., May, P., & Wilmes, P. (2021). PathoFact: a pipeline for the prediction of virulence factors and antimicrobial resistance genes in metagenomic data. Microbiome, 9(1), [49].


    • Cui, S., Li, M., Hassan, R. Y. A., Heintz-Buschart, A., Wang, J., & Bilitewski, U. (2020). Inhibition of Respiration of Candida albicans by Small Molecules Increases Phagocytosis Efficacy by Macrophages. mSphere, 5(2), [01620].
    • Fischer, F., Romero, R., Hellhund, A., Linne, U., Bertrams, W., Pinkenburg, O., Eldin, H. S., Binder, K., Jacob, R., Walker, A., Stecher, B., Basic, M., Luu, M., Mahdavi, R., Heintz-Buschart, A., Visekruna, A., & Steinhoff, U. (2020). Dietary cellulose induces anti-inflammatory immunity and transcriptional programs via maturation of the intestinal microbiota. Gut Microbes, 12(1), 1-17.
    • Ganther, M., Yim, B., Ibrahim, Z., Bienert, M. D., Lippold, E., MacCario, L., Sørensen, S. J., Bienert, G. P., Vetterlein, D., Heintz-Buschart, A., Blagodatskaya, E., Smalla, K., & Tarkka, M. T. (2020). Compatibility of X-ray computed tomography with plant gene expression, rhizosphere bacterial communities and enzyme activities. Journal of Experimental Botany, 71(18), 5603-5614.
    • Goldmann, K., Boeddinghaus, R. S., Klemmer, S., Regan, K. M., Heintz-Buschart, A., Fischer, M., Prati, D., Piepho, H. P., Berner, D., Marhan, S., Kandeler, E., Buscot, F., & Wubet, T. (2020). Unraveling spatiotemporal variability of arbuscular mycorrhizal fungi in a temperate grassland plot. Environmental Microbiology, 22(3), 873-888.
    • Guerra, C. A., Heintz-Buschart, A., Sikorski, J., Chatzinotas, A., Guerrero-Ramírez, N., Cesarz, S., Beaumelle, L., Rillig, M. C., Maestre, F. T., Delgado-Baquerizo, M., Buscot, F., Overmann, J., Patoine, G., Phillips, H. R. P., Winter, M., Wubet, T., Küsel, K., Bardgett, R. D., Cameron, E. K., ... Eisenhauer, N. (2020). Blind spots in global soil biodiversity and ecosystem function research. Nature Communications, 11(1), 3870.
    • Herold, M., Martínez Arbas, S., Narayanasamy, S., Sheik, A. R., Kleine-Borgmann, L. A. K., Lebrun, L. A., Kunath, B. J., Roume, H., Bessarab, I., Williams, R. B. H., Gillece, J. D., Schupp, J. M., Keim, P. S., Jäger, C., Hoopmann, M. R., Moritz, R. L., Ye, Y., Li, S., Tang, H., ... Wilmes, P. (2020). Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance. Nature Communications, 11(1), [5281].
    • Jurburg, S. D., Konzack, M., Eisenhauer, N., & Heintz-Buschart, A. (2020). The archives are half-empty: an assessment of the availability of microbial community sequencing data. Communications biology, 3(1), [474].
    • Schleuss, P. M., Widdig, M., Heintz-Buschart, A., Kirkman, K., & Spohn, M. (2020). Interactions of nitrogen and phosphorus cycling promote P acquisition and explain synergistic plant-growth responses. Ecology, 101(5), [e03003].
    • Weißbecker, C., Schnabel, B., & Heintz-Buschart, A. (2020). Dadasnake, a snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology. GigaScience, 9(12), [giaa135].
    • Widdig, M., Heintz-Buschart, A., Schleuss, P. M., Guhr, A., Borer, E. T., Seabloom, E. W., & Spohn, M. (2020). Effects of nitrogen and phosphorus addition on microbial community composition and element cycling in a grassland soil. Soil Biology and Biochemistry, 151, [108041].


    • Hickl, O., Heintz-Buschart, A., Trautwein-Schult, A., Hercog, R., Bork, P., Wilmes, P., & Becher, D. (2019). Sample Preservation and Storage Significantly Impact Taxonomic and Functional Profiles in Metaproteomics Studies of the Human Gut Microbiome. Microorganisms, 7(9).
    • Peters, A., Krumbholz, P., Jäger, E., Heintz-Buschart, A., Çakir, M. V., Rothemund, S., Gaudl, A., Ceglarek, U., Schöneberg, T., & Stäubert, C. (2019). Metabolites of lactic acid bacteria present in fermented foods are highly potent agonists of human hydroxycarboxylic acid receptor 3. PLOS Genetics, 15(5), [e1008145].
    • Schleuss, P. M., Widdig, M., Heintz-Buschart, A., Guhr, A., Martin, S., Kirkman, K., & Spohn, M. (2019). Stoichiometric controls of soil carbon and nitrogen cycling after long-term nitrogen and phosphorus addition in a mesic grassland in South Africa. Soil Biology and Biochemistry, 135, 294-303.
    • Schmidt, T. S. B., Hayward, M. R., Coelho, L. P., Li, S. S., Costea, P. I., Voigt, A. Y., Wirbel, J., Maistrenko, O. M., Alves, R. J. C., Bergsten, E., de Beaufort, C., Sobhani, I., Heintz-Buschart, A., Sunagawa, S., Zeller, G., Wilmes, P., & Bork, P. (2019). Extensive transmission of microbes along the gastrointestinal tract. eLife, 8, [e42693].
    • Weißbecker, C., Heintz-Buschart, A., Bruelheide, H., Buscot, F., & Wubet, T. (2019). Linking Soil Fungal Generality to Tree Richness in Young Subtropical Chinese Forests. Microorganisms, 7(11).


    • Habier, J., May, P., Heintz-Buschart, A., Ghosal, A., Wienecke-Baldacchino, A. K., Nolte-‘t Hoen, E. N. M., Wilmes, P., & Fritz, J. V. (2018). Extraction and analysis of RNA isolated from pure bacteria-derived outer membrane vesicles. In Methods in Molecular Biology (pp. 213-230). (Methods in Molecular Biology; Vol. 1737). Humana Press Inc..
    • Heintz-Buschart, A., & Wilmes, P. (2018). Human Gut Microbiome: Function Matters. Trends in Microbiology, 26(7), 563-574.
    • Heintz-Buschart, A., Pandey, U., Wicke, T., Sixel-Döring, F., Janzen, A., Sittig-Wiegand, E., Trenkwalder, C., Oertel, W. H., Mollenhauer, B., & Wilmes, P. (2018). The nasal and gut microbiome in Parkinson's disease and idiopathic rapid eye movement sleep behavior disorder. Movement Disorders, 33(1), 88-98.
    • Heintz-Buschart, A., Yusuf, D., Kaysen, A., Etheridge, A., Fritz, J. V., May, P., de Beaufort, C., Upadhyaya, B. B., Ghosal, A., Galas, D. J., & Wilmes, P. (2018). Small RNA profiling of low biomass samples: Identification and removal of contaminants. BMC Biology, 16(1), [52].
    • Laloo, A. E., Wei, J., Wang, D., Narayanasamy, S., Vanwonterghem, I., Waite, D., Steen, J., Kaysen, A., Heintz-Buschart, A., Wang, Q., Schulz, B., Nouwens, A., Wilmes, P., Hugenholtz, P., Yuan, Z., & Bond, P. L. (2018). Mechanisms of Persistence of the Ammonia-Oxidizing Bacteria Nitrosomonas to the Biocide Free Nitrous Acid. Environmental Science and Technology, 52(9), 5386-5397.
    • Malabirade, A., Habier, J., Heintz-Buschart, A., May, P., Godet, J., Halder, R., Etheridge, A., Galas, D., Wilmes, P., & Fritz, J. V. (2018). The RNA complement of outer membrane vesicles from Salmonella enterica Serovar Typhimurium under distinct culture conditions. Frontiers in Microbiology, 9(AUG), [2015].
    • Wampach, L., Heintz-Buschart, A., Fritz, J. V., Ramiro-Garcia, J., Habier, J., Herold, M., Narayanasamy, S., Kaysen, A., Hogan, A. H., Bindl, L., Bottu, J., Halder, R., Sjöqvist, C., May, P., Andersson, A. F., de Beaufort, C., & Wilmes, P. (2018). Birth mode is associated with earliest strain-conferred gut microbiome functions and immunostimulatory potential. Nature Communications, 9(1), [5091].


    • Kaysen, A., Heintz-Buschart, A., Muller, E. E. L., Narayanasamy, S., Wampach, L., Laczny, C. C., Graf, N., Simon, A., Franke, K., Bittenbring, J., Wilmes, P., & Schneider, J. G. (2017). Integrated meta-omic analyses of the gastrointestinal tract microbiome in patients undergoing allogeneic hematopoietic stem cell transplantation. Translational Research, 186, 79-94.e1.
    • Wampach, L., Heintz-Buschart, A., Hogan, A., Muller, E. E. L., Narayanasamy, S., Laczny, C. C., Hugerth, L. W., Bindl, L., Bottu, J., Andersson, A. F., de Beaufort, C., & Wilmes, P. (2017). Colonization and succession within the human gut microbiome by archaea, bacteria, and microeukaryotes during the first year of life. Frontiers in Microbiology, 8(MAY), [738].


    • Cui, S., Hassan, R. Y. A., Heintz-Buschart, A., & Bilitewski, U. (2016). Regulation of Candida albicans interaction with macrophages through the activation of HOG pathway by genistein. Molecules, 21(2), [162].
    • Fritz, J. V., Heintz-Buschart, A., Ghosal, A., Wampach, L., Etheridge, A., Galas, D., & Wilmes, P. (2016). Sources and Functions of Extracellular Small RNAs in Human Circulation. Annual Review of Nutrition, 36, 301-336.
    • Heintz-Buschart, A., May, P., Laczny, C. C., Lebrun, L. A., Bellora, C., Krishna, A., Wampach, L., Schneider, J. G., Hogan, A., De Beaufort, C., & Wilmes, P. (2016). Integrated multi-omics of the human gut microbiome in a case study of familial type 1 diabetes. Nature Microbiology, 2(1), [16180].
    • Laczny, C. C., Muller, E. E. L., Heintz-Buschart, A., Herold, M., Lebrun, L. A., Hogan, A., May, P., de Beaufort, C., & Wilmes, P. (2016). Identification, recovery, and refinement of hitherto undescribed population-level genomes from the human gastrointestinal tract. Frontiers in Microbiology, 7(JUN), [884].
    • Narayanasamy, S., Jarosz, Y., Muller, E. E. L., Heintz-Buschart, A., Herold, M., Kaysen, A., Laczny, C. C., Pinel, N., May, P., & Wilmes, P. (2016). IMP: A pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses. Genome Biology, 17(1), [260].


    • Chen, X., Miché, L., Sachs, S., Wang, Q., Buschart, A., Yang, H., Vera Cruz, C. M., Hurek, T., & Reinhold-Hurek, B. (2015). Rice responds to endophytic colonization which is independent of the common symbiotic signaling pathway. New Phytologist, 208(2), 531-543.
    • Ghosal, A., Upadhyaya, B. B., Fritz, J. V., Heintz-Buschart, A., Desai, M. S., Yusuf, D., Huang, D., Baumuratov, A., Wang, K., Galas, D., & Wilmes, P. (2015). The extracellular RNA complement of Escherichia coli. MicrobiologyOpen, 4(2), 252-266.
    • Mathay, C., Hamot, G., Henry, E., Georges, L., Bellora, C., Lebrun, L., De Witt, B., Ammerlaan, W., Buschart, A., Wilmes, P., & Betsou, F. (2015). Method optimization for fecal sample collection and fecal DNA extraction. Biopreservation and Biobanking, 13(2), 79-93.
    • Roume, H., Heintz-Buschart, A., Muller, E. E. L., May, P., Satagopam, V. P., Laczny, C. C., Narayanasamy, S., Lebrun, L. A., Hoopmann, M. R., Schupp, J. M., Gillece, J. D., Hicks, N. D., Engelthaler, D. M., Sauter, T., Keim, P. S., Moritz, R. L., & Wilmes, P. (2015). Comparative integrated omics: Identification of key functionalities in microbial community-wide metabolic networks. npj Biofilms and Microbiomes, 1, [15007].
    • Wilmes, P., Heintz-Buschart, A., & Bond, P. L. (2015). A decade of metaproteomics: Where we stand and what the future holds. PROTEOMICS, 15(20), 3409-3417.


    • Muller, E. E. L., Pinel, N., Laczny, C. C., Hoopmann, M. R., Narayanasamy, S., Lebrun, L. A., Roume, H., Lin, J., May, P., Hicks, N. D., Heintz-Buschart, A., Wampach, L., Liu, C. M., Price, L. B., Gillece, J. D., Guignard, C., Schupp, J. M., Vlassis, N., Baliga, N. S., ... Wilmes, P. (2014). Community-integrated omics links dominance of a microbial generalist to fine-tuned resource usage. Nature Communications, 5, [5603].


    • Heintz-Buschart, A., Eickhoff, H., Hohn, E., & Bilitewski, U. (2013). Identification of inhibitors of yeast-to-hyphae transition in Candida albicans by a reporter screening assay. Journal of Biotechnology, 164(1), 137-142.
    • Roume, H., Heintz-Buschart, A., Muller, E. E. L., & Wilmes, P. (2013). Sequential isolation of metabolites, RNA, DNA, and proteins from the same unique sample. In Microbial Metagenomics, Metatranscriptomics, and Metaproteomics (pp. 219-236). (Methods in Enzymology; Vol. 531). Academic Press Inc..


    • Buschart, A., Burakowska, A., & Bilitewski, U. (2012). The fungicide fludioxonil antagonizes fluconazole activity in the human fungal pathogen Candida albicans. Journal of Medical Microbiology, 61(PART12), 1696-1703.
    • Buschart, A., Gremmer, K., El-Mowafy, M., van den Heuvel, J., Mueller, P. P., & Bilitewski, U. (2012). A novel functional assay for fungal histidine kinases group III reveals the role of HAMP domains for fungicide sensitivity. Journal of Biotechnology, 157(1), 268-277.
    • Buschart, A., Sachs, S., Chen, X., Herglotz, J., Krause, A., & Reinhold-Hurek, B. (2012). Flagella mediate endophytic competence rather than act as MAMPs in rice-Azoarcus sp. strain BH72 interactions. Molecular Plant-Microbe Interactions, 25(2), 191-199.



    • Phillips, H. R. P., Heintz-Buschart, A., & Eisenhauer, N. (2020). Putting soil invertebrate diversity on the map. Molecular Ecology, 29(4), 655-657.
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
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