Harnessing the landscape of microbial culture media to predict new organism–media pairings

Oberhardt, Matthew; Zarecki, Raphy; Gronow, Sabine; Lang, Elke; Klenk, Hans Peter; Gophna, Uri; Ruppin, Eytan

doi:10.1038/ncomms9493

Cited by 135 publications

(93 citation statements)

References 26 publications

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“…It is obvious that the functional properties of these microorganisms in the oral biofilm environment are of high interest from the clinical and disease prevention perspectives. While one strategy would be to prevent growth conditions favoring detrimental bacteria, other pursuits will require a more detailed knowledge pertaining to the cultivation and cocultivation of all biofilm inhabitants (62)(63)(64)(65). Such insights will be helpful in designing target-specific approaches for the prevention of and/or intervention in diseases exhibiting an oral-biofilm-based etiology.…”

Section: Discussionmentioning

confidence: 99%

Microbial Diversity in the Early In Vivo -Formed Dental Biofilm

Heller

Helmerhorst

Gower

et al. 2016

Appl Environ Microbiol

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f Although the mature dental biofilm composition is well studied, there is very little information on the earliest phase of in vivo tooth colonization. Progress in dental biofilm collection methodologies and techniques of large-scale microbial identification have made new studies in this field of oral biology feasible. The aim of this study was to characterize the temporal changes and diversity of the cultivable and noncultivable microbes in the early dental biofilm. Samples of early dental biofilm were collected from 11 healthy subjects at 0, 2, 4, and 6 h after removal of plaque and pellicle from tooth surfaces. With the semiquantitative Human Oral Microbiome Identification Microarray (HOMIM) technique, which is based on 16S rRNA sequence hybridizations, plaque samples were analyzed with the currently available 407 HOMIM microbial probes. This led to the identification of at least 92 species, with streptococci being the most abundant bacteria across all time points in all subjects. High-frequency detection was also made with Haemophilus parainfluenzae, Gemella haemolysans, Slackia exigua, and Rothia species. Abundance changes over time were noted for Streptococcus anginosus and Streptococcus intermedius (P ‫؍‬ 0.02), Streptococcus mitis bv. 2 (P ‫؍‬ 0.0002), Streptococcus oralis (P ‫؍‬ 0.0002), Streptococcus cluster I (P ‫؍‬ 0.003), G. haemolysans (P ‫؍‬ 0.0005), and Stenotrophomonas maltophilia (P ‫؍‬ 0.02). Among the currently uncultivable microbiota, eight phylotypes were detected in the early stages of biofilm formation, one belonging to the candidate bacterial division TM7, which has attracted attention due to its potential association with periodontal disease.

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Section: Discussionmentioning

confidence: 99%

Microbial Diversity in the Early In Vivo -Formed Dental Biofilm

Heller

Helmerhorst

Gower

et al. 2016

Appl Environ Microbiol

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“…Genome analysis, often combined with computational modelling approaches, has provided new insight into the nutrient requirements of various microorganisms that inhabit the human body. The ability to investigate multiple microorganisms simultaneously despite our lack of success in cultivating them in the laboratory 29,30 has opened the door to in proteome allocation (such as amino acid composition) 36 and are also dependent on the growth stage of the organism 37 . Therefore, the energetic burden for different microorganisms is not evenly distributed within a community.…”

Section: Auxotrophies In Microbial Communitiesmentioning

confidence: 99%

“…These experiments are constrained to a limited number of microorganisms and are most frequently performed with two members. Furthermore, co-culturing is mostly restricted to cultivated microorganisms, and the outcome is dependent on the cultivation method and medium composition, reducing its applicability to natural systems 29,30 .…”

mentioning

confidence: 99%

The social network of microorganisms — how auxotrophies shape complex communities

2018

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Microorganisms engage in complex interactions with other organisms and their environment. Recent studies have shown that these interactions are not limited to the exchange of electron donors. Most microorganisms are auxotrophs, thus relying on external nutrients for growth, including the exchange of amino acids and vitamins. Currently, we lack a deeper understanding of auxotrophies in microorganisms and how nutrient requirements differ between different strains and different environments. In this Opinion article, we describe how the study of auxotrophies and nutrient requirements among members of complex communities will enable new insights into community composition and assembly. Understanding this complex network over space and time is crucial for developing strategies to interrogate and shape microbial communities.

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“…To circumvent these limitations, conventional approaches for microbiota growth have been modified to include environment specific media 103–106 , optimization of growth conditions based upon (meta)genomic information 106 , inclusion of helper organisms 107,108 and higher throughput cultivation strategies 105,109–112 . Efforts are also underway to cultivate both native and designer microbiome communities using in vitro and in vivo model systems 104 and new model systems continue to be developed 113,114 .…”

Section: Functional Validationmentioning

confidence: 99%

Microbiome and metabolome data integration provides insight into health and disease

Shaffer

Armstrong

Phelan

et al. 2017

Translational Research

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For much of our history, the most basic information about the microbial world has evaded characterization. Next-generation sequencing has led to a rapid increase in understanding of the structure and function of host-associated microbial communities in diverse diseases ranging from obesity to autism. Through experimental systems such as gnotobiotic mice only colonized with known microbes, a causal relationship between microbial communities and disease phenotypes has been supported. Now microbiome research must move beyond correlations and general demonstration of causality to develop mechanistic understandings of microbial influence, including through their metabolic activities. Similar to the microbiome field, advances in technologies for cataloguing small molecules have broadened our understanding of the metabolites that populate our bodies. Integration of microbial and metabolomics data paired with experimental validation has promise for identifying microbial influence on host physiology through production, modification or degradation of bioactive metabolites. Realization of microbial metabolic activities that affect health is hampered by gaps in our understanding of 1) biological properties of microbes and metabolites, 2) which microbial enzymes/pathways produce which metabolites and 3) the effects of metabolites on hosts. Capitalizing upon known mechanistic relationships and filling gaps in our understanding has the potential to enable translational microbiome research across disease contexts.

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Harnessing the landscape of microbial culture media to predict new organism–media pairings

Cited by 135 publications

References 26 publications

Microbial Diversity in the Early In Vivo -Formed Dental Biofilm

Microbial Diversity in the Early In Vivo -Formed Dental Biofilm

The social network of microorganisms — how auxotrophies shape complex communities

Microbiome and metabolome data integration provides insight into health and disease

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