Papers by Burkhardt Flemer
Background: Alteration of the gut microbiota by repeated antibiotic treatment increases susceptib... more Background: Alteration of the gut microbiota by repeated antibiotic treatment increases susceptibility to Clostridioides difficile infection. Faecal microbiota transplantation from donors with a normal microbiota effectively treats C. difficile infection.
Background and aims: Microbiota alterations are linked with colorectal cancer (CRC) and notably h... more Background and aims: Microbiota alterations are linked with colorectal cancer (CRC) and notably higher abundance of putative oral bacteria on colonic tumours. However, it is not known if colonic mucosa-associated taxa are indeed orally derived, if such cases are a distinct subset of patients or if the oral microbiome is generally suitable for screening for CRC.
Methods: We profiled the microbiota in oral swabs, colonic mucosae and stool from individuals with CRC (99 subjects), colorectal polyps (32) or controls (103).
Results: Several oral taxa were differentiallyabundant in CRC compared with controls, for example, Streptococcus and Prevotellas pp. A classification model of oral swab microbiota distinguished individuals with CRC or polyps from controls (sensitivity: 53% (CRC)/67% (polyps); specificity: 96%). Combining the data from faecal microbiota and oral swab microbiota increased the sensitivity of this model to 76% (CRC)/88% (polyps). We detected similar bacterial networks in colonic microbiota and oral microbiota datasets comprising putative oral biofilm forming bacteria. While these taxa were more abundant in CRC, core networks between pathogenic, CRC-associated oral bacteria such as Peptostreptococcus, Parvimonas and Fusobacterium were also detected in healthy controls. High abundance of Lachnospiraceae was negatively associated with the colonisation of colonic tissue with oral-like bacterial networks suggesting a protective role for certain microbiota types against CRC, possibly by conferring colonisation resistance to CRC-associated oral taxa and possibly mediated through habitual diet.
Conclusion: The heterogeneity of CRC may relate to microbiota types that either predispose or provide resistance to the disease, and profiling the oral microbiome may offer an alternative screen for detecting CRC.
Studies of the community of bacteria in the human intestine have had a major impact on gastroente... more Studies of the community of bacteria in the human intestine have had a major impact on gastroenterology research in the last decade. As summarized elsewhere in this issue, it is now appreciated that altered microbial communities in the gut are associated with a broad range of functional gastrointestinal disorders as well as being increasingly linked to extraintestinal diseases. It is important to point out that, at the time of writing, there are no examples other than Clostridium difficile– ssociated diarrhea (CDAD) where an altered microbiota is responsible for a disease and where the disease can be cured by restoring a normal microbiota. There is mounting evidence, however, for microbiota involvement in obesity, inflammatory bowel disease (IBD), irritable bowel syndrome, type 2 diabetes mellitus, and metabolic syndrome, and many microbiome start-up companies are scrambling to develop first-to-market...
François Brugere (2017): Fecal microbiota variation across the lifespan of the healthy laboratory... more François Brugere (2017): Fecal microbiota variation across the lifespan of the healthy laboratory rat, Gut Microbes,
The term microbiome refers to the collection of microbes or microbial genes in a specified locati... more The term microbiome refers to the collection of microbes or microbial genes in a specified location or clinical sample. Identifying micro-organisms has historically relied upon bacteriological culture, which is time consuming and difficult to effectively implement. The recent adaptation of culture-independent techniques for profiling microbial communities, allied with next-generation massively parallel DNA sequencing, allows clinician scientists to determine the entire microbial content of a specimen to a forensic level of detail within 48 hours. The technology is still young, and the main thrust of current efforts is to identify how changes in the microbiome covary with a variety of syndromes and diseases, and to determine if these changes are causative or consequential. Regardless of the outcome of these investigations, it is already apparent that the gut microbiome is a useful biomarker for intestinal and extraintestinal disease. In this review, the authors summarize the main concepts in microbiome analysis, and prospects for the microbiome's clinical deployment.
Objective: A signature that unifies the colorectal cancer (CRC) microbiota across multiple studie... more Objective: A signature that unifies the colorectal cancer (CRC) microbiota across multiple studies has not been identified. In addition to methodological variance, heterogeneity may be caused by both microbial and host response differences, which was addressed in this study.
Design: We prospectively studied the colonic microbiota and the expression of specific host response genes using faecal and mucosal samples (‘ON’ and ‘OFF’ the tumour, proximal and distal) from 59 patients undergoing surgery for CRC, 21 individuals with polyps and 56 healthy controls. Microbiota composition was determined by 16S rRNA amplicon sequencing; expression of host genes involved in CRC progression and immune response was quantified by real-time quantitative PCR.
Results: The microbiota of patients with CRC differed from that of controls, but alterations were not restricted to the cancerous tissue. Differences between distal and proximal cancers were detected and faecal microbiota only partially reflected mucosal microbiota in CRC. Patients with CRC can be stratified based on higher level structures of mucosal-associated bacterial co-abundance groups (CAGs) that resemble the previously formulated concept of enterotypes. Of these, Bacteroidetes Cluster 1 and Firmicutes Cluster 1 were in decreased abundance in CRC mucosa, whereas Bacteroidetes Cluster 2, Firmicutes Cluster 2, Pathogen Cluster and Prevotella Cluster showed increased abundance in CRC mucosa. CRC-associated CAGs were differentially correlated with the expression of host immunoinflammatory response genes.
Conclusions: CRC-associated microbiota profiles differ from those in healthy subjects and are linked with distinct mucosal gene-expression profiles. Compositional alterations in the microbiota are not restricted to cancerous tissue and differ between distal and proximal cancers.
Journal of Applied Microbiology, 2012
Hb25_Springer Handbook of Marine Biotechnology, 2015
ABSTRACT Marine sponge - anatomy and physiology; Sponge-associated microorganisms; Symbiotic func... more ABSTRACT Marine sponge - anatomy and physiology; Sponge-associated microorganisms; Symbiotic functions of sponge-associated microorganisms; Biotechnological potential of marine sponges - pharmacological potential; Exploiting the pharmacological potential of marine sponges; Metagenomic strategies for natural product discovery.
Marine …, 2010
The marine environment is extremely diverse, with huge variations in pressure and temperature. Ne... more The marine environment is extremely diverse, with huge variations in pressure and temperature. Nevertheless, life, especially microbial life, thrives throughout the marine biosphere and microbes have adapted to all the divergent environments present. Large scale DNA sequence based approaches have recently been used to investigate the marine environment and these studies have revealed that the oceans harbor unprecedented microbial diversity. Novel gene families with representatives only within such metagenomic datasets represent a large proportion of the ocean metagenome. The presence of so many new gene families from these uncultured and highly diverse microbial populations represents a challenge for the understanding of and exploitation of the biology and biochemistry of the ocean environment. The application of new metagenomic and single cell genomics tools offers new ways to explore the complete metabolic diversity of the marine biome.
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Papers by Burkhardt Flemer
Methods: We profiled the microbiota in oral swabs, colonic mucosae and stool from individuals with CRC (99 subjects), colorectal polyps (32) or controls (103).
Results: Several oral taxa were differentiallyabundant in CRC compared with controls, for example, Streptococcus and Prevotellas pp. A classification model of oral swab microbiota distinguished individuals with CRC or polyps from controls (sensitivity: 53% (CRC)/67% (polyps); specificity: 96%). Combining the data from faecal microbiota and oral swab microbiota increased the sensitivity of this model to 76% (CRC)/88% (polyps). We detected similar bacterial networks in colonic microbiota and oral microbiota datasets comprising putative oral biofilm forming bacteria. While these taxa were more abundant in CRC, core networks between pathogenic, CRC-associated oral bacteria such as Peptostreptococcus, Parvimonas and Fusobacterium were also detected in healthy controls. High abundance of Lachnospiraceae was negatively associated with the colonisation of colonic tissue with oral-like bacterial networks suggesting a protective role for certain microbiota types against CRC, possibly by conferring colonisation resistance to CRC-associated oral taxa and possibly mediated through habitual diet.
Conclusion: The heterogeneity of CRC may relate to microbiota types that either predispose or provide resistance to the disease, and profiling the oral microbiome may offer an alternative screen for detecting CRC.
Design: We prospectively studied the colonic microbiota and the expression of specific host response genes using faecal and mucosal samples (‘ON’ and ‘OFF’ the tumour, proximal and distal) from 59 patients undergoing surgery for CRC, 21 individuals with polyps and 56 healthy controls. Microbiota composition was determined by 16S rRNA amplicon sequencing; expression of host genes involved in CRC progression and immune response was quantified by real-time quantitative PCR.
Results: The microbiota of patients with CRC differed from that of controls, but alterations were not restricted to the cancerous tissue. Differences between distal and proximal cancers were detected and faecal microbiota only partially reflected mucosal microbiota in CRC. Patients with CRC can be stratified based on higher level structures of mucosal-associated bacterial co-abundance groups (CAGs) that resemble the previously formulated concept of enterotypes. Of these, Bacteroidetes Cluster 1 and Firmicutes Cluster 1 were in decreased abundance in CRC mucosa, whereas Bacteroidetes Cluster 2, Firmicutes Cluster 2, Pathogen Cluster and Prevotella Cluster showed increased abundance in CRC mucosa. CRC-associated CAGs were differentially correlated with the expression of host immunoinflammatory response genes.
Conclusions: CRC-associated microbiota profiles differ from those in healthy subjects and are linked with distinct mucosal gene-expression profiles. Compositional alterations in the microbiota are not restricted to cancerous tissue and differ between distal and proximal cancers.
Methods: We profiled the microbiota in oral swabs, colonic mucosae and stool from individuals with CRC (99 subjects), colorectal polyps (32) or controls (103).
Results: Several oral taxa were differentiallyabundant in CRC compared with controls, for example, Streptococcus and Prevotellas pp. A classification model of oral swab microbiota distinguished individuals with CRC or polyps from controls (sensitivity: 53% (CRC)/67% (polyps); specificity: 96%). Combining the data from faecal microbiota and oral swab microbiota increased the sensitivity of this model to 76% (CRC)/88% (polyps). We detected similar bacterial networks in colonic microbiota and oral microbiota datasets comprising putative oral biofilm forming bacteria. While these taxa were more abundant in CRC, core networks between pathogenic, CRC-associated oral bacteria such as Peptostreptococcus, Parvimonas and Fusobacterium were also detected in healthy controls. High abundance of Lachnospiraceae was negatively associated with the colonisation of colonic tissue with oral-like bacterial networks suggesting a protective role for certain microbiota types against CRC, possibly by conferring colonisation resistance to CRC-associated oral taxa and possibly mediated through habitual diet.
Conclusion: The heterogeneity of CRC may relate to microbiota types that either predispose or provide resistance to the disease, and profiling the oral microbiome may offer an alternative screen for detecting CRC.
Design: We prospectively studied the colonic microbiota and the expression of specific host response genes using faecal and mucosal samples (‘ON’ and ‘OFF’ the tumour, proximal and distal) from 59 patients undergoing surgery for CRC, 21 individuals with polyps and 56 healthy controls. Microbiota composition was determined by 16S rRNA amplicon sequencing; expression of host genes involved in CRC progression and immune response was quantified by real-time quantitative PCR.
Results: The microbiota of patients with CRC differed from that of controls, but alterations were not restricted to the cancerous tissue. Differences between distal and proximal cancers were detected and faecal microbiota only partially reflected mucosal microbiota in CRC. Patients with CRC can be stratified based on higher level structures of mucosal-associated bacterial co-abundance groups (CAGs) that resemble the previously formulated concept of enterotypes. Of these, Bacteroidetes Cluster 1 and Firmicutes Cluster 1 were in decreased abundance in CRC mucosa, whereas Bacteroidetes Cluster 2, Firmicutes Cluster 2, Pathogen Cluster and Prevotella Cluster showed increased abundance in CRC mucosa. CRC-associated CAGs were differentially correlated with the expression of host immunoinflammatory response genes.
Conclusions: CRC-associated microbiota profiles differ from those in healthy subjects and are linked with distinct mucosal gene-expression profiles. Compositional alterations in the microbiota are not restricted to cancerous tissue and differ between distal and proximal cancers.