Results 1-20 of 224.
Bookmark and Share    
Full Text
Peer Reviewed
See detailMicrobiome in Colorectal Cancer: How to Getfrom Meta-omics to Mechanism?
Ternes, Dominik UL; Karta, Jessica UL; Tsenkova, Mina UL et al

in Trends in Microbiology (2020)

Mounting evidence from metagenomic analyses suggests that a state of pathological microbial imbalance or dysbiosis is prevalent in the gut of patients with colorectal cancer. Several bacterial taxa have ... [more ▼]

Mounting evidence from metagenomic analyses suggests that a state of pathological microbial imbalance or dysbiosis is prevalent in the gut of patients with colorectal cancer. Several bacterial taxa have been identified of which representative isolate cultures interact with human cancer cells in vitro and trigger disease path-ways in animal models. However, how the complex interrelationships in dysbiotic communities may be involved in cancer pathogenesis remains a crucial question.Here, we provide a survey of current knowledge of the gut microbiome in colorectal cancer. Moving beyond observational studies, we outline new experimental approaches for gaining ecosystem-level mechanistic understanding of the gut microbiome’s role in cancer pathogenesis [less ▲]

Detailed reference viewed: 126 (9 UL)
Full Text
Peer Reviewed
See detailConnecting environmental exposure and neurodegeneration using cheminformatics and high resolution mass spectrometry: potential and challenges
Schymanski, Emma UL; Baker, Nancy C.; Williams, Antony J et al

in Environmental Science. Processes and Impacts (2019)

Connecting chemical exposures over a lifetime to complex chronic diseases with multifactorial causes such as neurodegenerative diseases is an immense challenge requiring a long-term, interdisciplinary ... [more ▼]

Connecting chemical exposures over a lifetime to complex chronic diseases with multifactorial causes such as neurodegenerative diseases is an immense challenge requiring a long-term, interdisciplinary approach. Rapid developments in analytical and data technologies, such as non-target high resolution mass spectrometry (NT-HR-MS), have opened up new possibilities to accomplish this, inconceivable 20 years ago. While NT-HR-MS is being applied to increasingly complex research questions, there are still many unidentified chemicals and uncertainties in linking exposures to human health outcomes and environmental impacts. In this perspective, we explore the possibilities and challenges involved in using cheminformatics and NT-HR-MS to answer complex questions that cross many scientific disciplines, taking the identification of potential (small molecule) neurotoxicants in environmental or biological matrices as a case study. We explore capturing literature knowledge and patient exposure information in a form amenable to high-throughput data mining, and the related cheminformatic challenges. We then briefly cover which sample matrices are available, which method(s) could potentially be used to detect these chemicals in various matrices and what remains beyond the reach of NT-HR-MS. We touch on the potential for biological validation systems to contribute to mechanistic understanding of observations and explore which sampling and data archiving strategies may be required to form an accurate, sustained picture of small molecule signatures on extensive cohorts of patients with chronic neurodegenerative disorders. Finally, we reflect on how NT-HR-MS can support unravelling the contribution of the environment to complex diseases. [less ▲]

Detailed reference viewed: 52 (7 UL)
Full Text
Peer Reviewed
See detailIntegrated In Vitro and In Silico Modeling Delineates the Molecular Effects of a Synbiotic Regimen on Colorectal-Cancer-Derived Cells
Greenhalgh, Kacy UL; Ramiro Garcia, Javier UL; Heinken et al

in Cell Reports (2019), 27

By modulating the human gut microbiome, prebiotics and probiotics (combinations of which are called synbiotics) may be used to treat diseases such as colorectal cancer (CRC). Methodological limitations ... [more ▼]

By modulating the human gut microbiome, prebiotics and probiotics (combinations of which are called synbiotics) may be used to treat diseases such as colorectal cancer (CRC). Methodological limitations have prevented determining the potential combina- torial mechanisms of action of such regimens. We expanded our HuMiX gut-on-a-chip model to co-culture CRC-derived epithelial cells with a model probiotic under a simulated prebiotic regimen, and we integrated the multi-omic results with in silico metabolic modeling. In contrast to individual prebi- otic or probiotic treatments, the synbiotic regimen caused downregulation of genes involved in procarci- nogenic pathways and drug resistance, and reduced levels of the oncometabolite lactate. Distinct ratios of organic and short-chain fatty acids were produced during the simulated regimens. Treatment of primary CRC-derived cells with a molecular cocktail reflecting the synbiotic regimen attenuated self-renewal ca- pacity. Our integrated approach demonstrates the potential of modeling for rationally formulating synbi- otics-based treatments in the future. [less ▲]

Detailed reference viewed: 213 (24 UL)
Full Text
Peer Reviewed
See detailDeep neural networks outperform human expert's capacity in characterizing bioleaching bacterial biofilm composition
Buetti-Dinh, Antoine; Galli, Vanni; Bellenberg, Sören et al

in Biotechnology Reports (2019)

Background Deep neural networks have been successfully applied to diverse fields of computer vision. However, they only outperform human capacities in a few cases. Methods The ability of deep neural ... [more ▼]

Background Deep neural networks have been successfully applied to diverse fields of computer vision. However, they only outperform human capacities in a few cases. Methods The ability of deep neural networks versus human experts to classify microscopy images was tested on biofilm colonization patterns formed on sulfide minerals composed of up to three different bioleaching bacterial species attached to chalcopyrite sample particles. Results A low number of microscopy images per category (<600) was sufficient for highly efficient computational analysis of the biofilm's bacterial composition. The use of deep neural networks reached an accuracy of classification of ∼90% compared to ∼50% for human experts. Conclusions Deep neural networks outperform human experts’ capacity in characterizing bacterial biofilm composition involved in the degradation of chalcopyrite. This approach provides an alternative to standard, time-consuming biochemical methods. [less ▲]

Detailed reference viewed: 128 (20 UL)
Full Text
Peer Reviewed
See detailExtensive transmission of microbes along the gastrointestinal tract
Schmidt, Thomas; Hayward, Matthew; Coelho, Luis et al

in eLife (2019)

The gastrointestinal tract is abundantly colonized by microbes, yet the translocation of oral species to the intestine is considered a rare aberrant event, and a hallmark of disease. By studying salivary ... [more ▼]

The gastrointestinal tract is abundantly colonized by microbes, yet the translocation of oral species to the intestine is considered a rare aberrant event, and a hallmark of disease. By studying salivary and fecal microbial strain populations of 310 species in 470 individuals from five countries, we found that transmission to, and subsequent colonization of, the large intestine by oral microbes is common and extensive among healthy individuals. We found evidence for a vast majority of oral species to be transferable, with increased levels of transmission in colorectal cancer and rheumatoid arthritis patients and, more generally, for species described as opportunistic pathogens. This establishes the oral cavity as an endogenous reservoir for gut microbial strains, and oral-fecal transmission as an important process that shapes the gastrointestinal microbiome in health and disease. [less ▲]

Detailed reference viewed: 167 (6 UL)
Full Text
Peer Reviewed
See detailInfluence of Macro-Substrate Composition in Wastewater on Micropollutant Removal
Christen, Anne UL; Gallé, Tom; Köhler, Christian et al

in the mobile app "MICROPOL 2019" (2019)

Detailed reference viewed: 50 (13 UL)
See detailSystems ecology of microbiomes
Wilmes, Paul UL

Scientific Conference (2018, December)

Detailed reference viewed: 56 (9 UL)
See detailMicrobiome: the environment within
Wilmes, Paul UL

Scientific Conference (2018, December)

Detailed reference viewed: 38 (3 UL)
See detailSystems ecology of the human microbiome
Wilmes, Paul UL

Scientific Conference (2018, November)

Detailed reference viewed: 33 (0 UL)
See detailThe ecology of the unseen
Wilmes, Paul UL

Scientific Conference (2018, October)

Detailed reference viewed: 17 (0 UL)
See detailLe microbiote humain et son impacte sur la santé
Wilmes, Paul UL

Scientific Conference (2018, October)

Detailed reference viewed: 20 (0 UL)
See detailUnderstanding the role of the microbiome in Parkinson’s disease
Wilmes, Paul UL

Scientific Conference (2018, October)

Detailed reference viewed: 23 (0 UL)
Full Text
See detailA multi-omic view of invasive genetic elements and their linked prokaryotic population dynamics within a mixed microbial community
Martinez Arbas, Susana UL; Narayanasamy, Shaman; Herold, Malte et al

Poster (2018, September 11)

Detailed reference viewed: 76 (7 UL)
See detailMicrobial Systems Ecology for identifying key functions driving host-microbiome-diet interactions
Wilmes, Paul UL

Scientific Conference (2018, September)

Detailed reference viewed: 25 (0 UL)
See detailUnraveling the combinatorial mechanisms linking the gut microbiome to Parkinson’s disease
Wilmes, Paul UL

Scientific Conference (2018, September)

Detailed reference viewed: 18 (1 UL)
See detailSystems Ecology of microbiomes: identifying key functions
Wilmes, Paul UL

Scientific Conference (2018, August)

Detailed reference viewed: 21 (0 UL)
See detailThe integration of quantitative big data from microbial consortia: what is there to gain?
Wilmes, Paul UL

Scientific Conference (2018, August)

Detailed reference viewed: 21 (1 UL)