scholarly journals Gut metabolites predict Clostridioides difficile recurrence

Author(s):  
Jennifer J Dawkins ◽  
Jessica R Allegretti ◽  
Travis E Gibson ◽  
Emma McClure ◽  
Mary Delaney ◽  
...  

Background Clostridioides difficile infection (CDI) is the most common hospital acquired infection in the U.S., with recurrence rates >15%. Although primary CDI has been extensively linked to gut microbial dysbiosis, less is known about the factors that promote or mitigate recurrence. Moreover, previous studies have not shown that microbial abundances in the gut measured by 16S rRNA amplicon sequencing alone can accurately predict CDI recurrence. Results We conducted a prospective, longitudinal study of 53 non-immunocompromised participants with primary CDI. Stool sample collection began pre-CDI antibiotic treatment at the time of diagnosis, and continued up to eight weeks post-antibiotic treatment, with weekly or twice weekly collections. Samples were analyzed using: (1) 16S rRNA amplicon sequencing, (2) liquid chromatography/mass-spectrometry metabolomics measuring 1387 annotated metabolites, and (3) short-chain fatty acid profiling. The amplicon sequencing data showed significantly delayed recovery of microbial diversity in recurrent participants, and depletion of key anaerobic taxa at multiple time-points, including Clostridium cluster XIVa and IV taxa. The metabolomic data also showed delayed recovery in recurrent participants, and moreover mapped to pathways suggesting distinct functional abnormalities in the microbiome or host, such as decreased microbial deconjugation activity, lowered levels of endocannabinoids, and elevated markers of host cell damage. Further, using predictive statistical/machine learning models, we demonstrated that the metabolomic data, but not the other data sources, can accurately predict future recurrence at one week (AUC 0.77 [0.71, 0.86; 95% interval]) and two weeks (AUC 0.77 [0.69, 0.85; 95% interval]) post-treatment for primary CDI. Conclusions The prospective, longitudinal and multi-omic nature of our CDI recurrence study allowed us to uncover previously unrecognized dynamics in the microbiome and host presaging recurrence, and, in particular, to elucidate changes in the understudied gut metabolome. Moreover, we demonstrated that a small set of metabolites can accurately predict future recurrence. Our findings have implications for development of diagnostic tests and treatments that could ultimately short-circuit the cycle of CDI recurrence, by providing candidate metabolic biomarkers for diagnostics development, as well as offering insights into the complex microbial and metabolic alterations that are protective or permissive for recurrence.

2021 ◽  
Author(s):  
Jennifer J Dawkins ◽  
Jessica R Allegretti ◽  
Travis E Gibson ◽  
Emma McClure ◽  
Mary Delaney ◽  
...  

Abstract Background Clostridioides difficile infection (CDI) is the most common hospital acquired infection in the U.S., with recurrence rates >15%. Although primary CDI has been extensively linked to gut microbial dysbiosis, less is known about the factors that promote or mitigate recurrence. Moreover, previous studies have not shown that microbial abundances in the gut measured by 16S rRNA amplicon sequencing alone can accurately predict CDI recurrence. Results We conducted a prospective, longitudinal study of 53 non-immunocompromised participants with primary CDI. Stool sample collection began pre-CDI antibiotic treatment at the time of diagnosis, and continued up to eight weeks post-antibiotic treatment, with weekly or twice weekly collections. Samples were analyzed using: (1) 16S rRNA amplicon sequencing, (2) liquid chromatography/mass-spectrometry metabolomics measuring 1387 annotated metabolites, and (3) short-chain fatty acid profiling. The amplicon sequencing data showed significantly delayed recovery of microbial diversity in recurrent participants, and depletion of key anaerobic taxa at multiple time-points, including Clostridium cluster XIVa and IV taxa. The metabolomic data also showed delayed recovery in recurrent participants, and moreover mapped to pathways suggesting distinct functional abnormalities in the microbiome or host, such as decreased microbial deconjugation activity, lowered levels of endocannabinoids, and elevated markers of host cell damage. Further, using predictive statistical/machine learning models, we demonstrated that the metabolomic data, but not the other data sources, can accurately predict future recurrence at one week (AUC 0.77 [0.71, 0.86; 95% interval]) and two weeks (AUC 0.77 [0.69, 0.85; 95% interval]) post-treatment for primary CDI. Conclusions The prospective, longitudinal and multi-omic nature of our CDI recurrence study allowed us to uncover previously unrecognized dynamics in the microbiome and host presaging recurrence, and, in particular, to elucidate changes in the understudied gut metabolome. Moreover, we demonstrated that a small set of metabolites can accurately predict future recurrence. Our findings have implications for development of diagnostic tests and treatments that could ultimately short-circuit the cycle of CDI recurrence, by providing candidate metabolic biomarkers for diagnostics development, as well as offering insights into the complex microbial and metabolic alterations that are protective or permissive for recurrence.


2021 ◽  
pp. ijgc-2020-002107
Author(s):  
Tamara Jones ◽  
Carolina Sandler ◽  
Dimitrios Vagenas ◽  
Monika Janda ◽  
Andreas Obermair ◽  
...  

ObjectivePhysical activity following cancer diagnosis is associated with improved outcomes, including potential survival benefits, yet physical activity levels among common cancer types tend to decrease following diagnosis and remain low. Physical activity levels following diagnosis of less common cancers, such as ovarian cancer, are less known. The objectives of this study were to describe physical activity levels and to explore characteristics associated with physical activity levels in women with ovarian cancer from pre-diagnosis to 2 years post-diagnosis.MethodsAs part of a prospective longitudinal study, physical activity levels of women with ovarian cancer were assessed at multiple time points between pre-diagnosis and 2 years post-diagnosis. Physical activity levels and change in physical activity were described using metabolic equivalent task hours and minutes per week, and categorically (sedentary, insufficiently, or sufficiently active). Generalized Estimating Equations were used to explore whether participant characteristics were related to physical activity levels.ResultsA total of 110 women with ovarian cancer with a median age of 62 years (range 33–88) at diagnosis were included. 53–57% of the women were sufficiently active post-diagnosis, although average physical activity levels for the cohort were below recommended levels throughout the 2-year follow-up period (120–142.5min/week). A decrease or no change in post-diagnosis physical activity was reported by 44–60% of women compared with pre-diagnosis physical activity levels. Women diagnosed with stage IV disease, those earning a lower income, those receiving chemotherapy, and those currently smoking or working were more likely to report lower physical activity levels and had increased odds of being insufficiently active or sedentary.ConclusionsInterventions providing patients with appropriate physical activity advice and support for behavior change could potentially improve physical activity levels and health outcomes.


Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2414
Author(s):  
Laura Sanjulián ◽  
Alexandre Lamas ◽  
Rocío Barreiro ◽  
Alberto Cepeda ◽  
Cristina A. Fente ◽  
...  

The objective of this work was to characterize the microbiota of breast milk in healthy Spanish mothers and to investigate the effects of lactation time on its diversity. A total of ninety-nine human milk samples were collected from healthy Spanish women and were assessed by means of next-generation sequencing of 16S rRNA amplicons and by qPCR. Firmicutes was the most abundant phylum, followed by Bacteroidetes, Actinobacteria, and Proteobacteria. Accordingly, Streptococcus was the most abundant genus. Lactation time showed a strong influence in milk microbiota, positively correlating with Actinobacteria and Bacteroidetes, while Firmicutes was relatively constant over lactation. 16S rRNA amplicon sequencing showed that the highest alpha-diversity was found in samples of prolonged lactation, along with wider differences between individuals. As for milk nutrients, calcium, magnesium, and selenium levels were potentially associated with Streptococcus and Staphylococcus abundance. Additionally, Proteobacteria was positively correlated with docosahexaenoic acid (DHA) levels in breast milk, and Staphylococcus with conjugated linoleic acid. Conversely, Streptococcus and trans-palmitoleic acid showed a negative association. Other factors such as maternal body mass index or diet also showed an influence on the structure of these microbial communities. Overall, human milk in Spanish mothers appeared to be a complex niche shaped by host factors and by its own nutrients, increasing in diversity over time.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Caitlin M. Singleton ◽  
Francesca Petriglieri ◽  
Jannie M. Kristensen ◽  
Rasmus H. Kirkegaard ◽  
Thomas Y. Michaelsen ◽  
...  

AbstractMicroorganisms play crucial roles in water recycling, pollution removal and resource recovery in the wastewater industry. The structure of these microbial communities is increasingly understood based on 16S rRNA amplicon sequencing data. However, such data cannot be linked to functional potential in the absence of high-quality metagenome-assembled genomes (MAGs) for nearly all species. Here, we use long-read and short-read sequencing to recover 1083 high-quality MAGs, including 57 closed circular genomes, from 23 Danish full-scale wastewater treatment plants. The MAGs account for ~30% of the community based on relative abundance, and meet the stringent MIMAG high-quality draft requirements including full-length rRNA genes. We use the information provided by these MAGs in combination with >13 years of 16S rRNA amplicon sequencing data, as well as Raman microspectroscopy and fluorescence in situ hybridisation, to uncover abundant undescribed lineages belonging to important functional groups.


Helicobacter ◽  
2021 ◽  
Author(s):  
Boldbaatar Gantuya ◽  
Hashem B. El Serag ◽  
Batsaikhan Saruuljavkhlan ◽  
Dashdorj Azzaya ◽  
Takashi Matsumoto ◽  
...  

2021 ◽  
Vol 9 (7) ◽  
pp. 1525
Author(s):  
Can Akpolat ◽  
Ana Beatriz Fernández ◽  
Pinar Caglayan ◽  
Baris Calli ◽  
Meral Birbir ◽  
...  

Prokaryotic communities and physico-chemical characteristics of 30 brine samples from the thalassohaline Tuz Lake (Salt Lake), Deep Zone, Kayacik, Kaldirim, and Yavsan salterns (Turkey) were analyzed using 16S rRNA amplicon sequencing and standard methods, respectively. Archaea (98.41% of reads) was found to dominate in these habitats in contrast to the domain Bacteria (1.38% of reads). Representatives of the phylum Euryarchaeota were detected as the most predominant, while 59.48% and 1.32% of reads, respectively, were assigned to 18 archaeal genera, 19 bacterial genera, 10 archaeal genera, and one bacterial genus that were determined to be present, with more than 1% sequences in the samples. They were the archaeal genera Haloquadratum, Haloarcula, Halorhabdus, Natronomonas, Halosimplex, Halomicrobium, Halorubrum, Halonotius, Halolamina, Halobacterium, and Salinibacter within the domain Bacteria. The genera Haloquadratum and Halorhabdus were found in all sampling sites. While Haloquadratum, Haloarcula, and Halorhabdus were the most abundant genera, two uncultured Tuz Lake Halobacteria (TLHs) 1 and 2 were detected in high abundance, and an additional uncultured haloarchaeal TLH-3 was found as a minor abundant uncultured taxon. Their future isolation in pure culture would permit us to expand our knowledge on hypersaline thalassohaline habitats, as well as their ecological role and biomedical and biotechnological potential applications.


Author(s):  
Henrik Christensen ◽  
Anna Jasmine Andersson ◽  
Steffen Lynge Jørgensen ◽  
Josef Korbinian Vogt

2017 ◽  
Author(s):  
Jon G Sanders ◽  
Piotr Lukasik ◽  
Megan E Frederickson ◽  
Jacob A Russell ◽  
Ryuichi Koga ◽  
...  

AbstractAbundance is a key parameter in microbial ecology, and important to estimates of potential metabolite flux, impacts of dispersal, and sensitivity of samples to technical biases such as laboratory contamination. However, modern amplicon-based sequencing techniques by themselves typically provide no information about the absolute abundance of microbes. Here, we use fluorescence microscopy and quantitative PCR as independent estimates of microbial abundance to test the hypothesis that microbial symbionts have enabled ants to dominate tropical rainforest canopies by facilitating herbivorous diets, and compare these methods to microbial diversity profiles from 16S rRNA amplicon sequencing. Through a systematic survey of ants from a lowland tropical forest, we show that the density of gut microbiota varies across several orders of magnitude among ant lineages, with median individuals from many genera only marginally above detection limits. Supporting the hypothesis that microbial symbiosis is important to dominance in the canopy, we find that the abundance of gut bacteria is positively correlated with stable isotope proxies of herbivory among canopy-dwelling ants, but not among ground-dwelling ants. Notably, these broad findings are much more evident in the quantitative data than in the 16S rRNA sequencing data. Our results help to resolve a longstanding question in tropical rainforest ecology, and have broad implications for the interpretation of sequence-based surveys of microbial diversity.


2020 ◽  
Author(s):  
Kimothy L Smith ◽  
Howard A Shuman ◽  
Douglas Findeisen

AbstractWe conducted two studies of water samples from buildings with normal occupancy and water usage compared to water from buildings that were unoccupied with little or no water usage due to the COVID-19 shutdown. Study 1 had 52 water samples obtained ad hoc from buildings in four metropolitan locations in different states in the US and a range of building types. Study 2 had 36 water samples obtained from two buildings in one metropolitan location with matched water sample types. One of the buildings had been continuously occupied, and the other substantially vacant for approximately 3 months. All water samples were analyzed using 16S rRNA amplicon sequencing with a MinION from Oxford Nanopore Technologies. More than 127 genera of bacteria were identified, including genera with members that are known to include more than 50 putative frank and opportunistic pathogens. While specific results varied among sample locations, 16S rRNA amplicon abundance and the diversity of bacteria were higher in water samples from unoccupied buildings than normally occupied buildings as was the abundance of sequenced amplicons of genera known to include pathogenic bacterial members. In both studies Legionella amplicon abundance was relatively small compared to the abundance of the other bacteria in the samples. Indeed, when present, the relative abundance of Legionella amplicons was lower in samples from unoccupied buildings. Legionella did not predominate in any of the water samples and were found, on average, in 9.6% of samples in Study 1 and 8.3% of samples in Study 2.SynopsisComparison of microbial community composition in the plumbing of occupied and unoccupied buildings during the COVID-19 pandemic shutdown.


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