Intestinal microbiome landscaping : insight in community assemblage and implications for microbial modulation strategies

High individuality, large complexity and limited understanding of the mechanisms underlying human intestinal microbiome function remain the major challenges for designing beneficial modulation strategies. Exemplified by the analysis of intestinal bacteria in a thousand Western adults, we discuss key concepts of the human intestinal microbiome landscape, i.e. the compositional and functional 'core', the presence of community types and the existence of alternative stable states. Genomic investigation of core taxa revealed functional redundancy, which is expected to stabilize the ecosystem, as well as taxa with specialized functions that have the potential to shape the microbiome landscape. The contrast between Prevotella-and Bacteroides-dominated systems has been well described. However, less known is the effect of not so abundant bacteria, for example, Dialister spp. that have been proposed to exhibit distinct bistable dynamics. Studies employing time-series analysis have highlighted the dynamical variation in the microbiome landscape with and without the effect of defined perturbations, such as the use of antibiotics or dietary changes. We incorporate ecosystem-level observations of the human intestinal microbiota and its keystone species to suggest avenues for designing microbiome modulation strategies to improve host health.Peer reviewe

Feasibility of Metatranscriptome Analysis from Infant Gut Microbiota: Adaptation to Solid Foods Results in Increased Activity of Firmicutes at Six Months

Peer reviewe

Feasibility of Metatranscriptome Analysis from Infant Gut Microbiota: Adaptation to Solid Foods Results in Increased Activity of Firmicutes at Six Months

Newborns are rapidly colonized by microbes and their intestinal tracts contain highly dynamic and rapidly developing microbial communities in the first months of life. In this study, we describe the feasibility of isolating mRNA from rapidly processed faecal samples and applying deep RNA-Seq analysis to provide insight into the active contributors of the microbial community in early life. Specific attention is given to the impact of removing rRNA from the mRNA on the phylogenetic and transcriptional profiling and its analysis depth. A breastfed baby was followed in the first six months of life during adaptation to solid food, dairy products, and formula. It was found that, in the weaning period, the total transcriptional activity of Actinobacteria, mainly represented by Bifidobacterium, decreased while that of Firmicutes increased over time. Moreover, Firmicutes and Actinobacteria, including the canonical Bifidobacteria as well as Collinsella, were found to be important contributors to carbohydrate fermentation and vitamin biosynthesis in the infant intestine. Finally, the expression of Lactobacillus rhamnosus-like genes was detected, likely following transfer from the mother who consumed L. rhamnosus GG. The study indicates that metatranscriptome analysis of the infant gut microbiota is feasible on infant stool samples and can be used to provide insight into the core activities of the developing community.</p

A novel technique capable of taking 'protected' biopsies for reliable assessment of the distribution of microbiota along the colonic mucosa

We evaluated a novel 'protected' biopsy method to reliably ascertain the spatial distribution of the mucosa-adherent colonic microbiota. Apart from minor differences at genus level, overall similarities along the colon were high between the various areas, irrespective of protected or unprotected sampling.Peer reviewe

Heat shock protein expression analysis in canine osteosarcoma reveals HSP60 as a potentially relevant therapeutic target

Heat shock proteins (HSP) are highly conserved across eukaryotic and prokaryotic species. These proteins play a role in response to cellular stressors, protecting cells from damage and facilitating recovery. In tumor cells, HSPs can have cytoprotective effects and interfere with apoptotic cascades. This study was performed to assess the prognostic and predictive values of the gene expression of HSP family members in canine osteosarcoma (OS) and their potential for targeted therapy. Gene expressions for HSP were assessed using quantitative PCR (qPCR) on 58 snap-frozen primary canine OS tumors and related to clinic-pathological parameters. A significant increased expression of HSP60 was found in relation to shorter overall survival and an osteoblastic phenotype. Therefore, the function of HSP60 was investigated in more detail. Immunohistochemical analysis revealed heterogeneous staining for HSP60 in tumors. The highest immunoreactivity was found in tumors of short surviving dogs. Next HSP expression was shown in a variety of canine and human OS cell lines by qPCR and Western blot. In two highly metastatic cell lines HSP60 expression was silenced using siRNA resulting in decreased cell proliferation and induction of apoptosis in both cell lines. It is concluded that overexpression of HSP60 is associated with a poor prognosis of OS and should be evaluated as a new target for therapy

Toward responsible clinical n-of-1 strategies for rare diseases

N-of-1 strategies can provide high-quality evidence of treatment efficacy at the individual level and optimize evidence-based selection of off-label treatments for patients with rare diseases. Given their design characteristics, n-of-1 strategies are considered to lay at the intersection between medical research and clinical care. Therefore, whether n-of-1 strategies should be governed by research or care regulations remains a debated issue. Here, we delineate differences between medical research and optimized clinical care, and distinguish the regulations which apply to either. We also set standards for responsible optimized clinical n-of-1 strategies with (off-label) treatments for rare diseases. Implementing clinical n-of-1 strategies as defined here could aid in optimized treatment selection for such diseases

Dental implants in dentate primary and secondary Sjögren's syndrome patients:A multicenter prospective cohort study

Objectives: To prospectively assess the clinical performance and patient-reported outcomes of dental implants in dentate patients with primary and secondary Sjögren's syndrome (pSS and sSS, respectively) compared to patients without SS. Materials and Methods: Thirty-seven implants were placed in 17 patients with pSS/sSS and 26 implants in 17 non-SS patients to replace missing (pre)molars. Clinical performance, marginal bone-level changes, patient satisfaction, and oral health-related quality of life (OHRQoL) were assessed at 1 (T1), 6 (T6), 12 (T12), and 18 (T18) months after placement of the superstructure. Marginal bone-level changes were measured on standardized dental radiographs. Clinical parameters included implant and crown survival, plaque, bleeding and gingival indices, and probing depth. Patient satisfaction and OHRQoL were assessed with validated questionnaires. Results: Implant survival at T18 was 100% in the patients with pSS/sSS and 96.2% in the non-SS group. Mean marginal bone loss at T18 did not differ between patients with pSS/sSS and non-SS patients, 1.10 ± 1.04 and 1.04 ± 0.75 mm, respectively (p =.87). Clinical performance was good with no differences between the groups for all outcome measures (p >.05). OHRQoL in patients with pSS/sSS had improved significantly after placement of implant supported crowns at all measuring moments compared to baseline (p <.05). Nevertheless, patient satisfaction and OHRQoL remained significantly higher for patients without SS at all measuring moments (p <.05). Conclusion: Dental implants can be successfully applied in dentate patients with pSS/sSS and have a positive effect on OHRQoL

Mining microbial metatranscriptomes for expression of antibiotic resistance genes under natural conditions

Antibiotic resistance genes are found in a broad range of ecological niches associated with complex microbiota. Here we investigated if resistance genes are not only present, but also transcribed under natural conditions. Furthermore, we examined the potential for antibiotic production by assessing the expression of associated secondary metabolite biosynthesis gene clusters. Metatranscriptome datasets from intestinal microbiota of four human adults, one human infant, 15 mice and six pigs, of which only the latter have received antibiotics prior to the study, as well as from sea bacterioplankton, a marine sponge, forest soil and sub-seafloor sediment, were investigated. We found that resistance genes are expressed in all studied ecological niches, albeit with niche-specific differences in relative expression levels and diversity of transcripts. For example, in mice and human infant microbiota predominantly tetracycline resistance genes were expressed while in human adult microbiota the spectrum of expressed genes was more diverse, and also included beta-lactam, aminoglycoside and macrolide resistance genes. Resistance gene expression could result from the presence of natural antibiotics in the environment, although we could not link it to expression of corresponding secondary metabolites biosynthesis clusters. Alternatively, resistance gene expression could be constitutive, or these genes serve alternative roles besides antibiotic resistance.Peer reviewe

Disruptions of Anaerobic Gut Bacteria Are Associated with Stroke and Post-stroke Infection : a Prospective Case-Control Study

In recent years, preclinical studies have illustrated the potential role of intestinal bacterial composition in the risk of stroke and post-stroke infections. The results of these studies suggest that bacteria capable of producing volatile metabolites, including trimethylamine-N-oxide (TMAO) and butyrate, play opposing, yet important roles in the cascade of events leading to stroke. However, no large-scale studies have been undertaken to determine the abundance of these bacterial communities in stroke patients and to assess the impact of disrupted compositions of the intestinal microbiota on patient outcomes. In this prospective case-control study, rectal swabs from 349 ischemic and hemorrhagic stroke patients (median age, 71 years; IQR: 67-75) were collected within 24 h of hospital admission. Samples were subjected to 16S rRNA amplicon sequencing and subsequently compared with samples obtained from 51 outpatient age- and sex-matched controls (median age, 72 years; IQR, 62-80) with similar cardiovascular risk profiles but without active signs of stroke. Plasma protein biomarkers were analyzed using a combination of nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS). Alpha and beta diversity analyses revealed higher disruption of intestinal communities during ischemic and hemorrhagic stroke compared with non-stroke matched control subjects. Additionally, we observed an enrichment of bacteria implicated in TMAO production and a loss of butyrate-producing bacteria. Stroke patients displayed two-fold lower plasma levels of TMAO than controls (median 1.97 vs 4.03 mu M, Wilcoxonp <0.0001). Finally, lower abundance of butyrate-producing bacteria within 24 h of hospital admission was an independent predictor of enhanced risk of post-stroke infection (odds ratio 0.77,p = 0.005), but not of mortality or functional patient outcome. In conclusion, aberrations in trimethylamine- and butyrate-producing gut bacteria are associated with stroke and stroke-associated infections.Peer reviewe

KidneyNetwork:Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease

Abstract: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. Translational statement: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.</p