Potential Role of Inflammation-Promoting Biliary Microbiome in Primary Sclerosing Cholangitis and Cholangiocarcinoma.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a major risk factor for cholangiocarcinoma (CCA). We investigated biliary and fecal microbiota to determine whether specific microbes in the bile or stool are associated with PSC or CCA. METHODS: Bile was obtained from 32 patients with PSC, 23 with CCA with PSC, 26 with CCA without PSC, and 17 controls. Over 90% of bile samples were from patients with perihilar CCA. Stool was obtained from 31 patients with PSC (11 were matched to bile), 16 with CCA with PSC (10 matched to bile), and 11 with CCA without PSC (6 matched to bile). Microbiota composition was assessed using 16SrRNA-marker-based sequencing and was compared between groups. RESULTS: Bile has a unique microbiota distinguished from negative DNA controls and stool. Increased species richness and abundance of Fusobacteria correlated with duration of PSC and characterized the biliary microbiota in CCA. Stool microbiota composition showed no significant differences between groups. CONCLUSIONS: We identified a unique microbial signature in the bile of patients with increased duration of PSC or with CCA, suggesting a role for microbiota-driven inflammation in the pathogenesis and or progression to perihilar CCA. Further studies are needed to test this hypothesis.

Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing.

Metagenomic shotgun sequencing has the potential to transform how serious infections are diagnosed by offering universal, culture-free pathogen detection. This may be especially advantageous for microbial diagnosis of prosthetic joint infection (PJI) by synovial fluid analysis since synovial fluid cultures are not universally positive and since synovial fluid is easily obtained preoperatively. We applied a metagenomics-based approach to synovial fluid in an attempt to detect microorganisms in 168 failed total knee arthroplasties. Genus- and species-level analyses of metagenomic sequencing yielded the known pathogen in 74 (90%) and 68 (83%) of the 82 culture-positive PJIs analyzed, respectively, with testing of two (2%) and three (4%) samples, respectively, yielding additional pathogens not detected by culture. For the 25 culture-negative PJIs tested, genus- and species-level analyses yielded 19 (76%) and 21 (84%) samples with insignificant findings, respectively, and 6 (24%) and 4 (16%) with potential pathogens detected, respectively. Genus- and species-level analyses of the 60 culture-negative aseptic failure cases yielded 53 (88%) and 56 (93%) cases with insignificant findings and 7 (12%) and 4 (7%) with potential clinically significant organisms detected, respectively. There was one case of aseptic failure with synovial fluid culture growth; metagenomic analysis showed insignificant findings, suggesting possible synovial fluid culture contamination. Metagenomic shotgun sequencing can detect pathogens involved in PJI when applied to synovial fluid and may be particularly useful for culture-negative cases.

Identification of Prosthetic Joint Infection Pathogens Using a Shotgun Metagenomics Approach.

Background: Metagenomic shotgun sequencing has the potential to change how many infections, particularly those caused by difficult-to-culture organisms, are diagnosed. Metagenomics was used to investigate prosthetic joint infections (PJIs), where pathogen detection can be challenging. Methods: Four hundred eight sonicate fluid samples generated from resected hip and knee arthroplasties were tested, including 213 from subjects with infections and 195 from subjects without infection. Samples were enriched for microbial DNA using the MolYsis basic kit, whole-genome amplified, and sequenced using Illumina HiSeq 2500 instruments. A pipeline was designed to screen out human reads and analyze remaining sequences for microbial content using the Livermore Metagenomics Analysis Toolkit and MetaPhlAn2 tools. Results: When compared to sonicate fluid culture, metagenomics was able to identify known pathogens in 94.8% (109/115) of culture-positive PJIs, with additional potential pathogens detected in 9.6% (11/115). New potential pathogens were detected in 43.9% (43/98) of culture-negative PJIs, 21 of which had no other positive culture sources from which these microorganisms had been detected. Detection of microorganisms in samples from uninfected aseptic failure cases was conversely rare (7/195 [3.6%] cases). The presence of human and contaminant microbial DNA from reagents was a challenge, as previously reported. Conclusions: Metagenomic shotgun sequencing is a powerful tool to identify a wide range of PJI pathogens, including difficult-to-detect pathogens in culture-negative infections.

A comprehensive analysis of breast cancer microbiota and host gene expression.

The inflammatory tumoral-immune response alters the physiology of the tumor microenvironment, which may attenuate genomic instability. In addition to inducing inflammatory immune responses, several pathogenic bacteria produce genotoxins. However the extent of microbial contribution to the tumor microenvironment biology remains unknown. We utilized The Cancer Genome Atlas, (TCGA) breast cancer data to perform a novel experiment utilizing unmapped and mapped RNA sequencing read evidence to minimize laboratory costs and effort. Our objective was to characterize the microbiota and associate the microbiota with the tumor expression profiles, for 668 breast tumor tissues and 72 non-cancerous adjacent tissues. The prominent presence of Proteobacteria was increased in the tumor tissues and conversely Actinobacteria abundance increase in non-cancerous adjacent tissues. Further, geneset enrichment suggests Listeria spp to be associated with the expression profiles of genes involved with epithelial to mesenchymal transitions. Moreover, evidence suggests H. influenza may reside in the surrounding stromal material and was significantly associated with the proliferative pathways: G2M checkpoint, E2F transcription factors, and mitotic spindle assembly. In summary, further unraveling this complicated interplay should enable us to better diagnose and treat breast cancer patients.

The Microbiome of Aseptically Collected Human Breast Tissue in Benign and Malignant Disease.

Globally breast cancer is the leading cause of cancer death among women. The breast consists of epithelium, stroma and a mucosal immune system that make up a complex microenvironment. Growing awareness of the role of microbes in the microenvironment recently has led to a series of findings important for human health. The microbiome has been implicated in cancer development and progression at a variety of body sites including stomach, colon, liver, lung, and skin. In this study, we assessed breast tissue microbial signatures in intraoperatively obtained samples using 16S rDNA hypervariable tag sequencing. Our results indicate a distinct breast tissue microbiome that is different from the microbiota of breast skin tissue, breast skin swabs, and buccal swabs. Furthermore, we identify distinct microbial communities in breast tissues from women with cancer as compared to women with benign breast disease. Malignancy correlated with enrichment in taxa of lower abundance including the genera Fusobacterium, Atopobium, Gluconacetobacter, Hydrogenophaga and Lactobacillus. This work confirms the existence of a distinct breast microbiome and differences between the breast tissue microbiome in benign and malignant disease. These data provide a foundation for future investigation on the role of the breast microbiome in breast carcinogenesis and breast cancer prevention.

Multiple sclerosis patients have a distinct gut microbiota compared to healthy controls.

Multiple sclerosis (MS) is an immune-mediated disease, the etiology of which involves both genetic and environmental factors. The exact nature of the environmental factors responsible for predisposition to MS remains elusive; however, it's hypothesized that gastrointestinal microbiota might play an important role in pathogenesis of MS. Therefore, this study was designed to investigate whether gut microbiota are altered in MS by comparing the fecal microbiota in relapsing remitting MS (RRMS) (n = 31) patients to that of age- and gender-matched healthy controls (n = 36). Phylotype profiles of the gut microbial populations were generated using hypervariable tag sequencing of the V3-V5 region of the 16S ribosomal RNA gene. Detailed fecal microbiome analyses revealed that MS patients had distinct microbial community profile compared to healthy controls. We observed an increased abundance of Psuedomonas, Mycoplana, Haemophilus, Blautia, and Dorea genera in MS patients, whereas control group showed increased abundance of Parabacteroides, Adlercreutzia and Prevotella genera. Thus our study is consistent with the hypothesis that MS patients have gut microbial dysbiosis and further study is needed to better understand their role in the etiopathogenesis of MS.

Comparison of microbial DNA enrichment tools for metagenomic whole genome sequencing.

Metagenomic whole genome sequencing for detection of pathogens in clinical samples is an exciting new area for discovery and clinical testing. A major barrier to this approach is the overwhelming ratio of human to pathogen DNA in samples with low pathogen abundance, which is typical of most clinical specimens. Microbial DNA enrichment methods offer the potential to relieve this limitation by improving this ratio. Two commercially available enrichment kits, the NEBNext Microbiome DNA Enrichment Kit and the Molzym MolYsis Basic kit, were tested for their ability to enrich for microbial DNA from resected arthroplasty component sonicate fluids from prosthetic joint infections or uninfected sonicate fluids spiked with Staphylococcus aureus. Using spiked uninfected sonicate fluid there was a 6-fold enrichment of bacterial DNA with the NEBNext kit and 76-fold enrichment with the MolYsis kit. Metagenomic whole genome sequencing of sonicate fluid revealed 13- to 85-fold enrichment of bacterial DNA using the NEBNext enrichment kit. The MolYsis approach achieved 481- to 9580-fold enrichment, resulting in 7 to 59% of sequencing reads being from the pathogens known to be present in the samples. These results demonstrate the usefulness of these tools when testing clinical samples with low microbial burden using next generation sequencing.