Draft genome sequence of two "Candidatus Intestinicoccus colisanans" strains isolated from faeces of healthy humans.

OBJECTIVES: In order to provide a better insight into the functional capacity of the human gut microbiome, we isolated a novel bacterium, "Candidatus Intestinicoccus colisanans" gen. nov. sp. nov., and performed whole genome sequencing. This study will provide new insights into the functional potential of this bacterium and its role in modulating host health and well-being. We expect that this data resource will be useful in providing additional insight into the diversity and functional potential of the human microbiome. DATA DESCRIPTION: Here, we report the first draft genome sequences of "Candidatus Intestinicoccus colisanans" strains MH27-1 and MH27-2, recovered from faeces collected from healthy human donors. The genomes were sequenced using short-read Illumina technology and whole-genome-based comparisons and phylogenomics reconstruction indicate that "Candidatus Intestinicoccus colisanans" represents a novel genus and species within the family Acutalibacteraceae. Both genomes were estimated to be > 98% completed and to range in size from 2.9 to 3.3 Mb with a G + C content of approximately 51%. The gene repertoire of "Candidatus Intestinicoccus colisanans" indicate it is likely a saccharolytic gut bacterium.

Semantic segmentation for fully automated macrofouling analysis on coatings after field exposure.

Biofouling is a major challenge for sustainable shipping, filter membranes, heat exchangers, and medical devices. The development of fouling-resistant coatings requires the evaluation of their effectiveness. Such an evaluation is usually based on the assessment of fouling progression after different exposure times to the target medium (e.g. salt water). The manual assessment of macrofouling requires expert knowledge about local fouling communities due to high variances in phenotypical appearance, has single-image sampling inaccuracies for certain species, and lacks spatial information. Here an approach for automatic image-based macrofouling analysis was presented. A dataset with dense labels prepared from field panel images was made and a convolutional network (adapted U-Net) for the semantic segmentation of different macrofouling classes was proposed. The establishment of macrofouling localization allows for the generation of a successional model which enables the determination of direct surface attachment and in-depth epibiotic studies.

Administration of Hookworm Excretory/Secretory Proteins Improves Glucose Tolerance in a Mouse Model of Type 2 Diabetes.

Diabetes is recognised as the world's fastest growing chronic condition globally. Helminth infections have been shown to be associated with a lower prevalence of type 2 diabetes (T2D), in part due to their ability to induce a type 2 immune response. Therefore, to understand the molecular mechanisms that underlie the development of T2D-induced insulin resistance, we treated mice fed on normal or diabetes-promoting diets with excretory/secretory products (ES) from the gastrointestinal helminth Nippostrongylus brasiliensis. We demonstrated that treatment with crude ES products from adult worms (AES) or infective third-stage larvae (L3ES) from N. brasiliensis improved glucose tolerance and attenuated body weight gain in mice fed on a high glycaemic index diet. N. brasiliensis ES administration to mice was associated with a type 2 immune response measured by increased eosinophils and IL-5 in peripheral tissues but not IL-4, and with a decrease in the level of IL-6 in adipose tissue and corresponding increase in IL-6 levels in the liver. Moreover, treatment with AES or L3ES was associated with significant changes in the community composition of the gut microbiota at the phylum and order levels. These data highlight a role for N. brasiliensis ES in modulating the immune response associated with T2D, and suggest that N. brasiliensis ES contain molecules with therapeutic potential for treating metabolic syndrome and T2D.

Autism-related dietary preferences mediate autism-gut microbiome associations.

There is increasing interest in the potential contribution of the gut microbiome to autism spectrum disorder (ASD). However, previous studies have been underpowered and have not been designed to address potential confounding factors in a comprehensive way. We performed a large autism stool metagenomics study (n = 247) based on participants from the Australian Autism Biobank and the Queensland Twin Adolescent Brain project. We found negligible direct associations between ASD diagnosis and the gut microbiome. Instead, our data support a model whereby ASD-related restricted interests are associated with less-diverse diet, and in turn reduced microbial taxonomic diversity and looser stool consistency. In contrast to ASD diagnosis, our dataset was well powered to detect microbiome associations with traits such as age, dietary intake, and stool consistency. Overall, microbiome differences in ASD may reflect dietary preferences that relate to diagnostic features, and we caution against claims that the microbiome has a driving role in ASD.

Evaluation of the Microba Community Profiler for Taxonomic Profiling of Metagenomic Datasets From the Human Gut Microbiome.

A fundamental goal of microbial ecology is to accurately determine the species composition in a given microbial ecosystem. In the context of the human microbiome, this is important for establishing links between microbial species and disease states. Here we benchmark the Microba Community Profiler (MCP) against other metagenomic classifiers using 140 moderate to complex in silico microbial communities and a standardized reference genome database. MCP generated accurate relative abundance estimates and made substantially fewer false positive predictions than other classifiers while retaining a high recall rate. We further demonstrated that the accuracy of species classification was substantially increased using the Microba Genome Database, which is more comprehensive than reference datasets used by other classifiers and illustrates the importance of including genomes of uncultured taxa in reference databases. Consequently, MCP classifies appreciably more reads than other classifiers when using their recommended reference databases. These results establish MCP as best-in-class with the ability to produce comprehensive and accurate species profiles of human gastrointestinal samples.

Layer-by-Layer Deposited Hybrid Polymer Coatings Based on Polysaccharides and Zwitterionic Silanes with Marine Antifouling Properties.

Polyelectrolyte multilayer (PEM) assembly is a versatile tool to construct low-fouling coatings. For application in the marine environment, their structure needs to be stabilized by covalent linkage. Here, we introduce an approach for spin coating of silane-based sol-gel chemistries using layer-by-layer assembly of polysaccharide-based hybrid polymer coatings (LBLHPs). The silane sol-gel chemistry allows the films to be cross-linked under water-based and mild reaction conditions. Two different silanes were used for this purpose, a conventional triethoxymethyl silane and a de novo synthesized zwitterionic silane. The polysaccharide-silane hybrid polymer coatings were thoroughly characterized with spectroscopic ellipsometry, water contact angle (WCA) goniometry, attenuated total reflection-Fourier transform infrared spectroscopy, and atomic force microscopy. The coatings showed good stability in seawater, smooth surfaces, a high degree of hydration, and WCAs below or close to the Berg limit. LBLHPs showed low-fouling properties in biological assays against nonspecific protein adsorption, attachment of the diatom Navicula perminuta, and settlement of zoospores of the macroalga Ulva linza.

Critical evaluation of faecal microbiome preservation using metagenomic analysis.

The ability to preserve microbial communities in faecal samples is essential as increasing numbers of studies seek to use the gut microbiome to identify biomarkers of disease. Here we use shotgun metagenomics to rigorously evaluate the technical and compositional reproducibility of five room temperature (RT) microbial stabilisation methods compared to the best practice of flash-freezing. These methods included RNALater, OMNIGene-GUT, a dry BBL swab, LifeGuard, and a novel method for preserving faecal samples, a Copan FLOQSwab in an active drying tube (FLOQSwab-ADT). Each method was assessed using six replicate faecal samples from five participants, totalling 180 samples. The FLOQSwab-ADT performed best for both technical and compositional reproducibility, followed by RNAlater and OMNIgene-GUT. LifeGuard and the BBL swab had unpredictable outgrowth of Escherichia species in at least one replicate from each participant. We further evaluated the FLOQSwab-ADT in an additional 239 samples across 10 individuals after storage at -20 °C, RT, and 50 °C for four weeks compared to fresh controls. The FLOQSwab-ADT maintained its performance across all temperatures, indicating this method is an excellent alternative to existing RT stabilisation methods.

Fully Convolutional Neural Network for Detection and Counting of Diatoms on Coatings after Short-Term Field Exposure.

While the use of deep learning is a valuable technology for automatic detection systems for medical data and images, the biofouling community is still lacking an analytical tool for the detection and counting of diatoms on samples after short-term field exposure. In this work, a fully convolutional neural network was implemented as a fast and simple approach to detect diatoms on two-channel (fluorescence and phase-contrast) microscopy images by predicting bounding boxes. The developed approach performs well with only a small number of trainable parameters and a F1 score of 0.82. Counting diatoms was evaluated on a data set of 600 microscopy images of three different surface chemistries (hydrophilic and hydrophobic) and is very similar to counting by humans while demanding only a fraction of the analysis time.

Author Correction: Increased susceptibility of airway epithelial cells from ataxia-telangiectasia to S. pneumoniae infection due to oxidative damage and impaired innate immunity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Infection with the sheep gastrointestinal nematode Teladorsagia circumcincta increases luminal pathobionts.

BACKGROUND: The multifaceted interactions between gastrointestinal (GI) helminth parasites, host gut microbiota and immune system are emerging as a key area of research within the field of host-parasite relationships. In spite of the plethora of data available on the impact that GI helminths exert on the composition of the gut microflora, whether alterations of microbial profiles are caused by direct parasite-bacteria interactions or, indirectly, by alterations of the GI environment (e.g. mucosal immunity) remains to be determined. Furthermore, no data is thus far available on the downstream roles that qualitative and quantitative changes in gut microbial composition play in the overall pathophysiology of parasite infection and disease. RESULTS: In this study, we investigated the fluctuations in microbiota composition and local immune microenvironment of sheep vaccinated against, and experimentally infected with, the 'brown stomach worm' Teladorsagia circumcincta, a parasite of worldwide socio-economic significance. We compared the faecal microbial profiles of vaccinated and subsequently infected sheep with those obtained from groups of unvaccinated/infected and unvaccinated/uninfected animals. We show that alterations of gut microbial composition are associated mainly with parasite infection, and that this involves the expansion of populations of bacteria with known pro-inflammatory properties that may contribute to the immunopathology of helminth disease. Using novel quantitative approaches for the analysis of confocal microscopy-derived images, we also show that gastric tissue infiltration of T cells is driven by parasitic infection rather than anti-helminth vaccination. CONCLUSIONS: Teladorsagia circumcincta infection leads to an expansion of potentially pro-inflammatory gut microbial species and abomasal T cells. This data paves the way for future experiments aimed to determine the contribution of the gut flora to the pathophysiology of parasitic disease, with the ultimate aim to design and develop novel treatment/control strategies focused on preventing and/or restricting bacterial-mediated inflammation upon infection by GI helminths. Video Abstract.

Chronic High-Fat Diet Induces Early Barrett's Esophagus in Mice through Lipidome Remodeling.

Esophageal adenocarcinoma (EAC) incidence has been rapidly increasing, potentially associated with the prevalence of the risk factors gastroesophageal reflux disease (GERD), obesity, high-fat diet (HFD), and the precursor condition Barrett's esophagus (BE). EAC development occurs over several years, with stepwise changes of the squamous esophageal epithelium, through cardiac metaplasia, to BE, and then EAC. To establish the roles of GERD and HFD in initiating BE, we developed a dietary intervention model in C57/BL6 mice using experimental HFD and GERD (0.2% deoxycholic acid, DCA, in drinking water), and then analyzed the gastroesophageal junction tissue lipidome and microbiome to reveal potential mechanisms. Chronic (9 months) HFD alone induced esophageal inflammation and metaplasia, the first steps in BE/EAC pathogenesis. While 0.2% deoxycholic acid (DCA) alone had no effect on esophageal morphology, it synergized with HFD to increase inflammation severity and metaplasia length, potentially via increased microbiome diversity. Furthermore, we identify a tissue lipid signature for inflammation and metaplasia, which is characterized by elevated very-long-chain ceramides and reduced lysophospholipids. In summary, we report a non-transgenic mouse model, and a tissue lipid signature for early BE. Validation of the lipid signature in human patient cohorts could pave the way for specific dietary strategies to reduce the risk of BE in high-risk individuals.

Helminths, polyparasitism, and the gut microbiome in the Philippines.

Polyparasitism, involving soil-transmitted helminths. and Schistosoma blood flukes, is common in low to middle income countries. These helminths impact on the gut environment and can cause changes to the gut microbiome composition. Here we examined the gut microbiome in individuals with polyparasitism from two human cohorts in the Philippines utilising DNA sequencing-based profiling. Multiple helminth species infections were high with 70.3% of study participants harbouring at least two parasite species, and 16% harbouring at least five species. Increased numbers of helminth co-infections, in particular with the gut-resident soil-transmitted helminths, were significantly associated with increased bacterial diversity; however no significant parasite-gut microbiome associations were evident for individuals infected only with Schistosoma japonicum. In general, a healthy gut is associated with high bacterial diversity, which in these human cohorts may be the result of helminth-mediated immune modulation, or due to changes in the gut environment caused by these parasitic helminths.

Chromosome arm aneuploidies shape tumour evolution and drug response.

Chromosome arm aneuploidies (CAAs) are pervasive in cancers. However, how they affect cancer development, prognosis and treatment remains largely unknown. Here, we analyse CAA profiles of 23,427 tumours, identifying aspects of tumour evolution including probable orders in which CAAs occur and CAAs predicting tissue-specific metastasis. Both haematological and solid cancers initially gain chromosome arms, while only solid cancers subsequently preferentially lose multiple arms. 72 CAAs and 88 synergistically co-occurring CAA pairs multivariately predict good or poor survival for 58% of 6977 patients, with negligible impact of whole-genome doubling. Additionally, machine learning identifies 31 CAAs that robustly alter response to 56 chemotherapeutic drugs across cell lines representing 17 cancer types. We also uncover 1024 potential synthetic lethal pharmacogenomic interactions. Notably, in predicting drug response, CAAs substantially outperform  mutations and focal deletions/amplifications combined. Thus, CAAs predict cancer prognosis, shape tumour evolution, metastasis and drug response, and may advance precision oncology.

Gastrointestinal Helminth Infection Improves Insulin Sensitivity, Decreases Systemic Inflammation, and Alters the Composition of Gut Microbiota in Distinct Mouse Models of Type 2 Diabetes.

Type 2 diabetes (T2D) is a major health problem and is considered one of the top 10 diseases leading to death globally. T2D has been widely associated with systemic and local inflammatory responses and with alterations in the gut microbiota. Microorganisms, including parasitic worms and gut microbes have exquisitely co-evolved with their hosts to establish an immunological interaction that is essential for the formation and maintenance of a balanced immune system, including suppression of excessive inflammation. Herein we show that both prophylactic and therapeutic infection of mice with the parasitic hookworm-like nematode, Nippostrongylus brasiliensis, significantly reduced fasting blood glucose, oral glucose tolerance and body weight gain in two different diet-induced mouse models of T2D. Helminth infection was associated with elevated type 2 immune responses including increased eosinophil numbers in the mesenteric lymph nodes, liver and adipose tissues, as well as increased expression of IL-4 and alternatively activated macrophage marker genes in adipose tissue, liver and gut. N. brasiliensis infection was also associated with significant compositional changes in the gut microbiota at both the phylum and order levels. Our findings show that N. brasiliensis infection drives changes in local and systemic immune cell populations, and that these changes are associated with a reduction in systemic and local inflammation and compositional changes in the gut microbiota which cumulatively might be responsible for the improved insulin sensitivity observed in infected mice. Our findings indicate that carefully controlled therapeutic hookworm infection in humans could be a novel approach for treating metabolic syndrome and thereby preventing T2D.

The Association between the Comprehensive Epstein-Barr Virus Serologic Profile and Endemic Burkitt Lymphoma.

BACKGROUND: The discovery of Epstein-Barr virus (EBV) in Burkitt lymphoma tumors represented the first link between a virus and cancer in humans, but the underlying role of this virus in endemic Burkitt lymphoma remains unclear. Nearly all children in Burkitt lymphoma-endemic areas are seropositive for EBV, but only a small percentage develop disease. Variation in EBV-directed immunity could be an explanatory cofactor. METHODS: We examined serum from 150 Burkitt lymphoma cases and 150 controls using a protein microarray that measured IgG and IgA antibodies against 202 sequences across the entire EBV proteome. Variation in the EBV-directed antibody repertoire between Burkitt lymphoma cases and controls was assessed using unpaired t tests. ORs quantifying the association between anti-EBV IgG response tertiles and Burkitt lymphoma status were adjusted for age, sex, and study year. RESULTS: Thirty-three anti-EBV IgG responses were elevated in Burkitt lymphoma cases compared with controls (P ≤ 0.0003). Burkitt lymphoma-associated IgG elevations were strongest for EBV proteins involved in viral replication and antiapoptotic signaling. Specifically, we observed ORs ≥4 for BMRF1 (early antigen), BBLF1 (tegument protein), BHRF1 (Bcl-2 homolog), BZLF1 (Zebra), BILF2 (glycoprotein), BLRF2 [viral capsid antigen (VCA)p23], BDLF4, and BFRF3 (VCAp18). Adjustment for malaria exposure and inheritance of the sickle cell variant did not alter associations. CONCLUSIONS: Our data suggest that the anti-EBV serologic profile in patients with Burkitt lymphoma is altered, with strong elevations in 33 of the measured anti-EBV IgG antibodies relative to disease-free children. IMPACT: The Burkitt lymphoma-specific signature included EBV-based markers relevant for viral replication and antiapoptotic activity, providing clues for future Burkitt lymphoma pathogenesis research.

Immune Signature Against Plasmodium falciparum Antigens Predicts Clinical Immunity in Distinct Malaria Endemic Communities.

A large body of evidence supports the role of antibodies directed against the Plasmodium spp. parasite in the development of naturally acquired immunity to malaria, however an antigen signature capable of predicting protective immunity against Plasmodium remains to be identified. Key challenges for the identification of a predictive immune signature include the high dimensionality of data produced by high-throughput technologies and the limitation of standard statistical tests in accounting for synergetic interactions between immune responses to multiple targets. In this study, using samples collected from young children in Ghana at multiple time points during a longitudinal study, we adapted a predictive modeling framework which combines feature selection and machine learning techniques to identify an antigen signature of clinical immunity to malaria. Our results show that an individual's immune status can be accurately predicted by measuring antibody responses to a small defined set of 15 target antigens. We further demonstrate that the identified immune signature is highly versatile and capable of providing precise and accurate estimates of clinical protection from malaria in an independent geographic community. Our findings pave the way for the development of a robust point-of-care test to identify individuals at high risk of disease and which could be applied to monitor the impact of vaccinations and other interventions. This approach could be also translated to biomarker discovery for other infectious diseases.

Potential clinical utility of multiple target quantitative polymerase chain reaction (qPCR) array to detect microbial pathogens in patients with chronic obstructive pulmonary disease (COPD).

BACKGROUND: Culture-independent methods such as quantitative polymerase chain reaction (qPCR) are more sensitive for detecting pathogens than conventional culture. This study aimed to test the clinical potential of a multiple target qPCR array in identifying sputum pathogens, compared to traditional culture. METHODS: Forty chronic obstructive pulmonary disease (COPD) patients provided spontaneous sputum and blood samples during an exacerbation event (n=25 patients) and in stable state (n=15 patients). Sputum was processed and analysed by microscopy, culture and sensitivity testing (MCS) to identify living microbial isolates, and multiple target qPCR (44 targets for bacterial and fungal pathogens and antibiotic resistance genes), and 16S rRNA gene sequencing. RESULTS: Six microbial isolates (5 bacterial, 1 fungal) were cultured from 20 exacerbation and 10 stable patient sputum samples. Four of these microbial isolates had their presence in patient sputum confirmed by qPCR. All bacterial targets detected by qPCR were further confirmed by 16S rRNA gene sequencing at a genus level. qPCR identified significantly more bacterial pathogens than culture (P<0.001). The most prevalent bacterial species identified by qPCR were Streptococcus pneumoniae (72% of patients), Pseudomonas aeruginosa (40%), Prevotella oris (32%) and Haemophilus influenzae (17%). Microbial species diversity and richness were not significantly different between samples obtained from exacerbating and clinically stable cases. 16S rRNA gene sequencing identified Pseudomonas 4408227 (P=0.022, FDR =0.043 AUC =0.72) as a significantly different bacterial OTU (operational taxonomic units) in exacerbation sputum samples compared to stable state samples. CONCLUSIONS: Multiple target qPCR was more sensitive for detection of sputum pathogens in COPD patients than conventional culture. 16S rRNA gene sequencing confirmed the identity at a genus level of all bacterial targets detected by qPCR, as well as identifying bacterial OTUs that could potentially be used to distinguish between exacerbation and stable COPD disease states. Multiple target qPCR pathogen detection in the sputum of COPD patients warrants further investigation to determine how it may influence COPD clinical management.

Microbiota and Body Composition During the Period of Complementary Feeding.

OBJECTIVES: This study aimed to explore the associations between food group intake, faecal microbiota profile, and body composition during the period of complementary feeding. METHODS: Diet was assessed using a quantitative food frequency questionnaire, faecal microbiota profile was assessed using 16S rRNA gene sequencing, and body composition was assessed using bioelectrical impedance analysis and dual energy x-ray absorptiometry, in a cohort of 50 infants aged 6 to 24 months of age. RESULTS: During this critical period of microbiota development, age was the strongest predictor of microbiota composition with network analysis revealing a cluster of genera positively associated with age. A separate cluster comprised genera associated with fat mass index with Bifidobacterium showing the strongest correlation with fat mass index (rho = 0.55, P = 0.001, false discovery rate [FDR] = 0.018). Dairy intake was both negatively correlated with Bacteroides (rho = -0.49, P < 0.001, FDR = 0.024) and positively correlated with lean mass index (rho = 0.44, P = 0.007, FDR = 0.024). Antibiotics use in the first month of life had the most striking influence on body composition and was associated with an increase in mean body mass index z score of 1.17 (P = 0.001) and body fat of 3.5% (P = 0.001). CONCLUSIONS: Our results suggested that antibiotics use in the first month of life had the most striking influence on body composition in this cohort of infants aged 6 to 24 months, whereas dairy intake interacted with both microbiota and body composition in early life.