Metagenomic Profiling Research Articles

Metagenomic insights into the functional genes across transects in a typical estuarine marsh

Salt marshes are potentially one of the most efficient carbon (C) sinks worldwide and perform important ecosystem functions, but sea level rise alters marsh sediments properties and thus threatens microbial roles in ecosystem functioning. Yet, the mechanisms of interactions of biochemical processes with microorganisms and their functions are still not fully understood. Here, this study investigated metagenomic taxonomic and functional profiling from the water-land conjugation up to about 300 m, 1000 m, and 2500 m in three parallel transects, respectively, in Hangzhou Bay, China. The results showed that soil physicochemical factors drove metagenomic taxonomic and functional genes in the 2500-m transect significantly different from other sites. The 2500-m transect had a greater abundance of Chloroflexi and Acidobacteria but lower in Proteobacteria. The metagenomic functional genes related to Phosphorus Metabolism (PHO) and Potassium Metabolism (POT) increased in the 2500 m. Additionally, nutrient-cycling functions and the genera of Anaeromyxobacter, Roseiflexus, and Geobacter related to PHO, POT at 2500 m were significantly greater than those of other transects. Carbon cycling functions within Carbohydrates (CHO) also differed significantly across transects. These research results demonstrated that the relative abundance of metagenomic microorganisms and their functional genes were significantly separated across the three transects. The vegetation type, salinity, and soil properties might be among the influencing factors.

Depression and fatigue in active IBD from a microbiome perspective—a Bayesian approach to faecal metagenomics

BackgroundExtraintestinal symptoms are common in inflammatory bowel diseases (IBD) and include depression and fatigue. These are highly prevalent especially in active disease, potentially due to inflammation-mediated changes in the microbiota-gut-brain axis. The aim of this study was to investigate the associations between structural and functional microbiota characteristics and severity of fatigue and depressive symptoms in patients with active IBD.MethodsWe included clinical data of 62 prospectively enrolled patients with IBD in an active disease state. Patients supplied stool samples and completed the questionnaires regarding depression and fatigue symptoms. Based on taxonomic and functional metagenomic profiles of faecal gut microbiota, we used Bayesian statistics to investigate the associative networks and triangle motifs between bacterial genera, functional modules and symptom severity of self-reported fatigue and depression.ResultsAssociations with moderate to strong evidence were found for 3 genera (Odoribacter, Anaerotruncus and Alistipes) and 3 functional modules (pectin, glycosaminoglycan and central carbohydrate metabolism) with regard to depression and for 4 genera (Intestinimonas, Anaerotruncus, Eubacterium and Clostridiales g.i.s) and 2 functional modules implicating amino acid and central carbohydrate metabolism with regard to fatigue.ConclusionsThis study provides the first evidence of association triplets between microbiota composition, function and extraintestinal symptoms in active IBD. Depression and fatigue were associated with lower abundances of short-chain fatty acid producers and distinct pathways implicating glycan, carbohydrate and amino acid metabolism. Our results suggest that microbiota-directed therapeutic approaches may reduce fatigue and depression in IBD and should be investigated in future research.

The "Crosstalk" between Microbiota and Metabolomic Profile of Kefalograviera Cheese after the Innovative Feeding Strategy of Dairy Sheep by Omega-3 Fatty Acids.

The purpose of this study was to examine the effects of two different feeding systems, a control or a flaxseed and lupin diet (experimental), for a sheep flock, on the microbiota and metabolome of Kefalograviera cheese samples produced by their milk. In particular, the microbiota present in Kefalograviera cheese samples was analyzed using 16S rRNA gene sequencing, while ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) was applied to investigate the chemical profile of the cheeses, considering the different feeding systems applied. The metagenomic profile was found to be altered by the experimental feeding system and significantly correlated to specific cheese metabolites, with Streptococcaceae and Lactobacillaceae establishing positive and negative correlations with the discriminant metabolites. Overall, more than 120 features were annotated and identified with high confidence level across the samples while most of them belonged to specific chemical classes. Characteristic analytes detected in different concentrations in the experimental cheese samples including arabinose, dulcitol, hypoxanthine, itaconic acid, L-arginine, L-glutamine and succinic acid. Therefore, taken together, our results provide an extensive foodomics approach for Kefalograviera cheese samples from different feeding regimes, investigating the metabolomic and metagenomic biomarkers that could be used to foresee, improve, and control cheese ripening outcomes, demonstrating the quality of the experimental Kefalograviera cheese.

Multi-omic phenotyping reveals host-microbe responses to bariatric surgery, glycaemic control and obesity

BackgroundResolution of type 2 diabetes (T2D) is common following bariatric surgery, particularly Roux-en-Y gastric bypass. However, the underlying mechanisms have not been fully elucidated.MethodsTo address this we compare the integrated serum, urine and faecal metabolic profiles of participants with obesity ± T2D (n = 80, T2D = 42) with participants who underwent Roux-en-Y gastric bypass or sleeve gastrectomy (pre and 3-months post-surgery; n = 27), taking diet into account. We co-model these data with shotgun metagenomic profiles of the gut microbiota to provide a comprehensive atlas of host-gut microbe responses to bariatric surgery, weight-loss and glycaemic control at the systems level.ResultsHere we show that bariatric surgery reverses several disrupted pathways characteristic of T2D. The differential metabolite set representative of bariatric surgery overlaps with both diabetes (19.3% commonality) and body mass index (18.6% commonality). However, the percentage overlap between diabetes and body mass index is minimal (4.0% commonality), consistent with weight-independent mechanisms of T2D resolution. The gut microbiota is more strongly correlated to body mass index than T2D, although we identify some pathways such as amino acid metabolism that correlate with changes to the gut microbiota and which influence glycaemic control.ConclusionWe identify multi-omic signatures associated with responses to surgery, body mass index, and glycaemic control. Improved understanding of gut microbiota - host co-metabolism may lead to novel therapies for weight-loss or diabetes. However, further experiments are required to provide mechanistic insight into the role of the gut microbiota in host metabolism and establish proof of causality.

Long-term continuous mono-cropping of Macadamia integrifolia greatly affects soil physicochemical properties, rhizospheric bacterial diversity, and metabolite contents.

Macadamia integrifolia is the most economically important Proteaceae crop known for its edible nuts. The present study was conducted to examine the effect of continuous cultivation (for 1, 5, and 20 years) of M. integrifolia on soil quality, bacterial diversity, and metabolites. Soil rhizospheres from three different Macadamia rhizosphere orchards, 1-year monoculture orchard (CK), 5-year monoculture orchard (Y5), and 20-year monoculture orchard (Y20), were analyzed through metagenomic and metabolomic profiling. The soil physicochemical properties, including organic matter, and available nutrients (P, N, and K) were first increased significantly (p < 0.05) from the CK to the Y5 group and then decreased (p < 0.05) from the Y5 to the Y20 group. The soil pH continuously decreased (p < 0.05) over time from CK to Y20. Metagenomic profiling revealed that Actinobacteria, Acidobacteria, and Proteobacteria were the top three abundant phyla with their inconsistent relative abundance patterns from CK to Y20 (CK: 23.76%, Y5: 34. 06%, and Y20: 31.55%), (CK: 13.59%, Y5: 18.59%, and Y20: 21.35%), and (CK: 27.59%, Y5: 15.98%, and Y20: 17.08%), respectively. Furthermore, the Y5 rhizospheres had a higher number of beneficial bacterial genera belonging to Proteobacteria and Actinobacteria than the Y20 rhizospheres. The KEGG annotation analysis revealed that cellular processes, organism systems, metabolism, and genetic information were the most enriched functional categories. CAZy database screening indicated the highest enrichment of glycoside hydrolases following the glycoside transferases and carbohydrate-binding modules. Differential metabolite analysis revealed the highest number of metabolites (11) in the Y5 group than in the Y20 group (6). It is concluded that continuous monoculture of M. integrifolia improves the soil physicochemical properties, bacterial diversity, and metabolite contents in short-term planted orchards which, however, are deteriorated in long-term planted orchards.

AsgeneDB: a curated orthology arsenic metabolism gene database and computational tool for metagenome annotation.

Arsenic (As) is the most ubiquitous toxic metalloid in nature. Microbe-mediated As metabolism plays an important role in global As biogeochemical processes, greatly changing its toxicity and bioavailability. While metagenomic sequencing may advance our understanding of the As metabolism capacity of microbial communities in different environments, accurate metagenomic profiling of As metabolism remains challenging due to low coverage and inaccurate definitions of As metabolism gene families in public orthology databases. Here we developed a manually curated As metabolism gene database (AsgeneDB) comprising 400 242 representative sequences from 59 As metabolism gene families, which are affiliated with 1653 microbial genera from 46 phyla. AsgeneDB achieved 100% annotation sensitivity and 99.96% annotation accuracy for an artificial gene dataset. We then applied AsgeneDB for functional and taxonomic profiling of As metabolism in metagenomes from various habitats (freshwater, hot spring, marine sediment and soil). The results showed that AsgeneDB substantially improved the mapping ratio of short reads in metagenomes from various environments. Compared with other databases, AsgeneDB provides more accurate, more comprehensive and faster analysis of As metabolic genes. In addition, we developed an R package, Asgene, to facilitate the analysis of metagenome sequencing data. Therefore, AsgeneDB and the associated Asgene package will greatly promote the study of As metabolism in microbial communities in various environments.

Antibiotics and probiotics impact gut antimicrobial resistance gene reservoir in COVID-19 patients

ABSTRACT Dysbiosis of gut microbiota is well-described in patients with coronavirus 2019 (COVID-19), but the dynamics of antimicrobial resistance genes (ARGs) reservoir, known as resistome, is less known. Here, we performed longitudinal fecal metagenomic profiling of 142 patients with COVID-19, characterized the dynamics of resistome from diagnosis to 6 months after viral clearance, and reported the impact of antibiotics or probiotics on the ARGs reservoir. Antibiotic-naive patients with COVID-19 showed increased abundance and types, and higher prevalence of ARGs compared with non-COVID-19 controls at baseline. Expansion in resistome was mainly driven by tetracycline, vancomycin, and multidrug-resistant genes and persisted for at least 6 months after clearance of SARS-CoV-2. Patients with expanded resistome exhibited increased prevalence of Klebsiella sp. and post-acute COVID-19 syndrome. Antibiotic treatment resulted in further increased abundance of ARGs whilst oral probiotics (synbiotic formula, SIM01) significantly reduced the ARGs reservoir in the gut microbiota of COVID-19 patients during the acute infection and recovery phase. Collectively, these findings shed new insights on the dynamic of ARGs reservoir in COVID-19 patients and the potential role of microbiota-directed therapies in reducing the burden of accumulated ARGs.

Aspirin, Risk of Colorectal Cancer, & Genetic Risk-Reply.

We appreciated the letter by Koulaouzidis and colleagues, which highlights the need for further studies to understand the mechanistic basis for aspirin's effect on colorectal cancer. Alongside their summary of our work (1) in the context of prior studies, they suggest that the effect of aspirin on gut microbiota should be examined. We agree that this is a high priority. As a rationale, they highlight research that shows aspirin appears to alter the gut microbiome to promote bacteria that are anti-inflammatory, thereby reducing colorectal cancer risk (2). We would further add that preclinical studies identify specific microbes that promote a proinflammatory environment, leading to induction of the enzymes that synthesize oncogenic prostaglandins which are inhibited by aspirin. Our group has also demonstrated that aspirin significantly inhibits tumorigenesis in ApcMin/+ mice inoculated with F. nucleatum and adenomas in aspirin users have significantly less Fusobacterium compared with nonaspirin users (3–5). These results are further supported by recent findings that aspirin treatment raises aspirin plasma concentrations and lowers tumor burden in microbiota-depleted mouse colorectal cancer models (ApcMin/+ and AOM/DSS), compared with microbiome-intact models and causes shifts in fecal metagenomic profiles of microbiome-intact mice that modulate aspirin bioavailability (6). Finally, a small randomized trial showed that aspirin alters the relative abundance of gut bacteria associated with colorectal cancer (7).Beyond playing a role in the development progression of colorectal cancer (8), the gut microbiome is being exploited to develop fecal microbial markers as a possible biomarker of colorectal cancer risk (9). If these studies are successful, gut microbiome risk markers could be leveraged alongside other risk measures including diet, age, and polygenic risk score to help identify patients who may have a more optimal risk-benefit profile for aspirin prevention.See the original Letter to the Editor, p. 701A.T. Chan reports personal fees from Bayer Pharma AG, Boehringer Ingelheim; grants and personal fees from Pfizer Inc.; and grants from Zoe, Ltd. outside the submitted work. No disclosures were reported by the other author.

S3353 Improvement in Paediatric Autoimmune Neuropsychiatric Disorders Associated With Streptococcal Infections (PANDAS) Syndrome Following Treatment With a Combination of Antibiotics and Fecal Microbiome Transplantation (FMT)

Introduction: Paediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS) syndrome is a condition that impairs normal neurological brain function and is triggered by a streptococcal infection. It is characterised by an obsessive-compulsive disorder (OCD) tic disorder, or both and usually occurs suddenly between the age of 3-12 years. Other symptoms include mood changes, anxiety, attention deficit/hyperactivity disorder, trouble sleeping, and joint pain. Metagenomic profiles of those with PANDAS syndrome show an altered gut bacterial community. Commonly treatment involves antibiotics for streptococcal infection. Here, we report on the effects of fecal microbiota transplantation (FMT) on a set of identical twins with concomitant PANDAS syndrome. Case Description/Methods: Case 1: A male (16yrs) presented with slow transit type constipation with a colonic transit half clearance time of 70minutes. His medical history also showed he had PANDAS syndrome and later tested positive for Clostridium Difficile (C. difficile). The patient was treated with metronidazole before receiving a single dose of FMT which was transfused colonoscopically. At 1-month the patient tested negative for C. difficile. Post treatment he reported significant improvement in abdominal pain, bloating and constipation that lasted 2 years. Simultaneously he reported symptom improvement in anxiety, depression, and Rheumatoid Arthritis which are associated with PANDAS syndrome. Case 2: A male (16yrs) presented with severe constipation with a normal colonic transit half clearance time of 50minutes. Constipation prompted a worsening of symptoms of concomitant PANDAS syndrome which had previously been treated with steroids. After further testing he was found to have C. difficile for which he was prescribed metronidazole and vancomycin before receiving a single dose of FMT by colonoscopic infusion. At 1-month post treatment eradication of C. difficile was confirmed. Post treatment he reported experiencing improvement in constipation, diarrhoea, flatulence, and vomiting which lasted for 2 years. He also reported symptom improvement in Autism, OCD, and Rheumatoid Arthritis which are linked to PANDAS syndrome. Discussion: To the best of our knowledge these are the first cases of improvement in PANDAS symptoms after FMT treatment. Further study is required into the effects of FMT on PANDAS syndrome before FMT can be confirmed as a potential treatment.

Distinct skin microbiome community structures in congenital ichthyosis.

The ichthyoses are rare genetic keratinizing disorders that share the characteristics of an impaired epidermal barrier and increased risk of microbial infections. Although ichthyotic diseases share a T helper (Th) 17 cell immune signature, including increased expression of antimicrobial peptides, the skin microbiota of ichthyoses is virtually unexplored. To analyse the metagenome profile of skin microbiome for major congenital ichthyosis subtypes. Body site-matched skin surface samples were collected from the scalp, upper arm and upper buttocks of 16 healthy control participants and 22 adult patients with congenital forms of ichthyosis for whole metagenomics sequencing analysis. Taxonomic profiling showed significant shifts in bacteria and fungi abundance and sporadic viral increases across ichthyosis subtypes. Cutibacterium acnes and Malassezia were significantly reduced across body sites, consistent with skin barrier disruption and depletion of lipids. Microbial richness was reduced, with specific increases in Staphylococcus and Corynebacterium genera, as well as shifts in fungal species, including Malassezia. Malassezia globosa was reduced at all body sites, whereas M. sympodialis was reduced in the ichthyotic upper arm and upper buttocks. Malassezia slooffiae, by contrast, was strikingly increased at all body sites in participants with congenital ichthyosiform erythroderma (CIE) and lamellar ichthyosis (LI). A previously undescribed Trichophyton species was also detected as sporadically colonizing the skin of patients with CIE, LI and epidermolytic ichthyosis subtypes. The ichthyosis skin microbiome is significantly altered from healthy skin with specific changes predominating among ichthyosis subtypes. Skewing towards the Th17 pathway may represent a response to the altered microbial colonization in ichthyosis. What is already known about this topic? The skin microbiome of congenital ichthyoses is largely unexplored. Microbes play an important role in pathogenesis, as infections are common. The relative abundances of staphylococci and corynebacteria is increased in the cutaneous microbiome of patients with Netherton syndrome, but extension of these abundances to all congenital ichthyoses is unexplored. What does this study add? A common skin microbiome signature was observed across congenital ichthyoses. Distinct microbiome features were associated with ichthyosis subtypes. Changes in microbiome may contribute to T helper 17 cell immune polarization. What is the translational message? These data provide the basis for comparison of the microbiome with lipidomic and transcriptomic alterations in these forms of ichthyosis and consideration of correcting the dysbiosis as a therapeutic intervention.

Colitis-associated intestinal microbiota regulates brain glycine and host behavior in mice

Inflammatory bowel diseases (IBD) are chronic and relapsing inflammatory disorders of the gastrointestinal tract with complex etiology and no strategies for complete cure. IBD are often complicated by mental disorders like anxiety and depression, indicating substantial shifts in the microbiota gut-brain axis. However, the mechanisms connecting IBD to mental diseases are still under debate. Here we use Muc2 knockout mouse model of chronic colitis to uncouple the effects of the intestinal microbiota on host behavior from chronic inflammation in the gut. Muc2 knockout male mice exhibit high exploratory activity, reduced anxiety-related behaviors, impaired sensorimotor gating, and altered social preference towards males and females. Microbial transfer to wild-type mice via littermate co-housing shows that colitis-associated microbiota rather than inflammation per se defines behavioral features in Muc2 colitis model. Metagenomic profiling and combination of antibiotic treatments revealed that bacterial species Akkermansia muciniphila is associated with the behavioral phenotype in mutants, and that its intestinal abundance correlates with social preference towards males. Metabolomic analysis together with pharmacological inhibition of Gly and NMDA receptors helped us to determine that brain glycine is responsible for the behavioral phenotype in Muc2 mice. Blood and brain metabolic profiles suggest that microbiota-dependent changes in choline metabolism might be involved in regulation of central glycine neurotransmission. Taken together, our data demonstrates that colitis-associated microbiota controls anxiety, sensorimotor gating and social behavior via metabolic regulation of the brain glycinergic system, providing new venues to combat neurological complications of IBD.

Effect of experimentally increased nutrient availability on the structure, metabolic activities, and potential microbial functions of a maritime Antarctic microbial mat.

The role of competitive interactions based on resource utilisation was explored in a phototrophic microbial mat from Byers Peninsula (Maritime Antarctica). Shotgun metagenomic profiling of the mat showed a taxonomic and functionally diverse microbial community. The heterotrophic bacterial community was dominated by Proteobacteria, where genera typically found in polar habitats, such as Janthinobacterium, Pseudomonas, and Polaromonas, were highly prevalent. Cyanobacteria played the main role as primary producers, accompanied by diatoms and chlorophytes. To test the potential effects of the inorganic nutrient (N and P) availability on this community, a fully factorial nitrate and phosphorus addition experiment was conducted in situ. The mat exhibited a functional and structural response to the nutrient amendments. Compared to the undisturbed mat, phosphorus fertilisation favoured the growth of (non-heterocystous) cyanobacteria relative to that of diatoms, as indicated by changes in the carotenoid pigment biomarkers. Although no mat accretion was visible, fertilisation improved the phototrophic activity, and, mainly, when P was amended, the production of exopolymeric substances was favoured, whereas further changes in the vertical distribution of primary production activity were observed as well. Illumina amplicon sequencing of the 16S rRNA gene also demonstrated changes in the relative abundance of heterotrophic prokaryotes, which were detectable from the phylum to the genus level and mainly related to the amendment of nitrogen. Predictions made on the functional skills of these shifted prokaryotic communities indicated changes in abundance selecting taxa with a metabolic adaptation to the new nutrient scenarios. They mainly consisted of the enhancement of ecological strategies and metabolic regulatory mechanisms related to the uptake and metabolising of either nitrogen or phosphorus, regulated by its availability whether in a balanced way or not. This study is a pioneer in demonstrating how shifts in the regional dynamic of nutrients might alter the metabolic equilibrium of these initially considered homeostatic benthic communities. They can be accordingly considered as taxonomically diverse microbiomes with a functional repertoire still inclined to respond to the biogeochemical alteration of nutrient cycles, although occurring in a cold extreme environment where biological activity is partially restricted by environmental harshness.

A Comprehensive Metagenomic Analysis Framework Revealing Microbiome Profile and Potential for Hydrocarbon Degradation and Carbohydrate Metabolism in a Himalayan Artificial Lake

The high-altitude lakes are ecological habitats accommodating a vast diversity of microbial populations. These microbes are efficient sources for a variety of enzymes. The objective of this study is to perform in-depth metagenomic profiling of an artificial lake ecosystem located in the Sikkim Himalayan region, deciphering the hydrocarbon degradation potential of this site and mining biocatalysts of industrial importance. In the present study, metagenomic analysis of an artificial Himalayan lake, located in North Sikkim, India, was performed. A comprehensive taxonomic and functional profiling revealed gene mapped to pathways for degradation of hydrocarbons such as toluene, benzoate, ethylbenzene, etc. This site was rich in iron, and the metagenomic investigation revealed genomic signatures of the iron-reducing bacterium; Geothrix fermentans. The appraisal of the carbohydrate metabolic potential of this site divulged the predominance of β-galactosidase genes. The artificial lake metagenome was further compared to publicly available saline and freshwater lakes. At the taxonomic, as well as functional levels, it was found to be closer to freshwater lake metagenome, e.g., Medonta Lake, US, and freshwater Vanda Lake, Antarctica. The microbial community profiling and functional contribution of the artificial Himalayan lake would be beneficial for mining genes encoding various industrially relevant enzymes.

A blood-based circulating microbial metagenomic panel for early diagnosis and prognosis of oesophageal adenocarcinoma.

Emerging evidence indicates the potential clinical significance of specific microbial signatures as diagnostic and prognostic biomarkers, in multiple cancers. However, to date, no studies have systematically interrogated circulating metagenome profiling in oesophageal adenocarcinoma (EAC) patients, particularly as novel non-invasive, early detection, surveillance and prognostic classifiers. Metagenome sequencing was performed on 81 serum specimens collected across EAC spectrum, with sequencing reads classified using Bracken and MetaPhlAn3. Followed by the Linear Discriminant Analysis effect size (LEfSe) method to identify microbial profiles between groups. Logistic regression and Kaplan-Meier analyses were used to build classifiers. A significant loss of alpha and beta diversity was identified in serum specimens from EAC patients. We observed a shift in microbial taxa between each group-at the phylum, genus, and species level-with Lactobacillus sakei as the most prominent species in gastroesophageal reflux (GERD) vs other patient groups. Interestingly, LEfSe analysis identified a complete loss of Lactobacillus (L. Sakei and L. Curvatus), Collinsella stercoris and Bacteroides stercoris but conversely a significant increase in Escherichia coli in patients with EAC. Finally, we developed a metagenome panel that discriminated EAC from GERD patients with an AUC value of 0.89 (95% CI: 0.78-0.95; P < 0.001) and this panel in conjunction with the TNM stage was a robust predictor of overall survival (≥24 months; AUC = 0.84 (95% CI: 0.66-0.92; P = 0.006)). This study firstly describes unique blood-based microbial profiles in patients across EAC carcinogenesis, that are further utilised to establish a novel circulating diagnostic and prognostic metagenomic signature for EAC. Accumulating data indicates the clinical relevance of specific microbial signatures as diagnostic and prognostic biomarkers, in multiple cancers. However, to date, no studies have systematically interrogated circulating metagenome profiling in patients with oesophageal adenocarcinoma (EAC). Herein, we performed metagenome sequencing in serum specimens from EAC patients 81 collected across EAC spectrum and observed a significant loss of alpha and beta diversity, with a shift in microbial taxa between each group-at the phylum, genus, and species level-with Lactobacillus sakei as the most prominent species in gastroesophageal reflux (GERD) vs other patient groups. Interestingly, LEfSe analysis identified a complete loss of Lactobacillus (L. Sakei and L. Curvatus), Collinsella stercoris and Bacteroides stercoris but conversely a significant increase in Escherichia coli in patients with EAC. Finally, we developed a metagenome panel that discriminated EAC from GERD patients with an AUC value of 0.89 and this panel, in conjunction with the TNM stage, was a robust predictor of overall survival. This study for the first time describes unique blood-based microbial profiles in patients across EAC carcinogenesis, that are further utilised to establish a novel circulating diagnostic and prognostic metagenomic signature for EAC.

Fungi composition in settled dust associated with fractional exhaled nitric oxide in school children with asthma

Fungi exposure has been significantly linked to respiratory illness. However, numerous fungi taxa that are potentially allergenic still undocumented and leave a barrier to establishing a clear connection between exposure and health risks. This study aimed to evaluate the association of fungi composition in settled dust with fractional exhaled nitric oxide (FeNO) levels among school children with doctor-diagnosed asthma. A cross-sectional study was undertaken among secondary school students in eight schools in the urban area of Hulu Langat, Selangor, Malaysia. A total of 470 school children (aged 14 years old) were randomly selected and their FeNO levels were measured and allergic skin prick tests were conducted. The settled dust samples were collected and analysed by using metagenomic technique to determine the fungi composition. The general linear regression with complex sampling was employed to determine the interrelationship. In total, 2645 fungal operational taxonomic units (OTUs) were characterised from the sequencing process which belongs to Ascomycota (60.7 %), Basidiomycota (36.4 %), Glomeromycota (2.9 %) and Chytridiomycota (0.04 %). The top five mostly abundance in all dust samples were Aspergillus clavatus (27.2 %), followed by Hyphoderma multicystidium (12.2 %), Verrucoconiothyrium prosopidis (9.4 %), Ganoderma tuberculosum (9.2 %), and Heterochaete shearii (7.2 %). The regression results indicated that A. clavatus, Brycekendrickomyces acaciae, Candida parapsilosis, Hazslinszkyomyces aloes, H. multicystidium, H. shearii, Starmerella meliponinorum, V. prosopidis were associated in increased of FeNO levels among the asthmatic group at 0.992 ppb (95 % CI = 0.34–1.68), 2.887 ppb (95 % CI = 2.09–3.76), 0.809 ppb (95 % CI = 0.14–1.49), 0.647 ppb (95 % CI = 0.36–0.94), 1.442 ppb (95 % CI = 0.29–2.61), 1.757 ppb (95 % CI = 0.59–2.87), 1.092 ppb (95 % CI = 0.43–1.75) and 1.088 ppb (95 % CI = 0.51–1.62), respectively. To our knowledge, this is a new finding. The findings pointed out that metagenomics profiling of fungi could enhance our understanding of a complex interrelation between rare and unculturable fungi with airway inflammation.

Association between Gut Microbiota with Mild Cognitive Impairment and Alzheimer’s Disease in a Thai Population

Background: Mild cognitive impairment (MCI) and Alzheimer’s disease (AD) are common in older adults. Much recent work has implicated the connection between the gut and the brain via bidirectional communication of the gastrointestinal tract and the central nervous system through biochemical signaling. Altered gut microbiota composition has shown controversial results based on geographic location, age, diet, physical activity, psychological status, underlying diseases, medication, and drug use. Objectives: This study aimed to investigate the relationships of gut microbiota with MCI and AD. Methods: 16S metagenome profiles from stool collection of participant groups (normal; n = 20, MCI; n = 12, AD; n = 20) were analyzed. The diagnosis of cognitive conditions was made by standard criteria consisting of clinical interviews, physical examinations, cognitive assessments, laboratory examinations, and neuroimaging by both structural neuroimaging and amyloid positron emission tomography scans. Correlations between medical factors with food frequency and the fecal microbiome were elucidated. Results: A significant difference at the operational taxonomic unit level was observed. The significantly higher abundance of bacteria in nondementia patients belonged to the Clostridiales order, including Clostridium sensu stricto 1 (p < 0.0001), Fusicatenibacter (p = 0.0007), Lachnospiraceae (p = 0.001), Agathobacter (p = 0.021), and Fecalibacterium (p < 0.0001). In contrast, Escherichia-Shigella (p = 0.0002), Bacteroides (p = 0.0014), Holdemanella (p < 0.0001), Romboutsia (p = 0.001), and Megamonas (p = 0.047) were the dominant genera in the AD group. Left and right hippocampus and right amygdala volumes were significantly decreased in the AD group (p < 0.001) and significantly correlated with the groups of bacteria that were significantly different between groups. Conclusion: There was a relationship between the composition of the gut microbiome and neurodegenerative disorders, including MCI and AD. Reduction of Clostridiaceae and increases in Enterobacteriaceae and Bacteroides were associated with persons with MCI and AD, consistent with previous studies. The altered gut microbiome could be potentially targeted for the early diagnosis of dementia and the reduction of AD risk.

34783 Metagenomic microbial profiling of keratinocyte carcinomas in solid organ transplant recipients

In healthy individuals, a symbiotic relationship exists between the host and its microbiota; however, disruption of this ecosystem may lead to chronic inflammation and skin diseases such as atopic dermatitis, psoriasis, rosacea, and acne. Altered microbiota has also been linked to malignancies such as breast, colorectal, and gastric cancers. Solid organ transplant recipients are at increased risk of malignancy, especially at microbiota-rich sites such as the skin. In contrast, the incidence of common malignancies in more sterile areas (i.e., breast and prostate) are reduced post-transplantation. Medication-induced immunosuppression may play a role in carcinogenesis, in part by decreasing immune-mediated tumor surveillance. However, it does not account for the striking increase in cancer at high microbial density sites. Therefore, it is essential to understand the complex interplay between the skin microbiota, inflammation, and immunity in health and disease. To date, there are no studies that have investigated the cutaneous microbiota in transplant recipients. We hypothesize that metagenomic sequencing will reveal microbial dysbiosis in patients post-transplant, thereby identifying tumour-specific species/strains of bacteria. By understanding the microbiota-host interactions of keratinocyte carcinomas in transplant recipients, we further the development of diagnostic and prognostic tools essential for the management of skin cancer. Identifying specific tumour-associated microbes holds great therapeutic potential, with treatment options including prebiotics, probiotics, antibiotics, and microbial transplants.

Crowdsourced benchmarking of taxonomic metagenome profilers: lessons learned from the sbv IMPROVER Microbiomics challenge

BackgroundSelection of optimal computational strategies for analyzing metagenomics data is a decisive step in determining the microbial composition of a sample, and this procedure is complex because of the numerous tools currently available. The aim of this research was to summarize the results of crowdsourced sbv IMPROVER Microbiomics Challenge designed to evaluate the performance of off-the-shelf metagenomics software as well as to investigate the robustness of these results by the extended post-challenge analysis. In total 21 off-the-shelf taxonomic metagenome profiling pipelines were benchmarked for their capacity to identify the microbiome composition at various taxon levels across 104 shotgun metagenomics datasets of bacterial genomes (representative of various microbiome samples) from public databases. Performance was determined by comparing predicted taxonomy profiles with the gold standard.ResultsMost taxonomic profilers performed homogeneously well at the phylum level but generated intermediate and heterogeneous scores at the genus and species levels, respectively. kmer-based pipelines using Kraken with and without Bracken or using CLARK-S performed best overall, but they exhibited lower precision than the two marker-gene-based methods MetaPhlAn and mOTU. Filtering out the 1% least abundance species—which were not reliably predicted—helped increase the performance of most profilers by increasing precision but at the cost of recall. However, the use of adaptive filtering thresholds determined from the sample’s Shannon index increased the performance of most kmer-based profilers while mitigating the tradeoff between precision and recall.Conclusionskmer-based metagenomic pipelines using Kraken/Bracken or CLARK-S performed most robustly across a large variety of microbiome datasets. Removing non-reliably predicted low-abundance species by using diversity-dependent adaptive filtering thresholds further enhanced the performance of these tools. This work demonstrates the applicability of computational pipelines for accurately determining taxonomic profiles in clinical and environmental contexts and exemplifies the power of crowdsourcing for unbiased evaluation.

Shift in Microbial Community Structure with Temperature in Deulajhari Hot Spring Cluster, Odisha, India

Hot springs are the reservoirs of novel hyperthermophilic and often mesophilic bacteria that provide information about the prevailing community structure. Here we analyzed the metagenome profile based 16S rRNA amplicon sequencing of the three different springs from Deulajhari hot spring cluster, S1, S2 and S3, having a range of temperature (43°C to 65°C), pH (7.14 – 8.10) and variation in N, P, K, TOC, Salinity, COD and TDS. These thermal spring clusters are covered with the dense vegetation of Pandanus and continuously enriched by plant leaf debris, thus resulting in a high amount of total organic carbon (TOC). The number of phyla varied among the springs: 20 in S1 (43°C), 18 in S2 (55°C) and 24 in S3 (65°C) from the 16S rRNA data. Out of the reported phyla in each spring, the most abundant were Chloroflexi, Proteobacteria, Chlorobi and Acidobacteria, which correlated with the temperature gradient. Various metabolic pathways such as ABC transporters, Two-component system, Purine metabolism were most abundantly present in the S2 sample compared to the other two. The CCA analysis revealed the correlation between physiochemical parameters and their functional annotation. The present study establishes the relation between the physiological parameters and the structural distribution of microbiota along the temperature gradient.

DeepToA: an ensemble deep-learning approach to predicting the theater of activity of a microbiome

Metagenomics is the study of microbiomes using DNA sequencing. A microbiome consists of an assemblage of microbes that is associated with a 'theater of activity' (ToA). An important question is, to what degree does the taxonomic and functional content of the former depend on the (details of the) latter? Here, we investigate a related technical question: Given a taxonomic and/or functional profile estimated from metagenomic sequencing data, how to predict the associated ToA? We present a deep-learning approach to this question. We use both taxonomic and functional profiles as input. We apply node2vec to embed hierarchical taxonomic profiles into numerical vectors. We then perform dimension reduction using clustering, to address the sparseness of the taxonomic data and thus make the problem more amenable to deep-learning algorithms. Functional features are combined with textual descriptions of protein families or domains. We present an ensemble deep-learning framework DeepToA for predicting the ToA of amicrobial community, based on taxonomic and functional profiles. We use SHAP (SHapley Additive exPlanations) values to determine which taxonomic and functional features are important for the prediction. Based on 7560 metagenomic profiles downloaded from MGnify, classified into 10 different theaters of activity, we demonstrate that DeepToA has an accuracy of 98.30%. We show that adding textual information to functional features increases the accuracy. Our approach is available at http://ab.inf.uni-tuebingen.de/software/deeptoa. Supplementary data are available at Bioinformatics online.